Cognitive effort investment: Does disposition become action?

Contrary to the law of less work, individuals with high levels of need for cognition and self-control tend to choose harder tasks more often. While both traits can be integrated into a core construct of dispositional cognitive effort investment, its relation to actual cognitive effort investment remains unclear. As individuals with high levels of cognitive effort investment are characterized by a high intrinsic motivation towards effortful cognition, they would be less likely to increase their effort based on expected payoff, but rather based on increasing demand. In the present study, we measured actual effort investment on multiple dimensions, i.e., subjective load, reaction time, accuracy, early and late frontal midline theta power, N2 and P3 amplitude, and pupil dilation. In a sample of N = 148 participants, we examined the relationship of dispositional cognitive effort investment and effort indices during a flanker and an n-back task with varying demand and payoff. Exploratorily, we examined this relationship for the two subdimensions cognitive motivation and effortful-self-control as well. In both tasks, effort indices were sensitive to demand and partly to payoff. The analyses revealed a main effect of cognitive effort investment for accuracy (n-back task), interaction effects with payoff for reaction time (n-back and flanker task) and P3 amplitude (n-back task) and demand for early frontal midline theta power (flanker task). Taken together, our results partly support the notion that individuals with high levels of cognitive effort investment exert effort more efficiently. Moreover, the notion that these individuals exert effort regardless of payoff is partly supported, too. This may further our understanding of the conditions under which person-situation interactions occur, i.e. the conditions under which situations determine effort investment in goal-directed behavior more than personality, and vice versa.

Associations between hair cortisol and subjective stress measures in a large occupational sample.

BACKGROUND: Hair cortisol concentrations (HCC) are commonly used to capture long-term cumulative cortisol secretion in stress research. However, data on associations between HCC and subjective stress measures have been inconsistent. This may partly be due to bias introduced by smaller-sized academic samples. Here, we investigate associations between HCC and (work-) stress-related measures in a large occupational, predominantly male, sample. METHODS: Demographic, anthropometric, and self-reported data were collected as part of an occupational health assessment for employees of an airplane manufacturing company (N = 1258). Hair samples (3 cm) were obtained and glucocorticoid concentrations (HCC and hair cortisone, HairE) were analyzed using liquid chromatography-tandem mass spectrometry. RESULTS: HCC and HairE were unrelated to self-report measures of perceived stress, work-related stress (effort-reward imbalance, overcommitment), and other stress-related constructs. Group-based analyses concerning associations with job strain revealed a small effect of individuals with high job strain (n = 281) exhibiting higher HCC than the remaining sample (n = 811). CONCLUSIONS: Our data replicate previous findings of no consistent associations between hair glucocorticoids and subjective stress-related questionnaire data, besides evidence for elevated HCC in a high job strain group. Further research addressing open methodological questions regarding HCC by means of advanced stress assessment methods is needed.

Simulation-based learning influences real-life attitudes.

Humans can vividly simulate hypothetical experiences. This ability draws on our memories (e.g., of familiar people and locations) to construct imaginings that resemble real-life events (e.g., of meeting a person at a location). Here, we examine the hypothesis that we also learn from such simulated episodes much like from actual experiences. Specifically, we show that the mere simulation of meeting a familiar person (unconditioned stimulus; US) at a known location (conditioned stimulus; CS) changes how people value the location. We provide key evidence that this simulation-based learning strengthens pre-existing CS-US associations and that it leads to a transfer of valence from the US to the CS. The data thus highlight a mechanism by which we learn from simulated experiences.

Dispositional cognitive effort investment and behavioral demand avoidance: Are they related?

