Metacognition and reasoning

This article considers the cognitive architecture of human meta-reasoning: that is, metacognition concerning one's own reasoning and decision-making. The view we defend is that meta-reasoning is a cobbled-together skill comprising diverse self-management strategies acquired through individual and cultural learning. These approximate the monitoring-and-control functions of a postulated adaptive system for metacognition by recruiting mechanisms that were designed for quite other purposes.     

Principal component analysis in combination with case-based reasoning for detecting therapeutically correct and incorrect measurements in continuous glucose monitoring systems

This paper introduces a data-driven methodology for detecting therapeutically correct and incorrect measurements in continuous glucose monitoring systems (CGMSs) in an intensive care unit (ICU). The data collected from 22 patients in an ICU with insulin therapy were obtained following the protocol established in the ICU. Measurements were classified using principal component analysis (PCA) in combination with case-based reasoning (CBR), where a PCA model was built to extract features that were used as inputs of the CBR system. CBR was trained to recognize patterns and classify these data. Experimental results showed that this methodology is a potential tool to distinguish between therapeutically correct and incorrect measurements from a CGMS, using the information provided by the monitor itself, and incorporating variables about the patient's clinical condition.     

The influences of task difficulty and response correctness on neural systems supporting fluid reasoning

This functional magnetic resonance imaging (fMRI) study examined neural contributions to managing task difficulty and response correctness during fluid reasoning. Previous studies investigate reasoning by independently varying visual complexity or task difficulty, or the specific domain. Under natural conditions these factors interact in a complex manner to support dynamic combinations of perceptual and conceptual processes. This study investigated fluid reasoning under circumstances that would represent the cognitive flexibility of real life decision-making. Results from a mixed effects analysis corrected for multiple comparisons indicate involvement of cortical and subcortical areas during fluid reasoning. A 2 × 2 ANOVA illustrates activity related to variances in task difficulty correlated with increased blood oxygenation level-dependent (BOLD)-signal in the left middle frontal gyrus (BA6). Activity related to response correctness correlated with increased BOLD-signal in a larger, distributed system including right middle frontal gyrus (BA6), right superior parietal lobule (BA7), left inferior parietal lobule (BA40), left lingual gyrus (BA19), and left cerebellum (Lobule VI). The dissociation of function in left BA 6 for task difficulty and right BA6 for response correctness and the involvement of a more diffuse network involving the left cerebellum in response correctness extends knowledge about contributions of classic motor and premotor areas supporting higher level cognition.     

The design of a novel context-aware policy model to support machine-based learning and reasoning

The purpose of autonomic networking is to manage the business and technical complexity of networked components and systems. However, the lack of a common lingua franca makes it impossible to use vendor-specific network management data to ascertain the state of the network at any given time. Furthermore, the tools used to analyze management data are all different, and hence require different data in different formats. This complicates the construction of context from diverse information sources. This paper describes a new version of the DEN-ng context-aware policy model, which is part of the FOCALE autonomic network architecture. This model has been built using three guiding principles: (1) both the context model and the policy model are rooted in information models, so that they can govern managed entities, (2) each model is expressly constructed to facilitate the generation of ontologies, so that reasoning about policies constructed from the model may be done, and (3) the model is expressly constructed so that a policy language that supports machine-based reasoning and learning can be developed from it.

Dream logic—The inferential reasoning paradigm.

Dream thought is both impoverished and non-logical. While some inferential reasoning is present in dreaming, many illogicalities that would demand cognitive attention during waking go unnoticed during sleep. The physiological basis of this illogicality may include frontal lobe inactivation and amionergic demodulation. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Grey parrots use inferential reasoning based on acoustic cues alone

Our ability to make logical inferences is considered as one of the cornerstones of human intelligence, fuelling investigations of reasoning abilities in non-human animals. Yet, the evidence to date is equivocal, with apes as the prime candidates to possess these skills. For instance, in a two-choice task, apes can identify the location of hidden food if it is indicated by a rattling noise caused by the shaking of a baited container. More importantly, they also use the absence of noise during the shaking of the empty container to infer that this container is not baited. However, since the inaugural report of apes solving this task, to the best of our knowledge, no comparable evidence could be found in any other tested species such as monkeys and dogs. Here, we report the first successful and instantaneous solution of the shaking task through logical inference by a non-ape species, the African grey parrot. Surprisingly, the performance of the birds was sensitive to the shaking movement: they were successful with containers shaken horizontally, but not with vertical shaking resembling parrot head-bobbing. Thus, grey parrots seem to possess ape-like cross-modal reasoning skills, but their reliance on these abilities is influenced by low-level interferences.     

