The brain rapidly processes and adapts to new information by dynamically transitioning between whole-brain functional networks. In this whole-brain modeling study we investigate the relevance of spatiotemporal scale in whole-brain functional networks. This is achieved through estimating brain parcellations at different spatial scales (100–900 regions) and time series at different temporal scales (from milliseconds to seconds) generated by a whole-brain model fitted to fMRI data. We quantify the richness of the dynamic repertoire at each spatiotemporal scale by computing the entropy of transitions between whole-brain functional networks. The results show that the optimal relevant spatial scale is around 300 regions and a temporal scale of ar...
There is intense interest in fMRI research on whole-brain functional connectivity, and however, two ...
In order to survive in a complex environment, the human brain relies on the ability to flexibly adap...
The development of new experimental techniques in parallel with a continuous increase of computation...
The brain rapidly processes and adapts to new information by dynamically transitioning between whol...
A key unresolved problem in neuroscience is to determine the relevant timescale for understanding sp...
To provide an effective substrate for cognitive processes, functional brain networks should be able ...
Comprehending the interplay between spatial and temporal characteristics of neural dynamics can cont...
Fulltext embargoed for: 6 months post date of publicationNeuronal dynamics display a complex spatiot...
Brain signaling occurs across a wide range of spatial and temporal scales, and analysis of brain sig...
Brain network models (BNMs) have become a promising theoretical framework for simulating signals tha...
The properties of functional brain networks strongly depend on how their nodes are chosen. Commonly,...
The analysis of time-varying activity and connectivity patterns (i.e., the chronnectome) using resti...
The human brain is the most fascinating and complex organ. It directs all our actions and thoughts. ...
International audienceStudies employing functional connectivity-type analyses have established that ...
How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open que...
There is intense interest in fMRI research on whole-brain functional connectivity, and however, two ...
In order to survive in a complex environment, the human brain relies on the ability to flexibly adap...
The development of new experimental techniques in parallel with a continuous increase of computation...
The brain rapidly processes and adapts to new information by dynamically transitioning between whol...
A key unresolved problem in neuroscience is to determine the relevant timescale for understanding sp...
To provide an effective substrate for cognitive processes, functional brain networks should be able ...
Comprehending the interplay between spatial and temporal characteristics of neural dynamics can cont...
Fulltext embargoed for: 6 months post date of publicationNeuronal dynamics display a complex spatiot...
Brain signaling occurs across a wide range of spatial and temporal scales, and analysis of brain sig...
Brain network models (BNMs) have become a promising theoretical framework for simulating signals tha...
The properties of functional brain networks strongly depend on how their nodes are chosen. Commonly,...
The analysis of time-varying activity and connectivity patterns (i.e., the chronnectome) using resti...
The human brain is the most fascinating and complex organ. It directs all our actions and thoughts. ...
International audienceStudies employing functional connectivity-type analyses have established that ...
How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open que...
There is intense interest in fMRI research on whole-brain functional connectivity, and however, two ...
In order to survive in a complex environment, the human brain relies on the ability to flexibly adap...
The development of new experimental techniques in parallel with a continuous increase of computation...