bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multisensory Perception
Authors: Spence Charles 
Published: April 2018

AbstractThere has been a huge growth of interest in the topic of multisensory perception over the past half century. The majority of this research has focused on the spatial senses of vision, audition, and touch. Multisensory interactions would appear to be the norm, not the exception. Cross‐modal interactions (which include examples of multisensory integration) are influenced by stimulus timing. Interactions between the senses tend to be maximal when the component stimuli fall within the temporal window of integration that is approximately centered on simultaneity. Spatial coincidence between component stimuli modulates multisensory integration only under conditions of target location uncertainty and/or when space is somehow relevant to the participant's task. Bayesian decision theory has largely replaced previous accounts of why the senses interact in quite the way that they do, and can explain why one sense often dominates over the others. The study of interactions between the senses is now a core component of research into perception both in humans and increasingly in other species as well.
Perception and Interactive Technology
Authors: Scheller Meike , Petrini Karin , Proulx Michael J. 
Published: April 2018

Abstract“What does it mean, to see?” was the question that David Marr used to motivate his computation approach to understandingVision(Marr, 1982). Marr's answer, building on Aristotle, was that “vision is the process of discovering from images what is present in the world, and where it is” (p. 3). Although we humans might have a preference for visual perception, we are endowed with other senses that provide us with a rich experience (Chapter 14, this volume). Therefore the broader question might be: What does it mean, to perceive? Although this might be seen as a philosophical question of sorts, it gets to the important issue of how we define perceptual experience scientifically so that we may study it. The importance of defining it is crucial for research applications: If we aim to restore a sense such as vision in blindness or hearing in deafness, what does it mean to see or to hear such that we will know when restoration has been successful? This chapter reviews the interaction between multisensory perception and interactive technological approaches to sensory rehabilitation.
Perceptual Learning
Authors: Green C. Shawn , Banai Karen , Lu Zhong‐Lin , Bavelier Daphne 
Published: April 2018

AbstractPerceptual learning refers to a long‐term change in the ability to extract perceptual information from the environment that arises via experience or practice. In this chapter, we first explore many examples of perceptual learning in relatively simple as well as in more complex tasks. Furthermore, we do so across sensory modalities (vision, audition, touch, taste, smell) with the goal of highlighting the commonalities seen in perceptual learning across systems that are typically considered separately. We then consider the most substantial issues in the domain, including the question of learning specificity (i.e., when do improvements on one task transfer to new unpracticed tasks?), the conditions under which learning occurs, the neural basis of perceptual learning, computational models of perceptual learning, and potential real‐world applications of perceptual learning. We conclude with future directions; although the field has clearly made tremendous progress over the past century or more, there remain critical gaps in our knowledge that preclude our ability to fully harness perceptual learning to make a real‐world impact.
Dynamic Sensory‐Motor Adaptation to Earth Gravity
Authors: Lackner James R. , DiZio Paul 
Published: April 2018

AbstractGravity is such a constant environmental influence on spatial orientation and movement that the active CNS adaptations to it are easily underestimated, and they are best revealed when the background force conditions are altered. This chapter reviews illusions and movement errors that occur in hypo‐ and hypergravity environments as well as in a rotating artificial gravity environment where additional novel dynamic Coriolis forces are present. The phenomena reviewed reveal the importance of tactile cues from contact forces on the body surface and proprioceptive cues from muscle spindle and tendon receptor loading that are usually perceptually inaccessible, in addition to the vestibular cues that traditionally receive consideration. The role of these touch, pressure, and kinesthetic cues in visual and auditory localization, body schema, motor coordination, and learning of simple reaching movements to complex postural balancing are discussed.
Word Processing
Authors: Cai Zhenguang G. , Vigliocco Gabriella 
Published: April 2018

AbstractThis chapter reviews theories and empirical research on how humans retrieve meaning from speech or text. We first review research concerning how word meanings are represented. Here theories are divided between embodiment accounts proposing that word meanings are grounded in sensorimotor systems, and distributional semantics accounts proposing that meanings can be viewed as inter‐word distributional relations. We argue that these two approaches deal with different aspects of word meanings and should be integrated. For meaning retrieval, we discuss previous research showing that both meaning dominance and prior context determine the access and retrieval of meanings. We also discuss how the selected and unselected meanings may be later suppressed and re‐instantiated. Finally, we propose that prior, concurrent, or subsequent contexts—situated in the framework of inferential/predictive language processing—play different roles in word processing. Prior context constitutes the prior knowledge that sets the stage for word recognition and meaning retrieval, concurrent context constrains the recognition of the word/meaning, and subsequent context updates lexico‐semantic knowledge against recent experience. We propose that future research should investigate words in their natural habitat of contextualized and multimodal language communication.
Discourse and Dialogue
Authors: Brennan Susan E. , Kuhlen Anna K. , Charoy Jeanne 
Published: April 2018

