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To Err and Err, but Less and Less TOERRANDERR,BUTLESSANDLESS Predictive coding and affective value in perception, art, and autism sander van de cruys Dissertation offered to obtain the degree of Doctor of Psychology (PhD) supervisor: Prof. Dr. Johan Wagemans Laboratory of Experimental Psychology Faculty of Psychology and Pedagogical Sciences KU Leuven 2014 © 2014, Sander Van de Cruys Cover image created by randall casaer. Title adapted from the poem The road to wisdom by the Danish scientist piet hein. Back cover image from Les Songes Drolatiques de Pantagruel (1565) attributed to françois desprez, but based on the fabulous, chimerical characters invented by françois ra- belais. Typographical style based on classicthesis developed by andré miede (GNU General Public Licence). Typeset in LATEX. abstract The importance of prediction or expectation in the functioning of the mind is appreciated at least since the birth of psychology as a separate discipline. From minute moment-to-moment predictions of the movements of a melody or a ball, to the long-term plans of our friends and foes, we continuously predict the world around us, because we learned the statistical regularities that govern it. It is often only when predictions go awry —when the sensory input does not match with the predictions we implicitly formed— that we become conscious of this incessant predictive activity of our brains. In the last decennia, a computational model called predictive coding emerged that attempts to formalize this matching pro- cess, hence explaining perceptual inference and learning. The predictive coding scheme describes how each level in the cortical processing hierarchy predicts inputs from levels below. In this way resources can be focused on that part of the input that was unpredicted, and therefore signals important changes in the environment that are still to be explained. In doing so the brain is guided by a single principle known as the prediction error minimization principle. Its constant effort to reduce uncertainty relative to its predictions is thought to enable adaptive behavior in a computationally manageable way. The appeal of this account is clear from the recent surge in studies using it to explain findings across virtually all subfields of psychology. Indeed, a generalized form of predictive coding has been proposed as Grand Unified Theory for psychology. Unpacking the prediction error minimization principle in these disparate fields has led to powerful, integrating insights. But is this just another short-lived fad in psy- chology? Or are its roots deeper and its branches as far-reaching as its proponents foreshadow? We will only know if we examine the framework (its assumptions, implementations, implications and limitations) in full detail. The main mission of this dissertation is to do a small but, so we will argue, important part of this work. Specifically, we focus on how affective processes can have their place in this theory, since this has so far remained underexposed, given the mainly cognitive and perceptual character of previous work. To do so, we start with two elaborate ‘case studies’. The first applies predictive coding to autism spectrum disorders, a psychiatric syndrome characterized by difficulties in social, cognitive and affective processing. We argue that the weight (or ‘precision’) attributed to prediction errors in autism is unduly high and inflexible, rather than determined by context uncertainty. This may explain both their peculiar behavior in cognitive and perceptual tasks, and their affective-motivational troubles. The second case is an application of predictive coding to visual art. Here we develop the hypothesis that making predic- tive progress (i. e., actively reducing prediction errors) is intrinsically pleasurable, which helps to explain affective experiences in art appreciation. These theoretical studies are followed by two empirical works, of which the first is an initial step in subjecting the hypothesis of predictive progress and pleasure to the test, using Gestalt discovery in two-tone images. The second investigates whether perception can be biased by affective relevance of the top-down priors or predictions applied to interpret a stimulus. It uses bistable point-light figures and finds some support that this is indeed the case. The closing chapter attempts to zoom out and build a coherent account of positive and negative affective value within the confines of the predictive coding framework. The core explanatory factor here is the rate of prediction error reduction and the (unexpected) changes in these rates. A host of evidence seems consistent with this idea that affective experience reflects a form of non-conceptual metacognition about prediction error dynamics. In sum, this new application of