Bayesian networks as models of human judgement under uncertainty: The role of causal assumptions in belief updating

1999 ◽  
Vol 8 (1) ◽  
pp. 30-39
Author(s):  
Marcus Plach
Author(s):  
Ziqing Yao ◽  
Xuanyi Lin ◽  
Xiaoqing Hu

Abstract When people are confronted with feedback that counters their prior beliefs, they preferentially rely on desirable rather than undesirable feedback in belief updating, i.e. an optimism bias. In two pre-registered EEG studies employing an adverse life event probability estimation task, we investigated the neurocognitive processes that support the formation and the change of optimism biases in immediate and 24 h delayed tests. We found that optimistic belief updating biases not only emerged immediately but also became significantly larger after 24 h, suggesting an active role of valence-dependent offline consolidation processes in the change of optimism biases. Participants also showed optimistic memory biases: they were less accurate in remembering undesirable than desirable feedback probabilities, with inferior memories of undesirable feedback associated with lower belief updating in the delayed test. Examining event-related brain potentials (ERPs) revealed that desirability of feedback biased initial encoding: desirable feedback elicited larger P300s than undesirable feedback, with larger P300 amplitudes predicting both higher belief updating and memory accuracies. These results suggest that desirability of feedback could bias both online and offline memory-related processes such as encoding and consolidation, with both processes contributing to the formation and change of optimism biases.


Author(s):  
Martin Biehl ◽  
Takashi Ikegami ◽  
Daniel Polani

We present a first formal analysis of specific and complete local integration. Complete local integration was previously proposed as a criterion for detecting entities or wholes in distributed dynamical systems. Such entities in turn were conceived to form the basis of a theory of emergence of agents within dynamical systems. Here, we give a more thorough account of the underlying formal measures. The main contribution is the disintegration theorem which reveals a special role of completely locally integrated patterns (what we call ι-entities) within the trajectories they occur in. Apart from proving this theorem we introduce the disintegration hierarchy and its refinement-free version as a way to structure the patterns in a trajectory. Furthermore we construct the least upper bound and provide a candidate for the greatest lower bound of specific local integration. Finally, we calculate the i-entities in small example systems as a first sanity check and find that ι-entities largely fulfil simple expectations.


2018 ◽  
Vol 30 (12) ◽  
pp. 1803-1820 ◽  
Author(s):  
Marieke Jepma ◽  
Stephen B. R. E. Brown ◽  
Peter R. Murphy ◽  
Stephany C. Koelewijn ◽  
Boukje de Vries ◽  
...  

To make optimal predictions in a dynamic environment, the impact of new observations on existing beliefs—that is, the learning rate—should be guided by ongoing estimates of change and uncertainty. Theoretical work has proposed specific computational roles for various neuromodulatory systems in the control of learning rate, but empirical evidence is still sparse. The aim of the current research was to examine the role of the noradrenergic and cholinergic systems in learning rate regulation. First, we replicated our recent findings that the centroparietal P3 component of the EEG—an index of phasic catecholamine release in the cortex—predicts trial-to-trial variability in learning rate and mediates the effects of surprise and belief uncertainty on learning rate (Study 1, n = 17). Second, we found that pharmacological suppression of either norepinephrine or acetylcholine activity produced baseline-dependent effects on learning rate following nonobvious changes in an outcome-generating process (Study 1). Third, we identified two genes, coding for α2A receptor sensitivity ( ADRA2A) and norepinephrine reuptake ( NET), as promising targets for future research on the genetic basis of individual differences in learning rate (Study 2, n = 137). Our findings suggest a role for the noradrenergic and cholinergic systems in belief updating and underline the importance of studying interactions between different neuromodulatory systems.


Cognition ◽  
2007 ◽  
Vol 105 (3) ◽  
pp. 704-714 ◽  
Author(s):  
José C. Perales ◽  
Andrés Catena ◽  
Antonio Maldonado ◽  
Antonio Cándido

2018 ◽  
Vol 3 (4) ◽  

Accumulating evidence shows that the central nervous system (CNS) regulates the activity of the immune system. Concerning the role of immune system in cancer, psychosocial influences on immune function provide a mechanism of association between psychosocial factors (like interpersonal aggression) and cancer prognosis. Social conflicts between males, involving high aggression stress and threat (psychosocial conflicts) produce both an allostatic state and allostatic load. The costs for aggressors (Hawks) and victims (Doves) tested under semi laboratory conditions are quite different. Testosterone does not cause aggression, only exaggerates the pre-existing pattern and response to environmental triggers of aggression.


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