AbstractLanguage use is inherently social; discourse and dialogue unfold in social contexts. This chapter presents an introduction to the cognitive science of discourse and dialogue, from an interdisciplinary perspective that includes experimental psycholinguistics, sociolinguistics, artificial intelligence, human–machine interaction, and neuroscience. Two dominant experimental traditions, language‐as‐product and language‐as‐action, are discussed, and some classic issues, findings, and theories in discourse processing are presented. Topics surveyed include information packaging, referential communication, achieving joint meanings in dialogue, models of discourse and dialogue structure, audience design and partner‐specific processing, and the neural bases of discourse and dialogue. Evidence from experiments and examples from communicative contexts are presented that shed light on how people plan, interpret, and coordinate language within dialogue. The research presented here holds implications for writing for better comprehension, improving robustness in human interaction with spoken dialogue systems, and understanding the neural processing of language during communication.
Reading
Authors: Carreiras Manuel , Armstrong Blair C. , Duñabeitia Jon Andoni 
Published: April 2018

AbstractCommunication via written words is one of humanity's greatest inventions and plays a critical role in modern society. This chapter outlines the key cognitive, neural, and computational aspects of the reading system. In so doing, it shows how reading takes advantage of domain‐general processing abilities and bootstraps written communication from other neurocomputational systems, including vision and spoken language processing. It also explains how failure in different parts of the reading system can lead to reading disorders such as dyslexia. Furthermore, emerging trends reveal exciting new directions for reading research, including advancing the understanding of how the brain changes as a function of learning to read, how the brain adapts to process different languages, and how to formalize our understanding of reading in more biologically plausible models. This chapter thus outlines how an interdisciplinary perspective to understanding reading has and will continue to advance our understanding of reading in ways that are critical for both fundamental and applied aims.
Bilingualism
Authors: Kroll Judith F. , Navarro‐Torres Christian A. 
Published: April 2018

AbstractBilingualism is a tool that provides cognitive and language scientists with a means to investigate the interactions between language and cognition that would otherwise be impenetrable in the minds and brains of monolingual speakers. In this chapter we review the highlights of the recent research on the consequences of bilingualism for language processing, for cognition, and for the neural processes that support them. Contrary to the view that monolinguals are the norm and bilinguals the exception, the new research takes the bilingual, not as a more complex language user, but as a model for the plasticity of the systems associated with language development and language use. We describe three models of bilingual processing that provide an historical framework for research on this topic. We then review the evidence for the parallel activation of the bilingual's two languages and its consequences for language, cognition, and the brain.
Creativity
Authors: Chrysikou Evangelia G. 
Published: April 2018

AbstractThe purpose of this chapter is to provide an overview of some key background issues and recent trends in the experimental and cognitive neuroscience study of creativity. Despite its status as a hallmark of higher order thinking, research on creativity has not progressed with the same rigor as the study of other aspects of human cognition. Among the challenges for creativity researchers are concerns with the operational definition and measurement of this seemingly elusive ability. Research on the neurocognitive bases of creative thinking suggests that creativity is highly multifaceted and requires intricate interhemispheric interactions among a widely distributed network of brain regions. Recent theoretical and methodological perspectives highlight the importance of moving away from approaching creativity as a unitary construct, synonymous to the abstract concept of divergent thinking. Instead, they focus on specific cognitive and neural processes underlying creative thought, which may rely on trade‐offs between spontaneous and regulatory brain networks.
Language Acquisition
Authors: Lidz Jeffrey , Perkins Laurel 
Published: April 2018

AbstractLanguage acquisition provides a new window into the rich structure of the human language faculty and explains how it develops in interaction with its environment and the rest of human cognition. This chapter discusses how children learn the phonology of their language and solve the problem of word segmentation. It explains how children learn the grammatical categories of words in their language as well as some semantic and syntactic properties associated with those categories. The chapter discusses a strategy called semantic bootstrapping that could help children learn the grammatical categories of some words based on the types of meanings those words have. It considers the acquisition of constraints on pronoun interpretation and on quantifier scope. Learning which words belong to which grammatical categories is another problem that children need to solve when learning their lexicon.
Development of Episodic Memory: Processes and Implications
Authors: Coughlin Christine , Leckey Sarah , Ghetti Simona 
Published: April 2018

