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Titolo:
Encoding categorical and coordinate spatial relations without input-outputcorrelations: New simulation models
Autore:
Baker, DP; Chabris, CF; Kosslyn, SM;
Indirizzi:
Harvard Univ, Dept Psychol, Cambridge, MA 02138 USA Harvard Univ Cambridge MA USA 02138 Dept Psychol, Cambridge, MA 02138 USA
Titolo Testata:
COGNITIVE SCIENCE
fascicolo: 1, volume: 23, anno: 1999,
pagine: 33 - 51
SICI:
0364-0213(199901/03)23:1<33:ECACSR>2.0.ZU;2-O
Fonte:
ISI
Lingua:
ENG
Soggetto:
HEMISPHERIC-SPECIALIZATION; CEREBRAL HEMISPHERES; REPRESENTATIONS; ASYMMETRY;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Social & Behavioral Sciences
Citazioni:
21
Recensione:
Indirizzi per estratti:
Indirizzo: Kosslyn, SM Harvard Univ, Dept Psychol, 33 Kirkland St, Cambridge, MA 02138 USA Harvard Univ 33 Kirkland St Cambridge MA USA 02138 A 02138 USA
Citazione:
D.P. Baker et al., "Encoding categorical and coordinate spatial relations without input-outputcorrelations: New simulation models", COGN SCI, 23(1), 1999, pp. 33-51

Abstract

Cook (1995) criticized Kosslyn, Chabris, Marsolek, & Koenig's (1992) network simulation models of spatial relations encoding in port because the absolute position of a stimulus in the input array was correlated with its spatial relation to a landmark;, thus, on at least some trials, the networks did not need to compute spatial relations. The network models reported here include larger input arrays, which allow stimuli to appear in a large range of locations with on equal probability of being above or below a "bar," thus eliminating the confound present in earlier models. The results confirm the original hypothesis that as the size of the network's receptive fields increases, performance on a coordinate spatial relations task (which requires computing precise, metric distance) will be relatively better than on a categorical spatial relations task (which requires computing above/below relative to a landmark).

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Documento generato il 19/01/20 alle ore 08:56:31