Search results

Through a review of historically famous cases and a chronicle of neurotechnology development, this chapter discusses brain structure and brain function as two distinct yet interrelated paths to understand the relative contributions of anatomical and physiological mechanisms to the human brain–behavior relationship. From an organizational neuroscience perspective, the chapter describes over a dozen neuroimaging technologies that are classified under four groupings: morphologic, invasive metabolic, noninvasive metabolic, and electromagnetic. We then discuss neuroimaging variables that may be useful in social science investigations, and we underscore electroencephalography as a particularly useful modality for the study of individuals and groups in organizational settings. The chapter concludes by considering emerging science and novel brain technologies for the organizational researcher as we look to the future.

Neuroimaging research has substantially enhanced our understanding of the neurobiological mechanisms of typical and atypical learning in children. These developments can advance the design of novel approaches to diagnosis and intervention for learning disabilities. Despite the promise of educational neuroscience, there are still walls between neuroscience and special education researchers such that more collaboration and understanding are needed between these disciplines. This chapter attempts to break down the walls by discussing how neuroimaging techniques can be incorporated into special education research. We also present arguments as to why neuroscience is “the next big thing” in special education research and the obstacles that must be overcome in order for neuroscience to be incorporated into education research. To describe how neurobiology might impact special education, we focus primarily on reading disability. We believe that educational neuroscience can aid in the identification and intervention of other learning disorders as well.

Decision-making rationality is said to be bounded by managers’ cognitive capabilities. Recent studies indicate that accounting functions evolved to augment the cognitively bounded human brain in handling complex economic exchanges. The neuroscience discipline suggests that human brains have the ability to implement “automatic” processes of positive versus negative emotional stimuli to make rational decisions. Neuroscientific evidence shows that the activations in the ventral striatum decrease with negative emotional information/motives and increase with positive emotional information/motives. The authors, hence, argue that our understanding of the decision-making rationality in financial and managerial decisions could be enhanced by using a functional neuroimaging approach.

Decision-making rationality has been focal in debt covenant violation and earnings management research. The contracting theory predicts a relationship between managers’ decisions and the proximity of violating debt covenants. However, no prior research has investigated brain activities associated with the evaluation of debt covenant violation and earnings management. Meanwhile, in another strand of research, there is an extensive prior literature concerning the consequences of managers’ decisions and the use of accounting information in relation to their evaluative style, i.e., supervisory style. The authors argue that the relationship between the proximity to debt covenants violation and earnings management incentives is contingent upon managers’ supervisory style. However, no previous research has examined the impact of the supervisory style on earnings management in the context of the proximity to debt covenants violation and other earnings management incentives.

In this research note, we argue that neuroaccounting could be relied on to examine the relationship between the proximity to debt covenants and earnings management, contingent upon managers’ supervisory style, by capturing brain activities. The adoption of the neuroscience functional neuroimaging approach in this field should contribute to the understanding of managers’ behaviors and provide implications for research and practitioners. The goal of this research note is to provide a new avenue for future research in this field.

This chapter presents a sociological analysis of the work involved in producing neuroimaging scans used in clinical practice. Drawing on fieldwork in magnetic resonance imaging (MRI) units in hospitals and free-standing imaging centers; in-depth interviews with technologists, radiologists, and neurologists; and reviews of relevant medical literatures, this analysis demonstrates how assembly line techniques structure neuroimaging work. Neuroimages (after being ordered by the referring clinician) are created in an image production line where scans of brains, breasts, livers, and other body parts are all produced: although some facilities may focus on one area of the body, most create an array of scans. Following MRI scans as they are produced demonstrates how medical work emphasizes repetition, specialization, and efficiency – key features of mass production. On the medical assembly line, the organization of work aims to transform patients into objects – ones that multiply as scans are created and circulated. Neurologists, radiologists, and technologists are positioned as skilled workers who manage the flow of bodies and the production of knowledge with the aim of producing health or, at the very least, knowledge of illness. Patients are also actors who actively impact the imaging production process. Previous scholarship has shown that diagnostic work involves a distributed form of expertise; one that involves patients, other medical professionals, machines, and neurologists. This chapter demonstrates that the deployment and synchronization of this expertise is a form of labor, involving distinct professions, professional hierarchies, and reimbursement systems. Working conditions are central to the production of MRI scans as knowledge and contribute to the social shaping of neuroimaging techniques.

