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Sample records for human discrimination learning

  1. 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).

  2. 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.

  3. 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…

  4. 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.

  5. Learning discriminant face descriptor.

    Science.gov (United States)

    Lei, Zhen; Pietikäinen, Matti; Li, Stan Z

    2014-02-01

    Local feature descriptor is an important module for face recognition and those like Gabor and local binary patterns (LBP) have proven effective face descriptors. Traditionally, the form of such local descriptors is predefined in a handcrafted way. In this paper, we propose a method to learn a discriminant face descriptor (DFD) in a data-driven way. The idea is to learn the most discriminant local features that minimize the difference of the features between images of the same person and maximize that between images from different people. In particular, we propose to enhance the discriminative ability of face representation in three aspects. First, the discriminant image filters are learned. Second, the optimal neighborhood sampling strategy is soft determined. Third, the dominant patterns are statistically constructed. Discriminative learning is incorporated to extract effective and robust features. We further apply the proposed method to the heterogeneous (cross-modality) face recognition problem and learn DFD in a coupled way (coupled DFD or C-DFD) to reduce the gap between features of heterogeneous face images to improve the performance of this challenging problem. Extensive experiments on FERET, CAS-PEAL-R1, LFW, and HFB face databases validate the effectiveness of the proposed DFD learning on both homogeneous and heterogeneous face recognition problems. The DFD improves POEM and LQP by about 4.5 percent on LFW database and the C-DFD enhances the heterogeneous face recognition performance of LBP by over 25 percent.

  6. Discrimination Learning in Children

    Science.gov (United States)

    Ochocki, Thomas E.; And Others

    1975-01-01

    Examined the learning performance of 192 fourth-, fifth-, and sixth-grade children on either a two or four choice simultaneous color discrimination task. Compared the use of verbal reinforcement and/or punishment, under conditions of either complete or incomplete instructions. (Author/SDH)

  7. Discriminating the stimulus elements during human odor-taste learning: a successful analytic stance does not eliminate learning.

    Science.gov (United States)

    Stevenson, Richard J; Mahmut, Mehmet K

    2011-10-01

    Odor "sweetness" may arise from experiencing odors and tastes together, resulting in a flavor memory that is later reaccessed by the odor. Forming a flavor memory may be impaired if the taste and odor elements are apparent during exposure, suggesting that configural processing may underpin learning. Using a new procedure, participants made actual flavor discriminations for one odor-taste pair (e.g., Taste A vs. Odor X-Taste A) and mock discriminations for another (e.g., Odor Y-Taste B vs. Odor Y-Taste B). Participants, who were successful at detecting the actual flavor discriminations, demonstrated equal amounts of learning for both odor-taste pairings. These results suggest that although a capacity to discriminate flavor into its elements may be necessary to support learning, whether participants experience a configural or elemental flavor representation may not.

  8. Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses

    OpenAIRE

    Bisele, M; Bencsik, M; Lewis, MGC; Barnett, CT

    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 ...

  9. Discriminative learning for speech recognition

    CERN Document Server

    He, Xiadong

    2008-01-01

    In this book, we introduce the background and mainstream methods of probabilistic modeling and discriminative parameter optimization for speech recognition. The specific models treated in depth include the widely used exponential-family distributions and the hidden Markov model. A detailed study is presented on unifying the common objective functions for discriminative learning in speech recognition, namely maximum mutual information (MMI), minimum classification error, and minimum phone/word error. The unification is presented, with rigorous mathematical analysis, in a common rational-functio

  10. Neural correlates of face gender discrimination learning.

    Science.gov (United States)

    Su, Junzhu; Tan, Qingleng; Fang, Fang

    2013-04-01

    Using combined psychophysics and event-related potentials (ERPs), we investigated the effect of perceptual learning on face gender discrimination and probe the neural correlates of the learning effect. Human subjects were trained to perform a gender discrimination task with male or female faces. Before and after training, they were tested with the trained faces and other faces with the same and opposite genders. ERPs responding to these faces were recorded. Psychophysical results showed that training significantly improved subjects' discrimination performance and the improvement was specific to the trained gender, as well as to the trained identities. The training effect indicates that learning occurs at two levels-the category level (gender) and the exemplar level (identity). ERP analyses showed that the gender and identity learning was associated with the N170 latency reduction at the left occipital-temporal area and the N170 amplitude reduction at the right occipital-temporal area, respectively. These findings provide evidence for the facilitation model and the sharpening model on neuronal plasticity from visual experience, suggesting a faster processing speed and a sparser representation of face induced by perceptual learning.

  11. Visual Aversive Learning Compromises Sensory Discrimination.

    Science.gov (United States)

    Shalev, Lee; Paz, Rony; Avidan, Galia

    2018-03-14

    Aversive learning is thought to modulate perceptual thresholds, which can lead to overgeneralization. However, it remains undetermined whether this modulation is domain specific or a general effect. Moreover, despite the unique role of the visual modality in human perception, it is unclear whether this aspect of aversive learning exists in this modality. The current study was designed to examine the effect of visual aversive outcomes on the perception of basic visual and auditory features. We tested the ability of healthy participants, both males and females, to discriminate between neutral stimuli, before and after visual learning. In each experiment, neutral stimuli were associated with aversive images in an experimental group and with neutral images in a control group. Participants demonstrated a deterioration in discrimination (higher discrimination thresholds) only after aversive learning. This deterioration was measured for both auditory (tone frequency) and visual (orientation and contrast) features. The effect was replicated in five different experiments and lasted for at least 24 h. fMRI neural responses and pupil size were also measured during learning. We showed an increase in neural activations in the anterior cingulate cortex, insula, and amygdala during aversive compared with neutral learning. Interestingly, the early visual cortex showed increased brain activity during aversive compared with neutral context trials, with identical visual information. Our findings imply the existence of a central multimodal mechanism, which modulates early perceptual properties, following exposure to negative situations. Such a mechanism could contribute to abnormal responses that underlie anxiety states, even in new and safe environments. SIGNIFICANCE STATEMENT Using a visual aversive-learning paradigm, we found deteriorated discrimination abilities for visual and auditory stimuli that were associated with visual aversive stimuli. We showed increased neural

  12. Discrimination learning with variable stimulus 'salience'

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    Treviño Mario

    2011-08-01

    Full Text Available Abstract Background In nature, sensory stimuli are organized in heterogeneous combinations. Salient items from these combinations 'stand-out' from their surroundings and determine what and how we learn. Yet, the relationship between varying stimulus salience and discrimination learning remains unclear. Presentation of the hypothesis A rigorous formulation of the problem of discrimination learning should account for varying salience effects. We hypothesize that structural variations in the environment where the conditioned stimulus (CS is embedded will be a significant determinant of learning rate and retention level. Testing the hypothesis Using numerical simulations, we show how a modified version of the Rescorla-Wagner model, an influential theory of associative learning, predicts relevant interactions between varying salience and discrimination learning. Implications of the hypothesis If supported by empirical data, our model will help to interpret critical experiments addressing the relations between attention, discrimination and learning.

  13. Perceptual learning of motion direction discrimination with suppressed and unsuppressed MT in humans: an fMRI study.

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    Benjamin Thompson

    Full Text Available The middle temporal area of the extrastriate visual cortex (area MT is integral to motion perception and is thought to play a key role in the perceptual learning of motion tasks. We have previously found, however, that perceptual learning of a motion discrimination task is possible even when the training stimulus contains locally balanced, motion opponent signals that putatively suppress the response of MT. Assuming at least partial suppression of MT, possible explanations for this learning are that 1 training made MT more responsive by reducing motion opponency, 2 MT remained suppressed and alternative visual areas such as V1 enabled learning and/or 3 suppression of MT increased with training, possibly to reduce noise. Here we used fMRI to test these possibilities. We first confirmed that the motion opponent stimulus did indeed suppress the BOLD response within hMT+ compared to an almost identical stimulus without locally balanced motion signals. We then trained participants on motion opponent or non-opponent stimuli. Training with the motion opponent stimulus reduced the BOLD response within hMT+ and greater reductions in BOLD response were correlated with greater amounts of learning. The opposite relationship between BOLD and behaviour was found at V1 for the group trained on the motion-opponent stimulus and at both V1 and hMT+ for the group trained on the non-opponent motion stimulus. As the average response of many cells within MT to motion opponent stimuli is the same as their response to non-directional flickering noise, the reduced activation of hMT+ after training may reflect noise reduction.

  14. Discriminative Transfer Learning for General Image Restoration

    KAUST Repository

    Xiao, Lei

    2018-04-30

    Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

  15. Discriminative Transfer Learning for General Image Restoration

    KAUST Repository

    Xiao, Lei; Heide, Felix; Heidrich, Wolfgang; Schö lkopf, Bernhard; Hirsch, Michael

    2018-01-01

    Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

  16. Discrimination aware decision tree learning

    NARCIS (Netherlands)

    Kamiran, F.; Calders, T.G.K.; Pechenizkiy, M.

    2010-01-01

    Recently, the following problem of discrimination aware classification was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B. This problem is motivated by the fact

  17. Discrimination aware decision tree learning

    NARCIS (Netherlands)

    Kamiran, F.; Calders, T.G.K.; Pechenizkiy, M.

    2010-01-01

    Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B. This problem is motivated by the fact

  18. Conditional discrimination learning: A critique and amplification

    OpenAIRE

    Schrier, Allan M.; Thompson, Claudia R.

    1980-01-01

    Carter and Werner recently reviewed the literature on conditional discrimination learning by pigeons, which consists of studies of matching-to-sample and oddity-from-sample. They also discussed three models of such learning: the “multiple-rule” model (learning of stimulus-specific relations), the “configuration” model, and the “single-rule” model (concept learning). Although their treatment of the multiple-rule model, which seems most applicable to the pigeon data, is generally excellent, the...

  19. Dogs can discriminate human smiling faces from blank expressions.

    Science.gov (United States)

    Nagasawa, Miho; Murai, Kensuke; Mogi, Kazutaka; Kikusui, Takefumi

    2011-07-01

    Dogs have a unique ability to understand visual cues from humans. We investigated whether dogs can discriminate between human facial expressions. Photographs of human faces were used to test nine pet dogs in two-choice discrimination tasks. The training phases involved each dog learning to discriminate between a set of photographs of their owner's smiling and blank face. Of the nine dogs, five fulfilled these criteria and were selected for test sessions. In the test phase, 10 sets of photographs of the owner's smiling and blank face, which had previously not been seen by the dog, were presented. The dogs selected the owner's smiling face significantly more often than expected by chance. In subsequent tests, 10 sets of smiling and blank face photographs of 20 persons unfamiliar to the dogs were presented (10 males and 10 females). There was no statistical difference between the accuracy in the case of the owners and that in the case of unfamiliar persons with the same gender as the owner. However, the accuracy was significantly lower in the case of unfamiliar persons of the opposite gender to that of the owner, than with the owners themselves. These results suggest that dogs can learn to discriminate human smiling faces from blank faces by looking at photographs. Although it remains unclear whether dogs have human-like systems for visual processing of human facial expressions, the ability to learn to discriminate human facial expressions may have helped dogs adapt to human society.

  20. Unifying generative and discriminative learning principles

    Directory of Open Access Journals (Sweden)

    Strickert Marc

    2010-02-01

    Full Text Available Abstract Background The recognition of functional binding sites in genomic DNA remains one of the fundamental challenges of genome research. During the last decades, a plethora of different and well-adapted models has been developed, but only little attention has been payed to the development of different and similarly well-adapted learning principles. Only recently it was noticed that discriminative learning principles can be superior over generative ones in diverse bioinformatics applications, too. Results Here, we propose a generalization of generative and discriminative learning principles containing the maximum likelihood, maximum a posteriori, maximum conditional likelihood, maximum supervised posterior, generative-discriminative trade-off, and penalized generative-discriminative trade-off learning principles as special cases, and we illustrate its efficacy for the recognition of vertebrate transcription factor binding sites. Conclusions We find that the proposed learning principle helps to improve the recognition of transcription factor binding sites, enabling better computational approaches for extracting as much information as possible from valuable wet-lab data. We make all implementations available in the open-source library Jstacs so that this learning principle can be easily applied to other classification problems in the field of genome and epigenome analysis.

  1. Discriminative Bayesian Dictionary Learning for Classification.

    Science.gov (United States)

    Akhtar, Naveed; Shafait, Faisal; Mian, Ajmal

    2016-12-01

    We propose a Bayesian approach to learn discriminative dictionaries for sparse representation of data. The proposed approach infers probability distributions over the atoms of a discriminative dictionary using a finite approximation of Beta Process. It also computes sets of Bernoulli distributions that associate class labels to the learned dictionary atoms. This association signifies the selection probabilities of the dictionary atoms in the expansion of class-specific data. Furthermore, the non-parametric character of the proposed approach allows it to infer the correct size of the dictionary. We exploit the aforementioned Bernoulli distributions in separately learning a linear classifier. The classifier uses the same hierarchical Bayesian model as the dictionary, which we present along the analytical inference solution for Gibbs sampling. For classification, a test instance is first sparsely encoded over the learned dictionary and the codes are fed to the classifier. We performed experiments for face and action recognition; and object and scene-category classification using five public datasets and compared the results with state-of-the-art discriminative sparse representation approaches. Experiments show that the proposed Bayesian approach consistently outperforms the existing approaches.

  2. Abstract numerical discrimination learning in rats.

    Science.gov (United States)

    Taniuchi, Tohru; Sugihara, Junko; Wakashima, Mariko; Kamijo, Makiko

    2016-06-01

    In this study, we examined rats' discrimination learning of the numerical ordering positions of objects. In Experiments 1 and 2, five out of seven rats successfully learned to respond to the third of six identical objects in a row and showed reliable transfer of this discrimination to novel stimuli after being trained with three different training stimuli. In Experiment 3, the three rats from Experiment 2 continued to be trained to respond to the third object in an object array, which included an odd object that needed to be excluded when identifying the target third object. All three rats acquired this selective-counting task of specific stimuli, and two rats showed reliable transfer of this selective-counting performance to test sets of novel stimuli. In Experiment 4, the three rats from Experiment 3 quickly learned to respond to the third stimulus in object rows consisting of either six identical or six different objects. These results offer strong evidence for abstract numerical discrimination learning in rats.

  3. Hyperspectral Image Classification Using Discriminative Dictionary Learning

    International Nuclear Information System (INIS)

    Zongze, Y; Hao, S; Kefeng, J; Huanxin, Z

    2014-01-01

    The hyperspectral image (HSI) processing community has witnessed a surge of papers focusing on the utilization of sparse prior for effective HSI classification. In sparse representation based HSI classification, there are two phases: sparse coding with an over-complete dictionary and classification. In this paper, we first apply a novel fisher discriminative dictionary learning method, which capture the relative difference in different classes. The competitive selection strategy ensures that atoms in the resulting over-complete dictionary are the most discriminative. Secondly, motivated by the assumption that spatially adjacent samples are statistically related and even belong to the same materials (same class), we propose a majority voting scheme incorporating contextual information to predict the category label. Experiment results show that the proposed method can effectively strengthen relative discrimination of the constructed dictionary, and incorporating with the majority voting scheme achieve generally an improved prediction performance

  4. Braille character discrimination in blindfolded human subjects.

    Science.gov (United States)

    Kauffman, Thomas; Théoret, Hugo; Pascual-Leone, Alvaro

    2002-04-16

    Visual deprivation may lead to enhanced performance in other sensory modalities. Whether this is the case in the tactile modality is controversial and may depend upon specific training and experience. We compared the performance of sighted subjects on a Braille character discrimination task to that of normal individuals blindfolded for a period of five days. Some participants in each group (blindfolded and sighted) received intensive Braille training to offset the effects of experience. Blindfolded subjects performed better than sighted subjects in the Braille discrimination task, irrespective of tactile training. For the left index finger, which had not been used in the formal Braille classes, blindfolding had no effect on performance while subjects who underwent tactile training outperformed non-stimulated participants. These results suggest that visual deprivation speeds up Braille learning and may be associated with behaviorally relevant neuroplastic changes.

