Visual affects: Linking curiosity, Aha-Erlebnis, and memory through information gain

Insight in the Conspiracist's Mind

Academic AbstractThe motto of the conspiracist, "Do your own research," may seem ludicrous to scientists. Indeed, it is often dismissed as a mere rhetorical device that conspiracists use to give themselves the semblance of science. In this perspective paper, we explore the information-seeking activities ("research") that conspiracists do engage in. Drawing on the experimental psychology of aha experiences, we explain how these activities, as well as the epistemic experiences that precede (curiosity) or follow (insight or "aha" experiences) them, may play a crucial role in the appeal and development of conspiracy beliefs. Aha moments have properties that can be exploited by conspiracy theories, such as the potential for false but seemingly grounded conclusions. Finally, we hypothesize that the need for autonomous epistemic agency and discovery is universal but increases as people experience more uncertainty and/or feel epistemically excluded in society, hence linking it to existing literature on explaining conspiracy theories.

Role of Metacognitive Confidence Judgments in Curiosity: Different Effects of Confidence on Curiosity Across Epistemic and Perceptual Domains

Previous research suggests that curiosity is sometimes induced by novel information one has no relevant knowledge about, but it is sometimes induced by new information about something that one is familiar with and has prior knowledge about. However, the conditions under which novelty or familiarity triggers curiosity remain unclear. Using metacognitive confidence judgments as a proxy to quantify the amount of knowledge, this study evaluates the relationship between the amount of relevant knowledge and curiosity. We reviewed previous studies on the relationship between subjective curiosity and confidence and reanalyzed existing large-sample data. The findings indicate that the relationship between curiosity and confidence differs depending on the nature of the stimuli: epistemic versus perceptual. Regarding perceptual stimuli, curiosity is stronger when individuals have lower confidence levels. By contrast, for epistemic stimuli, curiosity is stronger when individuals have higher confidence levels. These results suggest that curiosity triggered by perceptual stimuli is based on perceived novelty, whereas that triggered by epistemic stimuli is based on familiarity with prior knowledge.

Prediction error minimization as a common computational principle for curiosity and creativity

We propose expanding the authors' shared novelty-seeking basis for creativity and curiosity by emphasizing an underlying computational principle: Minimizing prediction errors (mismatch between predictions and incoming data). Curiosity is tied to the anticipation of minimizing prediction errors through future, novel information, whereas creative AHA moments are connected to the actual minimization of prediction errors through current, novel information.

Cultivating creativity: predictive brains and the enlightened room problem

How can one conciliate the claim that humans are uncertainty minimizing systems that seek to navigate predictable and familiar environments with the claim that humans can be creative? We call this the Enlightened Room Problem (ERP). The solution, we suggest, lies not (or not only) in the error-minimizing brain but in the environment itself. Creativity emerges from various degrees of interplay between predictive brains and changing environments: ones that repeatedly move the goalposts for our own error-minimizing machinery. By (co)constructing these challenging worlds, we effectively alter and expand the space within which our own prediction engines operate, and that function as 'exploration bubbles' that enable information seeking, uncertainty minimizing minds to penetrate deeper and deeper into artistic, scientific and engineering space. In what follows, we offer a proof of principle for this kind of environmentally led cognitive expansion. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

The aesthetic valve: how aesthetic appreciation may switch emotional states from anxiety to curiosity

Pursuing new knowledge in the entropic environment is pivotal for survival. However, dealing with uncertainty is a costly challenge for the agent surrounded by the stochastic sensory world, giving rise to different epistemic emotions, such as curiosity and anxiety. We recently proposed that aesthetic appreciation may have the role of associating pleasant feedback with the update of predictive representations. According to this idea, aesthetic appreciation and its associated rewarding feeling could drive people to seek new knowledge over anxiety. However, the relationship between aesthetic appreciation, curiosity, and anxiety has been still under-examined in the literature. Here, we explore the relationship between these epistemic emotions in a series of three experiments. In study 1, we examined whether music-induced aesthetic appreciation would influence curiosity in a gambling task. In studies 2a and 2b, we explore the relationship between music-induced aesthetic appreciation and anxiety state. Overall, aesthetic appreciation promoted curiosity-driven behaviour while it was negatively associated with anxiety. These results were consistent with the idea that aesthetic appreciation could act as a 'valve', prompting the individual to perceive curiosity (i.e. to consider novelty as a valuable opportunity to acquire new knowledge) rather than anxiety (i.e. to consider novelty as a risk to be avoided). This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

