Counterfactual thinking induces different neural patterns of memory modification in anxious individuals.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
09 05 2024
09 05 2024
Historique:
received:
16
12
2023
accepted:
07
05
2024
medline:
10
5
2024
pubmed:
10
5
2024
entrez:
9
5
2024
Statut:
epublish
Résumé
Episodic counterfactual thinking (eCFT) is the process of mentally simulating alternate versions of experiences, which confers new phenomenological properties to the original memory and may be a useful therapeutic target for trait anxiety. However, it remains unclear how the neural representations of a memory change during eCFT. We hypothesized that eCFT-induced memory modification is associated with changes to the neural pattern of a memory primarily within the default mode network, moderated by dispositional anxiety levels. We tested this proposal by examining the representational dynamics of eCFT for 39 participants varying in trait anxiety. During eCFT, lateral parietal regions showed progressively more distinct activity patterns, whereas medial frontal neural activity patterns became more similar to those of the original memory. Neural pattern similarity in many default mode network regions was moderated by trait anxiety, where highly anxious individuals exhibited more generalized representations for upward eCFT (better counterfactual outcomes), but more distinct representations for downward eCFT (worse counterfactual outcomes). Our findings illustrate the efficacy of examining eCFT-based memory modification via neural pattern similarity, as well as the intricate interplay between trait anxiety and eCFT generation.
Identifiants
pubmed: 38724623
doi: 10.1038/s41598-024-61545-x
pii: 10.1038/s41598-024-61545-x
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
10630Informations de copyright
© 2024. The Author(s).
Références
De Brigard, F. & Parikh, N. Episodic counterfactual thinking. Curr. Dir. Psychol. Sci. 28, 59–66 (2019).
doi: 10.1177/0963721418806512
Branch, J. G. Individual differences in the frequency of voluntary & involuntary episodic memories, future thoughts, and counterfactual thoughts. Psychol. Res. https://doi.org/10.1007/s00426-023-01802-2 (2023).
doi: 10.1007/s00426-023-01802-2
pubmed: 36781455
Byrne, R. M. J. Mental models and counterfactual thoughts about what might have been. Trends Cogn. Sci. 6, 426–431 (2002).
pubmed: 12413576
doi: 10.1016/S1364-6613(02)01974-5
Mandel, D. Counterfactuals, emotions, and context. Cogn. Emot. 17, 139–159 (2003).
pubmed: 29715740
doi: 10.1080/02699930302275
Kahneman, D. & Miller, D. T. Norm theory: Comparing reality to its alternatives. Psychol. Rev. 93, 136–153 (1986).
doi: 10.1037/0033-295X.93.2.136
Roese, N. J. Counterfactual thinking. Psychol. Bull. 121, 133–148 (1997).
pubmed: 9000895
doi: 10.1037/0033-2909.121.1.133
De Brigard, F., Hanna, E., St Jacques, P. L. & Schacter, D. L. How thinking about what could have been affects how we feel about what was. Cogn. Emot. 33, 646–659 (2019).
pubmed: 29857781
doi: 10.1080/02699931.2018.1478280
Parikh, N., De Brigard, F. & LaBar, K. S. The efficacy of downward counterfactual thinking for regulating emotional memories in anxious individuals. Front. Psychol. 12, 5730 (2022).
doi: 10.3389/fpsyg.2021.712066
Speer, M. E., Ibrahim, S., Schiller, D. & Delgado, M. R. Finding positive meaning in memories of negative events adaptively updates memory. Nat. Commun. 12, 6601 (2021).
pubmed: 34782605
pmcid: 8593143
doi: 10.1038/s41467-021-26906-4
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).
pubmed: 20817334
doi: 10.1016/j.cpr.2010.08.005
Nolen-Hoeksema, S., Wisco, B. E. & Lyubomirsky, S. Rethinking rumination. Perspect. Psychol. Sci. 3, 400–424 (2008).
pubmed: 26158958
doi: 10.1111/j.1745-6924.2008.00088.x
Tagini, S. et al. Counterfactual thinking in psychiatric and neurological diseases: A scoping review. PLOS ONE 16, e0246388 (2021).
pubmed: 33592003
pmcid: 7886174
doi: 10.1371/journal.pone.0246388
Ruiselová, Z., Prokopcáková, A. & Kresánek, J. Counterfactual thinking as a coping strategy—Cognitive and emotional aspects. Stud. Psychol. 51, 237–249 (2009).
