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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...

The Role of Ion Channels in Neuronal Computation

The Role of Ion Channels in Neuronal Computation

A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....

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...

Neuronal Communication

Neuronal Communication

Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...

Integration of Synaptic Events

Integration of Synaptic Events

Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...

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Related Experiment Video

Updated: Dec 7, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

Emerging Memristive Artificial Synapses and Neurons for Energy-Efficient Neuromorphic Computing.

Sanghyeon Choi¹, Jehyeon Yang¹, Gunuk Wang¹

¹KU-KIST Graduate School of Converging Science and Technology, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea.

Advanced Materials (Deerfield Beach, Fla.)

|October 2, 2020

Summary

Memristors offer dynamic reconfiguration for artificial neural networks, mimicking synaptic and neuronal functions. Understanding their principles is key for advanced neuromorphic computing hardware.

Keywords:

artificial neural networks artificial neurons artificial synapses memristive electronic devices memristors neuromorphic electronics

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Last Updated: Dec 7, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

A Method for Growing Bio-memristors from Slime Mold

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Published on: November 2, 2017

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

Published on: April 15, 2015

Area of Science:

Materials Science
Computer Engineering
Neuroscience

Background:

Memristors exhibit history-dependent electrical behavior, enabling emulation of biological synapses and neurons.
This functionality is crucial for developing artificial neural networks and neuromorphic computing systems.
Understanding memristor switching principles and device architectures is vital for hardware implementation.

Purpose of the Study:

To review memristors and related devices for artificial synapses and neurons.
To present device structures, switching principles, and applications in neuromorphic systems.
To discuss recent advances in memristive artificial neural networks and learning algorithms.

Main Methods:

Comprehensive literature review of memristor devices and applications.
Sequential presentation of device structures and switching mechanisms.
Overview of recent hardware implementations and learning algorithms in memristive ANNs.

Main Results:

Highlighted various memristor devices mimicking synaptic and neuronal functionalities.
Detailed device structures, switching principles, and applications.
Introduced advances in memristive artificial neural networks and hardware.

Conclusions:

Memristors are essential for neuromorphic computing, offering analog synaptic and neuronal emulation.
Challenges remain in achieving high-performance, energy-efficient memristive neuromorphic hardware.
This report serves as a guide for memristor research in neuromorphic computing.