Response time modelling reveals evidence for multiple, distinct sources of moral decision caution.

People are often cautious in delivering moral judgements of others' behaviours, as falsely accusing others of wrongdoing can be costly for social relationships. Caution might further be present when making judgements in information-dynamic environments, as contextual updates can change our minds. This study investigated the processes with which moral valence and context expectancy drive caution in moral judgements. Across two experiments, participants (N = 122) made moral judgements of others' sharing actions. Prior to judging, participants were informed whether contextual information regarding the deservingness of the recipient would follow. We found that participants slowed their moral judgements when judging negatively valenced actions and when expecting contextual updates. Using a diffusion decision model framework, these changes were explained by shifts in drift rate and decision bias (valence) and boundary setting (context), respectively. These findings demonstrate how moral decision caution can be decomposed into distinct aspects of the unfolding decision process.

Tracking dynamic adjustments to decision making and performance monitoring processes in conflict tasks.

How we exert control over our decision-making has been investigated using conflict tasks, which involve stimuli containing elements that are either congruent or incongruent. In these tasks, participants adapt their decision-making strategies following exposure to incongruent stimuli. According to conflict monitoring accounts, conflicting stimulus features are detected in medial frontal cortex, and the extent of experienced conflict scales with response time (RT) and frontal theta-band activity in the Electroencephalogram (EEG). However, the consequent adjustments to decision processes following response conflict are not well-specified. To characterise these adjustments and their neural implementation we recorded EEG during a modified Flanker task. We traced the time-courses of performance monitoring processes (frontal theta) and multiple processes related to perceptual decision-making. In each trial participants judged which of two overlaid gratings forming a plaid stimulus (termed the S1 target) was of higher contrast. The stimulus was divided into two sections, which each contained higher contrast gratings in either congruent or incongruent directions. Shortly after responding to the S1 target, an additional S2 target was presented, which was always congruent. Our EEG results suggest enhanced sensory evidence representations in visual cortex and reduced evidence accumulation rates for S2 targets following incongruent S1 stimuli. Results of a follow-up behavioural experiment indicated that the accumulation of sensory evidence from the incongruent (i.e. distracting) stimulus element was adjusted following response conflict. Frontal theta amplitudes positively correlated with RT following S1 targets (in line with conflict monitoring accounts). Following S2 targets there was no such correlation, and theta amplitude profiles instead resembled decision evidence accumulation trajectories. Our findings provide novel insights into how cognitive control is implemented following exposure to conflicting information, which is critical for extending conflict monitoring accounts.

Perceptual change-of-mind decisions are sensitive to absolute evidence magnitude.

To navigate the world safely, we often need to rapidly 'change our mind' about decisions. Current models assume that initial decisions and change-of-mind decisions draw upon common sources of sensory evidence. In two-choice scenarios, this evidence may be 'relative' or 'absolute'. For example, when judging which of two objects is the brightest, the luminance difference and luminance ratio between the two objects are sources of 'relative' evidence, which are invariant across additive and multiplicative luminance changes. Conversely, the overall luminance of the two objects combined is a source of 'absolute' evidence, which necessarily varies across symmetric luminance manipulations. Previous studies have shown that initial decisions are sensitive to both relative and absolute evidence; however, it is unknown whether change-of-mind decisions are sensitive to absolute evidence. Here, we investigated this question across two experiments. In each experiment participants indicated which of two flickering greyscale squares was brightest. Following an initial decision, the stimuli remained on screen for a brief period and participants could change their response. To investigate the effect of absolute evidence, the overall luminance of the two squares was varied whilst either the luminance difference (Experiment 1) or luminance ratio (Experiment 2) was held constant. In both experiments we found that increases in absolute evidence led to faster, less accurate initial responses and slower changes of mind. Change-of-mind accuracy decreased when the luminance difference was held constant, but remained unchanged when the luminance ratio was fixed. We show that the three existing change-of-mind models cannot account for our findings. We then fit three alternative models, previously used to account for the effect of absolute evidence on one-off decisions, to the data. A leaky competing accumulator model best accounted for the changes in behaviour across absolute evidence conditions - suggesting an important role for input-dependent leak in explaining perceptual changes of mind.

Neural correlates of cue-induced changes in decision-making distinguish subjects with gambling disorder from healthy controls.

