Last week's workout or restless night could impact your brain well into next week

By Pooja Toshniwal PahariaReviewed by Danielle Ellis, B.Sc.Oct 10 2024

Researchers monitored one individual's brain and behavioral activity over five months using brain scans, wearable devices, and smartphone data.

In a recent study published in PLoS Biology, researchers performed neuroimaging to evaluate the impact of physiological, environmental, and behavioral factors on functional connectivity in the human brain.

Background

External variables such as sleep quality, physical exercise, and social interactions influence mental states on various timelines. Major mental diseases exhibit considerable variations in brain function across timelines, and functional brain connection patterns correctly reflect mood swings. However, limited research exists on brain activity concerning cognitive and psychological qualities and sampling time.

Few studies have investigated changes in brain functional connections in response to environmental, physiological, and behavioral changes over different timelines. Longitudinal studies with frequent measurement points are required to investigate brain-behavior interactions and time-dependent effects.

About the study

In the present study, researchers studied a 33-year-old female using precision functional mapping to assess brain responses to environmental, physiological, and behavioral changes.

The researchers gathered 133 days of behavioral data using cellphones and wearables and 30 functional magnetic resonance imaging (fMRI) scans to assess attention, memory, resting state, and the impact of naturalistic stimuli. The study dataset includes brain activity data from several fMRI activities and objective data from environmental elements acquired using autonomous sensors.

The researchers assessed functional brain connections during four separate tasks: the Psychomotor Vigilance Test (PVT) for sustained attention, resting state, movie-watching as a realistic paradigm, and dual 1-back and 2-back tests for working memory. They also monitored external variables such as sleep, physical activity, autonomic nervous system (ANS) activity, and mood with cutting-edge cell phones and wearable gadgets.

The researchers assessed cognitive function daily over 19 weeks and conducted fMRI twice weekly over 15 weeks. Quora rings recorded physical activity and sleep. A smartphone application tracked mood and daily events. In addition, the participant filled out the Positive and Negative Affect Schedule (PANAS) questionnaire. Time-lagged studies examined cross-correlations of timelines with behavioral, physiological, and lifestyle variables that influence functional brain connection.

The researchers investigated the effects of behavioral, physiological, and lifestyle variables on functional brain connection patterns. They investigated the correlation between sleep and attentional tasks in the fronto-parietal (FPN), default mode (DMN), cingulo-opercular, and somatomotor networks. They also examined the relationship between sleep, physical exercise patterns, and functional connections related to working memory.

The researchers investigated whether increasing similarity in mood, sleep patterns, or ANS activity between days translates into higher inter-day similarities during movie-watching activities. Additionally, they examined whether sleep habits over the previous 15 days were associated with functional connectivity during sustained attention tasks and how sleep influences these connections across different timeframes. Furthermore, they explored whether daily behavioral, physiological, and lifestyle variables could explain variation in time-segment categorization accuracy.

Results

The study reveals that patterns of physical exercise and sleep are associated with functional connections in the brain during tasks like attention, working memory, and resting-state functional MRI. Sleep patterns in the previous 15 days also correlate with connections in the FPN, DMN, somatomotor, and cingulo-opercular brain networks during attention tasks. Mood, sleep, and ANS activity also influence the accuracy of time segment classification during movie-watching tasks.

Sleep and physical exercise influence brain connectivity while performing cognitively demanding activities. Still, heart rate variability (HRV) and breathing rates are more crucial for connectivity during the resting state and watching movies. Longer sleep hours and more interruptions increase DMN global efficiency and somatomotor integration. Less physical activity the day before is also related to a weaker connection and less FPN integration.

The previous day's maximum HRV value was related to connections between the middle temporal gyrus and the insula on the left and connectivity between the posterior cingulate gyrus and the cerebellum on the right. A lower minimum HRV the day before is related to weaker between-network integration for the FPN.

The team found a negative link between the previous day's restless sleep and ISC activity in the left superior parietal sulcus but a positive relationship between mean HRV and ISC activity in the left medial superior frontal gyrus. The DMN and FPN's global efficiency showed consistent connections with short lags of awake time and long lags of sleep length, but their participation coefficient was unaffected.

Conclusion

The findings indicate that physiological and behavioral variables are associated with short- and long-term brain connectivity, up to 15 days. During realistic stimuli such as movies, brain activity is linked to respiratory rate patterns in specific brain areas within eight to 11 days. Combining brain connections, physiological information, and environmental signals will drive environmental neuroscientific research and facilitate precision healthcare.