Free-viewing Gaze Patterns Reveal a Mood-congruency Bias in MDD During an Affective FMRI/eye-tracking Task

Overview

Journal Eur Arch Psychiatry Clin Neurosci

Specialties Neurology
Psychiatry

Date 2023 Apr 23

PMID 37087709

Authors

Rui Sun

Julia Fietz

Mira Erhart

Dorothee Poehlchen

Lara Henco

Tanja M Bruckl

Michael Czisch

Philipp G Saemann

Victor I Spoormaker

Affiliations

Soon will be listed here.

Abstract

Major depressive disorder (MDD) has been related to abnormal amygdala activity during emotional face processing. However, a recent large-scale study (n = 28,638) found no such correlation, which is probably due to the low precision of fMRI measurements. To address this issue, we used simultaneous fMRI and eye-tracking measurements during a commonly employed emotional face recognition task. Eye-tracking provide high-precision data, which can be used to enrich and potentially stabilize fMRI readouts. With the behavioral response, we additionally divided the active task period into a task-related and a free-viewing phase to explore the gaze patterns of MDD patients and healthy controls (HC) and compare their respective neural correlates. Our analysis showed that a mood-congruency attentional bias could be detected in MDD compared to healthy controls during the free-viewing phase but without parallel amygdala disruption. Moreover, the neural correlates of gaze patterns reflected more prefrontal fMRI activity in the free-viewing than the task-related phase. Taken together, spontaneous emotional processing in free viewing might lead to a more pronounced mood-congruency bias in MDD, which indicates that combined fMRI with eye-tracking measurement could be beneficial for our understanding of the underlying psychopathology of MDD in different emotional processing phases.Trial Registration: The BeCOME study is registered on ClinicalTrials (gov: NCT03984084) by the Max Planck Institute of Psychiatry in Munich, Germany.

Citing Articles

Reduced positive attentional bias in patients with borderline personality disorder compared with non-patients: results from a free-viewing eye-tracking study.

Wenk T, Gunther A, Webelhorst C, Kersting A, Bodenschatz C, Suslow T Borderline Personal Disord Emot Dysregul. 2024; 11(1):24.

PMID: 39278912 PMC: 11403868. DOI: 10.1186/s40479-024-00267-y.

References

Fournier J, Chase H, Almeida J, Phillips M . Model specification and the reliability of fMRI results: implications for longitudinal neuroimaging studies in psychiatry. PLoS One. 2014; 9(8):e105169. PMC: 4148299. DOI: 10.1371/journal.pone.0105169. View

Bruckl T, Spoormaker V, Samann P, Brem A, Henco L, Czamara D . The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes. BMC Psychiatry. 2020; 20(1):213. PMC: 7216390. DOI: 10.1186/s12888-020-02541-z. View

Gee D, McEwen S, Forsyth J, Haut K, Bearden C, Addington J . Reliability of an fMRI paradigm for emotional processing in a multisite longitudinal study. Hum Brain Mapp. 2015; 36(7):2558-79. PMC: 4478164. DOI: 10.1002/hbm.22791. View

Van Vleet T, Stark-Inbar A, Merzenich M, Jordan J, Wallace D, Lee M . Biases in processing of mood-congruent facial expressions in depression. Psychiatry Res. 2019; 275:143-148. PMC: 6504610. DOI: 10.1016/j.psychres.2019.02.076. View

Nejad A, Fossati P, Lemogne C . Self-referential processing, rumination, and cortical midline structures in major depression. Front Hum Neurosci. 2013; 7:666. PMC: 3794427. DOI: 10.3389/fnhum.2013.00666. View

Suslow T, Husslack A, Kersting A, Bodenschatz C . Attentional biases to emotional information in clinical depression: A systematic and meta-analytic review of eye tracking findings. J Affect Disord. 2020; 274:632-642. DOI: 10.1016/j.jad.2020.05.140. View

