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Rhythmic sampling revisited: Experimental paradigms and neural mechanisms
Author(s) -
Kienitz Ricardo,
Schmid Michael C.,
Dugué Laura
Publication year - 2022
Publication title -
european journal of neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.346
H-Index - 206
eISSN - 1460-9568
pISSN - 0953-816X
DOI - 10.1111/ejn.15489
Subject(s) - covert , rhythm , neuroscience , sensory system , neurophysiology , psychology , cognition , sampling (signal processing) , experience sampling method , cognitive psychology , human brain , computer science , medicine , social psychology , philosophy , linguistics , filter (signal processing) , computer vision
Sampling of information is thought to be an important aspect of explorative behaviour. Evidence for it has been gained in behavioural assessments of a variety of overt and covert cognitive domains, including sensation, attention, memory, eye movements and dexterity. A common aspect across many findings is that sampling tends to exhibit a rhythmicity at low frequencies (theta, 4–8 Hz; alpha, 9–12 Hz). Neurophysiological investigations in a wide range of species, including rodents, non‐human primates and humans have demonstrated the presence of sampling related neural oscillations in a number of brain areas ranging from early sensory cortex, hippocampus to high‐level cognitive areas. However, to assess whether rhythmic sampling represents a general aspect of exploratory behaviour one must critically evaluate the task parameters, and their potential link with neural oscillations. Here we focus on sampling during attentive vision to present an overview on the experimental conditions that are used to investigate rhythmic sampling and associated oscillatory brain activity in this domain. This review aims to (1) provide guidelines to efficiently quantify behavioural rhythms, (2) compare results from human and non‐human primate studies and (3) argue that the underlying neural mechanisms of sampling can co‐occur in both sensory and high‐level areas.

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