CellExplorer: a graphical user interface and a standardized pipeline for visualizing and characterizing single neurons
Bibliographic record
Abstract
Abstract The large diversity of neuron types of the brain, characterized by a unique set of electrophysiological characteristics, provides the means by which cortical circuits perform complex operations. To quantify, compare, and visualize the functional features of single neurons, we have developed the open-source framework, CellExplorer. It consists of three components: a processing module that calculates standardized physiological metrics, performs neuron type classification and detects putative monosynaptic connections, a flexible data structure, and a powerful graphical interface. The graphical interface makes it possible to explore any combination of pre-computed features at the speed of a mouse click. The CellExplorer framework allows users to process and relate their data to a growing collection of “ground truth” neurons from different genetic lines, as well as to tens of thousands of single neurons collected across our labs. We believe CellExplorer will accelerate the linking of physiological properties of single neurons in the intact brain to genetically identified types.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".