WorldWideScience

Sample records for human category learning

  1. Attentional Bias in Human Category Learning: The Case of Deep Learning.

    Science.gov (United States)

    Hanson, Catherine; Caglar, Leyla Roskan; Hanson, Stephen José

    2018-01-01

    Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987) showed that stimuli can have structures with features that are statistically uncorrelated (separable) or statistically correlated (integral) within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974). In contrast to humans, a single hidden layer backpropagation (BP) neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993). This "failure" to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1) by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2) by investigating whether a Deep Learning (DL) network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc.), would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993). Second, we show that using the same low dimensional stimuli, Deep Learning (DL), unlike BP but similar to humans, learns separable category structures more quickly than integral category structures

  2. Attentional Bias in Human Category Learning: The Case of Deep Learning

    Directory of Open Access Journals (Sweden)

    Catherine Hanson

    2018-04-01

    Full Text Available Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987 showed that stimuli can have structures with features that are statistically uncorrelated (separable or statistically correlated (integral within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974. In contrast to humans, a single hidden layer backpropagation (BP neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993. This “failure” to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1 by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2 by investigating whether a Deep Learning (DL network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc., would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993. Second, we show that using the same low dimensional stimuli, Deep Learning (DL, unlike BP but similar to humans, learns separable category structures more quickly than integral category

  3. Information-integration category learning and the human uncertainty response.

    Science.gov (United States)

    Paul, Erick J; Boomer, Joseph; Smith, J David; Ashby, F Gregory

    2011-04-01

    The human response to uncertainty has been well studied in tasks requiring attention and declarative memory systems. However, uncertainty monitoring and control have not been studied in multi-dimensional, information-integration categorization tasks that rely on non-declarative procedural memory. Three experiments are described that investigated the human uncertainty response in such tasks. Experiment 1 showed that following standard categorization training, uncertainty responding was similar in information-integration tasks and rule-based tasks requiring declarative memory. In Experiment 2, however, uncertainty responding in untrained information-integration tasks impaired the ability of many participants to master those tasks. Finally, Experiment 3 showed that the deficit observed in Experiment 2 was not because of the uncertainty response option per se, but rather because the uncertainty response provided participants a mechanism via which to eliminate stimuli that were inconsistent with a simple declarative response strategy. These results are considered in the light of recent models of category learning and metacognition.

  4. Blocking in Category Learning

    OpenAIRE

    Bott, Lewis; Hoffman, Aaron B.; Murphy, Gregory L.

    2007-01-01

    Many theories of category learning assume that learning is driven by a need to minimize classification error. When there is no classification error, therefore, learning of individual features should be negligible. We tested this hypothesis by conducting three category learning experiments adapted from an associative learning blocking paradigm. Contrary to an error-driven account of learning, participants learned a wide range of information when they learned about categories, and blocking effe...

  5. Warping similarity space in category learning by human subjects: the role of task difficulty

    OpenAIRE

    Pevtzow, Rachel; Harnad, Stevan

    1997-01-01

    In innate Categorical Perception (CP) (e.g., colour perception), similarity space is "warped," with regions of increased within-category similarity (compression) and regions of reduced between-category similarity (separation) enh ancing the category boundaries and making categorisation reliable and all-or-none rather than graded. We show that category learning can likewise warp similarity space, resolving uncertainty near category boundaries. Two Hard and two Easy texture learning tasks were ...

  6. SUSTAIN: a network model of category learning.

    Science.gov (United States)

    Love, Bradley C; Medin, Douglas L; Gureckis, Todd M

    2004-04-01

    SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.

  7. Transcranial infrared laser stimulation improves rule-based, but not information-integration, category learning in humans.

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    Blanco, Nathaniel J; Saucedo, Celeste L; Gonzalez-Lima, F

    2017-03-01

    This is the first randomized, controlled study comparing the cognitive effects of transcranial laser stimulation on category learning tasks. Transcranial infrared laser stimulation is a new non-invasive form of brain stimulation that shows promise for wide-ranging experimental and neuropsychological applications. It involves using infrared laser to enhance cerebral oxygenation and energy metabolism through upregulation of the respiratory enzyme cytochrome oxidase, the primary infrared photon acceptor in cells. Previous research found that transcranial infrared laser stimulation aimed at the prefrontal cortex can improve sustained attention, short-term memory, and executive function. In this study, we directly investigated the influence of transcranial infrared laser stimulation on two neurobiologically dissociable systems of category learning: a prefrontal cortex mediated reflective system that learns categories using explicit rules, and a striatally mediated reflexive learning system that forms gradual stimulus-response associations. Participants (n=118) received either active infrared laser to the lateral prefrontal cortex or sham (placebo) stimulation, and then learned one of two category structures-a rule-based structure optimally learned by the reflective system, or an information-integration structure optimally learned by the reflexive system. We found that prefrontal rule-based learning was substantially improved following transcranial infrared laser stimulation as compared to placebo (treatment X block interaction: F(1, 298)=5.117, p=0.024), while information-integration learning did not show significant group differences (treatment X block interaction: F(1, 288)=1.633, p=0.202). These results highlight the exciting potential of transcranial infrared laser stimulation for cognitive enhancement and provide insight into the neurobiological underpinnings of category learning. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Individual differences in attention during category learning

    NARCIS (Netherlands)

    Lee, M.D.; Wetzels, R.

    2010-01-01

    A central idea in many successful models of category learning—including the Generalized Context Model (GCM)—is that people selectively attend to those dimensions of stimuli that are relevant for dividing them into categories. We use the GCM to re-examine some previously analyzed category learning

  9. Words can slow down category learning.

    Science.gov (United States)

    Brojde, Chandra L; Porter, Chelsea; Colunga, Eliana

    2011-08-01

    Words have been shown to influence many cognitive tasks, including category learning. Most demonstrations of these effects have focused on instances in which words facilitate performance. One possibility is that words augment representations, predicting an across the-board benefit of words during category learning. We propose that words shift attention to dimensions that have been historically predictive in similar contexts. Under this account, there should be cases in which words are detrimental to performance. The results from two experiments show that words impair learning of object categories under some conditions. Experiment 1 shows that words hurt performance when learning to categorize by texture. Experiment 2 shows that words also hurt when learning to categorize by brightness, leading to selectively attending to shape when both shape and hue could be used to correctly categorize stimuli. We suggest that both the positive and negative effects of words have developmental origins in the history of word usage while learning categories. [corrected

  10. Observation versus classification in supervised category learning.

    Science.gov (United States)

    Levering, Kimery R; Kurtz, Kenneth J

    2015-02-01

    The traditional supervised classification paradigm encourages learners to acquire only the knowledge needed to predict category membership (a discriminative approach). An alternative that aligns with important aspects of real-world concept formation is learning with a broader focus to acquire knowledge of the internal structure of each category (a generative approach). Our work addresses the impact of a particular component of the traditional classification task: the guess-and-correct cycle. We compare classification learning to a supervised observational learning task in which learners are shown labeled examples but make no classification response. The goals of this work sit at two levels: (1) testing for differences in the nature of the category representations that arise from two basic learning modes; and (2) evaluating the generative/discriminative continuum as a theoretical tool for understand learning modes and their outcomes. Specifically, we view the guess-and-correct cycle as consistent with a more discriminative approach and therefore expected it to lead to narrower category knowledge. Across two experiments, the observational mode led to greater sensitivity to distributional properties of features and correlations between features. We conclude that a relatively subtle procedural difference in supervised category learning substantially impacts what learners come to know about the categories. The results demonstrate the value of the generative/discriminative continuum as a tool for advancing the psychology of category learning and also provide a valuable constraint for formal models and associated theories.

  11. The Role of Corticostriatal Systems in Speech Category Learning.

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    Yi, Han-Gyol; Maddox, W Todd; Mumford, Jeanette A; Chandrasekaran, Bharath

    2016-04-01

    One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  12. When does fading enhance perceptual category learning?

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    Pashler, Harold; Mozer, Michael C

    2013-07-01

    Training that uses exaggerated versions of a stimulus discrimination (fading) has sometimes been found to enhance category learning, mostly in studies involving animals and impaired populations. However, little is known about whether and when fading facilitates learning for typical individuals. This issue was explored in 7 experiments. In Experiments 1 and 2, observers discriminated stimuli based on a single sensory continuum (time duration and line length, respectively). Adaptive fading dramatically improved performance in training (unsurprisingly) but did not enhance learning as assessed in a final test. The same was true for nonadaptive linear fading (Experiment 3). However, when variation in length (predicting category membership) was embedded among other (category-irrelevant) variation, fading dramatically enhanced not only performance in training but also learning as assessed in a final test (Experiments 4 and 5). Fading also helped learners to acquire a color saturation discrimination amid category-irrelevant variation in hue and brightness, although this learning proved transitory after feedback was withdrawn (Experiment 7). Theoretical implications are discussed, and we argue that fading should have practical utility in naturalistic category learning tasks, which involve extremely high dimensional stimuli and many irrelevant dimensions. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  13. Pattern-Induced Covert Category Learning in Songbirds.

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    Comins, Jordan A; Gentner, Timothy Q

    2015-07-20

    Language is uniquely human, but its acquisition may involve cognitive capacities shared with other species. During development, language experience alters speech sound (phoneme) categorization. Newborn infants distinguish the phonemes in all languages but by 10 months show adult-like greater sensitivity to native language phonemic contrasts than non-native contrasts. Distributional theories account for phonetic learning by positing that infants infer category boundaries from modal distributions of speech sounds along acoustic continua. For example, tokens of the sounds /b/ and /p/ cluster around different mean voice onset times. To disambiguate overlapping distributions, contextual theories propose that phonetic category learning is informed by higher-level patterns (e.g., words) in which phonemes normally occur. For example, the vowel sounds /Ι/ and /e/ can occupy similar perceptual spaces but can be distinguished in the context of "with" and "well." Both distributional and contextual cues appear to function in speech acquisition. Non-human species also benefit from distributional cues for category learning, but whether category learning benefits from contextual information in non-human animals is unknown. The use of higher-level patterns to guide lower-level category learning may reflect uniquely human capacities tied to language acquisition or more general learning abilities reflecting shared neurobiological mechanisms. Using songbirds, European starlings, we show that higher-level pattern learning covertly enhances categorization of the natural communication sounds. This observation mirrors the support for contextual theories of phonemic category learning in humans and demonstrates a general form of learning not unique to humans or language. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Supervised and Unsupervised Learning of Multidimensional Acoustic Categories

    Science.gov (United States)

    Goudbeek, Martijn; Swingley, Daniel; Smits, Roel

    2009-01-01

    Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributionally defined visual categories has shown that categories defined over 1 dimension are easy to learn and that learning multidimensional categories is…

  15. Order of Presentation Effects in Learning Color Categories

    Science.gov (United States)

    Sandhofer, Catherine M.; Doumas, Leonidas A. A.

    2008-01-01

    Two studies, an experimental category learning task and a computational simulation, examined how sequencing training instances to maximize comparison and memory affects category learning. In Study 1, 2-year-old children learned color categories with three training conditions that varied in how categories were distributed throughout training and…

  16. Category Learning Research in the Interactive Online Environment Second Life

    Science.gov (United States)

    Andrews, Jan; Livingston, Ken; Sturm, Joshua; Bliss, Daniel; Hawthorne, Daniel

    2011-01-01

    The interactive online environment Second Life allows users to create novel three-dimensional stimuli that can be manipulated in a meaningful yet controlled environment. These features suggest Second Life's utility as a powerful tool for investigating how people learn concepts for unfamiliar objects. The first of two studies was designed to establish that cognitive processes elicited in this virtual world are comparable to those tapped in conventional settings by attempting to replicate the established finding that category learning systematically influences perceived similarity . From the perspective of an avatar, participants navigated a course of unfamiliar three-dimensional stimuli and were trained to classify them into two labeled categories based on two visual features. Participants then gave similarity ratings for pairs of stimuli and their responses were compared to those of control participants who did not learn the categories. Results indicated significant compression, whereby objects classified together were judged to be more similar by learning than control participants, thus supporting the validity of using Second Life as a laboratory for studying human cognition. A second study used Second Life to test the novel hypothesis that effects of learning on perceived similarity do not depend on the presence of verbal labels for categories. We presented the same stimuli but participants classified them by selecting between two complex visual patterns designed to be extremely difficult to label. While learning was more challenging in this condition , those who did learn without labels showed a compression effect identical to that found in the first study using verbal labels. Together these studies establish that at least some forms of human learning in Second Life parallel learning in the actual world and thus open the door to future studies that will make greater use of the enriched variety of objects and interactions possible in simulated environments

  17. Category learning in the color-word contingency learning paradigm.

    Science.gov (United States)

    Schmidt, James R; Augustinova, Maria; De Houwer, Jan

    2018-04-01

    In the typical color-word contingency learning paradigm, participants respond to the print color of words where each word is presented most often in one color. Learning is indicated by faster and more accurate responses when a word is presented in its usual color, relative to another color. To eliminate the possibility that this effect is driven exclusively by the familiarity of item-specific word-color pairings, we examine whether contingency learning effects can be observed also when colors are related to categories of words rather than to individual words. To this end, the reported experiments used three categories of words (animals, verbs, and professions) that were each predictive of one color. Importantly, each individual word was presented only once, thus eliminating individual color-word contingencies. Nevertheless, for the first time, a category-based contingency effect was observed, with faster and more accurate responses when a category item was presented in the color in which most of the other items of that category were presented. This finding helps to constrain episodic learning models and sets the stage for new research on category-based contingency learning.

  18. The Role of Feedback Contingency in Perceptual Category Learning

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    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

  19. Mere exposure alters category learning of novel objects

    Directory of Open Access Journals (Sweden)

    Jonathan R Folstein

    2010-08-01

    Full Text Available We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning.

  20. Mere exposure alters category learning of novel objects.

    Science.gov (United States)

    Folstein, Jonathan R; Gauthier, Isabel; Palmeri, Thomas J

    2010-01-01

    We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning.

  1. Classification versus inference learning contrasted with real-world categories.

    Science.gov (United States)

    Jones, Erin L; Ross, Brian H

    2011-07-01

    Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories--what each category is like--while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.

  2. The impact of category structure and training methodology on learning and generalizing within-category representations.

    Science.gov (United States)

    Ell, Shawn W; Smith, David B; Peralta, Gabriela; Hélie, Sébastien

    2017-08-01

    When interacting with categories, representations focused on within-category relationships are often learned, but the conditions promoting within-category representations and their generalizability are unclear. We report the results of three experiments investigating the impact of category structure and training methodology on the learning and generalization of within-category representations (i.e., correlational structure). Participants were trained on either rule-based or information-integration structures using classification (Is the stimulus a member of Category A or Category B?), concept (e.g., Is the stimulus a member of Category A, Yes or No?), or inference (infer the missing component of the stimulus from a given category) and then tested on either an inference task (Experiments 1 and 2) or a classification task (Experiment 3). For the information-integration structure, within-category representations were consistently learned, could be generalized to novel stimuli, and could be generalized to support inference at test. For the rule-based structure, extended inference training resulted in generalization to novel stimuli (Experiment 2) and inference training resulted in generalization to classification (Experiment 3). These data help to clarify the conditions under which within-category representations can be learned. Moreover, these results make an important contribution in highlighting the impact of category structure and training methodology on the generalization of categorical knowledge.

  3. The transfer of category knowledge by macaques (Macaca mulatta) and humans (Homo sapiens).

    Science.gov (United States)

    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).

  4. Procedural-Based Category Learning in Patients with Parkinson's Disease: Impact of Category Number and Category Continuity

    Directory of Open Access Journals (Sweden)

    J. Vincent eFiloteo

    2014-02-01

    Full Text Available Previously we found that Parkinson's disease (PD patients are impaired in procedural-based category learning when category membership is defined by a nonlinear relationship between stimulus dimensions, but these same patients are normal when the rule is defined by a linear relationship (Filoteo et al., 2005; Maddox & Filoteo, 2001. We suggested that PD patients' impairment was due to a deficit in recruiting ‘striatal units' to represent complex nonlinear rules. In the present study, we further examined the nature of PD patients' procedural-based deficit in two experiments designed to examine the impact of (1 the number of categories, and (2 category discontinuity on learning. Results indicated that PD patients were impaired only under discontinuous category conditions but were normal when the number of categories was increased from two to four. The lack of impairment in the four-category condition suggests normal integrity of striatal medium spiny cells involved in procedural-based category learning. In contrast, and consistent with our previous observation of a nonlinear deficit, the finding that PD patients were impaired in the discontinuous condition suggests that these patients are impaired when they have to associate perceptually distinct exemplars with the same category. Theoretically, this deficit might be related to dysfunctional communication among medium spiny neurons within the striatum, particularly given that these are cholinergic neurons and a cholinergic deficiency could underlie some of PD patients’ cognitive impairment.

  5. Chromatic Perceptual Learning but No Category Effects without Linguistic Input.

    Science.gov (United States)

    Grandison, Alexandra; Sowden, Paul T; Drivonikou, Vicky G; Notman, Leslie A; Alexander, Iona; Davies, Ian R L

    2016-01-01

    Perceptual learning involves an improvement in perceptual judgment with practice, which is often specific to stimulus or task factors. Perceptual learning has been shown on a range of visual tasks but very little research has explored chromatic perceptual learning. Here, we use two low level perceptual threshold tasks and a supra-threshold target detection task to assess chromatic perceptual learning and category effects. Experiment 1 investigates whether chromatic thresholds reduce as a result of training and at what level of analysis learning effects occur. Experiment 2 explores the effect of category training on chromatic thresholds, whether training of this nature is category specific and whether it can induce categorical responding. Experiment 3 investigates the effect of category training on a higher level, lateralized target detection task, previously found to be sensitive to category effects. The findings indicate that performance on a perceptual threshold task improves following training but improvements do not transfer across retinal location or hue. Therefore, chromatic perceptual learning is category specific and can occur at relatively early stages of visual analysis. Additionally, category training does not induce category effects on a low level perceptual threshold task, as indicated by comparable discrimination thresholds at the newly learned hue boundary and adjacent test points. However, category training does induce emerging category effects on a supra-threshold target detection task. Whilst chromatic perceptual learning is possible, learnt category effects appear to be a product of left hemisphere processing, and may require the input of higher level linguistic coding processes in order to manifest.

  6. Can Semi-Supervised Learning Explain Incorrect Beliefs about Categories?

    Science.gov (United States)

    Kalish, Charles W.; Rogers, Timothy T.; Lang, Jonathan; Zhu, Xiaojin

    2011-01-01

    Three experiments with 88 college-aged participants explored how unlabeled experiences--learning episodes in which people encounter objects without information about their category membership--influence beliefs about category structure. Participants performed a simple one-dimensional categorization task in a brief supervised learning phase, then…

  7. Error Discounting in Probabilistic Category Learning

    Science.gov (United States)

    Craig, Stewart; Lewandowsky, Stephan; Little, Daniel R.

    2011-01-01

    The assumption in some current theories of probabilistic categorization is that people gradually attenuate their learning in response to unavoidable error. However, existing evidence for this error discounting is sparse and open to alternative interpretations. We report 2 probabilistic-categorization experiments in which we investigated error…

  8. Incidental Learning of Sound Categories is Impaired in Developmental Dyslexia

    Science.gov (United States)

    Gabay, Yafit; Holt, Lori L.

    2015-01-01

    Developmental dyslexia is commonly thought to arise from specific phonological impairments. However, recent evidence is consistent with the possibility that phonological impairments arise as symptoms of an underlying dysfunction of procedural learning. The nature of the link between impaired procedural learning and phonological dysfunction is unresolved. Motivated by the observation that speech processing involves the acquisition of procedural category knowledge, the present study investigates the possibility that procedural learning impairment may affect phonological processing by interfering with the typical course of phonetic category learning. The present study tests this hypothesis while controlling for linguistic experience and possible speech-specific deficits by comparing auditory category learning across artificial, nonlinguistic sounds among dyslexic adults and matched controls in a specialized first-person shooter videogame that has been shown to engage procedural learning. Nonspeech auditory category learning was assessed online via within-game measures and also with a post-training task involving overt categorization of familiar and novel sound exemplars. Each measure reveals that dyslexic participants do not acquire procedural category knowledge as effectively as age- and cognitive-ability matched controls. This difference cannot be explained by differences in perceptual acuity for the sounds. Moreover, poor nonspeech category learning is associated with slower phonological processing. Whereas phonological processing impairments have been emphasized as the cause of dyslexia, the current results suggest that impaired auditory category learning, general in nature and not specific to speech signals, could contribute to phonological deficits in dyslexia with subsequent negative effects on language acquisition and reading. Implications for the neuro-cognitive mechanisms of developmental dyslexia are discussed. PMID:26409017

  9. Incidental learning of sound categories is impaired in developmental dyslexia.

    Science.gov (United States)

    Gabay, Yafit; Holt, Lori L

    2015-12-01

    Developmental dyslexia is commonly thought to arise from specific phonological impairments. However, recent evidence is consistent with the possibility that phonological impairments arise as symptoms of an underlying dysfunction of procedural learning. The nature of the link between impaired procedural learning and phonological dysfunction is unresolved. Motivated by the observation that speech processing involves the acquisition of procedural category knowledge, the present study investigates the possibility that procedural learning impairment may affect phonological processing by interfering with the typical course of phonetic category learning. The present study tests this hypothesis while controlling for linguistic experience and possible speech-specific deficits by comparing auditory category learning across artificial, nonlinguistic sounds among dyslexic adults and matched controls in a specialized first-person shooter videogame that has been shown to engage procedural learning. Nonspeech auditory category learning was assessed online via within-game measures and also with a post-training task involving overt categorization of familiar and novel sound exemplars. Each measure reveals that dyslexic participants do not acquire procedural category knowledge as effectively as age- and cognitive-ability matched controls. This difference cannot be explained by differences in perceptual acuity for the sounds. Moreover, poor nonspeech category learning is associated with slower phonological processing. Whereas phonological processing impairments have been emphasized as the cause of dyslexia, the current results suggest that impaired auditory category learning, general in nature and not specific to speech signals, could contribute to phonological deficits in dyslexia with subsequent negative effects on language acquisition and reading. Implications for the neuro-cognitive mechanisms of developmental dyslexia are discussed. Copyright © 2015 Elsevier Ltd. All rights

  10. The helpfulness of category labels in semi-supervised learning depends on category structure.

    Science.gov (United States)

    Vong, Wai Keen; Navarro, Daniel J; Perfors, Amy

    2016-02-01

    The study of semi-supervised category learning has generally focused on how additional unlabeled information with given labeled information might benefit category learning. The literature is also somewhat contradictory, sometimes appearing to show a benefit to unlabeled information and sometimes not. In this paper, we frame the problem differently, focusing on when labels might be helpful to a learner who has access to lots of unlabeled information. Using an unconstrained free-sorting categorization experiment, we show that labels are useful to participants only when the category structure is ambiguous and that people's responses are driven by the specific set of labels they see. We present an extension of Anderson's Rational Model of Categorization that captures this effect.

  11. Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

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    Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

    2004-01-01

    Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

  12. Perceptual category learning and visual processing: An exercise in computational cognitive neuroscience.

    Science.gov (United States)

    Cantwell, George; Riesenhuber, Maximilian; Roeder, Jessica L; Ashby, F Gregory

    2017-05-01

    The field of computational cognitive neuroscience (CCN) builds and tests neurobiologically detailed computational models that account for both behavioral and neuroscience data. This article leverages a key advantage of CCN-namely, that it should be possible to interface different CCN models in a plug-and-play fashion-to produce a new and biologically detailed model of perceptual category learning. The new model was created from two existing CCN models: the HMAX model of visual object processing and the COVIS model of category learning. Using bitmap images as inputs and by adjusting only a couple of learning-rate parameters, the new HMAX/COVIS model provides impressively good fits to human category-learning data from two qualitatively different experiments that used different types of category structures and different types of visual stimuli. Overall, the model provides a comprehensive neural and behavioral account of basal ganglia-mediated learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Toward A Dual-Learning Systems Model of Speech Category Learning

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    Bharath eChandrasekaran

    2014-07-01

    Full Text Available More than two decades of work in vision posits the existence of dual-learning systems of category learning. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion, while the reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-learning systems models hypothesize that in learning natural categories, learners initially use the reflective system and, with practice, transfer control to the reflexive system. The role of reflective and reflexive systems in auditory category learning and more specifically in speech category learning has not been systematically examined. In this article we describe a neurobiologically-constrained dual-learning systems theoretical framework that is currently being developed in speech category learning and review recent applications of this framework. Using behavioral and computational modeling approaches, we provide evidence that speech category learning is predominantly mediated by the reflexive learning system. In one application, we explore the effects of normal aging on non-speech and speech category learning. We find an age related deficit in reflective-optimal but not reflexive-optimal auditory category learning. Prominently, we find a large age-related deficit in speech learning. The computational modeling suggests that older adults are less likely to transition from simple, reflective, uni-dimensional rules to more complex, reflexive, multi-dimensional rules. In a second application we summarize a recent study examining auditory category learning in individuals with elevated depressive symptoms. We find a deficit in reflective-optimal and an enhancement in reflexive-optimal auditory category learning. Interestingly, individuals with elevated depressive symptoms also show an advantage in learning speech categories. We end with a brief summary and description of a number of future directions.

  14. Cross-Situational Learning with Bayesian Generative Models for Multimodal Category and Word Learning in Robots

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    Akira Taniguchi

    2017-12-01

    Full Text Available In this paper, we propose a Bayesian generative model that can form multiple categories based on each sensory-channel and can associate words with any of the four sensory-channels (action, position, object, and color. This paper focuses on cross-situational learning using the co-occurrence between words and information of sensory-channels in complex situations rather than conventional situations of cross-situational learning. We conducted a learning scenario using a simulator and a real humanoid iCub robot. In the scenario, a human tutor provided a sentence that describes an object of visual attention and an accompanying action to the robot. The scenario was set as follows: the number of words per sensory-channel was three or four, and the number of trials for learning was 20 and 40 for the simulator and 25 and 40 for the real robot. The experimental results showed that the proposed method was able to estimate the multiple categorizations and to learn the relationships between multiple sensory-channels and words accurately. In addition, we conducted an action generation task and an action description task based on word meanings learned in the cross-situational learning scenario. The experimental results showed that the robot could successfully use the word meanings learned by using the proposed method.

  15. Concurrent Dynamics of Category Learning and Metacognitive Judgments

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    Valnea Žauhar

    2016-09-01

    Full Text Available In two experiments, we examined the correspondence between the dynamics of metacognitive judgments and classification accuracy when participants were asked to learn category structures of different levels of complexity, i.e., to learn tasks of types I, II and III according to Shepard, Hovland, and Jenkins (1961. The stimuli were simple geometrical figures varying in the following three dimensions: color, shape, and size. In Experiment 1, we found moderate positive correlations between confidence and accuracy in task type II and weaker correlation in task type I and III. Moreover, the trend analysis in the backward learning curves revealed that there is a non-linear trend in accuracy for all three task types, but the same trend was observed in confidence for the task type I and II but not for task type III. In Experiment 2, we found that the feeling-of-warmth judgments (FOWs showed moderate positive correlation with accuracy in all task types. Trend analysis revealed a similar non-linear component in accuracy and metacognitive judgments in task type II and III but not in task type I. Our results suggest that FOWs are a more sensitive measure of the progress of learning than confidence because FOWs capture global knowledge about the category structure, while confidence judgments are given at the level of an individual exemplar.

  16. A deep learning method for classifying mammographic breast density categories.

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    Mohamed, Aly A; Berg, Wendie A; Peng, Hong; Luo, Yahong; Jankowitz, Rachel C; Wu, Shandong

    2018-01-01

    Mammographic breast density is an established risk marker for breast cancer and is visually assessed by radiologists in routine mammogram image reading, using four qualitative Breast Imaging and Reporting Data System (BI-RADS) breast density categories. It is particularly difficult for radiologists to consistently distinguish the two most common and most variably assigned BI-RADS categories, i.e., "scattered density" and "heterogeneously dense". The aim of this work was to investigate a deep learning-based breast density classifier to consistently distinguish these two categories, aiming at providing a potential computerized tool to assist radiologists in assigning a BI-RADS category in current clinical workflow. In this study, we constructed a convolutional neural network (CNN)-based model coupled with a large (i.e., 22,000 images) digital mammogram imaging dataset to evaluate the classification performance between the two aforementioned breast density categories. All images were collected from a cohort of 1,427 women who underwent standard digital mammography screening from 2005 to 2016 at our institution. The truths of the density categories were based on standard clinical assessment made by board-certified breast imaging radiologists. Effects of direct training from scratch solely using digital mammogram images and transfer learning of a pretrained model on a large nonmedical imaging dataset were evaluated for the specific task of breast density classification. In order to measure the classification performance, the CNN classifier was also tested on a refined version of the mammogram image dataset by removing some potentially inaccurately labeled images. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to measure the accuracy of the classifier. The AUC was 0.9421 when the CNN-model was trained from scratch on our own mammogram images, and the accuracy increased gradually along with an increased size of training samples

  17. Comparing the effects of positive and negative feedback in information-integration category learning.

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    Freedberg, Michael; Glass, Brian; Filoteo, J Vincent; Hazeltine, Eliot; Maddox, W Todd

    2017-01-01

    Categorical learning is dependent on feedback. Here, we compare how positive and negative feedback affect information-integration (II) category learning. Ashby and O'Brien (2007) demonstrated that both positive and negative feedback are required to solve II category problems when feedback was not guaranteed on each trial, and reported no differences between positive-only and negative-only feedback in terms of their effectiveness. We followed up on these findings and conducted 3 experiments in which participants completed 2,400 II categorization trials across three days under 1 of 3 conditions: positive feedback only (PFB), negative feedback only (NFB), or both types of feedback (CP; control partial). An adaptive algorithm controlled the amount of feedback given to each group so that feedback was nearly equated. Using different feedback control procedures, Experiments 1 and 2 demonstrated that participants in the NFB and CP group were able to engage II learning strategies, whereas the PFB group was not. Additionally, the NFB group was able to achieve significantly higher accuracy than the PFB group by Day 3. Experiment 3 revealed that these differences remained even when we equated the information received on feedback trials. Thus, negative feedback appears significantly more effective for learning II category structures. This suggests that the human implicit learning system may be capable of learning in the absence of positive feedback.

  18. Dissociation of Category-Learning Systems via Brain Potentials

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    Robert G Morrison

    2015-07-01

    Full Text Available Behavioral, neuropsychological, and neuroimaging evidence has suggested that categories can often be learned via either an explicit rule-based mechanism critically dependent on medial temporal and prefrontal brain regions, or via an implicit information-integration mechanism relying on the basal ganglia. In this study, participants viewed sine-wave gratings (i.e., Gabor patches that varied on two dimensions and learned to categorize them via trial-by-trial feedback. Two different stimulus distributions were used; one was intended to encourage an explicit rule-based process and the other an implicit information-integration process. We monitored brain activity with scalp electroencephalography (EEG while each participant (1 passively observed stimuli represented of both distributions, (2 categorized stimuli from one distribution, and, one week later, (3 categorized stimuli from the other distribution. Categorization accuracy was similar for the two distributions. Subtractions of Event-Related Potentials (ERPs for correct and incorrect trials were used to identify neural differences in rule-based and information-integration categorization processes. We identified an occipital brain potential that was differentially modulated by categorization condition accuracy at an early latency (150 - 250 ms, likely reflecting the degree of holistic processing. A stimulus-locked late positive complex associated with explicit memory updating was modulated by accuracy in the rule-based, but not the information-integration task. Likewise, a feedback-locked P300 ERP associated with expectancy was correlated with performance only in the rule-based, but not the information-integration condition. These results provide additional evidence for distinct brain mechanisms supporting rule-based versus implicit information-integration category learning and use.

  19. Categorial compositionality: a category theory explanation for the systematicity of human cognition.

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    Steven Phillips

    Full Text Available Classical and Connectionist theories of cognitive architecture seek to explain systematicity (i.e., the property of human cognition whereby cognitive capacity comes in groups of related behaviours as a consequence of syntactically and functionally compositional representations, respectively. However, both theories depend on ad hoc assumptions to exclude specific instances of these forms of compositionality (e.g. grammars, networks that do not account for systematicity. By analogy with the Ptolemaic (i.e. geocentric theory of planetary motion, although either theory can be made to be consistent with the data, both nonetheless fail to fully explain it. Category theory, a branch of mathematics, provides an alternative explanation based on the formal concept of adjunction, which relates a pair of structure-preserving maps, called functors. A functor generalizes the notion of a map between representational states to include a map between state transformations (or processes. In a formal sense, systematicity is a necessary consequence of a higher-order theory of cognitive architecture, in contrast to the first-order theories derived from Classicism or Connectionism. Category theory offers a re-conceptualization for cognitive science, analogous to the one that Copernicus provided for astronomy, where representational states are no longer the center of the cognitive universe--replaced by the relationships between the maps that transform them.

  20. Categorial compositionality: a category theory explanation for the systematicity of human cognition.

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    Phillips, Steven; Wilson, William H

    2010-07-22

    Classical and Connectionist theories of cognitive architecture seek to explain systematicity (i.e., the property of human cognition whereby cognitive capacity comes in groups of related behaviours) as a consequence of syntactically and functionally compositional representations, respectively. However, both theories depend on ad hoc assumptions to exclude specific instances of these forms of compositionality (e.g. grammars, networks) that do not account for systematicity. By analogy with the Ptolemaic (i.e. geocentric) theory of planetary motion, although either theory can be made to be consistent with the data, both nonetheless fail to fully explain it. Category theory, a branch of mathematics, provides an alternative explanation based on the formal concept of adjunction, which relates a pair of structure-preserving maps, called functors. A functor generalizes the notion of a map between representational states to include a map between state transformations (or processes). In a formal sense, systematicity is a necessary consequence of a higher-order theory of cognitive architecture, in contrast to the first-order theories derived from Classicism or Connectionism. Category theory offers a re-conceptualization for cognitive science, analogous to the one that Copernicus provided for astronomy, where representational states are no longer the center of the cognitive universe--replaced by the relationships between the maps that transform them.

  1. Human Machine Learning Symbiosis

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    Walsh, Kenneth R.; Hoque, Md Tamjidul; Williams, Kim H.

    2017-01-01

    Human Machine Learning Symbiosis is a cooperative system where both the human learner and the machine learner learn from each other to create an effective and efficient learning environment adapted to the needs of the human learner. Such a system can be used in online learning modules so that the modules adapt to each learner's learning state both…

  2. Two Pathways to Stimulus Encoding in Category Learning?

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    Davis, Tyler; Love, Bradley C.; Maddox, W. Todd

    2008-01-01

    Category learning theorists tacitly assume that stimuli are encoded by a single pathway. Motivated by theories of object recognition, we evaluate a dual-pathway account of stimulus encoding. The part-based pathway establishes mappings between sensory input and symbols that encode discrete stimulus features, whereas the image-based pathway applies holistic templates to sensory input. Our experiments use rule-plus-exception structures in which one exception item in each category violates a salient regularity and must be distinguished from other items. In Experiment 1, we find that discrete representations are crucial for recognition of exceptions following brief training. Experiments 2 and 3 involve multi-session training regimens designed to encourage either part or image-based encoding. We find that both pathways are able to support exception encoding, but have unique characteristics. We speculate that one advantage of the part-based pathway is the ability to generalize across domains, whereas the image-based pathway provides faster and more effortless recognition. PMID:19460948

  3. Human cloning: category, dignity, and the role of bioethics.

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    Shuster, Evelyne

    2003-10-01

    Human cloning has been simultaneously a running joke for massive worldwide publicity of fringe groups like the Raelians, and the core issue of an international movement at the United Nations in support of a treaty to ban the use of cloning techniques to produce a child (so called reproductive cloning). Yet, even though debates on human cloning have greatly increased since the birth of Dolly, the clone sheep, in 1997, we continue to wonder whether cloning is after all any different from other methods of medically assisted reproduction, and what exactly makes cloning an 'affront to the dignity of humans.' Categories we adopt matter mightily as they inform but can also misinform and lead to mistaken and unproductive decisions. And thus bioethicists have a responsibility to ensure that the proper categories are used in the cloning debates and denounce those who try to win the ethical debate through well-crafted labels rather than well-reasoned argumentations. But it is as important for bioethicists to take a position on broad issues such as human cloning and species altering interventions. One 'natural question' would be, for example, should there be an international treaty to ban human reproductive cloning?

  4. More than words: Adults learn probabilities over categories and relationships between them.

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    Hudson Kam, Carla L

    2009-04-01

    This study examines whether human learners can acquire statistics over abstract categories and their relationships to each other. Adult learners were exposed to miniature artificial languages containing variation in the ordering of the Subject, Object, and Verb constituents. Different orders (e.g. SOV, VSO) occurred in the input with different frequencies, but the occurrence of one order versus another was not predictable. Importantly, the language was constructed such that participants could only match the overall input probabilities if they were tracking statistics over abstract categories, not over individual words. At test, participants reproduced the probabilities present in the input with a high degree of accuracy. Closer examination revealed that learner's were matching the probabilities associated with individual verbs rather than the category as a whole. However, individual nouns had no impact on word orders produced. Thus, participants learned the probabilities of a particular ordering of the abstract grammatical categories Subject and Object associated with each verb. Results suggest that statistical learning mechanisms are capable of tracking relationships between abstract linguistic categories in addition to individual items.

  5. Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems.

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    Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

    2016-01-01

    It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.

  6. Learning about the internal structure of categories through classification and feature inference.

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    Jee, Benjamin D; Wiley, Jennifer

    2014-01-01

    Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

  7. The cost of selective attention in category learning: developmental differences between adults and infants.

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    Best, Catherine A; Yim, Hyungwook; Sloutsky, Vladimir M

    2013-10-01

    Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6-8months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. Copyright © 2013 Elsevier Inc. All rights reserved.

  8. The cost of selective attention in category learning: Developmental differences between adults and infants

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    Best, Catherine A.; Yim, Hyungwook; Sloutsky, Vladimir M.

    2013-01-01

    Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6–8 months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. PMID:23773914

  9. Relative risk of probabilistic category learning deficits in patients with schizophrenia and their siblings

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    Weickert, Thomas W.; Goldberg, Terry E.; Egan, Michael F.; Apud, Jose A.; Meeter, Martijn; Myers, Catherine E.; Gluck, Mark A; Weinberger, Daniel R.

    2010-01-01

    Background While patients with schizophrenia display an overall probabilistic category learning performance deficit, the extent to which this deficit occurs in unaffected siblings of patients with schizophrenia is unknown. There are also discrepant findings regarding probabilistic category learning acquisition rate and performance in patients with schizophrenia. Methods A probabilistic category learning test was administered to 108 patients with schizophrenia, 82 unaffected siblings, and 121 healthy participants. Results Patients with schizophrenia displayed significant differences from their unaffected siblings and healthy participants with respect to probabilistic category learning acquisition rates. Although siblings on the whole failed to differ from healthy participants on strategy and quantitative indices of overall performance and learning acquisition, application of a revised learning criterion enabling classification into good and poor learners based on individual learning curves revealed significant differences between percentages of sibling and healthy poor learners: healthy (13.2%), siblings (34.1%), patients (48.1%), yielding a moderate relative risk. Conclusions These results clarify previous discrepant findings pertaining to probabilistic category learning acquisition rate in schizophrenia and provide the first evidence for the relative risk of probabilistic category learning abnormalities in unaffected siblings of patients with schizophrenia, supporting genetic underpinnings of probabilistic category learning deficits in schizophrenia. These findings also raise questions regarding the contribution of antipsychotic medication to the probabilistic category learning deficit in schizophrenia. The distinction between good and poor learning may be used to inform genetic studies designed to detect schizophrenia risk alleles. PMID:20172502

  10. When more is less: Feedback effects in perceptual category learning

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    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

  11. Consider the category: The effect of spacing depends on individual learning histories.

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    Slone, Lauren K; Sandhofer, Catherine M

    2017-07-01

    The spacing effect refers to increased retention following learning instances that are spaced out in time compared with massed together in time. By one account, the advantages of spaced learning should be independent of task particulars and previous learning experiences given that spacing effects have been demonstrated in a variety of tasks across the lifespan. However, by another account, spaced learning should be affected by previous learning because past learning affects the memory and attention processes that form the crux of the spacing effect. The current study investigated whether individuals' learning histories affect the role of spacing in category learning. We examined the effect of spacing on 24 2- to 3.5-year-old children's learning of categories organized by properties to which children's previous learning experiences have biased them to attend (i.e., shape) and properties to which children are less biased to attend (i.e., texture and color). Spaced presentations led to significantly better learning of shape categories, but not of texture or color categories, compared with massed presentations. In addition, generalized estimating equations analyses revealed positive relations between the size of children's "shape-side" productive vocabularies and their shape category learning and between the size of children's "against-the-system" productive vocabularies and their texture category learning. These results suggest that children's attention to and memory for novel object categories are strongly related to their individual word-learning histories. Moreover, children's learned attentional biases affected the types of categories for which spacing facilitated learning. These findings highlight the importance of considering how learners' previous experiences may influence future learning. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. The perceptual effects of learning object categories that predict perceptual goals

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    Van Gulick, Ana E.; Gauthier, Isabel

    2014-01-01

    In classic category learning studies, subjects typically learn to assign items to one of two categories, with no further distinction between how items on each side of the category boundary should be treated. In real life, however, we often learn categories that dictate further processing goals, for instance with objects in only one category requiring further individuation. Using methods from category learning and perceptual expertise, we studied the perceptual consequences of experience with objects in tasks that rely on attention to different dimensions in different parts of the space. In two experiments, subjects first learned to categorize complex objects from a single morphspace into two categories based on one morph dimension, and then learned to perform a different task, either naming or a local feature judgment, for each of the two categories. A same-different discrimination test before and after each training measured sensitivity to feature dimensions of the space. After initial categorization, sensitivity increased along the category-diagnostic dimension. After task association, sensitivity increased more for the category that was named, especially along the non-diagnostic dimension. The results demonstrate that local attentional weights, associated with individual exemplars as a function of task requirements, can have lasting effects on perceptual representations. PMID:24820671

  13. An Examination of Strategy Implementation during Abstract Nonlinguistic Category Learning in Aphasia

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    Vallila-Rohter, Sofia; Kiran, Swathi

    2015-01-01

    Purpose: Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Method: Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases…

  14. Heterogeneity in Perceptual Category Learning by High Functioning Children with Autism Spectrum Disorder

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    Eduardo eMercado

    2015-06-01

    Full Text Available Previous research suggests that high functioning children with Autism Spectrum Disorder (ASD sometimes have problems learning categories, but often appear to perform normally in categorization tasks. The deficits that individuals with ASD show when learning categories have been attributed to executive dysfunction, general deficits in implicit learning, atypical cognitive strategies, or abnormal perceptual biases and abilities. Several of these psychological explanations for category learning deficits have been associated with neural abnormalities such as cortical underconnectivity. The present study evaluated how well existing neurally-based theories account for atypical perceptual category learning shown by high functioning children with ASD across multiple category learning tasks involving novel, abstract shapes. Consistent with earlier results, children’s performances revealed two distinct patterns of learning and generalization associated with ASD: one was indistinguishable from performance in typically developing children; the other revealed dramatic impairments. These two patterns were evident regardless of training regimen or stimulus set. Surprisingly, some children with ASD showed both patterns. Simulations of perceptual category learning could account for the two observed patterns in terms of differences in neural plasticity. However, no current psychological or neural theory adequately explains why a child with ASD might show such large fluctuations in category learning ability across training conditions or stimulus sets.

  15. Heterogeneity in perceptual category learning by high functioning children with autism spectrum disorder.

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    Mercado, Eduardo; Church, Barbara A; Coutinho, Mariana V C; Dovgopoly, Alexander; Lopata, Christopher J; Toomey, Jennifer A; Thomeer, Marcus L

    2015-01-01

    Previous research suggests that high functioning (HF) children with autism spectrum disorder (ASD) sometimes have problems learning categories, but often appear to perform normally in categorization tasks. The deficits that individuals with ASD show when learning categories have been attributed to executive dysfunction, general deficits in implicit learning, atypical cognitive strategies, or abnormal perceptual biases and abilities. Several of these psychological explanations for category learning deficits have been associated with neural abnormalities such as cortical underconnectivity. The present study evaluated how well existing neurally based theories account for atypical perceptual category learning shown by HF children with ASD across multiple category learning tasks involving novel, abstract shapes. Consistent with earlier results, children's performances revealed two distinct patterns of learning and generalization associated with ASD: one was indistinguishable from performance in typically developing children; the other revealed dramatic impairments. These two patterns were evident regardless of training regimen or stimulus set. Surprisingly, some children with ASD showed both patterns. Simulations of perceptual category learning could account for the two observed patterns in terms of differences in neural plasticity. However, no current psychological or neural theory adequately explains why a child with ASD might show such large fluctuations in category learning ability across training conditions or stimulus sets.

  16. Adaptive learning in a compartmental model of visual cortex - how feedback enables stable category learning and refinement

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    Georg eLayher

    2014-12-01

    Full Text Available The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, but both belong to the category of felines. In other words, tigers and leopards are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in the computational neurosciences. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of (sub- category representations. We demonstrate the temporal evolution of such learning and show how the approach successully establishes category and subcategory

  17. The development of automaticity in short-term memory search: Item-response learning and category learning.

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    Cao, Rui; Nosofsky, Robert M; Shiffrin, Richard M

    2017-05-01

    In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across trials. In item-response learning, subjects learn long-term mappings between individual items and target versus foil responses. In category learning, subjects learn high-level codes corresponding to separate sets of items and learn to attach old versus new responses to these category codes. To distinguish between these 2 forms of learning, we tested subjects in categorized varied mapping (CV) conditions: There were 2 distinct categories of items, but the assignment of categories to target versus foil responses varied across trials. In cases involving arbitrary categories, CV performance closely resembled standard varied-mapping performance without categories and departed dramatically from CM performance, supporting the item-response-learning hypothesis. In cases involving prelearned categories, CV performance resembled CM performance, as long as there was sufficient practice or steps taken to reduce trial-to-trial category-switching costs. This pattern of results supports the category-coding hypothesis for sufficiently well-learned categories. Thus, item-response learning occurs rapidly and is used early in CM training; category learning is much slower but is eventually adopted and is used to increase the efficiency of search beyond that available from item-response learning. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  18. Study preferences for exemplar variability in self-regulated category learning.

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    Wahlheim, Christopher N; DeSoto, K Andrew

    2017-02-01

    Increasing exemplar variability during category learning can enhance classification of novel exemplars from studied categories. Four experiments examined whether participants preferred variability when making study choices with the goal of later classifying novel exemplars. In Experiments 1-3, participants were familiarised with exemplars of birds from multiple categories prior to making category-level assessments of learning and subsequent choices about whether to receive more variability or repetitions of exemplars during study. After study, participants classified novel exemplars from studied categories. The majority of participants showed a consistent preference for variability in their study, but choices were not related to category-level assessments of learning. Experiment 4 provided evidence that study preferences were based primarily on theoretical beliefs in that most participants indicated a preference for variability on questionnaires that did not include prior experience with exemplars. Potential directions for theoretical development and applications to education are discussed.

