Enhanced detection sensitivity of neuronal activity patterns using CaMPARI1 vs. CaMPARI2
Bibliographic record
Abstract
Calcium-modulated photoactivatable ratiometric integrator (CaMPARI) is a calcium ion (Ca 2+ )- and light-dependent genetically encoded fluorescent activity integrator that can capture snapshots of neuronal activity through an irreversible process known as photoconversion. This unique property was previously used to label neurons based upon their tuning properties in order to map synaptic connectivity and to record large-scale neuronal activity in freely moving mice without attaching any mechanical device to them. The latest version of CaMPARI (CaMPARI2) was engineered to enhance the contrast generated by photoconverting the green protein to the activity-dependent red form and to reduce the Ca 2+ -independent photoconversion rate compared to the first generation of CaMPARI (CaMPARI1). However, here we show that this optimization process also resulted in reduced photoconversion efficiency of active neurons in the mouse cortex and hippocampus. Through side-by-side comparison of the two CaMPARI sensors under several experimental conditions, we show that CaMPARI1 exhibits a substantially higher red-to-green ratio in active cells than CaMPARI2. In addition, we show that CaMPARI1 also functions as a more sensitive traditional Ca 2+ sensor than CaMPARI2 by producing larger activity-driven dynamic fluorescence changes in the observed neurons. Therefore, we conclude that during the optimization process of CaMPARI2, some of the sensor’s characteristics were not predicted properly by in vitro screening assays, and therefore in vivo screening and validation steps should be included in future optimization attempts to increase the predictability of screening pipelines.
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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 | 0.001 |
| 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".