Individual differences moderate effects in an Unusual Disease paradigm: A psychophysical data collection lab approach and an online experiment.

We report two studies investigating individual intuitive-deliberative cognitive-styles and risk-styles as moderators of the framing effect in Tversky and Kahneman's famous Unusual Disease problem setting. We examined framing effects in two ways: counting the number of frame-inconsistent choices and comparing the proportions of risky choices depending on gain-loss framing. Moreover, in addition to gain-loss frames, we systematically varied the number of affected people, probabilities of surviving/dying, type of disease, and response deadlines. Study 1 used a psychophysical data collection approach and a sample of 43 undergraduate students, each performing 480 trials. Study 2 was an online study incorporating psychophysical elements in a social science approach using a larger and more heterogeneous sample, i.e., 262 participants performed 80 trials each. In both studies, the effect of framing on risky choice proportions was moderated by risk-styles. Cognitive-styles measured on different scales moderated the framing effect only in study 2. The effects of disease type, probability of surviving/dying, and number of affected people on risky choice frequencies were also affected by cognitive-styles and risk-styles but different for both studies and to different extents. We found no relationship between the number of frame-inconsistent choices and cognitive-styles or risk-styles, respectively.

Keep your budget together! Investigating determinants on risky decision-making about losses.

The present study investigates the influence of framing, different amounts to lose, and probabilities of a risky and sure choice option, time limits, and need on risky decision-making. For a given block of trials, participants were equipped with a personal budget (number of points). On each trial within a block, a specific initial amount is possibly taken from the budget by the outcome of a gamble or the choice of a sure loss option. The goal was to avoid losing points from the budget for not falling below a predefined need threshold. Three different levels of induced need were included. Employing a psychophysical experimental approach, we furthermore tested a sequential component of human risk behavior towards a need threshold inspired by research on animal foraging behavior. Risk-sensitivity models and the Stone-Geary framework serve as generating hypotheses on need thresholds. We found that framing, need, and probabilities influenced risky choices. Time limits and initial amounts moderated the framing effect. No sequential component was observed.

A two-stage diffusion modeling approach to the compelled-response task.

The issue of how perception and motor planning interact to generate a given choice between actions is a fundamental question in both psychology and neuroscience. Salinas and colleagues have developed a behavioral paradigm, the compelled-response task, where the signal that instructs the subject to make an eye movement is given before the cue that indicates which of two possible target choices is the correct one. When the cue is given rather late, the participant must guess and make an uninformed random choice. Perceptual performance can be tracked as a function of the amount of time during which sensory information is available. In Salinas' accelerated race-to-threshold model, two variables race against each other to a threshold, at which a saccade is initiated. The source of random variability is in the initial state of information buildup across trials. This implies that incorrect decisions are due to the inertia of the racing variables that have, at the start, sampled a constant buildup in the "wrong" direction. Here we suggest an alternative, non-time-homogeneous two-stage-diffusion model that is able to predict both response time distributions and choice probabilities with a few easy-to-interpret parameters and without assuming cross-trial parameter variability. It is falsifiable already at the level of qualitative features, for example, predicting bimodal reaction time (RT) distributions for particular gap times. It connects the compelled-response paradigm with an approach to decision making that has been uniquely successful in describing both behavioral and neural data in a variety of experimental settings for the last 40 years. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Gamble for the needy! Does identifiability enhances donation?

