How somatotopic is the motor cortex hand area?

Bringing transcranial mapping into shape: Sulcus-aligned mapping captures motor somatotopy in human primary motor hand area

Motor representations express some degree of somatotopy in human primary motor hand area (M1HAND), but within-M1HAND corticomotor somatotopy has been difficult to study with transcranial magnetic stimulation (TMS). Here we introduce a "linear" TMS mapping approach based on the individual shape of the central sulcus to obtain mediolateral corticomotor excitability profiles of the abductor digiti minimi (ADM) and first dorsal interosseus (FDI) muscles. In thirteen young volunteers, we used stereotactic neuronavigation to stimulate the right M1HAND with a small eight-shaped coil at 120% of FDI resting motor threshold. We pseudorandomly stimulated six targets located on a straight mediolateral line corresponding to the overall orientation of the central sulcus with a fixed coil orientation of 45° to the mid-sagittal line (STRAIGHT-450FIX) or seven targets in the posterior part of the crown of the central sulcus following the bending of the central sulcus (CURVED). CURVED mapping employed a fixed (CURVED-450FIX) or flexible coil orientation producing always a current perpendicular to the sulcal wall (CURVED-900FLEX). During relaxation, CURVED but not STRAIGHT mapping revealed distinct corticomotor excitability peaks in M1HAND with the excitability maximum of ADM located medially to the FDI maximum. This mediolateral somatotopy was still present during tonic contraction of the ADM or FDI. During ADM contraction, cross-correlation between the spatial excitability profiles of ADM and FDI was lowest for CURVED-900FLEX. Together, the results show that within-M1HAND somatotopy can be readily probed with linear TMS mapping aligned to the sulcal shape. Sulcus-aligned linear mapping will benefit non-invasive studies of representational plasticity in human M1HAND.

Hand use predicts the structure of representations in sensorimotor cortex

Fine finger movements are controlled by the population activity of neurons in the hand area of primary motor cortex. Experiments using microstimulation and single-neuron electrophysiology suggest that this area represents coordinated multi-joint, rather than single-finger movements. However, the principle by which these representations are organized remains unclear. We analyzed activity patterns during individuated finger movements using functional magnetic resonance imaging (fMRI). Although the spatial layout of finger-specific activity patterns was variable across participants, the relative similarity between any pair of activity patterns was well preserved. This invariant organization was better explained by the correlation structure of everyday hand movements than by correlated muscle activity. This also generalized to an experiment using complex multi-finger movements. Finally, the organizational structure correlated with patterns of involuntary co-contracted finger movements for high-force presses. Together, our results suggest that hand use shapes the relative arrangement of finger-specific activity patterns in sensory-motor cortex.

Decoding a wide range of hand configurations from macaque motor, premotor, and parietal cortices

Despite recent advances in decoding cortical activity for motor control, the development of hand prosthetics remains a major challenge. To reduce the complexity of such applications, higher cortical areas that also represent motor plans rather than just the individual movements might be advantageous. We investigated the decoding of many grip types using spiking activity from the anterior intraparietal (AIP), ventral premotor (F5), and primary motor (M1) cortices. Two rhesus monkeys were trained to grasp 50 objects in a delayed task while hand kinematics and spiking activity from six implanted electrode arrays (total of 192 electrodes) were recorded. Offline, we determined 20 grip types from the kinematic data and decoded these hand configurations and the grasped objects with a simple Bayesian classifier. When decoding from AIP, F5, and M1 combined, the mean accuracy was 50% (using planning activity) and 62% (during motor execution) for predicting the 50 objects (chance level, 2%) and substantially larger when predicting the 20 grip types (planning, 74%; execution, 86%; chance level, 5%). When decoding from individual arrays, objects and grip types could be predicted well during movement planning from AIP (medial array) and F5 (lateral array), whereas M1 predictions were poor. In contrast, predictions during movement execution were best from M1, whereas F5 performed only slightly worse. These results demonstrate for the first time that a large number of grip types can be decoded from higher cortical areas during movement preparation and execution, which could be relevant for future neuroprosthetic devices that decode motor plans.

A neuroanatomical framework for upper limb synergies after stroke

Muscle synergies describe common patterns of co- or reciprocal activation that occur during movement. After stroke, these synergies change, often in stereotypical ways. The mechanism underlying this change reflects damage to key motor pathways as a result of the stroke lesion, and the subsequent reorganization along the neuroaxis, which may be further detrimental or restorative to motor function. The time course of abnormal synergy formation seems to lag spontaneous recovery that occurs in the initial weeks after stroke. In healthy individuals, motor cortical activity, descending via the corticospinal tract (CST) is the predominant driver of voluntary behavior. When the CST is damaged after stroke, other descending pathways may be up-regulated to compensate. The contribution of these pathways may emerge as new synergies take shape at the chronic stage after stroke, as a result of plasticity along the neuroaxis. The location of the stroke lesion and properties of the secondary descending pathways and their regulation are then critical for shaping the synergies in the remaining motor behavior. A consideration of the integrity of remaining descending motor pathways may aid in the design of new rehabilitation therapies.

Evidence for inhibitory deficits in the prefrontal cortex in schizophrenia

Abnormal gamma-aminobutyric acid inhibitory neurotransmission is a key pathophysiological mechanism underlying schizophrenia. Transcranial magnetic stimulation can be combined with electroencephalography to index long-interval cortical inhibition, a measure of GABAergic receptor-mediated inhibitory neurotransmission from the frontal and motor cortex. In previous studies we have reported that schizophrenia is associated with inhibitory deficits in the dorsolateral prefrontal cortex compared to healthy subjects and patients with bipolar disorder. The main objective of the current study was to replicate and extend these initial findings by evaluating long-interval cortical inhibition from the dorsolateral prefrontal cortex in patients with schizophrenia compared to patients with obsessive-compulsive disorder. A total of 111 participants were assessed: 38 patients with schizophrenia (average age: 35.71 years, 25 males, 13 females), 27 patients with obsessive-compulsive disorder (average age: 36.15 years, 11 males, 16 females) and 46 healthy subjects (average age: 33.63 years, 23 females, 23 males). Long-interval cortical inhibition was measured from the dorsolateral prefrontal cortex and motor cortex through combined transcranial magnetic stimulation and electroencephalography. In the dorsolateral prefrontal cortex, long-interval cortical inhibition was significantly reduced in patients with schizophrenia compared to healthy subjects (P = 0.004) and not significantly different between patients with obsessive-compulsive disorder and healthy subjects (P = 0.5445). Long-interval cortical inhibition deficits in the dorsolateral prefrontal cortex were also significantly greater in patients with schizophrenia compared to patients with obsessive-compulsive disorder (P = 0.0465). There were no significant differences in long-interval cortical inhibition across all three groups in the motor cortex. These results demonstrate that long-interval cortical inhibition deficits in the dorsolateral prefrontal cortex are specific to patients with schizophrenia and are not a generalized deficit that is shared by disorders of severe psychopathology.

