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

Overview of Cell-Matrix Interactions

Overview of Cell-Matrix Interactions

The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...

You might also read

Related Articles

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

Sort by

Same author

Predicting progression to proliferative diabetic retinopathy using automated versus manual quantification of retinal haemorrhages.

Eye (London, England)·2026

Same author

Singular vectors of sums of rectangular random matrices and optimal estimation of high-rank signals: The extensive spike model.

Physical review. E·2023

Same author

A unified theory for the computational and mechanistic origins of grid cells.

Neuron·2022

Same author

Classical-Contextual Interactions in V1 May Rely on Dendritic Computations.

Neuroscience·2022

Same author

Optimizing a Neuron for Reliable Dendritic Subunit Pooling.

Neuroscience·2021

Same author

How Dendrites Affect Online Recognition Memory.

PLoS computational biology·2019

Search research articles

Related Experiment Video

Updated: Aug 25, 2025

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

Object Boundary Detection in Natural Images May Depend on "Incitatory" Cell-Cell Interactions.

Gabriel C Mel¹, Chaithanya A Ramachandra², Bartlett W Mel³

¹Department of Computer Science, University of Southern California, Los Angeles, California 90089 meldefon@gmail.com.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience

|October 14, 2022

Summary

Researchers explored how simple cells in the visual cortex detect object boundaries. They found a common neural circuit, "incitation," can generate boundary signals from simple cell inputs, aiding natural image recognition.

Keywords:

V1 cortical circuits excitatory-inhibitory interactions natural image statistics vision

More Related Videos

In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces

In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces

Published on: March 19, 2010

Author Spotlight: Advances in Evaluating Human Lung Epithelial Cells' Response to Metal-Organic Frameworks

Author Spotlight: Advances in Evaluating Human Lung Epithelial Cells' Response to Metal-Organic Frameworks

Published on: May 26, 2023

Related Experiment Videos

Last Updated: Aug 25, 2025

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces

In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces

Published on: March 19, 2010

Author Spotlight: Advances in Evaluating Human Lung Epithelial Cells' Response to Metal-Organic Frameworks

Author Spotlight: Advances in Evaluating Human Lung Epithelial Cells' Response to Metal-Organic Frameworks

Published on: May 26, 2023

Area of Science:

Computational neuroscience
Visual cortex function
Neural circuit analysis

Background:

Object boundary detection is vital for visual recognition but its neural basis in the visual cortex is unclear.
Conventional models of simple cells in primary visual cortex (V1) are insufficient for natural boundary detection.
Understanding cell-cell interactions is key to deciphering visual processing.

Purpose of the Study:

To investigate how simple cells contribute to object boundary detection in the visual cortex.
To predict the circuitry enabling boundary cells from conventional simple cell populations.
To characterize simple cell-boundary cell interactions.

Main Methods:

Analyzed 30,000 natural image patches to understand boundary statistics.
Applied Bayes' rule to model simple cell influence on hypothetical boundary cells based on spatial and orientational offsets.
Modeled neural circuits using direct excitation and indirect inhibition ('incitation').

Main Results:

Identified three fundamental cell-cell interaction types: rising, falling, and nonmonotonic.
Demonstrated that the 'incitation' circuit motif can replicate all observed interaction types.
Showed that synaptic weights for incitation circuits can be learned via a single-layer delta rule.

Conclusions:

Incitatory interconnections are a versatile computational mechanism for the cortex.
This circuit motif can extract high-quality boundary probability signals from simple cell populations in V1.
Findings offer a new framework for understanding cortical cell-cell interconnections in natural image classification.