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Journal ArticleDOI

Cognitive neuroscience of human counterfactual reasoning

TL;DR: It is proposed that counterfactual thinking depends on an integrative network of systems for affective processing, mental simulation, and cognitive control that together enable adaptive behavior and goal-directed decision making and make recommendations for the study ofcounterfactual inference in health, aging, and disease.
Abstract: Counterfactual reasoning is a hallmark of human thought, enabling the capacity to shift from perceiving the immediate environment to an alternative, imagined perspective. Mental representations of counterfactual possibilities (e.g., imagined past events or future outcomes not yet at hand) provide the basis for learning from past experience, enable planning and prediction, support creativity and insight, and give rise to emotions and social attributions (e.g., regret and blame). Yet remarkably little is known about the psychological and neural foundations of counterfactual reasoning. In this review, we survey recent findings from psychology and neuroscience indicating that counterfactual thought depends on an integrative network of systems for affective processing, mental simulation, and cognitive control. We review evidence to elucidate how these mechanisms are systematically altered through psychiatric illness and neurological disease. We propose that counterfactual thinking depends on the coordination of multiple information processing systems that together enable adaptive behavior and goal-directed decision making and make recommendations for the study of counterfactual inference in health, aging, and disease.

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Citations
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Posted Content
TL;DR: A novel SGG framework based on causal inference but not the conventional likelihood is presented, which uses Total Direct Effect (TDE) as the proposed final predicate score for unbiased SGG and can be widely applied in the community who seeks unbiased predictions.
Abstract: Today's scene graph generation (SGG) task is still far from practical, mainly due to the severe training bias, e.g., collapsing diverse "human walk on / sit on / lay on beach" into "human on beach". Given such SGG, the down-stream tasks such as VQA can hardly infer better scene structures than merely a bag of objects. However, debiasing in SGG is not trivial because traditional debiasing methods cannot distinguish between the good and bad bias, e.g., good context prior (e.g., "person read book" rather than "eat") and bad long-tailed bias (e.g., "near" dominating "behind / in front of"). In this paper, we present a novel SGG framework based on causal inference but not the conventional likelihood. We first build a causal graph for SGG, and perform traditional biased training with the graph. Then, we propose to draw the counterfactual causality from the trained graph to infer the effect from the bad bias, which should be removed. In particular, we use Total Direct Effect (TDE) as the proposed final predicate score for unbiased SGG. Note that our framework is agnostic to any SGG model and thus can be widely applied in the community who seeks unbiased predictions. By using the proposed Scene Graph Diagnosis toolkit on the SGG benchmark Visual Genome and several prevailing models, we observed significant improvements over the previous state-of-the-art methods.

264 citations


Cites background from "Cognitive neuroscience of human cou..."

  • ...For both machines and humans, decision making is a collaboration of content (endogenous reasons) and context (exogenous reasons) [56]....

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Proceedings ArticleDOI
14 Jun 2020
TL;DR: In this article, the authors propose to use the counterfactual causality from the trained graph to infer the effect from the bad bias, which should be removed, and use Total Direct Effect (TDE) as the proposed final predicate score for unbiased SGG.
Abstract: Today’s scene graph generation (SGG) task is still far from practical, mainly due to the severe training bias, e.g., collapsing diverse "human walk on / sit on / lay on beach" into "human on beach". Given such SGG, the down-stream tasks such as VQA can hardly infer better scene structures than merely a bag of objects. However, debiasing in SGG is not trivial because traditional debiasing methods cannot distinguish between the good and bad bias, e.g., good context prior (e.g., "person read book" rather than "eat") and bad long-tailed bias (e.g., "near" dominating "behind / in front of"). In this paper, we present a novel SGG framework based on causal inference but not the conventional likelihood. We first build a causal graph for SGG, and perform traditional biased training with the graph. Then, we propose to draw the counterfactual causality from the trained graph to infer the effect from the bad bias, which should be removed. In particular, we use Total Direct Effect (TDE) as the proposed final predicate score for unbiased SGG. Note that our framework is agnostic to any SGG model and thus can be widely applied in the community who seeks unbiased predictions. By using the proposed Scene Graph Diagnosis toolkit on the SGG benchmark Visual Genome and several prevailing models, we observed significant improvements over the previous state-of-the-art methods.

