Cerebral cortical mechanisms of reaching movements

Initial and corrective submovement encoding differences within primary motor cortex during precision reaching

Precision reaching often requires corrective submovements to obtain the desired goal. Most studies of reaching have focused on single initial movements, and implied the cortical encoding model was the same for all submovements. However, corrective submovements may show different encoding patterns from the initial submovement with distinct patterns of activation across the population. Two rhesus macaques performed a precision center-out-task with small targets. Neural activity from single units in the primary motor cortex and associated behavioral data were recorded to evaluate movement characteristics. Neural population data and individual neuronal firing rates identified with a peak finding algorithm to identify peaks in hand speed were examined for encoding differences between initial and corrective submovements. Individual neurons were fitted with a regression model that included the reach vector, position, and speed to predict firing rate. For both initial and corrective submovements, the largest effect remained movement direction. We observed a large subset changed their preferred direction greater than 45° between initial and corrective submovements. Neuronal depth of modulation also showed considerable variation when adjusted for movement speed. By using principal component analysis, neural trajectories of initial and corrective submovements progressed through different neural subspaces. These findings all suggest that different neural encoding patterns exist for initial and corrective submovements within the cortex. We hypothesize that this variation in how neurons change to encode small, corrective submovements might allow for a larger portion of the neural space being used to encode a greater range of movements with varying amplitudes and levels of precision.NEW & NOTEWORTHY Neuronal recordings matched with kinematic behavior were collected in a precision center-out task that often required corrective movements. We reveal large differences in preferred direction and depth of modulation between initial and corrective submovements across the neural population. We then present a model of the neural population describing how these shifts in tuning create different subspaces for signaling initial and corrective movements likely to improve motor precision.

Neuronal travelling waves explain rotational dynamics in experimental datasets and modelling

Spatiotemporal properties of neuronal population activity in cortical motor areas have been subjects of experimental and theoretical investigations, generating numerous interpretations regarding mechanisms for preparing and executing limb movements. Two competing models, representational and dynamical, strive to explain the relationship between movement parameters and neuronal activity. A dynamical model uses the jPCA method that holistically characterizes oscillatory activity in neuron populations by maximizing the data rotational dynamics. Different rotational dynamics interpretations revealed by the jPCA approach have been proposed. Yet, the nature of such dynamics remains poorly understood. We comprehensively analyzed several neuronal-population datasets and found rotational dynamics consistently accounted for by a traveling wave pattern. For quantifying rotation strength, we developed a complex-valued measure, the gyration number. Additionally, we identified parameters influencing rotation extent in the data. Our findings suggest that rotational dynamics and traveling waves are typically the same phenomena, so reevaluation of the previous interpretations where they were considered separate entities is needed.

Rapid Online Corrections for Proprioceptive and Visual Perturbations Recruit Similar Circuits in Primary Motor Cortex

An important aspect of motor function is our ability to rapidly generate goal-directed corrections for disturbances to the limb or behavioral goal. The primary motor cortex (M1) is a key region involved in processing feedback for rapid motor corrections, yet we know little about how M1 circuits are recruited by different sources of sensory feedback to make rapid corrections. We trained two male monkeys (Macaca mulatta) to make goal-directed reaches and on random trials introduced different sensory errors by either jumping the visual location of the goal (goal jump), jumping the visual location of the hand (cursor jump), or applying a mechanical load to displace the hand (proprioceptive feedback). Sensory perturbations evoked a broad response in M1 with ∼73% of neurons (n = 257) responding to at least one of the sensory perturbations. Feedback responses were also similar as response ranges between the goal and cursor jumps were highly correlated (range of r = [0.91, 0.97]) as were the response ranges between the mechanical loads and the visual perturbations (range of r = [0.68, 0.86]). Lastly, we identified the neural subspace each perturbation response resided in and found a strong overlap between the two visual perturbations (range of overlap index, 0.73-0.89) and between the mechanical loads and visual perturbations (range of overlap index, 0.36-0.47) indicating each perturbation evoked similar structure of activity at the population level. Collectively, our results indicate rapid responses to errors from different sensory sources target similar overlapping circuits in M1.

Initial and corrective submovement encoding differences within primary motor cortex during precision reaching

Precision reaching tasks often require corrective submovements for successful completion. Most studies of reaching have focused on single initial movements, and the cortical encoding model was implied to be the same for all submovements. However, corrective submovements may show different encoding patterns from the initial submovement with distinct patterns of activation across the population. Two rhesus macaques performed a precision center-out-task with small targets. Neural activity from single units in primary motor cortex and associated behavioral data were recorded to evaluate movement characteristics. Neural population data and individual neuronal firing rates identified with a peak finding algorithm to identify peaks in hand speed were examined for encoding differences between initial and corrective submovements. Individual neurons were fitted with a regression model that included the reach vector, position, and speed to predict firing rate. For both initial and corrective submovements, the largest effect remained movement direction. We observed a large subset changed their preferred direction greater than 45° between initial and corrective submovements. Neuronal depth of modulation also showed considerable variation when adjusted for movement speed. By utilizing principal component analysis, neural trajectories of initial and corrective submovements progressed through different neural subspaces. These findings all suggest that different neural encoding patterns exist for initial and corrective submovements within the cortex. We hypothesize that this variation in how neurons change to encode small, corrective submovements might allow for a larger portion of the neural space being used to encode a greater range of movements with varying amplitudes and levels of precision.

New and Noteworthy

Neuronal recordings matched with kinematic behavior were collected in a precision center-out task that often required corrective movements. We reveal large differences in preferred direction and depth of modulation between initial and corrective submovements across the neural population. We then present a model of the neural population describing how these shifts in tuning create different subspaces for signaling initial and corrective movements likely to improve motor precision.

