Visuomotor Areas Research Articles

Similar neural states, but dissimilar decoding patterns for motor control in parietal cortex.

Discrete neural states are associated with reaching movements across the fronto-parietal network. Here, the Hidden Markov Model (HMM) applied to spiking activity of the somato-motor parietal area PE revealed a sequence of states similar to those of the contiguous visuomotor areas PEc and V6A. Using a coupled clustering and decoding approach, we proved that these neural states carried spatiotemporal information regarding behaviour in all three posterior parietal areas. However, comparing decoding accuracy, PE was less informative than V6A and PEc. In addition, V6A outperformed PEc in target inference, indicating functional differences among the parietal areas. To check the consistency of these differences, we used both a supervised and an unsupervised variant of the HMM, and compared its performance with two more common classifiers, Support Vector Machine and Long-Short Term Memory. The differences in decoding between areas were invariant to the algorithm used, still showing the dissimilarities found with HMM, thus indicating that these dissimilarities are intrinsic in the information encoded by parietal neurons. These results highlight that, when decoding from the parietal cortex, for example, in brain machine interface implementations, attention should be paid in selecting the most suitable source of neural signals, given the great heterogeneity of this cortical sector.

Neural mechanisms for executive control of speed-accuracy trade-off

The medial frontal cortex (MFC) plays an important but disputed role in speed-accuracy trade-off (SAT). In samples of neural spiking in the supplementary eye field (SEF) in the MFC simultaneous with the visuomotor frontal eye field and superior colliculus in macaques performing a visual search with instructed SAT, during accuracy emphasis, most SEF neurons discharge less from before stimulus presentation until response generation. Discharge rates adjust immediately and simultaneously across structures upon SAT cue changes. SEF neurons signal choice errors with stronger and earlier activity during accuracy emphasis. Other neurons signal timing errors, covarying with adjusting response time. Spike correlations between neurons in the SEF and visuomotor areas did not appear, disappear, or change sign across SAT conditions or trial outcomes. These results clarify findings with noninvasive measures, complement previous neurophysiological findings, and endorse the role of the MFC as a critic for the actor instantiated in visuomotor structures.

Distinct Neural Components of Visually Guided Grasping during Planning and Execution.

Selecting suitable grasps on three-dimensional objects is a challenging visuomotor computation, which involves combining information about an object (e.g., its shape, size, and mass) with information about the actor's body (e.g., the optimal grasp aperture and hand posture for comfortable manipulation). Here, we used functional magnetic resonance imaging to investigate brain networks associated with these distinct aspects during grasp planning and execution. Human participants of either sex viewed and then executed preselected grasps on L-shaped objects made of wood and/or brass. By leveraging a computational approach that accurately predicts human grasp locations, we selected grasp points that disentangled the role of multiple grasp-relevant factors, that is, grasp axis, grasp size, and object mass. Representational Similarity Analysis revealed that grasp axis was encoded along dorsal-stream regions during grasp planning. Grasp size was first encoded in ventral stream areas during grasp planning then in premotor regions during grasp execution. Object mass was encoded in ventral stream and (pre)motor regions only during grasp execution. Premotor regions further encoded visual predictions of grasp comfort, whereas the ventral stream encoded grasp comfort during execution, suggesting its involvement in haptic evaluation. These shifts in neural representations thus capture the sensorimotor transformations that allow humans to grasp objects.SIGNIFICANCE STATEMENT Grasping requires integrating object properties with constraints on hand and arm postures. Using a computational approach that accurately predicts human grasp locations by combining such constraints, we selected grasps on objects that disentangled the relative contributions of object mass, grasp size, and grasp axis during grasp planning and execution in a neuroimaging study. Our findings reveal a greater role of dorsal-stream visuomotor areas during grasp planning, and, surprisingly, increasing ventral stream engagement during execution. We propose that during planning, visuomotor representations initially encode grasp axis and size. Perceptual representations of object material properties become more relevant instead as the hand approaches the object and motor programs are refined with estimates of the grip forces required to successfully lift the object.

The reduction of saccadic inhibition by distractor repetition.

