scholarly journals Distinct linear and non-linear trajectories of reward and punishment reversal learning during development: Relevance for dopamine's role in adolescent decision making

2011 ◽  
Vol 1 (4) ◽  
pp. 578-590 ◽  
Author(s):  
Marieke E. van der Schaaf ◽  
Eveline Warmerdam ◽  
Eveline A. Crone ◽  
Roshan Cools
Keyword(s):  
Decision Making ◽  
Reversal Learning ◽  
Non Linear ◽  
Reward And Punishment

scholarly journals Is our perception of the spread of COVID-19 inherently inaccurate?

2021 ◽  
Author(s):  
Alexander Maier
Keyword(s):  
Decision Making ◽  
Subjective Perception ◽  
Logarithmic Function ◽  
Original Formulation ◽  
Global Crisis ◽  
New Information ◽  
The World ◽  
Non Linear ◽  
The Future ◽  
Linear Nature

One of the most fundamental insights into the nature of our subjective perception of the world around us is that it is not veridical. In other words, we tend to not perceive information about the world around us accurately. Instead, our brains interpret new information through a host of innate and learned mechanisms that can introduce bias and distortions One of the best studied mechanisms that guide – and distort – our perception is the psychophysical Weber-Fechner law. According to this empirically derived, mathematically formulated law we tend to put more emphasis on smaller deviations in size while underestimating larger changes. The original formulation of the Weber-Fechner law takes the shape of a logarithmic function and is commonly applied to somatosensory perception such as the weight of an object. However, later work showed that the Weber-Fechner law can be generalized and describe a large variety of perceived changes in magnitude that even go beyond the sensory domain. Here we investigate the hypothesis that our perception of data associated with the spread of COVID-19 and similar pandemics is governed by the same psychophysical laws. Based on several recently published studies, we demonstrate that the Weber-Fechner law can be shown to directly affect the decision-making of officials in response to this global crisis as well as the greater public at large. We discuss how heightened awareness of the non-linear nature of subjective perception could help alleviate problematic judgements in similar situations in the future.

Introduction: the absurdity of bureaucracy

2017 ◽  
Author(s):  
Nina Holm Vohnsen
Keyword(s):  
Decision Making ◽  
Development Studies ◽  
Writing Style ◽  
Non Linear ◽  
Analytical Writing

The introduction lays out the book’s empirical interest (the repercussions of policy), the analytical focus (decision-making) and its theoretical aim (to theorize the non-linear aspect of implementation by addressing it through the lens of the absurd). This introduction firmly places the book in the fields of implementation and development studies, but does so by introducing a focus on all that is rejected, ignored and excluded from planning and bureaucratic decision-making. The introduction also provides a reflection on how best to write complexity and incoherency, and it develops the book’s primary analytical writing style inspired by photojournalism, more specifically environmental portraiture (Kobré 2008).

scholarly journals Establishing the Dopamine Dependency of Human Striatal Signals During Reward and Punishment Reversal Learning

2012 ◽  
Vol 24 (3) ◽  
pp. 633-642 ◽  
Author(s):  
Marieke E. van der Schaaf ◽  
Martine R. van Schouwenburg ◽  
Dirk E.M. Geurts ◽  
Arnt F.A. Schellekens ◽  
Jan K. Buitelaar ◽  
...  
Keyword(s):  
Reversal Learning ◽  
Reward And Punishment

scholarly journals Trading off the cost of conflict against expected rewards

2018 ◽  
Author(s):  
Nura Sidarus ◽  
Stefano Palminteri ◽  
Valérian Chambon
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Cognitive Control ◽  
Reversal Learning ◽  
Computational Models ◽  
Learning Task ◽  
Learning Rates ◽  
Different Types ◽  
Irrelevant Distractors ◽  
The Cost

AbstractValue-based decision-making involves trading off the cost associated with an action against its expected reward. Research has shown that both physical and mental effort constitute such subjective costs, biasing choices away from effortful actions, and discounting the value of obtained rewards. Facing conflicts between competing action alternatives is considered aversive, as recruiting cognitive control to overcome conflict is effortful. Yet, it remains unclear whether conflict is also perceived as a cost in value-based decisions. The present study investigated this question by embedding irrelevant distractors (flanker arrows) within a reversal-learning task, with intermixed free and instructed trials. Results showed that participants learned to adapt their choices to maximize rewards, but were nevertheless biased to follow the suggestions of irrelevant distractors. Thus, the perceived cost of being in conflict with an external suggestion could sometimes trump internal value representations. By adapting computational models of reinforcement learning, we assessed the influence of conflict at both the decision and learning stages. Modelling the decision showed that conflict was avoided when evidence for either action alternative was weak, demonstrating that the cost of conflict was traded off against expected rewards. During the learning phase, we found that learning rates were reduced in instructed, relative to free, choices. Learning rates were further reduced by conflict between an instruction and subjective action values, whereas learning was not robustly influenced by conflict between one’s actions and external distractors. Our results show that the subjective cost of conflict factors into value-based decision-making, and highlights that different types of conflict may have different effects on learning about action outcomes.

scholarly journals Population coding of valence in the basolateral amygdala

2018 ◽  
Author(s):  
Xian Zhang ◽  
Bo Li
Keyword(s):  
Associative Learning ◽  
Reversal Learning ◽  
Basolateral Amygdala ◽  
Population Coding ◽  
Neuronal Responses ◽  
Conditioned Stimuli ◽  
Reward And Punishment

AbstractThe basolateral amygdala (BLA) plays an important role in associative learning, by representing both conditioned stimuli (CSs) and unconditioned stimuli (USs) of positive and negative valences, and by forming associations between CSs and USs. However, how such associations are formed and updated during learning remains unclear. Here we show that associative learning driven by reward and punishment profoundly alters BLA neuronal responses at population levels, reducing noise correlations and transforming the representations of CSs to resemble the distinctive valence-specific representations of USs. This transformation is accompanied by the emergence of prevalent inhibitory CS and US responses, and by the plasticity of CS responses in individual BLA neurons. During reversal learning wherein the expected valences are reversed, BLA population CS representations are remapped onto ensembles representing the opposite valences and track the switching in valence-specific behavioral actions. Our results reveal how signals predictive of opposing valences in the BLA evolve during reward and punishment learning, and how these signals might be updated and used to guide flexible behaviors.

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