Calcium influx during striatal upstates (Evans et al. 2013)

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"... To investigate the mechanisms that underlie the relationship between calcium and AP timing, we have developed a realistic biophysical model of a medium spiny neuron (MSN). ... Using this model, we found that either the slow inactivation of dendritic sodium channels (NaSI) or the calcium inactivation of voltage-gated calcium channels (CDI) can cause high calcium corresponding to early APs and lower calcium corresponding to later APs. We found that only CDI can account for the experimental observation that sensitivity to AP timing is dependent on NMDA receptors. Additional simulations demonstrated a mechanism by which MSNs can dynamically modulate their sensitivity to AP timing and show that sensitivity to specifically timed pre- and postsynaptic pairings (as in spike timing-dependent plasticity protocols) is altered by the timing of the pairing within the upstate. …"
1 . Evans RC, Maniar YM, Blackwell KT (2013) Dynamic modulation of spike timing-dependent calcium influx during corticostriatal upstates. J Neurophysiol 110:1631-45 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Striatum;
Cell Type(s): Neostriatum medium spiny direct pathway GABA cell;
Channel(s): I Na,t; I L high threshold; I N; I A; I K; I K,Ca; I A, slow; I Krp; I R;
Gap Junctions:
Receptor(s): AMPA; NMDA; Gaba;
Gene(s): Cav1.3 CACNA1D; Cav1.2 CACNA1C; Cav2.2 CACNA1B;
Simulation Environment: GENESIS;
Model Concept(s): Oscillations; STDP; Calcium dynamics;
Implementer(s): Evans, Rebekah [Rebekah.Evans at];
Search NeuronDB for information about:  Neostriatum medium spiny direct pathway GABA cell; AMPA; NMDA; Gaba; I Na,t; I L high threshold; I N; I A; I K; I K,Ca; I A, slow; I Krp; I R;
BK.g *
CaT.g *
gaba_channel.g *
KaF.g *
KaFnew.g *
Kir.g *
NaF.g *
NaFslowinact.g *
SK.g *
tabchanforms.g *

/***************************MS Model, Version 9.1	*********************
****************************   NaF.g 	*********************
updated Rebekah Evans 3/22/12					

//**ref: Nobukuni Ogata, 1990

function make_NaF_channel
float Erev       = 0.05      // V

    str path = "NaF_channel" 

    float xmin  = -0.10  /* minimum voltage we will see in the simulation */     // V
    float xmax  = 0.05  /* maximum voltage we will see in the simulation */      // V
    int xdivsFiner = 3000
    int c = 0
   float increment = (xmax - xmin)*1e3/xdivsFiner  // mV

//Inactivation constants for alphas and betas
//units are mV, ms
	//mtau fits ogata figure 5 perfectly, but no qfactor is applied.  
    float mtau_min=0.1
	float mtau_rate = 1.45
	float mtau_slope = 8
    float mtau_vhalf=-62
	//activation minf fits Ogata 1990 figure 3C (which is cubed root) 
	float mss_rate = 1
	float mss_vhalf = -25
	float mss_slope = -10

	//htau fits the main -50 through -10 slope of Ogata figure 9 (log tau), but a qfact of 2 is already taken into account.  
    float htau_min=0.2754
	float htau_rate = 1.2
	float htau_slope = 3
    float htau_vhalf=-42
	//inactivation hinf fits Ogata 1990 figure 6B
	float hss_rate = 1
	float hss_vhalf = -60
	float hss_slope = 6
 	 /****** End vars used to enable genesis calculations **********/ 	 

    create tabchannel {path} 
    call {path} TABCREATE X {xdivsFiner} {xmin} {xmax}  // activation   gate
    call {path} TABCREATE Y {xdivsFiner} {xmin} {xmax}  // inactivation gate

   float x = -100.00             // mV

   echo "Make naF, qfactor=" {qfactorNaF}

 for(c = 0; c < {xdivsFiner} + 1; c = c + 1) 

        float m_ss = {sig_form {mss_rate} {mss_vhalf} {mss_slope} {x}}
        float m_tau = {mtau_min} + {sig_form {mtau_rate} {mtau_vhalf} {mtau_slope} {x}}*{sig_form {mtau_rate} {mtau_vhalf} {-mtau_slope} {x}}
        float h_ss = {sig_form {hss_rate} {hss_vhalf} {hss_slope} {x}}
        float h_tau = {htau_min} + {sig_form {htau_rate} {htau_vhalf} {htau_slope} {x}}
   /* 1e-3 converts from ms to sec */		

	    setfield {path} X_A->table[{c}] {1e-3*{m_tau}/{qfactorNaF}}
        setfield {path} X_B->table[{c}] {m_ss}
	    setfield {path} Y_A->table[{c}] {2e-3*{h_tau}/{qfactorNaF}}  //qfact of 2 taken into account in original fit.  
        setfield {path} Y_B->table[{c}] {h_ss}

		x = x + increment

/* Defines the powers of m Hodgkin-Huxley equation*/
    setfield {path} Ek {Erev} Xpower 3 Ypower 1

    /* fill the tables with the values of tau and minf/hinf
     * calculated from tau and minf/hinf
   tweaktau {path} X
   tweaktau {path} Y   


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