Neuron selection based on deflection coefficient maximization for the neural decoding of dexterous finger movements

Future generations of brain-machine interface (BMI) will require more dexterous motion control such as hand and finger movements. Since a population of neurons in the primary motor cortex (M1) area is correlated with finger movements, neural activities recorded in M1 area are used to reconstruct an intended finger movement. In a BMI system, decoding discrete finger movements from a large number of input neurons does not guarantee a higher decoding accuracy in spite of the increase in computational burden. Hence, we hypothesize that selecting neurons important for coding dexterous flexion/extension of finger movements would improve the BMI performance. In this paper, two metrics are presented to quantitatively measure the importance of each neuron based on Bayes risk minimization and deflection coefficient maximization in a statistical decision problem. Since motor cortical neurons are active with movements of several different fingers, the proposed method is more suitable for a discrete decoding of flexion-extension finger movements than the previous methods for decoding reaching movements. In particular, the proposed metrics yielded high decoding accuracies across all subjects and also in the case of including six combined two-finger movements. While our data acquisition and analysis was done off-line and post processing, our results point to the significance of highly coding neurons in improving BMI performance.

Spatial computation with gamma oscillations

Gamma oscillations in cortex have been extensively studied with relation to behavior in both humans and animal models; however, their computational role in the processing of behaviorally relevant signals is still not clear. One oft-overlooked characteristic of gamma oscillations is their spatial distribution over the cortical space and the computational consequences of such an organization. Here, we advance the proposal that the spatial organization of gamma oscillations is of major importance for their function. The interaction of specific spatial distributions of oscillations with the functional topography of cortex enables select amplification of neuronal signals, which supports perceptual and cognitive processing.

Analysis of hand synergies in healthy subjects during bimanual manipulation of various objects

BACKGROUND

Hand synergies have been extensively studied over the last few decades. Objectives of such research are numerous. In neuroscience, the aim is to improve the understanding of motor control and its ability to reduce the control dimensionality. In applied research fields like robotics the aim is to build biomimetic hand structures, or in prosthetics to design more performant underactuated replacement hands. Nevertheless, most of the synergy schemes identified to this day have been obtained from grasping experiments performed with one single (generally dominant) hand to objects placed in a given position and orientation in space. Aiming at identifying more generic synergies, we conducted similar experiments on postural synergy identification during bimanual manipulation of various objects in order to avoid the factors due to the extrinsic spatial position of the objects.

METHODS

Ten healthy naive subjects were asked to perform a selected "grasp-give-receive" task with both hands using 9 objects. Subjects were wearing Cyberglove Ⓒ on both hands, allowing a measurement of the joint posture (15 degrees of freedom) of each hand. Postural synergies were then evaluated through Principal Component Analysis (PCA). Matches between the identified Principal Components and the human hand joints were analyzed thanks to the correlation matrix. Finally, statistical analysis was performed on the data in order to evaluate the effect of some specific variables on the hand synergies: object shape, hand side (i.e., laterality) and role (giving or receiving hand).

RESULTS

Results on PCs are consistent with previous literature showing that a few principal components might be sufficient to describe a large variety of different grasps. Nevertheless some simple and strong correlations between PCs and clearly identified sets of hand joints were obtained in this study. In addition, these groupings of DoF corresponds to well-defined anatomo-functional finger joints according to muscle groups. Moreover, despite our protocol encouraging symmetric grasping, some right-left side differences were observed.

CONCLUSION

The set of identified synergies presented here should be more representative of hand synergies in general since they are based on both hands motion. Preliminary results, that should be deepened, also highlight the influence of hand dominance and side. Thanks to their strong correlation with anatomo-functional joints, these synergies could therefore be used to design underactuated robotics hands.

Restoring sensorimotor function through intracortical interfaces: progress and looming challenges

The loss of a limb or paralysis resulting from spinal cord injury has devastating consequences on quality of life. One approach to restoring lost sensory and motor abilities in amputees and patients with tetraplegia is to supply them with implants that provide a direct interface with the CNS. Such brain-machine interfaces might enable a patient to exert voluntary control over a prosthetic or robotic limb or over the electrically induced contractions of paralysed muscles. A parallel interface could convey sensory information about the consequences of these movements back to the patient. Recent developments in the algorithms that decode motor intention from neuronal activity and in approaches to convey sensory feedback by electrically stimulating neurons, using biomimetic and adaptation-based approaches, have shown the promise of invasive interfaces with sensorimotor cortices, although substantial challenges remain.

Decoding repetitive finger movements with brain activity acquired via non-invasive electroencephalography

We investigated how well repetitive finger tapping movements can be decoded from scalp electroencephalography (EEG) signals. A linear decoder with memory was used to infer continuous index finger angular velocities from the low-pass filtered fluctuations of the amplitude of a plurality of EEG signals distributed across the scalp. To evaluate the accuracy of the decoder, the Pearson's correlation coefficient (r) between the observed and predicted trajectories was calculated in a 10-fold cross-validation scheme. We also assessed attempts to decode finger kinematics from EEG data that was cleaned with independent component analysis (ICA), EEG data from peripheral sensors, and EEG data from rest periods. A genetic algorithm (GA) was used to select combinations of EEG channels that maximized decoding accuracies. Our results (lower quartile r = 0.18, median r = 0.36, upper quartile r = 0.50) show that delta-band EEG signals contain useful information that can be used to infer finger kinematics. Further, the highest decoding accuracies were characterized by highly correlated delta band EEG activity mostly localized to the contralateral central areas of the scalp. Spectral analysis of EEG also showed bilateral alpha band (8–13 Hz) event related desynchronizations (ERDs) and contralateral beta band (20–30 Hz) event related synchronizations (ERSs) localized over central scalp areas. Overall, this study demonstrates the feasibility of decoding finger kinematics from scalp EEG signals.

Local domains of motor cortical activity revealed by fiber-optic calcium recordings in behaving nonhuman primates

Brain mapping experiments involving electrical microstimulation indicate that the primary motor cortex (M1) directly regulates muscle contraction and thereby controls specific movements. Possibly, M1 contains a small circuit "map" of the body that is formed by discrete local networks that code for specific movements. Alternatively, movements may be controlled by distributed, larger-scale overlapping circuits. Because of technical limitations, it remained unclear how movement-determining circuits are organized in M1. Here we introduce a method that allows the functional mapping of small local neuronal circuits in awake behaving nonhuman primates. For this purpose, we combined optic-fiber-based calcium recordings of neuronal activity and cortical microstimulation. The method requires targeted bulk loading of synthetic calcium indicators (e.g., OGB-1 AM) for the staining of neuronal microdomains. The tip of a thin (200 µm) optical fiber can detect the coherent activity of a small cluster of neurons, but is insensitive to the asynchronous activity of individual cells. By combining such optical recordings with microstimulation at two well-separated sites of M1, we demonstrate that local cortical activity was tightly associated with distinct and stereotypical simple movements. Increasing stimulation intensity increased both the amplitude of the movements and the level of neuronal activity. Importantly, the activity remained local, without invading the recording domain of the second optical fiber. Furthermore, there was clear response specificity at the two recording sites in a trained behavioral task. Thus, the results provide support for movement control in M1 by local neuronal clusters that are organized in discrete cortical domains.

