Building a Network: A Walk-Through

[Pre-built parameter files for this walk-through are available in the samples\walk-through network

sub-folder.]

The Network module in Neurosim can simulate neural circuits containing an arbitrary number of

neurons, linked by a wide variety of synaptic types. As an example, we will build a circuit that is

loosely based on the auditory system of an owl – specifically, that part of the system that

implements the Jeffress mechanism for localizing sound origin in the horizontal (azimuth) plane. This

is investigated in detail in one of the Tutorials supplied with Neurosim, but in brief, the mechanism

depends on the difference in the time of arrival of sound at the two ears (the inter-aural time

difference, ITD) when the sound comes from an off-centre source. The time difference is computed

using a combination of axonal delay lines and synaptic coincidence detection. See Sillar et al. (2016)

for a recent review of the mechanism.

Start the Network module of Neurosim.

Warm Up If you are new to Neurosim, it might be helpful to warm up with a quick tour of some editing

features that you can use while building networks.

HOWEVER, you can safely skip this section if you already know what you are doing.

Note the two neurons, N1 and N2, showing as yellow blobs. The blue diamond indicates a spiking

chemical synapse (type a) from N1 to N2. N1 has 2 square boxes above it, which represent external

stimuli.

In the following you will:

Move neurons and groups of neurons

Add neurons

Change connections

Duplicate neurons and connections

Move and duplicate stimuli

Delete neurons and connections

Start again!

Follow these instructions:

Drag N2 to a new location 2 grid nodes directly below N1.

That is how you move a single neuron and its associated connection.

Click-and-drag from above-left of N1 to below-right of N2. A box will draw on the screen as

you drag the mouse, and this should surround both neurons.

When you release the mouse, both N1 and N2 are selected, and will be drawn with a thicker outline.

Drag N1 (or N2) to a new position.

All the selected neurons move together.

Click outside of any neuron to deselect all neurons.

Right-click a grid node away from N1 and N2.

o Select Add neuron from the context menu.

A new neuron, N3, appears at the nearest grid to the location you clicked. This will have the

properties of the most recently-added neuron.

Drag the blue diamond synapse symbol from N2 to N3.

This changes the post-synaptic neuron for this connection.

Right-click on the diamond synapse symbol.

o Select Edit connexion from the context menu.

o Change the Source neuron to 2.

o Change the Class to Non-spiking chemical

o Change the Type to b: hyperpolarizing IPSP

This changes lots of connection properties in one go.

Click N1 and then click N3.

This selects the two neurons individually, without having to drag around them.

Control-drag N1 or N3 to a new location. (Hold down the control key before you press the

mouse button.)

This duplicates N1 and N3 as N4 and N5, and also the connection between N2 and N3, so N2 also

connects to N5. The original neurons remain in place and selected.

Drag the square stimulus box 2 above N1, to N3.

This moves the stimulus.

Drag the stimulus box 2 so that it is positioned directly underneath N3.

This just re-arranges the layout on the screen.

Control-drag the stimulus box 2 to N5.

This duplicates the stimulus. Note that a new stimulus (3) appears in the Stimulus list in the

Experimental Control panel on the left of the layout area.

Right-click N2 (which should be pre-synaptic to N3 and N5).

o Select Delete Neuron from the context menu.

N2 disappears, along with its synaptic connections. The other neurons are re-numbered to fill the

gap.

Finally, select the menu command Model: Reset.

This restores the circuit to its default condition.

IMPORTANT NOTE: Neurosim does not have an undo facility. So if you are building a complex

network, it is a really good idea to save your work frequently, probably using a new name each time.

This means that you can revert to an earlier version if it all goes wrong.

Walk-Through Open or reset the Network module of Neurosim if it is not already the selected module.

Select ms as the Time units at the top of the Experimental Control panel.

Select the Options: Integration menu command to open the Integration dialog

o We will need higher time resolution than the default, so set the Integration time

step to 0.05 ms.

o Click OK.

