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Tuber Locations Associated with Infantile Spasms Map to a Common Brain Network
Abstract
Objective
Approximately 50% of patients with Tuberous Sclerosis Complex develop infantile spasms, a sudden‐onset epilepsy syndrome associated with poor neurological outcomes. While an increased burden of tubers confers an elevated risk of infantile spasms, it remains unknown whether some tuber locations confer higher risk than others. Here, we test whether tuber location and connectivity are associated with infantile spasms.
Methods
We segmented tubers from 123 children with (n=74) and without (n=49) infantile spasms from a prospective observational cohort. We used voxel‐wise lesion symptom mapping to test for an association between spasms and tuber location. We then used lesion network mapping to test for an association between spasms and connectivity with tuber locations. Finally, we tested the discriminability of identified associations with logistic regression and cross validation as well as statistical mediation.
Results
Tuber locations associated with infantile spasms were heterogenous, and no single location was significantly associated with spasms. However, >95% of tuber locations associated with spasms were functionally connected to the globus pallidi and cerebellar vermis. These connections were specific compared to tubers in patients without spasms. Logistic regression found that globus pallidus connectivity was a stronger predictor of spasms (OR 1.96, 95%CI [1.10, 3.50], p=0.02) than tuber burden (OR 1.65, 95%CI [0.90, 3.04], p=0.11), with a mean ROC area under the curve of 0.73 (+/‐0.1) during repeated cross validation.
Interpretation
Connectivity between tuber locations and the bilateral globus pallidus is associated with infantile spasms. Our findings lend insight into spasm pathophysiology and may identify patients at risk.
This article is protected by copyright. All rights reserved.
... 7,8 Lesion network mapping (LNM) is a new technique that accounts for lesion connectivity and can help link rare lesion-induced syndromes to neuroanatomy. [11][12][13][14][15][16][17][18][19][20] The technique compares lesion locations to normalized resting state functional connectivity maps to determine group level differences. 20,21 Both blindsight patients and blindsight-negative controls have a brain injury causing conscious vision loss, but only blindsight patients have unconscious visual perception. ...
... Lesion network mapping is a new, but extensively validated technique which compares structural lesion locations to normalized resting state functional connectivity maps to identify brain networks disrupted by a given lesion. [11][12][13][14][15][16][17][18][19][20] In brief, resting state functional connectivity between each lesion location and all other brain voxels was computed using a large connectome database from healthy young individuals (n=1000, mean age 21.3 years, range 18-35 years, 42.7% male) 30 . Functional connectivity results were combined across the 1000 subjects using a random effects analysis, producing a single "lesion network map" for each patient. ...
... This result is consistent with recent We show a group-level difference as in prior lesion network mapping work 20, 21 but it is worth discussing how to interpret this group difference. While lesion network mapping has been most extensively used to evaluate lesions that cause a new symptom13,15,16,18,20 or loss of function19, 21 , ...
Objective
Blindsight is a disorder where brain injury causes loss of conscious but not unconscious visual perception. Prior studies have produced conflicting results regarding the neuroanatomical pathways involved in this unconscious perception.
Methods
We performed a systematic literature search to identify lesion locations causing visual field loss in patients with blindsight (n=34) and patients without blindsight (n=35). Resting state functional connectivity between each lesion location and all other brain voxels was computed using a large connectome database (n=1000). Connections significantly associated with blindsight (versus no blindsight) were identified.
Results
Functional connectivity between lesion locations and the ipsilesional medial pulvinar was significantly associated with blindsight (FWE p=0.029). No significant connectivity differences were found to other brain regions previously implicated in blindsight. This finding was independent of methods (e.g. flipping lesions to the left or right) and stimulus type (moving versus static).
Interpretation
Connectivity to the ipsilesional medial pulvinar best differentiates lesion locations associated with blindsight versus those without blindsight. Our results align with recent data from animal models and provide insight into the neuroanatomical substrate of unconscious visual abilities in patients.
This article is protected by copyright. All rights reserved.
... However, there is evidence suggesting that diffuse alterations to functional connectivity (FC) may be a key characteristic of ES. Supporting this hypothesis is a recent lesion mapping study in children with TSC, which found that strong negative FC to bilateral globi pallidi and cerebellar vermi predicts ES rather than any specific tuber location 7 . Two scalp EEG studies have provided separate evidence for ES and developmental delay being a state of excessive global connectivity 5,12 . ...
... However, this is not the rule, and in this study ES were equally seen across both focal and complex EZ organisations. Our findings, together with recent studies 5,7,12 , support the concept that ES is associated with a network characterised by increased cortical synchrony. This network dynamic may be largely driven by widespread connectivity and anatomical alterations, rather than tuber epileptogenicity. ...
Objective:
Epileptic Spasms (ES) are common in Tuberous Sclerosis Complex (TSC). However the underlying network alterations and relationship with epileptogenic tubers are poorly understood. We examined interictal functional connectivity (FC) using stereo-EEG (SEEG) in patients with TSC to investigate the relationship between tubers, epileptogenicity and ES.
Methods:
We analysed 18 patients with TSC who underwent SEEG (mean age 11.5 years). The dominant tuber (DT) was defined as the most epileptogenic tuber using the Epileptogenicity Index. Epileptogenic Zone (EZ) organisation was quantitatively separated into focal (isolated DT) and complex (all other patterns). Using a 20 minute interictal recording, FC was estimated with non-linear regression, h2 . We calculated i) intrazone FC within all sampled tubers and normal appearing cortical zones respectively, and ii) interzone FC involving connections between DT, other tubers and normal cortex. The relationship between FC and i) presence of ES as a current seizure type at the time of SEEG, ii) EZ organisation, iii) epileptogenicity was analysed using a mixed generalized linear model. Spike rate and distance between zones were considered in the model as covariates RESULTS: Six patients had ES as a current seizure type at time of SEEG. ES patients had a great number of tubers with FLAIR hypointense centre (p < 0.001) and none had TSC1 mutations. The presence of ES was independently associated with increased FC within both intrazone (p = 0.033) and interzone (p = 0.011) networks. Post-hoc analyses identified that increased FC was associated with ES across tuber and non-tuber networks. EZ organisation and epileptogenicity biomarkers were not associated with FC.
Significance:
Increased cortical synchrony amongst both tuber and non-tuber networks is characteristic of patients with ES and independent of both EZ organisation and tuber epileptogenicity. This further supports the prospect of FC biomarkers aiding treatment paradigms in TSC.
... In the recent work by Cohen et al, 6 the authors applied a novel and exciting method of "lesion mapping" to a large cohort of children with and without ES to identify the networks underlying the development of ES. Cohen's work extends the functional connectivity-based lesion mapping technique described by Boes et al. 7 Specifically, Boes et al found that particular functional deficits can be better predicted by an individual lesion's functional connectivity than by its specific location in the brain. ...
... Cohen et al. 6 have applied this concept of lesion network mapping to TSC using neuroimaging data gathered for the TSC Autism Centre of Excellence Network (TACERN). TACERN is a multicentre prospective study in which patients were enrolled in the first year of life and followed longitudinally through 36 months. ...
... The copyright holder for this preprint this version posted February 22, 2023. ; https://doi.org/10.1101/2023.02.14.23285901 doi: medRxiv preprint connectome in DBS and other pediatric research applications (for instance, mapping networks associated with specific lesions causing childhood neurological diseases) 59 . Furthermore, whole brain mapping of DBS therapeutic-effects allows for building a common network that can be targeted by invasive and non-invasive neuromodulatory techniques 60 . ...
Introduction
Deep brain stimulation (DBS) is an established treatment in patients with pharmaco-resistant neurological disorders of different ages. Surgical targeting and postoperative programming of DBS depend on the spatial location of the stimulating electrodes in relation to the surrounding anatomical structures and on electrode connectivity to a specific distributed pattern of brain networks. Such information is usually collected using group-level analysis which relies on the availability normative imaging-resources (atlases and connectomes). To this end, analyzing DBS data of children with debilitating neurological disorders like dystonia would make benefit from such resources, especially given the developmental differences between adults and children neuroimaging data. We assembled pediatric, normative neuroimaging-resources from open-access neuroimaging datasets and illustrated their utility on a cohort of children with dystonia treated with pallidal DBS. We aimed to derive a local pallidal sweetspot and explore a connectivity fingerprint associated with pallidal stimulation to exemplify the utility of the assembled imaging resources.
Methods
A pediatric average brain template was implemented and used to localize DBS electrodes of twenty patients of the GEPESTIM registry cohort. Next, a pediatric subcortical atlas was also employed to highlight anatomical structures of interest. Local pallidal sweetspot was modeled and its degree of overlap with stimulation volumes was calculated as a correlate of individual clinical outcome. Additionally, a pediatric functional connectome of neurotypical subjects was built to allow network-based analyses and decipher a connectivity fingerprint responsible for clinical improvement in our cohort.
Results
We successfully implemented a pediatric neuroimaging dataset that will be made available to public use as a tool for DBS-analyses. Overlap of stimulation volumes with the identified DBS-sweetspot model correlated significantly with improvement on a local spatial level (R = 0.46, permuted p = 0.019). Functional connectivity fingerprint of DBS-outcome was determined as a network correlate of therapeutic pallidal stimulation in children with dystonia (R = 0.30, permuted p = 0.003).
Conclusions
Local sweetspot and distributed network models provide neuroanatomical substrates for DBS-associated clinical outcome in dystonia using pediatric neuroimaging surrogate data. The current implementation of pediatric neuroimaging dataset might help improving the practice of DBS-neuroimaging analyses in pediatric patients.