Cross-cultural variation in the development of folk ecological reasoning

Two studies examined children's reasoning about biological kinds in populations that vary in formal education and direct experience with the natural world, a Western (urban U.S.) and a Non-Western population (Tanna, Vanuatu). Study 1 examined children's concepts of ecological relatedness between species (N = 97, 5–13-year-olds). U.S. children provided more taxonomic explanations than Ni-Vanuatu children, who provided more ecological, physiological, and utility explanations than U.S. children. Ecological explanations were most common overall and more common among older than younger children across cultures. In Study 2, children (N = 106, 6–11-year-olds) sorted pictures of natural kinds into groups. U.S. children were more likely than Ni-Vanuatu children to categorize a human as an animal and the tendency to group a human with other animals increased with age in the U.S. Despite substantial differences in cultural, educational, and ecological input, children in both populations privileged ecological reasoning. In contrast, taxonomic reasoning was more variable between populations, which may reflect differences in experience with formal education.     

Mechanistic reasoning and informed consent

Evidence‐based medicine (EBM) proponents have argued that mechanistic evidence concerning medical treatments should be considered secondary to evidence derived from randomized controlled trials (RCTs). One common criticism of RCTs is that they often do not yield results that are generalizable to clinical practice, and that for clinical practice application, mechanistic evidence is needed. However, proponents of EBM have argued that mechanistic reasoning is often unreliable and thus not very useful. Here we suggest an important role of mechanistic explanation that has been left out of this discussion entirely, namely, its importance in a patient’s decision of whether or not to take certain drugs. We argue that in certain cases, knowing how a treatment works is just as important for the patient as knowing whether it does. In this paper, we explore how and why giving patients mechanistic information can be an important factor in obtaining informed consent for medical treatment, focusing on the example case of hormonal contraceptives.     

The role of the DLPFC in inductive reasoning of MCI patients and normal agings: An fMRI study

Previous studies of young people have revealed that the left dorsolateral prefrontal cortex (DLPFC) plays an important role in inductive reasoning. An fMRI experiment was performed in this study to examine whether the left DLPFC was involved in inductive reasoning of MCI patients and normal agings, and whether the activation pattern of this region was different between MCI patients and normal agings. The fMRI results indicated that MCI patients had no difference from normal agings in behavior per-formance (reaction time and accuracy) and the activation pattern of DLPFC. However, the BOLD re-sponse of the DLPFC region for MCI patients was weaker than that for normal agings, and the func-tional connectivity between the bilateral DLPFC regions for MCI patients was significantly higher than for normal agings. Taken together, these results indicated that DLPFC plays an important role in inductive reasoning of agings, and the functional abnormity of DLPFC may be an earlier marker of MCI before structural alterations.     

Rethinking relevance: Repetition priming reveals the psychological reality of adaptive specializations for reasoning

Theories advanced to explain conditional reasoning range from those that invoke inference systems that evolved for specific domains (such as social exchange, precautions, or deontic regulations) to relevance theory, a relatively domain-general account that invokes conversational pragmatics. The present research utilized a novel extension of repetition priming, in conjunction with the Wason selection task (a widely known and used task to test people's conditional reasoning), to evaluate alternative theories of human reasoning. Across five experiments, testing over 600 participants, consistent priming across selection tasks was demonstrated. The pattern of priming effects supports models of human reasoning based on specific evolved reasoning abilities, and was inconsistent with general conditional reasoning models such as relevance theory. These results also converge with neurological and clinical evidence of divided psychological processes for reasoning about relatively specific domains, based on functionally distinct inference systems.     

