ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2017
Feedback Inhibition Shapes Emergent Computational Properties of Cortical Microcircuit Motifs.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Article
- Beyond-local neural information processing in neuronal networks.Computational and structural biotechnology journal · 2024Article
- Social state gates vision using three circuit mechanisms inbioRxiv : the preprint server for biology · 2024Article
- Local prediction-learning in high-dimensional spaces enables neural networks to plan.Nature communications · 2024Article
- Phase information is conserved in sparse, synchronous population-rate-codes via phase-to-rate recoding.Nature communications · 2023Article
- The effects of distractors on brightness perception based on a spiking network.Scientific reports · 2023Article
- Emergence of probabilistic representation in the neural network of primary visual cortex.iScience · 2022Article
- Unsupervised Learning and Clustered Connectivity Enhance Reinforcement Learning in Spiking Neural Networks.Frontiers in computational neuroscience · 2021Article
- Feedback Inhibition Shapes Emergent Computational Properties of Cortical Microcircuit Motifs.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2017Article
- Article
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Abstract
Cortical microcircuits are very complex networks, but they are composed of a relatively small number of stereotypical motifs. Hence, one strategy for throwing light on the computational function of cortical microcircuits is to analyze emergent computational properties of these stereotypical microcircuit motifs. We are addressing here the question how spike timing-dependent plasticity shapes the computational properties of one motif that has frequently been studied experimentally: interconnected populations of pyramidal cells and parvalbumin-positive inhibitory cells in layer 2/3. Experimental studies suggest that these inhibitory neurons exert some form of divisive inhibition on the pyramidal cells. We show that this data-based form of feedback inhibition, which is softer than that of winner-take-all models that are commonly considered in theoretical analyses, contributes to the emergence of an important computational function through spike timing-dependent plasticity: The capability to disentangle superimposed firing patterns in upstream networks, and to represent their information content through a sparse assembly code.
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