EZ-CDM: Fast, simple, robust, and accurate estimation of circular diffusion model parameters.

The investigation of cognitive processes that form the basis of decision-making in paradigms involving continuous outcomes has gained the interest of modeling researchers who aim to develop a dynamic decision theory that accounts for both speed and accuracy. One of the most important of these continuous models is the circular diffusion model (CDM, Smith. Psychological Review, 123(4), 425. 2016), which posits a noisy accumulation process mathematically described as a stochastic two-dimensional Wiener process inside a disk. Despite the considerable benefits of this model, its mathematical intricacy has limited its utilization among scholars. Here, we propose a straightforward and user-friendly method for estimating the CDM parameters and fitting the model to continuous-scale data using simple formulas that can be readily computed and do not require theoretical knowledge of model fitting or extensive programming. Notwithstanding its simplicity, we demonstrate that the aforementioned method performs with a level of accuracy that is comparable to that of the maximum likelihood estimation method. Furthermore, a robust version of the method is presented, which maintains its simplicity while exhibiting a high degree of resistance to contaminant responses. Additionally, we show that the approach is capable of reliably measuring the key parameters of the CDM, even when these values are subject to across-trial variability. Finally, we demonstrate the practical application of the method on experimental data. Specifically, an illustrative example is presented wherein the method is employed along with estimating the probability of guessing. It is hoped that the straightforward methodology presented here will, on the one hand, help narrow the divide between theoretical constructs and empirical observations on continuous response tasks and, on the other hand, inspire cognitive psychology researchers to shift their laboratory investigations towards continuous response paradigms.

Are there jumps in evidence accumulation, and what, if anything, do they reflect psychologically? An analysis of Lévy Flights models of decision-making.

According to existing theories of simple decision-making, decisions are initiated by continuously sampling and accumulating perceptual evidence until a threshold value has been reached. Many models, such as the diffusion decision model, assume a noisy accumulation process, described mathematically as a stochastic Wiener process with Gaussian distributed noise. Recently, an alternative account of decision-making has been proposed in the Lévy Flights (LF) model, in which accumulation noise is characterized by a heavy-tailed power-law distribution, controlled by a parameter, [Formula: see text]. The LF model produces sudden large "jumps" in evidence accumulation that are not produced by the standard Wiener diffusion model, which some have argued provide better fits to data. It remains unclear, however, whether jumps in evidence accumulation have any real psychological meaning. Here, we investigate the conjecture by Voss et al. (Psychonomic Bulletin & Review, 26(3), 813-832, 2019) that jumps might reflect sudden shifts in the source of evidence people rely on to make decisions. We reason that if jumps are psychologically real, we should observe systematic reductions in jumps as people become more practiced with a task (i.e., as people converge on a stable decision strategy with experience). We fitted five versions of the LF model to behavioral data from a study by Evans and Brown (Psychonomic Bulletin & Review, 24(2), 597-606, 2017), using a five-layer deep inference neural network for parameter estimation. The analysis revealed systematic reductions in jumps as a function of practice, such that the LF model more closely approximated the standard Wiener model over time. This trend could not be attributed to other sources of parameter variability, speaking against the possibility of trade-offs with other model parameters. Our analysis suggests that jumps in the LF model might be capturing strategy instability exhibited by relatively inexperienced observers early on in task performance. We conclude that further investigation of a potential psychological interpretation of jumps in evidence accumulation is warranted.

Neural symphony of risky decision making in children with ADHD: Insights from transcranial alternating current stimulation and cognitive modeling.

BACKGROUND: The ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC) are key brain regions involved in risky decision making, affected in individuals with attention deficit hyperactivity disorder (ADHD). This study aims to examine how entrainment of these areas impacts the process and outcome of risky decision making in children with ADHD. METHODS: Eighteen children with ADHD performed the balloon analogue risk-taking task (BART) during five different sessions of tACS (1.5 mA, 6 Hz), separated by one-week intervals, via (1) two channels with synchronized stimulation over the left dlPFC and right vmPFC, (2) the same electrode placement with anti-phase stimulation, (3) stimulation over the left dlPFC only, (4) stimulation over right vmPFC only, and (5) sham stimulation. Four-parameter and constant-sensitivity models were used to model the data. RESULTS: The study showed that synchronized stimulation was associated with a reduction in positive prior belief, risk propensity, and deterministic selection. Desynchronized stimulation was associated with accelerated learning from initial selections. Isolated stimulation of the dlPFC leads to riskier decision enhanced learning updates and risk propensity, whereas isolated stimulation of the vmPFC facilitated faster learning and increased probabilistic selection. CONCLUSION: The results highlight the important roles of the dlPFC and vmPFC and their communication in decision making, showcasing their impact on various aspects of the decision-making process. The findings provide valuable insights into the complex interplay between cognitive and emotional factors in shaping our choices.

Anxiety, concerns and COVID-19: Cross-country perspectives from families and individuals with neurodevelopmental conditions.

