Functional imaging of stroke recovery: an ecological review from a neural network perspective with an emphasis on motor systems

Association of TMS-EEG interhemispheric imbalance with upper limb motor impairment in chronic stroke patients: An exploratory study

OBJECTIVE

We aimed to investigate the involvement of interhemispheric cortical dynamics as measured by combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) in recovery of upper limb (UL) motor functions in chronic stroke patients.

METHODS

Ten patients with a history of single ischemic chronic stroke were enrolled (4F, 63.8 ± 9.9 years). Each patient underwent TMS-EEG recordings to evaluate interhemispheric cortical dynamics as well as a reaching task recorded with inertial measurement units, and a series of clinical assessments. TMS-EEG neurophysiological data were analysed considering spatiotemporal, power response, and interhemispheric balance (IHB) dynamics.

RESULTS

We found that IHB index (IHBi) and low-frequency power (LFP) (4-13 Hz) in the affected hemisphere were associated with the degree of UL impairment.

CONCLUSION

Increased IHBi due to stroke is an unfavourable factor of UL' functions. Similarly, LFP of both hemispheres is strongly correlated with clinical and kinematic outcomes.

SIGNIFICANCE

TMS-EEG biomarkers of interhemispheric unbalance could be used to estimate functional recovery and drive tailored neuromodulation and neurorehabilitation approaches.

Relationship Between Ipsilesional Upper Extremity Motor Function and Corpus Callosum Integrity in Patients With Unilateral Stroke: A Diffusion Tensor Imaging Study

This study aims to investigate the relationship between ipsilesional upper extremity (UE) motor function and the integrity of the subregions of the corpus callosum in hemiparetic stroke patients with motor deficits of the dominant or non-dominant ipsilesional side. Twenty participants with unilateral UE deficits after stroke were included. Each of the 10 participants had lesions on the left and right sides. The ipsilesional UE function was assessed with the Jebsen-Taylor hand function test (JHFT), the 9-hole peg test (9HPT), and grip and pinch strength tests. Fractional anisotropy (FA) was calculated for the integrity of the 5 subregions of the corpus callosum. Pearson's correlation analysis was conducted to investigate the relationship between UE function and the integrity of the callosal subregions. The results of JHFT and 9HPT showed a significant correlation with the FA value of the corpus callosum I projecting to the frontal lobe in the left lesion group (p < 0.05). There was no correlation between the ipsilesional UE motor function and the FA value of the ulnar subregion in the right lesion group (p > 0.05). These results showed that the motor deficits of the ipsilesional UE correlated with the integrity of callosal fiber projection to the prefrontal area when the ipsilesional side was non-dominant.

General principles of brain electromagnetic rhythmic oscillations and implications for neuroplasticity

Neuro-plasticity describes the ability of the brain in achieving novel functions, either by transforming its internal connectivity, or by changing the elements of which it is made, meaning that, only those changes, that affect both structural and functional aspects of the system, can be defined as "plastic." The concept of plasticity can be applied to molecular as well as to environmental events that can be recognized as the basic mechanism by which our brain reacts to the internal and external stimuli. When considering brain plasticity within a clinical context-that is the process linked with changes of brain functions following a lesion- the term "reorganization" is somewhat synonymous, referring to the specific types of structural/functional modifications observed as axonal sprouting, long-term synaptic potentiation/inhibition or to the plasticity related genomic responses. Furthermore, brain rewires during maturation, and aging thus maintaining a remarkable learning capacity, allowing it to acquire a wide range of skills, from motor actions to complex abstract reasoning, in a lifelong expression. In this review, the contribution on the "neuroplasticity" topic coming from advanced analysis of EEG rhythms is put forward.

Longitudinal Electroencephalography Analysis in Subacute Stroke Patients During Intervention of Brain-Computer Interface With Exoskeleton Feedback

Background

Brain-computer interface (BCI) has been regarded as a newly developing intervention in promoting motor recovery in stroke survivors. Several studies have been performed in chronic stroke to explore its clinical and subclinical efficacy. However, evidence in subacute stroke was poor, and the longitudinal sensorimotor rhythm changes in subacute stroke after BCI with exoskeleton feedback were still unclear.