  19. INCREASES IN FUNCTIONAL CONNECTIVITY BETWEEN PREFRONTAL CORTEX AND STRIATUM DURING CATEGORY LEARNING

    Science.gov (United States)

    Antzoulatos, Evan G.; Miller, Earl K.

    2014-01-01

    SUMMARY Functional connectivity between the prefrontal cortex (PFC) and striatum (STR) is thought critical for cognition, and has been linked to conditions like autism and schizophrenia. We recorded from multiple electrodes in PFC and STR while monkeys acquired new categories. Category learning was accompanied by an increase in beta-band synchronization of LFPs between, but not within, the PFC and STR. After learning, different pairs of PFC-STR electrodes showed stronger synchrony for one or the other category, suggesting category-specific functional circuits. This category-specific synchrony was also seen between PFC spikes and STR LFPs, but not the reverse, reflecting the direct monosynaptic connections from the PFC to STR. However, causal connectivity analyses suggested that the polysynaptic connections from STR to the PFC exerted a stronger overall influence. This supports models positing that the basal ganglia “train” the PFC. Category learning may depend on the formation of functional circuits between the PFC and STR. PMID:24930701

  20. Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization.

    Science.gov (United States)

    Gao, Shenghua; Tsang, Ivor Wai-Hung; Ma, Yi

    2014-02-01

    This paper targets fine-grained image categorization by learning a category-specific dictionary for each category and a shared dictionary for all the categories. Such category-specific dictionaries encode subtle visual differences among different categories, while the shared dictionary encodes common visual patterns among all the categories. To this end, we impose incoherence constraints among the different dictionaries in the objective of feature coding. In addition, to make the learnt dictionary stable, we also impose the constraint that each dictionary should be self-incoherent. Our proposed dictionary learning formulation not only applies to fine-grained classification, but also improves conventional basic-level object categorization and other tasks such as event recognition. Experimental results on five data sets show that our method can outperform the state-of-the-art fine-grained image categorization frameworks as well as sparse coding based dictionary learning frameworks. All these results demonstrate the effectiveness of our method.

  1. Differences between Neural Activity in Prefrontal Cortex and Striatum during Learning of Novel Abstract Categories

    OpenAIRE

    Antzoulatos, Evan G.; Miller, Earl K.

    2011-01-01

    Learning to classify diverse experiences into meaningful groups, like categories, is fundamental to normal cognition. To understand its neural basis, we simultaneously recorded from multiple electrodes in the lateral prefrontal cortex and dorsal striatum, two interconnected brain structures critical for learning. Each day, monkeys learned to associate novel, abstract dot-based categories with a right vs. left saccade. Early on, when they could acquire specific stimulus-response associations, ...

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

    Science.gov (United States)

    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.

  3. Adaptive learning in a compartmental model of visual cortex—how feedback enables stable category learning and refinement

    Science.gov (United States)

    Layher, Georg; Schrodt, Fabian; Butz, Martin V.; Neumann, Heiko

    2014-01-01

    The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, both of which are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in computational neuroscience. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of additional (sub-) category representations. We demonstrate the temporal evolution of such learning and show how the proposed combination of an associative memory with a modulatory feedback integration successfully establishes category and subcategory representations

  4. Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

    OpenAIRE

    Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

    2016-01-01

    It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed...

  5. More Is Generally Better: Higher Working Memory Capacity Does Not Impair Perceptual Category Learning

    Science.gov (United States)

    Kalish, Michael L.; Newell, Ben R.; Dunn, John C.

    2017-01-01

    It is sometimes supposed that category learning involves competing explicit and procedural systems, with only the former reliant on working memory capacity (WMC). In 2 experiments participants were trained for 3 blocks on both filtering (often said to be learned explicitly) and condensation (often said to be learned procedurally) category…

  6. The contribution of temporary storage and executive processes to category learning.

    Science.gov (United States)

    Wang, Tengfei; Ren, Xuezhu; Schweizer, Karl

    2015-09-01

    Three distinctly different working memory processes, temporary storage, mental shifting and inhibition, were proposed to account for individual differences in category learning. A sample of 213 participants completed a classic category learning task and two working memory tasks that were experimentally manipulated for tapping specific working memory processes. Fixed-links models were used to decompose data of the category learning task into two independent components representing basic performance and improvement in performance in category learning. Processes of working memory were also represented by fixed-links models. In a next step the three working memory processes were linked to components of category learning. Results from modeling analyses indicated that temporary storage had a significant effect on basic performance and shifting had a moderate effect on improvement in performance. In contrast, inhibition showed no effect on any component of the category learning task. These results suggest that temporary storage and the shifting process play different roles in the course of acquiring new categories. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Can machine learning explain human learning?

    NARCIS (Netherlands)

    Vahdat, M.; Oneto, L.; Anguita, D.; Funk, M.; Rauterberg, G.W.M.

    2016-01-01

    Learning Analytics (LA) has a major interest in exploring and understanding the learning process of humans and, for this purpose, benefits from both Cognitive Science, which studies how humans learn, and Machine Learning, which studies how algorithms learn from data. Usually, Machine Learning is

  8. Categorial Compositionality: A Category Theory Explanation for the Systematicity of Human Cognition

    OpenAIRE

    Phillips, Steven; Wilson, William H.

    2010-01-01

    Classical and Connectionist theories of cognitive architecture seek to explain systematicity (i.e., the property of human cognition whereby cognitive capacity comes in groups of related behaviours) as a consequence of syntactically and functionally compositional representations, respectively. However, both theories depend on ad hoc assumptions to exclude specific instances of these forms of compositionality (e.g. grammars, networks) that do not account for systematicity. By analogy with the P...

  9. Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers.

    Science.gov (United States)

    Chen, Chi-Hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

    2017-08-01

    Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership than English, were able to learn words and form object categories when trained with the same type of structures. The results indicate that both groups of learners successfully extracted multiple levels of co-occurrence and used them to learn words and object categories simultaneously. However, marked individual differences in performance were also found, suggesting possible interference and competition in processing the two concurrent streams of regularities. Copyright © 2016 Cognitive Science Society, Inc.

  10. Incremental Learning of Perceptual Categories for Open-Domain Sketch Recognition

    National Research Council Canada - National Science Library

    Lovett, Andrew; Dehghani, Morteza; Forbus, Kenneth

    2007-01-01

    .... This paper describes an incremental learning technique for opendomain recognition. Our system builds generalizations for categories of objects based upon previous sketches of those objects and uses those generalizations to classify new sketches...

  11. On Learning Natural-Science Categories That Violate the Family-Resemblance Principle.

    Science.gov (United States)

    Nosofsky, Robert M; Sanders, Craig A; Gerdom, Alex; Douglas, Bruce J; McDaniel, Mark A

    2017-01-01

    The general view in psychological science is that natural categories obey a coherent, family-resemblance principle. In this investigation, we documented an example of an important exception to this principle: Results of a multidimensional-scaling study of igneous, metamorphic, and sedimentary rocks (Experiment 1) suggested that the structure of these categories is disorganized and dispersed. This finding motivated us to explore what might be the optimal procedures for teaching dispersed categories, a goal that is likely critical to science education in general. Subjects in Experiment 2 learned to classify pictures of rocks into compact or dispersed high-level categories. One group learned the categories through focused high-level training, whereas a second group was required to simultaneously learn classifications at a subtype level. Although high-level training led to enhanced performance when the categories were compact, subtype training was better when the categories were dispersed. We provide an interpretation of the results in terms of an exemplar-memory model of category learning.

  12. Bifurcation and category learning in network models of oscillating cortex

    Science.gov (United States)

    Baird, Bill

    1990-06-01

    A genetic model of oscillating cortex, which assumes “minimal” coupling justified by known anatomy, is shown to function as an associative memory, using previously developed theory. The network has explicit excitatory neurons with local inhibitory interneuron feedback that forms a set of nonlinear oscillators coupled only by long-range excitatory connections. Using a local Hebb-like learning rule for primary and higher-order synapses at the ends of the long-range connections, the system learns to store the kinds of oscillation amplitude patterns observed in olfactory and visual cortex. In olfaction, these patterns “emerge” during respiration by a pattern forming phase transition which we characterize in the model as a multiple Hopf bifurcation. We argue that these bifurcations play an important role in the operation of real digital computers and neural networks, and we use bifurcation theory to derive learning rules which analytically guarantee CAM storage of continuous periodic sequences-capacity: N/2 Fourier components for an N-node network-no “spurious” attractors.

  13. Prediction of human protein function according to Gene Ontology categories

    DEFF Research Database (Denmark)

    Jensen, Lars Juhl; Gupta, Ramneek; Stærfeldt, Hans Henrik

    2003-01-01

    developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories-transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors...

  14. Distributional learning aids linguistic category formation in school-age children.

    Science.gov (United States)

    Hall, Jessica; Owen VAN Horne, Amanda; Farmer, Thomas

    2018-05-01

    The goal of this study was to determine if typically developing children could form grammatical categories from distributional information alone. Twenty-seven children aged six to nine listened to an artificial grammar which contained strategic gaps in its distribution. At test, we compared how children rated novel sentences that fit the grammar to sentences that were ungrammatical. Sentences could be distinguished only through the formation of categories of words with shared distributional properties. Children's ratings revealed that they could discriminate grammatical and ungrammatical sentences. These data lend support to the hypothesis that distributional learning is a potential mechanism for learning grammatical categories in a first language.

  15. Linguistic labels, dynamic visual features, and attention in infant category learning.

    Science.gov (United States)

    Deng, Wei Sophia; Sloutsky, Vladimir M

    2015-06-01

    How do words affect categorization? According to some accounts, even early in development words are category markers and are different from other features. According to other accounts, early in development words are part of the input and are akin to other features. The current study addressed this issue by examining the role of words and dynamic visual features in category learning in 8- to 12-month-old infants. Infants were familiarized with exemplars from one category in a label-defined or motion-defined condition and then tested with prototypes from the studied category and from a novel contrast category. Eye-tracking results indicated that infants exhibited better category learning in the motion-defined condition than in the label-defined condition, and their attention was more distributed among different features when there was a dynamic visual feature compared with the label-defined condition. These results provide little evidence for the idea that linguistic labels are category markers that facilitate category learning. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. The effect of category learning on attentional modulation of visual cortex.

    Science.gov (United States)

    Folstein, Jonathan R; Fuller, Kelly; Howard, Dorothy; DePatie, Thomas

    2017-09-01

    Learning about visual object categories causes changes in the way we perceive those objects. One likely mechanism by which this occurs is the application of attention to potentially relevant objects. Here we test the hypothesis that category membership influences the allocation of attention, allowing attention to be applied not only to object features, but to entire categories. Participants briefly learned to categorize a set of novel cartoon animals after which EEG was recorded while participants distinguished between a target and non-target category. A second identical EEG session was conducted after two sessions of categorization practice. The category structure and task design allowed parametric manipulation of number of target features while holding feature frequency and category membership constant. We found no evidence that category membership influenced attentional selection: a postero-lateral negative component, labeled the selection negativity/N250, increased over time and was sensitive to number of target features, not target categories. In contrast, the right hemisphere N170 was not sensitive to target features. The P300 appeared sensitive to category in the first session, but showed a graded sensitivity to number of target features in the second session, possibly suggesting a transition from rule-based to similarity based categorization. Copyright © 2017. Published by Elsevier Ltd.

  17. Attribute conjunctions and the part configuration advantage in object category learning.

    Science.gov (United States)

    Saiki, J; Hummel, J E

    1996-07-01

    Five experiments demonstrated that in object category learning people are particularly sensitive to conjunctions of part shapes and relative locations. Participants learned categories defined by a part's shape and color (part-color conjunctions) or by a part's shape and its location relative to another part (part-location conjunctions). The statistical properties of the categories were identical across these conditions, as were the salience of color and relative location. Participants were better at classifying objects defined by part-location conjunctions than objects defined by part-color conjunctions. Subsequent experiments revealed that this effect was not due to the specific color manipulation or the role of location per se. These results suggest that the shape bias in object categorization is at least partly due to sensitivity to part-location conjunctions and suggest a new processing constraint on category learning.

  18. Human Learning and Memory

    Science.gov (United States)

    Lieberman, David A.

    2012-01-01

    This innovative textbook is the first to integrate learning and memory, behaviour, and cognition. It focuses on fascinating human research in both memory and learning (while also bringing in important animal studies) and brings the reader up to date with the latest developments in the subject. Students are encouraged to think critically: key…

  19. Behavioral evidence for differences in social and non-social category learning

    Directory of Open Access Journals (Sweden)

    Lucile eGamond

    2012-08-01

    Full Text Available When meeting someone for the very first time one spontaneously categorizes the seen person on the basis of his/her appearance. Categorization is based on the association between some physical features and category labels that can be social (character trait… or non-social (tall, thin. Surprisingly little is known about how such associations are formed, particularly in the social domain. Here, we aimed at testing whether social and non-social category learning may be dissociated. We presented subjects with a large number of faces that had to be rated according to social or non-social labels, and induced an association between a facial feature (inter-eye distance and the category labels using two different procedures. In a first experiment, we used a feedback procedure to reinforce the association; behavioral measures revealed an association between the physical feature manipulated and abstract non-social categories, while no evidence for an association with social labels could be found. In a second experiment, we used passive exposure to the association between physical features and labels; we obtained behavioral evidence for learning of both social and non-social categories. These results support the view of the specificity of social category learning; they suggest that social categories are best acquired through unsupervised procedures that can be considered as a simplified proxy for group transmission.

  20. Emergence of category-level sensitivities in non-native speech sound learning

    Directory of Open Access Journals (Sweden)

    Emily eMyers

    2014-08-01

    Full Text Available Over the course of development, speech sounds that are contrastive in one’s native language tend to become perceived categorically: that is, listeners are unaware of variation within phonetic categories while showing excellent sensitivity to speech sounds that span linguistically meaningful phonetic category boundaries. The end stage of this developmental process is that the perceptual systems that handle acoustic-phonetic information show special tuning to native language contrasts, and as such, category-level information appears to be present at even fairly low levels of the neural processing stream. Research on adults acquiring non-native speech categories offers an avenue for investigating the interplay of category-level information and perceptual sensitivities to these sounds as speech categories emerge. In particular, one can observe the neural changes that unfold as listeners learn not only to perceive acoustic distinctions that mark non-native speech sound contrasts, but also to map these distinctions onto category-level representations. An emergent literature on the neural basis of novel and non-native speech sound learning offers new insight into this question. In this review, I will examine this literature in order to answer two key questions. First, where in the neural pathway does sensitivity to category-level phonetic information first emerge over the trajectory of speech sound learning? Second, how do frontal and temporal brain areas work in concert over the course of non-native speech sound learning? Finally, in the context of this literature I will describe a model of speech sound learning in which rapidly-adapting access to categorical information in the frontal lobes modulates the sensitivity of stable, slowly-adapting responses in the temporal lobes.

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

    Science.gov (United States)

    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.

  2. Large-scale weakly supervised object localization via latent category learning.

    Science.gov (United States)

    Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

    2015-04-01

    Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

  3. The Role of Age and Executive Function in Auditory Category Learning

    Science.gov (United States)

    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

  4. Compensatory Processing During Rule-Based Category Learning in Older Adults

    Science.gov (United States)

    Bharani, Krishna L.; Paller, Ken A.; Reber, Paul J.; Weintraub, Sandra; Yanar, Jorge; Morrison, Robert G.

    2016-01-01

    Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex. PMID:26422522

  5. A connectionist model of category learning by individuals with high-functioning autism spectrum disorder.

    Science.gov (United States)

    Dovgopoly, Alexander; Mercado, Eduardo

    2013-06-01

    Individuals with autism spectrum disorder (ASD) show atypical patterns of learning and generalization. We explored the possible impacts of autism-related neural abnormalities on perceptual category learning using a neural network model of visual cortical processing. When applied to experiments in which children or adults were trained to classify complex two-dimensional images, the model can account for atypical patterns of perceptual generalization. This is only possible, however, when individual differences in learning are taken into account. In particular, analyses performed with a self-organizing map suggested that individuals with high-functioning ASD show two distinct generalization patterns: one that is comparable to typical patterns, and a second in which there is almost no generalization. The model leads to novel predictions about how individuals will generalize when trained with simplified input sets and can explain why some researchers have failed to detect learning or generalization deficits in prior studies of category learning by individuals with autism. On the basis of these simulations, we propose that deficits in basic neural plasticity mechanisms may be sufficient to account for the atypical patterns of perceptual category learning and generalization associated with autism, but they do not account for why only a subset of individuals with autism would show such deficits. If variations in performance across subgroups reflect heterogeneous neural abnormalities, then future behavioral and neuroimaging studies of individuals with ASD will need to account for such disparities.

  6. The Effect of Zipfian Frequency Variations on Category Formation in Adult Artificial Language Learning

    Science.gov (United States)

    Schuler, Kathryn D.; Reeder, Patricia A.; Newport, Elissa L.; Aslin, Richard N.

    2017-01-01

    Successful language acquisition hinges on organizing individual words into grammatical categories and learning the relationships between them, but the method by which children accomplish this task has been debated in the literature. One proposal is that learners use the shared distributional contexts in which words appear as a cue to their…

  7. Feedback-based probabilistic category learning is selectively impaired in attention/hyperactivity deficit disorder.

    Science.gov (United States)

    Gabay, Yafit; Goldfarb, Liat

    2017-07-01

    Although Attention-Deficit Hyperactivity Disorder (ADHD) is closely linked to executive function deficits, it has recently been attributed to procedural learning impairments that are quite distinct from the former. These observations challenge the ability of the executive function framework solely to account for the diverse range of symptoms observed in ADHD. A recent neurocomputational model emphasizes the role of striatal dopamine (DA) in explaining ADHD's broad range of deficits, but the link between this model and procedural learning impairments remains unclear. Significantly, feedback-based procedural learning is hypothesized to be disrupted in ADHD because of the involvement of striatal DA in this type of learning. In order to test this assumption, we employed two variants of a probabilistic category learning task known from the neuropsychological literature. Feedback-based (FB) and paired associate-based (PA) probabilistic category learning were employed in a non-medicated sample of ADHD participants and neurotypical participants. In the FB task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of the response. In the PA learning task, participants viewed the cue and its associated outcome simultaneously without receiving an overt response or corrective feedback. In both tasks, participants were trained across 150 trials. Learning was assessed in a subsequent test without a presentation of the outcome or corrective feedback. Results revealed an interesting disassociation in which ADHD participants performed as well as control participants in the PA task, but were impaired compared with the controls in the FB task. The learning curve during FB training differed between the two groups. Taken together, these results suggest that the ability to incrementally learn by feedback is selectively disrupted in ADHD participants. These results are discussed in relation to both

  8. An interplay of fusiform gyrus and hippocampus enables prototype- and exemplar-based category learning.

    Science.gov (United States)

    Lech, Robert K; Güntürkün, Onur; Suchan, Boris

    2016-09-15

    The aim of the present study was to examine the contributions of different brain structures to prototype- and exemplar-based category learning using functional magnetic resonance imaging (fMRI). Twenty-eight subjects performed a categorization task in which they had to assign prototypes and exceptions to two different families. This test procedure usually produces different learning curves for prototype and exception stimuli. Our behavioral data replicated these previous findings by showing an initially superior performance for prototypes and typical stimuli and a switch from a prototype-based to an exemplar-based categorization for exceptions in the later learning phases. Since performance varied, we divided participants into learners and non-learners. Analysis of the functional imaging data revealed that the interaction of group (learners vs. non-learners) and block (Block 5 vs. Block 1) yielded an activation of the left fusiform gyrus for the processing of prototypes, and an activation of the right hippocampus for exceptions after learning the categories. Thus, successful prototype- and exemplar-based category learning is associated with activations of complementary neural substrates that constitute object-based processes of the ventral visual stream and their interaction with unique-cue representations, possibly based on sparse coding within the hippocampus. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Deep Learning and Developmental Learning: Emergence of Fine-to-Coarse Conceptual Categories at Layers of Deep Belief Network.

    Science.gov (United States)

    Sadeghi, Zahra

    2016-09-01

    In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.

  10. Rule-based category learning in children: the role of age and executive functioning.

    Directory of Open Access Journals (Sweden)

    Rahel Rabi

    Full Text Available 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.

  11. Category learning strategies in younger and older adults: Rule abstraction and memorization.

    Science.gov (United States)

    Wahlheim, Christopher N; McDaniel, Mark A; Little, Jeri L

    2016-06-01

    Despite the fundamental role of category learning in cognition, few studies have examined how this ability differs between younger and older adults. The present experiment examined possible age differences in category learning strategies and their effects on learning. Participants were trained on a category determined by a disjunctive rule applied to relational features. The utilization of rule- and exemplar-based strategies was indexed by self-reports and transfer performance. Based on self-reported strategies, the frequencies of rule- and exemplar-based learners were not significantly different between age groups, but there was a significantly higher frequency of intermediate learners (i.e., learners not identifying with a reliance on either rule- or exemplar-based strategies) in the older than younger adult group. Training performance was higher for younger than older adults regardless of the strategy utilized, showing that older adults were impaired in their ability to learn the correct rule or to remember exemplar-label associations. Transfer performance converged with strategy reports in showing higher fidelity category representations for younger adults. Younger adults with high working memory capacity were more likely to use an exemplar-based strategy, and older adults with high working memory capacity showed better training performance. Age groups did not differ in their self-reported memory beliefs, and these beliefs did not predict training strategies or performance. Overall, the present results contradict earlier findings that older adults prefer rule- to exemplar-based learning strategies, presumably to compensate for memory deficits. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  12. Human simulations of vocabulary learning.

    Science.gov (United States)

    Gillette, J; Gleitman, H; Gleitman, L; Lederer, A

    1999-12-07

    The work reported here experimentally investigates a striking generalization about vocabulary acquisition: Noun learning is superior to verb learning in the earliest moments of child language development. The dominant explanation of this phenomenon in the literature invokes differing conceptual requirements for items in these lexical categories: Verbs are cognitively more complex than nouns and so their acquisition must await certain mental developments in the infant. In the present work, we investigate an alternative hypothesis; namely, that it is the information requirements of verb learning, not the conceptual requirements, that crucially determine the acquisition order. Efficient verb learning requires access to structural features of the exposure language and thus cannot take place until a scaffolding of noun knowledge enables the acquisition of clause-level syntax. More generally, we experimentally investigate the hypothesis that vocabulary acquisition takes place via an incremental constraint-satisfaction procedure that bootstraps itself into successively more sophisticated linguistic representations which, in turn, enable new kinds of vocabulary learning. If the experimental subjects were young children, it would be difficult to distinguish between this information-centered hypothesis and the conceptual change hypothesis. Therefore the experimental "learners" are adults. The items to be "acquired" in the experiments were the 24 most frequent nouns and 24 most frequent verbs from a sample of maternal speech to 18-24-month-old infants. The various experiments ask about the kinds of information that will support identification of these words as they occur in mother-to-child discourse. Both the proportion correctly identified and the type of word that is identifiable changes significantly as a function of information type. We discuss these results as consistent with the incremental construction of a highly lexicalized grammar by cognitively and pragmatically

  13. The Survival Processing Effect with Intentional Learning of Ad Hoc Categories

    Directory of Open Access Journals (Sweden)

    Anastasiya Savchenko

    2014-04-01

    Full Text Available Previous studies have shown that memory is adapted to remember information when it is processed in a survival context. This study investigates how procedural changes in Marinho (2012 study might have led to her failure to replicate the survival mnemonic advantage. In two between-subjects design experiments, participants were instructed to learn words from ad hoc categories and to rate their relevance to a survival or a control scenario. No survival advantage was obtained in either experiment. The Adjusted Ratio of Clustering (ARC scores revealed that including the category labels made the participants rely more on the category structure of the list. Various procedural aspects of the conducted experiments are discussed as possible reasons underlying the absence of the survival effect.

  14. Simulating Category Learning and Set Shifting Deficits in Patients Weight-Restored from Anorexia Nervosa

    Science.gov (United States)

    2014-01-01

    Neuropsychology, in press     Simulating Category Learning and Set Shifting Deficits in Patients Weight-Restored from Anorexia Nervosa J...University   Objective: To examine set shifting in a group of women previously diagnosed with anorexia nervosa (AN) who are now weight-restored (AN-WR...participant fails to switch to the new rule but rather persists with the previously correct rule. Adult patients with Anorexia Nervosa (AN) are often impaired

  15. Associative learning in baboons (Papio papio) and humans (Homo sapiens): species differences in learned attention to visual features.

    Science.gov (United States)

    Fagot, J; Kruschke, J K; Dépy, D; Vauclair, J

    1998-10-01

    We examined attention shifting in baboons and humans during the learning of visual categories. Within a conditional matching-to-sample task, participants of the two species sequentially learned two two-feature categories which shared a common feature. Results showed that humans encoded both features of the initially learned category, but predominantly only the distinctive feature of the subsequently learned category. Although baboons initially encoded both features of the first category, they ultimately retained only the distinctive features of each category. Empirical data from the two species were analyzed with the 1996 ADIT connectionist model of Kruschke. ADIT fits the baboon data when the attentional shift rate is zero, and the human data when the attentional shift rate is not zero. These empirical and modeling results suggest species differences in learned attention to visual features.

  16. Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

    Science.gov (United States)

    Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

    2017-06-09

    In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

  17. Criterial noise effects on rule-based category learning: the impact of delayed feedback.

    Science.gov (United States)

    Ell, Shawn W; Ing, A David; Maddox, W Todd

    2009-08-01

    Variability in the representation of the decision criterion is assumed in many category-learning models, yet few studies have directly examined its impact. On each trial, criterial noise should result in drift in the criterion and will negatively impact categorization accuracy, particularly in rule-based categorization tasks, where learning depends on the maintenance and manipulation of decision criteria. In three experiments, we tested this hypothesis and examined the impact of working memory on slowing the drift rate. In Experiment 1, we examined the effect of drift by inserting a 5-sec delay between the categorization response and the delivery of corrective feedback, and working memory demand was manipulated by varying the number of decision criteria to be learned. Delayed feedback adversely affected performance, but only when working memory demand was high. In Experiment 2, we built on a classic finding in the absolute identification literature and demonstrated that distributing the criteria across multiple dimensions decreases the impact of drift during the delay. In Experiment 3, we confirmed that the effect of drift during the delay is moderated by working memory. These results provide important insights into the interplay between criterial noise and working memory, as well as providing important constraints for models of rule-based category learning.

  18. Comparing the neural basis of monetary reward and cognitive feedback during information-integration category learning.

    Science.gov (United States)

    Daniel, Reka; Pollmann, Stefan

    2010-01-06

    The dopaminergic system is known to play a central role in reward-based learning (Schultz, 2006), yet it was also observed to be involved when only cognitive feedback is given (Aron et al., 2004). Within the domain of information-integration category learning, in which information from several stimulus dimensions has to be integrated predecisionally (Ashby and Maddox, 2005), the importance of contingent feedback is well established (Maddox et al., 2003). We examined the common neural correlates of reward anticipation and prediction error in this task. Sixteen subjects performed two parallel information-integration tasks within a single event-related functional magnetic resonance imaging session but received a monetary reward only for one of them. Similar functional areas including basal ganglia structures were activated in both task versions. In contrast, a single structure, the nucleus accumbens, showed higher activation during monetary reward anticipation compared with the anticipation of cognitive feedback in information-integration learning. Additionally, this activation was predicted by measures of intrinsic motivation in the cognitive feedback task and by measures of extrinsic motivation in the rewarded task. Our results indicate that, although all other structures implicated in category learning are not significantly affected by altering the type of reward, the nucleus accumbens responds to the positive incentive properties of an expected reward depending on the specific type of the reward.

  19. Creating Objects and Object Categories for Studying Perception and Perceptual Learning

    Science.gov (United States)

    Hauffen, Karin; Bart, Eugene; Brady, Mark; Kersten, Daniel; Hegdé, Jay

    2012-01-01

    In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created

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

    Science.gov (United States)

    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.

  1. Definitions of the categories that determine the role of human in social and economic processes

    Directory of Open Access Journals (Sweden)

    Smachylo Valentina

    2016-01-01

    Full Text Available The priorities of the national economy development indicate the growing role of a person in the economic process of creating added value and capitalization of enterprises that require new approaches to the management process in this area. This requires the definition of basic categories that define the role and place of man in the socio-economic processes and characterise a person in the process of work. The article defines the basic aspects that must be considered in the study of the categories «staff», «personnel», «human resources», «cadre», «human potential», «cadre potential», «economically active population», «employment potential», «human capital»: evolution of concepts, level of socio-economic development, the presence or potentiality of human resources, the level of research, management paradigm. The essence, differentiation and interrelation of the given categories in the specified areas are justified. The necessity of socially responsible approach to management is underlined.

  2. Human semi-supervised learning.

    Science.gov (United States)

    Gibson, Bryan R; Rogers, Timothy T; Zhu, Xiaojin

    2013-01-01

    Most empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real-world learning scenarios, however, are semi-supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a knowledgeable source. A large body of work in machine learning has investigated how learning can exploit both labeled and unlabeled data provided to a learner. Using equivalences between models found in human categorization and machine learning research, we explain how these semi-supervised techniques can be applied to human learning. A series of experiments are described which show that semi-supervised learning models prove useful for explaining human behavior when exposed to both labeled and unlabeled data. We then discuss some machine learning models that do not have familiar human categorization counterparts. Finally, we discuss some challenges yet to be addressed in the use of semi-supervised models for modeling human categorization. Copyright © 2013 Cognitive Science Society, Inc.

  3. Young children’s learning of relational categories:multiple comparisons and their cognitive constraints

    Directory of Open Access Journals (Sweden)

    Jean-Pierre eThibaut

    2015-05-01

    Full Text Available Relational categories are notoriously difficult to learn because they are not defined by intrinsic stable properties. We studied the impact of comparisons on relational concept learning with a novel word learning task in 42-month-old children. Capitalizing on Gentner et al. (2011, two, three or four pairs of stimuli were introduced with a novel relational word. In a given trial, the set of pairs was composed of either close or far pairs (e.g., close pair: knife1-watermelon, knife2-orange, knife3-slice of bread and knife4-meat; far pair: ax-evergreen tree, saw-log, cutter-cardboard and knife-slice of bread, for the cutter for relation. Close pairs (2 vs. 3 vs. 4 pairs led to random generalizations whereas comparisons with far pairs gave the expected relational generalization. The 3 pair case gave the best results. It is argued that far pairs promote deeper comparisons than close pairs. As shown by a control experiment, this was the case only when far pairs display well known associations.

  4. Perceptual learning and human expertise.

    Science.gov (United States)

    Kellman, Philip J; Garrigan, Patrick

    2009-06-01

    We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual

  5. Perceptual learning and human expertise

    Science.gov (United States)

    Kellman, Philip J.; Garrigan, Patrick

    2009-06-01

    We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual

  6. Deep-learning-based classification of FDG-PET data for Alzheimer's disease categories

    Science.gov (United States)

    Singh, Shibani; Srivastava, Anant; Mi, Liang; Caselli, Richard J.; Chen, Kewei; Goradia, Dhruman; Reiman, Eric M.; Wang, Yalin

    2017-11-01

    Fluorodeoxyglucose (FDG) positron emission tomography (PET) measures the decline in the regional cerebral metabolic rate for glucose, offering a reliable metabolic biomarker even on presymptomatic Alzheimer's disease (AD) patients. PET scans provide functional information that is unique and unavailable using other types of imaging. However, the computational efficacy of FDG-PET data alone, for the classification of various Alzheimers Diagnostic categories, has not been well studied. This motivates us to correctly discriminate various AD Diagnostic categories using FDG-PET data. Deep learning has improved state-of-the-art classification accuracies in the areas of speech, signal, image, video, text mining and recognition. We propose novel methods that involve probabilistic principal component analysis on max-pooled data and mean-pooled data for dimensionality reduction, and multilayer feed forward neural network which performs binary classification. Our experimental dataset consists of baseline data of subjects including 186 cognitively unimpaired (CU) subjects, 336 mild cognitive impairment (MCI) subjects with 158 Late MCI and 178 Early MCI, and 146 AD patients from Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We measured F1-measure, precision, recall, negative and positive predictive values with a 10-fold cross validation scheme. Our results indicate that our designed classifiers achieve competitive results while max pooling achieves better classification performance compared to mean-pooled features. Our deep model based research may advance FDG-PET analysis by demonstrating their potential as an effective imaging biomarker of AD.

  7. Robot learning from human teachers

    CERN Document Server

    Chernova, Sonia

    2014-01-01

    Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn f

  8. Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment (Presentation)

    Science.gov (United States)

    Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...

  9. Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment

    Science.gov (United States)

    Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...

  10. Reducing consistency in human realism increases the uncanny valley effect; increasing category uncertainty does not.

    Science.gov (United States)

    MacDorman, Karl F; Chattopadhyay, Debaleena

    2016-01-01

    Human replicas may elicit unintended cold, eerie feelings in viewers, an effect known as the uncanny valley. Masahiro Mori, who proposed the effect in 1970, attributed it to inconsistencies in the replica's realism with some of its features perceived as human and others as nonhuman. This study aims to determine whether reducing realism consistency in visual features increases the uncanny valley effect. In three rounds of experiments, 548 participants categorized and rated humans, animals, and objects that varied from computer animated to real. Two sets of features were manipulated to reduce realism consistency. (For humans, the sets were eyes-eyelashes-mouth and skin-nose-eyebrows.) Reducing realism consistency caused humans and animals, but not objects, to appear eerier and colder. However, the predictions of a competing theory, proposed by Ernst Jentsch in 1906, were not supported: The most ambiguous representations-those eliciting the greatest category uncertainty-were neither the eeriest nor the coldest. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  11. Age-related difference in the effective neural connectivity associated with probabilistic category learning

    International Nuclear Information System (INIS)

    Yoon, Eun Jin; Cho, Sang Soo; Kim, Hee Jung; Bang, Seong Ae; Park, Hyun Soo; Kim, Yu Kyeong; Kim, Sang Eun

    2007-01-01

    Although it is well known that explicit memory is affected by the deleterious changes in brain with aging, but effect of aging in implicit memory such as probabilistic category learning (PCL) is not clear. To identify the effect of aging on the neural interaction for successful PCL, we investigated the neural substrates of PCL and the age-related changes of the neural network between these brain regions. 23 young (age, 252 y; 11 males) and 14 elderly (673 y; 7 males) healthy subjects underwent FDG PET during a resting state and 150-trial weather prediction (WP) task. Correlations between the WP hit rates and regional glucose metabolism were assessed using SPM2 (P diff (37) = 142.47, P<0.005), Systematic comparisons of each path revealed that frontal crosscallosal and the frontal to parahippocampal connection were most responsible for the model differences (P<0.05). For the successful PCL, the elderly recruits the basal ganglia implicit memory system but MTL recruitment differs from the young. The inadequate MTL correlation pattern in the elderly is may be caused by the changes of the neural pathway related with explicit memory. These neural changes can explain the decreased performance of PCL in elderly subjects

  12. Motivation categories in college students’ learning engagement behaviors and outcomes in Taiwan: An application of cluster analysis

    OpenAIRE

    Tzu-Ling Hsieh

    2016-01-01

    This study explores how different motivation categories influence college students’ learning engagement behaviors and outcomes under the context of eastern culture. 178 junior college students were surveyed at a four-year research university in Taiwan. The study addressed two research questions: 1. Are there subgroups of students with significantly different motivation profiles? 2. If so, do these subgroups of students differ significantly in terms of their engagement behaviors and learning o...

  13. Striatal and Hippocampal Entropy and Recognition Signals in Category Learning: Simultaneous Processes Revealed by Model-Based fMRI

    Science.gov (United States)

    Davis, Tyler; Love, Bradley C.; Preston, Alison R.

    2012-01-01

    Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and…

  14. Due Process in Dual Process: Model-Recovery Simulations of Decision-Bound Strategy Analysis in Category Learning

    Science.gov (United States)

    Edmunds, Charlotte E. R.; Milton, Fraser; Wills, Andy J.

    2018-01-01

    Behavioral evidence for the COVIS dual-process model of category learning has been widely reported in over a hundred publications (Ashby & Valentin, 2016). It is generally accepted that the validity of such evidence depends on the accurate identification of individual participants' categorization strategies, a task that usually falls to…

  15. The Effect of Feedback Delay on Perceptual Category Learning and Item Memory: Further Limits of Multiple Systems.

    Science.gov (United States)

    Stephens, Rachel G; Kalish, Michael L

    2018-02-01

    Delayed feedback during categorization training has been hypothesized to differentially affect 2 systems that underlie learning for rule-based (RB) or information-integration (II) structures. We tested an alternative possibility: that II learning requires more precise item representations than RB learning, and so is harmed more by a delay interval filled with a confusable mask. Experiments 1 and 2 examined the effect of feedback delay on memory for RB and II exemplars, both without and with concurrent categorization training. Without the training, II items were indeed more difficult to recognize than RB items, but there was no detectable effect of delay on item memory. In contrast, with concurrent categorization training, there were effects of both category structure and delayed feedback on item memory, which were related to corresponding changes in category learning. However, we did not observe the critical selective impact of delay on II classification performance that has been shown previously. Our own results were also confirmed in a follow-up study (Experiment 3) involving only categorization training. The selective influence of feedback delay on II learning appears to be contingent on the relative size of subgroups of high-performing participants, and in fact does not support that RB and II category learning are qualitatively different. We conclude that a key part of successfully solving perceptual categorization problems is developing more precise item representations, which can be impaired by delayed feedback during training. More important, the evidence for multiple systems of category learning is even weaker than previously proposed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  16. [Problem based learning: achievement of educational goals in the information and comprehension sub-categories of Bloom cognitive domain].

    Science.gov (United States)

    Montecinos, P; Rodewald, A M

    1994-06-01

    The aim this work was to assess and compare the achievements of medical students, subjected to problem based learning methodology. The information and comprehension categories of Bloom were tested in 17 medical students in four different occasions during the physiopathology course, using a multiple choice knowledge test. There was a significant improvement in the number of correct answers towards the end of the course. It is concluded that these medical students obtained adequate learning achievements in the information subcategory of Bloom using problem based learning methodology, during the physiopathology course.

  17. Approximation to the distribution of fitness effects across functional categories in human segregating polymorphisms.

    Directory of Open Access Journals (Sweden)

    Fernando Racimo

    2014-11-01

    Full Text Available Quantifying the proportion of polymorphic mutations that are deleterious or neutral is of fundamental importance to our understanding of evolution, disease genetics and the maintenance of variation genome-wide. Here, we develop an approximation to the distribution of fitness effects (DFE of segregating single-nucleotide mutations in humans. Unlike previous methods, we do not assume that synonymous mutations are neutral or not strongly selected, and we do not rely on fitting the DFE of all new nonsynonymous mutations to a single probability distribution, which is poorly motivated on a biological level. We rely on a previously developed method that utilizes a variety of published annotations (including conservation scores, protein deleteriousness estimates and regulatory data to score all mutations in the human genome based on how likely they are to be affected by negative selection, controlling for mutation rate. We map this and other conservation scores to a scale of fitness coefficients via maximum likelihood using diffusion theory and a Poisson random field model on SNP data. Our method serves to approximate the deleterious DFE of mutations that are segregating, regardless of their genomic consequence. We can then compare the proportion of mutations that are negatively selected or neutral across various categories, including different types of regulatory sites. We observe that the distribution of intergenic polymorphisms is highly peaked at neutrality, while the distribution of nonsynonymous polymorphisms has a second peak at [Formula: see text]. Other types of polymorphisms have shapes that fall roughly in between these two. We find that transcriptional start sites, strong CTCF-enriched elements and enhancers are the regulatory categories with the largest proportion of deleterious polymorphisms.

  18. Age-related difference in the effective neural connectivity associated with probabilistic category learning

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Eun Jin; Cho, Sang Soo; Kim, Hee Jung; Bang, Seong Ae; Park, Hyun Soo; Kim, Yu Kyeong; Kim, Sang Eun [Seoul National Univ. College of Medicine, Seoul (Korea, Republic of)

    2007-07-01

    Although it is well known that explicit memory is affected by the deleterious changes in brain with aging, but effect of aging in implicit memory such as probabilistic category learning (PCL) is not clear. To identify the effect of aging on the neural interaction for successful PCL, we investigated the neural substrates of PCL and the age-related changes of the neural network between these brain regions. 23 young (age, 252 y; 11 males) and 14 elderly (673 y; 7 males) healthy subjects underwent FDG PET during a resting state and 150-trial weather prediction (WP) task. Correlations between the WP hit rates and regional glucose metabolism were assessed using SPM2 (P<0.05 uncorrected). For path analysis, seven brain regions (bilateral middle frontal gyri and putamen, left fusiform gyrus, anterior cingulate and right parahippocampal gyri) were selected based on the results of the correlation analysis. Model construction and path analysis processing were done by AMOS 5.0. The elderly had significantly lower total hit rates than the young (P<0.005). In the correlation analysis, both groups showed similar metabolic correlation in frontal and striatal area. But correlation in the medial temporal lobe (MTL) was found differently by group. In path analysis, the functional networks for the constructed model was accepted (X(2) =0.80, P=0.67) and it proved to be significantly different between groups (X{sub diff}(37) = 142.47, P<0.005), Systematic comparisons of each path revealed that frontal crosscallosal and the frontal to parahippocampal connection were most responsible for the model differences (P<0.05). For the successful PCL, the elderly recruits the basal ganglia implicit memory system but MTL recruitment differs from the young. The inadequate MTL correlation pattern in the elderly is may be caused by the changes of the neural pathway related with explicit memory. These neural changes can explain the decreased performance of PCL in elderly subjects.

  19. Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.

    Science.gov (United States)

    Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L; Schulz, Andreas L; Ohl, Frank W; Lommerzheim, Marcel; Neumann, Heiko

    2016-01-01

    Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden

  20. Picture-Word Differences in Discrimination Learning: 11. Effects of Conceptual Categories

    Science.gov (United States)

    Bourne, Lyle E.; And Others

    1976-01-01

    Investigates the prediction that the usual superiority of pictures over words for repetitions of the same items would disappear for items that were different instances of repeated categories. (Author/RK)

  1. A Note on DeCaro, Thomas, and Beilock (2008): Further Data Demonstrate Complexities in the Assessment of Information-Integration Category Learning

    Science.gov (United States)

    Tharp, Ian J.; Pickering, Alan D.

    2009-01-01

    DeCaro et al. [DeCaro, M. S., Thomas, R. D., & Beilock, S. L. (2008). "Individual differences in category learning: Sometimes less working memory capacity is better than more." "Cognition, 107"(1), 284-294] explored how individual differences in working memory capacity differentially mediate the learning of distinct category structures.…

  2. Vicarious Learning from Human Models in Monkeys

    OpenAIRE

    Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

    2012-01-01

    We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was app...

  3. Vicarious learning from human models in monkeys.

    Science.gov (United States)

    Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

    2012-01-01

    We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

  4. Vicarious learning from human models in monkeys.

    Directory of Open Access Journals (Sweden)

    Rossella Falcone

    Full Text Available We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

  5. Managing Human Resource Learning for Innovation

    DEFF Research Database (Denmark)

    Nielsen, Peter

    Managing human resource learning for innovation develops a systemic understanding of building innovative capabilities. Building innovative capabilities require active creation, coordination and absorption of useful knowledge and thus a cohesive management approach to learning. Often learning...... in organizations and work is approached without considerations on how to integrate it in the management of human resources. The book investigates the empirical conditions for managing human resources learning for innovation. With focus on innovative performance the importance of modes of innovation, clues...

  6. Probabilistic Category Learning in Developmental Dyslexia: Evidence from Feedback and Paired-Associate Weather Prediction Tasks

    Science.gov (United States)

    Gabay, Yafit; Vakil, Eli; Schiff, Rachel; Holt, Lori L.

    2015-01-01

    Objective Developmental dyslexia is presumed to arise from specific phonological impairments. However, an emerging theoretical framework suggests that phonological impairments may be symptoms stemming from an underlying dysfunction of procedural learning. Method We tested procedural learning in adults with dyslexia (n=15) and matched-controls (n=15) using two versions of the Weather Prediction Task: Feedback (FB) and Paired-associate (PA). In the FB-based task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of response. In the PA-based learning task, participants viewed the cue and its associated outcome simultaneously without overt response or feedback. In both versions, participants trained across 150 trials. Learning was assessed in a subsequent test without presentation of the outcome, or corrective feedback. Results The Dyslexia group exhibited impaired learning compared with the Control group on both the FB and PA versions of the weather prediction task. Conclusions The results indicate that the ability to learn by feedback is not selectively impaired in dyslexia. Rather it seems that the probabilistic nature of the task, shared by the FB and PA versions of the weather prediction task, hampers learning in those with dyslexia. Results are discussed in light of procedural learning impairments among participants with dyslexia. PMID:25730732

  7. Basic level category structure emerges gradually across human ventral visual cortex.

    Science.gov (United States)

    Iordan, Marius Cătălin; Greene, Michelle R; Beck, Diane M; Fei-Fei, Li

    2015-07-01

    Objects can be simultaneously categorized at multiple levels of specificity ranging from very broad ("natural object") to very distinct ("Mr. Woof"), with a mid-level of generality (basic level: "dog") often providing the most cognitively useful distinction between categories. It is unknown, however, how this hierarchical representation is achieved in the brain. Using multivoxel pattern analyses, we examined how well each taxonomic level (superordinate, basic, and subordinate) of real-world object categories is represented across occipitotemporal cortex. We found that, although in early visual cortex objects are best represented at the subordinate level (an effect mostly driven by low-level feature overlap between objects in the same category), this advantage diminishes compared to the basic level as we move up the visual hierarchy, disappearing in object-selective regions of occipitotemporal cortex. This pattern stems from a combined increase in within-category similarity (category cohesion) and between-category dissimilarity (category distinctiveness) of neural activity patterns at the basic level, relative to both subordinate and superordinate levels, suggesting that successive visual areas may be optimizing basic level representations.

  8. Picture-Word Differences in Discrimination Learning: II. Effects of Conceptual Categories.

    Science.gov (United States)

    Bourne, Lyle E., Jr.; And Others

    A well established finding in the discrimination learning literature is that pictures are learned more rapidly than their associated verbal labels. It was hypothesized in this study that the usual superiority of pictures over words in a discrimination list containing same-instance repetitions would disappear in a discrimination list containing…

  9. Binocular Fusion and Invariant Category Learning due to Predictive Remapping during Scanning of a Depthful Scene with Eye Movements

    Directory of Open Access Journals (Sweden)

    Stephen eGrossberg

    2015-01-01

    Full Text Available How does the brain maintain stable fusion of 3D scenes when the eyes move? Every eye movement causes each retinal position to process a different set of scenic features, and thus the brain needs to binocularly fuse new combinations of features at each position after an eye movement. Despite these breaks in retinotopic fusion due to each movement, previously fused representations of a scene in depth often appear stable. The 3D ARTSCAN neural model proposes how the brain does this by unifying concepts about how multiple cortical areas in the What and Where cortical streams interact to coordinate processes of 3D boundary and surface perception, spatial attention, invariant object category learning, predictive remapping, eye movement control, and learned coordinate transformations. The model explains data from single neuron and psychophysical studies of covert visual attention shifts prior to eye movements. The model further clarifies how perceptual, attentional, and cognitive interactions among multiple brain regions (LGN, V1, V2, V3A, V4, MT, MST, PPC, LIP, ITp, ITa, SC may accomplish predictive remapping as part of the process whereby view-invariant object categories are learned. These results build upon earlier neural models of 3D vision and figure-ground separation and the learning of invariant object categories as the eyes freely scan a scene. A key process concerns how an object’s surface representation generates a form-fitting distribution of spatial attention, or attentional shroud, in parietal cortex that helps maintain the stability of multiple perceptual and cognitive processes. Predictive eye movement signals maintain the stability of the shroud, as well as of binocularly fused perceptual boundaries and surface representations.

