Gauging response time distributions to examine the effect of facial expression inversion

Introduction

We used images of facial expressions (FEs) of emotion in a speeded Same/Different task to examine (i) distributional characteristics of response times (RTs) in relation to inter-stimulus similarity and (ii) the impact of inversion on FE processing.

Methods

Stimuli were seven emotion prototypes, posed by one male and one female, and eight intermediate morphs. Image pairs (N = 225) were presented for 500 ms, upright or inverted, in a block design, each 100 times.

Results

For both upright and inverted FEs, RTs were a non-monotonic function: median values were longest for stimulus pairs of intermediate similarity, decreasing for both more-dissimilar and more-similar pairs. RTs of "Same" and "Different" judgments followed ex-Gaussian distributions. The non-monotonicity is interpreted within a dual-process decision model framework as reflecting the infrequency of identical pairs, shifting the balance between the Same and Different processes. The effect of stimulus inversion was gauged by comparing RT-based multidimensional scaling solutions for the two presentation modes. Solutions for upright and inverted FEs showed little difference, with both displaying some evidence of categorical perception. The same features appeared in hierarchical clustering solutions.

Discussion

This outcome replicates and reinforces the solutions derived from accuracy of "Different" responses reported in our earlier companion paper. We attribute this lack of inversion effect to the brief exposure time, allowing low-level visual processing to dominate Same/Different decisions while elevating early featural analysis, which is insensitive to face orientation but enables initial positive/negative valence categorization of FEs.

Head Motion During MRI Predicted by out-of-Scanner Sustained Attention Performance in Attention-Deficit/Hyperactivity Disorder

Objective: To characterize head movements in children with ADHD using an ex-Gaussian distribution and examine associations with out-of-scanner sustained attention. Method: Fifty-six children with ADHD and 61 controls aged 9 to 11 years completed the Sustained Attention to Response Task (SART) and resting-state functional magnetic resonance imaging (fMRI). In-scanner head motion was calculated using ex-Gaussian estimates for mu, sigma, and tau in delta variation signal and framewise displacement. Sustained attention was evaluated through omission errors and tau in response time on the SART. Results: Mediation analysis revealed that out-of-scanner attention lapses (omissions during the SART) mediated the relationship between ADHD diagnosis and in-scanner head motion (tau in delta variation signal), indirect effect: B = 1.29, 95% confidence interval (CI) = [0.07, 3.15], accounting for 29% of the association. Conclusion: Findings suggest a critical link between trait-level sustained attention and infrequent large head movements during scanning (tau in head motion) and highlight fundamental challenges in measuring the neural basis of sustained attention.

Decomposing the composite face effect: Evidence for non-holistic processing based on the ex-Gaussian distribution

Composite faces fuse the top and bottom halves from two different faces to create a powerful illusion of a novel face. It has been argued that composite faces are processed holistically, namely that the constituent face parts are perceived as a template, rather than independent features. This study sought to uncover the locus of the composite face effect by relating its empirical reaction time distributions to theoretical ex-Gaussian parameters. The results showed that the composite face effect for unfamiliar (Experiment 1) and familiar (Experiment 2) faces is generated by pure changes in the exponential component of the ex-Gaussian distribution. This held true for both partial and complete design measures. The exponential component has been attributed to working memory and attentional processes. The results suggest the involvement of attentional and working memory processes in the composite face effect and in the perception of faces in general. They cast doubts on the holistic nature of face processing. The results also provide important constraints on future computational theories of the effect.

Asymmetry in serial femtosecond crystallography data

Distribution analysis of intensity observations in serial femtosecond crystallography data processing helps to separate Bragg reflections from the background detector response.

Serial crystallography is an increasingly important approach to protein crystallography that exploits both X-ray free-electron laser (XFEL) and synchrotron radiation. Serial crystallography recovers complete X-ray diffraction data by processing and merging diffraction images from thousands of randomly oriented non-uniform microcrystals, of which all observations are partial Bragg reflections. Random fluctuations in the XFEL pulse energy spectrum, variations in the size and shape of microcrystals, integrating over millions of weak partial observations and instabilities in the XFEL beam position lead to new types of experimental errors. The quality of Bragg intensity estimates deriving from serial crystallography is therefore contingent upon assumptions made while modeling these data. Here it is observed that serial femtosecond crystallography (SFX) Bragg reflections do not follow a unimodal Gaussian distribution and it is recommended that an idealized assumption of single Gaussian peak profiles be relaxed to incorporate apparent asymmetries when processing SFX data. The phenomenon is illustrated by re-analyzing data collected from microcrystals of the Blastochloris viridis photosynthetic reaction center and comparing these intensity observations with conventional synchrotron data. The results show that skewness in the SFX observations captures the essence of the Wilson plot and an empirical treatment is suggested that can help to separate the diffraction Bragg intensity from the background.