... TMS sites are more likely to relieve depression if they are functionally anticorrelated to the subgenual cingulate 72 . Similar approaches have now been used to map the causal neuroanatomy of movement disorders [86][87][88][89][90][91] , mood disorders 71,90,92-95 , anxiety-related disorders [96][97][98] , psychotic disorders 99-101 , disorders of consciousness [102][103][104] , and various other neuropsychiatric phenomena [105][106][107][108][109] . ...
Mapping human brain function is a long-standing goal of neuroscience that promises to inform the development of new treatments for brain disorders. Early maps of human brain function were based on locations of brain damage or brain stimulation that caused a functional change. Over time, this approach was largely replaced by technologies such as functional neuroimaging, which identify brain regions in which activity is correlated with behaviours or symptoms. Despite their advantages, these technologies reveal correlations, not causation. This creates challenges for interpreting the data generated from these tools and using them to develop treatments for brain disorders. A return to causal mapping of human brain function based on brain lesions and brain stimulation is underway. New approaches can combine these causal sources of information with modern neuroimaging and electrophysiology techniques to gain new insights into the functions of specific brain areas. In this Review, we provide a definition of causality for translational research, propose a continuum along which to assess the relative strength of causal information from human brain mapping studies and discuss recent advances in causal brain mapping and their relevance for developing treatments. In this Review, Siddiqi et al. examine causal approaches to mapping human brain function. They provide a definition of causality for translational research, propose a framework for assessing causality strength in brain mapping studies and cover advances in techniques and their use in developing treatments for brain disorders.
... As one example of how lesion network mapping may provide insight into neurodevelopmental symptoms, we recently found that connectivity between cortical tubers and the subcortical globi pallidi is a strong predictor of infantile spasms, a sudden-onset epileptic syndrome that affects up to 55% of children with TSC and is strongly associated with poor neurological outcome if not treated rapidly [82][83][84][85]. This study sought to predict an epilepsy syndrome and did not directly focus on developmental outcomes. ...
A wide variety of model systems and experimental techniques can provide insight into the structure and function of the human brain in typical development and in neurodevelopmental disorders. Unfortunately, this work, whether based on manipulation of animal models or observational and correlational methods in humans, has a high attrition rate in translating scientific discovery into practicable treatments and therapies for neurodevelopmental disorders.
With new computational and neuromodulatory approaches to interrogating brain networks, opportunities exist for “bedside-to bedside-translation” with a potentially shorter path to therapeutic options. Specifically, methods like lesion network mapping can identify brain networks involved in the generation of complex symptomatology, both from acute onset lesion-related symptoms and from focal developmental anomalies. Traditional neuroimaging can examine the generalizability of these findings to idiopathic populations, while non-invasive neuromodulation techniques such as transcranial magnetic stimulation provide the ability to do targeted activation or inhibition of these specific brain regions and networks. In parallel, real-time functional MRI neurofeedback also allow for endogenous neuromodulation of specific targets that may be out of reach for transcranial exogenous methods.
Discovery of novel neuroanatomical circuits for transdiagnostic symptoms and neuroimaging-based endophenotypes may now be feasible for neurodevelopmental disorders using data from cohorts with focal brain anomalies. These novel circuits, after validation in large-scale highly characterized research cohorts and tested prospectively using noninvasive neuromodulation and neurofeedback techniques, may represent a new pathway for symptom-based targeted therapy.
Background:
Emotion regulation has been linked to specific brain networks based on functional neuroimaging, but networks causally involved in emotion regulation remain unknown.
Methods:
We studied patients with focal brain damage (n=167) who completed the "managing emotion" subscale of the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), a measure of emotion regulation. First, we tested whether patients with lesions to an a priori network derived from functional neuroimaging showed impaired emotion regulation. Next, we leveraged lesion network mapping to derive a de novo brain network for emotion regulation. Finally, we used an independent lesion database (n=629) to test whether damage to this lesion-derived network would increase the risk of neuropsychiatric conditions associated with emotion regulation impairment.
Results:
First, patients with lesions intersecting the a priori emotion regulation network derived from functional neuroimaging showed impairments in the managing emotion subscale of the MSCEIT. Next, our de novo brain network for emotion regulation derived from lesion data was defined by functional connectivity (FC) to the left ventrolateral prefrontal cortex (vlPFC). Finally, lesions from the independent database associated with mania, criminality, and depression intersected this de novo brain network more than lesions associated with other disorders.
Conclusions:
The findings suggest that emotion regulation maps to a connected brain network centered on the left vlPFC. Lesion damage to part of this network is associated with reported difficulties in managing emotions and is related to increased likelihood of having one of several neuropsychiatric disorders.
Objective:
Tuberous Sclerosis Complex (TSC) is associated with focal brain "tubers" and a high incidence of autism spectrum disorder (ASD). The location of brain tubers associated with autism may provide insight into the neuroanatomical substrate of ASD symptoms.
Methods:
We delineated tuber locations for 115 TSC participants with ASD (n = 31) and without ASD (n = 84) from the Tuberous Sclerosis Complex Autism Center of Excellence Research Network. We tested for associations between ASD diagnosis and tuber burden within the whole brain, specific lobes, and at eight regions of interest derived from the ASD neuroimaging literature including the anterior cingulate, orbitofrontal and posterior parietal cortices, the inferior frontal and fusiform gyri, the superior temporal sulcus, the amygdala, and the supplemental motor area. Next, we performed an unbiased data-driven voxel-wise lesion symptom mapping (VLSM) analysis. Finally, we calculated the risk of ASD associated with positive findings from the above analyses.
Results:
There were no significant ASD-related differences in tuber burden across the whole-brain, within specific lobes, or within a priori regions derived from the ASD literature. However, using VLSM analysis we found that tubers involving the right fusiform face area (FFA) were associated with a 3.7-fold increased risk of developing ASD.
Interpretation:
While TSC is a rare cause of ASD, there is a strong association between tuber involvement of the right FFA and ASD diagnosis. This highlights a potentially causative mechanism for developing autism in TSC that may guide research into ASD symptoms more generally. This article is protected by copyright. All rights reserved.
Hintergrund und Ziele: Bei epilepsiechirurgischen Eingriffen besteht das Risiko für postoperative Defizite. Zur prächirurgischen Risikoabschätzung dient die Lokalisierung von einzelnen kognitiven Fähigkeiten im Gehirn. Für einige der höheren kognitiven Fähigkeiten ist noch nicht zweifelsfrei und klar erwiesen, ob sie eindeutig zu lokalisieren sind und an welcher Stelle sie sich befinden. In der vorliegenden Arbeit wurde die Methode des „voxel-based lesion behaviour mapping“ (VLBM) verwendet, um das Benennen als eine verbale und das Schätzen als eine nonverbale kognitive Fähigkeit bei Patientinnen und Patienten mit einem epilepsiechirurgischen Eingriff bei fokaler Epilepsie möglichst genau lokalisieren zu können. Methodik: Insgesamt wurden 107 Fälle mit epilepsiechirurgischem Eingriff des Epilepsiezentrums Erlangen mit entsprechender Bildgebung aus dem Zeitraum von 2012 bis 2020 eingeschlossen. Die meisten operativen Eingriffe erfolgten im rechten oder linken Temporallappen. Der Boston Naming Test (BNT) wurde in 97 Fällen durchgeführt, der Test zum kognitiven Schätzen (TKS) in 95. Die Tests fanden vor und nach der Operation statt. Für das Lesionmapping durchliefen die MRT-Daten verschiedene Schritte, welche eine Bildregistrierung, das Einzeichnen der Läsion sowie eine Segmentierung und Normalisierung beinhalteten. Im Anschluss erfolgte die statistische Analyse mittels NiiStat. Ergebnisse und Beobachtungen: Eine Verschlechterung im BNT war mit einem Läsionsdefekt von insgesamt 8617 Voxel vor allem im linken inferioren temporalen Bereich mit Ausbreitung nach anterior assoziiert. Im Rahmen der Analyse mit der Freedman-Lane Permutation konnte dies unter Berücksichtigung der Covariaten Alter und Geschlecht gezeigt werden. Es wurden keine signifikanten Voxel für eine Verschlechterung im TKS im Bereich des Temporallappens gefunden. In der Gruppe mit Testung im BNT lag zum Zeitpunkt der Operation im Mittel ein Alter von 38,9 Jahre vor, der Anteil von Frauen betrug 45,4%. Eine Operation am Temporallappen erfolgte links bei 43,3% und rechts bei 33,0%. Als Ätiologie war bei 33,0% unter anderem eine Hippocampussklerose bekannt. Bei den Patientinnen und Patienten mit einer Testung im TKS lagen vergleichbare Werte vor (Alter im Mittel 38,5 Jahre, 42% weiblich, Operation am Temporallappen links in 42,1% und rechts in 33,7%, Hippocampussklerose unter anderem bei 32,6%). Bei 39 von 95 Fällen zeigte sich im präoperativen Testergebnis eine Beeinträchtigung im TKS mit weniger als 11 von 16 Punkten, welche im Mittel nach der Operation (-1,6303) einen besseren z-Wert im Vergleich zum Messzeitpunkt vor der Operation (-2,3641) erzielten. Schlussfolgerungen und Diskussion: In dieser Arbeit wurde Lesionmapping an Patientinnen und Patienten mit epilepsiechirurgischen Eingriffen und dabei vornehmlich Temporallappenresektionen durchgeführt. Läsionen im linken Temporallappen gingen mit einer Verschlechterung im BNT einher. Dieses Ergebnis stimmt mit anderen Studien, welche bspw. mittels fMRT oder kortikaler Stimulation durchgeführt wurden, überein. Eine Änderung im Test zum kognitiven Schätzen zeigte keine auffälligen Voxel bezüglich einer Verschlechterung. Eine mögliche Ursache dafür ist eine nicht ausreichende Anzahl an epilepsiechirurgischen Eingriffen mit einer Resektion im Frontallappen.
