Object vision to hand action in macaque parietal, premotor, and motor cortices

Phase-Dependent Visual and Sensorimotor Integration of Features for Grasp Computations before and after Effector Specification

The simple act of viewing and grasping an object involves complex sensorimotor control mechanisms that have been shown to vary as a function of multiple object and other task features such as object size, shape, weight, and wrist orientation. However, these features have been mostly studied in isolation. In contrast, given the nonlinearity of motor control, its computations require multiple features to be incorporated concurrently. Therefore, the present study tested the hypothesis that grasp computations integrate multiple task features superadditively in particular when these features are relevant for the same action phase. We asked male and female human participants to reach-to-grasp objects of different shapes and sizes with different wrist orientations. Also, we delayed the movement onset using auditory signals to specify which effector to use. Using electroencephalography and representative dissimilarity analysis to map the time course of cortical activity, we found that grasp computations formed superadditive integrated representations of grasp features during different planning phases of grasping. Shape-by-size representations and size-by-orientation representations occurred before and after effector specification, respectively, and could not be explained by single-feature models. These observations are consistent with the brain performing different preparatory, phase-specific computations; visual object analysis to identify grasp points at abstract visual levels; and downstream sensorimotor preparatory computations for reach-to-grasp trajectories. Our results suggest the brain adheres to the needs of nonlinear motor control for integration. Furthermore, they show that examining the superadditive influence of integrated representations can serve as a novel lens to map the computations underlying sensorimotor control.

Visual sensitivity at the service of action control in posterior parietal cortex

The posterior parietal cortex (PPC) serves as a crucial hub for the integration of sensory with motor cues related to voluntary actions. Visual input is used in different ways along the dorsomedial and the dorsolateral visual pathways. Here we focus on the dorsomedial pathway and recognize a visual representation at the service of action control. Employing different experimental paradigms applied to behaving monkeys while single neural activity is recorded from the medial PPC (area V6A), we show how plastic visual representation can be, matching the different contexts in which the same object is proposed. We also present data on the exchange between vision and arm actions and highlight how this rich interplay can be used to weight different sensory inputs in order to monitor and correct arm actions online. Indeed, neural activity during reaching or reach-to-grasp actions can be excited or inhibited by visual information, suggesting that the visual perception of action, rather than object recognition, is the most effective factor for area V6A. Also, three-dimensional object shape is encoded dynamically by the neural population, according to the behavioral context of the monkey. Along this line, mirror neuron discharges in V6A indicate the plasticity of visual representation of the graspable objects, that changes according to the context and peaks when the object is the target of one's own action. In other words, object encoding in V6A is a visual encoding for action.

Mixed selectivity in monkey anterior intraparietal area during visual and motor processes

Classical studies suggest that the anterior intraparietal area (AIP) contributes to the encoding of specific information such as objects and actions of self and others, through a variety of neuronal classes, such as canonical, motor and mirror neurons. However, these studies typically focused on a single variable, leaving it unclear whether distinct sets of AIP neurons encode a single or multiple sources of information and how multimodal coding emerges. Here, we chronically recorded monkey AIP neurons in a variety of tasks and conditions classically employed in separate experiments. Most cells exhibited mixed selectivity for observed objects, executed actions, and observed actions, enhanced when this information came from the monkey's peripersonal working space. In contrast with the classical view, our findings indicate that multimodal coding emerges in AIP from partially-mixed selectivity of individual neurons for a variety of information relevant for planning actions directed to both physical objects and other subjects.

How to construct liquid-crystal spectacles to control vision of real-world objects and environments

A major challenge in studying naturalistic vision lies in controlling stimulus and scene viewing time. This is especially the case for studies using real-world objects as stimuli (rather than computerized images) because real objects cannot be "onset" and "offset" in the same way that images can be. Since the late 1980s, one solution to this problem has been to have the observer wear electro-optic spectacles with computer-controlled liquid-crystal lenses that switch between transparent ("open") and translucent ("closed") states. Unfortunately, the commercially available glasses (PLATO Visual Occlusion Spectacles) command a high price tag, the hardware is fragile, and the glasses cannot be customized. This led us to explore how to manufacture liquid-crystal occlusion glasses in our own laboratory. Here, we share the products of our work by providing step-by-step instructions for researchers to design, build, operate, and test liquid-crystal glasses for use in experimental contexts. The glasses can be assembled with minimal technical knowledge using readily available components, and they can be customized for different populations and applications. The glasses are robust, and they can be produced at a fraction of the cost of commercial alternatives. Tests of reliability and temporal accuracy show that the performance of our laboratory prototype was comparable to that of the PLATO glasses. We discuss the results of our work with respect to implications for promoting rigor and reproducibility, potential use cases, comparisons with other liquid-crystal shutter glasses, and how users can find information regarding future updates and developments.

Cortico-spinal modularity in the parieto-frontal system: A new perspective on action control

Classical neurophysiology suggests that the motor cortex (MI) has a unique role in action control. In contrast, this review presents evidence for multiple parieto-frontal spinal command modules that can bypass MI. Five observations support this modular perspective: (i) the statistics of cortical connectivity demonstrate functionally-related clusters of cortical areas, defining functional modules in the premotor, cingulate, and parietal cortices; (ii) different corticospinal pathways originate from the above areas, each with a distinct range of conduction velocities; (iii) the activation time of each module varies depending on task, and different modules can be activated simultaneously; (iv) a modular architecture with direct motor output is faster and less metabolically expensive than an architecture that relies on MI, given the slow connections between MI and other cortical areas; (v) lesions of the areas composing parieto-frontal modules have different effects from lesions of MI. Here we provide examples of six cortico-spinal modules and functions they subserve: module 1) arm reaching, tool use and object construction; module 2) spatial navigation and locomotion; module 3) grasping and observation of hand and mouth actions; module 4) action initiation, motor sequences, time encoding; module 5) conditional motor association and learning, action plan switching and action inhibition; module 6) planning defensive actions. These modules can serve as a library of tools to be recombined when faced with novel tasks, and MI might serve as a recombinatory hub. In conclusion, the availability of locally-stored information and multiple outflow paths supports the physiological plausibility of the proposed modular perspective.

