Recognition and Cognitive Risk Assessment of Brain Dysfunction in Patients with Migraine by Resting-state Functional Magnetic Resonance Imaging
Bibliographic record
Abstract
Using Resting-State Functional Magnetic Resonance Imaging (rest-fMRI) to post-process the data of the resting-state fMRI image of migraine patients and healthy controls without external conditions, analyze the spontaneous activity of nerve cells in the brain area without external stimulus, and analyze the changes of its brain functional network signals, so as to further analyze the relationship between the functional changes of multiple brain regions and clinical manifestations of migraine.At the same time, the Montreal Cognitive Assessment (MoCA) scale was used to screen the cognitive function of the above participants, which was associated with the functional changes of brain areas obtained by fMRI, so as to evaluate whether migraine will affect cognitive function.Method: Twenty-nine patients with migraine in our hospital from September 2020 to March 2021 were included.Patients with migraine were the case group (group A), then according to whether there was Patent Foramen Ovale (PFO), they were divided into migraine group with patent foramen ovale (group A1,20) and migraine group without patent foramen ovale (group A2,9).and selected 14 healthy people whose age, and education level match the case group, that is the control group (group B).Montreal cognitive assessment scale was used to test the cognitive function domains such as visual space, executive function, attention, memory, abstraction and orientation, using statistical software SPSS (Statistic a Product and Service Solutions) version 23.0, using Kruskal-Wallis H test, the P value is less than 0.05 as statistically different.Resting state fMRI pre-processing and post-processing auxiliary software MATLABR2010a, REST for subsequent processing of the data.Result: Alff values of bilateral cerebellar hemisphere, bilateral frontotemporal occipital parietal lobe, thalamus and basal ganglia in group A were significantly higher than those in group B (P< 0.05).Alff values of right temporal lobe in group A1 were significantly higher than those in group A2 (P<0.05).Alff values of bilateral cerebellar hemisphere, bilateral frontotemporal parietal lobe, left thalamus and basal ganglia in group A1 were significantly lower than those in group A2 (P< 0.05).The statistical results of MOCA scale scores in group A were lower than those in group B, and the difference was statistically significant (P<0.05),manifested in visual space and executive function, attention, memory, language ability, abstraction, and orientation.There was no significant difference in naming, language, abstraction, and delayed recall between A1 group and A2 group Montreal Cognitive Assessment Scale score statistics (P>0.05).The difference between visual space and execution, attention, and orientation was statistically significant (P<0.05).Conclusion: Migraine patients have abnormal connections in multiple brain areas in the resting state, resulting in abnormal brain function information integration, which is consistent with a variety of clinical manifestations of migraine patients.Migraine patients cause cognitive dysfunction, which can be manifested as damage to visual space and executive function, attention, memory, language ability, abstraction, and orientation; compared with migraine patients without patent foramen ovale, there is oval Migraine patients with patent foramen have more prominent cognitive impairments in visual space and execution, attention, and orientation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".