  5. Active Discriminative Dictionary Learning for Weather Recognition

    Directory of Open Access Journals (Sweden)

    Caixia Zheng

    2016-01-01

    Full Text Available Weather recognition based on outdoor images is a brand-new and challenging subject, which is widely required in many fields. This paper presents a novel framework for recognizing different weather conditions. Compared with other algorithms, the proposed method possesses the following advantages. Firstly, our method extracts both visual appearance features of the sky region and physical characteristics features of the nonsky region in images. Thus, the extracted features are more comprehensive than some of the existing methods in which only the features of sky region are considered. Secondly, unlike other methods which used the traditional classifiers (e.g., SVM and K-NN, we use discriminative dictionary learning as the classification model for weather, which could address the limitations of previous works. Moreover, the active learning procedure is introduced into dictionary learning to avoid requiring a large number of labeled samples to train the classification model for achieving good performance of weather recognition. Experiments and comparisons are performed on two datasets to verify the effectiveness of the proposed method.

  6. Perceptual Learning: 12-Month-Olds' Discrimination of Monkey Faces

    Science.gov (United States)

    Fair, Joseph; Flom, Ross; Jones, Jacob; Martin, Justin

    2012-01-01

    Six-month-olds reliably discriminate different monkey and human faces whereas 9-month-olds only discriminate different human faces. It is often falsely assumed that perceptual narrowing reflects a permanent change in perceptual abilities. In 3 experiments, ninety-six 12-month-olds' discrimination of unfamiliar monkey faces was examined. Following…

  7. Sex differences in conditioned stimulus discrimination during context-dependent fear learning and its retrieval in humans: the role of biological sex, contraceptives and menstrual cycle phases.

    Science.gov (United States)

    Lonsdorf, Tina B; Haaker, Jan; Schümann, Dirk; Sommer, Tobias; Bayer, Janine; Brassen, Stefanie; Bunzeck, Nico; Gamer, Matthias; Kalisch, Raffael

    2015-11-01

    Anxiety disorders are more prevalent in women than in men. Despite this sexual dimorphism, most experimental studies are conducted in male participants and studies focusing on sex differences are sparse. In addition, the role of hormonal contraceptives and menstrual cycle phase in fear conditioning and extinction processes remain largely unknown. We investigated sex differences in context-dependent fear acquisition and extinction (day 1) and their retrieval/expression (day 2). Skin conductance responses (SCRs), fear and unconditioned stimulus expectancy ratings were obtained. We included 377 individuals (261 women) in our study. Robust sex differences were observed in all dependent measures. Women generally displayed higher subjective ratings but smaller SCRs than men and showed reduced excitatory/inhibitory conditioned stimulus (CS+/CS-) discrimination in all dependent measures. Furthermore, women using hormonal contraceptives showed reduced SCR CS discrimination on day 2 than men and free-cycling women, while menstrual cycle phase had no effect. Possible limitations include the simultaneous testing of up to 4 participants in cubicles, which might have introduced a social component, and not assessing postexperimental contingency awareness. The response pattern in women shows striking similarity to previously reported sex differences in patients with anxiety. Our results suggest that pronounced deficits in associative discrimination learning and subjective expression of safety information (CS- responses) might underlie higher prevalence and higher symptom rates seen in women with anxiety disorders. The data call for consideration of biological sex and hormonal contraceptive use in future studies and may suggest that targeting inhibitory learning during therapy might aid precision medicine.

  8. 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…

  9. Task-irrelevant emotion facilitates face discrimination learning.

    Science.gov (United States)

    Lorenzino, Martina; Caudek, Corrado

    2015-03-01

    We understand poorly how the ability to discriminate faces from one another is shaped by visual experience. The purpose of the present study is to determine whether face discrimination learning can be facilitated by facial emotions. To answer this question, we used a task-irrelevant perceptual learning paradigm because it closely mimics the learning processes that, in daily life, occur without a conscious intention to learn and without an attentional focus on specific facial features. We measured face discrimination thresholds before and after training. During the training phase (4 days), participants performed a contrast discrimination task on face images. They were not informed that we introduced (task-irrelevant) subtle variations in the face images from trial to trial. For the Identity group, the task-irrelevant features were variations along a morphing continuum of facial identity. For the Emotion group, the task-irrelevant features were variations along an emotional expression morphing continuum. The Control group did not undergo contrast discrimination learning and only performed the pre-training and post-training tests, with the same temporal gap between them as the other two groups. Results indicate that face discrimination improved, but only for the Emotion group. Participants in the Emotion group, moreover, showed face discrimination improvements also for stimulus variations along the facial identity dimension, even if these (task-irrelevant) stimulus features had not been presented during training. The present results highlight the importance of emotions for face discrimination learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING.

    Science.gov (United States)

    Guo, Yanrong; Zhan, Yiqiang; Gao, Yaozong; Jiang, Jianguo; Shen, Dinggang

    2013-01-01

    Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appearance in a non-parametric fashion, the learned dictionaries still lack the discriminative power between prostate and non-prostate tissues, which is critical for accurate prostate segmentation. In this paper, we propose to integrate deformable model with a novel learning scheme, namely the Distributed Discriminative Dictionary ( DDD ) learning, which can capture image appearance in a non-parametric and discriminative fashion. In particular, three strategies are designed to boost the tissue discriminative power of DDD. First , minimum Redundancy Maximum Relevance (mRMR) feature selection is performed to constrain the dictionary learning in a discriminative feature space. Second , linear discriminant analysis (LDA) is employed to assemble residuals from different dictionaries for optimal separation between prostate and non-prostate tissues. Third , instead of learning the global dictionaries, we learn a set of local dictionaries for the local regions (each with small appearance variations) along prostate boundary, thus achieving better tissue differentiation locally. In the application stage, DDDs will provide the appearance cues to robustly drive the deformable model onto the prostate boundary. Experiments on 50 MR prostate images show that our method can yield a Dice Ratio of 88% compared to the manual segmentations, and have 7% improvement over the conventional AAM.

  11. Unsupervised spike sorting based on discriminative subspace learning.

    Science.gov (United States)

    Keshtkaran, Mohammad Reza; Yang, Zhi

    2014-01-01

    Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

  12. 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

  13. 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

  14. Discrimination of complex human behavior by pigeons (Columba livia and humans.

    Directory of Open Access Journals (Sweden)

    Muhammad A J Qadri

    Full Text Available The cognitive and neural mechanisms for recognizing and categorizing behavior are not well understood in non-human animals. In the current experiments, pigeons and humans learned to categorize two non-repeating, complex human behaviors ("martial arts" vs. "Indian dance". Using multiple video exemplars of a digital human model, pigeons discriminated these behaviors in a go/no-go task and humans in a choice task. Experiment 1 found that pigeons already experienced with discriminating the locomotive actions of digital animals acquired the discrimination more rapidly when action information was available than when only pose information was available. Experiments 2 and 3 found this same dynamic superiority effect with naïve pigeons and human participants. Both species used the same combination of immediately available static pose information and more slowly perceived dynamic action cues to discriminate the behavioral categories. Theories based on generalized visual mechanisms, as opposed to embodied, species-specific action networks, offer a parsimonious account of how these different animals recognize behavior across and within species.

  15. Polarimetric SAR image classification based on discriminative dictionary learning model

    Science.gov (United States)

    Sang, Cheng Wei; Sun, Hong

    2018-03-01

    Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

  16. Horse breed discrimination using machine learning methods

    Czech Academy of Sciences Publication Activity Database

    Burócziová, Monika; Riha, J.

    2009-01-01

    Roč. 50, č. 4 (2009), s. 375-377 ISSN 1234-1983 Institutional research plan: CEZ:AV0Z50450515 Keywords : Breed discrimination * Genetics diversity * Horse breeds Subject RIV: EG - Zoology Impact factor: 1.324, year: 2009

  17. Learning for pitch and melody discrimination in congenital amusia.

    Science.gov (United States)

    Whiteford, Kelly L; Oxenham, Andrew J

    2018-03-23

    Congenital amusia is currently thought to be a life-long neurogenetic disorder in music perception, impervious to training in pitch or melody discrimination. This study provides an explicit test of whether amusic deficits can be reduced with training. Twenty amusics and 20 matched controls participated in four sessions of psychophysical training involving either pure-tone (500 Hz) pitch discrimination or a control task of lateralization (interaural level differences for bandpass white noise). Pure-tone pitch discrimination at low, medium, and high frequencies (500, 2000, and 8000 Hz) was measured before and after training (pretest and posttest) to determine the specificity of learning. Melody discrimination was also assessed before and after training using the full Montreal Battery of Evaluation of Amusia, the most widely used standardized test to diagnose amusia. Amusics performed more poorly than controls in pitch but not localization discrimination, but both groups improved with practice on the trained stimuli. Learning was broad, occurring across all three frequencies and melody discrimination for all groups, including those who trained on the non-pitch control task. Following training, 11 of 20 amusics no longer met the global diagnostic criteria for amusia. A separate group of untrained controls (n = 20), who also completed melody discrimination and pretest, improved by an equal amount as trained controls on all measures, suggesting that the bulk of learning for the control group occurred very rapidly from the pretest. Thirty-one trained participants (13 amusics) returned one year later to assess long-term maintenance of pitch and melody discrimination. On average, there was no change in performance between posttest and one-year follow-up, demonstrating that improvements on pitch- and melody-related tasks in amusics and controls can be maintained. The findings indicate that amusia is not always a life-long deficit when using the current standard

  18. Dynamic functional brain networks involved in simple visual discrimination learning.

    Science.gov (United States)

    Fidalgo, Camino; Conejo, Nélida María; González-Pardo, Héctor; Arias, Jorge Luis

    2014-10-01

    Visual discrimination tasks have been widely used to evaluate many types of learning and memory processes. However, little is known about the brain regions involved at different stages of visual discrimination learning. We used cytochrome c oxidase histochemistry to evaluate changes in regional brain oxidative metabolism during visual discrimination learning in a water-T maze at different time points during training. As compared with control groups, the results of the present study reveal the gradual activation of cortical (prefrontal and temporal cortices) and subcortical brain regions (including the striatum and the hippocampus) associated to the mastery of a simple visual discrimination task. On the other hand, the brain regions involved and their functional interactions changed progressively over days of training. Regions associated with novelty, emotion, visuo-spatial orientation and motor aspects of the behavioral task seem to be relevant during the earlier phase of training, whereas a brain network comprising the prefrontal cortex was found along the whole learning process. This study highlights the relevance of functional interactions among brain regions to investigate learning and memory processes. Copyright © 2014 Elsevier Inc. All rights reserved.

  19. Discriminative object tracking via sparse representation and online dictionary learning.

    Science.gov (United States)

    Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua

    2014-04-01

    We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.

  20. 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

  1. Weighted Discriminative Dictionary Learning based on Low-rank Representation

    International Nuclear Information System (INIS)

    Chang, Heyou; Zheng, Hao

    2017-01-01

    Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods. (paper)

  2. Dorsolateral Striatum Engagement Interferes with Early Discrimination Learning

    Directory of Open Access Journals (Sweden)

    Hadley C. Bergstrom

    2018-05-01

    Full Text Available Summary: In current models, learning the relationship between environmental stimuli and the outcomes of actions involves both stimulus-driven and goal-directed systems, mediated in part by the DLS and DMS, respectively. However, though these models emphasize the importance of the DLS in governing actions after extensive experience has accumulated, there is growing evidence of DLS engagement from the onset of training. Here, we used in vivo photosilencing to reveal that DLS recruitment interferes with early touchscreen discrimination learning. We also show that the direct output pathway of the DLS is preferentially recruited and causally involved in early learning and find that silencing the normal contribution of the DLS produces plasticity-related alterations in a PL-DMS circuit. These data provide further evidence suggesting that the DLS is recruited in the construction of stimulus-elicited actions that ultimately automate behavior and liberate cognitive resources for other demands, but with a cost to performance at the outset of learning. : What is the contribution of the DLS in early discrimination learning? Bergstrom et al. show using in vivo optogenetics, fluorescence in situ hybridization, and brain-wide activity mapping that silencing the DLS facilitates early discrimination learning, drives activity in a parallel PL-DMS circuit, and preferentially recruits the DLS “direct” output pathway. Keywords: striatum, reward, goal-directed, habit, optogenetics, plasticity, cognition, Arc

  3. Discrimination between smiling faces: Human observers vs. automated face analysis.

    Science.gov (United States)

    Del Líbano, Mario; Calvo, Manuel G; Fernández-Martín, Andrés; Recio, Guillermo

    2018-05-11

    This study investigated (a) how prototypical happy faces (with happy eyes and a smile) can be discriminated from blended expressions with a smile but non-happy eyes, depending on type and intensity of the eye expression; and (b) how smile discrimination differs for human perceivers versus automated face analysis, depending on affective valence and morphological facial features. Human observers categorized faces as happy or non-happy, or rated their valence. Automated analysis (FACET software) computed seven expressions (including joy/happiness) and 20 facial action units (AUs). Physical properties (low-level image statistics and visual saliency) of the face stimuli were controlled. Results revealed, first, that some blended expressions (especially, with angry eyes) had lower discrimination thresholds (i.e., they were identified as "non-happy" at lower non-happy eye intensities) than others (especially, with neutral eyes). Second, discrimination sensitivity was better for human perceivers than for automated FACET analysis. As an additional finding, affective valence predicted human discrimination performance, whereas morphological AUs predicted FACET discrimination. FACET can be a valid tool for categorizing prototypical expressions, but is currently more limited than human observers for discrimination of blended expressions. Configural processing facilitates detection of in/congruence(s) across regions, and thus detection of non-genuine smiling faces (due to non-happy eyes). Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Discrimination against women and the human rights of women

    OpenAIRE

    Žunić Natalija

    2014-01-01

    This paper investigates the concept of the human rights of women and its connection with the phenomenon and the instances of discrimination against women. Discrimination against women, its social visibility and the fight against it, within the idea of the rights and the equality of women, are a source of many theoretical debates. Academic discussions and a powerful influence of the women's movement have brought about the establishment and the exercise of the human rights of women at different...

  5. Learning Dictionaries of Discriminative Image Patches

    DEFF Research Database (Denmark)

    Dahl, Anders Lindbjerg; Larsen, Rasmus

    2011-01-01

    using dictionaries of image patches with associated label data. The approach is based on ideas from sparse generative image models and texton based texture modeling. The intensity and label dictionaries are learned from training images with associated label information of (a subset) of the pixels based...... on a modified vector quantization approach. For new images the intensity dictionary is used to encode the image data and the label dictionary is used to build a segmentation of the image. We demonstrate the algorithm on composite and real texture images and show how successful training is possible even...

  6. Gender Discrimination, Human Capital and Marriage

    OpenAIRE

    Sylvain E. Dessy; Stephane Pallage

    2009-01-01

    We show that the recognition of basic women's rights in developing countries may have important positive spillovers on the whole sphere of labor market transactions, with more women seeking education and an overall lesser wage discrimination against women. A combination of basic women's rights such as marriage consent, access to credit and the right to do business is shown to have important effects on the wage women can earn for their labor. Access to credit/entrepreneurship, in particular, r...

  7. Functional discrimination of membrane proteins using machine learning techniques

    Directory of Open Access Journals (Sweden)

    Yabuki Yukimitsu

    2008-03-01

    Full Text Available Abstract Background Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amino acid residues in membrane proteins that perform major functions, such as channels/pores, electrochemical potential-driven transporters and primary active transporters. Results We observed that the residues Asp, Asn and Tyr are dominant in channels/pores whereas the composition of hydrophobic residues, Phe, Gly, Ile, Leu and Val is high in electrochemical potential-driven transporters. The composition of all the amino acids in primary active transporters lies in between other two classes of proteins. We have utilized different machine learning algorithms, such as, Bayes rule, Logistic function, Neural network, Support vector machine, Decision tree etc. for discriminating these classes of proteins. We observed that most of the algorithms have discriminated them with similar accuracy. The neural network method discriminated the channels/pores, electrochemical potential-driven transporters and active transporters with the 5-fold cross validation accuracy of 64% in a data set of 1718 membrane proteins. The application of amino acid occurrence improved the overall accuracy to 68%. In addition, we have discriminated transporters from other α-helical and β-barrel membrane proteins with the accuracy of 85% using k-nearest neighbor method. The classification of transporters and all other proteins (globular and membrane showed the accuracy of 82%. Conclusion The performance of discrimination with amino acid occurrence is better than that with amino acid composition. We suggest that this method could be effectively used to discriminate transporters from all other globular and membrane proteins, and classify them into channels/pores, electrochemical and active transporters.

