Both Corticospinal and Reticulospinal Tracts Control Force of Contraction

The control of contraction strength is a key part of movement control. In primates, both corticospinal and reticulospinal cells provide input to motoneurons. Corticospinal discharge is known to correlate with force, but there are no previous reports of how reticular formation (RF) activity modulates with different contractions. Here we trained two female macaque monkeys (body weight 5.9-6.9kg) to pull a handle which could be loaded with 0.5-6kg weights, and recorded from identified pyramidal tract neurons (PTNs) in primary motor cortex and RF cells during task performance. Population-averaged firing rate increased monotonically with higher force for the RF, but showed a complex profile with little net modulation for PTNs. This reflected a more heterogeneous profile of rate modulation across the PTN population, leading to cancellation in the average. Linear discriminant analysis (LDA) classified the force based on the time course of rate modulation equally well for PTNs and RF cells. Peak firing rate had significant linear correlation with force for 43/92 (46.7%) PTNs and 21/46 (43.5%) RF cells. For almost all (20/21) RF cells the correlation coefficient was positive; similar numbers of PTNs (22 vs 21) had positive vs negative coefficients. Considering the timing of force representation, similar fractions (PTNs: 61.2%; RF cells: 55.5%) commenced coding before the onset of muscle activity. We conclude that both corticospinal and reticulospinal tracts contribute to control of contraction force; the reticulospinal tract seems to specify an overall signal simply related to force, whereas corticospinal cell activity would be better suited for fine-scale adjustments.SIGNIFICANCE STATEMENTFor the first time, we compare coding of force for corticospinal and reticular formation cells in awake behaving monkeys, over a wide range of contraction strengths likely to come close to maximum voluntary contraction. Both cortical and brainstem systems coded similarly well for force, but whereas reticular formation cells carried a simple uniform signal, corticospinal neurons were more heterogenous. This may reflect a role in gross specification of a coordinated movement, versus more fine-grained adjustments around individual joints

Recent advances in our understanding of the primate corticospinal system [version 1; referees: 2 approved]

The last few years have seen major advances in our understanding of the organisation and function of the corticospinal tract (CST). These have included studies highlighting important species-specific variations in the different functions mediated by the CST. In the primate, the most characteristic feature is direct cortico-motoneuronal (CM) control of muscles, particularly of hand and finger muscles. This system, which is unique to dexterous primates, is probably at its most advanced level in humans. We now know much more about the origin of the CM system within the cortical motor network, and its connectivity within the spinal cord has been quantified. We have learnt much more about how the CM system works in parallel with other spinal circuits receiving input from the CST and how the CST functions alongside other brainstem motor pathways. New work in the mouse has provided fascinating insights into the contribution of the CM system to dexterity. Finally, accumulating evidence for the involvement of CM projections in motor neuron disease has highlighted the importance of advances in basic neuroscience for our understanding and possible treatment of a devastating neurological disease

Brainstem Circuits Controlling Action Diversification

Neuronal circuits that regulate movement are distributed throughout the nervous system. The brainstem is an important interface between upper motor centers involved in action planning and circuits in the spinal cord ultimately leading to execution of body movements. Here we focus on recent work using genetic and viral entry points to reveal the identity of functionally dedicated and frequently spatially intermingled brainstem populations essential for action diversification, a general principle conserved throughout evolution. Brainstem circuits with distinct organization and function control skilled forelimb behavior, orofacial movements, and locomotion. They convey regulatory parameters to motor output structures and collaborate in the construction of complex natural motor behaviors. Functionally tuned brainstem neurons for different actions serve as important integrators of synaptic inputs from upstream centers, including the basal ganglia and cortex, to regulate and modulate behavioral function in different contexts

Integrating Cortical Sensorimotor Representations Across Spatial Scales and Task Contexts

Our understanding of how brains function is stratified between two very different scales: mesoscale (what function a given cortical area performs), measured with tools like fMRI; and microscale (what a given neuron does), measured with implanted microelectrodes. While extensive research has been done to characterize brain activity at both of these spatial scales, describing relationships between these two domains has proven difficult. Identifying ways to integrate findings between these scales is valuable for both research and clinical applications, but is particularly important for intracortical brain-computer interfaces (BCIs), which aim to restore motor function after paralysis or amputation. In humans, the brain is much larger than the available microelectrode arrays, so determining where to place the arrays is a critical aspect of ensuring optimal performance. BCIs preferentially target primary motor and somatosensory cortices, due to their direct relationship to motor control and critical role in skilled and dexterous movements. However, despite these areas displaying a relatively ordered spatial organization, it is difficult to accurately predict the behavior of neurons recorded from a given area for several reasons. Mesoscale activity is overlapping, with activity relating to multiple different movements observed in a single area. Additionally, neurons have flexible behavior, displaying different “tuning” to similar behavior under different contexts. Here I present my research integrating neuroimaging-based cortical mapping with directly-recorded neural activity in human sensorimotor cortex. First, I examine how the large-scale organization of sensorimotor representations measured with fMRI is affected by contextual sensory information. I then examine how spatially separate neural populations recorded with intracortical microelectrode arrays encode different types of movement. Finally, I examine whether how population encoding changes to reflect contextual sensory information using the same task as in the fMRI study. Together, these results provide a foundation for reconciling neural activity across spatial scales and task contexts, and will inform the design and placement of more capable BCI systems

