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;
function createRandTimeTables(path,name,nTables,meanFreq,duration)
    int i,nTables
    float meanFreq,duration
    str path
    str name
    if(!{exists {path}})
        create neutral {path}
// Loop to setup time table objects
    for (i = 1;i<nTables+1;i=i+1)
        create timetable {path}/{name}[{i}]
        setfield {path}/{name}[{i}] maxtime {duration} act_val 1.0 method 1 meth_desc1 {meanFreq}
        call {path}/{name}[{i}] TABFILL
        // Note: Time Table can connect directly to synapse with
        //       activation message, but not SPIKE message; Spike message
        //       is handled differently by SYNCHAN, allowing creating of synapse with weights/delays
        create spikegen {path}/{name}[{i}]/spikes

        setfield {path}/{name}[{i}]/spikes \
                 output_amp 1 thresh 0.5 abs_refract 0.0001

        addmsg {path}/{name}[{i}] {path}/{name}[{i}]/spikes \
               INPUT activation

// Connect time tables to synapses

function countSynapses(synTypeSearchString, return_synpath,synindex)
    str synTypeSearchString
    str synpath
    int return_synpath
    int synindex
    int syncount = 0
    str compt
    str searchstr
    foreach compt ({el {neuronname}/##/{synTypeSearchString}})
        syncount = syncount+1
        if (syncount == synindex)
            //echo {compt} {syncount}
            synpath = compt
    //echo {"syncount= "@{syncount}}
    if (return_synpath==1)
        return synpath
        return syncount

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