Tuberous sclerosis complex is a rare genetic disease associated with mutations in the TSC1 or TSC2 genes, which cause overactivation of the mTOR complex. In the past 5 years, understanding has increased of the cellular consequences of TSC1 and TSC2 genetic variants and the mTORC1 overactivation in neurons and glial cells and their contribution to network dysfunction. Infants and young children (aged 1–5 years) with tuberous sclerosis complex might now benefit from early assessment of gene variant status and mosaicism. In the past 5 years, substantial advances have also been made in our understanding of mTOR-related neuropathology and the molecular aspects of both epileptogenesis and co-occurring neurodevelopmental disorders. Many potential disease-modifying strategies have been identified, including developments in targeted therapies based on molecular findings in epilepsy. Reliable EEG and MRI biomarkers are now available to identify, at a younger age than previously possible, infants with tuberous sclerosis complex who are at risk of epilepsy, autism, and developmental delay. Vigabatrin has been used successfully as a treatment in infants with tuberous sclerosis complex who showed abnormalities on EEG before seizure onset. The scope for mitigation of tuberous sclerosis complex-associated symptoms has expanded, including the use of mTOR inhibitors such as sirolimus and everolimus. Close cooperation between clinical and basic neuroscientists has provided new opportunities for future advances.
Despite the prevalence of anhedonia across multiple psychiatric disorders, its relevance to treatment selection and prognostication can be unclear (Davey et al., Psychol Med 42(10):2071-81, 2012). Given the challenges in pharmacological and psychosocial treatment, there has been increasing attention devoted to neuroanatomically-targeted treatments. This chapter will present a brief introduction to circuit-targeted therapeutics in psychiatry (Sect. 1), an overview of brain mapping as it relates to anhedonia (Sect. 2), a review of existing studies on brain stimulation for anhedonia (Sect. 3), and a description of emerging approaches to circuit-based neuromodulation for anhedonia (Sect. 4).
Emotion regulation has been linked to specific brain networks based on functional neuroimaging. We found that damage to these networks was associated with emotion regulation impairment in patients following focal brain injury (n = 167). Next, we used this lesion dataset to derive a de novo brain network for emotion regulation, which was defined by functional connectivity to the left ventrolateral prefrontal cortex (vlPFC). Finally, we used an independent lesion database (n = 629) to test whether damage to this lesion-derived network would increase the risk of neuropsychiatric conditions associated with emotion regulation impairment. We found that lesions causing mania, criminality, and depression intersected this network more than lesions causing other disorders. We conclude that emotion regulation maps to a connected brain network centered on the left vlPFC. Damage to this network impairs emotion regulation and may increase the risk of specific neuropsychiatric disorders.
Objective
We investigated the relationship of quantitative cerebral lesions on magnetic resonance imaging (MRI) and the onset age, seizure mode, and antiseizure treatment effectiveness of epilepsy in children with tuberous sclerosis complex (TSC).
Methods
We reviewed the clinical characteristics and MRI information of 44 children with TSC who had experienced epileptic seizures. Supratentorial tubers were quantitatively manually measured to calculate the tuber brain proportion (TBP). The numbers of cortical/subcortical cyst-like tubers, diffuse lesions, SEN, and SEGA were also evaluated.
Results
Twelve children (27.3%) had experienced infantile spasms, thirteen children (29.5%) had early-onset epilepsy, twenty-seven patients (64.3%) had a significant reduction in the frequency of seizures after antiseizure treatments. The median TBP was 9.2%, and diffuse lesions (range: 0-2) and cortical cyst-like lesions (range: 0-17) were seen in seven and seventeen children, respectively. The values of TBP (P<0.001), diffuse lesions (P<0.001), and cortical cyst-like tubers (P<0.001) were all associated with early-onset epilepsy. The values of TBP (P=0.004) and cortical cyst-like tuber (P<0.001) were associated with the occurrence of infantile spasms. The values of TBP (P=0.01), diffuse lesions (P=0.04), and cortical cyst-like tubers (P=0.004) were negatively associated with the effectiveness of antiseizure treatments. There was no significant correlation between subcortical cyst-like tuber, SEN, SEGA, and epilepsy severity.
Conclusions
Increasing abnormality of the cerebral hemispheres, as shown by quantitative MRI analysis including TBP, cortical cyst-like tubers, and diffuse lesions, is associated with measures of more severe epilepsy due to TSC. The values of TBP demonstrate strong significance for early-onset epilepsy.
Objective
We retrospectively assessed the localizing value of patient-history-based semiology (PHS), video-based semiology (VS), long-term monitoring video electroencephalography (LTM-VEEG) and interictal high resolution electric source imaging (HR-ESI) in the presurgical workup of patients with tuberous sclerosis complex (TSC).
Methods
Data from 24 consecutive TSC surgical candidates who underwent both HR-ESI and LTM-VEEG was retrospectively collected. PHS and VS were analyzed to hypothesize the symptomatogenic zone localization. LTM-VEEG and HR-ESI localization results were extracted from the diagnostic reports. Localizing value was compared between modalities, taken the resected/disconnected area of surgical patients in consideration. HR-ESI’s impact on the epileptogenic zone hypothesis and surgical workup was evaluated.
Results
Semiology, interictal EEG, ictal EEG and HR-ESI were localizing in 25%, 54%, 63% and 79% of patients. Inter-modality concordance ranged between 33-89%. In good surgical outcome patients, PHS, VS, interictal EEG, ictal EEG and HR-ESI showed concordance with resected area in 1/9 (11%), 0/9 (0%), 4/9 (44%), 3/9 (33%) and 6/9 patients (67%). HR-ESI positively impacts clinical management in 50% of patients.
Conclusions
In presurgical evaluation of TSC patients, semiology often has limited localizing value. Presurgical work-up benefits from HR-ESI.
Significance
Our findings may advice future presurgical epilepsy workup of TSC patients with the ultimate aim to improve outcome.
Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.
Tuberous Sclerosis Complex (TSC) is a rare autosomal dominant condition that affects multiple body systems. Disruption of the mammalian target of rapamycin (mTOR) pathway results in abnormal cell growth, proliferation, protein synthesis and cell differentiation and migration in TSC. In the central nervous system, mTOR disruption is also believed to influence neuronal excitability and promote epileptogenesis. Epilepsy is the most common neurological manifestation of TSC and affects 80-90% of individuals with high rates of treatment resistance (up to 75%). The onset of epilepsy in the majority of individuals with TSC occurs before the age of 2 years, which is a critical time in neurodevelopment. Both medically refractory epilepsy and early-onset epilepsy are associated with intellectual disability in TSC, while seizure control and remission are associated with lower rates of cognitive impairment. Our current knowledge of the treatment of epilepsy in TSC has expanded immensely over the last decade. Several new therapies such as, preemptive vigabatrin therapy in infants, cannabidiol, and mTOR inhibitors have emerged in recent years for the treatment of epilepsy in TSC. This review will provide clinicians with a comprehensive overview of the pharmacological and non-pharmacological therapies available for the treatment of epilepsy related to TSC.
Objective
: To develop and test a deep learning model to automatically detect malformations of cortical development (MCD).
Methods
: We trained a deep learning model to distinguish between diffuse cortical malformation (CM), periventricular nodular heterotopia (PVNH), and normal magnetic resonance imaging (MRI). We trained 4 different convolutional neural network (CNN) architectures. We used batch normalization, global average pooling, dropout layers, transfer learning, and data augmentation to minimize overfitting.
Results
: There were 45 subjects (866 images) with a normal MRI, 52 subjects (790 images) with CM, and 32 subjects (750 images) with PVNH. There was no subject overlap between the training, validation, and test sets. The InceptionResNetV2 architecture performed best in the validation set in all models and was evaluated in the test set with the following results: 1) the model distinguishing between CM and normal MRI yielded an area under the curve (AUC) of 0.89 and accuracy of 0.81; 2) the model distinguishing between PVNH and normal MRI yielded an AUC of 0.90 and accuracy of 0.84; 3) the model distinguishing between the three classes (CM, PVNH, and normal MRI) yielded an AUC of 0.88 and accuracy of 0.74. Visualization with gradient-weighted class activation maps and saliency maps showed that the deep learning models classified images based on relevant areas within each image.
Significance
: This study showed that CNNs can detect MCD at clinically useful performance level with a fully automated workflow without image feature selection.
Objective
Epilepsy develops in 70–90% of children with Tuberous Sclerosis Complex (TSC) and is often resistant to medication. Recently, the concept of preventive antiepileptic treatment to modify the natural history of epilepsy has been proposed. EPISTOP was a clinical trial designed to compare preventive versus conventional antiepileptic treatment in TSC infants.
Methods
In this multi‐center study, 94 infants with TSC without seizure history were followed with monthly video electroencephalography (EEG), and received vigabatrin either as conventional antiepileptic treatment, started after the first electrographic or clinical seizure, or preventively when epileptiform EEG activity before seizures was detected. At six sites, subjects were randomly allocated to treatment in a 1:1 ratio in a randomized controlled trial (RCT). At four sites, treatment allocation was fixed, denoted an open‐label trial (OLT). Subjects were followed until 2 years of age. The primary endpoint was the time to first clinical seizure.
