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The comprehensive approach of studying nonverbal behavior is exemplified best in observational studies assessing dyadic interaction in intimate relationships, such as between couples and parents with their children. The study of couple and parent–child relationships within the family are important because they are some of the most influential and defining relationships human establish in people–s lives. This chapter focuses on various nonverbal behavioral coding systems used in the laboratory when studying committed relationships. Various coding system such as Specific Affect Coding System (SPAFF), Triadic Interaction Coding System (TICS), and psychophysiological assessment were used in this study. The discussion of each coding system is organized into sections providing information about the background and evolution of these coding systems, equipment required to implement these systems into the laboratory used for this study, guidelines for training, some significant findings as a result of the implementation of these coding systems, and some recommendations for future research.

Philip Gerrans first explains the “predictive coding conception of cognition” which treats the mind as a hierarchy of cognitive systems devoted to the cancellation of error signals. Although the deep consequences of this theory for understanding consciousness have not been fully explored, Andy Clark has suggested that the logical consequence of the predictive coding view is that intuitive distinctions between higher and lower level cognitive systems need to be rethought. This suggests that conscious experience itself produced by very low level sensory and perceptual processes should be at the mercy of beliefs, since those beliefs can ultimately cancel the prediction errors generated by those systems. Gerrans explores this idea in the context of explanations of the “sense of agency,” the phenomenologically-elusive experience of being the agent of an action. Much of the relevant data comes from the study of schizophrenic delusions of alien control that use predictive coding models to explain the role of correlated neural activation. Garrans argues that the sense of agency is not as vulnerable to context effects as Clark and others have argued.

This chapter attempts to illuminate some of the mechanisms that gave rise to doubts that facial expression and affective experience are highly interrelated. Generally, the idea advanced is that low correlations should not inevitably be interpreted as nonconsistent response patterns or as evidence of a behavior-experience discrepancy. It is argued that the approach used to compute the correlations constitutes the major neglected factor: even for a given data set it produces systematic variations in the size of the coefficients to be obtained. The analyses show that it is not justified to conclude that the different elements of exhilaration behavior are correlated with judged funniness to different extents, despite the fact that the uncorrected coefficients suggested such an interpretation. The data presented is reprinted humor research that shows that the application of highly sophisticated assessment tools, like the Facial Action Coding System (FACS), generally boosts the size of the coefficients, and even the least favorable Design A yields a coefficient of .65 in the control group.

This chapter measures more subtle aspects of facial expression, distinguishing among different types of smiling. It also reports the findings from the first use of the Facial Action Coding System (FACS) to measure facial expressions when people deliberately lie. There were different types of smiles distinguished. The deception scenario was relevant to emotion, whereas most of the scenarios used by prior investigators were not. It is shown that smiles should no longer be considered a single category of behavior. Masking smiles would not always be the type of facial behavior that would betray a lie.

This chapter presents a study that implemented the first version of an automated method of face analysis and assessed its concurrent validity with manual Facial Action Coding System (FACS) coding. Discriminant function analyses are performed on the feature point measurements for action units in brow, eye, and mouth regions. The automated face analysis by feature point tracking demonstrated high concurrent validity with manual FACS coding. The work regarding the behavioral and computer scientists is presented in order to develop and apply a computer-vision-based approach, the CMU/Pitt Automated Facial Image Analysis (AFA) System, to these aspects of facial expression. A summary of the progress with AFA in the recognition and analysis of facial action units and emergent applications to problems in emotion theory and clinical practice is also given.

This chapter presents an approach for developing a fully automatic Facial Action Coding System (FACS). The approach uses state-of-the-art machine learning techniques that can be applied to recognition of any facial action. The results of Study I provided guidance as to which image representations, or feature extraction methods, are most effective for facial action recognition. Gabor wavelets and Independent Component Analysis gave best performance. Study II found that machine learning techniques applied directly to the warped images is a promising approach for automatic coding of spontaneous facial expressions. Generally, the data employed hand-labeled feature points for the head pose tracking step. Furthermore, three of the issues are discussed in detail: (1) collection of a database of spontaneous facial expressions, (2) fully automatic face detection and tracking, and (3) fully automatic 3D head pose estimation.

