Neuron

A neuron is a specialized biological cell that receives, integrates and transmits signals. Its shape separates places where inputs arrive from places where outputs reach other biological cells: this functional asymmetry is neuronal polarity. Understanding a neuron therefore means connecting its anatomy to changes in membrane potential, rather than treating it as a wire that merely forwards every input.

In a common multipolar neuron, branching dendrites receive inputs at synapses; the soma contains the cell nucleus and most major organelles; the axon carries signals to distant or nearby targets; and axon terminals form output contacts. All these regions belong to one biological cell enclosed by a continuous cell membrane. An axon can branch, allowing one neuron to influence several receiving biological cells.^[ref]

At an input chemical synapse, a neurotransmitter acts on a receptor, changing an electric current directly or through signal transduction.^[ref] A resulting synaptic potential contributes to synaptic integration in the dendrites and soma. In many spiking neurons, sufficiently strong depolarization recruits voltage-gated ion channels in the axon initial segment, initiating an action potential that propagates along the axon. At an output chemical synapse, calcium entry through voltage-gated ion channels promotes synaptic vesicle exocytosis, releasing neurotransmitter. An action potential is thus regenerated electrically along a cell membrane; it is not a packet of neurotransmitter travelling from the dendrites to the axon terminals.^[ref]

The compartments are specializations, not exclusive jobs. Inputs can contact the soma or axon as well as dendrites; dendrites can support active voltage-gated ion channels. Paired recordings from a pyramidal neuron's soma and dendrite or axon established that an action potential can begin in the axon and propagate back into the dendrites. The usual output direction therefore does not make every electrical signal strictly one-way.^[ref] An electrical synapse, which directly couples cytoplasms through gap junctions, also differs from the sending-and-receiving arrangement of a chemical synapse.^[ref]

Nor does every neuron have the upper diagram's shape. A bipolar neuron has two main processes, one dendrite and one axon; a multipolar neuron has several dendrites; and a pseudounipolar neuron has a single process from the soma that divides into peripheral and central branches. In the last arrangement, sensory signals can travel past the soma rather than obligatorily through it. These shape categories do not specify every neuron's receptor, connectivity or firing behavior.^[ref] Some neurons in the retina communicate through graded changes in membrane potential without generating action potentials.^[ref]

Why timing changes the computation. Synaptic integration can combine inputs at different locations, called spatial summation, and inputs arriving at different times, called temporal summation. A minimal example uses the leaky integrate-and-fire model with the illustrative parameters already given there: resting and reset membrane potential $-65\mathrm{mV}$, firing threshold $-50\mathrm{mV}$, electrical resistance $R=100\mathrm{M\Omega }$, capacitance $C=200\mathrm{pF}$, time constant $\tau =RC=20\mathrm{ms}$ and neuronal refractory period $2\mathrm{ms}$. These are chosen model values, not measured properties of a particular neuron. Before firing, a constant inward electric current $I$ starting from rest givesThe exponential function expresses the competition between charging the cell membrane's capacitance and leakage through its electrical resistance.^[ref]

Two $100\mathrm{pA}$ inputs, each lasting $40\mathrm{ms}$, produce different outputs depending on their timing. Either input alone reaches only $-56.3534\mathrm{mV}$. Applied together, they give $I=200\mathrm{pA}$ and reach threshold after $20\ln 4\mathrm{ms}\approx 27.7259\mathrm{ms}$, producing one action potential event during the pulse. If instead the second input begins $20\mathrm{ms}$ after the first ends, the earlier depolarization has partly decayed: the second pulse peaks at approximately $-55.9229\mathrm{mV}$ and neither pulse produces an action potential. The two-input protocols deliver the same total electric charge, $8\mathrm{pC}$, yet only the coincident protocol fires. Counting total input alone misses this timing dependence.

This example makes a neuron a detector of sufficiently clustered input, not a perfect logical gate: different parameters change the result. Actual dendrites introduce location-dependent filtering and active responses, and an inhibitory postsynaptic potential or shunting inhibition can change whether another input succeeds. The single-compartment leaky integrate-and-fire model omits these mechanisms.^[ref] Across connected neurons, branching axons distribute outputs while converging synapses combine inputs; spike trains can support temporal coding and rate coding, and synaptic plasticity changes the influence of an input. Connectivity and cellular dynamics together determine the computation.^[ref][ref]

Testing the connection between structure and function. Whole-cell recording connects anatomy to a measured membrane potential. In a published mouse protocol, a two-photon microscope guides solution-filled glass pipettes to neurons; an amplifier and bath reference electrode complete the electrical recording apparatus. A high-resistance seal forms against the cell membrane, then brief suction opens the membrane patch beneath the tip. In current clamp, the amplifier supplies a chosen electric current and records the resulting membrane potential, unlike voltage clamp, which controls voltage and measures electric current. The investigators used $500\mathrm{ms}$ current steps of several amplitudes to characterize excitability and firing, and negative current pulses to estimate input electrical resistance.^[ref]

The observable is a voltage trace, including graded responses and action potentials. Comparing injected electric current with that trace tests how input becomes output; it does not identify every underlying ion channel. The protocol checks access electrical resistance, which can distort voltage and action potential measurements, and includes intervals without stimulation to record spontaneous activity. In a teaching replication, repeated zero-input trials and monitoring baseline drift would provide further controls; these are recommended comparisons, not additional results attributed to the paper. A recording at the soma also cannot establish the local voltage everywhere in a branching dendrite, and this anesthetized preparation does not establish behavior in every awake neuron.^[ref]

A complementary experiment used simultaneous whole-cell recordings from the soma and an apical dendrite or axon of the same pyramidal neuron in a brain slice. The relative onset times of action potentials, together with sodium currents in excised dendrite membrane patches, supported axonal initiation followed by active propagation into dendrites. Pairing sites within one neuron is a useful comparison because it avoids confusing differences between cells with differences between compartments. Instrument timing and comparable recording quality would be essential controls when reproducing the inference. Only the published abstract was accessible here, so no unverified timing values, drug controls or channel distributions are supplied.^[ref]

A neuron whose recorded activity has related selectivity during action execution and observation. This response property does not by itself identify the neuron’s necessary behavioural function or its developmental origin.

A retinal interneuron contributing diverse temporal, inhibitory and other interactions in inner retinal circuits.