AbstractThis chapter provides an account of the development of episodic memory. The contributions of binding and control processes to gains within each developmental period (infancy, childhood, and adolescence) are discussed. Structural and functional changes within the hippocampus and prefrontal cortex are also highlighted, providing an overview of age‐related changes in critical neural areas. Finally, the functional consequences of the protracted developmental trajectory of episodic memory are discussed, with special consideration given to the influence of episodic memory on future event imagination and learning.
Development of Mathematical Reasoning
Authors: Iuculano Teresa , Menon Vinod 
Published: April 2018

AbstractMathematical cognition provides a foundation for the development of skills critical for success in the 21st century. The use of mathematics to categorize, visualize, and manipulate information now extends to virtually all domains of human activity, making the necessity for basic mathematical skills more pressing than ever. This chapter summarizes current knowledge about the developmental and neurocognitive basis of mathematical reasoning. We review central cognitive theories and summarize emerging findings on the perceptual and cognitive building blocks of numerical cognition, the functional brain circuits associated with them, and the multiple memory and cognitive‐control systems that play a critical role in scaffolding children's mathematical skill development. We highlight neurodevelopmental models and functional brain circuits that go beyond individual regions involved in number processing and demonstrate that brain systems and circuits engaged by the developing brain are not the same as those engaged in adult brains sculpted by years of learning.
Emotion Development from an Experimental and Individual Differences Lens
Authors: Pérez‐Edgar Koraly , Hastings Paul 
Published: April 2018

AbstractThis chapter reviews the historical and empirical forces that have shaped the study of emotional development within the broader field of developmental psychology. Our central argument is that a broader methodological base is needed in order to best capture complex patterns of affect across context and time. In particular, the use of both naturalistic observations and experimental methods allows us to capture and explain patterns of development that are both possible and probable. In addition, the systematic inclusion of individual differences will move us away from the difficult task of trying to capture the elusive “average child.” This strategy may improve our understanding of emotion development and advance our overarching goal of improving the robustness of our science.
Attitudes
Authors: Bengal Steven T. , Gretton Jeremy D. , Wegener Duane T. 
Published: April 2018

AbstractAttitudes are evaluations of objects in one's intrapsychic or social environment. These evaluations play a key role in perception, thinking, and behavior. As such, attitudes are directly relevant to virtually any realm in which human behavior plays a key role. In this chapter, we discuss the thriving research literature on attitudes and attitude change, linking current theories and questions to the history of related work that extends back to the early 1900s. In so doing, we also link current and previous research questions to the cognitive, metacognitive, affective, and neuroscientific questions that have contributed to the field's current understanding of attitude‐related phenomena.
Implicit Social Cognition
Authors: Hahn Adam , Gawronski Bertram 
Published: April 2018

AbstractThis chapter provides an overview of theories, methods, key findings, and controversies in research on implicit social cognition. We start by introducing the conceptual origins of implicit social cognition, definitions of the term “implicit,” and the most important measurement instruments. We further review research on dissociations between implicit and explicit measures, the prediction of behavior, and factors that cause systematic variation on implicit measures (formation and change of mental representations, context effects). In the last part of the chapter, we discuss common questions and ongoing controversies in implicit social cognition and provide an outlook on future research. Together, this chapter provides an overview of the current status of research on implicit social cognition.
Bayesian Methods in Cognitive Modeling
Authors: Lee Michael D. 
Published: April 2018

AbstractBayesian statistical methods provide a flexible and principled framework for relating cognitive models to behavioral data. They allow for cognitive models to be formalized, evaluated, and applied, supporting inferences about parameters, the testing of models, and making predictions about data. This chapter argues that Bayesian methods are most useful for cognitive modeling in allowing more ambitious accounts of cognition to be considered, including models that include hierarchical, latent‐mixture, or common‐cause structures. These theoretical possibilities, and the practical mechanics of using Bayesian methods implemented as graphical models, are demonstrated by means of an extended case study involving psychophysical models of the perception of duration for auditory and visual stimuli. The case study demonstrates a number of general features of the Bayesian approach—representing uncertainty, being sensitive to model complexity, dealing with contaminants, allowing for individual differences, making predictions and generalizations, and so on—while emphasizing the role of informative prior distributions to capture theoretical assumptions about cognitive variables and the complementary roles of parameter inference and model testing in answering research questions.
Statistical Inference
Authors: Morey Richard D. 
Published: April 2018