Non-shared coding of observed and executed actions prevails in macaque ventral premotor mirror neurons

According to the mirror mechanism the discharge of F5 mirror neurons of a monkey observing another individual performing an action is a motor representation of the observed action that may serve to understand or learn from the action. This hypothesis, if strictly interpreted, requires mirror neurons to exhibit an action tuning that is shared between action observation and execution. Due to insufficient data it remains contentious if this requirement is met. To fill in the gaps, we conducted an experiment in which identical objects had to be manipulated in three different ways in order to serve distinct action goals. Using three methods, including cross-task classification, we found that at most time points F5 mirror neurons did not encode observed actions with the same code underlying action execution. However, in about 20% of neurons there were time periods with a shared code. These time periods formed a distinct cluster and cannot be considered a product of chance. Population classification yielded non-shared coding for observed actions in the whole population, which was at times optimal and consistently better than shared coding in differentially selected subpopulations. These results support the hypothesis of a representation of observed actions based on a strictly defined mirror mechanism only for small subsets of neurons and only under the assumption of time-resolved readout. Considering alternative concepts and recent findings, we propose that during observation mirror neurons represent the process of a goal pursuit from the observer's viewpoint. Whether the observer's goal pursuit, in which the other's action goal becomes the observer's action goal, or the other's goal pursuit is represented remains to be clarified. In any case, it may allow the observer to use expectations associated with a goal pursuit to directly intervene in or learn from another's action.

Decoding and geometry of ten finger movements in human posterior parietal cortex and motor cortex

Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb paralysis.Approach. Two tetraplegic participants were each implanted with a 96-channel array in the left posterior parietal cortex (PPC). One of the participants was additionally implanted with a 96-channel array near the hand knob of the left motor cortex (MC). Across tens of sessions, we recorded neural activity while the participants attempted to move individual fingers of the right hand. Offline, we classified attempted finger movements from neural firing rates using linear discriminant analysis with cross-validation. The participants then used the neural classifier online to control individual fingers of a brain-machine interface (BMI). Finally, we characterized the neural representational geometry during individual finger movements of both hands.Main Results. The two participants achieved 86% and 92% online accuracy during BMI control of the contralateral fingers (chance = 17%). Offline, a linear decoder achieved ten-finger decoding accuracies of 70% and 66% using respective PPC recordings and 75% using MC recordings (chance = 10%). In MC and in one PPC array, a factorized code linked corresponding finger movements of the contralateral and ipsilateral hands.Significance. This is the first study to decode both contralateral and ipsilateral finger movements from PPC. Online BMI control of contralateral fingers exceeded that of previous finger BMIs. PPC and MC signals can be used to control individual prosthetic fingers, which may contribute to a hand restoration strategy for people with tetraplegia.

F = ma. Is the macaque brain Newtonian?

Intuitive Physics, the ability to anticipate how the physical events involving mass objects unfold in time and space, is a central component of intelligent systems. Intuitive physics is a promising tool for gaining insight into mechanisms that generalize across species because both humans and non-human primates are subject to the same physical constraints when engaging with the environment. Physical reasoning abilities are widely present within the animal kingdom, but monkeys, with acute 3D vision and a high level of dexterity, appreciate and manipulate the physical world in much the same way humans do.

Information-processing dynamics in neural networks of macaque cerebral cortex reflect cognitive state and behavior

One of the essential functions of biological neural networks is the processing of information. This includes everything from processing sensory information to perceive the environment, up to processing motor information to interact with the environment. Due to methodological limitations, it has been historically unclear how information processing changes during different cognitive or behavioral states and to what extent information is processed within or between the network of neurons in different brain areas. In this study, we leverage recent advances in the calculation of information dynamics to explore neural-level processing within and between the frontoparietal areas AIP, F5, and M1 during a delayed grasping task performed by three macaque monkeys. While information processing was high within all areas during all cognitive and behavioral states of the task, interareal processing varied widely: During visuomotor transformation, AIP and F5 formed a reciprocally connected processing unit, while no processing was present between areas during the memory period. Movement execution was processed globally across all areas with predominance of processing in the feedback direction. Furthermore, the fine-scale network structure reconfigured at the neuron level in response to different grasping conditions, despite no differences in the overall amount of information present. These results suggest that areas dynamically form higher-order processing units according to the cognitive or behavioral demand and that the information-processing network is hierarchically organized at the neuron level, with the coarse network structure determining the behavioral state and finer changes reflecting different conditions.

Complementary contribution of the medial and lateral human parietal cortex to grasping: a repetitive TMS study

The dexterous control of our grasping actions relies on the cooperative activation of many brain areas. In the parietal lobe, 2 grasp-related areas collaborate to orchestrate an accurate grasping action: dorsolateral area AIP and dorsomedial area V6A. Single-cell recordings in monkeys and fMRI studies in humans have suggested that both these areas specify grip aperture and wrist orientation, but encode these grasping parameters differently, depending on the context. To elucidate the causal role of phAIP and hV6A, we stimulated these areas, while participants were performing grasping actions (unperturbed grasping). rTMS over phAIP impaired the wrist orientation process, whereas stimulation over hV6A impaired grip aperture encoding. In a small percentage of trials, an unexpected reprogramming of grip aperture or wrist orientation was required (perturbed grasping). In these cases, rTMS over hV6A or over phAIP impaired reprogramming of both grip aperture and wrist orientation. These results represent the first direct demonstration of a different encoding of grasping parameters by 2 grasp-related parietal areas.

Modulation of neural co-firing to enhance network transmission and improve motor function after stroke

Stroke is a leading cause of disability. While neurotechnology has shown promise for improving upper limb recovery after stroke, efficacy in clinical trials has been variable. Our central thesis is that to improve clinical translation, we need to develop a common neurophysiological framework for understanding how neurotechnology alters network activity. Our perspective discusses principles for how motor networks, both healthy and those recovering from stroke, subserve reach-to-grasp movements. We focus on neural processing at the resolution of single movements, the timescale at which neurotechnologies are applied, and discuss how this activity might drive long-term plasticity. We propose that future studies should focus on cross-area communication and bridging our understanding of timescales ranging from single trials within a session to across multiple sessions. We hope that this perspective establishes a combined path forward for preclinical and clinical research with the goal of more robust clinical translation of neurotechnology.

Dynamic Causal Modelling of Hierarchical Planning

Hierarchical planning (HP) is a strategy that optimizes the planning by storing the steps towards the goal (lower-level planning) into subgoals (higher-level planning). In the framework of model-based reinforcement learning, HP requires the computation through the transition value between higher-level hierarchies. Previous study identified the dmPFC, PMC and SPL were involved in the computation process of HP respectively. However, it is still unclear about how these regions interaction with each other to support the computation in HP, which could deepen our understanding about the implementation of plan algorithm in hierarchical environment. To address this question, we conducted an fMRI experiment using a virtual subway navigation task. We identified the activity of the dmPFC, premotor cortex (PMC) and superior parietal lobe (SPL) with general linear model (GLM) in HP. Then, Dynamic Causal Modelling (DCM) was performed to quantify the influence of the higher- and lower-planning on the connectivity between the brain areas identified by the GLM. The strongest modulation effect of the higher-level planning was found on the dmPFC→right PMC connection. Furthermore, using Parametric Empirical Bayes (PEB), we found the modulation of higher-level planning on the dmPFC→right PMC and right PMC→SPL connections could explain the individual difference of the response time. We conclude that the dmPFC-related connectivity takes the response to the higher-level planning, while the PMC acts as the bridge between the higher-level planning to behavior outcome.

