Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-27T20:03:13.127Z Has data issue: false hasContentIssue false
  • English
  • Français

Attentional bias modification (ABM) training induces spontaneous brain activity changes in young women with subthreshold depression: a randomized controlled trial

Published online by Cambridge University Press:  11 November 2015

H. Li ,
D. Wei ,
M. Browning ,
X. Du ,
Q. Zhang  and
J. Qiu
H. Li
Affiliation:
Department of Psychology, Shanghai Normal University, Shanghai, China Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Faculty of Psychology, Southwest University, Chongqing, China
D. Wei
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Faculty of Psychology, Southwest University, Chongqing, China
M. Browning
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
X. Du
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Faculty of Psychology, Southwest University, Chongqing, China
Q. Zhang
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Faculty of Psychology, Southwest University, Chongqing, China
J. Qiu*
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Faculty of Psychology, Southwest University, Chongqing, China
*
*Address for correspondence: Professor J. Qiu, Faculty of Psychology, Southwest University, No. 2, TianSheng Road, Beibei District, Chongqing 400715, China. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Attention bias modification (ABM) training has been suggested to effectively reduce depressive symptoms, and may be useful in the prevention of the illness in individuals with subthreshold symptoms, yet little is known about the spontaneous brain activity changes associated with ABM training.

Method

Resting-state functional MRI was used to explore the effects of ABM training on subthreshold depression (SubD) and corresponding spontaneous brain activity changes. Participants were 41 young women with SubD and 26 matched non-depressed controls. Participants with SubD were randomized to receive either ABM or placebo training during 28 sessions across 4 weeks. Non-depressed controls were assessed before training only. Attentional bias, depressive severity, and spontaneous brain activity before and after training were assessed in both training groups.

Results

Findings revealed that compared to active control training, ABM training significantly decreased depression symptoms, and increased attention for positive stimuli. Resting-state data found that ABM training significantly reduced amplitude of low-frequency fluctuations (ALFF) of the right anterior insula (AI) and right middle frontal gyrus which showed greater ALFF than non-depressed controls before training; Functional connectivity strength between right AI and the right frontoinsular and right supramarginal gyrus were significantly decreased after training within the ABM group; moreover, the improvement of depression symptoms following ABM significantly correlated with the connectivity strength reductions between right AI and right frontoinsular and right supramarginal gyrus.

Conclusion

These results suggest that ABM has the potential to reshape the abnormal patterns of spontaneous brain activity in relevant neural circuits associated with depression.

