Drift-diffusion Model Research Articles

Electrical Doping Regulation of Carrier Recombination Enhances the Perovskite Solar Cell Efficiency beyond 28.

With the power conversion efficiency (PCE) of perovskite solar cells (PSCs) exceeding 26.7%, achieving further enhancements in device performance has become a key research focus. Here, we investigate the impact of electrical doping in the perovskite layer using the drift-diffusion equation-based device physics model, coupled with a self-developed equivalent circuit model. Our results demonstrate that electrical doping can increase the PCE from 24.78% to >28%. In-depth theoretical analysis reveals that these improvements in performance are driven by the modulation of carrier recombination processes through doping, leading to significant increases in the open-circuit voltage and fill factor. Additionally, we explore the influence of physical parameters on device performance. Our study identifies an optimal doping concentration range from 1.0 × 1017 to 1.0 × 1019 cm-3 and a transport layer mobility of >0.01 cm2 V-1 s-1. This work provides a theoretical foundation for the development of ultra-high-performance PSCs through targeted electrical doping strategies.

Impulsive adolescents exhibit inefficient processing and a low decision threshold when decoding facial expressions of emotions.

Borderline personality disorder (BPD) is a debilitating psychiatric illness whose symptoms frequently emerge during adolescence. Initial studies in adults suggest that the interpersonal difficulties common in BPD may emerge from disrupted processing of social and emotional stimuli. Less is known about these processes in adolescents with BPD symptoms, despite substantial changes in socioemotional processing during this developmental period. 86 adolescents and young adults with and without BPD symptoms completed an emotional interference task involving the identification of a facial emotion expression in the presence of a conflicting or congruent emotion word. We used hierarchical drift diffusion modeling to index speed of processing and decision boundary. Using Bayesian multilevel regression, we characterized age-related differences in facial emotion processing. We then examined whether BPD symptom dimensions were associated with facial emotion processing on this task. To determine the specificity of our effects, we analyzed behavioral data from a corresponding nonemotional interference task. Impulsivity, but not negative affectivity or interpersonal dysfunction, predicted inefficient processing when presented with conflicting negative emotional stimuli. Across both tasks, impulsivity in adolescents was further associated with a lower decision boundary. Impulsive adolescents were especially likely to make fast, but inaccurate decisions about another person's emotional state. Impulsive adolescents with BPD symptoms are prone to making errors when appraising facial expressions of emotions, which may potentiate or worsen interpersonal conflicts. Our findings highlight the role of lower-level social cognitive processes in interpersonal difficulties among vulnerable youth during a sensitive developmental window.

Psychometrics of drift-diffusion model parameters derived from the Eriksen flanker task: Reliability and validity in two independent samples.

The flanker task is a widely used measure of cognitive control abilities. Drift-diffusion modeling of flanker task behavior can yield separable parameters of cognitive control-related subprocesses, but the parameters' psychometrics are not well-established. We examined the reliability and validity of four behavioral measures: (1) raw accuracy, (2) reaction time (RT) interference, (3) NIH Toolbox flanker score, and (4) two drift-diffusion model (DDM) parameters-drift rate and boundary separation-capturing evidence accumulation efficiency and speed-accuracy trade-off, respectively. Participants from two independent studies - one cross-sectional (N = 381) and one with three timepoints (N = 83) - completed the flanker task while electroencephalography data were collected. Across both studies, drift rate and boundary separation demonstrated comparable split-half and test-retest reliability to accuracy, RT interference, and NIH Toolbox flanker score, but better incremental convergent validity with psychophysiological measures (i.e., the error-related negativity; ERN) and neuropsychological measures of cognitive control than the other behavioral indices. Greater drift rate (i.e., faster and more accurate responses) to congruent and incongruent stimuli, and smaller boundary separation to incongruent stimuli were related to 1) larger ERN amplitudes (in both studies) and 2) faster and more accurate inhibition and set-shifting over and above raw accuracy, reaction time, and NIH Toolbox flanker scores (in Study 1). Computational models, such as DDM, can parse behavioral performance into subprocesses that exhibit comparable reliability to other scoring approaches, but more meaningful relationships with other measures of cognitive control. The application of these computational models may be applied to existing data and enhance the identification of cognitive control deficits in psychiatric disorders.

