Ventral Premotor Research Articles

Action simulation and mirroring in children with autism spectrum disorders

Mental imitation, perhaps a precursor to motor imitation, involves visual perspective-taking and motor imagery. Research on mental imitation in autism spectrum disorders (ASD) has been rather limited compared to that on motor imitation. The main objective of this fMRI study is to determine the differences in brain responses underlying mirroring and mentalizing networks during mental imitation in children and adolescents with ASD. Thirteen high-functioning children and adolescents with ASD and 15 age-and- IQ-matched typically developing (TD) control participants took part in this fMRI study. In the MRI scanner, participants were shown cartoon pictures of people performing everyday actions (Transitive actions: e.g., ironing clothes but with the hand missing; and Intransitive actions: e.g., clapping hands with the palms missing) and were asked to identify which hand or palm orientation would best fit the gap. The main findings are: 1) both groups performed equally while processing transitive and intransitive actions; 2) both tasks yielded activation in the bilateral inferior frontal gyrus (IFG) and inferior parietal lobule (IPL) in ASD and TD groups; 3) Increased activation was seen in ASD children, relative to TD, in left ventral premotor and right middle temporal gyrus during intransitive actions; and 4) ASD symptom severity positively correlated with activation in left parietal, right middle temporal, and right premotor regions across all subjects. Overall, our findings suggest that regions mediating mirroring may be recruiting more brain resources in ASD and may have implications for understanding social movement through modeling.

Longitudinal Structural and Functional Differences Between Proportional and Poor Motor Recovery After Stroke

Background. Evolution of motor function during the first months after stroke is stereotypically bifurcated, consisting of either recovery to about 70% of maximum possible improvement (“proportional recovery, PROP”) or in little to no improvement (“poor recovery, POOR”). There is currently no evidence that any rehabilitation treatment will prevent POOR and favor PROP. Objective. To perform a longitudinal and multimodal assessment of functional and structural changes in brain organization associated with PROP. Methods. Fugl-Meyer Assessments of the upper extremity and high-density electroencephalography (EEG) were obtained from 63 patients, diffusion tensor imaging from 46 patients, at 2 and 4 weeks (T0) and at 3 months (T1) after stroke onset. Results. We confirmed the presence of 2 distinct recovery patterns (PROP and POOR) in our sample. At T0, PROP patients had greater integrity of the corticospinal tract (CST) and greater EEG functional connectivity (FC) between the affected hemisphere and rest of the brain, in particular between the ventral premotor and the primary motor cortex. POOR patients suffered from degradation of corticocortical and corticofugal fiber tracts in the affected hemisphere between T0 and T1, which was not observed in PROP patients. Better initial CST integrity correlated with greater initial global FC, which was in turn associated with less white matter degradation between T0 and T1. Conclusions. These findings suggest links between initial CST integrity, systems-level cortical network plasticity, reduction of white matter atrophy, and clinical motor recovery after stroke. This identifies candidate treatment targets.

Cortical Afferents and Myeloarchitecture Distinguish the Medial Intraparietal Area (MIP) from Neighboring Subdivisions of the Macaque Cortex.

The parietal reach region (PRR) in the medial bank of the macaque intraparietal sulcus has been a subject of considerable interest in research aimed at the development of brain-controlled prosthetic arms, but its anatomical organization remains poorly characterized. We examined the anatomical organization of the putative PRR territory based on myeloarchitecture and retrograde tracer injections. We found that the medial bank includes three areas: an extension of the dorsal subdivision of V6A (V6Ad), the medial intraparietal area (MIP), and a subdivision of area PE (PEip). Analysis of corticocortical connections revealed that both V6Ad and MIP receive inputs from visual area V6; the ventral subdivision of V6A (V6Av); medial (PGm, 31), superior (PEc), and inferior (PFG/PF) parietal association areas; and intraparietal areas AIP and VIP. They also receive long-range projections from the superior temporal sulcus (MST, TPO), cingulate area 23, and the dorsocaudal (area F2) and ventral (areas F4/F5) premotor areas. In comparison with V6Ad, MIP receives denser input from somatosensory areas, the primary motor cortex, and the medial motor fields, as well as from visual cortex in the ventral precuneate cortex and frontal regions associated with oculomotor guidance. Unlike MIP, V6Ad receives stronger visual input, from the caudal inferior parietal cortex (PG/Opt) and V6Av, whereas PEip shows marked emphasis on anterior parietal, primary motor, and ventral premotor connections. These anatomical results suggest that MIP and V6A have complementary roles in sensorimotor behavior, with MIP more directly involved in movement planning and execution in comparison with V6A.

