Perspectives on classical controversies about the motor cortex

A theory of brain-computer interface learning via low-dimensional control

A remarkable demonstration of the flexibility of mammalian motor systems is primates' ability to learn to control brain-computer interfaces (BCIs). This constitutes a completely novel motor behavior, yet primates are capable of learning to control BCIs under a wide range of conditions. BCIs with carefully calibrated decoders, for example, can be learned with only minutes to hours of practice. With a few weeks of practice, even BCIs with randomly constructed decoders can be learned. What are the biological substrates of this learning process? Here, we develop a theory based on a re-aiming strategy, whereby learning operates within a low-dimensional subspace of task-relevant inputs driving the local population of recorded neurons. Through comprehensive numerical and formal analysis, we demonstrate that this theory can provide a unifying explanation for disparate phenomena previously reported in three different BCI learning tasks, and we derive a novel experimental prediction that we verify with previously published data. By explicitly modeling the underlying neural circuitry, the theory reveals an interpretation of these phenomena in terms of biological constraints on neural activity.

Multiplicative joint coding in preparatory activity for reaching sequence in macaque motor cortex

Although the motor cortex has been found to be modulated by sensory or cognitive sequences, the linkage between multiple movement elements and sequence-related responses is not yet understood. Here, we recorded neuronal activity from the motor cortex with implanted micro-electrode arrays and single electrodes while monkeys performed a double-reach task that was instructed by simultaneously presented memorized cues. We found that there existed a substantial multiplicative component jointly tuned to impending and subsequent reaches during preparation, then the coding mechanism transferred to an additive manner during execution. This multiplicative joint coding, which also spontaneously emerged in recurrent neural networks trained for double reach, enriches neural patterns for sequential movement, and might explain the linear readout of elemental movements.

Preparatory activity and the expansive null-space

The study of the cortical control of movement experienced a conceptual shift over recent decades, as the basic currency of understanding shifted from single-neuron tuning towards population-level factors and their dynamics. This transition was informed by a maturing understanding of recurrent networks, where mechanism is often characterized in terms of population-level factors. By estimating factors from data, experimenters could test network-inspired hypotheses. Central to such hypotheses are 'output-null' factors that do not directly drive motor outputs yet are essential to the overall computation. In this Review, we highlight how the hypothesis of output-null factors was motivated by the venerable observation that motor-cortex neurons are active during movement preparation, well before movement begins. We discuss how output-null factors then became similarly central to understanding neural activity during movement. We discuss how this conceptual framework provided key analysis tools, making it possible for experimenters to address long-standing questions regarding motor control. We highlight an intriguing trend: as experimental and theoretical discoveries accumulate, the range of computational roles hypothesized to be subserved by output-null factors continues to expand.

Pain-sensorimotor interactions: New perspectives and a new model

How pain and sensorimotor behavior interact has been the subject of research and debate for many decades. This article reviews theories bearing on pain-sensorimotor interactions and considers their strengths and limitations in the light of findings from experimental and clinical studies of pain-sensorimotor interactions in the spinal and craniofacial sensorimotor systems. A strength of recent theories is that they have incorporated concepts and features missing from earlier theories to account for the role of the sensory-discriminative, motivational-affective, and cognitive-evaluative dimensions of pain in pain-sensorimotor interactions. Findings acquired since the formulation of these recent theories indicate that additional features need to be considered to provide a more comprehensive conceptualization of pain-sensorimotor interactions. These features include biopsychosocial influences that range from biological factors such as genetics and epigenetics to psychological factors and social factors encompassing environmental and cultural influences. Also needing consideration is a mechanistic framework that includes other biological factors reflecting nociceptive processes and glioplastic and neuroplastic changes in sensorimotor and related brain and spinal cord circuits in acute or chronic pain conditions. The literature reviewed and the limitations of previous theories bearing on pain-sensorimotor interactions have led us to provide new perspectives on these interactions, and this has prompted our development of a new concept, the Theory of Pain-Sensorimotor Interactions (TOPSMI) that we suggest gives a more comprehensive framework to consider the interactions and their complexity. This theory states that pain is associated with plastic changes in the central nervous system (CNS) that lead to an activation pattern of motor units that contributes to the individual's adaptive sensorimotor behavior. This activation pattern takes account of the biological, psychological, and social influences on the musculoskeletal tissues involved in sensorimotor behavior and on the plastic changes and the experience of pain in that individual. The pattern is normally optimized in terms of biomechanical advantage and metabolic cost related to the features of the individual's musculoskeletal tissues and aims to minimize pain and any associated sensorimotor changes, and thereby maintain homeostasis. However, adverse biopsychosocial factors and their interactions may result in plastic CNS changes leading to less optimal, even maladaptive, sensorimotor changes producing motor unit activation patterns associated with the development of further pain. This more comprehensive theory points towards customized treatment strategies, in line with the management approaches to pain proposed in the biopsychosocial model of pain.

Distinct neural representations during a brain-machine interface and manual reaching task in motor cortex, prefrontal cortex, and striatum

Although brain-machine interfaces (BMIs) are directly controlled by the modulation of a select local population of neurons, distributed networks consisting of cortical and subcortical areas have been implicated in learning and maintaining control. Previous work in rodents has demonstrated the involvement of the striatum in BMI learning. However, the prefrontal cortex has been largely ignored when studying motor BMI control despite its role in action planning, action selection, and learning abstract tasks. Here, we compare local field potentials simultaneously recorded from primary motor cortex (M1), dorsolateral prefrontal cortex (DLPFC), and the caudate nucleus of the striatum (Cd) while nonhuman primates perform a two-dimensional, self-initiated, center-out task under BMI control and manual control. Our results demonstrate the presence of distinct neural representations for BMI and manual control in M1, DLPFC, and Cd. We find that neural activity from DLPFC and M1 best distinguishes control types at the go cue and target acquisition, respectively, while M1 best predicts target-direction at both task events. We also find effective connectivity from DLPFC → M1 throughout both control types and Cd → M1 during BMI control. These results suggest distributed network activity between M1, DLPFC, and Cd during BMI control that is similar yet distinct from manual control.

