scholarly journals The balance between Bayesian inference and default mode determines the generation of tinnitus from decreased auditory input: A volume entropy‐based study

2021 ◽  
Author(s):  
Jae‐Jin Song ◽  
Jaemin Park ◽  
Ja‐Won Koo ◽  
Sang‐Yeon Lee ◽  
Sven Vanneste ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Auditory Input ◽  
Default Mode ◽  
Volume Entropy

Sensory and Cognitive Components of Auditory Processing in Individuals With Tinnitus

2019 ◽  
Vol 28 (4) ◽  
pp. 834-842
Author(s):  
Harini Vasudevan ◽  
Hari Prakash Palaniswamy ◽  
Ramaswamy Balakrishnan
Keyword(s):  
Selective Attention ◽  
Auditory Processing ◽  
Function Analysis ◽  
Event Related Potential ◽  
Oscillatory Activity ◽  
Default Mode ◽  
Auditory Selective Attention ◽  
Cognitive Components ◽  
Mode Function ◽  
Related Potentials

Purpose The main purpose of the study is to explore the auditory selective attention abilities (using event-related potentials) and the neuronal oscillatory activity in the default mode network sites (using electroencephalogram [EEG]) in individuals with tinnitus. Method Auditory selective attention was measured using P300, and the resting state EEG was assessed using the default mode function analysis. Ten individuals with continuous and bothersome tinnitus along with 10 age- and gender-matched control participants underwent event-related potential testing and 5 min of EEG recording (at wakeful rest). Results Individuals with tinnitus were observed to have larger N1 and P3 amplitudes along with prolonged P3 latency. The default mode function analysis revealed no significant oscillatory differences between the groups. Conclusion The current study shows changes in both the early sensory and late cognitive components of auditory processing. The change in the P3 component is suggestive of selective auditory attention deficit, and the sensory component (N1) suggests an altered bottom-up processing in individuals with tinnitus.

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.

Increased Default Mode Network Connectivity Following EEG Neurofeedback in PTSD

2012 ◽  
Author(s):  
Rosemarie Kluetsch ◽  
Tomas Ros ◽  
Jean Theberge ◽  
Paul Frewen ◽  
Christian Schmahl ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Network Connectivity ◽  
Default Mode ◽  
Eeg Neurofeedback

Default mode network connections supporting intra-individual variability in typically developing primary school children: An EEG study.

2020 ◽  
Vol 34 (7) ◽  
pp. 811-823
Author(s):  
Evgeniya Yu. Privodnova ◽  
Helena R. Slobodskaya ◽  
Andrey V. Bocharov ◽  
Alexander E. Saprigyn ◽  
Gennady G. Knyazev
Keyword(s):  
Primary School ◽  
School Children ◽  
Default Mode Network ◽  
Individual Variability ◽  
Primary School Children ◽  
Typically Developing ◽  
Default Mode ◽  
Network Connections

Frequency domains of resting state default mode network activity in schizophrenia

2014 ◽  
Vol 45 (01) ◽  
Author(s):  
G Mingoia ◽  
K Langbein ◽  
M Dietzek ◽  
G Wagner ◽  
S Smesny ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Network Activity ◽  
Default Mode ◽  
Frequency Domains

2092-P: Impact of Insulin Resistance on Response to a Meal by Salience, Executive Control, and Default Mode Resting State Networks in Humans

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 2092-P
Author(s):  
LETICIA ESPOSITO SEWAYBRICKER ◽  
SUSAN J. MELHORN ◽  
MARY K. ASKREN ◽  
MARY WEBB ◽  
VIDHI TYAGI ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Executive Control ◽  
Resting State ◽  
Resting State Networks ◽  
Default Mode
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