  10. Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements

    Science.gov (United States)

    Grossberg, Stephen; Srinivasan, Karthik; Yazdanbakhsh, Arash

    2015-01-01

    How does the brain maintain stable fusion of 3D scenes when the eyes move? Every eye movement causes each retinal position to process a different set of scenic features, and thus the brain needs to binocularly fuse new combinations of features at each position after an eye movement. Despite these breaks in retinotopic fusion due to each movement, previously fused representations of a scene in depth often appear stable. The 3D ARTSCAN neural model proposes how the brain does this by unifying concepts about how multiple cortical areas in the What and Where cortical streams interact to coordinate processes of 3D boundary and surface perception, spatial attention, invariant object category learning, predictive remapping, eye movement control, and learned coordinate transformations. The model explains data from single neuron and psychophysical studies of covert visual attention shifts prior to eye movements. The model further clarifies how perceptual, attentional, and cognitive interactions among multiple brain regions (LGN, V1, V2, V3A, V4, MT, MST, PPC, LIP, ITp, ITa, SC) may accomplish predictive remapping as part of the process whereby view-invariant object categories are learned. These results build upon earlier neural models of 3D vision and figure-ground separation and the learning of invariant object categories as the eyes freely scan a scene. A key process concerns how an object's surface representation generates a form-fitting distribution of spatial attention, or attentional shroud, in parietal cortex that helps maintain the stability of multiple perceptual and cognitive processes. Predictive eye movement signals maintain the stability of the shroud, as well as of binocularly fused perceptual boundaries and surface representations. PMID:25642198

  11. Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements.

    Science.gov (United States)

    Grossberg, Stephen; Srinivasan, Karthik; Yazdanbakhsh, Arash

    2014-01-01

    How does the brain maintain stable fusion of 3D scenes when the eyes move? Every eye movement causes each retinal position to process a different set of scenic features, and thus the brain needs to binocularly fuse new combinations of features at each position after an eye movement. Despite these breaks in retinotopic fusion due to each movement, previously fused representations of a scene in depth often appear stable. The 3D ARTSCAN neural model proposes how the brain does this by unifying concepts about how multiple cortical areas in the What and Where cortical streams interact to coordinate processes of 3D boundary and surface perception, spatial attention, invariant object category learning, predictive remapping, eye movement control, and learned coordinate transformations. The model explains data from single neuron and psychophysical studies of covert visual attention shifts prior to eye movements. The model further clarifies how perceptual, attentional, and cognitive interactions among multiple brain regions (LGN, V1, V2, V3A, V4, MT, MST, PPC, LIP, ITp, ITa, SC) may accomplish predictive remapping as part of the process whereby view-invariant object categories are learned. These results build upon earlier neural models of 3D vision and figure-ground separation and the learning of invariant object categories as the eyes freely scan a scene. A key process concerns how an object's surface representation generates a form-fitting distribution of spatial attention, or attentional shroud, in parietal cortex that helps maintain the stability of multiple perceptual and cognitive processes. Predictive eye movement signals maintain the stability of the shroud, as well as of binocularly fused perceptual boundaries and surface representations.

  12. Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task

    Science.gov (United States)

    Tabor, Whitney; Cho, Pyeong W.; Dankowicz, Harry

    2013-01-01

    Human participants and recurrent ("connectionist") neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular ("strong") classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the…

  13. Real-time learning of predictive recognition categories that chunk sequences of items stored in working memory

    Directory of Open Access Journals (Sweden)

    Stephen eGrossberg

    2014-10-01

    Full Text Available How are sequences of events that are temporarily stored in a cognitive working memory unitized, or chunked, through learning? Such sequential learning is needed by the brain in order to enable language, spatial understanding, and motor skills to develop. In particular, how does the brain learn categories, or list chunks, that become selectively tuned to different temporal sequences of items in lists of variable length as they are stored in working memory, and how does this learning process occur in real time? The present article introduces a neural model that simulates learning of such list chunks. In this model, sequences of items are temporarily stored in an Item-and-Order, or competitive queuing, working memory before learning categorizes them using a categorization network, called a Masking Field, which is a self-similar, multiple-scale, recurrent on-center off-surround network that can weigh the evidence for variable-length sequences of items as they are stored in the working memory through time. A Masking Field hereby activates the learned list chunks that represent the most predictive item groupings at any time, while suppressing less predictive chunks. In a network with a given number of input items, all possible ordered sets of these item sequences, up to a fixed length, can be learned with unsupervised or supervised learning. The self-similar multiple-scale properties of Masking Fields interacting with an Item-and-Order working memory provide a natural explanation of George Miller's Magical Number Seven and Nelson Cowan's Magical Number Four. The article explains why linguistic, spatial, and action event sequences may all be stored by Item-and-Order working memories that obey similar design principles, and thus how the current results may apply across modalities. Item-and-Order properties may readily be extended to Item-Order-Rank working memories in which the same item can be stored in multiple list positions, or ranks, as in the list

  14. Effects of musicality and motivational orientation on auditory category learning: a test of a regulatory-fit hypothesis.

    Science.gov (United States)

    McAuley, J Devin; Henry, Molly J; Wedd, Alan; Pleskac, Timothy J; Cesario, Joseph

    2012-02-01

    Two experiments investigated the effects of musicality and motivational orientation on auditory category learning. In both experiments, participants learned to classify tone stimuli that varied in frequency and duration according to an initially unknown disjunctive rule; feedback involved gaining points for correct responses (a gains reward structure) or losing points for incorrect responses (a losses reward structure). For Experiment 1, participants were told at the start that musicians typically outperform nonmusicians on the task, and then they were asked to identify themselves as either a "musician" or a "nonmusician." For Experiment 2, participants were given either a promotion focus prime (a performance-based opportunity to gain entry into a raffle) or a prevention focus prime (a performance-based criterion that needed to be maintained to avoid losing an entry into a raffle) at the start of the experiment. Consistent with a regulatory-fit hypothesis, self-identified musicians and promotion-primed participants given a gains reward structure made more correct tone classifications and were more likely to discover the optimal disjunctive rule than were musicians and promotion-primed participants experiencing losses. Reward structure (gains vs. losses) had inconsistent effects on the performance of nonmusicians, and a weaker regulatory-fit effect was found for the prevention focus prime. Overall, the findings from this study demonstrate a regulatory-fit effect in the domain of auditory category learning and show that motivational orientation may contribute to musician performance advantages in auditory perception.

  15. Specific neural traces for intonational discourse categories as revealed by human-evoked potentials.

    Science.gov (United States)

    Borràs-Comes, Joan; Costa-Faidella, Jordi; Prieto, Pilar; Escera, Carles

    2012-04-01

    The neural representation of segmental and tonal phonological distinctions has been shown by means of the MMN ERP, yet this is not the case for intonational discourse contrasts. In Catalan, a rising-falling intonational sequence can be perceived as a statement or as a counterexpectational question, depending exclusively on the size of the pitch range interval of the rising movement. We tested here, using the MMN, whether such categorical distinctions elicited distinct neurophysiological patterns of activity, supporting their specific neural representation. From a behavioral identification experiment, we set the boundary between the two categories and defined four stimuli across the continuum. Although the physical distance between each pair of stimuli was kept constant, the central pair represented an across-category contrast, whereas the other pairs represented within-category contrasts. These four auditory stimuli were contrasted by pairs in three different oddball blocks. The mean amplitude of the MMN was larger for the across-category contrast, suggesting that intonational contrasts in the target language can be encoded automatically in the auditory cortex. These results are in line with recent findings in other fields of linguistics, showing that, when a boundary between categories is crossed, the MMN response is not just larger but rather includes a separate subcomponent.

  16. Learning Grammatical Categories from Distributional Cues: Flexible Frames for Language Acquisition

    Science.gov (United States)

    St. Clair, Michelle C.; Monaghan, Padraic; Christiansen, Morten H.

    2010-01-01

    Numerous distributional cues in the child's environment may potentially assist in language learning, but what cues are useful to the child and when are these cues utilised? We propose that the most useful source of distributional cue is a flexible frame surrounding the word, where the language learner integrates information from the preceding and…

  17. Learning to Match Auditory and Visual Speech Cues: Social Influences on Acquisition of Phonological Categories

    Science.gov (United States)

    Altvater-Mackensen, Nicole; Grossmann, Tobias

    2015-01-01

    Infants' language exposure largely involves face-to-face interactions providing acoustic and visual speech cues but also social cues that might foster language learning. Yet, both audiovisual speech information and social information have so far received little attention in research on infants' early language development. Using a preferential…

  18. Induced lexical categories enhance cross-situational learning of word meanings

    NARCIS (Netherlands)

    Alishahi, A.; Chrupala, Grzegorz

    2014-01-01

    In this paper we bring together two sources of information that have been proposed as clues used by children acquiring word meanings. One mechanism is cross-situational learning which exploits co-occurrences between words and their referents in perceptual context accompanying utterances. The other

  19. The ontogeny of phonological categories and the primacy of lexical learning in linguistic development.

    Science.gov (United States)

    Beckman, M E; Edwards, J

    2000-01-01

    In this paper, we draw on recent developments in several areas of cognitive science that suggest that the lexicon is at the core of grammatical generalizations at several different levels of representation. Evidence comes from many sources, including recent studies on language processing in adults and on language acquisition in children. Phonological behavior is influenced very early by pattern frequency in the lexicon of the ambient language, and we propose that phonological acquisition might provide the initial bootstrapping into grammatical generalization in general. The phonological categories over which pattern frequencies are calculated, however, are neither transparently available in the audiovisual signal nor deterministically fixed by the physiological and perceptual capacities of the species. Therefore, we need several age-appropriate models of how the lexicon can influence a child's interactions with the ambient language over the course of phonological acquisition.

  20. When bad stress goes good: increased threat reactivity predicts improved category learning performance.

    Science.gov (United States)

    Ell, Shawn W; Cosley, Brandon; McCoy, Shannon K

    2011-02-01

    The way in which we respond to everyday stressors can have a profound impact on cognitive functioning. Maladaptive stress responses in particular are generally associated with impaired cognitive performance. We argue, however, that the cognitive system mediating task performance is also a critical determinant of the stress-cognition relationship. Consistent with this prediction, we observed that stress reactivity consistent with a maladaptive, threat response differentially predicted performance on two categorization tasks. Increased threat reactivity predicted enhanced performance on an information-integration task (i.e., learning is thought to depend upon a procedural-based memory system), and a (nonsignificant) trend for impaired performance on a rule-based task (i.e., learning is thought to depend upon a hypothesis-testing system). These data suggest that it is critical to consider both variability in the stress response and variability in the cognitive system mediating task performance in order to fully understand the stress-cognition relationship.

  1. Finding biomedical categories in Medline®

    Directory of Open Access Journals (Sweden)

    Yeganova Lana

    2012-10-01

    Full Text Available Abstract Background There are several humanly defined ontologies relevant to Medline. However, Medline is a fast growing collection of biomedical documents which creates difficulties in updating and expanding these humanly defined ontologies. Automatically identifying meaningful categories of entities in a large text corpus is useful for information extraction, construction of machine learning features, and development of semantic representations. In this paper we describe and compare two methods for automatically learning meaningful biomedical categories in Medline. The first approach is a simple statistical method that uses part-of-speech and frequency information to extract a list of frequent nouns from Medline. The second method implements an alignment-based technique to learn frequent generic patterns that indicate a hyponymy/hypernymy relationship between a pair of noun phrases. We then apply these patterns to Medline to collect frequent hypernyms as potential biomedical categories. Results We study and compare these two alternative sets of terms to identify semantic categories in Medline. We find that both approaches produce reasonable terms as potential categories. We also find that there is a significant agreement between the two sets of terms. The overlap between the two methods improves our confidence regarding categories predicted by these independent methods. Conclusions This study is an initial attempt to extract categories that are discussed in Medline. Rather than imposing external ontologies on Medline, our methods allow categories to emerge from the text.

  2. Categorial compositionality II: universal constructions and a general theory of (quasi-systematicity in human cognition.

    Directory of Open Access Journals (Sweden)

    Steven Phillips

    2011-08-01

    Full Text Available A complete theory of cognitive architecture (i.e., the basic processes and modes of composition that together constitute cognitive behaviour must explain the systematicity property--why our cognitive capacities are organized into particular groups of capacities, rather than some other, arbitrary collection. The classical account supposes: (1 syntactically compositional representations; and (2 processes that are sensitive to--compatible with--their structure. Classical compositionality, however, does not explain why these two components must be compatible; they are only compatible by the ad hoc assumption (convention of employing the same mode of (concatenative compositionality (e.g., prefix/postfix, where a relation symbol is always prepended/appended to the symbols for the related entities. Architectures employing mixed modes do not support systematicity. Recently, we proposed an alternative explanation without ad hoc assumptions, using category theory. Here, we extend our explanation to domains that are quasi-systematic (e.g., aspects of most languages, where the domain includes some but not all possible combinations of constituents. The central category-theoretic construct is an adjunction involving pullbacks, where the primary focus is on the relationship between processes modelled as functors, rather than the representations. A functor is a structure-preserving map (or construction, for our purposes. An adjunction guarantees that the only pairings of functors are the systematic ones. Thus, (quasi-systematicity is a necessary consequence of a categorial cognitive architecture whose basic processes are functors that participate in adjunctions.

  3. Categorial compositionality II: universal constructions and a general theory of (quasi-)systematicity in human cognition.

    Science.gov (United States)

    Phillips, Steven; Wilson, William H

    2011-08-01

    A complete theory of cognitive architecture (i.e., the basic processes and modes of composition that together constitute cognitive behaviour) must explain the systematicity property--why our cognitive capacities are organized into particular groups of capacities, rather than some other, arbitrary collection. The classical account supposes: (1) syntactically compositional representations; and (2) processes that are sensitive to--compatible with--their structure. Classical compositionality, however, does not explain why these two components must be compatible; they are only compatible by the ad hoc assumption (convention) of employing the same mode of (concatenative) compositionality (e.g., prefix/postfix, where a relation symbol is always prepended/appended to the symbols for the related entities). Architectures employing mixed modes do not support systematicity. Recently, we proposed an alternative explanation without ad hoc assumptions, using category theory. Here, we extend our explanation to domains that are quasi-systematic (e.g., aspects of most languages), where the domain includes some but not all possible combinations of constituents. The central category-theoretic construct is an adjunction involving pullbacks, where the primary focus is on the relationship between processes modelled as functors, rather than the representations. A functor is a structure-preserving map (or construction, for our purposes). An adjunction guarantees that the only pairings of functors are the systematic ones. Thus, (quasi-)systematicity is a necessary consequence of a categorial cognitive architecture whose basic processes are functors that participate in adjunctions.

  4. When Humans Become Animals: Development of the Animal Category in Early Childhood

    Science.gov (United States)

    Herrmann, Patricia A.; Medin, Douglas L.; Waxman, Sandra R.

    2012-01-01

    The current study examines 3- and 5-year-olds' representation of the concept we label "animal" and its two nested concepts--"animal"[subscript contrastive] (including only non-human animals) and "animal"[subscript inclusive] (including both humans and non-human animals). Building upon evidence that naming promotes object categorization, we…

  5. Optimizing learning of scientific category knowledge in the classroom: the case of plant identification.

    Science.gov (United States)

    Kirchoff, Bruce K; Delaney, Peter F; Horton, Meg; Dellinger-Johnston, Rebecca

    2014-01-01

    Learning to identify organisms is extraordinarily difficult, yet trained field biologists can quickly and easily identify organisms at a glance. They do this without recourse to the use of traditional characters or identification devices. Achieving this type of recognition accuracy is a goal of many courses in plant systematics. Teaching plant identification is difficult because of variability in the plants' appearance, the difficulty of bringing them into the classroom, and the difficulty of taking students into the field. To solve these problems, we developed and tested a cognitive psychology-based computer program to teach plant identification. The program incorporates presentation of plant images in a homework-based, active-learning format that was developed to stimulate expert-level visual recognition. A controlled experimental test using a within-subject design was performed against traditional study methods in the context of a college course in plant systematics. Use of the program resulted in an 8-25% statistically significant improvement in final exam scores, depending on the type of identification question used (living plants, photographs, written descriptions). The software demonstrates how the use of routines to train perceptual expertise, interleaved examples, spaced repetition, and retrieval practice can be used to train identification of complex and highly variable objects. © 2014 B. K. Kirchoff et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  6. Right to Development and Right to the City : A Proposal of Human Rights Categories Universal as assumptions Citizenship

    Directory of Open Access Journals (Sweden)

    Alessandra Danielle Carneiro dos Santos Hilário

    2016-05-01

    Full Text Available This article discusses the Right to the City, in a conceptual dimension and wide, and his dialectical relationship with the Universal Declaration of Human Rights of 1948 and its universalism and cultural relativism categories. The Right to the City (RtC is capitula- ted as one of the categories of the Human Right to Development from the compartments on Human Rights to descend from the Universal Declaration of Human Rights. Linked to this assumption, the discussion of universalism and cultural relativism theories bring to the fore important questions and considerations as to RtC condition, since in its current design and trampled by an evil legacy of neoliberalism, this right has demonstrated the need for authoritative action of the State, given the nature of fundamental human right of the third dimension. Through RtC, boasts up of economic, social and cultural rights, requiring a positive action of the state as compliance guarantee this human right. In this bias, relevant are discussions about the concept of law, morality, liberalism, effectiveness and universality of human rights theories and cultural relativism in dialectic with the RtC and its complexity. It starts from the assumption that the Universal Declaration of Human Rights and other statements which have descended universality (despite criticism, however, this har- vest, it is imperative closer examination of the concept, forecast, guarantee and effective- ness fundamental human rights, which may lead to a mixed application of universalistic and relativistic theories when analyzed from the perspective of these institutes. The Hu- man Right to Development (RtD presupposes notions of environmental sustainability and economic democracy, with qualified participation of social subjects (wide citizenship, seen continuous and articulated perspective as guiding the development process.

  7. Category Selectivity of Human Visual Cortex in Perception of Rubin Face–Vase Illusion

    Directory of Open Access Journals (Sweden)

    Xiaogang Wang

    2017-09-01

    Full Text Available When viewing the Rubin face–vase illusion, our conscious perception spontaneously alternates between the face and the vase; this illusion has been widely used to explore bistable perception. Previous functional magnetic resonance imaging (fMRI studies have studied the neural mechanisms underlying bistable perception through univariate and multivariate pattern analyses; however, no studies have investigated the issue of category selectivity. Here, we used fMRI to investigate the neural mechanisms underlying the Rubin face–vase illusion by introducing univariate amplitude and multivariate pattern analyses. The results from the amplitude analysis suggested that the activity in the fusiform face area was likely related to the subjective face perception. Furthermore, the pattern analysis results showed that the early visual cortex (EVC and the face-selective cortex could discriminate the activity patterns of the face and vase perceptions. However, further analysis of the activity patterns showed that only the face-selective cortex contains the face information. These findings indicated that although the EVC and face-selective cortex activities could discriminate the visual information, only the activity and activity pattern in the face-selective areas contained the category information of face perception in the Rubin face–vase illusion.

  8. The Development of Automaticity in Short-Term Memory Search: Item-Response Learning and Category Learning

    Science.gov (United States)

    Cao, Rui; Nosofsky, Robert M.; Shiffrin, Richard M.

    2017-01-01

    In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across…

  9. Contested Categories

    DEFF Research Database (Denmark)

    Drawing on social science perspectives, Contested Categories presents a series of empirical studies that engage with the often shifting and day-to-day realities of life sciences categories. In doing so, it shows how such categories remain contested and dynamic, and that the boundaries they create...

  10. Effects of statistical learning on the acquisition of grammatical categories through Qur'anic memorization: A natural experiment.

    Science.gov (United States)

    Zuhurudeen, Fathima Manaar; Huang, Yi Ting

    2016-03-01

    Empirical evidence for statistical learning comes from artificial language tasks, but it is unclear how these effects scale up outside of the lab. The current study turns to a real-world test case of statistical learning where native English speakers encounter the syntactic regularities of Arabic through memorization of the Qur'an. This unique input provides extended exposure to the complexity of a natural language, with minimal semantic cues. Memorizers were asked to distinguish unfamiliar nouns and verbs based on their co-occurrence with familiar pronouns in an Arabic language sample. Their performance was compared to that of classroom learners who had explicit knowledge of pronoun meanings and grammatical functions. Grammatical judgments were more accurate in memorizers compared to non-memorizers. No effects of classroom experience were found. These results demonstrate that real-world exposure to the statistical properties of a natural language facilitates the acquisition of grammatical categories. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Competitive debate classroom as a cooperative learning technique for the human resources subject

    Directory of Open Access Journals (Sweden)

    Guillermo A. SANCHEZ PRIETO

    2018-01-01

    Full Text Available The paper shows an academic debate model as a cooperative learning technique for teaching human resources at University. The general objective of this paper is to conclude if academic debate can be included in the category of cooperative learning. The Specific objective it is presenting a model to implement this technique. Thus the first part of the paper shows the concept of cooperative learning and its main characteristics. The second part presents the debate model believed to be labelled as cooperative learning. Last part concludes with the characteristics of the model that match different aspects or not of the cooperative learning.

  12. The evolutionary basis of human social learning.

    Science.gov (United States)

    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.

  13. The effects of Nicotinic Acid and Xanthinol Nicotinate on human memory in different categories of age

    NARCIS (Netherlands)

    Loriaux, S.M.; Deijen, J.B.; Orlebeke, J.F.; de Swart, J.H.

    1985-01-01

    The treatment effect of nicotinic acid and xanthinol nicotinate on human memory was compared with placebo in 96 healthy subjects. Forty-three subjects were young (35-45 years), 30 subjects middle aged (55-65 years) and 23 subjects were old aged (75-85 years). Pre- and post-treatment scores were

  14. An Enquiry concerning the nature of Conceptual Categories: a case-study on the social dimension of human cognition

    Directory of Open Access Journals (Sweden)

    John eStewart

    2014-06-01

    Full Text Available Cognitive Science, in all its guises, has not yet accorded any fundamental importance to the social dimension of human cognition. In order to illustrate the possibilities that have not so far been developed, this article seeks to pursue the idea, first put forward by Durkheim, that the major categories which render conceptual thought possible may actually have a social origin. Durkheim illustrated his thesis, convincingly enough, by examining the societies of Australian aborigines. The aim here is to extend this idea to cover the case of the conceptual categories underpinning modern Western science, as they developed historically first in Ancient Greece, and then at the Renaissance. These major non-empirical concepts include those of abstract Space (Euclidean space, perfectly homogeneous in all its dimensions; abstract Time (conceived as spatially linearized, with the possibility of imaginatively going back and forth; and a number of canonical logical categories (equality, abstract quantity, essential versus accidental properties, the continuous and the discontinuous, the transcendental…. Sohn-Rethel has proposed that the heart of the conceptual categories in question is to be found in an analysis of the exchange abstraction. This hypothesis will be fleshed out by examining the co-emergence of new social structures and new forms of conceptual thought in the course of historical evolution. This includes the Renaissance, which saw the emergence of both Capitalism and Modern Science; and on the contemporary situation, where the form of social life is dominated by financial speculation which goes together with the advent of automation in the processes of production. It is concluded that Cognitive Science, and in particular the nascent paradigm of Enaction, would do well to broaden its transdisciplinary scope to include the dimensions of sociology and anthropology.

  15. An enquiry concerning the nature of conceptual categories: a case-study on the social dimension of human cognition.

    Science.gov (United States)

    Stewart, John

    2014-01-01

    Cognitive Science, in all its guises, has not yet accorded any fundamental importance to the social dimension of human cognition. In order to illustrate the possibilities that have not so far been developed, this article seeks to pursue the idea, first put forward by Durkheim, that the major categories which render conceptual thought possible may actually have a social origin. Durkheim illustrated his thesis, convincingly enough, by examining the societies of Australian aborigines. The aim here is to extend this idea to cover the case of the conceptual categories underpinning modern Western science, as they developed historically first in Ancient Greece, and then at the Renaissance. These major non-empirical concepts include those of abstract Space (Euclidean space, perfectly homogeneous in all its dimensions); abstract Time (conceived as spatially linearized, with the possibility of imaginatively going back and forth); and a number of canonical logical categories (equality, abstract quantity, essential versus accidental properties, the continuous and the discontinuous, the transcendental…). Sohn-Rethel (1978) has proposed that the heart of the conceptual categories in question is to be found in an analysis of the exchange abstraction. This hypothesis will be fleshed out by examining the co-emergence of new social structures and new forms of conceptual thought in the course of historical evolution. This includes the Renaissance, which saw the emergence of both Capitalism and Modern Science; and on the contemporary situation, where the form of social life is dominated by financial speculation which goes together with the advent of automation in the processes of production. It is concluded that Cognitive Science, and in particular the nascent paradigm of Enaction, would do well to broaden its transdisciplinary scope to include the dimensions of sociology and anthropology.

  16. Human Spaceflight Conjunction Assessment: Lessons Learned

    Science.gov (United States)

    Smith, Jason T.

    2011-01-01

    This viewgraph presentation reviews the process of a human space flight conjunction assessment and lessons learned from the more than twelve years of International Space Station (ISS) operations. Also, the application of these lessons learned to a recent ISS conjunction assessment with object 84180 on July 16, 2009 is also presented.

  17. Decoding human mental states by whole-head EEG+fNIRS during category fluency task performance

    Science.gov (United States)

    Omurtag, Ahmet; Aghajani, Haleh; Onur Keles, Hasan

    2017-12-01

    Objective. Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system’s ability to decode mental states and compare it with its unimodal components. Approach. We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. Main results. EEG+fNIRS’s decoding accuracy was greater than that of its subsystems, partly due to the new type of neurovascular features made available by hybrid data. Significance. Availability of an accurate and practical decoding method has potential implications for medical diagnosis, brain-computer interface design, and neuroergonomics.

  18. Dental and Medical Students' Use and Perceptions of Learning Resources in a Human Physiology Course.

    Science.gov (United States)

    Tain, Monica; Schwartzstein, Richard; Friedland, Bernard; Park, Sang E

    2017-09-01

    The aim of this study was to determine the use and perceived utility of various learning resources available during the first-year Integrated Human Physiology course at the dental and medical schools at Harvard University. Dental and medical students of the Class of 2018 were surveyed anonymously online in 2015 regarding their use of 29 learning resources in this combined course. The learning resources had been grouped into four categories to discern frequency of use and perceived usefulness among the categories. The survey was distributed to 169 students, and 73 responded for a response rate of 43.2%. There was no significant difference among the learning resource categories in frequency of use; however, there was a statistically significant difference among categories in students' perceptions of usefulness. No correlation was found between frequency of use and perceived usefulness of each category. Students seemingly were not choosing the most useful resources for them. These results suggest that, in the current educational environment, where new technologies and self-directed learning are highly sought after, there remains a need for instructor-guided learning.

  19. Sleep spindle-related reactivation of category-specific cortical regions after learning face-scene associations

    DEFF Research Database (Denmark)

    Bergmann, Til O; Mölle, Matthias; Diedrichs, Jens

    2012-01-01

    Newly acquired declarative memory traces are believed to be reactivated during NonREM sleep to promote their hippocampo-neocortical transfer for long-term storage. Yet it remains a major challenge to unravel the underlying neuronal mechanisms. Using simultaneous electroencephalography (EEG......-coupled reactivation of brain regions representing the specific task stimuli was traced during subsequent NonREM sleep with EEG-informed fMRI. Relative to the control task, learning face-scene associations triggered a stronger combined activation of neocortical and hippocampal regions during subsequent sleep. Notably......) and functional magnetic resonance imaging (fMRI) recordings in humans, we show that sleep spindles play a key role in the reactivation of memory-related neocortical representations. On separate days, participants either learned face-scene associations or performed a visuomotor control task. Spindle...

  20. Dissociable Learning Processes Underlie Human Pain Conditioning.

    Science.gov (United States)

    Zhang, Suyi; Mano, Hiroaki; Ganesh, Gowrishankar; Robbins, Trevor; Seymour, Ben

    2016-01-11

    Pavlovian conditioning underlies many aspects of pain behavior, including fear and threat detection [1], escape and avoidance learning [2], and endogenous analgesia [3]. Although a central role for the amygdala is well established [4], both human and animal studies implicate other brain regions in learning, notably ventral striatum and cerebellum [5]. It remains unclear whether these regions make different contributions to a single aversive learning process or represent independent learning mechanisms that interact to generate the expression of pain-related behavior. We designed a human parallel aversive conditioning paradigm in which different Pavlovian visual cues probabilistically predicted thermal pain primarily to either the left or right arm and studied the acquisition of conditioned Pavlovian responses using combined physiological recordings and fMRI. Using computational modeling based on reinforcement learning theory, we found that conditioning involves two distinct types of learning process. First, a non-specific "preparatory" system learns aversive facial expressions and autonomic responses such as skin conductance. The associated learning signals-the learned associability and prediction error-were correlated with fMRI brain responses in amygdala-striatal regions, corresponding to the classic aversive (fear) learning circuit. Second, a specific lateralized system learns "consummatory" limb-withdrawal responses, detectable with electromyography of the arm to which pain is predicted. Its related learned associability was correlated with responses in ipsilateral cerebellar cortex, suggesting a novel computational role for the cerebellum in pain. In conclusion, our results show that the overall phenotype of conditioned pain behavior depends on two dissociable reinforcement learning circuits. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. Categorial Ontology of Complex Systems, Meta-Systems and Levels: The Emergence of Life, Human Consciousness and Society

    Directory of Open Access Journals (Sweden)

    James F. Glazebrook

    2010-06-01

    Full Text Available Relational structures of organisms and the human mind are naturally represented in terms of novel variable topology concepts, non-Abelian categories and Higher Dimensional Algebra{ relatively new concepts that would be defined in
    this tutorial paper. A unifying theme of local-to-global approaches to organismic development, evolution and human consciousness leads to novel patterns of relations that emerge in super- and ultra- complex systems in terms of compositions of local procedures [1]. The claim is defended in this paper that human consciousness is unique and should be viewed as an ultra-complex, global process of processes, at a meta-level not sub{summed by, but compatible with, human brain dynamics [2]-[5]. The emergence of consciousness and its existence
    are considered to be dependent upon an extremely complex structural and functional unit with an asymmetric network topology and connectivities{the human brain. However, the appearance of human consciousness is shown to be critically dependent upon societal co-evolution, elaborate language-symbolic communication and `virtual', higher dimensional, non{commutative processes involving separate space and time perceptions. Theories of the mind are approached from the theory of levels and ultra-complexity viewpoints that throw
    new light on previous semantic models in cognitive science. Anticipatory systems and complex causality at the top levels of reality are discussed in the context of psychology, sociology and ecology. A paradigm shift towards non-commutative, or more generally, non-Abelian theories of highly complex dynamics [6] is suggested to unfold now in physics, mathematics, life and cognitive sciences, thus leading to the realizations of higher dimensional algebras in neurosciences and psychology, as well as in human genomics, bioinformatics and interactomics. The presence of strange attractors in modern society dynamics gives rise to very serious concerns for the future

  2. T-category remains an important prognostic factor for oropharyngeal carcinoma in the era of human papillomavirus.

    Science.gov (United States)

    Mackenzie, P; Pryor, D; Burmeister, E; Foote, M; Panizza, B; Burmeister, B; Porceddu, S

    2014-10-01

    To determine prognostic factors for locoregional relapse (LRR), distant relapse and all-cause death in a contemporary cohort of locoregionally advanced oropharyngeal squamous cell carcinoma (OSCC) treated with definitive chemoradiotherapy or radiotherapy alone. OSCC patients treated with definitive radiotherapy between 2005 and 2010 were identified from a prospective head and neck database. Patient age, gender, smoking history, human papillomavirus (HPV) status, T- and N-category, lowest involved nodal level and gross tumour volume of the primary (GTV-p) and nodal (GTV-n) disease were analysed in relation to LRR, distant relapse and death by way of univariate and multivariate analysis. In total, 130 patients were identified, 88 HPV positive, with a median follow-up of 42 months. On multivariate analysis HPV status was a significant predictor of LRR (hazard ratio 0.15; 95% confidence interval 0.05-0.51) and death (hazard ratio 0.29; 95% confidence interval 0.14-0.59) but not distant relapse (hazard ratio 0.53, 95% confidence interval 0.22-1.27). Increasing T-category was associated with a higher risk of LRR (hazard ratio 1.80 for T3/4 versus T1/2; 95% confidence interval 1.08-2.99), death (hazard ratio 1.37, 95% confidence interval 1.06-1.77) and distant relapse (hazard ratio 1.35; 95% confidence interval 1.00-1.83). Increasing GTV-p was associated with increased risk of distant relapse and death. N3 disease and low neck nodes were significant for LRR, distant relapse and death on univariate analysis only. Tumour HPV status was the strongest predictor of LRR and death. T-category is more predictive of distant relapse and may provide additional prognostic value for LRR and death when accounting for HPV status. Copyright © 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  3. Perceptual Learning of Intonation Contour Categories in Adults and 9- to 11-Year-Old Children: Adults Are More Narrow-Minded

    Science.gov (United States)

    Kapatsinski, Vsevolod; Olejarczuk, Paul; Redford, Melissa A.

    2017-01-01

    We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns, whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of…

  4. Models as Relational Categories

    Science.gov (United States)

    Kokkonen, Tommi

    2017-11-01

    Model-based learning (MBL) has an established position within science education. It has been found to enhance conceptual understanding and provide a way for engaging students in authentic scientific activity. Despite ample research, few studies have examined the cognitive processes regarding learning scientific concepts within MBL. On the other hand, recent research within cognitive science has examined the learning of so-called relational categories. Relational categories are categories whose membership is determined on the basis of the common relational structure. In this theoretical paper, I argue that viewing models as relational categories provides a well-motivated cognitive basis for MBL. I discuss the different roles of models and modeling within MBL (using ready-made models, constructive modeling, and generative modeling) and discern the related cognitive aspects brought forward by the reinterpretation of models as relational categories. I will argue that relational knowledge is vital in learning novel models and in the transfer of learning. Moreover, relational knowledge underlies the coherent, hierarchical knowledge of experts. Lastly, I will examine how the format of external representations may affect the learning of models and the relevant relations. The nature of the learning mechanisms underlying students' mental representations of models is an interesting open question to be examined. Furthermore, the ways in which the expert-like knowledge develops and how to best support it is in need of more research. The discussion and conceptualization of models as relational categories allows discerning students' mental representations of models in terms of evolving relational structures in greater detail than previously done.

  5. Learning and motivation in the human striatum.

    Science.gov (United States)

    Shohamy, Daphna

    2011-06-01

    The past decade has seen a dramatic change in our understanding of the role of the striatum in behavior. Early perspectives emphasized a role for the striatum in habitual learning of stimulus-response associations and sequences of actions. Recent advances from human neuroimaging research suggest a broader role for the striatum in motivated learning. New findings demonstrate that the striatum represents multiple learning signals and highlight the contribution of the striatum across many cognitive domains and contexts. Recent findings also emphasize interactions between the striatum and other specialized brain systems for learning. Together, these findings suggest that the striatum contributes to a distributed network that learns to select actions based on their predicted value in order to optimize behavior. Copyright © 2011 Elsevier Ltd. All rights reserved.

  6. "Wide-Awake Learning": Integrative Learning and Humanities Education

    Science.gov (United States)

    Booth, Alan

    2011-01-01

    This article reviews the development of integrative learning and argues that it has an important role to play in broader conceptions of the undergraduate curriculum recently advanced in the UK. It suggests that such a focus might also provide arts and humanities educators with a hopeful prospect in difficult times: a means by which the distinctive…

  7. Resonant Cholinergic Dynamics in Cognitive and Motor Decision-Making: Attention, Category Learning, and Choice in Neocortex, Superior Colliculus, and Optic Tectum.

    Science.gov (United States)

    Grossberg, Stephen; Palma, Jesse; Versace, Massimiliano

    2015-01-01

    Freely behaving organisms need to rapidly calibrate their perceptual, cognitive, and motor decisions based on continuously changing environmental conditions. These plastic changes include sharpening or broadening of cognitive and motor attention and learning to match the behavioral demands that are imposed by changing environmental statistics. This article proposes that a shared circuit design for such flexible decision-making is used in specific cognitive and motor circuits, and that both types of circuits use acetylcholine to modulate choice selectivity. Such task-sensitive control is proposed to control thalamocortical choice of the critical features that are cognitively attended and that are incorporated through learning into prototypes of visual recognition categories. A cholinergically-modulated process of vigilance control determines if a recognition category and its attended features are abstract (low vigilance) or concrete (high vigilance). Homologous neural mechanisms of cholinergic modulation are proposed to focus attention and learn a multimodal map within the deeper layers of superior colliculus. This map enables visual, auditory, and planned movement commands to compete for attention, leading to selection of a winning position that controls where the next saccadic eye movement will go. Such map learning may be viewed as a kind of attentive motor category learning. The article hereby explicates a link between attention, learning, and cholinergic modulation during decision making within both cognitive and motor systems. Homologs between the mammalian superior colliculus and the avian optic tectum lead to predictions about how multimodal map learning may occur in the mammalian and avian brain and how such learning may be modulated by acetycholine.

  8. Resonant cholinergic dynamics in cognitive and motor decision-making:Attention, category learning, and choice in neocortex, superior colliculus, and optic tectum

    Directory of Open Access Journals (Sweden)

    Stephen eGrossberg

    2016-01-01

    Full Text Available Freely behaving organisms need to rapidly calibrate their perceptual, cognitive, and motor decisions based on continuously changing environmental conditions. These plastic changes include sharpening or broadening of cognitive and motor attention and learning to match the behavioral demands that are imposed by changing environmental statistics. This article proposes that a shared circuit design for such flexible decision-making is used in specific cognitive and motor circuits, and that both types of circuits use acetylcholine to modulate choice selectivity. Such task-sensitive control is proposed to control thalamocortical choice of the critical features that are cognitively attended and that are incorporated through learning into prototypes of visual recognition categories. A cholinergically-modulated process of vigilance control determines if a recognition category and its attended features are abstract (low vigilance or concrete (high vigilance. Homologous neural mechanisms of cholinergic modulation are proposed to focus attention and learn a multimodal map within the deeper layers of superior colliculus. This map enables visual, auditory, and planned movement commands to compete for attention, leading to selection of a winning position that controls where the next saccadic eye movement will go. Such map learning may be viewed as a kind of attentive motor category learning. The article hereby explicates a link between attention, learning, and cholinergic modulation during decision making within both cognitive and motor systems. Homologs between the mammalian superior colliculus and the avian optic tectum lead to predictions about how multimodal map learning may occur in the avian brain and how such learning may be modulated by acetycholine.

  9. Artificial agents learning human fairness

    NARCIS (Netherlands)

    Jong, de S.; Tuyls, K.P.; Verbeeck, K.; Padgham, xx; Parkes, xx

    2008-01-01

    Recent advances in technology allow multi-agent systems to be deployed in cooperation with or as a service for humans. Typically, those systems are designed assuming individually rational agents, according to the principles of classical game theory. However, research in the field of behavioral

  10. Sequential causal learning in humans and rats

    NARCIS (Netherlands)

    Lu, H.; Rojas, R.R.; Beckers, T.; Yuille, A.; Love, B.C.; McRae, K.; Sloutsky, V.M.

    2008-01-01

    Recent experiments (Beckers, De Houwer, Pineño, & Miller, 2005;Beckers, Miller, De Houwer, & Urushihara, 2006) have shown that pretraining with unrelated cues can dramatically influence the performance of humans in a causal learning paradigm and rats in a standard Pavlovian conditioning paradigm.

  11. Modeling human learning involved in car driving

    NARCIS (Netherlands)

    Wewerinke, P.H.

    1994-01-01

    In this paper, car driving is considered at the level of human tracking and maneuvering in the context of other traffic. A model analysis revealed the most salient features determining driving performance and safety. Learning car driving is modelled based on a system theoretical approach and based

  12. Social learning in humans and other animals.

    Directory of Open Access Journals (Sweden)

    Jean-François eGariépy

    2014-03-01

    Full Text Available Decisions made by individuals can be influenced by what others think and do. Social learning includes a wide array of behaviors such as imitation, observational learning of novel foraging techniques, peer or parental influences on individual preferences, as well as outright teaching. These processes are believed to underlie an important part of cultural variation among human populations and may also explain intraspecific variation in behavior between geographically distinct populations of animals. Recent neurobiological studies have begun to uncover the neural basis of social learning. Here we review experimental evidence from the past few decades showing that social learning is a widespread set of skills present in multiple animal species. In mammals, the temporoparietal junction, the dorsomedial and dorsolateral prefrontal cortex, as well as the anterior cingulate gyrus, appear to play critical roles in social learning. Birds, fish and insects also learn from others, but the underlying neural mechanisms remain poorly understood. We discuss the evolutionary implications of these findings and highlight the importance of emerging animal models that permit precise modification of neural circuit function for elucidating the neural basis of social learning.

  13. Multi-task learning with group information for human action recognition

    Science.gov (United States)

    Qian, Li; Wu, Song; Pu, Nan; Xu, Shulin; Xiao, Guoqiang

    2018-04-01

    Human action recognition is an important and challenging task in computer vision research, due to the variations in human motion performance, interpersonal differences and recording settings. In this paper, we propose a novel multi-task learning framework with group information (MTL-GI) for accurate and efficient human action recognition. Specifically, we firstly obtain group information through calculating the mutual information according to the latent relationship between Gaussian components and action categories, and clustering similar action categories into the same group by affinity propagation clustering. Additionally, in order to explore the relationships of related tasks, we incorporate group information into multi-task learning. Experimental results evaluated on two popular benchmarks (UCF50 and HMDB51 datasets) demonstrate the superiority of our proposed MTL-GI framework.

  14. A Neurocomputational Model of Dopamine and Prefrontal-Striatal Interactions during Multicue Category Learning by Parkinson Patients

    Science.gov (United States)

    Moustafa, Ahmed A.; Gluck, Mark A.

    2011-01-01

    Most existing models of dopamine and learning in Parkinson disease (PD) focus on simulating the role of basal ganglia dopamine in reinforcement learning. Much data argue, however, for a critical role for prefrontal cortex (PFC) dopamine in stimulus selection in attentional learning. Here, we present a new computational model that simulates…

  15. Accounting for individual differences in human associative learning

    OpenAIRE

    Byrom, Nicola C.

    2013-01-01

    Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility ...

  16. Organizational Categories as Viewing Categories

    OpenAIRE

    Mik-Meyer, Nanna

    2005-01-01

    This paper explores how two Danish rehabilitation organizations textual guidelines for assessment of clients’ personality traits influence the actual evaluation of clients. The analysis will show how staff members produce institutional identities corresponding to organizational categories, which very often have little or no relevance for the clients evaluated. The goal of the article is to demonstrate how the institutional complex that frames the work of the organizations produces the client ...

  17. From Shared Contexts to Syntactic Categories: The Role of Distributional Information in Learning Linguistic Form-Classes

    Science.gov (United States)

    Reeder, Patricia A.; Newport, Elissa L.; Aslin, Richard N.

    2013-01-01

    A fundamental component of language acquisition involves organizing words into grammatical categories. Previous literature has suggested a number of ways in which this categorization task might be accomplished. Here we ask whether the patterning of the words in a corpus of linguistic input ("distributional information") is sufficient, along with a…

  18. Proactive Interference in Human Predictive Learning

    OpenAIRE

    Castro, Leyre; Ortega, Nuria; Matute, Helena

    2002-01-01

    The impairment in responding to a secondly trained association because of the prior training of another (i.e., proactive interference) is a well-established effect in human and animal research, and it has been demonstrated in many paradigms. However, learning theories have been concerned with proactive interference only when the competing stimuli have been presented in compound at some moment of the training phase. In this experiment we investigated the possibility of proactive interference b...

  19. Effective post-literacy learning: A question of a national human resource strategy

    Science.gov (United States)

    Ahmed, Manzoor

    1989-12-01

    Initial literacy courses must be followed by opportunities for consolidating the mechanics of literacy skills and practical application of three skills in life. Experience has shown that these `post-literacy' objectives can be achieved, not by a second stage of the literacy course, but by a range of opportunities for learning and application of learning through a network of continuing education opportunities geared to the diverse needs and circumstances of different categories of neo-literates. A taxonomy of learner categories and learning needs is seen as a basis for planning and supporting the network of post-literacy learning. Examples from China, India and Thailand demonstrate the importance of recognizing the continuity of literacy and post-literacy efforts, the need for commitment of resources for this continuum of learning, the role of an organizational structure to deal with this continuum in a coordinated way, and the value of a comprehensive range of learning opportunities for neo-literates. A necessary condition for success in building a network of continuing learning opportunities and contributing to the creation of a `learning society' is to make human resource development the core of national development. It is argued that the scope and dimensions of post-literacy continuing education are integrally linked with the goal of mass basic education and ultimately with the vision of a `learning society'. Such a vision can be a reality only with a serious human resource development focus in national development that will permit the necessary mobilization of resources, the coordination of sectors of government and society and the generation of popular enthusiasm. A radical or an incremental approach can be taken to move towards the primacy of a human resource strategy in national development. In either case, a functioning coordination and support mechanism has to be developed for the key elements of mass basic education including post-literacy learning.

  20. Medical humanities: a closer look at learning.

    Science.gov (United States)

    Patterson, A; Sharek, D; Hennessy, M; Phillips, M; Schofield, S

    2016-06-01

    The inclusion of medical humanities with medical curricula is a question that has been the focus of attention for many within the evolving field. This study addressed the question from a medical education perspective and aimed to investigate what students at Trinity College Dublin learned from participating in a short medical humanities student-selected module in their first year of an undergraduate medical programme. A total of 156 students provided a written reflection on a memorable event that occurred during their student-selected module. The reflections were analysed using the Reflection Evaluation for Learners' Enhanced Competencies Tool (REFLECT) and through qualitative thematic analysis of the written reflections. Evidence of learning from the REFLECT quantitative analysis showed that 50% of students displayed higher levels of reflection when describing their experience. The reflection content analysis supported the heterogeneous nature of learning outcome for students, with evidence to support the idea that the module provided opportunities for students to explore their beliefs, ideas and feelings regarding a range of areas outside their current experience or world view, to consider the views of others that they may have not previously been aware of, to reflect on their current views, and to consider their future professional practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  1. Accounting for individual differences in human associative learning.

    Science.gov (United States)

    Byrom, Nicola C

    2013-09-04

    Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility in learning caused by external factors, there has been limited work considering how to model the influence of dispositional factors. This review looks at the range of individual differences in human associative learning that have been explored and the attempts to account for, and model, this flexibility. To fully understand human associative learning, further research needs to attend to the causes of variation in human learning.