Decoding Kinematics Using Task-Independent Movement-Phase-Specific Encoding Models

Neural decoders of kinematic variables have largely relied on task-dependent (TD) encoding models of the neural activity. TD decoders, though, require prior knowledge of the tasks, which may be unavailable, lack scalability as the number of tasks grows, and require a large number of trials per task to reduce the effects of neuronal variability. The execution of movements involves a sequence of phases (e.g., idle, planning, and so on) whose progression contributes to the neuronal variability. We hypothesize that information about the movement phase facilitates the decoding of kinematics and compensates for the lack of prior knowledge about the task. We test this hypothesis by designing a task-independent movement-phase-specific (TI-MPS) decoding algorithm. The algorithm assumes that movements proceed through a consistent sequence of phases regardless of the specific task, and it builds one model per phase by combining data from different tasks. Phase transitions are detected online from neural data and, for each phase, a specific encoding model is used. The TI-MPS algorithm was tested on single-unit recordings from 437 neurons in the dorsal and ventral pre-motor cortices from two nonhuman primates performing 3-D multi-object reach-to-grasp tasks. The TI-MPS decoder accurately decoded kinematics from tasks it was not trained for and outperformed TD approaches (one-way ANOVA with Tukey's post-hoc test and -value <0.05). Results indicate that a TI paradigm with MPS models may help decoding kinematics when prior information about the task is unavailable and pave the way toward clinically viable prosthetics.

Corticospinal control from M1 and PMv areas on inhibitory cervical propriospinal neurons in humans.

Inhibitory propriospinal neurons with diffuse projections onto upper limb motoneurons have been revealed in humans using peripheral nerve stimulation. This system is supposed to mediate descending inhibition to motoneurons, to prevent unwilling muscle activity. However, the corticospinal control onto inhibitory propriospinal neurons has never been investigated so far in humans. We addressed the question whether inhibitory cervical propriospinal neurons receive corticospinal inputs from primary motor (M1) and ventral premotor areas (PMv) using spatial facilitation method. We have stimulated M1 or PMv using transcranial magnetic stimulation (TMS) and/or median nerve whose afferents are known to activate inhibitory propriospinal neurons. Potential input convergence was evaluated by studying the change in monosynaptic reflexes produced in wrist extensor electromyogram (EMG) after isolated and combined stimuli in 17 healthy subjects. Then, to determine whether PMv controlled propriospinal neurons directly or through PMv‐M1 interaction, we tested the connectivity between PMv and propriospinal neurons after a functional disruption of M1 produced by paired continuous theta burst stimulation (cTBS). TMS over M1 or PMv produced reflex inhibition significantly stronger on combined stimulations, compared to the algebraic sum of effects induced by isolated stimuli. The extra‐inhibition induced by PMv stimulation remained even after cTBS which depressed M1 excitability. The extra‐inhibition suggests the existence of input convergence between peripheral afferents and corticospinal inputs onto inhibitory propriospinal neurons. Our results support the existence of direct descending influence from M1 and PMv onto inhibitory propriospinal neurons in humans, possibly though direct corticospinal or via reticulospinal inputs.

Cerebello-Cortical Differences in Effective Connectivity of the Dominant and Non-dominant Hand during a Visuomotor Paradigm of Grip Force Control.

