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Toward an Electrophysiological " Sweet Spot " for Deep Brain Stimulation in the Subthalamic Nucleus
Human Brain Mapping
Abstract
Enhanced beta-band activity recorded in patients suffering from Parkinson's Disease (PD) has been described as a potential physiomarker for disease severity. Beta power is suppressed by Levodopa intake and STN deep brain stimulation (DBS) and correlates with disease severity across patients. The aim of the present study was to explore the promising signature of the physiomarker in the spatial domain. Based on local field potential data acquired from 54 patients undergoing STN-DBS, power values within alpha, beta, low beta, and high beta bands were calculated. Values were projected into common stereotactic space after DBS lead localization. Recorded beta power values were significantly higher at posterior and dorsal lead positions, as well as in active compared with inactive pairs. The peak of activity in the beta band was situated within the sensorimotor functional zone of the nucleus. In contrast, higher alpha activity was found in a more ventromedial region, potentially corresponding to associative or pre-motor functional zones of the STN. Beta-and alpha-power peaks were then used as seeds in a fiber tracking experiment. Here, the beta-site received more input from primary motor cortex whereas the alpha-site was more strongly connected to premotor and prefrontal areas. The results summarize predominant spatial locations of frequency signatures recorded in STN-DBS patients in a probabilistic fashion. The site of predominant beta-activity may serve as an electrophysiologically determined target for optimal outcome in STN-DBS for PD in the future.
... Previous studies have shown that neural activity in the cortex and STN feature spectral topographies during resting state 63,64 and movement execution 65,66 . Consistent with these findings, when we grouped SPC maps by cortical regions of interest (ROIs), we observed qualitatively distinct SPC patterns (Fig. S8). ...
... How can stimulating the same target nucleus consistently ameliorate some Parkinsonian symptoms yet have mixed and variable effects on the speech-motor system? Our results align with the notion that variability in DBS lead placement can explain most of the reported variance of outcomes in the literature 63 . Relative to the optimal therapeutic target defined by Caire et al. 100 (x = −12.6 mm, y = −13.4 ...
... Second, because recording locations were clinically determined, we had uneven coverage of the STN and of the lateral speech-motor cortex. Most microelectrode trajectories traversed the dorsolateral part of the STN, the clinical target for PD DBS 63 . Hence, sampling of the ventromedial region of the STN is limited. ...
Speech provides a rich context for understanding how cortical interactions with the basal ganglia contribute to unique human behaviors, but opportunities for direct human intracranial recordings across cortical-basal ganglia networks are rare. Here we have recorded electrocorticographic signals in the cortex synchronously with single units in the basal ganglia during awake neurosurgeries where participants spoke syllable repetitions. We have discovered that individual subthalamic nucleus (STN) neurons have transient (200 ms) spike-phase coupling (SPC) events with multiple cortical regions. The spike timing of STN neurons is locked to the phase of theta-alpha oscillations in the supramarginal and posterior superior temporal gyrus during speech planning and production. Speech sound errors occur when this STN-cortical interaction is delayed. Our results suggest that timely interactions between the STN and the posterior perisylvian cortex support auditory-motor coordinate transformation or phonological working memory during speech planning. These findings establish a framework for understanding cortical-basal ganglia interaction in other human behaviors, and additionally indicate that firing-rate based models are insufficient for explaining basal ganglia circuit behavior.
... In comparison, the role of basal ganglia signals in the context of the apathy-impulsivity spectrum is understudied. Only few data are pointing to an increase in ventromedial sub-beta oscillations (5)(6)(7)(8)(9)(10)(11)(12) and an association of it to trait impulsivity and impulse control behavior, while no studies so far describe a basal ganglia neurophysiological correlate of apathy [27][28][29][30][31][32] . ...
... With this data-driven approach, we could evidence that the most informative spectral gradient in this frequency range spans along a dorsal-ventral axis, allocating the beta frequency activity to the dorsal and the sub-beta oscillations toward the ventral, limbic STN. While an increase of beta power in the dorsal STN is well known, this work supports the presence of higher alpha activity toward the ventral STN that so far has only been described by few studies 31,32 . What is the functional relevance of this spectral gradient present in a majority of subjects? ...
... This is likely due to a higher, yet spatially refined beta synchronization contralateral to the more affected hemi-body side 44 . Moreover, the stimulation contacts providing a better rigidity response to DBS also pick up more beta activity and are located more dorsally on the STN gradient axis, which is in line with previous results 12,32,[45][46][47][48] . On the other hand, focusing on the neuropsychiatric domain, we found that a higher degree of apathetic symptoms was associated with low ventral alpha activity in the STN, which has not been described yet at the level of the basal ganglia. ...
Sensing-based deep brain stimulation should optimally consider both the motor and neuropsychiatric domain to maximize quality of life of Parkinson’s disease (PD) patients. Here we characterize the neurophysiological properties of the subthalamic nucleus (STN) in 69 PD patients using a newly established neurophysiological gradient metric and contextualize it with motor symptoms and apathy. We could evidence a STN power gradient that holds most of the spectral information between 5 and 30 Hz spanning along the dorsal-ventral axis. It shows elevated power in the sub-beta range (8-12 Hz) toward the ventral STN, and elevated dorsal beta power (16–24 Hz) indicative for the hemispheres contralateral to the more affected hemi-body side. The rigidity response to DBS was highest dorsally on the axis. Importantly, apathetic symptoms can be related to reduced ventral alpha power. In conclusion, the STN spectral gradient may inform about the motor and neuropsychiatric domain, supporting integrative closed-loop strategies.
... More recently, in the era of deep brain stimulation (DBS), there have been several studies that describe the most effective therapeutic sites (i.e., sweet spots) for PD with STN-DBS (13). Although these studies were generally based on a small number of patients, the notion emerged that different electrode locations differentially improved motor features of PD (14)(15)(16)(17). Very recently, a major neuroimaging study in a large cohort (n = 129) of patients with PD who underwent bilateral STN-DBS carried out a data-driven analysis to identify the stimulated tracts related to the optimal clinical outcomes for each cardinal motor manifestation (18). ...
... Thus, the findings presented here are sound and reproducible. Previous assessments of STN topography and clinical efficacy have been directed by and large to defining the most effective placement for DBS electrode location (14)(15)(16)(17). However, a recent study by Rajamani et al. (18) reported a similar topographic organization for STN-cortical connectivity based on the effect of DBS electrodes. ...
... Another potential pitfall is that nonlinear warping of lesions into the standard MNI space may become a source of bias. However, localization in the standard MNI space of both lesions and DBS (i.e., electrodes and volume of tissue activated) has been successfully and extensively used to explain clinical outcomes in previous studies (14,64). The nonlinear registration method used in this study has been shown to account for intersubject anatomical variability more effectively compared with other nonlinear deformation algorithms (69). ...
The subthalamic nucleus (STN) modulates basal ganglia output and plays a fundamental role in the pathophysiology of Parkinson’s disease (PD). Blockade/ablation of the STN improves motor signs in PD. We assessed the topography of focused ultrasound subthalamotomy ( n = 39) by voxel-based lesion-symptom mapping to identify statistically validated brain voxels with the optimal effect against each cardinal feature and their respective cortical connectivity patterns by diffusion-weighted tractography. Bradykinesia and rigidity amelioration were associated with ablation of the rostral motor STN subregion connected to the supplementary motor and premotor cortices, whereas antitremor effect was explained by lesioning the posterolateral STN projection to the primary motor cortex. These findings were corroborated prospectively in another PD cohort ( n = 12). This work concurs with recent deep brain stimulation findings that suggest different corticosubthalamic circuits underlying each PD cardinal feature. Our results provide sound evidence in humans of segregated anatomy of subthalamic-cortical connections and their distinct role in PD pathophysiology and normal motor control.
... Among the 25 included studies, 5 studies concerned retrospective research [16,[20][21][22][23], 11 studies analysed data from ten or less patients [1,5,13,15,[24][25][26][27][28][29][30], 17 articles originated from the work of six independent research groups (group #1: [11,13,15,21,31,32]; group #2: [17,20,33]; group #3: [1,16]; group #4: [5,24]; group #5: [22,34]; group #6: [29,30]). Some articles included data collected from partially overlapping patient populations [11,13,29,30]. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint figure 3). ...
... Among the 25 included studies, 5 studies concerned retrospective research [16,[20][21][22][23], 11 studies analysed data from ten or less patients [1,5,13,15,[24][25][26][27][28][29][30], 17 articles originated from the work of six independent research groups (group #1: [11,13,15,21,31,32]; group #2: [17,20,33]; group #3: [1,16]; group #4: [5,24]; group #5: [22,34]; group #6: [29,30]). Some articles included data collected from partially overlapping patient populations [11,13,29,30]. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint figure 3). ...
... p=0.645) used monopolar recordings and a low-beta-peak feature [31]; the second (p=0.062) used bipolar recordings and a z-score for high-beta-power [22]; notably in both studies other considered beta-related features were significantly correlated. For 39% a predictive accuracy of two times the a priori chance or more ( ...
Background: Programming deep brain stimulation (DBS) of the subthalamic nucleus for optimal symptom control in Parkinson's Disease (PD) requires time and trained personnel. Novel implantable neurostimulators allow local field potentials (LFP) recording, which could be used to identify the optimal (chronic) stimulation contact. However, literature is inconclusive on which LFP features and prediction techniques are most effective.
Objective: To evaluate the performance of different LFP-based physiomarkers for predicting the optimal (chronic) stimulation contacts.
Methods: A literature search was conducted across nine databases, resulting in 418 individual papers. Two independent reviewers screened the articles based on title, abstract, and full text. The quality of included studies was assessed using a modified Joanna Briggs Institute Critical Appraisal Checklist for Case Series. Results were categorised in four classes based on the predictive performance with respect to the a priori chance.
Results: Twenty-five studies were included. Single-factor beta-band predictions demonstrated positive performance scores in 94% of the outcomes. Predictions based on single non-beta-frequency factors yielded positive scores in only 25% of the outcomes, with positive results mainly for high frequency oscillations. Multi-factor predictions (e.g. machine learning) achieved accuracy scores within the two highest performance classes more often than single beta-based predictions (100% versus 39%).
Conclusion: Predicting the optimal stimulation contact based on LFP recordings is feasible and can improve DBS programming efficiency in PD. Single beta-band predictions show more promising results than non-beta-frequency factors alone, but are outperformed by multi-factor predictions. Future research should further explore multi-factor prediction for optimal contact identification.
... To date, the most promising brain biomarkers in PD patients are the local field potentials (LFPs) recorded directly from implanted DBS electrodes. Strong oscillatory beta activity (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) of STN-LFPs could be a valid biomarker for bradykinesia and rigidity, as it is associated with the severity of PD-related motor symptoms [8] and symptom improvement due to levodopa administration [9] and STN-DBS [10]. ...
... During aDBS+ and cDBS+, dopaminergic therapy was stable and maintained (i.e., +) with levodopa/carbidopa 100/25 mg TID, opicapone 50 mg QD, and rasagiline 1 mg QD. The aDBS+ settings were: C+1−, 2.6-3.9 mA, 130 Hz, 80 µs (left STN); C+8−, 2.6-3.0 mA, 130 Hz, 80 µs (right STN) (see Methods, Figures 1 and S1 [28][29][30]). The cDBS+ settings were: C+1−, 3.4 mA, 130 Hz, 80 µs (left STN), and C+8−, 2.8 mA, 130 Hz, 80 µs (right STN). ...
... DBS electrodes and contacts were localized based on pre-and postoperative neuroimaging using a tool designed for this task (as implemented in Lead-DBS software [28]). Atlas used for 2D and 3D visualization: Electrophysiological Atlas of STN Activity [29]. Sweet spots were calculated and visualized according to [30]. ...
Conventional DBS (cDBS) for Parkinson’s disease uses constant, predefined stimulation parameters, while the currently available adaptive DBS (aDBS) provides the possibility of adjusting current amplitude with respect to subthalamic activity in the beta band (13–30 Hz). This preliminary study on one patient aims to describe how these two stimulation modes affect basal ganglia dynamics and, thus, behavior in the long term. We collected clinical data (UPDRS-III and -IV) and subthalamic recordings of one patient with Parkinson’s disease treated for one year with aDBS, alternated with short intervals of cDBS. Moreover, after nine months, the patient discontinued all dopaminergic drugs while keeping aDBS. Clinical benefits of aDBS were superior to those of cDBS, both with and without medications. This improvement was paralleled by larger daily fluctuations of subthalamic beta activity. Moreover, with aDBS, subthalamic beta activity decreased during asleep with respect to awake hours, while it remained stable in cDBS. These preliminary data suggest that aDBS might be more effective than cDBS in preserving the functional role of daily beta fluctuations, thus leading to superior clinical benefit. Our results open new perspectives for a restorative brain network effect of aDBS as a more physiological, bidirectional, brain–computer interface.
... Within the dorsolateral STN of patients with PD, local field potentials (LFPs) frequently exhibit increased oscillatory synchrony and elevated power in the beta frequency range of 13-30Hz 6,11-17 . Clinical evidence from human studies supports the growing consensus that LFP activity within this beta range is implicated in tonic movement 15,18,19 , is strongly correlated with rigidity and bradykinesia [20][21][22] , and that attenuation of beta power by dopaminergic medication and DBS results in symptom improvement 6,[12][13][14][15]19,[23][24][25] . Associations with symptom improvement are further supported by targeting the lower beta band (~13-20 Hz) 15,23,24,[26][27][28][29] , although there are ...
... Maximal amplitude beta peak (MBP) presence in LFP power spectral densities (PSD) were strongly related to the "electrophysiological sweet spot" for lead placement in 92% of patients undergoing DBS 6,33 . As such, several studies have corroborated the utility of PSDs to identify MBP to guide clinical decisions on DBS contact selection and parameterization in order to suppress beta power, which generally elicits clinical benefit 6,10,12,18,23,34 . ...
... Maximal amplitude beta peak (MBP) presence in LFP power spectral densities (PSD) were strongly related to the "electrophysiological sweet spot" for lead placement in 92% of patients undergoing DBS 6,33 . As such, several studies have corroborated the utility of PSDs to identify MBP to guide clinical decisions on DBS contact selection and parameterization in order to suppress beta power, which generally elicits clinical benefit 6,10,12,18,23,34 . While current clinical-commercial tools, including those from Medtronic 24 , Newronika 35 , and PINS 36 permit spectral analysis, there remains a need to systematically quantify LFP peaks from PSDs [ Fig. 1]. ...
Oscillatory activity within the beta frequency range (13–30 Hz) serves as a Parkinson’s disease biomarker for tailoring deep brain stimulation (DBS) treatments. Currently, identifying clinically relevant beta signals, specifically frequencies of peak amplitudes within the beta spectral band, is a subjective process. To inform potential strategies for objective clinical decision making, we assessed algorithms for identifying beta peaks and devised a standardized approach for both research and clinical applications. Employing a novel monopolar referencing strategy, we utilized a brain sensing device to measure beta peak power across distinct contacts along each DBS electrode implanted in the subthalamic nucleus. We then evaluated the accuracy of ten beta peak detection algorithms against a benchmark established by expert consensus. The most accurate algorithms, all sharing similar underlying algebraic dynamic peak amplitude thresholding approaches, matched the expert consensus in performance and reliably predicted the clinical stimulation parameters during follow-up visits. These findings highlight the potential of algorithmic solutions to overcome the subjective bias in beta peak identification, presenting viable options for standardizing this process. Such advancements could lead to significant improvements in the efficiency and accuracy of patient-specific DBS therapy parameterization.
