Art Perception And Appreciation By Ma Aurora Ortiz Pdf

Among the main challenges of the predictive brain/mind concept is how to link prediction at the neural level to prediction at the cognitive-psychological level and finding conceptually robust and empirically verifiable ways to harness this theoretical framework toward explaining higher-order mental and cognitive phenomena, including the subjective experience of aesthetic and symbolic forms. Building on the tentative prediction error account of visual art, this article extends the application of the predictive coding framework to the visual arts. It does so by linking this theoretical discussion to a subjective, phenomenological account of how a work of art is experienced. In order to engage more deeply with a work of art, viewers must be able to tune or adapt their prediction mechanism to recognize art as a specific class of objects whose ontological nature defies predictability, and they must be able to sustain a productive flow of predictions from low-level sensory, recognitional to abstract semantic, conceptual, and affective inferences. The affective component of the process of predictive error optimization that occurs when a viewer enters into dialog with a painting is constituted both by activating the affective affordances within the image and by the affective consequences of prediction error minimization itself.

The predictive coding framework also has implications for the problem of the culturality of vision. A person’s mindset, which determines what top–down expectations and predictions are generated, is co-constituted by culture-relative skills and knowledge, which form hyperpriors that operate in the perception of art. INTRODUCTIONThe old notion of perception as unconscious, knowledge-driven inference or hypothesis testing , which asserts that the brain actively anticipates upcoming sensory input rather than passively registering it, has now been recast in the terms of contemporary neuroscience, and has recently undergone an unprecedented revitalization. It has been linked to the idea of the Bayesian brain – a probability machine that constantly makes predictions about the world and then updates them based on what it senses.

According to predictive coding model of perceptual inference, subjects try to infer the causes of their sensations based on multi-level generative models of the world (;;;; ). Predictions (priors) about the probable cause of sensory input, generated in higher levels of processing hierarchy, are continuously updated by prediction errors which code mismatches between expected and actual data. Recently, some theorists have further extended the predictive coding framework (or predictive error minimization, PEM) from brain to mind, applying it to a variety of cognitive mechanisms beyond perception itself. According to philosopher the Bayesian approach constitutes the “grand unified theory of mind as perception, action and attention are all in the same business of reducing sensory prediction error resulting with our exchanges with environment” (, p. 1330) notes, the higher-order aspects of inference in the brain represent the frontiers of theoretical neurobiology.

The main challenge is to link prediction at the neural level with prediction at the cognitive-psychological level and to find conceptually robust and empirically verifiable ways to harness this theoretical framework toward explaining higher-order mental and cognitive phenomena, including the subjective experience of aesthetic and symbolic forms. A step in this direction has been taken in the recently proposed “tentative prediction error account of visual art” (TPEA; ).It is the aim of this article to further extend the application of the predictive coding framework to the visual arts. To do this in a productive way requires moving from the rather abstract level of theory formulation to a more detailed discussion of particular instances of response to a work of art, that is, it requires testing the theoretical model against a specific case study. Consequently, the article is organized into three sections. First, I shall articulate some objections to and problems with the current formulation of the prediction error account of art perception.

Based on these observations, the second section presents a case study of an encounter with a particular painting in order to expand upon some key some aspects of predictive coding in visual art. I shall focus especially on the problem of the emotional response to a work of art within the PEM framework. Finally, I shall point out further implications of this theoretical model for the question of the social and cultural determination of vision.

PREDICTION ERROR OPTIMIZATION VERSUS THE RUSH TO THE OBJECTAny theory should be measured against empirical findings, in this case on what we know about how people actually interact with works of art. Seen in this light, the main objection to tentative prediction error immediately becomes apparent: the model describes an ideal situation, which represents a distinct minority of actual encounters with art works. This does not invalidate the theory as such, but addressing this discrepancy paves the way to pursuing some crucial aspects of predictive mind in art experience.When observing people’s reactions in front of works of art in a museum or gallery, one quickly notices that many viewers are content with performing the simple act of recognition, displacing the visual substance of the work as soon as possible with the kind of understanding that evidently does not prompt or entice further viewing. This situation is eloquently captured in an anecdote recounted by Rudolph Arnheim:“I remember once watching a teacher with her second-graders approaching a piece of abstract sculpture in a museum gallery. ‘What is this?’ asked the children. The teacher, very unsure herself, went closer and looked at the label.

