Comparison of short- and long-term effects of neurofeedback and transcranial electrical stimulation on the motor learning in healthy adults.

Researchers are exploring non-invasive neuromodulation techniques like transcranial direct current stimulation (tDCS) and neurofeedback (NFB) for enhancing motor learning. While tDCS modulates brain excitability using exogenous electric fields, NFB is an endogenous brain stimulation technique that enables individuals to regulate brain excitability in a closed-loop system. Despite their differing mechanisms, a direct comparison of their effects on motor learning is lacking. This study aimed to compare tDCS and NFB on online learning, short-term offline learning, and long-term offline learning in healthy participants, seeking to identify the most effective method for motor learning enhancement. In this parallel, randomized, single-blinded, controlled trial, 100 healthy participants were randomly assigned to one of five groups: real tDCS, sham tDCS, real NFB, sham NFB, and passive control. Primary outcomes included normalized reaction time (NRT), normalized response accuracy (NRA), and normalized skill index (NSI), measured through a serial reaction time task. Secondary outcomes involved physical and mental fatigue, assessed using a visual analog scale. The study involved 14 blocks of 80 trials each. Online learning was assessed by changes in NRT, NRA, and NSI between Block 3 and Block 9. Short-term and long-term offline learning were evaluated by changes in these measures between Block 9 and Block 11, and between Block 9 and Block 13, respectively. RESULTS: showed a significant decrease in NRA in the sham tDCS and passive control groups from block 3-9, with no changes in other groups. NRT significantly decreased in all intervention groups from block 9-11, with no change in the control group. The NSI significantly increased across all intervention groups between blocks 9 and 11, with large to very large effect sizes, while the passive control group saw a medium effect size increase. Furthermore, NRA significantly increased in the real NFB and real tDCS groups from block 9 to block 13. NRT also significantly decreased in all intervention groups when comparing block 13 to block 9, while the passive control group showed no significant changes. Notably, the reduction in NRT from block 9 to block 13 was significantly greater in the real tDCS group than in the control group, with a mean difference of 0.087 (95 % CI: 0.004-0.169, p = 0.031). Additionally, NSI significantly increased in all intervention groups except the control group from block 9 to block 13. In conclusion, neither NFB nor tDCS had a significant positive impact on online learning. However, both real and sham versions of tDCS and NFB resulted in notable improvements in short-term offline learning. The difference in improvement between NFB and tDCS, as well as between real and sham interventions, was not statistically significant, suggesting that the placebo effect may play a significant role in enhancing short-term offline learning. For long-term offline learning, both brain stimulation methods, particularly tDCS, showed positive effects, although the placebo effect also appeared to contribute.

Association of accelerometer measured sedentary behavior patterns with cognitive functions in sedentary office workers: Insights from SMART-STEP study.

BACKGROUND: High levels of sedentary behavior in workplaces are currently recognized as an independent risk factor for cognitive dysfunction and poor mental health. However, sedentary patterns vary between workdays and non-workdays, which may influence cognitive functions. OBJECTIVE: The present study aimed to quantify and compare work and nonwork device-measured sedentary time (ST) and its association with cognitive function in Indian office workers. METHODS: In an ongoing randomized controlled trial (SMART-STEP), the baseline data of 136 full-time office workers, including accelerometer-measured sedentary patterns and cognitive functions, were analyzed. The ST was measured using a hip-worn accelerometer (Actigraph wGT3X-BT) for seven days, and executive functions were measured using computer-based tests. Linear regression models were employed to analyze the relationships between ST and executive function measures. RESULTS: The median daily ST of Indian office workers was 11.41 hours. The ST was greater on both workdays (11.43 hrs.) and non-workdays (11.14 hrs.) though different (F = 6.76, p = 0.001, ηp2 = 0.032). Office workers accumulate more prolonged sitting bouts (+21.36 min) during work days than non-workdays. No associations between device-measured ST and executive functions were observed. CONCLUSION: Indian office workers exhibited high ST patterns, especially on workdays. Although lower than workdays, Indian office workers exhibited more ST patterns during non-workdays than did their Western counterparts. Culturally adaptable workplace and leisure time physical activity interventions are needed to address the high ST of Indian office workers.

Influences of Vehicle Communication on Human Driving Reactions: A Simulator Study on Reaction Times and Behavior for Forensic Accident Analysis.

