Dynamic functional connectivity in bipolar disorder is associated with executive function and processing speed: A preliminary study.

Abstract

Objective Disturbances in functional connectivity have been suggested to contribute to cognitive and emotion processing deficits observed in bipolar disorder (BD). Functional connectivity between medial prefrontal cortex (mPFC) and other brain regions may be particularly abnormal. The goal of the present study was to characterize the temporal dynamics of the default mode network (DMN) connectivity in BD and examine its association with cognition. Method In a preliminary study, euthymic BD (n=15) and healthy comparison (HC, n=19) participants underwent resting-state functional magnetic resonance imaging, using high-resolution sequences adapted from the Human Connectome Project, and completed neuropsychological measures of processing speed and executive function. A seed-based approach was used to measure DMN correlations in each participant, with regions of interest in the mPFC, posterior cingulate cortex (PCC), and lateral parietal cortex. Subsequently, to characterize temporal dynamics, correlational analyses between the mPFC and other DMN nodes were repeated using a sliding-window correlational analysis with subsets of the time series. Results When averaged across the entire scan, there were no group differences in overall connectivity strength between the mPFC and other regions of the DMN. However, dynamic connectivity between the mPFC and PCC was altered in BD, such that connectivity was less variable (i.e., more rigid) over time. Decreased connectivity variability was associated with slower processing speed and reduced cognitive set-shifting in BD patients. Conclusions Variability in resting-state functional connectivity may be an index of internetwork flexibility that is reduced in BD and a correlate of ongoing cognitive impairment during periods of euthymia.

Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns

“…DFC‐Var measures the overall fluctuating level for each functional connectivity across time, which is similar to the power of fluctuation of correlation across time windows (Elton & Gao, ). We found that DFC‐Var can significantly predict individual executive function, which is consistent with the findings of a recent study (Nguyen et al, ). DFC‐Sta measures the tendency to maintain a metastable state during a short period of time (Allen et al, ) and might be associated with the transition between different states.…”

Dynamic Functional Connectivity Reveals Abnormal Variability and Hyper‐connected Pattern in Autism Spectrum Disorder

“…While no significant result was found in the SFC analysis, we did observe a significant difference in the temporal variability of DFC between the ASD and TD groups, which is concordant with a previous report regarding bipolar disorder [Nguyen et al, ]. It might illustrate that DFC offers unique chronnectomic information [Rashid et al, ], and these measures of DFC seem to be more sensitive than those of SFC.…”

“…These processes require mentalizing, which involves the PCC (DMN) and IFGoper [Herbet et al, 2013;Monk et al, 2009;Muller & Fishman, 2018]. Although some neuroimaging studies [Allen et al, 2014;Nguyen et al, 2017] reported that higher cognition was related to greater variability, Douw, Wakeman, Tanaka, Liu, and Stufflebeam [2016] demonstrated that higher resting-state frontoparietal network (FPN)-DMN dynamics were related to poorer cognitive flexibility. Meanwhile, increased variance of connectivity of the PCC to other DMN regions during the resting state was associated with slower reaction times on a subsequent attention task [Lin et al, 2016].…”

Aberrant patterns of default‐mode network functional connectivity associated with metabolic syndrome: A resting‐state study

“…Resting state FC analysis offers the ability to study functional networks without confounding effects of cognitive ability to perform a particular task, making its application appealing to clinical population with cognitive impairment (Auer, 2008;Fox & Raichle, 2007;Greicius, 2008;Rogers, Morgan, Newton, & Gore, 2007). Indeed, disruption in resting state FC patterns have been identified in a wide range of psychiatric and neurodegenerative disorders, including Alzheimer's disease (Greicius et al, 2004;Sorg, Riedl, Perneczky, Kurz, & Wohlschlager, 2009), Parkinson's disease (Helmich et al, 2009;Wu et al, 2009), mild cognitive impairment (Bai et al, 2009;Pihlajamaki, Jauhiainen, & Soininen, 2009;Sorg et al, 2007), schizophrenia (Jafri, Pearlson, Stevens, & Calhoun, 2008;Rashid, Damaraju, Pearlson, & Calhoun, 2014;Repovs, Csernansky, & Barch, 2011), bipolar disorder (Nguyen et al, 2017), and depression (Greicius, 2008). Thus, FC of the DMN may also prove to be a useful marker to elucidate the impact of MetS, as well as comorbid vascular RFs on brain functioning and connectivity.…”