When visual distractors are presented far from the goal of an impending voluntary saccadic eye movement, saccade execution will occur less frequently about 90 ms after distractor appearance, a phenomenon known as saccadic inhibition. However, it is also known that neural responses in visual and visuomotor areas of the brain will be attenuated if a visual stimulus appears several times in the same location in rapid succession. In particular, such visual adaptation can affect neurons in the mammalian superior colliculus (SC). As the SC is known to be intimately involved in the production of saccadic eye movements, and thus perhaps in saccadic inhibition, we used a memory-guided saccade task to test whether saccadic inhibition in humans would diminish if a distractor appeared several times in quick succession. We found that distractor repetition reduced saccadic inhibition considerably when distractors appeared opposite in space to the goal of the impending saccade. In addition, when three distractors appeared in quick succession but in different, spatially disparate locations, with only the final distractor appearing opposite the saccade goal, saccadic inhibition was reduced by an intermediate level, suggesting that its reduction due to distractor inhibition spatially generalizes. This suggests that distractor suppression can help reduce the impact that suddenly appearing visual stimuli have on purposive eye movement behavior.NEW & NOTEWORTHY This work combines approaches studying saccadic inhibition and visual adaptation to demonstrate that saccadic inhibition is largely eliminated with stimulus repetition. This is likely to be the largest demonstrated effect of visual stimulus context on saccadic inhibition. It also provides evidence for the existence of a mechanism that acts to suppress the effect of frequently appearing visual stimuli on purposive eye movement behavior in dynamic visual environments.

Left or right ear? A neuroimaging study using combined taVNS/fMRI to understand the interaction between ear stimulation target and lesion location in chronic stroke

BackgroundImplanted vagus nerve stimulation (VNS) and transcutaneous auricular VNS (taVNS) have been primarily administered clinically to the unilateral-left vagus nerve. This left-only convention has proved clinically beneficial in brain disorders. However, in stroke survivors, the presence of a lesion in the brain may complicate VNS-mediated signaling, and it is important to understand the laterality effects of VNS in stroke survivors to optimize the intervention. ObjectiveTo understand whether taVNS delivered to different ear targets relative to the lesion (ipsilesional vs contralesional vs bilateral vs sham) impacts blood oxygenation level dependent (BOLD) signal propagation in stroke survivors. MethodsWe enrolled 20 adults with a prior history of stroke. Each participant underwent a single visit, during which taVNS was delivered concurrently during functional magnetic resonance imaging (fMRI) acquisition. Each participant received three discrete active stimulation conditions (ipsilesional, contralesional, bilateral) and one sham condition in a randomized order. Stimulation-related BOLD signal changes in the active conditions were compared to sham conditions to understand the interaction taVNS and laterality effects. ResultsAll active taVNS conditions deactivated the contralesional default mode network related regions compared to sham, however only ipsilesional taVNS enhanced the activations in the ipsilesional visuomotor and secondary visual cortex. Furthermore, we reveal an interaction in task activations between taVNS and cortical visuomotor areas, where ipsilesional taVNS significantly increased ipsilesional visuomotor activity and decreased contralesional visuomotor activity compared to sham. ConclusionLaterality of taVNS relative to the lesion is a critical factor in optimizing taVNS in a stroke population, with ipsilesional stimulation providing largest direct brain activation and should be explored further when designing taVNS studies in neurorehabilitation.

Modulations of Cortical Power and Connectivity in Alpha and Beta Bands during the Preparation of Reaching Movements

Planning goal-directed movements towards different targets is at the basis of common daily activities (e.g., reaching), involving visual, visuomotor, and sensorimotor brain areas. Alpha (8-13 Hz) and beta (13-30 Hz) oscillations are modulated during movement preparation and are implicated in correct motor functioning. However, how brain regions activate and interact during reaching tasks and how brain rhythms are functionally involved in these interactions is still limitedly explored. Here, alpha and beta brain activity and connectivity during reaching preparation are investigated at EEG-source level, considering a network of task-related cortical areas. Sixty-channel EEG was recorded from 20 healthy participants during a delayed center-out reaching task and projected to the cortex to extract the activity of 8 cortical regions per hemisphere (2 occipital, 2 parietal, 3 peri-central, 1 frontal). Then, we analyzed event-related spectral perturbations and directed connectivity, computed via spectral Granger causality and summarized using graph theory centrality indices (in degree, out degree). Results suggest that alpha and beta oscillations are functionally involved in the preparation of reaching in different ways, with the former mediating the inhibition of the ipsilateral sensorimotor areas and disinhibition of visual areas, and the latter coordinating disinhibition of the contralateral sensorimotor and visuomotor areas.