A retinal interneuron contributing lateral interactions among photoreceptor signals and spatial context. Its participation in a circuit does not imply that every perceptual surround effect originates at that one cell type.

A retinal interneuron relaying photoreceptor signals toward ganglion-cell circuits. ON and OFF types differ in how changes in photoreceptor output affect their responses.

Parallel retinal pathways emphasizing increments and decrements in stimulation. Their sign differences depend on synaptic transformations of photoreceptor output; an ON pathway is not simply a photoreceptor that depolarizes to light.

A retinal output neuron conveying information through action potentials. Its responses reflect inputs transformed by retinal circuitry rather than a direct copy of one cone voltage.

A retinal ganglion-cell type with dendrites in two strata, identified with an S-ON opponent pathway in primates. Anatomy and physiology together establish a distinct route for S-cone signals; the traditional blue-on label does not equate its discharge with unique blue experience.

A retinal ganglion-cell type whose central retinal circuitry can support fine spatial sampling and cone-opponent responses. Functional spatial and chromatic roles need not correspond to entirely separate anatomical channels.

A small neuron found in several brain regions. Cerebellar granule cells supply parallel fibers; dentate granule cells participate in sparse hippocampal input coding. These are anatomically distinct populations, so a shared descriptive name does not imply an identical circuit role.

Named for Jan Evangelista Purkyně, a cerebellar neuron receiving many parallel fiber inputs and a powerful climbing fiber input. Simple-spike and complex-spike responses provide distinct physiological readouts in studies of motor learning.

Synaptic integration is the conversion of inputs at a neuron's synapses into a changing membrane potential and, in a spiking neuron, the timing or absence of action potentials. Spatial summation concerns inputs at different locations; temporal summation concerns inputs at different times. A useful question is whether individually ineffective inputs can act together, and whether an inhibitory postsynaptic potential changes that cooperation. The answer depends on location, timing and the receiving neuron's state.

A synaptic potential is a voltage response, whereas synaptic conductance describes activated ion channels. With inward-positive electric current, the contribution of input $j$ isHere $g_j$ is its synaptic conductance, $E_j$ its reversal potential and $V$ the local membrane potential. The driving force $E_j-V$ is an electric potential difference. An EPSP generally brings the membrane potential toward a more positive reversal potential, but its driving force shrinks during depolarization. An IPSP need not produce hyperpolarization: a reversal potential above rest but below the neuronal firing threshold can produce depolarization while opposing a larger excursion. At $E_j=V$, the added synaptic conductance initially carries zero electric current yet can cause shunting inhibition of another input.^[ref]

Two distinct nonlinearities matter. Even a passive cell membrane can show sublinear synaptic integration when added synaptic conductances reduce driving force and effective electrical resistance. Active voltage-gated ion channels and NMDA receptors can instead amplify sufficiently concentrated inputs and produce a dendritic spike. Neither summing prescribed electric currents nor adding separate measured EPSPs is an exact universal rule for a branching neuron.^[ref]

Spatial summation combines inputs arriving at different synapses. Location matters because a dendrite has axial electrical resistance and leaky membrane capacitance: a local synaptic potential need not arrive at the soma with its original amplitude or time course. A passive dendritic cable makes this attenuation explicit. The superposition principle applies to fixed electric current inputs in a linear passive model, but adding synaptic conductances changes the model's coefficients. Compare voltage changes relative to the same baseline, rather than adding absolute membrane potentials.

A motivating experiment. A 2004 study used $300$–$350\mu \mathrm{m}$ cortical slices from $18$–$28$-day-old rats at $35$–$36{}^{\circ }\mathrm{C}$. Somatic whole-cell recordings measured EPSPs in layer-5 pyramidal neurons. Two fine stimulating electrodes were positioned beside imaged dendrites; calcium-sensitive dye localized activation. Each site was stimulated alone, then both together, usually with paired pulses $20\mathrm{ms}$ apart. Comparing the combined voltage trace with the sum of individual changes tested the summation rule. Nearby inputs on one branch showed strong amplification at intermediate strengths; inputs on different branches were approximately linear.^[ref]

Blocking both excitatory receptor classes eliminated voltage and calcium responses, checking against direct electrical activation. NMDA receptor blockers eliminated or markedly reduced amplification; comparisons with inhibition intact and blocked addressed inhibitory contributions. These controls support local active integration. Passing axons could still recruit unintended synapses; somatic voltage does not measure every local membrane potential. The study tested subthreshold slice responses and pairs of branches, not arbitrary activity in an intact brain.^[ref]

A passive dendritic cable models a uniform dendrite with axial electrical resistance, membrane leak and membrane capacitance, excluding active ion channels. Let $r_a$ be axial electrical resistance per length, $r_m$ membrane electrical resistance times length, and $c_m$ membrane capacitance per length. For voltage deviation $v=V-E_L$ from the leak reversal potential, electric charge conservation gives the partial differential equation$i$ is imposed inward electric current per length. Units are $r_a:\Omega /\mathrm{m}$, $r_m:\Omega \mathrm{m}$ and $c_m:\mathrm{F}/\mathrm{m}$, so ${\tau }_m$ is a time and $\lambda$ a length. On a source-free semi-infinite cable with imposed $v(0)=v_0$ and $v(x)\to 0$ as $x\to \infty$, the steady state isDifferentiate twice to verify the ordinary differential equation ${\lambda }^2{v}^{\prime \prime }-v=0$. At $x=\lambda$, the amplitude is $e^{-1}\approx 0.368$ of the boundary amplitude. This is a stationary attenuation law, not the complete waveform of a brief EPSP. Transient passive spread also broadens and delays responses. Finite ends, branch points and the soma's load alter the solution; distance alone cannot specify every real synaptic potential.^[ref]

The spatial panel uses two compartments with membrane potentials $V_s,V_d$, one representing the soma and one a dendrite. Set $v_s=V_s-E_L$, $v_d=V_d-E_L$, with leak reversal potential $E_L=-65\mathrm{mV}$, each membrane capacitance $C=100\mathrm{pF}$, each leak electrical conductance $g_L=5\mathrm{nS}$ and axial electrical conductance $g_c=10\mathrm{nS}$. Electric charge conservation givesThis chosen passive model has two decay time constants, $C/g_L=20\mathrm{ms}$ for the equal-voltage mode and $C/(g_L+2g_c)=4\mathrm{ms}$ for the voltage-difference mode. Starting from rest, a $100\mathrm{pA}$ step into the soma gives, with $u$ the time since onset,while the same step into the dendrite gives$u$ is expressed in $\mathrm{ms}$. Their long-time rises are $12$ and $8\mathrm{mV}$ respectively. Applying both inputs gives $20(1-e^{-u/20})\mathrm{mV}$ exactly: spatial attenuation coexists with linear summation of prescribed electric currents. After the steps end, both modes decay with their respective time constants. This deliberately coarse model is not a reconstructed dendrite or a fit to the experiment above.

