1,304 research outputs found
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
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Changes in size and age at maturity of Columbia River upriver bright fall chinook salmon (Oncorhynchus tshawytscha) : implications for stock fitness, commercial value, and management
The average size and age of chinook salmon (Oncorhynchus
tshawytscha) caught in commercial fisheries along the Pacific Coast
of North America have decreased substantially in this century. These
declines might be caused in part by changes in size and age at
maturity within the stocks contributing to those fisheries. Upriver
Brights (Brights), a stock of fall chinook salmon in the Columbia
River, are one of those stocks. The purposes of this study were to
(1) determine if average size and age at maturity of Brights have
declined, (2) gain a better understanding of the factors that may
contribute to such declines, and (3) describe potential consequences
of these changes.
Data from in-river fisheries suggest that the average weight of
mature Brights returning to the Columbia River has decreased
approximately 2.7 kg since the 1910s, an average rate of about 0.1
lb·yr⁻¹ (45 g·yr⁻¹ ). Most of the potential biases in these data tend
to make this estimate conservative. Insufficient data were available
to describe changes in average age at maturity.
There are many potential causes for the decline in average size
of mature Brights, including factors that affect very early life
stages. Other researchers have determined that size at maturity
appears to be highly influenced by inheritance, gender, and growth
rate. I describe how maternal size can influence -- through time of
spawning, choice of spawning site, and egg size -- the viability of
the young, which carry the dam's genes for size. The size-related
ability to produce viable offspring may have been changed by
modifications in the environment. Very little is known about how
changes in the natural environment for spawning, incubation, and
rearing may have contributed to a decline in average size at
maturity. Artificial propagation and rearing, such as at Priest
Rapids Hatchery, seems to produce adult Brights that are smaller,
younger, and more likely to be male than their natural counterparts.
The net result is that the average hatchery fish may have only about
0.80 of the reproductive potential of the average natural fish.
Changes in growth conditions in the ocean probably did not contribute
to the change in size, although the ocean fisheries of Southeast
Alaska and British Columbia appear to select, in the genetic sense,
against large size and old age in Brights.
Since 1978, in-river commercial fisheries have caught larger
Brights and a higher proportion of females than are found in the
escapement of the Priest Rapids Hatchery component of the stock, but
the fisheries impact the two sexes differently by taking the larger
males and the smaller females. The effect on the natural component
may differ because of their apparently larger average size. I found
no evidence that larger fish or more females were caught when 8-in.
minimum restrictions were in effect on gillnet mesh size relative to
periods when mesh size was not restricted. Impounding the mainstem
during the last 50+ yr may have removed obstacles to migration (e.g.,
Celilo Falls) that selected for large size in Brights, but that
hypothesis could not be tested.
The perserverance of larger and older phenotypes in the Bright
stock suggests that countervailing selection -- perhaps during
spawning, incubation, and/or early rearing -- may have resisted the
effects of a century of size- and age-selective fisheries. That
resistance, however, may reduce the productivity of the stock.
Declines in average size and age at maturity can have
undesireable consequences. Lower average size means less biomass
landed and lower commercial value. Lower average fecundity and a
diminished ability to reproduce in some environments are also
expected. Loss of size and age classes may reduce the ability of the
stock to adapt to environmental variations.
These results are relevant to several management practices. A
holistic approach to fishery management issues is necessary to avoid
erroneous conclusions based on narrow perspectives. Measuring
reproductive potential of the catch and escapement would be superior
to the conventional practice of simply counting numbers of fish.
Many aspects of artificial propagation can be improved, including
broodstock aquisition, mating regimes, and rearing practices. Stock
abundance is a major factor in determining the effect of many
management practices on the stock. In general, fisheries managers
must be mindful that they manage very complex natural systems
Creative thinking and brain network development in schoolchildren.
Fostering creative minds has always been a premise to ensure adaptation to new challenges of human civilization. While some alternative educational settings (i.e., Montessori) were shown to nurture creative skills, it is unknown how they impact underlying brain mechanisms across the school years. This study assessed creative thinking and resting-state functional connectivity via fMRI in 75 children (4-18 y.o.) enrolled either in Montessori or traditional schools. We found that pedagogy significantly influenced creative performance and underlying brain networks. Replicating past work, Montessori-schooled children showed higher scores on creative thinking tests. Using static functional connectivity analysis, we found that Montessori-schooled children showed decreased within-network functional connectivity of the salience network. Moreover, using dynamic functional connectivity, we found that traditionally-schooled children spent more time in a brain state characterized by high intra-default mode network connectivity. These findings suggest that pedagogy may influence brain networks relevant to creative thinking-particularly the default and salience networks. Further research is needed, like a longitudinal study, to verify these results given the implications for educational practitioners. A video abstract of this article can be viewed at https://www.youtube.com/watch?v=xWV_5o8wB5g . RESEARCH HIGHLIGHTS: Most executive jobs are prospected to be obsolete within several decades, so creative skills are seen as essential for the near future. School experience has been shown to play a role in creativity development, however, the underlying brain mechanisms remained under-investigated yet. Seventy-five 4-18 years-old children, from Montessori or traditional schools, performed a creativity task at the behavioral level, and a 6-min resting-state MR scan. We uniquely report preliminary evidence for the impact of pedagogy on functional brain networks
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
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
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
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
Metaphorically speaking: Cognitive abilities and the production of figurative speech.
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 metaphors remain largely unexplained. Recent evidence suggests that 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 model of intelligence contribute to generating these different types of metaphors. Specifically, the roles of fluid intelligence (Gf), crystallized intelligence (Gc), and broad 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. For creative metaphor, there were large effects of Gf (ß = .45) and Gr (ß = .52); for conventional metaphor, there was a moderate effect of Gc (ß = .30). Creative and conventional metaphors thus appear to be anchored in different patterns of abilities: Creative metaphors rely more on executive processes, whereas conventional metaphors primarily draw from acquired vocabulary knowledge
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