Individuals tend to avoid cognitive demand, yet, individual differences appear to exist. Recent evidence from two studies suggests that individuals high in the personality traits Self-Control and Need for Cognition that are related to the broader construct Cognitive Effort Investment are less prone to avoid cognitive demand and show less effort discounting. These findings suggest that cost-benefit models of decision-making that integrate the costs due to effort should consider individual differences in the willingness to exert mental effort. However, to date, there are almost no replication attempts of the above findings. For the present conceptual replication, we concentrated on the avoidance of cognitive demand and used a longitudinal design and latent state-trait modeling. This approach enabled us to separate the trait-specific variance in our measures of Cognitive Effort Investment and Demand Avoidance that is due to stable, individual differences from the variance that is due to the measurement occasion, the methods used, and measurement error. Doing so allowed us to test the assumption that self-reported Cognitive Effort Investment is related to behavioral Demand Avoidance more directly by relating their trait-like features to each other. In a sample of N = 217 participants, we observed both self-reported Cognitive Effort Investment and behavioral Demand Avoidance to exhibit considerable portions of trait variance. However, these trait variances were not significantly related to each other. Thus, our results call into question previous findings of a relationship between self-reported effort investment and demand avoidance. We suggest that novel paradigms are needed to emulate real-world effortful situations and enable better mapping between self-reported measures and behavioral markers of the willingness to exert cognitive effort.

Forming attitudes via neural activity supporting affective episodic simulations.

Humans have the adaptive capacity for imagining hypothetical episodes. Such episodic simulation is based on a neural network that includes the ventromedial prefrontal cortex (vmPFC). This network draws on existing knowledge (e.g., of familiar people and places) to construct imaginary events (e.g., meeting with the person at that place). Here, we test the hypothesis that a simulation changes attitudes towards its constituent elements. In two experiments, we demonstrate how imagining meeting liked versus disliked people (unconditioned stimuli, UCS) at initially neutral places (conditioned stimuli, CS) changes the value of these places. We further provide evidence that the vmPFC codes for representations of those elements (i.e., of individual people and places). Critically, attitude changes induced by the liked UCS are based on a transfer of positive affective value between the representations (i.e., from the UCS to the CS). Thereby, we reveal how mere imaginings shape attitudes towards elements (i.e., places) from our real-life environment.

An adaptive function of mental time travel: Motivating farsighted decisions.

The episodic memory system allows us to experience the emotions of past, counterfactual, and prospective events. We outline how this phenomenological experience can convey motivational incentives for farsighted decisions. In this way, we challenge important arguments for Mahr & Csibra's (M&C's) conclusion that future-oriented mental time travel is unlikely to be a central function of episodic memory.

Modeling fear-conditioned bradycardia in humans.

Across species, cued fear conditioning is a common experimental paradigm to investigate aversive Pavlovian learning. While fear-conditioned stimuli (CS+) elicit overt behavior in many mammals, this is not the case in humans. Typically, autonomic nervous system activity is used to quantify fear memory in humans, measured by skin conductance responses (SCR). Here, we investigate whether heart period responses (HPR) evoked by the CS, often observed in humans and small mammals, are suitable to complement SCR as an index of fear memory in humans. We analyze four datasets involving delay and trace conditioning, in which heart beats are identified via electrocardiogram or pulse oximetry, to show that fear-conditioned heart rate deceleration (bradycardia) is elicited and robustly distinguishes CS+ from CS-. We then develop a psychophysiological model (PsPM) of fear-conditioned HPR. This PsPM is inverted to yield estimates of autonomic input into the heart. We show that the sensitivity to distinguish CS+ and CS- (predictive validity) is higher for model-based estimates than peak-scoring analysis, and compare this with SCR. Our work provides a novel tool to investigate fear memory in humans that allows direct comparison between species.

Modeling event-related heart period responses.

Cardiac rhythm is generated locally in the sinoatrial node, but modulated by central neural input. This may provide a possibility to infer central processes from observed phasic heart period responses (HPR). Currently, operational methods are used for HPR analysis. These methods embody implicit assumptions on how central states influence heart period. Here, we build an explicit psychophysiological model (PsPM) for event-related HPR. This phenomenological PsPM is based on three experiments involving white noise sounds, an auditory oddball task, and emotional picture viewing. The model is optimized with respect to predictive validity-the ability to separate experimental conditions from each other. To validate the PsPM, an independent sample of participants is presented with auditory stimuli of varying intensity and emotional pictures of negative and positive valence, at short intertrial intervals. Our model discriminates these experimental conditions from each other better than operational approaches. We conclude that our PsPM is more sensitive to distinguish experimental manipulations based on heart period data than operational methods, and furnishes a principled approach to analysis of HPR.