Cooperative intelligent transport systems (C-ITSs) are mass-produced and sold in Europe, promising enhanced safety and comfort. Direct vehicle communication, known as vehicle-to-everything (V2X) communication, is crucial in this context. Drivers receive warnings about potential hazards by exchanging vehicle status and environmental data with other communication-enabled vehicles. However, the impact of these warnings on drivers and their inclusion in accident reconstruction remains uncertain. Unlike sensor-based warnings, V2X warnings may not provide a visible reason for the alert, potentially affecting reaction times and behavior. In this work, a simulator study on V2X warnings was conducted with 32 participants to generate findings on reaction times and behavior for accident reconstruction in connection with these systems. Two scenarios from the Car-2-Car Communication Consortium were implemented: "Stationary Vehicle Warning-Broken-Down Vehicle" and "Dangerous Situation-Electronic Emergency Brake Lights". Volkswagen's warning concept was utilized, as they are the sole provider of cooperative vehicles in Europe. Results show that V2X warnings without visible reasons did not negatively impact reaction times or behavior, with average reaction times between 0.58 s (steering) and 0.69 s (braking). No significant distraction or search for warning reasons was observed. However, additional information in the warnings caused confusion and was seldom noticed by subjects. In this study, participants responded correctly and appropriately to the shown false-positive warnings. A wrong reaction triggering an accident is possible but unlikely. Overall, V2X warnings showed no negative impacts compared with sensor-based systems. This means that there are no differences in accident reconstruction regarding the source of the warning (sensors or communication). However, it is important that it is known that there was a warning, which is why the occurrence of V2X warnings should also be saved in the EDR in the future.

Using reaction time procedures to assess implicit attitudes toward violence in a nonconvicted male sample.

In this study, we sought to capture implicit attitudes toward violence by administering response latency measures. We then examined their associations with explicit (e.g., assessed with self-report) attitudes toward violence and self-reported violent behavior in a combined sample of males from a Canadian university and males from the general community (N = 251; 156 students and 95 community members). To date, there have been mixed findings regarding these associations; some of this inconsistency may be due to the difficulty in accurately conceptualizing and assessing implicit attitudes toward violence. Therefore, we administered three response latency measures to assess this construct: a violence evaluation implicit association test (VE-IAT), a personalized VE-IAT (P-VE-IAT), and a violence evaluation relational responding task, along with three self-report measures of explicit attitudes toward violence and three self-report measures of violent behavior. More positive implicit attitudes toward violence were related to more positive explicit attitudes toward violence (for VE-IAT and P-VE-IAT; r = 0.18 to 0.22), greater likelihood of violence (for VE-IAT; r = 0.18 and for P-VE-IAT; r = 0.16), and greater propensity for violence (for the VE-IAT; r = 0.16). All measures of explicit attitudes toward violence and violent behavior were moderately to strongly associated with one another (r = 0.42 to 0.81). Furthermore, implicit attitudes toward violence explained additional variance in some violent outcomes above explicit attitudes alone. Our findings suggest that scores on certain reaction time measures are important for understanding likelihood and propensity for violence, especially when combined with explicit attitude measures.

Reaction-dependent optical behavior and theoretical perspectives of colloidal ZnSe quantum dots.

Colloidal quantum dots (QDs) are attracting research interest because of their unique optical properties that result from the quantum confinement effect. ZnSe QDs, which are II-VI semiconductors, offer a wide direct bandgap (2.7 eV), making them promising for applications such as light-emitting diodes, photodetectors, and biomedical labeling. In the present work, colloidal ZnSe (QDs) were synthesized by the hot-injection method with a Zn:Se ratio of 1:1. The optical properties of ZnSe QDs obtained at different reaction times were investigated by spectrophotometric UV-vis absorption and emission measurements. The as-synthesized ZnSe QDs exhibit blue excitonic emission, and no defect emission was detected. Transmission electron micrographs indicated that the QDs have a spherical morphology with dimensions ranging from 3.69 to 4.53 nm. In particular, the Brus model was applied to demonstrate a correlation between the QD sizes and the optical bandgaps obtained from Tauc plots.

In masks we trust: explicit and implicit reactions to masked faces vary by political orientation.