Results
In 54 subjects epileptiform EEG abnormalities were identified before seizures. Twenty‐seven were included in the RCT and 27 in the OLT. The time to the first clinical seizure was significantly longer with preventive than conventional treatment (RCT: 364 95% CI: 223, 535) vs. 124 days (95% CI: 33, 149); OLT: 426 (95% CI: 258, 628) vs. 106 days (95% CI: 11, 149). At 24 months, our pooled analysis showed preventive treatment reduced the risk of clinical seizures (odds ratio [OR] = 0.21, p = 0.032), drug‐resistant epilepsy (OR = 0.23, p = 0.022), and infantile spasms (OR = 0, p < 0.001). No adverse events related to preventive treatment were noted.
Interpretation
Preventive treatment with vigabatrin was safe and modified the natural history of seizures in TSC, reducing the risk and severity of epilepsy.
Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, a number of studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and estimation of clinical improvement that they may generate.
Data from 33 patients suffering from Parkinson's Disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely either patient-specific diffusion-MRI data, disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were constructed and used to estimate the clinical improvement in out of sample data.
All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on a novel multi-center cohort. In a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample predictions of clinical improvements were calculated. Using either patient-specific connectivity (R = 0.43 at p = 0.001), an age- and disease-matched group connectome (R = 0.25, p = 0.048) and a normative connectome based on healthy/young subjects (R = 0.31 at p = 0.028), significant predictions could be made and underlying optimal connectivity profiles were highly similar.
Our results of patient-specific connectivity and normative connectomes lead to similar main conclusions about which brain areas are associated with clinical improvement. Still, although results were not significantly different, they hint at the fact that patient-specific connectivity may bear the potential of estimating slightly more variance when compared to group connectomes. Furthermore, use of normative connectomes involves datasets with high signal-to-noise acquired on specialized MRI hardware, while clinical datasets as the ones used here may not exactly match their quality. Our findings support the role of DBS electrode connectivity profiles as a promising method to investigate DBS effects and to potentially guide DBS programming.
Damage to the right fusiform face area can disrupt the ability to recognize faces, a classic example of how damage to a specialized brain region can disrupt a specialized brain function. However, similar symptoms can arise from damage to other brain regions, and face recognition is now thought to depend on a distributed brain network. The extent of this network and which regions are critical for facial recognition remains unclear. Here, we derive this network empirically based on lesion locations causing clinically significant impairments in facial recognition. Cases of acquired prosopagnosia were identified through a systematic literature search and lesion locations were mapped to a common brain atlas. The network of brain regions connected to each lesion location was identified using resting state functional connectivity from healthy participants (n = 1000), a technique termed lesion network mapping. Lesion networks were overlapped to identify connections common to lesions causing prosopagnosia. Reproducibility was assessed using split-half replication. Specificity was assessed through comparison with non-specific control lesions (n = 135) and with control lesions associated with symptoms other than prosopagnosia (n = 155). Finally, we tested whether our facial recognition network derived from clinically evident cases of prosopagnosia could predict subclinical facial agnosia in an independent lesion cohort (n = 31). Our systematic literature search identified 44 lesions causing prosopagnosia, only 29 of which intersected the right fusiform face area. However, all 44 lesion locations fell within a single brain network defined by connectivity to the right fusiform face area. Less consistent connectivity was found to other face-selective regions. Surprisingly, all 44 lesion locations were also functionally connected, through negative correlation, with regions in the left frontal cortex. This connectivity pattern was highly reproducible and specific to lesions causing prosopagnosia. Positive connectivity to the right fusiform face area and negative connectivity to left frontal regions were independent predictors of prosopagnosia and predicted subclinical facial agnosia in an independent lesion cohort. We conclude that lesions causing prosopagnosia localize to a single functionally connected brain network defined by connectivity to the right fusiform face area and to left frontal regions. Implications of these findings for models of facial recognition deficits are discussed.
Objective:
To determine if routine electroencephalography (EEG) in seizure-naive infants with tuberous sclerosis complex (TSC) can predict epilepsy and subsequent neurocognitive outcomes.
Methods:
Forty infants 7 months of age or younger and meeting the genetic or clinical diagnostic criteria for tuberous sclerosis were enrolled. Exclusion criteria included prior history of seizures or treatment with antiseizure medications. At each visit, seizure history and 1-hour awake and asleep video-EEG, standardized across all sites, were obtained until 2 years of age. Developmental assessments (Mullen and Vineland-II) were completed at 6, 12, and 24 months of age.
Results:
Of 40 infants enrolled (mean age of 82.4 days), 32 completed the study. Two were lost to follow-up and six were treated with antiepileptic drugs (AEDs) due to electrographic seizures and/or interictal epileptiform discharges (IEDs) on their EEG studies prior to the onset of clinical seizures. Seventeen of the 32 remaining children developed epilepsy at a mean age of 7.5 months (standard deviation [SD] = 4.4). Generalized/focal slowing, hypsarrhythmia, and generalized/focal attenuation were not predictive for the development of clinical seizures. Presence of IEDs had a 77.3% positive predictive value and absence a 70% negative predictive value for developing seizures by 2 years of age. IEDs preceded clinical seizure onset by 3.6 months (mean). Developmental testing showed significant decline, only in infants with ongoing seizures, but not infants who never developed seizures or whose seizures came under control.
Significance:
IEDs identify impending epilepsy in the majority (77%) of seizure-naive infants with TSC. The use of a 1-hour awake and asleep EEG can be used as a biomarker for ongoing epileptogenesis in most, but not all, infants with TSC. Persistent seizures, but not history of interictal epileptiform activity or history of well-controlled seizures, correlated with low scores on the Vineland and Mullen tests at 2 years of age.
Complex neurologic and psychiatric syndromes cannot be understood on the basis of focal brain lesions. Functional neuroimaging, maps of interrelated regions called the connectome, and the combination of lesion analysis with networks of the connectome offer a new way to understand neurologic function and disease.
Fully convolutional deep neural networks have been asserted to be fast and precise frameworks with great potential in image segmentation. One of the major challenges in training such networks raises when data is unbalanced, which is common in many medical imaging applications such as lesion segmentation where lesion class voxels are often much lower in numbers than non-lesion voxels. A trained network with unbalanced data may make predictions with high precision and low recall, being severely biased towards the non-lesion class which is particularly undesired in most medical applications where false negatives are actually more important than false positives. Various methods have been proposed to address this problem including two step training, sample re-weighting, balanced sampling, and more recently similarity loss functions, and focal loss. In this work we trained fully convolutional deep neural networks using an asymmetric similarity loss function to mitigate the issue of data imbalance and achieve much better trade-off between precision and recall. To this end, we developed a 3D fully convolutional densely connected network (FC-DenseNet) with large overlapping image patches as input and an asymmetric similarity loss layer based on Tversky index (using F
β
scores). We used large overlapping image patches as inputs for intrinsic and extrinsic data augmentation, a patch selection algorithm, and a patch prediction fusion strategy using B-spline weighted soft voting to account for the uncertainty of prediction in patch borders. We applied this method to multiple sclerosis (MS) lesion segmentation based on two different datasets of MSSEG 2016 and ISBI longitudinal MS lesion segmentation challenge, where we achieved average Dice similarity coefficients of 69.9% and 65.74%, respectively, achieving top performance in both challenges. We compared the performance of our network trained with F
β
loss, focal loss, and generalized Dice loss (GDL) functions. Through September 2018 our network trained with focal loss ranked first according to the ISBI challenge overall score and resulted in the lowest reported lesion false positive rate among all submitted methods. Our network trained with the asymmetric similarity loss led to the lowest surface distance and the best lesion true positive rate that is arguably the most important performance metric in a clinical decision support system for lesion detection. The asymmetric similarity loss function based on F
β
scores allows training networks that make a better balance between precision and recall in highly unbalanced image segmentation. We achieved superior performance in MS lesion segmentation using a patchwise 3D FC-DenseNet with a patch prediction fusion strategy, trained with asymmetric similarity loss functions.
Tuberous Sclerosis Complex (TSC) is characterized by a high prevalence of autism spectrum disorders (ASD). Little is known about the relation between cortical dysplasia and ASD severity in TSC. We assessed ASD severity (using the Autism Diagnostic Observation Scale), tuber and radial migration line (RML) count and location, and cognitive functioning in 52 children with TSC and performed regression and mediation analyses. Tuber and RML count were strongly positively related to ASD severity. However, when correcting for cognitive functioning, the majority of associations became insignificant and only total tuber count remained associated to the severity of restricted/repetitive behaviors. Occipital RML count remained associated with overall ASD severity, and social communication/interaction deficit severity specifically. This study shows the important explanatory role of cognitive functioning in the association between cortical dysplasia and ASD severity, and the relevance of separately studying the two ASD subdomains.
Electronic supplementary material
The online version of this article (doi:10.1007/s00787-017-1066-z) contains supplementary material, which is available to authorized users.
Adolescence is a time of dramatic changes in brain structure and function, and the adolescent brain is highly susceptible to being altered by experiences like substance use. However, there is much we have yet to learn about how these experiences influence brain development, how they promote or interfere with later health outcomes, or even what healthy brain development looks like. A large longitudinal study beginning in early adolescence could help us understand the normal variability in adolescent brain and cognitive development and tease apart the many factors that influence it. Recent advances in neuroimaging, informatics, and genetics technologies have made it feasible to conduct a study of sufficient size and scope to answer many outstanding questions. At the same time, several Institutes across the NIH recognized the value of collaborating in such a project because of its ability to address the role of biological, environmental, and behavioral factors like gender, pubertal hormones, sports participation, and social/economic disparities on brain development as well as their association with the emergence and progression of substance use and mental illness including suicide risk. Thus, the Adolescent Brain Cognitive Development study was created to answer the most pressing public health questions of our day.
