Punishment is fundamental to the evolution of cooperative norms in teams, organizations, and societies. Based on findings that people are faster when punishing others (relative to when withholding punishment), dual-process theories of punishment assert that humans have an intuitive tendency to punish, which requires effortful deliberation to overcome. Here, we propose an alternative single-process theory that models punishment decisions as a sequential sampling process. We provide supporting evidence for this theory using a public goods game experiment that experimentally manipulates the (...) cost–benefit tradeoff across the game. We show that people are not systematically faster when punishing (versus withholding) across tradeoffs. We also find an inverted-U-shaped relationship between response times and the strength of preferences for punishing, and a negative association between punishment rates and the relative speed of punishment across individuals. Further computational analysis using the drift–diffusion model (DDM) reveals that, on average, people exhibit a pre-disposition to withhold punishment. Our study provides a unified single-process framework for studying the micro-foundations of punishment and integrating process measures to better describe and predict behavior. (shrink)

A framing bias shows risk aversion in problems framed as “gains” and risk seeking in problems framed as “losses,” even when these are objectively equivalent and probabilities and outcomes values are explicitly provided. We test this framing bias in situations where decision makers rely on their own experience, sampling the problem's options and seeing the outcomes before making a choice. In Experiment 1, we replicate the framing bias in description-based decisions and find risk indifference in gains and losses in experience-based (...) decisions. Predictions of an Instance-Based Learning model suggest that objective probabilities as well as the number of samples taken are factors that contribute to the lack of framing effect. We test these two factors in Experiment 2 and find no framing effect when a few samples are taken but when large samples are taken, the framing effect appears regardless of the objective probability values. Implications of behavioral results and cognitive modeling are discussed. (shrink)

Diffusion models are widely-used and successful accounts of the time course of two-choice decision making. Most diffusion models assume constant boundaries, which are the threshold levels of evidence that must be sampled from a stimulus to reach a decision. We summarize theoretical results from statistics that relate distributions of decisions and response times to diffusion models with time-varying boundaries. We then develop a computational method for finding time-varying boundaries from empirical data, and apply our new method to two problems. The (...) first problem involves finding the time-varying boundaries that make diffusion models equivalent to the alternative sequential sampling class of accumulator models. The second problem involves finding the time-varying boundaries, at the individual level, that best fit empirical data for perceptual stimuli that provide equal evidence for both decision alternatives. We discuss the theoretical and modeling implications of using time-varying boundaries in diffusion models, as well as the limitations and potential of our approach to their inference. (shrink)

Satisficing is a central concept in both individual and social multiagent decision making. In this paper we first extend the notion of satisficing by formally modeling the tradeoff between costs and decision failure. Second, we extend this notion of “neo”-satisficing into the context of social or multiagent decision making and interaction, and model the social conditioning of preferences in a satisficing framework.

We review how leaky competing accumulators (LCAs) can be used to model decision making in two‐alternative, forced‐choice tasks, and we show how they reduce to drift diffusion (DD) processes in special cases. As continuum limits of the sequential probability ratio test, DD processes are optimal in producing decisions of specified accuracy in the shortest possible time. Furthermore, the DD model can be used to derive a speed–accuracy trade‐off that optimizes reward rate for a restricted class of two alternative forced‐choice decision (...) tasks. We review findings that compare human performance with this benchmark, and we reveal both approximations to and deviations from optimality. We then discuss three potential sources of deviations from optimality at the psychological level—avoidance of errors, poor time estimation, and minimization of the cost of control—and review recent theoretical and empirical findings that address these possibilities. We also discuss the role of cognitive control in changing environments and in modulating exploitation and exploration. Finally, we consider physiological factors in which nonlinear dynamics may also contribute to deviations from optimality. (shrink)

The experiments Feldman and Levin suggest do not definitively test their proposed solution to the problem of selecting muscle activations. Their test of the movement directions that elicit EMG activity can be interpreted without regard to the form of the central commands, and their fast elbow flexion test is based on a forward computation that obscures the insensitivity of the predicted trajectory to the details of the putative commands.