Predicting instabilities: an embodied perspective on unstable experiences with art and design

Predictive Processing (PP) provides a theoretical framework that describes perception as a process attempting to increase the predictability of stimulations by updating predictions or exploring new sensations. Moreover, perception and action are assumed to be closely linked within this process. While organisms seem to strive for predictability, we sometimes expose ourselves to objects and situations that challenge sense-making-such conditions often break perceptual habits or offer multiple possible meanings. This paper updates a previous qualification of these experiences of 'Semantic Instability' (SeIns) by following an embodied and situated understanding of perception and cognition. We suggest that art perception essentially differs from problem-solving as in engaging with art, we typically integrate contradictory elements dynamically and without the ultimate goal of resolving the contradictions-on the contrary, SeIns itself can generate aesthetic hedonics and interest. We discuss how current embodied accounts of PP might help understand what motivates such unstable yet insightful and pleasurable nonlinear sense-making processes. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

Order and change in art: towards an active inference account of aesthetic experience

How to account for the power that art holds over us? Why do artworks touch us deeply, consoling, transforming or invigorating us in the process? In this paper, we argue that an answer to this question might emerge from a fecund framework in cognitive science known as predictive processing (a.k.a. active inference). We unpack how this approach connects sense-making and aesthetic experiences through the idea of an 'epistemic arc', consisting of three parts (curiosity, epistemic action and aha experiences), which we cast as aspects of active inference. We then show how epistemic arcs are built and sustained by artworks to provide us with those satisfying experiences that we tend to call 'aesthetic'. Next, we defuse two key objections to this approach; namely, that it places undue emphasis on the cognitive component of our aesthetic encounters-at the expense of affective aspects-and on closure and uncertainty minimization (order)-at the expense of openness and lingering uncertainty (change). We show that the approach offers crucial resources to account for the open-ended, free and playful behaviour inherent in aesthetic experiences. The upshot is a promising but deflationary approach, both philosophically informed and psychologically sound, that opens new empirical avenues for understanding our aesthetic encounters. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

Aesthetics and predictive processing: grounds and prospects of a fruitful encounter

In the last few years, a remarkable convergence of interests and results has emerged between scholars interested in the arts and aesthetics from a variety of perspectives and cognitive scientists studying the mind and brain within the predictive processing (PP) framework. This convergence has so far proven fruitful for both sides: while PP is increasingly adopted as a framework for understanding aesthetic phenomena, the arts and aesthetics, examined under the lens of PP, are starting to be seen as important windows into our mental functioning. The result is a vast and fast-growing research programme that promises to deliver important insights into our aesthetic encounters as well as a wide range of psychological phenomena of general interest. Here, we present this developing research programme, describing its grounds and highlighting its prospects. We start by clarifying how the study of the arts and aesthetics encounters the PP picture of mental functioning (§1). We then go on to outline the prospects of this encounter for the fields involved: philosophy and history of art (§2), psychology of aesthetics and neuroaesthetics (§3) and psychology and neuroscience more generally (§4). The upshot is an ambitious but well-defined framework within which aesthetics and cognitive science can partner up to illuminate crucial aspects of the human mind. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

Curiosity evolves as information unfolds

When people feel curious, they often seek information to resolve their curiosity. Reaching resolution, however, does not always occur in a single step but instead may follow the accumulation of information over time. Here, we investigated changes in curiosity over a dynamic information-gathering process and how these changes related to affective and cognitive states as well as behavior. Human participants performed an Evolving Line Drawing Task, during which they reported guesses about the drawings' identities and made choices about whether to keep watching. In Study 1, the timing of choices was predetermined and externally imposed, while in Study 2, participants had agency in the timing of guesses and choices. Using this dynamic paradigm, we found that even within a single information-gathering episode, curiosity evolved in concert with other emotional states and with confidence. In both studies, we showed that the relationship between curiosity and confidence depended on stimulus entropy (unique guesses across participants) and on guess accuracy. We demonstrated that curiosity is multifaceted and can be experienced as either positive or negative depending on the state of information gathering. Critically, even when given the choice to alleviate uncertainty immediately (i.e., view a spoiler), higher curiosity promoted continuing to engage in the information-gathering process. Collectively, we show that curiosity changes over information accumulation to drive engagement with external stimuli, rather than to shortcut the path to resolution, highlighting the value inherent in the process of discovery.