  2. Accounting for Individual Differences in Human Associative Learning.

    Directory of Open Access Journals (Sweden)

    Nicola C Byrom

    2013-09-01

    Full Text Available Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility in learning caused by external factors, there has been limited work considering how to model the influence of dispositional factors. This review looks at the range of individual differences in human associative learning that have been explored and the attempts to account for, and model, this flexibility. To fully understand human associative learning, further research needs to attend to the causes of variation in human learning.

  3. ROBOT LEARNING OF OBJECT MANIPULATION TASK ACTIONS FROM HUMAN DEMONSTRATIONS

    Directory of Open Access Journals (Sweden)

    Maria Kyrarini

    2017-08-01

    Full Text Available Robot learning from demonstration is a method which enables robots to learn in a similar way as humans. In this paper, a framework that enables robots to learn from multiple human demonstrations via kinesthetic teaching is presented. The subject of learning is a high-level sequence of actions, as well as the low-level trajectories necessary to be followed by the robot to perform the object manipulation task. The multiple human demonstrations are recorded and only the most similar demonstrations are selected for robot learning. The high-level learning module identifies the sequence of actions of the demonstrated task. Using Dynamic Time Warping (DTW and Gaussian Mixture Model (GMM, the model of demonstrated trajectories is learned. The learned trajectory is generated by Gaussian mixture regression (GMR from the learned Gaussian mixture model.  In online working phase, the sequence of actions is identified and experimental results show that the robot performs the learned task successfully.

  4. Autonomous development and learning in artificial intelligence and robotics: Scaling up deep learning to human-like learning.

    Science.gov (United States)

    Oudeyer, Pierre-Yves

    2017-01-01

    Autonomous lifelong development and learning are fundamental capabilities of humans, differentiating them from current deep learning systems. However, other branches of artificial intelligence have designed crucial ingredients towards autonomous learning: curiosity and intrinsic motivation, social learning and natural interaction with peers, and embodiment. These mechanisms guide exploration and autonomous choice of goals, and integrating them with deep learning opens stimulating perspectives.

  5. Food category consumption and obesity prevalence across countries: an application of Machine Learning method to big data analysis

    Science.gov (United States)

    Dunstan, Jocelyn; Fallah-Fini, Saeideh; Nau, Claudia; Glass, Thomas; Global Obesity Prevention Center Team

    The applications of sophisticated mathematical and numerical tools in public health has been demonstrated to be useful in predicting the outcome of public intervention as well as to study, for example, the main causes of obesity without doing experiments with the population. In this project we aim to understand which kind of food consumed in different countries over time best defines the rate of obesity in those countries. The use of Machine Learning is particularly useful because we do not need to create a hypothesis and test it with the data, but instead we learn from the data to find the groups of food that best describe the prevalence of obesity.

  6. Clustering Patterns of Engagement in Massive Open Online Courses (MOOCs): The Use of Learning Analytics to Reveal Student Categories

    Science.gov (United States)

    Khalil, Mohammad; Ebner, Martin

    2017-01-01

    Massive Open Online Courses (MOOCs) are remote courses that excel in their students' heterogeneity and quantity. Due to the peculiarity of being massiveness, the large datasets generated by MOOC platforms require advanced tools and techniques to reveal hidden patterns for purposes of enhancing learning and educational behaviors. This publication…

  7. Amplifying human ability through autonomics and machine learning in IMPACT

    Science.gov (United States)

    Dzieciuch, Iryna; Reeder, John; Gutzwiller, Robert; Gustafson, Eric; Coronado, Braulio; Martinez, Luis; Croft, Bryan; Lange, Douglas S.

    2017-05-01

    Amplifying human ability for controlling complex environments featuring autonomous units can be aided by learned models of human and system performance. In developing a command and control system that allows a small number of people to control a large number of autonomous teams, we employ an autonomics framework to manage the networks that represent mission plans and the networks that are composed of human controllers and their autonomous assistants. Machine learning allows us to build models of human and system performance useful for monitoring plans and managing human attention and task loads. Machine learning also aids in the development of tactics that human supervisors can successfully monitor through the command and control system.

  8. Sensorimotor learning configures the human mirror system.

    Science.gov (United States)

    Catmur, Caroline; Walsh, Vincent; Heyes, Cecilia

    2007-09-04

    Cells in the "mirror system" fire not only when an individual performs an action but also when one observes the same action performed by another agent [1-4]. The mirror system, found in premotor and parietal cortices of human and monkey brains, is thought to provide the foundation for social understanding and to enable the development of theory of mind and language [5-9]. However, it is unclear how mirror neurons acquire their mirror properties -- how they derive the information necessary to match observed with executed actions [10]. We address this by showing that it is possible to manipulate the selectivity of the human mirror system, and thereby make it operate as a countermirror system, by giving participants training to perform one action while observing another. Before this training, participants showed event-related muscle-specific responses to transcranial magnetic stimulation over motor cortex during observation of little- and index-finger movements [11-13]. After training, this normal mirror effect was reversed. These results indicate that the mirror properties of the mirror system are neither wholly innate [14] nor fixed once acquired; instead they develop through sensorimotor learning [15, 16]. Our findings indicate that the human mirror system is, to some extent, both a product and a process of social interaction.

  9. Learnable Classes of Categorial Grammars.

    Science.gov (United States)

    Kanazawa, Makoto

    Learnability theory is an attempt to illuminate the concept of learnability using a mathematical model of learning. Two models of learning of categorial grammars are examined here: the standard model, in which sentences presented to the learner are flat strings of words, and one in which sentences are presented in the form of functor-argument…

  10. Auditory and phonetic category formation

    NARCIS (Netherlands)

    Goudbeek, Martijn; Cutler, A.; Smits, R.; Swingley, D.; Cohen, Henri; Lefebvre, Claire

    2017-01-01

    Among infants' first steps in language acquisition is learning the relevant contrasts of the language-specific phonemic repertoire. This learning is viewed as the formation of categories in a multidimensional psychophysical space. Research in the visual modality has shown that for adults, some kinds

  11. Basic category theory

    CERN Document Server

    Leinster, Tom

    2014-01-01

    At the heart of this short introduction to category theory is the idea of a universal property, important throughout mathematics. After an introductory chapter giving the basic definitions, separate chapters explain three ways of expressing universal properties: via adjoint functors, representable functors, and limits. A final chapter ties all three together. The book is suitable for use in courses or for independent study. Assuming relatively little mathematical background, it is ideal for beginning graduate students or advanced undergraduates learning category theory for the first time. For each new categorical concept, a generous supply of examples is provided, taken from different parts of mathematics. At points where the leap in abstraction is particularly great (such as the Yoneda lemma), the reader will find careful and extensive explanations. Copious exercises are included.

  12. Learned helplessness or expectancy-value? A psychological model for describing the experiences of different categories of unemployed people.

    Science.gov (United States)

    García Rodríguez, Y

    1997-06-01

    Various studies have explored the relationships between unemployment and expectation of success, commitment to work, motivation, causal attributions, self-esteem and depression. A model is proposed that assumes the relationships between these variables are moderated by (a) whether or not the unemployed individual is seeking a first job and (b) age. It is proposed that for the unemployed who are seeking their first job (seekers) the relationships among these variables will be consistent with expectancy-value theory, but for those who have had a previous job (losers), the relationships will be more consistent with learned helplessness theory. It is further assumed that within this latter group the young losers will experience "universal helplessness" whereas the adult losers will experience "personal helplessness".

  13. Visual memory needs categories

    OpenAIRE

    Olsson, Henrik; Poom, Leo

    2005-01-01

    Capacity limitations in the way humans store and process information in working memory have been extensively studied, and several memory systems have been distinguished. In line with previous capacity estimates for verbal memory and memory for spatial information, recent studies suggest that it is possible to retain up to four objects in visual working memory. The objects used have typically been categorically different colors and shapes. Because knowledge about categories is stored in long-t...

  14. A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers.

    Science.gov (United States)

    Romo-Bucheli, David; Janowczyk, Andrew; Gilmore, Hannah; Romero, Eduardo; Madabhushi, Anant

    2017-06-01

    The treatment and management of early stage estrogen receptor positive (ER+) breast cancer is hindered by the difficulty in identifying patients who require adjuvant chemotherapy in contrast to those that will respond to hormonal therapy. To distinguish between the more and less aggressive breast tumors, which is a fundamental criterion for the selection of an appropriate treatment plan, Oncotype DX (ODX) and other gene expression tests are typically employed. While informative, these gene expression tests are expensive, tissue destructive, and require specialized facilities. Bloom-Richardson (BR) grade, the common scheme employed in breast cancer grading, has been shown to be correlated with the Oncotype DX risk score. Unfortunately, studies have also shown that the BR grade determined experiences notable inter-observer variability. One of the constituent categories in BR grading is the mitotic index. The goal of this study was to develop a deep learning (DL) classifier to identify mitotic figures from whole slides images of ER+ breast cancer, the hypothesis being that the number of mitoses identified by the DL classifier would correlate with the corresponding Oncotype DX risk categories. The mitosis detector yielded an average F-score of 0.556 in the AMIDA mitosis dataset using a 6-fold validation setup. For a cohort of 174 whole slide images with early stage ER+ breast cancer for which the corresponding Oncotype DX score was available, the distributions of the number of mitoses identified by the DL classifier was found to be significantly different between the high vs low Oncotype DX risk groups (P machine classifier trained to separate low/high Oncotype DX risk categories using the mitotic count determined by the DL classifier yielded a 83.19% classification accuracy. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

  15. Editorial: Technology for higher education, adult learning and human performance

    OpenAIRE

    Minhong Wang; Chi-Cheng Chang; Feng Wu

    2013-01-01

    This special issue is dedicated to technology-enabled approaches for improving higher education, adult learning, and human performance. Improvement of learning and human development for sustainable development has been recognized as a key strategy for individuals, institutions, and organizations to strengthen their competitive advantages. It becomes crucial to help adult learners and knowledge workers to improve their self-directed and life-long learning capabilities. Meanwhile, advances in t...

  16. Learning-dependent plasticity in human auditory cortex during appetitive operant conditioning.

    Science.gov (United States)

    Puschmann, Sebastian; Brechmann, André; Thiel, Christiane M

    2013-11-01

    Animal experiments provide evidence that learning to associate an auditory stimulus with a reward causes representational changes in auditory cortex. However, most studies did not investigate the temporal formation of learning-dependent plasticity during the task but rather compared auditory cortex receptive fields before and after conditioning. We here present a functional magnetic resonance imaging study on learning-related plasticity in the human auditory cortex during operant appetitive conditioning. Participants had to learn to associate a specific category of frequency-modulated tones with a reward. Only participants who learned this association developed learning-dependent plasticity in left auditory cortex over the course of the experiment. No differential responses to reward predicting and nonreward predicting tones were found in auditory cortex in nonlearners. In addition, learners showed similar learning-induced differential responses to reward-predicting and nonreward-predicting tones in the ventral tegmental area and the nucleus accumbens, two core regions of the dopaminergic neurotransmitter system. This may indicate a dopaminergic influence on the formation of learning-dependent plasticity in auditory cortex, as it has been suggested by previous animal studies. Copyright © 2012 Wiley Periodicals, Inc.

  17. How categories come to matter

    DEFF Research Database (Denmark)

    Leahu, Lucian; Cohn, Marisa; March, Wendy

    2013-01-01

    In a study of users' interactions with Siri, the iPhone personal assistant application, we noticed the emergence of overlaps and blurrings between explanatory categories such as "human" and "machine". We found that users work to purify these categories, thus resolving the tensions related to the ...... initial data analysis, due to our own forms of latent purification, and outline the particular analytic techniques that helped lead to this discovery. We thus provide an illustrative case of how categories come to matter in HCI research and design.......In a study of users' interactions with Siri, the iPhone personal assistant application, we noticed the emergence of overlaps and blurrings between explanatory categories such as "human" and "machine". We found that users work to purify these categories, thus resolving the tensions related...

  18. Human capital and human resource management to achieve ambidextrous learning: A structural perspective

    Directory of Open Access Journals (Sweden)

    Mirta Diaz-Fernandez

    2017-01-01

    Full Text Available Organisational learning has become increasingly important for strategic renewal. Ambidextrous organisations are especially successful in the current environment, where firms are required to be efficient and adapt to change. Using a structural approach, this study discusses arguments about the nature of ambidexterity and identifies the kinds of human capital that better support specific learning types and HRM practices suited to these components of human capital. Results highlight learning differences between marketing and production units, as well as different HRM practices and human capital orientations. This study points out that human capital mediates between HRM practices and learning.

  19. Stimulus Dependency of Object-Evoked Responses in Human Visual Cortex: An Inverse Problem for Category Specificity

    Science.gov (United States)

    Graewe, Britta; De Weerd, Peter; Farivar, Reza; Castelo-Branco, Miguel

    2012-01-01

    Many studies have linked the processing of different object categories to specific event-related potentials (ERPs) such as the face-specific N170. Despite reports showing that object-related ERPs are influenced by visual stimulus features, there is consensus that these components primarily reflect categorical aspects of the stimuli. Here, we re-investigated this idea by systematically measuring the effects of visual feature manipulations on ERP responses elicited by both structure-from-motion (SFM)-defined and luminance-defined object stimuli. SFM objects elicited a novel component at 200–250 ms (N250) over parietal and posterior temporal sites. We found, however, that the N250 amplitude was unaffected by restructuring SFM stimuli into meaningless objects based on identical visual cues. This suggests that this N250 peak was not uniquely linked to categorical aspects of the objects, but is strongly determined by visual stimulus features. We provide strong support for this hypothesis by parametrically manipulating the depth range of both SFM- and luminance-defined object stimuli and showing that the N250 evoked by SFM stimuli as well as the well-known N170 to static faces were sensitive to this manipulation. Importantly, this effect could not be attributed to compromised object categorization in low depth stimuli, confirming a strong impact of visual stimulus features on object-related ERP signals. As ERP components linked with visual categorical object perception are likely determined by multiple stimulus features, this creates an interesting inverse problem when deriving specific perceptual processes from variations in ERP components. PMID:22363479

  20. Associative learning and the control of human dietary behavior.

    Science.gov (United States)

    Brunstrom, Jeffrey M

    2007-07-01

    Most of our food likes and disliked are learned. Relevant forms of associative learning have been identified in animals. However, observations of the same associative processes are relatively scarce in humans. The first section of this paper outlines reasons why this might be the case. Emphasis is placed on recent research exploring individual differences and the importance or otherwise of hunger and contingency awareness. The second section briefly considers the effect of learning on meal size, and the author revisits the question of how learned associations might come to influence energy intake in humans.

  1. Building phonetic categories: an argument for the role of sleep

    Directory of Open Access Journals (Sweden)

    F. Sayako Earle

    2014-10-01

    Full Text Available The current review provides specific predictions for the role of sleep-mediated memory consolidation in the formation of new speech sound representations. Specifically, this discussion will highlight selected literature on the different ideas concerning category representation in speech, followed by a broad overview of memory consolidation and how it relates to human behavior, as relevant to speech/perceptual learning. In combining behavioral and physiological accounts from animal models with insights from the human consolidation literature on auditory skill/word learning, we are in the early stages of understanding how the transfer of experiential information between brain structures during sleep manifests in changes to online perception. Arriving at the conclusion that this process is crucial in perceptual learning and the formation of novel categories, further speculation yields the adjacent claim that the habitual disruption in this process leads to impoverished quality in the representation of speech sounds.

  2. Human Rights between Political Identity and Historical Category. Czechoslovakia and East Central Europe in a Global Context

    Czech Academy of Sciences Publication Activity Database

    Kopeček, Michal

    2016-01-01

    Roč. 4, č. 1 (2016), s. 5-18 ISSN 2336-3142 Institutional support: RVO:68378114 Keywords : human rights * history * socialism Subject RIV: AB - History OBOR OECD: History (history of science and technology to be 6.3, history of specific sciences to be under the respective headings) http://www.usd.cas.cz/casopis/czech-journal-of-contemporary-history-4-2016/

  3. Theorising Learning and Nature: Post-Human Possibilities and Problems

    Science.gov (United States)

    Quinn, Jocey

    2013-01-01

    In their predominantly theoretical turn to the material, post-humanist feminists often focus on "nature", arguing that the nature/culture binary has collapsed and that fixed distinctions between human and non-human spheres no longer hold. Conversely, outdoor learning sees nature as a space where humans act and has been more concerned…

  4. Libertarianism & Category-Mistake

    Directory of Open Access Journals (Sweden)

    Carlos G. Patarroyo G.

    2009-12-01

    Full Text Available This paper offers a defense against two accusations according to which libertarianism incurs in a category-mistake. The philosophy of Gilbert Ryle will be used to explain the reasons which ground these accusations. Further, it will be shown why, although certain sorts of libertarianism based on agent-causation or Cartesian dualism incur in these mistakes, there is at least one version of libertarianism to which this criticism does not necessarily apply: the version that seeks to find in physical indeterminism the grounding of human free will.

  5. Mobile human-computer interaction perspective on mobile learning

    CSIR Research Space (South Africa)

    Botha, Adèle

    2010-10-01

    Full Text Available Applying a Mobile Human Computer Interaction (MHCI) view to the domain of education using Mobile Learning (Mlearning), the research outlines its understanding of the influences and effects of different interactions on the use of mobile technology...

  6. Prevention of Learned Helplessness in Humans.

    Science.gov (United States)

    Klee, Steven; Meyer, Robert G.

    1979-01-01

    Explored prevention of learned helplessness through the use of thermal biofeedback training and varied explanations of performance. It was found that only in the biofeedback group receiving accurate feedback was there any prevention of the subsequent development of learned helplessness behavior. (Author)

  7. Debriefing after Human Patient Simulation and Nursing Students' Learning

    Science.gov (United States)

    Benhuri, Gloria

    2014-01-01

    Human Patient Simulation (HPS) exercises with life-like computerized manikins provide clinical experiences for nursing students in a safe environment followed by debriefing that promotes learning. Quantitative research in techniques to support learning from debriefing is limited. The purpose of the quantitative quasi-experimental study using a…

  8. Using human brain activity to guide machine learning.

    Science.gov (United States)

    Fong, Ruth C; Scheirer, Walter J; Cox, David D

    2018-03-29

    Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human brain has long served as a source of inspiration for machine learning, little effort has been made to directly use data collected from working brains as a guide for machine learning algorithms. Here we demonstrate a new paradigm of "neurally-weighted" machine learning, which takes fMRI measurements of human brain activity from subjects viewing images, and infuses these data into the training process of an object recognition learning algorithm to make it more consistent with the human brain. After training, these neurally-weighted classifiers are able to classify images without requiring any additional neural data. We show that our neural-weighting approach can lead to large performance gains when used with traditional machine vision features, as well as to significant improvements with already high-performing convolutional neural network features. The effectiveness of this approach points to a path forward for a new class of hybrid machine learning algorithms which take both inspiration and direct constraints from neuronal data.

  9. Human resource management and learning for innovation: pharmaceuticals in Mexico

    OpenAIRE

    Santiago-Rodriguez, Fernando

    2010-01-01

    This paper investigates the influence of human resource management on learning from internal and external sources of knowledge. Learning for innovation is a key ingredient of catching-up processes. The analysis builds on survey data about pharmaceutical firms in Mexico. Results show that the influence of human resource management is contingent on the knowledge flows and innovation goals pursued by the firm. Practices such as training-- particularly from external partners; and remuneration for...

  10. A machine learning model with human cognitive biases capable of learning from small and biased datasets.

    Science.gov (United States)

    Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro

    2018-05-09

    Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.

  11. Learning and Retention through Predictive Inference and Classification

    Science.gov (United States)

    Sakamoto, Yasuaki; Love, Bradley C.

    2010-01-01

    Work in category learning addresses how humans acquire knowledge and, thus, should inform classroom practices. In two experiments, we apply and evaluate intuitions garnered from laboratory-based research in category learning to learning tasks situated in an educational context. In Experiment 1, learning through predictive inference and…

  12. Consistent individual differences in human social learning strategies.

    Science.gov (United States)

    Molleman, Lucas; van den Berg, Pieter; Weissing, Franz J

    2014-04-04

    Social learning has allowed humans to build up extensive cultural repertoires, enabling them to adapt to a wide variety of environmental and social conditions. However, it is unclear which social learning strategies people use, especially in social contexts where their payoffs depend on the behaviour of others. Here we show experimentally that individuals differ in their social learning strategies and that they tend to employ the same learning strategy irrespective of the interaction context. Payoff-based learners focus on their peers' success, while decision-based learners disregard payoffs and exclusively focus on their peers' past behaviour. These individual differences may be of considerable importance for cultural evolution. By means of a simple model, we demonstrate that groups harbouring individuals with different learning strategies may be faster in adopting technological innovations and can be more efficient through successful role differentiation. Our study highlights the importance of individual variation for human interactions and sheds new light on the dynamics of cultural evolution.

  13. Do domestic dogs learn words based on humans' referential behaviour?

    Directory of Open Access Journals (Sweden)

    Sebastian Tempelmann

    Full Text Available Some domestic dogs learn to comprehend human words, although the nature and basis of this learning is unknown. In the studies presented here we investigated whether dogs learn words through an understanding of referential actions by humans rather than simple association. In three studies, each modelled on a study conducted with human infants, we confronted four word-experienced dogs with situations involving no spatial-temporal contiguity between the word and the referent; the only available cues were referential actions displaced in time from exposure to their referents. We found that no dogs were able to reliably link an object with a label based on social-pragmatic cues alone in all the tests. However, one dog did show skills in some tests, possibly indicating an ability to learn based on social-pragmatic cues.

  14. Haptic Human-Human Interaction Through a Compliant Connection Does Not Improve Motor Learning in a Force Field

    NARCIS (Netherlands)

    Beckers, Niek; Keemink, Arvid; van Asseldonk, Edwin; van der Kooij, Herman; Prattichizzo, Domenico; Shinoda, Hiroyuki; Tan, Hong Z.; Ruffaldi, Emanuele; Frisoli, Antonio

    2018-01-01

    Humans have a natural ability to haptically interact with other humans, for instance during physically assisting a child to learn how to ride a bicycle. A recent study has shown that haptic human-human interaction can improve individual motor performance and motor learning rate while learning to

  15. A Human Capabilities Framework for Evaluating Student Learning

    Science.gov (United States)

    Walker, Melanie

    2008-01-01

    This paper proposes a human capabilities approach for evaluating student learning and the social and pedagogical arrangements that support equality in capabilities for all students. It outlines the focus on valuable beings and doings in the capability approach developed by Amartya Sen, and Martha Nussbaum's capabilities focus on human flourishing.…

  16. The Law Review Approach: What the Humanities Can Learn

    Science.gov (United States)

    Mendenhall, Allen

    2013-01-01

    Readers of this journal probably know how the peer review process works in the humanities disciplines and at various journals. Therefore the author explains how the law review process generally works and then what the humanities can learn and borrow from the law review process. He ends by advocating for a hybrid law review/peer review approach to…

  17. Apprenticeship Learning: Learning to Schedule from Human Experts

    Science.gov (United States)

    2016-06-09

    identified by the heuristic . A spectrum of problems (i.e. traveling salesman, job-shop scheduling, multi-vehicle routing) was represented , as task locations...caus- ing the codification of this knowledge to become labori- ous. We propose a new approach for capturing domain- expert heuristics through a...demonstrate that this approach accu- rately learns multi-faceted heuristics on both a synthetic data set incorporating job-shop scheduling and vehicle

  18. Data categories for marine planning

    Science.gov (United States)

    Lightsom, Frances L.; Cicchetti, Giancarlo; Wahle, Charles M.

    2015-01-01

    The U.S. National Ocean Policy calls for a science- and ecosystem-based approach to comprehensive planning and management of human activities and their impacts on America’s oceans. The Ocean Community in Data.gov is an outcome of 2010–2011 work by an interagency working group charged with designing a national information management system to support ocean planning. Within the working group, a smaller team developed a list of the data categories specifically relevant to marine planning. This set of categories is an important consensus statement of the breadth of information types required for ocean planning from a national, multidisciplinary perspective. Although the categories were described in a working document in 2011, they have not yet been fully implemented explicitly in online services or geospatial metadata, in part because authoritative definitions were not created formally. This document describes the purpose of the data categories, provides definitions, and identifies relations among the categories and between the categories and external standards. It is intended to be used by ocean data providers, managers, and users in order to provide a transparent and consistent framework for organizing and describing complex information about marine ecosystems and their connections to humans.

  19. Management Education: Reflective Learning on Human Interaction

    Science.gov (United States)

    Clydesdale, Greg

    2016-01-01

    Purpose: This paper aims to describe an attempt to develop a more effective technique to teach self-awareness and relationship skills. Design/methodology/approach: A journal is used in combination with a model of human nature. The model lists human characteristics that the management trainee must identify in themselves and others they interact…

  20. Learning Human Aspects of Collaborative Software Development

    Science.gov (United States)

    Hadar, Irit; Sherman, Sofia; Hazzan, Orit

    2008-01-01

    Collaboration has become increasingly widespread in the software industry as systems have become larger and more complex, adding human complexity to the technological complexity already involved in developing software systems. To deal with this complexity, human-centric software development methods, such as Extreme Programming and other agile…

  1. Learning to Segment Human by Watching YouTube.

    Science.gov (United States)

    Liang, Xiaodan; Wei, Yunchao; Chen, Yunpeng; Shen, Xiaohui; Yang, Jianchao; Lin, Liang; Yan, Shuicheng

    2016-08-05

    An intuition on human segmentation is that when a human is moving in a video, the video-context (e.g., appearance and motion clues) may potentially infer reasonable mask information for the whole human body. Inspired by this, based on popular deep convolutional neural networks (CNN), we explore a very-weakly supervised learning framework for human segmentation task, where only an imperfect human detector is available along with massive weakly-labeled YouTube videos. In our solution, the video-context guided human mask inference and CNN based segmentation network learning iterate to mutually enhance each other until no further improvement gains. In the first step, each video is decomposed into supervoxels by the unsupervised video segmentation. The superpixels within the supervoxels are then classified as human or non-human by graph optimization with unary energies from the imperfect human detection results and the predicted confidence maps by the CNN trained in the previous iteration. In the second step, the video-context derived human masks are used as direct labels to train CNN. Extensive experiments on the challenging PASCAL VOC 2012 semantic segmentation benchmark demonstrate that the proposed framework has already achieved superior results than all previous weakly-supervised methods with object class or bounding box annotations. In addition, by augmenting with the annotated masks from PASCAL VOC 2012, our method reaches a new stateof- the-art performance on the human segmentation task.

  2. Individual differences in the learning potential of human beings

    Science.gov (United States)

    Stern, Elsbeth

    2017-01-01

    To the best of our knowledge, the genetic foundations that guide human brain development have not changed fundamentally during the past 50,000 years. However, because of their cognitive potential, humans have changed the world tremendously in the past centuries. They have invented technical devices, institutions that regulate cooperation and competition, and symbol systems, such as script and mathematics, that serve as reasoning tools. The exceptional learning ability of humans allows newborns to adapt to the world they are born into; however, there are tremendous individual differences in learning ability among humans that become obvious in school at the latest. Cognitive psychology has developed models of memory and information processing that attempt to explain how humans learn (general perspective), while the variation among individuals (differential perspective) has been the focus of psychometric intelligence research. Although both lines of research have been proceeding independently, they increasingly converge, as both investigate the concepts of working memory and knowledge construction. This review begins with presenting state-of-the-art research on human information processing and its potential in academic learning. Then, a brief overview of the history of psychometric intelligence research is combined with presenting recent work on the role of intelligence in modern societies and on the nature-nurture debate. Finally, promising approaches to integrating the general and differential perspective will be discussed in the conclusion of this review.

  3. Associationism and cognition: human contingency learning at 25.

    Science.gov (United States)

    Shanks, David R

    2007-03-01

    A major topic within human learning, the field of contingency judgement, began to emerge about 25 years ago following publication of an article on depressive realism by Alloy and Abramson (1979). Subsequently, associationism has been the dominant theoretical framework for understanding contingency learning but this has been challenged in recent years by an alternative cognitive or inferential approach. This article outlines the key conceptual differences between these approaches and summarizes some of the main methods that have been employed to distinguish between them.

  4. Social Fear Learning: from Animal Models to Human Function.

    Science.gov (United States)

    Debiec, Jacek; Olsson, Andreas

    2017-07-01

    Learning about potential threats is critical for survival. Learned fear responses are acquired either through direct experiences or indirectly through social transmission. Social fear learning (SFL), also known as vicarious fear learning, is a paradigm successfully used for studying the transmission of threat information between individuals. Animal and human studies have begun to elucidate the behavioral, neural and molecular mechanisms of SFL. Recent research suggests that social learning mechanisms underlie a wide range of adaptive and maladaptive phenomena, from supporting flexible avoidance in dynamic environments to intergenerational transmission of trauma and anxiety disorders. This review discusses recent advances in SFL studies and their implications for basic, social and clinical sciences. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Can theories of animal discrimination explain perceptual learning in humans?

    Science.gov (United States)

    Mitchell, Chris; Hall, Geoffrey

    2014-01-01

    We present a review of recent studies of perceptual learning conducted with nonhuman animals. The focus of this research has been to elucidate the mechanisms by which mere exposure to a pair of similar stimuli can increase the ease with which those stimuli are discriminated. These studies establish an important role for 2 mechanisms, one involving inhibitory associations between the unique features of the stimuli, the other involving a long-term habituation process that enhances the relative salience of these features. We then examine recent work investigating equivalent perceptual learning procedures with human participants. Our aim is to determine the extent to which the phenomena exhibited by people are susceptible to explanation in terms of the mechanisms revealed by the animal studies. Although we find no evidence that associative inhibition contributes to the perceptual learning effect in humans, initial detection of unique features (those that allow discrimination between 2 similar stimuli) appears to depend on an habituation process. Once the unique features have been detected, a tendency to attend to those features and to learn about their properties enhances subsequent discrimination. We conclude that the effects obtained with humans engage mechanisms additional to those seen in animals but argue that, for the most part, these have their basis in learning processes that are common to animals and people. In a final section, we discuss some implications of this analysis of perceptual learning for other aspects of experimental psychology and consider some potential applications. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

  6. Categories from scratch

    NARCIS (Netherlands)

    Poss, R.

    2014-01-01

    The concept of category from mathematics happens to be useful to computer programmers in many ways. Unfortunately, all "good" explanations of categories so far have been designed by mathematicians, or at least theoreticians with a strong background in mathematics, and this makes categories

  7. Learning Semantics of Gestural Instructions for Human-Robot Collaboration

    Science.gov (United States)

    Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

    2018-01-01

    Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions. PMID:29615888

  8. Learning Semantics of Gestural Instructions for Human-Robot Collaboration.

    Science.gov (United States)

    Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

    2018-01-01

    Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions.

  9. Grammatical Constructions as Relational Categories.

    Science.gov (United States)

    Goldwater, Micah B

    2017-07-01

    This paper argues that grammatical constructions, specifically argument structure constructions that determine the "who did what to whom" part of sentence meaning and how this meaning is expressed syntactically, can be considered a kind of relational category. That is, grammatical constructions are represented as the abstraction of the syntactic and semantic relations of the exemplar utterances that are expressed in that construction, and it enables the generation of novel exemplars. To support this argument, I review evidence that there are parallel behavioral patterns between how children learn relational categories generally and how they learn grammatical constructions specifically. Then, I discuss computational simulations of how grammatical constructions are abstracted from exemplar sentences using a domain-general relational cognitive architecture. Last, I review evidence from adult language processing that shows parallel behavioral patterns with expert behavior from other cognitive domains. After reviewing the evidence, I consider how to integrate this account with other theories of language development. Copyright © 2017 Cognitive Science Society, Inc.

  10. Acute psychophysiological stress impairs human associative learning.

    Science.gov (United States)

    Ehlers, M R; Todd, R M

    2017-11-01

    Addiction is increasingly discussed asa disorder of associative learning processes, with both operant and classical conditioning contributing to the development of maladaptive habits. Stress has long been known to promote drug taking and relapse and has further been shown to shift behavior from goal-directed actions towards more habitual ones. However, it remains to be investigated how acute stress may influence simple associative learning processes that occur before a habit can be established. In the present study, healthy young adults were exposed to either acute stress or a control condition half an hour before performing simple classical and operant conditioning tasks. Psychophysiological measures confirmed successful stress induction. Results of the operant conditioning task revealed reduced instrumental responding under delayed acute stress that resembled behavioral responses to lower levels of reward. The classical conditioning experiment revealed successful conditioning in both experimental groups; however, explicit knowledge of conditioning as indicated by stimulus ratings differentiated the stress and control groups. These findings suggest that operant and classical conditioning are differentially influenced by the delayed effects of acute stress with important implications for the understanding of how new habitual behaviors are initially established. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Color descriptors for object category recognition

    NARCIS (Netherlands)

    van de Sande, K.E.A.; Gevers, T.; Snoek, C.G.M.

    2008-01-01

    Category recognition is important to access visual information on the level of objects. A common approach is to compute image descriptors first and then to apply machine learning to achieve category recognition from annotated examples. As a consequence, the choice of image descriptors is of great

  12. Learning to Detect Human-Object Interactions

    KAUST Repository

    Chao, Yu-Wei; Liu, Yunfan; Liu, Xieyang; Zeng, Huayi; Deng, Jia

    2017-01-01

    In this paper we study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among the detected objects. We introduce HICO-DET, a new large benchmark for HOI detection, by augmenting the current HICO classification benchmark with instance annotations. We propose Human-Object Region-based Convolutional Neural Networks (HO-RCNN), a novel DNN-based framework for HOI detection. At the core of our HO-RCNN is the Interaction Pattern, a novel DNN input that characterizes the spatial relations between two bounding boxes. We validate the effectiveness of our HO-RCNN using HICO-DET. Experiments demonstrate that our HO-RCNN, by exploiting human-object spatial relations through Interaction Patterns, significantly improves the performance of HOI detection over baseline approaches.

  13. Teaching, Learning, and the Human Quest: Wisdom

    Science.gov (United States)

    Jarvis, Peter

    2011-01-01

    Wisdom is a complex phenomenon: it finds its home primarily but not exclusively in theology, philosophy, psychology, education--that is, in the humanities--and in life itself. In a paradoxical manner, wisdom finds its home in the world of the unanswerable, where there are no empirical proofs and no obvious answers. Wisdom actually finds its place…

  14. Learning to Detect Human-Object Interactions

    KAUST Repository

    Chao, Yu-Wei

    2017-02-17

    In this paper we study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among the detected objects. We introduce HICO-DET, a new large benchmark for HOI detection, by augmenting the current HICO classification benchmark with instance annotations. We propose Human-Object Region-based Convolutional Neural Networks (HO-RCNN), a novel DNN-based framework for HOI detection. At the core of our HO-RCNN is the Interaction Pattern, a novel DNN input that characterizes the spatial relations between two bounding boxes. We validate the effectiveness of our HO-RCNN using HICO-DET. Experiments demonstrate that our HO-RCNN, by exploiting human-object spatial relations through Interaction Patterns, significantly improves the performance of HOI detection over baseline approaches.

  15. Beyond the Categories.

    Science.gov (United States)

    Weeks, Jeffrey

    2015-07-01

    Shushu is a Turkish Cypriot drag performance artist and the article begins with a discussion of a short film about him by a Greek Cypriot playwright, film maker, and gay activist. The film is interesting in its own right as a documentary about a complex personality, but it is also relevant to wider discussion of sexual and gender identity and categorization in a country divided by history, religion, politics, and military occupation. Shushu rejects easy identification as gay or transgender, or anything else. He is his own self. But refusing a recognized and recognizable identity brings problems, and I detected a pervasive mood of melancholy in his portrayal. The article builds from this starting point to explore the problematic nature of identities and categorizations in the contemporary world. The analysis opens with the power of words and language in defining and classifying sexuality. The early sexologists set in motion a whole catalogue of categories which continue to shape sexual thinking, believing that they were providing a scientific basis for a more humane treatment of sexual variations. This logic continues in DSM-5. The historical effect, however, has been more complex. Categorizations have often fixed individuals into a narrow band of definitions and identities that marginalize and pathologize. The emergence of radical sexual-social movements from the late 1960s offered new forms of grassroots knowledge in opposition to the sexological tradition, but at first these movements worked to affirm rather than challenge the significance of identity categories. Increasingly, however, identities have been problematized and challenged for limiting sexual and gender possibilities, leading to the apparently paradoxical situation where sexual identities are seen as both necessary and impossible. There are emotional costs both in affirming a fixed identity and in rejecting one. Shushu is caught in this dilemma, leading to the pervasive sense of loss that shapes the

  16. Learning collaborative teamwork: an argument for incorporating the humanities.

    Science.gov (United States)

    Hall, Pippa; Brajtman, Susan; Weaver, Lynda; Grassau, Pamela Anne; Varpio, Lara

    2014-11-01

    A holistic, collaborative interprofessional team approach, which includes patients and families as significant decision-making members, has been proposed to address the increasing burden being placed on the health-care system. This project hypothesized that learning activities related to the humanities during clinical placements could enhance interprofessional teamwork. Through an interprofessional team of faculty, clinical staff, students, and patient representatives, we developed and piloted the self-learning module, "interprofessional education for collaborative person-centred practice through the humanities". The module was designed to provide learners from different professions and educational levels with a clinical placement/residency experience that would enable them, through a lens of the humanities, to better understand interprofessional collaborative person-centred care without structured interprofessional placement activities. Learners reported the self-paced and self-directed module to be a satisfactory learning experience in all four areas of care at our institution, and certain attitudes and knowledge were significantly and positively affected. The module's evaluation resulted in a revised edition providing improved structure and instruction for students with no experience in self-directed learning. The module was recently adapted into an interactive bilingual (French and English) online e-learning module to facilitate its integration into the pre-licensure curriculum at colleges and universities.

  17. Contingency learning in human fear conditioning involves the ventral striatum.

    Science.gov (United States)

    Klucken, Tim; Tabbert, Katharina; Schweckendiek, Jan; Merz, Christian Josef; Kagerer, Sabine; Vaitl, Dieter; Stark, Rudolf

    2009-11-01

    The ability to detect and learn contingencies between fearful stimuli and their predictive cues is an important capacity to cope with the environment. Contingency awareness refers to the ability to verbalize the relationships between conditioned and unconditioned stimuli. Although there is a heated debate about the influence of contingency awareness on conditioned fear responses, neural correlates behind the formation process of contingency awareness have gained only little attention in human fear conditioning. Recent animal studies indicate that the ventral striatum (VS) could be involved in this process, but in human studies the VS is mostly associated with positive emotions. To examine this question, we reanalyzed four recently published classical fear conditioning studies (n = 117) with respect to the VS at three distinct levels of contingency awareness: subjects, who did not learn the contingencies (unaware), subjects, who learned the contingencies during the experiment (learned aware) and subjects, who were informed about the contingencies in advance (instructed aware). The results showed significantly increased activations in the left and right VS in learned aware compared to unaware subjects. Interestingly, this activation pattern was only found in learned but not in instructed aware subjects. We assume that the VS is not involved when contingency awareness does not develop during conditioning or when contingency awareness is unambiguously induced already prior to conditioning. VS involvement seems to be important for the transition from a contingency unaware to a contingency aware state. Implications for fear conditioning models as well as for the contingency awareness debate are discussed.

  18. Discrimination of artificial categories structured by family resemblances: a comparative study in people (Homo sapiens) and pigeons (Columba livia).

    Science.gov (United States)

    Makino, Hiroshi; Jitsumori, Masako

    2007-02-01

    Adult humans (Homo sapiens) and pigeons (Columba livia) were trained to discriminate artificial categories that the authors created by mimicking 2 properties of natural categories. One was a family resemblance relationship: The highly variable exemplars, including those that did not have features in common, were structured by a similarity network with the features correlating to one another in each category. The other was a polymorphous rule: No single feature was essential for distinguishing the categories, and all the features overlapped between the categories. Pigeons learned the categories with ease and then showed a prototype effect in accord with the degrees of family resemblance for novel stimuli. Some evidence was also observed for interactive effects of learning of individual exemplars and feature frequencies. Humans had difficulty in learning the categories. The participants who learned the categories generally responded to novel stimuli in an all-or-none fashion on the basis of their acquired classification decision rules. The processes that underlie the classification performances of the 2 species are discussed.

  19. Human resource recommendation algorithm based on ensemble learning and Spark

    Science.gov (United States)

    Cong, Zihan; Zhang, Xingming; Wang, Haoxiang; Xu, Hongjie

    2017-08-01

    Aiming at the problem of “information overload” in the human resources industry, this paper proposes a human resource recommendation algorithm based on Ensemble Learning. The algorithm considers the characteristics and behaviours of both job seeker and job features in the real business circumstance. Firstly, the algorithm uses two ensemble learning methods-Bagging and Boosting. The outputs from both learning methods are then merged to form user interest model. Based on user interest model, job recommendation can be extracted for users. The algorithm is implemented as a parallelized recommendation system on Spark. A set of experiments have been done and analysed. The proposed algorithm achieves significant improvement in accuracy, recall rate and coverage, compared with recommendation algorithms such as UserCF and ItemCF.

  20. Teaching and Learning Children's Human Rights: A Research Synthesis

    Science.gov (United States)

    Brantefors, Lotta; Quennerstedt, Ann

    2016-01-01

    The study presented in this paper is a research synthesis examining how issues relating to the teaching and learning of children's human rights have been approached in educational research. Drawing theoretically on the European Didaktik tradition, the purpose of the paper is to map and synthesise the educational interest in children's rights…

  1. Learning in human-dolphin interactions at zoological facilities

    Science.gov (United States)

    Sweeney, Diane L.

    This research aimed to better understand learning in zoological settings, particularly learning about marine mammals, by investigating the research question, what do people learn through interacting with dolphins in zoological facilities? Sociocultural situated learning theory, specifically a Community of Practice (CoP) model of learning (Lave & Wenger, 1991), was the theoretical framework. The CoP model allowed for diversity of knowledge, interest, motivations, and goals that existed among the community of animal enthusiasts at three commercial zoological facilities, and also for peripheral to more central types of participation. I collected data through interviews of spectators, visitors, and trainers (n=51), observations (n=16), and an online questionnaire of past-visitors (n=933). Data were coded, categorized, and analyzed based on the National Science Foundation's (Friedman, 2008) and the National Research Council's (2009) frameworks for informal science education. Five principal findings answered the research question. First, all participants gained new knowledge within three broad categories: (a) dolphin physiology and natural history, (b) care and training of dolphins, and (c) conservation. Second, all participants constructed personal meanings by connecting the activity to experiences, beliefs, and practices outside the interaction context. Almost all participants made associations with conservation. Third, most participants shifted their attitudes and gained a sense of personal agency about beginning or increasing stewardship actions. Fourth, visitors learned interspecies etiquette skills; trainers learned skills in dolphin training and management, people management, and teaching. Fifth, visitors had long-lasting memories of the experience that occurred eight months to 18 years in the past. Popular cultural ideas about dolphins and the ways the dolphins were represented influenced visitors' expectations and the types of learning. Potential physical

  2. Human-level control through deep reinforcement learning

    Science.gov (United States)

    Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

    2015-02-01

    The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

  3. Human-level control through deep reinforcement learning.

    Science.gov (United States)

    Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A; Veness, Joel; Bellemare, Marc G; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

    2015-02-26

    The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

  4. Human reinforcement learning subdivides structured action spaces by learning effector-specific values

    OpenAIRE

    Gershman, Samuel J.; Pesaran, Bijan; Daw, Nathaniel D.

    2009-01-01

    Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable, due to the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning – such as prediction error signals for action valuation associated with dopamine and the striatum – can cope with this “curse of dimensionality...

  5. Lessons learned from HRA and human-system modeling efforts

    International Nuclear Information System (INIS)

    Hallbert, B.P.

    1993-01-01

    Human-System modeling is not unique to the field of Human Reliability Analysis (HRA). Since human factors professionals first began their explorations of human activities, they have done so with the concept of open-quotes systemclose quotes in mind. Though the two - human and system - are distinct, they can be properly understood only in terms of each other: the system provides a context in which goals and objectives for work are defined, and the human plays either a pre-defined or ad hoc role in meeting these goals. In this sense, every intervention which attempts to evaluate or improve upon some system parameter requires that an understanding of human-system interactions be developed. It is too often the case, however, that somewhere between the inception of a system and its implementation, the human-system relationships are overlooked, misunderstood, or inadequately framed. This results in mismatches between demands versus capabilities of human operators, systems which are difficult to operate, and the obvious end product-human error. The lessons learned from human system modeling provide a valuable feedback mechanism to the process of HRA, and the technologies which employ this form of modeling

  6. Category I structures program

    International Nuclear Information System (INIS)

    Endebrock, E.G.; Dove, R.C.

    1981-01-01

    The objective of the Category I Structure Program is to supply experimental and analytical information needed to assess the structural capacity of Category I structures (excluding the reactor cntainment building). Because the shear wall is a principal element of a Category I structure, and because relatively little experimental information is available on the shear walls, it was selected as the test element for the experimental program. The large load capacities of shear walls in Category I structures dictates that the experimental tests be conducted on small size shear wall structures that incorporates the general construction details and characteristics of as-built shear walls

  7. Human reinforcement learning subdivides structured action spaces by learning effector-specific values.

    Science.gov (United States)

    Gershman, Samuel J; Pesaran, Bijan; Daw, Nathaniel D

    2009-10-28

    Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable because of the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning-such as prediction error signals for action valuation associated with dopamine and the striatum-can cope with this "curse of dimensionality." We propose a reinforcement learning framework that allows for learned action valuations to be decomposed into effector-specific components when appropriate to a task, and test it by studying to what extent human behavior and blood oxygen level-dependent (BOLD) activity can exploit such a decomposition in a multieffector choice task. Subjects made simultaneous decisions with their left and right hands and received separate reward feedback for each hand movement. We found that choice behavior was better described by a learning model that decomposed the values of bimanual movements into separate values for each effector, rather than a traditional model that treated the bimanual actions as unitary with a single value. A decomposition of value into effector-specific components was also observed in value-related BOLD signaling, in the form of lateralized biases in striatal correlates of prediction error and anticipatory value correlates in the intraparietal sulcus. These results suggest that the human brain can use decomposed value representations to "divide and conquer" reinforcement learning over high-dimensional action spaces.

  8. Learning objects as coadjuvants in the human physiology teaching-learning process

    Directory of Open Access Journals (Sweden)

    Marcus Vinícius Lara

    2014-08-01

    Full Text Available The use of Information and Communication Technologies (ICTs in the academic environment of biomedical area has gained much importance, both for their ability to complement the understanding of the subject obtained in the classroom, is the ease of access, or makes more pleasure the learning process, since these tools are present in everyday of the students and use a simple language. Considering that, this study aims to report the experience of building learning objects in human physiology as a tool for learning facilitation, and discuss the impact of this teaching methodology

  9. Actively learning human gaze shifting paths for semantics-aware photo cropping.

    Science.gov (United States)

    Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong

    2014-05-01

    Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons.