Parikh, N., LaBar, K. S. & De Brigard, F. Phenomenology of counterfactual thinking is dampened in anxious individuals. Cogn. Emot. 34, 1737–1745 (2020).
pubmed: 32752933
doi: 10.1080/02699931.2020.1802230
Schwabe, L. & Wolf, O. T. New episodic learning interferes with the reconsolidation of autobiographical memories. PLOS ONE 4, e7519 (2009).
pubmed: 19844577
pmcid: 2760149
doi: 10.1371/journal.pone.0007519
Walker, M. P., Brakefield, T., Allan Hobson, J. & Stickgold, R. Dissociable stages of human memory consolidation and reconsolidation. Nature 425, 616–620 (2003).
De Brigard, F., Addis, D. R., Ford, J. H., Schacter, D. L. & Giovanello, K. S. Remembering what could have happened: Neural correlates of episodic counterfactual thinking. Neuropsychologia 51, 2401–2414 (2013).
pubmed: 23376052
pmcid: 3919504
doi: 10.1016/j.neuropsychologia.2013.01.015
Van Hoeck, N. et al. Counterfactual thinking: An fMRI study on changing the past for a better future. Soc. Cogn. Affect. Neurosci. 8, 556–564 (2013).
pubmed: 22403155
doi: 10.1093/scan/nss031
Addis, D. R. & Schacter, D. L. Constructive episodic simulation: Temporal distance and detail of past and future events modulate hippocampal engagement. Hippocampus 18, 227–237 (2008).
pubmed: 18157862
doi: 10.1002/hipo.20405
Parikh, N., Ruzic, L., Stewart, G. W., Spreng, R. N. & De Brigard, F. What if? Neural activity underlying semantic and episodic counterfactual thinking. NeuroImage 178, 332–345 (2018).
pubmed: 29807153
doi: 10.1016/j.neuroimage.2018.05.053
Faul, L., St. Jacques, P. L., DeRosa, J. T., Parikh, N. & De Brigard, F. Differential contribution of anterior and posterior midline regions during mental simulation of counterfactual and perspective shifts in autobiographical memories. NeuroImage 215, 116843 (2020).
De Brigard, F., Nathan Spreng, R., Mitchell, J. P. & Schacter, D. L. Neural activity associated with self, other, and object-based counterfactual thinking. NeuroImage 109, 12–26 (2015).
Khoudary, A. et al. Neural differences between internal and external episodic counterfactual thoughts. Philos. Trans. R. Soc. B Biol. Sci. 377, 20210337 (2022).
doi: 10.1098/rstb.2021.0337
Kriegeskorte, N., Mur, M. & Bandettini, P. Representational similarity analysis—Connecting the branches of systems neuroscience. Front. Syst. Neurosci. 2, 4 (2008).
Shimamura, A. P. Episodic retrieval and the cortical binding of relational activity. Cogn. Affect. Behav. Neurosci. 11, 277–291 (2011).
pubmed: 21638193
doi: 10.3758/s13415-011-0031-4
Ramanan, S., Piguet, O. & Irish, M. Rethinking the role of the angular gyrus in remembering the past and imagining the future: The contextual integration model. Neuroscientist 24, 342–352 (2018).
pubmed: 29283042
doi: 10.1177/1073858417735514
McCormick, C., Barry, D. N., Jafarian, A., Barnes, G. R. & Maguire, E. A. vmPFC drives hippocampal processing during autobiographical memory recall regardless of remoteness. Cereb. Cortex 30, 5972–5987 (2020).
pubmed: 32572443
pmcid: 7899055
doi: 10.1093/cercor/bhaa172
Lin, W.-J., Horner, A. J. & Burgess, N. Ventromedial prefrontal cortex, adding value to autobiographical memories. Sci. Rep. 6, 28630 (2016).
pubmed: 27338616
pmcid: 4919650
doi: 10.1038/srep28630
Kocovski, N. L., Endler, N. S., Rector, N. A. & Flett, G. L. Ruminative coping and post-event processing in social anxiety. Behav. Res. Ther. 43, 971–984 (2005).
pubmed: 15967169
doi: 10.1016/j.brat.2004.06.015
Monforton, J., Vickers, K. & Antony, M. M. “If only I didn’t embarrass myself in front of the class!”: Social anxiety and upward counterfactual thinking. J. Soc. Clin. Psychol. 31, 312–328 (2012).
