Cognitive and Psychological Symptoms in Post-COVID-19 Condition: A Systematic Review of Structural and Functional Neuroimaging, Neurophysiology, and Intervention Studies
Bibliographic record
Abstract
Objective: To investigate the structural, functional, and neurophysiological brain changes associated with post-COVID-19 condition (PCC)-related cognitive and psychological issues and evaluate the efficacy of noninvasive brain stimulation (NIBS) and cognitive rehabilitation interventions. Data Sources: Electronic databases, including Web of Science, PubMed, and Embase, were systematically searched for articles published before February 1, 2025, using terms such as "post-COVID-19 condition," "cognitive dysfunction," "brain changes," "noninvasive brain stimulation," and "cognitive rehabilitation." Language was restricted to English, and only studies involving human participants were included. Study Selection: Studies with human participants aged ≥18 years diagnosed with PCC, employing magnetic resonance imaging, functional magnetic resonance imaging, positron emission tomography, and electroencephalography, and interventions such as NIBS and cognitive rehabilitation were included. Articles were selected through independent review by multiple authors, with consensus resolving discrepancies. Of the 123 studies initially identified, 78 met the inclusion criteria. Data Extraction: Data on participant demographics, methodologies, neurophysiological changes, and intervention outcomes were extracted by 2 independent reviewers using predefined guidelines. Study quality was assessed using the Newcastle-Ottawa Scale and Critical Appraisal Skills Program tools. Data Synthesis: Seventy-eight studies with over 5900 participants met the inclusion criteria. Significant cognitive impairments were observed in attention, executive function, and memory (N=78). Key findings included mixed evidence of gray matter (N=16) and white matter volume changes (N=20), cortical thickness alterations (N=9), variations in functional connectivity (N=14), electrophysiology (N=9), and blood flow (N=8). NIBS, including transcranial magnetic stimulation (N=8) and transcranial direct current stimulation (N=2), showed potential benefits for managing depression and cognitive impairments. Although cognitive rehabilitation (N=3) showed promise, it requires further investigation. Conclusions: This review highlights the complex neurologic underpinnings of PCC and the potential of NIBS and cognitive rehabilitation as interventions. Further research is essential to refine these interventions and establish evidence-based strategies for addressing long-term cognitive and psychological effects of PCC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".