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Principal component analysis and brain-based predictors of emotion regulation in anxiety and depression

Published online by Cambridge University Press:  25 October 2018

Heide Klumpp ,
Kerry L. Kinney ,
Runa Bhaumik  and
Jacklynn M. Fitzgerald
Heide Klumpp*
Affiliation:
Departments of Psychiatry and Psychology (HK, KLK), University of Illinois at Chicago, Chicago, IL, USA
Kerry L. Kinney
Affiliation:
Departments of Psychiatry and Psychology (HK, KLK), University of Illinois at Chicago, Chicago, IL, USA
Runa Bhaumik
Affiliation:
Department of Psychiatry (RB), University of Illinois at Chicago, Chicago, IL, USA
Jacklynn M. Fitzgerald
Affiliation:
Department of Psychology (JMF), University of Wisconsin – Milwaukee, Milwaukee, WI, USA
*
Author for correspondence: Heide Klumpp, E-mail: [email protected]
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Abstract

Background

Reappraisal, an adaptive emotion regulation strategy, is associated with frontal engagement. In internalizing psychopathologies (IPs) such as anxiety and depression frontal activity is atypically reduced suggesting impaired regulation capacity. Yet, successful reappraisal is often demonstrated at the behavioral level. A data-driven approach was used to clarify brain and behavioral relationships in IPs.

Methods

During functional magnetic resonance imaging, anxious [general anxiety disorder (n = 43), social anxiety disorder (n = 72)] and depressed (n = 47) patients reappraised negative images to reduce negative affect (‘ReappNeg’) and viewed negative images (‘LookNeg’). After each trial, the affective state was reported. A cut-point (i.e. values <0 based on ΔReappNeg-LookNeg) demarcated successful reappraisers. Neural activity for ReappNeg-LookNeg, derived from 37 regions of interest, was submitted to Principal Component Analysis (PCA) to identify unique components of reappraisal-related brain response. PCA factors, symptom severity, and self-reported habitual reappraisal were submitted to discriminant function analysis and linear regression to examine whether these data predicted successful reappraisal (yes/no) and variance in reappraisal ability.

Results

Most patients (63%) were successful reappraisers according to the behavioral criterion (values<0; ΔReappNeg-LookNeg). Discriminant function analysis was not significant for PCA factors, symptoms, or habitual reappraisal. For regression, more activation in a factor with high loadings for frontal regions predicted better reappraisal facility. Results were not significant for other variables.

Conclusions

At the individual level, more activation in a ‘frontal’ factor corresponded with better reappraisal facility. However, neither brain nor behavioral variables classified successful reappraisal (yes/no). Findings suggest individual differences in regions strongly implicated in reappraisal play a role in on-line reappraisal capability.

Keywords

Anxietydepressionemotion regulationfMRIneuroimagingreappraisal
Type
Original Articles
Information
Psychological Medicine , Volume 49 , Issue 14 , October 2019 , pp. 2320 - 2329
Copyright
Copyright © Cambridge University Press 2018 

