Deep learning models in cognitive sciences
- Submission status
- Closed
- Submission deadline
Deep learning is understood as a form of machine learning which imitates how humans acquire knowledge. It first gained a lot of attention as it has enabled machines to approach and tackle cognitive tasks at which humans excel in a human-like fashion - including object recognition, speech processing, and cognitive planning. More recently, cognitive scientists have turned to deep learning models to study human cognition and its neural underpinnings.
This Collections welcomes research from the areas of Psychology, Neuroscience or other Cognitive Sciences, using deep learning approaches to study cognitive phenomena.
Editors
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Ioannis Delis
University of Leeds, UK
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Mohammed Hasanuzzaman
Munster Technological University, Ireland
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Shelli Kesler
University of Texas at Austin, USA
Ioannis Delis is a Lecturer and Assistant Professor at the School of Biomedical Sciences, University of Leeds. His research interests lie in the area of Computational Cognitive Neuroscience with a focus on perceptual decision-making, multi-sensory processing and motor control. His lab combines large-scale data analysis and computational modelling with behavioural experiments and neuroimaging/neurophysiology techniques to understand the neural and behavioural mechanisms underlying sensorimotor behaviours in healthy humans and clinical populations. Dr Delis has been an Editorial Board Member for Scientific Reports since 2019.
Mohammed Hasanuzzaman is a Funded Investigator at ADAPT Centre - A World-Leading Science Foundation of Ireland Research Centre, Ireland. He is also a Lecturer at the Department of Computer Science at Munster Technological University, Ireland, and a Research Associate at GREYC-CNRS UMR 6071 Research Centre, France. His research interests and activities over the past years have been in Artificial Intelligence, mainly spanning Natural Language Processing (NLP), Data Science, Data Mining, Multimodal Learning (image, video, and text), Social Media Analytics, and Machine Learning/Deep Learning applications for various domains. Dr Hasanuzzaman has been an Editorial Board Member for Scientific Reports since 2022.
Shelli Kesler is an Associate Professor at the University of Texas at Austin. She is a Cognitive Neuroscientist who studies the neural mechanisms of cancer-related cognitive impairment. Specifically, she uses neuroimaging and machine learning to identify biotypes of cognitive impairment and to predict which patients are at highest risk. Dr Kesler has been an Editorial Board Member for Scientific Reports since 2019.