Anti-Hebbian plasticity in the motor cortex promotes defensive freezing

Regional brain activity often decreases from baseline levels in response to external events, but how neurons develop such negative responses is unclear. To study this, we leveraged the negative response that develops in the primary motor cortex (M1) after classical fear learning. We trained mice with a fear conditioning paradigm while imaging their brains with standard two-photon microscopy. This enabled monitoring changes in neuronal responses to the tone with synaptic resolution through learning. We found that M1 layer 5 pyramidal neurons (L5 PNs) developed negative tone responses within an hour after conditioning, which depended on the weakening of their dendritic spines that were active during training. Blocking this form of anti-Hebbian plasticity using an optogenetic manipulation of CaMKII activity disrupted negative tone responses and freezing. Therefore, reducing the strength of spines active at the time of memory encoding leads to negative responses of L5 PNs. In turn, these negative responses curb M1's capacity for promoting movement, thereby aiding freezing. Collectively, this work provides a mechanistic understanding of how area-specific negative responses to behaviorally relevant cues can be achieved.

Invariant neural dynamics drive commands to control different movements

It has been proposed that the nervous system has the capacity to generate a wide variety of movements because it reuses some invariant code. Previous work has identified that dynamics of neural population activity are similar during different movements, where dynamics refer to how the instantaneous spatial pattern of population activity changes in time. Here, we test whether invariant dynamics of neural populations are actually used to issue the commands that direct movement. Using a brain-machine interface (BMI) that transforms rhesus macaques' motor-cortex activity into commands for a neuroprosthetic cursor, we discovered that the same command is issued with different neural-activity patterns in different movements. However, these different patterns were predictable, as we found that the transitions between activity patterns are governed by the same dynamics across movements. These invariant dynamics are low dimensional, and critically, they align with the BMI, so that they predict the specific component of neural activity that actually issues the next command. We introduce a model of optimal feedback control (OFC) that shows that invariant dynamics can help transform movement feedback into commands, reducing the input that the neural population needs to control movement. Altogether our results demonstrate that invariant dynamics drive commands to control a variety of movements and show how feedback can be integrated with invariant dynamics to issue generalizable commands.

Behavioral decomposition reveals rich encoding structure employed across neocortex in rats

The cortical population code is pervaded by activity patterns evoked by movement, but it remains largely unknown how such signals relate to natural behavior or how they might support processing in sensory cortices where they have been observed. To address this we compared high-density neural recordings across four cortical regions (visual, auditory, somatosensory, motor) in relation to sensory modulation, posture, movement, and ethograms of freely foraging male rats. Momentary actions, such as rearing or turning, were represented ubiquitously and could be decoded from all sampled structures. However, more elementary and continuous features, such as pose and movement, followed region-specific organization, with neurons in visual and auditory cortices preferentially encoding mutually distinct head-orienting features in world-referenced coordinates, and somatosensory and motor cortices principally encoding the trunk and head in egocentric coordinates. The tuning properties of synaptically coupled cells also exhibited connection patterns suggestive of area-specific uses of pose and movement signals, particularly in visual and auditory regions. Together, our results indicate that ongoing behavior is encoded at multiple levels throughout the dorsal cortex, and that low-level features are differentially utilized by different regions to serve locally relevant computations.

Interhemispheric differences of pyramidal cells in the primary motor cortices of schizophrenia patients investigated postmortem

Motor disturbances are observed in schizophrenia patients, but the neuroanatomical background is unknown. Our aim was to investigate the pyramidal cells of the primary motor cortex (BA 4) in both hemispheres of postmortem control and schizophrenia subjects-8 subjects in each group-with 2.5-5.5 h postmortem interval. The density and size of the Sternberger monoclonal incorporated antibody 32 (SMI32)-immunostained pyramidal cells in layer 3 and 5 showed no change; however, the proportion of larger pyramidal cells is decreased in layer 5. Giant pyramidal neurons (Betz cells) were investigated distinctively with SMI32- and parvalbumin (PV) immunostainings. In the right hemisphere of schizophrenia subjects, the density of Betz cells was decreased and their PV-immunopositive perisomatic input showed impairment. Part of the Betz cells contained PV in both groups, but the proportion of PV-positive cells has declined with age. The rat model of antipsychotic treatment with haloperidol and olanzapine showed no differences in size and density of SMI32-immunopositive pyramidal cells. Our results suggest that motor impairment of schizophrenia patients may have a morphological basis involving the Betz cells in the right hemisphere. These alterations can have neurodevelopmental and neurodegenerative explanations, but antipsychotic treatment does not explain them.

Neural Plasticity in Sensorimotor Brain-Machine Interfaces

Brain-machine interfaces (BMIs) aim to treat sensorimotor neurological disorders by creating artificial motor and/or sensory pathways. Introducing artificial pathways creates new relationships between sensory input and motor output, which the brain must learn to gain dexterous control. This review highlights the role of learning in BMIs to restore movement and sensation, and discusses how BMI design may influence neural plasticity and performance. The close integration of plasticity in sensory and motor function influences the design of both artificial pathways and will be an essential consideration for bidirectional devices that restore both sensory and motor function.

Distinct neural representations during a brain-machine interface and manual reaching task in motor cortex, prefrontal cortex, and striatum

Although brain-machine interfaces (BMIs) are directly controlled by the modulation of a select local population of neurons, distributed networks consisting of cortical and subcortical areas have been implicated in learning and maintaining control. Previous work in rodent BMI has demonstrated the involvement of the striatum in BMI learning. However, the prefrontal cortex has been largely ignored when studying motor BMI control despite its role in action planning, action selection, and learning abstract tasks. Here, we compare local field potentials simultaneously recorded from the primary motor cortex (M1), dorsolateral prefrontal cortex (DLPFC), and the caudate nucleus of the striatum (Cd) while nonhuman primates perform a two-dimensional, self-initiated, center-out task under BMI control and manual control. Our results demonstrate the presence of distinct neural representations for BMI and manual control in M1, DLPFC, and Cd. We find that neural activity from DLPFC and M1 best distinguish between control types at the go cue and target acquisition, respectively. We also found effective connectivity from DLPFC→M1 throughout trials across both control types and Cd→M1 during BMI control. These results suggest distributed network activity between M1, DLPFC, and Cd during BMI control that is similar yet distinct from manual control.

