About this Research Topic
The human brain is an incredibly complex and dynamic system that controls our thoughts, emotions, and behavior. Cognitive, social, developmental, and translational neuroscience are fields that seek to understand how the brain functions and how it can go wrong in neurological and psychiatric disorders. In recent years, there has been a surge of interest in applying artificial intelligence (AI) techniques to these fields, with the hope of accelerating discoveries and improving patient outcomes. AI techniques, such as machine learning and deep learning, are well-suited to analyzing large and complex datasets that are characteristic of neuroscience research. These techniques can be used to identify patterns in brain activity, predict outcomes in response to different interventions, and develop new diagnostic and therapeutic approaches for neurological and psychiatric disorders. For example, AI-based models can be used to analyze neuroimaging data to identify biomarkers for early detection of Alzheimer's disease or to predict treatment outcomes for depression.
The use of AI techniques in neuroscience research also presents unique opportunities to study complex social behaviors and interactions, which have traditionally been challenging to study using traditional research methods. For example, AI techniques can be used to analyze social network data and predict the spread of infectious diseases or to study the dynamics of social interaction in autism spectrum disorder. However, the use of AI in neuroscience research also raises important ethical considerations and challenges. For example, there is a risk of bias in the data and algorithms used in AI models, which could lead to inaccurate or unfair predictions. Additionally, the interpretability of deep learning models is often limited, making it difficult to understand how they arrive at their predictions.
This research topic aims to explore the latest research in AI applications for human cognitive, social, developmental, and translational neuroscience and to highlight the opportunities and challenges associated with these techniques. By bringing together experts from different fields, this research topic will provide a comprehensive overview of the current state-of-the-art in AI applications in neuroscience research and identify opportunities for future collaborations and translational research efforts. Ultimately, this special issue aims to promote the responsible use of AI techniques in neuroscience research and clinical practice and to improve outcomes for patients with neurological and psychiatric disorders.
Topics of Interest include, but are not limited to:
• Machine learning and deep learning approaches for analyzing neuroimaging data in cognitive and social neuroscience research
• AI-based models for predicting cognitive and social outcomes in developmental neuroscience research
• Diagnosis and treatment of neurological and psychiatric disorders using AI techniques
• Applications of AI for studying social behavior and interactions in neuroscience research
• AI-based models for translational neuroscience research and drug discovery
• Ethical considerations and challenges associated with AI applications in neuroscience research and clinical practice
The use of AI techniques in neuroscience research also presents unique opportunities to study complex social behaviors and interactions, which have traditionally been challenging to study using traditional research methods. For example, AI techniques can be used to analyze social network data and predict the spread of infectious diseases or to study the dynamics of social interaction in autism spectrum disorder. However, the use of AI in neuroscience research also raises important ethical considerations and challenges. For example, there is a risk of bias in the data and algorithms used in AI models, which could lead to inaccurate or unfair predictions. Additionally, the interpretability of deep learning models is often limited, making it difficult to understand how they arrive at their predictions.
This research topic aims to explore the latest research in AI applications for human cognitive, social, developmental, and translational neuroscience and to highlight the opportunities and challenges associated with these techniques. By bringing together experts from different fields, this research topic will provide a comprehensive overview of the current state-of-the-art in AI applications in neuroscience research and identify opportunities for future collaborations and translational research efforts. Ultimately, this special issue aims to promote the responsible use of AI techniques in neuroscience research and clinical practice and to improve outcomes for patients with neurological and psychiatric disorders.
Topics of Interest include, but are not limited to:
• Machine learning and deep learning approaches for analyzing neuroimaging data in cognitive and social neuroscience research
• AI-based models for predicting cognitive and social outcomes in developmental neuroscience research
• Diagnosis and treatment of neurological and psychiatric disorders using AI techniques
• Applications of AI for studying social behavior and interactions in neuroscience research
• AI-based models for translational neuroscience research and drug discovery
• Ethical considerations and challenges associated with AI applications in neuroscience research and clinical practice
Keywords: Artificial intelligence, Ethics, AI Applications
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.
