Neural responses to ambiguity involve domain-general and domain-specific emotion processing systems

Extant research has examined the process of decision making under uncertainty, specifically in situations of ambiguity. However, much of this work has been conducted in the context of semantic and low-level visual processing. An open question is whether ambiguity in social signals (e.g., emotional facial expressions) is processed similarly or whether a unique set of processors come on-line to resolve ambiguity in a social context. Our work has examined ambiguity using surprised facial expressions, as they have predicted both positive and negative outcomes in the past. Specifically, whereas some people tended to interpret surprise as negatively valenced, others tended toward a more positive interpretation. Here, we examined neural responses to social ambiguity using faces (surprise) and nonface emotional scenes (International Affective Picture System). Moreover, we examined whether these effects are specific to ambiguity resolution (i.e., judgments about the ambiguity) or whether similar effects would be demonstrated for incidental judgments (e.g., nonvalence judgments about ambiguously valenced stimuli). We found that a distinct task control (i.e., cingulo-opercular) network was more active when resolving ambiguity. We also found that activity in the ventral amygdala was greater to faces and scenes that were rated explicitly along the dimension of valence, consistent with findings that the ventral amygdala tracks valence. Taken together, there is a complex neural architecture that supports decision making in the presence of ambiguity: (a) a core set of cortical structures engaged for explicit ambiguity processing across stimulus boundaries and (b) other dedicated circuits for biologically relevant learning situations involving faces

Looking Through the Lens of Individual Differences: Relationships Between Personality, Cognitive Control, Language Processing, and Genes

The study of individual differences in cognitive abilities and personality traits has the potential to inform our understanding of how the processing mechanisms underlying different behaviors are organized. In the current set of studies, we applied an individual-differences approach to the study of sources of variation in individuals’ personality traits, cognitive control, and linguistic ambiguity resolution abilities. In Chapter 2, we investigated the relationship between motivational personality traits and cognitive control abilities. The results demonstrated that individual differences in the personality traits of approach and avoidance predict performance on verbal and nonverbal versions of the Stroop task. These results are suggestive of a hemisphere-specific organization of approach/avoidance personality traits and verbal/nonverbal cognitive control abilities. Furthermore, these results are consistent with previous findings of hemispheric asymmetry in terms of the distribution of dopaminergic and norephinephrine signaling pathways. In Chapter 3, we investigated the extent to which the same processing mechanisms are used to resolve lexical and syntactic conflict. In addition, we incorporated a behavioral genetics approach to investigate this commonality at the neurotransmitter level. We explored whether genetic variation in catechol-O-methyltransferase (COMT), a gene that regulates the catabolism of dopamine in prefrontal cortex, is related to individuals’ ability to resolve lexical and syntactic conflict. The results of this study demonstrated that individual differences in the ability to resolve lexical conflict are related to variation in syntactic conflict resolution abilities. This finding supports constraint satisfaction theories of language processing. We also showed that those individuals with the variant of the COMT gene resulting in less availability of dopamine at the synapse tended to have greater difficulty processing both lexical and syntactic ambiguities. These results provide novel evidence that dopamine plays a role in linguistic ambiguity resolution. In sum, the results from the current set of studies reveal how an individual-differences approach can be used to investigate several different factors involved in the context-dependent regulation of behavior

Neuroeconomics: How Neuroscience Can Inform Economics

Neuroeconomics uses knowledge about brain mechanisms to inform economic analysis, and roots economics in biology. It opens up the "black box" of the brain, much as organizational economics adds detail to the theory of the firm. Neuroscientists use many tools— including brain imaging, behavior of patients with localized brain lesions, animal behavior, and recording single neuron activity. The key insight for economics is that the brain is composed of multiple systems which interact. Controlled systems ("executive function") interrupt automatic ones. Emotions and cognition both guide decisions. Just as prices and allocations emerge from the interaction of two processes—supply and demand— individual decisions can be modeled as the result of two (or more) processes interacting. Indeed, "dual-process" models of this sort are better rooted in neuroscientific fact, and more empirically accurate, than single-process models (such as utility-maximization). We discuss how brain evidence complicates standard assumptions about basic preference, to include homeostasis and other kinds of state-dependence. We also discuss applications to intertemporal choice, risk and decision making, and game theory. Intertemporal choice appears to be domain-specific and heavily influenced by emotion. The simplified ß-d of quasi-hyperbolic discounting is supported by activation in distinct regions of limbic and cortical systems. In risky decision, imaging data tentatively support the idea that gains and losses are coded separately, and that ambiguity is distinct from risk, because it activates fear and discomfort regions. (Ironically, lesion patients who do not receive fear signals in prefrontal cortex are "rationally" neutral toward ambiguity.) Game theory studies show the effect of brain regions implicated in "theory of mind", correlates of strategic skill, and effects of hormones and other biological variables. Finally, economics can contribute to neuroscience because simple rational-choice models are useful for understanding highly-evolved behavior like motor actions that earn rewards, and Bayesian integration of sensorimotor information

The social brain: neural basis of social knowledge

Social cognition in humans is distinguished by psychological processes that allow us to make inferences about what is going on inside other people—their intentions, feelings, and thoughts. Some of these processes likely account for aspects of human social behavior that are unique, such as our culture and civilization. Most schemes divide social information processing into those processes that are relatively automatic and driven by the stimuli, versus those that are more deliberative and controlled, and sensitive to context and strategy. These distinctions are reflected in the neural structures that underlie social cognition, where there is a recent wealth of data primarily from functional neuroimaging. Here I provide a broad survey of the key abilities, processes, and ways in which to relate these to data from cognitive neuroscience