A hypothesis about sensorimotor integration (the λ model) is described and applied to movement control and kinesthesia. The central idea is that the nervous system organizes positional frames of reference for the sensorimotor apparatus and produces active movements by shifting the frames in terms of spatial coordinates. Kinematic and electromyographic patterns are not programmed, but emerge from the dynamic interaction among the system s components, including external forces within the designated frame of reference. Motoneuronal threshold properties and proprioceptive inputs to (...) motoneurons may be cardinal components of the physiological mechanism that produces positional frames of reference. The hypothesis that intentional movements are produced by shifting the frame of reference is extended to multi-muscle and multi-degrees-of-freedom systems with a solution of the redundancy problem that allows the control of a joint alone or in combination with other joints to produce any desired limb configuration and movement trajectory. The model also implies that for each motor behavior, the nervous system uses a strategy that minimizes the number of changeable control variables and keeps the parameters of these changes invariant. Examples are provided of simulated kinematic and electromyographic signals from single- and multi-joint arm movements produced by suggested patterns of control variables. Empirical support is provided and additional tests of the model are suggested. The model is contrasted with others based on the ideas of programming of motoneuronal activity, muscle forces, stiffness, or movement kinematics. (shrink)

Recently proposed models of risky choice imply systematic violations of transitivity of preference. This study explored whether people show the predicted intransitivity of the two models proposed to account for the certainty effect in Allais paradoxes. In order to distinguish “true” violations from those produced by “error,” a model was fit in which each choice can have a different error rate and each person can have a different pattern of preferences that need not be transitive. Error rate for a choice (...) is estimated from preference reversals between repeated presentations of the same choice. Results showed that few people repeated intransitive patterns. We can retain the hypothesis that all participants were transitive. (shrink)

As more criminals are imprisoned, other individuals change their behavior to replace them, as predicted by the theory of strategic behavior. The physiological correlates of sociopathy suggest that research in cognitive neuroscience can lead toward a solution. Promising pathways include building upon current knowledge of self-deceit, the independence of positive and negative emotions, the lateralization of risk and caution, and the conditions promoting prosocial behavior.

Recent studies lend support to the two-pathway model of the evolution of sociopathy with evidence that: 1) psychopathy (primary sociopathy) is a discrete type and 2) in general, sociopaths have relatively high levels of reproductive success. Hare's Psychopathy Checklist may provide a start for the revision of terminology that will be necessary to distinguish between primary and secondary trajectories.

A consideration of the genetics of sociopathy suggests the following. The author's Evolutionary Stable Strategy (ESS) types 2 to 4 are more likely than types 1 and 5 in crimes of violence, and there may not be an ESS for crimes of property or for sociopathy. Correlations between sociopathy and crimes of property are also more likely due to environmental than to genetic variants, and correlations between sociopathy and crimes of property are due more to environmental than genetic variants.

Questions are raised about several issues discussed by Mealey: (1) the nature of the distinction between primary and secondary sociopaths, (2) some difficulties with a general arousal theory of criminality, and (3) the possible role of countervailing forces in the development of sociopathy. An important area that calls for attention is the patterning of different specific emotions in the lives of sociopaths as compared to other groups.

In this article, I argue that the use of scientific models that attribute intentional content to complex systems bears a striking similarity to the way in which statistical descriptions are used. To demonstrate this, I compare and contrast an intentional model with a statistical model, and argue that key similarities between the two give us compelling reasons to consider both as a type of phenomenological model. I then demonstrate how intentional descriptions play an important role in scientific methodology as a (...) type of phenomenal model, and argue that this makes them as essential as any other model of this type. (shrink)

Models of risk-taking as used in the social sciences may be improved by including concepts from life history theory, particularly environmental unpredictability and life expectancy. Community college students completed self-report questionnaires measuring these constructs along with several well-known correlates. The frequency of risk-taking was higher for those with higher future unpredictability beliefs and shorter lifespan estimates (as measured by the Future Lifespan Assessment developed for this study), and unpredictability beliefs remained significant after accounting for standard predictors, such as sex and (...) temperament. The results demonstrate the usefulness of applying concepts from life history theory to enhance our understanding of human behavior. (shrink)

