Multiscale integration of neural, social, and network theory to understand and predict transitions from illness to wellness: a proof of concept with mindfulness, hypnosis and alcohol use disorders
Abstract
MURI TOPIC 6: How are individualsÕ bodies and minds impacted by social forces, and vice versa? We propose the use of specific cognitive strategies based on mindfulness and hypnosis to develop causal models that relate brain dynamics, cognitive states, and social network resources. We focus on alcohol use and abuse, as a natural case study for understanding mind-body-community connections, and a framework in which to develop an integrated mathematical model for predicting and controlling state transitions of an individualÕs neural, cognitive, biophysiological, and social networks. Practically, this research is essential because alcohol use is a leading cause of preventable injury and death stemming from both disease and risky decisions while intoxicated. Binge drinking is common and destructive on US military bases, and alcohol use accounts for 10% of deaths in working-age adults. Alcohol use and abuse are theorized to arise from a dynamic interplay between intra-individual (i.e. brain, cognitive and physiological networks) and extra-individual (i.e. social networks) processes, and are strongly tied to mesolimbic brain reward system reactivity to alcohol-related cues. Further, many behaviors, including alcohol consumption, spread from person to person, highlighting the role of interpersonal interactions with social network members. Rather than considering intra- and extra-individual processes in isolation, progress in understanding the generative mechanisms and dynamics of decision making must account for differences in: brain network architecture and function, receptivity to influence, and group level social structures that promote different decision pathways and levels of behavioral contagion. Given this, it is surprising that prior studies have largely considered brain mechanisms and social network variables in isolation. To address this gap, we will employ experimental manipulations of key strategies known to affect cognitive states (mindfulness and hypnosis), with the goal of developing a causal model of how different brain and cognitive states interact with social resources to predict behavioral trajectories. Our overarching goal is to develop a causal multiscale model of intra-individual (i.e. neural, cognitive, physiological) and extra-individual (i.e. social) processes in terms of dynamic neural and social networks that govern exposure to alcohol-relevant cues, personal reactions to these cues, and the ability to regulate responses to them. Social factors cut across each of these dimensions: whether and how much drinking by members of a personÕs social network can influence cue exposure, and the personÕs reactivity to those cues may vary as a function of how susceptible they are to mimicking and adopting the behaviors of network members. In addition, the ability to change drinking behavior may in turn depend on the strategy the person adopts to regulate the desire to drink and their capacity to implement that strategy. We propose a two phase approach to address these scientific objectives. Phase 1 perturbs brain states and tests the effects on individual and network outcomes; Phase 2 perturbs network states and tests the effect on individual and network outcomes. Specifically, Phase 1 will develop the multiscale model based on experimental manipulation of mindfulness and hypnosis, and characterizes interactions between baseline social network resources and regulatory strategy on dynamic neural responses and controllability, and downstream cognitive, physiological, and behavioral outcomes. Phase 2 experimentally perturbs social network structure to further validate and refine our model. Our team includes international leaders in social and affective neuroscience (UPenn: Falk, PI; Columbia: Ochsner, Co-PI), network neuroscience and network control theory (UPenn: Bassett, Co-PI), and mathematical modeling of multiscale and multilayer networks (UNC: Mucha, Co-PI)
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 14, 2019
- Source ID
- W911NF1810244
Entities
People
- Emily B Falk
Organizations
- Army Contracting Command
- United States Army
- University of Pennsylvania