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References

Aldao, A, Nolen-Hoeksema, S and Schweizer, S (2010) Emotion-regulation strategies across psychopathology: a meta-analytic review. Clinical Psychology Review 30, 217–237.Google Scholar
Ball, TM, Stein, MB, Ramsawh, HJ, Campbell-Sills, L and Paulus, MP (2014) Single-subject anxiety treatment outcome prediction using functional neuroimaging. Neuropsychopharmacology 39, 1254–1261.Google Scholar
Banks, SJ, Eddy, KT, Angstadt, M, Nathan, PJ and Phan, KL (2007) Amygdala–frontal connectivity during emotion regulation. Social Cognitive and Affective Neuroscience 2, 303–312.Google Scholar
Buhle, JT, Silvers, JA, Wager, TD, Lopez, R, Onyemekwu, C, Kober, H, Weber, J and Ochsner, KN (2014) Cognitive reappraisal of emotion: a meta-analysis of human neuroimaging studies. Cerebral Cortex 24, 2981–2990.Google Scholar
Cerny, BA and Kaiser, HF (1977) A study of a measure of sampling adequacy for factor-analytic correlation matrices. Multivariate Behavioral Research 12, 43–47.Google Scholar
Clementz, BA, Sweeney, JA, Hamm, JP, Ivleva, EI, Ethridge, LE, Pearlson, GD, Keshavan, MS and Tamminga, CA (2016) Identification of distinct psychosis biotypes using brain-based biomarkers. American Journal of Psychiatry 173, 373–384.Google Scholar
Doehrmann, O, Ghosh, SS, Polli, FE, Reynolds, GO, Horn, F, Keshavan, A, Triantafyllou, C, Saygin, ZM, Whitfield-Gabrieli, S, Hofmann, SG, Pollack, M and Gabrieli, JD (2013) Predicting treatment response in social anxiety disorder from functional magnetic resonance imaging. JAMA Psychiatry 70, 87–97.Google Scholar
Downar, J, Blumberger, DM and Daskalakis, ZJ (2016) The neural crossroads of psychiatric illness: an emerging target for brain stimulation. Trends in Cognitive Sciences 20, 107–120.Google Scholar
Drysdale, AT, Grosenick, L, Downar, J, Dunlop, K, Mansouri, F, Meng, Y, Fetcho, RN, Zebley, B, Oathes, DJ, Etkin, A, Schatzberg, AF, Sudheimer, K, Keller, J, Mayberg, HS, Gunning, FM, Alexopoulos, GS, Fox, MD, Pascual-Leone, A, Voss, HU, Casey, B, Dubin, MJ and Liston, C (2016) Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nature Medicine 23, 28–38.Google Scholar
Eippert, F, Veit, R, Weiskopf, N, Erb, M, Birbaumer, N and Anders, S (2007) Regulation of emotional responses elicited by threat-related stimuli. Human Brain Mapping 28, 409–423.Google Scholar
Fernandez, KC, Jazaieri, H and Gross, JJ (2016) Emotion regulation: a transdiagnostic perspective on a new RDoC Domain. Cognitive Therapy and Research 40, 426–440.Google Scholar
First, MB, Williams, J, Karg, R and Spitzer, RL (2015) Structured Clinical Interview for DSM-5. Arlington, VA: American Psychiatric Association.Google Scholar
Fitzgerald, JM, MacNamara, A, DiGangi, JA, Kennedy, AE, Rabinak, CA, Patwell, R, Greenstein, JE, Proescher, E, Rauch, SAM, Hajcak, G and Phan, KL (2016) An electrocortical investigation of voluntary emotion regulation in combat-related posttraumatic stress disorder. Psychiatry Research: Neuroimaging 249, 113–121.Google Scholar
Fitzgerald, JM, MacNamara, A, Kennedy, AE, Rabinak, CA, Rauch, SAM, Liberzon, I and Phan, KL (2017 a) Individual differences in cognitive reappraisal use and emotion regulatory brain function in combat-exposed veterans with and without PTSD. Depression and Anxiety 34, 79–88.Google Scholar
Fitzgerald, JM, Phan, KL, Kennedy, AE, Shankman, SA, Langenecker, SA and Klumpp, H (2017 b) Prefrontal and amygdala engagement during emotional reactivity and regulation in generalized anxiety disorder. Journal of Affective Disorders 218, 398–406.Google Scholar
Ford, BQ, Karnilowicz, HR and Mauss, IB (2017) Understanding reappraisal as a multicomponent process: the psychological health benefits of attempting to use reappraisal depend on reappraisal success. Emotion 17, 905–911.Google Scholar
Frank, DW, Dewitt, M, Hudgens-Haney, M, Schaeffer, DJ, Ball, BH, Schwarz, NF, Hussein, AA, Smart, LM and Sabatinelli, D (2014) Emotion regulation: quantitative meta-analysis of functional activation and deactivation. Neuroscience & Biobehavioral Reviews 45, 202–211.Google Scholar