Signature of electrothermal transport in 18 nm vertical junctionless gate-all-around nanowire field effect transistors

Abstract Addressing temperature hot-spots resulting from self-heating effects (SHE) poses a significant challenge in the design of emerging nanoscale transistors, such as vertical junctionless nanowire field-effect transistors (VNWFETs), due to reduced thermal conductivity. Consequently, electrothermal modeling becomes crucial for a comprehensive understanding of the underlying physical mechanisms governing carrier degradation and thermal conduction in these nanoscale devices. In this study, we present an enhanced drift-diffusion model coupled with nonlocal Guyer-Krumhansl (GK) equations to accurately capture carrier-phonon interactions and explore the electrothermal characteristics of gate-all-around (GAA) VNWFETs. Pulsed current-voltage (I–V) measurements are employed to investigate the performance of a state-of-the-art 18nm VNWFET technology. Furthermore, we report on the influences of both trapping and SHE under high-bias conditions for varying pulse widths. Our findings reveal that optimization of mobility degradation mechanisms allows for improved control over the physical behavior of carrier transport in these emerging technologies. Through careful consideration of these factors, it becomes possible to enhance the overall performance of GAA VNWFETs, particularly in mitigating temperature hot-spots and addressing challenges associated with self-heating effects.

Prior probability biases perceptual choices by modulating the accumulation rate, rather than the baseline, of decision evidence

Abstract The prior probability of an upcoming stimulus has been shown to influence the formation of perceptual decisions. Computationally these effects have typically been attributed to changes in the starting point (i.e. baseline) of evidence accumulation in sequential sampling models. More recently, it has also been proposed that prior probability might additionally lead to changes in the rate of evidence accumulation. Here, we introduce a neurally-informed behavioural modelling approach to understand whether prior probability influences the starting point, the rate of evidence accumulation or both. To this end, we employ a well-established visual object categorization task for which two neural components underpinning participants’ choices have been characterised using single-trial analysis of the electroencephalogram. These components are reliable measures of trial-by-trial variability in the quality of the relevant decision evidence, which we use to constrain the estimation of a hierarchical drift diffusion model of perceptual choice. We find that, unlike previous computational accounts, constraining the model with the endogenous variability in the relevant decision evidence, results in prior probability effects being explained primarily by changes in the rate of evidence accumulation rather than changes in the starting point or a combination of both. Ultimately, our neurally-informed modelling approach helps disambiguate the mechanistic effect of prior probability on perceptual decision formation, suggesting that prior probability biases primarily the interpretation of sensory evidence towards the most likely stimulus.

Enhanced intentional inhibition with increased subliminal action preparation.

Intentional inhibition, the ability to voluntarily inhibit or suspend an action preparation, is closely related to self-control. It is widely believed that subliminal stimuli can also activate action preparation, but whether intentional inhibition is enhanced or disrupted with greater subliminal action preparation remains unclear. In this study, participants voluntarily decided whether or not to perform the action in the scenario with subliminal action preparation, and the strength of the action preparation was manipulated by a precueing procedure. The results, based on behavioural measures and drift-diffusion models, showed that intentional inhibition enhanced with increasing subliminal action preparation, suggesting that as subliminal action preparation increases, people are more inclined to make inhibitory decisions. This study provides evidence for a framework in which strong subliminal action preparation induces enhanced cognitive monitoring.

Rat movements reflect internal decision dynamics in an evidence accumulation task.