Structural and functional differences are known to exist within the cortical sensorimotor networks with respect to the dominant vs. non-dominant hand. Similarly, the cerebellum, a key structure in the sensorimotor network with its cerebello-cortical connections, has been reported to respond differently when using the dominant vs. non-dominant hand. Several groups have already investigated causal interactions during diverse motor paradigms using effective connectivity but few have studied the larger visuomotor network, including key structures such as the parietal cortex and the cerebellum, with both hands. Moreover, the effect of force level on such interactions is still unclear. We therefore sought to determine the hemispheric asymmetries in the cerebello-cortical sensorimotor network in right-handers at two force levels (5% and 10% maximum voluntary contraction) for both hands. Cerebello-cortical modulations were investigated in 28 healthy, right-handed volunteers by determining the effective connectivity during a visuomotor task at two force levels under fMRI. A network was built consisting of the left and right primary motor (M1), ventral premotor (PMv) and posterior parietal cortices (PPC), in addition to the supplementary motor area (SMA), and the ipsilateral cerebellum (Cer) to the hand performing the motor task. Task performance (precision of isometric grip force tracking) did not differ between hands, nor did task-related activations in the sensorimotor areas apart from the contralateral primary motor cortex. However, during visuomotor control of the non-dominant hand, connectivity analysis revealed causal modulations between (i) the ipsilateral cerebellum and SMA, and (ii) the ipsilatearl cerebellum and contralateral PPC, which was not the case when using the dominant hand. These cerebello-cortical modulations for the non-dominant hand were more present at the higher of the two force levels. We conclude that precision force generation executed with the non-dominant hand, compared to the dominant hand, may require enhanced cerebello-cortical interaction to ensure equivalent left-right task performance.

Decoding finger movement in humans using synergy of EEG cortical current signals

The synchronized activity of neuronal populations across multiple distant brain areas may reflect coordinated interactions of large-scale brain networks. Currently, there is no established method to investigate the temporal transitions between these large-scale networks that would allow, for example, to decode finger movements. Here we applied a matrix factorization method employing principal component and temporal independent component analyses to identify brain activity synchronizations. In accordance with previous studies investigating “muscle synergies”, we refer to this activity as “brain activity synergy”. Using electroencephalography (EEG), we first estimated cortical current sources (CSs) and then identified brain activity synergies within the estimated CS signals. A decoding analysis for finger movement in eight directions showed that such CS synergies provided more information for dissociating between movements than EEG sensor signals, EEG synergy, or CS signals, suggesting that temporal activation patterns of the synchronizing CSs may contain information related to motor control. A quantitative analysis of features selected by the decoders further revealed temporal transitions among the primary motor area, dorsal and ventral premotor areas, pre-supplementary motor area, and supplementary motor area, which may reflect transitions in motor planning and execution. These results provide a proof of concept for brain activity synergy estimation using CSs.

Neural Patterns of Reorganization after Intensive Robot-Assisted Virtual Reality Therapy and Repetitive Task Practice in Patients with Chronic Stroke.

