About this Research Topic
In recent years, the achievements made by scientists have been exceptional, leading to major advancements in the fast-growing field of Human Neuroscience. In this regard, engineering approaches to cognitive neuroscience have always been important and have attracted the attention of world scientists in this field. A Research Topic focused on Cognitive Neuroscience allows for a comprehensive examination of recent advancements and developments in the field and can provide a platform for researchers to share their findings and insights with others. This allows for a comprehensive examination of the current state of the field and provides a valuable resource for the scientific community and beyond. Additionally, it can help to raise awareness of the importance of evaluating cognitive neuroscience and encourage further research in this area, ultimately leading to the development of more effective treatments for individuals with difficulties in this field.
This Research Topic is focused on new insights, novel developments, current challenges, latest discoveries, recent advances, and future perspectives in the field of Cognitive Neuroscience. The Research Topic solicits brief, forward-looking contributions from researchers that describe the state of the art, outlining recent developments and major accomplishments that have been achieved and that need to occur to move the field forward. Authors are encouraged to identify the greatest challenges in the sub-disciplines, and how to address those challenges.
The goal of this Research Topic is to shed light on the progress made in the past decade in the Cognitive Neuroscience field, and on its future challenges to provide a thorough overview of the field. This article collection will inspire, inform, and provide direction and guidance to researchers in the field. We aim to improve the understanding of the relation between cognitive processes and resting state networks, the dynamics of cognitive processes, and applications of machine learning methodologies on the biomedical signal/image and the relationship between findings. Methods and applications in cognitive neuroscience using biomedical signal/image processing aim to highlight the latest experimental techniques and methods used to investigate fundamental questions about the mental processes involved in cognition.
We welcome several types of submissions: Original Research Articles, Review Articles, Method Articles, Clinical Trials, Case Reports, and Mini-Review Articles. The aim of the topic is to address key subjects about the methodology, application, and interpretation of biomedical modalities in cognitive neuroscience, including:
• Evaluating working memory, attention, decision-making, learning, source memory, cognitive control, computational speed, impulsive behaviors, and risk-taking.
• Interpretation of EEG-fMRI findings in cognitive neuroscience
• EEG and fMRI dynamic connectivity
• Deep learning and other artificial intelligence methods for cognitive neuroscience
• Advances and applications of biomedical modalities in cognitive neuroscience
• Definition of cognitive neural networks using biomedical modalities
• Assessment of sensorimotor interactions using biomedical modalities
• Localization of cognitive functions in the brain using biomedical modalities
• Resting-state networks and their relations with cognitive neural networks
This Research Topic is focused on new insights, novel developments, current challenges, latest discoveries, recent advances, and future perspectives in the field of Cognitive Neuroscience. The Research Topic solicits brief, forward-looking contributions from researchers that describe the state of the art, outlining recent developments and major accomplishments that have been achieved and that need to occur to move the field forward. Authors are encouraged to identify the greatest challenges in the sub-disciplines, and how to address those challenges.
The goal of this Research Topic is to shed light on the progress made in the past decade in the Cognitive Neuroscience field, and on its future challenges to provide a thorough overview of the field. This article collection will inspire, inform, and provide direction and guidance to researchers in the field. We aim to improve the understanding of the relation between cognitive processes and resting state networks, the dynamics of cognitive processes, and applications of machine learning methodologies on the biomedical signal/image and the relationship between findings. Methods and applications in cognitive neuroscience using biomedical signal/image processing aim to highlight the latest experimental techniques and methods used to investigate fundamental questions about the mental processes involved in cognition.
We welcome several types of submissions: Original Research Articles, Review Articles, Method Articles, Clinical Trials, Case Reports, and Mini-Review Articles. The aim of the topic is to address key subjects about the methodology, application, and interpretation of biomedical modalities in cognitive neuroscience, including:
• Evaluating working memory, attention, decision-making, learning, source memory, cognitive control, computational speed, impulsive behaviors, and risk-taking.
• Interpretation of EEG-fMRI findings in cognitive neuroscience
• EEG and fMRI dynamic connectivity
• Deep learning and other artificial intelligence methods for cognitive neuroscience
• Advances and applications of biomedical modalities in cognitive neuroscience
• Definition of cognitive neural networks using biomedical modalities
• Assessment of sensorimotor interactions using biomedical modalities
• Localization of cognitive functions in the brain using biomedical modalities
• Resting-state networks and their relations with cognitive neural networks
Keywords: Brain Connectivity, Working Memory, Attention, Decision-making, Learning, Source memory, Cognitive Control, Computational Speed, Impulsive Behaviors, Risk-Taking, gambling task, EEG, fMRI, fNIRS, Machine Learning, Deep Learnin, Artificial Intelligence, Simultaneous EEG-fMRI, Emotion, Cognitive Neuroscience
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
