Psychological construction represents an important new approach to psychological phenomena, one that has the promise to help us reconceptualize the mind both as a behavioral and as a biological system. It has so far been developed in the greatest detail for emotion, but it has important implications for how researchers approach other mental phenomena such as reasoning, memory, and language use. Its key contention is that phenomena that are characterized in (folk) psychological vocabulary are not themselves basic features of the (...) mind, but are constructed from more basic psychological operations. The framework of mechanistic explanation, currently under development in philosophy of science, can provide a useful perspective on the psychological construction approach. A central insight of the mechanistic account of explanation is that biological and psychological phenomena result from mechanisms in which component parts and operations do not individually exhibit the phenomena of interest but function together in an orchestrated and sometimes in a complex dynamical manner to generate it. While at times acknowledging the compatibility of the mechanist approach with constructionist approach (Lindquist, Wager, Kober, Bliss-Moreau, & Barrett, 2012), proponents of the constructionist approach have at other times pitched their approach as anti-mechanist. For example, Barrett (2009) claims that the psychological constructionist approach rejects machines as the primary metaphor for understanding the mind, instead favoring a recipe metaphor; constructionism also purportedly rejects the “mechanistic” picture of causation, which it portrays as linear or sequential in nature (see also Barrett, Wilson-Mendenhall, & Barsalou, in press). While some mechanistic accounts do fit this description, we will see that the mechanisms generating phenomena can be complex and dynamic, producing phenomena far less stereotypic and more adaptive than people often associate with machines. Our goal, however, is not just to render constructionism and mechanism compatible. Philosophers of science have been examining the nature of mechanistic explanation in biology with the goal of gaining new insights into the operation of science. We will identify some of the places where the mechanistic account can shed new light on the constructionist project. (shrink)

InThe Cognitive-Emotional Brain(Pessoa 2013), I describe the many ways that emotion and cognition interact and are integrated in the brain. The book summarizes five areas of research that support this integrative view and makes four arguments to organize each area. (1) Based on rodent and human data, I propose that the amygdala's functions go beyond emotion as traditionally conceived. Furthermore, the processing of emotion-laden information is capacity limited, thus not independent of attention and awareness. (2) Cognitive-emotional interactions in the human (...) prefrontal cortex (PFC) assume diverse forms and are not limited to mutual suppression. Particularly, the lateral PFC is a focal point for cognitive-emotional interactions. (3) Interactions between motivation and cognition can be seen across a range of perceptual and cognitive tasks. Motivation shapes behavior in specific ways – for example, by reducing response conflict or via selective effects on working memory. Traditional accounts, by contrast, typically describe motivation as a global activation independent of particular control demands. (4) Perception and cognition are directly influenced by information with affective or motivational content in powerful ways. A dual competition model outlines a framework for such interactions at the perceptual and executive levels. A specific neural architecture is proposed that embeds emotional and motivational signals into perception and cognition through multiple channels. (5) A network perspective should supplant the strategy of understanding the brain in terms of individual regions. More broadly, in a network view of brain architecture, “emotion” and “cognition” may be used as labels of certain behaviors, but will not map cleanly into compartmentalized pieces of the brain. (shrink)

Neural reuse is a form of neuroplasticity whereby neural elements originally developed for one purpose are put to multiple uses. A diverse behavioral repertoire is achieved by means of the creation of multiple, nested, and overlapping neural coalitions, in which each neural element is a member of multiple different coalitions and cooperates with a different set of partners at different times. Neural reuse has profound implications for how we think about our continuity with other species, for how we understand the (...) similarities and differences between psychological processes, and for how best to pursue a unified science of the mind.After Phrenology: Neural Reuse and the Interactive Brain(2014; henceforthAfter Phrenologyin this Précis) surveys the terrain and advocates for a series of reforms in psychology and cognitive neuroscience. The book argues that, among other things, we should capture brain function in a multidimensional manner, develop a new, action-oriented vocabulary for psychology, and recognize that higher-order cognitive processes are built from complex configurations of already evolved circuitry. (shrink)

Characterizing how activity in the central and autonomic nervous systems corresponds to distinct emotional states is one of the central goals of affective neuroscience. Despite the ease with which individuals label their own experiences, identifying specific autonomic and neural markers of emotions remains a challenge. Here we explore how multivariate pattern classification approaches offer an advantageous framework for identifying emotion-specific biomarkers and for testing predictions of theoretical models of emotion. Based on initial studies using multivariate pattern classification, we suggest that (...) central and autonomic nervous system activity can be reliably decoded into distinct emotional states. Finally, we consider future directions in applying pattern classification to understand the nature of emotion in the nervous system. (shrink)

Classical theories of emotion have long debated the extent to which human emotion is a universal or culturally constructed experience. Recent advances in emotion research in cultural neuroscience highlight several aspects of emotional generation and experience that are both phylogenetically conserved as well as constructed within human cultural contexts. This review highlights theories and methods from cultural neuroscience that examine how cultural and biological processes shape emotional generation, experience, and regulation across multiple time scales. Recent advances in the neurobiological basis (...) of culture-bound syndromes, such as Hwa-Byung (fire illness), provide further novel insights into emotion and mental health across cultures. Implications for emotion research in cultural neuroscience for population health disparities in psychopathology and global mental health will be discussed. (shrink)