Prehension kinematics in humans and macaques

Non-human primates, especially rhesus macaques, have been a dominant model to study sensorimotor control of the upper limbs. Indeed, human and macaques have similar hands and homologous neural circuits to mediate manual behavior. However, few studies have systematically and quantitatively compared the manual behaviors of the two species. Such comparison is critical for assessing the validity of using the macaque sensorimotor system as a model of its human counterpart. In this study, we systematically compared the prehensile behaviors of humans and rhesus macaques using an identical experimental setup. We found human and macaque prehension kinematics to be generally similar with a few subtle differences. While the structure of the pre-shaping hand postures is similar in humans and macaques, human postures are more object-specific and human joints are less intercorrelated. Conversely, monkeys demonstrate more stereotypical pre-shaping behaviors that are common across all objects and more variability in their postures across repeated presentations of the same object. Despite these subtle differences in manual behavior between humans and monkeys, our results bolster the use of the macaque model to understand the neural mechanisms of manual dexterity in humans.

Diagnostic Neurophysiologic Biomarkers for Task‐Specific Dystonia

Background

Task-specific dystonia (TSD) is a challenging clinical diagnosis with no objective diagnostic biomarkers.

Objective

The objective of this study was to test 2 neurophysiologic variables using transcranial magnetic stimulation as potential diagnostic biomarkers for TSD.

Methods

We tested (1) cortical silent period (CSP) and (2) dorsal inferior parietal lobule-motor cortex (dIPL-M1) physiologic connectivity in 9 patients with the writer's cramp form of TSD and 12 healthy volunteers on 2 separate sessions.

Results

CSP was significantly prolonged (P < 0.0001) in TSD and could classify TSD with high sensitivity and specificity with areas under the receiver operating characteristic curve (AUCs) = 0.94 and 0.90, respectively, for 2 separate sessions with an intraclass correlation = 0.79. dIPL-M1 interaction was notable for significant motor cortical inhibition in TSD compared with facilitation in healthy subjects (P < 0.0001) and could classify TSD with high sensitivity and specificity with AUCs = 0.96 and 0.86, respectively.

Conclusion

CSP and dIPL-M1 physiologic connectivity can classify TSD with high sensitivity, specificity, reproducibility, and reliability.

The science and engineering behind sensitized brain-controlled bionic hands

Advances in our understanding of brain function, along with the development of neural interfaces that allow for the monitoring and activation of neurons, have paved the way for brain-machine interfaces (BMIs), which harness neural signals to reanimate the limbs via electrical activation of the muscles or to control extracorporeal devices, thereby bypassing the muscles and senses altogether. BMIs consist of reading out motor intent from the neuronal responses monitored in motor regions of the brain and executing intended movements with bionic limbs, reanimated limbs, or exoskeletons. BMIs also allow for the restoration of the sense of touch by electrically activating neurons in somatosensory regions of the brain, thereby evoking vivid tactile sensations and conveying feedback about object interactions. In this review, we discuss the neural mechanisms of motor control and somatosensation in able-bodied individuals and describe approaches to use neuronal responses as control signals for movement restoration and to activate residual sensory pathways to restore touch. Although the focus of the review is on intracortical approaches, we also describe alternative signal sources for control and noninvasive strategies for sensory restoration.

Decoding grasp and speech signals from the cortical grasp circuit in a tetraplegic human

The cortical grasp network encodes planning and execution of grasps and processes spoken and written aspects of language. High-level cortical areas within this network are attractive implant sites for brain-machine interfaces (BMIs). While a tetraplegic patient performed grasp motor imagery and vocalized speech, neural activity was recorded from the supramarginal gyrus (SMG), ventral premotor cortex (PMv), and somatosensory cortex (S1). In SMG and PMv, five imagined grasps were well represented by firing rates of neuronal populations during visual cue presentation. During motor imagery, these grasps were significantly decodable from all brain areas. During speech production, SMG encoded both spoken grasp types and the names of five colors. Whereas PMv neurons significantly modulated their activity during grasping, SMG's neural population broadly encoded features of both motor imagery and speech. Together, these results indicate that brain signals from high-level areas of the human cortex could be used for grasping and speech BMI applications.

From Parametric Representation to Dynamical System: Shifting Views of the Motor Cortex in Motor Control

In contrast to traditional representational perspectives in which the motor cortex is involved in motor control via neuronal preference for kinetics and kinematics, a dynamical system perspective emerging in the last decade views the motor cortex as a dynamical machine that generates motor commands by autonomous temporal evolution. In this review, we first look back at the history of the representational and dynamical perspectives and discuss their explanatory power and controversy from both empirical and computational points of view. Here, we aim to reconcile the above perspectives, and evaluate their theoretical impact, future direction, and potential applications in brain-machine interfaces.

Compartmentalized dynamics within a common multi-area mesoscale manifold represent a repertoire of human hand movements

The human hand is unique in the animal kingdom for unparalleled dexterity, ranging from complex prehension to fine finger individuation. How does the brain represent such a diverse repertoire of movements? We evaluated mesoscale neural dynamics across the human "grasp network," using electrocorticography and dimensionality reduction methods, for a repertoire of hand movements. Strikingly, we found that the grasp network represented both finger and grasping movements alike. Specifically, the manifold characterizing the multi-areal neural covariance structure was preserved during all movements across this distributed network. In contrast, latent neural dynamics within this manifold were surprisingly specific to movement type. Aligning latent activity to kinematics further uncovered distinct submanifolds despite similarities in synergistic coupling of joints between movements. We thus find that despite preserved neural covariance at the distributed network level, mesoscale dynamics are compartmentalized into movement-specific submanifolds; this mesoscale organization may allow flexible switching between a repertoire of hand movements.

Distributed yet compartmentalized neural dynamics of hand actions

In this issue of Neuron,Natraj et al. (2021) demonstrate that finger and hand grasping movements are represented in the human fronto-parietal grasp network in a compartmentalized fashion. The movements are encoded in a distributed network that is preserved across various hand actions. The neural dynamics are specific to particular hand movements, leading to movement-specific submanifolds in the network.

Exploring Cognition with Brain-Machine Interfaces

Traditional brain-machine interfaces decode cortical motor commands to control external devices. These commands are the product of higher-level cognitive processes, occurring across a network of brain areas, that integrate sensory information, plan upcoming motor actions, and monitor ongoing movements. We review cognitive signals recently discovered in the human posterior parietal cortex during neuroprosthetic clinical trials. These signals are consistent with small regions of cortex having a diverse role in cognitive aspects of movement control and body monitoring, including sensorimotor integration, planning, trajectory representation, somatosensation, action semantics, learning, and decision making. These variables are encoded within the same population of cells using structured representations that bind related sensory and motor variables, an architecture termed partially mixed selectivity. Diverse cognitive signals provide complementary information to traditional motor commands to enable more natural and intuitive control of external devices.

