Brain activity propagation: elucidating origins, mechanisms, and behavioral significance

The presentation will focus on infra-slow global brain activity, reviewing its various forms across spatial scales and species, along with evidence of its potential relevance to various brain functions. Specifically, I will review the infra-slow global brain activity measured using various modalities in species: from micro-level neuronal recordings from mice, to meso-level local field potential (LFP) from monkeys, and macro-level fMRI signals in humans. Furthermore, I will discuss evidence linking this global brain activity to seconds-scale arousal fluctuations, “offline” memory processes, “online” sensory processing and memory functions, as well as its potential role in brain waste clearance in neurodegenerative diseases.  

The hierarchical organization of the cortex affords bottom-up sensory integration and top-down control. Notably, top-down hierarchical processing necessarily involves activity propagating through space from higher- to lower-order areas. However, most fMRI studies of hierarchical processing have chiefly quantified activity fluctuations in fixed regions over time rather than accounting for activity propagations over space. This gap is critical for adolescent neurodevelopment: the emergence of mood disorders and mortality via risk-taking behaviors and are in part attributed to impairments top-down control, but it is unknown whether top-down propagations become more prominent with development in youth. Here, we fill these gaps by adapting an established computer vision method—optical flow—to quantify the direction of infraslow (<.1Hz) cortical activity propagations in a large sample of youth. Optical flow effectively recovered activity directionality in simulations, uncovered significant enrichment for bottom-up and top-down propagations in every participant tested, and revealed that top-down propagations increase with task-demands and over neurodevelopment.
Image preprocessing followed an updated protocol from the Human Connectome Project MRI pipeline including gradient, bias field, and EPI-distortion correction, template normalization, re-alignment, boundary-based registration, and gaussian smoothing. Functional images also underwent bandpass filtering (0.008-0.09 Hz) and 27-parameter nuisance regression. Our samples were the Human Connectome-Development Project (HCP-D, n = 388) and the Midnight Scan Club (MSC, n = 10).
We adapted spherical optical flow to spherical registrations of each participant’s preprocessed functional timeseries. At its core, this technique estimates a regularized vector field that explains the displacement of signal between two temporally adjacent frames. Only temporally adjacent frames with low motion that were in the same low-motion continuous (>10 frame) segments were subjected to optical flow analyses.
To operationalize optical flow vectors as either bottom-up or top-down, we extracted the gradient vector field (∇) of a scalar map of functional hierarchy (FH) for a vector field describing hierarchical ascent (bottom-up directionality). Activity flow moving within 90 degrees of ∇FH was considered bottom-up, and activity flow >90 degrees from ∇FH was considered top-down. Head motion was covaried for in all results.
Despite noise and spherical inflation of the simulated data, measurement of the vector fields obtained from the simulated data revealed a prominent alignment of the directions recovered by optical flow with the ground truth relative to conservative spatial permutations (p< 0.001).
In applying this approach to real data from HCP-D, we found a predominance of both bottom-up and top-down hierarchical propagations, which formed a bimodal distribution. These bimodal distributions were evident at the single participant level: angular distributions of propagations were bimodal in every participant in the HCP-D sample (p < 0.001 for all participants) and every participant in the MSC sample (p < 0.013 for all participants) relative to conservative spatial permutations.
Having described hierarchical activity propagations at rest, we next sought to determine whether they were modulated by the performance of a demanding cognitive task. We compared propagations observed during rest with those present during a modified Go/NoGo task, where top-down control is required to suppress reflexive button-pressing. Analyses revealed more top-down propagations during task than rest (n = 281, t = 2.37–13.97, p < 0.05).
Given increases in top-down cortical propagations during a cognitive control task and that cognitive control improves with age, we next evaluated whether top-down propagations increased with age. Maturation from 8-22 years old was associated with widespread increases in the proportion of top-down propagations across the cortex (Δ Adjusted R2 = 0.01–0.19, p < 0.05). This increased prevalence of top-down propagations was evident even when measurements were averaged across the entire cortex (Δ Adjusted R2 = 0.14, p = 1.7 × 10−14). When covarying for the most-reported finding in functional cortical development, default mode segregation, the relationship between age and increased top-down activity movement was unimpacted and yielded an effect size several times larger than that observed for default mode segregation.
Analysis of the movement of cortical activity over space revealed substantial enrichment for bottom-up and top-down propagations in every participant. Top-down propagations increased during the performance of a demanding cognitive task and with maturation. These results implicate cortical propagations as a novel mechanism of hierarchical processing and neurodevelopment. 

