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 Regulation01:37

Neural Regulation

43.4K
Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
43.4K
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

488
Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
488
Protein Complex Assembly02:41

Protein Complex Assembly

16.8K
Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
16.8K
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

44.6K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
44.6K
How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

38.0K
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
38.0K
Spindle Assembly02:50

Spindle Assembly

4.3K
Spindle assembly occurs through three, often coexisting, pathways – the centrosome-mediated pathway, the chromatin-mediated pathway, and the microtubule-mediated pathway – collectively contributing to form a robust spindle apparatus.
In most cells, centrosomes are the primary microtubule nucleation centers. In the centrosome-mediated pathway, the G2-prophase transition triggers centrosome maturation and increased microtubule nucleation. Progressive nucleation results in a...
4.3K

You might also read

Related Articles

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

Sort by
Same author

A sensorimotor instability drives a locomotor transition during fish development.

Science advances·2026
Same author

Neural temporal scaling accounts for robust hunting behavior across temperatures.

Nature communications·2026
Same author

Distinct distributed neural dynamics predict pallium-dependent social approach.

Nature communications·2026
Same author

Larval zebrafish minimize energy consumption during hunting via adaptive movement selection.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Phase transitions for polyadic epidemic and voter models with multiscale groups.

Physical review. E·2025
Same author

Zebrafish sleep displays distinct sub-states.

bioRxiv : the preprint server for biology·2025
Same journal

An endogenous viral element of Aedes albopictus is translated and limits cognate virus.

BMC biology·2026
Same journal

Environmental sex determination in the cyst nematode Globodera pallida defaults to male development.

BMC biology·2026
Same journal

Marine mammals as models for charting the evolution of social vocal rhythm.

BMC biology·2026
Same journal

Associations between immunosenescence and domain-specific cognition in the Health and Retirement Study Harmonized Cognitive Assessment Protocol.

BMC biology·2026
Same journal

Experimental evidence for behavioural cooling as a response to virus infection in an ectothermic vertebrate.

BMC biology·2026
Same journal

DNA damage at an early developmental stage affects neurodevelopment in sterlet (Acipenser ruthenus).

BMC biology·2026
See all related articles

Related Experiment Video

Updated: Feb 2, 2026

In Vivo Calcium Imaging of Taste-Induced Neural Responses in Adult Drosophila
06:30

In Vivo Calcium Imaging of Taste-Induced Neural Responses in Adult Drosophila

Published on: March 7, 2025

1.3K

Detecting neural assemblies in calcium imaging data.

Jan Mölter1,2, Lilach Avitan1, Geoffrey J Goodhill3,4

  • 1Queensland Brian Institute, The University of Queensland, Brisbane, 4072, Australia.

BMC Biology
|November 30, 2018
PubMed
Summary
This summary is machine-generated.

Identifying neural assemblies from calcium imaging data is challenging. The graph theory (SGC) and independent component analysis (ICA) algorithms, along with a modified principal component analysis (Promax), show superior performance in detecting these neuronal groups.

Keywords:
ClusteringPopulation codingSpontaneous activity

More Related Videos

Functional Calcium Imaging in Developing Cortical Networks
16:33

Functional Calcium Imaging in Developing Cortical Networks

Published on: October 22, 2011

39.7K
Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software
06:50

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Published on: October 30, 2018

9.9K

Related Experiment Videos

Last Updated: Feb 2, 2026

In Vivo Calcium Imaging of Taste-Induced Neural Responses in Adult Drosophila
06:30

In Vivo Calcium Imaging of Taste-Induced Neural Responses in Adult Drosophila

Published on: March 7, 2025

1.3K
Functional Calcium Imaging in Developing Cortical Networks
16:33

Functional Calcium Imaging in Developing Cortical Networks

Published on: October 22, 2011

39.7K
Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software
06:50

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Published on: October 30, 2018

9.9K

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Data Analysis

Background:

  • Neuronal activity often occurs in coordinated groups known as neural assemblies.
  • Reliably identifying these assemblies from calcium imaging data is a significant challenge.
  • The comparative performance of various assembly-detection algorithms is not well understood.

Purpose of the Study:

  • To evaluate and compare the performance of several recently developed algorithms for detecting neural assemblies in calcium imaging data.
  • To determine which algorithms are most effective at recovering known assembly structures.

Main Methods:

  • Generated large surrogate calcium imaging datasets with known assembly structures.
  • Tested algorithms including independent component analysis (ICA), principal component analysis (Promax), similarity analysis (CORE), singular value decomposition (SVD), graph theory (SGC), and frequent item set mining (FIM-X).
  • Evaluated algorithm performance based on parameters like array size, number of assemblies, assembly size, overlap, and signal strength, and applied them to zebrafish optic tectum data.

Main Results:

  • The graph theory (SGC) and independent component analysis (ICA) algorithms, along with a modified Promax algorithm, demonstrated strong performance in recovering simulated assemblies.
  • Principal component analysis-Promax (PCA-Promax) and frequent item set mining (FIM-X) showed weaker performance and greater dependence on factors like neural array size.
  • The SGC algorithm yielded assemblies most consistent with averaged responses in zebrafish optic tectum data.

Conclusions:

  • The choice of algorithm significantly impacts the identification of neural assemblies from calcium imaging data.
  • Certain algorithms, specifically SGC and ICA, consistently outperform others in detecting neural assemblies.
  • Previous research utilizing these algorithms may require re-evaluation in light of algorithm-dependent performance variations.