  8. 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…

  9. Neighbors Based Discriminative Feature Difference Learning for Kinship Verification

    DEFF Research Database (Denmark)

    Duan, Xiaodong; Tan, Zheng-Hua

    2015-01-01

    In this paper, we present a discriminative feature difference learning method for facial image based kinship verification. To transform feature difference of an image pair to be discriminative for kinship verification, a linear transformation matrix for feature difference between an image pair...... than the commonly used feature concatenation, leading to a low complexity. Furthermore, there is no positive semi-definitive constrain on the transformation matrix while there is in metric learning methods, leading to an easy solution for the transformation matrix. Experimental results on two public...... databases show that the proposed method combined with a SVM classification method outperforms or is comparable to state-of-the-art kinship verification methods. © Springer International Publishing AG, Part of Springer Science+Business Media...

  10. Discrimination against women and the human rights of women

    Directory of Open Access Journals (Sweden)

    Žunić Natalija

    2014-01-01

    Full Text Available This paper investigates the concept of the human rights of women and its connection with the phenomenon and the instances of discrimination against women. Discrimination against women, its social visibility and the fight against it, within the idea of the rights and the equality of women, are a source of many theoretical debates. Academic discussions and a powerful influence of the women's movement have brought about the establishment and the exercise of the human rights of women at different levels of the public and the private spheres of society, as a substantial part of the universal regime of human rights.

  11. Discrimination learning and attentional set formation in a mouse model of Fragile X.

    Science.gov (United States)

    Casten, Kimberly S; Gray, Annette C; Burwell, Rebecca D

    2011-06-01

    Fragile X Syndrome is the most prevalent genetic cause of mental retardation. Selective deficits in executive function, including inhibitory control and attention, are core features of the disorder. In humans, Fragile X results from a trinucleotide repeat in the Fmr1 gene that renders it functionally silent and has been modeled in mice by targeted deletion of the Fmr1 gene. Fmr1 knockout (KO) mice recapitulate many features of Fragile X syndrome, but evidence for deficits in executive function is inconsistent. To address this issue, we trained wild-type and Fmr1 KO mice on an experimental paradigm that assesses attentional set-shifting. Mice learned to discriminate between stimuli differing in two of three perceptual dimensions. Successful discrimination required attending only to the relevant dimension, while ignoring irrelevant dimensions. Mice were trained on three discriminations in the same perceptual dimension, each followed by a reversal. This procedure normally results in the formation of an attentional set to the relevant dimension. Mice were then required to shift attention and discriminate based on a previously irrelevant perceptual dimension. Wild-type mice exhibited the increase in trials to criterion expected when shifting attention from one perceptual dimension to another. In contrast, the Fmr1 KO group failed to show the expected increase, suggesting impairment in forming an attentional set. Fmr1 KO mice also exhibited a general impairment in learning discriminations and reversals. This is the first demonstration that Fmr1 KO mice show a deficit in attentional set formation.

  12. Semi-supervised learning for ordinal Kernel Discriminant Analysis.

    Science.gov (United States)

    Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

    2016-12-01

    Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. 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…

  14. [Discrimination and homophobia associated to the human immunodeficiency virus epidemic].

    Science.gov (United States)

    Orozco-Núñez, Emanuel; Alcalde-Rabanal, Jacqueline Elizabeth; Ruiz-Larios, José Arturo; Sucilla-Pérez, Héctor; García-Cerde, Rodrigo

    2015-01-01

    To describe a political mapping on discrimination and homophobia associated to human immunodeficiency virus (HIV) in the context of public institutions in Mexico. The political mapping was conducted in six Mexican states. Stakeholders who were involved in HIV actions from public and private sectors were included. Semistructured interviews were applied to explore homophobia and discrimination associated with HIV. Information was systematized using the Policy Maker software, which is a good support for analyzing health policies. Discriminatory and homophobic practices in the public domain occurred, damaging people´s integrity via insults, derision and hate crimes. Most stakeholders expressed a supportive position to prevent discrimination and homophobia and some of them had great influence on policy-making decisions. It was found that state policy frameworks are less specific in addressing these issues. Homophobia and discrimination associated to HIV are still considered problematic in Mexico. Homophobia is a very sensitive issue that requires further attention. Also, an actual execution of governmental authority requires greater enforcement of laws against discrimination and homophobia.

  15. Global discriminative learning for higher-accuracy computational gene prediction.

    Directory of Open Access Journals (Sweden)

    Axel Bernal

    2007-03-01

    Full Text Available Most ab initio gene predictors use a probabilistic sequence model, typically a hidden Markov model, to combine separately trained models of genomic signals and content. By combining separate models of relevant genomic features, such gene predictors can exploit small training sets and incomplete annotations, and can be trained fairly efficiently. However, that type of piecewise training does not optimize prediction accuracy and has difficulty in accounting for statistical dependencies among different parts of the gene model. With genomic information being created at an ever-increasing rate, it is worth investigating alternative approaches in which many different types of genomic evidence, with complex statistical dependencies, can be integrated by discriminative learning to maximize annotation accuracy. Among discriminative learning methods, large-margin classifiers have become prominent because of the success of support vector machines (SVM in many classification tasks. We describe CRAIG, a new program for ab initio gene prediction based on a conditional random field model with semi-Markov structure that is trained with an online large-margin algorithm related to multiclass SVMs. Our experiments on benchmark vertebrate datasets and on regions from the ENCODE project show significant improvements in prediction accuracy over published gene predictors that use intrinsic features only, particularly at the gene level and on genes with long introns.

  16. Effects of Learning about Historical Gender Discrimination on Early Adolescents' Occupational Judgments and Aspirations

    Science.gov (United States)

    Pahlke, Erin; Bigler, Rebecca S.; Green, Vanessa A.

    2010-01-01

    To examine the consequences of learning about gender discrimination, early adolescents (n = 121, aged 10-14) were randomly assigned to receive either (a) standard biographical lessons about historical figures (standard condition) or (b) nearly identical lessons that included information about gender discrimination (discrimination condition).…

  17. Effects of Learning about Gender Discrimination on Adolescent Girls' Attitudes toward and Interest in Science

    Science.gov (United States)

    Weisgram, Erica S.; Bigler, Rebecca S.

    2007-01-01

    Gender discrimination has contributed to the gender imbalance in scientific fields. However, research on the effects of informing adolescent girls about gender discrimination in these fields is rare and controversial. To examine the consequences of learning about gender-based occupational discrimination, adolescent girls (n= 158, ages 11 to 14)…

  18. Fronto-striatal grey matter contributions to discrimination learning in Parkinson's disease

    NARCIS (Netherlands)

    O'Callaghan, C.; Moustafa, A.A.; de Wit, S.; Shine, J.M.; Robbins, T.W.; Lewis, S.J.G.; Hornberger, M.

    2013-01-01

    Discrimination learning deficits in Parkinson's disease (PD) have been well-established. Using both behavioral patient studies and computational approaches, these deficits have typically been attributed to dopamine imbalance across the basal ganglia. However, this explanation of impaired learning in

  19. Discriminating Drivers through Human Factor and Behavioral Difference

    Directory of Open Access Journals (Sweden)

    Ju Seok Oh

    2011-05-01

    Full Text Available Since Greenwood and Woods' (1919 study in tendency of accident, many researchers have insisted that various human factors (sensation seeking, anger, anxiety are highly correlated with reckless driving and traffic accidents. Oh and Lee (2011 designed the Driving Behavior Determinants Questionnaire, a psychological tool to predict danger level of drivers and discriminate them into three groups (normal, unintentionally reckless, and intentionally reckless by their characteristics, attitude, and expected reckless behavior level. This tool's overall accuracy of discrimination was 70%. This study aimed to prove that the discrimination reflects the behavioral difference of drivers. Twenty-four young drivers were requested to react to the visual stimuli (tests for subjective speed sense, simple visual reaction time, and left turning at own risk. The results showed no differences in subjective speed sense among the driver groups, which means drivers' excessive speeding behaviors occur due to intention based on personality and attitude, not because of sensory disorders. In addition, there were no differences in simple reaction time among driver groups. However, the results of the ‘Left turning at drivers’ own risk task” revealed significant group differences. All reckless drivers showed a greater degree of dangerous left turning behaviors than the normal group did.

  20. The time course of shape discrimination in the human brain.

    Science.gov (United States)

    Ales, Justin M; Appelbaum, L Gregory; Cottereau, Benoit R; Norcia, Anthony M

    2013-02-15

    The lateral occipital cortex (LOC) activates selectively to images of intact objects versus scrambled controls, is selective for the figure-ground relationship of a scene, and exhibits at least some degree of invariance for size and position. Because of these attributes, it is considered to be a crucial part of the object recognition pathway. Here we show that human LOC is critically involved in perceptual decisions about object shape. High-density EEG was recorded while subjects performed a threshold-level shape discrimination task on texture-defined figures segmented by either phase or orientation cues. The appearance or disappearance of a figure region from a uniform background generated robust visual evoked potentials throughout retinotopic cortex as determined by inverse modeling of the scalp voltage distribution. Contrasting responses from trials containing shape changes that were correctly detected (hits) with trials in which no change occurred (correct rejects) revealed stimulus-locked, target-selective activity in the occipital visual areas LOC and V4 preceding the subject's response. Activity that was locked to the subjects' reaction time was present in the LOC. Response-locked activity in the LOC was determined to be related to shape discrimination for several reasons: shape-selective responses were silenced when subjects viewed identical stimuli but their attention was directed away from the shapes to a demanding letter discrimination task; shape-selectivity was present across four different stimulus configurations used to define the figure; LOC responses correlated with participants' reaction times. These results indicate that decision-related activity is present in the LOC when subjects are engaged in threshold-level shape discriminations. Copyright © 2012 Elsevier Inc. All rights reserved.

  1. From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination.

    Science.gov (United States)

    De Meo, Rosanna; Bourquin, Nathalie M-P; Knebel, Jean-François; Murray, Micah M; Clarke, Stephanie

    2015-09-01

    Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra

  2. Effects of X-ray radiation on complex visual discrimination learning and social recognition memory in rats.

    Directory of Open Access Journals (Sweden)

    Catherine M Davis

    Full Text Available The present report describes an animal model for examining the effects of radiation on a range of neurocognitive functions in rodents that are similar to a number of basic human cognitive functions. Fourteen male Long-Evans rats were trained to perform an automated intra-dimensional set shifting task that consisted of their learning a basic discrimination between two stimulus shapes followed by more complex discrimination stages (e.g., a discrimination reversal, a compound discrimination, a compound reversal, a new shape discrimination, and an intra-dimensional stimulus discrimination reversal. One group of rats was exposed to head-only X-ray radiation (2.3 Gy at a dose rate of 1.9 Gy/min, while a second group received a sham-radiation exposure using the same anesthesia protocol. The irradiated group responded less, had elevated numbers of omitted trials, increased errors, and greater response latencies compared to the sham-irradiated control group. Additionally, social odor recognition memory was tested after radiation exposure by assessing the degree to which rats explored wooden beads impregnated with either their own odors or with the odors of novel, unfamiliar rats; however, no significant effects of radiation on social odor recognition memory were observed. These data suggest that rodent tasks assessing higher-level human cognitive domains are useful in examining the effects of radiation on the CNS, and may be applicable in approximating CNS risks from radiation exposure in clinical populations receiving whole brain irradiation.

  3. Effects of X-ray radiation on complex visual discrimination learning and social recognition memory in rats.

    Science.gov (United States)

    Davis, Catherine M; Roma, Peter G; Armour, Elwood; Gooden, Virginia L; Brady, Joseph V; Weed, Michael R; Hienz, Robert D

    2014-01-01

    The present report describes an animal model for examining the effects of radiation on a range of neurocognitive functions in rodents that are similar to a number of basic human cognitive functions. Fourteen male Long-Evans rats were trained to perform an automated intra-dimensional set shifting task that consisted of their learning a basic discrimination between two stimulus shapes followed by more complex discrimination stages (e.g., a discrimination reversal, a compound discrimination, a compound reversal, a new shape discrimination, and an intra-dimensional stimulus discrimination reversal). One group of rats was exposed to head-only X-ray radiation (2.3 Gy at a dose rate of 1.9 Gy/min), while a second group received a sham-radiation exposure using the same anesthesia protocol. The irradiated group responded less, had elevated numbers of omitted trials, increased errors, and greater response latencies compared to the sham-irradiated control group. Additionally, social odor recognition memory was tested after radiation exposure by assessing the degree to which rats explored wooden beads impregnated with either their own odors or with the odors of novel, unfamiliar rats; however, no significant effects of radiation on social odor recognition memory were observed. These data suggest that rodent tasks assessing higher-level human cognitive domains are useful in examining the effects of radiation on the CNS, and may be applicable in approximating CNS risks from radiation exposure in clinical populations receiving whole brain irradiation.

  4. Effects of X-Ray Radiation on Complex Visual Discrimination Learning and Social Recognition Memory in Rats

    Science.gov (United States)

    Davis, Catherine M.; Roma, Peter G.; Armour, Elwood; Gooden, Virginia L.; Brady, Joseph V.; Weed, Michael R.; Hienz, Robert D.

    2014-01-01

    The present report describes an animal model for examining the effects of radiation on a range of neurocognitive functions in rodents that are similar to a number of basic human cognitive functions. Fourteen male Long-Evans rats were trained to perform an automated intra-dimensional set shifting task that consisted of their learning a basic discrimination between two stimulus shapes followed by more complex discrimination stages (e.g., a discrimination reversal, a compound discrimination, a compound reversal, a new shape discrimination, and an intra-dimensional stimulus discrimination reversal). One group of rats was exposed to head-only X-ray radiation (2.3 Gy at a dose rate of 1.9 Gy/min), while a second group received a sham-radiation exposure using the same anesthesia protocol. The irradiated group responded less, had elevated numbers of omitted trials, increased errors, and greater response latencies compared to the sham-irradiated control group. Additionally, social odor recognition memory was tested after radiation exposure by assessing the degree to which rats explored wooden beads impregnated with either their own odors or with the odors of novel, unfamiliar rats; however, no significant effects of radiation on social odor recognition memory were observed. These data suggest that rodent tasks assessing higher-level human cognitive domains are useful in examining the effects of radiation on the CNS, and may be applicable in approximating CNS risks from radiation exposure in clinical populations receiving whole brain irradiation. PMID:25099152

  5. Subcortical plasticity following perceptual learning in a pitch discrimination task

    OpenAIRE

    Carcagno, Samuele; Plack, Christopher J.

    2011-01-01

    Practice can lead to dramatic improvements in the discrimination of auditory stimuli. In this study, we investigated changes of the frequency-following response (FFR), a subcortical component of the auditory evoked potentials, after a period of pitch discrimination training. Twenty-seven adult listeners were trained for 10 h on a pitch discrimination task using one of three different complex tone stimuli. One had a static pitch contour, one had a rising pitch contour, and one had a falling pi...

  6. Training with Differential Outcomes Enhances Discriminative Learning and Visuospatial Recognition Memory in Children Born Prematurely

    Science.gov (United States)

    Martinez, Lourdes; Mari-Beffa, Paloma; Roldan-Tapia, Dolores; Ramos-Lizana, Julio; Fuentes, Luis J.; Estevez, Angeles F.

    2012-01-01

    Previous studies have demonstrated that discriminative learning is facilitated when a particular outcome is associated with each relation to be learned. When this training procedure is applied (the differential outcome procedure; DOP), learning is faster and more accurate than when the more common non-differential outcome procedure is used. This…

  7. Post-training depletions of basolateral amygdala serotonin fail to disrupt discrimination, retention, or reversal learning

    Directory of Open Access Journals (Sweden)

    G. Jesus eOchoa

    2015-05-01

    Full Text Available In goal-directed pursuits, the basolateral amygdala (BLA is critical in learning about changes in the value of rewards. BLA-lesioned rats show enhanced reversal learning, a task employed to measure the flexibility of response to changes in reward. Similarly, there is a trend for enhanced discrimination learning, suggesting that BLA may modulate formation of stimulus-reward associations. There is a parallel literature on the importance of serotonin (5HT in new stimulus-reward and reversal learning. Recent postulations implicate 5HT in learning from punishment. Whereas dopaminergic involvement is critical in behavioral activation and reinforcement, 5HT may be most critical for aversive processing and behavioral inhibition, complementary cognitive processes. Given these findings, a 5HT-mediated mechanism in BLA may mediate the facilitated learning observed previously. The present study investigated the effects of selective 5HT lesions in BLA using 5,7-dihydroxytryptamine (5,7-DHT versus infusions of saline (Sham on discrimination, retention, and deterministic reversal learning. Rats were required to reach an 85% correct pairwise discrimination and single reversal criterion prior to surgery. Postoperatively, rats were then tested on the 1 retention of the pretreatment discrimination pair 2 discrimination of a novel pair and 3 reversal learning performance. We found statistically comparable preoperative learning rates between groups, intact postoperative retention, and unaltered novel discrimination and reversal learning in 5,7-DHT rats. These findings suggest that 5HT in BLA is not required for formation and flexible adjustment of new stimulus-reward associations when the strategy to efficiently solve the task has already been learned. Given the complementary role of orbitofrontal cortex in reward learning and its interconnectivity with BLA, these findings add to the list of dissociable mechanisms for BLA and orbitofrontal cortex in reward learning.