Perceptual decision-making involves multiple cognitive processes, including accumulation of sensory evidence, planning, and executing a motor action. How these processes are intertwined is unclear; some models assume that decision-related processes precede motor execution, whereas others propose that movements reflecting on-going decision processes occur before commitment to a choice. Here we combine and apply two complementary methods to study the relationship between decision processes and the movements leading up to a choice. The first is a free response pulse-based evidence accumulation task, in which stimuli continue until choice is reported and the second is a motion-based drift diffusion model (mDDM), in which movement variables from video pose estimation constrain decision parameters on a trial-by-trial basis. We find the mDDM provides a better model fit to rats' decisions in the free response accumulation task than traditional DDM models. Interestingly, on each trial we observed a period of time, prior to choice, that was characterized by head immobility. The length of this period was positively correlated with the rats' decision bounds and stimuli presented during this period had the greatest impact on choice. Together these results support a model in which internal decision dynamics are reflected in movements and demonstrate that inclusion of movement parameters improves the performance of diffusion-to-bound decision models.

The temporal profile of self-prioritization

Personal relevance exerts a powerful influence on decisional processing, such that arbitrary stimuli associated with the self are classified more rapidly than identical material linked with other people. Notwithstanding numerous demonstrations of this facilitatory effect, it remains unclear whether self-prioritization is a temporally stable outcome of decision-making. Accordingly, using a shape-label matching task in combination with computational modeling, the current experiment investigated this matter. The results were informative. First, regardless of the target of comparison (i.e., friend or stranger), self-prioritization was a persistent product of decision-making across the testing session. Second, a variant of the standard drift diffusion model in which decisional boundaries collapsed gradually over the course of the task best fit the observed data. Third, whereas the efficiency of stimulus processing increased for other-related stimuli during the task, it decreased for self-related material. Collectively, these findings advance understanding of the temporal profile of self-prioritization.

Emotion-Driven Moral Evaluation: A Mechanistic Study Based on the Drift-Diffusion Model.

Moral evaluation is identified as the first stage in the theory of moral judgment, and academics believe that it may align with the social intuitionist model. This study aims to prove that the model's emotional dominance hypothesis applies to moral evaluation by presenting a computational decision-making model that mathematically formalizes this emotional dominance decision-making process. We also compared different types of valence evaluation tasks to test the emotional priority hypothesis. We used a convenience sampling method to randomly recruit 30 enrolled college students. The drift-diffusion model was employed to analyze reaction times for words with various emotional and moral valences Additionally, we designed different valence evaluation tasks based on the response relevance hypothesis and evaluated the processing order through reaction time comparisons. The analysis revealed that the emotional mechanism of immoral evaluation differs from moral evaluation. An increase in emotional valence accelerates the speed of evidence accumulation (v) for moral evaluation (M = 1.21, 0.2% < 0 < 99.8%) but lowers decision caution (a) in immoral evaluation (M = -0.64, 96.1% < 0 < 3.9%). In contrast, moral valence does not have a significant influence on evaluation processes (v, M = -0.28, 72.1% < 0 < 27.9%; a, M = -0.32, 79.3% < 0 < 20.7%). Furthermore, We found no significant difference in reaction times between moral and immoral words in the emotional evaluation task (F(1,29) = 0.55, p = 0.464, partial η2 = 0.02), but a significant difference existed in the moral evaluation task (F(1,29) = 17.99, p < 0.001, partial η2 = 0.38), indicating that the tendency of relatively fast immoral evaluation in emotional evaluation tasks may be caused by emotional priority. Our findings support the intuitive model's emotional dominance hypothesis and introduce a new emotional mechanism into moral evaluation. This study clarifies the distinct emotional processes in moral and immoral evaluations, fills a gap in the research on moral evaluation, and offers insights into human decision-making in moral contexts.

Apathy and effort-based decision-making in Alzheimer's disease and subjective cognitive impairment.

