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A Cross-sectional Study of Attention Bias for Facial Expression Stimulation in Patients with Stroke at the Convalescence Stage

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A Correction to this article was published on 18 December 2020

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Abstract

Background

Post-stroke depression increases the likelihood of adverse physical symptoms. Attentional bias (AB) for negative stimuli is important in depression onset, maintenance, and remission. Stroke is more likely in older adults, who can have reduced cognitive function. Individuals with mild cognitive impairment (MCI) can have delayed reaction times (RTs). We hypothesized that RT to select neutral facial expression is affected by depressive symptoms and cognitive function in patients with stroke.

Methods

This study analyzed 61 patients with stroke. Beck Depression Inventory-Second Edition (BDI-II) and Profile of Mood States (short version) scores were determined. Task stimuli comprised eight pairs of facial expressions containing affective (angry) and neutral faces. AB was measured as the RT to select the neutral face in two simultaneously presented images using attention bias modification (ABM) software. Patients were grouped according to depressive symptoms using BDI-II scores. Between-subject factors of depressive symptoms and cognitive function were determined by ANCOVA.

Results

No significant interaction was found between depressive symptoms and cognitive function on RT. There was a main effect of cognitive function, but not depressive symptoms. In patients with hemiparesis and depressive symptoms, RT was significantly shorter in patients without MCI compared with patients with MCI.

Conclusions

People with stroke and elevated depression symptoms with hemiparesis but without MCI quickly selected neutral facial expressions from neutral and aversive expressions, and thus do not need ABM to escape aversive stimuli. ABM in response to aversive stimuli may be useful in evaluating negative emotions in individuals with post-stroke depression without MCI.

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References

  1. Mitchell AJ, Sheth B, Gill J, et al. Prevalence and predictors of post-stroke mood disorders: a meta-analysis and meta-regression of depression, anxiety and adjustment disorder. Gen Hosp Psychiatry. 2017;47:48–60.

    Article  PubMed  Google Scholar 

  2. Hackett ML, Yapa C, Parag V, Anderson CS. Frequency of depression after stroke: a systematic review of observational studies. Stroke. 2005;36:1330–40.

    Article  PubMed  Google Scholar 

  3. Krishnamurthi RV, Feigin VL, Forouzanfar MH, et al. Global and regional burden of first-ever ischaemic and haemorrhagic stroke during 1990–2010: findings from the Global Burden of Disease Study. Lancet Glob Health. 2010;2013:e259-281.

    Google Scholar 

  4. Li J, Oakley LD, Brown RL, Li Y, Ye M, Luo Y. Early symptom measurement of post-stroke depression (PSD). J Affect Disord. 2016;197:215–22.

    Article  PubMed  Google Scholar 

  5. Wuthrich VM, Johnco CJ, Wetherell JL. Differences in anxiety and depression symptoms: comparison between older and younger clinical samples. Int Psychogeriatr. 2015;27:1523–32.

    Article  PubMed  Google Scholar 

  6. Wei J, Ying M, Xie L, et al. Late-life depression and cognitive function among older adults in the U.S.: The National Health and Nutrition Examination Survey 2011–2014. J Psychiatr Res. 2019;111:30–5.

    Article  PubMed  Google Scholar 

  7. Akinyemi RO, Allan L, Owolabi MO, et al. Profile and determinants of vascular cognitive impairment in African stroke survivors: the CogFAST Nigeria Study. J Neurol Sci. 2014;346:241–9.

    Article  PubMed  Google Scholar 

  8. Ezema CI, Akusoba PC, Nweke MC, Uchewoke CU, Agono J, Usoro G. Influence of post-stroke depression on functional independence in activities of daily living. Ethiop J Health Sci. 2019;29:841–6.

    PubMed  PubMed Central  Google Scholar 

  9. Fujita T, Sato A, Tsuchiya K, et al. Relationship between grooming performance and motor and cognitive functions in stroke patients with receiver operating characteristic analysis. J Stroke Cerebrovasc Dis. 2017;26:2828–33.

    Article  PubMed  Google Scholar 

  10. Haghgoo HA, Pazuki ES, Hosseini AS, Rassafiani M. Depression, activities of daily living and quality of life in patients with stroke. J Neurol Sci. 2013;328:87–91.