Previous studies in the context of the COVID-19 pandemic indicated that wearing a medical-style mask affects whether a stranger's face is judged as more trustworthy, socially desirable, or likely to be ill. However, given political controversies around mask use, these effects might vary by political orientation. In a pre-registered online experiment, we measured evaluations of trustworthiness, social desirability and perceived illness in masked and unmasked faces by 1241 British and US participants. We included questions on political orientation, along with the implicit online-VAAST approach/avoid task to test reaction times to masked/unmasked faces. There was a medium-sized effect of masks on trustworthiness and a significant interaction with political orientation, in that conservatives found masked faces less trustworthy than did liberals. Participants were quicker to approach masked than unmasked faces, but conservatives were relatively slower than liberals. The effects on trustworthiness suggest that differential moralization of novel social norms can affect how their adherents are evaluated in terms of their suitability for social interactions. Furthermore, the congruence between implicit and explicit methods implies that such differences can have deep-seated effects on reactions.

A hybrid approach to dynamic cognitive psychometrics : Dynamic cognitive psychometrics.

Dynamic cognitive psychometrics measures mental capacities based on the way behavior unfolds over time. It does so using models of psychological processes whose validity is grounded in research from experimental psychology and the neurosciences. However, these models can sometimes have undesirable measurement properties. We propose a "hybrid" modeling approach that achieves good measurement by blending process-based and descriptive components. We demonstrate the utility of this approach in the stop-signal paradigm, in which participants make a series of speeded choices, but occasionally are required to withhold their response when a "stop signal" occurs. The stop-signal paradigm is widely used to measure response inhibition based on a modeling framework that assumes a race between processes triggered by the choice and the stop stimuli. However, the key index of inhibition, the latency of the stop process (i.e., stop-signal reaction time), is not directly observable, and is poorly estimated when the choice and the stop runners are both modeled by psychologically realistic evidence-accumulation processes. We show that using a descriptive account of the stop process, while retaining a realistic account of the choice process, simultaneously enables good measurement of both stop-signal reaction time and the psychological factors that determine choice behavior. We show that this approach, when combined with hierarchical Bayesian estimation, is effective even in a complex choice task that requires participants to perform only a relatively modest number of test trials.

Differential correlates of fear and anxiety in salience perception: A behavioral and ERP study with adolescents.

Anxiety disorders are the most common psychopathologies among adolescents. Their diagnostic criteria include both fear and anxiety symptomatology, although according to the literature, we can find evidence for some distinction between these two emotions. The present study contribute to this distinction, exploring the effects of trait fear and trait anxiety on behavioral and neural correlates. Thirty-two participants (aged 11-16 years) performed two experimental tasks of salient target detection, including visual stimuli that were manipulated to become salient, while reaction times and EEG were recorded. Results of both tasks revealed differential effects of trait fear and trait anxiety assessed through the Fear Survey Schedule for Children-Revised and the Youth Anxiety Measure for DSM-5 on reaction times and ERP components amplitudes. Specifically, higher symptoms from Separation Anxiety Disorder increased early neural visual processing and decreased reaction times for more salient stimuli. Also, trait fear reduced later neural visual processing of salient stimuli. These findings may provide a significant contribution to guiding psychological interventions, especially with adolescents presenting higher levels of anxiety-related symptomatology.

How Many Participants? How Many Trials? Maximizing the Power of Reaction Time Studies.

Due to limitations in the resources available for carrying out reaction time (RT) experiments, researchers often have to choose between testing relatively few participants with relatively many trials each or testing relatively many participants with relatively few trials each. To compare the experimental power that would be obtained under each of these options, I simulated virtual experiments using subsets of participants and trials from eight large real RT datasets examining 19 experimental effects. The simulations compared designs using the first N T trials from N P randomly selected participants, holding constant the total number of trials across all participants, N P × N T . The [ N P , N T ] combination maximizing the power to detect each effect depended on how the mean and variability of that effect changed with practice. For most effects, power was greater in designs having many participants with few trials each rather than the reverse, suggesting that researchers should usually try to recruit large numbers of participants for short experimental sessions. In some cases, power for a fixed total number of trials across all participants was maximized by having as few as two trials per participant in each condition. Where researchers can make plausible predictions about how their effects will change over the course of a session, they can use those predictions to increase their experimental power.

Differences in Ex-Gaussian Parameters from Response Time Distributions Between Individuals with and Without Attention Deficit/Hyperactivity Disorder: A Meta-analysis.