A hierarchical sensorimotor control framework for human-in-the-loop robotic hands

Human manual dexterity relies critically on touch. Robotic and prosthetic hands are much less dexterous and make little use of the many tactile sensors available. We propose a framework modeled on the hierarchical sensorimotor controllers of the nervous system to link sensing to action in human-in-the-loop, haptically enabled, artificial hands.

Alf Brodal's stroke in 1972: A brilliant self-report by a neuroanatomy professor

Alf Brodal (1910-1988) was a professor of anatomy at the University of Oslo, Norway, and the author of almost 200 articles and medical textbooks including Neurological Anatomy in Relation to Clinical Neurology. He suffered a right hemisphere embolic stroke during a lecture trip abroad in April 1972. In the following year, he described his own clinical picture and the recovery process in an article published in Brain, making insightful observations based on his vast neuroanatomical knowledge. His comments and analyses remain largely valid after 50 years.

New insights on single-neuron selectivity in the era of population-level approaches

In the past, neuroscience was focused on individual neurons seen as the functional units of the nervous system, but this approach fell short over time to account for new experimental evidence, especially for what concerns associative and motor cortices. For this reason and thanks to great technological advances, a part of modern research has shifted the focus from the responses of single neurons to the activity of neural ensembles, now considered the real functional units of the system. However, on a microscale, individual neurons remain the computational components of these networks, thus the study of population dynamics cannot prescind from studying also individual neurons which represent their natural substrate. In this new framework, ideas such as the capability of single cells to encode a specific stimulus (neural selectivity) may become obsolete and need to be profoundly revised. One step in this direction was made by introducing the concept of “mixed selectivity,” the capacity of single cells to integrate multiple variables in a flexible way, allowing individual neurons to participate in different networks. In this review, we outline the most important features of mixed selectivity and we also present recent works demonstrating its presence in the associative areas of the posterior parietal cortex. Finally, in discussing these findings, we present some open questions that could be addressed by future studies.

Neuronal population dynamics during motor plan cancellation in nonhuman primates

To understand the cortical neuronal dynamics behind movement generation and control, most studies have focused on tasks where actions were planned and then executed using different instances of visuomotor transformations. However, to fully understand the dynamics related to movement control, one must also study how movements are actively inhibited. Inhibition, indeed, represents the first level of control both when different alternatives are available and only one solution could be adopted and when it is necessary to maintain the current position. We recorded neuronal activity from a multielectrode array in the dorsal premotor cortex (PMd) of monkeys performing a countermanding reaching task that requires, in a subset of trials, them to cancel a planned movement before its onset. In the analysis of the neuronal state space of PMd, we found a subspace in which activities conveying temporal information were confined during active inhibition and position holding. Movement execution required activities to escape from this subspace toward an orthogonal subspace and, furthermore, surpass a threshold associated with the maturation of the motor plan. These results revealed further details in the neuronal dynamics underlying movement control, extending the hypothesis that neuronal computation confined in an "output-null" subspace does not produce movements.

Beyond language: The unspoken sensory-motor representation of the tongue in non-primates, non-human and human primates

The English idiom "on the tip of my tongue" commonly acknowledges that something is known, but it cannot be immediately brought to mind. This phrase accurately describes sensorimotor functions of the tongue, which are fundamental for many tongue-related behaviors (e.g., speech), but often neglected by scientific research. Here, we review a wide range of studies conducted on non-primates, non-human and human primates with the aim of providing a comprehensive description of the cortical representation of the tongue's somatosensory inputs and motor outputs across different phylogenetic domains. First, we summarize how the properties of passive non-noxious mechanical stimuli are encoded in the putative somatosensory tongue area, which has a conserved location in the ventral portion of the somatosensory cortex across mammals. Second, we review how complex self-generated actions involving the tongue are represented in more anterior regions of the putative somato-motor tongue area. Finally, we describe multisensory response properties of the primate and non-primate tongue area by also defining how the cytoarchitecture of this area is affected by experience and deafferentation.

Moving in on human motor cortex. Characterizing the relationship between body parts with non-rigid population response fields

For cortical motor activity, the relationships between different body part representations is unknown. Through reciprocal body part relationships, functionality of cortical motor areas with respect to whole body motor control can be characterized. In the current study, we investigate the relationship between body part representations within individual neuronal populations in motor cortices, following a 7 Tesla fMRI 18-body-part motor experiment in combination with our newly developed non-rigid population Response Field (pRF) model and graph theory. The non-rigid pRF metrics reveal somatotopic structures in all included motor cortices covering frontal, parietal, medial and insular cortices and that neuronal populations in primary sensorimotor cortex respond to fewer body parts than secondary motor cortices. Reciprocal body part relationships are estimated in terms of uniqueness, clique-formation, and influence. We report unique response profiles for the knee, a clique of body parts surrounding the ring finger, and a central role for the shoulder and wrist. These results reveal associations among body parts from the perspective of the central nervous system, while being in agreement with intuitive notions of body part usage.

Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control

Establishing the basic knowledge, methodology, and technology for a framework for the continuous decoding of hand/arm movement intention was the aim of the ERC-funded project “Feel Your Reach”. In this work, we review the studies and methods we performed and implemented in the last 6 years, which build the basis for enabling severely paralyzed people to non-invasively control a robotic arm in real-time from electroencephalogram (EEG). In detail, we investigated goal-directed movement detection, decoding of executed and attempted movement trajectories, grasping correlates, error processing, and kinesthetic feedback. Although we have tested some of our approaches already with the target populations, we still need to transfer the “Feel Your Reach” framework to people with cervical spinal cord injury and evaluate the decoders’ performance while participants attempt to perform upper-limb movements. While on the one hand, we made major progress towards this ambitious goal, we also critically discuss current limitations.