247 citations

Book ChapterDOI
TL;DR: The functional theory of counterfactual thinking as mentioned in this paper has been used extensively in the literature to understand why and how cognitive and behavioral outcomes are influenced by episodic counterfactuality, including preparing for goal pursuit and regulating affect.
Abstract: Thinking about what might have been—counterfactual thinking—is a common feature of the mental landscape. Key questions about counterfactual thinking center on why and how they occur and what downstream cognitive and behavioral outcomes they engender. The functional theory of counterfactual thinking aims to answer these and other questions by drawing connections to goal cognition and by specifying distinct functions that counterfactuals may serve, including preparing for goal pursuit and regulating affect. Since the publication of our last theoretical statement ( Epstude & Roese, 2008 ), numerous lines of empirical evidence support, or are rendered more readily understandable, when glimpsed through the lens of the functional theory. However, other lines of evidence have called into question the very basis of the theory. We integrate a broad range of findings spanning several psychological disciplines so as to present an updated version of the functional theory. We integrate findings from social psychology, cognitive neuroscience, developmental psychology, clinical psychology, and health psychology that support the claim that episodic counterfactual thoughts are geared mainly toward preparation and goal striving and are generally beneficial for individuals. Counterfactuals may influence behavior via either a content-specific pathway (in which the counterfactual insight informs behavior change) or a content-neutral pathway (in which the negative affect from the counterfactual motivates generic behavior change). Challenges to the functional theory of counterfactual thinking center on whether counterfactuals typically cohere to a structural form amenable to goal striving and whether behavioral consequences are mainly dysfunctional rather than functional. Integrating both supporting and challenging evidence, we offer a new theoretical synthesis intended to clarify the literature and guide future research in multiple disciplines of psychology.

143 citations

Journal ArticleDOI
TL;DR: It is shown that individual differences in reasoning ability and cognitive style of thinking are positively associated with a preference for utilitarian solutions, but bear no relationship to harm-relevant concerns.
Abstract: Sacrificial moral dilemmas elicit a strong conflict between the motive to not personally harm someone and the competing motive to achieving the greater good, which is often described as the “utilitarian” response. Some prior research suggests that reasoning abilities and deliberative cognitive style are associated with endorsement of utilitarian solutions, but, as has more recently been emphasized, both conceptual and methodological issues leave open the possibility that utilitarian responses are due instead to a reduced emotional response to harm. Across 8 studies, using self-report, behavioral performance, and neuroanatomical measures, we show that individual differences in reasoning ability and cognitive style of thinking are positively associated with a preference for utilitarian solutions, but bear no relationship to harm-relevant concerns. These findings support the dual-process model of moral decision making and highlight the utility of process dissociation methods. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

60 citations

Journal ArticleDOI
TL;DR: It is found that individuals who scored high on a measure of psychopathy were as or more likely than individuals low on psychopathy to report negative affect in response to regret-inducing counterfactual outcomes, and diminished behavioral regret sensitivity predicted a higher number of prior incarcerations, and moderated the relationship between psychopathy and incarceration history.
Abstract: Psychopathy is associated with persistent antisocial behavior and a striking lack of regret for the consequences of that behavior. Although explanatory models for psychopathy have largely focused on deficits in affective responsiveness, recent work indicates that aberrant value-based decision making may also play a role. On that basis, some have suggested that psychopathic individuals may be unable to effectively use prospective simulations to update action value estimates during cost–benefit decision making. However, the specific mechanisms linking valuation, affective deficits, and maladaptive decision making in psychopathy remain unclear. Using a counterfactual decision-making paradigm, we found that individuals who scored high on a measure of psychopathy were as or more likely than individuals low on psychopathy to report negative affect in response to regret-inducing counterfactual outcomes. However, despite exhibiting intact affective regret sensitivity, they did not use prospective regret signals to guide choice behavior. In turn, diminished behavioral regret sensitivity predicted a higher number of prior incarcerations, and moderated the relationship between psychopathy and incarceration history. These findings raise the possibility that maladaptive decision making in psychopathic individuals is not a consequence of their inability to generate or experience negative emotions. Rather, antisocial behavior in psychopathy may be driven by a deficit in the generation of forward models that integrate information about rules, costs, and goals with stimulus value representations to promote adaptive behavior.

52 citations


Cites background or result from "Cognitive neuroscience of human cou..."

  • ...In keeping with prior work (26, 30, 35), we considered...

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  • ...Notably, counterfactual thinking and regret engage strikingly similar neural circuitry (25, 26)....

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References
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Book
01 Jan 1988
TL;DR: This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning, which ranges from the history of the field's intellectual foundations to the most recent developments and applications.
Abstract: Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability. The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

37,989 citations


"Cognitive neuroscience of human cou..." refers background in this paper

  • ...These findings indicate that vmPFC/mOFC abnormalities result in impairments in expectation-based regulation of emotions and behavior (Mellers et al., 1997; Sutton and Barto, 1998; Levens et al., 2014)....

