Abstract

Many recent studies describe learning-related changes in sensory and motor areas, but few have directly probed for improvement in neuronal coding after learning. We used information theory to analyze single-cell activity from the primary motor cortex of monkeys, before and after learning a local rotational visuomotor task. We show that after learning, neurons in the primary motor cortex conveyed more information about the direction of movement and did so with relation to their directional sensitivity. Similar to recent findings in sensory systems, this specific improvement in encoding is correlated with an increase in the slope of the neurons' tuning curve. We further demonstrate that the improved information after learning enables a more accurate reconstruction of movement direction from neuronal populations. Our results suggest that similar mechanisms govern learning in sensory and motor areas and provide further evidence for a tight relationship between the locality of learning and the properties of neurons; namely, cells only show plasticity if their preferred direction is near the training one. The results also suggest that simple learning tasks can enhance the performance of brain–machine interfaces.

Highlights

  • Practice can induce behavioral improvement that is often specific to the situation experienced during the practice sessions

  • A line of studies found that when monkeys perform reaching movements and adapt to directional errors induced by force fields, primary motor cortex (M1) cells shift their preferred direction (PD) in about the same way as for the muscle activity needed to perform the task (Gandolfo et al 2000; Li et al 2001; Padoa-Schioppa et al 2002)

  • We have recently shown that learning a local rotational visuomotor task can induce an elevation in the activity of single neurons in M1 (Paz et al 2003) and that these changes are observed only in a specific subpopulation of neurons, those with a PD close to the movement direction used during the learning

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Summary

Introduction

Practice can induce behavioral improvement that is often specific to the situation experienced during the practice sessions (or ‘‘training’’) Such findings suggest that changes occur in neurons with fine selectivity (or ‘‘tuning’’) for the stimuli experienced or the movements made during training. They use the full distribution (estimated from the data) of neuronal activity and do not assume any specific shape of the tuning curve or noise distribution. This allows for a more fine-tuned examination of learning-related changes. They provide a measure as to how well different directions can be differentiated, based on neuronal activity.

Results
Discussion
Materials and Methods
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