Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Neural Circuits01:25

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...
Integration of Synaptic Events01:28

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...
The Synapse02:47

The Synapse

Neurons communicate with one another by passing on their electrical signals to other neurons. A synapse is the location where two neurons meet to exchange signals. At the synapse, the neuron that sends the signal is called the presynaptic cell, while the neuron that receives the message is called the postsynaptic cell. Note that most neurons can be both presynaptic and postsynaptic, as they both transmit and receive information.
Electrical Synapses01:28

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...
Synaptic Signaling01:09

Synaptic Signaling

Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Most synapses are chemical, meaning an electrical impulse or action potential spurs the release of chemical messengers called neurotransmitters. The neuron sending the signal is called the presynaptic neuron, and the neuron receiving the signal is the postsynaptic neuron.
The presynaptic neuron fires an action potential that...
Synaptic Signaling01:12

Synaptic Signaling

Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.

You might also read

Related Articles

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

Sort by
Same author

EventHD: Robust and efficient hyperdimensional learning with neuromorphic sensor.

Frontiers in neuroscience·2022
Same author

Learning to Recognize Actions From Limited Training Examples Using a Recurrent Spiking Neural Model.

Frontiers in neuroscience·2018
Same author

Criticality as a Set-Point for Adaptive Behavior in Neuromorphic Hardware.

Frontiers in neuroscience·2015
Same author

Synaptic plasticity enables adaptive self-tuning critical networks.

PLoS computational biology·2015
Same author

Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity.

Frontiers in computational neuroscience·2015
Same author

A novel analytical characterization for short-term plasticity parameters in spiking neural networks.

Frontiers in computational neuroscience·2014
Same journal

Multiplexed Crossbar GFET Array With BioADC for Multi-Modal Aptamer-Based Sensing.

IEEE transactions on biomedical circuits and systems·2026
Same journal

A VPG-Based Adaptive Windowing PPG Sensor IC for Low-Power Wearable Monitoring.

IEEE transactions on biomedical circuits and systems·2026
Same journal

A Chopper Amplifier with Feedforward SAR ADC Assisted DC Servo Loop Achieving ±1V DC Offset Cancellation in 2.1s for Neural Signal Recordings.

IEEE transactions on biomedical circuits and systems·2026
Same journal

ANP-R: A 22nm 0.88pJ/SOP Asynchronous SNN-based Processor with Coarse-Grained Reconfigurable Architecture Enabling Multisensory On-chip Incremental Learning for Edge AI.

IEEE transactions on biomedical circuits and systems·2026
Same journal

A High-Efficiency Neural Processing SoC for Adaptive Closed-Loop Neuromodulation.

IEEE transactions on biomedical circuits and systems·2026
Same journal

DustNet: A Wireless Network of Ultrasonic Neural Implants.

IEEE transactions on biomedical circuits and systems·2026
See all related articles

Related Experiment Video

Updated: May 9, 2026

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

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

Published on: March 9, 2019

Energy-efficient neuron, synapse and STDP integrated circuits.

Jose M Cruz-Albrecht1, Michael W Yung, Narayan Srinivasa

  • 1Microelectronics Laboratory, HRL Laboratories LLC, Malibu, CA 90265 USA. jcruz@hrl.com

IEEE Transactions on Biomedical Circuits and Systems
|July 16, 2013
PubMed
Summary
This summary is machine-generated.

We developed ultra-low energy, biologically inspired neuron and synapse circuits with spike-timing-dependent plasticity. These novel integrated circuits demonstrate efficient operation, consuming only 0.4 pJ per spike and synaptic event.

More Related Videos

Compartmentalization of Human Stem Cell-Derived Neurons within Pre-Assembled Plastic Microfluidic Chips
06:46

Compartmentalization of Human Stem Cell-Derived Neurons within Pre-Assembled Plastic Microfluidic Chips

Published on: May 3, 2019

Related Experiment Videos

Last Updated: May 9, 2026

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

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

Published on: March 9, 2019

Compartmentalization of Human Stem Cell-Derived Neurons within Pre-Assembled Plastic Microfluidic Chips
06:46

Compartmentalization of Human Stem Cell-Derived Neurons within Pre-Assembled Plastic Microfluidic Chips

Published on: May 3, 2019

Area of Science:

  • Neuromorphic Engineering
  • Integrated Circuit Design
  • Biologically Inspired Computing

Background:

  • Traditional computing faces limitations in energy efficiency for complex tasks.
  • Biologically inspired circuits offer a promising alternative for low-power computation.
  • Spiking neural networks (SNNs) mimic biological neurons and synapses for efficient information processing.

Purpose of the Study:

  • To design, fabricate, and test ultra-low energy, biologically inspired neuron and synapse integrated circuits.
  • To incorporate a spike-timing-dependent plasticity (STDP) learning rule into the synapse circuit.
  • To evaluate the energy efficiency of the developed neuromorphic circuits.

Main Methods:

  • Utilized a 90 nm CMOS process for circuit design and fabrication.
  • Developed integrated circuits for artificial neurons and synapses.
  • Implemented a circuit for spike-timing-dependent plasticity (STDP) learning.
  • Conducted experimental measurements to validate circuit functionality and energy consumption.

Main Results:

  • Successfully designed, fabricated, and tested neuron and synapse integrated circuits.
  • Demonstrated proper operation of the circuits through experimental measurements.
  • Achieved ultra-low energy consumption: approximately 0.4 pJ per spike for the neuron and 0.4 pJ per synaptic operation for the synapse with STDP.

Conclusions:

  • The developed biologically inspired neuron and synapse circuits with STDP are functional and highly energy-efficient.
  • These circuits represent a significant advancement in low-power neuromorphic engineering.
  • The demonstrated ultra-low energy consumption (0.4 pJ) is suitable for large-scale, power-constrained neuromorphic systems.