  8. Interaction between age and perceptual similarity in olfactory discrimination learning in F344 rats: relationships with spatial learning

    Science.gov (United States)

    Yoder, Wendy M.; Gaynor, Leslie S.; Burke, Sara N.; Setlow, Barry; Smith, David W.; Bizon, Jennifer L.

    2017-01-01

    Emerging evidence suggests that aging is associated with a reduced ability to distinguish perceptually similar stimuli in one’s environment. As the ability to accurately perceive and encode sensory information is foundational for explicit memory, understanding the neurobiological underpinnings of discrimination impairments that emerge with advancing age could help elucidate the mechanisms of mnemonic decline. To this end, there is a need for preclinical approaches that robustly and reliably model age-associated perceptual discrimination deficits. Taking advantage of rodents’ exceptional olfactory abilities, the present study applied rigorous psychophysical techniques to the evaluation of discrimination learning in young and aged F344 rats. Aging did not influence odor detection thresholds or the ability to discriminate between perceptually distinct odorants. In contrast, aged rats were disproportionately impaired relative to young on problems that required discriminations between perceptually similar olfactory stimuli. Importantly, these disproportionate impairments in discrimination learning did not simply reflect a global learning impairment in aged rats, as they performed other types of difficult discriminations on par with young rats. Among aged rats, discrimination deficits were strongly associated with spatial learning deficits. These findings reveal a new, sensitive behavioral approach for elucidating the neural mechanisms of cognitive decline associated with normal aging. PMID:28259065

  9. 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.

  10. 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

  11. Discrimination of holograms and real objects by pigeons (Columba livia) and humans (Homo sapiens).

    Science.gov (United States)

    Stephan, Claudia; Steurer, Michael M; Aust, Ulrike

    2014-08-01

    The type of stimulus material employed in visual tasks is crucial to all comparative cognition research that involves object recognition. There is considerable controversy about the use of 2-dimensional stimuli and the impact that the lack of the 3rd dimension (i.e., depth) may have on animals' performance in tests for their visual and cognitive abilities. We report evidence of discrimination learning using a completely novel type of stimuli, namely, holograms. Like real objects, holograms provide full 3-dimensional shape information but they also offer many possibilities for systematically modifying the appearance of a stimulus. Hence, they provide a promising means for investigating visual perception and cognition of different species in a comparative way. We trained pigeons and humans to discriminate either between 2 real objects or between holograms of the same 2 objects, and we subsequently tested both species for the transfer of discrimination to the other presentation mode. The lack of any decrements in accuracy suggests that real objects and holograms were perceived as equivalent in both species and shows the general appropriateness of holograms as stimuli in visual tasks. A follow-up experiment involving the presentation of novel views of the training objects and holograms revealed some interspecies differences in rotational invariance, thereby confirming and extending the results of previous studies. Taken together, these results suggest that holograms may not only provide a promising tool for investigating yet unexplored issues, but their use may also lead to novel insights into some crucial aspects of comparative visual perception and categorization.

  12. Reduced autobiographical memory specificity is associated with impaired discrimination learning in anxiety disorder patients

    Science.gov (United States)

    Lenaert, Bert; Boddez, Yannick; Vervliet, Bram; Schruers, Koen; Hermans, Dirk

    2015-01-01

    Associative learning plays an important role in the development of anxiety disorders, but a thorough understanding of the variables that impact such learning is still lacking. We investigated whether individual differences in autobiographical memory specificity are related to discrimination learning and generalization. In an associative learning task, participants learned the association between two pictures of female faces and a non-aversive outcome. Subsequently, six morphed pictures functioning as generalization stimuli (GSs) were introduced. In a sample of healthy participants (Study 1), we did not find evidence for differences in discrimination learning as a function of memory specificity. In a sample of anxiety disorder patients (Study 2), individuals who were characterized by low memory specificity showed deficient discrimination learning relative to high specific individuals. In contrast to previous findings, results revealed no effect of memory specificity on generalization. These results indicate that impaired discrimination learning, previously shown in patients suffering from an anxiety disorder, may be—in part—due to limited memory specificity. Together, these studies emphasize the importance of incorporating cognitive variables in associative learning theories and their implications for the development of anxiety disorders. In addition, re-analyses of the data (Study 3) showed that patients suffering from panic disorder showed higher outcome expectancies in the presence of the stimulus that was never followed by an outcome during discrimination training, relative to patients suffering from other anxiety disorders and healthy participants. Because we used a neutral, non-aversive outcome (i.e., drawing of a lightning bolt), these data suggest that learning abnormalities in panic disorder may not be restricted to fear learning, but rather reflect a more general associative learning deficit that also manifests in fear irrelevant contexts. PMID

  13. Further Exploration of Human Neonatal Chromatic-Achromatic Discrimination.

    Science.gov (United States)

    Adams, Russell J.

    1995-01-01

    Newborns were habituated to white squares of varying size and luminance and retested with colored squares for recovery of habituation. Newborns could discriminate yellow-green from white in large squares, but not in small squares. They could not discriminate blue, blue-green, or purple from white. Results suggest newborns have little…

  14. Discriminating Microbial Species Using Protein Sequence Properties and Machine Learning

    NARCIS (Netherlands)

    Shahib, Ali Al-; Gilbert, David; Breitling, Rainer

    2007-01-01

    Much work has been done to identify species-specific proteins in sequenced genomes and hence to determine their function. We assumed that such proteins have specific physico-chemical properties that will discriminate them from proteins in other species. In this paper, we examine the validity of this

  15. Subcortical plasticity following perceptual learning in a pitch discrimination task.

    Science.gov (United States)

    Carcagno, Samuele; Plack, Christopher J

    2011-02-01

    Practice can lead to dramatic improvements in the discrimination of auditory stimuli. In this study, we investigated changes of the frequency-following response (FFR), a subcortical component of the auditory evoked potentials, after a period of pitch discrimination training. Twenty-seven adult listeners were trained for 10 h on a pitch discrimination task using one of three different complex tone stimuli. One had a static pitch contour, one had a rising pitch contour, and one had a falling pitch contour. Behavioral measures of pitch discrimination and FFRs for all the stimuli were measured before and after the training phase for these participants, as well as for an untrained control group (n = 12). Trained participants showed significant improvements in pitch discrimination compared to the control group for all three trained stimuli. These improvements were partly specific for stimuli with the same pitch modulation (dynamic vs. static) and with the same pitch trajectory (rising vs. falling) as the trained stimulus. Also, the robustness of FFR neural phase locking to the sound envelope increased significantly more in trained participants compared to the control group for the static and rising contour, but not for the falling contour. Changes in FFR strength were partly specific for stimuli with the same pitch modulation (dynamic vs. static) of the trained stimulus. Changes in FFR strength, however, were not specific for stimuli with the same pitch trajectory (rising vs. falling) as the trained stimulus. These findings indicate that even relatively low-level processes in the mature auditory system are subject to experience-related change.

  16. Human Drug Discrimination: Elucidating the Neuropharmacology of Commonly Abused Illicit Drugs.

    Science.gov (United States)

    Bolin, B Levi; Alcorn, Joseph L; Reynolds, Anna R; Lile, Joshua A; Stoops, William W; Rush, Craig R

    2016-06-07

    Drug-discrimination procedures empirically evaluate the control that internal drug states have over behavior. They provide a highly selective method to investigate the neuropharmacological underpinnings of the interoceptive effects of drugs in vivo. As a result, drug discrimination has been one of the most widely used assays in the field of behavioral pharmacology. Drug-discrimination procedures have been adapted for use with humans and are conceptually similar to preclinical drug-discrimination techniques in that a behavior is differentially reinforced contingent on the presence or absence of a specific interoceptive drug stimulus. This chapter provides a basic overview of human drug-discrimination procedures and reviews the extant literature concerning the use of these procedures to elucidate the underlying neuropharmacological mechanisms of commonly abused illicit drugs (i.e., stimulants, opioids, and cannabis) in humans. This chapter is not intended to review every available study that used drug-discrimination procedures in humans. Instead, when possible, exemplary studies that used a stimulant, opioid, or Δ 9 -tetrahydrocannabinol (the primary psychoactive constituent of cannabis) to assess the discriminative-stimulus effects of drugs in humans are reviewed for illustrative purposes. We conclude by commenting on the current state and future of human drug-discrimination research.

  17. Pitch Discrimination Learning: Specificity for Pitch and Harmonic Resolvability, and Electrophysiological Correlates

    OpenAIRE

    Carcagno, Samuele; Plack, Christopher J.

    2011-01-01

    Multiple-hour training on a pitch discrimination task dramatically decreases the threshold for detecting a pitch difference between two harmonic complexes. Here, we investigated the specificity of this perceptual learning with respect to the pitch and the resolvability of the trained harmonic complex, as well as its cortical electrophysiological correlates. We trained 24 participants for 12 h on a pitch discrimination task using one of four different harmonic complexes. The complexes differed...

  18. Dog's discrimination of human selfish and generous attitudes: the role of individual recognition, experience, and experimenters' gender.

    Science.gov (United States)

    Carballo, Fabricio; Freidin, Esteban; Putrino, Natalia; Shimabukuro, Carolina; Casanave, Emma; Bentosela, Mariana

    2015-01-01

    Discrimination of and memory for others' generous and selfish behaviors could be adaptive abilities in social animals. Dogs have seemingly expressed such skills in both direct and indirect interactions with humans. However, recent studies suggest that their capacity may rely on cues other than people's individual characteristics, such as the place where the person stands. Thus, the conditions under which dogs recognize individual humans when solving cooperative tasks still remains unclear. With the aim of contributing to this problem, we made dogs interact with two human experimenters, one generous (pointed towards the food, gave ostensive cues, and allowed the dog to eat it) and the other selfish (pointed towards the food, but ate it before the dog could have it). Then subjects could choose between them (studies 1-3). In study 1, dogs took several training trials to learn the discrimination between the generous and the selfish experimenters when both were of the same gender. In study 2, the discrimination was learned faster when the experimenters were of different gender as evidenced both by dogs' latencies to approach the bowl in training trials as well as by their choices in preference tests. Nevertheless, dogs did not get confused by gender when the experimenters were changed in between the training and the choice phase in study 3. We conclude that dogs spontaneously used human gender as a cue to discriminate between more and less cooperative experimenters. They also relied on some other personal feature which let them avoid being confused by gender when demonstrators were changed. We discuss these results in terms of dogs' ability to recognize individuals and the potential advantage of this skill for their lives in human environments.

  19. Dog's discrimination of human selfish and generous attitudes: the role of individual recognition, experience, and experimenters' gender.

    Directory of Open Access Journals (Sweden)

    Fabricio Carballo

    Full Text Available Discrimination of and memory for others' generous and selfish behaviors could be adaptive abilities in social animals. Dogs have seemingly expressed such skills in both direct and indirect interactions with humans. However, recent studies suggest that their capacity may rely on cues other than people's individual characteristics, such as the place where the person stands. Thus, the conditions under which dogs recognize individual humans when solving cooperative tasks still remains unclear. With the aim of contributing to this problem, we made dogs interact with two human experimenters, one generous (pointed towards the food, gave ostensive cues, and allowed the dog to eat it and the other selfish (pointed towards the food, but ate it before the dog could have it. Then subjects could choose between them (studies 1-3. In study 1, dogs took several training trials to learn the discrimination between the generous and the selfish experimenters when both were of the same gender. In study 2, the discrimination was learned faster when the experimenters were of different gender as evidenced both by dogs' latencies to approach the bowl in training trials as well as by their choices in preference tests. Nevertheless, dogs did not get confused by gender when the experimenters were changed in between the training and the choice phase in study 3. We conclude that dogs spontaneously used human gender as a cue to discriminate between more and less cooperative experimenters. They also relied on some other personal feature which let them avoid being confused by gender when demonstrators were changed. We discuss these results in terms of dogs' ability to recognize individuals and the potential advantage of this skill for their lives in human environments.

  20. Dopamine modulates memory consolidation of discrimination learning in the auditory cortex.

    Science.gov (United States)

    Schicknick, Horst; Reichenbach, Nicole; Smalla, Karl-Heinz; Scheich, Henning; Gundelfinger, Eckart D; Tischmeyer, Wolfgang

    2012-03-01

    In Mongolian gerbils, the auditory cortex is critical for discriminating rising vs. falling frequency-modulated tones. Based on our previous studies, we hypothesized that dopaminergic inputs to the auditory cortex during and shortly after acquisition of the discrimination strategy control long-term memory formation. To test this hypothesis, we studied frequency-modulated tone discrimination learning of gerbils in a shuttle box GO/NO-GO procedure following differential treatments. (i) Pre-exposure of gerbils to the frequency-modulated tones at 1 day before the first discrimination training session severely impaired the accuracy of the discrimination acquired in that session during the initial trials of a second training session, performed 1 day later. (ii) Local injection of the D1/D5 dopamine receptor antagonist SCH-23390 into the auditory cortex after task acquisition caused a discrimination deficit of similar extent and time course as with pre-exposure. This effect was dependent on the dose and time point of injection. (iii) Injection of the D1/D5 dopamine receptor agonist SKF-38393 into the auditory cortex after retraining caused a further discrimination improvement at the beginning of subsequent sessions. All three treatments, which supposedly interfered with dopamine signalling during conditioning and/or retraining, had a substantial impact on the dynamics of the discrimination performance particularly at the beginning of subsequent training sessions. These findings suggest that auditory-cortical dopamine activity after acquisition of a discrimination of complex sounds and after retrieval of weak frequency-modulated tone discrimination memory further improves memory consolidation, i.e. the correct association of two sounds with their respective GO/NO-GO meaning, in support of future memory recall. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  1. Valence of Facial Cues Influences Sheep Learning in a Visual Discrimination Task

    Directory of Open Access Journals (Sweden)

    Lucille G. A. Bellegarde

    2017-11-01

    Full Text Available Sheep are one of the most studied farm species in terms of their ability to process information from faces, but little is known about their face-based emotion recognition abilities. We investigated (a whether sheep could use images of sheep faces taken in situation of varying valence as cues in a simultaneous discrimination task and (b whether the valence of the situation affects their learning performance. To accomplish this, we photographed faces of sheep in three situations inducing emotional states of neutral (ruminating in the home pen or negative valence (social isolation or aggressive interaction. Sheep (n = 35 first had to learn a discrimination task with colored cards. Animals that reached the learning criterion (n = 16 were then presented with pairs of images of the face of a single individual taken in the neutral situation and in one of the negative situations. Finally, sheep had to generalize what they had learned to new pairs of images of faces taken in the same situation, but of a different conspecific. All sheep that learned the discrimination task with colored cards reached the learning criterion with images of faces. Sheep that had to associate a negative image with a food reward learned faster than sheep that had to associate a neutral image with a reward. With the exception of sheep from the aggression-rewarded group, sheep generalized this discrimination to images of faces of different individuals. Our results suggest that sheep can perceive the emotional valence displayed on faces of conspecifics and that this valence affects learning processes.

  2. Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI

    Directory of Open Access Journals (Sweden)

    Ling-Li Zeng

    2018-04-01

    Full Text Available Background: A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. Methods: A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Findings: Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. Interpretation: The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the “disconnectivity” model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Keywords: Schizophrenia, Deep learning, Connectome, f

  3. Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data

    OpenAIRE

    Veale, M; Binns, RDP

    2017-01-01

    Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining (DADM) and fairness, accountability and transparency machine learning (FATML), their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data o...

  4. Segmentation of MR images via discriminative dictionary learning and sparse coding: Application to hippocampus labeling

    OpenAIRE

    Tong, Tong; Wolz, Robin; Coupe, Pierrick; Hajnal, Joseph V.; Rueckert, Daniel

    2013-01-01

    International audience; We propose a novel method for the automatic segmentation of brain MRI images by using discriminative dictionary learning and sparse coding techniques. In the proposed method, dictionaries and classifiers are learned simultaneously from a set of brain atlases, which can then be used for the reconstruction and segmentation of an unseen target image. The proposed segmentation strategy is based on image reconstruction, which is in contrast to most existing atlas-based labe...

