[Show abstract][Hide abstract] ABSTRACT: Background:
Reduced muscle strength is an independent risk factor for falls and related to postural instability in individuals with Parkinson's disease. The ability of resistance training to improve postural control still remains unclear.
To compare resistance training with balance training to improve postural control in people with Parkinson's disease.
40 patients with idiopathic Parkinson's disease (Hoehn&Yahr: 2.5-3.0) were randomly assigned into resistance or balance training (2x/week for 7 weeks). Assessments were performed at baseline, 8- and 12-weeks follow-up: primary outcome: Fullerton Advanced Balance (FAB) scale; secondary outcomes: center of mass analysis during surface perturbations, Timed-up-and-go-test, Unified Parkinson's Disease Rating Scale, Clinical Global Impression, gait analysis, maximal isometric leg strength, PDQ-39, Beck Depression Inventory. Clinical tests were videotaped and analysed by a second rater, blind to group allocation and assessment time.
32 participants (resistance training: n = 17, balance training: n = 15; 8 drop-outs) were analyzed at 8-weeks follow-up. No significant difference was found in the FAB scale when comparing the effects of the two training types (p = 0.14; effect size (Cohen's d) = -0.59). Participants from the resistance training group, but not from the balance training group significantly improved on the FAB scale (resistance training: +2.4 points, Cohen's d = -0.46; balance training: +0.3 points, Cohen's d = -0.08). Within the resistance training group, improvements of the FAB scale were significantly correlated with improvements of rate of force development and stride time variability. No significant differences were found in the secondary outcome measures when comparing the training effects of both training types.
The difference between resistance and balance training to improve postural control in people with Parkinson's disease was small and not significant with this sample size. There was weak evidence that freely coordinated resistance training might be more effective than balance training. Our results indicate a relationship between the enhancement of rate of force development and the improvement of postural control.
ClinicalTrials.gov ID: NCT02253563.
PLoS ONE 10/2015; 10(10):e0140584. DOI:10.1371/journal.pone.0140584 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Subthalamic nucleus deep brain stimulation (STN-DBS) therapy is an effective treatment for the motor symptoms of advanced Parkinson’s disease (PD). However, the underlying neurophysio- logical mechanisms for the motor improvement are uncertain. We utilised a simultaneous functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) neuroimaging approach to map cortical activation changes to motor performance in a PD patient “ON” and “OFF” STN-DBS.
Methods: The subject was a male (76y) with bilateral STN-DBS (unipolar stimulation at 160Hz and 3.3V). The experimental design consisted of an “OFF” followed by an “ON” stimulation condition. In both conditions, the subject performed a self-paced finger tapping (FT) task followed by a finger sequence (FS) task with his right hand in blocked design (30-s task, 30-s rest, repeated 5 times). During performance of the FT/FS task with the right hand, changes from rest in oxygenated (O2Hb) and deoxygenated hae- moglobin concentrations were measured by an fNIRS system (Oxymon MkIII, AMS) from 15 channels covering the contralateral cortical sensorimotor network. EEG signals from 256 channels (GES-300MR, EGI) were collected synchronously with fNIRS signals.
Results/Discussion: Concomitant with the improved FT/FS task performance, fNIRS results showed a reduction in contralateral cortical sensorimotor network activation (i.e. smaller and less var- iable increase in O2Hb over the 5 FT/FS task blocks) in the “ON” than “OFF” condition. The EEG results indicated that the mean power in the Beta and Gamma bands were lower in the “ON” than “OFF” condition. However, the mean power in the Delta band, which was approximately at the FT/FS movement frequency (1-3 Hz), was higher in the “ON” than “OFF” condition.
Conclusion: This case study showed that STN-DBS facilitates voluntary finger movement performance by a more efficient cortical activation pattern to perform the finger movement tasks, possibly by facilitating the voluntary frequency band (Delta) and suppressing the involuntary frequency bands (Beta/Gamma).
1st International Brain Stimulation Conference, Singapore; 03/2015
[Show abstract][Hide abstract] ABSTRACT: Background / Purpose:
The aim of this study was to identify if cross frequency coupling is present in Parkinson's disease (PD) patients during the ON state of deep brain stimulator (DBS). Also, to understand the influence of the DBS frequency on other frequency oscillations present in the brain of the PD patients. The source analysis method used here is the dynamic imaging of coherent sources (DICS) ( Gross et al . 2001 ) with a realistic boundary element method forward model ( Fuchs et al. 2002 ). Finally, to describe the cross frequency coupling in the identified sources using the measure frequency to frequency coupling ( Jirsa et al. 2013 ).
The source analysis revealed the networks influenced during the deep brain simulation in the PD patients. The existing frequency-frequency coupling revealed that this could be one reason in solving a larger puzzle of why deep brain stimulation affects only the involuntary and not the voluntary actions in the PD patients.
