Beyond noise to function: reframing the global brain activity and its dynamic topography

Abstract

How global and local activity interact with each other is a common question in complex systems like climate and economy. Analogously, the brain too displays ‘global’ activity that interacts with local-regional activity and modulates behavior. The brain’s global activity, investigated as global signal in fMRI, so far, has mainly been conceived as non-neuronal noise. We here review the findings from healthy and clinical populations to demonstrate the neural basis and functions of global signal to brain and behavior. We show that global signal (i) is closely coupled with physiological signals and modulates the arousal level; and (ii) organizes an elaborated dynamic topography and coordinates the different forms of cognition. We also postulate a Dual-Layer Model including both background and surface layers. Together, the latest evidence strongly suggests the need to go beyond the view of global signal as noise by embracing a dual-layer model with background and surface layer.

Towards a systematization of brain oscillatory activity in actions

“…Further conceptual implications for neurophysiological research methodology. While the BRAC framework conceptualizes the interplay of oscillatory activity in different frequencies in terms in terms of their cognitive function, it is important to mention that another important aspect of brain physiological activity may also able to do sothe so-called global signal (GS) 145 . GS has a specific physiological basis which mediates the level of arousal and coordinates the cortical regions' and networks' activities, thereby organizing different forms of cognition 145 .…”

“…While the BRAC framework conceptualizes the interplay of oscillatory activity in different frequencies in terms in terms of their cognitive function, it is important to mention that another important aspect of brain physiological activity may also able to do sothe so-called global signal (GS) 145 . GS has a specific physiological basis which mediates the level of arousal and coordinates the cortical regions' and networks' activities, thereby organizing different forms of cognition 145 . It has been argued that GS is driven by the infra-slow fluctuations upon which the activity of faster frequencies is organized through phase-amplitude coupling.…”

Narratives engage brain and body: bidirectional interactions during natural story listening

“…An alternative explanation of our results at these slow time scales is that increased heart rate (and breathing) increases blood oxygenation. There is a global signal in fMRI at infra-slow timescales (<0.1Hz) that correlates with respiratory volume 68,69 and respiration volume/rate correlates with neural activity 70 . However, these slow fluctuations in fMRI signals that are attributed to fluctuations in arousal are in the infra-slow times-scales 0.01-0.1Hz 51 .…”

Using in silico perturbational approach to identify critical areas in schizophrenia

“…In order to move to a more individualised approach and address heterogeneity limitations, it would be also extremely important to switch from group-level to patient-level analysis and simulations. Finally, future research should apply multimodal imaging such as EEG-fMRI or in OPM-MEG in order to fully solve the debate on the extent to which global signal reflects meaningful neuronal processes (Glasser 2019, Zhang and Northoff 2022) and whether a portion of it should be attributed to artefacts (Power 2019, Aquino 2022).…”

“…Such fluctuations, often quantified as the mean signal averaged across the entire brain and referred to as the global signal, have long been considered to be noise, and therefore generally removed from the data using a procedure called global signal regression (GSR) (Aquino et al 2020;Liu, Nalci, and Falahpour 2017;Power et al 2017). Several studies though have highlighted how correction of this signal may alter some of the effects of interest (Glasser et al 2019;Zhang and Northoff 2022). In this regards, some papers pointed out the importance of deeply investigating its role in schizophrenia (Yang et al 2014(Yang et al , 2017.…”