Predictive Error Reduction and the Twofold Nature of Aesthetic Pleasure

2016 ◽  
Vol 4 (4) ◽  
pp. 327-338 ◽  
Author(s):  
Gianluca Consoli
Keyword(s):  
Common Core ◽  
Subjective Experience ◽  
Aesthetic Experience ◽  
Complex Dynamics ◽  
Predictive Coding ◽  
Aesthetic Perception ◽  
Perceptual Inference ◽  
Functional Relationships ◽  
Aesthetic Pleasure ◽  
Points Of View

Recently, the predictive coding account of perceptual inference has been extended to visual aesthetic experience, in particular to the experience enabled by artworks that challenge habitual predictions and ordinary perceptual routines. By virtue of its dynamical approaches, the predictive coding account of visual art catches aesthetic perception and evaluation as a complex dynamics of intertwined perpetual, affective and cognitive processes. On the basis of some of the most relevant findings of these dynamical approaches, I argue that aesthetic pleasure has a complex and original nature, something akin to a twofold nature. Specifically, I argue that aesthetic pleasure is twofold from different points of view: (a) it represents the connection of two very different functions, namely anticipation and reaction; (b) its different forms share a specific common core; however, this common core can be instantiated by very different functional relationships of causes and effects; (c) aesthetic pleasure represents a positive affective appraisal accompanying first-order elaboration, but it can also co-activate negative subjective experience, mixing together positive and negative affect.

scholarly journals Estetika Simbolik pada Desain Bangunan Komersil di Kawasan Perdagangan Cihampelas

Humaniora ◽  
2012 ◽  
Vol 3 (2) ◽  
pp. 475 ◽  
Author(s):  
Doni Morika
Keyword(s):  
Human Body ◽  
Aesthetic Experience ◽  
Broad Sense ◽  
Aesthetic Sense ◽  
Aesthetic Pleasure ◽  
Behavior Settings ◽  
Points Of View ◽  
The Aesthetic

The notion of aesthetics so far did not produce a conclusion crystallized from various points of view offered by observer. It came from the standpoint of behavioral and psychological environment to obtain the aesthetic sense which was based on the notion of meaning, perception, and aesthetic experience. In the philosophy of beauty "aesthetic experience" was in the view of phenomenology of the aesthetic experience of the "thing". Sensory aesthetic experience was based on observations at the same time with the whole soul of the human body and produced a feeling of participating bound, carried away, and enticed her feelings toward an aesthetic pleasure and experience. The question raised then is how these symptoms that could affect the behavior settings in the broad sense. Good answers to these questions will be able to make designers better understand the behavior of the users as well as empower designers to contribute to the environment.  

Aesthetic Significance Of Holidays

2020 ◽  
Vol 2 (08) ◽  
pp. 647-651
Author(s):  
Shadimetova Gulchehra Mamurovna
Keyword(s):  
Life Events ◽  
Theoretical Basis ◽  
Aesthetic Perception ◽  
National Pride ◽  
Aesthetic Taste ◽  
National Values ◽  
Aesthetic Pleasure ◽  
History Of ◽  
Artistic Images ◽  
Methodological Aspects

Holidays have the power to reflect the nation's views, imagination, vision and national values about the scientist and man through artistic images. In addition, holidays form and strengthen feelings such as national pride and national pride, which are composed of such principles as nationhood, popularity, heroism, beauty, grandeur, as well as aesthetic pleasure, aesthetic interest, aesthetic taste and formation of aesthetic ideals – forming a composition of aesthetic perception that distinguishes people from other life events. In this article, the stages of development of holidays and their artistic and aesthetic features will be studied and studied on a scientific and theoretical basis. Also, the philosophical-aesthetic analysis of the concept of the holiday, the history of its development and scientific-methodological aspects are studied.

scholarly journals Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex

2016 ◽  
Vol 2 (11) ◽  
pp. e1601335 ◽  
Author(s):  
Jorge F. Mejias ◽  
John D. Murray ◽  
Henry Kennedy ◽  
Xiao-Jing Wang
Keyword(s):  
Large Scale ◽  
Complex Dynamics ◽  
Predictive Coding ◽  
Causality Analysis ◽  
Frequency Dependent ◽  
Brain Functions ◽  
Wide Range ◽  
Cortical Laminar ◽  
Feedback Frequency ◽  
Visual Cortical

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.

