Intermittent brain network reconfigurations and the resistance to social media influence

Abstract

Since their 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.

The UnCODE system: A neurocentric systems approach for classifying the goals and methods of Cognitive Warfare

“…The Diagnose class of CogWar goals arises from adversaries identifying that learning about the input and output relationships of target neural systems can inform the design of methods used to reach CogWar goals. This can include any research aimed at understanding the general function of human and nonhuman neural systems, studying the effect of behavioral interventions, identifying cognitive traits and processes that predict human performance in hybrid and operative settings (e.g., [42][43][44][45][46][47][48][49][50][51][52][53][54][55]), studying the behavior of target populations on social media [7], studying what type of content spreads faster on social media [56], studying what type of neural activity predicts opinion change [57,58], monitoring when stress levels degrade cognitive performance, behavioral tracking using digital devices, collect data to generate digital twins [4,56], or extract information from brain activity through surveillance of brain signals and hacking of brain-computer interfaces [8,59]. Diagnose goals may include developing informative and educational models and frameworks that can be used to understand performance in hybrid contexts (e.g., [60][61][62][63][64], or the interrelatedness between CogWar-related capabilities and action spaces such as the CogWar House Model [16] and the Holistic Bow-Tie model of CogWar [2].…”

Brain flexibility increases during the peri-ovulatory phase as compared to early follicular phase of the menstrual cycle

“…Critical systems can typically be explored by robust statistical analysis and modelling. A critical system operates in a highly variable, adaptive, and flexible dynamic regime Cocchi et al (2017) 7 Brain flexibility It refers to the brain's ability to explore a large number of its possible dynamical states Pinto et al (2022) 8 Neuronal avalanches A cascade of neural events (e.g. action potentials) that starts from a single event and propagates throughout the network, typically across spatial and temporal scales These cascades have been described by a critical branching process Beggs et al (2003) 9 Branching ratio (σ) The ratio between the number of activations in consecutive time steps.…”

Cognitive flexibility but not cognitive styles influence deepfake detection skills and metacognitive accuracy

“…Due to the opportunities enabled by recent technological developments, there has been renewed interest in understanding social engineering from a deeper perspective of human cognition (Baek & Falk, 2018;Montañez et al, 2020). This research has mainly addressed neurocognitive factors related to the processing of the information that is meant to influence, such as sentiment processing, mentalizing abilities, brain network flexibility (Baek et al, 2021;Lima Dias Pinto et al, 2022), and tendencies towards suspicion (Vishwanath et al, 2018). Considerably less effort has been dedicated to studying the neurocognitive factors related to making judgments about the novel tools and technologies that cybercriminals use to facilitate different modes of influence.…”