[regular session] Assessment of Effective Connectivity in Alzheimer’s Disease Using Granger Causality

In this session, we learned how to evaluated resting-state magnetoencephalography (MEG) activity from 36 AD patients and 26 healthy controls by means of Granger Causality (GC), an effective connectivity measure that provides an estimation of the information flow between brain regions. The purpose of this paper was to investigate the hypothesis of disrupted directional connectivity patterns of resting-state MEG in AD.

Recently, brain connectivity has been intensively explored as a potential tool for the comprehension of the underlying mechanisms associated to AD. In particular, a key concept of connectivity, effective connectivity, refers to the direction of the influence that a neurophysiological event exerts to another one [1]. It has been reported that AD elicits connectivity abnormalities between certain cortical regions. Specifically related to effective connectivity, Directed Transfer Function (DTF) has been applied on EEG signals reporting decreased parieto-to-frontal couplings in AD subjects mostly pronounced in α and β bands [2].

Classical GC is a synchrony measure, which is useful to evaluate the information flow between two signals.

Definition If the knowledge of the past of both X1(t) and X2(t) reduces the variance of the prediction error of X2(t) in comparison with the knowledge of the past of X2(t) alone, then a signal X1(t) causes the signal X2(t) in Granger sense.[3]

1

Let is take the first figure as an example. It shows an overall connectivity increase in δ band for AD patients, which is more pronounced between distant areas. Connectivity increments inδ band were previously reported in literature by means of coherence (COH). However, these results differ from other publications that reported abnormal decrements in this band. These contradictory results suggest that the connectivity behaviour of δ band is inconclusive to characterize AD.

In summary, the paper’s findings support the notion that AD is accompanied by effective connectivity abnormalities. In this regard, GC can be considered a promising tool to define potential parameters for AD directional connectivity characterization.

 

Juan-Cruz C, Gómez C, Poza J, et al. Assessment of Effective Connectivity in Alzheimer’s Disease Using Granger Causality[M]//Converging Clinical and Engineering Research on Neurorehabilitation II. Springer International Publishing, 2017: 763-767.

[1] K. J. Friston, “Functional and effective connectivity: a review,” Brain Connect., vol. 1, no. 1, pp. 13–36, 2011.

[2] F. Vecchio and C. Babiloni, “Direction of Information Flow in Alzheimer’s Disease and MCI Patients.,” Int. J. Alzheimers. Dis., vol. 2011, p. 214580, 2011.

[3] Granger CWJ (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37:424– 438

 

Speaker:Huitong  Ding  Date:2017.08.30

Participants:

Supervisors: Xia Que

Students: Jinge Yan, Yuting Wang, Huitong Ding, Hong Ming, Peng Han,Yongbo Xiao

Personal leave: Yue Yin, Siyuan Jiang, Xu Chen, Chen Tang, Jie Liu, Bo Jing, Yue Teng, You Duan, Xiaohui Yao

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