Age-related differences in reaction time task performance in young children.

PubMed

Kiselev, Sergey; Espy, Kimberly Andrews; Sheffield, Tiffany

2009-02-01

Performance of reaction time (RT) tasks was investigated in young children and adults to test the hypothesis that age-related differences in processing speed supersede a "global" mechanism and are a function of specific differences in task demands and processing requirements. The sample consisted of 54 4-year-olds, 53 5-year-olds, 59 6-year-olds, and 35 adults from Russia. Using the regression approach pioneered by Brinley and the transformation method proposed by Madden and colleagues and Ridderinkhoff and van der Molen, age-related differences in processing speed differed among RT tasks with varying demands. In particular, RTs differed between children and adults on tasks that required response suppression, discrimination of color or spatial orientation, reversal of contingencies of previously learned stimulus-response rules, and greater stimulus-response complexity. Relative costs of these RT task differences were larger than predicted by the global difference hypothesis except for response suppression. Among young children, age-related differences larger than predicted by the global difference hypothesis were evident when tasks required color or spatial orientation discrimination and stimulus-response rule complexity, but not for response suppression or reversal of stimulus-response contingencies. Process-specific, age-related differences in processing speed that support heterochronicity of brain development during childhood were revealed.

Logical-rule models of classification response times: a synthesis of mental-architecture, random-walk, and decision-bound approaches.

PubMed

Fific, Mario; Little, Daniel R; Nosofsky, Robert M

2010-04-01

We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli along a set of component dimensions. Those independent decisions are then combined via logical rules to determine the overall categorization response. The time course of the independent decisions is modeled via random-walk processes operating along individual dimensions. Alternative mental architectures are used as mechanisms for combining the independent decisions to implement the logical rules. We derive fundamental qualitative contrasts for distinguishing among the predictions of the rule models and major alternative models of classification RT. We also use the models to predict detailed RT-distribution data associated with individual stimuli in tasks of speeded perceptual classification. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Probabilistic Cue Combination: Less Is More

ERIC Educational Resources Information Center

Yurovsky, Daniel; Boyer, Ty W.; Smith, Linda B.; Yu, Chen

2013-01-01

Learning about the structure of the world requires learning probabilistic relationships: rules in which cues do not predict outcomes with certainty. However, in some cases, the ability to track probabilistic relationships is a handicap, leading adults to perform non-normatively in prediction tasks. For example, in the "dilution effect,"…

The role of feedback contingency in perceptual category learning.

PubMed

Ashby, F Gregory; Vucovich, Lauren E

2016-11-01

Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how feedback contingency affects category learning, and current theories assign little or no importance to this variable. Two experiments examined the effects of contingency degradation on rule-based and information-integration category learning. In rule-based tasks, optimal accuracy is possible with a simple explicit rule, whereas optimal accuracy in information-integration tasks requires integrating information from 2 or more incommensurable perceptual dimensions. In both experiments, participants each learned rule-based or information-integration categories under either high or low levels of feedback contingency. The exact same stimuli were used in all 4 conditions, and optimal accuracy was identical in every condition. Learning was good in both high-contingency conditions, but most participants showed little or no evidence of learning in either low-contingency condition. Possible causes of these effects, as well as their theoretical implications, are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The Role of Feedback Contingency in Perceptual Category Learning

PubMed Central

Ashby, F. Gregory; Vucovich, Lauren E.

2016-01-01

Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how feedback contingency affects category learning, and current theories assign little or no importance to this variable. Two experiments examined the effects of contingency degradation on rule-based and information-integration category learning. In rule-based tasks, optimal accuracy is possible with a simple explicit rule, whereas optimal accuracy in information-integration tasks requires integrating information from two or more incommensurable perceptual dimensions. In both experiments, participants each learned rule-based or information-integration categories under either high or low levels of feedback contingency. The exact same stimuli were used in all four conditions and optimal accuracy was identical in every condition. Learning was good in both high-contingency conditions, but most participants showed little or no evidence of learning in either low-contingency condition. Possible causes of these effects are discussed, as well as their theoretical implications. PMID:27149393

Category Learning in Rhesus Monkeys: A Study of the Shepard, Hovland, and Jenkins (1961) Tasks

ERIC Educational Resources Information Center

Smith, J. David; Minda, John Paul; Washburn, David A.

2004-01-01

In influential research, R. N. Shepard, C. I. Hovland, and H. M. Jenkins (1961) surveyed humans' categorization abilities using tasks based in rules, exclusive-or (XOR) relations, and exemplar memorization. Humans' performance was poorly predicted by cue-conditioning or stimulus-generalization theories, causing Shepard et al. to describe it in…

Program Predicts Time Courses of Human/Computer Interactions

NASA Technical Reports Server (NTRS)

Vera, Alonso; Howes, Andrew

2005-01-01

CPM X is a computer program that predicts sequences of, and amounts of time taken by, routine actions performed by a skilled person performing a task. Unlike programs that simulate the interaction of the person with the task environment, CPM X predicts the time course of events as consequences of encoded constraints on human behavior. The constraints determine which cognitive and environmental processes can occur simultaneously and which have sequential dependencies. The input to CPM X comprises (1) a description of a task and strategy in a hierarchical description language and (2) a description of architectural constraints in the form of rules governing interactions of fundamental cognitive, perceptual, and motor operations. The output of CPM X is a Program Evaluation Review Technique (PERT) chart that presents a schedule of predicted cognitive, motor, and perceptual operators interacting with a task environment. The CPM X program allows direct, a priori prediction of skilled user performance on complex human-machine systems, providing a way to assess critical interfaces before they are deployed in mission contexts.

A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning

PubMed Central

Balcarras, Matthew; Womelsdorf, Thilo

2016-01-01

Learning in a new environment is influenced by prior learning and experience. Correctly applying a rule that maps a context to stimuli, actions, and outcomes enables faster learning and better outcomes compared to relying on strategies for learning that are ignorant of task structure. However, it is often difficult to know when and how to apply learned rules in new contexts. In our study we explored how subjects employ different strategies for learning the relationship between stimulus features and positive outcomes in a probabilistic task context. We test the hypothesis that task naive subjects will show enhanced learning of feature specific reward associations by switching to the use of an abstract rule that associates stimuli by feature type and restricts selections to that dimension. To test this hypothesis we designed a decision making task where subjects receive probabilistic feedback following choices between pairs of stimuli. In the task, trials are grouped in two contexts by blocks, where in one type of block there is no unique relationship between a specific feature dimension (stimulus shape or color) and positive outcomes, and following an un-cued transition, alternating blocks have outcomes that are linked to either stimulus shape or color. Two-thirds of subjects (n = 22/32) exhibited behavior that was best fit by a hierarchical feature-rule model. Supporting the prediction of the model mechanism these subjects showed significantly enhanced performance in feature-reward blocks, and rapidly switched their choice strategy to using abstract feature rules when reward contingencies changed. Choice behavior of other subjects (n = 10/32) was fit by a range of alternative reinforcement learning models representing strategies that do not benefit from applying previously learned rules. In summary, these results show that untrained subjects are capable of flexibly shifting between behavioral rules by leveraging simple model-free reinforcement learning and context-specific selections to drive responses. PMID:27064794

Simians in the Shape School: A comparative study of executive attention.

PubMed

French, Kristin; Beran, Michael J; Espy, Kimberly Andrews; Washburn, David A

2018-01-08

Executive functions (EF) have been studied extensively in children and adults. However, EF tasks for young children can be difficult to administer and interpret. Espy (1997, Developmental Neuropsychology, 13, 495-499) designed the Shape School task to measure inhibition and switching in preschool-aged children. Shape School presents cartoon-like characters that children must flexibly name by their color, their shape, or both, depending on cues that indicate the appropriate rule. Shape School has been found to be age sensitive as well as predictive of performance on other EF tasks. We presented a computerized analogue of Shape School to seven rhesus macaques. Monkeys were trained to categorize characters by color or shape, or to inhibit this response, depending on whether the characters had eyes open, eyes closed, or wore hats. Monkeys performed above chance on the inhibition and switching components of the task. Long runs of a single classification rule and long runs of noninhibition trials had no significant impact on performance when the rule changed or inhibition was required. This nonverbal adaptation of Shape School can measure EF in nonhuman animals and could be used in conjunction with other EF tasks to provide a clearer picture of both human and nonhuman executive functions.

Granular support vector machines with association rules mining for protein homology prediction.

PubMed

Tang, Yuchun; Jin, Bo; Zhang, Yan-Qing

2005-01-01

Protein homology prediction between protein sequences is one of critical problems in computational biology. Such a complex classification problem is common in medical or biological information processing applications. How to build a model with superior generalization capability from training samples is an essential issue for mining knowledge to accurately predict/classify unseen new samples and to effectively support human experts to make correct decisions. A new learning model called granular support vector machines (GSVM) is proposed based on our previous work. GSVM systematically and formally combines the principles from statistical learning theory and granular computing theory and thus provides an interesting new mechanism to address complex classification problems. It works by building a sequence of information granules and then building support vector machines (SVM) in some of these information granules on demand. A good granulation method to find suitable granules is crucial for modeling a GSVM with good performance. In this paper, we also propose an association rules-based granulation method. For the granules induced by association rules with high enough confidence and significant support, we leave them as they are because of their high "purity" and significant effect on simplifying the classification task. For every other granule, a SVM is modeled to discriminate the corresponding data. In this way, a complex classification problem is divided into multiple smaller problems so that the learning task is simplified. The proposed algorithm, here named GSVM-AR, is compared with SVM by KDDCUP04 protein homology prediction data. The experimental results show that finding the splitting hyperplane is not a trivial task (we should be careful to select the association rules to avoid overfitting) and GSVM-AR does show significant improvement compared to building one single SVM in the whole feature space. Another advantage is that the utility of GSVM-AR is very good because it is easy to be implemented. More importantly and more interestingly, GSVM provides a new mechanism to address complex classification problems.

Resolving task rule incongruence during task switching by competitor rule suppression.

PubMed

Meiran, Nachshon; Hsieh, Shulan; Dimov, Eduard

2010-07-01

Task switching requires maintaining readiness to execute any task of a given set of tasks. However, when tasks switch, the readiness to execute the now-irrelevant task generates interference, as seen in the task rule incongruence effect. Overcoming such interference requires fine-tuned inhibition that impairs task readiness only minimally. In an experiment involving 2 object classification tasks and 2 location classification tasks, the authors show that irrelevant task rules that generate response conflicts are inhibited. This competitor rule suppression (CRS) is seen in response slowing in subsequent trials, when the competing rules become relevant. CRS is shown to operate on specific rules without affecting similar rules. CRS and backward inhibition, which is another inhibitory phenomenon, produced additive effects on reaction time, suggesting their mutual independence. Implications for current formal theories of task switching as well as for conflict monitoring theories are discussed. (c) 2010 APA, all rights reserved

The neural implementation of task rule activation in the task-cuing paradigm: an event-related fMRI study.

PubMed

Shi, Yiquan; Zhou, Xiaolin; Müller, Hermann J; Schubert, Torsten

2010-07-01

To isolate the neural correlates for task rule activation from those related to general task preparation, the effect of a cue explicitly specifying the S-R correspondences (rule-cue) was contrasted with the effects of a cue specifying only the task to performed (task-cue). While the task-cue provides merely information about the type of task, the rule-cue is explicit about both the task type and the task rule (i.e., the set of S-R correspondences). The rule-cue was expected to activate the task rule more efficiently in the preparation period (prior to target presentation); by contrast, in the task-cue condition, part of the task rule activation was expected to be postponed into the task execution period (following the presentation of the target). In an event-related fMRI experiment, we found the right anterior and middle parts of the middle frontal and superior frontal gyri, the right inferior frontal junction, the pre-SMA, as well as the right superior and inferior parietal lobes to show larger activation elicited by the rule-cue than by the task-cue prior to target presentation. Conversely, the results revealed larger activations in these regions in the task-cue than in the rule-cue condition during the task execution period. In summary, this study identified some of the neural correlates of task rule activation and showed that these are a subset of the general task preparation network. Copyright (c) 2010 Elsevier Inc. All rights reserved.

The emergent executive: a dynamic field theory of the development of executive function.

PubMed

Buss, Aaron T; Spencer, John P

2014-06-01

Executive function (EF) is a central aspect of cognition that undergoes significant changes in early childhood. Changes in EF in early childhood are robustly predictive of academic achievement and general quality of life measures later in adulthood. We present a dynamic neural field (DNF) model that provides a process-based account of behavior and developmental change in a key task used to probe the early development of executive function—the Dimensional Change Card Sort (DCCS) task. In the DCCS, children must flexibly switch from sorting cards either by shape or color to sorting by the other dimension. Typically, 3-year-olds, but not 5-year-olds, lack the flexibility to do so and perseverate on the first set of rules when instructed to switch. Using the DNF model, we demonstrate how rule-use and behavioral flexibility come about through a form of dimensional attention. Further, developmental change is captured by increasing the robustness and precision of dimensional attention. Note that although this enables the model to effectively switch tasks, the dimensional attention system does not “know” the details of task-specific performance. Rather, correct performance emerges as a property of system–wide interactions. We show how this captures children’s behavior in quantitative detail across 14 versions of the DCCS task. Moreover, we successfully test a set of novel predictions with 3-year-old children from a version of the task not explained by other theories.

Resolving Task Rule Incongruence during Task Switching by Competitor Rule Suppression

ERIC Educational Resources Information Center

Meiran, Nachshon; Hsieh, Shulan; Dimov, Eduard

2010-01-01

Task switching requires maintaining readiness to execute any task of a given set of tasks. However, when tasks switch, the readiness to execute the now-irrelevant task generates interference, as seen in the task rule incongruence effect. Overcoming such interference requires fine-tuned inhibition that impairs task readiness only minimally. In an…

Deontic reasoning with emotional content: evolutionary psychology or decision theory?

PubMed

Perham, Nick; Oaksford, Mike

2005-09-10

Three experiments investigated the contrasting predictions of the evolutionary and decision-theoretic approaches to deontic reasoning. Two experiments embedded a hazard management (HM) rule in a social contract scenario that should lead to competition between innate modules. A 3rd experiment used a pure HM task. Threatening material was also introduced into the antecedent, p, of a deontic rule, if p then must q. According to the evolutionary approach, more HM responses (Cosmides & Tooby, 2000) are predicted when p is threatening, whereas decision theory predicts fewer. All 3 experiments were consistent with decision theory. Other theories are discussed, and it is concluded that they cannot account for the behavior observed in these experiments. 2005 Lawrence Erlbaum Associates, Inc.

When global rule reversal meets local task switching: The neural mechanisms of coordinated behavioral adaptation to instructed multi-level demand changes.

PubMed

Shi, Yiquan; Wolfensteller, Uta; Schubert, Torsten; Ruge, Hannes

2018-02-01

Cognitive flexibility is essential to cope with changing task demands and often it is necessary to adapt to combined changes in a coordinated manner. The present fMRI study examined how the brain implements such multi-level adaptation processes. Specifically, on a "local," hierarchically lower level, switching between two tasks was required across trials while the rules of each task remained unchanged for blocks of trials. On a "global" level regarding blocks of twelve trials, the task rules could reverse or remain the same. The current task was cued at the start of each trial while the current task rules were instructed before the start of a new block. We found that partly overlapping and partly segregated neural networks play different roles when coping with the combination of global rule reversal and local task switching. The fronto-parietal control network (FPN) supported the encoding of reversed rules at the time of explicit rule instruction. The same regions subsequently supported local task switching processes during actual implementation trials, irrespective of rule reversal condition. By contrast, a cortico-striatal network (CSN) including supplementary motor area and putamen was increasingly engaged across implementation trials and more so for rule reversal than for nonreversal blocks, irrespective of task switching condition. Together, these findings suggest that the brain accomplishes the coordinated adaptation to multi-level demand changes by distributing processing resources either across time (FPN for reversed rule encoding and later for task switching) or across regions (CSN for reversed rule implementation and FPN for concurrent task switching). © 2017 Wiley Periodicals, Inc.

Development of cognitive control and executive functions from 4 to 13 years: Evidence from manipulations of memory, inhibition, and task switching

PubMed Central

Davidson, Matthew C.; Amso, Dima; Anderson, Loren Cruess; Diamond, Adele

2006-01-01

Predictions concerning development, interrelations, and possible independence of working memory, inhibition, and cognitive flexibility were tested in 325 participants (roughly 30 per age from 4 to 13 years and young adults; 50% female). All were tested on the same computerized battery, designed to manipulate memory and inhibition independently and together, in steady state (single-task blocks) and during task-switching, and to be appropriate over the lifespan and for neuroimaging (fMRI). This is one of the first studies, in children or adults, to explore: (a) how memory requirements interact with spatial compatibility and (b) spatial incompatibility effects both with stimulus-specific rules (Simon task) and with higher-level, conceptual rules. Even the youngest children could hold information in mind, inhibit a dominant response, and combine those as long as the inhibition required was steady-state and the rules remained constant. Cognitive flexibility (switching between rules), even with memory demands minimized, showed a longer developmental progression, with 13-year-olds still not at adult levels. Effects elicited only in Mixed blocks with adults were found in young children even in single-task blocks; while young children could exercise inhibition in steady state it exacted a cost not seen in adults, who (unlike young children) seemed to re-set their default response when inhibition of the same tendency was required throughout a block. The costs associated with manipulations of inhibition were greater in young children while the costs associated with increasing memory demands were greater in adults. Effects seen only in RT in adults were seen primarily in accuracy in young children. Adults slowed down on difficult trials to preserve accuracy; but the youngest children were impulsive; their RT remained more constant but at an accuracy cost on difficult trials. Contrary to our predictions of independence between memory and inhibition, when matched for difficulty RT correlations between these were as high as 0.8, although accuracy correlations were less than half that. Spatial incompatibility effects and global and local switch costs were evident in children and adults, differing only in size. Other effects (e.g., asymmetric switch costs and the interaction of switching rules and switching response-sites) differed fundamentally over age. PMID:16580701

Model construction of “earning money by taking photos”

NASA Astrophysics Data System (ADS)

Yang, Jingmei

2018-03-01

In the era of information, with the increasingly developed network, “to earn money by taking photos” is a self-service model under the mobile Internet. The user downloads the APP, registers as a member of the APP, and then takes a task that needs to take photographs from the APP and earns the reward of the task on the APP. The article uses the task data and membership information data of an already completed project, including the member’s location and reputation value. On the basis of reasonable assumption, the data was processed with the MATLAB, SPSS and Excel software. This article mainly studied problems of the function relationship between the task performance, task position (GPS latitude and GPS longitude) and task price of users, analyzed the project’s task pricing rules and the reasons why the task is not completed, and applied multivariate regression function and GeoQ software to analyze the data, studied the task pricing rules, applied the chart method to solve the complex data, clear and easy to understand, and also reality simulation is applied to analyze why the tasks are not completed. Also, compared with the previous program, a new task pricing program is designed for the project to obtain the confidence level by means of the SPSS software, to estimate the reasonable range of the task pricing, predict and design a new pricing program on the reasonable price range.

Progress in mental workload measurement

NASA Technical Reports Server (NTRS)

Moray, Neville; Turksen, Burhan; Aidie, Paul; Drascic, David; Eisen, Paul

1986-01-01

Two new techniques are described, one using subjective, the other physiological data for the measurement of workload in complex tasks. The subjective approach uses fuzzy measurement to analyze and predict the difficulty of combinations of skill based and rule based behavior from the difficulty of skill based behavior and rule based behavior measured separately. The physiological technique offers an on-line real-time filter for measuring the Mulder signal at 0.1 Hz in the heart rate variability spectrum.

Electrophysiological responses to feedback during the application of abstract rules.

PubMed

Walsh, Matthew M; Anderson, John R

2013-11-01

Much research focuses on how people acquire concrete stimulus-response associations from experience; however, few neuroscientific studies have examined how people learn about and select among abstract rules. To address this issue, we recorded ERPs as participants performed an abstract rule-learning task. In each trial, they viewed a sample number and two test numbers. Participants then chose a test number using one of three abstract mathematical rules they freely selected from: greater than the sample number, less than the sample number, or equal to the sample number. No one rule was always rewarded, but some rules were rewarded more frequently than others. To maximize their earnings, participants needed to learn which rules were rewarded most frequently. All participants learned to select the best rules for repeating and novel stimulus sets that obeyed the overall reward probabilities. Participants differed, however, in the extent to which they overgeneralized those rules to repeating stimulus sets that deviated from the overall reward probabilities. The feedback-related negativity (FRN), an ERP component thought to reflect reward prediction error, paralleled behavior. The FRN was sensitive to item-specific reward probabilities in participants who detected the deviant stimulus set, and the FRN was sensitive to overall reward probabilities in participants who did not. These results show that the FRN is sensitive to the utility of abstract rules and that the individual's representation of a task's states and actions shapes behavior as well as the FRN.

Electrophysiological Responses to Feedback during the Application of Abstract Rules

PubMed Central

Walsh, Matthew M.; Anderson, John R.

2017-01-01

Much research focuses on how people acquire concrete stimulus–response associations from experience; however, few neuroscientific studies have examined how people learn about and select among abstract rules. To address this issue, we recorded ERPs as participants performed an abstract rule-learning task. In each trial, they viewed a sample number and two test numbers. Participants then chose a test number using one of three abstract mathematical rules they freely selected from: greater than the sample number, less than the sample number, or equal to the sample number. No one rule was always rewarded, but some rules were rewarded more frequently than others. To maximize their earnings, participants needed to learn which rules were rewarded most frequently. All participants learned to select the best rules for repeating and novel stimulus sets that obeyed the overall reward probabilities. Participants differed, however, in the extent to which they overgeneralized those rules to repeating stimulus sets that deviated from the overall reward probabilities. The feedback-related negativity (FRN), an ERP component thought to reflect reward prediction error, paralleled behavior. The FRN was sensitive to item-specific reward probabilities in participants who detected the deviant stimulus set, and the FRN was sensitive to overall reward probabilities in participants who did not. These results show that the FRN is sensitive to the utility of abstract rules and that the individualʼs representation of a taskʼs states and actions shapes behavior as well as the FRN. PMID:23915052

Using Dynamic Assessment to Evaluate the Expressive Syntax of Children who use Augmentative and Alternative Communication

PubMed Central

King, Marika R.; Binger, Cathy; Kent-Walsh, Jennifer

2015-01-01

The developmental readiness of four 5-year-old children to produce basic sentences using graphic symbols on an augmentative and alternative communication (AAC) device during a dynamic assessment (DA) task was examined. Additionally, the ability of the DA task to predict performance on a subsequent experimental task was evaluated. A graduated prompting framework was used during DA. Measures included amount of support required to produce the targets, modifiability (change in participant performance) within a DA session, and predictive validity of DA. Participants accurately produced target structures with varying amounts of support. Modifiability within DA sessions was evident for some participants, and partial support was provided for the measures of predictive validity. These initial results indicate that DA may be a viable way to measure young children’s developmental readiness to learn how to sequence simple, rule-based messages via aided AAC. PMID:25621928

Verbal and Non-verbal Fluency in Adults with Developmental Dyslexia: Phonological Processing or Executive Control Problems?

PubMed

Smith-Spark, James H; Henry, Lucy A; Messer, David J; Zięcik, Adam P

2017-08-01

The executive function of fluency describes the ability to generate items according to specific rules. Production of words beginning with a certain letter (phonemic fluency) is impaired in dyslexia, while generation of words belonging to a certain semantic category (semantic fluency) is typically unimpaired. However, in dyslexia, verbal fluency has generally been studied only in terms of overall words produced. Furthermore, performance of adults with dyslexia on non-verbal design fluency tasks has not been explored but would indicate whether deficits could be explained by executive control, rather than phonological processing, difficulties. Phonemic, semantic and design fluency tasks were presented to adults with dyslexia and without dyslexia, using fine-grained performance measures and controlling for IQ. Hierarchical regressions indicated that dyslexia predicted lower phonemic fluency, but not semantic or design fluency. At the fine-grained level, dyslexia predicted a smaller number of switches between subcategories on phonemic fluency, while dyslexia did not predict the size of phonemically related clusters of items. Overall, the results suggested that phonological processing problems were at the root of dyslexia-related fluency deficits; however, executive control difficulties could not be completely ruled out as an alternative explanation. Developments in research methodology, equating executive demands across fluency tasks, may resolve this issue. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Differences in perceptual learning transfer as a function of training task.

PubMed

Green, C Shawn; Kattner, Florian; Siegel, Max H; Kersten, Daniel; Schrater, Paul R

2015-01-01

A growing body of research--including results from behavioral psychology, human structural and functional imaging, single-cell recordings in nonhuman primates, and computational modeling--suggests that perceptual learning effects are best understood as a change in the ability of higher-level integration or association areas to read out sensory information in the service of particular decisions. Work in this vein has argued that, depending on the training experience, the "rules" for this read-out can either be applicable to new contexts (thus engendering learning generalization) or can apply only to the exact training context (thus resulting in learning specificity). Here we contrast learning tasks designed to promote either stimulus-specific or stimulus-general rules. Specifically, we compare learning transfer across visual orientation following training on three different tasks: an orientation categorization task (which permits an orientation-specific learning solution), an orientation estimation task (which requires an orientation-general learning solution), and an orientation categorization task in which the relevant category boundary shifts on every trial (which lies somewhere between the two tasks above). While the simple orientation-categorization training task resulted in orientation-specific learning, the estimation and moving categorization tasks resulted in significant orientation learning generalization. The general framework tested here--that task specificity or generality can be predicted via an examination of the optimal learning solution--may be useful in building future training paradigms with certain desired outcomes.

Cognitive flexibility in young children: General or task-specific capacity?

PubMed

Deák, Gedeon O; Wiseheart, Melody

2015-10-01

Cognitive flexibility is the ability to adapt to changing tasks or problems. To test whether cognitive flexibility is a coherent cognitive capacity in young children, we tested 3- to 5-year-olds' performance on two forms of task switching, rule-based (Three Dimension Changes Card Sorting, 3DCCS) and inductive (Flexible Induction of Meaning-Animates and Objects, FIM-Ob and FIM-An), as well as tests of response speed, verbal working memory, inhibition, and reasoning. Results suggest that cognitive flexibility is not a globally coherent trait; only the two inductive word-meaning (FIM) tests showed high inter-test coherence. Task- and knowledge-specific factors also determine children's flexibility in a given test. Response speed, vocabulary size, and causal reasoning skills further predicted individual and age differences in flexibility, although they did not have the same predictive relation with all three flexibility tests. Copyright © 2015 Elsevier Inc. All rights reserved.

Decision paths in complex tasks

NASA Technical Reports Server (NTRS)

Galanter, Eugene

1991-01-01

Complex real world action and its prediction and control has escaped analysis by the classical methods of psychological research. The reason is that psychologists have no procedures to parse complex tasks into their constituents. Where such a division can be made, based say on expert judgment, there is no natural scale to measure the positive or negative values of the components. Even if we could assign numbers to task parts, we lack rules i.e., a theory, to combine them into a total task representation. We compare here two plausible theories for the amalgamation of the value of task components. Both of these theories require a numerical representation of motivation, for motivation is the primary variable that guides choice and action in well-learned tasks. We address this problem of motivational quantification and performance prediction by developing psychophysical scales of the desireability or aversiveness of task components based on utility scaling methods (Galanter 1990). We modify methods used originally to scale sensory magnitudes (Stevens and Galanter 1957), and that have been applied recently to the measure of task 'workload' by Gopher and Braune (1984). Our modification uses utility comparison scaling techniques which avoid the unnecessary assumptions made by Gopher and Braune. Formula for the utility of complex tasks based on the theoretical models are used to predict decision and choice of alternate paths to the same goal.

The impact of egocentric vs. allocentric agency attributions on the neural bases of reasoning about social rules.

PubMed

Canessa, Nicola; Pantaleo, Giuseppe; Crespi, Chiara; Gorini, Alessandra; Cappa, Stefano F

2014-09-18

We used the "standard" and "switched" social contract versions of the Wason Selection-task to investigate the neural bases of human reasoning about social rules. Both these versions typically elicit the deontically correct answer, i.e. the proper identification of the violations of a conditional obligation. Only in the standard version of the task, however, this response corresponds to the logically correct one. We took advantage of this differential adherence to logical vs. deontical accuracy to test the different predictions of logic rule-based vs. visuospatial accounts of inferential abilities in 14 participants who solved the standard and switched versions of the Selection-task during functional-Magnetic-Resonance-Imaging. Both versions activated the well known left fronto-parietal network of deductive reasoning. The standard version additionally recruited the medial parietal and right inferior parietal cortex, previously associated with mental imagery and with the adoption of egocentric vs. allocentric spatial reference frames. These results suggest that visuospatial processes encoding one's own subjective experience in social interactions may support and shape the interpretation of deductive arguments and/or the resulting inferences, thus contributing to elicit content effects in human reasoning. Copyright © 2014 Elsevier B.V. All rights reserved.

Prospective Coding by Spiking Neurons

PubMed Central

Brea, Johanni; Gaál, Alexisz Tamás; Senn, Walter

2016-01-01

Animals learn to make predictions, such as associating the sound of a bell with upcoming feeding or predicting a movement that a motor command is eliciting. How predictions are realized on the neuronal level and what plasticity rule underlies their learning is not well understood. Here we propose a biologically plausible synaptic plasticity rule to learn predictions on a single neuron level on a timescale of seconds. The learning rule allows a spiking two-compartment neuron to match its current firing rate to its own expected future discounted firing rate. For instance, if an originally neutral event is repeatedly followed by an event that elevates the firing rate of a neuron, the originally neutral event will eventually also elevate the neuron’s firing rate. The plasticity rule is a form of spike timing dependent plasticity in which a presynaptic spike followed by a postsynaptic spike leads to potentiation. Even if the plasticity window has a width of 20 milliseconds, associations on the time scale of seconds can be learned. We illustrate prospective coding with three examples: learning to predict a time varying input, learning to predict the next stimulus in a delayed paired-associate task and learning with a recurrent network to reproduce a temporally compressed version of a sequence. We discuss the potential role of the learning mechanism in classical trace conditioning. In the special case that the signal to be predicted encodes reward, the neuron learns to predict the discounted future reward and learning is closely related to the temporal difference learning algorithm TD(λ). PMID:27341100

Motivation to comply with task rules and multitasking performance: The role of need for cognitive closure and goal importance.

PubMed

Szumowska, Ewa; Kossowska, Małgorzata; Roets, Arne

2018-01-01

In three studies, we examined the role task rules play in multitasking performance. We postulated that rules should be especially important for individuals highly motivated to have structure and clear answers, i.e., those high on need for cognitive closure (NFC). High NFC should thus be related to greater compliance with task rules. Specifically, given high goal importance, NFC should be more strongly related to a multitasking strategy when multitasking is imposed by the rules, and to a mono-tasking strategy when monotasking is imposed by the rules. This should translate into better multitasking or mono-tasking performance, depending on condition. Overall, the results were supportive as NFC was related to a more mono-tasking strategy in the mono-tasking condition (Studies 1 and 2 only) and more dual-tasking strategy in the dual-tasking condition (Studies 1-3). This translated into respective differences in performance. The effects were significant only when goal importance was high (Study 1) and held when cognitive ability was controlled for (Study 2).

Cue response dissociates inhibitory processes: task identity information is related to backward inhibition but not to competitor rule suppression.

PubMed

Regev, Shirley; Meiran, Nachshon

2017-01-01

In task switching, a conflict between competing task-sets is resolved by inhibiting the interfering task-set. Recent models have proposed a framework of the task-set as composed of two hierarchical components: abstract task identity (e.g., respond to quantity) and more concrete task rules (e.g., category-response rules mapping the categories "one" and "three" to the left and right keys, respectively). The present study explored whether task-set inhibition is the outcome of a general control process or whether it reflects multiple inhibitory processes, each targeting a different component of the competing task-set. To this end, two effects of task-set inhibition were examined: backward inhibition (BI), reflecting the suppression of a just-performed task-set that is no longer relevant; and, competitor rule suppression (CRS), reflecting the suppression of an irrelevant task-set that generates a response conflict. In two task switching experiments, each involving three tasks, we asked participants to make two responses: a cue response, indicating the identity of the relevant task (e.g., "Color"), and a target response requiring the implementation of the task rule (e.g., "Red"). The results demonstrate that BI, but not CRS, appears in cue responses, and thus, suggests that BI reflects inhibition that influences representations related to abstract task identity, rather than (just) competing responses or response rules. These results support a dissociation between inhibitory processes in task switching. The current findings also provide further evidence for a multi-component conceptualization of task-set and task-set inhibition.

Rapid Transfer of Abstract Rules to Novel Contexts in Human Lateral Prefrontal Cortex

PubMed Central

Cole, Michael W.; Etzel, Joset A.; Zacks, Jeffrey M.; Schneider, Walter; Braver, Todd S.

2011-01-01

Flexible, adaptive behavior is thought to rely on abstract rule representations within lateral prefrontal cortex (LPFC), yet it remains unclear how these representations provide such flexibility. We recently demonstrated that humans can learn complex novel tasks in seconds. Here we hypothesized that this impressive mental flexibility may be possible due to rapid transfer of practiced rule representations within LPFC to novel task contexts. We tested this hypothesis using functional MRI and multivariate pattern analysis, classifying LPFC activity patterns across 64 tasks. Classifiers trained to identify abstract rules based on practiced task activity patterns successfully generalized to novel tasks. This suggests humans can transfer practiced rule representations within LPFC to rapidly learn new tasks, facilitating cognitive performance in novel circumstances. PMID:22125519

Are Stimulus-Response Rules Represented Phonologically for Task-Set Preparation and Maintenance?

ERIC Educational Resources Information Center

van 't Wout, Félice; Lavric, Aureliu; Monsell, Stephen

2013-01-01

Accounts of task-set control generally assume that the current task's stimulus-response (S-R) rules must be elevated to a privileged state of activation. How are they represented in this state? In 3 task-cuing experiments, we tested the hypothesis that phonological working memory is used to represent S-R rules for task-set control by getting…

Dynamic Task Optimization in Remote Diabetes Monitoring Systems.

PubMed

Suh, Myung-Kyung; Woodbridge, Jonathan; Moin, Tannaz; Lan, Mars; Alshurafa, Nabil; Samy, Lauren; Mortazavi, Bobak; Ghasemzadeh, Hassan; Bui, Alex; Ahmadi, Sheila; Sarrafzadeh, Majid

2012-09-01

Diabetes is the seventh leading cause of death in the United States, but careful symptom monitoring can prevent adverse events. A real-time patient monitoring and feedback system is one of the solutions to help patients with diabetes and their healthcare professionals monitor health-related measurements and provide dynamic feedback. However, data-driven methods to dynamically prioritize and generate tasks are not well investigated in the domain of remote health monitoring. This paper presents a wireless health project (WANDA) that leverages sensor technology and wireless communication to monitor the health status of patients with diabetes. The WANDA dynamic task management function applies data analytics in real-time to discretize continuous features, applying data clustering and association rule mining techniques to manage a sliding window size dynamically and to prioritize required user tasks. The developed algorithm minimizes the number of daily action items required by patients with diabetes using association rules that satisfy a minimum support, confidence and conditional probability thresholds. Each of these tasks maximizes information gain, thereby improving the overall level of patient adherence and satisfaction. Experimental results from applying EM-based clustering and Apriori algorithms show that the developed algorithm can predict further events with higher confidence levels and reduce the number of user tasks by up to 76.19 %.

Dynamic Task Optimization in Remote Diabetes Monitoring Systems

PubMed Central

Suh, Myung-kyung; Woodbridge, Jonathan; Moin, Tannaz; Lan, Mars; Alshurafa, Nabil; Samy, Lauren; Mortazavi, Bobak; Ghasemzadeh, Hassan; Bui, Alex; Ahmadi, Sheila; Sarrafzadeh, Majid

2016-01-01

Diabetes is the seventh leading cause of death in the United States, but careful symptom monitoring can prevent adverse events. A real-time patient monitoring and feedback system is one of the solutions to help patients with diabetes and their healthcare professionals monitor health-related measurements and provide dynamic feedback. However, data-driven methods to dynamically prioritize and generate tasks are not well investigated in the domain of remote health monitoring. This paper presents a wireless health project (WANDA) that leverages sensor technology and wireless communication to monitor the health status of patients with diabetes. The WANDA dynamic task management function applies data analytics in real-time to discretize continuous features, applying data clustering and association rule mining techniques to manage a sliding window size dynamically and to prioritize required user tasks. The developed algorithm minimizes the number of daily action items required by patients with diabetes using association rules that satisfy a minimum support, confidence and conditional probability thresholds. Each of these tasks maximizes information gain, thereby improving the overall level of patient adherence and satisfaction. Experimental results from applying EM-based clustering and Apriori algorithms show that the developed algorithm can predict further events with higher confidence levels and reduce the number of user tasks by up to 76.19 %. PMID:27617297

Different strategies in solving series completion inductive reasoning problems: an fMRI and computational study.

PubMed

Liang, Peipeng; Jia, Xiuqin; Taatgen, Niels A; Zhong, Ning; Li, Kuncheng

2014-08-01

Neural correlate of human inductive reasoning process is still unclear. Number series and letter series completion are two typical inductive reasoning tasks, and with a common core component of rule induction. Previous studies have demonstrated that different strategies are adopted in number series and letter series completion tasks; even the underlying rules are identical. In the present study, we examined cortical activation as a function of two different reasoning strategies for solving series completion tasks. The retrieval strategy, used in number series completion tasks, involves direct retrieving of arithmetic knowledge to get the relations between items. The procedural strategy, used in letter series completion tasks, requires counting a certain number of times to detect the relations linking two items. The two strategies require essentially the equivalent cognitive processes, but have different working memory demands (the procedural strategy incurs greater demands). The procedural strategy produced significant greater activity in areas involved in memory retrieval (dorsolateral prefrontal cortex, DLPFC) and mental representation/maintenance (posterior parietal cortex, PPC). An ACT-R model of the tasks successfully predicted behavioral performance and BOLD responses. The present findings support a general-purpose dual-process theory of inductive reasoning regarding the cognitive architecture. Copyright © 2014 Elsevier B.V. All rights reserved.

Reasoning with alternative explanations in physics: The cognitive accessibility rule

NASA Astrophysics Data System (ADS)

Heckler, Andrew F.; Bogdan, Abigail M.

2018-06-01

A critical component of scientific reasoning is the consideration of alternative explanations. Recognizing that decades of cognitive psychology research have demonstrated that relative cognitive accessibility, or "what comes to mind," strongly affects how people reason in a given context, we articulate a simple "cognitive accessibility rule", namely that alternative explanations are considered less frequently when an explanation with relatively high accessibility is offered first. In a series of four experiments, we test the cognitive accessibility rule in the context of consideration of alternative explanations for six physical scenarios commonly found in introductory physics curricula. First, we administer free recall and recognition tasks to operationally establish and distinguish between the relative accessibility and availability of common explanations for the physical scenarios. Then, we offer either high or low accessibility explanations for the physical scenarios and determine the extent to which students consider alternatives to the given explanations. We find two main results consistent across algebra- and calculus-based university level introductory physics students for multiple answer formats. First, we find evidence that, at least for some contexts, most explanatory factors are cognitively available to students but not cognitively accessible. Second, we empirically verify the cognitive accessibility rule and demonstrate that the rule is strongly predictive, accounting for up to 70% of the variance of the average student consideration of alternative explanations across scenarios. Overall, we find that cognitive accessibility can help to explain biases in the consideration of alternatives in reasoning about simple physical scenarios, and these findings lend support to the growing number of science education studies demonstrating that tasks relevant to science education curricula often involve rapid, automatic, and potentially predictable processes and outcomes.

Deontic Reasoning with Emotional Content: Evolutionary Psychology or Decision Theory?

ERIC Educational Resources Information Center

Perham, Nick; Oaksford, Mike

2005-01-01

Three experiments investigated the contrasting predictions of the evolutionary and decision-theoretic approaches to deontic reasoning. Two experiments embedded a hazard management (HM) rule in a social contract scenario that should lead to competition between innate modules. A 3rd experiment used a pure HM task. Threatening material was also…

Parsing the roles of the frontal lobes and basal ganglia in task control using multivoxel pattern analysis

PubMed Central

Kehagia, Angie A.; Ye, Rong; Joyce, Dan W.; Doyle, Orla M.; Rowe, James B.; Robbins, Trevor W.

2017-01-01

Cognitive control has traditionally been associated with the prefrontal cortex, based on observations of deficits in patients with frontal lesions. However, evidence from patients with Parkinson’s disease (PD) indicates that subcortical regions also contribute to control under certain conditions. We scanned 17 healthy volunteers while they performed a task switching paradigm that previously dissociated performance deficits arising from frontal lesions in comparison with PD, as a function of the abstraction of the rules that are switched. From a multivoxel pattern analysis by Gaussian Process Classification (GPC), we then estimated the forward (generative) model to infer regional patterns of activity that predict Switch / Repeat behaviour between rule conditions. At 1000 permutations, Switch / Repeat classification accuracy for concrete rules was significant in the basal ganglia, but at chance in the frontal lobe. The inverse pattern was obtained for abstract rules, whereby the conditions were successfully discriminated in the frontal lobe but not in the basal ganglia. This double dissociation highlights the difference between cortical and subcortical contributions to cognitive control and demonstrates the utility of multivariate approaches in investigations of functions that rely on distributed and overlapping neural substrates. PMID:28387585

The cooking task: making a meal of executive functions

PubMed Central

Doherty, T. A.; Barker, L. A.; Denniss, R.; Jalil, A.; Beer, M. D.

2015-01-01

Current standardized neuropsychological tests may fail to accurately capture real-world executive deficits. We developed a computer-based Cooking Task (CT) assessment of executive functions and trialed the measure with a normative group before use with a head-injured population. Forty-six participants completed the computerized CT and subtests from standardized neuropsychological tasks, including the Tower and Sorting Tests of executive function from the Delis-Kaplan Executive Function System (D-KEFS) and the Cambridge prospective memory test (CAMPROMPT), in order to examine whether standardized executive function tasks, predicted performance on measurement indices from the CT. Findings showed that verbal comprehension, rule detection and prospective memory contributed to measures of prospective planning accuracy and strategy implementation of the CT. Results also showed that functions necessary for cooking efficacy differ as an effect of task demands (difficulty levels). Performance on rule detection, strategy implementation and flexible thinking executive function measures contributed to accuracy on the CT. These findings raise questions about the functions captured by present standardized tasks particularly at varying levels of difficulty and during dual-task performance. Our preliminary findings also indicate that CT measures can effectively distinguish between executive function and Full Scale IQ abilities. Results of the present study indicate that the CT shows promise as an ecologically valid measure of executive function for future use with a head-injured population and indexes selective executive function’s captured by standardized tests. PMID:25717294

The cooking task: making a meal of executive functions.

PubMed

Doherty, T A; Barker, L A; Denniss, R; Jalil, A; Beer, M D

2015-01-01

Current standardized neuropsychological tests may fail to accurately capture real-world executive deficits. We developed a computer-based Cooking Task (CT) assessment of executive functions and trialed the measure with a normative group before use with a head-injured population. Forty-six participants completed the computerized CT and subtests from standardized neuropsychological tasks, including the Tower and Sorting Tests of executive function from the Delis-Kaplan Executive Function System (D-KEFS) and the Cambridge prospective memory test (CAMPROMPT), in order to examine whether standardized executive function tasks, predicted performance on measurement indices from the CT. Findings showed that verbal comprehension, rule detection and prospective memory contributed to measures of prospective planning accuracy and strategy implementation of the CT. Results also showed that functions necessary for cooking efficacy differ as an effect of task demands (difficulty levels). Performance on rule detection, strategy implementation and flexible thinking executive function measures contributed to accuracy on the CT. These findings raise questions about the functions captured by present standardized tasks particularly at varying levels of difficulty and during dual-task performance. Our preliminary findings also indicate that CT measures can effectively distinguish between executive function and Full Scale IQ abilities. Results of the present study indicate that the CT shows promise as an ecologically valid measure of executive function for future use with a head-injured population and indexes selective executive function's captured by standardized tests.

R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

PRIMsrc is a novel implementation of a non-parametric bump hunting procedure, based on the Patient Rule Induction Method (PRIM), offering a unified treatment of outcome variables, including censored time-to-event (Survival), continuous (Regression) and discrete (Classification) responses. To fit the model, it uses a recursive peeling procedure with specific peeling criteria and stopping rules depending on the response. To validate the model, it provides an objective function based on prediction-error or other specific statistic, as well as two alternative cross-validation techniques, adapted to the task of decision-rule making and estimation in the three types of settings. PRIMsrc comes as an open source R package, including at this point: (i) a main function for fitting a Survival Bump Hunting model with various options allowing cross-validated model selection to control model size (#covariates) and model complexity (#peeling steps) and generation of cross-validated end-point estimates; (ii) parallel computing; (iii) various S3-generic and specific plotting functions for data visualization, diagnostic, prediction, summary and display of results. It is available on CRAN and GitHub. PMID:26798326

Similarity-Dissimilarity Competition in Disjunctive Classification Tasks

PubMed Central

Mathy, Fabien; Haladjian, Harry H.; Laurent, Eric; Goldstone, Robert L.

2013-01-01

Typical disjunctive artificial classification tasks require participants to sort stimuli according to rules such as “x likes cars only when black and coupe OR white and SUV.” For categories like this, increasing the salience of the diagnostic dimensions has two simultaneous effects: increasing the distance between members of the same category and increasing the distance between members of opposite categories. Potentially, these two effects respectively hinder and facilitate classification learning, leading to competing predictions for learning. Increasing saliency may lead to members of the same category to be considered less similar, while the members of separate categories might be considered more dissimilar. This implies a similarity-dissimilarity competition between two basic classification processes. When focusing on sub-category similarity, one would expect more difficult classification when members of the same category become less similar (disregarding the increase of between-category dissimilarity); however, the between-category dissimilarity increase predicts a less difficult classification. Our categorization study suggests that participants rely more on using dissimilarities between opposite categories than finding similarities between sub-categories. We connect our results to rule- and exemplar-based classification models. The pattern of influences of within- and between-category similarities are challenging for simple single-process categorization systems based on rules or exemplars. Instead, our results suggest that either these processes should be integrated in a hybrid model, or that category learning operates by forming clusters within each category. PMID:23403979

Stochastic Dynamics Underlying Cognitive Stability and Flexibility

PubMed Central

Ueltzhöffer, Kai; Armbruster-Genç, Diana J. N.; Fiebach, Christian J.

2015-01-01

Cognitive stability and flexibility are core functions in the successful pursuit of behavioral goals. While there is evidence for a common frontoparietal network underlying both functions and for a key role of dopamine in the modulation of flexible versus stable behavior, the exact neurocomputational mechanisms underlying those executive functions and their adaptation to environmental demands are still unclear. In this work we study the neurocomputational mechanisms underlying cue based task switching (flexibility) and distractor inhibition (stability) in a paradigm specifically designed to probe both functions. We develop a physiologically plausible, explicit model of neural networks that maintain the currently active task rule in working memory and implement the decision process. We simplify the four-choice decision network to a nonlinear drift-diffusion process that we canonically derive from a generic winner-take-all network model. By fitting our model to the behavioral data of individual subjects, we can reproduce their full behavior in terms of decisions and reaction time distributions in baseline as well as distractor inhibition and switch conditions. Furthermore, we predict the individual hemodynamic response timecourse of the rule-representing network and localize it to a frontoparietal network including the inferior frontal junction area and the intraparietal sulcus, using functional magnetic resonance imaging. This refines the understanding of task-switch-related frontoparietal brain activity as reflecting attractor-like working memory representations of task rules. Finally, we estimate the subject-specific stability of the rule-representing attractor states in terms of the minimal action associated with a transition between different rule states in the phase-space of the fitted models. This stability measure correlates with switching-specific thalamocorticostriatal activation, i.e., with a system associated with flexible working memory updating and dopaminergic modulation of cognitive flexibility. These results show that stochastic dynamical systems can implement the basic computations underlying cognitive stability and flexibility and explain neurobiological bases of individual differences. PMID:26068119

A New Data Mining Scheme Using Artificial Neural Networks

PubMed Central

Kamruzzaman, S. M.; Jehad Sarkar, A. M.

2011-01-01

Classification is one of the data mining problems receiving enormous attention in the database community. Although artificial neural networks (ANNs) have been successfully applied in a wide range of machine learning applications, they are however often regarded as black boxes, i.e., their predictions cannot be explained. To enhance the explanation of ANNs, a novel algorithm to extract symbolic rules from ANNs has been proposed in this paper. ANN methods have not been effectively utilized for data mining tasks because how the classifications were made is not explicitly stated as symbolic rules that are suitable for verification or interpretation by human experts. With the proposed approach, concise symbolic rules with high accuracy, that are easily explainable, can be extracted from the trained ANNs. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and the accuracy. The effectiveness of the proposed approach is clearly demonstrated by the experimental results on a set of benchmark data mining classification problems. PMID:22163866

A Conceptual Framework for Predicting Error in Complex Human-Machine Environments

NASA Technical Reports Server (NTRS)

Freed, Michael; Remington, Roger; Null, Cynthia H. (Technical Monitor)

1998-01-01

We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely.

The Emergent Executive: A Dynamic Field Theory of the Development of Executive Function

PubMed Central

Buss, Aaron T.; Spencer, John P.

2015-01-01

A dynamic neural field (DNF) model is presented which provides a process-based account of behavior and developmental change in a key task used to probe the early development of executive function—the Dimensional Change Card Sort (DCCS) task. In the DCCS, children must flexibly switch from sorting cards either by shape or color to sorting by the other dimension. Typically, 3-year-olds, but not 4-year-olds, lack the flexibility to do so and perseverate on the first set of rules when instructed to switch. In the DNF model, rule-use and behavioral flexibility come about through a form of dimensional attention which modulates activity within different cortical fields tuned to specific feature dimensions. In particular, we capture developmental change by increasing the strength of excitatory and inhibitory neural interactions in the dimensional attention system as well as refining the connectivity between this system and the feature-specific cortical fields. Note that although this enables the model to effectively switch tasks, the dimensional attention system does not ‘know’ the details of task-specific performance. Rather, correct performance emerges as a property of system-wide neural interactions. We show how this captures children's behavior in quantitative detail across 12 versions of the DCCS task. Moreover, we successfully test a set of novel predictions with 3-year-old children from a version of the task not explained by other theories. PMID:24818836

A neural mechanism of cognitive control for resolving conflict between abstract task rules.

PubMed

Sheu, Yi-Shin; Courtney, Susan M

2016-12-01

Conflict between multiple sensory stimuli or potential motor responses is thought to be resolved via bias signals from prefrontal cortex (PFC). However, population codes in the PFC also represent abstract information, such as task rules. How is conflict between active abstract representations resolved? We used functional neuroimaging to investigate the mechanism responsible for resolving conflict between abstract representations of task rules. Participants performed two different tasks based on a cue. We manipulated the degree of conflict at the task-rule level by training participants to associate the color and shape dimensions of the cue with either the same task rule (congruent cues) or different ones (incongruent cues). Phonological and semantic tasks were used in which performance depended on learned, abstract representations of information, rather than sensory features of the target stimulus or on any habituated stimulus-response associations. In addition, these tasks activate distinct regions that allowed us to measure magnitude of conflict between tasks. We found that incongruent cues were associated with increased activity in several cognitive control areas, including the inferior frontal gyrus, inferior parietal lobule, insula, and subcortical regions. Conflict between abstract representations appears to be resolved by rule-specific activity in the inferior frontal gyrus that is correlated with enhanced activity related to the relevant information. Furthermore, multi-voxel pattern analysis of the activity in the inferior frontal gyrus was shown to carry information about both the currently relevant rule (semantic/phonological) and the currently relevant cue context (color/shape). Similar to models of attentional selection of conflicting sensory or motor representations, the current findings indicate part of the frontal cortex provides a bias signal, representing task rules, that enhances task-relevant information. However, the frontal cortex can also be the target of these bias signals in order to enhance abstract representations that are independent of particular stimuli or motor responses. Copyright © 2016 Elsevier Ltd. All rights reserved.

A neural mechanism of cognitive control for resolving conflict between abstract task rules

PubMed Central

Sheu, Yi-Shin; Courtney, Susan M.

2016-01-01

Conflict between multiple sensory stimuli or potential motor responses is thought to be resolved via bias signals from prefrontal cortex. However, population codes in the prefrontal cortex also represent abstract information, such as task rules. How is conflict between active abstract representations resolved? We used functional neuroimaging to investigate the mechanism responsible for resolving conflict between abstract representations of task rules. Participants performed two different tasks based on a cue. We manipulated the degree of conflict at the task-rule level by training participants to associate the color and shape dimensions of the cue with either the same task rule (congruent cues) or different ones (incongruent cues). Phonological and semantic tasks were used in which performance depended on learned, abstract representations of information, rather than sensory features of the target stimulus or on any habituated stimulus-response associations. In addition, these tasks activate distinct regions that allowed us to measure magnitude of conflict between tasks. We found that incongruent cues were associated with increased activity in several cognitive control areas, including the inferior frontal gyrus, inferior parietal lobule, insula, and subcortical regions. Conflict between abstract representations appears to be resolved by rule-specific activity in the inferior frontal gyrus that is correlated with enhanced activity related to the relevant information. Furthermore, multivoxel pattern analysis of the activity in the inferior frontal gyrus was shown to carry information about both the currently relevant rule (semantic/phonological) and the currently relevant cue context (color/shape). Similar to models of attentional selection of conflicting sensory or motor representations, the current findings indicate part of the frontal cortex provides a bias signal, representing task rules, that enhances task-relevant information. However, the frontal cortex can also be the target of these bias signals in order to enhance abstract representations that are independent of particular stimuli or motor responses. PMID:27771559

Foraging Ecology Predicts Learning Performance in Insectivorous Bats

PubMed Central

Clarin, Theresa M. A.; Ruczyński, Ireneusz; Page, Rachel A.

2013-01-01

Bats are unusual among mammals in showing great ecological diversity even among closely related species and are thus well suited for studies of adaptation to the ecological background. Here we investigate whether behavioral flexibility and simple- and complex-rule learning performance can be predicted by foraging ecology. We predict faster learning and higher flexibility in animals hunting in more complex, variable environments than in animals hunting in more simple, stable environments. To test this hypothesis, we studied three closely related insectivorous European bat species of the genus Myotis that belong to three different functional groups based on foraging habitats: M. capaccinii, an open water forager, M. myotis, a passive listening gleaner, and M. emarginatus, a clutter specialist. We predicted that M. capaccinii would show the least flexibility and slowest learning reflecting its relatively unstructured foraging habitat and the stereotypy of its natural foraging behavior, while the other two species would show greater flexibility and more rapid learning reflecting the complexity of their natural foraging tasks. We used a purposefully unnatural and thus species-fair crawling maze to test simple- and complex-rule learning, flexibility and re-learning performance. We found that M. capaccinii learned a simple rule as fast as the other species, but was slower in complex rule learning and was less flexible in response to changes in reward location. We found no differences in re-learning ability among species. Our results corroborate the hypothesis that animals’ cognitive skills reflect the demands of their ecological niche. PMID:23755146

What is preexisting strength? Predicting free association probabilities, similarity ratings, and cued recall probabilities.

PubMed

Nelson, Douglas L; Dyrdal, Gunvor M; Goodmon, Leilani B

2005-08-01

Measuring lexical knowledge poses a challenge to the study of the influence of preexisting knowledge on the retrieval of new memories. Many tasks focus on word pairs, but words are embedded in associative networks, so how should preexisting pair strength be measured? It has been measured by free association, similarity ratings, and co-occurrence statistics. Researchers interpret free association response probabilities as unbiased estimates of forward cue-to-target strength. In Study 1, analyses of large free association and extralist cued recall databases indicate that this interpretation is incorrect. Competitor and backward strengths bias free association probabilities, and as with other recall tasks, preexisting strength is described by a ratio rule. In Study 2, associative similarity ratings are predicted by forward and backward, but not by competitor, strength. Preexisting strength is not a unitary construct, because its measurement varies with method. Furthermore, free association probabilities predict extralist cued recall better than do ratings and co-occurrence statistics. The measure that most closely matches the criterion task may provide the best estimate of the identity of preexisting strength.

A Swarm Optimization approach for clinical knowledge mining.

PubMed

Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A

2015-10-01

Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The optimum decision rules for the oddity task.

PubMed

Versfeld, N J; Dai, H; Green, D M

1996-01-01

This paper presents the optimum decision rule for an m-interval oddity task in which m-1 intervals contain the same signal and one is different or odd. The optimum decision rule depends on the degree of correlation among observations. The present approach unifies the different strategies that occur with "roved" or "fixed" experiments (Macmillan & Creelman, 1991, p. 147). It is shown that the commonly used decision rule for an m-interval oddity task corresponds to the special case of highly correlated observations. However, as is also true for the same-different paradigm, there exists a different optimum decision rule when the observations are independent. The relation between the probability of a correct response and d' is derived for the three-interval oddity task. Tables are presented of this relation for the three-, four-, and five-interval oddity task. Finally, an experimental method is proposed that allows one to determine the decision rule used by the observer in an oddity experiment.

Phonological reduplication in sign language: Rules rule

PubMed Central

Berent, Iris; Dupuis, Amanda; Brentari, Diane

2014-01-01

Productivity—the hallmark of linguistic competence—is typically attributed to algebraic rules that support broad generalizations. Past research on spoken language has documented such generalizations in both adults and infants. But whether algebraic rules form part of the linguistic competence of signers remains unknown. To address this question, here we gauge the generalization afforded by American Sign Language (ASL). As a case study, we examine reduplication (X→XX)—a rule that, inter alia, generates ASL nouns from verbs. If signers encode this rule, then they should freely extend it to novel syllables, including ones with features that are unattested in ASL. And since reduplicated disyllables are preferred in ASL, such a rule should favor novel reduplicated signs. Novel reduplicated signs should thus be preferred to nonreduplicative controls (in rating), and consequently, such stimuli should also be harder to classify as nonsigns (in the lexical decision task). The results of four experiments support this prediction. These findings suggest that the phonological knowledge of signers includes powerful algebraic rules. The convergence between these conclusions and previous evidence for phonological rules in spoken language suggests that the architecture of the phonological mind is partly amodal. PMID:24959158

Efficiency in Rule- vs. Plan-Based Movements Is Modulated by Action-Mode.

PubMed

Scheib, Jean P P; Stoll, Sarah; Thürmer, J Lukas; Randerath, Jennifer

2018-01-01

The rule/plan motor cognition (RPMC) paradigm elicits visually indistinguishable motor outputs, resulting from either plan- or rule-based action-selection, using a combination of essentially interchangeable stimuli. Previous implementations of the RPMC paradigm have used pantomimed movements to compare plan- vs. rule-based action-selection. In the present work we attempt to determine the generalizability of previous RPMC findings to real object interaction by use of a grasp-to-rotate task. In the plan task, participants had to use prospective planning to achieve a comfortable post-handle rotation hand posture. The rule task used implementation intentions (if-then rules) leading to the same comfortable end-state. In Experiment A, we compare RPMC performance of 16 healthy participants in pantomime and real object conditions of the experiment, within-subjects. Higher processing efficiency of rule- vs. plan-based action-selection was supported by diffusion model analysis. Results show a significant response-time increase in the pantomime condition compared to the real object condition and a greater response-time advantage of rule-based vs. plan-based actions in the pantomime compared to the real object condition. In Experiment B, 24 healthy participants performed the real object RPMC task in a task switching vs. a blocked condition. Results indicate that plan-based action-selection leads to longer response-times and less efficient information processing than rule-based action-selection in line with previous RPMC findings derived from the pantomime action-mode. Particularly in the task switching mode, responses were faster in the rule compared to the plan task suggesting a modulating influence of cognitive load. Overall, results suggest an advantage of rule-based action-selection over plan-based action-selection; whereby differential mechanisms appear to be involved depending on the action-mode. We propose that cognitive load is a factor that modulates the advantageous effect of implementation intentions in motor cognition on different levels as illustrated by the varying speed advantages and the variation in diffusion parameters per action-mode or condition, respectively.

Minimal perceptrons for memorizing complex patterns

NASA Astrophysics Data System (ADS)

Pastor, Marissa; Song, Juyong; Hoang, Danh-Tai; Jo, Junghyo

2016-11-01

Feedforward neural networks have been investigated to understand learning and memory, as well as applied to numerous practical problems in pattern classification. It is a rule of thumb that more complex tasks require larger networks. However, the design of optimal network architectures for specific tasks is still an unsolved fundamental problem. In this study, we consider three-layered neural networks for memorizing binary patterns. We developed a new complexity measure of binary patterns, and estimated the minimal network size for memorizing them as a function of their complexity. We formulated the minimal network size for regular, random, and complex patterns. In particular, the minimal size for complex patterns, which are neither ordered nor disordered, was predicted by measuring their Hamming distances from known ordered patterns. Our predictions agree with simulations based on the back-propagation algorithm.

Rule induction performance in amnestic mild cognitive impairment and Alzheimer's dementia: examining the role of simple and biconditional rule learning processes.