Self-Relevance Predicts the Aesthetic Appeal of Real and Synthetic Artworks Generated via Neural Style Transfer

What determines the aesthetic appeal of artworks? Recent work suggests that aesthetic appeal can, to some extent, be predicted from a visual artwork's image features. Yet a large fraction of variance in aesthetic ratings remains unexplained and may relate to individual preferences. We hypothesized that an artwork's aesthetic appeal depends strongly on self-relevance. In a first study (N = 33 adults, online replication N = 208), rated aesthetic appeal for real artworks was positively predicted by rated self-relevance. In a second experiment (N = 45 online), we created synthetic, self-relevant artworks using deep neural networks that transferred the style of existing artworks to photographs. Style transfer was applied to self-relevant photographs selected to reflect participant-specific attributes such as autobiographical memories. Self-relevant, synthetic artworks were rated as more aesthetically appealing than matched control images, at a level similar to human-made artworks. Thus, self-relevance is a key determinant of aesthetic appeal, independent of artistic skill and image features.

Beauty and Uncertainty as Transformative Factors: A Free Energy Principle Account of Aesthetic Diagnosis and Intervention in Gestalt Psychotherapy

Drawing from field theory, Gestalt therapy conceives psychological suffering and psychotherapy as two intentional field phenomena, where unprocessed and chaotic experiences seek the opportunity to emerge and be assimilated through the contact between the patient and the therapist (i.e., the intentionality of contacting). This therapeutic approach is based on the therapist’s aesthetic experience of his/her embodied presence in the flow of the healing process because (1) the perception of beauty can provide the therapist with feedback on the assimilation of unprocessed experiences; (2) the therapist’s attentional focus on intrinsic aesthetic diagnostic criteria can facilitate the modification of rigid psychopathological fields by supporting the openness to novel experiences. The aim of the present manuscript is to review recent evidence from psychophysiology, neuroaesthetic research, and neurocomputational models of cognition, such as the free energy principle (FEP), which support the notion of the therapeutic potential of aesthetic sensibility in Gestalt psychotherapy. Drawing from neuroimaging data, psychophysiology and recent neurocognitive accounts of aesthetic perception, we propose a novel interpretation of the sense of beauty as a self-generated reward motivating us to assimilate an ever-greater spectrum of sensory and affective states in our predictive representation of ourselves and the world and supporting the intentionality of contact. Expecting beauty, in the psychotherapeutic encounter, can help therapists tolerate uncertainty avoiding impulsive behaviours and to stay tuned to the process of change.

Does Machine Understanding Require Consciousness?

This article addresses the question of whether machine understanding requires consciousness. Some researchers in the field of machine understanding have argued that it is not necessary for computers to be conscious as long as they can match or exceed human performance in certain tasks. But despite the remarkable recent success of machine learning systems in areas such as natural language processing and image classification, important questions remain about their limited performance and about whether their cognitive abilities entail genuine understanding or are the product of spurious correlations. Here I draw a distinction between natural, artificial, and machine understanding. I analyse some concrete examples of natural understanding and show that although it shares properties with the artificial understanding implemented in current machine learning systems it also has some essential differences, the main one being that natural understanding in humans entails consciousness. Moreover, evidence from psychology and neurobiology suggests that it is this capacity for consciousness that, in part at least, explains for the superior performance of humans in some cognitive tasks and may also account for the authenticity of semantic processing that seems to be the hallmark of natural understanding. I propose a hypothesis that might help to explain why consciousness is important to understanding. In closing, I suggest that progress toward implementing human-like understanding in machines—machine understanding—may benefit from a naturalistic approach in which natural processes are modelled as closely as possible in mechanical substrates.