Keywords

Attentional bias modificationbrain plasticityresting-state fMRIsubthreshold depression
Type
Original Articles
Information
Psychological Medicine , Volume 46 , Issue 5 , April 2016 , pp. 909 - 920
Copyright
Copyright © Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arditte, KA, Joormann, J (2014). Rumination moderates the effects of cognitive bias modification of attention. Cognitive Therapy and Research 38, 189–199.CrossRefGoogle Scholar
Avery, JA, Drevets, WC, Moseman, SE, Bodurka, J, Barcalow, JC, Simmons, WK (2014). Major depressive disorder is associated with abnormal interoceptive activity and functional connectivity in the insula. Biological Psychiatry 76, 258–266.Google Scholar
Baert, S, De Raedt, R, Schacht, R, Koster, EH (2010). Attentional bias training in depression: therapeutic effects depend on depression severity. Journal of Behavior Therapy and Experimental Psychiatry 41, 265–274.Google Scholar
Beck, AT (1976). Cognitive Therapy and the Emotional Disorders. International Universities Press: Oxford.Google Scholar
Beck, AT (2008). The evolution of the cognitive model of depression and its neurobiological correlates. American Journal of Psychiatry 165, 969–977.CrossRefGoogle ScholarPubMed
Beck, AT, Steer, RA, Brown, G (1996). Manual for the Beck Depression Inventory – II. Psychological Corporation: San Antonio, TX.Google Scholar
Beevers, CG, Clasen, P, Stice, E, Schnyer, D (2010). Depression symptoms and cognitive control of emotion cues: a functional magnetic resonance imaging study. Neuroscience 167, 97–103.Google Scholar
Biswal, B, Zerrin Yetkin, F, Haughton, VM, Hyde, JS (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magnetic Resonance in Medicine 34, 537–541.Google Scholar
Britton, JC, Suway, JG, Clementi, MA, Fox, NA, Pine, DS, Bar-Haim, Y (2015). Neural changes with Attention Bias Modification (ABM): for anxiety: a randomized trial. Social Cognitive & Affective Neuroscience 10, 913–920.CrossRefGoogle ScholarPubMed
Brody, AL, Saxena, S, Stoessel, P, Gillies, LA, Fairbanks, LA, Alborzian, S, Phelps, ME, Huang, SC, Wu, HM, Ho, ML, Ho, MK, Au, SC, Maidment, K, Baxter, LR Jr. (2001). Regional brain metabolic changes in patients with major depression treated with either paroxetine or interpersonal therapy: preliminary findings. Archives of General Psychiatry 58, 631–640.CrossRefGoogle ScholarPubMed
Browning, M, Holmes, E, Harmer, C (2010 a). The modification of attentional bias to emotional information: a review of the techniques, mechanisms, and relevance to emotional disorders. Cognitive, Affective & Behavioral Neuroscience 10, 8–20.Google Scholar
Browning, M, Holmes, EA, Charles, M, Cowen, PJ, Harmer, CJ (2012). Using attentional bias modification as a cognitive vaccine against depression. Biological Psychiatry 72, 572–579.CrossRefGoogle ScholarPubMed
Browning, M, Holmes, EA, Murphy, SE, Goodwin, GM, Harmer, CJ (2010 b). Lateral prefrontal cortex mediates the cognitive modification of attentional bias. Biological Psychiatry 67, 919–925.Google Scholar
Chen, F, Lv, X, Fang, J, Yu, S, Sui, J, Fan, L, Li, T, Hong, Y, Wang, X, Wang, W, Jiang, T (2015). The effect of body–mind relaxation meditation induction on major depressive disorder: a resting-state fMRI study. Journal of Affective Disorders 183, 75–82.Google Scholar
Chumbley, J, Worsley, K, Flandin, G, Friston, K (2010). Topological FDR for neuroimaging. Neuroimage 49, 3057–3064.Google Scholar
Corbetta, M, Shulman, GL (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Review Neuroscience 3, 201–215.Google Scholar
Cuijpers, P, Smit, F, Van Straten, A (2007). Psychological treatments of subthreshold depression: a meta-analytic review. Acta Psychiatrica Scandinavica 115, 434–441.CrossRefGoogle ScholarPubMed
