Forward Dendritic Spikes: A Mechanism for Parallel Processing in Dendritic Subunits and Shifting Output Codes

Forward Dendritic Spikes: A Mechanism for Parallel Processing in Dendritic Subunits and Shifting Output Codes

Oscar Herreras (Cajal Institute, Spain), Julia Makarova (Cajal Institute, Spain) and José Manuel Ibarz (Hospital Ramón y Cajal, Spain)
DOI: 10.4018/978-1-59904-996-0.ch003
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Neurons send trains of action potentials to communicate each other. Different messages are issued according to varying inputs, but they can also mix them up in a multiplexed language transmitted through a single cable, the axon. This remarkable property arises from the capability of dendritic domains to work semi autonomously and even decide output. We review the underlying mechanisms and theoretical implications of the role of voltage-dependent dendritic currents on the forward transmission of synaptic inputs, with special emphasis in the initiation, integration and forward conduction of dendritic spikes. When these spikes reach the axon, output decision was made in one of many parallel dendritic substations. When failed, they still serve as an internal language to transfer information between dendritic domains. This notion brakes with the classic view of neurons as the elementary units of the brain and attributes them computational/storage capabilities earlier billed to complex brain circuits.

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Table of Contents
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Chapter 1
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Chapter 2
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Chapter 3
Oscar Herreras, Julia Makarova, José Manuel Ibarz
Neurons send trains of action potentials to communicate each other. Different messages are issued according to varying inputs, but they can also mix... Sample PDF
Forward Dendritic Spikes: A Mechanism for Parallel Processing in Dendritic Subunits and Shifting Output Codes
Chapter 4
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Spiking Neural P Systems: An Overview
Chapter 5
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Chapter 6
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Recent Methodology in Connectionist Systems
Chapter 7
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Chapter 10
Computing vs. Genetics  (pages 165-181)
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Computing vs. Genetics
Chapter 11
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Chapter 13
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Chapter 14
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Chapter 15
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Chapter 16
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Chapter 17
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Graph Based Evolutionary Algorithms
Chapter 18
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Chapter 19
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