Multivariate Analysis of Electrophysiological Signals Reveals the Time Course of Precision Grasps Programs: Evidence for Nonhierarchical Evolution of Grasp Control

Current understanding of the neural processes underlying human grasping suggests that grasp computations involve gradients of higher to lower level representations and, relatedly, visual to motor processes. However, it is unclear whether these processes evolve in a strictly canonical manner from higher to intermediate and to lower levels given that this knowledge importantly relies on functional imaging, which lacks temporal resolution. To examine grasping in fine temporal detail here we used multivariate EEG analysis. We asked participants to grasp objects while controlling the time at which crucial elements of grasp programs were specified. We first specified the orientation with which participants should grasp objects, and only after a delay we instructed participants about which effector to use to grasp, either the right or the left hand. We also asked participants to grasp with both hands because bimanual and left-hand grasping share intermediate-level grasp representations. We observed that grasp programs evolved in a canonical manner from visual representations, which were independent of effectors to motor representations that distinguished between effectors. However, we found that intermediate representations of effectors that partially distinguished between effectors arose after representations that distinguished among all effector types. Our results show that grasp computations do not proceed in a strictly hierarchically canonical fashion, highlighting the importance of the fine temporal resolution of EEG for a comprehensive understanding of human grasp control.SIGNIFICANCE STATEMENT A long-standing assumption of the grasp computations is that grasp representations progress from higher to lower level control in a regular, or canonical, fashion. Here, we combined EEG and multivariate pattern analysis to characterize the temporal dynamics of grasp representations while participants viewed objects and were subsequently cued to execute an unimanual or bimanual grasp. Interrogation of the temporal dynamics revealed that lower level effector representations emerged before intermediate levels of grasp representations, thereby suggesting a partially noncanonical progression from higher to lower and then to intermediate level grasp control.

The neural mechanisms of manual dexterity

The hand endows us with unparalleled precision and versatility in our interactions with objects, from mundane activities such as grasping to extraordinary ones such as virtuoso pianism. The complex anatomy of the human hand combined with expansive and specialized neuronal control circuits allows a wide range of precise manual behaviours. To support these behaviours, an exquisite sensory apparatus, spanning the modalities of touch and proprioception, conveys detailed and timely information about our interactions with objects and about the objects themselves. The study of manual dexterity provides a unique lens into the sensorimotor mechanisms that endow the nervous system with the ability to flexibly generate complex behaviour.

Parietal maps of visual signals for bodily action planning

The posterior parietal cortex (PPC) has long been understood as a high-level integrative station for computing motor commands for the body based on sensory (i.e., mostly tactile and visual) input from the outside world. In the last decade, accumulating evidence has shown that the parietal areas not only extract the pragmatic features of manipulable objects, but also subserve sensorimotor processing of others’ actions. A paradigmatic case is that of the anterior intraparietal area (AIP), which encodes the identity of observed manipulative actions that afford potential motor actions the observer could perform in response to them. On these bases, we propose an AIP manipulative action-based template of the general planning functions of the PPC and review existing evidence supporting the extension of this model to other PPC regions and to a wider set of actions: defensive and locomotor actions. In our model, a hallmark of PPC functioning is the processing of information about the physical and social world to encode potential bodily actions appropriate for the current context. We further extend the model to actions performed with man-made objects (e.g., tools) and artifacts, because they become integral parts of the subject’s body schema and motor repertoire. Finally, we conclude that existing evidence supports a generally conserved neural circuitry that transforms integrated sensory signals into the variety of bodily actions that primates are capable of preparing and performing to interact with their physical and social world.

Two Distinct Systems Represent Contralateral and Ipsilateral Sensorimotor Processes in the Human Premotor Cortex: A Dense TMS Mapping Study

Animal brains contain behaviorally committed representations of the surrounding world, which integrate sensory and motor information. In primates, sensorimotor mechanisms reside in part in the premotor cortex (PM), where sensorimotor neurons are topographically clustered according to functional specialization. Detailed functional cartography of the human PM is still under investigation. We explored the topographic distribution of spatially dependent sensorimotor functions in healthy volunteers performing left or right, hand or foot, responses to visual cues presented in the left or right hemispace, thus combining independently stimulus side, effector side, and effector type. Event-related transcranial magnetic stimulation was applied to single spots of a dense grid of 10 points on the participants' left hemiscalp, covering the whole PM. Results showed: (1) spatially segregated hand and foot representations, (2) focal representations of contralateral cues and movements in the dorsal PM, and (3) distributed representations of ipsilateral cues and movements in the ventral and dorso-medial PM. The present novel causal information indicates that (1) the human PM is somatotopically organized and (2) the left PM contains sensory-motor representations of both hemispaces and of both hemibodies, but the hemispace and hemibody contralateral to the PM are mapped on a distinct, nonoverlapping cortical region compared to the ipsilateral ones.

Organization of Parieto-Prefrontal and Temporo-Prefrontal Networks in the Macaque

The connectivity among architectonically defined areas of the frontal, parietal, and temporal cortex of the macaque has been extensively mapped through tract tracing methods. To investigate the statistical organization underlying this connectivity, and identify its underlying architecture, we performed a hierarchical cluster analysis on 69 cortical areas based on their anatomically defined inputs. We identified 10 frontal, 4 parietal, and 5 temporal hierarchically related sets of areas (clusters), defined by unique sets of inputs and typically composed of anatomically contiguous areas. Across cortex, clusters that share functional properties were linked by dominant information processing circuits in a topographically organized manner that reflects the organization of the main fiber bundles in the cortex. This led to a dorsal-ventral subdivision of the frontal cortex, where dorsal and ventral clusters showed privileged connectivity with parietal and temporal areas, respectively. Ventrally, temporo-frontal circuits encode information to discriminate objects in the environment, their value, emotional properties, and functions such as memory and spatial navigation. Dorsal parieto-frontal circuits encode information for selecting, generating, and monitoring appropriate actions based on visual-spatial and somatosensory information. This organization may reflect evolutionary antecedents, in which the vertebrate pallium, which is the ancestral cortex, was defined by a ventral and lateral olfactory region and a medial hippocampal region.

Visually and Tactually Guided Grasps Lead to Different Neuronal Activity in Non-human Primates

Movements are defining characteristics of all behaviors. Animals walk around, move their eyes to explore the world or touch structures to learn more about them. So far we only have some basic understanding of how the brain generates movements, especially when we want to understand how different areas of the brain interact with each other. In this study we investigated the influence of sensory object information on grasp planning in four different brain areas involved in vision, touch, movement planning, and movement generation in the parietal, somatosensory, premotor and motor cortex. We trained one monkey to grasp objects that he either saw or touched beforehand while continuously recording neural spiking activity with chronically implanted floating multi-electrode arrays. The animal was instructed to sit in the dark and either look at a shortly illuminated object or reach out and explore the object with his hand in the dark before lifting it up. In a first analysis we confirmed that the animal not only memorizes the object in both tasks, but also applies an object-specific grip type, independent of the sensory modality. In the neuronal population, we found a significant difference in the number of tuned units for sensory modalities during grasp planning that persisted into grasp execution. These differences were sufficient to enable a classifier to decode the object and sensory modality in a single trial exclusively from neural population activity. These results give valuable insights in how different brain areas contribute to the preparation of grasp movement and how different sensory streams can lead to distinct neural activity while still resulting in the same action execution.

