scholarly journals Aversive Pavlovian Control of Instrumental Behavior in Humans

2013 ◽  
Vol 25 (9) ◽  
pp. 1428-1441 ◽  
Author(s):  
Dirk E. M. Geurts ◽  
Quentin J. M. Huys ◽  
Hanneke E. M. den Ouden ◽  
Roshan Cools

Adaptive behavior involves interactions between systems regulating Pavlovian and instrumental control of actions. Here, we present the first investigation of the neural mechanisms underlying aversive Pavlovian–instrumental transfer using fMRI in humans. Recent evidence indicates that these Pavlovian influences on instrumental actions are action-specific: Instrumental approach is invigorated by appetitive Pavlovian cues but inhibited by aversive Pavlovian cues. Conversely, instrumental withdrawal is inhibited by appetitive Pavlovian cues but invigorated by aversive Pavlovian cues. We show that BOLD responses in the amygdala and the nucleus accumbens were associated with behavioral inhibition by aversive Pavlovian cues, irrespective of action context. Furthermore, BOLD responses in the ventromedial prefrontal cortex differed between approach and withdrawal actions. Aversive Pavlovian conditioned stimuli modulated connectivity between the ventromedial prefrontal cortex and the caudate nucleus. These results show that action-specific aversive control of instrumental behavior involves the modulation of fronto-striatal interactions by Pavlovian conditioned stimuli.

2017 ◽  
Author(s):  
Amitai Shenhav ◽  
Mark A. Straccia ◽  
Jonathan D. Cohen ◽  
Matthew M. Botvinick

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).


2021 ◽  
Author(s):  
Payam Piray ◽  
Roshan Cools ◽  
Ivan Toni

Human decisions are known to be strongly influenced by the manner in which options are presented, the "framing effect". Here, we ask whether decision-makers are also influenced by how advice from other knowledgeable agents are framed, a "social framing effect". Concretely, do students learn better from a teacher who often frames advice by emphasizing appetitive outcomes, or do they learn better from another teacher who usually emphasizes avoiding options that can be harmful to their progress? We study the computational and neural mechanisms by which framing of advice affect decision-making, social learning, and trust. We found that human participants are more likely to trust and follow an adviser who often uses an appetitive frame for advice compared with another one who often uses an aversive frame. This social framing effect is implemented through a modulation of the integrative abilities of the ventromedial prefrontal cortex. At the time of choice, this region combines information learned via personal experiences of reward with social information, but the combination differs depending on the social framing of advice. Personally-acquired information is weighted more strongly when dealing with an adviser who uses an aversive frame. The findings suggest that social advice is systematically incorporated into our decisions, while being affected by biases similar to those influencing individual value-based learning.


2015 ◽  
Vol 112 (16) ◽  
pp. 5195-5200 ◽  
Author(s):  
James D. Howard ◽  
Jay A. Gottfried ◽  
Philippe N. Tobler ◽  
Thorsten Kahnt

Nervous systems must encode information about the identity of expected outcomes to make adaptive decisions. However, the neural mechanisms underlying identity-specific value signaling remain poorly understood. By manipulating the value and identity of appetizing food odors in a pattern-based imaging paradigm of human classical conditioning, we were able to identify dissociable predictive representations of identity-specific reward in orbitofrontal cortex (OFC) and identity-general reward in ventromedial prefrontal cortex (vmPFC). Reward-related functional coupling between OFC and olfactory (piriform) cortex and between vmPFC and amygdala revealed parallel pathways that support identity-specific and -general predictive signaling. The demonstration of identity-specific value representations in OFC highlights a role for this region in model-based behavior and reveals mechanisms by which appetitive behavior can go awry.


2019 ◽  
Author(s):  
David Victor Smith ◽  
Mauricio Delgado

Our behavior is inextricably linked to rewards in our environment. This observation has sparked considerable interest in understanding the neural mechanisms that support reward processing in humans. Early neuroimaging studies implicated regions such as the striatum and ventromedial prefrontal cortex (VMPFC) in reward processing, particularly how activation in these regions is modulated by anticipation and receipt of rewards. These findings have been extended in the context of models that account for the representation of subjective value, which influences decision making. Building from these findings, researchers are now beginning to characterize how social information has idiosyncratic influences on reward processing.


2020 ◽  
Vol 30 (08) ◽  
pp. 2050041
Author(s):  
Daniele Caligiore ◽  
Pierandrea Mirino

Several data have demonstrated that during the widely used experimental paradigm for studying associative learning, trace eye blinking conditioning (TEBC), there is a strong interaction between cerebellum and medial prefrontal cortex (mPFC). Despite this evidence, the neural mechanisms underlying this interaction are still not clear. Here, we propose a neurophysiologically plausible computational model to address this issue. The model is constrained on the basis of two critical anatomo-physiological features: (i) the cerebello-cortical organization through two circuits, respectively, targeting M1 and mPFC; (ii) the different timing in the plasticity mechanisms of these parallel circuits produced by the granule cells time sensitivity according to which different subpopulations are active at different moments during conditioned stimuli. The computer simulations run with the model suggest that these features are critical to understand how the cooperation between cerebellum and mPFC supports motor areas during TEBC. In particular, a greater trace interval produces greater plasticity changes at the slow path synapses involving mPFC with respect to plasticity changes at the fast path involving M1. As a consequence, the greater is the trace interval, the stronger is the mPFC involvement. The model has been validated by reproducing data collected through recent real mice experiments.


2020 ◽  
Vol 48 (7) ◽  
pp. 1-19
Author(s):  
Ryan T. Daley ◽  
Holly J. Bowen ◽  
Eric C. Fields ◽  
Angela Gutchess ◽  
Elizabeth A. Kensinger

Self-relevance effects are often confounded by the presence of emotional content, rendering it difficult to determine how brain networks functionally connected to the ventromedial prefrontal cortex (vmPFC) are affected by the independent contributions of self-relevance and emotion. This difficulty is complicated by age-related changes in functional connectivity between the vmPFC and other default mode network regions, and regions typically associated with externally oriented networks. We asked groups of younger and older adults to imagine placing emotional and neutral objects in their home or a stranger's home. An age-invariant vmPFC cluster showed increased activation for self-relevant and emotional content processing. Functional connectivity analyses revealed age × self-relevance interactions in vmPFC connectivity with the anterior cingulate cortex. There were also age × emotion interactions in vmPFC functional connectivity with the anterior insula, orbitofrontal gyrus, inferior frontal gyrus, and supramarginal gyrus. Interactions occurred in regions with the greatest differences between the age groups, as revealed by conjunction analyses. Implications of the findings are discussed.


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