A cortical information bottleneck during decision-making

Decision-making emerges from distributed computations across multiple brain areas, but it is unclear why the brain distributes the computation. In deep learning, artificial neural networks use multiple areas (or layers) to form optimal representations of task inputs. These optimal representations are sufficient to perform the task well, but minimal so they are invariant to other irrelevant variables. We recorded single neurons and multiunits in dorsolateral prefrontal cortex (DLPFC) and dorsal premotor cortex (PMd) in monkeys during a perceptual decision-making task. We found that while DLPFC represents task-related inputs required to compute the choice, the downstream PMd contains a minimal sufficient, or optimal, representation of the choice. To identify a mechanism for how cortex may form these optimal representations, we trained a multi-area recurrent neural network (RNN) to perform the task. Remarkably, DLPFC and PMd resembling representations emerged in the early and late areas of the multi-area RNN, respectively. The DLPFC-resembling area partially orthogonalized choice information and task inputs and this choice information was preferentially propagated to downstream areas through selective alignment with inter-area connections, while remaining task information was not. Our results suggest that cortex uses multi-area computation to form minimal sufficient representations by preferential propagation of relevant information between areas.

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

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

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

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

Rotational dynamics in motor cortex are consistent with a feedback controller

Recent studies have identified rotational dynamics in motor cortex (MC), which many assume arise from intrinsic connections in MC. However, behavioral and neurophysiological studies suggest that MC behaves like a feedback controller where continuous sensory feedback and interactions with other brain areas contribute substantially to MC processing. We investigated these apparently conflicting theories by building recurrent neural networks that controlled a model arm and received sensory feedback from the limb. Networks were trained to counteract perturbations to the limb and to reach toward spatial targets. Network activities and sensory feedback signals to the network exhibited rotational structure even when the recurrent connections were removed. Furthermore, neural recordings in monkeys performing similar tasks also exhibited rotational structure not only in MC but also in somatosensory cortex. Our results argue that rotational structure may also reflect dynamics throughout the voluntary motor system involved in online control of motor actions.

Functional Imaging of the Cerebellum during Action Execution and Observation

We employed the ¹⁴C-deoxyglucose autoradiographic method to map the activity in the cerebellar cortex of rhesus monkeys that performed forelimb movements either in the light or in the dark and of monkeys that observed forelimb movements executed by a human experimenter. The execution of forelimb movements, both in the light and in the dark, activated the forelimb representations in the cerebellar hemispheric extensions of 1) vermian lobules IV-VI and 2) vermian lobule VIIIB, ipsilaterally to the moving forelimb. Activations in the former forelimb representation involved both a paravermal and a lateral hemispheric region. Also, Crus II posterior in the ansiform lobule (the hemispheric expansion of lobule VIIB) was activated bilaterally by execution of movements in the light but not in the dark. Action observation activated the lateral-most region of the forelimb representation in the lateral hemispheric extension of vermian lobules IV-VI, as well as the crus II posterior, bilaterally. Our results demonstrate that the cerebellar cortex, in addition to its involvement in the generation of movement, is also recruited in the perception of observed movements. Moreover, our findings suggest a modularity gradient in the primate cerebellar cortex, which progresses from unimodal (medially) to multimodal (laterally) functional areas.

A Dissociation of Attention, Executive Function and Reaction to Difficulty: Development of the MindPulse Test, a Novel Digital Neuropsychological Test for Precise Quantification of Perceptual-Motor Decision-Making Processes

Traditionally, neuropsychological testing has assessed processing speed and precision, closely related to the ability to perform high-order cognitive tasks. An individual making a decision under time pressure must constantly rebalance its speed to action in order to account for possible errors. A deficit in processing speed appears to be afrequent disorder caused by cerebral damage — but it can be hard to pinpoint the exact cause of the slowdown. It is therefore important to separate the perceptual-motor component of processing speed from the decision-time component. We present a technique to isolate Reaction Times (RTs): a short digital test to assess the decision-making abilities of individuals by gauging their ability to balance between speed and precision. Our hypothesis is that some subjects willaccelerate, and others slow down in the face of the difficulty. This pilot study, conducted on 83 neurotypical adult volunteers, used images stimuli. The test was designed to measure RTs and correctness. After learning release gesture, the subjects were presented with three tasks: a simple Reaction Time task, a Go/No-Go, and a complex Go/No-Go with 2 simultaneous Choices. All three tasks have in common a perceptual component and a motor response. By measuring the 3 reference points requiring attentional and executive processing, while progressively increasing the conceptual complexity of the task, we were able to compare the processing times for different tasks — thus calculating the deceleration specific to the reaction time linked to difficulty. We defined the difficulty coefficient of a task as being the ratio of the group average time of this task minus the base time/average time of the unit task minus the base time. We found that RTs can be broken down into three elementary, uncorrelated components: Reaction Time, Executive Speed, and Reaction to Difficulty (RD). We hypothesized that RD reflects how the subject reacts to difficulty by accelerating (RD < 0) or decelerating (RD > 0). Thus we provide here a first proof of concept: the ability to measure four axes of the speed-precision trade-off inherent in a subject’s fundamental decision making: perceptual-motor speed, executive speed, subject accuracy, and reaction to difficulty.

A Neurorobotic Embodiment for Exploring the Dynamical Interactions of a Spiking Cerebellar Model and a Robot Arm During Vision-Based Manipulation Tasks

While the original goal for developing robots is replacing humans in dangerous and tedious tasks, the final target shall be completely mimicking the human cognitive and motor behavior. Hence, building detailed computational models for the human brain is one of the reasonable ways to attain this. The cerebellum is one of the key players in our neural system to guarantee dexterous manipulation and coordinated movements as concluded from lesions in that region. Studies suggest that it acts as a forward model providing anticipatory corrections for the sensory signals based on observed discrepancies from the reference values. While most studies consider providing the teaching signal as error in joint-space, few studies consider the error in task-space and even fewer consider the spiking nature of the cerebellum on the cellular-level. In this study, a detailed cellular-level forward cerebellar model is developed, including modeling of Golgi and Basket cells which are usually neglected in previous studies. To preserve the biological features of the cerebellum in the developed model, a hyperparameter optimization method tunes the network accordingly. The efficiency and biological plausibility of the proposed cerebellar-based controller is then demonstrated under different robotic manipulation tasks reproducing motor behavior observed in human reaching experiments.