The conductance panels use the existing one-compartment synaptic potential equation, with $C=200\mathrm{pF}$, $g_L=10\mathrm{nS}$, $E_L=-65\mathrm{mV}$ and excitatory reversal potential $E_e=0\mathrm{mV}$. For a constant excitatory synaptic conductance $g_e$, the steady state voltage rise and membrane time constant areEach isolated $2\mathrm{nS}$ input has a limiting rise $130/12\approx 10.833\mathrm{mV}$. Adding those isolated rises predicts $21.667\mathrm{mV}$, but opening both together gives $260/14\approx 18.571\mathrm{mV}$. The two conductances share a changing driving force. This is sublinear input summation even though the voltage ordinary differential equation is linear for each prescribed conductance waveform.

Add $g_i=20\mathrm{nS}$ with reversal potential $E_i=E_L$ to the joint $4\mathrm{nS}$ excitation. The limiting rise becomes $260/34\approx 7.647\mathrm{mV}$ and the membrane time constant becomes $200/34\approx 5.882\mathrm{ms}$. The shunt alone leaves rest unchanged. At the joint-excitation-only steady state $V\approx -46.429\mathrm{mV}$, however, its inward electric current would be $20(-65+46.429)\approx -371.429\mathrm{pA}$: it opposes that excursion. The finite $50\mathrm{ms}$ traces in the diagram approach, but need not reach, these limiting voltages. See shunting inhibition for the constant-electric current comparison.

Temporal summation is overlap of responses to inputs arriving at different times. It can occur at one repeatedly activated synapse or across several synapses; it is not defined by reuse of a particular contact. For prescribed electric current inputs in a passive compartment, residual depolarization from earlier pulses changes the voltage reached by later pulses. The membrane time constant sets how rapidly that residual decays, while the duration of synaptic conductance and spatial filtering by a passive dendritic cable can add other timescales.

For the diagram, write $v=V-E_L$, choose inward-positive imposed electric current $I$, and use the ordinary differential equationA rectangular pulse of amplitude $I_0=300\mathrm{pA}$ and duration $d=5\mathrm{ms}$, starting from rest, ends withAfterwards its contribution decays as $A{e}^{-(t-d)/{\tau }_m}$. The superposition principle therefore gives, at the end of the third pulse with onset spacing $\Delta \ge d$,For $\Delta =5\mathrm{ms}$ this is $15.829\mathrm{mV}$, so the peak membrane potential is $-49.171\mathrm{mV}$. For $\Delta =30\mathrm{ms}$ it is $8.447\mathrm{mV}$, giving $-56.553\mathrm{mV}$. Both protocols inject $3I_{0}d=4.5\mathrm{pC}$ of electric charge; equal charge does not imply equal peak voltage because the leak drains charge while it is delivered.

In the adjacent-pulse case, the illustrative neuronal firing threshold $-50\mathrm{mV}$ is crossed at $10+20\log 2\approx 23.863\mathrm{ms}$. A leaky integrate-and-fire model would emit its first event there and reset, so its later trajectory would differ from the passive diagram. The widely spaced train never reaches that threshold. Thus changing input timing alone can change whether an event occurs. A real neuron's neuronal firing threshold is also state-dependent, and synaptic conductance pulses are not prescribed electric current pulses.^[ref]

Measured responses to repeated presynaptic action potentials may also change through synaptic plasticity. A larger second response can therefore reflect a stronger second input as well as residual postsynaptic voltage. To isolate passive temporal summation, compare known injected electric current waveforms with their single-pulse responses under stable recording conditions; to test actual synapses, measure whether input efficacy changes. These are proposed discriminating comparisons, not additional controls claimed for the slice experiment.^[ref]

The membrane time constant of a passive uniform compartment is its membrane capacitance $C$ divided by its total fixed electrical conductance $G$. After input removal, voltage deviation from the relevant equilibrium undergoes exponential decay; in one membrane time constant it falls to $e^{-1}$ of its initial value. For leak alone, $G=g_L$; while fixed synaptic conductances are open, $G=g_L+{\sum }_j{g}_j$. Thus shunting inhibition can both reduce voltage responses and shorten the integration window. This is a local passive timescale: a branching dendrite can have several decay modes, and a time-varying synaptic conductance need not admit one constant ${\tau }_m$.

A neuronal firing threshold specifies the condition for initiating an action potential. The leaky integrate-and-fire model uses a prescribed membrane potential $\vartheta$; real initiation involves active voltage-gated ion channels and depends on recent activity and recording site. A threshold drawn on a passive voltage trace is a comparison criterion, not a simulated action potential.

A dendritic spike is a regenerative local voltage event in a dendrite. Its effect at the soma depends on propagation and attenuation; local regeneration does not by itself establish a somatic action potential. It is an active mechanism beyond the passive dendritic cable.

An NMDA receptor is an ionotropic receptor gating an ion channel with voltage-dependent magnesium block. This voltage dependence permits cooperative amplification when inputs produce sufficient local depolarization; calcium can also pass through the open channel.^[ref]

Changes in responsiveness during sustained or repeated input. Adaptation makes activity depend on recent stimulation and can invalidate a model whose rate depends only on the present stimulus.

Changes in visual response associated with prevailing light input. Receptor gain, later neural gain and appearance reference points can adjust on different timescales; threshold loss is not automatically tissue damage.

Adjustment of visual responses to the spectral statistics of prevailing stimulation. Changes in gain or reference levels can partially stabilize color judgments despite different illumination or receptor signals. Adaptation is an explanatory mechanism to test; similarity on a color test does not uniquely identify its neural implementation.

A diagonal model applying gains $g_j$ to cone signals. If a change transforms every relevant catch as $Q_j\mapsto k_j{Q}_j$, gains $g_j\mapsto g_j/k_j$ preserve the normalized outputs exactly. A general illuminant change need not produce the same channelwise factors for every surface, so exact cancellation is conditional.

