False memories for scenes using the DRM paradigm

Result code in 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>

Alternative codes found

RIV/68081740:_____/21:00533426

Result on the web

<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>

Result language

angličtina

Original language name

False memories for scenes using the DRM paradigm

Original language description

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.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

50101 - Psychology (including human - machine relations)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2021

Confidentiality

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

Name of the periodical

Vision Research

ISSN

0042-6989

e-ISSN

—

Volume of the periodical

178

Issue of the periodical within the volume

Jan

Country of publishing house

GB - UNITED KINGDOM

Number of pages

12

Pages from-to

55-66

UT code for WoS article

000604937900007

EID of the result in the Scopus database

2-s2.0-85093702816