Understanding brain states across spacetime informed by whole-brain modelling

Abstract

In order to survive in a complex environment, the human brain relies on the ability to flexibly adapt ongoing behaviour according to intrinsic and extrinsic signals. This capability has been linked to specific whole-brain activity patterns whose relative stability (order) allows for consistent functioning, supported by sufficient intrinsic instability needed for optimal adaptability. The emergent, spontaneous balance between order and disorder in brain activity over spacetime underpins distinct brain states. For example, depression is characterized by excessively rigid, highly ordered states, while psychedelics can bring about more disordered, sometimes overly flexible states. Recent developments in systems, computational and theoretical neuroscience have started to make inroads into the characterization of such complex dynamics over space and time. Here, we review recent insights drawn from neuroimaging and whole-brain modelling motivating using mechanistic principles from dynamical system theory to study and characterize brain states. We show how different healthy and altered brain states are associated to characteristic spacetime dynamics which in turn may offer insights that in time can inspire new treatments for rebalancing brain states in disease. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Keywords: complexity; connectomics; emergence; functional magnetic resonance imaging; spatio-temporal dynamics; whole-brain models.

Figure 1.

The brain as a complex system. (a) A shift in perspective towards considering the brain's function and structure as an integrated network of relationships as opposed to solely localized descriptions of individual regions of interest. (b) In many biological systems such as the brain, interactions between stimuli and measurement outputs are mostly nonlinear. (c) The spontaneous formation of spatio-temporal patterns from intrinsic brain processes is indicative of self-organization. (d) Complex activity patterns are detected across many spatial and temporal scales, from neurones to whole brain, from milliseconds to minutes. (e) A system at the edge of instability can have characteristics of critical dynamics. (f) The interactions of constituent parts at the mesoscopic scale give rise to brain activity patterns emerging at the macroscopic scale that cannot be merely explained by the individual parts alone (adapted from [1] and [16]). (Online version in colour.)

Figure 2.

Dynamic approaches to functional MRI. (a) Substrate-based representation of fMRI activity. fMRI signals are parcellated into regions; their temporal relationship is quantified and clustered to obtain a set of spatial patterns that dynamically evolve in time. Substrate-based measures allow us to summarize the spatial patterns dynamics. (b) Connectome harmonic decomposition (CHD) is an approach that considers spatial patterns expressed from the Laplacian eigenmodes of the structural connectome. The so-called connectome harmonics are then projected onto the time series allowing for analysis of these connectome harmonics in time (adapted from [46]). (Online version in colour.)

Figure 3.

Insights from whole-brain modelling. (a) Whole-brain models describe spatio-temporal dynamics in terms of stochastic nonlinear dynamics embedded in each region, which interact with other regions through the anatomical structure represented by the connectome. An important step in the description of such models is validation with empirical FC features. (b) Spatial and temporal organization of brain dynamics is preserved in models with structural connectomes exhibiting small-world properties [58] weakly coupled interactions between regions of interest and local dynamics poised at the edge of instability [59]. (c) The metastable regime of rich spontaneous brain dynamics can be perceived in-between the extreme cases of the spatial and temporal order continuum (adapted from [60]). (Online version in colour.)

Figure 4.

Psychedelic-induced state in space and time. Neuroimaging studies demonstrating various aspects of spatio-temporal dynamics under the influence of psychedelics. (a) LSD increases dynamic functional density, defined by averaged static functional connectivity between a region of interest and the rest of the brain, specifically in functional systems pertaining to the frontoparietal, default mode and salience networks [81]). (b) Repertoire broadening of brain substates, as described by connectome harmonics, in LSD and psilocybin-induced states [49]). (c) Temporal complexity, as defined by LZ-complexity, increases under psilocybin (PSIL), ketamine (KET) and LSD-induced states [82]. (d) Spatio-temporal dynamics alterations, as described by LEiDA, under the influence of psilocybin. Frontoparietal network becomes less frequently visited [83]. (Online version in colour.)

Figure 5.

Depressive state in space and time. Neuroimaging studies demonstrating various aspects of spatio-temporal dynamics in major depressive disorder. (a) Spatio-temporal dynamics alterations, as described by leading eigenvector dynamics analysis. A brain network consisting of frontoparietal, default-mode salience and striatum regions becomes visited less frequently and for shorter periods of time while the globally active network is more prevalent in vulnerable remitted-MDD patients compared to healthy controls [93]. (b) Global synchrony and temporal stability are both increased in MDD patients [94]. (Online version in colour.)

Figure 6.

Activity landscape. Brain activity in different brain states as described by fMRI. Here, the depressive state, resting-state and psychedelic state. Activity landscape where the brain's spatio-temporal dynamics can be perceived as a temporal trajectory through an n-dimensional terrain of weakly coupled substates constrained by the structural connectome. Optimal healthy functioning is expected to be observed in the resting-state with enough stability and flexibility. In depressive states, specific attractors become pronounced, making it more difficult to escape from their vicinity. On the contrary, psychedelic-induced states will result in a ‘flattened’ landscape and thus will allow for more flexibility to move within the landscape (adapted from [49]). (Online version in colour.)