Multiyear variability of very-low-frequency ambient noise

2019 ◽  
Vol 146 (4) ◽  
pp. 2849-2849
Author(s):  
Anthony I. Eller ◽  
David L. Bradley ◽  
Kevin D. Heaney
Keyword(s):  
Ambient Noise ◽  
Low Frequency ◽  
Very Low Frequency

A review of DREA's very low‐frequency ambient noise program

1978 ◽  
Vol 64 (S1) ◽  
pp. S45-S45
Author(s):  
I. A. Fraser ◽  
H. M. Merklinger ◽  
J. H. Stockhausen
Keyword(s):  
Ambient Noise ◽  
Low Frequency ◽  
Very Low Frequency

Long term very low frequency ambient noise: A window to the ocean and atmosphere

2021 ◽  
Vol 149 (4) ◽  
pp. A90-A90
Author(s):  
Anthony I. Eller ◽  
Kevin D. Heaney ◽  
James J. Murray ◽  
David L. Bradley
Keyword(s):  
Ambient Noise ◽  
Low Frequency ◽  
Very Low Frequency

Global examination of the wind-dependence of very low frequency underwater ambient noise

2016 ◽  
Vol 139 (3) ◽  
pp. 1110-1123 ◽  
Author(s):  
Stephen M. Nichols ◽  
David L. Bradley
Keyword(s):  
Ambient Noise ◽  
Low Frequency ◽  
Very Low Frequency

The Attenuation of Very Low Frequency Brain Oscillations in Transitions from a Rest State to Active Attention

2009 ◽  
Vol 23 (4) ◽  
pp. 191-198 ◽  
Author(s):  
Suzannah K. Helps ◽  
Samantha J. Broyd ◽  
Christopher J. James ◽  
Anke Karl ◽  
Edmund J. S. Sonuga-Barke
Keyword(s):  
Brain Activity ◽  
Sampling Rate ◽  
Low Frequency ◽  
Future Research ◽  
Adhd Symptoms ◽  
Default Mode ◽  
Very Low Frequency ◽  
Wide Range ◽  
Interference Hypothesis ◽  
Mode Interference

Background: The default mode interference hypothesis ( Sonuga-Barke & Castellanos, 2007 ) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized to the VLFO pattern. Here, we tested these predictions using DC-EEG recordings within and outside of a previously identified network of electrode locations hypothesized to reflect DMN activity (i.e., S3 network; Helps et al., 2008 ). Method: 24 young adults (mean age 22.3 years; 8 male), sampled to include a wide range of ADHD symptoms, took part in a study of rest to task transitions. Two conditions were compared: 5 min of rest (eyes open) and a 10-min simple 2-choice RT task with a relatively high sampling rate (ISI 1 s). DC-EEG was recorded during both conditions, and the low-frequency spectrum was decomposed and measures of the power within specific bands extracted. Results: Shift from rest to task led to an attenuation of VLFO activity within the S3 network which was inversely associated with ADHD symptoms. RT during task also showed a VLFO signature. During task there was a small but significant degree of synchronization between EEG and RT in the VLFO band. Attenuators showed a lower degree of synchrony than nonattenuators. Discussion: The results provide some initial EEG-based support for the default mode interference hypothesis and suggest that failure to attenuate VLFO in the S3 network is associated with higher synchrony between low-frequency brain activity and RT fluctuations during a simple RT task. Although significant, the effects were small and future research should employ tasks with a higher sampling rate to increase the possibility of extracting robust and stable signals.

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