Changes following exposure to variation around a mean color or luminance. Holding the mean input fixed helps distinguish adaptation to variation from a simple account based on changed average cone catch, while receptor nonlinearities and task factors still require controls.

A synapse is a signaling junction between a neuron and another biological cell. The sending side is presynaptic and the receiving side postsynaptic. At a chemical synapse, released neurotransmitter acts on a receptor in the receiving cell membrane. At an electrical synapse, gap junctions provide a direct path for electric current between cells. See 1.1 Elements of Neuronal Systems.

In a common sequence at a chemical synapse, an arriving action potential opens voltage-gated ion channels selective for calcium. Calcium entry triggers fusion of synaptic vesicles with the presynaptic cell membrane, releasing neurotransmitter into the synaptic cleft. Binding to a receptor changes postsynaptic electrical resistance and conductance, directly through an ion channel or through an intracellular signaling pathway. The resulting change in membrane potential is a synaptic potential. See Ion Channels and the Electrical Properties of Membranes.

A useful conductance approximation writes the inward-positive synaptic electric current aswhere $g_{\mathrm{syn}}\ge 0$ describes the activated electrical resistance and conductance, $V$ is the postsynaptic membrane potential, and $E_{\mathrm{syn}}$ is the reversal potential, the voltage at which this current vanishes. Opening these channels tends to pull $V$ toward $E_{\mathrm{syn}}$; it does not prescribe a current of fixed sign independently of $V$.

For a worked example, let $V=-65\mathrm{mV}$ and $g_{\mathrm{syn}}=1\mathrm{nS}$. A reversal potential of $0\mathrm{mV}$ gives $I_{\mathrm{syn}}=65\mathrm{pA}$, an inward electric current that raises membrane potential. A reversal potential of $-75\mathrm{mV}$ instead gives $-10\mathrm{pA}$, which lowers membrane potential. These are illustrative calculations, not measurements. A reversal potential of $-60\mathrm{mV}$ can raise $V$ from $-65\mathrm{mV}$ yet oppose reaching a threshold of $-50\mathrm{mV}$: a depolarizing input need not be excitatory.

An excitatory synapse favors a subsequent action potential, whereas an inhibitory synapse opposes it. The effect depends on the receptor, the permeating ions, their gradients and the reversal potential; a neurotransmitter does not have one fixed excitatory or inhibitory sign in every context. Even with $E_{\mathrm{syn}}=V$, an added conductance can reduce responses to other inputs by lowering effective electrical resistance, an effect called shunting inhibition. See Purves and colleagues: excitatory and inhibitory postsynaptic potentials. This dependence matters when translating a biological synapse into a signed weight or an imposed electric current in computational neuroscience.

Changes in synaptic efficacy over time. Activity-dependent plasticity can support learning and development, but also requires constraints to prevent unbounded growth or competition in simplified models.

A decaying record of recent activity that marks a state or connection as eligible for modification by a later teaching signal. An accumulating value-learning trace is $e_t=\gamma \lambda e_{t-1}+x(s_t)$, giving $\Delta w=\alpha {\delta }_t{e}_t$. Other traces record action-policy gradients or pre/post synaptic events. The update and episode-boundary convention must be specified; an eligibility trace is not automatically identical to the visual activity trace used for trace learning.

A persistent increase in synaptic efficacy induced by an appropriate pattern of activity. Its presence is a possible storage mechanism; a memory model must still explain which inputs are modified, the learning conditions and how subsequent activity retrieves the stored information.

Short-lived changes in synaptic efficacy dependent on recent activity, including facilitation and depression. Such changes can alter a network's response to a later input even when its immediately recorded activity does not reveal the retained information.

Constraints or interactions make the strengthening of some inputs limit others. In developmental models, competition together with input correlations can segregate ON and OFF subregions or inputs from the two eyes; correlations alone do not specify the full biological developmental mechanism.

A learning rule can constrain the sum or norm of incoming synaptic weights to prevent unbounded Hebbian learning. For ${\sum }_i{w}_{ai}=S$, subtracting the mean unconstrained update from each update preserves the sum. Bounds and renormalization may also be needed to keep excitatory weights nonnegative. Normalization of learning weights is distinct from divisive gain control in instantaneous neural responses.

A chemical signal released by a neuron that changes a target cell's activity through its receptors. Its effect depends on the receptor and ionic mechanism rather than being intrinsically excitatory or inhibitory in every context.

A peptide used in neural signalling. Release, receptor distribution and interactions with other transmitters affect its function.

A peptide signal involved in endocrine and neural stress regulation. Its actions within a defined local circuit need not match a whole-organism hormone concentration.

A major transmitter commonly associated with inhibitory signalling through appropriate receptors. Its cellular effect depends on receptor and ionic conditions; suppressing an inhibitory neuron can disinhibit its targets.

Regulation of neural processing by chemical signals that can alter excitability, plasticity, gain or network state. Effects depend on receptor, target and timescale rather than only transmitter identity.

Observations establish what signals naturally covary with defined events; interventions estimate consequences of changing a specified target. Convergence requires matching cell population, projection, timescale and behavioural endpoint, with direct target engagement measurements and controls for off-target drug effects.

A signal acting in neuromodulation. The same molecule can have different functions at different receptors and targets; the label does not imply slow action or a single diffuse behavioural purpose.

A catecholamine transmitter involved in arousal, attention and other state-dependent functions, also called noradrenaline.

A monoamine transmitter also called 5-hydroxytryptamine. Distinct receptors and circuits can have different effects; blood levels are not a direct reading of synaptic transmission in the brain.

A neurotransmitter involved in multiple neural functions. Some phasic dopamine-neuron responses are consistent with reward-prediction-error signalling, and timed interventions can affect learning. This does not mean that every dopamine neuron or every timescale carries one identical scalar error.^[ref]

A subtype of receptor for dopamine involved in neural signalling and targeted by many antipsychotic medications. Receptor blockade is a pharmacological action, not a complete psychological description of treatment response.