Ellis A, Wells T, Vanderlind W, Beevers C . The role of controlled attention on recall in major depression. Cogn Emot. 2013; 28(3):520-9. PMC: 3948215. DOI: 10.1080/02699931.2013.832153. View

Hu C, Di X, Eickhoff S, Zhang M, Peng K, Guo H . Distinct and common aspects of physical and psychological self-representation in the brain: A meta-analysis of self-bias in facial and self-referential judgements. Neurosci Biobehav Rev. 2015; 61:197-207. DOI: 10.1016/j.neubiorev.2015.12.003. View

Maunsell J, Treue S . Feature-based attention in visual cortex. Trends Neurosci. 2006; 29(6):317-22. DOI: 10.1016/j.tins.2006.04.001. View

10.

Zhou H, Chen X, Shen Y, Li L, Chen N, Zhu Z . Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression. Neuroimage. 2019; 206:116287. DOI: 10.1016/j.neuroimage.2019.116287. View

11.

Disner S, Shumake J, Beevers C . Self-referential schemas and attentional bias predict severity and naturalistic course of depression symptoms. Cogn Emot. 2016; 31(4):632-644. DOI: 10.1080/02699931.2016.1146123. View

12.

Doucet G, Janiri D, Howard R, OBrien M, Andrews-Hanna J, Frangou S . Transdiagnostic and disease-specific abnormalities in the default-mode network hubs in psychiatric disorders: A meta-analysis of resting-state functional imaging studies. Eur Psychiatry. 2020; 63(1):e57. PMC: 7355168. DOI: 10.1192/j.eurpsy.2020.57. View

13.

van den Bulk B, Koolschijn P, Meens P, van Lang N, Van der Wee N, Rombouts S . How stable is activation in the amygdala and prefrontal cortex in adolescence? A study of emotional face processing across three measurements. Dev Cogn Neurosci. 2012; 4:65-76. PMC: 6987697. DOI: 10.1016/j.dcn.2012.09.005. View

14.

Lipp I, Murphy K, Wise R, Caseras X . Understanding the contribution of neural and physiological signal variation to the low repeatability of emotion-induced BOLD responses. Neuroimage. 2013; 86:335-42. PMC: 3898985. DOI: 10.1016/j.neuroimage.2013.10.015. View

15.

Nord C, Gray A, Charpentier C, Robinson O, Roiser J . Unreliability of putative fMRI biomarkers during emotional face processing. Neuroimage. 2017; 156:119-127. PMC: 5553850. DOI: 10.1016/j.neuroimage.2017.05.024. View

16.

Insel T, Cuthbert B, Garvey M, Heinssen R, Pine D, Quinn K . Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am J Psychiatry. 2010; 167(7):748-51. DOI: 10.1176/appi.ajp.2010.09091379. View

17.

Sauder C, Hajcak G, Angstadt M, Phan K . Test-retest reliability of amygdala response to emotional faces. Psychophysiology. 2013; 50(11):1147-56. PMC: 3827856. DOI: 10.1111/psyp.12129. View

18.

Armstrong T, Olatunji B . Eye tracking of attention in the affective disorders: a meta-analytic review and synthesis. Clin Psychol Rev. 2012; 32(8):704-23. PMC: 3556338. DOI: 10.1016/j.cpr.2012.09.004. View

19.

Walter H, von Kalckreuth A, Schardt D, Stephan A, Goschke T, Erk S . The temporal dynamics of voluntary emotion regulation. PLoS One. 2011; 4(8):e6726. PMC: 3175755. DOI: 10.1371/journal.pone.0006726. View

20.

Schneider M, Elbau I, Nantawisarakul T, Pohlchen D, Bruckl T, BeCOME Working Group . Pupil Dilation during Reward Anticipation Is Correlated to Depressive Symptom Load in Patients with Major Depressive Disorder. Brain Sci. 2020; 10(12). PMC: 7760331. DOI: 10.3390/brainsci10120906. View