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Gosavi, R. S.

Publications and source records attributed to Gosavi, R. S..

3 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↗

Brain plasticity for visual words: Elementary school teachers can drive changes in weeks that rival those formed over years

This study aims to investigate the impact of vocabulary acquisition through short-term classroom learning and its relation to broader forms of vocabulary learning through long-term exposure in daily life. Through a two week of "learning sprint" in collaboration with a local elementary school and EEG-Steady State Visual Evoked Potentials (EEG-SSVEP) paradigm, we assessed new vocabulary learning in first and second graders within their pedagogical environment. We then compared the results with the word frequency effect, a well-established phenonmenon that reflects long-term vocabulary learning. After two weeks of classroom instruction, newly acquired words elicited neural responses similar to those of high-frequency words, with the effect significantly correlated with childrens phonological decoding skills. Additionally, we successfully replicated the word frequency effect using the SSVEP paradigm for the first time. These findings highlight the potential of the "learning sprint" model for conducting neuroscience research in authentic educational settings, thereby fostering a stronger connection between education and neuroscience.

neuroscience↗