Examining Complexity across Domains: Relating Subjective and Objective Measures of Affective Environmental Scenes, Paintings and Music

Abstract

Subjective complexity has been found to be related to hedonic measures of preference, pleasantness and beauty, but there is no consensus about the nature of this relationship in the visual and musical domains. Moreover, the affective content of stimuli has been largely neglected so far in the study of complexity but is crucial in many everyday contexts and in aesthetic experiences. We thus propose a cross-domain approach that acknowledges the multidimensional nature of complexity and that uses a wide range of objective complexity measures combined with subjective ratings. In four experiments, we employed pictures of affective environmental scenes, representational paintings, and Romantic solo and chamber music excerpts. Stimuli were pre-selected to vary in emotional content (pleasantness and arousal) and complexity (low versus high number of elements). For each set of stimuli, in a between-subjects design, ratings of familiarity, complexity, pleasantness and arousal were obtained for a presentation time of 25 s from 152 participants. In line with Berlyne’s collative-motivation model, statistical analyses controlling for familiarity revealed a positive relationship between subjective complexity and arousal, and the highest correlations were observed for musical stimuli. Evidence for a mediating role of arousal in the complexity-pleasantness relationship was demonstrated in all experiments, but was only significant for females with regard to music. The direction and strength of the linear relationship between complexity and pleasantness depended on the stimulus type and gender. For environmental scenes, the root mean square contrast measures and measures of compressed file size correlated best with subjective complexity, whereas only edge detection based on phase congruency yielded equivalent results for representational paintings. Measures of compressed file size and event density also showed positive correlations with complexity and arousal in music, which is relevant for the discussion on which aspects of complexity are domain-specific and which are domain-general.

Titles change the esthetic appreciations of paintings

“…This argument also fits more general perception research that shows that dis-fluent processed stimuli due to novelty, complexity, or ambiguity are often liked (Hekkert et al, 2003; Jakesch and Leder, 2009; Marin and Leder, 2013). …”

Berlyne Revisited: Evidence for the Multifaceted Nature of Hedonic Tone in the Appreciation of Paintings and Music

“…To be sure, Berlyne’s (1971, 1974a) psychobiological model of esthetic experience and his New Experimental Esthetics have been very influential in the field (Konečni, 1978; Silvia, 2005), but besides empirical support for his theory a non-negligible number of conflicting results have also been reported (Vitz, 1964; Osborne and Farley, 1970; Kreitler et al, 1974; Nicki and Gale, 1977; Krupinski and Locher, 1988; Neperud and Marschalek, 1988; Messinger, 1998; Stamps Iii, 2002; Eisenberg and Thompson, 2003; Nadal et al, 2010; Marin and Leder, 2013). Therefore, the current research project sought to contribute to the emerging literature by offering explanations for the discrepant research findings regarding Berlyne’s theory.…”

“…Berlyne’s theory has been put to test with a wide range of stimuli, ranging from abstract patterns to paintings and from simple melodic sequences to real music (for a review see (Nadal, 2007; Nadal et al, 2010; Marin and Leder, 2013). Although Berlyne’s psychobiological model has been fruitful in the study of psychology and the arts (Silvia, 2005; Jacobsen, 2006), it has also generated criticism, mostly stemming from the fact that the inverted-U shape relationship between collative variables and hedonic value could not always be replicated.…”

The Use of Eye Tracking in Non-Immersive Virtual Reality for Cognitive Assessment

“…Ambos os pares de imagens USO DE EYE TRACKING EM REALIDADE VIRTUAL 26 www.sp-ps.pt continham vários objetos com sete diferenças entre elas. A complexidade visual objetiva para cada par de imagens foi calculada com base método de deteção de arestas de Canny (raio do kernel Gaussiano = 5px; limiar 2.5 -7.5px) e deteção de perímetro (Marin & Leder, 2013 O protocolo incluiu um questionário socio demográfico (género, idade, nacionalidade), juntamente com questões para avaliar os conhecimentos de informática, e o MMSE para avaliar as capacidades cognitiva (Folstein et al, 1975). Todos os participantes foram avaliados individualmente, com um tempo de duração entre 10 a 15 minutos.…”