Investigation of Neural Substrates of Erroneous Behavior in a Delayed-Response Task

Motor cortical neurons exhibit persistent selective activities (selectivity) during motor planning. Experimental perturbation of selectivity results in the failure of short-term memory retention and consequent behavioral biases, demonstrating selectivity as a neural characteristic of encoding previous sensory input or future action. However, even without experimental manipulation, animals occasionally fail to maintain short-term memory leading to erroneous choice. Here, we investigated neural substrates that lead to the incorrect formation of selectivity during short-term memory. We analyzed neuronal activities in anterior lateral motor cortex (ALM) of mice, a region known to be engaged in motor planning while mice performed the tactile delayed-response task. We found that highly selective neurons lost their selectivity while originally nonselective neurons showed selectivity during the error trials where mice licked toward incorrect direction. We assumed that those alternations would reflect changes in intrinsic properties of population activity. Thus, we estimated an intrinsic manifold shared by neuronal population (shared space), using factor analysis (FA) and measured the association of individual neurons with the shared space by communality, the variance of neuronal activity accounted for by the shared space. We found a positive correlation between selectivity and communality over ALM neurons, which disappeared in erroneous behavior. Notably, neurons showing selectivity alternations between correct and incorrect licking also underwent proportional changes in communality. Our results demonstrated that the extent to which an ALM neuron is associated with the intrinsic manifolds of population activity may elucidate its selectivity and that disruption of this association may alter selectivity, likely leading to erroneous behavior.

Clinical Imaging-Derived Metrics of Corticospinal Tract Structural Integrity Are Associated With Post-stroke Motor Outcomes: A Retrospective Study

Objective

The primary objective of this study was to retrospectively investigate associations between clinical magnetic resonance imaging-based (MRI) metrics of corticospinal tract (CST) status and paretic upper extremity (PUE) motor recovery in patients that completed acute inpatient rehabilitation (AR) post-stroke.

Methods

We conducted a longitudinal chart review of patients post-stroke who received care in the Emory University Hospital system during acute hospitalization, AR, and outpatient therapy. We extracted demographic information, stroke characteristics, and longitudinal documentation of post-stroke motor function from institutional electronic medical records. Serial assessments of paretic shoulder abduction and finger extension were estimated (E-SAFE) and an estimated Action Research Arm Test (E-ARAT) score was used to quantify 3-month PUE motor function outcome. Clinically-diagnostic MRI were used to create lesion masks that were spatially normalized and overlaid onto a white matter tract atlas delineating CST contributions emanating from six cortical seed regions to obtain the percentage of CST lesion overlap. Metric associations were investigated with correlation and cluster analyses, Kruskal-Wallis tests, classification and regression tree analysis.

Results

Thirty-four patients met study eligibility criteria. All CST overlap percentages were correlated with E-ARAT however, ventral premotor tract (PMv) overlap was the only tract that remained significantly correlated after multiple comparisons adjustment. Lesion overlap percentage in CST contributions from all seed regions was significantly different between outcome categories. Using MRI metrics alone, dorsal premotor (PMd) and PMv tracts classified recovery outcome category with 79.4% accuracy. When clinical and MRI metrics were combined, AR E-SAFE, patient age, and overall CST lesion overlap classified patients with 88.2% accuracy.

Conclusions

Study findings revealed clinical MRI-derived CST lesion overlap was associated with PUE motor outcome post-stroke and that cortical projections within the CST, particularly those emanating from non-M1 cortical areas, prominently ventral premotor (PMv) and dorsal premotor (PMd) cortices, distinguished between PUE outcome groups. Exploratory predictive models using clinical MRI metrics, either alone or in combination with clinical measures, were able to accurately identify recovery outcome category for the study cohort during both the acute and early subacute phases of post-stroke recovery. Prospective studies are recommended to determine the predictive utility of including clinical imaging-based biomarkers of white matter tract structural integrity in predictive models of post-stroke recovery.

Automatic mapping of multiplexed social receptive fields by deep learning and GPU-accelerated 3D videography

Social interactions powerfully impact the brain and the body, but high-resolution descriptions of these important physical interactions and their neural correlates are lacking. Currently, most studies rely on labor-intensive methods such as manual annotation. Scalable and objective tracking methods are required to understand the neural circuits underlying social behavior. Here we describe a hardware/software system and analysis pipeline that combines 3D videography, deep learning, physical modeling, and GPU-accelerated robust optimization, with automatic analysis of neuronal receptive fields recorded in interacting mice. Our system ("3DDD Social Mouse Tracker") is capable of fully automatic multi-animal tracking with minimal errors (including in complete darkness) during complex, spontaneous social encounters, together with simultaneous electrophysiological recordings. We capture posture dynamics of multiple unmarked mice with high spatiotemporal precision (~2 mm, 60 frames/s). A statistical model that relates 3D behavior and neural activity reveals multiplexed 'social receptive fields' of neurons in barrel cortex. Our approach could be broadly useful for neurobehavioral studies of multiple animals interacting in complex low-light environments.

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.

Does motor noise contaminate estimates of the precision of visual working memory?

The continuous-report task, in which subjects report the color of visual working memory representation by clicking on a color wheel, has become the gold standard for measuring the precision and number of representations stored in visual working memory. This task requires fine motor control, typically with a mouse, but the precision of responses have been interpreted as being entirely due to the precision of the memory representations, without regard to the contribution of noise from the response effectors (i.e., motor control of the hand). Here we tested the seemingly likely possibility that motor noise contaminates our estimates of visual memory representations in the continuous-report task by simply asking subjects to complete the color wheel continuous-report task using either their dominant or non-dominant hand on different blocks of trials. We found that subjects took longer to complete the task with their non-dominant hand, but this did not affect the precision of their responses. Our findings suggest that this commonly used task to study visual memory may be relatively immune from contamination by motor noise at the output stage.

Neural Encoding of Reaches in a Linear Cortical Model

To effectively control the arm, motor cortical neurons must produce complex patterns of activation that vary with the position and orientation of the arm and reach direction. In order to better understand how such a finely tuned dynamical system could arise and what its basic organizing principles are, we develop a model of the motor cortex as a linear dynamical system with feedback coupled to a two-joint model of the macaque arm. By optimizing the connections between neural populations with respect to an objective function that penalizes error between hand and target, as well as neural and muscular energy use, we show that certain properties of the motor cortex, such as muscle synergies, can naturally be obtained. We also demonstrate that the optimization process produces a stable neural system in which targets in the physical space are mapped to attracting fixed points in the neural state space. Finally, we show that this optimization process produces neural units with complex spatial and temporal activation patterns.

