ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2018
A network model of behavioural performance in a rule learning task.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- Biophysical mechanisms underlying the generation and maintenance of rule-learning engram.Communications biology · 2026Article
- Three-factor learning in spiking neural networks: An overview of methods and trends from a machine learning perspective.Patterns (New York, N.Y.) · 2025Review
- Neural circuits and symbolic processing.Neurobiology of learning and memory · 2021Review
- The Unexplored Territory of Neural Models: Potential Guides for Exploring the Function of Metabotropic Neuromodulation.Neuroscience · 2021Review
- Prefrontal oscillations modulate the propagation of neuronal activity required for working memory.Neurobiology of learning and memory · 2020Article
- A neural circuit model for a contextual association task inspired by recommender systems.Hippocampus · 2020Article
- The Role of Hierarchical Dynamical Functions in Coding for Episodic Memory and Cognition.Journal of cognitive neuroscience · 2019Article
- Temporal Flexibility of Systems Consolidation and the Synaptic Occupancy/Reset Theory (SORT): Cues About the Nature of the Engram.Frontiers in synaptic neuroscience · 2019Article
- Taxonomies of psychological individual differences: biological perspectives on millennia-long challenges.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Article
- Diversity in action: exchange of perspectives and reflections on taxonomies of individual differences.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Review
- A Cellular Mechanism Underlying Enhanced Capability for Complex Olfactory Discrimination Learning.eNeuroArticle
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.
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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.