Schedule of Events | Search Abstracts | Symposia | Invited Symposia | Poster Sessions | Data Blitz Sessions

Poster B145

Cortical Hubs of Highly Superior Autobiographical Memory

Poster Session B - Sunday, April 14, 2024, 8:00 – 10:00 am EDT, Sheraton Hall ABC

William Orwig1,2 (williamorwig@g.harvard.edu), Ibai Diez2, Elisenda Bueichekú2, Tiziana Pedale3,4, Fabrizio Parente3, Patrizia Campolongo4, Daniel Schacter1, Jorge Sepulcre2, Valerio Santangelo3,5; 1Harvard University, 2Massachusetts General Hospital & Harvard Medical School, 3Fondazione Santa Lucia, 4Sapienza University of Rome, 5University of Perugia

Highly Superior Autobiographical Memory (HSAM) is a rare form of enhanced memory in which individuals demonstrate an extraordinary capacity to remember details of their personal lives with high levels of accuracy and vividness. Neuroimaging studies have identified brain activation in cortical midline regions -specifically, key nodes within the default network- associated with remembering events from one’s past. Extending this research on the neural underpinnings of autobiographical memory, the present study utilizes graph theory analyses to compare functional brain connectivity in a cohort of HSAM (n=12) and healthy controls (n=29). We perform seed-based analysis based on resting-state fMRI data to assess how specific cortical regions within the autobiographical memory network are differentially connected in HSAM individuals. Additionally, we apply a whole-brain connectivity analysis to identify differences in brain hub-network topology associated with enhanced autobiographical memory. Results show converging patterns of increased connectivity involving cortical midline areas in HSAM. Whole-brain analysis also reveals enhanced connectivity across prefrontal and posterior cingulate cortices in HSAM individuals. Together, these results extend prior research, identifying essential cortical hubs within the default network associated with enhanced autobiographical memory.

Topic Area: LONG-TERM MEMORY: Episodic

 

CNS Account Login

CNS2024-Logo_FNL-02

April 13–16  |  2024