Different Levels Of Task Difficulty Research Articles

Identifying inefficient strategies in automation-aided signal detection.

Automated diagnostic aids can assist human operators in signal detection tasks, providing alarms, warnings, or diagnoses. Operators often use decision aids poorly, though, falling short of best possible performance levels. Previous research has suggested that operators interact with binary signal detection aids using a sluggish contingent cutoff (CC) strategy (Robinson & Sorkin, 1985), shifting their response criterion in the direction stipulated by the aid's diagnosis each trial but making adjustments that are smaller than optimal. The present study tested this model by examining the efficiency of automation-aided signal detection under different levels of task difficulty. In a pair of experiments, participants performed a numeric decision-making task requiring them to make signal or noise judgments on the basis of probabilistic readings. The mean reading values of signal and noise states differed between groups of participants, producing two levels of task difficulty. Data were fit with the CC model and two alternative accounts of automation-aided strategy: a discrete deference (DD) model, which assumed participants defer to the aid on a subset of trials and a mixture model, which assumed that participants choose randomly between the CC and DD strategies every trial. Model fits favored the mixture model. The results indicate multiple forms of inefficiency in operators' strategies for using signal detection aids. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Rehabilitation Supported by Immersive Virtual Reality for Adults With Communication Disorders: Semistructured Interviews and Usability Survey Study.

Individuals who have acquired communication disorders often struggle to transfer the skills they learn during therapy sessions to real-life situations. Immersive virtual reality (VR) technology has the potential to create realistic communication environments that can be used both in clinical settings and for practice at home by individuals with communication disorders. This research aims to enhance our understanding of the acceptance, usefulness, and usability of a VR application (SIM:Kitchen), designed for communication rehabilitation. Additionally, this research aims to identify the perceived barriers and benefits of using VR technology from the perspective of individuals with acquired communication disorders. Semistructured interviews and usability surveys were conducted with 10 individuals with acquired neurogenic communication disorders aged 46-81 (mean 58, SD 9.57) years after trialing an immersive VR application. The audio-recorded interviews were transcribed and analyzed to identify themes. The quantitative data regarding the usability of the system associated with participants' immersion experience in the VR application were promising. Findings from semistructured interviews are discussed across five key thematic areas including (1) participant's attitude toward VR, (2) perceived usefulness of the VR system, (3) perceived ease of use of the VR system, (4) their willingness to continue using VR, and (5) the factors they perceived as challenges or facilitators to adopting this VR technology. Overall, participants in this study found the VR experience to be enjoyable and were impressed by the realism of the VR application designed for communication rehabilitation. This study highlighted personally relevant, immersive VR interventions with different levels of task difficulty that could enhance technology uptake in the context of communication rehabilitation. However, it is essential that VR hand controller technology is refined to be more naturalistic in movement and able to accommodate user capabilities.

Increased Risk of Falling in Older Adults When Coordinating Obstacle Avoidance and Grasping.

This study aimed to investigate the kinematic changes in obstacle avoidance and prehension tasks performed simultaneously by older adults with a history of falls at different levels of task difficulty. Twenty-six older adults were divided into faller and nonfaller groups. The experimental protocol was divided into two different tasks: walking with obstacle avoidance and walking with obstacle avoidance combined with a reach-to-grasp task. Two types of sensors (Kinect v2 and Leap Motion Controller, respectively) were used to analyze gait and grasp. Fallers presented kinematic changes associated with the grasping task during obstacle avoidance, such as a decrease in the velocity of the center of mass and the step length, an increase in the step width, a decrease in toe-obstacle horizontal distance, and an increase in vertical foot clearance distance, and an increase in movement time in the grasping task compared with nonfallers. To cope with the obstacle avoidance demands of both walking and grasping, fallers turned to a specific sequencing strategy. While slowing down, they attended first to the grasping task and then to crossing the obstacle on the floor.

Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty

Working memory, which is regarded as the foundation of cognitive processes, is a system that stores, processes, and manipulates information in short intervals of time that are actually needed for daily functioning. This study aimed to assess the brain activity of healthy controls (HC) while performing the N-back task, which is one of the most popularly used tests for evaluating working memory along with functional magnetic resonance imaging (fMRI). In this regard, we collected fMRI data from right-handed individuals in a 3.0 T scanner during the Persian version of the visual variant N-back task performance with three levels of complexity varied throughout the experiment (1, 2, and 3-back conditions) to increase the cognitive demands. The statistical parametric mapping (SPM12) software was used to analyze fMRI data for the identification of cognitive load-dependent activation patterns based on contrast images obtained from different levels of task difficulty. Our findings showed that as cognitive complexity increased, the number of significant activation clusters and cluster extent increased in several areas distributed in the cerebellum, frontoparietal lobes, insula, SMA, and lenticular nucleus, the majority of which are recognized for their role in working memory. Furthermore, deactivation patterns during 1-, 2-, and 3-back vs. 0-back contrasts revealed significant clusters in brain regions that are mostly described as being part of the default mode network (DMN). Based on previous research, our results supported the recognized involvement of the mentioned cortical and subcortical areas in various types or levels of N-back tasks. This study found that altering activation patterns by increasing task difficulty could aid in evaluating the various stages of cognitive dysfunction in many brain diseases such as multiple sclerosis (MS) and Alzheimer's disease by comparing controls in future studies to apply early appropriate treatment strategies.

Research on the influences of information presentation on information capture and performance in digital control systems

ABSTRACT This study investigates the effects of information presentation on operator performance in digital control systems at different levels of task difficulty in order to resolve the conflict between ‘large amounts of information’ and ‘limited display’. By using software to present figures of varying difficulty as target information, the operator’s behaviour such as page switching and target clicking is simulated to obtain data. Simultaneously, eye-tracking technique was used to analyse how the way information was presented at different levels of difficulty influenced the subjects’ search performance. The results show that subjects’ performance gradually decreases as the difficulty of the numbers grows for both presentations, and it is found that the complexity of the content of the navigation bar may have influenced the subjects to some extent. In addition, the different position of the navigation bar where the target is located will result in a change in the search pattern. It is noticeable that dividing the single page into double pages can effectively alleviate the contradiction of ‘large amount of information’ and ‘limited display’ in designing the system interface. Therefore, this study provides certain guideline value for the interface design of digital control systems.

Impact Analysis of Situation Awareness Based on a Multitasking Difficulty Quantitative Model

Situation awareness (SA) is a key indicator of operator task performance and behavioral safety in Human-Machine Interaction (HMI), and task difficulty is an important influencing factors in establishing and maintaining SA, especially in safety-critical scenarios such as flying and nuclear. However, the complexity and diversity of multitasking make it difficult to quantify task difficulty, which to a certain extent limits the research on cognitive research. To solve this problem, we proposed an approach to quantifying task difficulty in multitasking and analyzed the effect of task difficulty on different levels of SA through experiments in this paper. First, a task difficulty measure for a single meta-task was developed based on Shannon’s information theory, including both discrete and continuous meta-tasks. Next, a three-dimensional attribute model of meta-tasks was proposed to measure the difficulty value added by concurrent tasks based on multiple resource theory. Finally, an experiment was conducted to measure SA at different levels based on SAGAT, and SA under different levels of task difficulty was analyzed. The results showed a strong negative correlation between SA and task difficulty. Specifically, compared to SA at the comprehension and prediction levels, SA at the perceptual level was more easily influenced by task difficulty. This study can provide some reference for the quantify of task difficulty in human factors experiments, the optimization of tasks in HMI, and the selection of operator attention allocation strategies.

Nonlinear dynamics of EEG responses to unmanned vehicle visual detection with different levels of task difficulty

The main objective of this study was to examine the presence of chaos in the EEG recordings of brain activity under simulated unmanned ground vehicle visual detection scenarios with different levels of task difficulty. One hundred and fifty people participated in the experiment and completed four visual detection task scenarios: (1) change detection, (2) a threat detection task, (3) a dual-task with different change detection task rates, and (4) a dual-task with different threat detection task rates. We used the largest Lyapunov exponent and correlation dimension of the EEG data and performed 0–1 tests on the EEG data. The results revealed a change in the level of nonlinearity in the EEG data corresponding to different levels of cognitive task difficulty. The differences in EEG nonlinearity measures among the studied levels of task difficulty, as well as between a single task scenario and a dual-task scenario, have also been assessed. The results increase our understanding of the nature of unmanned systems' operational requirements.

