Prefrontal cortical activation during working memory task anticipation contributes to discrimination between bipolar and unipolar depression

Abstract

Distinguishing bipolar disorder (BD) from major depressive disorder (MDD) is clinically challenging, especially during depressive episodes. While both groups are characterized by aberrant working memory and anticipatory processing, the role of these processes in discriminating BD from MDD remains unexplored. In this study, we examine how brain activation corresponding to anticipation of and performance on easy vs. difficult working memory tasks with emotional stimuli contributes to discrimination among BD, MDD, and healthy controls (HC). Depressed individuals with BD (n = 18), MDD (n = 23), and HC (n = 23) were scanned while performing a working memory task in which they had to first anticipate performance on 1-back (easy) or 2-back (difficult) tasks with happy, fearful, or neutral faces, and then, perform the task. Anticipation-related and task-related brain activation was measured in the whole brain using functional magnetic resonance imagining. We used an elastic-net regression for variable selection, and a random forest classifier for BD vs. MDD classification. The former selected the activation differences (1-back minus 2-back) in the lateral and medial prefrontal cortices (PFC) during task anticipation and performance on the working memory tasks with fearful and neutral faces as variables relevant for BD vs. MDD classification. BD vs. MDD were classified with 70.7% accuracy (p < 0.01) based on the neuroimaging measures alone, with 80.5% accuracy (p = 0.001) based on clinical measures alone, and with 85.4% accuracy (p < 0.001) based on clinical and neuroimaging measures together. These findings suggest that PFC activation during working memory task anticipation and performance may be an important biological marker distinguishing BD from MDD.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: N-back task.
Fig. 2: Behavioral results.
Fig. 3: Neuroimaging and elastic-net regression results.

References

  1. 1.

    Hirschfeld RMA, Lewis L, Vornik LA. Perceptions and impact of bipolar disorder: how far have we really come? Results of the national depressive and manic-depressive association 2000 survey of individuals with bipolar disorder. J Clin Psychiatry. 2003;64:161–74.

  2. 2.

    de Almeida JR, Phillips ML. Distinguishing between unipolar depression and bipolar depression: current and future clinical and neuroimaging perspectives. Biol Psychiatry. 2013;73:111–8.

  3. 3.

    Baddeley A. Working memory. Curr Biol. 2010;20:R136–40.

  4. 4.

    Owen AM, McMillan KM, Laird AR, Bullmore E. N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Hum Brain Mapp. 2005;25:46–59.

  5. 5.

    Jonides J, Schumacher EH, Smith EE, Lauber EJ, Awh E, Minoshima S, et al. Verbal working memory load affects regional brain activation as measured by PET. J Cogn Neurosci. 1997;9:462–75.

  6. 6.

    Nystrom LE, Braver TS, Sabb FW, Delgado MR, Noll DC, Cohen JD. Working memory for letters, shapes, and locations: fMRI evidence against stimulus-based regional organization in human prefrontal cortex. Neuroimage. 2000;11:424–46.

  7. 7.

    Manelis A, Reder LM. He who is well prepared has half won the battle: an FMRI study of task preparation. Cereb Cortex. 2015;25:726–35.

  8. 8.

    Manelis A, Reder LM. Effective connectivity among the working memory regions during preparation for and during performance of the n-back task. Front Hum Neurosci. 2014. https://doi.org/10.3389/fnhum.2014.00593.

  9. 9.

    Curtis CE, D’Esposito M. The effects of prefrontal lesions on working memory performance and theory. Cogn Affect Behav Neurosci. 2004;4:528–39.

  10. 10.

    Ueda K, Okamoto Y, Okada G, Yamashita H, Hori T, Yamawaki S. Brain activity during expectancy of emotional stimuli: an fMRI study. Neuroreport. 2003;14:51–5.

  11. 11.

    Sohn M-H, Albert MV, Jung K, Carter CS, Anderson JR. Anticipation of conflict monitoring in the anterior cingulate cortex and the prefrontal cortex. Proc Natl Acad Sci USA. 2007;104:10330–4.

  12. 12.