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

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

Egocentric metric representations in peripersonal space: A bridge between motor resources and spatial memory

Research on visuospatial memory has shown that egocentric (subject-to-object) and allocentric (object-to-object) reference frames are connected to categorical (non-metric) and coordinate (metric) spatial relations, and that motor resources are recruited especially when processing spatial information in peripersonal (within arm reaching) than extrapersonal (outside arm reaching) space. In order to perform our daily-life activities, these spatial components cooperate along a continuum from recognition-related (e.g., recognizing stimuli) to action-related (e.g., reaching stimuli) purposes. Therefore, it is possible that some types of spatial representations rely more on action/motor processes than others. Here, we explored the role of motor resources in the combinations of these visuospatial memory components. A motor interference paradigm was adopted in which participants had their arms bent behind their back or free during a spatial memory task. This task consisted in memorizing triads of objects and then verbally judging what was the object: (1) closest to/farthest from the participant (egocentric coordinate); (2) to the right/left of the participant (egocentric categorical); (3) closest to/farthest from a target object (allocentric coordinate); and (4) on the right/left of a target object (allocentric categorical). The triads appeared in participants' peripersonal (Experiment 1) or extrapersonal (Experiment 2) space. The results of Experiment 1 showed that motor interference selectively damaged egocentric-coordinate judgements but not the other spatial combinations. The results of Experiment 2 showed that the interference effect disappeared when the objects were in the extrapersonal space. A third follow-up study using a within-subject design confirmed the overall pattern of results. Our findings provide evidence that motor resources play an important role in the combination of coordinate spatial relations and egocentric representations in peripersonal space.

Distinct cortical networks for hand movement initiation and directional processing: An EEG study

Movement preparation and initiation have been shown to involve large scale brain networks. Recent findings suggest that movement preparation and initiation are represented in functionally distinct cortical networks. In electroencephalographic (EEG) recordings, movement initiation is reflected as a strong negative potential at medial central channels that is phase-locked to the movement onset - the movement-related cortical potential (MRCP). Movement preparation describes the process of transforming high level movement goals to low level commands. An integral part of this transformation process is directional processing (i.e., where to move). The processing of movement direction during visuomotor and oculomotor tasks is associated with medial parieto-occipital cortex (PO) activity, phase-locked to the presentation of potential movement goals. We surmised that the network generating the MRCP (movement initiation) would encode less information about movement direction than the parieto-occipital network processing movement direction. Here, we studied delta band EEG activity during center-out reaching movements (2D; 4 directions) in visuomotor and oculomotor tasks. In 15 healthy participants, we found a consistent representation of movement direction in PO 300–400 ​ms after the direction cue irrespective of the task. Despite generating the MRCP, sensorimotor areas (SM) encoded less information about the movement direction than PO. Moreover, the encoded directional information in SM was less consistent across participants and specific to the visuomotor task. In a classification approach, we could infer the four movement directions from the delta band EEG activity with moderate accuracies up to 55.9%. The accuracies for cue-aligned data were significantly higher than for movement onset-aligned data in either task, which also suggests a stronger representation of movement direction during movement preparation. Therefore, we present direct evidence that EEG delta band amplitude modulations carry information about both arm movement initiation and movement direction, and that they are represented in two distinct cortical networks.

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Delta band EEG carries information about arm movement initiation and direction.

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Movement initiation and direction are represented in two distinct cortical networks.

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Information about movement direction is primarily encoded in parieto-occipital areas.

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The activity in parieto-occipital areas is phase-locked to the direction cue.

Stiffness as a control factor for object manipulation

During manipulation, force is exerted with the expectation that an object will move in an intended manner. This prediction is a learned coordination between force and movement. Mechanically, impedance is a way to describe this coordination, and object interaction could be anticipated by setting impedance before the hand moves the object. This strategy would be especially important at the end of a reach, because feedback is ineffective for rapid force changes. Since mechanical impedance is not subject to the time delays of feedback, it can, if set properly, produce the desired motion on impact. We examined this possibility by instructing subjects to move a handle to a specific target position along a track. The handle was locked in place until the subject exerted enough force to cross a threshold; the handle was then released abruptly to move along the track. We hypothesized that this ballistic release task would encourage subjects to modify impedance in anticipation of the upcoming movement and found that one component of impedance, stiffness, varied in a way that matched the behavioral demands of the task. Analysis suggests that this stiffness was set before the handle moved and governed the subsequent motion. We also found separate components of muscle activity that corresponded to stiffness and to changes in force. Our results show that subjects used a robust and efficient strategy to coordinate force and displacement by modulating muscle activity in a way that was behaviorally relevant in the task.NEW & NOTEWORTHY The arm can behave like a spring, and this mechanical behavior can be advantageous in situations requiring rapid changes in force and/or displacement. Selection of a proper "virtual" spring before the occurrence of a rapid transient could facilitate a desired responsive movement. We show that these spring-like arm mechanics, set in anticipation of an instantaneous force change, function as an efficient strategy to control movement when feedback is ineffective.

Emerging ideas and tools to study the emergent properties of the cortical neural circuits for voluntary motor control in non-human primates

For years, neurophysiological studies of the cerebral cortical mechanisms of voluntary motor control were limited to single-electrode recordings of the activity of one or a few neurons at a time. This approach was supported by the widely accepted belief that single neurons were the fundamental computational units of the brain (the “neuron doctrine”). Experiments were guided by motor-control models that proposed that the motor system attempted to plan and control specific parameters of a desired action, such as the direction, speed or causal forces of a reaching movement in specific coordinate frameworks, and that assumed that the controlled parameters would be expressed in the task-related activity of single neurons. The advent of chronically implanted multi-electrode arrays about 20 years ago permitted the simultaneous recording of the activity of many neurons. This greatly enhanced the ability to study neural control mechanisms at the population level. It has also shifted the focus of the analysis of neural activity from quantifying single-neuron correlates with different movement parameters to probing the structure of multi-neuron activity patterns to identify the emergent computational properties of cortical neural circuits. In particular, recent advances in “dimension reduction” algorithms have attempted to identify specific covariance patterns in multi-neuron activity which are presumed to reflect the underlying computational processes by which neural circuits convert the intention to perform a particular movement into the required causal descending motor commands. These analyses have led to many new perspectives and insights on how cortical motor circuits covertly plan and prepare to initiate a movement without causing muscle contractions, transition from preparation to overt execution of the desired movement, generate muscle-centered motor output commands, and learn new motor skills. Progress is also being made to import optical-imaging and optogenetic toolboxes from rodents to non-human primates to overcome some technical limitations of multi-electrode recording technology.

