Dendritic computation - PubMed
We discuss why these dendritic properties may be essential for the computations performed by the neuron and the network and provide theoretical and experimental examples to support this view.
Illuminating dendritic function with computational models
May 11, 2020 · Computational models allow the fast, systematic, exhaustive and reversible manipulation of properties that may not be amenable to direct manipulation in living tissue, …
In the first part of this review we describe the dendritic computational toolkit, i.e., the biophysical mechanisms in dendrites, which endow them with potential computational powers. We focus on the most recent find-ings and group them according to the type of computations being carried out.
Dendritic Computing: Branching Deeper into Machine Learning
May 1, 2022 · We review studies on computational implications of dendritic nonlinearities in neurons. We discuss how synaptic plasticity can interact with dendritic nonlinearities for improved learning. We link these studies to applications in machine learning and deep learning.
DenRAM: neuromorphic dendritic architecture with RRAM for …
Apr 24, 2024 · Neuroscience findings emphasize the role of dendritic branching in neocortical pyramidal neurons for non-linear computations and signal processing. Dendritic branches facilitate temporal feature...
Dendritic action potentials and computation in human layer 2/ ... - Science
Jan 3, 2020 · In this work, we investigated the dendrites of layer 2 and 3 (L2/3) pyramidal neurons of the human cerebral cortex ex vivo. In these neurons, we discovered a class of calcium-mediated dendritic action potentials (dCaAPs) whose waveform and effects on neuronal output have not been previously described.
Dendritic Computing: Branching Deeper into Machine Learning
May 1, 2022 · We review studies on computational implications of dendritic nonlinearities in neurons. We discuss how synaptic plasticity can interact with dendritic nonlinearities for improved learning. We link these studies to applications in machine learning and deep learning.
A synaptic learning rule for exploiting nonlinear dendritic computation
Oct 28, 2021 · Here, we develop a learning rule from dendritic cable theory and use it to investigate the processing capacity of a detailed pyramidal neuron model. We show that computations using spatial or temporal features of synaptic input patterns can be learned, and even synergistically combined, to solve a canonical nonlinear feature-binding problem.
Dendritic computations captured by an effective point neuron …
Jul 10, 2019 · Our model captures the somatic voltage response of a neuron with complex dendrites and is capable of performing rich dendritic computations.
DENDRITIC COMPUTATION - Annual Reviews
We discuss why these dendritic properties may be essential for the computations performed by the neuron and the network and provide theoretical and experimental examples to support this view.
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