A collaboration page for work with Eric Shea-Brown's lab at the University of Washington.

Question: What is the character of network correlations in learned and NEF-generated networks of spiking LIF neurons.

Approach:

Simulate a few basic networks (i.e. communication channel and integrator), and examine the correlational structure. Compare and contrast the NEF weights with learned weights.

• We can do the simulations of the networks (i.e. generate files with spike times over populations of cells)
• Eric's group has good methods for doing the correlational analyses.

Points to discuss:

Parameters of the simulations

• How long should runs be? 1000s
• How many neurons in the network? 100/layer
• What kinds of cells and parameters? LIF; 20ms membrane; 2ms refractory; max firing 10-100hz;
• What kind of input? Bandlimited white noise, to 30hz (?)

Other

Extensions:

• If there is a mismatch, can we enforce correlational structure while generating desired weights in the NEF?