PubMed

Oosterman, Joukje M; Heringa, Sophie M; Kessels, Roy P C; Biessels, Geert Jan; Koek, Huiberdina L; Maes, Joseph H R; van den Berg, Esther

2017-04-01

Rule induction tests such as the Wisconsin Card Sorting Test require executive control processes, but also the learning and memorization of simple stimulus-response rules. In this study, we examined the contribution of diminished learning and memorization of simple rules to complex rule induction test performance in patients with amnestic mild cognitive impairment (aMCI) or Alzheimer's dementia (AD). Twenty-six aMCI patients, 39 AD patients, and 32 control participants were included. A task was used in which the memory load and the complexity of the rules were independently manipulated. This task consisted of three conditions: a simple two-rule learning condition (Condition 1), a simple four-rule learning condition (inducing an increase in memory load, Condition 2), and a complex biconditional four-rule learning condition-inducing an increase in complexity and, hence, executive control load (Condition 3). Performance of AD patients declined disproportionately when the number of simple rules that had to be memorized increased (from Condition 1 to 2). An additional increment in complexity (from Condition 2 to 3) did not, however, disproportionately affect performance of the patients. Performance of the aMCI patients did not differ from that of the control participants. In the patient group, correlation analysis showed that memory performance correlated with Condition 1 performance, whereas executive task performance correlated with Condition 2 performance. These results indicate that the reduced learning and memorization of underlying task rules explains a significant part of the diminished complex rule induction performance commonly reported in AD, although results from the correlation analysis suggest involvement of executive control functions as well. Taken together, these findings suggest that care is needed when interpreting rule induction task performance in terms of executive function deficits in these patients.

Some Memories are Odder than Others: Judgments of Episodic Oddity Violate Known Decision Rules

PubMed Central

O’Connor, Akira R.; Guhl, Emily N.; Cox, Justin C.; Dobbins, Ian G.

2011-01-01

Current decision models of recognition memory are based almost entirely on one paradigm, single item old/new judgments accompanied by confidence ratings. This task results in receiver operating characteristics (ROCs) that are well fit by both signal-detection and dual-process models. Here we examine an entirely new recognition task, the judgment of episodic oddity, whereby participants select the mnemonically odd members of triplets (e.g., a new item hidden among two studied items). Using the only two known signal-detection rules of oddity judgment derived from the sensory perception literature, the unequal variance signal-detection model predicted that an old item among two new items would be easier to discover than a new item among two old items. In contrast, four separate empirical studies demonstrated the reverse pattern: triplets with two old items were the easiest to resolve. This finding was anticipated by the dual-process approach as the presence of two old items affords the greatest opportunity for recollection. Furthermore, a bootstrap-fed Monte Carlo procedure using two independent datasets demonstrated that the dual-process parameters typically observed during single item recognition correctly predict the current oddity findings, whereas unequal variance signal-detection parameters do not. Episodic oddity judgments represent a case where dual- and single-process predictions qualitatively diverge and the findings demonstrate that novelty is “odder” than familiarity. PMID:22833695

Are stimulus-response rules represented phonologically for task-set preparation and maintenance?

PubMed

van 't Wout, Félice; Lavric, Aureliu; Monsell, Stephen

2013-09-01

Accounts of task-set control generally assume that the current task's stimulus-response (S-R) rules must be elevated to a privileged state of activation. How are they represented in this state? In 3 task-cuing experiments, we tested the hypothesis that phonological working memory is used to represent S-R rules for task-set control by getting participants to switch between 2 sets of arbitrary S-R rules and manipulating the articulatory duration (Experiment 1) or phonological similarity (Experiments 2 and 3) of the names of the stimulus terms. The task cue specified which of 2 objects (Experiment 1) or consonants (Experiment 2) in a display to identify with a key press. In Experiment 3, participants switched between identifying an object/consonant and its color/visual texture. After practice, neither the duration nor the similarity of the stimulus terms had detectable effects on overall performance, task-switch cost, or its reduction with preparation. Only in the initial single-task training blocks was phonological similarity a significant handicap. Hence, beyond a very transient role, there is no evidence that (declarative) phonological working memory makes a functional contribution to representing S-R rules for task-set control, arguably because once learned, they are represented in nonlinguistic procedural working memory. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Modeling of Depth Cue Integration in Manual Control Tasks

NASA Technical Reports Server (NTRS)

Sweet, Barbara T.; Kaiser, Mary K.; Davis, Wendy

2003-01-01

Psychophysical research has demonstrated that human observers utilize a variety of visual cues to form a perception of three-dimensional depth. However, most of these studies have utilized a passive judgement paradigm, and failed to consider depth-cue integration as a dynamic and task-specific process. In the current study, we developed and experimentally validated a model of manual control of depth that examines how two potential cues (stereo disparity and relative size) are utilized in both first- and second-order active depth control tasks. We found that stereo disparity plays the dominate role for determining depth position, while relative size dominates perception of depth velocity. Stereo disparity also plays a reduced role when made less salient (i.e., when viewing distance is increased). Manual control models predict that position information is sufficient for first-order control tasks, while velocity information is required to perform a second-order control task. Thus, the rules for depth-cue integration in active control tasks are dependent on both task demands and cue quality.

Motion direction discrimination training reduces perceived motion repulsion.

PubMed

Jia, Ke; Li, Sheng

2017-04-01

Participants often exaggerate the perceived angular separation between two simultaneously presented motion stimuli, which is referred to as motion repulsion. The overestimation helps participants differentiate between the two superimposed motion directions, yet it causes the impairment of direction perception. Since direction perception can be refined through perceptual training, we here attempted to investigate whether the training of a direction discrimination task changes the amount of motion repulsion. Our results showed a direction-specific learning effect, which was accompanied by a reduced amount of motion repulsion both for the trained and the untrained directions. The reduction of the motion repulsion disappeared when the participants were trained on a luminance discrimination task (control experiment 1) or a speed discrimination task (control experiment 2), ruling out any possible interpretation in terms of adaptation or training-induced attentional bias. Furthermore, training with a direction discrimination task along a direction 150° away from both directions in the transparent stimulus (control experiment 3) also had little effect on the amount of motion repulsion, ruling out the contribution of task learning. The changed motion repulsion observed in the main experiment was consistent with the prediction of the recurrent model of perceptual learning. Therefore, our findings demonstrate that training in direction discrimination can benefit the precise direction perception of the transparent stimulus and provide new evidence for the recurrent model of perceptual learning.

Mechanisms of rule acquisition and rule following in inductive reasoning.

PubMed

Crescentini, Cristiano; Seyed-Allaei, Shima; De Pisapia, Nicola; Jovicich, Jorge; Amati, Daniele; Shallice, Tim

2011-05-25

Despite the recent interest in the neuroanatomy of inductive reasoning processes, the regional specificity within prefrontal cortex (PFC) for the different mechanisms involved in induction tasks remains to be determined. In this study, we used fMRI to investigate the contribution of PFC regions to rule acquisition (rule search and rule discovery) and rule following. Twenty-six healthy young adult participants were presented with a series of images of cards, each consisting of a set of circles numbered in sequence with one colored blue. Participants had to predict the position of the blue circle on the next card. The rules that had to be acquired pertained to the relationship among succeeding stimuli. Responses given by subjects were categorized in a series of phases either tapping rule acquisition (responses given up to and including rule discovery) or rule following (correct responses after rule acquisition). Mid-dorsolateral PFC (mid-DLPFC) was active during rule search and remained active until successful rule acquisition. By contrast, rule following was associated with activation in temporal, motor, and medial/anterior prefrontal cortex. Moreover, frontopolar cortex (FPC) was active throughout the rule acquisition and rule following phases before a rule became familiar. We attributed activation in mid-DLPFC to hypothesis generation and in FPC to integration of multiple separate inferences. The present study provides evidence that brain activation during inductive reasoning involves a complex network of frontal processes and that different subregions respond during rule acquisition and rule following phases.

Spatiotemporal neurodynamics of automatic temporal expectancy in 9-month old infants.

PubMed

Mento, Giovanni; Valenza, Eloisa

2016-11-04

Anticipating events occurrence (Temporal Expectancy) is a crucial capacity for survival. Yet, there is little evidence about the presence of cortical anticipatory activity from infancy. In this study we recorded the High-density electrophysiological activity in 9 month-old infants and adults undergoing an audio-visual S1-S2 paradigm simulating a lifelike "Peekaboo" game inducing automatic temporal expectancy of smiling faces. The results indicate in the S2-preceding Contingent Negative Variation (CNV) an early electrophysiological signature of expectancy-based anticipatory cortical activity. Moreover, the progressive CNV amplitude increasing across the task suggested that implicit temporal rule learning is at the basis of expectancy building-up over time. Cortical source reconstruction suggested a common CNV generator between adults and infants in the right prefrontal cortex. The decrease in the activity of this area across the task (time-on-task effect) further implied an early, core role of this region in implicit temporal rule learning. By contrast, a time-on-task activity boost was found in the supplementary motor area (SMA) in adults and in the temporoparietal regions in infants. Altogether, our findings suggest that the capacity of the human brain to translate temporal predictions into anticipatory neural activity emerges ontogenetically early, although the underlying spatiotemporal cortical dynamics change across development.

Measuring the construct of executive control in schizophrenia: defining and validating translational animal paradigms for discovery research.

PubMed

Gilmour, Gary; Arguello, Alexander; Bari, Andrea; Brown, Verity J; Carter, Cameron; Floresco, Stan B; Jentsch, David J; Tait, David S; Young, Jared W; Robbins, Trevor W

2013-11-01

Executive control is an aspect of cognitive function known to be impaired in schizophrenia. Previous meetings of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) group have more precisely defined executive control in terms of two constructs: "rule generation and selection", and "dynamic adjustments of control". Next, human cognitive tasks that may effectively measure performance with regard to these constructs were identified to be developed into practical and reliable measures for use in treatment development. The aim of this round of CNTRICS meetings was to define animal paradigms that have sufficient promise to warrant further investigation for their utility in measuring these constructs. Accordingly, "reversal learning" and the "attentional set-shifting task" were nominated to assess the construct of rule generation and selection, and the "stop signal task" for the construct of dynamic adjustments of control. These tasks are described in more detail here, with a particular focus on their utility for drug discovery efforts. Presently, each assay has strengths and weaknesses with regard to this point and increased emphasis on improving practical aspects of testing, understanding predictive validity, and defining biomarkers of performance represent important objectives in attaining confidence in translational validity here. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Towards Better Computational Models of the Balance Scale Task: A Reply to Shultz and Takane

ERIC Educational Resources Information Center

van der Maas, Han L. J.; Quinlan, Philip T.; Jansen, Brenda R. J.

2007-01-01

In contrast to Shultz and Takane [Shultz, T.R., & Takane, Y. (2007). Rule following and rule use in the balance-scale task. "Cognition", in press, doi:10.1016/j.cognition.2006.12.004.] we do not accept that the traditional Rule Assessment Method (RAM) of scoring responses on the balance scale task has advantages over latent class analysis (LCA):…

Patterns of brain and cardiovascular activation while solving rule-discovery and rule-application numeric tasks.

PubMed

Sosnowski, Tytus; Rynkiewicz, Andrzej; Wordecha, Małgorzata; Kępkowicz, Anna; Majewska, Adrianna; Pstrągowska, Aleksandra; Oleksy, Tomasz; Wypych, Marek; Marchewka, Artur

2017-07-01

It is known that solving mental tasks leads to tonic increase in cardiovascular activity. Our previous research showed that tasks involving rule application (RA) caused greater tonic increase in cardiovascular activity than tasks requiring rule discovery (RD). However, it is not clear what brain mechanisms are responsible for this difference. The aim of two experimental studies was to compare the patterns of brain and cardiovascular activity while both RD and the RA numeric tasks were being solved. The fMRI study revealed greater brain activation while solving RD tasks than while solving RA tasks. In particular, RD tasks evoked greater activation of the left inferior frontal gyrus and selected areas in the parietal, and temporal cortices, including the precuneus, supramarginal gyrus, angular gyrus, inferior parietal lobule, and the superior temporal gyrus, and the cingulate cortex. In addition, RA tasks caused larger increases in HR than RD tasks. The second study, carried out in a cardiovascular laboratory, showed greater increases in heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) while solving RA tasks than while solving RD tasks. The results support the hypothesis that RD and RA tasks involve different modes of information processing, but the neuronal mechanism responsible for the observed greater cardiovascular response to RA tasks than to RD tasks is not completely clear. Copyright © 2017. Published by Elsevier B.V.

Cholinergic Overstimulation Attenuates Rule Selectivity in Macaque Prefrontal Cortex.

PubMed

Major, Alex J; Vijayraghavan, Susheel; Everling, Stefan

2018-01-31

Acetylcholine is released in the prefrontal cortex (PFC) and is a key modulator of cognitive performance in primates. Cholinergic stimulation has been shown to have beneficial effects on performance of cognitive tasks, and cholinergic receptors are being actively explored as promising targets for ameliorating cognitive deficits in Alzheimer's disease. We hypothesized that cholinergic stimulation of PFC during performance of a cognitive task would augment neuronal activity and neuronal coding of task attributes. We iontophoretically applied the general cholinergic receptor agonist carbachol onto neurons in dorsolateral PFC (DLPFC) of male rhesus macaques performing rule-guided prosaccades and antisaccades, a well established oculomotor task for testing cognitive control. Carbachol application had heterogeneous effects on neuronal excitability, with both excitation and suppression observed in significant proportions. Contrary to our prediction, neurons with rule-selective activity exhibited a reduction in selectivity during carbachol application. Cholinergic stimulation disrupted rule selectivity regardless of whether it had suppressive or excitatory effects on these neurons. In addition, cholinergic stimulation excited putative pyramidal neurons, whereas the activity of putative interneurons remained unchanged. Moreover, cholinergic stimulation attenuated saccade direction selectivity in putative pyramidal neurons due to nonspecific increases in activity. Our results suggest excessive cholinergic stimulation has detrimental effects on DLPFC representations of task attributes. These findings delineate the complexity and heterogeneity of neuromodulation of cerebral cortex by cholinergic stimulation, an area of active exploration with respect to the development of cognitive enhancers. SIGNIFICANCE STATEMENT The neurotransmitter acetylcholine is known to be important for cognitive processes in the prefrontal cortex. Removal of acetylcholine from prefrontal cortex can disrupt short-term memory performance and is reminiscent of Alzheimer's disease, which is characterized by degeneration of acetylcholine-producing neurons. Stimulation of cholinergic receptors is being explored to create cognitive enhancers for the treatment of Alzheimer's disease and other psychiatric diseases. Here, we stimulated cholinergic receptors in prefrontal cortex and examined its effects on neurons that are engaged in cognitive behavior. Surprisingly, cholinergic stimulation decreased neurons' ability to discriminate between rules. This work suggests that overstimulation of acetylcholine receptors could disrupt neuronal processing during cognition and is relevant to the design of cognitive enhancers based on stimulating the cholinergic system. Copyright © 2018 the authors 0270-6474/18/381137-14$15.00/0.

Orientation Transfer in Vernier and Stereoacuity Training.

PubMed

Snell, Nathaniel; Kattner, Florian; Rokers, Bas; Green, C Shawn

2015-01-01

Human performance on various visual tasks can be improved substantially via training. However, the enhancements are frequently specific to relatively low-level stimulus dimensions. While such specificity has often been thought to be indicative of a low-level neural locus of learning, recent research suggests that these same effects can be accounted for by changes in higher-level areas--in particular in the way higher-level areas read out information from lower-level areas in the service of highly practiced decisions. Here we contrast the degree of orientation transfer seen after training on two different tasks--vernier acuity and stereoacuity. Importantly, while the decision rule that could improve vernier acuity (i.e. a discriminant in the image plane) would not be transferable across orientations, the simplest rule that could be learned to solve the stereoacuity task (i.e. a discriminant in the depth plane) would be insensitive to changes in orientation. Thus, given a read-out hypothesis, more substantial transfer would be expected as a result of stereoacuity than vernier acuity training. To test this prediction, participants were trained (7500 total trials) on either a stereoacuity (N = 9) or vernier acuity (N = 7) task with the stimuli in either a vertical or horizontal configuration (balanced across participants). Following training, transfer to the untrained orientation was assessed. As predicted, evidence for relatively orientation specific learning was observed in vernier trained participants, while no evidence of specificity was observed in stereo trained participants. These results build upon the emerging view that perceptual learning (even very specific learning effects) may reflect changes in inferences made by high-level areas, rather than necessarily fully reflecting changes in the receptive field properties of low-level areas.

Efficiency in Rule- vs. Plan-Based Movements Is Modulated by Action-Mode

PubMed Central

Scheib, Jean P. P.; Stoll, Sarah; Thürmer, J. Lukas; Randerath, Jennifer

2018-01-01

The rule/plan motor cognition (RPMC) paradigm elicits visually indistinguishable motor outputs, resulting from either plan- or rule-based action-selection, using a combination of essentially interchangeable stimuli. Previous implementations of the RPMC paradigm have used pantomimed movements to compare plan- vs. rule-based action-selection. In the present work we attempt to determine the generalizability of previous RPMC findings to real object interaction by use of a grasp-to-rotate task. In the plan task, participants had to use prospective planning to achieve a comfortable post-handle rotation hand posture. The rule task used implementation intentions (if-then rules) leading to the same comfortable end-state. In Experiment A, we compare RPMC performance of 16 healthy participants in pantomime and real object conditions of the experiment, within-subjects. Higher processing efficiency of rule- vs. plan-based action-selection was supported by diffusion model analysis. Results show a significant response-time increase in the pantomime condition compared to the real object condition and a greater response-time advantage of rule-based vs. plan-based actions in the pantomime compared to the real object condition. In Experiment B, 24 healthy participants performed the real object RPMC task in a task switching vs. a blocked condition. Results indicate that plan-based action-selection leads to longer response-times and less efficient information processing than rule-based action-selection in line with previous RPMC findings derived from the pantomime action-mode. Particularly in the task switching mode, responses were faster in the rule compared to the plan task suggesting a modulating influence of cognitive load. Overall, results suggest an advantage of rule-based action-selection over plan-based action-selection; whereby differential mechanisms appear to be involved depending on the action-mode. We propose that cognitive load is a factor that modulates the advantageous effect of implementation intentions in motor cognition on different levels as illustrated by the varying speed advantages and the variation in diffusion parameters per action-mode or condition, respectively. PMID:29593612

Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences.

PubMed

Bhat, Ajaz Ahmad; Mohan, Vishwanathan; Sandini, Giulio; Morasso, Pietro

2016-07-01

Emerging studies indicate that several species such as corvids, apes and children solve 'The Crow and the Pitcher' task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause-effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended 'learning-prediction-abstraction' loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents. Results further demonstrate that by cumulatively interacting with few objects, the predictions of the robot in case of novel objects converge close to the physical law, i.e. the Archimedes principle: this being independent of both the objects explored during learning and the order of their cumulative exploration. © 2016 The Author(s).

Good times, bad times: how personal disadvantage moderates the relationship between social dominance and efforts to win.

PubMed

Cozzolino, Philip J; Snyder, Mark

2008-10-01

Recent work has linked social dominance orientation (SDO) to ruthless, uncaring individuals who see the world as a competitive jungle. This need to "rule the jungle," then, should become activated when high SDOs are in positions that threaten their chances of victory. In Study 1, the authors manipulated advantage and disadvantage in the form of resources; in an ensuing task, they observed higher levels of greed only among disadvantaged high SDOs. In Study 2, high SDOs with less opportunity to compete relative to others evidenced significantly more extra-effort to win, even though their effort broke the rules. In Study 3, the authors replicated this effect and demonstrated that extra-effort predicted increased beliefs in actual performance, which in turn predicted decisions to argue for a higher score. In sum, the results provide support for the notion of SDO reflecting underlying needs to compete and win at all costs.

Goal-Directed Decision Making with Spiking Neurons.

PubMed

Friedrich, Johannes; Lengyel, Máté

2016-02-03

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. Copyright © 2016 the authors 0270-6474/16/361529-18$15.00/0.

Goal-Directed Decision Making with Spiking Neurons

PubMed Central

Lengyel, Máté

2016-01-01

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. SIGNIFICANCE STATEMENT Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. PMID:26843636

Masked priming effect reflects evidence accumulated by the prime.

PubMed

Kinoshita, Sachiko; Norris, Dennis

2010-01-01

In the same-different match task, masked priming is observed with the same responses but not different responses. Norris and Kinoshita's (2008) Bayesian reader account of masked priming explains this pattern based on the same principle as that explaining the absence of priming for nonwords in the lexical decision task. The pattern of priming follows from the way the model makes optimal decisions in the two tasks; priming does not depend on first activating the prime and then the target. An alternative explanation is in terms of a bias towards responding "same" that exactly counters the facilitatory effect of lexical access. The present study tested these two views by varying both the degree to which the prime predicts the response and the visibility of the prime. Unmasked primes produced effects expected from the view that priming is influenced by the degree to which the prime predicts the response. In contrast, with masked primes, the size of priming for the same response was completely unaffected by predictability. These results rule out response bias as an explanation of the absence of masked priming for different responses and, in turn, indicate that masked priming is not a consequence of automatic lexical access of the prime.

Vietnamese children and language-based processing tasks.

PubMed

Hwa-Froelich, Deborah A; Matsuo, Hisako

2005-07-01

Vietnamese children's performance on language-based processing tasks of fast-mapping (FM) word-learning and dynamic assessment (DA) word- and rule-learning tasks were investigated. Twenty-one first- and second-generation Vietnamese preschool children participated in this study. All children were enrolled in 2 Head Start programs in a large city in the Midwest. All children had passed a developmental assessment and routine speech, language, and hearing screenings. All participants were taught 4 invented monosyllabic words in an FM word task, an invented monosyllabic suffix rule (-po) meaning "a part of" in a DA rule task, and 4 invented bisyllabic words in a DA word task. Potential relationships among task performances were investigated. Receptive task performances, expressive task performances, and task totals were added to create receptive total, expressive total, and accumulated performance total (APT) scores. Relationships among receptive total, expressive total, and APT scores were also investigated. Significant correlations were found between FM word, DA rule, and the receptive total. The expressive total correlated with all task total scores, APT, age, and modifiability scores. Modifiability scores correlated with the two DA tasks, expressive total, and the APT. Findings indicate that FM word and the expressive total were positively correlated with most of the other tasks, composite totals, and age. Performance on language-based processing tasks may provide valuable information for separating typically developing Vietnamese preschool children from their peers with language disorders. Practitioners should consider linguistic characteristics of target stimuli. Comparisons should include task, receptive, expressive, and APT.

Cue-type manipulation dissociates two types of task set inhibition: backward inhibition and competitor rule suppression.

PubMed

Regev, Shirley; Meiran, Nachshon

2016-07-01

Backward inhibition (BI) reflects the suppression of a recently abandoned task set to allow for smooth transition to a new task even when the rules do not generate a response conflict. Competitor rule suppression (CRS) reflects the inhibition/suppression of irrelevant task rules when these rules generate a response conflict even if they have not recently been abandoned. We assessed whether BI and CRS are differentially affected by the difficulty in retrieving category-response mappings from memory. Retrieval demands were manipulated via the information provided by the task cues, which either indicated the relevant dimension (dimension cues; "color") or the relevant dimension with its category-to-key mapping (mapping cues; "red green", indicating that "red" and "green" go with the left/right responses, respectively). CRS was larger with dimension compared to mapping cues when cue-type varied between groups and was larger after trials involving dimension cues when cue-type varied on a trial-by-trial basis. In contrast, BI was not influenced by cue-type. These results suggest that task switching involve at least two distinct inhibitory processes, with CRS being related to the ease of retrieval of category-response mappings from memory.

Age-Related Brain Activation Changes during Rule Repetition in Word-Matching.

PubMed

Methqal, Ikram; Pinsard, Basile; Amiri, Mahnoush; Wilson, Maximiliano A; Monchi, Oury; Provost, Jean-Sebastien; Joanette, Yves

2017-01-01

Objective: The purpose of this study was to explore the age-related brain activation changes during a word-matching semantic-category-based task, which required either repeating or changing a semantic rule to be applied. In order to do so, a word-semantic rule-based task was adapted from the Wisconsin Sorting Card Test, involving the repeated feedback-driven selection of given pairs of words based on semantic category-based criteria. Method: Forty healthy adults (20 younger and 20 older) performed a word-matching task while undergoing a fMRI scan in which they were required to pair a target word with another word from a group of three words. The required pairing is based on three word-pair semantic rules which correspond to different levels of semantic control demands: functional relatedness, moderately typical-relatedness (which were considered as low control demands), and atypical-relatedness (high control demands). The sorting period consisted of a continuous execution of the same sorting rule and an inferred trial-by-trial feedback was given. Results: Behavioral performance revealed increases in response times and decreases of correct responses according to the level of semantic control demands (functional vs. typical vs. atypical) for both age groups (younger and older) reflecting graded differences in the repetition of the application of a given semantic rule. Neuroimaging findings of significant brain activation showed two main results: (1) Greater task-related activation changes for the repetition of the application of atypical rules relative to typical and functional rules, and (2) Changes (older > younger) in the inferior prefrontal regions for functional rules and more extensive and bilateral activations for typical and atypical rules. Regarding the inter-semantic rules comparison, only task-related activation differences were observed for functional > typical (e.g., inferior parietal and temporal regions bilaterally) and atypical > typical (e.g., prefrontal, inferior parietal, posterior temporal, and subcortical regions). Conclusion: These results suggest that healthy cognitive aging relies on the adaptive changes of inferior prefrontal resources involved in the repetitive execution of semantic rules, thus reflecting graded differences in support of task demands.

Rule-violations sensitise towards negative and authority-related stimuli.

PubMed

Wirth, Robert; Foerster, Anna; Rendel, Hannah; Kunde, Wilfried; Pfister, Roland

2018-05-01

Rule violations have usually been studied from a third-person perspective, identifying situational factors that render violations more or less likely. A first-person perspective of the agent that actively violates the rules, on the other hand, is only just beginning to emerge. Here we show that committing a rule violation sensitises towards subsequent negative stimuli as well as subsequent authority-related stimuli. In a Prime-Probe design, we used an instructed rule-violation task as the Prime and a word categorisation task as the Probe. Also, we employed a control condition that used a rule inversion task as the Prime (instead of rule violations). Probe targets were categorised faster after a violation relative to after a rule-based response if they related to either, negative valence or authority. Inversions, however, primed only negative stimuli and did not accelerate the categorisation of authority-related stimuli. A heightened sensitivity towards authority-related targets thus seems to be specific to rule violations. A control experiment showed that these effects cannot be explained in terms of semantic priming. Therefore, we propose that rule violations necessarily activate authority-related representations that make rule violations qualitatively different from simple rule inversions.

Aggression, emotional self-regulation, attentional bias, and cognitive inhibition predict risky driving behavior.

PubMed

Sani, Susan Raouf Hadadi; Tabibi, Zahra; Fadardi, Javad Salehi; Stavrinos, Despina

2017-12-01

The present study explored whether aggression, emotional regulation, cognitive inhibition, and attentional bias towards emotional stimuli were related to risky driving behavior (driving errors, and driving violations). A total of 117 applicants for taxi driver positions (89% male, M age=36.59years, SD=9.39, age range 24-62years) participated in the study. Measures included the Ahwaz Aggression Inventory, the Difficulties in emotion regulation Questionnaire, the emotional Stroop task, the Go/No-go task, and the Driving Behavior Questionnaire. Correlation and regression analyses showed that aggression and emotional regulation predicted risky driving behavior. Difficulties in emotion regulation, the obstinacy and revengeful component of aggression, attentional bias toward emotional stimuli, and cognitive inhibition predicted driving errors. Aggression was the only significant predictive factor for driving violations. In conclusion, aggression and difficulties in regulating emotions may exacerbate risky driving behaviors. Deficits in cognitive inhibition and attentional bias toward negative emotional stimuli can increase driving errors. Predisposition to aggression has strong effect on making one vulnerable to violation of traffic rules and crashes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Brief Report: Impaired Flexible Item Selection Task (FIST) in School-Age Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Yerys, Benjamin E.; Wolff, Brian C.; Moody, Eric; Pennington, Bruce F.; Hepburn, Susan L.

2012-01-01

Cognitive flexibility has been measured with inductive reasoning or explicit rule tasks in individuals with autism spectrum disorders (ASD). The "Flexible Item Selection Task" (FIST) differs from previous cognitive flexibility tasks in ASD research by giving children an abstract, ambiguous rule to switch. The ASD group (N = 22; Mean age = 8.28…

Estimation of State Transition Probabilities: A Neural Network Model

NASA Astrophysics Data System (ADS)

Saito, Hiroshi; Takiyama, Ken; Okada, Masato

2015-12-01

Humans and animals can predict future states on the basis of acquired knowledge. This prediction of the state transition is important for choosing the best action, and the prediction is only possible if the state transition probability has already been learned. However, how our brains learn the state transition probability is unknown. Here, we propose a simple algorithm for estimating the state transition probability by utilizing the state prediction error. We analytically and numerically confirmed that our algorithm is able to learn the probability completely with an appropriate learning rate. Furthermore, our learning rule reproduced experimentally reported psychometric functions and neural activities in the lateral intraparietal area in a decision-making task. Thus, our algorithm might describe the manner in which our brains learn state transition probabilities and predict future states.

International Space Station Noise Constraints Flight Rule Process

NASA Technical Reports Server (NTRS)

Limardo, Jose G.; Allen, Christopher S.; Danielson, Richard W.

2014-01-01

Crewmembers onboard the International Space Station (ISS) live in a unique workplace environment for as long as 6 -12 months. During these long-duration ISS missions, noise exposures from onboard equipment are posing concerns for human factors and crewmember health risks, such as possible reductions in hearing sensitivity, disruptions of crew sleep, interference with speech intelligibility and voice communications, interference with crew task performance, and reduced alarm audibility. The purpose of this poster is to describe how a recently-updated noise constraints flight rule is being used to implement a NASA-created Noise Exposure Estimation Tool and Noise Hazard Inventory to predict crew noise exposures and recommend when hearing protection devices are needed.

Motor command inhibition and the representation of response mode during motor imagery.

PubMed

Scheil, Juliane; Liefooghe, Baptist

2018-05-01

Research on motor imagery proposes that overt actions during motor imagery can be avoided by proactively signaling subthreshold motor commands to the effectors and by invoking motor-command inhibition. A recent study by Rieger, Dahm, and Koch (2017) found evidence in support of motor command inhibition, which indicates that MI cannot be completed on the sole basis of subthreshold motor commands. However, during motor imagery, participants know in advance when a covert response is to be made and it is thus surprising such additional motor-command inhibition is needed. Accordingly, the present study tested whether the demand to perform an action covertly can be proactively integrated by investigating the formation of task-specific action rules during motor imagery. These task-specific action rules relate the decision rules of a task to the mode in which these rules need to be applied (e.g., if smaller than 5, press the left key covertly). To this end, an experiment was designed in which participants had to switch between two numerical judgement tasks and two response modes: covert responding and overt responding. First, we observed markers of motor command inhibition and replicated the findings of Rieger and colleagues. Second, we observed evidence suggesting that task-specific action rules are created for the overt response mode (e.g., if smaller than 5, press the left key). In contrast, for the covert response mode, no task-specific action rules are formed and decision rules do not include mode-specific information (e.g., if smaller than 5, left). Copyright © 2018 Elsevier B.V. All rights reserved.

Shared internal models for feedforward and feedback control.

PubMed

Wagner, Mark J; Smith, Maurice A

2008-10-15

A child often learns to ride a bicycle in the driveway, free of unforeseen obstacles. Yet when she first rides in the street, we hope that if a car suddenly pulls out in front of her, she will combine her innate goal of avoiding an accident with her learned knowledge of the bicycle, and steer away or brake. In general, when we train to perform a new motor task, our learning is most robust if it updates the rules of online error correction to reflect the rules and goals of the new task. Here we provide direct evidence that, after a new feedforward motor adaptation, motor feedback responses to unanticipated errors become precisely task appropriate, even when such errors were never experienced during training. To study this ability, we asked how, if at all, do online responses to occasional, unanticipated force pulses during reaching arm movements change after adapting to altered arm dynamics? Specifically, do they change in a task-appropriate manner? In our task, subjects learned novel velocity-dependent dynamics. However, occasional force-pulse perturbations produced unanticipated changes in velocity. Therefore, after adaptation, task-appropriate responses to unanticipated pulses should compensate corresponding changes in velocity-dependent dynamics. We found that after adaptation, pulse responses precisely compensated these changes, although they were never trained to do so. These results provide evidence for a smart feedback controller which automatically produces responses specific to the learned dynamics of the current task. To accomplish this, the neural processes underlying feedback control must (1) be capable of accurate real-time state prediction for velocity via a forward model and (2) have access to recently learned changes in internal models of limb dynamics.

Anticipatory Regulation of Action Control in a Simon Task: Behavioral, Electrophysiological, and fMRI Correlates

PubMed Central

Strack, Gamze; Kaufmann, Christian; Kehrer, Stefanie; Brandt, Stephan; Stürmer, Birgit

2013-01-01

With the present study we investigated cue-induced preparation in a Simon task and measured electroencephalogram and functional magnetic resonance imaging (fMRI) data in two within-subjects sessions. Cues informed either about the upcoming (1) spatial stimulus-response compatibility (rule cues), or (2) the stimulus location (position cues), or (3) were non-informative. Only rule cues allowed anticipating the upcoming compatibility condition. Position cues allowed anticipation of the upcoming location of the Simon stimulus but not its compatibility condition. Rule cues elicited fastest and most accurate performance for both compatible and incompatible trials. The contingent negative variation (CNV) in the event-related potential (ERP) of the cue-target interval is an index of anticipatory preparation and was magnified after rule cues. The N2 in the post-target ERP as a measure of online action control was reduced in Simon trials after rule cues. Although compatible trials were faster than incompatible trials in all cue conditions only non-informative cues revealed a compatibility effect in additional indicators of Simon task conflict like accuracy and the N2. We thus conclude that rule cues induced anticipatory re-coding of the Simon task that did not involve cognitive conflict anymore. fMRI revealed that rule cues yielded more activation of the left rostral, dorsal, and ventral prefrontal cortex as well as the pre-SMA as compared to POS and NON-cues. Pre-SMA and ventrolateral prefrontal activation after rule cues correlated with the effective use of rule cues in behavioral performance. Position cues induced a smaller CNV effect and exhibited less prefrontal and pre-SMA contributions in fMRI. Our data point to the importance to disentangle different anticipatory adjustments that might also include the prevention of upcoming conflict via task re-coding. PMID:23408377

Differential impact of relevant and irrelevant dimension primes on rule-based and information-integration category learning.

PubMed

Grimm, Lisa R; Maddox, W Todd

2013-11-01

Research has identified multiple category-learning systems with each being "tuned" for learning categories with different task demands and each governed by different neurobiological systems. Rule-based (RB) classification involves testing verbalizable rules for category membership while information-integration (II) classification requires the implicit learning of stimulus-response mappings. In the first study to directly test rule priming with RB and II category learning, we investigated the influence of the availability of information presented at the beginning of the task. Participants viewed lines that varied in length, orientation, and position on the screen, and were primed to focus on stimulus dimensions that were relevant or irrelevant to the correct classification rule. In Experiment 1, we used an RB category structure, and in Experiment 2, we used an II category structure. Accuracy and model-based analyses suggested that a focus on relevant dimensions improves RB task performance later in learning while a focus on an irrelevant dimension improves II task performance early in learning. © 2013.

Schizotypy and Performance on an Insight Problem-Solving Task: The Contribution of Persecutory Ideation.

PubMed

Cosgrave, Jan; Haines, Ross; Golodetz, Stuart; Claridge, Gordon; Wulff, Katharina; van Heugten-van der Kloet, Dalena

2018-01-01

Insight problem solving is thought to underpin creative thought as it incorporates both divergent (generating multiple ideas and solutions) and convergent (arriving at the optimal solution) thinking approaches. The current literature on schizotypy and creativity is mixed and requires clarification. An alternate approach was employed by designing an exploratory web-based study using only correlates of schizotypal traits (paranoia, dissociation, cognitive failures, fantasy proneness, and unusual sleep experiences) and examining which (if any) predicted optimal performance on an insight problem-solving task. One hundred and twenty-one participants were recruited online from the general population and completed the number reduction task. The discovery of the hidden rule (HR) was used as a measure of insight. Multivariate logistic regression analyses highlighted persecutory ideation to best predict the discovery of the HR (OR = 1.05; 95% CI 1.01-1.10, p = 0.017), with a one-point increase in persecutory ideas corresponding to the participant being 5% more likely to discover the HR. This result suggests that persecutory ideation, above other schizotypy correlates, may be involved in insight problem solving.

Contributions of Lateral and Orbital Frontal Regions to Abstract Rule Acquisition and Reversal in Monkeys

PubMed Central

La Camera, Giancarlo; Bouret, Sebastien; Richmond, Barry J.

2018-01-01

The ability to learn and follow abstract rules relies on intact prefrontal regions including the lateral prefrontal cortex (LPFC) and the orbitofrontal cortex (OFC). Here, we investigate the specific roles of these brain regions in learning rules that depend critically on the formation of abstract concepts as opposed to simpler input-output associations. To this aim, we tested monkeys with bilateral removals of either LPFC or OFC on a rapidly learned task requiring the formation of the abstract concept of same vs. different. While monkeys with OFC removals were significantly slower than controls at both acquiring and reversing the concept-based rule, monkeys with LPFC removals were not impaired in acquiring the task, but were significantly slower at rule reversal. Neither group was impaired in the acquisition or reversal of a delayed visual cue-outcome association task without a concept-based rule. These results suggest that OFC is essential for the implementation of a concept-based rule, whereas LPFC seems essential for its modification once established. PMID:29615854

Flankers Facilitate 3-Year-Olds' Performance in a Card-Sorting Task

ERIC Educational Resources Information Center

Jordan, Patricia L.; Morton, J. Bruce

2008-01-01

Three-year-old children often act inflexibly in card-sorting tasks by continuing to sort by an old rule after being asked to switch and sort by a new rule. This inflexibility has been variously attributed to age-related constraints on higher order rule use, object redescription, and attention shifting. In 2 experiments, flankers that were…

Learning and transfer of category knowledge in an indirect categorization task.

PubMed

Helie, Sebastien; Ashby, F Gregory

2012-05-01

Knowledge representations acquired during category learning experiments are 'tuned' to the task goal. A useful paradigm to study category representations is indirect category learning. In the present article, we propose a new indirect categorization task called the "same"-"different" categorization task. The same-different categorization task is a regular same-different task, but the question asked to the participants is about the stimulus category membership instead of stimulus identity. Experiment 1 explores the possibility of indirectly learning rule-based and information-integration category structures using the new paradigm. The results suggest that there is little learning about the category structures resulting from an indirect categorization task unless the categories can be separated by a one-dimensional rule. Experiment 2 explores whether a category representation learned indirectly can be used in a direct classification task (and vice versa). The results suggest that previous categorical knowledge acquired during a direct classification task can be expressed in the same-different categorization task only when the categories can be separated by a rule that is easily verbalized. Implications of these results for categorization research are discussed.

Integrating machine learning and physician knowledge to improve the accuracy of breast biopsy.

PubMed

Dutra, I; Nassif, H; Page, D; Shavlik, J; Strigel, R M; Wu, Y; Elezaby, M E; Burnside, E

2011-01-01

In this work we show that combining physician rules and machine learned rules may improve the performance of a classifier that predicts whether a breast cancer is missed on percutaneous, image-guided breast core needle biopsy (subsequently referred to as "breast core biopsy"). Specifically, we show how advice in the form of logical rules, derived by a sub-specialty, i.e. fellowship trained breast radiologists (subsequently referred to as "our physicians") can guide the search in an inductive logic programming system, and improve the performance of a learned classifier. Our dataset of 890 consecutive benign breast core biopsy results along with corresponding mammographic findings contains 94 cases that were deemed non-definitive by a multidisciplinary panel of physicians, from which 15 were upgraded to malignant disease at surgery. Our goal is to predict upgrade prospectively and avoid surgery in women who do not have breast cancer. Our results, some of which trended toward significance, show evidence that inductive logic programming may produce better results for this task than traditional propositional algorithms with default parameters. Moreover, we show that adding knowledge from our physicians into the learning process may improve the performance of the learned classifier trained only on data.

Choosing the Rules: Distinct and Overlapping Frontoparietal Representations of Task Rules for Perceptual Decisions

PubMed Central

Kriegeskorte, Nikolaus; Carlin, Johan D.; Rowe, James B.

2013-01-01

Behavior is governed by rules that associate stimuli with responses and outcomes. Human and monkey studies have shown that rule-specific information is widely represented in the frontoparietal cortex. However, it is not known how establishing a rule under different contexts affects its neural representation. Here, we use event-related functional MRI (fMRI) and multivoxel pattern classification methods to investigate the human brain's mechanisms of establishing and maintaining rules for multiple perceptual decision tasks. Rules were either chosen by participants or specifically instructed to them, and the fMRI activation patterns representing rule-specific information were compared between these contexts. We show that frontoparietal regions differ in the properties of their rule representations during active maintenance before execution. First, rule-specific information maintained in the dorsolateral and medial frontal cortex depends on the context in which it was established (chosen vs specified). Second, rule representations maintained in the ventrolateral frontal and parietal cortex are independent of the context in which they were established. Furthermore, we found that the rule-specific coding maintained in anticipation of stimuli may change with execution of the rule: representations in context-independent regions remain invariant from maintenance to execution stages, whereas rule representations in context-dependent regions do not generalize to execution stage. The identification of distinct frontoparietal systems with context-independent and context-dependent task rule representations, and the distinction between anticipatory and executive rule representations, provide new insights into the functional architecture of goal-directed behavior. PMID:23864675

Cognitive control over learning: Creating, clustering and generalizing task-set structure

PubMed Central

Collins, Anne G.E.; Frank, Michael J.

2013-01-01

Executive functions and learning share common neural substrates essential for their expression, notably in prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning, but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for cognitive control. We investigate this question from three complementary angles. First, we develop a new computational “C-TS” (context-task-set) model inspired by non-parametric Bayesian methods, specifying how the learner might infer hidden structure and decide whether to re-use that structure in new situations, or to create new structure. Second, we develop a neurobiologically explicit model to assess potential mechanisms of such interactive structured learning in multiple circuits linking frontal cortex and basal ganglia. We systematically explore the link betweens these levels of modeling across multiple task demands. We find that the network provides an approximate implementation of high level C-TS computations, where manipulations of specific neural mechanisms are well captured by variations in distinct C-TS parameters. Third, this synergism across models yields strong predictions about the nature of human optimal and suboptimal choices and response times during learning. In particular, the models suggest that participants spontaneously build task-set structure into a learning problem when not cued to do so, which predicts positive and negative transfer in subsequent generalization tests. We provide evidence for these predictions in two experiments and show that the C-TS model provides a good quantitative fit to human sequences of choices in this task. These findings implicate a strong tendency to interactively engage cognitive control and learning, resulting in structured abstract representations that afford generalization opportunities, and thus potentially long-term rather than short-term optimality. PMID:23356780

Coactivation of cognitive control networks during task switching.

PubMed

Yin, Shouhang; Deák, Gedeon; Chen, Antao

2018-01-01

The ability to flexibly switch between tasks is considered an important component of cognitive control that involves frontal and parietal cortical areas. The present study was designed to characterize network dynamics across multiple brain regions during task switching. Functional magnetic resonance images (fMRI) were captured during a standard rule-switching task to identify switching-related brain regions. Multiregional psychophysiological interaction (PPI) analysis was used to examine effective connectivity between these regions. During switching trials, behavioral performance declined and activation of a generic cognitive control network increased. Concurrently, task-related connectivity increased within and between cingulo-opercular and fronto-parietal cognitive control networks. Notably, the left inferior frontal junction (IFJ) was most consistently coactivated with the 2 cognitive control networks. Furthermore, switching-dependent effective connectivity was negatively correlated with behavioral switch costs. The strength of effective connectivity between left IFJ and other regions in the networks predicted individual differences in switch costs. Task switching was supported by coactivated connections within cognitive control networks, with left IFJ potentially acting as a key hub between the fronto-parietal and cingulo-opercular networks. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The evolutionary basis of human social learning

PubMed Central

Morgan, T. J. H.; Rendell, L. E.; Ehn, M.; Hoppitt, W.; Laland, K. N.

2012-01-01

Humans are characterized by an extreme dependence on culturally transmitted information. Such dependence requires the complex integration of social and asocial information to generate effective learning and decision making. Recent formal theory predicts that natural selection should favour adaptive learning strategies, but relevant empirical work is scarce and rarely examines multiple strategies or tasks. We tested nine hypotheses derived from theoretical models, running a series of experiments investigating factors affecting when and how humans use social information, and whether such behaviour is adaptive, across several computer-based tasks. The number of demonstrators, consensus among demonstrators, confidence of subjects, task difficulty, number of sessions, cost of asocial learning, subject performance and demonstrator performance all influenced subjects' use of social information, and did so adaptively. Our analysis provides strong support for the hypothesis that human social learning is regulated by adaptive learning rules. PMID:21795267

The evolutionary basis of human social learning.

PubMed

Morgan, T J H; Rendell, L E; Ehn, M; Hoppitt, W; Laland, K N

2012-02-22

Humans are characterized by an extreme dependence on culturally transmitted information. Such dependence requires the complex integration of social and asocial information to generate effective learning and decision making. Recent formal theory predicts that natural selection should favour adaptive learning strategies, but relevant empirical work is scarce and rarely examines multiple strategies or tasks. We tested nine hypotheses derived from theoretical models, running a series of experiments investigating factors affecting when and how humans use social information, and whether such behaviour is adaptive, across several computer-based tasks. The number of demonstrators, consensus among demonstrators, confidence of subjects, task difficulty, number of sessions, cost of asocial learning, subject performance and demonstrator performance all influenced subjects' use of social information, and did so adaptively. Our analysis provides strong support for the hypothesis that human social learning is regulated by adaptive learning rules.

Transfer between local and global processing levels by pigeons (Columba livia) and humans (Homo sapiens) in exemplar- and rule-based categorization tasks.

PubMed

Aust, Ulrike; Braunöder, Elisabeth

2015-02-01

The present experiment investigated pigeons' and humans' processing styles-local or global-in an exemplar-based visual categorization task in which category membership of every stimulus had to be learned individually, and in a rule-based task in which category membership was defined by a perceptual rule. Group Intact was trained with the original pictures (providing both intact local and global information), Group Scrambled was trained with scrambled versions of the same pictures (impairing global information), and Group Blurred was trained with blurred versions (impairing local information). Subsequently, all subjects were tested for transfer to the 2 untrained presentation modes. Humans outperformed pigeons regarding learning speed and accuracy as well as transfer performance and showed good learning irrespective of group assignment, whereas the pigeons of Group Blurred needed longer to learn the training tasks than the pigeons of Groups Intact and Scrambled. Also, whereas humans generalized equally well to any novel presentation mode, pigeons' transfer from and to blurred stimuli was impaired. Both species showed faster learning and, for the most part, better transfer in the rule-based than in the exemplar-based task, but there was no evidence of the used processing mode depending on the type of task (exemplar- or rule-based). Whereas pigeons relied on local information throughout, humans did not show a preference for either processing level. Additional tests with grayscale versions of the training stimuli, with versions that were both blurred and scrambled, and with novel instances of the rule-based task confirmed and further extended these findings. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences

PubMed Central

2016-01-01

Emerging studies indicate that several species such as corvids, apes and children solve ‘The Crow and the Pitcher’ task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause–effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended ‘learning–prediction–abstraction’ loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents. Results further demonstrate that by cumulatively interacting with few objects, the predictions of the robot in case of novel objects converge close to the physical law, i.e. the Archimedes principle: this being independent of both the objects explored during learning and the order of their cumulative exploration. PMID:27466440

Connectivity patterns in cognitive control networks predict naturalistic multitasking ability.

PubMed

Wen, Tanya; Liu, De-Cyuan; Hsieh, Shulan

2018-06-01

Multitasking is a fundamental aspect of everyday life activities. To achieve a complex, multi-component goal, the tasks must be subdivided into sub-tasks and component steps, a critical function of prefrontal networks. The prefrontal cortex is considered to be organized in a cascade of executive processes from the sensorimotor to anterior prefrontal cortex, which includes execution of specific goal-directed action, to encoding and maintaining task rules, and finally monitoring distal goals. In the current study, we used a virtual multitasking paradigm to tap into real-world performance and relate it to each individual's resting-state functional connectivity in fMRI. While did not find any correlation between global connectivity of any of the major networks with multitasking ability, global connectivity of the lateral prefrontal cortex (LPFC) was predictive of multitasking ability. Further analysis showed that multivariate connectivity patterns within the sensorimotor network (SMN), and between-network connectivity of the frontoparietal network (FPN) and dorsal attention network (DAN), predicted individual multitasking ability and could be generalized to novel individuals. Together, these results support previous research that prefrontal networks underlie multitasking abilities and show that connectivity patterns in the cascade of prefrontal networks may explain individual differences in performance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Automatic identification of variables in epidemiological datasets using logic regression.

PubMed

Lorenz, Matthias W; Abdi, Negin Ashtiani; Scheckenbach, Frank; Pflug, Anja; Bülbül, Alpaslan; Catapano, Alberico L; Agewall, Stefan; Ezhov, Marat; Bots, Michiel L; Kiechl, Stefan; Orth, Andreas

2017-04-13

For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.

How Can Students Generalize the Chain Rule? The Roles of Abduction in Mathematical Modeling

ERIC Educational Resources Information Center

Park, Jin Hyeong; Lee, Kyeong-Hwa

2016-01-01

The purpose of this study is to design a modeling task to facilitate students' inquiries into the chain rule in calculus and to analyze the results after implementation of the task. In this study, we take a modeling approach to the teaching and learning of the chain rule by facilitating the generalization of students' models and modeling…

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

PubMed

Chen, Antao; Li, Hong; Feng, Tingyong; Gao, Xuemei; Zhang, Zhongming; Li, Fuhong; Yang, Dong

2005-12-01

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.

Brain negativity as an indicator of predictive error processing: the contribution of visual action effect monitoring.

PubMed

Joch, Michael; Hegele, Mathias; Maurer, Heiko; Müller, Hermann; Maurer, Lisa Katharina

2017-07-01

The error (related) negativity (Ne/ERN) is an event-related potential in the electroencephalogram (EEG) correlating with error processing. Its conditions of appearance before terminal external error information suggest that the Ne/ERN is indicative of predictive processes in the evaluation of errors. The aim of the present study was to specifically examine the Ne/ERN in a complex motor task and to particularly rule out other explaining sources of the Ne/ERN aside from error prediction processes. To this end, we focused on the dependency of the Ne/ERN on visual monitoring about the action outcome after movement termination but before result feedback (action effect monitoring). Participants performed a semi-virtual throwing task by using a manipulandum to throw a virtual ball displayed on a computer screen to hit a target object. Visual feedback about the ball flying to the target was masked to prevent action effect monitoring. Participants received a static feedback about the action outcome (850 ms) after each trial. We found a significant negative deflection in the average EEG curves of the error trials peaking at ~250 ms after ball release, i.e., before error feedback. Furthermore, this Ne/ERN signal did not depend on visual ball-flight monitoring after release. We conclude that the Ne/ERN has the potential to indicate error prediction in motor tasks and that it exists even in the absence of action effect monitoring. NEW & NOTEWORTHY In this study, we are separating different kinds of possible contributors to an electroencephalogram (EEG) error correlate (Ne/ERN) in a throwing task. We tested the influence of action effect monitoring on the Ne/ERN amplitude in the EEG. We used a task that allows us to restrict movement correction and action effect monitoring and to control the onset of result feedback. We ascribe the Ne/ERN to predictive error processing where a conscious feeling of failure is not a prerequisite. Copyright © 2017 the American Physiological Society.

Automating CPM-GOMS

NASA Technical Reports Server (NTRS)

John, Bonnie; Vera, Alonso; Matessa, Michael; Freed, Michael; Remington, Roger

2002-01-01

CPM-GOMS is a modeling method that combines the task decomposition of a GOMS analysis with a model of human resource usage at the level of cognitive, perceptual, and motor operations. CPM-GOMS models have made accurate predictions about skilled user behavior in routine tasks, but developing such models is tedious and error-prone. We describe a process for automatically generating CPM-GOMS models from a hierarchical task decomposition expressed in a cognitive modeling tool called Apex. Resource scheduling in Apex automates the difficult task of interleaving the cognitive, perceptual, and motor resources underlying common task operators (e.g. mouse move-and-click). Apex's UI automatically generates PERT charts, which allow modelers to visualize a model's complex parallel behavior. Because interleaving and visualization is now automated, it is feasible to construct arbitrarily long sequences of behavior. To demonstrate the process, we present a model of automated teller interactions in Apex and discuss implications for user modeling. available to model human users, the Goals, Operators, Methods, and Selection (GOMS) method [6, 21] has been the most widely used, providing accurate, often zero-parameter, predictions of the routine performance of skilled users in a wide range of procedural tasks [6, 13, 15, 27, 28]. GOMS is meant to model routine behavior. The user is assumed to have methods that apply sequences of operators and to achieve a goal. Selection rules are applied when there is more than one method to achieve a goal. Many routine tasks lend themselves well to such decomposition. Decomposition produces a representation of the task as a set of nested goal states that include an initial state and a final state. The iterative decomposition into goals and nested subgoals can terminate in primitives of any desired granularity, the choice of level of detail dependent on the predictions required. Although GOMS has proven useful in HCI, tools to support the construction of GOMS models have not yet come into general use.

Win-stay and win-shift lever-press strategies in an appetitively reinforced task for rats.

PubMed

Reed, Phil

2016-12-01

Two experiments examined acquisition of win-stay, win-shift, lose-stay, and lose-shift rules by which hungry rats could earn food reinforcement. In Experiment 1, two groups of rats were trained in a two-lever operant task that required them to follow either a win-stay/lose-shift or a win-shift/lose-stay contingency. The rates of acquisition of the individual rules within each contingency differed: lose-shift and lose-stay rules were acquired faster than win-stay and win-shift rules. Contrary to a number of previous reports, the win-shift rule was acquired less rapidly than any of the other rules. In Experiment 2, the four rules were taught separately, but subjects still acquired the win-shift rule more slowly than any of the other rules.

Neural underpinnings of divergent production of rules in numerical analogical reasoning.

PubMed

Wu, Xiaofei; Jung, Rex E; Zhang, Hao

2016-05-01

Creativity plays an important role in numerical problem solving. Although the neural underpinnings of creativity have been studied over decades, very little is known about neural mechanisms of the creative process that relates to numerical problem solving. In the present study, we employed a numerical analogical reasoning task with functional Magnetic Resonance Imaging (fMRI) to investigate the neural correlates of divergent production of rules in numerical analogical reasoning. Participants performed two tasks: a multiple solution analogical reasoning task and a single solution analogical reasoning task. Results revealed that divergent production of rules involves significant activations at Brodmann area (BA) 10 in the right middle frontal cortex, BA 40 in the left inferior parietal lobule, and BA 8 in the superior frontal cortex. The results suggest that right BA 10 and left BA 40 are involved in the generation of novel rules, and BA 8 is associated with the inhibition of initial rules in numerical analogical reasoning. The findings shed light on the neural mechanisms of creativity in numerical processing. Copyright © 2016 Elsevier B.V. All rights reserved.

How do pre-adolescent children interpret conditionals?

PubMed

Markovits, Henry; Brisson, Janie; de Chantal, Pier-Luc

2016-12-01

Studies examining children's basic understanding of conditionals have led to very different conclusions. On the one hand, conditional inference tasks suggest that young children are able to interpret familiar conditionals in a complex manner. In contrast, truth-table tasks suggest that before adolescence, children have limited (conjunctive) representations of conditionals. We hypothesized that the latter results are due to use of what are essentially arbitrary conditionals. To examine this, we gave a truth-table task using two kinds of conditional rules, Arbitrary and Imaginary categorical rules (If an animal is a bori, then it has red wings) to 9- and 12-year-olds. Results with the Arbitrary rules were consistent with those found in previous studies, with the most frequent interpretation being the Conjunctive one. However, among even the youngest children, the most frequent interpretation of the Imaginary categorical rules was the defective conditional, which is only found with much older adolescents with Arbitrary rules. These results suggest that working memory limitations are not an important developmental factor in how young children interpret conditional rules.

Breaking the Rules: Do Infants Have a True Understanding of False Belief?

ERIC Educational Resources Information Center

Yott, Jessica; Poulin-Dubois, Diane

2012-01-01

It has been suggested that infants' performance on the false belief task can be explained by the use of behavioural rules. To test this hypothesis, 18-month-old infants were trained to learn the new rule that an object that disappeared in location A could be found in location B. Infants were then administered a false belief task based on the…

Orientation Transfer in Vernier and Stereoacuity Training

PubMed Central

Snell, Nathaniel; Kattner, Florian; Rokers, Bas; Green, C. Shawn

2015-01-01

Human performance on various visual tasks can be improved substantially via training. However, the enhancements are frequently specific to relatively low-level stimulus dimensions. While such specificity has often been thought to be indicative of a low-level neural locus of learning, recent research suggests that these same effects can be accounted for by changes in higher-level areas–in particular in the way higher-level areas read out information from lower-level areas in the service of highly practiced decisions. Here we contrast the degree of orientation transfer seen after training on two different tasks—vernier acuity and stereoacuity. Importantly, while the decision rule that could improve vernier acuity (i.e. a discriminant in the image plane) would not be transferable across orientations, the simplest rule that could be learned to solve the stereoacuity task (i.e. a discriminant in the depth plane) would be insensitive to changes in orientation. Thus, given a read-out hypothesis, more substantial transfer would be expected as a result of stereoacuity than vernier acuity training. To test this prediction, participants were trained (7500 total trials) on either a stereoacuity (N = 9) or vernier acuity (N = 7) task with the stimuli in either a vertical or horizontal configuration (balanced across participants). Following training, transfer to the untrained orientation was assessed. As predicted, evidence for relatively orientation specific learning was observed in vernier trained participants, while no evidence of specificity was observed in stereo trained participants. These results build upon the emerging view that perceptual learning (even very specific learning effects) may reflect changes in inferences made by high-level areas, rather than necessarily fully reflecting changes in the receptive field properties of low-level areas. PMID:26700311

Individual differences in learning and transfer: stable tendencies for learning exemplars versus abstracting rules.

PubMed

McDaniel, Mark A; Cahill, Michael J; Robbins, Mathew; Wiener, Chelsea

2014-04-01

We hypothesize that during training some learners may focus on acquiring the particular exemplars and responses associated with the exemplars (termed exemplar learners), whereas other learners attempt to abstract underlying regularities reflected in the particular exemplars linked to an appropriate response (termed rule learners). Supporting this distinction, after training (on a function-learning task), participants displayed an extrapolation profile reflecting either acquisition of the trained cue-criterion associations (exemplar learners) or abstraction of the function rule (rule learners; Studies 1a and 1b). Further, working memory capacity (measured by operation span [Ospan]) was associated with the tendency to rely on rule versus exemplar processes. Studies 1c and 2 examined the persistence of these learning tendencies on several categorization tasks. Study 1c showed that rule learners were more likely than exemplar learners (indexed a priori by extrapolation profiles) to resist using idiosyncratic features (exemplar similarity) in generalization (transfer) of the trained category. Study 2 showed that the rule learners but not the exemplar learners performed well on a novel categorization task (transfer) after training on an abstract coherent category. These patterns suggest that in complex conceptual tasks, (a) individuals tend to either focus on exemplars during learning or on extracting some abstraction of the concept, (b) this tendency might be a relatively stable characteristic of the individual, and (c) transfer patterns are determined by that tendency.

Individual Differences in Learning and Transfer: Stable Tendencies for Learning Exemplars versus Abstracting Rules

PubMed Central

McDaniel, Mark A.; Cahill, Michael J.; Robbins, Mathew; Wiener, Chelsea

2013-01-01

We hypothesize that during training some learners may focus on acquiring the particular exemplars and responses associated with the exemplars (termed exemplar learners), whereas other learners attempt to abstract underlying regularities reflected in the particular exemplars linked to an appropriate response (termed rule learners). Supporting this distinction, after training (on a function-learning task), participants either displayed an extrapolation profile reflecting acquisition of the trained cue-criterion associations (exemplar learners) or abstraction of the function rule (rule learners; Studies 1a and 1b). Further, working memory capacity (measured by Ospan) was associated with the tendency to rely on rule versus exemplar processes. Studies 1c and 2 examined the persistence of these learning tendencies on several categorization tasks. Study 1c showed that rule learners were more likely than exemplar learners (indexed a priori by extrapolation profiles) to resist using idiosyncratic features (exemplar similarity) in generalization (transfer) of the trained category. Study 2 showed that the rule learners but not the exemplar learners performed well on a novel categorization task (transfer) after training on an abstract coherent category. These patterns suggest that in complex conceptual tasks, (a) individuals tend to either focus on exemplars during learning or on extracting some abstraction of the concept, (b) this tendency might be a relatively stable characteristic of the individual, and (c) transfer patterns are determined by that tendency. PMID:23750912

Reinforcement Learning of Linking and Tracing Contours in Recurrent Neural Networks

PubMed Central

Brosch, Tobias; Neumann, Heiko; Roelfsema, Pieter R.