To investigate how neediness and identifiability of a recipient influence the willingness of a donor to invest resources in charity-like lotteries we propose a new game, called 'need game'. Similar to the dictator game, the need game includes two players, one active player (the donor or dictator) and one passive player (the recipient). Both players require a minimum need (ND and NR), expressed in terms of points. The donor is endowed with KD points and must retain at least ND points, i.e., the need, with ND < KD, at the end of the game with n rounds. The recipient starts with KR points and must end the game with at least NR points, i.e., the need, with KR < NR < KD. The donor is asked to choose one of three different amounts from KD to place a bet on a lottery. If won, the gain is added to the endowment. If lost, the recipient receives the points. The recipient is paid only when his/her need threshold is obtained; likewise the donor gets paid only when his/her need threshold is maintained. The main focus here is on need of both players (ND = NR = 2, 200, and ND = NR = 0 serving as baseline control) and the identifiability of the recipient (no information, described by text and picture, and physical presence). We probe whether the amount invested by the donor depends on need and identifiability of the recipient. In addition, we include the framing of the game as gain or loss, different probabilities to win/lose, and different time limits as covariates. We found that each of these factors can play a role when investing in charity-like lotteries.

Formal models and quantitative measures of multisensory integration: a selective overview.

Multisensory integration (MI) is defined as the neural process by which unisensory signals are combined to form a new product that is significantly different from the responses evoked by the modality-specific component stimuli. In recent years, MI research has seen exponential growth in the number of empirical and theoretical studies. This study presents a selective overview of formal modeling approaches to MI. Emphasis is on models and measures for behavioral paradigms, such as localization, judgment of temporal order or simultaneity, and reaction times, but some concepts for the modeling of single-cell spike rates are treated as well. We identify a number of essential concepts underlying most model classes, such as Bayesian causal inference, probability summation, coactivation, and time window of integration. Quantitative indexes for measuring and comparing the strength of MI across different paradigms are also discussed. Whereas progress over the last years is remarkable, we point out some strengths and weaknesses of the modeling approaches and discuss some obstacles toward a unified theory of MI.

A Dynamic Dual Process Model of Intertemporal Choice.

Dual process theories of decision making describe choice as the result of an automatic System 1, which is quick to activate but behaves impulsively, and a deliberative System 2, which is slower to activate but makes decisions in a rational and controlled manner. However, most existent dual process theories are verbal descriptions and do not generate testable qualitative and quantitative predictions. In this paper, we describe a formalized dynamic dual process model framework of intertemporal choice that allows for precise, experimentally testable predictions regarding choice probability and response time distributions. The framework is based on two-stage stochastic process models to account for the two postulated systems and to capture the dynamics and uncertainty involved in decision making. Using quasi closed form solutions, we illustrate how different factors (timing of System 1, time constraint, and preferences in both systems), which are reflected in the model parameters, influence qualitative and quantitative model predictions. Furthermore, we show how an existing static-deterministic model on intertemporal choice can be implemented in the framework allowing for testable predictions. The proposed framework can bring novel insights into the processes underlying intertemporal choices.

Dependency in multisensory integration: a copula-based analysis.

The notion of copula has attracted attention from the field of contextuality and probability. A copula is a function that joins a multivariate distribution to its one-dimensional marginal distributions. Thereby, it allows characterizing the multivariate dependency separately from the specific choice of margins. Here, we demonstrate the use of copulas by investigating the structure of dependency between processing stages in a stochastic model of multisensory integration, which describes the effect of stimulation by several sensory modalities on human reaction times. We derive explicit terms for the covariance and Kendall's tau between the processing stages and point out the specific role played by two stochastic order relations, the usual stochastic order and the likelihood ratio order, in determining the sign of dependency. This article is part of the theme issue 'Contextuality and probability in quantum mechanics and beyond'.

Automatic biases in intertemporal choice.

Dual process theories of intertemporal decision making propose that decision makers automatically favor immediate rewards. In this paper, we use a drift diffusion model to implement these theories, and empirically investigate the role of their proposed automatic biases. Our model permits automatic biases in the response process, in the form of a shifted starting point, as well as automatic biases in the evaluation process, in the form of an additive drift rate intercept. We fit our model to individual-level choice and response time data, and find that automatic biases (as measured though the starting point and drift rate intercept in our model) are prevalent in intertemporal choice, but that the type, magnitude, and direction of these biases vary greatly across individuals. Our results pose new challenges for theories of intertemporal choice behavior.

