The spatial patterning of each neurodegenerative disease relates closely to a distinct structural and functional network in the human brain. The presentation will mainly describe how network-sensitive neuroimaging methods such as resting-state functional magnetic resonance imaging (FMRI) and diffusion MRI can shed light on brain network dysfunction associated with pathology and cognitive decline from preclinical to clinical dementia. The speaker will introduce network-based neurodegeneration model followed by supporting brain imaging evidence of this model using a series of studies in preclinical, prodromal, and clinical dementia. Specifically, findings from two independent datasets on how amyloid and cerebrovascular pathology influence brain functional networks crosssectionally and longitudinally in individuals with mild cognitive impairment and dementia will be presented.
The presentation will also shed light on how brain white matter abnormalities such as extracellular water increases and axonal damage relate to amyloid and cerebrovascular burden and influence cognition. Furthermore, the speaker will demonstrate early network vulnerability patterns in cognitively normal elderly at risk of cognitive decline ordementia. For example, longitudinal brain functional network organizational changes such as loss of functional segregation are related to processing speed decline in cognitively normal older adults. The presentation will also touch on some recent findings o n how structural network disruption relate to cognition in stroke patients and how age impacts brain network dynamics and performance. These findings underscore the importance of longitudinal design and push beyond region-specific differences to connect early brain network changes with pathology and cognitive decline. Further developed with machine learning approaches, multimodal networkspecific imaging signatures will help revealdisease mechanisms and facilitate early detection, prognosis, and intervention design for at-risk populations.
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