Neurophysiological signatures in the retrieval of individual autobiographical memories of real-life episodic events
Autobiographical memory (AM) refers to recollected events that belong to an individuals past. In a classical episodic retrieval experiment in a laboratory, the events to be remembered are words or pictures that have hardly any personal relevance. While such stimuli provide necessary experimental and controlled conditions helping to advance in the understanding of memory, they do not capture the whole complexity of real-world stimuli. Recently, the incorporation of wearable cameras has allowed us to study the cognitive and neural bases of AM retrieval without active participant involvement, and they have been demonstrated to elicit a strong sense of first-person episodic recollection enhancing ecological validity. Here, we provide a new approach to understanding the retrieval of personal events, implementing a convolution network-based algorithm for the selection of the stimuli while monitoring participants memory retrieval with scalp EEG recordings over three periods of time after encoding (1 week, 2 weeks, and 6 to 12 months). We also examined an individual with a condition termed Aphantasia that provided more insights into the sensitivity of our protocol in the investigation of individual AM using real-life sequences.