Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Neural Circuits

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...

Neuron Structure

Neuron Structure

Neuron Structure

Neuron Structure

Neurons are the main type of cell in the nervous system that generate and transmit electrochemical signals. They primarily communicate with each other using neurotransmitters at specific junctions called synapses. Neurons come in many shapes that often relate to their function, but most share three main structures: an axon and dendrites that extend out from a cell body.
Structure and Function of Neurons
The neuronal cell body—the soma— houses the nucleus and organelles vital to...

Network Function of a Circuit

Network Function of a Circuit

Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.

Electrical Synapses

Electrical Synapses

Electrical synapses found in all nervous systems play important and unique roles. In these synapses, the presynaptic and postsynaptic membranes are very close together (3.5 nm) and are actually physically connected by channel proteins forming gap junctions.
Gap junctions allow the current to pass directly from one cell to the next. In contrast, in the chemical synapse, the neurotransmitters carry the information through the synaptic cleft from one neuron to the next. They consist of two...

Circuit Terminology

Circuit Terminology

An electrical network is a system composed of interconnected elements, such as resistors, capacitors, inductors, and voltage or current sources. Unlike a circuit, an electrical network does not necessarily form a closed path. In other words, while all circuits can be considered networks due to their interconnected nature, not every network qualifies as a circuit.
A circuit, on the other hand, is also an interconnected system of electrical elements but must contain one or more closed paths.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Modeling spatial contrast sensitivity in responses of primate retinal ganglion cells to natural movies.

PLoS computational biology·2026

Same author

Absence of local retinotopy in the mouse optic tract.

Frontiers in neural circuits·2026

Same author

Spatial Adaptation of Primate Retinal Ganglion Cells Between Artificial and Natural Stimuli.

eNeuro·2026

Same author

[Remodeling of the internal retina-Implications for targeted optogenetics].

Die Ophthalmologie·2026

Same author

The central histaminergic system slows visual processing in the retina and lateral geniculate nucleus of awake mice.

PLoS biology·2025

Same author

Atypical cortical feedback underlies failure to process contextual information in the superior colliculus of Scn2a<sup>+/-</sup> autism model mice.

Nature communications·2025

Same journal

Increased rates of hybridization in swordtails are associated with water pollution.

Current biology : CB·2026

Same journal

Visual uncertainty and task demands shape active sensing strategies in mice.

Current biology : CB·2026

Same journal

An adaptable, self-organizing, single-cell morphology circuit optimizes suctorian predatory trap structure.

Current biology : CB·2026

Same journal

Temporal tuning of switch-like virulence expression resolves environmental uncertainty through phenotypic heterogeneity.

Current biology : CB·2026

Same journal

An abstract relational map emerges in the human medial prefrontal cortex with consolidation.

Current biology : CB·2026

Same journal

Phloem evolved gradually and asynchronously to xylem in early vascular plants.

Current biology : CB·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 9, 2026

Electrophysiological and Morphological Characterization of Neuronal Microcircuits in Acute Brain Slices Using Paired Patch-Clamp Recordings

Electrophysiological and Morphological Characterization of Neuronal Microcircuits in Acute Brain Slices Using Paired Patch-Clamp Recordings

Published on: January 10, 2015

Neural Circuit Inference from Function to Structure.

Esteban Real¹, Hiroki Asari¹, Tim Gollisch²

¹Harvard University, Cambridge, MA 02139, USA.

Current Biology : CB

|January 10, 2017

Summary

This summary is machine-generated.

Researchers developed a novel modeling approach to infer neural circuit structure from limited brain recordings. This framework integrates anatomical and physiological data, successfully predicting internal circuit dynamics and connectivity for better neuroscience big data analysis.

Keywords:

bipolar cells brain circuit circuit model computational neuroscience ganglion cells machine learning neural code neurophysiology retina vision

More Related Videos

Juxtasomal Biocytin Labeling to Study the Structure-function Relationship of Individual Cortical Neurons

Juxtasomal Biocytin Labeling to Study the Structure-function Relationship of Individual Cortical Neurons

Published on: February 25, 2014

Viral Tracing of Genetically Defined Neural Circuitry

Viral Tracing of Genetically Defined Neural Circuitry

Published on: October 17, 2012

Related Experiment Videos

Last Updated: Mar 9, 2026

Electrophysiological and Morphological Characterization of Neuronal Microcircuits in Acute Brain Slices Using Paired Patch-Clamp Recordings

Electrophysiological and Morphological Characterization of Neuronal Microcircuits in Acute Brain Slices Using Paired Patch-Clamp Recordings

Published on: January 10, 2015

Juxtasomal Biocytin Labeling to Study the Structure-function Relationship of Individual Cortical Neurons

Juxtasomal Biocytin Labeling to Study the Structure-function Relationship of Individual Cortical Neurons

Published on: February 25, 2014

Viral Tracing of Genetically Defined Neural Circuitry

Viral Tracing of Genetically Defined Neural Circuitry

Published on: October 17, 2012

Area of Science:

Neuroscience
Computational Neuroscience
Systems Neuroscience

Background:

Technological advancements offer new insights into brain circuit connectivity and dynamics.
Integrating anatomical and physiological data requires robust quantitative frameworks.

Purpose of the Study:

To present a modeling approach for inferring neural circuit structure from sparse recordings.
To link anatomical constraints with physiological data for circuit inference.

Main Methods:

Recorded visual responses from retinal ganglion cells.
Developed and systematically generated circuit models representing retinal neurons and connections.
Fitted models to experimental data using partial anatomical knowledge as a regularizer.

Main Results:

Optimal models accurately reproduced ganglion cell outputs.
Models predicted dynamics and connectivity of unobserved internal neurons.
Model predictions were experimentally validated.

Conclusions:

The circuit inference framework effectively integrates diverse neuroscience data.
This approach facilitates understanding of complex neural circuits and big data in neuroscience.