Dentate gyrus mossy cells exhibit sparse coding via adaptive spike threshold dynamics
Bibliographic record
Abstract
Abstract Hilar mossy cells (hMCs) are glutamatergic neurons in the dentate gyrus (DG) that receive inputs primarily from DG granule cells (GCs), CA3 pyramidal cells and local inhibitory interneurons. The hMCs then provide direct excitatory and disynaptic inhibitory feedback input to GCs. Behavioral and in vivo single unit recording experiments have implicated hMCs in pattern separation as well as is in spatial navigation and learning. It has, however, been difficult to mechanistically link the in vivo physiological behavior of hMCs with their intrinsic excitability properties that convert their synaptic inputs into spiking output. Here, we carried out electrophysiological recordings from the main cell types in the DG and found that hMCs displayed a highly adaptive threshold acting over a remarkably protracted time-scale. The hMC spike threshold increased linearly with increasing current stimulation and saturated at high current intensities. This threshold also increased in response to spiking and this effect also decayed over a long timescale, allowing for activity-dependent summation that limited hMC firing rates. This mechanism operates in parallel with a prominent medium after-hyperpolarizing potential (AHP) generated by the small conductance K + channel. Based on experimentally derived parameters, we developed a phenomenological exponential integrate-and-fire model that closely mimics the hMC adaptive threshold. This lightweight model is amenable to its incorporation into large network models of the DG that will be conducive to deepen our understanding of the neural bases of pattern separation, spatial learning and navigation in the hippocampus. Statement of significance Recent studies on hilar mossy cells have revealed that they are implicated in spatial navigation and mnemonic functions. Yet, the basic intrinsic characterization of these hMCs is still too superficial to explain their spiking behavior in vivo . Here, we describe novel biophysical properties of hMCs, including an independent relationship between spike latency and spike threshold as well as a slowly adapting spike threshold. These findings complement several other biophysical and connectivity similarities between hMCs and CA3 pyramidal cells, while emphasizing the contrast with hilar interneurons. Additionally, our results are well captured by a phenomenological model of the hMC which provides a useful framework to study the neural substrate of spatial navigation and learning in the dentate gyrus.
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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) | 0.000 | 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) | 0.001 | 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".