Recurrent and concurrent patterns of regional BOLD dynamics and functional connectivity dynamics in cognitive decline

Abstract

Background The brain’s dynamic spontaneous neural activity and dynamic functional connectivity (dFC) are both important in supporting cognition, but how these two types of brain dynamics evolve and co-evolve in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remain unclear. The aim of the present study was to investigate recurrent and concurrent patterns of two types of dynamic brain states correlated with cognitive decline. Methods The present study analyzed resting-state functional magnetic resonance imaging data from 62 SCD patients, 75 MCI patients, and 70 healthy controls (HCs). We used the sliding-window and clustering method to identify two types of recurrent brain states from both dFC and dynamic regional spontaneous activity, as measured by dynamic fractional amplitude of low-frequency fluctuations (dfALFF). Then, the occurrence frequency of a dFC or dfALFF state and the co-occurrence frequency of a pair of dFC and dfALFF states among all time points are extracted for each participant to describe their dynamics brain patterns. Results We identified a few recurrent states of dfALFF and dFC and further ascertained the co-occurrent patterns of these two types of dynamic brain states (i.e., dfALFF and dFC states). Importantly, the occurrence frequency of a default-mode network (DMN)-dominated dFC state was significantly different between HCs and SCD patients, and the co-occurrence frequencies of a DMN-dominated dFC state and a DMN-dominated dfALFF state were also significantly different between SCD and MCI patients. These two dynamic features were both significantly positively correlated with Mini-Mental State Examination scores. Conclusion Our findings revealed novel fMRI-based neural signatures of cognitive decline from recurrent and concurrent patterns of dfALFF and dFC, providing strong evidence supporting SCD as the transition phase between normal aging and MCI. This finding holds potential to differentiate SCD patients from HCs via both dFC and dfALFF as objective neuroimaging biomarkers, which may aid in the early diagnosis and intervention of Alzheimer’s disease.

Altered basal forebrain function during whole-brain network activity at pre- and early-plaque stages of Alzheimer’s disease in TgF344-AD rats

“…Key differences consisted mainly of a decreased co-activation of the BFB with the DMLN, decreased BOLD activity within the DMLN and an increased BOLD activity in the CG in TgF344-AD rats. These results are consistent with similar observations describing changes in the QPP-DMN + in a recent human study (54). Using dynamic FC analyses in healthy controls and patients with subjective cognitive decline, Liang et al observed decreased occurrence of a brain state where DMN was activated, while other networks were deactivated (54), a brainstate which resembles the QPP-DMLN observed in this study.…”

“…These results are consistent with similar observations describing changes in the QPP-DMN + in a recent human study (54). Using dynamic FC analyses in healthy controls and patients with subjective cognitive decline, Liang et al observed decreased occurrence of a brain state where DMN was activated, while other networks were deactivated (54), a brainstate which resembles the QPP-DMLN observed in this study. The analogy between the ndings of Liang et al and the current study suggest similar alterations in DMLN activity are observed in patients with subjective cognitive decline and at pre-plaque stages in the TgF344-AD rat.…”

Static and dynamic functional connectivity variability of the anterior-posterior hippocampus with subjective cognitive decline

“…Accumulating studies have suggested that the brain is intrinsically a dynamic system with discrete model switching rapidly [ 16 ], and dynamic indices based on sliding-window changes may be more informative than static indices [ 17 ]. Recently, studies have shown that SCD exhibits significantly increased fractional windows and mean dwell time [ 18 ] and decreased occurrence frequency [ 19 ] of a DMN-dominated dynamic functional connectivity (dFC) state compared to that of healthy controls. The significant role of dFC in SCD has been gradually recognized, but previous studies were based on whole-brain network-based analyses, and little research has been performed using seed-to-voxel-based analyses.…”

Exploring dynamic functional connectivity alterations in the preclinical stage of Alzheimer’s disease: an exploratory study from SICOLDE

“…However, extensive evidence suggests that FC, even at rest, should be understood as a dynamic measure. In recent years, dynamic FCs obtained from rs-fMRI time series has proven highly informative regarding the underlying brain connectivity patterns, as it enables slight changes over a short period of time to be explored (18)(19)(20). For example, research based on slidingwindow analysis found that the occurrence frequency of a default mode network (DMN)-dominated dynamic FC state was signi cantly different in SCD patients (20).…”

“…In recent years, dynamic FCs obtained from rs-fMRI time series has proven highly informative regarding the underlying brain connectivity patterns, as it enables slight changes over a short period of time to be explored (18)(19)(20). For example, research based on slidingwindow analysis found that the occurrence frequency of a default mode network (DMN)-dominated dynamic FC state was signi cantly different in SCD patients (20). However, there have been few attempts to directly compare static and dynamic FCs or to determine whether dynamic FCs could undergo stable and subtle changes in subjects with SCD.…”