Functional connectivity (FC) reflects brain-wide communication essential for cognition, yet the role of underlying biophysical factors in shaping FC remains unclear. We quantify the influence of physical factors—structural connectivity (SC) and Euclidean distance (DC), which capture anatomical wiring and regional distance—and molecular factors—gene expression similarity (GC), and neuroreceptor congruence (RC), representing neurobiological similarity—on resting-state FC. We assess how these factors impact graph-theoretic and gradient features, capturing pairwise and higher-order interactions. By generating remnant functional networks after selectively removing connections tied to specific factors, we show that molecular factors, particularly RC, dominate graph-theoretic features, while gradient features are shaped by a mix of molecular and physical factors, especially GC and DC. SC has a surprisingly minor role. We also link FC alterations to biophysical factors in schizophrenia, bipolar disorder, and attention deficit/hyperactivity disorder (ADHD), with physical factors differentiating these groups. These insights are key for understanding FC across various applications, including task performance, development, and clinical conditions. Author Summary We introduce and utilize a remnant functional networks-based framework to investigate how the brain’s functional connectivity (FC), representative of the brain-wide communication network essential for cognition, is shaped by various biophysical —physical and molecular—factors, including structural connectivity, physical distance, and neuroreceptor similarities. Our findings reveal that molecular factors, particularly neuroreceptor congruence, play a dominant role in shaping FC network features, while structural connectivity has a surprisingly minor influence. Applying this framework, we identify distinct biophysical drivers of FC alterations in schizophrenia, bipolar disorder, and ADHD, offering insights into the unique characteristics of these disorders. This study emphasizes the significance of molecular factors in shaping FC and provides a tool for exploring these associations across various contexts, including task performance, development, and clinical conditions.

Author Summary Using a graphical framework approach, our findings suggest that following awakening from slow wave sleep: (a) a prioritization scheme may underlie recovery rates for different behaviors; (b) long-range neural connections orchestrating local-global operations are uniquely disrupted; and (c) a peppermint odorant is able to minimize disruption to long-range connections. This research (a) advances the knowledge of neural processes during the transition from sleep to wakefulness and (b) applies a novel methodological approach to sleep-wake brain states. Further research is needed to apply this analytical method to alternative interventions and sleep-wake transition scenarios. Abstract Sleep inertia is the brief period of impaired alertness and performance experienced immediately after waking. Little is known about the neural mechanisms underlying this phenomenon. A better understanding of the neural processes during sleep inertia may offer insight into the awakening process. We observed brain activity every 15 min for 1 hr following abrupt awakening from slow wave sleep during the biological night. Using 32-channel electroencephalography, a network science approach, and a within-subject design, we evaluated power, clustering coefficient, and path length across frequency bands under both a control and intervention conditions. We found that under control conditions, the awakening brain is characterized by an immediate reduction in global theta, alpha, and beta power. Simultaneously, we observed a decrease in the clustering coefficient and an increase in path length within the delta band. Exposure to an odorant (i.e., peppermint) immediately after awakening ameliorated changes in clustering. Our results suggest that long-range network communication within the brain is crucial to the awakening process and that the brain may prioritize these long-range connections during this transitional state. Our study highlights a novel neurophysiological signature of the awakening brain and provides some initial evidence that may accelerate the process via interventions.

Since its development, social media has grown as a source of information and has a significant impact on opinion formation. Individuals interact with others and content via social media platforms in a variety of ways, but it remains unclear how decision-making and associated neural processes are impacted by the online sharing of informational content, from factual to fabricated. Here, we use EEG to estimate dynamic reconfigurations of brain networks and probe the neural changes underlying opinion change (or formation) within individuals interacting with a simulated social media platform. Our findings indicate that the individuals who changed their opinions are characterized by less frequent network reconfigurations while those who did not change their opinions tend to have more flexible brain networks with frequent reconfigurations. The nature of these frequent network configurations suggests a fundamentally different thought process between intervals in which individuals are easily influenced by social media and those in which they are not. We also show that these reconfigurations are distinct to the brain dynamics during an in-person discussion with strangers on the same content. Together, these findings suggest that brain network reconfigurations may not only be diagnostic to the informational context but also the underlying opinion formation. Author Summary Distinctive neural underpinnings of opinion formation and change during in-person and online social interactions are not well understood. Here, we analyze EEG recordings of the participants interacting with a simulated social media platform and during an in-person discussion by using a network-based analysis approach. We show that the structure of network reconfigurations during these interactions is diagnostic of the opinion change and the context in which information was received.