Oscar Verlinski,’ she read. The children, satisfied, moved to the next object.”(, p. 61)Besides providing a depressively true account of the nature of many encounters between visitors and works of art in a museum, of the way in which people harvest meaning from works of art, observation captures some essential aspect of the process in which viewers make sense of art images. It describes the moment when the visual object, presented to view and soliciting an understanding, gets an “answer.” As a paradigmatic example of an act of translation, or displacement, it highlights the violent and terminal substitution of the visual presence of an art work with a label in the mind’s eye of the viewer. The moment the exhibit becomes the “gift of Oscar Verlinski” in the eyes of the inquiring children, it ceases to be a sculpture, an object endowed with visual and aesthetic interest.

In other words, the story neatly describes the psychological reality of surprise minimization in an encounter with an art work. By fixating on identification, the viewer’s interrogation of an object is effectively concluded.

And as much as if in the given case the object had been answered “correctly” (as e.g., “abstract sculpture,” or “work by Anthony Caro”). The moment the visible content of the art object is recognized as what it depicts, the viewing is concluded, instead of a series of exchanges between the image and the viewer opening up and ushering in reciprocal play, inviting the viewer into the rich possibilities of dialog. Very often, moreover, the viewer recognizes the content of the image as its subject – that is, the culturally ingrained capacity for recognizing subjects in pictorial content is grafted onto the biologically ingrained propensity for perceptual identification – and thereby translates or displaces the pictorial meaning. This mode of grasping a painting or sculpture can be seen as an extension of the evolutionary programmed operation of visual awareness, the role of which is to produce the best current interpretation of the visual scene, in the light of past experience, either our own or of our ancestors, and to make it available to the parts of the brain that plan and execute voluntary motor outputs. CASE STUDYTo obtain a better idea of how predictions operates in art perception, it is necessary to support a theoretical model with at least a minimal phenomenological account of actual viewing experience of specific work of art.

I shall do this with a remarkable painting by contemporary American painter Vincent Desiderio, which is an analytically rewarding case of an image that is not perceptually unstable, so the viewer is able to swiftly recognize the depicted objects; however, identification does not yield to understanding in the sense of a well-understood subject or an established symbolic/iconographic theme. The viewer’s (I assume a motivated viewer, willing and able to endure more than a fleeting encounter with the painting) initial response to the picture within PEM is plausibly explained by the mechanisms by which sensory predictions subserving recognition are exercised. In addition to contextual modulation, the low spatial frequency information in the image that encodes its gross properties triggers object and category information, which in turn serves as a prediction template to guide further sensory processing, i.e., the high spatial frequency perception that conveys details (,;; ). But despite the relative ease with which most individual objects in a pictorial space can be identified, the beholder is left puzzled as to what is transpiring in the depicted scene, what the meaning of the painting is. There is no help to be obtained from applying the usual strategy of seeking external guidance, for looking at the caption and learning that the title of the work is Spiegel im Spiegel ( Figure ) offers no explanation or definite clue.

The opacity of the painting in terms of its recognizable meaning will lead the motivated viewer to further attempt to minimize prediction error by engaging in an active search, and doing so by using both general strategies of PEM at the same time: by changing sensory input through action (that is, performing an active visual search in front of the painting) and by alternating the predictions through perception, that is, making the model fit the sensory input. Without a high-order generative model or predictive “template” (; ) against which to match the observed sensory data, the viewer will try both to adjust his expectations and simultaneously to explain away those visible aspects that resist imminent understanding. While most objects in the pictorial space can indeed be easily identified as such, there are mismatches waiting to be resolved – most notably understanding the expressions and gazes of the faces of both figures, or precisely defining the area in which they come closest to each other. Vincent Desiderio, Spiegel im Spiegel (2010), oil on canvas. © Vincent Desiderio, courtesy of Marlborough Gallery, New York.Prolonged engagement with the image unleashes a cycle of PEM, which enters conscious awareness and may be verbalized (and even socialized if the viewer interacts with a companion) as, for example: what exactly is the bandaged man clutching in his hand?

