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

The Synapse

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.

You might also read

Related Articles

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

Sort by

Same author

Cohort Definition by Gestational Age Does Not Mean Ignoring Birthweight.

Acta paediatrica (Oslo, Norway : 1992)·2026

Same author

A highly sensitive genetically encoded red cAMP sensor for multiplex imaging in vivo.

Nature communications·2026

Same author

Gestational Age-Specific Prevalence of Retinopathy of Prematurity in Very Preterm Infants: An Exploratory Meta-Analysis.

Acta paediatrica (Oslo, Norway : 1992)·2026

Same author

Mapping spatially organized molecular and genetic signatures of schizophrenia across multiple scales in human prefrontal cortex.

bioRxiv : the preprint server for biology·2026

Same author

Sensitive and Selective Next-Generation FRET-based PKA Biosensors.

bioRxiv : the preprint server for biology·2026

Same author

Digital self-efficacy training and its effects on self-efficacy and mental health outcomes: A randomized controlled trial.

Psychiatry research·2025

Same journal

Genetic Impacts on Variability of Body Fat Distribution Uncover Gene-Environment and Gene-Gene Interactions.

bioRxiv : the preprint server for biology·2026

Same journal

16S ribosomal RNA modification drives transcript-specific translation efficiency.

bioRxiv : the preprint server for biology·2026

Same journal

FlcE latches onto the FliL-stator complex to turbocharge flagellar motility in <i>Borrelia burgdorferi</i>.

bioRxiv : the preprint server for biology·2026

Same journal

Synaptic pruning, myelination and the emergence of psychiatric disorders in late adolescence.

bioRxiv : the preprint server for biology·2026

Same journal

Structural and functional insights into the Rcs phosphorelay.

bioRxiv : the preprint server for biology·2026

Same journal

The structural basis of RanGAP1 regulation and catalysis in nuclear transport.

bioRxiv : the preprint server for biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 28, 2026

Analyzing Synaptic Modulation of Drosophila melanogaster Photoreceptors after Exposure to Prolonged Light

Analyzing Synaptic Modulation of Drosophila melanogaster Photoreceptors after Exposure to Prolonged Light

Published on: February 10, 2017

SynAPSeg: A novel dataset and image analysis framework for deep learning-based synapse detection and quantification.

Pascal Schamber¹, Sahana Darbhamulla¹, Molly Boyer¹

¹Department of Neuroscience, Tufts University, Boston, MA, USA.

Biorxiv : the Preprint Server for Biology

|March 27, 2026

Summary

This summary is machine-generated.

SynAPSeg offers a novel deep learning framework for analyzing synaptic puncta, enabling large-scale mapping of neural circuits and revealing age-related synaptic changes in the brain.

More Related Videos

Quantifying Synapses: an Immunocytochemistry-based Assay to Quantify Synapse Number

Quantifying Synapses: an Immunocytochemistry-based Assay to Quantify Synapse Number

Published on: November 16, 2010

DetectSyn: A Rapid, Unbiased Fluorescent Method to Detect Changes in Synapse Density

DetectSyn: A Rapid, Unbiased Fluorescent Method to Detect Changes in Synapse Density

Published on: July 22, 2022

Related Experiment Videos

Last Updated: Mar 28, 2026

Analyzing Synaptic Modulation of Drosophila melanogaster Photoreceptors after Exposure to Prolonged Light

Analyzing Synaptic Modulation of Drosophila melanogaster Photoreceptors after Exposure to Prolonged Light

Published on: February 10, 2017

Quantifying Synapses: an Immunocytochemistry-based Assay to Quantify Synapse Number

Quantifying Synapses: an Immunocytochemistry-based Assay to Quantify Synapse Number

Published on: November 16, 2010

DetectSyn: A Rapid, Unbiased Fluorescent Method to Detect Changes in Synapse Density

DetectSyn: A Rapid, Unbiased Fluorescent Method to Detect Changes in Synapse Density

Published on: July 22, 2022

Area of Science:

Neuroscience
Computational Neuroscience
Biophysics

Background:

Quantifying synaptic organization at circuit scales is a major challenge in neuroscience.
Current deep learning tools often fail to segment synaptic puncta in dense tissues.
There is a need for robust, scalable analysis methods for synaptic architecture.

Purpose of the Study:

To introduce SynAPSeg, an open-source deep learning framework for synaptic puncta segmentation and analysis.
To develop and validate deep learning models for accurate synaptic puncta quantification.
To enable large-scale mapping of synaptic organization and study synaptic changes in aging.

Main Methods:

Developed SynAPSeg, an open-source deep learning framework.
Created the first large-scale, publicly available instance segmentation dataset for synaptic puncta.
Trained deep learning models achieving expert-level performance on benchmark datasets.
Integrated models into an interactive interface supporting multi-dimensional data and automated pipelines.
Applied SynAPSeg to map millions of PSD95 puncta in the hippocampus and analyze aging-related synaptic changes in CA1 parvalbumin neurons.

Main Results:

SynAPSeg models achieved expert-level performance in synaptic puncta segmentation.
A comprehensive mapping of nearly 4 million PSD95 puncta in dorsal hippocampus inhibitory interneurons revealed regional differences.
Analysis of aged CA1 parvalbumin neurons showed a reduction in PSD95 density, indicating impaired glutamatergic recruitment.
The framework demonstrated scalability for large-scale synaptic architecture analysis.

Conclusions:

SynAPSeg provides a scalable, automated solution for synaptic puncta segmentation and quantification.
The framework facilitates large-scale synaptic mapping and the study of synaptic plasticity in health and disease.
Findings suggest that reduced PSD95 density in aged CA1 PV neurons may contribute to cognitive decline.