A Turntable Setup for Testing Visual and Tactile Grasping Movements in Non-human Primates

Grasping movements are some of the most common movements primates do every day. They are important for social interactions as well as picking up objects or food. Usually, these grasping movements are guided by vision but proprioceptive and haptic inputs contribute greatly. Since grasping behaviors are common and easy to motivate, they represent an ideal task for understanding the role of different brain areas during planning and execution of complex voluntary movements in primates. For experimental purposes, a stable and repeatable presentation of the same object as well as the variation of objects is important in order to understand the neural control of movement generation. This is even more the case when investigating the role of different senses for movement planning, where objects need to be presented in specific sensory modalities. We developed a turntable setup for non-human primates (macaque monkeys) to investigate visually and tactually guided grasping movements with an option to easily exchange objects. The setup consists of a turntable that can fit six different objects and can be exchanged easily during the experiment to increase the number of presented objects. The object turntable is connected to a stepper motor through a belt system to automate rotation and hence object presentation. By increasing the distance between the turntable and the stepper motor, metallic components of the stepper motor are kept at a distance to the actual recording setup, which allows using a magnetic-based data glove to track hand kinematics. During task execution, the animal sits in the dark and is instructed to grasp the object in front of it. Options to turn on a light above the object allow for visual presentation of the objects, while the object can also remain in the dark for exclusive tactile exploration. A red LED is projected onto the object by a one-way mirror that serves as a grasp cue instruction for the animal to start grasping the object. By comparing kinematic data from the magnetic-based data glove with simultaneously recorded neural signals, this setup enables the systematic investigation of neural population activity involved in the neural control of hand grasping movements.

Local and system mechanisms for action execution and observation in parietal and premotor cortices

The action observation network (AON) includes a system of brain areas largely shared with action execution in both human and nonhuman primates. Yet temporal and tuning specificities of distinct areas and of physiologically identified neuronal classes in the encoding of self and others’ action remain unknown. We recorded the activity of 355 single units from three crucial nodes of the AON, the anterior intraparietal area (AIP), and premotor areas F5 and F6, while monkeys performed a Go/No-Go grasping task and observed an experimenter performing it. At the system level, during task execution, F6 displays a prevalence of suppressed neurons and signals whether an action has to be performed, whereas AIP and F5 share a prevalence of facilitated neurons and remarkable target selectivity; during task observation, F5 stands out for its unique prevalence of facilitated neurons and its stronger and earlier modulation than AIP and F6. By applying unsupervised clustering of spike waveforms, we found distinct cell classes unevenly distributed across areas, with different firing properties and carrying specific visuomotor signals. Broadly spiking neurons exhibited a balanced amount of facilitated and suppressed activity during action execution and observation, whereas narrower spiking neurons showed more mutually facilitated responses during the execution of one’s own and others’ action, particularly in areas AIP and F5. Our findings elucidate the time course of activity and firing properties of neurons in the AON during one’s own and others’ action, from the system level of anatomically distinct areas to the local level of physiologically distinct cell classes.

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F6 neurons show a prevalence of suppressed activity, encoding whether to act

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Area F5 and AIP share a prevalence of facilitated neurons and target selectivity

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Across-areas, waveform-based clustering distinguished three neuronal classes

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Narrow-spiking neurons exhibit mutual modulation during self and others’ action

Grasping of Real-World Objects Is Not Biased by Ensemble Perception

The visual system is known to extract summary representations of visually similar objects which bias the perception of individual objects toward the ensemble average. Although vision plays a large role in guiding action, less is known about whether ensemble representation is informative for action. Motor behavior is tuned to the veridical dimensions of objects and generally considered resistant to perceptual biases. However, when the relevant grasp dimension is not available or is unconstrained, ensemble perception may be informative to behavior by providing gist information about surrounding objects. In the present study, we examined if summary representations of a surrounding ensemble display influenced grip aperture and orientation when participants reached-to-grasp a central circular target which had an explicit size but importantly no explicit orientation that the visuomotor system could selectively attend to. Maximum grip aperture and grip orientation were not biased by ensemble statistics during grasping, although participants were able to perceive and provide manual estimations of the average size and orientation of the ensemble display. Support vector machine classification of ensemble statistics achieved above-chance classification accuracy when trained on kinematic and electromyography data of the perceptual but not grasping conditions, supporting our univariate findings. These results suggest that even along unconstrained grasping dimensions, visually-guided behaviors toward real-world objects are not biased by ensemble processing.

From Observed Action Identity to Social Affordances

Others' observed actions cause continuously changing retinal images, making it challenging to build neural representations of action identity. The monkey anterior intraparietal area (AIP) and its putative human homologue (phAIP) host neurons selective for observed manipulative actions (OMAs). The neuronal activity of both AIP and phAIP allows a stable readout of OMA identity across visual formats, but human neurons exhibit greater invariance and generalize from observed actions to action verbs. These properties stem from the convergence in AIP of superior temporal signals concerning: (i) observed body movements; and (ii) the changes in the body-object relationship. We propose that evolutionarily preserved mechanisms underlie the specification of observed-actions identity and the selection of motor responses afforded by them, thereby promoting social behavior.

Transient deactivation of dorsal premotor cortex or parietal area 5 impairs feedback control of the limb in macaques

We can generate goal-directed motor corrections with surprising speed, but their neural basis is poorly understood. Here, we show that temporary cooling of dorsal premotor cortex (PMd) impaired both spatial accuracy and the speed of corrective responses, whereas cooling parietal area 5 (A5) impaired only spatial accuracy. Simulations based on optimal feedback control (OFC) models demonstrated that "deactivation" of the control policy (reduction in feedback gain) and state estimation (reduction in Kalman gain) caused impairments similar to that observed for PMd and A5 cooling, respectively. Furthermore, combined deactivation of both cortical regions led to additive impairments of individual deactivations, whereas reducing the amount of cooling to PMd led to impairments in response speed but not spatial accuracy, both also predicted by OFC models. These results provide causal support that frontoparietal circuits beyond primary somatosensory and motor cortices are involved in generating goal-directed motor corrections.

