The effectiveness of working memory training on reducing depression through changing in attentional networks

Document Type : Original Article

Authors

1 Master of Cognitive Psychology, New Sciences and Technologies Campus, Semnan University, Semnan, Iran

2 استادیار، گروه علوم شناختی، دانشکده روانشناسی و علوم‌تربیتی، دانشگاه سمنان، سمنان، ایران

Abstract

Abstract
Introduction: Depression has always been one of the most common psychological disorders. The aim of this study was to investigate the effect of working memory training on improving depression symptoms and triple-attentional networks. Method: The current study includes 34 Semnan University students selected by the convenience sampling method and randomly placed in two groups. The pre-test consisting of BDI-II and computerized triple attention network test was performed on all subjects. Then, the experimental group underwent working memory training with N-Back for 5 sessions. The mentioned tests were performed as a post-test in similar conditions to the pre-test. Results: The analysis of covariance showed that visual working memory training with N-Back significantly diminishes depressive symptoms and the function of the triple attention network in students. The effect sizes for the variables of depressive symptoms and attention were 0.382 and 0.704, respectively. Conclusion: Due to the importance of optimal processing of beliefs in improving depressive symptoms according to cognitive theory and the decisive role of cognitive function of attention in this field, visual working memory training can be said to improve the noted symptoms through changes in the triple attention network. The practical implication of the present study is the usefulness of computer cognitive interventions to improve mental disorders. Thus, it is suggested to use visual working memory in computer tasks along with other interventions to improve depression.

