Default mode network model (Matsui et al 2014)

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Default mode network (DMN) shows intrinsic, high-level activity at rest. We tested a hypothesis proposed for its role in sensory information processing: Intrinsic DMN activity facilitates neural responses to sensory input. A neural network model, consisting of a sensory network (Nsen) and a DMN, was simulated. The Nsen contained cell assemblies. Each cell assembly comprised principal cells, GABAergic interneurons (Ia, Ib), and glial cells. We let the Nsen carry out a perceptual task: detection of sensory stimuli. … This enabled the Nsen to reliably detect the stimulus. We suggest that intrinsic default model network activity may accelerate the reaction speed of the sensory network by modulating its ongoing-spontaneous activity in a subthreshold manner. Ambient GABA contributes to achieve an optimal ongoing spontaneous subthreshold neuronal state, in which GABAergic gliotransmission triggered by the intrinsic default model network activity may play an important role.
1 . Matsui H, Zheng M, Hoshino O (2014) Facilitation of neuronal responses by intrinsic default mode network activity. Neural Comput 26:2441-64 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Gap Junctions:
Receptor(s): GabaA; Glutamate;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: C or C++ program;
Model Concept(s): Sensory processing;
Search NeuronDB for information about:  GabaA; Glutamate; Gaba; Glutamate;
#define h 1.0e-4          //time step
#define c_p 500e-12       //capacitance of P cell
#define c_Ia 200e-12      //            of Ia cell
#define c_Ib 600e-12      //            of Ib cell
#define c_gl 45e-12       //            of glial cell
#define g_p 25e-9         //conductance of P cells
#define g_Ia 20e-9        //            of Ia cell
#define g_Ib 15e-9        //            of Ib cell
#define g_gl 9e-9         //            of glial cell
#define gh_AMPA 0.5e-9    //maximal conductance for AMPA receptor
#define gh_GABA 0.7e-9    //                    for GABA receptor
#define a_p 290e-12       //sensory input current
#define a_AMPA 1.1e+6     //channel opening rate for AMPA receptor
#define a_GABA 5.0e+6     //                     for GABA receptor
#define b_AMPA 190        //channel closing rate for AMPA receptor
#define b_GABA 180        //                     for GABA receptor
#define n_p 270           //steepness of sigmoid function for P cell
#define n_Ia 240          //                              for Ia cell
#define n_Ib 360          //                              for Ib cell
#define n_p_DMN 230       //                              for P (DMN) cell
#define n_Ib_DMN 320      //                              for Ib (DMN) cell
#define s_p -0.0335       //threshold of sigmoid function for P cell
#define s_Ia -0.0390      //                              for Ia cell
#define s_Ib -0.040       //                              for Ib cell
#define s_p_DMN -0.0330   //                              for P (DMN) cell
#define s_Ib_DMN -0.040   //                              for Ib (DMN) cell
#define gam 2.5           //decay constant for ambient GABA concentration 
#define T_GL 140e+7       //GABA transfer coefficient 
#define GABA_0 1.0e-6     //basal ambinet GABA concentration
#define GABA_max 1.5e-6   //maximal ambient GABA concentration
#define GABA_min 0.0      //minimal ambient GABA concentration
#define u_AMPA_rev 0.0    //reversal potential of AMPA receptor
#define u_GABA_rev -80e-3 //                   of GABA receptor
#define u_gl_rev -70e-3   //                   of glial transpoter
#define o_p 60.0e+1       //amount of extrasynaptic GABAa receptor
#define u_p_rest -65e-3   //resting potential of P cell
#define u_Ia_rest -70e-3  //                  of Ia cell
#define u_Ib_rest -70e-3  //                  of Ib cell
#define u_gl_rest -70e-3  //                  of glial cell
#define inp 3.0           //stimulus relevant cell assembly 
#define t_p 0.01          //broadness of input 
#define w_pp 6.5          //synaptic weight from P to P
#define w_pp_DMN 8.0      //synaptic weight from P (DMN) to P (DMN)
#define w_pIb 4.0         //synaptic weight from Ib to P
#define w_pIb_DMN 14.0    //synaptic weight from Ib (DMN) to P
#define w_Ibp 60.0        //synaptic weight from P to Ib
#define w_Ibp_DMN 4.50    //synaptic weight from P (DMN) to Ib
#define w_Ia 30.0         //synaptic weight from P to Ia
#define	w_gl_Ia 20.0      //synaptic weight from Ia to glia
#define w_Ia_DMN 0.0      //synaptic weight from P (DMN) to Ia/////strength of tonic excitation (#: 4.0)
#define	w_p_DMN_Nsen 0.0   //synaptic weight from P (DMN) to P//////strength of phasic excitation(*: 0.535)
#define inp_t 2.0         //input time
#define inp_t_len 0.5     //input time length
#define t_end 3.0         //simulation time
#define seed 5            //seed of random number
#define m 10              //cell unit number of output data (data.csv)