scholarly journals Adaptive Engagement of Cognitive Control in Context-Dependent Decision Making

2016 ◽  
pp. bhv333 ◽  
Author(s):  
Michael L. Waskom ◽  
Michael C. Frank ◽  
Anthony D. Wagner
Keyword(s):  
Decision Making ◽  
Cognitive Control ◽  
Context Dependent

A Bird in the Hand Isn’t Good for Long

2018 ◽  
Vol 65 (1) ◽  
pp. 23-31 ◽  
Author(s):  
Stefan Scherbaum ◽  
Simon Frisch ◽  
Maja Dshemuchadse
Keyword(s):  
Decision Making ◽  
Cognitive Control ◽  
The Other ◽  
Decision Task ◽  
Short Term ◽  
Additional Time ◽  
Control Processes ◽  
Folk Wisdom ◽  
Study Participants ◽  
Insight Into

Abstract. Folk wisdom tells us that additional time to make a decision helps us to refrain from the first impulse to take the bird in the hand. However, the question why the time to decide plays an important role is still unanswered. Here we distinguish two explanations, one based on a bias in value accumulation that has to be overcome with time, the other based on cognitive control processes that need time to set in. In an intertemporal decision task, we use mouse tracking to study participants’ responses to options’ values and delays which were presented sequentially. We find that the information about options’ delays does indeed lead to an immediate bias that is controlled afterwards, matching the prediction of control processes needed to counter initial impulses. Hence, by using a dynamic measure, we provide insight into the processes underlying short-term oriented choices in intertemporal decision making.

Age-Related Differences in Motivational Integration and Cognitive Control

2019 ◽  
Author(s):  
Debbie Marianne Yee ◽  
Sarah L Adams ◽  
Asad Beck ◽  
Todd Samuel Braver
Keyword(s):  
Older Adults ◽  
Decision Making ◽  
Cognitive Control ◽  
Task Performance ◽  
Cognitive Task ◽  
Monetary Reward ◽  
Potential Candidate ◽  
Younger Adults ◽  
Age Related ◽  
Cognitive Task Performance

Motivational incentives play an influential role in value-based decision-making and cognitive control. A compelling hypothesis in the literature suggests that the brain integrates the motivational value of diverse incentives (e.g., motivational integration) into a common currency value signal that influences decision-making and behavior. To investigate whether motivational integration processes change during healthy aging, we tested older (N=44) and younger (N=54) adults in an innovative incentive integration task paradigm that establishes dissociable and additive effects of liquid (e.g., juice, neutral, saltwater) and monetary incentives on cognitive task performance. The results reveal that motivational incentives improve cognitive task performance in both older and younger adults, providing novel evidence demonstrating that age-related cognitive control deficits can be ameliorated with sufficient incentive motivation. Additional analyses revealed clear age-related differences in motivational integration. Younger adult task performance was modulated by both monetary and liquid incentives, whereas monetary reward effects were more gradual in older adults and more strongly impacted by trial-by-trial performance feedback. A surprising discovery was that older adults shifted attention from liquid valence toward monetary reward throughout task performance, but younger adults shifted attention from monetary reward toward integrating both monetary reward and liquid valence by the end of the task, suggesting differential strategic utilization of incentives. Together these data suggest that older adults may have impairments in incentive integration, and employ different motivational strategies to improve cognitive task performance. The findings suggest potential candidate neural mechanisms that may serve as the locus of age-related change, providing targets for future cognitive neuroscience investigations.

scholarly journals Cognitive Control of Working Memory: A Model-Based Approach

2021 ◽  
Vol 11 (6) ◽  
pp. 721
Author(s):  
Russell J. Boag ◽  
Niek Stevenson ◽  
Roel van Dooren ◽  
Anne C. Trutti ◽  
Zsuzsika Sjoerds ◽  
...  
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Cognitive Control ◽  
Relevant Information ◽  
Decision Time ◽  
Control Processes ◽  
Prepotent Response ◽  
New Information ◽  
Empirical Performance ◽  
Flow Of Information

Working memory (WM)-based decision making depends on a number of cognitive control processes that control the flow of information into and out of WM and ensure that only relevant information is held active in WM’s limited-capacity store. Although necessary for successful decision making, recent work has shown that these control processes impose performance costs on both the speed and accuracy of WM-based decisions. Using the reference-back task as a benchmark measure of WM control, we conducted evidence accumulation modeling to test several competing explanations for six benchmark empirical performance costs. Costs were driven by a combination of processes, running outside of the decision stage (longer non-decision time) and showing the inhibition of the prepotent response (lower drift rates) in trials requiring WM control. Individuals also set more cautious response thresholds when expecting to update WM with new information versus maintain existing information. We discuss the promise of this approach for understanding cognitive control in WM-based decision making.

A preliminary study of gray matter volume differences related to context-dependent and independent decision-making

2021 ◽  
Author(s):  
Zhang Jinbo
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Gray Matter ◽  
Cognitive Bias ◽  
Gray Matter Volume ◽  
Neural Basis ◽  
Matter Volume ◽  
Decision Styles ◽  
Context Dependent ◽  
Independent Decision

Facing the high degree of uncertainty of the environment, we have evolved two kinds of decision-making styles: context-dependent and context-independent decision. However, the underlying neural basis of these two kinds of decision styles was mostly unknown. Here, the cognitive bias task was applied to split participants into the context-independent decision-maker and context-dependent decision-maker based on the cognitive bias task scores. Then, we used voxel-based morphometry to directly investigate its underlying differences in gray matter volume. We found that the gray matter volume of the prefrontal cortex and parietal regions, such as inferior parietal lobule, was larger in context-dependent decision-makers than that of the context-independent decision-maker.

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 Distributed context-dependent choice information in mouse dorsal-parietal cortex

2021 ◽  
Author(s):  
Javier Orlandi ◽  
Mohammad Adbolrahmani ◽  
Ryo Aoki ◽  
Dmitry Lyamzin ◽  
Andrea Benucci
Keyword(s):  
Decision Making ◽  
Decision Variable ◽  
Visual Stream ◽  
Posterior Cortex ◽  
Neural Data ◽  
Context Dependent ◽  
Cortical Regions ◽  
Low Dimensional ◽  
Independent Decision ◽  
The Brain

Abstract Choice information appears in the brain as distributed signals with top-down and bottom-up components that together support decision-making computations. In sensory and associative cortical regions, the presence of choice signals, their strength, and area specificity are known to be elusive and changeable, limiting a cohesive understanding of their computational significance. In this study, examining the mesoscale activity in mouse posterior cortex during a complex visual discrimination task, we found that broadly distributed choice signals defined a decision variable in a low-dimensional embedding space of multi-area activations, particularly along the ventral visual stream. The subspace they defined was near-orthogonal to concurrently represented sensory and motor-related activations, and it was modulated by task difficulty and contextually by the animals’ attention state. To mechanistically relate choice representations to decision-making computations, we trained recurrent neural networks with the animals’ choices and found an equivalent decision variable whose context-dependent dynamics agreed with that of the neural data. In conclusion, our results demonstrated an independent decision variable broadly represented in the posterior cortex, controlled by task features and cognitive demands. Its dynamics reflected decision computations, possibly linked to context-dependent feedback signals used for probabilistic-inference computations in variable animal-environment interactions.

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