Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


2006 | 37 | 1 | 7-15

Article title

A neural model of mere exposure: The EXAC mechanism

Authors

Title variants

Languages of publication

EN

Abstracts

EN
Previous research has shown that 'the mere exposure effect' is strongest for subliminal presentations (meta-analysis: Bornstein, 1989). Further, in the range of subliminal presentations times, the relation between recognition and affect is paradoxical - participants cannot effectively recognize novel from familiar stimuli, yet they perceive the familiar stimuli as more pleasant. The mechanisms of this paradoxical phenomenon (named 'the primacy of affect'; Zajonc, 1984) remain unexplained. In this paper, we propose a simple neural network model ('EXAC': Exposure and Affect Counter) of the subliminal mere exposure effect. Analysis of the model's performance shows that the capability for fast novelty detection can be a natural property of very simple network structures. The novelty detection function generated by EXAC fits the affective function obtained from behavioral data. For weakly learned patterns (corresponding to short presentation times in behavioral research), the network model 'prefers' known stimuli before it can recognize them. AUTHORS' NOTE: The data in this paper and earlier description of the model was previously published in Polish in Drogosz M., & Nowak A., (1995) Symulacyjna teoria efektu ekspozycji: siec neuropodobna EXAC. Przeglad Psychologiczny, 38, 65–84.

Keywords

Year

Volume

37

Issue

1

Pages

7-15

Physical description

Document type

ARTICLE

Contributors

author
author
  • M. Drogosz, Instytut Psychologii PAN, ul. Chodakowska 19/31, 03-815 Warszawa, Poland

References

Document Type

Publication order reference

Identifiers

CEJSH db identifier
06PLAAAA01773827

YADDA identifier

bwmeta1.element.a3aaf394-502f-30db-bbe9-cb40932a2073
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.