Identification of cerebral cortices processing acceleration, velocity, and position during directional reaching movement with deep neural network and explainable AI

Cerebral cortical representation of motor kinematics is crucial for understanding human motor behavior, potentially extending to efficient control of the brain-computer interface. Numerous single-neuron studies have found the existence of a relationship between neuronal activity and motor kinematics such as acceleration, velocity, and position. Despite differences between kinematic characteristics, it is hard to distinguish neural representations of these kinematic characteristics with macroscopic functional images such as electroencephalography (EEG) and magnetoencephalography (MEG). The reason might be because cortical signals are not sensitive enough to segregate kinematic characteristics due to their limited spatial and temporal resolution. Considering different roles of each cortical area in producing movement, there might be a specific cortical representation depending on characteristics of acceleration, velocity, and position. Recently, neural network modeling has been actively pursued in the field of decoding. We hypothesized that neural features of each kinematic parameter could be identified with a high-performing model for decoding with an explainable AI method. Time-series deep neural network (DNN) models were used to measure the relationship between cortical activity and motor kinematics during reaching movement. With DNN models, kinematic parameters of reaching movement in a 3D space were decoded based on cortical source activity obtained from MEG data. An explainable artificial intelligence (AI) method was then adopted to extract the map of cortical areas, which strongly contributed to decoding each kinematics from DNN models. We found that there existed differed as well as shared cortical areas for decoding each kinematic attribute. Shared areas included bilateral supramarginal gyri and superior parietal lobules known to be related to the goal of movement and sensory integration. On the other hand, dominant areas for each kinematic parameter (the contralateral motor cortex for acceleration, the contralateral parieto-frontal network for velocity, and bilateral visuomotor areas for position) were mutually exclusive. Regarding the visuomotor reaching movement, the motor cortex was found to control the muscle force, the parieto-frontal network encoded reaching movement from sensory information, and visuomotor areas computed limb and gaze coordination in the action space. To the best of our knowledge, this is the first study to discriminate kinematic cortical areas using DNN models and explainable AI.

Egomotion-related visual areas respond to goal-directed movements.

Integration of proprioceptive signals from the various effectors with visual feedback of self-motion from the retina is necessary for whole-body movement and locomotion. Here, we tested whether the human visual motion areas involved in processing optic flow signals simulating self-motion are also activated by goal-directed movements (as saccades or pointing) performed with different effectors (eye, hand, and foot), suggesting a role in visually guiding movements through the external environment. To achieve this aim, we used a combined approach of task-evoked activity and effective connectivity (PsychoPhysiological Interaction, PPI) by fMRI. We localized a set of six egomotion-responsive visual areas through the flow field stimulus and distinguished them into visual (pIPS/V3A, V6+ , IPSmot/VIP) and visuomotor (pCi, CSv, PIC) areas according to recent literature. We tested their response to a visuomotor task implying spatially directed delayed eye, hand, and foot movements. We observed a posterior-to-anterior gradient of preference for eye-to-foot movements, with posterior (visual) regions showing a preference for saccades, and anterior (visuomotor) regions showing a preference for foot pointing. No region showed a clear preference for hand pointing. Effective connectivity analysis showed that visual areas were more connected to each other with respect to the visuomotor areas, particularly during saccades. We suggest that visual and visuomotor egomotion regions can play different roles within a network that integrates sensory-motor signals with the aim of guiding movements in the external environment.

Visuomotor processing is altered after peripheral nerve damage in neuralgic amyotrophy.

