The brain displays intrinsic durations in its own spontaneous activity - Intrinsic Neural Timescales (INTs). INTs are hierarchically organized, with shorter durations within unimodal regions and longer intervals in multimodal domains. Despite significant progress, it's currently not known whether the unimodal-multimodal hierarchical organization undergoes recurrent changes itself - consistent with the existence of a dynamic repertoire of INT topographies. To this aim, we characterized the dynamics of topographic INT states by clustering the dynamic ACW-0 matrices in two different datasets: the source-reconstructed HCP resting-state MEG dataset, and a hd-EEG resting-state dataset, composed of healthy individuals and people with disorders of consciousness (DoCs). We found that healthy subjects display dynamic transitions between different INT states, which exhibit changing degrees of uni-transmodal cortical hierarchies. These dynamic transitions show non-random behavior, with moderate degrees of unpredictability and evidence of nontrivial memory effects. Unlike in healthy subjects, these properties are disrupted in DoC patients, who exhibit less predictable INT state transitions and less memory effects. Together, our results show a prominent role for the temporal richness of the transitions between different INT topographic states in the awake state which, as evidenced by our results, is key for maintaining an adequate level of consciousness.
Dynamic topographies of intrinsic neural timescales: a key role for consciousness
Buccellato, Andrea;Facca, Massimiliano;Bisiacchi, Patrizia;Del Felice, Alessandra;
2025
Abstract
The brain displays intrinsic durations in its own spontaneous activity - Intrinsic Neural Timescales (INTs). INTs are hierarchically organized, with shorter durations within unimodal regions and longer intervals in multimodal domains. Despite significant progress, it's currently not known whether the unimodal-multimodal hierarchical organization undergoes recurrent changes itself - consistent with the existence of a dynamic repertoire of INT topographies. To this aim, we characterized the dynamics of topographic INT states by clustering the dynamic ACW-0 matrices in two different datasets: the source-reconstructed HCP resting-state MEG dataset, and a hd-EEG resting-state dataset, composed of healthy individuals and people with disorders of consciousness (DoCs). We found that healthy subjects display dynamic transitions between different INT states, which exhibit changing degrees of uni-transmodal cortical hierarchies. These dynamic transitions show non-random behavior, with moderate degrees of unpredictability and evidence of nontrivial memory effects. Unlike in healthy subjects, these properties are disrupted in DoC patients, who exhibit less predictable INT state transitions and less memory effects. Together, our results show a prominent role for the temporal richness of the transitions between different INT topographic states in the awake state which, as evidenced by our results, is key for maintaining an adequate level of consciousness.Pubblicazioni consigliate
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