  10. The structure and formation of natural categories

    Science.gov (United States)

    Fisher, Douglas; Langley, Pat

    1990-01-01

    Categorization and concept formation are critical activities of intelligence. These processes and the conceptual structures that support them raise important issues at the interface of cognitive psychology and artificial intelligence. The work presumes that advances in these and other areas are best facilitated by research methodologies that reward interdisciplinary interaction. In particular, a computational model is described of concept formation and categorization that exploits a rational analysis of basic level effects by Gluck and Corter. Their work provides a clean prescription of human category preferences that is adapted to the task of concept learning. Also, their analysis was extended to account for typicality and fan effects, and speculate on how the concept formation strategies might be extended to other facets of intelligence, such as problem solving.

  11. Human-like brain hemispheric dominance in birdsong learning.

    Science.gov (United States)

    Moorman, Sanne; Gobes, Sharon M H; Kuijpers, Maaike; Kerkhofs, Amber; Zandbergen, Matthijs A; Bolhuis, Johan J

    2012-07-31

    Unlike nonhuman primates, songbirds learn to vocalize very much like human infants acquire spoken language. In humans, Broca's area in the frontal lobe and Wernicke's area in the temporal lobe are crucially involved in speech production and perception, respectively. Songbirds have analogous brain regions that show a similar neural dissociation between vocal production and auditory perception and memory. In both humans and songbirds, there is evidence for lateralization of neural responsiveness in these brain regions. Human infants already show left-sided dominance in their brain activation when exposed to speech. Moreover, a memory-specific left-sided dominance in Wernicke's area for speech perception has been demonstrated in 2.5-mo-old babies. It is possible that auditory-vocal learning is associated with hemispheric dominance and that this association arose in songbirds and humans through convergent evolution. Therefore, we investigated whether there is similar song memory-related lateralization in the songbird brain. We exposed male zebra finches to tutor or unfamiliar song. We found left-sided dominance of neuronal activation in a Broca-like brain region (HVC, a letter-based name) of juvenile and adult zebra finch males, independent of the song stimulus presented. In addition, juvenile males showed left-sided dominance for tutor song but not for unfamiliar song in a Wernicke-like brain region (the caudomedial nidopallium). Thus, left-sided dominance in the caudomedial nidopallium was specific for the song-learning phase and was memory-related. These findings demonstrate a remarkable neural parallel between birdsong and human spoken language, and they have important consequences for our understanding of the evolution of auditory-vocal learning and its neural mechanisms.

  12. Categories and logical syntax

    NARCIS (Netherlands)

    Klev, Ansten Morch

    2014-01-01

    The notions of category and type are here studied through the lens of logical syntax: Aristotle's as well as Kant's categories through the traditional form of proposition `S is P', and modern doctrines of type through the Fregean form of proposition `F(a)', function applied to argument. Topics

  13. Computing color categories

    NARCIS (Netherlands)

    Yendrikhovskij, S.N.; Rogowitz, B.E.; Pappas, T.N.

    2000-01-01

    This paper is an attempt to develop a coherent framework for understanding, modeling, and computing color categories. The main assumption is that the structure of color category systems originates from the statistical structure of the perceived color environment. This environment can be modeled as

  14. The Impacts of System and Human Factors on Online Learning Systems Use and Learner Satisfaction

    Science.gov (United States)

    Alshare, Khaled A.; Freeze, Ronald D.; Lane, Peggy L.; Wen, H. Joseph

    2011-01-01

    Success in an online learning environment is tied to both human and system factors. This study illuminates the unique contributions of human factors (comfort with online learning, self-management of learning, and perceived Web self-efficacy) to online learning system success, which is measured in terms of usage and satisfaction. The research model…

  15. An impoverished machine: challenges to human learning and instructional technology.

    Science.gov (United States)

    Taraban, Roman

    2008-08-01

    Many of the limitations to human learning and processing identified by cognitive psychologists over the last 50 years still hold true, including computational constraints, low learning rates, and unreliable processing. Instructional technology can be used in classrooms and in other learning contexts to address these limitations to learning. However, creating technological innovations is not enough. As part of psychological science, the development and assessment of instructional systems should be guided by theories and practices within the discipline. The technology we develop should become an object of research like other phenomena that are studied. In the present article, I present an informal account of my own work in assessing instructional technology for engineering thermodynamics to show not only the benefits, but also the limitations, in studying the technology we create. I conclude by considering several ways of advancing the development of instructional technology within the SCiP community, including interdisciplinary research and envisioning learning contexts that differ radically from traditional learning focused on lectures and testing.

  16. Human Systems Integration in Practice: Constellation Lessons Learned

    Science.gov (United States)

    Zumbado, Jennifer Rochlis

    2012-01-01

    NASA's Constellation program provided a unique testbed for Human Systems Integration (HSI) as a fundamental element of the Systems Engineering process. Constellation was the first major program to have HSI mandated by NASA's Human Rating document. Proper HSI is critical to the success of any project that relies on humans to function as operators, maintainers, or controllers of a system. HSI improves mission, system and human performance, significantly reduces lifecycle costs, lowers risk and minimizes re-design. Successful HSI begins with sufficient project schedule dedicated to the generation of human systems requirements, but is by no means solely a requirements management process. A top-down systems engineering process that recognizes throughout the organization, human factors as a technical discipline equal to traditional engineering disciplines with authority for the overall system. This partners with a bottoms-up mechanism for human-centered design and technical issue resolution. The Constellation Human Systems Integration Group (HSIG) was a part of the Systems Engineering and Integration (SE&I) organization within the program office, and existed alongside similar groups such as Flight Performance, Environments & Constraints, and Integrated Loads, Structures and Mechanisms. While the HSIG successfully managed, via influence leadership, a down-and-in Community of Practice to facilitate technical integration and issue resolution, it lacked parallel top-down authority to drive integrated design. This presentation will discuss how HSI was applied to Constellation, the lessons learned and best practices it revealed, and recommendations to future NASA program and project managers. This presentation will discuss how Human Systems Integration (HSI) was applied to NASA's Constellation program, the lessons learned and best practices it revealed, and recommendations to future NASA program and project managers on how to accomplish this critical function.

  17. How we learn to make decisions: rapid propagation of reinforcement learning prediction errors in humans.

    Science.gov (United States)

    Krigolson, Olav E; Hassall, Cameron D; Handy, Todd C

    2014-03-01

    Our ability to make decisions is predicated upon our knowledge of the outcomes of the actions available to us. Reinforcement learning theory posits that actions followed by a reward or punishment acquire value through the computation of prediction errors-discrepancies between the predicted and the actual reward. A multitude of neuroimaging studies have demonstrated that rewards and punishments evoke neural responses that appear to reflect reinforcement learning prediction errors [e.g., Krigolson, O. E., Pierce, L. J., Holroyd, C. B., & Tanaka, J. W. Learning to become an expert: Reinforcement learning and the acquisition of perceptual expertise. Journal of Cognitive Neuroscience, 21, 1833-1840, 2009; Bayer, H. M., & Glimcher, P. W. Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron, 47, 129-141, 2005; O'Doherty, J. P. Reward representations and reward-related learning in the human brain: Insights from neuroimaging. Current Opinion in Neurobiology, 14, 769-776, 2004; Holroyd, C. B., & Coles, M. G. H. The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679-709, 2002]. Here, we used the brain ERP technique to demonstrate that not only do rewards elicit a neural response akin to a prediction error but also that this signal rapidly diminished and propagated to the time of choice presentation with learning. Specifically, in a simple, learnable gambling task, we show that novel rewards elicited a feedback error-related negativity that rapidly decreased in amplitude with learning. Furthermore, we demonstrate the existence of a reward positivity at choice presentation, a previously unreported ERP component that has a similar timing and topography as the feedback error-related negativity that increased in amplitude with learning. The pattern of results we observed mirrored the output of a computational model that we implemented to compute reward

  18. An Educational Game for Learning Human Immunology: What Do Students Learn and How Do They Perceive?

    Science.gov (United States)

    Cheng, Meng-Tzu; Su, TzuFen; Huang, Wei-Yu; Chen, Jhih-Hao

    2014-01-01

    The scientific concepts of human immunology are inherently complicated and extremely difficult to understand. Hence, this study reports on the development of an educational game entitled "Humunology" and examines the impact of using "Humunology" for learning how the body's defense system works. A total of 132 middle school…

  19. CHISSL: A Human-Machine Collaboration Space for Unsupervised Learning

    Energy Technology Data Exchange (ETDEWEB)

    Arendt, Dustin L.; Komurlu, Caner; Blaha, Leslie M.

    2017-07-14

    We developed CHISSL, a human-machine interface that utilizes supervised machine learning in an unsupervised context to help the user group unlabeled instances by her own mental model. The user primarily interacts via correction (moving a misplaced instance into its correct group) or confirmation (accepting that an instance is placed in its correct group). Concurrent with the user's interactions, CHISSL trains a classification model guided by the user's grouping of the data. It then predicts the group of unlabeled instances and arranges some of these alongside the instances manually organized by the user. We hypothesize that this mode of human and machine collaboration is more effective than Active Learning, wherein the machine decides for itself which instances should be labeled by the user. We found supporting evidence for this hypothesis in a pilot study where we applied CHISSL to organize a collection of handwritten digits.

  20. Casual Games and Casual Learning About Human Biological Systems

    Science.gov (United States)

    Price, C. Aaron; Gean, Katherine; Christensen, Claire G.; Beheshti, Elham; Pernot, Bryn; Segovia, Gloria; Person, Halcyon; Beasley, Steven; Ward, Patricia

    2016-02-01

    Casual games are everywhere. People play them throughout life to pass the time, to engage in social interactions, and to learn. However, their simplicity and use in distraction-heavy environments can attenuate their potential for learning. This experimental study explored the effects playing an online, casual game has on awareness of human biological systems. Two hundred and forty-two children were given pretests at a Museum and posttests at home after playing either a treatment or control game. Also, 41 children were interviewed to explore deeper meanings behind the test results. Results show modest improvement in scientific attitudes, ability to identify human biological systems and in the children's ability to describe how those systems work together in real-world scenarios. Interviews reveal that children drew upon their prior school learning as they played the game. Also, on the surface they perceived the game as mainly entertainment but were easily able to discern learning outcomes when prompted. Implications for the design of casual games and how they can be used to enhance transfer of knowledge from the classroom to everyday life are discussed.

  1. Triangulated categories (AM-148)

    CERN Document Server

    Neeman, Amnon

    2014-01-01

    The first two chapters of this book offer a modern, self-contained exposition of the elementary theory of triangulated categories and their quotients. The simple, elegant presentation of these known results makes these chapters eminently suitable as a text for graduate students. The remainder of the book is devoted to new research, providing, among other material, some remarkable improvements on Brown''s classical representability theorem. In addition, the author introduces a class of triangulated categories""--the ""well generated triangulated categories""--and studies their properties. This

  2. A dictionary learning approach for human sperm heads classification.

    Science.gov (United States)

    Shaker, Fariba; Monadjemi, S Amirhassan; Alirezaie, Javad; Naghsh-Nilchi, Ahmad Reza

    2017-12-01

    To diagnose infertility in men, semen analysis is conducted in which sperm morphology is one of the factors that are evaluated. Since manual assessment of sperm morphology is time-consuming and subjective, automatic classification methods are being developed. Automatic classification of sperm heads is a complicated task due to the intra-class differences and inter-class similarities of class objects. In this research, a Dictionary Learning (DL) technique is utilized to construct a dictionary of sperm head shapes. This dictionary is used to classify the sperm heads into four different classes. Square patches are extracted from the sperm head images. Columnized patches from each class of sperm are used to learn class-specific dictionaries. The patches from a test image are reconstructed using each class-specific dictionary and the overall reconstruction error for each class is used to select the best matching class. Average accuracy, precision, recall, and F-score are used to evaluate the classification method. The method is evaluated using two publicly available datasets of human sperm head shapes. The proposed DL based method achieved an average accuracy of 92.2% on the HuSHeM dataset, and an average recall of 62% on the SCIAN-MorphoSpermGS dataset. The results show a significant improvement compared to a previously published shape-feature-based method. We have achieved high-performance results. In addition, our proposed approach offers a more balanced classifier in which all four classes are recognized with high precision and recall. In this paper, we use a Dictionary Learning approach in classifying human sperm heads. It is shown that the Dictionary Learning method is far more effective in classifying human sperm heads than classifiers using shape-based features. Also, a dataset of human sperm head shapes is introduced to facilitate future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Object-graphs for context-aware visual category discovery.

    Science.gov (United States)

    Lee, Yong Jae; Grauman, Kristen

    2012-02-01

    How can knowing about some categories help us to discover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for recurring objects without human supervision, but existing methods assume no prior information and thus tend to perform poorly for cluttered scenes with multiple objects. We propose to leverage knowledge about previously learned categories to enable more accurate discovery, and address challenges in estimating their familiarity in unsegmented, unlabeled images. We introduce two variants of a novel object-graph descriptor to encode the 2D and 3D spatial layout of object-level co-occurrence patterns relative to an unfamiliar region and show that by using them to model the interaction between an image’s known and unknown objects, we can better detect new visual categories. Rather than mine for all categories from scratch, our method identifies new objects while drawing on useful cues from familiar ones. We evaluate our approach on several benchmark data sets and demonstrate clear improvements in discovery over conventional purely appearance-based baselines.

  4. Human-Guided Learning for Probabilistic Logic Models

    Directory of Open Access Journals (Sweden)

    Phillip Odom

    2018-06-01

    Full Text Available Advice-giving has been long explored in the artificial intelligence community to build robust learning algorithms when the data is noisy, incorrect or even insufficient. While logic based systems were effectively used in building expert systems, the role of the human has been restricted to being a “mere labeler” in recent times. We hypothesize and demonstrate that probabilistic logic can provide an effective and natural way for the expert to specify domain advice. Specifically, we consider different types of advice-giving in relational domains where noise could arise due to systematic errors or class-imbalance inherent in the domains. The advice is provided as logical statements or privileged features that are thenexplicitly considered by an iterative learning algorithm at every update. Our empirical evidence shows that human advice can effectively accelerate learning in noisy, structured domains where so far humans have been merely used as labelers or as designers of the (initial or final structure of the model.

  5. Extending human potential in a technical learning environment

    Science.gov (United States)

    Fielden, Kay A.

    This thesis is a report of a participatory inquiry process looking at enhancing the learning process in a technical academic field in high education by utilising tools and techniques which go beyond the rational/logical, intellectual domain in a functional, objective world. By empathising with, nurturing and sustaining the whole person, and taking account of past patterning as well as future visions including technological advances to augment human awareness, the scene is set for depth learning. Depth learning in a tertiary environment can only happen as a result of the dynamic that exists between the dominant, logical/rational, intellectual paradigm and the experiential extension of the boundaries surrounding this domain. Any experiences which suppress the full, holistic expression of our being alienate us from the fullness of the expression and hence from depth learning. Depth learning is indicated by intrinsic motivation, which is more likely to occur in a trusting and supporting environment. The research took place within a systemic intellectual framework, where emergence is the prime characteristic used to evaluate results.

  6. Analysis of rare categories

    CERN Document Server

    He, Jingrui

    2012-01-01

    This book focuses on rare category analysis where the majority classes have smooth distributions and the minority classes exhibit the compactness property. It focuses on challenging cases where the support regions of the majority and minority classes overlap.

  7. Consumer Product Category Database

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Chemical and Product Categories database (CPCat) catalogs the use of over 40,000 chemicals and their presence in different consumer products. The chemical use...

  8. Product Category Management Issues

    OpenAIRE

    Żukowska, Joanna

    2011-01-01

    The purpose of the paper is to present the issues related to category management. It includes the overview of category management definitions and the correct process of exercising it. Moreover, attention is paid to the advantages of brand management, the benefits the supplier and retailer may obtain in this way. The risk element related to this topics is also presented herein. Joanna Żukowska

  9. Efectos del desarrollo en la memoria de trabajo y el aprendizaje de categorías en niños Developmet effects on working memory and category learning in children

    Directory of Open Access Journals (Sweden)

    Federico José Sánchez

    2009-12-01

    Full Text Available Se han reportado diferencias relacionadas con la edad en el desempeño de diversas tareas dependientes del lóbulo frontal, incluyendo tareas de memoria de trabajo (Luciana and Nelson, 1998; Luna et al. 2001; Bunge et al., 2002. Se han encontrado también efectos de edad y género sobre la memoria de trabajo en niños (Vuontela et. al, 2003. Además, el aprendizaje de categorías ha sido asociado con la actividad del lóbulo frontal (Dickins, 2000; Schlund 2007. El presente trabajo investigó los efectos de la edad y el género sobre la memoria de trabajo y el aprendizaje de categorías en niños de 8 a 13 años. Se encontraron efectos de edad y género sobre la memoria de trabajo, y en la tarea de aprendizaje de categorías sólo se observaron efectos de la edad. Los resultados sugieren que el desempeño de memoria de trabajo podría estar asociado con la velocidad de procesamiento en el aprendizaje de categorías.Age-related differences have been reported in the performance of several frontal lobe-dependent tasks, including working memory (Luciana and Nelson, 1998; Luna et al. 2001; Bunge et al., 2002. Effects of age and gender on working memory have been found in children (Vuontela et. al, 2003. On the other hand, category learning has also been associated with frontal lobe activity (Dickins, 2000; Schlund 2007. The present study addressed the effects of age and gender on working memory and category learning, in 8-13 year old children. Age and gender effects were found on the working memory task, and age effects only were observed on category learning. The results suggest that working memory performance might be associated with processing speed in the category learning task.

  10. Mixed-complexity artificial grammar learning in humans and macaque monkeys: evaluating learning strategies.

    Science.gov (United States)

    Wilson, Benjamin; Smith, Kenny; Petkov, Christopher I

    2015-03-01

    Artificial grammars (AG) can be used to generate rule-based sequences of stimuli. Some of these can be used to investigate sequence-processing computations in non-human animals that might be related to, but not unique to, human language. Previous AG learning studies in non-human animals have used different AGs to separately test for specific sequence-processing abilities. However, given that natural language and certain animal communication systems (in particular, song) have multiple levels of complexity, mixed-complexity AGs are needed to simultaneously evaluate sensitivity to the different features of the AG. Here, we tested humans and Rhesus macaques using a mixed-complexity auditory AG, containing both adjacent (local) and non-adjacent (longer-distance) relationships. Following exposure to exemplary sequences generated by the AG, humans and macaques were individually tested with sequences that were either consistent with the AG or violated specific adjacent or non-adjacent relationships. We observed a considerable level of cross-species correspondence in the sensitivity of both humans and macaques to the adjacent AG relationships and to the statistical properties of the sequences. We found no significant sensitivity to the non-adjacent AG relationships in the macaques. A subset of humans was sensitive to this non-adjacent relationship, revealing interesting between- and within-species differences in AG learning strategies. The results suggest that humans and macaques are largely comparably sensitive to the adjacent AG relationships and their statistical properties. However, in the presence of multiple cues to grammaticality, the non-adjacent relationships are less salient to the macaques and many of the humans. © 2015 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  11. From Perceptual Categories to Concepts: What Develops?

    Science.gov (United States)

    Sloutsky, Vladimir M.

    2010-01-01

    People are remarkably smart: they use language, possess complex motor skills, make non-trivial inferences, develop and use scientific theories, make laws, and adapt to complex dynamic environments. Much of this knowledge requires concepts and this paper focuses on how people acquire concepts. It is argued that conceptual development progresses from simple perceptual grouping to highly abstract scientific concepts. This proposal of conceptual development has four parts. First, it is argued that categories in the world have different structure. Second, there might be different learning systems (sub-served by different brain mechanisms) that evolved to learn categories of differing structures. Third, these systems exhibit differential maturational course, which affects how categories of different structures are learned in the course of development. And finally, an interaction of these components may result in the developmental transition from perceptual groupings to more abstract concepts. This paper reviews a large body of empirical evidence supporting this proposal. PMID:21116483

  12. Categories of transactions

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    This chapter discusses the types of wholesale sales made by utilities. The Federal Energy Regulatory Commission (FERC), which regulates inter-utility sales, divides these sales into two broad categories: requirements and coordination. A variety of wholesale sales do not fall neatly into either category. For example, power purchased to replace the Three Mile Island outage is in a sense a reliability purchase, since it is bought on a long-term firm basis to meet basic load requirements. However, it does not fit the traditional model of a sale considered as part of each utility's long range planning. In addition, this chapter discusses transmission services, with a particular emphasis on wheeling

  13. Learning on human resources management in the radiology residency program

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira, Aparecido Ferreira de; Lederman, Henrique Manoel; Batista, Nildo Alves, E-mail: aparecidoliveira@ig.com.br [Universidade Federal de Sao Paulo (EPM/UNIFESP), Sao Paulo, SP (Brazil). Escola Paulista de Medicina

    2014-03-15

    Objective: to investigate the process of learning on human resource management in the radiology residency program at Escola Paulista de Medicina - Universidade Federal de Sao Paulo, aiming at improving radiologists' education. Materials and methods: exploratory study with a quantitative and qualitative approach developed with the faculty staff, preceptors and residents of the program, utilizing a Likert questionnaire (46), taped interviews (18), and categorization based on thematic analysis. Results: According to 71% of the participants, residents have clarity about their role in the development of their activities, and 48% said that residents have no opportunity to learn how to manage their work in a multidisciplinary team. Conclusion: Isolation at medical records room, little interactivity between sectors with diversified and fixed activities, absence of a previous culture and lack of a training program on human resources management may interfere in the development of skills for the residents' practice. There is a need to review objectives of the medical residency in the field of radiology, incorporating, whenever possible, the commitment to the training of skills related to human resources management thus widening the scope of abilities of the future radiologists. (author)

  14. Learning on human resources management in the radiology residency program

    International Nuclear Information System (INIS)

    Oliveira, Aparecido Ferreira de; Lederman, Henrique Manoel; Batista, Nildo Alves

    2014-01-01

    Objective: to investigate the process of learning on human resource management in the radiology residency program at Escola Paulista de Medicina - Universidade Federal de Sao Paulo, aiming at improving radiologists' education. Materials and methods: exploratory study with a quantitative and qualitative approach developed with the faculty staff, preceptors and residents of the program, utilizing a Likert questionnaire (46), taped interviews (18), and categorization based on thematic analysis. Results: According to 71% of the participants, residents have clarity about their role in the development of their activities, and 48% said that residents have no opportunity to learn how to manage their work in a multidisciplinary team. Conclusion: Isolation at medical records room, little interactivity between sectors with diversified and fixed activities, absence of a previous culture and lack of a training program on human resources management may interfere in the development of skills for the residents' practice. There is a need to review objectives of the medical residency in the field of radiology, incorporating, whenever possible, the commitment to the training of skills related to human resources management thus widening the scope of abilities of the future radiologists. (author)

  15. Teaching and Learning French--A Tale of Desire in the Humanities

    Science.gov (United States)

    Cunningham, Catriona

    2017-01-01

    This article considers the way we talk about learning and teaching the humanities in higher education in the UK. By using the tools of the arts and humanities within the scholarship of learning and teaching, and examining a personal perspective, the author explores the transformational impact of French language learning and teaching. Close textual…

  16. Applying lessons learned to enhance human performance and reduce human error for ISS operations

    Energy Technology Data Exchange (ETDEWEB)

    Nelson, W.R.

    1998-09-01

    A major component of reliability, safety, and mission success for space missions is ensuring that the humans involved (flight crew, ground crew, mission control, etc.) perform their tasks and functions as required. This includes compliance with training and procedures during normal conditions, and successful compensation when malfunctions or unexpected conditions occur. A very significant issue that affects human performance in space flight is human error. Human errors can invalidate carefully designed equipment and procedures. If certain errors combine with equipment failures or design flaws, mission failure or loss of life can occur. The control of human error during operation of the International Space Station (ISS) will be critical to the overall success of the program. As experience from Mir operations has shown, human performance plays a vital role in the success or failure of long duration space missions. The Department of Energy`s Idaho National Engineering and Environmental Laboratory (INEEL) is developed a systematic approach to enhance human performance and reduce human errors for ISS operations. This approach is based on the systematic identification and evaluation of lessons learned from past space missions such as Mir to enhance the design and operation of ISS. This paper describes previous INEEL research on human error sponsored by NASA and how it can be applied to enhance human reliability for ISS.

  17. Optimized Assistive Human-Robot Interaction Using Reinforcement Learning.

    Science.gov (United States)

    Modares, Hamidreza; Ranatunga, Isura; Lewis, Frank L; Popa, Dan O

    2016-03-01

    An intelligent human-robot interaction (HRI) system with adjustable robot behavior is presented. The proposed HRI system assists the human operator to perform a given task with minimum workload demands and optimizes the overall human-robot system performance. Motivated by human factor studies, the presented control structure consists of two control loops. First, a robot-specific neuro-adaptive controller is designed in the inner loop to make the unknown nonlinear robot behave like a prescribed robot impedance model as perceived by a human operator. In contrast to existing neural network and adaptive impedance-based control methods, no information of the task performance or the prescribed robot impedance model parameters is required in the inner loop. Then, a task-specific outer-loop controller is designed to find the optimal parameters of the prescribed robot impedance model to adjust the robot's dynamics to the operator skills and minimize the tracking error. The outer loop includes the human operator, the robot, and the task performance details. The problem of finding the optimal parameters of the prescribed robot impedance model is transformed into a linear quadratic regulator (LQR) problem which minimizes the human effort and optimizes the closed-loop behavior of the HRI system for a given task. To obviate the requirement of the knowledge of the human model, integral reinforcement learning is used to solve the given LQR problem. Simulation results on an x - y table and a robot arm, and experimental implementation results on a PR2 robot confirm the suitability of the proposed method.

  18. Identifying the Learning Styles and Instructional Tool Preferences of Beginning Food Science and Human Nutrition Majors

    Science.gov (United States)

    Bohn, D. M.; Rasmussen, C. N.; Schmidt, S. J.

    2004-01-01

    Learning styles vary among individuals, and understanding which instructional tools certain learning styles prefer can be utilized to enhance student learning. Students in the introductory Food Science and Human Nutrition course (FSHN 101), taught at the Univ. of Illinois at Urbana-Champaign, were asked to complete Gregorc's Learning Style…

  19. Human Subjects Protection: A Source for Ethical Service-Learning Practice

    Science.gov (United States)

    Wendler, Rachael

    2012-01-01

    Human subjects research ethics were developed to ensure responsible conduct when university researchers learn by interacting with community members. As service-learning students also learn by interacting with community members, a similar set of principles may strengthen the ethical practice of service-learning. This article identifies ethical…

  20. Reminder cues modulate the renewal effect in human predictive learning

    Directory of Open Access Journals (Sweden)

    Javier Bustamante

    2016-12-01

    Full Text Available Associative learning refers to our ability to learn about regularities in our environment. When a stimulus is repeatedly followed by a specific outcome, we learn to expect the outcome in the presence of the stimulus. We are also able to modify established expectations in the face of disconfirming information (the stimulus is no longer followed by the outcome. Both the change of environmental regularities and the related processes of adaptation are referred to as extinction. However, extinction does not erase the initially acquired expectations. For instance, following successful extinction, the initially learned expectations can recover when there is a context change – a phenomenon called the renewal effect, which is considered as a model for relapse after exposure therapy. Renewal was found to be modulated by reminder cues of acquisition and extinction. However, the mechanisms underlying the effectiveness of reminder cues are not well understood. The aim of the present study was to investigate the impact of reminder cues on renewal in the field of human predictive learning. Experiment I demonstrated that renewal in human predictive learning is modulated by cues related to acquisition or extinction. Initially, participants received pairings of a stimulus and an outcome in one context. These stimulus-outcome pairings were preceded by presentations of a reminder cue (acquisition cue. Then, participants received extinction in a different context in which presentations of the stimulus were no longer followed by the outcome. These extinction trials were preceded by a second reminder cue (extinction cue. During a final phase conducted in a third context, participants showed stronger expectations of the outcome in the presence of the stimulus when testing was accompanied by the acquisition cue compared to the extinction cue. Experiment II tested an explanation of the reminder cue effect in terms of simple cue-outcome associations. Therefore

  1. Effectiveness of using blended learning strategies for teaching and learning human anatomy.

    Science.gov (United States)

    Pereira, José A; Pleguezuelos, Eulogio; Merí, Alex; Molina-Ros, Antoni; Molina-Tomás, M Carmen; Masdeu, Carlos

    2007-02-01

    This study aimed to implement innovative teaching methods--blended learning strategies--that include the use of new information technologies in the teaching of human anatomy and to analyse both the impact of these strategies on academic performance, and the degree of user satisfaction. The study was carried out among students in Year 1 of the biology degree curriculum (human biology profile) at Pompeu Fabra University, Barcelona. Two groups of students were tested on knowledge of the anatomy of the locomotor system and results compared between groups. Blended learning strategies were employed in 1 group (BL group, n = 69); the other (TT group; n = 65) received traditional teaching aided by complementary material that could be accessed on the Internet. Both groups were evaluated using the same types of examination. The average marks presented statistically significant differences (BL 6.3 versus TT 5.0; P < 0.0001). The percentage pass rate for the subject in the first call was higher in the BL group (87.9% versus 71.4%; P = 0.02), reflecting a lower incidence of students who failed to sit the examination (BL 4.3% versus TT 13.8%; P = 0.05). There were no differences regarding overall satisfaction with the teaching received. Blended learning was more effective than traditional teaching for teaching human anatomy.

  2. Consumer Product Category Database

    Science.gov (United States)

    The Chemical and Product Categories database (CPCat) catalogs the use of over 40,000 chemicals and their presence in different consumer products. The chemical use information is compiled from multiple sources while product information is gathered from publicly available Material Safety Data Sheets (MSDS). EPA researchers are evaluating the possibility of expanding the database with additional product and use information.

  3. On Logical Characterisation of Human Concept Learning based on Terminological Systems

    DEFF Research Database (Denmark)

    Badie, Farshad

    2018-01-01

    The central focus of this article is the epistemological assumption that knowledge could be generated based on human beings' experiences and over their conceptions of the world. Logical characterisation of human inductive learning over their produced conceptions within terminological systems and ...... and analysis of actual human inductive reasoning (and learning). This research connects with the topics 'logic & learning', 'cognitive modelling' and 'terminological knowledge representation'.......The central focus of this article is the epistemological assumption that knowledge could be generated based on human beings' experiences and over their conceptions of the world. Logical characterisation of human inductive learning over their produced conceptions within terminological systems...

  4. Toward a tactile language for human-robot interaction: two studies of tacton learning and performance.

    Science.gov (United States)

    Barber, Daniel J; Reinerman-Jones, Lauren E; Matthews, Gerald

    2015-05-01

    Two experiments were performed to investigate the feasibility for robot-to-human communication of a tactile language using a lexicon of standardized tactons (tactile icons) within a sentence. Improvements in autonomous systems technology and a growing demand within military operations are spurring interest in communication via vibrotactile displays. Tactile communication may become an important element of human-robot interaction (HRI), but it requires the development of messaging capabilities approaching the communication power of the speech and visual signals used in the military. In Experiment 1 (N = 38), we trained participants to identify sets of directional, dynamic, and static tactons and tested performance and workload following training. In Experiment 2 (N = 76), we introduced an extended training procedure and tested participants' ability to correctly identify two-tacton phrases. We also investigated the impact of multitasking on performance and workload. Individual difference factors were assessed. Experiment 1 showed that participants found dynamic and static tactons difficult to learn, but the enhanced training procedure in Experiment 2 produced competency in performance for all tacton categories. Participants in the latter study also performed well on two-tacton phrases and when multitasking. However, some deficits in performance and elevation of workload were observed. Spatial ability predicted some aspects of performance in both studies. Participants may be trained to identify both single tactons and tacton phrases, demonstrating the feasibility of developing a tactile language for HRI. Tactile communication may be incorporated into multi-modal communication systems for HRI. It also has potential for human-human communication in challenging environments. © 2014, Human Factors and Ergonomics Society.

  5. Models as Relational Categories

    Science.gov (United States)

    Kokkonen, Tommi

    2017-01-01

    Model-based learning (MBL) has an established position within science education. It has been found to enhance conceptual understanding and provide a way for engaging students in authentic scientific activity. Despite ample research, few studies have examined the cognitive processes regarding learning scientific concepts within MBL. On the other…

  6. Functional categories in comparative linguistics

    DEFF Research Database (Denmark)

    Rijkhoff, Jan

    , Roger M. 1979. Linguistic knowledge and cultural knowledge: some doubts and speculation. American Anthropologist 81-1, 14-36. Levinson, Stephen C. 1997. From outer to inner space: linguistic categories and non-linguistic thinking. In J. Nuyts and E. Pederson (eds.), Language and Conceptualization, 13......). Furthermore certain ‘ontological categories’ are language-specific (Malt 1995). For example, speakers of Kalam (New Guinea) do not classify the cassowary as a bird, because they believe it has a mythical kinship relation with humans (Bulmer 1967).       In this talk I will discuss the role of functional...

  7. Human medial frontal cortex activity predicts learning from errors.

    Science.gov (United States)

    Hester, Robert; Barre, Natalie; Murphy, Kevin; Silk, Tim J; Mattingley, Jason B

    2008-08-01

    Learning from errors is a critical feature of human cognition. It underlies our ability to adapt to changing environmental demands and to tune behavior for optimal performance. The posterior medial frontal cortex (pMFC) has been implicated in the evaluation of errors to control behavior, although it has not previously been shown that activity in this region predicts learning from errors. Using functional magnetic resonance imaging, we examined activity in the pMFC during an associative learning task in which participants had to recall the spatial locations of 2-digit targets and were provided with immediate feedback regarding accuracy. Activity within the pMFC was significantly greater for errors that were subsequently corrected than for errors that were repeated. Moreover, pMFC activity during recall errors predicted future responses (correct vs. incorrect), despite a sizeable interval (on average 70 s) between an error and the next presentation of the same recall probe. Activity within the hippocampus also predicted future performance and correlated with error-feedback-related pMFC activity. A relationship between performance expectations and pMFC activity, in the absence of differing reinforcement value for errors, is consistent with the idea that error-related pMFC activity reflects the extent to which an outcome is "worse than expected."

  8. Aversive learning shapes neuronal orientation tuning in human visual cortex.

    Science.gov (United States)

    McTeague, Lisa M; Gruss, L Forest; Keil, Andreas

    2015-07-28

    The responses of sensory cortical neurons are shaped by experience. As a result perceptual biases evolve, selectively facilitating the detection and identification of sensory events that are relevant for adaptive behaviour. Here we examine the involvement of human visual cortex in the formation of learned perceptual biases. We use classical aversive conditioning to associate one out of a series of oriented gratings with a noxious sound stimulus. After as few as two grating-sound pairings, visual cortical responses to the sound-paired grating show selective amplification. Furthermore, as learning progresses, responses to the orientations with greatest similarity to the sound-paired grating are increasingly suppressed, suggesting inhibitory interactions between orientation-selective neuronal populations. Changes in cortical connectivity between occipital and fronto-temporal regions mirror the changes in visuo-cortical response amplitudes. These findings suggest that short-term behaviourally driven retuning of human visual cortical neurons involves distal top-down projections as well as local inhibitory interactions.

  9. Human Activity Recognition from Body Sensor Data using Deep Learning.

    Science.gov (United States)

    Hassan, Mohammad Mehedi; Huda, Shamsul; Uddin, Md Zia; Almogren, Ahmad; Alrubaian, Majed

    2018-04-16

    In recent years, human activity recognition from body sensor data or wearable sensor data has become a considerable research attention from academia and health industry. This research can be useful for various e-health applications such as monitoring elderly and physical impaired people at Smart home to improve their rehabilitation processes. However, it is not easy to accurately and automatically recognize physical human activity through wearable sensors due to the complexity and variety of body activities. In this paper, we address the human activity recognition problem as a classification problem using wearable body sensor data. In particular, we propose to utilize a Deep Belief Network (DBN) model for successful human activity recognition. First, we extract the important initial features from the raw body sensor data. Then, a kernel principal component analysis (KPCA) and linear discriminant analysis (LDA) are performed to further process the features and make them more robust to be useful for fast activity recognition. Finally, the DBN is trained by these features. Various experiments were performed on a real-world wearable sensor dataset to verify the effectiveness of the deep learning algorithm. The results show that the proposed DBN outperformed other algorithms and achieves satisfactory activity recognition performance.

  10. CHURCH, Category, and Speciation

    Directory of Open Access Journals (Sweden)

    Rinderknecht Jakob Karl

    2018-01-01

    Full Text Available The Roman Catholic definition of “church”, especially as applied to groups of Protestant Christians, creates a number of well-known difficulties. The similarly complex category, “species,” provides a model for applying this term so as to neither lose the centrality of certain examples nor draw a hard boundary to rule out border cases. In this way, it can help us to more adequately apply the complex ecclesiology of the Second Vatican Council. This article draws parallels between the understanding of speciation and categorization and the definition of Church since the council. In doing so, it applies the work of cognitive linguists, including George Lakoff, Zoltan Kovecses, Giles Fauconnier and Mark Turner on categorization. We tend to think of categories as containers into which we sort objects according to essential criteria. However, categories are actually built inductively by making associations between objects. This means that natural categories, including species, are more porous than we assume, but nevertheless bear real meaning about the natural world. Taxonomists dispute the border between “zebras” and “wild asses,” but this distinction arises out of genetic and evolutionary reality; it is not merely arbitrary. Genetic descriptions of species has also led recently to the conviction that there are four species of giraffe, not one. This engagement will ground a vantage point from which the Council‘s complex ecclesiology can be more easily described so as to authentically integrate its noncompetitive vision vis-a-vis other Christians with its sense of the unique place held by Catholic Church.

  11. Libertarianism & Category-Mistake

    OpenAIRE

    Carlos G. Patarroyo G.

    2009-01-01

    This paper offers a defense against two accusations according to which libertarianism incurs in a category-mistake. The philosophy of Gilbert Ryle will be used to explain the reasons which ground these accusations. Further, it will be shown why, although certain sorts of libertarianism based on agent-causation or Cartesian dualism incur in these mistakes, there is at least one version of libertarianism to which this criticism does not necessarily apply: the version that seeks to find in physi...

  12. Convergence semigroup categories

    Directory of Open Access Journals (Sweden)

    Gary Richardson

    2013-09-01

    Full Text Available Properties of the category consisting of all objects of the form (X, S, λ are investigated, where X is a convergence space, S is a commutative semigroup, and λ: X × S → X is a continuous action. A “generalized quotient” of each object is defined without making the usual assumption that for each fixed g ∈ S, λ(., g : X  → X is an injection.

  13. Categories and Commutative Algebra

    CERN Document Server

    Salmon, P

    2011-01-01

    L. Badescu: Sur certaines singularites des varietes algebriques.- D.A. Buchsbaum: Homological and commutative algebra.- S. Greco: Anelli Henseliani.- C. Lair: Morphismes et structures algebriques.- B.A. Mitchell: Introduction to category theory and homological algebra.- R. Rivet: Anneaux de series formelles et anneaux henseliens.- P. Salmon: Applicazioni della K-teoria all'algebra commutativa.- M. Tierney: Axiomatic sheaf theory: some constructions and applications.- C.B. Winters: An elementary lecture on algebraic spaces.

  14. Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response.

    Science.gov (United States)

    Ofli, Ferda; Meier, Patrick; Imran, Muhammad; Castillo, Carlos; Tuia, Devis; Rey, Nicolas; Briant, Julien; Millet, Pauline; Reinhard, Friedrich; Parkan, Matthew; Joost, Stéphane

    2016-03-01

    Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resolution of aerial imagery is an order of magnitude higher than the imagery produced by the most sophisticated commercial satellites today. Both the United States Federal Emergency Management Agency (FEMA) and the European Commission's Joint Research Center (JRC) have noted that aerial imagery will inevitably present a big data challenge. The purpose of this article is to get ahead of this future challenge by proposing a hybrid crowdsourcing and real-time machine learning solution to rapidly process large volumes of aerial data for disaster response in a time-sensitive manner. Crowdsourcing can be used to annotate features of interest in aerial images (such as damaged shelters and roads blocked by debris). These human-annotated features can then be used to train a supervised machine learning system to learn to recognize such features in new unseen images. In this article, we describe how this hybrid solution for image analysis can be implemented as a module (i.e., Aerial Clicker) to extend an existing platform called Artificial Intelligence for Disaster Response (AIDR), which has already been deployed to classify microblog messages during disasters using its Text Clicker module and in response to Cyclone Pam, a category 5 cyclone that devastated Vanuatu in March 2015. The hybrid solution we present can be applied to both aerial and satellite imagery and has applications beyond disaster response such as wildlife protection, human rights, and archeological exploration. As a proof of concept, we recently piloted this solution using very high-resolution aerial photographs of a wildlife reserve in Namibia to support rangers with their wildlife conservation efforts (SAVMAP project, http://lasig.epfl.ch/savmap ). The

  15. 21 CFR 330.5 - Drug categories.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 5 2010-04-01 2010-04-01 false Drug categories. 330.5 Section 330.5 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) DRUGS FOR HUMAN...) Stimulants. (r) Antitussives. (s) Allergy treatment products. (t) Cold remedies. (u) Antirheumatic products...

  16. LIBERTARISMO & ERROR CATEGORIAL

    Directory of Open Access Journals (Sweden)

    Carlos G. Patarroyo G.

    2009-01-01

    Full Text Available En este artículo se ofrece una defensa del libertarismo frente a dos acusaciones según las cuales éste comete un error categorial. Para ello, se utiliza la filosofía de Gilbert Ryle como herramienta para explicar las razones que fundamentan estas acusaciones y para mostrar por qué, pese a que ciertas versiones del libertarismo que acuden a la causalidad de agentes o al dualismo cartesiano cometen estos errores, un libertarismo que busque en el indeterminismo fisicalista la base de la posibilidad de la libertad humana no necesariamente puede ser acusado de incurrir en ellos.

  17. Libertarismo & Error Categorial

    OpenAIRE

    PATARROYO G, CARLOS G

    2009-01-01

    En este artículo se ofrece una defensa del libertarismo frente a dos acusaciones según las cuales éste comete un error categorial. Para ello, se utiliza la filosofía de Gilbert Ryle como herramienta para explicar las razones que fundamentan estas acusaciones y para mostrar por qué, pese a que ciertas versiones del libertarismo que acuden a la causalidad de agentes o al dualismo cartesiano cometen estos errores, un libertarismo que busque en el indeterminismo fisicalista la base de la posibili...

  18. Duo: A Human/Wearable Hybrid for Learning About Common Manipulate Objects

    National Research Council Canada - National Science Library

    Kemp, Charles C

    2002-01-01

    ... with them. Duo is a human/wearable hybrid that is designed to learn about this important domain of human intelligence by interacting with natural manipulable objects in unconstrained environments...

  19. Thalamic control of human attention driven by memory and learning.

    Science.gov (United States)

    de Bourbon-Teles, José; Bentley, Paul; Koshino, Saori; Shah, Kushal; Dutta, Agneish; Malhotra, Paresh; Egner, Tobias; Husain, Masud; Soto, David

    2014-05-05

    The role of the thalamus in high-level cognition-attention, working memory (WM), rule-based learning, and decision making-remains poorly understood, especially in comparison to that of cortical frontoparietal networks [1-3]. Studies of visual thalamus have revealed important roles for pulvinar and lateral geniculate nucleus in visuospatial perception and attention [4-10] and for mediodorsal thalamus in oculomotor control [11]. Ventrolateral thalamus contains subdivisions devoted to action control as part of a circuit involving the basal ganglia [12, 13] and motor, premotor, and prefrontal cortices [14], whereas anterior thalamus forms a memory network in connection with the hippocampus [15]. This connectivity profile suggests that ventrolateral and anterior thalamus may represent a nexus between mnemonic and control functions, such as action or attentional selection. Here, we characterize the role of thalamus in the interplay between memory and visual attention. We show that ventrolateral lesions impair the influence of WM representations on attentional deployment. A subsequent fMRI study in healthy volunteers demonstrates involvement of ventrolateral and, notably, anterior thalamus in biasing attention through WM contents. To further characterize the memory types used by the thalamus to bias attention, we performed a second fMRI study that involved learning of stimulus-stimulus associations and their retrieval from long-term memory to optimize attention in search. Responses in ventrolateral and anterior thalamic nuclei tracked learning of the predictiveness of these abstract associations and their use in directing attention. These findings demonstrate a key role for human thalamus in higher-level cognition, notably, in mnemonic biasing of attention. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  20. 3D Reconstruction of human bones based on dictionary learning.

    Science.gov (United States)

    Zhang, Binkai; Wang, Xiang; Liang, Xiao; Zheng, Jinjin

    2017-11-01

    An effective method for reconstructing a 3D model of human bones from computed tomography (CT) image data based on dictionary learning is proposed. In this study, the dictionary comprises the vertices of triangular meshes, and the sparse coefficient matrix indicates the connectivity information. For better reconstruction performance, we proposed a balance coefficient between the approximation and regularisation terms and a method for optimisation. Moreover, we applied a local updating strategy and a mesh-optimisation method to update the dictionary and the sparse matrix, respectively. The two updating steps are iterated alternately until the objective function converges. Thus, a reconstructed mesh could be obtained with high accuracy and regularisation. The experimental results show that the proposed method has the potential to obtain high precision and high-quality triangular meshes for rapid prototyping, medical diagnosis, and tissue engineering. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

  1. Contextual control of attentional allocation in human discrimination learning.

    Science.gov (United States)

    Uengoer, Metin; Lachnit, Harald; Lotz, Anja; Koenig, Stephan; Pearce, John M

    2013-01-01

    In 3 human predictive learning experiments, we investigated whether the allocation of attention can come under the control of contextual stimuli. In each experiment, participants initially received a conditional discrimination for which one set of cues was trained as relevant in Context 1 and irrelevant in Context 2, and another set was relevant in Context 2 and irrelevant in Context 1. For Experiments 1 and 2, we observed that a second discrimination based on cues that had previously been trained as relevant in Context 1 during the conditional discrimination was acquired more rapidly in Context 1 than in Context 2. Experiment 3 revealed a similar outcome when new stimuli from the original dimensions were used in the test stage. Our results support the view that the associability of a stimulus can be controlled by the stimuli that accompany it.

  2. How Social and Human Capital Predict Participation in Lifelong Learning: A Longitudinal Data Analysis

    Science.gov (United States)

    Knipprath, Heidi; De Rick, Katleen

    2015-01-01

    Policy makers and researchers are increasingly showing interest in lifelong learning due to a rising unemployment rate in recent years. Much attention has been paid to determinants and benefits of lifelong learning but not to the impact of social capital on lifelong learning so far. In this article, we study how social and human capital can…

  3. Social learning solves the problem of narrow-peaked search landscapes : experimental evidence in humans

    NARCIS (Netherlands)

    Acerbi, A.; Tennie, C.; Mesoudi, A.

    2016-01-01

    The extensive use of social learning is considered a major reason for the ecological success of humans. Theoretical considerations, models and experiments have explored the evolutionary basis of social learning, showing the conditions under which learning from others is more adaptive than individual

  4. Utilizing Service Learning in a College-Level Human Sexuality Course

    Science.gov (United States)

    Jenkins, Dusty D.

