Neural Engineering Framework

Neural Engineering Framework

The NEF is the main method we use for constructing neural simulations.

The NEF is the main method we use for constructing neural simulations. A quick overview of the framework can be found below. The book Neural Engineering from MIT Press is a full description of the framework. However, we are constantly working on improving and extending these methods.

Our group is developing a general computational framework for modeling the function of complex neural ensembles. The framework is grounded in the well- established principles of signal processing, statistical inference, and good engineering design. It provides a rational and robust strategy for simulating and evaluating the function of a wide variety of specific neural circuits. We are currently applying this framework to specific projects in sensory processing, motor control, and cognitive function.

Specific features of our modeling approach:

  • Provides a novel characterization of population-temporal coding that combines population vectors with linear decoding of neural spikes;
  • Unifies control (and dynamic systems) theory with biologically plausible, spiking models of neural function;
  • Provides a general way to generate circuits that have analytically determined synaptic weights that provide a desired functionality;
  • Promotes the formulation of specific hypotheses about circuit function and about key design constraints.

See the publications page for applications of the NEF.

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