Atomoxetine could improve intra-individual variability in drug-naïve adults with attention-deficit/hyperactivity disorder comparably with methylphenidate: A head-to-head randomized clinical trial

OBJECTIVE

Intra-individual variability in reaction time (IIV-RT) is common in individuals with attention-deficit/hyperactivity disorder (ADHD). It can be improved by stimulants. However, the effects of atomoxetine on IIV-RT are inconclusive. We aimed to investigate the effects of atomoxetine on IIV-RT, and directly compared its efficacy with methylphenidate in adults with ADHD.

METHODS

An 8-10 week, open-label, head-to-head, randomized clinical trial was conducted in 52 drug-naïve adults with ADHD, who were randomly assigned to two treatment groups: immediate-release methylphenidate (n=26) thrice daily (10-20 mg per dose) and atomoxetine once daily (n=26) (0.5-1.2 mg/kg/day). IIV-RT, derived from the Conners' continuous performance test (CCPT), was represented by the Gaussian (reaction time standard error, RTSE) and ex-Gaussian models (sigma and tau). Other neuropsychological functions, including response errors and mean of reaction time, were also measured. Participants received CCPT assessments at baseline and week 8-10 (60.4±6.3 days).

RESULTS

We found comparable improvements in performances of CCPT between the immediate-release methylphenidate- and atomoxetine-treated groups. Both medications significantly improved IIV-RT in terms of reducing tau values with comparable efficacy. In addition, both medications significantly improved inhibitory control by reducing commission errors.

CONCLUSION

Our results provide evidence to support that atomoxetine could improve IIV-RT and inhibitory control, of comparable efficacy with immediate-release methylphenidate, in drug-naïve adults with ADHD. Shared and unique mechanisms underpinning these medication effects on IIV-RT awaits further investigation.

The effect of noise-induced variance on parameter recovery from reaction times

Background

Technical noise can compromise the precision and accuracy of the reaction times collected in psychological experiments, especially in the case of Internet-based studies. Although this noise seems to have only a small impact on traditional statistical analyses, its effects on model fit to reaction-time distributions remains unexplored.

Results

Across four simulations we study the impact of technical noise on parameter recovery from data generated from an ex-Gaussian distribution and from a Ratcliff Diffusion Model. Our results suggest that the impact of noise-induced variance tends to be limited to specific parameters and conditions.

Conclusions

Although we encourage researchers to adopt all measures to reduce the impact of noise on reaction-time experiments, we conclude that the typical amount of noise-induced variance found in these experiments does not pose substantial problems for statistical analyses based on model fitting.

The Impact of Target Frequency on Intra-Individual Variability in Euthymic Bipolar Disorder: A Comparison of Two Sustained Attention Tasks

Greater intra-individual variability (IIV) in reaction time (RT) on a sustained attention task has been reported in patients with bipolar disorder (BD) compared with healthy controls. However, it is unclear whether IIV is task specific, or whether it represents general cross-task impairment in BD. This study aimed to investigate whether IIV occurs in sustained attention tasks with different parameters. Twenty-two patients with BD (currently euthymic) and 17 controls completed two sustained attention tasks on different occasions: a low target frequency (~20%) Vigil continuous performance test (CPT) and a high target frequency (~70%) CPT version A-X (CPT-AX). Variability measures (individual standard deviation and coefficient of variation) were calculated per participant, and ex-Gaussian modeling was also applied. This was supplemented by Vincentile analysis to characterize RT distributions. Results indicated that participants (patients and controls) were generally slower and more variable when completing the Vigil CPT compared with CPT-AX. Significant group differences were also observed in the Vigil CPT, with euthymic BD patients being more variable than controls. This result suggests that IIV in BD demonstrates some degree of task specificity. Further research should incorporate analysis of additional RT distributional models (drift diffusion and fast Fourier transform) to fully characterize the pattern of IIV in BD, as well as its relationship to cognitive processes.

Developmental differences in intra-individual variability in children with ADHD and ASD

BACKGROUND

Intra-individual variability reflects temporal variation within an individual's performance on a cognitive task. Children with developmental disorders, such as ADHD and ASD show increased levels of intra-individual variability. In typical development, intra-individual variability decreases sharply between the ages 6 and 20. The tight link between intra-individual variability and age has led to the suggestion that it may be marker of neural development. As there is accumulating evidence that ADHD and ASD are characterised by atypical neurodevelopmental trajectories, we set out to explore developmental changes in intra-individual variability in subjects with ADHD and ASD.