Assessing the effective connectivity of premotor areas during real vs imagined grasping: a DCM-PEB approach

The parieto-frontal circuit underlying grasping, which requires the serial involvement of the anterior intraparietal area (aIPs) and the ventral premotor cortex (PMv), has been recently extended enlightening the role of the dorsal premotor cortex (PMd). The supplementary motor area (SMA) has been also suggested to encode grip force for grasping actions; furthermore, both PMd and SMA are known to play a crucial role in motor imagery. Here, we aimed at assessing the dynamic couplings between left aIPs, PMv, PMd, SMA and primary motor cortex (M1) by comparing executed and imagined right-hand grasping, using Dynamic Causal Modelling (DCM) and Parametrical Empirical Bayes (PEB) analyses. 24 subjects underwent an fMRI exam (3T) during which they were asked to perform or imagine a grasping movement visually cued by photographs of commonly used objects. We tested whether the two conditions a) exert a modulatory effect on both forward and feedback couplings among our areas of interest, and b) differ in terms of strength and sign of these parameters. Results of the real condition confirmed the serial involvement of aIPs, PMv and M1. PMv also exerted a positive influence on PMd and SMA, but received an inhibitory feedback only from PMd. Our results suggest that a general motor program for grasping is planned by the aIPs-PMv circuit; then, PMd and SMA encode high-level features of the movement. During imagery, the connection strength from aIPs to PMv was weaker and the information flow stopped in PMv; thus, a less complex motor program was planned. Moreover, results suggest that SMA and PMd cooperate to prevent motor execution. In conclusion, the comparison between execution and imagery reveals that during grasping premotor areas dynamically interplay in different ways, depending on task demands.

The role of the inferior parietal lobule in writer's cramp

Humans have a distinguishing ability for fine motor control that is subserved by a highly evolved cortico-motor neuronal network. The acquisition of a particular motor skill involves a long series of practice movements, trial and error, adjustment and refinement. At the cortical level, this acquisition begins in the parieto-temporal sensory regions and is subsequently consolidated and stratified in the premotor-motor cortex. Task-specific dystonia can be viewed as a corruption or loss of motor control confined to a single motor skill. Using a multimodal experimental approach combining neuroimaging and non-invasive brain stimulation, we explored interactions between the principal nodes of the fine motor control network in patients with writer's cramp and healthy matched controls. Patients and healthy volunteers underwent clinical assessment, diffusion-weighted MRI for tractography, and functional MRI during a finger tapping task. Activation maps from the task-functional MRI scans were used for target selection and neuro-navigation of the transcranial magnetic stimulation. Single- and double-pulse TMS evaluation included measurement of the input-output recruitment curve, cortical silent period, and amplitude of the motor evoked potentials conditioned by cortico-cortical interactions between premotor ventral (PMv)-motor cortex (M1), anterior inferior parietal lobule (aIPL)-M1, and dorsal inferior parietal lobule (dIPL)-M1 before and after inducing a long term depression-like plastic change to dIPL node with continuous theta-burst transcranial magnetic stimulation in a randomized, sham-controlled design. Baseline dIPL-M1 and aIPL-M1 cortico-cortical interactions were facilitatory and inhibitory, respectively, in healthy volunteers, whereas the interactions were converse and significantly different in writer's cramp. Baseline PMv-M1 interactions were inhibitory and similar between the groups. The dIPL-PMv resting state functional connectivity was increased in patients compared to controls, but no differences in structural connectivity between the nodes were observed. Cortical silent period was significantly prolonged in writer's cramp. Making a long term depression-like plastic change to dIPL node transformed the aIPL-M1 interaction to inhibitory (similar to healthy volunteers) and cancelled the PMv-M1 inhibition only in the writer's cramp group. These findings suggest that the parietal multimodal sensory association region could have an aberrant downstream influence on the fine motor control network in writer's cramp, which could be artificially restored to its normal function.

A goal-driven modular neural network predicts parietofrontal neural dynamics during grasping

One of the primary ways we interact with the world is using our hands. In macaques, the circuit spanning the anterior intraparietal area, the hand area of the ventral premotor cortex, and the primary motor cortex is necessary for transforming visual information into grasping movements. However, no comprehensive model exists that links all steps of processing from vision to action. We hypothesized that a recurrent neural network mimicking the modular structure of the anatomical circuit and trained to use visual features of objects to generate the required muscle dynamics used by primates to grasp objects would give insight into the computations of the grasping circuit. Internal activity of modular networks trained with these constraints strongly resembled neural activity recorded from the grasping circuit during grasping and paralleled the similarities between brain regions. Network activity during the different phases of the task could be explained by linear dynamics for maintaining a distributed movement plan across the network in the absence of visual stimulus and then generating the required muscle kinematics based on these initial conditions in a module-specific way. These modular models also outperformed alternative models at explaining neural data, despite the absence of neural data during training, suggesting that the inputs, outputs, and architectural constraints imposed were sufficient for recapitulating processing in the grasping circuit. Finally, targeted lesioning of modules produced deficits similar to those observed in lesion studies of the grasping circuit, providing a potential model for how brain regions may coordinate during the visually guided grasping of objects.

Visual Functions of Primate Area V4

Area V4-the focus of this review-is a mid-level processing stage along the ventral visual pathway of the macaque monkey. V4 is extensively interconnected with other visual cortical areas along the ventral and dorsal visual streams, with frontal cortical areas, and with several subcortical structures. Thus, it is well poised to play a broad and integrative role in visual perception and recognition-the functional domain of the ventral pathway. Neurophysiological studies in monkeys engaged in passive fixation and behavioral tasks suggest that V4 responses are dictated by tuning in a high-dimensional stimulus space defined by form, texture, color, depth, and other attributes of visual stimuli. This high-dimensional tuning may underlie the development of object-based representations in the visual cortex that are critical for tracking, recognizing, and interacting with objects. Neurophysiological and lesion studies also suggest that V4 responses are important for guiding perceptual decisions and higher-order behavior.

Movement initiation and grasp representation in premotor and primary motor cortex mirror neurons

Pyramidal tract neurons (PTNs) within macaque rostral ventral premotor cortex (F5) and (M1) provide direct input to spinal circuitry and are critical for skilled movement control. Contrary to initial hypotheses, they can also be active during action observation, in the absence of any movement. A population-level understanding of this phenomenon is currently lacking. We recorded from single neurons, including identified PTNs, in (M1) (n = 187), and F5 (n = 115) as two adult male macaques executed, observed, or withheld (NoGo) reach-to-grasp actions. F5 maintained a similar representation of grasping actions during both execution and observation. In contrast, although many individual M1 neurons were active during observation, M1 population activity was distinct from execution, and more closely aligned to NoGo activity, suggesting this activity contributes to withholding of self-movement. M1 and its outputs may dissociate initiation of movement from representation of grasp in order to flexibly guide behaviour.

