Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

Decreased intersubject synchrony in dynamic valence ratings of sad movie contents in dysphoric individuals.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • معلومة اضافية
    • المصدر:
      Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep
    • بيانات النشر:
      Original Publication: London : Nature Publishing Group, copyright 2011-
    • الموضوع:
    • نبذة مختصرة :
      Emotional reactions to movies are typically similar between people. However, depressive symptoms decrease synchrony in brain responses. Less is known about the effect of depressive symptoms on intersubject synchrony in conscious stimulus-related processing. In this study, we presented amusing, sad and fearful movie clips to dysphoric individuals (those with elevated depressive symptoms) and control participants to dynamically rate the clips' valences (positive vs. negative). We analysed both the valence ratings' mean values and intersubject correlation (ISC). We used electrodermal activity (EDA) to complement the measurement in a separate session. There were no group differences in either the EDA or mean valence rating values for each movie type. As expected, the valence ratings' ISC was lower in the dysphoric than the control group, specifically for the sad movie clips. In addition, there was a negative relationship between the valence ratings' ISC and depressive symptoms for sad movie clips in the full sample. The results are discussed in the context of the negative attentional bias in depression. The findings extend previous brain activity results of ISC by showing that depressive symptoms also increase variance in conscious ratings of valence of stimuli in a mood-congruent manner.
      (© 2021. The Author(s).)
    • References:
      American Psychiatric Association. American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders Fifth Edition. Arlington (2013).
      Beck, A. T. Depression: Clinical, experimental, and theoretical aspects. (Hoeber Medical Division, 1967).
      Beck, A. T. The evolution of the cognitive model of depression and its neurobiological correlates. Am. J. Psychiatry 165, 969–977 (2008). (PMID: 1862834810.1176/appi.ajp.2008.08050721)
      Peckham, A. D., McHugh, R. K. & Otto, M. W. A meta-analysis of the magnitude of biased attention in depression. Depress. Anxiety 27, 1135–1142 (2010). (PMID: 2104952710.1002/da.20755)
      Epp, A. M., Dobson, K. S., Dozois, D. J. A. & Frewen, P. A. A systematic meta-analysis of the Stroop task in depression. Clin. Psychol. Rev. 32, 316–328 (2012). (PMID: 2245979210.1016/j.cpr.2012.02.005)
      Caseras, X., Garner, M., Bradley, B. P. & Mogg, K. Biases in visual orienting to negative and positive scenes in dysphoria: An eye movement study. J. Abnorm. Psychol. 116, 491–497 (2007). (PMID: 1769670510.1037/0021-843X.116.3.491)
      Kellough, J. L., Beevers, C. G., Ellis, A. J. & Wells, T. T. Time course of selective attention in clinically depressed young adults: An eye tracking study. Behav. Res. Ther. https://doi.org/10.1016/j.brat.2008.07.004 (2008). (PMID: 10.1016/j.brat.2008.07.004187607712584153)
      Zhao, Q. et al. Early perceptual anomaly of negative facial expression in depression: An event-related potential study. Neurophysiol. Clin. 45, 435–443 (2015). (PMID: 2660297210.1016/j.neucli.2015.09.011)
      Zhang, D., He, Z., Chen, Y. & Wei, Z. Deficits of unconscious emotional processing in patients with major depression: An ERP study. J. Affect. Disord. 199, 13–20 (2016). (PMID: 2705764810.1016/j.jad.2016.03.056)
      Xu, Q. et al. Automatic processing of changes in facial emotions in dysphoria: A magnetoencephalography study. Front. Hum. Neurosci. 12, 1–17 (2018). (PMID: 10.3389/fnhum.2018.00186)
      Ruohonen, E. M., Alhainen, V. & Astikainen, P. Event-related potentials to task-irrelevant sad faces as a state marker of depression. Biol. Psychol. 149, 107806 (2020).
      Leppänen, J. M., Milders, M., Bell, J. S., Terriere, E. & Hietanen, J. K. Depression biases the recognition of emotionally neutral faces. Psychiatry Res. 128, 123–133 (2004). (PMID: 1548895510.1016/j.psychres.2004.05.020)
      Gollan, J. K., Pane, H. T., McCloskey, M. S. & Coccaro, E. F. Identifying differences in biased affective information processing in major depression. Psychiatry Res. 159, 18–24 (2008). (PMID: 18342954257194210.1016/j.psychres.2007.06.011)
      Hasson, U. Intersubject synchronization of cortical activity during natural vision. Science (80-. ). 303, 1634–1640 (2004).
      Hasson, U., Malach, R. & Heeger, D. J. Reliability of cortical activity during natural stimulation. Trends Cogn. Sci. 14, 40–48 (2010). (PMID: 2000460810.1016/j.tics.2009.10.011)
      Sachs, M. E., Habibi, A., Damasio, A. & Kaplan, J. T. Dynamic intersubject neural synchronization reflects affective responses to sad music. Neuroimage 218, 116512 (2020).
