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]
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): Audition;
Implementer(s): Tikidji-Hamburyan, Ruben [ruben.tikidji.hamburyan at gmail.com] ; Vasilkov, Viacheslav [vasilkov.va at gmail.com];
TITLE Random current


NEURON {
    SUFFIX rgi
    RANGE dc, sd, driver
    NONSPECIFIC_CURRENT i
}

UNITS {
    (mA) = (milliamp)
    (mA/cm2) = (nanoamp/cm2)
}


PARAMETER {
	dt	     (ms)
	dc	= 0. (mA/cm2)	: DC offset of the overall current
	sd	= 0. (mA/cm2)	: square root of the steady-state variance of the current
}

ASSIGNED {
    i (mA/cm2)              : overall sinusoidal noisy current
    driver
}

INITIAL {
    i = dc
}

BREAKPOINT {
    i = dc - sd*driver
}






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