According to the conceptual act theory, emotions emerge when physical sensations in the self and physical actions in others are meaningfully linked to situations during a process that can be called both cognitive and perceptual (creating emotional experiences, and emotion perceptions, respectively). There are key four hypotheses: (a) an emotion (like anger) is a conceptual category, populated with instances that are tailored to the environment; (b) each instance of emotion is constructed within the brain’s functional architecture of domain-general core systems; (...) (c) the workings of each system must be holistically understood within the momentary state of the brain, the body, and the surrounding context; (d) being emergent states, emotional episodes have functional features that physical states, alone, do not have. Similarities and differences to other theoretical approaches to emotion are discussed. (shrink)

In this paper, I summarize an emerging debate in the cognitive sciences over the right taxonomy for understanding cognition – the right theory of and vocabulary for describing the structure of the mind – and the proper role of neuroscientific evidence in specifying this taxonomy. In part because the discussion clearly entails a deep reconsideration of the supposed autonomy of psychology from neuroscience, this is a debate in which philosophers should be interested, with which they should be familiar, and to (...) which they should contribute. Here, I outline some of the positions being advocated, and reflect on some of the possible implications of this work both for scientific and folk psychology. (shrink)

Psychological construction constitutes a different paradigm for the scientific study of emotion when compared to the current paradigm that is inspired by faculty psychology. This new paradigm is more consistent with the post-Darwinian conceptual framework in biology that includes a focus on (a) population thinking (vs. typologies), (b) domain-general core systems (vs. physical essences), and (c) constructive analysis (vs. reductionism). Three psychological construction approaches (the OCC model, the iterative reprocessing model, and the conceptual act theory) are discussed with respect to (...) these ideas. (shrink)

By the late 1990s, several converging trends in economics, psychology, and neuroscience had set the stage for the birth of a new scientific field known as “neuroeconomics”. Without the availability of an extensive variety of experimental designs for dealing with individual and social decision-making provided by experimental economics and psychology, many neuroeconomics studies could not have been developed. At the same time, without the significant progress made in neuroscience for grasping and understanding brain functioning, neuroeconomics would have never seen the (...) light of day. The paper is an overview of the main significant advances in the knowledge of brain functioning by neuroscience that have contributed to the emergence of neuroeconomics and its rise over the past two decades. These advances are grouped over three non-independent topics referred to as the “emo-rational” brain, “social” brain, and “computational” brain. For each topic, it emphasizes findings considered as critical to the birth and development of neuroeconomics while highlighting some of prominent questions about which knowledge should be improved by future research. In parallel, it shows that the boundaries between neuroeconomics and several recent sub-fields of cognitive neuroscience, such as affective, social, and more generally, decision neuroscience, are rather porous. (shrink)

Although the neural systems that underlie spoken language are well-known, how they adapt to evolving social cues during natural conversations remains an unanswered question. In this work we investigate the neural correlates of face-to-face conversations between two individuals using functional near infrared spectroscopy and acoustical analyses of concurrent audio recordings. Nineteen pairs of healthy adults engaged in live discussions on two controversial topics where their opinions were either in agreement or disagreement. Participants were matched according to their a priori opinions (...) on these topics as assessed by questionnaire. Acoustic measures of the recorded speech including the fundamental frequency range, median fundamental frequency, syllable rate, and acoustic energy were elevated during disagreement relative to agreement. Consistent with both the a priori opinion ratings and the acoustic findings, neural activity associated with long-range functional networks, rather than the canonical language areas, was also differentiated by the two conditions. Specifically, the frontoparietal system including bilateral dorsolateral prefrontal cortex, left supramarginal gyrus, angular gyrus, and superior temporal gyrus showed increased activity while talking during disagreement. In contrast, talking during agreement was characterized by increased activity in a social and attention network including right supramarginal gyrus, bilateral frontal eye-fields, and left frontopolar regions. Further, these social and visual attention networks were more synchronous across brains during agreement than disagreement. Rather than localized modulation of the canonical language system, these findings are most consistent with a model of distributed and adaptive language-related processes including cross-brain neural coupling that serves dynamic verbal exchanges. (shrink)

We point out that constructionist models from experimental psychology account for the sociocultural, psychological, and neural levels of analysis in emotion. Individual constructionist models form a “metamodel” that integrates the levels of analysis important to a science of emotion. By clarifying the multilevel nature of constructionism, we hope to help lay a strong foundation for future cross-disciplinary collaborations.

Over a century ago, William James outlined the first psychological constructionist model of emotion, arguing that emotions are phenomena constructed of more basic psychological parts. In this article, I outline a modern psychological constructionist model of emotion. I first explore the history of psychological construction to demonstrate that psychological constructionist models have historically emerged in an attempt to explain variability in emotion that cannot be accounted for by other approaches. I next discuss the modern psychological constructionist model of emotion that (...) I take in my own research, outlining its hypotheses, existing empirical support, and areas of future research. I conclude by arguing that psychological constructionist models can help scientists better understand the human mind. (shrink)

Although emotion is closely associated with motivation, and interacts with perception, cognition, and action, many conceptualizations still treat emotion as separate from these domains. Here, a comparative/evolutionary anatomy framework is presented to motivate the idea that long-range, distributed circuits involving the midbrain, thalamus, and forebrain are central to emotional processing. It is proposed that emotion can be understood in terms of large-scale network interactions spanning the neuroaxis that form “functionally integrated systems.” At the broadest level, the argument is made that (...) we need to move beyond a Newtonian view of causation to one involving complex systems where bidirectional influences and nonlinearities abound. Therefore, understanding interactions between subsystems and signal integration becomes central to unraveling the organization of the emotional brain. (shrink)

Carlos González-García, Sonia Alguacil, Pío Tudela y María Ruz Centro de Investigación Mente, Cerebro y Comportamiento (CIMCYC), Universidad de Granada, … Read More →.