Approximately 50% of patients with tuberous sclerosis complex (TSC) present intractable epilepsy, and surgery is an option for those patients. Hereby, we analyze long-term seizure control and neuropsychological outcomes of epilepsy surgery in patients with TSC. Clinical data were retrospectively collected from 66 patients with TSC and epilepsy followed up over 5 years, 51 of whom underwent epilepsy surgery between 2001 and 2011. Reductions in the number of seizures were analyzed at 1-year (1FU), 5-year (5FU), and 10-year (10FU) follow-ups visits after the operation. Influential factors on postoperative seizure free and intelligence quotient (IQ) and quality-of-life (QOL) outcomes were evaluated at 5FU. Resective procedures included 26 tuber resections, 15 lobectomies, and 10 tuber resections and lobectomies. Corpus callosotomies were performed as the adjunctive approach in 11 cases with low IQ. The percentages of seizure-free cases were 74.5% at 1FU, 58.8% at 5FU, and 47.8% at 10FU, and the predictive factor for long-term postoperative seizure freedom was the history of preoperative seizures and preoperative full-scale IQ. Significant improvements were found in performance IQ, full-scale IQ, and QOL in patients from the surgery group, particularly those who were seizure free after the operation. Our study showed that epilepsy surgery in TSC with epilepsy rendered improvements in seizure control, full-scale IQ, and QOL. Satisfactory long-term seizure control was often achieved with an early operation and without mental retardation, and improvements in QOL and IQ were frequently observed in postoperative patients who remained seizure free.
The number of resting state functional connectivity MRI studies continues to expand at a rapid rate along with the options for data processing. Of the processing options, few have generated as much controversy as global signal regression and the subsequent observation of negative correlations (anti-correlations). This debate has motivated new processing strategies and advancement in the field, but has also generated significant confusion and contradictory guidelines. In this article, we work towards a consensus regarding global signal regression. We highlight several points of agreement including the fact that there is not a single “right” way to process resting state data that reveals the “true” nature of the brain. Although further work is needed, different processing approaches likely reveal complementary insights about the brain's functional organisation.
Significance
Functional MRI (fMRI) is 25 years old, yet surprisingly its most common statistical methods have not been validated using real data. Here, we used resting-state fMRI data from 499 healthy controls to conduct 3 million task group analyses. Using this null data with different experimental designs, we estimate the incidence of significant results. In theory, we should find 5% false positives (for a significance threshold of 5%), but instead we found that the most common software packages for fMRI analysis (SPM, FSL, AFNI) can result in false-positive rates of up to 70%. These results question the validity of a number of fMRI studies and may have a large impact on the interpretation of weakly significant neuroimaging results.
Objective:
We reviewed our experience of surgery for epileptic spasms (ES) with or without history of infantile spasms.
Methods:
Data were reviewed from 65 (33 male) patients with ES who underwent surgery between 1993 and 2014; palliative cases were excluded.
Results:
Mean age at surgery was 5.1 (range 0.2-19) years, with mean postsurgical follow-up of 45.3 (6-120) months. Mean number of anticonvulsants used preoperatively was 4.2 (2-8), which decreased to 1.2 (0-4) postoperatively (p < 0.0001). Total hemispherectomy was the most commonly performed surgery (n = 20), followed by subtotal hemispherectomy (n = 17), multilobar resection (n = 13), lobectomy (n = 7), tuberectomy (n = 6), and lobectomy + tuberectomy (n = 2), with International League Against Epilepsy (ILAE) class I outcome in 20, 10, 7, 6, 3, and 0 patients, respectively (total 46/65 (71%); 22 off medication). Shorter duration of epilepsy (p = 0.022) and presence of magnetic resonance imaging (MRI) lesion (p = 0.026) were independently associated with class I outcome. Of 34 patients operated <3 years after seizure onset, 30 (88%) achieved class I outcome. Thirty-seven (79%) of 47 patients with lesional MRI had class-I outcome, whereas 9 (50%) of 18 with normal MRI had class I outcome. Positron emission tomography (PET) scan was abnormal in almost all patients [61 (97%) of 63 with lateralizing/localizing findings in 56 (92%) of 61 patients, thus helping in surgical decision making and guiding subdural grid placements, particularly in patients with nonlesional MRI. Fifteen patients had postoperative complications, mostly minor.
Significance:
Curative epilepsy surgery in ES patients, with or without history of infantile spasms, is best accomplished at an early age and in those patients with lesional abnormalities on MRI with electroencephalography (EEG) concordance. Good outcomes can be achieved even when there is no MRI lesion but positive PET localization.
In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators. (46 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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.
Summary Tuberous sclerosis is one of the few established medical causes of autism spectrum disorder and is a unique neurogenetic model for testing theories about the brain basis of the syndrome. We conducted a retrospective case study of the neuro-epileptic risk factors predisposing to autism spectrum disorder in individuals with tuberous sclerosis to test current neurobiological theories of autism spectrum disorder. We found that an autism spectrum disorder diagnosis was associated with the presence of cortical tubers in the temporal but not other lobes of the brain. Indeed, the presence of tubers in the temporal lobes appeared to be a necessary but not sufficient risk factor for the development of an autism spectrum disorder. However, contrary to the predictions of some theories, the location of tubers in specific regions of the temporal lobe, such as the superior temporal gyrus or the right temporal lobe, did not determine which individuals with temporal lobe tubers developed an autism spectrum disorder. Instead, outcome was associated with various indices of epileptic activity including evidence of temporal lobe epileptiform discharges on EEG, the age to onset of seizures in the first 3 years of life and a history of infantile spasms. The results indicated that individuals with tuberous sclerosis are at very high risk of developing an autism spectrum disorder when temporal lobe tubers are present and associated with temporal lobe epileptiform discharges and early-onset, persistent spasm-like seizures. These risk markers constitute useful clinical indicators of prognosis, but further research is required to identify the neurobiological mechanisms responsible for their association with outcome. Most especially, it will be important to test whether, as the findings suggest, there is a critical early stage of brain maturation during which temporal lobe epilepsy perturbs the development of brain systems that underpin ‘social intelligence’ and possibly other cognitive skills, thereby inducing an autism spectrum disorder.
Tuberous sclerosis complex (TSC) is associated with intellectual disability, but the risk pathways are poorly understood.
The Tuberous Sclerosis 2000 Study is a prospective longitudinal study of the natural history of TSC. One hundred and twenty-five UK children age 0-16 years with TSC and born between January 2001 and December 2006 were studied. Intelligence was assessed using standardized measures at ≥2 years of age. The age of onset of epilepsy, the type of seizure disorder, the frequency and duration of seizures, as well as the response to treatment was assessed at interview and by review of medical records. The severity of epilepsy in the early years was estimated using the E-Chess score. Genetic studies identified the mutations and the number of cortical tubers was determined from brain scans.
TSC2 mutations were associated with significantly higher cortical tuber count than TSC1 mutations. The extent of brain involvement, as indexed by cortical tuber count, was associated with an earlier age of onset and severity of epilepsy. In turn, the severity of epilepsy was strongly associated with the degree of intellectual impairment. Structural equation modelling supported a causal pathway from genetic abnormality to cortical tuber count to epilepsy severity to intellectual outcome. Infantile spasms and status epilepticus were important contributors to seizure severity.
The findings support the proposition that severe, early onset epilepsy may impair intellectual development in TSC and highlight the potential importance of early, prompt and effective treatment or prevention of epilepsy in tuberous sclerosis.
Tuberous sclerosis complex (TSC) is characterized by benign hamartomas in multiple organs including the brain and its clinical phenotypes may be associated with abnormal neural connections. We aimed to provide the first detailed findings on disrupted structural brain networks in TSC patients. Structural whole-brain connectivity maps were constructed using structural and diffusion MRI in 20 TSC (age range: 3-24 years) and 20 typically developing (TD; 3-23 years) subjects. We assessed global (short- and long-association and interhemispheric fibers) and regional white matter connectivity, and performed graph theoretical analysis using gyral pattern- and atlas-based node parcellations. Significantly higher mean diffusivity (MD) was shown in TSC patients than in TD controls throughout the whole brain and positively correlated with tuber load severity. A significant increase in MD was mainly influenced by an increase in radial diffusivity. Furthermore, interhemispheric connectivity was particularly reduced in TSC, which leads to increased network segregation within hemispheres. TSC patients with developmental delay (DD) showed significantly higher MD than those without DD primarily in intrahemispheric connections. Our analysis allows non-biased determination of differential white matter involvement, which may provide better measures of "lesion load" and lead to a better understanding of disease mechanisms.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Magnetic resonance imaging (MRI) plays a vital role in the scientific investigation and clinical management of multiple sclerosis. Analyses of binary multiple sclerosis lesion maps are typically “mass univariate” and conducted with standard linear models that are ill suited to the binary nature of the data and ignore the spatial dependence between nearby voxels (volume elements). Smoothing the lesion maps does not entirely eliminate the non-Gaussian nature of the data and requires an arbitrary choice of the smoothing parameter. Here we present a Bayesian spatial model to accurately model binary lesion maps and to determine if there is spatial dependence between lesion location and subject specific covariates such as MS subtype, age, gender, disease duration and disease severity measures. We apply our model to binary lesion maps derived from T 2 -weighted MRI images from 250 multiple sclerosis patients classified into five clinical subtypes, and demonstrate unique modeling and predictive capabilities over existing methods.
