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

Deconvolution01:20

Deconvolution

655
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
655
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

1.7K
Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
1.7K
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

1.1K
In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
1.1K
Convolution Properties I01:20

Convolution Properties I

644
Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
644
Interference and Superposition of Waves01:07

Interference and Superposition of Waves

7.3K
When two waves of the same nature occur in the same region simultaneously, they result in interference. Interference of waves implies that the net effect of the waves is the sum of the individual waves' effects. However, it does not imply that the individual waves affect the propagation of other waves.
Interference occurs in mechanical waves, such as sound waves, waves on a string, and surface water waves. Mechanical waves correspond to the physical displacement of particles. Hence,...
7.3K
Interference and Decay01:16

Interference and Decay

549
Forgetting is a complex cognitive phenomenon influenced by several factors, among which interference and decay are particularly prominent. These processes explain why individuals often struggle to retrieve specific information from memory, leading to lapses in recall that can be observed in everyday situations.
Interference occurs when competing memories hinder the retrieval of particular information. It can be classified into two types: proactive and retroactive interference. Proactive...
549

You might also read

Related Articles

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

Sort by
Same author

Beyond gray matter: unveiling the critical role of white matter in Alzheimer's disease.

Progress in neuro-psychopharmacology & biological psychiatry·2026
Same author

Domain-General Decoupling and Context-Specific Buffering: Transdiagnostic Eye-Tracking Biomarkers of ASD and ADHD During Naturalistic Viewing.

bioRxiv : the preprint server for biology·2026
Same author

Unique Amygdala Signatures and Shared Prefrontal Deficits in Autism: Mapping Social Heterogeneity via Naturalistic functional Magnetic Resonance Imaging.

bioRxiv : the preprint server for biology·2026
Same author

Glymphatic Dysfunction, Brain Damage, and Clinical Disability in Spinocerebellar Ataxia Type 3.

Movement disorders : official journal of the Movement Disorder Society·2026
Same author

Dynamic Alterations of Functional Systems in Alzheimer's Disease: A Co-Activation Pattern Analysis.

Human brain mapping·2026
Same author

Dynamic brain connectivity patterns induced by oxytocin: An fMRI Co-Activation pattern analysis study.

Molecular psychiatry·2026

Related Experiment Video

Updated: Mar 8, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

5.2K

Imperfect (de)convolution may introduce spurious psychophysiological interactions and how to avoid it.

Xin Di1, Richard C Reynolds2, Bharat B Biswal1

  • 1Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey.

Human Brain Mapping
|January 21, 2017
PubMed
Summary

Centering the psychological variable in psychophysiological interaction (PPI) analysis is crucial. This ensures accurate brain connectivity findings by preventing spurious correlations, especially in functional MRI studies.

Keywords:
connectivityfMRImean centeringpsychophysiological interactions

More Related Videos

Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback
05:43

Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback

Published on: May 23, 2019

5.9K
A Two-interval Forced-choice Task for Multisensory Comparisons
07:13

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

11.5K

Related Experiment Videos

Last Updated: Mar 8, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

5.2K
Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback
05:43

Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback

Published on: May 23, 2019

5.9K
A Two-interval Forced-choice Task for Multisensory Comparisons
07:13

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

11.5K

Area of Science:

  • Neuroimaging
  • Cognitive Neuroscience
  • Functional Magnetic Resonance Imaging (fMRI)

Background:

  • Psychophysiological interaction (PPI) is a standard fMRI method to assess condition-specific functional connectivity.
  • PPI involves multiplying experimental design (psychological variable) with seed region activity (physiological variable).
  • Non-centering the psychological variable can introduce confounds, mimicking true connectivity.

Purpose of the Study:

  • To investigate the impact of psychological variable centering on PPI analysis.
  • To identify and mitigate confounds in PPI analysis arising from imperfect hemodynamic modeling.
  • To validate methods for accurate assessment of condition-specific functional connectivity.

Main Methods:

  • Analysis of two block-designed fMRI datasets (visual checkerboard, hemispheric tasks).
  • Comparison of PPI results with and without centering the psychological variable.
  • Inclusion of a deconvolve-reconvolved physiological covariate as an alternative correction.

Main Results:

  • Uncorrected PPI analyses (without centering) yielded false positives, showing connectivity between regions with known baseline connections.
  • Centering the psychological variable or adding a deconvolve-reconvolved covariate effectively suppressed these spurious findings.
  • Corrected PPI results aligned with direct tests of condition-specific coupling differences.

Conclusions:

  • Centering the psychological variable is essential for valid PPI analysis in fMRI.
  • Alternatively, incorporating a deconvolve-reconvolved physiological covariate can correct for confounds.
  • These methods ensure accurate interpretation of condition-dependent brain connectivity.