Neurons in Primary Motor Cortex Encode External Perturbations during an Orientation Reaching Task

When confronting an abrupt external perturbation force during movement, subjects continuously adjust their behaviors to adapt to changes. Such adaptation is of great importance for realizing flexible motor control in varied environments, but the potential cortical neuronal mechanisms behind it have not yet been elucidated. Aiming to reveal potential neural control system compensation for external disturbances, we applied an external orientation perturbation while monkeys performed an orientation reaching task and simultaneously recorded the neural activity in the primary motor cortex (M1). We found that a subpopulation of neurons in the primary motor cortex specially created a time-locked activity in response to a “go” signal in the adaptation phase of the impending orientation perturbation and did not react to a “go” signal under the normal task condition without perturbation. Such neuronal activity was amplified as the alteration was processed and retained in the extinction phase; then, the activity gradually faded out. The increases in activity during the adaptation to the orientation perturbation may prepare the system for the impending response. Our work provides important evidence for understanding how the motor cortex responds to external perturbations and should advance research about the neurophysiological mechanisms underlying motor learning and adaptation.

Magnetic Resonance Imaging-Based Structural Covariance Changes of the Striatum in Lifelong Premature Ejaculation Patients

BACKGROUND

The striatum has been reported to be implicated in various neurological diseases, including lifelong premature ejaculation (LPE). Altered striatum-related functional connectivity was investigated in LPE patients in previous studies; however, structural abnormalities in the striatum have been less studied in LPE.

PURPOSE

To identify the gray matter volume (GMV) and structural covariance patterns of the striatum between LPE patients and healthy controls (HCs).

STUDY TYPE

Prospective.

SUBJECTS

Forty-three LPE patients and 31 male HCs.

FIELD STRENGTH/SEQUENCE

3.0 T magnetic resonance imaging (MRI) scanner; T1-weighted imaging using a spoiled gradient recalled echo sequence.

ASSESSMENT

Preprocessing of structural MRI data and the striatum-seeded GMV computation were conducted using SPM12.

STATISTICAL TESTS

Two sample t-test was used to compare differences in GMV of the striatum between patients and HCs. Regions showing altered between-group GMV were considered as seeds for structural covariance analysis in two groups. Additionally, correlations between GMV findings and clinical features were assessed with age and total intracranial volume (TIV) as covariates and with age, TIV, anxiety, and depression scores as covariates in the patient group, P < 0.05 was considered statistically significant.

RESULTS

Compared to HCs, LPE patients had significantly decreased GMV in four regions located in the bilateral caudate and putamen. Distinct striatum-based structural covariance patterns in the two groups were mainly related to the thalamus, amygdala, insula, anterior cingulate cortex, middle cingulate cortex, medial prefrontal cortex, primary motor cortex, and precuneus/cuneus. LPE patients showed that GMV in the bilateral caudate negatively correlated with the premature ejaculation diagnostic tool (PEDT) scores (r = -0.369, r = -0.377, respectively).

DATA CONCLUSION

Our findings indicated that LPE patients had altered GMV and structural covariance patterns in the striatum compared to HCs. The correlations between abnormal GMV and PEDT were also shown in the present findings. These findings may contribute to enhancing the understanding of the pathophysiology of LPE.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 3.

Windows and periscopes into primate behavior

Calcium imaging of neurons in monkeys making reaches is complicated by brain movements and limited by shallow imaging depth. In a pair of recent studies, Trautmann et al., 2021 and Bollimunta et al. (2021) present complementary solutions to these problems.

Motor-like neural dynamics in two parietal areas during arm reaching

The classical view on motor control makes a clear distinction between the role of motor cortex in controlling muscles and parietal cortex in processing movement plans and goals. However, the strong parieto-frontal connections argue against such clear-cut separation of function. Modern dynamical approaches revealed that population activity in motor cortex can be captured by a limited number of patterns, called neural states that are preserved across diverse motor behaviors. Whether such dynamics are also present in parietal cortex is unclear. Here, we studied neural dynamics in the primate parietal cortex during arm movements and found three main states temporally coupled to the planning, execution and target holding epochs. Strikingly, as reported recently in motor cortex, execution was subdivided into distinct, arm acceleration- and deceleration-related, states. These results suggest that dynamics across parieto-frontal areas are highly consistent and hint that parietal population activity largely reflects timing constraints while motor actions unfold.

Body language signals for rodent social communication

Integration of social cues to initiate adaptive emotional and behavioral responses is a fundamental aspect of animal and human behavior. In humans, social communication includes prominent nonverbal components, such as social touch, gestures and facial expressions. Comparative studies investigating the neural basis of social communication in rodents has historically been centered on olfactory signals and vocalizations, with relatively less focus on non-verbal social cues. Here, we outline two exciting research directions: First, we will review recent observations pointing to a role of social facial expressions in rodents. Second, we will review observations that point to a role of 'non-canonical' rodent body language: body posture signals beyond stereotyped displays in aggressive and sexual behavior. In both sections, we will outline how social neuroscience can build on recent advances in machine learning, robotics and micro-engineering to push these research directions forward towards a holistic systems neurobiology of rodent body language.

Optimal anticipatory control as a theory of motor preparation: A thalamo-cortical circuit model

Across a range of motor and cognitive tasks, cortical activity can be accurately described by low-dimensional dynamics unfolding from specific initial conditions on every trial. These "preparatory states" largely determine the subsequent evolution of both neural activity and behavior, and their importance raises questions regarding how they are, or ought to be, set. Here, we formulate motor preparation as optimal anticipatory control of future movements and show that the solution requires a form of internal feedback control of cortical circuit dynamics. In contrast to a simple feedforward strategy, feedback control enables fast movement preparation by selectively controlling the cortical state in the small subspace that matters for the upcoming movement. Feedback but not feedforward control explains the orthogonality between preparatory and movement activity observed in reaching monkeys. We propose a circuit model in which optimal preparatory control is implemented as a thalamo-cortical loop gated by the basal ganglia.