... Power was normalized to the standard deviation of the 4-45 Hz and 55-95 Hz bands as described previously [13]. Power was averaged within the normalized spectra across the following four canonical frequency bands: theta (4-8 Hz); alpha (9-13 Hz); low-frequency (4-13 Hz); low beta (14-20 Hz); high beta (21)(22)(23)(24)(25)(26)(27)(28)(29)(30); beta (14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30). We used the find_peaks algorithm in sciPy and visually checked the spectral peaks for descriptive statistics. ...
... To investigate the low-frequency and high beta power distribution within STN using electrode localizations, the recorded power values were mapped into standard stereotactic MNI space following the subcortical electrophysiology mapping methodology [14]. All patients' normalized band power was assigned to the Euclidean midpoint between the constituent contacts of the bipolar contact pairs. ...
Objective
Deep brain stimulation offers a unique opportunity to record neural activity of the basal ganglia. While much work in dystonia has focused on the globus pallidus internus, expanding research to investigate subthalamic nucleus (STN) activity in various dystonia types is critical to provide a comprehensive understanding of dystonia pathophysiology.
Methods
STN and cortex activity were recorded from 17 patients with cervical dystonia (CD), 19 with Meige syndrome, and 9 with generalized dystonia (GD) during the lead externalized period. We investigated local and network oscillatory characteristics, including power, bursts, and coherence. Additionally, we explored the relationship between these features and the severity of dystonic symptoms within each group and conducted a comparative analysis across the different dystonia types.
Results
Peaks of low‐frequency (4–13 Hz) and beta (14–30 Hz) power were present in the STN of all patients; most of the beta peaks are distributed in the high beta range (20–30 Hz). The CD and GD groups showed longer low‐frequency bursts and greater high beta power in STN than the Meige group. Interestingly, the CD group showed stronger STN‐cortex low‐frequency coherence, while the GD group had stronger STN‐cortex high beta coherence. Combined, low‐frequency and beta features could predict symptom severity with a performance of 73% in the CD group and 82% in the GD group.
Interpretation
Low‐frequency and high‐beta oscillations are present in the STN across all three types of dystonia. The distinct patterns may be associated with different underlying pathological mechanisms.
... DBS neurosurgeons know well that electrode positioning matters [6]. Clinicians who program the stimulation pulse also know timing is critical [7]. ...
... In summary, our paper proposes the heterogeneous axonal response as a further potential source of variability, in addition to previously identified patient-specific factors, including surgical misplacement [6], connectivity [64], anatomical differences, and conductivity [22], and physiological or neural dynamics-related factors, such as reverberations in the basal ganglia circuitry [55], [65], [66] and synaptic modulation [67]. The interaction between these nonlinear factors is a subject for further investigation. ...
Deep brain stimulation (DBS) is an established treatment for neurodegenerative movement disorders such as Parkinson's disease that mitigates symptoms by overwriting pathological signals from the central nervous system to the motor system. Nearly all computational models of DBS, directly or indirectly, associate clinical improvements with the extent of fiber activation in the vicinity of the stimulating electrode. However, it is not clear how such activation modulates information transmission. Here, we use the exact cable equation for straight or curved axons and show that DBS segregates the signaling pathways into one of the three communicational modes: complete information blockage, uni-, and bi-directional transmission. Furthermore, all these modes respond to the stimulating pulse in an asynchronous but frequency-locked fashion. Asynchrony depends on the geometry of the axon, its placement and orientation, and the stimulation protocol. At the same time, the electrophysiology of the nerve determines frequency-locking. Such a trimodal response challenges the notion of activation as a binary state and studies that correlate it with the DBS outcome. Importantly, our work suggests that a mechanistic understanding of DBS action relies on distinguishing between these three modes of information transmission.
... In these lead contacts, PAC was detectable and correlated with the best contact placed in the motor STN according to the Lead-DBS tool and clinical setting based on the effect on motor symptoms. According to these analysessee Fig. 2, beta-HFO PAC seems to be a more precise marker for selecting the stimulation sweet spot 26,27 . Beta-HFO PAC is linked with beta power hypersynchrony, which is known to be a correlate of parkinsonian main motor symptoms and the "off" state condition. ...
... Effective DBS treatment and good clinical outcomes are related to specific MRI structural connectivity that can be evaluated using human connectome data without the need for additional imaging 21 . The importance of anatomical connections of the DBS electrodes to the area of SMA has been confirmed 26 . In our study, we have documented that the electrode contacts with the highest beta-HFO PAC have structural connectivity only to the SMA, in contrast to the other contacts that can influence much wider frontal and parietal regions. ...
Beta hypersynchrony was recently introduced into clinical practice in Parkinson’s disease (PD) to identify the best stimulation contacts and for adaptive deep brain stimulation (aDBS) sensing. However, many other oscillopathies accompany the disease, and beta power sensing may not be optimal for all patients. The aim of this work was to study the potential clinical usefulness of beta power phase-amplitude coupling (PAC) with high frequency oscillations (HFOs). Subthalamic nucleus (STN) local field potentials (LFPs) from externalized DBS electrodes were recorded and analyzed in PD patients ( n = 19). Beta power and HFOs were evaluated in a resting-state condition; PAC was then studied and compared with the electrode contact positions, structural connectivity, and medication state. Beta-HFO PAC (mainly in the 200–500 Hz range) was observed in all subjects. PAC was detectable more specifically in the motor part of the STN compared to beta power and HFOs. Moreover, the presence of PAC better corresponds to the stimulation setup based on the clinical effect. PAC is also sensitive to the laterality of symptoms and dopaminergic therapy, where the greater PAC cluster reflects the more affected side and medication “off” state. Coupling between beta power and HFOs is known to be a correlate of the PD “off” state. Beta-HFO PAC seems to be more sensitive than beta power itself and could be more helpful in the selection of the best clinical stimulation contact and probably also as a potential future input signal for aDBS.
... DBS neurosurgeons know well that the electrode positioning matters [21]. Clinicians who program the stimulation pulse also know timing is critical [12]. ...
... With our proposition, clinicians can frame such optimization as finding the best combination of blocked, uni-, and bidirectional fractions, a paradigm that could not have been explored before via overlap-based models such as the volume of tissue activated (e.g., [7], [23], [32], [34]). This paper enlists the heterogeneous axonal response as another possible source of variability in addition to patientspecific factors (surgical misplacement [21] or connectivity [5]) and physiology-or neural dynamics-related factors (reverberations in the basal ganglia circuitry [29], [37], [38] and synaptic modulation [36]). The interplay between these nonlinear factors is subject to further investigation. ...
Deep brain stimulation is an established treatment for neurodegenerative movement disorders such as Parkinson's disease that mitigates symptoms by overwriting pathological signals from the central nervous system to the motor system. Nearly all computational models of DBS, directly or indirectly, associate clinical improvements with the extent of fibre activation in the vicinity of the stimulating electrode. However, it is not clear how such activation modulates information transmission. Here, we use the exact cable equation for straight or curved axons and show that DBS segregates the signalling pathways into one of the three communicational modes: complete information blockage, uni-, and bi-directional transmission. Furthermore, all these modes respond to the stimulating pulse in an asynchronous but frequency-locked fashion. Asynchrony depends on the geometry of the axon, its placement and orientation, and the stimulation protocol. At the same time, the electrophysiology of the nerve determines frequency-locking. Such a trimodal response challenges the notion of activation as a binary state and studies that correlate it with the DBS outcome. Importantly, our work suggests that a mechanistic understanding of DBS action relies on distinguishing between these three modes of information transmission.
... Non-motor symptoms in PD patients, including emotional symptoms, can negatively impact their daily life and mental health and are receiving increasing attention. While numerous studies have investigated the optimal stimulation sites for improving motor symptoms through DBS (Tödt et al., 2022, Horn et al., 2017a, limited research has been conducted on sweet spot analysis and structural connectivity analysis for emotional outcomes in patients. This study prospectively followed 56 PD patients who underwent bilateral STN-DBS for six months, systematically evaluating its therapeutic effects on emotional symptoms. ...
Objective
STN-DBS is an effective treatment for Parkinson’s disease (PD), improving motor symptoms, but its impact on non-motor symptoms, such as anxiety and depression, remain unclear. This study investigates the relationship between electrode contact locations, their corresponding volume of tissue activated (VTA), and postoperative changes in emotional symptoms. It aims to identify optimal group-level stimulation sites for improving anxiety and depression in PD patients and to develop a structural connectome to explore how cortical regions targeted by fiber projections correlate with mood outcomes.
Methods
We retrospectively studied 56 PD patients who underwent bilateral STN-DBS, assessed 6 months post-surgery. Standardized scales evaluated motor, affective, and cognitive symptoms before and after the procedure. Electrode positions were reconstructed using Lead-DBS, and VTAs were calculated. Voxel-wise sweet spot and structural connectivity analyses investigated how stimulation sites influenced clinical outcomes.
Results
Compared to preoperative assessments, postoperative evaluations revealed varying degrees of improvement in motor function, quality of life, and symptoms of anxiety and depression in PD patients (p < 0.05). The amelioration of anxiety and depression was associated with electrode contacts located in the ventral region of the STN. Specifically, improvements in anxiety were positively correlated with the VTA in the limbic region of the right STN. Sweet spot analysis revealed that stimulation of the ventrocentral region of the left STN was significantly associated with emotional improvement. Structural connectivity analysis revealed that fiber tracts to the prefrontal cortex (PFC) were positively associated with anxiety and depression improvement, while those to the sensorimotor cortex (SMC) showed a negative correlation.
Conclusion
STN-DBS markedly improves motor symptoms and quality of life in PD patients while also positively impacting anxiety and depressive symptoms. The ventral STN is likely the optimal stimulation target for ameliorating anxiety and depressive symptoms. The therapeutic effects of STN-DBS electrodes may promote postoperative improvements in anxiety and depression by modulating fiber tracts connected to prefrontal regions. Future research should leverage connectome mapping and isolated fiber tracts to refine electrode placement, using directional leads to target specific STN subregions for improved symptom management.
... In single-element STN LFP recordings, beta-band activity was dominant in the sensorimotor part of the STN with inputs from the primary motor cortex 57 DBS predicted treatment efficacy 58 , and it was hypothesized that motor function preservation may rely on the modulation of subthalamic beta LFP activity 59 . Prolonged bursting synchronizations of beta oscillation in the subthalamic nucleus correspond to transient yet excessive increases in beta amplitude, and they have been linked with impaired motor command and execution in PD 60 . ...
Compound network dynamics in beta and gamma bands determine the severity of bradykinesia in Parkinson’s disease. We explored its subthalamic stimulation related changes parallel with improvement of complex hand movements. Thirty eight patients with Parkinson’s disease treated with bilateral stimulation accomplished voluntary and traced spiral drawing with their more affected hand on a digital tablet. A 64 channel electroencephalography was recorded, low and high beta and gamma power was computed in subthalamic and motor cortical sources at four stimulation levels. Subthalamic cortical effective connectivity was calculated, and subnetwork models were created. Beta power decreased, and gamma power increased in sources ipsilateral to stimulation with increasing stimulation intensity. Networks comprising the primary motor cortex played a dominant role in predicting the improvement of voluntary drawing speed. Subthalamic stimulation diminished the hyperdirect high beta information processing and promoted the cortico cortical interactions of the primary motor cortex in the high gamma band.
... While theta-alpha coupling consisted in a pattern dominated by frontal sources with a peak in the middle frontal gyrus, low and high beta coupling mapped to Rolandic areas, with low beta showing a more lateral distribution and high beta dominated by mesial cortico-STN coupling in the motor cortex(Figure 2 b-d). Maps were similar across the three frequency bands and confirmed a strong connection between the frontal cortex and STN, with lower frequencies including more associative-limbic domains while faster frequencies more strongly mapping to motor regions51,52 . ...
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves motor symptoms in patients with Parkinsons disease. Using functional MRI, optimal DBS response networks have been characterized. However, neural activity associated with Parkinsonian symptoms is magnitudes faster than what can be resolved by this method. While both spatial and temporal domains of these networks appear critical, no single study has yet investigated both domains simultaneously.
Here, we aim to close this gap using subthalamic local field potentials that were concurrently recorded alongside whole-brain magnetoencephalography in a multi-center cohort of patients that underwent STN-DBS for the treatment of Parkinsons disease (N = 100 hemispheres). In every cortical vertex, cortico-subthalamic coupling was correlated with stimulation outcomes.
This network spatially resembled fMRI-based findings (R = 0.40, P = 0.039) and explained significant amounts of variance in clinical outcomes (βstd = 0.30, P = 0.002), while theta-alpha and low beta coupling did not show significant associations with DBS response (theta-alpha: βstd = -0.02, P = 0.805; low beta: βstd = -0.08, P = 0.426). The optimal high beta coupling map was robust when subjected to various cross-validation designs (10-fold cross-validation: R = 0.29, P = 0.009; split-half design: R = 0.31, P = 0.026) and was able to predict outcomes across DBS centers (R = 0.74; P(1) = 8.9e-5).
We identified a DBS response network that i) resembles the previously defined MRI network and ii) operates in the high-beta band. Maximal connectivity to this network was associated with optimal DBS outcomes and was able to cross-predict clinical improvements across DBS surgeons and centers.
... The empirical fMRI BOLD data, to which the whole-brain model is fitted (see Fig. 1 [29] and Refs. [34][35][36][37][38][39][40][41][42] therein). The only fixed parameter in the model is the local bifurcation parameter which is set to the value a j = −0.02 ...
The brain is able to sustain many different states as shown by the daily natural transitions between wakefulness and sleep. Yet, the underlying complex dynamics of these brain states are essentially in nonequilibrium. Here, we develop a thermodynamical formalism based on the off-equilibrium extension of the fluctuation-dissipation theorem (FDT) together with a whole-brain model. This allows us to investigate the nonequilibrium dynamics of different brain states and more specifically to apply this formalism to wakefulness and deep sleep brain states. We show that the off-equilibrium thermodynamical signatures of brain states are significantly different in terms of the overall level of differential and integral violation of FDT. Furthermore, the framework allows for a detailed understanding of how different brain regions and networks are contributing to the off-equilibrium signatures in different brain states. Overall, this framework shows great promise for characterizing and differentiating brain states in health and disease.
Published by the American Physical Society 2025
... Within STN, ERNA is highly focal and localises to a similar hot spot as the optimal one for clinical DBS benefit 101,102 . Several groups have also reported correlations between ERNA and clinical scores or beta activity 90,97,[103][104][105] , and ERNA is modulated by dopaminergic medication 98 . ...
