High-sensitivity neuroimaging biomarkers for the identification of amnestic mild cognitive impairment based on resting-state fMRI and a triple network model

Abstract

Many functional magnetic resonance imaging (fMRI) studies have indicated that Granger causality analysis (GCA) is a suitable method for revealing causal effects between brain regions. The purpose of the present study was to identify neuroimaging biomarkers with a high sensitivity to amnestic mild cognitive impairment (aMCI). The resting-state fMRI data of 30 patients with Alzheimer's disease (AD), 14 patients with aMCI, and 18 healthy controls (HC) were evaluated using GCA. This study focused on the "triple networks" concept, a recently proposed higher-order functioning-related brain network model that includes the default-mode network (DMN), salience network (SN), and executive control network (ECN). As expected, GCA techniques were able to reveal differences in connectivity in the three core networks among the three patient groups. The fMRI data were pre-processed using DPARSFA v2.3 and REST v1.8. Voxel-wise GCA was performed using the REST-GCA in the REST toolbox. The directed (excitatory and inhibitory) connectivity obtained from GCA could differentiate among the AD, aMCI and HC groups. This result suggests that analysing the directed connectivity of inter-hemisphere connections represents a sensitive method for revealing connectivity changes observed in patients with aMCI. Specifically, inhibitory within-DMN connectivity from the posterior cingulate cortex (PCC) to the hippocampal formation and from the thalamus to the PCC as well as excitatory within-SN connectivity from the dorsal anterior cingulate cortex (dACC) to the striatum, from the ECN to the DMN, and from the SN to the ECN demonstrated that changes in connectivity likely reflect compensatory effects in aMCI. These findings suggest that changes observed in the triple networks may be used as sensitive neuroimaging biomarkers for the early detection of aMCI.

Altered Patterns of Functional Connectivity and Causal Connectivity in Salience Subnetwork of Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment

“…Consequently, our results reveal that there might be a different impairment in FC of aSN in cognitive function across the aMCI and SCD. A recent study has indicated that within-SN CC between the dACC and the striatum is abnormal in aMCI when compared to the HC group (Yu et al, 2019), yet there are only a few studies on the altered CC patterns between the SN subnetworks (aSN and pSN networks) and the whole brain. Then, a previous study has proven that directed connectivity, implemented in GCA within DPABI, can reveal the compensatory or pathological mechanisms of AD to some extent (Menon, 2011).…”

“…As one of the phases between normal aging and dementia, amnestic mild cognitive impairment (aMCI) subjects have a 10-15% possibility of developing into AD per year (Petersen et al, 2002;Yang et al, 2017). Subjective cognitive decline (SCD) is the stage referring to the elderly subjects that can last for decades earlier than the onset of dementia when persons subjectively complain of memory impairment without corresponding objective clinical manifestations, while person's scores are in the normal scope through standardized neuropsychological tests (Huang et al, 2018a;Funaki et al, 2019;Yu et al, 2019). Furthermore, converging evidence suggests that SCD poses risk for developing into MCI and AD, although it may likewise be of early preclinical stages of other neurodegeneration diseases (Berger-Sieczkowski et al, 2019;Caillaud et al, 2019).…”

Development of Dynamic Functional Architecture during Early Infancy

“…For example, the VAN, FPN, and DMN that are involved in a "triple network" hypothetic model (Menon, 2011) showed linear increases in their pairwise Vbetween-net. It has been proposed that such three networks are the "core" neurocognitive networks and their functional interactions are important for complex, high-order cognitive functions (Menon, 2011) and could be responsible for psychiatric and neurological disorders, such as depression (Berman et al, 2011), schizophrenia (Palaniyappan et al, 2011), and dementia (Zhou et al, 2010;Yu et al, 2017). Recently, researchers have found that the dynamic network switch supports flexible attention (mainly via DAN and VAN) and cognitive control (mainly via FPN) to meet time-varying changes in cognitive demands, and the loss of such optimized dynamics may lead to poor task performance in a decision-making task (Taghia et al, 2018).…”

Intrinsic connectivity networks underlying individual differences in control‐averse behavior

“…Three ICNs are particularly relevant for the cognitive and emotional information processing underlying social behavior: the central executive network (CEN), the salience network (SN), and the default mode network (DMN) (Menon, ). The CEN, also referred to as the frontoparietal network (Smith et al, ), consists primarily of nodes in the dorsolateral prefrontal cortex (dlPFC) and the lateral posterior parietal cortex (PPC) and has been associated with high‐level cognitive functions such as planning, goal‐directed decision making, and working memory (Menon, ; Seeley et al, ; White, Joseph, Francis, & Liddle, ; Yu et al, ). The SN, also referred to as the cingulo‐opercular network (Chen et al, ; Elton & Gao, ; Hahn et al, ) or the executive control network (Smith et al, ), is anchored in the dorsal anterior cingulate cortex (ACC) and the anterior insula and has been associated with the detection of and orientation to salient external stimuli as well as the autonomic integration of internal events (Menon, ; Seeley et al, ).…”