2015-01-01

The processing of a visual stimulus can be subdivided into a number of stages. Upon stimulus presentation there is an early phase of feedforward processing where the visual information is propagated from lower to higher visual areas for the extraction of basic and complex stimulus features. This is followed by a later phase where horizontal connections within areas and feedback connections from higher areas back to lower areas come into play. In this later phase, image elements that are behaviorally relevant are grouped by Gestalt grouping rules and are labeled in the cortex with enhanced neuronal activity (object-based attention in psychology). Recent neurophysiological studies revealed that reward-based learning influences these recurrent grouping processes, but it is not well understood how rewards train recurrent circuits for perceptual organization. This paper examines the mechanisms for reward-based learning of new grouping rules. We derive a learning rule that can explain how rewards influence the information flow through feedforward, horizontal and feedback connections. We illustrate the efficiency with two tasks that have been used to study the neuronal correlates of perceptual organization in early visual cortex. The first task is called contour-integration and demands the integration of collinear contour elements into an elongated curve. We show how reward-based learning causes an enhancement of the representation of the to-be-grouped elements at early levels of a recurrent neural network, just as is observed in the visual cortex of monkeys. The second task is curve-tracing where the aim is to determine the endpoint of an elongated curve composed of connected image elements. If trained with the new learning rule, neural networks learn to propagate enhanced activity over the curve, in accordance with neurophysiological data. We close the paper with a number of model predictions that can be tested in future neurophysiological and computational studies. PMID:26496502

Syntactic Recursion Facilitates and Working Memory Predicts Recursive Theory of Mind

PubMed Central

Arslan, Burcu; Hohenberger, Annette; Verbrugge, Rineke

2017-01-01

In this study, we focus on the possible roles of second-order syntactic recursion and working memory in terms of simple and complex span tasks in the development of second-order false belief reasoning. We tested 89 Turkish children in two age groups, one younger (4;6–6;5 years) and one older (6;7–8;10 years). Although second-order syntactic recursion is significantly correlated with the second-order false belief task, results of ordinal logistic regressions revealed that the main predictor of second-order false belief reasoning is complex working memory span. Unlike simple working memory and second-order syntactic recursion tasks, the complex working memory task required processing information serially with additional reasoning demands that require complex working memory strategies. Based on our results, we propose that children’s second-order theory of mind develops when they have efficient reasoning rules to process embedded beliefs serially, thus overcoming a possible serial processing bottleneck. PMID:28072823

Predicting the threshold of pulse-train electrical stimuli using a stochastic auditory nerve model: the effects of stimulus noise.

PubMed

Xu, Yifang; Collins, Leslie M

2004-04-01

The incorporation of low levels of noise into an electrical stimulus has been shown to improve auditory thresholds in some human subjects (Zeng et al., 2000). In this paper, thresholds for noise-modulated pulse-train stimuli are predicted utilizing a stochastic neural-behavioral model of ensemble fiber responses to bi-phasic stimuli. The neural refractory effect is described using a Markov model for a noise-free pulse-train stimulus and a closed-form solution for the steady-state neural response is provided. For noise-modulated pulse-train stimuli, a recursive method using the conditional probability is utilized to track the neural responses to each successive pulse. A neural spike count rule has been presented for both threshold and intensity discrimination under the assumption that auditory perception occurs via integration over a relatively long time period (Bruce et al., 1999). An alternative approach originates from the hypothesis of the multilook model (Viemeister and Wakefield, 1991), which argues that auditory perception is based on several shorter time integrations and may suggest an NofM model for prediction of pulse-train threshold. This motivates analyzing the neural response to each individual pulse within a pulse train, which is considered to be the brief look. A logarithmic rule is hypothesized for pulse-train threshold. Predictions from the multilook model are shown to match trends in psychophysical data for noise-free stimuli that are not always matched by the long-time integration rule. Theoretical predictions indicate that threshold decreases as noise variance increases. Theoretical models of the neural response to pulse-train stimuli not only reduce calculational overhead but also facilitate utilization of signal detection theory and are easily extended to multichannel psychophysical tasks.

Testing Bayesian and heuristic predictions of mass judgments of colliding objects

PubMed Central

Sanborn, Adam N.

2014-01-01

Mass judgments of colliding objects have been used to explore people's understanding of the physical world because they are ecologically relevant, yet people display biases that are most easily explained by a small set of heuristics. Recent work has challenged the heuristic explanation, by producing the same biases from a model that copes with perceptual uncertainty by using Bayesian inference with a prior based on the correct combination rules from Newtonian mechanics (noisy Newton). Here I test the predictions of the leading heuristic model (Gilden and Proffitt, 1989) against the noisy Newton model using a novel manipulation of the standard mass judgment task: making one of the objects invisible post-collision. The noisy Newton model uses the remaining information to predict above-chance performance, while the leading heuristic model predicts chance performance when one or the other final velocity is occluded. An experiment using two different types of occlusion showed better-than-chance performance and response patterns that followed the predictions of the noisy Newton model. The results demonstrate that people can make sensible physical judgments even when information critical for the judgment is missing, and that a Bayesian model can serve as a guide in these situations. Possible algorithmic-level accounts of this task that more closely correspond to the noisy Newton model are explored. PMID:25206345

Anvil Forecast Tool in the Advanced Weather Interactive Processing System, Phase II

NASA Technical Reports Server (NTRS)

Barrett, Joe H., III

2008-01-01

Meteorologists from the 45th Weather Squadron (45 WS) and Spaceflight Meteorology Group have identified anvil forecasting as one of their most challenging tasks when predicting the probability of violations of the Lightning Launch Commit Criteria and Space Light Rules. As a result, the Applied Meteorology Unit (AMU) created a graphical overlay tool for the Meteorological Interactive Data Display Systems (MIDDS) to indicate the threat of thunderstorm anvil clouds, using either observed or model forecast winds as input.

High solar activity predictions through an artificial neural network

NASA Astrophysics Data System (ADS)

Orozco-Del-Castillo, M. G.; Ortiz-Alemán, J. C.; Couder-Castañeda, C.; Hernández-Gómez, J. J.; Solís-Santomé, A.

The effects of high-energy particles coming from the Sun on human health as well as in the integrity of outer space electronics make the prediction of periods of high solar activity (HSA) a task of significant importance. Since periodicities in solar indexes have been identified, long-term predictions can be achieved. In this paper, we present a method based on an artificial neural network to find a pattern in some harmonics which represent such periodicities. We used data from 1973 to 2010 to train the neural network, and different historical data for its validation. We also used the neural network along with a statistical analysis of its performance with known data to predict periods of HSA with different confidence intervals according to the three-sigma rule associated with solar cycles 24-26, which we found to occur before 2040.

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Adaptive Encoding of Outcome Prediction by Prefrontal Cortex Ensembles Supports Behavioral Flexibility.

PubMed

Del Arco, Alberto; Park, Junchol; Wood, Jesse; Kim, Yunbok; Moghaddam, Bita

2017-08-30

The prefrontal cortex (PFC) is thought to play a critical role in behavioral flexibility by monitoring action-outcome contingencies. How PFC ensembles represent shifts in behavior in response to changes in these contingencies remains unclear. We recorded single-unit activity and local field potentials in the dorsomedial PFC (dmPFC) of male rats during a set-shifting task that required them to update their behavior, among competing options, in response to changes in action-outcome contingencies. As behavior was updated, a subset of PFC ensembles encoded the current trial outcome before the outcome was presented. This novel outcome-prediction encoding was absent in a control task, in which actions were rewarded pseudorandomly, indicating that PFC neurons are not merely providing an expectancy signal. In both control and set-shifting tasks, dmPFC neurons displayed postoutcome discrimination activity, indicating that these neurons also monitor whether a behavior is successful in generating rewards. Gamma-power oscillatory activity increased before the outcome in both tasks but did not differentiate between expected outcomes, suggesting that this measure is not related to set-shifting behavior but reflects expectation of an outcome after action execution. These results demonstrate that PFC neurons support flexible rule-based action selection by predicting outcomes that follow a particular action. SIGNIFICANCE STATEMENT Tracking action-outcome contingencies and modifying behavior when those contingencies change is critical to behavioral flexibility. We find that ensembles of dorsomedial prefrontal cortex neurons differentiate between expected outcomes when action-outcome contingencies change. This predictive mode of signaling may be used to promote a new response strategy at the service of behavioral flexibility. Copyright © 2017 the authors 0270-6474/17/378363-11$15.00/0.

Acquisition, representation and rule generation for procedural knowledge

NASA Technical Reports Server (NTRS)

Ortiz, Chris; Saito, Tim; Mithal, Sachin; Loftin, R. Bowen

1991-01-01

Current research into the design and continuing development of a system for the acquisition of procedural knowledge, its representation in useful forms, and proposed methods for automated C Language Integrated Production System (CLIPS) rule generation is discussed. The Task Analysis and Rule Generation Tool (TARGET) is intended to permit experts, individually or collectively, to visually describe and refine procedural tasks. The system is designed to represent the acquired knowledge in the form of graphical objects with the capacity for generating production rules in CLIPS. The generated rules can then be integrated into applications such as NASA's Intelligent Computer Aided Training (ICAT) architecture. Also described are proposed methods for use in translating the graphical and intermediate knowledge representations into CLIPS rules.

Breaking the rules: do infants have a true understanding of false belief?

PubMed

Yott, Jessica; Poulin-Dubois, Diane

2012-03-01

It has been suggested that infants' performance on the false belief task can be explained by the use of behavioural rules. To test this hypothesis, 18-month-old infants were trained to learn the new rule that an object that disappeared in location A could be found in location B. Infants were then administered a false belief task based on the violation of expectation (VOE) paradigm, an intention understanding task, and a modified detour-reaching task. Results revealed that infants looked significantly longer at the display when the experimenter looked for the toy in the full box (box with the toy) compared to infants who observed the experimenter search in the empty box (box without the toy). Results also revealed significant correlations between infants' looking time at the display and their scores on the intention task and on the detour-reaching task. Taken together, these findings suggest that infants possess an implicit understanding of false belief. In addition, they challenge the view that success on the implicit false belief task does not require executive functioning abilities. © 2011 The British Psychological Society.

Targeted training of the decision rule benefits rule-guided behavior in Parkinson's disease.

PubMed

Ell, Shawn W

2013-12-01

The impact of Parkinson's disease (PD) on rule-guided behavior has received considerable attention in cognitive neuroscience. The majority of research has used PD as a model of dysfunction in frontostriatal networks, but very few attempts have been made to investigate the possibility of adapting common experimental techniques in an effort to identify the conditions that are most likely to facilitate successful performance. The present study investigated a targeted training paradigm designed to facilitate rule learning and application using rule-based categorization as a model task. Participants received targeted training in which there was no selective-attention demand (i.e., stimuli varied along a single, relevant dimension) or nontargeted training in which there was selective-attention demand (i.e., stimuli varied along a relevant dimension as well as an irrelevant dimension). Following training, all participants were tested on a rule-based task with selective-attention demand. During the test phase, PD patients who received targeted training performed similarly to control participants and outperformed patients who did not receive targeted training. As a preliminary test of the generalizability of the benefit of targeted training, a subset of the PD patients were tested on the Wisconsin card sorting task (WCST). PD patients who received targeted training outperformed PD patients who did not receive targeted training on several WCST performance measures. These data further characterize the contribution of frontostriatal circuitry to rule-guided behavior. Importantly, these data also suggest that PD patient impairment, on selective-attention-demanding tasks of rule-guided behavior, is not inevitable and highlight the potential benefit of targeted training.

Proving Properties of Rule-Based Systems

DTIC Science & Technology

1990-12-01

in these systems and enable us to use them with more confidence. Each system of rules is encoded as a set of axioms that define the system theory . The...operation of the rule language and information about the subject domain are also described in the system theory . Validation tasks, such as...the validity of the conjecture in the system theory , we have carried out the corresponding validation task. If the proof is restricted to be

Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.

PubMed

Pasolli, Edoardo; Truong, Duy Tin; Malik, Faizan; Waldron, Levi; Segata, Nicola

2016-07-01

Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the "healthy" microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.

Sleep facilitates learning a new linguistic rule

PubMed Central

Batterink, Laura J.; Oudiette, Delphine; Reber, Paul J.; Paller, Ken A.

2014-01-01

Natural languages contain countless regularities. Extraction of these patterns is an essential component of language acquisition. Here we examined the hypothesis that memory processing during sleep contributes to this learning. We exposed participants to a hidden linguistic rule by presenting a large number of two-word phrases, each including a noun preceded by one of four novel words that functioned as an article (e.g., gi rhino). These novel words (ul, gi, ro and ne) were presented as obeying an explicit rule: two words signified that the noun referent was relatively near, and two that it was relatively far. Undisclosed to participants was the fact that the novel articles also predicted noun animacy, with two of the articles preceding animate referents and the other two preceding inanimate referents. Rule acquisition was tested implicitly using a task in which participants responded to each phrase according to whether the noun was animate or inanimate. Learning of the hidden rule was evident in slower responses to phrases that violated the rule. Responses were delayed regardless of whether rule-knowledge was consciously accessible. Brain potentials provided additional confirmation of implicit and explicit rule-knowledge. An afternoon nap was interposed between two 20-min learning sessions. Participants who obtained greater amounts of both slow-wave and rapid-eye-movement sleep showed increased sensitivity to the hidden linguistic rule in the second session. We conclude that during sleep, reactivation of linguistic information linked with the rule was instrumental for stabilizing learning. The combination of slow-wave and rapid-eye-movement sleep may synergistically facilitate the abstraction of complex patterns in linguistic input. PMID:25447376

Similar Task Features Shape Judgment and Categorization Processes

ERIC Educational Resources Information Center

Hoffmann, Janina A.; von Helversen, Bettina; Rieskamp, Jörg

2016-01-01

The distinction between similarity-based and rule-based strategies has instigated a large body of research in categorization and judgment. Within both domains, the task characteristics guiding strategy shifts are increasingly well documented. Across domains, past research has observed shifts from rule-based strategies in judgment to…

Remembering the best and worst of times: memories for extreme outcomes bias risky decisions.

PubMed

Madan, Christopher R; Ludvig, Elliot A; Spetch, Marcia L

2014-06-01

When making decisions on the basis of past experiences, people must rely on their memories. Human memory has many well-known biases, including the tendency to better remember highly salient events. We propose an extreme-outcome rule, whereby this memory bias leads people to overweight the largest gains and largest losses, leading to more risk seeking for relative gains than for relative losses. To test this rule, in two experiments, people repeatedly chose between fixed and risky options, where the risky option led equiprobably to more or less than did the fixed option. As was predicted, people were more risk seeking for relative gains than for relative losses. In subsequent memory tests, people tended to recall the extreme outcome first and also judged the extreme outcome as having occurred more frequently. Across individuals, risk preferences in the risky-choice task correlated with these memory biases. This extreme-outcome rule presents a novel mechanism through which memory influences decision making.

Impact of ambiguity and risk on decision making in mild Alzheimer's disease.

PubMed

Sinz, H; Zamarian, L; Benke, T; Wenning, G K; Delazer, M

2008-01-01

Decisions under ambiguity and decisions under risk are crucial types of decision making in daily living at any age. This is the first study assessing these two types of decisions in patients with mild dementia of Alzheimer's type (DAT) by means of the Iowa Gambling Task (IGT) and a newly developed, Probability-Associated Gambling (PAG) task. While rules for gains and losses are implicit in the IGT, in the PAG task rules are explicit and winning probabilities, which change from trial to trial, can be estimated. Results of the IGT indicated that DAT patients made more disadvantageous decisions than healthy controls. Patients also shifted more frequently among decks, i.e. under ambiguity decisions were taken randomly and no advantageous strategy was established over time by DAT patients. Thus, not only actual choices but also development of advantageous strategies may be revealing about decision making in the IGT. Compared to controls, patients demonstrated less advantageous choices in the PAG task as well. They gambled more often in the low winning probabilities and less frequently in the high probabilities than healthy participants. Patients' performance on both tasks correlated with measures of executive functions. Findings of the present investigation are consistent with the early pathological cerebral changes and related (cognitive, emotional) deficits reported for DAT. As suggested by our study, decisions under ambiguity as well as decisions under risk are impaired in mild DAT. It may thus be expected that patients with mild DAT have difficulties in taking decisions in every-day life situations, both in cases of ambiguity (information on probability is missing or conflicting, and the expected utility of the different options is incalculable) and in cases of risk (outcomes can be predicted by well-defined or estimable probabilities).

Communicating eating-related rules. Suggestions are more effective than restrictions.

PubMed

Stok, F Marijn; de Vet, Emely; de Wit, John B F; Renner, Britta; de Ridder, Denise T D

2015-03-01

A common social influence technique for curbing unhealthy eating behavior is to communicate eating-related rules (e.g. 'you should not eat unhealthy food'). Previous research has shown that such restrictive rules sometimes backfire and actually increase unhealthy consumption. In the current studies, we aimed to investigate if a milder form of social influence, a suggested rule, is more successful in curbing intake of unhealthy food. We also investigated how both types of rules affected psychological reactance. Students (N = 88 in Study 1, N = 51 in Study 2) completed a creativity task while a bowl of M&M's was within reach. Consumption was either explicitly forbidden (restrictive rule) or mildly discouraged (suggested rule). In the control condition, consumption was either explicitly allowed (Study 1) or M&M's were not provided (Study 2). Measures of reactance were assessed after the creativity task. Subsequently, a taste test was administered where all participants were allowed to consume M&M's. Across both studies, consumption during the creativity task did not differ between the restrictive- and suggested-rule-conditions, indicating that both are equally successful in preventing initial consumption. Restrictive-rule-condition participants reported higher reactance and consumed more in the free-eating taste-test phase than suggested-rule-condition participants and control-group participants, indicating a negative after-effect of restriction. RESULTS show that there are more and less effective ways to communicate eating-related rules. A restrictive rule, as compared to a suggested rule, induced psychological reactance and led to greater unhealthy consumption when participants were allowed to eat freely. It is important to pay attention to the way in which eating-related rules are communicated. Copyright © 2014 Elsevier Ltd. All rights reserved.

The hierarchy of task decision and response selection: a task-switching event related potentials study.

PubMed

Braverman, Ami; Berger, Andrea; Meiran, Nachshon

2014-07-01

According to "hierarchical" multi-step theories, response selection is preceded by a decision regarding which task rule should be executed. Other theories assume a "flat" single-step architecture in which task information and stimulus information are simultaneously considered. Using task switching, the authors independently manipulated two kinds of conflict: task conflict (with information that potentially triggers the relevant or the competing task rule/identity) and response conflict (with information that potentially triggers the relevant or the competing response code/motor response). Event related potentials indicated that the task conflict effect began before the response conflict effect and carried on in parallel with it. These results are more in line with the hierarchical view. Copyright © 2014 Elsevier Inc. All rights reserved.

The relationship between second-order false belief and display rules reasoning: the integration of cognitive and affective social understanding.

PubMed

Naito, Mika; Seki, Yoshimi

2009-01-01

To investigate the relation between cognitive and affective social understanding, Japanese 4- to 8-year-olds received tasks of first- and second-order false beliefs and prosocial and self-presentational display rules. From 6 to 8 years, children comprehended display rules, as well as second-order false belief, using social pressures justifications decreasingly and motivational justifications with embedded perspectives increasingly with age. Although not related to either type of display across ages, second-order tasks were associated with both types of display tasks only at 8 years when examined in each age group. Results suggest that children base their second-order theory of mind and display rules understanding on distinct reasoning until middle childhood, during which time the originally distinct aspects of social understanding are integrated.

Rules and more rules: the effects of multiple tasks, extensive training, and aging on task-switching performance.

PubMed

Buchler, Norbou G; Hoyer, William J; Cerella, John

2008-06-01

Task-switching performance was assessed in young and older adults as a function of the number of task sets to be actively maintained in memory (varied from 1 to 4) over the course of extended training (5 days). Each of the four tasks required the execution of a simple computational algorithm, which was instantaneously cued by the color of the two-digit stimulus. Tasks were presented in pure (task set size 1) and mixed blocks (task set sizes 2, 3, 4), and the task sequence was unpredictable. By considering task switching beyond two tasks, we found evidence for a cognitive control system that is not overwhelmed by task set size load manipulations. Extended training eliminated age effects in task-switching performance, even when the participants had to manage the execution of up to four tasks. The results are discussed in terms of current theories of cognitive control, including task set inertia and production system postulates.

Rule-Based Category Learning in Down Syndrome

ERIC Educational Resources Information Center

Phillips, B. Allyson; Conners, Frances A.; Merrill, Edward; Klinger, Mark R.

2014-01-01

Rule-based category learning was examined in youths with Down syndrome (DS), youths with intellectual disability (ID), and typically developing (TD) youths. Two tasks measured category learning: the Modified Card Sort task (MCST) and the Concept Formation test of the Woodcock-Johnson-III (Woodcock, McGrew, & Mather, 2001). In regression-based…

Rule-Selection and Action-Selection have a Shared Neuroanatomical Basis in the Human Prefrontal and Parietal Cortex

PubMed Central

Hughes, L.; Eckstein, D.; Owen, A.M.

2008-01-01

The human capacity for voluntary action is one of the major contributors to our success as a species. In addition to choosing actions themselves, we can also voluntarily choose behavioral codes or sets of rules that can guide future responses to events. Such rules have been proposed to be superordinate to actions in a cognitive hierarchy and mediated by distinct brain regions. We used event-related functional magnetic resonance imaging to study novel tasks of rule-based and voluntary action. We show that the voluntary selection of rules to govern future responses to events is associated with activation of similar regions of prefrontal and parietal cortex as the voluntary selection of an action itself. The results are discussed in terms of hierarchical models and the adaptive coding potential of prefrontal neurons and their contribution to a global workspace for nonautomatic tasks. These tasks include the choices we make about our behavior. PMID:18234684

The Lexical Stroop Sort (LSS) picture-word task: a computerized task for assessing the relationship between language and executive functioning in school-aged children.

PubMed

Wilbourn, Makeba Parramore; Kurtz, Laura E; Kalia, Vrinda

2012-03-01

The relationship between language development and executive function (EF) in children is not well understood. The Lexical Stroop Sort (LSS) task is a computerized EF task created for the purpose of examining the relationship between school-aged children's oral language development and EF. To validate this new measure, a diverse sample of school-aged children completed standardized oral language assessments, the LSS task, and the widely used Dimensional Change Card Sort (DCCS; Zelazo, 2006) task. Both EF tasks require children to sort stimuli into categories based on predetermined rules. While the DCCS largely relies on visual stimuli, the LSS employs children's phonological loop to access their semantic knowledge base. Accuracy and reaction times were recorded for both tasks. Children's scores on the LSS task were correlated with their scores on the DCCS task, and a similar pattern of relationships emerged between children's vocabulary and the two EF tasks, thus providing convergent validity for the LSS. However, children's phonological awareness was associated with their scores on the LSS, but not with those on the DCCS. In addition, a mediation model was used to elucidate the predictive relationship between phonological awareness and children's performance on the LSS task, with children's vocabulary fully mediating this relationship. The use of this newly created and validated LSS task with different populations, such as preschoolers and bilinguals, is also discussed.

Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

PubMed

Orhan, A Emin; Ma, Wei Ji

2017-07-26

Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

Representing the healthcare organization in a post-Sarbanes-Oxley world: new rules, new paradigms, new perils.

PubMed

Horton, William W

2004-01-01

The Sarbanes-Oxley Act (Act) significantly changed the expected corporate behavior of public companies. The Act governs the relationship between corporate organizations and their in-house or outside counsel. Under Section 307 of the Act, the Securities and Exchange Commission initially proposed expansive rules regarding counsel's duties. After comments and criticism from much of the bar, a final, narrower, version of rules under Section 307 (Final Rule) was adopted. The Final Rule contains alternative reporting procedures, attorney responsibilities, and sanctions for violations. In addition to the Act, the American Bar Association's (ABA) Task Force on Corporate Responsibility(Task Force), which was itself a reaction to Enron, reported on the importance of counsel's role in a corporate setting (Cheek Report). The ABA adopted amendments to its Model Rules of Professional Conduct (Model Rules) 1.6 and 1.13 as proposed in the Cheek Report. The Final Rule and amended Model Rules together suggest that attorneys may owe duties beyond those owed to their clients.

Working Memory Development in Monolingual and Bilingual Children

ERIC Educational Resources Information Center

Morales, Julia; Calvo, Alejandra; Bialystok, Ellen

2013-01-01

Two studies are reported comparing the performance of monolingual and bilingual children on tasks requiring different levels of working memory. In the first study, 56 5-year-olds performed a Simon-type task that manipulated working memory demands by comparing conditions based on two rules and four rules and manipulated conflict resolution demands…

Reasoning versus text processing in the Wason selection task: a nondeontic perspective on perspective effects.

PubMed

Almor, A; Sloman, S A

2000-09-01

We argue that perspective effects in the Wason four-card selection task are a product of the linguistic interpretation of the rule in the context of the problem text and not of the reasoning process underlying card selection. In three experiments, participants recalled the rule they used in either a selection or a plausibility rating task. The results showed that (1) participants tended to recall rules compatible with their card selection and not with the rule as stated in the problem and (2) recall was not affected by whether or not participants performed card selection. We conclude that perspective effects in the Wason selection task do not concern how card selection is reasoned about but instead reflect the inferential text processing involved in the comprehension of the problem text. Together with earlier research that showed selection performance in nondeontic contexts to be indistinguishable from selection performance in deontic contexts (Almor & Sloman, 1996; Sperber, Cara, & Girotto, 1995), the present results undermine the claim that reasoning in a deontic context elicits specialized cognitive processes.

Functional requirements for reward-modulated spike-timing-dependent plasticity.

PubMed

Frémaux, Nicolas; Sprekeler, Henning; Gerstner, Wulfram

2010-10-06

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.

Drifting from slow to "D'oh!": working memory capacity and mind wandering predict extreme reaction times and executive control errors.

PubMed

McVay, Jennifer C; Kane, Michael J

2012-05-01

A combined experimental, individual-differences, and thought-sampling study tested the predictions of executive attention (e.g., Engle & Kane, 2004) and coordinative binding (e.g., Oberauer, Süβ, Wilhelm, & Sander, 2007) theories of working memory capacity (WMC). We assessed 288 subjects' WMC and their performance and mind-wandering rates during a sustained-attention task; subjects completed either a go/no-go version requiring executive control over habit or a vigilance version that did not. We further combined the data with those from McVay and Kane (2009) to (1) gauge the contributions of WMC and attentional lapses to the worst performance rule and the tail, or τ parameter, of reaction time (RT) distributions; (2) assess which parameters from a quantitative evidence-accumulation RT model were predicted by WMC and mind-wandering reports; and (3) consider intrasubject RT patterns--particularly, speeding--as potential objective markers of mind wandering. We found that WMC predicted action and thought control in only some conditions, that attentional lapses (indicated by task-unrelated-thought reports and drift-rate variability in evidence accumulation) contributed to τ, performance accuracy, and WMC's association with them and that mind-wandering experiences were not predicted by trial-to-trial RT changes, and so they cannot always be inferred from objective performance measures. (c) 2012 APA, all rights reserved.

Colloquium paper: adaptive specializations, social exchange, and the evolution of human intelligence.

PubMed

Cosmides, Leda; Barrett, H Clark; Tooby, John

2010-05-11

Blank-slate theories of human intelligence propose that reasoning is carried out by general-purpose operations applied uniformly across contents. An evolutionary approach implies a radically different model of human intelligence. The task demands of different adaptive problems select for functionally specialized problem-solving strategies, unleashing massive increases in problem-solving power for ancestrally recurrent adaptive problems. Because exchange can evolve only if cooperators can detect cheaters, we hypothesized that the human mind would be equipped with a neurocognitive system specialized for reasoning about social exchange. Whereas humans perform poorly when asked to detect violations of most conditional rules, we predicted and found a dramatic spike in performance when the rule specifies an exchange and violations correspond to cheating. According to critics, people's uncanny accuracy at detecting violations of social exchange rules does not reflect a cheater detection mechanism, but extends instead to all rules regulating when actions are permitted (deontic conditionals). Here we report experimental tests that falsify these theories by demonstrating that deontic rules as a class do not elicit the search for violations. We show that the cheater detection system functions with pinpoint accuracy, searching for violations of social exchange rules only when these are likely to reveal the presence of someone who intends to cheat. It does not search for violations of social exchange rules when these are accidental, when they do not benefit the violator, or when the situation would make cheating difficult.

Adaptive specializations, social exchange, and the evolution of human intelligence

PubMed Central

Cosmides, Leda; Barrett, H. Clark; Tooby, John

2010-01-01

Blank-slate theories of human intelligence propose that reasoning is carried out by general-purpose operations applied uniformly across contents. An evolutionary approach implies a radically different model of human intelligence. The task demands of different adaptive problems select for functionally specialized problem-solving strategies, unleashing massive increases in problem-solving power for ancestrally recurrent adaptive problems. Because exchange can evolve only if cooperators can detect cheaters, we hypothesized that the human mind would be equipped with a neurocognitive system specialized for reasoning about social exchange. Whereas humans perform poorly when asked to detect violations of most conditional rules, we predicted and found a dramatic spike in performance when the rule specifies an exchange and violations correspond to cheating. According to critics, people's uncanny accuracy at detecting violations of social exchange rules does not reflect a cheater detection mechanism, but extends instead to all rules regulating when actions are permitted (deontic conditionals). Here we report experimental tests that falsify these theories by demonstrating that deontic rules as a class do not elicit the search for violations. We show that the cheater detection system functions with pinpoint accuracy, searching for violations of social exchange rules only when these are likely to reveal the presence of someone who intends to cheat. It does not search for violations of social exchange rules when these are accidental, when they do not benefit the violator, or when the situation would make cheating difficult. PMID:20445099

Service without a smile: comparing the consequences of neutral and positive display rules.

PubMed

Trougakos, John P; Jackson, Christine L; Beal, Daniel J

2011-03-01

We used an experimental design to examine the intrapersonal and interpersonal processes through which neutral display rules, compared to positive display rules, influence objective task performance of poll workers and ratings provided by survey respondents of the poll workers. Student participants (N = 140) were trained to adhere to 1 of the 2 display rule conditions while delivering opinion surveys to potential patrons of an organization during a 40-min period. Results showed that, compared to positive display rules, neutral display rules resulted in less task persistence and greater avoidance behavior. These effects were mediated through a greater use of expression suppression. In addition, neutral display rules resulted in less positive respondent mood, which accounted for lower ratings of service quality and of overall favorability attitudes toward the sponsoring organization. The importance and ubiquity of neutral display rules are discussed, given the potential for positive and negative consequences at work. PsycINFO Database Record (c) 2011 APA, all rights reserved.

Sleep facilitates learning a new linguistic rule.

PubMed

Batterink, Laura J; Oudiette, Delphine; Reber, Paul J; Paller, Ken A

2014-12-01

Natural languages contain countless regularities. Extraction of these patterns is an essential component of language acquisition. Here we examined the hypothesis that memory processing during sleep contributes to this learning. We exposed participants to a hidden linguistic rule by presenting a large number of two-word phrases, each including a noun preceded by one of four novel words that functioned as an article (e.g., gi rhino). These novel words (ul, gi, ro and ne) were presented as obeying an explicit rule: two words signified that the noun referent was relatively near, and two that it was relatively far. Undisclosed to participants was the fact that the novel articles also predicted noun animacy, with two of the articles preceding animate referents and the other two preceding inanimate referents. Rule acquisition was tested implicitly using a task in which participants responded to each phrase according to whether the noun was animate or inanimate. Learning of the hidden rule was evident in slower responses to phrases that violated the rule. Responses were delayed regardless of whether rule-knowledge was consciously accessible. Brain potentials provided additional confirmation of implicit and explicit rule-knowledge. An afternoon nap was interposed between two 20-min learning sessions. Participants who obtained greater amounts of both slow-wave and rapid-eye-movement sleep showed increased sensitivity to the hidden linguistic rule in the second session. We conclude that during sleep, reactivation of linguistic information linked with the rule was instrumental for stabilizing learning. The combination of slow-wave and rapid-eye-movement sleep may synergistically facilitate the abstraction of complex patterns in linguistic input. Copyright © 2014 Elsevier Ltd. All rights reserved.

Knowledge-based reasoning in the Paladin tactical decision generation system

NASA Technical Reports Server (NTRS)

Chappell, Alan R.

1993-01-01

A real-time tactical decision generation system for air combat engagements, Paladin, has been developed. A pilot's job in air combat includes tasks that are largely symbolic. These symbolic tasks are generally performed through the application of experience and training (i.e. knowledge) gathered over years of flying a fighter aircraft. Two such tasks, situation assessment and throttle control, are identified and broken out in Paladin to be handled by specialized knowledge based systems. Knowledge pertaining to these tasks is encoded into rule-bases to provide the foundation for decisions. Paladin uses a custom built inference engine and a partitioned rule-base structure to give these symbolic results in real-time. This paper provides an overview of knowledge-based reasoning systems as a subset of rule-based systems. The knowledge used by Paladin in generating results as well as the system design for real-time execution is discussed.

Enhancements to the Design Manager's Aide for Intelligent Decomposition (DeMAID)

NASA Technical Reports Server (NTRS)

Rogers, James L.; Barthelemy, Jean-Francois M.

1992-01-01

This paper discusses the addition of two new enhancements to the program Design Manager's Aide for Intelligent Decomposition (DeMAID). DeMAID is a knowledge-based tool used to aid a design manager in understanding the interactions among the tasks of a complex design problem. This is done by ordering the tasks to minimize feedback, determining the participating subsystems, and displaying them in an easily understood format. The two new enhancements include (1) rules for ordering a complex assembly process and (2) rules for determining which analysis tasks must be re-executed to compute the output of one task based on a change in input to that or another task.

Enhancements to the Design Manager's Aide for Intelligent Decomposition (DeMaid)

NASA Technical Reports Server (NTRS)

Rogers, James L.; Barthelemy, Jean-Francois M.

1992-01-01

This paper discusses the addition of two new enhancements to the program Design Manager's Aide for Intelligent Decomposition (DeMAID). DeMAID is a knowledge-based tool used to aid a design manager in understanding the interactions among the tasks of a complex design problem. This is done by ordering the tasks to minimize feedback, determining the participating subsystems, and displaying them in an easily understood format. The two new enhancements include (1) rules for ordering a complex assembly process and (2) rules for determining which analysis tasks must be re-executed to compute the output of one task based on a change in input to that or another task.

Test of a potential link between analytic and nonanalytic category learning and automatic, effortful processing.

PubMed

Tracy, J I; Pinsk, M; Helverson, J; Urban, G; Dietz, T; Smith, D J

2001-08-01

The link between automatic and effortful processing and nonanalytic and analytic category learning was evaluated in a sample of 29 college undergraduates using declarative memory, semantic category search, and pseudoword categorization tasks. Automatic and effortful processing measures were hypothesized to be associated with nonanalytic and analytic categorization, respectively. Results suggested that contrary to prediction strong criterion-attribute (analytic) responding on the pseudoword categorization task was associated with strong automatic, implicit memory encoding of frequency-of-occurrence information. Data are discussed in terms of the possibility that criterion-attribute category knowledge, once established, may be expressed with few attentional resources. The data indicate that attention resource requirements, even for the same stimuli and task, vary depending on the category rule system utilized. Also, the automaticity emerging from familiarity with analytic category exemplars is very different from the automaticity arising from extensive practice on a semantic category search task. The data do not support any simple mapping of analytic and nonanalytic forms of category learning onto the automatic and effortful processing dichotomy and challenge simple models of brain asymmetries for such procedures. Copyright 2001 Academic Press.

Fear of negative evaluation biases social evaluation inference: evidence from a probabilistic learning task.

PubMed

Button, Katherine S; Kounali, Daphne; Stapinski, Lexine; Rapee, Ronald M; Lewis, Glyn; Munafò, Marcus R

2015-01-01

Fear of negative evaluation (FNE) defines social anxiety yet the process of inferring social evaluation, and its potential role in maintaining social anxiety, is poorly understood. We developed an instrumental learning task to model social evaluation learning, predicting that FNE would specifically bias learning about the self but not others. During six test blocks (3 self-referential, 3 other-referential), participants (n = 100) met six personas and selected a word from a positive/negative pair to finish their social evaluation sentences "I think [you are / George is]…". Feedback contingencies corresponded to 3 rules, liked, neutral and disliked, with P[positive word correct] = 0.8, 0.5 and 0.2, respectively. As FNE increased participants selected fewer positive words (β = -0.4, 95% CI -0.7, -0.2, p = 0.001), which was strongest in the self-referential condition (FNE × condition 0.28, 95% CI 0.01, 0.54, p = 0.04), and the neutral and dislike rules (FNE × condition × rule, p = 0.07). At low FNE the proportion of positive words selected for self-neutral and self-disliked greatly exceeded the feedback contingency, indicating poor learning, which improved as FNE increased. FNE is associated with differences in processing social-evaluative information specifically about the self. At low FNE this manifests as insensitivity to learning negative self-referential evaluation. High FNE individuals are equally sensitive to learning positive or negative evaluation, which although objectively more accurate, may have detrimental effects on mental health.

The nonlinear, complex sequential organization of behavior in schizophrenic patients: neurocognitive strategies and clinical correlations.

PubMed

Paulus, M P; Perry, W; Braff, D L

1999-09-01

Thought disorder is a hallmark of schizophrenia and can be inferred from disorganized behavior. Measures of the sequential organization of behavior are important because they reflect the cognitive processes of the selection and sequencing of behavioral elements, which generate observable and analyzable behavioral patterns. In this context, sequences of choices generated by schizophrenic patients in a two-choice guessing task fluctuate significantly, which reflects an "oscillating dysregulation" between highly predictable and highly unpredictable subsequences within a single test session. In this study, we aimed to clarify the significance of dysregulation by seeing whether demographic, clinical, neuropsychological, and psychological measures predict the degree of dysregulation observed on this two-choice task. Thirty schizophrenic patients repeatedly performed a LEFT or RIGHT key press that was followed by a stimulus, which occurred randomly on the left or right side of the computer screen. Thus, the stimulus location had nothing to do with the key press behavior. The range of key press sequence predictabilities as measured by the dynamical entropy was used to quantify the dysregulation of response sequences and reflects the range of fixity and randomness of the responses. A factor analysis was performed and step-wise multiple regression analyses were used to relate the factor scores to demographic, clinical, symptomatic, Wisconsin Card Sorting Test (WCST), and Rorschach variables. The LEFT/RIGHT key press sequences were determined by three factors: 1) the degree of win-stay/lose-shift strategy; 2) the degree of contextual influence on the current choice; and 3) the degree of dysregulation on the choice task. Demographic and clinical variables did not predict any of the three response patterns on the choice task. In contrast, the WCST and Rorschach test predicted performance on various factors of choice task response patterns. Schizophrenic patients employ several rules, i.e., "win-stay/lose-shift" and "decide according to the previous choice," that fluctuate significantly when generating sequences on this task, confirming that a basic behavioral dysregulation occurs in a single schizophrenic subject across a single test session. The organization or the "temporal architecture" of the behavioral sequences is not related to symptoms per se, but is related to deficits in executive functioning, problem solving, and perceptual organizational abilities.

Switching between Abstract Rules Reflects Disease Severity but Not Dopaminergic Status in Parkinson's Disease

ERIC Educational Resources Information Center

Kehagia, Angie A.; Cools, Roshan; Barker, Roger A.; Robbins, Trevor W.

2009-01-01

This study sought to disambiguate the impact of Parkinson's disease (PD) on cognitive control as indexed by task set switching, by addressing discrepancies in the literature pertaining to disease severity and paradigm heterogeneity. A task set is governed by a rule that determines how relevant stimuli (stimulus set) map onto specific responses…

Young Children's Understanding of Beliefs about Moral and Conventional Rule Violations

ERIC Educational Resources Information Center

Conry-Murray, Clare

2013-01-01

Children of ages 3-5 ("N" = 62) were assessed by using standard theory-of-mind tasks and unusual belief tasks related to false information and beliefs endorsing violations of moral (welfare and fairness) and social conventional (school rules) domains. Younger children (under 5 years) did not accurately attribute unusual factual beliefs…

The Opposites Task: Using General Rules to Test Cognitive Flexibility in Preschoolers

ERIC Educational Resources Information Center

Baker, Sara T.; Friedman, Ori; Leslie, Alan M.

2010-01-01

Executive functions play an important role in cognitive development, and during the preschool years especially, children's performance is limited in tasks that demand flexibility in their behavior. We asked whether preschoolers would exhibit limitations when they are required to apply a general rule in the context of novel stimuli on every trial…

Rule Following and Rule Use in the Balance-Scale Task

ERIC Educational Resources Information Center

Shultz, Thomas R.; Takane, Yoshio

2007-01-01

Quinlan et al. [Quinlan, p., van der Mass, H., Jansen, B., Booij, O., & Rendell, M. (this issue). Re-thinking stages of cognitive development: An appraisal of connectionist models of the balance scale task. "Cognition", doi:10.1016/j.cognition.2006.02.004] use Latent Class Analysis (LCA) to criticize a connectionist model of development on the…

Relations as Rules: The Role of Attention in the Dimensional Change Card Sort Task

ERIC Educational Resources Information Center

Honomichl, Ryan D.; Chen, Zhe

2011-01-01

Preschoolers are typically unable to switch sorting rules during the Dimensional Change Card Sort task. One explanation for this phenomenon is attentional inflexibility (Kirkham, Cruess, & Diamond, 2003). In 4 experiments with 3- to 4-year-olds, we tested this hypothesis by examining the influence of dimensional salience on switching performance.…

Brain Regions Involved in the Learning and Application of Reward Rules in a Two-Deck Gambling Task

ERIC Educational Resources Information Center

Hartstra, E.; Oldenburg, J. F. E.; Van Leijenhorst, L.; Rombouts, S. A. R. B.; Crone, E. A.

2010-01-01

Decision-making involves the ability to choose between competing actions that are associated with uncertain benefits and penalties. The Iowa Gambling Task (IGT), which mimics real-life decision-making, involves learning a reward-punishment rule over multiple trials. Patients with damage to ventromedial prefrontal cortex (VMPFC) show deficits…

Association Rule-based Predictive Model for Machine Failure in Industrial Internet of Things

NASA Astrophysics Data System (ADS)

Kwon, Jung-Hyok; Lee, Sol-Bee; Park, Jaehoon; Kim, Eui-Jik

2017-09-01

This paper proposes an association rule-based predictive model for machine failure in industrial Internet of things (IIoT), which can accurately predict the machine failure in real manufacturing environment by investigating the relationship between the cause and type of machine failure. To develop the predictive model, we consider three major steps: 1) binarization, 2) rule creation, 3) visualization. The binarization step translates item values in a dataset into one or zero, then the rule creation step creates association rules as IF-THEN structures using the Lattice model and Apriori algorithm. Finally, the created rules are visualized in various ways for users’ understanding. An experimental implementation was conducted using R Studio version 3.3.2. The results show that the proposed predictive model realistically predicts machine failure based on association rules.

The development of inhibitory control in preschool children: effects of "executive skills" training.

PubMed

Dowsett, S M; Livesey, D J

2000-03-01

As one of several processes involved in the executive functioning of the cognitive system, inhibitory control plays a significant role in determining how various mental processes work together in the successful performance of a task. Studies of response inhibition have shown that although 3-year-old children have the cognitive capacity to learn the rules required for response control, indicated by the correct verbal response, developmental constraints prevent them from withholding the correct response (Bell & Livesey, 1985; Livesey & Morgan, 1991). Some argue that these abulic dissociations are relative to children's ability to reflect on the rules required for response control (Zelazo, Reznick, & Pinon, 1995). The current study showed that repeated exposure to tasks facilitating the acquisition of increasingly complex rule structures could improve inhibitory control (as measured by a go/no-go discrimination learning task), even in children aged 3 years. These tasks included a variant of Diamond and Boyer's (1989) modified version of the Wisconsin Card Sort Task and a simplification of the change paradigm (Logan & Burkell, 1986). It is argued that experience with these tasks increased the acquisition of complex rules by placing demands on executive processes. This includes response control and other executive functions, such as representational flexibility, the ability to maintain information in working memory, the selective control of attention, and proficiency at error correction. The role of experiential variables in the development of inhibitory control is discussed in terms of the interaction between neural development and appropriate executive task experience in the early years. Copyright 2000 John Wiley & Sons, Inc.

The rational clinical examination. Does this patient have strep throat?

PubMed

Ebell, M H; Smith, M A; Barry, H C; Ives, K; Carey, M

2000-12-13

Sore throat is a common complaint, and identifying patients with group A beta-hemolytic streptococcal pharyngitis (strep throat) is an important task for clinicians. Previous reviews have not systematically reviewed and synthesized the evidence. To review the precision and accuracy of the clinical examination in diagnosing strep throat. MEDLINE search for articles about diagnosis of strep throat using history-taking and physical examination. Large blinded, prospective studies (having > or =300 patients with sore throat) reporting history and physical examination data and using throat culture as the reference standard were included. Of 917 articles identified by the search, 9 met all inclusion criteria. Pairs of authors independently reviewed each article and used consensus to resolve discrepancies. The most useful findings for evaluating the likelihood of strep throat are presence of tonsillar exudate, pharyngeal exudate, or exposure to strep throat infection in the previous 2 weeks (positive likelihood ratios, 3.4, 2.1, and 1.9, respectively) and the absence of tender anterior cervical nodes, tonsillar enlargement, or exudate (negative likelihood ratios, 0.60, 0.63, and 0.74, respectively). No individual element of history-taking or physical examination is accurate enough by itself to rule in or rule out strep throat. Three validated clinical prediction rules are described for adult and pediatric populations. While no single element of history-taking or physical examination is sufficiently accurate to exclude or diagnose strep throat, a well-validated clinical prediction rule can be useful and can help physicians make more informed use of rapid antigen tests and throat cultures.

Divided attention limits perception of 3-D object shapes

PubMed Central

Scharff, Alec; Palmer, John; Moore, Cathleen M.

2013-01-01

Can one perceive multiple object shapes at once? We tested two benchmark models of object shape perception under divided attention: an unlimited-capacity and a fixed-capacity model. Under unlimited-capacity models, shapes are analyzed independently and in parallel. Under fixed-capacity models, shapes are processed at a fixed rate (as in a serial model). To distinguish these models, we compared conditions in which observers were presented with simultaneous or sequential presentations of a fixed number of objects (The extended simultaneous-sequential method: Scharff, Palmer, & Moore, 2011a, 2011b). We used novel physical objects as stimuli, minimizing the role of semantic categorization in the task. Observers searched for a specific object among similar objects. We ensured that non-shape stimulus properties such as color and texture could not be used to complete the task. Unpredictable viewing angles were used to preclude image-matching strategies. The results rejected unlimited-capacity models for object shape perception and were consistent with the predictions of a fixed-capacity model. In contrast, a task that required observers to recognize 2-D shapes with predictable viewing angles yielded an unlimited capacity result. Further experiments ruled out alternative explanations for the capacity limit, leading us to conclude that there is a fixed-capacity limit on the ability to perceive 3-D object shapes. PMID:23404158

There are limits to the effects of task instructions: Making the automatic effects of task instructions context-specific takes practice.

PubMed

Braem, Senne; Liefooghe, Baptist; De Houwer, Jan; Brass, Marcel; Abrahamse, Elger L

2017-03-01

Unlike other animals, humans have the unique ability to share and use verbal instructions to prepare for upcoming tasks. Recent research showed that instructions are sufficient for the automatic, reflex-like activation of responses. However, systematic studies into the limits of these automatic effects of task instructions remain relatively scarce. In this study, the authors set out to investigate whether this instruction-based automatic activation of responses can be context-dependent. Specifically, participants performed a task of which the stimulus-response rules and context (location on the screen) could either coincide or not with those of an instructed to-be-performed task (whose instructions changed every run). In 2 experiments, the authors showed that the instructed task rules had an automatic impact on performance-performance was slowed down when the merely instructed task rules did not coincide, but, importantly, this effect was not context-dependent. Interestingly, a third and fourth experiment suggests that context dependency can actually be observed, but only when practicing the task in its appropriate context for over 60 trials or after a sufficient amount of practice on a fixed context (the context was the same for all instructed tasks). Together, these findings seem to suggest that instructions can establish stimulus-response representations that have a reflexive impact on behavior but are insensitive to the context in which the task is known to be valid. Instead, context-specific task representations seem to require practice. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Application of the EVEX resource to event extraction and network construction: Shared Task entry and result analysis

PubMed Central

2015-01-01

Background Modern methods for mining biomolecular interactions from literature typically make predictions based solely on the immediate textual context, in effect a single sentence. No prior work has been published on extending this context to the information automatically gathered from the whole biomedical literature. Thus, our motivation for this study is to explore whether mutually supporting evidence, aggregated across several documents can be utilized to improve the performance of the state-of-the-art event extraction systems. In this paper, we describe our participation in the latest BioNLP Shared Task using the large-scale text mining resource EVEX. We participated in the Genia Event Extraction (GE) and Gene Regulation Network (GRN) tasks with two separate systems. In the GE task, we implemented a re-ranking approach to improve the precision of an existing event extraction system, incorporating features from the EVEX resource. In the GRN task, our system relied solely on the EVEX resource and utilized a rule-based conversion algorithm between the EVEX and GRN formats. Results In the GE task, our re-ranking approach led to a modest performance increase and resulted in the first rank of the official Shared Task results with 50.97% F-score. Additionally, in this paper we explore and evaluate the usage of distributed vector representations for this challenge. In the GRN task, we ranked fifth in the official results with a strict/relaxed SER score of 0.92/0.81 respectively. To try and improve upon these results, we have implemented a novel machine learning based conversion system and benchmarked its performance against the original rule-based system. Conclusions For the GRN task, we were able to produce a gene regulatory network from the EVEX data, warranting the use of such generic large-scale text mining data in network biology settings. A detailed performance and error analysis provides more insight into the relatively low recall rates. In the GE task we demonstrate that both the re-ranking approach and the word vectors can provide slight performance improvement. A manual evaluation of the re-ranking results pinpoints some of the challenges faced in applying large-scale text mining knowledge to event extraction. PMID:26551766

The Construct of Attention in Schizophrenia

PubMed Central

Luck, Steven J.; Gold, James M.

2008-01-01

Schizophrenia is widely thought to involve deficits of attention. However, the term attention can be defined so broadly that impaired performance on virtually any task could be construed as evidence for a deficit in attention, and this has slowed cumulative progress in understanding attention deficits in schizophrenia. To address this problem, we divide the general concept of attention into two distinct constructs: input selection, the selection of task-relevant inputs for further processing; and rule selection, the selective activation of task-appropriate rules. These constructs are closely tied to working memory, because input selection mechanisms are used to control the transfer of information into working memory and because working memory stores the rules used by rule selection mechanisms. These constructs are also closely tied to executive function, because executive systems are used to guide input selection and because rule selection is itself at key aspect of executive function. Within the domain of input selection, it is important to distinguish between the control of selection—the processes that guide attention to task-relevant inputs—and the implementation of selection—the processes that enhance the processing of the relevant inputs and suppress the irrelevant inputs. Current evidence suggests that schizophrenia involves a significant impairment in the control of selection but little or no impairment in the implementation of selection. Consequently, the CNTRICS participants agreed by consensus that attentional control should be a priority target for measurement and treatment research in schizophrenia. PMID:18374901

Developmental Trajectory of Rule Detection in Four- to Six-Year-Old Children

ERIC Educational Resources Information Center

Li, Wei; Cao, Bihua; Hu, Lijuan; Li, Fuhong

2017-01-01

Children younger than three years old are able to detect hidden rules in numerical sequences, and this ability matches that of adults by age seven. However, the developmental trajectory of this ability during the ages of four to six remains unknown. The present study adopted a modified Brixton task to address this issue. In this task, children…

The Effects of Focused/Unfocused Audio-Appended Reading Tasks on Intermediate Female EFL Learners' Written Accuracy

ERIC Educational Resources Information Center

Alavinia, Parviz; Shafaei, Ali; Salimi, Asghar

2018-01-01

The current research study was conducted to examine the impacts of focused and unfocused audio-appended reading tasks on female EFL learners' acquisition of a rule-bound structure (passive voice) and a non-rule-bound structure (prepositions). The participants of this study involved ninety intermediate female English learners. They were assigned…

A Connectionist Model of a Continuous Developmental Transition in the Balance Scale Task

ERIC Educational Resources Information Center

Schapiro, Anna C.; McClelland, James L.

2009-01-01

A connectionist model of the balance scale task is presented which exhibits developmental transitions between "Rule I" and "Rule II" behavior [Siegler, R. S. (1976). Three aspects of cognitive development. "Cognitive Psychology," 8, 481-520.] as well as the "catastrophe flags" seen in data from Jansen and van der Maas [Jansen, B. R. J., & van der…

Normative and descriptive accounts of the influence of power and contingency on causal judgement.

PubMed

Perales, José C; Shanks, David R

2003-08-01

The power PC theory (Cheng, 1997) is a normative account of causal inference, which predicts that causal judgements are based on the power p of a potential cause, where p is the cause-effect contingency normalized by the base rate of the effect. In three experiments we demonstrate that both cause-effect contingency and effect base-rate independently affect estimates in causal learning tasks. In Experiment 1, causal strength judgements were directly related to power p in a task in which the effect base-rate was manipulated across two positive and two negative contingency conditions. In Experiments 2 and 3 contingency manipulations affected causal estimates in several situations in which power p was held constant, contrary to the power PC theory's predictions. This latter effect cannot be explained by participants' conflation of reliability and causal strength, as Experiment 3 demonstrated independence of causal judgements and confidence. From a descriptive point of view, the data are compatible with Pearce's (1987) model, as well as with several other judgement rules, but not with the Rescorla-Wagner (Rescorla & Wagner, 1972) or power PC models.

Conditional Reasoning in Schizophrenic Patients.

PubMed

Kornreich, Charles; Delle-Vigne, Dyna; Brevers, Damien; Tecco, Juan; Campanella, Salvatore; Noël, Xavier; Verbanck, Paul; Ermer, Elsa

2017-01-01

Conditional reasoning (if p then q) is used very frequently in everyday situations. Conditional reasoning is impaired in brain-lesion patients, psychopathy, alcoholism, and polydrug dependence. Many neurocognitive deficits have also been described in schizophrenia. We assessed conditional reasoning in 25 patients with schizophrenia, 25 depressive patients, and 25 controls, using the Wason selection task in three different domains: social contracts, precautionary rules, and descriptive rules. Control measures included depression, anxiety, and severity of schizophrenia measures as a Verbal Intelligence Scale. Patients with schizophrenia were significantly impaired on all conditional reasoning tasks compared to depressives and controls. However, the social contract and precautions tasks yielded better results than the descriptive tasks. Differences between groups disappeared for social contract but remained for precautions and descriptive tasks when verbal intelligence was used as a covariate. These results suggest that domain-specific reasoning mechanisms, proposed by evolutionary psychologists, are relatively resilient in the face of brain network disruptions that impair more general reasoning abilities. Nevertheless, patients with schizophrenia could encounter difficulties understanding precaution rules and social contracts in real-life situations resulting in unwise risk-taking and misunderstandings in the social world.

The Interactive Effects of the Availability of Objectives and/or Rules on Computer-Based Learning: A Replication.

ERIC Educational Resources Information Center

Merrill, Paul F.; And Others

To replicate and extend the results of a previous study, this project investigated the effects of behavioral objectives and/or rules on computer-based learning task performance. The 133 subjects were randomly assigned to an example-only, objective-example, rule example, or objective-rule example group. The availability of rules and/or objectives…

Developing an International Register of Clinical Prediction Rules for Use in Primary Care: A Descriptive Analysis

PubMed Central

Keogh, Claire; Wallace, Emma; O’Brien, Kirsty K.; Galvin, Rose; Smith, Susan M.; Lewis, Cliona; Cummins, Anthony; Cousins, Grainne; Dimitrov, Borislav D.; Fahey, Tom

2014-01-01

PURPOSE We describe the methodology used to create a register of clinical prediction rules relevant to primary care. We also summarize the rules included in the register according to various characteristics. METHODS To identify relevant articles, we searched the MEDLINE database (PubMed) for the years 1980 to 2009 and supplemented the results with searches of secondary sources (books on clinical prediction rules) and personal resources (eg, experts in the field). The rules described in relevant articles were classified according to their clinical domain, the stage of development, and the clinical setting in which they were studied. RESULTS Our search identified clinical prediction rules reported between 1965 and 2009. The largest share of rules (37.2%) were retrieved from PubMed. The number of published rules increased substantially over the study decades. We included 745 articles in the register; many contained more than 1 clinical prediction rule study (eg, both a derivation study and a validation study), resulting in 989 individual studies. In all, 434 unique rules had gone through derivation; however, only 54.8% had been validated and merely 2.8% had undergone analysis of their impact on either the process or outcome of clinical care. The rules most commonly pertained to cardiovascular disease, respiratory, and musculoskeletal conditions. They had most often been studied in the primary care or emergency department settings. CONCLUSIONS Many clinical prediction rules have been derived, but only about half have been validated and few have been assessed for clinical impact. This lack of thorough evaluation for many rules makes it difficult to retrieve and identify those that are ready for use at the point of patient care. We plan to develop an international web-based register of clinical prediction rules and computer-based clinical decision support systems. PMID:25024245

Contrast class cues and performance facilitation in a hypothesis-testing task: evidence for an iterative counterfactual model.

PubMed

Gale, Maggie; Ball, Linden J

2012-04-01

Hypothesis-testing performance on Wason's (Quarterly Journal of Experimental Psychology 12:129-140, 1960) 2-4-6 task is typically poor, with only around 20% of participants announcing the to-be-discovered "ascending numbers" rule on their first attempt. Enhanced solution rates can, however, readily be observed with dual-goal (DG) task variants requiring the discovery of two complementary rules, one labeled "DAX" (the standard "ascending numbers" rule) and the other labeled "MED" ("any other number triples"). Two DG experiments are reported in which we manipulated the usefulness of a presented MED exemplar, where usefulness denotes cues that can establish a helpful "contrast class" that can stand in opposition to the presented 2-4-6 DAX exemplar. The usefulness of MED exemplars had a striking facilitatory effect on DAX rule discovery, which supports the importance of contrast-class information in hypothesis testing. A third experiment ruled out the possibility that the useful MED triple seeded the correct rule from the outset and obviated any need for hypothesis testing. We propose that an extension of Oaksford and Chater's (European Journal of Cognitive Psychology 6:149-169, 1994) iterative counterfactual model can neatly capture the mechanisms by which DG facilitation arises.

Rule-Based Category Learning in Children: The Role of Age and Executive Functioning

PubMed Central

Rabi, Rahel; Minda, John Paul

2014-01-01

Rule-based category learning was examined in 4–11 year-olds and adults. Participants were asked to learn a set of novel perceptual categories in a classification learning task. Categorization performance improved with age, with younger children showing the strongest rule-based deficit relative to older children and adults. Model-based analyses provided insight regarding the type of strategy being used to solve the categorization task, demonstrating that the use of the task appropriate strategy increased with age. When children and adults who identified the correct categorization rule were compared, the performance deficit was no longer evident. Executive functions were also measured. While both working memory and inhibitory control were related to rule-based categorization and improved with age, working memory specifically was found to marginally mediate the age-related improvements in categorization. When analyses focused only on the sample of children, results showed that working memory ability and inhibitory control were associated with categorization performance and strategy use. The current findings track changes in categorization performance across childhood, demonstrating at which points performance begins to mature and resemble that of adults. Additionally, findings highlight the potential role that working memory and inhibitory control may play in rule-based category learning. PMID:24489658

The Balance-Scale Task Revisited: A Comparison of Statistical Models for Rule-Based and Information-Integration Theories of Proportional Reasoning

PubMed Central

Hofman, Abe D.; Visser, Ingmar; Jansen, Brenda R. J.; van der Maas, Han L. J.

2015-01-01

We propose and test three statistical models for the analysis of children’s responses to the balance scale task, a seminal task to study proportional reasoning. We use a latent class modelling approach to formulate a rule-based latent class model (RB LCM) following from a rule-based perspective on proportional reasoning and a new statistical model, the Weighted Sum Model, following from an information-integration approach. Moreover, a hybrid LCM using item covariates is proposed, combining aspects of both a rule-based and information-integration perspective. These models are applied to two different datasets, a standard paper-and-pencil test dataset (N = 779), and a dataset collected within an online learning environment that included direct feedback, time-pressure, and a reward system (N = 808). For the paper-and-pencil dataset the RB LCM resulted in the best fit, whereas for the online dataset the hybrid LCM provided the best fit. The standard paper-and-pencil dataset yielded more evidence for distinct solution rules than the online data set in which quantitative item characteristics are more prominent in determining responses. These results shed new light on the discussion on sequential rule-based and information-integration perspectives of cognitive development. PMID:26505905

Face-induced expectancies influence neural mechanisms of performance monitoring.

PubMed

Osinsky, Roman; Seeger, Jennifer; Mussel, Patrick; Hewig, Johannes

2016-04-01

In many daily situations, the consequences of our actions are predicted by cues that are often social in nature. For instance, seeing the face of an evaluator (e.g., a supervisor at work) may activate certain evaluative expectancies, depending on the history of prior encounters with that particular person. We investigated how such face-induced expectancies influence neurocognitive functions of performance monitoring. We recorded an electroencephalogram while participants completed a time-estimation task, during which they received performance feedback from a strict and a lenient evaluator. During each trial, participants first saw the evaluator's face before performing the task and, finally, receiving feedback. Therefore, faces could be used as predictive cues for the upcoming evaluation. We analyzed electrocortical signatures of performance monitoring at the stages of cue processing, task performance, and feedback reception. Our results indicate that, at the cue stage, seeing the strict evaluator's face results in an anticipatory preparation of fronto-medial monitoring mechanisms, as reflected by a sustained negative-going amplitude shift (i.e., the contingent negative variation). At the performance stage, face-induced expectancies of a strict evaluation rule led to increases of early performance monitoring signals (i.e., frontal-midline theta power). At the final stage of feedback reception, violations of outcome expectancies differentially affected the feedback-related negativity and frontal-midline theta power, pointing to a functional dissociation between these signatures. Altogether, our results indicate that evaluative expectancies induced by face-cues lead to adjustments of internal performance monitoring mechanisms at various stages of task processing.

RM-SORN: a reward-modulated self-organizing recurrent neural network.

PubMed

Aswolinskiy, Witali; Pipa, Gordon

2015-01-01

Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain.

Connecting clinical and actuarial prediction with rule-based methods.