Neuromodulation therapy comprises a range of non-destructive and adjustable methods for modulating neural activity using electrical stimulations, chemical agents, or mechanical interventions. Here, we discuss how electrophysiological brain recording and imaging at multiple scales, from cells to large-scale brain networks, contribute to defining the target location and stimulation parameters of neuromodulation, with an emphasis on deep brain stimulation (DBS).
... Both dMRI datasets were preprocessed and made available as part of the freely available Lead-DBS software package [46]. The precise preprocessing is described in details in Horn and colleagues [47], but briefly, the data was processed using a generalized q-sampling imaging algorithm implemented in DSI studio [48]. Segmentation of the T2-weighted anatomical images produced a white-matter mask and coregistering the images to the b0 image of the diffusion data using SPM12. ...
The brain needs to perform time-critical computations to ensure survival. A potential solution lies in the nonlocal, distributed computation at the whole-brain level made possible by criticality and amplified by the rare long-range connections found in the brain's unique anatomical structure. This nonlocality can be captured by the mathematical structure of Schrödinger's wave equation, which is at the heart of the complex harmonics decomposition (CHARM) framework that performs the necessary dimensional manifold reduction able to extract nonlocality in critical spacetime brain dynamics. Using a large neuroimaging dataset of over 1000 people, CHARM captured the critical, nonlocal and long-range nature of brain dynamics and the underlying mechanisms were established using a precise whole-brain model. Equally, CHARM revealed the significantly different critical dynamics of wakefulness and sleep. Overall, CHARM is a promising theoretical framework for capturing the low-dimensionality of the complex network dynamics observed in neuroscience and provides evidence that networks of brain regions rather than individual brain regions are the key computational engines of critical brain dynamics.
Published by the American Physical Society 2025
... The exact mechanism of DBS functioning remains largely unknown. Mainly, the activation of the area of SMA is thought to occur via the activation of fibers within the hyper-direct pathway and to have the highest importance for the STN-DBS response in PD 54,55 . A previous crucial MRI study has described independent structural and functional connectivity predictors of clinical improvement-STN structural connectivity to the prefrontal cortex, including SMA and inferior frontal cortex and functional anticorrelation to the area of primary motor cortex 53 . ...
The aim of this work was to study the effect of deep brain stimulation of the subthalamic nucleus (STN-DBS) on the subnetwork of subcortical and cortical motor regions and on the whole brain connectivity using the functional connectivity analysis in Parkinson’s disease (PD). The high-density source space EEG was acquired and analyzed in 43 PD subjects in DBS on and DBS off stimulation states (off medication) during a cognitive-motor task. Increased high gamma band (50–100 Hz) connectivity within subcortical regions and between subcortical and cortical motor regions was significantly associated with the Movement Disorders Society – Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) III improvement after DBS. Whole brain neural correlates of cognitive performance were also detected in the high gamma (50–100 Hz) band. A whole brain multifrequency connectivity profile was found to classify optimal and suboptimal responders to DBS with a positive predictive value of 0.77, negative predictive value of 0.55, specificity of 0.73, and sensitivity of 0.60. Specific connectivity patterns related to PD, motor symptoms improvement after DBS, and therapy responsiveness predictive connectivity profiles were uncovered.
... The acquisition parameters are described in detail on the HCP website 74 . The preprocessing steps are outlined in 75 ; in brief, the data were processed using a generalized q-sampling imaging algorithm implemented in DSI Studio (http://dsi-studio.labsolver.org). This preprocessing was facilitated by the freely available Lead-DBS software package (https://www.lead-dbs.org/). ...
Dissociation, an altered state of consciousness in which individuals feel detached from their body, environment, and sense of self, is a common feature of Post-Traumatic Stress Disorder (PTSD). Despite its significance, the neurocognitive processes underlying dissociation remain poorly understood, potentially limiting the effectiveness of PTSD diagnostics and treatment. To address this gap, we apply network control theory to examine neural dynamics corresponding to dissociative states in two contexts: intravenous ketamine administration, an anesthetic known to induce dissociative states (n=30, healthy volunteers), and therapeutic interventions in PTSD patients expected to alleviate dissociative symptoms (n=78). Ketamine administration led to brain dynamics resembling those observed in PTSD patients pre-treatment, with increased dominance of a default mode network meta-state and decreased dominance of a somatomotor meta-state. While ketamine did not significantly alter the brain's energetic landscape, transition energies increased post-treatment in PTSD patients, potentially indicating more organized and less entropic brain dynamics.
... 33 Streamline connectivity profiles associated with each lesion were estimated using a normative dataset of neurologically healthy individuals with high quality diffusion MRI data from the Human Connectome Project's MGH 32-fold group connectome, as used in previous work. 36,37 For structural lesion network mapping, the challenges of signal averaging within a large lesion mask that occur with rs-fcMRI do not apply, and thus only the lesion-seeded approach was used. The direction of streamlines was not constrained to any other ROI beyond the starting 'seed' ROI. ...
Temporal lobe (TL) epilepsy surgery is an effective treatment option for patients with drug-resistant epilepsy. However, neurosurgery poses a risk for cognitive deficits - up to one third of patients have a decline in naming ability following TL surgery. In this study, we aimed to better understand the neural correlates associated with reduced naming performance after TL surgery, with the goal of informing surgical planning strategies to mitigate the risk of dysnomia.
We retrospectively identified 85 patients who underwent temporal lobe (TL) resective surgery (49 left TL, 36 right TL) for whom naming ability was assessed before and >3 months post-surgery using the Boston Naming Test (BNT). We used multivariate lesion-symptom mapping to identify resection sites associated with naming decline, and we used lesion-network mapping to evaluate the broader functional and structural connectivity profiles of resection sites associated with naming decline. We validated our findings in an independent cohort of 59 individuals with left temporal lobectomy, along with repeating all analyses after combining the cohorts.
Lesion laterality and location were important predictors of post-surgical naming performance. Naming performance significantly improved after right temporal lobectomy (P = 0.015) while a decrement in performance was observed following left temporal lobectomy (P = 0.002). Declines in naming performance were associated with surgical resection of the left anterior middle temporal gyrus (Brodmann area 21, r =0.41, P = <.001), along with a previously implicated basal temporal language area. Resection sites linked to naming decline showed a functional connectivity profile featuring a left-lateralized network closely resembling the extended semantic \ default mode network, and a structural connectivity profile featuring major temporo-frontal association white matter tracts coursing through the temporal stem.
This extends prior work by implicating the left anterior middle temporal gyrus in naming decline and provides additional support for the role of the previously identified basal temporal language area in naming decline. Importantly, the structural and functional connectivity profiles of these regions suggest they are key nodes of a broader extended semantic network. Together these regional and network findings may help in surgical planning and discussions of prognosis.
... The freely available Lead-DBS software package (https://www.lead-dbs.org/) provides the pre-processing described in detail in Horn et al. [37]. In brief, the data were processed by using a q-sampling imaging algorithm implemented in DSI studio (http://dsi-studio.labsolver.org). ...
Depression is a multifactorial clinical syndrome with a low pharmacological treatment response rate. Therefore, identifying predictors of treatment response capable of providing the basis for future developments of individualized therapies is crucial. Here, we applied model-free and model-based measures of whole-brain turbulent dynamics in resting-state functional magnetic resonance imaging (fMRI) in healthy controls and unmedicated depressed patients. After eight weeks of treatment with selective serotonin reuptake inhibitors (SSRIs), patients were classified as responders and non-responders according to the Hamilton Depression Rating Scale 6 (HAMD6). Using the model-free approach, we found that compared to healthy controls and responder patients, non-responder patients presented disruption of the information transmission across spacetime scales. Furthermore, our results revealed that baseline turbulence level is positively correlated with beneficial pharmacological treatment outcomes. Importantly, our model-free approach enabled prediction of which patients would turn out to be non-responders. Finally, our model-based approach provides mechanistic evidence that non-responder patients are less sensitive to stimulation and, consequently, less prone to respond to treatment. Overall, we demonstrated that different levels of turbulent dynamics are suitable for predicting response to SSRIs treatment in depression.
... The scans, spanning approximately 89 minutes, adhered to acquisition parameters detailed in Thomas et al (78). Connectivity was estimated using the method outlined by Horn et al (79). Briefly, the data was processed using a generalized q-sampling imaging algorithm implemented in DSI studio (http://dsi-studio.labsolver.org). ...
The multidimensional nature of schizophrenia requires a comprehensive exploration of the functional and structural brain networks. While prior research has provided valuable insights into these aspects, our study goes a step further to investigate the reconfiguration of the hierarchy of brain dynamics, which can help understand how brain regions interact and coordinate in schizophrenia. We applied an innovative thermodynamic framework, which allows for a quantification of the degree of functional hierarchical organization by analysing resting state fMRI-data. Our findings reveal increased hierarchical organization at the whole-brain level and within specific resting-state networks in individuals with schizophrenia, which correlated with negative symptoms, positive formal thought disorder and apathy. Moreover, using a machine learning approach, we showed that hierarchy measures allow a robust diagnostic separation between healthy controls and schizophrenia patients. Thus, our findings provide new insights into the nature of functional connectivity anomalies in schizophrenia, suggesting that they could be caused by the breakdown of the functional orchestration of brain dynamics.
... However, the ideal anatomical sub-target for STN-DBS remains a matter of debate. Advanced imaging and clinical experience have identified different anatomical targets [4,5] for stimulation within the STN [6,7] or dorsomedial to the STN within the caudal zona incerta (cZI) [8]. More recently, a white matter tract directly connecting the motor cortex to the STN, termed the hyperdirect pathway (HDP) [9,10], has gained interest as some studies found that HDP activation may be driving therapeutic DBS effects [11][12][13][14][15]. ...
Background
Subthalamic deep brain stimulation (STN-DBS) is a well-established therapy to treat Parkinson’s disease (PD). However, the STN-DBS sub-target remains debated. Recently, a white matter tract termed the hyperdirect pathway (HDP), directly connecting the motor cortex to STN, has gained interest as HDP stimulation is hypothesized to drive DBS therapeutic effects. Previously, we have investigated EEG-based evoked potentials (EPs) to better understand the neuroanatomical origins of the DBS clinical effect. We found a 3-millisecond peak (P3) relating to clinical benefit, and a 10-millisecond peak (P10) suggesting nigral side effects. Here, we aimed to investigate the neuroanatomical origins of DBS EPs using probabilistic mapping.
Methods
EPs were recorded using EEG whilst low-frequency stimulation was delivered at all DBS-contacts individually. Next, EPs were mapped onto the patients’ individual space and then transformed to MNI standard space. Using voxel-wise and fiber-wise probabilistic mapping, we determined hotspots/hottracts and coldspots/coldtracts for P3 and P10. Topography analysis was also performed to determine the spatial distribution of the DBS EPs.
Results
In all 13 patients (18 hemispheres), voxel- and fiber-wise probabilistic mapping resulted in a P3-hotspot/hottract centered on the posterodorsomedial STN border indicative of HDP stimulation, while the P10-hotspot/hottract covered large parts of the substantia nigra.
Conclusion
This study investigated EP-based probabilistic mapping in PD patients during STN-DBS, revealing a P3-hotspot/hottract in line with HDP stimulation and P10-hotspot/hottract related to nigral stimulation. Results from this study provide key evidence for an electrophysiological measure of HDP and nigral stimulation.
... HCP scans are acquired using specialized MR hardware and consequently boast superior signal-to-noise ratios and fidelity than can be achieved at most academic centres 20,21 . The number of HCP subjects sampled to construct these connectomes has also varied; a handful of studies have used larger connectomes compiled from ~400-850 individuals 22,23 , while the majority have utilized connectomes aggregated from 30-40 healthy subjects [24][25][26][27][28][29][30][31][32][33][34] . Other studies have leveraged dMRI scans from patients with the same condition as the population of interest in order to construct 'disease-specific' connectomes that might better capture the connectivity differences that likely characterize patients with certain longstanding neurological conditions 35 . ...
Diffusion-weighted MRI (dMRI) is a widely used neuroimaging modality that permits the in vivo exploration of white matter connections in the human brain. Normative structural connectomics – the application of large-scale, group-derived dMRI datasets to out-of-sample cohorts – have increasingly been leveraged to study the network correlates of focal brain interventions, insults, and other regions-of-interest (ROIs). Here, we provide a normative, whole-brain connectome in MNI space that enables researchers to interrogate fiber streamlines that are likely perturbed by given ROIs, even in the absence of subject-specific dMRI data. Assembled from multi-shell dMRI data of 985 healthy Human Connectome Project subjects using generalized Q-sampling imaging and multispectral normalization techniques, this connectome comprises ~12 million unique streamlines, the largest to date. It has already been utilized in at least 18 peer-reviewed publications, most frequently in the context of neuromodulatory interventions like deep brain stimulation and focused ultrasound. Now publicly available, this connectome will constitute a useful tool for understanding the wider impact of focal brain perturbations on white matter architecture going forward.
... Increased oscillatory neuronal activity in the basal ganglia, particularly the subthalamic nucleus (STN), at frequencies of 8-30 Hz is widely used electrophysiological marker of Parkinson's disease [Hammond et al., 2007]. Drug therapy (levodopa-based drugs) [Kuhn et al., 2006;Kuhn et al., 2009;Tinkhauser, 2017a] and subthalamic nucleus deep brain stimulation (DBS) [Kuhn et al., 2008;Oswal et al., 2016;Horn et al., 2017;Tinkhauser et al., 2017b], which reduce pathological oscillations, are used to alleviate the symptoms of parkinsonism. ...
... The role of deep brain stimulation (DBS) in modulating the ability of PD patients to ambulate has been controversial since its inception. Although electrical stimulation in the subthalamic nucleus (STN) effectively alleviates cardinal motor symptoms in PD (Pötter-Nerger and Volkmann, 2013;Horn et al., 2017), its efficacy for improving gait impairments and other axial signs is not as predictable (Barbe et al., 2020). These diverging results may be due to differences in stimulation parameters (Fan et al., 2023;Moreau et al., 2008;Ramdhani et al., 2015), which have led to interest in low-frequency stimulation (LFS, at 60---85 Hz) as an effective approach to immediately address these challenges (Mügge et al., 2023). ...
Background
A reduction in stride length is considered a key characteristic of gait kinematics in Parkinson’s disease (PD) and has been identified as a predictor of falls. Although low-frequency stimulation (LFS) has been suggested as a method to improve gait characteristics, the underlying structural network is not well understood.
Objective
This study aims to investigate the structural correlates of changes in stride length during LFS (85 Hz).
Methods
Objective gait performance was retrospectively evaluated in 19 PD patients who underwent deep brain stimulation (DBS) at 85 Hz and 130 Hz. Individual DBS contacts and volumes of activated tissue (VAT) were computed using preoperative magnetic resonance imaging (MRI) and postoperative computed tomography (CT) scans. Structural connectivity profiles to predetermined cortical and mesencephalic areas were estimated using a normative connectome.