Differential relationships between mathematics self-efficacy and national test performance according to perceived task difficulty

ABSTRACT We explore the effect of students’ perceived task difficulty on the mathematics self-efficacy – performance relationship. Specifically, we expand on previous reciprocal effects studies through including students’ self-efficacy for different levels of task difficulty in an empirical investigation. We examined students’ self-efficacy for easy, medium difficulty, and hard tasks and performance on a national mathematics test in a longitudinal study of 95 Norwegian students from grade 8 to grade 9. We found differential relationships between self-efficacy for different levels of task difficulty and national test performance. In support of the ‘skill development’ model, grade 8 national test performance predicted grade 9 self-efficacy for medium and hard, but not easy, tasks. While mastery experiences are likely to arise more easily on easier tasks, such experiences are likely to matter more on harder tasks. Our findings highlight the importance of supporting students’ engagement with challenging tasks to strengthen both their performance and self-efficacy.

Investigation of electroencephalography variations of mental workload in the exposure of the psychoacoustic in both male and female groups.

Most studies have examined the effect of the physical aspects of noise while the effect of exposure to psychoacoustic parameters at different task difficulty levels has been less evaluated. Therefore, this study was performed with the aim of investigating the brainwave in the face of psychoacoustic and the change of difficulty level of task. 120 persons were exposed to 16 psychoacoustic parameters (loudness, sharpness, roughness and fluctuation strength). Each person was asked to complete the three N-Back task difficulty levels. At the same time, brain waves were recorded and the subject completed the NASA-TLX questionnaire. Finally, brain indices including alpha1, alpha2, PrTeta, PrAlpha and EI were examined. With increasing loudness, sharpness and fluctuation, the alpha-1 and alpha-2 index (mental fatigue (increased. Loudness and roughness also increased the PrTeta and PrAlpha (annoyance). For the EI (Engagement Index), increasing fluctuation caused a decrease in the level of consciousness and engagement. In addition, exposure to psychoacoustic parameters at high and medium difficulty levels caused a greater effect on alpha, alpha2, PrTeta and PrAlpha indices. High level of difficulty task reduce the accuracy rate and increase the reaction time to stimuli in the N-Back task, and increase the mean of dimensions of the NASA-TLX questionnaire in the exposure of all psychoacoustic aspect.With increasing loudness, sharpness and fluctuation, the alpha-1 and alpha-2 index (mental fatigue (increased. Loudness and roughness also increased the PrTeta and PrAlpha (annoyance). For the EI (Engagement Index), increasing fluctuation caused a decrease in the level of consciousness and engagement. In addition, exposure to psychoacoustic parameters at high and medium difficulty levels caused a greater effect on alpha, alpha2, PrTeta and PrAlpha indices. High level of difficulty task reduce the accuracy rate and increase the reaction time to stimuli in the N-Back task, and increase the mean of dimensions of the NASA-TLX questionnaire in the exposure of all psychoacoustic aspect. Considering the effect of psychoacoustic at different levels of task difficulty on the mental load and cognitive function is essential to prevent damage to the person and his performance.

Does the Effect of Stereotypes in Older People Depend Upon Task Intensity?

This study examined the effect of negative and positive stereotypes on the strength produced by older adults at different perceived effort intensities, reflecting different levels of task difficulty. Fifty older women were randomly assigned to a positive stereotype, a negative stereotype, or a control condition. Before (T1) and after (T2) the stereotype manipulation, they were asked to perform a voluntary isometric contraction at a level of muscular effort that corresponded to four perceived effort intensities ("easy," "moderate," hard" and "very hard"). Results showed that participants attained greater strength during the easy and hard tasks after exposure to both positive and negative stereotypes. At the moderate and very hard intensities, stereotype induction did not significantly change the strength from the baseline performance. While these results are not fully in line with the stereotype threat theory, they provide evidence that task difficulty could modulate the effect of aging stereotypes during physical tasks.

Correlation Between Physiological and Performance-Based Metrics to Estimate Pilots' Cognitive Workload.

