Evidence map›Paper›PMID 32381648›Full record

ArticleeNeuro

A Model for Structured Information Representation in Neural Networks of the Brain.

Michael G Müller, Christos H Papadimitriou, Wolfgang Maass, Robert Legenstein

Abstract read
In one paragraph

Article in eNeuro. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Michael G MüllerInstitute of Theoretical Computer Science, Graz University of Technology, Graz 8010, Austria.ORCID 0000-0001-7025-5090
Christos H PapadimitriouComputer Science Department, Columbia University, New York, NY 10027.
Wolfgang MaassInstitute of Theoretical Computer Science, Graz University of Technology, Graz 8010, Austria.ORCID 0000-0002-1178-087X
Robert LegensteinInstitute of Theoretical Computer Science, Graz University of Technology, Graz 8010, Austria robert.legenstein@igi.tugraz.at.

Funding

Austrian Science Fund FWF I 3251
6 · The paper itself

Abstract

Humans can reason at an abstract level and structure information into abstract categories, but the underlying neural processes have remained unknown. Recent experimental data provide the hint that this is likely to involve specific subareas of the brain from which structural information can be decoded. Based on this data, we introduce the concept of assembly projections, a general principle for attaching structural information to content in generic networks of spiking neurons. According to the assembly projections principle, structure-encoding assemblies emerge and are dynamically attached to content representations through Hebbian plasticity mechanisms. This model provides the basis for explaining a number of experimental data and provides a basis for modeling abstract computational operations of the brain.

Indexed as

Models, NeurologicalNeural Networks, ComputerBrainHumansNeuronsassembliescognitionfactorized codesHebbian plasticityspiking neural networksstructural knowledge

Identifiers

PMID32381648
PMCPMC7266140

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.