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PubMed1995

"If I feel anxious, there must be danger": ex-consequentia reasoning in inferring danger in anxiety disorders.

It has been suggested that neurotic patients engage in 'emotional reasoning', i.e. draw invalid conclusions about a situation on the basis of their subjective emotional response. The present experiment investigated whether anxiety patients infer danger on the basis of their anxious response, whereas normals infer danger only on the basis of objective information. Four groups of anxiety patients (52 spider phobics, 41 panic patients, 38 social phobics, and 31 other anxiety patients) and 24 normal controls made ratings of the danger they perceived in scripts in which information about objective safety vs objective danger, and anxiety response vs non-anxiety response information were systematically varied. As hypothesized, anxiety patients were not only influenced by objective danger information, but also by anxiety response information, whereas normal controls were not. The effect was neither situation-specific, nor specific for panic patients. This tendency to infer danger on the basis of subjective anxiety ('ex-consequentia reasoning') may play a role in the development and maintenance of anxiety disorders.

Adult↗
PubMed1993

Competence reasoning--handling ambiguous and imprecise data in the Pro.M.D. expert system shell.

The Pro.M.D. expert system shell (Pohl and Trendelenburg, Methods Inf Med 1988;27:111-117) is a computer program tool for knowledge-based computer interpretation of laboratory data. Competence reasoning deals with more or less vague knowledge. Vague knowledge is knowledge using vague data. In Pro.M.D. terminology, vague data are called 'semi-known'. Examples of semi-known numbers are numeric intervals like [5.2,8.8] (= all numbers between lower limit 5.2 and upper limit 8.8 are possible), or imprecise numbers like N[4,1] (= numbers vary around mean of 4 with standard deviation of 1). Semi-known qualitative data are ambiguous information on alternative values like low or normal (= from three alternatives low or normal are possible and high is impossible) or probability distributions on the alternatives like low in 60% or normal in 30% or high in 10% (= low, normal and high appear with the respective probabilities). Regarding vagueness, data may be divided into known data (unambiguous and precise information), semi-known data (ambiguous or imprecise information) or unknown data (no information). Semi-known data may be further subdivided into probabilistic data, where the probability distribution of domain values is known (e.g. Gaussian distribution) and possibilistic data, where probability distribution of domain values is not known (e.g. intervals). Probabilistic data may be obtained either by completely counting the population's individuals or by estimation from samples. In the latter case sample size is another measure for data vagueness. In the Pro.M.D. expert system shell functions are being implemented for input, output, calculation and testing of semi-known data. Thus, instruments for competence reasoning in Pro.M.D. will help to build up reliable and user friendly knowledge-based systems.

Clinical Laboratory Information Systems↗
PubMed1989

Believability and syllogistic reasoning.

In this paper we investigate the locus of believability effects in syllogistic reasoning. We identify three points in the reasoning process at which such effects could occur: the initial interpretation of premises, the examination of alternative representations of them (in all of which any valid conclusion must be true), and the "filtering" of putative conclusions. The effect of beliefs at the first of these loci is well established. In this paper we report three experiments that examine whether beliefs have an effect at the other two loci. In experiments 1 and 2 subjects drew their own conclusions from syllogisms that suggested believable or unbelievable ones. In the third experiment they evaluated conclusions that were presented to them. The data show that beliefs both affect the examination of alternative models and act as a filter on putative conclusions. We conclude by showing how some types of problem and some problem contents make the existence of alternative models more obvious than others.

Humans↗
PubMed1990

Paralogical reasoning: Evans, Johnson-Laird, and Byrne on liar and truth-teller puzzles.