Select the Options: Configure view menu command to open the Configure Setup View

dialog.

Set the Grid spacing to 25. This will help with the layout later.

Right-click the post-synaptic neuron in the default circuit (N2) and select Delete neuron

from the context menu.

Click Del all in the Stimulus group of the Experimental Control panel.

We now have just a single neuron in the circuit. (We could have also got here by

selecting the Neuron: Delete all menu command.)

Select the File: Save As menu command and save the circuit as Jeff 1 in case we run into

problems and need to revert to this stage.

Coincidence Detection Coincidence detection is at the heart of the Jeffress mechanism, so we will set this up first with just a

single post-synaptic neuron.

Set up the neurons First we will make two sensory neurons (one for each ear) plus one post-synaptic coincidence

detector.

Right-click the layout area a few nodes to the right of the single neuron, and select Add

neuron from the context menu.

Repeat this at a node below and between the other two neurons, so that the three resulting

neurons form a V shape in the layout area.

Double-click N1 to open the Neuron Properties dialog.

o Set the Description to “left ear sensory”.

The text of the description will show as a tooltip if you hover your mouse

over the neuron in the Setup layout area.

o Click Apply. This “locks in” the changes without dismissing the dialog.

o Set the Source to 2 (in the top left of the dialog).

o Set the Description to “right ear sensory”.

o Click the Trace colour button (the coloured block to the right of the label).

Select blue as the colour, and click OK to accept this.

o Click Apply.

o Set the Source to 3.

o Set the Description to “coincidence layer”.

o Click the Trace colour button (the coloured block to the right of the label).

Select dark green as the colour, and click OK to accept this.

o Click OK to accept the entries and dismiss the Properties dialog.

Set up the Results display We now have three neurons, so we will set up the Results display so that we can see their activity.

Click Traces in the Results view to open the Trace and Axis Setup dialog

o Enter 2 in the Neuron(s) edit box of axis 2 (which is already selected as showing).

o Delete the 1 in the Stimulus edit box of axis 3 so that the box is empty, and press

Tab or Enter. This should enable the Neuron edit box for data entry.

o Enter 3 into the Neuron edit box of axis 3.

o Edit the Axis label of axis 3 to read “N3 (mV)”.

o Check the Show box of axis 4.

o Edit the Axis label of axis 4 to read “stim”.

o Enter “1 2” into the Stimulus edit box of axis 4.

o Click OK to accept the entries and dismiss the Trace dialog.

Click the Revert axis scales button in the Results toolbar to set default scale values for

all axes.

Click Start to check that things are OK

You should see flat lines for all traces, since as yet absolutely nothing has been

programmed to happen.

Save the file as Jeff 2.

The next task is to set up coincidence detection. This requires some precisely-timed spikes in the

sensory neurons, and synaptic connections to the coincidence detector.

Set up two pulse stimuli

Set the Results time base (the right-hand X axis scale) to 30 ms so that we can see details of

the timing.

In the Stimulus group of the Experimental Control panel:

Set the Target N to 1.

Set the Duration to 1 ms.

Set the Delay to 10 ms.

Click New.

This applies a stimulus to N1, which should be visible in the Setup view as a square

box attached to the neuron.

For convenience, drag the box until it is vertically above N1.

If necessary, reposition N1 by dragging it to a new location. It will snap to a grid node.

Click Start.

The response to the stimulus is visible, but subthreshold. We want the sensory neurons to be quite

sensitive, so we will change their threshold.

Double-click N1 to open the Properties dialog again.

o In the Integrate-and-fire group, set the Initial threshold to -55 mV.

Click Start. The neuron now spikes, which is what we want.

o In the Properties dialog, check the box beside the Threshold that we just changed.

o At the bottom of the dialog, enter “2” into the Extended Apply list edit box.

o Click Apply.