What is the function of the white band around the boy’s neck? In particular, what do the figures’ expressions convey? What state is the boy in – is he sleeping, comatose, dying? The content of the pictorial scene at the level of individual objects will be almost completely resolved as observed information is “iteratively reconciled across multipe levels of visual processing hierarchy, resulting in a progressive reduction in prediction error as the visual system settles on a single perceptual interpretation of the sensory input” (, p.

However, the identification of individual objects does not directly enable inferences about their relationships and hence about the meaning of the whole scene. It thus triggers a succession of higher-level, semantic predictions, which unfold through an ongoing exploration of the painting and concern above all the nature of the interaction between the depicted figures (is their enigmatic implied relationship indeed what the painting is “about”?). Similarly, the representational status of the scene remains uncertain: is it to be perceived as a real scene, or as a fantasy image (dream, vision) of the artist, or is to be seen as the state and content of the momentary state of consciousness of one of the depicted protagonists?

Art Perception And Appreciation By Ma Aurora Ortiz Pdf Online

Moreover, for an attentive viewer, the process of prediction error minimization does not transpire just at the level of (virtual) depicted objects and their relationships. Rather, there is a concomitant awareness of how objects arise from the painterly medium – in this case from Desiderio’s rich and deeply textured brushwork, with individual marks oscillating between representational, mimetic and non-mimetic function. On that level, one of the mismatches relates to the perception of the spatial setting and its uncertain representational status. The ambiguous spatial construction thwarts and frustrates attempts to recognize it in terms of some kind of empirical environment; the viewer’s perception of the virtual pictorial space as some sort of non-descript enclosed space, delineated by the ground and the wall, easily shifts to an awareness of the picture plane and markings, which seem to deny any claim to mimetic optical veracity. AFFECTIVE PREDICTIONSThe entire process of individual meaning-making out of this harrowing (others used even more expressive terms such as “strikingly frightening and nightmarish”) painting, within the predictive coding framework, is steeped in affective significance.

While individual feelings will naturally differ, a central part of a viewer’s encounter with the image is his or her emotional reaction to it. Recent models in affective neuroscience insist that affective meaning is not something superadded on the perceptual act pure and simple; rather, while the brain is engaged in object recognition, it concurrently extracts affective value from the observed scene, particularly its valence (;; see also, p. 255 for an early formulation). Affective (and interoceptive) predictions occur in rapid timescales and concurrently, not as a separate step, consequently conscious percepts are intrinsically infused with affective value. According to ) model, the brain’s prediction about the meaning of a visual sensation includes some representation of affective impact (or similar sensations) from the past. Moreover, the affective state of the perceiver at the moment of the initial encounter exerts top–down effects on visual processing , thereby constraining the formation of predictions from the sensory level upward.Some authors have further argued that viewers recognize the “emotional gist” of the scene, referred to as the global emotionality, whereby the scene can be rapidly identified as positive, negative, or neutral without having to explore the individual (local) features of the scene. In the given case, the phenomenology of the viewing experience does not support the notion of instantaneous emotional gist, but rather that of an affective reaction that unfolds throughout the entire duration of seeing.

