Long-term stability of single neuron activity in the motor system.

How an established behavior is retained and consistently produced by a nervous system in constant flux remains a mystery. One possible solution to ensure long-term stability in motor output is to fix the activity patterns of single neurons in the relevant circuits. Alternatively, activity in single cells could drift over time provided that the population dynamics are constrained to produce the same behavior.

Learning-induced changes in the neural circuits underlying motor sequence execution.

As the old adage goes: practice makes perfect. Yet, the neural mechanisms by which rote repetition transforms a halting behavior into a fluid, effortless, and "automatic" action are not well understood. Here we consider the possibility that well-practiced motor sequences, which initially rely on higher-level decision-making circuits, become wholly specified in lower-level control circuits.

Movement Decomposition in the Primary Motor Cortex.

A complex action can be described as the composition of a set of elementary movements. While both kinematic and dynamic elements have been proposed to compose complex actions, the structure of movement decomposition and its neural representation remain unknown. Here, we examined movement decomposition by modeling the temporal dynamics of neural populations in the primary motor cortex of macaque monkeys performing forelimb reaching movements.

Micrographia, much beyond the writer's hand.

Introduction: This review on micrographia aims to draw the clinician's attention to non-Parkinsonian etiologies, provide clues to differential diagnosis, and summarize current knowledge on the phenomenology, etiology, and mechanisms underlying micrographia.

Methods: A systematic review of the existing literature was performed.

Results: Micrographia, namely small sized handwriting has long been attributed to Parkinson's disease.

Scale-invariant movement encoding in the human motor system.

How does the human motor system encode our incredibly diverse motor repertoire in an efficient manner? One possible way of encoding movements efficiently is to represent them according to their shape/trajectory without regard to their size, by using neural populations that are invariant across scale. To examine this hypothesis, we recorded movement kinematics and functional magnetic resonance imaging (fMRI) while subjects wrote three letters in two different scales. A classification algorithm was trained to identify each letter according to its associated voxel-by-voxel response pattern in each of several motor areas.