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Exploring Alzheimer's disease: a comprehensive brain connectome-based survey.
Zhang, Lu; Qu, Junqi; Ma, Haotian; Chen, Tong; Liu, Tianming; Zhu, Dajiang.
Afiliación
  • Zhang L; Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA.
  • Qu J; Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA.
  • Ma H; Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA.
  • Chen T; Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA.
  • Liu T; Department of Computer Science, The University of Georgia, Athens, GA 30602, USA.
  • Zhu D; Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA.
Psychoradiology ; 4: kkad033, 2024.
Article en En | MEDLINE | ID: mdl-38333558
ABSTRACT
Dementia is an escalating global health challenge, with Alzheimer's disease (AD) at its forefront. Substantial evidence highlights the accumulation of AD-related pathological proteins in specific brain regions and their subsequent dissemination throughout the broader area along the brain network, leading to disruptions in both individual brain regions and their interconnections. Although a comprehensive understanding of the neurodegeneration-brain network link is lacking, it is undeniable that brain networks play a pivotal role in the development and progression of AD. To thoroughly elucidate the intricate network of elements and connections constituting the human brain, the concept of the brain connectome was introduced. Research based on the connectome holds immense potential for revealing the mechanisms underlying disease development, and it has become a prominent topic that has attracted the attention of numerous researchers. In this review, we aim to systematically summarize studies on brain networks within the context of AD, critically analyze the strengths and weaknesses of existing methodologies, and offer novel perspectives and insights, intending to serve as inspiration for future research.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Psychoradiology Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Psychoradiology Año: 2024 Tipo del documento: Article