Identifying the leak between memory systems
Abstract
Information leaks out between memories. Highly complex information can be transferred between memory systems. The abstract serial structure of a word-list can be transferred to, and so enhance the formation of a motor skill memory. Equally, sharing a common abstract structure can protect memories from disruption, and more broadly creates a network linking the fate of different types of memory together. From these studies comes a new perspective of memory leaks as a training signal operating between memory systems. We seek to identify the training signal leaking out of a memory system. The functional state of the motor system will be measured during word-list learning. Any change in its functional state, which occurs exclusively when the word-list shares a common property with an earlier motor task (serial structure), and is related (correlated) with word-list learning will indicate that information is leaking out from the motor system to guide word-list learning (another memory type). Establishing that a memory leak between memory systems operates, as a training signal will provide fundamental insights. It will demonstrate a novel mechanism for how knowledge learnt in one situation can be applied flexibly to a novel situation (generalization). It explains the dynamics of human learning – an initial fast performance change due to the training signal directly driving activity changes, while, slow performance changes ensue due to the signal driving network strength changes that take time to develop (fast-slow learning). It also provides a solution to the energetic and computational challenges of memory formation (ill-posed problem).Tapping into an identified teaching signal may enhance brain-machine interfaces. It provides exactly what this technology requires- a physiologically relevant signal constructed to drive plastic change, and support adaptive behaviour. This could improve injury rehabilitation, and the control of devices in environments as wide ranging as the battlefield and Space.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2023
- Source ID
- FA86552117057
Entities
People
- Edwin M Robertson
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Glasgow