False memories for scenes using the DRM paradigm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11210%2F21%3A10421380" target="_blank" >RIV/00216208:11210/21:10421380 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68081740:_____/21:00533426

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=B61nzwQyQC" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=B61nzwQyQC</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.visres.2020.09.009" target="_blank" >10.1016/j.visres.2020.09.009</a>

Jazyk výsledku

angličtina

Název v původním jazyce

False memories for scenes using the DRM paradigm

Popis výsledku v původním jazyce

People are remarkably good at remembering photographs. To further investigate the nature of the stored representations and the fidelity of human memories, it would be useful to evaluate the visual similarity of stimuli presented in experiments. Here, we explored the possible use of convolutional neural networks (CNN) as a measure of perceptual or representational similarity of visual scenes with respect to visual memory research. In Experiment 1, we presented participants with sets of nine images from the same scene category and tested whether they were able to detect the most distant scene in the image space defined by CNN. Experiment 2 was a visual variant of the Deese-Roediger-McDermott paradigm. We asked participants to remember a set of photographs from the same scene category. The photographs were preselected based on their distance to a particular visual prototype (defined as centroid of the image space). In the recognition test, we observed higher false alarm rates for scenes closer to this visual prototype. Our findings show that the similarity measured by CNN is reflected in human behavior: people can detect odd-one-out scenes or be lured to false alarms with similar stimuli. This method can be used for further studies regarding visual memory for complex scenes.

Název v anglickém jazyce

False memories for scenes using the DRM paradigm

Popis výsledku anglicky

People are remarkably good at remembering photographs. To further investigate the nature of the stored representations and the fidelity of human memories, it would be useful to evaluate the visual similarity of stimuli presented in experiments. Here, we explored the possible use of convolutional neural networks (CNN) as a measure of perceptual or representational similarity of visual scenes with respect to visual memory research. In Experiment 1, we presented participants with sets of nine images from the same scene category and tested whether they were able to detect the most distant scene in the image space defined by CNN. Experiment 2 was a visual variant of the Deese-Roediger-McDermott paradigm. We asked participants to remember a set of photographs from the same scene category. The photographs were preselected based on their distance to a particular visual prototype (defined as centroid of the image space). In the recognition test, we observed higher false alarm rates for scenes closer to this visual prototype. Our findings show that the similarity measured by CNN is reflected in human behavior: people can detect odd-one-out scenes or be lured to false alarms with similar stimuli. This method can be used for further studies regarding visual memory for complex scenes.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50101 - Psychology (including human - machine relations)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Vision Research

ISSN

0042-6989

e-ISSN

—

Svazek periodika

178

Číslo periodika v rámci svazku

Jan

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

12

Strana od-do

55-66

Kód UT WoS článku

000604937900007

EID výsledku v databázi Scopus

2-s2.0-85093702816