Apathy is a significant feature in Alzheimer's disease (AD) and subjective cognitive impairment (SCI), though its mechanisms are not well established. An effort-based decision-making (EBDM) framework was applied to investigate apathy in 30 AD patients, 41 SCI participants, and 55 healthy controls (HC). Data were analyzed using a drift-diffusion model (DDM) to uncover latent psychological processes. SCI participants reported higher apathy than AD patients and HC. However, informant reports of apathy in AD patients were higher than self-reports and indicated significant apathy compared to HC. Both the AD and SCI groups showed reduced sensitivity to effort changes, linked to executive dysfunction in AD and apathy in SCI. Increased resting functional cortical connectivity with the nucleus accumbens (NA) was associated with higher apathy in SCI. These results highlight a similar disruption of EBDM in AD and SCI, differentially related to executive functioning in AD and apathy in SCI. This is the first study investigating apathy using an effort-based decision-making (EBDM) framework in Alzheimer's disease (AD) and subjective cognitive impairment (SCI).Self-reports underestimate apathy in AD patients when compared to informant reports and healthy controls (HC). SCI participants, in whom self and informant reports were more concordant, also showed higher degrees of apathy.Both AD and SCI groups showed reduced sensitivity to effort.Reduced sensitivity to effort correlates with executive dysfunction in AD and apathy, but not depression, in SCI.Increased nucleus accumbens (ventral striatum) connectivity with the frontoparietal network was associated with higher apathy scores in SCI.The results thus suggest that while AD and SCI can have similar deficits in EBDM, these deficits correlate with distinct clinical manifestations: executive dysfunction in AD and apathy in SCI.

Lower motivation for rewarded mental effort in tobacco dependence.

Tobacco dependence is characterized by decision-making impairments, which may increase the risk of smoking relapse by lowering the capacity to resist the immediate gratification of nicotine consumption. Because controlling one's desires for immediate rewards is experienced as effortful, aversion to effortful control processes may also influence the prospects of successful smoking cessation. We therefore tested whether persons who smoke, compared with persons who do not smoke, show a lower willingness to engage in goal-directed mental effort. Thirty-seven persons who smoke and 38 persons who do not smoke performed a decision task requiring choices on whether to exert a demanding attention task for monetary rewards. Using state-of-the-art drift-diffusion modeling, we found that persons who smoke showed a stronger starting bias toward effort-free rewards. Taken together, our process model approach allowed us to identify the subcomponents of the decision process underlying the stronger aversion against mental effort in tobacco dependence, which may contribute to altered decision making by lowering the motivation to engage in effortful control processes when trying to suppress the desire for nicotine consumption. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Physically stressed bees expect less reward in an active choice judgement bias test.

Emotion-like states in animals are commonly assessed using judgment bias tests that measure judgements of ambiguous cues. Some studies have used these tests to argue for emotion-like states in insects. However, most of these results could have other explanations, including changes in motivation and attention. To control for these explanations, we developed a novel judgment bias test, requiring bumblebees to make an active choice indicating their interpretation of ambiguous stimuli. Bumblebees were trained to associate high or low rewards, in two different reward chambers, with distinct colours. We subsequently presented bees with ambiguous colours between the two learnt colours. In response, physically stressed bees were less likely than control bees to enter the reward chamber associated with high reward. Signal detection and drift diffusion models showed that stressed bees were more likely to choose low reward locations in response to ambiguous cues. The signal detection model further showed that the behaviour of stressed bees was explained by a reduction in the estimated probability of high rewards. We thus provide strong evidence for judgement biases in bees and suggest that their stress-induced behaviour is explained by reduced expectation of higher rewards, as expected for a pessimistic judgement bias.

Logarithmic Sobolev inequalities for bounded domains and applications to drift-diffusion equations

We prove logarithmic Sobolev inequalities on higher-dimensional bounded smooth domains based on novel Gagliardo-Nirenberg type interpolation inequalities. Moreover, we use them to address the long-time dynamics of some nonlinear nonlocal drift-diffusion models and prove the exponential decay of their solutions to constant steady states.

The Role of the Rat Prefrontal Cortex and Sex Differences in Decision-Making.