Stable readout of observed actions from format-dependent activity of monkey's anterior intraparietal neurons

The anterior intraparietal area (AIP) is a crucial hub in the observed manipulative action (OMA) network of primates. While macaques observe manipulative action videos, their AIP neuronal activity robustly encodes first the viewpoint from which the action is observed, then the actor’s body posture, and finally the observed-action identity. Despite the lack of fully invariant OMA-selective single neurons, OMA exemplars could be decoded accurately from the activity of a set of units that maintain stable OMA selectivity despite rescaling their firing rate across formats. We propose that by integrating signals multiplicatively about others’ action and their visual format, the AIP can provide a stable readout of OMA identity at the population level.

Humans accurately identify observed actions despite large dynamic changes in their retinal images and a variety of visual presentation formats. A large network of brain regions in primates participates in the processing of others’ actions, with the anterior intraparietal area (AIP) playing a major role in routing information about observed manipulative actions (OMAs) to the other nodes of the network. This study investigated whether the AIP also contributes to invariant coding of OMAs across different visual formats. We recorded AIP neuronal activity from two macaques while they observed videos portraying seven manipulative actions (drag, drop, grasp, push, roll, rotate, squeeze) in four visual formats. Each format resulted from the combination of two actor’s body postures (standing, sitting) and two viewpoints (lateral, frontal). Out of 297 recorded units, 38% were OMA-selective in at least one format. Robust population code for viewpoint and actor’s body posture emerged shortly after stimulus presentation, followed by OMA selectivity. Although we found no fully invariant OMA-selective neuron, we discovered a population code that allowed us to classify action exemplars irrespective of the visual format. This code depends on a multiplicative mixing of signals about OMA identity and visual format, particularly evidenced by a set of units maintaining a relatively stable OMA selectivity across formats despite considerable rescaling of their firing rate depending on the visual specificities of each format. These findings suggest that the AIP integrates format-dependent information and the visual features of others’ actions, leading to a stable readout of observed manipulative action identity.

Neural Trajectories in the Supplementary Motor Area and Motor Cortex Exhibit Distinct Geometries, Compatible with Different Classes of Computation

The supplementary motor area (SMA) is believed to contribute to higher order aspects of motor control. We considered a key higher order role: tracking progress throughout an action. We propose that doing so requires population activity to display low "trajectory divergence": situations with different future motor outputs should be distinct, even when present motor output is identical. We examined neural activity in SMA and primary motor cortex (M1) as monkeys cycled various distances through a virtual environment. SMA exhibited multiple response features that were absent in M1. At the single-neuron level, these included ramping firing rates and cycle-specific responses. At the population level, they included a helical population-trajectory geometry with shifts in the occupied subspace as movement unfolded. These diverse features all served to reduce trajectory divergence, which was much lower in SMA versus M1. Analogous population-trajectory geometry, also with low divergence, naturally arose in networks trained to internally guide multi-cycle movement.

Hierarchical Action Encoding Within the Human Brain

Humans are able to interact with objects with extreme flexibility. To achieve this ability, the brain does not only control specific muscular patterns, but it also needs to represent the abstract goal of an action, irrespective of its implementation. It is debated, however, how abstract action goals are implemented in the brain. To address this question, we used multivariate pattern analysis of functional magnetic resonance imaging data. Human participants performed grasping actions (precision grip, whole hand grip) with two different wrist orientations (canonical, rotated), using either the left or right hand. This design permitted to investigate a hierarchical organization consisting of three levels of abstraction: 1) “concrete action” encoding; 2) “effector-dependent goal” encoding (invariant to wrist orientation); and 3) “effector-independent goal” encoding (invariant to effector and wrist orientation). We found that motor cortices hosted joint encoding of concrete actions and of effector-dependent goals, while the parietal lobe housed a convergence of all three representations, comprising action goals within and across effectors. The left lateral occipito-temporal cortex showed effector-independent goal encoding, but no convergence across the three levels of representation. Our results support a hierarchical organization of action encoding, shedding light on the neural substrates supporting the extraordinary flexibility of human hand behavior.

Cortical pattern generation during dexterous movement is input-driven

Motor cortex controls skilled arm movement by sending temporal patterns of activity to lower motor centers¹. Local cortical dynamics are thought to shape these patterns throughout movement execution^2–4. External inputs have been implicated in setting the initial state of motor cortex^5,6, but they may also have a pattern-generating role. Here, we dissect the contribution of local dynamics and inputs to cortical pattern generation during a prehension task in mice. Perturbing cortex to an aberrant state prevented movement initiation, but after the perturbation was released, cortex either bypassed the normal initial state and immediately generated the pattern that controls reaching, or it failed to generate this pattern. The difference in these two outcomes was likely due to external inputs. We directly investigated the role of inputs by inactivating thalamus; this perturbed cortical activity and disrupted limb kinematics at any stage of the movement. Activation of thalamocortical axon terminals at different frequencies disrupted cortical activity and arm movement in a graded manner. Simultaneous recordings revealed that both thalamic activity and the current state of cortex predicted changes in cortical activity. Thus, the pattern generator for dexterous arm movement is distributed across multiple, strongly-interacting brain regions.

A versatile robotic platform for the design of natural, three-dimensional reaching and grasping tasks in monkeys

OBJECTIVE

Translational studies on motor control and neurological disorders require detailed monitoring of sensorimotor components of natural limb movements in relevant animal models. However, available experimental tools do not provide a sufficiently rich repertoire of behavioral signals. Here, we developed a robotic platform that enables the monitoring of kinematics, interaction forces, and neurophysiological signals during user-defined upper limb tasks for monkeys.

APPROACH

We configured the platform to position instrumented objects in a three-dimensional workspace and provide an interactive dynamic force-field.

MAIN RESULTS

We show the relevance of our platform for fundamental and translational studies with three example applications. First, we study the kinematics of natural grasp in response to variable interaction forces. We then show simultaneous and independent encoding of kinematic and forces in single unit intra-cortical recordings from sensorimotor cortical areas. Lastly, we demonstrate the relevance of our platform to develop clinically relevant brain computer interfaces in a kinematically unconstrained motor task.

SIGNIFICANCE

Our versatile control structure does not depend on the specific robotic arm used and allows for the design and implementation of a variety of tasks that can support both fundamental and translational studies of motor control.