Multisensory Integration and Exogenous Spatial Attention: A Time-window-of-integration Analysis.

Although it is well documented that occurrence of an irrelevant and nonpredictive sound facilitates motor responses to a subsequent target light appearing nearby, the cause of this "exogenous spatial cuing effect" has been under discussion. On the one hand, it has been postulated to be the result of a shift of visual spatial attention possibly triggered by parietal and/or cortical supramodal "attention" structures. On the other hand, the effect has been considered to be due to multisensory integration based on the activation of multisensory convergence structures in the brain. Recent RT experiments have suggested that multisensory integration and exogenous spatial cuing differ in their temporal profiles of facilitation: When the nontarget occurs 100-200 msec before the target, facilitation is likely driven by crossmodal exogenous spatial attention, whereas multisensory integration effects are still seen when target and nontarget are presented nearly simultaneously. Here, we develop an extension of the time-window-of-integration model that combines both mechanisms within the same formal framework. The model is illustrated by fitting it to data from a focused attention task with a visual target and an auditory nontarget presented at horizontally or vertically varying positions. Results show that both spatial cuing and multisensory integration may coexist in a single trial in bringing about the crossmodal facilitation of RT effects. Moreover, the formal analysis via time window of integration allows to predict and quantify the contribution of either mechanism as they occur across different spatiotemporal conditions.

A dynamic dual process model of intertemporal choice

Dual process theories of decision making describe choice as the result of an automatic System 1, which is quick to activate but behaves impulsively, and a deliberative System 2, which is slower to activate but makes decisions in a rational and controlled manner. However, most existent dual process theories are verbal descriptions and do not generate testable qualitative and quantitative predictions. In this paper, we describe a formalized dynamic dual process model framework of intertemporal choice that allows for precise, experimentally testable predictions regarding choice probability and response time distributions. The framework is based on two-stage stochastic process models to account for the two postulated systems and to capture the dynamics and uncertainty involved in decision making. Using quasi closed form solutions, we illustrate how different factors (timing of System 1, time constraint, and preferences in both systems), which are reflected in the model parameters, influence qualitative and quantitative model predictions. Furthermore, we show how an existing static-deterministic model on intertemporal choice can be implemented in the framework allowing for testable predictions. The proposed framework can bring novel insights into the processes underlying intertemporal choices

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Paradox resolved: Stop signal race model with negative dependence.

The ability to inhibit our responses voluntarily is an important case of cognitive control. The stop-signal paradigm is a popular tool to study response inhibition. Participants perform a response time task (go task), and occasionally, the go stimulus is followed by a stop signal after a variable delay, indicating subjects to withhold their response (stop task). The main interest of modeling is in estimating the unobservable stop-signal processing time, that is, the covert latency of the stopping process as a characterization of the response inhibition mechanism. In the independent race model, the stop-signal task is represented as a race between stochastically independent go and stop processes. Without making any specific distributional assumptions about the processing times, the model allows estimating the mean time to cancel a response. Neurophysiological studies on countermanding saccadic eye movements, however, have shown that the neural correlates of go and stop processes consist of networks of mutually interacting gaze-shifting and gaze-holding neurons. This poses a major challenge in formulating linking propositions between the behavioral and neural findings. Here we propose a dependent race model that postulates perfect negative stochastic dependence between go and stop activations. The model is consistent with the concept of interacting processes while retaining the simplicity and elegance of the distribution-free independent race model. For mean data, the dependent model's predictions remain identical to those of the independent model. The resolution of this apparent paradox advances the understanding of mechanisms of response inhibition and paves the way for modeling more complex situations. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Multisensory perception reflects individual differences in processing temporal correlations.