Embodied Aesthetics

2018 ◽  
pp. 890-910
Author(s):  
Barbara Gail Montero
Keyword(s):  
Aesthetic Experience ◽  
The Body ◽  
Traditional View ◽  
Bodily Experience ◽  
Aesthetic Pleasure ◽  
Embodied Aesthetics ◽  
The Aesthetic ◽  
Bodily Movements

Although great art frequently revers the body, bodily experience itself is traditionally excluded from the aesthetic realm. This tradition, however, is in tension with the experience of expert dancers who find intense aesthetic pleasure in the experience of their own bodily movements. How to resolve this tension is the goal of this chapter. More specifically, in contrast to the traditional view that denigrates the bodily even while elevating the body, I aim to make sense of dancers’ embodied aesthetic experience of their own movements, as well as observers’ embodied aesthetic experience of seeing bodies move.

scholarly journals Predictive Coding Models for Pain Perception

2019 ◽  
Author(s):  
Yuru Song ◽  
Mingchen Yao ◽  
Helen Kemprecos ◽  
Áine Byrne ◽  
Zhengdong Xiao ◽  
...  
Keyword(s):  
Experimental Data ◽  
Chronic Pain ◽  
Pain Perception ◽  
Predictive Coding ◽  
Oscillatory Activity ◽  
Top Down ◽  
Perceptual Inference ◽  
Bottom Up ◽  
Temporal Coordination ◽  
Mechanistic Insight

AbstractPain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we use a predictive coding paradigm to characterize both evoked and spontaneous pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats—two regions known to encode the sensory-discriminative and affective-emotional aspects of pain, respectively. We further propose a framework of predictive coding to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Specifically, we develop a high-level, empirical and phenomenological model to describe the macroscopic dynamics of bottom-up and top-down activity. Supported by recent experimental data, we also develop a mechanistic mean-field model to describe the mesoscopic population neuronal dynamics in the S1 and ACC populations, in both naive and chronic pain-treated animals. Our proposed predictive coding models not only replicate important experimental findings, but also provide new mechanistic insight into the uncertainty of expectation, placebo or nocebo effect, and chronic pain.Author SummaryPain perception in the mammalian brain is encoded through multiple brain circuits. The experience of pain is often associated with brain rhythms or neuronal oscillations at different frequencies. Understanding the temporal coordination of neural oscillatory activity from different brain regions is important for dissecting pain circuit mechanisms and revealing differences between distinct pain conditions. Predictive coding is a general computational framework to understand perceptual inference by integrating bottom-up sensory information and top-down expectation. Supported by experimental data, we propose a predictive coding framework for pain perception, and develop empirical and biologically-constrained computational models to characterize oscillatory dynamics of neuronal populations from two cortical circuits—one for the sensory-discriminative experience and the other for affective-emotional experience, and further characterize their temporal coordination under various pain conditions. Our computational study of biologically-constrained neuronal population model reveals important mechanistic insight on pain perception, placebo analgesia, and chronic pain.

scholarly journals ELT- Autobiographic memory: a source for communicative competence

2016 ◽  
Vol 3 (1) ◽  
pp. 9
Author(s):  
A.V.S. Jayaannapurna
Keyword(s):  
Personal Experience ◽  
Subjective Experience ◽  
Aesthetic Experience ◽  
Communicative Competence ◽  
New Horizons ◽  
Autobiographic Memory ◽  
Inherent Nature

Language with all its paraphernalia, opens its wings of expression and communication in to new horizons of aesthetic experience. In addition, there is the inherent nature of language itself, which ultimately represents, symbolises, expresses, and can even shape our experience, but it is not the experience itself .With in communication, there is a lot of translation that must take place to go from the essence of our personal experience to the communication of words. In order to understand autobiographic memories, we use language to bridge the gap between dimensions ― between the dimension of subjective experience and the dimension of objective manifestation.

A Farewell to Art: Aesthetics as a Topic in Psychology and Neuroscience

2020 ◽  
Vol 15 (3) ◽  
pp. 630-642 ◽  
Author(s):  
Martin Skov ◽  
Marcos Nadal
Keyword(s):  
Aesthetic Experience ◽  
Behavioral Control ◽  
Sensory Stimuli ◽  
Hedonic Value ◽  
Hedonic Valuation ◽  
Emotional Processes ◽  
Aesthetic Pleasure ◽  
Substantial Progress ◽  
The Aesthetic ◽  
Definition Of

Empirical aesthetics and neuroaesthetics study two main issues: the valuation of sensory objects and art experience. These two issues are often treated as if they were intrinsically interrelated: Research on art experience focuses on how art elicits aesthetic pleasure, and research on valuation focuses on special categories of objects or emotional processes that determine the aesthetic experience. This entanglement hampers progress in empirical aesthetics and neuroaesthetics and limits their relevance to other domains of psychology and neuroscience. Substantial progress in these fields is possible only if research on aesthetics is disentangled from research on art. We define aesthetics as the study of how and why sensory stimuli acquire hedonic value. Under this definition, aesthetics becomes a fundamental topic for psychology and neuroscience because it links hedonics (the study of what hedonic valuation is in itself) and neuroeconomics (the study of how hedonic values are integrated into decision making and behavioral control). We also propose that this definition of aesthetics leads to concrete empirical questions, such as how perceptual information comes to engage value signals in the reward circuit or why different psychological and neurobiological factors elicit different appreciation events for identical sensory objects.

scholarly journals A Smart Way of Coping with Common Core Challenges - Introduction to CAFA SmartWorkbook

