Affective creativity meets classic creativity in the scanner

Abstract

The investigation of neurocognitive processes underlying more real-life creative behavior is among the greatest challenges in creativity research. In this fMRI study, we addressed this issue by investigating functional patterns of brain activity while participants were required to be creative in an affective context. Affective creativity was assessed in terms of individual's inventiveness in generating alternative appraisals for anger-evoking events, which has recently emerged as a new ability concept in cognitive reappraisal research. In addition, a classic divergent thinking task was administered. Both creativity tasks yielded strong activation in left prefrontal regions, indicating their shared cognitive processing demands like the inhibition of prepotent responses, shifting between different perspectives and controlled memory retrieval. Regarding task-specific differences, classic creative ideation activated a characteristic divergent thinking network comprising the left supramarginal, inferior temporal, and inferior frontal gyri. Affective creativity on the other hand specifically recruited the right superior frontal gyrus, presumably involved in the postretrieval monitoring of reappraisal success, and core hubs of the default-mode network, which are also implicated in social cognition. As a whole, by taking creativity research to the realm of emotion, this study advances our understanding of how more real-life creativity is rooted in the brain. Hum Brain Mapp 39:393-406, 2018.V C 2017 Wiley Periodicals, Inc.

The Dynamics of Creative Ideation: Introducing a New Assessment Paradigm

“…In MTCI, this feature is proposed in the intent to (1) limit stimulus-dependency (range of stimuli offered), and (2), control the number of responses generated (addressing fluency-originality dependency and trade-off; Zarnegar et al, 1988). Although such multi-trial single-response formats showed high reliability, predictive validity (Prabhakaran et al, 2014) and convergent validity with multi-response tasks (Perchtold et al, 2018), it has been criticized for its loss of open-endedness and potential for tracking iterative CI processes (Mouchiroud and Lubart, 2001; Hass, 2017). Yet, while both formats engage DT, observable responses uncover only one’s reported ideas which, as noted above, is insufficient to genuinely track the time-course of CI.…”

“…Neuroscience studies have often adapted DT tasks in a way that separates CI from response production time generally confounded in DT scores (Benedek et al, in press). Regrettably, it has resulted in overly constrained paradigms, imposing rigid time-structures for different phases of CI (e.g., 15 s “think time”, 10 s response time; Ellamil et al, 2012; Perchtold et al, 2018; Rominger et al, 2018) or requiring subjects to actively “signal” an idea (Heinonen et al, 2016; Boot et al, 2017). Consistent with recent computerized assessments (Hart et al, 2017; Loesche et al, 2018), log-analysis of test-takers’ interactions with MTCI tasks can inform a more realistic chronology of broad, qualitatively distinct phases of CI (Figure 1): (1) Exploration – response formulation, or “thinking” phase, measured by the time between stimulus presentation (timestamp a) and the onset of the response marked by the first interaction with the digital-platform (e.g., screen-touch, or typing; timestamp b) – (2) Production : response production phase, measured by the time between the first (timestamp b) and the last (timestamp c) interaction with the platform in producing the response (e.g., finger-doodling for graphic responses, typing text for verbal responses) – (3) Verification : “control” phase in which the produced response is being validated or discarded, measured by the time between the last interaction to produce the response (timestamp c), and the action (e.g., click) to validate the response/move on to next item (timestamp d).…”

Creativity is associated with a characteristic U-shaped function of alpha power changes accompanied by an early increase in functional coupling

“…As a result of this growing interest, there are an increasing number of cognitive neuroscience studies attempting to unveil potential brain mechanisms associated with creative ideation (see, e.g., Arden, Chavez, Grazioplene, & Jung, 2010; Fink & Benedek, 2014; Jung & Vartanian, 2018; Pidgeon et al, 2016). Though research in this field is still at an early stage, considerable progress has been achieved in unveiling relevant brain mechanisms of divergent thinking by means of event- and task-related (de)synchronization of power in the EEG alpha band (TRP; e.g., Benedek, Bergner, Könen, Fink, & Neubauer, 2011; Benedek, Schickel, Jauk, Fink, & Neubauer, 2014; Fink, Benedek, Grabner, Staudt, & Neubauer, 2007; Fink, Graif, & Neubauer, 2009; Fink, Rominger et al, 2018; Jausovec, 2000; Rominger, Papousek, Perchtold et al, 2018; for an overview see Fink & Benedek, 2014).…”

Creative challenge: Regular exercising moderates the association between task-related heart rate variability changes and individual differences in originality

“…For the present investigation, a single answer (i.e., best idea) and self-paced version of the AU task was used. This approach was applied in order to more strongly focus on the originality aspect of creativity [26]. The self-paced procedure appropriately captures the spontaneous nature of the creative thinking process [71–75]; however, it also implicates high demands on self-regulatory mechanisms.…”

“…Each trial started with a white cross (10 s), followed by a picture of a common object (idea generation phase with a max. response time of 15 s; see Perchtold et al [26] for a similar procedure). After the “idea button” was pressed, the participants rated the originality of their idea on a 6-point Likert-scale (max.…”