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

Integration of Synaptic Events01:28

Integration of Synaptic Events

5.6K
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...
5.6K
Vision01:24

Vision

61.3K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
61.3K
Visual System01:26

Visual System

2.2K
Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
2.2K
Neural Circuits01:25

Neural Circuits

3.2K
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...
3.2K
Synaptic Signaling01:09

Synaptic Signaling

7.0K
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...
7.0K
Synaptic Signaling01:12

Synaptic Signaling

81.4K
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.
81.4K

You might also read

Related Articles

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

Sort by
Same author

Spatially local inhibition and synaptic plasticity together enable dynamic, context-dependent integration of parallel sensory pathways.

Cell reports·2026
Same author

Origin and functional impact of early nonlinearities in primate retina.

bioRxiv : the preprint server for biology·2026
Same author

Filter, Detector, Predictor: The expanding repertoire of retinal computation in vertebrates.

Vision research·2026
Same author

Surround motion modulates the encoding properties of primate retinal ganglion cells.

Cell reports·2026
Same author

Rod-cone signal interference impairs mesopic motion discriminability in a model circuit.

bioRxiv : the preprint server for biology·2026
Same author

Cone bipolar cell synapses generate transient versus sustained signals in parallel ON pathways of the mouse retina.

eLife·2025
Same journal

Fast-conducting mechanonociceptors uniquely engage reflexive and affective pain circuitry to drive protective responses.

Neuron·2026
Same journal

Sparse component analysis: A method that uncovers separable computations within neural population activity.

Neuron·2026
Same journal

Spatiomolecular mapping reveals anatomical organization of heterogeneous cell types in the human nucleus accumbens.

Neuron·2026
Same journal

TGF-β1-induced endothelial transcytosis drives blood-brain barrier leakage during aging.

Neuron·2026
Same journal

Image space opens up for visual neuroscience.

Neuron·2026
Same journal

Septal GLP-1 receptors control alcohol taking and seeking.

Neuron·2026
See all related articles

Related Experiment Video

Updated: Mar 20, 2026

Electrophysiological Investigations of Retinogeniculate and Corticogeniculate Synapse Function
09:09

Electrophysiological Investigations of Retinogeniculate and Corticogeniculate Synapse Function

Published on: August 7, 2019

6.6K

Synaptic Rectification Controls Nonlinear Spatial Integration of Natural Visual Inputs.

Maxwell H Turner1, Fred Rieke2

  • 1Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA; Graduate Program in Neuroscience, University of Washington, Seattle, WA 98195, USA.

Neuron
|June 7, 2016
PubMed
Summary
This summary is machine-generated.

Neural responses to natural stimuli differ between primate retinal ganglion cell (RGC) types. Off parasol RGCs show nonlinear spatial integration, while On parasol RGCs are more linear, impacting visual encoding models.

More Related Videos

Inducing Long-Term Plasticity of Intrinsic Neuronal Excitability in Neurons of the Dorsal Lateral Geniculate Nucleus
05:01

Inducing Long-Term Plasticity of Intrinsic Neuronal Excitability in Neurons of the Dorsal Lateral Geniculate Nucleus

Published on: September 20, 2024

851
Implementing Dynamic Clamp with Synaptic and Artificial Conductances in Mouse Retinal Ganglion Cells
11:46

Implementing Dynamic Clamp with Synaptic and Artificial Conductances in Mouse Retinal Ganglion Cells

Published on: May 16, 2013

12.9K

Related Experiment Videos

Last Updated: Mar 20, 2026

Electrophysiological Investigations of Retinogeniculate and Corticogeniculate Synapse Function
09:09

Electrophysiological Investigations of Retinogeniculate and Corticogeniculate Synapse Function

Published on: August 7, 2019

6.6K
Inducing Long-Term Plasticity of Intrinsic Neuronal Excitability in Neurons of the Dorsal Lateral Geniculate Nucleus
05:01

Inducing Long-Term Plasticity of Intrinsic Neuronal Excitability in Neurons of the Dorsal Lateral Geniculate Nucleus

Published on: September 20, 2024

851
Implementing Dynamic Clamp with Synaptic and Artificial Conductances in Mouse Retinal Ganglion Cells
11:46

Implementing Dynamic Clamp with Synaptic and Artificial Conductances in Mouse Retinal Ganglion Cells

Published on: May 16, 2013

12.9K

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Vision Science

Background:

  • Understanding neural responses to natural stimuli is crucial for sensory systems.
  • Retinal computation is well-studied but often uses artificial stimuli.
  • The mapping of artificial stimulus-based models to natural stimuli is unclear.

Purpose of the Study:

  • To investigate how retinal ganglion cells (RGCs) process natural visual stimuli.
  • To compare the spatial integration linearity of On and Off parasol RGCs with natural stimuli.
  • To determine the impact of nonlinear spatial integration on predicting RGC responses.

Main Methods:

  • Recording neural responses from primate Off and On parasol RGCs.
  • Presenting natural and artificial visual stimuli.
  • Analyzing spatial integration properties and synaptic inputs.
  • Developing computational models to predict RGC responses.

Main Results:

  • Off parasol RGCs exhibit nonlinear spatial integration of natural stimuli.
  • On parasol RGCs show surprisingly linear spatial integration of natural stimuli.
  • Both cell types display nonlinear integration with artificial stimuli.
  • Rectified excitatory synaptic input underlies nonlinear integration of natural stimuli.

Conclusions:

  • Spatial integration linearity in RGCs differs for natural versus artificial stimuli.
  • Accounting for nonlinear spatial integration significantly improves models predicting RGC responses to natural images.
  • This asymmetry in processing natural stimuli has implications for visual information encoding.