Materials and Methods

Fourteen stroke patients in subacute stage were recruited and randomly allocated to BCI group (n = 7) and the control group (n = 7). Brain-computer interface training with exoskeleton feedback was applied in the BCI group three times a week for 4 weeks. The Fugl-Meyer Assessment of Upper Extremity (FMA-UE) scale was used to assess motor function improvement. Brain-computer interface performance was calculated across the 12-time interventions. Sensorimotor rhythm changes were explored by event-related desynchronization (ERD) changes and topographies.

Results

After 1 month BCI intervention, both the BCI group (p = 0.032) and the control group (p = 0.048) improved in FMA-UE scores. The BCI group (12.77%) showed larger percentage of improvement than the control group (7.14%), and more patients obtained good motor recovery in the BCI group (57.1%) than did the control group (28.6%). Patients with good recovery showed relatively higher online BCI performance, which were greater than 70%. And they showed a continuous improvement in offline BCI performance and obtained a highest value in the last six sessions of interventions during BCI training. However, patients with poor recovery reached a platform in the first six sessions of interventions and did not improve any more or even showed a decrease. In sensorimotor rhythm, patients with good recovery showed an enhanced ERD along with time change. Topographies showed that the ipsilesional hemisphere presented stronger activations after BCI intervention.

Conclusion

Brain-computer interface training with exoskeleton feedback was feasible in subacute stroke patients. Brain-computer interface performance can be an index to evaluate the efficacy of BCI intervention. Patients who presented increasingly stronger or continuously strong activations (ERD) may obtain better motor recovery.

Finding the Intersection of Neuroplasticity, Stroke Recovery, and Learning: Scope and Contributions to Stroke Rehabilitation

Aim

Neural plastic changes are experience and learning dependent, yet exploiting this knowledge to enhance clinical outcomes after stroke is in its infancy. Our aim was to search the available evidence for the core concepts of neuroplasticity, stroke recovery, and learning; identify links between these concepts; and identify and review the themes that best characterise the intersection of these three concepts.

Methods

We developed a novel approach to identify the common research topics among the three areas: neuroplasticity, stroke recovery, and learning. A concept map was created a priori, and separate searches were conducted for each concept. The methodology involved three main phases: data collection and filtering, development of a clinical vocabulary, and the development of an automatic clinical text processing engine to aid the process and identify the unique and common topics. The common themes from the intersection of the three concepts were identified. These were then reviewed, with particular reference to the top 30 articles identified as intersecting these concepts.

Results

The search of the three concepts separately yielded 405,636 publications. Publications were filtered to include only human studies, generating 263,751 publications related to the concepts of neuroplasticity (n = 6,498), stroke recovery (n = 79,060), and learning (n = 178,193). A cluster concept map (network graph) was generated from the results; indicating the concept nodes, strength of link between nodes, and the intersection between all three concepts. We identified 23 common themes (topics) and the top 30 articles that best represent the intersecting themes. A time-linked pattern emerged.

Discussion and Conclusions

Our novel approach developed for this review allowed the identification of the common themes/topics that intersect the concepts of neuroplasticity, stroke recovery, and learning. These may be synthesised to advance a neuroscience-informed approach to stroke rehabilitation. We also identified gaps in available literature using this approach. These may help guide future targeted research.

Dynamic Alterations in Spontaneous Neural Activity in Multiple Brain Networks in Subacute Stroke Patients: A Resting-State fMRI Study

Objective: To examine whether subacute stroke patients would exhibit abnormal dynamic characteristics of brain activity relative to healthy controls (HC) and to investigate whether the altered dynamic regional indexes were associated with clinical behavior in stroke patients. Methods: The dynamic amplitude of low-frequency fluctuations (dALFF) and dynamic regional homogeneity (dReHo) in 42 subacute stroke patients and 55 healthy controls were compared. Correlation analyses between dALFF and dReHo in regions showing significant intergroup differences and clinical scores (i.e., the National Institutes of Health Stroke Scale, Fugl-Meyer assessment and lesion volume size) were conducted in stroke patients. Receiver operating characteristic (ROC) curve analysis was used to determine the potential value of altered dynamic regional indexes to identify stroke patients. Results: Significantly dALFF in the bilateral cerebellum posterior lobe (CPL), ipsilesional superior parietal lobe, ipsilesional inferior temporal gyrus (ITG), the midline supplementary motor area (SMA), ipsilesional putamen and lentiform nucleus were detected in stroke patients compared to HC. Relative to the HC group, the stroke patients showed significant differences in dReHo in the contralesional rectal gyrus, contralesional ITG, contralesional pons, ipsilesional middle frontal gyrus (MFG). Significant correlations between dALFF variability in midline SMA and Fugl-Meyer assessment (FMA) scores or between dReHo variability in the ipsilesional MFG and FMA scores were detected in stroke patients. Furthermore, the ROC curve revealed that dynamic ALFF at SMA and ReHo at ipsilesional MFG might have the potential to distinguish stroke patients. Conclusion: The pattern of intrinsic brain activity variability is altered in stroke patients compared with HC, and dynamic ALFF/ReHo might be potential tools to assess stroke patients' motor function.

Comparison of EEG measurement of upper limb movement in motor imagery training system

BACKGROUND

One of the most promising applications for electroencephalogram (EEG)-based brain computer interface is for stroke rehabilitation. Implemented as a standalone motor imagery (MI) training system or as part of a rehabilitation robotic system, many studies have shown benefits of using them to restore motor control in stroke patients. Hand movements have widely been chosen as MI tasks. Although potentially more challenging to analyze, wrist and forearm movement such as wrist flexion/extension and forearm pronation/supination should also be considered for MI tasks, because these movements are part of the main exercises given to patients in conventional stroke rehabilitation. This paper will evaluate the effectiveness of such movements for MI tasks.

METHODS

Three hand and wrist movement tasks which were hand opening/closing, wrist flexion/extension and forearm pronation/supination were chosen as motor imagery tasks for both hands. Eleven subjects participated in the experiment. All of them completed hand opening/closing task session. Ten subjects completed two MI task sessions which were hand opening/closing and wrist flexion/extension. Five subjects completed all three MI tasks sessions. Each MI task comprised 8 sessions spanning a 4 weeks period. For classification, feature extraction based on common spatial pattern (CSP) algorithm was used. Two types were implemented, one with conventional CSP (termed WB) and one with an increase number of features achieved by filtering EEG data into five bands (termed FB). Classification was done by linear discriminant analysis (LDA) and support vector machine (SVM).

RESULTS

Eight-fold cross validation was applied on EEG data. LDA and SVM gave comparable classification accuracy. FB achieved significantly higher classification accuracy compared to WB. The accuracy of classifying wrist flexion/extension task were higher than that of classifying hand opening/closing task in all subjects. Classifying forearm pronation/supination task achieved higher accuracy than classifying hand opening/closing task in most subjects but achieved lower accuracy than classifying wrist flexion/extension task in all subjects. Significant improvements of classification accuracy were found in nine subjects when considering individual sessions of experiments of all MI tasks. The results of classifying hand opening/closing task and wrist flexion/extension task were comparable to the results of classifying hand opening/closing task and forearm pronation/supination task. Classification accuracy of wrist flexion/extension task and forearm pronation/supination task was lower than those of hand movement tasks and wrist movement tasks.

CONCLUSION

High classification accuracy of the three MI tasks support the possibility of using EEG-based stroke rehabilitation system with these movements. Either LDA or SVM can equally be chosen as a classifier since the difference of their accuracies is not statistically significant. Significantly higher classification accuracy made FB more suitable for classifying MI task compared to WB. More training sessions could potentially lead to better accuracy as evident in most subjects in this experiment.