    Christopher G, MacDonald J. The impact of clinical depression on working memory. Cogn Neuropsychiatry. 2005;10:379–99.

  13. 13.

    Clark L, Iversen SD, Goodwin GM. Sustained attention deficit in bipolar disorder. Br J Psychiatry. 2002;180:313–9.

  14. 14.

    Gohier B, Ferracci L, Surguladze SA, Lawrence E, El Hage W, Kefi MZ, et al. Cognitive inhibition and working memory in unipolar depression. J Affect Disord. 2009;116:100–5.

  15. 15.

    Harvey P-O, Fossati P, Pochon J-B, Levy R, Lebastard G, Lehéricy S, et al. Cognitive control and brain resources in major depression: an fMRI study using the n-back task. Neuroimage. 2005;26:860–9.

  16. 16.

    Lee C-Y, Wang L-J, Lee Y, Hung C-F, Huang Y-C, Lee M-I, et al. Differentiating bipolar disorders from unipolar depression by applying the brief assessment of cognition in affective disorders. Psychol Med. 2018;48:929–38.

  17. 17.

    Marazziti D, Consoli G, Picchetti M, Carlini M, Faravelli L. Cognitive impairment in major depression. Eur J Pharm. 2010;626:83–6.

  18. 18.

    Roca M, Vives M, López-Navarro E, García-Campayo J, Gili M. Cognitive impairments and depression: a critical review. Actas Esp Psiquiatr. 2015;43:187–93.

  19. 19.

    Taylor Tavares JV, Clark L, Cannon DM, Erickson K, Drevets WC, Sahakian BJ. Distinct profiles of neurocognitive function in unmedicated unipolar depression and bipolar II depression. Biol Psychiatry. 2007;62:917–24.

  20. 20.

    Almeida JRC, Mourao-Miranda J, Aizenstein HJ, Versace A, Kozel FA, Lu H, et al. Pattern recognition analysis of anterior cingulated cortex blood flow to classify depression polarity. Br J Psychiatry. 2013;203:310–1.

  21. 21.

    Delvecchio G, Fossati P, Boyer P, Brambilla P, Falkai P, Gruber O, et al. Common and distinct neural correlates of emotional processing in Bipolar Disorder and Major Depressive Disorder: a voxel-based meta-analysis of functional magnetic resonance imaging studies. Eur Neuropsychopharmacol. 2012;22:100–13.

  22. 22.

    Fournier JC, Keener MT, Almeida J, Kronhaus DM, Phillips ML. Amygdala and whole-brain activity to emotional faces distinguishes major depressive disorder and bipolar disorder. Bipolar Disord. 2013;15:741–52.

  23. 23.

    Townsend J, Altshuler LL. Emotion processing and regulation in bipolar disorder: a review. Bipolar Disord. 2012;14:326–39.

  24. 24.

    Zhu Y, Quan W, Wang H, Ma Y, Yan J, Zhang H, et al. Prefrontal activation during a working memory task differs between patients with unipolar and bipolar depression: a preliminary exploratory study. J Affect Disord. 2018;225:64–70.

  25. 25.

    Andersen SM, Spielman LA, Bargh JA. Future-event schemas and certainty about the future: automaticity in depressives’ future-event predictions. J Pers Soc Psychol. 1992;63:711–23.

  26. 26.

    Strunk DR, Lopez H, DeRubeis RJ. Depressive symptoms are associated with unrealistic negative predictions of future life events. Behav Res Ther. 2006;44:861–82.

  27. 27.

    Bertocci MA, Bebko GM, Mullin BC, Langenecker SA, Ladouceur CD, Almeida JRC, et al. Abnormal anterior cingulate cortical activity during emotional n-back task performance distinguishes bipolar from unipolar depressed females. Psychol Med. 2012;42:1417–28.

  28. 28.

    Chase HW, Nusslock R, Almeida JR, Forbes EE, LaBarbara EJ, Phillips ML. Dissociable patterns of abnormal frontal cortical activation during anticipation of an uncertain reward or loss in bipolar versus major depression. Bipolar Disord. 2013;15:839–54.

  29. 29.

