On the Relation between Bursts and Dynamic Synapse Properties: A Modulation-Based Ansatz

<table>Time course of <svg height="15.0875" id="M69" style="vertical-align:-2.3205pt" version="1.1" viewbox="0 0 26.825001 15.0875" width="26.825001" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg> and convergence limits <svg height="11.9625" id="M71" style="vertical-align:-3.39069pt" version="1.1" viewbox="0 0 14.925 11.9625" width="14.925" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg> for high and low pulse rates <svg height="16.3125" id="M72" style="vertical-align:-3.27605pt" version="1.1" viewbox="0 0 15.8375 16.3125" width="15.8375" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg> and <svg height="16.3125" id="M73" style="vertical-align:-3.27605pt" version="1.1" viewbox="0 0 15.8375 16.3125" width="15.8375" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg>, respectively. <svg height="12.4375" id="M74" style="vertical-align:-0.1638pt" version="1.1" viewbox="0 0 47.712502 12.4375" width="47.712502" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg> in this example.</table>

Computational Intelligence and Neuroscience

fig4

Figure 4

Figure 4: On the Relation between Bursts and Dynamic Synapse Properties: A Modulation-Based Ansatz 