Recent research from Aalto University shows that the external factors influencing your daily life, such as your workout or restless night last week, could continue to affect your brain's functioning well into the following week.
Brain Connectivity Is Not Static
Published in PLOS Biology, the study reveals that factors like sleep, physical activity, and mood directly impact brain connectivity, with effects unfolding over varying time scales.
Exploring how environmental and physiological factors affect brain activity over time is crucial for understanding the brain's dynamic nature. Traditional research designs, particularly cross-sectional studies, have primarily focused on capturing brain activity at a single moment without considering the natural temporal fluctuations. While these studies have contributed valuable insights, they lack data on how brain connectivity changes day by day or even week by week, limiting our understanding of how the brain adjusts to ongoing experiences.
In contrast, this study provides a more nuanced view of the brain’s flexibility. Neural activity can shift rapidly in milliseconds, adapting to immediate stimuli, or evolve more gradually over days or even weeks, as seen in psychiatric disorders where brain dynamics are altered. This variability highlights the importance of studying brain connectivity over multiple time scales. By tracking daily changes in mood and performance, functional brain connectivity patterns offer a window into how external factors like sleep and physical activity engage and modify neural networks.
The study collected 133 days of data from a single subject using wearables and smartphones, along with 30 functional magnetic resonance imaging (fMRI) scans. These tools allowed the researchers to track how external factors such as sleep quality, physical activity, and autonomic nervous system (ANS) function influence brain activity during tasks involving attention, memory, and resting state.
This study showed that brain connectivity is not static but fluctuates in response to daily environmental and physiological factors. For instance, the study found that sleep quality and physical activity were closely linked to brain connectivity during attention and memory tasks. Specifically, sleep was found to influence functional connectivity in networks responsible for sustained attention, such as the fronto-parietal and default mode networks, while physical activity was more relevant for tasks involving working memory. Graphic from Schimmelpfennig and colleagues (2023).
In addition, the study demonstrated that heart rate variability and respiration rate were significantly associated with resting-state brain connectivity and movie-watching tasks. These findings suggest that the autonomic nervous system plays a crucial role in modulating brain connectivity in states of low cognitive demand.
Interestingly, the study also revealed that the effects of daily behavior on brain connectivity could extend beyond 24 hours. For example, sleep patterns from up to 15 days prior had a lasting impact on brain function during attention tasks, highlighting the importance of considering longer time scales when studying brain-behavior relationships.
The study identified two distinct phases in which external factors influenced brain connectivity. The short-term wave, lasting less than seven days, captured rapid adaptations, such as heart rate variability, which produced quick alterations in brain connectivity. Meanwhile, the long-term wave, lasting up to 15 days, pointed to more gradual effects, particularly from mood and sleep, which impacted brain areas associated with attention and memory. Interestingly, the study also found that some of these effects, especially those related to sleep duration, exhibited delayed impacts. The influence of a poor night’s sleep could take several days to manifest fully in changes to brain connectivity, suggesting that the brain may accumulate and respond to external factors over time.
Another layer of complexity arose in how sex hormones, such as estradiol, which fluctuates during the menstrual cycle, might modulate brain connectivity. Estradiol influences both sleep patterns and heart rate variability, potentially contributing to the observed delays in the impact of external factors on brain function.
The study also highlighted the high degree of individual variability, not only across different tasks but even from session to session. While neural networks are generally stable, they exhibit significant day-to-day variations that are directly linked to external factors such as sleep and physical activity. This variability underscores the importance of personalized approaches in understanding brain function and behavior.
The implications of this research extend beyond understanding normal brain function. The person-centered approach used in this study offers a powerful tool for detecting early signs of neurological disorders. By linking brain activity with physiological and environmental data, researchers may be able to identify early warning signs of conditions like Alzheimer’s disease or depression. Co-author Dr. Nick Hayward, a neuroscientist at the University of Cambridge, emphasizes that real-time monitoring of brain changes could lead to earlier interventions in patient care, revolutionizing personalized healthcare.
Conclusion
This study serves as a proof of concept for how continuous, real-life data collection can advance neuroscience. By integrating wearables with repeated brain scans, the research provides an unparalleled level of detail in understanding how everyday habits shape brain connectivity.
