ArticleNature communications2023
Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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Who cites it
47 citing papers in PubMed.
- Protocol for analyzing slow cortical dynamics in mouse neuronal recordings.STAR protocols · 2026Article
- Neural timescales from a computational perspective.Nature neuroscience · 2026Review
- Self-Oscillatory Neuron-like Devices for Unconventional Computing Applications.Chemical reviews · 2026Review
- Selective control of prefrontal neural timescales by parietal cortex.Nature communications · 2026Article
- Critical Dynamics in the Association Cortex Predict Higher Intelligence in Typically Developing Children.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- iSTTC: A robust method for accurate estimation of intrinsic neural timescales from single-unit recordings.PLoS computational biology · 2026Article
- Article
- Exploiting correlations across trials and behavioral sessions to improve neural decoding.Neuron · 2026Article
- Neurons in auditory cortex integrate information within a constrained and context-invariant temporal window.Current biology : CB · 2025Article
- Cross-species evidence for the refinement of intrinsic neural timescales supporting executive system maturation through adolescence.bioRxiv : the preprint server for biology · 2025Article
- Intrinsic Neural Timescales Relate to Event-Related Activity-Key Role for Intracolumnar Connections.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Article
- From Speech Semantics to Brain Activity-Timescales Are Key in Their Information Transfer.Human brain mapping · 2025Article
- Adaptive proximity to criticality underlies amplification of ultra-slow fluctuations during free recall.PLoS computational biology · 2025Article
- A doubly stochastic renewal framework for partitioning spiking variability.Nature communications · 2025Article
- Exploiting correlations across trials and behavioral sessions to improve neural decoding.bioRxiv : the preprint server for biology · 2025Article
- Network dynamics underlying activity-timescale differences between cortical regions.bioRxiv : the preprint server for biology · 2025Article
- Neurons in auditory cortex integrate information within constrained temporal windows that are invariant to the stimulus context and information rate.bioRxiv : the preprint server for biology · 2025Article
- Sustained attention in attention-deficit subjects and the impact of binaural beat stimulation evaluated by behavior and EEG.Experimental brain research · 2025Article
- Brain-wide organization of intrinsic timescales at single-neuron resolution.bioRxiv : the preprint server for biology · 2025Article
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8 authors.
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Abstract
Intrinsic timescales characterize dynamics of endogenous fluctuations in neural activity. Variation of intrinsic timescales across the neocortex reflects functional specialization of cortical areas, but less is known about how intrinsic timescales change during cognitive tasks. We measured intrinsic timescales of local spiking activity within columns of area V4 in male monkeys performing spatial attention tasks. The ongoing spiking activity unfolded across at least two distinct timescales, fast and slow. The slow timescale increased when monkeys attended to the receptive fields location and correlated with reaction times. By evaluating predictions of several network models, we found that spatiotemporal correlations in V4 activity were best explained by the model in which multiple timescales arise from recurrent interactions shaped by spatially arranged connectivity, and attentional modulation of timescales results from an increase in the efficacy of recurrent interactions. Our results suggest that multiple timescales may arise from the spatial connectivity in the visual cortex and flexibly change with the cognitive state due to dynamic effective interactions between neurons.
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