    Manelis A, Almeida JRC, Stiffler R, Lockovich JC, Aslam HA, Phillips ML. Anticipation-related brain connectivity in bipolar and unipolar depression: a graph theory approach. Brain. 2016;139:2554–66.

  30. 30.

    Roiser JP, Sahakian BJ. Hot and cold cognition in depression. CNS Spectr. 2013;18:139–49.

  31. 31.

    Zou H, Hastie T. Regularization and variable selection via the Elastic Net. J Royal Stat Soc. 2005;67:301–20.

  32. 32.

    Evans JS, Murphy MA, Holden ZA, Cushman SA. Modeling Species Distribution and Change Using Random Forest. In: Drew C, Wiersma Y, Huettmann F (eds). Predictive Species and Habitat Modeling in Landscape Ecology. New York, NY: Springer; 2011.

  33. 33.

    Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56–62.

  34. 34.

    Sheehan DV. MINI-Mini International neuropsychiatric interview-english version 5.0. 0-DSM-IV. J Clin Psychiatry. 1998;59:34–57.

  35. 35.

    Blair JR, Spreen O. Predicting premorbid IQ: a revision of the national adult reading test. Clin Neuropsychol. 1989;3:129–36.

  36. 36.

    Young RC, Biggs JT, Ziegler VE, Meyer DA. A rating scale for mania: reliability, validity and sensitivity. Br J Psychiatry. 1978;133:429–35.

  37. 37.

    Dell’Osso L, Armani A, Rucci P, Frank E, Fagiolini A, Corretti G, et al. Measuring mood spectrum: comparison of interview (SCI-MOODS) and self-report (MOODS-SR) instruments. Compr Psychiatry. 2002;43:69–73.

  38. 38.

    Spielberger CD, Gorsuch RL, Lushene R, Vagg PR, Jacobs GA. Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press; 1983.

  39. 39.

    Snaith RP, Hamilton M, Morley S, Humayan A, Hargreaves D, Trigwell P. A scale for the assessment of hedonic tone the Snaith-Hamilton Pleasure Scale. Br J Psychiatry. 1995;167:99–103.

  40. 40.

    Hassel S, Almeida JR, Kerr N, Nau S, Ladouceur CD, Fissell K, et al. Elevated striatal and decreased dorsolateral prefrontal cortical activity in response to emotional stimuli in euthymic bipolar disorder: no associations with psychotropic medication load. Bipolar Disord. 2008;10:916–27.

  41. 41.

    Manelis A, Reder LM. Effective connectivity among the working memory regions during preparation for and during performance of the n-back task. Front Hum Neurosci. 2014;8:593.

  42. 42.

    Tottenham N, Tanaka JW, Leon AC, McCarry T, Nurse M, Hare TA, et al. The NimStim set of facial expressions: judgments from untrained research participants. Psychiatry Res. 2009;168:242–9.

  43. 43.

    Goeleven E, De Raedt R, Leyman L, Verschuere B. The Karolinska directed emotional faces: a validation study. Cogn Emot. 2008;22:1094–118.

  44. 44.

    Abler B, Erk S, Herwig U, Walter H. Anticipation of aversive stimuli activates extended amygdala in unipolar depression. J Psychiatr Res. 2007;41:511–22.

  45. 45.

    Esteban O, Birman D, Schaer M, Koyejo OO, Poldrack RA, Gorgolewski KJ. MRIQC: advancing the automatic prediction of image quality in MRI from unseen sites. PLoS ONE. 2017;12:e0184661.

  46. 46.

    Esteban O, Markiewicz CJ, Blair RW, Moodie CA, Isik AI, Erramuzpe A, et al. fMRIPrep: a robust preprocessing pipeline for functional MRI. Nat Methods. 2019;16:111–6.

  47. 47.

    Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage. 1999;9:179–94.

  48. 48.

    Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging. 2001;20:45–57.

  49. 49.

    Cox RW, Hyde JS. Software tools for analysis and visualization of fMRI data. NMR Biomed. 1997;10:171–8.

  50. 50.

    Greve DN, Fischl B. Accurate and robust brain image alignment using boundary-based registration. Neuroimage. 2009;48:63–72.

