Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userThe Role of Engagement, Honing, and Mindfulness in Creativity
97
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
As both our external world and inner worlds become more complex, we are faced with more novel challenges, hardships, and duress. Creative thinking is needed to provide fresh perspectives and solve new problems.Because creativity can be conducive to accessing and reliving traumatic memories, emotional scars may be exacerbated by creative practices before these are transformed and released. Therefore, in preparing our youth to thrive in an increasingly unpredictable world, it could be helpful to cultivate in them an understanding of the creative process and its relationship to hardship, as well as tools and techniques for fostering not just creativity but self-awareness and mindfulness. This chapter is a review of theories of creativity through the lens of their capacity to account for the relationship between creativity and hardship, as well as the therapeutic effects of creativity. We also review theories and research on aspects of mindfulness attending to potential therapeutic effects of creativity. Drawing upon the creativity and mindfulness literatures, we sketch out what an introductory creativity and mindfulness module might look like as part of an educational curriculum designed to address the unique challenges of the 21st Century.
rate research
Read More
Creativity is perhaps what most differentiates humans from other species. It involves the capacity to shift between divergent and convergent modes of thought in response to task demands. Divergent thought has been characterized as the kind of thinking needed to generate multiple solutions, while convergent thought has been characterized as the kind of thinking needed for tasks in with one solution. Divergent thought has been conceived of as reflecting on the task from unconventional perspectives, while convergent thought has been conceived of as reflecting on it from conventional perspectives. Personality traits correlated with creativity include openness to experience, tolerance of ambiguity, and self-confidence. Evidence that creativity is linked with affective disorders is mixed. Neuroscientific research using electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) suggests that creativity is associated with a loosening of cognitive control and decreased arousal. The distributed, content-addressable structure of associative memory is conducive to bringing task-relevant items to mind without the need for explicit search. Human creativity dates back to the earliest stone tools over three million years ago, with the Paleolithic marking the onset of art, science, and religion. Areas of controversy concern the relative contributions of expertise, chance, and intuition, the importance of process versus product, whether creativity is domain-specific versus domain-general, the extent to which creativity is correlated with affective disorders, and whether divergent thought entails the generation of multiple ideas or the honing of a single initially ambiguous mental representation that may manifest as different external outputs. Areas for further research include computational modeling, the biological basis of creativity, and studies that track ideation processes over time.
We advance a hypothesis that creativity has evolved with evolution of internal representations, possibly from amniotes to primates, and further in human cultural evolution. Representations separated sensing from acting and gave internal room for creativity. To see (or perform any sensing), creatures with internal representations had to modify these representations to fit sensor signals. Therefore the knowledge instinct, KI, the drive to fit representations to the world, had to evolve along with internal representations. Until primates, it remained simple, without language internal representations could not evolve from perceptions to abstract representations, and abstract thoughts were not possible. We consider creative vs. non-creative decision making, and compare KI with Kahneman-Tverskys heuristic thinking. We identify higher, conscious levels of KI with the drive for creativity (DC) and discuss the roles of language and music, brain mechanisms involved, and experimental directions for testing the advanced hypotheses.
It is proposed that both human creativity and human consciousness are (unintended) consequences of the human brains extraordinary energy efficiency. The topics of creativity and consciousness are treated separately, though have a common sub-structure. It is argued that creativity arises from a synergy between two cognitive modes of the human brain (which broadly coincide with Kahnemans Systems 1 and 2). In the first, available energy is spread across a relatively large network of neurons. As such, the amount of energy per active neuron is so small that the operation of such neurons is susceptible to thermal (ultimately quantum decoherent) noise. In the second, available energy is focussed on a small enough subset of neurons to guarantee a deterministic operation. An illustration of how this synergy can lead to creativity with implications for computing in silicon are discussed. Starting with a discussion of the concept of free will, the notion of consciousness is defined in terms of an awareness of what are perceived to be nearby counterfactual worlds in state space. It is argued that such awareness arises from an interplay between our memories on the one hand, and quantum physical mechanisms (where, unlike in classical physics, nearby counterfactual worlds play an indispensable dynamical role) in the ion channels of neural networks. As with the brains susceptibility to noise, it is argued that in situations where quantum physics plays a role in the brain, it does so for reasons of energy efficiency. As an illustration of this definition of consciousness, a novel proposal is outlined as to why quantum entanglement appears so counter-intuitive.
In recent years, the field of neuroscience has gone through rapid experimental advances and extensive use of quantitative and computational methods. This accelerating growth has created a need for methodological analysis of the role of theory and the modeling approaches currently used in this field. Toward that end, we start from the general view that the primary role of science is to solve empirical problems, and that it does so by developing theories that can account for phenomena within their domain of application. We propose a commonly-used set of terms - descriptive, mechanistic, and normative - as methodological designations that refer to the kind of problem a theory is intended to solve. Further, we find that models of each kind play distinct roles in defining and bridging the multiple levels of abstraction necessary to account for any neuroscientific phenomenon. We then discuss how models play an important role to connect theory and experiment, and note the importance of well-defined translation functions between them. Furthermore, we describe how models themselves can be used as a form of experiment to test and develop theories. This report is the summary of a discussion initiated at the conference Present and Future Theoretical Frameworks in Neuroscience, which we hope will contribute to a much-needed discussion in the neuroscientific community.
Observability and controllability are essential concepts to the design of predictive observer models and feedback controllers of networked systems. For example, noncontrollable mathematical models of real systems have subspaces that influence model behavior, but cannot be controlled by an input. Such subspaces can be difficult to determine in complex nonlinear networks. Since almost all of the present theory was developed for linear networks without symmetries, here we present a numerical and group representational framework, to quantify the observability and controllability of nonlinear networks with explicit symmetries that shows the connection between symmetries and nonlinear measures of observability and controllability. We numerically observe and theoretically predict that not all symmetries have the same effect on network observation and control. Our analysis shows that the presence of symmetry in a network may decrease observability and controllability, although networks containing only rotational symmetries remain controllable and observable. These results alter our view of the nature of observability and controllability in complex networks, change our understanding of structural controllability, and affect the design of mathematical models to observe and control such networks.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
