Untangling Dendrites with Quantitative Models

Segev, Idan; London, Michael

doi:10.1126/science.290.5492.744

Cited by 278 publications

(194 citation statements)

References 85 publications

(36 reference statements)

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“…Dendrites have recently received a great deal of attention and substantial progress has been made in understanding their function [132][133][134] . Axons deserve comparable attention so that their complex properties can be fully explored.…”

Section: Resultsmentioning

confidence: 99%

Information processing in the axon

2004

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Section: Resultsmentioning

confidence: 99%

Information processing in the axon

2004

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“…Among these are the spatial distribution of inputs along dendrites as pioneered by Rall (1967), nonlinear dendritic interactions (for reviews see Koch andSegev 2000, Segev andLondon 2000), or the impact of high conductance states (Destexhe et al 2003;Geisler et al 2005).…”

Section: Discussionmentioning

confidence: 99%

The response of cortical neurons to in vivo-like input current: theory and experiment: II. Time-varying and spatially distributed inputs

et al. 2008

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The response of a population of neurons to time-varying synaptic inputs can show a rich phenomenology, hardly predictable from the dynamical properties of the membrane's inherent time constants. For example, a network of neurons in a state of spontaneous activity can respond significantly more rapidly than each single neuron taken individually. Under the assumption that the statistics of the synaptic input is the same for a population of similarly behaving neurons (mean field approximation), it is possible to greatly simplify the study of neural circuits, both in the case in which the statistics of the input are stationary (reviewed in La Camera et al. in Biol Cybern, 2008) and in the case in which they are time varying and unevenly distributed over the dendritic tree. Here, we review theoretical and experimental results on the single-neuron properties that are relevant for the dynamical collective behavior of a population of neurons. We focus on the response of integrate-and-fire neurons and real cortical neurons to long-lasting, noisy, in vivo-like stationary inputs and show how the theory can predict the observed rhythmic activity of cultures of neurons. We then show how cortical neurons adapt on multiple time scales in response to input with stationary statistics in vitro. Next, we review how it is possible to study the general response properties of a neural circuit to time-varying inputs by estimating the response of single neurons to noisy sinusoidal currents. Finally, we address the dendrite-soma interactions in cortical neurons leading to gain modulation and spike bursts, and show how these effects can be captured by a two-compartment integrate-and-fire neuron. Most of the experimental results reviewed in this article have been successfully reproduced by simple integrate-and-fire model neurons.

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“…In mammals, the development of a proper dendritic branching pattern strongly relies on extracellular cues, such as neurotransmitters, trophic factors, the extracellular matrix, and cell adhesion molecules and the subsequent adjustment of the dynamics of intracellular processes that underlie dendrite growth and stability (3,4). The Ras-phosphoinositide 3-kinase (PI3K) and Ras-extracellular signal-regulated kinase (ERK) signaling pathways were previously shown to contribute to brain-derived neurotrophic factor (BDNF) 2 driven dendritic arborization, most likely via activation of mTOR and its downstream effector p70S6K1 (S6K1) (5). The S6K1-dependent translation of cytoskeleton-regulating proteins was shown to be sufficient to drive axonal growth (6).…”

mentioning

confidence: 99%

“…The electrical properties of neurons are regulated by the composition and density of synapses and pattern of dendritic branching (1,2). In mammals, the development of a proper dendritic branching pattern strongly relies on extracellular cues, such as neurotransmitters, trophic factors, the extracellular matrix, and cell adhesion molecules and the subsequent adjustment of the dynamics of intracellular processes that underlie dendrite growth and stability (3,4).…”

mentioning

confidence: 99%