The neuroscience of musical improvisation

Abstract: Researchers have recently begun to examine the neural basis of musical improvisation, one of the most complex forms of creative behavior. The emerging field of improvisation neuroscience has implications not only for the study of artistic expertise, but also for understanding the neural underpinnings of domain-general processes such as motor control and language production. This review synthesizes functional magnetic resonance imagining (fMRI) studies of musical improvisation, including vocal and instrumental improvisation, with samples of jazz pianists, classical musicians, freestyle rap artists, and non-musicians. A network of prefrontal brain regions commonly linked to improvisatory behavior is highlighted, including the presupplementary motor area, medial prefrontal cortex, inferior frontal gyrus, dorsolateral prefrontal cortex, and dorsal premotor cortex. Activation of premotor and lateral prefrontal regions suggests that a seemingly unconstrained behavior may actually benefit from motor planning and cognitive control. Yet activation of cortical midline regions points to a role of spontaneous cognition characteristic of the default network. Together, such results may reflect cooperation between large-scale brain networks associated with cognitive control and spontaneous thought. The improvisation literature is integrated with Pressing's theoretical model, and discussed within the broader context of research on the brain basis of creative cognition

The time course of creativity: Multivariate classification of default and executive network contributions to creative cognition over time

Research indicates that creative cognition depends on both associative and controlled processes, corresponding to the brain's default mode network (DMN) and executive control network (ECN) networks. However, outstanding questions include how the DMN and ECN operate over time during creative task performance, and whether creative cognition involves distinct generative and evaluative stages. To address these questions, we used multivariate pattern analysis (MVPA) to assess how the DMN and ECN contribute to creative cognition over three successive time phases during the production of a single creative idea. Training classifiers to predict trial condition (creative vs non-creative), we used classification accuracy as a measure of the extent of creative activity in each brain network and time phase. Across both networks, classification accuracy was highest in early phases, decreased in mid phases, and increased again in later phases, following a U-shaped curve. Notably, classification accuracy was significantly greater in the ECN than the DMN during early phases, while differences between networks at later time phases were non-significant. We also computed correlations between classification accuracy and human-rated creative performance, to assess how relevant the creative activity in each network was to the creative quality of ideas. In line with expectations, classification accuracy in the DMN was most related to creative quality in early phases, decreasing in later phases, while classification accuracy in the ECN was least related to creative quality in early phases, increasing in later phases. Given the theorized roles of the DMN in generation and the ECN in evaluation, we interpret these results as tentative evidence for the existence of separate generative and evaluative stages in creative cognition that depend on distinct neural substrates

Towards Greater Computational Modeling in Neurocognitive Creativity Research

Creative cognition is the driving force behind all cultural and scientific progress. In recent years, the field of neurocognitive creativity research (NCR) has made considerable progress in revealing the neural and psychological correlates of creative cognition. However, a detailed understanding of how cognitive processes produce creative ideas, and how these processes interact differently across tasks and individuals, remains elusive. In this article, we argue that the increased adoption of computational modeling can help greatly in achieving this goal. While the verbal theories guiding NCR have evolved from broader accounts into more specific descriptions of neurocognitive processes, they remain more open to interpretation and harder to falsify than formal models. Translating theories into computational models can make them more concrete, accessible, and easier to compare, and helps researchers to develop causal hypotheses for how variation in cognitive factors leads to variation in creative outcomes. Currently, however, computational modeling of creativity is conducted almost entirely separately from NCR, and few attempts have been made to embody the cognitive theories of NCR in models that can simulate performance on common lab-based tasks. In this paper, we discuss theories of creative cognition and how they might benefit from the wider adoption of formal modeling. We also examine recent computational models of creativity and how these might be improved and better integrated with NCR. Finally, we describe a pathway toward a mechanistic understanding of creative cognition through the integration of computational modeling, psychological theory, and empirical research, outlining an example model based on dual-process accounts

Evaluation of Poetic Creativity: Predictors and the Role of Expertise - A Multilevel Approach

