// genesis 2.2 // Kerstin Menne // Medical University of Luebeck, 10.05.2001 // // file defining all global constants //===================================================================== // equilibrium potentials and other important information for channels //===================================================================== float EREST_ACT = -0.060 // Volts; resting membrane potential; gets randomized // and is therefore slightly different for different // cells float ENA = 0.115 + EREST_ACT // 0.055 // Na equilibrium potential float pyr_EK = -0.015 + EREST_ACT // -0.075; K equilibrium potential for // pyramidal cells float int_EK = -0.025 + EREST_ACT // -0.085; K equilibrium potential for // interneurons float ECA = 0.140 + EREST_ACT // 0.080; Ca equilibrium potential float Q10_synapse = 1.0 // 3.0 float E_GABAA = -0.075 // Volt float G_GABAA = 1 // Siemens*m^-2 float E_NMDA = 0.0 // equilibrium potentials and gmax-values for float G_NMDA = 1 // synchan elements float E_AMPA = 0.0 // maximum conductance of synchan elements is defined float G_AMPA = 1 // by values in cell descriptor files float E_GABAB = -0.080 float G_GABAB = 1 // 20 float GABAA_frequency = 0 // provides input for synchan elements in case float GABAB_frequency = 0 // float AMPA_frequency = 0 // there are no incoming SPIKE messages float NMDA_frequency = 0 // at the moment not used // all other relevant constants for the cells are defined by means of the cell // descriptor files //=========================================================== // cell and network names //========================================================== str pyr_cell_name = "/pyr" str pyr_array_name = "/pyr_array" // array of pyramidal cells str fb_cell_name = "/fb" str fb_array_name = "/fb_array" // array of fb interneurons str ff_cell_name = "/ff" str ff_array_name = "/ff_array" // array of ff interneurons str aff_input_name = "/aff" // randomspike object str aff_input_array_name = "/aff_array" // array for afferent input //============================================================ // network dimensions //========================================================== int pyr_nx = 6 // number of pyramidal cells along x-axis int pyr_ny = 12 // number of pyramidal cells along y-axis int n_of_pyr // number of pyramidal cells in array n_of_pyr = {pyr_nx}*{pyr_ny} float pyr_dx = 40e-6 // distance between pyramidal cells in x-dimension float pyr_dy = 40e-6 // distance between pyramidal cells in y-dimension float pyr_origin_x = 0 // x-coordinate for first element in network float pyr_origin_y = 0 // y-coordinate for first element in network int fb_nx = 3 // number of feedback interneurons along x-axis int fb_ny = 3 // 3 number of feedback interneurons along y-axis int n_of_fb // number of feedback interneurons in array n_of_fb = {fb_nx}*{fb_ny} float fb_dx = 80e-6 // distance between fb interneurons in x-dimension float fb_dy = 160e-6 // 60 distance between fb interneurons in y-dimension float fb_origin_x = 20e-6 // x-coordinate for first element in network float fb_origin_y = 20e-6 // y-coordinate for first element in network int ff_nx = 3 // number of feedforward interneurons along x-axis int ff_ny = 3 // 3 number of feedforward interneurons along y-axis int n_of_ff // number of feedforward interneurons in array n_of_ff = {ff_nx}*{ff_ny} float ff_dx = 80e-6 // distance between ff interneurons in x-dimension float ff_dy = 160e-6 // 60 distance between ff interneurons in y-dimension float ff_origin_x = 20e-6 // x-coordinate for first element in network float ff_origin_y = 100e-6 // y-coordinate for first element in network int aff_nx = 4 // number of randomspike elements along x-axis int aff_ny = 8 // number of randomspike elements along y-axis int n_of_aff // number of randomspike elements in array n_of_aff = {aff_nx}*{aff_ny} float aff_dx = 60e-6 // distance between randomspike elements in x-dimension float aff_dy = 60e-6 // distance between randomspike elements in y-dimension float aff_origin_x = 0 // x-coordinate for first element in network float aff_origin_y = 0 // y-coordinate for first element in network //=================================================================== // x1,y1,z1, x2,y2,z2 for destination mask of volumeconnect //================================================================== float aff2pyr_x1 = -1 // meter float aff2pyr_y1 = -1 // employment of this huge number ensures, that float aff2pyr_z1 = -1 // connections are made from each element in the float aff2pyr_x2 = 1 // source region to each element in the destination float aff2pyr_y2 = 1 // region; afferents can have contacts to float aff2pyr_z2 = 1 // pyramidal cells everywhere in the network float aff2ff_x1 = -1 // meter float aff2ff_y1 = -1 // afferents can have contacts to ff interneurons float aff2ff_z1 = -1 // everywhere in the network float aff2ff_x2 = 1 // float aff2ff_y2 = 1 // float aff2ff_z2 = 1 // float pyr2pyr_x1 = -1 // meter float pyr2pyr_y1 = -1 // employment of this huge number ensures, that float pyr2pyr_z1 = -1 // connections are made from each element in the float pyr2pyr_x2 = 1 // source region to each element in the destination float pyr2pyr_y2 = 1 // region; pyramidal cells can have contacts to other float pyr2pyr_z2 = 1 // pyramidal cell