De Raedt, R, Koster, EH (2010). Understanding vulnerability for depression from a cognitive neuroscience perspective: a reappraisal of attentional factors and a new conceptual framework. Cognitive, Affective & Behavioral Neuroscience 10, 50–70.CrossRefGoogle Scholar
Disner, SG, Beevers, CG, Haigh, EAP, Beck, AT (2011). Neural mechanisms of the cognitive model of depression. Nature Reviews Neuroscience 12, 467–477.Google Scholar
Farb, NA, Anderson, AK, Segal, ZV (2012). The mindful brain and emotion regulation in mood disorders. Canadian Journal of Psychiatry 57, 70–77.CrossRefGoogle ScholarPubMed
First, MB, Spitzer, RL, Gibbon, M, Williams, JB (2001). Structured Clinical Interview for DSM-IV-TR Axis I Disorders-Patient Edition (SCID-I/P. 2/2001 Revision). Biometrics Research Department, New York State Psychiatric Institute: New York.Google Scholar
Foland-Ross, LC, Hamilton, JP, Joormann, J, Berman, MG, Jonides, J, Gotlib, IH (2013). The neural basis of difficulties disengaging from negative irrelevant material in major depression. Psychological Science 24, 334–344.Google Scholar
Frewen, PA, Dozois, DJ, Lanius, RA (2008). Neuroimaging studies of psychological interventions for mood and anxiety disorders: empirical and methodological review. Clinical Psychology Review 28, 228–246.Google Scholar
Fu, CH, Steiner, H, Costafreda, SG (2013). Predictive neural biomarkers of clinical response in depression: a meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies. Neurobiology of Disease 52, 75–83.Google Scholar
Goldapple, K, Segal, Z, Garson, C, Lau, M, Bieling, P, Kennedy, S, Mayberg, SH (2004). Modulation of cortical-limbic pathways in major depression: treatment-specific effects of cognitive behavior therapy. Archives of General Psychiatry 61, 34–41.Google Scholar
Gotlib, IH, Joormann, J, Foland-Ross, LC (2014). Understanding familial risk for depression: a 25-year perspective. Perspectives on Psychological Science 9, 94–108.Google Scholar
Hakamata, Y, Lissek, S, Bar-Haim, Y, Britton, JC, Fox, NA, Leibenluft, E, Ernst, M, Pine, DS (2010). Attention bias modification treatment: a meta-analysis toward the establishment of novel treatment for anxiety. Biological Psychiatry 68, 982–990.Google Scholar
Hallion, LS, Ruscio, AM (2011). A meta-analysis of the effect of cognitive bias modification on anxiety and depression. Psychological Bulletin 137, 940–958.Google Scholar
Hamilton, JP, Etkin, A, Furman, DJ, Lemus, MG, Johnson, RF, Gotlib, IH (2012). Functional neuroimaging of major depressive disorder: a meta-analysis and new integration of baseline activation and neural response data. American Journal of Psychiatry 169, 693–703.Google Scholar
Herwig, U, Kaffenberger, T, Baumgartner, T, Jäncke, L (2007). Neural correlates of a ‘pessimistic’ attitude when anticipating events of unknown emotional valence. Neuroimage 34, 848–858.Google Scholar
Johnson, DR (2009). Goal-directed attentional deployment to emotional faces and individual differences in emotional regulation. Journal of Research in Personality 43, 8–13.Google Scholar
Kaiser, RH, Andrews-Hanna, JR, Wager, TD, Pizzagalli, DA (2015). Large-scale network dysfunction in major depressive disorder a meta-analysis of resting-state functional connectivity. JAMA Psychiatry 72, 603–611.CrossRefGoogle ScholarPubMed
Karsten, J, Hartman, CA, Smit, JH, Zitman, FG, Beekman, AT, Cuijpers, P, van der Does, AJ, Ormel, J, Nolen, WA, Penninx, BW (2011). Psychiatric history and subthreshold symptoms as predictors of the occurrence of depressive or anxiety disorder within 2 years. British Journal of Psychiatry 198, 206–212.Google Scholar
