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Introduction to Methods in Artificial Intelligence and Cognitive Neurology.
1Department of Neurology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA.
Dental Clinics of North America
|March 13, 2026
Summary
Artificial intelligence (AI) and machine learning (ML) are explained, focusing on neural networks. The article compares AI
Area of Science:
- Interdisciplinary science bridging artificial intelligence (AI), machine learning (ML), and cognitive neurology.
- Focus on computational neuroscience and artificial neural networks (ANNs).
- Exploration of neurodegenerative disorders and their impact on cognitive functions.
Background:
- Artificial intelligence and machine learning have seen significant advancements.
- Neural networks are a popular implementation of machine learning.
- Cognitive neurology studies the neural basis of cognition and its disorders.
Purpose of the Study:
- To introduce fundamental concepts of artificial intelligence and machine learning.
- To provide an overview of cognitive neurology, including neurodegenerative disorders.
- To draw parallels between human cognitive functions and artificial neural network capabilities.
Main Methods:
- Review of the history and advancements in artificial intelligence and machine learning.
- Nontechnical explanation of neural network architecture and function.
- Survey of major neurodegenerative disorders and their associated neuroanatomical correlates.
Main Results:
- Established the foundational principles of AI, ML, and neural networks.
- Detailed the key aspects of cognitive neurology and neurodegenerative diseases.
- Identified specific human cognitive functions and their attempted recapitulation by ANNs.
Conclusions:
- Artificial neural networks offer a computational framework for understanding cognitive functions.
- Parallels exist between biological neural processing and artificial neural network models.
- Further research can leverage AI and neurology to advance understanding of the brain.
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