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Journal ArticleDOI
TL;DR: It is proposed that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them, which provide bias signals to other brain structures whose net effect is to guide the flow of activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task.
Abstract: ▪ Abstract The prefrontal cortex has long been suspected to play an important role in cognitive control, in the ability to orchestrate thought and action in accordance with internal goals. Its neural basis, however, has remained a mystery. Here, we propose that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them. They provide bias signals to other brain structures whose net effect is to guide the flow of activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task. We review neurophysiological, neurobiological, neuroimaging, and computational studies that support this theory and discuss its implications as well as further issues to be addressed

10,943 citations


"Cognitive neuroscience of human cou..." refers background in this paper

  • ...…network enables the integration of multiple sources of information and supports the regulation and control of thought and behavior (e.g., Miller and Cohen, 2001; Seeley et al., 2007; Dosenbach et al., 2008; Vincent et al., 2008; Nelson et al., 2010; Spreng and Grady, 2010; Shackman et al., 2011;…...

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  • ..., and Miller, D. T. (1986). Norm theory: comparing reality to its alternatives....

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Journal ArticleDOI
TL;DR: The field of neuroscience has, after a long period of looking the other way, again embraced emotion as an important research area, and much of the progress has come from studies of fear, and especially fear conditioning as mentioned in this paper.
Abstract: The field of neuroscience has, after a long period of looking the other way, again embraced emotion as an important research area. Much of the progress has come from studies of fear, and especially fear conditioning. This work has pin- pointed the amygdala as an important component of the system involved in the acqui- sition, storage, and expression of fear memory and has elucidated in detail how stimuli enter, travel through, and exit the amygdala. Some progress has also been made in understanding the cellular and molecular mechanisms that underlie fear conditioning, and recent studies have also shown that the findings from experimental animals apply to the human brain. It is important to remember why this work on emotion succeeded where past efforts failed. It focused on a psychologically well-defined aspect of emo- tion, avoided vague and poorly defined concepts such as "affect," "hedonic tone," or "emotional feelings," and used a simple and straightforward experimental approach. With so much research being done in this area today, it is important that the mistakes of the past not be made again. It is also time to expand from this foundation into broader aspects of mind and behavior

7,347 citations

Journal ArticleDOI
TL;DR: Two distinct networks typically coactivated during functional MRI tasks are identified, anchored by dorsal anterior cingulate and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an “executive-control network” that links dorsolateral frontal and parietal neocortices.
Abstract: Variations in neural circuitry, inherited or acquired, may underlie important individual differences in thought, feeling, and action patterns. Here, we used task-free connectivity analyses to isolate and characterize two distinct networks typically coactivated during functional MRI tasks. We identified a "salience network," anchored by dorsal anterior cingulate (dACC) and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an "executive-control network" that links dorsolateral frontal and parietal neocortices. These intrinsic connectivity networks showed dissociable correlations with functions measured outside the scanner. Prescan anxiety ratings correlated with intrinsic functional connectivity of the dACC node of the salience network, but with no region in the executive-control network, whereas executive task performance correlated with lateral parietal nodes of the executive-control network, but with no region in the salience network. Our findings suggest that task-free analysis of intrinsic connectivity networks may help elucidate the neural architectures that support fundamental aspects of human behavior.

6,049 citations


"Cognitive neuroscience of human cou..." refers background in this paper

  • ...…the integration of multiple sources of information and supports the regulation and control of thought and behavior (e.g., Miller and Cohen, 2001; Seeley et al., 2007; Dosenbach et al., 2008; Vincent et al., 2008; Nelson et al., 2010; Spreng and Grady, 2010; Shackman et al., 2011; Barbey et al.,…...

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  • ...This network is consistently linked to maintaining task goals and monitoring actions, as well as contributing to slow behavioral adjustments over time (e.g., Seeley et al., 2007; Dosenbach et al., 2008; Power et al., 2011; Chein and Schneider, 2012)....

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Journal ArticleDOI
TL;DR: The results suggest a functional architecture for the cognitive control of emotion that dovetails with findings from other human and nonhuman research on emotion.

3,817 citations


"Cognitive neuroscience of human cou..." refers background in this paper

  • ...…arousal and evaluative judgments (Berntson et al., 2011), especially in integrating sensory and associative information to process negative stimuli (e.g., LeDoux, 2000; Dolan, 2002; Ochsner and Gross, 2005; Phelps, 2006; Lewis et al., 2007; Kim et al., 2011; Bzdok et al., 2013; Denny et al., 2013)....

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  • ..., 2011), especially in integrating sensory and associative information to process negative stimuli (e.g., LeDoux, 2000; Dolan, 2002; Ochsner and Gross, 2005; Phelps, 2006; Lewis et al., 2007; Kim et al., 2011; Bzdok et al., 2013; Denny et al., 2013)....

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