The brain is a dynamic system characterized by continuously evolving neural activity interacting across networks. Temporal synchronization between networks reveals time-varying features, including rapid reconfigurations into transient whole-brain states and spatiotemporal propagations over time. These dynamic patterns, observed across species, reflect ongoing cognition and arousal, enabling the brain’s adaptation to internal and external environments. In this talk, we introduce how these functional dynamics develop in humans and adapt under anesthesia in nonhuman primates (NHPs). In humans, spatiotemporal propagations along sensory-association, task-positive-to-default, and somatomotor-visual axes exhibit age-dependent changes. The sensory-association and task-positive-to-default propagations grow in prominence with age, supporting cognitive maturity. Notably, top-down propagations along the sensory-association axis strongly predict cognitive performance, reflecting the emergence of adult-like dynamic configurations. In NHPs, anesthesia alters functional dynamics by modulating coactivation patterns and their occurrence rate. Increasing isoflurane concentrations shift temporal properties such as duration and transitions between dynamic states while preserving certain spatial patterns. Together, this work highlights the evolution of functional dynamics across development and their adaptation under altered states, offering insights into the mechanisms underlying cognition and the potential for cross-species translational neuroscience. 

Brain activity fluctuates over time, and understanding the factors that influence such fluctuations is crucial for understanding the flexible nature of the brain and cognition. Recent work in animals and humans has revealed the presence of specific spatio-temporal patterns in global brain activity in the form of travelling waves that propagate over tens of seconds. In particular, it has been shown that activity propagates following a principal gradient from unimodal to transmodal regions. This activity propagation has been observed across experimental and analytic approaches, indicating its ubiquity and hinting towards a physiological relevance, but its functional meaning remains unclear. Given the prominent role of neuromodulatory systems in regulating brain activity and behavior, that neuromodulators affect neural gain and excitability, and that manipulation of neuromodulatory activity have been shown to affect indices of functional connectivity typically measured on slow time scales, I had previously hypothesized that neuromodulatory systems modulate the spatio-temporal propagation of brain activity in specific ways. In the talk I will present a series of studies aimed to directly assess how different neuromodulatory systems influences spatio-temporal patterns of brain activity in humans. Employing fMRI datasets that included pharmacological manipulations of different monoaminergic neuromodulators and placebo conditions, as well as pupillometric signatures of arousal-related neuromodulation, I investigated how neuromodulatory activity influenced different aspects of travelling wave activity as measured with fMRI in humans. Specifically, I assessed the effect of atomoxetine, which increases the levels of noradrenaline and dopamine in the brain (N = 36), and the effect of lysergic acid diethylamide (LSD), a serotoninergic agonist (N = 15). Furthermore, I examined travelling wave activity across resting state and task conditions. I found that different levels of neuromodulatory tone affect the speed of travelling wave propagation over the cortex, and that this was related to measures of functional network topology. I also examined temporal variations in pupil size as a signature of transient changes in neuromodulatory activity, and found that periods of travelling waves were characterized by larger pupil size. The results suggest that the overall levels of different arousal-related neuromodulatory systems affect travelling wave propagation, and that this modulated propagation shapes integrated functional connectivity features. Furthermore, pupil signatures indicated that instantaneous changes in neuromodulatory activity may act as time-specific regulators of travelling wave activity. The findings highlight specific effects of both prolonged and transient neuromodulatory influences on slow brain dynamics, suggesting a finely tuned regulation of brain communication at the slow time scales.