Its initial stages appear to be related to the perception of affective affordances within the pictorial space, especially bodily postures and facial expressions of both depicted figures. As recent eye-tracking studies have demonstrated, the eye initially tends to fixate on emotional objects rather than more salient, neutral ones, and emotional saliency can override visual saliency defined by features such as intensity, color and orientation (; ). At the same time, people process the emotional implications of biologically emotional stimuli related to survival or reproduction automatically, but engage in more elaborative processing when confronted with socially emotional stimuli.The generally weak correlation between emotions and their predicted expressions is in this case further augmented by the fact that neither figure’s expression can be quickly interpreted, as they are both partly obscured and partly indeterminate. While neither figure constitutes emotional affordance of the kind usually used in neuroimaging experiments (that is, a stimulus with imminent threat or fear value), both are imbued with a saliency that involves the basic repertoire of emotional reactions.

The boy’s indeterminate expression signals a loss of consciousness, illness, or perhaps even death – all of them possibilities suffused with a strong affective valence. Similarly, the man’s body, completely wrapped in bandages, constitutes a powerful affordance whose negative valence is linked to instinctive fears of illness, accident, or disfiguration, that is, basic emotions related to bodily harm and/or survival. However, it is not just such biologically determined associations that determine how the affective response unfolds, as the process will likely also involve memories of culturally transmitted contents. Thus the eerie feeling the bandaged human figure elicits may not derive from individual experiences of bodily harm or medical treatment (or fears thereof), but also from affectively inscribed memories of experiencing and reacting to similar representations of uncanny objects – e.g., in horror movies. One should likewise note that while low-level visual properties generally contribute to an object’s perceived valence , this factor is even more important in the case of an art work.

The affective salience of the figures is thus inherently constituted by the painterly medium, that is, by the way Desiderio’s brushwork and handling of color depict them as objects in the pictorial space. THE LIMITATIONS OF THE DOPAMINERGIC REWARD ACCOUNTAccording to tentative prediction error hypothesis, it is the incompatibility (prediction error) that causes a part of the emotionality that viewers encounter in works of art. Their main thesis is that the reduction of unpredictability is experienced as positive and pleasurable. Thus: “The effort of mental work one has to do to cope with the prediction error is a condition sine qua non for receiving perceptual pleasure of a Gestalt formation (prediction error reduction)” (TPE, 1046).

The authors suggest that the degree of mental effort viewers make to compensate for unpredictability is related to reward. This is then further linked to dopaminergic reward modulation, whereby unexpected reward are associated with increased dopamine peaks.

Artists are thus in the business of postponing the final gratification: by using minimal prediction errors painters can ensure that viewers will obtain their reward and not give up prematurely. Similar claims have recently been made by, who argues “that the response of dopaminergic neurons to anticipated pleasure may be the physiological basis of the pleasure we experience when looking at art. Art may give rise to feelings of well-being because it predicts biological reward, even though further reward beyond the pleasure of viewing and vicariously experiencing may never materialize” (, pp. 428–429), and other recent opinions concur that positive emotional valence, or pleasure, is elicited in the transition from a state of high to low surprise.These views align with recent research on the neurobiology of reward. It is well-established that reward has a direct, non-volitional impact on perception, changing the salience of objects for attention. Dopamine receptors were found to mediate prefrontal control of signals in the visual cortex. Studies based on the monetary reward prospect paradigm reveal that reward leads to the tuning of sensory neurons and modulates the neural dynamics of early visual category processing (; for an overview of reward-related modification of sensory processing in the cortex, see; ).

More specifically, proposed that the interpretation of a novel and richly stimulating visual pattern leads to feelings of pleasure, because such patterns initially activate an abundant set of associations in the ventral visual pathway that manifest dense mu-opioid receptors. GRASPING MEANING – THE OUTCOME OF PREDICTIVE ERROR OPTIMIZATIONAs discussed above, in many (if not most) encounters with works of art, the recognition of the subject is accomplished instantaneously and does not lead to extensive engagement with the work, that is, once the minimization of prediction error at the level of object recognition concludes the viewing, there is no expectation of further reward and hence no motivation for a prolonged viewing and thinking about the work. Returning to the case study of Vincent Desiderio’s painting, two distinct patterns of response can be postulated. In each case, the viewer, having more or less effortlessly accomplished the recognition of objects in the scene, is left puzzling over the meaning of the painting – the image itself does not provide sufficient clues with which to optimize prediction error.