Neuralgic amyotrophy is a common peripheral nerve disorder caused by autoimmune inflammation of the brachial plexus, clinically characterized by acute pain and weakness of the shoulder muscles, followed by motor impairment. Despite recovery of the peripheral nerves, patients often have residual motor dysfunction of the upper extremity, leading to persistent pain related to altered biomechanics of the shoulder region. Building on clinical signs that suggest a role for cerebral mechanisms in these residual complaints, here we show and characterize cerebral alterations following neuralgic amyotrophy. Neuralgic amyotrophy patients often develop alternative motor strategies, which suggests that (mal)adaptations may occur in somatomotor and/or visuomotor brain areas. Here, we tested where changes in cerebral sensorimotor representations occur in neuralgic amyotrophy, while controlling for altered motor execution due to peripheral neuropathy. We additionally explore the relation between potential cerebral alterations in neuralgic amyotrophy and clinical symptoms. During functional MRI scanning, 39 neuralgic amyotrophy patients with persistent, lateralized symptoms in the right upper extremity and 23 matched healthy participants solved a hand laterality judgement task that can activate sensorimotor representations of the upper extremity, across somatomotor and visuomotor brain areas. Behavioural and cerebral responses confirmed the involvement of embodied, sensorimotor processes across groups. Compared with healthy participants, neuralgic amyotrophy patients were slower in hand laterality judgement and had decreased cerebral activity specific to their affected limb in two higher-order visual brain regions: the right extrastriate cortex and the parieto-occipital sulcus. Exploratory analyses revealed that across patients, extrastriate activity specific to the affected limb decreased as persistent pain increased, and affected limb-related parieto-occipital activity decreased as imagery performance of the affected limb became slower. These findings suggest that maladaptive cerebral plasticity in visuomotor areas involved in sensorimotor integration plays a role in residual motor dysfunction and subsequent persistent pain in neuralgic amyotrophy. Rehabilitation interventions that apply visuomotor strategies to improve sensorimotor integration may help to treat neuralgic amyotrophy patients.

Changes in brain morphometry after motor rehabilitation in chronic stroke

Purpose Recent studies have revealed structural changes after motor rehabilitation, but its morphological changes related to upper limb motor behaviours have not been studied exhaustively. Therefore, we aimed to map the grey matter (GM) changes associated with motor rehabilitation after stroke using voxel-based morphometry (VBM), deformation-based morphometry (DBM), and surface-based morphometry (SBM). Methods Forty-one patients with chronic stroke received twelve sessions of low-frequency repetitive transcranial magnetic stimulation plus intensive occupational therapy. MRI data were obtained before and after the intervention. Fugl-Meyer Assessment and Wolf Motor Function Test-Functional Ability Scale were assessed at the two-time points. We performed VBM, DBM, and SBM analyses using T1-weighted images. A correlation analysis was performed between cortical thickness in motor areas and clinical outcomes. Results Clinical outcomes significantly improved after the intervention. VBM showed significant GM volume changes in ipsilesional and contralesional primary motor regions. DBM results demonstrated GM changes contralesionally and ipsilesionally after the intervention. SBM results showed significant cortical thickness changes in posterior visuomotor coordination, precentral, postcentral gyri of the ipsilesional hemisphere and contralesional visuomotor area after the intervention. A combination of threshold p < .05, False Discovery Rate and p < .001 (uncorrected) were considered significant. In addition, cortical thickness changes of the ipsilesional motor areas were significantly correlated with the clinical outcome changes. Conclusions We found GM structural changes in areas involved in motor, visuomotor and somatosensory functions after the intervention. Furthermore, our findings suggest that structural plasticity changes in chronic stroke could occur in the ipsilesional and contralesional hemispheres after motor rehabilitation.

Working memory gates visual input to primate prefrontal neurons.

Visually guided behavior relies on the integration of sensory input and information held in working memory (WM). Yet it remains unclear how this is accomplished at the level of neural circuits. We studied the direct visual cortical inputs to neurons within a visuomotor area of prefrontal cortex in behaving monkeys. We show that the efficacy of visual input to prefrontal cortex is gated by information held in WM. Surprisingly, visual input to prefrontal neurons was found to target those with both visual and motor properties, rather than preferentially targeting other visual neurons. Furthermore, activity evoked from visual cortex was larger in magnitude, more synchronous, and more rapid, when monkeys remembered locations that matched the location of visual input. These results indicate that WM directly influences the circuitry that transforms visual input into visually guided behavior.