This will “lock in” all values in the Properties dialog to the source neuron,

which is N1. It will also apply any properties that have the box beside them

checked to all neurons in the Extended Apply list. In this case there is only

N2 in the list, but you could apply the threshold change to any number of

neurons in the circuit.

o Check that this has worked by changing the Source neuron (at the top left of the

dialog) to 2. The threshold should be set to -55 mV, just like N1.

o Click OK to dismiss the Properties dialog.

Hold down the control key and drag the square box of stimulus 1 and drop it onto N2 in the

layout view.

This will duplicate stimulus 1 and attach the duplicate to N2.

In the Experimental Control panel, check that stimulus 2 is selected, and change its Delay to

15 ms

Click Start.

We now have spikes in both the sensory neurons, N1 and N2, and we can control their timing. So we

are now ready to set up coincidence detection.

Make the connections

Click Clear.

Select the Connexions: Add menu command.

The cursor changes to an up arrow, indicating that you can click on something.

Click on N1 and drag the line to N3.

When you release the cursor the Synaptic Connexion dialog opens.

o Note that one of the options is to set a synaptic Delay, but ignore this for now. Just

click OK to accept the defaults.

Repeat, dragging from N2 to N3, to make another connection.

At this point, the section of the layout view should look like this:

Click Start.

Two EPSPs are visible in the post-synaptic coincidence detector (trace 3, green). However, they are

quite small and rather long lasting. Even with 5 ms delay between the inputs, they show summation.

Select the Synapses: Spiking chemical menu command to open the Spiking Chemical

Synapse Types dialog.

There are a lot of options here, but we can ignore most of them.

o Set the Synaptic conductance to 0.5 to increase the strength of the EPSPs.

o Set the Decay rate to 1 ms to make the EPSPs briefer.

o Set the Relative facilitation to 1, so that the EPSP conductance change does not

depend on pre-synaptic spike frequency.

o Click OK to accept the entries and dismiss the Synapse dialog.

Double-click N3 to open the Properties dialog.

o Set the Leak conductance to 0.333 mS/cm2.

This will make the membrane of the sensory neuron a bit more leaky, thus

reducing the time constant, and also making the EPSPs a bit smaller.

The number is arbitrary – it was found by trial and error and works OK for

this simulation.

Click Start.

The EPSPs are larger and briefer, although there is still some summation. But we can now test

coincidence detection.

Select the Options: Run on change menu command.

Right-click the spin button associated with the stimulus Delay

o Set Delta to 1 in the Spin Control Properties dialog.

With stimulus 2 selected, click the down arrow on the Delay spin button.

Repeatedly click the down arrow to reduce the delay, until the delay to stimulus 2 is 5 ms.

Observe what happens to the EPSPs in the Results view.

We are now in a situation where the summation of two EPSPs that are coincident crosses threshold

and elicits a post-synaptic spike, but a 1 ms interval between the EPSPs in either direction fails to

cross threshold. This is a good basis for coincidence detection.

Click Clear.

Save the file as Jeff 3.

Generate a Pure-Tone Auditory Stimulus A brief pulse is an adequate representation of an auditory stimulus such as a click, but most stimuli

involve ongoing noise. Furthermore, primary auditory neurons are frequency-specific. So we will

change the stimulus to be more like a pure-tone sound.

We will apply a fairly low frequency sine-wave stimulus of 3 ms period (333 Hz) to the sensory

neurons. Auditory sensory neurons respond to such stimuli with spikes that are phase-locked to the

sine wave, but they do not spike on every cycle of the input. We want to reproduce this sort of

behaviour.

In the Stimulus group of the Experimental Control panel:

Select the Sine wave option from the stimulus choices.

Set the Amplitude to 0.87

This is a number found by trial-and-error to be suitable. We could find a “nicer” number,

but we would have to adjust other parameters such as threshold, so it is easier to just

use this.

Set the Period to 3.

Set the Delay to 4.