Multivariate Analysis of Electrophysiological Signals Reveals the Temporal Properties of Visuomotor Computations for Precision Grips

The frontoparietal networks underlying grasping movements have been extensively studied, especially using fMRI. Accordingly, whereas much is known about their cortical locus much less is known about the temporal dynamics of visuomotor transformations. Here, we show that multivariate EEG analysis allows for detailed insights into the time course of visual and visuomotor computations of precision grasps. Male and female human participants first previewed one of several objects and, upon its reappearance, reached to grasp it with the thumb and index finger along one of its two symmetry axes. Object shape classifiers reached transient accuracies of 70% at ∼105 ms, especially based on scalp sites over visual cortex, dropping to lower levels thereafter. Grasp orientation classifiers relied on a system of occipital-to-frontal electrodes. Their accuracy rose concurrently with shape classification but ramped up more gradually, and the slope of the classification curve predicted individual reaction times. Further, cross-temporal generalization revealed that dynamic shape representation involved early and late neural generators that reactivated one another. In contrast, grasp computations involved a chain of generators attaining a sustained state about 100 ms before movement onset. Our results reveal the progression of visual and visuomotor representations over the course of planning and executing grasp movements.SIGNIFICANCE STATEMENT Grasping an object requires the brain to perform visual-to-motor transformations of the object's properties. Although much of the neuroanatomic basis of visuomotor transformations has been uncovered, little is known about its time course. Here, we orthogonally manipulated object visual characteristics and grasp orientation, and used multivariate EEG analysis to reveal that visual and visuomotor computations follow similar time courses but display different properties and dynamics.

Differential neural dynamics underling pragmatic and semantic affordance processing in macaque ventral premotor cortex

Premotor neurons play a fundamental role in transforming physical properties of observed objects, such as size and shape, into motor plans for grasping them, hence contributing to “pragmatic” affordance processing. Premotor neurons can also contribute to “semantic” affordance processing, as they can discharge differently even to pragmatically identical objects depending on their behavioural relevance for the observer (i.e. edible or inedible objects). Here, we compared the response of monkey ventral premotor area F5 neurons tested during pragmatic (PT) or semantic (ST) visuomotor tasks. Object presentation responses in ST showed shorter latency and lower object selectivity than in PT. Furthermore, we found a difference between a transient representation of semantic affordances and a sustained representation of pragmatic affordances at both the single neuron and population level. Indeed, responses in ST returned to baseline within 0.5 s whereas in PT they showed the typical sustained visual-to-motor activity during Go trials. In contrast, during No-go trials, the time course of pragmatic and semantic information processing was similar. These findings suggest that premotor cortex generates different dynamics depending on pragmatic and semantic information provided by the context in which the to-be-grasped object is presented.

Corticocortical Systems Underlying High-Order Motor Control

Cortical networks are characterized by the origin, destination, and reciprocity of their connections, as well as by the diameter, conduction velocity, and synaptic efficacy of their axons. The network formed by parietal and frontal areas lies at the core of cognitive-motor control because the outflow of parietofrontal signaling is conveyed to the subcortical centers and spinal cord through different parallel pathways, whose orchestration determines, not only when and how movements will be generated, but also the nature of forthcoming actions. Despite intensive studies over the last 50 years, the role of corticocortical connections in motor control and the principles whereby selected cortical networks are recruited by different task demands remain elusive. Furthermore, the synaptic integration of different cortical signals, their modulation by transthalamic loops, and the effects of conduction delays remain challenging questions that must be tackled to understand the dynamical aspects of parietofrontal operations. In this article, we evaluate results from nonhuman primate and selected rodent experiments to offer a viewpoint on how corticocortical systems contribute to learning and producing skilled actions. Addressing this subject is not only of scientific interest but also essential for interpreting the devastating consequences for motor control of lesions at different nodes of this integrated circuit. In humans, the study of corticocortical motor networks is currently based on MRI-related methods, such as resting-state connectivity and diffusion tract-tracing, which both need to be contrasted with histological studies in nonhuman primates.

Grasping with a new hand: Improved performance and normalized grasp-selective brain responses despite persistent functional changes in primary motor cortex and low-level sensory and motor impairments

Hand loss can now be reversed through surgical transplantation years or decades after amputation. Remarkably, these patients come to use their new hand to skilfully grasp and manipulate objects. The brain mechanisms that make this possible are unknown. Here we test the hypothesis that the anterior intraparietal cortex (aIPC) - a multimodal region implicated in hand preshaping and error correction during grasping - plays a key role in this compensatory grasp control. Motion capture and fMRI are used to characterize hand kinematics and brain responses during visually guided grasping with a transplanted hand at 26 and 41 months post-transplant in patient DR, a former hand amputee of 13 years. Compared with matched controls, DR shows increasingly normal grasp kinematics paralleled by increasingly robust grasp-selective fMRI responses within the very same brain areas that show grasp-selectivity in controls, including the aIPC, premotor and cerebellar cortices. Paradoxically, over this same time DR exhibits significant limitations in basic sensory and motor functions, and persistent amputation-related functional reorganization of primary motor cortex. Movements of the non-transplanted hand positively activate the ipsilateral primary motor hand area - a functional marker of persistent interhemispheric amputation-related reorganization. Our data demonstrate for the first time that even after more than a decade of living as an amputee the normative functional brain organization governing the control of grasping can be restored. We propose that the aIPC and interconnected premotor and cerebellar cortices enable grasp normalization by compensating for the functional impact of reorganizational changes in primary sensorimotor cortex and targeting errors in regenerating peripheral nerves.

Functional specialization of macaque premotor F5 subfields with respect to hand and mouth movements: A comparison of task and resting-state fMRI

Based on architectonic, tract-tracing or functional criteria, the rostral portion of ventral premotor cortex in the macaque monkey, also termed area F5, has been divided into several subfields. Cytoarchitectonical investigations suggest the existence of three subfields, F5c (convexity), F5p (posterior) and F5a (anterior). Electrophysiological investigations have suggested a gradual dorso-ventral transition from hand- to mouth-dominated motor fields, with F5p and ventral F5c strictly related to hand movements and mouth movements, respectively. The involvement of F5a in this respect, however, has received much less attention. Recently, data-driven resting-state fMRI approaches have also been used to examine the presence of distinct functional fields in macaque ventral premotor cortex. Although these studies have suggested several functional clusters in/near macaque F5, so far the parcellation schemes derived from these clustering methods do not completely retrieve the same level of F5 specialization as suggested by aforementioned invasive techniques. Here, using seed-based resting-state fMRI analyses, we examined the functional connectivity of different F5 seeds with key regions of the hand and face/mouth parieto-frontal-insular motor networks. In addition, we trained monkeys to perform either hand grasping or ingestive mouth movements in the scanner in order to compare resting-state with task-derived functional hand and mouth motor networks. In line with previous single-cell investigations, task-fMRI suggests involvement of F5p, dorsal F5c and F5a in the execution of hand grasping movements, while non-communicative mouth movements yielded particularly pronounced responses in ventral F5c. Corroborating with anatomical tracing data of macaque F5 subfields, seed-based resting-state fMRI suggests a transition from predominant functional correlations with the hand-motor network in F5p to mostly mouth-motor network functional correlations in ventral F5c. Dorsal F5c yielded robust functional correlations with both hand- and mouth-motor networks. In addition, the deepest part of the fundus of the inferior arcuate, corresponding to area 44, displayed a strikingly different functional connectivity profile compared to neighboring F5a, suggesting a different functional specialization for these two neighboring regions.