This paper discusses the utilization of pilots' physiological indications such as electroencephalographic (EEG) signals, ocular parameters, and pilot performance-based quantitative metrics to estimate cognitive workload. The study aims to derive a non-invasive technique to estimate pilot's cognitive workload and study their correlation with standard physiological parameters. Initially, we conducted a set of user trials using well-established psychometric tests for evaluating the effectiveness of pupil and gaze-based ocular metrics for estimating cognitive workload at different levels of task difficulty and lighting conditions. Later, we conducted user trials with the NALSim flight simulator using a business class Learjet aircraft model. We analyzed participants' ocular parameters, power levels of different EEG frequency bands, and flight parameters for estimating variations in cognitive workload. Results indicate that introduction of secondary task increases pilot's cognitive workload significantly. The beta frequency band of EEG, nearest neighborhood index specifying distribution of gaze fixation, L1 Norm of power spectral density of pupil diameter, and the duty cycle metric indicated variations in cognitive workload.

Effects of balance training on balance performance in youth: role of training difficulty

BackgroundCross-sectional studies have shown that balance performance can be challenged by the level of task difficulty (e.g., varying stance conditions, sensory manipulations). However, it remains unclear whether the application of different levels of task difficulty during balance training (BT) leads to altered adaptations in balance performance. Thus, we examined the effects of BT conducted under a high versus a low level of task difficulty on balance performance.MethodsForty male adolescents were randomly assigned to a BT program using a low (BT-low: n = 20; age: 12.4 ± 2.0 yrs) or a high (BT-high: n = 20; age: 12.5 ± 2.5 yrs) level of balance task difficulty. Both groups trained for 7 weeks (2 sessions/week, 30–35 min each). Pre- and post-training assessments included measures of static (one-legged stance [OLS] time), dynamic (10-m gait velocity), and proactive (Y-Balance Test [YBT] reach distance, Functional Reach Test [FRT]; Timed-Up-and-Go Test [TUG]) balance.ResultsSignificant main effects of Test (i.e., pre- to post-test improvements) were observed for all but one balance measure (i.e., 10-m gait velocity). Additionally, a Test x Group interaction was detected for the FRT in favor of the BT-high group (Δ + 8%, p < 0.001, d = 0.35). Further, tendencies toward significant Test x Group interactions were found for the YBT anterior reach (in favor of BT-high: Δ + 9%, p < 0.001, d = 0.60) and for the OLS with eyes opened and on firm surface (in favor of BT-low: Δ + 31%, p = 0.003, d = 0.67).ConclusionsFollowing 7 weeks of BT, enhancements in measures of static, dynamic, and proactive balance were observed in the BT-high and BT-low groups. However, BT-high appears to be more effective for increasing measures of proactive balance, whereas BT-low seems to be more effective for improving proxies of static balance.Trial registrationCurrent Controlled Trials ISRCTN83638708 (Retrospectively registered 19th June, 2020).

Effects of Performance and Task Duration on Mental Workload during Working Memory Task

N-back is a working memory (WM) task to study mental workload on the prefrontal cortex (PFC). We assume that the subject’s performance and changes in mental workload over time depends on the length of the experiment. The performance of the participant can change positively due to the participant’s learning process or negatively because of objective mental fatigue and/or sleepiness. In this pilot study, we examined the PFC activation of 23 healthy subjects while they performed an N-back task with two different levels of task difficulty (2-, and 3-back). The hemodynamic responses were analyzed along with the behavioral data (correct answers). A comparison was done between the hemodynamic activation and behavioral data between the two different task levels and between the beginning and end of the 3-back task. Our results show that there is a significant difference between the two task levels, which is due to the difference in task complication. In addition, a significant difference was seen between the beginning and end of the 3-back task in both behavioral data and hemodynamics due to the subject’s learning process throughout the experiment.

Effects of noise on mental performance and annoyance considering task difficulty level and tone components of noise.

