Motor directional tuning across brain areas: directional resonance and the role of inhibition for directional accuracy

Functional balance at rest of hemispheric homologs assessed via normalized compression distance

Introduction

The formation and functioning of neural networks hinge critically on the balance between structurally homologous areas in the hemispheres. This balance, reflecting their physiological relationship, is fundamental for learning processes. In our study, we explore this functional homology in the resting state, employing a complexity measure that accounts for the temporal patterns in neurodynamics.

Methods

We used Normalized Compression Distance (NCD) to assess the similarity over time, neurodynamics, of the somatosensory areas associated with hand perception (S1). This assessment was conducted using magnetoencephalography (MEG) in conjunction with Functional Source Separation (FSS). Our primary hypothesis posited that neurodynamic similarity would be more pronounced within individual subjects than across different individuals. Additionally, we investigated whether this similarity is influenced by hemisphere or age at a population level.

Results

Our findings validate the hypothesis, indicating that NCD is a robust tool for capturing balanced functional homology between hemispheric regions. Notably, we observed a higher degree of neurodynamic similarity in the population within the left hemisphere compared to the right. Also, we found that intra-subject functional homology displayed greater variability in older individuals than in younger ones.

Discussion

Our approach could be instrumental in investigating chronic neurological conditions marked by imbalances in brain activity, such as depression, addiction, fatigue, and epilepsy. It holds potential for aiding in the development of new therapeutic strategies tailored to these complex conditions, though further research is needed to fully realize this potential.

Localizing EEG Recordings Associated With a Balance Threat During Unexpected Postural Translations in Young and Elderly Adults

Balance perturbations are accompanied by global cortical activation that increases in magnitude when postural perturbations are unexpected, potentially due to the addition of a startle response. A specific site for best recording the response to unexpected destabilization has not been identified. We hypothesize that a single sensor located near to subcortical brainstem mechanisms could serve as a marker for the response to unpredictable postural events. Twenty healthy young (20.8 ± 2.9 yrs) and 20 healthy elder (71.7 ± 4.2 yrs) adults stood upright on a dynamic platform with eyes open. Platform translations (20 cm at 100 cm/s) were delivered in the posterior (29 trials) and anterior (5 catch trials) directions. Active EEG electrodes were located at Fz and Cz and bilaterally on the mastoids. Following platform acceleration onset, 300 ms of EEG activity from each trial was detrended, baseline-corrected, and normalized to the first trial. Average Root-Mean-Square (RMS) values across "unpredictable" and "predictable" events were computed for each channel. EEG RMS responses were significantly greater with unpredictable than predictable disturbances: Cz ( [Formula: see text]), Fz ( [Formula: see text]), and mastoid ( [Formula: see text]). EEG RMS responses were also significantly greater in elderly than young adults at Cz ( [Formula: see text]) and mastoid ( [Formula: see text]). A significant effect of sex in the responses at the mastoid sensors ( [Formula: see text]) revealed that elderly male adults were principally responsible for the age effect. These results confirm that the cortical activity resulting from an unexpected postural disturbance could be portrayed by a single sensor located over the mastoid bone in both young and elderly adults.

Peripersonal encoding of forelimb proprioception in the mouse somatosensory cortex

Conscious perception of limb movements depends on proprioceptive neural responses in the somatosensory cortex. In contrast to tactile sensations, proprioceptive cortical coding is barely studied in the mammalian brain and practically non-existent in rodent research. To understand the cortical representation of this important sensory modality we developed a passive forelimb displacement paradigm in behaving mice and also trained them to perceptually discriminate where their limb is moved in space. We delineated the rodent proprioceptive cortex with wide-field calcium imaging and optogenetic silencing experiments during behavior. Our results reveal that proprioception is represented in both sensory and motor cortical areas. In addition, behavioral measurements and responses of layer 2/3 neurons imaged with two-photon microscopy reveal that passive limb movements are both perceived and encoded in the mouse cortex as a spatial direction vector that interfaces the limb with the body's peripersonal space.