Finger-specific loss of independent control of movements in musicians with focal dystonia

The loss of independent control of finger movements impairs the dexterous use of the hand. Focal hand dystonia is characterised by abnormal structural and functional changes at the cortical and subcortical regions responsible for individuated finger movements and by the loss of surround inhibition in the finger muscles. However, little is known about the pathophysiological impact of focal dystonia on the independent control of finger movements. Here we addressed this issue by asking pianists with and without focal dystonia to repetitively strike a piano key with one of the four fingers as fast as possible while the remaining digits kept the adjacent keys depressed. Using principal component analysis and cluster analysis to the derived keystroke data, we successfully classified pianists according to the presence or absence of dystonic symptoms with classification rates and cross-validation scores of approximately 90%. This confirmed the effects of focal dystonia on the individuated finger movements. Interestingly, the movement features that contributed to successful classification differed across fingers. Compared to healthy pianists, pianists with an affected index finger were characterised predominantly by stronger keystrokes, whereas pianists with affected middle or ring fingers exhibited abnormal temporal control of the keystrokes, such as slowness and rhythmic inconsistency. The selective alternation of the movement features indicates a finger-specific loss of the independent control of finger movements in focal dystonia of musicians.

Neurologic heuristics and artistic whimsy: the cerebral cartography of Wilder Penfield

Neurosurgeon Wilder Penfield played a singularly important role in expanding our knowledge of functional neuroanatomy and neurophysiology in the twentieth century. Trained under Charles Sherrington, William Osler, and Otfrid Foerster, Penfield was an early leader in efforts to map the cerebral cortex via direct electrical stimulation of the brain. In 1937, Penfield introduced an entirely new concept for illustrating the relative sizes and locations of discrete functional regions within the sensorimotor cortex--the homunculus-to exemplify the "order and comparative extent" of specific functional regions. Over the subsequent two decades, Penfield and colleagues introduced several more "little men" to portray the functional maps of other important brain structures (i.e., supplementary motor area, insular cortex, thalamus). These later homunculi were more crudely drawn, and Penfield referred to them as essentially heuristic devices. The actual intent in producing these homunculi remains uncertain, and despite the extraordinary impact of these artistic renderings on the field, the question is raised as to whether the allure of the artwork seemed to wrest control from-and then to guide-the dissemination of science, rather than the other way around.

Independence and control of the fingers depend on direction and contraction mode

Both biomechanical and neural factors are suggested to contribute to the limited independence of finger movement and involuntary force production. The purpose of this study was to evaluate finger independence by examining the activity of the four compartments of extensor digitorum (ED) and flexor digitorum superficialis (FDS) and involuntary force production in the non-task fingers using the "enslaving effect" (EE). Twelve male participants performed a series of 5s sub-maximal exertions at 5%, 25%, 50% and 75% of maximum using isometric isotonic and ramp flexion and extension exertions. Ramp exertions were performed from 0% to 85% of each finger's maximum force with ascending and descending phases taking 4.5s. EE was lower in flexion exertions likely due to the higher activity of the antagonist ED compartments counterbalancing the involuntary activation of the non-task FDS compartments. Minimal FDS activity was seen during extension exertions. At forces up to and including 50%, both EE and muscle activity of the non-task compartments were significantly higher in descending exertions than isotonic or ascending exertions. Up to mid-level forces, both finger proximity and contraction mode affect involuntary force production and muscle activation while only finger proximity contributed to finger independence at higher forces.

Overlapping connections within the motor cortico-basal ganglia circuit: fMRI-tractography analysis

Contribution of the subcortical nuclei to the coordination of human behavior is dependent on the existence of appropriate anatomical architecture. Interpretations of available data have led to opposing 'information funneling' and 'parallel processing' hypotheses. Using motor circuit as a model, we examined whether cortico-subcortical circuits, especially cortico-basal ganglia circuits, are funneled or parallel in the control of volitional movement. Twenty-five healthy subjects underwent functional magnetic resonance imaging (fMRI). Activated clusters during self-initiated, sequential finger-to-thumb opposition movements of the left hand were identified in the bilateral supplementary motor area (SMA), right lateral premotor cortex (PM) and primary motor cortex (M1), and in the right striatum and thalamus. These functionally defined clusters were applied to probabilistic tractography based on diffusion-weighted MRI to examine patterns of connectivity. Striatal and thalamic sub-regions with high probabilities of connection to the motor cortices partially overlapped, with connection to the two premotor areas outspreading rostrally relative to M1. We suggest that, on a macroscopic anatomical level, there is overlap as well as segregation among connections of the motor cortices with the striatum and thalamus. This supports the notion that neuronal information of the motor cortices is funneled, and parallel processing is not an exclusive principle in the basal ganglia.

Neural bases of hand synergies

The human hand has so many degrees of freedom that it may seem impossible to control. A potential solution to this problem is “synergy control” which combines dimensionality reduction with great flexibility. With applicability to a wide range of tasks, this has become a very popular concept. In this review, we describe the evolution of the modern concept using studies of kinematic and force synergies in human hand control, neurophysiology of cortical and spinal neurons, and electromyographic (EMG) activity of hand muscles. We go beyond the often purely descriptive usage of synergy by reviewing the organization of the underlying neuronal circuitry in order to propose mechanistic explanations for various observed synergy phenomena. Finally, we propose a theoretical framework to reconcile important and still debated concepts such as the definitions of “fixed” vs. “flexible” synergies and mechanisms underlying the combination of synergies for hand control.

The force synergy of human digits in static and dynamic cylindrical grasps

This study explores the force synergy of human digits in both static and dynamic cylindrical grasping conditions. The patterns of digit force distribution, error compensation, and the relationships among digit forces are examined to quantify the synergetic patterns and coordination of multi-finger movements. This study recruited 24 healthy participants to perform cylindrical grasps using a glass simulator under normal grasping and one-finger restricted conditions. Parameters such as the grasping force, patterns of digit force distribution, and the force coefficient of variation are determined. Correlation coefficients and principal component analysis (PCA) are used to estimate the synergy strength under the dynamic grasping condition. Specific distribution patterns of digit forces are identified for various conditions. The compensation of adjacent fingers for the force in the normal direction of an absent finger agrees with the principle of error compensation. For digit forces in anti-gravity directions, the distribution patterns vary significantly by participant. The forces exerted by the thumb are closely related to those exerted by other fingers under all conditions. The index-middle and middle-ring finger pairs demonstrate a significant relationship. The PCA results show that the normal forces of digits are highly coordinated. This study reveals that normal force synergy exists under both static and dynamic cylindrical grasping conditions.

