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.