Phase-Specific Microstimulation Differentially Modulates Beta Oscillations and Affects Behavior.

It is widely accepted that Beta-band oscillations play a role in sensorimotor behavior. To further explore this role, we developed a hybrid platform to combine neural operant conditioning and phase-specific intracortical microstimulation (ICMS). We trained monkeys, implanted with 96 electrode arrays in the motor cortex, to volitionally enhance local field potential (LFP) Beta-band (20-30 Hz) activity at selected sites using a brain-machine interface.

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.

Spatial computation with gamma oscillations.

Gamma oscillations in cortex have been extensively studied with relation to behavior in both humans and animal models; however, their computational role in the processing of behaviorally relevant signals is still not clear. One oft-overlooked characteristic of gamma oscillations is their spatial distribution over the cortical space and the computational consequences of such an organization. Here, we advance the proposal that the spatial organization of gamma oscillations is of major importance for their function.

A Bayesian approach for characterizing direction tuning curves in the supplementary motor area of behaving monkeys.

Neural responses are commonly studied in terms of "tuning curves," characterizing changes in neuronal response as a function of a continuous stimulus parameter. In the motor system, neural responses to movement direction often follow a bell-shaped tuning curve for which the exact shape determines the properties of neuronal movement coding. Estimating the shape of that tuning curve robustly is hard, especially when directions are sampled unevenly and at a coarse resolution.

Inducing γ oscillations and precise spike synchrony by operant conditioning via brain-machine interface.

Neural oscillations in the low-gamma range (30-50 Hz) have been implicated in neuronal synchrony, computation, behavior, and cognition. Abnormal low-gamma activity, hypothesized to reflect impaired synchronization, has been evidenced in several brain disorders. Thus, understanding the relations between gamma oscillations, neuronal synchrony and behavior is a major research challenge.

Cross-sensory transfer of sensory-motor information: visuomotor learning affects performance on an audiomotor task, using sensory-substitution.

Visual-to-auditory sensory-substitution devices allow users to perceive a visual image using sound. Using a motor-learning task, we found that new sensory-motor information was generalized across sensory modalities. We imposed a rotation when participants reached to visual targets, and found that not only seeing, but also hearing the location of targets via a sensory-substitution device resulted in biased movements.

Single neurons in M1 and premotor cortex directly reflect behavioral interference.

Some motor tasks, if learned together, interfere with each other's consolidation and subsequent retention, whereas other tasks do not. Interfering tasks are said to employ the same internal model whereas noninterfering tasks use different models. The division of function among internal models, as well as their possible neural substrates, are not well understood.

Closed-loop deep brain stimulation is superior in ameliorating parkinsonism.

Continuous high-frequency deep brain stimulation (DBS) is a widely used therapy for advanced Parkinson's disease (PD) management. However, the mechanisms underlying DBS effects remain enigmatic and are the subject of an ongoing debate. Here, we present and test a closed-loop stimulation strategy for PD in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) primate model of PD.

Just do it: action-dependent learning allows sensory prediction.

Sensory-motor learning is commonly considered as a mapping process, whereby sensory information is transformed into the motor commands that drive actions. However, this directional mapping, from inputs to outputs, is part of a loop; sensory stimuli cause actions and vice versa. Here, we explore whether actions affect the understanding of the sensory input that they cause.

The representation of visual and motor aspects of reaching movements in the human motor cortex.

The human primary motor cortex (M1) is robustly activated during visually guided hand movements. M1 multivoxel patterns of functional MRI activation are more correlated during repeated hand movements to the same targets than to greatly differing ones, and therefore potentially contain information about movement direction. It is unclear, however, whether direction specificity is due to the motor command, as implicitly assumed, or to the visual aspects of the task, such as the target location and the direction of the cursor's trajectory.

Expressions of multiple neuronal dynamics during sensorimotor learning in the motor cortex of behaving monkeys.

Previous studies support the notion that sensorimotor learning involves multiple processes. We investigated the neuronal basis of these processes by recording single-unit activity in motor cortex of non-human primates (Macaca fascicularis), during adaptation to force-field perturbations. Perturbed trials (reaching to one direction) were practiced along with unperturbed trials (to other directions).

Online adaptation and over-trial learning in macaque visuomotor control.

When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.

The neuronal basis of long-term sensorimotor learning.

The brain has a remarkable ability to learn and adjust behavior. For instance, the brain can adjust muscle activation to cope with changes in the environment. However, the neuronal mechanisms behind this adaptation are not clear.

Neuronal correlates of memory formation in motor cortex after adaptation to force field.

