A novel multiple objective optimization framework for constraining conductance-based neuron models by experimental data
We present a novel framework for automatically constraining parameters of compartmental models of neurons, given a large set of experimentally measured responses of these neurons. In experiments, intrinsic noise gives rise to a large variability (e.g., in firing pattern) in the voltage responses to...
Main Authors: | Shaul Druckmann, Yoav Banitt, Albert A Gidon, Felix Schürmann, Henry Markram, Idan Segev |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2007-10-01
|
Series: | Frontiers in Neuroscience |
Subjects: | |
Online Access: | http://journal.frontiersin.org/Journal/10.3389/neuro.01.1.1.001.2007/full |
Similar Items
-
Firing frequency maxima of fast-spiking neurons in human, monkey and mouse neocortex
by: Bo Wang, et al.
Published: (2016-10-01) -
Perceptron Learning and Classification in a Modeled Cortical Pyramidal Cell
by: Toviah Moldwin, et al.
Published: (2020-04-01) -
The Role of Hub Neurons in Modulating Cortical Dynamics
by: Eyal Gal, et al.
Published: (2021-09-01) -
Human Cortical Pyramidal Neurons: From Spines to Spikes via Models
by: Guy Eyal, et al.
Published: (2018-06-01) -
A ‘Facebook’ for neurons: rebuilding a realistic corticostriatal ‘social network’ from dissociated cells.
by: Marianela eGarcia Munoz, et al.
Published: (2015-04-01)