Click the Apply button.

This allows the current settings to be applied to multiple stimuli.

o Enter “1 2” in the Apply Stimulus Parameters dialog.

o Click OK.

This makes stimuli 1 and 2 identical.

Click Clear.

Set the Delay to Stimulus 2 to 5.5 ms.

The stimulus onset is now earlier in the left neuron than the right, indicating a sound

origin to the left of the midline

Click Start to see what happens.

o If you still have Run on change selected from the last activity, de-select it and click

Clear, then Start, to clean up the screen.

In the Results view you should see both sine wave stimuli in the lower trace, as red and blue lines.

They are in anti-phase with each other, because the difference in the delay times of the two stimuli

is 1.5 ms, which is exactly half the sine wave period.

N1 and N2 both fire a single spike at the onset of the stimulus, but are silent for several cycles after

that, and then spike again. This is because of the relative refractory period after the first spike. This

is a reasonable neural property, so we will leave it alone. Note that the EPSPs in N3 are not

coincident, and N3 does not spike.

In a real nervous system, all neurons and all stimuli have some noise associated with them. In fact,

noise is an essential feature of sensory systems that can actually improve their sensitivity (look up

stochastic resonance in sensory neurobiology if you want more information on this). So we will add

some noise to the sensory neurons.

Double-click N1 to open the Neuron Properties dialog.

Check the Tonic input box near the top right of the Properties dialog. The Tonic Input dialog

opens.

o Set the Noise to 0.5 mV.

This means that random number drawn from a uniform distribution in the

range -0.5 to +0.5 will be added to the membrane potential at each

integration step in the simulation.

[This is not a great method for adding noise in a simulation where strict

realism is required, since its effect depends on the integration time step

which is obviously not part of the biology. But it is fast, and adequate for our

purposes here.]

o Click Close to dismiss the Tonic Input dialog. It is a child of the Properties dialog, and

changes are automatically applied unless the Properties dialog is closed by

Cancelling.

Check the box just to the right of the Tonic input box.

Enter “1 2” into the Extended Apply list near the bottom of the Properties dialog.

Click Apply.

This will apply the membrane noise that you set for N1 to N2 as well.

Click OK to accept entries and dismiss the Properties dialog.

Check the Auto clear box near the top of the Results view.

Click Start several times.

Note that the membrane potentials of both N1 and N2 now shows some random variability, and

occasionally spikes occur on the peak of a sine wave. You will probably see 2 or 3 spikes in each 30

ms simulation run. This seems about right for a just supra-threshold auditory stimulus. Each spike in

either pre-synaptic neuron generates an EPSP in N3, but these are mainly subthreshold.

Save the file as Jeff 4.

At this stage we have two neurons (N1 and N2) that perform a reasonable simulation of auditory

afferents, and a working coincidence detector (N3). We now need to implement the delay lines of

the Jeffress mechanism.

Jeffress Mechanism We now need to create the coincidence detection layer: an array of neurons like just like N3 but with

synaptic delays from each ear that increase by 0.2 ms as you progress along the array (this choice is

somewhat arbitrary, but reasonable for this frequency). We will have 19 neurons in this layer in

total. We want an odd number so that there will be a central neuron in the array, which will be the

neuron that is activated best when the sound originates on the midline and arrives at both ears

simultaneously. And 19 is a large enough number to show what we are interested in for this model,

without being too unwieldly.

We could build the array by repeating the process described above for each extra neuron, but that

would be quite tedious.

First we want to expand the layout area horizontally to make sure that there is enough room for the

array.

Select View: Circuit area: Increase layout H. This adds some horizontal space.

Now we add the additional neurons.

Hold down the control key, and click-and-drag N3, releasing it on the next grid node on its

right.

This duplicates N3, including its synaptic connections. So we now have a new

neuron N4, which also gets synaptic input from the sensory neurons N1 and N2. The

input has the same delay (0 ms) as that to N3, but don’t worry about that. We can

adjust it later.