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent neurodevelopmental disorders in childhood and adolescence. Differences in reaction times (RT) in cognitive tasks have been consistently observed between ADHD and typical participants. Instead of estimating means and standard deviations, fitting non-symmetrical distributions like the ex-Gaussian, characterized by three parameters (µ, σ, and τ), account for the whole RT distributions. A meta-analysis is performed with all the available literature using ex-Gaussian distributions for comparisons between individuals with ADHD and controls. Results show that τ and σ are generally greater for ADHD samples, while µ tends to be larger for typical groups but only for younger ages. Differences in τ are also moderated by ADHD subtypes. τ and σ show, respectively, quadratic and linear relationships with inter-stimulus intervals from Continuous Performance Test and Go/No Go tasks. Furthermore, tasks and cognitive domains influence the three parameters. Interpretations of ex-Gaussian parameters and clinical implications of these findings are also discussed. Fitting ex-Gaussian distributions to RT data is a useful way to explore differences between individuals with ADHD and healthy controls.

Alterations in Brain Activity Induced by Transcranial Magnetic Stimulation and Their Relation to Decision Making.

Understanding the intricate dynamics between conscious choice and neural processes is crucial for unraveling the complexity of human decision-making. This study investigates the effects of inhibitory Transcranial Magnetic Stimulation (TMS) on choice bias, shedding light on the malleability of cognitive-motor functions involved in decisions. While reaction times remained unaffected, inhibitory TMS to either the left or right motor cortex led to a significant bias in screen side preference during a choice task. These findings suggest that our cognitive-motor processes underlying decision-making can be unconsciously influenced by TMS. Furthermore, analysis of choice attribution categories revealed individual variability, emphasizing the complex nature of the decision-making process. These insights contribute to the ongoing exploration of the neural mechanisms governing human choice. As the neural basis of free will continues to captivate scientific inquiry, this research advances our understanding of the intricate relationship between neural circuits and conscious intention.

EMG measured reaction time as a predictor of invalid symptom report in psychosomatic patients.

Background: Symptom validity tests (SVTs) and performance validity tests (PVTs) are important tools in sociomedical assessments, especially in the psychosomatic context where diagnoses mainly depend on clinical observation and self-report measures. This study examined the relationship between reaction times (RTs) and scores on the Structured Inventory of Malingered Symptomatology (SIMS). It was proposed that slower RTs and larger standard deviations of reaction times (RTSDs) would be observed in participants who scored above the SIMS cut-off (>16). Methods: Direct surface electromyography (EMG) was used to capture RTs during a computer-based RT test in 152 inpatients from a psychosomatic rehabilitation clinic in Germany. Correlation analyses and Mann-Whitney U were used to examine the relationship between RTs and SIMS scores and to assess the potential impact of covariates such as demographics, medical history, and vocational challenges on RTs. Therefore, dichotomized groups based on each potential covariate were compared. Results: Significantly longer RTs and larger RTSDs were found in participants who scored above the SIMS cut-off. Current treatment with psychopharmacological medication, diagnosis of depression, and age had no significant influence on the RT measures. However, work-related problems had a significant impact on RTSDs. Conclusion: There was a significant relationship between longer and more inconsistent RTs and indicators of exaggerated or feigned symptom report on the SIMS in psychosomatic rehabilitation inpatients. Findings from this study provide a basis for future research developing a new RT-based PVT.

The scaling of mental computation in a sorting task.

Many cognitive models provide valuable insights into human behavior. Yet the algorithmic complexity of candidate models can fail to capture how human reaction times scale with increasing input complexity. In the current work, we investigate the algorithms underlying human cognitive processes. Computer science characterizes algorithms by their time and space complexity scaling with problem size. We propose to use participants' reaction times to study how human computations scale with increasing input complexity. We tested this approach in a task where participants had to sort sequences of rectangles by their size. Our results showed that reaction times scaled close to linearly with sequence length and that participants learned and actively used latent structure whenever it was provided. This behavior was in line with a computational model that used the observed sequences to form hypotheses about the latent structures, searching through candidate hypotheses in a directed fashion. These results enrich our understanding of plausible cognitive models for efficient mental sorting and pave the way for future studies using reaction times to investigate the scaling of mental computations across psychological domains.

Vigilance Decrement During On-Road Partially Automated Driving Across Four Systems.