Neurophysiological mechanisms of sensorimotor recovery from stroke

Ischemic stroke often results in the devastating loss of nervous tissue in the cerebral cortex, leading to profound motor deficits when motor territory is lost, and ultimately resulting in a substantial reduction in quality of life for the stroke survivor. The International Classification of Functioning, Disability and Health (ICF) was developed in 2002 by the World Health Organization (WHO) and provides a framework for clinically defining impairment after stroke. While the reduction of burdens due to neurological disease is stated as a mission objective of the National Institute of Neurological Disorders and Stroke (NINDS), recent clinical trials have been unsuccessful in translating preclinical research breakthroughs into actionable therapeutic treatment strategies with meaningful progress towards this goal. This means that research expanding another NINDS mission is now more important than ever: improving fundamental knowledge about the brain and nervous system in order to illuminate the way forward. Past work in the monkey model of ischemic stroke has suggested there may be a relationship between motor improvements after injury and the ability of the animal to reintegrate sensory and motor information during behavior. This relationship may be subserved by sprouting cortical axonal processes that originate in the spared premotor cortex after motor cortical injury in squirrel monkeys. The axons were observed to grow for relatively long distances (millimeters), significantly changing direction so that it appears that they specifically navigate around the injury site and reorient toward the spared sensory cortex. Critically, it remains unknown whether such processes ever form functional synapses, and if they do, whether such synapses perform meaningful calculations or other functions during behavior. The intent of this dissertation was to study this phenomenon in both intact rats and rats with a focal ischemia in primary motor cortex (M1) contralateral to the preferred forelimb during a pellet retrieval task. As this proved to be a challenging and resource-intensive endeavor, a primary objective of the dissertation became to provide the tools to facilitate such a project to begin with. This includes the creation of software, hardware, and novel training and behavioral paradigms for the rat model. At the same time, analysis of previous experimental data suggested that plasticity in the neural activity of the bilateral motor cortices of rats performing pellet retrievals after focal M1 ischemia may exhibit its most salient changes with respect to functional changes in behavior via mechanisms that were different than initially hypothesized. Specifically, a major finding of this dissertation is the finding that evidence of plasticity in the unit activity of bilateral motor cortical areas of the reaching rat is much stronger at the level of population features. These features exhibit changes in dynamics that suggest a shift in network fixed points, which may relate to the stability of filtering performed during behavior. It is therefore predicted that in order to define recovery by comparison to restitution, a specific type of fixed point dynamics must be present in the cortical population state. A final suggestion is that the stability or presence of these dynamics is related to the reintegration of sensory information to the cortex, which may relate to the positive impact of physical therapy during rehabilitation in the postacute window. Although many more rats will be needed to state any of these findings as a definitive fact, this line of inquiry appears to be productive for identifying targets related to sensorimotor integration which may enhance the efficacy of future therapeutic strategies

Neural State Changes in Primate Motor Cortex During Arm Movements with Distinct Control Requirements

The primary motor cortex (M1) is an important structure of the motor system that contributes to many aspects of movement. Firing patterns of M1 neurons can be surprisingly complex, and there is substantial interest in understanding these patterns and their relation to behavior. Here, we characterize the temporal structure of M1 activity during reaching in several ways. First, we show that single neurons encode movement information in a series of discrete segments. Information is stably encoded during each brief segment, and the firing patterns of most neurons transition between segments at similar times during movement. This pattern may therefore reflect transitions between different neural “states.” Next, we establish that the sequence of states observed during behavior is related to a sequence of distinct drivers, including visuospatial information and visual feedback from a movement. If no feedback is provided, neurons may produce a truncated response sequence. Last, we link the temporal structure of firing patterns to the structure of reaches and demonstrate that the classical two-component model of reaching is reflected in M1 activity. Our findings may help establish a useful framework for interpreting seemingly complex neural activity during behavior

A ventral root interface for neuroprosthetic control of locomotion

Recent advances in state of the art prosthetic limbs have demonstrated unprecedented levels of dexterity and control within the constraints of an anthropomorphic structure. Unfortunately, patients still struggle to naturally control and rely upon relatively simpler lower limb devices with just one or two joints. For patients living with the loss of a limb, functional motor circuitry is still intact through the spinal cord and into the peripheral nerves, transforming higher level control signals into discrete muscle activations. An interface at the spinal roots can take advantage of this final output of the nervous system to control the device, completely avoiding some of the context sensitivity issues in higher level structures. Further, the anatomical separation of motor and sensory signals into distinct ventral and dorsal components and the relative stability of the spinal column provide a path towards a targeted neuroprosthetic interface. This dissertation develops and validates methods to target motor axons in the ventral roots with multielectrode arrays. We demonstrate the ability to chronically record well-isolated signals from diverse populations of motor axons and develop techniques to identify the muscles they innervate. We subsequently use these motor signals to estimate kinematics during locomotion as accurately as estimations from simultaneously recorded muscle activity in the intact limb, demonstrating that a ventral root prosthetic interface is possible for patients living with loss of limb