Simultaneous Recording of Motor Evoked Potentials in Hand, Wrist and Arm Muscles to Assess Corticospinal Divergence

The purpose of this study was to further develop methods to assess corticospinal divergence and muscle coupling using transcranial magnetic stimulation (TMS). Ten healthy right-handed adults participated (7 females, age 34.0 ± 12.9 years). Monophasic single pulses were delivered to 14 sites over the right primary motor cortex at 40, 60, 80 and 100% of maximum stimulator output (MSO), using MRI-based neuronavigation. Motor evoked potentials (MEPs) were recorded simultaneously from 9 muscles of the contralateral hand, wrist and arm. For each intensity, corticospinal divergence was quantified by the average number of muscles that responded to TMS per cortical site, coactivation across muscle pairs as reflected by overlap of cortical representations, and correlation of MEP amplitudes across muscle pairs. TMS to each muscle's most responsive site elicited submaximal MEPs in most other muscles. The number of responsive muscles per cortical site and the extent of coactivation increased with increasing intensity (ANOVA, p < 0.001). In contrast, correlations of MEP amplitudes did not differ across the 60, 80 and 100% MSO intensities (ANOVA, p = 0.34), but did differ across muscle pairs (ANOVA, p < 0.001). Post hoc analysis identified 4 sets of muscle pairs (Tukey homogenous subsets, p < 0.05). Correlations were highest for pairs involving two hand muscles and lowest for pairs that included an upper arm muscle. Correlation of MEP amplitudes may quantify varying levels of muscle coupling. In future studies, this approach may be a biomarker to reveal altered coupling induced by neural injury, neural repair and/or motor learning.

Enhanced structural connectivity within the motor loop in professional boxers prior to a match

Professional boxers train to reduce their body mass before a match to refine their body movements. To test the hypothesis that the well-defined movements of boxers are represented within the motor loop (cortico-striatal circuit), we first elucidated the brain structure and functional connectivity specific to boxers and then investigated plasticity in relation to boxing matches. We recruited 21 male boxers 1 month before a match (Time1) and compared them to 22 age-, sex-, and body mass index (BMI)-matched controls. Boxers were longitudinally followed up within 1 week prior to the match (Time2) and 1 month after the match (Time3). The BMIs of boxers significantly decreased at Time2 compared with those at Time1 and Time3. Compared to controls, boxers presented significantly higher gray matter volume in the left putamen, a critical region representing motor skill training. Boxers presented significantly higher functional connectivity than controls between the left primary motor cortex (M1) and left putamen, which is an essential region for establishing well-defined movements. Boxers also showed significantly higher structural connectivity in the same region within the motor loop from Time1 to Time2 than during other periods, which may represent the refined movements of their body induced by training for the match.

Corticospinal excitability and motor representation after long-term resistance training

It is poorly understood how the central nervous system adapts to resistance training, especially after years of exposure. We compared corticospinal excitability and motor representation assessed with transcranial magnetic stimulation (TMS) between long-term resistance trained (LRT, ≥3 years) versus untrained (UNT) males (n = 15/group). Motor-evoked potentials (MEPs) were obtained from the biceps brachii during isometric elbow flexion. Stimulus-response curves were created at the hotspot during 10% maximum voluntary torque (MVT) contractions. Maximum peak-to-peak MEP amplitude (MEPmax) was acquired with 100% stimulator output intensity, whilst 25%-100% MVT was produced. Maps were created during 10% MVT contractions, with an individualised TMS intensity eliciting 20% MEPmax at the hotspot. LRT had a 48% lower stimulus-response curve slope than UNT (p < .05). LRT also had a 66% larger absolute map size, although TMS intensity used for mapping was greater in LRT versus UNT (48% vs. 26% above active motor threshold) to achieve a target 20% MEPmax at the hotspot, due to the lower slope of LRT. Map size was strongly correlated with the TMS intensity used for mapping (r = 0.776, p < .001). Once map size was normalised to TMS intensity, there was no difference between the groups (p = .683). We conclude that LRT had a lower stimulus-response curve slope/excitability, suggesting higher neural efficiency. TMS map size was overwhelmingly determined by TMS intensity, even when the MEP response at the hotspot was matched among individuals, likely due to larger current spread with higher intensities. Motor representation appears similar between LRT and UNT given no difference in the normalised map size.

Perisomatic innervation and neurochemical features of giant pyramidal neurons in both hemispheres of the human primary motor cortex

Betz cells-the gigantopyramidal neurons found in high amount in the primary motor cortex-are among of the most characteristic neuronal cells. A part of them contains the calcium-binding protein parvalbumin (PV) in primates. However, less is known about these cells in the human motor cortex despite their important role in different neurological disorders. Therefore, the aim of our study was to investigate the neurochemical features and perisomatic input properties of Betz cells in control human samples with short post-mortem interval. We used different microscopic techniques to investigate the primary motor cortex of both hemispheres. The soma size and density, and expression of PV of the Betz cells were investigated. Furthermore, we used confocal fluorescent and electron microscopy to examine their perisomatic input. The soma size and density showed moderate variability among samples and hemispheres. Post-mortem interval and hemispherical localization did not influence these features. Around 70% of Betz cells expressed PV, but in less intensity than the cortical interneurons. Betz neurons receive dense perisomatic input, which are mostly VIAAT- (vesicular inhibitory amino acid transporter) and PV immunopositive. In the electron microscope, we found PV-immunolabelled terminals with asymmetric-like synaptic structure, too. Terminals with morphologically similar synaptic specialisation were also found among vGluT2- (vesicular glutamate transporter type 2) immunostained terminals contacting Betz cells. Our data suggest that Betz cells' morphological properties showed less variability among subjects and hemispheres than the density of them. Their neurochemical and perisomatic input characteristics support their role in execution of fast and precise movements.

The human primary somatosensory cortex encodes imagined movement in the absence of sensory information

Classical systems neuroscience positions primary sensory areas as early feed-forward processing stations for refining incoming sensory information. This view may oversimplify their role given extensive bi-directional connectivity with multimodal cortical and subcortical regions. Here we show that single units in human primary somatosensory cortex encode imagined reaches in a cognitive motor task, but not other sensory–motor variables such as movement plans or imagined arm position. A population reference-frame analysis demonstrates coding relative to the cued starting hand location suggesting that imagined reaching movements are encoded relative to imagined limb position. These results imply a potential role for primary somatosensory cortex in cognitive imagery, engagement during motor production in the absence of sensation or expected sensation, and suggest that somatosensory cortex can provide control signals for future neural prosthetic systems.

