Context-modular memory networks support high-capacity, flexible, and robust associative memories

W.F. Podlaski, E.J. Agnes, T.P. Vogels, BioRxiv (2020).

Preprint | Published | English
Author
Podlaski, William F. ; Agnes, Everton J. ; Vogels, Tim PIST Austria
Abstract
Context, such as behavioral state, is known to modulate memory formation and retrieval, but is usually ignored in associative memory models. Here, we propose several types of contextual modulation for associative memory networks that greatly increase their performance. In these networks, context inactivates specific neurons and connections, which modulates the effective connectivity of the network. Memories are stored only by the active components, thereby reducing interference from memories acquired in other contexts. Such networks exhibit several beneficial characteristics, including enhanced memory capacity, high robustness to noise, increased robustness to memory overloading, and better memory retention during continual learning. Furthermore, memories can be biased to have different relative strengths, or even gated on or off, according to contextual cues, providing a candidate model for cognitive control of memory and efficient memory search. An external context-encoding network can dynamically switch the memory network to a desired state, which we liken to experimentally observed contextual signals in prefrontal cortex and hippocampus. Overall, our work illustrates the benefits of organizing memory around context, and provides an important link between behavioral studies of memory and mechanistic details of neural circuits.</jats:p><jats:sec><jats:title>SIGNIFICANCE</jats:title><jats:p>Memory is context dependent — both encoding and recall vary in effectiveness and speed depending on factors like location and brain state during a task. We apply this idea to a simple computational model of associative memory through contextual gating of neurons and synaptic connections. Intriguingly, this results in several advantages, including vastly enhanced memory capacity, better robustness, and flexible memory gating. Our model helps to explain (i) how gating and inhibition contribute to memory processes, (ii) how memory access dynamically changes over time, and (iii) how context representations, such as those observed in hippocampus and prefrontal cortex, may interact with and control memory processes.
Publishing Year
Date Published
2020-01-09
Journal Title
bioRxiv
Page
30
IST-REx-ID

Cite this

Podlaski WF, Agnes EJ, Vogels TP. Context-modular memory networks support high-capacity, flexible, and robust associative memories. bioRxiv. 2020.
Podlaski, W. F., Agnes, E. J., & Vogels, T. P. (2020). Context-modular memory networks support high-capacity, flexible, and robust associative memories. BioRxiv. Cold Spring Harbor Laboratory.
Podlaski, William F., Everton J. Agnes, and Tim P Vogels. “Context-Modular Memory Networks Support High-Capacity, Flexible, and Robust Associative Memories.” BioRxiv. Cold Spring Harbor Laboratory, 2020.
W. F. Podlaski, E. J. Agnes, and T. P. Vogels, “Context-modular memory networks support high-capacity, flexible, and robust associative memories,” bioRxiv. Cold Spring Harbor Laboratory, 2020.
Podlaski WF, Agnes EJ, Vogels TP. 2020. Context-modular memory networks support high-capacity, flexible, and robust associative memories. bioRxiv.
Podlaski, William F., et al. “Context-Modular Memory Networks Support High-Capacity, Flexible, and Robust Associative Memories.” BioRxiv, Cold Spring Harbor Laboratory, 2020.
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