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Updated: Feb 21, 2026

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Decoding Natural Behavior from Neuroethological Embedding
Published on: October 3, 2025
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Decoding the neural dynamics of everyday prospective remembering: a hidden Markov model approach
Stefano Vicentin1, Davide Buzzi Reschini2, Paola Santacesaria3
1Department of General Psychology, University of Padua, Padua, Italy.
Frontiers in Human Neuroscience
|February 20, 2026
Summary
This study reveals how the brain
Area of Science:
- Cognitive Neuroscience
- Neuroimaging
Background:
- Prospective memory (PM) is crucial for daily life, involving delayed intentions.
- Traditional PM research often overlooked sustained neural activity supporting intention maintenance.
Purpose of the Study:
- To investigate the neural dynamics of intention maintenance during naturalistic prospective memory tasks.
- To explore the roles of the dorsal attention network (DAN) and default mode network (DMN) in PM.
Main Methods:
- High-density EEG and individual MRI were used during a naturalistic PM paradigm.
- Hidden Markov Modeling (HMM) analyzed source-level brain activity, identifying distinct brain states.
Main Results:
- Six brain states were identified; State 3 (DAN-involved) dominated time-based PM.
- State 6 (DMN-involved) was linked to intention retrieval.
- Activity in these states correlated with PM accuracy.
Conclusions:
- DAN and DMN exhibit complementary roles in prospective remembering (monitoring vs. retrieval).
- Combining HMM with naturalistic paradigms provides novel insights into real-world intention maintenance.
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