ArticleNature communications2020
Decoding individual identity from brain activity elicited in imagining common experiences.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Medial temporal default mode network selectively encodes autobiographical visual imagery.Science advances · 2026Article
- Neural decoding of autobiographical mental image features with a general semantic model.Nature communications · 2025Article
- A Rapid Cortical Learning Process Supporting Students' Knowledge Construction During Real Classroom Teaching.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Stimulus Selection Influences Prediction of Individual Phenotypes in Naturalistic Conditions.Human brain mapping · 2025Article
- Speaker differences in volitional voice modulation reflected in empathy and functional activation patterns.PloS one · 2025Article
- Decoding face recognition abilities in the human brain.PNAS nexus · 2024Article
- Family lexicon: Using language models to encode memories of personally familiar and famous people and places in the brain.PloS one · 2024Article
- Experientially-grounded and distributional semantic vectors uncover dissociable representations of conceptual categories.Language, cognition and neuroscience · 2024Article
- Testing cognitive theories with multivariate pattern analysis of neuroimaging data.Nature human behaviour · 2023Review
- A Multi-Dimensional Model of Fatigue in Old Age: Implications for Brain Aging.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2023Article
- Brainprints: identifying individuals from magnetoencephalograms.Communications biology · 2022Article
- Deep Artificial Neural Networks Reveal a Distributed Cortical Network Encoding Propositional Sentence-Level Meaning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
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Authors and funding
6 authors.
Funding
Abstract
Everyone experiences common events differently. This leads to personal memories that presumably provide neural signatures of individual identity when events are reimagined. We present initial evidence that these signatures can be read from brain activity. To do this, we progress beyond previous work that has deployed generic group-level computational semantic models to distinguish between neural representations of different events, but not revealed interpersonal differences in event representations. We scanned 26 participants' brain activity using functional Magnetic Resonance Imaging as they vividly imagined themselves personally experiencing 20 common scenarios (e.g., dancing, shopping, wedding). Rather than adopting a one-size-fits-all approach to generically model scenarios, we constructed personal models from participants' verbal descriptions and self-ratings of sensory/motor/cognitive/spatiotemporal and emotional characteristics of the imagined experiences. We demonstrate that participants' neural representations are better predicted by their own models than other peoples'. This showcases how neuroimaging and personalized models can quantify individual-differences in imagined experiences.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.