Neurocognitive free will

Time, valence, and imagination: a comparative study of thoughts in restricted and unrestricted mind wandering

William James' "stream of thought" is a key component of human cognition. Such thoughts arise in both restricted and unrestricted contexts, either with or without the presence of a secondary task. This study examines the similarities and differences in thoughts produced in these two contexts, which we call restricted and unrestricted mind wandering. Participants performed a mindfulness task representing restricted mind wandering and an unrestricted thought task where they spontaneously explored thoughts, reporting them as they arose. Participants then self-rated their thoughts based on valence, temporal orientation (past/present/future), and reality orientation (imaginary vs. real). Participants' emotional states were also evaluated using the Emotion Recall Task (ERT) and the PANAS questionnaire. Unrestricted mind wandering generated more thoughts, which were more positive and future-oriented than those in restricted mind wandering. Additionally, participants' thought valence correlated with their PANAS and ERT scores. Approximately 1 out of 4 thoughts in both restricted and unrestricted mind wandering were imaginary, with increased future orientation linked to more imaginative thought. Despite the statistical differences separating restricted and unrestricted thought, effect sizes were predominantly small, indicating that the thoughts arise during these two types of mind wandering are largely of the same kind.

Divergent and Convergent Creativity Are Different Kinds of Foraging

According to accounts of neural reuse and embodied cognition, higher-level cognitive abilities recycle evolutionarily ancient mechanisms for perception and action. Here, building on these accounts, we investigate whether creativity builds on our capacity to forage in space ("creativity as strategic foraging"). We report systematic connections between specific forms of creative thinking-divergent and convergent-and corresponding strategies for searching in space. U.S. American adults completed two tasks designed to measure creativity. Before each creativity trial, participants completed an unrelated search of a city map. Between subjects, we manipulated the search pattern, with some participants seeking multiple, dispersed spatial locations and others repeatedly converging on the same location. Participants who searched divergently in space were better at divergent thinking but worse at convergent thinking; this pattern reversed for participants who had converged repeatedly on a single location. These results demonstrate a targeted link between foraging and creativity, thus advancing our understanding of the origins and mechanisms of high-level cognition.

A theory of the skill-performance relationship

The skill-performance relationship is a cornerstone of a meritocratic society. People are selected for schools, colleges and jobs based on the premise that more skillful individuals perform better. Scientific understanding of the skill-performance relationship demands that the effect of skill on performance is objectively assessed without subjective, social, and political considerations. One of the best areas for this analysis is sports. In many sports settings, the skill-performance relationship can objectively be examined at the technical, behavioral, psychological, and neurological levels. This examination reveals that skill and performance are inextricably intertwined. While skill affects performance, performance in turn defines and affects skill. To disentangle the previously confusing and interchangeable use of these key constructs, the paper presents a theoretical model specifying that ability and effort have their own direct effects on performance, as well as indirect effects on performance through skill possession and skill execution in cognitive and physical domains of human performance. Thus, ability and skill are not the same. Although skill is a key determinant of performance, recent theory and research suggests that successful performers are successful not just because of their skills per se, but because they take advantage of their skills by creating more occurrences of momentum, making them last longer, and using them to bounce back faster from streaks of unsuccessful performance. Thus, momentum is an important mediator of the effects of skill on performance.

Evolution of Consciousness

The natural evolution of consciousness in different animal species mandates that conscious experiences are causally potent in order to confer any advantage in the struggle for survival. Any endeavor to construct a physical theory of consciousness based on emergence within the framework of classical physics, however, leads to causally impotent conscious experiences in direct contradiction to evolutionary theory since epiphenomenal consciousness cannot evolve through natural selection. Here, we review recent theoretical advances in describing sentience and free will as fundamental aspects of reality granted by quantum physical laws. Modern quantum information theory considers quantum states as a physical resource that endows quantum systems with the capacity to perform physical tasks that are classically impossible. Reductive identification of conscious experiences with the quantum information comprised in quantum brain states allows for causally potent consciousness that is capable of performing genuine choices for future courses of physical action. The consequent evolution of brain cortical networks contributes to increased computational power, memory capacity, and cognitive intelligence of the living organisms.

