Bibliographic record
Abstract
Most models of schizophrenia are based on basal ganglia-thalamocortical (BGTC) neuronal circuits or brain structures that project to them. Two new neuronal networks have been described which include many of the brain regions associated with BGTC neuronal circuits. These networks have been characterized with a new brain-imaging technique based on low-frequency fluctuations of the blood oxygen level-dependent (BOLD) signal. The new network associated with attention-demanding tasks is referred to as the task-related network and the network associated with stimulus-independent thought during the resting state is referred to as the default network. The 2 networks have been proposed to be negatively correlated or anticorrelated. This article critically reviews the rationale for these anticorrelated networks, the technique with which they are characterized, and preliminary findings in schizophrenia and other neuropsychiatric disorders. Regions associated with the default network overlap with regions important in motivation and are activated by memory retrieval, auditory hallucinations, and ketamine. Task-related networks are necessary for performance of neurocognitive tasks on which schizophrenic patients often perform poorly. It is concluded that anticorrelated networks can be viewed as complementary ways of understanding self-monitoring and task performance which extend present models of schizophrenia based on BGTC circuits. However, there are some limitations with regard the present understanding of brain structures involved in self-monitoring and the lack of asymmetry in the network which may mediate stimulus-independent thought. Further investigations of the default network assessed by low-frequency fluctuations in the BOLD signal seem warranted.
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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 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".