Cognitive control of saccadic selection and inhibition from within the core cortical saccadic network

The ability to select the task-relevant stimulus for a saccadic eye movement, while inhibiting saccades to task-irrelevant stimuli, is crucial for active vision. Here, we present a novel saccade-contingent behavioural paradigm and investigate the neural basis of the central cognitive functions underpinning such behaviour - saccade selection, saccade inhibition and saccadic choice – in female and male human participants. The paradigm allows for exceptionally well-matched contrasts, with task demands formalized with stochastic accumulation-to-threshold models. Using functional magnetic resonance imaging, we replicated the core cortical eye-movement network for saccade generation (frontal eye fields, posterior parietal cortex and higher-level visual areas). However, in contrast to previously published tasks, saccadic selection and inhibition recruited only this core network. Brain12 behaviour analyses further showed that inhibition efficiency may be underpinned by white matter integrity of tracts between key saccade generating regions, and that inhibition efficiency is associated with right inferior frontal gyrus engagement, potentially implementing general-purpose inhibition. The core network, however, was insufficient for saccadic choice which recruited anterior regions commonly attributed to saccadic action selection, including dorsolateral prefrontal cortex and anterior cingulate cortex. Jointly, the results indicate that extra-saccadic activity observed for free choice, and in previously published tasks probing saccadic control, is likely due to increased load on higher-level cognitive processes, and not saccadic selection per se, which is achieved within the canonical cortical eye movement network

How to Change the Weight of Rare Events in Decisions from Experience

When making risky choices, two kinds of information are crucial: outcome values and outcome probabilities. Here, we demonstrate that the juncture at which value and probability information is provided has a fundamental effect on choice. Across four experiments involving 489 participants, we compare two decision making scenarios: one where value information is revealed during sampling (Standard), and one where value information is revealed after sampling (Value-Ignorance). On average, participants made riskier choices when value information was provided after sampling. Moreover, parameter estimates from a hierarchical Bayesian implementation of cumulative prospect theory suggested that participants overweighted rare events when value information was absent during sampling, but showed no overweighting in the Standard condition. This suggests that the impact of rare events on choice relies crucially on the timing of probability and value integration. We provide paths towards mechanistic explanations of our results based on frameworks which assume different underlying cognitive architectures

Increasing compliance with low tidal volume ventilation in the ICU with two nudge-based interventions: evaluation through intervention time-series analyses

Objectives: Low tidal volume (TVe) ventilation improves outcomes for ventilated patients, and the majority of clinicians state they implement it. Unfortunately, most patients never receive low TVes. ‘Nudges’ influence decision-making with subtle cognitive mechanisms and are effective in many contexts. There have been few studies examining their impact on clinical decision-making. We investigated the impact of 2 interventions designed using principles from behavioural science on the deployment of low TVe ventilation in the intensive care unit (ICU). Setting: University Hospitals Bristol, a tertiary, mixed medical and surgical ICU with 20 beds, admitting over 1300 patients per year. Participants: Data were collected from 2144 consecutive patients receiving controlled mechanical ventilation for more than 1 hour between October 2010 and September 2014. Patients on controlled mechanical ventilation for more than 20 hours were included in the final analysis. Interventions: (1) Default ventilator settings were adjusted to comply with low TVe targets from the initiation of ventilation unless actively changed by a clinician. (2) A large dashboard was deployed displaying TVes in the format mL/kg ideal body weight (IBW) with alerts when TVes were excessive. Primary outcome measure: TVe in mL/kg IBW. Findings: TVe was significantly lower in the defaults group. In the dashboard intervention, TVe fell more quickly and by a greater amount after a TVe of 8 mL/kg IBW was breached when compared with controls. This effect improved in each subsequent year for 3 years. Conclusions: This study has demonstrated that adjustment of default ventilator settings and a dashboard with alerts for excessive TVe can significantly influence clinical decision-making. This offers a promising strategy to improve compliance with low TVe ventilation, and suggests that using insights from behavioural science has potential to improve the translation of evidence into practice

The optimality of perception and cognition: the perception-cognition gap explored

The ability to choose wisely is crucial for our survival. Yet, the received wisdom has been that humans choose irrationally and sub-optimally. This conclusion is largely based on studies in which participants are asked to make choices on the basis of explicit numerical information. Lately, our ability to make such high-level choices has been contrasted with our ability to make low-level (perceptual or perceptuo-motor) choices. Remarkably, we seem able to make near-optimal low-level choices. Taken at face value, the discrepancy gives rise to a perception-cognition gap. The gap implies, for example, that our ancestors were much better at choosing where to put their feet on a rocky ridge (a perceptuo-motor task), compared to choosing which prey to hunt (a cognitive task).The work reported herein probes this gap. There are many differences between literatures showing optimal and sub-optimal performance. The main approach taken here was to match low- and high-level tasks as closely as possible to eliminate such differences. When this is done one finds very little evidence for a perception-cognition gap. Moreover, once the standards of performance assessment of the respective literature are applied to data generated under such conditions it becomes apparent that the cause of the gap seems to lie in the standards themselves. When low-level standards are applied, human choice, whether low- or high-level, looks good. When high-level standards are applied, human choice, whether low- or high-level, looks rather poor. It is easy to see then, that applying high-level standards to high-level tasks, and low-level standards to low-level tasks, will give rise to a “gap”, with no or little actual difference in performance