Mapping the spatio-temporal structure of motor cortical LFP and spiking activities during reach-to-grasp movements

Grasping an object involves shaping the hand and fingers in relation to the object's physical properties. Following object contact, it also requires a fine adjustment of grasp forces for secure manipulation. Earlier studies suggest that the control of hand shaping and grasp force involve partially segregated motor cortical networks. However, it is still unclear how information originating from these networks is processed and integrated. We addressed this issue by analyzing massively parallel signals from population measures (local field potentials, LFPs) and single neuron spiking activities recorded simultaneously during a delayed reach-to-grasp task, by using a 100-electrode array chronically implanted in monkey motor cortex. Motor cortical LFPs exhibit a large multi-component movement-related potential (MRP) around movement onset. Here, we show that the peak amplitude of each MRP component and its latency with respect to movement onset vary along the cortical surface covered by the array. Using a comparative mapping approach, we suggest that the spatio-temporal structure of the MRP reflects the complex physical properties of the reach-to-grasp movement. In addition, we explored how the spatio-temporal structure of the MRP relates to two other measures of neuronal activity: the temporal profile of single neuron spiking activity at each electrode site and the somatosensory receptive field properties of single neuron activities. We observe that the spatial representations of LFP and spiking activities overlap extensively and relate to the spatial distribution of proximal and distal representations of the upper limb. Altogether, these data show that, in motor cortex, a precise spatio-temporal pattern of activation is involved for the control of reach-to-grasp movements and provide some new insight about the functional organization of motor cortex during reaching and object manipulation.

A multivariate method to determine the dimensionality of neural representation from population activity

How do populations of neurons represent a variable of interest? The notion of feature spaces is a useful concept to approach this question: According to this model, the activation patterns across a neuronal population are composed of different pattern components. The strength of each of these components varies with one latent feature, which together are the dimensions along which the population represents the variable. Here we propose a new method to determine the number of feature dimensions that best describes the activation patterns. The method is based on Gaussian linear classifiers that use only the first d most important pattern dimensions. Using cross-validation, we can identify the classifier that best matches the dimensionality of the neuronal representation. We test this method on two datasets of motor cortical activation patterns measured with functional magnetic resonance imaging (fMRI), during (i) simultaneous presses of all fingers of a hand at different force levels and (ii) presses of different individual fingers at a single force level. As expected, the new method shows that the representation of force is low-dimensional; the neural activation for different force levels is scaled versions of each other. In comparison, individual finger presses are represented in a full, four-dimensional feature space. The approach can be used to determine an important characteristic of neuronal population codes without knowing the form of the underlying features. It therefore provides a novel tool in the building of quantitative models of neuronal population activity as measured with fMRI or other approaches.

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Neural population activity represents external variables using multiple feature dimensions.

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We present a general method to determine the dimensionality of this feature space.

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Primary motor cortex represents force through a low-dimensional feature space.

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Individual finger movements are represented using a four-dimensional feature space.

A meta-analysis of cortical inhibition and excitability using transcranial magnetic stimulation in psychiatric disorders

OBJECTIVE

To evaluate transcranial magnetic stimulation (TMS) measures of inhibition and excitation in obsessive-compulsive disorder (OCD), major depressive disorder (MDD) and schizophrenia (SCZ).

METHODS

Paradigms included: short-interval cortical inhibition (SICI), cortical silent period (CSP), resting motor threshold, intracortical facilitation, and motor evoked potential amplitude. A literature search was performed using PubMed, Ovid Medline, Embase Psychiatry and PsycINFO 1990 through April 2012.

RESULTS

A significant Hedge's g was found for decreased SICI (g=0.572, 95% confidence interval [0.179, 0.966], p=0.004), enhanced intracortical facilitation (g=0.446, 95% confidence interval [0.042, 0.849], p=0.030) and decreased CSP (g=-0.466, 95% confidence interval [-0.881, -0.052], p=0.027) within the OCD population. For MDD, significant effect sizes were demonstrated for decreased SICI (g=0.641, 95% confidence interval [0.384, 0.898], p=0.000) and shortened CSP (g=-1.232, 95% confidence interval [-1.530, -0.933], p=0.000). In SCZ, a significant Hedge's g was shown for decreased SICI (g=0.476, 95% confidence interval [0.331, 0.620], p=0.000).

CONCLUSION

Inhibitory deficits are a ubiquitous finding across OCD, MDD, SCZ and enhancement of intracortical facilitation is specific to OCD.

SIGNIFICANCE

Provides a clear platform from which diagnostic procedures can be developed.

Hand posture classification using electrocorticography signals in the gamma band over human sensorimotor brain areas

OBJECTIVE

Brain-machine interface systems translate recorded neural signals into command signals for assistive technology. In individuals with upper limb amputation or cervical spinal cord injury, the restoration of a useful hand grasp could significantly improve daily function. We sought to determine if electrocorticographic (ECoG) signals contain sufficient information to select among multiple hand postures for a prosthetic hand, orthotic, or functional electrical stimulation system.

APPROACH

We recorded ECoG signals from subdural macro- and microelectrodes implanted in motor areas of three participants who were undergoing inpatient monitoring for diagnosis and treatment of intractable epilepsy. Participants performed five distinct isometric hand postures, as well as four distinct finger movements. Several control experiments were attempted in order to remove sensory information from the classification results. Online experiments were performed with two participants.

MAIN RESULTS

Classification rates were 68%, 84% and 81% for correct identification of 5 isometric hand postures offline. Using 3 potential controls for removing sensory signals, error rates were approximately doubled on average (2.1×). A similar increase in errors (2.6×) was noted when the participant was asked to make simultaneous wrist movements along with the hand postures. In online experiments, fist versus rest was successfully classified on 97% of trials; the classification output drove a prosthetic hand. Online classification performance for a larger number of hand postures remained above chance, but substantially below offline performance. In addition, the long integration windows used would preclude the use of decoded signals for control of a BCI system.

