Computational Neuroscience Journal Club

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• Dr Theoklitos Amvrosiadis, Puria Radmard
• Tuesday 21 November 2023, 14:00-15:00
• CBL Seminar Room, Engineering Department, 4th floor Baker building.

If you have a question about this talk, please contact Puria Radmard.

Please join us for our fortnightly Computational Neuroscience journal club on Tuesday 21st November at 2pm UK time in the CBL seminar room, or online on zoom.

The title is ‘Systems Consolidation’, presented by Theoklitos Amvrosiadis and Puria Radmard.

Zoom information: https://eng-cam.zoom.us/j/84204498431?pwd=Um1oU284b1YxWThObGw4ZU9XZitWdz09 Meeting ID: 842 0449 8431 Passcode: 684140

Summary:

In this talk, Theo will give an in depth summary of Sun et al., 2023: “Organizing memories for generalization in complementary learning systems”, published in Nature Neuroscience, after Puria introduces some of the key concepts for a background understanding.

Abstract for Sun et al., 2023: “Memorization and generalization are complementary cognitive processes that jointly promote adaptive behavior. For example, animals should memorize safe routes to specific water sources and generalize from these memories to discover environmental features that predict new ones. These functions depend on systems consolidation mechanisms that construct neocortical memory traces from hippocampal precursors, but why systems consolidation only applies to a subset of hippocampal memories is unclear. Here we introduce a new neural network formalization of systems consolidation that reveals an overlooked tension—unregulated neocortical memory transfer can cause overfitting and harm generalization in an unpredictable world. We resolve this tension by postulating that memories only consolidate when it aids generalization. This framework accounts for partial hippocampal–cortical memory transfer and provides a normative principle for reconceptualizing numerous observations in the field. Generalization-optimized systems consolidation thus provides new insight into how adaptive behavior benefits from complementary learning systems specialized for memorization and generalization.”

This talk is part of the Computational Neuroscience series.

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