Results
LFS led to a significant improvement in stride length compared to 130 Hz stimulation. The intersection between VAT and the associative subregion of the subthalamic nucleus (STN) was associated with an improvement in stride length and had structural connections to the supplementary motor area, prefrontal cortex, and pedunculopontine nucleus. Conversely, we found that a lack of improvement was linked to stimulation volumes connected to cortico-diencephalic fibers bypassing the STN dorsolaterally. The robustness of the connectivity model was verified through leave-one-patient-out, 5-, and 10-fold cross cross-validation paradigms.
Conclusion
These findings offer new insights into the structural connectivity that underlies gait changes following LFS. Targeting the non-motor subregion of the STN with LFS on an individual level may present a potential therapeutic approach for PD patients with gait disorders.
... While the precise mechanisms of action of DBS are not known, high-frequency stimulation can modulate local and distally connected neuronal populations within a pathological brain network to produce the desired therapeutic benefit, similar to those seen with ablative procedures [23]. Optimal target selection (depending on the condition being treated and underlying pathological brain circuits), accurate lead placement and optimal stimulation parameter selection can radically affect the overall response to treatment [28,29]. ...
Major Depressive Disorder continues to remain one of the most prevalent psychiatric diseases globally. Despite multiple trials of conventional therapies, a subset of patients fail to have adequate benefit to treatment. Deep brain stimulation (DBS) is a promising treatment in this difficult to treat population and has shown strong antidepressant effects across multiple cohorts. Nearly two decades of work have provided insights into the potential for chronic focal stimulation in precise brain targets to modulate pathological brain circuits that are implicated in the pathogenesis of depression. In this paper we review the rationale that prompted the selection of various brain targets for DBS, their subsequent clinical outcomes and common adverse events reported. We additionally discuss some of the pitfalls and challenges that have prevented more widespread adoption of this technology as well as future directions that have shown promise in improving therapeutic efficacy of DBS in the treatment of depression.
... Converging evidence suggests that DBS involving the posterodorsal STN facilitates the most effective suppression of motor symptoms with minimal side effects [14][15][16][17]. This region contains the STN motor region and the entry zone of relevant fiber tracts [18][19][20][21][22]. Furthermore, the region corresponds to the distribution of pathological beta-activity within the STN [23]. Notably, the role of the white matter adjacent to the STN is debated [24]. ...
Background
Conventional deep brain stimulation (DBS) programming via trial-and-error warrants improvement to ensure swift achievement of optimal outcomes. The definition of a sweet spot for subthalamic DBS in Parkinson’s disease (PD-STN-DBS) may offer such advancement.
Objective
This investigation examines the association of long-term motor outcomes with contact selection during monopolar review and different strategies for anatomically informed contact selection in a retrospective real-life cohort of PD-STN-DBS.
Methods
We compared contact selection based on a monopolar review (MPR) to multiple anatomically informed contact selection strategies in a cohort of 28 PD patients with STN-DBS. We employed a commercial software package for contact selection based on visual assessment of individual anatomy following two predefined strategies and two algorithmic approaches with automatic targeting of either the sensorimotor STN or our previously published sweet spot. Similarity indices between chronic stimulation and contact selection strategies were correlated to motor outcomes at 12 months follow-up.
Results
Lateralized motor outcomes of chronic DBS were correlated to the similarity between chronic stimulation and visual contact selection targeting the dorsal part of the posterior STN (rho = 0.36, p = 0.007). Similar relationships could not be established for MPR or any of the other investigated strategies.
Conclusions
Our data demonstrates that a visual contact selection following a predefined strategy can be linked to beneficial long-term motor outcomes in PD-STN-DBS. Since similar correlations could not be observed for the other approaches to anatomically informed contact selection, we conclude that clear definitions and prospective validation of any approach to imaging-based DBS-programming is warranted.
... lead-dbs. org/) provided the preprocessing which is described in detail in Horn and colleagues 62 . Standardized methods in Lead-DBS were used to produce the structural connectomes for the Schaefer parcellation scheme 60 . ...
Whole-brain models have proven to be useful to understand the emergence of collective activity among neural populations or brain regions. These models combine connectivity matrices, or connectomes, with local node dynamics, noise, and, eventually, transmission delays. Multiple choices for the local dynamics have been proposed. Among them, nonlinear oscillators corresponding to a supercritical Hopf bifurcation have been used to link brain connectivity and collective phase and amplitude dynamics in different brain states. Here, we studied the linear fluctuations of this model to estimate its stationary statistics, i.e., the instantaneous and lagged covariances and the power spectral densities. This linear approximation—that holds in the case of heterogeneous parameters and time-delays—allows analytical estimation of the statistics and it can be used for fast parameter explorations to study changes in brain state, changes in brain activity due to alterations in structural connectivity, and modulations of parameter due to non-equilibrium dynamics.
... Subthalamic beta-band activity is the most intensely studied LFP biomarker for parkinsonian symptoms, and its use as a control signal in adaptive DBS systems is beginning to transition out of the research environment and into clinical settings [11]. In addition, subthalamic DBS delivered at electrode locations that also exhibit a high degree of beta-band LFP activity are typically associated with good therapeutic outcomes [12]. Therefore, one application for patient-specific DBS LFP simulations is to use the model system to predict the spatial localization of a volume of synchronous neurons that give rise to the beta-band activity [6]. ...
Objective
Local field potential (LFP) recordings from deep brain stimulation (DBS) electrodes are commonly used in research analyses, and are beginning to be used in clinical practice. Computational models of DBS LFPs provide tools for investigating the biophysics and neural synchronization that underlie LFP signals. However, technical standards for DBS LFP model parameterization remain to be established. Therefore, the goal of this study was to evaluate the role of the volume conductor (VC) model complexity on simulated LFP signals in the subthalamic nucleus (STN).
Approach
We created a detailed human head VC model that explicitly represented the inhomogeneity and anisotropy associated with 12 different tissue structures. This VC model represented our “gold standard” for technical detail and electrical realism. We then incrementally decreased the complexity of the VC model and quantified the impact on the simulated LFP recordings. Identical STN neural source activity was used when comparing the different VC model variants.
Results
Ignoring tissue anisotropy reduced the simulated LFP amplitude by ~12%, while eliminating soft tissue heterogeneity had a negligible effect on the recordings. Simplification of the VC model to consist of a single homogenous isotropic tissue medium with a conductivity of 0.215 S/m contributed an additional ~3% to the error.
Significance
Highly detailed VC models do generate different results than simplified VC models. However, with errors in the range of ~15%, the use of a well-parameterized simple VC model is likely to be acceptable in most contexts for DBS LFP modeling.
Identifying lesion sites associated with central poststroke pain (CPSP) may facilitate targeted screening for early symptoms, possibly even paving the way for preventive measures and earlier treatment initiation. Here, we test the hypothesis that damage to a nociceptive pathway extending from the brainstem to the cerebral cortex, and including white matter tracts, is associated with CPSP. We investigated the lesion locations of 72 patients with CPSP relative to poststroke comparison subjects without pain (n = 123), divided into a discovery and independent validation data set. The study included three main analyses: (1) we compared lesion intersection with our a priori region of interest (ROI) between groups with and without CPSP, (2) we performed lesion-symptom mapping to evaluate whether lesions associated with CPSP localize to the a priori ROI, and (3) we used lesion network mapping to infer the broader structural and functional connectivity patterns associated with CPSP lesions. CPSP lesions overlapped the nociceptive pathway ROI to a greater extent than comparison lesions. Lesion-symptom mapping identified a CPSP-associated region overlapping with the ventrocaudal thalamus and adjacent white matter, which was located mostly within the a priori ROI. Lesion network mapping demonstrated that lesions associated with CPSP disrupt nodes and tracts of the nociceptive pathway ROI. Interestingly, the CPSP lesion network results demonstrated connectivity to intereffector nodes of the primary motor cortex, providing a novel link between CPSP and the somato–cognitive action network. Together, these findings indicate that CPSP can be conceptualized as a lesion-associated network disruption of the nociceptive pathway and somato–cognitive action network.
Background
Temporal interference stimulation (TIS) is a novel noninvasive electrical stimulation technique to focally modulate deep brain regions; a minimum of two high‐frequency signals ( f 1 and f 2 > 1 kHz) interfere to create an envelope‐modulated signal at a deep brain target with the frequency of modulation equal to the difference frequency: Δ f = | f 2 – f 1 |.
Objective
The goals of this study were to verify the capability of TIS to modulate the subthalamic nucleus (STN) with Δ f and to compare the effect of TIS and conventional deep brain stimulation (DBS) on the STN beta oscillations in patients with Parkinson's disease (PD).
Methods
DBS leads remained externalized after implantation, allowing local field potentials (LFPs) recordings in eight patients with PD. TIS was performed initially by two pairs ( f 1 = 9.00 kHz; f 2 = 9.13 kHz, 4 mA peak‐peak per pair maximum) of scalp electrodes placed in temporoparietal regions to focus the envelope signal maximum (Δ f = 130 Hz) at the motor part of the STN target.
Results
The comparison between the baseline LFPs and recordings after TIS and conventional DBS sessions showed substantial suppression of high beta power peak after both types of stimulation in all patients.
Conclusions
TIS has the potential to effectively modulate the STN and reduce the beta oscillatory activity in a completely noninvasive manner, as is traditionally possible only with intracranial DBS. Future studies should confirm the clinical effectiveness of TIS and determine whether TIS could be used to identify optimal DBS candidates and individualize DBS targets. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Background
Optimizing deep brain stimulation (DBS) in Parkinson’s disease (PD) requires a complex process for evaluating clinical benefit and adverse effects. Localizing the contact with maximum beta (13-30Hz) power using a novel in-clinic sensing-monopolar (SenseMP) recording may improve the efficiency of selecting clinically optimal DBS settings.
Objective
Compare the clinical outcomes of optimal programming settings determined by SenseMP versus standard-of-care monopolar review (ReviewMP) for DBS therapy in PD.
Methods
Ten PD patients (4F/6M, post-diagnosis = 9.2 ± 3.5 years; on/off percent change = 43.7 ± 14.0) with bilateral subthalamic nucleus (STN) DBS were recruited. Independent evaluation of unilateral STN DBS was assessed with both SenseMP to identify the DBS contact detecting maximum beta peak power and ReviewMP. MDS-UPDRS Part III assessments for unilateral symptoms were compared between SenseMP and ReviewMP, and the time to complete these two conditions was recorded.
Results
Change from baseline in overall clinical outcomes did not differ between conditions (SenseMP = 60.5%, ReviewMP = 60.1% (p = 0.85); 19 hemispheres), nor were there differences in sub-analysis for bradykinesia, rigidity, and tremor. Using SenseMP to identify and conduct single contact ReivewMP was more time efficient than ReviewMP: 16.3 ± 3.6 minutes vs. 124.3 ± 23.1 minutes (p = 5.46e-15). SenseMP identified the maximum beta contact in SenseBP pairs at a specific level (17/20 times).
Conclusion
This study demonstrates that SenseMP localization of maximum beta peak power for DBS contact selection provides equivalent clinical efficacy to ReviewMP at a fraction of the required time.
Parkinson's disease is linked to increased beta oscillations in the subthalamic nucleus, which correlate with motor symptoms. However, findings across studies have varied. Our standardized analysis of multicenter datasets reveals that insufficient sample sizes contributed to these discrepancies - a challenge we address by pooling datasets into one large cohort (n=119). Moving beyond beta power, we disentangled spectral components reflecting distinct neural processes. Combining aperiodic offset, low beta, and low gamma oscillations explained significantly more variance in symptom severity than beta alone. Moreover, interhemispheric within-patient analyses showed that, unlike beta oscillations, aperiodic broadband power - likely reflecting spiking activity - was increased in the more affected hemisphere. These findings identify aperiodic broadband power as a potential biomarker for adaptive deep brain stimulation and provide novel insights into the relationship between subthalamic hyperactivity and motor symptoms in human Parkinson's disease.
Freezing of gait (FOG) is a significant disability in Parkinson disease (PD). Deep brain stimulation (DBS) of the subthalamic nucleus (STN) only partially alleviates it, with approximately one-third of patients experiencing worsening FOG within a year after surgery. The precise role of STN dysfunction in gait disabilities and FOG remains not fully elucidated. To investigate this, we recorded gait and STN local field potential (LFP) activity in 38 PD patients, both Off and On dopamine medication. Our analysis focused on the relationship between gait performance and STN neuronal activity, particularly examining differences in LFP activity across the posterior-sensorimotor and central-associative regions of the STN. When Off dopamine medication, 12 patients experienced FOG during recordings, with a total of 263 FOG episodes documented. Even in trials without FOG episodes, these patients exhibited altered gait initiation strategies, prioritizing stepping rhythm to manage balance and initiate walking. In contrast, non-FOG patients maintained a higher walking pace. STN activity patterns revealed key differences. In FOG patients, weaker STN alpha/low beta band activity in the STN was associated with walking pace, while stronger decreased low beta band activity correlated with rhythm and balance control. This low beta band association extended from the posterior-sensorimotor to the central-associative STN. In contrast, non-FOG patients showed a more restricted relationship between low beta band activity and gait performance, confined to the posterior STN. As stepping rhythm deteriorated further in FOG patients, FOG episodes occurred. FOG episodes were preceeded by a significant positive relationship between high beta power and rhythm restricted to the posterior STN, with a reverse negative relationship with pace, and a disruption in low beta desynchronization across both posterior and central STN regions. Dopamine medication significantly improved gait patterns, and partially restored STN neuronal activity, reducing differences between FOG and non-FOG patients. These findings differentiate two FOG states, i.e. predisposition and occurrence, each associated with distinct gait initiation strategies and STN activity patterns. They suggest distinct pathophysiological roles of low and high beta band STN activity within specific STN regions in regulating gait and FOG. These findings provide key insights for refining targeted DBS therapies.
Deep brain stimulation (DBS) is an established treatment for motor disorders like Parkinson’s disease, but its mechanisms and effects on neurons and networks are not fully understood, limiting research-driven progress. This review presents a framework that combines neurophysiological insights and translational research to enhance DBS therapy, emphasizing biomarkers, device technology, and symptom-specific neuromodulation. It also examines the role of animal research in improving DBS, while acknowledging challenges in clinical translation.
Deep brain stimulation (DBS) has been established as an effective neuromodulatory treatment for Parkinson's disease (PD) with motor complications or refractory tremor. Various DBS devices with unique technology platforms are commercially available and deliver continuous, open-loop stimulation. The Percept™ family of neurostimulators use BrainSense™ technology with five key features to sense local field potentials while stimulating, enabling integration of physiologic data into the routine practice of DBS programming. The newly approved Percept™ rechargeable RC implantable pulse generator offers a smaller, thinner design and reduced recharge time with prolonged recharge interval. In this review, we describe the application of local field potential sensing-based programming in PD and highlight the potential future clinical implementation of closed-loop stimulation using the Percept™ RC implantable pulse generator.
Background
Segmented electrodes for deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson’s disease (PD) enable directional current steering leading to expanded programming options.