Rotating components in mechanical systems produce tonal noises and the presence of these tones effect the quality and comfort of occupants leading to annoyance and a decrease in mental performance. The ISO 1996-2 and ANSI S1.13 standards have described metrics to quantify the effects of prominent tones, but more research on how noise attributes effect annoyance and performance, especially in different levels of task difficulty are necessary. This paper investigates relations between noise metrics, annoyance responses and mental performance under different task difficulty levels while exposed to background noise with tonal components. In this study, sixty participants were evaluated on subjective perceived annoyance and varying workloads while exposed to 18 noise signals with three different prominence tones at three frequency tones and two background noise levels while doing three different levels of n-back tasks in a controlled test chamber. Performance parameters were measured by recording the reaction time, the correct rate, and the number of misses. The results indicate an increasing trend for number of misses and reaction times at higher task difficulty levels, but a decrease for correct rate. The study results showed a significant difference for subjective responses except for annoyance and loudness under different levels of task difficulty. The participants were more annoyed with higher background noise levels, lower tone frequencies and increasing tone levels especially under increasing task difficulty. Loudness metrics highly correlate with other noise metrics. Three models for the prediction of perceived annoyance are presented based on the most strongly correlated noise metrics using neural network models. Each of the three models had different input parameters and different network structures. The accuracy and MSE of all three neural network models show it to be appropriate for predicting perceived annoyance. The results show the effect of tonal noise on annoyance and mental performance especially in different levels of task difficulty. The results also suggest that neural network models have high accuracy and efficiency, and can be used to predict noise annoyance. Model 1 is preferred in certain aspects, such as lower input parameters, making it more user-friendly. The best neural network model included both loudness metrics and tonality metrics. It seems that combined metrics have the least importance and are unnecessary in the proposed neural network model.

Decoding go/no-go decisions from eye movements.

Neural activity in brain areas involved in the planning and execution of eye movements predicts the outcome of an upcoming perceptual decision. Many real-world decisions, such as whether to swing at a baseball pitch, are accompanied by characteristic eye-movement behavior. Here we ask whether human eye-movement kinematics can sensitively predict decision outcomes in a go/no-go task requiring rapid interceptive hand movements. Observers (n = 45) viewed a moving target that passed through or missed a designated strike box. Critically, the target disappeared briefly after launch, and observers had to predict the target's trajectory, withholding a hand movement if it missed (no-go) or intercepting inside the strike box (go). We found that go/no-go decisions were reflected in distinct eye-movement responses on a trial-by-trial basis: Eye-position error and targeting-saccade dynamics predicted decision outcome with 76% accuracy across conditions. Model prediction accuracy was related to observers' decision accuracy across different levels of task difficulty and sensory-signal strength. Our findings suggest that eye movements provide a sensitive and continuous readout of internal neural decision-making processes and reflect decision-task requirements in human observers.

EEG Correlates of the Flow State: A Combination of Increased Frontal Theta and Moderate Frontocentral Alpha Rhythm in the Mental Arithmetic Task

Flow experience is a subjective state experienced during holistic involvement in a certain activity, which has been reported to function as a factor promoting motivation, skill development, and better performance in the activity. To verify the positive effects of flow and develop a method to utilize it, the establishment of a reliable measurement of the flow state is essential. The present study utilized an electroencephalogram (EEG) during an experimentally evoked flow state and examined the possibility of objective measurement of immediate flow. A total of 16 participants (10 males, 6 females) participated in the experiment that employed a mental arithmetic task developed in a previous study. Post-trial self-report of the flow state and EEG during task execution were measured and compared among three conditions (Boredom, Flow, and Overload) that had different levels of task difficulty. Furthermore, the correlations between subjective flow items and EEG activity were examined. As expected, the ratings on the subjective evaluation items representing the flow state were the highest in the Flow condition. Regarding the EEG data, theta activities in the frontal areas were higher in the Flow and the Overload conditions than in the Boredom condition, and alpha activity in the frontal areas and the right central area gradually increased depending on the task difficulty. These EEG activities correlated with self-reported flow experience, especially items related to the concentration on the task and task difficulty. From the results, the flow state was characterized by increased theta activities in the frontal areas and moderate alpha activities in the frontal and central areas. The former may be related to a high level of cognitive control and immersion in task, and the latter suggests that the load on the working memory was not excessive. The findings of this study suggest the possibility of distinguishing the flow state from other states using multiple EEG activities and indicate the need for other physiological indicators corresponding to the other aspects of flow experience.

Cognitive Load Reduces Perceived Linguistic Convergence Between Dyads.

Speech convergence is the tendency of talkers to become more similar to someone they are listening or talking to, whether that person is a conversational partner or merely a voice heard repeating words. To elucidate the nature of the mechanisms underlying convergence, this study uses different levels of task difficulty on speech convergence within dyads collaborating on a task. Dyad members had to build identical LEGO® constructions without being able to see each other's construction, and with each member having half of the instructions required to complete the construction. Three levels of task difficulty were created, with five dyads at each level (30 participants total). Task difficulty was also measured using completion time and error rate. Listeners who heard pairs of utterances from each dyad judged convergence to be occurring in the Easy condition and to a lesser extent in the Medium condition, but not in the Hard condition. Amplitude envelope acoustic similarity analyses of the same utterance pairs showed that convergence occurred in dyads with shorter completion times and lower error rates. Together, these results suggest that while speech convergence is a highly variable behavior, it may occur more in contexts of low cognitive load. The relevance of these results for the current automatic and socially-driven models of convergence is discussed.