Several approaches to rehabilitation of the hand following a stroke have emerged over the last two decades. These treatments, including repetitive task practice (RTP), robotically assisted rehabilitation and virtual rehabilitation activities, produce improvements in hand function but have yet to reinstate function to pre-stroke levels—which likely depends on developing the therapies to impact cortical reorganization in a manner that favors or supports recovery. Understanding cortical reorganization that underlies the above interventions is therefore critical to inform how such therapies can be utilized and improved and is the focus of the current investigation. Specifically, we compare neural reorganization elicited in stroke patients participating in two interventions: a hybrid of robot-assisted virtual reality (RAVR) rehabilitation training and a program of RTP training. Ten chronic stroke subjects participated in eight 3-h sessions of RAVR therapy. Another group of nine stroke subjects participated in eight sessions of matched RTP therapy. Functional magnetic resonance imaging (fMRI) data were acquired during paretic hand movement, before and after training. We compared the difference between groups and sessions (before and after training) in terms of BOLD intensity, laterality index of activation in sensorimotor areas, and the effective connectivity between ipsilesional motor cortex (iMC), contralesional motor cortex, ipsilesional primary somatosensory cortex (iS1), ipsilesional ventral premotor area (iPMv), and ipsilesional supplementary motor area. Last, we analyzed the relationship between changes in fMRI data and functional improvement measured by the Jebsen Taylor Hand Function Test (JTHFT), in an attempt to identify how neurophysiological changes are related to motor improvement. Subjects in both groups demonstrated motor recovery after training, but fMRI data revealed RAVR-specific changes in neural reorganization patterns. First, BOLD signal in multiple regions of interest was reduced and re-lateralized to the ipsilesional side. Second, these changes correlated with improvement in JTHFT scores. Our findings suggest that RAVR training may lead to different neurophysiological changes when compared with traditional therapy. This effect may be attributed to the influence that augmented visual and haptic feedback during RAVR training exerts over higher-order somatosensory and visuomotor areas.

Spatial and viewpoint selectivity for others\u2019 observed actions in monkey ventral premotor mirror neurons

The spatial location and viewpoint of observed actions are closely linked in natural social settings. For example, actions observed from a subjective viewpoint necessarily occur within the observer’s peripersonal space. Neurophysiological studies have shown that mirror neurons (MNs) of the monkey ventral premotor area F5 can code the spatial location of live observed actions. Furthermore, F5 MN discharge can also be modulated by the viewpoint from which filmed actions are seen. Nonetheless, whether and to what extent MNs can integrate viewpoint and spatial location of live observed actions remains unknown. We addressed this issue by comparing the activity of 148 F5 MNs while macaque monkeys observed an experimenter grasping in three different combinations of viewpoint and spatial location, namely, lateral view in the (1) extrapersonal and (2) peripersonal space and (3) subjective view in the peripersonal space. We found that the majority of MNs were space-selective (60.8%): those selective for the peripersonal space exhibited a preference for the subjective viewpoint both at the single-neuron and population level, whereas space-unselective neurons were view invariant. These findings reveal the existence of a previously neglected link between spatial and viewpoint selectivity in MN activity during live-action observation.

The extended object-grasping network.

Grasping is the most important skilled motor act of primates. It is based on a series of sensorimotor transformations through which the affordances of the objects to be grasped are transformed into appropriate hand movements. It is generally accepted that a circuit formed by inferior parietal areas AIP and PFG and ventral premotor area F5 represents the core circuit for sensorimotor transformations for grasping. However, selection and control of appropriate grip should also depend on higher-order information, such as the meaning of the object to be grasped, and the overarching goal of the action in which grasping is embedded. In this review, we describe recent findings showing that specific sectors of the ventrolateral prefrontal cortex are instrumental in controlling higher-order aspects of grasping. We show that these prefrontal sectors control the premotor cortex through two main gateways: the anterior subdivision of ventral area F5-sub-area F5a-, and the pre-supplementary area (area F6). We then review functional studies showing that both F5a and F6, besides being relay stations of prefrontal information, also play specific roles in grasping. Namely, sub-area F5a is involved in stereoscopic analysis of 3D objects, and in planning cue-dependent grasping activity. As for area F6, this area appears to play a crucial role in determining when to execute the motor program encoded in the parieto-premotor circuit. The recent discovery that area F6 contains a set of neurons encoding specific grip types suggests that this area, besides controlling "when to go", also may control the grip type, i.e., "how to go". We conclude by discussing clinical syndromes affecting grasping actions and their possible mechanisms.

An input-output linear time invariant model captures neuronal firing responses to external and behavioral events.