  51. 51.

    Jenkinson M, Bannister P, Brady M, Smith S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage. 2002;17:825–41.

  52. 52.

    Pruim RHR, Mennes M, van Rooij D, Llera A, Buitelaar JK, Beckmann CF. ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data. Neuroimage. 2015;112:267–77.

  53. 53.

    Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. Neuroimage. 2014;92:381–97.

  54. 54.

    Lockhart R, Taylor J, Tibshirani RJ, Tibshirani R. A significance test for the LASSO. Ann Stat. 2014;42:413–68.

  55. 55.

    Taylor J, Tibshirani RJ. Statistical learning and selective inference. Proc Natl Acad Sci USA. 2015;112:7629–34.

  56. 56.

    Croxson PL, Walton ME, O’Reilly JX, Behrens TEJ, Rushworth MFS. Effort-based cost-benefit valuation and the human brain. J Neurosci. 2009;29:4531–41.

  57. 57.

    Herwig U, Baumgartner T, Kaffenberger T, Brühl A, Kottlow M, Schreiter-Gasser U, et al. Modulation of anticipatory emotion and perception processing by cognitive control. Neuroimage. 2007;37:652–62.

  58. 58.

    Badre D, Wagner AD. Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia. 2007;45:2883–901.

  59. 59.

    Oztekin I, Badre D. Distributed patterns of brain activity that lead to forgetting. Front Hum Neurosci. 2011;5:86.

  60. 60.

    Brass M, von Cramon DY. Selection for cognitive control: a functional magnetic resonance imaging study on the selection of task-relevant information. J Neurosci. 2004;24:8847–52.

  61. 61.

    Bush G, Shin LM, Holmes J, Rosen BR, Vogt BA. The Multi-Source Interference Task: validation study with fMRI in individual subjects. Mol Psychiatry. 2003;8:60.

  62. 62.

    Leppänen JM, Milders M, Bell JS, Terriere E, Hietanen JK. Depression biases the recognition of emotionally neutral faces. Psychiatry Res. 2004;128:123–33.

  63. 63.

    Manelis A, Huppert T, Rodgers E, Swartz HA, Phillips ML. The role of the right prefrontal cortex in recognition of facial emotional expressions in depressed individuals: fNIRS study. J Affect Disord. 2019;258:151–8.

  64. 64.

    Barbey AK, Koenigs M, Grafman J. Dorsolateral prefrontal contributions to human working memory. Cortex. 2013;49:1195–205.

  65. 65.

    Kaller CP, Rahm B, Spreer J, Weiller C, Unterrainer JM. Dissociable contributions of left and right dorsolateral prefrontal cortex in planning. Cereb Cortex. 2011;21:307–17.

  66. 66.

    Fellows LK, Farah MJ. Different underlying impairments in decision-making following ventromedial and dorsolateral frontal lobe damage in humans. Cereb Cortex. 2005;15:58–63.

  67. 67.

    Sagliano L, D’Olimpio F, Panico F, Gagliardi S, Trojano L. The role of the dorsolateral prefrontal cortex in early threat processing: a TMS study. Soc Cogn Affect Neurosci. 2016;11:1992–8.

  68. 68.

    Manelis A, Stiffler R, Lockovich JC, Almeida JRC, Aslam HA, Phillips ML. Longitudinal changes in brain activation during anticipation of monetary loss in bipolar disorder. Psychol Med. 2019;49:2781–8.

  69. 69.

    Hyun J, Sliwinski MJ, Smyth JM. Waking up on the wrong side of the bed: the effects of stress anticipation on working memory in daily life. J Gerontol B Psychol Sci Soc Sci. 2019;74:38–46.

Download references

Acknowledgements

The authors thank the participants for taking part in this research study.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Anna Manelis.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Manelis, A., Iyengar, S., Swartz, H.A. et al. Prefrontal cortical activation during working memory task anticipation contributes to discrimination between bipolar and unipolar depression. Neuropsychopharmacol. 45, 956–963 (2020). https://doi.org/10.1038/s41386-020-0638-7

Download citation