Brain Connectivity, Neural Networks, and Resilience in Aging and Neurodegeneration.

IF 4.7 2区 医学 Q1 PATHOLOGY
Diego Szczupak, Lovisa LjungQvist Brinson, Christi L Kolarcik
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引用次数: 0

Abstract

The importance of complex systems has become increasingly evident in recent years. The nervous system is one such example, with neural networks sitting at the intersection of complex networks and biology. A particularly exciting feature is the resilience of complex systems. For example, the ability of the nervous system to perform even in the face of challenges that include neuronal loss, neuroinflammation, protein accumulation, axonal disruptions, and metabolic stress is an intriguing and exciting line of investigation. In neurodegenerative diseases, neural network resilience is responsible for the time between the earliest disease-linked changes and clinical symptom onset and disease diagnosis. In this way, connectivity resilience of neurons within the complex network of cells that make up the nervous system has significant implications. This review provides an overview of relevant concepts related to complex systems with a focus on the connectivity of the nervous system. It discusses the development of the neural network and how a delicate balance determines how this complex system responds to injury, with examples illustrating maladaptive plasticity. The review then addresses the implications of these concepts, methods to understand brain connectivity and neural networks, and recent research efforts aimed at understanding neurodegeneration from this perspective. This study aims to provide foundational knowledge and an overview of current research directions in this evolving and exciting area of neuroscience.

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来源期刊
CiteScore
11.40
自引率
0.00%
发文量
178
审稿时长
30 days
期刊介绍: The American Journal of Pathology, official journal of the American Society for Investigative Pathology, published by Elsevier, Inc., seeks high-quality original research reports, reviews, and commentaries related to the molecular and cellular basis of disease. The editors will consider basic, translational, and clinical investigations that directly address mechanisms of pathogenesis or provide a foundation for future mechanistic inquiries. Examples of such foundational investigations include data mining, identification of biomarkers, molecular pathology, and discovery research. Foundational studies that incorporate deep learning and artificial intelligence are also welcome. High priority is given to studies of human disease and relevant experimental models using molecular, cellular, and organismal approaches.
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