Investigating how neurons in different motor regions respond to external stimuli and behavioral events provides insight into motor control. A recent approach to studying neuronal activity is to construct a zero-input linear time invariant (ZI-LTI) state-space model, wherein the state vector consists of firing rate signals for different populations of neurons across motor regions. This approach allows for the populations to influence each other in a dynamical manner given an initial firing rate condition, and the model can accurately reconstruct firing rates within a limited epoch in the motor task during which no event occurs. Here, we generalize this LTI modeling approach to characterize firing responses of neurons to two events (a go cue and movement onset) in a movement task with a non-zero input LTI state-space model, herein referred to as input-output LTI (IO-LTI). Specifically, responses from 196 neurons in the primary motor (M1), ventral premotor (PMv), and dorsal premotor cortex (PMd) were recorded and modeled in two nonhuman primates executing a reach-to-grasp task. We found that a single IO-LTI model can reconstruct neuronal firing rate patterns of six populations of these neurons across the three areas in the presence of multiple events (go cue, movement onset). This is the first step towards constructing generative models of neuronal firing rates in the presence of multiple events, which then can be used to construct better decoders for brain machine interactive control.

Visuotactile integration modulates motor performance in a perceptual decision-making task

Body ownership is critically dependent on multimodal integration as for instance revealed in the Rubber Hand Illusion (RHI) and a number of studies which have addressed the neural correlates of the processes underlying this phenomenon. Both experimental and clinical research have shown that the structures underlying body ownership seem to significantly overlap with those of motor control including the parietal and ventral premotor cortices, Temporal Parietal Junction (TPJ) and the insula. This raises the question of whether this structural overlap between body ownership and motor control structures is of any functional significance. Here, we investigate the specific question of whether experimentally induced ownership over a virtual limb can modulate the performance of that limb in a simple sensorimotor task. Using a Virtual reality (VR) environment we modulate body ownership in three experimental conditions with respect to the (in)congruence of stimulus configurations. Our results show that the degree of ownership directly modulates motor performance. This implies that body ownership is not exclusively a perceptual and/or subjective multimodal state but that it is tightly coupled to systems for decision-making and motor control.

Contrasting Modulatory Effects from the Dorsal and Ventral Premotor Cortex on Primary Motor Cortex Outputs.

The dorsal and ventral premotor cortices (PMd and PMv, respectively) each take part in unique aspects for the planning and execution of hand movements. These premotor areas are components of complex anatomical networks that include the primary motor cortex (M1) of both hemispheres. One way that PMd and PMv could play distinct roles in hand movements is by modulating the outputs of M1 differently. However, patterns of effects from PMd and PMv on the outputs of M1 have not been compared systematically. Our goals were to study how PMd within the same (i.e., ipsilateral or iPMd) and in the opposite hemisphere (i.e., contralateral or cPMd) can shape M1 outputs and then compare these effects with those induced by PMv. We used paired-pulse protocols with intracortical microstimulation techniques in sedated female cebus monkeys while recording EMG signals from intrinsic hand and forearm muscles. A conditioning stimulus was delivered in iPMd or cPMd concurrently or before a test stimulus in M1. The patterns of modulatory effects from PMd were compared with those from PMv collected in the same animals. Striking differences were revealed. Conditioning stimulation in iPMd induced more frequent and powerful inhibitory effects on M1 outputs compared with iPMv. In the opposite hemisphere, cPMd conditioning induced more frequent and powerful facilitatory effects than cPMv. These contrasting patterns of modulatory effects could allow PMd and PMv to play distinct functions for the control of hand movements and predispose them to undertake different, perhaps somewhat opposite, roles in motor recovery after brain injury.SIGNIFICANCE STATEMENT The dorsal and ventral premotor cortices (PMd and PMv, respectively) are two specialized areas involved in the control of hand movements in primates. One way that PMd and PMv could participate in hand movements is by modulating or shaping the primary motor cortex (M1) outputs to hand muscles. Here, we studied the patterns of modulation from PMd within the same and in the opposite hemisphere on the outputs of M1 and compared them with those from PMv. We found that PMd and PMv have strikingly different effects on M1 outputs. These contrasting patterns of modulation provide a substrate that may allow PMd and PMv to carry distinct functions for the preparation and execution of hand movements and for recovery after brain injury.

