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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.

Many psychologists posit that intrinsic motivation generated by personal interest and spontaneous satisfactions is qualitatively different from extrinsic motivation generated by external rewards. However, the contemporary neural understanding of human motivation has been developed almost exclusively based on the neural mechanisms of extrinsic motivation. In neuroscience studies on extrinsic motivation, striatum activity has been consistently observed as the core neural system related to human motivation. Recently, a few studies have started examining the neural system behind intrinsic motivation. Though these studies have found that striatum activity is crucial for the generation of intrinsic motivation, the unique neural basis of intrinsic motivation has not yet been fully identified. I suggest that insular cortex activity, known to be related to intrinsic enjoyment and satisfaction, is a unique neural component of intrinsic motivation. In this chapter, I addressed the theoretical background to and empirical evidence for this postulation.

In light of the growing interest in neuroscience within the managerial and organizational cognition (MOC) scholarly domain at large, this chapter advances current knowledge on core neuroscience methods. It does so by building on the theoretical analysis put forward by Healey and Hodgkinson (2014, 2015), and by offering a thorough – yet accessible – methodological framework for a better understanding of key cognitive and social neuroscience methods. Classifying neuroscience methods based on their degree of resolution, functionality, and anatomical focus, the chapter outlines their features, practicalities, advantages and disadvantages. Specifically, it focuses on functional magnetic resonance imaging, electroencephalography, magnetoencephalography, heart rate variability, and skin conductance response. Equipped with knowledge of these methods, researchers will be able to further their understanding of the potential synergies between management and neuroscience, to better appreciate and evaluate the value of neuroscience methods, and to look at new ways to frame old and new research questions in MOC. The chapter also builds bridges between researchers and practitioners by rebalancing the hype and hopes surrounding the use of neuroscience in management theory and practice.

We reflect upon the histories of the behavioral science and the neuroscience of motivation, taking note of how these increasingly consilient disciplines inform each other. This volume’s chapters illustrate how the field has moved beyond the study of immediate external rewards to the examination of neural mechanisms underlying varied motivational and appetitive states. Exemplifying this trend, we focus on emerging knowledge about intrinsic motivation, linking it with research on both the play and exploratory behaviors of nonhuman animals. We also speculate about large-scale brain networks related to salience processing as a possibly unique component of human intrinsic motivation. We further review emerging studies on neural correlates of basic psychological needs during decision making that are beginning to shine light on the integrative processes that support autonomous functioning. As with the contributions in this volume, such research reflects the increasing iteration between mechanistic studies and contemporary psychological models of human motivation.

Chapter 1 introduces the science of psychophysics to establish the initial condition and expectations for the work. The chapter begins with an overview of psychophysics, its limitations, and its measurement approaches, which are equivalent to the sensation processes. The science of psychophysics is delineated and differentiated from similar fields of study to discriminate it as a science, which is equivalent to the processes of perception. Finally, this information is compiled into a table, which integrates the information into a cognitive model of the nested systems to be discussed (cognition).

In a psychophysical learning system, this chapter establishes the definition of psychophysics, removes irrelevant information from the conceptual framework, and relates the information to future discussions (immediacy), which creates a flow within the learning process.

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.

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.

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.