Give me a sign: decoding four complex hand gestures based on high-density ECoG

The increasing understanding of human brain functions makes it possible to directly interact with the brain for therapeutic purposes. Implantable brain computer interfaces promise to replace or restore motor functions in patients with partial or complete paralysis. We postulate that neuronal states associated with gestures, as they are used in the finger spelling alphabet of sign languages, provide an excellent signal for implantable brain computer interfaces to restore communication. To test this, we evaluated decodability of four gestures using high-density electrocorticography in two participants. The electrode grids were located subdurally on the hand knob area of the sensorimotor cortex covering a surface of 2.5–5.2 cm². Using a pattern-matching classification approach four types of hand gestures were classified based on their pattern of neuronal activity. In the two participants the gestures were classified with 97 and 74 % accuracy. The high frequencies (>65 Hz) allowed for the best classification results. This proof-of-principle study indicates that the four gestures are associated with a reliable and discriminable spatial representation on a confined area of the sensorimotor cortex. This robust representation on a small area makes hand gestures an interesting control feature for an implantable BCI to restore communication for severely paralyzed people.     

Blood oxygenation level dependent contrast resting state networks are relevant to functional activity in the neocortical sensorimotor system

The relevance of correlations between blood oxygenation level dependent (BOLD) signal changes across the brain acquired at rest (resting state networks, or RSN) to functional networks was tested using two quantitative criteria: (1) the localisation of major RSN correlation clusters and the task-related maxima defined in BOLD fMRI signal changes from the same subjects; and (2) the relative hemispheric lateralisation (LI) of BOLD fMRI signal changes in sensorimotor cortex. RSN were defined on the basis of signal changes correlated with that of a “seed” voxel in the primary sensorimotor cortex. We found a generally close spatial correspondence between clusters of correlated BOLD signal change in RSN and activation maxima associated with hand movement. Conventional BOLD fMRI during active hand movement showed the expected wide variation in relative hemispheric lateralisation of LI for sensorimotor cortex across the subjects. There was a good correlation between LIs for the active hand movement task and the RSN (r=0.74, p<0.001). The RSN thus define anatomically relevant regions of motor cortex and change with functionally relevant variations in hemispheric lateralisation of sensorimotor cortical interactions with hand movement.     

Online binary decision decoding using functional near-infrared spectroscopy for the development of brain–computer interface

In this paper, a functional near-infrared spectroscopy (fNIRS)-based online binary decision decoding framework is developed. Fourteen healthy subjects are asked to mentally make “yes” or “no” decisions in answers to the given questions. For obtaining “yes” decoding, the subjects are asked to perform a mental task that causes a cognitive load on the prefrontal cortex, while for making “no” decoding, they are asked to relax. Signals from the prefrontal cortex are collected using continuous-wave near-infrared spectroscopy. It is observed and verified, using the linear discriminant analysis (LDA) and the support vector machine (SVM) classifications, that the cortical hemodynamic responses for making a “yes” decision are distinguishable from those for making a “no” decision. Using mean values of the changes in the concentration of hemoglobin as features, binary decisions are classified into two classes, “yes” and “no,” with an average classification accuracy of 74.28 % using LDA and 82.14 % using SVM. These results demonstrate and suggest the feasibility of fNIRS for a brain–computer interface.     

Whole-Brain Haemodynamic After-Effects of 1-Hz Magnetic Stimulation of the Posterior Superior Temporal Cortex During Action Observation

The posterior superior temporal sulcus (pSTS) is active when observing biological motion. We investigated the functional connections of the pSTS node within the action observation network by measuring the after-effect of focal repetitive transcranial magnetic stimulation (rTMS) with whole-brain functional magnetic resonance imaging (fMRI). Participants received 1-Hz rTMS over the pSTS region for 10 min and underwent fMRI immediately after. While scanned, they were shown short video clips of a hand grasping an object (grasp clips) or moving next to it (control clips). rTMS–fMRI was repeated for four consecutive blocks. In two blocks we stimulated the left pSTS region and in the other two the right pSTS region. For each side TMS was applied with an effective intensity (95 % of motor threshold) or with ineffective intensity (50 % of motor threshold). Brain regions showing interactive effects of (clip type) × (TMS intensity) were identified in the lateral temporo-occipital cortex, in the anterior intraparietal region and in the ventral premotor cortex. Remote effects of rTMS were mostly limited to the stimulated hemisphere and consisted in an increase of blood oxygen level-dependent responses to grasp clips compared to control clips. We show that the pSTS occupies a pivotal relay position during observation of goal-directed actions.     

