scholarly journals Spatial gradient in activity within the insula reflects dissociable neural mechanisms underlying context-dependent advantageous and disadvantageous inequity aversion

2018 ◽  
Author(s):  
Xiaoxue Gao ◽  
Hongbo Yu ◽  
Ignacio Saez ◽  
Philip R. Blue ◽  
Lusha Zhu ◽  
...  
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Inequity Aversion ◽  
Neural Mechanisms ◽  
Anterior Cingulate ◽  
Spatial Gradient ◽  
Model Free ◽  
Interpersonal Guilt ◽  
Decision Making Processes ◽  
Context Dependent

AbstractHumans are capable of integrating social contextual information into decision-making processes to adjust their attitudes towards inequity. This context-dependency emerges both when individual is better off (i.e. advantageous inequity) and worse off (i.e. disadvantageous inequity) than others. It is not clear however, whether the context-dependent processing of advantageous and disadvantageous inequity rely on dissociable or shared neural mechanisms. Here, by combining an interpersonal interactive game that gave rise to interpersonal guilt and different versions of the dictator games that enabled us to characterize individual weights on aversion to advantageous and disadvantageous inequity, we investigated the neural mechanisms underlying the two forms of inequity aversion in the interpersonal guilt context. In each round, participants played a dot-estimation task with an anonymous co-player. The co-players received pain stimulation with 50% probability when anyone responded incorrectly. At the end of each round, participants completed a dictator game, which determined payoffs of him/herself and the co-player. Both computational model-based and model-free analyses demonstrated that when inflicting pain upon co-players (i.e., the guilt context), participants cared more about advantageous inequity and became less sensitive to disadvantageous inequity, compared with other social contexts. The contextual effects on two forms of inequity aversion are uncorrelated with each other at the behavioral level. Neuroimaging results revealed that the context-dependent representation of inequity aversion exhibited a spatial gradient in activity within the insula, with anterior parts predominantly involved in the aversion to advantageous inequity and posterior parts predominantly involved in the aversion to disadvantageous inequity. The dissociable mechanisms underlying the two forms of inequity aversion are further supported by the involvement of right dorsolateral prefrontal cortex and dorsomedial prefrontal cortex in advantageous inequity processing, and the involvement of right amygdala and dorsal anterior cingulate cortex in disadvantageous inequity processing. These results extended our understanding of decision-making processes involving inequity and the social functions of inequity aversion.

scholarly journals Distinguishing neural correlates of context-dependent advantageous- and disadvantageous-inequity aversion

2018 ◽  
Vol 115 (33) ◽  
pp. E7680-E7689 ◽  
Author(s):  
Xiaoxue Gao ◽  
Hongbo Yu ◽  
Ignacio Sáez ◽  
Philip R. Blue ◽  
Lusha Zhu ◽  
...  
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Computational Models ◽  
Social Contexts ◽  
Inequity Aversion ◽  
Context Dependency ◽  
Anterior Cingulate ◽  
Dorsal Anterior Cingulate Cortex ◽  
Decision Making Processes ◽  
Context Dependent

Humans can integrate social contextual information into decision-making processes to adjust their responses toward inequity. This context dependency emerges when individuals receive more (i.e., advantageous inequity) or less (i.e., disadvantageous inequity) than others. However, it is not clear whether context-dependent processing of advantageous and disadvantageous inequity involves differential neurocognitive mechanisms. Here, we used fMRI to address this question by combining an interactive game that modulates social contexts (e.g., interpersonal guilt) with computational models that enable us to characterize individual weights on inequity aversion. In each round, the participant played a dot estimation task with an anonymous coplayer. The coplayer would receive pain stimulation with 50% probability when either of them responded incorrectly. At the end of each round, the participant completed a variant of dictator game, which determined payoffs for him/herself and the coplayer. Computational modeling demonstrated the context dependency of inequity aversion: when causing pain to the coplayer (i.e., guilt context), participants cared more about the advantageous inequity and became more tolerant of the disadvantageous inequity, compared with other conditions. Consistently, neuroimaging results suggested the two types of inequity were associated with differential neurocognitive substrates. While the context-dependent processing of advantageous inequity was associated with social- and mentalizing-related processes, involving left anterior insula, right dorsolateral prefrontal cortex, and dorsomedial prefrontal cortex, the context-dependent processing of disadvantageous inequity was primarily associated with emotion- and conflict-related processes, involving left posterior insula, right amygdala, and dorsal anterior cingulate cortex. These results extend our understanding of decision-making processes related to inequity aversion.