On the Homology of the Dominant and Non-Dominant Corticospinal Tracts: A Novel Neurophysiological Assessment

OBJECTIVES

The homology of hemispheric cortical areas plays a crucial role in brain functionality. Here, we extend this concept to the homology of the dominant and non-dominant hemi-bodies, investigating the relationship of the two corticospinal tracts (CSTs). The evoked responses provide an estimate of the number of in-phase recruitments via their amplitude as a suitable indicator of the neuronal projections' integrity. An innovative concept derived from experience in the somatosensory system is that their morphology reflects the recruitment pattern of the whole circuit.

METHODS

CST homology was assessed via the Fréchet distance between the morphologies of motor-evoked potentials (MEPs) using a transcranial magnetic stimulation (TMS) in the homologous left- and right-hand first dorsal interosseous muscles of 40 healthy volunteers (HVs). We tested the working hypothesis that the inter-side Fréchet distance was higher than the two intra-side distances.

RESULTS

In addition to a clear confirmation of the working hypothesis (p < 0.0001 for both hemi-bodies) verified in all single subjects, we observed that the intra-side Fréchet distance was higher for the dominant than the non-dominant one. Interhemispheric morphology similarity increased with right-handedness prevalence (p = 0.004).

CONCLUSIONS

The newly introduced measure of circuit recruitment patterning represents a potential benchmark for the evaluation of inter-lateral mechanisms expressing the relationship between homologous hemilateral structures subtending learning and suggests that variability in recruitment patterning physiologically increases in circuits expressing greater functionality.

Effective Intracerebral Connectivity in Acute Stroke: A TMS-EEG Study

Stroke is a major cause of disability because of its motor and cognitive sequelae even when the acute phase of stabilization of vital parameters is overcome. The most important improvements occur in the first 8-12 weeks after stroke, indicating that it is crucial to improve our understanding of the dynamics of phenomena occurring in this time window to prospectively target rehabilitation procedures from the earliest stages after the event. Here, we studied the intracortical excitability properties of delivering transcranial magnetic stimulation (TMS) to the primary motor cortex (M1) of left and right hemispheres in 17 stroke patients who suffered a mono-lateral left hemispheric stroke, excluding pure cortical damage. All patients were studied within 10 days of symptom onset. TMS-evoked potentials (TEPs) were collected via a TMS-compatible electroencephalogram system (TMS-EEG) concurrently with motor-evoked responses (MEPs) induced in the contralateral first dorsal interosseous muscle. Comparison with age-matched healthy volunteers was made by collecting the same bilateral-stimulation data in nine healthy volunteers as controls. Excitability in the acute phase revealed relevant changes in the relationship between left lesioned and contralesionally right hemispheric homologous areas both for TEPs and MEPs. While the paretic hand displayed reduced MEPs compared to the non-paretic hand and to healthy volunteers, TEPs revealed an overexcitable lesioned hemisphere with respect to both healthy volunteers and the contra-lesion side. Our quantitative results advance the understanding of the impairment of intracortical inhibitory networks. The neuronal dysfunction most probably changes the excitatory/inhibitory on-center off-surround organization that supports already acquired learning and reorganization phenomena that support recovery from stroke sequelae.

The dynamic shaping of local cortical circuitry by sex and age, and its relation to Pattern Comparison Processing Speed

Previous resting-state functional magnetic resonance imaging (fMRI) studies have shown that the strength of local neural interactions decreases with distance. Here we extend that line of research to evaluate effects of sex and age on local cortical circuitry in 6 cortical areas (superior frontal, precentral, postcentral, superior parietal, inferior parietal, lateral occipital) using data acquired from 1,054 healthy young adults who participated in the Human Connectome Project. We confirmed previous findings that the strength of zero-lag correlations between prewhitened, resting-state, blood level oxygenation-dependent (BOLD) fMRI time series decreased with distance locally, and documented that the rate of decrease with distance ("spatial steepness") (a) was progressively lower from anterior to posterior areas, (b) was greater in women, especially in anterior areas, (c) increased with age, particularly for women, (d) was significantly correlated with percent inhibition, and (e) was positively and highly significantly correlated with pattern comparison processing speed (PCPS). A hierarchical tree clustering analysis of this dependence of PCPS on spatial steepness revealed a differential organization in processing that information between the two hemispheres, namely a more independent vs. a more integrative processing in the left and right hemispheres, respectively. These findings document sex and age differences in dynamic local cortical interactions, and provide evidence that spatial sharpening of these interactions may underlie cognitive processing speed differently organized in the two hemispheres.

