Correlation between neural spike trains increases with firing rate
Abstract
Populations of neurons in the retina, olfactory system, visual and somatosensory thalamus, and several cortical regions show temporal correlation between the discharge times of their action potentials (spike trains). Correlated firing has been linked to stimulus encoding, attention, stimulus discrimination, and motor behaviour. Nevertheless, the mechanisms underlying correlated spiking are poorly understood, and its coding implications are still debated. It is not clear, for instance, whether correlations between the discharges of two neurons are determined solely by the correlation between their afferent currents, or whether they also depend on the mean and variance of the input. We addressed this question by computing the spike train correlation coefficient of unconnected pairs of in vitro cortical neurons receiving correlated inputs. Notably, even when the input correlation remained fixed, the spike train output correlation increased with the firing rate, but was largely independent of spike train variability. With a combination of analytical techniques and numerical simulations using 'integrate-and-fire' neuron models we show that this relationship between output correlation and firing rate is robust to input heterogeneities. Finally, this overlooked relationship is replicated by a standard threshold-linear model, demonstrating the universality of the result. This connection between the rate and correlation of spiking activity links two fundamental features of the neural code.
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The degree to which the synaptic input underlying Vm fluctuations is temporally correlated can vary with overall drive to a network or with firing rates and is regulated by behavioural state transitions during wakefulness.
“The degree to which the synaptic input underlying Vm fluctuations is temporally correlated can vary with overall drive to a network or with firing rates70 and is regulated by behavioural state transitions during wakefulness29,71–74.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [70]
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- Authors
- de la Rocha, J., Doiron, B., Shea-Brown, E., Josić, K., & Reyes, A.
- Affiliations
- University of Pittsburgh (US)
- New York University (US)
- Corresponding author
- Doiron, Brent
- Venue
- Nature
- Published
- 2007-08-16
- Volume
- 448
- Issue
- 7155
- Pages
- 802-806
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2131423842
- Cited by
- 644
- References
- 30
- Citations by year
- 2026: 16 · 2025: 34 · 2024: 25 · 2023: 21 · 2022: 25 · 2021: 23 · 2020: 26 · 2019: 28 · 2018: 18 · 2017: 43 · 2016: 47 · 2015: 54 · 2014: 52 · 2013: 47 · 2012: 42
- FWCI
- 17.15
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- spike train correlations, firing rate, neural coding, correlated firing, integrate-and-fire neuron model, spike train variability, population coding
- MeSH terms
- Action Potentials, Animals, Auditory Cortex, Models, Neurological, Neurons, Somatosensory Cortex, Time Factors, Mice
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