    2017-01-01

    Implementing service learning into college courses has been shown to have positive benefits for both students and community members; however, service learning has not been largely evaluated in the literature on human sexuality courses. Thus, the purpose of the current study was to design, implement, and evaluate a service learning project in a…

  5. Literacy Learning in a Digitally Rich Humanities Classroom: Embracing Multiple, Collaborative, and Simultaneous Texts

    Science.gov (United States)

    Buckley-Marudas, Mary Frances

    2016-01-01

    Understanding what happens when teachers embrace digital media for literacy learning is critical to realizing the potential of learning in the digital era. This article examines some of the ways that a high school teacher and his students leverage digital technologies for literacy learning in their humanities classrooms. The author introduces the…

  6. Challenges of nursing teaching-learning to care for human dying - professors' perceptions

    Directory of Open Access Journals (Sweden)

    Emanuelle Caires Dias Araújo Nunes

    2017-10-01

    Full Text Available Abstract The objective of this study was to investigate professors' perceptions about their experiences in the teaching-learning process of nursing care in relation to dying. This is a descriptive-exploratory, qualitative research, delimited by data saturation, was carried out with 11 nursing professors from three higher education institutions. Data collection involved the drawing-text theme technique and a semi-structured interview. Analysis used the technique of collective subject discourse. The results identified three categories: How I would like to take care in the context of finitude - my challenge; Challenging fragilities in the teaching of nurses in the context of care concerned with death and dying; Strategies to compensate or promote more substantial nurse training related to care in finitude. We conclude that the graduation of the nurses studied did not satisfactorily develop the necessary skills and abilities to deal with human death and dying. This study infers the need of permanent education to support transformations in this area.

  7. Teaching practices epistemologically differentiated about human body learning

    Directory of Open Access Journals (Sweden)

    Rosália Maria Ribeiro de Aragão

    2011-12-01

    Full Text Available How could we teach about THE HUMAN BODY as a different way, in both epistemological and pedagogical approaches? How could we leave behind stagnant as well as stagnating aspects of traditional way of teaching, such as the fragmentation/segmentation of contents, the far away reality, the excessive use of details or else, whenever learning about our own body? These are some of the questions we have considered when trying to escape the bad influence which came from our "environment formation" - putting it on all the marks we have acquired inside or even outside school - trying to overview as meaning our body working...in constant interaction with the surrounding ambient. Among those pointed kind of formation marks we frequently acquire from studying at the University - which need to be transcended —here we come to detach those innumerable contacts with both anatomized and misfigurated supposed human bodies' which didn't even look like actual human bodies, because they could never seem to have sheltered life inside themselves. They were inert as well as static bodies, only used as a such of vain "didactic materials" that could/can permit many teachers on their educational formation to focus a certain teaching approach which only seeks both the students' memorization of an infinitude of "complicated words", and to structure the systems -by several procedures of nouns definition and/or classification - as part of the so called biological organism. In order to do a different way of teaching, we have based our approach on three alternative teaching methodologies which focus these matters under a constructive perspective. On those three focused studies, it is possible to observe that some very principles of a present day teaching approach were there considered to achieve some of them: the respect for the students' previous ideas; the understanding about knowledge as something that is not established for good but as ever changeable and, at last, the

  8. Mimvec: a deep learning approach for analyzing the human phenome.

    Science.gov (United States)

    Gan, Mingxin; Li, Wenran; Zeng, Wanwen; Wang, Xiaojian; Jiang, Rui

    2017-09-21

    The human phenome has been widely used with a variety of genomic data sources in the inference of disease genes. However, most existing methods thus far derive phenotype similarity based on the analysis of biomedical databases by using the traditional term frequency-inverse document frequency (TF-IDF) formulation. This framework, though intuitive, not only ignores semantic relationships between words but also tends to produce high-dimensional vectors, and hence lacks the ability to precisely capture intrinsic semantic characteristics of biomedical documents. To overcome these limitations, we propose a framework called mimvec to analyze the human phenome by making use of the state-of-the-art deep learning technique in natural language processing. We converted 24,061 records in the Online Mendelian Inheritance in Man (OMIM) database to low-dimensional vectors using our method. We demonstrated that the vector presentation not only effectively enabled classification of phenotype records against gene ones, but also succeeded in discriminating diseases of different inheritance styles and different mechanisms. We further derived pairwise phenotype similarities between 7988 human inherited diseases using their vector presentations. With a joint analysis of this phenome with multiple genomic data, we showed that phenotype overlap indeed implied genotype overlap. We finally used the derived phenotype similarities with genomic data to prioritize candidate genes and demonstrated advantages of this method over existing ones. Our method is capable of not only capturing semantic relationships between words in biomedical records but also alleviating the dimensional disaster accompanying the traditional TF-IDF framework. With the approaching of precision medicine, there will be abundant electronic records of medicine and health awaiting for deep analysis, and we expect to see a wide spectrum of applications borrowing the idea of our method in the near future.

  9. Injecting learning experience into geoethics for human and natural sustainability

    Science.gov (United States)

    Crookall, David

    2016-04-01

    Our early life experience has a strong influence on our actions in later life. Humans today are just starting to re-learn, collectively, how to treat Earth with the respect that it deserves and that is needed for our offspring to inherit a decent home. However, we still have a long way to go to instill in people at large the ethics, knowledge and skills necessary to ensure a healthy journey for humanity on spaceship. The experience of early upbringing, of schooling and of everyday life is probably the only path strong enough to develop in people a strong desire for ethical behaviour towards their environment. The problem is that the measures taken today to ensure the development of ethical behaviours in the population at large are woefully inadequate. At best, western school programmes contain a few lessons devoted to the environment, and even then they usually just pay lip service to the basics of the environment; they rarely aim to instill skills and knowledge in order to understand and care deeply for the environment. My presentation will suggest some practical ways to help communities build ethical frameworks and strategies to guide and generate tools, methods and activities that guide young people (pupils, students, scholars, researchers) to toward more ethical behaviours regarding their environment and their communities. Examples might include: - Developing geoethical dimensions of internships, in all areas; - Designing, testing and running simulation/games+debriefing providing a rich affective-cognitive context for grappling with geoethical problems- eg, FISH BANKS, KEEP COOL. - Pressuring governments to make geoethics, environmental care and climate change understanding central components of (almost) all educational programmes (in, eg, history, language, business, law, medicine, etc). - Subsidizing environmental-care summer schools for families and teachers at all levels. - Etc. One of my actions is founding a academic journal in the area, maybe with the

  10. Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction

    Science.gov (United States)

    de Greeff, Joachim; Belpaeme, Tony

    2015-01-01

    Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children’s social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a “mental model” of the robot, tailoring the tutoring to the robot’s performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot’s bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance. PMID:26422143

  11. Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction.

    Science.gov (United States)

    de Greeff, Joachim; Belpaeme, Tony

    2015-01-01

    Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children's social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a "mental model" of the robot, tailoring the tutoring to the robot's performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot's bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance.

  12. Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction.

    Directory of Open Access Journals (Sweden)

    Joachim de Greeff

    Full Text Available Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children's social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference; the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a "mental model" of the robot, tailoring the tutoring to the robot's performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot's bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance.

  13. Understanding Collective Learning and Human Agency in Diverse ...

    African Journals Online (AJOL)

    2018-05-07

    May 7, 2018 ... knowledge about the type of learning that creates such change, how such learning emerges, or how it ... social inequalities and damaged people–nature relations. The Think ..... interpersonal relationality and more. The Think ...

  14. Language categories in Russian morphology

    OpenAIRE

    زهرایی زهرایی

    2009-01-01

    When studying Russian morphology, one can distinguish two categories. These categories are “grammatical” and “lexico-grammatical”. Grammatical categories can be specified through a series of grammatical features of words. Considering different criteria, Russian grammarians and linguists divide grammatical categories of their language into different types. In determining lexico-grammatical types, in addition to a series of grammatical features, they also consider a series of lexico-semantic fe...

  15. A Human/Computer Learning Network to Improve Biodiversity Conservation and Research

    OpenAIRE

    Kelling, Steve; Gerbracht, Jeff; Fink, Daniel; Lagoze, Carl; Wong, Weng-Keen; Yu, Jun; Damoulas, Theodoros; Gomes, Carla

    2012-01-01

    In this paper we describe eBird, a citizen-science project that takes advantage of the human observational capacity to identify birds to species, which is then used to accurately represent patterns of bird occurrences across broad spatial and temporal extents. eBird employs artificial intelligence techniques such as machine learning to improve data quality by taking advantage of the synergies between human computation and mechanical computation. We call this a Human-Computer Learning Network,...

  16. Human dorsal striatum encodes prediction errors during observational learning of instrumental actions.

    Science.gov (United States)

    Cooper, Jeffrey C; Dunne, Simon; Furey, Teresa; O'Doherty, John P

    2012-01-01

    The dorsal striatum plays a key role in the learning and expression of instrumental reward associations that are acquired through direct experience. However, not all learning about instrumental actions require direct experience. Instead, humans and other animals are also capable of acquiring instrumental actions by observing the experiences of others. In this study, we investigated the extent to which human dorsal striatum is involved in observational as well as experiential instrumental reward learning. Human participants were scanned with fMRI while they observed a confederate over a live video performing an instrumental conditioning task to obtain liquid juice rewards. Participants also performed a similar instrumental task for their own rewards. Using a computational model-based analysis, we found reward prediction errors in the dorsal striatum not only during the experiential learning condition but also during observational learning. These results suggest a key role for the dorsal striatum in learning instrumental associations, even when those associations are acquired purely by observing others.

  17. Human likeness: cognitive and affective factors affecting adoption of robot-assisted learning systems

    Science.gov (United States)

    Yoo, Hosun; Kwon, Ohbyung; Lee, Namyeon

    2016-07-01

    With advances in robot technology, interest in robotic e-learning systems has increased. In some laboratories, experiments are being conducted with humanoid robots as artificial tutors because of their likeness to humans, the rich possibilities of using this type of media, and the multimodal interaction capabilities of these robots. The robot-assisted learning system, a special type of e-learning system, aims to increase the learner's concentration, pleasure, and learning performance dramatically. However, very few empirical studies have examined the effect on learning performance of incorporating humanoid robot technology into e-learning systems or people's willingness to accept or adopt robot-assisted learning systems. In particular, human likeness, the essential characteristic of humanoid robots as compared with conventional e-learning systems, has not been discussed in a theoretical context. Hence, the purpose of this study is to propose a theoretical model to explain the process of adoption of robot-assisted learning systems. In the proposed model, human likeness is conceptualized as a combination of media richness, multimodal interaction capabilities, and para-social relationships; these factors are considered as possible determinants of the degree to which human cognition and affection are related to the adoption of robot-assisted learning systems.

  18. Human demonstrations for fast and safe exploration in reinforcement learning

    NARCIS (Netherlands)

    Schonebaum, G.K.; Junell, J.L.; van Kampen, E.

    2017-01-01

    Reinforcement learning is a promising framework for controlling complex vehicles with a high level of autonomy, since it does not need a dynamic model of the vehicle, and it is able to adapt to changing conditions. When learning from scratch, the performance of a reinforcement learning controller

  19. Convergent transcriptional specializations in the brains of humans and song-learning birds

    DEFF Research Database (Denmark)

    Pfenning, Andreas R.; Hara, Erina; Whitney, Osceola

    2014-01-01

    Song-learning birds and humans share independently evolved similarities in brain pathways for vocal learning that are essential for song and speech and are not found in most other species. Comparisons of brain transcriptomes of song-learning birds and humans relative to vocal nonlearners identified...... convergent gene expression specializations in specific song and speech brain regions of avian vocal learners and humans. The strongest shared profiles relate bird motor and striatal song-learning nuclei, respectively, with human laryngeal motor cortex and parts of the striatum that control speech production...... and learning. Most of the associated genes function in motor control and brain connectivity. Thus, convergent behavior and neural connectivity for a complex trait are associated with convergent specialized expression of multiple genes....

  20. Learning Human Actions by Combining Global Dynamics and Local Appearance.

    Science.gov (United States)

    Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J

    2014-12-01

    In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.

  1. Ambiguity Produces Attention Shifts in Category Learning

    Science.gov (United States)

    Vadillo, Miguel A.; Orgaz, Cristina; Luque, David; Nelson, James Byron

    2016-01-01

    It has been suggested that people and nonhuman animals protect their knowledge from interference by shifting attention toward the context when presented with information that contradicts their previous beliefs. Despite that suggestion, no studies have directly measured changes in attention while participants are exposed to an interference…

  2. Matching based on biological categories in Orangutans (Pongo abelii and a Gorilla (Gorilla gorilla gorilla

    Directory of Open Access Journals (Sweden)

    Jennifer Vonk

    2013-09-01

    Full Text Available Following a series of experiments in which six orangutans and one gorilla discriminated photographs of different animal species in a two-choice touch screen procedure, Vonk & MacDonald (2002 and Vonk & MacDonald (2004 concluded that orangutans, but not the gorilla, seemed to learn intermediate level category discriminations, such as primates versus non-primates, more rapidly than they learned concrete level discriminations, such as orangutans versus humans. In the current experiments, four of the same orangutans and the gorilla were presented with delayed matching-to-sample tasks in which they were rewarded for matching photos of different members of the same primate species; golden lion tamarins, Japanese macaques, and proboscis monkeys, or family; gibbons, lemurs (Experiment 1, and subsequently for matching photos of different species within the following classes: birds, reptiles, insects, mammals, and fish (Experiment 2. Members of both Great Ape species were rapidly able to match the photos at levels above chance. Orangutans matched images from both category levels spontaneously whereas the gorilla showed effects of learning to match intermediate level categories. The results show that biological knowledge is not necessary to form natural categories at both concrete and intermediate levels.

  3. Climate for Learning: A Symposium. Creating a Climate for Learning, and the Humanizing Process. The Principal and School Discipline. Curriculum Bulletin Vol. XXXII, No. 341.

    Science.gov (United States)

    Johnson, Simon O.; Chaky, June

    This publication contains two articles focusing on creating a climate for learning. In "Creating a Climate for Learning, and the Humanizing Process," Simon O. Johnson offers practical suggestions for creating a humanistic learning environment. The author begins by defining the basic concepts--humanism, affective education, affective situation,…

  4. Intrinsically motivated reinforcement learning for human-robot interaction in the real-world.

    Science.gov (United States)

    Qureshi, Ahmed Hussain; Nakamura, Yutaka; Yoshikawa, Yuichiro; Ishiguro, Hiroshi

    2018-03-26

    For a natural social human-robot interaction, it is essential for a robot to learn the human-like social skills. However, learning such skills is notoriously hard due to the limited availability of direct instructions from people to teach a robot. In this paper, we propose an intrinsically motivated reinforcement learning framework in which an agent gets the intrinsic motivation-based rewards through the action-conditional predictive model. By using the proposed method, the robot learned the social skills from the human-robot interaction experiences gathered in the real uncontrolled environments. The results indicate that the robot not only acquired human-like social skills but also took more human-like decisions, on a test dataset, than a robot which received direct rewards for the task achievement. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. Health effects of risk-assessment categories

    International Nuclear Information System (INIS)

    Kramer, C.F.; Rybicka, K.; Knutson, A.; Morris, S.C.

    1983-10-01

    Environmental and occupational health effects associated with exposures to various chemicals are a subject of increasing concern. One recently developed methodology for assessing the health impacts of various chemical compounds involves the classification of similar chemicals into risk-assessment categories (RACs). This report reviews documented human health effects for a broad range of pollutants, classified by RACs. It complements other studies that have estimated human health effects by RAC based on analysis and extrapolation of data from animal research

  6. Health effects of risk-assessment categories

    Energy Technology Data Exchange (ETDEWEB)

    Kramer, C.F.; Rybicka, K.; Knutson, A.; Morris, S.C.

    1983-10-01

    Environmental and occupational health effects associated with exposures to various chemicals are a subject of increasing concern. One recently developed methodology for assessing the health impacts of various chemical compounds involves the classification of similar chemicals into risk-assessment categories (RACs). This report reviews documented human health effects for a broad range of pollutants, classified by RACs. It complements other studies that have estimated human health effects by RAC based on analysis and extrapolation of data from animal research.

  7. Categorical Structure among Shared Features in Networks of Early-Learned Nouns

    Science.gov (United States)

    Hills, Thomas T.; Maouene, Mounir; Maouene, Josita; Sheya, Adam; Smith, Linda

    2009-01-01

    The shared features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the…

  8. Learning about the Human Genome. Part 2: Resources for Science Educators. ERIC Digest.

    Science.gov (United States)

    Haury, David L.

    This ERIC Digest identifies how the human genome project fits into the "National Science Education Standards" and lists Human Genome Project Web sites found on the World Wide Web. It is a resource companion to "Learning about the Human Genome. Part 1: Challenge to Science Educators" (Haury 2001). The Web resources and…

  9. Development of Human Resources Using New Technologies in Long-Life Learning

    Directory of Open Access Journals (Sweden)

    Micu Bogdan Ghilic

    2011-01-01

    Full Text Available Information and communication technologies (ICT offer new opportunities to reinvent the education and to make people and makes learning more fun and contemporary but poses many problems to educational institutions. Implementation of ICT determines major structural changes in the organizations and mental switch from bureaucratic mentality to customer-oriented one. In this paper I try to evaluate methods of developing the lifelong learning programs, impact to human resources training and development and the impact of this process on educational institutions. E-learning usage in training the human resources can make a new step in development of the education institutions, human resources and companies.

  10. Interactive machine learning for health informatics: when do we need the human-in-the-loop?

    Science.gov (United States)

    Holzinger, Andreas

    2016-06-01

    Machine learning (ML) is the fastest growing field in computer science, and health informatics is among the greatest challenges. The goal of ML is to develop algorithms which can learn and improve over time and can be used for predictions. Most ML researchers concentrate on automatic machine learning (aML), where great advances have been made, for example, in speech recognition, recommender systems, or autonomous vehicles. Automatic approaches greatly benefit from big data with many training sets. However, in the health domain, sometimes we are confronted with a small number of data sets or rare events, where aML-approaches suffer of insufficient training samples. Here interactive machine learning (iML) may be of help, having its roots in reinforcement learning, preference learning, and active learning. The term iML is not yet well used, so we define it as "algorithms that can interact with agents and can optimize their learning behavior through these interactions, where the agents can also be human." This "human-in-the-loop" can be beneficial in solving computationally hard problems, e.g., subspace clustering, protein folding, or k-anonymization of health data, where human expertise can help to reduce an exponential search space through heuristic selection of samples. Therefore, what would otherwise be an NP-hard problem, reduces greatly in complexity through the input and the assistance of a human agent involved in the learning phase.

  11. Human Factors Throughout the Life Cycle: Lessons Learned from the Shuttle Program. [Human Factors in Ground Processing

    Science.gov (United States)

    Kanki, Barbara G.

    2011-01-01

    With the ending of the Space Shuttle Program, it is critical that we not forget the Human Factors lessons we have learned over the years. At every phase of the life cycle, from manufacturing, processing and integrating vehicle and payload, to launch, flight operations, mission control and landing, hundreds of teams have worked together to achieve mission success in one of the most complex, high-risk socio-technical enterprises ever designed. Just as there was great diversity in the types of operations performed at every stage, there was a myriad of human factors that could further complicate these human systems. A single mishap or close call could point to issues at the individual level (perceptual or workload limitations, training, fatigue, human error susceptibilities), the task level (design of tools, procedures and aspects of the workplace), as well as the organizational level (appropriate resources, safety policies, information access and communication channels). While we have often had to learn through human mistakes and technological failures, we have also begun to understand how to design human systems in which individuals can excel, where tasks and procedures are not only safe but efficient, and how organizations can foster a proactive approach to managing risk and supporting human enterprises. Panelists will talk about their experiences as they relate human factors to a particular phase of the shuttle life cycle. They will conclude with a framework for tying together human factors lessons-learned into system-level risk management strategies.

  12. Learning to walk before we run: what can medical education learn from the human body about integrated care?

    Directory of Open Access Journals (Sweden)

    Eron G. Manusov

    2013-05-01

    Full Text Available True integration requires a shift in all levels of medical and allied health education; one that emphasizes team learning, practicing, and evaluating from the beginning of each students' educational experience whether that is as physician, nurse, psychologist, or any other health profession.  Integration of healthcare services will not occur until medical education focuses, like the human body, on each system working inter-dependently and cohesively to maintain balance through continual change and adaptation.  The human body develops and maintains homeostasis by a process of communication: true integrated care relies on learned interprofessionality and ensures shared responsibility and practice.

  13. Learning to walk before we run: what can medical education learn from the human body about integrated care.

    Science.gov (United States)

    Manusov, Eron G; Marlowe, Daniel P; Teasley, Deborah J

    2013-04-01

    True integration requires a shift in all levels of medical and allied health education; one that emphasizes team learning, practicing, and evaluating from the beginning of each students' educational experience whether that is as physician, nurse, psychologist, or any other health profession. Integration of healthcare services will not occur until medical education focuses, like the human body, on each system working inter-dependently and cohesively to maintain balance through continual change and adaptation. The human body develops and maintains homeostasis by a process of communication: true integrated care relies on learned interprofessionality and ensures shared responsibility and practice.

  14. Continuing Robot Skill Learning after Demonstration with Human Feedback

    Directory of Open Access Journals (Sweden)

    Argall Brenna D.

    2011-12-01

    Full Text Available Though demonstration-based approaches have been successfully applied to learning a variety of robot behaviors, there do exist some limitations. The ability to continue learning after demonstration, based on execution experience with the learned policy, therefore has proven to be an asset to many demonstration-based learning systems. This paper discusses important considerations for interfaces that provide feedback to adapt and improve demonstrated behaviors. Feedback interfaces developed for two robots with very different motion capabilities - a wheeled mobile robot and high degree-of-freedom humanoid - are highlighted.

  15. Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior

    Science.gov (United States)

    2006-09-28

    navigate in an unstructured environment to a specific target or location. 15. SUBJECT TERMS autonomous vehicles , fuzzy logic, learning behavior...ANSI-Std Z39-18 Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior FINAL REPORT 9/28/2006 Dean B. Edwards Department...the future, as greater numbers of autonomous vehicles are employed, it is hoped that lower LONG-TERM GOALS Use LAGR (Learning Applied to Ground Robots

  16. Action Search: Learning to Search for Human Activities in Untrimmed Videos

    KAUST Repository

    Alwassel, Humam; Heilbron, Fabian Caba; Ghanem, Bernard

    2017-01-01

    Traditional approaches for action detection use trimmed data to learn sophisticated action detector models. Although these methods have achieved great success at detecting human actions, we argue that huge information is discarded when ignoring

  17. Adding the Human Touch to Asynchronous Online Learning

    Science.gov (United States)

    Glenn, Cynthia Wheatley

    2018-01-01

    For learners to actively accept responsibility in a virtual classroom platform, it is necessary to provide special motivation extending across the traditional classroom setting into asynchronous online learning. This article explores specific ways to do this that bridge the gap between ground and online students' learning experiences, and how…

  18. Learning as a Machine: Crossovers between Humans and Machines

    Science.gov (United States)

    Hildebrandt, Mireille

    2017-01-01

    This article is a revised version of the keynote presented at LAK '16 in Edinburgh. The article investigates some of the assumptions of learning analytics, notably those related to behaviourism. Building on the work of Ivan Pavlov, Herbert Simon, and James Gibson as ways of "learning as a machine," the article then develops two levels of…

  19. Casual Games and Casual Learning about Human Biological Systems

    Science.gov (United States)

    Price, C. Aaron; Gean, Katherine; Christensen, Claire G.; Beheshti, Elham; Pernot, Bryn; Segovia, Gloria; Person, Halcyon; Beasley, Steven; Ward, Patricia

    2016-01-01

    Casual games are everywhere. People play them throughout life to pass the time, to engage in social interactions, and to learn. However, their simplicity and use in distraction-heavy environments can attenuate their potential for learning. This experimental study explored the effects playing an online, casual game has on awareness of human…

  20. Chinese View of Learning and Implications for Developing Human Resources

    Science.gov (United States)

    Yang, Baiyin; Zheng, Wei; Li, Mingfei

    2006-01-01

    Chinese society has a unique view of teaching and learning that has evolved from its long history and is heavily embedded in its social and cultural roots. However, no systematic effort has been made to outline how cultural factors such as values and beliefs influence learning. This paper identifies traditional Chinese values and beliefs in…

  1. Technology and human issues in reusing learning objects

    NARCIS (Netherlands)

    Collis, Betty; Strijker, A.

    2004-01-01

    Reusing learning objects is as old as retelling a story or making use of libraries and textbooks, and in electronic form has received an enormous new impetus because of the World Wide Web and Web technologies. Are we at the brink of changing the "shape and form of learning, ... of being able to

  2. Human Cadavers vs. Multimedia Simulation: A Study of Student Learning in Anatomy

    Science.gov (United States)

    Saltarelli, Andrew J.; Roseth, Cary J.; Saltarelli, William A.

    2014-01-01

    Multimedia and simulation programs are increasingly being used for anatomy instruction, yet it remains unclear how learning with these technologies compares with learning with actual human cadavers. Using a multilevel, quasi-experimental-control design, this study compared the effects of "Anatomy and Physiology Revealed" (APR) multimedia…

  3. Enrolment Purposes, Instructional Activities, and Perceptions of Attitudinal Learning in a Human Trafficking MOOC

    Science.gov (United States)

    Watson, Sunnie Lee; Kim, Woori

    2016-01-01

    This study examines learner enrolment purposes, perceptions on instructional activities and their relationship to learning gains in a Massive Open Online Course (MOOC) for attitudinal change regarding human trafficking. Using an author-developed survey, learners reported their perceptions on instructional activities and learning gains within the…

  4. Learning Agreements and Socially Responsible Approaches to Professional and Human Resource Development in the United Kingdom

    Science.gov (United States)

    Wallis, Emma

    2008-01-01

    This article draws upon original qualitative data to present an initial assessment of the significance of learning agreements for the development of socially responsible approaches to professional and human resource development within the workplace. The article suggests that the adoption of a partnership-based approach to learning is more…

  5. Learning from video modeling examples : Effects of seeing the human model's face

    NARCIS (Netherlands)

    Van Gog, Tamara; Verveer, Ilse; Verveer, Lise

    2014-01-01

    Video modeling examples in which a human(-like) model shows learners how to perform a task are increasingly used in education, as they have become very easy to create and distribute in e-learning environments. However, little is known about design guidelines to optimize learning from video modeling

  6. Learning-related human brain activations reflecting individual finances.

    Science.gov (United States)

    Tobler, Philippe N; Fletcher, Paul C; Bullmore, Edward T; Schultz, Wolfram

    2007-04-05

    A basic tenet of microeconomics suggests that the subjective value of financial gains decreases with increasing assets of individuals ("marginal utility"). Using concepts from learning theory and microeconomics, we assessed the capacity of financial rewards to elicit behavioral and neuronal changes during reward-predictive learning in participants with different financial backgrounds. Behavioral learning speed during both acquisition and extinction correlated negatively with the assets of the participants, irrespective of education and age. Correspondingly, response changes in midbrain and striatum measured with functional magnetic resonance imaging were slower during both acquisition and extinction with increasing assets and income of the participants. By contrast, asymptotic magnitudes of behavioral and neuronal responses after learning were unrelated to personal finances. The inverse relationship of behavioral and neuronal learning speed with personal finances is compatible with the general concept of decreasing marginal utility with increasing wealth.

  7. Grammatical category dissociation in multilingual aphasia.

    Science.gov (United States)

    Faroqi-Shah, Yasmeen; Waked, Arifi N

    2010-03-01

    Word retrieval deficits for specific grammatical categories, such as verbs versus nouns, occur as a consequence of brain damage. Such deficits are informative about the nature of lexical organization in the human brain. This study examined retrieval of grammatical categories across three languages in a trilingual person with aphasia who spoke Arabic, French, and English. In order to delineate the nature of word production difficulty, comprehension was tested, and a variety of concomitant lexical-semantic variables were analysed. The patient demonstrated a consistent noun-verb dissociation in picture naming and narrative speech, with severely impaired production of verbs across all three languages. The cross-linguistically similar noun-verb dissociation, coupled with little evidence of semantic impairment, suggests that (a) the patient has a true "nonsemantic" grammatical category specific deficit, and (b) lexical organization in multilingual speakers shares grammatical class information between languages. The findings of this study contribute to our understanding of the architecture of lexical organization in bilinguals.

  8. Subject categories and scope descriptions

    International Nuclear Information System (INIS)

    2002-01-01

    This document is one in a series of publications known as the ETDE/INIS Joint Reference Series. It defines the subject categories and provides the scope descriptions to be used for categorization of the nuclear literature for the preparation of INIS and ETDE input by national and regional centres. Together with the other volumes of the INIS Reference Series it defines the rules, standards and practices and provides the authorities to be used in the International Nuclear Information System and ETDE. A complete list of the volumes published in the INIS Reference Series may be found on the inside front cover of this publication. This INIS/ETDE Reference Series document is intended to serve two purposes: to define the subject scope of the International Nuclear Information System (INIS) and the Energy Technology Data Exchange (ETDE) and to define the subject classification scheme of INIS and ETDE. It is thus the guide to the inputting centres in determining which items of literature should be reported, and in determining where the full bibliographic entry and abstract of each item should be included in INIS or ETDE database. Each category is identified by a category code consisting of three alphanumeric characters. A scope description is given for each subject category. The scope of INIS is the sum of the scopes of all the categories. With most categories cross references are provided to other categories where appropriate. Cross references should be of assistance in finding the appropriate category; in fact, by indicating topics that are excluded from the category in question, the cross references help to clarify and define the scope of the category to which they are appended. A Subject Index is included as an aid to subject classifiers, but it is only an aid and not a means for subject classification. It facilitates the use of this document, but is no substitute for the description of the scope of the subject categories

  9. Active Learning and Flipped Classroom, Hand in Hand Approach to Improve Students Learning in Human Anatomy and Physiology

    Science.gov (United States)

    Entezari, Maria; Javdan, Mohammad

    2016-01-01

    Because Human Anatomy and Physiology (A&P), a gateway course for allied health majors, has high dropout rates nationally, it is challenging to find a successful pedagogical intervention. Reports on the effect of integration of flipped classrooms and whether it improves learning are contradictory for different disciplines. Thus many educators…

  10. A learning-based autonomous driver: emulate human driver's intelligence in low-speed car following

    Science.gov (United States)

    Wei, Junqing; Dolan, John M.; Litkouhi, Bakhtiar

    2010-04-01

    In this paper, an offline learning mechanism based on the genetic algorithm is proposed for autonomous vehicles to emulate human driver behaviors. The autonomous driving ability is implemented based on a Prediction- and Cost function-Based algorithm (PCB). PCB is designed to emulate a human driver's decision process, which is modeled as traffic scenario prediction and evaluation. This paper focuses on using a learning algorithm to optimize PCB with very limited training data, so that PCB can have the ability to predict and evaluate traffic scenarios similarly to human drivers. 80 seconds of human driving data was collected in low-speed (car-following scenarios. In the low-speed car-following tests, PCB was able to perform more human-like carfollowing after learning. A more general 120 kilometer-long simulation showed that PCB performs robustly even in scenarios that are not part of the training set.

  11. Ian Hacking, Learner Categories and Human Taxonomies

    Science.gov (United States)

    Davis, Andrew

    2008-01-01

    I use Ian Hacking's views to explore ways of classifying people, exploiting his distinction between indifferent kinds and interactive kinds, and his accounts of how we "make up" people. The natural kind/essentialist approach to indifferent kinds is explored in some depth. I relate this to debates in psychiatry about the existence of mental…

  12. Cross-cultural Comparison of Learning in Human Hunting : Implications for Life History Evolution.

    Science.gov (United States)

    MacDonald, Katharine

    2007-12-01

    This paper is a cross-cultural examination of the development of hunting skills and the implications for the debate on the role of learning in the evolution of human life history patterns. While life history theory has proven to be a powerful tool for understanding the evolution of the human life course, other schools, such as cultural transmission and social learning theory, also provide theoretical insights. These disparate theories are reviewed, and alternative and exclusive predictions are identified. This study of cross-cultural regularities in how children learn hunting skills, based on the ethnographic literature on traditional hunters, complements existing empirical work and highlights future areas for investigation.

  13. SnapAnatomy, a computer-based interactive tool for independent learning of human anatomy.

    Science.gov (United States)

    Yip, George W; Rajendran, Kanagasuntheram

    2008-06-01

    Computer-aided instruction materials are becoming increasing popular in medical education and particularly in the teaching of human anatomy. This paper describes SnapAnatomy, a new interactive program that the authors designed for independent learning of anatomy. SnapAnatomy is primarily tailored for the beginner student to encourage the learning of anatomy by developing a three-dimensional visualization of human structure that is essential to applications in clinical practice and the understanding of function. The program allows the student to take apart and to accurately put together body components in an interactive, self-paced and variable manner to achieve the learning outcome.

  14. Veterinary and human medicine: learning from each other.

    Science.gov (United States)

    Honey, Laura

    2016-03-26

    A well-attended session at this year's joint SPVS/VPMA congress considered what lessons the medical and veterinary professions might learn from one another. Laura Honey reports. British Veterinary Association.

  15. Understanding Collective Learning and Human Agency in Diverse ...

    African Journals Online (AJOL)

    2018-05-07

    May 7, 2018 ... new social systems that are more sustainable and socially just. ... collection to these international deliberations about the role of education in enabling ... learning can foster and contribute to the development of change agents ...

  16. Dependent Narcissism, Organizational Learning, and Human Resource Development

    Science.gov (United States)

    Godkin, Lynn; Allcorn, Seth

    2009-01-01

    Narcissistic leadership can benefit organizational performance. Aberrant narcissism can destroy the psychosocial health of groups, limiting performance. This article examines Dependent Organizational Disorder, a common form of narcissism, which infects leadership, thwarts performance, and interrupts organizational learning. Dependent…

  17. Human learning: Power laws or multiple characteristic time scales?

    Directory of Open Access Journals (Sweden)

    Gottfried Mayer-Kress

    2006-09-01

    Full Text Available The central proposal of A. Newell and Rosenbloom (1981 was that the power law is the ubiquitous law of learning. This proposition is discussed in the context of the key factors that led to the acceptance of the power law as the function of learning. We then outline the principles of an epigenetic landscape framework for considering the role of the characteristic time scales of learning and an approach to system identification of the processes of performance dynamics. In this view, the change of performance over time is the product of a superposition of characteristic exponential time scales that reflect the influence of different processes. This theoretical approach can reproduce the traditional power law of practice – within the experimental resolution of performance data sets - but we hypothesize that this function may prove to be a special and perhaps idealized case of learning.

  18. The composition of category conjunctions.

    Science.gov (United States)

    Hutter, Russell R C; Crisp, Richard J

    2005-05-01

    In three experiments, the authors investigated the impression formation process resulting from the perception of familiar or unfamiliar social category combinations. In Experiment 1, participants were asked to generate attributes associated with either a familiar or unfamiliar social category conjunction. Compared to familiar combinations, the authors found that when the conjunction was unfamiliar, participants formed their impression less from the individual constituent categories and relatively more from novel emergent attributes. In Experiment 2, the authors replicated this effect using alternative experimental materials. In Experiment 3, the effect generalized to additional (orthogonally combined) gender and occupation categories. The implications of these findings for understanding the processes involved in the conjunction of social categories, and the formation of new stereotypes, are discussed.

  19. Neural prediction errors reveal a risk-sensitive reinforcement-learning process in the human brain.

    Science.gov (United States)

    Niv, Yael; Edlund, Jeffrey A; Dayan, Peter; O'Doherty, John P

    2012-01-11

    Humans and animals are exquisitely, though idiosyncratically, sensitive to risk or variance in the outcomes of their actions. Economic, psychological, and neural aspects of this are well studied when information about risk is provided explicitly. However, we must normally learn about outcomes from experience, through trial and error. Traditional models of such reinforcement learning focus on learning about the mean reward value of cues and ignore higher order moments such as variance. We used fMRI to test whether the neural correlates of human reinforcement learning are sensitive to experienced risk. Our analysis focused on anatomically delineated regions of a priori interest in the nucleus accumbens, where blood oxygenation level-dependent (BOLD) signals have been suggested as correlating with quantities derived from reinforcement learning. We first provide unbiased evidence that the raw BOLD signal in these regions corresponds closely to a reward prediction error. We then derive from this signal the learned values of cues that predict rewards of equal mean but different variance and show that these values are indeed modulated by experienced risk. Moreover, a close neurometric-psychometric coupling exists between the fluctuations of the experience-based evaluations of risky options that we measured neurally and the fluctuations in behavioral risk aversion. This suggests that risk sensitivity is integral to human learning, illuminating economic models of choice, neuroscientific models of affective learning, and the workings of the underlying neural mechanisms.

  20. Empowering Learning through Natural, Human, and Building Ecologies.

    Science.gov (United States)

    Kobet, Robert J.

    This article asserts that it is critical to understand the connections between human ecology and building ecology to create humane environments that show inspiration and creativity and that also serve diverse needs. It calls for efforts to: (1) construct an environmental education approach that fuses the three ecologies (natural, human, and…

  1. Social categories as markers of intrinsic interpersonal obligations.

    Science.gov (United States)

    Rhodes, Marjorie; Chalik, Lisa

    2013-06-01

    Social categorization is an early-developing feature of human social cognition, yet the role that social categories play in children's understanding of and predictions about human behavior has been unclear. In the studies reported here, we tested whether a foundational functional role of social categories is to mark people as intrinsically obligated to one another (e.g., obligated to protect rather than harm). In three studies, children (aged 3-9, N = 124) viewed only within-category harm as violating intrinsic obligations; in contrast, they viewed between-category harm as violating extrinsic obligations defined by explicit rules. These data indicate that children view social categories as marking patterns of intrinsic interpersonal obligations, suggesting that a key function of social categories is to support inferences about how people will relate to members of their own and other groups.

  2. Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

    Science.gov (United States)

    Marucci-Wellman, Helen R; Corns, Helen L; Lehto, Mark R

    2017-01-01

    Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NB SW =NB BI-GRAM =SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as

  3. Towards Semantic Analysis of Training-Learning Relationships within Human-Machine Interactions

    DEFF Research Database (Denmark)

    Badie, Farshad

    2016-01-01

    In this article First-Order Predicate Logic (FOL) is employed for analysing some relationships between human beings and machines. Based on FOL, I will be conceptually and logically concerned with semantic analysis of training-learning relationships in human-machine interaction. The central focus...

  4. Inquiry-Based Learning in Teacher Education: A Primary Humanities Example

    Science.gov (United States)

    Preston, Lou; Harvie, Kate; Wallace, Heather

    2015-01-01

    Inquiry-based learning features strongly in the new Australian Humanities and Social Sciences curriculum and increasingly in primary school practice. Yet, there is little research into, and few exemplars of, inquiry approaches in the primary humanities context. In this article, we outline and explain the implementation of a place-based simulation…

  5. Waist-High and Knee-Deep: Humane Learning beyond Polemics and Precincts

    Science.gov (United States)

    Higgins, Chris

    2015-01-01

    In this essay, Chris Higgins sets out to disentangle the tradition of humane learning from contemporary distinctions and debates. The first section demonstrates how a bloated and incoherent "humanism" now functions primarily as a talisman or a target, that is, as a prompt to choose sides. It closes with the image of Doris Salcedo's…

  6. Intrinsic interactive reinforcement learning - Using error-related potentials for real world human-robot interaction.

    Science.gov (United States)

    Kim, Su Kyoung; Kirchner, Elsa Andrea; Stefes, Arne; Kirchner, Frank

    2017-12-14

    Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic environments based on feedback. Explicit human feedback during robot RL is advantageous, since an explicit reward function can be easily adapted. However, it is very demanding and tiresome for a human to continuously and explicitly generate feedback. Therefore, the development of implicit approaches is of high relevance. In this paper, we used an error-related potential (ErrP), an event-related activity in the human electroencephalogram (EEG), as an intrinsically generated implicit feedback (rewards) for RL. Initially we validated our approach with seven subjects in a simulated robot learning scenario. ErrPs were detected online in single trial with a balanced accuracy (bACC) of 91%, which was sufficient to learn to recognize gestures and the correct mapping between human gestures and robot actions in parallel. Finally, we validated our approach in a real robot scenario, in which seven subjects freely chose gestures and the real robot correctly learned the mapping between gestures and actions (ErrP detection (90% bACC)). In this paper, we demonstrated that intrinsically generated EEG-based human feedback in RL can successfully be used to implicitly improve gesture-based robot control during human-robot interaction. We call our approach intrinsic interactive RL.

  7. A Conceptual Framework over Contextual Analysis of Concept Learning within Human-Machine Interplays

    DEFF Research Database (Denmark)

    Badie, Farshad

    2016-01-01

    This research provides a contextual description concerning existential and structural analysis of ‘Relations’ between human beings and machines. Subsequently, it will focus on conceptual and epistemological analysis of (i) my own semantics-based framework [for human meaning construction] and of (ii......) a well-structured machine concept learning framework. Accordingly, I will, semantically and epistemologically, focus on linking those two frameworks for logical analysis of concept learning in the context of human-machine interrelationships. It will be demonstrated that the proposed framework provides...

  8. How do Category Managers Manage?

    DEFF Research Database (Denmark)

    Hald, Kim Sundtoft; Sigurbjornsson, Tomas

    2013-01-01

    The aim of this research is to explore the managerial role of category managers in purchasing. A network management perspective is adopted. A case based research methodology is applied, and three category managers managing a diverse set of component and service categories in a global production...... firm is observed while providing accounts of their progress and results in meetings. We conclude that the network management classification scheme originally deve loped by Harland and Knight (2001) and Knight and Harland (2005) is a valuable and fertile theoretical framework for the analysis...

  9. Using a model of human visual perception to improve deep learning.

    Science.gov (United States)

    Stettler, Michael; Francis, Gregory

    2018-04-17

    Deep learning algorithms achieve human-level (or better) performance on many tasks, but there still remain situations where humans learn better or faster. With regard to classification of images, we argue that some of those situations are because the human visual system represents information in a format that promotes good training and classification. To demonstrate this idea, we show how occluding objects can impair performance of a deep learning system that is trained to classify digits in the MNIST database. We describe a human inspired segmentation and interpolation algorithm that attempts to reconstruct occluded parts of an image, and we show that using this reconstruction algorithm to pre-process occluded images promotes training and classification performance. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Perceptions of nursing undergraduate students concerning the human dimension in the learning process.

    Science.gov (United States)

    de Oliveira Camillo, Simone; Lúcia da Silva, Ana; Jefferson do Nascimento, Alan

    2007-01-01

    This study aimed to identify and interpret the perceptions presented by undergraduate students of a Nursing course after internship in Mental Health. Twelve nursing undergraduate students at the Nursing School of ABC Foundation - Santo André, São Paulo, Brazil were interviewed. These interviews using a semi-structure script were performed and recorded in August 2004. Through Content Analysis, thematic modality, four categories were identified, 1. mental health: providing understanding of the other; 2. respect for the human being: the importance of listening, 3. mental health: contributing for a contextualized view of the patient and 4. nursing graduation: undesirable "signs and symptoms" of the profession. The analysis and the discussion of these categories suggest the possibility of teaching based on the human condition. Thus, we support the idea of new research been carried out, considering that the Mental Health discipline must be valued in the Political and Pedagogical projects of the Nursing Undergraduate Courses.

  11. Human Computation An Integrated Approach to Learning from the Crowd

    CERN Document Server

    Law, Edith

    2011-01-01

    Human computation is a new and evolving research area that centers around harnessing human intelligence to solve computational problems that are beyond the scope of existing Artificial Intelligence (AI) algorithms. With the growth of the Web, human computation systems can now leverage the abilities of an unprecedented number of people via the Web to perform complex computation. There are various genres of human computation applications that exist today. Games with a purpose (e.g., the ESP Game) specifically target online gamers who generate useful data (e.g., image tags) while playing an enjoy

  12. Right away: A late, right-lateralized category effect complements an early, left-lateralized category effect in visual search.

    Science.gov (United States)

    Constable, Merryn D; Becker, Stefanie I

    2017-10-01

    According to the Sapir-Whorf hypothesis, learned semantic categories can influence early perceptual processes. A central finding in support of this view is the lateralized category effect-namely, the finding that categorically different colors (e.g., blue and green hues) can be discriminated faster than colors within the same color category (e.g., different hues of green), especially when they are presented in the right visual field. Because the right visual field projects to the left hemisphere, this finding has been popularly couched in terms of the left-lateralization of language. However, other studies have reported bilateral category effects, which has led some researchers to question the linguistic origins of the effect. Here we examined the time course of lateralized and bilateral category effects in the classical visual search paradigm by means of eyetracking and RT distribution analyses. Our results show a bilateral category effect in the manual responses, which is combined of an early, left-lateralized category effect and a later, right-lateralized category effect. The newly discovered late, right-lateralized category effect occurred only when observers had difficulty locating the target, indicating a specialization of the right hemisphere to find categorically different targets after an initial error. The finding that early and late stages of visual search show different lateralized category effects can explain a wide range of previously discrepant findings.

  13. Understanding Collective Learning and Human Agency in Diverse ...

    African Journals Online (AJOL)

    2018-05-07

    May 7, 2018 ... made between students' lives, their African identities and local natural places. Introduction to the Think Piece Collection: 'Collective Learning and Change ... is increasingly recognised in the social-ecological and global change sciences. For example, ..... processes that allow for the change agent to act.

  14. Slower Reacquisition after Partial Extinction in Human Contingency Learning

    Science.gov (United States)

    Morís, Joaquín; Barberia, Itxaso; Vadillo, Miguel A.; Andrades, Ainhoa; López, Francisco J.

    2017-01-01

    Extinction is a very relevant learning phenomenon from a theoretical and applied point of view. One of its most relevant features is that relapse phenomena often take place once the extinction training has been completed. Accordingly, as extinction-based therapies constitute the most widespread empirically validated treatment of anxiety disorders,…

  15. Learning Intercultural Communication Skills with Virtual Humans: Feedback and Fidelity

    Science.gov (United States)

    Lane, H. Chad; Hays, Matthew Jensen; Core, Mark G.; Auerbach, Daniel

    2013-01-01

    In the context of practicing intercultural communication skills, we investigated the role of fidelity in a game-based, virtual learning environment as well as the role of feedback delivered by an intelligent tutoring system. In 2 experiments, we compared variations on the game interface, use of the tutoring system, and the form of the feedback.…

  16. Human Economy and Entrepreneurial Learning in a Voluntary Organization

    DEFF Research Database (Denmark)

    Revsbech, Christine

    2014-01-01

    "Based on five months anthropological field study in a British affiliate of an American charity in London, Revsbech asks what does learning look like in a social voluntary organization for youth. Her chapter argues that volunteers develop entrepreneurial abilities by shifting flexibly between...

  17. Homological algebra in -abelian categories

    Indian Academy of Sciences (India)

    Deren Luo

    2017-08-16

    Aug 16, 2017 ... Homological algebra in n-abelian categories. 627. We recall the Comparison lemma, together with its dual, plays a central role in the sequel. Lemma 2.1 [13, Comparison lemma 2.1]. Let C be an additive category and X ∈ Ch. ≥0(C) a complex such that for all k ≥ 0the morphism dk+1. X is a weak cokernel ...