Objective
This retrospective study covering a longitudinal period of up to 7 years compares the efficacy of segmented and non-segmented leads in motor symptom alleviation and reduction of dopaminergic medication in PD patients treated in a specialized center and assesses the long-term use of directional steering in clinical routine.
Methods
Demographic data and clinical scores before surgery and at 12-month follow-up (12MFU) as well as stimulation parameters at 12MFU and last follow-up (LFU) were assessed in all patients implanted with segmented leads between 01/2016 and 12/2019 and non-segmented leads in a corresponding time-period. Patients were classified as very good (>60 %), good (30–60 %) and poor (<30 %) responders according to DBS-induced motor improvement.
Results
Clinical data at 12MFU was available for 61/96 patients with segmented (SEG) and 42/53 with non-segmented leads (N-SEG). Mean DBS-induced motor improvement and reduction of medication at 12MFU did not differ significantly between SEG and N-SEG groups or in a subgroup analysis of steering modes. There was a lower proportion of poor responders in the SEG compared with the N-SEG group (23% vs. 31%), though not statistically significant. At LFU, the percentage of patients set at directional steering increased from 54% to 70%.
Conclusion
Efficacy in reduction of motor symptoms and medication does not differ between electrode types for STN-DBS at 12 months follow-up. The use of directional steering increases over time and may account for a lower proportion of poor responders.
Different whole-brain computational models have been recently developed to investigate hypotheses related to brain mechanisms. Among these, the Dynamic Mean Field (DMF) model is particularly attractive, combining a biophysically realistic model that is scaled up via a mean-field approach and multimodal imaging data. However, an important barrier to the widespread usage of the DMF model is that current implementations are computationally expensive, supporting only simulations on brain parcellations that consider less than 100 brain regions. Here, we introduce an efficient and accessible implementation of the DMF model: the FastDMF. By leveraging analytical and numerical advances—including a novel estimation of the feedback inhibition control parameter and a Bayesian optimization algorithm—the FastDMF circumvents various computational bottlenecks of previous implementations, improving interpretability, performance, and memory use. Furthermore, these advances allow the FastDMF to increase the number of simulated regions by one order of magnitude, as confirmed by the good fit to fMRI data parcellated at 90 and 1,000 regions. These advances open the way to the widespread use of biophysically grounded whole-brain models for investigating the interplay between anatomy, function, and brain dynamics and to identify mechanistic explanations of recent results obtained from fine-grained neuroimaging recordings.
The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic review aims to cover mostly findings related to changes in the physical distribution of neurons and their connections—the connectome—both structural and functional, as well as their modelling approaches. It does not intend to offer an extensive description of all conditions affecting the brain; rather, it presents the most common ones. Thus, here, we highlight the need for accurate brain modelling that can subsequently be used to understand brain function and be applied to diagnose, track, and simulate treatments for the most prevalent pathologies affecting the brain.
Control of actions allows adaptive, goal-directed behaviour. The basal ganglia, including the subthalamic nucleus, are thought to play a central role in dynamically controlling actions through recurrent negative feedback loops with the cerebral cortex. Here, we summarize recent translational studies that used deep brain stimulation to record neural activity from and apply electrical stimulation to the subthalamic nucleus in people with Parkinson’s disease.
These studies have elucidated spatial, spectral and temporal features of the neural mechanisms underlying the controlled delay of actions in cortico-subthalamic networks and demonstrated their causal effects on behaviour in distinct processing windows. While these mechanisms have been conceptualized as control signals for suppressing impulsive response tendencies in conflict tasks and as decision threshold adjustments in value-based and perceptual decisions, we propose a common framework linking decision-making, cognition and movement. Within this framework, subthalamic deep brain stimulation can lead to suboptimal choices by reducing the time that patients take for deliberation before committing to an action. However, clinical studies have consistently shown that the occurrence of impulse control disorders is reduced, not increased, after subthalamic deep brain stimulation surgery. This apparent contradiction can be reconciled when recognizing the multifaceted nature of impulsivity, its underlying mechanisms and modulation by treatment. While subthalamic deep brain stimulation renders patients susceptible to making decisions without proper forethought, this can be disentangled from effects related to dopamine comprising sensitivity to benefits versus costs, reward delay aversion and learning from outcomes.
Alterations in these dopamine-mediated mechanisms are thought to underlie the development of impulse control disorders and can be relatively spared with reduced dopaminergic medication after subthalamic deep brain stimulation. Together, results from studies using deep brain stimulation as an experimental tool have improved our understanding of action control in the human brain and have important implications for treatment of patients with neurological disorders.
Parkinson’s disease (PD) is characterized by the disruption of repetitive, concurrent and sequential motor actions
due to compromised timing-functions principally located in cortex-basal ganglia (BG) circuits. Increasing evidence
suggests that motor impairments in untreated PD patients are linked to an excessive synchronization of
cortex-BG activity at beta frequencies (13–30 Hz). Levodopa and subthalamic nucleus deep brain stimulation
(STN-DBS) suppress pathological beta-band reverberation and improve the motor symptoms in PD. Yet a dynamic
tuning of beta oscillations in BG-cortical loops is fundamental for movement-timing and synchronization,
and the impact of PD therapies on sensorimotor functions relying on neural transmission in the beta frequency-
range remains controversial. Here, we set out to determine the differential effects of network neuromodulation
through dopaminergic medication (ON and OFF levodopa) and STN-DBS (ON-DBS, OFF-DBS) on tapping synchronization
and accompanying cortical activities. To this end, we conducted a rhythmic finger-tapping study
with high-density EEG-recordings in 12 PD patients before and after surgery for STN-DBS and in 12 healthy
controls. STN-DBS significantly ameliorated tapping parameters as frequency, amplitude and synchrony to the
given auditory rhythms. Aberrant neurophysiologic signatures of sensorimotor feedback in the beta-range were
found in PD patients: their neural modulation was weaker, temporally sluggish and less distributed over the right
cortex in comparison to controls. Levodopa and STN-DBS boosted the dynamics of beta-band modulation over
the right hemisphere, hinting to an improved timing of movements relying on tactile feedback. The strength of
the post-event beta rebound over the supplementary motor area correlated significantly with the tapping
asynchrony in patients, thus indexing the sensorimotor match between the external auditory pacing signals and
the performed taps. PD patients showed an excessive interhemispheric coherence in the beta-frequency range
during the finger-tapping task, while under DBS-ON the cortico-cortical connectivity in the beta-band was
normalized. Ultimately, therapeutic DBS significantly ameliorated the auditory-motor coupling of PD patients,
enhancing the electrophysiological processing of sensorimotor feedback-information related to beta-band activity,
and thus allowing a more precise cued-tapping performance.
Increased oscillatory beta activity in basal ganglia is one of the main electrophysiological biomarkers of impaired motor control in Parkinson’s disease. However, the functional role of dynamical rhythmic processes during movements is still not investigated in detail. We used microelectrode recordings to investigate the subthalamic nucleus neuronal activity in 9 patients with Parkinson’s disease during deep brain stimulation surgery. We have shown that the amplitude of the subthalamic nucleus alpha (7–12 Hz) and low-beta (12–20 Hz) activity correlated with motor impairment indices in patients with Parkinson’s disease. Also, we have shown that, in contrast to beta rhythmic activity, the magnitude of alpha activity decreased significantly during motor tests execution. Moreover, the degree of rhythmic activity suppression in the alpha band correlated with the severity of bradykinesia. These results allow us to suppose that, along with beta activities, subthalamic nucleus neuronal alpha activity also participate in motor control of Parkinson’s disease patients.
Oscillatory activity within the beta frequency range (13-30Hz) serves as a Parkinson’s disease biomarker for tailoring deep brain stimulation (DBS) treatments. Currently, identifying clinically relevant beta signals, specifically frequencies of peak amplitudes within the beta spectral band, is a subjective process. To inform potential strategies for objective clinical decision making, we assessed algorithms for identifying beta peaks and devised a standardized approach for both research and clinical applications. Employing a novel monopolar referencing strategy, we utilized a brain sensing device to measure beta peak power across distinct contacts along each DBS electrode implanted in the subthalamic nucleus. We then evaluated the accuracy of ten beta peak detection algorithms, both existing and new, against a benchmark established by expert consensus. The most accurate algorithms matched the expert consensus in performance and reliably predicted the clinical stimulation parameters during follow-up visits. These findings highlight the potential of algorithmic solutions to overcome the subjective bias in beta peak identification, presenting viable options for standardizing this process. Such advancements could lead to significant improvements in the efficiency and accuracy of patient-specific DBS therapy parameterization.
Background
Deep Brain Stimulation (DBS), applying chronic electrical stimulation of subcortical structures, is a clinical intervention applied in major neurologic disorders. In order to achieve a good clinical effect, accurate electrode placement is necessary. The primary localisation is typically based on presurgical MRI imaging, often followed by intra-operative electrophysiology recording to increase the accuracy and to compensate for brain shift, especially in cases where the surgical target is small, and there is low contrast: e.g., in Parkinson’s disease (PD) and in its common target, the subthalamic nucleus (STN).
Methods
We propose a novel, fully automatic method for intra-operative surgical navigation. First, the surgical target is segmented in presurgical MRI images using a statistical shape-intensity model. Next, automated alignment with intra-operatively recorded microelectrode recordings is performed using a probabilistic model of STN electrophysiology. We apply the method to a dataset of 120 PD patients with clinical T2 1.5T images, of which 48 also had available microelectrode recordings (MER).
Results
The proposed segmentation method achieved STN segmentation accuracy around dice = 0.60 compared to manual segmentation. This is comparable to the state-of-the-art on low-resolution clinical MRI data. When combined with electrophysiology-based alignment, we achieved an accuracy of 0.85 for correctly including recording sites of STN-labelled MERs in the final STN volume.
Conclusion
The proposed method combines image-based segmentation of the subthalamic nucleus with microelectrode recordings to estimate their mutual location during the surgery in a fully automated process. Apart from its potential use in clinical targeting, the method can be used to map electrophysiological properties to specific parts of the basal ganglia structures and their vicinity.
Background
The ventral intermediate nucleus of the thalamus (VIM) is an effective target for deep brain stimulation in tremor patients. Despite its therapeutic importance, its oscillatory coupling to cortical areas has rarely been investigated in humans.
Objectives
The objective of this study was to identify the cortical areas coupled to the VIM in patients with essential tremor.
Methods
We combined resting‐state magnetoencephalography with local field potential recordings from the VIM of 19 essential tremor patients. Whole‐brain maps of VIM–cortex coherence in several frequency bands were constructed using beamforming and compared with corresponding maps of subthalamic nucleus (STN) coherence based on data from 19 patients with Parkinson's disease. In addition, we computed spectral Granger causality.
Results
The topographies of VIM–cortex and STN–cortex coherence were very similar overall but differed quantitatively. Both nuclei were coupled to the ipsilateral sensorimotor cortex in the high‐beta band; to the sensorimotor cortex, brainstem, and cerebellum in the low‐beta band; and to the temporal cortex, brainstem, and cerebellum in the alpha band. High‐beta coherence to sensorimotor cortex was stronger for the STN ( P = 0.014), whereas low‐beta coherence to the brainstem was stronger for the VIM ( P = 0.017). Although the STN was driven by cortical activity in the high‐beta band, the VIM led the sensorimotor cortex in the alpha band.
Conclusions
Thalamo‐cortical coupling is spatially and spectrally organized. The overall similar topographies of VIM–cortex and STN–cortex coherence suggest that functional connections are not necessarily unique to one subcortical structure but might reflect larger frequency‐specific networks involving VIM and STN to a different degree. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
In Parkinson’s disease, imbalances between ‘antikinetic’ and ‘prokinetic’ patterns of neuronal oscillatory activity are related to motor dysfunction. Invasive brain recordings from the motor network have suggested that medical or surgical therapy can promote a prokinetic state by inducing narrowband gamma rhythms (65–90 Hz). Excessive narrowband gamma in the motor cortex promotes dyskinesia in rodent models, but the relationship between narrowband gamma and dyskinesia in humans has not been well established.
To assess this relationship, we used a sensing-enabled deep brain stimulator system, attached to both motor cortex and basal ganglia (subthalamic or pallidal) leads, paired with wearable devices that continuously tracked motor signs in the contralateral upper limbs. We recorded 984 h of multisite field potentials in 30 hemispheres of 16 subjects with Parkinson’s disease (2/16 female, mean age 57 ± 12 years) while at home on usual antiparkinsonian medications. Recordings were done 2–4 weeks after implantation, prior to starting therapeutic stimulation.
Narrowband gamma was detected in the precentral gyrus, subthalamic nucleus or both structures on at least one side of 92% of subjects with a clinical history of dyskinesia. Narrowband gamma was not detected in the globus pallidus. Narrowband gamma spectral power in both structures co-fluctuated similarly with contralateral wearable dyskinesia scores (mean correlation coefficient of ρ = 0.48 with a range of 0.12–0.82 for cortex, ρ = 0.53 with a range of 0.5–0.77 for subthalamic nucleus). Stratification analysis showed the correlations were not driven by outlier values, and narrowband gamma could distinguish ‘on’ periods with dyskinesia from ‘on’ periods without dyskinesia. Time lag comparisons confirmed that gamma oscillations herald dyskinesia onset without a time lag in either structure when using 2-min epochs. A linear model incorporating the three oscillatory bands (beta, theta/alpha and narrowband gamma) increased the predictive power of dyskinesia for several subject hemispheres. We further identified spectrally distinct oscillations in the low gamma range (40–60 Hz) in three subjects, but the relationship of low gamma oscillations to dyskinesia was variable.
Our findings support the hypothesis that excessive oscillatory activity at 65–90 Hz in the motor network tracks with dyskinesia similarly across both structures, without a detectable time lag. This rhythm may serve as a promising control signal for closed-loop deep brain stimulation using either cortical or subthalamic detection.
The brain is a nonequilibrium system whose dynamics change in different brain states, such as wakefulness and deep sleep. Thermodynamics provides the tools for revealing these nonequilibrium dynamics. We used violations of the fluctuation-dissipation theorem to describe the hierarchy of nonequilibrium dynamics associated with different brain states. Together with a whole-brain model fitted to empirical human neuroimaging data, and deriving the appropriate analytical expressions, we were able to capture the deviation from equilibrium in different brain states that arises from asymmetric interactions and hierarchical organization.
The subthalamic nucleus (STN) is a key structure for somatic motor control via the basal ganglia. In the present study, we demonstrate that the STN of the macaque monkey has dual sets of body part representations. Each of the two separate portions of the STN is characterized with somatotopically arranged direct cortical inputs that are derived from the primary motor cortex (MI) and the supplementary motor area (SMA). The first set of body part representations is transformed from the MI to the lateral STN, whereas the second set is transformed from the SMA to the medial STN. Intracortical microstimulation mapping was carried out to guide paired injections of anterograde tracers into somatotopically corresponding regions of the MI and the SMA. We found that direct inputs from the MI were allocated mostly within the lateral half of the STN, whereas those from the SMA were distributed predominantly within its medial half. Of particular interest was that the arrangement of somatotopical representations from the SMA to the medial STN was reversed against the ordering of those from the MI to the lateral STN; the orofacial, forelimb, and hindlimb parts were represented from medial to lateral within the medial STN, whereas these body parts were represented, in the inverse order, mediolaterally within the lateral STN. Moreover, inputs from homotopical MI and SMA regions were found to converge only partially into the STN. The present findings could account for somatotopically specific involuntary movements manifested in hemiballism that is caused by destruction of the STN.
