A Complex Systems Perspective on Neuroimaging Studies of Behaviour and Its Disorders

Abstract

The study of complex systems deals with emergent behaviour that arises as a result of nonlinear spatio-temporal interactions between a large number of components both within the system, as well as between the system and its environment. There is a strong case to be made that neural systems as well as their emergent behaviour and disorders, can be studied within the framework of complexity science. In particular, the field of neuroimaging has begun to apply both theoretical and experimental procedures originating in complexity science – usually in parallel with traditional methodologies. Here, we demonstrate that the use of such traditional models may distort the outcomes of neuroimaging experiments – hence affecting their interpretability and raising questions about their reliability.Therefore, we argue in favor of adopting a complex systems-based methodology in the study of neuroimaging, alongside appropriate experimental paradigms, and with minimal influences from non-complex systems approaches. Our exposition includes a review of the fundamental mathematical concepts, combined with practical examples and a compilation of results from the literature.

What it is like to be a bit: an integrated information decomposition account of emergent mental phenomena

“…Note that the notion of causal emergence is not new, dating back at least to the book Problems of Life and Mind by George Lewes ( Lewes 1879/2012 ; Turkheimer et al. 2021 ), with several proposed quantifications (see e.g.…”

“…2021 ). Such an extension is necessary if we are to investigate complex, multivariate systems with intricate causal relationships, of which the human brain is a prime example ( Turkheimer et al. 2021 ; Varley et al.…”