ArticleJournal of neurophysiology2009
Wiener-Volterra characterization of neurons in primary auditory cortex using poisson-distributed impulse train inputs.
Article in Journal of neurophysiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- Incorporating behavioral and sensory context into spectro-temporal models of auditory encoding.Hearing research · 2018Review
- Computational Modeling of Neurotransmitter Release Evoked by Electrical Stimulation: Nonlinear Approaches to Predicting Stimulation-Evoked Dopamine Release.ACS chemical neuroscience · 2017Article
- Input-Specific Gain Modulation by Local Sensory Context Shapes Cortical and Thalamic Responses to Complex Sounds.Neuron · 2016Article
- Integration over multiple timescales in primary auditory cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2013Article
- Frequency response areas in the inferior colliculus: nonlinearity and binaural interaction.Frontiers in neural circuits · 2013Article
- Free energy and dendritic self-organization.Frontiers in systems neuroscience · 2011Article
- Nonlinear cross-frequency interactions in primary auditory cortex spectrotemporal receptive fields: a Wiener-Volterra analysis.Journal of computational neuroscience · 2010Article
- Complex spectral interactions encoded by auditory cortical neurons: relationship between bandwidth and pattern.Frontiers in systems neuroscience · 2010Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An extension of the Wiener-Volterra theory to a Poisson-distributed impulse train input was used to characterize the temporal response properties of neurons in primary auditory cortex (AI) of the ketamine-anesthetized cat. Both first- and second-order "Poisson-Wiener" (PW) models were tested on their predictions of temporal modulation transfer functions (tMTFs), which were derived from extracellular spike responses to periodic click trains with click repetition rates of 2-64 Hz. Second-order (i.e., nonlinear) PW fits to the measured tMTFs could be described as very good in a majority of cases (e.g., predictability >or=80%) and were almost always superior to first-order (i.e., linear) fits. In all sampled neurons, second-order PW kernels showed strong compressive nonlinearities (i.e., a depression of the impulse response) but never expansive nonlinearities (i.e., a facilitation of the impulse response). In neurons with low-pass tMTFs, the depression decayed exponentially with the interstimulus lag, whereas in neurons with band-pass tMTFs, the depression was typically double-peaked, and the second peak occurred at a lag that correlated with the neuron's best modulation frequency. It appears that modulation-tuning in AI arises in part from an interplay of two nonlinear processes with distinct time courses.
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