Emerging concepts for the dynamical organization of resting-state activity in the brain

Abstract

A broad body of experimental work has demonstrated that apparently spontaneous brain activity is not random. At the level of large-scale neural systems, as measured with functional MRI (fMRI), this ongoing activity reflects the organization of a series of highly coherent functional networks. These so-called resting-state networks (RSNs) closely relate to the underlying anatomical connectivity but cannot be understood in those terms alone. Here we review three large-scale neural system models of primate neocortex that emphasize the key contributions of local dynamics, signal transmission delays and noise to the emerging RSNs. We propose that the formation and dissolution of resting-state patterns reflects the exploration of possible functional network configurations around a stable anatomical skeleton.

Neuronal oscillations in the EEG under varying cognitive load: A comparative study between slow waves and faster oscillations

“…Moreover, both the amplitude and phase of the ER and Background task ICs were very different in the slow wave band (Figure 6 (a)) -this could be due to the different morphology of these two types of task ICs. Meanwhile, the substantial overlap between rest and task classes in the slow wave band, in comparison to that observed for higher frequencies such as theta and alpha, is consistent with the VLF theoretical models and fMRI BOLD imaging studies on the slow waves (Fox et al 2006;Fransson, 2006;Sonuga Barke and Castellanos, 2007;Deco, 2011), which suggest that despite experiencing changes during different brain states the slow waves persist across these states. The slow wave mechanism that is affecting the brain sources and/or that is being affected by the different loadings during task does not operate in a binary fashion, i.e.…”

“…Rather the ongoing slow wave activity might be causing the resting brain to operate at the edge of bifurcation, awaiting the next cognitive act (Deco, 2011). Furthermore, the rest-to-task separation of the slow wave features, although low, might be reflecting the different…”

Cognitive impairment in epilepsy: the role of reduced network flexibility

“…Findings such as these have led to the hypothesis that the dorsal posterior cingulate cortex (a key DMN hub) influences whole‐brain network meta‐stability, ‘tuning’ network interactions throughout the brain, thereby enabling rapid transitions between different neural states 22. Such dynamics have been argued to constitute the essence of the network basis of cognition 12, 39…”

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

“…Functional magnetic resonance imaging studies of brain networks aim to demonstrate correlations among BOLD fluctuations in different brain regions (Biswal et al, 1995), while those involving electro-or magnetoencephalography (EEG/MEG) typically evaluate correlations among fluctuations in the amplitude of oscillatory activity in different brain regions (de Pasquale et al, 2010;Fries, 2015). Researchers have proposed that the resting-state networks (RSNs) measured using fMRI (rsfMRI) reflect a sort of "constant inner state of exploration" that optimizes the system for a given impending input, thus influencing perception and cognitive processing (Deco et al, 2011). While this idea appears intuitive, the fluctuations observed using rsfMRI occur too slowly to be associated with preparation for a given unpredictable input and allow for a fast and adequate reaction.…”