Neural foundations of overt and covert actions

We used fMRI to assess the human brain areas activated for execution, observation and 1st person motor imagery of a visually guided tracing task with the index finger. Voxel-level conjunction analysis revealed several cortical areas activated in common across all three motor conditions, namely, the upper limb representation of the primary motor and somatosensory cortices, the dorsal and ventral premotor, the superior and inferior parietal cortices as well as the posterior part of the superior and middle temporal gyrus including the temporo-parietal junction (TPj) and the extrastriate body area (EBA). Functional connectivity analyses corroborated the notion that a common sensory-motor fronto-parieto-temporal cortical network is engaged for execution, observation, and imagination of the very same action. Taken together these findings are consistent with the more parsimonious account of motor cognition provided by the mental simulation theory rather than the recently revised mirror neuron view Action imagination and observation were each associated with several additional functional connections, which may serve the distinction between overt action and its covert counterparts, and the attribution of action to the correct agent. For example, the central position of the right middle and inferior frontal gyrus in functional connectivity during motor imagery may reflect the suppression of movements during mere imagination of action, and may contribute to the distinction between ‘imagined’ and ‘real’ action. Also, the central role of the right EBA in observation, assessed by functional connectivity analysis, may be related to the attribution of action to the ‘external agent’ as opposed to the ‘self’.

Decoding Grasping Movements from the Parieto-Frontal Reaching Circuit in the Nonhuman Primate

Prehension movements typically include a reaching phase, guiding the hand toward the object, and a grip phase, shaping the hand around it. The dominant view posits that these components rely upon largely independent parieto-frontal circuits: a dorso-medial circuit involved in reaching and a dorso-lateral circuit involved in grasping. However, mounting evidence suggests a more complex arrangement, with dorso-medial areas contributing to both reaching and grasping. To investigate the role of the dorso-medial reaching circuit in grasping, we trained monkeys to reach-and-grasp different objects in the dark and determined if hand configurations could be decoded from functional magnetic resonance imaging (MRI) responses obtained from the reaching and grasping circuits. Indicative of their established role in grasping, object-specific grasp decoding was found in anterior intraparietal (AIP) area, inferior parietal lobule area PFG and ventral premotor region F5 of the lateral grasping circuit, and primary motor cortex. Importantly, the medial reaching circuit also conveyed robust grasp-specific information, as evidenced by significant decoding in parietal reach regions (particular V6A) and dorsal premotor region F2. These data support the proposed role of dorso-medial "reach" regions in controlling aspects of grasping and demonstrate the value of complementing univariate with more sensitive multivariate analyses of functional MRI (fMRI) data in uncovering information coding in the brain.

Dissociation between sustained single-neuron spiking and transient β-LFP oscillations in primate motor cortex.

