Resting Brain Fluctuations Are Intrinsically Coupled to Visual Response Dynamics

Abstract

How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional magnetic resonance imaging to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) are the most prominent component of mouse resting brain dynamics. These QPPs captured the temporal alignment of anticorrelation between the default mode (DMN)- and task-positive (TPN)-like networks, with global brain fluctuations, and activity in neuromodulatory nuclei of the reticular formation. Specifically, the phase of QPPs prior to stimulation could significantly stratify subsequent visual response magnitude, suggesting QPPs relate to brain state fluctuations. This is the first observation in mice that dynamics of the DMN- and TPN-like networks, and particularly their anticorrelation, capture a brain state dynamic that affects sensory processing. Interestingly, QPPs also displayed transient onset response properties during visual stimulation, which covaried with deactivations in the reticular formation. We conclude that QPPs appear to capture a brain state fluctuation that may be orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.

An isotropic EPI database and analytical pipelines for rat brain resting-state fMRI

“…This approach was recently utilized by an awake rat resting-state fMRI database and derived similar results ( Liu et al, 2020 ). The metric was built on robust cingulate and RSC FC, as both are considered to be key nodes of the DMN ( Tu et al, 2021a ; Tu et al, 2021b ; Peeters at al., 2020 ; Belloy et al, 2021 ; Coletta et al, 2020 ; Grandjean et al, 2020 ; Paasonen et al, 2018 ; Lu et al, 2012 ), whereas the cingulate and somatosensory FC is usually low ( Gozzi and Schwarz, 2016 ), or often in opposing states ( Belloy et al, 2018 ; Gutierrez-Barragan et al, 2019 ). Nevertheless, emerging studies have shown dichotomous involvement of cingulate cortex in both the DMN and the SN ( Tsai et al, 2020 ; Mandino et al, 2019b ).…”

Functional Connectivity of the Brain Across Rodents and Humans

“…On the positive side, stronger gradients can be used to provide the necessary high spatial resolution. Rodent data is frequently non-isotropic, with an in-plane resolution of 0.2–0.5 mm and 0.4–1.0 mm slice thickness ( Schwarz et al, 2013 ; Liska et al, 2015 ; Becq et al, 2020 ; Tsai et al, 2020 ; Belloy et al, 2021 ) while isotropic rodent data has ∼0.5 mm 3 voxels ( Kundu et al, 2014 ) compared to about 2–3 mm 3 voxels for isotropic human data ( Franzmeier et al, 2017 ). Repetition rates (TRs) in these studies are typically 1–3 s for both humans and rodents.…”

“…Quasi-periodic patterns (QPPs) are spatiotemporal patterns of activity that occur repeatedly throughout the scan. A pattern-finding algorithm has been developed ( Majeed et al, 2011 ) and popularly used ( Belloy et al, 2018a , b , 2021 ; Yousefi et al, 2018 ; Abbas et al, 2019b ; Yousefi and Keilholz, 2021 ) to detect the most prominent QPPs that are recurring over the course of the whole scan. Yet, recent advances allow us to understand these patterns within this continuous process more thoroughly by identifying spatiotemporal trajectories ( Zhang et al, 2021 ).…”

Rhythmicity in heart rate and its surges usher a special period of sleep, a likely home for PGO waves

“…We note that an ILF oscillations in the range 0.01–0.2 Hz is also observed in the fMRI BOLD signal, with the most stable amplitude seen in the slow (0.027–0.073 Hz) band as defined by Buzsáki ( Buzsáki and Draguhn, 2004 ; Zuo et al, 2010 ). These quasiperiodic patterns in fMRI have been attributed to changes in neuromodulation initiated in the reticular formation and they were shown to modulate sensory processing ( Belloy et al, 2020 ). Our results point to an additional contribution to the fMRI slow oscillations due to increased blood flow during rhythmic surges generated during REM0 periods.…”