Background: The COVID-19 pandemic had a major impact on the mental health and well-being of children with neurodevelopmental conditions (NDCs) and of their families worldwide. However, there is insufficient evidence to understand how different factors (e.g., individual, family, country, children) have impacted on anxiety levels of families and their children with NDCs developed over time. Methods: We used data from a global survey assessing the experience of 8043 families and their children with NDCs (mean of age (m) = 13.18 years, 37% female) and their typically developing siblings (m = 12.9 years, 45% female) in combination with data from the European Centre for Disease Prevention and Control, the University of Oxford, and the Central Intelligence Agency (CIA) World Factbook, to create a multilevel data set. Using stepwise multilevel modelling, we generated child-, family- and country-related factors that may have contributed to the anxiety levels of children with NDCs, their siblings if they had any, and their parents. All data were reported by parents. Results: Our results suggest that parental anxiety was best explained by family-related factors such as concerns about COVID-19 and illness. Children's anxiety was best explained by child-related factors such as children's concerns about loss of routine, family conflict, and safety in general, as well as concerns about COVID-19. In addition, anxiety levels were linked to the presence of pre-existing anxiety conditions for both children with NDCs and their parents. Conclusions: The present study shows that across the globe there was a raise in anxiety levels for both parents and their children with NDCs because of COVID-19 and that country-level factors had little or no impact on explaining differences in this increase, once family and child factors were considered. Our findings also highlight that certain groups of children with NDCs were at higher risk for anxiety than others and had specific concerns. Together, these results show that anxiety of families and their children with NDCs during the COVID-19 pandemic were predicted by very specific concerns and worries which inform the development of future toolkits and policy. Future studies should investigate how country factors can play a protective role during future crises.

Transcranial direct current stimulation alters the process of reward processing in children with ADHD: Evidence from cognitive modeling.

BACKGROUND: The ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC) are the neural underpinnings of reward processing, which is impaired in individuals with attention deficit hyperactivity disorder (ADHD). In the present study, we aimed to explore the impact of the vmPFC and the dlPFC regulation on reward processing. METHODS: Twenty-six children with ADHD performed the balloon analogue risk-taking task (BART) and chocolate delay discounting task (CDDT) during five different sessions of transcranial direct current stimulation (tDCS), separated by a one-week interval: anodal left dlPFC/cathodal right vmPFC, the reversed electrode positioning, anodal left dlPFC stimulation with extracranial return electrode, anodal right vmPFC stimulation with extracranial return electrodes, and sham stimulation. Four-parameter and constant-sensitivity models were used to model the data. RESULTS: In the BART, anodal dlPFC/cathodal vmPFC stimulation facilitated conservative decision making, anodal tDCS over dlPFC with extracranial return electrode increased positive beliefs about the explosion of a balloon, and anodal vmPFC/cathodal dlPFC stimulation reduced ongoing learning in the process of decision making. In the CDDT, anodal vmPFC stimulation with extracranial return electrode decreased impatience in the process of the task. CONCLUSION: These results suggest a role of the left dlPFC and right vmPFC in the outcome of decision making and the process of risky decision making and delay discounting.

Transcranial direct current stimulation (tDCS) alters the pattern of information processing in children with ADHD: Evidence from drift diffusion modeling.

OBJECTIVE: Performance accuracy and reaction time in cognitive tasks are routinely used to evaluate the efficacy of tDCS to affect cognitive task performance. tDCS alters the excitability of targeted brain areas and thereby alters performance of cognitive tasks. The drift diffusion model (DDM) provides some additional measures to explore information processing style, such as (non)decision time, bias for decision, and speed of information processing. DDM parameters are informative for the study of cognitive impairments in children with ADHD. In the present study, we aimed to evaluate the impact of tDCS on cognitive performance via DDM measures. METHODS: This study conducted DDM modeling and reanalysis of two exploratory, single-blinded, within-subject design experiments, which were published earlier. In the first experiment, twenty- four children with ADHD performed a Go/ No- Go task during anodal or sham tDCS over the right dlPFC. In the second experiment, twenty- five children with ADHD performed the 1- back working memory task during anodal or sham tDCS over the left dlPFC. We reanalyzed the data after DDM modeling. RESULTS: The conventional performance measures revealed no significant effect of tDCS on No- Go accuracy in the first experiment and 1-back accuracy in the second experiment. The 1-back reaction time and speed-accuracy tradeoff were however improved under the real stimulation condition. The DDM measures identified increased No-Go- bias and decision time with respect to inhibitory control, and an increased threshold and amount of information required for response in the 1- back test. CONCLUSION: In children with ADHD, anodal tDCS over the right dlPFC induces more conservative and less impulsive decisions. Furthermore, anodal tDCS over the left dlPFC enhanced efficacy of working memory performance with respect to agility and capacity. The experimental results show that drift diffusion modeling is useful for evaluation of the impact of tDCS on the style of information processing.