Acetylcholine is a neurotransmitter that acts through nicotinic ionotropic receptors and muscarinic metabotropic receptors. The receptor and the target cell's machinery determine the response; acetylcholine itself does not specify whether coupling is direct or mediated by intracellular signal transduction. ^[ref]

A chemical synapse transmits a signal by releasing neurotransmitter from a presynaptic neuron to act on postsynaptic receptors across a synaptic cleft. The two cell membranes remain separate. A typical fast transmission sequence is:

See Chemical Synapses and 3.1 Synapses. The fast pathway uses synaptic vesicles prepared near release sites; it does not require a distant synaptic vesicle to travel across the terminal after every action potential. See Basic Neurochemistry: calcium entry and vesicles at release sites. Some chemical synapses release neurotransmitter in response to graded presynaptic membrane potential changes rather than action potentials.

Neurotransmitter clearance limits how long released neurotransmitter remains available. Depending on the neurotransmitter and location, diffusion away, uptake through membrane transport proteins into the sending or neighboring biological cells, and breakdown by enzymes contribute. Receptor binding and unbinding also affect response duration. Recovering synaptic vesicle membrane is a separate recycling task; uptake of released neurotransmitter is not the return of an intact synaptic vesicle. See General Principles of Cell Communication.

This electrical-to-chemical-to-electrical sequence offers several places to adjust a signal: synaptic release probability, receptor availability and neurotransmitter clearance can change its strength or duration. It helps explain why synaptic plasticity can modify communication between neurons, and why an arriving action potential need not cause a postsynaptic action potential.

Otto Loewi's 1936 Nobel lecture describes his 1921 experiment: fluid from a frog heart whose nerves had been stimulated produced the corresponding response when transferred to another heart. The transferable substance established chemical mediation in that preparation. This was evidence for released chemical signaling, not yet an identification of synaptic vesicle fusion and not a claim that every synapse is chemical. See Loewi, The Chemical Transmission of Nerve Action, Nobel lecture, 12 December 1936.

Release or signalling by more than one transmitter from a neuron or pathway. Manipulating a cell identified by one transmitter can therefore change other signals as well.

Neurotransmitter clearance removes released neurotransmitter from the region where it can activate receptors, through diffusion, cellular uptake or enzyme-mediated breakdown. Its routes and rates help delimit a chemical synapse's response in space and time; see the mechanisms and source under chemical synapse.

The synaptic cleft is the extracellular gap between the sending and receiving cell membranes of a chemical synapse. Released neurotransmitter crosses this gap to reach a receptor. ^[ref]

A synaptic vesicle is a small membrane-bounded compartment in a presynaptic terminal that stores neurotransmitter for release. Fusion with the cell membrane exposes its contents to the synaptic cleft; the packet supplied by one synaptic vesicle is a quantum of release. Quantal neurotransmitter release refers to these discrete packets, rather than the release of one molecule at a time. The postsynaptic response to a packet can vary with its contents, receptors and recording conditions. See Purves and colleagues: vesicles as the source of transmitter quanta.

The useful cycle is filling, preparation for fusion, calcium-triggered exocytosis, and recovery of membrane and proteins through endocytosis for reuse. Different recovery routes occur; recycling need not preserve a particular synaptic vesicle as an identifiable container throughout. Limited availability of prepared synaptic vesicles can reduce release during repeated stimulation, while changes in synaptic release probability can also change successive responses. See Basic Neurochemistry: secretion machinery and vesicle reuse and 3.1 Synapses.

For an illustrative calculation, assume four release sites, each with one prepared synaptic vesicle, each releasing with synaptic release probability $p=0.25$ during one presynaptic action potential. Assume independent Bernoulli trials and at most one release per site. The released packet count $K$ has a binomial distribution:The probability of no release is $\mathbb{P}(K=0)=0.75^4=0.31640625$; at least one release has probability $0.68359375$. An expected value of one packet does not mean that every action potential releases one packet. If each packet contributes a stipulated $0.5\mathrm{nS}$ conductance increment and increments add, the expected value of that increment is $0.5\mathrm{nS}$, with zero increment on about $31.6\%$ of trials. These assumptions are a teaching model: shared calcium fluctuations, unequal sites, depletion and nonlinear receptor responses can invalidate them.

Quantal neurotransmitter release is release of neurotransmitter in discrete packets associated with individual synaptic vesicles. Packet count and postsynaptic packet response are different quantities; see the binomial distribution example under synaptic vesicle.

Synaptic release probability is the probability of release at a specified site during a specified opportunity, such as one presynaptic action potential. It depends on the site's state and conditions; it is not the probability that the receiving neuron fires. In the example under synaptic vesicle, $p$ refers to one available site, whereas $1-(1-p{)}^4$ refers to any of four independent sites releasing.

Shunting inhibition is suppression of another input's effect through increased synaptic conductance: opening additional ion channels lowers effective electrical resistance, reducing the voltage response to a given added electric current. When the added reversal potential equals the resting membrane potential, there can be no voltage change at rest and still be inhibition of a simultaneous input. See 1.4 Limitations of the Leaky Integrate-and-Fire Model.

Use the passive synaptic potential model below with leak $g_L=10\mathrm{nS}$, $E_L=-65\mathrm{mV}$ and capacitance $C=200\mathrm{pF}$. A sustained inward test electric current of $I_{\mathrm{ext}}=100\mathrm{pA}$ alone gives a steady voltage increase of $I_{\mathrm{ext}}/g_L=10\mathrm{mV}$, so $V_{\infty }=-55\mathrm{mV}$. Effective electrical resistance is $100\mathrm{M\Omega }$ and the time constant is $20\mathrm{ms}$.

Now hold a shunting conductance $g_i=20\mathrm{nS}$ open with $E_i=E_L=-65\mathrm{mV}$. With no test electric current, rest stays at $-65\mathrm{mV}$. With the same $100\mathrm{pA}$ test electric current, total conductance becomes $30\mathrm{nS}$, so the steady voltage increase is only $100/30\simeq 3.333\mathrm{mV}$: $V_{\infty }\simeq -61.667\mathrm{mV}$. Effective electrical resistance is $33.333\mathrm{M\Omega }$ and the time constant is $200/30\simeq 6.667\mathrm{ms}$. A faster response can therefore be smaller. At the original rest the shunting electric current is zero; at $V=-55\mathrm{mV}$ it is $20(-65+55)=-200\mathrm{pA}$, opposing the voltage excursion.

The factor of three reduction applies to this constant-electric current, constant-conductance example. A finite pulse, conductance-driven input or spatially extended dendrite need not have the same reduction. The interesting feature is conditional action: the shunt can leave a quiet neuron's voltage unchanged yet reshape its response when another input arrives. A model that represents all inhibition as a fixed outward electric current misses this behavior.