Rehabilitation of Motor Function after Stroke: A Multiple Systematic Review Focused on Techniques to Stimulate Upper Extremity Recovery

Stroke is one of the leading causes for disability worldwide. Motor function deficits due to stroke affect the patients' mobility, their limitation in daily life activities, their participation in society and their odds of returning to professional activities. All of these factors contribute to a low overall quality of life. Rehabilitation training is the most effective way to reduce motor impairments in stroke patients. This multiple systematic review focuses both on standard treatment methods and on innovating rehabilitation techniques used to promote upper extremity motor function in stroke patients. A total number of 5712 publications on stroke rehabilitation was systematically reviewed for relevance and quality with regards to upper extremity motor outcome. This procedure yielded 270 publications corresponding to the inclusion criteria of the systematic review. Recent technology-based interventions in stroke rehabilitation including non-invasive brain stimulation, robot-assisted training, and virtual reality immersion are addressed. Finally, a decisional tree based on evidence from the literature and characteristics of stroke patients is proposed. At present, the stroke rehabilitation field faces the challenge to tailor evidence-based treatment strategies to the needs of the individual stroke patient. Interventions can be combined in order to achieve the maximal motor function recovery for each patient. Though the efficacy of some interventions may be under debate, motor skill learning, and some new technological approaches give promising outcome prognosis in stroke motor rehabilitation.

Hallucinations as top-down effects on perception

The problem of whether and how information is integrated across hierarchical brain networks embodies a fundamental tension in contemporary cognitive neuroscience, and by extension, cognitive neuropsychiatry. Indeed, the penetrability of perceptual processes in a 'top-down' manner by higher-level cognition-a natural extension of hierarchical models of perception-may contradict a strictly modular view of mental organization. Furthermore, some in the cognitive science community have challenged cognitive penetration as an unlikely, if not impossible, process. We review the evidence for and against top-down influences in perception, informed by a predictive coding model of perception and drawing heavily upon the literature of computational neuroimaging. We extend these findings to propose a way in which these processes may be altered in mental illness. We propose that hallucinations - perceptions without stimulus - can be understood as top-down effects on perception, mediated by inappropriate perceptual priors.

Neuroplasticity for spontaneous functional recovery after neonatal hypoxic ischemic brain injury in rats observed by functional MRI and diffusion tensor imaging

For infants and children, an incredible resilience from injury is often observed. There is growing evidence that functional recovery after brain injury might well be a consequence of the reorganization of the neural network as a process of neuroplasticity. We demonstrate the presence of neuroplasticity at work in spontaneous recovery after neonatal hypoxic ischemic (HI) injury, by elucidating a precise picture in which such reorganization takes place using functional MRI techniques. For all 12 siblings, 6 rats were subjected to severe HI brain injury and 6 rats underwent sham operation only. Severe HI brain injury was induced to postnatal day 7 (p7) Sprague-Dawley rats according to the Rice-Vannucci model (right carotid artery occlusion followed by 150min of hypoxia with 8% O2 and 92% of N2). Brain activation maps along with anatomical and functional connectivity maps related to the sensory motor function were obtained at adult (p63) using blood oxygen level dependent (BOLD)-functional MRI (fMRI), resting state-functional MRI (rs-fMRI) and diffusion tensor imaging (DTI); each of these MRI data was related to sensory motor functional outcome. In-depth investigation of the functional MRI data revealed: 1) intra-hemispheric expansion of BOLD signal activation in the contralesional undamaged hemisphere for ipsilesional forepaw stimuli to include the M2 and Cg1 in addition to the S1 and M1 wide spreading in the anterior and posterior directions, 2) inter-hemispheric transfer of BOLD signal activation for contralesional forepaw stimuli, normally routed to the injured hemisphere, to analogous sites in the contralesional undamaged hemisphere, localized newly to the M1 and M2 with a reduced portion of the S1, 3) inter-hemispheric axonal disconnection and axonal rewiring within the undamaged hemisphere as shown through DTI, and 4) increased functional interactions within the cingulate gyrus in the HI injured rats as shown through rs-fMRI. The BOLD signal amplitudes as well as DTI and rs-fMRI data well correlate with behavioral tests (tape to remove). We found that function normally utilizing what would be the injured hemisphere is transferred to the uninjured hemisphere, and functionality of the uninjured hemisphere remains not untouched but is also rewired in an expansion corresponding to the newly formed sensorimotor function from both the contralesional and the ipsilesional sides. The conclusion drawn from the data in our current study is that enhanced motor function in the contralesional hemisphere governs both the normal and damaged sides, indicating that active plasticity with brain laterality was spontaneously generated to overcome functional loss and established autonomously through normal experience via modification of neural circuitry for neonatal HI injured brain.