SIGNIFICANCE

These results suggest that ECoG is a plausible source of command signals for prosthetic grasp selection. Overall, avenues remain for improvement through better electrode designs and placement, better participant training, and characterization of non-stationarities such that ECoG could be a viable signal source for grasp control for amputees or individuals with paralysis.

fNIRS exhibits weak tuning to hand movement direction

Functional near-infrared spectroscopy (fNIRS) has become an established tool to investigate brain function and is, due to its portability and resistance to electromagnetic noise, an interesting modality for brain-machine interfaces (BMIs). BMIs have been successfully realized using the decoding of movement kinematics from intra-cortical recordings in monkey and human. Recently, it has been shown that hemodynamic brain responses as measured by fMRI are modulated by the direction of hand movements. However, quantitative data on the decoding of movement direction from hemodynamic responses is still lacking and it remains unclear whether this can be achieved with fNIRS, which records signals at a lower spatial resolution but with the advantage of being portable. Here, we recorded brain activity with fNIRS above different cortical areas while subjects performed hand movements in two different directions. We found that hemodynamic signals in contralateral sensorimotor areas vary with the direction of movements, though only weakly. Using these signals, movement direction could be inferred on a single-trial basis with an accuracy of ∼65% on average across subjects. The temporal evolution of decoding accuracy resembled that of typical hemodynamic responses observed in motor experiments. Simultaneous recordings with a head tracking system showed that head movements, at least up to some extent, do not influence the decoding of fNIRS signals. Due to the low accuracy, fNIRS is not a viable alternative for BMIs utilizing decoding of movement direction. However, due to its relative resistance to head movements, it is promising for studies investigating brain activity during motor experiments.

Dynamical degrees of freedom and correlations in isometric finger force production

Prior research has concluded that the correlations of isometric finger forces represent the extent to which the fingers are controlled as a single unit. If this is the case, finger force correlations should be consistent with estimates of the controlled (dynamical) degrees of freedom in finger forces. The present study examined the finger force correlations and the dynamical degrees of freedom in four isometric force tasks. The tasks were to produce a preferred level of force with the (a) Index, (b) Ring, (c) Both fingers and also to (d) Rest the fingers on the load cells. Dynamical degrees of freedom in finger forces were lowest in the Both finger force task and progressively higher in the Ring, Index and Resting finger force tasks. The finger force correlations were highest in the Resting and lowest in the Index and Ring finger tasks. The results for the dynamical degrees of freedom in finger forces were consistent with a reduction in degrees of freedom in response to the degrees of freedom problem and the task constraints. The results for the finger force correlations were inconsistent with a reduction in the dynamical degrees of freedom. These findings indicate that finger force correlations do not necessarily reflect the coupling of finger forces. The findings also highlight the value of time-domain analyses to reveal the organization of control in isometric finger forces.

Neuron Selection by Relative Importance for Neural Decoding of Dexterous Finger Prosthesis Control Application

Future generations of upper limb prosthesis will have dexterous hand with individual fingers and will be controlled directly by neural signals. Neurons from the primary motor (M1) cortex code for finger movements and provide the source for neural control of dexterous prosthesis. Each neuron's activation can be quantified by the change in firing rate before and after finger movement, and the quantified value is then represented by the neural activity over each trial for the intended movement. Since this neural activity varies with the intended movement, we define the relative importance of each neuron independent of specific intended movements. The relative importance of each neuron is determined by the inter-movement variance of the neural activities for respective intended movements. Neurons are ranked by the relative importance and then a subpopulation of rank-ordered neurons is selected for the neural decoding. The use of the proposed neuron selection method in individual finger movements improved decoding accuracy by 21.5% in the case of decoding with only 5 neurons and by 9.2% in the case of decoding with only 10 neurons. With only 15 highly-ranked neurons, a decoding accuracy of 99.5% was achieved. The performance improvement is still maintained when combined movements of two fingers were included though the decoding accuracy fell to 95.7%. Since the proposed neuron selection method can achieve the targeting accuracy of decoding algorithms with less number of input neurons, it can be significant for developing brain-machine interfaces for direct neural control of hand prostheses.

Inhibition of the cortex using transcranial magnetic stimulation in psychiatric populations: current and future directions

Several lines of evidence suggest that deficits in γ-aminobutyric acid (GABA) inhibitory neurotransmission are implicated in the pathophysiology of schizophrenia, bipolar disorder, major depressive disorder and obsessive-compulsive disorder. Cortical inhibition refers to a neurophysiological process, whereby GABA inhibitory interneurons selectively attenuate pyramidal neurons. Transcranial magnetic stimulation (TMS) represents a noninvasive technique to measure cortical inhibition, excitability and plasticity in the cortex. These measures were traditionally specific to the motor cortex, which is an important limitation when nonmotor neurophysiological processes are of primary interest. Recently, TMS has been combined with electro encephalography (EEG) to derive such measurements directly from the cortex. This review focuses on neurophysiological studies related to inhibitory and excitatory TMS paradigms, linking dysfunctional GABAergic neurotransmission to disease states. We review evidence that suggests cortical inhibition deficits among psychiatric populations and demonstrate how each disorder has a specific neurophysiological response to treatment. We conclude by discussing the future directions of TMS combined with EEG, demonstrating the potential to identify biological markers of neuropsychiatric disorders.

Human motor cortical activity is selectively phase-entrained on underlying rhythms

The functional significance of electrical rhythms in the mammalian brain remains uncertain. In the motor cortex, the 12-20 Hz beta rhythm is known to transiently decrease in amplitude during movement, and to be altered in many motor diseases. Here we show that the activity of neuronal populations is phase-coupled with the beta rhythm on rapid timescales, and describe how the strength of this relation changes with movement. To investigate the relationship of the beta rhythm to neuronal dynamics, we measured local cortical activity using arrays of subdural electrocorticographic (ECoG) electrodes in human patients performing simple movement tasks. In addition to rhythmic brain processes, ECoG potentials also reveal a spectrally broadband motif that reflects the aggregate neural population activity beneath each electrode. During movement, the amplitude of this broadband motif follows the dynamics of individual fingers, with somatotopically specific responses for different fingers at different sites on the pre-central gyrus. The 12-20 Hz beta rhythm, in contrast, is widespread as well as spatially coherent within sulcal boundaries and decreases in amplitude across the pre- and post-central gyri in a diffuse manner that is not finger-specific. We find that the amplitude of this broadband motif is entrained on the phase of the beta rhythm, as well as rhythms at other frequencies, in peri-central cortex during fixation. During finger movement, the beta phase-entrainment is diminished or eliminated. We suggest that the beta rhythm may be more than a resting rhythm, and that this entrainment may reflect a suppressive mechanism for actively gating motor function.