doi: 10.1521/jscp.2012.31.3.312
Gagne, C., Dayan, P. & Bishop, S. J. When planning to survive goes wrong: Predicting the future and replaying the past in anxiety and PTSD. Curr. Opin. Behav. Sci. 24, 89–95 (2018).
doi: 10.1016/j.cobeha.2018.03.013
Thakral, P. P., Madore, K. P., Kalinowski, S. E. & Schacter, D. L. Modulation of hippocampal brain networks produces changes in episodic simulation and divergent thinking. Proc. Natl. Acad. Sci. 117, 12729–12740 (2020).
pubmed: 32457143
pmcid: 7293701
doi: 10.1073/pnas.2003535117
St. Jacques, P. L., Szpunar, K. K. & Schacter, D. L. Shifting visual perspective during retrieval shapes autobiographical memories. NeuroImage 148, 103–114 (2017).
Bertossi, E., Aleo, F., Braghittoni, D. & Ciaramelli, E. Stuck in the here and now: Construction of fictitious and future experiences following ventromedial prefrontal damage. Neuropsychologia 81, 107–116 (2016).
pubmed: 26707714
doi: 10.1016/j.neuropsychologia.2015.12.015
McCormick, C., Ciaramelli, E., De Luca, F. & Maguire, E. A. Comparing and contrasting the cognitive effects of hippocampal and ventromedial prefrontal cortex damage: A review of human lesion studies. Neuroscience 374, 295–318 (2018).
pubmed: 28827088
doi: 10.1016/j.neuroscience.2017.07.066
Brand, M. & Markowitsch, H. J. Memory processes and the orbitofrontal cortex. In The Orbitofrontal Cortex (eds. Zald, D. & Rauch, S.). https://doi.org/10.1093/acprof:oso/9780198565741.003.0011 (Oxford University Press, 2006).
Hebscher, M. & Gilboa, A. A boost of confidence: The role of the ventromedial prefrontal cortex in memory, decision-making, and schemas. Neuropsychologia 90, 46–58 (2016).
pubmed: 27150705
doi: 10.1016/j.neuropsychologia.2016.05.003
Barrash, J., Tranel, D. & Anderson, S. W. Acquired personality disturbances associated with bilateral damage to the ventromedial prefrontal region. Dev. Neuropsychol. 18, 355–381 (2000).
pubmed: 11385830
doi: 10.1207/S1532694205Barrash
Camille, N. et al. The involvement of the orbitofrontal cortex in the experience of regret. Science 304, 1167–1170 (2004).
pubmed: 15155951
doi: 10.1126/science.1094550
Bertossi, E., Candela, V., De Luca, F. & Ciaramelli, E. Episodic future thinking following vmPFC damage: Impaired event construction, maintenance, or narration?. Neuropsychology 31, 337–348 (2017).
pubmed: 28054822
doi: 10.1037/neu0000345
Borsini, A., Wallis, A. S. J., Zunszain, P., Pariante, C. M. & Kempton, M. J. Characterizing anhedonia: A systematic review of neuroimaging across the subtypes of reward processing deficits in depression. Cogn. Affect. Behav. Neurosci. 20, 816–841 (2020).
pubmed: 32472419
pmcid: 7395022
doi: 10.3758/s13415-020-00804-6
Sumner, J. A., Griffith, J. W. & Mineka, S. Overgeneral autobiographical memory as a predictor of the course of depression: A meta-analysis. Behav. Res. Ther. 48, 614–625 (2010).
pubmed: 20399418
pmcid: 2878838
doi: 10.1016/j.brat.2010.03.013
Coricelli, G., Dolan, R. J. & Sirigu, A. Brain, emotion and decision making: The paradigmatic example of regret. Trends Cogn. Sci. 11, 258–265 (2007).
pubmed: 17475537
doi: 10.1016/j.tics.2007.04.003
Moneta, N., Garvert, M. M., Heekeren, H. R. & Schuck, N. W. Task state representations in vmPFC mediate relevant and irrelevant value signals and their behavioral influence. Nat. Commun. 14, 3156 (2023).
pubmed: 37258534
pmcid: 10232498
doi: 10.1038/s41467-023-38709-w
Du, J. Y., Hallford, D. J. & Busby Grant, J. Characteristics of episodic future thinking in anxiety: A systematic review and meta-analysis. Clin. Psychol. Rev. 95, 102162 (2022).
