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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]

The study of nervous systems, from the properties of individual neurons to circuits, development, behavior and information processing.

An organism is an individual living system, made of one biological cell or an integrated assembly of biological cells. An Escherichia coli cell is an entire organism; a neuron is normally a specialized part of an animal. Metabolism, regulated exchange through cell membranes, and inherited information connect these very different scales. See OpenStax Biology 2e, 1.2: living systems and levels of organization.

Keep two questions separate: how many biological cells make the organism, and how those biological cells are organized. A yeast and an Escherichia coli are both unicellular organisms, but the yeast is a eukaryote and the Escherichia coli a prokaryote. A plant and an animal are multicellular organisms with eukaryotic cellular organization. Neither distinction ranks organisms as better or worse: natural selection acts on reproduction in particular environments.

Orientation selectivity is a systematic dependence of a visual neuron's response on the axis of a bar, edge or stripe pattern presented in its receptive field, under specified stimulus conditions. Here the angle $\theta$ measures the stripe axis from horizontal: $0^{\circ }$ is horizontal and $90^{\circ }$ vertical. An axis has no arrow, so $\theta$ and $\theta +180^{\circ }$ describe the same orientation. A preference for one direction of movement across that axis is an additional property; the 1962 recordings included both equal and unequal responses to opposite movements. ^[ref]

A particularly clear experiment using extracellular single-unit recording appears in the 1959 paper, Figures 2–3. A bright $1^{\circ }\times 8^{\circ }$ slit was centered on the same receptive field and rotated through successive angles; each presentation lasted one second. The vertical slit strongly increased the extracellularly recorded spike train, whereas the horizontal slit was ineffective. Small-spot tests had identified ON and OFF receptive-field subregions, with a central ON region and opposing flanks: rotation illuminated less of the center and more of the flanks. Geometry and location therefore mattered together. These dimensions belong to that recorded unit, not to every neuron. ^[ref]

An orientation tuning curve summarizes a controlled angle sweep. Keep location, size and visual contrast fixed; for a stripe pattern also specify spatial frequency and phase. The same signed spatial filter model of a simple cell can produce strong orientation selectivity and strong dependence on phase, as the following original toy illustrates. Its smooth curves are calculated predictions, not digitized or invented biological measurements.

A physiological sensor detects a relevant condition and changes a signal. In thermoregulation, temperature-sensitive neurons supply information about internal and skin temperature. Sensing a disturbance and sensing its internal consequence need not be the same operation.

The primary visual cortex, often abbreviated V1, is an early cortical stage of visual processing. Its neurons have receptive fields: changing a stimulus in a particular part of the visible scene can change their spike trains. Orientation selectivity adds a further distinction: at the same location, a properly aligned bar can evoke a strong response while a rotated bar evokes little. Simple cells make the dependence on local position and visual contrast especially clear. See the original experiments under orientation selectivity and simple cell.

In their 1962 study, David Hubel and Torsten Wiesel recorded from forty cats under thiopental anesthesia, maintained light anesthesia while monitoring cortical electrical activity, and used succinylcholine to stabilize the eyes. White-light patterns were projected onto a screen $1.5\mathrm{m}$ away. Extracellular single-unit recording with tungsten electrodes sampled individual units; receptive fields were mapped separately for each eye. This connected controlled stimulus geometry to individual spike trains. ^[ref]

These acute, anesthetized-cat recordings do not directly measure human perception or responses during awake behavior. The useful idea is a local description of structure: a population can distinguish where a feature lies, which way it is aligned, and which side is brighter. The signed spatial filter model of a simple cell turns that idea into a computable example. One neuron's preferred stimulus does not establish recognition of an entire object. Likewise, orientation selectivity in one neuron and an orderly map of preferences across primary visual cortex are different findings: rodents can have strong orientation selectivity without the orderly arrangement typical of some other species. ^[ref] The existing correlation-based development of visual cortical maps and orientation-map self-organization sections describe hypotheses about how organization develops.

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.

A simple cell is a visual cortical neuron whose receptive field has spatially separable ON and OFF receptive-field subregions. Elongated neighboring subregions give a preferred orientation and a sensitivity to the location and polarity of visual contrast. “Simple” describes the response organization; it does not describe a simpler cell body or a particular shape of neuron.

Hubel and Wiesel's 1962 classification emphasized four observations: distinguishable ON and OFF receptive-field subregions, summation within each region, antagonism between regions, and qualitative prediction of responses to differently shaped stimuli from those regions' arrangement. A slit fitting an elongated center was more effective than a smaller spot; a larger patch could invade opposing flanks and lose effectiveness. An edge separating bright and dark regions could be effective when its boundary matched the boundary between subregions. These were observations about spike trains, rather than an assertion of exact linearity. ^[ref]

The following deliberately coarse signed spatial filter model of a simple cell makes the geometry easy to count. A centered bright bar contributes positively at five sites. Rotating it preserves its area but mixes positive and negative weights; shifting it preserves its orientation but changes which weights it samples. The model is useful because it predicts distinct effects of these three manipulations instead of treating any bright stimulus as equivalent.

A simple cell is not an ideal linear sensor. Its spike train is nonnegative in event count, and neural adaptation can change responsiveness. The signed spatial filter model of a simple cell supplies a useful approximation to spatial drive and an explicit output rule. Comparing predictions with unseen stimuli is more informative than assuming the rule from the name “simple”. In contrast, the existing complex cell models explore tolerance to phase and local displacement.

Twelve resting volunteers wore a water-perfused suit. Tubes covered the torso, upper arms and legs; the right forearm remained uncovered for laser Doppler blood-flow measurement. Six thermocouples estimated mean skin temperature; a sublingual thermocouple measured oral temperature. A dry-air capsule measured local sweat output from outgoing air moisture. ^[ref]

After two control scans near $34{}^{\circ }\mathrm{C}$ skin temperature, the suit cooled and then warmed the skin. Mean oral temperature was $36.6{}^{\circ }\mathrm{C}$ during both cooling and early warming; mean skin readings were $30.5$ and $38.2{}^{\circ }\mathrm{C}$. Cutaneous vascular conductance fell during cooling and rose during warming. The inference is that compensatory blood-flow responses can precede an appreciable internal temperature change. ^[ref]

Repeated baselines controlled comparison within participants; closed mouths reduced oral-probe cooling artifacts. A later control with reduced oral temperature was excluded. Oral temperature is a proxy, local flow is not whole-body heat transfer, and the fixed condition order leaves time effects possible. Brain imaging measured regional blood flow, not direct neuron firing or causal necessity. ^[ref]