For many years it has been speculated that some learning and attention problems in children are related to underlying problems in neurological functioning. In fact, the IDEA (1997) definition of learning disabilities utilizes terminology that specifically includes neurological processes and conditions: Specific learning disabilities means a disorder in one or more of the basic psychological processes involved in understanding or in using language, spoken or written, which may manifest itself in an imperfect ability to listen, think, speak, read, write, spell, or do mathematical calculations. The term includes such conditions as perceptual handicaps, brain injury, minimal brain dysfunction, dyslexia, and developmental aphasia. The term does not include children who have learning problems which are primarily the result of visual, hearing, or motor handicaps, of mental retardation, or of environmental, cultural, or economic disadvantage.This chapter begins with a review of the role of neuroimaging in advancing an understanding of the basis and nature of learning and attention problems. The ever-increasing sophistication of neurodiagnostic technology has made it possible to obtain more precise information about neuroanatomical and neurophysiological bases of behavior, including learning and attention. Advances in technology have greatly increased the ability to study the functioning of the brain during the performance of relatively complex mental activities. With this advanced technology it is becoming increasingly possible to visualize normal and abnormal brain functioning, including important components of basic academic skills. The chapter includes a discussion of the recent evidence about the neurological basis of learning and attention problems.

Purpose – This experimental economics study using brain imaging techniques investigates the risk-ambiguity distinction in relation to the source preference hypothesis (Fox & Tversky, 1995) in which identically distributed risks arising from different sources of uncertainty may engender distinct preferences for the same decision maker, contrary to classical economic thinking. The use of brain imaging enables sharper testing of the implications of different models of decision-making including Chew and Sagi's (2008) axiomatization of source preference.

Methodology/approach – Using fMRI, brain activations were observed when subjects make 48 sequential binary choices among even-chance lotteries based on whether the trailing digits of a number of stock prices at market closing would be odd or even. Subsequently, subjects rate familiarity of the stock symbols.

Findings – When contrasting brain activation from more familiar sources with those from less familiar ones, regions appearing to be more active include the putamen, medial frontal cortex, and superior temporal gyrus. ROI analysis showed that the activation patterns in the familiar–unfamiliar and unfamiliar–familiar contrasts are similar to those in the risk–ambiguity and ambiguity–risk contrasts reported by Hsu et al. (2005). This supports the conjecture that the risk-ambiguity distinction can be subsumed by the source preference hypothesis.

Research limitations/implications – Our odd–even design has the advantage of inducing the same “unambiguous” probability of half for each subject in each binary comparison. Our finding supports the implications of the Chew–Sagi model and rejects models based on global probabilistic sophistication, including rank-dependent models derived from non-additive probabilities, e.g., Choquet expected utility and cumulative prospect theory, as well as those based on multiple priors, e.g., α-maxmin. The finding in Hsu et al. (2005) that orbitofrontal cortex lesion patients display neither ambiguity aversion nor risk aversion offers further support to the Chew–Sagi model. Our finding also supports the Levy et al. (2007) contention of a single valuation system encompassing risk and ambiguity aversion.

Originality/value of chapter – This is the first neuroimaging study of the source preference hypothesis using a design which can discriminate among decision models ranging from risk-based ones to those relying on multiple priors.

Purpose – This chapter provides an overview of the policy implications of neuroscience and argues that research initiatives, individual use, and aggregate social consequences of unfolding knowledge about the brain and the accompanying applications require particularly close scrutiny because of the centrality of the brain to human behavior and thoughts.

