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)

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 lambda model predicts that the command received by each motor nucleus during locomotion is specific for the joint at which its muscle acts and is independent of external conditions. However, investigation of the commands received by motor nuclei during fictive locomotion and of the sensitivity of these commands to feedback from the limb during locomotion indicates that neither condition is satisfied.

Extrapersonal frames of reference for aimed movements are representationally convenient. They may, however, carry associated costs when the movement is executed in terms of the complex coordination of multiple joints they require. Studies that have measured both fingertip and joint paths suggest the motor systems may seek a compromise between simplicity of extrapersonal spatial representation and computational simplicity of multi-joint execution.

In this brief commentary the author concentrates on the treatment perspectives of Mealey's model. The main weakness of the model is that it does not provide a satisfactory theoretical connection between treatment and different types of target behavior. Even within the primary-secondary distinction, there are large individual differences that should not be overlooked in the planning of treatment.

Models of central control variables (CVs) that are expressed in positional reference frames and rely on proprioception as the dominant specifier of muscle activation patterns have not yet been shown to be adequate for the description of fast, voluntary movement, even of single joints. An alternative model with illustrative data is proposed.

Kinematic properties of reaching movements reflect constraints imposed on the joint angles. Contemporary models present solutions to the redundancy problem by a pseudoinverse procedure (Whitney 1969) or without any inversion (Berkenblit et al. 1986). Feldman & Levin suggest a procedure based on a regular inversion. These procedures are considered as an outcome of a more general approach.

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)

In approaching the question of whether groups of people can have cognitive capacities that are fundamentally different than the cognitive capacities of the individuals within the group, we lay out a Multiple, Interactive Levels of Cognitive Systems (MILCS) framework. The goal of MILCS is to explain the kinds of cognitive processes typically studied by cognitive scientists, such as perception, attention, memory, categorization, decision making, problem solving, and judgment. Rather than focusing on high-level constructs such as modules in an information processing (...) flow diagram or internal representations, MILCS focuses on mechanisms that allow systems to engage in flexible, adaptive behavior. Examples of these mechanisms are network structure-process pairs that: combine data from perception with top-down theories, achieve consistency and consensus through information exchange, selectively attend to information globally assessed as relevant, and develop specialized units from originally homogeneous networks through competition among the units. Two such systems are considered in some detail -- lateral inhibition within a network for selecting from a candidate set the option that is most attractive, and a diffusion process for accumulating evidence to reach a generally rapid and accurate decision. These system descriptions are aptly applied at multiple levels, including within and across people. These systems provide accounts that unify cognitive processes across multiple levels, can be expressed in a common vocabulary provided by network science, are inductively powerful yet appropriately constrained, and are applicable to a large number of superficially diverse cognitive systems. Given that people are typically highly motivated to participate in strong groups, cognitively resourceful people will tend to form groups that effectively employ cognitive systems at higher levels than the individuals. The impressive cognitive capacities of individual people do not eliminate the need to talk about group cognition. Instead, smart people generally form smart groups. (shrink)

The search for simplifying principles in motor control motivates the target article. One method that the CNS uses to simplify the task of controlling a limb's mechanical properties is absent from the article. Evidence from multi-joint, force-field measurements and from kinematics that points to the existence of multi-joint primitives as control variables is discussed.

Recent results have shown that the relative activation of muscles is different for isometric contractions and for movements. These results exclude an explanation of muscle activation patterns by a combination ofreciprocal and coactivation commands. These results also indicate that joint stiffness is not uniquely determined and that it may be different for isometric contractions and movements.

Sociobiological explanation requires both a reliable and a valid definition of the sociopathy phenotype. Mealey assumes that such reliable and valid definition of sociopathy exists in her A review of psychiatric literature on the diagnosis of antisocial personality disorder clearly demonstrates that this assumption is faulty. There is substantial disagreement among diagnostic systems (e.g., RDC, DSM-III) over what constitutes the antisocial phenotype, different systems identify different individuals as sociopathic. Without a valid definition of sociopathy, sociobiological theories like Mealey's should be (...) viewed as entirely speculative. (shrink)

A dynamic context model of interactive behavior was developed to explain results from two experiments that tested the effects of interaction costs on encoding strategies, cognitive representations, and response selection processes in a decision-making and a judgment task. The model assumes that the dynamic context defined by the mixes of internal and external representations and processes are sensitive to the interaction cost imposed by the task environment. The model predicts that changes in the dynamic context may lead to systematic biases (...) in cognitive representations and processes that eventually influence decision-making and judgment outcomes. Consistent with the predictions by the model, results from the experiments showed that as interaction costs increased, encoding strategies and cognitive representations shifted from perception-based to memory-based. Memory-based comparisons of the stimuli enhanced the similarity and dominance effects, and led to stronger systematic biases in response outcomes in a choice task. However, in a judgment task, memory-based representations enhanced only the dominance effects. Results suggested that systematic response biases in the dominance context were caused by biases in the cognitive representations of the stimuli, but response biases in the similarity context were caused by biases in the comparison process induced by the choice task. Results suggest that changes in interaction costs not only change whether information was assessed from the external world or from memory but also introduce systematic biases in the cognitive representation of the information, which act as biased inputs to the subsequent decision-making and judgment processes. Results are consistent with the idea of interactive cognition, which proposes that representations and processes are contingent on the dynamic context defined by the information flow between the external task environment and internal cognition. (shrink)

The λ model suggests that detailed kinematics arise from changes in control variables and need not be explicitly planned. However, we have shown that when moving a grasped object, grip force is precisely modulated in phase with acceleration-dependent inertial load. This suggests that the motor system can predict detailed kinematics. This prediction may be based on a forward model of the dynamics of the loaded limb.

