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Eric Shea-Brown

 

Thursday 2nd June 2016

Time: 4.00pm

 

Ground Floor Seminar Room

25 Howland Street, London, W1T 4JG

 

Assembling collective activity in neural circuits

There is an avalanche of new data on the brain's connectivity and on its
coherent dynamics. Many of us are asking: how does the the former lead to
the latter? In our approach, we start with basic statistics of a network’s
dynamics, such as its coherence (spike time correlations) or its average
response to time-dependent inputs. Then, we use graphical and point process
methods to isolate the contribution of successively more-complex network
features. We show how these network features can be efficiently combined,
yielding a set of low-order graph statistics we name "motif
cumulants." These can be sampled experimentally, and appear to contain the
necessary information to predict overall coherence and response dynamics in
a neural population.