Eric Shea-Brown who has come all the way from U of Washington will be speaking about:
A mechanistic approach to multi-spike patterns in neural circuits:
There is a combinatorial explosion in the number of possible activity patterns in neural circuits of increasing size, enabling an enormous complexity in which patterns occur and how this depends on incoming stimuli. However, recent experiments show that this complexity is not always accessed -- the activity of many neural populations is remarkably well captured by simpler descriptions that rely only on the activity of single neurons and neuron pairs.
What is especially intriguing is that these pairwise descriptions succeed even in cases where circuit architecture seems likely to create a far more complex set of outputs. We seek a mechanistic understanding of this phenomenon -- and predictions for when it will break down -- based on simple models of spike generation, circuit connectivity, and stimuli. This also offers a chance to explore how much (and how little) beyond-pairwise spike patterns can matter to coding in different circuits.
As a specific application, we consider the empirical success of pairwise models in capturing the activity of ON-parasol retinal ganglion cells. We first use intracellular recordings to fully constrain a model of the underlying circuit dynamics. Our theory then provides an explanation for experimental findings based on ON-parasol stimulus filtering and spike generation properties.
This is joint work with Andrea Barreiro, Julijana Gjorgjieva, and Fred Rieke.