  5. Combining generative and discriminative representation learning for lung CT analysis with convolutional restricted Boltzmann machines

    DEFF Research Database (Denmark)

    van Tulder, Gijs; de Bruijne, Marleen

    2016-01-01

    The choice of features greatly influences the performance of a tissue classification system. Despite this, many systems are built with standard, predefined filter banks that are not optimized for that particular application. Representation learning methods such as restricted Boltzmann machines may...... outperform these standard filter banks because they learn a feature description directly from the training data. Like many other representation learning methods, restricted Boltzmann machines are unsupervised and are trained with a generative learning objective; this allows them to learn representations from...... unlabeled data, but does not necessarily produce features that are optimal for classification. In this paper we propose the convolutional classification restricted Boltzmann machine, which combines a generative and a discriminative learning objective. This allows it to learn filters that are good both...

  6. Pitch discrimination learning: specificity for pitch and harmonic resolvability, and electrophysiological correlates.

    Science.gov (United States)

    Carcagno, Samuele; Plack, Christopher J

    2011-08-01

    Multiple-hour training on a pitch discrimination task dramatically decreases the threshold for detecting a pitch difference between two harmonic complexes. Here, we investigated the specificity of this perceptual learning with respect to the pitch and the resolvability of the trained harmonic complex, as well as its cortical electrophysiological correlates. We trained 24 participants for 12 h on a pitch discrimination task using one of four different harmonic complexes. The complexes differed in pitch and/or spectral resolvability of their components by the cochlea, but were filtered into the same spectral region. Cortical-evoked potentials and a behavioral measure of pitch discrimination were assessed before and after training for all the four complexes. The change in these measures was compared to that of two control groups: one trained on a level discrimination task and one without any training. The behavioral results showed that learning was partly specific to both pitch and resolvability. Training with a resolved-harmonic complex improved pitch discrimination for resolved complexes more than training with an unresolved complex. However, we did not find evidence that training with an unresolved complex leads to specific learning for unresolved complexes. Training affected the P2 component of the cortical-evoked potentials, as well as a later component (250-400 ms). No significant changes were found on the mismatch negativity (MMN) component, although a separate experiment showed that this measure was sensitive to pitch changes equivalent to the pitch discriminability changes induced by training. This result suggests that pitch discrimination training affects processes not measured by the MMN, for example, processes higher in level or parallel to those involved in MMN generation.

  7. Perceived Discrimination and International Students' Learning: An Empirical Investigation

    Science.gov (United States)

    Karuppan, Corinne M.; Barari, Mahua

    2011-01-01

    At a time when the number of internationally mobile students worldwide has been growing steadily, the US share of this market has been declining. Since, as it is often claimed, international students are the best ambassadors for their host countries, an effective recruitment strategy is to enhance their learning experience, with the expectation…

  8. Learning temporal context shapes prestimulus alpha oscillations and improves visual discrimination performance.

    Science.gov (United States)

    Toosi, Tahereh; K Tousi, Ehsan; Esteky, Hossein

    2017-08-01

    Time is an inseparable component of every physical event that we perceive, yet it is not clear how the brain processes time or how the neuronal representation of time affects our perception of events. Here we asked subjects to perform a visual discrimination task while we changed the temporal context in which the stimuli were presented. We collected electroencephalography (EEG) signals in two temporal contexts. In predictable blocks stimuli were presented after a constant delay relative to a visual cue, and in unpredictable blocks stimuli were presented after variable delays relative to the visual cue. Four subsecond delays of 83, 150, 400, and 800 ms were used in the predictable and unpredictable blocks. We observed that predictability modulated the power of prestimulus alpha oscillations in the parieto-occipital sites: alpha power increased in the 300-ms window before stimulus onset in the predictable blocks compared with the unpredictable blocks. This modulation only occurred in the longest delay period, 800 ms, in which predictability also improved the behavioral performance of the subjects. Moreover, learning the temporal context shaped the prestimulus alpha power: modulation of prestimulus alpha power grew during the predictable block and correlated with performance enhancement. These results suggest that the brain is able to learn the subsecond temporal context of stimuli and use this to enhance sensory processing. Furthermore, the neural correlate of this temporal prediction is reflected in the alpha oscillations. NEW & NOTEWORTHY It is not well understood how the uncertainty in the timing of an external event affects its processing, particularly at subsecond scales. Here we demonstrate how a predictable timing scheme improves visual processing. We found that learning the predictable scheme gradually shaped the prestimulus alpha power. These findings indicate that the human brain is able to extract implicit subsecond patterns in the temporal context of

  9. An Information Analysis of 2-, 3-, and 4-Word Verbal Discrimination Learning.

    Science.gov (United States)

    Arima, James K.; Gray, Francis D.

    Information theory was used to qualify the difficulty of verbal discrimination (VD) learning tasks and to measure VD performance. Words for VD items were selected with high background frequency and equal a priori probabilities of being selected as a first response. Three VD lists containing only 2-, 3-, or 4-word items were created and equated for…

  10. Patterns of Learning in Verbal Discrimination as an Interaction of Social Reinforcement and Sex Combinations

    Science.gov (United States)

    Ratliff, Richard G.; And Others

    1976-01-01

    A total of 540 college students were run in two verbal discrimination learning studies (the second, a replication of the first) with one of three verbal reward conditions. In both studies, equal numbers of male and female subjects were run in each reward condition by each male and female experimenter. (MS)

  11. Roles of Approval Motivation and Generalized Expectancy for Reinforcement in Children's Conceptual Discrimination Learning

    Science.gov (United States)

    Nyce, Peggy A.; And Others

    1977-01-01

    Forty-four third graders were given a two-choice conceptual discrimination learning task. The two major factors were (1) four treatment groups varying at the extremes on two personality measures, approval motivation and locus of control and (2) sex. (MS)

  12. Multi-level discriminative dictionary learning with application to large scale image classification.

    Science.gov (United States)

    Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

    2015-10-01

    The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

  13. Learning Auditory Discrimination with Computer-Assisted Instruction: A Comparison of Two Different Performance Objectives.

    Science.gov (United States)

    Steinhaus, Kurt A.

    A 12-week study of two groups of 14 college freshmen music majors was conducted to determine which group demonstrated greater achievement in learning auditory discrimination using computer-assisted instruction (CAI). The method employed was a pre-/post-test experimental design using subjects randomly assigned to a control group or an experimental…

  14. Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning.

    Science.gov (United States)

    Wang, Jinhua; Yang, Xi; Cai, Hongmin; Tan, Wanchang; Jin, Cangzheng; Li, Li

    2016-06-07

    Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer.

  15. Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning.

    Science.gov (United States)

    Zhou, Tao; Liu, Fanghui; Bhaskar, Harish; Yang, Jie

    2017-09-12

    In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can provide good discriminative representations of both target and background. We accomplish this by exploiting the recovery ability of low-rank matrices. That is if we assume that the data from the same class are linearly correlated, then the corresponding basis vectors learned from the training set of each class shall render the dictionary to become approximately low-rank. The proposed dictionary learning technique incorporates a reconstruction error that improves the reliability of classification. Also, a multiconstraint objective function is designed to enable active learning of a discriminative and robust dictionary. Further, an optimal solution is obtained by iteratively computing the dictionary, coefficients, and by simultaneously learning the classifier parameters. Finally, a simple yet effective likelihood function is implemented to estimate the optimal state of the target during tracking. Moreover, to make the dictionary adaptive to the variations of the target and background during tracking, an online update criterion is employed while learning the new dictionary. Experimental results on a publicly available benchmark dataset have demonstrated that the proposed tracking algorithm performs better than other state-of-the-art trackers.

  16. Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

    Science.gov (United States)

    Zeng, Ling-Li; Wang, Huaning; Hu, Panpan; Yang, Bo; Pu, Weidan; Shen, Hui; Chen, Xingui; Liu, Zhening; Yin, Hong; Tan, Qingrong; Wang, Kai; Hu, Dewen

    2018-04-01

    A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the "disconnectivity" model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Copyright © 2018 German Center for Neurodegenerative Diseases (DZNE). Published by Elsevier B.V. All rights reserved.

  17. Supervised orthogonal discriminant subspace projects learning for face recognition.

    Science.gov (United States)

    Chen, Yu; Xu, Xiao-Hong

    2014-02-01

    In this paper, a new linear dimension reduction method called supervised orthogonal discriminant subspace projection (SODSP) is proposed, which addresses high-dimensionality of data and the small sample size problem. More specifically, given a set of data points in the ambient space, a novel weight matrix that describes the relationship between the data points is first built. And in order to model the manifold structure, the class information is incorporated into the weight matrix. Based on the novel weight matrix, the local scatter matrix as well as non-local scatter matrix is defined such that the neighborhood structure can be preserved. In order to enhance the recognition ability, we impose an orthogonal constraint into a graph-based maximum margin analysis, seeking to find a projection that maximizes the difference, rather than the ratio between the non-local scatter and the local scatter. In this way, SODSP naturally avoids the singularity problem. Further, we develop an efficient and stable algorithm for implementing SODSP, especially, on high-dimensional data set. Moreover, the theoretical analysis shows that LPP is a special instance of SODSP by imposing some constraints. Experiments on the ORL, Yale, Extended Yale face database B and FERET face database are performed to test and evaluate the proposed algorithm. The results demonstrate the effectiveness of SODSP. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. 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...

  19. Modeling human color categorization: Color discrimination and color memory

    OpenAIRE

    Heskes, T.; van den Broek, Egon; Lucas, P.; Hendriks, Maria A.; Vuurpijl, L.G.; Puts, M.J.H.; Wiegerinck, W.

    2003-01-01

    Color matching in Content-Based Image Retrieval is done using a color space and measuring distances between colors. Such an approach yields non-intuitive results for the user. We introduce color categories (or focal colors), determine that they are valid, and use them in two experiments. The experiments conducted prove the difference between color categorization by the cognitive processes color discrimination and color memory. In addition, they yield a Color Look-Up Table, which can improve c...

  20. Serum Metabolomic Profiles for Human Pancreatic Cancer Discrimination

    Directory of Open Access Journals (Sweden)

    Takao Itoi

    2017-04-01

    Full Text Available This study evaluated the clinical use of serum metabolomics to discriminate malignant cancers including pancreatic cancer (PC from malignant diseases, such as biliary tract cancer (BTC, intraductal papillary mucinous carcinoma (IPMC, and various benign pancreaticobiliary diseases. Capillary electrophoresismass spectrometry was used to analyze charged metabolites. We repeatedly analyzed serum samples (n = 41 of different storage durations to identify metabolites showing high quantitative reproducibility, and subsequently analyzed all samples (n = 140. Overall, 189 metabolites were quantified and 66 metabolites had a 20% coefficient of variation and, of these, 24 metabolites showed significant differences among control, benign, and malignant groups (p < 0.05; Steel–Dwass test. Four multiple logistic regression models (MLR were developed and one MLR model clearly discriminated all disease patients from healthy controls with an area under receiver operating characteristic curve (AUC of 0.970 (95% confidential interval (CI, 0.946–0.994, p < 0.0001. Another model to discriminate PC from BTC and IPMC yielded AUC = 0.831 (95% CI, 0.650–1.01, p = 0.0020 with higher accuracy compared with tumor markers including carcinoembryonic antigen (CEA, carbohydrate antigen 19-9 (CA19-9, pancreatic cancer-associated antigen (DUPAN2 and s-pancreas-1 antigen (SPAN1. Changes in metabolomic profiles might be used to screen for malignant cancers as well as to differentiate between PC and other malignant diseases.

  1. A perceptual learning deficit in Chinese developmental dyslexia as revealed by visual texture discrimination training.

    Science.gov (United States)

    Wang, Zhengke; Cheng-Lai, Alice; Song, Yan; Cutting, Laurie; Jiang, Yuzheng; Lin, Ou; Meng, Xiangzhi; Zhou, Xiaolin

    2014-08-01

    Learning to read involves discriminating between different written forms and establishing connections with phonology and semantics. This process may be partially built upon visual perceptual learning, during which the ability to process the attributes of visual stimuli progressively improves with practice. The present study investigated to what extent Chinese children with developmental dyslexia have deficits in perceptual learning by using a texture discrimination task, in which participants were asked to discriminate the orientation of target bars. Experiment l demonstrated that, when all of the participants started with the same initial stimulus-to-mask onset asynchrony (SOA) at 300 ms, the threshold SOA, adjusted according to response accuracy for reaching 80% accuracy, did not show a decrement over 5 days of training for children with dyslexia, whereas this threshold SOA steadily decreased over the training for the control group. Experiment 2 used an adaptive procedure to determine the threshold SOA for each participant during training. Results showed that both the group of dyslexia and the control group attained perceptual learning over the sessions in 5 days, although the threshold SOAs were significantly higher for the group of dyslexia than for the control group; moreover, over individual participants, the threshold SOA negatively correlated with their performance in Chinese character recognition. These findings suggest that deficits in visual perceptual processing and learning might, in part, underpin difficulty in reading Chinese. Copyright © 2014 John Wiley & Sons, Ltd.

  2. Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification.

    Science.gov (United States)

    Wen, Zaidao; Hou, Biao; Jiao, Licheng

    2017-05-03

    Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

  3. Aversive reinforcement improves visual discrimination learning in free-flying honeybees.

    Directory of Open Access Journals (Sweden)

    Aurore Avarguès-Weber

    Full Text Available BACKGROUND: Learning and perception of visual stimuli by free-flying honeybees has been shown to vary dramatically depending on the way insects are trained. Fine color discrimination is achieved when both a target and a distractor are present during training (differential conditioning, whilst if the same target is learnt in isolation (absolute conditioning, discrimination is coarse and limited to perceptually dissimilar alternatives. Another way to potentially enhance discrimination is to increase the penalty associated with the distractor. Here we studied whether coupling the distractor with a highly concentrated quinine solution improves color discrimination of both similar and dissimilar colors by free-flying honeybees. As we assumed that quinine acts as an aversive stimulus, we analyzed whether aversion, if any, is based on an aversive sensory input at the gustatory level or on a post-ingestional malaise following quinine feeding. METHODOLOGY/PRINCIPAL FINDINGS: We show that the presence of a highly concentrated quinine solution (60 mM acts as an aversive reinforcer promoting rejection of the target associated with it, and improving discrimination of perceptually similar stimuli but not of dissimilar stimuli. Free-flying bees did not use remote cues to detect the presence of quinine solution; the aversive effect exerted by this substance was mediated via a gustatory input, i.e. via a distasteful sensory experience, rather than via a post-ingestional malaise. CONCLUSION: The present study supports the hypothesis that aversion conditioning is important for understanding how and what animals perceive and learn. By using this form of conditioning coupled with appetitive conditioning in the framework of a differential conditioning procedure, it is possible to uncover discrimination capabilities that may remain otherwise unsuspected. We show, therefore, that visual discrimination is not an absolute phenomenon but can be modulated by experience.

  4. Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

    Science.gov (United States)

    Keshtkaran, Mohammad Reza; Yang, Zhi

    2017-06-01

    Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

  5. Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

    Science.gov (United States)

    Keshtkaran, Mohammad Reza; Yang, Zhi

    2017-06-01

    Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

  6. 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.

  7. 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.

  8. Discriminative Vision-Based Recovery and Recognition of Human Motion

    NARCIS (Netherlands)

    Poppe, Ronald Walter

    2009-01-01

    The automatic analysis of human motion from images opens up the way for applications in the domains of security and surveillance, human-computer interaction, animation, retrieval and sports motion analysis. In this dissertation, the focus is on robust and fast human pose recovery and action

  9. Food approach conditioning and discrimination learning using sound cues in benthic sharks.

    Science.gov (United States)

    Vila Pouca, Catarina; Brown, Culum

    2018-07-01

    The marine environment is filled with biotic and abiotic sounds. Some of these sounds predict important events that influence fitness while others are unimportant. Individuals can learn specific sound cues and 'soundscapes' and use them for vital activities such as foraging, predator avoidance, communication and orientation. Most research with sounds in elasmobranchs has focused on hearing thresholds and attractiveness to sound sources, but very little is known about their abilities to learn about sounds, especially in benthic species. Here we investigated if juvenile Port Jackson sharks could learn to associate a musical stimulus with a food reward, discriminate between two distinct musical stimuli, and whether individual personality traits were linked to cognitive performance. Five out of eight sharks were successfully conditioned to associate a jazz song with a food reward delivered in a specific corner of the tank. We observed repeatable individual differences in activity and boldness in all eight sharks, but these personality traits were not linked to the learning performance assays we examined. These sharks were later trained in a discrimination task, where they had to distinguish between the same jazz and a novel classical music song, and swim to opposite corners of the tank according to the stimulus played. The sharks' performance to the jazz stimulus declined to chance levels in the discrimination task. Interestingly, some sharks developed a strong side bias to the right, which in some cases was not the correct side for the jazz stimulus.

