Evidence map›Paper›PMID 22053155›Full record

ArticleFrontiers in neuroinformatics2011

Knowledge synthesis with maps of neural connectivity.

Marcelo Tallis, Richard Thompson, Thomas A Russ, Gully A P C Burns

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 42% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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 at 1 institution in 1 country.

Marcelo TallisInformation Sciences Institute, University of Southern California Marina del Rey, CA, USA.
Richard Thompson
Thomas A Russ
Gully A P C Burns
University of Southern California · US

Funding

BIO-INFORMATICS RESEARCH NETWORK COORDINATING CENTER (BIRN-CC)U24RR025736 · NCRR · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KESSELMAN, CARL · 2009 to 2011
$15.0M
Bio-Informatics Research Network Coordinating Center (BIRN-CC)U24GM104203 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KESSELMAN, CARL · 2012 to 2013
$8.3M
Informatics Infrastructure for vector-based neuroanatomical atlasesR01MH079068 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BURNS, GULLY A. · 2009 to 2013
$1.6M
BioScholar: a Biomedical Knowledge Engineering framework based on the published lR01GM083871 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BURNS, GULLY A. · 2008 to 2011
$1.0M
NCRR NIH HHS U24 RR025736NIGMS NIH HHS R01 GM083871NIGMS NIH HHS U24 GM104203NIMH NIH HHS R01 MH079068
6 · The paper itself

Abstract

This paper describes software for neuroanatomical knowledge synthesis based on neural connectivity data. This software supports a mature methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus, and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macro connections using the Swanson third edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the data mapping components within a unified web-application. As a step toward developing an accurate sub-regional account of neural connectivity, we provide navigational access between the data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called "Knowledge Engineering from Experimental Design" (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web-application that allows anatomical data sets to be described within a standard experimental context and thus indexed by non-spatial experimental design features.

Indexed as

knowledge engineeringneural connectivityneuroanatomical mappingtract-tracing

Identifiers

PMID22053155
PMCPMC3205380
OpenAlexW2036824853

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.