Subjective vividness of motor imagery has a neural signature in human premotor and parietal cortex

Motor imagery (MI) is the process in which subjects imagine executing a body movement with a strong kinesthetic component from a first-person perspective. The individual capacity to elicit such mental images is not universal but varies within and between subjects. Neuroimaging studies have shown that these inter-as well as intra-individual differences in imagery quality mediate the amplitude of neural activity during MI on a group level. However, these analyses were not sensitive to forms of representation that may not map onto a simple modulation of overall amplitude. Therefore, the present study asked how far the subjective impression of motor imagery vividness is reflected by a spatial neural code, and how patterns of neural activation in different motor regions relate to specific imagery impressions. During fMRI scanning, 20 volunteers imagined three different types of right-hand actions. After each imagery trial, subjects were asked to evaluate the perceived vividness of their imagery. A correlation analysis compared the rating differences and neural dissimilarity values of the rating groups separately for each region of interest. Results showed a significant positive correlation in the left vPMC and right IPL, indicating that these regions particularly reflect perceived imagery vividness in that similar rated trials evoke more similar neural patterns. A decoding analysis revealed that the vividness of the motor image related systematically to the action specificity of neural activation patterns in left vPMC and right SPL. Imagined actions accompanied by higher vividness ratings were significantly more distinguishable within these areas. Altogether, results showed that spatial patterns of neural activity within the human motor cortices reflect the individual vividness of imagined actions. Hence, the findings reveal a link between the subjective impression of motor imagery vividness and objective physiological markers.

Unilateral movement preparation causes task-specific modulation of TMS responses in the passive, opposite limb

KEY POINTS

Activity in the primary motor cortices of both hemispheres increases during unilateral movement preparation, but the functional role of ipsilateral motor cortex activity is unknown. Ipsilateral motor cortical activity could represent subliminal 'motor planning' for the passive limb. Alternatively, it could represent the state of the active limb, to support coordination between the limbs should a bimanual movement be required. Here we assessed how preparation of forces toward different directions, with the left wrist, alters evoked responses to transcranial magnetic stimulation of left motor cortex. Preparation of a unilateral movement caused excitability increases in ipsilateral motor cortex that reflected forces produced with the active limb in an intrinsic (body-centred), rather than an extrinsic (world-centred), coordinate system. These results suggest that ipsilateral motor cortical activity prior to unilateral action reflects the state of the active limb, rather than subliminal motor planning for the passive limb.

ABSTRACT

Corticospinal excitability is modulated for muscles on both sides of the body during unilateral movement preparation. For the effector, there is a progressive increase in excitability, and a shift in direction of muscle twitches evoked by transcranial magnetic stimulation (TMS) toward the impending movement. By contrast, the directional characteristics of excitability changes in the opposite (passive) limb have not been fully characterized. Here we assessed how preparation of voluntary forces towards four spatially distinct visual targets with the left wrist alters muscle twitches and motor-evoked potentials (MEPs) elicited by TMS of left motor cortex. MEPs were facilitated significantly more in muscles homologous to agonist rather than antagonist muscles in the active limb, from 120 ms prior to voluntary EMG onset. Thus, unilateral motor preparation has a directionally specific influence on pathways projecting to the opposite limb that corresponds to the active muscles rather than the direction of movement in space. The directions of TMS-evoked twitches also deviated toward the impending force direction of the active limb, according to muscle-based coordinates, following the onset of voluntary EMG. The data indicate that preparation of a unilateral movement increases task-dependent excitability in ipsilateral motor cortex, or its downstream projections, that reflects the forces applied by the active limb in an intrinsic (body-centred), rather than an extrinsic (world-centred), coordinate system. The results suggest that ipsilateral motor cortical activity prior to unilateral action reflects the state of the active limb, rather than subliminal motor planning for the passive limb.

Dynamics of directional tuning and reference frames in humans: A high-density EEG study

Recent developments in EEG recording and signal processing have made it possible to record in an unconstrained, natural movement task, therefore EEG provides a promising approach to understanding the neural mechanisms of upper-limb reaching control. This study specifically addressed how EEG dynamics in the time domain encoded finger movement directions (directional tuning) and posture dependence (movement reference frames) by applying representational similarity analysis. High-density EEG covering the entire scalp was recorded while participants performed eight-directional, center-out reaching movements, thereby allowing us to explore directional selectivity of EEG sources over the brain beyond somatosensory areas. A majority of the source processes exhibited statistically significant directional tuning during peri-movement periods. In addition, directional tuning curves shifted systematically when the shoulder angle was rotated to perform the task within a more laterally positioned workspace, the degree of tuning curve rotation falling between that predicted by models assuming extrinsic and shoulder-based reference frames. We conclude that temporal dynamics of neural mechanisms for motor control can be studied noninvasively in humans using high-density EEG and that directional sensitivity of motor and non-motor processing is not limited within the sensorimotor areas but extends to the whole brain areas.

Hierarchical Organization Within the Ventral Premotor Cortex of the Macaque Monkey

Recent studies have revealed that the ventral premotor cortex (PMv) of nonhuman primates plays a pivotal role in various behaviors that require the transformation of sensory cues to appropriate actions. Examples include decision-making based on various sensory cues, preparation for upcoming motor behavior, adaptive sensorimotor transformation, and the generation of motor commands using rapid sensory feedback. Although the PMv has frequently been regarded as a single entity, it can be divided into at least five functionally distinct regions: F4, a dorsal convexity region immediately rostral to the primary motor cortex (M1); F5p, a cortical region immediately rostral to F4, lying within the arcuate sulcus; F5c, a ventral convexity region rostral to F4; and F5a, located in the caudal bank of the arcuate sulcus inferior limb lateral to F5p. Among these, F4 can be further divided into dorsal and ventral subregions (F4d and F4v), which are involved in forelimb and orofacial movements, respectively. F5p contains "mirror neurons" to understand others' actions based on visual and other types of information, and F4d and F5p work together as a functional complex involved in controlling forelimb and eye movements, most efficiently in the execution and completion of coordinated eye-hand movements for reaching and grasping under visual guidance. In contrast, F5c and F5a are hierarchically higher than the F4d, F5p, and F5v complexes, and play a role in decision-making based on various sensory discriminations. Hence, the PMv subregions form a hierarchically organized integral system from decision-making to eye-hand coordination under various behavioral circumstances.