PubMed

Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

2015-06-01

Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

The Role of Age and Executive Function in Auditory Category Learning

PubMed Central

Reetzke, Rachel; Maddox, W. Todd; Chandrasekaran, Bharath

2015-01-01

Auditory categorization is a natural and adaptive process that allows for the organization of high-dimensional, continuous acoustic information into discrete representations. Studies in the visual domain have identified a rule-based learning system that learns and reasons via a hypothesis-testing process that requires working memory and executive attention. The rule-based learning system in vision shows a protracted development, reflecting the influence of maturing prefrontal function on visual categorization. The aim of the current study is two-fold: (a) to examine the developmental trajectory of rule-based auditory category learning from childhood through adolescence, into early adulthood; and (b) to examine the extent to which individual differences in rule-based category learning relate to individual differences in executive function. Sixty participants with normal hearing, 20 children (age range, 7–12), 21 adolescents (age range, 13–19), and 19 young adults (age range, 20–23), learned to categorize novel dynamic ripple sounds using trial-by-trial feedback. The spectrotemporally modulated ripple sounds are considered the auditory equivalent of the well-studied Gabor patches in the visual domain. Results revealed that auditory categorization accuracy improved with age, with young adults outperforming children and adolescents. Computational modeling analyses indicated that the use of the task-optimal strategy (i.e. a conjunctive rule-based learning strategy) improved with age. Notably, individual differences in executive flexibility significantly predicted auditory category learning success. The current findings demonstrate a protracted development of rule-based auditory categorization. The results further suggest that executive flexibility coupled with perceptual processes play important roles in successful rule-based auditory category learning. PMID:26491987

Fast and slow brain rhythms in rule/expectation violation tasks: focusing on evaluation processes by excluding motor action.

PubMed

Tzur, Gabriel; Berger, Andrea

2009-03-17

Theta rhythm has been connected to ERP components such as the error-related negativity (ERN) and the feedback-related negativity (FRN). The nature of this theta activity is still unclear, that is, whether it is related to error detection, conflict between responses or reinforcement learning processes. We examined slow (e.g., theta) and fast (e.g., gamma) brain rhythms related to rule violation. A time-frequency decomposition analysis on a wide range of frequencies band (0-95 Hz) indicated that the theta activity relates to evaluation processes, regardless of motor/action processes. Similarities between the theta activities found in rule-violation tasks and in tasks eliciting ERN/FRN suggest that this theta activity reflects the operation of general evaluation mechanisms. Moreover, significant effects were found also in fast brain rhythms. These effects might be related to the synchronization between different types of cognitive processes involving the fulfillment of a task (e.g., working memory, visual perception, mathematical calculation, etc.).

Prediction of linear B-cell epitopes of hepatitis C virus for vaccine development

PubMed Central

2015-01-01

Background High genetic heterogeneity in the hepatitis C virus (HCV) is the major challenge of the development of an effective vaccine. Existing studies for developing HCV vaccines have mainly focused on T-cell immune response. However, identification of linear B-cell epitopes that can stimulate B-cell response is one of the major tasks of peptide-based vaccine development. Owing to the variability in B-cell epitope length, the prediction of B-cell epitopes is much more complex than that of T-cell epitopes. Furthermore, the motifs of linear B-cell epitopes in different pathogens are quite different (e. g. HCV and hepatitis B virus). To cope with this challenge, this work aims to propose an HCV-customized sequence-based prediction method to identify B-cell epitopes of HCV. Results This work establishes an experimentally verified dataset comprising the B-cell response of HCV dataset consisting of 774 linear B-cell epitopes and 774 non B-cell epitopes from the Immune Epitope Database. An interpretable rule mining system of B-cell epitopes (IRMS-BE) is proposed to select informative physicochemical properties (PCPs) and then extracts several if-then rule-based knowledge for identifying B-cell epitopes. A web server Bcell-HCV was implemented using an SVM with the 34 informative PCPs, which achieved a training accuracy of 79.7% and test accuracy of 70.7% better than the SVM-based methods for identifying B-cell epitopes of HCV and the two general-purpose methods. This work performs advanced analysis of the 34 informative properties, and the results indicate that the most effective property is the alpha-helix structure of epitopes, which influences the connection between host cells and the E2 proteins of HCV. Furthermore, 12 interpretable rules are acquired from top-five PCPs and achieve a sensitivity of 75.6% and specificity of 71.3%. Finally, a conserved promising vaccine candidate, PDREMVLYQE, is identified for inclusion in a vaccine against HCV. Conclusions This work proposes an interpretable rule mining system IRMS-BE for extracting interpretable rules using informative physicochemical properties and a web server Bcell-HCV for predicting linear B-cell epitopes of HCV. IRMS-BE may also apply to predict B-cell epitopes for other viruses, which benefits the improvement of vaccines development of these viruses without significant modification. Bcell-HCV is useful for identifying B-cell epitopes of HCV antigen to help vaccine development, which is available at http://e045.life.nctu.edu.tw/BcellHCV. PMID:26680271

Report: Efficiency of EPA’s Rule Development Process Can Be Better Measured Through Improved Management and Information

EPA Pesticide Factsheets

Report #13-P-0167, February 28, 2013. Rule development is one of the Agency’s principal tasks. EPA develops rules to carry out the environmental and public health protection laws passed by Congress.

Neural activity in superior parietal cortex during rule-based visual-motor transformations.

PubMed

Hawkins, Kara M; Sayegh, Patricia; Yan, Xiaogang; Crawford, J Douglas; Sergio, Lauren E

2013-03-01

Cognition allows for the use of different rule-based sensorimotor strategies, but the neural underpinnings of such strategies are poorly understood. The purpose of this study was to compare neural activity in the superior parietal lobule during a standard (direct interaction) reaching task, with two nonstandard (gaze and reach spatially incongruent) reaching tasks requiring the integration of rule-based information. Specifically, these nonstandard tasks involved dissociating the planes of reach and vision or rotating visual feedback by 180°. Single unit activity, gaze, and reach trajectories were recorded from two female Macaca mulattas. In all three conditions, we observed a temporal discharge pattern at the population level reflecting early reach planning and on-line reach monitoring. In the plane-dissociated task, we found a significant overall attenuation in the discharge rate of cells from deep recording sites, relative to standard reaching. We also found that cells modulated by reach direction tended to be significantly tuned either during the standard or the plane-dissociated task but rarely during both. In the standard versus feedback reversal comparison, we observed some cells that shifted their preferred direction by 180° between conditions, reflecting maintenance of directional tuning with respect to the reach goal. Our findings suggest that the superior parietal lobule plays an important role in processing information about the nonstandard nature of a task, which, through reciprocal connections with precentral motor areas, contributes to the accurate transformation of incongruent sensory inputs into an appropriate motor output. Such processing is crucial for the integration of rule-based information into a motor act.

Dynamic Trial-by-Trial Recoding of Task-Set Representations in the Frontoparietal Cortex Mediates Behavioral Flexibility

PubMed Central

Qiao, Lei; Zhang, Lijie

2017-01-01

Cognitive flexibility forms the core of the extraordinary ability of humans to adapt, but the precise neural mechanisms underlying our ability to nimbly shift between task sets remain poorly understood. Recent functional magnetic resonance imaging (fMRI) studies employing multivoxel pattern analysis (MVPA) have shown that a currently relevant task set can be decoded from activity patterns in the frontoparietal cortex, but whether these regions support the dynamic transformation of task sets from trial to trial is not clear. Here, we combined a cued task-switching protocol with human (both sexes) fMRI, and harnessed representational similarity analysis (RSA) to facilitate a novel assessment of trial-by-trial changes in neural task-set representations. We first used MVPA to define task-sensitive frontoparietal and visual regions and found that neural task-set representations on switch trials are less stably encoded than on repeat trials. We then exploited RSA to show that the neural representational pattern dissimilarity across consecutive trials is greater for switch trials than for repeat trials, and that the degree of this pattern dissimilarity predicts behavior. Moreover, the overall neural pattern of representational dissimilarities followed from the assumption that repeating sets, compared with switching sets, results in stronger neural task representations. Finally, when moving from cue to target phase within a trial, pattern dissimilarities tracked the transformation from previous-trial task representations to the currently relevant set. These results provide neural evidence for the longstanding assumptions of an effortful task-set reconfiguration process hampered by task-set inertia, and they demonstrate that frontoparietal and stimulus processing regions support “dynamic adaptive coding,” flexibly representing changing task sets in a trial-by-trial fashion. SIGNIFICANCE STATEMENT Humans can fluently switch between different tasks, reflecting an ability to dynamically configure “task sets,” rule representations that link stimuli to appropriate responses. Recent studies show that neural signals in frontal and parietal brain regions can tell us which of two tasks a person is currently performing. However, it is not known whether these regions are also involved in dynamically reconfiguring task-set representations when switching between tasks. Here we measured human brain activity during task switching and tracked the similarity of neural task-set representations from trial to trial. We show that frontal and parietal brain regions flexibly recode changing task sets in a trial-by-trial fashion, and that task-set similarity over consecutive trials predicts behavior. PMID:28972126

Goal neglect and knowledge chunking in the construction of novel behaviour☆

PubMed Central

Bhandari, Apoorva; Duncan, John

2014-01-01

Task complexity is critical in cognitive efficiency and fluid intelligence. To examine functional limits in task complexity, we examine the phenomenon of goal neglect, where participants with low fluid intelligence fail to follow task rules that they otherwise understand. Though neglect is known to increase with task complexity, here we show that – in contrast to previous accounts – the critical factor is not the total complexity of all task rules. Instead, when the space of task requirements can be divided into separate sub-parts, neglect is controlled by the complexity of each component part. The data also show that neglect develops and stabilizes over the first few performance trials, i.e. as instructions are first used to generate behaviour. In all complex behaviour, a critical process is combination of task events with retrieved task requirements to create focused attentional episodes dealing with each decision in turn. In large part, we suggest, fluid intelligence may reflect this process of converting complex requirements into effective attentional episodes. PMID:24141034

Competition between learned reward and error outcome predictions in anterior cingulate cortex.

PubMed

Alexander, William H; Brown, Joshua W

2010-02-15

The anterior cingulate cortex (ACC) is implicated in performance monitoring and cognitive control. Non-human primate studies of ACC show prominent reward signals, but these are elusive in human studies, which instead show mainly conflict and error effects. Here we demonstrate distinct appetitive and aversive activity in human ACC. The error likelihood hypothesis suggests that ACC activity increases in proportion to the likelihood of an error, and ACC is also sensitive to the consequence magnitude of the predicted error. Previous work further showed that error likelihood effects reach a ceiling as the potential consequences of an error increase, possibly due to reductions in the average reward. We explored this issue by independently manipulating reward magnitude of task responses and error likelihood while controlling for potential error consequences in an Incentive Change Signal Task. The fMRI results ruled out a modulatory effect of expected reward on error likelihood effects in favor of a competition effect between expected reward and error likelihood. Dynamic causal modeling showed that error likelihood and expected reward signals are intrinsic to the ACC rather than received from elsewhere. These findings agree with interpretations of ACC activity as signaling both perceptions of risk and predicted reward. Copyright 2009 Elsevier Inc. All rights reserved.

Rule Encoding in Orbitofrontal Cortex and Striatum Guides Selection

PubMed Central

Castagno, Meghan D.; Hayden, Benjamin Y.

2016-01-01

Active maintenance of rules, like other executive functions, is often thought to be the domain of a discrete executive system. An alternative view is that rule maintenance is a broadly distributed function relying on widespread cortical and subcortical circuits. Tentative evidence supporting this view comes from research showing some rule selectivity in the orbitofrontal cortex and dorsal striatum. We recorded in these regions and in the ventral striatum, which has not been associated previously with rule representation, as macaques performed a Wisconsin Card Sorting Task. We found robust encoding of rule category (color vs shape) and rule identity (six possible rules) in all three regions. Rule identity modulated responses to potential choice targets, suggesting that rule information guides behavior by highlighting choice targets. The effects that we observed were not explained by differences in behavioral performance across rules and thus cannot be attributed to reward expectation. Our results suggest that rule maintenance and rule-guided selection of options are distributed processes and provide new insight into orbital and striatal contributions to executive control. SIGNIFICANCE STATEMENT Rule maintenance, an important executive function, is generally thought to rely on dorsolateral brain regions. In this study, we examined activity of single neurons in orbitofrontal cortex and in ventral and dorsal striatum of macaques in a Wisconsin Card Sorting Task. Neurons in all three areas encoded rules and rule categories robustly. Rule identity also affected neural responses to potential choice options, suggesting that stored information is used to influence decisions. These results endorse the hypothesis that rule maintenance is a broadly distributed mental operation. PMID:27807165

Perceptual training methods compared: the relative efficacy of different approaches to enhancing sport-specific anticipation.

PubMed

Abernethy, Bruce; Schorer, Jörg; Jackson, Robin C; Hagemann, Norbert

2012-06-01

The comparative efficacy of different perceptual training approaches for the improvement of anticipation was examined using a goalkeeping task from European handball that required the rapid prediction of shot direction. Novice participants (N = 60) were assigned equally to four different training groups and two different control groups (a placebo group and a group who undertook no training). The training groups received either (i) explicit rules to guide anticipation; (ii) direction as to the location of the key anticipatory cues provided either just verbally (verbal cueing) or supplemented with color highlighting (color cueing); or (iii) undertook a matching judgment task to encourage implicit learning. Performance of the groups was compared on an anticipation test administered before training, after the training intervention, under a condition involving evaluative stress, and after a 5-month retention period. The explicit learning, verbal cueing, and implicit learning conditions provided the greatest sustained improvements in performance whereas the group given color cueing performed no better than the control groups. Only the implicit learning group showed performance superior to the control groups under the stress situation. The verbal cueing, color cueing, and implicit learning groups formulated the lowest number of explicit rules related to the critical shoulder cue although the reported use of general cues and rules based on all cues did not differ between any of the groups. Anticipation can be improved through a variety of different perceptual training approaches with the relative efficacy of the different approaches being contingent upon both the time scale and conditions under which learning is assessed.

Fear of Negative Evaluation Biases Social Evaluation Inference: Evidence from a Probabilistic Learning Task

PubMed Central

Button, Katherine S.; Kounali, Daphne; Stapinski, Lexine; Rapee, Ronald M.; Lewis, Glyn; Munafò, Marcus R.

2015-01-01

Background Fear of negative evaluation (FNE) defines social anxiety yet the process of inferring social evaluation, and its potential role in maintaining social anxiety, is poorly understood. We developed an instrumental learning task to model social evaluation learning, predicting that FNE would specifically bias learning about the self but not others. Methods During six test blocks (3 self-referential, 3 other-referential), participants (n = 100) met six personas and selected a word from a positive/negative pair to finish their social evaluation sentences “I think [you are / George is]…”. Feedback contingencies corresponded to 3 rules, liked, neutral and disliked, with P[positive word correct] = 0.8, 0.5 and 0.2, respectively. Results As FNE increased participants selected fewer positive words (β = −0.4, 95% CI −0.7, −0.2, p = 0.001), which was strongest in the self-referential condition (FNE × condition 0.28, 95% CI 0.01, 0.54, p = 0.04), and the neutral and dislike rules (FNE × condition × rule, p = 0.07). At low FNE the proportion of positive words selected for self-neutral and self-disliked greatly exceeded the feedback contingency, indicating poor learning, which improved as FNE increased. Conclusions FNE is associated with differences in processing social-evaluative information specifically about the self. At low FNE this manifests as insensitivity to learning negative self-referential evaluation. High FNE individuals are equally sensitive to learning positive or negative evaluation, which although objectively more accurate, may have detrimental effects on mental health. PMID:25853835

Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule.

PubMed

Beyeler, Michael; Dutt, Nikil D; Krichmar, Jeffrey L

2013-12-01

Understanding how the human brain is able to efficiently perceive and understand a visual scene is still a field of ongoing research. Although many studies have focused on the design and optimization of neural networks to solve visual recognition tasks, most of them either lack neurobiologically plausible learning rules or decision-making processes. Here we present a large-scale model of a hierarchical spiking neural network (SNN) that integrates a low-level memory encoding mechanism with a higher-level decision process to perform a visual classification task in real-time. The model consists of Izhikevich neurons and conductance-based synapses for realistic approximation of neuronal dynamics, a spike-timing-dependent plasticity (STDP) synaptic learning rule with additional synaptic dynamics for memory encoding, and an accumulator model for memory retrieval and categorization. The full network, which comprised 71,026 neurons and approximately 133 million synapses, ran in real-time on a single off-the-shelf graphics processing unit (GPU). The network was constructed on a publicly available SNN simulator that supports general-purpose neuromorphic computer chips. The network achieved 92% correct classifications on MNIST in 100 rounds of random sub-sampling, which is comparable to other SNN approaches and provides a conservative and reliable performance metric. Additionally, the model correctly predicted reaction times from psychophysical experiments. Because of the scalability of the approach and its neurobiological fidelity, the current model can be extended to an efficient neuromorphic implementation that supports more generalized object recognition and decision-making architectures found in the brain. Copyright © 2013 Elsevier Ltd. All rights reserved.

Rhinal and Dorsolateral Prefrontal Cortex Lesions Produce Selective Impairments in Object and Spatial Learning and Memory in Canines

PubMed Central

Christie, Lori-Ann; Saunders, Richard C.; Kowalska, Danuta, M.; MacKay, William A.; Head, Elizabeth; Cotman, Carl W.; Milgram, Norton W.

2014-01-01

To examine the effects of rhinal and dorsolateral prefrontal cortex lesions on object and spatial recognition memory in canines, we used a protocol in which both an object (delayed non-matching to sample, or DNMS) and a spatial (delayed non-matching to position or DNMP) recognition task were administered daily. The tasks used similar procedures such that only the type of stimulus information to be remembered differed. Rhinal cortex (RC) lesions produced a selective deficit on the DNMS task, both in retention of the task rules at short delays and in object recognition memory. By contrast, performance on the DNMP task remained intact at both short and long delay intervals in RC animals. Subjects who received dorsolateral prefrontal cortex (dlPFC) lesions were impaired on a spatial task at a short, 5-sec delay, suggesting disrupted retention of the general task rules, however, this impairment was transient; long-term spatial memory performance was unaffected in dlPFC subjects. The present results provide support for the involvement of the RC in object, but not visuospatial, processing and recognition memory, whereas the dlPFC appears to mediate retention of a non-matching rule. These findings support theories of functional specialization within the medial temporal lobe and frontal cortex and suggest that rhinal and dorsolateral prefrontal cortices in canines are functionally similar to analogous regions in other mammals. PMID:18792072

Validation and comparison of clinical prediction rules for invasive candidiasis in intensive care unit patients: a matched case-control study

PubMed Central

2011-01-01

Introduction Due to the increasing prevalence and severity of invasive candidiasis, investigators have developed clinical prediction rules to identify patients who may benefit from antifungal prophylaxis or early empiric therapy. The aims of this study were to validate and compare the Paphitou and Ostrosky-Zeichner clinical prediction rules in ICU patients in a 689-bed academic medical center. Methods We conducted a retrospective matched case-control study from May 2003 to June 2008 to evaluate the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of each rule. Cases included adults with ICU stays of at least four days and invasive candidiasis matched to three controls by age, gender and ICU admission date. The clinical prediction rules were applied to cases and controls via retrospective chart review to evaluate the success of the rules in predicting invasive candidiasis. Paphitou's rule included diabetes, total parenteral nutrition (TPN) and dialysis with or without antibiotics. Ostrosky-Zeichner's rule included antibiotics or central venous catheter plus at least two of the following: surgery, immunosuppression, TPN, dialysis, corticosteroids and pancreatitis. Conditional logistic regression was performed to evaluate the rules. Discriminative power was evaluated by area under the receiver operating characteristic curve (AUC ROC). Results A total of 352 patients were included (88 cases and 264 controls). The incidence of invasive candidiasis among adults with an ICU stay of at least four days was 2.3%. The prediction rules performed similarly, exhibiting low PPVs (0.041 to 0.054), high NPVs (0.983 to 0.990) and AUC ROCs (0.649 to 0.705). A new prediction rule (Nebraska Medical Center rule) was developed with PPVs, NPVs and AUC ROCs of 0.047, 0.994 and 0.770, respectively. Conclusions Based on low PPVs and high NPVs, the rules are most useful for identifying patients who are not likely to develop invasive candidiasis, potentially preventing unnecessary antifungal use, optimizing patient ICU care and facilitating the design of forthcoming antifungal clinical trials. PMID:21846332

Neural networks supporting switching, hypothesis testing, and rule application

PubMed Central

Liu, Zhiya; Braunlich, Kurt; Wehe, Hillary S.; Seger, Carol A.

2015-01-01

We identified dynamic changes in recruitment of neural connectivity networks across three phases of a flexible rule learning and set-shifting task similar to the Wisconsin Card Sort Task: switching, rule learning via hypothesis testing, and rule application. During fMRI scanning, subjects viewed pairs of stimuli that differed across four dimensions (letter, color, size, screen location), chose one stimulus, and received feedback. Subjects were informed that the correct choice was determined by a simple unidimensional rule, for example “choose the blue letter.” Once each rule had been learned and correctly applied for 4-7 trials, subjects were cued via either negative feedback or visual cues to switch to learning a new rule. Task performance was divided into three phases: Switching (first trial after receiving the switch cue), hypothesis testing (subsequent trials through the last error trial), and rule application (correct responding after the rule was learned). We used both univariate analysis to characterize activity occurring within specific regions of the brain, and a multivariate method, constrained principal component analysis for fMRI (fMRI-CPCA), to investigate how distributed regions coordinate to subserve different processes. As hypothesized, switching was subserved by a limbic network including the ventral striatum, thalamus, and parahippocampal gyrus, in conjunction with cortical salience network regions including the anterior cingulate and frontoinsular cortex. Activity in the ventral striatum was associated with switching regardless of how switching was cued; visually cued shifts were associated with additional visual cortical activity. After switching, as subjects moved into the hypothesis testing phase, a broad fronto-parietal-striatal network (associated with the cognitive control, dorsal attention, and salience networks) increased in activity. This network was sensitive to rule learning speed, with greater extended activity for the slowest learning speed late in the time course of learning. As subjects shifted from hypothesis testing to rule application, activity in this network decreased and activity in the somatomotor and default mode networks increased. PMID:26197092

Neural networks supporting switching, hypothesis testing, and rule application.

PubMed

Liu, Zhiya; Braunlich, Kurt; Wehe, Hillary S; Seger, Carol A

2015-10-01

We identified dynamic changes in recruitment of neural connectivity networks across three phases of a flexible rule learning and set-shifting task similar to the Wisconsin Card Sort Task: switching, rule learning via hypothesis testing, and rule application. During fMRI scanning, subjects viewed pairs of stimuli that differed across four dimensions (letter, color, size, screen location), chose one stimulus, and received feedback. Subjects were informed that the correct choice was determined by a simple unidimensional rule, for example "choose the blue letter". Once each rule had been learned and correctly applied for 4-7 trials, subjects were cued via either negative feedback or visual cues to switch to learning a new rule. Task performance was divided into three phases: Switching (first trial after receiving the switch cue), hypothesis testing (subsequent trials through the last error trial), and rule application (correct responding after the rule was learned). We used both univariate analysis to characterize activity occurring within specific regions of the brain, and a multivariate method, constrained principal component analysis for fMRI (fMRI-CPCA), to investigate how distributed regions coordinate to subserve different processes. As hypothesized, switching was subserved by a limbic network including the ventral striatum, thalamus, and parahippocampal gyrus, in conjunction with cortical salience network regions including the anterior cingulate and frontoinsular cortex. Activity in the ventral striatum was associated with switching regardless of how switching was cued; visually cued shifts were associated with additional visual cortical activity. After switching, as subjects moved into the hypothesis testing phase, a broad fronto-parietal-striatal network (associated with the cognitive control, dorsal attention, and salience networks) increased in activity. This network was sensitive to rule learning speed, with greater extended activity for the slowest learning speed late in the time course of learning. As subjects shifted from hypothesis testing to rule application, activity in this network decreased and activity in the somatomotor and default mode networks increased. Copyright © 2015 Elsevier Ltd. All rights reserved.

Rumination and the mood-as-input hypothesis: Does congruence matter?

PubMed

Fisak, Brian; Kissinger-Knox, Alicia; Cibrian, Enrique

2018-06-08

The mood-as-input hypothesis (MAIH), which emphasizes the role of mood and stop rules on perseverative thinking, has been extensively studied in relation to worry (Meeten & Davey, 2011). However, relatively few studies have focused on the applicability of the MAIH to depressive rumination. Consequently, two studies were conducted to further examine the potential relevance of the MAIH to depressive rumination. In the first study, a sample of undergraduate students completed a rumination interview under one of four conditions, including mood (positive vs. negative) and stop rule (as-many-as can (AMA) and feel like stopping (FL)). It was anticipated that participants in the negative mood/AMA and the positive mood/FL conditions would exhibit the most persistence in the rumination interview. A second, follow-up study was conducted in which a positive rumination condition was added to examine the role of congruence between mood induction and task valence on interview performance. In the first study, support for predictions of the MAIH was found in the negative mood conditions but not the positive mood conditions. In the second study, as predicted, under conditions of mood congruence, the original predictions of the MAIH were supported. However, under conditions of mood incongruence, participants appeared to default to the assigned stop rule. Although the findings are promising, it is noteworthy that the sample was non-clinical. Further, this approach to studying depressive rumination may have somewhat limited ecological validity, as the research was conducted in a controlled laboratory setting. Overall, the current findings provide insight into the conditions under which depressive rumination is most likely to occur. Copyright © 2018. Published by Elsevier Ltd.

Increasing On-Task Behavior in Every Student in a Second-Grade Classroom during Transitions: Validating the Color Wheel System

ERIC Educational Resources Information Center

Fudge, Daniel L.; Skinner, Christopher H.; Williams, Jacqueline L.; Cowden, Dan; Clark, Janice; Bliss, Stacy L.

2008-01-01

A single-case (B-C-B-C) experimental design was used to evaluate the effects of the Color Wheel classroom management system (CWS) on on-task (OT) behavior in an intact, general-education, 2nd-grade classroom during transitions. The CWS included three sets of rules, posted cues to indicate the rules students are expected to be following at that…

Learning to use working memory: a reinforcement learning gating model of rule acquisition in rats

PubMed Central

Lloyd, Kevin; Becker, Nadine; Jones, Matthew W.; Bogacz, Rafal

2012-01-01

Learning to form appropriate, task-relevant working memory representations is a complex process central to cognition. Gating models frame working memory as a collection of past observations and use reinforcement learning (RL) to solve the problem of when to update these observations. Investigation of how gating models relate to brain and behavior remains, however, at an early stage. The current study sought to explore the ability of simple RL gating models to replicate rule learning behavior in rats. Rats were trained in a maze-based spatial learning task that required animals to make trial-by-trial choices contingent upon their previous experience. Using an abstract version of this task, we tested the ability of two gating algorithms, one based on the Actor-Critic and the other on the State-Action-Reward-State-Action (SARSA) algorithm, to generate behavior consistent with the rats'. Both models produced rule-acquisition behavior consistent with the experimental data, though only the SARSA gating model mirrored faster learning following rule reversal. We also found that both gating models learned multiple strategies in solving the initial task, a property which highlights the multi-agent nature of such models and which is of importance in considering the neural basis of individual differences in behavior. PMID:23115551

The Decision to Engage Cognitive Control Is Driven by Expected Reward-Value: Neural and Behavioral Evidence

PubMed Central

Dixon, Matthew L.; Christoff, Kalina

2012-01-01

Cognitive control is a fundamental skill reflecting the active use of task-rules to guide behavior and suppress inappropriate automatic responses. Prior work has traditionally used paradigms in which subjects are told when to engage cognitive control. Thus, surprisingly little is known about the factors that influence individuals' initial decision of whether or not to act in a reflective, rule-based manner. To examine this, we took three classic cognitive control tasks (Stroop, Wisconsin Card Sorting Task, Go/No-Go task) and created novel ‘free-choice’ versions in which human subjects were free to select an automatic, pre-potent action, or an action requiring rule-based cognitive control, and earned varying amounts of money based on their choices. Our findings demonstrated that subjects' decision to engage cognitive control was driven by an explicit representation of monetary rewards expected to be obtained from rule-use. Subjects rarely engaged cognitive control when the expected outcome was of equal or lesser value as compared to the value of the automatic response, but frequently engaged cognitive control when it was expected to yield a larger monetary outcome. Additionally, we exploited fMRI-adaptation to show that the lateral prefrontal cortex (LPFC) represents associations between rules and expected reward outcomes. Together, these findings suggest that individuals are more likely to act in a reflective, rule-based manner when they expect that it will result in a desired outcome. Thus, choosing to exert cognitive control is not simply a matter of reason and willpower, but rather, conforms to standard mechanisms of value-based decision making. Finally, in contrast to current models of LPFC function, our results suggest that the LPFC plays a direct role in representing motivational incentives. PMID:23284730

Automation based on knowledge modeling theory and its applications in engine diagnostic systems using Space Shuttle Main Engine vibrational data. M.S. Thesis

NASA Technical Reports Server (NTRS)

Kim, Jonnathan H.

1995-01-01

Humans can perform many complicated tasks without explicit rules. This inherent and advantageous capability becomes a hurdle when a task is to be automated. Modern computers and numerical calculations require explicit rules and discrete numerical values. In order to bridge the gap between human knowledge and automating tools, a knowledge model is proposed. Knowledge modeling techniques are discussed and utilized to automate a labor and time intensive task of detecting anomalous bearing wear patterns in the Space Shuttle Main Engine (SSME) High Pressure Oxygen Turbopump (HPOTP).

Individual differences in the benefits of feedback for learning.

PubMed

Kelley, Christopher M; McLaughlin, Anne Collins

2012-02-01

Research on learning from feedback has produced ambiguous guidelines for feedback design--some have advocated minimal feedback, whereas others have recommended more extensive feedback that highly supported performance. The objective of the current study was to investigate how individual differences in cognitive resources may predict feedback requirements and resolve previous conflicted findings. Cognitive resources were controlled for by comparing samples from populations with known differences, older and younger adults.To control for task demands, a simple rule-based learning task was created in which participants learned to identify fake Windows pop-ups. Pop-ups were divided into two categories--those that required fluid ability to identify and those that could be identified using crystallized intelligence. In general, results showed participants given higher feedback learned more. However, when analyzed by type of task demand, younger adults performed comparably with both levels of feedback for both cues whereas older adults benefited from increased feedbackfor fluid ability cues but from decreased feedback for crystallized ability cues. One explanation for the current findings is feedback requirements are connected to the cognitive abilities of the learner-those with higher abilities for the type of demands imposed by the task are likely to benefit from reduced feedback. We suggest the following considerations for feedback design: Incorporate learner characteristics and task demands when designing learning support via feedback.

Task switching in video game players: Benefits of selective attention but not resistance to proactive interference.

PubMed

Karle, James W; Watter, Scott; Shedden, Judith M

2010-05-01

Research into the perceptual and cognitive effects of playing video games is an area of increasing interest for many investigators. Over the past decade, expert video game players (VGPs) have been shown to display superior performance compared to non-video game players (nVGPs) on a range of visuospatial and attentional tasks. A benefit of video game expertise has recently been shown for task switching, suggesting that VGPs also have superior cognitive control abilities compared to nVGPs. In two experiments, we examined which aspects of task switching performance this VGP benefit may be localized to. With minimal trial-to-trial interference from minimally overlapping task set rules, VGPs demonstrated a task switching benefit compared to nVGPs. However, this benefit disappeared when proactive interference between tasks was increased, with substantial stimulus and response overlap in task set rules. We suggest that VGPs have no generalized benefit in task switching-related cognitive control processes compared to nVGPs, with switch cost reductions due instead to a specific benefit in controlling selective attention. Copyright 2009 Elsevier B.V. All rights reserved.

Switching between Tasks and Responses: A Developmental Study

ERIC Educational Resources Information Center

Crone, Eveline A.; Bunge, Silvia A.; van der Molen, Maurits W.; Ridderinkhof, K. Richard

2006-01-01

Task switching requires the ability to flexibly switch between task rules and responses, and is sensitive to developmental change. We tested the hypothesis that developmental changes in task switch performance are associated with changes in the facilitating or interfering effect of the previously retrieved stimulus-response (S-R) association.…

Songbirds and humans apply different strategies in a sound sequence discrimination task.

PubMed

Seki, Yoshimasa; Suzuki, Kenta; Osawa, Ayumi M; Okanoya, Kazuo

2013-01-01

The abilities of animals and humans to extract rules from sound sequences have previously been compared using observation of spontaneous responses and conditioning techniques. However, the results were inconsistently interpreted across studies possibly due to methodological and/or species differences. Therefore, we examined the strategies for discrimination of sound sequences in Bengalese finches and humans using the same protocol. Birds were trained on a GO/NOGO task to discriminate between two categories of sound stimulus generated based on an "AAB" or "ABB" rule. The sound elements used were taken from a variety of male (M) and female (F) calls, such that the sequences could be represented as MMF and MFF. In test sessions, FFM and FMM sequences, which were never presented in the training sessions but conformed to the rule, were presented as probe stimuli. The results suggested two discriminative strategies were being applied: (1) memorizing sound patterns of either GO or NOGO stimuli and generating the appropriate responses for only those sounds; and (2) using the repeated element as a cue. There was no evidence that the birds successfully extracted the abstract rule (i.e., AAB and ABB); MMF-GO subjects did not produce a GO response for FFM and vice versa. Next we examined whether those strategies were also applicable for human participants on the same task. The results and questionnaires revealed that participants extracted the abstract rule, and most of them employed it to discriminate the sequences. This strategy was never observed in bird subjects, although some participants used strategies similar to the birds when responding to the probe stimuli. Our results showed that the human participants applied the abstract rule in the task even without instruction but Bengalese finches did not, thereby reconfirming that humans have to extract abstract rules from sound sequences that is distinct from non-human animals.

Cognitive underpinnings of nationalistic ideology in the context of Brexit.

PubMed

Zmigrod, Leor; Rentfrow, Peter J; Robbins, Trevor W

2018-05-08

Nationalistic identities often play an influential role in citizens' voting behavior and political engagement. Nationalistic ideologies tend to have firm categories and rules for what belongs to and represents the national culture. In a sample of 332 UK citizens, we tested whether strict categorization of stimuli and rules in objective cognitive tasks would be evident in strongly nationalistic individuals. Using voting behavior and attitudes from the United Kingdom's 2016 EU referendum, we found that a flexible representation of national identity and culture was linked to cognitive flexibility in the ideologically neutral Wisconsin Card Sorting Test and Remote Associates Test, and to self-reported flexibility under uncertainty. Path analysis revealed that subjective and objective cognitive inflexibility predicted heightened authoritarianism, nationalism, conservatism, and system justification, and these in turn were predictive of support for Brexit and opposition to immigration, the European Union, and free movement of labor. This model accounted for 47.6% of the variance in support for Brexit. Path analysis models were also predictive of participants' sense of personal attachment to the United Kingdom, signifying that individual differences in cognitive flexibility may contribute toward ideological thinking styles that shape both nationalistic attitudes and personal sense of nationalistic identity. These findings further suggest that emotionally neutral "cold" cognitive information processing-and not just "hot" emotional cognition-may play a key role in ideological behavior and identity.

Training self-assessment and task-selection skills to foster self-regulated learning: Do trained skills transfer across domains?

PubMed

Raaijmakers, Steven F; Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J G; van Gog, Tamara

2018-01-01

Students' ability to accurately self-assess their performance and select a suitable subsequent learning task in response is imperative for effective self-regulated learning. Video modeling examples have proven effective for training self-assessment and task-selection skills, and-importantly-such training fostered self-regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task-selection rule or a more general heuristic task-selection rule in biology would transfer to self-regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task-selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self-regulated learning in math. Future research should investigate how to support transfer of task-selection skills across domains.

Effects of two doses of glucose and a caffeine-glucose combination on cognitive performance and mood during multi-tasking.

PubMed

Scholey, Andrew; Savage, Karen; O'Neill, Barry V; Owen, Lauren; Stough, Con; Priestley, Caroline; Wetherell, Mark

2014-09-01

This study assessed the effects of two doses of glucose and a caffeine-glucose combination on mood and performance of an ecologically valid, computerised multi-tasking platform. Following a double-blind, placebo-controlled, randomised, parallel-groups design, 150 healthy adults (mean age 34.78 years) consumed drinks containing placebo, 25 g glucose, 60 g glucose or 60 g glucose with 40 mg caffeine. They completed a multi-tasking framework at baseline and then 30 min following drink consumption with mood assessments immediately before and after the multi-tasking framework. Blood glucose and salivary caffeine were co-monitored. The caffeine-glucose group had significantly better total multi-tasking scores than the placebo or 60 g glucose groups and were significantly faster at mental arithmetic tasks than either glucose drink group. There were no significant treatment effects on mood. Caffeine and glucose levels confirmed compliance with overnight abstinence/fasting, respectively, and followed the predicted post-drink patterns. These data suggest that co-administration of glucose and caffeine allows greater allocation of attentional resources than placebo or glucose alone. At present, we cannot rule out the possibility that the effects are due to caffeine alone Future studies should aim at disentangling caffeine and glucose effects. © 2014 The Authors. Human Psychopharmacology: Clinical and Experimental published by John Wiley & Sons, Ltd.

Effects of two doses of glucose and a caffeine–glucose combination on cognitive performance and mood during multi-tasking

PubMed Central

Scholey, Andrew; Savage, Karen; O'Neill, Barry V; Owen, Lauren; Stough, Con; Priestley, Caroline; Wetherell, Mark

2014-01-01

Background This study assessed the effects of two doses of glucose and a caffeine–glucose combination on mood and performance of an ecologically valid, computerised multi-tasking platform. Materials and methods Following a double-blind, placebo-controlled, randomised, parallel-groups design, 150 healthy adults (mean age 34.78 years) consumed drinks containing placebo, 25 g glucose, 60 g glucose or 60 g glucose with 40 mg caffeine. They completed a multi-tasking framework at baseline and then 30 min following drink consumption with mood assessments immediately before and after the multi-tasking framework. Blood glucose and salivary caffeine were co-monitored. Results The caffeine–glucose group had significantly better total multi-tasking scores than the placebo or 60 g glucose groups and were significantly faster at mental arithmetic tasks than either glucose drink group. There were no significant treatment effects on mood. Caffeine and glucose levels confirmed compliance with overnight abstinence/fasting, respectively, and followed the predicted post-drink patterns. Conclusion These data suggest that co-administration of glucose and caffeine allows greater allocation of attentional resources than placebo or glucose alone. At present, we cannot rule out the possibility that the effects are due to caffeine alone Future studies should aim at disentangling caffeine and glucose effects. PMID:25196040

If this then that: an introduction to automated task services.

PubMed

Hoy, Matthew B

2015-01-01

This article explores automated task services, a type of website that allows users to create rules that are triggered by activity on one website and perform a task on another site. The most well-known automated task service is If This Then That (IFTTT), but recently a large number of these services have sprung up. These services can be used to connect websites, apps, business services, and even devices such as phones and home automation equipment. This allows for millions of possible combinations of rules, triggers, and actions. Librarians can put these services to use in many ways, from automating social media postings to remembering to bring their umbrella when rain is in the forecast. A list of popular automated task services is included, as well as a number of ideas for using these services in libraries.

Rapidly Measuring the Speed of Unconscious Learning: Amnesics Learn Quickly and Happy People Slowly

PubMed Central

Dienes, Zoltan; Baddeley, Roland J.; Jansari, Ashok

2012-01-01

Background We introduce a method for quickly determining the rate of implicit learning. Methodology/Principal Findings The task involves making a binary prediction for a probabilistic sequence over 10 minutes; from this it is possible to determine the influence of events of a different number of trials in the past on the current decision. This profile directly reflects the learning rate parameter of a large class of learning algorithms including the delta and Rescorla-Wagner rules. To illustrate the use of the method, we compare a person with amnesia with normal controls and we compare people with induced happy and sad moods. Conclusions/Significance Learning on the task is likely both associative and implicit. We argue theoretically and demonstrate empirically that both amnesia and also transient negative moods can be associated with an especially large learning rate: People with amnesia can learn quickly and happy people slowly. PMID:22457759

Knowledge of Previous Tasks: Task Similarity Influences Bias in Task Duration Predictions

PubMed Central

Thomas, Kevin E.; König, Cornelius J.

2018-01-01

Bias in predictions of task duration has been attributed to misremembering previous task duration and using previous task duration as a basis for predictions. This research sought to further examine how previous task information affects prediction bias by manipulating task similarity and assessing the role of previous task duration feedback. Task similarity was examined through participants performing two tasks 1 week apart that were the same or different. Duration feedback was provided to all participants (Experiment 1), its recall was manipulated (Experiment 2), and its provision was manipulated (Experiment 3). In all experiments, task similarity influenced bias on the second task, with predictions being less biased when the first task was the same task. However, duration feedback did not influence bias. The findings highlight the pivotal role of knowledge about previous tasks in task duration prediction and are discussed in relation to the theoretical accounts of task duration prediction bias. PMID:29881362

Bilinearity, Rules, and Prefrontal Cortex

PubMed Central

Dayan, Peter

2007-01-01

Humans can be instructed verbally to perform computationally complex cognitive tasks; their performance then improves relatively slowly over the course of practice. Many skills underlie these abilities; in this paper, we focus on the particular question of a uniform architecture for the instantiation of habitual performance and the storage, recall, and execution of simple rules. Our account builds on models of gated working memory, and involves a bilinear architecture for representing conditional input-output maps and for matching rules to the state of the input and working memory. We demonstrate the performance of our model on two paradigmatic tasks used to investigate prefrontal and basal ganglia function. PMID:18946523

Response Selection Difficulty and Asymmetrical Costs of Switching Between Tasks and Stimuli: No Evidence for an Exogenous Component of Task-Set Reconfiguration

ERIC Educational Resources Information Center

Hubner, Mike; Kluwe, Rainer H.; Luna-Rodriguez, Aquiles; Peters, Alexandra

2004-01-01

Four task-switching experiments examined the notion of an exogenous component of task-set reconfiguration (i.e., a process needed to shift task set that is not initiated in the absence of a task-associated figuration stimulus). The authors varied the complexity and familiarity of stimulus-response (SR) mapping rules to produce differentially…

Models of Quantitative Estimations: Rule-Based and Exemplar-Based Processes Compared

ERIC Educational Resources Information Center

von Helversen, Bettina; Rieskamp, Jorg

2009-01-01

The cognitive processes underlying quantitative estimations vary. Past research has identified task-contingent changes between rule-based and exemplar-based processes (P. Juslin, L. Karlsson, & H. Olsson, 2008). B. von Helversen and J. Rieskamp (2008), however, proposed a simple rule-based model--the mapping model--that outperformed the…

Effective Bayesian Transfer Learning

DTIC Science & Technology

2010-03-01

reasonable value of k , defined by the task B training set size. Transfer Regret 1 Regret = 100 * G AB B No Transfer With Transfer AB...a. REPORT U b . ABSTRACT U c. THIS PAGE U 19b. TELEPHONE NUMBER (Include area code) N/A Standard Form 298 (Rev. 8-98) Prescribed...rule set given the prior and developed staged approximate inference strategy, in which data from observed tasks 1 to k are used to infer general rule

Music models aberrant rule decoding and reward valuation in dementia

PubMed Central

Clark, Camilla N; Golden, Hannah L; McCallion, Oliver; Nicholas, Jennifer M; Cohen, Miriam H; Slattery, Catherine F; Paterson, Ross W; Fletcher, Phillip D; Mummery, Catherine J; Rohrer, Jonathan D; Crutch, Sebastian J; Warren, Jason D

2018-01-01

Abstract Aberrant rule- and reward-based processes underpin abnormalities of socio-emotional behaviour in major dementias. However, these processes remain poorly characterized. Here we used music to probe rule decoding and reward valuation in patients with frontotemporal dementia (FTD) syndromes and Alzheimer’s disease (AD) relative to healthy age-matched individuals. We created short melodies that were either harmonically resolved (‘finished’) or unresolved (‘unfinished’); the task was to classify each melody as finished or unfinished (rule processing) and rate its subjective pleasantness (reward valuation). Results were adjusted for elementary pitch and executive processing; neuroanatomical correlates were assessed using voxel-based morphometry. Relative to healthy older controls, patients with behavioural variant FTD showed impairments of both musical rule decoding and reward valuation, while patients with semantic dementia showed impaired reward valuation but intact rule decoding, patients with AD showed impaired rule decoding but intact reward valuation and patients with progressive non-fluent aphasia performed comparably to healthy controls. Grey matter associations with task performance were identified in anterior temporal, medial and lateral orbitofrontal cortices, previously implicated in computing diverse biological and non-biological rules and rewards. The processing of musical rules and reward distils cognitive and neuroanatomical mechanisms relevant to complex socio-emotional dysfunction in major dementias. PMID:29186630

Distrust and the positive test heuristic: dispositional and situated social distrust improves performance on the Wason rule discovery task.

PubMed

Mayo, Ruth; Alfasi, Dana; Schwarz, Norbert

2014-06-01

Feelings of distrust alert people not to take information at face value, which may influence their reasoning strategy. Using the Wason (1960) rule identification task, we tested whether chronic and temporary distrust increase the use of negative hypothesis testing strategies suited to falsify one's own initial hunch. In Study 1, participants who were low in dispositional trust were more likely to engage in negative hypothesis testing than participants high in dispositional trust. In Study 2, trust and distrust were induced through an alleged person-memory task. Paralleling the effects of chronic distrust, participants exposed to a single distrust-eliciting face were 3 times as likely to engage in negative hypothesis testing as participants exposed to a trust-eliciting face. In both studies, distrust increased negative hypothesis testing, which was associated with better performance on the Wason task. In contrast, participants' initial rule generation was not consistently affected by distrust. These findings provide first evidence that distrust can influence which reasoning strategy people adopt. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Design Characteristics Influence Performance of Clinical Prediction Rules in Validation: A Meta-Epidemiological Study.

PubMed

Ban, Jong-Wook; Emparanza, José Ignacio; Urreta, Iratxe; Burls, Amanda

2016-01-01

Many new clinical prediction rules are derived and validated. But the design and reporting quality of clinical prediction research has been less than optimal. We aimed to assess whether design characteristics of validation studies were associated with the overestimation of clinical prediction rules' performance. We also aimed to evaluate whether validation studies clearly reported important methodological characteristics. Electronic databases were searched for systematic reviews of clinical prediction rule studies published between 2006 and 2010. Data were extracted from the eligible validation studies included in the systematic reviews. A meta-analytic meta-epidemiological approach was used to assess the influence of design characteristics on predictive performance. From each validation study, it was assessed whether 7 design and 7 reporting characteristics were properly described. A total of 287 validation studies of clinical prediction rule were collected from 15 systematic reviews (31 meta-analyses). Validation studies using case-control design produced a summary diagnostic odds ratio (DOR) 2.2 times (95% CI: 1.2-4.3) larger than validation studies using cohort design and unclear design. When differential verification was used, the summary DOR was overestimated by twofold (95% CI: 1.2 -3.1) compared to complete, partial and unclear verification. The summary RDOR of validation studies with inadequate sample size was 1.9 (95% CI: 1.2 -3.1) compared to studies with adequate sample size. Study site, reliability, and clinical prediction rule was adequately described in 10.1%, 9.4%, and 7.0% of validation studies respectively. Validation studies with design shortcomings may overestimate the performance of clinical prediction rules. The quality of reporting among studies validating clinical prediction rules needs to be improved.

When representations conflict with reality: the preschooler's problem with false beliefs and "false" photographs.

PubMed

Zaitchik, D

1990-04-01

It has been argued that young preschoolers cannot correctly attribute a false belief to a deceived actor (Wimmer & Perner, 1983). Some researchers claim that the problem lies in the child's inadequate epistemology (Chandler & Boyes, 1982; Wellman, 1988); as such, it is specific to the child's theory of mind and no such problem should appear in reasoning about nonmental representations. This prediction is tested below in the "false photograph" task: here an actor takes a photograph of an object in location X; the object is then moved to location Y. Preschool subjects are asked: "In the picture, where is the object?" Results indicate that photographs are no easier to reason about than are beliefs. Manipulations to boost performance on the photograph task proved ineffective. Further, an explanation of the failure as a processing limitation having nothing to do with the representational nature of beliefs or photographs was ruled out. It is argued that young children's failure on the false belief task is not due to an inadequate epistemology (though they may have one) and is symptomatic of a larger problem with representations.

Goal neglect and knowledge chunking in the construction of novel behaviour.

PubMed

Bhandari, Apoorva; Duncan, John

2014-01-01

Task complexity is critical in cognitive efficiency and fluid intelligence. To examine functional limits in task complexity, we examine the phenomenon of goal neglect, where participants with low fluid intelligence fail to follow task rules that they otherwise understand. Though neglect is known to increase with task complexity, here we show that - in contrast to previous accounts - the critical factor is not the total complexity of all task rules. Instead, when the space of task requirements can be divided into separate sub-parts, neglect is controlled by the complexity of each component part. The data also show that neglect develops and stabilizes over the first few performance trials, i.e. as instructions are first used to generate behaviour. In all complex behaviour, a critical process is combination of task events with retrieved task requirements to create focused attentional episodes dealing with each decision in turn. In large part, we suggest, fluid intelligence may reflect this process of converting complex requirements into effective attentional episodes. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Cerebellar tDCS Does Not Enhance Performance in an Implicit Categorization Learning Task.

PubMed

Verhage, Marie C; Avila, Eric O; Frens, Maarten A; Donchin, Opher; van der Geest, Jos N

2017-01-01

Background: Transcranial Direct Current Stimulation (tDCS) is a form of non-invasive electrical stimulation that changes neuronal excitability in a polarity and site-specific manner. In cognitive tasks related to prefrontal and cerebellar learning, cortical tDCS arguably facilitates learning, but the few studies investigating cerebellar tDCS, however, are inconsistent. Objective: We investigate the effect of cerebellar tDCS on performance of an implicit categorization learning task. Methods: Forty participants performed a computerized version of an implicit categorization learning task where squares had to be sorted into two categories, according to an unknown but fixed rule that integrated both the size and luminance of the square. Participants did one round of categorization to familiarize themselves with the task and to provide a baseline of performance. After that, 20 participants received anodal tDCS (20 min, 1.5 mA) over the right cerebellum, and 19 participants received sham stimulation and simultaneously started a second session of the categorization task using a new rule. Results: As expected, subjects performed better in the second session than in the first, baseline session, showing increased accuracy scores and reduced reaction times. Over trials, participants learned the categorization rule, improving their accuracy and reaction times. However, we observed no effect of anodal tDCS stimulation on overall performance or on learning, compared to sham stimulation. Conclusion: These results suggest that cerebellar tDCS does not modulate performance and learning on an implicit categorization task.

[Usefulness of clinical prediction rules for ruling out deep vein thrombosis in a hospital emergency department].

PubMed

Rosa-Jiménez, Francisco; Rosa-Jiménez, Ascensión; Lozano-Rodríguez, Aquiles; Santoro-Martínez, María Del Carmen; Duro-López, María Del Carmen; Carreras-Álvarez de Cienfuegos, Amelia

2015-01-01

To compare the efficacy of the most familiar clinical prediction rules in combination with D-dimer testing to rule out a diagnosis of deep vein thrombosis (DVT) in a hospital emergency department. Retrospective cross-sectional analysis of the case records of all patients attending a hospital emergency department with suspected lower-limb DVT between 1998 and 2002. Ten clinical prediction scores were calculated and D-dimer levels were available for all patients. The gold standard was ultrasound diagnosis of DVT by an independent radiologist who was blinded to clinical records. For each prediction rule, we analyzed the effectiveness of the prediction strategy defined by "low clinical probability and negative D-dimer level" against the ultrasound diagnosis. A total of 861 case records were reviewed and 577 cases were selected; the mean (SD) age was 66.7 (14.2) years. DVT was diagnosed in 145 patients (25.1%). Only the Wells clinical prediction rule and 4 other models had a false negative rate under 2%. The Wells criteria and the score published by Johanning and colleagues identified higher percentages of cases (15.6% and 11.6%, respectively). This study shows that several clinical prediction rules can be safely used in the emergency department, although none of them have proven more effective than the Wells criteria.

A Study of Pattern Prediction in the Monitoring Data of Earthen Ruins with the Internet of Things.

PubMed

Xiao, Yun; Wang, Xin; Eshragh, Faezeh; Wang, Xuanhong; Chen, Xiaojiang; Fang, Dingyi

2017-05-11

An understanding of the changes of the rammed earth temperature of earthen ruins is important for protection of such ruins. To predict the rammed earth temperature pattern using the air temperature pattern of the monitoring data of earthen ruins, a pattern prediction method based on interesting pattern mining and correlation, called PPER, is proposed in this paper. PPER first finds the interesting patterns in the air temperature sequence and the rammed earth temperature sequence. To reduce the processing time, two pruning rules and a new data structure based on an R-tree are also proposed. Correlation rules between the air temperature patterns and the rammed earth temperature patterns are then mined. The correlation rules are merged into predictive rules for the rammed earth temperature pattern. Experiments were conducted to show the accuracy of the presented method and the power of the pruning rules. Moreover, the Ming Dynasty Great Wall dataset was used to examine the algorithm, and six predictive rules from the air temperature to rammed earth temperature based on the interesting patterns were obtained, with the average hit rate reaching 89.8%. The PPER and predictive rules will be useful for rammed earth temperature prediction in protection of earthen ruins.

Social and nonsocial category discriminations in a chimpanzee (Pan troglodytes) and American black bears (Ursus americanus).

PubMed

Vonk, Jennifer; Johnson-Ulrich, Zoe

2014-09-01

One captive adult chimpanzee and 3 adult American black bears were presented with a series of natural category discrimination tasks on a touch-screen computer. This is the first explicit comparison of bear and primate abilities using identical tasks, and the first test of a social concept in a carnivore. The discriminations involved a social relationship category (mother/offspring) and a nonsocial category involving food items. The social category discrimination could be made using knowledge of the overarching mother/offspring concept, whereas the nonsocial category discriminations could be made only by using perceptual rules, such as "choose images that show larger and smaller items of the same type." The bears failed to show above-chance transfer on either the social or nonsocial discriminations, indicating that they did not use either the perceptual rule or knowledge of the overarching concept of mother/offspring to guide their choices in these tasks. However, at least 1 bear remembered previously reinforced stimuli when these stimuli were recombined, later. The chimpanzee showed transfer on a control task and did not consistently apply a perceptual rule to solve the nonsocial task, so it is possible that he eventually acquired the social concept. Further comparisons between species on identical tasks assessing social knowledge will help illuminate the selective pressures responsible for a range of social cognitive skills.

Strategic behavior, workload, and performance in task scheduling

NASA Technical Reports Server (NTRS)

Moray, Neville; Dessouky, Mohamed I.; Kijowski, Brian A.; Adapathya, Ravi

1991-01-01

Scheduling theory is proposed as a normative model for strategic behavior when operators are confronted by several tasks, all of which should be completed within a fixed time span, and when they are free to choose the order in which the tasks should be done. Three experiments are described to investigate the effect of knowing the correct scheduling rule on the efficiency of performance, subjective workload, and choice of strategy under different conditions of time pressure. The most potent effects are from time pressure. The reasons for the weak effect of knowing the rules are discussed, and implications for strategic behavior, displays, and decision aids are indicated.

Task switching in rhesus macaques (Macaca mulatta) and tufted capuchin monkeys (Cebus apella) during computerized categorization tasks.

PubMed

Smith, Travis R; Beran, Michael J

2018-05-31

The present experiments extended to monkeys a previously used abstract categorization procedure (Castro & Wasserman, 2016) where pigeons had categorized arrays of clipart icons based upon two task rules: the number of clipart objects in the array or the variability of objects in the array. Experiment 1 replicated Castro and Wasserman by using capuchin monkeys and rhesus monkeys and reported that monkeys' performances were similar to pigeons' in terms of acquisition, pattern of errors, and the absence of switch costs. Furthermore, monkeys' insensitivity to the added irrelevant information suggested that an associative (rather than rule-based) categorization mechanism was dominant. Experiment 2 was conducted to include categorization cue reversals to determine (a) whether the monkeys would quickly adapt to the reversals and inhibit interference from a prereversal task rule (consistent with a rule-based mechanism) and (b) whether the latency to make a response prior to a correct or incorrect outcome was informative about the presence of a cognitive mechanism. The cue reassignment produced profound and long-lasting performance deficits, and a long reacquisition phase suggested the involvement of associative learning processes; however, monkeys also displayed longer latencies to choose prior to correct responses on challenging trials, suggesting the involvement of nonassociative processes. Together these performances suggest a mix of associative and cognitive-control processes governing monkey categorization judgments. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Self-Associations Influence Task-Performance through Bayesian Inference

PubMed Central

Bengtsson, Sara L.; Penny, Will D.

2013-01-01

The way we think about ourselves impacts greatly on our behavior. This paper describes a behavioral study and a computational model that shed new light on this important area. Participants were primed “clever” and “stupid” using a scrambled sentence task, and we measured the effect on response time and error-rate on a rule-association task. First, we observed a confirmation bias effect in that associations to being “stupid” led to a gradual decrease in performance, whereas associations to being “clever” did not. Second, we observed that the activated self-concepts selectively modified attention toward one’s performance. There was an early to late double dissociation in RTs in that primed “clever” resulted in RT increase following error responses, whereas primed “stupid” resulted in RT increase following correct responses. We propose a computational model of subjects’ behavior based on the logic of the experimental task that involves two processes; memory for rules and the integration of rules with subsequent visual cues. The model incorporates an adaptive decision threshold based on Bayes rule, whereby decision thresholds are increased if integration was inferred to be faulty. Fitting the computational model to experimental data confirmed our hypothesis that priming affects the memory process. This model explains both the confirmation bias and double dissociation effects and demonstrates that Bayesian inferential principles can be used to study the effect of self-concepts on behavior. PMID:23966937

A Short Note on Rules and Higher Order Rules.

ERIC Educational Resources Information Center

Scandura, Joseph M.

This brief paper argues that structural analysis--an extended form of cognitive task analysis--demonstrates that both domain dependent and domain independent knowledge can be derived from specific content domains. It is noted that the major difference between the two is that lower order rules (specific knowledge) are derived directly from specific…

Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

ERIC Educational Resources Information Center

Zhang, Zhidong

2016-01-01

This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

Children's Knowledge of Display Rules for Emotional Expression and Control.

ERIC Educational Resources Information Center

Doubleday, Catherine; And Others

An important task for children is to acquire their culture's rules for emotional display. Accurate knowledge of display rules prescribing, for example, safe targets for anger or indelicate situations for excitement helps regulate expressive behavior and mediate the impact of emotional expression on the self and others. In this study, children's…

One Giant Leap for Categorizers: One Small Step for Categorization Theory

PubMed Central

Smith, J. David; Ell, Shawn W.

2015-01-01

We explore humans’ rule-based category learning using analytic approaches that highlight their psychological transitions during learning. These approaches confirm that humans show qualitatively sudden psychological transitions during rule learning. These transitions contribute to the theoretical literature contrasting single vs. multiple category-learning systems, because they seem to reveal a distinctive learning process of explicit rule discovery. A complete psychology of categorization must describe this learning process, too. Yet extensive formal-modeling analyses confirm that a wide range of current (gradient-descent) models cannot reproduce these transitions, including influential rule-based models (e.g., COVIS) and exemplar models (e.g., ALCOVE). It is an important theoretical conclusion that existing models cannot explain humans’ rule-based category learning. The problem these models have is the incremental algorithm by which learning is simulated. Humans descend no gradient in rule-based tasks. Very different formal-modeling systems will be required to explain humans’ psychology in these tasks. An important next step will be to build a new generation of models that can do so. PMID:26332587

Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks

PubMed Central

Miconi, Thomas

2017-01-01

Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial. Networks endowed with this learning rule can successfully learn nontrivial tasks requiring flexible (context-dependent) associations, memory maintenance, nonlinear mixed selectivities, and coordination among multiple outputs. The resulting networks replicate complex dynamics previously observed in animal cortex, such as dynamic encoding of task features and selective integration of sensory inputs. We conclude that recurrent neural networks offer a plausible model of cortical dynamics during both learning and performance of flexible behavior. DOI: http://dx.doi.org/10.7554/eLife.20899.001 PMID:28230528

Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks.

PubMed

Miconi, Thomas

2017-02-23

Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial. Networks endowed with this learning rule can successfully learn nontrivial tasks requiring flexible (context-dependent) associations, memory maintenance, nonlinear mixed selectivities, and coordination among multiple outputs. The resulting networks replicate complex dynamics previously observed in animal cortex, such as dynamic encoding of task features and selective integration of sensory inputs. We conclude that recurrent neural networks offer a plausible model of cortical dynamics during both learning and performance of flexible behavior.

Dynamical genetic programming in XCSF.

PubMed

Preen, Richard J; Bull, Larry

2013-01-01

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to artificial neural networks. This paper presents results from an investigation into using a temporally dynamic symbolic representation within the XCSF learning classifier system. In particular, dynamical arithmetic networks are used to represent the traditional condition-action production system rules to solve continuous-valued reinforcement learning problems and to perform symbolic regression, finding competitive performance with traditional genetic programming on a number of composite polynomial tasks. In addition, the network outputs are later repeatedly sampled at varying temporal intervals to perform multistep-ahead predictions of a financial time series.

Search performance is better predicted by tileability than presence of a unique basic feature.