People's performance on knight/knave problems is deliberate. They make assumptions, draw deductive inferences from them, and evaluate the consequences of these inferences. In an initial paper on this topic (Rips, 1989), I proposed a model for a subset of such problems that depend on sentential reasoning. The main component of the model is a set of natural-deduction rules, drawn from prior work on propositional inference. This natural-deduction framework seems well suited to explain the reasoning that subjects display on these problems, since it incorporates a mechanism for making assumptions and following them up. Moreover, the number of assumptions and rule applications needed to solve a problem yields an intuitively appealing measure of how difficult the problem should be. In accord with this prediction, the experiments found increases in error rates and reaction times as a function of the assumptions-plus-inferences measure. In their note, Johnson-Laird and Byrne sketch a possible alternative. Their account posits five processing strategies tailored to this problem domain and a mechanism for evaluating sentential arguments based on mental models. The mental-model component is a variation on the usual truth-table method, where individual models correspond to truth-table rows. The main prediction of this component is that the more models subjects must consider, the harder the problem. However, the experiment reported here found no evidence for this prediction. Problems with larger numbers of models do not yield higher error rates than those with few. What does cause difficulties for subjects is scope relations among connectives, a fact that inference-rule theories can easily explain. Given these findings, it's not surprising that the predictive burden for knight/knave problems must be carried by Johnson-Laird and Byrne's strategies, rather than by mental models. These strategies control the order in which subjects consider parts of the problem, and they provide possible stopping points. There are, however, several difficulties with these strategies. Of their four new strategies, Johnson-Laird and Byrne offer no evidence at all for two of them. Of the remaining two, only one accounts for a significant proportion of the variance when allowance is made for confounding variables. Moreover, all four strategies are ad hoc, rather than being derived from some more general theory. Certainly, much remains to be done in filling out the picture of how such problems are handled, as both Evans and Johnson-Laird and Byrne point out.(ABSTRACT TRUNCATED AT 400 WORDS)

Concept Formation↗
PubMed1991

Reasoning about the height and location of a hidden object in 4.5- and 6.5-month-old infants.

The present experiments examined 6.5- and 4.5-month-old infants' ability to represent and to reason about the height and location of a hidden object. In Experiments 1 and 2, the infants were habituated to a screen that rotated back and forth through a 180 degree arc, in the manner of a drawbridge. Following habituation, a box was placed behind the screen, and the infants saw two test events. In one (possible event), the screen rotated until it reached the occluded box; in the other (impossible event), the screen rotated through either the top 80% or the top 50% of the space occupied by the box. The results indicated that (a) the 6.5-month-old infants were surprised when the screen rotated through the top 80%, but not the top 50%, of the box and (b) the 4.5-month-old infants failed to be surprised even when the screen rotated through the top 80% of the box (4.5-month-old infants do show surprise, however, when the screen rotates through the entire (100%) box (Baillargeon, 1987a]. Experiments 3 and 4 tested whether infants would be better at detecting that the screen rotated farther than it should if provided with a second, identical box to the side of the box behind the screen. This second box stood out of the screen's path and so remained visible throughout the test trials. The results indicated that with the second box present (a) the 6.5-month-old infants showed surprise when the screen rotated through the top 50% of the occluded box and (b) the 4.5-month-old infants were surprised when the screen rotated through either the top 80% or the top 50% of the box. The results of Experiment 5 revealed that the improvement in performance brought about by the second box disappeared when this box was no longer in the same fronto-parallel plane as the box behind the screen. Different models are considered to describe the impressive quantitative and qualitative physical reasoning abilities revealed by these findings.

Cognition↗
PubMed1992

The early development of numerical reasoning.

Children of age 1-4 years were found capable of engaging in numerical reasoning. Children were presented with a task in which they placed a set of objects one by one into an opaque container. An experimenter then visibly performed either an addition, a subtraction, or no transformation on the screened set. Children were then instructed to remove all objects from the container. Across two experiments, children searched for and removed the correct number of objects when set numerosity was small. Knowledge of numerical identity and knowledge of the effects of addition and subtraction transformations on numerosity were present even in children who had not yet begun to count verbally. These findings provide evidence that the emergence of numerical reasoning does not depend upon the prior development of a verbal counting ability or upon cultural experience with numbers.

Child Development↗
PubMedDate not supplied

Focussing in reasoning and decision making.