      Franchak, J. M., Heeger, D. J., Hasson, U. & Adolph, K. E. Free viewing Gaze behavior in infants and adults. Infancy 21, 262–287 (2016). (PMID: 2713457310.1111/infa.12119)
      Lahnakoski, J. M. et al. Synchronous brain activity across individuals underlies shared psychological perspectives. Neuroimage 100, 316–324 (2014). (PMID: 2493668710.1016/j.neuroimage.2014.06.022)
      Nguyen, M., Vanderwal, T. & Hasson, U. Shared understanding of narratives is correlated with shared neural responses. Neuroimage 184, 161–170 (2019). (PMID: 3021754310.1016/j.neuroimage.2018.09.010)
      Nummenmaa, L. et al. Emotions promote social interaction by synchronizing brain activity across individuals. Proc. Natl. Acad. Sci. U. S. A. 109, 9599–9604 (2012). (PMID: 22623534338613510.1073/pnas.1206095109)
      Lankinen, K., Saari, J., Hari, R. & Koskinen, M. Intersubject consistency of cortical MEG signals during movie viewing. Neuroimage 92, 217–224 (2014). (PMID: 2453105210.1016/j.neuroimage.2014.02.004)
      Lankinen, K. et al. Consistency and similarity of MEG- and fMRI-signal time courses during movie viewing. Neuroimage 173, 361–369 (2018). (PMID: 2948632510.1016/j.neuroimage.2018.02.045)
      Dmochowski, J. P., Sajda, P., Dias, J. & Parra, L. C. Correlated components of ongoing EEG point to emotionally laden attention - A possible marker of engagement?. Front. Hum. Neurosci. 6, 1–9 (2012). (PMID: 10.3389/fnhum.2012.00112)
      Ki, J. J., Kelly, S. P. & Parra, L. C. Attention strongly modulates reliability of neural responses to naturalistic narrative stimuli. J. Neurosci. 36, 3092–3101 (2016). (PMID: 26961961660175810.1523/JNEUROSCI.2942-15.2016)
      Poulsen, A. T., Kamronn, S., Dmochowski, J., Parra, L. C. & Hansen, L. K. EEG in the classroom: Synchronised neural recordings during video presentation. Sci. Rep. 7, 1–9 (2017). (PMID: 10.1038/srep43916)
      Maffei, A. Spectrally resolved EEG intersubject correlation reveals distinct cortical oscillatory patterns during free-viewing of affective scenes. Psychophysiology 57, 1–15 (2020). (PMID: 10.1111/psyp.13652)
      Chang, W. T. et al. Combined MEG and EEG show reliable patterns of electromagnetic brain activity during natural viewing. Neuroimage 114, 49–56 (2015). (PMID: 2584229010.1016/j.neuroimage.2015.03.066)
      Hasson, U. et al. Shared and idiosyncratic cortical activation patterns in autism revealed under continuous real-life viewing conditions. Autism Res. 2, 220–231 (2009). (PMID: 19708061277592910.1002/aur.89)
      Salmi, J. et al. The brains of high functioning autistic individuals do not synchronize with those of others. NeuroImage Clin. 3, 489–497 (2013). (PMID: 24273731383005810.1016/j.nicl.2013.10.011)
      Byrge, L., Dubois, J., Tyszka, J. M., Adolphs, R. & Kennedy, D. P. Idiosyncratic brain activation patterns are associated with poor social comprehension in autism. J. Neurosci. 35, 5837–5850 (2015). (PMID: 25855192438893610.1523/JNEUROSCI.5182-14.2015)
      Tu, P. C. et al. Reduced synchronized brain activity in schizophrenia during viewing of comedy movies. Sci. Rep. 9, 1–11 (2019). (PMID: 10.1038/s41598-019-48957-w)
      Yang, Z. et al. Individualized psychiatric imaging based on inter-subject neural synchronization in movie watching. Neuroimage 216, 116227 (2020).
      Guo, C. C., Nguyen, V. T., Hyett, M. P., Parker, G. B. & Breakspear, M. J. Out-of-sync: Disrupted neural activity in emotional circuitry during film viewing in melancholic depression. Sci. Rep. 5, 1–12 (2015).
      Gruskin, D. C., Rosenberg, M. D. & Holmes, A. J. Relationships between depressive symptoms and brain responses during emotional movie viewing emerge in adolescence. Neuroimage 216, 116217 (2020).
      Clark, D. A. & Beck, A. T. Cognitive theory and therapy of anxiety and depression: Convergence with neurobiological findings. Trends Cogn. Sci. 14, 418–424 (2010). (PMID: 2065580110.1016/j.tics.2010.06.007)
      Yiend, J. The effects of emotion on attention: A review of attentional processing of emotional information. Cogn. Emot. 24, 3–47 (2010). (PMID: 10.1080/02699930903205698)
      Dawson, M. E., Schell, A. M. & Filion, D. L. The electrodermal system. in Handbook of Psychophysiology 217–243. https://doi.org/10.1017/9781107415782.010 (Cambridge University Press, 2016).
