Dendritic computation

One of the central questions in neuroscience is how particular tasks, or computations, are implemented by neural networks to generate behavior. The prevailing view has been that information processing in neural networks results primarily from the properties of synapses and the connectivity of neuron...

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Bibliographic Details
Published in:Annual review of neuroscience 2005-01, Vol.28 (1), p.503-532
Main Authors: LONDON, Michael, HÄUSSER, Michael
Format: Article
Language:English
Subjects:
Animals
Biological and medical sciences
Brain
Computer Simulation
Dendrites - physiology
Diagnostic Imaging - methods
Fundamental and applied biological sciences. Psychology
General aspects. Models. Methods
Humans
Membrane Potentials - physiology
Models, Neurological
Nerve Net - physiology
Neurology
Neurons
Neurons - cytology
Neurons - physiology
Nonlinear Dynamics
Synapses - physiology
Vertebrates: nervous system and sense organs
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Summary:One of the central questions in neuroscience is how particular tasks, or computations, are implemented by neural networks to generate behavior. The prevailing view has been that information processing in neural networks results primarily from the properties of synapses and the connectivity of neurons within the network, with the intrinsic excitability of single neurons playing a lesser role. As a consequence, the contribution of single neurons to computation in the brain has long been underestimated. Here we review recent work showing that neuronal dendrites exhibit a range of linear and nonlinear mechanisms that allow them to implement elementary computations. 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.
ISSN:0147-006X
1545-4126
DOI:10.1146/annurev.neuro.28.061604.135703