Abnormal dynamic functional connectivity in Alzheimer’s disease

Abstract

Aims Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Previous studies have demonstrated abnormalities in functional connectivity (FC) of AD under the assumption that FC is stationary during scanning. However, studies on the FC dynamics of AD, which may provide more insightful perspectives in understanding the neural mechanisms of AD, remain largely unknown. Methods Combining the sliding‐window approach and the k‐means algorithm, we identified three reoccurring dynamic FC states from resting‐state fMRI data of 26 AD and 26 healthy controls. The between‐group differences both in FC states and in regional temporal variability were calculated, followed by a correlation analysis of these differences with cognitive performances of AD patients. Results We identified three reoccurring FC states and found abnormal FC mainly in the frontal and temporal cortices. The temporal properties of FC states were changed in AD as characterized by decreased dwell time in State I and increased dwell time in State II. Besides, we found decreased regional temporal variability mainly in the somatomotor, temporal and parietal regions. Disrupted dynamic FC was significantly correlated with cognitive performances of AD patients. Conclusion Our findings suggest abnormal dynamic FC in AD patients, which provides novel insights for understanding the pathophysiological mechanisms of AD.

Impaired dynamic profile of brain recurring functional connectivity states in Alzheimer’s disease

“…The global state in the present study characterized by a whole brain connectivity profile with absence of strong negative correlations that participants spend most of their time in this state. This finding is in accordance with previous findings in healthy participants (Allen et al, 2014; Cabral et al, 2017; Larabi et al, 2020), AD and dementia (Fu et al, 2019; Gu et al, 2020; Jones et al, 2012; Niu et al, 2019; Schumacher et al, 2019), aging (Tian et al, 2018; Viviano et al, 2017), and other psychiatric and neuro-degenerative diseases (Figueroa et al, 2019; Kim et al, 2017).…”

“…The other recurring FC state that AD patients had lower probability of occurrence and spent less time compared to HC subjects are located in SMN-sub-VIS networks. Decreased ability access to brain areas were located mainly in DMN, SN, FPN, SMN, sub and VIS networks in AD patients compared to HC subjects consistent with many previous findings (Brier et al, 2012; Dai et al, 2015; Greicius et al, 2004; Gu et al, 2020; Mosimann et al, 2004; Schumacher et al, 2019). For the DMN,FPN and SN, the decreased access to these networks might be associated with impaired cognitive functions, as the DMN plays a pivotal role in essential cognitive processes (Buckner et al, 2008; Zhao et al, 2018) and especially influences memory consolidation (Greicius et al, 2004), and the FPN is involved in cognitive control and has also been reported to be also affected by AD (Zhao et al, 2018).…”

“…The reason behind the selection of a window of approximately 100 sec length was that it is the shortest possible window to capture a full cycle of the slowest frequency component due to high-pass cutoff frequency (0.01 Hz) (Betzel et al, 2016; Leonardi & Van De Ville, 2015; Maleki Balajoo et al, 2020; Zalesky & Breakspear, 2015). It is noteworthy that, Gu et al, (2020) utilized a short window length (i.e., 30 sec) to estimate dFC patterns compared with current study, however, window length between 30 and 100 sec has been proposed as a good window length for dFC analysis (Vergara, Abrol, & Calhoun, 2019; Wilson et al, 2015). Then, we defined an exponentially tapered function as proposed by (Pozzi et al, 2012) and used in (Betzel et al, 2016; Zalesky et al, 2014) for each window and calculated the weighted Pearson product-moment correlation between regions i and j using the observations only within that window.…”

“…Previous studies have ignored dynamic nature of FC and mostly focused on assessing ‘static’ FC which represents mean connectivity over the period of scanning (Damoiseaux, Prater, Miller, & Greicius, 2012; Greicius, Srivastava, Reiss, & Menon, 2004; Sorg, Riedl, Perneczky, Kurz, & Wohlschlager, 2009; Zhao, Lu, Metmer, Li, & Lu, 2018). Most recently, several studies have provided empirical evidences in healthy subjects (Cabral et al, 2017; Larabi et al, 2020; Maleki Balajoo, Asemani, Khadem, & Soltanian-Zadeh, 2020) and psychiatric (Figueroa et al, 2019; Sakoglu et al, 2010) and neurological (Fu et al, 2019; Gu et al, 2020; Jones et al, 2012; Kim et al, 2017; Niu et al, 2019; Schumacher et al, 2019; Sourty et al, 2016) disorders that not only the intrinsic brain FC at rest is dynamic during the period of scanning (Allen et al, 2014; Betzel, Fukushima, He, Zuo, & Sporns, 2016; Chang & Glover, 2010; Hutchison et al, 2013), but also temporal properties of FC reconfiguration over time are associated with symptoms, behavioral and cognitive performance (Cabral et al, 2017; Figueroa et al, 2019; Gu et al, 2020; Larabi et al, 2020; Tian, Li, Wang, & Yu, 2018; Viviano, Raz, Yuan, & Damoiseaux, 2017). For AD, few studies have investigated dynamic functional connectivity (dFC) impairments or reconfiguration of brain FC states over time by using rs-fMRI data (Fu et al, 2019; Gu et al, 2020; Jones et al, 2012; Schumacher et al, 2019).…”

“…Findings from other studies suggest temporal properties of recurring FC states are generally disrupted in AD, but detailed findings are not convergent. For example, Gu et al, (2020) and Fu et al, (2019) reported patients with AD spent less time in baseline (global) state compared with HC subjects, while Schumacher et al (2019) reported an opposite result using a similar method proposed in (Fu et al, 2019). On the other hand, Gu et al, (2020) reported significant association between impaired dFC and cognitive performances in patients with AD, while Schumacher et al, (2019) indicated no significant relation between impaired dFC and clinical symptom severity.…”