Our principal hypothesis is that reasoning and decision making are alike in that they both depend on the construction of mental models, and so they should both give rise to similar phenomena. In this paper, we consider one such phenomenon, which we refer to as "focussing": individuals are likely to restrict their thoughts to what is explicitly represented in their models. We show that focussing occurs in four domains. First, individuals fail to draw inferences in the modus tollens form: if p then q, not-q, therefore not-p, because they focus on their initial models of the conditional, which make explicit only the case where the antecedent (p) and consequent (q) occur. Second, in Wason's selection task, they similarly tend to select only those cards that are explicitly represented in their initial models of the conditional rule. Third, their requests for information in order to enable them to make a decision about whether or not to carry out a certain action are focussed on the action to the exclusion of alternatives to it. In each of these cases, we show how the focussing bias can be reduced by certain experimental manipulations. Finally, in counterfactual reasoning, focussing underlies individuals' attempts to imagine an alternative scenario that avoids an unfortunate ending to a story.

Adolescent↗
PubMed1993

The mental model theory of conditional reasoning: critical appraisal and revision.

Johnson-Laird and Byrne (1991) present a theory of conditional inference based upon the manipulation of mental models. In the present paper, the theory is critically examined with regard to its ability to account for psychological data, principally with respect to the rate at which people draw the four basic inferences of modus ponens (MP), denial of the antecedent (DA), affirmation of the consequent (AC) and modus tollens (MT). It is argued first that the theory is unclear in its definition and in particular with regard to predictions of problem difficulty. Clarification and specification of principles are consequently provided here. Next, it is argued that there are a number of phenomena in the conditional reasoning literature for which the theory cannot account in its present form. Specifically, (a) the relatively frequency of DA and AC inferences on affirmative conditional is not as predicted by the theory, (b) differences occur between inferences on if then and only if rules beyond the capacity of the theory to explain and (c) there is no account of the "negative conclusion bias" observed when negated components are introduced into the rules. A number of revisions to the mental model theory of conditional reasoning are proposed in order to account for these findings.

Cognition↗
PubMed1994

Calibration-based reasoning about collision events in 11-month-old infants.

Previous research indicates that, when a moving object collides with a stationary object, infants expect the stationary object to be displaced. The present experiment examined whether infants believe that the size of the moving object affects how far the stationary object is displaced. In the experiment, 11-month-old infants sat in front of a horizontal track; to the left of the track was an inclined ramp. A wheeled toy bug rested on the track at the bottom of the ramp. The infants in the midpoint condition were first familiarized with an event in which a medium-sized cylinder rolled down the ramp and hit the bug, causing it to roll to the middle of the track. Next, the infants saw one of two test events. In both events, novel cylinders were introduced, and the bug now rolled to the end of the track. The two test cylinders were identical to the familiarization cylinder in material but not in size: one was larger (large-cylinder event) and one was smaller (small-cylinder event) than the familiarization cylinder. The infants in the endpoint condition saw the same familiarization and test events as the infants in the midpoint condition except that the bug rolled to the end rather than to the middle of the track in the familiarization event. The infants in the midpoint condition looked reliably longer at the small-than at the large-cylinder event, whereas the infants in the endpoint condition tended to look equally at the two events. These results indicated that the infants (a) believed that the size of the cylinder affected the length of the bug's displacement and (b) used the familiarization event to calibrate their predictions about the test events. After watching the bug roll to the middle of the track when hit by the medium cylinder, the infants were surprised to see the bug roll to the end of the track with the small but not the large cylinder. After watching the bug roll to the end of the track when hit by the medium cylinder, however, the infants were not surprised to see the bug do the same with either the small or the large cylinder. Parallel results were obtained with adult subjects. The present findings have implications for research on the nature and development of infants' physical reasoning as well as for assessments of causal reasoning in infancy.

Adult↗
PubMed1996

Mental models and temporal reasoning.