    Article  PubMed  Google Scholar 

  11. Mathews A, MacLeod C. Cognitive vulnerability to emotional disorders. Annu Rev Clin Psychol. 2005;1:167–95.

    Article  PubMed  Google Scholar 

  12. Taylor JL, John CH. Attentional and memory bias in persecutory delusions and depression. Psychopathology. 2004;37:233–41.

    Article  PubMed  Google Scholar 

  13. Cavanagh J, Geisler MW. Mood effects on the ERP processing of emotional intensity in faces: a P3 investigation with depressed students. Int J Psychophysiol. 2006;60:27–33.

    Article  PubMed  Google Scholar 

  14. Joormann J, Gotlib IH. Selective attention to emotional faces following recovery from depression. J Abnorm Psychol. 2007;116:80–5.

    Article  PubMed  Google Scholar 

  15. Koster EH, Crombez G, Verschuere B, Van Damme S, Wiersema JR. Components of attentional bias to threat in high trait anxiety: facilitated engagement, impaired disengagement, and attentional avoidance. Behav Res Ther. 2006;44:1757–71.

    Article  PubMed  Google Scholar 

  16. Surguladze S, Brammer MJ, Keedwell P, et al. A differential pattern of neural response toward sad versus happy facial expressions in major depressive disorder. Biol Psychiatry. 2005;57:201–9.

    Article  PubMed  Google Scholar 

  17. MacLeod C, Rutherford E, Campbell L, Ebsworthy G, Holker L. Selective attention and emotional vulnerability: assessing the causal basis of their association through the experimental manipulation of attentional bias. J Abnorm Psychol. 2002;111:107–23.

    Article  PubMed  Google Scholar 

  18. Leyman L, De Raedt R, Vanderhasselt MA, Baeken C. Effects of repetitive transcranial magnetic stimulation of the dorsolateral prefrontal cortex on the attentional processing of emotional information in major depression: a pilot study. Psychiatry Res. 2011;185:102–7.

    Article  PubMed  Google Scholar 

  19. Dai Q, Hu L, Feng Z. Attentional bias modification reduces clinical depression and enhances attention toward happiness. J Psychiatr Res. 2019;109:145–55.

    Article  PubMed  Google Scholar 

  20. Lazarov A, Bar-Haim Y. Attention bias modification treatment reduces depression symptoms in youth. J Am Acad Child Adolesc Psychiatry. 2016;55:161–2.

    Article  PubMed  Google Scholar 

  21. Yang W, Zhang JX, Ding Z, Xiao L. Attention bias modification treatment for adolescents with major depression: a randomized controlled trial. J Am Acad Child Adolesc Psychiatry. 2016;55(208–218):e2.

    Google Scholar 

  22. Mohlman J, Price RB, Vietri J. Attentional bias in older adults: effects of generalized anxiety disorder and cognitive behavior therapy. J Anxiety Disord. 2013;27:585–91.

    Article  PubMed  Google Scholar 

  23. Reed AE, Chan L, Mikels JA. Meta-analysis of the age-related positivity effect: age differences in preferences for positive over negative information. Psychol Aging. 2014;29:1–15.

    Article  PubMed  Google Scholar 

  24. Namaky N, Beltzer ML, Werntz AJ, Lambert AE, Isaacowitz DM, Teachman BA. Moderators of age effects on attention bias toward threat and its association with anxiety. J Affect Disord. 2017;216:46–57.

    Article  PubMed  Google Scholar 

  25. Carstensen LL, DeLiema M. The positivity effect: a negativity bias in youth fades with age. Curr Opin Behav Sci. 2018;19:7–12.

    Article  PubMed  Google Scholar 

  26. Isaacowitz DM, Toner K, Goren D, Wilson HR. Looking while unhappy: mood-congruent gaze in young adults, positive gaze in older adults. Psychol Sci. 2008;19:848–53.

    Article  PubMed  Google Scholar 

  27. Prochwicz K, Gawęda Ł. Depression and anxiety mediate the relationship between temperament and character and psychotic-like experiences in healthy subjects. Psychiatry Res. 2016;246:195–202.

    Article  PubMed  Google Scholar 

  28. Balestri M, Porcelli S, Souery D, et al. Temperament and character influence on depression treatment outcome. J Affect Disord. 2019;252:464–74.

    Article  PubMed  Google Scholar 

  29. Afanasiev S, Aharon-Peretz J, Granot M. Personality type as a predictor for depressive symptoms and reduction in quality of life among stroke survivals. Am J Geriatr Psychiatry. 2013;21:832–9.