Conceptual graph operations for formal visual reasoning in the medical domain

ObjectiveConceptual graphs (CGs) are used to represent clinical guidelines because they support visual reasoning with a logical background, making them a potentially valuable representation for guidelines.Materials and methodsConceptual graph formalism has an essential and basic component: a formal vocabulary that drives all of the other mechanisms, notably specialization and projection. The graph's theoretical operations, such as projection, rules, derivation, constraints, probabilities and uncertainty, support diagrammatic reasoning.ResultsA conceptual graph's graphical user interface includes a multilingual vocabulary management, some query and decision-making facilities and visual graph representations that are simple and interesting for user interactions. The described proposition using the Conceptual Graph user interface (CoGui) improves the performance of the actors in the diagnostic context of heart failure with preserved ejection fraction.DiscussionCGs capture the essential features of the medical processes underlying clinical reasoning. CGs are indeed useful as a way for the physician to represent guidelines, and well-defined semantic representations allow users to have a maximal understanding of the knowledge reasoning process.ConclusionCG operations of visual representations that uncover some of the actual complexities of clinicians’ reasoning have been tested in clinical guideline comprehension and used to translate text and diagrammatic guidelines into computer interpretable representations.     

Public reasoning about voluntary assisted dying: An analysis of submissions to the Queensland Parliament,Australia

The use of voluntary assisted dying as an end‐of‐life option has stimulated concerns and debates over the past decades. Although public attitudes towards voluntary assisted dying (including euthanasia and physician‐assisted suicide) are well researched, there has been relatively little study of the different reasons, normative reasoning and rhetorical strategies that people invoke in supporting or contesting voluntary assisted dying in everyday life. Using a mix of computational textual mining techniques, keyword study and qualitative thematic coding to analyse public submissions to a parliamentary inquiry into voluntary assisted dying in Australia, this study critically examines the different reasons, normative reasoning and rhetorical strategies that people invoke in supporting or contesting voluntary assisted dying in everyday life. The analysis identified complex and potentially contradictory ethical principles being invoked on both sides of the debate. These findings deepen our understanding of the moral basis of public reasoning about end‐of‐life matters and will help to inform future discussions on policy and law reform. The findings underscore the importance of sound normative reasoning and the use of caution when interpreting opinion polls to inform policy.     

The diversity effect of inductive reasoning under segment manipulation of complex cognition

The present study proposed the idea of segment manipulation of complex cognition (SMCC), and technically made it possible the quantitative treatment and systematical manipulation on the premise diversity. The segment manipulation of complex cognition divides the previous inductive strengths judgment task into three distinct steps, attempting to particularly distinguish the psychological processes and their rules. The results in Experiment 1 showed that compared with the traditional method, the quantitative treatment and systematical manipulation of SMCC on the diversity did not change the task’s nature, and remain rational and a good measurement of inductive strength judgment. The results in Experiment 2 showed that the participants’ response rules in the triple-step task were expected from our proposal, and that in Step 2 the “feeling of surprise” (FOS), which seems implausible but predicted from the diversity premises, was measured, and its component might be the critical part that produced the diversity effect. The “feeling of surprise” may reflect the impact of emotion on cognition, representing a strong revision to premise probability principle of pure rational hypothesis proposed by Lo et al., and its roles in the diversity effect are worthy of further research. In this regards were discussed the mistakes that the premise probability principle makes when it takes posterity probability as prior probability.     

The diversity effect of inductive reasoning under segment manipulation of complex cognition

Forming a general reasonable conclusion from a limited number of examples is one of the most mar-velous psychological activities of human beings. This kind of activities is inductive reasoning which is a key issue rising from the cross fields of psychology, phi-losophy, cognitive science, and so on. It is a thinking process of generalizing from concrete cases. The di-versity effect of inductive reasoning refers to the phe-nomenon that the inductive argument of more diverse premise can obtain s…     

Use of comparative reasoning tools for evaluation of the effect of sterilization conditions on fermentations to produce acidic fibroblast growth factor

The effects of various medium sterilization conditions on fermentations of a recombinant, acidic fibroblast growth factor (aFGF) producing Escherichia coli have been studied. Changes in the medium resulting from sterilization were monitored by pH and absorption spectra. This simple experiment provided excellent data for the demonstration of the usefulness of comparative reasoning tools in order to evaluate the effect of sterilization on fermentation performance. The time profiles of the main parameters (e.g., carbon dioxide evolution rate, dissolved oxygen, pH, and aFGF productivity) were simplified into piecewise contiguous linear segments, each of which was sequentially numbered. The length, position, and slope of each tine were then characterized. Application of the comparative reasoning tools confirmed that separate sterilization of the glucose was necessary for the success of the process, despite adding to the cost and complexity. The comparative data analysis also showed that scaleup with longer sterilization holding and cooling times would not be detrimental to aFGF production. (c) 1995 John Wiley & Sons, Inc.     