This research demonstrates that our brains are in constant flux, shaped by daily experiences and physiological states. The effects of daily behavior on brain connectivity can extend beyond 24 hours. For example, sleep patterns from up to 15 days prior were found to have a lasting impact on brain function during attention tasks, highlighting the importance of considering longer time scales when studying brain-behavior relationships. The integration of real-world data with advanced neuroimaging techniques not only deepens our understanding of brain dynamics but also holds promise for enhancing the early detection and treatment of neurological diseases.
Open-Access Articles
Schimmelpfennig, J., Topczewski, J., Zajkowski, W., & Jankowiak-Siuda, K. (2023). The role of the salience network in cognitive and affective deficits. Frontiers in Human Neuroscience, 17, 1133367. https://doi.org/10.3389/fnhum.2023.1133367
Triana, A. M., Salmi, J., Hayward, N. M. E. A., Saramäki, J., & Glerean, E. (2024). Longitudinal single-subject neuroimaging study reveals effects of daily environmental, physiological, and lifestyle factors on functional brain connectivity. PLoS Biology, 22(10), e3002797. https://doi.org/10.1371/journal.pbio.3002797
Glossary
autonomic nervous system (ANS): the part of the nervous system responsible for regulating involuntary bodily functions, such as heart rate and respiration.
blood oxygen-level dependent (BOLD): a method used in fMRI to measure brain activity based on changes in blood oxygenation.
brain connectivity: the functional and structural interactions between different regions of the brain, encompassing how various parts of the brain communicate and coordinate with each other. Functional brain connectivity describes the statistical relationships or correlations between brain regions based on neural activity, often measured through techniques like functional magnetic resonance imaging (fMRI). It reflects how brain regions work together during specific tasks or at rest. Structural brain connectivity, on the other hand, refers to the physical connections between brain regions, such as neural pathways and networks formed by white matter tracts.
default mode network (DMN): a network of brain regions active when the brain is at rest and not focused on the external environment.
estradiol: a hormone that belongs to the estrogen group and is the most biologically active form of estrogen in the human body. It plays a crucial role in the development and regulation of the female reproductive system and secondary sexual characteristics. Estradiol also affects various other systems, including the cardiovascular, musculoskeletal, and nervous systems. In the brain, estradiol influences cognition, mood, and brain connectivity, as well as modulates sleep patterns and heart rate variability, contributing to its broader effects on brain function and behavior.
fronto-parietal network (FPN): a large-scale brain network primarily involved in executive functions, such as decision-making, problem-solving, and cognitive control. It connects regions in the frontal and parietal lobes of the brain, including the dorsolateral prefrontal cortex (DLPFC) and the posterior parietal cortex. The FPN is crucial for goal-directed behavior, attention regulation, working memory, and switching between different cognitive tasks. This network is highly flexible, adjusting its activity to support various tasks, and it interacts with other networks, such as the default mode network (DMN), to manage cognitive processes.
functional connectivity: the statistical dependencies between different brain regions, reflecting how these areas communicate.
functional magnetic resonance imaging (fMRI): a neuroimaging technique that measures brain activity by detecting changes in blood flow.
heart rate variability (HRV): a measure of the variation in time between consecutive heartbeats, often used as an indicator of autonomic nervous system function.
precision functional mapping: a method of neuroimaging that involves collecting large amounts of data from a single individual over time to capture individual variability in brain function.
resting-state brain connectivity: the patterns of functional communication between different regions of the brain when an individual is not actively engaged in a specific task. This type of connectivity is measured during a state of rest, typically with eyes closed or open but without performing any external cognitive or motor tasks. Resting-state connectivity is commonly studied using functional magnetic resonance imaging (fMRI), which tracks spontaneous fluctuations in brain activity across various regions. These fluctuations reveal intrinsic networks, such as the default mode network (DMN), that are active even when the brain is at rest. Resting-state connectivity provides insights into the brain's baseline functional organization and is useful for understanding various brain disorders and individual differences in cognitive functioning.
resting-state fMRI: a type of fMRI used to measure brain activity when a subject is not engaged in any specific task, providing insights into the brain's default mode of operation.
wearable sensors: devices worn by individuals that collect data on physiological and behavioral metrics, such as heart rate, physical activity, and sleep.
working memory: a cognitive system responsible for temporarily holding and manipulating information needed for complex tasks such as reasoning, learning, and decision-making. It serves as a mental workspace that allows individuals to keep information accessible for short periods, typically seconds to minutes, while performing tasks like problem-solving, planning, or comprehending language. Working memory is essential for activities that require concentration and control, and it plays a key role in executive functions. The fronto-parietal network, among other brain regions, is heavily involved in supporting working memory processes.
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