Combining Dynamic Network Analysis and Cerebral Carryover Effect to Evaluate the Impacts of Reading Social Media Posts and Science Fiction in the Natural State on the Human Brain

Abstract

Social media has been associated with decreased attention, memory, and learning abilities; however, the underlying mechanisms remain unclear. Dynamic function network connectivity (dFNC) analysis is suitable for uncovering dynamical brain activity. Besides, the effects of a cognitive task may persist for a while on the brain, even after the termination of the task, also known as the carryover effect. Consequently, we combined the dFNC analysis and cerebral carryover effects to study the brain dynamics of reading social media posts in the natural state and comparatively investigated the brain dynamics of reading science fiction on the smartphone. We performed functional MRI (fMRI) scans of all subjects at baseline and then assigned them a social media post or science fiction reading task. Immediately after, another fMRI scanning was performed for these subjects. We found that the change between dFNC states, the number of dFNC states, and the total distances increased after reading science fiction. Furthermore, the global, local, and nodal efficiencies of the deep-thinking state tended to increase after reading science fiction. On reading social media posts, the functional connectivity (FC) between the default mode network (DMN) and bilateral frontoparietal network (FPN) decreased, while the FC between DMN and visual network (VN) increased. Given the current evidence, we concluded that reading science fiction could substantially increase brain activity and network efficiency, while social media was related to abnormal FCs between DMN, VN, and FPN.

Increasing the reliability of functional connectivity by predicting long-scan functional connectivity based on short-scan functional connectivity: model exploration, explanation, validation, and application

“…Besides, the differences in three GLMs could be explained as differences in distribution features of FC matrices predicted by them. Thirdly, our results were robust across the Consortium for Reliability and Reproducibility (CoRR) Project (17) and our local dataset (18,19). Finally, our methods had the potential to enhance the test-retest reliability of FC and the performance of connectome-based predictive models (CPM).…”

“…Our Local dataset (18,19) included 38 subjects that aged between 18 and 22, and all subjects completed 2 runs of fMRI scan (5 mins per run, TR = 2 s). Finally, 38×300×15 timeseries were obtained.…”

A Systematic Review of Structural and Functional MRI Studies Investigating Social Networking Site Use

“…A recent study by Hu et al [68] used dynamic functional network connectivity analysis to investigate the brain dynamics of reading SNS posts on a smartphone. Resting-state fMRI was first recorded at baseline before participants were assigned to either a social media or science fiction reading task, which took place outside of the scanner.…”

“…The PCC constitutes a central structure of the default mode network (DMN), a neural network that is maximally activated at rest [117,118]. The DMN has been found to show increased activation and altered functional connectivity with various other regions (including regions in the dorsal and ventral attention networks) when viewing personalised TikTok videos and after reading SNS microblogs [68,80,81]. Such findings imply that passively consuming SNS content (particularly personalised content) may activate a neural state similar to that when mind wandering, which may facilitate prolonged use through modulating attention and inducing absent-minded scrolling/browsing of SNS feeds.…”

“…The precuneus, a region which neighbours the PCC, is another core hub of the DMN and is therefore also implicated in studies demonstrating alterations of DMN activity and functional connectivity when viewing SNS content [68,80,81]. The precuneus is also thought to play an important role in a range of complex tasks including visuo-spatial imagery, memory retrieval and self-referential cognition [120].…”