Enhanced effective connectivity in mild occipital stroke patients with hemianopia

Plasticity-based spontaneous recovery and rehabilitation intervention of stroke-induced hemianopia have drawn great attention in recent years. However, the underlying neural mechanism remains unknown. This study aims to investigate brain network disruption and reorganization in hemianopia patients due to mild occipital stroke. Resting-state networks were constructed from 12 hemianopia patients with right occipital infarct by partial directed coherence analysis of multi-channel electroencephalograms. Compared with control subjects, the patients presented enhanced connectivity owing to newly formed connections. Compensational connections mostly originated from the peri-infarct area and targeted contralesional frontal, central, and parietal cortices. These new ipsilesional-to-contralesional inter-hemispheric connections coordinately presented significant correlation with the extent of vision loss. The enhancement of connectivity might be the neural substrate for brain plasticity in stroke-induced hemianopia and may shed light on plasticity-based recovery or rehabilitation.

Time to get rid of the 'Modular' in neuropsychology: a unified theory of anosognosia as aberrant predictive coding

Cognitive neuroscience, being more inclusive and ambitious in scope than cognitive neuropsychology, seems to have taken the place of the latter within the modern neurosciences. Nevertheless, recent advances in the neurosciences afford neuropsychology with epistemic possibilities that simply did not exist even 15 years ago. Human lesion studies still have an important role to play in shaping such possibilities, particularly when combined with other methods of enquiry. I first outline theoretical and methodological advances within the neurosciences that can inform and shape the rebirth of a dynamic, non-modular neuropsychology. I then use an influential computational theory of brain function, the free energy principle, to suggest an unified account of anosognosia for hemiplegia as a research example of the potential for transition from a modular, cognitive neuropsychology to a dynamic, computational and even restorative neuropsychology. These and many other adjectives that can flexibly, take the place of 'cognitive' next to 'neuropsychology' will hopefully designate the much needed rebirth and demarcation of a field, neuropsychology itself, that has somehow lost its place within the modern neurosciences and yet seems to have a unique and important role to play in the future understanding of the brain.

White matter reorganization and functional response after focal cerebral ischemia in the rat

After stroke, the brain has shown to be able to achieve spontaneous functional recovery despite severe cerebral damage. This phenomenon is poorly understood. To address this issue, focal transient ischemia was induced by 60 min middle cerebral artery occlusion in Wistar rats. The evolution of stroke was followed using two magnetic resonance imaging modalities: diffusion spectrum imaging (acquired before, one and four weeks after stroke) and functional magnetic resonance imaging (acquired before and five weeks after stroke). To confirm the imaging observations, immunohistochemical staining for myelin, astrocytes and macrophages/microglia was added. At four weeks after stroke, a focal alteration of the diffusion anisotropy was observed between the ipsilesional ventricle and the lesion area. Using tractography this perturbation was identified as reorganization of the ipsilesional internal capsule. Functional imaging at five weeks after ischemia demonstrated activation of the primary sensorimotor cortex in both hemispheres in all rats except one animal lacking a functional response in the ipsilesional cortex. Furthermore, fiber tracking showed a transhemispheric fiber connection through the corpus callosum, which-in the rat without functional recovery-was lost. Our study shows the influence of the internal capsule reorganization, combined with inter-hemispheric connections though the corpus callosum, on the functional activation of the brain from stroke. In conclusion, tractography opens a new door to non-invasively investigate the structural correlates of lack of functional recovery after stroke.

