Evidence map›Paper›PMID 37663143›Full record

ArticleFrontiers in chemistry2023

Hormonal computing: a conceptual approach.

Jordi Vallverdú, Max Talanov, Alexey Leukhin, Elsa Fatykhova, Victor Erokhin

Abstract read
In one paragraph

Article in Frontiers in chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jordi VallverdúICREA Academia, Universitat Autònoma de Barcelona, Bellaterra, Spain.
Max TalanovInstitute for Artificial Intelligence R&D, Novi Sad, Serbia.
Alexey LeukhinLaboratory of Neuromorphic Computing and Neurosimulatons, Kazan Federal University, Kazan, Russia.
Elsa FatykhovaChildren's Republican Clinical Hospital, Ministry of Health of the Republic of Tatarstan, Kazan, Russia.
Victor ErokhinIstituto dei Materiali per l'Elettronica ed il Magnetismo, National Research Council (CNR), Parma, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper provides a conceptual roadmap for the use of hormonal bioinspired models in a broad range of AI, neuroengineering, or computational systems. The functional signaling nature of hormones provides an example of a reliable multidimensional information management system that can solve parallel multitasks. Two existing examples of hormonal computing bioinspired possibilities are shortly reviewed, and two novel approaches are introduced, with a special emphasis on what researchers propose as hormonal computing for neurorehabilitation in patients with complete spinal cord injuries. They extend the use of epidural electrical stimulation (EES) by applying sequential stimulations to limbs through prostheses. The prostheses include various limb models and are connected to a neurostimulation bus called the central pattern generator (CPG). The CPG bus utilizes hormonal computing principles to coordinate the stimulation of the spinal cord and muscles.

Indexed as

bioinspirationhormonal computinghormonesprogrammingsensorssignaling

Identifiers

PMID37663143
PMCPMC10469008

What OpenQuestion holds

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LicenceCC BY
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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.