Choosing to make an effort: the role of striatum in signaling physical effort of a chosen action.

The possibility that we will have to invest effort influences our future choice behavior. Indeed deciding whether an action is actually worth taking is a key element in the expression of human apathy or inertia. There is a well developed literature on brain activity related to the anticipation of effort, but how effort affects actual choice is less well understood. Furthermore, prior work is largely restricted to mental as opposed to physical effort or has confounded temporal with effortful costs. Here we investigated choice behavior and brain activity, using functional magnetic resonance imaging, in a study where healthy participants are required to make decisions between effortful gripping, where the factors of force (high and low) and reward (high and low) were varied, and a choice of merely holding a grip device for minimal monetary reward. Behaviorally, we show that force level influences the likelihood of choosing an effortful grip. We observed greater activity in the putamen when participants opt to grip an option with low effort compared with when they opt to grip an option with high effort. The results suggest that, over and above a nonspecific role in movement anticipation and salience, the putamen plays a crucial role in computations for choice that involves effort costs.

Pain relativity in motor control.

Motivational theories of pain highlight its role in people's choices of actions that avoid bodily damage. By contrast, little is known regarding how pain influences action implementation. To explore this less-understood area, we conducted a study in which participants had to rapidly point to a target area to win money while avoiding an overlapping penalty area that would cause pain in their contralateral hand. We found that pain intensity and target-penalty proximity repelled participants' movement away from pain and that motor execution was influenced not by absolute pain magnitudes but by relative pain differences. Our results indicate that the magnitude and probability of pain have a precise role in guiding motor control and that representations of pain that guide action are, at least in part, relative rather than absolute. Additionally, our study shows that the implicit monetary valuation of pain, like many explicit valuations (e.g., patients' use of rating scales in medical contexts), is unstable, a finding that has implications for pain treatment in clinical contexts.

The probabilistic approach to human reasoning.

A recent development in the cognitive science of reasoning has been the emergence of a probabilistic approach to the behaviour observed on ostensibly logical tasks. According to this approach the errors and biases documented on these tasks occur because people import their everyday uncertain reasoning strategies into the laboratory. Consequently participants' apparently irrational behaviour is the result of comparing it with an inappropriate logical standard. In this article, we contrast the probabilistic approach with other approaches to explaining rationality, and then show how it has been applied to three main areas of logical reasoning: conditional inference, Wason's selection task and syllogistic reasoning.

Scale invariance in the retrieval of retrospective and prospective memories.

How does memory retrieval depend on time scale? One strong hypothesis is that such retrieval is scale-invariant (i.e., invariant across different time scales). To test this hypothesis, three groups of participants were given 4 min to recall what they did yesterday, last week, or last year (retrospective memories), and 4 min to recall what they intended to do tomorrow, next week, or next year (prospective memories). In line with scale invariance, retrieval performance was indistinguishable across time scales, for both retrospective and prospective memory. An additional finding was that significantly more prospective memories were recalled than retrospective memories, confirming previous observations of the "intention-superiority effect" (Goschke & Kuhl, 1993).

Human rationality and the psychology of reasoning: where do we go from here?

British psychologists have been at the forefront of research into human reasoning for 40 years. This article describes some past research milestones within this tradition before outlining the major theoretical positions developed in the UK. Most British reasoning researchers have contributed to one or more of these positions. We identify a common theme that is emerging in all these approaches, that is, the problem of explaining how prior general knowledge affects reasoning. In our concluding comments we outline the challenges for future research posed by this problem.

Connectionist psycholinguistics: capturing the empirical data.

Connectionist psycholinguistics is an emerging approach to modeling empirical data on human language processing using connectionist computational architectures. For almost 20 years, connectionist models have increasingly been used to model empirical data across many areas of language processing. We critically review four key areas: speech processing, sentence processing, language production, and reading aloud, and evaluate progress against three criteria: data contact, task veridicality, and input representativeness. Recent connectionist modeling efforts have made considerable headway toward meeting these criteria, although it is by no means clear whether connectionist (or symbolic) psycholinguistics will eventually provide an integrated model of full-scale human language processing.