Exploration and modulation of brain network interactions with noninvasive brain stimulation in combination with neuroimaging

Much recent work in systems neuroscience has focused on how dynamic interactions between different cortical regions underlie complex brain functions such as motor coordination, language and emotional regulation. Various studies using neuroimaging and neurophysiologic techniques have suggested that in many neuropsychiatric disorders, these dynamic brain networks are dysregulated. Here we review the utility of combined noninvasive brain stimulation and neuroimaging approaches towards greater understanding of dynamic brain networks in health and disease. Brain stimulation techniques, such as transcranial magnetic stimulation and transcranial direct current stimulation, use electromagnetic principles to alter brain activity noninvasively, and induce focal but also network effects beyond the stimulation site. When combined with brain imaging techniques such as functional magnetic resonance imaging, positron emission tomography and electroencephalography, these brain stimulation techniques enable a causal assessment of the interaction between different network components, and their respective functional roles. The same techniques can also be applied to explore hypotheses regarding the changes in functional connectivity that occur during task performance and in various disease states such as stroke, depression and schizophrenia. Finally, in diseases characterized by pathologic alterations in either the excitability within a single region or in the activity of distributed networks, such techniques provide a potential mechanism to alter cortical network function and architectures in a beneficial manner.

A minimal set of electrodes for motor imagery BCI to control an assistive device in chronic stroke subjects: a multi-session study

The brain-computer interface (BCI) system has been developed to assist people with motor disability. To make the system more user-friendly, it is a challenge to reduce the electrode preparation time and have a good reliability. This study aims to find a minimal set of electrodes for an individual stroke subject for motor imagery to control an assistive device using functional electrical stimulation for 20 sessions with accuracy higher than 90%. The characteristics of this minimal electrode set were evaluated with two popular algorithms: Fisher's criterion and support-vector machine recursive feature elimination (SVM-RFE). The number of calibration sessions for channel selection required for robust control of these 20 sessions was also investigated. Five chronic stroke patients were recruited for the study. Our results suggested that the number of calibration sessions for channel selection did not have a significant effect on the classification accuracy. A performance index devised in this study showed that one training day with 12 electrodes using the SVM-RFE method achieved the best balance between the number of electrodes and accuracy in the 20-session data. Generally, 8-36 channels were required to maintain accuracy higher than 90% in 20 BCI training sessions for chronic stroke patients.

Modulation of large-scale brain networks by transcranial direct current stimulation evidenced by resting-state functional MRI

BACKGROUND

Brain areas interact mutually to perform particular complex brain functions such as memory or language. Furthermore, under resting-state conditions several spatial patterns have been identified that resemble functional systems involved in cognitive functions. Among these, the default-mode network (DMN), which is consistently deactivated during task periods and is related to a variety of cognitive functions, has attracted most attention. In addition, in resting-state conditions some brain areas engaged in focused attention (such as the anticorrelated network, AN) show a strong negative correlation with DMN; as task demand increases, AN activity rises, and DMN activity falls.

OBJECTIVE

We combined transcranial direct current stimulation (tDCS) with functional magnetic resonance imaging (fMRI) to investigate these brain network dynamics.

METHODS

Ten healthy young volunteers underwent four blocks of resting-state fMRI (10-minutes), each of them immediately after 20 minutes of sham or active tDCS (2 mA), on two different days. On the first day the anodal electrode was placed over the left dorsolateral prefrontal cortex (DLPFC) (part of the AN) with the cathode over the contralateral supraorbital area, and on the second day, the electrode arrangement was reversed (anode right-DLPFC, cathode left-supraorbital).

RESULTS

After active stimulation, functional network connectivity revealed increased synchrony within the AN components and reduced synchrony in the DMN components.