Changes in the functional MR signal in motor and non-motor areas during intermittent fatiguing hand exercise

The aim of this study was to determine whether there were significant changes in the time course of the functional magnetic resonance imaging (fMRI) signal in motor and non-motor regions of both cerebral hemispheres during a unilateral fatiguing exercise of the hand. Twelve subjects performed a submaximal (30%) intermittent fatiguing handgrip exercise (3 s grip, 2 s release, left hand) for ∼9 min during fMRI scanning. Regression analysis was used to measure changes in fMRI signal from primary sensorimotor cortex (SM1), premotor cortex and visual cortex (V1) in both hemispheres. Force declined to 77 ± 3.6% of prefatigue maximal force (P < 0.05). The fMRI signal from SM1 contralateral to the fatiguing hand increased by 1.2 ± 0.5% of baseline (P < 0.05). The fMRI signal from the ipsilateral SM1 did not change significantly. Premotor cortex showed a similar pattern but did not reach significance. The signal from V1 increased significantly for both hemispheres (contralateral 1.3 ± 0.9%, ipsilateral 1.5 ± 0.9% of baseline and P < 0.05). During the performance of a unimanual, submaximal fatiguing exercise there is an increase in activation of motor and non-motor regions. The results are in keeping with the notion of an increase in sensory processing and corticomotor drive during fatiguing exercise to maintain task performance as fatigue develops.     

Cortical effect and functional recovery by the electromyography-triggered neuromuscular stimulation in chronic stroke patients

We investigated the effect of electromyography (EMG)-triggered neuromuscular electrical stimulation (NMES; EMG-stim) on functional recovery of the hemiparetic hand and the related cortical activation pattern in chronic stroke patients. We enrolled 14 stroke patients, who were randomly assigned to the EMG-stim (n=7) or the control groups (n=7). The EMG-stim was applied to the wrist extensor of the EMG-stim group for two sessions (30min/session) a day, five times per week for 10 weeks. Four functional tests (box and block, strength, the accuracy index, and the on/offset time of muscle contraction) and functional MRI (fMRI) were performed before and after treatment. fMRI was measured at 1.5T in parallel with timed finger flexion-extension movements at a fixed rate. Following treatment, the EMG-stim group showed a significant improvement in all functional tests. The main cortical activation change with such functional improvement was shifted from the ipsilateral sensorimotor cortex (SMC) to the contralateral SMC. We demonstrated that 10-week EMG-stim can induce functional recovery and change of cortical activation pattern in the hemiparetic hand of chronic stroke patients.     

基于表面肌电信号的手势识别与分析

目的 研究利用前臂及手部表面肌电( surface electromyography,sEMG)信号进行手势识别的方法,以及不同 手势下拇指、食指的关节角度,探讨 sEMG 信号控制外骨骼手的可行性。 方法 采集 20 名健康右利手受试者右侧 前臂及手部 6 块肌肉 sEMG 信号。 提取 sEMG 信号的时域特征值,对比人工神经网络( artificial neural network, ANN)、K-近邻(K-nearest neighbor, KNN)、决策树(decision tree, DT)、随机森林( random forest, RF)和支持向量机(support vector machine, SVM)等多种分类器对 6 种日常手势进行识别。 同时,采用 Vicon 摄像机跟踪系统捕捉右手拇指、食指运动轨迹,计算拇指、食指关节角度。 结果 利用前臂及手部 sEMG 信号可以实现 6 种手势的模式识别,其中 ANN 分类器的分类预测效果最好,测试集预测精度可达 97. 9% ,Kappa 系数可达 0. 975。 同时,计算得到不同手势下拇指、食指的关节角度,并进行不同手势下关节角度相关性分析。 结论 利用前臂及手部 sEMG 信号进 行手势识别,能够实现具有几乎完全一致的分类预测结果。 研究结果证明了 sEMG 信号手势识别应用于外骨骼手 控制的可行性。     

The enhanced cortical activation induced by transcranial direct current stimulation during hand movements

