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Record W4407931154 · doi:10.1101/2025.02.24.639992

Axially decoupled photo-stimulation and two photon readout ( <i>ADePT</i> ) for mapping functional connectivity of neural circuits

2025· preprint· en· W4407931154 on OpenAlexaff
Matthew Koh, Francesca Anselmi, Sanjeev Kumar Kaushalya, Diego E. Hernández, Walter G. Bast, Pablo S. Villar, Honggoo Chae, Martin B. Davis, S. Sai Surya Teja, Zhe Qu, Viviana Gradinaru, Priyanka Gupta, Arkarup Banerjee, Dinu F. Albeanu

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsCanadian Society for Digital Humanities
Fundersnot available
KeywordsOptogeneticsNeuroscienceOlfactory bulbBiological neural networkStimulationInhibitory postsynaptic potentialExcitatory postsynaptic potentialSomaGABAergicPremovement neuronal activityBiologyCentral nervous system

Abstract

fetched live from OpenAlex

Abstract All-optical in vivo physiology enables three-dimensional interrogation of neural circuits function. Here, we introduce ADePT (Axially-Decoupled Photo-stimulation and Two-photon readout), a strategy that combines flexible optogenetic stimulation with neural activity imaging. ADePT achieves axially contained widefield patterned stimulation by coupling a digital micro-mirror device illuminated by a solid-state laser to a motorized holographic diffuser, while in parallel performing multiphoton imaging across different z-planes. As a proof of principle, we apply ADePT to map excitatory and inhibitory functional connectivity in the mouse early olfactory system. By controlling activity in individual glomeruli on the olfactory bulb surface and recording responses from output mitral and tufted cells in deeper layers, we identify cohorts of sister cells driven by the same parent glomerulus and analyze their distinct connectivity patterns. We further report specificity in the inhibitory circuitry, as we find that GABAergic/dopaminergic (DAT+) interneurons associated with different glomeruli selectively suppress baseline and odor-evoked activity in distinct mitral and tufted cell populations. Together, these results establish ADePT as a platform for high-throughput functional connectivity mapping in optically accessible brain regions.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.053
GPT teacher head0.287
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

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