PubMed

Chang, Honghua; Rosenholtz, Ruth

2016-08-01

Traditional models of visual search such as feature integration theory (FIT; Treisman & Gelade, 1980), have suggested that a key factor determining task difficulty consists of whether or not the search target contains a "basic feature" not found in the other display items (distractors). Here we discriminate between such traditional models and our recent texture tiling model (TTM) of search (Rosenholtz, Huang, Raj, Balas, & Ilie, 2012b), by designing new experiments that directly pit these models against each other. Doing so is nontrivial, for two reasons. First, the visual representation in TTM is fully specified, and makes clear testable predictions, but its complexity makes getting intuitions difficult. Here we elucidate a rule of thumb for TTM, which enables us to easily design new and interesting search experiments. FIT, on the other hand, is somewhat ill-defined and hard to pin down. To get around this, rather than designing totally new search experiments, we start with five classic experiments that FIT already claims to explain: T among Ls, 2 among 5s, Q among Os, O among Qs, and an orientation/luminance-contrast conjunction search. We find that fairly subtle changes in these search tasks lead to significant changes in performance, in a direction predicted by TTM, providing definitive evidence in favor of the texture tiling model as opposed to traditional views of search.

Search performance is better predicted by tileability than presence of a unique basic feature

PubMed Central

Chang, Honghua; Rosenholtz, Ruth

2016-01-01

Traditional models of visual search such as feature integration theory (FIT; Treisman & Gelade, 1980), have suggested that a key factor determining task difficulty consists of whether or not the search target contains a “basic feature” not found in the other display items (distractors). Here we discriminate between such traditional models and our recent texture tiling model (TTM) of search (Rosenholtz, Huang, Raj, Balas, & Ilie, 2012b), by designing new experiments that directly pit these models against each other. Doing so is nontrivial, for two reasons. First, the visual representation in TTM is fully specified, and makes clear testable predictions, but its complexity makes getting intuitions difficult. Here we elucidate a rule of thumb for TTM, which enables us to easily design new and interesting search experiments. FIT, on the other hand, is somewhat ill-defined and hard to pin down. To get around this, rather than designing totally new search experiments, we start with five classic experiments that FIT already claims to explain: T among Ls, 2 among 5s, Q among Os, O among Qs, and an orientation/luminance-contrast conjunction search. We find that fairly subtle changes in these search tasks lead to significant changes in performance, in a direction predicted by TTM, providing definitive evidence in favor of the texture tiling model as opposed to traditional views of search. PMID:27548090

Are there signature limits in early theory of mind?

PubMed

Fizke, Ella; Butterfill, Stephen; van de Loo, Lea; Reindl, Eva; Rakoczy, Hannes

2017-10-01

Current theory-of-mind research faces the challenge of reconciling two sets of seemingly incompatible findings: Whereas children come to solve explicit verbal false belief (FB) tasks from around 4years of age, recent studies with various less explicit measures such as looking time, anticipatory looking, and spontaneous behavior suggest that even infants can succeed on some FB tasks. In response to this tension, two-systems theories propose to distinguish between an early-developing system, tracking simple forms of mental states, and a later-developing system, based on fully developed concepts of belief and other propositional attitudes. One prediction of such theories is that the early-developing system has signature limits concerning aspectuality. We tested this prediction in two experiments. The first experiment showed (in line with previous findings) that 2- and 3-year-olds take into account a protagonist's true or false belief about the location of an object in their active helping behavior. In contrast, toddlers' helping behavior did not differentiate between true and false belief conditions when the protagonist's belief essentially involved aspectuality. Experiment 2 replicated these findings with a more stringent method designed to rule out more parsimonious explanations. Taken together, the current findings are compatible with the possibility that early theory-of-mind reasoning is subject to signature limits as predicted by the two-systems account. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantity yields quality when it comes to creativity: a brain and behavioral test of the equal-odds rule

PubMed Central

Jung, Rex E.; Wertz, Christopher J.; Meadows, Christine A.; Ryman, Sephira G.; Vakhtin, Andrei A.; Flores, Ranee A.

2015-01-01

The creativity research community is in search of a viable cognitive measure providing support for behavioral observations that higher ideational output is often associated with higher creativity (known as the equal-odds rule). One such measure has included divergent thinking: the production of many examples or uses for a common or single object or image. We sought to test the equal-odds rule using a measure of divergent thinking, and applied the consensual assessment technique to determine creative responses as opposed to merely original responses. We also sought to determine structural brain correlates of both ideational fluency and ideational creativity. Two-hundred forty-six subjects were subjected to a broad battery of behavioral measures, including a core measure of divergent thinking (Foresight), and measures of intelligence, creative achievement, and personality (i.e., Openness to Experience). Cortical thickness and subcortical volumes (e.g., thalamus) were measured using automated techniques (FreeSurfer). We found that higher number of responses on the divergent thinking task was significantly associated with higher creativity (r = 0.73) as independently assessed by three judges. Moreover, we found that creativity was predicted by cortical thickness in regions including the left frontal pole and left parahippocampal gyrus. These results support the equal-odds rule, and provide neuronal evidence implicating brain regions involved with “thinking about the future” and “extracting future prospects.” PMID:26161075

Intuitive and deliberate judgments are based on common principles.

PubMed

Kruglanski, Arie W; Gigerenzer, Gerd

2011-01-01

A popular distinction in cognitive and social psychology has been between intuitive and deliberate judgments. This juxtaposition has aligned in dual-process theories of reasoning associative, unconscious, effortless, heuristic, and suboptimal processes (assumed to foster intuitive judgments) versus rule-based, conscious, effortful, analytic, and rational processes (assumed to characterize deliberate judgments). In contrast, we provide convergent arguments and evidence for a unified theoretical approach to both intuitive and deliberative judgments. Both are rule-based, and in fact, the very same rules can underlie both intuitive and deliberate judgments. The important open question is that of rule selection, and we propose a 2-step process in which the task itself and the individual's memory constrain the set of applicable rules, whereas the individual's processing potential and the (perceived) ecological rationality of the rule for the task guide the final selection from that set. Deliberate judgments are not generally more accurate than intuitive judgments; in both cases, accuracy depends on the match between rule and environment: the rules' ecological rationality. Heuristics that are less effortful and in which parts of the information are ignored can be more accurate than cognitive strategies that have more information and computation. The proposed framework adumbrates a unified approach that specifies the critical dimensions on which judgmental situations may vary and the environmental conditions under which rules can be expected to be successful.

Rules for Optical Testing

NASA Technical Reports Server (NTRS)

Stahl, H. Philip

2014-01-01

Based on 30 years of optical testing experience, a lot of mistakes, a lot of learning and a lot of experience, I have defined seven guiding principles for optical testing - regardless of how small or how large the optical testing or metrology task: Fully Understand the Task, Develop an Error Budget, Continuous Metrology Coverage, Know where you are, Test like you fly, Independent Cross-Checks, Understand All Anomalies. These rules have been applied with great success to the inprocess optical testing and final specification compliance testing of the JWST mirrors.

Learning Semantic Tags from Big Data for Clinical Text Representation.

PubMed

Li, Yanpeng; Liu, Hongfang

2015-01-01

In clinical text mining, it is one of the biggest challenges to represent medical terminologies and n-gram terms in sparse medical reports using either supervised or unsupervised methods. Addressing this issue, we propose a novel method for word and n-gram representation at semantic level. We first represent each word by its distance with a set of reference features calculated by reference distance estimator (RDE) learned from labeled and unlabeled data, and then generate new features using simple techniques of discretization, random sampling and merging. The new features are a set of binary rules that can be interpreted as semantic tags derived from word and n-grams. We show that the new features significantly outperform classical bag-of-words and n-grams in the task of heart disease risk factor extraction in i2b2 2014 challenge. It is promising to see that semantics tags can be used to replace the original text entirely with even better prediction performance as well as derive new rules beyond lexical level.

Uncertainty Reduction for Stochastic Processes on Complex Networks

NASA Astrophysics Data System (ADS)

Radicchi, Filippo; Castellano, Claudio

2018-05-01

Many real-world systems are characterized by stochastic dynamical rules where a complex network of interactions among individual elements probabilistically determines their state. Even with full knowledge of the network structure and of the stochastic rules, the ability to predict system configurations is generally characterized by a large uncertainty. Selecting a fraction of the nodes and observing their state may help to reduce the uncertainty about the unobserved nodes. However, choosing these points of observation in an optimal way is a highly nontrivial task, depending on the nature of the stochastic process and on the structure of the underlying interaction pattern. In this paper, we introduce a computationally efficient algorithm to determine quasioptimal solutions to the problem. The method leverages network sparsity to reduce computational complexity from exponential to almost quadratic, thus allowing the straightforward application of the method to mid-to-large-size systems. Although the method is exact only for equilibrium stochastic processes defined on trees, it turns out to be effective also for out-of-equilibrium processes on sparse loopy networks.

Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods.

PubMed

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J Sunil

2014-08-01

We introduce a survival/risk bump hunting framework to build a bump hunting model with a possibly censored time-to-event type of response and to validate model estimates. First, we describe the use of adequate survival peeling criteria to build a survival/risk bump hunting model based on recursive peeling methods. Our method called "Patient Recursive Survival Peeling" is a rule-induction method that makes use of specific peeling criteria such as hazard ratio or log-rank statistics. Second, to validate our model estimates and improve survival prediction accuracy, we describe a resampling-based validation technique specifically designed for the joint task of decision rule making by recursive peeling (i.e. decision-box) and survival estimation. This alternative technique, called "combined" cross-validation is done by combining test samples over the cross-validation loops, a design allowing for bump hunting by recursive peeling in a survival setting. We provide empirical results showing the importance of cross-validation and replication.

Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

We introduce a survival/risk bump hunting framework to build a bump hunting model with a possibly censored time-to-event type of response and to validate model estimates. First, we describe the use of adequate survival peeling criteria to build a survival/risk bump hunting model based on recursive peeling methods. Our method called “Patient Recursive Survival Peeling” is a rule-induction method that makes use of specific peeling criteria such as hazard ratio or log-rank statistics. Second, to validate our model estimates and improve survival prediction accuracy, we describe a resampling-based validation technique specifically designed for the joint task of decision rule making by recursive peeling (i.e. decision-box) and survival estimation. This alternative technique, called “combined” cross-validation is done by combining test samples over the cross-validation loops, a design allowing for bump hunting by recursive peeling in a survival setting. We provide empirical results showing the importance of cross-validation and replication. PMID:26997922

Brain signatures of early lexical and morphological learning of a new language.

PubMed

Havas, Viktória; Laine, Matti; Rodríguez Fornells, Antoni

2017-07-01

Morphology is an important part of language processing but little is known about how adult second language learners acquire morphological rules. Using a word-picture associative learning task, we have previously shown that a brief exposure to novel words with embedded morphological structure (suffix for natural gender) is enough for language learners to acquire the hidden morphological rule. Here we used this paradigm to study the brain signatures of early morphological learning in a novel language in adults. Behavioural measures indicated successful lexical (word stem) and morphological (gender suffix) learning. A day after the learning phase, event-related brain potentials registered during a recognition memory task revealed enhanced N400 and P600 components for stem and suffix violations, respectively. An additional effect observed with combined suffix and stem violations was an enhancement of an early N2 component, most probably related to conflict-detection processes. Successful morphological learning was also evident in the ERP responses to the subsequent rule-generalization task with new stems, where violation of the morphological rule was associated with an early (250-400ms) and late positivity (750-900ms). Overall, these findings tend to converge with lexical and morphosyntactic violation effects observed in L1 processing, suggesting that even after a short exposure, adult language learners can acquire both novel words and novel morphological rules. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Integrated Children Disease Prediction Tool within a Special Social Network.

PubMed

Apostolova Trpkovska, Marika; Yildirim Yayilgan, Sule; Besimi, Adrian

2016-01-01

This paper proposes a social network with an integrated children disease prediction system developed by the use of the specially designed Children General Disease Ontology (CGDO). This ontology consists of children diseases and their relationship with symptoms and Semantic Web Rule Language (SWRL rules) that are specially designed for predicting diseases. The prediction process starts by filling data about the appeared signs and symptoms by the user which are after that mapped with the CGDO ontology. Once the data are mapped, the prediction results are presented. The phase of prediction executes the rules which extract the predicted disease details based on the SWRL rule specified. The motivation behind the development of this system is to spread knowledge about the children diseases and their symptoms in a very simple way using the specialized social networking website www.emama.mk.

Speed-Accuracy Response Models: Scoring Rules Based on Response Time and Accuracy

ERIC Educational Resources Information Center

Maris, Gunter; van der Maas, Han

2012-01-01

Starting from an explicit scoring rule for time limit tasks incorporating both response time and accuracy, and a definite trade-off between speed and accuracy, a response model is derived. Since the scoring rule is interpreted as a sufficient statistic, the model belongs to the exponential family. The various marginal and conditional distributions…

Service without a Smile: Comparing the Consequences of Neutral and Positive Display Rules

ERIC Educational Resources Information Center

Trougakos, John P.; Jackson, Christine L.; Beal, Daniel J.

2011-01-01

We used an experimental design to examine the intrapersonal and interpersonal processes through which neutral display rules, compared to positive display rules, influence objective task performance of poll workers and ratings provided by survey respondents of the poll workers. Student participants (N = 140) were trained to adhere to 1 of the 2…

Amnestic mild cognitive impairment: functional MR imaging study of response in posterior cingulate cortex and adjacent precuneus during problem-solving tasks.

PubMed

Jin, Guangwei; Li, Kuncheng; Hu, Yingying; Qin, Yulin; Wang, Xiangqing; Xiang, Jie; Yang, Yanhui; Lu, Jie; Zhong, Ning

2011-11-01

To compare the blood oxygen level-dependent (BOLD) response, measured with functional magnetic resonance (MR) imaging, in the posterior cingulate cortex (PCC) and adjacent precuneus regions between healthy control subjects and patients with amnestic mild cognitive impairment (MCI) during problem-solving tasks. This study was approved by the institutional review board. Each subject provided written informed consent. Thirteen patients with amnestic MCI and 13 age- and sex-matched healthy control subjects participated in the study. The functional magnetic resonance (MR) imaging tasks were simplified 4 × 4-grid number placement puzzles that were divided into a simple task (using the row rule or the column rule to solve the puzzle) and a complex task (using both the row and column rules to solve the puzzle). Behavioral results and functional imaging results between the healthy control group and the amnestic MCI group were analyzed. The accuracy for the complex task in the healthy control group was significantly higher than that in the amnestic MCI group (P < .05). The healthy control group exhibited a deactivated BOLD signal intensity (SI) change in the bilateral PCC and adjacent precuneus regions during the complex task, whereas the amnestic MCI group showed activation. The positive linear correlations between the BOLD SI change in bilateral PCC and adjacent precuneus regions and in bilateral hippocampi in the amnestic MCI group were significant (P < .001), while in the healthy control group, they were not (P ≥ .23). These findings suggest that an altered BOLD response in amnestic MCI patients during complex tasks might be related to a decline in problem-solving ability and to memory impairment and, thus, may indicate a compensatory response to memory impairment. RSNA, 2011

Broca's area and the language instinct.

PubMed

Musso, Mariacristina; Moro, Andrea; Glauche, Volkmar; Rijntjes, Michel; Reichenbach, Jürgen; Büchel, Christian; Weiller, Cornelius

2003-07-01

Language acquisition in humans relies on abilities like abstraction and use of syntactic rules, which are absent in other animals. The neural correlate of acquiring new linguistic competence was investigated with two functional magnetic resonance imaging (fMRI) studies. German native speakers learned a sample of 'real' grammatical rules of different languages (Italian or Japanese), which, although parametrically different, follow the universal principles of grammar (UG). Activity during this task was compared with that during a task that involved learning 'unreal' rules of language. 'Unreal' rules were obtained manipulating the original two languages; they used the same lexicon as Italian or Japanese, but were linguistically illegal, as they violated the principles of UG. Increase of activation over time in Broca's area was specific for 'real' language acquisition only, independent of the kind of language. Thus, in Broca's area, biological constraints and language experience interact to enable linguistic competence for a new language.

Design Characteristics Influence Performance of Clinical Prediction Rules in Validation: A Meta-Epidemiological Study

PubMed Central

Ban, Jong-Wook; Emparanza, José Ignacio; Urreta, Iratxe; Burls, Amanda

2016-01-01

Background Many new clinical prediction rules are derived and validated. But the design and reporting quality of clinical prediction research has been less than optimal. We aimed to assess whether design characteristics of validation studies were associated with the overestimation of clinical prediction rules’ performance. We also aimed to evaluate whether validation studies clearly reported important methodological characteristics. Methods Electronic databases were searched for systematic reviews of clinical prediction rule studies published between 2006 and 2010. Data were extracted from the eligible validation studies included in the systematic reviews. A meta-analytic meta-epidemiological approach was used to assess the influence of design characteristics on predictive performance. From each validation study, it was assessed whether 7 design and 7 reporting characteristics were properly described. Results A total of 287 validation studies of clinical prediction rule were collected from 15 systematic reviews (31 meta-analyses). Validation studies using case-control design produced a summary diagnostic odds ratio (DOR) 2.2 times (95% CI: 1.2–4.3) larger than validation studies using cohort design and unclear design. When differential verification was used, the summary DOR was overestimated by twofold (95% CI: 1.2 -3.1) compared to complete, partial and unclear verification. The summary RDOR of validation studies with inadequate sample size was 1.9 (95% CI: 1.2 -3.1) compared to studies with adequate sample size. Study site, reliability, and clinical prediction rule was adequately described in 10.1%, 9.4%, and 7.0% of validation studies respectively. Conclusion Validation studies with design shortcomings may overestimate the performance of clinical prediction rules. The quality of reporting among studies validating clinical prediction rules needs to be improved. PMID:26730980

Automated revision of CLIPS rule-bases

NASA Technical Reports Server (NTRS)

Murphy, Patrick M.; Pazzani, Michael J.

1994-01-01

This paper describes CLIPS-R, a theory revision system for the revision of CLIPS rule-bases. CLIPS-R may be used for a variety of knowledge-base revision tasks, such as refining a prototype system, adapting an existing system to slightly different operating conditions, or improving an operational system that makes occasional errors. We present a description of how CLIPS-R revises rule-bases, and an evaluation of the system on three rule-bases.

Cognitive Control over Learning: Creating, Clustering, and Generalizing Task-Set Structure

ERIC Educational Resources Information Center

Collins, Anne G. E.; Frank, Michael J.

2013-01-01

Learning and executive functions such as task-switching share common neural substrates, notably prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for…

Role of Prefrontal Cortex in Learning and Generalizing Hierarchical Rules in 8-Month-Old Infants.

PubMed

Werchan, Denise M; Collins, Anne G E; Frank, Michael J; Amso, Dima

2016-10-05

Recent research indicates that adults and infants spontaneously create and generalize hierarchical rule sets during incidental learning. Computational models and empirical data suggest that, in adults, this process is supported by circuits linking prefrontal cortex (PFC) with striatum and their modulation by dopamine, but the neural circuits supporting this form of learning in infants are largely unknown. We used near-infrared spectroscopy to record PFC activity in 8-month-old human infants during a simple audiovisual hierarchical-rule-learning task. Behavioral results confirmed that infants adopted hierarchical rule sets to learn and generalize spoken object-label mappings across different speaker contexts. Infants had increased activity over right dorsal lateral PFC when rule sets switched from one trial to the next, a neural marker related to updating rule sets into working memory in the adult literature. Infants' eye blink rate, a possible physiological correlate of striatal dopamine activity, also increased when rule sets switched from one trial to the next. Moreover, the increase in right dorsolateral PFC activity in conjunction with eye blink rate also predicted infants' generalization ability, providing exploratory evidence for frontostriatal involvement during learning. These findings provide evidence that PFC is involved in rudimentary hierarchical rule learning in 8-month-old infants, an ability that was previously thought to emerge later in life in concert with PFC maturation. Hierarchical rule learning is a powerful learning mechanism that allows rules to be selected in a context-appropriate fashion and transferred or reused in novel contexts. Data from computational models and adults suggests that this learning mechanism is supported by dopamine-innervated interactions between prefrontal cortex (PFC) and striatum. Here, we provide evidence that PFC also supports hierarchical rule learning during infancy, challenging the current dogma that PFC is an underdeveloped brain system until adolescence. These results add new insights into the neurobiological mechanisms available to support learning and generalization in very early postnatal life, providing evidence that PFC and the frontostriatal circuitry are involved in organizing learning and behavior earlier in life than previously known. Copyright © 2016 the authors 0270-6474/16/3610314-09$15.00/0.

Role of Prefrontal Cortex in Learning and Generalizing Hierarchical Rules in 8-Month-Old Infants

PubMed Central

Werchan, Denise M.; Collins, Anne G.E.; Frank, Michael J.

2016-01-01

Recent research indicates that adults and infants spontaneously create and generalize hierarchical rule sets during incidental learning. Computational models and empirical data suggest that, in adults, this process is supported by circuits linking prefrontal cortex (PFC) with striatum and their modulation by dopamine, but the neural circuits supporting this form of learning in infants are largely unknown. We used near-infrared spectroscopy to record PFC activity in 8-month-old human infants during a simple audiovisual hierarchical-rule-learning task. Behavioral results confirmed that infants adopted hierarchical rule sets to learn and generalize spoken object–label mappings across different speaker contexts. Infants had increased activity over right dorsal lateral PFC when rule sets switched from one trial to the next, a neural marker related to updating rule sets into working memory in the adult literature. Infants' eye blink rate, a possible physiological correlate of striatal dopamine activity, also increased when rule sets switched from one trial to the next. Moreover, the increase in right dorsolateral PFC activity in conjunction with eye blink rate also predicted infants' generalization ability, providing exploratory evidence for frontostriatal involvement during learning. These findings provide evidence that PFC is involved in rudimentary hierarchical rule learning in 8-month-old infants, an ability that was previously thought to emerge later in life in concert with PFC maturation. SIGNIFICANCE STATEMENT Hierarchical rule learning is a powerful learning mechanism that allows rules to be selected in a context-appropriate fashion and transferred or reused in novel contexts. Data from computational models and adults suggests that this learning mechanism is supported by dopamine-innervated interactions between prefrontal cortex (PFC) and striatum. Here, we provide evidence that PFC also supports hierarchical rule learning during infancy, challenging the current dogma that PFC is an underdeveloped brain system until adolescence. These results add new insights into the neurobiological mechanisms available to support learning and generalization in very early postnatal life, providing evidence that PFC and the frontostriatal circuitry are involved in organizing learning and behavior earlier in life than previously known. PMID:27707968

A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules

PubMed Central

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

2015-01-01

Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods. PMID:25938136

A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules.

PubMed

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods.

Enhanced visual processing contributes to matrix reasoning in autism

PubMed Central

Soulières, Isabelle; Dawson, Michelle; Samson, Fabienne; Barbeau, Elise B.; Sahyoun, Cherif; Strangman, Gary E.; Zeffiro, Thomas A.; Mottron, Laurent

2009-01-01

Recent behavioral investigations have revealed that autistics perform more proficiently on Raven's Standard Progressive Matrices (RSPM) than would be predicted by their Wechsler intelligence scores. A widely-used test of fluid reasoning and intelligence, the RSPM assays abilities to flexibly infer rules, manage goal hierarchies, and perform high-level abstractions. The neural substrates for these abilities are known to encompass a large frontoparietal network, with different processing models placing variable emphasis on the specific roles of the prefrontal or posterior regions. We used functional magnetic resonance imaging to explore the neural bases of autistics' RSPM problem solving. Fifteen autistic and eighteen non-autistic participants, matched on age, sex, manual preference and Wechsler IQ, completed 60 self-paced randomly-ordered RSPM items along with a visually similar 60-item pattern matching comparison task. Accuracy and response times did not differ between groups in the pattern matching task. In the RSPM task, autistics performed with similar accuracy, but with shorter response times, compared to their non-autistic controls. In both the entire sample and a subsample of participants additionally matched on RSPM performance to control for potential response time confounds, neural activity was similar in both groups for the pattern matching task. However, for the RSPM task, autistics displayed relatively increased task-related activity in extrastriate areas (BA18), and decreased activity in the lateral prefrontal cortex (BA9) and the medial posterior parietal cortex (BA7). Visual processing mechanisms may therefore play a more prominent role in reasoning in autistics. PMID:19530215

A neurocomputational account of cognitive deficits in Parkinson’s disease

PubMed Central

Hélie, Sébastien; Paul, Erick J.; Ashby, F. Gregory

2014-01-01

Parkinson’s disease (PD) is caused by the accelerated death of dopamine (DA) producing neurons. Numerous studies documenting cognitive deficits of PD patients have revealed impairments in a variety of tasks related to memory, learning, visuospatial skills, and attention. While there have been several studies documenting cognitive deficits of PD patients, very few computational models have been proposed. In this article, we use the COVIS model of category learning to simulate DA depletion and show that the model suffers from cognitive symptoms similar to those of human participants affected by PD. Specifically, DA depletion in COVIS produced deficits in rule-based categorization, non-linear information-integration categorization, probabilistic classification, rule maintenance, and rule switching. These were observed by simulating results from younger controls, older controls, PD patients, and severe PD patients in five well-known tasks. Differential performance among the different age groups and clinical populations was modeled simply by changing the amount of DA available in the model. This suggests that COVIS may not only be an adequate model of the simulated tasks and phenomena but also more generally of the role of DA in these tasks and phenomena. PMID:22683450

Modelling Chemical Reasoning to Predict and Invent Reactions.

PubMed

Segler, Marwin H S; Waller, Mark P

2017-05-02

The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

New social tasks for cognitive psychology; or, new cognitive tasks for social psychology.

PubMed

Wettersten, John

2014-01-01

To elucidate how differing theories of rationality lead to differing practices, their social rules must be analyzed. This is true not merely in science but also in society at large. This analysis of social thinking requires both the identification of innate cognitive social psychological processes and explanations of their relations with differing rules of rational practice. These new tasks can enable social psychologists to contribute to the study of how social situations facilitate or inhibit rational practice and enable cognitive psychologists to improve social psychological theory. In contrast to dominant current research strategies, social and cognitive psychologists can integrate social studies of rational practices and their consequences with studies of underlying cognitive psychological processes. In this article I do not attempt to carry out these tasks but rather point to both their lack of recognition and their importance.

Performance predictions affect attentional processes of event-based prospective memory.

PubMed

Rummel, Jan; Kuhlmann, Beatrice G; Touron, Dayna R

2013-09-01

To investigate whether making performance predictions affects prospective memory (PM) processing, we asked one group of participants to predict their performance in a PM task embedded in an ongoing task and compared their performance with a control group that made no predictions. A third group gave not only PM predictions but also ongoing-task predictions. Exclusive PM predictions resulted in slower ongoing-task responding both in a nonfocal (Experiment 1) and in a focal (Experiment 2) PM task. Only in the nonfocal task was the additional slowing accompanied by improved PM performance. Even in the nonfocal task, however, was the correlation between ongoing-task speed and PM performance reduced after predictions, suggesting that the slowing was not completely functional for PM. Prediction-induced changes could be avoided by asking participants to additionally predict their performance in the ongoing task. In sum, the present findings substantiate a role of metamemory for attention-allocation strategies of PM. Copyright © 2013 Elsevier Inc. All rights reserved.

Role of medial cortical, hippocampal and striatal interactions during cognitive set-shifting.

PubMed

Graham, Steven; Phua, Elaine; Soon, Chun Siong; Oh, Tomasina; Au, Chris; Shuter, Borys; Wang, Shih-Chang; Yeh, Ing Berne

2009-05-01

To date, few studies have examined the functional connectivity of brain regions involved in complex executive function tasks, such as cognitive set-shifting. In this study, eighteen healthy volunteers performed a cognitive set-shifting task modified from the Wisconsin card sort test while undergoing functional magnetic resonance imaging. These modifications allowed better disambiguation between cognitive processes and revealed several novel findings: 1) peak activation in the caudate nuclei in the first instance of negative feedback signaling a shift in rule, 2) lowest caudate activation once the rule had been identified, 3) peak hippocampal activation once the identity of the rule had been established, and 4) decreased hippocampal activation during the generation of new rule candidates. This pattern of activation across cognitive set-shifting events suggests that the caudate nuclei play a role in response generation when the identity of the new rule is unknown. In contrast, the reciprocal pattern of hippocampal activation suggests that the hippocampi help consolidate knowledge about the correct stimulus-stimulus associations, associations that become inappropriate once the rule has changed. Functional connectivity analysis using Granger Causality Mapping revealed that caudate and hippocampal regions interacted indirectly via a circuit involving the medial orbitofrontal and posterior cingulate regions, which are known to bias attention towards stimuli based on expectations built up from task-related feedback. Taken together, the evidence suggests that these medial regions may mediate striato-hippocampal interactions and hence affect goal-directed attentional transitions from a response strategy based on stimulus-reward heuristics (caudate-dependent) to one based on stimulus-stimulus associations (hippocampus-dependent).

Rule-Guided Executive Control of Response Inhibition: Functional Topography of the Inferior Frontal Cortex

PubMed Central

Cai, Weidong; Leung, Hoi-Chung

2011-01-01

Background The human inferior frontal cortex (IFC) is a large heterogeneous structure with distinct cytoarchitectonic subdivisions and fiber connections. It has been found involved in a wide range of executive control processes from target detection, rule retrieval to response control. Since these processes are often being studied separately, the functional organization of executive control processes within the IFC remains unclear. Methodology/Principal Findings We conducted an fMRI study to examine the activities of the subdivisions of IFC during the presentation of a task cue (rule retrieval) and during the performance of a stop-signal task (requiring response generation and inhibition) in comparison to a not-stop task (requiring response generation but not inhibition). We utilized a mixed event-related and block design to separate brain activity in correspondence to transient control processes from rule-related and sustained control processes. We found differentiation in control processes within the IFC. Our findings reveal that the bilateral ventral-posterior IFC/anterior insula are more active on both successful and unsuccessful stop trials relative to not-stop trials, suggesting their potential role in the early stage of stopping such as triggering the stop process. Direct countermanding seems to be outside of the IFC. In contrast, the dorsal-posterior IFC/inferior frontal junction (IFJ) showed transient activity in correspondence to the infrequent presentation of the stop signal in both tasks and the left anterior IFC showed differential activity in response to the task cues. The IFC subdivisions also exhibited similar but distinct patterns of functional connectivity during response control. Conclusions/Significance Our findings suggest that executive control processes are distributed across the IFC and that the different subdivisions of IFC may support different control operations through parallel cortico-cortical and cortico-striatal circuits. PMID:21673969

What cognitive strategies do orangutans (Pongo pygmaeus) use to solve a trial-unique puzzle-tube task incorporating multiple obstacles?

PubMed

Tecwyn, Emma C; Thorpe, Susannah K S; Chappell, Jackie

2012-01-01

Apparently sophisticated behaviour during problem-solving is often the product of simple underlying mechanisms, such as associative learning or the use of procedural rules. These and other more parsimonious explanations need to be eliminated before higher-level cognitive processes such as causal reasoning or planning can be inferred. We presented three Bornean orangutans with 64 trial-unique configurations of a puzzle-tube to investigate whether they were able to consider multiple obstacles in two alternative paths, and subsequently choose the correct direction in which to move a reward in order to retrieve it. We were particularly interested in how subjects attempted to solve the task, namely which behavioural strategies they could have been using, as this is how we may begin to elucidate the cognitive mechanisms underpinning their choices. To explore this, we simulated performance outcomes across the 64 trials for various procedural rules and rule combinations that subjects may have been using based on the configuration of different obstacles. Two of the three subjects solved the task, suggesting that they were able to consider at least some of the obstacles in the puzzle-tube before executing action to retrieve the reward. This is impressive compared with the past performances of great apes on similar, arguably less complex tasks. Successful subjects may have been using a heuristic rule combination based on what they deemed to be the most relevant cue (the configuration of the puzzle-tube ends), which may be a cognitively economical strategy.

Requiem for the max rule?

PubMed Central

Ma, Wei Ji; Shen, Shan; Dziugaite, Gintare; van den Berg, Ronald

2015-01-01

In tasks such as visual search and change detection, a key question is how observers integrate noisy measurements from multiple locations to make a decision. Decision rules proposed to model this process haven fallen into two categories: Bayes-optimal (ideal observer) rules and ad-hoc rules. Among the latter, the maximum-of-outputs (max) rule has been most prominent. Reviewing recent work and performing new model comparisons across a range of paradigms, we find that in all cases except for one, the optimal rule describes human data as well as or better than every max rule either previously proposed or newly introduced here. This casts doubt on the utility of the max rule for understanding perceptual decision-making. PMID:25584425

The Relationship between Second-Order False Belief and Display Rules Reasoning: The Integration of Cognitive and Affective Social Understanding

ERIC Educational Resources Information Center

Naito, Mika; Seki, Yoshimi

2009-01-01

To investigate the relation between cognitive and affective social understanding, Japanese 4- to 8-year-olds received tasks of first- and second-order false beliefs and prosocial and self-presentational display rules. From 6 to 8 years, children comprehended display rules, as well as second-order false belief, using social pressures justifications…

Strong support for relocation to other work tasks: A cross-sectional study of attitudes to sickness insurance regulations in Sweden.

PubMed

Hensing, G; Holmgren, K; Rohdén, H

2015-01-01

Profound changes are taking place in the Swedish welfare state. The general population's attitudes are important insofar changes will be perceived as fair and effective to become implemented. The aim was to study attitudes to the strictness of the sick-leave rules, relocation to other work tasks after 3 months of sick leave and applications for new jobs after 6 months of sick leave. Eligible for this questionnaire study were 1,140 individuals aged 19 to 64 years. Their attitudes were analyzed in relation to age, gender, political ideology and health status. Health status was measured as sick-leave experiences, self-reported health and level of symptoms. Showed that 42% considered the sick-leave rules to be too strict, 60% found relocation to other work tasks to be good while 35% found that applications for new work were good. In logistic regression analyses, high sick-leave experience was associated with increased odds of finding the sick-leave rules too strict and disagreement with relocation to other work tasks or application for new jobs. In conclusion, strong support was found for relocation to other work tasks with the present employer. Earlier research on returning to work has found workplace interventions to be efficient. From a policy perspective it seems relevant to promote such interventions given the strong public opinion in their favor.

Streamling the Change Management with Business Rules

NASA Technical Reports Server (NTRS)

Savela, Christopher

2015-01-01

Will discuss how their organization is trying to streamline workflows and the change management process with business rules. In looking for ways to make things more efficient and save money one way is to reduce the work the workflow task approvers have to do when reviewing affected items. Will share the technical details of the business rules, how to implement them, how to speed up the development process by using the API to demonstrate the rules in action.

Dopamine reward prediction errors reflect hidden state inference across time

PubMed Central

Starkweather, Clara Kwon; Babayan, Benedicte M.; Uchida, Naoshige; Gershman, Samuel J.

2017-01-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a ‘belief state’). In this work, we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling exhibited a striking difference between two tasks that differed only with respect to whether reward was delivered deterministically. Our results favor an associative learning rule that combines cached values with hidden state inference. PMID:28263301

Repeating the Past: Prevention Focus Motivates Repetition, Even For Unethical Decisions

PubMed Central

Zhang, Shu; Cornwell, James F.M.; Higgins, E. Tory

2013-01-01

Prevention-focused individuals are motivated to maintain the status quo. Given this, we predicted that individuals with a strong prevention focus, either as a chronic predisposition or situationally induced, would treat their initial decision of how to behave on a first task as the status quo, and thus be motivated to repeat that decision on a subsequent task—even for decisions that are ethically questionable. Five studies supported this prediction in multiple ethical domains: whether or not to overstate performance (Studies 1, 2a, 2b), to disclose disadvantageous facts (Study 3), and to pledge a donation (Study 4). The prevention-repetition effect was observed when initial and subsequent decisions were in the same domain (Studies 1-3) and in different domains (Study 4). Alternative accounts such as justification for the initial decision and preference for consistency were ruled out (Study 2b). PMID:24277774

Interpretive understanding, sympathy, and moral emotion attribution in oppositional defiant disorder symptomatology.

PubMed

Dinolfo, Caterina; Malti, Tina

2013-10-01

This study examined the relations between interpretive understanding, sympathy, and moral emotion attribution (MEA) in the prediction of oppositional defiant disorder (ODD) symptomatology in an ethnically diverse sample of 128 4- and 8-year-old children (49 % girls). Caregivers rated the children's ODD symptoms. Interpretive understanding was assessed using an advanced theory-of-mind task. Sympathy was measured via caregiver- and child-report. Strength of MEA was assessed utilizing the children's responses to six hypothetical moral transgressions. Results revealed that interpretive understanding, sympathy, and strength of MEA in the exclusion domain predicted ODD symptoms negatively. Caregiver-reported sympathy partially mediated and moderated the relation between interpretive understanding and ODD symptoms. Strength of MEA in the rule violation domain moderated the relation between interpretive understanding and ODD symptoms. The findings shed light on the importance of social-cognitive and affective-moral antecedents of ODD symptoms.

Dopamine reward prediction errors reflect hidden-state inference across time.

PubMed

Starkweather, Clara Kwon; Babayan, Benedicte M; Uchida, Naoshige; Gershman, Samuel J

2017-04-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a 'belief state'). Here we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling showed a notable difference between two tasks that differed only with respect to whether reward was delivered in a deterministic manner. Our results favor an associative learning rule that combines cached values with hidden-state inference.

The Rule of Five for Non-Oral Routes of Drug Delivery: Ophthalmic, Inhalation and Transdermal

PubMed Central

Choy, Young Bin; Prausnitz, Mark R.

2011-01-01

The Rule of Five predicts suitability of drug candidates, but was developed primarily using orally administered drugs. Here, we test whether the Rule of Five predicts drugs for delivery via non-oral routes, specifically ophthalmic, inhalation and transdermal. We assessed 111 drugs approved by FDA for those routes of administration and found that >98% of current non-oral drugs have physicochemical properties within the limits of the Rule of Five. However, given the inherent bias in the dataset, this analysis was not able to assess whether drugs with properties outside those limits are poor candidates. Indeed, further analysis indicates that drugs well outside the Rule of Five limits, including hydrophilic macromolecules, can be delivered by inhalation. In contrast, drugs currently administered across skin fall within more stringent limits than predicted by the Rule of Five, but new transdermal delivery technologies may make these constraints obsolete by dramatically increasing skin permeability. The Rule of Five does appear to apply well to ophthalmic delivery. We conclude that although current non-oral drugs mostly have physicochemical properties within the Rule of Five thresholds, the Rule of Five should not be used to predict non-oral drug candidates, especially for inhalation and transdermal routes. PMID:20967491

Termination of Resuscitation Rules to Predict Neurological Outcomes in Out-of-Hospital Cardiac Arrest for an Intermediate Life Support Prehospital System.

PubMed

Cheong, Randy Wang Long; Li, Huihua; Doctor, Nausheen Edwin; Ng, Yih Yng; Goh, E Shaun; Leong, Benjamin Sieu-Hon; Gan, Han Nee; Foo, David; Tham, Lai Peng; Charles, Rabind; Ong, Marcus Eng Hock

2016-01-01

Futile resuscitation can lead to unnecessary transports for out-of-hospital cardiac arrest (OHCA). The Basic Life Support (BLS) and Advanced Life Support (ALS) termination of resuscitation (TOR) guidelines have been validated with good results in North America. This study aims to evaluate the performance of these two rules in predicting neurological outcomes of OHCA patients in Singapore, which has an intermediate life support Emergency Medical Services (EMS) system. A retrospective cohort study was carried out on Singapore OHCA data collected from April 2010 to May 2012 for the Pan-Asian Resuscitation Outcomes Study (PAROS). The outcomes of each rule were compared to the actual neurological outcomes of the patients. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and predicted transport rates of each test were evaluated. A total of 2,193 patients had cardiac arrest of presumed cardiac etiology. TOR was recommended for 1,411 patients with the BLS-TOR rule, with a specificity of 100% (91.9, 100.0) for predicting poor neurological outcomes, PPV 100% (99.7, 100.0), sensitivity 65.7% (63.6, 67.7), NPV 5.6% (4.1, 7.5), and transportation rate 35.6%. Using the ALS-TOR rule, TOR was recommended for 587 patients, specificity 100% (91.9, 100.0) for predicting poor neurological outcomes, PPV 100% (99.4, 100.0), sensitivity 27.3% (25.4, 29.3), NPV 2.7% (2.0, 3.7), and transportation rate 73.2%. BLS-TOR predicted survival (any neurological outcome) with specificity 93.4% (95% CI 85.3, 97.8) versus ALS-TOR 98.7% (95% CI 92.9, 99.8). Both the BLS and ALS-TOR rules had high specificities and PPV values in predicting neurological outcomes, the BLS-TOR rule had a lower predicted transport rate while the ALS-TOR rule was more accurate in predicting futility of resuscitation. Further research into unique local cultural issues would be useful to evaluate the feasibility of any system-wide implementation of TOR.

Developing a Computerised Multiple Elements Test for Organisational Difficulties

ERIC Educational Resources Information Center

Hynes, Sinead M.; Fish, Jessica; Evans, Jonathan J.; Manly, Tom

2015-01-01

Executive function is best measured in loosely structured, multi-component tasks that reflect real-life demands. These tasks require participants to develop a strategy, keep a plan in mind and monitor time. Errors include ignoring stated goals ("goal neglect"), over-allocation of time to one task and violating rules. Teasing apart such…

Applications of artificial intelligence to mission planning

NASA Technical Reports Server (NTRS)

Ford, Donnie R.; Floyd, Stephen A.; Rogers, John S.

1990-01-01

The following subject areas are covered: object-oriented programming task; rule-based programming task; algorithms for resource allocation; connecting a Symbolics to a VAX; FORTRAN from Lisp; trees and forest task; software data structure conversion; software functionality modifications and enhancements; portability of resource allocation to a TI MicroExplorer; frontier of feasibility software system; and conclusions.

Healthcare provider perceptions of clinical prediction rules

PubMed Central

Richardson, Safiya; Khan, Sundas; McCullagh, Lauren; Kline, Myriam; Mann, Devin; McGinn, Thomas

2015-01-01

Objectives To examine internal medicine and emergency medicine healthcare provider perceptions of usefulness of specific clinical prediction rules. Setting The study took place in two academic medical centres. A web-based survey was distributed and completed by participants between 1 January and 31 May 2013. Participants Medical doctors, doctors of osteopathy or nurse practitioners employed in the internal medicine or emergency medicine departments at either institution. Primary and secondary outcome measures The primary outcome was to identify the clinical prediction rules perceived as most useful by healthcare providers specialising in internal medicine and emergency medicine. Secondary outcomes included comparing usefulness scores of specific clinical prediction rules based on provider specialty, and evaluating associations between usefulness scores and perceived characteristics of these clinical prediction rules. Results Of the 401 healthcare providers asked to participate, a total of 263 (66%), completed the survey. The CHADS2 score was chosen by most internal medicine providers (72%), and Pulmonary Embolism Rule-Out Criteria (PERC) score by most emergency medicine providers (45%), as one of the top three most useful from a list of 24 clinical prediction rules. Emergency medicine providers rated their top three significantly more positively, compared with internal medicine providers, as having a better fit into their workflow (p=0.004), helping more with decision-making (p=0.037), better fitting into their thought process when diagnosing patients (p=0.001) and overall, on a 10-point scale, more useful (p=0.009). For all providers, the perceived qualities of useful at point of care, helps with decision making, saves time diagnosing, fits into thought process, and should be the standard of clinical care correlated highly (≥0.65) with overall 10-point usefulness scores. Conclusions Healthcare providers describe clear preferences for certain clinical prediction rules, based on medical specialty. PMID:26338684

Reward-dependent learning in neuronal networks for planning and decision making.

PubMed

Dehaene, S; Changeux, J P

2000-01-01

Neuronal network models have been proposed for the organization of evaluation and decision processes in prefrontal circuitry and their putative neuronal and molecular bases. The models all include an implementation and simulation of an elementary reward mechanism. Their central hypothesis is that tentative rules of behavior, which are coded by clusters of active neurons in prefrontal cortex, are selected or rejected based on an evaluation by this reward signal, which may be conveyed, for instance, by the mesencephalic dopaminergic neurons with which the prefrontal cortex is densely interconnected. At the molecular level, the reward signal is postulated to be a neurotransmitter such as dopamine, which exerts a global modulatory action on prefrontal synaptic efficacies, either via volume transmission or via targeted synaptic triads. Negative reinforcement has the effect of destabilizing the currently active rule-coding clusters; subsequently, spontaneous activity varies again from one cluster to another, giving the organism the chance to discover and learn a new rule. Thus, reward signals function as effective selection signals that either maintain or suppress currently active prefrontal representations as a function of their current adequacy. Simulations of this variation-selection have successfully accounted for the main features of several major tasks that depend on prefrontal cortex integrity, such as the delayed-response test, the Wisconsin card sorting test, the Tower of London test and the Stroop test. For the more complex tasks, we have found it necessary to supplement the external reward input with a second mechanism that supplies an internal reward; it consists of an auto-evaluation loop which short-circuits the reward input from the exterior. This allows for an internal evaluation of covert motor intentions without actualizing them as behaviors, by simply testing them covertly by comparison with memorized former experiences. This element of architecture gives access to enhanced rates of learning via an elementary process of internal or covert mental simulation. We have recently applied these ideas to a new model, developed with M. Kerszberg, which hypothesizes that prefrontal cortex and its reward-related connections contribute crucially to conscious effortful tasks. This model distinguishes two main computational spaces within the human brain: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative and attentional processors. We postulate that workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice; they selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously co-activated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. This model makes predictions concerning the spatio-temporal activation patterns during brain imaging of cognitive tasks, particularly concerning the conditions of activation of dorsolateral prefrontal cortex and anterior cingulate, their relation to reward mechanisms, and their specific reaction during error processing.

Bayesian probability estimates are not necessary to make choices satisfying Bayes' rule in elementary situations.

PubMed

Domurat, Artur; Kowalczuk, Olga; Idzikowska, Katarzyna; Borzymowska, Zuzanna; Nowak-Przygodzka, Marta

2015-01-01

This paper has two aims. First, we investigate how often people make choices conforming to Bayes' rule when natural sampling is applied. Second, we show that using Bayes' rule is not necessary to make choices satisfying Bayes' rule. Simpler methods, even fallacious heuristics, might prescribe correct choices reasonably often under specific circumstances. We considered elementary situations with binary sets of hypotheses and data. We adopted an ecological approach and prepared two-stage computer tasks resembling natural sampling. Probabilistic relations were inferred from a set of pictures, followed by a choice which was made to maximize the chance of a preferred outcome. Use of Bayes' rule was deduced indirectly from choices. Study 1 used a stratified sample of N = 60 participants equally distributed with regard to gender and type of education (humanities vs. pure sciences). Choices satisfying Bayes' rule were dominant. To investigate ways of making choices more directly, we replicated Study 1, adding a task with a verbal report. In Study 2 (N = 76) choices conforming to Bayes' rule dominated again. However, the verbal reports revealed use of a new, non-inverse rule, which always renders correct choices, but is easier than Bayes' rule to apply. It does not require inversion of conditions [transforming P(H) and P(D|H) into P(H|D)] when computing chances. Study 3 examined the efficiency of three fallacious heuristics (pre-Bayesian, representativeness, and evidence-only) in producing choices concordant with Bayes' rule. Computer-simulated scenarios revealed that the heuristics produced correct choices reasonably often under specific base rates and likelihood ratios. Summing up we conclude that natural sampling results in most choices conforming to Bayes' rule. However, people tend to replace Bayes' rule with simpler methods, and even use of fallacious heuristics may be satisfactorily efficient.

Bayesian probability estimates are not necessary to make choices satisfying Bayes’ rule in elementary situations

PubMed Central

Domurat, Artur; Kowalczuk, Olga; Idzikowska, Katarzyna; Borzymowska, Zuzanna; Nowak-Przygodzka, Marta

2015-01-01

This paper has two aims. First, we investigate how often people make choices conforming to Bayes’ rule when natural sampling is applied. Second, we show that using Bayes’ rule is not necessary to make choices satisfying Bayes’ rule. Simpler methods, even fallacious heuristics, might prescribe correct choices reasonably often under specific circumstances. We considered elementary situations with binary sets of hypotheses and data. We adopted an ecological approach and prepared two-stage computer tasks resembling natural sampling. Probabilistic relations were inferred from a set of pictures, followed by a choice which was made to maximize the chance of a preferred outcome. Use of Bayes’ rule was deduced indirectly from choices. Study 1 used a stratified sample of N = 60 participants equally distributed with regard to gender and type of education (humanities vs. pure sciences). Choices satisfying Bayes’ rule were dominant. To investigate ways of making choices more directly, we replicated Study 1, adding a task with a verbal report. In Study 2 (N = 76) choices conforming to Bayes’ rule dominated again. However, the verbal reports revealed use of a new, non-inverse rule, which always renders correct choices, but is easier than Bayes’ rule to apply. It does not require inversion of conditions [transforming P(H) and P(D|H) into P(H|D)] when computing chances. Study 3 examined the efficiency of three fallacious heuristics (pre-Bayesian, representativeness, and evidence-only) in producing choices concordant with Bayes’ rule. Computer-simulated scenarios revealed that the heuristics produced correct choices reasonably often under specific base rates and likelihood ratios. Summing up we conclude that natural sampling results in most choices conforming to Bayes’ rule. However, people tend to replace Bayes’ rule with simpler methods, and even use of fallacious heuristics may be satisfactorily efficient. PMID:26347676

Stock price change rate prediction by utilizing social network activities.

PubMed

Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

Stock Price Change Rate Prediction by Utilizing Social Network Activities

PubMed Central

Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

On the applicability of STDP-based learning mechanisms to spiking neuron network models

NASA Astrophysics Data System (ADS)

Sboev, A.; Vlasov, D.; Serenko, A.; Rybka, R.; Moloshnikov, I.

2016-11-01

The ways to creating practically effective method for spiking neuron networks learning, that would be appropriate for implementing in neuromorphic hardware and at the same time based on the biologically plausible plasticity rules, namely, on STDP, are discussed. The influence of the amount of correlation between input and output spike trains on the learnability by different STDP rules is evaluated. A usability of alternative combined learning schemes, involving artificial and spiking neuron models is demonstrated on the iris benchmark task and on the practical task of gender recognition.

Anxiety Evokes Hypofrontality and Disrupts Rule-Relevant Encoding by Dorsomedial Prefrontal Cortex Neurons.

PubMed

Park, Junchol; Wood, Jesse; Bondi, Corina; Del Arco, Alberto; Moghaddam, Bita

2016-03-16

Anxiety is a debilitating symptom of most psychiatric disorders, including major depression, post-traumatic stress disorder, schizophrenia, and addiction. A detrimental aspect of anxiety is disruption of prefrontal cortex (PFC)-mediated executive functions, such as flexible decision making. Here we sought to understand how anxiety modulates PFC neuronal encoding of flexible shifting between behavioral strategies. We used a clinically substantiated anxiogenic treatment to induce sustained anxiety in rats and recorded from dorsomedial PFC (dmPFC) and orbitofrontal cortex (OFC) neurons while they were freely moving in a home cage and while they performed a PFC-dependent task that required flexible switches between rules in two distinct perceptual dimensions. Anxiety elicited a sustained background "hypofrontality" in dmPFC and OFC by reducing the firing rate of spontaneously active neuronal subpopulations. During task performance, the impact of anxiety was subtle, but, consistent with human data, behavior was selectively impaired when previously correct conditions were presented as conflicting choices. This impairment was associated with reduced recruitment of dmPFC neurons that selectively represented task rules at the time of action. OFC rule representation was not affected by anxiety. These data indicate that a neural substrate of the decision-making deficits in anxiety is diminished dmPFC neuronal encoding of task rules during conflict-related actions. Given the translational relevance of the model used here, the data provide a neuronal encoding mechanism for how anxiety biases decision making when the choice involves overcoming a conflict. They also demonstrate that PFC encoding of actions, as opposed to cues or outcome, is especially vulnerable to anxiety. A debilitating aspect of anxiety is its impact on decision making and flexible control of behavior. These cognitive constructs depend on proper functioning of the prefrontal cortex (PFC). Understanding how anxiety affects PFC encoding of cognitive events is of great clinical and evolutionary significance. Using a clinically valid experimental model, we find that, under anxiety, decision making may be skewed by salient and conflicting environmental stimuli at the expense of flexible top-down guided choices. We also find that anxiety suppresses spontaneous activity of PFC neurons, and weakens encoding of task rules by dorsomedial PFC neurons. These data provide a neuronal encoding scheme for how anxiety disengages PFC during decision making. Copyright © 2016 the authors 0270-6474/16/363322-14$15.00/0.

Social and physical aggression trajectories from childhood through late adolescence: Predictors of psychosocial maladjustment at age 18.

PubMed

Ehrenreich, Samuel E; Beron, Kurt J; Underwood, Marion K

2016-03-01

This research examined whether following social and physical aggression trajectories across Grades 3-12 predicted psychological maladjustment. Teachers rated participants' (n = 287, 138 boys) aggressive behavior at the end of each school year. Following the 12th grade, psychosocial outcomes were measured: rule-breaking behaviors, internalizing symptoms, and narcissistic and borderline personality features. Following the highest social aggression trajectory predicted rule-breaking behavior; the medium social aggression trajectory was not a significant predictor of any outcome. Following the highest physical aggression trajectory predicted rule-breaking, internalizing symptoms, and narcissism, whereas the medium physical aggression trajectory predicted rule-breaking and internalizing symptoms. (c) 2016 APA, all rights reserved).

Social and physical aggression trajectories from childhood through late adolescence: Predictors of psychosocial maladjustment at age 18

PubMed Central

Ehrenreich, Samuel E.; Beron, Kurt J.; Underwood, Marion K.

2016-01-01

This research examined whether following social and physical aggression trajectories across grades 3–12 predicted psychological maladjustment. Teachers rated participants’ (n=287, 138 boys) aggressive behavior at the end of each school year. Following the 12th grade, psychosocial outcomes were measured: rule-breaking behaviors, internalizing symptoms, and narcissistic and borderline personality features. Following the highest social aggression trajectory predicted rule-breaking behavior; the medium social aggression trajectory was not a significant predictor of any outcome. Following the highest physical aggression trajectory predicted rule-breaking, internalizing symptoms and narcissism, whereas the medium physical aggression trajectory predicted rule-breaking and internalizing symptoms. PMID:26891018

Fighter pilots' heart rate, heart rate variation and performance during an instrument flight rules proficiency test.

PubMed

Mansikka, Heikki; Virtanen, Kai; Harris, Don; Simola, Petteri

2016-09-01

Increased task demand will increase the pilot mental workload (PMWL). When PMWL is increased, mental overload may occur resulting in degraded performance. During pilots' instrument flight rules (IFR) proficiency test, PMWL is typically not measured. Therefore, little is known about workload during the proficiency test and pilots' potential to cope with higher task demands than those experienced during the test. In this study, fighter pilots' performance and PMWL was measured during a real IFR proficiency test in an F/A-18 simulator. PMWL was measured using heart rate (HR) and heart rate variation (HRV). Performance was rated using Finnish Air Force's official rating scales. Results indicated that HR and HRV differentiate varying task demands in situations where variations in performance are insignificant. It was concluded that during a proficiency test, PMWL should be measured together with the task performance measurement. Copyright © 2016 Elsevier Ltd. All rights reserved.

POPEYE: A production rule-based model of multitask supervisory control (POPCORN)

NASA Technical Reports Server (NTRS)

Townsend, James T.; Kadlec, Helena; Kantowitz, Barry H.

1988-01-01

Recent studies of relationships between subjective ratings of mental workload, performance, and human operator and task characteristics have indicated that these relationships are quite complex. In order to study the various relationships and place subjective mental workload within a theoretical framework, we developed a production system model for the performance component of the complex supervisory task called POPCORN. The production system model is represented by a hierarchial structure of goals and subgoals, and the information flow is controlled by a set of condition-action rules. The implementation of this production system, called POPEYE, generates computer simulated data under different task difficulty conditions which are comparable to those of human operators performing the task. This model is the performance aspect of an overall dynamic psychological model which we are developing to examine and quantify relationships between performance and psychological aspects in a complex environment.

Validating and updating a prediction rule for serious bacterial infection in patients with fever without source.

PubMed

Bleeker, S E; Derksen-Lubsen, G; Grobbee, D E; Donders, A R T; Moons, K G M; Moll, H A

2007-01-01

To externally validate and update a previously developed rule for predicting the presence of serious bacterial infections in children with fever without apparent source. Patients, 1-36 mo, presenting with fever without source, were prospectively enrolled. Serious bacterial infection included bacterial meningitis, sepsis, bacteraemia, pneumonia, urinary tract infection, bacterial gastroenteritis, osteomyelitis/ethmoiditis. The generalizability of the original rule was determined. Subsequently, the prediction rule was updated using all available data of the patients with fever without source (1996-1998 and 2000-2001, n = 381) using multivariable logistic regression. the generalizability of the rule appeared insufficient in the new patients (n = 150). In the updated rule, independent predictors from history and examination were duration of fever, vomiting, ill clinical appearance, chest-wall retractions and poor peripheral circulation (ROC area (95%CI): 0.69 (0.63-0.75)). Additional independent predictors from laboratory were serum white blood cell count and C-reactive protein, and in urinalysis > or = 70 white bloods (ROC area (95%CI): 0.83 (0.78-0.88). A previously developed prediction rule for predicting the presence of serious bacterial infection in children with fever without apparent source was updated. Its clinical score can be used as a first screening tool. Additional laboratory testing may specify the individual risk estimate (range: 4-54%) further.

Characterizing Behavioral and Brain Changes Associated with Practicing Reasoning Skills

PubMed Central

Mackey, Allyson P.; Miller Singley, Alison T.; Wendelken, Carter; Bunge, Silvia A.

2015-01-01

We have reported previously that intensive preparation for a standardized test that taxes reasoning leads to changes in structural and functional connectivity within the frontoparietal network. Here, we investigated whether reasoning instruction transfers to improvement on unpracticed tests of reasoning, and whether these improvements are associated with changes in neural recruitment during reasoning task performance. We found behavioral evidence for transfer to a transitive inference task, but no evidence for transfer to a rule generation task. Across both tasks, we observed reduced lateral prefrontal activation in the trained group relative to the control group, consistent with other studies of practice-related changes in brain activation. In the transitive inference task, we observed enhanced suppression of task-negative, or default-mode, regions, consistent with work suggesting that better cognitive skills are associated with more efficient switching between networks. In the rule generation task, we found a pattern consistent with a training-related shift in the balance between phonological and visuospatial processing. Broadly, we discuss general methodological considerations related to the analysis and interpretation of training-related changes in brain activation. In summary, we present preliminary evidence for changes in brain activation associated with practice of high-level cognitive skills. PMID:26368278

Modern architectures for intelligent systems: reusable ontologies and problem-solving methods.

PubMed Central

Musen, M. A.

1998-01-01

When interest in intelligent systems for clinical medicine soared in the 1970s, workers in medical informatics became particularly attracted to rule-based systems. Although many successful rule-based applications were constructed, development and maintenance of large rule bases remained quite problematic. In the 1980s, an entire industry dedicated to the marketing of tools for creating rule-based systems rose and fell, as workers in medical informatics began to appreciate deeply why knowledge acquisition and maintenance for such systems are difficult problems. During this time period, investigators began to explore alternative programming abstractions that could be used to develop intelligent systems. The notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) domain-independent problem-solving methods-standard algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper will highlight how intelligent systems for diverse tasks can be efficiently automated using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community. PMID:9929181

Modern architectures for intelligent systems: reusable ontologies and problem-solving methods.

PubMed

Musen, M A

1998-01-01

When interest in intelligent systems for clinical medicine soared in the 1970s, workers in medical informatics became particularly attracted to rule-based systems. Although many successful rule-based applications were constructed, development and maintenance of large rule bases remained quite problematic. In the 1980s, an entire industry dedicated to the marketing of tools for creating rule-based systems rose and fell, as workers in medical informatics began to appreciate deeply why knowledge acquisition and maintenance for such systems are difficult problems. During this time period, investigators began to explore alternative programming abstractions that could be used to develop intelligent systems. The notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) domain-independent problem-solving methods-standard algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper will highlight how intelligent systems for diverse tasks can be efficiently automated using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.

Taking a gamble or playing by the rules: Dissociable prefrontal systems implicated in probabilistic versus deterministic rule-based decisions

PubMed Central

Bhanji, Jamil P.; Beer, Jennifer S.; Bunge, Silvia A.

2014-01-01

A decision may be difficult because complex information processing is required to evaluate choices according to deterministic decision rules and/or because it is not certain which choice will lead to the best outcome in a probabilistic context. Factors that tax decision making such as decision rule complexity and low decision certainty should be disambiguated for a more complete understanding of the decision making process. Previous studies have examined the brain regions that are modulated by decision rule complexity or by decision certainty but have not examined these factors together in the context of a single task or study. In the present functional magnetic resonance imaging study, both decision rule complexity and decision certainty were varied in comparable decision tasks. Further, the level of certainty about which choice to make (choice certainty) was varied separately from certainty about the final outcome resulting from a choice (outcome certainty). Lateral prefrontal cortex, dorsal anterior cingulate cortex, and bilateral anterior insula were modulated by decision rule complexity. Anterior insula was engaged more strongly by low than high choice certainty decisions, whereas ventromedial prefrontal cortex showed the opposite pattern. These regions showed no effect of the independent manipulation of outcome certainty. The results disambiguate the influence of decision rule complexity, choice certainty, and outcome certainty on activity in diverse brain regions that have been implicated in decision making. Lateral prefrontal cortex plays a key role in implementing deterministic decision rules, ventromedial prefrontal cortex in probabilistic rules, and anterior insula in both. PMID:19781652

The Power of a "Maverick" in Collaborative Problem Solving: An Experimental Investigation of Individual Perspective-Taking Within a Group.