Click the layout screen above and to the left of N3, hold down the mouse button, and drag a

box around N3 and N4, releasing the mouse button below and to the right of N4. This

selects them both (they are drawn with a thicker outline to indicate their selected status).

Hold down the control key, and click-and-drag N3, releasing it on the next grid node to the

right of N4.

This duplicates both the selected neurons, so we now have 4 neurons in total.

Now draw the selection box around all 4 neurons, and again control-drag to make a total of

8.

Repeat to get 16 neurons.

Finally, unselect all neurons by clicking in the layout area away from any neuron, and draw

the selection box around just 3 neurons, and control-drag these to the end of the array.

You should now have 19 neurons in a line. You may want to move the array to make the layout more

accessible.

To move one or more neurons, draw the selection box around the target neurons, and drag

and drop them to their new location (do not control drag – that would duplicate them).

At this point your screen may look like this:

We have all the neurons we need, and we have them correctly connected to the sensory neurons,

BUT the synaptic delays are all 0.

The easiest way to adjust a lot of connections where there is a straightforward pattern is to do it

externally in a program like Excel.

Select the Connexions: Clipboard: Copy command.

Then Paste the data into a program like Excel (or even just Notepad).

The data should look like this:

Source Target Type ID Delay

1 3 1 a 0

2 3 1 a 0

1 4 1 a 0

2 4 1 a 0

1 5 1 a 0

2 5 1 a 0

Etc.

We want to replace the 0s in the Delay column with values which change by 0.2 ms between each

neuron in the array. This can be done in Excel by sorting by the Source column, and then replicating

values in the Delay column appropriately. You should end up with something like this:

Source Target Type ID Delay

1 3 1 a 0.2

1 4 1 a 0.4

1 5 1 a 0.6

1 6 1 a 0.8

1 7 1 a 1

1 8 1 a 1.2

1 9 1 a 1.4

1 10 1 a 1.6

1 11 1 a 1.8

1 12 1 a 2

1 13 1 a 2.2

1 14 1 a 2.4

1 15 1 a 2.6

1 16 1 a 2.8

1 17 1 a 3

1 18 1 a 3.2

1 19 1 a 3.4

1 20 1 a 3.6

1 21 1 a 3.8

2 3 1 a 3.8

2 4 1 a 3.6

2 5 1 a 3.4

2 6 1 a 3.2

2 7 1 a 3

2 8 1 a 2.8

2 9 1 a 2.6

2 10 1 a 2.4

2 11 1 a 2.2

2 12 1 a 2

2 13 1 a 1.8

2 14 1 a 1.6

2 15 1 a 1.4

2 16 1 a 1.2

2 17 1 a 1

2 18 1 a 0.8

2 19 1 a 0.6

2 20 1 a 0.4

2 21 1 a 0.2

Copy the data in the modified table (or use that above) to the clipboard.

In Neurosim, select the Connexions: Clipboard: Paste menu command.

o Click Yes when you are asked whether to delete existing connections. You want to

overwrite them all, so yes is appropriate.

At this point it would be wise to save the file as Jeff 5.

Check that connection delays are correct by double-clicking a few of the blue diamond

shapes indicating a synapse, and looking at the delay value in the Synaptic Connexion dialog.

WARNING: it is extremely easy to move a connection from one neuron to another

when they are overlaid as closely as they are in this circuit. To avoid this risk, you

may want to move (drag-and-drop) a neuron out of the array line, so that its

synapses are more easily isolated. You can move it back again once you have

checked it.

Final Touches Now it’s time to try it out.

Neurosim can display a maximum of 16 traces showing the membrane potentials of neurons, but in

this case we are really only interested in the occurrence of spikes. So we will use a spike only display.

In the Results view:

Set the time scale (right-hand X axis scale) to 2000

Select Scroll as the Trigger mode.

Select Spike vs Time as the Display mode.