Design/methodology/approach – The chapter summarizes the technological context of interventions in the brain and discusses their policy implications. It then examines research findings, principally from neuroimaging studies, that relate to decision making and emotions and looks at their potential impact on frameworks of political decision making.

Findings – Research on brain structure and functioning raises difficult policy issues and necessitates a reevaluation of our assumptions concerning the policy process, itself.

Practical implications – Given the inevitability of expanded strategies for exploration and therapy of the brain and the concerns they raise, it is important that these issues surrounding their application be clarified and debated before such techniques fall into routine use.

Originality/value – The chapter provides original analysis of the policy ramifications of interventions in the brain and neuroscience in general and makes some observations about the brain and society.

The authors speculate only about relatively short-term advances in special education for students with emotional and behavioral disorders. Speculation is confined to the overlapping areas of core values, technologies, neuroscience, and law/policy. In core values, the authors hope to see a resurgence of commitment to special, effective instruction and to practice aligned with scientific evidence. It is hoped that technologies will advance practices in instruction, improve the uses of artificial intelligence in teacher training and teaching, and encourage the appropriate use of artificial reproduction to avoid disorders. Neuroscience, it is hoped, will yield more reliable and helpful classification of disorders, better and more useful imaging, and more effective treatment of a variety of emotional, behavioral, and academic problems. In law and policy, the authors hope the Supreme Court's Endrew case will result in greater focus on challenging, appropriate education. Law and policy should also encourage trauma sensitivity in education, make whole-school approaches to trauma sensitivity the priority, and avoid universal trauma screening. Students' and families' legitimate interests in confidentiality and data privacy should be protected in newly constructed information-sharing infrastructures.

Purpose – This chapter offers an integrative review of psychological and neurobiological differences between younger and older adults that might impact economic behavior. Focusing on key health economic challenges facing the elderly, it offers perspectives on how these psychological and neurobiological factors may influence decision-making over the life course and considers future interdisciplinary research directions.

Methodology/approach – We review relevant literature from three domains that are essential for developing a comprehensive science of decision-making and economic behavior in aging (psychology, neuroscience, and economics), consider implications for prescription drug coverage and long-term care (LTC) insurance, and highlight future research directions.

Findings – Older adults face many complex economic decisions that directly affect their health and well-being, including LTC insurance, prescription drug plans, and end of life care. Economic research suggests that many older Americans are not making cost-effective and economically rational decisions. While economic models provide insight into some of the financial incentives associated with these decisions, they typically do not consider the roles of cognition and affect in decision-making. Research has established that older age is associated with predictable declines in many cognitive functions and evidence is accumulating that distinct social motives and affect-processing profiles emerge in older age. It is unknown how these age differences impact the economic behaviors of older people and implies opportunities for path-breaking interdisciplinary research.

Originality/value of the chapter – Our chapter looks to develop interdisciplinary research to better understand the causes and consequences of age-related changes in economic decision-making and guide interventions to improve public programs and overall social welfare.

This chapter introduces electroencephalography (EEG), a measure of neurophysiological activity, as a critical method for investigating individual and team decision-making and cognition. EEG is a useful tool for expanding the theoretical and research horizons in organizational cognitive neuroscience, with a lower financial cost and higher portability than other neuroimaging methods (e.g., functional magnetic resonance imaging). This chapter briefly reviews past work that has applied cognitive neuroscience methods to investigate cognitive processes and outcomes. The focus is on describing contemporary EEG measures that reflect individual cognition and compare them to complementary measures in the field of psychology and management. The authors discuss how neurobiological measures of cognition relate to and may predict both individual cognitive performance and team cognitive performance (decision-making). This chapter aims to assist scholars in the field of managerial and organizational cognition in understanding the complementarity between psychological and neurophysiological methods, and how they may be combined to develop new hypotheses in the intersection of these research fields.