Conductance-Based Synapses
Spikes open synaptic channels, which change the voltage of an attached neuron.
Abstract
An arriving spike opens synaptic channels. Their conductance then decays, while current through them changes the receiving neuron's voltage. We use a simple animation to explore how synaptic weight, decay time and reversal potential shape this response, then combine excitatory and inhibitory inputs.
Introduction
A spike causes neurotransmitter release. The transmitter crosses the synaptic cleft and opens channels embedded in the receiving neuron’s membrane. We represent their combined conductance by , measured in nanosiemens (nS). Each arrival at time adds the synaptic weight ; between arrivals, conductance decays with time constant . Time and are in milliseconds (ms), and labels spikes. The Dirac impulse has unit area and units of inverse milliseconds; each impulse adds nS at arrival.[1]
Open channels carry current according to the difference between their reversal potential and the neuron’s voltage , both in millivolts (mV):
Here is in picoamperes (pA), positive when it raises voltage. Above , reversal potential makes the current depolarising; below it, hyperpolarising. At equality, net current is zero even with open channels. This sign convention is opposite to the outward-positive convention in reference [1].
Between output spikes, the receiving neuron also leaks towards its resting voltage :
is membrane capacitance, set to 100 picofarads (pF); is leak conductance, set to 10 nS; and mV. A leaky integrate-and-fire rule adds output spikes: reaching the threshold mV emits a spike and resets voltage to mV. There is no refractory interval.[2]
Explore the synapse
Increase Weight to open more channels, or Decay to keep them open longer. Move Reversal above or below −65 mV to raise or lower the neuron’s voltage. At −65 mV, channels still open but the neuron stays at rest. Reversal potential changes the voltage response, not the conductance trace. The default weight of 8 nS produces output spikes; the voltage trace reaches threshold and resets.
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Excitatory and inhibitory inputs
Two presynaptic neurons now feed the receiving neuron: E supplies excitation and I supplies inhibition. Each has its own conductance, or , and nonnegative synaptic weight, or , all in nS. Their conductances obey the same decay-and-arrival rule:
labels the input, its spike arrival times, and its decay time in ms. Here ms and ms. Both currents act on the same membrane voltage:
and are the two reversal potentials, adjustable in Figure 2 and initially set to 0 and −75 mV; capacitance, leak and rest retain their values from equation (3). These are illustrative settings. The two channel symbols represent two distinct conductance components, each combining the physical channels activated by its input.[1]
Increase Weight to strengthen excitation, or Weight to strengthen inhibition. Set either to zero to remove its current. At its default reversal, the inhibitory conductance pulls voltage towards −75 mV and can suppress output spikes. Inhibition therefore uses a positive conductance with a different reversal potential, rather than a negative weight. The default weights are nS and nS, which allow the receiving neuron to fire. Its threshold and reset follow equation (4). Changing can change the polarity of the I-pathway current: it becomes depolarising when .
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Parameters
| Parameter | Illustrative setting |
|---|---|
| Neurons | |
| Membrane capacitance | 100 pF |
| Leak conductance | 10 nS |
| Rest / reset / threshold | -65 / -65 / -50 mV |
| Passive time constant (derived) | 10 ms |
| Refractory interval | None |
| Synapses and weights | |
| Single-input initial weight / decay / reversal | 8 nS / 12 ms / 0 mV |
| Dual E / I initial weights | 8 / 4 nS |
| Dual E / I decay times | 12 / 20 ms |
| Dual E / I initial reversals | 0 / −75 mV |
| Input and simulation | |
| Timestep / schematic delay | 0.25 / 8 ms |
| Prescribed single-input spike interval | 30 ms |
| Membrane update | Exact passive update with conductances held constant during the step |
| Conductance update | Exponential decay and event increments |
These are browser-model choices, not fitted values or run evidence. Membrane and timing constants are imported from the same script as the animation; slider defaults are the authored initial settings. Sliders change the live state. The passive time constant is capacitance divided by leak conductance.
References
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Wulfram Gerstner, Werner M. Kistler, Richard Naud and Liam Paninski. Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition. Cambridge University Press, 2014. Chapter 3.1, “Synapses”.
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Wulfram Gerstner, Werner M. Kistler, Richard Naud and Liam Paninski. Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition. Cambridge University Press, 2014. Chapter 1.3, “Integrate-And-Fire Models”.