Matiar Jafari, Tyson Aflalo et al. show that the human primary somatosensory cortex is activated when subjects imagine reaches in a cognitive motor task, but not when they plan movement or imagine a static limb position. These results highlight a role for this region in cognitive imagery and motor control in the absence of sensory information.

Modulation of the human sensorimotor system by afferent somatosensory input: evidence from experimental pressure stimulation and physiotherapy

Peripheral afferent input is critical for human motor control and motor learning. Both skin and deep muscle mechanoreceptors can affect motor behaviour when stimulated. Whereas some modalities such as vibration have been employed for decades to alter cutaneous and proprioceptive input, both experimentally and therapeutically, the central effects of mechanical pressure stimulation have been studied less frequently. This discrepancy is especially striking when considering the limited knowledge of the neurobiological principles of frequently used physiotherapeutic techniques that utilise peripheral stimulation, such as reflex locomotion therapy. Our review of the available literature pertaining to pressure stimulation focused on transcranial magnetic stimulation (TMS) and neuroimaging studies, including both experimental studies in healthy subjects and clinical trials. Our search revealed a limited number of neuroimaging papers related to peripheral pressure stimulation and no evidence of effects on cortical excitability. In general, the majority of imaging studies agreed on the significant involvement of cortical motor areas during the processing of pressure stimulation. Recent data also point to the specific role of subcortical structures, such as putamen or brainstem reticular formation. A thorough comparison of the published results often demonstrated, however, major inconsistencies which are thought to be due to variable stimulation protocols and statistical power. In conclusion, localised peripheral sustained pressure is a potent stimulus inducing changes in cortical activation within sensory and motor areas. Despite historical evidence for modulation of motor behaviour, no direct link can be established based on available fMRI and electrophysiological data. We highlight the limited amount of research devoted to this stimulus modality, emphasise current knowledge gaps, present recent developments in the field and accentuate evidence awaiting replication or confirmation in future neuroimaging and electrophysiological studies.

Spatiotemporal transformations for gaze control

Sensorimotor transformations require spatiotemporal coordination of signals, that is, through both time and space. For example, the gaze control system employs signals that are time-locked to various sensorimotor events, but the spatial content of these signals is difficult to assess during ordinary gaze shifts. In this review, we describe the various models and methods that have been devised to test this question, and their limitations. We then describe a new method that can (a) simultaneously test between all of these models during natural, head-unrestrained conditions, and (b) track the evolving spatial continuum from target (T) to future gaze coding (G, including errors) through time. We then summarize some applications of this technique, comparing spatiotemporal coding in the primate frontal eye field (FEF) and superior colliculus (SC). The results confirm that these areas preferentially encode eye-centered, effector-independent parameters, and show-for the first time in ordinary gaze shifts-a spatial transformation between visual and motor responses from T to G coding. We introduce a new set of spatial models (T-G continuum) that revealed task-dependent timing of this transformation: progressive during a memory delay between vision and action, and almost immediate without such a delay. We synthesize the results from our studies and supplement it with previous knowledge of anatomy and physiology to propose a conceptual model where cumulative transformation noise is realized as inaccuracies in gaze behavior. We conclude that the spatiotemporal transformation for gaze is both local (observed within and across neurons in a given area) and distributed (with common signals shared across remote but interconnected structures).

A bang-bang control model predicts the triphasic muscles activity during hand reaching

There are numerous ways to reach for an apple hanging from a tree. Yet, our motor system uses a specific muscle activity pattern that features activity bursts and silent periods. We suggest that these bursts are an evidence against the common view that the brain controls the commands to the muscles in a smooth continuous manner. Instead, we propose a model in which a motor plan is transformed into a piecewise-constant control signal that is low-pass filtered and transmitted to the muscles with different muscle-specific delays. We use a Markov chain Monte Carlo (MCMC) method to identify transitions in the state of the muscles following initial activation and show that fitting a bang-bang control model to the kinematics of movement predicts these transitions in the state of the muscles. Such a bang-bang controller suggests that the brain reduces the complexity of the problem of ballistic movements control by sending commands to the muscles at sparse times. Identifying this bang-bang controller can be useful to develop efficient controllers for neuroprostheses and other physical human-robot interaction systems.NEW & NOTEWORTHY While ballistic hand reaching movements are characterized by smooth position and velocity signals, the activity of the muscles exhibits bursts and silent periods. Here, we propose that a model based on bang-bang control provides the link between the abrupt changes in the muscle activity and the smooth reaching trajectory. Using bang-bang control instead of continuous control may simplify the design of prostheses and other physical human-robot interaction systems.

Towards an ontology of cognitive processes and their neural substrates: A structural equation modeling approach

A key challenge in the field of cognitive neuroscience is to identify discriminable cognitive functions, and then map these functions to brain activity. In the current study, we set out to explore the relationships between performance arising from different cognitive tasks thought to tap different domains of cognition, and then to test whether these distinct latent cognitive abilities also are subserved by corresponding “latent” brain substrates. To this end, we tested a large sample of adults under the age of 40 on twelve cognitive tasks as they underwent fMRI scanning. Exploratory factor analysis revealed 4-factor model, dissociating tasks into processes corresponding to episodic memory retrieval, reasoning, speed of processing and vocabulary. An analysis of the topographic covariance patterns of the BOLD-response acquired during each task similarity also converged on four neural networks that corresponded to the 4 latent factors. These results suggest that distinct ontologies of cognition are subserved by corresponding distinct neural networks.

Distributed processing of movement signaling

Basic neurophysiological research with monkeys has shown how neurons in the motor cortex have firing rates tuned to movement direction. This original finding would have been difficult to uncover without the use of a behaving primate paradigm in which subjects grasped a handle and moved purposefully to targets in different directions. Subsequent research, again using behaving primate models, extended these findings to continuous drawing and to arm and hand movements encompassing action across multiple joints. This research also led to robust extraction algorithms in which information from neuronal populations is used to decode movement intent. The ability to decode intended movement provided the foundation for neural prosthetics in which brain-controlled interfaces are used by paralyzed human subjects to control computer cursors or high-performance motorized prosthetic arms and hands. This translation of neurophysiological laboratory findings to therapy is a clear example of why using nonhuman primates for basic research is valuable for advancing treatment of neurological disorders. Recent research emphasizes the distribution of intention signaling through neuronal populations and shows how many movement parameters are encoded simultaneously. In addition to direction and velocity, the arm's impedance has now been found to be encoded as well. The ability to decode motion and force from neural populations will make it possible to extend neural prosthetic paradigms to precise interaction with objects, enabling paralyzed individuals to perform many tasks of daily living.