Determining the relationship between single-neuron spiking and transient (20 Hz) β-local field potential (β-LFP) oscillations is an important step for understanding the role of these oscillations in motor cortex. We show that whereas motor cortex firing rates and beta spiking rhythmicity remain sustained during steady-state movement preparation periods, β-LFP oscillations emerge, in contrast, as short transient events. Single-neuron mean firing rates within and outside transient β-LFP events showed no differences, and no consistent correlation was found between the beta oscillation amplitude and firing rates, as was the case for movement- and visual cue-related β-LFP suppression. Importantly, well-isolated single units featuring beta-rhythmic spiking (43%, 125/292) showed no apparent or only weak phase coupling with the transient β-LFP oscillations. Similar results were obtained for the population spiking. These findings were common in triple microelectrode array recordings from primary motor (M1), ventral (PMv), and dorsal premotor (PMd) cortices in nonhuman primates during movement preparation. Although beta spiking rhythmicity indicates strong membrane potential fluctuations in the beta band, it does not imply strong phase coupling with β-LFP oscillations. The observed dissociation points to two different sources of variation in motor cortex β-LFPs: one that impacts single-neuron spiking dynamics and another related to the generation of mesoscopic β-LFP signals. Furthermore, our findings indicate that rhythmic spiking and diverse neuronal firing rates, which encode planned actions during movement preparation, may naturally limit the ability of different neuronal populations to strongly phase-couple to a single dominant oscillation frequency, leading to the observed spiking and β-LFP dissociation.NEW & NOTEWORTHY We show that whereas motor cortex spiking rates and beta (~20 Hz) spiking rhythmicity remain sustained during steady-state movement preparation periods, β-local field potential (β-LFP) oscillations emerge, in contrast, as transient events. Furthermore, the β-LFP phase at which neurons spike drifts: phase coupling is typically weak or absent. This dissociation points to two sources of variation in the level of motor cortex beta: one that impacts single-neuron spiking and another related to the generation of measured mesoscopic β-LFPs.

Encoding of Both Reaching and Grasping Kinematics in Dorsal and Ventral Premotor Cortices.

Classically, it has been hypothesized that reach-to-grasp movements arise from two discrete parietofrontal cortical networks. As part of these networks, the dorsal premotor cortex (PMd) has been implicated in the control of reaching movements of the arm, whereas the ventral premotor cortex (PMv) has been associated with the control of grasping movements of the hand. Recent studies have shown that such a strict delineation of function along anatomical boundaries is unlikely, partly because reaching to different locations can alter distal hand kinematics and grasping different objects can affect kinematics of the proximal arm. Here, we used chronically implanted multielectrode arrays to record unit-spiking activity in both PMd and PMv simultaneously while rhesus macaques engaged in a reach-to-grasp task. Generalized linear models were used to predict the spiking activity of cells in both areas as a function of different kinematic parameters, as well as spike history. To account for the influence of reaching on hand kinematics and vice versa, we applied demixed principal components analysis to define kinematics synergies that maximized variance across either different object locations or grip types. We found that single cells in both PMd and PMv encode the kinematics of both reaching and grasping synergies, suggesting that this classical division of reach and grasp in PMd and PMv, respectively, does not accurately reflect the encoding preferences of cells in those areas.SIGNIFICANCE STATEMENT For reach-to-grasp movements, the dorsal premotor cortex (PMd) has been implicated in the control of reaching movements of the arm, whereas the ventral premotor cortex (PMv) has been associated with the control of grasping movements of the hand. We recorded unit-spiking activity in PMd and PMv simultaneously while macaques performed a reach-to-grasp task. We modeled the spiking activity of neurons as a function of kinematic parameters and spike history. We applied demixed principal components analysis to define kinematics synergies. We found that single units in both PMd and PMv encode the kinematics of both reaching and grasping synergies, suggesting that the division of reach and grasp in PMd and PMv, respectively, cannot be made based on their encoding properties.

Common and distinct brain regions processing multisensory bodily signals for peripersonal space and body ownership