Fiber tractography based on non-invasive diffusion imaging is at the heart of connectivity studies of the human brain. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain dataset with ground truth white matter tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. While most state-of-the-art algorithms reconstructed 90% of ground truth bundles to at least some extent, on average they produced four times more invalid than valid bundles. About half of the invalid bundles occurred systematically in the majority of submissions. Our results demonstrate fundamental ambiguities inherent to tract reconstruction methods based on diffusion orientation information, with critical consequences for the approach of diffusion tractography in particular and human connectivity studies in general.
The published journal version is also available at https://www.nature.com/articles/s41467-017-01285-x
Objective:
Beta band oscillations in the subthalamic nucleus (STN) have been proposed as a pathophysiological signature in patients with Parkinson's disease (PD). The aim of this study was to investigate the potential association between oscillatory activity in the STN and symptom severity in PD.
Methods:
Subthalamic local field potentials were recorded from 63 PD patients in a dopaminergic OFF state. Power-spectra were analyzed for the frequency range from 5 to 95 Hz and correlated with individual UPDRS-III motor scores in the OFF state.
Results:
A correlation between total UPDRS-III scores and 8 to 35 Hz activity was revealed across all patients (ρ = 0.44, P < .0001). When correlating each frequency bin, a narrow range from 10 to 15 Hz remained significant for the correlation (false discovery rate corrected P < .05).
Conclusion:
Our results show a correlation between local STN 8 to 35 Hz power and impairment in PD, further supporting the role of subthalamic oscillatory activity as a potential biomarker for PD.
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The use of subthalamic nucleus deep brain stimulation in Parkinson’s disease is limited in some patients by behavioural side-effects. Using perioperative electrophysiological recordings and presurgical neuroimaging, Accolla et al . characterize the anatomical networks modulated by deep brain stimulation, and reveal the existence of overlapping functional areas within the nucleus.
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The use of subthalamic nucleus deep brain stimulation in Parkinson’s disease is limited in some patients by behavioural side-effects. Using perioperative electrophysiological recordings and presurgical neuroimaging, Accolla et al . characterize the anatomical networks modulated by deep brain stimulation, and reveal the existence of overlapping functional areas within the nucleus.
Objective:
High-amplitude beta band oscillations within the subthalamic nucleus are frequently associated with Parkinson's disease but it is unclear how they might lead to motor impairments. Here we investigate a likely pathological coupling between the phase of beta band oscillations and the amplitude of high-frequency oscillations around 300 Hz.
Methods:
We analysed an extensive data set comprising resting-state recordings obtained from deep brain stimulation electrodes in 33 patients before and/or after taking dopaminergic medication. We correlated mean values of spectral power and phase-amplitude coupling with severity of hemibody bradykinesia/rigidity. In addition, we used simultaneously recorded magnetoencephalography to look at functional interactions between the subthalamic nucleus and ipsilateral motor cortex.
Results:
Beta band power and phase-amplitude coupling within the subthalamic nucleus correlated positively with severity of motor impairment. This effect was more pronounced within the low-beta range, whilst coherence between subthalamic nucleus and motor cortex was dominant in the high-beta range.
Conclusions:
We speculate that the beta band might impede pro-kinetic high-frequency activity patterns when phase-amplitude coupling is prominent. Furthermore, results provide evidence for a functional subdivision of the beta band into low and high frequencies.
Significance:
Our findings contribute to the interpretation of oscillatory activity within the cortico-basal ganglia circuit.
Objectives:
Recent studies suggest that oscillatory beta activity could be used as a state biomarker in patients with Parkinson's disease for subthalamic closed-loop stimulation with the intention of improving clinical benefit. Here we investigate the feasibility of subthalamic recordings via a novel chronically implanted pulse generator.
Methods:
Subthalamic local field potential recordings were obtained from eight patients before and during deep brain stimulation (DBS). All data were analyzed in the frequency domain using Fourier transform-based methods and compared between ON and OFF stimulation conditions.
Results:
Distinct peaks of oscillatory beta band activity were found in 12 of 15 electrodes. DBS induced a significant frequency specific suppression of oscillatory beta activity (p = 0.002).
Conclusion:
The results of the study suggest that oscillatory beta band synchronization and its modulation by DBS is recordable with a system suitable for chronic implantation and may serve as a biomarker for subthalamic closed-loop stimulation in patients with Parkinson's disease.
A traditional and widely used approach for linking neurological symptoms to specific brain regions involves identifying overlap in lesion location across patients with similar symptoms, termed lesion mapping. This approach is powerful and broadly applicable, but has limitations when symptoms do not localize to a single region or stem from dysfunction in regions connected to the lesion site rather than the site itself. A newer approach sensitive to such network effects involves functional neuroimaging of patients, but this requires specialized brain scans beyond routine clinical data, making it less versatile and difficult to apply when symptoms are rare or transient. In this article we show that the traditional approach to lesion mapping can be expanded to incorporate network effects into symptom localization without the need for specialized neuroimaging of patients. Our approach involves three steps: (i) transferring the three-dimensional volume of a brain lesion onto a reference brain; (ii) assessing the intrinsic functional connectivity of the lesion volume with the rest of the brain using normative connectome data; and (iii) overlapping lesion-associated networks to identify regions common to a clinical syndrome. We first tested our approach in peduncular hallucinosis, a syndrome of visual hallucinations following subcortical lesions long hypothesized to be due to network effects on extrastriate visual cortex. While the lesions themselves were heterogeneously distributed with little overlap in lesion location, 22 of 23 lesions were negatively correlated with extrastriate visual cortex. This network overlap was specific compared to other subcortical lesions (P < 10(-5)) and relative to other cortical regions (P < 0.01). Next, we tested for generalizability of our technique by applying it to three additional lesion syndromes: central post-stroke pain, auditory hallucinosis, and subcortical aphasia. In each syndrome, heterogeneous lesions that themselves had little overlap showed significant network overlap in cortical areas previously implicated in symptom expression (P < 10(-4)). These results suggest that (i) heterogeneous lesions producing similar symptoms share functional connectivity to specific brain regions involved in symptom expression; and (ii) publically available human connectome data can be used to incorporate these network effects into traditional lesion mapping approaches. Because the current technique requires no specialized imaging of patients it may prove a versatile and broadly applicable approach for localizing neurological symptoms in the setting of brain lesions.
© The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Primary dystonia has been associated with an underlying dysfunction of a wide network of brain regions including the motor cortex, basal ganglia, cerebellum, brainstem and spinal cord. Dystonia can be effectively treated by pallidal deep brain stimulation although the mechanism of this effect is not well understood. Here, we sought to characterize cortico-basal ganglia functional connectivity using a frequency-specific measure of connectivity-coherence. We recorded direct local field potentials from the human pallidum simultaneously with whole head magnetoencephalography to characterize functional connectivity in the cortico-pallidal oscillatory network in nine patients with idiopathic dystonia. Three-dimensional cortico-pallidal coherence images were compared to surrogate images of phase shuffled data across patients to reveal clusters of significant coherence (family-wise error P < 0.01, voxel extent 1000). Three frequency-specific, spatially-distinct cortico-pallidal networks have been identified: a pallido-temporal source of theta band (4-8 Hz) coherence, a pallido-cerebellar source of alpha band (7-13 Hz) coherence and a cortico-pallidal source of beta band (13-30 Hz) coherence over sensorimotor areas. Granger-based directionality analysis revealed directional coupling with the pallidal local field potentials leading in the theta and alpha band and the magnetoencephalographic cortical source leading in the beta band. The degree of pallido-cerebellar coupling showed an inverse correlation with dystonic symptom severity. Our data extend previous findings in patients with Parkinson's disease describing motor cortex-basal ganglia oscillatory connectivity in the beta band to patients with dystonia. Source coherence analysis revealed two additional frequency-specific networks involving the temporal cortex and the cerebellum. Pallido-cerebellar oscillatory connectivity and its association with dystonic symptoms provides further confirmation of cerebellar involvement in dystonia that has been recently reported using functional magnetic resonance imaging and fibre tracking.
Significance
Brain stimulation is a powerful treatment for an increasing number of psychiatric and neurological diseases, but it is unclear why certain stimulation sites work or where in the brain is the best place to stimulate to treat a given patient or disease. We found that although different types of brain stimulation are applied in different locations, targets used to treat the same disease most often are nodes in the same brain network. These results suggest that brain networks might be used to understand why brain stimulation works and to improve therapy by identifying the best places to stimulate the brain.
Despite advances in understanding basic organizational principles of the human basal ganglia, accurate in vivo assessment of their anatomical properties is essential to improve early diagnosis in disorders with corticosubcortical pathology and optimize target planning in deep brain stimulation. Main goal of this study was the detailed topological characterization of limbic, associative, and motor subdivisions of the subthalamic nucleus (STN) in relation to corresponding corticosubcortical circuits. To this aim, we used magnetic resonance imaging and investigated independently anatomical connectivity via white matter tracts next to brain tissue properties. On the basis of probabilistic diffusion tractography we identified STN subregions with predominantly motor, associative, and limbic connectivity. We then computed for each of the nonoverlapping STN subregions the covariance between local brain tissue properties and the rest of the brain using high-resolution maps of magnetization transfer (MT) saturation and longitudinal (R1) and transverse relaxation rate (R2*). The demonstrated spatial distribution pattern of covariance between brain tissue properties linked to myelin (R1 and MT) and iron (R2*) content clearly segregates between motor and limbic basal ganglia circuits. We interpret the demonstrated covariance pattern as evidence for shared tissue properties within a functional circuit, which is closely linked to its function. Our findings open new possibilities for investigation of changes in the established covariance pattern aiming at accurate diagnosis of basal ganglia disorders and prediction of treatment outcome. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
Functional magnetic resonance imaging (MRI) data are usually registered into standard anatomical space. However, standard atlases, such as LPBA40, the Harvard–Oxford atlas, FreeSurfer, and the Jülich cytoarchitectonic maps all lack important detailed information about small subcortical structures like the substantia nigra and subthalamic nucleus. Here we introduce a new subcortical probabilistic atlas based on ultra-high resolution in-vivo anatomical imaging from 7 T MRI. The atlas includes six important but elusive subcortical nuclei: the striatum, the globus pallidus internal and external segment (GPi/e), the subthalamic nucleus, the substantia nigra, and the red nucleus. With a sample of 30 young subjects and carefully cross-validated delineation protocols, our atlas is able to capture the anatomical variability within healthy populations for each of the included structures at an unprecedented level of detail. All the generated probabilistic atlases are registered to MNI standard space and are publicly available.
To further determine the causes of variable outcome from deep brain stimulation of the subthalamic nucleus (DBS-STN) in patients with Parkinson disease (PD).
Data were obtained from our cohort of 309 patients with PD who underwent DBS-STN between 1996 and 2009. We examined the relationship between the 1-year motor, cognitive, and psychiatric outcomes and (1) preoperative PD clinical features, (2) MRI measures, (3) surgical procedure, and (4) locations of therapeutic contacts.
Pre- and postoperative results were obtained in 262 patients with PD. The best motor outcome was obtained when stimulating contacts were located within the STN as compared with the zona incerta (64% vs 49% improvement). Eighteen percent of the patients presented a postoperative cognitive decline, which was found to be principally related to the surgical procedure. Other factors predictive of poor cognitive outcome were perioperative confusion and psychosis. Nineteen patients showed a stimulation-induced hypomania, which was related to both the form of the disease (younger age, shorter disease duration, higher levodopa responsiveness) and the ventral contact location. Postoperative depression was more frequent in patients already showing preoperative depressive and/or residual axial motor symptoms.
In this homogeneous cohort of patients with PD, we showed that (1) the STN is the best target to improve motor symptoms, (2) postoperative cognitive deficit is mainly related to the surgery itself, and (3) stimulation-induced hypomania is related to a combination of both the disease characteristics and a more ventral STN location.
The subthalamic nucleus (STN) is an important node of the cortico-basal ganglia network and the main target of deep brain stimulation (DBS) in Parkinson's disease. Histological studies have revealed an inhomogeneous iron distribution within the STN, which has been related to putative subdivisions within this nucleus. Here, we investigate the iron distribution in more detail using quantitative susceptibility mapping (QSM), a novel magnetic resonance imaging (MRI) contrast mechanism. QSM allows for detailed assessment of iron content in both in vivo and postmortem tissue. Twelve human participants and 7 postmortem brain samples containing the STN were scanned using ultra-high field 7 Tesla (T) MRI. Iron concentrations were found to be higher in the medial-inferior tip of the STN. Using quantitative methods we show that the increase of iron concentration towards the medial-inferior tip is of a gradual rather than a discrete nature. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
The role of distinct limbic areas in emotion regulation has been largely inferred from neuroimaging studies. Recently, the opportunity for intracranial recordings from limbic areas has arisen in patients undergoing deep brain stimulation (DBS) for neuropsychiatric disorders including major depressive disorder (MDD) and obsessive compulsive disorder (OCD). Here we test the hypothesis that distinct temporal patterns of local field potential (LFP) activity in the human limbic system reflect disease state and symptom severity in MDD and OCD patients. To this end, we recorded LFPs via implanted DBS electrodes from the bed nucleus of stria terminalis (BNST area) in 12 patients (5 OCD, 7 MDD) and from the subgenual cingulate cortex in 7 MDD patients (CG25 area). We found a distinct pattern of oscillatory activity with significantly higher α-power in MDD compared with OCD in the BNST area (broad α-band 8-14 Hz; P<0.01) and a similar level of α-activity in the CG25 area as in the BNST area in MDD patients. The mean α-power correlated with severity of depressive symptoms as assessed by the Beck depression inventory in MDD (n=14, r=0.55, P=0.042) but not with severity of obsessive compulsive symptoms in OCD. Here we show larger α-band activity in MDD patients compared with OCD recorded from intracranial DBS targets. Our results suggest that α-activity in the limbic system may be a signature of symptom severity in MDD and may serve as a potential state biomarker for closed loop DBS in MDD.Molecular Psychiatry advance online publication, 11 February 2014; doi:10.1038/mp.2014.2.
