Previous studies have shown that synchronized beta frequency (14 -30 Hz) oscillations in the primary motor cortex are involved in maintaining steady contractions of contralateral arm and hand muscles. However, little is known about the role of postcentral cortical areas in motor maintenance and their patterns of interaction with motor cortex. We investigated the functional relations of beta-synchronized neuronal assemblies in pre-and postcentral areas of two monkeys as they pressed a hand lever during the wait period of a visual discrimination task. By using power and coherence spectral analysis, we identified a beta-synchronized largescale network linking pre-and postcentral areas. We then used Granger causality spectra to measure directional influences among recording sites. In both monkeys, strong Granger causal influences were observed from primary somatosensory cortex to both motor cortex and inferior posterior parietal cortex, with the latter area also exerting Granger causal influences on motor cortex. Granger causal influences from motor cortex to postcentral sites, however, were weak in one monkey and not observed in the other. These results are the first, to our knowledge, to demonstrate in awake monkeys that synchronized beta oscillations bind multiple sensorimotor areas into a large-scale network during motor maintenance behavior and carry Granger causal influences from primary somatosensory and inferior posterior parietal cortices to motor cortex.cerebral cortex ͉ motor maintenance ͉ parietal ͉ local field potential ͉ coherence O scillatory activity in the beta frequency range (14-30 Hz) is widely observed in sensorimotor cortex in relation to motor behavior in both humans (1, 2) and nonhuman primates (3-6). Specifically, beta oscillations in monkeys appear in local field potential (LFP) and spiking activity during tactile exploratory forelimb movements (4, 7, 8), movement preparation (5, 6, 9), and steady-state isometric contractions (10). Beta oscillatory activity is often observed to be synchronized between different parts of sensorimotor cortex (4,5,7,(9)(10)(11), between motor cortical LFPs and descending pyramidal tract neuron discharge (10, 12), between single motor units (13,14), and between motor cortical activity and muscle activity (1,4,10,12,15,16).Although the role of beta oscillations in the outflow of activity from motor cortex to muscles is relatively well characterized for certain types of behavior, the relation of beta oscillations in postcentral areas and motor cortex remains poorly understood. This article addresses the functional relations between beta oscillations in pre-and postcentral cortical areas in premovement motor maintenance behavior. It has long been proposed that behavior of this type depends on a corticoperipheral cortical sensorimotor loop (17, 18), and more recently that this loop is supported by oscillatory neuronal activity (19). Reports of beta oscillations in both somatosensory and motor cortices during premovement maintenance behavior (3, 5, 6, 9), taken toge...

Since the first descriptions of sensorimotor rhythms by Berger (1929) and by Jasper and Penfield (1949), the potential role of beta oscillations (~13-30 Hz) in the brain has been intensely investigated. We start this review by showing that experimental studies in humans and monkeys have reached a consensus on the facts that sensorimotor beta power is low during movement, transiently increases after movement end (the "beta rebound") and tonically increases during object grasping. Recently, a new surge of studies exploiting more complex sensorimotor tasks including multiple events, such as instructed delay tasks, reveal novel characteristics of beta oscillatory activity. We therefore proceed by critically reviewing also this literature to understand whether modulations of beta oscillations in task epochs other than those during and after movement are consistent across studies, and whether they can be reconciled with a role for beta oscillations in sensorimotor transmission. We indeed find that there are additional processes that also strongly affect sensorimotor beta oscillations, such as visual cue anticipation and processing, fitting with the view that beta oscillations reflect heightened sensorimotor transmission beyond somatosensation. However, there are differences among studies, which may be interpreted more readily if we assume multiple processes, whose effects on the overall measured beta power overlap in time. We conclude that beta oscillations observed in sensorimotor cortex may serve large-scale communication between sensorimotor and other areas and the periphery.

The premotor cortex is well known for its role in motor planning. In addition, recent studies have shown that it is also involved in nonmotor functions such as attention and memory, a notion derived from both animal neurophysiology and human functional imaging. The present study is an attempt to bridge the gap between these experimental techniques in the human brain, using a task initially designed to dissociate attention from intention in the monkey, and recently adapted for a functional magnetic resonance imaging (fMRI) study [Simon, S.R., Meunier, M., Piettre, L., Berardi, A.M., Segebarth, C.M., Boussaoud, D. (2002). Task-related changes in cortical synchronization are spatially coincident with the hemodynamic response. Neuroimage, 16,. Intracranial EEG was recorded from the cortical regions preferentially active in the spatial attention and/or working memory task and those involved in motor intention. The results show that, among the different intracranial EEG responses, only the high gamma frequency (60 -200 Hz) oscillatory activity both dissociates attention/ memory from motor intention and spatially colocalizes with the fMRIidentified premotor substrates of these two functions. This finding provides electrophysiological confirmation that the human premotor cortex is involved in spatial attention and/or working memory. Additionally, it provides timely support to the idea that high gamma frequency oscillations are involved in the cascade of neural processes underlying the hemodynamic responses measured with fMRI [Logothetis, N.K., Pauls, J., Augath, M., Trinath, T. and Oeltermann, A. (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature, 412,, and suggests a functional selectivity of the gamma oscillations that could be critical for future EEG investigations, whether experimental or clinical. D