Goldin, P, Manber, T, Hakimi, S, Canli, T and Gross, JJ (2009) Neural bases of social anxiety disorder: emotional reactivity and cognitive regulation during social and physical threat. Archives of General Psychiatry 66, 170–180.Google Scholar
Gorka, SM, Phan, KL, Lyons, M, Mori, S, Angstadt, M and Rabinak, CA (2016) Cannabinoid modulation of frontolimbic activation and connectivity during volitional regulation of negative affect. Neuropsychopharmacology 41, 1888–1896.Google Scholar
Gross, JJ and John, OP (2003) Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. Journal of Personality and Social Psychology 85, 348–362.Google Scholar
Gruber, J, Hay, AC and Gross, JJ (2014) Rethinking emotion: cognitive reappraisal is an effective positive and negative emotion regulation strategy in bipolar disorder. Emotion 14, 388–396.Google Scholar
Guadagnoli, E and Velicer, WF (1988) Relation to sample size to the stability of component patterns. Psychological Bulletin 103, 265–275.Google Scholar
Hajcak, G and Nieuwenhuis, S (2006) Reappraisal modulates the electrocortical response to unpleasant pictures. Cognitive, Affective, & Behavioral Neuroscience 6, 291–297.Google Scholar
Hamilton, M (1959) The assessment of anxiety states by rating. British Journal of Medical Psychology 32, 50–55.Google Scholar
Hamilton, M (1960) A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry 23, 56–62.Google Scholar
Insel, T, Cuthbert, B, Garvey, M, Heinssen, R, Pine, DS, Quinn, K, Sanislow, C and Wang, P (2010) Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. American Journal of Psychiatry 167, 748–751.Google Scholar
Kaiser, HF and Rice, J (1974) Little Jiffy, Mark IV. Educational and Psychological Measurement 34, 111–117.Google Scholar
Kivity, Y and Huppert, JD (2018) Are individuals diagnosed with social anxiety disorder successful in regulating their emotions? A mixed-method investigation using self-report, subjective, and event-related potentials measures. Journal of Affective Disorders 236, 298–305.Google Scholar
Klumpp, H, Roberts, J, Kennedy, AE, Shankman, SA, Langenecker, SA, Gross, JJ and Phan, KL (2017) Emotion regulation related neural predictors of cognitive behavioral therapy response in social anxiety disorder. Progress in Neuro-Psychopharmacology and Biological Psychiatry 75, 106–112.Google Scholar
Klumpp, H, Bhaumik, R, Kinney, KL and Fitzgerald, JM (2018) Principal component analysis and neural predictors of emotion regulation. Behavioural Brain Research 338, 128–133.Google Scholar
Kozak, MJ and Cuthbert, BN (2016) The NIMH research domain criteria initiative: background, issues, and pragmatics: NIMH research domain criteria initiative. Psychophysiology 53, 286–297.Google Scholar
Lang, PJ, Bradley, MM and Cuthbert, BN (2008) International Affective Picture System (IAPS): Affective Ratings of Pictures and Instruction Manual. Technical Report A-8. Gainesville, FL: University of Florida.Google Scholar
LeDoux, JE (2000) Emotion circuits in the brain. Annual Review of Neuroscience 23, 155–184.Google Scholar
LeDoux, JE (2014) Coming to terms with fear. Proceedings of the National Academy of Sciences 111, 2871–2878.Google Scholar
Liu, DY and Thompson, RJ (2017) Selection and implementation of emotion regulation strategies in major depressive disorder: an integrative review. Clinical Psychology Review 57, 183–194.Google Scholar
MacNamara, A, Rabinak, CA, Kennedy, AE, Fitzgerald, DA, Liberzon, I, Stein, MB and Phan, KL (2015) Emotion regulatory brain function and SSRI treatment in PTSD: neural correlates and predictors of change. Neuropsychopharmacology 41, 611–618.Google Scholar
Mayberg, HS, Brannan, SK, Mahurin, RK, Jerabek, PA, Brickman, JS, Tekell, JL, Silva, JA, McGinnis, S, Glass, TG, Martin, CC and Fox, PT (1997) Cingulate function in depression: a potential predictor of treatment response. Neuroreport 8, 1057–1061.Google Scholar
McRae, K, Gross, JJ, Weber, J, Robertson, ER, Sokol-Hessner, P, Ray, RD, Gabrieli, JDE and Ochsner, KN (2012) The development of emotion regulation: an fMRI study of cognitive reappraisal in children, adolescents and young adults. Social Cognitive and Affective Neuroscience 7, 11–22.Google Scholar