The aim of this study is to evaluate whether tDCS applied on the primary motor cortex (M1) in company with hand movements could enhance cortical activation, using functional MRI (fMRI). Twelve right-handed normal subjects were recruited. Real tDCS and sham tDCS with hand movements were applied during fMRI scanning. Subjects performed grasp-release hand movements at a metronome-guided frequency of 1Hz, while direct current with 1.0mA was delivered to the primary motor cortex. The averaged cortical map and the intensity index were compared between real tDCS with hand movements and sham tDCS with hand movements. Our result showed that cortical activation on the primary sensorimotor cortex was observed under both of two conditions; real tDCS with hand movements and sham tDCS with hand movements. Voxel count and peak intensity were 365.10±227.23 and 5.66±1.97, respectively, in the left primary sensorimotor cortex during real tDCS with right hand movements; in contrast, those were 182.20±117.88 and 4.12±0.88, respectively, during sham tDCS with right hand movements. Significant differences in voxel count and peak intensity were observed between real tDCS and sham tDCS (p<0.05). We found that anodal tDCS application during motor task enhanced cortical activation on the underlying targeted motor cortex, compared with the same motor task without tDCS. Therefore, it seemed that tDCS induced more cortical activity and modulated brain function when concurrently applied with motor task.     

Segmentation, Feature Extraction, and Multiclass Brain Tumor Classification

Multiclass brain tumor classification is performed by using a diversified dataset of 428 post-contrast T1-weighted MR images from 55 patients. These images are of primary brain tumors namely astrocytoma (AS), glioblastoma multiforme (GBM), childhood tumor-medulloblastoma (MED), meningioma (MEN), secondary tumor-metastatic (MET), and normal regions (NR). Eight hundred fifty-six regions of interest (SROIs) are extracted by a content-based active contour model. Two hundred eighteen intensity and texture features are extracted from these SROIs. In this study, principal component analysis (PCA) is used for reduction of dimensionality of the feature space. These six classes are then classified by artificial neural network (ANN). Hence, this approach is named as PCA-ANN approach. Three sets of experiments have been performed. In the first experiment, classification accuracy by ANN approach is performed. In the second experiment, PCA-ANN approach with random sub-sampling has been used in which the SROIs from the same patient may get repeated during testing. It is observed that the classification accuracy has increased from 77 to 91 %. PCA-ANN has delivered high accuracy for each class: AS—90.74 %, GBM—88.46 %, MED—85 %, MEN—90.70 %, MET—96.67 %, and NR—93.78 %. In the third experiment, to remove bias and to test the robustness of the proposed system, data is partitioned in a manner such that the SROIs from the same patient are not common for training and testing sets. In this case also, the proposed system has performed well by delivering an overall accuracy of 85.23 %. The individual class accuracy for each class is: AS—86.15 %, GBM—65.1 %, MED—63.36 %, MEN—91.5 %, MET—65.21 %, and NR—93.3 %. A computer-aided diagnostic system comprising of developed methods for segmentation, feature extraction, and classification of brain tumors can be beneficial to radiologists for precise localization, diagnosis, and interpretation of brain tumors on MR images.     

High-Resolution fMRI of Auditory Cortical Map Changes in Unilateral Hearing Loss and Tinnitus

Animal models of hearing loss and tinnitus observe pathological neural activity in the tonotopic frequency maps of the primary auditory cortex. Here, we applied ultra high-field fMRI at 7 T to test whether human patients with unilateral hearing loss and tinnitus also show altered functional activity in the primary auditory cortex. The high spatial resolution afforded by 7 T imaging allowed tonotopic mapping of primary auditory cortex on an individual subject basis. Eleven patients with unilateral hearing loss and tinnitus were compared to normal-hearing controls. Patients showed an over-representation and hyperactivity in a region of the cortical map corresponding to low frequencies sounds, irrespective of the hearing loss and tinnitus range, which in most cases affected higher frequencies. This finding of hyperactivity in low frequency map regions, irrespective of hearing loss range, is consistent with some previous studies in animal models and corroborates a previous study of human tinnitus. Thus these findings contribute to accumulating evidence that gross cortical tonotopic map reorganization is not a causal factor of tinnitus.     

