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Schizophrenia is a disabling psychotic illness that has been associated with alterations in synaptic connectivity and neurotransmission. Since event-related potential (ERP) components are typically generated by the summation of postsynaptic potentials produced by neural populations, these measures are well suited to assess such pathophysiological alterations. This chapter reviews the utility of ERP components in the investigation of the cognitive and neural mechanisms affected by schizophrenia. It focuses on five components: mismatch negativity (MMN), P50 measures of sensory gating, N100 and P300 in the oddball discrimination paradigms, and the N400 component elicited during language processing. These components test key cognitive systems affected by schizophrenia: sensory memory (MMN), sensory processing and inhibition (P50, N1), selective attention and working memory (P300), and semantic processing (N400). These components are discussed with respect to the following issues: (1) cognitive and neural systems indexed by the component, (2) abnormalities in schizophrenia, (3) sensitivity and specificity to schizophrenia, (4) clinical correlates, and (5) relationship to genetic variation. ERP components are well validated biomarkers for schizophrenia which have significant promise in the characterization of genomic and epigenomic factors, pharmacological response in humans and animal models, and the developmental and cognitive expression of the illness.

This article provides an overview of what shapes the acoustic signals that arrive at the ear. There are three physical processes which are capable of generating audible sound: a vibrating surface, a turbulent fluid, and a rapid pressure change. It is structured as an account of the journey of a sound wave, from first generation, then propagation outdoors, followed by transmission into a building and indoor reverberation to its final reception, perception, and assessment. It throws light on how the signals that arrive at the ear are generated; how environment influences these signals; and how sound is perceived, controlled, and assessed in the environment. It gives information on basic principles, common measurements and current modelling techniques. Finally, it suggests that the external environment is complex and the acoustic signals arriving the ear reflect this complexity by carrying information about their production, their interaction with the environment, and their transmission through it.

Music’s continual temporal changes make it a useful stimulus for studying cognitive and neural processes unfolding over time. Although this dynamic nature is widely recognized on a macro level, the importance of temporal changes in individual notes is less widely discussed. For example, textbooks often focus on power spectra—time invariant summaries of spectral information—to explain differences in timbre between musical instruments. Unfortunately, this approach overlooks the importance of dynamic fluctuations in individual notes’ overtones. This chapter highlights the under-recognized importance of temporal structure in musical sounds by synthesizing a diverse range of research on musical acoustics and perception. It concludes by contrasting the rich temporal dynamics of musical sounds with the temporally invariant tones common in auditory perception research—which exhibit significant shortcomings regarding ecological validity. Although this creates barriers for generalizing outcomes from experiments with simplistic tones, it also offers exciting new topics for future research.

This chapter is from the forthcoming The Oxford Handbook of Affective Computing edited by Rafael Calvo, Sidney K. D'Mello, Jonathan Gratch, and Arvid Kappas. The brain is involved in the registration, evaluation, and representation of emotional events and in the subsequent planning and execution of appropriate actions. Novel interface technologies—so-called affective brain-computer interfaces (aBCI)—can use this rich neural information, occurring in response to affective stimulation, for the detection of the user’s affective state. This chapter gives an overview of the promises and challenges that arise from the possibility of neurophysiology-based affect detection, with a special focus on electrophysiological signals. After outlining the potential of aBCI relative to other sensing modalities, the reader is introduced to the neurophysiological and neurotechnological background of this interface technology. Potential application scenarios are situated in a general framework of brain-computer interfaces. Finally, the main scientific and technological challenges that have yet to be solved on the way toward reliable affective brain-computer interfaces are discussed.

This article introduces a number of critical features of the afferent synapse with particular reference to mammalian hearing. The auditory synapse is the first relay point for the input of sound into the nervous system and the properties of this synapse determine how well a signal from the hair cells is relayed up the auditory brainstem. This information is re-encoded as a pattern in the auditory nerve for subsequent analysis by the brain. The design of the afferent synapse ensures that the information content is not degraded. The article describes the structure and physiology of the afferent synapse and explains the presynaptic and postsynaptic mechanisms. Furthermore, it reveals the paired presynaptic and postsynaptic responses. In addition, it also describes the concept of synaptic adaptation and the genetics of the synapse. It also states that it is sometimes necessary to extrapolate from non-mammalian systems.

Memory is one of the cognitive functions that deteriorate most with age. The types of memory most affected by aging are working memory, the short-term memory maintenance and simultaneous manipulation of information, and episodic memory, our memory for personally experienced past events. Functional neuroimaging studies indicate important roles in age-related memory decline for the medial temporal lobe (MTL) and prefrontal cortex (PFC) regions, which have been linked to two major cognitive aging theories, the resource and binding deficit hypotheses, respectively. Interestingly, functional neuroimaging findings also indicate that aging is not exclusively associated with decline. Some older adults seem to deal with PFC and MTL decline by shifting to alternative brain resources that can compensate for their memory deficits. In the future, these findings may help to distinguish normal aging from early Alzheimer’s dementia and the development of memory remediation therapies.