An electrical synapse passes ionic electric current directly between neurons through gap junctions, whose paired channels connect the two cytoplasms. It does not require synaptic vesicle release and postsynaptic neurotransmitter binding. Transmission across the junction is very fast; the receiving cell membrane's capacitance and other conductances still determine its voltage response. Electrical coupling can coordinate the timing of activity across neurons. See Purves and colleagues: electrical synapses and gap junctions.

For a passive junction with constant conductance $g_j$, the inward electric current into cell 2 iswhere each $V_k$ is the cell's membrane potential, measured against a common extracellular reference. Taking $g_j=2\mathrm{nS}$, $V_1=-55\mathrm{mV}$ and $V_2=-65\mathrm{mV}$ gives $20\mathrm{pA}$ into cell 2 and the equal opposite electric current into cell 1. Exchanging the voltages reverses the electric current. Both depolarization and hyperpolarization can therefore be transmitted; an electrical synapse is not inherently an excitatory connection.

Many electrical synapses conduct in both directions, but this does not guarantee equal voltage responses: the cells can have different effective electrical resistance and capacitance. Some junctions rectify, meaning they conduct preferentially in one direction, so the constant-$g_j$ formula is insufficient. A concrete molecular example is the original study ^[ref]. Bidirectionality is thus a common property with important qualifications, rather than part of the definition.

A synaptic potential is a postsynaptic change in membrane potential caused by activity at a synapse. Unlike the regenerative action potential, a passive synaptic potential is graded: its size depends on input strength, the initial membrane potential and the receiving cell membrane's properties. Local voltage changes can decay before reaching the soma; their timing and overlap help determine whether an action potential follows. See Ion Channels and the Electrical Properties of Membranes.

Depolarization means that the interior becomes less negative relative to the exterior; hyperpolarization means that it becomes more negative. Excitation and inhibition instead describe whether an input promotes or opposes postsynaptic action potential generation. An inhibitory postsynaptic potential can be depolarizing, and shunting inhibition can occur with no voltage change at rest. The receptor, permeating ions, ionic gradients and reversal potential matter. See Purves and colleagues: excitation, inhibition and depolarizing inhibition.

A worked passive model treats the receiving membrane as one compartment with capacitance $C>0$, leak conductance $g_L>0$, and activated synaptic conductances $g_e,g_i\ge 0$:All electric currents are inward-positive. Each term $g(E-V)$ vanishes at its reversal potential $E$; $\mathrm{nS}\times \mathrm{mV}=\mathrm{pA}$. With constant parameters, the ordinary differential equation hasHere $G$ is total conductance, $1/G$ is effective electrical resistance, $V_{\infty }$ is the steady state and $\tau$ the time constant. Without imposed electric current, $V_{\infty }$ is a conductance-weighted average of the reversal potentials. This approximation omits spatial structure, changing ionic gradients and active voltage-gated ion channels; it calculates passive voltage responses, not actual action potential waveforms. See 3.1 Synapses for the mechanism behind the terms; the inward-positive convention here reverses that source's synaptic-current sign.

Take the same illustrative leak and capacitance as under shunting inhibition, start at $V(0)=-65\mathrm{mV}$ and set $I_{\mathrm{ext}}=0$. Opening $g_e=2\mathrm{nS}$ with $E_e=0\mathrm{mV}$ gives $V_{\infty }=-650/12\simeq -54.167\mathrm{mV}$ and $\tau \simeq 16.667\mathrm{ms}$. Its initial inward electric current is $2(0+65)=130\mathrm{pA}$. Adding $g_i=20\mathrm{nS}$ with $E_i=-65\mathrm{mV}$ changes $V_{\infty }$ to $(-650-1300)/32=-60.9375\mathrm{mV}$ and $\tau =6.25\mathrm{ms}$. This is shunting inhibition of the same excitatory drive.

For comparison, $g_i=20\mathrm{nS}$ with $E_i=-75\mathrm{mV}$ alone gives $V_{\infty }\simeq -71.667\mathrm{mV}$: hyperpolarization. With $E_i=-60\mathrm{mV}$ instead, it alone gives $V_{\infty }\simeq -61.667\mathrm{mV}$: depolarization. Yet adding this depolarizing conductance to the $g_e=2\mathrm{nS}$ excitatory drive lowers that drive's $V_{\infty }$ from $-54.167$ to $(-650-1200)/32=-57.8125\mathrm{mV}$. At an illustrative firing threshold $V=-50\mathrm{mV}$, its electric current is $20(-60+50)=-200\mathrm{pA}$, opposing threshold approach. The combined trace initially rises faster than the excitatory drive alone, before settling below it. Thus the sign of a voltage change at rest alone does not determine excitation or inhibition; a claim about firing must specify input strength, timing and the neuron's state.

Synaptic conductance describes how strongly activated synaptic ion channels conduct electric current for a given driving force. In the passive approximation, $I_{\mathrm{syn}}=g_{\mathrm{syn}}(E_{\mathrm{syn}}-V)$, with inward-positive electric current. It is the electrical conductance contribution of a synapse; its postsynaptic voltage response also depends on the driving force, the other membrane electrical conductances, and the capacitance. The synaptic potential model and shunting inhibition example show why a nonzero synaptic conductance can have zero electric current at rest.

An excitatory postsynaptic potential is a synaptic potential associated with increased likelihood of a postsynaptic action potential. Its size and effect depend on the receiving neuron's state; the definition concerns firing, not a fixed neurotransmitter identity. See synaptic potential for the mechanism and source.

An inhibitory postsynaptic potential is a synaptic potential associated with decreased likelihood of a postsynaptic action potential. It can involve hyperpolarization or depolarization; an inhibitory conductance can even produce no measurable voltage change at rest. See synaptic potential and shunting inhibition for worked examples and sources.

An action potential is a brief regenerative excursion of membrane potential, produced by changing electrical resistance and conductance through voltage-gated ion channels. In a typical fast neuronal action potential, sodium entry raises membrane potential, activating further sodium channels. This feedback produces the rapid rising phase. Inactivation of sodium channels and increased conductance to potassium then lower membrane potential again; persisting potassium conductance can produce an undershoot below the resting level. See Purves and colleagues: the ionic basis of action potentials.

