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

  • Enyan Yu
  • Zhengluan Liao
  • Yunfei Tan
  • Yaju Qiu
  • Junpeng Zhu
  • Zhang Han
  • Jue Wang
  • Xinwei Wang
  • Hong Wang
  • Yan Chen
  • Qi Zhang
  • Yumei Li
  • Dewang Mao
  • Zhongxiang Ding
Original Research

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.

Keywords

Functional magnetic resonance imaging (fMRI) Alzheimer’s disease Amnestic mild cognitive impairment Granger causality analysis Default-mode network 

Abbreviations

ACC

Anterior cingulate cortex

AD

Alzheimer’s disease

ALFF

Amplitude of low-frequency fluctuations

aMCI

Amnestic mild cognitive impairment

ANCOVA

One-way analysis of covariance

ANOVA

One-way analysis of variance

BOLD

Blood oxygenation level-dependent

dACC

Dorsal anterior cingulate cortex

dlPFC

Dorsolateral prefrontal cortex

DMN

Default-mode network

ECN

Executive control network

EPI

Echo-planar imaging

FC

Functional connectivity

fMRI

Functional magnetic resonance imaging

FOV

Field of view

GCA

Granger causality analysis

HC

Healthy controls

IPC

Inferior parietal cortex

ITC

Inferior temporal cortex

MMSE

Mini mental state evaluation

MoCA

Montreal cognitive scale

MPFC

Medial prefrontal cortex

MPRAGE

Magnetization-prepared rapid gradient echo

PCC

Cingulate cortex

PCC

Posterior cingulate cortex

PPC

Lateral posterior parietal cortex

ROI

Region of interest

SN

Salience network

TE

Echo time

TR

Repetition time

Notes

Acknowledgements

This study is funded by the Zhejiang Provincial Natural Science Foundation of China (no. Y2091289, LY16H180007, LY13H180016) and the Science Foundation from Health Commission of Zhejiang Province (no. 2013RCA001, 2016147373, ZKJ-ZJ-1503). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Compliance with ethical standards

Conflict of interest

Enyan Yu, Zhengluan Liao, Yunfei Tan, Yaju Qiu, Junpeng Zhu, Zhang Han, Jue Wang, Xinwei Wang, Hong Wang, Yan Chen, Qi Zhang, Yumei Li, Dewang Mao, and Zhongxiang Ding declare that they have no conflict of interest.

Informed consent

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and the Helsinki Declaration of 1975, and the applicable revisions at the time of investigation. Informed consent was obtained from all patients. The study was approved by the institutional Ethics Committee number: 2012KY002.

Supplementary material

11682_2017_9727_Fig7_ESM.jpg (164 kb)
Supplemental Fig. 1

Position of the three seed points of the triple networks. A, Posterior cingulate cortex (PCC) of the default-mode network (DMN); B, dorsal anterior cingulate cortex dACC of the salience network (SN); and C, dorsolateral prefrontal cortex (dlPFC) of the executive control network (ECN) (JPEG 163 kb)

11682_2017_9727_MOESM1_ESM.tif (1.5 mb)
High Resolution Image (TIFF 1521 kb)
11682_2017_9727_Fig8_ESM.jpg (640 kb)
Supplemental Fig. 2

The driving effect from PCC to other brain regions. (JPEG 639 kb)

11682_2017_9727_MOESM2_ESM.tif (7.5 mb)
High Resolution Image (TIFF 7721 kb)
11682_2017_9727_Fig9_ESM.jpg (625 kb)
Supplemental Fig. 3

The driving effect to PCC from other brain areas. (JPEG 624 kb)

11682_2017_9727_MOESM3_ESM.tif (7.2 mb)
High Resolution Image (TIFF 7422 kb)

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Enyan Yu
    • 1
  • Zhengluan Liao
    • 1
  • Yunfei Tan
    • 1
  • Yaju Qiu
    • 1
  • Junpeng Zhu
    • 1
  • Zhang Han
    • 2
  • Jue Wang
    • 3
  • Xinwei Wang
    • 1
  • Hong Wang
    • 1
  • Yan Chen
    • 1
  • Qi Zhang
    • 1
  • Yumei Li
    • 4
  • Dewang Mao
    • 4
  • Zhongxiang Ding
    • 4
  1. 1.Department of PsychiatryZhejiang Provincial People’s HospitalHangzhouChina
  2. 2.Center for Cognition and Brain DisordersHangzhou Normal UniversityZhejiangChina
  3. 3.Department of PsychiatryTongde Hospital of Zhejiang ProvinceHangzhouChina
  4. 4.Department of RadiologyZhejiang Provincial People’s HospitalHangzhouChina

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