Altered static and dynamic functional network connectivity in Alzheimer's disease and subcortical ischemic vascular disease: shared and specific brain connectivity abnormalities

AbstractApolipoprotein E (APOE) polymorphic alleles are genetic factors associated with Alzheimer’s disease (AD) risk. Although previous studies have explored the link between AD genetic risk and static functional network connectivity (sFNC), to the best of our knowledge, no previous studies have evaluated the association between dynamic FNC (dFNC) and AD genetic risk. Here, we examined the link between sFNC, dFNC, and AD genetic risk with a reproducible, data-driven approach. We used rs-fMRI, demographic, and APOE data from cognitively normal individuals (N=894) between 42 to 95 years of age (mean = 70 years). We divided individuals into low, moderate, and high-risk groups. Using Pearson correlation, we calculated sFNC across seven brain networks. We also calculated dFNC with a sliding window and Pearson correlation. The dFNC windows were partitioned into three distinct states with k-means clustering. Next, we calculated the amount of time each subject spent in each state, called occupancy rate or OCR. We compared both sFNC and OCR, estimated from dFNC, across individuals with different genetic risk and found that both sFNC and dFNC are related to AD genetic risk. We found that higher AD risk reduces within-visual sensory network (VSN) sFNC and that individuals with higher AD risk spend more time in a state with lower within-VSN dFNC. Additionally, we found that AD genetic risk affects whole-brain sFNC and dFNC in women but not in men. In conclusion, we presented novel insights into the links between sFNC, dFNC, and AD genetic risk.

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Structural and Functional Network Connectivity Breakdown in Alzheimer's Disease Studied with Magnetic Resonance Imaging Techniques

Journal of Alzheimer s Disease ◽

10.3233/jad-2011-101854 ◽

2011 ◽

Vol 24 (3) ◽

pp. 455-474 ◽

Cited By ~ 47

Author(s):

Massimo Filippi ◽

Federica Agosta

Keyword(s):

Magnetic Resonance Imaging ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Magnetic Resonance ◽

Imaging Techniques ◽

Network Connectivity ◽

Functional Network ◽

Resonance Imaging ◽

Functional Network Connectivity ◽

Magnetic Resonance Imaging Techniques

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P1-395: FUNCTIONAL NETWORK CONNECTIVITY CHANGES IN EARLY AND LATE ONSET ALZHEIMER'S DISEASE

Alzheimer s & Dementia ◽

10.1016/j.jalz.2018.06.403 ◽

2006 ◽

Vol 14 (7S_Part_8) ◽

pp. P453-P454

Author(s):

Lorenzo Pini ◽

Cristina Geroldi ◽

Roberta Baruzzi ◽

Samantha Galluzzi ◽

Monica Bertocchi ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Late Onset ◽

Network Connectivity ◽

Functional Network ◽

Functional Network Connectivity

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The relationship between dynamic functional network connectivity and spatial orientation in healthy young adults

10.1101/2021.02.14.431143 ◽

2021 ◽

Author(s):

Mohammad S. E. Sendi ◽

Charles A. Ellis ◽

Robyn L. Miller ◽

David H. Salat ◽

Vince D. Calhoun

Keyword(s):

Young Adults ◽

Spatial Orientation ◽

Brain Connectivity ◽

Network Connectivity ◽

Brain Regions ◽

Functional Network ◽

Sensorimotor Network ◽

Functional Network Connectivity ◽

The Relationship ◽

Dynamic Functional Network Connectivity

ABSTRACTSpatial orientation is essential to interacting with a physical environment, and better understanding it could contribute to a better understanding of a variety of diseases and disorders that are characterized by deficits in spatial orientation. Many previous studies have focused on the relationship between spatial orientation and individual brain regions, though in recent years studies have begun to examine spatial orientation from a network perspective. This study analyzes dynamic functional network connectivity (dFNC) values extracted from over 800 resting-state fMRI recordings of healthy young adults (age 22-37 years) and applies unsupervised machine learning methods to identify neural brain states that occur across all subjects. We estimated the occupancy rate (OCR) for each subject, which was proportional to the amount of time that they spent in each state, and investigated the link between the OCR and spatial orientation and the state-specific FNC values and spatial orientation controlling for age and sex. Our findings showed that the amount of time subjects spent in a state characterized by increased connectivity within and between visual, auditory, and sensorimotor networks and within the default mode network while at rest corresponded to their performance on tests of spatial orientation. We also found that increased sensorimotor network connectivity in two of the identified states negatively correlated with decreased spatial orientation, further highlighting the relationship between the sensorimotor network and spatial orientation. This study provides insight into how the temporal properties of the functional brain connectivity within and between key brain networks may influence spatial orientation.

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