For an illustrative electrical calculation, write inward sodium electric current as $I_{\mathrm{Na}}=g_{\mathrm{Na}}(E_{\mathrm{Na}}-V)$. At $V=-50\mathrm{mV}$, taking $E_{\mathrm{Na}}=60\mathrm{mV}$ and $g_{\mathrm{Na}}=10\mathrm{nS}$ gives $I_{\mathrm{Na}}=1.1\mathrm{nA}$ inward. A potassium current $I_{\mathrm{K}}=g_{\mathrm{K}}(E_{\mathrm{K}}-V)$ with $E_{\mathrm{K}}=-80\mathrm{mV}$ and $g_{\mathrm{K}}=20\mathrm{nS}$ gives $-0.6\mathrm{nA}$, outward. These illustrative values expose opposing driving forces; a waveform requires the conductances to evolve with membrane potential and time, as in the Hodgkin-Huxley model.

An action potential propagates along an axon because local electric currents bring neighboring regions of cell membrane into the regime where their voltage-gated ion channels regenerate the signal. It is a traveling pattern of excitation, not a packet of sodium ions traversing the entire axon. Regeneration allows an action potential to travel without the passive attenuation of a small local voltage change. See Ion Channels and the Electrical Properties of Membranes.

The neuronal refractory period constrains how soon another action potential can follow. Under comparable conditions, successive action potentials have roughly stereotyped shapes, making event count and timing useful for neural coding; waveform details can nevertheless change with channel state and conditions. The leaky integrate-and-fire model abstracts each action potential to a threshold event and reset. Its reset jump is a mathematical rule, not the actual regenerative waveform produced by sodium and potassium currents.

Sustained membrane potential depolarization can prevent repeated action potentials because voltage-dependent ion-channel inactivation leaves too few available sodium channels. This differs from a reduced response to a passive current step: active Hodgkin-Huxley model dynamics and recovery from inactivation are essential to the mechanism.

A compound action potential is an extracellularly recorded sum of activity from multiple axons. Amplitude and waveform depend on recruitment and relative arrival times. The documented neuronal paired-pulse recovery experiment illustrates why recovery of a summed response is not recovery of one neuron.

A neuronal refractory period is the change in excitability following an action potential: recent firing changes whether, and how readily, a neuron can fire again. The absolute neuronal refractory period prevents a second regenerative action potential; during the relative neuronal refractory period, some stimuli that work after full recovery still fail. These are useful distinctions, but their durations are not universal constants. The preparation, temperature, starting membrane potential, stimulation protocol and criterion for detecting an action potential must accompany a measured interval.

The mechanism continues the opposing sodium and potassium electric currents described under action potential and the Hodgkin-Huxley model. After a spike, ion-channel inactivation leaves fewer sodium-selective voltage-gated ion channels available for regenerative depolarization, while persisting potassium electrical conductance opposes that depolarization. In the Hodgkin-Huxley model, recovery of $h$ restores sodium availability and relaxation of $n$ reduces potassium electrical conductance. Closed but available channels differ from inactivated channels: opening and recovery from ion-channel inactivation are different processes.^[ref]

This short memory matters for spike trains: a stimulus-only Poisson process can predict very short interspike intervals that a refractory neuron cannot produce. Neuronal paired-pulse recovery makes that memory visible. The phenomenological paired-pulse recovery example below separates a chosen recovery rule, pulse strength and event readout; refractory limits on neuronal firing then shows why an absolute bound is not a prediction of sustained firing rate.

During an absolute neuronal refractory period, the excitable region cannot initiate a second distinct regenerative action potential under the physiological stimulation conditions being considered. Extensive sodium ion-channel inactivation is central for a fast sodium-dependent action potential. “Cannot fire” concerns regeneration; an imposed pulse can still move membrane potential or leave a recording artifact. Failure of just one fixed-amplitude test pulse does not establish an absolute neuronal refractory period: the same failure can occur in the relative neuronal refractory period.

The boundary is an operational question about distinguishable action potentials and the range of stimulation tested. A drawn vertical line is useful in the phenomenological paired-pulse recovery model, where it is imposed explicitly; it should not be mistaken for a universal sharp biochemical switch.

During a relative neuronal refractory period, another action potential is possible, but incomplete recovery changes the excitation needed to obtain it. Remaining sodium ion-channel inactivation and elevated potassium electrical conductance both matter. A hyperpolarization after an action potential can increase the voltage excursion needed for firing, while extra electrical conductance can drain an injected pulse faster. Thus a single fixed neuronal firing threshold measured from the instantaneous voltage misses relevant state variables.^[ref]

Recovery can depend on earlier spikes as well as the last one; the Hodgkin-Huxley model and neural adaptation provide richer histories than an imposed reset. A fixed hold in a leaky integrate-and-fire model is a useful simplification with a specified domain, rather than a complete explanation of a relative neuronal refractory period.^[ref]

Neuronal paired-pulse recovery probes the effect of an earlier action potential with a later test stimulus. First establish a conditioning action potential; then vary the delay $\Delta$ to a test pulse of specified amplitude, duration and delivery site. Record whether a second action potential occurs, its timing and, where relevant, its waveform. Repeating the test across amplitudes distinguishes recovery of responsiveness to one pulse from recovery of the minimum effective pulse. Direct current clamp stimulation can probe the receiving neuron's excitability; stimulation through a synapse additionally allows synaptic plasticity to alter the input.

A documented whole-nerve teaching experiment keeps a bundle of axons in physiological solution, with its proximal end drawn into a stimulating tube and its distal end into a recording tube. The suction electrodes use short plastic tubes and $1\mathrm{ml}$ syringe-plunger terminals, held by O-rings. Longitudinal electric currents create a voltage drop in the thin solution layer between bundle and tube, read by a cathode-ray oscilloscope. Electrode fit affects amplitude. An immediate stimulation artifact remains even without the nerve, whereas the neural signal arrives after a delay.^[ref][ref]

The paired-stimulus exercise sets $0.1\mathrm{ms}$ pulses to obtain a maximal undistorted A wave of the compound action potential, then increases the spacing. The described first response remains constant while the second grows with spacing. Different axons recover at different times; the summed response therefore grows as more contribute. A smaller second compound action potential does not mean every individual action potential has shrunk. The source contrasts this with a single axon's response or failure. Its response-amplitude recovery criterion is not a universal single-cell threshold criterion.^[ref]

Useful additional controls would include single-pulse baselines interleaved with paired trials, a verified conditioning action potential, enough rest between trials, and fixed temperature, electrode geometry, pulse width and initial membrane potential. Confirm stimulus delivery and amplifier recovery, separate the stimulus artifact from a second neural event, and check whether waveforms overlap before measuring amplitudes. These are proposed checks, not additional results claimed for that teaching experiment. Even a clean compound action potential does not uniquely identify sodium availability: recruitment, propagation and synchronization of different axons influence the summed signal. Nor does failure at a distant recording site alone distinguish failed initiation from failed propagation.

