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Korisky, A.

Publications and source records attributed to Korisky, A..

6 recordsLinked to original sources

Bringing Attention to Education: Revisiting the Neural Mechanisms of Selective Attention in Naturalistic Learning

In the context of education, attention can be considered the gateway for learning, yet it remains unclear which neural mechanisms of attention identified under controlled laboratory conditions are most relevant when children engage in meaningful learning. Here, we addressed this question by experimentally manipulating attention while 5th- and 6th-grade students learned novel educational content from their own teacher. Working in partnership with an experienced classroom teacher, we co-developed naturalistic auditory and visual learning streams and manipulated whether students prioritized or ignored the speech. Using school-based electroencephalography and temporal response function modeling, we examined whether attention modulated early sensory or later stages of cortical speech processing. Attention selectively modulated speech processing at approximately 170 ms, with no evidence for modulation at earlier sensory stages, supporting a predominant role for late-stage attentional selection during learning. Importantly, individual differences in attentional modulation were associated with learning: students who more strongly increased neural tracking of the speech when it was task-relevant learned more effectively from spoken instruction. The same late-stage neural mechanism also distinguished students whom their teacher independently identified as stronger attenders during everyday classroom learning. Together, these findings connect late-stage attentional modulation across experimental neural dynamics, individual learning outcomes, and teacher observations of classroom behavior. More broadly, they demonstrate how studying attention within educationally meaningful contexts can help identify which neural mechanisms are most consequential for successful learning.

neuroscience↗

Auditory attention reorganizes the phase alignment of neural oscillations

Auditory attention enables the selection of behaviorally relevant sounds in dynamic environments, supporting the flexible allocation of neural resources over time. Although neural entrainment has been proposed as a mechanism for temporal prediction in audition, human studies have largely emphasized changes in response strength, leaving unresolved whether attention reorganizes the temporal alignment of entrained activity across hierarchical cortical networks. Here, we introduce the Selective Temporal Alignment of Components (STAC) framework to dissociate stimulus-driven and attention-controlled dynamics using non-invasive EEG. In a series of experiments across two independent adolescent cohorts (n = 79), Reliable Components Analysis (RCA) revealed two dissociable entrained networks with distinct spatial, functional, and attentional profiles: a sensory-driven network that remained tightly stimulus-locked and a frontal-auditory network that exhibited systematic attention-dependent phase shifts. These phase dynamics were consistent across independent cohorts and stable within individuals, and critically, predicted performance on a standardized neuropsychological measure of auditory attention. Together, these findings establish selective temporal alignment as a robust and behaviorally relevant neural mechanism underlying auditory attentional control.

neuroscience↗

Toward precision EEG: Assessing the reliability of individual-level ERPs across EEG Systems

Event-related potentials (ERPs) are among the most established tools for studying the neural mechanisms of perception and cognition. Advancing toward precision EEG, however, places new demands for a better understanding of how reliable neural markers are at the individual subject level. We conducted two complementary experiments to examine the reliability of N100 and P300 components in an auditory oddball paradigm with three sounds (Standard, Target, and Novel). In Experiment 1, we evaluated the consistency at both the group level and the individual level across four EEG systems: one research-grade wired system (BioSemi) and three mobile devices--Smarting, DSI-24, and EPOC X. At the group level, all systems demonstrated the canonical N100 and P300 components; however, the EPOC X system showed a significantly reduced signal-to-noise ratio compared to the others. At the individual level, temporal and spatial clustering analyses showed that N100 and P300 components were detectable in most individuals (70-85%), with additional significant responses appearing outside this range. We further calculated the similarity of individual responses across participants ("typicality index"), which revealed highly consistent responses to Standard and Novel sounds, alongside divergent patterns of responses to Targets. In Experiment 2, we assessed the within-participant reliability of N100 and P300 using a test-retest design. Results indicated high within-participant consistency of response patterns for all three stimuli, demonstrating that individual ERPs remain reliably stable over time, even when they deviate from canonical group-level patterns. The current study contributes to the ongoing discussion regarding the utility and reliability of ERP-based metrics for precision imaging and highlights important methodological considerations for their practical implementation.

neuroscience↗

Neurophysiological Patterns of Attention and Distraction during Realistic Virtual-Reality Classroom Learning in Adults with and without ADHD