OBJECTIVE: This study uses a detection task to measure changes in driver vigilance when operating four different partially automated systems. BACKGROUND: Research show temporal declines in detection task performance during manual and fully automated driving, but the accuracy of using this approach for measuring changes in driver vigilance during on-road partially automated driving is yet unproven. METHOD: Participants drove four different vehicles (Tesla Model 3, Cadillac CT6, Volvo XC90, and Nissan Rogue) equipped with level-2 systems in manual and partially automated modes. Response times to a detection task were recorded over eight consecutive time periods. RESULTS: Bayesian analysis revealed a main effect of time period and an interaction between mode and time period. A main effect of vehicle and a time period x vehicle interaction were also found. CONCLUSION: Results indicated that the reduction in detection task performance over time was worse during partially automated driving. Vehicle-specific analysis also revealed that detection task performance changed across vehicles, with slowest response time found for the Volvo. APPLICATION: The greater decline in detection performance found in automated mode suggests that operating level-2 systems incurred in a greater vigilance decrement, a phenomenon that is of interest for Human Factors practitioners and regulators. We also argue that the observed vehicle-related differences are attributable to the unique design of their in-vehicle interfaces.

Towards personalized and optimized fitting of cochlear implants.

A cochlear implant (CI) is a neurotechnological device that restores total sensorineural hearing loss. It contains a sophisticated speech processor that analyzes and transforms the acoustic input. It distributes its time-enveloped spectral content to the auditory nerve as electrical pulsed stimulation trains of selected frequency channels on a multi-contact electrode that is surgically inserted in the cochlear duct. This remarkable brain interface enables the deaf to regain hearing and understand speech. However, tuning of the large (>50) number of parameters of the speech processor, so-called "device fitting," is a tedious and complex process, which is mainly carried out in the clinic through 'one-size-fits-all' procedures. Current fitting typically relies on limited and often subjective data that must be collected in limited time. Despite the success of the CI as a hearing-restoration device, variability in speech-recognition scores among users is still very large, and mostly unexplained. The major factors that underly this variability incorporate three levels: (i) variability in auditory-system malfunction of CI-users, (ii) variability in the selectivity of electrode-to-auditory nerve (EL-AN) activation, and (iii) lack of objective perceptual measures to optimize the fitting. We argue that variability in speech recognition can only be alleviated by using objective patient-specific data for an individualized fitting procedure, which incorporates knowledge from all three levels. In this paper, we propose a series of experiments, aimed at collecting a large amount of objective (i.e., quantitative, reproducible, and reliable) data that characterize the three processing levels of the user's auditory system. Machine-learning algorithms that process these data will eventually enable the clinician to derive reliable and personalized characteristics of the user's auditory system, the quality of EL-AN signal transfer, and predictions of the perceptual effects of changes in the current fitting.

Visual Motor Reaction Times Predict Receptive and Expressive Language Development in Early School-Age Children.

Proficiency of multisensory processing and motor skill are often associated with early cognitive, social, and language development. However, little research exists regarding the relationship between multisensory motor reaction times (MRTs) to auditory, visual and audiovisual stimuli, and classical measures of receptive language and expressive vocabulary development in school-age children. Thus, this study aimed to examine the concurrent development of performance in classical tests of receptive (Peabody Picture Vocabulary Test; abbreviated as PPVT) and expressive vocabulary (Expressive Vocabulary Test; abbreviated as EVT), nonverbal intelligence (NVIQ) (determined with the aid of Raven's Colored Progressive Matrices; abbreviated as RCPM), speed of visual-verbal processing in the Rapid Automatic Naming (RAN) test, Eye-Hand Co-ordination (EHC) in the SLURP task, and multisensory MRTs, in children (n = 75), aged between 5 and 10 years. Bayesian statistical analysis showed evidence for age group differences in EVT performance, while PPVT was only different for the youngest group of children aged 5-6, supporting different developmental trajectories in vocabulary acquisition. Bayesian correlations revealed evidence for associations between age, NVIQ, and vocabulary measures, with decisive evidence and a higher correlation (r = 0.57 to 0.68) between EVT, MRT tasks, and EHC visuomotor processing. This was further supported by regression analyses indicating that EVT performance was the strongest unique predictor of multisensory MRTs, EHC, and RAN time. Additionally, visual MRTs were found to predict both receptive and expressive vocabulary. The findings of the study have important implications as accessible school-based assessments of the concurrent development of NVIQ, language, and multisensory processing; and hence as rapid and timely measures of developmental and neurodevelopmental status.