Sociopaths are “outstanding” members of society in two senses: politically, they draw our attention because of the inordinate amount of crime they commit, and psychologically, they hold our fascination because most ofus cannot fathom the cold, detached way they repeatedly harm and manipulate others. Proximate explanations from behavior genetics, child development, personality theory, learning theory, and social psychology describe a complex interaction of genetic and physiological risk factors with demographic and micro environmental variables that predispose a portion of the population (...) to chronic antisocial behavior. More recent, evolutionary and game theoretic models have tried to present an ultimate explanation of sociopathy as the expression of a frequency-dependent life strategy which is selected, in dynamic equilibrium, in response to certain varying environmental circumstances. This paper tries to integrate the proximate, developmental models with the ultimate, evolutionary ones, suggesting that two developmentally different etiologies of sociopathy emerge from two different evolutionary mechanisms. Social strategies for minimizing the incidence of sociopathic behavior in modern society should consider the two different etiologies and the factors that contribute to them. (shrink)

Discrete choice experiments—selecting the best and/or worst from a set of options—are increasingly used to provide more efficient and valid measurement of attitudes or preferences than conventional methods such as Likert scales. Discrete choice data have traditionally been analyzed with random utility models that have good measurement properties but provide limited insight into cognitive processes. We extend a well-established cognitive model, which has successfully explained both choices and response times for simple decision tasks, to complex, multi-attribute discrete choice data. The (...) fits, and parameters, of the extended model for two sets of choice data (involving patient preferences for dermatology appointments, and consumer attitudes toward mobile phones) agree with those of standard choice models. The extended model also accounts for choice and response time data in a perceptual judgment task designed in a manner analogous to best–worst discrete choice experiments. We conclude that several research fields might benefit from discrete choice experiments, and that the particular accumulator-based models of decision making used in response time research can also provide process-level instantiations for random utility models. (shrink)

To have a fully integrated understanding of neurobiological systems, we must address two fundamental questions: 1. What do brains do (what is their function)? and 2. How do brains do whatever it is that they do (how is that function implemented)? I begin by arguing that these questions are necessarily inter-related. Thus, addressing one without consideration of an answer to the other, as is often done, is a mistake. I then describe what I take to be the best available approach (...) to addressing both questions. Specifically, to address 2, I adopt the Neural Engineering Framework (NEF) of Eliasmith & Anderson [Neural engineering: Computation representation and dynamics in neurobiological systems. Cambridge, MA: MIT Press, 2003] which identifies implementational principles for neural models. To address 1, I suggest that adopting statistical modeling methods for perception and action will be functionally sufficient for capturing biological behavior. I show how these two answers will be mutually constraining, since the process of model selection for the statistical method in this approach can be informed by known anatomical and physiological properties of the brain, captured by the NEF. Similarly, the application of the NEF must be informed by functional hypotheses, captured by the statistical modeling approach. (shrink)

According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...) and only sustained empirical research in cognitive science will determine the extent to which that is true. (shrink)

Van Gelder (1995) has recently spearheaded a movement to challenge the dominance of connectionist and classicist models in cognitive science. The dynamical conception of cognition is van Gelder's replacement for the computation bound paradigms provided by connectionism and classicism. He relies on the Watt governor to fulfill the role of a dynamicist Turing machine and claims that the Motivational Oscillatory Theory (MOT) provides a sound empirical basis for dynamicism. In other words, the Watt governor is to be the theoretical exemplar (...) of the class of systems necessary for cognition and MOT is an empirical instantiation of that class. However, I shall argue that neither the Watt governor nor MOT successfully fulfill these prescribed roles. This failure, along with van Gelder's peculiar use of the concept of computation and his struggle with representationalism, prevent him from providing a convincing alternative to current cognitive theories. (shrink)

In a recent series of publications, dynamicist researchers have proposed a new conception of cognitive functioning. This conception is intended to replace the currently dominant theories of connectionism and symbolicism. The dynamicist approach to cognitive modeling employs concepts developed in the mathematical field of dynamical systems theory. They claim that cognitive models should be embedded, low-dimensional, complex, described by coupled differential equations, and non-representational. In this paper I begin with a short description of the dynamicist project and its role as (...) a cognitive theory. Subsequently, I determine the theoretical commitments of dynamicists, critically examine those commitments and discuss current examples of dynamicist models. In conclusion, I determine dynamicism's relation to symbolicism and connectionism and find that the dynamicist goal to establish a new paradigm has yet to be realized. (shrink)

The dynamics of neural populations capture the laws of the mindThis paper focuses on the level of neural networks. Examining the case of recurrent neural networks, the paper argues that the dynamics of neural populations form a privileged level of explanation in cognitive science. According to Schöner, this level is privileged, because it enables cognitive scientists to discover the laws governing organisms’ cognition and behaviour.