Emotion perception in adult attention-deficit hyperactivity disorder.

This study examined identification of emotional information in facial expression, prosody, and their combination in 23 adult patients with combined attention deficit-hyperactivity disorder (ADHD) versus 31 healthy controls (HC) matched for gender, age, and education. We employed a stimulus set which was carefully balanced for valence as well as recognizability of the expressed emotions as determined in an independent sample of HC to avoid potential biases due to different levels of task difficulty. ADHD patients were characterized by impaired recognition of all employed categories (neutral, happiness, eroticism, disgust, anger). Basic cognitive functions as assessed by neuropsychological testing, such as sustained attention, constancy of alertness, and verbal intelligence partially explained lower recognition rates. Removal of the correlated variance by means of regression analyses did not abolish lower performance in ADHD indicating deficits in social cognition independent of these neuropsychological factors (p<0.05). Lower performance correlated with self-rated emotional intelligence (r=0.38, p<0.05) indicating that adults with ADHD are aware of their problems in emotion perception. ADHD patients could partly compensate their deficit in unimodal emotion perception by audiovisual integration as revealed by larger gains in emotion recognition accuracy during bimodal presentation (p<0.05) as compared to HC. These behavioral results can serve as foundation for future neuroimaging studies and point rather towards sensory-specific regions than audiovisual integration areas in perception of emotional information in adult ADHD.

EEG-based prediction of cognitive workload induced by arithmetic: a step towards online adaptation in numerical learning

Numeracy is a key competency for living in our modern knowledge society. Therefore, it is essential to support numerical learning from basic to more advanced competency levels. From educational psychology it is known that learning is most effective when the respective content is neither too easy nor too demanding in relation to learners’ prerequisites. However, so far it is difficult to assess individual’s cognitive workload independently from performance to adapt learning environments accordingly. In the present study, we aim at identifying learners’ cognitive workload induced by addition tasks of varying difficulty using electroencephalography (EEG). To this end, a classifier using specific features in the EEG-signal is trained to differentiate between different levels of task difficulty significantly above chance level and with high consistency over all participants. Importantly, our model even allows for the prediction of cognitive demands induced by the addition tasks in a cross-participant approach. Closer inspection of the crucial EEG features indicates that oscillations in the theta and alpha band recorded from parietal electrodes are most reflective of current task difficulty. In summary, we are able to differentiate cognitive workload of participants independently from performance based on data of only a small number of electrodes. This suggests that a reduced EEG-setup combined with cross-participant classification may be a feasible approach to assess learners’ cognitive workload.

Re-encountering individuals who previously engaged in joint gaze modulates subsequent gaze cueing.

We assessed the extent to which previous experience of joint gaze with people (i.e., looking toward the same object) modulates later gaze cueing of attention elicited by those individuals. Participants in Experiments 1 and 2a/b first completed a saccade/antisaccade task while a to-be-ignored face either looked at, or away from, the participants' eye movement target. Two faces always engaged in joint gaze with the participant, whereas 2 other faces never engaged in joint gaze. Then, we assessed standard gaze cueing in response to these faces to ascertain the effect of these prior interactions on subsequent social attention episodes. In Experiment 1, the face's eyes moved before the participant's target appeared, meaning that the participant always gaze-followed 2 faces and never gaze-followed 2 other faces. We found that this prior experience modulated the timecourse of subsequent gaze cueing. In Experiments 2a/b, the participant looked at the target first, then was either followed (i.e., the participant initiated joint gaze), or was not followed. These participants then showed an overall decrement of gaze cueing with individuals who had previously followed participants' eyes (Experiment 2a), an effect that was associated with autism spectrum quotient scores and modulated perceived trustworthiness of the faces (Experiment 2b). Experiment 3 demonstrated that these modulations are unlikely to be because of the association of different levels of task difficulty with particular faces. These findings suggest that establishing joint gaze with others influences subsequent social attention processes that are generally thought to be relatively insensitive to learning from prior episodes.