CONCLUSIONS

Our study reveals a reconfiguration of intrinsic brain activity networks after active tDCS. These effects may help to explain earlier reports of improvements in cognitive functions after anodal-tDCS, where increasing cortical excitability may have facilitated reconfiguration of functional brain networks to address upcoming cognitive demands.

Identifying abnormal connectivity in patients using dynamic causal modeling of FMRI responses

Functional imaging studies of brain damaged patients offer a unique opportunity to understand how sensorimotor and cognitive tasks can be carried out when parts of the neural system that support normal performance are no longer available. In addition to knowing which regions a patient activates, we also need to know how these regions interact with one another, and how these inter-regional interactions deviate from normal. Dynamic causal modeling (DCM) offers the opportunity to assess task-dependent interactions within a set of regions. Here we review its use in patients when the question of interest concerns the characterization of abnormal connectivity for a given pathology. We describe the currently available implementations of DCM for fMRI responses, varying from the deterministic bilinear models with one-state equation to the stochastic non-linear models with two-state equations. We also highlight the importance of the new Bayesian model selection and averaging tools that allow different plausible models to be compared at the single subject and group level. These procedures allow inferences to be made at different levels of model selection, from features (model families) to connectivity parameters. Following a critical review of previous DCM studies that investigated abnormal connectivity we propose a systematic procedure that will ensure more flexibility and efficiency when using DCM in patients. Finally, some practical and methodological issues crucial for interpreting or generalizing DCM findings in patients are discussed.

An extended motor network generates beta and gamma oscillatory perturbations during development

This study examines the time course and neural generators of oscillatory beta and gamma motor responses in typically-developing children. Participants completed a unilateral flexion-extension task using each index finger as whole-head magnetoencephalography (MEG) data were acquired. These MEG data were imaged in the frequency-domain using spatial filtering and the resulting event-related synchronizations and desynchronizations (ERS/ERD) were subjected to voxel-wise statistical analyses to illuminate time-frequency specific activation patterns. Consistent with adult data, these children exhibited a pre-movement ERD that was strongest over the contralateral post-central gyrus, and a post-movement ERS response with the most prominent peak being in the contralateral precentral gyrus near premotor cortices. We also observed a high-frequency (approximately 80 Hz) ERS response that coincided with movement onset and was centered on the contralateral precentral gyrus, slightly superior and posterior to the beta ERS. In addition to pre- and post-central gyri activations, these children exhibited beta and gamma activity in supplementary motor areas (SMA) before and during movement, and beta activation in cerebellar cortices before and after movement. We believe the gamma synchronization may be an excellent candidate signal of basic cortical motor control, as the spatiotemporal dynamics indicate the primary motor cortex generates this response (and not the beta oscillations) which is closely yoked to the initial muscle activation. Lastly, these data suggest several additional neural regions including the SMA and cerebellum are involved in basic movements during development.

Implications of brain plasticity to brain-machine interfaces operation a potential paradox?

The adult brain has the remarkable ability to plastically reorganize itself in order to record memories (experiences), to add abilities, and to learn skills, significantly expanding the carnet of resources useful for facing and solving the unpredictability of any daily life activity, that is, artistic and cultural activities. Brain plasticity also plays a crucial role in reorganizing central nervous system's networks after any lesion, being it sudden and localized, or progressive and diffuse, in order to partly or totally restore lost and/or compromised functions. In severely affected neurological patients unable to move and to communicate with the external environment, technologies implementing brain-machine interfaces (BMIs) can be of valuable help and support. Subjects operating within a BMI frame must learn how to produce a meaningful signal for an external reader; how to increase the signal-to-noise ratio at a level which makes it suitable for rapid communication with the machine; and how to improve the speed and specificity (bit rate) of signal production as a new language for governing and controlling a machine. Since it is of absolute importance for the patient to be able to maintain such a skill for a prolonged lapse of time (i.e., until his/her lost abilities are restored by a therapy and/or a different technology), neurophysiological phenomena at the base of plastic changes are obviously of remarkable importance within any BMI and are the content of the present chapter.