Negative correlations in the sequential evolution of interspike intervals (ISIs) are a signature of memory in neuronal spiketrains. They provide coding benefits including firingrate stabilization, improved detectability of weak sensory signals, and enhanced transmission of information by improving signaltonoise ratio. Primary electrosensory afferent spiketrains in weakly electric fish fall into two categories based on the pattern of ISI correlations: nonbursting units have negative correlations which remain negative but decay to zero with increasing lags (Type I ISI correlations), and bursting units have oscillatory (alternating sign) correlation which damp to zero with increasing lags (Type II ISI correlations). Here, we predict and match observed ISI correlations in these afferents using a stochastic dynamic threshold model. We determine the ISI correlation function as a function of an arbitrary discrete noise correlation function
Complete theoretical understanding of the most complex superconductors requires a detailed knowledge of the symmetry of the superconducting energygap
 Award ID(s):
 1849751
 Publication Date:
 NSFPAR ID:
 10209425
 Journal Name:
 npj Quantum Materials
 Volume:
 6
 Issue:
 1
 ISSN:
 23974648
 Publisher:
 Nature Publishing Group
 Sponsoring Org:
 National Science Foundation
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