scholarly journals Dissociable neural mechanisms track evidence accumulation for selection of attention versus action

2017 ◽  
Author(s):  
Amitai Shenhav ◽  
Mark A. Straccia ◽  
Jonathan D. Cohen ◽  
Matthew M. Botvinick
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Stimulus Dimension ◽  
Ventromedial Prefrontal Cortex ◽  
Neural Mechanisms ◽  
Anterior Cingulate ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Different Levels ◽  
Selection Of

AbstractDecision-making is typically studied as a sequential process from the selection of what to attend (e.g., between possible tasks, stimuli, or stimulus attributes) to the selection of which actions to take based on the attended information. However, people often gather information across these levels in parallel. For instance, even as they choose their actions, they may continue to evaluate how much to attend other tasks or dimensions of information within a task. We scanned participants while they made such parallel evaluations, simultaneously weighing how much to attend two dynamic stimulus attributes and which response to give based on the attended information. Regions of prefrontal cortex tracked information about the stimulus attributes in dissociable ways, related to either the predicted reward (ventromedial prefrontal cortex) or the degree to which that attribute was being attended (dorsal anterior cingulate, dACC). Within dACC, adjacent regions tracked uncertainty at different levels of the decision, regarding what to attend versus how to respond. These findings bridge research on perceptual and value-based decision-making, demonstrating that people dynamically integrate information in parallel across different levels of decision making.Naturalistic decisions allow an individual to weigh their options within a particular task (e.g., how best to word the introduction to a paper) while also weighing how much to attend other tasks (e.g., responding to e-mails). These different types of decision-making have a hierarchical but reciprocal relationship: Decisions at higher levels inform the focus of attention at lower levels (e.g., whether to select between citations or email addresses) while, at the same time, information at lower levels (e.g., the salience of an incoming email) informs decisions regarding which task to attend. Critically, recent studies suggest that decisions across these levels may occur in parallel, continuously informed by information that is integrated from the environment and from one’s internal milieu1,2.Research on cognitive control and perceptual decision-making has examined how responses are selected when attentional targets are clearly defined (e.g., based on instruction to attend a stimulus dimension), including cases in which responding requires accumulating information regarding a noisy percept (e.g., evidence favoring a left or right response)3-7. Separate research on value-based decision-making has examined how individuals select which stimulus dimension(s) to attend in order to maximize their expected rewards8-11. However, it remains unclear how the accumulation of evidence to select high-level goals and/or attentional targets interacts with the simultaneous accumulation of evidence to select responses according to those goals (e.g., based on the perceptual properties of the stimuli). Recent work has highlighted the importance of such interactions to understanding task selection12-15, multi-attribute decision-making16-18, foraging behavior19-21, cognitive effort22,23, and self-control24-27.While these interactions remain poorly understood, previous research has identified candidate neural mechanisms associated with multi-attribute value-based decision-making11,28,29 and with selecting a response based on noisy information from an instructed attentional target3–5. These research areas have implicated the ventromedial prefrontal cortex (vmPFC) in tracking the value of potential targets of attention (e.g., stimulus attributes)8,11 and the dorsal anterior cingulate cortex (dACC) in tracking an individual’s uncertainty regarding which response to select30–32. It has been further proposed that dACC may differentiate between uncertainty at each of these parallel levels of decision-making (e.g., at the level of task goals or strategies vs. specific motor actions), and that these may be separately encoded at different locations along the dACC’s rostrocaudal axis32,33. However, neural activity within and across these prefrontal regions has not yet been examined in a setting in which information is weighed at both levels within and across trials.Here we use a value-based perceptual decision-making task to examine how people integrate different dynamic sources of information to decide (a) which perceptual attribute to attend and (b) how to respond based on the evidence for that attribute. Participants performed a task in which they regularly faced a conflict between attending the stimulus attribute that offered the greater reward or the attribute that was more perceptually salient (akin to persevering in writing one’s paper when an enticing email awaits). We demonstrate that dACC and vmPFC track evidence for the two attributes in dissociable ways. Across these regions, vmPFC weighs attribute evidence by the reward it predicts and dACC weighs it by its attentional priority (i.e., the degree to which that attribute drives choice). Within dACC, adjacent regions differentiated between uncertainty at the two levels of the decision, regarding what to attend (rostral dACC) versus how to respond (caudal dACC).

