Decoding texture perception during oral processing of model solid foods (biscuits) using electromyography and...

Elucidating the relationship between food textural properties and neural signal responses is essential for understanding oral perception mechanisms. This knowledge may also provide a neuroscientific foundation for the precise modulation of food texture. In this study, model solid foods (biscuits) with textural gradients were prepared by modulating their resistant starch (RS) and hazelnut contents. The effects of formulation components on textural characteristics and their underlying neurophysiological mechanisms were elucidated through the integration of confocal laser scanning microscopy, low-field nuclear magnetic resonance spectroscopy, texture profile analysis, biomimetic mastication simulation, dynamic sensory evaluation, electromyography (EMG), and electroencephalography (EEG). The increased hardness and chewiness induced by RS addition were attributed to enhanced structural resistance and energy dissipation. Conversely, the incorporation of hazelnut granules increased the fracturability and granularity of the biscuits by modifying moisture distribution and introducing structural heterogeneities. Dynamic sensory evaluation revealed that textural attributes evolved systematically with mastication duration, transitioning from hardness- and fracturability-dominated perception in the initial phase to viscosity-dominant perception in the latter phase. RS elevated sensory intensity ratings for hardness and chewiness while decreasing viscosity intensity (p < 0.05), whereas hazelnut granules addition enhanced perceived granularity (p < 0.05). The EMG evaluation revealed that high RS samples were associated with increased burst duration, amplitude, root mean square values, and cumulative muscle activity (p < 0.05). In EEG recordings, amplitude variations at specific electrodes (C4, FC3, and FC4) were strongly correlated with perceived hardness and chewiness (r > 0.7). Our findings suggest that such neural indices may serve as objective biomarkers for distinguishing samples based on their textural attributes, particularly hardness and chewiness. This study therefore provides valuable insights into the quantitative characterization of dynamic texture perception during food oral processing.