Poetry is one of the most creative expressions of language, but how we evaluate the creativity of a poem is not properly characterized. The present study investigated the role of various subjective qualities – clarity, aesthetic appeal, felt valence, arousal, and surprise – in predicting the creativity judgment of English poems. Participants (N=129) were presented with a broad range of English poems; they rated each poem on six characteristics: clarity, aesthetic appeal, felt valence, felt arousal, surprise and overall creativity. Linear multilevel analysis showed that aesthetic appeal was the strongest predictor of poetic creativity, followed by surprise and felt valence. Multilevel mediation analysis indicated significant mediation by surprise and felt valence on the relationship between aesthetic appeal and creativity at both within and between-participant levels. Further, expertise in English literature was found to significantly moderate the effects of all three predictors on the evaluation of creativity. The study simultaneously captured the surprise-evoking line(s). Using the semantic distance computing approach, we have shown the objective validation of the subjectively chosen line(s) of surprise. Altogether, our findings suggest a parsimonious model of evaluation of creativity of poems and its interaction with expertise

Use or Consequences: Probing the Cognitive Difference Between Two Measures of Divergent Thinking

Recent studies have highlighted both similarities and differences between the cognitive processing that underpins memory retrieval and that which underpins creative thinking. To date, studies have focused more heavily on the Alternative Uses task, but fewer studies have investigated the processing underpinning other idea generation tasks. This study examines both Alternative Uses and Consequences idea generation with a methods pulled from cognitive psychology, and a novel method for evaluating the creativity of such responses. Participants were recruited from Amazon Mechanical Turk using a custom interface allowing for requisite experimental control. Results showed that both Alternative Uses and Consequences generation are well approximated by an exponential cumulative response time model, consistent with studies of memory retrieval. Participants were also slower to generate their first consequence compared with first responses to Alternative Uses, but inter-response time was negatively related to pairwise similarity on both tasks. Finally, the serial order effect is exhibited for both tasks, with Consequences earning more creative evaluations than Uses. The results have implications for burgeoning neuroscience research on creative thinking, and suggestions are made for future areas of inquiry. In addition, the experimental apparatus described provides an equitable way for researchers to obtain good quality cognitive data for divergent thinking tasks

The Neuroscience of Musical Improvisation

Researchers have recently begun to examine the neural basis of musical improvisation, one of the most complex forms of creative behavior. The emerging field of improvisation neuroscience has implications not only for the study of artistic expertise, but also for understanding the neural underpinnings of domain-general processes such as motor control and language production. This review synthesizes functional magnetic resonance imagining (fMRI) studies of musical improvisation, including vocal and instrumental improvisation, with samples of jazz pianists, classical musicians, freestyle rap artists, and non-musicians. A network of prefrontal brain regions commonly linked to improvisatory behavior is highlighted, including the pre-supplementary motor area, medial prefrontal cortex, inferior frontal gyrus, dorsolateral prefrontal cortex, and dorsal premotor cortex. Activation of premotor and lateral prefrontal regions suggests that a seemingly unconstrained behavior may actually benefit from motor planning and cognitive control. Yet activation of cortical midline regions points to a role of spontaneous cognition characteristic of the default network. Together, such results may reflect cooperation between large-scale brain networks associated with cognitive control and spontaneous thought. The improvisation literature is integrated with Pressing’s theoretical model, and discussed within the broader context of research on the brain basis of creative cognition