For viewer A, the semantic opacity of the painting does not constitute a challenge to be engaged with, resulting in a negatively valenced experience, which provides no incentive for further viewing (or for repeating such an experience). The well-documented aversion to modern art can be partly explained within this framework. On the other hand, viewer B, in the course of a much more extended, consciously reflected, viewing, experiences a cascade of prediction errors minimizations, which entails the simultaneous formation of new predictions, and thus again arrives at no final “solution” as to the meaning of the depicted scene.

Art Perception And Appreciation By Ma Aurora Ortiz Pdf File

At a certain point she leaves the painting with the best interpretation available at the moment; in the terms of PEM, she explains away the image (and her own reaction to it) given her continuously updated generative model. The optimization of prediction error concludes with the best possible outcome for the moment, but that outcome remains tentative, as subjectively the painting retains its enigma, lingering in memory and even generating new associations. The experience itself, although subjectively felt as something disquieting, troubling and certainly not inherently pleasurable, may ultimately be perceived as rewarding, and as providing motivation for another encounter of this kind. This fully accords with some recent accounts of aesthetic experience as being disruptive and transformative at its core.This is not the end of story, however, as our case study provides an apt opportunity to observe how the response to art work within the PEM framework is further, and perhaps decisively, affected by the viewer’s access to external facts, some kind of extra-pictorial information that cannot be gathered from the visible configuration of the image itself. In the given case, the key information is the knowledge that in this (and several other paintings) Desiderio depicted his severely physically and mentally handicapped son Sam, who needs a tube to breathe and whom he has been constantly caring for. The viewer realizes that the painting is not to be understood entirely as a fantasy image or a dream, and that the visible content of the scene refers to an existing aspect of reality. Some remaining sensory mismatches are consequently minimized (“the white tube around the boy’s neck is the breathing tube”), while simultaneously new (semantic) ones are generated (“If the boy is the artist’s son, is it likely that the bandaged figure is the painter himself?

PREDICTIVE ERROR MINIMIZATION AND THE CULTURALITY OF VISIONIn this section I shall point to some strategic implications of the predictive coding framework for art history and visual studies. The observation that predictions in visual art are dependent on the specific history of stimulation (, pp. 1044–1045, see also ) corresponds to the long-standing and widely shared understanding that perception depends on one’s personal and cultural background (; ). Recent research has extended these views by examining the qualitative difference in the ability to predict between experts and novices, emphasizing that experts have more resources for generating predictions, but also that they make more elaborate and accurate predictions in a given context (; ).

But importantly, the inter-individual differences in art perception do not stem from expertise alone, but need to be conceived more broadly. Summarizing earlier insights, argued that perceptual experience depends on “mental set,” without much elaborating of this notion.

More precisely, as I shall argue, the inter-individual differences in art perception depend on three variables: (i) personality traits/affective style – that is, how and why individuals differ in how they respond to emotional incentives. These have a strong modulatory effect, especially with respect to the affective aspects of art perception, so, for example, individuals with neurotic and anxious personality traits are more sensitive to processing facial or bodily expressions in particular (;; ); (ii) culture-cognitive capital related to the experiential situation, that is, the skills and knowledge related to visual perception and viewing art works; and (iii) the momentary psychosomatic state of the observer.Jointly, these three aspects form a mindset, which determines the generation of top–down expectations and predictions. Alternatively, mindset itself can be conceived of as the sum total – or repertoire – of predictions that pertain to the given task and as such it is further primed by the given experiential situation. In the case of a typical visual art experience, entering the museum or art gallery (or mere prospect thereof) serves to prime the mindset, forming a global expectation about the experience – a potentially fascinating and enjoyable event for person A, or the prospect of something boring and tedious that has to be endured for person B, with many variations in between.