Electrophysiological studies suggest that rest tremor in Parkinson's disease is associated with an alteration of oscillatory activity. Although it is well known that tremor depends on cortico-muscular coupling, it is unclear whether synchronization within and between brain areas is specifically related to the presence and severity of tremor. To tackle this longstanding issue, we took advantage of naturally occurring spontaneous tremor fluctuations and investigated cerebral synchronization in the presence and absence of rest tremor. We simultaneously recorded local field potentials from the subthalamic nucleus, the magnetoencephalogram and the electromyogram of forearm muscles in 11 patients with Parkinson's disease (all male, age: 52-74 years). Recordings took place the day after surgery for deep brain stimulation, after withdrawal of anti-parkinsonian medication. We selected epochs containing spontaneous rest tremor and tremor-free epochs, respectively, and compared power and coherence between subthalamic nucleus, cortex and muscle across conditions. Tremor-associated changes in cerebro-muscular coherence were localized by Dynamic Imaging of Coherent Sources. Subsequently, cortico-cortical coupling was analysed by computation of the imaginary part of coherency, a coupling measure insensitive to volume conduction. After tremor onset, local field potential power increased at individual tremor frequency and cortical power decreased in the beta band (13-30 Hz). Sensor level subthalamic nucleus-cortex, cortico-muscular and subthalamic nucleus-muscle coherence increased during tremor specifically at tremor frequency. The increase in subthalamic nucleus-cortex coherence correlated with the increase in electromyogram power. On the source level, we observed tremor-associated increases in cortico-muscular coherence in primary motor cortex, premotor cortex and posterior parietal cortex contralateral to the tremulous limb. Analysis of the imaginary part of coherency revealed tremor-dependent coupling between these cortical areas at tremor frequency and double tremor frequency. Our findings demonstrate a direct relationship between the synchronization of cerebral oscillations and tremor manifestation. Furthermore, they suggest the feasibility of tremor detection based on local field potentials and might thus become relevant for the design of closed-loop stimulation systems.
Brain-computer interfaces (BCIs) could potentially be used to interact with pathological brain signals to intervene and ameliorate their effects in disease states. Here, we provide proof-of-principle of this approach by using a BCI to interpret pathological brain activity in patients with advanced Parkinson disease (PD) and to use this feedback to control when therapeutic deep brain stimulation (DBS) is delivered. Our goal was to demonstrate that by personalizing and optimizing stimulation in real time, we could improve on both the efficacy and efficiency of conventional continuous DBS.
We tested BCI-controlled adaptive DBS (aDBS) of the subthalamic nucleus in 8 PD patients. Feedback was provided by processing of the local field potentials recorded directly from the stimulation electrodes. The results were compared to no stimulation, conventional continuous stimulation (cDBS), and random intermittent stimulation. Both unblinded and blinded clinical assessments of motor effect were performed using the Unified Parkinson's Disease Rating Scale.
Motor scores improved by 66% (unblinded) and 50% (blinded) during aDBS, which were 29% (p = 0.03) and 27% (p = 0.005) better than cDBS, respectively. These improvements were achieved with a 56% reduction in stimulation time compared to cDBS, and a corresponding reduction in energy requirements (p < 0.001). aDBS was also more effective than no stimulation and random intermittent stimulation.
BCI-controlled DBS is tractable and can be more efficient and efficacious than conventional continuous neuromodulation for PD. Ann Neurol 2013.
Background:
The dorso-lateral part of the subthalamic nucleus (STN) is considered as the usual target of deep brain stimulation for Parkinson's disease. Nevertheless, the exact anatomical location of the electrode contacts used for chronic stimulation is still a matter of debate. The aim of this study was to perform a systematic review of the existing literature on this issue.
Method:
We searched for studies on the anatomical location of active contacts published until December 2012.
Results:
We identified 13 studies, published between 2002 and 2010, including 260 patients and 466 electrodes. One hundred and sixty-four active contacts (35 %) were identified within the STN, 117 (25 %) at the interface between STN and the surrounding structures, 184 (40 %) above the STN and one within the substantia nigra. We observed great discrepancies between the different series. The contra-lateral improvement was between 37 and 78.5 % for contacts located within the STN, between 48.6 and 73 % outside the STN, between 65.3 and 66 % at the interface. The authors report no clear correlation between anatomical location and stimulation parameters.
Conclusions:
Post-operative analysis of the anatomical location of active contacts is difficult, and all the methods used are debatable. The relationship between the anatomical location of active contacts and the clinical effectiveness of stimulation is unclear. It would be necessary to take into account the volume of the electrode contacts and the diffusion of the stimulation. We can nevertheless assume that the interface between dorso-lateral STN, zona incerta and Forel's fields could be directly involved in the effects of stimulation.
The identification of a hyperdirect cortico-subthalamic nucleus connection highlighted the important role of the subthalamic nucleus (STN) in regulating behavior. However, this pathway was shown primarily from motor areas. Hyperdirect pathways associated with cognitive and motivational cortical regions are particularly relevant given recent data from deep brain stimulation, both for neurologic and psychiatric disorders. Our experiments were designed to demonstrate the existence and organization of prefrontal-STN projections, help delineate the “limbic” STN, and determine whether convergence between cortico-STN fibers from functionally diverse cortical areas exists in the STN. We injected anterograde tracers in the ventromedial prefrontal, orbitofrontal, anterior cingulate, and dorsal prefrontal cortices of Macaca nemestrina and Macaca fascicularis to analyze the organization of terminals and passing fibers in the STN.
Results show a topographically organized prefrontal hyperdirect pathway in primates. Limbic areas project to the medial tip of the nucleus, straddling its border and extending into the lateral hypothalamus. Associative areas project to the medial half, motor areas to the lateral half. Limbic projections terminated primarily rostrally and motor projections more caudally. The extension of limbic projections into the lateral hypothalamus, suggests that this region be included in the STN. A high degree of convergence exists between projections from functionally diverse cortical areas, creating potentially important interfaces between terminal fields. Taken together, the results provide an anatomical substrate to extend the role of the hyperdirect pathway in models of basal ganglia function, and new keys for understanding deep brain stimulation effects on cognitive and motivational aspects of behavior.
Subthalamic stimulation reduces motor disability and improves quality of life in patients with advanced Parkinson's disease who have severe levodopa-induced motor complications. We hypothesized that neurostimulation would be beneficial at an earlier stage of Parkinson's disease.
In this 2-year trial, we randomly assigned 251 patients with Parkinson's disease and early motor complications (mean age, 52 years; mean duration of disease, 7.5 years) to undergo neurostimulation plus medical therapy or medical therapy alone. The primary end point was quality of life, as assessed with the use of the Parkinson's Disease Questionnaire (PDQ-39) summary index (with scores ranging from 0 to 100 and higher scores indicating worse function). Major secondary outcomes included parkinsonian motor disability, activities of daily living, levodopa-induced motor complications (as assessed with the use of the Unified Parkinson's Disease Rating Scale, parts III, II, and IV, respectively), and time with good mobility and no dyskinesia.
For the primary outcome of quality of life, the mean score for the neurostimulation group improved by 7.8 points, and that for the medical-therapy group worsened by 0.2 points (between-group difference in mean change from baseline to 2 years, 8.0 points; P=0.002). Neurostimulation was superior to medical therapy with respect to motor disability (P<0.001), activities of daily living (P<0.001), levodopa-induced motor complications (P<0.001), and time with good mobility and no dyskinesia (P=0.01). Serious adverse events occurred in 54.8% of the patients in the neurostimulation group and in 44.1% of those in the medical-therapy group. Serious adverse events related to surgical implantation or the neurostimulation device occurred in 17.7% of patients. An expert panel confirmed that medical therapy was consistent with practice guidelines for 96.8% of the patients in the neurostimulation group and for 94.5% of those in the medical-therapy group.
Subthalamic stimulation was superior to medical therapy in patients with Parkinson's disease and early motor complications. (Funded by the German Ministry of Research and others; EARLYSTIM ClinicalTrials.gov number, NCT00354133.).
Background and purpose:
Neurosurgical interventions of the thalamus rely on transferring stereotactic coordinates from an atlas onto the patient's MR brain images. We propose a prototype application for performing thalamus target map individualization by fusing patient-specific thalamus geometric information and diffusion tensor tractography.
Materials and methods:
Previously, our workgroup developed a thalamus atlas by fusing anatomic information from 7 histologically processed thalami. Thalamocortical connectivity maps were generated from DTI scans of 40 subjects by using a previously described procedure and were mapped to a standard neuroimaging space. These data were merged into a statistical shape model describing the morphologic variability of the thalamic outline, nuclei, and connectivity landmarks. This model was used to deform the atlas to individual images. Postmortem MR imaging scans were used to quantify the accuracy of nuclei predictions.
Results:
Reliable tractography-based markers were located in the ventral lateral thalamus, with the somatosensory connections coinciding with the VPLa and VPLp nuclei; and motor/premotor connections, with the VLpv and VLa nuclei. Prediction accuracy of thalamus outlines was higher with the SSM approach than the ACPC alignment of data (0.56 mm versus 1.24; Dice overlap: 0.87 versus 0.7); for individual nuclei: 0.65 mm, Dice: 0.63 (SSM); 1.24 mm, Dice: 0.4 (ACPC).
Conclusions:
Previous studies have already applied DTI to the thalamus. As a further step in this direction, we demonstrate a hybrid approach by using statistical shape models, which have the potential to cope with intersubject variations in individual thalamus geometry.
Based on the Fourier transform relation between diffusion magnetic resonance (MR) signals and the underlying diffusion displacement, a new relation is derived to estimate the spin distribution function (SDF) directly from diffusion MR signals. This relation leads to an imaging method called generalized q -sampling imaging (GQI), which can obtain the SDF from the shell sampling scheme used in q -ball imaging (QBI) or the grid sampling scheme used in diffusion spectrum imaging (DSI). The accuracy of GQI was evaluated by a simulation study and an in vivo experiment in comparison with QBI and DSI. The simulation results showed that the accuracy of GQI was comparable to that of QBI and DSI. The simulation study of GQI also showed that an anisotropy index, named quantitative anisotropy, was correlated with the volume fraction of the resolved fiber component. The in vivo images of GQI demonstrated that SDF patterns were similar to the ODFs reconstructed by QBI or DSI. The tractography generated from GQI was also similar to those generated from QBI and DSI. In conclusion, the proposed GQI method can be applied to grid or shell sampling schemes and can provide directional and quantitative information about the crossing fibers.
The University of Iowa’s Psychiatric Iowa Neuroimaging Consortium (PINC) has developed a program for mutual information registration of 3D brain imaging data using ITK classes, called BRAINSFit. We have written a helper class, itk::MultiModal3DMutualRegistrationHelper to simplify implementation and testing of different transform representations and optimizers. We have added a transform meeting the ITK standard, itk::ScaleVersor3DTransform. BRAINSFit is based on the registration examples from ITK, but adds new features, including the ability to employ different transform representations and optimization functions. Our goal was to determine best practices for registering 3D rigid multimodal MRI of the human brain. A version of the current program is employed here at PINC daily for automated processing of acquired brain images.
This project is managed on the NITRC site. http://www.nitrc.org/projects/multimodereg/
On the NITRC website, you can acquire the latest source code via SVN, or by downloading a compressed file which is generated every night. Binary versions are also available.
Although progress has been made in understanding the optimal anatomic structures as target areas for DBS, little effort has been put into modeling and predicting electromagnetic field properties of activated DBS electrodes and understanding their interactions with the adjacent tissue. Currently, DBS is performed with the patient awake to assess the effectiveness and the side effect spectrum of stimulation. This study was designed to create a robust and rather simple numeric and visual tool that provides sufficient and practical relevant information to visualize the patient's individual VAT.
Multivariate polynomial fitting of previously obtained data from a finite-element model, based on a similar DBS system, was used. The model estimates VAT as a first-approximation sphere around the active DBS contact, using stimulation voltages and individual tissue-electrode impedances. Validation uses data from 2 patients with PD by MR imaging, DTI, fiber tractography, and postoperative CT data.
Our model can predict VAT for impedances between 500 and 2000 Ω with stimulation voltages up to 10 V. It is based on assumptions for monopolar DBS. Evaluation of 2 DBS cases showed a convincing correspondence between predicted VAT and neurologic (side) effects (internal capsule activation).
Stimulation effects during DBS can be readily explained with this simple VAT model. Its implementation in daily clinical routine might help in understanding the types of tissues activated during DBS. This technique might have the potential to facilitate DBS implantations with the patient under general anesthesia while yielding acceptable clinical effectiveness.
Using conventional MRI the subthalamic nucleus (STN) is not clearly defined. Our objective was to define the anatomy of the STN using 9.4 T MRI of post mortem tissue with histological validation. Spin-echo (SE) and 3D gradient-echo (GE) images were obtained at 9.4 T in 8 post mortem tissue blocks and compared directly with corresponding histological slides prepared with Luxol Fast Blue/Cresyl Violet (LFB/CV) in 4 cases and Perl stain in 3. The variability of the STN anatomy was studied using internal reference points. The anatomy of the STN and surrounding structures was demonstrated in all three anatomical planes using 9.4 T MR images in concordance with LFB/CV stained histological sections. Signal hypointensity was seen in 6/8 cases in the anterior and medial STN that corresponded with regions of more intense Perl staining. There was significant variability in the volume, shape and location of the borders of the STN. Using 9.4 T MRI, the internal signal characteristics and borders of the STN are clearly defined and significant anatomical variability is apparent. Direct visualisation of the STN is possible using high field MRI and this is particularly relevant, given its anatomical variability, for planning deep brain stimulation.
The basal ganglia receive cortical inputs through two main stations - the striatum and the subthalamic nucleus (STN). The information flowing along the corticostriatal system is transmitted to the basal ganglia circuitry via the "direct and indirect" striatofugal pathways, while information that flows through the STN is transmitted along the so-called "hyperdirect" pathway. The functional significance of this dual entry system is not clear. Although the corticostriatal system has been thoroughly characterized anatomically and electrophysiologically, such is not the case for the corticosubthalamic system. In order to provide further insights into the intricacy of this complex anatomical organization, this review examines and compares the anatomical and functional organization of the corticostriatal and corticosubthalamic systems, and highlights some key issues that must be addressed to better understand the mechanisms by which these two neural systems may interact to regulate basal ganglia functions and dysfunctions.
In neurosurgical literature, findings such as deep brain stimulation (DBS) electrode positions are conventionally reported in relation to the anterior and posterior commissures of the individual patient (AC/PC coordinates). However, the neuroimaging literature including neuroanatomical atlases, activation patterns, and brain connectivity maps has converged on a different population-based standard (MNI coordinates). Ideally, one could relate these two literatures by directly transforming MRIs from neurosurgical patients into MNI space. However obtaining these patient MRIs can prove difficult or impossible, especially for older studies or those with hundreds of patients. Here, we introduce a methodology for mapping an AC/PC coordinate (such as a DBS electrode position) to MNI space without the need for MRI scans from the patients themselves. We validate our approach using a cohort of DBS patients in which MRIs are available, and test whether several variations on our approach provide added benefit. We then use our approach to convert previously reported DBS electrode coordinates from eight different neurological and psychiatric diseases into MNI space. Finally, we demonstrate the value of such a conversion using the DBS target for essential tremor as an example, relating the site of the active DBS contact to different MNI atlases as well as anatomical and functional connectomes in MNI space.
