Altered corticostriatal connectivity in long-COVID patients is associated with cognitive impairment, 2025, Troll et al

[forestglip]

Altered corticostriatal connectivity in long-COVID patients is associated with cognitive impairment

Marie Troll, Meng Li, Tara Chand, Marlene Machnik, Tonia Rocktäschel, Antonia Toepffer, Johanna Ballez, Kathrin Finke, Daniel Güllmar, Jürgen R. Reichenbach, Martin Walter, Bianca Besteher

Background
The COVID-19 pandemic has had a significant impact on the health of millions of people worldwide, and many manifest new or persistent symptoms long after the initial onset of the infection. One of the leading symptoms of long-COVID is cognitive impairment, which includes memory loss, lack of concentration, and brain fog. Understanding the nature and underlying mechanisms of cognitive impairment in long-COVID is important for developing preventive and therapeutic interventions.

Methods
Our present study investigated functional connectivity (FC) changes in patients with long-COVID and their associations with cognitive impairment. Resting-state functional MRI data from 60 long-COVID patients and 52 age- and sex-matched healthy controls were analyzed using seed-based functional connectivity analysis.

Results
We found increased FC between the right caudate nucleus and both the left and right precentral gyri in long-COVID patients compared with healthy controls. In addition, elevated FC was observed between the right anterior globus pallidus and posterior cingulate cortex as well as the right temporal pole in long-COVID patients. Importantly, the magnitude of FC between the caudate and the left precentral gyrus showed a significant negative correlation with Montreal Cognitive Assessment (MoCA) scores and a negative correlation with Trail Making Test B performance in the patient group.

Conclusion
Patients with long-COVID present enhanced FC between the caudate and the left precentral gyrus. Furthermore, those FC alterations are related to the severity of cognitive impairment, particularly in the domain of executive functions.

Link | PDF (Psychological Medicine) [Open Access]

 

[Yann04]

An ANCOVA was conducted to assess the influence of age, sex, education, the severity of acute COVID-19 infection, duration of long-COVID symptoms, depression, and fatigue severity on the MoCA and TMT A and B scores among patients. Age was found to have a significant negative effect on MoCA scores (estimate = −0.05, t = −2.39, p = 0.021, η2 = 0.13), with older age being associated with lower MoCA scores. Sex also had a significant effect on the MoCA score (estimate = −1.70, t = −3.02, p = 0.004, η2 = 0.06), with males having lower MoCA scores than females. Depression severity also significantly affected MoCA scores, with greater depression severity linked to lower MoCA scores (estimate = −0.09, t = −2.06, p = 0.045, η2 = 0.32). Education, severity of acute COVID-19 infection, duration of long-COVID symptoms, and fatigue severity did not significantly affect MoCA scores (Table 3). The Variance Inflation Factor values for all the predictors were below the threshold of 10, indicating no significant multicollinearity.

Another study taking the correlation with depression scores uncritically at face value unfortunately.

 

[SNT Gatchaman]

This entire body of literature may have to be thrown out.

Lazily copy-pasting the Google AI description —

Resting-state functional connectivity (rs-fMRI) maps brain networks by analyzing spontaneous, synchronized fluctuations in the BOLD signal (oxygen levels) between different brain regions while a person is resting, revealing how areas functionally "talk" to each other even without a task. This powerful, non-invasive tool identifies intrinsic brain networks (like the Default Mode Network) and helps study brain organization in health and diseases like Alzheimer's, autism, and schizophrenia, offering insights beyond task-based scans by avoiding performance-related confounds.

From BOLD signal changes can oppose oxygen metabolism across the human cortex (2025) —

Here we found that about 40% of voxels with significant BOLD signal changes during various tasks showed reversed oxygen metabolism, particularly in the default mode network. These ‘discordant’ voxels differed in baseline oxygen extraction fraction and regulated oxygen demand via oxygen extraction fraction changes, whereas ‘concordant’ voxels depended mainly on cerebral blood flow changes.

Discordant voxels, however, show ∆BOLD opposite to their metabolic response

We found that in a substantial fraction of voxels with significant BOLD responses, oxygen metabolism changes in the opposite direction to both positive and negative BOLD signals. Notably, these discordant voxels regulated oxygen demand primarily via changes in OEF, rather than CBF. These findings challenge the canonical hemodynamic response model, demonstrating that ∆BOLD alone can lead to misleading interpretations of underlying neuronal activity.