Grip Constancy but Not Perceptual Size Constancy Survives Lesions of Early Visual Cortex

Object constancies are central constructs in theories of visual phenomenology. A powerful example is "size constancy," in which the perceived size of an object remains stable despite changes in viewing distance [1-4]. Evidence from neuropsychology [5], neuroimaging [6-11], transcranial magnetic stimulation [12, 13], single-unit and lesion studies in monkey [14-20], and computational modeling [21] suggests that re-entrant processes involving reciprocal interactions between primary visual cortex (V1) and extrastriate visual areas [22-26] play an essential role in mediating size constancy. It is seldom appreciated, however, that object constancies must also operate for the visual guidance of goal-directed action. For example, when reaching out to pick up an object, the hand's in-flight aperture scales with size of the goal object [27-30] and is refractory to the decrease in retinal-image size with increased viewing distance [31-41] (Figure1), a phenomenon we call "grip constancy." Does grip constancy, like perceptual constancy, depend on V1 or can it be mediated by pathways that bypass it altogether? We tested these possibilities in an individual, M.C., who has bilateral lesions encompassing V1 and much of the ventral visual stream. We show that her perceptual estimates of object size co-vary with retinal-image size rather than real-world size as viewing distance varies. In contrast, M.C. shows near-normal scaling of in-flight grasp aperture to object size despite changes in viewing distance. Thus, although early visual cortex is necessary for perceptual object constancy, it is unnecessary for grip constancy, which is mediated instead by separate visual inputs to dorsal-stream visuomotor areas [42-48].

Frontal eye field neurons selectively signal the reward value of prior actions.

The consequences of individual actions are typically unknown until well after they are executed. This fact necessitates a mechanism that bridges delays between specific actions and reward outcomes. We looked for the presence of such a mechanism in the post-movement activity of neurons in the frontal eye field (FEF), a visuomotor area in prefrontal cortex. Monkeys performed an oculomotor gamble task in which they made eye movements to different locations associated with dynamically varying reward outcomes. Behavioral data showed that monkeys tracked reward history and made choices according to their own risk preferences. Consistent with previous studies, we observed that the activity of FEF neurons is correlated with the expected reward value of different eye movements before a target appears. Moreover, we observed that the activity of FEF neurons continued to signal the direction of eye movements, the expected reward value, and their interaction well after the movements were completed and when targets were no longer within the neuronal response field. In addition, this post-movement information was also observed in local field potentials, particularly in low-frequency bands. These results show that neural signals of prior actions and expected reward value persist across delays between those actions and their experienced outcomes. These memory traces may serve a role in reward-based learning in which subjects need to learn actions predicting delayed reward.

Cortical thickness in visuo-motor areas is related to motor outcomes after STN DBS for Parkinson's disease

IntroductionDeep brain stimulation (DBS) is a widely accepted therapy for Parkinson's disease. While outcome predictors such as levodopa-response are well established, there remains a need for objective and unbiased predictors in clinical practice. We performed an exploratory study to examine whether cortical thickness, derived from preoperative MRI, correlates with postoperative outcome. MethodsUsing freesurfer, we retrospectively measured cortical thickness on the preoperative MRI of 38 patients who underwent bilateral STN-DBS for PD during a 4-year period. The Unified Parkinson Disease Rating motor (UPDRS III) and experiences of daily living subscales (UPDRS II) were collected at baseline and six months after surgery. As an initial analysis, a series of partial correlations was conducted to evaluate the association between postoperative outcome scores and average cortical thickness from predefined regions of interest, adjusting for candidate confounders, without correcting for multiple comparisons. A confirmatory vertex-wise analysis was performed using a cluster-wise correction for multiple comparisons. ResultsBased on the ROI analysis, the strongest correlation with motor outcome was found to be with the left lateral-occipital cortex. Patients with greater cortical thickness in this area presented with greater improvements in motor scores. This relationship was also supported by the vertex-wise analysis. Greater cortical thickness in frontal and temporal regions may be correlated with greater post-operative improvements in UPDRS II, but this was not confirmed in the vertex-wise analysis. ConclusionsOur data indicate that greater cortical thickness in visuo-motor areas is correlated with motor outcomes after DBS for PD. Further prospective investigations are needed to confirm our findings and better-investigate potential image biomarkers.

Cortical network fingerprints predict deep brain stimulation outcome in dystonia

Deep brain stimulation (DBS) is an effective evidence-based therapy for dystonia. However, no unequivocal predictors of therapy responses exist. We investigated whether patients optimally responding to DBS present distinct brain network organization and structural patterns. From a German multicenter cohort of 82 dystonia patients with segmental and generalized dystonia who received DBS implantation in the globus pallidus internus, we classified patients based on the clinical response 3 years after DBS. Patients were assigned to the superior-outcome group or moderate-outcome group, depending on whether they had above or below 70% motor improvement, respectively. Fifty-one patients met MRI-quality and treatment response requirements (mean age, 51.3 ± 13.2 years; 25 female) and were included in further analysis. From preoperative MRI we assessed cortical thickness and structural covariance, which were then fed into network analysis using graph theory. We designed a support vector machine to classify subjects for the clinical response based on individual gray-matter fingerprints. The moderate-outcome group showed cortical atrophy mainly in the sensorimotor and visuomotor areas and disturbed network topology in these regions. The structural integrity of the cortical mantle explained about 45% of the DBS stimulation amplitude for optimal response in individual subjects. Classification analyses achieved up to 88% of accuracy using individual gray-matter atrophy patterns to predict DBS outcomes. The analysis of cortical integrity, informed by group-level network properties, could be developed into independent predictors to identify dystonia patients who benefit from DBS. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Egomotion-related visual areas respond to active leg movements.

Monkey neurophysiology and human neuroimaging studies have demonstrated that passive viewing of optic flow stimuli activates a cortical network of temporal, parietal, insular, and cingulate visual motion regions. Here, we tested whether the human visual motion areas involved in processing optic flow signals simulating self-motion are also activated by active lower limb movements, and hence are likely involved in guiding human locomotion. To this aim, we used a combined approach of task-evoked activity and resting-state functional connectivity by fMRI. We localized a set of six egomotion-responsive visual areas (V6+, V3A, intraparietal motion/ventral intraparietal [IPSmot/VIP], cingulate sulcus visual area [CSv], posterior cingulate sulcus area [pCi], posterior insular cortex [PIC]) by using optic flow. We tested their response to a motor task implying long-range active leg movements. Results revealed that, among these visually defined areas, CSv, pCi, and PIC responded to leg movements (visuomotor areas), while V6+, V3A, and IPSmot/VIP did not (visual areas). Functional connectivity analysis showed that visuomotor areas are connected to the cingulate motor areas, the supplementary motor area, and notably to the medial portion of the somatosensory cortex, which represents legs and feet. We suggest that CSv, pCi, and PIC perform the visual analysis of egomotion-like signals to provide sensory information to the motor system with the aim of guiding locomotion.

Anterior Temporal Lobectomy Impairs Neural Classification of Body Emotions in Right Superior Temporal Sulcus and Reduces Emotional Enhancement in Distributed Brain Areas without Affecting Behavioral Classification.

Humans with amygdalar lesions show proportional reductions of the emotional response to facial expressions in the fusiform face area as well as deficits in emotion recognition from facial expressions. While processing of bodily expressions shares many similarities with facial expressions, there is no substantial evidence that lesions of the amygdala result in similar behavioral and neural sequelae. We combined behavioral assessment with functional neuroimaging in a group of male and female humans with unilateral anterior temporal lobe (ATL) resections, including the amygdala (right: n = 10; left: n = 10) and 12 matched controls. The objective was to assess whether the amygdala is crucial for the recognition of body expressions and for modulatory effects on distant areas during perception of body expressions. The behavioral results revealed normal performance in both patient groups on emotion categorization of body expressions. The neuroimaging results showed that ATL patients displayed no enhanced activations in right fusiform body area and left extrastriate body area and that left ATL patients additionally displayed no enhanced activations in right posterior superior temporal sulcus and right extrastriate body area, respectively. Multivoxel pattern analysis revealed altered categorization capacity between emotional and neutral stimuli in right posterior superior temporal sulcus in right ATL patients. In addition, we also found emotional enhancement in frontal, parietal, occipital, and cingulate regions in controls. Together, our data show that the amygdala and ATLs are not necessary for recognition of dynamic body expressions, but suggest that amygdala lesions affect body emotion processing in distant brain areas.SIGNIFICANCE STATEMENT For humans, information from emotional expressions of others is crucial to support social interactions. The majority of emotion studies has focused on facial expressions; however, in daily life, we also use information from body postures and body movement. Visual processing of body expressions relies on a brain network, including body-specific visual areas and visuomotor areas. Even though the importance of the amygdala and its modulatory effects on distant brain regions have been documented, it remains unclear whether the amygdala plays a crucial role in emotional body processing. By combining behavioral and neuroimaging data in patients with amygdalar lesions, we provide further evidence for its modulatory effect on distant areas during the perception of body expressions.