Anterograde interference emerges along a gradient as a function of task similarity: A behavioural study

Anterograde interference emerges when two opposite (B → A) or identical tasks (A → A) are learned in close temporal succession, suggesting that interference cannot be fully accounted for by competing memories. Informed by neurobiological evidence, this work tested the hypothesis that interference depends upon the degree of overlap between the neural networks involved in the learning of two tasks. In a fully within‐subject and counterbalanced design, participants (n = 24) took part in two learning sessions where the putative overlap between learning‐specific neural networks was behaviourally manipulated across four conditions by modifying reach direction and the effector used during gradual visuomotor adaptation. The results showed that anterograde interference emerged regardless of memory competition—that is, to a similar extent in the B → A and A → A conditions—and along a gradient as a function of the tasks' similarity. Specifically, learning under similar reaching conditions generated more anterograde interference than learning under dissimilar reaching conditions, suggesting that putatively overlapping neural networks are required to generate interference. Overall, these results indicate that competing memories are not the sole contributor to anterograde interference and suggest that overlapping neural networks between two learning sessions are required to trigger interference. One discussed possibility is that initial learning modifies the properties of its neural networks to constrain further plasticity induction and learning capabilities, therefore causing anterograde interference in a network‐dependent manner. One implication is that learning‐specific neural networks must be maximally dissociated to minimize the interfering influences of previous learning on subsequent learning.

A Revised Computational Neuroanatomy for Motor Control

We discuss a new framework for understanding the structure of motor control. Our approach integrates existing models of motor control with the reality of hierarchical cortical processing and the parallel segregated loops that characterize cortical-subcortical connections. We also incorporate the recent claim that cortex functions via predictive representation and optimal information utilization. Our framework assumes that each cortical area engaged in motor control generates a predictive model of a different aspect of motor behavior. In maintaining these predictive models, each area interacts with a different part of the cerebellum and BG. These subcortical areas are thus engaged in domain-appropriate system identification and optimization. This refocuses the question of division of function among different cortical areas. What are the different aspects of motor behavior that are predictively modeled? We suggest that one fundamental division is between modeling of task and body whereas another is the model of state and action. Thus, we propose that the posterior parietal cortex, somatosensory cortex, premotor cortex, and motor cortex represent task state, body state, task action, and body action, respectively. In the second part of this review, we demonstrate how this division of labor can better account for many recent findings of movement encoding, especially in the premotor and posterior parietal cortices.

Nonlinear Effects of Dopamine D1 Receptor Activation on Visuomotor Coordination Task Performance

Dopamine plays an important role in the modulation of neuroplasticity, which serves as the physiological basis of cognition. The physiological effects of dopamine depend on receptor subtypes, and the D1 receptor is critically involved in learning and memory formation. Evidence from both animal and human studies shows a dose-dependent impact of D1 activity on performance. However, the direct association between physiology and behavior in humans remains unclear. In this study, four groups of healthy participants were recruited, and each group received placebo or medication inducing a low, medium, or high amount of D1 activation via the combination of levodopa and a D2 antagonist. After medication, fMRI was conducted during a visuomotor learning task. The behavioral results revealed an inverted U-shaped effect of D1 activation on task performance, where medium-dose D1 activation led to superior learning effects, as compared to placebo as well as low- and high-dose groups. A respective dose-dependent D1 modulation was also observed for cortical activity revealed by fMRI. Further analysis demonstrated a positive correlation between task performance and cortical activation at the left primary motor cortex. Our results indicate a nonlinear curve of D1 modulation on motor learning in humans and the respective physiological correlates in corresponding brain areas.

Human motor fatigability as evoked by repetitive movements results from a gradual breakdown of surround inhibition

Motor fatigability emerges when demanding tasks are executed over an extended period of time. Here, we used repetitive low-force movements that cause a gradual reduction in movement speed (or 'motor slowing') to study the central component of fatigability in healthy adults. We show that motor slowing is associated with a gradual increase of net excitability in the motor network and, specifically, in primary motor cortex (M1), which results from overall disinhibition. Importantly, we link performance decrements to a breakdown of surround inhibition in M1, which is associated with high coactivation of antagonistic muscle groups. This is consistent with the model that a loss of inhibitory control might broaden the tuning of population vectors such that movement patterns become more variable, ill-timed and effortful. We propose that the release of inhibition in M1 is an important mechanism underpinning motor fatigability and, potentially, also pathological fatigue as frequently observed in patients with brain disorders.