Sports psychology suggests that mental rehearsal facilitates physical practice in athletes and clinical rehabilitation attempts to use mental rehearsal to restore motor function in hemiplegic patients. Our aim was to examine whether mental rehearsal is equivalent to physical learning, and to determine the optimal proportions of real execution and rehearsal. Subjects were asked to grasp an object and insert it into an adapted slot. One group (G0) practiced the task only by physical execution (240 trials); three groups imagined performing the task in different rates of trials (25%, G25; 50%, G50; 75%, G75), and physically executed movements for the remaining trials; a fourth, control group imagined a visual rotation task in 75% of the trials and then performed the same motor task as the others groups. Movement time (MT) was compared for the first and last physical trials, together with other key trials, across groups. All groups learned, suggesting that mental rehearsal is equivalent to physical motor learning. More importantly, when subjects rehearsed the task for large numbers of trials (G50 and G75), the MT of the first executed trial was significantly shorter than the first executed trial in the physical group (G0), indicating that mental practice is better than no practice at all. Comparison of the first executed trial in G25, G50 and G75 with the corresponding trials in G0 (61, 121 and 181 trials), showed equivalence between mental and physical practice. At the end of training, the performance was much better with high rates of mental practice (G50/G75) compared to physical practice alone (G0), especially when the task was difficult. These findings confirm that mental rehearsal can be beneficial for motor learning and suggest that imagery might be used to supplement or partly replace physical practice in clinical rehabilitation.

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Current learning theory provides a comprehensive description of how humans and other animals learn, and places behavioral flexibility and automaticity at heart of adaptive behaviors. However, the computations supporting the interactions between goal-directed and habitual decision-making systems are still poorly understood. Previous functional magnetic resonance imaging (fMRI) results suggest that the brain hosts complementary computations that may differentially support goal-directed and habitual processes in the form of a dynamical interplay rather than a serial recruitment of strategies. To better elucidate the computations underlying flexible behavior, we develop a dual-system computational model that can predict both performance (i.e., participants' choices) and modulations in reaction times during learning of a stimulus–response association task. The habitual system is modeled with a simple Q-Learning algorithm (QL). For the goal-directed system, we propose a new Bayesian Working Memory (BWM) model that searches for information in the history of previous trials in order to minimize Shannon entropy. We propose a model for QL and BWM coordination such that the expensive memory manipulation is under control of, among others, the level of convergence of the habitual learning. We test the ability of QL or BWM alone to explain human behavior, and compare them with the performance of model combinations, to highlight the need for such combinations to explain behavior. Two of the tested combination models are derived from the literature, and the latter being our new proposal. In conclusion, all subjects were better explained by model combinations, and the majority of them are explained by our new coordination proposal.

Functional magnetic resonance imaging (fMRI) exploits blood-oxygen-level-dependent (BOLD) contrasts to map neural activity associated with a variety of brain functions including sensory processing, motor control, and cognitive and emotional functions. The general linear model (GLM) approach is used to reveal task-related brain areas by searching for linear correlations between the fMRI time course and a reference model. One of the limitations of the GLM approach is the assumption that the covariance across neighbouring voxels is not informative about the cognitive function under examination. Multivoxel pattern analysis (MVPA) represents a promising technique that is currently exploited to investigate the information contained in distributed patterns of neural activity to infer the functional role of brain areas and networks. MVPA is considered as a supervised classification problem where a classifier attempts to capture the relationships between spatial pattern of fMRI activity and experimental conditions. In this paper , we review MVPA and describe the mathematical basis of the classification algorithms used for decoding fMRI signals, such as support vector machines (SVMs). In addition, we describe the workflow of processing steps required for MVPA such as feature selection, dimensionality reduction, cross-validation, and classifier performance estimation based on receiver operating characteristic (ROC) curves.

In order to assess the role played by area V6A in visuomotor control, two adult green monkeys ( Cercopithecus aethiops) were subjected to small, bilateral lesions in the anterior bank of the parieto-occipital sulcus. Before and after the lesions, monkeys were tested for naturally designed reaching, grasping and picking-up pieces of food from various positions on a plate and from a differently oriented narrow slit. All movements were recorded with closed circuit TV and analysed offline on a single-photogram basis for defective reaching and wrist orientation. V6A lesions provoked parietal weakness, reluctance to move, and specific deficits in reaching, wrist orientation and grasping. Recovery from the observed deficits was rapid, even after a second, contralateral lesion was given, creating a bilateral lesion. Thus, together with previous anatomical and electrophysiological data, these results directly support the hypothesis that area V6A is part of the network involved in the control of reaching movements and wrist orientation.