- raw_fields
{
"n": null,
"doi": "10.1038/s41593-025-02024-y",
"claim": "Holographic optogenetics + compressive-sensing E connectivity mapping in mouse cortex; method-comparison angle for paired-recording vs optogenetic E->E estimates.",
"cite_key": "Chen2025b",
"evidence": "Characterizing synaptic connectivity in living neural circuits is key to understanding the interplay between network structure and function during behavior. However, the throughput of current in vivo synaptic mapping methods remains very limited. Here, we present a framework for increasing mapping throughput and speed that combines two-photon holographic optogenetic stimulation of presynaptic neurons, whole-cell recordings of postsynaptic responses and compressive sensing reconstruction of sparse connectivity. Under sequential single-cell stimulation, the method enables rapid probing of connectivity across up to 100 potential presynaptic cells within ~5 min in the visual cortex of anesthetized mice, identifying synaptic pairs along with their strength and spatial distribution. Furthermore, in sparsely connected populations, holographic multi-cell stimulation combined with a compressive sensing approach further improved sampling efficiency and recovered most connections found using the sequential approach, with up to a threefold reduction in the number of required measurements. Overall, these results highlight the potential for higher throughput in vivo circuit analysis and d",
"effect_size": null,
"text_access": "abstract_only",
"study_system": "High-throughput synaptic connectivity mapping using in vivo two-photon holographic optogenetics and compressive sensing.",
"argument_role": "supporting",
"replication_status": null,
"claim_source_sentence": "Here, we present a framework for increasing mapping throughput and speed that combines two-photon holographic optogenetic stimulation of presynaptic neurons, whole-cell recordings of postsynaptic responses and compressive sensing reconstruction of spars[e connectivity in mouse cortex].",
"source_provenance_status": "non_substring_match",
"replication_evidence_dois": [],
"effect_size_source_sentence": null
}- source_refs
[
"paper:paper-218c7dbe65b1"
]
- source_span
Here, we present a framework for increasing mapping throughput and speed that combines two-photon holographic optogenetic stimulation of presynaptic neurons, whole-cell recordings of postsynaptic responses and compressive sensing reconstruction of spars[e connectivity in mouse cortex].
- evidence_refs
[
{
"ref": "paper:paper-218c7dbe65b1"
}
]- source_policy
{
"mode": "public_source_pointer_with_short_context",
"notes": [
"Local review repositories are read-only inputs.",
"SciDEX stores paper metadata, structured evidence, file pointers, and short citation contexts; it does not copy full review prose."
],
"source_commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
"source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}- evidence_summary
Characterizing synaptic connectivity in living neural circuits is key to understanding the interplay between network structure and function during behavior. However, the throughput of current in vivo synaptic mapping methods remains very limited. Here, we present a framework for increasing mapping throughput and speed that combines two-photon holographic optogenetic stimulation of presynaptic neurons, whole-cell recordings of postsynaptic responses and compressive sensing reconstruction of sparse connectivity. Under sequential single-cell stimulation, the method enables rapid probing of connectivity across up to 100 potential presynaptic cells within ~5 min in the visual cortex of anesthetized mice, identifying synaptic pairs along with their strength and spatial distribution. Furthermore, in sparsely connected populations, holographic multi-cell stimulation combined with a compressive sensing approach further improved sampling efficiency and recovered most connections found using the sequential approach, with up to a threefold reduction in the number of required measurements. Overall, these results highlight the potential for higher throughput in vivo circuit analysis and deeper insights into brain structure-function relationships.