Keywords

Main Subjects

References

  1. Shapiro MO, Short NA, Morabito D, Schmidt NB. Prospective associations between intolerance of uncertainty and psychopathology. Personality and Individual Differences. 2020 Nov 1;166:110210.
  2. Newton DF, Fee C, Nikolova YS, Sibille E. Altered GABAergic function, cortical microcircuitry, and information processing in depression. InNeurobiology of depression 2019 Jan 1 (pp. 315-329). Academic Press.
  3. Lau JY, Waters AM. Annual Research Review: An expanded account of information‐processing mechanisms in risk for child and adolescent anxiety and depression. Journal of Child Psychology and Psychiatry. 2017 Apr;58(4):387-407.
  4. Zaremba D, Kalthoff IS, Förster K, Redlich R, Grotegerd D, Leehr EJ, Meinert S, Dohm K, Bürger C, Enneking V, Böhnlein J. The effects of processing speed on memory impairment in patients with major depressive disorder. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 2019 Jun 8;92:494-500.
  5. Prado CE, Watt S, Crowe SF. A meta-analysis of the effects of antidepressants on cognitive functioning in depressed and non-depressed samples. Neuropsychology review. 2018 Mar;28(1):32-72.
  6. Qu C, Sas C, Doherty G. Exploring and designing for memory impairments in depression. InProceedings of the 2019 CHI conference on human factors in computing systems 2019 May 2 (pp. 1-15).
  7. Dillon DG, Pizzagalli DA. Mechanisms of memory disruption in depression. Trends in neurosciences. 2018 Mar 1;41(3):137-49.
  8. Bishop SJ, Gagne C. Anxiety, depression, and decision making: a computational perspective. Annual review of neuroscience. 2018 Jul 8;41:371-88.
  9. Culbreth AJ, Moran EK, Barch DM. Effort-cost decision-making in psychosis and depression: could a similar behavioral deficit arise from disparate psychological and neural mechanisms?. Psychological Medicine. 2018 Apr;48(6):889-904.
  10. Nowicka-Sauer K, Hajduk A, Kujawska-Danecka H, Banaszkiewicz D, Smoleńska Ż, Czuszyńska Z, Siebert J. Illness perception is significantly determined by depression and anxiety in systemic lupus erythematosus. Lupus. 2018 Mar;27(3):454-60.
  11. Maydych V. The interplay between stress, inflammation, and emotional attention: relevance for depression. Frontiers in neuroscience. 2019 Apr 24;13:384.
  12. Nejati V, Fathi E, Shahidi S, Salehinejad MA. Cognitive training for modifying interpretation and attention bias in depression: Relevance to mood improvement and implications for cognitive intervention in depression. Asian Journal of Psychiatry. 2019 Jan 1;39:23-8.
  13. Mennen AC, Norman KA, Turk-Browne NB. Attentional bias in depression: understanding mechanisms to improve training and treatment. Current opinion in psychology. 2019 Oct 1;29:266-73.
  14. Rose EJ, Ebmeier KP. Pattern of impaired working memory during major depression. Journal of affective disorders. 2006 Feb 1;90(2-3):149-61.
  15. Nazarboland N, Farzaneh H. Working Memory Impairments in Patients with Major Depressive Disorder. Iranian Journal of Psychiatry and Clinical Psychology. 2009;15(3):308-13. [Persian]
  16. Leone de Voogd E, Wiers RW, Zwitser RJ, Salemink E. Emotional working memory training as an online intervention for adolescent anxiety and depression: A randomised controlled trial. Australian Journal of Psychology. 2016 Sep 1;68(3):228-38.
  17. Wanmaker S, Geraerts E, Franken IH. A working memory training to decrease rumination in depressed and anxious individuals: a double-blind randomized controlled trial. Journal of affective disorders. 2015 Apr 1;175:310-9.
  18. Beloe P, Derakshan N. Adaptive working memory training can reduce anxiety and depression vulnerability in adolescents. Developmental science. 2020 Jul;23(4):e12831.
  19. Chaurasia N, Singh IL, Singh T, Tiwari T, Singh A. Effect of depression on attentional network system among rheumatoid arthritis patients—A cross-sectional study. Journal of Family Medicine and Primary Care. 2020 Apr;9(4):1974.
  20. Roy LB, Sparing R, Fink GR, Hesse MD. Modulation of attention functions by anodal tDCS on right PPC. Neuropsychologia. 2015 Jul 1;74:96-107.
  21. Posner MI, Raichle ME. Image of mind. Scientific American Library/Scientific American Books.‏ 1994.
  22. Fathi Rezaei Z, Farsi AR, Vaez Mousavi SMK. The effect of cognitive training on the efficiency of the executive control network of attention and processing speed (with Hebb's theory approach). Modern psychological research. 2014 Dec 22;36(9):75-100. [Persian]
  23. Eskandarnejad M, Rezaei F. The Effect of Aerobic Exercise on Neural Networks of Attention and Working Memory. The Neuroscience Journal of Shefaye Khatam. 2018 Apr 10;6(2):31-40. [Persian]
  24. Eskandarnejad M, Ashayeri H, Rezaei F. Investigate the Effect of Aerobic Activity with and without Cognitive Load on Alerting Network of Attention. Motor Behavior. 2017 Jul 23;9(28):173-88. [Persian]
  25. Askarian Kalat H, Efficacy of transcranial random noise stimulation (tRNS) on subjective tinnitus symptoms decrease and mood improvement: Comparison of bilateral auditory cortex and rDLPFC electrical stimulation. [M. A. Dissertation]. Mashhad: Ferdowsi university; 2017.
  26. Kasaeian K, Kiamanesh A, Bahrami H. A comparison of active memory performance and sustained attention among students with and without learning disabilities. Journal of Learning Disabilities. 2014; 3(4): 112-123. [Persian]
  27. Rezaei F, The effects of motor training with different level of cognitive load on attention networks and brain electrical activity. [M. A. Dissertation]. Tabriz: university of Tabriz; 2016.
  28. Carbone E, Vianello E, Carretti B, Borella E. Working memory training for older adults after major surgery: Benefits to cognitive and emotional functioning. The American Journal of Geriatric Psychiatry. 2019 Nov 1;27(11):1219-27.
  29. Zhao X, Dang C, Maes JH. Effects of working memory training on EEG, cognitive performance, and self-report indices potentially relevant for social anxiety. Biological Psychology. 2020 Feb 1;150:107840.
  30. Jopling E, Gotlib IH, LeMoult J. Effects of working memory training on cognitive, affective, and biological responses to stress in major depression: A novel cognitive bias modification protocol. Journal of affective disorders. 2020 Mar 15;265:45-51.
  31. Kamal Nia M. Kaviani Mehr S, Sahraji Sh. Effectiveness of N-Back training software on working memory in students with dyslexia. 2nd International Conference on Humanities, psychology & Sociak science. 2016 March 15. [Persian]
  32. Faissner M, Kriston L, Moritz S, Jelinek L. Course and stability of cognitive and metacognitive beliefs in depression. Depression and Anxiety. 2018 Dec;35(12):1239-46.
  33. Martin A, Boadi N, Fernandes C, Watt S, Robinson-Wood T. Applying resistance theory to depression in Black women. Journal of Systemic Therapies. 2013 Mar 1;32(1):1.
  34. Poorafkari, n. DSM-IV classification of mental disorders. (2000). Tehran: Azadeh Publishing. [Persian]
  35. Ishigami, Y., Eskes, G. A., Tyndall, A. V., Longman, R. S., Drogos, L. L., & Poulin, M. J. The Attention Network Test-Interaction (ANT-I): reliability and validity in healthy older adults. Experimental Brain Research, 2016 234(3), 815-827.
  36. MacLeod, J. W., Lawrence, M. A., McConnell, M. M., Eskes, G. A., Klein, R. M., & Shore, D. I. Appraising the ANT: Psychometric and theoretical considerations of the Attention Network Test. Neuropsychology, 2010 24(5), 637.
  37. Rahimi, Ch. Application of Beck's depression in Iranian students, clinical psychology and personality (Behavioral Sciences), 2014, 12, 10, 173-188. [Persian]

Files

History

  • Receive Date: 07 October 2022
  • Revise Date: 08 April 2023
  • Accept Date: 25 April 2023

Share

How to cite

Statistics