Poster No:
1637
Submission Type:
Abstract Submission
Authors:
Ehsan Eqlimi1,2,3, Heather Read1
Institutions:
1Sensory Perception & Neuroscience Lab, Department of Biomedical Engineering, University of Connecticut, Storrs, CT, USA, 2WAVES Research Group, Department of Information Technology, Ghent University, Ghent, Belgium, 3Data Science Team, Department of Process and Quality, AZORG Hospital (formerly OLV), Aalst, Belgium
First Author:
Ehsan Eqlimi
Sensory Perception & Neuroscience Lab, Department of Biomedical Engineering|WAVES Research Group, Department of Information Technology, Ghent University|Data Science Team, Department of Process and Quality, AZORG Hospital (formerly OLV)
University of Connecticut, Storrs, CT, USA|Ghent, Belgium|Aalst, Belgium
Co-Author:
Heather Read
Sensory Perception & Neuroscience Lab, Department of Biomedical Engineering
University of Connecticut, Storrs, CT, USA
Introduction:
Brain alpha oscillations, central to cognitive processes, face evolving interpretations. In the auditory context, uncertainty arises from auditory alpha's existence, EEG measurability, and potential visual alpha dependence. A pivotal 1999 finding challenged expectations, suggesting alpha's inhibitory role as a neural cyclic 'brake' during mental activity. The causality of this relationship remains debated. Research distinguishes lower and upper alpha frequencies, crucial for identifying peaks in diverse brain regions during cognitive tasks. Alpha oscillations play a key role in parsing sensory information, emphasizing power, frequency, and phase in tasks requiring perceptual parsing and temporal binding. EEG studies on alpha oscillations focus on parsing brain responses into components, offering insight into short-term information processing. Yet, understanding prolonged behaviors, especially in goal-oriented tasks with continuous and complex information, remains a gap. Our HD-EEG study addresses this, investigating alpha oscillation modulations during attentive listening to 5-minute speeches with and without multitalker noise. We explore their predictive role in memory and retention performance, aiming to enhance comprehension of alpha oscillations' extended cognitive engagement.
Methods:
23 listeners underwent 4 speeches without and 3 with multitalker background noise, covering diverse Belgian culture topics. The 64-channel EEG data was recorded continuously during attentive listening, followed by a written exam 45 minutes later to assess scores for all 7 speeches. After preprocessing, three alpha oscillation features were extracted: alpha peak frequency, alpha peak power, and long-range temporal correlations (LRTC). Linear mixed-effect modeling analyzed multitalker noise impact and its linear relationship with exam scores. Time-frequency analysis using a GAMM compared topics and background noise effects. Nonparametric cluster-based permutation testing assessed channel influence on alpha manifestation.
Results:
Despite a significant decline in exam scores with background noise, no difference in alpha peak power and frequency was observed. However, alpha LRTC increased during multitalker noise, correlating negatively with exam scores, suggesting a role in speech perception and memory in noise. Increased synchronization of alpha peak frequency occurred in temporal lobes, contrasting with higher alpha peak power mainly in occipital lobes and less in temporal, central, and frontal areas. Nonparametric tests showed no significance, but alpha LRTC changed significantly with background noise, increasing in occipital and temporal regions and decreasing in the frontal region. This suggests enhanced suppression of task-irrelevant input in occipital and temporal regions, with increased task-vigilance in frontal areas. In theory, increased LRTC in occipital and temporal regions could facilitate suppression of task-irrelevant background audio and visual input. Conversely, decreased LRTC in frontal executive control areas could facilitate task-vigilance. Overall, LRTC increased across channels in the noisy condition. Analyzing the modulated alpha changes over time, measured by LRTC, inspired us to examine the evolving alpha power pattern between conditions. Although no significant difference was found in average alpha power, temporal progression analysis using GAMM uncovered a significant increase in noisy conditions in the second part of the trend (after the first minute).
Conclusions:
Results emphasize alpha oscillations' role in top-down speech attention, highlighting temporal dynamics during distractions. Heightened cognitive effort is reflected in increased alpha LRTC, suggesting implications for focused attention and speech information encoding. The two-stage alpha trend reveals initial sensory processes and a subsequent increase in effort for higher-level cognitive engagement, including mnemonic binding and memory encoding, especially evident in multitalker noise.
Language:
Speech Perception 2
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis 1
Perception, Attention and Motor Behavior:
Attention: Auditory/Tactile/Motor
Keywords:
Cognition
Electroencephaolography (EEG)
Language
Perception
Other - alpha oscillations, speech comprehension
1|2Indicates the priority used for review
Provide references using author date format
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Klimesch, W., Doppelmayr, M., Schwaiger, J., Auinger, P., & Winkler, T. (1999). 'Paradoxical' alpha synchronization in a memory task. Cognitive Brain Research, 7(4), 493–501.
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