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

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software06:50

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

9.9K
We present two analytical protocols that can be used to analyze intracranial electroencephalography data using the Statistical Parametric Mapping (SPM) software: time-frequency statistical parametric mapping analysis for neural activity, and dynamic causal modeling of induced responses for intra- and inter-regional...
9.9K
Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI10:35

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI

33.3K
Simultaneous electroencephalography (EEG) and functional Magnetic Resonance imaging (fMRI) is a powerful neuroimaging tool. However, the inside of an MRI scanner forms a difficult environment for EEG data recording and safety must be considered whenever operating EEG equipment inside a scanner. Here, we present an optimised EEG-fMRI data acquisition...
33.3K
Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation06:33

Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation

12.3K
We present a protocol for concurrent collection of EEG/fMRI data, and synchronized MR clock signal recording. We demonstrate this method using a unique paradigm whereby subjects receive ‘cold glove’ instructions during scanning, and EEG/fMRI data are recorded along with hand temperature measurements both before and after hypnotic...
12.3K
Correlation of Experimental Data01:23

Correlation of Experimental Data

480
Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
480
Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data09:09

Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data

10.2K
To investigate flow velocities and directionality of filamentous-actin at the T cell immunological synapse, live-cell super-resolution imaging is combined with total internal reflection fluorescence and quantified with spatio-temporal image correlation spectroscopy.
10.2K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

34.4K
Neuroimaging researchers typically consider the brain's response as the mean activity across repeated experimental trials and disregard signal variability over time as "noise". However, it is becoming clear that there is signal in that noise. This article describes the novel method of multiscale entropy for quantifying brain signal variability in the time...
34.4K

You might also read

Related Articles

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

Sort by
Same author

Discovering Novel intracranial EEG Biomarkers of Seizure Generating Tissue through Time-Frequency Analysis.

medRxiv : the preprint server for health sciences·2026
Same author

Functional remodeling of the parasubthalamic nucleus drives alcohol drinking escalation in dependence.

bioRxiv : the preprint server for biology·2026
Same author

Detrended fluctuation analysis of amygdala-hippocampal beta synchrony reveals network rigidity in depression associated with temporal lobe epilepsy.

Journal of neural engineering·2026
Same author

Dual-engram architecture within a single striatal cell type distinctly controls alcohol relapse and extinction.

Neuron·2026
Same author

Artificial intelligence for adaptive neuromodulation in drug-resistant epilepsy.

Epilepsia·2026
Same author

Optimization of cortico-cortical spectral response analysis parameters for seizure onset zone localization.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2026
Same journal

Multimodal Contrastive Spatiotemporal Self-Organizing Neural Networks for In-Home Activity Learning of Mild Cognitive Impairment.

IEEE journal of biomedical and health informatics·2026
Same journal

Integrating Multi-View Residue Graph and Protein Language Model for Cell-Penetrating Peptide Prediction via Global-Local Graph Aggregation and Cross-Attentive Fusion.

IEEE journal of biomedical and health informatics·2026
Same journal

An Ultra-Lightweight Cross-scale Attention Mamba Network for Accurate Skin Lesion Segmentation.

IEEE journal of biomedical and health informatics·2026
Same journal

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

IEEE journal of biomedical and health informatics·2026
Same journal

stDGCN: A dual-augmentation graph convolutional network for identifying spatial domains with attention mechanism.

IEEE journal of biomedical and health informatics·2026
Same journal

Patient-specific Biomechanical Investigation of Percutaneous Pulmonary Valves: Towards the Integration of Routinely Acquired Clinical Data and Fluid-structure Interaction Simulations.

IEEE journal of biomedical and health informatics·2026
See all related articles

Related Experiment Video

Updated: Jan 20, 2026

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

Inference on Long-Range Temporal Correlations in Human EEG Data.

Rachel J Smith, Hernando C Ombao, Daniel W Shrey

    IEEE Journal of Biomedical and Health Informatics
    |September 4, 2019
    PubMed
    Summary
    This summary is machine-generated.

    We developed a moving-block bootstrap method to calculate confidence intervals for the Detrended Fluctuation Analysis (DFA) exponent in neural time series. This approach provides reliable uncertainty measures for DFA exponents in electroencephalographic (EEG) data.

    More Related Videos

    Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI
    10:35

    Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI

    Published on: June 3, 2013

    33.3K
    Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation
    06:33

    Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation

    Published on: January 5, 2014

    12.3K

    Related Experiment Videos

    Last Updated: Jan 20, 2026

    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
    Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI
    10:35

    Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI

    Published on: June 3, 2013

    33.3K
    Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation
    06:33

    Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation

    Published on: January 5, 2014

    12.3K

    Area of Science:

    • Neuroscience
    • Signal Processing
    • Statistical Analysis

    Background:

    • Detrended Fluctuation Analysis (DFA) quantifies long-range temporal dependence in neural time series.
    • The DFA exponent reflects the strength of temporal correlations but lacks confidence intervals for single segments.
    • Existing methods do not provide uncertainty measures for DFA exponents in electroencephalographic (EEG) data.

    Purpose of the Study:

    • To introduce a statistical measure of uncertainty for the DFA exponent in EEG data.
    • To develop a method for generating confidence intervals for the DFA exponent using a moving-block bootstrap (MBB).
    • To assess the impact of time series length, artifacts, and discontinuities on DFA exponent estimation.

    Main Methods:

    • Application of a moving-block bootstrap (MBB) to electroencephalographic (EEG) data.
    • Testing the influence of time series length, artifacts, and discontinuities on the DFA exponent.
    • Validation of the MBB-DFA method using simulated and human EEG data.

    Main Results:

    • Signal lengths of approximately 5 minutes yield stable DFA exponent measurements.
    • Artifacts positively bias DFA exponent distributions, while discontinuities have a minimal impact.
    • The MBB-DFA method accurately estimates DFA exponents and their confidence intervals.

    Conclusions:

    • The proposed MBB-DFA method provides accurate confidence intervals for DFA exponents in neural data.
    • This method enables dynamic tracking of long-range temporal dependence and within-subject comparisons.
    • The approach enhances the utility of DFA by offering measures of certainty and statistical significance for neural data analysis.