scholarly journals Model-free decision making is prioritized when learning to avoid harming others

2020 ◽  
Vol 117 (44) ◽  
pp. 27719-27730 ◽  
Author(s):  
Patricia L. Lockwood ◽  
Miriam C. Klein-Flügge ◽  
Ayat Abdurahman ◽  
Molly J. Crockett
Keyword(s):  
Decision Making ◽  
Neural Mechanisms ◽  
Anterior Cingulate ◽  
Prediction Errors ◽  
Neural Basis ◽  
Subgenual Anterior Cingulate Cortex ◽  
Model Free ◽  
Moral Learning ◽  
Electric Shocks ◽  
Dorsolateral Prefrontal

Moral behavior requires learning how our actions help or harm others. Theoretical accounts of learning propose a key division between “model-free” algorithms that cache outcome values in actions and “model-based” algorithms that map actions to outcomes. Here, we tested the engagement of these mechanisms and their neural basis as participants learned to avoid painful electric shocks for themselves and a stranger. We found that model-free decision making was prioritized when learning to avoid harming others compared to oneself. Model-free prediction errors for others relative to self were tracked in the thalamus/caudate. At the time of choice, neural activity consistent with model-free moral learning was observed in subgenual anterior cingulate cortex (sgACC), and switching after harming others was associated with stronger connectivity between sgACC and dorsolateral prefrontal cortex. Finally, model-free moral learning varied with individual differences in moral judgment. Our findings suggest moral learning favors efficiency over flexibility and is underpinned by specific neural mechanisms.

scholarly journals The Neural System of Metacognition Accompanying Decision-Making in The Prefrontal Cortex

2017 ◽  
Author(s):  
Lirong Qiu ◽  
Jie Su ◽  
Yinmei Ni ◽  
Yang Bai ◽  
Xiaoli Li ◽  
...  
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Neural System ◽  
Neural Mechanisms ◽  
Anterior Cingulate ◽  
Decision Making Process ◽  
Dorsal Anterior Cingulate Cortex ◽  
Decision Uncertainty ◽  
Uncertainty Monitoring ◽  
Frontopolar Cortex

AbstractDecision-making is usually accompanied by metacognition, through which a decision maker monitors the decision uncertainty and consequently revises the decision, even prior to feedback. However, the neural mechanisms of metacognition remain controversial: one theory proposes that metacognition coincides the decision-making process; and another addresses that it entails an independent neural system in the prefrontal cortex (PFC). Here we devised a novel paradigm of “decision-redecision” to investigate the metacognition process in redecision, in comparison with the decision process. We here found that the anterior PFC, including dorsal anterior cingulate cortex (dACC) and lateral frontopolar cortex (lFPC), were exclusively activated after the initial decisions. dACC was involved in decision uncertainty monitoring, whereas lFPC was involved in decision adjustment controlling, subject to control demands of the tasks. Our findings support that the PFC is essentially involved in metacognition and further suggest that functions of the PFC in metacognition are dissociable.

scholarly journals Dissociable roles of cortical excitation-inhibition balance during patch-leaving versus value-guided decisions

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Luca F. Kaiser ◽  
Theo O. J. Gruendler ◽  
Oliver Speck ◽  
Lennart Luettgau ◽  
Gerhard Jocham
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Neuronal Activity ◽  
Ventromedial Prefrontal Cortex ◽  
Anterior Cingulate ◽  
Mutual Inhibition ◽  
Dorsal Anterior Cingulate Cortex ◽  
Cortical Excitation ◽  
The Cost

