AIMC Topic: Acoustic Stimulation
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Sensory cortex is optimized for prediction of future input.
eLife
Jun 18, 2018
Neurons in sensory cortex are tuned to diverse features in natural scenes. But what determines which features neurons become selective to? Here we explore the idea that neuronal selectivity is optimized to represent features in the recent sensory pas...
Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification.
Journal of neural engineering
Feb 15, 2018
OBJECTIVE: Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG ...
Single-ended prediction of listening effort using deep neural networks.
Hearing research
Dec 27, 2017
The effort required to listen to and understand noisy speech is an important factor in the evaluation of noise reduction schemes. This paper introduces a model for Listening Effort prediction from Acoustic Parameters (LEAP). The model is based on met...
Cortical frequency-specific plasticity is independently induced by intracortical circuitry.
Neuroscience letters
Dec 21, 2017
Auditory learning induces frequency-specific plasticity in the auditory cortex. Both the auditory cortex and thalamus are involved in the cortical plasticity; however, the precise role of the intracortical circuity remains unclear until the contribut...
Music viewed by its entropy content: A novel window for comparative analysis.
PloS one
Oct 17, 2017
Polyphonic music files were analyzed using the set of symbols that produced the Minimal Entropy Description, which we call the Fundamental Scale. This allowed us to create a novel space to represent music pieces by developing: (a) a method to adjust ...
Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users.
Hearing research
Nov 30, 2016
Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in nois...
Persons with Hearing Disabilities
Speech Perception
Audiometry, Speech
Perceptual Masking
Signal Processing, Computer-Assisted
Prosthesis Design
Acoustics
Aged, 80 and over
Sound Spectrography
Acoustic Stimulation
Young Adult
Humans
Comprehension
Cochlear Implantation
Adult
Neural Networks, Computer
Electric Stimulation
Middle Aged
Algorithms
Noise
Speech Intelligibility
Aged
Cochlear Implants
An integrated model of pitch perception incorporating place and temporal pitch codes with application to cochlear implant research.
Hearing research
Nov 12, 2016
Although the neural mechanisms underlying pitch perception are not yet fully understood, there is general agreement that place and temporal representations of pitch are both used by the auditory system. This paper describes a neural network model of ...
Neural network training as a dissipative process.
Neural networks : the official journal of the International Neural Network Society
Jun 21, 2016
This paper analyzes the practical issues and reports some results on a theory in which learning is modeled as a continuous temporal process driven by laws describing the interactions of intelligent agents with their own environment. The classic regul...
Cortical Transformation of Spatial Processing for Solving the Cocktail Party Problem: A Computational Model(1,2,3).
eNeuro
Feb 2, 2016
In multisource, "cocktail party" sound environments, human and animal auditory systems can use spatial cues to effectively separate and follow one source of sound over competing sources. While mechanisms to extract spatial cues such as interaural tim...
A neural-based vocoder implementation for evaluating cochlear implant coding strategies.
Hearing research
Jan 14, 2016
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and ref...
Voice Quality
Loudness Perception
Psychoacoustics
Humans
Cochlear Implants
Neural Networks, Computer
Persons with Hearing Disabilities
Computer Simulation
Auditory Pathways
Speech Perception
Cochlear Implantation
Time Factors
Speech Acoustics
Female
Stochastic Processes
Electroencephalography
Auditory Threshold
Adult
Electric Stimulation
Signal Processing, Computer-Assisted
Male
Prosthesis Design
Middle Aged
Acoustic Stimulation
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