AIMC Topic: Auditory Perception

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Optimal multimodal feature combination and classifier selection for music-based EEG signal analysis.

Computers in biology and medicine
PURPOSE: Music perception is a fundamental human experience, integral to cognitive and emotional processing, making it a crucial area for neuroscientific investigation. This study examined the neural dynamics underlying music perception and identifie...

Unsupervised Accuracy Estimation for Brain-Computer Interfaces Based on Selective Auditory Attention Decoding.

IEEE transactions on bio-medical engineering
OBJECTIVE: Selective auditory attention decoding (AAD) algorithms process brain data such as electroencephalography to decode to which of multiple competing sound sources a person attends. Example use cases are neuro-steered hearing aids or communica...

Exploring Neural Dynamics in the Auditory Telencephalon of Crows Using Functional Ultrasound Imaging.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Crows, renowned for advanced cognitive abilities and vocal communication, rely on intricate auditory systems. While the neuroanatomy of corvid auditory pathways is partially explored, the underlying neurophysiological mechanisms are largely unknown. ...

Distinct processing stages of cross-modal conflict in schizophrenia: The role of auditory cortex underactivation.

Schizophrenia research
BACKGROUND: The cross-modal conflict deficit is a key feature of schizophrenia. However, it remains largely unknown whether cross-modal conflict in schizophrenia diverges at distinct processing stages and its potential association with the auditory c...

Robot or human musicians? The modulating role of perceived performer on how music influences food choices.

Applied psychology. Health and well-being
Previous research has shown that music robots may reshape people's perceptions of music and health-related behaviors. We investigated how the perceived identity of the music performers (humans or robots) influenced people's music-induced mental image...

Predicting artificial neural network representations to learn recognition model for music identification from brain recordings.

Scientific reports
Recent studies have demonstrated that the representations of artificial neural networks (ANNs) can exhibit notable similarities to cortical representations when subjected to identical auditory sensory inputs. In these studies, the ability to predict ...

Enhancing music recognition using deep learning-powered source separation technology for cochlear implant users.

The Journal of the Acoustical Society of America
Cochlear implant (CI) is currently the vital technological device for assisting deaf patients in hearing sounds and greatly enhances their sound listening appreciation. Unfortunately, it performs poorly for music listening because of the insufficient...

A Deep Learning Based Approach to Synthesize Intelligible Speech with Limited Temporal Envelope Information.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Envelope waveforms can be extracted from multiple frequency bands of a speech signal, and envelope waveforms carry important intelligibility information for human speech communication. This study aimed to investigate whether a deep learning-based mod...

Hierarchical Learning of Statistical Regularities over Multiple Timescales of Sound Sequence Processing: A Dynamic Causal Modeling Study.

Journal of cognitive neuroscience
Our understanding of the sensory environment is contextualized on the basis of prior experience. Measurement of auditory ERPs provides insight into automatic processes that contextualize the relevance of sound as a function of how sequences change ov...

Perceptual Effects of Adjusting Hearing-Aid Gain by Means of a Machine-Learning Approach Based on Individual User Preference.

Trends in hearing
This study investigated a method to adjust hearing-aid gain by use of a machine-learning algorithm that estimates the optimal setting of gain parameters based on user preference indicated in an iterative paired-comparison procedure. Twenty hearing-im...