Kennedy, SH, Konarski, JZ, Segal, ZV, Lau, MA, Bieling, PJ, McIntyre, RS, Mayberg, HS (2007). Differences in brain glucose metabolism between responders to CBT and venlafaxine in a 16-week randomized controlled trial. American Journal of Psychiatry 164, 778–788.Google Scholar
Kessler, RC (1994). Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: results from the National Comorbidity Survey. Archives of General Psychiatry 51, 8–9.Google Scholar
Liu, CH, Li, F, Li, SF, Wang, YJ, Tie, CL, Wu, HY, Zhou, Z, Zhang, D, Dong, J, Yang, Z, Wang, CY (2012). Abnormal baseline brain activity in bipolar depression: a resting state functional magnetic resonance imaging study. Psychiatry Research: Neuroimaging 203, 175–179.Google Scholar
Liu, CH, Ma, X, Wu, X, Fan, TT, Zhang, Y, Zhou, FC, Li, LJ, Li, F, Tie, CL, Li, SF, Zhang, D, Zhou, Z, Dong, J, Wang, YJ, Yao, L, Wang, CY (2013). Resting-state brain activity in major depressive disorder patients and their siblings. Journal of Affective Disorders 149, 299–306.Google Scholar
Lui, S, Wu, Q, Qiu, L, Yang, X, Kuang, W, Chan, RCK, Huang, X, Kemp, GJ, Mechelli, A, Gong, Q (2011). Resting-state functional connectivity in treatment-resistant depression. American Journal of Psychiatry 168, 642–648.Google Scholar
Ma, Y (2015). Neuropsychological mechanism underlying antidepressant effect: a systematic meta-analysis. Molecular Psychiatry 20, 311–319.Google Scholar
Månsson, KNT, Carlbring, P, Frick, A, Engman, J, Olsson, CJ, Bodlund, O, Furmark, T, Andersson, G (2013). Altered neural correlates of affective processing after internet-delivered cognitive behavior therapy for social anxiety disorder. Psychiatry Research: Neuroimaging 214, 229–237.Google Scholar
MacLeod, C, Mathews, A (2012). Cognitive bias modification approaches to anxiety. Annual Review of Clinical Psychology 8, 189–217.Google Scholar
MacLeod, C, Rutherford, E, Campbell, L, Ebsworthy, G, Holker, L (2002). Selective attention and emotional vulnerability: assessing the causal basis of their association through the experimental manipulation of attentional bias. Journal of Abnormal Psychology 111, 107–123.Google Scholar
Mayberg, HS, Lozano, AM, Voon, V, McNeely, HE, Seminowicz, D, Hamani, C, Schwalb, JM, Kennedy, SH (2005). Deep brain stimulation for treatment-resistant depression. Neuron 45, 651–660.CrossRefGoogle ScholarPubMed
McGrath, CL, Kelley, ME, Holtzheimer, PE, Dunlop, BW, Craighead, WE, Franco, AR, Craddock, RC, Mayberg, HS (2013). Toward a neuroimaging treatment selection biomarker for major depressive disorder. JAMA Psychiatry 70, 821–829.CrossRefGoogle Scholar
Menon, V (2011). Large-scale brain networks and psychopathology: a unifying triple network model. Trends in Cognitive Sciences 15, 483–506.Google Scholar
Menon, V, Uddin, LQ (2010). Saliency, switching, attention and control: a network model of insula function. Brain Structure and Function 214, 655–667.CrossRefGoogle ScholarPubMed
Mogoaşe, C, David, D, Koster, EH (2014). Clinical efficacy of attentional bias modification procedures: an updated meta-analysis. Journal of Clinical Psychology 70, 1133–1157.Google Scholar
Pannekoek, JN, Werff, S, Meens, PH, Bulk, BG, Jolles, DD, Veer, IM, van Lang, ADJ, Rombouts, SARB, van der Wee, NJA, Vermeiren, RR (2014). Aberrant resting-state functional connectivity in limbic and salience networks in treatment-naïve clinically depressed adolescents. Journal of Child Psychology and Psychiatry 55, 1317–1327.Google Scholar
Pennant, ME, Loucas, CE, Whittington, C, Creswell, C, Fonagy, P, Fuggle, P, Kelvinf, R, Naqvia, S, Stocktona, S, Kendall, T (2015). Computerised therapies for anxiety and depression in children and young people: a systematic review and meta-analysis. Behaviour Research and Therapy 67, 1–18.CrossRefGoogle Scholar
