Dynamic topographies of intrinsic neural timescales: a key role for consciousness.
Andrea Buccellato, Di Zang, Yasir Çatal, Bianca Ventura, Massimiliano Facca, Zengxin Qi, Patrizia Bisiacchi, Alessandra Del Felice, Xuehai Wu, Georg Northoff
Computers in biology and medicine October 1, 2025 DOI: 10.1016/j.compbiomed.2025.111102 via PubMed
Summary
AI-generated from the abstractThe brain's spontaneous activity has intrinsic durations—Intrinsic Neural Timescales (INTs)—that are hierarchically organized, with shorter durations in sensory regions and longer ones in association areas. This study shows that the topographic organization of INTs is not fixed but dynamically changes over time. Healthy individuals exhibit transitions between different INT states that are moderately predictable and show memory effects. In people with disorders of consciousness, these transitions become less predictable and show reduced memory effects, suggesting that the temporal richness of INT state transitions is important for maintaining normal consciousness.
Study at a glance
| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Population | Healthy individuals and people with disorders of consciousness |
| Keywords | Brain topography Consciousness Neural dynamics |
| Key finding | Healthy subjects show dynamic transitions between different INT states that are moderately predictable and exhibit memory effects, while these properties are disrupted in patients with disorders of consciousness. |
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.