Searching for two things at once: evidence of exclusivity in semantic and autobiographical memory retrieval.

We examined whether retrieval from semantic memory (Experiment 1) and autobiographical memory (Experiment 2) is exclusive, or whether people can search for two things at once. In Experiment 1, participants retrieved items as quickly as possible over 4 ruin from single categories (e.g., foods, countries) and from disjunctive categories (e.g., foods or countries). In Experiment 2, participants retrieved autobiographical episodes associated with single cue words (e.g., flower, ticket) or with disjunctive cue words (e.g., flower or ticket). In both experiments, retrieval of items from the disjunctive category did not exceed predictions based on optimal sequencing of retrieval from the corresponding two single categories. That is, exclusivity was observed to occur in retrieval from among multiple nonoverlapping categories in both semantic and autobiographical memory.

Probabilities and polarity biases in conditional inference.

A probabilistic computational level model of conditional inference is proposed that can explain polarity biases in conditional inference (e.g., J. St. B. T. Evans, 1993). These biases are observed when J. St. B. T. Evans's (1972) negations paradigm is used in the conditional inference task. The model assumes that negations define higher probability categories than their affirmative counterparts (M. Oaksford & K. Stenning, 1992); for example, P(not-dog) > P(dog). This identification suggests that polarity biases are really a rational effect of high-probability categories. Three experiments revealed that, consistent with this probabilistic account, when high-probability categories are used instead of negations, a high-probability conclusion effect is observed. The relationships between the probabilistic model and other phenomena and other theories in conditional reasoning are discussed.

Ten years of the rational analysis of cognition.

Rational analysis is an empirical program that attempts to explain the function and purpose of cognitive processes. This article looks back on a decade of research outlining the rational analysis methodology and how the approach relates to other work in cognitive science. We illustrate rational analysis by considering how it has been applied to memory and reasoning. From the perspective of traditional cognitive science, the cognitive system can appear to be a rather arbitrary assortment of mechanisms with equally arbitrary limitations. In contrast, rational analysis views cognition as intricately adapted to its environment and to the problems it faces.

Scale-invariance as a unifying psychological principle.

How can the classical psychological laws be explained and unified? It is proposed here that scale-invariance is a unifying principle. Distributions of many environmental magnitudes are observed to be scale invariant; that is, the statistical structure of the world remains the same at different measurement scales [Mandelbrot, B., 1982. The Fractal Geometry of Nature (2nd Edn.). W.H. Freeman, San Francisco, CA; Bak, P., 1997. How Nature Works: The Science of Self-organized Criticality. Oxford University Press, Oxford, UK]. We hypothesise that the perceptual-motor system reflects and preserves these scale invariances. This allows derivation of several of the most widely applicable psychological laws governing perception and action across domains and species (Weber's, Stevens', Fitts' and Piéron's Laws). We suggest that these fundamental laws reflect accommodation of the perceptuo-motor system to the scale-invariant physical world and therefore have a common foundation.

The probability heuristics model of syllogistic reasoning.

A probability heuristic model (PHM) for syllogistic reasoning is proposed. An informational ordering over quantified statements suggests simple probability based heuristics for syllogistic reasoning. The most important is the "min-heuristic": choose the type of the least informative premise as the type of the conclusion. The rationality of this heuristic is confirmed by an analysis of the probabilistic validity of syllogistic reasoning which treats logical inference as a limiting case of probabilistic inference. A meta-analysis of past experiments reveals close fits with PHM. PHM also compares favorably with alternative accounts, including mental logics, mental models, and deduction as verbal reasoning. Crucially, PHM extends naturally to generalized quantifiers, such as Most and Few, which have not been characterized logically and are, consequently, beyond the scope of current mental logic and mental model theories. Two experiments confirm the novel predictions of PHM when generalized quantifiers are used in syllogistic arguments. PHM suggests that syllogistic reasoning performance may be determined by simple but rational informational strategies justified by probability theory rather than by logic.

Similarity and rules: distinct? Exhaustive? Empirically distinguishable?

The distinction between rule-based and similarity-based processes in cognition is of fundamental importance for cognitive science, and has been the focus of a large body of empirical research. However, intuitive uses of the distinction are subject to theoretical difficulties and their relation to empirical evidence is not clear. We propose a 'core' distinction between rule- and similarity-based processes, in terms of the way representations of stored information are 'matched' with the representation of a novel item. This explication captures the intuitively clear-cut cases of processes of each type, and resolves apparent problems with the rule/similarity distinction. Moreover, it provides a clear target for assessing the psychological and AI literatures. We show that many lines of psychological evidence are less conclusive than sometimes assumed, but suggest that converging lines of evidence may be persuasive. We then argue that the AI literature suggests that approaches which combine rules and similarity are an important new focus for empirical work.

Bootstrapping Word Boundaries: A Bottom-up Corpus-Based Approach to Speech Segmentation

Speech is continuous, and isolating meaningful chunks for lexical access is a nontrivial problem. In this paper we use neural network models and more conventional statistics to study the use of sequential phonological probabilities in the segmentation of an idealized phonological transcription of the London-Lund Corpus; these speech data are representative of genuine conversational English. We demonstrate, first, that the distribution of phonetic segments in English is an important cue to segmentation, and, second, that the distributional information is such that it might allow the infant, beginning with only a sensitivity to the statistics of subsegmental primitives, to bootstrap into a series of increasingly sophisticated segmentation competences, ending with an adult competence. We discuss the relation between the behavior of the models and existing psycholinguistic studies of speech segmentation. In particular, we confirm the utility of the Metrical Segmentation Strategy (Cutler & Norris, 1988) and demonstrate a route by which this utility might be recognized by the infant, without requiring the prior specification of categories like "syllable" or "strong syllable."

Probabilistic and distributional approaches to language acquisition.

Recent computational research on natural language corpora has revealed that relatively simple statistical learning mechanisms can make an important contribution to certain aspects of language acquisition. For example, statistical and connectionist methods can provide valuable cues to word segmentation and to the acquisition of inflectional morphology, syntactic classes and aspects of word meaning. In each case, these cues are partial, and must be integrated with additional information, whether from other environmental cues or innate knowledge, to provide a complete solution to the acquisition problem. The success of these methods with real natural language corpora demonstrates their feasibility as part of the language acquisition mechanism, an area where previously most research has been limited to highly idealized artificial input or to a priori considerations regarding the feasibility of acquisition mechanisms. Exploring probabilistic learning mechanisms with natural language input provides both an empirical basis for assessing how innate constraints interact with information derived from the environment, and a source of hypotheses for experimental testing.

Results of extracranial-intracranial arterial bypass for bilateral carotid occlusion.

The results of superficial temporal to middle cerebral artery bypass surgery for bilateral internal carotid artery occlusion were reviewed in 39 patients. Preoperative symptoms included recurrent transient ischemic attacks (TIA's) in 31 patients (80%) and mild or moderate stroke in 15 (29%). Deficits were unilateral in 23 cases and bilateral in 14. Dementia or personality changes were observed in 19 patients (49%). Operative morbidity occurred in six of 39 cases and was neurological in one; the surgical mortality rate was 8% (three of 39 patients), including two cases of cerebral hemorrhage. The outcome was good or excellent (relief of TIA's and reduction of neurological deficit) in 82% of patients over a follow-up period of 3 to 139 months. Five patients had a late postoperative stroke, which occurred in the unoperated hemisphere in each case; one patient had an ipsilateral TIA 6 years after the bypass procedure. These results suggest that an extracranial-intracranial arterial bypass procedure to augment collateral cerebral blood flow can be performed safely in patients with bilateral internal carotid artery occlusion and may be associated with relief of ischemic symptoms. Future studies may document a role for this procedure in the prevention of stroke.