    Article  PubMed  Google Scholar 

  30. Wilson RS, Boyle PA, Levine SR, et al. Harm avoidance and cerebral infarction. Neuropsychology. 2014;28:305–11.

    Article  PubMed  Google Scholar 

  31. Choi JS, Park SM, Roh MS, et al. Dysfunctional inhibitory control and impulsivity in internet addiction. Psychiatry Res. 2014;215:424–8.

    Article  PubMed  Google Scholar 

  32. van Peer JM, Roelofs K, Rotteveel M, van Dijk JG, Spinhoven P, Ridderinkhof KR. The effects of cortisol administration on approach-avoidance behavior: an event-related potential study. Biol Psychol. 2007;76:135–46.

    Article  PubMed  Google Scholar 

  33. Knight M, Seymour TL, Gaunt JT, Baker C, Nesmith K, Mather M. Aging and goal-directed emotional attention: distraction reverses emotional biases. Emotion. 2007;7:705–14.

    Article  PubMed  Google Scholar 

  34. Gupta RS, Kujawa A, Vago DR. The neural chronometry of threat-related attentional bias: event-related potential (ERP) evidence for early and late stages of selective attentional processing. Int J Psychophysiol. 2019;146:20–42.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Inui K, Kakigi R. Temporal analysis of the flow from V1 to the extrastriate cortex in humans. J Neurophysiol. 2006;96:775–84.

    Article  PubMed  Google Scholar 

  36. Di Russo F, Berchicci M, Bianco V, et al. Normative event-related potentials from sensory and cognitive tasks reveal occipital and frontal activities prior and following visual events. Neuroimage. 2019;196:173–87.

    Article  PubMed  Google Scholar 

  37. Patel SH, Azzam PN. Characterization of N200 and P300: selected studies of the event-related potential. Int J Med Sci. 2005;2:147–54.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Ziemann U, Tergau F, Wassermann EM, Wischer S, Hildebrandt J, Paulus W. Demonstration of facilitatory I wave interaction in the human motor cortex by paired transcranial magnetic stimulation. J Physiol. 1998;511:181–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Beard C, Sawyer AT, Hofmann SG. Efficacy of attention bias modification using threat and appetitive stimuli: a meta-analytic review. Behav Ther. 2012;43:724–40.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Demeyer I, Sanchez A, De Raedt R. Older adults’ attentional deployment: differential gaze patterns for different negative mood states. J Behav Ther Exp Psychiatry. 2017;55:49–56.

    Article  PubMed  Google Scholar 

  41. Bar-Haim Y, Lamy D, Pergamin L, Bakermans-Kranenburg MJ, van IJzendoorn MH. Threat-related attentional bias in anxious and nonanxious individuals: a meta-analytic study. Psychol Bull. 2007;133:1–24.

    Article  PubMed  Google Scholar 

  42. Broomfield NM, Davies R, MacMahon K, Ali F, Cross SM. Further evidence of attention bias for negative information in late life depression. Int J Geriatr Psychiatry. 2007;22:175–80.

    Article  PubMed  Google Scholar 

  43. Armstrong T, Olatunji BO. Eye tracking of attention in the affective disorders: a meta-analytic review and synthesis. Clin Psychol Rev. 2012;32:704–23.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Kuckertz JM, Najmi S, Baer K. Amir N. Refining the analysis of mechanism-outcome relationships for anxiety treatment: A preliminary investigation using mixed models. Behav Modif; 2019. p. 1454455198421055.

    Google Scholar 

  45. See J, MacLeod C, Bridle R. The reduction of anxiety vulnerability through the modification of attentional bias: a real-world study using a home-based cognitive bias modification procedure. J Abnorm Psychol. 2009;118:65–75.

    Article  PubMed  Google Scholar 

  46. Luo X, Ikani N, Barth A, Rengers L, Becker E, Rinck M. Attention bias modification in specific fears: spiders versus snakes. J Behav Ther Exp Psychiatry. 2015;49(Pt A):30–6.

    Article  PubMed  Google Scholar 

  47. Sharpe L, Johnson A, Dear BF. Attention bias modification and its impact on experimental pain outcomes: comparison of training with words versus faces in pain. Eur J Pain. 2015;19:1248–57.

    Article  CAS  PubMed  Google Scholar 

  48. Campbell A, Murray JE, Atkinson L, Ruffman T. Face age and eye gaze influence older adults’ emotion recognition. J Gerontol B Psychol Sci Soc Sci. 2017;72:633–6.