Roiser, JP, Elliott, R, Sahakian, BJ (2011). Cognitive mechanisms of treatment in depression. Neuropsychopharmacology 37, 117–136.Google Scholar
Seeley, WW, Menon, V, Schatzberg, AF, Keller, J, Glover, GH, Kenna, H, Reiss, AL, Greicius, MD (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. Journal of Neuroscience 27, 2349–2356.CrossRefGoogle ScholarPubMed
Sheline, YI, Barch, DM, Price, JL, Rundle, MM, Vaishnavi, SN, Snyder, AZ, Mintuna, MA, Wanga, S, Coalson, RS, Raichle, ME (2009). The default mode network and self-referential processes in depression. Proceedings of the National Academy of Sciences USA 106, 1942–1947.CrossRefGoogle ScholarPubMed
Sheline, YI, Price, JL, Yan, Z, Mintun, MA (2010). Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proceedings of the National Academy of Sciences USA 107, 11020–11025.Google Scholar
Spielberger, CD, Gorsuch, RL, Lushene, R, Vagg, PR, Jacobs, GA (1983). Manual for the state-trait anxiety inventory (STAI). Consulting Psychologists Press: Palo Alto, CA.Google Scholar
Sun, C, Wu, Z, Wu, Z, Xu, S (1994). Age differences in RAVEN test and the relation between the differences and memory training of ‘method of loci’. Acta Psychologica Sinica 26, 59–63.Google Scholar
Sylvester, CM, Barch, DM, Corbetta, M, Power, JD, Schlaggar, BL, Luby, JL (2013). Resting state functional connectivity of the ventral attention network in children with a history of depression or anxiety. Journal of the American Academy of Child & Adolescent Psychiatry 52, 1326–1336.Google Scholar
Taylor, CT, Aupperle, RL, Flagan, T, Simmons, AN, Amir, N, Stein, MB, Paulus, MP (2014). Neural correlates of a computerized attention modification program in anxious subjects. Social Cognitive & Affective Neuroscience 9, 1379–1387.Google Scholar
Tottenham, N, Tanaka, JW, Leon, AC, McCarry, T, Nurse, M, Hare, TA, Marcus, DJ, Westerlund, A, Casey, BJ, Nelson, C (2009). The NimStim set of facial expressions: judgments from untrained research participants. Psychiatry Research 168, 242–249.Google Scholar
Thomas, C, Baker, CI (2013). Teaching an adult brain new tricks: a critical review of evidence for training-dependent structural plasticity in humans. Neuroimage 73, 225–236.CrossRefGoogle Scholar
Vossel, S, Geng, JJ, Fink, GR (2014). Dorsal and ventral attention systems distinct neural circuits but collaborative roles. The Neuroscientist 20, 150–159.Google Scholar
Wells, TT, Beevers, CG (2010). Biased attention and dysphoria: manipulating selective attention reduces subsequent depressive symptoms. Cognition and Emotion 24, 719–728.Google Scholar
Weingarten, CP, Strauman, TJ (2015). Neuroimaging for psychotherapy research: current trends . Psychotherapy Research 25, 185–213.Google Scholar
Wu, QZ, Li, DM, Kuang, WH, Zhang, TJ, Lui, S, Huang, XQ, Chan, RC, Kemp, GJ, Gong, QY (2011). Abnormal regional spontaneous neural activity in treatment-refractory depression revealed by resting-state fMRI. Human Brain Mapping 32, 1290–1299.Google Scholar
Yang, W, Ding, Z, Dai, T, Peng, F, Zhang, JX (2014). Attention Bias Modification training in individuals with depressive symptoms: a randomized controlled trial. Journal of Behavior Therapy and Experimental Psychiatry 49, 101–111.Google Scholar
Zang, YF, He, Y, Zhu, CZ, Cao, QJ, Sui, MQ, Liang, M, Tian, LX, Jiang, TZ, Wang, YF (2007). Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain & Development 29, 83–91.Google Scholar
Zhou, Y, Yu, C, Zheng, H, Liu, Y, Song, M, Qin, W, Li, K, Jiang, T (2010). Increased neural resources recruitment in the intrinsic organization in major depression. Journal of Affective Disorders 121, 220–230.Google Scholar
Supplementary material: File

Li supplementary material

Li supplementary material 1

Download Li supplementary material(File)
File 314.9 KB