load_file("nrngui.hoc")
load_file("testgroup.ses")
load_file("runtest.ses")
objref vbox
vbox = new VBox()
vbox.intercept(1) //all following creations go into the "vbox" box
xpanel("Comments")
xlabel("'Biophysical' cell with multiple input streams")
xlabel("Demonstration of efficient convergence and stream-specific use-dependent plasticity.")
xlabel("In NEURON, multiple input streams ('spike trains') can share a single postsynaptic")
xlabel("mechanism so that the conductance of the shared mechanism equals the total conductance")
xlabel("that would have occurred if each input stream had its own separate mechanism. This is")
xlabel("computationally efficient because it means that only one set of equations has to be")
xlabel("solved to find the net effect of any number of input streams. Furthermore, the")
xlabel("postsynaptic action of each input stream can show its own use-dependent plasticity.")
xpanel()
xpanel("Instructions")
xlabel("Postsynaptic C0 carries three postsynaptic conductance mechanisms, called")
xlabel("FDSExp2Syn[0], FDSExp2Syn[1], and FDSExp2Syn[2], that have identical biophysical")
xlabel("properties, including short-term plasticity.")
xlabel("Presynaptic Sfast1 fires at 100 ms intervals and drives FDSExp2Syn[0].")
xlabel("Presynaptic Sslow2 fires half as fast and drives FDSExp2Syn[1].")
xlabel("In addition, Sfast1 and Sslow2 both drive FDSExp2Syn[2].")
xlabel("That is, FDSExp2Syn[2] receives convergent input streams from different sources.")
xlabel("1. Before examining the GUI tools used to make this net, run a simulation and")
xlabel(" verify that the blue trace stays on top of the x axis. This shows that")
xlabel(" FDSExp2Syn[0].g + FDSExp2Syn[1].g - FDSExp2Syn[2].g = 0")
xlabel("2. For fastest results, be sure to use 'Local variable dt'")
xlabel(" (see the VariableTimeStep window)")
xlabel("3. Use")
xlabel(" NEURON Main Menu / Window / netstuff")
xlabel(" to reveal the GUI for this demo's network")
xpanel()
vbox.intercept(0) //ends intercept mode
vbox.map() //draw the box and its contents