Putting the “Sensory” Into Sensorimotor Control: The Role of Sensorimotor Integration in Goal-Directed Hand Movements After Stroke

Integration of sensory and motor information is one-step, among others, that underlies the successful production of goal-directed hand movements necessary for interacting with our environment. Disruption of sensorimotor integration is prevalent in many neurologic disorders, including stroke. In most stroke survivors, persistent paresis of the hand reduces function and overall quality of life. Current rehabilitative methods are based on neuroplastic principles to promote motor learning that focuses on regaining motor function lost due to paresis, but the sensory contributions to motor control and learning are often overlooked and currently understudied. There is a need to evaluate and understand the contribution of both sensory and motor function in the rehabilitation of skilled hand movements after stroke. Here, we will highlight the importance of integration of sensory and motor information to produce skilled hand movements in healthy individuals and individuals after stroke. We will then discuss how compromised sensorimotor integration influences relearning of skilled hand movements after stroke. Finally, we will propose an approach to target sensorimotor integration through manipulation of sensory input and motor output that may have therapeutic implications

Optimal anticipatory control as a theory of motor preparation

Supported by a decade of primate electrophysiological experiments, the prevailing theory of neural motor control holds that movement generation is accomplished by a preparatory process that progressively steers the state of the motor cortex into a movement-specific optimal subspace prior to movement onset. The state of the cortex then evolves from these optimal subspaces, producing patterns of neural activity that serve as control inputs to the musculature. This theory, however, does not address the following questions: what characterizes the optimal subspace and what are the neural mechanisms that underlie the preparatory process? We address these questions with a circuit model of movement preparation and control. Specifically, we propose that preparation can be achieved by optimal feedback control (OFC) of the cortical state via a thalamo-cortical loop. Under OFC, the state of the cortex is selectively controlled along state-space directions that have future motor consequences, and not in other inconsequential ones. We show that OFC enables fast movement preparation and explains the observed orthogonality between preparatory and movement-related monkey motor cortex activity. This illustrates the importance of constraining new theories of neural function with experimental data. However, as recording technologies continue to improve, a key challenge is to extract meaningful insights from increasingly large-scale neural recordings. Latent variable models (LVMs) are powerful tools for addressing this challenge due to their ability to identify the low-dimensional latent variables that best explain these large data sets. One shortcoming of most LVMs, however, is that they assume a Euclidean latent space, while many kinematic variables, such as head rotations and the configuration of an arm, are naturally described by variables that live on non-Euclidean latent spaces (e.g., SO(3) and tori). To address this shortcoming, we propose the Manifold Gaussian Process Latent Variable Model, a method for simultaneously inferring nonparametric tuning curves and latent variables on non-Euclidean latent spaces. We show that our method is able to correctly infer the latent ring topology of the fly and mouse head direction circuits.This work was supported by a Trinity-Henry Barlow scholarship and a scholarship from the Ministry of Education, ROC Taiwan

Encoding of Object Presence and Manipulation Affordances in the Frontoparietal Grasp Network

The ability to grasp and manipulate objects is a fundamental human capacity. Loss of this function due to injury or disease can result in the inability to independently perform tasks of daily living. Brain computer interfaces (BCIs), which decode neural activity to control assistive devices, represent a new class of potential therapies to restore arm and hand function. Recent efforts to implement BCI control of a robotic hand for grasping have been hindered by unexpected neural modulations in primary motor cortex (M1) related to the contextual factor of whether movements were made with or without an object present. We designed and carried out three experiments in healthy rhesus macaque monkeys to characterize the influence of various object-related contextual factors on movement features (MFs — kinematics and muscle activity of the arm and hand) and on neural activity in three grasp-related brain areas: M1, ventral premotor cortex (PMV) and anterior intraparietal area (AIP). A novel method was devised to implant intracortical microelectrode arrays in PMV and AIP for these experiments. In Experiment 1, monkeys performed similar reaching movements with or without an object present. In Experiment 2, monkeys performed similar grasps on a set of objects with different grip affordances (objects could be grasped in multiple ways). In Experiment 3, monkeys performed similar grasps on two objects with different use affordances (one was stationary and one could be lifted). All object-related contextual factors were found to evoke small but significant differences in MFs despite task requirements remaining constant across contexts. These context-dependent behavioral differences were accompanied by proportionately larger neural differences in all three brain areas. The presence or absence of an object resulted in changes in neuronal firing rates that could not be accounted for by linear encoding of MFs. This object presence signal was found to interact with MF encoding in M1 in a way that was detrimental for BCI-style MF decoding. Object grip affordance differences resulted in similar but smaller neural modulations that did not impact MF decoding. Neural modulations related to object use affordance were prominent only in PMV