A Preliminary Study of Brain Functional Magnetic Resonance Imaging in TextReading and Comprehension
Bibliographic record
Abstract
BACKGROUND: Few studies have focused on the changes in human brain function activities caused by reading Chinese characters with different intelligibility and whether it can reflect the understanding and cognitive ability of the human brain. OBJECTIVE: Task-fMRI based on Chinese character reading tasks with different intelligibility was used to explore activated brain regions and their cognitive changes. METHODS: Volunteers were randomly recruited using advertisements. Forty volunteers were recruited based on strict inclusion and exclusion criteria, and 40 volunteers were recruited. Brain function data of 40 healthy right-handed volunteers in fuzzy/clear Chinese reading tasks were collected using a Siemens Skyra 3.0T magnetic resonance scanner. Data were preprocessed and statistically analyzed using the statistical software SPM12.0 to observe the activation of the cortex and analyze its characteristics and possible changes in cognitive function. RESULTS: Task-fMRI analysis: (1) The main brain regions activated in fuzzy/clear reading tasks were located in the occipital visual cortex (P < 0.001); (2) a paired sample t-test suggested that there was a significant difference in BOLD signals in the brain regions activated by fuzzy/clear reading tasks (P < 0.001, equiv Z = 4.25). Compared with the fuzzy reading task, the brain regions more strongly activated in the clear reading task were mainly located in the right superior frontal gyrus and the bilateral temporal lobe. Compared with the clear reading task, the brain region that was more strongly activated in the fuzzy reading task was mainly located in the right fusiform gyrus. CONCLUSION: Clear Chinese character information mainly activates the dorsal stream of the visual-spatial network. This reflects the information transmission of the brain after understanding the text content and is responsible for guiding and controlling attention. Fuzzy words that cannot provide clear text content activate the fusiform gyrus of the ventral stream of the visual-spatial network, strengthening the function of orthographic processing.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".