AbstractStatistical inference has grown to be an indispensable tool for scientists seeking to make sense of data. This chapter describes three approaches for a large majority of statistical inferences drawn in the scientific literature which includes: frequentist approaches, likelihood approaches, and Bayesian approaches. Typical approaches to frequentist hypothesis testing use a principle of evidence involving decision error rates. The sampling distribution of a test statistic assuming that the null hypothesis is true will depend on known factors. The Bayesian approach to statistical inference is concerned with drawing rational inference from a sample, where rational is defined by an application of Bayes' theorem to formalized beliefs about a parameter or other unknown quantity. The likelihood approach in statistical inference is characterized by a particular viewpoint: The evidence in the data regarding parameters can be found in the likelihood function L. The likelihood function is the probability mass or density function viewed as a function of unknown parameters for fixed, observed data.
Elementary Signal Detection and Threshold Theory
Authors: Kellen David , Klauer Karl Christoph 
Published: April 2018

AbstractSignal detection and threshold model classes are important measurement tools that disentangle the contribution of different factors such as discriminability and response/guessing‐bias based on observed categorical responses. This chapter provides an introduction to both model classes by discussing their theoretical foundations and different measures that can be derived from them. Measures and tests are exemplified with previously published data from the fields of perception and memory.
Methods in Psychophysics
Authors: Wichmann Felix A. , Jäkel Frank 
Published: April 2018

AbstractTypically researchers in psychology are interested in substantive issues about the mind—how we see, hear, categorize, or reason about the world. To answer the multitude of yet unanswered substantive questions about the mind, one typically conducts experiments to collect data, analyzes the data obtained, and then interprets them in the context of current theories and models. Here we look at some of the aspects of the first two steps, the collection and analysis of behavioral data from psychophysical experiments. We concentrate on the various experimental designs for experiments of thethresholdorjust noticeable difference(JND) type. Subsequent to data acquistion, we suggest to use Bayesian inference to estimate the psychometric function of a beta‐binomial model as the default data analysis if there is a single independent variable. For multidimensional data and exploratory data analyses, we briefly introduce multidimensional psychometric function estimation techniques, making use of regularization techniques from machine learning. We conclude our chapter with a discussion of the timeliness of the two commandments of psychophysics:Know thy stimulusby Wilson Geisler andThou shalt not be lazy (when gathering data), which we attribute to Karl Dallenbach.
Response Times and Decision‐Making
Authors: Donkin Christopher , Brown Scott D. 
Published: April 2018

AbstractResponse times have been very informative for the understanding of mental processes, for many years. The most useful analyses of response times have been those based on cognitive theories of decision making, known as evidence accumulation models. We review the history of decision‐making models, and the empirical phenomena that have guided their development. We focus particularly on the common elements of the models, as they represent theoretical agreement about the most fundamental elements of decision‐making theory. We also review the practical usage of evidence accumulation models as data‐analysis tools, with a discussion of the strengths and weaknesses of this popular approach. While popular, model‐based analysis of response time data can be challenging, and so we review developments that make those analyses easier, and also discuss common approaches to the most common problems in plotting, parameter estimation, and model selection.
The Stop‐Signal Paradigm
Authors: Matzke Dora , Verbruggen Frederick , Logan Gordon D. 
Published: April 2018

AbstractResponse inhibition—the ability to stop responses that are no longer appropriate—is frequently studied with the stop‐signal paradigm. In the stop‐signal paradigm, participants perform a choice response time task that is occasionally interrupted by a stop signal. The stop signal prompts participants to withhold their response on that trial. Performance in the stop‐signal paradigm is typically formalized as a horse race between a go and a stop process. If the go process wins the race, the response in executed; if the stop process wins the race, the response is inhibited. The stop‐signal paradigm owes its popularity to the underlying horse‐race model that enables researchers to estimate the latency of the unobservable stop response. In this chapter, we present a theoretical review of the stop‐signal paradigm and the corresponding horse‐race model. First we focus on the standard independent horse‐race model and discuss the most important measures of inhibitory control in the stop‐signal paradigm. We then describe the latest developments in the model‐based analysis of stop‐signal data. We conclude the chapter with recommendations on how to run stop‐signal experiments and how to report and interpret the results of stop‐signal studies.
Neural Recordings at Multiple Scales
Authors: Maier Alexander , Schall Jeffrey D. , Woodman Geoffrey F. 
Published: April 2018

AbstractThis chapter surveys the acquisition, analysis, and interpretation of neural activity recorded as spikes from single neurons or from populations of neurons and as the local voltage fluctuations derived from synaptic potentials. It also considers how these measures relate to those obtained from outside the brain through the electroencephalogram or from energy and oxygen utilization through functional magnetic resonance imaging.