Evidence map›Paper›PMID 26855758›Full record

ArticleInterface focus2016

Advancing multiscale structural mapping of the brain through fluorescence imaging and analysis across length scales.

L J Hogstrom, S M Guo, K Murugadoss, M Bathe

Abstract read
In one paragraph

Article in Interface focus, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Imaging the aged brain: pertinence and methods.Quantitative imaging in medicine and surgery · 2019
    Review
  5. Hard X-Ray Nanoholotomography: Large-Scale, Label-Free, 3D Neuroimaging beyond Optical Limit.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2018
    Article
  6. Article
  7. 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

4 authors.

L J HogstromDepartment of Biological Engineering , Massachusetts Institute of Technology , 77 Massachusetts Avenue, Building 16, Room 255, Cambridge, MA 02139 , USA.
S M GuoDepartment of Biological Engineering , Massachusetts Institute of Technology , 77 Massachusetts Avenue, Building 16, Room 255, Cambridge, MA 02139 , USA.
K MurugadossDepartment of Biological Engineering , Massachusetts Institute of Technology , 77 Massachusetts Avenue, Building 16, Room 255, Cambridge, MA 02139 , USA.
M BatheDepartment of Biological Engineering , Massachusetts Institute of Technology , 77 Massachusetts Avenue, Building 16, Room 255, Cambridge, MA 02139 , USA.

Funding

Ultra-Multiplexed Nanoscale In Situ Proteomics for Understanding Synapse TypesU01MH106011 · NIMH · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BATHE, MARK, BOYDEN, EDWARD S. · 2014 to 2016
$2.2M
NIMH NIH HHS U01 MH106011
6 · The paper itself

Abstract

Brain function emerges from hierarchical neuronal structure that spans orders of magnitude in length scale, from the nanometre-scale organization of synaptic proteins to the macroscopic wiring of neuronal circuits. Because the synaptic electrochemical signal transmission that drives brain function ultimately relies on the organization of neuronal circuits, understanding brain function requires an understanding of the principles that determine hierarchical neuronal structure in living or intact organisms. Recent advances in fluorescence imaging now enable quantitative characterization of neuronal structure across length scales, ranging from single-molecule localization using super-resolution imaging to whole-brain imaging using light-sheet microscopy on cleared samples. These tools, together with correlative electron microscopy and magnetic resonance imaging at the nanoscopic and macroscopic scales, respectively, now facilitate our ability to probe brain structure across its full range of length scales with cellular and molecular specificity. As these imaging datasets become increasingly accessible to researchers, novel statistical and computational frameworks will play an increasing role in efforts to relate hierarchical brain structure to its function. In this perspective, we discuss several prominent experimental advances that are ushering in a new era of quantitative fluorescence-based imaging in neuroscience along with novel computational and statistical strategies that are helping to distil our understanding of complex brain structure.

Indexed as

brain structurefluorescence imagingmultiscale analysis and modelling

Identifiers

PMID26855758
PMCPMC4686247

What OpenQuestion holds

Textmetadata
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.