Chunking Versus Transitional Probabilities: Differentiating Between Theories of Statistical Learning.

There are two main approaches to how statistical patterns are extracted from sequences: The transitional probability approach proposes that statistical learning occurs through the computation of probabilities between items in a sequence. The chunking approach, including models such as PARSER and TRACX, proposes that units are extracted as chunks. Importantly, the chunking approach suggests that the extraction of full units weakens the processing of subunits while the transitional probability approach suggests that both units and subunits should strengthen. Previous findings using sequentially organized, auditory stimuli or spatially organized, visual stimuli support the chunking approach. However, one limitation of prior studies is that most assessed learning with the two-alternative forced-choice task. In contrast, this pre-registered experiment examined the two theoretical approaches in sequentially organized, visual stimuli using an online self-paced task-arguably providing a more sensitive index of learning as it occurs-and a secondary offline familiarity judgment task. During the self-paced task, abstract shapes were covertly organized into eight triplets (ABC) where one in every eight was altered (BCA) from the canonical structure in a way that disrupted the full unit while preserving a subunit (BC). Results from the offline familiarity judgment task revealed that the altered triplets were perceived as highly familiar, suggesting the learned representations were relatively flexible. More importantly, results from the online self-paced task demonstrated that processing for subunits, but not unit-initial stimuli, was impeded in the altered triplet. The pattern of results is in line with the chunking approach to statistical learning and, more specifically, the TRACX model.

Investigating Auditory Perception at Europe's Highest Mountain Lodge.

Altitude hypoxia can impair sensory and cognitive functions, from causing slowed responses to sensory hallucinations. In a field study, we tested 12 expeditioners at varied altitudes (low: 1696 m; high: 4556 m) with a simple auditory detection task and a dichotic listening paradigm in which a voice was presented, lateralized, within a binaural white noise stream. Slower reaction times and a reduced right ear advantage might be expected at high (vs. low) altitude, due to hypoxia. The participants' performances on both tasks did not differ between conditions, revealing that these functions are resistant to short-term hypoxia in young healthy adults.

The Contribution of Visual and Auditory Working Memory and Non-Verbal IQ to Motor Multisensory Processing in Elementary School Children.

Although cognitive abilities have been shown to facilitate multisensory processing in adults, the development of cognitive abilities such as working memory and intelligence, and their relationship to multisensory motor reaction times (MRTs), has not been well investigated in children. Thus, the aim of the current study was to explore the contribution of age-related cognitive abilities in elementary school-age children (n = 75) aged 5-10 years, to multisensory MRTs in response to auditory, visual, and audiovisual stimuli, and a visuomotor eye-hand co-ordination processing task. Cognitive performance was measured on classical working memory tasks such as forward and backward visual and auditory digit spans, and the Raven's Coloured Progressive Matrices (RCPM test of nonverbal intelligence). Bayesian Analysis revealed decisive evidence for age-group differences across grades on visual digit span tasks and RCPM scores but not on auditory digit span tasks. The results also showed decisive evidence for the relationship between performance on more complex visually based tasks, such as difficult items of the RCPM and visual digit span, and multisensory MRT tasks. Bayesian regression analysis demonstrated that visual WM digit span tasks together with nonverbal IQ were the strongest unique predictors of multisensory processing. This suggests that the capacity of visual memory rather than auditory processing abilities becomes the most important cognitive predictor of multisensory MRTs, and potentially contributes to the expected age-related increase in cognitive abilities and multisensory motor processing.

Generalised exponential-Gaussian distribution: a method for neural reaction time analysis.

Reaction times (RTs) are an essential metric used for understanding the link between brain and behaviour. As research is reaffirming the tight coupling between neuronal and behavioural RTs, thorough statistical modelling of RT data is thus essential to enrich current theories and motivate novel findings. A statistical distribution is proposed herein that is able to model the complete RT's distribution, including location, scale and shape: the generalised-exponential-Gaussian (GEG) distribution. The GEG distribution enables shifting the attention from traditional means and standard deviations to the entire RT distribution. The mathematical properties of the GEG distribution are presented and investigated via simulations. Additionally, the GEG distribution is featured via four real-life data sets. Finally, we discuss how the proposed distribution can be used for regression analyses via generalised additive models for location, scale and shape (GAMLSS).