20th Annual Meeting of the Organization for Human Brain Mapping (OHBM) 2014; 08/2014
[Show abstract][Hide abstract] ABSTRACT: An effective mechanism in neuronal communication is oscillatory neuronal synchronization. The neuronal gamma-band (30-100 Hz) synchronization is associated with attention which is induced by a certain visual stimuli. Numerous studies have shown that the gamma-band activity is observed in the visual cortex. However, impact of different head modeling techniques and sensor types to localize gamma-band activity have not yet been reported. To do this, the brain activity was recorded using 306 magnetoencephalography (MEG) sensors, consisting of 102 magnetometers and 102 pairs of planar gradiometers (one measuring the derivative of the magnetic field along the latitude and the other along the longitude), and the data were analyzed with respect to time, frequency, and location of the strongest response. The spherical head models with a single-shell and overlapping spheres (local sphere) have been used as a forward model for calculating the external magnetic fields generated from the gamma-band activity. For each sensor type, the subject-specific frequency range of the gamma-band activity was obtained from the spectral analysis. The identified frequency range of interest with the highest gamma-band activity is then localized using a spatial-filtering technique known as dynamic imaging of coherent sources (DICS). The source analysis for all the subjects revealed that the gradiometer sensors which measure the derivative along the longitude, showed sources close to the visual cortex (cuneus) as compared to the other gradiometer sensors which measure the derivative along the latitude. However, using the magnetometer sensors, it was not possible to localize the sources in the region of interest. When comparing the two head models, the local-sphere model helps in localizing the source more focally as compared to the single-shell head model.
[Show abstract][Hide abstract] ABSTRACT: The most well-known non-invasive electric and magnetic field measurement modalities are the electroencephalography (EEG) and magnetoencephalography (MEG). The first aim of the study was to implement the recently developed realistic head model which uses an integrative approach for both the modalities. The second aim of this study was to find the network of coherent sources and the modes of interactions within this network during isometric contraction (ISC) at (15-30 Hz) in healthy subjects. The third aim was to test the effective connectivity revealed by both the modalities analyzing them separately and combined. The Welch periodogram method was used to estimate the coherence spectrum between the EEG and the electromyography (EMG) signals followed by the realistic head modelling and source analysis method dynamic imaging of coherent sources (DICS) to find the network of coherent sources at the individual peak frequency within the beta band in healthy subjects. The last step was to identify the effective connectivity between the identified sources using the renormalized partial directed coherence method. The cortical and sub-cortical network comprised of the primary sensory motor cortex (PSMC), secondary motor area (SMA), and the cerebellum (C). The cortical and sub-cortical network responsible for the isometric contraction was similar in both the modalities when analysing them separately and combined. The SNR was not significantly different between the two modalities separately and combined. However, the coherence values were significantly higher in the combined modality in comparison to each of the modality separately. The effective connectivity analysis revealed plausible additional connections in the combined modality analysis.
[Show abstract][Hide abstract] ABSTRACT: Owing to the recent advances in multi-modal data analysis, the aim of the present study was to analyze the functional network of the brain which remained the same during the eyes-open (EO) and eyes-closed (EC) resting task. The simultaneously recorded electroencephalogram (EEG) and magnetoencephalogram (MEG) were used for this study, recorded from five distinct cortical regions of the brain. We focused on the `alpha' functional network, corresponding to the individual peak frequency in the alpha band. The total data set of 120 seconds was divided into three segments of 18 seconds each, taken from start, middle, and end of the recording. This segmentation allowed us to analyze the evolution of the underlying functional network. The method of time-resolved partial directed coherence (tPDC) was used to assess the causality. This method allowed us to focus on the individual peak frequency in the `alpha' band (7-13 Hz). Because of the significantly higher power in the recorded EEG in comparison to MEG, at the individual peak frequency of the alpha band, results rely only on EEG. The MEG was used only for comparison. Our results show that different regions of the brain start to `disconnect' from one another over the course of time. The driving signals, along with the feedback signals between different cortical regions start to recede over time. This shows that, with the course of rest, brain regions reduce communication with each another.
