Multidimensional sequence learning in patients with focal basal ganglia lesions

Abstract INTRODUCTION Learning a motor skill involves organizing a series of complex movements into sequences that can be executed efficiently and reproducibly. Once learned, these sequences generate lasting changes in motor control circuits. Animal studies suggest that the interaction between the motor cortex and basal ganglia is critically involved in motor sequence learning. In particular, the cortical neurons can encode sequence-specific information that is stored subcortically once the sequence is learned. However, how motor sequence learning in humans is not well understood. In disease states like Parkinson disease, where dopaminergic denervation to the striatum affects motor functions and motor learning, understanding the circuit mechanisms of motor learning dysfunction is critical for improving motor rehabilitation. METHODS We study the neural basis of motor sequence learning in 4 Parkinson patients by performing chronic recordings of field potentials from the motor cortex (1 patient) or prefrontal cortex (3 patients) and the pallidum while patients performed the serial reaction time task (SRTT). RESULTS All patients exhibited improvements in motor sequence learning in the SRTT. There is task-modulated increase in theta (4-8 Hz) oscillations during sequence-specific trials in the motor cortex. The pallidum in all patients showed similar increases in theta oscillation at the start of motor sequences. CONCLUSION This is the first illustration of cortical basal ganglia network interactions recorded from the human brain during motor sequence learning. Increases in cortical and subcortical theta oscillations may provide a mechanism for encoding of movement sequences.

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Contributions of the basal ganglia to action sequence learning and performance

10.31234/osf.io/qp247 ◽

2019 ◽

Author(s):

Eric Garr

Keyword(s):

Reinforcement Learning ◽

Basal Ganglia ◽

Sequence Learning ◽

Computational Framework ◽

Action Sequence ◽

Action Sequences ◽

The Hierarchical Structure ◽

And Performance ◽

Action Sequencing

Animals engage in intricately woven and choreographed action sequences that are constructed from trial-and-error learning. The mechanisms by which the brain links together individual actions which are later recalled as fluid chains of behavior are not fully understood, but there is broad consensus that the basal ganglia play a crucial role in this process. This paper presents a comprehensive review of the role of the basal ganglia in action sequencing, with a focus on whether the computational framework of reinforcement learning can capture key behavioral features of sequencing and the neural mechanisms that underlie them. While a simple neurocomputational model of reinforcement learning can capture key features of action sequence learning, this model is not sufficient to capture goal-directed control of sequences or their hierarchical representation. The hierarchical structure of action sequences, in particular, poses a challenge for building better models of action sequencing, and it is in this regard that further investigations into basal ganglia information processing may be informative.

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