Low throughput screening in neuroscience: using light to study central synapses one at a time
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Neurophotonic approaches have fostered substantial progress in our understanding of the brain by providing an assortment of means to either monitor or manipulate neural processes. Among these approaches, the development of two-photon uncaging provides a useful and flexible approach to manipulate the activity of individual synapses. In this short piece, we explore how this technique has emerged at the intersection of chemistry, optics, and electrophysiology to enable spatially and temporally precise photoactivation for studying functional aspects of synaptic transmission and dendritic integration. We discuss advantages and limitations of this approach, focusing on our efforts to study several functional aspects of glutamate receptors using uncaging of glutamate. Among other advancements, this approach has contributed to further our understanding of the subcellular regulation, trafficking, and biophysical features of glutamate receptors (e.g., desensitization and silent synapse regulation), the dynamics of spine calcium, and the integrative features of dendrites, and how these functions are altered by several forms of plasticity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it