Publications by authors named "Brett A Schmerl"
Article Synopsis
- Complex networks can be analyzed by counting subgraphs in which nodes participate, leading to the concept of motif-role fingerprints that distinguish between structural and functional versions of these counts.
- A mathematical approach allows for transforming functional motif-role fingerprints, derived from directed adjacency matrices, into unique structural ones using a specific conversion matrix.
- This methodology could enhance metrics for analyzing complex networks, particularly in areas like neuronal connectomes, anomaly detection, and network similarities, with practical applications demonstrated through provided Matlab code.
Channel-noise-induced stochastic facilitation in an auditory brainstem neuron model.
Phys Rev E Stat Nonlin Soft Matter Phys
November 2013
Neuronal membrane potentials fluctuate stochastically due to conductance changes caused by random transitions between the open and closed states of ion channels. Although it has previously been shown that channel noise can nontrivially affect neuronal dynamics, it is unknown whether ion-channel noise is strong enough to act as a noise source for hypothesized noise-enhanced information processing in real neuronal systems, i.e.
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