METHOD

We used propensity score matching to match a cross-sectional sample of children with ADHD, ASD and control subjects (N = 405, aged 6-19 years old) for age, IQ and gender. We used ex-Gaussian distribution parameters to characterise intra-individual variability on fast responses (sigma) and slow responses (tau).

RESULT

Results showed that there was a similar decrease in mean response times with age across groups, and an interaction between age and group for measures of variability, where there was a much lower rate of change in the variability parameters (sigma and tau) for subjects with ASD compared with the other two groups. Subjects with ADHD had higher intra-individual variability, reflected by both sigma and tau, but the rate of decrease in variability with age was similar to that of the controls.

CONCLUSION

These results suggest that subjects with ADHD, ASD and controls differ in the rate at which intra-individual variability decreases during development, and support the idea that intra-individual variability may be a marker of neural development, mimicking the neurodevelopmental changes in these disorders.

Intra-individual reaction time variability based on ex-Gaussian distribution as a potential endophenotype for attention-deficit/hyperactivity disorder

OBJECTIVE

Intra-individual variability in reaction time (IIV-RT), defined by standard deviation of RT (RTSD), is considered as an endophenotype for attention-deficit/hyperactivity disorder (ADHD). Ex-Gaussian distributions of RT, rather than RTSD, could better characterize moment-to-moment fluctuations in neuropsychological performance. However, data of response variability based on ex-Gaussian parameters as an endophenotypic candidate for ADHD are lacking.

METHOD

We assessed 411 adolescents with clinically diagnosed ADHD based on the DSM-IV-TR criteria as probands, 138 unaffected siblings, and 138 healthy controls. The output parameters, mu, sigma, and tau, of an ex-Gaussian RT distribution were derived from the Conners' continuous performance test. Multi-level models controlling for sex, age, comorbidity, and use of methylphenidate were applied.

RESULTS

Compared with unaffected siblings and controls, ADHD probands had elevated sigma value, omissions, commissions, and mean RT. Unaffected siblings formed an intermediate group in-between probands and controls in terms of tau value and RTSD. There was no between-group difference in mu value. Conforming to a context-dependent nature, unaffected siblings still had an intermediate tau value in-between probands and controls across different interstimulus intervals.

CONCLUSION

Our findings suggest IIV-RT represented by tau may be a potential endophenotype for inquiry into genetic underpinnings of ADHD in the context of heterogeneity.

Recall of sequences based on the position of the first cue stimulus in rats

We investigated the ability of rats to recall sequences of nose-poke holes with a modified serial reaction time task. In each trial, a sequence was randomly selected and the position of the first illuminated hole, which functioned as a cue stimulus, informed the rats whether the following sequence was a predictable one or not, based on prior training. The rats responded predictively only when the cues of the predictable sequences were presented. They did not show predictive responses when the cues of unpredictable sequences were presented, even though the unpredictable sequences partially had the same order of holes as the predictable sequences. These results indicate that the rats can recall sequences on the basis of presentation of the first cue stimulus informing predictable or unpredictable sequences. Recording neuronal activity while rats perform this behavioral task would be useful to elucidate neuronal mechanisms that mediate sequence recall.

Release the BEESTS: Bayesian Estimation of Ex-Gaussian STop-Signal reaction time distributions

The stop-signal paradigm is frequently used to study response inhibition. In this paradigm, participants perform a two-choice response time (RT) task where the primary task is occasionally interrupted by a stop-signal that prompts participants to withhold their response. The primary goal is to estimate the latency of the unobservable stop response (stop signal reaction time or SSRT). Recently, Matzke et al. (2013) have developed a Bayesian parametric approach (BPA) that allows for the estimation of the entire distribution of SSRTs. The BPA assumes that SSRTs are ex-Gaussian distributed and uses Markov chain Monte Carlo sampling to estimate the parameters of the SSRT distribution. Here we present an efficient and user-friendly software implementation of the BPA-BEESTS-that can be applied to individual as well as hierarchical stop-signal data. BEESTS comes with an easy-to-use graphical user interface and provides users with summary statistics of the posterior distribution of the parameters as well various diagnostic tools to assess the quality of the parameter estimates. The software is open source and runs on Windows and OS X operating systems. In sum, BEESTS allows experimental and clinical psychologists to estimate entire distributions of SSRTs and hence facilitates the more rigorous analysis of stop-signal data.