Deciphering the contribution of oriens-lacunosum/moleculare (OLM) cells to intrinsic theta rhythms using biophysical local field potential (LFP) models
Bibliographic record
Abstract
Abstract Oscillations in local field potentials (LFPs) commonly occur and analyses of them fuel brain function hypotheses. An understanding of the cellular correlates and pathways affecting LFPs is needed but many overlapping pathways in vivo makes this difficult to achieve. A prevalent LFP rhythm in the hippocampus is ‘theta’ (3-12 Hz). Theta rhythms emerge intrinsically in an in vitro whole hippocampus preparation and thus can be produced by local interactions between interneurons and pyramidal (PYR) cells. Overlapping pathways are much reduced in this preparation making it possible to decipher the contribution of different cell types to LFP generation. We focus on oriens-lacunosum/moleculare (OLM) cells as a major class of interneurons in the hippocampus. They can influence PYR cells through two distinct pathways, (i) by direct inhibition of PYR cell distal dendrites, and (ii) by indirect disinhibition of PYR cell proximal dendrites by inhibiting bistratified cells (BiCs) that target them. We use previous inhibitory network models and build biophysical LFP models using volume conductor theory. We assess the effect of OLM cells to ongoing intrinsic LFP theta rhythms by directly comparing our model LFP features with experiment. We find that robust LFP theta responses adhering to reproducible experimental criteria occur only for particular connectivities between OLM cells and BiCs. Decomposition of the LFP reveals that OLM cell inputs onto the PYR cell regulate robustness of LFP responses without affecting average power and that the robust response depends on co-activation of distal inhibition and basal excitation. We use our models to estimate the spatial extent of the region generating LFP theta rhythms, leading us to predict that about 22,000 PYR cells participate in generating the LFP theta rhythm. Besides allowing us to understand OLM cells’ contributions to intrinsic theta rhythms, our work can drive hypothesis developments of cellular contributions in vivo . Author Summary Oscillatory local field potentials (LFPs) are extracellularly recorded potentials that are widely used to interpret information processing in the brain. For example, theta LFP rhythms (3-12 Hz) are correlated with memory processing and it is known that particular inhibitory cell types control their existence. As such, it is critical for us to appreciate how various cell types contribute to the characteristics of LFP rhythms. A precise biophysical modeling scheme linking activity at the cellular level and the recorded signal has been established. However, it is difficult to assess cellular contributions in vivo because of many spatiotemporally overlapping pathways that prevent the unambiguous separation of signals. Using an in vitro preparation that exhibits intrinsic theta (3-12 Hz) rhythms and where there is much less overlap, we build biophysical LFP models to explore cell contributions to ongoing intrinsic theta rhythms. We uncover distinct contributions from different cell types and show that robust theta rhythms depend specifically on one of the cell types. We are able to determine this because our LFP models have direct links with experiment and we are able to perform thousands of simulations.
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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) | 0.000 | 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 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".