This chapter evaluates the potential of visible facial behavior in studies of affective disorders. Despite the limits in the samples studied, the results should encourage clinical investigators to consider measuring facial expressions. At the very least, the data argue for repeating these studies with larger samples and better measures of clinical improvement and psychopathology. Results also showed that facial measures may be of use also in distinguishing subgroups among patients who share the same diagnosis. An article regarding depression and expression is presented. It reports the only evidence on the relationship between the Facial Action Coding System (FACS) and emotion FACS (EMFACS) scoring.

This chapter presents a new approach to the microanalytic study of cognitive-affective regulatory processes in psychotherapeutic interaction. In this approach, the examination of the expressive component of emotions communicated through facial expressions is of central importance. The question as to whether comparable prototypical affective microsequences also occur in therapies and what role they play in affective regulation is specifically examined. So far, the observations made suggest that the enacted object relation structures do not all show the same temporal characteristics but that certain processes need longer time periods. Considering the present state of research, it seems useful to interpret Facial Action Coding System (FACS) data not only with the emotion prediction tables but also taking the situative context, especially the interactive and the temporal aspects, into consideration.

This chapter uses Facial Action Coding System (FACS) to examine the impact of smoking opportunity in a study that addressed some of the limitations of the Sayette and Hufford (1995) study. It also investigates the extent to which two predetermined clusters of action units (AUs) would appear during smoking cue exposure. results of Experiment 1 revealed that smoking opportunity influenced self-reported urge prior to smoking cue exposure. The data that abstinent smokers were more likely to express positive AUs than were nonabstinent smokers during smoking cue exposure replicates the pattern found in the initial study (Sayette & Hufford, 1995). Data from Experiment 2 suggests further that urge ratings may be influenced not only by whether one expects to smoke, but also by when one expects to smoke. Results also indicated that under certain conditions (i.e., 15-sec), craving may be linked to positive affect. Thus, both of these experiments highlight the role that impatience can play in craving. The use of FACS to identify Contextual Factors Influencing Craving is also discussed.

This collection of articles vividly illustrates how rich and diverse is the information that can be obtained by measuring facial behavior. A methodological issue that should be of concern to all Facial Action Coding System (FACS) users, new and old, is considered. Next, the substantive matters raised by the basic research chapters, and then the substantive issues raised by the applied research chapters, are addressed. It specifically discusses the issues about FACS scoring. There can be no single conclusion from this set of very interesting studies, beyond the very simple and dramatically illustrated fact that measurement of facial behavior reveals unique and important information about a wide variety of psychological phenomena.

The goals of this chapter is to present a rationale and methodology for closely examining emotional expression and verbal narratives from videotape of group therapy sessions. Empirical evidence about the role of emotional expression in breast cancer survival provides a justification for the careful study this chapter is based upon. A general discussion of behavioral research on group therapy and the rationale and hypotheses that have generated this particular study of emotion in breast cancer support groups is presented. The chapter describes the methodology for coding these naturally occurring groups, to present some sample data from the work, and to offer the emotion coding and verbal narrative definitions. The use of Specific Affect Coding System (SPAFF) has allowed the study to code specific emotion categories across a wide range of natural behavior and emotions. This study has also used the James Long System (JLC) which has allowed for continuous data at the frame by frame level of analysis to be sampled.

Large-scale systems are hierarchically organized to manage their complexity. Silicon computing makes extensive use of hierarchies but computational models of the brain have tended to sidestep hierarchical organization. The central premise of the book is that the brain can be seen as an ordered layered system of hierarchical organization. Higher levels of abstraction provide economical descriptions cognitive problems that can be searched quickly as lower levels handle important bookkeeping details. Within the benefits of such an organization, the slowness of the neural circuitry is still a formidable enterprise. The brain’s principle computational tricks are introduced. Finally the adequacy of the computational enterprise itself is touched upon.