PubMed

Hayashi, Yugo

2018-05-01

Integrating different perspectives is a sophisticated strategy for developing constructive interactions in collaborative problem solving. However, cognitive aspects such as individuals' knowledge and bias often obscure group consensus and produce conflict. This study investigated collaborative problem solving, focusing on a group member interacting with another member having a different perspective (a "maverick"). It was predicted that mavericks might mitigate disadvantages and facilitate perspective taking during problem solving. Thus, 344 university students participated in two laboratory-based experiments by engaging in a simple rule-discovery task that raised conflicts among perspectives. They interacted with virtual partners whose conversations were controlled by multiple conversational agents. Results show that when participants interacted with a maverick during the task, they were able to take others' perspectives and integrate different perspectives to solve the problem. Moreover, when participants interacted in groups with a positive mood, groups with a maverick outperformed groups having several perspectives. Copyright © 2018 Cognitive Science Society, Inc.

A comparison of signal detection theory to the objective threshold/strategic model of unconscious perception.

PubMed

Haase, Steven J; Fisk, Gary D

2011-08-01

A key problem in unconscious perception research is ruling out the possibility that weak conscious awareness of stimuli might explain the results. In the present study, signal detection theory was compared with the objective threshold/strategic model as explanations of results for detection and identification sensitivity in a commonly used unconscious perception task. In the task, 64 undergraduate participants detected and identified one of four briefly displayed, visually masked letters. Identification was significantly above baseline (i.e., proportion correct > .25) at the highest detection confidence rating. This result is most consistent with signal detection theory's continuum of sensory states and serves as a possible index of conscious perception. However, there was limited support for the other model in the form of a predicted "looker's inhibition" effect, which produced identification performance that was significantly below baseline. One additional result, an interaction between the target stimulus and type of mask, raised concerns for the generality of unconscious perception effects.

The relation between resting state connectivity and creativity in adolescents before and after training.

PubMed

Cousijn, Janna; Zanolie, Kiki; Munsters, Robbert J M; Kleibeuker, Sietske W; Crone, Eveline A

2014-01-01

An important component of creativity is divergent thinking, which involves the ability to generate novel and useful problem solutions. In this study, we tested the relation between resting-state functional connectivity of brain areas activated during a divergent thinking task (i.e., supramarginal gyrus, middle temporal gyrus, medial frontal gyrus) and the effect of practice in 32 adolescents aged 15-16. Over a period of two weeks, an experimental group (n = 16) conducted an 8-session Alternative Uses Task (AUT) training and an active control group (n = 16) conducted an 8-session rule switching training. Resting-state functional connectivity was measured before (pre-test) and after (post-test) training. Across groups at pre-test, stronger connectivity between the middle temporal gyrus and bilateral postcentral gyrus was associated with better divergent thinking performance. The AUT-training, however, did not significantly change functional connectivity. Post hoc analyses showed that change in divergent thinking performance over time was predicted by connectivity between left supramarginal gyrus and right occipital cortex. These results provide evidence for a relation between divergent thinking and resting-state functional connectivity in a task-positive network, taking an important step towards understanding creative cognition and functional brain connectivity.

Why aren’t they happy? An analysis of end-user satisfaction with Electronic health records

PubMed Central

Unni, Prasad; Staes, Catherine; Weeks, Howard; Kramer, Heidi; Borbolla, Damion; Slager, Stacey; Taft, Teresa; Chidambaram, Valliammai; Weir, Charlene

2016-01-01

Introduction. Implementations of electronic health records (EHR) have been met with mixed outcome reviews. Complaints about these systems have led to many attempts to have useful measures of end-user satisfaction. However, most user satisfaction assessments do not focus on high-level reasoning, despite the complaints of many physicians. Our study attempts to identify some of these determinants. Method. We developed a user satisfaction survey instrument, based on pre-identified and important clinical and non-clinical clinician tasks. We surveyed a sample of in-patient physicians and focused on using exploratory factor analyses to identify underlying high-level cognitive tasks. We used the results to create unique, orthogonal variables representative of latent structure predictive of user satisfaction. Results. Our findings identified 3 latent high-level tasks that were associated with end-user satisfaction: a) High- level clinical reasoning b) Communicate/coordinate care and c) Follow the rules/compliance. Conclusion: We were able to successfully identify latent variables associated with satisfaction. Identification of communicability and high-level clinical reasoning as important factors determining user satisfaction can lead to development and design of more usable electronic health records with higher user satisfaction. PMID:28269962

Selective representation of task-relevant objects and locations in the monkey prefrontal cortex.

PubMed

Everling, Stefan; Tinsley, Chris J; Gaffan, David; Duncan, John

2006-04-01

In the monkey prefrontal cortex (PFC), task context exerts a strong influence on neural activity. We examined different aspects of task context in a temporal search task. On each trial, the monkey (Macaca mulatta) watched a stream of pictures presented to left or right of fixation. The task was to hold fixation until seeing a particular target, and then to make an immediate saccade to it. Sometimes (unilateral task), the attended pictures appeared alone, with a cue at trial onset indicating whether they would be presented to left or right. Sometimes (bilateral task), the attended picture stream (cued side) was accompanied by an irrelevant stream on the opposite side. In two macaques, we recorded responses from a total of 161 cells in the lateral PFC. Many cells (75/161) showed visual responses. Object-selective responses were strongly shaped by task relevance - with stronger responses to targets than to nontargets, failure to discriminate one nontarget from another, and filtering out of information from an irrelevant stimulus stream. Location selectivity occurred rather independently of object selectivity, and independently in visual responses and delay periods between one stimulus and the next. On error trials, PFC activity followed the correct rules of the task, rather than the incorrect overt behaviour. Together, these results suggest a highly programmable system, with responses strongly determined by the rules and requirements of the task performed.

Requiem for the max rule?

PubMed

Ma, Wei Ji; Shen, Shan; Dziugaite, Gintare; van den Berg, Ronald

2015-11-01

In tasks such as visual search and change detection, a key question is how observers integrate noisy measurements from multiple locations to make a decision. Decision rules proposed to model this process have fallen into two categories: Bayes-optimal (ideal observer) rules and ad-hoc rules. Among the latter, the maximum-of-outputs (max) rule has been the most prominent. Reviewing recent work and performing new model comparisons across a range of paradigms, we find that in all cases except for one, the optimal rule describes human data as well as or better than every max rule either previously proposed or newly introduced here. This casts doubt on the utility of the max rule for understanding perceptual decision-making. Copyright © 2015 Elsevier Ltd. All rights reserved.

ReactPRED: a tool to predict and analyze biochemical reactions.

PubMed

Sivakumar, Tadi Venkata; Giri, Varun; Park, Jin Hwan; Kim, Tae Yong; Bhaduri, Anirban

2016-11-15

Biochemical pathways engineering is often used to synthesize or degrade target chemicals. In silico screening of the biochemical transformation space allows predicting feasible reactions, constituting these pathways. Current enabling tools are customized to predict reactions based on pre-defined biochemical transformations or reaction rule sets. Reaction rule sets are usually curated manually and tailored to specific applications. They are not exhaustive. In addition, current systems are incapable of regulating and refining data with an aim to tune specificity and sensitivity. A robust and flexible tool that allows automated reaction rule set creation along with regulated pathway prediction and analyses is a need. ReactPRED aims to address the same. ReactPRED is an open source flexible and customizable tool enabling users to predict biochemical reactions and pathways. The tool allows automated reaction rule creation from a user defined reaction set. Additionally, reaction rule degree and rule tolerance features allow refinement of predicted data. It is available as a flexible graphical user interface and a console application. ReactPRED is available at: https://sourceforge.net/projects/reactpred/ CONTACT: anirban.b@samsung.com or ty76.kim@samsung.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Next-Generation Undersea Warfare and Undersea Distributed Networked Systems

DTIC Science & Technology

2007-01-31

Probability of false alarm R5 Redeployment, refueling, repositioning, replacement, and recovery ROE Rules of engagement RSTA Reconnaissance, surveillance...and decision aids) at a given point, considering mission, tasks, rules of engagement (ROE), objectives, and other appropriate factors. " Manning within...trajectories are important and must occur concurrently; they must, however, be governed by different rule sets.21 II Mission Capability Centric .•UDNS

C4ISR Architecture Working Group (AWG), Architecture Framework Version 2.0.

DTIC Science & Technology

1997-12-18

Vision Name Name/identifier of document that contains doctrine, goals, or vision Type Doctrine, goals, or vision Description Text summary description...e.g., organization, directive, order) Description Text summary of tasking •Rules, Criteria, or Conventions Name Name/identifier of document that...contains rules, criteria, or conventions Type One of: rules, criteria, or conventions Description Text summary description of contents or

Rule learning in autism: the role of reward type and social context.

PubMed

Jones, E J H; Webb, S J; Estes, A; Dawson, G

2013-01-01

Learning abstract rules is central to social and cognitive development. Across two experiments, we used Delayed Non-Matching to Sample tasks to characterize the longitudinal development and nature of rule-learning impairments in children with Autism Spectrum Disorder (ASD). Results showed that children with ASD consistently experienced more difficulty learning an abstract rule from a discrete physical reward than children with DD. Rule learning was facilitated by the provision of more concrete reinforcement, suggesting an underlying difficulty in forming conceptual connections. Learning abstract rules about social stimuli remained challenging through late childhood, indicating the importance of testing executive functions in both social and non-social contexts.

Update on SLD Engineering Tools Development

NASA Technical Reports Server (NTRS)

Miller, Dean R.; Potapczuk, Mark G.; Bond, Thomas H.

2004-01-01

The airworthiness authorities (FAA, JAA, Transport Canada) will be releasing a draft rule in the 2006 timeframe concerning the operation of aircraft in a Supercooled Large Droplet (SLD) environment aloft. The draft rule will require aircraft manufacturers to demonstrate that their aircraft can operate safely in an SLD environment for a period of time to facilitate a safe exit from the condition. It is anticipated that aircraft manufacturers will require a capability to demonstrate compliance with this rule via experimental means (icing tunnels or tankers) and by analytical means (ice prediction codes). Since existing icing research facilities and analytical codes were not developed to account for SLD conditions, current engineering tools are not adequate to support compliance activities in SLD conditions. Therefore, existing capabilities need to be augmented to include SLD conditions. In response to this need, NASA and its partners conceived a strategy or Roadmap for developing experimental and analytical SLD simulation tools. Following review and refinement by the airworthiness authorities and other international research partners, this technical strategy has been crystallized into a project plan to guide the SLD Engineering Tool Development effort. This paper will provide a brief overview of the latest version of the project plan and technical rationale, and provide a status of selected SLD Engineering Tool Development research tasks which are currently underway.

Collaborative Brain-Computer Interface for Aiding Decision-Making

PubMed Central

Poli, Riccardo; Valeriani, Davide; Cinel, Caterina

2014-01-01

We look at the possibility of integrating the percepts from multiple non-communicating observers as a means of achieving better joint perception and better group decisions. Our approach involves the combination of a brain-computer interface with human behavioural responses. To test ideas in controlled conditions, we asked observers to perform a simple matching task involving the rapid sequential presentation of pairs of visual patterns and the subsequent decision as whether the two patterns in a pair were the same or different. We recorded the response times of observers as well as a neural feature which predicts incorrect decisions and, thus, indirectly indicates the confidence of the decisions made by the observers. We then built a composite neuro-behavioural feature which optimally combines the two measures. For group decisions, we uses a majority rule and three rules which weigh the decisions of each observer based on response times and our neural and neuro-behavioural features. Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with the majority rule. An analysis of event-related potentials indicates that substantial differences are present in the proximity of the response for correct and incorrect trials, further corroborating the idea of using hybrids of brain-computer interfaces and traditional strategies for improving decision making. PMID:25072739

Grey matter volume in the cerebellum is related to the processing of grammatical rules in a second language: a structural voxel-based morphometry study.

PubMed

Pliatsikas, Christos; Johnstone, Tom; Marinis, Theodoros

2014-02-01

The experience of learning and using a second language (L2) has been shown to affect the grey matter (GM) structure of the brain. Importantly, GM density in several cortical and subcortical areas has been shown to be related to performance in L2 tasks. Here, we show that bilingualism can lead to increased GM volume in the cerebellum, a structure that has been related to the processing of grammatical rules. Additionally, the cerebellar GM volume of highly proficient L2 speakers is correlated to their performance in a task tapping on grammatical processing in an L2, demonstrating the importance of the cerebellum for the establishment and use of grammatical rules in an L2.

Brain Dynamics in Predicting Driving Fatigue Using a Recurrent Self-Evolving Fuzzy Neural Network.

PubMed

Liu, Yu-Ting; Lin, Yang-Yin; Wu, Shang-Lin; Chuang, Chun-Hsiang; Lin, Chin-Teng

2016-02-01

This paper proposes a generalized prediction system called a recurrent self-evolving fuzzy neural network (RSEFNN) that employs an on-line gradient descent learning rule to address the electroencephalography (EEG) regression problem in brain dynamics for driving fatigue. The cognitive states of drivers significantly affect driving safety; in particular, fatigue driving, or drowsy driving, endangers both the individual and the public. For this reason, the development of brain-computer interfaces (BCIs) that can identify drowsy driving states is a crucial and urgent topic of study. Many EEG-based BCIs have been developed as artificial auxiliary systems for use in various practical applications because of the benefits of measuring EEG signals. In the literature, the efficacy of EEG-based BCIs in recognition tasks has been limited by low resolutions. The system proposed in this paper represents the first attempt to use the recurrent fuzzy neural network (RFNN) architecture to increase adaptability in realistic EEG applications to overcome this bottleneck. This paper further analyzes brain dynamics in a simulated car driving task in a virtual-reality environment. The proposed RSEFNN model is evaluated using the generalized cross-subject approach, and the results indicate that the RSEFNN is superior to competing models regardless of the use of recurrent or nonrecurrent structures.

A Novel Biclustering Approach to Association Rule Mining for Predicting HIV-1–Human Protein Interactions

PubMed Central

Mukhopadhyay, Anirban; Maulik, Ujjwal; Bandyopadhyay, Sanghamitra

2012-01-01

Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1–human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1–human interaction network. Novel HIV-1–human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed. PMID:22539940

Combined rule extraction and feature elimination in supervised classification.

PubMed

Liu, Sheng; Patel, Ronak Y; Daga, Pankaj R; Liu, Haining; Fu, Gang; Doerksen, Robert J; Chen, Yixin; Wilkins, Dawn E

2012-09-01

There are a vast number of biology related research problems involving a combination of multiple sources of data to achieve a better understanding of the underlying problems. It is important to select and interpret the most important information from these sources. Thus it will be beneficial to have a good algorithm to simultaneously extract rules and select features for better interpretation of the predictive model. We propose an efficient algorithm, Combined Rule Extraction and Feature Elimination (CRF), based on 1-norm regularized random forests. CRF simultaneously extracts a small number of rules generated by random forests and selects important features. We applied CRF to several drug activity prediction and microarray data sets. CRF is capable of producing performance comparable with state-of-the-art prediction algorithms using a small number of decision rules. Some of the decision rules are biologically significant.

Post-KR Delay Intervals and Mental Practice: A Test of Adams' Closed Loop Theory

ERIC Educational Resources Information Center

Bole, Ronald

1976-01-01

The present study suggests that post-KR delay interval time or activity in the interval has little to do with learning on a self-paced positioning task, not ruling out that on ballistic tasks or more complex nonballistic tasks that a learner could make use of additional time or strategy. (MB)

77 FR 17534 - Self-Regulatory Organizations; The Depository Trust Company; Notice of Filing of Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-26

... Association (``SIFMA'') formed the MMI Blue-Sky Task Force (``Task Force'') to address systemic and unique... processing. The Task Force, along other money market industry members,\\8\\ determined that DTC's current MMI... amount or proceeds after the 3 p.m. E.T. deadline for RTP instructions.\\9\\ Accordingly, DTC is proposing...

Dissociable Top-Down Anticipatory Neural States for Different Linguistic Dimensions

ERIC Educational Resources Information Center

Ruz, Maria; Nobre, Anna C.

2008-01-01

When preparing to perform a task, the brain settles into task-set states which are relevant for the selection of the appropriate task-rules and stimulus-response mappings. The way this selection takes place within the Language domain is not well understood. We used high-density electrophysiological recordings while participants were engaged in a…

Goal Neglect and Working Memory Capacity in 4- to 6-Year-Old Children

ERIC Educational Resources Information Center

Marcovitch, Stuart; Boseovski, Janet J.; Knapp, Robin J.; Kane, Michael J.

2010-01-01

Goal neglect is the phenomenon of failing to execute the momentary demands of a task despite understanding and being able to recall the task instructions. Successful goal maintenance is more likely to occur in adults with high working memory capacity (WMC) who can keep rules mentally accessible while performing the task. The current study…

Natural frequencies facilitate diagnostic inferences of managers

PubMed Central

Hoffrage, Ulrich; Hafenbrädl, Sebastian; Bouquet, Cyril

2015-01-01

In Bayesian inference tasks, information about base rates as well as hit rate and false-alarm rate needs to be integrated according to Bayes’ rule after the result of a diagnostic test became known. Numerous studies have found that presenting information in a Bayesian inference task in terms of natural frequencies leads to better performance compared to variants with information presented in terms of probabilities or percentages. Natural frequencies are the tallies in a natural sample in which hit rate and false-alarm rate are not normalized with respect to base rates. The present research replicates the beneficial effect of natural frequencies with four tasks from the domain of management, and with management students as well as experienced executives as participants. The percentage of Bayesian responses was almost twice as high when information was presented in natural frequencies compared to a presentation in terms of percentages. In contrast to most tasks previously studied, the majority of numerical responses were lower than the Bayesian solutions. Having heard of Bayes’ rule prior to the study did not affect Bayesian performance. An implication of our work is that textbooks explaining Bayes’ rule should teach how to represent information in terms of natural frequencies instead of how to plug probabilities or percentages into a formula. PMID:26157397

Brain activity across the development of automatic categorization: A comparison of categorization tasks using multi-voxel pattern analysis

PubMed Central

Soto, Fabian A.; Waldschmidt, Jennifer G.; Helie, Sebastien; Ashby, F. Gregory

2013-01-01

Previous evidence suggests that relatively separate neural networks underlie initial learning of rule-based and information-integration categorization tasks. With the development of automaticity, categorization behavior in both tasks becomes increasingly similar and exclusively related to activity in cortical regions. The present study uses multi-voxel pattern analysis to directly compare the development of automaticity in different categorization tasks. Each of three groups of participants received extensive training in a different categorization task: either an information-integration task, or one of two rule-based tasks. Four training sessions were performed inside an MRI scanner. Three different analyses were performed on the imaging data from a number of regions of interest (ROIs). The common patterns analysis had the goal of revealing ROIs with similar patterns of activation across tasks. The unique patterns analysis had the goal of revealing ROIs with dissimilar patterns of activation across tasks. The representational similarity analysis aimed at exploring (1) the similarity of category representations across ROIs and (2) how those patterns of similarities compared across tasks. The results showed that common patterns of activation were present in motor areas and basal ganglia early in training, but only in the former later on. Unique patterns were found in a variety of cortical and subcortical areas early in training, but they were dramatically reduced with training. Finally, patterns of representational similarity between brain regions became increasingly similar across tasks with the development of automaticity. PMID:23333700

Rapid extraction of auditory feature contingencies.

PubMed

Bendixen, Alexandra; Prinz, Wolfgang; Horváth, János; Trujillo-Barreto, Nelson J; Schröger, Erich

2008-07-01

Contingent relations between sensory events render the environment predictable and thus facilitate adaptive behavior. The human capacity to detect such relations has been comprehensively demonstrated in paradigms in which contingency rules were task-relevant or in which they applied to motor behavior. The extent to which contingencies can also be extracted from events that are unrelated to the current goals of the organism has remained largely unclear. The present study addressed the emergence of contingency-related effects for behaviorally irrelevant auditory stimuli and the cortical areas involved in the processing of such contingency rules. Contingent relations between different features of temporally separate events were embedded in a new dynamic protocol. Participants were presented with the auditory stimulus sequences while their attention was captured by a video. The mismatch negativity (MMN) component of the event-related brain potential (ERP) was employed as an electrophysiological correlate of contingency detection. MMN generators were localized by means of scalp current density (SCD) and primary current density (PCD) analyses with variable resolution electromagnetic tomography (VARETA). Results show that task-irrelevant contingencies can be extracted from about fifteen to twenty successive events conforming to the contingent relation. Topographic and tomographic analyses reveal the involvement of the auditory cortex in the processing of contingency violations. The present data provide evidence for the rapid encoding of complex extrapolative relations in sensory areas. This capacity is of fundamental importance for the organism in its attempt to model the sensory environment outside the focus of attention.

A Diffusion Model Explanation of the Worst Performance Rule for Reaction Time and IQ

ERIC Educational Resources Information Center

Ratcliff, Roger; Schmiedek, Florian; McKoon, Gail

2008-01-01

The worst performance rule for cognitive tasks [Coyle, T.R. (2003). IQ, the worst performance rule, and Spearman's law: A reanalysis and extension. "Intelligence," 31, 567-587] in which reaction time is measured is the result that IQ scores correlate better with longer (i.e., 0.7 and 0.9 quantile) reaction times than shorter (i.e., 0.1 and 0.3…

The Design and Implementation of an Object-Oriented, Production-Rule Interpreter.

DTIC Science & Technology

1984-12-01

S. CONTRACT OR GRANT NUMBER(s) .Heinz M. McArthur 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK AREA & WORK UNIT...implementation of two prototype interpreters for Omega, an object-oriented, production- rule programming language. The first implementation is a throw- away...production-rule programming language. The first implementa- tion is a throw-away prototype written in LISP; the second implementation is a more complete

Intuitive Interference in Probabilistic Reasoning

ERIC Educational Resources Information Center

Babai, Reuven; Brecher, Tali; Stavy, Ruth; Tirosh, Dina

2006-01-01

One theoretical framework which addresses students' conceptions and reasoning processes in mathematics and science education is the intuitive rules theory. According to this theory, students' reasoning is affected by intuitive rules when they solve a wide variety of conceptually non-related mathematical and scientific tasks that share some common…

Validity of the MicroDYN Approach: Complex Problem Solving Predicts School Grades beyond Working Memory Capacity

ERIC Educational Resources Information Center

Schweizer, Fabian; Wustenberg, Sascha; Greiff, Samuel

2013-01-01

This study examines the validity of the complex problem solving (CPS) test MicroDYN by investigating a) the relation between its dimensions--rule identification (exploration strategy), rule knowledge (acquired knowledge), rule application (control performance)--and working memory capacity (WMC), and b) whether CPS predicts school grades in…

Parkinson's disease and dopaminergic therapy—differential effects on movement, reward and cognition

PubMed Central

Hughes, L.; Ghosh, B. C. P.; Eckstein, D.; Williams-Gray, C. H.; Fallon, S.; Barker, R. A.; Owen, A. M.

2008-01-01

Cognitive deficits are very common in Parkinson's disease particularly for ‘executive functions’ associated with frontal cortico-striatal networks. Previous work has identified deficits in tasks that require attentional control like task-switching, and reward-based tasks like gambling or reversal learning. However, there is a complex relationship between the specific cognitive problems faced by an individual patient, their stage of disease and dopaminergic treatment. We used a bimodality continuous performance task during fMRI to examine how patients with Parkinson's disease represent the prospect of reward and switch between competing task rules accordingly. The task-switch was not separately cued but was based on the implicit reward relevance of spatial and verbal dimensions of successive compound stimuli. Nineteen patients were studied in relative ‘on’ and ‘off’ states, induced by dopaminergic medication withdrawal (Hoehn and Yahr stages 1–4). Patients were able to successfully complete the task and establish a bias to one or other dimension in order to gain reward. However the lateral prefrontal cortex and caudate nucleus showed a non-linear U-shape relationship between motor disease severity and regional brain activation. Dopaminergic treatment led to a shift in this U-shape function, supporting the hypothesis of differential neurodegeneration in separate motor and cognitive cortico–striato–thalamo–cortical circuits. In addition, anterior cingulate activation associated with reward expectation declined with more severe disease, whereas activation following actual rewards increased with more severe disease. This may facilitate a change in goal-directed behaviours from deferred predicted rewards to immediate actual rewards, particularly when on dopaminergic treatment. We discuss the implications for investigation and optimal treatment of this common condition at different stages of disease. PMID:18577547

Validation of predictive rules and indices of severity for community acquired pneumonia

PubMed Central

Ewig, S; de Roux, A; Bauer, T; Garcia, E; Mensa, J; Niederman, M; Torres, A

2004-01-01

Background: A study was undertaken to validate the modified American Thoracic Society (ATS) rule and two British Thoracic Society (BTS) rules for the prediction of ICU admission and mortality of community acquired pneumonia and to provide a validation of these predictions on the basis of the pneumonia severity index (PSI). Method: Six hundred and ninety six consecutive patients (457 men (66%), mean (SD) age 67.8 (17.1) years, range 18–101) admitted to a tertiary care hospital were studied prospectively. Of these, 116 (16.7%) were admitted to the ICU. Results: The modified ATS rule achieved a sensitivity of 69% (95% CI 50.7 to 77.2), specificity of 97% (95% CI 96.4 to 98.9), positive predictive value of 87% (95% CI 78.3 to 93.1), and negative predictive value of 94% (95% CI 91.8 to 95.8) in predicting admission to the ICU. The corresponding predictive indices for mortality were 94% (95% CI 82.5 to 98.7), 93% (95% CI 90.6 to 94.7), 49% (95% CI 38.2 to 59.7), and 99.5% (95% CI 98.5 to 99.9), respectively. These figures compared favourably with both the BTS rules. The BTS-CURB criteria achieved predictions of pneumonia severity and mortality comparable to the PSI. Conclusions: This study confirms the power of the modified ATS rule to predict severe pneumonia in individual patients. It may be incorporated into current guidelines for the assessment of pneumonia severity. The CURB criteria may be used as an alternative tool to PSI for the detection of low risk patients. PMID:15115872

Control of information in working memory: Encoding and removal of distractors in the complex-span paradigm.

PubMed

Oberauer, Klaus; Lewandowsky, Stephan

2016-11-01

The article reports four experiments with complex-span tasks in which encoding of memory items alternates with processing of distractors. The experiments test two assumptions of a computational model of complex span, SOB-CS: (1) distractor processing impairs memory because distractors are encoded into working memory, thereby interfering with memoranda; and (2) free time following distractors is used to remove them from working memory by unbinding their representations from list context. Experiment 1 shows that distractors are erroneously chosen for recall more often than not-presented stimuli, demonstrating that distractors are encoded into memory. Distractor intrusions declined with longer free time, as predicted by distractor removal. Experiment 2 shows these effects even when distractors precede the memory list, ruling out an account based on selective rehearsal of memoranda during free time. Experiments 3 and 4 test the notion that distractors decay over time. Both experiments show that, contrary to the notion of distractor decay, the chance of a distractor intruding at test does not decline with increasing time since encoding of that distractor. Experiment 4 provides additional evidence against the prediction from distractor decay that distractor intrusions decline over an unfilled retention interval. Taken together, the results support SOB-CS and rule out alternative explanations. Data and simulation code are available on Open Science Framework: osf.io/3ewh7. Copyright © 2016 Elsevier B.V. All rights reserved.

ERPs recorded during early second language exposure predict syntactic learning.

PubMed

Batterink, Laura; Neville, Helen J

2014-09-01

Millions of adults worldwide are faced with the task of learning a second language (L2). Understanding the neural mechanisms that support this learning process is an important area of scientific inquiry. However, most previous studies on the neural mechanisms underlying L2 acquisition have focused on characterizing the results of learning, relying upon end-state outcome measures in which learning is assessed after it has occurred, rather than on the learning process itself. In this study, we adopted a novel and more direct approach to investigate neural mechanisms engaged during L2 learning, in which we recorded ERPs from beginning adult learners as they were exposed to an unfamiliar L2 for the first time. Learners' proficiency in the L2 was then assessed behaviorally using a grammaticality judgment task, and ERP data acquired during initial L2 exposure were sorted as a function of performance on this task. High-proficiency learners showed a larger N100 effect to open-class content words compared with closed-class function words, whereas low-proficiency learners did not show a significant N100 difference between open- and closed-class words. In contrast, amplitude of the N400 word category effect correlated with learners' L2 comprehension, rather than predicting syntactic learning. Taken together, these results indicate that learners who spontaneously direct greater attention to open- rather than closed-class words when processing L2 input show better syntactic learning, suggesting a link between selective attention to open-class content words and acquisition of basic morphosyntactic rules. These findings highlight the importance of selective attention mechanisms for L2 acquisition.

Rule Learning in Autism: The Role of Reward Type and Social Context

PubMed Central

Jones, E. J. H.; Webb, S. J.; Estes, A.; Dawson, G.

2013-01-01

Learning abstract rules is central to social and cognitive development. Across two experiments, we used Delayed Non-Matching to Sample tasks to characterize the longitudinal development and nature of rule-learning impairments in children with Autism Spectrum Disorder (ASD). Results showed that children with ASD consistently experienced more difficulty learning an abstract rule from a discrete physical reward than children with DD. Rule learning was facilitated by the provision of more concrete reinforcement, suggesting an underlying difficulty in forming conceptual connections. Learning abstract rules about social stimuli remained challenging through late childhood, indicating the importance of testing executive functions in both social and non-social contexts. PMID:23311315

Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.

PubMed

Bösner, Stefan; Haasenritter, Jörg; Becker, Annette; Karatolios, Konstantinos; Vaucher, Paul; Gencer, Baris; Herzig, Lilli; Heinzel-Gutenbrunner, Monika; Schaefer, Juergen R; Abu Hani, Maren; Keller, Heidi; Sönnichsen, Andreas C; Baum, Erika; Donner-Banzhoff, Norbert

2010-09-07

Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result

Influence on Simon and SNARC Effects of a Nonspatial Stimulus-Response Mapping: Between-Task Logical Recoding

ERIC Educational Resources Information Center

Treccani, Barbara; Milanese, Nadia; Umilta, Carlo

2010-01-01

In 4 experiments, we intermixed trials in which the stimulus color was relevant with trials where participants had to judge the stimulus shape or parity and found that the logical-recoding rule (Hedge & Marsh, 1975) applied to the relevant dimension in a task can generalize to the irrelevant dimension of the other task. The mapping…

TASK: Anarchy in the Artroom

ERIC Educational Resources Information Center

Schubert, Cynthia; Van Patten, Kelda

2012-01-01

Most teenagers do not really like to be told what to do. For that matter, most adults don't either. This article discusses contemporary artist Oliver Herring's TASK, which is an opportunity for participants to bend or define the rules on their own terms. It is about choice, and, for many, it is a dream come true. TASK is controlled chaos that can…

Coreference analysis in clinical notes: a multi-pass sieve with alternate anaphora resolution modules.

PubMed

Jonnalagadda, Siddhartha Reddy; Li, Dingcheng; Sohn, Sunghwan; Wu, Stephen Tze-Inn; Wagholikar, Kavishwar; Torii, Manabu; Liu, Hongfang

2012-01-01

This paper describes the coreference resolution system submitted by Mayo Clinic for the 2011 i2b2/VA/Cincinnati shared task Track 1C. The goal of the task was to construct a system that links the markables corresponding to the same entity. The task organizers provided progress notes and discharge summaries that were annotated with the markables of treatment, problem, test, person, and pronoun. We used a multi-pass sieve algorithm that applies deterministic rules in the order of preciseness and simultaneously gathers information about the entities in the documents. Our system, MedCoref, also uses a state-of-the-art machine learning framework as an alternative to the final, rule-based pronoun resolution sieve. The best system that uses a multi-pass sieve has an overall score of 0.836 (average of B(3), MUC, Blanc, and CEAF F score) for the training set and 0.843 for the test set. A supervised machine learning system that typically uses a single function to find coreferents cannot accommodate irregularities encountered in data especially given the insufficient number of examples. On the other hand, a completely deterministic system could lead to a decrease in recall (sensitivity) when the rules are not exhaustive. The sieve-based framework allows one to combine reliable machine learning components with rules designed by experts. Using relatively simple rules, part-of-speech information, and semantic type properties, an effective coreference resolution system could be designed. The source code of the system described is available at https://sourceforge.net/projects/ohnlp/files/MedCoref.

An efficient approach to understanding and predicting the effects of multiple task characteristics on performance.

PubMed

Richardson, Miles

2017-04-01

In ergonomics there is often a need to identify and predict the separate effects of multiple factors on performance. A cost-effective fractional factorial approach to understanding the relationship between task characteristics and task performance is presented. The method has been shown to provide sufficient independent variability to reveal and predict the effects of task characteristics on performance in two domains. The five steps outlined are: selection of performance measure, task characteristic identification, task design for user trials, data collection, regression model development and task characteristic analysis. The approach can be used for furthering knowledge of task performance, theoretical understanding, experimental control and prediction of task performance. Practitioner Summary: A cost-effective method to identify and predict the separate effects of multiple factors on performance is presented. The five steps allow a better understanding of task factors during the design process.

Smooth criminal: convicted rule-breakers show reduced cognitive conflict during deliberate rule violations.

PubMed

Jusyte, Aiste; Pfister, Roland; Mayer, Sarah V; Schwarz, Katharina A; Wirth, Robert; Kunde, Wilfried; Schönenberg, Michael

2017-09-01

Classic findings on conformity and obedience document a strong and automatic drive of human agents to follow any type of rule or social norm. At the same time, most individuals tend to violate rules on occasion, and such deliberate rule violations have recently been shown to yield cognitive conflict for the rule-breaker. These findings indicate persistent difficulty to suppress the rule representation, even though rule violations were studied in a controlled experimental setting with neither gains nor possible sanctions for violators. In the current study, we validate these findings by showing that convicted criminals, i.e., individuals with a history of habitual and severe forms of rule violations, can free themselves from such cognitive conflict in a similarly controlled laboratory task. These findings support an emerging view that aims at understanding rule violations from the perspective of the violating agent rather than from the perspective of outside observer.

Prefrontal Contributions to Rule-Based and Information-Integration Category Learning

ERIC Educational Resources Information Center

Schnyer, David M.; Maddox, W. Todd; Ell, Shawn; Davis, Sarah; Pacheco, Jenni; Verfaellie, Mieke

2009-01-01

Previous research revealed that the basal ganglia play a critical role in category learning [Ell, S. W., Marchant, N. L., & Ivry, R. B. (2006). "Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks." "Neuropsychologia", 44(10), 1737-1751; Maddox, W. T. & Filoteo, J.…

The advantages of the surface Laplacian in brain-computer interface research.

PubMed

McFarland, Dennis J

2015-09-01

Brain-computer interface (BCI) systems frequently use signal processing methods, such as spatial filtering, to enhance performance. The surface Laplacian can reduce spatial noise and aid in identification of sources. In BCI research, these two functions of the surface Laplacian correspond to prediction accuracy and signal orthogonality. In the present study, an off-line analysis of data from a sensorimotor rhythm-based BCI task dissociated these functions of the surface Laplacian by comparing nearest-neighbor and next-nearest neighbor Laplacian algorithms. The nearest-neighbor Laplacian produced signals that were more orthogonal while the next-nearest Laplacian produced signals that resulted in better accuracy. Both prediction and signal identification are important for BCI research. Better prediction of user's intent produces increased speed and accuracy of communication and control. Signal identification is important for ruling out the possibility of control by artifacts. Identifying the nature of the control signal is relevant both to understanding exactly what is being studied and in terms of usability for individuals with limited motor control. Copyright © 2014 Elsevier B.V. All rights reserved.

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making.

PubMed

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks.

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

PubMed Central

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks. PMID:28824512

Predictive performance of universal termination of resuscitation rules in an Asian community: are they accurate enough?

PubMed

Chiang, Wen-Chu; Ko, Patrick Chow-In; Chang, Anna Marie; Liu, Sot Shih-Hung; Wang, Hui-Chih; Yang, Chih-Wei; Hsieh, Ming-Ju; Chen, Shey-Ying; Lai, Mei-Shu; Ma, Matthew Huei-Ming

2015-04-01

Prehospital termination of resuscitation (TOR) rules have not been widely validated outside of Western countries. This study evaluated the performance of TOR rules in an Asian metropolitan with a mixed-tier emergency medical service (EMS). We analysed the Utstein registry of adult, non-traumatic out-of-hospital cardiac arrests (OHCAs) in Taipei to test the performance of TOR rules for advanced life support (ALS) or basic life support (BLS) providers. ALS and BLS-TOR rules were tested in OHCAs among three subgroups: (1) resuscitated by ALS, (2) by BLS and (3) by mixed ALS and BLS. Outcome definition was in-hospital death. Sensitivity, specificity, positive predictive value (PPV), negative predictive value and decreased transport rate (DTR) among various provider combinations were calculated. Of the 3489 OHCAs included, 240 were resuscitated by ALS, 1727 by BLS and 1522 by ALS and BLS. Overall survival to hospital discharge was 197 patients (5.6%). Specificity and PPV of ALS-TOR and BLS-TOR for identifying death ranged from 70.7% to 81.8% and 95.1% to 98.1%, respectively. Applying the TOR rules would have a DTR of 34.2-63.9%. BLS rules had better predictive accuracy and DTR than ALS rules among all subgroups. Application of the ALS and BLS TOR rules would have decreased OHCA transported to the hospital, and BLS rules are reasonable as the universal criteria in a mixed-tier EMS. However, 1.9-4.9% of those who survived would be misclassified as non-survivors, raising concern of compromising patient safety for the implementation of the rules. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Semantic Web Research Trends and Directions

DTIC Science & Technology

2006-01-01

workflow templates. Workflow templates are used for various different tasks such as en- coding business rules in a B2B application, specifying domain...recently suggest that rules are desirable in this space, both in terms of their expressivity, and in some cases, due to their attractive computational...of OWL documents. However, in most cases, a more attractive solution is to simply write a rule that captures the inference needed, as it is reusable

The cognitive bases of the development of past and future episodic cognition in preschoolers.

PubMed

Ünal, Gülten; Hohenberger, Annette

2017-10-01

The aim of this study was to use a minimalist framework to examine the joint development of past and future episodic cognition and their underlying cognitive abilities in 3- to 5-year-old Turkish preschoolers. Participants engaged in two main tasks, a what-where-when (www) task to measure episodic memory and a future prediction task to measure episodic future thinking. Three additional tasks were used for predicting children's performance in the two main tasks: a temporal language task, an executive function task, and a spatial working memory task. Results indicated that past and future episodic tasks were significantly correlated with each other even after controlling for age. Hierarchical multiple regressions showed that, after controlling for age, the www task was predicted by executive functions, possibly supporting binding of episodic information and by linguistic abilities. The future prediction task was predicted by linguistic abilities alone, underlining the importance of language for episodic past and future thinking. Copyright © 2017 Elsevier Inc. All rights reserved.

Multimodal neural correlates of cognitive control in the Human Connectome Project.

PubMed

Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas; Kandala, Sridhar; Calhoun, Vince D; Barch, Deanna M

2017-12-01

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions hypothesized to be modulated by cognitive control signaling, such as visual cortex. Taken together, these results illustrate the potential utility of multi-modal analyses in identifying the neural correlates of cognitive control across different indicators of brain structure and function. Copyright © 2017 Elsevier Inc. All rights reserved.

Response Times to Stimuli of Increasing Complexity as a Function of Aging

ERIC Educational Resources Information Center

Jordan, T. C.; Rabbitt, P. M. A.

1977-01-01

These experiments consider the effects of aging on response times to stimuli of increasing complexity in serial choice RT tasks, whether age differences were reduced or abolished on such tasks, and examines repetition effects of a particular coding rule. (Author/RK)

No interpretation without representation: the role of domain-specific representations and inferences in the Wason selection task.

PubMed

Fiddick, L; Cosmides, L; Tooby, J

2000-10-16

The Wason selection task is a tool used to study reasoning about conditional rules. Performance on this task changes systematically when one varies its content, and these content effects have been used to argue that the human cognitive architecture contains a number of domain-specific representation and inference systems, such as social contract algorithms and hazard management systems. Recently, however, Sperber, Cara & Girotto (Sperber, D., Cara, F., & Girotto, V. (1995). Relevance theory explains the selection task. Cognition, 57, 31-95) have proposed that relevance theory can explain performance on the selection task - including all content effects - without invoking inference systems that are content-specialized. Herein, we show that relevance theory alone cannot explain a variety of content effects - effects that were predicted in advance and are parsimoniously explained by theories that invoke domain-specific algorithms for representing and making inferences about (i) social contracts and (ii) reducing risk in hazardous situations. Moreover, although Sperber et al. (1995) were able to use relevance theory to produce some new content effects in other domains, they conducted no experiments involving social exchanges or precautions, and so were unable to determine which - content-specialized algorithms or relevance effects - dominate reasoning when the two conflict. When experiments, reported herein, are constructed so that the different theories predict divergent outcomes, the results support the predictions of social contract theory and hazard management theory, indicating that these inference systems override content-general relevance factors. The fact that social contract and hazard management algorithms provide better explanations for performance in their respective domains does not mean that the content-general logical procedures posited by relevance theory do not exist, or that relevance effects never occur. It does mean, however, that one needs a principled way of explaining which effects will dominate when a set of inputs activate more than one reasoning system. We propose the principle of pre-emptive specificity - that the human cognitive architecture should be designed so that more specialized inference systems pre-empt more general ones whenever the stimuli centrally fit the input conditions of the more specialized system. This principle follows from evolutionary and computational considerations that are common to both relevance theory and the ecological rationality approach.

Preschool Phonological and Morphological Awareness As Longitudinal Predictors of Early Reading and Spelling Development in Greek.

PubMed

Diamanti, Vassiliki; Mouzaki, Angeliki; Ralli, Asimina; Antoniou, Faye; Papaioannou, Sofia; Protopapas, Athanassios

2017-01-01

Different language skills are considered fundamental for successful reading and spelling acquisition. Extensive evidence has highlighted the central role of phonological awareness in early literacy experiences. However, many orthographic systems also require the contribution of morphological awareness. The goal of this study was to examine the morphological and phonological awareness skills of preschool children as longitudinal predictors of reading and spelling ability by the end of first grade, controlling for the effects of receptive and expressive vocabulary skills. At Time 1 preschool children from kindergartens in the Greek regions of Attika, Crete, Macedonia, and Thessaly were assessed on tasks tapping receptive and expressive vocabulary, phonological awareness (syllable and phoneme), and morphological awareness (inflectional and derivational). Tasks were administered through an Android application for mobile devices (tablets) featuring automatic application of ceiling rules. At Time 2 one year later the same children attending first grade were assessed on measures of word and pseudoword reading, text reading fluency, text reading comprehension, and spelling. Complete data from 104 children are available. Hierarchical linear regression and commonality analyses were conducted for each outcome variable. Reading accuracy for both words and pseudowords was predicted not only by phonological awareness, as expected, but also by morphological awareness, suggesting that understanding the functional role of word parts supports the developing phonology-orthography mappings. However, only phonological awareness predicted text reading fluency at this age. Longitudinal prediction of reading comprehension by both receptive vocabulary and morphological awareness was already evident at this age, as expected. Finally, spelling was predicted by preschool phonological awareness, as expected, as well as by morphological awareness, the contribution of which is expected to increase due to the spelling demands of Greek inflectional and derivational suffixes introduced at later grades.

Selective testing strategies for diagnosing group A streptococcal infection in children with pharyngitis: a systematic review and prospective multicentre external validation study

PubMed Central

Cohen, Jérémie F.; Cohen, Robert; Levy, Corinne; Thollot, Franck; Benani, Mohamed; Bidet, Philippe; Chalumeau, Martin

2015-01-01

Background: Several clinical prediction rules for diagnosing group A streptococcal infection in children with pharyngitis are available. We aimed to compare the diagnostic accuracy of rules-based selective testing strategies in a prospective cohort of children with pharyngitis. Methods: We identified clinical prediction rules through a systematic search of MEDLINE and Embase (1975–2014), which we then validated in a prospective cohort involving French children who presented with pharyngitis during a 1-year period (2010–2011). We diagnosed infection with group A streptococcus using two throat swabs: one obtained for a rapid antigen detection test (StreptAtest, Dectrapharm) and one obtained for culture (reference standard). We validated rules-based selective testing strategies as follows: low risk of group A streptococcal infection, no further testing or antibiotic therapy needed; intermediate risk of infection, rapid antigen detection for all patients and antibiotic therapy for those with a positive test result; and high risk of infection, empiric antibiotic treatment. Results: We identified 8 clinical prediction rules, 6 of which could be prospectively validated. Sensitivity and specificity of rules-based selective testing strategies ranged from 66% (95% confidence interval [CI] 61–72) to 94% (95% CI 92–97) and from 40% (95% CI 35–45) to 88% (95% CI 85–91), respectively. Use of rapid antigen detection testing following the clinical prediction rule ranged from 24% (95% CI 21–27) to 86% (95% CI 84–89). None of the rules-based selective testing strategies achieved our diagnostic accuracy target (sensitivity and specificity > 85%). Interpretation: Rules-based selective testing strategies did not show sufficient diagnostic accuracy in this study population. The relevance of clinical prediction rules for determining which children with pharyngitis should undergo a rapid antigen detection test remains questionable. PMID:25487666

Prospective comparison of three predictive rules for assessing severity of community‐acquired pneumonia in Hong Kong

PubMed Central

Man, Shin Yan; Lee, Nelson; Ip, Margaret; Antonio, Gregory E; Chau, Shirley SL; Mak, Paulina; Graham, Colin A; Zhang, Mingdong; Lui, Grace; Chan, Paul K S; Ahuja, Anil T; Hui, David S; Sung, Joseph J Y; Rainer, Timothy H

2007-01-01

Background Community‐acquired pneumonia (CAP) is a leading infectious cause of death throughout the world, including Hong Kong. Aim To compare the ability of three validated prediction rules for CAP to predict mortality in Hong Kong: the 20 variable Pneumonia Severity Index (PSI), the 6‐point CURB65 scale adopted by the British Thoracic Society and the simpler CRB65. Methods A prospective observational study of 1016 consecutive inpatients with CAP (583 men, mean (SD) age 72 (17) years) was performed in a university hospital in the New Territories of Hong Kong in 2004. The patients were classified into three risk groups (low, intermediate and high) according to each rule. The ability of the three rules to predict 30 day mortality was compared. Results The overall mortality and intensive care unit (ICU) admission rates were 8.6% and 4.0%, respectively. PSI, CURB65 and CRB65 performed similarly, and the areas under the receiver operating characteristic (ROC) curve were 0.736 (95% CI 0.687 to 0.736), 0.733 (95% CI 0.679 to 0.787) and 0.694 (95% CI 0.634 to 0.753), respectively. All three rules had high negative predictive values but relatively low positive predictive values at all cut‐off points. Larger proportions of patients were identified as low risk by PSI (47.2%) and CURB65 (43.3%) than by CRB65 (12.6%). Conclusion All three predictive rules have a similar performance in predicting the severity of CAP, but CURB65 is more suitable than the other two for use in the emergency department because of its simplicity of application and ability to identify low‐risk patients. PMID:17121867

Ottawa Ankle Rules and Subjective Surgeon Perception to Evaluate Radiograph Necessity Following Foot and Ankle Sprain

PubMed Central

Pires, RES; Pereira, AA; Abreu-e-Silva, GM; Labronici, PJ; Figueiredo, LB; Godoy-Santos, AL; Kfuri, M

2014-01-01

Background: Foot and ankle injuries are frequent in emergency departments. Although only a few patients with foot and ankle sprain present fractures and the fracture patterns are almost always simple, lack of fracture diagnosis can lead to poor functional outcomes. Aim: The present study aims to evaluate the reliability of the Ottawa ankle rules and the orthopedic surgeon subjective perception to assess foot and ankle fractures after sprains. Subjects and Methods: A cross-sectional study was conducted from July 2012 to December 2012. Ethical approval was granted. Two hundred seventy-four adult patients admitted to the emergency department with foot and/or ankle sprain were evaluated by an orthopedic surgeon who completed a questionnaire prior to radiographic assessment. The Ottawa ankle rules and subjective perception of foot and/or ankle fractures were evaluated on the questionnaire. Results: Thirteen percent (36/274) patients presented fracture. Orthopedic surgeon subjective analysis showed 55.6% sensitivity, 90.1% specificity, 46.5% positive predictive value and 92.9% negative predictive value. The general orthopedic surgeon opinion accuracy was 85.4%. The Ottawa ankle rules presented 97.2% sensitivity, 7.8% specificity, 13.9% positive predictive value, 95% negative predictive value and 19.9% accuracy respectively. Weight-bearing inability was the Ottawa ankle rule item that presented the highest reliability, 69.4% sensitivity, 61.6% specificity, 63.1% accuracy, 21.9% positive predictive value and 93% negative predictive value respectively. Conclusion: The Ottawa ankle rules showed high reliability for deciding when to take radiographs in foot and/or ankle sprains. Weight-bearing inability was the most important isolated item to predict fracture presence. Orthopedic surgeon subjective analysis to predict fracture possibility showed a high specificity rate, representing a confident method to exclude unnecessary radiographic exams. PMID:24971221

A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules.

PubMed

Nguyen, Su; Mei, Yi; Xue, Bing; Zhang, Mengjie

2018-06-04

Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine learning, and optimisation techniques has made the automated design of dispatching rules possible and automatically discovered rules are competitive or outperform existing rules developed by researchers. Genetic programming is one of the most popular approaches to discovering dispatching rules in the literature, especially for complex production systems. However, the large heuristic search space may restrict genetic programming from finding near optimal dispatching rules. This paper develops a new hybrid genetic programming algorithm for dynamic job shop scheduling based on a new representation, a new local search heuristic, and efficient fitness evaluators. Experiments show that the new method is effective regarding the quality of evolved rules. Moreover, evolved rules are also significantly smaller and contain more relevant attributes.

Evil genius? How dishonesty can lead to greater creativity.

PubMed

Gino, Francesca; Wiltermuth, Scott S

2014-04-01

We propose that dishonest and creative behavior have something in common: They both involve breaking rules. Because of this shared feature, creativity may lead to dishonesty (as shown in prior work), and dishonesty may lead to creativity (the hypothesis we tested in this research). In five experiments, participants had the opportunity to behave dishonestly by overreporting their performance on various tasks. They then completed one or more tasks designed to measure creativity. Those who cheated were subsequently more creative than noncheaters, even when we accounted for individual differences in their creative ability (Experiment 1). Using random assignment, we confirmed that acting dishonestly leads to greater creativity in subsequent tasks (Experiments 2 and 3). The link between dishonesty and creativity is explained by a heightened feeling of being unconstrained by rules, as indicated by both mediation (Experiment 4) and moderation (Experiment 5).

Nothing can be coincidence: synaptic inhibition and plasticity in the cerebellar nuclei

PubMed Central

Pugh, Jason R.; Raman, Indira M.

2009-01-01

Many cerebellar neurons fire spontaneously, generating 10–100 action potentials per second even without synaptic input. This high basal activity correlates with information-coding mechanisms that differ from those of cells that are quiescent until excited synaptically. For example, in the deep cerebellar nuclei, Hebbian patterns of coincident synaptic excitation and postsynaptic firing fail to induce long-term increases in the strength of excitatory inputs. Instead, excitatory synaptic currents are potentiated by combinations of inhibition and excitation that resemble the activity of Purkinje and mossy fiber afferents that is predicted to occur during cerebellar associative learning tasks. Such results indicate that circuits with intrinsically active neurons have rules for information transfer and storage that distinguish them from other brain regions. PMID:19178955

Redundancy checking algorithms based on parallel novel extension rule

NASA Astrophysics Data System (ADS)

Liu, Lei; Yang, Yang; Li, Guangli; Wang, Qi; Lü, Shuai

2017-05-01

Redundancy checking (RC) is a key knowledge reduction technology. Extension rule (ER) is a new reasoning method, first presented in 2003 and well received by experts at home and abroad. Novel extension rule (NER) is an improved ER-based reasoning method, presented in 2009. In this paper, we first analyse the characteristics of the extension rule, and then present a simple algorithm for redundancy checking based on extension rule (RCER). In addition, we introduce MIMF, a type of heuristic strategy. Using the aforementioned rule and strategy, we design and implement RCHER algorithm, which relies on MIMF. Next we design and implement an RCNER (redundancy checking based on NER) algorithm based on NER. Parallel computing greatly accelerates the NER algorithm, which has weak dependence among tasks when executed. Considering this, we present PNER (parallel NER) and apply it to redundancy checking and necessity checking. Furthermore, we design and implement the RCPNER (redundancy checking based on PNER) and NCPPNER (necessary clause partition based on PNER) algorithms as well. The experimental results show that MIMF significantly influences the acceleration of algorithm RCER in formulae on a large scale and high redundancy. Comparing PNER with NER and RCPNER with RCNER, the average speedup can reach up to the number of task decompositions when executed. Comparing NCPNER with the RCNER-based algorithm on separating redundant formulae, speedup increases steadily as the scale of the formulae is incrementing. Finally, we describe the challenges that the extension rule will be faced with and suggest possible solutions.

Normalizing biomedical terms by minimizing ambiguity and variability

PubMed Central

Tsuruoka, Yoshimasa; McNaught, John; Ananiadou, Sophia

2008-01-01

Background One of the difficulties in mapping biomedical named entities, e.g. genes, proteins, chemicals and diseases, to their concept identifiers stems from the potential variability of the terms. Soft string matching is a possible solution to the problem, but its inherent heavy computational cost discourages its use when the dictionaries are large or when real time processing is required. A less computationally demanding approach is to normalize the terms by using heuristic rules, which enables us to look up a dictionary in a constant time regardless of its size. The development of good heuristic rules, however, requires extensive knowledge of the terminology in question and thus is the bottleneck of the normalization approach. Results We present a novel framework for discovering a list of normalization rules from a dictionary in a fully automated manner. The rules are discovered in such a way that they minimize the ambiguity and variability of the terms in the dictionary. We evaluated our algorithm using two large dictionaries: a human gene/protein name dictionary built from BioThesaurus and a disease name dictionary built from UMLS. Conclusions The experimental results showed that automatically discovered rules can perform comparably to carefully crafted heuristic rules in term mapping tasks, and the computational overhead of rule application is small enough that a very fast implementation is possible. This work will help improve the performance of term-concept mapping tasks in biomedical information extraction especially when good normalization heuristics for the target terminology are not fully known. PMID:18426547

Can history and exam alone reliably predict pneumonia?

PubMed

Graffelman, A W; le Cessie, S; Knuistingh Neven, A; Wilemssen, F E J A; Zonderland, H M; van den Broek, P J

2007-06-01

Prediction rules based on clinical information have been developed to support the diagnosis of pneumonia and help limit the use of expensive diagnostic tests. However, these prediction rules need to be validated in the primary care setting. Adults who met our definition of lower respiratory tract infection (LRTI) were recruited for a prospective study on the causes of LRTI, between November 15, 1998 and June 1, 2001 in the Leiden region of The Netherlands. Clinical information was collected and chest radiography was performed. A literature search was also done to find prediction rules for pneumonia. 129 patients--26 with pneumonia and 103 without--were included, and 6 prediction rules were applied. Only the model with the addition of a test for C-reactive protein had a significant area under the curve of 0.69 (95% confidence interval [CI], 0.58-0.80), with a positive predictive value of 47% (95% CI, 23-71) and a negative predictive value of 84% (95% CI, 77-91). The pretest probabilities for the presence and absence of pneumonia were 20% and 80%, respectively. Models based only on clinical information do not reliably predict the presence of pneumonia. The addition of an elevated C-reactive protein level seems of little value.

Intertransaction Class Association Rule Mining Based on Genetic Network Programming and Its Application to Stock Market Prediction

NASA Astrophysics Data System (ADS)

Yang, Yuchen; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

Intertransaction association rules have been reported to be useful in many fields such as stock market prediction, but still there are not so many efficient methods to dig them out from large data sets. Furthermore, how to use and measure these more complex rules should be considered carefully. In this paper, we propose a new intertransaction class association rule mining method based on Genetic Network Programming (GNP), which has the ability to overcome some shortages of Apriori-like based intertransaction association methods. Moreover, a general classifier model for intertransaction rules is also introduced. In experiments on the real world application of stock market prediction, the method shows its efficiency and ability to obtain good results and can bring more benefits with a suitable classifier considering larger interval span.

Child personality facets and overreactive parenting as predictors of aggression and rule-breaking trajectories from childhood to adolescence.

PubMed

Becht, Andrik I; Prinzie, Peter; Deković, Maja; van den Akker, Alithe L; Shiner, Rebecca L

2016-05-01

This study examined trajectories of aggression and rule breaking during the transition from childhood to adolescence (ages 9-15), and determined whether these trajectories were predicted by lower order personality facets, overreactive parenting, and their interaction. At three time points separated by 2-year intervals, mothers and fathers reported on their children's aggression and rule breaking (N = 290, M age = 8.8 years at Time 1). At Time 1, parents reported on their children's personality traits and their own overreactivity. Growth mixture modeling identified three aggression trajectories (low decreasing, high decreasing, and high increasing) and two rule-breaking trajectories (low and high). Lower optimism and compliance and higher energy predicted trajectories for both aggression and rule breaking, whereas higher expressiveness and irritability and lower orderliness and perseverance were unique risk factors for increasing aggression into adolescence. Lower concentration was a unique risk factor for increasing rule breaking. Parental overreactivity predicted higher trajectories of aggression but not rule breaking. Only two Trait × Overreactivity interactions were found. Our results indicate that personality facets could differentiate children at risk for different developmental trajectories of aggression and rule breaking.

Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

PubMed Central

Bennett, Kristin P.

2014-01-01

We develop a novel approach for incorporating expert rules into Bayesian networks for classification of Mycobacterium tuberculosis complex (MTBC) clades. The proposed knowledge-based Bayesian network (KBBN) treats sets of expert rules as prior distributions on the classes. Unlike prior knowledge-based support vector machine approaches which require rules expressed as polyhedral sets, KBBN directly incorporates the rules without any modification. KBBN uses data to refine rule-based classifiers when the rule set is incomplete or ambiguous. We develop a predictive KBBN model for 69 MTBC clades found in the SITVIT international collection. We validate the approach using two testbeds that model knowledge of the MTBC obtained from two different experts and large DNA fingerprint databases to predict MTBC genetic clades and sublineages. These models represent strains of MTBC using high-throughput biomarkers called spacer oligonucleotide types (spoligotypes), since these are routinely gathered from MTBC isolates of tuberculosis (TB) patients. Results show that incorporating rules into problems can drastically increase classification accuracy if data alone are insufficient. The SITVIT KBBN is publicly available for use on the World Wide Web. PMID:24864238

Network mechanisms of intentional learning

PubMed Central

Hampshire, Adam; Hellyer, Peter J.; Parkin, Beth; Hiebert, Nole; MacDonald, Penny; Owen, Adrian M.; Leech, Robert; Rowe, James

2016-01-01

The ability to learn new tasks rapidly is a prominent characteristic of human behaviour. This ability relies on flexible cognitive systems that adapt in order to encode temporary programs for processing non-automated tasks. Previous functional imaging studies have revealed distinct roles for the lateral frontal cortices (LFCs) and the ventral striatum in intentional learning processes. However, the human LFCs are complex; they house multiple distinct sub-regions, each of which co-activates with a different functional network. It remains unclear how these LFC networks differ in their functions and how they coordinate with each other, and the ventral striatum, to support intentional learning. Here, we apply a suite of fMRI connectivity methods to determine how LFC networks activate and interact at different stages of two novel tasks, in which arbitrary stimulus-response rules are learnt either from explicit instruction or by trial-and-error. We report that the networks activate en masse and in synchrony when novel rules are being learnt from instruction. However, these networks are not homogeneous in their functions; instead, the directed connectivities between them vary asymmetrically across the learning timecourse and they disengage from the task sequentially along a rostro-caudal axis. Furthermore, when negative feedback indicates the need to switch to alternative stimulus–response rules, there is additional input to the LFC networks from the ventral striatum. These results support the hypotheses that LFC networks interact as a hierarchical system during intentional learning and that signals from the ventral striatum have a driving influence on this system when the internal program for processing the task is updated. PMID:26658925

Promoting Changes in Children's Predictive Rules about Natural Phenomena: The Role of Computer-Based Modelling Strategies. Technical Report.

ERIC Educational Resources Information Center

Frenette, Micheline

Trying to change the predictive rule for the sinking and floating phenomena, students have a great difficulty in understanding density and they are insensitive to empirical counter-examples designed to challenge their own rule. The purpose of this study is to examine the process whereby students from sixth and seventh grades relinquish their…

Assessing the Legality of State Tournament Bans in Interscholastic Athletics

ERIC Educational Resources Information Center

Scott, Beau

2017-01-01

State high school athletic associations are tasked with facilitating equitable athletic opportunities for all member schools. To accomplish this task, state associations implement rules designed to ensure competitive balance (Johnson, Tracy, & Pierce, 2015). With over 7.8 million participants, interscholastic athletics are extremely popular…

Improving the Interpretability of Classification Rules Discovered by an Ant Colony Algorithm: Extended Results.

PubMed

Otero, Fernando E B; Freitas, Alex A

2016-01-01

Most ant colony optimization (ACO) algorithms for inducing classification rules use a ACO-based procedure to create a rule in a one-at-a-time fashion. An improved search strategy has been proposed in the cAnt-Miner[Formula: see text] algorithm, where an ACO-based procedure is used to create a complete list of rules (ordered rules), i.e., the ACO search is guided by the quality of a list of rules instead of an individual rule. In this paper we propose an extension of the cAnt-Miner[Formula: see text] algorithm to discover a set of rules (unordered rules). The main motivations for this work are to improve the interpretation of individual rules by discovering a set of rules and to evaluate the impact on the predictive accuracy of the algorithm. We also propose a new measure to evaluate the interpretability of the discovered rules to mitigate the fact that the commonly used model size measure ignores how the rules are used to make a class prediction. Comparisons with state-of-the-art rule induction algorithms, support vector machines, and the cAnt-Miner[Formula: see text] producing ordered rules are also presented.