Movement-related activity in the periarcuate cortex of monkeys during coordinated eye and hand movements

To determine the role of the periarcuate cortex during coordinated eye and hand movements in monkeys, the present study examined neuronal activity in this region during movement with the hand, eyes, or both as effectors toward a visuospatial target. Similar to the primary motor cortex (M1), the dorsal premotor cortex contained a higher proportion of neurons that were closely related to hand movements, whereas saccade-related neurons were frequently recorded from the frontal eye field (FEF). Interestingly, neurons that exhibited activity related to both eye and hand movements were recorded most frequently in the ventral premotor cortex (PMv), located between the FEF and M1. Neuronal activity in the periarcuate cortex was highly modulated during coordinated movements compared with either eye or hand movement only. Additionally, a small number of neurons were active specifically during one of the three task modes, which could be dissociated from the effector activity. In this case, neuron onset was either ahead of or behind the onset of eye and/or hand movement, and some neuronal activity lasted until reward delivery signaled successful completion of reaching. The present findings indicate that the periarcuate cortex, particularly the PMv, plays important roles in orchestrating coordinated movements from the initiation to the termination of reaching.

NEW & NOTEWORTHY Movement-related neuronal activity was recorded throughout the periarcuate cortex of monkeys that performed a task requiring them to move their hand only, eyes only, or both hand and eyes toward visuospatial targets. Most typically, neurons were found that were commonly active regardless of different effectors, from movement initiation to completion of a successful outcome. The findings suggest that the periarcuate cortex as a whole plays a crucial role in initiating and completing coordinated eye-hand movements.

Noise-Robust Modes of the Retinal Population Code Have the Geometry of "Ridges" and Correspond to Neuronal Communities

An appealing new principle for neural population codes is that correlations among neurons organize neural activity patterns into a discrete set of clusters, which can each be viewed as a noise-robust population codeword. Previous studies assumed that these codewords corresponded geometrically with local peaks in the probability landscape of neural population responses. Here, we analyze multiple data sets of the responses of approximately 150 retinal ganglion cells and show that local probability peaks are absent under broad, nonrepeated stimulus ensembles, which are characteristic of natural behavior. However, we find that neural activity still forms noise-robust clusters in this regime, albeit clusters with a different geometry. We start by defining a soft local maximum, which is a local probability maximum when constrained to a fixed spike count. Next, we show that soft local maxima are robustly present and can, moreover, be linked across different spike count levels in the probability landscape to form a ridge. We found that these ridges comprise combinations of spiking and silence in the neural population such that all of the spiking neurons are members of the same neuronal community, a notion from network theory. We argue that a neuronal community shares many of the properties of Donald Hebb's classic cell assembly and show that a simple, biologically plausible decoding algorithm can recognize the presence of a specific neuronal community.

Altered tuning in primary motor cortex does not account for behavioral adaptation during force field learning

Although primary motor cortex (M1) is intimately involved in the dynamics of limb movement, its inputs may be more closely related to higher-order aspects of movement and multi-modal sensory feedback. Motor learning is thought to result from the adaption of internal models that compute transformations between these representations. While the psychophysics of motor learning has been studied in many experiments, the particular role of M1 in the process remains the subject of debate. Studies of learning-related changes in the spatial tuning of M1 neurons have yielded conflicting results. To resolve the discrepancies, we recorded from M1 during curl field adaptation in a reaching task. Our results suggest that aside from the addition of the load itself, the relation of M1 to movement dynamics remains unchanged as monkeys adapt behaviorally. Accordingly, we implemented a musculoskeletal model to generate synthetic neural activity having a fixed dynamical relation to movement and showed that these simulated neurons reproduced the observed behavior of the recorded M1 neurons. The stable representation of movement dynamics in M1 suggests that behavioral changes are mediated through progressively altered recruitment of M1 neurons, while the output effect of those neurons remained largely unchanged.

The effect of concussion history on cognitive-motor integration in elite hockey players

AIM

To observe the effects of concussion history on cognitive-motor integration in elite-level athletes.

METHODS

The study included 102 National Hockey League draft prospects (n = 51 concussion history [CH]; n = 51 no history [NC]). Participants completed two computer-based visuomotor tasks, one involved 'standard' visuomotor mapping and one involved 'nonstandard' mapping in which vision and action were decoupled.

RESULTS

We observed a significant effect of group on reaction time (CH slower) and accuracy (CH worse), but a group by condition interaction only for reaction time (p < 0.05). There were no other deficits found. We discussed these findings in comparison to our previous work with non-elite athletes.

CONCLUSION

Previously concussed elite-level athletes may have lingering neurological deficits that are not detected using standard clinical assessments.

Motor Planning, Not Execution, Separates Motor Memories

Recent theories of limb control emphasize motor cortex as a dynamical system, with planning setting the initial neural state, and execution arising from the self-limiting evolution of the intrinsic neural dynamics. Therefore, movements that share an initial trajectory but then diverge might have different neural states during the execution of the identical initial trajectories. We hypothesized that motor adaptation maps neural states to changes in motor command. This predicts that two opposing perturbations, which interfere when experienced over the same movement, could be learned if each is associated with a different plan even if not executed. We show that planning, but not executing, different follow-through movements allow opposing perturbations to be learned simultaneously over the same movement. However, no learning occurs if different follow throughs are executed, but not planned prior to movement initiation. Our results suggest neural, rather than physical states, are the critical factor associated with motor adaptation.

