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date: 18 February 2019

Abstract and Keywords

This article describes the neural engineering framework (NEF), a systematic approach to studying neural systems that has collected and extended a set of consistent methods that are highly general. The NEF draws heavily on past work in theoretical neuroscience, integrating work on neural coding, population representation, and neural dynamics to enable the construction of large-scale biologically plausible neural simulations. It is based on the principles that neural representations defined by a combination of nonlinear encoding and optimal linear decoding and that neural dynamics are characterized by considering neural representations as control theoretic state variables.

Keywords: neural engineering framework, neural systems, theoretical neuroscience, neural coding, population representation, neural dynamics, neural simulations

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