Biology subjects

Raghavan, V. S.

Publications and source records attributed to Raghavan, V. S..

3 recordsLinked to original sources

bioRxiv2026

During natural vision, semantic novelty modulates fixation-related processing in primate cortex

We sample visual scenes with short gaze fixations separated by saccades. While low-level integration is known, semantic integration of foveal vision across fixations remains unclear. We hypothesized that the brain responds to changes in semantic information from one fixation to the next, and therefore postulated a neural signal associated with semantic novelty for each saccade. Novelty was measured from different layers of a deep network on foveal vision. Only semantic, and not low- or mid-level, novelty modulated frontal and occipital fixation-related potentials in male and female human scalp EEG during natural viewing of full-length movies (3.4x106 saccades). Intracranial recordings in male and female humans (9.0x104 saccades) and female non-human primates (Macaca mulatta; 3.3x104 saccades) revealed broadband high-frequency activity modulations in scene-specific ventral visual and frontal brain areas only for semantic novelty. This modulation was stronger for movies than static images, and frontal modulation occurred early alongside occipital modulation, suggesting top-down effects. This modulation of fixation-related activity with novelty suggests that foveal representations are integrated across fixations to construct scene representations during natural viewing in primates.

neuroscience↗

bioRxiv2024

Distinct roles of SNR, speech Intelligibility, and attentional effort on neural speech tracking in noise

Robust neural encoding of speech in noise is influenced by several factors, including signal-to-noise ratio (SNR), speech intelligibility (SI), and attentional effort (AE). Yet, the interaction and distinct role of these factors remain unclear. In this study, fourteen native English speakers performed selective speech listening tasks at various SNR levels while EEG responses were recorded. Attentional performance was assessed using a repeated word detection task, and attentional effort was inferred from subjects gaze velocity. Results indicate that both SNR and SI enhance neural tracking of target speech, with distinct effects influenced by the previously overlooked role of attentional effort. Specifically, at high levels of SI, increasing SNR leads to reduced attentional effort, which in turn decreases neural speech tracking. Our findings highlight the importance of differentiating the roles of SNR, SI, and AE in neural speech processing and advance our understanding of how noisy speech is processed in the auditory pathway.

neuroscience↗

bioRxiv2024

Decoding the Unintelligible: Neural Speech Tracking in Low Signal-to-Noise Ratios

Understanding speech in noisy environments is challenging for both human listeners and speech technologies, with significant implications for hearing aid design and communication systems. Auditory attention decoding (AAD) aims to decode the attended talker from neural signals to enhance their speech and improve perception. However, whether this decoding remains reliable under severely degraded listening conditions remains unclear. In this study, we investigated selective neural tracking of the attended speaker under adverse listening conditions. Using EEG recordings in a multi-talker speech perception task with varying SNR, participants task performance--quantified through a repeated-word detection task--was analyzed as a proxy for perceptual accuracy and attentional focus, while neural responses were used to decode the attended talker. Despite substantial degradation in task performance, we found that neural tracking of attended speech persists, suggesting that the brain retains sufficient information for decoding. These findings demonstrate that even in highly challenging conditions, AAD remains feasible, offering a potential avenue for improving speech perception in brain-informed audio technologies, such as hearing aids, that leverage AAD to enhance listening experiences in real-world noisy environments.

neuroscience↗