The Tweedledum and Tweedledee of dynamic decisions: Discriminating between diffusion decision and accumulator models.

Theories of dynamic decision-making are typically built on evidence accumulation, which is modeled using racing accumulators or diffusion models that track a shifting balance of support over time. However, these two types of models are only two special cases of a more general evidence accumulation process where options correspond to directions in an accumulation space. Using this generalized evidence accumulation approach as a starting point, I identify four ways to discriminate between absolute-evidence and relative-evidence models.

Decisions among shifting choice alternatives reveal option-general representations of evidence.

Dynamic models of choice typically describe the decision-making process in terms of the degree or balance of support for available response options. However, these alternative-specific representations of support are liable to fail when the available options change during the course of a decision. We suggest that people may use alternative-general representations, where stimulus feature information-rather than option-specific support-is accumulated over time and mapped onto support for available options as they appear.

The Social Environment Matters for Telomere Length and Internalizing Problems During Adolescence.

Depression and anxiety symptoms are on the rise among adolescents. With increasing evidence that cellular aging may be associated with depressive and anxiety symptoms, there is an urgent need to identify the social environment context that may moderate this link. This study addresses this research gap by investigating the moderating role of the social environment on the relation between telomere length and emotional health among adolescents.

Improving the reliability and validity of the IAT with a dynamic model driven by similarity.

The Implicit Association Test (IAT), like many behavioral measures, seeks to quantify meaningful individual differences in cognitive processes that are difficult to assess with approaches like self-reports. However, much like other behavioral measures, many IATs appear to show low test-retest reliability and typical scoring methods fail to quantify all of the decision-making processes that generate the overt task performance. Here, we develop a new modeling approach for IATs based on the geometric similarity representation (GSR) model.

Explaining the description-experience gap in risky decision-making: learning and memory retention during experience as causal mechanisms.

When making decisions based on probabilistic outcomes, people guide their behavior using knowledge gathered through both indirect descriptions and direct experience. Paradoxically, how people obtain information significantly impacts apparent preferences. A ubiquitous example is the description-experience gap: individuals seemingly overweight low probability events when probabilities are described yet underweight them when probabilities must be experienced firsthand.

A unified theory of discrete and continuous responding.

Understanding the cognitive processes underlying choice requires theories that can disentangle the representation of stimuli from the processes that map these representations onto observed responses. We develop a dynamic theory of how stimuli are mapped onto discrete (choice) and onto continuous response scales. It proposes that the mapping from a stimulus to an internal representation and then to an evidence accumulation process is accomplished using multiple reference points or "anchors.

Rational inference strategies and the genesis of polarization and extremism.

Polarization and extremism are often viewed as the product of psychological biases or social influences, yet they still occur in the absence of any bias or irrational thinking. We show that individual decision-makers implementing optimal dynamic decision strategies will become polarized, forming extreme views relative to the true information in their environment by virtue of how they sample new information. Extreme evidence enables decision makers to stop considering new information, whereas weak or moderate evidence is unlikely to trigger a decision and is thus under-sampled.

Reconciling similarity across models of continuous selections.

Recently developed models of decision-making have provided accounts of the cognitive processes underlying choice on tasks where responses can fall along a continuum, such as identifying the color or orientation of a stimulus. Even though nearly all of these models seek to extend diffusion decision processes to a continuum of response options, they vary in terms of complexity, tractability, and their ability to predict patterns of data such as multimodal distributions of responses. We suggest that these differences are almost entirely due to differences in how these models account for the similarity among response options.

Temporal oscillations in preference strength provide evidence for an open system model of constructed preference.

The decision process is often conceptualized as a constructive process in which a decision maker accumulates information to form preferences about the choice options and ultimately make a response. Here we examine how these constructive processes unfold by tracking dynamic changes in preference strength. Across two experiments, we observed that mean preference strength systematically oscillated over time and found that eliciting a choice early in time strongly affected the pattern of preference oscillation later in time.

Hierarchies improve individual assessment of temporal discounting behavior.

Delay discounting behavior has proven useful in assessing impulsivity across a wide range of populations. As such, accurate estimation of the shape of each individual's temporal discounting profile is paramount when drawing conclusions about how impulsivity relates to clinical and health outcomes such as gambling, addiction, and obesity. Here, we identify an estimation problem with current methods of assessing temporal discounting behavior, and propose a simple solution.

A dynamic model of deciding not to choose.

We propose a dynamic theory of decisions not to choose which of 2 options is correct. Such "do not-know" judgments are of theoretical and practical importance in domains ranging from comparative psychology, psychophysics, episodic memory, and metacognition to applied areas including educational testing and eyewitness testimony. However, no previous theory has provided a detailed quantitative account of the time it takes to make both definitive and do not-know responses and their relative frequencies.

A distributional and dynamic theory of pricing and preference.

