Accelerated Cognitive Ageing in epilepsy: exploring the effective connectivity between resting-state networks and its relation to cognitive decline

A Bernas; L E M Breuer; R Lamerichs; A J A de Louw; A P Aldenkamp; S Zinger

doi:10.1016/j.heliyon.2020.e03951

Accelerated Cognitive Ageing in epilepsy: exploring the effective connectivity between resting-state networks and its relation to cognitive decline

Heliyon. 2020 Jun 5;6(6):e03951. doi: 10.1016/j.heliyon.2020.e03951. eCollection 2020 Jun.

Authors

A Bernas^{1

2

3}, L E M Breuer², R Lamerichs^{1

2

4}, A J A de Louw^{1

2}, A P Aldenkamp^{1

2

5

3}, S Zinger^{1

2}

Affiliations

¹ Department of Electrical Engineering, University of Technology, Eindhoven, the Netherlands.
² Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, the Netherlands.
³ School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands.
⁴ Philips Research, Eindhoven, the Netherlands.
⁵ Department of Neurology and Clinical Neurophysiology, Maastricht University Medical Center, Maastricht, the Netherlands.

Abstract

Objective: This study aims at understanding the dynamic functional brain organization in Accelerated Cognitive Ageing (ACA) in epilepsy. We also assess to which extend the (abnormal) effective connectivity between brain networks correlates with the (estimated) decline in IQ scores observed in the ACA patients.

Material and methods: Two multi-echo resting-state fMRI scans of 10 ACA patients and 14 age- and education-matched healthy controls were acquired. A task-based fMRI was acquired in-between those two scans, for possible cognitive fatigue effects on reserve capacity. Granger causality (GC), a measure of effective connectivity between brain regions, was applied on 7 major cognitive networks, and group-wise compared, using permutation testing statistics. This was performed on each of the resting-state sessions independently. We assessed the correlation between the cognitive deterioration scores (representing cognitive decline), and the paired-networks granger causality values.

Results: The cingulate cortex appeared to be more engaged in ACA patients. Its dynamics towards the right fronto-parietal cortex, salience network, and the dorsal attention networks (DAN) was stronger than in controls, only in the first resting-state scan session. The Granger causality from the DAN to the default mode network (DMN) and from the ventral attention network (VAN) to the left fronto-parietal network (FPL) was also stronger in ACA patients and again only in the first scans. In the second resting-state scans, only the DMN was more strongly connected with the cingulate cortex in ACA patients. A weaker GC from DMN to FPL, and stronger GC from the salience network to cingulate cortex were associated with more decline in the Full-scale IQ and more GC from DMN to VAN would lead to more decline in the Perceptual Reasoning Index in ACA.

Conclusion: The results are in line with the hypothesis of over-recruitment at low cognitive load, and exhaustion at higher cognitive load, as shown by the compensation-related utilization of neural circuits hypothesis (CRUNCH) model for ageing. Moreover, the DMN to VAN directed connectivity strongly correlates with the (estimated) decline in the Perceptual Reasoning Index, which is also in line with a recent study on ageing with mild cognitive impairment in elderly, and the posterior-anterior shift in aging (PASA) model. This study therefore supports the idea that the cognitive decline in our patients resembles the decline observed in healthy ageing, but in an accelerated mode. This study also sheds light on the directions of the impaired connectivity between the main networks involved in the deterioration process, which can be helpful for future development of treatment solutions.

Keywords: Accelerated cognitive ageing; Ageing; Aging; Biomarkers; Clinical research; Cognition; Cognitive decline; Cognitive neuroscience; Effective connectivity; Epilepsy; Fmri; Granger causality; Image processing; Medical imaging; Mental health; Nervous system; Neuroscience; Psychiatry.