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- Joshua H Goldwyn, Nikita S Imennov, Michael Famulare, Eric Shea-Brown
- Physical review. E, Statistical, nonlinear, and…
- 2011

The random transitions of ion channels between conducting and nonconducting states generate a source of internal fluctuations in a neuron, known as channel noise. The standard method for modeling the states of ion channels nonlinearly couples continuous-time Markov chains to a differential equation for voltage. Beginning with the work of R. F. Fox and Y.-N.… (More)

- Michael Famulare, Amit Kapoor
- PloS one
- 2015

Wild poliovirus type 3 (WPV3) has not been seen anywhere since the last case of WPV3-associated paralysis in Nigeria in November 2012. At the time of writing, the most recent case of wild poliovirus type 1 (WPV1) in Nigeria occurred in July 2014, and WPV1 has not been seen in Africa since a case in Somalia in August 2014. No cases associated with… (More)

- Brian Nils Lundstrom, Michael Famulare, Larry B. Sorensen, William J. Spain, Adrienne L. Fairhall
- Journal of Computational Neuroscience
- 2009

Neuronal responses are often characterized by the firing rate as a function of the stimulus mean, or the f-I curve. We introduce a novel classification of neurons into Types A, B-, and B+ according to how f-I curves are modulated by input fluctuations. In Type A neurons, the f-I curves display little sensitivity to input fluctuations when the mean current… (More)

- Rebecca A Mease, Michael Famulare, Julijana Gjorgjieva, William J Moody, Adrienne L Fairhall
- The Journal of neuroscience : the official…
- 2013

Adaptation is a fundamental computational motif in neural processing. To maintain stable perception in the face of rapidly shifting input, neural systems must extract relevant information from background fluctuations under many different contexts. Many neural systems are able to adjust their input-output properties such that an input's ability to trigger a… (More)

- Michael Famulare, Adrienne L. Fairhall
- Neural Computation
- 2010

The relationship between a neuron's complex inputs and its spiking output defines the neuron's coding strategy. This is frequently and effectively modeled phenomenologically by one or more linear filters that extract the components of the stimulus that are relevant for triggering spikes and a nonlinear function that relates stimulus to firing probability.… (More)

- Michael Famulare, Hao Hu
- International health
- 2015

BACKGROUND
Phylogeography improves our understanding of spatial epidemiology. However, application to practical problems requires choices among computational tools to balance statistical rigor, computational complexity, sensitivity to sampling strategy and interpretability.
METHODS
We introduce a fast, heuristic algorithm to reconstruct partially-observed… (More)

A neuron transforms its input into output spikes, and this transformation is the basic unit of computation in the nervous system. The spiking response of the neuron to a complex, time-varying input can be predicted from the detailed biophysical properties of the neuron, modeled as a deterministic nonlinear dynamical system. In the tradition of neural… (More)

The random transitions of ion channels between conducting and non-conducting states generate a source of internal fluctuations in a neuron, known as channel noise. The standard method for modeling fluctuations in the states of ion channels uses continuous-time Markov chains nonlinearly coupled to a differential equation for voltage. Beginning with the work… (More)

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