Effective Connectivity of Cortical Sensorimotor Networks During Finger Movement Tasks: A Simultaneous fNIRS,fMRI, EEG Study

Recently, interest has been growing to understand the underlying dynamic directional relationship between simultaneously activated regions of the brain during motor task performance. Such directionality analysis (or effective connectivity analysis), based on non-invasive electrophysiological (electroencephalography—EEG) and hemodynamic (functional near infrared spectroscopy—fNIRS; and functional magnetic resonance imaging—fMRI) neuroimaging modalities can provide an estimate of the motor task-related information flow from one brain region to another. Since EEG, fNIRS and fMRI modalities achieve different spatial and temporal resolutions of motor-task related activation in the brain, the aim of this study was to determine the effective connectivity of cortico-cortical sensorimotor networks during finger movement tasks measured by each neuroimaging modality. Nine healthy subjects performed right hand finger movement tasks of different complexity (simple finger tapping-FT, simple finger sequence-SFS, and complex finger sequence-CFS). We focused our observations on three cortical regions of interest (ROIs), namely the contralateral sensorimotor cortex (SMC), the contralateral premotor cortex (PMC) and the contralateral dorsolateral prefrontal cortex (DLPFC). We estimated the effective connectivity between these ROIs using conditional Granger causality (GC) analysis determined from the time series signals measured by fMRI (blood oxygenation level-dependent-BOLD), fNIRS (oxygenated-O₂Hb and deoxygenated-HHb hemoglobin), and EEG (scalp and source level analysis) neuroimaging modalities. The effective connectivity analysis showed significant bi-directional information flow between the SMC, PMC, and DLPFC as determined by the EEG (scalp and source), fMRI (BOLD) and fNIRS (O₂Hb and HHb) modalities for all three motor tasks. However the source level EEG GC values were significantly greater than the other modalities. In addition, only the source level EEG showed a significantly greater forward than backward information flow between the ROIs. This simultaneous fMRI, fNIRS and EEG study has shown through independent GC analysis of the respective time series that a bi-directional effective connectivity occurs within a cortico-cortical sensorimotor network (SMC, PMC and DLPFC) during finger movement tasks.     

Robust localization of the contralateral precentral gyrus in hemiparetic patients using the unimpaired ipsilateral hand: a clinical functional magnetic resonance imaging protocol

Tumor related contralateral motor deficits complicate preoperative functional magnetic resonance imaging (fMRI). In plegic patients the localization of the sensorimotor cortex is often impossible. In this context we developed a clinical fMRI protocol dedicated to patients with motor deficits using the unaffected ipsilateral hand. Based on the hypothesis that selfpaced finger movements recruit more and larger neuronal populations with rising task complexity, different motor tasks were tested regarding ipsilateral localization in ten right handed volunteers. Complex finger opposition localized the ipsilateral premotor cortex (Brodman area 6) robustly and was introduced to preoperative fMRI in hemiparetic patients as functional landmark to identify the precentral gyrus on the tumors side. Additional contralateral automated tactile stimulation localized the primary somatosensory cortex and completed the protocol.     

Effect of fuzzy partitioning in Crohn’s disease classification: a neuro-fuzzy-based approach

Crohn’s disease (CD) diagnosis is a tremendously serious health problem due to its ultimately effect on the gastrointestinal tract that leads to the need of complex medical assistance. In this study, the backpropagation neural network fuzzy classifier and a neuro-fuzzy model are combined for diagnosing the CD. Factor analysis is used for data dimension reduction. The effect on the system performance has been investigated when using fuzzy partitioning and dimension reduction. Additionally, further comparison is done between the different levels of the fuzzy partition to reach the optimal performance accuracy level. The performance evaluation of the proposed system is estimated using the classification accuracy and other metrics. The experimental results revealed that the classification with level-8 partitioning provides a classification accuracy of 97.67 %, with a sensitivity and specificity of 96.07 and 100 %, respectively.     

Thyroid Nodule Recognition Based on Feature Selection and Pixel Classification Methods

Statistical approach is a valuable way to describe texture primitives. The aim of this study is to design and implement a classifier framework to automatically identify the thyroid nodules from ultrasound images. Using rigorous mathematical foundations, this article focuses on developing a discriminative texture analysis method based on texture variations corresponding to four biological areas (normal thyroid, thyroid nodule, subcutaneous tissues, and trachea). Our research follows three steps: automatic extraction of the most discriminative first-order statistical texture features, building a classifier that automatically optimizes and selects the valuable features, and correlating significant texture parameters with the four biological areas of interest based on pixel classification and location characteristics. Twenty ultrasound images of normal thyroid and 20 that present thyroid nodules were used. The analysis involves both the whole thyroid ultrasound images and the region of interests (ROIs). The proposed system and the classification results are validated using the receiver operating characteristics which give a better overall view of the classification performance of methods. It is found that the proposed approach is capable of identifying thyroid nodules with a correct classification rate of 83 % when whole image is analyzed and with a percent of 91 % when the ROIs are analyzed.     

