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Related Concept Videos

Brain Waves01:23

Brain Waves

Brain waves are electrical signals generated by the neurons in the brain, which are regularly monitored to measure mental activities. Brain waves and their frequency ranges can be measured using an electroencephalogram or EEG. There are four main types of brain waves, each with distinct characteristics:
Muscle Stimulation Frequency01:22

Muscle Stimulation Frequency

The contraction strength of muscles is regulated by motor neurons, which modulate the frequency of action potentials dispatched to the motor units based on the body's requirements. This process of varying the muscle stimulation frequency allows muscles to contract with a force that is precisely tailored to the needs of the moment, whether lifting a feather or a heavy box.
Wave summation
At low firing rates, motor neurons induce individual twitch contractions in muscle fibers. These twitches...
Determination of Expected Frequency01:08

Determination of Expected Frequency

Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...

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Related Experiment Video

Updated: May 11, 2026

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Higher frequency network activity flow predicts lower frequency node activity in intrinsic low-frequency BOLD

Sahil Bajaj1, Bhim Mani Adhikari, Mukesh Dhamala

  • 1Department of Physics and Astronomy, Georgia State University, Atlanta, Georgia, United States of America.

Plos One
|May 22, 2013
PubMed
Summary

The brain

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Published on: July 21, 2021

Area of Science:

  • Neuroscience
  • Brain Imaging
  • Network Analysis

Background:

  • The brain exhibits electrical and metabolic activity even at rest.
  • Low-frequency oscillations (LFO) in functional magnetic resonance imaging (fMRI) blood oxygen level-dependent (BOLD) signals reflect this resting-state activity.
  • These intrinsic oscillations can dynamically change over seconds to minutes.

Purpose of the Study:

  • To investigate the dynamic nature of default-mode network (DMN) activity during resting conditions.
  • To analyze temporal changes in low-frequency oscillations (LFO) within the DMN using fMRI BOLD signals.
  • To explore relationships between network activity, frequency bands, and structural connectivity.

Main Methods:

  • Utilized wavelet-transform based time-frequency analysis on fMRI BOLD signals.
  • Focused on the default-mode network (DMN) including posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), left middle temporal cortex (LMTC), and left angular gyrus (LAG).
  • Analyzed spectral power, causal flow patterns, and correlated network activity with diffusion tensor imaging (DTI) data.

Main Results:

  • Intrinsic LFO within the DMN show significant dynamic changes over time.
  • Positive linear relationships observed between slow-4 network flow and slow-5 node activity, and slow-3 network flow and slow-4 node activity.
  • Net causal flow in the slow-3 band correlated with structural connectivity (fiber count) from diffusion tensor imaging (DTI) data.

Conclusions:

  • The resting brain is not entirely at rest, exhibiting dynamic network activity.
  • Higher frequency network activity flow can predict lower frequency node activity.
  • Brain network activity flow reflects underlying structural connectivity.