Many people, and particularly individuals with Attention Deficit (Hyperactivity) Disorder (AD(H)D), find it difficult to maintain attention during classroom learning. However, traditional paradigms used to evaluate attention do not capture the complexity and dynamic nature of real-life classrooms. Using a novel Virtual Reality platform, coupled with measurement of neural activity, eye-gaze and skin conductance, here we studied the neurophysiological manifestations of attention and distractibility, under realistic learning conditions. Individuals with AD(H)D exhibited higher neural responses to irrelevant sounds and reduced speech tracking of the teacher, relative to controls. Additional neurophysiological measures, such the power of alpha-oscillations and frequency of gaze-shifts away from the teacher, contributed to explaining variance in self-reported AD(H)D symptoms across the sample. These ecologically-valid findings provide critical insight into the neurophysiological mechanisms underlying individual differences in the capacity for sustained attention and the proneness to distraction and mind-wandering, experienced in real-life situations.

neuroscience↗

An ecological investigation of the effect of background noise on speech processing in a Virtual Classroom

Many real-life situations can be extremely noisy. Psychoacoustic studies have shown that background noise can have a detrimental effect on the ability to process and understand speech. However, most studies use stimuli and task designs that are highly artificial, limiting their generalization to more realistic contexts. Moreover, to date, we do not fully understand the neurophysiological consequences of trying to pay attention to speech in a noisy place. To address this lab to real-life gap and increase the ecological validity of speech in noise research, here we introduce a novel audiovisual Virtual Reality (VR) experimental platform. Combined with neurophysiological measurements of neural activity (EEG), eye-gaze and skin conductance (GSR) we studied the effects of background noise in a realistic context where the ability to process and understand continuous speech is especially important: A VR Classroom. Participants (n=32) sat in a VR Classroom and were told to pay attention to mini-lecture segments by a virtual teacher. Trials were either Quiet or contained background construction noise, emitted from outside the classroom window, which was either Continuous (drilling) or Intermittent (air hammers). Result show that background noise had a detrimental effect on learning outcomes, which was also accompanied by reduced neural tracking of the teachers speech. Comparison of the two noise types showed that the intermittent construction noise was more disruptive than continuous noise, as index by both behavioral and neural measures, and it also elicited higher skin-conductance levels, reflecting heightened arousal. Interesting, eye-gaze dynamics were not affected by the presence of noise. This study advances our understanding of the neurophysiological effects of background noise and extends it to more ecologically relevant contexts. It also emphasizes the role that temporal dynamics play for processing speech in noise, highlighting the need to consider the features of realistic noises, as we expand speech in noise research to increasingly realistic circumstances.

neuroscience↗

Neural Speech-Tracking During Selective Attention and Attention-Switching Between Concurrent Talkers: A spatially realistic audiovisual study

Paying attention to a target talker in multi-talker scenarios is associated with its more accurate neural-tracking relative to competing non-target speech. This "neural-bias" to target speech has largely been demonstrated in experimental setups where target and non-target speech are acoustically controlled and interchangeable. However, in real-life situations this is rarely the case. For example, listeners often look at the talker they are paying attention to while non-target speech is heard (but not seen) from peripheral locations. To enhance the ecological-relevance of attention research, here we studied whether neural-bias towards target speech is observed in a spatially realistic audiovisual context, and how this is affected by switching the identity of the target talker. Group-level results show robust neural-bias towards target speech, an effect that persisted and generalized after switching the identity of the target talker. In line with previous studies, this supports the utility of the speech-tracking approach for studying speech processing and attention in spatially realistic settings. However, a more nuanced picture emerges when inspecting data of individual participants. Although reliable neural speech-tracking could be established in most participants, this was not correlated with neural-bias or with behavioral performance, and >50% of participant showed similarly robust neural tracking of both target and non-target speech. These results indicate that neural-bias toward the target is not a ubiquitous, or necessary, marker of selective attention (at least as measured from scalp-EEG), and suggest that individuals diverge in their internal prioritization among concurrent speech, perhaps reflecting different listening strategies or capabilities under realistic conditions. Significance StatementThis work contributes to ongoing efforts to study the neural mechanisms involved in selective attention to speech under ecologically relevant conditions, emulating the type of speech materials, multisensory experience, and spatial realism of natural environments. Group-level results show that under these more realistic conditions, the hallmark signature of selective attention - namely the modulation of sensory representation, and its robustness to switches in target-identity - is conserved, at least at the group level. At the same time, results point to an underlying diversity among participants in how that this modulation manifests, raising the possibility that differences in listening strategies, motivation or personal traits lead to differences in the way that individuals encode and process competing stimuli, under ecological conditions.

neuroscience↗