Where language meets meaningful action: a combined behavior and lesion analysis of aphasia and apraxia

It is debated how language and praxis are co-represented in the left hemisphere (LH). As voxel-based lesion-symptom mapping in LH stroke patients with aphasia and/or apraxia may contribute to this debate, we here investigated the relationship between language and praxis deficits at the behavioral and lesion levels in 50 sub-acute stroke patients. We hypothesized that language and (meaningful) action are linked via semantic processing in Broca’s region. Behaviorally, half of the patients suffered from co-morbid aphasia and apraxia. While 24 % (n = 12) of all patients exhibited aphasia without apraxia, apraxia without aphasia was rare (n = 2, 4 %). Left inferior frontal, insular, inferior parietal, and superior temporal lesions were specifically associated with deficits in naming, reading, writing, or auditory comprehension. In contrast, lesions affecting the left inferior frontal gyrus, premotor cortex, and the central region as well as the inferior parietal lobe were associated with apraxic deficits (i.e., pantomime, imitation of meaningful and meaningless gestures). Thus, contrary to the predictions of the embodied cognition theory, lesions to sensorimotor and premotor areas were associated with the severity of praxis but not language deficits. Lesions of Brodmann area (BA) 44 led to combined apraxic and aphasic deficits. Data suggest that BA 44 acts as an interface between language and (meaningful) action thereby supporting parcellation schemes (based on connectivity and receptor mapping) which revealed a BA 44 sub-area involved in semantic processing.     

Increase of the ornithine decarboxylase/polyamine system and transglutaminase upregulation in the spinal cord of aged rats

The adult mammalian brain has the capacity of reorganising its neural connections in response to lesions/modifications of the peripheral and central nervous system. We show in vivo, using functional magnetic resonance imaging (fMRI), that in paraplegics the lower-limb sensorimotor cortex is invaded by the arm representation. This functional reshaping appears to be reversible. Indeed, surgical transfer of the ulnar nerve to the ipsilateral quadriceps and hip muscles allowed their contraction in a paraplegic patient. During fMRI, these voluntary movements activated the hip and thigh representation in sensorimotor cortex. We suggest that the functional recovery of the lower-limb functional maps might have been driven by the restored somatosensory inputs from the reactivated periphery. The voluntary movements of the lower-limbs are regained through the 're-awakening' of the corresponding sensorimotor cortex.     

Hemispheric asymmetry in cerebrovascular reactivity of the human primary motor cortex: an in vivo study at 7 T

Current functional MRI (fMRI) approaches assess underlying neuronal activity through monitoring the related local variations in cerebral blood oxygenation, blood volume and blood flow. This vascular response is likely to vary across brain regions and across individuals, depending on the composition of the local vascular bed and on the vascular capacity to dilate. The most widely used technique uses the blood oxygen level dependent (BOLD) fMRI signal, which arises from a complex combination of all of these factors. The model of handedness provides a case where one brain region (dominant motor cortex) is known to have a stronger BOLD response over another (non‐dominant motor cortex) during hand motor task performance. We predict that this is accompanied by a higher vascular reactivity in the dominant motor cortex, when compared with the non‐dominant motor cortex. Precise measurement of end‐tidal CO₂ and a novel sinusoidal CO₂ respiratory challenge were combined with the high sensitivity and finer spatial resolution available for fMRI at 7 T to measure BOLD cerebrovascular reactivity (CVR) in eight healthy male participants. BOLD CVR was compared between the left (dominant) and right (non‐dominant) primary motor cortices of right‐handed adults. Hemispheric asymmetry in vascular reactivity was predicted and observed in the primary motor cortex (left CVR = 0.60 ± 0.15%/mm Hg; right CVR = 0.47 ± 0.08%/mm Hg; left CVR > right CVR, P = 0.04), the first reported evidence of such a vascular difference. These findings demonstrate a cerebral vascular asymmetry between the left and right primary motor cortex. The origin of this asymmetry largely arises from the contribution of large draining veins. This work has implications for future motor laterality studies that use BOLD, and it is also suggestive of a vascular plasticity in the human primary motor cortex. Copyright © 2015 John Wiley & Sons, Ltd.     

