Striatal Spiny Projection Neuron, inhibition enhances spatial specificity (Dorman et al 2018)

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We use a computational model of a striatal spiny projection neuron to investigate dendritic spine calcium dynamics in response to spatiotemporal patterns of synaptic inputs. We show that spine calcium elevation is stimulus-specific, with supralinear calcium elevation in cooperatively stimulated spines. Intermediate calcium elevation occurs in neighboring non-stimulated dendritic spines, predicting heterosynaptic effects. Inhibitory synaptic inputs enhance the difference between peak calcium in stimulated spines, and peak calcium in non-stimulated spines, thereby enhancing stimulus specificity.
1 . Dorman DB, Jedrzejewska-Szmek J, Blackwell KT (2018) Inhibition enhances spatially-specific calcium encoding of synaptic input patterns in a biologically constrained model. Elife, Kennedy, Mary B, ed. [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: Basal ganglia;
Cell Type(s): Neostriatum spiny neuron;
Channel(s): Ca pump; Kir; I A; I A, slow; I CAN; I K,Ca; I Krp; I Na,t; I L high threshold; I R; I T low threshold; IK Bkca; IK Skca; Na/Ca exchanger;
Gap Junctions:
Receptor(s): AMPA; NMDA; GabaA;
Gene(s): Cav3.2 CACNA1H; Cav3.3 CACNA1I; Cav1.2 CACNA1C; Cav1.3 CACNA1D; Cav2.2 CACNA1B; Kv4.2 KCND2; Kir2.1 KCNJ2; Kv2.1 KCNB1;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: GENESIS;
Model Concept(s): Calcium dynamics; Detailed Neuronal Models; Synaptic Integration; Synaptic Plasticity;
Implementer(s): Dorman, Daniel B ;
Search NeuronDB for information about:  GabaA; AMPA; NMDA; I Na,t; I L high threshold; I T low threshold; I A; I K,Ca; I CAN; I A, slow; Na/Ca exchanger; I Krp; I R; Ca pump; Kir; IK Bkca; IK Skca; Gaba; Glutamate;
/***************************		MS Model, Version 9.1 *********************
**************************** 	    	Kirg 			*********************
						Rebekah Evans updated 3/22/12 

function make_KIR_channel

 //initial parameters for making tab channel
	float Erev = -0.09
	int m_power = 1
    int h_power = 0
//units are mV, ms
	float mA_rate = 1e-5
	float mA_slope = -11
	float mB_rate = 1.2
	float mB_vhalf = 30
	float mB_slope = -50

	str path = "KIR_channel" 

    float xmin  = -0.15  /* minimum voltage we will see in the simulation */     // V
    float xmax  = 0.05  /* maximum voltage we will see in the simulation */      // V
    int xdivsFiner = 4000
    int c = 0

   float increment = (xmax - xmin)*1e3/xdivsFiner  // mV
   float x = -150.00 
    create tabchannel {path} 
    call {path} TABCREATE X {xdivsFiner} {xmin} {xmax}  // activation   gate

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

    /* fill the tables with the values of tau and minf/hinf
     * calculated from tau and minf/hinf
	for (c = 0; c < {xdivsFiner} + 1; c = c + 1)
		float m_alpha = {exp_form {mA_rate} {mA_slope} {-x}}
		float m_beta = {sig_form {mB_rate} {mB_vhalf} {mB_slope} {x}}
		float mtau = {1e-3}/{{m_alpha}+{m_beta}}

		setfield {path} X_A->table[{c}] {({mtau}*2)/{qfactorKir}}
		setfield {path} X_B->table[{c}] {{m_alpha}/({m_alpha}+{m_beta})}
		x = x + increment
    tweaktau {path} X

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