  10. 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...

  11. Abnormality detection of mammograms by discriminative dictionary learning on DSIFT descriptors.

    Science.gov (United States)

    Tavakoli, Nasrin; Karimi, Maryam; Nejati, Mansour; Karimi, Nader; Reza Soroushmehr, S M; Samavi, Shadrokh; Najarian, Kayvan

    2017-07-01

    Detection and classification of breast lesions using mammographic images are one of the most difficult studies in medical image processing. A number of learning and non-learning methods have been proposed for detecting and classifying these lesions. However, the accuracy of the detection/classification still needs improvement. In this paper we propose a powerful classification method based on sparse learning to diagnose breast cancer in mammograms. For this purpose, a supervised discriminative dictionary learning approach is applied on dense scale invariant feature transform (DSIFT) features. A linear classifier is also simultaneously learned with the dictionary which can effectively classify the sparse representations. Our experimental results show the superior performance of our method compared to existing approaches.

  12. Vicarious trial-and-error behavior and hippocampal cytochrome oxidase activity during Y-maze discrimination learning in the rat.

    Science.gov (United States)

    Hu, Dan; Xu, Xiaojuan; Gonzalez-Lima, Francisco

    2006-03-01

    The present study investigated whether more vicarious trial-and-error (VTE) behavior, defined by head movement from one stimulus to another at a choice point during simultaneous discriminations, led to better visual discrimination learning in a Y-maze, and whether VTE behavior was a function of the hippocampus by measuring regional brain cytochrome oxidase (C.O.) activity, an index of neuronal metabolic activity. The results showed that the more VTEs a rat made, the better the rat learned the visual discrimination. Furthermore, both learning and VTE behavior during learning were correlated to C.O. activity in the hippocampus, suggesting that the hippocampus plays a role in VTE behavior during discrimination learning.

  13. Mechanisms underlying speech sound discrimination and categorization in humans and zebra finches

    NARCIS (Netherlands)

    Burgering, Merel A.; ten Cate, Carel; Vroomen, Jean

    Speech sound categorization in birds seems in many ways comparable to that by humans, but it is unclear what mechanisms underlie such categorization. To examine this, we trained zebra finches and humans to discriminate two pairs of edited speech sounds that varied either along one dimension (vowel

  14. Performance and strategy comparisons of human listeners and logistic regression in discriminating underwater targets.

    Science.gov (United States)

    Yang, Lixue; Chen, Kean

    2015-11-01

    To improve the design of underwater target recognition systems based on auditory perception, this study compared human listeners with automatic classifiers. Performances measures and strategies in three discrimination experiments, including discriminations between man-made and natural targets, between ships and submarines, and among three types of ships, were used. In the experiments, the subjects were asked to assign a score to each sound based on how confident they were about the category to which it belonged, and logistic regression, which represents linear discriminative models, also completed three similar tasks by utilizing many auditory features. The results indicated that the performances of logistic regression improved as the ratio between inter- and intra-class differences became larger, whereas the performances of the human subjects were limited by their unfamiliarity with the targets. Logistic regression performed better than the human subjects in all tasks but the discrimination between man-made and natural targets, and the strategies employed by excellent human subjects were similar to that of logistic regression. Logistic regression and several human subjects demonstrated similar performances when discriminating man-made and natural targets, but in this case, their strategies were not similar. An appropriate fusion of their strategies led to further improvement in recognition accuracy.

  15. Rapid discrimination of visual scene content in the human brain

    Science.gov (United States)

    Anokhin, Andrey P.; Golosheykin, Simon; Sirevaag, Erik; Kristjansson, Sean; Rohrbaugh, John W.; Heath, Andrew C.

    2007-01-01

    The rapid evaluation of complex visual environments is critical for an organism's adaptation and survival. Previous studies have shown that emotionally significant visual scenes, both pleasant and unpleasant, elicit a larger late positive wave in the event-related brain potential (ERP) than emotionally neutral pictures. The purpose of the present study was to examine whether neuroelectric responses elicited by complex pictures discriminate between specific, biologically relevant contents of the visual scene and to determine how early in the picture processing this discrimination occurs. Subjects (n=264) viewed 55 color slides differing in both scene content and emotional significance. No categorical judgments or responses were required. Consistent with previous studies, we found that emotionally arousing pictures, regardless of their content, produce a larger late positive wave than neutral pictures. However, when pictures were further categorized by content, anterior ERP components in a time window between 200−600 ms following stimulus onset showed a high selectivity for pictures with erotic content compared to other pictures regardless of their emotional valence (pleasant, neutral, and unpleasant) or emotional arousal. The divergence of ERPs elicited by erotic and non-erotic contents started at 185 ms post-stimulus in the fronto-central midline regions, with a later onset in parietal regions. This rapid, selective, and content-specific processing of erotic materials and its dissociation from other pictures (including emotionally positive pictures) suggests the existence of a specialized neural network for prioritized processing of a distinct category of biologically relevant stimuli with high adaptive and evolutionary significance. PMID:16712815

  16. Valence of facial cues influences sheep learning in a visual discrimination task

    OpenAIRE

    Bellegarde, Lucille; Erhard, Hans; Weiss, A.; Boissy, Alain; Haskell, M.J.

    2017-01-01

    Sheep are one of the most studied farm species in terms of their ability to process information from faces, but little is known about their face-based emotion recognition abilities. We investigated (a) whether sheep could use images of sheep faces taken in situation of varying valence as cues in a simultaneous discrimination task and (b) whether the valence of the situation affects their learning performance. To accomplish this, we photographed faces of sheep in three situations inducing emot...

  17. Valence of Facial Cues Influences Sheep Learning in a Visual Discrimination Task

    OpenAIRE

    Lucille G. A. Bellegarde; Lucille G. A. Bellegarde; Lucille G. A. Bellegarde; Hans W. Erhard; Alexander Weiss; Alain Boissy; Marie J. Haskell

    2017-01-01

    Sheep are one of the most studied farm species in terms of their ability to process information from faces, but little is known about their face-based emotion recognition abilities. We investigated (a) whether sheep could use images of sheep faces taken in situation of varying valence as cues in a simultaneous discrimination task and (b) whether the valence of the situation affects their learning performance. To accomplish this, we photographed faces of sheep in three situations inducing emot...

  18. Transfer of Perceptual Learning of Depth Discrimination Between Local and Global Stereograms

    OpenAIRE

    Gantz, Liat; Bedell, Harold

    2010-01-01

    Several previous studies reported differences when stereothresholds are assessed with local-contour stereograms vs. complex random-dot stereograms (RDSs). Dissimilar thresholds may be due to differences in the properties of the stereograms (e.g., spatial frequency content, contrast, inter-element separation, area) or to different underlying processing mechanisms. This study examined the transfer of perceptual learning of depth discrimination between local and global RDSs with similar properti...

  19. Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data

    Directory of Open Access Journals (Sweden)

    Michael Veale

    2017-11-01

    Full Text Available Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining (DADM and fairness, accountability and transparency machine learning (FATML, their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data on sensitive attributes such as gender, ethnicity, sexuality or disability needed to diagnose and mitigate emergent indirect discrimination-by-proxy, such as redlining. Such organisations might also lack the knowledge and capacity to identify and manage fairness issues that are emergent properties of complex sociotechnical systems. This paper presents and discusses three potential approaches to deal with such knowledge and information deficits in the context of fairer machine learning. Trusted third parties could selectively store data necessary for performing discrimination discovery and incorporating fairness constraints into model-building in a privacy-preserving manner. Collaborative online platforms would allow diverse organisations to record, share and access contextual and experiential knowledge to promote fairness in machine learning systems. Finally, unsupervised learning and pedagogically interpretable algorithms might allow fairness hypotheses to be built for further selective testing and exploration. Real-world fairness challenges in machine learning are not abstract, constrained optimisation problems, but are institutionally and contextually grounded. Computational fairness tools are useful, but must be researched and developed in and with the messy contexts that will shape their deployment, rather than just for imagined situations. Not doing so risks real, near-term algorithmic harm.

  20. 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

  1. Dissociable Hippocampal and Amygdalar D1-like receptor contribution to Discriminated Pavlovian conditioned approach learning

    Science.gov (United States)

    Andrzejewski, Matthew E; Ryals, Curtis

    2016-01-01

    Pavlovian conditioning is an elementary form of reward-related behavioral adaptation. The mesolimbic dopamine system is widely considered to mediate critical aspects of reward-related learning. For example, initial acquisition of positively-reinforced operant behavior requires dopamine (DA) D1 receptor (D1R) activation in the basolateral amygdala (BLA), central nucleus of the amygdala (CeA), and the ventral subiculum (vSUB). However, the role of D1R activation in these areas on appetitive, non-drug-related, Pavlovian learning is not currently known. In separate experiments, microinfusions of the D1-like receptor antagonist SCH-23390 (3.0 nmol/0.5 μL per side) into the amygdala and subiculum preceded discriminated Pavlovian conditioned approach (dPCA) training sessions. D1-like antagonism in all three structures impaired the acquisition of discriminated approach, but had no effect on performance after conditioning was asymptotic. Moreover, dissociable effects of D1-like antagonism in the three structures on components of discriminated responding were obtained. Lastly, the lack of latent inhibition in drug-treated groups may elucidate the role of D1-like in reward-related Pavlovian conditioning. The present data suggest a role for the D1 receptors in the amygdala and hippocampus in learning the significance of conditional stimuli, but not in the expression of conditional responses. PMID:26632336

  2. Differential effects of visual context on pattern discrimination by pigeons (Columba livia) and humans (Homo sapiens).

    Science.gov (United States)

    Kelly, Debbie M; Cook, Robert G

    2003-06-01

    Three experiment examined the role of contextual information during line orientation and line position discriminations by pigeons (Columba livia) and humans (Homo sapiens). Experiment 1 tested pigeons' performance with these stimuli in a target localization task using texture displays. Experiments 2 and 3 tested pigeons and humans, respectively, with small and large variations of these stimuli in a same-different task. Humans showed a configural superiority effect when tested with displays constructed from large elements but not when tested with the smaller, more densely packed texture displays. The pigeons, in contrast, exhibited a configural inferiority effect when required to discriminate line orientation, regardless of stimulus size. These contrasting results suggest a species difference in the perceptionand use of features and contextual information in the discrimination of line information.

  3. Learning discriminative distance functions for valve retrieval and improved decision support in valvular heart disease

    Science.gov (United States)

    Voigt, Ingmar; Vitanovski, Dime; Ionasec, Razvan I.; Tsymal, Alexey; Georgescu, Bogdan; Zhou, Shaohua K.; Huber, Martin; Navab, Nassir; Hornegger, Joachim; Comaniciu, Dorin

    2010-03-01

    Disorders of the heart valves constitute a considerable health problem and often require surgical intervention. Recently various approaches were published seeking to overcome the shortcomings of current clinical practice,that still relies on manually performed measurements for performance assessment. Clinical decisions are still based on generic information from clinical guidelines and publications and personal experience of clinicians. We present a framework for retrieval and decision support using learning based discriminative distance functions and visualization of patient similarity with relative neighborhood graphsbased on shape and derived features. We considered two learning based techniques, namely learning from equivalence constraints and the intrinsic Random Forest distance. The generic approach enables for learning arbitrary user-defined concepts of similarity depending on the application. This is demonstrated with the proposed applications, including automated diagnosis and interventional suitability classification, where classification rates of up to 88.9% and 85.9% could be observed on a set of valve models from 288 and 102 patients respectively.

  4. Words from spontaneous conversational speech can be recognized with human-like accuracy by an error-driven learning algorithm that discriminates between meanings straight from smart acoustic features, bypassing the phoneme as recognition unit.

    Science.gov (United States)

    Arnold, Denis; Tomaschek, Fabian; Sering, Konstantin; Lopez, Florence; Baayen, R Harald

    2017-01-01

    Sound units play a pivotal role in cognitive models of auditory comprehension. The general consensus is that during perception listeners break down speech into auditory words and subsequently phones. Indeed, cognitive speech recognition is typically taken to be computationally intractable without phones. Here we present a computational model trained on 20 hours of conversational speech that recognizes word meanings within the range of human performance (model 25%, native speakers 20-44%), without making use of phone or word form representations. Our model also generates successfully predictions about the speed and accuracy of human auditory comprehension. At the heart of the model is a 'wide' yet sparse two-layer artificial neural network with some hundred thousand input units representing summaries of changes in acoustic frequency bands, and proxies for lexical meanings as output units. We believe that our model holds promise for resolving longstanding theoretical problems surrounding the notion of the phone in linguistic theory.

  5. Separate and combined effects of the GABAB agonist baclofen and Δ9-THC in humans discriminating Δ9-THC

    Science.gov (United States)

    Lile, Joshua A.; Kelly, Thomas H.; Hays, Lon R.

    2012-01-01

    Background Our previous research with the GABA reuptake inhibitor tiagabine suggested the involvement GABA in the interoceptive effects of Δ9-THC. The aim of the present study was to determine the potential involvement of the GABAB receptor subtype by assessing the separate and combined effects of the GABAB-selective agonist baclofen and Δ9-THC using pharmacologically specific drug-discrimination procedures. Methods Eight cannabis users learned to discriminate 30 mg oral Δ9-THC from placebo and then received baclofen (25 and 50 mg), Δ9-THC (5, 15 and 30 mg) and placebo, alone and in combination. Self-report, task performance and physiological measures were also collected. Results Δ9-THC functioned as a discriminative stimulus, produced subjective effects typically associated with cannabinoids (e.g., High, Stoned, Like Drug), elevated heart rate and impaired rate and accuracy on a psychomotor performance task. Baclofen alone (50 mg) substituted for the Δ9-THC discriminative stimulus, and both baclofen doses shifted the discriminative-stimulus effects of Δ9-THC leftward/upward. Similar results were observed on other cannabinoid-sensitive outcomes, although baclofen generally did not engender Δ9-THC-like subjective responses when administered alone. Conclusions These results suggest that the GABAB receptor subtype is involved in the abuse-related effects of Δ9-THC, and that GABAB receptors were responsible, at least in part, for the effects of tiagabine-induced elevated GABA on cannabinoid-related behaviors in our previous study. Future research should test GABAergic compounds selective for other GABA receptor subtypes (i.e., GABAA) to determine the contribution of the different GABA receptors in the effects of Δ9-THC, and by extension cannabis, in humans. PMID:22699093

  6. Long term effects of aversive reinforcement on colour discrimination learning in free-flying bumblebees.

    Directory of Open Access Journals (Sweden)

    Miguel A Rodríguez-Gironés

    Full Text Available The results of behavioural experiments provide important information about the structure and information-processing abilities of the visual system. Nevertheless, if we want to infer from behavioural data how the visual system operates, it is important to know how different learning protocols affect performance and to devise protocols that minimise noise in the response of experimental subjects. The purpose of this work was to investigate how reinforcement schedule and individual variability affect the learning process in a colour discrimination task. Free-flying bumblebees were trained to discriminate between two perceptually similar colours. The target colour was associated with sucrose solution, and the distractor could be associated with water or quinine solution throughout the experiment, or with one substance during the first half of the experiment and the other during the second half. Both acquisition and final performance of the discrimination task (measured as proportion of correct choices were determined by the choice of reinforcer during the first half of the experiment: regardless of whether bees were trained with water or quinine during the second half of the experiment, bees trained with quinine during the first half learned the task faster and performed better during the whole experiment. Our results confirm that the choice of stimuli used during training affects the rate at which colour discrimination tasks are acquired and show that early contact with a strongly aversive stimulus can be sufficient to maintain high levels of attention during several hours. On the other hand, bees which took more time to decide on which flower to alight were more likely to make correct choices than bees which made fast decisions. This result supports the existence of a trade-off between foraging speed and accuracy, and highlights the importance of measuring choice latencies during behavioural experiments focusing on cognitive abilities.