[Show abstract][Hide abstract] ABSTRACT: Electroencephalography (EEG) and magnetoencephalography (MEG) are the two modalities for measuring neuronal dynamics at a millisecond temporal resolution. Different source analysis methods, to locate the dipoles in the brain from which these dynamics originate, have been readily applied to both modalities alone. However, direct comparisons and possible advantages of combining both modalities have rarely been assessed during voluntary movements using coherent source analysis. In the present study, the cortical and sub-cortical network of coherent sources at the finger tapping task frequency (2-4 Hz) and the modes of interaction within this network were analysed in 15 healthy subjects using a beamformer approach called the dynamic imaging of coherent sources (DICS) with subsequent source signal reconstruction and renormalized partial directed coherence analysis (RPDC). MEG and EEG data were recorded simultaneously allowing the comparison of each of the modalities separately to that of the combined approach. We found the identified network of coherent sources for the finger tapping task as described in earlier studies when using only the MEG or combined MEG+EEG whereas the EEG data alone failed to detect single sub-cortical sources. The signal-to-noise ratio (SNR) level of the coherent rhythmic activity at the tapping frequency in MEG and combined MEG+EEG data was significantly higher than EEG alone. The functional connectivity analysis revealed that the combined approach had more active connections compared to either of the modalities during the finger tapping (FT) task. These results indicate that MEG is superior in the detection of deep coherent sources and that the SNR seems to be more vital than the sensitivity to theoretical dipole orientation and the volume conduction effect in the case of EEG.
PLoS ONE 03/2014; 9(3):e91441. DOI:10.1371/journal.pone.0091441 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: A new technique for discrimination of Parkinson tremor from essential tremor is presented in this paper. This technique is based on Statistical Signal Characterization (SSC) of the spectrum of the accelerometer signal. The data has been recorded for diagnostic purposes in the Department of Neurology of the University of Kiel, Germany. Two sets of data are used. The training set, which consists of 21 essential-tremor (ET) subjects and 19 Parkinson-disease (PD) subjects, is used to obtain the threshold value of the classification factor differentiating between the two subjects. The test data set, which consists of 20 ET and 20 PD subjects, is used to test the technique and evaluate its performance. Three of twelve newly derived SSC parameters show good discrimination results. Specific results of those three parameters on training data and test data are shown in detail. A linear combination of the effects of those parameters on the discrimination results is also included. A total discrimination accuracy of 90% is obtained.
[Show abstract][Hide abstract] ABSTRACT: The concept of focal epilepsies includes a seizure origin in brain regions with hyper synchronous activity (epileptogenic zone and seizure onset zone) and a complex epileptic network of different brain areas involved in the generation, propagation, and modulation of seizures. The purpose of this work was to study functional and effective connectivity between regions involved in networks of epileptic seizures. The beginning and middle part of focal seizures from ictal surface EEG data were analyzed using dynamic imaging of coherent sources (DICS), an inverse solution in the frequency domain which describes neuronal networks and coherences of oscillatory brain activities. The information flow (effective connectivity) between coherent sources was investigated using the renormalized partial directed coherence (RPDC) method. In 8/11 patients, the first and second source of epileptic activity as found by DICS were concordant with the operative resection site; these patients became seizure free after epilepsy surgery. In the remaining 3 patients, the results of DICS / RPDC calculations and the resection site were discordant; these patients had a poorer post-operative outcome. The first sources as found by DICS were located predominantly in cortical structures; subsequent sources included some subcortical structures: thalamus, Nucl. Subthalamicus and cerebellum. DICS seems to be a powerful tool to define the seizure onset zone and the epileptic networks involved. Seizure generation seems to be related to the propagation of epileptic activity from the primary source in the seizure onset zone, and maintenance of seizures is attributed to the perpetuation of epileptic activity between nodes in the epileptic network. Despite of these promising results, this proof of principle study needs further confirmation prior to the use of the described methods in the clinical praxis.
PLoS ONE 10/2013; 8(10):e78422. DOI:10.1371/journal.pone.0078422 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Spatial attention is a lateralized feature of the human brain. Whereas the role of cortical areas of the nondominant hemisphere on spatial attention has been investigated in detail, the impact of the BG, and more precisely the subthalamic nucleus, on signs and symptoms of spatial attention is not well understood. Here we used unilateral deep brain stimulation of the subthalamic nucleus to reversibly, specifically, and intraindividually modify the neuronal BG outflow and its consequences on signs and symptoms of visuospatial attention in patients suffering from Parkinson's disease. We tested 13 patients with Parkinson's disease and chronic deep brain stimulation in three stimulation settings: unilateral right and left deep brain stimulation of the subthalamic nucleus as well as bilateral deep brain stimulation of the subthalamic nucleus. In all three stimulation settings, the patients viewed a set of pictures while an eye-tracker system recorded eye movements. During the exploration of the visual stimuli, we analyzed the time spent in each visual hemispace, as well as the number, duration, amplitude, peak velocity, acceleration peak, and speed of saccades. In the unilateral left-sided stimulation setting, patients show a shorter ipsilateral exploration time of the extrapersonal space, whereas number, duration, and speed of saccades did not differ between the different stimulation settings. These results demonstrated reduced visuospatial attention toward the side contralateral to the right subthalamic nucleus that was not being stimulated in a unilateral left-sided stimulation. Turning on the right stimulator, the reduced visuospatial attention vanished. These results support the involvement of the subthalamic nucleus in modulating spatial attention. Therefore, the subthalamic nucleus is part of the subcortical network that subserves spatial attention.
