Evidence map›Paper›PMID 41648483›Full record

ArticlebioRxiv : the preprint server for biology2026

Temporal sequence geometry enables odor recognition and generalization.

Jonathan V Gill, Mürsel Karadas, Shy Shoham, Dmitry Rinberg

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jonathan V GillDepartment of Neuroscience, NYU Grossman School of Medicine, New York, NY.ORCID 0000-0002-8516-296X
Mürsel KaradasDepartment of Neuroscience, NYU Grossman School of Medicine, New York, NY.ORCID 0000-0002-3685-576X
Shy ShohamDepartment of Neuroscience, NYU Grossman School of Medicine, New York, NY.ORCID 0000-0003-0376-3495
Dmitry RinbergDepartment of Neuroscience, NYU Grossman School of Medicine, New York, NY.ORCID 0000-0003-4888-9745

Funding

The Structure of Olfactory Neural and Perceptual SpacesU19NS112953 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI RINBERG, DMITRY · 2019 to 2023
$18.4M
Readout and control of spatiotemporal neuronal codes for behaviorU19NS107464 · NINDS · UNIVERSITY OF CHICAGO · PI BABADI, BEHTASH, CHIALVO, DANTE R · 2018 to 2022
$17.3M
Functional Analysis of Information Processing in the Peripheral Olfactory SystemR01DC022320 · NIDCD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Dmitry Rinberg · 2025 to 2026
$1.3M
NIDCD NIH HHS R01 DC022320NINDS NIH HHS U19 NS107464NINDS NIH HHS U19 NS112953
6 · The paper itself

Abstract

Animals encode sensory stimuli with precisely timed neural activity across modalities. For example, mice can rapidly recognize odors, independent of their concentration, using information relayed from their olfactory bulbs by complex spatiotemporal patterns of mitral and tufted cell (MTC) activity. Yet, it remains unknown how MTC activity patterns are structured, and what role precisely timed activity sequences play in guiding perception. Here we investigated the geometry of MTC odor tuning and the structure of odor response sequences by performing fast 2-photon calcium imaging of hundreds of MTCs with sub-sniff resolution. We constructed a space of MTC tuning using the pairwise correlations between MTC odor responses averaged over a sniff and discovered that odor specific sequential activity traversed this space in smooth, continuous trajectories. Further, we found that the early but not the later part of sequences carried concentration invariant information about odor identity. Finally, inspired by observation that neighboring MTCs in the tuning space are activated together in time independently of the odors presented, we propose a role of activity sequences in training the piriform cortex to learn perceptually generalizable odor representations. To test these ideas, we constructed and analyzed a computational model for sequence-based unsupervised training of synapses from MTCs to the piriform cortex, which revealed that sequential activity across the entire sniff permits perceptual generalization for novel odors, acting as a scaffold for learning relevant activity manifolds between networks.

Identifiers

PMID41648483
PMCPMC12871752

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.