everywhere in the network float pyr2fb_x1 = -1 // pyramidal cells contact fb interneurons everywhere float pyr2fb_y1 = -1 // in the network float pyr2fb_z1 = -1 float pyr2fb_x2 = 1 float pyr2fb_y2 = 1 float pyr2fb_z2 = 1 float fb2pyr_x1 = 0 // interneurons are only allowed to contact pyramidal float fb2pyr_y1 = 0 // cells within a distance of 500microns from the float fb2pyr_z1 = 0 // respective interneuron; since relative positions float fb2pyr_x2 = 1000e-6 // and elipsoidal sourcemask are used, 0,0,0 gives float fb2pyr_y2 = 1000e-6 // the position of the interneuron(center of ellipse) float fb2pyr_z2 = 1000e-6 // x2,y2,z2 specify lengthes of the axis float ff2pyr_x1 = 0 // this simulation is so small, that still each pyramidal float ff2pyr_y1 = 0 // is reached float ff2pyr_z1 = 0 float ff2pyr_x2 = 1000e-6 float ff2pyr_y2 = 1000e-6 float ff2pyr_z2 = 1000e-6 //=================================================================== // connection probabilities //=================================================================== float aff2pyr_AMPA_targets = 7 // number of potential target synchan elements // on a postsynaptic pyramidal cells; level // 3,5,6 float n_aff2pyr_AMPA = 48 // each pyramidal cell shall approximately receive // input to n_aff2pyr_AMPA channels; pyramidal cells // receive more recurrent excitation than excitation // from afferents float p_aff2pyr_AMPA = {n_aff2pyr_AMPA}/({n_of_aff}*{aff2pyr_AMPA_targets}) // 0.21 float aff2pyr_NMDA_targets = 7 // number of potential target synchan elements // on a postsynaptic pyramidal cells float n_aff2pyr_NMDA = 48 // each pyramidal cell shall approximately receive // input to n_pyr2pyr_NMDA channels; pyramidal cells // receive more recurrent excitation than excitation // from afferents float p_aff2pyr_NMDA = {n_aff2pyr_NMDA}/({n_of_aff}*{aff2pyr_NMDA_targets}) // 0.1 float aff2ff_AMPA_targets = 16 // level 7-9 float n_aff2ff_AMPA = 20 // float p_aff2ff_AMPA = {n_aff2ff_AMPA}/({n_of_aff}*{aff2ff_AMPA_targets}) // 0.04 float pyr2pyr_AMPA_targets = 20 // number of potential target synchan elements // on postsynaptic pyramidal cells float n_pyr2pyr_AMPA = 70 // each pyramidal cell shall approximately receive // input to n_pyr2pyr_AMPA channels float p_pyr2pyr_AMPA = {n_pyr2pyr_AMPA}/({n_of_pyr}*{pyr2pyr_AMPA_targets}) // 0.049 float pyr2pyr_NMDA_targets = 20 // level 2 and 8-10 float n_pyr2pyr_NMDA = 70 float p_pyr2pyr_NMDA = {n_pyr2pyr_NMDA}/({n_of_pyr}*{pyr2pyr_NMDA_targets}) // 0.049 float pyr2fb_AMPA_targets = 18 // level 1,2 and 6-8 float n_pyr2fb_AMPA = 60 float p_pyr2fb_AMPA = {n_pyr2fb_AMPA}/({n_of_pyr}*{pyr2fb_AMPA_targets}) // 0.06 float fb2pyr_GABA_A_targets = 6 // level 3-5 float n_fb2pyr_GABA_A = 35 float p_fb2pyr_GABA_A = {n_fb2pyr_GABA_A}/({n_of_fb}*{fb2pyr_GABA_A_targets}) // 0.65 float ff2pyr_GABA_B_targets = 8 // level 1 and 9,10 float n_ff2pyr_GABA_B = 7 float p_ff2pyr_GABA_B = {n_ff2pyr_GABA_B}/({n_of_ff}*{ff2pyr_GABA_B_targets}) // 0.097 //================================================================= // conduction velocities and percentage of randomization for delay //================================================================= float cond_vel_pyr_ax = 0.5 // m*s^-1; pyramidal cell axons are supposed to be // myelinated float cond_vel_fb_ax = 0.2 // unmyelinated float cond_vel_ff_ax = 0.2 // unmyelinated float cond_vel_aff_ax = 0.2 // mossy fibers are unmyelinated (Shepherd) float rand_delay_pyr_ax = 0.15 // calculated delay +/- upto 15% float rand_delay_fb_ax = 0.15 float rand_delay_ff_ax = 0.15 float rand_delay_aff_ax = 0.15 //================================================ // synaptic weights used in volumeweight-function //=============================================== float from_aff_weight = 1 // gmax defined by values in cell descriptor files float from_pyr_weight = 1 // pyramidal cell on presynaptic site float from_fb_weight = 1 // fb interneuron on presynaptic site float from_ff_weight = 1 // ff interneuron on presynaptic site float rand_from_aff_weight = 0.15 // calculated weight +/- up to 15% float rand_from_pyr_weight = 0.15 float rand_from_fb_weight = 0.15 float rand_from_ff_weight = 0.15 //============================================================== // spike generator and randomspike parameters //============================================================== float int_thresh = 0 // V; threshold for interneuronal spike-generator float int_refract = 0.001 // sec; refractory-period float int_amplitude = 1 float pyr_thresh = 0 // V; amplitude of spikes in axonal compartment is crucial float pyr_refract = 0.001 // sec float pyr_amplitude = 1 float aff_min_amp = 1 // parameters for randomspike float aff_max_amp = 1 // all spikes have unit amplitude float aff_rate = 40 // spikes per second float aff_abs_refract = 0.007 //==================================================================== // simulation parameter //==================================================================== float dt = 2.5e-5 // simulation time step in sec setclock 0 {dt} // set the simulation clock setclock 1 {dt} // used for graphical outputs //==================================================================== // hines solver //==================================================================== int chanmode = 1