[Show abstract][Hide abstract] ABSTRACT: Simultaneous recording of electroencephalogram (EEG) and electromyogram (EMG) with magnetic resonance imaging (MRI) provides great potential for studying human brain activity with high temporal and spatial resolution. But, due to the MRI, the recorded signals are contaminated with artifacts. The correction of these artifacts is important to use these signals for further spectral analysis. The coherence can reveal the cortical representation of peripheral muscle signal in particular motor tasks, e.g. finger movements. The artifact correction of these signals was done by two different algorithms the Brain vision analyzer (BVA) and the Matlab FMRIB plug-in for EEGLAB. The Welch periodogram method was used for estimating the cortico-muscular coherence. Our analysis revealed coherence with a frequency of 5Hz in the contralateral side of the brain. The entropy is estimated for the calculated coherence to get the distribution of coherence in the scalp. The significance of the paper is to identify the optimal algorithm to rectify the MR artifacts and as a first step to use both these signals EEG and EMG in conjunction with MRI for further studies.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 07/2013; 2013:4811-4814. DOI:10.1109/EMBC.2013.6610624
[Show abstract][Hide abstract] ABSTRACT: Brain activity can be measured using different modalities. Since most of the modalities tend to complement each other, it seems promising to measure them simultaneously. In to be presented research, the data recorded from Functional Magnetic Resonance Imaging (fMRI) and Near Infrared Spectroscopy (NIRS), simultaneously, are subjected to causality analysis using time-resolved partial directed coherence (tPDC). Time-resolved partial directed coherence uses the principle of state space modelling to estimate Multivariate Autoregressive (MVAR) coefficients. This method is useful to visualize both frequency and time dynamics of causality between the time series. Afterwards, causality results from different modalities are compared by estimating the Spearman correlation. In to be presented study, we used directionality vectors to analyze correlation, rather than actual signal vectors. Results show that causality analysis of the fMRI correlates more closely to causality results of oxy-NIRS as compared to deoxy-NIRS in case of a finger sequencing task. However, in case of simple finger tapping, no clear difference between oxy-fMRI and deoxy-fMRI correlation is identified.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 07/2013; 2013:2628-2631. DOI:10.1109/EMBC.2013.6610079
[Show abstract][Hide abstract] ABSTRACT: The aim of this study was to find the cortical and sub-cortical network responsible for the sensory evoked coherence in healthy subjects during electrical stimulation of right median nerve at wrist. The multitaper method was used to estimate the power and coherence spectrum followed by the source analysis method dynamic imaging of coherent sources (DICS) to find the highest coherent source for the basic frequency 3Hz and the complete cortical and sub-cortical network responsible for the sensory evoked coherence in healthy subjects. The highest coherent source for the basic frequency was in the posterior parietal cortex for all the subjects. The cortical and sub-cortical network comprised of the primary sensory motor cortex (SI), secondary sensory motor cortex (SII), frontal cortex and medial pulvinar nucleus in the thalamus. The cortical and sub-cortical network responsible for the sensory evoked coherence was found successfully with a 64-channel EEG system. The sensory evoked coherence is involved with a thalamo-cortical network in healthy subjects.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 07/2013; 2013:5369-5372. DOI:10.1109/EMBC.2013.6610762
[Show abstract][Hide abstract] ABSTRACT: Various source localization techniques have indicated the generators of each identifiable component of movement-related cortical potentials, since the discovery of the surface negative potential prior to self-paced movement by Kornhuber and Decke. Readiness potentials and fields preceding self-paced finger movements were recorded simultaneously using multichannel electroencephalography (EEG) and magnetoencephalography (MEG) from five healthy subjects. The cortical areas involved in this paradigm are the supplementary motor area (SMA) (bilateral), pre-SMA (bilateral), and contralateral motor area of the moving finger. This hypothesis is tested in this paper using the dipole source analysis independently for only EEG, only MEG, and both combined. To localize the sources, the forward problem is first solved by using the boundary-element method for realistic head models and by using a locally-fitted-sphere approach for spherical head models consisting of a set of connected volumes, typically representing the scalp, skull, and brain. In the source reconstruction it is to be expected that EEG predominantly localizes radially oriented sources while MEG localizes tangential sources at the desired region of the cortex. The effect of MEG on EEG is also observed when analyzing both combined data. When comparing the two head models, the spherical and the realistic head models showed similar results. The significant points for this study are comparing the source analysis between the two modalities (EEG and MEG) so as to assure that EEG is sensitive to mostly radially orientated sources while MEG is only sensitive to only tangential sources, and comparing the spherical and individual head models.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 07/2013; 2013:1362-1365. DOI:10.1109/EMBC.2013.6609762