choice bias
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2021 ◽  
Author(s):  
Ella Bosch ◽  
Matthias Fritsche ◽  
Christian Utzerath ◽  
Jan K. Buitelaar ◽  
Floris P. de Lange

Autism Spectrum Disorder (ASD) or autism is characterized by social and non-social symptoms, including sensory hyper- and hyposensitivities. A suggestion has been put forward that some of these symptoms could be explained by differences in how sensory information is integrated with its context, including a lower tendency to leverage the past in the processing of new perceptual input. At least two history-dependent effects of opposite directions have been described in the visual perception literature: a repulsive adaptation effect, where perception of a stimulus is biased away from an adaptor stimulus, and an attractive serial choice bias, where perceptual choices are biased towards the previous choice. In this study, we investigated whether autistic participants differed in either bias from typically developing controls (TD). Sixty-four adolescent participants (31 with ASD, 33 TD) were asked to categorize oriented line stimuli in two tasks which were designed so that we would induce either adaptation or serial choice bias. Although our tasks successfully induced both biases, in comparing the two groups, we found no differences in the magnitude of adaptation nor in the modulation of perceptual choices by the previous choice. In conclusion, we find no evidence of a decreased integration of the past in visual perception of autistic individuals.


2021 ◽  
Vol 31 (6) ◽  
pp. 1234-1244.e6 ◽  
Author(s):  
Gabriela Mochol ◽  
Roozbeh Kiani ◽  
Rubén Moreno-Bote

2021 ◽  
Author(s):  
Hongbo Yu ◽  
Jenifer Siegel ◽  
John Clithero ◽  
Molly Crockett

Moral behavior is susceptible to peer influence. How does information from peers influence moral preferences? We used drift-diffusion modeling to show that peer influence changes the value of moral behavior by prioritizing the choice attributes that align with peers’ goals. Study 1 (N = 100; preregistered) showed that participants accurately inferred the goals of prosocial and antisocial peers when observing their moral decisions. In Study 2 (N = 68), participants made moral decisions before and after observing the decisions of a prosocial or antisocial peer. Peer observation caused participants’ own preferences to resemble those of their peers. This peer influence effect on value computation manifested as an increased weight on choice attributes promoting the peers’ goals that occurred independently from peer influence on initial choice bias. Participants’ self-reported awareness of influence tracked more closely with computational measures of prosocial than antisocial influence. Our findings have implications for bolstering and blocking the effects of prosocial and antisocial influence on moral behavior.


2020 ◽  
Vol 20 (12) ◽  
pp. 9
Author(s):  
Ella Bosch ◽  
Matthias Fritsche ◽  
Benedikt V. Ehinger ◽  
Floris P. de Lange

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Jan Willem de Gee ◽  
Konstantinos Tsetsos ◽  
Lars Schwabe ◽  
Anne E Urai ◽  
David McCormick ◽  
...  

Decisions are often made by accumulating ambiguous evidence over time. The brain’s arousal systems are activated during such decisions. In previous work in humans, we found that evoked responses of arousal systems during decisions are reported by rapid dilations of the pupil and track a suppression of biases in the accumulation of decision-relevant evidence (de Gee et al., 2017). Here, we show that this arousal-related suppression in decision bias acts on both conservative and liberal biases, and generalizes from humans to mice, and from perceptual to memory-based decisions. In challenging sound-detection tasks, the impact of spontaneous or experimentally induced choice biases was reduced under high phasic arousal. Similar bias suppression occurred when evidence was drawn from memory. All of these behavioral effects were explained by reduced evidence accumulation biases. Our results point to a general principle of interplay between phasic arousal and decision-making.


2020 ◽  
Author(s):  
Jan Willem de Gee ◽  
Konstantinos Tsetsos ◽  
Lars Schwabe ◽  
Anne E Urai ◽  
David McCormick ◽  
...  
Keyword(s):  

Author(s):  
Ella Bosch ◽  
Matthias Fritsche ◽  
Benedikt V. Ehinger ◽  
Floris P de Lange

ABSTRACTPerceptual decisions are biased towards previous decisions. Previous research suggests that this choice repetition bias is increased after previous decisions of high confidence, as inferred from response time measures (Urai et al., 2017), but also when previous decisions were based on weak sensory evidence (Akaishi et al., 2014). As weak sensory evidence is typically associated with low confidence, these previous findings appear conflicting. To resolve this conflict, we set out to investigate the effect of decision confidence on choice repetition more directly by measuring explicit confidence ratings in a motion coherence discrimination task. Moreover, we explored how choice and stimulus history jointly affect subsequent perceptual choices. We found that participants were more likely to repeat previous choices of high subjective confidence, as well as previous fast choices, confirming the boost of choice repetition with decision confidence. Furthermore, we discovered that current choices were biased away from the previous evidence direction, not previous choice, and that this effect grew with previous evidence strength. These findings point towards simultaneous biases of choice repetition, modulated by decision confidence, and adaptation, modulated by the strength of evidence, which bias current perceptual decisions in opposite directions.


2019 ◽  
Vol 3 (12) ◽  
pp. 1345-1345
Author(s):  
Lior Lebovich ◽  
Ran Darshan ◽  
Yoni Lavi ◽  
David Hansel ◽  
Yonatan Loewenstein

2019 ◽  
Vol 122 (4) ◽  
pp. 1538-1554 ◽  
Author(s):  
Sanjna Banerjee ◽  
Shrey Grover ◽  
Suhas Ganesh ◽  
Devarajan Sridharan

Endogenous cueing of attention enhances sensory processing of the attended stimulus (perceptual sensitivity) and prioritizes information from the attended location for guiding behavioral decisions (spatial choice bias). Here, we test whether sensitivity and bias effects of endogenous spatial attention are under the control of common or distinct mechanisms. Human observers performed a multialternative visuospatial attention task with probabilistic spatial cues. Observers’ behavioral choices were analyzed with a recently developed multidimensional signal detection model (the m-ADC model). The model effectively decoupled the effects of spatial cueing on sensitivity from those on spatial bias and revealed striking dissociations between them. Sensitivity was highest at the cued location and not significantly different among uncued locations, suggesting a spotlight-like allocation of sensory resources at the cued location. On the other hand, bias varied systematically with cue validity, suggesting a graded allocation of decisional priority across locations. Cueing-induced modulations of sensitivity and bias were uncorrelated within and across subjects. Bias, but not sensitivity, correlated with key metrics of prioritized decision-making, including reaction times and decision optimality indices. In addition, we developed a novel metric, differential risk curvature, for distinguishing bias effects of attention from those of signal expectation. Differential risk curvature correlated selectively with m-ADC model estimates of bias but not with estimates of sensitivity. Our results reveal dissociable effects of endogenous attention on perceptual sensitivity and choice bias in a multialternative choice task and motivate the search for the distinct neural correlates of each. NEW & NOTEWORTHY Attention is often studied as a unitary phenomenon. Yet, attention can both enhance the perception of important stimuli (sensitivity) and prioritize such stimuli for decision-making (bias). Employing a multialternative spatial attention task with probabilistic cueing, we show that attention affects sensitivity and bias through dissociable mechanisms. Specifically, the effects on sensitivity alone match the notion of an attentional “spotlight.” Our behavioral model enables quantifying component processes of attention, and identifying their respective neural correlates.


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