Memories for habits and skills ("implicit or procedural memory") and memories for facts ("explicit or episodic memory") are built up in different brain systems and are vulnerable to different neurodegenerative disorders in humans. So that the striatum-based mechanisms underlying habit formation could be studied, chronic recordings from ensembles of striatal neurons were made with multiple tetrodes as rats learned a T-maze procedural task. Large and widely distributed changes in the neuronal activity patterns occurred in the sensorimotor striatum during behavioral acquisition, culminating in task-related activity emphasizing the beginning and end of the automatized procedure. The new ensemble patterns remained stable during weeks of subsequent performance of the same task. These results suggest that the encoding of action in the sensorimotor striatum undergoes dynamic reorganization as habit learning proceeds.

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There are situations in which one would like to know a good sequence of rangeimage views for obtaining a complete model of a scene. This paper describes two algorithms which use partial octree models to determine the "best" next view to take.

Harmonic functions are solutions to Laplace's Equation. As noted in a previous paper, they can be used to advantage for potential-eld path planning, since they do not exhibit spurious local minima. In this paper, harmonic functions are shown to have a n umber of other properties (including completeness) which are essential to robotics applications. These properties strongly recommend harmonic functions as a mechanism for robot control.

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