Dezhina, Zalina;
Smallwood, Jonathan;
Xu, Ting;
Turkheimer, Federico E;
Moran, Rosalyn J;
Friston, Karl J;
Leech, Robert;
(2023)
Establishing brain states in neuroimaging data.
PLoS Computational Biology
, 19
(10)
, Article e1011571. 10.1371/journal.pcbi.1011571.
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Abstract
The definition of a brain state remains elusive, with varying interpretations across different sub-fields of neuroscience-from the level of wakefulness in anaesthesia, to activity of individual neurons, voltage in EEG, and blood flow in fMRI. This lack of consensus presents a significant challenge to the development of accurate models of neural dynamics. However, at the foundation of dynamical systems theory lies a definition of what constitutes the 'state' of a system-i.e., a specification of the system's future. Here, we propose to adopt this definition to establish brain states in neuroimaging timeseries by applying Dynamic Causal Modelling (DCM) to low-dimensional embedding of resting and task condition fMRI data. We find that ~90% of subjects in resting conditions are better described by first-order models, whereas ~55% of subjects in task conditions are better described by second-order models. Our work calls into question the status quo of using first-order equations almost exclusively within computational neuroscience and provides a new way of establishing brain states, as well as their associated phase space representations, in neuroimaging datasets.
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