Visuomotor Correlates of Conflict Expectation in the Context of Motor Decisions.

Many behaviors require choosing between conflicting options competing against each other in visuomotor areas. Such choices can benefit from top-down control processes engaging frontal areas in advance of conflict when it is anticipated. Yet, very little is known about how this proactive control system shapes the visuomotor competition. Here, we used electroencephalography in human subjects (male and female) to identify the visual and motor correlates of conflict expectation in a version of the Eriksen Flanker task that required left or right responses according to the direction of a central target arrow surrounded by congruent or incongruent (conflicting) flankers. Visual conflict was either highly expected (it occurred in 80% of trials; mostly incongruent blocks) or very unlikely (20% of trials; mostly congruent blocks). We evaluated selective attention in the visual cortex by recording target- and flanker-related steady-state visual-evoked potentials (SSVEPs) and probed action selection by measuring response-locked potentials (RLPs) in the motor cortex. Conflict expectation enhanced accuracy in incongruent trials, but this improvement occurred at the cost of speed in congruent trials. Intriguingly, this behavioral adjustment occurred while visuomotor activity was less finely tuned: target-related SSVEPs were smaller while flanker-related SSVEPs were higher in mostly incongruent blocks than in mostly congruent blocks, and incongruent trials were associated with larger RLPs in the ipsilateral (nonselected) motor cortex. Hence, our data suggest that conflict expectation recruits control processes that augment the tolerance for inappropriate visuomotor activations (rather than processes that downregulate their amplitude), allowing for overflow activity to occur without having it turn into the selection of an incorrect response.SIGNIFICANCE STATEMENT Motor choices made in front of discordant visual information are more accurate when conflict can be anticipated, probably due to the engagement of top-down control from frontal areas. How this control system modulates activity within visual and motor areas is unknown. Here, we show that, when control processes are recruited in anticipation of conflict, as evidenced by higher midfrontal theta activity, visuomotor activity is less finely tuned: visual processing of the goal-relevant location was reduced and the motor cortex displayed more inappropriate activations, compared with when conflict was unlikely. We argue that conflict expectation is associated with an expansion of the distance-to-selection threshold, improving accuracy while the need for online control of visuomotor activity is reduced.

Real-time visuomotor behavior and electrophysiology recording setup for use with humans and monkeys.

Large-scale network dynamics in multiple visuomotor areas is of great interest in the study of eye-hand coordination in both human and monkey. To explore this, it is essential to develop a setup that allows for precise tracking of eye and hand movements. It is desirable that it is able to generate mechanical or visual perturbations of hand trajectories so that eye-hand coordination can be studied in a variety of conditions. There are simple solutions that satisfy these requirements for hand movements performed in the horizontal plane while visual stimuli and hand feedback are presented in the vertical plane. However, this spatial dissociation requires cognitive rules for eye-hand coordination different from eye-hand movements performed in the same space, as is the case in most natural conditions. Here we present an innovative solution for the precise tracking of eye and hand movements in a single reference frame. Importantly, our solution allows behavioral explorations under normal and perturbed conditions in both humans and monkeys. It is based on the integration of two noninvasive commercially available systems to achieve online control and synchronous recording of eye (EyeLink) and hand (KINARM) positions during interactive visuomotor tasks. We also present an eye calibration method compatible with different eye trackers that compensates for nonlinearities caused by the system's geometry. Our setup monitors the two effectors in real time with high spatial and temporal resolution and simultaneously outputs behavioral and neuronal data to an external data acquisition system using a common data format.NEW & NOTEWORTHY We developed a new setup for studying eye-hand coordination in humans and monkeys that monitors the two effectors in real time in a common reference frame. Our eye calibration method allows us to track gaze positions relative to visual stimuli presented in the horizontal workspace of the hand movements. This method compensates for nonlinearities caused by the system’s geometry and transforms kinematics signals from the eye tracker into the same coordinate system as hand and targets.

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.