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.

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.

Three-Dimensional Representation of Motor Space in the Mouse Superior Colliculus

From the act of exploring an environment to that of grasping a cup of tea, animals must put in register their motor acts with their surrounding space. In the motor domain, this is likely to be defined by a register of three-dimensional (3D) displacement vectors, whose recruitment allows motion in the direction of a target. One such spatially targeted action is seen in the head reorientation behavior of mice, yet the neural mechanisms underlying these 3D behaviors remain unknown. Here, by developing a head-mounted inertial sensor for studying 3D head rotations and combining it with electrophysiological recordings, we show that neurons in the mouse superior colliculus are either individually or conjunctively tuned to the three Eulerian components of head rotation. The average displacement vectors associated with motor-tuned colliculus neurons remain stable over time and are unaffected by changes in firing rate or the duration of spike trains. Finally, we show that the motor tuning of collicular neurons is largely independent from visual or landmark cues. By describing the 3D nature of motor tuning in the superior colliculus, we contribute to long-standing debate on the dimensionality of collicular motor decoding; furthermore, by providing an experimental paradigm for the study of the metric of motor tuning in mice, this study also paves the way to the genetic dissection of the circuits underlying spatially targeted motion.

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Development of inertial sensor system for monitoring 3D head movements in real time

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Neurons in the superior colliculus code for the full dimensionality of head rotations

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Firing rate correlates with velocity, but not head displacement angle

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The spatial tuning of collicular units is largely independent of visual or landmark cues

What Is the Evidence for Inter-laminar Integration in a Prefrontal Cortical Minicolumn?

The objective of this perspective article is to examine columnar inter-laminar integration during the executive control of behavior. The integration hypothesis posits that perceptual and behavioral signals are integrated within the prefrontal cortical inter-laminar microcircuits. Inter-laminar minicolumnar activity previously recorded from the dorsolateral prefrontal cortex (dlPFC) of nonhuman primates, trained in a visual delay match-to-sample (DMS) task, was re-assessed from an integrative perspective. Biomorphic multielectrode arrays (MEAs) played a unique role in the in vivo recording of columnar cell firing in the dlPFC layers 2/3 and 5/6. Several integrative aspects stem from these experiments: 1. Functional integration of perceptual and behavioral signals across cortical layers during executive control. The integrative effect of dlPFC minicolumns was shown by: (i) increased correlated firing on correct vs. error trials; (ii) decreased correlated firing when the number of non-matching images increased; and (iii) similar spatial firing preference across cortical-striatal cells during spatial-trials, and less on object-trials. 2. Causal relations to integration of cognitive signals by the minicolumnar turbo-engines. The inter-laminar integration between the perceptual and executive circuits was facilitated by stimulating the infra-granular layers with firing patterns obtained from supra-granular layers that enhanced spatial preference of percent correct performance on spatial trials. 3. Integration across hierarchical levels of the brain. The integration of intention signals (visual spatial, direction) with movement preparation (timing, velocity) in striatum and with the motor command and posture in midbrain is also discussed. These findings provide evidence for inter-laminar integration of executive control signals within brain's prefrontal cortical microcircuits.

Cortical neurons multiplex reward-related signals along with sensory and motor information

Rewards are known to influence neural activity associated with both motor preparation and execution. This influence can be exerted directly upon the primary motor (M1) and somatosensory (S1) cortical areas via the projections from reward-sensitive dopaminergic neurons of the midbrain ventral tegmental areas. However, the neurophysiological manifestation of reward-related signals in M1 and S1 are not well understood. Particularly, it is unclear how the neurons in these cortical areas multiplex their traditional functions related to the control of spatial and temporal characteristics of movements with the representation of rewards. To clarify this issue, we trained rhesus monkeys to perform a center-out task in which arm movement direction, reward timing, and magnitude were manipulated independently. Activity of several hundred cortical neurons was simultaneously recorded using chronically implanted microelectrode arrays. Many neurons (9-27%) in both M1 and S1 exhibited activity related to reward anticipation. Additionally, neurons in these areas responded to a mismatch between the reward amount given to the monkeys and the amount they expected: A lower-than-expected reward caused a transient increase in firing rate in 60-80% of the total neuronal sample, whereas a larger-than-expected reward resulted in a decreased firing rate in 20-35% of the neurons. Moreover, responses of M1 and S1 neurons to reward omission depended on the direction of movements that led to those rewards. These observations suggest that sensorimotor cortical neurons corepresent rewards and movement-related activity, presumably to enable reward-based learning.