Dynamic Motor Cortical Organization

Motor cortical organization has commonly been conceived as somatotopically ordered, with single body parts controlled from individual patches of cortical tissue. An opposing viewpoint suggests that motor cortex has a distnbuted, adaptive, and dynamic organi zation that underlies movement planning, performance, adaptation, and learning. Con verging evidence from anatomic, neurophysiologic, and functional neuroimaging sources indicates that the arm area of motor cortical areas in monkeys and humans has multiple, interconnected sites that ostensibly contribute to controlling various parts of the arm. These representations can exhibit rapid and sometimes enduring modifications following injury, changes in somatic sensory input, and motor learning. Activity-dependent changes in the intrinsic motor cortical network of horizontal and vertical connections coupled with ascending thalamic and corticocortical inputs could provide a substrate for dynamic mod ulation of motor cortex functional representations. NEUROSCIENTIST 3:158-165, 1997

Tuning Curves for Arm Posture Control in Motor Cortex Are Consistent with Random Connectivity

Neuronal responses characterized by regular tuning curves are typically assumed to arise from structured synaptic connectivity. However, many responses exhibit both regular and irregular components. To address the relationship between tuning curve properties and underlying circuitry, we analyzed neuronal activity recorded from primary motor cortex (M1) of monkeys performing a 3D arm posture control task and compared the results with a neural network model. Posture control is well suited for examining M1 neuronal tuning because it avoids the dynamic complexity of time-varying movements. As a function of hand position, the neuronal responses have a linear component, as has previously been described, as well as heterogeneous and highly irregular nonlinearities. These nonlinear components involve high spatial frequencies and therefore do not support explicit encoding of movement parameters. Yet both the linear and nonlinear components contribute to the decoding of EMG of major muscles used in the task. Remarkably, despite the presence of a strong linear component, a feedforward neural network model with entirely random connectivity can replicate the data, including both the mean and distributions of the linear and nonlinear components as well as several other features of the neuronal responses. This result shows that smoothness provided by the regularity in the inputs to M1 can impose apparent structure on neural responses, in this case a strong linear (also known as cosine) tuning component, even in the absence of ordered synaptic connectivity.

Primary motor cortex of the parkinsonian monkey: altered encoding of active movement

Abnormalities in the movement-related activation of the primary motor cortex (M1) are thought to be a major contributor to the motor signs of Parkinson's disease. The existing evidence, however, variably indicates that M1 is under-activated with movement, overactivated (due to a loss of functional specificity) or activated with abnormal timing. In addition, few models consider the possibility that distinct cortical neuron subtypes may be affected differently. Those gaps in knowledge were addressed by studying the extracellular activity of antidromically-identified lamina 5b pyramidal-tract type neurons (n = 153) and intratelencephalic-type corticostriatal neurons (n = 126) in the M1 of two monkeys as they performed a step-tracking arm movement task. We compared movement-related discharge before and after the induction of parkinsonism by administration of MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) and quantified the spike rate encoding of specific kinematic parameters of movement using a generalized linear model. The fraction of M1 neurons with movement-related activity declined following MPTP but only marginally. The strength of neuronal encoding of parameters of movement was reduced markedly (mean 29% reduction in the coefficients from the generalized linear model). This relative decoupling of M1 activity from kinematics was attributable to reductions in the coefficients that estimated the spike rate encoding of movement direction (-22%), speed (-40%), acceleration (-49%) and hand position (-33%). After controlling for MPTP-induced changes in motor performance, M1 activity related to movement itself was reduced markedly (mean 36% hypoactivation). This reduced activation was strong in pyramidal tract-type neurons (-50%) but essentially absent in corticostriatal neurons. The timing of M1 activation was also abnormal, with earlier onset times, prolonged response durations, and a 43% reduction in the prevalence of movement-related changes beginning in the 150-ms period that immediately preceded movement. Overall, the results are consistent with proposals that under-activation and abnormal timing of movement-related activity in M1 contribute to parkinsonian motor signs but are not consistent with the idea that a loss of functional specificity plays an important role. Given that pyramidal tract-type neurons form the primary efferent pathway that conveys motor commands to the spinal cord, the dysfunction of movement-related activity in pyramidal tract-type neurons is likely to be a central factor in the pathophysiology of parkinsonian motor signs.

Practice reduces task relevant variance modulation and forms nominal trajectory

Humans are capable of achieving complex tasks with redundant degrees of freedom. Much attention has been paid to task relevant variance modulation as an indication of online feedback control strategies to cope with motor variability. Meanwhile, it has been discussed that the brain learns internal models of environments to realize feedforward control with nominal trajectories. Here we examined trajectory variance in both spatial and temporal domains to elucidate the relative contribution of these control schemas. We asked subjects to learn reaching movements with multiple via-points, and found that hand trajectories converged to stereotyped trajectories with the reduction of task relevant variance modulation as learning proceeded. Furthermore, variance reduction was not always associated with task constraints but was highly correlated with the velocity profile. A model assuming noise both on the nominal trajectory and motor command was able to reproduce the observed variance modulation, supporting an expression of nominal trajectories in the brain. The learning-related decrease in task-relevant modulation revealed a reduction in the influence of optimal feedback around the task constraints. After practice, the major part of computation seems to be taken over by the feedforward controller around the nominal trajectory with feedback added only when it becomes necessary.

Context-Dependent Neural Activation: Internally and Externally Guided Rhythmic Lower Limb Movement in Individuals With and Without Neurodegenerative Disease

Parkinson’s disease is a neurodegenerative disorder that has received considerable attention in allopathic medicine over the past decades. However, it is clear that, to date, pharmacological and surgical interventions do not fully address symptoms of PD and patients’ quality of life. As both an alternative therapy and as an adjuvant to conventional approaches, several types of rhythmic movement (e.g., movement strategies, dance, tandem biking, and Tai Chi) have shown improvements to motor symptoms, lower limb control, and postural stability in people with PD (1–6). However, while these programs are increasing in number, still little is known about the neural mechanisms underlying motor improvements attained with such interventions. Studying limb motor control under task-specific contexts can help determine the mechanisms of rehabilitation effectiveness. Both internally guided (IG) and externally guided (EG) movement strategies have evidence to support their use in rehabilitative programs. However, there appears to be a degree of differentiation in the neural substrates involved in IG vs. EG designs. Because of the potential task-specific benefits of rhythmic training within a rehabilitative context, this report will consider the use of IG and EG movement strategies, and observations produced by functional magnetic resonance imaging and other imaging techniques. This review will present findings from lower limb imaging studies, under IG and EG conditions for populations with and without movement disorders. We will discuss how these studies might inform movement disorders rehabilitation (in the form of rhythmic, music-based movement training) and highlight research gaps. We believe better understanding of lower limb neural activity with respect to PD impairment during rhythmic IG and EG movement will facilitate the development of novel and effective therapeutic approaches to mobility limitations and postural instability.