  7. Gender discrimination, gender disparities in obesity and human development

    Directory of Open Access Journals (Sweden)

    Fabrizio Ferretti

    2017-03-01

    Full Text Available Measuring gender inequality and women’s empowerment is essential to understand the determinants of gender gaps, evaluate policies and monitor countries’ progress. With this aim, over the past two decades, research has mainly been directed towards the development of composite indices. The purpose of this paper is to introduce a new and interdisciplinary perspective to the current debate on measuring gender inequality in human development. As a starting point, we develop a simple macroeconomic model of the interdependence between human development and gender inequality. We then introduce a biometric indicator, based on the ratio of female to male body mass index, to measure women’s empowerment at the country level. Finally, by using the latest available data, we examine the ability of this biometric indicator to capture countries’ performance in achieving gender equality. We obtain five main results: 1 we provide a theoretical framework to explain the joint determination of human development and gender inequality; 2 we show how to use this framework to simulate the impact of exogenous shocks or policy changes; 3 we demonstrate that exogenous changes have a direct and a multiplier effect on human development and gender inequality; 4 we find that the distribution of obesity between the female and male populations represents a useful proxy variable for measuring gender equality at the country level; 5 finally, we use these results to integrate and develop existing knowledge on the ‘ecological’ approach to the overweight and obesity pandemic.

  8. Gender discrimination, gender disparities in obesity and human development.

    Science.gov (United States)

    Ferretti, Fabrizio; Mariani, Michele

    2017-03-01

    Measuring gender inequality and women's empowerment is essential to understand the determinants of gender gaps, evaluate policies and monitor countries' progress. With this aim, over the past two decades, research has mainly been directed towards the development of composite indices. The purpose of this paper is to introduce a new and interdisciplinary perspective to the current debate on measuring gender inequality in human development. As a starting point, we develop a simple macroeconomic model of the interdependence between human development and gender inequality. We then introduce a biometric indicator, based on the ratio of female to male body mass index, to measure women's empowerment at the country level. Finally, by using the latest available data, we examine the ability of this biometric indicator to capture countries' performance in achieving gender equality. We obtain five main results: 1) we provide a theoretical framework to explain the joint determination of human development and gender inequality; 2) we show how to use this framework to simulate the impact of exogenous shocks or policy changes; 3) we demonstrate that exogenous changes have a direct and a multiplier effect on human development and gender inequality; 4) we find that the distribution of obesity between the female and male populations represents a useful proxy variable for measuring gender equality at the country level; 5) finally, we use these results to integrate and develop existing knowledge on the 'ecological' approach to the overweight and obesity pandemic.

  9. Does Fine Color Discrimination Learning in Free-Flying Honeybees Change Mushroom-Body Calyx Neuroarchitecture?

    Science.gov (United States)

    Sommerlandt, Frank M J; Spaethe, Johannes; Rössler, Wolfgang; Dyer, Adrian G

    2016-01-01

    Honeybees learn color information of rewarding flowers and recall these memories in future decisions. For fine color discrimination, bees require differential conditioning with a concurrent presentation of target and distractor stimuli to form a long-term memory. Here we investigated whether the long-term storage of color information shapes the neural network of microglomeruli in the mushroom body calyces and if this depends on the type of conditioning. Free-flying honeybees were individually trained to a pair of perceptually similar colors in either absolute conditioning towards one of the colors or in differential conditioning with both colors. Subsequently, bees of either conditioning groups were tested in non-rewarded discrimination tests with the two colors. Only bees trained with differential conditioning preferred the previously learned color, whereas bees of the absolute conditioning group, and a stimuli-naïve group, chose randomly among color stimuli. All bees were then kept individually for three days in the dark to allow for complete long-term memory formation. Whole-mount immunostaining was subsequently used to quantify variation of microglomeruli number and density in the mushroom-body lip and collar. We found no significant differences among groups in neuropil volumes and total microglomeruli numbers, but learning performance was negatively correlated with microglomeruli density in the absolute conditioning group. Based on these findings we aim to promote future research approaches combining behaviorally relevant color learning tests in honeybees under free-flight conditions with neuroimaging analysis; we also discuss possible limitations of this approach.

  10. Spatial discrimination and visual discrimination

    DEFF Research Database (Denmark)

    Haagensen, Annika M. J.; Grand, Nanna; Klastrup, Signe

    2013-01-01

    Two methods investigating learning and memory in juvenile Gottingen minipigs were evaluated for potential use in preclinical toxicity testing. Twelve minipigs were tested using a spatial hole-board discrimination test including a learning phase and two memory phases. Five minipigs were tested...... in a visual discrimination test. The juvenile minipigs were able to learn the spatial hole-board discrimination test and showed improved working and reference memory during the learning phase. Performance in the memory phases was affected by the retention intervals, but the minipigs were able to remember...... the concept of the test in both memory phases. Working memory and reference memory were significantly improved in the last trials of the memory phases. In the visual discrimination test, the minipigs learned to discriminate between the three figures presented to them within 9-14 sessions. For the memory test...

  11. Pigeons learn stimulus identity and stimulus relations when both serve as redundant, relevant cues during same-different discrimination training.

    Science.gov (United States)

    Gibson, Brett M; Wasserman, Edward A

    2003-01-01

    The authors taught pigeons to discriminate displays of 16 identical items from displays of 16 nonidentical items. Unlike most same-different discrimination studies--where only stimulus relations could serve a discriminative function--both the identity of the items and the relations among the items were discriminative features of the displays. The pigeons learned about both stimulus identity and stimulus relations when these 2 sources of information served as redundant, relevant cues. In tests of associative competition, identity cues exerted greater stimulus control than relational cues. These results suggest that the pigeon can respond to both specific stimuli and general relations in the environment.

  12. Gender discrimination, gender disparities in obesity and human development

    OpenAIRE

    Ferretti, Fabrizio; Mariani, Michele

    2017-01-01

    Measuring gender inequality and women’s empowerment is essential to understand the determinants of gender gaps, evaluate policies and monitor countries’ progress. With this aim, over the past two decades, research has mainly been directed towards the development of composite indices. The purpose of this paper is to introduce a new and interdisciplinary perspective to the current debate on measuring gender inequality in human development. As a starting point, we develop a simple macroeconomic ...

  13. Discrimination of Rock Fracture and Blast Events Based on Signal Complexity and Machine Learning

    Directory of Open Access Journals (Sweden)

    Zilong Zhou

    2018-01-01

    Full Text Available The automatic discrimination of rock fracture and blast events is complex and challenging due to the similar waveform characteristics. To solve this problem, a new method based on the signal complexity analysis and machine learning has been proposed in this paper. First, the permutation entropy values of signals at different scale factors are calculated to reflect complexity of signals and constructed into a feature vector set. Secondly, based on the feature vector set, back-propagation neural network (BPNN as a means of machine learning is applied to establish a discriminator for rock fracture and blast events. Then to evaluate the classification performances of the new method, the classifying accuracies of support vector machine (SVM, naive Bayes classifier, and the new method are compared, and the receiver operating characteristic (ROC curves are also analyzed. The results show the new method obtains the best classification performances. In addition, the influence of different scale factor q and number of training samples n on discrimination results is discussed. It is found that the classifying accuracy of the new method reaches the highest value when q = 8–15 or 8–20 and n=140.

  14. Brightness discrimination learning in a Skinner box in prenatally X-irradiated rats

    International Nuclear Information System (INIS)

    Tamaki, Y.; Inouye, M.

    1976-01-01

    Male MP 1 albino rats were exposed to x-irradiation in utero at a single dose of 200 R on day 17 of gestation. The light-dark discrimination training in a Skinner box was continued until the animals attained a learning criterion of 0.80 correct response ratio for 3 consecutive days. Although during the unreinforced baseline sessions the total number of bar pressings in the irradiated animals was superior to that in the controls, performance between the control and the irradiated animals did not differ significantly in (a) the number of training days required to attain the learning criterion, (b) the total number of days on which the animals produced a correct response ratio more than 0.80, and (c) the number of consecutive days during which the correct response ratio was more than 0.75. The results obtained suggest that the irradiated animals were able to discriminate in brightness cues as well, or nearly as well, as the controls. The cortical-subcortical system mediating brightness discrimination in the irradiated animals is discussed. (author)

  15. Semi-Supervised Tensor-Based Graph Embedding Learning and Its Application to Visual Discriminant Tracking.

    Science.gov (United States)

    Hu, Weiming; Gao, Jin; Xing, Junliang; Zhang, Chao; Maybank, Stephen

    2017-01-01

    An appearance model adaptable to changes in object appearance is critical in visual object tracking. In this paper, we treat an image patch as a two-order tensor which preserves the original image structure. We design two graphs for characterizing the intrinsic local geometrical structure of the tensor samples of the object and the background. Graph embedding is used to reduce the dimensions of the tensors while preserving the structure of the graphs. Then, a discriminant embedding space is constructed. We prove two propositions for finding the transformation matrices which are used to map the original tensor samples to the tensor-based graph embedding space. In order to encode more discriminant information in the embedding space, we propose a transfer-learning- based semi-supervised strategy to iteratively adjust the embedding space into which discriminative information obtained from earlier times is transferred. We apply the proposed semi-supervised tensor-based graph embedding learning algorithm to visual tracking. The new tracking algorithm captures an object's appearance characteristics during tracking and uses a particle filter to estimate the optimal object state. Experimental results on the CVPR 2013 benchmark dataset demonstrate the effectiveness of the proposed tracking algorithm.

  16. Machinery fault diagnosis using joint global and local/nonlocal discriminant analysis with selective ensemble learning

    Science.gov (United States)

    Yu, Jianbo

    2016-11-01

    The vibration signals of faulty machine are generally non-stationary and nonlinear under those complicated working conditions. Thus, it is a big challenge to extract and select the effective features from vibration signals for machinery fault diagnosis. This paper proposes a new manifold learning algorithm, joint global and local/nonlocal discriminant analysis (GLNDA), which aims to extract effective intrinsic geometrical information from the given vibration data. Comparisons with other regular methods, principal component analysis (PCA), local preserving projection (LPP), linear discriminant analysis (LDA) and local LDA (LLDA), illustrate the superiority of GLNDA in machinery fault diagnosis. Based on the extracted information by GLNDA, a GLNDA-based Fisher discriminant rule (FDR) is put forward and applied to machinery fault diagnosis without additional recognizer construction procedure. By importing Bagging into GLNDA score-based feature selection and FDR, a novel manifold ensemble method (selective GLNDA ensemble, SE-GLNDA) is investigated for machinery fault diagnosis. The motivation for developing ensemble of manifold learning components is that it can achieve higher accuracy and applicability than single component in machinery fault diagnosis. The effectiveness of the SE-GLNDA-based fault diagnosis method has been verified by experimental results from bearing full life testers.

  17. Faster native vowel discrimination learning in musicians is mediated by an optimization of mnemonic functions.

    Science.gov (United States)

    Elmer, Stefan; Greber, Marielle; Pushparaj, Arethy; Kühnis, Jürg; Jäncke, Lutz

    2017-09-01

    The ability to discriminate phonemes varying in spectral and temporal attributes constitutes one of the most basic intrinsic elements underlying language learning mechanisms. Since previous work has consistently shown that professional musicians are characterized by perceptual and cognitive advantages in a variety of language-related tasks, and since vowels can be considered musical sounds within the domain of speech, here we investigated the behavioral and electrophysiological correlates of native vowel discrimination learning in a sample of professional musicians and non-musicians. We evaluated the contribution of both the neurophysiological underpinnings of perceptual (i.e., N1/P2 complex) and mnemonic functions (i.e., N400 and P600 responses) while the participants were instructed to judge whether pairs of native consonant-vowel (CV) syllables manipulated in the first formant transition of the vowel (i.e., from /tu/ to /to/) were identical or not. Results clearly demonstrated faster learning in musicians, compared to non-musicians, as reflected by shorter reaction times and higher accuracy. Most notably, in terms of morphology, time course, and voltage strength, this steeper learning curve was accompanied by distinctive N400 and P600 manifestations between the two groups. In contrast, we did not reveal any group differences during the early stages of auditory processing (i.e., N1/P2 complex), suggesting that faster learning was mediated by an optimization of mnemonic but not perceptual functions. Based on a clear taxonomy of the mnemonic functions involved in the task, results are interpreted as pointing to a relationship between faster learning mechanisms in musicians and an optimization of echoic (i.e., N400 component) and working memory (i.e., P600 component) functions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Hippocampus, Perirhinal Cortex, and Complex Visual Discriminations in Rats and Humans

    Science.gov (United States)

    Hales, Jena B.; Broadbent, Nicola J.; Velu, Priya D.; Squire, Larry R.; Clark, Robert E.

    2015-01-01

    Structures in the medial temporal lobe, including the hippocampus and perirhinal cortex, are known to be essential for the formation of long-term memory. Recent animal and human studies have investigated whether perirhinal cortex might also be important for visual perception. In our study, using a simultaneous oddity discrimination task, rats with…

  19. Human listeners provide insights into echo features used by dolphins (Tursiops truncatus) to discriminate among objects.

    Science.gov (United States)

    Delong, Caroline M; Au, Whitlow W L; Harley, Heidi E; Roitblat, Herbert L; Pytka, Lisa

    2007-08-01

    Echolocating bottlenose dolphins (Tursiops truncatus) discriminate between objects on the basis of the echoes reflected by the objects. However, it is not clear which echo features are important for object discrimination. To gain insight into the salient features, the authors had a dolphin perform a match-to-sample task and then presented human listeners with echoes from the same objects used in the dolphin's task. In 2 experiments, human listeners performed as well or better than the dolphin at discriminating objects, and they reported the salient acoustic cues. The error patterns of the humans and the dolphin were compared to determine which acoustic features were likely to have been used by the dolphin. The results indicate that the dolphin did not appear to use overall echo amplitude, but that it attended to the pattern of changes in the echoes across different object orientations. Human listeners can quickly identify salient combinations of echo features that permit object discrimination, which can be used to generate hypotheses that can be tested using dolphins as subjects.

  20. Common Elements Enhance or Retard Negative Patterning Discrimination Learning Depending on Modality of Stimuli

    Science.gov (United States)

    Redhead, Edward S.; Curtis, Cheryl

    2013-01-01

    Human contingency learning studies were used to compare the predictions of configural and elemental theories. In two experiments, participants were required to learn which stimuli were associated with an increase in core temperature of a fictitious nuclear plant. Experiments investigated the rate at which a simple negative patterning…

  1. Sparse representation for infrared Dim target detection via a discriminative over-complete dictionary learned online.

    Science.gov (United States)

    Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

    2014-05-27

    It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

  2. Sparse Representation for Infrared Dim Target Detection via a Discriminative Over-Complete Dictionary Learned Online

    Directory of Open Access Journals (Sweden)

    Zheng-Zhou Li

    2014-05-01

    Full Text Available It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn’t be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

  3. Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model

    OpenAIRE

    Lu, Jiasen; Kannan, Anitha; Yang, Jianwei; Parikh, Devi; Batra, Dhruv

    2017-01-01

    We present a novel training framework for neural sequence models, particularly for grounded dialog generation. The standard training paradigm for these models is maximum likelihood estimation (MLE), or minimizing the cross-entropy of the human responses. Across a variety of domains, a recurring problem with MLE trained generative neural dialog models (G) is that they tend to produce 'safe' and generic responses ("I don't know", "I can't tell"). In contrast, discriminative dialog models (D) th...

  4. Improved Discriminability of Spatiotemporal Neural Patterns in Rat Motor Cortical Areas as Directional Choice Learning Progresses

    Directory of Open Access Journals (Sweden)

    Hongwei eMao

    2015-03-01

    Full Text Available Animals learn to choose a proper action among alternatives to improve their odds of success in food foraging and other activities critical for survival. Through trial-and-error, they learn correct associations between their choices and external stimuli. While a neural network that underlies such learning process has been identified at a high level, it is still unclear how individual neurons and a neural ensemble adapt as learning progresses. In this study, we monitored the activity of single units in the rat medial and lateral agranular (AGm and AGl, respectively areas as rats learned to make a left or right side lever press in response to a left or right side light cue. We noticed that rat movement parameters during the performance of the directional choice task quickly became stereotyped during the first 2-3 days or sessions. But learning the directional choice problem took weeks to occur. Accompanying rats’ behavioral performance adaptation, we observed neural modulation by directional choice in recorded single units. Our analysis shows that ensemble mean firing rates in the cue-on period did not change significantly as learning progressed, and the ensemble mean rate difference between left and right side choices did not show a clear trend of change either. However, the spatiotemporal firing patterns of the neural ensemble exhibited improved discriminability between the two directional choices through learning. These results suggest a spatiotemporal neural coding scheme in a motor cortical neural ensemble that may be responsible for and contributing to learning the directional choice task.