Focal brain injury can sometimes lead to bizarre symptoms, such as the delusion that a family member has been replaced by an imposter (Capgras syndrome). How a single brain lesion could cause such a complex disorder is unclear, leading many to speculate that concurrent delirium, psychiatric disease, dementia, or a second lesion is required. Here we instead propose that Capgras and other delusional misidentification syndromes arise from single lesions at unique locations within the human brain connectome. This hypothesis is motivated by evidence that symptoms emerge from sites functionally connected to a lesion location, not just the lesion location itself. First, 17 cases of lesion-induced delusional misidentifications were identified and lesion locations were mapped to a common brain atlas. Second, lesion network mapping was used to identify brain regions functionally connected to the lesion locations. Third, regions involved in familiarity perception and belief evaluation, two processes thought to be abnormal in delusional misidentifications, were identified using meta-analyses of previous functional magnetic resonance imaging studies. We found that all 17 lesion locations were functionally connected to the left retrosplenial cortex, the region most activated in functional magnetic resonance imaging studies of familiarity. Similarly, 16 of 17 lesion locations were functionally connected to the right frontal cortex, the region most activated in functional magnetic resonance imaging studies of expectation violation, a component of belief evaluation. This connectivity pattern was highly specific for delusional misidentifications compared to four other lesion-induced neurological syndromes (P < 0.0001). Finally, 15 lesions causing other types of delusions were connected to expectation violation (P < 0.0001) but not familiarity regions, demonstrating specificity for delusion content. Our results provide potential neuroanatomical correlates for impaired familiarity perception and belief evaluation in patients with delusional misidentifications. More generally, we demonstrate a mechanism by which a single lesion can cause a complex neuropsychiatric syndrome based on that lesion's unique pattern of functional connectivity, without the need for pre-existing or hidden pathology.
Objective:
To characterize a brainstem location specific to coma-causing lesions, and its functional connectivity network.
Methods:
We compared 12 coma-causing brainstem lesions to 24 control brainstem lesions using voxel-based lesion-symptom mapping in a case-control design to identify a site significantly associated with coma. We next used resting-state functional connectivity from a healthy cohort to identify a network of regions functionally connected to this brainstem site. We further investigated the cortical regions of this network by comparing their spatial topography to that of known networks and by evaluating their functional connectivity in patients with disorders of consciousness.
Results:
A small region in the rostral dorsolateral pontine tegmentum was significantly associated with coma-causing lesions. In healthy adults, this brainstem site was functionally connected to the ventral anterior insula (AI) and pregenual anterior cingulate cortex (pACC). These cortical areas aligned poorly with previously defined resting-state networks, better matching the distribution of von Economo neurons. Finally, connectivity between the AI and pACC was disrupted in patients with disorders of consciousness, and to a greater degree than other brain networks.
Conclusions:
Injury to a small region in the pontine tegmentum is significantly associated with coma. This brainstem site is functionally connected to 2 cortical regions, the AI and pACC, which become disconnected in disorders of consciousness. This network of brain regions may have a role in the maintenance of human consciousness.
Deep brain stimulation is a powerful clinical method for movement disorders that no longer respond satisfactorily to pharmacological management, but its progress has been hampered by stagnation in technological procedure solutions and device development. Recently, the combined research efforts of bioengineers, neuroscientists, and clinicians have helped to better understand the mechanisms of deep brain stimulation, and solutions for the translational roadblock are emerging. Here, we define the needs for methodological advances in deep brain stimulation from a neurophysiological perspective and describe technological solutions that are currently evaluated for near-term clinical application. © 2016 International Parkinson and Movement Disorder Society.
Objective:
To determine whether neuroanatomically heterogeneous strokes causing hemichorea-hemiballismus localize to a common functional network.
Methods:
We identified 29 cases of lesion-induced hemichorea-hemiballismus from the literature and mapped each lesion volume onto a reference brain. Using a recently validated technique termed lesion network mapping, we tested whether these lesions belonged to the same functional network. To accomplish this, the network of brain regions functionally connected to each lesion was identified using a connectome dataset from healthy participants. Network maps were overlapped to identify any region functionally connected to our set of lesions. Specificity was evaluated using a case-control design; control cohorts included a group of similar lesions randomized to different brain locations and a second group of lesions causing a separate movement disorder, asterixis. Reproducibility was evaluated using an independent cohort of 10 additional hemichorea-hemiballismus cases.
Results:
Lesions showed heterogeneity in anatomical location, consistent with prior reports. However, at least 90% of these lesions showed network overlap in the posterolateral putamen. This result was specific to lesions causing hemichorea-hemiballismus and reproducible in an independent cohort. The putaminal overlap site was itself connected to a broader motor network that predicted the distribution of lesions causing hemichorea-hemiballismus.
Conclusions:
Strokes causing hemichorea-hemiballismus, while anatomically heterogeneous, localize to a common functional network. Specifically, lesions occur in regions functionally connected to the posterolateral putamen, a region previously implicated in hyperkinetic movement disorders. Lesion network mapping may be useful in identifying the neuroanatomical substrates of heterogeneous lesion-based disorders.
In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically,Statistical Parametric Mappingprovides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. * An essential reference and companion for users of the SPM software * Provides a complete description of the concepts and procedures entailed by the analysis of brain images * Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data * Stands as a compendium of all the advances in neuroimaging data analysis over the past decade * Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes * Structured treatment of data analysis issues that links different modalities and models * Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible.
The analysis of the structural architecture of the human brain in terms of connectivity between its sub-regions has provided profound insights into its underlying functional organization and has coined the concept of the "connectome", a structural description of the elements forming the human brain and the connections among them. Here, as a proof of concept, we introduce a novel group connectome in standard space based on a large sample of 169 subjects from the Enhanced Nathan Kline Institute - Rockland Sample (eNKI-RS). Whole brain structural connectomes of each subject were estimated with a global tracking approach, and the resulting fiber tracts were warped into standard stereotactic (MNI) space using DARTEL. Employing this group connectome, the results of published tracking studies (i.e., the JHU white matter and Oxford thalamic connectivity atlas) could be largely reproduced directly within MNI space. As a second experiment, a study that examined structural connectivity between regions of a functional network, namely the default mode network, was reproduced. Voxel-wise structural centrality was then calculated and compared to prior literature findings. Furthermore, including additional resting-state fMRI data from the same subjects, structural and functional connectivity matrices between approximately forty thousand nodes of the brain were calculated. This was done to estimate structure-function agreement indices of voxel-wise whole brain connectivity. Taken together, the combination of a novel whole brain fiber tracking approach and an advanced normalization method led to a group connectome that allowed (at least heuristically) to perform fiber tracking directly within MNI space. Hence, it may be used for various purposes such as the analysis of structural connectivity and modeling experiments that aim at studying the structure-function relationship of the human connectome. Moreover, it may even represent a first step towards a standard DTI template of the human brain in stereotactic space. The standardized group connectome might thus be a promising new resource to better understand and further analyze the anatomical architecture of the human brain on a population level.
This paper presents a virtual model of patients with Deep Brain Stimulation implants. The model is based on Human Connectome and 7 Tesla Magnetic Resonance Imaging (MRI) data. We envision that the proposed virtual patient simulator will enable radio frequency power dosimetry on patients with deep brain stimulation implants undergoing MRI. Results from the proposed virtual patient study may facilitate the use of clinical MRI instead of computed tomography scans. The virtual patient will be flexible and morphable to relate to patient-specific neurological and psychiatric conditions such as Obsessive Compulsive Disorder, which benefit from deep brain stimulation.
Objective: We developed a novel method to map behavioral effects of deep brain stimulation (DBS) across a 3D brain region and to assign statistical significance after stringent Type I error correction. This method was applied to behavioral changes in Parkinson disease (PD) induced by subthalamic nucleus (STN) DBS to determine whether these responses depended on anatomical location of DBS. Method: Fifty-one PD participants with STN DBS were evaluated off medication, with DBS off and during unilateral STN DBS with clinically optimized settings. Dependent variables included DBS-induced changes in Unified Parkinson Disease Rating Scale (UPDRS) subscores, kinematic measures of bradykinesia and rigidity, working memory, response inhibition, mood, anxiety, and akathisia. Weighted t-tests at each voxel produced p images showing where DBS most significantly affected each dependent variable based on outcomes of participants with nearby DBS. Finally, a permutation test computed the probability that this p image indicated significantly different responses based on stimulation site. Results: Most motor variables improved with DBS anywhere in the STN region, but several motor, cognitive and affective responses significantly depended on precise location stimulated, with peak p values in superior STN/zona incerta (quantified bradykinesia), dorsal STN (mood, anxiety), and inferior STN/substantia nigra (UPDRS tremor, working memory). Interpretation: Our method identified DBS-induced behavioral changes that depended significantly on DBS site. These results do not support complete functional segregation within STN, since movement improved with DBS throughout, and mood improved with dorsal STN DBS. Rather, findings support functional convergence of motor, cognitive and limbic information in STN.
ANN NEUROL 2014. © 2014 American Neurological Association.
The subthalamic nucleus (STN) is an important node of the cortico-basal ganglia network and the main target of deep brain stimulation (DBS) in Parkinson’s disease. Histological studies have revealed an inhomogeneous iron distribution within the STN, which has been related to putative sub- divisions within this nucleus. Here, we investigate the iron distribution in more detail using quantita- tive susceptibility mapping (QSM), a novel magnetic resonance imaging (MRI) contrast mechanism. QSM allows for detailed assessment of iron content in both in vivo and postmortem tissue. Twelve human participants and 7 postmortem brain samples containing the STN were scanned using ultra- high field 7 Tesla (T) MRI. Iron concentrations were found to be higher in the medial-inferior tip of the STN. Using quantitative methods we show that the increase of iron concentration towards the medial- inferior tip is of a gradual rather than a discrete nature.
Perhaps more than any other “-omics” endeavor, the accuracy and level of detail obtained from mapping the major connection pathways in the living human brain with diffusion MRI depend on the capabilities of the imaging technology used. The current tools are remarkable; allowing the formation of an “image” of the water diffusion probability distribution in regions of complex crossing fibers at each of half a million voxels in the brain. Nonetheless our ability to map the connection pathways is limited by the image sensitivity and resolution, and also the contrast and resolution in encoding of the diffusion probability distribution.
High-frequency stimulation of the subthalamic nucleus (STN-HFS) is highly effective in treating motor symptoms in Parkinson's disease (PD) and medication side effects as well as in improving quality of life. Despite preoperative screening for patients as eligible candidates for this treatment, electrode position may furthermore influence treatment quality. Here, we investigated the relationship between the anatomical site of stimulation within the MRI-defined STN and the outcome of PD patients after STN-HFS. In 30 PD patients with bilateral STN stimulation, we retrospectively defined the boundaries of the STN within the axial target plane of the stereotactic T2-weighted MRI and determined the position of the active electrode contact in relation to the border of the STN. The position of the active contact within the STN was the only variable to predict the outcome of STN stimulation. In contrast, covariates such as age, disease duration, symptom severity, and response to levodopa had no effect. The lateral position of the stimulation contact within the STN led to significantly better clinical improvement, lower stimulation parameters, and less need for postoperative dopaminergic medication. The outcome of patients with stimulation contacts within the medial region of the STN was significantly worse. Precise targeting of the lateral region of the STN is essential for achieving sufficient stimulation efficacy. Preoperative T2-weighted MRI might be a useful component of the targeting procedure to improve the outcome of PD patients.
Studies of mechanisms in the brain that allow complicated things to happen in a coordinated fashion have produced some of the most spectacular discoveries in neuroscience. This book provides support for the idea that spontaneous neuron activity, far from being mere noise, is actually the source of our cognitive abilities. It looks at the co-evolution of structure and function in the mammalian brain, illustrating how self-emerged oscillatory timing is the brains fundamental organizer of neuronal information. The small world-like connectivity of the cerebral cortex allows for global computation on multiple spatial and temporal scales. The perpetual interactions among the multiple network oscillators keep cortical systems in a highly sensitive metastable state and provide energy-efficient synchronizing mechanisms via weak links. In a sequence of cycles, this book travels from the physics of oscillations through neuronal assembly organization to complex cognitive processing and memory storage.
The subthalamic nucleus (STN) is a small, glutamatergic nucleus situated in the diencephalon. A critical component of normal motor function, it has become a key target for deep brain stimulation in the treatment of Parkinson's disease. Animal studies have demonstrated the existence of three functional sub-zones but these have never been shown conclusively in humans. In this work, a data driven method with diffusion weighted imaging demonstrated that three distinct clusters exist within the human STN based on brain connectivity profiles. The STN was successfully sub-parcellated into these regions, demonstrating good correspondence with that described in the animal literature. The local connectivity of each sub-region supported the hypothesis of bilateral limbic, associative and motor regions occupying the anterior, mid and posterior portions of the nucleus respectively. This study is the first to achieve in-vivo, non-invasive anatomical parcellation of the human STN into three anatomical zones within normal diagnostic scan times, which has important future implications for deep brain stimulation surgery.
We report on surface-based analyses that enhance our understanding of human cortical organization, including its convolutions and its parcellation into many distinct areas. The surface area of human neocortex averages 973 cm(2) per hemisphere, based on cortical midthickness surfaces of 2 cohorts of subjects. We implemented a method to register individual subjects to a hybrid version of the FreeSurfer "fsaverage" atlas whose left and right hemispheres are in precise geographic correspondence. Cortical folding patterns in the resultant population-average "fs_LR" midthickness surfaces are remarkably similar in the left and right hemispheres, even in regions showing significant asymmetry in 3D position. Both hemispheres are equal in average surface area, but hotspots of surface area asymmetry are present in the Sylvian Fissure and elsewhere, together with a broad pattern of asymmetries that are significant though small in magnitude. Multiple cortical parcellation schemes registered to the human atlas provide valuable reference data sets for comparisons with other studies. Identified cortical areas vary in size by more than 2 orders of magnitude. The total number of human neocortical areas is estimated to be ∼150 to 200 areas per hemisphere, which is modestly larger than a recent estimate for the macaque.
Histological studies have shown a relatively high iron concentration in the subthalamic nucleus (STN). T2- and T2*-weighted sequences have previously been used to visualize the STN in vivo. The phase information of gradient-echo images reflects the magnetic tissue properties more directly, e.g., iron is more paramagnetic than water. Unfortunately, phase images suffer from non-local effects and orientation dependency. The goal of this study is to delineate the STN more precisely using susceptibility maps, calculated from phase images, which directly index magnetic tissue properties while removing the non-local effects and orientation dependency. Use of 7T MRI enables high spatial resolution with good signal to noise ratio (SNR). Eight healthy subjects were scanned at 7T using a high-resolution 3D gradient-echo sequence. Susceptibility maps were calculated from phase data using a thresholding Fourier approach and a regularization approach using spatial priors. The susceptibility maps clearly distinguish the STN from the adjacent substantia nigra (SN). Their susceptibilities are quantitatively different (0.06 and 0.1 ppm for the STN and SN, respectively). These maps allowed the STN, SN, and the red nucleus to be manually segmented, thus providing 3D visualization of their boundaries. In sum, the STN can be more clearly distinguished from adjacent structures in susceptibility maps than in T2*-weighted images or phase images. Hum Brain Mapp, 2011. © 2011 Wiley-Liss, Inc.