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.
Permutation methods can provide exact control of false positives and allow the use of non-standard statistics, making only weak assumptions about the data. With the availability of fast and inexpensive computing, their main limitation would be some lack of flexibility to work with arbitrary experimental designs. In this paper we report on results on approximate permutation methods that are more flexible with respect to the experimental design and nuisance variables, and conduct detailed simulations to identify the best method for settings that are typical for imaging research scenarios. We present a generic framework for permutation inference for complex general linear models (glms) when the errors are exchangeable and/or have a symmetric distribution, and show that, even in the presence of nuisance effects, these permutation inferences are powerful while providing excellent control of false positives in a wide range of common and relevant imaging research scenarios. We also demonstrate how the inference on glm parameters, originally intended for independent data, can be used in certain special but useful cases in which independence is violated. Detailed examples of common neuroimaging applications are provided, as well as a complete algorithm - the "randomise" algorithm - for permutation inference with the glm.
Scikit-learn is a Python module integrating a wide range of state-of-the-art
machine learning algorithms for medium-scale supervised and unsupervised
problems. This package focuses on bringing machine learning to non-specialists
using a general-purpose high-level language. Emphasis is put on ease of use,
performance, documentation, and API consistency. It has minimal dependencies
and is distributed under the simplified BSD license, encouraging its use in
both academic and commercial settings. Source code, binaries, and documentation
can be downloaded from http://scikit-learn.sourceforge.net.
Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.
Active contour segmentation and its robust implementation using level sets have been studied thoroughly in the medical image analysis literature. Despite the availability of these powerful methods, clinical research still largely relies on manual slice-by-slice outlining for anatomical structure segmentation. To bridge the gap between methodological advances and clinical routine, we developed ITK-SNAP: an open source application intended to make level set segmentation easily accessible to a wide range of users with various levels of mathematical expertise. We briefly describe this new tool and report the results of a validation study in which ITK-SNAP was compared to manual segmentation of the caudate in the context of an ongoing child neuroimaging autism study. The integration of the SNAP tool with the Insight Toolkit was performed by Cognitica Corporation under support from the NIH NLM PO 467-MZ-202446-1. The validation study is supported by the NIH NIBIB grant P01 EB002779, the NIH Conte Center MH064065, and the UNC Neurodevelopmental Disorders Research Center, Developmental Neuroimaging Core. The MRI images of infants, caudate images and expert manual segmentations are funded by NIH RO1 MH61696 and NIMH MH 64580 (PI: Joseph Piven). Manual segmentations for the caudate study were performed by Michael Graves and Todd Mathews, with protocol development in collaboration with Cody Hazlett. Rachel Smith and Michael Graves were the raters for the SNAP segmentations.
Objective:
To determine the underlying etiologies in a contemporary cohort of infants with infantile spasms and to examine response to treatment.
Methods:
Identification of the underlying etiology and response to treatment in 377 infants enrolled in a clinical trial of the treatment of infantile spasms between 2007 and 2014 using a systematic review of history, examination, and investigations. They were classified using the pediatric adaptation of International Classification of Diseases, Tenth Revision (ICD-10).
Results:
A total of 219 of 377 (58%) had a proven etiology, of whom 128 (58%) responded, 58 of 108 (54%) were allocated hormonal treatment, and 70 of 111 (63%) had combination therapy. Fourteen of 17 (82%, 95% confidence interval [CI] 59% to 94%) infants with stroke and infarct responded (compared to 114 of 202 for the rest of the proven etiology group (56%, 95% CI 48% to 62%, chi-square 4.3, P = .037): the better response remains when treatment allocation and lead time are taken into account (odds ratio 5.1, 95% CI 1.1 to 23.6, P = .037). Twenty of 37 (54%, 95% CI 38% to 70%) infants with Down syndrome had cessation of spasms compared to 108 of 182 (59%, 95% CI 52% to 66%, chi-square 0.35, P = .55) for the rest of the proven etiology group. The lack of a significant difference remains after taking treatment modality and lead-time into account (odds ratio 0.8, 95% CI 0.4 to 1.7, P = .62). In Down syndrome infants, treatment modality did not appear to affect response: 11 of 20 (55%) allocated hormonal therapy responded, compared to 9 of 17 (53%) allocated combination therapy.
Significance:
This classification allows easy comparison with other classifications and with our earlier reports. Stroke and infarct have a better outcome than other etiologies, whereas Down syndrome might not respond to the addition of vigabatrin to hormonal treatment.
Objective:
To identify whether abnormal electroencephalography (EEG) connectivity is present before the onset of epileptic spasms (ES) in infants with tuberous sclerosis complex (TSC).
Methods:
Scalp EEG recordings were collected prospectively in infants diagnosed with TSC in the first year of life. This study compared the earliest recorded EEG from infants prior to ES onset (n = 16) and from infants who did not develop ES (n = 28). Five minutes of stage II or quiet sleep was clipped and filtered into canonical EEG frequency bands. Mutual information values between each pair of EEG channels were compared directly and used as a weighted graph to calculate graph measures of global efficiency, characteristic path length, average clustering coefficient, and modularity.
Results:
At the group level, infants who later developed ES had increased EEG connectivity in sleep. They had higher mutual information values between most EEG channels in all frequency bands adjusted for age. Infants who later developed ES had higher global efficiency and average clustering coefficients, shorter characteristic path lengths, and lower modularity across most frequency bands adjusted for age. This suggests that infants who went on to develop ES had increased local and long-range EEG connectivity with less segregation of graph regions into distinct modules.
Significance:
This study suggests that increased neural connectivity precedes clinical ES onset in a cohort of infants with TSC. Overconnectivity may reflect progressive pathologic network synchronization culminating in generalized ES. Further research is needed before scalp EEG connectivity measures can be used as a potential biomarker of ES risk and treatment response in pre-symptomatic infants with TSC.
Global signal regression (GSR) is one of the most debated preprocessing strategies for resting-state functional MRI. GSR effectively removes global artifacts driven by motion and respiration, but also discards globally distributed neural information and introduces negative correlations between certain brain regions. The vast majority of previous studies have focused on the effectiveness of GSR in removing imaging artifacts, as well as its potential biases. Given the growing interest in functional connectivity fingerprinting, here we considered the utilitarian question of whether GSR strengthens or weakens associations between resting-state functional connectivity (RSFC) and multiple behavioral measures across cognition, personality and emotion.
By applying the variance component model to the Brain Genomics Superstruct Project (GSP), we found that behavioral variance explained by whole-brain RSFC increased by an average of 47% across 23 behavioral measures after GSR. In the Human Connectome Project (HCP), we found that behavioral variance explained by whole-brain RSFC increased by an average of 40% across 58 behavioral measures, when GSR was applied after ICA-FIX de-noising. To ensure generalizability, we repeated our analyses using kernel regression. GSR improved behavioral prediction accuracies by an average of 64% and 12% in the GSP and HCP datasets respectively. Importantly, the results were consistent across methods. A behavioral measure with greater RSFC-explained variance (using the variance component model) also exhibited greater prediction accuracy (using kernel regression). A behavioral measure with greater improvement in behavioral variance explained after GSR (using the variance component model) also enjoyed greater improvement in prediction accuracy after GSR (using kernel regression). Furthermore, GSR appeared to benefit task performance measures more than self-reported measures.
Since GSR was more effective at removing motion-related and respiratory-related artifacts, GSR-related increases in variance explained and prediction accuracies were unlikely the result of motion-related or respiratory-related artifacts. However, it is worth emphasizing that the current study focused on whole-brain RSFC, so it remains unclear whether GSR improves RSFC-behavioral associations for specific connections or networks. Overall, our results suggest that at least in the case for young healthy adults, GSR strengthens the associations between RSFC and most (although not all) behavioral measures. Code for the variance component model and ridge regression can be found here: https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/preprocessing/Li2019_GSR.
Brain damage can occasionally result in paradoxical functional benefit, which could help identify therapeutic targets for neuromodulation. However, these beneficial lesions are rare and lesions in multiple different brain locations can improve the same symptom. Using a technique called lesion network mapping, we show that heterogeneous lesion locations resulting in tremor relief are all connected to common nodes in the cerebellum and thalamus, the latter of which is a proven deep brain stimulation target for tremor. These results suggest that lesion network mapping can identify the common substrate underlying therapeutic lesions and effective therapeutic targets.
This article is protected by copyright. All rights reserved.
Purpose:
To evaluate initial magnetic resonance imaging (MRI) abnormalities in infantile spasms, correlate them to clinical characteristics, and describe repeat imaging findings.
Methods:
A retrospective review of infantile spasm patients was conducted, classifying abnormal MRI into developmental, acquired, and nonspecific subgroups.
Results:
MRIs were abnormal in 52 of 71 infantile spasm patients (23 developmental, 23 acquired, and 6 nonspecific) with no correlation to the clinical infantile spasm characteristics. Both developmental and acquired subgroups exhibited cortical gray and/or white matter abnormalities. Additional abnormalities of deep gray structures, brain stem, callosum, and volume loss occurred in the structural acquired subgroup. Repeat MRI showed better definition of the extent of existing malformations.
Conclusion:
In structural infantile spasms, developmental/acquired subgroups showed differences in pattern of MRI abnormalities but did not correlate with clinical characteristics.