Associative thinking at the core of creativity

Creativity has long been thought to involve associative processes in memory: connecting concepts to form ideas, inventions, and artworks. However, associative thinking has been difficult to study due to limitations in modeling memory structure and retrieval processes. Recent advances in computational models of semantic memory allow researchers to examine how people navigate a semantic space of concepts when forming associations, revealing key search strategies associated with creativity. Here, we synthesize cognitive, computational, and neuroscience research on creativity and associative thinking. This Review highlights distinctions between free- and goal-directed association, illustrates the role of associative thinking in the arts, and links associative thinking to brain systems supporting both semantic and episodic memory - offering a new perspective on a longstanding creativity theory.

The evolution of imagination and the adaptive value of imaginary worlds

Characterizing the cultural evolution of imaginary worlds as a hedonic but non-adaptive exaptation from evolved exploratory tendencies, Dubourg and Baumard defend too narrow a conception of the adaptive evolution of imaginary worlds. Imagination and its imaginary worlds are ancient and adaptive, allowing deliberation over actions, consequences, and futures worth aspiring to, often engendering the world we see around us.

The influence of exposure to randomness on lateral thinking in divergent, convergent, and creative search

Exposure to random stimuli has often been suggested to help unlock problem-solving abilities and creativity, helping us to see problems differently and imagine new possibilities. Equally, randomness is widely used in computer science to escape local maxima and find effective solutions to intractable problems. However, randomness has rarely been used as a formal aid in human decision making or investigated in controlled experimental settings. In this pre-registered study, we tested the effect of extraneous random stimuli using Wikipedia's random page generator on 592 British participants' performance across three online tasks: one 'convergent' forecasting task and two 'divergent' fluency tasks. We found no improvement associated with the treatment and often significant impairment. A Bayesian meta-analysis of the tasks finds strong support for the null hypothesis. We conclude that stimulating lateral thinking through random stimuli is non-trivial and may require such stimuli to be sufficiently task-related or 'optimally random'.

Is the Mind a Network? Maps, Vehicles, and Skyhooks in Cognitive Network Science

Cognitive researchers often carve cognition up into structures and processes. Cognitive processes operate on structures, like vehicles driving over a map. Language alongside semantic and episodic memory are proposed to have structure, as are perceptual systems. Over these structures, processes operate to construct memory and solve problems by retrieving and manipulating information. Network science offers an approach to representing cognitive structures and has made tremendous inroads into understanding the nature of cognitive structure and process. But is the mind a network? If so, what kind? In this article, we briefly review the main metaphors, assumptions, and pitfalls prevalent in cognitive network science (maps and vehicles; one network/process to rule them all), highlight the need for new metaphors that elaborate on the map-and-vehicle framework (wormholes, skyhooks, and generators), and present open questions in studying the mind as a network (the challenge of capturing network change, what should the edges of cognitive networks be made of, and aggregated vs. individual-based networks). One critical lesson of this exercise is that the richness of the mind as network approach makes it a powerful tool in its own right; it has helped to make our assumptions more visible, generating new and fascinating questions, and enriching the prospects for future research. A second lesson is that the mind as a network-though useful-is incomplete. The mind is not a network, but it may contain them.

