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 Experiment Videos

Neuromorphic Microchips.

Kwabena Boahen1

  • 1University of Pennsylvania, USA.

Scientific American
|May 11, 2005
PubMed
Summary
This summary is machine-generated.

Brain-inspired electronics offer new possibilities for restoring vision with implantable silicon retinas. This technology could also advance robotic eyes and smart sensors.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Catalyzing next-generation Artificial Intelligence through NeuroAI.

Nature communications·2023
Same author

Dendrocentric learning for synthetic intelligence.

Nature·2022
Same author

Optimal noise level for coding with tightly balanced networks of spiking neurons in the presence of transmission delays.

PLoS computational biology·2022
Same author

Cortical state dynamics and selective attention define the spatial pattern of correlated variability in neocortex.

Nature communications·2022
Same author

Selective modulation of cortical state during spatial attention.

Science (New York, N.Y.)·2016
Same author

A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm.

Advances in neural information processing systems·2014
See all related articles

Area of Science:

  • Neuroscience
  • Materials Science
  • Biomedical Engineering

Background:

  • The human brain's neural system demonstrates remarkable efficiency and complexity in information processing.
  • Current electronic systems often fall short of the brain's capabilities in terms of compactness and energy efficiency.

Purpose of the Study:

  • To explore the development of compact, efficient electronic systems inspired by the brain's neural architecture.
  • To investigate the potential of this technology for creating advanced sensory devices.

Main Methods:

  • Utilizing principles of neural network design for electronic circuits.
  • Developing novel materials and fabrication techniques for compact electronic components.

Main Results:

Related Experiment Videos

  • Demonstrated feasibility of brain-inspired electronic designs.
  • Achieved significant improvements in device efficiency and size.

Conclusions:

  • Compact, efficient electronics mimicking neural systems hold promise for significant technological advancements.
  • Potential applications include implantable silicon retinas for vision restoration and sophisticated robotic sensors.