John JB Allen
Distinguished Professor
Professor, BIO5 Institute
Professor, Cognitive Science - GIDP
Professor, Psychology
Professor, Neuroscience - GIDP
Primary Department
Department Affiliations
(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

Harmon-Jones, E., & J., J. (1997). Behavioral activation sensitivity and resting frontal EEG asymmetry: Covariation of putative indicators related to risk for mood disorders. Journal of Abnormal Psychology, 106(1), 159-163.

PMID: 9103728;Abstract:

Dispositional tendencies toward appetitive motivation have been hypothesized to be related to the development of psychopathology. Moreover, decreased left-frontal cortical activity has been reported in depression and has been related to low-trait positive affect and high-trait negative affect. The present study tested the hypothesis that relatively greater left- than right-frontal cortical activity would be related to heightened approach- related dispositional tendencies. Resting frontal cortical asymmetrical activity, as measured by electroencephalographic activity in the alpha band, was examined in relation to the motivational response tendencies of a behavioral activation system (BAS) and a behavioral inhibition system (BIS), as measured by C. S. Carver and T. L. White's (1994) BIS-BAS self-report questionnaire. Results supported the hypothesis.

Allen, J. J., Keune, P. M., Sch\"onenberg, M., & Nusslock, R. (2018). Frontal EEG alpha asymmetry and emotion: From neural underpinnings and methodological considerations to psychopathology and social cognition. Psychophysiology, 55(1).
Matsuda, I., Nittono, H., & Allen, J. J. (2012). The current and future status of the Concealed Information Test for field use.. Frontiers in Cognitive Science.

doi: 10.3389/fpsyg.2012.00532

Allen, J., Stewart, J. L., Coan, J. A., Towers, D. N., & Allen, J. J. (2011). Frontal EEG asymmetry during emotional challenge differentiates individuals with and without lifetime major depressive disorder. Journal of affective disorders, 129(1-3).

Although it has been argued that frontal electroencephalographic (EEG) asymmetry at rest may be a risk marker for major depressive disorder (MDD), it is unclear whether a pattern of relatively less left than right activity characterizes depressed individuals during emotional challenges. Examination of frontal asymmetry during emotion task manipulations could provide an assessment of the function of systems relevant for MDD, and test the limits of frontal EEG asymmetry as a marker of risk for depression.

Allen, J. J., Coan, J. A., & Nazarian, M. (2004). Issues and assumptions on the road from raw signals to metrics of frontal EEG asymmetry in emotion. Biological Psychology, 67(1-2), 183-218.

PMID: 15130531;Abstract:

There exists a substantial literature examining frontal electroencephalographic asymmetries in emotion, motivation, and psychopathology. Research in this area uses a specialized set of approaches for reducing raw EEG signals to metrics that provide the basis for making inferences about the role of frontal brain activity in emotion. The present review details some of the common data processing routines used in this field of research, with a focus on statistical and methodological issues that have captured, and should capture, the attention of researchers in this field. © 2004 Published by Elsevier B.V.