Parvalbumin and GAD65 Interneuron Inhibition in the Ventral Hippocampus Induces Distinct Behavioral Deficits Relevant to Schizophrenia
Bibliographic record
Abstract
Hyperactivity within the ventral hippocampus (vHPC) has been linked to both psychosis in humans and behavioral deficits in animal models of schizophrenia. A local decrease in GABA-mediated inhibition, particularly involving parvalbumin (PV)-expressing GABA neurons, has been proposed as a key mechanism underlying this hyperactive state. However, direct evidence is lacking for a causal role of vHPC GABA neurons in behaviors associated with schizophrenia. Here, we probed the behavioral function of two different but overlapping populations of vHPC GABA neurons that express either PV or GAD65 by selectively inhibiting these neurons with the pharmacogenetic neuromodulator hM4D. We show that acute inhibition of vHPC GABA neurons in adult mice results in behavioral changes relevant to schizophrenia. Inhibiting either PV or GAD65 neurons produced distinct behavioral deficits. Inhibition of PV neurons, affecting ∼80% of the PV neuron population, robustly impaired prepulse inhibition of the acoustic startle reflex (PPI), startle reactivity, and spontaneous alternation, but did not affect locomotor activity. In contrast, inhibiting a heterogeneous population of GAD65 neurons, affecting ∼40% of PV neurons and 65% of cholecystokinin neurons, increased spontaneous and amphetamine-induced locomotor activity and reduced spontaneous alternation, but did not alter PPI. Inhibition of PV or GAD65 neurons also produced distinct changes in network oscillatory activity in the vHPC in vivo. Together, these findings establish a causal role for vHPC GABA neurons in controlling behaviors relevant to schizophrenia and suggest a functional dissociation between the GABAergic mechanisms involved in hippocampal modulation of sensorimotor processes.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".