Predicting the need for CT imaging in children with minor head injury using an ensemble of Naive Bayes classifiers.

PubMed

Klement, William; Wilk, Szymon; Michalowski, Wojtek; Farion, Ken J; Osmond, Martin H; Verter, Vedat

2012-03-01

Using an automatic data-driven approach, this paper develops a prediction model that achieves more balanced performance (in terms of sensitivity and specificity) than the Canadian Assessment of Tomography for Childhood Head Injury (CATCH) rule, when predicting the need for computed tomography (CT) imaging of children after a minor head injury. CT is widely considered an effective tool for evaluating patients with minor head trauma who have potentially suffered serious intracranial injury. However, its use poses possible harmful effects, particularly for children, due to exposure to radiation. Safety concerns, along with issues of cost and practice variability, have led to calls for the development of effective methods to decide when CT imaging is needed. Clinical decision rules represent such methods and are normally derived from the analysis of large prospectively collected patient data sets. The CATCH rule was created by a group of Canadian pediatric emergency physicians to support the decision of referring children with minor head injury to CT imaging. The goal of the CATCH rule was to maximize the sensitivity of predictions of potential intracranial lesion while keeping specificity at a reasonable level. After extensive analysis of the CATCH data set, characterized by severe class imbalance, and after a thorough evaluation of several data mining methods, we derived an ensemble of multiple Naive Bayes classifiers as the prediction model for CT imaging decisions. In the first phase of the experiment we compared the proposed ensemble model to other ensemble models employing rule-, tree- and instance-based member classifiers. Our prediction model demonstrated the best performance in terms of AUC, G-mean and sensitivity measures. In the second phase, using a bootstrapping experiment similar to that reported by the CATCH investigators, we showed that the proposed ensemble model achieved a more balanced predictive performance than the CATCH rule with an average sensitivity of 82.8% and an average specificity of 74.4% (vs. 98.1% and 50.0% for the CATCH rule respectively). Automatically derived prediction models cannot replace a physician's acumen. However, they help establish reference performance indicators for the purpose of developing clinical decision rules so the trade-off between prediction sensitivity and specificity is better understood. Copyright © 2011 Elsevier B.V. All rights reserved.

A network model of behavioural performance in a rule learning task.

PubMed

Hasselmo, Michael E; Stern, Chantal E

2018-04-19

Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'. © 2018 The Author(s).

Primary motor cortex contributes to the implementation of implicit value-based rules during motor decisions.

PubMed

Derosiere, Gerard; Zénon, Alexandre; Alamia, Andrea; Duque, Julie

2017-02-01

In the present study, we investigated the functional contribution of the human primary motor cortex (M1) to motor decisions. Continuous theta burst stimulation (cTBS) was used to alter M1 activity while participants performed a decision-making task in which the reward associated with the subjects' responses (right hand finger movements) depended on explicit and implicit value-based rules. Subjects performed the task over two consecutive days and cTBS occurred in the middle of Day 2, once the subjects were just about to implement implicit rules, in addition to the explicit instructions, to choose their responses, as evident in the control group (cTBS over the right somatosensory cortex). Interestingly, cTBS over the left M1 prevented subjects from implementing the implicit value-based rule while its implementation was enhanced in the group receiving cTBS over the right M1. Hence, cTBS had opposite effects depending on whether it was applied on the contralateral or ipsilateral M1. The use of the explicit value-based rule was unaffected by cTBS in the three groups of subject. Overall, the present study provides evidence for a functional contribution of M1 to the implementation of freshly acquired implicit rules, possibly through its involvement in a cortico-subcortical network controlling value-based motor decisions. Copyright © 2016 Elsevier Inc. All rights reserved.

The “Silent Dog” Method: Analyzing the Impact of Self-Generated Rules When Teaching Different Computer Chains to Boys with Autism

PubMed Central

Arntzen, Erik; Halstadtro, Lill-Beathe; Halstadtro, Monica

2009-01-01

The purpose of the study was to extend the literature on verbal self-regulation by using the “silent dog” method to evaluate the role of verbal regulation over nonverbal behavior in 2 individuals with autism. Participants were required to talk-aloud while performing functional computer tasks.Then the effects of distracters with increasing demands on target behavior were evaluated as well as whether self-talk emitted by Participant 1 could be used to alter Participant 2's performance. Results suggest that participants' tasks seemed to be under control of self-instructions, and the rules generated from Participants 1's self-talk were effective in teaching computer skills to Participant 2. The silent dog method was useful in evaluating the possible role of self-generated rules in teaching computer skills to participants with autism. PMID:22477428

The "silent dog" method: analyzing the impact of self-generated rules when teaching different computer chains to boys with autism.

PubMed

Arntzen, Erik; Halstadtro, Lill-Beathe; Halstadtro, Monica

2009-01-01

The purpose of the study was to extend the literature on verbal self-regulation by using the "silent dog" method to evaluate the role of verbal regulation over nonverbal behavior in 2 individuals with autism. Participants were required to talk-aloud while performing functional computer tasks.Then the effects of distracters with increasing demands on target behavior were evaluated as well as whether self-talk emitted by Participant 1 could be used to alter Participant 2's performance. Results suggest that participants' tasks seemed to be under control of self-instructions, and the rules generated from Participants 1's self-talk were effective in teaching computer skills to Participant 2. The silent dog method was useful in evaluating the possible role of self-generated rules in teaching computer skills to participants with autism.

The Effects of Concurrent Verbal and Visual Tasks on Category Learning

ERIC Educational Resources Information Center

Miles, Sarah J.; Minda, John Paul

2011-01-01

Current theories of category learning posit separate verbal and nonverbal learning systems. Past research suggests that the verbal system relies on verbal working memory and executive functioning and learns rule-defined categories; the nonverbal system does not rely on verbal working memory and learns non-rule-defined categories (E. M. Waldron…

76 FR 74585 - Railroad Workplace Safety; Adjacent-Track On-Track Safety for Roadway Workers

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-30

... roadway workers on the ground is engaged in a common task with on-track, self-propelled equipment or..., self-propelled equipment on an occupied track. These amendments to the Roadway Worker Protection Rule... effective, the RWP Rule requires that roadway work groups engaged in ``large-scale maintenance or...

Children's Task-Switching Efficiency: Missing Our Cue?

ERIC Educational Resources Information Center

Holt, Anna E.; Deák, Gedeon

2015-01-01

In simple rule-switching tests, 3- and 4-year-olds can follow each of two sorting rules but sometimes make perseverative errors when switching. Older children make few errors but respond slowly when switching. These age-related changes might reflect the maturation of executive functions (e.g., inhibition). However, they might also reflect…

Ego depletion interferes with rule-defined category learning but not non-rule-defined category learning.

PubMed

Minda, John P; Rabi, Rahel

2015-01-01

Considerable research on category learning has suggested that many cognitive and environmental factors can have a differential effect on the learning of rule-defined (RD) categories as opposed to the learning of non-rule-defined (NRD) categories. Prior research has also suggested that ego depletion can temporarily reduce the capacity for executive functioning and cognitive flexibility. The present study examined whether temporarily reducing participants' executive functioning via a resource depletion manipulation would differentially impact RD and NRD category learning. Participants were either asked to write a story with no restrictions (the control condition), or without using two common letters (the ego depletion condition). Participants were then asked to learn either a set of RD categories or a set of NRD categories. Resource depleted participants performed more poorly than controls on the RD task, but did not differ from controls on the NRD task, suggesting that self regulatory resources are required for successful RD category learning. These results lend support to multiple systems theories and clarify the role of self-regulatory resources within this theory.

Implicit learning and reading: insights from typical children and children with developmental dyslexia using the artificial grammar learning (AGL) paradigm.

PubMed

Pavlidou, Elpis V; Williams, Joanne M

2014-07-01

We examined implicit learning in school-aged children with and without developmental dyslexia based on the proposal that implicit learning plays a significant role in mastering fluent reading. We ran two experiments with 16 typically developing children (9 to 11-years-old) and 16 age-matched children with developmental dyslexia using the artificial grammar learning (AGL) paradigm. In Experiment 1 (non-transfer task), children were trained on stimuli that followed patterns (rules) unknown to them. Subsequently, they were asked to decide from a novel set which stimuli follow the same rules (grammaticality judgments). In Experiment 2 (transfer task), training and testing stimuli differed in their superficial characteristics but followed the same rules. Again, children were asked to make grammaticality judgments. Our findings expand upon previous research by showing that children with developmental dyslexia show difficulties in implicit learning that are most likely specific to higher-order rule-like learning. These findings are discussed in relation to current theories of developmental dyslexia and of implicit learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ego depletion interferes with rule-defined category learning but not non-rule-defined category learning

PubMed Central

Minda, John P.; Rabi, Rahel

2015-01-01

Considerable research on category learning has suggested that many cognitive and environmental factors can have a differential effect on the learning of rule-defined (RD) categories as opposed to the learning of non-rule-defined (NRD) categories. Prior research has also suggested that ego depletion can temporarily reduce the capacity for executive functioning and cognitive flexibility. The present study examined whether temporarily reducing participants’ executive functioning via a resource depletion manipulation would differentially impact RD and NRD category learning. Participants were either asked to write a story with no restrictions (the control condition), or without using two common letters (the ego depletion condition). Participants were then asked to learn either a set of RD categories or a set of NRD categories. Resource depleted participants performed more poorly than controls on the RD task, but did not differ from controls on the NRD task, suggesting that self regulatory resources are required for successful RD category learning. These results lend support to multiple systems theories and clarify the role of self-regulatory resources within this theory. PMID:25688220

Debugging expert systems using a dynamically created hypertext network

NASA Technical Reports Server (NTRS)

Boyle, Craig D. B.; Schuette, John F.

1991-01-01

The labor intensive nature of expert system writing and debugging motivated this study. The hypothesis is that a hypertext based debugging tool is easier and faster than one traditional tool, the graphical execution trace. HESDE (Hypertext Expert System Debugging Environment) uses Hypertext nodes and links to represent the objects and their relationships created during the execution of a rule based expert system. HESDE operates transparently on top of the CLIPS (C Language Integrated Production System) rule based system environment and is used during the knowledge base debugging process. During the execution process HESDE builds an execution trace. Use of facts, rules, and their values are automatically stored in a Hypertext network for each execution cycle. After the execution process, the knowledge engineer may access the Hypertext network and browse the network created. The network may be viewed in terms of rules, facts, and values. An experiment was conducted to compare HESDE with a graphical debugging environment. Subjects were given representative tasks. For speed and accuracy, in eight of the eleven tasks given to subjects, HESDE was significantly better.

The transfer of category knowledge by macaques (Macaca mulatta) and humans (Homo sapiens).

PubMed

Zakrzewski, Alexandria C; Church, Barbara A; Smith, J David

2018-02-01

Cognitive psychologists distinguish implicit, procedural category learning (stimulus-response associations learned outside declarative cognition) from explicit-declarative category learning (conscious category rules). These systems are dissociated by category learning tasks with either a multidimensional, information-integration (II) solution or a unidimensional, rule-based (RB) solution. In the present experiments, humans and two monkeys learned II and RB category tasks fostering implicit and explicit learning, respectively. Then they received occasional transfer trials-never directly reinforced-drawn from untrained regions of the stimulus space. We hypothesized that implicit-procedural category learning-allied to associative learning-would transfer weakly because it is yoked to the training stimuli. This result was confirmed for humans and monkeys. We hypothesized that explicit category learning-allied to abstract category rules-would transfer robustly. This result was confirmed only for humans. That is, humans displayed explicit category knowledge that transferred flawlessly. Monkeys did not. This result illuminates the distinctive abstractness, stimulus independence, and representational portability of humans' explicit category rules. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

QUEST/Ada (query utility environment for software testing of Ada: The development of a program analysis environment for Ada, task 1, phase 3

NASA Technical Reports Server (NTRS)

Brown, David B.

1991-01-01

The results of research and development efforts of the first six months of Task 1, Phase 3 of the project are presented. The goals of Phase 3 are: (1) to further refine the rule base and complete the comparative rule base evaluation; (2) to implement and evaluate a concurrency testing prototype; (3) to convert the complete (unit-level and concurrency) testing prototype to a workstation environment; and (4) to provide a prototype development document to facilitate the transfer of research technology to a working environment. These goals were partially met and the results are summarized.

A biologically based model for the integration of sensory-motor contingencies in rules and plans: a prefrontal cortex based extension of the Distributed Adaptive Control architecture.

PubMed

Duff, Armin; Fibla, Marti Sanchez; Verschure, Paul F M J

2011-06-30

Intelligence depends on the ability of the brain to acquire and apply rules and representations. At the neuronal level these properties have been shown to critically depend on the prefrontal cortex. Here we present, in the context of the Distributed Adaptive Control architecture (DAC), a biologically based model for flexible control and planning based on key physiological properties of the prefrontal cortex, i.e. reward modulated sustained activity and plasticity of lateral connectivity. We test the model in a series of pertinent tasks, including multiple T-mazes and the Tower of London that are standard experimental tasks to assess flexible control and planning. We show that the model is both able to acquire and express rules that capture the properties of the task and to quickly adapt to changes. Further, we demonstrate that this biomimetic self-contained cognitive architecture generalizes to planning. In addition, we analyze the extended DAC architecture, called DAC 6, as a model that can be applied for the creation of intelligent and psychologically believable synthetic agents. Copyright © 2010 Elsevier Inc. All rights reserved.

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure.

PubMed

Lustgarten, Jonathan Lyle; Balasubramanian, Jeya Balaji; Visweswaran, Shyam; Gopalakrishnan, Vanathi

2017-03-01

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

The Relation between Resting State Connectivity and Creativity in Adolescents before and after Training

PubMed Central

Cousijn, Janna; Zanolie, Kiki; Munsters, Robbert J. M.; Kleibeuker, Sietske W.; Crone, Eveline A.

2014-01-01

An important component of creativity is divergent thinking, which involves the ability to generate novel and useful problem solutions. In this study, we tested the relation between resting-state functional connectivity of brain areas activated during a divergent thinking task (i.e., supramarginal gyrus, middle temporal gyrus, medial frontal gyrus) and the effect of practice in 32 adolescents aged 15–16. Over a period of two weeks, an experimental group (n = 16) conducted an 8-session Alternative Uses Task (AUT) training and an active control group (n = 16) conducted an 8-session rule switching training. Resting-state functional connectivity was measured before (pre-test) and after (post-test) training. Across groups at pre-test, stronger connectivity between the middle temporal gyrus and bilateral postcentral gyrus was associated with better divergent thinking performance. The AUT-training, however, did not significantly change functional connectivity. Post hoc analyses showed that change in divergent thinking performance over time was predicted by connectivity between left supramarginal gyrus and right occipital cortex. These results provide evidence for a relation between divergent thinking and resting-state functional connectivity in a task-positive network, taking an important step towards understanding creative cognition and functional brain connectivity. PMID:25188416

Exploring the limits of learning: Segregation of information integration and response selection is required for learning a serial reversal task

PubMed Central

Zanutto, B. Silvano

2017-01-01

Animals are proposed to learn the latent rules governing their environment in order to maximize their chances of survival. However, rules may change without notice, forcing animals to keep a memory of which one is currently at work. Rule switching can lead to situations in which the same stimulus/response pairing is positively and negatively rewarded in the long run, depending on variables that are not accessible to the animal. This fact raises questions on how neural systems are capable of reinforcement learning in environments where the reinforcement is inconsistent. Here we address this issue by asking about which aspects of connectivity, neural excitability and synaptic plasticity are key for a very general, stochastic spiking neural network model to solve a task in which rules change without being cued, taking the serial reversal task (SRT) as paradigm. Contrary to what could be expected, we found strong limitations for biologically plausible networks to solve the SRT. Especially, we proved that no network of neurons can learn a SRT if it is a single neural population that integrates stimuli information and at the same time is responsible of choosing the behavioural response. This limitation is independent of the number of neurons, neuronal dynamics or plasticity rules, and arises from the fact that plasticity is locally computed at each synapse, and that synaptic changes and neuronal activity are mutually dependent processes. We propose and characterize a spiking neural network model that solves the SRT, which relies on separating the functions of stimuli integration and response selection. The model suggests that experimental efforts to understand neural function should focus on the characterization of neural circuits according to their connectivity, neural dynamics, and the degree of modulation of synaptic plasticity with reward. PMID:29077735

Coreference analysis in clinical notes: a multi-pass sieve with alternate anaphora resolution modules

PubMed Central

Li, Dingcheng; Sohn, Sunghwan; Wu, Stephen Tze-Inn; Wagholikar, Kavishwar; Torii, Manabu; Liu, Hongfang

2012-01-01

Objective This paper describes the coreference resolution system submitted by Mayo Clinic for the 2011 i2b2/VA/Cincinnati shared task Track 1C. The goal of the task was to construct a system that links the markables corresponding to the same entity. Materials and methods The task organizers provided progress notes and discharge summaries that were annotated with the markables of treatment, problem, test, person, and pronoun. We used a multi-pass sieve algorithm that applies deterministic rules in the order of preciseness and simultaneously gathers information about the entities in the documents. Our system, MedCoref, also uses a state-of-the-art machine learning framework as an alternative to the final, rule-based pronoun resolution sieve. Results The best system that uses a multi-pass sieve has an overall score of 0.836 (average of B3, MUC, Blanc, and CEAF F score) for the training set and 0.843 for the test set. Discussion A supervised machine learning system that typically uses a single function to find coreferents cannot accommodate irregularities encountered in data especially given the insufficient number of examples. On the other hand, a completely deterministic system could lead to a decrease in recall (sensitivity) when the rules are not exhaustive. The sieve-based framework allows one to combine reliable machine learning components with rules designed by experts. Conclusion Using relatively simple rules, part-of-speech information, and semantic type properties, an effective coreference resolution system could be designed. The source code of the system described is available at https://sourceforge.net/projects/ohnlp/files/MedCoref. PMID:22707745

A logical model of cooperating rule-based systems

NASA Technical Reports Server (NTRS)

Bailin, Sidney C.; Moore, John M.; Hilberg, Robert H.; Murphy, Elizabeth D.; Bahder, Shari A.

1989-01-01

A model is developed to assist in the planning, specification, development, and verification of space information systems involving distributed rule-based systems. The model is based on an analysis of possible uses of rule-based systems in control centers. This analysis is summarized as a data-flow model for a hypothetical intelligent control center. From this data-flow model, the logical model of cooperating rule-based systems is extracted. This model consists of four layers of increasing capability: (1) communicating agents, (2) belief-sharing knowledge sources, (3) goal-sharing interest areas, and (4) task-sharing job roles.

A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies

PubMed Central

Dimitrov, Borislav D; Motterlini, Nicola; Fahey, Tom

2015-01-01

Objective Estimating calibration performance of clinical prediction rules (CPRs) in systematic reviews of validation studies is not possible when predicted values are neither published nor accessible or sufficient or no individual participant or patient data are available. Our aims were to describe a simplified approach for outcomes prediction and calibration assessment and evaluate its functionality and validity. Study design and methods: Methodological study of systematic reviews of validation studies of CPRs: a) ABCD2 rule for prediction of 7 day stroke; and b) CRB-65 rule for prediction of 30 day mortality. Predicted outcomes in a sample validation study were computed by CPR distribution patterns (“derivation model”). As confirmation, a logistic regression model (with derivation study coefficients) was applied to CPR-based dummy variables in the validation study. Meta-analysis of validation studies provided pooled estimates of “predicted:observed” risk ratios (RRs), 95% confidence intervals (CIs), and indexes of heterogeneity (I2) on forest plots (fixed and random effects models), with and without adjustment of intercepts. The above approach was also applied to the CRB-65 rule. Results Our simplified method, applied to ABCD2 rule in three risk strata (low, 0–3; intermediate, 4–5; high, 6–7 points), indicated that predictions are identical to those computed by univariate, CPR-based logistic regression model. Discrimination was good (c-statistics =0.61–0.82), however, calibration in some studies was low. In such cases with miscalibration, the under-prediction (RRs =0.73–0.91, 95% CIs 0.41–1.48) could be further corrected by intercept adjustment to account for incidence differences. An improvement of both heterogeneities and P-values (Hosmer-Lemeshow goodness-of-fit test) was observed. Better calibration and improved pooled RRs (0.90–1.06), with narrower 95% CIs (0.57–1.41) were achieved. Conclusion Our results have an immediate clinical implication in situations when predicted outcomes in CPR validation studies are lacking or deficient by describing how such predictions can be obtained by everyone using the derivation study alone, without any need for highly specialized knowledge or sophisticated statistics. PMID:25931829

Development of a prediction tool for patients presenting with acute cough in primary care: a prognostic study spanning six European countries.

PubMed

Bruyndonckx, Robin; Hens, Niel; Verheij, Theo Jm; Aerts, Marc; Ieven, Margareta; Butler, Christopher C; Little, Paul; Goossens, Herman; Coenen, Samuel

2018-05-01

Accurate prediction of the course of an acute cough episode could curb antibiotic overprescribing, but is still a major challenge in primary care. The authors set out to develop a new prediction rule for poor outcome (re-consultation with new or worsened symptoms, or hospital admission) in adults presenting to primary care with acute cough. Data were collected from 2604 adults presenting to primary care with acute cough or symptoms suggestive of lower respiratory tract infection (LRTI) within the Genomics to combat Resistance against Antibiotics in Community-acquired LRTI in Europe (GRACE; www.grace-lrti.org) Network of Excellence. Important signs and symptoms for the new prediction rule were found by combining random forest and logistic regression modelling. Performance to predict poor outcome in acute cough patients was compared with that of existing prediction rules, using the models' area under the receiver operator characteristic curve (AUC), and any improvement obtained by including additional test results (C-reactive protein [CRP], blood urea nitrogen [BUN], chest radiography, or aetiology) was evaluated using the same methodology. The new prediction rule, included the baseline Risk of poor outcome, Interference with daily activities, number of years stopped Smoking (> or <45 years), severity of Sputum, presence of Crackles, and diastolic blood pressure (> or <85 mmHg) (RISSC85). Though performance of RISSC85 was moderate (sensitivity 62%, specificity 59%, positive predictive value 27%, negative predictive value 86%, AUC 0.63, 95% confidence interval [CI] = 0.61 to 0.67), it outperformed all existing prediction rules used today (highest AUC 0.53, 95% CI = 0.51 to 0.56), and could not be significantly improved by including additional test results (highest AUC 0.64, 95% CI = 0.62 to 0.68). The new prediction rule outperforms all existing alternatives in predicting poor outcome in adult patients presenting to primary care with acute cough and could not be improved by including additional test results. © British Journal of General Practice 2018.

Adaptive robotic control driven by a versatile spiking cerebellar network.

PubMed

Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Carrillo, Richard R; Luque, Niceto R; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio

2014-01-01

The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Hippocampal BOLD response during category learning predicts subsequent performance on transfer generalization.

PubMed

Fera, Francesco; Passamonti, Luca; Herzallah, Mohammad M; Myers, Catherine E; Veltri, Pierangelo; Morganti, Giuseppina; Quattrone, Aldo; Gluck, Mark A

2014-07-01

To test a prediction of our previous computational model of cortico-hippocampal interaction (Gluck and Myers [1993, 2001]) for characterizing individual differences in category learning, we studied young healthy subjects using an fMRI-adapted category-learning task that has two phases, an initial phase in which associations are learned through trial-and-error feedback followed by a generalization phase in which previously learned rules can be applied to novel associations (Myers et al. [2003]). As expected by our model, we found a negative correlation between learning-related hippocampal responses and accuracy during transfer, demonstrating that hippocampal adaptation during learning is associated with better behavioral scores during transfer generalization. In addition, we found an inverse relationship between Blood Oxygenation Level Dependent (BOLD) activity in the striatum and that in the hippocampal formation and the orbitofrontal cortex during the initial learning phase. Conversely, activity in the dorsolateral prefrontal cortex, orbitofrontal cortex and parietal lobes dominated over that of the hippocampal formation during the generalization phase. These findings provide evidence in support of theories of the neural substrates of category learning which argue that the hippocampal region plays a critical role during learning for appropriately encoding and representing newly learned information so that that this learning can be successfully applied and generalized to subsequent novel task demands. Copyright © 2013 Wiley Periodicals, Inc.

Effortful control mediates relations between children's attachment security and their regard for rules of conduct

PubMed Central

Nordling, Jamie Koenig; Boldt, Lea J.; O'Bleness, Jessica; Kochanska, Grazyna

2015-01-01

Although attachment security has been associated with children's rule-compatible conduct, the mechanism through which attachment influences early regard for rules is not well established. We hypothesized that effortful control would mediate the link between security and indicators of children's emerging regard for rules (discomfort following rule violations, internalization of parents' and experimenter's rules, few externalizing behaviors). In a longitudinal study, the Attachment Q-Set was completed by parents, effortful control was observed, and Regard for Rules was observed and rated by parents. The proposed model fit the data well: Children's security to mothers predicted their effortful control, which in turn had a direct link to a greater Regard for Rules. Children's security with fathers did not predict effortful control. The mother-child relationship appears particularly important for positive developmental cascades of self-regulation and socialization. PMID:27158193

Mind-wandering, cognition, and performance: a theory-driven meta-analysis of attention regulation.

PubMed

Randall, Jason G; Oswald, Frederick L; Beier, Margaret E

2014-11-01

The current meta-analysis accumulates empirical findings on the phenomenon of mind-wandering, integrating and interpreting findings in light of psychological theories of cognitive resource allocation. Cognitive resource theory emphasizes both individual differences in attentional resources and task demands together to predict variance in task performance. This theory motivated our conceptual and meta-analysis framework by introducing moderators indicative of task-demand to predict who is more likely to mind-wander under what conditions, and to predict when mind-wandering and task-related thought are more (or less) predictive of task performance. Predictions were tested via a random-effects meta-analysis of correlations obtained from normal adult samples (k = 88) based on measurement of specified episodes of off-task and/or on-task thought frequency and task performance. Results demonstrated that people with fewer cognitive resources tend to engage in more mind-wandering, whereas those with more cognitive resources are more likely to engage in task-related thought. Addressing predictions of resource theory, we found that greater time-on-task-although not greater task complexity-tended to strengthen the negative relation between cognitive resources and mind-wandering. Additionally, increases in mind-wandering were generally associated with decreases in task performance, whereas increases in task-related thought were associated with increased performance. Further supporting resource theory, the negative relation between mind-wandering and performance was more pronounced for more complex tasks, though not longer tasks. Complementarily, the positive association between task-related thought and performance was stronger for more complex tasks and for longer tasks. We conclude by discussing implications and future research directions for mind-wandering as a construct of interest in psychological research. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Dilution: atheoretical burden or just load? A reply to Tsal and Benoni (2010).

PubMed

Lavie, Nilli; Torralbo, Ana

2010-12-01

Load theory of attention proposes that distractor processing is reduced in tasks with high perceptual load that exhaust attentional capacity within task-relevant processing. In contrast, tasks of low perceptual load leave spare capacity that spills over, resulting in the perception of task-irrelevant, potentially distracting stimuli. Tsal and Benoni (2010) find that distractor response competition effects can be reduced under conditions with a high search set size but low perceptual load (due to a singleton color target). They claim that the usual effect of search set size on distractor processing is not due to attentional load but instead attribute this to lower level visual interference. Here, we propose an account for their findings within load theory. We argue that in tasks of low perceptual load but high set size, an irrelevant distractor competes with the search nontargets for remaining capacity. Thus, distractor processing is reduced under conditions in which the search nontargets receive the spillover of capacity instead of the irrelevant distractor. We report a new experiment testing this prediction. Our new results demonstrate that, when peripheral distractor processing is reduced, it is the search nontargets nearest to the target that are perceived instead. Our findings provide new evidence for the spare capacity spillover hypothesis made by load theory and rule out accounts in terms of lower level visual interference (or mere "dilution") for cases of reduced distractor processing under low load in displays of high set size. We also discuss additional evidence that discounts the viability of Tsal and Benoni's dilution account as an alternative to perceptual load.

The diminishing criterion model for metacognitive regulation of time investment.

PubMed

Ackerman, Rakefet

2014-06-01

According to the Discrepancy Reduction Model for metacognitive regulation, people invest time in cognitive tasks in a goal-driven manner until their metacognitive judgment, either judgment of learning (JOL) or confidence, meets their preset goal. This stopping rule should lead to judgments above the goal, regardless of invested time. However, in many tasks, time is negatively correlated with JOL and confidence, with low judgments after effortful processing. This pattern has often been explained as stemming from bottom-up fluency effects on the judgments. While accepting this explanation for simple tasks, like memorizing pairs of familiar words, the proposed Diminishing Criterion Model (DCM) challenges this explanation for complex tasks, like problem solving. Under the DCM, people indeed invest effort in a goal-driven manner. However, investing more time leads to increasing compromise on the goal, resulting in negative time-judgment correlations. Experiment 1 exposed that with word-pair memorization, negative correlations are found only with minimal fluency and difficulty variability, whereas in problem solving, they are found consistently. As predicted, manipulations of low incentives (Experiment 2) and time pressure (Experiment 3) in problem solving revealed greater compromise as more time was invested in a problem. Although intermediate confidence ratings rose during the solving process, the result was negative time-confidence correlations (Experiments 3, 4, and 5), and this was not eliminated by the opportunity to respond "don't know" (Experiments 4 and 5). The results suggest that negative time-judgment correlations in complex tasks stem from top-down regulatory processes with a criterion that diminishes with invested time. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Dilution

PubMed Central

Lavie, Nilli; Torralbo, Ana

2010-01-01

Load theory of attention proposes that distractor processing is reduced in tasks with high perceptual load that exhaust attentional capacity within task-relevant processing. In contrast, tasks of low perceptual load leave spare capacity that spills over, resulting in the perception of task-irrelevant, potentially distracting stimuli. Tsal and Benoni (2010) find that distractor response competition effects can be reduced under conditions with a high search set size but low perceptual load (due to a singleton color target). They claim that the usual effect of search set size on distractor processing is not due to attentional load but instead attribute this to lower level visual interference. Here, we propose an account for their findings within load theory. We argue that in tasks of low perceptual load but high set size, an irrelevant distractor competes with the search nontargets for remaining capacity. Thus, distractor processing is reduced under conditions in which the search nontargets receive the spillover of capacity instead of the irrelevant distractor. We report a new experiment testing this prediction. Our new results demonstrate that, when peripheral distractor processing is reduced, it is the search nontargets nearest to the target that are perceived instead. Our findings provide new evidence for the spare capacity spillover hypothesis made by load theory and rule out accounts in terms of lower level visual interference (or mere “dilution”) for cases of reduced distractor processing under low load in displays of high set size. We also discuss additional evidence that discounts the viability of Tsal and Benoni's dilution account as an alternative to perceptual load. PMID:21133554

Emotion and Deliberative Reasoning in Moral Judgment

PubMed Central

Cummins, Denise Dellarosa; Cummins, Robert C.

2012-01-01

According to an influential dual-process model, a moral judgment is the outcome of a rapid, affect-laden process and a slower, deliberative process. If these outputs conflict, decision time is increased in order to resolve the conflict. Violations of deontological principles proscribing the use of personal force to inflict intentional harm are presumed to elicit negative affect which biases judgments early in the decision-making process. This model was tested in three experiments. Moral dilemmas were classified using (a) decision time and consensus as measures of system conflict and (b) the aforementioned deontological criteria. In Experiment 1, decision time was either unlimited or reduced. The dilemmas asked whether it was appropriate to take a morally questionable action to produce a “greater good” outcome. Limiting decision time reduced the proportion of utilitarian (“yes”) decisions, but contrary to the model’s predictions, (a) vignettes that involved more deontological violations logged faster decision times, and (b) violation of deontological principles was not predictive of decisional conflict profiles. Experiment 2 ruled out the possibility that time pressure simply makes people more like to say “no.” Participants made a first decision under time constraints and a second decision under no time constraints. One group was asked whether it was appropriate to take the morally questionable action while a second group was asked whether it was appropriate to refuse to take the action. The results replicated that of Experiment 1 regardless of whether “yes” or “no” constituted a utilitarian decision. In Experiment 3, participants rated the pleasantness of positive visual stimuli prior to making a decision. Contrary to the model’s predictions, the number of deontological decisions increased in the positive affect rating group compared to a group that engaged in a cognitive task or a control group that engaged in neither task. These results are consistent with the view that early moral judgments are influenced by affect. But they are inconsistent with the view that (a) violation of deontological principles are predictive of differences in early, affect-based judgment or that (b) engaging in tasks that are inconsistent with the negative emotional responses elicited by such violations diminishes their impact. PMID:22973255

Promoter Sequences Prediction Using Relational Association Rule Mining

PubMed Central

Czibula, Gabriela; Bocicor, Maria-Iuliana; Czibula, Istvan Gergely

2012-01-01

In this paper we are approaching, from a computational perspective, the problem of promoter sequences prediction, an important problem within the field of bioinformatics. As the conditions for a DNA sequence to function as a promoter are not known, machine learning based classification models are still developed to approach the problem of promoter identification in the DNA. We are proposing a classification model based on relational association rules mining. Relational association rules are a particular type of association rules and describe numerical orderings between attributes that commonly occur over a data set. Our classifier is based on the discovery of relational association rules for predicting if a DNA sequence contains or not a promoter region. An experimental evaluation of the proposed model and comparison with similar existing approaches is provided. The obtained results show that our classifier overperforms the existing techniques for identifying promoter sequences, confirming the potential of our proposal. PMID:22563233

Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways.

PubMed

Saidi, Rabie; Boudellioua, Imane; Martin, Maria J; Solovyev, Victor

2017-01-01

It is becoming more evident that computational methods are needed for the identification and the mapping of pathways in new genomes. We introduce an automatic annotation system (ARBA4Path Association Rule-Based Annotator for Pathways) that utilizes rule mining techniques to predict metabolic pathways across wide range of prokaryotes. It was demonstrated that specific combinations of protein domains (recorded in our rules) strongly determine pathways in which proteins are involved and thus provide information that let us very accurately assign pathway membership (with precision of 0.999 and recall of 0.966) to proteins of a given prokaryotic taxon. Our system can be used to enhance the quality of automatically generated annotations as well as annotating proteins with unknown function. The prediction models are represented in the form of human-readable rules, and they can be used effectively to add absent pathway information to many proteins in UniProtKB/TrEMBL database.

Human Cognition and Information Display in C3I System Tasks.

DTIC Science & Technology

1988-12-01

goes without saying that rule-based tasks are the easiest to automate, but for reasons discussed earlier, they still merit our attention . Moreover...selective attention task. Since selective attention must operate after memory retrieval, it is only when different responses are elicited that the...stimuli that is processed by impairing the memory traces of signals that originally attract less attention . Although the research reviewed above gives

Single neurons in prefrontal cortex encode abstract rules.

PubMed

Wallis, J D; Anderson, K C; Miller, E K

2001-06-21

The ability to abstract principles or rules from direct experience allows behaviour to extend beyond specific circumstances to general situations. For example, we learn the 'rules' for restaurant dining from specific experiences and can then apply them in new restaurants. The use of such rules is thought to depend on the prefrontal cortex (PFC) because its damage often results in difficulty in following rules. Here we explore its neural basis by recording from single neurons in the PFC of monkeys trained to use two abstract rules. They were required to indicate whether two successively presented pictures were the same or different depending on which rule was currently in effect. The monkeys performed this task with new pictures, thus showing that they had learned two general principles that could be applied to stimuli that they had not yet experienced. The most prevalent neuronal activity observed in the PFC reflected the coding of these abstract rules.

Adolescents' as active agents in the socialization process: legitimacy of parental authority and obligation to obey as predictors of obedience.

PubMed

Darling, Nancy; Cumsille, Patricio; Martínez, M Loreto

2007-04-01

Adolescents' agreement with parental standards and beliefs about the legitimacy of parental authority and their own obligation to obey were used to predict adolescents' obedience, controlling for parental monitoring, rules, and rule enforcement. Hierarchical linear models were used to predict both between-adolescent and within-adolescent, issue-specific differences in obedience in a sample of 703 Chilean adolescents (M age=15.0 years). Adolescents' global agreement with parents and global beliefs about their obligation to obey predicted between-adolescent obedience, controlling for parental monitoring, age, and gender. Adolescents' issue-specific agreement, legitimacy beliefs, and obligation to obey predicted issue-specific obedience, controlling for rules and parents' reports of rule enforcement. The potential of examining adolescents' agreement and beliefs about authority as a key link between parenting practices and adolescents' decisions to obey is discussed.

Pooled individual patient data from five countries were used to derive a clinical prediction rule for coronary artery disease in primary care.

PubMed

Aerts, Marc; Minalu, Girma; Bösner, Stefan; Buntinx, Frank; Burnand, Bernard; Haasenritter, Jörg; Herzig, Lilli; Knottnerus, J André; Nilsson, Staffan; Renier, Walter; Sox, Carol; Sox, Harold; Donner-Banzhoff, Norbert

2017-01-01

To construct a clinical prediction rule for coronary artery disease (CAD) presenting with chest pain in primary care. Meta-Analysis using 3,099 patients from five studies. To identify candidate predictors, we used random forest trees, multiple imputation of missing values, and logistic regression within individual studies. To generate a prediction rule on the pooled data, we applied a regression model that took account of the differing standard data sets collected by the five studies. The most parsimonious rule included six equally weighted predictors: age ≥55 (males) or ≥65 (females) (+1); attending physician suspected a serious diagnosis (+1); history of CAD (+1); pain brought on by exertion (+1); pain feels like "pressure" (+1); pain reproducible by palpation (-1). CAD was considered absent if the prediction score is <2. The area under the ROC curve was 0.84. We applied this rule to a study setting with a CAD prevalence of 13.2% using a prediction score cutoff of <2 (i.e., -1, 0, or +1). When the score was <2, the probability of CAD was 2.1% (95% CI: 1.1-3.9%); when the score was ≥ 2, it was 43.0% (95% CI: 35.8-50.4%). Clinical prediction rules are a key strategy for individualizing care. Large data sets based on electronic health records from diverse sites create opportunities for improving their internal and external validity. Our patient-level meta-analysis from five primary care sites should improve external validity. Our strategy for addressing site-to-site systematic variation in missing data should improve internal validity. Using principles derived from decision theory, we also discuss the problem of setting the cutoff prediction score for taking action. Copyright © 2016 Elsevier Inc. All rights reserved.

Haunted by a doppelgänger: irrelevant facial similarity affects rule-based judgments.

PubMed

von Helversen, Bettina; Herzog, Stefan M; Rieskamp, Jörg

2014-01-01

Judging other people is a common and important task. Every day professionals make decisions that affect the lives of other people when they diagnose medical conditions, grant parole, or hire new employees. To prevent discrimination, professional standards require that decision makers render accurate and unbiased judgments solely based on relevant information. Facial similarity to previously encountered persons can be a potential source of bias. Psychological research suggests that people only rely on similarity-based judgment strategies if the provided information does not allow them to make accurate rule-based judgments. Our study shows, however, that facial similarity to previously encountered persons influences judgment even in situations in which relevant information is available for making accurate rule-based judgments and where similarity is irrelevant for the task and relying on similarity is detrimental. In two experiments in an employment context we show that applicants who looked similar to high-performing former employees were judged as more suitable than applicants who looked similar to low-performing former employees. This similarity effect was found despite the fact that the participants used the relevant résumé information about the applicants by following a rule-based judgment strategy. These findings suggest that similarity-based and rule-based processes simultaneously underlie human judgment.

Learning a New Selection Rule in Visual and Frontal Cortex.

PubMed

van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R

2016-08-01

How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. © The Author 2016. Published by Oxford University Press.

Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia.

PubMed

Diuk, Carlos; Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew; Niv, Yael

2013-03-27

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.

The Hpp Rule with Memory and the Density Classification Task

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón

This article considers an extension to the standard framework of cellular automata by implementing memory capability in cells. It is shown that the important block HPP rule behaves as an excellent classifier of the density in the initial configuration when applied to cells endowed with pondered memory of their previous states. If the weighing is made so that the most recent state values are assigning the highest weights, the HPP rule surpasses the performance of the best two-dimensional density classifiers reported in the literature.

Real World Cognitive Multi-Tasking and Problem Solving: A Large Scale Cognitive Architecture Simulation Through High Performance Computing-Project Casie

DTIC Science & Technology

2008-03-01

computational version of the CASIE architecture serves to demonstrate the functionality of our primary theories. However, implementation of several other...following facts. First, based on Theorem 3 and Theorem 5, the objective function is non -increasing under updating rule (6); second, by the criteria for...reassignment in updating rule (7), it is trivial to show that the objective function is non -increasing under updating rule (7). A Unified View to Graph

Implicit and Explicit Knowledge Both Improve Dual Task Performance in a Continuous Pursuit Tracking Task.

PubMed

Ewolds, Harald E; Bröker, Laura; de Oliveira, Rita F; Raab, Markus; Künzell, Stefan

2017-01-01

The goal of this study was to investigate the effect of predictability on dual-task performance in a continuous tracking task. Participants practiced either informed (explicit group) or uninformed (implicit group) about a repeated segment in the curves they had to track. In Experiment 1 participants practices the tracking task only, dual-task performance was assessed after by combining the tracking task with an auditory reaction time task. Results showed both groups learned equally well and tracking performance on a predictable segment in the dual-task condition was better than on random segments. However, reaction times did not benefit from a predictable tracking segment. To investigate the effect of learning under dual-task situation participants in Experiment 2 practiced the tracking task while simultaneously performing the auditory reaction time task. No learning of the repeated segment could be demonstrated for either group during the training blocks, in contrast to the test-block and retention test, where participants performed better on the repeated segment in both dual-task and single-task conditions. Only the explicit group improved from test-block to retention test. As in Experiment 1, reaction times while tracking a predictable segment were no better than reaction times while tracking a random segment. We concluded that predictability has a positive effect only on the predictable task itself possibly because of a task-shielding mechanism. For dual-task training there seems to be an initial negative effect of explicit instructions, possibly because of fatigue, but the advantage of explicit instructions was demonstrated in a retention test. This might be due to the explicit memory system informing or aiding the implicit memory system.

Implicit and Explicit Knowledge Both Improve Dual Task Performance in a Continuous Pursuit Tracking Task

PubMed Central

Ewolds, Harald E.; Bröker, Laura; de Oliveira, Rita F.; Raab, Markus; Künzell, Stefan

2017-01-01

The goal of this study was to investigate the effect of predictability on dual-task performance in a continuous tracking task. Participants practiced either informed (explicit group) or uninformed (implicit group) about a repeated segment in the curves they had to track. In Experiment 1 participants practices the tracking task only, dual-task performance was assessed after by combining the tracking task with an auditory reaction time task. Results showed both groups learned equally well and tracking performance on a predictable segment in the dual-task condition was better than on random segments. However, reaction times did not benefit from a predictable tracking segment. To investigate the effect of learning under dual-task situation participants in Experiment 2 practiced the tracking task while simultaneously performing the auditory reaction time task. No learning of the repeated segment could be demonstrated for either group during the training blocks, in contrast to the test-block and retention test, where participants performed better on the repeated segment in both dual-task and single-task conditions. Only the explicit group improved from test-block to retention test. As in Experiment 1, reaction times while tracking a predictable segment were no better than reaction times while tracking a random segment. We concluded that predictability has a positive effect only on the predictable task itself possibly because of a task-shielding mechanism. For dual-task training there seems to be an initial negative effect of explicit instructions, possibly because of fatigue, but the advantage of explicit instructions was demonstrated in a retention test. This might be due to the explicit memory system informing or aiding the implicit memory system. PMID:29312083

Separating Decision and Encoding Noise in Signal Detection Tasks

PubMed Central

Cabrera, Carlos Alexander; Lu, Zhong-Lin; Dosher, Barbara Anne

2015-01-01

In this paper we develop an extension to the Signal Detection Theory (SDT) framework to separately estimate internal noise arising from representational and decision processes. Our approach constrains SDT models with decision noise by combining a multi-pass external noise paradigm with confidence rating responses. In a simulation study we present evidence that representation and decision noise can be separately estimated over a range of representative underlying representational and decision noise level configurations. These results also hold across a number of decision rules and show resilience to rule miss-specification. The new theoretical framework is applied to a visual detection confidence-rating task with three and five response categories. This study compliments and extends the recent efforts of researchers (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008; Rosner & Kochanski, 2009, Kellen, Klauer, & Singmann, 2012) to separate and quantify underlying sources of response variability in signal detection tasks. PMID:26120907

Task relevance modulates the behavioural and neural effects of sensory predictions

PubMed Central

Friston, Karl J.; Nobre, Anna C.

2017-01-01

The brain is thought to generate internal predictions to optimize behaviour. However, it is unclear whether predictions signalling is an automatic brain function or depends on task demands. Here, we manipulated the spatial/temporal predictability of visual targets, and the relevance of spatial/temporal information provided by auditory cues. We used magnetoencephalography (MEG) to measure participants’ brain activity during task performance. Task relevance modulated the influence of predictions on behaviour: spatial/temporal predictability improved spatial/temporal discrimination accuracy, but not vice versa. To explain these effects, we used behavioural responses to estimate subjective predictions under an ideal-observer model. Model-based time-series of predictions and prediction errors (PEs) were associated with dissociable neural responses: predictions correlated with cue-induced beta-band activity in auditory regions and alpha-band activity in visual regions, while stimulus-bound PEs correlated with gamma-band activity in posterior regions. Crucially, task relevance modulated these spectral correlates, suggesting that current goals influence PE and prediction signalling. PMID:29206225

On the origins of the task mixing cost in the cuing task-switching paradigm.

PubMed

Rubin, Orit; Meiran, Nachshon

2005-11-01

Poorer performance in conditions involving task repetition within blocks of mixed tasks relative to task repetition within blocks of single task is called mixing cost (MC). In 2 experiments exploring 2 hypotheses regarding the origins of MC, participants either switched between cued shape and color tasks, or they performed them as single tasks. Experiment 1 supported the hypothesis that mixed-tasks trials require the resolution of task ambiguity by showing that MC existed only with ambiguous stimuli that afforded both tasks and not with unambiguous stimuli affording only 1 task. Experiment 2 failed to support the hypothesis that holding multiple task sets in working memory (WM) generates MC by showing that systematic manipulation of the number of stimulus-response rules in WM did not affect MC. The results emphasize the role of competition management between task sets during task control.

Automated rule-base creation via CLIPS-Induce

NASA Technical Reports Server (NTRS)

Murphy, Patrick M.

1994-01-01

Many CLIPS rule-bases contain one or more rule groups that perform classification. In this paper we describe CLIPS-Induce, an automated system for the creation of a CLIPS classification rule-base from a set of test cases. CLIPS-Induce consists of two components, a decision tree induction component and a CLIPS production extraction component. ID3, a popular decision tree induction algorithm, is used to induce a decision tree from the test cases. CLIPS production extraction is accomplished through a top-down traversal of the decision tree. Nodes of the tree are used to construct query rules, and branches of the tree are used to construct classification rules. The learned CLIPS productions may easily be incorporated into a large CLIPS system that perform tasks such as accessing a database or displaying information.

Learning to Learn about Uncertain Feedback

ERIC Educational Resources Information Center

Faraut, Mailys C. M.; Procyk, Emmanuel; Wilson, Charles R. E.

2016-01-01

Unexpected outcomes can reflect noise in the environment or a change in the current rules. We should ignore noise but shift strategy after rule changes. How we learn to do this is unclear, but one possibility is that it relies on learning to learn in uncertain environments. We propose that acquisition of latent task structure during learning to…

Strategy Selection for Cognitive Skill Acquisition Depends on Task Demands and Working Memory Capacity

ERIC Educational Resources Information Center

Hinze, Scott R.; Bunting, Michael F; Pellegrino, James W.

2009-01-01

The involvement of working memory capacity (WMC) in ruled-based cognitive skill acquisition is well-established, but the duration of its involvement and its role in learning strategy selection are less certain. Participants (N=610) learned four logic rules, their corresponding symbols, or logic gates, and the appropriate input-output combinations…

Accuracy and precision of the signs and symptoms of streptococcal pharyngitis in children: a systematic review.

PubMed

Shaikh, Nader; Swaminathan, Nithya; Hooper, Emma G

2012-03-01

To conduct a systematic review to determine whether clinical findings can be used to rule in or to rule out streptococcal pharyngitis in children. Two authors independently searched MEDLINE and EMBASE. We included articles if they contained data on the accuracy of symptoms or signs of streptococcal pharyngitis, individually or combined into prediction rules, in children 3-18 years of age. Thirty-eight articles with data on individual symptoms and signs and 15 articles with data on prediction rules met all inclusion criteria. In children with sore throat, the presence of a scarlatiniform rash (likelihood ratio [LR], 3.91; 95% CI, 2.00-7.62), palatal petechiae (LR, 2.69; CI, 1.92-3.77), pharyngeal exudates (LR, 1.85; CI, 1.58-2.16), vomiting (LR, 1.79; CI, 1.58-2.16), and tender cervical nodes (LR, 1.72; CI, 1.54-1.93) were moderately useful in identifying those with streptococcal pharyngitis. Nevertheless, no individual symptoms or signs were effective in ruling in or ruling out streptococcal pharyngitis. Symptoms and signs, either individually or combined into prediction rules, cannot be used to definitively diagnose or rule out streptococcal pharyngitis. Copyright © 2012 Mosby, Inc. All rights reserved.

Adult age differences in predicting memory performance: the effects of normative information and task experience.

PubMed

McDonald-Miszczak, L; Hunter, M A; Hultsch, D F

1994-03-01

Two experiments addressed the effects of task information and experience on younger and older adults' ability to predict their memory for words. The first study examined the effects of normative task information on subjects' predictions for 30-word lists across three trials. The second study looked at the effects of making predictions and recalling either an easy (15) or a difficult (45) word list prior to making predictions and recalling a moderately difficult (30) word list. The results from both studies showed that task information and experience affected subjects' predictions and that elderly adults predicted their performance more accurately than younger adults.

Correcting Memory Improves Accuracy of Predicted Task Duration

ERIC Educational Resources Information Center

Roy, Michael M.; Mitten, Scott T.; Christenfeld, Nicholas J. S.

2008-01-01

People are often inaccurate in predicting task duration. The memory bias explanation holds that this error is due to people having incorrect memories of how long previous tasks have taken, and these biased memories cause biased predictions. Therefore, the authors examined the effect on increasing predictive accuracy of correcting memory through…

Metacognition of Multi-Tasking: How Well Do We Predict the Costs of Divided Attention?

PubMed Central

Finley, Jason R.; Benjamin, Aaron S.; McCarley, Jason S.

2014-01-01

Risky multi-tasking, such as texting while driving, may occur because people misestimate the costs of divided attention. In two experiments, participants performed a computerized visual-manual tracking task in which they attempted to keep a mouse cursor within a small target that moved erratically around a circular track. They then separately performed an auditory n-back task. After practicing both tasks separately, participants received feedback on their single-task tracking performance and predicted their dual-task tracking performance before finally performing the two tasks simultaneously. Most participants correctly predicted reductions in tracking performance under dual-task conditions, with a majority overestimating the costs of dual-tasking. However, the between-subjects correlation between predicted and actual performance decrements was near zero. This combination of results suggests that people do anticipate costs of multi-tasking, but have little metacognitive insight on the extent to which they are personally vulnerable to the risks of divided attention, relative to other people. PMID:24490818

Executive Control Over Cognition: Stronger and Earlier Rule-Based Modulation of Spatial Category Signals in Prefrontal Cortex Relative to Parietal Cortex

PubMed Central

Goodwin, Shikha J.; Blackman, Rachael K.; Sakellaridi, Sofia

2012-01-01

Human cognition is characterized by flexibility, the ability to select not only which action but which cognitive process to engage to best achieve the current behavioral objective. The ability to tailor information processing in the brain to rules, goals, or context is typically referred to as executive control, and although there is consensus that prefrontal cortex is importantly involved, at present we have an incomplete understanding of how computational flexibility is implemented at the level of prefrontal neurons and networks. To better understand the neural mechanisms of computational flexibility, we simultaneously recorded the electrical activity of groups of single neurons within prefrontal and posterior parietal cortex of monkeys performing a task that required executive control of spatial cognitive processing. In this task, monkeys applied different spatial categorization rules to reassign the same set of visual stimuli to alternative categories on a trial-by-trial basis. We found that single neurons were activated to represent spatially defined categories in a manner that was rule dependent, providing a physiological signature of a cognitive process that was implemented under executive control. We found also that neural signals coding rule-dependent categories were distributed between the parietal and prefrontal cortex—however, not equally. Rule-dependent category signals were stronger, more powerfully modulated by the rule, and earlier to emerge in prefrontal cortex relative to parietal cortex. This suggests that prefrontal cortex may initiate the switch in neural representation at a network level that is important for computational flexibility. PMID:22399773

Mouse-tracking evidence for parallel anticipatory option evaluation.

PubMed

Cranford, Edward A; Moss, Jarrod

2017-12-23

In fast-paced, dynamic tasks, the ability to anticipate the future outcome of a sequence of events is crucial to quickly selecting an appropriate course of action among multiple alternative options. There are two classes of theories that describe how anticipation occurs. Serial theories assume options are generated and evaluated one at a time, in order of quality, whereas parallel theories assume simultaneous generation and evaluation. The present research examined the option evaluation process during a task designed to be analogous to prior anticipation tasks, but within the domain of narrative text comprehension. Prior research has relied on indirect, off-line measurement of the option evaluation process during anticipation tasks. Because the movement of the hand can provide a window into underlying cognitive processes, online metrics such as continuous mouse tracking provide more fine-grained measurements of cognitive processing as it occurs in real time. In this study, participants listened to three-sentence stories and predicted the protagonists' final action by moving a mouse toward one of three possible options. Each story was presented with either one (control condition) or two (distractor condition) plausible ending options. Results seem most consistent with a parallel option evaluation process because initial mouse trajectories deviated further from the best option in the distractor condition compared to the control condition. It is difficult to completely rule out all possible serial processing accounts, although the results do place constraints on the time frame in which a serial processing explanation must operate.

Hierarchical Learning Induces Two Simultaneous, But Separable, Prediction Errors in Human Basal Ganglia

PubMed Central

Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew

2013-01-01

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously. PMID:23536092

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.

PubMed

Lindsay, Grace W; Rigotti, Mattia; Warden, Melissa R; Miller, Earl K; Fusi, Stefano

2017-11-08

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear "mixed" selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli-and in particular, to combinations of stimuli ("mixed selectivity")-is a topic of interest. Even though models with random feedforward connectivity are capable of creating computationally relevant mixed selectivity, such a model does not match the levels of mixed selectivity seen in the data analyzed in this study. Adding simple Hebbian learning to the model increases mixed selectivity to the correct level and makes the model match the data on several other relevant measures. This study thus offers predictions on how mixed selectivity and other properties evolve with training. Copyright © 2017 the authors 0270-6474/17/3711021-16$15.00/0.

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

PubMed Central

Lindsay, Grace W.

2017-01-01

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (“mixed selectivity”)—is a topic of interest. Even though models with random feedforward connectivity are capable of creating computationally relevant mixed selectivity, such a model does not match the levels of mixed selectivity seen in the data analyzed in this study. Adding simple Hebbian learning to the model increases mixed selectivity to the correct level and makes the model match the data on several other relevant measures. This study thus offers predictions on how mixed selectivity and other properties evolve with training. PMID:28986463

Memory Updating and Mental Arithmetic

PubMed Central

Han, Cheng-Ching; Yang, Tsung-Han; Lin, Chia-Yuan; Yen, Nai-Shing

2016-01-01

Is domain-general memory updating ability predictive of calculation skills or are such skills better predicted by the capacity for updating specifically numerical information? Here, we used multidigit mental multiplication (MMM) as a measure for calculating skill as this operation requires the accurate maintenance and updating of information in addition to skills needed for arithmetic more generally. In Experiment 1, we found that only individual differences with regard to a task updating numerical information following addition (MUcalc) could predict the performance of MMM, perhaps owing to common elements between the task and MMM. In Experiment 2, new updating tasks were designed to clarify this: a spatial updating task with no numbers, a numerical task with no calculation, and a word task. The results showed that both MUcalc and the spatial task were able to predict the performance of MMM but only with the more difficult problems, while other updating tasks did not predict performance. It is concluded that relevant processes involved in updating the contents of working memory support mental arithmetic in adults. PMID:26869971

Using Challenging Tasks for Formative Assessment on Quadratic Functions with Senior Secondary Students

ERIC Educational Resources Information Center

Wilkie, Karina J.

2016-01-01

Senior secondary mathematics students who develop conceptual understanding that moves them beyond "rules without reasons" to connections between related concepts are in a strong place to tackle the more difficult mathematics application problems. Current research is examining how the use of challenging tasks at different levels of…

Event-Related fMRI of Category Learning: Differences in Classification and Feedback Networks

ERIC Educational Resources Information Center

Little, Deborah M.; Shin, Silvia S.; Sisco, Shannon M.; Thulborn, Keith R.

2006-01-01

Eighteen healthy young adults underwent event-related (ER) functional magnetic resonance imaging (fMRI) of the brain while performing a visual category learning task. The specific category learning task required subjects to extract the rules that guide classification of quasi-random patterns of dots into categories. Following each classification…

Are Intuitive Rules Universal?

ERIC Educational Resources Information Center

Stavy, Ruth; Tsamir, Pessia; Tirosh, Dina; Lin, Fou lai; McRobbie, Campbell

In their work in science and mathematics education, the authors have observed that students intuitively react in similar ways to a wide variety of scientific tasks. These tasks differ with regard to their content area and/or to the reasoning required for their solution, but share some common, external features. We have identified three types of…

Cohort-Sequential Study of Conflict Inhibition during Middle Childhood

ERIC Educational Resources Information Center

Rollins, Leslie; Riggins, Tracy

2017-01-01

This longitudinal study examined developmental changes in conflict inhibition and error correction in three cohorts of children (5, 7, and 9 years of age). At each point of assessment, children completed three levels of Luria's tapping task (1980), which requires the inhibition of a dominant response and maintenance of task rules in working…

Adaptive optimal training of animal behavior

NASA Astrophysics Data System (ADS)

Bak, Ji Hyun; Choi, Jung Yoon; Akrami, Athena; Witten, Ilana; Pillow, Jonathan

Neuroscience experiments often require training animals to perform tasks designed to elicit various sensory, cognitive, and motor behaviors. Training typically involves a series of gradual adjustments of stimulus conditions and rewards in order to bring about learning. However, training protocols are usually hand-designed, and often require weeks or months to achieve a desired level of task performance. Here we combine ideas from reinforcement learning and adaptive optimal experimental design to formulate methods for efficient training of animal behavior. Our work addresses two intriguing problems at once: first, it seeks to infer the learning rules underlying an animal's behavioral changes during training; second, it seeks to exploit these rules to select stimuli that will maximize the rate of learning toward a desired objective. We develop and test these methods using data collected from rats during training on a two-interval sensory discrimination task. We show that we can accurately infer the parameters of a learning algorithm that describes how the animal's internal model of the task evolves over the course of training. We also demonstrate by simulation that our method can provide a substantial speedup over standard training methods.

Electrophysiological correlates of preparation and implementation for different types of task shifts.

PubMed

Hsieh, Shulan; Wu, Mengyao

2011-11-14

The ability to flexibly shift between tasks is central to cognitive control, but whether the same brain mechanisms mediate shifting across different tasks is unknown. In this study, we investigated whether variations in stimulus-dimensions or response-mapping might influence task switching in terms of its preparatory processes, as reflected in cue-locked event-related potentials (ERPs), and its implementation processes, as reflected in stimulus-locked ERPs. Participants judged pairs of digits as same or different in one of two conditions. In one condition, the task-relevant stimulus-dimension was either repeated or switched across trials while the response-mapping rule was kept constant. In the other condition, the task-relevant stimulus-dimension was kept constant while the response-mapping rule was repeated or switched across trials. The length of the preparatory interval was manipulated. Data revealed switch-related preparatory ERP components (including N2 and a late slow positivity) that were associated with both types of task shifting and an N400-like negativity that distinguished between the two types. Several switch-related implementation ERP components associated with both types of task shifting were found at posterior sites. Distinct frontal modulations of the N1, P2, and N2 were found to associate with the implementation of the response-mapping shift, whereas a slow positivity was associated with the implementation of the stimulus-dimension shift. Therefore, this study demonstrates that there are shared and distinct processes across different types of task shifting. Finally, because the same transition-cue was used for different task shifts, the distinct processes cannot be explained simply by differences in cue processing. Copyright © 2011 Elsevier B.V. All rights reserved.

Working-memory load and temporal myopia in dynamic decision making.

PubMed

Worthy, Darrell A; Otto, A Ross; Maddox, W Todd

2012-11-01

We examined the role of working memory (WM) in dynamic decision making by having participants perform decision-making tasks under single-task or dual-task conditions. In 2 experiments participants performed dynamic decision-making tasks in which they chose 1 of 2 options on each trial. The decreasing option always gave a larger immediate reward but caused future rewards for both options to decrease. The increasing option always gave a smaller immediate reward but caused future rewards for both options to increase. In each experiment we manipulated the reward structure such that the decreasing option was the optimal choice in 1 condition and the increasing option was the optimal choice in the other condition. Behavioral results indicated that dual-task participants selected the immediately rewarding decreasing option more often, and single-task participants selected the increasing option more often, regardless of which option was optimal. Thus, dual-task participants performed worse on 1 type of task but better on the other type. Modeling results showed that single-task participants' data were most often best fit by a win-stay, lose-shift (WSLS) rule-based model that tracked differences across trials, and dual-task participants' data were most often best fit by a Softmax reinforcement learning model that tracked recency-weighted average rewards for each option. This suggests that manipulating WM load affects the degree to which participants focus on the immediate versus delayed consequences of their actions and whether they employ a rule-based WSLS strategy, but it does not necessarily affect how well people weigh the immediate versus delayed benefits when determining the long-term utility of each option.