Click the Traces button to show the Spike vs Time dialog.

o Enter “1-21” in the Neurons edit box.

This will divide the vertical axis into 21 sections, one for each neuron.

o Select the Dots option in the Markers group.

o Select the From Setup View option in the Colour choice group.

o Click OK.

Check the Spike frequency graph box in the Display mode to open the Spike Frequency

graph dialog. This can be kept open while the simulation runs.

o Enter “3 – 21” in the Neuron monitor list, to indicate which neurons to display in the

graph (we don’t want to include the sensory neurons).

Click Start.

The scrolling display shows a dot in the appropriate row every time the neuron for that row spikes.

The top two rows show a high density of red and blue dots, which are the sensory neuron spikes.

However, there is very little pattern to the remainder of the dots from the coincidence layer, which

is a bit disappointing.

However, the frequency graph shows only very low frequency activity.

In the Frequency graph, change the top scale of the bar-chart display to 2.

Now it is apparent that the frequency graph is not actually flat, so there is some pattern to the

activity. But the overall activity level is only about 1 Hz in each neuron, which is very low indeed.

We need to get more excitation into the coincidence layer.

Click Clear.

Double-click N3 to open the Neuron Properties dialog (again).

Set the Leak equilibrium potential to -58 mV. This will give the neuron a slightly depolarized

resting potential, which should increase its general level of excitability.

Check the box just to the right of the equilibrium parameter edit box.

Enter “4 – 21” into the Extended Apply list.

Click OK. This will apply the changes to make all the neurons in the coincidence layer have

the elevated resting potential, and close the dialog.

In the Spike Frequency graph, change the top scale of the bar-chart display to 30.

This is because we expect there to be a higher spike frequency after changing the

resting potential. We could make the change after the experiment, but it is nice to

watch the frequency change as the simulation runs.

Click Start in the Results view.

When the simulation ends, there is now a clear pattern to the coincidence layer activity in both the

Results view and the Frequency graphs. There are two peaks of activity, centred around N8 and N16.

This reflects the phase ambiguity that is evident in the Jeffress mechanism found in the owl nucleus

laminaris brainstem region. This ambiguity persists right through to the behavioural level when the

owl is given a pure-tone auditory stimulus, but disappears if the stimulus is white noise. The reasons

for this are explored further in the main Tutorial section.

As a final check, let’s make the sound come from a midline source.

In the Experimental Control panel Stimulus group, set the Delay for Stimulus 2 to 4 ms, i.e.

make it the same as stimulus 1.

Click Start.

The peaks in the Frequency graph are now in different locations. The two graphs are shown below

for comparison. They look very like published records of spike frequencies recorded from the

laminaris neurons in the owl when presented with pure-tone stimuli (e.g. Fig 12 in Carr and Konishi,

19901)

Click the cancel x at the top right of the Spike Frequency dialog or uncheck the Spike

frequency graph box in the Results view to close the graph dialog.

Annotations and Images It can be useful to add text annotations to the Setup view (or the Results view) to improve

comprehension.

Right-click the display near to N2.

Choose Add annotation from the context menu.

o Enter “left ear” in the edit box of the Annotation dialog.

o The text is a bit small, so click the Font button.

Select size 12 from the Font dialog

Click OK to dismiss the Font dialog.

o Click OK to dismiss the dialog.

Control-drag the text of the annotation over towards the right ear. The annotation

duplicates.

Double-click the duplicate annotation.

o In the Annotation dialog, and edit the text to read “right ear”.

o Click OK to close the dialog.

Another option on the context menu is to add an image. You have to have a suitable image,

obviously, but you can add it to the view, and it will be save with the file along with all the other

parameter settings.

Finally, save the file as Jeff 6.

1 Carr, C.E, Konishi, M. (1990) A circuit for detection of interaural time differences in the brain stem of the barn owl. J. Neurosci., 10, 3227-3246.