Significance
Cases like that of Charles Whitman, who murdered 16 people after growth of a brain tumor, have sparked debate about why some brain lesions, but not others, might lead to criminal behavior. Here we systematically characterize such lesions and compare them with lesions that cause other symptoms. We find that lesions in multiple different brain areas are associated with criminal behavior. However, these lesions all fall within a unique functionally connected brain network involved in moral decision making. Furthermore, connectivity to competing brain networks predicts the abnormal moral decisions observed in these patients. These results provide insight into why some brain lesions, but not others, might predispose to criminal behavior, with potential neuroscience, medical, and legal implications.
Background
The optimal target in the dorsolateral prefrontal cortex (DLPFC) for treating depression with repetitive transcranial magnetic stimulation (rTMS) remains unknown. Better efficacy has been associated with stimulation sites that are 1) more anterior and lateral and 2) more functionally connected to the subgenual cingulate. Here we prospectively test whether these factors predict response in individual patients.
Methods
A primary cohort (Boston, N = 25) with medication-refractory depression underwent conventional open-label rTMS to the left DLPFC. A secondary cohort (Michigan, N = 16) underwent 4 weeks of sham followed by open label rTMS for non-responders (N = 12). In each patient, the location of the stimulation site was recorded with frameless stereotaxy. Connectivity between each patient’s stimulation site and the subgenual cingulate was assessed using resting state fcMRI from a cohort of healthy subjects (N = 1000), and confirmed using connectivity from depression patients (N = 38).
Results
In our primary cohort, antidepressant efficacy was predicted by stimulation sites that were both more antero-lateral (r = .51, p < .01) and more negatively correlated with the subgenual cingulate (r = -.55, p < .005). However, subgenual connectivity was the only independent predictor of response and the only factor to predict response to active (r = -.52, p < .05) but not sham rTMS in our secondary cohort.
Conclusions
This study provides prospective validation that functional connectivity between an individual’s rTMS cortical target and the subgenual cingulate predicts antidepressant response. Implications for improving the cortical rTMS target for depression are discussed.
Objectives:
Tuberous sclerosis complex (TSC) is a neurocutaneous genetic disorder with a high prevalence of epilepsy and neurodevelopmental disorders. TSC can be challenging to diagnose in infants because they often do not show many clinical signs early in life. In this study, we describe the timing and pattern of presenting and diagnostic features in a prospective longitudinal study of infants with TSC.
Methods:
Two multicenter, prospective studies enrolled 130 infants with definite TSC by clinical or genetic criteria and followed them longitudinally up to 36 months of age. Periodic study visits included medical and seizure histories, physical and neurologic examinations, and developmental assessments. Ages at which major and minor features of TSC and seizures were first identified were analyzed.
Results:
The most common initial presenting features of TSC were cardiac rhabdomyomas (59%) and hypomelanotic macules or other skin findings (39%), and 85% of infants presented with either or both. Ultimately, the most prevalent diagnostic TSC features were hypomelanotic macules (94%), tubers or other cortical dysplasias (94%), subependymal nodules (90%), and cardiac rhabdomyomas (82%). Thirty-five percent of infants presented prenatally, 41% presented at birth or within the first month of life, and 74% met criteria for TSC diagnosis at or within 30 days of presentation. Seizure onset occurred before or at initial presentation in only 15% of infants, but 73% developed epilepsy within the first year of life.
Conclusions:
Infants with TSC can often be identified early, before the onset of neurologic sequelae, enabling earlier diagnosis, surveillance, and possibly disease-modifying treatment.
Objective: The benefit of deep brain stimulation (DBS) for Parkinson's disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remains unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort.
Methods: A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of Unified Parkinson's Disease Rating Scale). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center.
Results: In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p < 0.001). This same connectivity profile predicted response in an independent patient cohort (p < 0.01). Structural and functional connectivity were independent predictors of clinical improvement (p < 0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease-matched to our DBS patients.
Interpretation: Effective STN-DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. This article is protected by copyright. All rights reserved.
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.
Statistical voxel-based lesion-behavior mapping (VLBM) in neurological patients with brain lesions is frequently used to examine the relationship between structure and function of the healthy human brain. Only recently, two simulation studies noted reduced anatomical validity of this method, observing the results of VLBM to be systematically misplaced by about 16 mm. However, both simulation studies differed from VLBM analyses of real data in that they lacked the proper use of two correction factors: lesion size and "sufficient lesion affection." In simulation experiments on a sample of 274 real stroke patients, we found that the use of these two correction factors reduced misplacement markedly compared to uncorrected VLBM. Apparently, the misplacement is due to physiological effects of brain lesion anatomy. Voxel-wise topographies of collateral damage in the real data were generated and used to compute a metric for the inter-voxel relation of brain damage. "Anatomical bias" vectors that were solely calculated from these inter-voxel relations in the patients' real anatomical data, successfully predicted the VLBM misplacement. The latter has the potential to help in the development of new VLBM methods that provide even higher anatomical validity than currently available by the proper use of correction factors. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.
Objective:
To assess the extent and evolution of tissue abnormality of tubers, perituber tissue, and normal-appearing white matter (NAWM) in patients with tuberous sclerosis complex using serial diffusion tensor imaging.
Methods:
We applied automatic segmentation based on a combined global-local intensity mixture model of 3T structural and 35 direction diffusion tensor MRIs (diffusion tensor imaging) to define 3 regions: tuber tissue, an equal volume perituber rim, and the remaining NAWM. For each patient, scan, lobe, and tissue type, we analyzed the averages of mean diffusivity (MD) and fractional anisotropy (FA) in a generalized additive mixed model.
Results:
Twenty-five patients (mean age 5.9 years; range 0.5-24.5 years) underwent 2 to 6 scans each, totaling 70 scans. Average time between scans was 1.2 years (range 0.4-2.9). Patient scans were compared with those of 73 healthy controls. FA values were lowest, and MD values were highest in tubers, next in perituber tissue, then in NAWM. Longitudinal analysis showed a positive (FA) and negative (MD) correlation with age in tubers, perituber tissue, and NAWM. All 3 tissue types followed a biexponential developmental trajectory, similar to the white matter of controls. An additional qualitative analysis showed a gradual transition of diffusion values across the tissue type boundaries.
Conclusions:
Similar to NAWM, tuber and perituber tissues in tuberous sclerosis complex undergo microstructural evolution with age. The extent of diffusion abnormality decreases with distance to the tuber, in line with known extension of histologic, immunohistochemical, and molecular abnormalities beyond tuber pathology.
Aim As relationships between autistic traits, epilepsy, and cognitive functioning remain poorly understood, these associations were explored in the biologically related disorders tuberous sclerosis complex (TSC), neurofibromatosis type 1 (NF1), and epilepsy.
Method The Social Responsiveness Scale (SRS), a quantitative measure of autistic traits, was distributed to caregivers or companions of patients with TSC, NF1, and childhood-onset epilepsy of unknown cause (EUC), and these results were compared with SRS data from individuals with idiopathic autism spectrum disorders (ASDs) and their unaffected siblings. Scores and trait profiles of autistic features were compared with cognitive outcomes, epilepsy variables, and genotype.
Results A total of 180 SRS questionnaires were completed in the TSC, NF1, and EUC outpatient clinics at the Massachusetts General Hospital (90 females, 90 males; mean age 21y, range 4–63y), and SRS data from 210 patients with ASD recruited from an autism research collaboration (167 males, 43 females; mean age 9y, range 4–22y) and 130 unaffected siblings were available. Regression models showed a significant association between SRS scores and intelligence outcomes (p<0.001) and various seizure variables (p<0.02), but not with a specific underlying disorder or genotype. The level of autistic features was strongly associated with intelligence outcomes in patients with TSC and epilepsy (p<0.01); in patients with NF1 these relationships were weaker (p=0.25). For all study groups, autistic trait subdomains covaried with neurocognitive comorbidity, with endophenotypes similar to that of idiopathic autism.
Interpretation Our data show that in TSC and childhood-onset epilepsy, the severity and phenotype of autistic features are inextricably linked with intelligence and epilepsy outcomes. Such relationships were weaker for individuals with NF1. Findings suggest that ASDs are not specific in these conditions.
GABAergic and glutamatergic neuronal systems in adult normal human brains were shown quantitatively and in detail through the distributions of glutamate decarboxylase (GAD) and glutamate dehydrogenase (GDH), respectively. Consecutive coronal sections containing part of the striatum and the substantia nigra were obtained from the right hemisphere of three deceased persons with no history of neurological or psychiatric diseases and were stained immunohistochemically for GAD and GDH. Each stained section was divided into approximately 3 million microareas and the immunohistochemical fluorescence intensity in each area was measured by a human brain mapping analyzer, which is a microphotometry system for analysis of the distribution of neurochemicals in a large tissue slice. In the analyzed brain regions, conspicuously intense GAD-like immunoreactivity was observed in the substantia nigra, globus pallidus, and hypothalamus. GDH was widely and rather evenly distributed in the gray matter compared to GAD, although intense GDH-like immunoreactivity was observed in the lateral geniculate nucleus and substantia nigra. Within the substantia nigra, the globus pallidus, and other regions, characteristic distributions of GAD- and GDH-like immunoreactivity were found. We believe that the analysis of the human brain by this novel technique can help to understand the functional distribution of neuronal systems in the normal human brain and may be able to identify abnormal changes in the diseased human brain. It can also provide basic data to help in the interpretation of functional magnetic resonance imaging or positron emission tomography. Hum. Brain Mapping 11:93–103, 2000. © 2000 Wiley-Liss, Inc.
FreeSurfer is a suite of tools for the analysis of neuroimaging data that provides an array of algorithms to quantify the functional, connectional and structural properties of the human brain. It has evolved from a package primarily aimed at generating surface representations of the cerebral cortex into one that automatically creates models of most macroscopically visible structures in the human brain given any reasonable T1-weighted input image. It is freely available, runs on a wide variety of hardware and software platforms, and is open source.
