Papers › Memory Encoding Model

Memory Encoding Model

2 Aug 2023arXiv:2308.01175archive 2025-07-28

Huzheng Yang, James Gee, Jianbo Shi

We explore a new class of brain encoding model by adding memory-related information as input. Memory is an essential brain mechanism that works alongside visual stimuli. During a vision-memory cognitive task, we found the non-visual brain is largely predictable using previously seen images. Our Memory Encoding Model (Mem) won the Algonauts 2023 visual brain competition even without model ensemble (single model score 66.8, ensemble score 70.8). Our ensemble model without memory input (61.4) can also stand a 3rd place. Furthermore, we observe periodic delayed brain response correlated to 6th-7th prior image, and hippocampus also showed correlated activity timed with this periodicity. We conjuncture that the periodic replay could be related to memory mechanism to enhance the working memory.

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my_create_unique_logdir_name huzeyann/MemoryEncodingModel/mem/cluster_utils.py official repository ran fingerprinted licence not identified · pointer only · d06fd7af129e7fbc · report
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my_nfs_cluster_job huzeyann/MemoryEncodingModel/mem/cluster_utils.py official repository unverified licence not identified · pointer only · 1341518e9ccaa51d · report

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