The effect of transcranial direct current stimulation on the cortical activation by motor task in the human brain: An fMRI study

Objectives: We attempted to evaluate whether cortical activation resulting from hand movements is changed by transcranial direct current stimulation (tDCS) applied on the primary motor cortex for the hand in the human brain, using functional MRI (fMRI). Methods: Fourteen normal subjects were recruited; subjects were randomly assigned to either the tDCS group (n = 7) or the sham group (n = 7). fMRI was performed with hand grasp-release movements at 1 Hz before and after 20 min of intervention (the tDCS group: anodal tDCS, the sham group: sham stimulation). Results: The activation of the tDCS underlying primary sensorimotor cortex (SM1) was significantly increased in the tDCS group (p < 0.05). By contrast, the SM1 was significantly decreased in the sham group in terms of the voxel count and intensity (p < 0.05). No subjects complained of any adverse symptoms or signs. Conclusion: We demonstrated that anodal tDCS increased the cortical excitability of the underlying motor cortex in the human brain. It seems that tDCS is an effective modality to modulate brain function.     

Comprehensive Functional Mapping Scheme for Non-Invasive Primary Sensorimotor Cortex Mapping

We introduce a novel multimodal scheme for primary sensorimotor hand area (SM1ha) mapping integrating multiple functional indicators from functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). Ten right-handed healthy subjects (19–33 years; 5 females, 5 males) and four patients (24–64 years; 2 females, 2 males) suffering from space-occupying brain lesion close to the central sulcus were studied. Functional indicators of the SM1ha were obtained from block-design fMRI motor protocol, and six MEG protocols: somatosensory evoked fields to electrical median-nerve stimulation, mu-rhythm suppression (~10 and ~20 Hz), corticomuscular coherence, and corticokinematic coherence with and without finger contacts. To assess the spatial spread of the functional indicators, their coordinates were subjected to principal component analysis to produce a centered ellipsoid with axis along principal components. Five to seven functional indicators were obtained for each participant. In all participants, the ellipsoid co-localized with the anatomical SM1ha. In healthy subjects, 50–100 % of functional indicators were located within 10 mm from the center of the ellipsoid. In patients, 17–100 % of functional indicators were located within 10 mm from the center of the ellipsoid. In conclusion, the multimodal scheme proposed led to a functional mapping of SM1ha that co-localized with anatomical SM1ha in all participants. The spread of the SM1ha functional indicators in some patients with brain lesions highlights the potential benefit of the proposed multimodal approach to assess the reliability of the non-invasive SM1ha mapping.     

Association Between the Basal Ganglia and Large-Scale Brain Networks in Epilepsy

Epilepsy may affect connectivity between the putamen and cortex even during the resting state. Putamen is part of the basal ganglia resting state network (BG-RSN) which is anti-correlated with the default mode network (DMN) in healthy subjects. Therefore, we aimed at studying the functional brain connectivity (FC) of the putamen with the cortical areas engaged in the DMN as well as with the primary somatomotor cortex which is a cortical region engaged in the BG-RSN. We compared the data obtained in patients with epilepsy with that in healthy controls (HC). Functional magnetic resonance imaging (fMRI) was performed in 10 HC and 24 patients with epilepsy: 14 patients with extratemporal epilepsy (PE) and 10 patients with temporal epilepsy (PT). Resting state fMRI data was obtained using the 1.5 T Siemens Symphony scanner. The Group ICA of fMRI Toolbox (GIFT) program was used for independent component analysis. The component representing the DMN was chosen according to a spatial correlation with a mask typical for DMN. The FC between the putamen and the primary somatomotor cortex was studied to assess the connectivity of the putamen within the BG-RSN. A second-level analysis was calculated to evaluate differences among the groups using SPM software. In patients with epilepsy as compared to HC, the magnitude of anti-correlation between the putamen and brain regions engaged in the DMN was significantly lower. In fact, the correlation changed the connectivity direction from negative in HC to positive in PE and PT. The disturbed FC of the BG in patients with epilepsy as compared with HC was further illustrated by a significant decrease in connectivity between the left/right putamen and the left/right somatomotor cortex, i.e. between regions that are engaged in the BG-RSN. The FC between the putamen and the cortex is disturbed in patients with epilepsy. This may reflect an altered function of the BG in epilepsy.