ArticleProceedings of the National Academy of Sciences of the United States of America2019
Dendritic computations captured by an effective point neuron model.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed, 46 citations in OpenAlex.
- Frequency-dependent coupling in response to oscillatory inputs in minimal networks of electrically coupled nodes: Gap junction networks and spatially extended neurons.Biological cybernetics · 2026Article
- Homeostatic dendritic neuron based on co-integrated volatile and non-volatile memristors for neuromorphic processing.Nature communications · 2026Article
- MASCAF: A Cable Model Fitting Pipeline for Topologically Complex Surface Meshes.bioRxiv : the preprint server for biology · 2026Article
- The Neural Analysis Toolkit Unifies Semi-Analytical Techniques to Simplify, Understand, and Simulate Dendrites.Neuroinformatics · 2026Article
- Robust input disentanglement through dendritic calcium-mediated action potentials.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Artificial intelligence as a surrogate brain: bridging neural dynamical models and data.National science review · 2026Review
- Neuromorphic computing paradigms enhance robustness through spiking neural networks.Nature communications · 2025Article
- A Model-Based Approach to Neuronal Electrical Activity and Spatial Organization Through the Neuronal Actin Cytoskeleton.Methods and protocols · 2025Article
- Lateral inhibition in V1 controls neural and perceptual contrast sensitivity.Nature neuroscience · 2025Article
- A computational neural model that incorporates both intrinsic dynamics and sensory feedback in the Aplysia feeding network.Biological cybernetics · 2024Article
- Is the Papez circuit the location of the elusive episodic memory engram?IBRO neuroscience reports · 2024Article
- Network-neuron interactions underlying sensory responses of layer 5 pyramidal tract neurons in barrel cortex.PLoS computational biology · 2024Article
- Emerging memristive neurons for neuromorphic computing and sensing.Science and technology of advanced materials · 2023Review
- A multilayer-multiplexer network processing scheme based on the dendritic integration in a single neuron.AIMS neuroscience · 2022Article
- Periodicity Pitch Perception Part III: Sensibility and Pachinko Volatility.Frontiers in neuroscience · 2022Article
- Biological constraints on neural network models of cognitive function.Nature reviews. Neuroscience · 2021Review
- A computational investigation of electrotonic coupling between pyramidal cells in the cortex.Journal of computational neuroscience · 2020Article
- Illuminating dendritic function with computational models.Nature reviews. Neuroscience · 2020Review
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Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Complex dendrites in general present formidable challenges to understanding neuronal information processing. To circumvent the difficulty, a prevalent viewpoint simplifies the neuronal morphology as a point representing the soma, and the excitatory and inhibitory synaptic currents originated from the dendrites are treated as linearly summed at the soma. Despite its extensive applications, the validity of the synaptic current description remains unclear, and the existing point neuron framework fails to characterize the spatiotemporal aspects of dendritic integration supporting specific computations. Using electrophysiological experiments, realistic neuronal simulations, and theoretical analyses, we demonstrate that the traditional assumption of linear summation of synaptic currents is oversimplified and underestimates the inhibition effect. We then derive a form of synaptic integration current within the point neuron framework to capture dendritic effects. In the derived form, the interaction between each pair of synaptic inputs on the dendrites can be reliably parameterized by a single coefficient, suggesting the inherent low-dimensional structure of dendritic integration. We further generalize the form of synaptic integration current to capture the spatiotemporal interactions among multiple synaptic inputs and show that a point neuron model with the synaptic integration current incorporated possesses the computational ability of a spatial neuron with dendrites, including direction selectivity, coincidence detection, logical operation, and a bilinear dendritic integration rule discovered in experiment. Our work amends the modeling of synaptic inputs and improves the computational power of a modeling neuron within the point neuron framework.
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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.