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Cross-subject decoding of internal mental states using predictive time-series modeling

AI Summary
  • Demonstrates feasibility of cross-subject decoding of internal mental states using predictive time-series modelling of neural signals.
  • Predictive time-series models capture temporal dynamics and improve generalisability across participants compared with static approaches.
  • Method offers interpretable markers for monitoring cognition and potential applications in clinical diagnosis and brain-computer interfaces.
Summarise with AI (MRCPsych/FRANZCP)

Sci Bull (Beijing). 2026 May 28:S2095-9273(26)00588-8. doi: 10.1016/j.scib.2026.05.060. Online ahead of print.

NO ABSTRACT

PMID:42285800 | DOI:10.1016/j.scib.2026.05.060

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