We report five experiments investigating reasoning based on temporal relations, such as: "John takes a shower before he drinks coffee". How individuals make temporal inferences has not been studied hitherto, but we conjectured that they construct mental models of events, and we developed a computer program that reasons in this way. As the program shows, a problem of the form: a before b b before c d while b e while c What is the relation between d and e? where a, b, c, etc. refer to everyday events, calls for just one model, whereas a problem in which the second premise is modified to c before b calls for multiple models because a may occur before c, after c, or at the same time as c. Experiments 1-3 showed that problems requiring one mental model elicited more correct responses than problems requiring multiple models, which in turn elicited more correct answers than multiple model problems with no valid answers. Experiment 4 contrasted the predictions of the model theory with those based on formal rules of inference; its results corroborated the model theory. Experiment 5 confirmed that a premise leading to multiple models took longer to read than the corresponding premise in one-model problems, and that latency to respond correctly was greater for multiple-model problems than for one-model problems. We conclude that the experiments corroborate the mental model theory.

Adolescent↗
PubMed1988

Theory formation in postulating enzyme kinetic mechanisms: reasoning with constraints.

This paper reports on a prototype system for modeling and analyzing the expert reasoning involved in postulating enzyme kinetic mechanisms. It involves data-driven, theory-driven, and analogical components of reasoning within a generate-and-test cycle. Its central component is a set of domain-specific "filters" for matching experimentally and theoretically derived constraints. The input to the system consists of an abstracted qualitative description of an experiment and prior knowledge reported in the literature. Its output shows how the results match those expected for a set of postulated reaction mechanism models and also provides a trace of which features do or do not match each of the candidate topological models. Results, constraints, and models are all analyzed and compared to those from other, similar experiments. We deduced rules for interpreting the qualitative features of enzyme kinetic experiments from natural language descriptions in the literature and verified that the rules were correct by predicting the results for typical mechanisms. We obtained the correct behavior for all 37 states of a complex enzyme mechanism involving three substrates and three products. We tested our system on data from several published reports dealing with the enzyme hexokinase and obtained detailed listings of the differences in conclusions and interpretation reported in several journal articles. This system, which provides qualitative representations of enzyme kinetic results, should facilitate further experimentation on theory formation in enzyme kinetics and lead to more efficient experimental designs.

Artificial Intelligence↗
PubMed1990

NEOANEMIA: a knowledge-based system emulating diagnostic reasoning.

Medical diagnosis can be modeled in terms of the classical notions of abduction, deduction, and induction. Abduction is making a preliminary guess that allows one to establish a set of plausible diagnostic hypotheses, followed by deduction for exploring their consequences and induction for testing the hypotheses with available patient data or for planning the acquisition of new data. Such a description of diagnostic reasoning at a knowledge level helps the construction of an expert system by fashioning the adopted expert system building tool to reflect the structure of the problem rather than by fitting the problem to the tool. To this aim, reasoning strategies need to be represented abstractly, separate from medical facts and relations, to make the design more transparent and explainable.

Anemia↗
PubMed1992

Development of a knowledge base for diagnostic reasoning in cardiology.

This paper reports on a formative evaluation of the diagnostic capabilities of the Heart Failure Program, which uses a probability network and a heuristic hypothesis generator. Using 242 cardiac cases collected from discharge summaries at a tertiary care hospital, we compared the diagnoses of the program to diagnoses collected from cardiologists using the same information as was available to the program. With some adjustments to the knowledge base, the Heart Failure Program produces appropriate diagnoses about 90% of the time on this training set. The main reasons for the inappropriate diagnoses of the remaining 10% include inadequate reasoning with temporal relations between cause and effect, severity relations, and independence of acute and chronic diseases.

Artificial Intelligence↗
PubMed1977

Electroencephalographic changes in the dominant hemisphere during memorizing and reasoning.

