Saurabh Vyas, Matthew D Golub, David Sussillo, Krishna V Shenoy
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Significant experimental, computational, and theoretical work has identified rich structure within the coordinated activity of interconnected neural populations. An emerging challenge now is to uncover the nature of the associated computations, how they are implemented, and what role they play in driving behavior. We term this computation through neural population dynamics. If successful, this framework will reveal general motifs of neural population activity and quantitatively describe how neural population dynamics implement computations necessary for driving goal-directed behavior. Here, we start with a mathematical primer on dynamical systems theory and analytical tools necessary to apply this perspective to experimental data. Next, we highlight some recent discoveries resulting from successful application of dynamical systems. We focus on studies spanning motor control, timing, decision-making, and working memory. Finally, we briefly discuss promising recent lines of investigation and future directions for the computation through neural population dynamics framework.
期刊介绍:
The Annual Review of Neuroscience is a well-established and comprehensive journal in the field of neuroscience, with a rich history and a commitment to open access and scholarly communication. The journal has been in publication since 1978, providing a long-standing source of authoritative reviews in neuroscience.
The Annual Review of Neuroscience encompasses a wide range of topics within neuroscience, including but not limited to: Molecular and cellular neuroscience, Neurogenetics, Developmental neuroscience, Neural plasticity and repair, Systems neuroscience, Cognitive neuroscience, Behavioral neuroscience, Neurobiology of disease. Occasionally, the journal also features reviews on the history of neuroscience and ethical considerations within the field.