BrainPharm: Computational model - Perfect Integrate and fire with noisy adaptation or fractional noise (Richard et al 2018)

Computational model

Data

Name

Perfect Integrate and fire with noisy adaptation or fractional noise (Richard et al 2018)

Submitter name

Patricio Orio

Pipeline ID

Model File

Codes-modeldb [16960]

Notes

"Here we show that a purely Markovian integrate-and-fire (IF) model, with a noisy slow adaptation term, can generate interspike intervals (ISIs) that appear as having Long-range dependency (LRD). However a proper analysis shows that this is not the case asymptotically. For comparison, we also consider a new model of individual IF neuron with fractional (non-Markovian) noise. The correlations of its spike trains are studied and proven to have LRD, unlike classical IF models."

Model Neurons

More Cells

Abstract integrate-and-fire leaky neuron Show Other

Model Currents

Model Receptors

Model Type

Model Concept

Simulator software

Python Show Other

Model papers

Richard A, Orio P, Tanré E (2018) Show Other

Gene

hg folder name (applicable when in ModelDB hg)

Region Organism

Model ID Number

Gap Junctions

Implemented by

Orio, Patricio [patricio.orio at uv.cl] Show Other
Richard, Alexandre Show Other

Public Submitter Email Address

patricio.orio@uv.cl

Other Neuron

Model Neurotransmitters

Other Receptor

Other Current

Other Neurotransmitter

Other Model Type

Other Concept

fractional noise

Other Simulator

Other Implementer

Alexandre Richard

Alternative Version

Citation

Default File Notes

Other Gene

Simulation Platform ID

Has Model View

False

Component

RAM

Hide Auto-launch button

False

Run Protocols

ICG Channel Details

Species

Other categories referring to Perfect Integrate and fire with noisy adaptation or fractional noise (Richard et al 2018)

Revisions:	12
Last Time:	3/27/2018 8:09:39 PM
Reviewer:	Robert A McDougal
Owner:	Patricio Orio