pubmed: 35660923
doi: 10.1016/j.cpr.2022.102162
Salgado, S. & Berntsen, D. My future is brighter than yours: The positivity bias in episodic future thinking and future self-images. Psychol. Res. 84, 1829–1845 (2020).
pubmed: 31037451
doi: 10.1007/s00426-019-01189-z
Epstude, K. & Roese, N. J. The functional theory of counterfactual thinking. Pers. Soc. Psychol. Rev. 12, 168–192 (2008).
pubmed: 18453477
pmcid: 2408534
doi: 10.1177/1088868308316091
Gamlin, J., Smallman, R., Epstude, K. & Roese, N. J. Dispositional optimism weakly predicts upward, rather than downward, counterfactual thinking: A prospective correlational study using episodic recall. PLOS ONE 15, e0237644 (2020).
pubmed: 32797102
pmcid: 7428155
doi: 10.1371/journal.pone.0237644
Buckner, R. L. & DiNicola, L. M. The brain’s default network: Updated anatomy, physiology and evolving insights. Nat. Rev. Neurosci. 20, 593–608 (2019).
pubmed: 31492945
doi: 10.1038/s41583-019-0212-7
D’Argembeau, A., Xue, G., Lu, Z.-L., Van der Linden, M. & Bechara, A. Neural correlates of envisioning emotional events in the near and far future. NeuroImage 40, 398–407 (2008).
pubmed: 18164213
doi: 10.1016/j.neuroimage.2007.11.025
Szpunar, K. K., St. Jacques, P. L., Robbins, C. A., Wig, G. S. & Schacter, D. L. Repetition-related reductions in neural activity reveal component processes of mental simulation. Soc. Cogn. Affect. Neurosci. 9, 712–722 (2014).
Wu, J. Q., Szpunar, K. K., Godovich, S. A., Schacter, D. L. & Hofmann, S. G. Episodic future thinking in generalized anxiety disorder. J. Anxiety Disord. 36, 1–8 (2015).
pubmed: 26398003
pmcid: 4658269
doi: 10.1016/j.janxdis.2015.09.005
Ferris, C. S., Inman, C. S. & Hamann, S. FMRI correlates of autobiographical memory: Comparing silent retrieval with narrated retrieval. Neuropsychologia 196, 108842 (2024).
pubmed: 38428520
doi: 10.1016/j.neuropsychologia.2024.108842
Charpentier, C. J. et al. How representative are neuroimaging samples? Large-scale evidence for trait anxiety differences between fMRI and behaviour-only research participants. Soc. Cogn. Affect. Neurosci. 16, 1057–1070 (2021).
pubmed: 33950220
pmcid: 8483285
doi: 10.1093/scan/nsab057
Dubois, J. & Adolphs, R. Building a science of individual differences from fMRI. Trends Cogn. Sci. 20, 425–443 (2016).
pubmed: 27138646
pmcid: 4886721
doi: 10.1016/j.tics.2016.03.014
Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R. & Jacobs, G. A. Manual for the State-Trait Anxiety Inventory (Consulting Psychologists Press, 1983).
De Brigard, F., Rodriguez, D. C. & Montañés, P. Exploring the experience of episodic past, future, and counterfactual thinking in younger and older adults: A study of a Colombian sample. Conscious. Cogn. Int. J. 51, 258–267 (2017).
doi: 10.1016/j.concog.2017.04.007
Esteban, O. et al. fMRIPrep: A robust preprocessing pipeline for functional MRI. Nat. Methods 16, 111–116 (2019).
pubmed: 30532080
doi: 10.1038/s41592-018-0235-4
Tustison, N. J. et al. N4ITK: Improved N3 bias correction. IEEE Trans. Med. Imaging 29, 1310–1320 (2010).
pubmed: 20378467
pmcid: 3071855
doi: 10.1109/TMI.2010.2046908
Avants, B. B., Epstein, C. L., Grossman, M. & Gee, J. C. Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain. Med. Image Anal. 12, 26–41 (2008).
pubmed: 17659998
doi: 10.1016/j.media.2007.06.004
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 20, 45–57 (2001).
pubmed: 11293691
doi: 10.1109/42.906424
Reuter, M., Rosas, H. D. & Fischl, B. Highly accurate inverse consistent registration: A robust approach. NeuroImage 53, 1181–1196 (2010).