Double representation of the wrist and elbow in human motor cortex

Movements of the fingers, hand and arm involve overlapping neural representations in primary motor cortex (M1). Monkey M1 exhibits a core-surround organisation in which cortical representation of the hand and fingers is surrounded by representations of the wrist, elbow and shoulder. A potentially homologous organisation in human M1 has only been observed in a single study, a functional MRI (fMRI) study by [J.D. Meier, T.N. Aflalo, S. Kastner & M.S. Graziano.(2008) J Neurophysiol, 100(4), 1800-1812]. The results of their study suggested a double representation of the wrist in human M1, an unprecedented finding. Our purpose was to document and simultaneously provide evidence that would extend the presence of double representation of the wrist to that of the elbow. Using fMRI, we observed somatotopic maps in M1 and the supplementary motor area (SMA), the only other cortical area that showed robust within-limb somatotopy during self-timed finger, wrist and elbow movements. We observed double wrist and elbow representation that bracketed finger fMRI responses in M1 and the SMA. Our results show that the cortical locations of these double representations are well predicted by local cortical anatomy. Double representation of the wrist and elbow is important because it violates the traditional somatotopic progression in M1 but it is consistent with the representation of synergistic movements involving adjacent effectors.

Spatial organization of cortical and spinal neurons controlling motor behavior

A major task of the central nervous system (CNS) is to control behavioral actions, which necessitates a precise regulation of muscle activity. The final components of the circuitry controlling muscles are the motorneurons, which settle into pools in the ventral horn of the spinal cord in positions that mirror the musculature organization within the body. This 'musculotopic' motor-map then becomes the internal CNS reference for the neuronal circuits that control motor commands. This review describes recent progress in defining the neuroanatomical organization of the higher-order motor circuits in the cortex and spinal cord, and our current understanding of the integrative features that contribute to complex motor behaviors. We highlight emerging evidence that cortical and spinal motor command centers are loosely organized with respect to the musculotopic spatial-map, but these centers also incorporate organizational features that associate with the function of different muscle groups during commonly enacted behaviors.

Speed invariance of independent control of finger movements in pianists

Independent control of finger movements characterizes skilled motor behaviors such as tool use and musical performance. The purpose of the present study was to identify the effect of movement frequency (tempo) on individuated finger movements in piano playing. Joint motion at the digits was recorded while 5 expert pianists were playing 30 excerpts from musical pieces with different fingering and key locations either at a predetermined normal tempo or as fast as possible. Principal component analysis and cluster analysis using an expectation-maximization algorithm determined three distinct patterns of finger movement coordination for a keypress with each of the index, middle, ring, and little fingers at each of the two tempi. The finger kinematics of each coordination pattern was overall similar across the tempi. Tone sequences assigned into each cluster were also similar for both tempi. A linear regression analysis determined no apparent difference in the amount of movement covariation between the striking and nonstriking fingers at both metacarpo-phalangeal and proximal-interphalangeal joints across the two tempi, which indicated no effect of tempo on independent finger movements in piano playing. In addition, the standard deviation of interkeystroke interval across strokes did not differ between the two tempi, indicating maintenance of rhythmic accuracy of keystrokes. Strong temporal constraints on finger movements during piano playing may underlie the maintained independent control of fingers over a wider range of tempi, a feature being likely to be specific to skilled pianists.

Preoperative multimodal motor mapping: a comparison of magnetoencephalography imaging, navigated transcranial magnetic stimulation, and direct cortical stimulation

OBJECT

Direct cortical stimulation (DCS) is the gold-standard technique for motor mapping during craniotomy. However, preoperative noninvasive motor mapping is becoming increasingly accurate. Two such noninvasive modalities are navigated transcranial magnetic stimulation (TMS) and magnetoencephalography (MEG) imaging. While MEG imaging has already been extensively validated as an accurate modality of noninvasive motor mapping, TMS is less well studied. In this study, the authors compared the accuracy of TMS to both DCS and MEG imaging.

METHODS

Patients with tumors in proximity to primary motor cortex underwent preoperative TMS and MEG imaging for motor mapping. The patients subsequently underwent motor mapping via intraoperative DCS. The loci of maximal response were recorded from each modality and compared. Motor strength was assessed at 3 months postoperatively.

RESULTS

Transcranial magnetic stimulation and MEG imaging were performed on 24 patients. Intraoperative DCS yielded 8 positive motor sites in 5 patients. The median distance ± SEM between TMS and DCS motor sites was 2.13 ± 0.29 mm, and between TMS and MEG imaging motor sites was 4.71 ± 1.08 mm. In no patients did DCS motor mapping reveal a motor site that was unrecognized by TMS. Three of 24 patients developed new, early neurological deficit in the form of upper-extremity paresis. At the 3-month follow-up evaluation, 2 of these patients were significantly improved, experiencing difficulty only with fine motor tasks; the remaining patient had improvement to 4/5 strength. There were no deaths over the course of the study.

CONCLUSIONS

Maps of the motor system generated with TMS correlate well with those generated by both MEG imaging and DCS. Negative TMS mapping also correlates with negative DCS mapping. Navigated TMS is an accurate modality for noninvasively generating preoperative motor maps.

A new method of accurate hand- and arm-tracking for small primates

The investigation of grasping movements in cortical motor areas depends heavily on the measurement of hand kinematics. Currently used methods for small primates need either a large number of sensors or provide insufficient accuracy. Here, we present both a novel glove based on electromagnetic tracking sensors that can operate at a rate of 100 Hz and a new modeling method that allows to monitor 27 degrees of freedom (DOF) of the hand and arm using only seven sensors. A rhesus macaque was trained to wear the glove while performing precision and power grips during a delayed grasping task in the dark without noticeable hindrance. During five recording sessions all 27 joint angles and their positions could be tracked reliably. Furthermore, the field generator did not interfere with electrophysiological recordings below 1 kHz and did not affect single-cell separation. Measurements with the glove proved to be accurate during static and dynamic testing (mean absolute error below 2° and 3°, respectively). This makes the glove a suitable solution for characterizing electrophysiological signals with respect to hand grasping and in particular for brain-machine interface applications.

Identifying neuron communities during a reach and grasp task using an unsupervised clustering analysis

Recent advances in brain-machine interfaces (BMIs) have allowed for high density recordings using microelectrode arrays. However, these large datasets present a challenge in how to practically identify features of interest and discard non-task-related neurons. Thus, we apply a previously reported unsupervised clustering analysis to neural data acquired from a non-human primate as it performed a center-out reach-and-grasp task. Although neurons were recorded from multiple arrays across motor and premotor areas, neurons were found to cluster into only two groups which differ by their mean firing rate. No spatial distribution of neurons was evident in different groups, either across arrays or at different depths. Using a Kalman filter to decode arm, hand, and finger kinematics, we find that using neurons from only one of the groups resulted in higher decoding accuracy (r=0.73) than using randomly selected neurons (r=0.68). This suggests that the proposed method can be used to prune the input space and identify an optimal population of neurons for BMI tasks.