The prefrontal cortex is critical for decision-making across species, with its activity linked to choosing between options. Drift Diffusion Models (DDMs) are commonly employed to understand the neural computations underlying this behavior. Studies exploring the specific roles of regions of the rodent prefrontal cortex in controlling the decision process are limited. This study explored the role of the prelimbic cortex (PLC) in decision-making using a two-alternative forced-choice task. Rats first learned to report the location of a lateralized visual stimulus. The brightness of the stimulus indicated its reward value. Then, the rats learned to make choices between pairs of stimuli. Sex differences in learning were observed, with females responding faster and more selectively to high-value stimuli than males. DDM analysis found that males had decreased decision thresholds during initial learning, whereas females maintained a consistently higher drift rate. Pharmacological manipulations revealed that PLC inactivation reduced the decision threshold for all rats, indicating that less information was needed to make a choice in the absence of normal PLC processing. Mu opioid receptor stimulation of the PLC had the opposite effect, raising the decision threshold and reducing bias in the decision process towards high-value stimuli. These effects were observed without any impact on the rats' choice preferences. Our findings suggest that PLC has an inhibitory role in the decision process and regulates the amount of evidence that is required to make a choice. That is, PLC activity controls "when", but not "how", to act.Significance Statement This study reports causal evidence for a part of the rat prefrontal cortex, the prelimbic cortex, in controlling the amount of information needed to make a choice. Results were based on reversible inactivation using the GABA-A agonist muscimol and by stimulation of mu opioid receptors using intra-cortical infusions of the selective mu agonist DAMGO. We also found evidence for a sex difference in learning and performing a visually guided two-alternative forced-choice task. Drift Diffusion Models found that females had stable decision processes throughout learning, and showed a persistent bias against the lower value option. By contrast, males exhibited changes in their decision processes, notably reducing the amount of information needed to make choice over the period of early choice learning.

Exogenous spatial attention selects associated novel bindings in working memory

Real-world environments are complex, demanding a diverse set of cognitive functions such as attention and working memory (WM) to perform adaptive behaviors. However, exogenous attention, characterized as automatic and involuntary, has primarily been studied by focusing on spatial perception. In particular, the ability of pure exogenous retro-cues to select and prioritize not only spatial locations, but also novel stimulus–response (S-R) bindings held in WM remains largely unexplored. Here, in two experimental series, we provide evidence that pure exogenous non-predictive retro-cues can select not only space, but also associated S-R bindings held in WM. Additional evidence from a drift–diffusion model hinted at the possibility that the mechanisms through which exogenous attention selects and prioritizes WM contents depend, at least partially, on the hierarchical relevance of the different dimensions encoded within a specific representation. These results highlight the relationship between pure exogenous attention and complex WM contents and shed light on current theoretical debates about the interaction of attention, memory, and action.

Getting more out of response time measures: Delineating separable motor and cognitive subcomponents of response time via drift diffusion modeling

Getting more out of response time measures: Delineating separable motor and cognitive subcomponents of response time via drift diffusion modeling

Decision cost hypersensitivity underlies Huntington's disease apathy.

The neuropsychiatric syndrome of apathy is now recognized to be a common and disabling condition in Huntington's disease (HD). However, the mechanisms underlying it are poorly understood. One way to investigate apathy is to utilise a theoretical framework of normal motivated behaviour, to determine where breakdown has occurred in people with this behavioural disruption. A fundamental computation underlying motivated, goal-directed behaviour across species is weighing up the costs and rewards associated with actions. Here, we asked whether people with apathy are more sensitive to costs of actions (physical effort and time delay), less sensitive to rewarding outcomes, or both. Based on the unique anatomical substrates associated with HD pathology, we hypothesised that a general hypersensitivity to costs would underpin HD apathy. Genetically confirmed carriers of the expanded Huntingtin gene (premanifest to mild motor manifest disease (n=53) were compared to healthy controls (n = 38). Participants performed a physical effort-based decision-making task (Apple Gathering Task) and a delay discounting task (Money Choice Questionnaire). Choice data was analysed using linear regression and drift diffusion models that also accounted for the time taken to make decisions. Apathetic people with HD accepted fewer offers overall on the Apple Gathering Task, specifically driven by increased sensitivity to physical effort costs, and not explained by motor severity, mood, cognition, or medication. Drift diffusion modelling provided further evidence of effort hypersensitivity, with apathy associated with a faster drift rate towards rejecting offers as a function of varying effort. Increased delay sensitivity was also associated with apathy, both when analysing raw choice and also drift rate, where there was moderate evidence of HD apathy drifting faster towards the immediately available (low cost) option. Furthermore, the effort and delay sensitivity parameters from these tasks were positively correlated. The results demonstrate a clear mechanism for apathy in HD, cost hypersensitivity, which manifests in both the effort and time costs associated with actions towards rewarding goals. This suggests that HD pathology may cause a domain-general disruption of cost processing, which is distinct to apathy occurrence in other brain disorders, and may require different therapeutic approaches.