We take the feeling that our body belongs to us for granted. However, recent research has shown that it is possible to alter the subjective sensation of body ownership (BO) by manipulating multisensory bodily inputs. Several frontal and parietal regions are known to specifically process multisensory cues presented close to the body, i.e., within the peripersonal space (PPS). It has been proposed that these PPS fronto-parietal regions also underlie BO. However, most previous studies investigated the brain mechanisms of either BO or of PPS processing separately and by using a variety of paradigms. Here, we conducted an extensive meta-analysis of functional neuroimaging studies to investigate PPS and BO processing in humans in order to: a) assess quantitatively where each one of these functions was individually processed in the brain; b) identify whether and where these processes shared common or engaged distinct brain mechanisms; c) characterize these areas in terms of whole-brain co-activation networks and functions, respectively. We identified (i) a bilateral PPS network including superior parietal, temporo-parietal and ventral premotor regions and (ii) a BO network including posterior parietal cortex (right intraparietal sulcus, IPS; and left IPS and superior parietal lobule, SPL), right ventral premotor cortex, and the left anterior insula. Co-activation maps related to both PPS and BO encompassed largely overlapping fronto-parietal networks, but whereas the PPS network was more frequently associated with sensorimotor tasks, the BO network was rather associated with attention and awareness tasks. Finally, the conjunction analysis showed that (iii) PPS and BO tasks anatomically overlapped only in two clusters located in the left parietal cortex (dorsally at the intersection between the SPL, the IPS and area 2 and ventrally between areas 2 and IPS). Distinct activations were located for PPS at the temporo-parietal junction and for BO in the anterior insula. These results in PPS and BO and provide evidence-based insight about the overlap of the two processes in the IPS region and the extensive connectivity between the two associated co-activation networks. They also show significant dissociations, with PPS fronto-parietal areas located more proximal to the central sulcus than BO areas. Such anatomical distinction may also reflect the different functions of the two processes, whereby PPS areas underlie a multisensory-motor interface for body-objects interaction and BO areas being involved in bodily awareness and self-consciousness.

Functional Organization of the Cerebral Cortex in Cued and Implicit Modality-Specific Anticipatory Attention. Analysis of α-Rhythm Coherence in the Sources Space

Studies in healthy right-handed subjects (N = 16, mean age 23 ± 5.7 years) analyzed the functional organization of the cerebral cortex during preparation to solve visual and auditory sensory tasks in two conditions: (1) anticipation of a visual or auditory signal after being told its modality (cued anticipatory attention) and (2) implicit anticipation formed during multiple repetition of a given sequence of visual and auditory stimuli. In both conditions subjects had to perform the same task – to identify the order of the stimuli (visual or auditory) in monomodal pairs. During the prestimulus period, the α frequency range was used to assess the coherence of cortical sources corresponding to previously selected cortical regions (regions of interest). More functional connections between cortical zones in the frontoparietal modulatory system were seen in cued anticipatory attention than during the period preceding appearance of the prompt stimulus, this obtaining in both sensory tasks. There was also a greater number of local connections between sensory-specific and associative (parietal and prefrontal) areas. Implicit anticipation preceding execution of the visual task was accompanied by an increase in connections between the ventral premotor cortex and the caudal (parietal and occipital) areas of the right hemisphere. Execution of the auditory task was preceded by an increase in connections between the auditory sensory cortex, the rostral part of the supplementary motor area, and the ventral premotor area. In contrast to cued attention, implicit anticipation was not accompanied by changes in frontoparietal connections. These results provide evidence of significant differences in the cerebral organization of these two types of anticipatory attention.

The Desire for Amputation or Paralyzation: Evidence for Structural Brain Anomalies in Body Integrity Identity Disorder (BIID).

BackgroundBody Integrity Identity Disorder (BIID) is a condition in which individuals perceive a mismatch between their internal body scheme and physical body shape, resulting in an absolute desire to be either amputated or paralyzed. The condition is hypothesized to be of congenital nature, but evidence for a neuro-anatomical basis is sparse.MethodsWe collected T1-weighted structural magnetic resonance imaging scans on a 3T scanner in eight individuals with BIID and 24 matched healthy controls, and analyzed the data using voxel-based morphometry.ResultsThe results showed reduced grey matter volume in the left dorsal and ventral premotor cortices and larger grey matter volume in the cerebellum (lobule VIIa) in individuals with BIID compared to controls.ConclusionThe premotor cortex and cerebellum are thought to be crucial for the experience of body-ownership and the integration of multisensory information. Our results suggest that BIID is associated with structural brain anomalies and might result from a dysfunction in the integration of multisensory information, leading to the feeling of disunity between the mental and physical body shape.