///////////////////////
/* net_dd_emodel.hoc */
///////////////////////

objref principalneuron[nPN]			// the "network" of Principal Cells (n = nPN)

begintemplate Principalneuron			// template of a Principal Cell

public  soma_principalneuron, old_v, drv_principalneuron, syn_IE, \
			switch_syn_IE, set_syn, change_Imu_principalneuron, \
			pre_list_IE, connect_pre_IE, is_connected_IE,\
			disconnect_cell_IE, syn_EE, pre_list_EE, connect_pre_EE, disconnect_cell_EE,\
      is_connected_EE, currents, index_PN, switch_syn_EE, indicing_PN,\
      bgdrive, inj_input, injvec, signinput

external n_d_principalneuron,n_L_principalneuron,n_seg_principalneuron,Ek_principalneuron,\
			 ARes_principalneuron,MCap_principalneuron,Rm_principalneuron, Vrest_principalneuron,\
       gna_principalneuron, shift_principalneuron, ena_principalneuron, gkdr_principalneuron,\
       gka_principalneuron, gkm_principalneuron,\
       Syn_IE_rise, SynE_IE, SynDel, SynADel, Imu_principalneuron, tstop,\
			 Syn_EE_rise, Syn_EE_decay, SynE_EE, Ek_principalneuron, tauvec_IE, Syn_IE_N,\
			 temiinj_PN, iinj_time, inj_step, BGSyn_rise_PN, BGSyn_decay_PN, max_ddcon_IE, nPN,\
       tPNinj_on, PN_SIGNSyn_rise, PN_SIGNSyn_decay 
			 
objref syn_IE[50], pre_list_IE, syn_EE, pre_list_EE, injvec,\
	     drv_principalneuron, net_c_interneuron, net_c_principalneuron, bgsyn, bgdrive_list, inj_PN,\
	     signinput_list, signsyn

create soma_principalneuron

proc init() {
   pre_list_IE = new List()
   pre_list_EE = new List()
   bgdrive_list = new List()
   signinput_list = new List()
   
   soma_principalneuron { 
		    //geometry
		    diam = n_d_principalneuron  L=n_L_principalneuron nseg=n_seg_principalneuron 
		    f_surf = area(0.5)/100000
		
		    //cable params
		    Ra = ARes_principalneuron cm=MCap_principalneuron v=Vrest_principalneuron 
		    old_v = Vrest_principalneuron
		
        //membrane mechanisms
        insert pas 
            e_pas=Vrest_principalneuron 
            g_pas=1/Rm_principalneuron 
                       
        insert na3
            gbar_na3 = gna_principalneuron
            sh_na3 = shift_principalneuron
            ena = ena_principalneuron
        insert kdr
            gkdrbar_kdr = gkdr_principalneuron
            sh_kdr = shift_principalneuron
            ek = Ek_principalneuron
        insert kap
            gkabar_kap = gka_principalneuron
            sh_kap = shift_principalneuron
        insert km
            gbar_km = gkm_principalneuron
            sh_km=shift_principalneuron
        
        // postsynaptic IPSCs
		    for i = 0,Syn_IE_N-1 {
            syn_IE[i] = new Exp2Syn(0.5)
            syn_IE[i].tau1 = Syn_IE_rise
            syn_IE[i].tau2 = tauvec_IE.x[i*(max_ddcon_IE/Syn_IE_N)]
            syn_IE[i].e = SynE_IE
        }
		    
		    // postsynaptic EPSCs
		    syn_EE = new Exp2Syn(0.5)		
		
		    syn_EE.tau1 = Syn_EE_rise
		    syn_EE.tau2 = Syn_EE_decay
		    syn_EE.e = SynE_EE
		    
		    // excitatory synapses for background drive
        bgsyn = new Exp2Syn(0.5)
        bgsyn.tau1 = BGSyn_rise_PN
        bgsyn.tau2 = BGSyn_decay_PN
        bgsyn.e = 0
        
        // excitatory synapses for synaptic input signal
        signsyn = new Exp2Syn(0.5)
        signsyn.tau1 = PN_SIGNSyn_rise
        signsyn.tau2 = PN_SIGNSyn_decay
        signsyn.e = 0

		    // IClamps - a) constant drive
		    drv_principalneuron = new IClamp(0.5)

		    drv_principalneuron.del = 0
		    drv_principalneuron.dur = tstop
		    drv_principalneuron.amp = Imu_principalneuron*f_surf	// nA
		    // excitatory curent injection - the density param. 'Imu' [uA/cm^2] should be converted 
		    // to the injected current 'amp' [nA] using the factor 'fsurf' derived from the 
		    // surface area [um^2] and the conversion of the units
		    
		    // IClamps - b) for shaped input
		    inj_PN = new IClamp(0.5)

		    inj_PN.del = 0
		    inj_PN.dur = tstop
	  }
}   

proc indicing_PN() {
  index_PN = $1
}

// ****IPSCs****
proc connect_pre_IE() {local f, axdel, strength
// $o1 arg is the **PRESynaptic** Cell, $2 is the distance between the cells, $3 gsyn, $4 distance for the tau-Vector
   axdel=$2*SynADel       // in ms distance between cells 50 um
                       	  // AP propagation  .25 m/s => 0.2 ms for one interval
   strength = $3*f_surf	  // synaptic strength calculate using the surface factor
   synno = int(($4*Syn_IE_N)/(max_ddcon_IE+1))   			   

   $o1.soma_interneuron pre_list_IE.append( new NetCon(&v(1),syn_IE[synno],-20,SynDel+axdel,strength))
  // list.append() adds new items to the list
	// NetCon: (presynaptic variable, target, thresh, delay, weight)
	// the last argument is the 'weight' with a range of [0-1] where 1 corresponds to 1 ęS peak 
	// conversion: 'SynG' [mS/cm^2] to 'weight' [uS] using the factor 'fsurf' derived from the 
	// surface area [um^2] and the conversion of the units
}

proc disconnect_cell_IE() {
   pre_list_IE.remove_all()
}

func is_connected_IE() {local i,c			// check if connected
   c = 0
   for i = 0,pre_list_IE.count()-1 {
		net_c_interneuron = pre_list_IE.object(i)		// get netCon object from list
		if ($o1 == net_c_interneuron.precell()) {c=1}
   }
   return c
}   

proc switch_syn_IE() {local i			// check if connected
   for i = 0,Syn_IE_N-1 {
      syn_IE[i].tau1 = Syn_IE_rise			// to make sure changes in syn params 
      syn_IE[i].tau2 = tauvec_IE.x[i*(max_ddcon_IE/Syn_IE_N)]
      syn_IE[i].e = SynE_IE
   }
   
   for i = 0,pre_list_IE.count()-1 {
	    net_c_interneuron = pre_list_IE.object(i)		// get netCon object from list
	    net_c_interneuron.active($1)
	 }
}


// ****EPSCs****
proc connect_pre_EE() {local f, axdel, strength
  // $o1 arg is the **PRSynEaptic** Cell, $2 is the distance between the cells, $3 gsyn
   axdel=$2*SynADel       // AP propagation  .25 m/s => 0.2 ms for one interval
   strength = $3*f_surf	  // synaptic strength calculate using the surface factor			   
   $o1.soma_principalneuron pre_list_EE.append( new NetCon(&v(1),syn_EE,-20,SynDel+axdel,strength))
   // list.append() adds new items to the list
	// NetCon: (presynaptic variable, target, thresh, delay, weight)
	// the last argument is the 'weight' with a range of [0-1] where 1 corresponds to 1 ęS peak 
	// conversion: 'SynG' [mS/cm^2] to 'weight' [uS] using the factor 'fsurf' derived from the 
	// surface area [um^2] and the conversion of the units
}

proc disconnect_cell_EE() {
   pre_list_EE.remove_all()
}

func is_connected_EE() {local i,c			// check if connected
   c = 0
   for i = 0,pre_list_EE.count()-1 {
		net_c_principalneuron = pre_list_EE.object(i)		// get netCon object from list
		if ($o1 == net_c_principalneuron.precell()) {c=1}
   }
   return c
}   

proc switch_syn_EE() {local i			// check if connected
   syn_EE.tau1 = Syn_EE_rise			// to make sure changes in syn params 
                                  // take place in the network
   syn_EE.tau2 = Syn_EE_decay
   
   syn_EE.e = SynE_EE

    for i = 0,pre_list_EE.count()-1 {
		  net_c_principalneuron = pre_list_EE.object(i)		// get netCon object from list
		  net_c_principalneuron.active($1)
		}
}



proc change_Imu_principalneuron() {
  if (numarg()<1) {
	 drv_principalneuron.amp = Imu_principalneuron*f_surf
	} else {
	 drv_principalneuron.amp = $1*f_surf
	}
}

// ****Background synaptic drive****
proc bgdrive() {
    strength = $2*f_surf
    bgdrive_list.append( new NetCon($o1,bgsyn,10,0,strength) )    
}

// ****Shaped input****
proc inj_input() {
  injvec = new Vector(tstop/inj_step)
  // $1 is the multiplicative factor that depends on the spatial position of the cell in the net!
  injvec = temiinj_PN.c.mul(f_surf*$1)
  // $2 is a variability factor determined by spainput_on_sd
  for i = tPNinj_on/inj_step,$2/inj_step {
      injvec.x[i-1] = 0
  }
  injvec.play(&inj_PN.amp,iinj_time,1)
}

proc signinput() {
    strength = $2*f_surf
    signinput_list.append( new NetCon($o1,signsyn,10,0,strength) )    
}

endtemplate Principalneuron