Functional diversity of brain networks supports consciousness and verbal intelligence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
How are the myriad stimuli arriving at our senses transformed into conscious thought? To address this question, in a series of studies, we asked whether a common mechanism underlies loss of information processing in unconscious states across different conditions, which could shed light on the brain mechanisms of conscious cognition. With a novel approach, we brought together for the first time, data from the same paradigm-a highly engaging auditory-only narrative-in three independent domains: anesthesia-induced unconsciousness, unconsciousness after brain injury, and individual differences in intellectual abilities during conscious cognition. During external stimulation in the unconscious state, the functional differentiation between the auditory and fronto-parietal systems decreased significantly relatively to the conscious state. Conversely, we found that stronger functional differentiation between these systems in response to external stimulation predicted higher intellectual abilities during conscious cognition, in particular higher verbal acuity scores in independent cognitive testing battery. These convergent findings suggest that the responsivity of sensory and higher-order brain systems to external stimulation, especially through the diversification of their functional responses is an essential feature of conscious cognition and verbal intelligence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it