Sensory signals originating from a single event, such as audiovisual speech, are temporally correlated. Correlated signals are known to facilitate multisensory integration and binding. We sought to further elucidate the nature of this relationship, hypothesizing that multisensory perception will vary with the strength of audiovisual correlation. Human participants detected near-threshold amplitude modulations in auditory and/or visual stimuli. During audiovisual trials, the frequency and phase of auditory modulations were varied, producing signals with a range of correlations. After accounting for individual differences which likely reflect relative unisensory temporal characteristics in participants, we found that multisensory perception varied linearly with strength of correlation. Diffusion modelling confirmed this and revealed that stimulus correlation is supplied to the decisional system as sensory evidence. These data implicate correlation as an important cue in audiovisual feature integration and binding and suggest correlational strength as an important factor for flexibility in these processes.

A dynamic dual process model of risky decision making.

Many phenomena in judgment and decision making are often attributed to the interaction of 2 systems of reasoning. Although these so-called dual process theories can explain many types of behavior, they are rarely formalized as mathematical or computational models. Rather, dual process models are typically verbal theories, which are difficult to conclusively evaluate or test. In the cases in which formal (i.e., mathematical) dual process models have been proposed, they have not been quantitatively fit to experimental data and are often silent when it comes to the timing of the 2 systems. In the current article, we present a dynamic dual process model framework of risky decision making that provides an account of the timing and interaction of the 2 systems and can explain both choice and response-time data. We outline several predictions of the model, including how changes in the timing of the 2 systems as well as time pressure can influence behavior. The framework also allows us to explore different assumptions about how preferences are constructed by the 2 systems as well as the dynamic interaction of the 2 systems. In particular, we examine 3 different possible functional forms of the 2 systems and 2 possible ways the systems can interact (simultaneously or serially). We compare these dual process models with 2 single process models using risky decision making data from Guo, Trueblood, and Diederich (2017). Using this data, we find that 1 of the dual process models significantly outperforms the other models in accounting for both choices and response times. (PsycINFO Database Record

Trimodal Race Model Inequalities in Multisensory Integration: I. Basics.

The race model inequality has become an important testing tool for the analysis of redundant signals tasks. In crossmodal reaction time experiments, the strength of violation of the inequality is taken as measure of multisensory integration occurring beyond probability summation. Here we extend previous results on trimodal race model inequalities and specify the underlying context invariance assumptions required for their validity. Some simulation results comparing the race model and the superposition model for Erlang distributed random variables illustrate the trimodal inequalities.

Measuring multisensory integration: from reaction times to spike counts.

A neuron is categorized as "multisensory" if there is a statistically significant difference between the response evoked, e.g., by a crossmodal stimulus combination and that evoked by the most effective of its components separately. Being responsive to multiple sensory modalities does not guarantee that a neuron has actually engaged in integrating its multiple sensory inputs: it could simply respond to the stimulus component eliciting the strongest response in a given trial. Crossmodal enhancement is commonly expressed as a proportion of the strongest mean unisensory response. This traditional index does not take into account any statistical dependency between the sensory channels under crossmodal stimulation. We propose an alternative index measuring by how much the multisensory response surpasses the level obtainable by optimally combining the unisensory responses, with optimality defined as probability summation under maximal negative stochastic dependence. The new index is analogous to measuring crossmodal enhancement in reaction time studies by the strength of violation of the "race model inequality', a numerical measure of multisensory integration. Since the new index tends to be smaller than the traditional one, neurons previously labeled as "multisensory' may lose that property. The index is easy to compute and it is sensitive to variability in data.

Thinking Fast Increases Framing Effects in Risky Decision Making.

Every day, people face snap decisions when time is a limiting factor. In addition, the way a problem is presented can influence people's choices, which creates what are known as framing effects. In this research, we explored how time pressure interacts with framing effects in risky decision making. Specifically, does time pressure strengthen or weaken framing effects? On one hand, research has suggested that framing effects evolve through the deliberation process, growing larger with time. On the other hand, dual-process theory attributes framing effects to an intuitive, emotional system that responds automatically to stimuli. In our experiments, participants made decisions about gambles framed in terms of either gains or losses, and time pressure was manipulated across blocks. Results showed increased framing effects under time pressure in both hypothetical and incentivized choices, which supports the dual-process hypothesis that these effects arise from a fast, intuitive system.

What health care services does the public want and who should decide? Ask them!

Most of the parties involved in healthcare decisions - governments, politicians, healthcare professionals, pharmaceutical companies, special interest groups - actively work to make their desires known. In Israel the public is part of the decision committee; in Germany health care decision are made more or less without the public being involved. In a recently published IJHPR article, Giora Kaplan and Orna Baron-Epel raise the question of how well acquainted senior decision makers in the Israeli health system are with the public's priorities regarding the services being considered for inclusion in the public funding list. This commentary speculates about the reasons for the discrepancies found in that article between the decision makers' and the public's view. Furthermore, it reports on survey results from Germany about who should be part of the decision making committee and briefly touches upon the situation in other OECD countries. While public opinion may not be the determining factor, all authors advocate a strengthening of the public's contribution to the health care decision making process, including steps to make decision makers aware of public priorities on an ongoing basis.

Prior knowledge of spatiotemporal configuration facilitates crossmodal saccadic response : A TWIN analysis.

Saccadic reaction times from a focused-attention task with a visual target and an acoustic nontarget support the hypothesis that the amount of saccadic facilitation in the presence of a nontarget increases with the prior knowledge of alignment with the target across different blocks of trials. The time-window-of-integration model can account for the size of the effect by having window size depend on the prior knowledge of alignment. Some efforts to identify the neural correlates of the effect are discussed.

The time window of multisensory integration: relating reaction times and judgments of temporal order.

Even though visual and auditory information of 1 and the same event often do not arrive at the sensory receptors at the same time, due to different physical transmission times of the modalities, the brain maintains a unitary perception of the event, at least within a certain range of sensory arrival time differences. The properties of this "temporal window of integration" (TWIN), its recalibration due to task requirements, attention, and other variables, have recently been investigated intensively. Up to now, however, there has been no consistent definition of "temporal window" across different paradigms for measuring its width. Here we propose such a definition based on our TWIN model (Colonius & Diederich, 2004). It applies to judgments of temporal order (or simultaneity) as well as to reaction time (RT) paradigms. Reanalyzing data from Mégevand, Molholm, Nayak, & Foxe (2013) by fitting the TWIN model to data from both paradigms, we confirmed the authors' hypothesis that the temporal window in an RT task tends to be wider than in a temporal-order judgment (TOJ) task. This first step toward a unified concept of TWIN should be a valuable tool in guiding investigations of the neural and cognitive bases of this so-far-somewhat elusive concept.

Fronto-central theta oscillations are related to oscillations in saccadic response times (SRT): an EEG and behavioral data analysis.

The phase reset hypothesis states that the phase of an ongoing neural oscillation, reflecting periodic fluctuations in neural activity between states of high and low excitability, can be shifted by the occurrence of a sensory stimulus so that the phase value become highly constant across trials (Schroeder et al., 2008). From EEG/MEG studies it has been hypothesized that coupled oscillatory activity in primary sensory cortices regulates multi sensory processing (Senkowski et al. 2008). We follow up on a study in which evidence of phase reset was found using a purely behavioral paradigm by including also EEG measures. In this paradigm, presentation of an auditory accessory stimulus was followed by a visual target with a stimulus-onset asynchrony (SOA) across a range from 0 to 404 ms in steps of 4 ms. This fine-grained stimulus presentation allowed us to do a spectral analysis on the mean SRT as a function of the SOA, which revealed distinct peak spectral components within a frequency range of 6 to 11 Hz with a modus of 7 Hz. The EEG analysis showed that the auditory stimulus caused a phase reset in 7-Hz brain oscillations in a widespread set of channels. Moreover, there was a significant difference in the average phase at which the visual target stimulus appeared between slow and fast SRT trials. This effect was evident in three different analyses, and occurred primarily in frontal and central electrodes.