Activity of single neurons in the motor cortex has been shown to change during acquisition of motor skills. We previously reported that the combined activity of cell ensembles in the motor cortex of monkeys (Macaca fascicularis) evolves during adaptation to a novel force field perturbation to encode the direction of compensatory force when reaching to visual targets. We also showed that the population directional signal was altered by the available sensory feedback.

Functional organization of human motor cortex: directional selectivity for movement.

In monkeys, neurons in the hand representation of the primary motor cortex (M1) are often tuned to the direction of hand movement, and there is evidence that these neurons are clustered according to their "preferred" direction of movement. However, this organizational principle has yet to be demonstrated in M1 of humans. We conducted a functional magnetic resonance imaging (fMRI) study in which participants used a joystick to move a cursor from a central origin to one of five equidistant targets.

Combined adaptiveness of specific motor cortical ensembles underlies learning.

Learning motor skills entails adaptation of neural computations that can generate or modify associations between sensations and actions. Indeed, humans can use different strategies when adapting to dynamic loads depending on available sensory feedback. Here, we examined how neural activity in motor cortex was modified when monkeys made arm reaches to a visual target and locally adapted to curl force field with or without visual trajectory feedback.

Discordant Tasks and Motor Adjustments Affect Interactions between Adaptations to Altered Kinematics and Dynamics.

Motor control and adaptation are multi-determinate processes with complex interactions. This is reflected for example in the ambiguous nature of interactions during sequential adaptation of reaching under kinematics and dynamics perturbations. It has been suggested that perturbations based on the same kinematic parameter interfere.

Trial-to-trial variability of single cells in motor cortices is dynamically modified during visuomotor adaptation.

Neurons in all brain areas exhibit variability in their spiking activity. Although part of this variability can be considered as noise that is detrimental to information processing, recent findings indicate that variability can also be beneficial. In particular, it was suggested that variability in the motor system allows for exploration of possible motor states and therefore can facilitate learning and adaptation to new environments.

Synchronization of midbrain dopaminergic neurons is enhanced by rewarding events.

The basal ganglia network is divided into two functionally related subsystems: the neuromodulators and the main axis. It is assumed that neuromodulators adjust cortico-striatal coupling. This adjustment might depend on the response properties and temporal interactions between neuromodulators.

Learning from learning: what can visuomotor adaptations tell us about the neuronal representation of movement?

The use of sensorimotor adaptation and learning paradigms in psychophyical and electrophysiological experiments can help to shed light on two fundamental questions. First, what are the computations that control sensorimotor behavior and, second, what are the neuronal mechanisms and representations underlying newly learned sensorimotor skills? We describe experiments that combined behavioral and electrophysioloigcal techniques and discuss implication of the results to three main questions: How do neuronal primitives of representation affect performance and learning? Do pre-motor and primary motor cortices form a hierarchy of computation, with different roles during learning and motor performance? How do these different cortical areas and the representations of movement change during the different stages of learning and memory formation?

The minimum information principle and its application to neural code analysis.

The study of complex information processing systems requires appropriate theoretical tools to help unravel their underlying design principles. Information theory is one such tool, and has been utilized extensively in the study of the neural code. Although much progress has been made in information theoretic methodology, there is still no satisfying answer to the question: "What is the information that a given property of the neural population activity (e.

Differences in context and feedback result in different trajectories and adaptation strategies in reaching.

Computational models of motor control have often explained the straightness of horizontal planar reaching movements as a consequence of optimal control. Departure from rectilinearity is thus regarded as sub-optimal. Here we examine if subjects may instead select to make curved trajectories following adaptation to force fields and visuomotor rotations.

Neural basis of sensorimotor learning: modifying internal models.

The neural basis of the internal models used in sensorimotor transformations is beginning to be uncovered. Sensorimotor learning involves the modification of such models. Different stages of sensory-motor processing have been explored with a continuum of experimental tasks, from learning arbitrary associations of sensory cues to movements, to adapting to altered kinematic and dynamic environments.

Encoding of probabilistic rewarding and aversive events by pallidal and nigral neurons.

Previous studies have rarely tested whether the activity of high-frequency discharge (HFD) neurons of the basal ganglia (BG) is modulated by expectation, delivery, and omission of aversive events. Therefore the full value domain encoded by the BG network is still unknown. We studied the activity of HFD neurons of the globus pallidus external segment (GPe, n=310), internal segment (GPi, n=149), and substantia nigra pars reticulata (SNr, n=145) in two monkeys during a classical conditioning task with cues predicting the probability of food, neutral, or airpuff outcomes.