Evidence map›Paper›PMID 30597931›Full record

ArticleAnimals : an open access journal from MDPI2018

Evaluation of Sheep Anticipatory Response to a Food Reward by Means of Functional Near-Infrared Spectroscopy.

Matteo Chincarini, Lina Qiu, Lorenzo Spinelli, Alessandro Torricelli, Michela Minero, Emanuela Dalla Costa, Massimo Mariscoli, Nicola Ferri, Melania Giammarco, Giorgio Vignola

Open access · goldAbstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

11 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. Finding biomarkers of experience in animals.Journal of animal science and biotechnology · 2024
    Review
  4. Article
  5. Non-invasive estimation ofFrontiers in veterinary science · 2023
    Article
  6. Review
  7. Shining new light on sensory brain activation and physiological measurement in seals using wearable optical technology.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  8. Dual-slope method for enhanced depth sensitivity in diffuse optical spectroscopy.Journal of the Optical Society of America. A, Optics, image science, and vision · 2019
    Article
  9. Article
  10. Article
  11. Review
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

10 authors at 5 institutions in 1 country.

Matteo ChincariniUniversità degli Studi di Teramo, Facoltà di Medicina Veterinaria, Località Piano d'Accio S.P. 18, 64100 Teramo, Italy. mchincarini@unite.it.ORCID 0000-0001-6369-4992
Lina QiuPolitecnico di Milano, Dipartimento di Fisica, piazza Leonardo da Vinci 32, 20133 Milano, Italy. lina.qiu@polimi.it.
Lorenzo SpinelliConsiglio Nazionale delle Ricerche, Istituto di Fotonica e Nanotecnologie, piazza Leonardo da Vinci 32, 20133 Milano, Italy. lorenzo.spinelli@polimi.it.
Alessandro TorricelliPolitecnico di Milano, Dipartimento di Fisica, piazza Leonardo da Vinci 32, 20133 Milano, Italy. alessandro.torricelli@polimi.it.
Michela MineroUniversità degli Studi di Milano, Dipartimento di Medicina Veterinaria, via Celoria 10, 20133 Milano, Italy. michela.minero@unimi.it.ORCID 0000-0001-8285-5501
Emanuela Dalla CostaUniversità degli Studi di Milano, Dipartimento di Medicina Veterinaria, via Celoria 10, 20133 Milano, Italy. emanuela.dallacosta@unimi.it.ORCID 0000-0002-5037-3759
Massimo MariscoliUniversità degli Studi di Teramo, Facoltà di Medicina Veterinaria, Località Piano d'Accio S.P. 18, 64100 Teramo, Italy. mmariscoli@unite.it.
Nicola FerriIstituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Campo Boario, 64100 Teramo, Italy. n.ferri@izs.it.
Melania GiammarcoUniversità degli Studi di Teramo, Facoltà di Medicina Veterinaria, Località Piano d'Accio S.P. 18, 64100 Teramo, Italy. mgiammarco@unite.it.
Giorgio VignolaUniversità degli Studi di Teramo, Facoltà di Medicina Veterinaria, Località Piano d'Accio S.P. 18, 64100 Teramo, Italy. gvignola@unite.it.
University of Teramo · ITIstituto di Fotonica e Nanotecnologie · ITUniversity of Milan · ITIstituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale · ITPolitecnico di Milano · IT

Funding

Doctoral program - Università degli Studi di Teramo (Italy) -Ministero dell'Istruzione, dell'Università e della Ricerca 2015Y5W9YP
6 · The paper itself

Abstract

Anticipatory behaviour to an oncoming food reward can be triggered via classical conditioning, implies the activation of neural networks, and may serve to study the emotional state of animals. The aim of this study was to investigate how the anticipatory response to a food reward affects the cerebral cortex activity in sheep. Eight ewes from the same flock were trained to associate a neutral auditory stimulus (water bubble) to the presence of a food reward (maize grains). Once conditioned, sheep were trained to wait 15 s behind a gate before accessing a bucket with food (anticipation phase). For 6 days, sheep were submitted to two sessions of six consecutive trials each. Behavioural reaction was filmed and changes in cortical oxy- and deoxy-hemoglobin concentration ([ΔO₂Hb] and [ΔHHb] respectively) following neuronal activation were recorded by functional near infrared spectroscopy (fNIRS). Compared to baseline, during the anticipation phase sheep increased their active behaviour, kept the head oriented to the gate (Wilcoxon's signed rank test;

Indexed as

animal welfareanticipatory behaviourfunctional near-infrared spectroscopy (fNIRS)neuroimagingsheep

Identifiers

PMID30597931
PMCPMC6356716
OpenAlexW2908314590

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.