All neurons have characteristic spike generation methods, but at the circuit level they are combined in many different ways. The slowness of the neural spike generation process suggests that standard models of cortical firing may be inadequate to describe the computational process, particularly for the issue of multiplexing. A first impression of the forebrain’s networks, particularly in its Cortical subsystem, suggests that it might be difficult to realize multiple independent neural computations since all the circuitry is interconnected in explicit ways such that any factorization is not obvious. Nonetheless from a practical computational viewpoint, it would seem that multiple, separate computations that share the common circuitry must be allowed. A representative radical approach is described achieves this independence.

This chapter examines the idea that bilingual proficiency is internally diverse—that is, componential. It shows that the proposed modification to Cummins’s Common Underlying Proficiency Model needs some modification itself and considers Paivio’s Bilingual Dual Coding Model as well as M. Paradis’s Three-Store Hypothesis. It also discusses why one language subsystem does not appear to affect another in certain cases, but prolific interaction seems to occur in other cases. Furthermore, it looks at how language combining and mixing are accomplished in a grammatically systematic way, how language and general cognition appear to be interdependent, maximum imbalance in bilingualism, how bilingual speech constitutes evidence of language separation, and borrowing and codeswitching. Finally, the chapter proposes a model of how two languages are represented in the bilingual, based on an extension of Jackendoff’s Tripartite Parallel Architecture.

This chapter focuses on explaining the main assumptions of the Theory of Event Coding, which is given such prominence because it is the most significant ideomotor approach. The chapter emphasizes the most significant theoretical issues that need to be addressed to verify the approach, examining whether agents acquire action–effect relationships as suggested by the theory and whether these agents are able to predict the perceptual effects as claimed in the theory. It also examines whether these predictions have any control over the action and which aspects of actions are controlled by these predictions, along with the implications of theory and related processes for representing the agent’s self.

Chapter 3 turns from this corporate model for writing to those that embrace a more literary understanding. I begin by looking at two films that represent programming—the 1957 romantic comedy Desk Set and the 2010 film The Social Network. Where films in the past treated computers as monoliths dropped into social spaces, this later film represents programming as a form of writing. Today the lines between programming and writing are blurry, since most writing for the Web depends on markup language that contains coding. Some have argued that we would be better to treat the act of writing code as a literary activity. All in all, the professions of writing and programming have evolved to form an essential part of what has been called the “creative economy” by Richard Florida. These ideas about writing and computing are articulated in Neal Stephenson’s open-source manifesto In the Beginning … Was the Command Line. Stephenson contrasts the graphical user interface (GUI) to the textual command line. Stephenson reveals the common belief that the writing embodied in the command line or in coding represents a more fundamental layer of the computer.

The ways in which people have distinguished between Strauss’s and Glaser’s stances on GTM; with the author’s own account. Later forms of coding, and the ways in which Strauss and Corbin, and Glaser sought to offer guidance for researchers. Kelle’s argument that both were trying in theor own ways to assist researchers in generating genuine categories. Charmaz’s advice to find a balance between ‘application’ and ‘emergence’. Bryant’s experience with numerous PhD students that they find their own ways around this, usually without recourse to Glaser’s coding families, or to Struass and Corbin’s coding paradigm.The problems of classification—Jorge Luis Borges and the fictional Chinese Encyclopaedia. Later stages of coding and categorizing. Examples of several PhD students’ different paths through GTM research; use of diagrams, cognitive maps, and situational maps. Research strategies as Situated Actions (based on the work of Lucy Suchman).

Detailed accounts taken from recent PhD students’ work based on Kathy Charmaz’s advice in her “Code for coding.” The chapter introduces the issue of translating as a form of coding very different from GTM coding—i.e. when the data is in one language but the research has to be reported in another one. It also explores the role of graphical and diagrammatic presentations in reporting GTM results and findings. The answers to six common questions arising in GTM-oriented research are intended to aid novice researchers, who typically ask: What do I code? When do I start coding? How will I know if my coding is working? How will I cope with all my codes? What about using technology? What’s the difference between line-by-line, word-by-word, and incident-by-incident coding?