This article examines age-related changes in the central auditory system from anatomical and neurochemical vantage points, and then the functional consequences of these structural changes are presented in the context of human perception and the underlying physiology of animal model systems. Neural processing in the central auditory system is dependent on the magnitude and timing of excitatory and inhibitory inputs to auditory neurons. Recent evidence suggests that there may be aging changes in other neurotransmitters at the level of the inferior colliculus. The molecular, anatomical, and neurochemical changes occurring with age in the auditory system have functional consequences for central auditory sound processing. Many of these are due to reduced cochlear outputs with age, and others appear to be somewhat independent of these peripheral changes, in line with neurodegenerative deficits of the aging brain. The article reveals that plasticity in the central auditory system often occurs well into old age, which is interesting from the perspectives of both basic neuroscience and future clinical interventions.

Alexithymia is a multifaceted personality construct characterized by the impaired ability to reflect on and regulate one’s own emotions. This chapter refers to a wide range of domains of investigation in the field of social neuroscience to capture and specify the processes that could account for the observed associations between such an inability to monitor and self-regulate emotions and altered social understanding and interactions. To this end, it provides empirical support for considering alexithymia as a relevant model to investigate the links between brain, cognition and behavior, notably not only to delineate potential pathways between dysfunctional cerebral circuits, poor emotional insight, and intersubjectivity, but also to further explore their links with self-oriented and other-oriented harming behaviors.

This chapter reviews event-related potential (ERP) studies in patients suffering from neurodegenerative diseases. Such studies have been conducted from two different points of view: using ERPs to learn something about the disease and using the disease to learn something about ERPs. This review focuses on the former aspect: the utility of ERPs in the clinic. Thus, ERP research in neurodegenerative diseases will be discussed from the perspective of the insights gained from ERPs (1) for diagnosis, (2) for delineating and understanding the consequences of the disease for cognition, and (3) for determining the prognosis about the course of the disease.

This chapter reviews the ultimate and proximate levels of analysis on altruism in humans, hoping to create an overarching framework that places each within a larger context that can stimulate human research informed by extensive empirical research in animals. The available neuroscientific evidence will be reviewed at the end, demonstrating consistently that decisions to help are mediated through overlapping decision and reward circuits that integrate emotional and contextual information into a unified somatic state that guides decisions to help. The chapter first defines the important terms, reviews in brief the most common and widely used biological models of altruism, and then provides evidence for these models. After this, the proximate mechanism will be explicated, largely through indirect evidence regarding the motivational and neural circuits thought to underlie decisions to help. The chapter ends with recommendations for future research to provide more direct evidence for the proximate mechanism, using more ecological tasks that elicit altruistic tendencies while being amenable to concurrent recording with neuroscientific tools.

Analogy is an inductive mechanism based on structured comparisons of mental representations. It is an important special case of role-based relational reasoning, in which inferences are generated on the basis of patterns of relational roles. Analogical reasoning is a complex process involving retrieval of structured knowledge from long-term memory, representing and manipulating role-filler bindings in working memory, identifying elements that play corresponding roles, generating new inferences, and learning abstract schemas. For empirical analogies, analogical inference is guided by causal knowledge about how the source analog operates. Simpler types of relation-based transfer can be produced by relational priming. Human analogical reasoning is heavily dependent on working memory and other executive functions supported by the prefrontal cortex, with the frontopolar subregion being selectively activated when multiple relations must be integrated to solve a problem.

Metacognition refers to the monitoring and control of basic cognitive processes. The presumption is that some minds have a cognitive executive that oversees and regulates thinking and problem solving to evaluate progress and optimize prospects. Comparative psychologists are currently exploring whether nonhuman animals share humans’ capacity for metacognition. Researchers have tested various species in perceptual, memory, and foraging metacognition paradigms. There is a growing consensus that some species may possess a basic metacognitive capacity, though theoretical debate continues. This chapter summarizes the current state of the empirical literature on animal metacognition, discussing the research’s progress to date, remaining empirical challenges and theoretical issues, and the research’s implications for broader issues of reflective mind and cognitive self-regulation in animals and humans.

Anomia is a term that describes the inability to retrieve a desired word, and is the most common deficit present across different aphasia syndromes. Anomic aphasia is a specific aphasia syndrome characterized by a primary deficit of word retrieval with relatively spared performance in other language domains, such as auditory comprehension and sentence production. Damage to a number of cognitive and motor systems can produce errors in word retrieval tasks, only subsets of which are language deficits. In the cognitive and neuropsychological underpinnings section, we discuss the major processing steps that occur in lexical retrieval and outline how deficits at each of the stages may produce anomia. The neuroanatomical correlates section will include a review of lesion and neuroimaging studies of language processing to examine anomia and anomia recovery in the acute and chronic stages. The assessment section will highlight how discrepancies in performance between tasks contrasting output modes and input modalities may provide insight into the locus of impairment in anomia. Finally, the treatment section will outline some of the rehabilitation techniques for forms of anomia, and take a closer look at the evidence base for different aspects of treatment.

Neuroscience research is beginning to uncover significant neurobiological impairments in antisocial, violent, and aggressive groups. The neurophysiologic basis of antisocial behavior is complex—many structures have been implicated, each of which may be related to antisocial behavior in different ways. Research in social neuroscience is helping us to better understand the role of many of these regions in normal social behavior, and thus why abnormality would result in a disruption of appropriate social behavior. This chapter highlights neuroscience data on antisocial individuals and provides interpretation based on the knowledge that has been gained in recent years in the field of social neuroscience.

In this chapter, we explore three types of applications of neuroscience to mathematics education: neurounderstanding, neuroprediction, and neurointervention. Neurounderstanding refers to the idea that neuroscience is generating knowledge on how people acquire mathematical skills and how this learning is reflected at the biological level. Such knowledge might yield a better understanding of the typical and atypical development of school-taught mathematical competencies. Neuroprediction deals with the potential of neuroimaging data to predict future mathematical skill acquisition and response to educational interventions. In neurointervention, we discuss how brain imaging data have been used to ground interventions targeted at mathematics learning and how education shapes the neural circuitry that underlies school-taught mathematics. We additionally elaborate on recently developed neurophysiological interventions that have been shown to affect mathematical learning. While these applications offer exciting opportunities for mathematics education, some potential caveats should be considered, which are discussed at the end of this chapter.

In her original Feature Integration Theory, Anne Treisman proposed that we process a limited set of basic preattentive, visual features in parallel across the visual field. Binding those features together into coherent, recognizable objects requires selective attention of item after item. In Treisman’s original conception, searches were divided into parallel feature searches and other serial self-terminating searches. Wolfe’s Guided Search model added the idea that the deployment of attention could be guided by preattentive information. In this view, the efficiency of search is related to the effectiveness of guidance on a continuum from perfect guidance, in the case of simple feature pop-out, to no guidance when no basic features distinguish target from distractors. This chapter reviews the evidence for different basic, preattentive features and describes the current understanding of the rules of guidance, the mechanics of visual search, and the relationship of these processes to visual awareness.

Arthropods are a much-studied group of animals. They include insects, spiders, and hard-shelled invertebrates such as crabs. This chapter reviews four broad topics on the navigational behavior of arthropods. The first is path integration, the ability to keep track of the straight-line distance and direction from one’s starting point. The second is route behavior, in which landmarks figure in various ways. The third is the use of landmarks, both to chart an initial course and to pinpoint a target. The fourth is map-like navigational behavior. The chapter presents an overview including some classic work and current trends and issues.

This chapter reviews studies documenting that nonhuman animals, such as pigeons and monkeys, are capable of learning artificial categories created based on assumptions concerning the structure of natural categories. Competencies of categorization may have evolved to cope with continuities and discontinuities existing in the external world. If so, the cognitive systems of diverse animal species, including humans, should be tied to and constrained by the basic structure of the real world that they have experienced during their evolution. Objects do not occur randomly in the world but are well organized in terms of family resemblances. Family resemblance is information at the category level. For example, AB and CD in the AB-BC-CD category cannot be bound together without BC. However, for organisms to learn a category, it is essential to have not only the family resemblance of the category as a whole, but also information at the exemplar and feature levels. Prototype effects are understood as part of the general processes through which structures of categories are learned.

This chapter reviews major recent findings in Asperger Syndrome (AS), ranging from behavior to neurobiology, and focusing both on social cognitive and executive processes and their interactions. The study of AS benefits from several lines of research on one hand, but on the other hand a lot of controversy remains as to whether the results of individual studies can be generalized to the entire AS population. This obviously highlights the need for further extensive research. But it also demonstrates a very hopeful and intense period for research aiming at: 1) better characterizing the clinical, behavioral, and cognitive phenotypes; 2) building a new conceptual framework through an integrative approach mixing emotional/social cognition and other areas of cognition; and 3) progressively supplanting the localizationism realm by applying recent massive advances in neuroimaging techniques and analysis that explore connectivity and functional interactions in large scale dynamic brain networks.

This chapter reviews the successes and failures of associative theory as an account of causal learning, the most prominent alternative approaches, and a possible reconciliation of these seemingly incompatible perspectives. It argues that causal learning can be constructively viewed as a special instance of associative learning, with constraints that mirror the constraints of some other types of associative learning (e.g., taste aversion). But the question of whether the observed parallels reflect analogy or homology has not yet been settled. Researchers should continue looking for analogies and common principles that would lead to organizing the principles of causal learning as well as other associative phenomena.