Brain and cognitive sciences

An MIT study has been making strides towards developing computational models that mimic the human auditory system, which could enhance the design of hearing aids, cochlear implants, and brain-machine interfaces. These computational models stem from advances in machine learning. The study found that internal representations generated by deep neural networks often mirror those within the…

A study by Massachusetts Institute of Technology (MIT) researchers has indicated that computational models that perform auditory tasks could speed up the development of improved hearing aids, cochlear implants, and brain-machine interfaces. In the study, the largest ever conducted into deep neural network-based models trained to perform hearing-related functions, it was found that most mimic…

Scientists at MIT have made significant progress in developing advanced computational models that can emulate the human auditory system, which could be pivotal in improving hearing aids, cochlear implants, and brain-machine interfaces. The researchers used deep neural networks—a type of artificial intelligence (AI) that imitates the human brain—to conduct the most extensive study so far…

Computational models that imitate how the human auditory system works may hold promise in developing technologies like enhanced cochlear implants, hearing aids, and brain-machine interfaces, a recent study from the Massachusetts Institute of Technology (MIT) reveals. The study focused on deep neural networks, machine learning-derived computational models that stimulate the basic structure of the human…

An MIT study has taken a significant step towards the development of computational models capable of mimicking the structure and function of the human auditory system. The models could have applications in the production of improved hearing aids, cochlear implants, and brain-machine interfaces. The researchers discovered that modern machine learning-derived computational models are progressing towards…

A recent study from MIT suggests that computational models built using machine learning could closely mimic the structure and function of the human auditory system. This discovery could potentially help researchers in designing more effective hearing aids, cochlear implants, and brain-machine interfaces. In the largest-ever examination of deep learning neural networks trained for auditory tasks, the…

A team from the Massachusetts Institute of Technology (MIT) has found that machine learning (ML) models can effectively mimic and understand the human auditory system, potentially helping to improve technologies such as cochlear implants, hearing aids and brain-machine interfaces. These findings are based on the largest-ever study of deep neural networks used to perform auditory…

MIT researchers have found that computational models derived from machine learning, designed to mimic the human auditory system, have the potential to improve hearing aids, cochlear implants, and brain-machine interfaces. They are moving closer to this goal by using these models in the largest study yet of deep neural networks trained to perform auditory tasks.…

MIT researchers have found that computational models based on machine learning that simulate the human auditory system are drawing closer to potentially helping in the creation of improved hearing aids, cochlear implants and brain-machine interfaces. The study is the most comprehensive comparison so far made between these computer models and the human auditory system. Notably,…

A study from MIT has suggested that machine-learning computational models can help design more effective hearing aids, cochlear implants, and brain-machine interfaces by mimicking the human auditory system. The study was based on deep neural networks which, when trained on auditory tasks, create internal representations similar to those generated in the human brain when processing…

A new study from MIT suggests that computational models rooted in machine learning are moving closer to simulating the structure and function of the human auditory system. Such technology could improve the development of hearing aids, cochlear implants, and brain-machine interfaces. The study analyzed deep neural networks trained for auditory tasks, finding similarities with the…

MIT researchers have found that computational models designed with machine learning techniques are becoming more accurate in mimicking the structure and function of the human auditory system. They believe these models could assist in the development of improved hearing aids, cochlear implants and brain-machine interfaces. In an extensive study of deep neural networks trained for…