Neurodevelopmental models of Schizophrenia
Bibliographic record
Abstract
Despite the obvious problems of modeling a disorder that is characterized by deficits in higher cognitive functions in lower animals, animal models of schizophrenia have aided in the advancement of the developmental hypothesis of schizophrenia. In fact, using three different animal models of schizophrenia, two of which we developed in our laboratory, we have been able to add support to the hypothesis. First, using NCAM knockout mice, which completely lack the neurodevelopmental molecule PSA-NCAM, we established the first genetic model of schizophrenia that not only presents with sensorimotor gating deficits but ventricular enlargement, both of which have been repeatedly demonstrated in schizophrenics. Next, we used neonatal Endo-N injections to enzymatically remove PSA from NCAM to demonstrate that only a brief disruption of neurodevelopment if sufficient to cause dopaminergic hyper-responsiveness. Finally, while trying to establish a genetic marker for the strain specific vulnerability to neonatal ventral hippocampal lesions (nVH) in Fisher and Lewis rat, we in fact discovered that the vulnerability is solely due to environmental factors, namely, the frequency of arched back nursing (ABN). Then making use of the variation in ABN in Sprague Dawley rats we established a new model in which nVH lesioned rats are separated into groups raised by dams with a High or Low frequency of ABN. Using this model, we demonstrated that the early environment is leading to disruption of the medial prefrontal cortex (MPFC), as characterized by working memory deficits, lack of MPFC control of locomotion and decreased anxiety, only in nVH lesioned rats raised by High ABN dams. Furthermore, we established that the early environment is not leading to sparing of function of the VH since nVH lesioned rats raised by both High and Low ABN dams have deficits on reference memory. Therefore, we have confirmed that genetic factors can lead to deficits in neurodevelopment that cause deficits pa
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".