This general expectation conditioned by all three variables thus sets the stage for specific predictions to be generated vis-a-vis the individual works of art encountered during the visit.Importantly, experience-based individual differences in viewing art works, which are partly dependent on culture-cognitive capital, link the predictive coding account of art perception to a major issue in art history and visual studies – the problem of the culturality and sociality of vision. In these and related disciplines, the biological-social continuum of seeing is routinely conceptualized as a distinction between vision (as a biological act) and visuality (as culturally and socially determined; e.g.,; ). As recently articulated by, p. 230): “When we speak of visuality, rather than simply vision or visual perception, we address the difference introduced into human seeing by traditional cultural meaning consolidated and reconfigured in images.” This conceptual distinction, however, is problematic and calls for alternative framework, which would have to consist of four levels in order to capture the process of vision in its biological and social complexity with more precision (, ).

Moving in a top–down fashion, these are the levels of:(1) Concepts, attitudes, values, and motives (and their discursive articulation) about images, vision and representation— that is, visuality in the strict sense of the term; these develop and persist on a time-scale of years to centuries. (2) The level of cognitive factors, which is strongly shaped by the environment and culture and roughly corresponds to ) notion of the “period eye”: semantic categories, patterns of inference experience and training in the range of representational conventions etc., that is, factors that operate in stretches ranging from the minutes of psychological time in individual perception to the historical time of years. (3) Perceptual strategies and processes – such as mechanisms of recognition, object identification and classification, patterns of saccadic eye movement, of selective visual attention, processes of unconscious embodied emotional and emphatic response, motor reaction activated by perception etc. These are processes that operate on both the conscious and the unconscious level and span a time frame of 100s of milliseconds to minutes.

(4) Mechanisms of detection of essential aspects of the scene, such as lines and edges, movement, color, binocular disparity, and related aspects of low-level vision – that is, biologically hard-wired unconscious events occurring on a time scale of up to ∼250 ms. Naturally, such a scheme implies neither a strict hierarchy nor hard boundaries between these stages, nor their mutual encapsulation. To the contrary, there is an ongoing, reciprocal relationship and feedback, whereby biologically embedded mechanisms interact with the higher levels of vision that can be modified by culture. Prediction errors at level 4, i.e., low-level vision, concerning mainly contrast and orientation, are sent further on in the processing stream and integrated into more complex messages concerning object identities, and then further on into semantic categories.

The two topmost levels – of visuality and cognitive categories – are in a strong sense culturally relative. But importantly, there is an increasing body of evidence suggesting that also at level 3, concerning perceptual strategies and processes, both culture and individual perceptual history penetrate perception (for an overview of this evidence, see; ). These stages operate on different time-scales and to an extent can be mapped as occurring in different areas of the brain, where higher levels represent the context in which the lower levels unfold (see also;, p. Representations thus depend on and interact with representations at other levels both within the topography of the brain and within the hierarchical conceptual scheme of vision outlined above.The experience-mediated perceptual-cognitive routines and skills that ensue from a viewer’s participation in a shared sphere of cultural habits and protocols of seeing and a sensitivity that is attuned to styles of representation ingrained in the viewer’s culture are all the produce of perceptual learning and – at the neuronal level – the mechanism of synaptic plasticity. There is an extensive body of recent research providing evidence on experience-dependent plasticity in adult brains and specifically on how perceptual expertise alters visual processing, e.g., by determining nature of object representation in the visual system (;;;;;;; ). It has been shown that the integration of top–down expectations and bottom–up sensory input can already be observed in the early visual cortex and that past experience modulates shape assignment and perceptual grouping (; ).