Human value learning and representation reflects rational adaptation to task demands

Humans and other animals routinely make choices between goods of different value. Choices are often made within identifiable contexts, such that an efficient learner may represent values relative to their local context. However, if goods occur across multiple contexts, a relative value code can lead to irrational choice. In this case, an absolute context-independent value is preferable to a relative code. Here, we test the hypothesis that value representation is not fixed, but rationally adapted to context expectations. In two experiments, we manipulated participants‟ expectations about whether item values learned within local contexts would need to be subsequently compared across contexts. Despite identical learning experiences, the group whose expectations included choices across local contexts, went on to learn more absolute-like representation than the group whose expectations only covered fixed local contexts. Thus, human value representation is neither relative nor absolute, but efficiently and rationally tuned to task demands

MEM-EX: An exemplar memory model of decisions from experience

Many real-world decisions must be made on basis of experienced outcomes. However, there is little consensus about the mechanisms by which people make these decisions from experience (DfE). Across five experiments, we identified several factors influencing DfE. We also introduce a novel computational modeling framework, the memory for exemplars model (MEM-EX), which posits that decision makers rely on memory for previously experienced outcomes to make choices. Using MEM-EX, we demonstrate how several cognitive mechanisms provide intuitive and parsimonious explanations for the effects of value-ignorance, salience, outcome order, and sample size. We also conduct a cross-validation analysis of several models within the MEM-EX framework, as well as a baseline model built on principles of reinforcement-learning. We find that MEM-EX consistently outperforms this baseline, demonstrating its value as a tool for making quantitative predictions without overfitting. We discuss the implications of these findings on our understanding of the interplay between attention, memory, and experience-based choice

The Bayesian boom: good thing or bad?

A series of high-profile critiques of Bayesian models of cognition have recently sparked controversy. These critiques question the contribution of rational, normative considerations in the study of cognition. The present article takes central claims from these critiques and evaluates them in light of specific models. Closer consideration of actual examples of Bayesian treatments of different cognitive phenomena allows one to defuse these critiques showing that they cannot be sustained across the diversity of applications of the Bayesian framework for cognitive modeling. More generally, there is nothing in the Bayesian framework that would inherently give rise to the deficits that these critiques perceive, suggesting they have been framed at the wrong level of generality. At the same time, the examples are used to demonstrate the different ways in which consideration of rationality uniquely benefits both theory and practice in the study of cognition

Decision making in slow and rapid reaching : Sacrificing success to minimize effort

Acknowledgement This work was supported by the James S. McDonnell Foundation (Scholar Award to ARH). Supplementary Material Data available at: https://zenodo.org/record/3604284Peer reviewedPostprin

On a theorem of Y. Miyashita

Background: Portion size is an important driver of larger meals. However, effects on food choice remain unclear. Objective: Our aim was to identify how portion size influences the effect of palatability and expected satiety on choice. Methods: In Study 1, adult participants (n = 24, 87.5% women) evaluated the palatability and expected satiety of 5 lunchtime meals and ranked them in order of preference. Separate ranks were elicited for equicaloric portions from 100 to 800 kcal (100-kcal steps). In Study 2, adult participants (n = 24, 75% women) evaluated 9 meals and ranked 100–600 kcal portions in 3 contexts (scenarios), believing that 1) the next meal would be at 1900, 2) they would receive only a bite of one food, and 3) a favorite dish would be offered immediately afterwards. Regression analysis was used to quantify predictors of choice. Results: In Study 1, the extent to which expected satiety and palatability predicted choice was highly dependent on portion size (P < 0.001). With smaller portions, expected satiety was a positive predictor, playing a role equal to palatability (100-kcal portions: expected satiety, β: 0.42; palatability, β: 0.46). With larger portions, palatability was a strong predictor (600-kcal portions: β: 0.53), and expected satiety was a poor or negative predictor (600-kcal portions: β: −0.42). In Study 2, this pattern was moderated by context (P = 0.024). Results from scenario 1 replicated Study 1. However, expected satiety was a poor predictor in both scenario 2 (expected satiety was irrelevant) and scenario 3 (satiety was guaranteed), and palatability was the primary driver of choice across all portions. Conclusions: In adults, expected satiety influences food choice, but only when small equicaloric portions are compared. Larger portions not only promote the consumption of larger meals, but they encourage the adoption of food choice strategies motivated solely by palatability