Infraslow fluctuations in global brain states shape ongoing memory reactivation dynamics during rest
Poster No:
848
Submission Type:
Abstract Submission
Authors:
Hyun-Woong Kim1, Ting Xu2, Karl-Heinz Nenning1, Mark D'esposito3, Stanley Colcombe1, Michael Milham2, Arielle Tambini1
Institutions:
1Nathan Kline Institute, Orangeburg, NY, 2Child Mind Institute, New York, NY, 3University of California, Berkeley, CA
First Author:
Co-Author(s):
Introduction:
A rich repertoire of spontaneous neural activity is present during rest. One example is the reactivation of representations of past experience, a key mechanism supporting memory consolidation (Tambini & Davachi, 2019). While the neural dynamics of awake memory reinstatement have been characterized at fast timescales (Higgins et al., 2020), it is unclear whether specific awake periods (e.g. brain states) at slower timescales, over seconds to minutes, promote reactivation and consolidation. To gain insight into this question, we examined how reactivation events take place according to slow fluctuations in global brain states. Prior work has isolated temporary brain states during rest via coactivation pattern (CAP) analysis (Liu et al., 2013), typically including a state that reflects internal vs. external processing (i.e., default vs. task-positive networks; e.g., Lee et al., 2024). The CAP dynamics are linked with slow fluctuations in global brain-wide activity (global fMRI signal, GS) (Gutierrez-Barragan et al., 2019), the amplitude of which is negatively associated with arousal levels (Wong et al., 2013). Here, we studied which brain states support memory reactivation by examining relations between temporal dynamics of reactivation events, brain states (i.e. CAPs), and GS phase/amplitude during rest.
Methods:
We analyzed an fMRI dataset (n=52), in which the reactivation of incidentally encoded object-face stimuli has been reported (Tambini & D'Esposito, 2020). Although transcranial magnetic stimulation (TMS) was applied in this study (Fig.1A), here we focused on reactivation dynamics regardless of TMS conditions. Reactivation events were defined as time points of post-encoding rest in which patterns of the hippocampus and lateral occipital cortex activity were concurrently similar to those of the encoding phase (Tanriverdi et al., 2023; Yu et al., 2024). To characterize global brain states during reactivation events, we isolated CAPs from the pre-encoding rest scans (Fig.1B) and assigned each post-encoding time point to the CAP with the strongest similarity to the current activity pattern. To examine the relationship between reactivation and GS fluctuations, we computed 1) the GS phase during reactivation events (Fig.2B) and 2) the rates of reactivation events across time windows with high vs. low GS amplitude (i.e., standard deviation) (Fig.2C).
Results:
We identified four pairs of distinct brain states (i.e., CAPs, Fig.1B). The CAP 1A/B pair captured modes of internal vs. external processing (differentially weighting default vs. dorsal attention networks). Other CAP pairs weighted the visual network (CAP 2A/B), the sensorimotor-association axis (CAP 3A/B), and somato-motor and ventral attention networks (CAP 4A/B). Reactivation occurred preferentially during one of each CAP pair - default, visual, and sensorimotor networks (all Ps<.017, Fig.2A). Reactivation also tended to occur during the peak (i.e., zero) phase of the GS (Fig.2B). In addition, reactivation took place more frequently during high vs. low GS amplitude time windows (P<.001; Fig.2C). Moreover, the rate of reactivation during high, but not low, GS amplitude time windows was positively correlated with subsequent memory retention (R=.46, P=.001).
Conclusions:
Reactivation preferentially occurred during specific brain states: those reflecting default and visual network activity, the peak of the GS, and time windows with higher GS amplitude fluctuations, suggesting that these states may promote (visual) memory reactivation. Importantly, more frequent reactivation during high GS amplitude periods was associated with better memory retention, suggesting that reactivation under low arousal facilitates consolidation (Raut et al., 2021; Wong et al., 2013). These results show that memory reactivation is coupled with ongoing, slow fluctuations in brain states and brain-wide activity and that slow changes in arousal during wakefulness may affect ongoing memory consolidation.
Brain Stimulation:
TMS
Learning and Memory:
Long-Term Memory (Episodic and Semantic) 1
Modeling and Analysis Methods:
Task-Independent and Resting-State Analysis 2
Keywords:
FUNCTIONAL MRI
Memory
Multivariate
1|2Indicates the priority used for review
Abstract Information
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