Memory leaks: information shared across memory systems. Issue 7 (July 2022)

• Record Type: Journal Article
• Authors: Robertson, Edwin M.
• Is Part Of: Trends in cognitive sciences. Volume 26:Issue 7(2022)
• Page Start: 544
• Page End: 554
• Publication Date: 2022-07
• Subjects: declarative learning -- memory consolidation -- offline processing -- procedural learning -- sequence learning; Cognitive science -- Periodicals; Cognitive neuroscience -- Periodicals; 153.05
• DOI: 10.1016/j.tics.2022.03.010
• Languages: English
• ISSNs: 1364-6613

Abstract

Abstract : The brain is highly segregated. Multiple mechanisms ensure that different types of memories are processed independently. Nonetheless, information leaks out across these memory systems. Only recently has the diversity of these leaks been revealed. Different memory types (skills vs. facts) can interact in simple ways, either allowing or preventing their further processing, or in more complex ways, allowing the sharing of abstract information between memories. Leaks occur from memories dependent upon hippocampal circuits, which have properties critical for leaks and activity patterns related to memory interactions. This hippocampal contribution is likely achieved in concert with cortical areas. Leaks between memories enable the application of knowledge in novel situations, explain learning dynamics, and solve important problems inherent to memory formation. Highlights: Memories leak out from otherwise segregated systems and affect the processing of different types of memory (skills vs. facts). A leak can disrupt the processing of another different type of memory and so modify the fate of the memory in a binary way (impaired vs. retained). Leaks can also be more sophisticated, with complex abstract information being shared between different types of memory, which enables generalization. Converging evidence implicates hippocampal circuits in playing a critical role in memory leaks and these may drive, and be driven, by cortical circuits. Leaks may explain learning dynamics, enable the flexible application of knowledge across different situations (generalization), and solve important memory problems (computational plus energetic).