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Given the limitations of current models, this chapter takes us back to the structure and functioning of brain regions themselves, focussing first on on systems considered important for understanding consciousness from a representational viewpoint: corticothalamic systems, cerebellum, basal ganglia, and hypothalamus. It examines whether systems for processing different sensory modalities share common grounds, thereby offering clues about shared requirements for conscious representation. Both at the level of local circuits and area-to-area connectivity, differences between systems are considerable, making it hard to extract such requirements. Turning to subcortical regions such as the cerebellum, basal ganglia and hypothalamus, it is noted that they also harbor sensing and information-processing principles that have been previously considered essential for conscious representation (e.g., recurrency, statistical dependence, complexity). Departing from the concept of conscious experience as multimodal, situational representation, it is arguably important to frame-shift from a “columnar” and strictly hierarchical view of the neocortex to a more “horizontal” view that emphasizes the unique reverberatory and recursive properties of the cortical network. This paves the way for exploring whether such properties may support construction of higher aggregate (multi-area) forms of representation from lower-level forms operating at the level of single neurons and within-area groups of neurons.

In broad outline the brain’s subsystems can be understood in terms of specific functionality. This chapter introduces these subsystems and provides and overview of how they work together to provide the brain’s cognitive capabilities. The focus of the chapter is the mammalian forebrain, an elaborate complex of structures that take advantage of phylogenetically earlier brain systems to create explicit programs. Executing current programs is the primary responsibility of the Cortical-Basal Ganglia-Thalamus loop. Creating new programs is handled by the Hippocampus, which interprets new information in terms of deviations form a vast library of existing programs, and the Amygdala, whose circuitry marks a potential programs importance. Numerical rating of marked programs as to importance and risk is achieved with the Hypothalamus’s modulation of neurotransmitters.

Variation in behaviour is an essential ingredient and necessary precondition for creativity. This chapter explores the role of associative learning processes in the generation of behavioural variability. Behavioural variability can be explicitly selected through reinforcement. Importantly, operant variability appears to reflect instrumental control of a stochastic process, rather than the dynamics of a memory process. Furthermore, variation in behaviour spontaneously increases as the expectation of reinforcement decreases. Expectation-induced variability is functionally relevant for generating novel solutions, and is linked to the unusually high creative output found in patients suffering from mood disorders, such as depression and bipolar disorder. Basal ganglia pathways in vertebrates appear to be centrally involved in modulating the trade-off between variability versus stereotypy in behaviour.

This chapter engages with empirical work to develop a theory about the musicality of repetition. Why does repetition musicalize? What is it about the engagement engendered by repetition that makes it quintessentially musical? Findings from developmental psychology, psycholinguistics, neuroscience, cognitive psychology, and music perception are brought together to demonstrate the special ways that repetition can guide attention in time, directing orientation to relatively lower or higher levels of the temporal structure. These modes of orientation, in turn, are shown to contribute to embodied experiences of music and shared subjectivity—critical elements of musical pleasure. The psychology of ritual, trance, addiction, obsessive compulsion, and repetitive behavior and interests in early childhood are taken to inform practices of repetition in the musical domain.

The learning of cognitive programs faces many technical difficulties, but the most important is the valuation of programs that have delayed rewards. The algorithms of Reinforcement Learning that the brain uses tackle this head-on are logically situated in the Basal Ganglia, which represent the abstract sequential components of motor and cognitive plans. Such sequences are evaluated in terms of their expected reward and risk, which in turn are coded, by using the neurotransmitters dopamine and serotonin respectively, which serves as a common evaluative currency. Reinforcement learning algorithms learn by adjusting deviations in expected reward, a signal, which can also be used to program the Cortex’s memory representations. Tesauro’s use of reinforcement to learn the game of Backgammon provides a superb example of the putative integration of the process between the two forebrain subsystems.

Is human cognition best characterized in terms of the systematic nature of classical symbol processing systems (as argued by Fodor & Pylyshyn, 1988), or in terms of the context-sensitive, embedded knowledge characteristic of classical connectionist or neural network systems? We attempt to bridge these contrasting perspectives in several ways. First, we argue that human cognition exhibits the full spectrum, from extreme context sensitivity to high levels of systematicity. Next, we leverage biologically-based computational modeling of different brain areas (and their interactions), at multiple levels of abstraction, to show how this full spectrum of behavior can be understood from a computational cognitive neuroscience perspective. In particular, recent computational modeling of the prefrontal cortex / basal ganglia circuit demonstrates a mechanism for variable binding that supports high levels of systematicity, in domains where traditional connectionist models fail. Thus, we find that this debate has helped advance our understanding of human cognition in many ways, and are optimistic that a careful consideration of the computational nature of neural processing can help bridge seemingly opposing viewpoints.

As its name implies, the main characteristics of obsessive-compulsive disorder (OCD) are obsessions and/or compulsions. Different types of obsessions and compulsions make OCD a heterogeneous condition. Also, OCD exists on a continuum from mild cases to those with extremely severe and incapacitating manifestations generally not seen in other anxiety disorders. Clinical manifestations of OCD are striking and leave few people who observe them unimpressed. This is arguably due to the seriousness with which persons with OCD take their own obsessions and compulsions along with concurrent realization that these same obsessions and compulsions are senseless and should be gotten rid of. Indeed, there are few other examples in psychopathology where insight and deficiency of insight stand together, and where espousing and fighting the absurd are so intertwined. For all these reasons, OCD is often portrayed as a puzzling or intriguing disorder; in addition, it often represents a treatment challenge. Obsessive-compulsive disorder is probably the least controversial condition within the anxiety disorders because its clinical features are well described and relatively easily recognized and because hardly anyone doubts its existence as a psychopathological entity. What is controversial about OCD, however, is where it belongs and how it should be classified. This is a consequence of a number of features of OCD that make it look different from other anxiety disorders and of the close relationship that OCD has with some conditions outside of the realm of anxiety disorders. Listed below are a number of key questions about OCD…. 1. In view of its different clinical features and the vastly different severity of these features, should OCD be considered a unitary condition or divided into subtypes? 2. If OCD is to be divided into subtypes, on the basis of what criteria should it be done? Types of obsessions and compulsions, reasons for performing compulsions, severity of illness, degree of insight, age of onset, or something else? 3. Should neutralizing responses other than compulsions be given a more prominent role in the description and conceptualization of OCD? 4. How does insight contribute to the conceptualization of OCD? 5. What are the core features of OCD? Is OCD primarily an affective disorder, is it characterized by a primary disturbance in thinking, or is it essentially a disorder of repetitive behaviors?