Abstract
For people with post-traumatic stress disorder (PTSD), recall of traumatic memories often displays as intrusions that differ profoundly from processing of ‘regular’ negative memories. These mnemonic features fueled theories speculating a unique cognitive state linked with traumatic memories. Yet, to date, little empirical evidence supports this view. Here we examined neural activity of patients with PTSD who were listening to narratives depicting their own memories. An intersubject representational similarity analysis of cross-subject semantic content and neural patterns revealed a differentiation in hippocampal representation by narrative type: semantically similar, sad autobiographical memories elicited similar neural representations across participants. By contrast, within the same individuals, semantically similar trauma memories were not represented similarly. Furthermore, we were able to decode memory type from hippocampal multivoxel patterns. Finally, individual symptom severity modulated semantic representation of the traumatic narratives in the posterior cingulate cortex. Taken together, these findings suggest that traumatic memories are an alternative cognitive entity that deviates from memory per se.
Similar content being viewed by others
Data availability
Data supporting the findings of this present study are deposited at https://osf.io/dc7jb. The Harvard–Oxford atlas is available at https://neurovault.org/collections/262. The Willard atlas is available at https://pyhrf.github.io/manual/parcellation_mask.html. The set of analyses described in the present study was not preregistered.
Code availability
The scripts used for data analysis are available at https://osf.io/dc7jb. The fMRI preprocessing was done in fMRIPrep and analyses were conducted primarily in MATLAB R2018b, R2020a and R2021a (MathWorks).
References
Weathers, F. W. et al. The Clinician-Administered PTSD Scale for DSM-5 (CAPS-5): development and initial psychometric evaluation in military veterans. Psychol. Assess. 30, 383–395 (2018).
Stevens, J. S. et al. Disrupted amygdala-prefrontal functional connectivity in civilian women with posttraumatic stress disorder. J. Psychiatr. Res 47, 1469–1478 (2013).
Davachi, L. Item, context and relational episodic encoding in humans. Curr. Opin. Neurobiol. 16, 693–700 (2006).
Ranganath, C. Binding items and contexts: the cognitive neuroscience of episodic memory. Curr. Dir. Psychol. Sci. 19, 131–137 (2010).
Ekstrom, A. D. & Ranganath, C. Space, time, and episodic memory: the hippocampus is all over the cognitive map. Hippocampus 28, 680–687 (2018).
Milivojevic, B., Varadinov, M., Grabovetsky, A. V., Collin, S. H. P. & Doeller, C. F. Coding of event nodes and narrative context in the hippocampus. J. Neurosci. 36, 12412–12424 (2016).
Cohn-Sheehy, B. I. et al. The hippocampus constructs narrative memories across distant events. Curr. Biol. 31, 4935–4945.e7 (2021).
Squire, L. R. & Wixted, J. T. The cognitive neuroscience of human memory since H.M. Annu. Rev. Neurosci. 34, 259–288 (2011).
Moscovitch, M., Cabeza, R., Winocur, G. & Nadel, L. Episodic memory and beyond: the hippocampus and neocortex in transformation. Annu Rev. Psychol. 67, 105–134 (2016).
Scoville, W. B. & Milner, B. Loss of recent memory after bilateral hippocampal lesions. J. Neurol. Neurosurg. Psychiatry 20, 11–21 (1957).
Karl, A. et al. A meta-analysis of structural brain abnormalities in PTSD. Neurosci. Biobehav. Rev. 30, 1004–1031 (2006).
Jin, C. et al. Abnormalities in whole-brain functional connectivity observed in treatment-naive post-traumatic stress disorder patients following an earthquake. Psychol. Med. 44, 1927–1936 (2014).
Miller, D. R. et al. Default mode network subsystems are differentially disrupted in posttraumatic stress disorder. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 2, 363–371 (2017).
Elzinga, B. M. & Bremner, J. D. Are the neural substrates of memory the final common pathway in posttraumatic stress disorder (PTSD)? J. Affect. Disord. 70, 1–17 (2002).
Brewin, C. R., Gregory, J. D., Lipton, M. & Burgess, N. Intrusive images in psychological disorders: characteristics, neural mechanisms, and treatment implications. Psychol. Rev. 117, 210–232 (2010).
Joshi, S. A., Duval, E. R., Kubat, B. & Liberzon, I. A review of hippocampal activation in post-traumatic stress disorder. Psychophysiology 57, e13357 (2020).
