Skip to main content

Cognitive neuroscience and artificial intelligence

Guest Editors:
Zhiyi Chen: Third Military Medical University, China
Ali Yadollahpour: University of Sheffield, UK


BMC Neuroscience welcomed submissions to our Collection on cognitive neuroscience and AI, which aimed to promote the integration of knowledge and advances in both fields. The ultimate goal of the Collection is advancing our understanding of human cognition and developing more sophisticated AI systems, and it covers a range of topics that lie at the intersection of cognitive neuroscience and AI, including but not limited to: neural network models of cognition, deep learning algorithms for neuroimaging data, brain-computer interfaces, and cognitive architectures for artificial intelligence.

Meet the Guest Editors

Back to top

Zhiyi Chen: Third Military Medical University, China

Dr Zhiyi Chen is currently appointed to a professorship at the Third Military Medical University School of Psychology, and is the designated director of its Experimental Research Center for Medical and Psychological Science. His research expertise lies in computational neuroimaging, machine learning and human decision making (e.g., human procrastination behaviors). Dr Chen's recent work involves meta-research and open science, especially concerning authorship inequalities, overfitting issues and improving the quality and reliability of AI-based neuropsychiatric diagnoses. He currently serves on the board of executives in the Chinese Open Science Network (COSN).
 

Ali Yadollahpour: University of Sheffield, UK

Ali Yadollahpour holds a BSc in Applied Physics, and MSc and PhD in Medical Physics. He served as assistant professor in Medical Physics at Ahvaz Jundishapur University of Medical Sciences (AJUMS), and currently serves as honorary lecturer in the University of Sheffield Department of Psychology. His main research interests are cognitive and computational neuroscience and neurorehabilitation. His MS and PhD theses focused on epilepsy modelling and treatment using brain stimulation. He has supervised more than 20 theses as well as more than 20 clinical and preclinical research projects. The main focus of these projects was developing multidisciplinary approaches for treatment of neurocognitive disorders, modelling the treatment response and/or disease modelling using computational approaches. Currently, he is working on developing personalized diagnostic and therapeutic methods for neurological disorders including depression and tinnitus.

About the collection

BMC Neuroscience is calling for submissions to our Collection on cognitive neuroscience and AI. Creating artificial neural networks that can replicate the functions and pattern recognition abilities of the human brain remains one of the primary goals of AI development today. Likewise, as artificial intelligence grows more advanced, it has become a useful guide in helping us increase our understanding of how our own brains function. The two fields have become more and more reciprocal in recent years, and advancements in the fields of cognitive science and AI have never been more connected.

With this Collection, we aim to promote the integration of knowledge and advances in both fields, with the ultimate goal of advancing our understanding of human cognition and developing more sophisticated AI systems. The Collection will cover a range of topics that lie at the intersection of cognitive neuroscience and AI, including but not limited to: neural network models of cognition, deep learning algorithms for neuroimaging data, brain-computer interfaces, and cognitive architectures for artificial intelligence. The collection will publish original research that contributes to the advancement of our understanding of the relationship between human cognition and artificial intelligence.

We welcome submissions from researchers and educators in the fields of neuroscience, artificial intelligence, psychology, and related disciplines, as well as professionals in the technology and pharmaceutical industries who are interested in the intersection of these fields. Topics of interest to this Collection include, but are not limited to:

•  Using neural networks to model cognitive processes
•  Neural network models of cognitive processing
•  Deep learning algorithms for neuroimaging applications
•  Cognitive architectures for developing intelligent AI systems
•  Integration of neuroimaging techniques and AI algorithms for predicting treatment outcomes in neurological disorders
•  Investigating the neural basis of attentional control using machine learning approaches
•  Developing explainable AI models for understanding neural mechanisms of learning and memory
•  Using cognitive neuroscience to guide the development of machine learning models for clinical decision-making
•  Investigations into the effects of non-invasive brain stimulation on neural networks and its implications for AI and cognitive neuroscience


Image credit: Peshkova / Getty Images / iStock

  1. The behavioral photosensitivity of animals could be quantified via the optomotor response (OMR), for example, and the luminous efficiency function (the range of visible light) should largely rely on the repert...

    Authors: Kiyono Mizoguchi, Mayu Sato, Rina Saito, Mayu Koshikuni, Mana Sakakibara, Ran Manabe, Yumi Harada, Tamaki Uchikawa, Satoshi Ansai, Yasuhiro Kamei, Kiyoshi Naruse and Shoji Fukamachi
    Citation: BMC Neuroscience 2023 24:67
    Content type: Research Published on:

  2. Previous studies have demonstrated the potential of machine learning (ML) in classifying physical pain from non-pain states using electroencephalographic (EEG) data. However, the application of ML to EEG data ...

    Authors: Tyler Mari, Jessica Henderson, S. Hasan Ali, Danielle Hewitt, Christopher Brown, Andrej Stancak and Nicholas Fallon
    Citation: BMC Neuroscience 2023 24:50
    Content type: Research Published on:

Submission Guidelines

Back to top

This Collection welcomes submission of Research Articles, Data Notes, Case Reports, Study Protocols, and Database Articles. Before submitting your manuscript, please ensure you have read our submission guidelines. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Cognitive neuroscience and artificial intelligence" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Guest Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests.