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Poster C153

Shared longitudinal neural representations of sleep, depression and cognition

Poster Session C - Sunday, April 14, 2024, 5:00 – 7:00 pm EDT, Sheraton Hall ABC

Mohamed Abdelhack1 (, Rajith Wickramatunga1, Daniel Felsky1,2,3; 1Centre for Addiction and Mental Health, 2University of Toronto, Toronto, 3Baycrest Hospital

Relationships between sleep, depression, and cognition are complex with many conflicting observations such as both insomnia and hypersomnia manifesting as symptoms of depression. We have recently shown counterintuitive correlations of shared neural representations between associations of longer sleep and increased frequency of insomnia and depression in resting-state activations. Insomnia and depression were associated with hyperconnectivity in resting-state activations but hypoactivation in task conditions. However, these observations were cross-sectional and therefore unable to inform potential causation. In this study, we begin to address the temporal aspect of these relationships with repeated resting-state fMRI scans paired with measures of sleep, depression, and cognition in UK-Biobank (N=1188). We measured the association between the change in fMRI signals between two scans and the change in phenotype recorded at each scan. This analysis revealed associations of change in sleep duration with top-down attentional modulation from frontoparietal to visual areas (coefficient=0.61; p-value=0.002) and associations of change in depression symptoms with functional connectivity between default mode and motor networks (coefficient=0.4; p-value=0.032). Additionally, brain-wide associations between changes in frequency of insomnia and both sleep duration and depressive symptoms were positively correlated while those between sleep duration and depression were not. This indicates that neural dynamics change similarly with increase in sleep duration and in insomnia frequency. These results further support the notion of insomnia as a hyperarousal state where neural dynamics resemble those of rested wakefulness. They enable us to understand the causal relationships between insomnia and depression which could ultimately inform new and more effective interventions.

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