Bidirectional Regulation of Cognitive and Anxiety-like Behaviors by Dentate Gyrus Mossy Cells in Male and Female Mice
Bibliographic record
Abstract
The dentate gyrus (DG) of the hippocampus is important for cognition and behavior. However, the circuits underlying these functions are unclear. DG mossy cells (MCs) are potentially important because of their excitatory synapses on the primary cell type, granule cells (GCs). However, MCs also activate GABAergic neurons, which inhibit GCs. We used viral delivery of designer receptors exclusively activated by designer drugs (DREADDs) in mice to implement a gain- and loss-of-function study of MCs in diverse behaviors. Using this approach, manipulations of MCs could bidirectionally regulate behavior. The results suggest that inhibiting MCs can reduce anxiety-like behavior and improve cognitive performance. However, not all cognitive or anxiety-related behaviors were influenced, suggesting specific roles of MCs in some, but not all, types of cognition and anxiety. Notably, several behaviors showed sex-specific effects, with females often showing more pronounced effects than the males. We also used the immediate early gene c-Fos to address whether DREADDs bidirectionally regulated MC or GC activity. We confirmed excitatory DREADDs increased MC c-Fos. However, there was no change in GC c-Fos, consistent with MC activation leading to GABAergic inhibition of GCs. In contrast, inhibitory DREADDs led to a large increase in GC c-Fos, consistent with a reduction in MC excitation of GABAergic neurons, and reduced inhibition of GCs. Together, these results suggest that MCs regulate anxiety and cognition in specific ways. We also raise the possibility that cognitive performance may be improved by reducing anxiety. SIGNIFICANCE STATEMENT The dentate gyrus (DG) has many important cognitive roles as well as being associated with affective behavior. This study addressed how a glutamatergic DG cell type called mossy cells (MCs) contributes to diverse behaviors, which is timely because it is known that MCs regulate the activity of the primary DG cell type, granule cells (GCs), but how MC activity influences behavior is unclear. We show, surprisingly, that activating MCs can lead to adverse behavioral outcomes, and inhibiting MCs have an opposite effect. Importantly, the results appeared to be task-dependent and showed that testing both sexes was important. Additional experiments indicated what MC and GC circuitry was involved. Together, the results suggest how MCs influence behaviors that involve the DG.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".