How tufted capuchin monkeys (Cebus apella spp) and common chimpanzees (Pan troglodytes) align objects to surfaces: insights into spatial reasoning and implications for tool use

This report addresses phylogenetic variation in a spatial skill that underlies tool use: aligning objects to a feature of a surface. Fragaszy and Cummins-Sebree's [Behavioral and Cognitive Neuroscience Reviews 4:282-306, 2005] model of relational spatial reasoning and Skill Development and Perception-Action theories guided the design of the study. We examined how capuchins and chimpanzees place stick objects of varying shapes into matching grooves on a flat surface. Although most individuals aligned the long axis of the object with the matching groove more often than expected by chance, all typically did so with poor precision. Some individuals managed to align a second feature, and only one (a capuchin monkey) achieved above-chance success at aligning three features with matching grooves. Our findings suggest that capuchins and chimpanzees do not reliably align objects along even one axis, and that neither species can reliably or easily master object placement tasks that require managing two or more spatial relations concurrently. Moreover, they did not systematically vary their behavior in a manner that would aid discovery of the affordances of the stick-surface combination beyond sliding the stick along the surface (which may have provided haptic information about the location of the groove). These limitations have profound consequences for the forms of tool use we can expect these individuals to master.     

Chimpanzees and bonobos distinguish between risk and ambiguity

Although recent research has investigated animal decision-making under risk, little is known about how animals choose under conditions of ambiguity when they lack information about the available alternatives. Many models of choice behaviour assume that ambiguity does not impact decision-makers, but studies of humans suggest that people tend to be more averse to choosing ambiguous options than risky options with known probabilities. To illuminate the evolutionary roots of human economic behaviour, we examined whether our closest living relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus), share this bias against ambiguity. Apes chose between a certain option that reliably provided an intermediately preferred food type, and a variable option that could vary in the probability that it provided a highly preferred food type. To examine the impact of ambiguity on ape decision-making, we interspersed trials in which chimpanzees and bonobos had no knowledge about the probabilities. Both species avoided the ambiguous option compared with their choices for a risky option, indicating that ambiguity aversion is shared by humans, bonobos and chimpanzees.     

On‐line yeast propagation process monitoring and control using an intelligent automatic control system

The monitoring and control of bioprocesses is a challenging task. This applies particularly if the actions to the process have to be carried out in real‐time. This work presents a system for on‐line monitoring and control of batch yeast propagation under limiting conditions based on a virtual plant operator, which uses the concept of intelligent control algorithms by means of fuzzy logic theory. Process information is provided on‐line using a sensor array comprising the measurement of OD, operating temperature, pressure, density, dissolved oxygen, and pH value. In this context practical problems arising through on‐line sensing and signal processing are addressed. The preprocessed sensor data are fed to a neural network for on‐line biomass estimation. The root mean squared error of prediction is 4 × 10⁶ cells/mL. The proposed system then triggers temperature and aeration by usage of a temperature dependent metabolic growth model and sensor data. The deviation of the predicted biomass from that of the reference trajectory as modeled by the metabolic growth model and its temporal derivative are used as inputs for the fuzzy temperature controller. The inputs used by the fuzzy aeration controller are the deviation of measured extract from that of the reference trajectory, the predicted cell count, and the dissolved oxygen concentration. The fuzzy‐based expert system allows to provide the desired yeast cell concentration of 100–120 × 10⁶ cells/mL at a minimum residual extract limit of 6.0 g/100 g at the required point of time. Thus, a dynamic adjustment of the propagation process to the overall production schedule is possible in order to produce the required amount of biomass at the right time.