https://github.com/csinva/axon-ap-propagation

Code for simulations of action potential propagation
https://github.com/csinva/axon-ap-propagation

action-potential axon neuron-simulations neuroscience simulation

Last synced: 19 days ago
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Code for simulations of action potential propagation

• Host: GitHub
• URL: https://github.com/csinva/axon-ap-propagation
• Owner: csinva
• Created: 2017-01-31T04:33:12.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2017-05-19T18:50:07.000Z (over 7 years ago)
• Last Synced: 2024-10-28T12:02:46.889Z (2 months ago)
• Topics: action-potential, axon, neuron-simulations, neuroscience, simulation
• Language: AMPL
• Size: 7.56 MB
• Stars: 1
• Watchers: 4
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# axon simulations

- tapering axon simulation code based on Johnson, Holmes, Brown, and Jung 2015

# setup

## run the code

- clone the repo

- compile the mod files (differs based on OS - see NEURON documentation)

- run main.hoc

# todo

# reference

## goals

1. maximize velocity

2. minimize energy

3. minimize noise variability

## constraints

- amount of protein membrane can sustain

### hypotheses

- node only gets to minimum needed

	- see brill et al ~1997

- Resting potential might be getting messed up

- Look at changing gbar

- Look at changing potassium conductances

## notes

- currently fires with noise

	- fires at very low voltage

- Johnson, Holmes, Brown, and Jung 2015

	- Goal: maximize conduction velocity but minimize metabolic costs

	- Myelination does this by decreasing capacitance

	- Increasing axon diameter does this by increasing ion flow

	- They assume fixed number of sodium channels and change morphology

	- 3 different taperings along the PARA

- other papers

	- base on Mcintyre, Richardson, and Grill 2001

	- empirical fits to blight, 1985 rat recording and david, 1995 rat recording

	

## done

- fixed surface area and looked at different diameters