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.