PhD Scientific Days 2020

Mental Sciences II. Lectures

EEG Functional Connectivity and Network Structure Mark Hub Overload and Vulnerable Brain Networks in Mild Cognitive Impairment during Memory Maintenance

Előadó neve

Dr. Fodor, Zsuzsanna

Előadó munkahelye

Department of Psychiatry and Psychotherapy, Semmelweis University

Előadó telefonszáma

+36305287876

Előadó e-mail címe

fodor.zsuzsanna@med.semmelweis-univ.hu

Az előadás címe

EEG Functional Connectivity and Network Structure Mark Hub Overload and Vulnerable Brain Networks in Mild Cognitive Impairment during Memory Maintenance

Szerző(k) neve és munkahelye

Zsuzsanna Fodor1, András Horváth PhD2, Gábor Csukly PhD3
1 Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest
2 Department of Neurology, National Institute of Clinical Neurosciences, Budapest
3 Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest

Szekció

Mental Sciences II. Lectures

Language of the presentation

Hungarian

Section, first choice

Mental Sciences

Section, second choice

Neurosciences

Összefoglaló szövege

Introduction: Changes in the functional interaction between brain regions have been reported in Alzheimer’s disease, especially in the alpha frequency band. Furthermore, beta-amyloid deposition primarily affects highly connected cortical hub regions that are essential for normal cognition but also constitute vulnerable spots of brain networks. From a network perspective, hub overload and failure might explain the pathological process of neurodegenerative diseases. However, it is not yet entirely known whether changes in functional connectivity (FC) and network structure are able to mark cognitive decline in the early stages of the disease.
Aim: Our study aimed to analyze EEG FC and network differences in the alpha band during memory maintenance between Mild Cognitive Impairment (MCI) patients and healthy elderly with subjective memory complaints.
Method: FC and network analysis of 17 MCI patients and 20 control participants were studied with 128-channel EEG during the Paired Associates Learning task. FC between EEG channels was estimated with the envelope correlation with leakage correction (AEC-c), a reliable measure of genuine connectivity. To examine network topology we applied the Minimum Spanning Tree (MST) approach that provides an unbiased reconstruction of the critical backbone of the original network and captures changes in topology while it addresses several methodological limitations.
Result: We did not find group differences in the mean FC in the alpha frequency band, however, memory load had a different modulatory effect in the two study groups: while increasing task difficulty enhanced connectivity in the control group, the MCI group showed significantly (p<0.05) diminished FC in the highest memory load condition, which might indicate the impairment of memory maintenance. Network analysis revealed increased maximum degree, betweenness centrality and degree divergence, and decreased diameter in the MCI group compared to the control group. This indicates a rerouted network in MCI with a more centralized topology and a more unequal traffic load distribution, where central hubs might become vulnerable to overload and failure.
Conclusion: FC sensitively reflects memory load-related modulation and impairment of memory retention in MCI, while changes in the network topology point to the increased vulnerability of brain networks of MCI patients.

Additional Information

Supervisor: Gábor Csukly
E-mail address: csukly.gabor@med.semmelweis-univ.hu
Doctoral School: Mental Health Sciences

Bemutatás módja

Szóbeli

Kind

Szabad

Status

elfogadva

Accepted presentation method

szóbeli

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

2755

Start

11:40

End

11:55

Authors (legacy)

Zsuzsanna Fodor1, András Horváth PhD2, Gábor Csukly PhD3
1 Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest
2 Department of Neurology, National Institute of Clinical Neurosciences, Budapest
3 Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest