Neural attentional-filter mechanisms of listening success in middle-aged and older individuals

Successful listening crucially depends on intact attentional filters that separate relevant from irrelevant information. Research into their neurobiological implementation has focused on two potential auditory filter strategies: the lateralization of alpha power and selective neural speech tracking. However, the functional interplay of the two neural filter strategies and their potency to index listening success in an ageing population remains unclear. Using electroencephalography and a dual-talker task in a representative sample of listeners (N = 155; age=39–80 years), we here demonstrate an often-missed link from single-trial behavioural outcomes back to trial-by-trial changes in neural attentional filtering. First, we observe preserved attentional–cue-driven modulation of both neural filters across chronological age and hearing levels. Second, neural filter states vary independently of one another, demonstrating complementary neurobiological solutions of spatial selective attention. Stronger neural speech tracking but not alpha lateralization boosts trial-to-trial behavioural performance. Our results highlight the translational potential of neural speech tracking as an individualized neural marker of adaptive listening behaviour.

The impact of neural attentional filters on listening behavior in a large cohort of aging individuals

Successful listening crucially depends on intact attentional filters that separate relevant from irrelevant information. Research into their neurobiological implementation has focused on one of two auditory filter strategies: the lateralization of alpha power and selective neural speech tracking. However, the functional interplay of the two neural filter strategies and their potency to index listening success in an aging population remains unclear. Using electroencephalography and a dual-talker task in a representative sample of aging listeners (N=155; age=39–80 years), we here demonstrate an often-missed link from single-trial behavioral outcomes back to trial-by-trial changes in neural attentional filtering. First, we observed preserved attentional– cue-driven modulation of both neural filters across chronological age and hearing levels. Second, neural filter states varied independently of one another, demonstrating a functional trade-off between distinct neurobiological attentional filter mechanisms. Stronger neural speech tracking but not alpha lateralization boosted trial-to-trial behavioral performance. Our results highlight the translational potential of neural speech tracking as an individualized neural marker of adaptive listening behavior.Significance statementSuccessful listening requires a form of attentional filtering into behaviorally relevant and irrelevant acoustic information. Most previous studies have focused on one of two candidate neural filter strategies: the lateralization of alpha power and selective neural speech tracking. Closing the gap between hitherto separate lines of research, we used electroencephalography and a dual-talker task in a large sample of aging listeners to directly probe the functional relevance of state- and trait-level changes in these neural filter strategies to listening success. We demonstrate the co-existence of largely independent neural filters that establish alternating regimes of strong alpha lateralization versus neural speech tracking. Additionally, our results emphasize the utility of neural speech tracking over alpha lateralization as a potential neural marker of an individual’s adaptive listening behavior.

A Hybrid Neural Filter (HNF) Based on Adaptive Median and Weiner Techniques for Reducing Speckle Noise of Ultrasound Liver Tumor Images

Pre-processing of image is considered to be an important aspect medical image analysis in order to enhance its quality. Noise reduction is performed for improvement in the visual quality and removing redundant image values. Ways of pre-processing of image are a necessity, for removing the noise and for quality enhancement of the image. Before applying any approach on medical images, measures used to pre-process seem to be vital for limiting the abnormalities’ findings with no influence from background of the medical image. In this work, a filter is proposed based on Adaptive Median and Weiner Hybrid Neural Filter for noise reduction. The review of filtering techniques is implemented using MATLAB platform, followed by comparison of results with different filtering techniques to show the system effectiveness.

Individual listening success explained by synergistic interaction of two distinct neural filters

Successful speech comprehension requires the listener to differentiate relevant from irrelevant sounds. Recent neurophysiological studies have typically addressed one of two candidate neural filter solutions for this problem: the selective neural tracking of speech in auditory cortex via the modulation of phase-locked cortical responses, or the suppression of irrelevant inputs via alpha power modulations in parieto-occipital cortex. However, empirical evidence on their relationship and direct relevance to behavior is scarce. Here, a large, age-varying sample (N=76, 39–70 years) underwent a challenging dichotic listening task. Irrespective of listeners’ age, measures of behavioral performance, neural speech tracking, and alpha power lateralization all increased in response to spatial-attention cues. Under most challenging conditions, individual listening success was predicted best by the synergistic interaction of these two distinct neural filter strategies. Trial-by-trial fluctuations of lateralized alpha power and ignored-speech tracking did not co-vary, which demonstrates two neurobiologically distinct filter mechanisms.