In addiction, there are few human studies on the neural basis of cue-induced changes in value-based decision making (Pavlovian-to-instrumental transfer, PIT). It is especially unclear whether neural alterations related to PIT are due to the physiological effects of substance abuse or rather related to learning processes and/or other etiological factors related to addiction. We have thus investigated whether neural activation patterns during a PIT task help to distinguish subjects with gambling disorder (GD), a nonsubstance-based addiction, from healthy controls (HCs). Thirty GD and 30 HC subjects completed an affective decision-making task in a functional magnetic resonance imaging (fMRI) scanner. Gambling-associated and other emotional cues were shown in the background during the task. Data collection and feature modeling focused on a network of nucleus accumbens (NAcc), amygdala, and orbitofrontal cortex (OFC) (derived from PIT and substance use disorder [SUD] studies). We built and tested a linear classifier based on these multivariate neural PIT signatures. GD subjects showed stronger PIT than HC subjects. Classification based on neural PIT signatures yielded a significant area under the receiver operating curve (AUC-ROC) (0.70, p = 0.013). GD subjects showed stronger PIT-related functional connectivity between NAcc and amygdala elicited by gambling cues, as well as between amygdala and OFC elicited by negative and positive cues. HC and GD subjects were thus distinguishable by PIT-related neural signatures including amygdala-NAcc-OFC functional connectivity. Neural PIT alterations in addictive disorders might not depend on the physiological effect of a substance of abuse but on related learning processes or even innate neural traits.

Moral judgements of fairness-related actions are flexibly updated to account for contextual information.

In everyday life we are constantly updating our moral judgements as we learn new information. However, this judgement updating process has not been systematically studied. We investigated how people update their moral judgements of fairness-related actions of others after receiving contextual information regarding the deservingness of the action recipient. Participants (N = 313) observed a virtual 'Decision-maker' share a portion of $10 with a virtual 'Receiver'. Participants were aware that the Decision-maker made these choices knowing the Receiver's previous offer to another person. Participants first made a context-absent judgement of the Decision-maker's offer to the Receiver, and then a subsequent context-present judgement of the same offer after learning the Receiver's previous offer. This sequence was repeated for varying dollar values of Decision-makers' and Receivers' offers. Patterns of judgements varied across individuals and were interpretable in relation to moral norms. Most participants flexibly switched from relying on context-independent norms (generosity, equality) to related, context-dependent norms (relative generosity, indirect reciprocity) as they integrated contextual information. Judgement of low offers varied across individuals, with a substantial minority of participants withholding their context-absent judgements of selfishness, and another minority that was lenient towards selfishness across both judgements. Our paradigm provides a novel framework for investigating how moral judgements evolve in real time as people learn more information about a given situation.

Cue-induced effects on decision-making distinguish subjects with gambling disorder from healthy controls.

While an increased impact of cues on decision-making has been associated with substance dependence, it is yet unclear whether this is also a phenotype of non-substance-related addictive disorders, such as gambling disorder (GD). To better understand the basic mechanisms of impaired decision-making in addiction, we investigated whether cue-induced changes in decision-making could distinguish GD from healthy control (HC) subjects. We expected that cue-induced changes in gamble acceptance and specifically in loss aversion would distinguish GD from HC subjects. Thirty GD subjects and 30 matched HC subjects completed a mixed gambles task where gambling and other emotional cues were shown in the background. We used machine learning to carve out the importance of cue dependency of decision-making and of loss aversion for distinguishing GD from HC subjects. Cross-validated classification yielded an area under the receiver operating curve (AUC-ROC) of 68.9% (p = .002). Applying the classifier to an independent sample yielded an AUC-ROC of 65.0% (p = .047). As expected, the classifier used cue-induced changes in gamble acceptance to distinguish GD from HC. Especially, increased gambling during the presentation of gambling cues characterized GD subjects. However, cue-induced changes in loss aversion were irrelevant for distinguishing GD from HC subjects. To our knowledge, this is the first study to investigate the classificatory power of addiction-relevant behavioral task parameters when distinguishing GD from HC subjects. The results indicate that cue-induced changes in decision-making are a characteristic feature of addictive disorders, independent of a substance of abuse.

Individual differences in social desirability are associated with white-matter microstructure of the external capsule.

Humans tend to present themselves in a positive light to gain social approval. This behavioral trait, termed social desirability, is important for various types of social success. Surprisingly, investigation into the neural underpinnings of social desirability has been limited and focused only on interindividual differences in dopamine receptor binding. These studies revealed reduced dopamine receptor binding in the striatum of individuals who are high in trait social desirability. Interestingly, high dopamine signaling has been associated with low white-matter integrity, irrespective of social desirability. Based on these findings, we hypothesized that a positive association exists between trait social desirability and the white-matter microstructure of the external capsule, which carries fibers to the striatum from the prefrontal cortex. To test this hypothesis, we collected diffusion tensor imaging data and examined the relationship between fractional anisotropy of the external capsule and participants' social desirability-our analysis revealed a positive association. As a second exploratory step, we examined the association between social desirability and white-matter microstructure throughout the whole brain. Our whole-brain analysis revealed associations within multiple major white-matter tracts, demonstrating that socially desirable behavior relies on connectivity between distributed brain regions.