Messina, I, Bianco, S, Sambin, M and Viviani, R (2015) Executive and semantic processes in reappraisal of negative stimuli: insights from a meta-analysis of neuroimaging studies. Frontiers in Psychology 6, 956.Google Scholar
Nelson, BD, Fitzgerald, DA, Klumpp, H, Shankman, SA and Phan, KL (2015) Prefrontal engagement by cognitive reappraisal of negative faces. Behavioural Brain Research 279, 218–225.Google Scholar
Ochsner, KN and Gross, JJ (2005) The cognitive control of emotion. Trends in Cognitive Sciences 9, 242–249.Google Scholar
Ochsner, KN, Bunge, SA, Gross, JJ and Gabrieli, JDE (2002) Rethinking feelings: an fMRI study of the cognitive regulation of emotion. Journal of Cognitive Neuroscience 14, 1215–1229.Google Scholar
Ochsner, KN, Silvers, JA and Buhle, JT (2012) Functional imaging studies of emotion regulation: a synthetic review and evolving model of the cognitive control of emotion. Annals of the New York Academy of Sciences 1251, E1–24.Google Scholar
Phan, KL, Fitzgerald, DA, Nathan, PJ, Moore, GJ, Uhde, TW and Tancer, ME (2005) Neural substrates for voluntary suppression of negative affect: a functional magnetic resonance imaging study. Biological Psychiatry 57, 210–219.Google Scholar
Picó-Pérez, M, Radua, J, Steward, T, Menchón, JM and Soriano-Mas, C (2017) Emotion regulation in mood and anxiety disorders: a meta-analysis of fMRI cognitive reappraisal studies. Progress in Neuro-Psychopharmacology and Biological Psychiatry 79, 96–104.Google Scholar
Poldrack, RA (2007) Region of interest analysis for fMRI. Social Cognitive and Affective Neuroscience 2, 67–70.Google Scholar
Quigley, L and Dobson, KS (2014) An examination of trait, spontaneous and instructed emotion regulation in dysphoria. Cognition and Emotion 28, 622–635.Google Scholar
Rabinak, CA, MacNamara, A, Kennedy, AE, Angstadt, M, Stein, MB, Liberzon, I and Phan, KL (2014) Focal and aberrant prefrontal engagement during emotion regulation in veterans with posttraumatic stress disorder. Depression and Anxiety 31, 851–861.Google Scholar
Salovey, P, Stroud, LR, Woolery, A and Epel, ES (2002) Perceived emotional intelligence, stress reactivity, and symptom reports: further explorations using the Trait Meta-Mood Scale. Psychology & Health 17, 611–627.Google Scholar
Thompson, DG, Kesler, SR, Sudheimer, K, Mehta, KM, Thompson, LW, Marquett, RM, Holland, JM, Reiser, R, Rasgon, N, Schatzberg, A and O'Hara, RM (2015) FMRI activation during executive function predicts response to cognitive behavioral therapy in older, depressed adults. American Journal of Geriatric Psychiatry 23, 13–22.Google Scholar
Tzourio-Mazoyer, N, Landeau, B, Papathanassiou, D, Crivello, F, Etard, O, Delcroix, N, Mazoyer, B and Joliot, M (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage 15, 273–289.Google Scholar
Vine, V and Aldao, A (2014) Impaired emotional clarity and psychopathology: a transdiagnostic deficit with symptom-specific pathways through emotion regulation. Journal of Social and Clinical Psychology 33, 319–342.Google Scholar
Visted, E, Vøllestad, J, Nielsen, MB and Schanche, E (2018) Emotion regulation in current and remitted depression: a systematic review and meta-analysis. Frontiers in Psychology 9, 1–20.Google Scholar
Wager, TD, Davidson, ML, Hughes, BL, Lindquist, MA and Ochsner, KN (2008) Prefrontal subcortical pathways mediating successful emotion regulation. Neuron 59, 1037–1050.Google Scholar
Werner, KH, Goldin, PR, Ball, TM, Heimberg, RG and Gross, JJ (2011) Assessing emotion regulation in social anxiety disorder: the Emotion Regulation Interview. Journal of Psychopathology and Behavioral Assessment 33, 346–354.Google Scholar
Williams, LM, Goldstein-Piekarski, AN, Chowdhry, N, Grisanzio, KA, Haug, NA, Samara, Z, Etkin, A, O'Hara, R, Schatzberg, AF, Suppes, T and Yesavage, J (2016) Developing a clinical translational neuroscience taxonomy for anxiety and mood disorder: protocol for the baseline-follow up Research domain criteria Anxiety and Depression (‘RAD’) project. BMC Psychiatry 16, 68, 1–14.Google Scholar
Zilverstand, A, Parvaz, MA and Goldstein, RZ (2017) Neuroimaging cognitive reappraisal in clinical populations to define neural targets for enhancing emotion regulation. A systematic review. NeuroImage 151, 105–116.Google Scholar