AbstractIn a dynamic world, it is essential to decide when to leave an exploited resource. Such patch-leaving decisions involve balancing the cost of moving against the gain expected from the alternative patch. This contrasts with value-guided decisions that typically involve maximizing reward by selecting the current best option. Patterns of neuronal activity pertaining to patch-leaving decisions have been reported in dorsal anterior cingulate cortex (dACC), whereas competition via mutual inhibition in ventromedial prefrontal cortex (vmPFC) is thought to underlie value-guided choice. Here, we show that the balance between cortical excitation and inhibition (E/I balance), measured by the ratio of GABA and glutamate concentrations, plays a dissociable role for the two kinds of decisions. Patch-leaving decision behaviour relates to E/I balance in dACC. In contrast, value-guided decision-making relates to E/I balance in vmPFC. These results support mechanistic accounts of value-guided choice and provide evidence for a role of dACC E/I balance in patch-leaving decisions.

scholarly journals Roles of Ventromedial Prefrontal Cortex and Anterior Cingulate in Subjective Valuation of Prospective Effort

2018 ◽  
Vol 29 (10) ◽  
pp. 4277-4290 ◽  
Author(s):  
Patrick S Hogan ◽  
Joseph K Galaro ◽  
Vikram S Chib
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Brain Activity ◽  
Blood Oxygenation ◽  
Ventromedial Prefrontal Cortex ◽  
Anterior Cingulate ◽  
Effort Level ◽  
Perceived Effort ◽  
Trade Offs ◽  
Subjective Valuation

Abstract The perceived effort level of an action shapes everyday decisions. Despite the importance of these perceptions for decision-making, the behavioral and neural representations of the subjective cost of effort are not well understood. While a number of studies have implicated anterior cingulate cortex (ACC) in decisions about effort/reward trade-offs, none have experimentally isolated effort valuation from reward and choice difficulty, a function that is commonly ascribed to this region. We used functional magnetic resonance imaging to monitor brain activity while human participants engaged in uncertain choices for prospective physical effort. Our task was designed to examine effort-based decision-making in the absence of reward and separated from choice difficulty—allowing us to investigate the brain’s role in effort valuation, independent of these other factors. Participants exhibited subjectivity in their decision-making, displaying increased sensitivity to changes in subjective effort as objective effort levels increased. Analysis of blood-oxygenation-level dependent activity revealed that the ventromedial prefrontal cortex (vmPFC) encoded the subjective valuation of prospective effort, and ACC activity was best described by choice difficulty. These results provide insight into the processes responsible for decision-making regarding effort, partly dissociating the roles of vmPFC and ACC in prospective valuation of effort and choice difficulty.

scholarly journals A Geometric Framework for Understanding Dynamic Information Integration in Context-Dependent Computation

2021 ◽  
Author(s):  
Xiaohan Zhang ◽  
Shenquan Liu ◽  
Zhe Sage Chen
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Information Integration ◽  
Principal Component ◽  
Population Coding ◽  
Geometric Framework ◽  
Context Dependent ◽  
Activity State ◽  
Low Dimensional ◽  
Context Cues

AbstractPrefrontal cortex plays a prominent role in performing flexible cognitive functions and working memory, yet the underlying computational principle remains poorly understood. Here we trained a rate-based recurrent neural network (RNN) to explore how the context rules are encoded, maintained across seconds-long mnemonic delay, and subsequently used in a context-dependent decision-making task. The trained networks emerged key experimentally observed features in the prefrontal cortex (PFC) of rodent and monkey experiments, such as mixed-selectivity, sparse representations, neuronal sequential activity and rotation dynamics. To uncover the high-dimensional neural dynamical system, we further proposed a geometric framework to quantify and visualize population coding and sensory integration in a temporally-defined manner. We employed dynamic epoch-wise principal component analysis (PCA) to define multiple task-specific subspaces and task-related axes, and computed the angles between task-related axes and these subspaces. In low-dimensional neural representations, the trained RNN first encoded the context cues in a cue-specific subspace, and then maintained the cue information with a stable low-activity state persisting during the delay epoch, and further formed line attractors for sensor integration through low-dimensional neural trajectories to guide decision making. We demonstrated via intensive computer simulations that the geometric manifolds encoding the context information were robust to varying degrees of weight perturbation in both space and time. Overall, our analysis framework provides clear geometric interpretations and quantification of information coding, maintenance and integration, yielding new insight into the computational mechanisms of context-dependent computation.

scholarly journals An evolutionary computational theory of prefrontal executive function in decision-making