Predicting nuclear gene coalescence from mitochondrial data: the three-times rule.

PubMed

Palumbi, S R; Cipriano, F; Hare, M P

2001-05-01

Coalescence theory predicts when genetic drift at nuclear loci will result in fixation of sequence differences to produce monophyletic gene trees. However, the theory is difficult to apply to particular taxa because it hinges on genetically effective population size, which is generally unknown. Neutral theory also predicts that evolution of monophyly will be four times slower in nuclear than in mitochondrial genes primarily because genetic drift is slower at nuclear loci. Variation in mitochondrial DNA (mtDNA) within and between species has been studied extensively, but can these mtDNA data be used to predict coalescence in nuclear loci? Comparison of neutral theories of coalescence of mitochondrial and nuclear loci suggests a simple rule of thumb. The "three-times rule" states that, on average, most nuclear loci will be monophyletic when the branch length leading to the mtDNA sequences of a species is three times longer than the average mtDNA sequence diversity observed within that species. A test using mitochondrial and nuclear intron data from seven species of whales and dolphins suggests general agreement with predictions of the three-times rule. We define the coalescence ratio as the mitochondrial branch length for a species divided by intraspecific mtDNA diversity. We show that species with high coalescence ratios show nuclear monophyly, whereas species with low ratios have polyphyletic nuclear gene trees. As expected, species with intermediate coalescence ratios show a variety of patterns. Especially at very high or low coalescence ratios, the three-times rule predicts nuclear gene patterns that can help detect the action of selection. The three-times rule may be useful as an empirical benchmark for evaluating evolutionary processes occurring at multiple loci.

External Validation of the Universal Termination of Resuscitation Rule for Out-of-Hospital Cardiac Arrest in British Columbia.

PubMed

Grunau, Brian; Taylor, John; Scheuermeyer, Frank X; Stenstrom, Robert; Dick, William; Kawano, Takahisa; Barbic, David; Drennan, Ian; Christenson, Jim

2017-09-01

The Universal Termination of Resuscitation Rule (TOR Rule) was developed to identify out-of-hospital cardiac arrests eligible for field termination of resuscitation, avoiding futile transportation to the hospital. The validity of the rule in emergency medical services (EMS) systems that do not routinely transport out-of-hospital cardiac arrest patients to the hospital is unknown. We seek to validate the TOR Rule in British Columbia. This study included consecutive, nontraumatic, adult, out-of-hospital cardiac arrests treated by EMS in British Columbia from April 2011 to September 2015. We excluded patients with active do-not-resuscitate orders and those with missing data. Following consensus guidelines, we examined the validity of the TOR Rule after 6 minutes of resuscitation (to approximate three 2-minute cycles of resuscitation). To ascertain rule performance at the different time junctures, we recalculated TOR Rule classification accuracy at subsequent 1-minute resuscitation increments. Of 6,994 consecutive, adult, EMS-treated, out-of-hospital cardiac arrests, overall survival was 15%. At 6 minutes of resuscitation, rule performance was sensitivity 0.72, specificity 0.91, positive predictive value 0.98, and negative predictive value 0.36. The TOR Rule recommended care termination for 4,367 patients (62%); of these, 92 survived to hospital discharge (false-positive rate 2.1%; 95% confidence interval 1.7% to 2.5%); however, this proportion steadily decreased with later application. The TOR Rule recommended continuation of resuscitation in 2,627 patients (38%); of these, 1,674 died (false-negative rate 64%; 95% confidence interval 62% to 66%). Compared with 6-minute application, test characteristics at 30 minutes demonstrated nearly perfect positive predictive value (1.0) and specificity (1.0) but a lower sensitivity (0.46) and negative predictive value (0.25). In this cohort of adult out-of-hospital cardiac arrest patients, the TOR Rule applied at 6 minutes falsely recommended care termination for 2.1% of patients; however, this decreased with later application. Systems using the TOR Rule to cease resuscitation in the field should consider rule application at points later than 6 minutes. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

QUEST/Ada (Query Utility Environment for Software Testing of Ada): The development of a prgram analysis environment for Ada, task 1, phase 2

NASA Technical Reports Server (NTRS)

Brown, David B.

1990-01-01

The results of research and development efforts are described for Task one, Phase two of a general project entitled The Development of a Program Analysis Environment for Ada. The scope of this task includes the design and development of a prototype system for testing Ada software modules at the unit level. The system is called Query Utility Environment for Software Testing of Ada (QUEST/Ada). The prototype for condition coverage provides a platform that implements expert system interaction with program testing. The expert system can modify data in the instrument source code in order to achieve coverage goals. Given this initial prototype, it is possible to evaluate the rule base in order to develop improved rules for test case generation. The goals of Phase two are the following: (1) to continue to develop and improve the current user interface to support the other goals of this research effort (i.e., those related to improved testing efficiency and increased code reliable); (2) to develop and empirically evaluate a succession of alternative rule bases for the test case generator such that the expert system achieves coverage in a more efficient manner; and (3) to extend the concepts of the current test environment to address the issues of Ada concurrency.

A drop in performance on a fluid intelligence test due to instructed-rule mindset.

PubMed

ErEl, Hadas; Meiran, Nachshon

2017-09-01

A 'mindset' is a configuration of processing resources that are made available for the task at hand as well as their suitable tuning for carrying it out. Of special interest, remote-relation abstract mindsets are introduced by activities sharing only general control processes with the task. To test the effect of a remote-relation mindset on performance on a Fluid Intelligence test (Raven's Advanced Progressive Matrices, RAPM), we induced a mindset associated with little usage of executive processing by requiring participants to execute a well-defined classification rule 12 times, a manipulation known from previous work to drastically impair rule-generation performance and associated cognitive processes. In Experiment 1, this manipulation led to a drop in RAPM performance equivalent to 10.1 IQ points. No drop was observed in a General Knowledge task. In Experiment 2, a similar drop in RAPM performance was observed (equivalent to 7.9 and 9.2 IQ points) regardless if participants were pre-informed about the upcoming RAPM test. These results indicate strong (most likely, transient) adverse effects of a remote-relation mindset on test performance. They imply that although the trait of Fluid Intelligence has probably not changed, mindsets can severely distort estimates of this trait.

The interaction of process and domain in prefrontal cortex during inductive reasoning

PubMed Central

Babcock, Laura; Vallesi, Antonino

2015-01-01

Inductive reasoning is an everyday process that allows us to make sense of the world by creating rules from a series of instances. Consistent with accounts of process-based fractionations of the prefrontal cortex (PFC) along the left–right axis, inductive reasoning has been reliably localized to left PFC. However, these results may be confounded by the task domain, which is typically verbal. Indeed, some studies show that right PFC activation is seen with spatial tasks. This study used fMRI to examine the effects of process and domain on the brain regions recruited during a novel pattern discovery task. Twenty healthy young adult participants were asked to discover the rule underlying the presentation of a series of letters in varied spatial locations. The rules were either verbal (pertaining to a single semantic category) or spatial (geometric figures). Bilateral ventrolateral PFC activations were seen for the spatial domain, while the verbal domain showed only left ventrolateral PFC. A conjunction analysis revealed that the two domains recruited a common region of left ventrolateral PFC. The data support a central role of left PFC in inductive reasoning. Importantly, they also suggest that both process and domain shape the localization of reasoning in the brain. PMID:25498406

The interaction of process and domain in prefrontal cortex during inductive reasoning.

PubMed

Babcock, Laura; Vallesi, Antonino

2015-01-01

Inductive reasoning is an everyday process that allows us to make sense of the world by creating rules from a series of instances. Consistent with accounts of process-based fractionations of the prefrontal cortex (PFC) along the left-right axis, inductive reasoning has been reliably localized to left PFC. However, these results may be confounded by the task domain, which is typically verbal. Indeed, some studies show that right PFC activation is seen with spatial tasks. This study used fMRI to examine the effects of process and domain on the brain regions recruited during a novel pattern discovery task. Twenty healthy young adult participants were asked to discover the rule underlying the presentation of a series of letters in varied spatial locations. The rules were either verbal (pertaining to a single semantic category) or spatial (geometric figures). Bilateral ventrolateral PFC activations were seen for the spatial domain, while the verbal domain showed only left ventrolateral PFC. A conjunction analysis revealed that the two domains recruited a common region of left ventrolateral PFC. The data support a central role of left PFC in inductive reasoning. Importantly, they also suggest that both process and domain shape the localization of reasoning in the brain. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

An Investigation of Privately Financed Renewable Energy Projects for Army Installations

DTIC Science & Technology

1990-09-01

PURPA ) restrictions, current Internal Revenue Service (IRS) rulings, and the expiration of Federal tax credits were identified. Task 3: Innovative...palatable to the policymakers. Existing legislation, including Federal acquisition regulations, PURPA restrictions, and existing tax laws, while not...discourage the application of renewable energy systems. The PURPA rules are undergoing evaluation. Although the effect of the FederalEnergy Regulating

Different Executive Functions Support Different Kinds of Cognitive Flexibility: Evidence from 2-, 3-, and 4-Year-Olds

ERIC Educational Resources Information Center

Blakey, Emma; Visser, Ingmar; Carroll, Daniel J.

2016-01-01

Improvements in cognitive flexibility during the preschool years have been linked to developments in both working memory and inhibitory control, though the precise contribution of each remains unclear. In the current study, one hundred and twenty 2-, 3-, and 4-year-olds completed two rule-switching tasks. In one version, children switched rules in…

Exposure to Family Violence and Internalizing and Externalizing Problems Among Spanish Adolescents.

PubMed

Izaguirre, Ainhoa; Calvete, Esther

2018-04-01

Exposure to intimate partner violence (IPV) and child maltreatment may have devastating consequences on children's development. The aim of this research was to examine the predictive associations between exposure to violence at home (witnessing violence against the mother and/or direct victimization by the parents) and adolescent internalizing and externalizing problems. A total of 613 Spanish adolescents (13-18 years) took part in this study. Results indicate that psychological victimization by the parents predicted an increase in anxious/depressive symptoms, aggressive and rule-breaking behavior, and substance abuse at Time 2. In addition, rule-breaking behavior predicted an increase in adolescents' substance abuse at Time 2. Concerning gender, psychological victimization predicted an increase in anxiety/depression, aggressive behavior, rule-breaking behavior, and substance abuse in boys; whereas in girls, psychological victimization only predicted an increase in anxiety/depression.

Analytic and rule-based decision support tool for VDT workstation adjustment and computer accessories arrangement.

PubMed

Rurkhamet, Busagarin; Nanthavanij, Suebsak

2004-12-01

One important factor that leads to the development of musculoskeletal disorders (MSD) and cumulative trauma disorders (CTD) among visual display terminal (VDT) users is their work posture. While operating a VDT, a user's body posture is strongly influenced by the task, VDT workstation settings, and layout of computer accessories. This paper presents an analytic and rule-based decision support tool called EQ-DeX (an ergonomics and quantitative design expert system) that is developed to provide valid and practical recommendations regarding the adjustment of a VDT workstation and the arrangement of computer accessories. The paper explains the structure and components of EQ-DeX, input data, rules, and adjustment and arrangement algorithms. From input information such as gender, age, body height, task, etc., EQ-DeX uses analytic and rule-based algorithms to estimate quantitative settings of a computer table and a chair, as well as locations of computer accessories such as monitor, document holder, keyboard, and mouse. With the input and output screens that are designed using the concept of usability, the interactions between the user and EQ-DeX are convenient. Examples are also presented to demonstrate the recommendations generated by EQ-DeX.

Skills, rules and knowledge in aircraft maintenance: errors in context

NASA Technical Reports Server (NTRS)

Hobbs, Alan; Williamson, Ann

2002-01-01

Automatic or skill-based behaviour is generally considered to be less prone to error than behaviour directed by conscious control. However, researchers who have applied Rasmussen's skill-rule-knowledge human error framework to accidents and incidents have sometimes found that skill-based errors appear in significant numbers. It is proposed that this is largely a reflection of the opportunities for error which workplaces present and does not indicate that skill-based behaviour is intrinsically unreliable. In the current study, 99 errors reported by 72 aircraft mechanics were examined in the light of a task analysis based on observations of the work of 25 aircraft mechanics. The task analysis identified the opportunities for error presented at various stages of maintenance work packages and by the job as a whole. Once the frequency of each error type was normalized in terms of the opportunities for error, it became apparent that skill-based performance is more reliable than rule-based performance, which is in turn more reliable than knowledge-based performance. The results reinforce the belief that industrial safety interventions designed to reduce errors would best be directed at those aspects of jobs that involve rule- and knowledge-based performance.

Preschoolers can infer general rules governing fantastical events in fiction.

PubMed

Van de Vondervoort, Julia W; Friedman, Ori

2014-05-01

Young children are frequently exposed to fantastic fiction. How do they make sense of the unrealistic and impossible events that occur in such fiction? Although children could view such events as isolated episodes, the present experiments suggest that children use such events to infer general fantasy rules. In 2 experiments, 2- to 4-year-olds were shown scenarios in which 2 animals behaved unrealistically (N = 78 in Experiment 1, N = 94 in Experiment 2). When asked to predict how other animals in the fiction would behave, children predicted novel behaviors consistent with the nature of the fiction. These findings suggest that preschoolers can infer the general rules that govern the events and entities in fantastic fiction and can use these rules to predict what events will happen in the fiction. The findings also provide evidence that children may infer fantasy rules at a more superordinate level than the basic level. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Simple Decision-Analytic Functions of the AUC for Ruling Out a Risk Prediction Model and an Added Predictor.

PubMed

Baker, Stuart G

2018-02-01

When using risk prediction models, an important consideration is weighing performance against the cost (monetary and harms) of ascertaining predictors. The minimum test tradeoff (MTT) for ruling out a model is the minimum number of all-predictor ascertainments per correct prediction to yield a positive overall expected utility. The MTT for ruling out an added predictor is the minimum number of added-predictor ascertainments per correct prediction to yield a positive overall expected utility. An approximation to the MTT for ruling out a model is 1/[P (H(AUC model )], where H(AUC) = AUC - {½ (1-AUC)} ½ , AUC is the area under the receiver operating characteristic (ROC) curve, and P is the probability of the predicted event in the target population. An approximation to the MTT for ruling out an added predictor is 1 /[P {(H(AUC Model:2 ) - H(AUC Model:1 )], where Model 2 includes an added predictor relative to Model 1. The latter approximation requires the Tangent Condition that the true positive rate at the point on the ROC curve with a slope of 1 is larger for Model 2 than Model 1. These approximations are suitable for back-of-the-envelope calculations. For example, in a study predicting the risk of invasive breast cancer, Model 2 adds to the predictors in Model 1 a set of 7 single nucleotide polymorphisms (SNPs). Based on the AUCs and the Tangent Condition, an MTT of 7200 was computed, which indicates that 7200 sets of SNPs are needed for every correct prediction of breast cancer to yield a positive overall expected utility. If ascertaining the SNPs costs $500, this MTT suggests that SNP ascertainment is not likely worthwhile for this risk prediction.

An investigation of the 'von Restorff' phenomenon in post-test workload ratings

NASA Technical Reports Server (NTRS)

Thornton, D. C.

1985-01-01

The von Restorff effect in post-task ratings of task difficulty is examined. Nine subjects performed a hovercraft simulation task which combined elements of skill-based tracking and rule- and knowledge-based process control for five days of one hour sessions. The effects of isolated increases in workload on rating of task performance, and on the number of command errors and river band hits are analyzed. It is observed that the position of the workload increase affects the number of bank hits and command errors. The data reveal that factors not directly related to the task performance influence subjective rating, and post-task ratings of workload are biased.

Time Sharing Between Robotics and Process Control: Validating a Model of Attention Switching.

PubMed

Wickens, Christopher Dow; Gutzwiller, Robert S; Vieane, Alex; Clegg, Benjamin A; Sebok, Angelia; Janes, Jess

2016-03-01

The aim of this study was to validate the strategic task overload management (STOM) model that predicts task switching when concurrence is impossible. The STOM model predicts that in overload, tasks will be switched to, to the extent that they are attractive on task attributes of high priority, interest, and salience and low difficulty. But more-difficult tasks are less likely to be switched away from once they are being performed. In Experiment 1, participants performed four tasks of the Multi-Attribute Task Battery and provided task-switching data to inform the role of difficulty and priority. In Experiment 2, participants concurrently performed an environmental control task and a robotic arm simulation. Workload was varied by automation of arm movement and both the phases of environmental control and existence of decision support for fault management. Attention to the two tasks was measured using a head tracker. Experiment 1 revealed the lack of influence of task priority and confirmed the differing roles of task difficulty. In Experiment 2, the percentage attention allocation across the eight conditions was predicted by the STOM model when participants rated the four attributes. Model predictions were compared against empirical data and accounted for over 95% of variance in task allocation. More-difficult tasks were performed longer than easier tasks. Task priority does not influence allocation. The multiattribute decision model provided a good fit to the data. The STOM model is useful for predicting cognitive tunneling given that human-in-the-loop simulation is time-consuming and expensive. © 2016, Human Factors and Ergonomics Society.

Scaling rules for the final decline to extinction

PubMed Central

Griffen, Blaine D.; Drake, John M.

2009-01-01

Space–time scaling rules are ubiquitous in ecological phenomena. Current theory postulates three scaling rules that describe the duration of a population's final decline to extinction, although these predictions have not previously been empirically confirmed. We examine these scaling rules across a broader set of conditions, including a wide range of density-dependent patterns in the underlying population dynamics. We then report on tests of these predictions from experiments using the cladoceran Daphnia magna as a model. Our results support two predictions that: (i) the duration of population persistence is much greater than the duration of the final decline to extinction and (ii) the duration of the final decline to extinction increases with the logarithm of the population's estimated carrying capacity. However, our results do not support a third prediction that the duration of the final decline scales inversely with population growth rate. These findings not only support the current standard theory of population extinction but also introduce new empirical anomalies awaiting a theoretical explanation. PMID:19141422

Modeling the prediction of business intelligence system effectiveness.

PubMed

Weng, Sung-Shun; Yang, Ming-Hsien; Koo, Tian-Lih; Hsiao, Pei-I

2016-01-01

Although business intelligence (BI) technologies are continually evolving, the capability to apply BI technologies has become an indispensable resource for enterprises running in today's complex, uncertain and dynamic business environment. This study performed pioneering work by constructing models and rules for the prediction of business intelligence system effectiveness (BISE) in relation to the implementation of BI solutions. For enterprises, effectively managing critical attributes that determine BISE to develop prediction models with a set of rules for self-evaluation of the effectiveness of BI solutions is necessary to improve BI implementation and ensure its success. The main study findings identified the critical prediction indicators of BISE that are important to forecasting BI performance and highlighted five classification and prediction rules of BISE derived from decision tree structures, as well as a refined regression prediction model with four critical prediction indicators constructed by logistic regression analysis that can enable enterprises to improve BISE while effectively managing BI solution implementation and catering to academics to whom theory is important.

A critical evaluation of monkey models of amnesia and dementia.

PubMed

Ridley, R M; Baker, H F

1991-01-01

In this review we consider various models of amnesia and dementia in monkeys and examine the validity of such models. In Section 2 we describe the various types of memory tests (tasks) available for use with monkeys and discuss the extent to which these tasks assess different facets of memory according to present theories of human memory. We argue that the rules which govern correct task performance are best regarded as a form of semantic rather than procedural memory, and that when information about stimulus attributes or reward associations is stored long-term then that knowledge is semantic. The demonstration of episodic memory in monkeys is problematic and the term recognition memory has been used too loosely. In particular, it is difficult to dissociate episodic memory for stimulus events from the use of semantic memory for the rule of the task, since dysfunction of either can produce impairment on performance of the same task. Tasks can also be divided into those which assess memory for stimulus-reward associations (evaluative memory) and those which tax stimulus-response associations including spatial and conditional responding (non-evaluative memory). This dissociation cuts across the distinction between semantic and episodic memory. In Section 3 we examine the usefulness of the classification of tasks described in Section 2 in clarifying our understanding of the contribution of the temporal lobes and the cholinergic system to memory. We conclude that evaluative and non-evaluative memory are mediated by separate parallel systems involving the amygdala and hippocampus, respectively.

Automatic learning of rules. A practical example of using artificial intelligence to improve computer-based detection of myocardial infarction and left ventricular hypertrophy in the 12-lead ECG.

PubMed

Kaiser, W; Faber, T S; Findeis, M

1996-01-01

The authors developed a computer program that detects myocardial infarction (MI) and left ventricular hypertrophy (LVH) in two steps: (1) by extracting parameter values from a 10-second, 12-lead electrocardiogram, and (2) by classifying the extracted parameter values with rule sets. Every disease has its dedicated set of rules. Hence, there are separate rule sets for anterior MI, inferior MI, and LVH. If at least one rule is satisfied, the disease is said to be detected. The computer program automatically develops these rule sets. A database (learning set) of healthy subjects and patients with MI, LVH, and mixed MI+LVH was used. After defining the rule type, initial limits, and expected quality of the rules (positive predictive value, minimum number of patients), the program creates a set of rules by varying the limits. The general rule type is defined as: disease = lim1l < p1 < or = lim1u and lim2l < p2 < or = lim2u and ... limnl < pn < or = limnu. When defining the rule types, only the parameters (p1 ... pn) that are known as clinical electrocardiographic criteria (amplitudes [mV] of Q, R, and T waves and ST-segment; duration [ms] of Q wave; frontal angle [degrees]) were used. This allowed for submitting the learned rule sets to an independent investigator for medical verification. It also allowed the creation of explanatory texts with the rules. These advantages are not offered by the neurons of a neural network. The learned rules were checked against a test set and the following results were obtained: MI: sensitivity 76.2%, positive predictive value 98.6%; LVH: sensitivity 72.3%, positive predictive value 90.9%. The specificity ratings for MI are better than 98%; for LVH, better than 90%.

The sensitivity of a virtual reality task to planning and prospective memory impairments: group differences and the efficacy of periodic alerts on performance.

PubMed

Sweeney, Siobhan; Kersel, Denyse; Morris, Robin G; Manly, Tom; Evans, Jonathan J

2010-04-01

Executive functions have been argued to be the most vulnerable to brain injury. In providing an analogue of everyday situations amenable to control and management virtual reality (VR) may offer better insights into planning deficits consequent upon brain injury. Here 17 participants with a non-progressive brain injury and reported executive difficulties in everyday life were asked to perform a VR task (working in a furniture storage unit) that emphasised planning, rule following and prospective memory tasks. When compared with an age and IQ-matched control group, the patients were significantly poorer in terms of their strategy, their time-based prospective memory, the overall time required and their propensity to break rules. An examination of sensitivity and specificity of the VR task to group membership (brain-injured or control) showed that, with specificity set at maximum, sensitivity was only modest (at just over 50%). A second component to the study investigated whether the patients' performance could be improved by periodic auditory alerts. Previous studies have demonstrated that such cues can improve performance on laboratory tests, executive tests and everyday prospective memory tasks. Here, no significant changes in performance were detected. Potential reasons for this finding are discussed, including symptom severity and differences in the tasks employed in previous studies.

Testing the performance of technical trading rules in the Chinese markets based on superior predictive test

NASA Astrophysics Data System (ADS)

Wang, Shan; Jiang, Zhi-Qiang; Li, Sai-Ping; Zhou, Wei-Xing

2015-12-01

Technical trading rules have a long history of being used by practitioners in financial markets. The profitable ability and efficiency of technical trading rules are yet controversial. In this paper, we test the performance of more than seven thousand traditional technical trading rules on the Shanghai Securities Composite Index (SSCI) from May 21, 1992 through June 30, 2013 and China Securities Index 300 (CSI 300) from April 8, 2005 through June 30, 2013 to check whether an effective trading strategy could be found by using the performance measurements based on the return and Sharpe ratio. To correct for the influence of the data-snooping effect, we adopt the Superior Predictive Ability test to evaluate if there exists a trading rule that can significantly outperform the benchmark. The result shows that for SSCI, technical trading rules offer significant profitability, while for CSI 300, this ability is lost. We further partition the SSCI into two sub-series and find that the efficiency of technical trading in sub-series, which have exactly the same spanning period as that of CSI 300, is severely weakened. By testing the trading rules on both indexes with a five-year moving window, we find that during the financial bubble from 2005 to 2007, the effectiveness of technical trading rules is greatly improved. This is consistent with the predictive ability of technical trading rules which appears when the market is less efficient.

Genetic learning in rule-based and neural systems

NASA Technical Reports Server (NTRS)

Smith, Robert E.

1993-01-01

The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

Age-related variance in decisions under ambiguity is explained by changes in reasoning, executive functions, and decision-making under risk.

PubMed

Schiebener, Johannes; Brand, Matthias

2017-06-01

Previous literature has explained older individuals' disadvantageous decision-making under ambiguity in the Iowa Gambling Task (IGT) by reduced emotional warning signals preceding decisions. We argue that age-related reductions in IGT performance may also be explained by reductions in certain cognitive abilities (reasoning, executive functions). In 210 participants (18-86 years), we found that the age-related variance on IGT performance occurred only in the last 60 trials. The effect was mediated by cognitive abilities and their relation with decision-making performance under risk with explicit rules (Game of Dice Task). Thus, reductions in cognitive functions in older age may be associated with both a reduced ability to gain explicit insight into the rules of the ambiguous decision situation and with failure to choose the less risky options consequently after the rules have been understood explicitly. Previous literature may have underestimated the relevance of cognitive functions for age-related decline in decision-making performance under ambiguity.

Microcomputer-based classification of environmental data in municipal areas

NASA Astrophysics Data System (ADS)

Thiergärtner, H.

1995-10-01

Multivariate data-processing methods used in mineral resource identification can be used to classify urban regions. Using elements of expert systems, geographical information systems, as well as known classification and prognosis systems, it is possible to outline a single model that consists of resistant and of temporary parts of a knowledge base including graphical input and output treatment and of resistant and temporary elements of a bank of methods and algorithms. Whereas decision rules created by experts will be stored in expert systems directly, powerful classification rules in form of resistant but latent (implicit) decision algorithms may be implemented in the suggested model. The latent functions will be transformed into temporary explicit decision rules by learning processes depending on the actual task(s), parameter set(s), pixels selection(s), and expert control(s). This takes place both at supervised and nonsupervised classification of multivariately described pixel sets representing municipal subareas. The model is outlined briefly and illustrated by results obtained in a target area covering a part of the city of Berlin (Germany).

Confirming a predicted selection rule in inelastic neutron scattering spectroscopy: the quantum translator-rotator H2 entrapped inside C60.

PubMed

Xu, Minzhong; Jiménez-Ruiz, Mónica; Johnson, Mark R; Rols, Stéphane; Ye, Shufeng; Carravetta, Marina; Denning, Mark S; Lei, Xuegong; Bačić, Zlatko; Horsewill, Anthony J

2014-09-19

We report an inelastic neutron scattering (INS) study of a H2 molecule encapsulated inside the fullerene C60 which confirms the recently predicted selection rule, the first to be established for the INS spectroscopy of aperiodic, discrete molecular compounds. Several transitions from the ground state of para-H2 to certain excited translation-rotation states, forbidden according to the selection rule, are systematically absent from the INS spectra, thus validating the selection rule with a high degree of confidence. Its confirmation sets a precedent, as it runs counter to the widely held view that the INS spectroscopy of molecular compounds is not subject to any selection rules.

The costs and benefits of temporal predictability: impaired inhibition of prepotent responses accompanies increased activation of task-relevant responses.

PubMed

Korolczuk, Inga; Burle, Boris; Coull, Jennifer T

2018-06-20

While the benefit of temporal predictability on sensorimotor processing is well established, it is still unknown whether this is due to efficient execution of an appropriate response and/or inhibition of an inappropriate one. To answer this question, we examined the effects of temporal predictability in tasks that required selective (Simon task) or global (Stop-signal task) inhibitory control of prepotent responses. We manipulated temporal expectation by presenting cues that either predicted (temporal cues) or not (neutral cues) when the target would appear. In the Simon task, performance was better when target location (left/right) was compatible with the hand of response and performance was improved further still if targets were temporally cued. However, Conditional Accuracy Functions revealed that temporal predictability selectively increased the number of fast, impulsive errors. Temporal cueing had no effect on selective response inhibition, as measured by the dynamics of the interference effect (delta plots) in the Simon task. By contrast, in the Stop-signal task, Stop-signal reaction time, a covert measure of a more global form of response inhibition, was significantly longer in temporally predictive trials. Therefore, when the time of target onset could be predicted in advance, it was harder to stop the impulse to respond to the target. Collectively, our results indicate that temporal cueing compounded the interfering effects of a prepotent response on task performance. We suggest that although temporal predictability enhances activation of task-relevant responses, it impairs inhibition of prepotent responses. Copyright © 2018 Elsevier B.V. All rights reserved.

The motor locus of no-go backward crosstalk.

PubMed

Durst, Moritz; Janczyk, Markus

2018-04-23

A frequent observation in dual-task studies is the backward crosstalk effect (BCE), meaning that aspects of a secondary Task 2 influence Task 1 performance. Up to this point, 2 major types of the BCE were investigated: a BCE based on dimensional overlap between both stimuli and/or responses (the compatibility-based BCE), and a BCE based on whether Task 2 is a go or no-go task (the no-go BCE). Recent evidence suggests that the compatibility-based BCE has its locus inside the response selection stage. The available evidence for the locus of the no-go BCE is still mixed, however. To this end, the 3 experiments reported in the present study used an extended psychological refractory period (PRP) paradigm with 3 subsequent tasks. Applying the locus of slack logic in Experiment 1, the no-go BCE was not absorbed into the cognitive slack and, thus, a locus before response selection could be ruled out. Subsequently applying the effect propagation logic in Experiment 2 and 3, the no-go BCE arising in Task 1 was even inverted in Task 3. Because no propagation of the no-go BCE was observed, a locus before or in response selection could be ruled out. Thus, we conclude that the no-go BCE has its locus during motor execution. Because the no-go BCE and the compatibility-based BCE are located in different stages, we suggest that both types of the BCE do not share a common underlying mechanism. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Drifting from Slow to “D’oh!” Working Memory Capacity and Mind Wandering Predict Extreme Reaction Times and Executive-Control Errors

PubMed Central

McVay, Jennifer C.; Kane, Michael J.

2012-01-01

A combined experimental, individual-differences, and thought-sampling study tested the predictions of executive attention (e.g., Engle & Kane, 2004) and coordinative binding (e.g., Oberauer, Süß, Wilhelm, & Sander, 2007) theories of working memory capacity (WMC). We assessed 288 subjects’ WMC and their performance and mind-wandering rates during a sustained-attention task; subjects completed either a go/no-go version requiring executive control over habit, or a vigilance version that did not. We further combined the data with those from McVay and Kane (2009) to: (1) gauge the contributions of WMC and attentional lapses to the worst-performance rule and the tail, or τ parameter, of response time (RT) distributions; (2) assess which parameters from a quantitative evidence-accumulation RT model were predicted by WMC and mind-wandering reports, and (3) consider intra-subject RT patterns – particularly, speeding – as potential objective markers of mind wandering. We found that WMC predicted action and thought control in only some conditions, that attentional lapses (indicated by TUT reports and drift-rate variability in evidence accumulation) contributed to τ, performance accuracy, and WMC’s association with them, and that mind-wandering experiences were not predicted by trial-to-trial RT changes, and so they cannot always be inferred from objective performance measures. PMID:22004270

[The Amsterdam wrist rules: the multicenter prospective derivation and external validation of a clinical decision rule for the use of radiography in acute wrist trauma].

PubMed

Walenkamp, Monique M J; Bentohami, Abdelali; Slaar, Annelie; Beerekamp, M S H Suzan; Maas, Mario; Jager, L C Cara; Sosef, Nico L; van Velde, Romuald; Ultee, Jan M; Steyerberg, Ewout W; Goslings, J C Carel; Schep, Niels W L

2016-01-01

Although only 39% of patients with wrist trauma have sustained a fracture, the majority of patients is routinely referred for radiography. The purpose of this study was to derive and externally validate a clinical decision rule that selects patients with acute wrist trauma in the Emergency Department (ED) for radiography. This multicenter prospective study consisted of three components: (1) derivation of a clinical prediction model for detecting wrist fractures in patients following wrist trauma; (2) external validation of this model; and (3) design of a clinical decision rule. The study was conducted in the EDs of five Dutch hospitals: one academic hospital (derivation cohort) and four regional hospitals (external validation cohort). We included all adult patients with acute wrist trauma. The main outcome was fracture of the wrist (distal radius, distal ulna or carpal bones) diagnosed on conventional X-rays. A total of 882 patients were analyzed; 487 in the derivation cohort and 395 in the validation cohort. We derived a clinical prediction model with eight variables: age; sex, swelling of the wrist; swelling of the anatomical snuffbox, visible deformation; distal radius tender to palpation; pain on radial deviation and painful axial compression of the thumb. The Area Under the Curve at external validation of this model was 0.81 (95% CI: 0.77-0.85). The sensitivity and specificity of the Amsterdam Wrist Rules (AWR) in the external validation cohort were 98% (95% CI: 95-99%) and 21% (95% CI: 15%-28). The negative predictive value was 90% (95% CI: 81-99%). The Amsterdam Wrist Rules is a clinical prediction rule with a high sensitivity and negative predictive value for fractures of the wrist. Although external validation showed low specificity and 100 % sensitivity could not be achieved, the Amsterdam Wrist Rules can provide physicians in the Emergency Department with a useful screening tool to select patients with acute wrist trauma for radiography. The upcoming implementation study will further reveal the impact of the Amsterdam Wrist Rules on the anticipated reduction of X-rays requested, missed fractures, Emergency Department waiting times and health care costs.

The effects of task difficulty, novelty and the size of the search space on intrinsically motivated exploration.

PubMed

Baranes, Adrien F; Oudeyer, Pierre-Yves; Gottlieb, Jacqueline

2014-01-01

Devising efficient strategies for exploration in large open-ended spaces is one of the most difficult computational problems of intelligent organisms. Because the available rewards are ambiguous or unknown during the exploratory phase, subjects must act in intrinsically motivated fashion. However, a vast majority of behavioral and neural studies to date have focused on decision making in reward-based tasks, and the rules guiding intrinsically motivated exploration remain largely unknown. To examine this question we developed a paradigm for systematically testing the choices of human observers in a free play context. Adult subjects played a series of short computer games of variable difficulty, and freely choose which game they wished to sample without external guidance or physical rewards. Subjects performed the task in three distinct conditions where they sampled from a small or a large choice set (7 vs. 64 possible levels of difficulty), and where they did or did not have the possibility to sample new games at a constant level of difficulty. We show that despite the absence of external constraints, the subjects spontaneously adopted a structured exploration strategy whereby they (1) started with easier games and progressed to more difficult games, (2) sampled the entire choice set including extremely difficult games that could not be learnt, (3) repeated moderately and high difficulty games much more frequently than was predicted by chance, and (4) had higher repetition rates and chose higher speeds if they could generate new sequences at a constant level of difficulty. The results suggest that intrinsically motivated exploration is shaped by several factors including task difficulty, novelty and the size of the choice set, and these come into play to serve two internal goals-maximize the subjects' knowledge of the available tasks (exploring the limits of the task set), and maximize their competence (performance and skills) across the task set.

Discovering rules for protein-ligand specificity using support vector inductive logic programming.

PubMed

Kelley, Lawrence A; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2009-09-01

Structural genomics initiatives are rapidly generating vast numbers of protein structures. Comparative modelling is also capable of producing accurate structural models for many protein sequences. However, for many of the known structures, functions are not yet determined, and in many modelling tasks, an accurate structural model does not necessarily tell us about function. Thus, there is a pressing need for high-throughput methods for determining function from structure. The spatial arrangement of key amino acids in a folded protein, on the surface or buried in clefts, is often the determinants of its biological function. A central aim of molecular biology is to understand the relationship between such substructures or surfaces and biological function, leading both to function prediction and to function design. We present a new general method for discovering the features of binding pockets that confer specificity for particular ligands. Using a recently developed machine-learning technique which couples the rule-discovery approach of inductive logic programming with the statistical learning power of support vector machines, we are able to discriminate, with high precision (90%) and recall (86%) between pockets that bind FAD and those that bind NAD on a large benchmark set given only the geometry and composition of the backbone of the binding pocket without the use of docking. In addition, we learn rules governing this specificity which can feed into protein functional design protocols. An analysis of the rules found suggests that key features of the binding pocket may be tied to conformational freedom in the ligand. The representation is sufficiently general to be applicable to any discriminatory binding problem. All programs and data sets are freely available to non-commercial users at http://www.sbg.bio.ic.ac.uk/svilp_ligand/.

The Effect of Labeling on Preschool Children's Performance in the Dimensional Change Card Sort Task

ERIC Educational Resources Information Center

Muller, Ulrich; Zelazo, Philip D.; Lurye, Leah E.; Liebermann, Dana P.

2008-01-01

Previous research suggests that experimenter-induced labeling of test cards improves preschoolers' performance on the Dimensional Change Card Sort Task (DCCS), a measure of flexible rule use. Three experiments attempted to further clarify how labeling aids performance on the DCCS. Experiment 1 examined the nature of the labeling effect but failed…

Some Memories Are Odder than Others: Judgments of Episodic Oddity Violate Known Decision Rules

ERIC Educational Resources Information Center

O'Connor, Akira R.; Guhl, Emily N.; Cox, Justin C.; Dobbins, Ian G.

2011-01-01

Current decision models of recognition memory are based almost entirely on one paradigm, single item old/new judgments accompanied by confidence ratings. This task results in receiver operating characteristics (ROCs) that are well fit by both signal-detection and dual-process models. Here we examine an entirely new recognition task, the judgment…

On the acquisition and representation of procedural knowledge

NASA Technical Reports Server (NTRS)

Saito, T.; Ortiz, C.; Loftin, R. B.

1992-01-01

Historically knowledge acquisition has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some of some types of knowledge, little attention has been devoted to procedural knowledge. NASA personnel frequently perform tasks that are primarily procedural in nature. Previous work is reviewed in the field of knowledge acquisition and then focus on knowledge acquisition for procedural tasks with special attention devoted to the Navy's VISTA tool. The design and development is described of a system for the acquisition and representation of procedural knowledge-TARGET (Task Analysis and Rule Generation Tool). TARGET is intended as a tool that permits experts to visually describe procedural tasks and as a common medium for knowledge refinement by the expert and knowledge engineer. The system is designed to represent the acquired knowledge in the form of production rules. Systems such as TARGET have the potential to profoundly reduce the time, difficulties, and costs of developing knowledge-based systems for the performance of procedural tasks.

Both hands at work: the effect of aging on upper-limb kinematics in a multi-step activity of daily living.

PubMed

Gulde, Philipp; Hermsdörfer, Joachim

2017-05-01

The kinematic performance of basic motor tasks shows a clear decrease with advancing age. This study examined if the rules known from such tasks can be generalized to activities of daily living. We examined the end-effector kinematics of 13 young and 13 elderly participants in the multi-step activity of daily living of tea-making. Furthermore, we analyzed bimanual behavior and hand dominance in the task using different conditions of execution. The elderly sample took substantially longer to complete the activity (almost 50%) with longer trajectories compared with the young sample. Models of multiple linear regression revealed that the longer trajectories prolonged the trial duration in both groups, and while movement speed influenced the trial duration of young participants, phases of inactivity negatively affected how long the activity took the elderly subjects. No differences were found regarding bimanual performance or hand dominance. We assume that in self-paced activities of daily living, the age-dependent differences in the kinematics are more likely to be based on the higher cognitive demands of the task rather than on pure motor capability. Furthermore, it seems that not all of the rules known from basic motor tasks can be generalized to activities of daily living.

Neuromodulation of Prefrontal Cortex in Non-Human Primates by Dopaminergic Receptors during Rule-Guided Flexible Behavior and Cognitive Control

PubMed Central

Vijayraghavan, Susheel; Major, Alex J.; Everling, Stefan

2017-01-01

The prefrontal cortex (PFC) is indispensable for several higher-order cognitive and executive capacities of primates, including representation of salient stimuli in working memory (WM), maintenance of cognitive task set, inhibition of inappropriate responses and rule-guided flexible behavior. PFC networks are subject to robust neuromodulation from ascending catecholaminergic systems. Disruption of these systems in PFC has been implicated in cognitive deficits associated with several neuropsychiatric disorders. Over the past four decades, a considerable body of work has examined the influence of dopamine on macaque PFC activity representing spatial WM. There has also been burgeoning interest in neuromodulation of PFC circuits involved in other cognitive functions of PFC, including representation of rules to guide flexible behavior. Here, we review recent neuropharmacological investigations conducted in our laboratory and others of the role of PFC dopamine receptors in regulating rule-guided behavior in non-human primates. Employing iontophoresis, we examined the effects of local manipulation of dopaminergic subtypes on neuronal activity during performance of rule-guided pro- and antisaccades, an experimental paradigm sensitive to PFC integrity, wherein deficits in performance are reliably observed in many neuropsychiatric disorders. We found dissociable effects of dopamine receptors on neuronal activity for rule representation and oculomotor responses and discuss these findings in the context of prior studies that have examined the role of dopamine in spatial delayed response tasks, attention, target selection, abstract rules, visuomotor learning and reward. The findings we describe here highlight the common features, as well as heterogeneity and context dependence of dopaminergic neuromodulation in regulating the efficacy of cognitive functions of PFC in health and disease. PMID:29259545

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reinforcement Learning Using a Continuous Time Actor-Critic Framework with Spiking Neurons

PubMed Central

Frémaux, Nicolas; Sprekeler, Henning; Gerstner, Wulfram

2013-01-01

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity. PMID:23592970

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

PubMed

Frémaux, Nicolas; Sprekeler, Henning; Gerstner, Wulfram

2013-04-01

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Interpretable Decision Sets: A Joint Framework for Description and Prediction

PubMed Central

Lakkaraju, Himabindu; Bach, Stephen H.; Jure, Leskovec

2016-01-01

One of the most important obstacles to deploying predictive models is the fact that humans do not understand and trust them. Knowing which variables are important in a model’s prediction and how they are combined can be very powerful in helping people understand and trust automatic decision making systems. Here we propose interpretable decision sets, a framework for building predictive models that are highly accurate, yet also highly interpretable. Decision sets are sets of independent if-then rules. Because each rule can be applied independently, decision sets are simple, concise, and easily interpretable. We formalize decision set learning through an objective function that simultaneously optimizes accuracy and interpretability of the rules. In particular, our approach learns short, accurate, and non-overlapping rules that cover the whole feature space and pay attention to small but important classes. Moreover, we prove that our objective is a non-monotone submodular function, which we efficiently optimize to find a near-optimal set of rules. Experiments show that interpretable decision sets are as accurate at classification as state-of-the-art machine learning techniques. They are also three times smaller on average than rule-based models learned by other methods. Finally, results of a user study show that people are able to answer multiple-choice questions about the decision boundaries of interpretable decision sets and write descriptions of classes based on them faster and more accurately than with other rule-based models that were designed for interpretability. Overall, our framework provides a new approach to interpretable machine learning that balances accuracy, interpretability, and computational efficiency. PMID:27853627

Semi-empirical correlation for binary interaction parameters of the Peng-Robinson equation of state with the van der Waals mixing rules for the prediction of high-pressure vapor-liquid equilibrium.

PubMed

Fateen, Seif-Eddeen K; Khalil, Menna M; Elnabawy, Ahmed O

2013-03-01

Peng-Robinson equation of state is widely used with the classical van der Waals mixing rules to predict vapor liquid equilibria for systems containing hydrocarbons and related compounds. This model requires good values of the binary interaction parameter kij . In this work, we developed a semi-empirical correlation for kij partly based on the Huron-Vidal mixing rules. We obtained values for the adjustable parameters of the developed formula for over 60 binary systems and over 10 categories of components. The predictions of the new equation system were slightly better than the constant-kij model in most cases, except for 10 systems whose predictions were considerably improved with the new correlation.

Prediction of vesicoureteral reflux after a first febrile urinary tract infection in children: validation of a clinical decision rule.

PubMed

Leroy, S; Marc, E; Adamsbaum, C; Gendrel, D; Bréart, G; Chalumeau, M

2006-03-01

To test the reproducibility of a highly sensitive clinical decision rule proposed to predict vesicoureteral reflux (VUR) after a first febrile urinary tract infection in children. This rule combines clinical (family history of uropathology, male gender, young age), biological (raised C reactive protein), and radiological (urinary tract dilation on renal ultrasound) predictors in a score, and provides 100% sensitivity. A retrospective hospital based cohort study included all children, 1 month to 4 years old, with a first febrile urinary tract infection. The sensitivities and specificities of the rule at the two previously proposed score thresholds (< or =0 and < or =5) to predict respectively, all-grade or grade > or =3 VUR, were calculated. A total of 149 children were included. VUR prevalence was 25%. The rule yielded 100% sensitivity and 3% specificity for all-grade VUR, and 93% sensitivity and 13% specificity for grade > or =3 VUR. Some methodological weaknesses explain this lack of reproducibility. The reproducibility of the previously proposed decision rule was poor and its potential contribution to clinical management of children with febrile urinary tract infection seems to be modest.

Prediction of vesicoureteral reflux after a first febrile urinary tract infection in children: validation of a clinical decision rule

PubMed Central

Leroy, S; Marc, E; Adamsbaum, C; Gendrel, D; Bréart, G; Chalumeau, M

2006-01-01

Aims To test the reproducibility of a highly sensitive clinical decision rule proposed to predict vesicoureteral reflux (VUR) after a first febrile urinary tract infection in children. This rule combines clinical (family history of uropathology, male gender, young age), biological (raised C reactive protein), and radiological (urinary tract dilation on renal ultrasound) predictors in a score, and provides 100% sensitivity. Methods A retrospective hospital based cohort study included all children, 1 month to 4 years old, with a first febrile urinary tract infection. The sensitivities and specificities of the rule at the two previously proposed score thresholds (⩽0 and ⩽5) to predict respectively, all‐grade or grade ⩾3 VUR, were calculated. Results A total of 149 children were included. VUR prevalence was 25%. The rule yielded 100% sensitivity and 3% specificity for all‐grade VUR, and 93% sensitivity and 13% specificity for grade ⩾3 VUR. Some methodological weaknesses explain this lack of reproducibility. Conclusions The reproducibility of the previously proposed decision rule was poor and its potential contribution to clinical management of children with febrile urinary tract infection seems to be modest. PMID:15890693

Theory of mind broad and narrow: reasoning about social exchange engages ToM areas, precautionary reasoning does not.

PubMed

Ermer, Elsa; Guerin, Scott A; Cosmides, Leda; Tooby, John; Miller, Michael B

2006-01-01

Baron-Cohen (1995) proposed that the theory of mind (ToM) inference system evolved to promote strategic social interaction. Social exchange--a form of co-operation for mutual benefit--involves strategic social interaction and requires ToM inferences about the contents of other individuals' mental states, especially their desires, goals, and intentions. There are behavioral and neuropsychological dissociations between reasoning about social exchange and reasoning about equivalent problems tapping other, more general content domains. It has therefore been proposed that social exchange behavior is regulated by social contract algorithms: a domain-specific inference system that is functionally specialized for reasoning about social exchange. We report an fMRI study using the Wason selection task that provides further support for this hypothesis. Precautionary rules share so many properties with social exchange rules--they are conditional, deontic, and involve subjective utilities--that most reasoning theories claim they are processed by the same neurocomputational machinery. Nevertheless, neuroimaging shows that reasoning about social exchange activates brain areas not activated by reasoning about precautionary rules, and vice versa. As predicted, neural correlates of ToM (anterior and posterior temporal cortex) were activated when subjects interpreted social exchange rules, but not precautionary rules (where ToM inferences are unnecessary). We argue that the interaction between ToM and social contract algorithms can be reciprocal: social contract algorithms requires ToM inferences, but their functional logic also allows ToM inferences to be made. By considering interactions between ToM in the narrower sense (belief-desire reasoning) and all the social inference systems that create the logic of human social interaction--ones that enable as well as use inferences about the content of mental states--a broader conception of ToM may emerge: a computational model embodying a Theory of Human Nature (ToHN).

What Visual Information Do Children and Adults Consider while Switching between Tasks? Eye-Tracking Investigation of Cognitive Flexibility Development

ERIC Educational Resources Information Center

Chevalier, Nicolas; Blaye, Agnes; Dufau, Stephane; Lucenet, Joanna

2010-01-01

This study investigated the visual information that children and adults consider while switching or maintaining object-matching rules. Eye movements of 5- and 6-year-old children and adults were collected with two versions of the Advanced Dimensional Change Card Sort, which requires switching between shape- and color-matching rules. In addition to…

When Seeing Is Knowing: The Role of Visual Cues in the Dissociation between Children's Rule Knowledge and Rule Use

ERIC Educational Resources Information Center

Buss, Aaron T.; Spencer, John P.

2012-01-01

The Dimensional Change Card Sort (DCCS) task requires children to switch from sorting cards based on shape or color to sorting based on the other dimension. Typically, 3-year-olds perseverate, whereas 4-year-olds flexibly sort by different dimensions. Zelazo and colleagues (1996, Cognitive Development, 11, 37-63) asked children questions about the…

Predicting Handwriting Difficulties Through Spelling Processes.

PubMed

Rodríguez, Cristina; Villarroel, Rebeca

This study examined whether spelling tasks contribute to the prediction of the handwriting status of children with poor and good handwriting skills in a cross-sectional study with 276 Spanish children from Grades 1 and 3. The main hypothesis was that the spelling tasks would predict the handwriting status of the children, although this influence would decrease with age due to a gradual automatization of handwriting skills. The results confirmed this hypothesis. Another interesting result was that the pattern of pseudoword and irregular word spellings as predictors of handwriting status changed from Grade 1 to Grade 3. In Grade 1, the pseudoword spelling task made a significant contribution, whereas the irregular word spelling task did not. The opposite pattern was found in Grade 3. These results may be a consequence of progressive acquisition of orthographic representations. The orthographic role of the task of writing the alphabet in order from memory in the prediction model was also analyzed. The writing of the alphabet in order from memory task made a significant contribution to the prediction of handwriting status of the children beyond the orthographic influence of spelling tasks. The additional effect of this task on the prediction of handwriting status is presumably due to the fact that this measure is based on fluency.

Attention toward contexts modulates context-specificity of behavior in human predictive learning: Evidence from the n-back task.

PubMed

Uengoer, Metin; Lucke, Sara; Lachnit, Harald

2018-02-20

According to the attentional theory of context processing (ATCP), learning becomes context specific when acquired under conditions that promote attention toward contextual stimuli regardless of whether attention deployment is guided by learning experience or by other factors unrelated to learning. In one experiment with humans, we investigated whether performance in a predictive learning task can be brought under contextual control by means of a secondary task that was unrelated to predictive learning, but supposed to modulate participants' attention toward contexts. Initially, participants acquired cue-outcome relationships presented in contexts that were each composed of two elements from two dimensions. Acquisition training in the predictive learning task was combined with a one-back task that required participants to match across consecutive trials context elements belonging to one of the two dimensions. During a subsequent test, we observed that acquisition behavior in the predictive learning task was disrupted by changing the acquisition context along the dimension that was relevant for the one-back task, while there was no evidence for context specificity of predictive learning when the acquisition context was changed along the dimension that was irrelevant for the one-back task. Our results support the generality of the principles advocated by ATCP.

Selective impairment of masked priming in dual-task performance.

PubMed

Fischer, Rico; Kiesel, Andrea; Kunde, Wilfried; Schubert, Torsten

2011-03-01

This study investigated the impact of divided attention on masked priming. In a dual-task setting, two tasks had to be carried out in close temporal succession: a tone discrimination task and a masked priming task. The order of the tasks was varied between experiments, and attention was always allocated to the first task-that is, the first task was prioritized. The priming task was the second (nonprioritized) task in Experiment 1 and the first (prioritized) task in Experiment 2. In both experiments, "novel" prime stimuli associated with semantic processing were essentially ineffective. However, there was intact priming by another type of prime stimuli associated with response priming. Experiment 3 showed that all these prime stimuli can reveal significant priming effects during a task-switching paradigm in which both tasks were performed consecutively. We conclude that dual-task specific interference processes (e.g., the simultaneous coordination of multiple stimulus-response rules) selectively impair priming that is assumed to rely on semantic processing.

Spaceborne construction and operations planning - Decision rules for selecting EVA, telerobot, and combined work-systems

NASA Technical Reports Server (NTRS)

Smith, Jeffrey H.

1992-01-01

An approach is presented for selecting an appropriate work-system for performing construction and operations tasks by humans and telerobots. The decision to use extravehicular activity (EVA) performed by astronauts, extravehicular robotics (EVR), or a combination of EVA and EVR is determined by the ratio of the marginal costs of EVA, EVR, and IVA. The approach proposed here is useful for examining cost trade-offs between tasks and performing trade studies of task improvement techniques (human or telerobotic).

When more is less: Feedback effects in perceptual category learning ☆

PubMed Central

Maddox, W. Todd; Love, Bradley C.; Glass, Brian D.; Filoteo, J. Vincent

2008-01-01

Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether their response was correct or incorrect, but are not informed of the correct category assignment. With full feedback subjects are informed of the correctness of their response and are also informed of the correct category assignment. An examination of the distinct neural circuits that subserve rule-based and information-integration category learning leads to the counterintuitive prediction that full feedback should facilitate rule-based learning but should also hinder information-integration learning. This prediction was supported in the experiment reported below. The implications of these results for theories of learning are discussed. PMID:18455155

The contribution of coping related variables and cardiac vagal activity on the performance of a dart throwing task under pressure.

PubMed

Mosley, Emma; Laborde, Sylvain; Kavanagh, Emma

2017-10-01

The aims of this study were 1) to assess the predictive role of coping related variables (CRV) on cardiac vagal activity (derived from heart rate variability), and 2) to investigate the influence of CRV (including cardiac vagal activity) on a dart throwing task under low pressure (LP) and high pressure (HP) conditions. Participants (n=51) completed trait CRV questionnaires: Decision Specific Reinvestment Scale, Movement Specific Reinvestment Scale and Trait Emotional Intelligence Questionnaire. They competed in a dart throwing task under LP and HP conditions. Cardiac vagal activity measurements were taken at resting, task and during recovery for 5min. Self-reported ratings of stress were recorded at three time points via a visual analogue scale. Upon completion of the task, self-report measures of motivation, stress appraisal, attention, perceived pressure and dart throwing experience were completed. Results indicated that resting cardiac vagal activity had no predictors. Task cardiac vagal activity was predicted by resting cardiac vagal activity in both pressure conditions with the addition of a trait CRV in HP. Post task cardiac vagal activity was predicted by resting cardiac vagal activity in both conditions with the addition of a trait CRV in HP. Cardiac vagal reactivity (difference from resting to task) was predicted by a trait CRV in HP conditions. Cardiac vagal recovery (difference from task to post task) was predicted by a state CRV only in LP. Dart throwing task performance was predicted by a combination of both CRV and cardiac vagal activity. The current research suggests that coping related variables and cardiac vagal activity influence dart throwing task performance differently dependent on pressure condition. Copyright © 2017 Elsevier Inc. All rights reserved.

Oculomotor Cognitive Control Abnormalities in Australian Rules Football Players with a History of Concussion.

PubMed

Clough, Meaghan; Mutimer, Steven; Wright, David K; Tsang, Adrian; Costello, Daniel M; Gardner, Andrew J; Stanwell, Peter; Mychasiuk, Richelle; Sun, Mujun; Brady, Rhys D; McDonald, Stuart J; Webster, Kyria M; Johnstone, Maddison R; Semple, Bridgette D; Agoston, Denes V; White, Owen B; Frayne, Richard; Fielding, Joanne; O'Brien, Terence J; Shultz, Sandy R

2018-03-01

This study used oculomotor, cognitive, and multi-modal magnetic resonance imaging (MRI) measures to assess for neurological abnormalities in current asymptomatic amateur Australian rules footballers (i.e., Australia's most participated collision sport) with a history of sports-related concussion (SRC). Participants were 15 male amateur Australian rules football players with a history of SRC greater than 6 months previously, and 15 sex-, age-, and education-matched athlete control subjects that had no history of neurotrauma or participation in collision sports. Participants completed a clinical interview, neuropsychological measures, and oculomotor measures of cognitive control. MRI investigation involved structural imaging, as well as diffusion tensor imaging and resting-state functional MRI sequences. Despite no group differences on conventional neuropsychological tests and multi-modal MRI measures, Australian rules football players with a history of SRC performed significantly worse on an oculomotor switch task: a measure of cognitive control that interleaves the response of looking towards a target (i.e., a prosaccade) with the response of looking away from a target (i.e., an antisaccade). Specifically, Australian footballers performed significantly shorter latency prosaccades and found changing from an antisaccade trial to a prosaccade trial (switch cost) significantly more difficult than control subjects. Poorer switch cost was related to poorer performance on a number of neuropsychological measures of inhibitory control. Further, when comparing performance on the cognitively more demanding switch task with performance on simpler, antisaccade/prosaccades tasks which require a single response, Australian footballers demonstrated a susceptibility to increased cognitive load, compared to the control group who were unaffected. These initial results suggest that current asymptomatic amateur Australian rules football players with a history of SRC may have persisting, subtle, cognitive changes, which are demonstrable on oculomotor cognitive measures. Future studies are required in order to further elucidate the full nature and clinical relevance of these findings.

The scaling behavior of hand motions reveals self-organization during an executive function task

NASA Astrophysics Data System (ADS)

Anastas, Jason R.; Stephen, Damian G.; Dixon, James A.

2011-05-01

Recent approaches to cognition explain cognitive phenomena in terms of interaction-dominant dynamics. In the current experiment, we extend this approach to executive function, a construct used to describe flexible, goal-oriented behavior. Participants were asked to perform a widely used executive function task, card sorting, under two conditions. In one condition, participants were given a rule with which to sort the cards. In the other condition, participants had to induce the rule from experimenter feedback. The motion of each participant’s hand was tracked during the sorting task. Detrended fluctuation analysis was performed on the inter-point time series using a windowing strategy to capture changes over each trial. For participants in the induction condition, the Hurst exponent sharply increased and then decreased. The Hurst exponents for the explicit condition did not show this pattern. Our results suggest that executive function may be understood in terms of changes in stability that arise from interaction-dominant dynamics.

On Supporting Physical Skill Discovery

NASA Astrophysics Data System (ADS)

Furukawa, Koichi; Suwa, Masaki; Kato, Takaaki

One of the main difficulties in motor skill acquisition is attributed to body control based on wrong mental models. This is true to various domains such as playing sports and playing musical instruments. In order to acquire adequate motor skill by modifying false belief, we need to help people find appropriate key points in achieving a body control and integrate them. In this paper, we investigate three approaches to realize such support. The first one is to encourage exploration of the relations among key points constituting a motor skill, using a technique of meta-cognitive verbalization. The second one is to represent a motor skill by appropriate mechanical models. The third one is to integrate rules for component tasks in achieving a compound task. These three approaches, we argue, help people build an integrated mental model consisting of multiple relations among various key points, one that seems to be indispensable for acquisition of motor skills. These ideas suggest the possibility to create new skill rules to perform difficult tasks automatically.

Deliberation's blindsight: how cognitive load can improve judgments.

PubMed

Hoffmann, Janina A; von Helversen, Bettina; Rieskamp, Jörg

2013-06-01

Multitasking poses a major challenge in modern work environments by putting the worker under cognitive load. Performance decrements often occur when people are under high cognitive load because they switch to less demanding--and often less accurate--cognitive strategies. Although cognitive load disturbs performance over a wide range of tasks, it may also carry benefits. In the experiments reported here, we showed that judgment performance can increase under cognitive load. Participants solved a multiple-cue judgment task in which high performance could be achieved by using a similarity-based judgment strategy but not by using a more demanding rule-based judgment strategy. Accordingly, cognitive load induced a shift to a similarity-based judgment strategy, which consequently led to more accurate judgments. By contrast, shifting to a similarity-based strategy harmed judgments in a task best solved by using a rule-based strategy. These results show how important it is to consider the cognitive strategies people rely on to understand how people perform in demanding work environments.

Psychopaths are impaired in social exchange and precautionary reasoning.

PubMed

Ermer, Elsa; Kiehl, Kent A

2010-10-01

Psychopaths show a profound lack of morality and behavioral controls in the presence of intact general intellectual functioning. Two hallmarks of psychopathy are the persistent violation of social contracts (i.e., cheating) and chronic, impulsive risky behavior. These behaviors present a puzzle: Can psychopaths understand and reason about what counts as cheating or risky behavior in a particular situation? We tested incarcerated psychopaths' and incarcerated nonpsychopaths' reasoning about social contract rules, precautionary rules, and descriptive rules using the Wason selection task. Results were consistent with our hypotheses: Psychopaths (compared with matched nonpsychopaths) showed significant impairment on social contract rules and precautionary rules, but not on descriptive rules. These results cannot be accounted for by differences in intelligence, motivation, or general antisocial tendency. These findings suggest that examination of evolutionarily identified reasoning processes can be a fruitful research approach for identifying which specific mechanisms are impaired in psychopathy.