John JB Allen

John JB Allen

Professor, Psychology
Distinguished Professor
Professor, BIO5 Institute
Member of the General Faculty
Professor, Neuroscience - GIDP
Member of the General Faculty
Member of the Graduate Faculty
Primary Department
Department Affiliations
Contact
(520) 621-7448

Work Summary

Depression is a major health problem that is often chronic or recurrent. Existing treatments have limited effectiveness, and are provided wihtout a clear indication that they will match a particular patient's needs. In this era of precision medicine, we strive to develop neurally-informed treatments for depression and related disorders.

Research Interest

Dr. Allen’s research spans several areas, but the main focus is the etiology and treatment of mood and anxiety disorders. His work focuses on identifying risk factors for depression using electroencephalographic and autonomic psychophysiological measures, especially EEG asymmetry, resting state fMRI connectivity, and cardiac vagal control. Based on these findings, he is developing novel and neurally-informed treatments for mood and anxiety disorders, including Transcranial Ultrasound, EEG biofeedback, and Transcranial Direct Current and Transcranial Alternating Current stimulation. Other work includes understanding how emotion and emotional disorders influence the way we make decisions and monitor our actions. Keywords: Depression, Neuromodulation, EEG, Resting-state fMRI

Publications

Stewart, J. L., Towers, D. N., Coan, J. A., & Allen, J. J. (2011). The oft-neglected role of parietal EEG asymmetry and risk for major depressive disorder. Psychophysiology, 48(1), 82-95.

PMID: 20525011;PMCID: PMC3000438;Abstract:

Relatively less right parietal activity may reflect reduced arousal and signify risk for major depressive disorder (MDD). Inconsistent findings with parietal electroencephalographic (EEG) asymmetry, however, suggest issues such as anxiety comorbidity and sex differences have yet to be resolved. Resting parietal EEG asymmetry was assessed in 306 individuals (31% male) with (n=143) and without (n=163) a DSM-IV diagnosis of lifetime MDD and no comorbid anxiety disorders. Past MDD+ women displayed relatively less right parietal activity than current MDD+ and MDD- women, replicating prior work. Recent caffeine intake, an index of arousal, moderated the relationship between depression and EEG asymmetry for women and men. Findings suggest that sex differences and arousal should be examined in studies of depression and regional brain activity. © 2010 Society for Psychophysiological Research.

Coan, J. A., & Allen, J. J. (2004). Frontal EEG asymmetry as a moderator and mediator of emotion. Biological Psychology, 67(1-2), 7-49.

PMID: 15130524;Abstract:

Frontal EEG asymmetry appears to serve as (1) an individual difference variable related to emotional responding and emotional disorders, and (2) a state-dependent concomitant of emotional responding. Such findings, highlighted in this review, suggest that frontal EEG asymmetry may serve as both a moderator and a mediator of emotion- and motivation-related constructs. Unequivocal evidence supporting frontal EEG asymmetry as a moderator and/or mediator of emotion is lacking, as insufficient attention has been given to analyzing the frontal EEG asymmetries in terms of moderators and mediators. The present report reviews the frontal EEG asymmetry literature from the framework of moderators and mediators, and overviews data analytic strategies that would support claims of moderation and mediation. © 2004 Elsevier B.V. All rights reserved.

Allen, J., Cavanagh, J. F., Cohen, M. X., & Allen, J. J. (2009). Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring. The Journal of neuroscience : the official journal of the Society for Neuroscience, 29(1).

Error-related activity in the medial prefrontal cortex (mPFC) is thought to work in conjunction with lateral prefrontal cortex (lPFC) as a part of an action-monitoring network, where errors signal the need for increased cognitive control. The neural mechanism by which this mPFC-lPFC interaction occurs remains unknown. We hypothesized that transient synchronous oscillations in the theta range reflect a mechanism by which these structures interact. To test this hypothesis, we extracted oscillatory phase and power from current-source-density-transformed electroencephalographic data recorded during a Flanker task. Theta power in the mPFC was diminished on the trial preceding an error and increased immediately after an error, consistent with predictions of an action-monitoring system. These power dynamics appeared to take place over a response-related background of oscillatory theta phase coherence. Theta phase synchronization between FCz (mPFC) and F5/6 (lPFC) sites was robustly increased during error trials. The degree of mPFC-lPFC oscillatory synchronization predicted the degree of mPFC power on error trials, and both of these dynamics predicted the degree of posterror reaction time slowing. Oscillatory dynamics in the theta band may in part underlie a mechanism of communication between networks involved in action monitoring and cognitive control.

Allen, J., Cavanagh, J. F., Frank, M. J., Klein, T. J., & Allen, J. J. (2010). Frontal theta links prediction errors to behavioral adaptation in reinforcement learning. NeuroImage, 49(4).

Investigations into action monitoring have consistently detailed a frontocentral voltage deflection in the event-related potential (ERP) following the presentation of negatively valenced feedback, sometimes termed the feedback-related negativity (FRN). The FRN has been proposed to reflect a neural response to prediction errors during reinforcement learning, yet the single-trial relationship between neural activity and the quanta of expectation violation remains untested. Although ERP methods are not well suited to single-trial analyses, the FRN has been associated with theta band oscillatory perturbations in the medial prefrontal cortex. Mediofrontal theta oscillations have been previously associated with expectation violation and behavioral adaptation and are well suited to single-trial analysis. Here, we recorded EEG activity during a probabilistic reinforcement learning task and fit the performance data to an abstract computational model (Q-learning) for calculation of single-trial reward prediction errors. Single-trial theta oscillatory activities following feedback were investigated within the context of expectation (prediction error) and adaptation (subsequent reaction time change). Results indicate that interactive medial and lateral frontal theta activities reflect the degree of negative and positive reward prediction error in the service of behavioral adaptation. These different brain areas use prediction error calculations for different behavioral adaptations, with medial frontal theta reflecting the utilization of prediction errors for reaction time slowing (specifically following errors), but lateral frontal theta reflecting prediction errors leading to working memory-related reaction time speeding for the correct choice.

Sanguinetti, J. L., Trujillo, L. T., Schnyer, D. M., Allen, J. J., & Peterson, M. A. (2015). Increased alpha band activity indexes inhibitory competition across a border during figure assignment. Vision research.