Cahill, L., Babinsky, R., Markowitsch, H. J. & McGaugh, J. L. The amygdala and emotional memory. Nature 377, 295–296 (1995).
Liberzon, I. & Sripada, C. S. The functional neuroanatomy of PTSD: a critical review. Prog. Brain Res. 167, 151–169 (2007).
Rauch, S. L. et al. Exaggerated amygdala response to masked facial stimuli in posttraumatic stress disorder: a functional MRI study. Biol. Psychiatry 47, 769–776 (2000).
Rauch, S. L. et al. A symptom provocation study of posttraumatic stress disorder using positron emission tomography and script-driven imagery. Arch. Gen. Psychiatry 53, 380–387 (1996).
Shin, L. M. et al. Regional cerebral blood flow in the amygdala and medial prefrontal cortex during traumatic imagery in male and female vietnam veterans with PTSD. Arch. Gen. Psychiatry 61, 168–176 (2004).
Etkin, A. & Wager, T. D. Functional neuroimaging of anxiety: a meta-analysis of emotional processing in PTSD, social anxiety disorder, and specific phobia. Am. J. Psychiatry 164, 1476–1488 (2007).
Kensinger, E. A. & Corkin, S. Two routes to emotional memory: distinct neural processes for valence and arousal. Proc. Natl Acad. Sci. USA 101, 3310–3315 (2004).
Phelps, E. A. Human emotion and memory: interactions of the amygdala and hippocampal complex. Curr. Opin. Neurobiol. 14, 198–202 (2004).
Fanselow, M. S. & LeDoux, J. E. Why we think plasticity underlying Pavlovian fear conditioning occurs in the basolateral amygdala. Neuron 23, 229–232 (1999).
Blair, H. T. & Fanselow, M. S. in Space, Time and Memory in the Hippocampal Formation (eds Derdikman, D. & Knierim, J. J.) 465–496 (Springer Vienna, 2014).
Davis, P. & Reijmers, L. G. The dynamic nature of fear engrams in the basolateral amygdala. Brain Res. Bull. 141, 44–49 (2018).
Brewin, C. R. Re-experiencing traumatic events in PTSD: new avenues in research on intrusive memories and flashbacks. Eur. J. Psychotraumatol. 6, 27180 (2015).
Rahman, N. & Brown, A. D. Mental time travel in post-traumatic stress disorder: current gaps and future directions. Front. Psychol. 12, 624707 (2021).
Rubin, D. C., Boals, A. & Berntsen, D. Memory in posttraumatic stress disorder: properties of voluntary and involuntary, traumatic and nontraumatic autobiographical memories in people with and without posttraumatic stress disorder symptoms. J. Exp. Psychol. Gen. 137, 591–614 (2008).
Brewin, C. R. Coherence, disorganization, and fragmentation in traumatic memory reconsidered: a response to Rubin et al. (2016). J. Abnorm. Psychol. 125, 1011–1017 (2016).
Foa, E. B., Molnar, C. & Cashman, L. Change in rape narratives during exposure therapy for posttraumatic stress disorder. J. Trauma Stress 8, 675–690 (1995).
Yeshurun, Y., Nguyen, M. & Hasson, U. The default mode network: where the idiosyncratic self meets the shared social world. Nat. Rev. Neurosci. 22, 181–192 (2021).
Andrews-Hanna, J. R., Saxe, R. & Yarkoni, T. Contributions of episodic retrieval and mentalizing to autobiographical thought: evidence from functional neuroimaging, resting-state connectivity, and fMRI meta-analyses. NeuroImage 91, 324–335 (2014).
Golland, Y. et al. Extrinsic and intrinsic systems in the posterior cortex of the human brain revealed during natural sensory stimulation. Cereb. Cortex 17, 766–777 (2007).
Simony, E. et al. Dynamic reconfiguration of the default mode network during narrative comprehension. Nat. Commun. 7, 12141 (2016).
Sambuco, N., Bradley, M. M. & Lang, P. J. Narrative imagery: emotional modulation in the default mode network. Neuropsychologia 164, 108087 (2022).
Akiki, T. J., Averill, C. L. & Abdallah, C. G. A network-based neurobiological model of PTSD: evidence from structural and functional neuroimaging studies. Curr. Psychiatry Rep. https://doi.org/10.1007/s11920-017-0840-4 (2017).
Koch, S. B. J. et al. Aberrant resting-state brain activity in posttraumatic stress disorder: a meta-analysis and systematic review. Depress. Anxiety 33, 592–605 (2016).