An effective drift-diffusion model for pandemic propagation and uncertainty prediction

Predicting pandemic evolution involves complex modeling challenges, typically involving detailed discrete mathematics executed on large volumes of epidemiological data. Making them physics based provides added intuition as well as predictive value. Differential equations have the advantage of offering smooth, well-behaved solutions that try to capture overall predictive trends and averages. In this paper, the canonical susceptible-infected-recovered model is simplified, in the process generating quasi-analytical solutions and fitting functions that agree well with the numerics, as well as infection data across multiple countries. The equations provide an elegant way to visualize the evolution of the pandemic spread, by drawing equivalents with the similar dynamics of a particle, whose location over time represents the growing fraction of the population that is infected. This particle slides down a potential whose shape is set by model epidemiological parameters such as reproduction rate. Potential sources of errors and their growth over time are identified, and the uncertainties are mapped into a diffusive jitter that tends to push the particle away from its minimum. The combined physical understanding and analytical expressions offered by such an intuitive drift-diffusion model sets the foundation for their eventual extension to a multi-patch model while offering practical error bounds and could thus be useful in making policy decisions going forward.

Cognitive Mechanisms of Aberrant Self-Referential Social Perception in Psychosis and Bipolar Disorder: Insights From Computational Modeling.

Individuals with schizophrenia (SZ) and bipolar disorder (BD) show disruptions in self-referential gaze perception-a social perceptual process related to symptoms and functioning. However, our current mechanistic understanding of these dysfunctions and relationships is imprecise. The present study used mathematical modeling to uncover cognitive processes driving gaze perception abnormalities in SZ and BD, and how they relate to cognition, symptoms, and social functioning. We modeled the behavior of 28 SZ, 38 BD, and 34 controls (HC) in a self-referential gaze perception task using drift-diffusion models parameterized to index key cognitive components: drift rate (evidence accumulation efficiency), drift bias (perceptual bias), start point (expectation bias), threshold separation (response caution), and nondecision time (encoding/motor processes). Results revealed that aberrant gaze perception in SZ and BD was driven by less efficient evidence accumulation, perceptual biases predisposing self-referential responses, and greater caution (SZ only). Across SZ and HC, poorer social functioning was related to greater expectation biases. Within SZ, perceptual and expectancy biases were associated with hallucination and delusion severity, respectively. These findings indicate that diminished evidence accumulation and perceptual biases may underlie altered gaze perception in patients and that SZ may engage in compensatory cautiousness, sacrificing response speed to preserve accuracy. Moreover, biases at the belief and perceptual levels may relate to symptoms and functioning. Computational modeling can, therefore, be used to achieve a more nuanced, cognitive process-level understanding of the mechanisms of social cognitive difficulties, including gaze perception, in individuals with SZ and BD.

Optimal level of human intracranial theta activity for behavioral switching in the subthalamo-medio-prefrontal circuit

The ability to switch between rules associating stimuli and responses depend on a circuit including the dorsomedial prefrontal cortex (dmPFC) and the subthalamic nucleus (STN). However, the precise neural implementations of switching remain unclear. To address this issue, we recorded local field potentials from the STN and from the dmPFC of neuropsychiatric patients during behavioral switching. Drift-diffusion modeling revealed that switching is associated with a shift in the starting point of evidence accumulation. Theta activity increases in dmPFC and STN during successful switch trials, while temporally delayed and excessive levels of theta lead to premature switch errors. This seemingly opposing impact of increased theta in successful and unsuccessful switching is explained by a negative correlation between theta activity and the starting point. Together, these results shed a new light on the neural mechanisms underlying the rapid reconfiguration of stimulus-response associations, revealing a Goldilocks’ effect of theta activity on switching behavior.