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<?xml version="1.0" encoding="UTF-8"?>

    This example shows a Level 3 compliant file, containing a number of connected cell models  

<neuroml xmlns=""  


<meta:notes>A completely specified network in NeuroML Level 3. While this is useful for
    exporting/importing/saving from an application, better practice might be to have the cell
    definitions, the channel mechanisms, and network specification in separate files.

<!-- The cell types present in the network-->
<cell name="CellA">
<meta:notes>Test cell for showing how channels can be placed on a cell</meta:notes>
<segments xmlns="">
<segment id ="0" name="Soma"  cable="0">
<proximal x="0" y="0" z="0" diameter="10"/>
<distal x="10" y="0" z="0" diameter="10"/>
<segment id ="1" name="Dendrite" parent="0" cable="1">
<proximal x="10" y="0" z="0" diameter="3"/>
<distal x="20" y="0" z="0" diameter="3"/>

<cables xmlns="">
<cable id="0" name="SomaCable">
<cable id="1" name="DendriteCable">
<biophysics  units="Physiological Units" >  
<bio:mechanism name="pas"  type="Channel Mechanism">
<bio:parameter name="gmax" value="0.0330033">
<bio:parameter value="1.0">
<bio:parameter value="0.1">
<!-- Note: this doesn't need to be specified in the network instance case,
                 but would be used when generating connections in the network template scenario. Can be
                 used to limit connections of a particular type to, say, apical dendrites -->

<net:potential_syn_loc synapse_type="DoubExpSynA" synapse_direction="preAndOrPost">
<net:potential_syn_loc synapse_type="DoubExpSynA" synapse_direction="post">
<!-- The biophysical mechanisms present in the network-->
<channels units="Physiological Units">

<channel_type name="pas" density="yes"   xmlns="">
<meta:notes>Simple example of a leak/passive conductance.</meta:notes>
<current_voltage_relation cond_law="ohmic" ion="non_specific" default_erev="-54.3" default_gmax="0.3"/>
<synapse_type name="DoubExpSynA"  xmlns="">
<doub_exp_syn max_conductance="1.0E-5" rise_time="1" decay_time="2" reversal_potential="0"/>

<!-- The cell populations present in the network-->

<populations  xmlns="">
<population name="CellGroupA" cell_type="CellA">
<instances size="3">
<instance id="0"><location x="0" y="0" z="0"/></instance>
<instance id="1"><location x="50" y="0" z="0"/></instance>
<instance id="2"><location x="100" y="0" z="0"/></instance>
<population name="CellGroupB" cell_type="CellA">
<instances size="2">
<instance id="0"><location x="0" y="100" z="0"/></instance>
<instance id="1"><location x="50" y="100" z="0"/></instance>
<!-- The projections between populations in the network-->
<projections units="Physiological Units" xmlns="">
<projection name="NetworkConnection" source="CellGroupA" target="CellGroupB">
<synapse_props synapse_type="DoubExpSynA" internal_delay="5" weight="1" threshold="-20"/>
<connections size="3">
<connection id="0" pre_cell_id="0" pre_segment_id = "0" pre_fraction_along="0.5" post_cell_id="1" post_segment_id = "1"/>
<connection id="1" pre_cell_id="2" pre_segment_id = "0" post_cell_id="0" post_segment_id = "0"/>
<connection id="2" pre_cell_id="1" pre_segment_id = "0" post_cell_id="1" post_segment_id = "1">
<properties internal_delay="10" weight="0.5"/>       <!-- adjusted value -->
<!-- The electrical inputs to the cells in the network -->
<inputs units="SI Units" xmlns="">
<input name="RandomInputLow">
<random_stim frequency="20" synaptic_mechanism="DoubExpSynA" />
<target population="CellGroupA">
<sites size="2">
<site cell_id="1" />    
<site cell_id="2"  segment_id = "1"/>  
<input name="RandomInputHigh">
<random_stim frequency="100" synaptic_mechanism="DoubExpSynA" />
<target population="CellGroupA">
<sites size="1">
<site cell_id="0" />