TY - JOUR
T1 - Intrinsic neural timescales
T2 - temporal integration and segregation
AU - Wolff, Annemarie
AU - Berberian, Nareg
AU - Golesorkhi, Mehrshad
AU - Gomez-Pilar, Javier
AU - Zilio, Federico
AU - Northoff, Georg
N1 - Funding Information:
This research has received funding from the European Union's Horizon 2020 Framework Program for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2). G.N. is grateful for funding provided by the University Medical Research Fund (UMRF), University of Ottawa Brain and Mind Research Institute (uOBMRI), and Canadian Institutes of Health Research (CIHR). We are also grateful to CIHR, NSERC, and SHERRC for supporting our tri-council grant from the Canada-UK Artificial Intelligence (AI) Initiative ?The self as agent-environment nexus: crossing disciplinary boundaries to help human selves and anticipate artificial selves? (ES/T01279X/1) (together with Karl J. Friston from the UK). No interests are declared.
Funding Information:
This research has received funding from the European Union’s Horizon 2020 Framework Program for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2). G.N. is grateful for funding provided by the University Medical Research Fund (UMRF) , University of Ottawa Brain and Mind Research Institute (uOBMRI) , and Canadian Institutes of Health Research (CIHR) . We are also grateful to CIHR, NSERC, and SHERRC for supporting our tri-council grant from the Canada-UK Artificial Intelligence (AI) Initiative ‘The self as agent-environment nexus: crossing disciplinary boundaries to help human selves and anticipate artificial selves’ (ES/T01279X/1) (together with Karl J. Friston from the UK).
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2022
Y1 - 2022
N2 - We are continuously bombarded by external inputs of various timescales from the environment. How does the brain process this multitude of timescales? Recent resting state studies show a hierarchy of intrinsic neural timescales (INT) with a shorter duration in unimodal regions (e.g., visual cortex and auditory cortex) and a longer duration in transmodal regions (e.g., default mode network). This unimodal–transmodal hierarchy is present across acquisition modalities [electroencephalogram (EEG)/magnetoencephalogram (MEG) and fMRI] and can be found in different species and during a variety of different task states. Together, this suggests that the hierarchy of INT is central to the temporal integration (combining successive stimuli) and segregation (separating successive stimuli) of external inputs from the environment, leading to temporal segmentation and prediction in perception and cognition.
AB - We are continuously bombarded by external inputs of various timescales from the environment. How does the brain process this multitude of timescales? Recent resting state studies show a hierarchy of intrinsic neural timescales (INT) with a shorter duration in unimodal regions (e.g., visual cortex and auditory cortex) and a longer duration in transmodal regions (e.g., default mode network). This unimodal–transmodal hierarchy is present across acquisition modalities [electroencephalogram (EEG)/magnetoencephalogram (MEG) and fMRI] and can be found in different species and during a variety of different task states. Together, this suggests that the hierarchy of INT is central to the temporal integration (combining successive stimuli) and segregation (separating successive stimuli) of external inputs from the environment, leading to temporal segmentation and prediction in perception and cognition.
KW - intrinsic neural timescales
KW - predictive coding
KW - rest and task states
KW - temporal receptive windows
KW - temporal segregation
KW - transmodal–unimodal hierarchy
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U2 - 10.1016/j.tics.2021.11.007
DO - 10.1016/j.tics.2021.11.007
M3 - Review article
C2 - 34991988
AN - SCOPUS:85122271821
SN - 1364-6613
VL - 26
SP - 159
EP - 173
JO - Trends in Cognitive Sciences
JF - Trends in Cognitive Sciences
IS - 2
ER -