pubmed: 20637289
doi: 10.1016/j.neuroimage.2010.07.020
Evans, A. C., Janke, A. L., Collins, D. L. & Baillet, S. Brain templates and atlases. NeuroImage 62, 911–922 (2012).
pubmed: 22248580
doi: 10.1016/j.neuroimage.2012.01.024
Jenkinson, M., Bannister, P., Brady, M. & Smith, S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage 17, 825–841 (2002).
pubmed: 12377157
doi: 10.1006/nimg.2002.1132
Cox, R. W. & Hyde, J. S. Software tools for analysis and visualization of fMRI data. NMR Biomed. 10, 171–178 (1997).
pubmed: 9430344
doi: 10.1002/(SICI)1099-1492(199706/08)10:4/5<171::AID-NBM453>3.0.CO;2-L
Jenkinson, M. & Smith, S. A global optimisation method for robust affine registration of brain images. Med. Image Anal. 5, 143–156 (2001).
pubmed: 11516708
doi: 10.1016/S1361-8415(01)00036-6
Greve, D. N. & Fischl, B. Accurate and robust brain image alignment using boundary-based registration. NeuroImage 48, 63–72 (2009).
pubmed: 19573611
doi: 10.1016/j.neuroimage.2009.06.060
Power, J. D. et al. Methods to detect, characterize, and remove motion artifact in resting state fMRI. NeuroImage 84, 320–341 (2014).
pubmed: 23994314
doi: 10.1016/j.neuroimage.2013.08.048
Satterthwaite, T. D. et al. An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. NeuroImage 64, 240–256 (2013).
pubmed: 22926292
doi: 10.1016/j.neuroimage.2012.08.052
Lanczos, C. A precision approximation of the gamma function. J. Soc. Ind. Appl. Math. Ser. B Numer. Anal. 1, 86–96 (1964).
Woolrich, M. W., Ripley, B. D., Brady, M. & Smith, S. M. Temporal autocorrelation in univariate linear modeling of FMRI data. NeuroImage 14, 1370–1386 (2001).
pubmed: 11707093
doi: 10.1006/nimg.2001.0931
Rolls, E. T., Huang, C.-C., Lin, C.-P., Feng, J. & Joliot, M. Automated anatomical labelling atlas 3. NeuroImage 206, 116189 (2020).
pubmed: 31521825
doi: 10.1016/j.neuroimage.2019.116189
Mumford, J. A., Turner, B. O., Ashby, F. G. & Poldrack, R. A. Deconvolving BOLD activation in event-related designs for multivoxel pattern classification analyses. NeuroImage 59, 2636–2643 (2012).
pubmed: 21924359
doi: 10.1016/j.neuroimage.2011.08.076
Bai, B., Kantor, P. & Shokoufandeh, A. Effectiveness of the finite impulse response model in content-based fMRI image retrieval. In Medical Image Computing and Computer-Assisted Intervention—MICCAI 2007 (eds. Ayache, N., Ourselin, S. & Maeder, A.). 742–750 https://doi.org/10.1007/978-3-540-75759-7_90 (Springer, 2007).
Goutte, C., Nielsen, F. A. & Hansen, K. H. Modeling the hemodynamic response in fMRI using smooth FIR filters. IEEE Trans. Med. Imaging 19, 1188–1201 (2000).
pubmed: 11212367
doi: 10.1109/42.897811
Daselaar, S. M. et al. The spatiotemporal dynamics of autobiographical memory: Neural correlates of recall, emotional intensity, and reliving. Cereb. Cortex 18, 217–229 (2008).
pubmed: 17548799
doi: 10.1093/cercor/bhm048
Hall, S. A., Brodar, K. E., LaBar, K. S., Berntsen, D. & Rubin, D. C. Neural responses to emotional involuntary memories in posttraumatic stress disorder: Differences in timing and activity. NeuroImage Clin. 19, 793–804 (2018).
pubmed: 30013923
pmcid: 6024199
doi: 10.1016/j.nicl.2018.05.009
Chen, W., Hribar, P. & Melessa, S. Incorrect inferences when using residuals as dependent variables. J. Acc. Res. 56, 751–796 (2018).
doi: 10.1111/1475-679X.12195
Chen, W., Hribar, P. & Melessa, S. J. On the use of residuals as dependent variables. J. Financ. Rep. 7, 69–83 (2022).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Methodol. 57, 289–300 (1995).
doi: 10.1111/j.2517-6161.1995.tb02031.x
Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means (2020).