ArticleFrontiers in physiology2013
Time scales in cognitive neuroscience.
Article in Frontiers in physiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 55 citations in OpenAlex.
- A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Algorithmic Approaches for Assessing Multiscale Irreversibility in Time Series: Review and Comparison.Entropy (Basel, Switzerland) · 2025Review
- Disrupted working memory event-related network dynamics in multiple sclerosis.Communications biology · 2024Article
- Bayesian inference is facilitated by modular neural networks with different time scales.PLoS computational biology · 2024Article
- A data-driven network decomposition of the temporal, spatial, and spectral dynamics underpinning visual-verbal working memory processes.Communications biology · 2023Article
- Editorial: Advances in brain dynamics in the healthy and psychiatric disorders.Frontiers in psychiatry · 2023Article
- The time scales of irreversibility in spontaneous brain activity are altered in obsessive compulsive disorder.Frontiers in psychiatry · 2023Article
- Detection of tACS Entrainment Critically Depends on Epoch Length.Frontiers in cellular neuroscience · 2022Article
- Acute Effects of Various Movement Noise in Differential Learning of Rope Skipping on Brain and Heart Recovery Analyzed by Means of Multiscale Fuzzy Measure Entropy.Frontiers in behavioral neuroscience · 2022Article
- Principles and open questions in functional brain network reconstruction.Human brain mapping · 2021Review
- Time in Brain: How Biological Rhythms Impact on EEG Signals and on EEG-Derived Brain Networks.Frontiers in network physiology · 2021Article
- Long-range temporal correlations in scale-free neuromorphic networks.Network neuroscience (Cambridge, Mass.) · 2020Article
- Time Irreversibility of Resting-State Activity in the Healthy Brain and Pathology.Frontiers in physiology · 2019Article
- Gauging Functional Brain Activity: From Distinguishability to Accessibility.Frontiers in physiology · 2019Article
- Multi-day rhythms modulate seizure risk in epilepsy.Nature communications · 2018Article
- Bridging Waves and Crucial Events in the Dynamics of the Brain.Frontiers in physiology · 2018Article
- Chronic ambulatory electrocorticography from human speech cortex.NeuroImage · 2017Article
- Near-Critical Dynamics in Stimulus-Evoked Activity of the Human Brain and Its Relation to Spontaneous Resting-State Activity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2015Article
- Experimental control of scaling behavior: what is not fractal?Experimental brain research · 2015Article
- Traumatic brain injury detection using electrophysiological methods.Frontiers in human neuroscience · 2015Review
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cognitive neuroscience boils down to describing the ways in which cognitive function results from brain activity. In turn, brain activity shows complex fluctuations, with structure at many spatio-temporal scales. Exactly how cognitive function inherits the physical dimensions of neural activity, though, is highly non-trivial, and so are generally the corresponding dimensions of cognitive phenomena. As for any physical phenomenon, when studying cognitive function, the first conceptual step should be that of establishing its dimensions. Here, we provide a systematic presentation of the temporal aspects of task-related brain activity, from the smallest scale of the brain imaging technique's resolution, to the observation time of a given experiment, through the characteristic time scales of the process under study. We first review some standard assumptions on the temporal scales of cognitive function. In spite of their general use, these assumptions hold true to a high degree of approximation for many cognitive (viz. fast perceptual) processes, but have their limitations for other ones (e.g., thinking or reasoning). We define in a rigorous way the temporal quantifiers of cognition at all scales, and illustrate how they qualitatively vary as a function of the properties of the cognitive process under study. We propose that each phenomenon should be approached with its own set of theoretical, methodological and analytical tools. In particular, we show that when treating cognitive processes such as thinking or reasoning, complex properties of ongoing brain activity, which can be drastically simplified when considering fast (e.g., perceptual) processes, start playing a major role, and not only characterize the temporal properties of task-related brain activity, but also determine the conditions for proper observation of the phenomena. Finally, some implications on the design of experiments, data analyses, and the choice of recording parameters are discussed.
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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.