Cortical circuits and modules in movement generation: experiments and theories

Here we review recent studies of the cortical circuits subserving the control of posture and movement. This topic is addressed from neurophysiological and evolutionary perspectives describing recent advancements achieved through experimental studies in humans and non-human primates. We also describe current debates and controversies concerning motor mapping within the motor cortex and the different computational approaches aimed at resolving the mystery around motor representations and computations. In recent years there is growing interest in the possibly modular organization of motor representations and dynamical processes and the potential of such studies to provide new clues into motor information processing. Hence this review focuses on motor modularity, highlighting the new research directions inspired by empirical findings and theoretical models developed within the last several years.

Advancing brain-machine interfaces: moving beyond linear state space models

Advances in recent years have dramatically improved output control by Brain-Machine Interfaces (BMIs). Such devices nevertheless remain robotic and limited in their movements compared to normal human motor performance. Most current BMIs rely on transforming recorded neural activity to a linear state space composed of a set number of fixed degrees of freedom. Here we consider a variety of ways in which BMI design might be advanced further by applying non-linear dynamics observed in normal motor behavior. We consider (i) the dynamic range and precision of natural movements, (ii) differences between cortical activity and actual body movement, (iii) kinematic and muscular synergies, and (iv) the implications of large neuronal populations. We advance the hypothesis that a given population of recorded neurons may transmit more useful information than can be captured by a single, linear model across all movement phases and contexts. We argue that incorporating these various non-linear characteristics will be an important next step in advancing BMIs to more closely match natural motor performance.

Distinct influence of hand posture on cortical activity during human grasping

We recently showed that subcortical circuits contribute to control the gain of motor cortical inputs to spinal motoneurons during precision grip of a small object. Here, we examine whether the involvement of the motor cortex could be revealed by grasping with different hand postures. Using noninvasive cortical, cervicomedullary, and peripheral nerve stimulation we examined in humans motor-evoked potentials (MEPs) and the activity in intracortical circuits (suppression of voluntary electromyography) and spinal motoneurons (F-waves) in intrinsic hand muscles when grasping a 6 mm cylinder with the index finger and thumb while the hand was held in the neutral position or during full pronation and supination. We demonstrate that the size of cortically evoked MEPs in the first dorsal interosseous, but not in the abductor pollicis brevis and abductor digit minimi muscles, was reduced to a similar extent during grasping with the hand pronated or supinated compared with the neutral position. Notably, the suppression of MEPs was present from the MEP onset, suggesting that indirect corticospinal pathways were less likely to be involved than direct connections. There was less intracortical inhibition targeting the first dorsal interosseous during hand pronation and supination compared with neutral and this negatively correlated with changes in MEP size. In contrast, cervicomedullary MEPs and F-waves remained unchanged across conditions, as did MEPs evoked during unopposed weak flexion of the index finger. Our findings reveal a distinct influence of the posture of the hand on the activity of cortical pathways controlling different hand muscles during grasping.

Prefrontal cortical recordings with biomorphic MEAs reveal complex columnar-laminar microcircuits for BCI/BMI implementation

The mammalian prefrontal cortex known as the seat of high brain functions uses a six layer distribution of minicolumnar neurons to coordinate the integration of sensory information and the selection of relevant signals for goal driven behavior. To reveal the complex functionality of these columnar microcircuits we employed simultaneous recordings with several configurations of biomorphic microelectrode arrays (MEAs) within cortical layers in adjacent minicolumns, in four nohuman primates (NHPs) performing a delayed match-to-sample (DMS) visual discrimination task. We examined: (1) the functionality of inter-laminar, and inter-columnar interactions between pairs of cells in the same or different minicolumns by use of normalized cross-correlation histograms (CCH), (2) the modulation of glutamate concentration in layer 2/3, and (3) the potential interactions within these microcircuits. The results demonstrate that neurons in both infra-granular and supra-granular layers interact through inter-laminar loops, as well as through intra-laminar to produce behavioral response signals. These results provide new insights into the manner in which prefrontal cortical microcircuitry integrates sensory stimuli used to provide behaviorally relevant signals that may be implemented in brain computer/machine interfaces (BCI/BMIs) during performance of the task.

