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 Experiment Video

Updated: Jul 17, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

Detecting the determinism of EEG time series using a nonlinear forecasting method.

Ying-Jie Li1, Fei-Yan Fan, Yi-Sheng Zhu

  • 1Sch. of Commun. & Inf. Eng., Shanghai Univ.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|February 7, 2007
PubMed
Summary

This study introduces a new method to assess time series determinism. Schizophrenia electroencephalogram (EEG) signals were found to be non-deterministic, unlike chaotic time series.

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

Acupuncture vs Sham Non-Acupoint Acupuncture for Irritable Bowel Syndrome: A Systematic Review and Meta-Analysis.

Gastroenterology·2026
Same author

Evidence-Based Guidelines for the Diagnosis and Treatment of Pediatric CKD-Mineral and Bone Disorder (Version 2024).

Kidney international reports·2026
Same author

Executive Summary of Evidence-Based Guidelines for the Diagnosis and Treatment of Pediatric CKD-Mineral and Bone Disorder (Version 2024).

Kidney international reports·2026
Same author

An Innovative Diagnostic Strategy for Malignant Pleural Effusion Using Discontinuous Gradient Centrifugation.

Archives of pathology & laboratory medicine·2026
Same author

[Determination of atmospheric intermediate volatility organic compounds with thermal desorption-flow modulator comprehensive two-dimensional gas chromatography- time-of-flight mass spectrometry].

Se pu = Chinese journal of chromatography·2026
Same author

Artificial intelligence-based prognostic modeling of immunoradiotherapy in Barcelona clinic liver cancer stage C hepatocellular carcinoma: a multicenter retrospective study.

Frontiers in oncology·2026

Area of Science:

  • Time Series Analysis
  • Nonlinear Dynamics
  • Neuroscience

Background:

  • Investigating the underlying nature of time series is crucial for accurate forecasting.
  • Distinguishing deterministic patterns from random noise is a key challenge in signal processing.

Purpose of the Study:

  • To develop and apply a novel nonlinear, non-parametric forecasting method to assess time series determinism.
  • To evaluate the predictability of different types of time series, including deterministic chaotic series, Gaussian noise, and electroencephalogram (EEG) signals from patients with schizophrenia.

Main Methods:

  • Utilized a nonlinear, non-parametric forecasting approach.
  • Introduced a new definition for 'prediction effect' to quantify predictability.
  • Applied the method to analyze deterministic chaotic time series, Gaussian random noise, and schizophrenia EEG signals.

More Related Videos

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
12:03

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

Published on: May 25, 2019

Related Experiment Videos

Last Updated: Jul 17, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
12:03

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

Published on: May 25, 2019

Main Results:

  • The new method successfully identified good prediction in deterministic chaotic time series.
  • No significant predictability was found for Gaussian random noise.
  • Electroencephalogram (EEG) signals from schizophrenic patients exhibited no discernible predictability, indicating non-determinism.

Conclusions:

  • The developed forecasting method effectively differentiates deterministic from non-deterministic time series.
  • Schizophrenia EEG signals are characterized as non-deterministic, suggesting a lack of underlying deterministic processes.
  • This finding has implications for understanding the neurophysiological basis of schizophrenia.