Title
The response of cortical neurons to in vivo-like input current: theory and experiment: II. Time-varying and spatially distributed inputs.
Abstract
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.
Year
DOI
Venue
2008
10.1007/s00422-008-0270-9
Biological Cybernetics
Keywords
Field
DocType
integrate-and-fire neuron,m. giugliano acknowledges support from the european commission keywords populations of spiking neurons · dynamics · integrate-and-fire model · patch clamp · calcium spikes,inherent time constant,general response property,multiple time scale,simple integrate-and-fire model neuron,single neuron,neural circuit,cortical neuron,vivo-like input current,real cortical neuron,neural networks,time constant,patch clamp,dynamics
Population,Collective behavior,Neuroscience,Computer science,Shunting inhibition,Artificial neural network,Neuron,Biological neural network,Winner-take-all,Time constant
Journal
Volume
Issue
ISSN
99
4-5
1432-0770
Citations 
PageRank 
References 
5
0.44
14
Authors
4
Name
Order
Citations
PageRank
Michele Giugliano110912.36
Giancarlo La Camera2385.05
Stefano Fusi366990.97
Walter Senn431627.52