Coding of movements in the motor cortex

The issue of coding of movement in the motor cortex has recently acquired special significance due to its fundamental importance in neuroprosthetic applications. The challenge of controlling a prosthetic arm by processed motor cortical activity has opened a new era of research in applied medicine but has also provided an 'acid test' for hypotheses regarding coding of movement in the motor cortex. The successful decoding of movement information from the activity of motor cortical cells using their directional tuning and population coding has propelled successful neuroprosthetic applications and, at the same time, asserted the utility of those early discoveries, dating back to the early 1980s.

Nanostructures: a platform for brain repair and augmentation

Nanoscale structures have been at the core of research efforts dealing with integration of nanotechnology into novel electronic devices for the last decade. Because the size of nanomaterials is of the same order of magnitude as biomolecules, these materials are valuable tools for nanoscale manipulation in a broad range of neurobiological systems. For instance, the unique electrical and optical properties of nanowires, nanotubes, and nanocables with vertical orientation, assembled in nanoscale arrays, have been used in many device applications such as sensors that hold the potential to augment brain functions. However, the challenge in creating nanowires/nanotubes or nanocables array-based sensors lies in making individual electrical connections fitting both the features of the brain and of the nanostructures. This review discusses two of the most important applications of nanostructures in neuroscience. First, the current approaches to create nanowires and nanocable structures are reviewed to critically evaluate their potential for developing unique nanostructure based sensors to improve recording and device performance to reduce noise and the detrimental effect of the interface on the tissue. Second, the implementation of nanomaterials in neurobiological and medical applications will be considered from the brain augmentation perspective. Novel applications for diagnosis and treatment of brain diseases such as multiple sclerosis, meningitis, stroke, epilepsy, Alzheimer's disease, schizophrenia, and autism will be considered. Because the blood brain barrier (BBB) has a defensive mechanism in preventing nanomaterials arrival to the brain, various strategies to help them to pass through the BBB will be discussed. Finally, the implementation of nanomaterials in neurobiological applications is addressed from the brain repair/augmentation perspective. These nanostructures at the interface between nanotechnology and neuroscience will play a pivotal role not only in addressing the multitude of brain disorders but also to repair or augment brain functions.

Cell directional spread determines accuracy, precision, and length of the neuronal population vector

The neuronal population vector (NPV) for movement direction is the sum of weighted neuronal directional contributions. Based on theoretical considerations, we proposed recently that the sharpness of tuning will impact the directional precision, accuracy, and length of the NPV, such that sharper tuning will yield NPV with higher precision, higher accuracy, and shorter length (Mahan and Georgopoulos in Front Neural Circuits 7:92, 2013). Furthermore, we proposed that controlling the inhibitory drive in a local network could be the mechanism by which the sharpness of directional tuning would be varied, resulting in a continuous specification and control of movement's directional precision, accuracy, and speed (Mahan and Georgopoulos in Front Neural Circuits 7:92, 2013, Fig. 5). As a first step in testing this idea, here we analyzed data from 899 cells recorded in the motor cortex during performance of a center → out task. There were two major findings. First, directional selectivity varied with cell activity, such that it was higher in cells with lower mean discharge rates. And second, NPVs calculated from subsets of cells with higher directional selectivity (and, correspondingly, lower mean discharge rates) were more accurate (i.e., closer to the movement), precise (i.e., less variable), and shorter (i.e., slower; Schwartz in Science 265:540-542, 1994). These findings confirm our predictions above made from modeling (Mahan and Georgopoulos in Front Neural Circuits 7:92, 2013) and provide a simple mechanism by which desired attributes of the directional motor command can be implemented. We hypothesize that the inhibitory drive in a local network is controlled directly and independently of recurrent collaterals or common excitatory inputs to other cells. This could be achieved by a private excitation/inhibition of key inhibitory interneurons in a way similar to that in operation for Renshaw cells in the spinal cord. The presence of such a private line of inhibitory control remains to be investigated.