ArticlePhysical review. E2016
Memory recall and spike-frequency adaptation.
Article in Physical review. E, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Repeated applications of high potassium elicit long-term changes in a motor circuit from the crab,iScience · 2022Article
- Modeling cortical synaptic effects of anesthesia and their cholinergic reversal.PLoS computational biology · 2022Article
- Theoretical analysis of effects of transcranial magneto-acoustical stimulation on neuronal spike-frequency adaptation.BMC neuroscience · 2022Article
- Alteration of Mesopontine Cholinergic Function by the Lack of KCNQ4 Subunit.Frontiers in cellular neuroscience · 2021Article
- Acetylcholine Mediates Dynamic Switching Between Information Coding Schemes in Neuronal Networks.Frontiers in systems neuroscience · 2019Article
- Modulation of neuronal dynamic range using two different adaptation mechanisms.Neural regeneration research · 2017Article
- Density-based clustering: A 'landscape view' of multi-channel neural data for inference and dynamic complexity analysis.PloS one · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The brain can reproduce memories from partial data; this ability is critical for memory recall. The process of memory recall has been studied using autoassociative networks such as the Hopfield model. This kind of model reliably converges to stored patterns that contain the memory. However, it is unclear how the behavior is controlled by the brain so that after convergence to one configuration, it can proceed with recognition of another one. In the Hopfield model, this happens only through unrealistic changes of an effective global temperature that destabilizes all stored configurations. Here we show that spike-frequency adaptation (SFA), a common mechanism affecting neuron activation in the brain, can provide state-dependent control of pattern retrieval. We demonstrate this in a Hopfield network modified to include SFA, and also in a model network of biophysical neurons. In both cases, SFA allows for selective stabilization of attractors with different basins of attraction, and also for temporal dynamics of attractor switching that is not possible in standard autoassociative schemes. The dynamics of our models give a plausible account of different sorts of memory retrieval.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.