  18. Pragmatic Frames for Teaching and Learning in Human-Robot Interaction: Review and Challenges.

    Science.gov (United States)

    Vollmer, Anna-Lisa; Wrede, Britta; Rohlfing, Katharina J; Oudeyer, Pierre-Yves

    2016-01-01

    One of the big challenges in robotics today is to learn from human users that are inexperienced in interacting with robots but yet are often used to teach skills flexibly to other humans and to children in particular. A potential route toward natural and efficient learning and teaching in Human-Robot Interaction (HRI) is to leverage the social competences of humans and the underlying interactional mechanisms. In this perspective, this article discusses the importance of pragmatic frames as flexible interaction protocols that provide important contextual cues to enable learners to infer new action or language skills and teachers to convey these cues. After defining and discussing the concept of pragmatic frames, grounded in decades of research in developmental psychology, we study a selection of HRI work in the literature which has focused on learning-teaching interaction and analyze the interactional and learning mechanisms that were used in the light of pragmatic frames. This allows us to show that many of the works have already used in practice, but not always explicitly, basic elements of the pragmatic frames machinery. However, we also show that pragmatic frames have so far been used in a very restricted way as compared to how they are used in human-human interaction and argue that this has been an obstacle preventing robust natural multi-task learning and teaching in HRI. In particular, we explain that two central features of human pragmatic frames, mostly absent of existing HRI studies, are that (1) social peers use rich repertoires of frames, potentially combined together, to convey and infer multiple kinds of cues; (2) new frames can be learnt continually, building on existing ones, and guiding the interaction toward higher levels of complexity and expressivity. To conclude, we give an outlook on the future research direction describing the relevant key challenges that need to be solved for leveraging pragmatic frames for robot learning and teaching.

  19. A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

    Science.gov (United States)

    Bassett, Danielle S; Mattar, Marcelo G

    2017-04-01

    Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Evolution of social learning does not explain the origin of human cumulative culture.

    Science.gov (United States)

    Enquist, Magnus; Ghirlanda, Stefano

    2007-05-07

    Because culture requires transmission of information between individuals, thinking about the origin of culture has mainly focused on the genetic evolution of abilities for social learning. Current theory considers how social learning affects the adaptiveness of a single cultural trait, yet human culture consists of the accumulation of very many traits. Here we introduce a new modeling strategy that tracks the adaptive value of many cultural traits, showing that genetic evolution favors only limited social learning owing to the accumulation of maladaptive as well as adaptive culture. We further show that culture can be adaptive, and refined social learning can evolve, if individuals can identify and discard maladaptive culture. This suggests that the evolution of such "adaptive filtering" mechanisms may have been crucial for the birth of human culture.

  1. Testing a measure of organizational learning capacity and readiness for transformational change in human services.

    Science.gov (United States)

    Bess, Kimberly D; Perkins, Douglas D; McCown, Diana L

    2011-01-01

    Transformative organizational change requires organizational learning capacity, which we define in terms of (1) internal and (2) external organizational systems alignment, and promoting a culture of learning, including (3) an emphasis on exploration and information, (4) open communication, (5) staff empowerment, and (6) support for professional development. We shortened and adapted Watkins and Marsick's Dimensions of Learning Organizations Questionnaire into a new 16-item Organizational Learning Capacity Scale (OLCS) geared more toward nonprofit organizations. The OLCS and its subscales measuring each of the above 6 dimensions are unusually reliable for their brevity. ANOVAs for the OLCS and subscales clearly and consistently confirmed extensive participant observations and other qualitative data from four nonprofit human service organizations and one local human service funding organization.

  2. The Effect of Contextual Teaching and Learning Combined with Peer Tutoring towards Learning Achievement on Human Digestive System Concept

    Directory of Open Access Journals (Sweden)

    Farhah Abadiyah

    2017-11-01

    Full Text Available This research aims to know the influence of contextual teaching and learning (CTL combined with peer tutoring toward learning achievement on human digestive system concept. This research was conducted at one of State Senior High School in South Tangerang in the academic year of 2016/2017. The research method was quasi experiment with nonequivalent pretest-postest control group design. The sample was taken by simple random sampling. The total of the sampels were 86 students which consisted of 44 students as a controlled group and 42 students as an experimental group. The research instrument was objective test which consisted of 25 multiple choice items of each pretest and posttest. The research also used observation sheets for teacher and students activity. The result of data analysis using t-test on the two groups show that the value of tcount was 2.40 and ttable was 1.99 on significant level α = 0,05, so that tcount > ttable.. This result indicated that there was influence of contextual teaching and learning (CTL combined with peer tutoring toward learning achievement on human digestive system concept.

  3. Previous experience in manned space flight: A survey of human factors lessons learned

    Science.gov (United States)

    Chandlee, George O.; Woolford, Barbara

    1993-01-01

    Previous experience in manned space flight programs can be used to compile a data base of human factors lessons learned for the purpose of developing aids in the future design of inhabited spacecraft. The objectives are to gather information available from relevant sources, to develop a taxonomy of human factors data, and to produce a data base that can be used in the future for those people involved in the design of manned spacecraft operations. A study is currently underway at the Johnson Space Center with the objective of compiling, classifying, and summarizing relevant human factors data bearing on the lessons learned from previous manned space flights. The research reported defines sources of data, methods for collection, and proposes a classification for human factors data that may be a model for other human factors disciplines.

  4. The Virtual Teacher (VT) Paradigm: Learning New Patterns of Interpersonal Coordination Using the Human Dynamic Clamp.

    Science.gov (United States)

    Kostrubiec, Viviane; Dumas, Guillaume; Zanone, Pier-Giorgio; Kelso, J A Scott

    2015-01-01

    The Virtual Teacher paradigm, a version of the Human Dynamic Clamp (HDC), is introduced into studies of learning patterns of inter-personal coordination. Combining mathematical modeling and experimentation, we investigate how the HDC may be used as a Virtual Teacher (VT) to help humans co-produce and internalize new inter-personal coordination pattern(s). Human learners produced rhythmic finger movements whilst observing a computer-driven avatar, animated by dynamic equations stemming from the well-established Haken-Kelso-Bunz (1985) and Schöner-Kelso (1988) models of coordination. We demonstrate that the VT is successful in shifting the pattern co-produced by the VT-human system toward any value (Experiment 1) and that the VT can help humans learn unstable relative phasing patterns (Experiment 2). Using transfer entropy, we find that information flow from one partner to the other increases when VT-human coordination loses stability. This suggests that variable joint performance may actually facilitate interaction, and in the long run learning. VT appears to be a promising tool for exploring basic learning processes involved in social interaction, unraveling the dynamics of information flow between interacting partners, and providing possible rehabilitation opportunities.

  5. Using Supervised Deep Learning for Human Age Estimation Problem

    Science.gov (United States)

    Drobnyh, K. A.; Polovinkin, A. N.

    2017-05-01

    Automatic facial age estimation is a challenging task upcoming in recent years. In this paper, we propose using the supervised deep learning features to improve an accuracy of the existing age estimation algorithms. There are many approaches solving the problem, an active appearance model and the bio-inspired features are two of them which showed the best accuracy. For experiments we chose popular publicly available FG-NET database, which contains 1002 images with a broad variety of light, pose, and expression. LOPO (leave-one-person-out) method was used to estimate the accuracy. Experiments demonstrated that adding supervised deep learning features has improved accuracy for some basic models. For example, adding the features to an active appearance model gave the 4% gain (the error decreased from 4.59 to 4.41).

  6. Sampling capacity underlies individual differences in human associative learning.

    Science.gov (United States)

    Byrom, Nicola C; Murphy, Robin A

    2014-04-01

    Though much work has studied how external factors, such as stimulus properties, influence generalization of associative strength, there has been limited exploration of the influence that internal dispositions may contribute to stimulus processing. Here we report 2 studies using a modified negative patterning discrimination to test the relationship between global processing and generalization. Global processing was associated with stronger negative patterning discrimination, indicative of limited generalization between distinct stimulus compounds and their constituent elements. In Experiment 2, participants pretrained to adopt global processing similarly showed strong negative patterning discrimination. These results demonstrate considerable individual difference in capacity to engage in negative patterning discrimination and suggest that the tendency toward global processing may be one factor explaining this variability. The need for models of learning to account for this variability in learning is discussed.

  7. Neural Computations Mediating One-Shot Learning in the Human Brain

    Science.gov (United States)

    Lee, Sang Wan; O’Doherty, John P.; Shimojo, Shinsuke

    2015-01-01

    Incremental learning, in which new knowledge is acquired gradually through trial and error, can be distinguished from one-shot learning, in which the brain learns rapidly from only a single pairing of a stimulus and a consequence. Very little is known about how the brain transitions between these two fundamentally different forms of learning. Here we test a computational hypothesis that uncertainty about the causal relationship between a stimulus and an outcome induces rapid changes in the rate of learning, which in turn mediates the transition between incremental and one-shot learning. By using a novel behavioral task in combination with functional magnetic resonance imaging (fMRI) data from human volunteers, we found evidence implicating the ventrolateral prefrontal cortex and hippocampus in this process. The hippocampus was selectively “switched” on when one-shot learning was predicted to occur, while the ventrolateral prefrontal cortex was found to encode uncertainty about the causal association, exhibiting increased coupling with the hippocampus for high-learning rates, suggesting this region may act as a “switch,” turning on and off one-shot learning as required. PMID:25919291

  8. One-trial overshadowing: Evidence for fast specific fear learning in humans.

    Science.gov (United States)

    Haesen, Kim; Beckers, Tom; Baeyens, Frank; Vervliet, Bram

    2017-03-01

    Adaptive defensive actions necessitate a fear learning system that is both fast and specific. Fast learning serves to minimize the number of threat confrontations, while specific learning ensures that the acquired fears are tied to threat-relevant cues only. In Pavlovian fear conditioning, fear acquisition is typically studied via repetitive pairings of a single cue with an aversive experience, which is not optimal for the examination of fast specific fear learning. In this study, we adopted the one-trial overshadowing procedure from basic learning research, in which a combination of two visual cues is presented once and paired with an aversive electrical stimulation. Using on-line shock expectancy ratings, skin conductance reactivity and startle reflex modulation as indices of fear learning, we found evidence of strong fear after a single conditioning trial (fast learning) as well as attenuated fear responding when only half of the trained stimulus combination was presented (specific learning). Moreover, specificity of fear responding tended to correlate with levels of state and trait anxiety. These results suggest that one-trial overshadowing can be used as a model to study fast specific fear learning in humans and individual differences therein. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Assortative social learning and its implications for human (and animal?) societies.

    Science.gov (United States)

    Katsnelson, Edith; Lotem, Arnon; Feldman, Marcus W

    2014-07-01

    Choosing from whom to learn is an important element of social learning. It affects learner success and the profile of behaviors in the population. Because individuals often differ in their traits and capabilities, their benefits from different behaviors may also vary. Homophily, or assortment, the tendency of individuals to interact with other individuals with similar traits, is known to affect the spread of behaviors in humans. We introduce models to study the evolution of assortative social learning (ASL), where assorting on a trait acts as an individual-specific mechanism for filtering relevant models from which to learn when that trait varies. We show that when the trait is polymorphic, ASL may maintain a stable behavioral polymorphism within a population (independently of coexistence with individual learning in a population). We explore the evolution of ASL when assortment is based on a nonheritable or partially heritable trait, and when ASL competes with different non-ASL strategies: oblique (learning from the parental generation) and vertical (learning from the parent). We suggest that the tendency to assort may be advantageous in the context of social learning, and that ASL might be an important concept for the evolutionary theory of social learning. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

  10. Neural computations mediating one-shot learning in the human brain.

    Directory of Open Access Journals (Sweden)

    Sang Wan Lee

    2015-04-01

    Full Text Available Incremental learning, in which new knowledge is acquired gradually through trial and error, can be distinguished from one-shot learning, in which the brain learns rapidly from only a single pairing of a stimulus and a consequence. Very little is known about how the brain transitions between these two fundamentally different forms of learning. Here we test a computational hypothesis that uncertainty about the causal relationship between a stimulus and an outcome induces rapid changes in the rate of learning, which in turn mediates the transition between incremental and one-shot learning. By using a novel behavioral task in combination with functional magnetic resonance imaging (fMRI data from human volunteers, we found evidence implicating the ventrolateral prefrontal cortex and hippocampus in this process. The hippocampus was selectively "switched" on when one-shot learning was predicted to occur, while the ventrolateral prefrontal cortex was found to encode uncertainty about the causal association, exhibiting increased coupling with the hippocampus for high-learning rates, suggesting this region may act as a "switch," turning on and off one-shot learning as required.

  11. Thalamic Control of Human Attention Driven by Memory and Learning

    OpenAIRE

    de Bourbon-Teles, José; Bentley, Paul; Koshino, Saori; Shah, Kushal; Dutta, Agneish; Malhotra, Paresh; Egner, Tobias; Husain, Masud; Soto, David

    2014-01-01

    Summary The role of the thalamus in high-level cognition—attention, working memory (WM), rule-based learning, and decision making—remains poorly understood, especially in comparison to that of cortical frontoparietal networks [1–3]. Studies of visual thalamus have revealed important roles for pulvinar and lateral geniculate nucleus in visuospatial perception and attention [4–10] and for mediodorsal thalamus in oculomotor control [11]. Ventrolateral thalamus contains subdivisions devoted to ac...

  12. Learning to Understand Natural Language with Less Human Effort

    Science.gov (United States)

    2015-05-01

    Supervision Distant supervision is a recent trend in information extraction. Distantly-supervised extractors are trained using a corpus of unlabeled text...consists of fill-in-the-blank natural language questions such as “Incan emperor ” or “Cunningham directed Auchtre’s second music video .” These questions...with an 132 unknown knowledge base, simultaneously learning how to semantically parse language and pop - ulate the knowledge base. The weakly

  13. Original article Temperamental variation in learned irrelevance in humans

    Directory of Open Access Journals (Sweden)

    Aleksandra Gruszka

    2015-07-01

    Full Text Available Background Learned irrelevance (LIRR represents one of the mechanisms of attentional set-shifting and refers to the inability to attend to, or to learn about, any aspect of a stimulus previously experienced as irrelevant. Although it has been extensively studied in the context of clinical populations, not much is known about LIRR effects in relation to normal variation in individual differences. The present study was designed to assess how temperamental factors may modulate LIRR. Participants and procedures Sixty-eight healthy volunteers performed a visual discrimination learning task modelled after Wisconsin Card Sorting Test. To test the susceptibility to learned irrelevance, participants were expected to shift their attention either to a dimension that prior to the extra-dimensional shift was completely irrelevant, or to a dimension that was previously partly correlated with reinforcement. Temperamental traits were assessed using the Formal Characteristics of Behaviour-Temperament Inventory (Zawadzki & Strelau, 1997. Intelligence level was stratified according to Raven’s Advanced Progressive Matrices (Raven, Raven, & Court, 2003. Results Low level of Briskness and high level of Perseverance were related to enhanced susceptibility to LIRR. High levels of Activity and Emotional Reactivity were related to the poorer performance on the extra-dimensional set-shifting. No effects of other temperament characteristics or intelligence on LIRR were observed. Conclusions The results confirm a strong variation in LIRR related to individual differences in temperament, which appears to be unrelated to DA function. Our results highlight the importance of considering individual differences in studies on cognitive control.

  14. Holography: A Transformative Technology for Learning and Human Performance Improvement

    Science.gov (United States)

    Frazer, Gary W.; Stevens, George H.

    2015-01-01

    Most past and current learning technologies have been one- or two-dimensional in presentation. This may be fine if one is looking at a map or even a fine painting. However, to fully appreciate the detail of a statue or a machine part, it is better to be able to look at it from all sides. Use of holographic images allows an item to be shared with a…

  15. Hedging Your Bets by Learning Reward Correlations in the Human Brain

    Science.gov (United States)

    Wunderlich, Klaus; Symmonds, Mkael; Bossaerts, Peter; Dolan, Raymond J.

    2011-01-01

    Summary Human subjects are proficient at tracking the mean and variance of rewards and updating these via prediction errors. Here, we addressed whether humans can also learn about higher-order relationships between distinct environmental outcomes, a defining ecological feature of contexts where multiple sources of rewards are available. By manipulating the degree to which distinct outcomes are correlated, we show that subjects implemented an explicit model-based strategy to learn the associated outcome correlations and were adept in using that information to dynamically adjust their choices in a task that required a minimization of outcome variance. Importantly, the experimentally generated outcome correlations were explicitly represented neuronally in right midinsula with a learning prediction error signal expressed in rostral anterior cingulate cortex. Thus, our data show that the human brain represents higher-order correlation structures between rewards, a core adaptive ability whose immediate benefit is optimized sampling. PMID:21943609

  16. Comparing statistical and machine learning classifiers: alternatives for predictive modeling in human factors research.

    Science.gov (United States)

    Carnahan, Brian; Meyer, Gérard; Kuntz, Lois-Ann

    2003-01-01

    Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches--genetic programming and decision tree induction--were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.

  17. A Benefit/Cost/Deficit (BCD) model for learning from human errors

    International Nuclear Information System (INIS)

    Vanderhaegen, Frederic; Zieba, Stephane; Enjalbert, Simon; Polet, Philippe

    2011-01-01

    This paper proposes an original model for interpreting human errors, mainly violations, in terms of benefits, costs and potential deficits. This BCD model is then used as an input framework to learn from human errors, and two systems based on this model are developed: a case-based reasoning system and an artificial neural network system. These systems are used to predict a specific human car driving violation: not respecting the priority-to-the-right rule, which is a decision to remove a barrier. Both prediction systems learn from previous violation occurrences, using the BCD model and four criteria: safety, for identifying the deficit or the danger; and opportunity for action, driver comfort, and time spent; for identifying the benefits or the costs. The application of learning systems to predict car driving violations gives a rate over 80% of correct prediction after 10 iterations. These results are validated for the non-respect of priority-to-the-right rule.

  18. Using virtual humans and computer animations to learn complex motor skills: a case study in karate

    Directory of Open Access Journals (Sweden)

    Spanlang Bernhard

    2011-12-01

    Full Text Available Learning motor skills is a complex task involving a lot of cognitive issues. One of the main issues consists in retrieving the relevant information from the learning environment. In a traditional learning situation, a teacher gives oral explanations and performs actions to provide the learner with visual examples. Using virtual reality (VR as a tool for learning motor tasks is promising. However, it raises questions about the type of information this kind of environments can offer. In this paper, we propose to analyze the impact of virtual humans on the perception of the learners. As a case study, we propose to apply this research problem to karate gestures. The results of this study show no significant difference on the after training performance of learners confronted to three different learning environments (traditional group, video and VR.

  19. Human factors in resuscitation: Lessons learned from simulator studies

    Directory of Open Access Journals (Sweden)

    Hunziker S

    2010-01-01

    Full Text Available Medical algorithms, technical skills, and repeated training are the classical cornerstones for successful cardiopulmonary resuscitation (CPR. Increasing evidence suggests that human factors, including team interaction, communication, and leadership, also influence the performance of CPR. Guidelines, however, do not yet include these human factors, partly because of the difficulties of their measurement in real-life cardiac arrest. Recently, clinical studies of cardiac arrest scenarios with high-fidelity video-assisted simulations have provided opportunities to better delineate the influence of human factors on resuscitation team performance. This review focuses on evidence from simulator studies that focus on human factors and their influence on the performance of resuscitation teams. Similar to studies in real patients, simulated cardiac arrest scenarios revealed many unnecessary interruptions of CPR as well as significant delays in defibrillation. These studies also showed that human factors play a major role in these shortcomings and that the medical performance depends on the quality of leadership and team-structuring. Moreover, simulated video-taped medical emergencies revealed that a substantial part of information transfer during communication is erroneous. Understanding the impact of human factors on the performance of a complex medical intervention like resuscitation requires detailed, second-by-second, analysis of factors involving the patient, resuscitative equipment such as the defibrillator, and all team members. Thus, high-fidelity simulator studies provide an important research method in this challenging field.

  20. Observing tutorial dialogues collaboratively: insights about human tutoring effectiveness from vicarious learning.

    Science.gov (United States)

    Chi, Michelene T H; Roy, Marguerite; Hausmann, Robert G M

    2008-03-01

    The goals of this study are to evaluate a relatively novel learning environment, as well as to seek greater understanding of why human tutoring is so effective. This alternative learning environment consists of pairs of students collaboratively observing a videotape of another student being tutored. Comparing this collaboratively observing environment to four other instructional methods-one-on-one human tutoring, observing tutoring individually, collaborating without observing, and studying alone-the results showed that students learned to solve physics problems just as effectively from observing tutoring collaboratively as the tutees who were being tutored individually. We explain the effectiveness of this learning environment by postulating that such a situation encourages learners to become active and constructive observers through interactions with a peer. In essence, collaboratively observing combines the benefit of tutoring with the benefit of collaborating. The learning outcomes of the tutees and the collaborative observers, along with the tutoring dialogues, were used to further evaluate three hypotheses explaining why human tutoring is an effective learning method. Detailed analyses of the protocols at several grain sizes suggest that tutoring is effective when tutees are independently or jointly constructing knowledge: with the tutor, but not when the tutor independently conveys knowledge. 2008 Cognitive Science Society, Inc.

  1. Witnessing change with aspiring nurses: a human becoming teaching-learning process in nursing education.

    Science.gov (United States)

    Letcher, Deborah C; Yancey, Nan Russell

    2004-01-01

    Nurse educators have the opportunity to encourage meaningful reflections of nursing students. Dr. Rosemarie Rizzo Parse's teaching-learning processes provide a framework for such experiences. Student reflection through journaling and student participation in dialogue using these processes brings about an opportunity for students to discover new meaning for themselves and others. The process of how two nurse educators incorporated the human becoming teaching-learning model into students' experiences is discussed. Excerpts of student journals, themes of student work, and considerations for future development of the teaching-learning model with students are discussed.

  2. Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans.

    Science.gov (United States)

    Fouragnan, Elsa; Queirazza, Filippo; Retzler, Chris; Mullinger, Karen J; Philiastides, Marios G

    2017-07-06

    Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo-mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning.

  3. A Comprehensive Review on Handcrafted and Learning-Based Action Representation Approaches for Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Allah Bux Sargano

    2017-01-01

    Full Text Available Human activity recognition (HAR is an important research area in the fields of human perception and computer vision due to its wide range of applications. These applications include: intelligent video surveillance, ambient assisted living, human computer interaction, human-robot interaction, entertainment, and intelligent driving. Recently, with the emergence and successful deployment of deep learning techniques for image classification, researchers have migrated from traditional handcrafting to deep learning techniques for HAR. However, handcrafted representation-based approaches are still widely used due to some bottlenecks such as computational complexity of deep learning techniques for activity recognition. However, approaches based on handcrafted representation are not able to handle complex scenarios due to their limitations and incapability; therefore, resorting to deep learning-based techniques is a natural option. This review paper presents a comprehensive survey of both handcrafted and learning-based action representations, offering comparison, analysis, and discussions on these approaches. In addition to this, the well-known public datasets available for experimentations and important applications of HAR are also presented to provide further insight into the field. This is the first review paper of its kind which presents all these aspects of HAR in a single review article with comprehensive coverage of each part. Finally, the paper is concluded with important discussions and research directions in the domain of HAR.

  4. Feature Inference Learning and Eyetracking

    Science.gov (United States)

    Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.

    2009-01-01

    Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…

  5. Typicality effects in artificial categories: is there a hemisphere difference?

    Science.gov (United States)

    Richards, L G; Chiarello, C

    1990-07-01

    In category classification tasks, typicality effects are usually found: accuracy and reaction time depend upon distance from a prototype. In this study, subjects learned either verbal or nonverbal dot pattern categories, followed by a lateralized classification task. Comparable typicality effects were found in both reaction time and accuracy across visual fields for both verbal and nonverbal categories. Both hemispheres appeared to use a similarity-to-prototype matching strategy in classification. This indicates that merely having a verbal label does not differentiate classification in the two hemispheres.

  6. Category O for quantum groups

    DEFF Research Database (Denmark)

    Andersen, Henning Haahr; Mazorchuk, Volodymyr

    2015-01-01

    We study the BGG-categories O_q associated to quantum groups. We prove that many properties of the ordinary BGG-category O for a semisimple complex Lie algebra carry over to the quantum case. Of particular interest is the case when q is a complex root of unity. Here we prove a tensor decomposition...... for simple modules, projective modules, and indecomposable tilting modules. Using the known Kazhdan–Lusztig conjectures for O and for finite-dimensional U_q-modules we are able to determine all irreducible characters as well as the characters of all indecomposable tilting modules in O_q . As a consequence......, we also recover the known result that the generic quantum case behaves like the classical category O....

  7. Teaching medical humanities in the digital world: affordances of technology-enhanced learning.

    Science.gov (United States)

    Kemp, Sandra Joy; Day, Giskin

    2014-12-01

    Medical humanities courses are typically taught in face-to-face teaching environments, but now medical humanities educators, alongside educators from other disciplines, are facing shifts in higher education towards online (and sometimes open) courses. For the medical humanities educator, there is limited guidance regarding how technology-enhanced learning design can support the learning outcomes associated with medical humanities. This article aims to provide useful direction for such educators on how digital technologies can be used through learner-focused pedagogies. Specific examples are provided as to how the affordances of Web 2.0 and other tools can be realised in innovative ways to help achieve skills development within the medical humanities. The guidance, alongside the practical suggestions for implementation, can provide important conceptual background for medical humanities educators who wish to embrace technology-enhanced learning, and reconceptualise or redesign medical humanities for an online or blended teaching environment. 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.

  8. What we have learned about plutonium from human data

    International Nuclear Information System (INIS)

    Voelz, G.L.

    1975-01-01

    Human data of plutonium deposition, internal distribution, and excretion have been obtained by observations after accidental occupational exposures, long-term follow-up studies on plutonium workers, and autopsy tissue analyses. No significant harmful effects have been noted in humans, although a small foreign-body type nodule around dermal implantations of plutonium has been described in eight persons. Methods used to estimate body burdens by urinary excretion values appear to be conservative generally compared to autopsy tissue burdens. Variations in autopsy tissue distribution appear to be related to the conditions of the plutonium exposure including mode of exposure, particle size, chemical composition, solubility in serum or tissue fluids, and time after exposure for internal redistribution. An important conclusion of this human data survey is the recognition of the inestimable value to be gained by continued careful studies on the life history of workers with higher plutonium exposures. (author)

  9. EMPOWERING THE HUMAN RESOURCES AND THE ROLE OF DISTANCE LEARNING

    Directory of Open Access Journals (Sweden)

    Sukmaya LAMA

    2012-07-01

    Full Text Available As the world is invaded by technological inventions and wonders, life becoming more fast and crazy, yet there can be no doubt that the critical factor for the development of a nation or a state is its human resource. The productivity of a nation is influenced by the number of its skilled population. When we look into the problem of underdevelopment from human resource perspective we are bound to take a look at the educational scenario. In India, the higher education scenario has been very sickly, due to the pro profit policies, lack of infrastructure, entry of private players, etc. The growth of distance education phenomenon in India has no doubt brought a ray of hope. The present paper aims to look into the role of distance education in Assam and the potential it carries in building a huge wealth of human resources.

  10. The role of conditioning, learning and dopamine in sexual behavior: a narrative review of animal and human studies

    NARCIS (Netherlands)

    Brom, Mirte; Both, Stephanie; Laan, Ellen; Everaerd, Walter; Spinhoven, Philip

    2014-01-01

    Many theories of human sexual behavior assume that sexual stimuli obtain arousing properties through associative learning processes. It is widely accepted that classical conditioning contributes to the etiology of both normal and maladaptive human behaviors. Despite the hypothesized importance of

  11. The role of conditioning, learning and dopamine in sexual behavior : A narrative review of animal and human studies

    NARCIS (Netherlands)

    Brom, M.; Both, S.; Laan, E.; Everaerd, W.; Spinhoven, P.

    Many theories of human sexual behavior assume that sexual stimuli obtain arousing properties through associative learning processes. It is widely accepted that classical conditioning contributes to the etiology of both normal and maladaptive human behaviors. Despite the hypothesized importance of

  12. FINANCIAL CONTROL AS A CATEGORY

    Directory of Open Access Journals (Sweden)

    Andrey Yu. Volkov

    2014-01-01

    Full Text Available The article reveals the basics of “financial control” as a category. The main attention is concentrated on the “control” itself (asa term, multiplicity of interpretation of“financial control” term and its juristic-practical matching. The duality of financial control category is detected. The identity of terms “financial control” and “state financial control” is justified. The article also offers ways of development of financial control juristical regulation.

  13. Learning and Recognition of a Non-conscious Sequence of Events in Human Primary Visual Cortex.

    Science.gov (United States)

    Rosenthal, Clive R; Andrews, Samantha K; Antoniades, Chrystalina A; Kennard, Christopher; Soto, David

    2016-03-21

    Human primary visual cortex (V1) has long been associated with learning simple low-level visual discriminations [1] and is classically considered outside of neural systems that support high-level cognitive behavior in contexts that differ from the original conditions of learning, such as recognition memory [2, 3]. Here, we used a novel fMRI-based dichoptic masking protocol-designed to induce activity in V1, without modulation from visual awareness-to test whether human V1 is implicated in human observers rapidly learning and then later (15-20 min) recognizing a non-conscious and complex (second-order) visuospatial sequence. Learning was associated with a change in V1 activity, as part of a temporo-occipital and basal ganglia network, which is at variance with the cortico-cerebellar network identified in prior studies of "implicit" sequence learning that involved motor responses and visible stimuli (e.g., [4]). Recognition memory was associated with V1 activity, as part of a temporo-occipital network involving the hippocampus, under conditions that were not imputable to mechanisms associated with conscious retrieval. Notably, the V1 responses during learning and recognition separately predicted non-conscious recognition memory, and functional coupling between V1 and the hippocampus was enhanced for old retrieval cues. The results provide a basis for novel hypotheses about the signals that can drive recognition memory, because these data (1) identify human V1 with a memory network that can code complex associative serial visuospatial information and support later non-conscious recognition memory-guided behavior (cf. [5]) and (2) align with mouse models of experience-dependent V1 plasticity in learning and memory [6]. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Learning-dependent plasticity with and without training in the human brain.

    Science.gov (United States)

    Zhang, Jiaxiang; Kourtzi, Zoe

    2010-07-27

    Long-term experience through development and evolution and shorter-term training in adulthood have both been suggested to contribute to the optimization of visual functions that mediate our ability to interpret complex scenes. However, the brain plasticity mechanisms that mediate the detection of objects in cluttered scenes remain largely unknown. Here, we combine behavioral and functional MRI (fMRI) measurements to investigate the human-brain mechanisms that mediate our ability to learn statistical regularities and detect targets in clutter. We show two different routes to visual learning in clutter with discrete brain plasticity signatures. Specifically, opportunistic learning of regularities typical in natural contours (i.e., collinearity) can occur simply through frequent exposure, generalize across untrained stimulus features, and shape processing in occipitotemporal regions implicated in the representation of global forms. In contrast, learning to integrate discontinuities (i.e., elements orthogonal to contour paths) requires task-specific training (bootstrap-based learning), is stimulus-dependent, and enhances processing in intraparietal regions implicated in attention-gated learning. We propose that long-term experience with statistical regularities may facilitate opportunistic learning of collinear contours, whereas learning to integrate discontinuities entails bootstrap-based training for the detection of contours in clutter. These findings provide insights in understanding how long-term experience and short-term training interact to shape the optimization of visual recognition processes.

  15. Social learning solves the problem of narrow-peaked search landscapes: experimental evidence in humans.

    Science.gov (United States)

    Acerbi, Alberto; Tennie, Claudio; Mesoudi, Alex

    2016-09-01

    The extensive use of social learning is considered a major reason for the ecological success of humans. Theoretical considerations, models and experiments have explored the evolutionary basis of social learning, showing the conditions under which learning from others is more adaptive than individual learning. Here we present an extension of a previous experimental set-up, in which individuals go on simulated 'hunts' and their success depends on the features of a 'virtual arrowhead' they design. Individuals can modify their arrowhead either by individual trial and error or by copying others. We study how, in a multimodal adaptive landscape, the smoothness of the peaks influences learning. We compare narrow peaks, in which solutions close to optima do not provide useful feedback to individuals, to wide peaks, where smooth landscapes allow an effective hill-climbing individual learning strategy. We show that individual learning is more difficult in narrow-peaked landscapes, but that social learners perform almost equally well in both narrow- and wide-peaked search spaces. There was a weak trend for more copying in the narrow than wide condition, although as in previous experiments social information was generally underutilized. Our results highlight the importance of tasks' design space when studying the adaptiveness of high-fidelity social learning.

  16. Lifelong learning of human actions with deep neural network self-organization.

    Science.gov (United States)

    Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan

    2017-12-01

    Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences. The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns. We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields. Lifelong learning is achieved in terms of prediction-driven neural dynamics in which the growth and the adaptation of the recurrent networks are driven by their capability to reconstruct temporally ordered input sequences. Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions. Additional experiments show the ability of our model to adapt to non-stationary input avoiding catastrophic interference. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  17. Using Ontologies for the E-learning System in Healthcare Human Resources Management

    Directory of Open Access Journals (Sweden)

    Lidia BAJENARU

    2015-01-01

    Full Text Available This paper provides a model for the use of ontology in e-learning systems for structuring educational content in the domain of healthcare human resources management (HHRM in Romania. In this respect we propose an effective method to improve the learning system by providing personalized learning paths created using ontology and advanced educational strategies to provide a personalized learning content for the medical staff. Personalization of e-learning process for the chosen target group will be achieved by setting up learning path for each user according to his profile. This will become possible using: domain ontology, learning objects, modeling student knowledge. Developing an ontology-based system for competence management allows complex interactions, providing intelligent interfacing. This is a new approach for the healthcare system managers in permanent training based on e-learning technologies and specific ontologies in a complex area that needs urgent modernization and efficiency to meet the public health economic, social and political context of Romania.

  18. The Development of Categorization: Effects of Classification and Inference Training on Category Representation

    Science.gov (United States)

    Deng, Wei; Sloutsky, Vladimir M.

    2015-01-01

    Does category representation change in the course of development? And if so, how and why? The current study attempted to answer these questions by examining category learning and category representation. In Experiment 1, 4-year-olds, 6-year-olds, and adults were trained with either a classification task or an inference task and their…

  19. Testing the Efficiency of Markov Chain Monte Carlo with People Using Facial Affect Categories

    Science.gov (United States)

    Martin, Jay B.; Griffiths, Thomas L.; Sanborn, Adam N.

    2012-01-01

    Exploring how people represent natural categories is a key step toward developing a better understanding of how people learn, form memories, and make decisions. Much research on categorization has focused on artificial categories that are created in the laboratory, since studying natural categories defined on high-dimensional stimuli such as…

  20. Development in the Learning Factory: Training Human Capital.

    Science.gov (United States)

    Barton, Harry; Delbridge, Rick

    2001-01-01

    A study of human resource practices in 18 automobile factories in the United States and Britain showed that manufacturing innovations are placing greater demands on line managers and workers. Training is being refocused to develop their interpersonal, team, and leadership skills. However, lack of time and suitable training facilities are barriers.…

  1. [Surgeons can learn from pilots: human factors in surgery].

    Science.gov (United States)

    Sockeel, P; Chatelain, E; Massoure, M-P; David, P; Chapellier, X; Buffat, S

    2009-06-01

    Human factors (HF) study is mandatory to get air transport pilot licences. In aviation, crew resource management (CRM) and declaration of adverse events (feedback) result in improving of air safety. Air missions and surgical procedures have similarities. Bridging the gap is tempting, despite severe warnings against simplistic adaptation. Putting HF theory into surgical practice: how to? Educational principles derived from CRM improve professional attitudes of a team. We propose to translate concepts of CRM to clinical teams. CRM training applying in surgery could allow the work environment to be restructured to reduce human error. Feedback: in aviation, the Bureau of Flight Safety deals with investigations for air events. Pilots, air traffic controllers can anonymously declare nuisance, resulting in a feedback for the whole air force. Adverse events are analysed. Usually, multilevel problems are found, rather than the only responsibility of the last operator. Understanding the mechanisms of human failure finally improves safety. In surgery, CRM and feedback would probably be helpful. Anyway, it requires time; people have to change their mind. Nevertheless people such as fighter pilots, who were very unwilling at the beginning, now consider HF as a cornerstone for security. But it is difficult to estimate the extent of HF-related morbidity and mortality. We propose as a first step to consider CRM and feedback in surgical procedure. HF deals with the mechanisms of human errors and the ways to improve safety and probably improve the surgical team's efficacy.

  2. Empowering the Human Resources and the Role of Distance Learning

    Science.gov (United States)

    Lama, Sukmaya; Kashyap, Mridusmita

    2012-01-01

    As the world is invaded by technological inventions and wonders, life becoming more fast and crazy, yet there can be no doubt that the critical factor for the development of a nation or a state is its human resource. The productivity of a nation is influenced by the number of its skilled population. When we look into the problem of…

  3. Learning from the continuities in humanity and nature

    Science.gov (United States)

    William R., Jr. Burch

    1977-01-01

    Though the emphasis in American life is upon dramatic social change, the firmer reality is our great continuity in social behavior and institutions. For example, though many strategies of child rearing have cycled through human society, the basic problems and responsible social unit remain the same. Of necessity, children have an ordered and holistic view of nature and...

  4. Socially intelligent autonomous agents that learn from human reward

    NARCIS (Netherlands)

    Li, Guangliang

    2016-01-01

    In the future, autonomous agents will operate in human inhabited environments in many real world applications and become an integral part of human’s daily lives. Therefore, when autonomous agents enter into the real world, they need to adapt to many novel, dynamic and complex situations that cannot

  5. Learning History through the Universal Declaration of Human Rights

    Science.gov (United States)

    Landorf, Hilary; Pineda, Martha Fernanda

    2007-01-01

    Although adolescent students often do not have knowledge of specific laws, they usually have a keen sense of justice and fairness. In this article, the author discusses the Universal Declaration of Human Rights (UDHR) as a powerful tool to channel students' sense of fairness into visible actions. Adopted in December 1948 by the General Assembly of…

  6. Managing human resources in the nuclear power industry: Lessons learned

    International Nuclear Information System (INIS)

    2003-08-01

    This report is intended for senior and middle level managers in nuclear operating organizations. Its objectives are to facilitate the recognition of priority issues with respect to managing human resources, and to provide pragmatic ideas regarding improvements. The human resource issues addressed in this report, if not managed effectively, can result in significant performance problems at nuclear power plants. About 10 years ago the IAEA initiated an effort to identify such management issues and to find effective practices to deal with them. This information was provided in IAEA Technical Reports Series No. 369, Management for Excellence in Nuclear Power Plant Performance - A Manual (1994). This report builds upon the information in the subject manual. In the past 10 years there have been significant changes in the nuclear power industry resulting primarily from more competitive energy markets and privatization of nuclear power plant operating organizations. In general, the industry has responded positively to these changes, as indicated by IAEA/WANO performance indicators that show both improved operational and safety performance. This report provides examples of approaches to managing human resources that have been effective in responding to these changes. This report was produced through a series of meetings, where meeting participants were asked to share information regarding effective practices in their organizations with respect to managing human resources. The information provided through these meetings was supplemented with good practices in this area identified through IAEA Operational Safety Review Teams (OSARTs) conducted during the past 10 years

  7. Trajectory learning from human demonstrations via manifold mapping

    CSIR Research Space (South Africa)

    Hiratsuka, M

    2016-10-01

    Full Text Available constantly, and to this end we present an approach for users to be able to easily teach a skill to a robot with any body configuration. Our proposed method requires a motion trajectory obtained from human demonstrations via a Kinect sensor, which...

  8. Adult Learning, Economy and Society

    DEFF Research Database (Denmark)

    Olesen, Henning Salling

    2010-01-01

    The article relates the different types of adult education, continuing education and training to an overall societal context of socio-economic modernization by focussing on the multiple functions of adult learning. Each of well known empirical categories is seen in its historical relation to mode...... embracing form which set a new framework for human participation in the new global society....

  9. Movement-related theta rhythm in humans: coordinating self-directed hippocampal learning.

    Directory of Open Access Journals (Sweden)

    Raphael Kaplan

    Full Text Available The hippocampus is crucial for episodic or declarative memory and the theta rhythm has been implicated in mnemonic processing, but the functional contribution of theta to memory remains the subject of intense speculation. Recent evidence suggests that the hippocampus might function as a network hub for volitional learning. In contrast to human experiments, electrophysiological recordings in the hippocampus of behaving rodents are dominated by theta oscillations reflecting volitional movement, which has been linked to spatial exploration and encoding. This literature makes the surprising cross-species prediction that the human hippocampal theta rhythm supports memory by coordinating exploratory movements in the service of self-directed learning. We examined the links between theta, spatial exploration, and memory encoding by designing an interactive human spatial navigation paradigm combined with multimodal neuroimaging. We used both non-invasive whole-head Magnetoencephalography (MEG to look at theta oscillations and Functional Magnetic Resonance Imaging (fMRI to look at brain regions associated with volitional movement and learning. We found that theta power increases during the self-initiation of virtual movement, additionally correlating with subsequent memory performance and environmental familiarity. Performance-related hippocampal theta increases were observed during a static pre-navigation retrieval phase, where planning for subsequent navigation occurred. Furthermore, periods of the task showing movement-related theta increases showed decreased fMRI activity in the parahippocampus and increased activity in the hippocampus and other brain regions that strikingly overlap with the previously observed volitional learning network (the reverse pattern was seen for stationary periods. These fMRI changes also correlated with participant's performance. Our findings suggest that the human hippocampal theta rhythm supports memory by coordinating

  10. International Conference on Category Theory

    CERN Document Server

    Pedicchio, Maria; Rosolini, Guiseppe

    1991-01-01

    With one exception, these papers are original and fully refereed research articles on various applications of Category Theory to Algebraic Topology, Logic and Computer Science. The exception is an outstanding and lengthy survey paper by Joyal/Street (80 pp) on a growing subject: it gives an account of classical Tannaka duality in such a way as to be accessible to the general mathematical reader, and to provide a key for entry to more recent developments and quantum groups. No expertise in either representation theory or category theory is assumed. Topics such as the Fourier cotransform, Tannaka duality for homogeneous spaces, braided tensor categories, Yang-Baxter operators, Knot invariants and quantum groups are introduced and studies. From the Contents: P.J. Freyd: Algebraically complete categories.- J.M.E. Hyland: First steps in synthetic domain theory.- G. Janelidze, W. Tholen: How algebraic is the change-of-base functor?.- A. Joyal, R. Street: An introduction to Tannaka duality and quantum groups.- A. Jo...

  11. Language universals without universal categories

    NARCIS (Netherlands)

    Croft, W.; van Lier, E.

    2012-01-01

    In this article, the authors present their views on an article by author Sandra Chung related to lexical categories. According to them, Chung's article critiques an analysis of word classes in Chamorro by author Donald M. Topping. They discuss the restatements made by Chung on Topping's criteria for

  12. Social learning as a way to overcome choice-induced preferences? Insights from humans and rhesus macaques.

    Directory of Open Access Journals (Sweden)

    ELISABETTA eMONFARDINI

    2012-09-01

    Full Text Available Much theoretical attention is currently devoted to social learning. Yet, empirical studies formally comparing its effectiveness relative to individual learning are rare. Here, we focus on free choice, which is at the heart of individual reward-based learning, but absent in social learning. Choosing among two equally valued options is known to create a preference for the selected option in both humans and monkeys. We thus surmised that social learning should be more helpful when choice-induced preferences retard individual learning than when they optimize it. To test this prediction, the same task requiring to find which among two items concealed a reward was applied to rhesus macaques and humans. The initial trial was individual or social, rewarded or unrewarded. Learning was assessed on the second trial. Choice-induced preference strongly affected individual learning. Monkeys and humans performed much more poorly after an initial negative choice than after an initial positive choice. Comparison with social learning verified our prediction. For negative outcome, social learning surpassed or at least equaled individual learning in all subjects. For positive outcome, the predicted superiority of individual learning did occur in a majority of subjects (5/6 monkeys and 6/12 humans. A minority kept learning better socially though, perhaps due to a more dominant/aggressive attitude toward peers. Poor learning from errors due to over-valuation of personal choices is among the decision-making biases shared by humans and animals. The present study suggests that choice-immune social learning may help curbing this potentially harmful tendency. Learning from successes is an easier path. The present data suggest that whether one tends to walk it alone or with a peer's help might depend on the social dynamics within the actor/observer dyad.

  13. Macaque monkeys can learn token values from human models through vicarious reward.

    Science.gov (United States)

    Bevacqua, Sara; Cerasti, Erika; Falcone, Rossella; Cervelloni, Milena; Brunamonti, Emiliano; Ferraina, Stefano; Genovesio, Aldo

    2013-01-01

    Monkeys can learn the symbolic meaning of tokens, and exchange them to get a reward. Monkeys can also learn the symbolic value of a token by observing conspecifics but it is not clear if they can learn passively by observing other actors, e.g., humans. To answer this question, we tested two monkeys in a token exchange paradigm in three experiments. Monkeys learned token values through observation of human models exchanging them. We used, after a phase of object familiarization, different sets of tokens. One token of each set was rewarded with a bit of apple. Other tokens had zero value (neutral tokens). Each token was presented only in one set. During the observation phase, monkeys watched the human model exchange tokens and watched them consume rewards (vicarious rewards). In the test phase, the monkeys were asked to exchange one of the tokens for food reward. Sets of three tokens were used in the first experiment and sets of two tokens were used in the second and third experiments. The valuable token was presented with different probabilities in the observation phase during the first and second experiments in which the monkeys exchanged the valuable token more frequently than any of the neutral tokens. The third experiments examined the effect of unequal probabilities. Our results support the view that monkeys can learn from non-conspecific actors through vicarious reward, even a symbolic task like the token-exchange task.

  14. Combining fMRI and behavioral measures to examine the process of human learning.

    Science.gov (United States)

    Karuza, Elisabeth A; Emberson, Lauren L; Aslin, Richard N

    2014-03-01

    Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning. Copyright © 2013 Elsevier Inc. All rights reserved.

  15. Learning about human population history from ancient and modern genomes.

    Science.gov (United States)

    Stoneking, Mark; Krause, Johannes

    2011-08-18

    Genome-wide data, both from SNP arrays and from complete genome sequencing, are becoming increasingly abundant and are now even available from extinct hominins. These data are providing new insights into population history; in particular, when combined with model-based analytical approaches, genome-wide data allow direct testing of hypotheses about population history. For example, genome-wide data from both contemporary populations and extinct hominins strongly support a single dispersal of modern humans from Africa, followed by two archaic admixture events: one with Neanderthals somewhere outside Africa and a second with Denisovans that (so far) has only been detected in New Guinea. These new developments promise to reveal new stories about human population history, without having to resort to storytelling.

  16. Naïve and Robust: Class-Conditional Independence in Human Classification Learning

    Science.gov (United States)

    Jarecki, Jana B.; Meder, Björn; Nelson, Jonathan D.

