Role of afferent-hair cell connectivity in determining spike train regularity (Holmes et al 2017)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:241240
"Vestibular bouton afferent terminals in turtle utricle can be categorized into four types depending on their location and terminal arbor structure: lateral extrastriolar (LES), striolar, juxtastriolar, and medial extrastriolar (MES). The terminal arbors of these afferents differ in surface area, total length, collecting area, number of boutons, number of bouton contacts per hair cell, and axon diameter (Huwe JA, Logan CJ, Williams B, Rowe MH, Peterson EH. J Neurophysiol 113: 2420 –2433, 2015). To understand how differences in terminal morphology and the resulting hair cell inputs might affect afferent response properties, we modeled representative afferents from each region, using reconstructed bouton afferents. ..."
Reference:
1 . Holmes WR, Huwe JA, Williams B, Rowe MH, Peterson EH (2017) Models of utricular bouton afferents: role of afferent-hair cell connectivity in determining spike train regularity. J Neurophysiol 117:1969-1986 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Axon;
Brain Region(s)/Organism: Turtle vestibular system;
Cell Type(s): Vestibular neuron; Turtle vestibular neuron;
Channel(s): I A; I h; I K; I K,Ca; I L high threshold; I M; I Na,t; I_KD;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potentials; Activity Patterns;
Implementer(s): Holmes, William [holmes at ohio.edu];
Search NeuronDB for information about:  I Na,t; I L high threshold; I A; I K; I M; I h; I K,Ca; I_KD;
COMMENT
Alpha function Hair Cell synapse 

activation follows Poisson rate (atau) time constant
alpha(t) = t/tau * exp( -t/tau )

ENDCOMMENT

VERBATIM
extern double du_dev0( );
extern double dexp_dev( );
ENDVERBATIM

NEURON {
  POINT_PROCESS 	afhcsyn_i0
  RANGE 		i, tau, atau, sw, del
  NONSPECIFIC_CURRENT 	i
}

PARAMETER {
  e 	= 0   	(mV)	: equib potential
  tau	= 1.3	(ms)	: time constant of alpha current
  atau	= 0	(ms)	: time constant of activation (default=0 => inactive )
  sw	= 0.1	(pS)	: default synaptic weight
  del	= 0.1	(ms)	: default delay

  idebug = 0
}

ASSIGNED {
  v (mV)
  i (nanoamp)
}

STATE {
  a (pS)
  g (pS)
}

UNITS {
 (mV) 	= (millivolt)
 (pS) 	= (picosiemens)
 PI	= (pi) (1)
}

INITIAL {
  net_send( 0, 1 )
  g = 0
}

BREAKPOINT {
  SOLVE state METHOD sparse
  i = g*( v - e )*(1e-06)
}

KINETIC state {
  ~ a <-> g ( 1/tau, 0 )
  ~ g  ->   ( 1/tau )
}

NET_RECEIVE( weight (pS)) {
  LOCAL wait
  UNITSOFF
  if( idebug ) {
    printf( "Net_receive afhcsyn: t %g flag %g", t, flag )
    if( flag == 0 ){ printf( " weight %g", weight ) }
    printf( "\n" )
  }
  if( flag == 0 ){
    a = a + weight * exp(1)
  }
  if( flag == 1 && atau > 0 ){	
    wait = del                   
    net_send( wait, 2 )
  }
  if( flag == 2 && atau > 0 ){	
    wait = dexp_dev( 1(ms)/atau )
    net_send( wait, 3 )
  }
  if( flag == 3 && atau > 0 ){	
    a = a + sw *exp(1)
    wait = dexp_dev( 1/atau )
    net_send( wait, 1 )
  }
  UNITSON
}