Cast in the terms of the PEM framework, previous experience and perceptual expertise generate distinct set of expectations (or priors) which determine interpretation of the image. Formation of a prediction error is achieved by adjusting synaptic efficacies both between and within levels of the processing hierarchy (; ). Post-synaptic effects either may be short-lived, directly impacting perception, or may control the updating and storage of predictions by inducing changes in synaptic growth. It is likely that it is by this mechanism that perceptual expertise becomes stabilized in the individual mind and by which it can even become collective in the sense of characterizing the perceptual habits of a certain group of people, so that commonalities can be observed in the social world of a particular group of viewers that govern how they form predictions in the perception of works of art (“period eye” according to one influential art-historical paradigm – cf. ).This kind of expertise is both enabling and constraining, as the following example will show.

Chinese literati and literati painting form a well-defined group of expert viewers of a well-defined body of art that to be understood requires a strong and specific form of visual-cognitive skills, some aspects of which can be indirectly inferred from their extensive writings reflecting on the subject. The predictions involved in their experience of painting operated at all four levels of the hierarchy: at the level of visuality, value-based judgments and preferences suggested what was worth looking at and was deemed to be of aesthetic value for the given social group and this determined the most general parameters of the perceptual encounter (e.g., by constraining attentional allocation according to the perceived value of the painting). At the level of cognitive factors, literati culture shaped predictions related to the semantic categorization of paintings, thus enabling the viewer-expert to differentiate and conceptualize not only specific topics and subjects or various styles, but also the variety of brushwork seen in the painting (so-called cunfa brushstrokes).

CONCLUDING REMARKS AND FUTURE DIRECTIONSI shall conclude by briefly outlining several possible directions in which the present accounts of the predictive coding framework for the visual arts can be further productively elaborated. The first direction, mentioned above, concerns the possibility of making some key theoretical accounts in art history and visual studies – such as ) classic account of the rise of naturalistic depiction, or “a general theory of visual culture” – compatible with the prediction error minimization framework. The second direction is to elaborate the model on the basis of further case studies of specific types of visual art objects. The theory could likely be productively applied to many pre-modern works of art, which in their original context of use served as objects endowed with specific functions, and where the “viewing” in the original setting was inextricably bound up with (or accompanied by) some sort of embodied action. Such works can be said to contain their own script for action; the experience of the original audience could thus be modeled through action-oriented predictive processing , which suggests that motor intentions, as they unfold into detailed motor actions, actively elicit continuous streams of sensory results that our brains predict. Furthermore, while note that the predictive framework does not explain the popularity of realist art, “which depicts the world as it is, thereby confirming rather than violating prediction error,” (TPEA, 1056) this genre of painting need not be discounted and the PEM framework can be elaborated for the naturalistic/realistic spectrum of artistic representations as well.The third challenge is even more complex, but offers the potential for truly interdisciplinary dialog between theorists of art and neuroscientists.

It has been argued that the actual virtue of predictive coding is the fact that it is typically implemented at a level of abstraction that is intermediate between that of low-level, biophysical, circuits and that of high-level, psychological, behaviors. While this indeed seems to be the case, the greatest challenge (as noted in the opening section) is linking the accounts of predictions at the neuronal level with those on the cognitive-psychological and cultural levels (see also ). While current research is providing an increasingly detailed insight into neuronal mechanisms, including an account of the interactions between prediction and error signals (;;;;; ), the relationship between the various levels of prediction operating in visual-arts perception, between the neuronal-architecture and cognitive-psychological levels of prediction, has hitherto been at best tentatively and sketchily explained. In particular, future work needs to address the nature of representational formats of hierarchically different levels of predictions. In other words, the notions of predictions (priors) needs to be related to range of terms currently used both within and outside the predictive coding framework to characterize disparate contents of mental representations underlying the recognition and interpretation of sensory content from across the hierarchy of vision, including, for example, the “generative image model” , the “pictorial schema” , the “image schema” , or “subjective internal representation”.

Much will also depend on whether (and how) some alignment can be made between the predictive coding framework and other current accounts of image perception, such as incremental grouping theory.The fourth challenge relates to determining how affective and empathic inference, as conceived in the PEM framework, arises out of integrated interaction between large-scale brain networks (;; ).