Hierarchical motor control in mammals and machines

Advances in artificial intelligence are stimulating interest in neuroscience. However, most attention is given to discrete tasks with simple action spaces, such as board games and classic video games. Less discussed in neuroscience are parallel advances in "synthetic motor control". While motor neuroscience has recently focused on optimization of single, simple movements, AI has progressed to the generation of rich, diverse motor behaviors across multiple tasks, at humanoid scale. It is becoming clear that specific, well-motivated hierarchical design elements repeatedly arise when engineering these flexible control systems. We review these core principles of hierarchical control, relate them to hierarchy in the nervous system, and highlight research themes that we anticipate will be critical in solving challenges at this disciplinary intersection.

Functional and Brain Activation Changes Following Specialized Upper-Limb Exercise in Parkinson's Disease

For the management of Parkinson's disease (PD), the concept of forced exercise (FE) has drawn interest. In PD subjects, the FE executed with lower limbs has been shown to lessen symptoms and to promote brain adaptive changes. Our study is aimed to investigate the effect of an upper-limb exercise, conceptually comparable with the FE, in PD. Upper-limb exercise was achieved in a sitting position by using a specially designed device (Angel's Wings^®). Clinical data, computerized dynamic posturography, magnetic resonance imaging (MRI) (resting-state MRI and arterial spin labeling), and neuropsychological tests were used before and after 2 months' exercise training. We found a significant long-lasting improvement in Unified Parkinson Disease Rating Scale (UPDRS)-III and cognitive scales, along with improvement in balance and postural control (better alignment of the gravity center and improvement in weight symmetry and in anticipatory motor strategies). Computerized dynamic posturography pointed out an enhanced central ability to integrate the vestibular signals with afferents from other sensory systems. Neuroimaging analyses after 2 months' exercise training showed, with respect to pretraining condition, many changes. An increase of the cerebral blood flow was evident in the left primary motor cortex (M1), left supplementary motor cortical area, and left cerebellar cortex. The bilateral globus pallidus showed an increased functional connectivity to the right central operculum, right posterior cingulate gyrus, and left sensorimotor cortex. Seed-to-voxel analysis demonstrated a functional connectivity between M1 and the left superior frontal gyrus. Left crus II showed strengthened connections with the left pre-rolandic area, left post-rolandic area, and left supramarginal area. These findings likely reflect compensatory mechanisms to the neuropathological hallmark of PD. Overall, our results show that this upper-limb exercise model, conceptually comparable with the FE already tested in the lower limbs, leads to a global improvement (involving non-exercised limbs) likely consistent with the functional changes observed in the central nervous system.

Dopaminergic modulation of motor network compensatory mechanisms in Parkinson's disease

The dopaminergic system has a unique gating function in the initiation and execution of movements. When the interhemispheric imbalance of dopamine inherent to the healthy brain is disrupted, as in Parkinson's disease (PD), compensatory mechanisms act to stave off behavioral changes. It has been proposed that two such compensatory mechanisms may be (a) a decrease in motor lateralization, observed in drug-naïve PD patients and (b) reduced inhibition - increased facilitation. Seeking to investigate the differential effect of dopamine depletion and subsequent substitution on compensatory mechanisms in non-drug-naïve PD, we studied 10 PD patients and 16 healthy controls, with patients undergoing two test sessions - "ON" and "OFF" medication. Using a simple visually-cued motor response task and fMRI, we investigated cortical motor activation - in terms of laterality, contra- and ipsilateral percent BOLD signal change and effective connectivity in the parametric empirical Bayes framework. We found that decreased motor lateralization persists in non-drug-naïve PD and is concurrent with decreased contralateral activation in the cortical motor network. Normal lateralization is not reinstated by dopamine substitution. In terms of effective connectivity, disease-related changes primarily affect ipsilaterally-lateralized homotopic cortical motor connections, while medication-related changes affect contralaterally-lateralized homotopic connections. Our findings suggest that, in non-drug-naïve PD, decreased lateralization is no longer an adaptive cortical mechanism, but rather the result of maladaptive changes, related to disease progression and long-term dopamine replacement. These findings highlight the need for the development of noninvasive therapies, which would promote the adaptive mechanisms of the PD brain.

Highly structured, partner-sex- and subject-sex-dependent cortical responses during social facial touch

Touch is a fundamental aspect of social, parental and sexual behavior. In contrast to our detailed knowledge about cortical processing of non-social touch, we still know little about how social touch impacts cortical circuits. We investigated neural activity across five frontal, motor and sensory cortical areas in rats engaging in naturalistic social facial touch. Information about social touch and the sex of the interaction partner (a biologically significant feature) is a major determinant of cortical activity. 25.3% of units were modulated during social touch and 8.3% of units displayed ‘sex-touch’ responses (responded differently, depending on the sex of the interaction partner). Single-unit responses were part of a structured, partner-sex- and, in some cases, subject-sex-dependent population response. Spiking neural network simulations indicate that a change in inhibitory drive might underlie these population dynamics. Our observations suggest that socio-sexual characteristics of touch (subject and partner sex) widely modulate cortical activity and need to be investigated with cellular resolution.

Touch is an important sensory modality during social encounters. Here the authors report that during naturalistic social encounters in rats, the cortical activity in widespread areas at the level of single neurons is modulated by sociosexual characteristics such as the subject and partner sex.

More than Just a "Motor": Recent Surprises from the Frontal Cortex

Motor and premotor cortices are crucial for the control of movements. However, we still know little about how these areas contribute to higher-order motor control, such as deciding which movements to make and when to make them. Here we focus on rodent studies and review recent findings, which suggest that-in addition to motor control-neurons in motor cortices play a role in sensory integration, behavioral strategizing, working memory, and decision-making. We suggest that these seemingly disparate functions may subserve an evolutionarily conserved role in sensorimotor cognition and that further study of rodent motor cortices could make a major contribution to our understanding of the evolution and function of the mammalian frontal cortex.