= Solution
An <action potential> is a brief regenerative change in a neuron's <membrane potential>, followed by repolarization and recovery. In a typical spiking neuron, depolarization recruits <voltage-gated ion channels>; inward current promotes further depolarization until inactivation and opposing currents terminate the event. The <neuronal refractory period> makes immediate repetition difficult or impossible. Once initiated, the roughly stereotyped event propagates along the <axon>. Its amplitude is therefore not generally the primary variable used to represent stimulus strength.
Inputs arriving at <synapses> on a <neuron> and its <dendrites> change membrane currents and produce graded voltage changes. Their spatial and temporal integration can trigger an <action potential>. At a chemical <synapse>, an arriving spike promotes release of a <neurotransmitter>, whose receptors alter the next neuron's conductances. Depending on the synapse and receptor mechanism, the input can promote or suppress the next neuron's firing. Thus information flows through activity patterns interacting with connectivity and synaptic dynamics, rather than by an identical voltage waveform simply passing unchanged across every cell.
In <rate coding>, a relevant response statistic is the number of spikes in a chosen interval, or the mean firing rate inferred from repeated trials or a population. For example, a sensory variable might be represented by mean counts of two versus five spikes in a $100$ ms window. A downstream neuron integrating many synaptic inputs over that window can distinguish the rates even if individual spike times vary. The window, averaging method and neuron's stimulus tuning must be specified; not every cell increases its rate for every stronger stimulus. <Neural adaptation> can also make the rate depend on recent stimulus history.
In <temporal coding>, precise times carry information beyond that count. Two responses containing the same number of spikes can differ in their first-spike latency after stimulus onset. Alternatively, spikes can lock to a particular phase of a periodic input, or relative timing across two neurons can encode coincidence. A decoder that reads only the long-window count discards those distinctions, whereas a temporally sensitive synapse or coincidence detector can use them.
\b[Rate coding uses a chosen frequency or count summary; temporal coding uses the arrangement of spike times relative to a reference.] They are complementary possibilities within <neural coding>, and a <spike train> can carry information in both. Stochastic variability does not prevent coding, but requires assessing how reliably different response distributions can be distinguished.
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