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Enregistrement W4300529265 · doi:10.24124/2022/59297

An examination of conceptual knowledge using near-infrared spectroscopy and electroencephalography

2022· dissertation· en· W4300529265 sur OpenAlexaff
Brian Duffels

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineNeuroscience
ThématiqueEEG and Brain-Computer Interfaces
Établissements canadiensUniversity of AlbertaUniversity of Northern British Columbia
Organismes subventionnairesnon disponible
Mots-clésAmodal perceptionCognitive psychologyPsychologyTask (project management)CategorizationElectroencephalographySemantic memoryCognitionPerceptionGrounded theoryPrefrontal cortexBrain activity and meditationCognitive scienceComputer scienceArtificial intelligenceNeuroscienceQualitative research

Résumé

récupéré en direct d'OpenAlex

Traditionally, models of conceptual knowledge have relied upon amodal theories that largely overlook how environmental stimuli are converted into amodal representations and how perceptions reactivate these representations and translate them back into subjective modal experiences. Developed more recently, grounded cognition theories propose that physical experiences and conceptual knowledge rely, at least in part, on the same brain regions. Thus, conceptual knowledge is hypothesized to be experienced through the reactivation of the same brain regions that are activated during physical experiences with the environment. Furthermore, if these grounded hypotheses are correct, researchers should be able to observe predictable influences of grounded information on brain activity as well as participant response latencies and accuracy in experimental conditions. To this end, three experiments were conducted testing these hypotheses using semantic categorization tasks while simultaneous recordings were taken using functional near infrared spectroscopy (NIRS) and electroencephalography. It was hypothesized that the influence of automatically reactivated grounded information would be facilitatory (i.e., resulting in faster and more accurate responses for semantically richer words) when it was task congruent, but would be inhibitory (i.e., resulting in slower and less accurate responses for semantically richer words) when it was task incongruent, thus illustrating the automatic simulation of grounded information in the processing and retrieval of conceptual knowledge. NIRS was employed to monitor event-related patterns of prefrontal cortex (PFC) hemodynamics associated with these tasks. It was hypothesized that trials with high levels of task-relevant semantic information would be discernably different than those with low levels or those trials high in task-incongruent information. That is, given the high levels of task-relevant semantic information, these trials should be comparatively easier, thus requiring less activity in the PFC, resulting in less pronounced hemodynamic responses. Electroencephalography was employed to monitor the full-scalp event-related patterns of brain activity associated with the experimental tasks. It was hypothesized that event-related potential deflections and scalp topography would be able to discern qualitatively and quantitatively different patterns of activity as a function of the amount and relevance of grounded information obtained through physical and emotional experiences with the word stimuli’s referents. The behavioural, accuracy, and electroencephalography data generally support these hypotheses. When a stimulus’s grounded information is high and task relevant, participants responded more quickly and accurately, and had discernably different patterns of brain activity than when a stimulus’s grounded information was low and task relevant. When a stimulus’s grounded information was high and task-irrelevant, participants were slower and less accurate, and exhibited patterns of brain activity that reflected both the additional semantic information and the additional processing necessary to reconcile the task incongruence. Unfortunately, data obtained from NIRS failed to illustrate meaningful condition differences. Possible reasons for this are discussed in detail in Chapter 3. Collectively, the data presented in this dissertation serve to advance and extend the claims made by grounded cognition theorists by illustrating the automatic simulation of information obtained through interactions with the environment. Further research is required to extend this work to other brain regions and to develop NIRS methods that can address these research questions.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,026
Tête enseignante GPT0,317
Écart entre enseignants0,292 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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