The purpose of this study was to assess the prevalence of and to identify epidemiologic, genetic, electrophysiologic, and neuroanatomic risk factors for autism spectrum disorders (ASD) in a cohort of patients with tuberous sclerosis complex (TSC).
A total of 103 patients with TSC were evaluated for ASD. A retrospective review of patients' records was performed, including mutational analysis. EEG reports were analyzed for the presence of ictal and interictal epileptiform features. Brain MRI scans were evaluated for TSC neuropathology, including tuber burden.
Of the 103 patients with TSC, 40%were diagnosed with an ASD. On univariate analysis, patients with ASD were less likely to have mutations in the TSC1 gene. Patients with ASD also had an earlier age at seizure onset and more frequent seizures. On EEG, those with ASD had a significantly greater amount of interictal epileptiform features in the left temporal lobe only. On MRI, there were no differences in the regional distribution of tuber burden, although those with TSC2 and ASD had a higher prevalence of cyst-like tubers.
The development of ASD in TSC is not well understood. Given our findings, ASD may be associated with persistent seizure activity early in development in particular brain regions, such as those responsible for social perception and communication in the left temporal lobe. The presence of cyst-like tubers on MRI could provide a structural basis or marker for ASD pathology in TSC, although studies assessing their effect on cortical function are needed.
Although normalization of brain images is critical to the analysis of structural damage across individuals, loss of tissue due to focal lesions presents challenges to the available normalization algorithms. Until recently, cost function masking, as advocated by Brett and colleagues (2001), was the accepted method to overcome difficulties encountered when normalizing damaged brains; however, development of the unified segmentation approach for normalization in SPM5 (Ashburner & Friston, 2005) offered an alternative. Crinion et al. (2007) demonstrated this approach produced normalization results without cost function masking that appeared to be robust to lesion effects when tested using the same simulated lesions studied by Brett et al. (2001). The present study sought to confirm the validity of this approach in brains with focal damage due to vascular events. To do so, we examined outcomes of normalization using unified segmentation with and without cost function masking in 49 brain images with chronic stroke. Lesion masks were created using two approaches (precise and rough drawings of lesion boundaries), and normalization was implemented with both smoothed and unsmoothed versions of the masks. We found that failure to employ cost function masking produced less accurate results in real and simulated lesions, compared to masked normalization, both in terms of deformation field displacement and voxelwise intensity differences. Additionally, unmasked normalization led to significant underestimation of lesion volume relative to all four masking conditions, especially in patients with large lesions. Taken together, these findings suggest cost function masking is still necessary when normalizing brain images with chronic infarcts.
Although epilepsy affects most patients with tuberous sclerosis complex (TSC), little is known about the natural history of epilepsy in this genetic disease.
A retrospective chart review of all patients with TSC seen between January 2002 and October 2008. Charts were reviewed for a history of infantile spasms (IS), seizure other than IS, refractory epilepsy, Lennox-Gastaut syndrome (LGS), anticonvulsant medication use, ages of seizure onset, last seizure, last clinic visit, clinical seizure phenotype(s), cognitive impairment, and genetic mutation.
Two hundred ninety-one patients were included. Among these patients, 37.8% had a history of IS; 85.2% had a history of seizure; 54.1% developed multiple seizure types, not including IS; 63.2% had seizure onset in the first year of life; and 12.1% of adults without a seizure history developed epilepsy. Of epilepsy patients, 62.5% developed refractory epilepsy and 33.5% achieved epilepsy remission; 37.5% of these patients achieved medication freedom. IS was a risk factor for refractory epilepsy (p<0.0001) and LGS (p<0.0001). History of seizure, IS, age at seizure onset, and refractory epilepsy each correlated with poor cognitive outcome (p<0.0001). Epilepsy remission correlated with better cognitive outcome (p<0.0001). TSC2 was a risk factor for IS and epilepsy; patients without an identified mutation were more likely to achieve remission.
Most patients with TSC develop epilepsy and most develop multiple seizure types. Onset typically occurs in the first year of life; however, adults remain at risk. Although refractory epilepsy is common, many patients achieve seizure control. Many features of seizure history are predictive of cognitive and epilepsy outcome.
Infantile spasms are characterized by age-specific expression of epileptic spasms and hypsarrhythmia and often result in significant cognitive impairment. Other epilepsies or autism often ensue especially in symptomatic IS (SIS). Cortical or subcortical damage, including white matter, have been implicated in the pathogenesis of SIS. To generate a model of SIS, we recreated this pathology by injecting rats with lipopolysaccharide and doxorubicin intracerebrally at postnatal day (P) 3 and with p-chlorophenylalanine intraperitoneally at P5. Spasms occurred between P4 and 13 and were associated with ictal EEG correlates, interictal EEG abnormalities and neurodevelopmental decline. After P9 other seizures, deficits in learning and memory, and autistic-like behaviors (indifference to other rats, increased grooming) were observed. Adrenocorticotropic hormone (ACTH) did not affect spasms. Vigabatrin transiently suppressed spasms at P5. This new model of SIS will be useful to study the neurobiology and treatment of SIS, including those that are refractory to ACTH.
Investigate whether patients on vigabatrin demonstrated new-onset and reversible T(2)-weighted magnetic resonance imaging (MRI) abnormalities.
MRI of patients treated during vigabatrin therapy was reviewed, following detection of new basal ganglia, thalamus, and corpus callosum hyperintensities in an infant treated for infantile spasms. Patients were assessed for age at time of MRI, diagnosis, duration, and dose, MRI findings pre-, on, and postvigabatrin, concomitant medications, and clinical correlation. These findings were compared to MRI in patients with infantile spasms who did not receive vigabatrin.
Twenty-three patients were identified as having MRI during the course of vigabatrin therapy. After excluding the index case, we detected new and reversible basal ganglia, thalamic, brainstem, or dentate nucleus abnormalities in 7 of 22 (32%) patients treated with vigabatrin. All findings were reversible following discontinuation of therapy. Diffusion-weighted imaging (DWI) was positive with apparent diffusion coefficient (ADC) maps demonstrating restricted diffusion. Affected versus unaffected patients, respectively, had a median age of 11 months versus 5 years, therapy duration 3 months versus 12 months, and dosage 170 mg/kg/day versus 87 mg/kg/day. All affected patients were treated for infantile spasms; none of 56 patients with infantile spasms who were not treated with vigabatrin showed the same abnormalities.
MRI abnormalities attributable to vigabatrin, characterized by new-onset and reversible T(2)-weighted hyperintensities and restricted diffusion in thalami, globus pallidus, dentate nuclei, brainstem, or corpus callosum were identified in 8 of 23 patients. Young age and relatively high dose appear to be risk factors.
The deep cerebellar nuclei (DCN) are the final integrative units of the cerebellar network. The strongest single afferent to the DCN is formed by GABAergic Purkinje neuron axons whose synapses constitute the majority of all synapses in the DCN, with their action strongly regulating the intrinsic activity of their target neurons. Although this is well established, it remains unclear whether all DCN cell groups receive a functionally similar inhibitory input. We previously characterized three types of mouse DCN neurons based on the expression of glutamic acid decarboxylase isoform 67 (GAD67), their active membrane properties and morphological features. Here we describe the GABAergic synapses in these cell groups and show that spontaneous GABAergic synaptic activity can be seen in all three cell types. Since the majority of DCN neurons fire action potentials spontaneously at high frequencies both in vivo and in vitro, we expected that spontaneous GABAergic synaptic activities mediated by intra-DCN synaptic connections could be uncovered by their sensitivity to TTX. However, TTX had little effect on spontaneous synaptic activity. It seems, therefore that functional GABAergic connectivity within the DCN is sparse and/or weak at least under our experimental conditions. Even though present in all cell types, the spontaneous GABAergic events showed significant differences between the cell types. The synaptic currents in GABAergic cells had lower amplitude, lower frequency and slower kinetics than those of non-GABAergic cells. These differences could not be sufficiently explained by considering only cell size differences or a differential GABA(A)-receptor alpha-subunit composition. Rather, the main differentiating factor appears to be the dendritic localization of GABAergic synapses in the GABAergic cells.
Infantile spasms are generalized seizures specific to early infancy, and are believed to result from complex cortical-subcortical interactions during a critical period of development. We used positron emission tomography (PET) to determine local cerebral metabolic rates for glucose (1CMRG1c) in 44 infants with spasms, in an attempt to define the neuroanatomical substrates that mediate these seizures. All infants were studied in the awake state during continuous electroencephalographic monitoring. The most consistent abnormality on PET, seen in 32 infants, was the symmetrical increase in 1CMRG1c in the lenticular nuclei, compared to age-matched normal infants (p less than 0.05). In 21 infants, even though the brain stem appeared to be visually more prominent compared to normal infants, statistically significant differences could not be demonstrated. Relative hypermetabolism of the lenticular nuclei (1) occurred irrespective of whether the spasms were cryptogenic or symptomatic, (2) was associated with focal cortical hypometabolism in 22 and focal cortical hypermetabolism in 5 of the 44 infants, and (3) was not characterized by any specific electroencephalographic abnormality during PET. These findings suggest that the lenticular nuclei may contribute to the pathophysiological state that predisposes to infantile spasms, and is consistent with the observation that spasms are clinically symmetrical even when focal cortical lesions are present. A scheme describing the neuronal circuitry likely to be involved in the generation of infantile spasms is proposed.