This chapter subsumes David Marr’s levels of analysis account of explanation in cognitive science under the framework of mechanistic explanation: Answering the questions that define each one of Marr’s three levels is tantamount to describing the component parts and operations of mechanisms, as well as their organization, behavior, and environmental context. By explicating these questions and showing how they are answered in several different cognitive science research programs, this chapter resolves some of the ambiguities that remain in Marr’s account, and (...) shows that many different areas and traditions of cognitive scientific research can be unified under the mechanistic framework. (shrink)

A number of scholars have recently defended the claim that there is a close connection between the evolutionary biological notion of fitness and the economic notion of utility: both are said to refer to an organism’s success in dealing with its environment, and both are said to play the same theoretical roles in their respective sciences. However, an analysis of two seemingly disparate but in fact structurally related phenomena—‘niche construction’ (the case where organisms change their environment to make it fit (...) to their needs) and ‘adaptive preferences’ (the case where agents change their wants to make them fit to what the world has given them)—shows that one needs to be very careful about the postulation of this sort of fitness–utility connection. Specifically, I here use the analysis of these two phenomena to establish when connecting fitness and utility is and is not possible. (shrink)

The lambda model of servocontrol seems superior to the alpha model in terms of dealing with the mechanical complexities of nonlinear and multiarticular muscles. Both, however, can be trivialized by noting that the “control variable” may simply be the sum of descending influences at propriospinal interneurons in the case of the lambda model or in the muscles themselves in the case of the alpha model. The notion that the brain explicitly computes output in terms of any such control variables may (...) be an engineering metaphor, useful for conceptual understanding but not for generating predictive hypotheses about higher motor circuitry. (shrink)

We argue that the concept of a control variable (CV) as described by Feldman and Levin needs to be revised because it does not account for the influence of sensory feedback from the periphery. We provide evidence from the realm of rhythmic movements that sensory feedback can permanently alter the frequency and phase of a centrally generated rhythm.

The equilibrium-point hypothesis (the λ-model) is superior to all other models of single-joint control and provides deep insights into the mechanisms of control of multi-joint movements. Attempts at associating control variables with neurophysiological variables look confusing rather than promising. Probabilistic mechanisms may play an important role in movement generation in redundant systems.

The lambda model provides a physiologically grounded terminology for describing muscle function and emphasizes the important influence of environmental and reflex-mediated effects on final states. However, lambda itself is only a convenient point on the length-tension curve; its importance should not be overemphasized. Ascribing movement to changes in a lambda-based frame of reference is generally valid, but it leaves unanswered a number of questions concerning mechanisms.

Mealey proposes two categorical classes of sociopath, primary and secondary. I criticize this distinction on the basis that constructs of this kind have proved unrealistic in personality taxonomy and that dimensional systems capture reality much more successfully. I suggest how such a system could work in this particular context.

Although Mealey's account provides several interesting hypotheses, her integration across disparate samples renders the value of her explanation for psychopathy ambiguous. Recent evidence on Psychopathy Checklist-identified samples (Hare, 1991) suggests primary emotional and cognitive deficits inconsistent with her model. Whereas high-anxious psychopaths display interpersonal deficits consistent with Mealey's hypotheses, low-anxious psychopaths' deficits appear more sensitive to situational parameters than predicted.

We doubt that primary sociopathy is adaptive, for three reasons: First, its prevalence is too low to require an adaptive explanation. Second, a common sequela of damage to the orbito-frontal lobes is Any pattern of behavior that can be produced by brain damage is unlikely to be adaptive. Third, we argue that most human social behavior is not under tight genetic control, but is produced by open-ended calculation of fitness-contingencies.

This commentary extends arousal theory to suggest an explanation for the well-established inverse correlation between church attendance and involvement in crime. In addition, the results of two surveys of social scientists are reviewed to reveal just how little impact the biosocial/sociobiological perspective has had thus far on social science.

Mealey's etiological distinction between primary and secondary sociopathy blurs the delineation between individual and group differences. She uses physiological evidence to support her claim of genetic influences, neglecting variability within social classes, frequency of delinquent behavior in upper and middle classes (measured by self-report), and discontinuity of criminal behavior across the life span. Finally, Mealey's proposals for differential intervention fall short of a future agenda, which should tailor to individual needs, not social classes.