Motor imagery of hand actions: Decoding the content of motor imagery from brain activity in frontal and parietal motor areas

How motor maps are organized while imagining actions is an intensely debated issue. It is particularly unclear whether motor imagery relies on action‐specific representations in premotor and posterior parietal cortices. This study tackled this issue by attempting to decode the content of motor imagery from spatial patterns of Blood Oxygen Level Dependent (BOLD) signals recorded in the frontoparietal motor imagery network. During fMRI‐scanning, 20 right‐handed volunteers worked on three experimental conditions and one baseline condition. In the experimental conditions, they had to imagine three different types of right‐hand actions: an aiming movement, an extension–flexion movement, and a squeezing movement. The identity of imagined actions was decoded from the spatial patterns of BOLD signals they evoked in premotor and posterior parietal cortices using multivoxel pattern analysis. Results showed that the content of motor imagery (i.e., the action type) could be decoded significantly above chance level from the spatial patterns of BOLD signals in both frontal (PMC, M1) and parietal areas (SPL, IPL, IPS). An exploratory searchlight analysis revealed significant clusters motor‐ and motor‐associated cortices, as well as in visual cortices. Hence, the data provide evidence that patterns of activity within premotor and posterior parietal cortex vary systematically with the specific type of hand action being imagined. Hum Brain Mapp 37:81–93, 2016. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Real-Time Neuroimaging and Cognitive Monitoring Using Wearable Dry EEG

GOAL

We present and evaluate a wearable high-density dry-electrode EEG system and an open-source software framework for online neuroimaging and state classification.

METHODS

The system integrates a 64-channel dry EEG form factor with wireless data streaming for online analysis. A real-time software framework is applied, including adaptive artifact rejection, cortical source localization, multivariate effective connectivity inference, data visualization, and cognitive state classification from connectivity features using a constrained logistic regression approach (ProxConn). We evaluate the system identification methods on simulated 64-channel EEG data. Then, we evaluate system performance, using ProxConn and a benchmark ERP method, in classifying response errors in nine subjects using the dry EEG system.

RESULTS

Simulations yielded high accuracy (AUC = 0.97 ± 0.021) for real-time cortical connectivity estimation. Response error classification using cortical effective connectivity [short-time direct-directed transfer function (sdDTF)] was significantly above chance with similar performance (AUC) for cLORETA (0.74 ±0.09) and LCMV (0.72 ±0.08) source localization. Cortical ERP-based classification was equivalent to ProxConn for cLORETA (0.74 ±0.16) but significantly better for LCMV (0.82 ±0.12) .

CONCLUSION

We demonstrated the feasibility for real-time cortical connectivity analysis and cognitive state classification from high-density wearable dry EEG.

SIGNIFICANCE

This paper is the first validated application of these methods to 64-channel dry EEG. This study addresses a need for robust real-time measurement and interpretation of complex brain activity in the dynamic environment of the wearable setting. Such advances can have broad impact in research, medicine, and brain-computer interfaces. The pipelines are made freely available in the open-source SIFT and BCILAB toolboxes.

The emergence of single neurons in clinical neurology

Single neuron actions and interactions are the sine qua non of brain function, and nearly all diseases and injuries of the CNS trace their clinical sequelae to neuronal dysfunction or failure. Remarkably, discussion of neuronal activity is largely absent in clinical neuroscience. Advances in neurotechnology and computational capabilities, accompanied by shifts in theoretical frameworks, have led to renewed interest in the information represented by single neurons. Using direct interfaces with the nervous system, millisecond-scale information will soon be extracted from single neurons in clinical environments, supporting personalized treatment of neurologic and psychiatric disease. In this Perspective, we focus on single-neuronal activity in restoring communication and motor control in patients suffering from devastating neurological injuries. We also explore the single neuron's role in epilepsy and movement disorders, surgical anesthesia, and in cognitive processes disrupted in neurodegenerative and neuropsychiatric disease. Finally, we speculate on how technological advances will revolutionize neurotherapeutics.

Dorsal premotor cortex: neural correlates of reach target decisions based on a color-location matching rule and conflicting sensory evidence

We recorded single-neuron activity in dorsal premotor (PMd) and primary motor cortex (M1) of two monkeys in a reach-target selection task. The monkeys chose between two color-coded potential targets by determining which target's color matched the predominant color of a multicolored checkerboard-like Decision Cue (DC). Different DCs contained differing numbers of colored squares matching each target. The DCs provided evidence about the correct target ranging from unambiguous (one color only) to very ambiguous and conflicting (nearly equal number of squares of each color). Differences in choice behavior (reach response times and success rates as a function of DC ambiguity) of the monkeys suggested that each applied a different strategy for using the target-choice evidence in the DCs. Nevertheless, the appearance of the DCs evoked a transient coactivation of PMd neurons preferring both potential targets in both monkeys. Reach response time depended both on how long it took activity to increase in neurons that preferred the chosen target and on how long it took to suppress the activity of neurons that preferred the rejected target, in both correct-choice and error-choice trials. These results indicate that PMd neurons in this task are not activated exclusively by a signal proportional to the net color bias of the DCs. They are instead initially modulated by the conflicting evidence supporting both response choices; final target selection may result from a competition between representations of the alternative choices. The results also indicate a temporal overlap between action selection and action initiation processes in PMd and M1.