Payload Performance Analysis for a Reusable Two-Stage-to-Orbit Vehicle

This paper investigates a unique approach in the development of a reusable launch vehicle where, instead of designing the vehicle to be reusable from its inception, as was done for the Space Shuttle, an expendable two stage launch vehicle is evolved over time into a reusable launch vehicle. To accomplish this objective, each stage is made reusable by adding the systems necessary to perform functions such as thermal protection and landing, without significantly altering the primary subsystems and outer mold line of the original expendable vehicle. In addition, some of the propellant normally used for ascent is used instead for additional propulsive maneuvers after staging in order to return both stages to the launch site, keep loads within acceptable limits and perform a soft landing. This paper presents a performance analysis that was performed to investigate the feasibility of this approach by quantifying the reduction in payload capability of the original expendable launch vehicle after accounting for the mass additions, trajectory changes and increased propellant requirements necessary for reusability. Results show that it is feasible to return both stages to the launch site with a positive payload capability equal to approximately 50 percent of an equivalent expendable launch vehicle. Further discussion examines the ability to return a crew/cargo capsule to the launch site and presents technical challenges that would have to be overcome

Metaphorically speaking: the role of cognitive abilities in the production of figurative language

Figurative language is one of the most common expressions of creative behavior in everyday life. However, the cognitive mechanisms behind figures of speech such as metaphor remain largely unexplained. Recent evidence suggests fluid and executive abilities are important to the generation of conventional and creative metaphors. The present study investigated whether several factors of the Cattell-Horn-Carroll (CHC) model of intelligence contribute to generating these different types of metaphors. Specifically, the roles of fluid intelligence (Gf), crystallized knowledge (Gc), and general retrieval ability (Gr) were explored. Participants completed a series of intelligence tests and were asked to produce conventional and creative metaphors. Structural equation modeling was used to assess the contribution of the different factors of intelligence to metaphor production. Model results for creative metaphor showed large effects of Gf (β = .45) and Gr (β = .52), whereas Gc had a moderate effect on conventional metaphor production (β = .30). The present research extends the traditional study of divergent thinking to an area important to everyday communication, and advances a testable framework of creative cognition based on the CHC model of intelligence

Brain networks underlying figurative language production

Metaphor is a common form of figurative language, yet little is known about how the brain produces novel figurative expressions. Related research suggests that dynamic interactions between large-scale brain systems support a range of complex cognitive processes, particularly those requiring focused internal attention and cognitive control. However, the extent to which these networks interact to support core processes of figurative language production remains unknown. The present research explored this question by assessing functional interactions between brain regions during novel metaphor production. Participants completed a metaphor production task and a literal control task during functional magnetic resonance imaging (fMRI). Whole-brain functional connectivity analysis revealed a distributed network associated with metaphor production, including several nodes of the default (precuneus and left angular gyrus; AG) and executive (right intraparietal sulcus; IPS) networks. Seed-based analyses showed direct function connections between core hubs of the default, salience, and executive networks. Moreover, analysis of temporal network dynamics found early functional coupling of the left AG and right anterior insula that preceded subsequent coupling of the left AG and left DLPFC, pointing to a potential switching mechanism underlying default and executive network interaction. These results extend recent work on the cooperative role of large-scale networks during complex cognitive processes, and suggest that metaphor production involves dynamic cooperation between brain systems linked to cognitive control, semantic integration, and spontaneously-generated thought

Why do ideas get more creative across time? An executive interpretation of the serial order effect in divergent thinking tasks.

The serial order effect—the tendency for later responses to a divergent thinking task to be better than earlier ones—is one of the oldest and most robust findings in modern creativity work. But why do ideas get better? Using new methods that afford a fine-grained look at temporal trajectories, we contrasted two explanations: the classic spreading activation account and a new account based on executive and strategic aspects of creative thought. After completing measures of fluid intelligence and personality, a sample of young adults (n = 133) completed a 10-min unusual uses task. Each response was time-stamped and then rated for creativity by three raters. Multilevel structural equation models estimated the trajectories of creativity and fluency across time and tested if intelligence moderated the effects of time. As in past work, creativity increased sharply with time and flattened slightly by the task's end, and fluency was highest in the task's first minute and then dropped sharply. Intelligence, however, moderated the serial order effect—as intelligence increased, the serial order effect diminished. Taken together, the findings are more consistent with a view that emphasizes executive processes, particularly processes involved in the strategic retrieval and manipulation of knowledge, than the simple spreading of activation to increasingly remote concepts