ArticleCognitive neurodynamics2017
A decision-making model based on a spiking neural circuit and synaptic plasticity.
Article in Cognitive neurodynamics, 2017. 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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7 citing papers in PubMed.
- Primate-informed neural network for visual decision-making.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Setting a double-capacitive neuron coupled with Josephson junction and piezoelectric source.Cognitive neurodynamics · 2024Article
- Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot.Frontiers in neurorobotics · 2023Article
- A neural algorithm for Drosophila linear and nonlinear decision-making.Scientific reports · 2020Article
- Neurodynamic analysis of Merkel cell-neurite complex transduction mechanism during tactile sensing.Cognitive neurodynamics · 2019Article
- A Temporal Signal-Processing Circuit Based on Spiking Neuron and Synaptic Learning.Frontiers in computational neuroscience · 2019Article
- Suppressing bursting synchronization in a modular neuronal network with synaptic plasticity.Cognitive neurodynamics · 2018Article
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Authors and funding
3 authors.
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Abstract
To adapt to the environment and survive, most animals can control their behaviors by making decisions. The process of decision-making and responding according to cues in the environment is stable, sustainable, and learnable. Understanding how behaviors are regulated by neural circuits and the encoding and decoding mechanisms from stimuli to responses are important goals in neuroscience. From results observed in Drosophila experiments, the underlying decision-making process is discussed, and a neural circuit that implements a two-choice decision-making model is proposed to explain and reproduce the observations. Compared with previous two-choice decision making models, our model uses synaptic plasticity to explain changes in decision output given the same environment. Moreover, biological meanings of parameters of our decision-making model are discussed. In this paper, we explain at the micro-level (i.e., neurons and synapses) how observable decision-making behavior at the macro-level is acquired and achieved.
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