Evidence map›Paper›PMID 40233136›Full record

ReviewAnnual review of neuroscience2025

Topological Neuroscience: Linking Circuits to Function.

Carina Curto, Nicole Sanderson

Abstract readReview
In one paragraph

Review in Annual review of neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

2 authors.

Carina CurtoDivision of Applied Mathematics and Carney Institute for Brain Science, Brown University, Providence, Rhode Island, USA; email: carina_curto@brown.edu.
Nicole SandersonDivision of Applied Mathematics and Carney Institute for Brain Science, Brown University, Providence, Rhode Island, USA; email: carina_curto@brown.edu.

Funding

CRCNS: Circuit dynamics in zebrafish larvae: mechanisms, modulation, and mathematical modeling of network topology and attractor dynamicsR01NS120581 · NINDS · PENNSYLVANIA STATE UNIVERSITY, THE · PI CURTO, CARINA · 2020 to 2023
$776k
NINDS NIH HHS R01 NS120581
6 · The paper itself

Abstract

We review recent developments of the use of topology in neuroscience. From grid cells and head direction cells to the geometry of olfactory space, modern applied topology methods such as persistent homology are increasingly being used to study neural circuits and perception. In addition to outlining the big picture and reviewing various applications of topological data analysis (TDA) to neuroscience, we take a deep dive into the basic homology computation to make the underlying mathematics more accessible to neuroscientists. A discussion of practical considerations and pointers to TDA software are also included.

Indexed as

BrainModels, NeurologicalNerve NetNeural PathwaysNeuronsNeurosciencesAnimalsHumansgraphgrid cellshead direction cellsneural circuitspersistent homologysimplicial complextopologytorus

Identifiers

PMID40233136
PMCPMC13148726

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.