Interaural time difference detection by slowly integrating neurons (Vasilkov Tikidji-Hamburyan 2012)

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Accession:150445
For localization of a sound source, animals and humans process the microsecond interaural time differences of arriving sound waves. How nervous systems, consisting of elements with time constants of about and more than 1 ms, can reach such high precision is still an open question. This model shows that population of 10000 slowly integrating Hodgkin-Huxley neurons with inhibitory and excitatory inputs (EI neurons) can detect minute temporal disparities in input signals which are significantly less than any time constant in the system.
Reference:
1 . Vasilkov VA, Tikidji-Hamburyan RA (2012) Accurate detection of interaural time differences by a population of slowly integrating neurons. Phys Rev Lett 108:138104 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Auditory brainstem;
Cell Type(s): Hodgkin-Huxley neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s):
Implementer(s): Tikidji-Hamburyan, Ruben [ruben.tikidji.hamburyan at gmail.com] ; Vasilkov, Viacheslav [vasilkov.va at gmail.com];
This model package provides NEURON codes associated with paper:
Vasilkov V. A. and Tikidji-Hamburyan R. A.(2012) 
Accurate Detection of Interaural Time Differences by a Population of Slowly Integrating Neurons.
Phys. Rev. Lett. 108, 138104. 

Scripts in this folder were used to produce Fig.3c of the paper.

Any questions for implementing the model should be directed to 
	Ruben Tikidji-Hamburyan (rtikid@lsuhsc.edu, ruben.tikidji.hamburyan@gmail.com) 
	OR/AND 
	Viacheslav Vasilkov (vasilkov.va@gmail.com)

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To run simulation:
under Linux:
$nrnivmodl
$nrngui -nogui hh10000-X-X-X.hoc

To get dat file:
$python csv2dat.py hh10000-X-X-X.csv
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File description:

README - this file

hh10000-gsyngrad-scan11-step0.01.hoc
hh10000-gsyngrad-scan55-step0.1.hoc
hh10000-delaygrad-scan11-step0.01.hoc
hh10000-delaygrad-scan55-step0.1.hoc
hh10000-jitter-scan11-step0.01.hoc
hh10000-jitter-scan55-step0.1.hoc
hh10000-noisecur-scan11-step0.01.hoc
hh10000-noisecur-scan55-step0.1.hoc
	every script produces a 'comma separated values' file(csv) with
	population-rate transfer function for 10000 Hodgkin-Huxley neurons
	model, with:
		gsyngrad - synaptic conductances gradients
		delaygrad - delay lines gradients 
		jitter - jitter in pathways
		noisecur - neuron intrinsic noise current
	scan11 / scan55 means that population-rate transfer function was tested 
		within [-1, 1]ms or [-5, 5]ms respectively.
	step - indicates ITD step for testing mesh in selected range. 

rgi.mod - mechanisms for noise current. For better performance, please
	use Ted Carnevale's InNp.mod for future versions.

hhcell.hoc - template for standard Hodgkin-Huxley neuron model with noise
	current. WARNING: To use scripts with thread mode, one must include
	independent random number generator in this template .

main.hoc - functions to run simulation iteratively and obtain population-rate
	transfer function. DON'T run this file. See Scripts above.

csv2dat.py - simple python script, to convert csv to standard two 
	columns dat file.