singleunit

Single unit, in neuroscience and related fields, refers to the measurement and analysis of activity from a single functional unit, typically a neuron, rather than the collective activity of many cells. The term is used most often to describe extracellular recordings in which a microelectrode picks up the electrical signals produced by one neuron, or, with spike sorting, attempts to attribute detected spikes to a single cell.

In practice, single-unit recording involves inserting a microelectrode into neural tissue and recording action potentials. The captured signals are processed to isolate spikes from individual neurons, a process called spike sorting. Researchers then analyze metrics such as firing rate, inter-spike intervals, and spike waveform shape to infer how a neuron responds to stimuli, encodes information, or participates in motor control. Single-unit data are valued for their cell-specific insight, but they require careful handling of issues such as electrode drift, spike overlap, and changes in unit detectability over time.

Single-unit recordings are contrasted with multiunit recordings, where the signal reflects the combined activity of several neurons on the same channel, offering easier data collection but with reduced ability to attribute activity to a single cell. Beyond neuroscience, the term single unit can also describe an individual component or module within a system—a standalone product, device, or functional block in engineering contexts.

In summary, single-unit analysis provides granular, neuron-level information that supports decoding neural coding and neural circuit function, while acknowledging technical challenges inherent to isolating single-neuron activity.