Evidence map›Paper›PMID 24905689›Full record

ArticlePloS one2014

Transfer entropy reconstruction and labeling of neuronal connections from simulated calcium imaging.

Javier G Orlandi, Olav Stetter, Jordi Soriano, Theo Geisel, Demian Battaglia

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

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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

50 citing papers in PubMed.

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  7. Neural network embedding of functional microconnectome.Network neuroscience (Cambridge, Mass.) · 2025
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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

5 authors.

Javier G OrlandiDepartament d'Estructura i Consituents de la Matèria, Universitat de Barcelona, Barcelona, Spain.
Olav StetterMax Planck Institute for Dynamics and Self-Organization, Göttingen, Germany; Georg-August-Universität, Physics Department, Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany.
Jordi SorianoDepartament d'Estructura i Consituents de la Matèria, Universitat de Barcelona, Barcelona, Spain.
Theo GeiselMax Planck Institute for Dynamics and Self-Organization, Göttingen, Germany; Georg-August-Universität, Physics Department, Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany.
Demian BattagliaMax Planck Institute for Dynamics and Self-Organization, Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Institut de Neurosciences des Systèmes, Inserm UMR1106, Aix-Marseille Université, Marseille, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuronal dynamics are fundamentally constrained by the underlying structural network architecture, yet much of the details of this synaptic connectivity are still unknown even in neuronal cultures in vitro. Here we extend a previous approach based on information theory, the Generalized Transfer Entropy, to the reconstruction of connectivity of simulated neuronal networks of both excitatory and inhibitory neurons. We show that, due to the model-free nature of the developed measure, both kinds of connections can be reliably inferred if the average firing rate between synchronous burst events exceeds a small minimum frequency. Furthermore, we suggest, based on systematic simulations, that even lower spontaneous inter-burst rates could be raised to meet the requirements of our reconstruction algorithm by applying a weak spatially homogeneous stimulation to the entire network. By combining multiple recordings of the same in silico network before and after pharmacologically blocking inhibitory synaptic transmission, we show then how it becomes possible to infer with high confidence the excitatory or inhibitory nature of each individual neuron.

Indexed as

EntropyModels, BiologicalOptical ImagingCalciumComputational BiologyImage Processing, Computer-AssistedNerve NetNeuronsCalcium

Identifiers

PMID24905689
PMCPMC4048312

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Registered trials

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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.