The EEG was recorded with bipolar technique in ten normal subjects in the frontal, temporal and occipital regions of the dominant hemisphere in four situations: (1) during an auditory memory test, (2) during 'auditory rest' (listening to white noise), (3) during a visual reasoning test and (4) during 'visual rest' (watching a black dot on a white screen). Computer analysis of the EEG was made by (a) an on-line automatic EEG analyser yielding measures of mean power, mean frequency and frequency spread (complexity) and (b) an off-line period-amplitude (P-A) analysis, which gave per cent activity time and mean voltage in 21 frequency bands. As compared to auditory rest the auditory memory test gave an amplitude increase frontally in the alpha, theta, and delta bands. During the visual reasoning test there was in addition an amplitude increase in the alpha band in the temporal region. During the auditory test a tendency to a decrease of the alpha activity was seen in all three regions but this decrease occurred only occipitally during the visual test. The two types of mental activity thus induced two patterns of regional EEG changes. These showed principal similarities to regional cerebral blood flow patterns which have been recorded during visual and auditory tests of about the same types as those used in the present study.

Auditory Perception↗
PubMed1989

Visuospatial problem solving, conceptual reasoning and sorting behaviour in multiple sclerosis out-patients.

Visuospatial problem solving, conceptual reasoning and shifting of set were studied in out-patients with definite and probable MS. The sample of MS patients was homogeneous with respect to 2 important dimensions. All were out-patients, leading a normal although handicap-restricted social life. Furthermore, in all patients relapse or obvious instability of the disease were absent for at least a month. On Raven's Progressive Matrices, the Category test and the Wisconsin Modified Card Sorting test, no significant differences were found between the group of MS patients and a control group of healthy volunteers. However, 18% of MS patients and 4% of controls were rated as performing slightly below the expected levels of cognition. Stepwise regression analysis failed to reveal effects of illness variables, and no difference between patients with definite and probable MS could be detected. Clearly, most socially integrated MS patients in stable disease stages are capable of normal visuospatial problem solving, abstract reasoning and shifting of set.

Adolescent↗
PubMed1984

Reasons for failure in treatment of pulmonary tuberculosis in Ethiopians.

This study was undertaken to determine the number of patients who started antituberculosis treatment at the Tuberculosis Centre in Addis Ababa but never completed a full regular course for one year. There were 460 or 6% of all the tuberculous patients that were treated for the disease in this period. The reasons for treatment failure were analyzed. Although the commonest cause of default was clinical improvement before completion of therapy, many of the reasons related to the socio-economic situation and cultural background in Ethiopia. Despite, which is a good result for unsupervised chemotherapy in a country such as Ethiopia.

Adolescent↗
PubMed1988

The longitudinal evaluation of verbal-reasoning in lead workers.

Four times during the course of a year, asymptomatic lead workers from the printing industry underwent a series of psychological tests assessing memory, attention, verbal-reasoning and spatial skills. In a syntactic reasoning task, the exposed group were less accurate, tended to be slower on the more complex problems and showed less consistent improvement over the year. An examination of subjects with changing blood-lead levels during the year showed that, within the exposed group, those with rising blood-lead levels were less accurate than those whose blood-leads fell or remained constant. This may indicate that effects of changing blood-lead concentrations depend upon overall level of exposure.

Adult↗
PubMed1987

A computational model of reasoning from the clinical literature.

This paper explores the premise that a formalized representation of empirical studies can play a central role in computer-based decision support. The specific motivations underlying this research include the following propositions: Reasoning from experimental evidence contained in the clinical literature is central to the decisions physicians make in patient care. A computational model, based upon a declarative representation for published reports of clinical studies, can drive a computer program that selectively tailors knowledge of the clinical literature as it is applied to a particular case. The development of such a computational model is an important first step toward filling a void in computer-based decision support systems. Furthermore, the model may help us better understand the general principles of reasoning from experimental evidence both in medicine and other domains. Roundsman is a developmental computer system which draws upon structured representations of the clinical literature in order to critique plans for the management of primary breast cancer. Roundsman is able to produce patient-specific analyses of breast cancer management options based on the 24 clinical studies currently encoded in its knowledge base. The Roundsman system is a first step in exploring how the computer can help to bring a critical analysis of the relevant literature to the physician, structured around a particular patient and treatment decision.

Artificial Intelligence↗