Zero-dimensional noise is not suitable for characterizing processing properties of detection mechanisms
Notice bibliographique
Résumé
Baker and Meese (2012) have recently published an article entitled, ‘‘Zero-dimensional noise: The best mask you never saw.’’ In this article, they describe 0D noise, which basically consists in randomly jittering the contrast of the target stimulus. In a series of experiments, they compared processing properties for a detection task in 0D with 2D noise (i.e., white pixel noise). They found that humans behave more like a noisy ideal observer under 0D than 2D noise. They argued that 0D noise is more suitable for equivalent noise paradigms than pixel noise because 0D noise introduces activity only within the detection mechanisms, whereas 2D noise also affects detection through cross-channel interactions. They propose that ‘‘0D noise offers a cleaner method for assessing the factors limiting human performance’’ (Baker & Meese, 2012, p. 9) within equivalent noise paradigms. Unfortunately, 0D noise is not suitable for characterizing processing properties of detection mechanisms because (a) the processing strategy underlying contrast detection in 0D noise differs from the one in no noise, and (b) detection threshold in 0D noise does not depend on any properties of the detection process. An underlying assumption of equivalent noise paradigms (Pelli, 1981) is that the same processing strategy operates in absence and presence of noise (i.e., the noise-invariant processing assumption, Allard & Cavanagh, 2011, 2012). Thus, if different processing strategies underlie contrast detection in no and 0D noise, then this compromises the application of the equivalent noise paradigms. A hint that the processing strategy differs in no noise and 0D noise is that the typical instructions given by the experimenter to the observer in detection tasks in no noise are not sufficient in 0D noise. For instance, for a contrast detection task in noiseless condition using a 2-interval forced choice paradigm (as used by Baker & Meese, 2012), the instructions can simply be: ‘‘Indicate whether the target was presented in the first or second interval.’’ These simple instructions are not sufficient in 0D noise because the observer usually perceives two stimuli, one in each interval. Consequently, in 0D noise, observers are not performing a ‘‘detection’’ task per se since they are usually detecting the target in both intervals. They are rather discriminating two contrasts while considering a polarity opposite to the target as a negative contrast. An additional indication that a ‘‘detection’’ task in 0D noise is really a discrimination task is that a classical yes-no detection task would be confusing and impractical in 0D noise because the observer almost always perceives a target. Consequently, given that adding 0D noise makes a detection task shift to a discrimination task and that this violates the noise-invariant processing assumption underlying equivalent noise paradigms, we conclude that 0D noise is not suitable for equivalent noise paradigms. Baker and Meese acknowledge that the processing strategy may differ between 0D and 2D noise because 2D noise contains ‘‘activity in the extraneous mechanisms’’ (Baker & Meese, 2012, p. 9), while 0D noise does not. However, they did not address the more relevant question of whether the processing strategy differs or not when the target is embedded in internal noise (i.e., no external noise) and in high (0D) noise. This question is crucial because equivalent noise paradigms implicitly assume that the processing strategy is the same in low and high noise. Given that internal noise is present in all mechanisms, if the processing strategy differs between 0D and 2D noise due to the activity in the extraneous mechanisms, it would also likely differ between no noise and 0D noise. In a recent study, Allard and Cavanagh (2011) have
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
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