We affirm the dynamical systems approach taken by Feldman and Levin, but argue that a more mathematically rigorous and standard exposition of the model according to dynamical systems theory would greatly increase readability and testability. Such an explication would also have heuristic value, suggesting new variations of the model. We present one such variant, a new solution to the redundancy problem.

Mealey distinguishes two types of sociopathy: (1) or obligate, and (2) or facultative. Either sociopathy evolved twice, or one form is derived from the other, e.g., through: (1) genetic assimilation generating polymorphism in the relative strength of biases favoring the development of otherwise facultative strategies, or (2) independently heritable but strategically relevant characteristics biasing the optimal selection of facultative strategies.

The lambda model of Feldman & Levin for intentional hand movement is compared with a hemispheric motor model (IIMM). Both models imply similar conclusions independently. This increases the validity of both models.

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)

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.

Behavioral biologists have long sought to link behavioral units (e.g., aggression, depression, sociopathy) with biological units (e.g., genes, neurotransmitters, hormones, neuroanatomical loci). These units, originally contrived for descriptive purposes, often lead to misunderstandings when they are reified for purposes of causal analysis. This genetic and biochemical explanation for sociopathy reflects such problems.

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.

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 complex systems approach (CSA) to characterizing cognitive function is purported to underlie a conceptual and methodological revolution by its proponents. I examine one central claim from each of the contributed papers and argue that the provided examples do not justify calls for radical change in how we do cognitive science. Instead, I note how currently available approaches in ‘‘standard’’ cognitive science are adequate (or even more appropriate) for understanding the CSA provided examples.

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)

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)

Emotion is critical in Mealey's conceptual arguments. However, several of her assertions about the role of emotion in sociopathy are problematic. Questions are raised regarding the link between lack of anxiety and low levels of secondary emotions such as love and sympathy, the argument that sociopaths are low in anxiety but high in neuroticism, and the designation of anxiety as a secondary emotion.

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.

The concept of a conservative control strategy minimizing the number of degrees of freedom used is criticised with reference to 3-D simple reaching and grasping experiments. The vector error in a redundant system would not be the prime controlled variable, but rather the posture for reaching, as exemplified by nearly straight displacements in joint space as opposed to curved ones in task space.

We present a theory of decision by sampling (DbS) in which, in contrast with traditional models, there are no underlying psychoeconomic scales. Instead, we assume that an attribute’s subjective value is constructed from a series of binary, ordinal comparisons to a sample of attribute values drawn from memory and is its rank within the sample. We assume that the sample reflects both the immediate distribution of attribute values from the current decision’s context and also the background, real-world distribution of attribute (...) values. DbS accounts for concave utility functions; losses looming larger than gains; hyperbolic temporal discounting; and the overestimation of small probabilities and the underestimation of large probabilities. Ó 2005 Elsevier Inc. All rights reserved. (shrink)

Digital computers play a special role in cognitive science—they may actually be instances of the phenomenon they are being used to model. This paper surveys some of the main issues involved in understanding the relationship between digital computers and cognition. It sketches the role of digital computers within orthodox computational cognitive science, in the light of a recently emerging alternative approach based around dynamical systems.

Our life is full of choices—choices that differ, among others, in the amount of information on which they are based. For instance, when facing a choice between two options that differ on several decision-relevant attributes, one could rely on the most relevant attribute only to make the decision, or one could integrate information from several attributes and base the choice on that combined information. When a decision maker bases her choice on the most relevant attribute only, however, what does this (...) mean with regard to the amount of information this decision maker had processed prior to making the decision: did she process information about the most relevant attribute only and ignored additional information, or did she consider additional pieces of information as well but let her choice nonetheless be guided by only the most relevant attribute? Understanding the cognitive processes underlying those choices that are based primarily on the most relevant attribute is the main subject of this thesis, in particular, the question of whether or not for these choices additional information is ignored, and if additional information is not ignored, how is this information being processed? The empirical results of several experiments reported here show that decision makers do not ignore information when this information is fully shown to them or when decision accuracy is of importance. Moreover, even when information has to be retrieved from memory, information is not completely ignored. Additionally, first evidence was found that decision makers inhibit information when it conflicts with their decisions. Finally, results of one experiment show that the likelihood of relying on only one piece of information increases under ego-depletion. (shrink)