Spatiotemporal variation of multiple neurophysiological signals in the primary motor cortex during dexterous reach-to-grasp movements

To examine the spatiotemporal distribution of discriminable information about reach-to-grasp movements in the primary motor cortex upper extremity representation, we implanted four microelectrode arrays in the anterior bank and lip of the central sulcus in each of two monkeys. We used linear discriminant analysis to compare information, quantified as decoding accuracy, contained in various neurophysiological signals. For all signal types, decoding accuracy increased immediately after the movement cue, peaked around movement onset, and declined during the static hold. Spike recordings and local field potential (LFP) time domain amplitude provided more discriminable information than LFP frequency domain power. Discriminable information on movement type was distributed evenly across recording sites by LFP amplitude and 1-4 Hz power but unevenly by 100-170 Hz power and spike recordings. These latter two signal types provided higher decoding accuracies closer to the hemispheric surface than deep in the anterior bank and also provided accuracies that varied along the central sulcus. This variation in the distribution of movement-type information may be related to differences in the rostral versus caudal regions of the primary motor cortex and to its underlying somatotopic organization. The even distribution of information by LFP amplitude and 1-4 Hz power compared with the more localized distribution by 100-170 Hz power and spikes suggest that these different neurophysiological signals reflect different underlying processes that distribute information through the motor cortex during reach-to-grasp movements.

Direction of movement is encoded in the human primary motor cortex

The present study investigated how direction of hand movement, which is a well-described parameter in cerebral organization of motor control, is incorporated in the somatotopic representation of the manual effector system in the human primary motor cortex (M1). Using functional magnetic resonance imaging (fMRI) and a manual step-tracking task we found that activation patterns related to movement in different directions were spatially disjoint within the representation area of the hand on M1. Foci of activation related to specific movement directions were segregated within the M1 hand area; activation related to direction 0° (right) was located most laterally/superficially, whereas directions 180° (left) and 270° (down) elicited activation more medially within the hand area. Activation related to direction 90° was located between the other directions. Moreover, by investigating differences between activations related to movement along the horizontal (0°+180°) and vertical (90°+270°) axis, we found that activation related to the horizontal axis was located more anterolaterally/dorsally in M1 than for the vertical axis, supporting that activations related to individual movement directions are direction- and not muscle related. Our results of spatially segregated direction-related activations in M1 are in accordance with findings of recent fMRI studies on neural encoding of direction in human M1. Our results thus provide further evidence for a direct link between direction as an organizational principle in sensorimotor transformation and movement execution coded by effector representations in M1.

Improving human plateaued motor skill with somatic stimulation

Procedural motor learning includes a period when no substantial gain in performance improvement is obtained even with repeated, daily practice. Prompted by the potential benefit of high-frequency transcutaneous electrical stimulation, we examined if the stimulation to the hand reduces redundant motor activity that likely exists in an acquired hand motor skill, so as to further upgrade stable motor performance. Healthy participants were trained until their motor performance of continuously rotating two balls in the palm of their right hand became stable. In the series of experiments, they repeated a trial performing this cyclic rotation as many times as possible in 15 s. In trials where we applied the stimulation to the relaxed thumb before they initiated the task, most reported that their movements became smoother and they could perform the movements at a higher cycle compared to the control trials. This was not possible when the dorsal side of the wrist was stimulated. The performance improvement was associated with reduction of amplitude of finger displacement, which was consistently observed irrespective of the task demands. Importantly, this kinematic change occurred without being noticed by the participants, and their intentional changes of motor strategies (reducing amplitude of finger displacement) never improved the performance. Moreover, the performance never spontaneously improved during one-week training without stimulation, whereas the improvement in association with stimulation was consistently observed across days during training on another week combined with the stimulation. The improved effect obtained in stimulation trials on one day partially carried over to the next day, thereby promoting daily improvement of plateaued performance, which could not be unlocked by the first-week intensive training. This study demonstrated the possibility of effectively improving a plateaued motor skill, and pre-movement somatic stimulation driving this behavioral change.

Plasticity in cortical motor upper-limb representation following stroke and rehabilitation: two longitudinal multi-joint FMRI case-studies

Motor dysfunction and recovery following stroke and rehabilitation are associated with primary motor cortex plasticity. To better track these effects we studied two patients with sub-acute sub-cortical stroke causing hemiparesis, who underwent an effective behavioral treatment termed Constraint Induced Movement Therapy (CIMT). The therapy involves 2 weeks of intensive motor training of the hemiparetic limb coupled with immobilization of the unaffected limb. The study included a longitudinal series of clinical evaluations and fMRI scans, before and after the treatment. The fMRI task included wrist, elbow, or ankle movements. Activity in the M1 upper-limb region of control subjects was stable, strictly contralateral, and similar in amplitude for elbow and wrist movements. These findings reflect the well-known contralateral motor control and support the idea of overlapping representations of adjacent joints in M1. In both patients, pre-CIMT activation patterns in M1 were tested twice and did not change significantly, were contralateral, and included elbow-wrist differences. Following CIMT, the clinical condition of both patients improved and three fMRI-explored prototypes were found: First, cluster position remained constant; Second, ipsilateral activity appeared in the unaffected hemispheres during hemiparetic movements; Third, patient-specific elbow-wrist inter and intra hemispheric differences were modified. All effects were long-lasting. We suggest that overlapping representations of adjacent joints contributed to the cortical plasticity observed following CIMT. Our findings should be confirmed by studying larger groups of homogeneous patients. Nevertheless, this study introduces multi-joint imaging studies and shows that it is both possible and valuable to carry it out in stroke patients.

Functional recovery following motor cortex lesions in non-human primates: experimental implications for human stroke patients

This review discusses selected classical works and contemporary research on recovery of contralesional fine hand motor function following lesions to motor areas of the cerebral cortex in non-human primates. Findings from both the classical literature and contemporary studies show that lesions of cortical motor areas induce paresis initially, but are followed by remarkable recovery of fine hand/digit motor function that depends on lesion size and post-lesion training. Indeed, in recent work where considerable quantification of fine digit function associated with grasping and manipulating small objects has been observed, very favorable recovery is possible with minimal forced use of the contralesional limb. Studies of the mechanisms underlying recovery have shown that following small lesions of the digit areas of primary motor cortex (M1), there is expansion of the digit motor representations into areas of M1 that did not produce digit movements prior to the lesion. However, after larger lesions involving the elbow, wrist and digit areas of M1, no such expansion of the motor representation was observed, suggesting that recovery was due to other cortical or subcortical areas taking over control of hand/digit movements. Recently, we showed that one possible mechanism of recovery after lesion to the arm areas of M1 and lateral premotor cortex is enhancement of corticospinal projections from the medially located supplementary motor area (M2) to spinal cord laminae containing neurons which have lost substantial input from the lateral motor areas and play a critical role in reaching and digit movements. Because human stroke and brain injury patients show variable, and usually poorer, recovery of hand motor function than that of nonhuman primates after motor cortex damage, we conclude with a discussion of implications of this work for further experimentation to improve recovery of hand function in human stroke patients.

