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

You might also read

Related Articles

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

Sort by
Same author

Learning Continuous Decomposable Models Using Mutual Information and Statistical Copulas.

Entropy (Basel, Switzerland)·2026
Same author

Editorial: Challenging our understanding of neurological and neuropsychiatric disorders by means of hybrid biological and technological tools: novel approaches in computational neuroscience, neuroengineering, and artificial intelligence.

Brain research·2026
Same author

Impact of ischemic lesion on sleep related connectivity in the sensorimotor cortex.

Frontiers in neuroscience·2025
Same author

Distinct Patterns of Temporally Coded Electrical Stimulation Interfere With Long-Range Interhemispheric Coupling in a Focal Model of Epilepsy.

Neuromodulation : journal of the International Neuromodulation Society·2025
Same author

Enabling Model-Based Design for Real-Time Spike Detection.

IEEE open journal of engineering in medicine and biology·2025
Same author

Intelligent Control to Suppress Epileptic Seizures in the Amygdala: In Silico Investigation Using a Network of Izhikevich Neurons.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2025

Related Experiment Video

Updated: Aug 30, 2025

Generation and On-Demand Initiation of Acute Ictal Activity in Rodent and Human Tissue
06:45

Generation and On-Demand Initiation of Acute Ictal Activity in Rodent and Human Tissue

Published on: January 19, 2019

9.0K

Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis.

Victor Hugo Batista Tsukahara1, Jordão Natal de Oliveira Júnior1, Vitor Bruno de Oliveira Barth1

  • 1Signal Processing Laboratory, School of Engineering of São Carlos, Department of Electrical Engineering, University of São Paulo, São Carlos, Brazil.

Frontiers in Neural Circuits
|August 29, 2022
PubMed
Summary

Dynamic Bayesian Networks (DBN) model brain connectivity during epileptic seizures in rats. This approach reveals seizure dynamics and offers insights into brain circuitry, aiding epilepsy research.

Keywords:
Bayesian NetworksLocal Field Potentialsepilepsyfunctional connectivitynetwork physiology

More Related Videos

Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model
09:47

Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model

Published on: October 18, 2015

10.2K
Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
08:20

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Published on: June 6, 2015

15.4K

Related Experiment Videos

Last Updated: Aug 30, 2025

Generation and On-Demand Initiation of Acute Ictal Activity in Rodent and Human Tissue
06:45

Generation and On-Demand Initiation of Acute Ictal Activity in Rodent and Human Tissue

Published on: January 19, 2019

9.0K
Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model
09:47

Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model

Published on: October 18, 2015

10.2K
Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
08:20

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Published on: June 6, 2015

15.4K

Area of Science:

  • Neuroscience
  • Systems Biology
  • Computational Biology

Background:

  • Epilepsy is a common neurological disorder characterized by recurrent seizures.
  • The brain functions as a complex network, with seizures viewed as emergent properties of neural interactions.
  • Network physiology offers a framework to study brain dynamics and coordination in health and disease.

Purpose of the Study:

  • To apply Dynamic Bayesian Networks (DBN) for modeling Local Field Potential (LFP) data in rats experiencing induced epileptic seizures.
  • To analyze brain connectivity using threshold analytics on the number of arcs in the DBN model.

Main Methods:

  • Utilized Dynamic Bayesian Networks (DBN) to analyze Local Field Potential (LFP) data from rats with induced seizures.
  • Employed threshold analytics to determine the number of arcs representing brain connectivity.
  • Correlated DBN findings with established neurobiological knowledge from pharmacological, lesion, and optogenetic studies.

Main Results:

  • DBN analysis successfully captured the dynamic changes in brain connectivity during seizure development (ictogenesis).
  • The identified network arcs showed significant correlation with existing neurobiological findings.
  • The study uncovered novel insights, including a discontinuity between forelimb clonus and generalized tonic-clonic seizure (GTCS) dynamics.

Conclusions:

  • Dynamic Bayesian Networks (DBN) coupled with threshold analytics provide a robust tool for analyzing functional brain connectivity.
  • This methodology offers valuable insights into brain circuitry and neural dynamics in both healthy and diseased states.
  • The approach is promising for advancing the understanding of epilepsy and other neurological disorders.