Dynamic functional connectivity patterns associated with dementia risk

Abstract

Background This study assesses the relationships between dynamic functional network connectivity (DFNC) and dementia risk. Methods DFNC of the default mode (DMN), salience (SN), and executive control networks was assessed in 127 cognitively unimpaired older adults. Stepwise regressions were performed with dementia risk and protective factors and biomarkers as predictors of DFNC. Results Associations were found between times spent in (i) a “weakly connected” state and lower self-reported engagement in early- and mid-life cognitive activity and higher LDL cholesterol; (ii) a “SN-negatively connected” state and higher blood pressure, higher depression score, and lower body mass index (BMI); (iii) a “strongly connected” state and higher self-reported engagement in early-life cognitive activity, Preclinical Alzheimer’s cognitive composite-5 score, and BMI; and (iv) a “DMN-negatively connected” state and higher self-reported engagement in early- and mid-life stimulating activities and lower LDL cholesterol and blood pressure. The lower number of state transitions was associated with lower brain perfusion. Conclusion DFNC states are differentially associated with dementia risk and could underlie reserve.

Dynamic functional connectivity MEG features of Alzheimer’s disease

“…Similar to our findings on the predictablity of dynamic spatial features, Fu et al (2019) examine the shared and specific dynamic functional connectivity in subcortical ischemic vascular disease and AD. Dautricourt et al (2022) show that dynamic FC states are differentially associated with dementia risk. However, the above mentioned studies have not clearly demonstrated that dynamic FC features can distinguish AD patients from healthy controls (Jones et al, 2012; Córdova-Palomera et al, 2017; Brenner et al, 2018).…”

“…Image data resolution is one obstacle for obtaining convincing evidence that dynamic FC generates strong predictors that distinct between AD and control samples. To date, most dynamic FC studies in AD have focused on low temporal resolution resting state functional magnetic resonance imaging (fMRI) (Schumacher et al, 2019; Sendi et al, 2021; Chumin et al, 2021; Ma et al, 2020; Dautricourt et al, 2022), restricting them only to detect state transitions that may occur in the timescale of seconds. However, micro-states with faster dynamics in the timescale of tens to hundredths of milleseconds are considered the basis for the rapid reorganization and adaptation of the functional networks of the brain (Van de Ville et al, 2010).…”

Biological Risk Factors Influencing Vascular Cognitive Impairments: A Review of the Evidence

“…While cardiovascular diseases and cognitive impairment (both MCI and dementia) are often comorbidities, sharing several risk factors such as smoking, obesity, and physical inactivity, it remains unclear whether cardiovascular diseases, vascular diseases, or events alone are attributable risk factors for the development of cognitive impairment. Disturbances in cerebral blood flow play a crucial role in the pathophysiological pathways leading to dementia, including Alzheimer's dementia, hypertension, coronary artery disease (CHD), stroke (including cerebral infarction and cerebral hemorrhage), and metabolic syndrome with its components, including diabetes and obesity, which may be considered potential risk factors for MCI, among other factors [20,46].…”

Alterations in Dynamic Functional Connectivity in Patients with Cerebral Small Vessel Disease

“…Our data are consistent with previous studies on many other neurological and psychiatric diseases, including Alzheimer’s disease [ 42 ], Parkinson’s disease [ 24 ], and schizophrenia [ 21 ]. Another study had also shown that spending more time in a weakly connected state is associated with insufficient cognitive reserve, which may reflect a lack of network efficiency [ 19 ]. CSVD is the most common of the mechanisms involved in vascular cognitive impairment [ 50 ].…”

“…However, some scholars have shown that brain activity is an inherently dynamic system and that the strength and directionality of FC can change significantly on rapid time scales as discrete FC patterns switch rapidly [ 18 ]. Dynamic functional connectivity (DFC) is a new concept that focuses on the dynamic features and patterns of brain networks and has received increasing attention [ 19 ]. Numerous studies suggested that this dynamic approach represents a powerful tool to gain novel insight into neurological diseases, such as autism spectrum disorders [ 20 ], schizophrenia [ 21 , 22 ], depressive disorder [ 23 ], Parkinson’s disease [ 24 ], and Alzheimer’s disease [ 25 ].…”