Mapping dynamic interactions among cognitive biases in depression

Depression is theorized to be caused in part by biased cognitive processing of emotional information. Yet, prior research has adopted a reductionist approach that does not characterize how biases in cognitive processes such as attention and memory work together to confer risk for this complex multifactorial disorder. Grounded in affective and cognitive science, we highlight four mechanisms to understand how attention biases, working memory difficulties, and long-term memory biases interact and contribute to depression. We review evidence for each mechanism and highlight time- and context-dependent dynamics. We outline methodological considerations and recommendations for research in this area. We conclude with directions to advance the understanding of depression risk, cognitive training interventions, and transdiagnostic properties of cognitive biases and their interactions

Ten Challenges for Decision Neuroscience

Decision neuroscience research, as currently practiced, employs the methods of neuroscience to investigate concepts drawn from the social sciences. A typical study selects one or more variables from psychological or economic models, manipulates or measures choices within a simplified choice task, and then identifies neural correlates. Using this “neuroeconomic” approach, researchers have described brain systems whose functioning shapes key economic variables, most notably aspects of subjective value. Yet, the standard approach has fundamental limitations. Important aspects of the mechanisms of decision making – from the sources of variability in decision making to the very computations supported by decision-related regions – remain incompletely understood. Here, I outline 10 outstanding challenges for future research in decision neuroscience. While some will be readily addressed using current methods, others will require new conceptual frameworks. Accordingly, a new strain of decision neuroscience will marry methods from economics and cognitive science to concepts from neurobiology and cognitive neuroscience

Self-directedness, integration and higher cognition

In this paper I discuss connections between self-directedness, integration and higher cognition. I present a model of self-directedness as a basis for approaching higher cognition from a situated cognition perspective. According to this model increases in sensorimotor complexity create pressure for integrative higher order control and learning processes for acquiring information about the context in which action occurs. This generates complex articulated abstractive information processing, which forms the major basis for higher cognition. I present evidence that indicates that the same integrative characteristics found in lower cognitive process such as motor adaptation are present in a range of higher cognitive process, including conceptual learning. This account helps explain situated cognition phenomena in humans because the integrative processes by which the brain adapts to control interaction are relatively agnostic concerning the source of the structure participating in the process. Thus, from the perspective of the motor control system using a tool is not fundamentally different to simply controlling an arm

Individual differences in valence bias: fMRI evidence of the initial negativity hypothesis

Facial expressions offer an ecologically valid model for examining individual differences in affective decision-making. They convey an emotional signal from a social agent and provide important predictive information about one’s environment (presence of potential rewards or threats). Although some expressions provide clear predictive information (angry, happy), others (surprised) are ambiguous in that they predict both positive and negative outcomes. Thus, surprised faces can delineate an individual’s valence bias, or the tendency to interpret ambiguity as positive or negative. Our initial negativity hypothesis suggests that the initial response to ambiguity is negative, and that positivity relies on emotion regulation. We tested this hypothesis by comparing brain activity during explicit emotion regulation (reappraisal) and while freely viewing facial expressions, and measuring the relationship between brain activity and valence bias. Brain regions recruited during reappraisal showed greater activity for surprise in individuals with an increasingly positive valence bias. Additionally, we linked amygdala activity with an initial negativity, revealing a pattern similarity in individuals with negative bias between viewing surprised faces and maintaining negativity. Finally, these individuals failed to show normal habituation to clear negativity. These results support the initial negativity hypothesis, and are consistent with emotion research in both children and adult populations

Lost in the socially extended mind: Genuine intersubjectivity and disturbed self-other demarcation in schizophrenia

Much of the characteristic symptomatology of schizophrenia can be understood as resulting from a pervasive sense of disembodiment. The body is experienced as an external machine that needs to be controlled with explicit intentional commands, which in turn leads to severe difficulties in interacting with the world in a fluid and intuitive manner. In consequence, there is a characteristic dissociality: Others become problems to be solved by intellectual effort and no longer present opportunities for spontaneous interpersonal alignment. This dissociality goes hand in hand with a progressive loss of the socially extended mind, which normally affords opportunities for co-regulation of cognitive and affective processes. However, at times people with schizophrenia report that they are confronted by the opposite of this dissociality, namely an unusual fluidity of the self-other boundary as expressed in experiences of ambiguous body boundaries, intrusions, and even merging with others. Here the person has not lost access to the socially extended mind but has instead become lost in it, possibly due to a weakened sense of self. We argue that this neglected aspect of schizophrenic social dysfunction can be usefully approached via the concept of genuine intersubjectivity: We normally participate in a shared experience with another person by implicitly co-regulating how our interaction unfolds. This co-regulation integrates our respective experience’s dynamical bases into one interpersonal process and gives the interaction an ambiguous second-person character. The upshot is that reports of abnormal self-other fluidity are not indicative of hallucinations without any basis in reality, but of a heightened sensitivity and vulnerability to processes of interpersonal alignment and mutual incorporation that form the normal basis of social life. We conclude by discussing implications of this view for both the science of consciousness as well as approaches to intervention and therapy