Choose the following original phenomenological mathematical model solely to calculate a paired-pulse readout. It is not experimental data, a fit to the teaching experiment, or a simulation of the Hodgkin-Huxley model. The conditioning action potential defines time zero. Test pulses have fixed width $0.2\mathrm{ms}$; $I$ denotes their inward electric current amplitude. Impose an absolute neuronal refractory period $t_{\mathrm{abs}}=2\mathrm{ms}$. No finite test amplitude generates an event for $0<\Delta <t_{\mathrm{abs}}$. After that hold, stipulate a required amplitudewith $I_{\infty }=0.2\mathrm{nA}$, dimensionless $A=2$ and recovery time constant ${\tau }_r=3\mathrm{ms}$. Emit a test event exactly when $I\ge I_{\mathrm{req}}(\Delta )$, including equality. For this ideal event readout, assign events to pulse onset and assume the conditioning event is successfully evoked. There is no calculated membrane potential, spike waveform, response latency or stochastic success probability.

The exponential decay represents a combined recovery deficit; it is neither the Hodgkin-Huxley model's $h$ nor a measured potassium electrical conductance. One such curve cannot separately identify sodium recovery and persistent potassium electrical conductance. A constant pulse-width amplitude criterion also does not establish an equivalent rule for other pulse widths or voltage trajectories.

At the hold boundary, $I_{\mathrm{req}}(2\mathrm{ms})=0.2(1+2)=0.6\mathrm{nA}$. At $\Delta =4\mathrm{ms}$,at $\Delta =6\mathrm{ms}$,Thus a $0.35\mathrm{nA}$ test fails at $1\mathrm{ms}$ because of the imposed hold, fails at $4\mathrm{ms}$ because recovery is insufficient for that amplitude, and succeeds at $6\mathrm{ms}$. At $4\mathrm{ms}$, a $0.5\mathrm{nA}$ pulse would instead succeed: failure of the weaker pulse was relative refractoriness.

For $I>I_{\infty }$, solve $I\ge I_{\mathrm{req}}(\Delta )$ using the logarithm. The earliest allowed delay isFor $I=0.35\mathrm{nA}$ this is $2+3\ln (8/3)\approx 4.942488\mathrm{ms}$; for $I=0.5\mathrm{nA}$ it is $2+3\ln (4/3)\approx 2.863046\mathrm{ms}$. If $I\ge 0.6\mathrm{nA}$, the imposed $2\mathrm{ms}$ hold is the only delay restriction. If $I\le I_{\infty }$, no finite delay passes the rule: the required amplitude stays strictly above its asymptotic baseline. A finite experimental “fully recovered” time therefore also needs a tolerance and a readout definition.

If every interspike interval is at least $t_{\mathrm{abs}}>0$, a sustained spike train has mean firing rate at most $1/t_{\mathrm{abs}}$. Across a window of duration $T$, the event count satisfies $N(T)\le 1+T/t_{\mathrm{abs}}$; dividing by $T$ and taking the long-time limit gives the bound. The extra one accounts for a possible first event. The bound permits much slower firing and says nothing about whether stronger drive can maintain the limiting rate in a real neuron.

For the chosen phenomenological paired-pulse recovery, the hold alone gives $500\mathrm{Hz}$. Add the further assumption that every successful event resets precisely the same recovery curve, with no accumulation from earlier events. Then $0.35\mathrm{nA}$ onset-timed pulses can sustain at most $1000/4.942488\approx 202.327\mathrm{Hz}$ in that model. This repeatable reset is an extra assumption: a two-pulse result alone cannot establish it. A real neuron's sustained rate also depends on neural adaptation, input delivery and evolving ion-channel inactivation. The existing leaky integrate-and-fire model similarly adds integration time to its imposed hold.

A homogeneous Poisson process of rate $\lambda$ has interspike intervals with an exponential distribution, soWith the purely illustrative choices $\lambda =100\mathrm{Hz}$ and $t_{\mathrm{abs}}=0.002\mathrm{s}$, this is $1-e^{-0.2}\approx 0.181269$. Thus about $18.13\%$ of intervals predicted by that model violate this chosen hold. Matching a mean spike train count does not make a stimulus-only Poisson process respect recent firing.

A minimal alternative is a renewal process with independent and identically distributed intervals $S=t_{\mathrm{abs}}+X$, where $X$ has an exponential distribution of rate $\lambda$. Its hazard function is zero during the hold and $\lambda$ afterwards. Its mean interval is $t_{\mathrm{abs}}+1/\lambda$ and long-run firing rate isThe same $100{\mathrm{s}}^{-1}$ rate after a $2\mathrm{ms}$ hold gives $83.333\mathrm{Hz}$, not $100\mathrm{Hz}$. This separate stochastic example has no gradual relative recovery; it illustrates why an available-state rate differs from an observed mean firing rate. Smooth dependence on time since the last event can extend the hazard function, while longer histories require more than this simple renewal process. Time-rescaled spike-train diagnostics can test the resulting history-dependent predictions against recorded spike trains.

A neuronal process that receives and integrates many inputs. Its geometry and membrane properties can make integration spatially and temporally selective.

A neuronal process that carries signals toward output sites, often by propagation of action potentials to synapses.

An axon from the inferior olive with powerful input to a Purkinje cell. Its activity can evoke a complex spike and participate in an instructive pathway for cerebellar error-driven learning.

A branch of a cerebellar granule-cell axon that forms synapses on Purkinje cells and other cerebellar neurons. Expanded granule-cell activity supplies a diverse input basis in cerebellar adaptive-filter models.

The axon initial segment is the specialized proximal region of an axon near the soma. In many neurons, its voltage-gated ion channels make it the site where an action potential begins. ^[ref]