The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again

Drawing from both enactivist and cognitivist perspectives on mind, I propose that explaining teleological phenomena may require reappraising both "Cartesian theaters" and mental homunculi in terms of embodied self-models (ESMs), understood as body maps with agentic properties, functioning as predictive-memory systems and cybernetic controllers. Quasi-homuncular ESMs are suggested to constitute a major organizing principle for neural architectures due to their initial and ongoing significance for solutions to inference problems in cognitive (and affective) development. Embodied experiences provide foundational lessons in learning curriculums in which agents explore increasingly challenging problem spaces, so answering an unresolved question in Bayesian cognitive science: what are biologically plausible mechanisms for equipping learners with sufficiently powerful inductive biases to adequately constrain inference spaces? Drawing on models from neurophysiology, psychology, and developmental robotics, I describe how embodiment provides fundamental sources of empirical priors (as reliably learnable posterior expectations). If ESMs play this kind of foundational role in cognitive development, then bidirectional linkages will be found between all sensory modalities and frontal-parietal control hierarchies, so infusing all senses with somatic-motoric properties, thereby structuring all perception by relevant affordances, so solving frame problems for embodied agents. Drawing upon the Free Energy Principle and Active Inference framework, I describe a particular mechanism for intentional action selection via consciously imagined (and explicitly represented) goal realization, where contrasts between desired and present states influence ongoing policy selection via predictive coding mechanisms and backward-chained imaginings (as self-realizing predictions). This embodied developmental legacy suggests a mechanism by which imaginings can be intentionally shaped by (internalized) partially-expressed motor acts, so providing means of agentic control for attention, working memory, imagination, and behavior. I further describe the nature(s) of mental causation and self-control, and also provide an account of readiness potentials in Libet paradigms wherein conscious intentions shape causal streams leading to enaction. Finally, I provide neurophenomenological handlings of prototypical qualia including pleasure, pain, and desire in terms of self-annihilating free energy gradients via quasi-synesthetic interoceptive active inference. In brief, this manuscript is intended to illustrate how radically embodied minds may create foundations for intelligence (as capacity for learning and inference), consciousness (as somatically-grounded self-world modeling), and will (as deployment of predictive models for enacting valued goals).

Determinism and Destigmatization: Mitigating Blame for Addiction

The brain disease model of addiction is widely endorsed by agencies concerned with treating behavioral disorders and combatting the stigma often associated with addiction. However, both its accuracy and its effectiveness in reducing stigma have been challenged. A proposed alternative, the “choice” model, recognizes the residual rational behavior control capacities of addicted individuals and their ability to make choices, some of which may cause harm. Since harmful choices are ordinarily perceived as blameworthy, the choice model may inadvertently help justify stigma. This paper seeks to fully naturalize the choice model by highlighting the determinants of voluntary action and thus increase its potential for destigmatizing addiction. In light of a deterministic understanding of behavior, it is unreasonable to suppose that addicted individuals could have made different choices in becoming addicted and in subsequent situations. To the extent that stigma is motivated by the supposition that addicted individuals could have chosen otherwise in actual situations, a deterministic understanding of addictive behavior promises to mitigate blame and stigma.

Multiscale Computation and Dynamic Attention in Biological and Artificial Intelligence

Biological and artificial intelligence (AI) are often defined by their capacity to achieve a hierarchy of short-term and long-term goals that require incorporating information over time and space at both local and global scales. More advanced forms of this capacity involve the adaptive modulation of integration across scales, which resolve computational inefficiency and explore-exploit dilemmas at the same time. Research in neuroscience and AI have both made progress towards understanding architectures that achieve this. Insight into biological computations come from phenomena such as decision inertia, habit formation, information search, risky choices and foraging. Across these domains, the brain is equipped with mechanisms (such as the dorsal anterior cingulate and dorsolateral prefrontal cortex) that can represent and modulate across scales, both with top-down control processes and by local to global consolidation as information progresses from sensory to prefrontal areas. Paralleling these biological architectures, progress in AI is marked by innovations in dynamic multiscale modulation, moving from recurrent and convolutional neural networks-with fixed scalings-to attention, transformers, dynamic convolutions, and consciousness priors-which modulate scale to input and increase scale breadth. The use and development of these multiscale innovations in robotic agents, game AI, and natural language processing (NLP) are pushing the boundaries of AI achievements. By juxtaposing biological and artificial intelligence, the present work underscores the critical importance of multiscale processing to general intelligence, as well as highlighting innovations and differences between the future of biological and artificial intelligence.

Foraging in Mind

People and other animals can search for information inside their heads. Where does this ability come from, and what does it enable cognitive systems to do? In this article, we address the behavioral and cognitive similarities between search in external environments and internal environments (e.g., memory). These require both maplike representations and the means to navigate them, and the latter involves modulation between exploitation and exploration analogous to a foraging process called area-restricted search. These findings have implications for understanding a number of cognitive abilities commonly considered to be hallmarks of the human species, such as well-developed executive control and goal-directed cognition, autonoetic consciousness (i.e., self-awareness), deliberation, and free will. Moreover, this research extends our conception of what organisms may share these abilities and how they evolved.