Decoding episodic autobiographical memory in naturalistic virtual reality.

Episodic autobiographical memory (EAM) is a long-term memory system of personally experienced events with their context - what, where, when - and subjective elements, e.g., emotions, thoughts, or self-reference.

The formation of episodic autobiographical memory is predicted by mental imagery, self-reference, and anticipated details.

Introduction: Despite the ecological nature of episodic memory (EM) and the importance of consolidation in its functioning, studies tackling both subjects are still scarce. Therefore, the present study aims at establishing predictions of the future of newly encoded information in EM in an ecological paradigm.

Methods: Participants recorded two personal events per day with a SenseCam portable camera, for 10 days, and characterized the events with different subjective scales (emotional valence and intensity, self-concept and self-relevance, perspective and anticipated details at a month, mental images…).

In search of a naturalistic neuroimaging approach: Exploration of general feasibility through the case of VR-fMRI and application in the domain of episodic memory.

Virtual Reality (VR) is an increasingly widespread tool for research as it allows the creation of experiments taking place in multimodal and daily-life-like environments, while keeping a strong experimental control. Adding neuroimaging to VR leads to a better understanding of the underlying brain networks activated during a naturalistic task, whether for research purposes or rehabilitation. The present paper focuses on the specific use of concurrent VR and fMRI and its technical challenges and feasibility, with a brief examination of the general existing solutions.