ReviewExperimental brain research2011
Nonrenewal spike train statistics: causes and functional consequences on neural coding.
Review in Experimental brain research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 28 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
28 citing papers in PubMed.
- A quality measure for repeating multiple-unit spike patterns.Biological cybernetics · 2026Article
- In vivo neural activity of electrosensory pyramidal cells: Biophysical characterization and phenomenological modeling.PLoS computational biology · 2025Article
- An integrate-and-fire approach to CaBiophysical journal · 2023Article
- A dynamic spike threshold with correlated noise predicts observed patterns of negative interval correlations in neuronal spike trains.Biological cybernetics · 2022Article
- Mean-return-time phase of a stochastic oscillator provides an approximate renewal description for the associated point process.Biological cybernetics · 2022Review
- Interspike interval correlations in neuron models with adaptation and correlated noise.PLoS computational biology · 2021Article
- Information filtering by coincidence detection of synchronous population output: analytical approaches to the coherence function of a two-stage neural system.Biological cybernetics · 2020Article
- Fano Factor: A Potentially Useful Information.Frontiers in computational neuroscience · 2020Article
- Mathematical Modeling and Analyses of Interspike-Intervals of Spontaneous Activity in Afferent Neurons of the Zebrafish Lateral Line.Scientific reports · 2018Article
- SK channel subtypes enable parallel optimized coding of behaviorally relevant stimulus attributes: A review.Channels (Austin, Tex.) · 2017Review
- Background firing in the auditory midbrain of the frog.IBRO reports · 2017Article
- Multi-scale detection of rate changes in spike trains with weak dependencies.Journal of computational neuroscience · 2017Article
- Social context differentially modulates activity of two interneuron populations in an avian basal ganglia nucleus.Journal of neurophysiology · 2016Article
- Burst Firing in the Electrosensory System of Gymnotiform Weakly Electric Fish: Mechanisms and Functional Roles.Frontiers in computational neuroscience · 2016Review
- Cardiac Arrest-Induced Global Brain Hypoxia-Ischemia during Development Affects Spontaneous Activity Organization in Rat Sensory and Motor Thalamocortical Circuits during Adulthood.Frontiers in neural circuits · 2016Article
- Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation.Journal of computational neuroscience · 2015Article
- Coding stimulus amplitude by correlated neural activity.Physical review. E, Statistical, nonlinear, and soft matter physics · 2015Article
- A model of synaptic vesicle-pool depletion and replenishment can account for the interspike interval distributions and nonrenewal properties of spontaneous spike trains of auditory-nerve fibers.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2014Article
- Temporal whitening by power-law adaptation in neocortical neurons.Nature neuroscience · 2013Article
- Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.PloS one · 2013Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
Abstract
Many neurons display significant patterning in their spike trains (e.g. oscillations, bursting), and there is accumulating evidence that information is contained in these patterns. In many cases, this patterning is caused by intrinsic mechanisms rather than external signals. In this review, we focus on spiking activity that displays nonrenewal statistics (i.e. memory that persists from one firing to the next). Such statistics are seen in both peripheral and central neurons and appear to be ubiquitous in the CNS. We review the principal mechanisms that can give rise to nonrenewal spike train statistics. These are separated into intrinsic mechanisms such as relative refractoriness and network mechanisms such as coupling with delayed inhibitory feedback. Next, we focus on the functional roles for nonrenewal spike train statistics. These can either increase or decrease information transmission. We also focus on how such statistics can give rise to an optimal integration timescale at which spike train variability is minimal and how this might be exploited by sensory systems to maximize the detection of weak signals. We finish by pointing out some interesting future directions for research in this area. In particular, we explore the interesting possibility that synaptic dynamics might be matched with the nonrenewal spiking statistics of presynaptic spike trains in order to further improve information transmission.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.