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This book addresses a critical gap at the intersection of artificial intelligence, neuroscience, and the global crisis of anti-science sentiment. Unlike existing texts that focus solely on technical applications or ethical considerations, this work provides a comprehensive framework that integrates cutting-edge AI methodologies with practical strategies for navigating political and social resistance to scientific progress.
The book's unique structure bridges three essential domains: technical innovation in neuroimaging and AI applications, ethical frameworks for responsible development, and actionable solutions for combating anti-science movements. Drawing from the international research experience of the Author across Germany, USA, and Finland, it offers rare cross-cultural insights into how different political systems impact neuroscience research and innovation. The primary objectives include:
1) demonstrating how AI transforms neurological disorder detection and treatment, particularly for conditions like Alzheimer's, Multiple Sclerosis, and Long COVID
2) establishing ethical guidelines for brain-computer interfaces and predictive neuroscience
3) providing evidence-based strategies for scientists to maintain research integrity while engaging effectively with public skepticism, and
4) creating institutional models that protect academic freedom in an era of increasing political polarization.
This work is intended for multiple audiences: healthcare professionals implementing AI solutions, ethicists and policy makers developing governance frameworks, researchers seeking technical advancement, hand science advocates combating misinformation. It fills a crucial gap by being the first comprehensive text to address both the promise of AI in neuroscience and the societal challenges threatening its progress.
The book's highly structured approach progressing from technical foundations through ethical considerations to practical solutions ensures readers gain both theoretical understanding and actionable strategies. By combining rigorous scientific content with accessible explanations and real-world case studies, it serves as both an academic reference and a practical guide for navigating the complex landscape of modern neuroscience.
Sommario
Part I. Foundations and Applications.- 1. Foundations of AI in Modern Neuroscience.- 2. Multimodal Analysis and Neurological Disorders.- 3. Biomimetic AI and the Brain.- 4. AI in Clinical Neuroscience Practice.- Part II. Ethical Dimensions and Challenges.- 5. Decoding Thoughts, Encoding Ethics.- 6. Consent and Autonomy in the Age of Predictive Neuroscience.- 7. Bias and Justice in Neurological AI.- 8. Replacing Animal Models with AI.- Part III. AI in the Anti-Science Era.- 9. The Global Anti-Science Movement and Neuroscience.- 10. Market Forces and Scientific Integrity.- 11. Academic Freedom in AI Neuroscience Research.- 12. The Politics of Brain Science.- Part IV. Solutions and Resistance Models.- 13. AI as a Tool Against Misinformation.- 14. Institutional Models for Scientific Integrity in Neuroscience Research.- 15. Global Collaboration in an Age of Nationalism.- 16. Engaging the Public.- Part V. The Future Landscape.- 17. The Long View for Brain Health Research.- 18. A Framework for Responsible Innovation.- 19. Scientists as Advocates.- 20. Epilogue: Charting the Path Forward.
Info autore
Thorsten Rudroff is a Professor (Docent) in Experimental Neuroimaging at the Turku PET Centre, University of Turku and Turku University Hospital, Finland. He previously held positions as Associate Professor at the University of Iowa and Assistant Professor at Colorado State University, USA. With over 20 years of experience in neurophysiology research, he has made significant contributions to understanding fatigue and cognitive dysfunction in neurological disorders, particularly in Multiple Sclerosis and Long COVID. His scientific work includes over 90 publications in prestigious journals and the Springer book "Long COVID Fatigue," which addresses the neurological underpinnings of this prevalent post-viral syndrome. Dr. Rudroff received his Ph.D. in Neurophysiology from the University of Constance, Germany, and completed his postdoctoral training at the University of Colorado, Boulder. He is particularly passionate about leveraging artificial intelligence to advance medical research and improve patient outcomes. Dr. Rudroff serves on multiple editorial boards and has received several significant research grants from the National Institutes of Health. His current research focuses on the intersection of neuroimaging, artificial intelligence, and Long COVID, with particular emphasis on developing innovative approaches to understand and treat fatigue symptoms. Furthermore, his focus is on developing AI-driven approaches for early detection of Alzheimer’s disease through neuroimaging biomarkers.
