Effects of Chemotherapy on Neural Processes During Cognitive Functioning in Early-Stage Breast Cancer Patients: An fMRI Study
Bibliographic record
Abstract
Functional Magnetic Resonance Imaging (fMRI) was used to examine brain activity in women with early stage Breast Cancer (BC) and to compare their neural profiles to a matched control group. This was accomplished as participants performed two working memory tasks, before and at two time points following the chemotherapy intervention of the BC group. Nineteen BC patients between the ages of 18 and 65 years were recruited from the Ottawa Hospital Regional Cancer Centre. The nineteen control participants were matched on sex, language, age and education. The results, from whole brain analyses, show significant differences in neural activity between BC patients and matched control participants during both verbal and visuospatial working memory tasks, before and right after chemotherapy. However, these differences were no longer observed one year post chemotherapy for verbal WM processing. Performance results were not significantly different between groups until the third imaging sessions when patients made significantly more errors of omission than controls for both tasks. Importantly, mood, anxiety and fatigue all played significant roles in the observed findings demonstrating the multifaceted nature of the impact of both cancer and chemotherapy on neural function during working memory. This is one of the first fMRI studies to measure neural activations during cognitive performance both before and after chemotherapy in BC patients and a control group while controlling for many potentially confounding variables. While BC patients should be made aware of the potential cognitive challenges they might face before, during and shortly after treatment, they can also feel reassured that these impairments may not be long lasting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".