Boccia, M. et al. Different neural modifications underpin PTSD after different traumatic events: an fMRI meta-analytic study. Brain Imaging Behav. 10, 226–237 (2016).
Kozlowski, A. C., Taddy, M. & Evans, J. A. The geometry of culture: analyzing the meanings of class through word embeddings. Am. Sociol. Rev. 84, 905–949 (2019).
Van Uden, C. E. et al. Modeling semantic encoding in a common neural representational space. Front. Neurosci. 12, 437 (2018).
Zhang, Y., Han, K., Worth, R. & Liu, Z. Connecting concepts in the brain by mapping cortical representations of semantic relations. Nat. Commun. 11, 1877 (2020).
Solomon, E. A., Lega, B. C., Sperling, M. R. & Kahana, M. J. Hippocampal theta codes for distances in semantic and temporal spaces. Proc. Natl Acad. Sci. USA 116, 24343–24352 (2019).
Mikolov, T., Chen, K., Corrado, G. & Dean, J. Efficient estimation of word representations in vector space. Preprint at https://arxiv.org/abs/1301.3781 (2013).
Mantel, N. The detection of disease clustering and a generalized regression approach. Cancer Res. 27, 209–220 (1967).
Nummenmaa, L. et al. Emotional speech synchronizes brains across listeners and engages large-scale dynamic brain networks. NeuroImage 102, 498–509 (2014).
Strange, B. A., Witter, M. P., Lein, E. S. & Moser, E. I. Functional organization of the hippocampal longitudinal axis. Nat. Rev. Neurosci. 15, 655–669 (2014).
Poppenk, J., Evensmoen, H. R., Moscovitch, M. & Nadel, L. Long-axis specialization of the human hippocampus. Trends Cogn. Sci. 17, 230–240 (2013).
Abdallah, C. G. et al. Anterior hippocampal dysconnectivity in posttraumatic stress disorder: a dimensional and multimodal approach. Transl. Psychiatry 7, e1045–e1047 (2017).
Malivoire, B. L., Girard, T. A., Patel, R. & Monson, C. M. Functional connectivity of hippocampal subregions in PTSD: relations with symptoms. BMC Psychiatry 18, 129 (2018).
Satpute, A. B., Mumford, J. A., Naliboff, B. D. & Poldrack, R. A. Human anterior and posterior hippocampus respond distinctly to state and trait anxiety. Emotion 12, 58–68 (2012).
Lanius, R. A. et al. The nature of traumatic memories: a 4-T fMRI functional connectivity analysis. Am. J. Psychiatry 161, 36–44 (2004).
Raichle, M. E. The brain’s default mode network. Annu. Rev. Neurosci. 38, 433–447 (2015).
Viganò, S. & Piazza, M. Distance and direction codes underlie navigation of a novel semantic space in the human brain. J. Neurosci. 40, 2727–2736 (2020).
Morton, N. W., Zippi, E. L., Noh, S. M. & Preston, A. R. Semantic knowledge of famous people and places is represented in hippocampus and distinct cortical networks. J. Neurosci. 41, 2762–2779 (2021).
Brunec, I. K., Robin, J., Olsen, R. K., Moscovitch, M. & Barense, M. D. Integration and differentiation of hippocampal memory traces. Neurosci. Biobehav. Rev. 118, 196–208 (2020).
Huth, A. G., De Heer, W. A., Griffiths, T. L., Theunissen, F. E. & Gallant, J. L. Natural speech reveals the semantic maps that tile human cerebral cortex. Nature 532, 453–458 (2016).
Patterson, K., Nestor, P. J. & Rogers, T. T. Where do you know what you know? The representation of semantic knowledge in the human brain. Nat. Rev. Neurosci. 8, 976–987 (2007).
Kim, B., Andrews-Hanna, J. R., Han, J., Lee, E. & Woo, C.-W. When self comes to a wandering mind: brain representations and dynamics of self-generated concepts in spontaneous thought. Sci. Adv. 8, eabn8616 (2022).
Anderson, M. C. et al. Neural systems underlying the suppression of unwanted memories. Science 303, 232–235 (2004).
Anderson, M. C. & Levy, B. J. Suppressing unwanted memories. Curr. Dir. Psychol. Sci. 18, 189–194 (2009).
Bedard-Gilligan, M., Zoellner, L. A. & Feeny, N. C. Is trauma memory special? Trauma narrative fragmentation in ptsd: effects of treatment and response. Clin. Psychol. Sci. 5, 212–225 (2018).
Duek, O. et al. Long term structural and functional neural changes following a single infusion of ketamine in PTSD. Neuropsychopharmacology https://doi.org/10.1038/s41386-023-01606-3 (2023).
First, M. B. & Gibbon, M. in Comprehensive Handbook of Psychological Assessment, Vol. 2: Personality Assessment (eds Hilsenroth, M. J. & Segal, D. L.) 134–143 (Wiley, 2004).
Lang, P. J., Levin, D. N., Miller, G. A. & Kozak, M. J. Fear behavior, fear imagery, and the psychophysiology of emotion: the problem of affective response integration. J. Abnorm. Psychol. 92, 276–306 (1983).
Pitman, R. K., Orr, S. P., Forgue, D. F., de Jong, J. B. & Claiborn, J. M. Psychophysiologic assessment of posttraumatic stress disorder imagery in Vietnam combat veterans. Arch. Gen. Psychiatry 44, 970–975 (1987).
Orr, S. P., Metzger, L. J. & Pitman, R. K. Psychophysiology of post-traumatic stress disorder. Psychiatr. Clin. North Am. 25, 271–293 (2002).
Brunet, A. et al. Trauma reactivation plus propranolol is associated with durably low physiological responding during subsequent script-driven traumatic imagery. Can. J. Psychiatry 59, 228–232 (2014).
Hoge, E. A. et al. Effect of acute posttrauma propranolol on PTSD outcome and physiological responses during script-driven imagery. CNS Neurosci. Ther. 18, 21–27 (2012).
Sinha, R. et al. Enhanced negative emotion and alcohol craving, and altered physiological responses following stress and cue exposure in alcohol dependent individuals. Neuropsychopharmacology 34, 1198–1208 (2009).
Vodrahalli, K. et al. Mapping between fMRI responses to movies and their natural language annotations. NeuroImage 180, 223–231 (2018).
Nguyen, M., Vanderwal, T. & Hasson, U. Shared understanding of narratives is correlated with shared neural responses. NeuroImage 184, 161–170 (2019).
Dimsdale-Zucker, H. R. & Ranganath, C. Representational similarity analyses: a practical guide for functional MRI applications. Handb. Behav. Neurosci. 28, 509–525 (2018).
Brysbaert, M., Warriner, A. B. & Kuperman, V. Concreteness ratings for 40 thousand generally known English word lemmas. Behav. Res Methods 46, 904–911 (2014).
Scott, G. G., Keitel, A., Becirspahic, M., Yao, B. & Sereno, S. C. Glasgow norms: ratings of 5,500 words on nine scales. Behav. Res. Methods 51, 1258–1270 (2019).
Mohammad, S. M. Obtaining reliable human ratings of valence, arousal, and dominance for 20,000 English words. In Proc. 56th Annual Meeting of the Association of Computational Linguistics (Vol. 1, Long Papers) 1, 174–184 (2018).
Van der Maaten, L. & Hinton, G. Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 2579–2605 (2008).
Esteban, O. et al. poldracklab/fmriprep: 1.0.0-rc5. Zenodo https://doi.org/10.5281/zenodo.996169 (2017).
Desikan, R. S. et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage 31, 968–980 (2006).
Deuker, L., Bellmund, J. L., Navarro Schröder, T. & Doeller, C. F. An event map of memory space in the hippocampus. eLife 5, e16534 (2016).
Op de Beeck, H. P. Against hyperacuity in brain reading: spatial smoothing does not hurt multivariate fMRI analyses? NeuroImage 49, 1943–1948 (2010).
Ben-Yakov, A. & Henson, R. N. The hippocampal film editor: sensitivity and specificity to event boundaries in continuous experience. J. Neurosci. 38, 10057–10068 (2018).
Chen, J. et al. Accessing real-life episodic information from minutes versus hours earlier modulates hippocampal and high-order cortical dynamics. Cereb. Cortex 26, 3428–3441 (2016).
Yeshurun, Y. et al. Same story, different story: the neural representation of interpretive frameworks. Psychol. Sci. 28, 307–319 (2017).
Finn, E. S. et al. Idiosynchrony: from shared responses to individual differences during naturalistic neuroimaging. NeuroImage 215, 116828 (2020).
Rhoads, S. A. et al. Mapping neural activity patterns to contextualized fearful facial expressions onto callous-unemotional (CU) traits: intersubject representational similarity analysis reveals less variation among high-CU adolescents. Personal. Neurosci. 3, e12 (2020).
Chen, P. H. A., Jolly, E., Cheong, J. H. & Chang, L. J. Intersubject representational similarity analysis reveals individual variations in affective experience when watching erotic movies. NeuroImage 216, 116851 (2020).
Steiger, J. H. Tests for comparing elements of a correlation matrix. Psychol. Bull. 87, 245–251 (1980).
Gliner, J. A., Leech, N. L. & Morgan, G. A. Problems with null hypothesis significance testing (NHST): what do the textbooks say? J. Exp. Educ. 71, 83–92 (2002).
Jeffreys, H. The Theory of Probability (Oxford Univ. Press, 1998).
Oganian, Y. & Chang, E. F. A speech envelope landmark for syllable encoding in human superior temporal gyrus. Sci. Adv. 5, eaay6279 (2019).
Shirer, W. R., Ryali, S., Rykhlevskaia, E., Menon, V. & Greicius, M. D. Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cereb. Cortex 22, 158–165 (2012).
Chen, J. et al. Shared memories reveal shared structure in neural activity across individuals. Nat. Neurosci. 20, 115–125 (2017).
Esteban, O. et al. fMRIPrep: a robust preprocessing pipeline for functional MRI. Nat. Methods 16, 111–116 (2019).
Gorgolewski, K. et al. Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. Front. Neuroinform. 5, 13 (2011).
Tustison, N. J. et al. N4ITK: improved N3 bias correction. IEEE Trans. Med. Imaging 29, 1310–1320 (2010).
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).
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).
Fonov, V. et al. Unbiased average age-appropriate atlases for pediatric studies. NeuroImage 54, 313–327 (2011).
Jenkinson, M. & Smith, S. A global optimisation method for robust affine registration of brain images. Med. Image Anal. 5, 143–156 (2001).
Greve, D. N. & Fischl, B. Accurate and robust brain image alignment using boundary-based registration. NeuroImage 48, 63–72 (2009).
Cox, R. W. & Hyde, J. S. Software tools for analysis and visualization of fMRI data. NMR Biomed. 10, 171–178 (1997).
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).
Power, J. D. et al. Methods to detect, characterize, and remove motion artifact in resting state fMRI. NeuroImage 84, 320–341 (2014).
Behzadi, Y., Restom, K., Liau, J. & Liu, T. T. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. NeuroImage 37, 90–101 (2007).
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).
Acknowledgements
We thank T. Orederu and Y. Yeshurun for helpful discussions. We also thank A. Ben Yakov and A. Ravia for their advice on analysis and preprocessing. The main source of funding for the present study was provided by: Independent Investigator Grant (no. 23260) from the Brain and Behavior Research Foundation (Institute of Human Relations (IHR)), Clinical Neurosciences Division of the National Center for PTSD (IHR), a private donation from the American Brain Society (IHR) and the Yale Center for Clinical Investigation, supported by a CTSA grant from the National Center for Advancing Translational Science, a component of the National Institutes of Health (NIH). Funding was also provided by the NIH (grant nos. R01MH122611 and R01MH123069) and The Ream Foundation to D.S. The contents of the manuscript are solely the responsibility of the authors and do not necessarily represent the official view of the NIH.
Author information
Authors and Affiliations
Contributions
O.P. conceptualized analyses, conducted and interpreted analyses and visualization, wrote the original draft and edited the paper. O.D. collected data, interpreted data analyses and edited the final paper. K.R.K. analyzed the data. C.G. collected data. J.H.K. obtained funding and edited the final paper. I.L. designed the study, interpreted data analyses and cowrote the paper. I.H.R. designed the study, obtained funding, collected data, interpreted the data analyses and cowrote the paper. D.S. conceptualized analyses, interpreted analyses, obtained funding, wrote the original draft and edited the paper.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Neuroscience thanks Choong-Wan Woo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Information
Supplementary Figs. 1–14 and Tables 1–3.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Perl, O., Duek, O., Kulkarni, K.R. et al. Neural patterns differentiate traumatic from sad autobiographical memories in PTSD. Nat Neurosci 26, 2226–2236 (2023). https://doi.org/10.1038/s41593-023-01483-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41593-023-01483-5
- Springer Nature America, Inc.
This article is cited by
-
Trauma und Erinnerung – ein Beitrag zur aktuellen Debatte in Recht und Psychotherapie
Der Nervenarzt (2024)