2015 ◽  
Vol 1 (2) ◽  
pp. 70 ◽  
Author(s):  
Jaehwa Choi ◽  
Miseon Kang ◽  
Najung Kim ◽  
William Dardick ◽  
Xinxin Zhang
Keyword(s):  
Common Core ◽  
Assessment Tool ◽  
School Administrators ◽  
Math Education ◽  
Educational Innovation ◽  
State Standards ◽  
Assessment Tools ◽  
Math Teachers ◽  
Information And Communication ◽  
Points Of View

<p>The Common Core State Standards (CCSS) in mathematics are currently adopted in most U.S. states. Nonetheless, most math teachers across the country are still experiencing difficulties in putting these standards into practice. Teachers and local school administrators are faced with a challenge of adapting methodologies in instruction and assessment to ensure that students master the knowledge and skills required in the new standards. This leads to an urgent need for well-designed teaching and assessment tools for math education that are aligned to the CCSS.</p><p>The purpose of this paper is to illustrate the Computer Adaptive Formative Assessment (CAFA) SmartWorkbook which is an Information and Communication Technology (ICT) based teaching and assessment tool specially designed for coping with challenges in implementing the CCSS in mathematics. The CAFA SmartWorkbook represents a new stage in exploring opportunities in educational innovation, capitalizing on advances in assessment and technology. This system can be an effective solution to cope with CCSS challenges in both theoretical and practical points of view for students, teachers, parents, and educational administrators.</p>

scholarly journals Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex

2016 ◽  
Author(s):  
Jorge F. Mejias ◽  
John D. Murray ◽  
Henry Kennedy ◽  
Xiao-Jing Wang
Keyword(s):  
Large Scale ◽  
Complex Dynamics ◽  
Predictive Coding ◽  
Target Area ◽  
Causality Analysis ◽  
Frequency Dependent ◽  
Brain Functions ◽  
Wide Range ◽  
Cortical Laminar ◽  
Feedback Frequency

AbstractInteractions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding predictive coding, executive control and a gamut of other brain functions. The underlying circuit mechanism, however, remains poorly understood and represents a major challenge in neuroscience. In the present work we tackled this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intra-laminar, inter-laminar, inter-areal and whole cortex) scales. The model was tested by reproducing, and shedding insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas: feedforward pathways are associated with enhanced gamma (30-70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low beta (8-15 Hz) oscillations. We found that in order for the model to account for the experimental observations, the feedback projection needs to predominantly target infragranular layers in a target area, which leads to a proposed circuit substrate for predictive coding. The model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of inter-areal signaling, as reported in recent monkey and human experiments. Taken together, this work highlights the importance of multi-scale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.

scholarly journals Predictive Neural Computations Support Spoken Word Recognition: Evidence from MEG and Competitor Priming

2020 ◽  
Author(s):  
Yingcan Carol Wang ◽  
Ediz Sohoglu ◽  
Rebecca A. Gilbert ◽  
Richard N. Henson ◽  
Matthew H. Davis
Keyword(s):  
Word Recognition ◽  
Prediction Error ◽  
Spoken Word Recognition ◽  
Predictive Coding ◽  
Spoken Word ◽  
Speech Comprehension ◽  
Speech Sounds ◽  
Neural Responses ◽  
Perceptual Inference ◽  
Neural Computations

AbstractHuman listeners achieve quick and effortless speech comprehension through computations of conditional probability using Bayes rule. However, the neural implementation of Bayesian perceptual inference remains unclear. Competitive-selection accounts (e.g. TRACE) propose that word recognition is achieved through direct inhibitory connections between units representing candidate words that share segments (e.g. hygiene and hijack share /haid3/). Manipulations that increase lexical uncertainty should increase neural responses associated with word recognition when words cannot be uniquely identified (during the first syllable). In contrast, predictive-selection accounts (e.g. Predictive-Coding) proposes that spoken word recognition involves comparing heard and predicted speech sounds and using prediction error to update lexical representations. Increased lexical uncertainty in words like hygiene and hijack will increase prediction error and hence neural activity only at later time points when different segments are predicted (during the second syllable). We collected MEG data to distinguish these two mechanisms and used a competitor priming manipulation to change the prior probability of specific words. Lexical decision responses showed delayed recognition of target words (hygiene) following presentation of a neighbouring prime word (hijack) several minutes earlier. However, this effect was not observed with pseudoword primes (higent) or targets (hijure). Crucially, MEG responses in the STG showed greater neural responses for word-primed words after the point at which they were uniquely identified (after /haid3/ in hygiene) but not before while similar changes were again absent for pseudowords. These findings are consistent with accounts of spoken word recognition in which neural computations of prediction error play a central role.Significance StatementEffective speech perception is critical to daily life and involves computations that combine speech signals with prior knowledge of spoken words; that is, Bayesian perceptual inference. This study specifies the neural mechanisms that support spoken word recognition by testing two distinct implementations of Bayes perceptual inference. Most established theories propose direct competition between lexical units such that inhibition of irrelevant candidates leads to selection of critical words. Our results instead support predictive-selection theories (e.g. Predictive-Coding): by comparing heard and predicted speech sounds, neural computations of prediction error can help listeners continuously update lexical probabilities, allowing for more rapid word identification.

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