    PubMed  Google Scholar 

  49. Shiroma PR, Thuras P, Johns B, Lim KO. Facial recognition of happiness among older adults with active and remitted major depression. Psychiatry Res. 2016;243:287–91.

    Article  PubMed  Google Scholar 

  50. Braun M, Traue HC, Frisch S, Deighton RM, Kessler H. Emotion recognition in stroke patients with left and right hemispheric lesion: results with a new instrument-the FEEL Test. Brain Cogn. 2005;58:193–201.

    Article  CAS  PubMed  Google Scholar 

  51. Abbott JD, Wijeratne T, Hughes A, Perre D, Lindell AK. The perception of positive and negative facial expressions by unilateral stroke patients. Brain Cogn. 2014;86:42–54.

    Article  PubMed  Google Scholar 

  52. Hussein T, Yiou E, Larue J. Age-related differences in motor coordination during simultaneous leg flexion and finger extension: influence of temporal pressure. PLoS ONE. 2013;8:e83064.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Mary A, Bourguignon M, Wens V, et al. Aging reduces experience-induced sensorimotor plasticity. A magnetoencephalographic study Neuroimage. 2015;104:59–68.

    Article  PubMed  Google Scholar 

  54. Salek Y, Anderson ND, Sergio L. Mild cognitive impairment is associated with impaired visual-motor planning when visual stimuli and actions are incongruent. Eur Neurol. 2011;66:283–93.

    Article  PubMed  Google Scholar 

  55. Warmenhoven F, van Rijswijk E, Engels Y, et al. The Beck Depression Inventory (BDI-II) and a single screening question as screening tools for depressive disorder in Dutch advanced cancer patients. Support Care Cancer. 2012;20:319–24.

    Article  PubMed  Google Scholar 

  56. Huffman JC, Doughty CT, Januzzi JL, Pirl WF, Smith FA, Fricchione GL. Screening for major depression in post-myocardial infarction patients: operating characteristics of the Beck Depression Inventory-II. Int J Psychiatry Med. 2010;40:187–97.

    Article  PubMed  Google Scholar 

  57. Evans TC, Britton JC. Improving the psychometric properties of dot-probe attention measures using response-based computation. J Behav Ther Exp Psychiatry. 2018;60:95–103.

    Article  PubMed  Google Scholar 

  58. Koizumi K, Tayama J, Ishioka T, et al. Anxiety, fatigue, and attentional bias toward threat in patients with hematopoietic tumors. PLoS ONE. 2018;13:e0192056.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Dailey MN, Joyce C, Lyons MJ, et al. Evidence and a computational explanation of cultural differences in facial expression recognition. Emotion. 2010;10:874–93.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Kojima M, Furukawa TA, Takahashi H, Kawai M, Nagaya T, Tokudome S. Cross-cultural validation of the Beck Depression Inventory-II in Japan. Psychiatry Res. 2002;110:291–9.

    Article  PubMed  Google Scholar 

  61. Lerdal A, Kottorp A, Gay CL, Grov EK, Lee KA. Rasch analysis of the Beck Depression Inventory-II in stroke survivors: a cross-sectional study. J Affect Disord. 2014;158:48–52.

    Article  PubMed  Google Scholar 

  62. Yokoyama K, Araki S, Kawakami N. Takeshita T [Production of the Japanese edition of profile of mood states (POMS): assessment of reliability and validity]. Nihon Koshu Eisei Zasshi. 1990;37:913–8.

    CAS  PubMed  Google Scholar 

  63. Ohnishi A, Mori K, Kohriyama K, Miyata M, Murai Y. Ikeda M [Japanese translation of profile of mood states (POMS)–interpretation of the fifty-six items of mood factors and their application in a manufacturing automotive parts factory]. J UOEH. 1993;15:147–54.

    Article  CAS  PubMed  Google Scholar 

  64. Bour A, Rasquin S, Boreas A, Limburg M, Verhey F. How predictive is the MMSE for cognitive performance after stroke? J Neurol. 2010;257:630–7.

