Jha, AditiAditiJhaMiyapuram, Krishna PrasadKrishna PrasadMiyapuram2026-01-222026-01-222025-01-01[9780443416255, 9780443416248]10.1016/B978-0-443-41624-8.00020-62-s2.0-105027234570https://repository.iitgn.ac.in/handle/IITG2025/33956This chapter provides a review of the current state of research that uses electroencephalography (EEG) as a central methodological tool to explore the neural dynamics of auditory perception. Drawing from a wide array of experimental paradigms, we provide a broad overview of how EEG can be employed to study the temporal and spatial dynamics of auditory processing in naturalistic and controlled settings. Special attention is given to event-related potentials (ERPs) and frequency domain analyses that have been used to identify distinct neural signatures associated with various acoustic features, such as pitch, rhythm, and timbre, as well as higher-order processes like music perception and affective auditory responses. The chapter reviews methodological advances and challenges in using EEG to decode complex auditory stimuli, highlighting the benefits of integrating machine learning and computational modeling. Further, we discuss the role of context, stimulus type, and listener variables in shaping auditory neural responses, emphasizing interdisciplinary research. This review offers a comprehensive overview of studying auditory cognition from the psychophysical and neuroscience perspectives.en-USfalseauditory perception | brain waves | cerebral cortex | electrodes | Electroencephalography | event-related potentials | machine learningBook Chapter195-2081 January 20250chBook Chapter