Distinct neuronal organizations of the caudal cingulate motor area and supplementary motor area in monkeys for ipsilateral and contralateral hand movements

The caudal cingulate motor area (CMAc) and the supplementary motor area (SMA) play important roles in movement execution. The present study aimed to characterize the functional organization of these regions during movement by investigating laterality representations in the CMAc and SMA of monkeys via an examination of neuronal activity during a button press movement with either the right or left hand. Three types of movement-related neuronal activity were observed: 1) with only the contralateral hand, 2) with only the ipsilateral hand, and 3) with either hand. Neurons in the CMAc represented contralateral and ipsilateral hand movements to the same degree, whereas neuronal representations in the SMA were biased toward contralateral hand movement. Furthermore, recording neuronal activities using a linear-array multicontact electrode with 24 contacts spaced 150 μm apart allowed us to analyze the spatial distribution of neurons exhibiting particular hand preferences at the submillimeter scale. The CMAc and SMA displayed distinct microarchitectural organizations. The contralateral, ipsilateral, and bilateral CMAc neurons were distributed homogeneously, whereas SMA neurons exhibiting identical hand preferences tended to cluster. These findings indicate that the CMAc, which is functionally organized in a less structured manner than the SMA is, controls contralateral and ipsilateral hand movements in a counterbalanced fashion, whereas the SMA, which is more structured, preferentially controls contralateral hand movements.

Motor adaptation and generalization of reaching movements using motor primitives based on spatial coordinates

The brain processes sensory and motor information in a wide range of coordinate systems, ranging from retinal coordinates in vision to body-centered coordinates in areas that control musculature. Here we focus on the coordinate system used in the motor cortex to guide actions and examine physiological and psychophysical evidence for an allocentric reference frame based on spatial coordinates. When the equations of motion governing reaching dynamics are expressed as spatial vectors, each term is a vector cross product between a limb-segment position and a velocity or acceleration. We extend this computational framework to motor adaptation, in which the cross-product terms form adaptive bases for canceling imposed perturbations. Coefficients of the velocity- and acceleration-dependent cross products are assumed to undergo plastic changes to compensate the force-field or visuomotor perturbations. Consistent with experimental findings, each of the cross products had a distinct reference frame, which predicted how an acquired remapping generalized to untrained location in the workspace. In response to force field or visual rotation, mainly the coefficients of the velocity- or acceleration-dependent cross products adapted, leading to transfer in an intrinsic or extrinsic reference frame, respectively. The model further predicted that remapping of visuomotor rotation should under- or overgeneralize in a distal or proximal workspace. The cross-product bases can explain the distinct patterns of generalization in visuomotor and force-field adaptation in a unified way, showing that kinematic and dynamic motor adaptation need not arise through separate neural substrates.

Systems view on spatial planning and perception based on invariants in agent-environment dynamics

Modeling agile and versatile spatial behavior remains a challenging task, due to the intricate coupling of planning, control, and perceptual processes. Previous results have shown that humans plan and organize their guidance behavior by exploiting patterns in the interactions between agent or organism and the environment. These patterns, described under the concept of Interaction Patterns (IPs), capture invariants arising from equivalences and symmetries in the interaction with the environment, as well as effects arising from intrinsic properties of human control and guidance processes, such as perceptual guidance mechanisms. The paper takes a systems' perspective, considering the IP as a unit of organization, and builds on its properties to present a hierarchical model that delineates the planning, control, and perceptual processes and their integration. The model's planning process is further elaborated by showing that the IP can be abstracted, using spatial time-to-go functions. The perceptual processes are elaborated from the hierarchical model. The paper provides experimental support for the model's ability to predict the spatial organization of behavior and the perceptual processes.

Allocentric versus egocentric representation of remembered reach targets in human cortex

The location of a remembered reach target can be encoded in egocentric and/or allocentric reference frames. Cortical mechanisms for egocentric reach are relatively well described, but the corresponding allocentric representations are essentially unknown. Here, we used an event-related fMRI design to distinguish human brain areas involved in these two types of representation. Our paradigm consisted of three tasks with identical stimulus display but different instructions: egocentric reach (remember absolute target location), allocentric reach (remember target location relative to a visual landmark), and a nonspatial control, color report (report color of target). During the delay phase (when only target location was specified), the egocentric and allocentric tasks elicited widely overlapping regions of cortical activity (relative to the control), but with higher activation in parietofrontal cortex for egocentric task and higher activation in early visual cortex for allocentric tasks. In addition, egocentric directional selectivity (target relative to gaze) was observed in the superior occipital gyrus and the inferior occipital gyrus, whereas allocentric directional selectivity (target relative to a visual landmark) was observed in the inferior temporal gyrus and inferior occipital gyrus. During the response phase (after movement direction had been specified either by reappearance of the visual landmark or a pro-/anti-reach instruction), the parietofrontal network resumed egocentric directional selectivity, showing higher activation for contralateral than ipsilateral reaches. These results show that allocentric and egocentric reach mechanisms use partially overlapping but different cortical substrates and that directional specification is different for target memory versus reach response.

Sampling time and performance in rat whisker sensory system

We designed a behavioural paradigm for vibro-tactile detection to characterise the sampling time and performance in the rat whisker sensory system. Rats initiated a trial by nose-poking into an aperture where their whiskers came into contact with two meshes. A continuous nose-poke for a random duration triggered stimulus presentation. Stimuli were a sequence of discrete Gaussian deflections of the mesh that increased in amplitude over time – across 5 conditions, time to maximum amplitude varied from 0.5 to 8 seconds. Rats indicated the detected stimulus by choosing between two reward spouts. Two rats completed more than 500 trials per condition. Rats' stimulus sampling duration increased and performance dropped with increasing task difficulty. For all conditions the median reaction time was longer for correct trials than incorrect trials. Higher rates of increment in stimulus amplitude resulted in faster rise in performance as a function of stimulus sampling duration. Rats' behaviour indicated a dynamic stimulus sampling whereby nose-poke was maintained until a stimulus was correctly identified or the rat experienced a false alarm. The perception was then manifested in behaviour after a motor delay. We thus modelled the results with 3 parameters: signal detection, false alarm, and motor delay. The model captured the main features of the data and produced parameter estimates that were biologically plausible and highly similar across the two rats.