      Berman, M. G. et al. Neural and behavioral effects of interference resolution in depression and rumination. Cogn. Affect. Behav. Neurosci. 11, 85–96 (2011). (PMID: 21264648400607410.3758/s13415-010-0014-x)
      Koster, E. H. W., De Lissnyder, E., Derakshan, N. & De Raedt, R. Understanding depressive rumination from a cognitive science perspective: The impaired disengagement hypothesis. Clin. Psychol. Rev. 31, 138–145 (2011). (PMID: 2081733410.1016/j.cpr.2010.08.005)
      Hautala, J., Loberg, O., Hietanen, J. K., Nummenmaa, L. & Astikainen, P. Effects of conversation content on viewing dyadic conversations. J. Eye Mov. Res. 9 (2016).
      Armstrong, T. & Olatunji, B. O. Eye tracking of attention in the affective disorders: A meta-analytic review and synthesis. Clin. Psychol. Rev. 32, 704–723 (2012). (PMID: 23059623355633810.1016/j.cpr.2012.09.004)
      Rantanen, M. et al. Attentional bias towards interpersonal aggression in depression – An eye movement study. Scand. J. Psychol. https://doi.org/10.1111/sjop.12735 (2021). (PMID: 10.1111/sjop.1273533956357)
      Berenbaum, H. & Oltmanns, T. F. Emotional experience and expression in schizophrenia and depression. J. Abnorm. Psychol. 101, 37–44 (1992). (PMID: 1537971437031610.1037/0021-843X.101.1.37)
      Sloan, D. M., Strauss, M. E., Quirk, S. W. & Sajatovic, M. Subjective and expressive emotional responses in depression. J. Affect. Disord. 46, 135–141 (1997). (PMID: 947961710.1016/S0165-0327(97)00097-9)
      Bylsma, L. M., Morris, B. H. & Rottenberg, J. A meta-analysis of emotional reactivity in major depressive disorder. Clin. Psychol. Rev. 28, 676–691 (2008). (PMID: 1800619610.1016/j.cpr.2007.10.001)
      Vuilleumier, P. How brains beware: Neural mechanisms of emotional attention. Trends Cogn. Sci. 9, 585–594 (2005). (PMID: 1628987110.1016/j.tics.2005.10.011)
      Fredrickson, B. L. The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. Am. Psychol. 56, 218–226 (2001). (PMID: 11315248312227110.1037/0003-066X.56.3.218)
      Bishop, S. J. Neurocognitive mechanisms of anxiety: An integrative account. Trends Cogn. Sci. 11, 307–316 (2007). (PMID: 1755373010.1016/j.tics.2007.05.008)
      Schaefer, A., Nils, F., Philippot, P. & Sanchez, X. Assessing the effectiveness of a large database of emotion-eliciting films: A new tool for emotion researchers. Cogn. Emot. 24, 1153–1172 (2010). (PMID: 10.1080/02699930903274322)
      Faul, F., Erdfelder, E., Lang, A.-G. & Buchner, A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 39, 175–191 (2007). (PMID: 1769534310.3758/BF03193146)
      Cohen, J. Statistical Power Analysis for the Behavioral Sciences. Statistical Power Analysis for the Behavioral Sciences. https://doi.org/10.4324/9780203771587 (Routledge, 1988).
      Beck, A. T., Steer, R. A. & Brown, G. K. Manual for the Beck Depression Inventory-II. (Psychol. Corp., 1996).
      Nummenmaa, L. et al. Emotional speech synchronizes brains across listeners and engages large-scale dynamic brain networks. Neuroimage 102, 498–509 (2014). (PMID: 2512871110.1016/j.neuroimage.2014.07.063)
      Luck, S. J. Basic principles of EPR recording. in An Introduction to the Event-Related Potential Technique 147–183 (Massachusetts Institute of Technology, 2014).
      Itkes, O., Kimchi, R., Haj-Ali, H., Shapiro, A. & Kron, A. Dissociating affective and semantic valence. J. Exp. Psychol. Gen. 146, 924–942 (2017). (PMID: 2841450810.1037/xge0000291)
      Benedek, M. & Kaernbach, C. Decomposition of skin conductance data by means of nonnegative deconvolution. Psychophysiology 47, 647–658 (2010). (PMID: 202305122904901)
      Benjamini, Y. & Yekutieli, D. The control of the false discovery rate in multiple testing under dependency. Ann. Stat. https://doi.org/10.1214/aos/1013699998 (2001). (PMID: 10.1214/aos/1013699998)
    • الموضوع:
      Date Created: 20210714 Date Completed: 20240725 Latest Revision: 20240725
    • الموضوع:
      20240726
    • الرقم المعرف:
      PMC8277793
    • الرقم المعرف:
      10.1038/s41598-021-93825-1
    • الرقم المعرف:
      34257384