641 research outputs found
Low-discrepancy sequences for piecewise smooth functions on the two-dimensional torus
We produce explicit low-discrepancy infinite sequences which can be used to
approximate the integral of a smooth periodic function restricted to a convex
domain with positive curvature in R^2. The proof depends on simultaneous
diophantine approximation and a general version of the Erdos-Turan inequality.Comment: 14 pages, 2 figure
Structured chaos shapes spike-response noise entropy in balanced neural networks
Large networks of sparsely coupled, excitatory and inhibitory cells occur
throughout the brain. A striking feature of these networks is that they are
chaotic. How does this chaos manifest in the neural code? Specifically, how
variable are the spike patterns that such a network produces in response to an
input signal? To answer this, we derive a bound for the entropy of multi-cell
spike pattern distributions in large recurrent networks of spiking neurons
responding to fluctuating inputs. The analysis is based on results from random
dynamical systems theory and is complimented by detailed numerical simulations.
We find that the spike pattern entropy is an order of magnitude lower than what
would be extrapolated from single cells. This holds despite the fact that
network coupling becomes vanishingly sparse as network size grows -- a
phenomenon that depends on ``extensive chaos," as previously discovered for
balanced networks without stimulus drive. Moreover, we show how spike pattern
entropy is controlled by temporal features of the inputs. Our findings provide
insight into how neural networks may encode stimuli in the presence of
inherently chaotic dynamics.Comment: 9 pages, 5 figure
- …