Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Aliasing

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...

Sampling Theorem

Sampling Theorem

In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.

Properties of Fourier series II

Properties of Fourier series II

Time scaling of signals is a crucial concept in signal processing that affects the Fourier series representation without altering its coefficients. The process modifies the fundamental frequency, thereby changing how the series represents the signal over time. This principle is essential in various applications, including audio and image processing, where signal manipulation is frequent. Understanding function symmetries is fundamental to simplifying the Fourier series.
A function f(t) is...

Bandpass Sampling

Bandpass Sampling

In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....

Expected Frequencies in Goodness-of-Fit Tests

Expected Frequencies in Goodness-of-Fit Tests

A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n) to the number of categories (k).

IR Spectrometers

IR Spectrometers

There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...

You might also read

Related Articles

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

Sort by

Same author

Timing is everything: brain energy metabolism in delirium.

Age and ageing·2026

Same author

Modulation of pulmonary IL-21 expression during latent TB and M. tuberculosis/SIV coinfection.

JCI insight·2026

Same author

The effect of induced humility on anger and P3b responses to frustrating events.

Social cognitive and affective neuroscience·2026

Same author

Work challenges and cancer-related cognitive impairment: level of education accounts for unmet needs beyond cognitive impairment severity.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer·2026

Same author

Major Lifetime Discrimination Exposure Accelerates Brain Microstructural Aging: Diffusion MRI Evidence From MIDUS.

Biopsychosocial science and medicine·2026

Same author

Functional and Clinical: An Explainable Deep Learning Model for Multimodal Alzheimer's Disease Classification.

Brain and behavior·2026

Search research articles

Related Experiment Video

Updated: Jul 8, 2025

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

Test-retest reliability of spectral parameterization by 1/f characterization using SpecParam.

Daniel J McKeown¹, Anna J Finley², Nicholas J Kelley³

¹The Mind Space Laboratory, Department of Psychology, Faculty of Society and Design, Bond University, Gold Coast, QLD 4229, Australia.

Cerebral Cortex (New York, N.Y. : 1991)

|December 15, 2023

Summary

This summary is machine-generated.

SpecParam reliably measures neural activity, but performs poorly with eyes open. This electroencephalography analysis tool shows good test-retest reliability for periodic and aperiodic brain activity.

Keywords:

EEG FOOOF aperiodic activity oscillations psychometrics

More Related Videos

Evanescent Field Based Photoacoustics: Optical Property Evaluation at Surfaces

Evanescent Field Based Photoacoustics: Optical Property Evaluation at Surfaces

Published on: July 26, 2016

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

Related Experiment Videos

Last Updated: Jul 8, 2025

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

Evanescent Field Based Photoacoustics: Optical Property Evaluation at Surfaces

Evanescent Field Based Photoacoustics: Optical Property Evaluation at Surfaces

Published on: July 26, 2016

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

Area of Science:

Neuroscience
Computational Neuroscience
Psychometrics

Background:

SpecParam (formerly FOOOF) quantifies periodic and aperiodic neural activity from EEG.
It may offer a non-invasive measure of excitation-inhibition balance.
Psychometric properties of SpecParam are largely unknown, limiting its application in cognitive neuroscience.

Purpose of the Study:

To assess the test-retest reliability of SpecParam's neural activity metrics.
To evaluate SpecParam's performance across different resting states and cognitive tasks.
To determine the suitability of SpecParam for measuring individual differences in brain activity.

Main Methods:

Intraclass correlation coefficients (ICCs) were used to examine test-retest reliability.
Data were collected across three sessions: 90 minutes apart and 30 days later.
Participants were 49 healthy young adults at rest (eyes open/closed) and during cognitive tasks (Math, Music, Memory).

Main Results:

Good ICCs (>0.70) were found for aperiodic exponent and offset.
Good ICCs (>0.66) were observed for periodic activity (alpha/beta power, frequency, bandwidth) across conditions.
SpecParam showed poor performance and reliability for eyes-open resting data, especially at non-central sites.

Conclusions:

SpecParam generally provides reliable metrics for individual differences in parameterized neural activity.
The technique shows promise for characterizing brain activity during cognitive tasks and eyes-closed rest.
Further research is needed to validate SpecParam's use with eyes-open resting EEG data.