Temporal dynamics of affect in the brain: Evidence from human imaging and animal models

Neural Variability and Cognitive Control in Individuals With Opioid Use Disorder

Importance

Opioid use disorder (OUD) impacts millions of people worldwide. Prior studies investigating its underpinning neural mechanisms have not often considered how brain signals evolve over time, so it remains unclear whether brain dynamics are altered in OUD and have subsequent behavioral implications.

Objective

To characterize brain dynamic alterations and their association with cognitive control in individuals with OUD.

Design, Setting, and Participants

This case-control study collected functional magnetic resonance imaging (fMRI) data from individuals with OUD and healthy control (HC) participants. The study was performed at an academic research center and an outpatient clinic from August 2019 to May 2024.

Exposure

Individuals with OUD were all recently stabilized on medications for OUD (<24 weeks).

Main Outcomes and Measures

Recurring brain states supporting different cognitive processes were first identified in an independent sample with 390 participants. A multivariate computational framework extended these brain states to the current dataset to assess their moment-to-moment engagement within each individual. Resting-state and naturalistic fMRI investigated whether brain dynamic alterations were consistently observed in OUD. Using a drug cue paradigm in participants with OUD, the association between cognitive control and brain dynamics during exposure to opioid-related information was studied. Variations in continuous brain state engagement (ie, state engagement variability [SEV]) were extracted during resting-state, naturalistic, and drug-cue paradigms. Stroop assessed cognitive control.

Results

Overall, 99 HC participants (54 [54.5%] female; mean [SD] age, 31.71 [12.16] years) and 76 individuals with OUD (31 [40.8%] female; mean [SD] age, 39.37 [10.47] years) were included. Compared with HC participants, individuals with OUD demonstrated consistent SEV alterations during resting-state (99 HC participants; 71 individuals with OUD; F4,161 = 6.83; P < .001) and naturalistic (96 HC participants; 76 individuals with OUD; F4,163 = 9.93; P < .001) fMRI. Decreased cognitive control was associated with lower SEV during the rest period of a drug cue paradigm among 70 participants with OUD. For example, lower incongruent accuracy scores were associated with decreased transition SEV (ρ58 = 0.34; P = .008).

Conclusions and Relevance

In this case-control study of brain dynamics in OUD, individuals with OUD experienced greater difficulty in effectively engaging various brain states to meet changing demands. Decreased cognitive control during the rest period of a drug cue paradigm suggests that these individuals had an impaired ability to disengage from opioid-related information. The current study introduces novel information that may serve as groundwork to strengthen cognitive control and reduce opioid-related preoccupation in OUD.

Investigating brain dynamics and their association with cognitive control in opioid use disorder using naturalistic and drug cue paradigms

Objectives

Opioid use disorder (OUD) impacts millions of people worldwide. The prevalence and debilitating effects of OUD present a pressing need to understand its neural mechanisms to provide more targeted interventions. Prior studies have linked altered functioning in large-scale brain networks with clinical symptoms and outcomes in OUD. However, these investigations often do not consider how brain responses change over time. Time-varying brain network engagement can convey clinically relevant information not captured by static brain measures.

Methods

We investigated brain dynamic alterations in individuals with OUD by applying a new multivariate computational framework to movie-watching (i.e., naturalistic; N=76) and task-based (N=70) fMRI. We further probed the associations between cognitive control and brain dynamics during a separate drug cue paradigm in individuals with OUD.

Results

Compared to healthy controls (N=97), individuals with OUD showed decreased variability in the engagement of recurring brain states during movie-watching. We also found that worse cognitive control was linked to decreased variability during the rest period when no opioid-related stimuli were present.

Conclusions

These findings suggest that individuals with OUD may experience greater difficulty in effectively engaging brain networks in response to evolving internal or external demands. Such inflexibility may contribute to aberrant response inhibition and biased attention toward opioid-related stimuli, two hallmark characteristics of OUD. By incorporating temporal information, the current study introduces novel information about how brain dynamics are altered in individuals with OUD and their behavioral implications.

Revealing the Complexity of Fatigue: A Review of the Persistent Challenges and Promises of Artificial Intelligence

Part I reviews persistent challenges obstructing progress in understanding complex fatigue's biology. Difficulties quantifying subjective symptoms, mapping multi-factorial mechanisms, accounting for individual variation, enabling invasive sensing, overcoming research/funding insularity, and more are discussed. Part II explores how emerging artificial intelligence and machine and deep learning techniques can help address limitations through pattern recognition of complex physiological signatures as more objective biomarkers, predictive modeling to capture individual differences, consolidation of disjointed findings via data mining, and simulation to explore interventions. Conversational agents like Claude and ChatGPT also have potential to accelerate human fatigue research, but they currently lack capacities for robust autonomous contributions. Envisioned is an innovation timeline where synergistic application of enhanced neuroimaging, biosensors, closed-loop systems, and other advances combined with AI analytics could catalyze transformative progress in elucidating fatigue neural circuitry and treating associated conditions over the coming decades.