MétaCan
Menu
Back to cohort
Record W3199868074 · doi:10.1088/1741-2552/ac28d2

Cortical network and connectivity underlying hedonic olfactory perception

2021· article· en· W3199868074 on OpenAlexaff
Alejandro Luis Callara, Alberto Greco, Johannes Frasnelli, Gianluca Rho, Nicola Vanello, Enzo Pasquale Scilingo

Bibliographic record

VenueJournal of Neural Engineering · 2021
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersMinistero dell’Istruzione, dell’Università e della RicercaEuropean CommissionDipartimenti di Eccellenza
KeywordsPosterior cingulateOrbitofrontal cortexPrecuneusParahippocampal gyrusNeurosciencePsychologyOdorMedial frontal gyrusPerceptionStimulus (psychology)Superior frontal gyrusValence (chemistry)Cognitive psychologyCognitionTemporal lobePrefrontal cortexChemistryEpilepsy

Abstract

fetched live from OpenAlex

Abstract Objective. The emotional response to olfactory stimuli implies the activation of a complex cascade of events triggered by structures lying in the limbic system. However, little is known about how this activation is projected up to cerebral cortex and how different cortical areas dynamically interact each other. Approach. In this study, we acquired EEG from human participants performing a passive odor-perception task with odorants conveying positive, neutral and negative valence. A novel methodological pipeline integrating global field power (GFP), independent component analysis (ICA), dipole source localization was applied to estimate effective connectivity in the challenging scenario of single-trial low-synchronized stimulation. Main results. We identified the brain network and the neural paths, elicited at different frequency bands, i.e. <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"><mml:mi>θ</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mn>4</mml:mn><mml:mo>−</mml:mo><mml:mn>7</mml:mn><mml:mrow><mml:mi mathvariant="normal">H</mml:mi><mml:mi mathvariant="normal">z</mml:mi></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"><mml:mi>α</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mn>8</mml:mn><mml:mo>−</mml:mo><mml:mn>12</mml:mn><mml:mrow><mml:mi mathvariant="normal">H</mml:mi><mml:mi mathvariant="normal">z</mml:mi></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"><mml:mi>β</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mn>13</mml:mn><mml:mo>−</mml:mo><mml:mn>30</mml:mn><mml:mrow><mml:mi mathvariant="normal">H</mml:mi><mml:mi mathvariant="normal">z</mml:mi></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:math> , involved in odor valence processing. This brain network includes the orbitofrontal cortex (OFC), the cingulate gyrus (CgG), the superior temporal gyrus (STG), the posterior cingulate cortex/precuneus (PCC/PCu) and the parahippocampal gyrus (PHG). It was analyzed using a time-varying multivariate autoregressive model to resolve time-frequency causal interactions. Specifically, the OFC acts as the main node for odor perception and evaluation of pleasant and unpleasant stimuli, whereas no specific path was observed for a neutral stimulus. Significance. The results introduce new evidences on the role of the OFC during hedonic perception and underpin its specificity during the odor valence assessment. Our findings suggest that, after the odor onset different, bidirectional interactions occur between the OFC and other brain regions associated with emotion recognition/categorization and memory according to the stimulus valence. This outcome unveils how the hedonic olfactory network dynamically changes based on odor valence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.334

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.179
GPT teacher head0.279
Teacher spread0.101 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Neural EngineeringSame topicOlfactory and Sensory Function StudiesFrench-language works237,207