Computational Neuroscience Glossary

A rapid, transient reversal of membrane potential that propagates along axons, serving as the fundamental unit of neural communication.

A stable state or set of states toward which a dynamical system evolves over time, used to model memory and decision-making in neural networks.

A statistical method that updates the probability of a hypothesis as new evidence becomes available, using Bayes' theorem.

A device that records neural signals and translates them into commands for computers or prosthetic devices.

A partial differential equation describing voltage spread along a passive neurite, derived from the electrical cable properties of dendrites and axons.

The application of computational modeling to understand and characterize psychiatric disorders as aberrations in neural computation.

A comprehensive map of all neural connections in a nervous system, ranging from individual synapses to large-scale fiber tracts.

A branching extension of a neuron that receives synaptic input from other neurons and conducts signals toward the cell body.

A mathematical framework describing how the state of a system evolves over time according to fixed rules, widely used to model neural circuit dynamics.

The average number of action potentials a neuron produces per unit time, commonly measured in spikes per second (Hz).

A theoretical framework proposing that biological systems minimize variational free energy, a quantity bounding the surprise of sensory observations.

The input-output relationship of a neuron or neural circuit, describing how the response magnitude changes with input intensity.

A synaptic learning rule in which concurrent activity of pre- and post-synaptic neurons leads to strengthening of their connection.

A mathematical framework quantifying information content, entropy, and channel capacity, applied in neuroscience to measure neural coding efficiency.

A transmembrane protein that allows specific ions to flow across the cell membrane, governing neuronal excitability and signal propagation.

The voltage difference across a neuron's cell membrane, determined by the distribution of ions and the permeability of ion channels.

An interconnected assembly of neurons (biological) or computational units (artificial) that processes information through weighted connections.

Rhythmic fluctuation in neural activity, observed across frequency bands and associated with various cognitive and behavioral states.

A chemical messenger released at synapses that transmits signals between neurons by binding to receptors on the postsynaptic cell.

A decoded estimate of a stimulus or motor command derived from the weighted sum of individual neurons' preferred directions and firing rates.

The region of sensory space and set of stimulus attributes that elicit a response from a particular neuron.

A computational framework in which an agent learns to maximize cumulative reward through trial and error, linked to dopaminergic signaling in the brain.

The steady-state membrane potential of a neuron when it is not actively signaling, typically around -70 millivolts.

The junction between two neurons where signals are transmitted, either chemically via neurotransmitters or electrically via gap junctions.

A reinforcement learning algorithm that updates value estimates based on the difference between successive predictions, linked to dopamine neuron activity.