Abstract #2088

Graph theory demonstrates lower nodal efficiency and transitivity in the Default Mode Network 6-12 months after admission for COVID-19 pneumonia

Joanah Shamiso Madzime^1,2, Jacqueline Hoare ^2,3, Betty Kadenge³, Sarah Heany³, and Ernesta Meintjes^1,2,4

¹Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa, ²Neuroscience Institute, University of Cape Town, Cape Town, South Africa, ³Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa, ⁴Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa

Synopsis

Keywords: Functional Connectivity, COVID-19

Motivation: Neural functional networks provide insights into the intrinsic function and integrity of brain areas.

Goal(s): The aim of the current study was to investigate the levels of functional integration and segregation of brain areas within the default mode network (DMN) in a cohort of adults 6-12 months after admission for SARS-CoV-2 pneumonia.

Approach: We used a functional atlas and graph-theoretical framework to model the topology of brain areas within the DMN.

Results: We found reduced functional integration within the DMN of adults previously admitted with SARS-CoV-2. Affected brain areas are involved in higher-cognitive memory processing functions.

Impact: Investigating the brain’s functional organization in the context of post-acute infection with SARS-CoV-2 can offer a window into the neuropathology of long COVID-19 symptoms.

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