Shared recollections of events linked to similar brain activity patterns

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by Ingrid Fadelli, Medical Xpress

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People who attended or experienced the same event often remember it in completely different ways. For instance, one person might remember a family dinner as warm and enjoyable, while another might recall that the same dinner was uncomfortable or emotionally demanding.

These differences in memory are known to emerge because the brain does not record memories exactly as they are but instead interprets them, forming personal representations. While numerous past studies have tried to uncover how the brain creates and stores these personal versions of events, their neural underpinnings have not yet been fully elucidated.

Researchers at the University of Toronto, McGill University and the University of California, Davis, recently tried to shed more light on the neural processes underpinning these differences in memory using a combination of imaging data and artificial intelligence (AI) models.

Their findings, published in Nature Communications Psychology, suggest that people who remember events similarly also exhibit similar brain activity patterns both when experiencing them and recalling them later.

"People can experience the same event yet form distinct memories shaped by individual interpretations," wrote June-Kyo Kim, Joshua Koh and their colleagues in their paper.

"Prior research shows that multivariate activity patterns in the default mode network (DMN) are correlated across individuals during shared experiences, suggesting a role in representing high-level event features. However, it remains unclear whether these shared neural patterns reflect similarity in subsequent memory content."

Left: Unthresholded whole-brain ROI maps of t-values showing the relationship between intersubject pattern similarity and topic similarity using the HCP-MMP1.0 atlas 27 . Right: The null distribution of the difference between the slopes from the DMN and the rest of the brain created from 10,000 random shuffles of network labels of the ROIs present alongside the real observed difference, as the red vertical line. The p-value is the proportion of random shuffles that created a difference greater than the observed difference. N = 24. Credit: Kim et al. (Communications Psychology, 2026).

Uncovering the neural roots of memory differences

To further explore why humans can remember the same event differently, the researchers analyzed brain activity recordings previously collected from 24 people who were watching the same animated videos. The recordings were collected using functional magnetic resonance imaging (fMRI), a technique that measures changes in blood flow associated with neural activity while people are completing specific tasks.

The researchers also analyzed the participants' recollections of the videos they had watched using natural language processing (NLP) models, AI systems that can process, summarize and generate text. These models allowed them to rapidly determine how similar or different people's recollections of the videos were.

The team's analyses of brain recordings specifically focused on the DMN. This is a large collection of interconnected brain regions known to become active when people are daydreaming, recalling personal memories or imagining future scenarios.

"We examined whether memory similarity correlates with intersubject spatial patterns in the DMN using a pre-existing dataset," wrote Kim, Koh and their colleagues.

"Twenty-four individuals watched and recounted two cartoon movies during fMRI scanning. Using topic modeling, we transformed verbal recall into vectors of latent topics to quantify memory similarity across participants."

Interestingly, the researchers observed that people who remembered the animated videos similarly, also exhibited similar patterns of brain activity. These similarities in brain activity were observed while they were watching the videos and while they were remembering them.

Diving into neural underpinnings of memory with AI

The team found that when people remembered a video similarly, activity in three key brain regions appeared to be most strongly alike. These regions included the posterior medial cortex, the medial prefrontal cortex and the anterior temporal cortex.

Overall, the results of this study suggest that these three brain regions play a crucial role in the personal interpretation of past events and their representation as subjective memories. Future research could try to shed more light on the three regions' unique contributions to personal memories.

"We found that greater similarity in recalled content was associated with stronger shared activation patterns at encoding and retrieval, particularly in the posterior medial, medial prefrontal and anterior temporal cortices," write the authors.

"These findings highlight the utility of natural language processing tools in linking memory representations to brain activity and underscore the DMN's role in encoding, interpreting and recalling complex event features."

Other researchers could draw inspiration from this study and also set out to investigate memory processes or other mental functions using a combination of imaging techniques and AI models. Meanwhile, the efforts by Kim, Koh and their colleagues could help improve existing psychological and neuroscientific models of episodic memory.

Written for you by our author Ingrid Fadelli, edited by Sadie Harley, and fact-checked and reviewed by Robert Egan—this article is the result of careful human work. We rely on readers like you to keep independent science journalism alive. If this reporting matters to you, please consider a donation (especially monthly). You'll get an ad-free account as a thank-you.

Publication details

June-Kyo Kim et al, Natural language processing captures memory content associated with shared neural patterns at encoding and retrieval, Communications Psychology (2026). DOI: 10.1038/s44271-026-00481-0.

Journal information: Communications Psychology

Key medical concepts

Default Mode NetworkFunctional MRIMemory, EpisodicNatural Language Processing

Clinical categories

Neurology Who's behind this story?

Ingrid Fadelli

Freelance journalist with BSc Psychology and MA International Journalism. Covers AI, robotics, neuroscience, and astrophysics since 2018. Full profile →

Sadie Harley

BSc Life Sciences & Ecology. Microbiology lab background with pharmaceutical news experience in oil, gas, and renewable industries. Full profile →

Robert Egan

Bachelor's in mathematical biology, Master's in creative writing. Well-traveled with unique perspectives on science and language. Full profile →

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