2014 ◽  
Vol 369 (1655) ◽  
pp. 20130474 ◽  
Author(s):  
Etienne Koechlin
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Adaptive Behaviour ◽  
Computational Theory ◽  
Critical Reasoning ◽  
Model Free ◽  
Evolutionary Advantage ◽  
Adaptive Processes ◽  
Principled Account ◽  
Selection Of

The prefrontal cortex subserves executive control and decision-making, that is, the coordination and selection of thoughts and actions in the service of adaptive behaviour. We present here a computational theory describing the evolution of the prefrontal cortex from rodents to humans as gradually adding new inferential Bayesian capabilities for dealing with a computationally intractable decision problem: exploring and learning new behavioural strategies versus exploiting and adjusting previously learned ones through reinforcement learning (RL). We provide a principled account identifying three inferential steps optimizing this arbitration through the emergence of (i) factual reactive inferences in paralimbic prefrontal regions in rodents; (ii) factual proactive inferences in lateral prefrontal regions in primates and (iii) counterfactual reactive and proactive inferences in human frontopolar regions. The theory clarifies the integration of model-free and model-based RL through the notion of strategy creation. The theory also shows that counterfactual inferences in humans yield to the notion of hypothesis testing, a critical reasoning ability for approximating optimal adaptive processes and presumably endowing humans with a qualitative evolutionary advantage in adaptive behaviour.

scholarly journals Corticoinsular circuits encode subjective value expectation and violation for effortful goal-directed behavior

2018 ◽  
Vol 115 (22) ◽  
pp. E5233-E5242 ◽  
Author(s):  
Amanda R. Arulpragasam ◽  
Jessica A. Cooper ◽  
Makiah R. Nuutinen ◽  
Michael T. Treadway
Keyword(s):  
Decision Making ◽  
Relevant Information ◽  
Neural Mechanisms ◽  
Anterior Cingulate ◽  
Error Signal ◽  
Value Prediction ◽  
Subjective Value ◽  
Effort Discounting ◽  
Trial History ◽  
Goal Directed Behavior

We are presented with choices each day about how to invest our effort to achieve our goals. Critically, these decisions must frequently be made under conditions of incomplete information, where either the effort required or possible reward to be gained is uncertain. Such choices therefore require the development of potential value estimates to guide effortful goal-directed behavior. To date, however, the neural mechanisms for this expectation process are unknown. Here, we used computational fMRI during an effort-based decision-making task where trial-wise information about effort costs and reward magnitudes was presented separately over time, thereby allowing us to model distinct effort/reward computations as choice-relevant information unfolded. We found that ventromedial prefrontal cortex (vmPFC) encoded expected subjective value. Further, activity in dorsal anterior cingulate (dACC) and anterior insula (aI) reflected both effort discounting as well as a subjective value prediction error signal derived from trial history. While prior studies have identified these regions as being involved in effort-based decision making, these data demonstrate their specific role in the formation and maintenance of subjective value estimates as relevant information becomes available.

Emotion-Based Decision Making in schizophrenia: evidence from the Iowa Gambling Task

2009 ◽  
Vol 18 (2) ◽  
pp. 104-106 ◽  
Author(s):  
Marcella Bellani ◽  
Luisa Tomelleri ◽  
Paolo Brambilla
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Iowa Gambling Task ◽  
Neural System ◽  
Anterior Cingulate ◽  
Emotional States ◽  
Human Beings ◽  
Complex Process ◽  
Social Conduct ◽  
Contextual Stimuli

The decision making can be defined as the mental process in which a “choice is made after reflecting on the consequences of that choice” (Bechara & Van Der Linden, 2005; Bechara et al., 1997). It is a complex process that involves cognitive as well as emotion-based functions. In fact human beings make fast adaptive decisions in daily life, and that is based on the skill to relate emotion to contextual stimuli in order to anticipate outcomes through activation of emotional states (Bechara et al., 2005). In this regard, the ventromedial prefrontal cortex (VMPFC) has been widely recognized to play a key role in the emotional decision making process. The VMPFC includes the medial part of the orbitofrontal cortex (OFC), the more ventral sectors of the medial prefrontal cortex and the anterior cingulate cortex (Bechara et al., 1997). In particular the OFC, within the VMPFC, is part of a neural system underpinning decision-making and reward-related behaviours which are thought to be linked to social conduct (Rolls, 2000).

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