    Article  PubMed  Google Scholar 

  65. Shigemori K, Ohgi S, Okuyama E, Shimura T, Schneider E. The factorial structure of the Mini-Mental State Examination (MMSE) in Japanese dementia patients. BMC Geriatr. 2010;10:36.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Roalf DR, Moore TM, Mechanic-Hamilton D, et al. Bridging cognitive screening tests in neurologic disorders: a crosswalk between the short Montreal Cognitive Assessment and Mini-Mental State Examination. Alzheimers Dement. 2017;13:947–52.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Tsai JC, Chen CW, Chu H, et al. Comparing the sensitivity, specificity, and predictive values of the Montreal cognitive assessment and mini-mental state examination when screening people for mild cognitive impairment and dementia in Chinese population. Arch Psychiatr Nurs. 2016;30:486–91.

    Article  PubMed  Google Scholar 

  68. Brunnstrom S. Motor testing procedures in hemiplegia: based on sequential recovery stages. Phys Ther. 1966;46:357–75.

    Article  CAS  PubMed  Google Scholar 

  69. Kokura Y, Maeda K, Wakabayashi H, Nishioka S, Higashi S. High nutritional-related risk on admission predicts less improvement of functional independence measure in geriatric stroke patients: a retrospective cohort study. J Stroke Cerebrovasc Dis. 2016;25:1335–41.

    Article  PubMed  Google Scholar 

  70. Umehara T, Tanaka R, Tsunematsu M, et al. Can the amount of interventions during the convalescent phase predict the achievement of independence in activities of daily living in patients with stroke? A retrospective cohort study. J Stroke Cerebrovasc Dis. 2018;27:2436–44.

    Article  PubMed  Google Scholar 

  71. Hanley CJ, Burianová H, Tommerdahl M. Towards establishing age-related cortical plasticity on the basis of somatosensation. Neuroscience. 2019;404:407–12.

    Article  CAS  PubMed  Google Scholar 

  72. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39:175–91.

    Article  PubMed  Google Scholar 

  73. Phillips M, Rogers P, Haworth J, Bayer A, Tales A. Intra-individual reaction time variability in mild cognitive impairment and Alzheimer’s disease: gender, processing load and speed factors. PLoS ONE. 2013;8:e65712.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Missonnier P, Deiber MP, Gold G, et al. Working memory load-related electroencephalographic parameters can differentiate progressive from stable mild cognitive impairment. Neuroscience. 2007;150:346–56.

    Article  CAS  PubMed  Google Scholar 

  75. Demeyer I, De Raedt R. Attentional bias for emotional information in older adults: the role of emotion and future time perspective. PLoS ONE. 2013;8:e65429.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Vierck E, Joyce PR. Influence of personality and neuropsychological ability on social functioning and self-management in bipolar disorder. Psychiatry Res. 2015;229:715–23.

    Article  PubMed  Google Scholar 

  77. Van Bockstaele B, Notebaert L, MacLeod C, et al. The effects of attentional bias modification on emotion regulation. J Behav Ther Exp Psychiatry. 2019;62:38–48.

    Article  PubMed  Google Scholar 

  78. Bagurdes LA, Mesulam MM, Gitelman DR, Weintraub S, Small DM. Modulation of the spatial attention network by incentives in healthy aging and mild cognitive impairment. Neuropsychologia. 2008;46:2943–8.

    Article  PubMed  Google Scholar 

  79. Cabrera I, Brugos D, Montorio I. Attentional biases in older adults with generalized anxiety disorder. J Anxiety Disord. 2020;71:102207.

    Article  PubMed  Google Scholar 

  80. Levin O, Cuypers K, Netz Y, et al. Age-related differences in human corticospinal excitability during simple reaction time. Neurosci Lett. 2011;487:53–7.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

We would like to thank the rehabilitation staff at the Toda Chuo Rehabilitation Hospital for their help to accomplish this study.

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Authors and Affiliations

  1. Department of Rehabilitation, Graduate School of Health Sciences, Saitama Prefectural University, Saitama, Japan

    Hirokazu Takizawa, Toshiyuki Ishioka, Kohei Koizumi, Naoki Nakaya & Toyohiro Hamaguchi

  2. Faculty of Human Sciences, Waseda University, Saitama, Japan

    Jun Tayama

  3. Faculty of Health Sciences, Tokyo Kasei University, Saitama, Japan

    Makoto Suzuki

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  1. Hirokazu Takizawa
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Correspondence to Toyohiro Hamaguchi.

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Takizawa, H., Ishioka, T., Koizumi, K. et al. A Cross-sectional Study of Attention Bias for Facial Expression Stimulation in Patients with Stroke at the Convalescence Stage. Int.J. Behav. Med. 28, 511–522 (2021). https://doi.org/10.1007/s12529-020-09940-2

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