predictive coding in issues of emotional value is worth following through, because of its parsimony, explanatory power, and the specific, testable research questions that can be derived from it. Most likely, the theory will be further refined by a joint effort of neurocomputa- tional modelers and experimental psychologists, for which we set out the tracks in the different chapters. iii samenvatting Psychologen onderkennen het belang van predicties of verwachtingen in het functioneren van de geest al sinds het ontstaan van hun discipline. Van de baan van een bal of het verloop van een melodie tot de plannen van onze partners en tegenstrevers, wij voorspellen voortdurend de wereld rondom ons, omdat we de statistische relaties die erin van kracht zijn geleerd hebben. Pas wanneer onze predicties mis zijn —wanneer de sensoriële informatie niet overeenstemt met de predicties die we er impliciet over vormen— worden we ons bewust van die voortdurende predictieve activiteit van onze hersenen. In de voorbije decennia ontwikkelden cognitieve neurowetenschappers een computationeel model met de naam predictive coding, dat dit iteratief matchen van predicties met input probeert te formaliseren, en zo perceptueel leren and inferentie tracht te verklaren. Het model beschrijft hoe elk niveau in de corticale hierarchie van perceptuele verwerking de neurale activiteit in een lager niveau voorspelt, zodat verwerkingsmiddelen toegespitst kunnen worden op het deel van de input dat onverwacht was. Dit deel omvat immers belangrijke veranderingen in de omgeving die nog niet opgenomen zijn in ons huidig mentaal model. De hersenen volgen hierbij één centraal principe bekend als het predictiefout-minimaliseringsprincipe. De constante inspanningen van het brein om de onzekerheid relatief tot zijn predicties te reduceren zouden adaptief gedrag mogelijk maken op een computationeel beheersbare manier. Een recente groei in studies die predictive coding aanwenden om bevindingen te verklaren in praktisch alle subdomeinen van de psychologie, is een bewijs van de aantrekkingskracht van dit model. Meer nog, een veralgemeende vorm van predictive coding wordt naar voor geschoven als unificerende theorie voor psychologie en de neurowetenschappen. Het doordenken van het predictiefout-minimaliseringsprincipe in de uiteenlopende subdomeinen heeft geleid to krachtige, integrerende inzichten. Maar is dit simpelweg de nieuwe rage in de psychologie, intens maar snel weer vergeten? Of reiken de wortels ervan dieper en de vertakkingen zo ver als zijn verdedigers ons voorhouden? We weten het pas als we het model kritisch on- derzocht hebben; zijn vooronderstellingen, implicaties en beperkingen inbegrepen. Het centrale doel van dit proefschrift is om van dat werk een klein maar, zo zullen we betogen, belangrijk deel te doen. We richten meer specifiek de aandacht op de plaats die affectieve processen kunnen hebben in dit kader, omdat dit tot nu toe onderbelicht bleef in het hoofdzakelijk cognitief en perceptueel getinte werk over predictive coding. We beginnen dit werk met twee uitvoerige ‘gevalsstudies’. In de eerste passen we predictive coding toe op autismespectrumstoornis, een psychiatrische syndroom gekenmerkt door moeilijkheden in sociale, cogni- tieve en affectieve verwerking. We beargumenteren dat het gewicht dat toegekend wordt aan predictiefouten (technisch: de ‘precisie’) in autisme onterecht hoog en inflexibel is, in plaats van aangepast aan onzekerheid in de context. Vanuit dat gegeven kunnen we zowel ongewoon gedrag in cognitieve en perceptuele taken begrijpen, als de affectief-motivationele problemen. In de tweede casus passen we predictive coding toe op visuele kunst. Hier ontwikkelen we de hypothese dat predictieve vooruitgang boeken (d.i., het actief reduce- ren van predictiefouten) intrinsiek plezierig is, en dat dit onze affectieve beleving van kunst helpt verklaren. Na deze theoretische studies volgen twee empirische werken, waarvan het eerste poogt de hypothese over predictieve vooruitgang en positief affect aan de test te onderwerpen. We gebruiken daarbij ontdekking van Gestalt (voorspelbare structuur) in vervormde afbeeldingen. Het tweede empirische werk bekijkt of perceptie (van bistabiele puntlichtfiguren) vertekend kan zijn door affectieve relevantie van predicties die we hanteren om een stimulus te interpreteren. In het afsluitende hoofdstuk zoomen we uit en trachten we een coherente invulling te geven aan positief en negatief affect binnen het computationeel kader van predictive coding. De verklarende factor aan de basis hier is verandering in predictiefouten over tijd (technisch: de eerste afgeleide van predictiefout) en (onverwachte ) veranderingen in die ‘tempo’s’. We bespreken een rist bevindingen die compatibel lijkt te zijn met het idee dat affectieve ervaring
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