Perspectives of Artificial Intelligence (AI) in Aging Neuroscience

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Computational Neuroscience and Neuroinformatics".

Deadline for manuscript submissions: 20 February 2025 | Viewed by 391

Special Issue Editor


E-Mail Website
Guest Editor
School of Computer Science, University of Lincoln, Lincoln LN6 7TS, UK
Interests: aging neuroscience; artificial gravity training; brain aging markers; brain language mapping; cognition; computerized cognitive training; functional connectivity; network neuroscience; neuroplasticity; sleep disorders

Special Issue Information

Dear Colleagues,

Over the past decade, the application of artificial intelligence in medicine and neuroscience has undergone exponential growth. Advances in big data acquisition and deep learning models have revolutionized aging neuroscience methodologies, particularly in the following areas: 1) the early detection and diagnosis of neurodegenerative conditions, 2) data fusion and processing in multi-modal neuroscientific data, 3) AI-powered cognitive and behavioral modeling, 4) drug discovery and development, and 5) chatbot applications and robotic assistance for independent living.

The aim of this Special Issue is to provide a comprehensive roadmap highlighting perspectives and challenges regarding AI methodologies in aging neuroscience. We welcome articles of all types that offer valuable insights into the following domains:

  • Identification of subtle patterns in neuroscientific data indicative of the onset of neurodegeneration;
  • AI tools for more accurate functional and structural mapping of age-related physiological and pathological changes;
  • Machine learning techniques for improving predictions of chronological aging;
  • AI-powered outcome measures for evaluating interventions and drugs aimed at preventing or delaying the onset of neurodegeneration;
  • Chatbots, robotic systems, and generative AI applications that promote active and healthy aging;
  • Natural Language Processing models serving as coaching or recommendation systems in both physiological and pathological aging.

Dr. Christos Frantzidis
Guest Editor

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Keywords

  • aging neuroscience
  • artificial intelligence
  • brain aging
  • big data acquisition
  • chatbots
  • deep learning
  • generative AI
  • robotic assistance
  • virtual coaches for active aging

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Published Papers

This special issue is now open for submission.
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