Theories that describe how people assign prices and make choices are typically based on the idea that both of these responses are derived from a common static, deterministic function used to assign utilities to options. However, preference reversals-where prices assigned to gambles conflict with preference orders elicited through binary choices-indicate that the response processes underlying these different methods of evaluation are more intricate. We address this issue by formulating a new computational model that assumes an initial bias or anchor that depends on type of price task (buying, selling, or certainty equivalents) and a stochastic evaluation accumulation process that depends on gamble attributes.

Testing the factor structure underlying behavior using joint cognitive models: Impulsivity in delay discounting and Cambridge gambling tasks.

Neurocognitive tasks are frequently used to assess disordered decision making, and cognitive models of these tasks can quantify performance in terms related to decision makers' underlying cognitive processes. In many cases, multiple cognitive models purport to describe similar processes, but it is difficult to evaluate whether they measure the same latent traits or processes. In this article, we develop methods for modeling behavior across multiple tasks by connecting cognitive model parameters to common latent constructs.

Comparison of Markov versus quantum dynamical models of human decision making.

What kind of dynamic decision process do humans use to make decisions? In this article, two different types of processes are reviewed and compared: Markov and quantum. Markov processes are based on the idea that at any given point in time a decision maker has a definite and specific level of support for available choice alternatives, and the dynamic decision process is represented by a single trajectory that traces out a path across time. When a response is requested, a person's decision or judgment is generated from the current location along the trajectory.

The Confidence Database.

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages.

Markov versus quantum dynamic models of belief change during evidence monitoring.

Two different dynamic models for belief change during evidence monitoring were evaluated: Markov and quantum. They were empirically tested with an experiment in which participants monitored evidence for an initial period of time, made a probability rating, then monitored more evidence, before making a second rating. The models were qualitatively tested by manipulating the time intervals in a manner that provided a test for interference effects of the first rating on the second.

Modeling accuracy, response time, and bias in continuous orientation judgments.

Despite the prevalence of real-world and laboratory tasks where people select among many options, cognitive models have traditionally focused on choices among small sets of alternatives. This has resulted in theoretical and empirical gaps in understanding the decision processes that go into selections among many alternatives or responses that fall along a continuum. This paper addresses these issues by modeling decisions in a perceptual study where participants produce continuous orientation judgments.

Neural implementation of operations used in quantum cognition.

Quantum probability theory has been successfully applied outside of physics to account for numerous findings from psychology regarding human judgement and decision making behavior. However, the researchers who have made these applications do not rely on the hypothesis that the brain is some type of quantum computer. This raises the question of how could the brain implement quantum algorithms other than quantum physical operations.

Strength and weight: The determinants of choice and confidence.

Evidence for different hypotheses is often treated as a singular construct, but it can be dissociated into two parts: its strength, the proportion of pieces of information favoring one hypothesis; and its weight, the total number of pieces of information available. However, cognitive and neural models of evidence accumulation often make a proportional representation assumption, implying that people take these two factors into account equally when making their decisions and judgments. We examine this assumption by directly manipulating the number of samples and the proportion favoring either of two alternatives in dynamic decision making and judgment tasks.

Interference effects of choice on confidence: Quantum characteristics of evidence accumulation.

Decision-making relies on a process of evidence accumulation which generates support for possible hypotheses. Models of this process derived from classical stochastic theories assume that information accumulates by moving across definite levels of evidence, carving out a single trajectory across these levels over time. In contrast, quantum decision models assume that evidence develops over time in a superposition state analogous to a wavelike pattern and that judgments and decisions are constructed by a measurement process by which a definite state of evidence is created from this indefinite state.

Patterns of sexual arousal in young, heterosexual men who experience condom-associated erection problems (CAEP).

Introduction: Condom-associated erection problems (CAEPs) are reported by a substantial number of young men and are associated with inconsistent and/or incomplete condom use. The underlying mechanisms of CAEP are not well understood, and research examining the possibility that men who report CAEP differ from other men in their sexual responsivity is lacking.

Aim: This study used psychophysiological methods to examine whether men who report CAEP have a higher threshold for sexual arousal, a stronger need for tactile stimulation, and/or more easily lose their sexual arousal due to neutral distractors or performance-related demands.

The effect of condoms on penile vibrotactile sensitivity thresholds in young, heterosexual men.

Introduction: Investigating the ways in which barrier methods such as condoms may affect penile sensory thresholds has potential relevance to the development of interventions in men who experience negative effects of condoms on sexual response and sensation. A quantitative, psychophysiological investigation examining the degree to which sensations are altered by condoms has, to date, not been conducted.

Aim: The objective of this study was to examine penile vibrotactile sensitivity thresholds in both flaccid and erect penises with and without a condom while comparing men who do and those who do not report condom-associated erection problems (CAEP).

What's the predicted outcome? Explanatory and predictive properties of the quantum probability framework.

Quantum probability (QP) provides a new perspective for cognitive science. However, one must be clear about the outcome the QP model is predicting. We discuss this concern in reference to modeling the subjective probabilities given by people as opposed to modeling the choice proportions of people.