    2018-01-01

    Humans excel in categorization. Yet from a computational standpoint, learning a novel probabilistic classification task involves severe computational challenges. The present paper investigates one way to address these challenges: assuming class-conditional independence of features. This feature independence assumption simplifies the inference…

  17. Evolution of Humans: Understanding the Nature and Methods of Science through Cooperative Learning

    Science.gov (United States)

    Lee, Yeung Chung

    2011-01-01

    This article describes the use of an enquiry-based approach to the study of human evolution in a practical context, integrating role-playing, jigsaw cooperative learning and scientific argumentation. The activity seeks to unravel the evolutionary relationships of five hominids and one ape from rather "messy" evidence. This approach enhanced the…

  18. Simultaneous and Sequential Feature Negative Discriminations: Elemental Learning and Occasion Setting in Human Pavlovian Conditioning

    Science.gov (United States)

    Baeyens, Frank; Vervliet, Bram; Vansteenwegen, Debora; Beckers, Tom; Hermans, Dirk; Eelen, Paul

    2004-01-01

    Using a conditioned suppression task, we investigated simultaneous (XA-/A+) vs. sequential (X [right arrow] A-/A+) Feature Negative (FN) discrimination learning in humans. We expected the simultaneous discrimination to result in X (or alternatively the XA configuration) becoming an inhibitor acting directly on the US, and the sequential…

  19. Improving Wellness on Campus: Service Learning in a Human Nutrition Class

    Science.gov (United States)

    Wood, Bonnie

    2003-01-01

    In a human nutrition class, students are paired with university faculty or staff volunteer participants. Students teach their service learning partners how to record their food consumption and physical activity during a typical 7-day period. Using these data, students complete nutritional assessments of their partners. (Contains 2 figures.)

  20. Effects of a Co-operative Learning Strategy on Ninth-Graders' Understanding of Human Nutrition.

    Science.gov (United States)

    Soyibo, Kola; Evans, Hermel G.

    2002-01-01

    Looks at the effect of teaching strategies on a group's attitude toward biology and understanding human nutrition. Used an experimental group that participated in co-operative learning and a control group taught using the lecture method. Involves ninth graders (n=156) from two high schools in Jamaica. (Author/YDS)

  1. Evaluating Interdisciplinary Collaborative Learning and Assessment in the Creative Arts and Humanities

    Science.gov (United States)

    Miles, Melissa; Rainbird, Sarah

    2015-01-01

    This article responds to the rising emphasis placed on interdisciplinary collaborative learning and its implications for assessment in higher education. It presents findings from a research project that examined the effectiveness of an interdisciplinary collaborative student symposium as an assessment task in an art school/humanities environment.…

  2. EFFECTS OF MAGNESIUM PEMOLINE UPON HUMAN LEARNING, MEMORY, AND PERFORMANCE TESTS.

    Science.gov (United States)

    SMITH, RONALD G.

    THIS STUDY WAS CONDUCTED DURING 1966 TO DETERMINE THE EFFECTS OF MAGNESIUM PEMOLINE (A COMBINATION OF 2-IMINO-5-PHENYL-4-OXAZOLIDINONE AND MAGNESIUM HYDROXIDE) ON A VARIETY OF HUMAN LEARNING, MEMORY, AND PERFORMANCE TASKS. MAGNESIUM PEMOLINE (25 OR 37.5 MG) OR A PLACEBO WAS ADMINISTERED ORALLY ON A DOUBLE-BLIND BASIS TO INTELLIGENCE-MATCHED GROUPS…

  3. Investigating the Effectiveness of an Educational Card Game for Learning How Human Immunology Is Regulated

    Science.gov (United States)

    Su, TzuFen; Cheng, Meng-Tzu; Lin, Shu-Hua

    2014-01-01

    This study was conducted in an attempt to investigate the effectiveness of an educational card game we developed for learning human immunology. Two semesters of evaluation were included to examine the impact of the game on students' understanding and perceptions of the game-based instruction. Ninety-nine senior high school students (11th graders)…

  4. Professional Learning in Human Resource Management: Problematising the Teaching of Reflective Practice

    Science.gov (United States)

    Griggs, V.; Holden, R.; Rae, J.; Lawless, A.

    2015-01-01

    Reflection and reflective practice are much discussed aspects of professional education. This paper conveys our efforts to problematise teaching reflective practice in human resources (HR) education. The research, on which the paper is based, engages with stakeholders involved in the professional learning and education of reflective practice in…

  5. Representations as Mediation between Purposes as Junior Secondary Science Students Learn about the Human Body

    Science.gov (United States)

    Olander, Clas; Wickman, Per-Olof; Tytler, Russell; Ingerman, Åke

    2018-01-01

    The aim of this article is to investigate students' meaning-making processes of multiple representations during a teaching sequence about the human body in lower secondary school. Two main influences are brought together to accomplish the analysis: on the one hand, theories on signs and representations as scaffoldings for learning and, on the…

  6. Challenges Implementing Work-Integrated Learning in Human Resource Management University Courses

    Science.gov (United States)

    Rook, Laura

    2017-01-01

    The examination of work-integrated learning (WIL) programs in the undergraduate Human Resource Management (HRM) curriculum is an area under-represented in the Australian literature. This paper identifies the challenges faced in implementing WIL into the HRM undergraduate curriculum. Qualitative semi-structured interviews were conducted with 38…

  7. Concept Mapping in the Humanities to Facilitate Reflection: Externalizing the Relationship between Public and Personal Learning

    Science.gov (United States)

    Kandiko, Camille; Hay, David; Weller, Saranne

    2013-01-01

    This article discusses how mapping techniques were used in university teaching in a humanities subject. The use of concept mapping was expanded as a pedagogical tool, with a focus on reflective learning processes. Data were collected through a longitudinal study of concept mapping in a university-level Classics course. This was used to explore how…

  8. Human Resource Development to Facilitate Experiential Learning: The Case of Yahoo Japan

    Science.gov (United States)

    Matsuo, Makoto

    2015-01-01

    Although work experiences are recognized as important mechanisms for developing leaders in organizations, existing research has focused primarily on work assignments rather than on human resource development (HRD) systems that promote experiential learning of managers. The primary goal of this study was to develop an HRD model for facilitating…

  9. Natural Learning for a Connected World: Education, Technology, and the Human Brain

    Science.gov (United States)

    Caine, Renate N.; Caine, Geoffrey

    2011-01-01

    Why do video games fascinate kids so much that they will spend hours pursuing a difficult skill? Why don't they apply this kind of intensity to their schoolwork? These questions are answered by the authors who pioneered brain/mind learning with the publication of "Making Connections: Teaching and the Human Brain". In their new book, "Natural…

  10. Human Capital Spillovers in Families: Do Parents Learn from or Lean on Their Children? NBER Working Paper No. 17235

    Science.gov (United States)

    Kuziemko, Ilyana

    2011-01-01

    I develop a model in which a child's acquisition of a given form of human capital incentivizes adults in his household to either learn from him (if children act as teachers then adults' cost of learning the skill falls) or lean on him (if children's human capital substitutes for that of adults in household production then adults' benefit of…

  11. Development of professional practice through problem-based learning in human nutrition and Dietetics

    Directory of Open Access Journals (Sweden)

    Romero-López Ma Carmen

    2016-01-01

    Full Text Available Although competency-based education is well established in health care education, research shows that the competencies do not always match the reality of clinical workplaces, especially in nutrition area. Student of Human Nutrition and Dietetics, have reported shortcomings in their general competencies, such as organizational skills, teamwork, knowledge to develop proposals for intervention. Were given to students a problem-based learning (PBL activity with collaborative learning competence for to investigate their evolutions in collaborative learning and the knowledge in nutrition education. The results suggest that the PBL provided better preparation with respect to several of the competencies. The effect of PBL for the experienced students' collaborative learning and education nutrition competencies is especially promising in the professional development of future nutritionists.

  12. "… It's Like the Immigrants Stick Together, the Stupid Ones, and the Ones Who Want to Learn Something": Dynamics of Peer Relations, Social Categories, and Dropout in Vocational Educational Training

    Science.gov (United States)

    Grønborg, Lisbeth

    2015-01-01

    This paper discusses how student identities are constituted through social categories and how this affects students' educational trajectories. Dropout is often described as a sudden event but this paper demonstrates how dropping out is a long-term process involving social interactions between the students. It is based on a field study in which the…

  13. Human-simulation-based learning to prevent medication error: A systematic review.

    Science.gov (United States)

    Sarfati, Laura; Ranchon, Florence; Vantard, Nicolas; Schwiertz, Vérane; Larbre, Virginie; Parat, Stéphanie; Faudel, Amélie; Rioufol, Catherine

    2018-01-31

    In the past 2 decades, there has been an increasing interest in simulation-based learning programs to prevent medication error (ME). To improve knowledge, skills, and attitudes in prescribers, nurses, and pharmaceutical staff, these methods enable training without directly involving patients. However, best practices for simulation for healthcare providers are as yet undefined. By analysing the current state of experience in the field, the present review aims to assess whether human simulation in healthcare helps to reduce ME. A systematic review was conducted on Medline from 2000 to June 2015, associating the terms "Patient Simulation," "Medication Errors," and "Simulation Healthcare." Reports of technology-based simulation were excluded, to focus exclusively on human simulation in nontechnical skills learning. Twenty-one studies assessing simulation-based learning programs were selected, focusing on pharmacy, medicine or nursing students, or concerning programs aimed at reducing administration or preparation errors, managing crises, or learning communication skills for healthcare professionals. The studies varied in design, methodology, and assessment criteria. Few demonstrated that simulation was more effective than didactic learning in reducing ME. This review highlights a lack of long-term assessment and real-life extrapolation, with limited scenarios and participant samples. These various experiences, however, help in identifying the key elements required for an effective human simulation-based learning program for ME prevention: ie, scenario design, debriefing, and perception assessment. The performance of these programs depends on their ability to reflect reality and on professional guidance. Properly regulated simulation is a good way to train staff in events that happen only exceptionally, as well as in standard daily activities. By integrating human factors, simulation seems to be effective in preventing iatrogenic risk related to ME, if the program is

  14. Cultural dimensions of learning

    Science.gov (United States)

    Eyford, Glen A.

    1990-06-01

    How, what, when and where we learn is frequently discussed, as are content versus process, or right brain versus left brain learning. What is usually missing is the cultural dimension. This is not an easy concept to define, but various aspects can be identified. The World Decade for Cultural Development emphasizes the need for a counterbalance to a quantitative, economic approach. In the last century poets also warned against brutalizing materialism, and Sorokin and others have described culture more recently in terms of cohesive basic values expressed through aesthetics and institutions. Bloom's taxonomy incorporates the category of affective learning, which internalizes values. If cultural learning goes beyond knowledge acquisition, perhaps the surest way of understanding the cultural dimension of learning is to examine the aesthetic experience. This can use myths, metaphors and symbols, and to teach and learn by using these can help to unlock the human potential for vision and creativity.

  15. Ageing and spatial reversal learning in humans: findings from a virtual water maze.

    Science.gov (United States)

    Schoenfeld, R; Foreman, N; Leplow, B

    2014-08-15

    Deterioration in spatial memory with normal ageing is well accepted. Animal research has shown spatial reversal learning to be most vulnerable to pathological changes in the brain, but this has never been tested in humans. We studied ninety participants (52% females, 20-80 yrs) in a virtual water maze with a reversal learning procedure. Neuropsychological functioning, mood and personality were assessed to control moderator effects. For data analysis, participants were subdivided post hoc into groups aged 20-24, 25-34, 35-44, 45-64 and 65-80 yrs. Initial spatial learning occurred in all age groups but 65-80-yrs-olds never reached the level of younger participants. When tested for delayed recall of spatial memory, younger people frequented the target area but those over 65 yrs did not. In spatial reversal learning, age groups over 45 yrs were deficient and the 65-80-yrs-olds showed no evidence of reversal. Spatial measures were associated with neuropsychological functioning. Extraversion and measures of depression moderated the age effect on the learning index with older introverted and non-depressed individuals showing better results. Measures of anxiety moderated the age effect on reversal learning with older people having higher anxiety scores showing a preserved reversal learning capability. Results confirmed age to be a major factor in spatial tasks but further showed neuropsychological functioning, psycho-affective determinants and personality traits to be significant predictors of individual differences. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. A Human-Centred Tangible approach to learning Computational Thinking

    Directory of Open Access Journals (Sweden)

    Tommaso Turchi

    2016-08-01

    Full Text Available Computational Thinking has recently become a focus of many teaching and research domains; it encapsulates those thinking skills integral to solving complex problems using a computer, thus being widely applicable in our society. It is influencing research across many disciplines and also coming into the limelight of education, mostly thanks to public initiatives such as the Hour of Code. In this paper we present our arguments for promoting Computational Thinking in education through the Human-centred paradigm of Tangible End-User Development, namely by exploiting objects whose interactions with the physical environment are mapped to digital actions performed on the system.

  17. I and Thou: learning the 'human' side of medicine.

    Science.gov (United States)

    Messinger, Atara; Chin-Yee, Benjamin

    2016-09-01

    This essay is a reflection on the doctor-patient relationship from the perspective of two medical students, which draws on the ideas of 20th-century philosopher Martin Buber. Although Buber never wrote about medicine directly, his 'philosophy of dialogue' raises fundamental questions about how human beings relate to one another, and can thus offer valuable insights into the nature of the clinical encounter. We argue that Buber's basic word pairs, 'I-You' and 'I-It', provide a useful heuristic for understanding different modes of caring for patients, which we illustrate using examples of illness narratives from two literary works: Tolstoy's Ivan Ilych and Margaret Edson's Wit Our essay demonstrates how the humanities in general and philosophy in particular can inform a more humanistic practice for healthcare trainees and practicing clinicians alike. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  18. Bridging the gap between human knowledge and machine learning

    Directory of Open Access Journals (Sweden)

    Juan Carlos ALVARADO-PÉREZ

    2015-12-01

    Full Text Available Nowadays, great amount of data is being created by several sources from academic, scientific, business and industrial activities. Such data intrinsically contains meaningful information allowing for developing techniques, and have scientific validity to explore the information thereof. In this connection, the aim of artificial intelligence (AI is getting new knowledge to make decisions properly. AI has taken an important place in scientific and technology development communities, and recently develops computer-based processing devices for modern machines. Under the premise, the premise that the feedback provided by human reasoning -which is holistic, flexible and parallel- may enhance the data analysis, the need for the integration of natural and artificial intelligence has emerged. Such an integration makes the process of knowledge discovery more effective, providing the ability to easily find hidden trends and patterns belonging to the database predictive model. As well, allowing for new observations and considerations from beforehand known data by using both data analysis methods and knowledge and skills from human reasoning. In this work, we review main basics and recent works on artificial and natural intelligence integration in order to introduce users and researchers on this emergent field. As well, key aspects to conceptually compare them are provided.

  19. The (human) science of medical virtual learning environments.

    Science.gov (United States)

    Stone, Robert J

    2011-01-27

    The uptake of virtual simulation technologies in both military and civilian surgical contexts has been both slow and patchy. The failure of the virtual reality community in the 1990s and early 2000s to deliver affordable and accessible training systems stems not only from an obsessive quest to develop the 'ultimate' in so-called 'immersive' hardware solutions, from head-mounted displays to large-scale projection theatres, but also from a comprehensive lack of attention to the needs of the end users. While many still perceive the science of simulation to be defined by technological advances, such as computing power, specialized graphics hardware, advanced interactive controllers, displays and so on, the true science underpinning simulation--the science that helps to guarantee the transfer of skills from the simulated to the real--is that of human factors, a well-established discipline that focuses on the abilities and limitations of the end user when designing interactive systems, as opposed to the more commercially explicit components of technology. Based on three surgical simulation case studies, the importance of a human factors approach to the design of appropriate simulation content and interactive hardware for medical simulation is illustrated. The studies demonstrate that it is unnecessary to pursue real-world fidelity in all instances in order to achieve psychological fidelity--the degree to which the simulated tasks reproduce and foster knowledge, skills and behaviours that can be reliably transferred to real-world training applications.

  20. Electrophysiological CNS-processes related to associative learning in humans.

    Science.gov (United States)

    Christoffersen, Gert R J; Schachtman, Todd R

    2016-01-01

    The neurophysiology of human associative memory has been studied with electroencephalographic techniques since the 1930s. This research has revealed that different types of electrophysiological processes in the human brain can be modified by conditioning: sensory evoked potentials, sensory induced gamma-band activity, periods of frequency-specific waves (alpha and beta waves, the sensorimotor rhythm and the mu-rhythm) and slow cortical potentials. Conditioning of these processes has been studied in experiments that either use operant conditioning or repeated contingent pairings of conditioned and unconditioned stimuli (classical conditioning). In operant conditioning, the appearance of a specific brain process is paired with an external stimulus (neurofeedback) and the feedback enables subjects to obtain varying degrees of control of the CNS-process. Such acquired self-regulation of brain activity has found practical uses for instance in the amelioration of epileptic seizures, Autism Spectrum Disorders (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). It has also provided communicative means of assistance for tetraplegic patients through the use of brain computer interfaces. Both extra and intracortically recorded signals have been coupled with contingent external feedback. It is the aim for this review to summarize essential results on all types of electromagnetic brain processes that have been modified by classical or operant conditioning. The results are organized according to type of conditioned EEG-process, type of conditioning, and sensory modalities of the conditioning stimuli. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Vaccines for the future: learning from human immunology

    Science.gov (United States)

    De Gregorio, Ennio; Rappuoli, Rino

    2012-01-01

    Summary Conventional vaccines have been extremely successful in preventing infections by pathogens expressing relatively conserved antigens through antibody‐mediated effector mechanisms. Thanks to vaccination some diseases have been eradicated and mortality due to infectious diseases has been significantly reduced. However, there are still many infections that are not preventable with vaccination, which represent a major cause of mortality worldwide. Some of these infections are caused by pathogens with a high degree of antigen variability that cannot be controlled only by antibodies, but require a mix of humoral and cellular immune responses. Novel technologies for antigen discovery, expression and formulation allow now for the development of vaccines that can better cope with pathogen diversity and trigger multifunctional immune responses. In addition, the application of new genomic assays and systems biology approaches in human immunology can help to better identify vaccine correlates of protection. The availability of novel vaccine technologies, together with the knowledge of the distinct human immune responses that are required to prevent different types of infection, should help to rationally design effective vaccines where conventional approaches have failed. PMID:21880117

  2. Visual artificial grammar learning: comparative research on humans, kea (Nestor notabilis) and pigeons (Columba livia)

    Science.gov (United States)

    Stobbe, Nina; Westphal-Fitch, Gesche; Aust, Ulrike; Fitch, W. Tecumseh

    2012-01-01

    Artificial grammar learning (AGL) provides a useful tool for exploring rule learning strategies linked to general purpose pattern perception. To be able to directly compare performance of humans with other species with different memory capacities, we developed an AGL task in the visual domain. Presenting entire visual patterns simultaneously instead of sequentially minimizes the amount of required working memory. This approach allowed us to evaluate performance levels of two bird species, kea (Nestor notabilis) and pigeons (Columba livia), in direct comparison to human participants. After being trained to discriminate between two types of visual patterns generated by rules at different levels of computational complexity and presented on a computer screen, birds and humans received further training with a series of novel stimuli that followed the same rules, but differed in various visual features from the training stimuli. Most avian and all human subjects continued to perform well above chance during this initial generalization phase, suggesting that they were able to generalize learned rules to novel stimuli. However, detailed testing with stimuli that violated the intended rules regarding the exact number of stimulus elements indicates that neither bird species was able to successfully acquire the intended pattern rule. Our data suggest that, in contrast to humans, these birds were unable to master a simple rule above the finite-state level, even with simultaneous item presentation and despite intensive training. PMID:22688635

  3. A Formal Calculus for Categories

    DEFF Research Database (Denmark)

    Cáccamo, Mario José

    This dissertation studies the logic underlying category theory. In particular we present a formal calculus for reasoning about universal properties. The aim is to systematise judgements about functoriality and naturality central to categorical reasoning. The calculus is based on a language which...... extends the typed lambda calculus with new binders to represent universal constructions. The types of the languages are interpreted as locally small categories and the expressions represent functors. The logic supports a syntactic treatment of universality and duality. Contravariance requires a definition...... of universality generous enough to deal with functors of mixed variance. Ends generalise limits to cover these kinds of functors and moreover provide the basis for a very convenient algebraic manipulation of expressions. The equational theory of the lambda calculus is extended with new rules for the definitions...

  4. Seismic Category I Structures Program

    International Nuclear Information System (INIS)

    Endebrock, E.G.; Dove, R.C.; Anderson, C.A.

    1984-01-01

    The Seismic Category I Structures Program currently being carried out at the Los Alamos National Laboratory is sponsored by the Mechanical/Structural Engineering Branch, Division of Engineering Technology of the Nuclear Regulatory Commission (NRC). This project is part of a program designed to increase confidence in the assessment of Category I nuclear power plant structural behavior beyond the design limit. The program involves the design, construction, and testing of heavily reinforced concrete models of auxiliary buildings, fuel-handling buildings, etc., but doe not include the reactor containment building. The overall goal of the program is to supply to the Nuclear Regulatory Commission experimental information and a validated procedure to establish the sensitivity of the dynamic response of these structures to earthquakes of magnitude beyond the design basis earthquake

  5. Different Categories of Business Risk

    Directory of Open Access Journals (Sweden)

    Simona-Valeria TOMA

    2011-11-01

    Full Text Available Every business organisation involves some element of risk. Unmitigated risks can result in lost opportunity, financial losses, loss of reputation, or loss of the right to operate in a jurisdiction. Like any other risk type, understanding business risks is quite important for every business to garner profits instead of facing losses. A business risk is a universal risk type; this means that every business in the world faces business risks. Therefore, it is imperative to understand the different categories of business risk in order to create the appropriate strategies. The aim of this paper is to describe the most important categories of business risks and to make sure that every type of risk receives equal treatment and consideration.

  6. Nonlinear Synchronization for Automatic Learning of 3D Pose Variability in Human Motion Sequences

    Directory of Open Access Journals (Sweden)

    Mozerov M

    2010-01-01

    Full Text Available A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.

  7. Virtue Ethics: The Misleading Category

    OpenAIRE

    Martha Nussbaum

    1998-01-01

    Virtue ethics is frequently considered to be a single category of ethical theory, and a rival to Kantianismand Utilitarianism. I argue that this approach is a mistake, because both Kantians and Utilitarians can, and do, have an interest in the virtues and the forrnation of character. But even if we focus on the group of ethical theorists who are most commonly called "virtue theorists" because they reject the guidance of both Kantianism and Utilitarianism, and derive inspiration from ancient G...

  8. Virtue Ethics: The Misleading Category

    OpenAIRE

    Nussbaum, Martha

    2013-01-01

    Virtue ethics is frequently considered to be a single category of ethical theory, and a rival to Kantianismand Utilitarianism. I argue that this approach is a mistake, because both Kantians and Utilitarians can, and do, have an interest in the virtues and the forrnation of character. But even if we focus on the group of ethical theorists who are most commonly called "virtue theorists" because they reject the guidance of both Kantianism and Utilitarianism, and derive inspiration from ancient G...

  9. 1999 who's who category index

    International Nuclear Information System (INIS)

    1999-01-01

    A classified index and alphabetical directory of Canadian corporate entities involved in the production, manufacturing, conversion, service, retail sales, research and development, transportation, insurance, legal and communications aspects of propane in Canada is provided. The alphabetical directory section provides the usual business information (name, postal address, phone, fax, e-mail and Internet addresses), names of principal officers, affiliations, products or services produced or marketed, and the category under which the company is listed in the classified index

  10. The humanization of technology and science in distance learning

    Science.gov (United States)

    Voelzke, Marcos Rincon; Rodrigues Ferreira, Orlando

    2016-07-01

    The Distance Education [DE] presents significant growth in graduates and postgraduates programs. Regarding this fact, new challenges arise and others must be considered, as the generation gap between digital immigrants and digital natives, the establishment of a population increasingly accustomed to Information and Communication Technologies [ICT] and teaching methodologies that should be used and developed. Vygotsky's model of social interaction related to mediation can and should be used in DE, and concerning historical, social and cultural approaches affecting Brazilian reality, Paulo Freire is still up-to-date, integrating humanization into the use of ICT. This work only proceeds with analyses of these elements, being an excerpt of the master's dissertation of one of the authors [Ferreira], under the guidance of another [Voelzke].

  11. Human development of the ability to learn from bad news

    Science.gov (United States)

    Moutsiana, Christina; Garrett, Neil; Clarke, Richard C.; Lotto, R. Beau; Blakemore, Sarah-Jayne; Sharot, Tali

    2013-01-01

    Humans show a natural tendency to discount bad news while incorporating good news into beliefs (the “good news–bad news effect”), an effect that may help explain seemingly irrational risk taking. Understanding how this bias develops with age is important because adolescents are prone to engage in risky behavior; thus, educating them about danger is crucial. We reveal a striking valence-dependent asymmetry in how belief updating develops with age. In the ages tested (9–26 y), younger age was associated with inaccurate updating of beliefs in response to undesirable information regarding vulnerability. In contrast, the ability to update beliefs accurately in response to desirable information remained relatively stable with age. This asymmetry was mediated by adequate computational use of positive but not negative estimation errors to alter beliefs. The results are important for understanding how belief formation develops and might help explain why adolescents do not respond adequately to warnings. PMID:24019466

  12. Human prion diseases: surgical lessons learned from iatrogenic prion transmission.

    Science.gov (United States)

    Bonda, David J; Manjila, Sunil; Mehndiratta, Prachi; Khan, Fahd; Miller, Benjamin R; Onwuzulike, Kaine; Puoti, Gianfranco; Cohen, Mark L; Schonberger, Lawrence B; Cali, Ignazio

    2016-07-01

    The human prion diseases, or transmissible spongiform encephalopathies, have captivated our imaginations since their discovery in the Fore linguistic group in Papua New Guinea in the 1950s. The mysterious and poorly understood "infectious protein" has become somewhat of a household name in many regions across the globe. From bovine spongiform encephalopathy (BSE), commonly identified as mad cow disease, to endocannibalism, media outlets have capitalized on these devastatingly fatal neurological conditions. Interestingly, since their discovery, there have been more than 492 incidents of iatrogenic transmission of prion diseases, largely resulting from prion-contaminated growth hormone and dura mater grafts. Although fewer than 9 cases of probable iatrogenic neurosurgical cases of Creutzfeldt-Jakob disease (CJD) have been reported worldwide, the likelihood of some missed cases and the potential for prion transmission by neurosurgery create considerable concern. Laboratory studies indicate that standard decontamination and sterilization procedures may be insufficient to completely remove infectivity from prion-contaminated instruments. In this unfortunate event, the instruments may transmit the prion disease to others. Much caution therefore should be taken in the absence of strong evidence against the presence of a prion disease in a neurosurgical patient. While the Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) have devised risk assessment and decontamination protocols for the prevention of iatrogenic transmission of the prion diseases, incidents of possible exposure to prions have unfortunately occurred in the United States. In this article, the authors outline the historical discoveries that led from kuru to the identification and isolation of the pathological prion proteins in addition to providing a brief description of human prion diseases and iatrogenic forms of CJD, a brief history of prion disease nosocomial transmission

  13. Social learning, culture and the 'socio-cultural brain' of human and non-human primates.

    Science.gov (United States)

    Whiten, Andrew; van de Waal, Erica

    2017-11-01

    Noting important recent discoveries, we review primate social learning, traditions and culture, together with associated findings about primate brains. We survey our current knowledge of primate cultures in the wild, and complementary experimental diffusion studies testing species' capacity to sustain traditions. We relate this work to theories that seek to explain the enlarged brain size of primates as specializations for social intelligence, that have most recently extended to learning from others and the cultural transmission this permits. We discuss alternative theories and review a variety of recent findings that support cultural intelligence hypotheses for primate encephalization. At a more fine-grained neuroscientific level we focus on the underlying processes of social learning, especially emulation and imitation. Here, our own and others' recent research has established capacities for bodily imitation in both monkeys and apes, results that are consistent with a role for the mirror neuron system in social learning. We review important convergences between behavioural findings and recent non-invasive neuroscientific studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Web-based e-learning and virtual lab of human-artificial immune system.

    Science.gov (United States)

    Gong, Tao; Ding, Yongsheng; Xiong, Qin

    2014-05-01

    Human immune system is as important in keeping the body healthy as the brain in supporting the intelligence. However, the traditional models of the human immune system are built on the mathematics equations, which are not easy for students to understand. To help the students to understand the immune systems, a web-based e-learning approach with virtual lab is designed for the intelligent system control course by using new intelligent educational technology. Comparing the traditional graduate educational model within the classroom, the web-based e-learning with the virtual lab shows the higher inspiration in guiding the graduate students to think independently and innovatively, as the students said. It has been found that this web-based immune e-learning system with the online virtual lab is useful for teaching the graduate students to understand the immune systems in an easier way and design their simulations more creatively and cooperatively. The teaching practice shows that the optimum web-based e-learning system can be used to increase the learning effectiveness of the students.

  15. Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.

    Science.gov (United States)

    Zhang, Wen; Zhu, Xiaopeng; Fu, Yu; Tsuji, Junko; Weng, Zhiping

    2017-12-01

    Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints. Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method. In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.

  16. Enhancing student perspectives of humanism in medicine: reflections from the Kalaupapa service learning project.

    Science.gov (United States)

    Lee, Winona K; Harris, Chessa C D; Mortensen, Kawika A; Long, Linsey M; Sugimoto-Matsuda, Jeanelle

    2016-05-09

    Service learning is endorsed by the Liaison Committee on Medical Education (LCME) as an integral part of U.S. medical school curricula for future physicians. Service learning has been shown to help physicians in training rediscover the altruistic reasons for pursuing medicine and has the potential to enhance students' perspectives of humanism in medicine. The Kalaupapa service learning project is a unique collaboration between disadvantaged post-baccalaureate students with an underserved rural community. This study was conducted to determine whether the Kalaupapa service learning curricula enhanced student perspectives of humanism in medicine at an early stage of their medical training. Program participants between 2008 and 2014 (n = 41) completed written reflections following the conclusion of the service learning project. Four prompts guided student responses. Reflections were thematically analyzed. Once all essays were read, team members compared their findings to condense or expand themes and assess levels of agreement. Emerging themes of resilience and unity were prominent throughout the student reflections. Students expressed respect and empathy for the patients' struggles and strengths, as well as those of their peers. The experience also reinforced students' commitment to service, particularly to populations in rural and underserved communities. Students also gained a deeper understanding of the patient experience and also of themselves as future physicians. To identify and address underserved and rural patients' health care needs, training programs must prepare an altruistic health care workforce that embraces the humanistic element of medicine. The Kalaupapa service learning project is a potential curricular model that can be used to enhance students' awareness and perspectives of humanism in medicine.

  17. "Folksonomies" on the Net: constructing alternative, creative and intercultural categories.

    Directory of Open Access Journals (Sweden)

    Corrado Petrucco

    2006-01-01

    Full Text Available Analysis of the creation of categories and classifications, with particular reference to the approach based on each person's unique perspective and sharing in a community 'practices on the Web This approach can' generate interesting side effects that stimulate creativity 'and the learning in an intercultural perspective.

  18. How learning might strengthen existing visual object representations in human object-selective cortex.

    Science.gov (United States)

    Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

    2016-02-15

    Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. An Interview with Joe McMann: Lessons Learned from Fifty Years of Observing Hardware and Human Behavior

    Science.gov (United States)

    McMann, Joe

    2011-01-01

    Pica Kahn conducted "An Interview with Joe McMann: Lessons Learned in Human and Hardware Behavior" on August 16, 2011. With more than 40 years of experience in the aerospace industry, McMann has gained a wealth of knowledge. This presentation focused on lessons learned in human and hardware behavior. During his many years in the industry, McMann observed that the hardware development process was intertwined with human influences, which impacted the outcome of the product.

  20. Prediction of Human Drug Targets and Their Interactions Using Machine Learning Methods: Current and Future Perspectives.

    Science.gov (United States)

    Nath, Abhigyan; Kumari, Priyanka; Chaube, Radha

    2018-01-01

    Identification of drug targets and drug target interactions are important steps in the drug-discovery pipeline. Successful computational prediction methods can reduce the cost and time demanded by the experimental methods. Knowledge of putative drug targets and their interactions can be very useful for drug repurposing. Supervised machine learning methods have been very useful in drug target prediction and in prediction of drug target interactions. Here, we describe the details for developing prediction models using supervised learning techniques for human drug target prediction and their interactions.

  1. International environmental governance: Lessons learned from Human Rights Institutional Reform

    Energy Technology Data Exchange (ETDEWEB)

    Fauchald, Ole Kristian

    2011-07-01

    This report focuses on the possibility of establishing a High Commissioner for the Environment and transforming the UNEP Governing Council into a Council for the Environment. For this purpose, it considers the parallels between human rights regimes and environmental regimes. It provides a short-list of functions to be covered by a reformed environmental governance regime, and discusses how the reform can be coordinated with UNEP, as well as with the current and future institutional framework for sustainable development. The report also discusses how the reform can be related to fifteen core multilateral environmental agreements. Finally, the report considers how the reform can be carried out through a discussion of five separate options: a decision by the UN General Assembly, by the ECOSOC, or by the UNEP Governing Council, as well as through agreements between conferences of parties of environmental agreements, or directly between states. A main purpose of the report, which has been commissioned by the Norwegian Ministry for the Environment, is to provide input to the preparations for the Rio+20 Conference in 2012.(auth)

  2. Reasoning, learning, and creativity: frontal lobe function and human decision-making.

    Directory of Open Access Journals (Sweden)

    Anne Collins

    Full Text Available The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.

  3. Reasoning, learning, and creativity: frontal lobe function and human decision-making.

    Science.gov (United States)

    Collins, Anne; Koechlin, Etienne

    2012-01-01

    The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.

  4. A category of its own?

    DEFF Research Database (Denmark)

    Elklit, Jørgen; Roberts, Nigel S.

    1996-01-01

    of these systems on the proportionality of the representation of political parties are, indeed, comparable. The four electoral systems were the basis of their countries' general elections during 1994. The results of these elections are used for analyses and discussions of the relative importance of the differences......At first sight, the electoral systems in Denmark, Germany, South Africa and Sweden may seem different and attaempt to categorize them together odd. All four, however, belong to the same category, which Arend Lijphart calls 'proportional representation two-tier districting systems', and the effects...

  5. 14 CFR 23.3 - Airplane categories.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Airplane categories. 23.3 Section 23.3... STANDARDS: NORMAL, UTILITY, ACROBATIC, AND COMMUTER CATEGORY AIRPLANES General § 23.3 Airplane categories. (a) The normal category is limited to airplanes that have a seating configuration, excluding pilot...

  6. Human Driving Forces and Their Impacts on Land Use/Land Cover. Hands-On! Developing Active Learning Modules on the Human Dimensions of Global Change.

    Science.gov (United States)

    Moser, Susanne

    This learning module aims to engage students in problem solving, critical thinking, scientific inquiry, and cooperative learning. The module is appropriate for use in any introductory or intermediate undergraduate course that focuses on human-environment relationships. The module explains that land use/cover change has occurred at all times in all…

  7. TU-G-303-03: Machine Learning to Improve Human Learning From Longitudinal Image Sets

    Energy Technology Data Exchange (ETDEWEB)

    Veeraraghavan, H. [Memorial Sloan-Kettering Cancer Center (United States)

    2015-06-15

    ‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding

  8. TU-G-303-03: Machine Learning to Improve Human Learning From Longitudinal Image Sets

    International Nuclear Information System (INIS)

    Veeraraghavan, H.

    2015-01-01

    ‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding

  9. Social learning and traditions in animals: evidence, definitions, and relationship to human culture.

    Science.gov (United States)

    Galef, Bennett G

    2012-11-01

    The number of publications concerned with social learning in nonhuman animals has expanded dramatically in recent decades. In this article, recent literature addressing three issues that have been of particular concern to those with both an interest in social learning and a background in experimental psychology are reviewed: (1) the definition as well as (2) empirical investigation of the numerous behavioral processes that support social learning in animals, and (3) the relationship of the 'traditions' seen in animals to the 'culture' that is so important in shaping the development of behavioral repertoires in humans. WIREs Cogn Sci 2012 doi: 10.1002/wcs.1196 For further resources related to this article, please visit the WIREs website. Copyright © 2012 John Wiley & Sons, Ltd.

  10. Consensus standards for introductory e-learning courses in human participants research ethics.

    Science.gov (United States)

    Williams, John R; Sprumont, Dominique; Hirtle, Marie; Adebamowo, Clement; Braunschweiger, Paul; Bull, Susan; Burri, Christian; Czarkowski, Marek; Fan, Chien Te; Franck, Caroline; Gefenas, Eugenjius; Geissbuhler, Antoine; Klingmann, Ingrid; Kouyaté, Bocar; Kraehenbhul, Jean-Pierre; Kruger, Mariana; Moodley, Keymanthri; Ntoumi, Francine; Nyirenda, Thomas; Pym, Alexander; Silverman, Henry; Tenorio, Sara

    2014-06-01

    This paper reports the results of a workshop held in January 2013 to begin the process of establishing standards for e-learning programmes in the ethics of research involving human participants that could serve as the basis of their evaluation by individuals and groups who want to use, recommend or accredit such programmes. The standards that were drafted at the workshop cover the following topics: designer/provider qualifications, learning goals, learning objectives, content, methods, assessment of participants and assessment of the course. The authors invite comments on the draft standards and eventual endorsement of a final version by all stakeholders. 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.

  11. Online human training of a myoelectric prosthesis controller via actor-critic reinforcement learning.

    Science.gov (United States)

    Pilarski, Patrick M; Dawson, Michael R; Degris, Thomas; Fahimi, Farbod; Carey, Jason P; Sutton, Richard S

    2011-01-01

    As a contribution toward the goal of adaptable, intelligent artificial limbs, this work introduces a continuous actor-critic reinforcement learning method for optimizing the control of multi-function myoelectric devices. Using a simulated upper-arm robotic prosthesis, we demonstrate how it is possible to derive successful limb controllers from myoelectric data using only a sparse human-delivered training signal, without requiring detailed knowledge about the task domain. This reinforcement-based machine learning framework is well suited for use by both patients and clinical staff, and may be easily adapted to different application domains and the needs of individual amputees. To our knowledge, this is the first my-oelectric control approach that facilitates the online learning of new amputee-specific motions based only on a one-dimensional (scalar) feedback signal provided by the user of the prosthesis. © 2011 IEEE

  12. Gaps in college biology students' understanding of photosynthesis: Implications for human constructivist learning theory and college classroom practice

    Science.gov (United States)

    Griffard, Phyllis Baudoin

    1999-11-01

    The main research question of this study was: What gaps in biochemical understanding are revealed by a range of university introductory biology students as they work through a critically acclaimed multimedia program on photosynthesis, and what are the corresponding implications for elaboration of the Ausubel-Novak-Gowin Learning Theory (ANG, now Human Constructivism)? Twelve students, mixed for ability, gender and ethnicity, were recruited from two sections of "Bio 101." Before and after instruction in photosynthesis, in-depth clinical interviews were conducted during which participants completed a range of cognitive tasks such as sorting, concept mapping, explaining and predicting. Some tasks involved interacting with a computer simulation of photosynthesis. This study primarily employed qualitative case study and verbal analysis methods. Verbal analysis of the clinical interviews revealed numerous gaps that were categorized into typologies. The two major categories were propositional gaps and processing gaps. Propositional gaps were evident in development of participants' concepts, links and constructs. Significant among these were conceptual distance gaps and continuity of matter gaps. Gaps such as convention gaps and relative significance gaps seem to be due to naivete in the discipline. Processing gaps included gaps in graphic decoding skills and relevant cognitive habits such as self-monitoring and consulting prior knowledge. Although the gaps were easier to detect and isolate with the above-average participants, all participants showed evidence of at least some of these gaps. Since some gaps are not unexpected at all but the highest literacy levels, not all the gaps identified are to be considered deficiencies. The gaps identified support the attention given by ANG theorists to the role of prior knowledge and metacognition as well as the value of graphic organizers in knowledge construction. In addition, this study revealed numerous gaps in graphic decoding

  13. Aspect as a Communicative Category

    DEFF Research Database (Denmark)

    Durst-Andersen, Per

    2018-01-01

    On the basis of internal evidence from primarily the use of imperfective forms and external evidence from primarily first language acquisition, it is argued that English, Russian, and French aspect differ from one another, because they go back to an obligatory choice among three possible communic......On the basis of internal evidence from primarily the use of imperfective forms and external evidence from primarily first language acquisition, it is argued that English, Russian, and French aspect differ from one another, because they go back to an obligatory choice among three possible...... communicative directions: should a grammatical category be grounded in the speaker's experience of a situation, in the situation referred to or in the hearer as information about the situation? The progressive vs. non-progressive distinction in English is acquired in the present tense of atelic (simplex) verbs...... to the meta-distinction between atelic (simplex) and telic (complex) verbs. It is second-person oriented. The specific order arrived at reflects the Peircean categories of Firstness, Secondness, and Thirdness and their predictions. This can account for the fact that the English and Russian types can be found...

  14. Neural mechanisms of human perceptual learning: electrophysiological evidence for a two-stage process.

    Science.gov (United States)

    Hamamé, Carlos M; Cosmelli, Diego; Henriquez, Rodrigo; Aboitiz, Francisco

    2011-04-26

    Humans and other animals change the way they perceive the world due to experience. This process has been labeled as perceptual learning, and implies that adult nervous systems can adaptively modify the way in which they process sensory stimulation. However, the mechanisms by which the brain modifies this capacity have not been sufficiently analyzed. We studied the neural mechanisms of human perceptual learning by combining electroencephalographic (EEG) recordings of brain activity and the assessment of psychophysical performance during training in a visual search task. All participants improved their perceptual performance as reflected by an increase in sensitivity (d') and a decrease in reaction time. The EEG signal was acquired throughout the entire experiment revealing amplitude increments, specific and unspecific to the trained stimulus, in event-related potential (ERP) components N2pc and P3 respectively. P3 unspecific modification can be related to context or task-based learning, while N2pc may be reflecting a more specific attentional-related boosting of target detection. Moreover, bell and U-shaped profiles of oscillatory brain activity in gamma (30-60 Hz) and alpha (8-14 Hz) frequency bands may suggest the existence of two phases for learning acquisition, which can be understood as distinctive optimization mechanisms in stimulus processing. We conclude that there are reorganizations in several neural processes that contribute differently to perceptual learning in a visual search task. We propose an integrative model of neural activity reorganization, whereby perceptual learning takes place as a two-stage phenomenon including perceptual, attentional and contextual processes.

  15. Preparation of human resources for future nuclear energy using FBNR as the instrument of learning

    International Nuclear Information System (INIS)

    Sefidvash, Farhang; Espinoza, Patricio; Guerrero, Victor Hugo

    2015-01-01

    An increasing number of developing countries are showing interest to become the emerging countries to nuclear energy. Most of these countries lack human resources and adequate infrastructures to enter such a venture. The principle objective of activities of FBNR Group is to train human resources for the countries that at the present lack the necessary conditions, but aim at the future clean and safe nuclear energy through the fourth generation and INPRO compatible nuclear reactors. The preparation for the future nuclear energy is done through development of innovative nuclear reactor that meets the INPRO philosophies and criteria. These countries may or may not have decided as yet to utilize nuclear energy, but are interested to gain a strong educational foundation for their future. The research and development of a small innovative nuclear reactor FBNR is used as the instrument for learning. The young scientists will learn how to be innovative with the vision of INPRO philosophy and criteria.

  16. Preparation of human resources for future nuclear energy using FBNR as the instrument of learning

    Energy Technology Data Exchange (ETDEWEB)

    Sefidvash, Farhang; Espinoza, Patricio; Guerrero, Victor Hugo [Escuela Politecnica Nacional (EPN), Quito (Ecuador); and others

    2015-11-15

    An increasing number of developing countries are showing interest to become the emerging countries to nuclear energy. Most of these countries lack human resources and adequate infrastructures to enter such a venture. The principle objective of activities of FBNR Group is to train human resources for the countries that at the present lack the necessary conditions, but aim at the future clean and safe nuclear energy through the fourth generation and INPRO compatible nuclear reactors. The preparation for the future nuclear energy is done through development of innovative nuclear reactor that meets the INPRO philosophies and criteria. These countries may or may not have decided as yet to utilize nuclear energy, but are interested to gain a strong educational foundation for their future. The research and development of a small innovative nuclear reactor FBNR is used as the instrument for learning. The young scientists will learn how to be innovative with the vision of INPRO philosophy and criteria.

  17. Two spatiotemporally distinct value systems shape reward-based learning in the human brain.

    Science.gov (United States)

    Fouragnan, Elsa; Retzler, Chris; Mullinger, Karen; Philiastides, Marios G

    2015-09-08

    Avoiding repeated mistakes and learning to reinforce rewarding decisions is critical for human survival and adaptive actions. Yet, the neural underpinnings of the value systems that encode different decision-outcomes remain elusive. Here coupling single-trial electroencephalography with simultaneously acquired functional magnetic resonance imaging, we uncover the spatiotemporal dynamics of two separate but interacting value systems encoding decision-outcomes. Consistent with a role in regulating alertness and switching behaviours, an early system is activated only by negative outcomes and engages arousal-related and motor-preparatory brain structures. Consistent with a role in reward-based learning, a later system differentially suppresses or activates regions of the human reward network in response to negative and positive outcomes, respectively. Following negative outcomes, the early system interacts and downregulates the late system, through a thalamic interaction with the ventral striatum. Critically, the strength of this coupling predicts participants' switching behaviour and avoidance learning, directly implicating the thalamostriatal pathway in reward-based learning.

  18. Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses.

    Science.gov (United States)

    Bisele, Maria; Bencsik, Martin; Lewis, Martin G C; Barnett, Cleveland T

    2017-01-01

    Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors' knowledge, this is the first study to optimise the development of a machine learning algorithm.

  19. Human tracking in thermal images using adaptive particle filters with online random forest learning

    Science.gov (United States)

    Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

    2013-11-01

    This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.

  20. Quality of clinical brain tumor MR spectra judged by humans and machine learning tools.

    Science.gov (United States)

    Kyathanahally, Sreenath P; Mocioiu, Victor; Pedrosa de Barros, Nuno; Slotboom, Johannes; Wright, Alan J; Julià-Sapé, Margarida; Arús, Carles; Kreis, Roland

    2018-05-01

    To investigate and compare human judgment and machine learning tools for quality assessment of clinical MR spectra of brain tumors. A very large set of 2574 single voxel spectra with short and long echo time from the eTUMOUR and INTERPRET databases were used for this analysis. Original human quality ratings from these studies as well as new human guidelines were used to train different machine learning algorithms for automatic quality control (AQC) based on various feature extraction methods and classification tools. The performance was compared with variance in human judgment. AQC built using the RUSBoost classifier that combats imbalanced training data performed best. When furnished with a large range of spectral and derived features where the most crucial ones had been selected by the TreeBagger algorithm it showed better specificity (98%) in judging spectra from an independent test-set than previously published methods. Optimal performance was reached with a virtual three-class ranking system. Our results suggest that feature space should be relatively large for the case of MR tumor spectra and that three-class labels may be beneficial for AQC. The best AQC algorithm showed a performance in rejecting spectra that was comparable to that of a panel of human expert spectroscopists. Magn Reson Med 79:2500-2510, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.