Hand kinematics of piano playing

Dexterous use of the hand represents a sophisticated sensorimotor function. In behaviors such as playing the piano, it can involve strong temporal and spatial constraints. The purpose of this study was to determine fundamental patterns of covariation of motion across joints and digits of the human hand. Joint motion was recorded while 5 expert pianists played 30 excerpts from musical pieces, which featured ∼50 different tone sequences and fingering. Principal component analysis and cluster analysis using an expectation-maximization algorithm revealed that joint velocities could be categorized into several patterns, which help to simplify the description of the movements of the multiple degrees of freedom of the hand. For the thumb keystroke, two distinct patterns of joint movement covariation emerged and they depended on the spatiotemporal patterns of the task. For example, the thumb-under maneuver was clearly separated into two clusters based on the direction of hand translation along the keyboard. While the pattern of the thumb joint velocities differed between these clusters, the motions at the metacarpo-phalangeal and proximal-phalangeal joints of the four fingers were more consistent. For a keystroke executed with one of the fingers, there were three distinct patterns of joint rotations, across which motion at the striking finger was fairly consistent, but motion of the other fingers was more variable. Furthermore, the amount of movement spillover of the striking finger to the adjacent fingers was small irrespective of the finger used for the keystroke. These findings describe an unparalleled amount of independent motion of the fingers.

Selective BOLD responses to individual finger movement measured with fMRI at 3T

Although the gross somatotopic organization of the posterior bank of the precentral gyrus is well established, a fine scale organization of the representations of the digits of the hand has not been fully characterized. Previous neuroimaging studies have failed to find clear evidence for a specificity of digit representations in motor cortex, but rather report a distributed network of control. Reported here are the results of two experiments; in Experiment 1 a sequential finger tapping task produced strong blood oxygen level dependent (BOLD) responses in the contralateral precentral gyrus, but there was a lack of specificity for distinguishing individual representations. A randomly ordered task did accomplish this goal. In the second experiment, a randomly ordered finger-tapping task was used and the findings demonstrated BOLD responses in clusters of voxels specific to movement of a single digit. The region of interest defined for each digit comprised several noncontiguous clusters. A "selectivity index" was developed to quantify the magnitude of the BOLD response to the movement of a specific digit, relative to BOLD response associated with movement of other digits. Strong evidence of BOLD selectivity (albeit not exclusivity) was found in the hemisphere contralateral to the cued digit; however, there was no evidence for an orderly spatial topography. These findings demonstrate that a selectivity of activation is quantifiable, supports a theory of noncontiguous distribution of control, and provides a method for comparing between healthy and impaired populations and investigating changes following training or intervention.

Propagating waves in human motor cortex

Previous studies in non-human primates (NHPs) have shown that beta oscillations (15–30 Hz) of local field potentials (LFPs) in the arm/hand areas of primary motor cortex (MI) propagate as traveling waves across the cortex. These waves exhibited two stereotypical features across animals and tasks: (1) The waves propagated in two dominant modal directions roughly 180° apart, and (2) their propagation speed ranged from 10 to 35 cm/s. It is, however, unknown if such cortical waves occur in the human motor cortex. This study shows that the two properties of propagating beta waves are present in MI of a tetraplegic human patient while he was instructed to perform an instruction delay center-out task using a cursor controlled by the chin. Moreover, we show that beta waves are sustained and have similar properties whether the subject was engaged in the task or at rest. The directions of the successive sustained waves both in the human subject and a NHP subject tended to switch from one dominant mode to the other, and at least in the NHP subject the estimated distance traveled between successive waves traveling into and out of the central sulcus is consistent with the hypothesis of wave reflection between the border of motor and somatosensory cortices. Further, we show that the occurrence of the beta waves is not uniquely tied to periods of increased power in the beta frequency band. These results demonstrate that traveling beta waves in MI are a general phenomenon occurring in human as well as NHPs. Consistent with the NHP data, the dominant directions of the beta LFP waves in human aligned to the proximal to distal gradient of joint representations in MI somatotopy. This consistent finding of wave propagation may imply the existence of a hardwired organization of motor cortex that mediates this spatiotemporal pattern.

Integration of sensory and motor representations of single fingers in the human cerebellum

The cerebellum is thought to play a key role in the integration of sensory and motor events. Little is known, however, about how sensory and motor maps in the cerebellum superimpose. In the present study we investigated the relationship between these two maps for the representation of single fingers. Participants made isometric key presses with individual fingers or received vibratory tactile stimulation to the fingertips while undergoing high-resolution functional magnetic resonance imaging (fMRI). Using multivariate analysis, we have demonstrated that the ipsilateral lobule V and VIII show patterns of activity that encode, within the same region, both which finger pressed and which finger was stimulated. The individual finger-specific activation patches are smaller than 3 mm and only show a weak somatotopic organization. To study the superposition of sensory and motor maps, we correlated the finger-specific patterns across the two conditions. In the neocortex, sensory stimulation of one digit led to activation of the same patches as force production by the same digit; in the cerebellum, these activation patches were organized in an uncorrelated manner. This suggests that, in the cerebellum, a movement of a particular finger is paired with a range of possible sensory outcomes. In summary, our results indicate a small and fractured representation of single digits in the cerebellum and suggest a fundamental difference in how the cerebellum and the neocortex integrate sensory and motor events.

Evidence for potentials and limitations of brain plasticity using an atlas of functional resectability of WHO grade II gliomas: towards a "minimal common brain"

Despite recent advances in non-invasive brain mapping imaging, the resectability of a given area in a patient harboring a WHO grade II glioma cannot be predicted preoperatively with high reliability, due to mechanisms of functional reorganization. Therefore, intraoperative mapping by direct electrical stimulation remains the gold standard for detection and preservation of eloquent areas during glioma surgery, because it enables to perform on-line anatomo-functional correlations. To study potentials and limitations of brain plasticity, we gathered 58 postoperative MRI of patients operated on for a WHO grade II glioma under direct electrical cortico-subcortical stimulation. Postoperative images were registered on the MNI template to construct an atlas of functional resectability for which each voxel represents the probability to observe residual non-resectable tumor, that is, non-compensable area. The resulting atlas offers a rigorous framework to identify areas with high plastic potential (i.e. with probabilities of residual tumor close to 0), with low compensatory capabilities (i.e. probabilities of residual tumor close to 1) and with intermediate level of resectability (probability around 0.5). The resulting atlas highlights the utmost importance of preserving a core of connectivity through the main associative pathways, namely, it supports the existence of a "minimal common brain" among patients.