  5. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

    International Nuclear Information System (INIS)

    Guo, Yanrong; Shao, Yeqin; Gao, Yaozong; Price, True; Oto, Aytekin; Shen, Dinggang

    2014-01-01

    Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on

  6. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

    Science.gov (United States)

    Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

    2014-01-01

    Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different

  7. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning.

    Science.gov (United States)

    Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

    2014-07-01

    Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different patches of the

  8. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Yanrong; Shao, Yeqin [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong; Price, True [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Computer Science, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Oto, Aytekin [Department of Radiology, Section of Urology, University of Chicago, Illinois 60637 (United States); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)

    2014-07-15

    Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on

  9. Statistics that learn: can logistic discriminant analysis improve diagnosis in brain SPECT?

    International Nuclear Information System (INIS)

    Behin-Ain, S.; Barnden, L.; Kwiatek, R.; Del Fante, P.; Casse, R.; Burnet, R.; Chew, G.; Kitchener, M.; Boundy, K.; Unger, S.

    2002-01-01

    Full text: Logistic discriminant analysis (LDA) is a statistical technique capable of discriminating individuals within a diseased group against normals. It also enables classification of various diseases within a group of patients. This technique provides a quantitative, automated and non-subjective clinical diagnostic tool. Based on a population known to have the disease and a normal control group, an algorithm was developed and trained to identify regions in the human brain responsible for the disease in question. The algorithm outputs a statistical map representing diseased or normal probability on a voxel or cluster basis from which an index is generated for each subject. The algorithm also generates a set of coefficients which is used to generate an index for the purpose of classification of new subjects. The results are comparable and complement those of Statistical Parametric Mapping (SPM) which employs a more common linear discriminant technique. The results are presented for brain SPECT studies of two diseases: chronic fatigue syndrome (CFS) and fibromyalgia (FM). A 100% specificity and 94% sensitivity is achieved for the CFS study (similar to SPM results) and for the FM study 82% specificity and 94% sensitivity is achieved with corresponding SPM results showing 90% specificity and 82% sensitivity. The results encourages application of LDA for discrimination of new single subjects as well as of diseased and normal groups. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc

  10. Discriminative stimuli that control instrumental tobacco-seeking by human smokers also command selective attention.

    Science.gov (United States)

    Hogarth, Lee; Dickinson, Anthony; Duka, Theodora

    2003-08-01

    Incentive salience theory states that acquired bias in selective attention for stimuli associated with tobacco-smoke reinforcement controls the selective performance of tobacco-seeking and tobacco-taking behaviour. To support this theory, we assessed whether a stimulus that had acquired control of a tobacco-seeking response in a discrimination procedure would command the focus of visual attention in a subsequent test phase. Smokers received discrimination training in which an instrumental key-press response was followed by tobacco-smoke reinforcement when one visual discriminative stimulus (S+) was present, but not when another stimulus (S-) was present. The skin conductance response to the S+ and S- assessed whether Pavlovian conditioning to the S+ had taken place. In a subsequent test phase, the S+ and S- were presented in the dot-probe task and the allocation of the focus of visual attention to these stimuli was measured. Participants learned to perform the instrumental tobacco-seeking response selectively in the presence of the S+ relative to the S-, and showed a greater skin conductance response to the S+ than the S-. In the subsequent test phase, participants allocated the focus of visual attention to the S+ in preference to the S-. Correlation analysis revealed that the visual attentional bias for the S+ was positively associated with the number of times the S+ had been paired with tobacco-smoke in training, the skin conductance response to the S+ and with subjective craving to smoke. Furthermore, increased exposure to tobacco-smoke in the natural environment was associated with reduced discrimination learning. These data demonstrate that discriminative stimuli that signal that tobacco-smoke reinforcement is available acquire the capacity to command selective attentional and elicit instrumental tobacco-seeking behaviour.

  11. Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data.

    Science.gov (United States)

    Tomazzoli, Maíra M; Pai Neto, Remi D; Moresco, Rodolfo; Westphal, Larissa; Zeggio, Amelia R S; Specht, Leandro; Costa, Christopher; Rocha, Miguel; Maraschin, Marcelo

    2015-12-01

    Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plant's resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( λ= 280-400 ηm), suggesting that besides the biological activities of those

  12. Different levels of food restriction reveal genotype-specific differences in learning a visual discrimination task.

    Directory of Open Access Journals (Sweden)

    Kalina Makowiecki

    Full Text Available In behavioural experiments, motivation to learn can be achieved using food rewards as positive reinforcement in food-restricted animals. Previous studies reduce animal weights to 80-90% of free-feeding body weight as the criterion for food restriction. However, effects of different degrees of food restriction on task performance have not been assessed. We compared learning task performance in mice food-restricted to 80 or 90% body weight (BW. We used adult wildtype (WT; C57Bl/6j and knockout (ephrin-A2⁻/⁻ mice, previously shown to have a reverse learning deficit. Mice were trained in a two-choice visual discrimination task with food reward as positive reinforcement. When mice reached criterion for one visual stimulus (80% correct in three consecutive 10 trial sets they began the reverse learning phase, where the rewarded stimulus was switched to the previously incorrect stimulus. For the initial learning and reverse phase of the task, mice at 90%BW took almost twice as many trials to reach criterion as mice at 80%BW. Furthermore, WT 80 and 90%BW groups significantly differed in percentage correct responses and learning strategy in the reverse learning phase, whereas no differences between weight restriction groups were observed in ephrin-A2⁻/⁻ mice. Most importantly, genotype-specific differences in reverse learning strategy were only detected in the 80%BW groups. Our results indicate that increased food restriction not only results in better performance and a shorter training period, but may also be necessary for revealing behavioural differences between experimental groups. This has important ethical and animal welfare implications when deciding extent of diet restriction in behavioural studies.

  13. A novel perceptual discrimination training task: Reducing fear overgeneralization in the context of fear learning.

    Science.gov (United States)

    Ginat-Frolich, Rivkah; Klein, Zohar; Katz, Omer; Shechner, Tomer

    2017-06-01

    Generalization is an adaptive learning mechanism, but it can be maladaptive when it occurs in excess. A novel perceptual discrimination training task was therefore designed to moderate fear overgeneralization. We hypothesized that improvement in basic perceptual discrimination would translate into lower fear overgeneralization in affective cues. Seventy adults completed a fear-conditioning task prior to being allocated into training or placebo groups. Predesignated geometric shape pairs were constructed for the training task. A target shape from each pair was presented. Thereafter, participants in the training group were shown both shapes and asked to identify the image that differed from the target. Placebo task participants only indicated the location of each shape on the screen. All participants then viewed new geometric pairs and indicated whether they were identical or different. Finally, participants completed a fear generalization test consisting of perceptual morphs ranging from the CS + to the CS-. Fear-conditioning was observed through physiological and behavioural measures. Furthermore, the training group performed better than the placebo group on the assessment task and exhibited decreased fear generalization in response to threat/safety cues. The findings offer evidence for the effectiveness of the novel discrimination training task, setting the stage for future research with clinical populations. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Yoshimasa eSeki

    2013-07-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  16. Accurate classification of brain gliomas by discriminate dictionary learning based on projective dictionary pair learning of proton magnetic resonance spectra.

    Science.gov (United States)

    Adebileje, Sikiru Afolabi; Ghasemi, Keyvan; Aiyelabegan, Hammed Tanimowo; Saligheh Rad, Hamidreza

    2017-04-01

    Proton magnetic resonance spectroscopy is a powerful noninvasive technique that complements the structural images of cMRI, which aids biomedical and clinical researches, by identifying and visualizing the compositions of various metabolites within the tissues of interest. However, accurate classification of proton magnetic resonance spectroscopy is still a challenging issue in clinics due to low signal-to-noise ratio, overlapping peaks of metabolites, and the presence of background macromolecules. This paper evaluates the performance of a discriminate dictionary learning classifiers based on projective dictionary pair learning method for brain gliomas proton magnetic resonance spectroscopy spectra classification task, and the result were compared with the sub-dictionary learning methods. The proton magnetic resonance spectroscopy data contain a total of 150 spectra (74 healthy, 23 grade II, 23 grade III, and 30 grade IV) from two databases. The datasets from both databases were first coupled together, followed by column normalization. The Kennard-Stone algorithm was used to split the datasets into its training and test sets. Performance comparison based on the overall accuracy, sensitivity, specificity, and precision was conducted. Based on the overall accuracy of our classification scheme, the dictionary pair learning method was found to outperform the sub-dictionary learning methods 97.78% compared with 68.89%, respectively. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  17. Does Fine Color Discrimination Learning in Free-Flying Honeybees Change Mushroom-Body Calyx Neuroarchitecture?

    Directory of Open Access Journals (Sweden)

    Frank M J Sommerlandt

    Full Text Available Honeybees learn color information of rewarding flowers and recall these memories in future decisions. For fine color discrimination, bees require differential conditioning with a concurrent presentation of target and distractor stimuli to form a long-term memory. Here we investigated whether the long-term storage of color information shapes the neural network of microglomeruli in the mushroom body calyces and if this depends on the type of conditioning. Free-flying honeybees were individually trained to a pair of perceptually similar colors in either absolute conditioning towards one of the colors or in differential conditioning with both colors. Subsequently, bees of either conditioning groups were tested in non-rewarded discrimination tests with the two colors. Only bees trained with differential conditioning preferred the previously learned color, whereas bees of the absolute conditioning group, and a stimuli-naïve group, chose randomly among color stimuli. All bees were then kept individually for three days in the dark to allow for complete long-term memory formation. Whole-mount immunostaining was subsequently used to quantify variation of microglomeruli number and density in the mushroom-body lip and collar. We found no significant differences among groups in neuropil volumes and total microglomeruli numbers, but learning performance was negatively correlated with microglomeruli density in the absolute conditioning group. Based on these findings we aim to promote future research approaches combining behaviorally relevant color learning tests in honeybees under free-flight conditions with neuroimaging analysis; we also discuss possible limitations of this approach.

  18. Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI.

    Science.gov (United States)

    Chyzhyk, Darya; Graña, Manuel; Öngür, Döst; Shinn, Ann K

    2015-05-01

    Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia, but patients with other neuropsychiatric conditions, and even a small percentage of healthy individuals, may also experience AH. Elucidating the neural mechanisms underlying AH in schizophrenia may offer insight into the pathophysiology associated with AH more broadly across multiple neuropsychiatric disease conditions. In this paper, we address the problem of classifying schizophrenia patients with and without a history of AH, and healthy control (HC) subjects. To this end, we performed feature extraction from resting state functional magnetic resonance imaging (rsfMRI) data and applied machine learning classifiers, testing two kinds of neuroimaging features: (a) functional connectivity (FC) measures computed by lattice auto-associative memories (LAAM), and (b) local activity (LA) measures, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF). We show that it is possible to perform classification within each pair of subject groups with high accuracy. Discrimination between patients with and without lifetime AH was highest, while discrimination between schizophrenia patients and HC participants was worst, suggesting that classification according to the symptom dimension of AH may be more valid than discrimination on the basis of traditional diagnostic categories. FC measures seeded in right Heschl's gyrus (RHG) consistently showed stronger discriminative power than those seeded in left Heschl's gyrus (LHG), a finding that appears to support AH models focusing on right hemisphere abnormalities. The cortical brain localizations derived from the features with strong classification performance are consistent with proposed AH models, and include left inferior frontal gyrus (IFG), parahippocampal gyri, the cingulate cortex, as well as several temporal and prefrontal cortical brain regions. Overall, the observed findings suggest that

  19. Enhanced discriminative fear learning of phobia-irrelevant stimuli in spider-fearful individuals

    Directory of Open Access Journals (Sweden)

    Carina eMosig

    2014-10-01

    Full Text Available Avoidance is considered as a central hallmark of all anxiety disorders. The acquisition and expression of avoidance which leads to the maintenance and exacerbation of pathological fear is closely linked to Pavlovian and operant conditioning processes. Changes in conditionability might represent a key feature of all anxiety disorders but the exact nature of these alterations might vary across different disorders. To date, no information is available on specific changes in conditionability for disorder-irrelevant stimuli in specific phobia (SP. The first aim of this study was to investigate changes in fear acquisition and extinction in spider-fearful individuals as compared to non-fearful participants by using the de novo fear conditioning paradigm. Secondly, we aimed to determine whether differences in the magnitude of context-dependent fear retrieval exist between spider-fearful and non-fearful individuals. Our findings point to an enhanced fear discrimination in spider-fearful individuals as compared to non-fearful individuals at both the physiological and subjective level. The enhanced fear discrimination in spider-fearful individuals was neither mediated by increased state anxiety, depression, nor stress tension. Spider-fearful individuals displayed no changes in extinction learning and/or fear retrieval. Surprisingly, we found no evidence for context-dependent modulation of fear retrieval in either group. Here we provide first evidence that spider-fearful individuals show an enhanced discriminative fear learning of phobia-irrelevant (de novo stimuli. Our findings provide novel insights into the role of fear acquisition and expression for the development and maintenance of maladaptive responses in the course of SP.

  20. Dopamine D2 receptors mediate two-odor discrimination and reversal learning in C57BL/6 mice

    Directory of Open Access Journals (Sweden)

    Grandy David K

    2004-04-01

    Full Text Available Abstract Background Dopamine modulation of neuronal signaling in the frontal cortex, midbrain, and striatum is essential for processing and integrating diverse external sensory stimuli and attaching salience to environmental cues that signal causal relationships, thereby guiding goal-directed, adaptable behaviors. At the cellular level, dopamine signaling is mediated through D1-like or D2-like receptors. Although a role for D1-like receptors in a variety of goal-directed behaviors has been identified, an explicit involvement of D2 receptors has not been clearly established. To determine whether dopamine D2 receptor-mediated signaling contributes to associative and reversal learning, we compared C57Bl/6J mice that completely lack functional dopamine D2 receptors to wild-type mice with respect to their ability to attach appropriate salience to external stimuli (stimulus discrimination and disengage from inappropriate behavioral strategies when reinforcement contingencies change (e.g. reversal learning. Results Mildly food-deprived female wild-type and dopamine D2 receptor deficient mice rapidly learned to retrieve and consume visible food reinforcers from a small plastic dish. Furthermore, both genotypes readily learned to dig through the same dish filled with sterile sand in order to locate a buried food pellet. However, the dopamine D2 receptor deficient mice required significantly more trials than wild-type mice to discriminate between two dishes, each filled with a different scented sand, and to associate one of the two odors with the presence of a reinforcer (food. In addition, the dopamine D2 receptor deficient mice repeatedly fail to alter their response patterns during reversal trials where the reinforcement rules were inverted. Conclusions Inbred C57Bl/6J mice that develop in the complete absence of functional dopamine D2 receptors are capable of olfaction but display an impaired ability to acquire odor-driven reinforcement contingencies

  1. PROCEDURE OF THE INSTITUTION OF HUMAN RIGHTS OMBUDSMAN OF BOSNIA AND HERZEGOVINA IN CASES OF DISCRIMINATION

    Directory of Open Access Journals (Sweden)

    Ljubinko Mitrović

    2017-12-01

    Full Text Available Human Rights Ombudspersons or national institutions for the protection of human rights in most of modern countries today are independent institutions established with the aim of promoting good governance and the rule of law, as well as protection of human rights and fundamental freedoms. Their jurisdiction includes, as a rule, protection and promotion of human rights and freedoms, as well as the functioning of the national preventive mechanisms for the prevention and the prevention of torture and other cruel, inhuman or degrading treatment or punishment. In addition, the powers of these institutions also cover procedures to be applied in cases involving freedom of access to information, and ministerial, governmental and other appointments. An important segment in functioning of the Ombudsman is the prevention or elimination of discrimination. Discrimination (originating from the Latin word discriminare: separate, distinguish, unwarranted discrimination or unequal treatment, or illegal distinction is a negative and socially dangerous phenomenon which in a nutshell means any unequal or different treatment including every exclusion, restriction or preference based on real or assumed grounds against any person or group of persons, and their blood relatives or otherwise related to them, on the basis of their race, color, language, religion, ethnicity, disability, age, national or social origin, political or other opinion, property, membership in a trade union or any other association, education, social status and sex, sexual expression or sexual orientation, and any other circumstance with a purpose or a consequence to disable or endanger recognition, enjoyment or exercise on an equal basis, rights and freedoms in all spheres of life. The methods applied in operation of the national bodies for the protection of equality, primarily the Institution of Human Rights Ombudsman of Bosnia and Herzegovina in discrimination cases are subject of this paper.

  2. Not All Same-Different Discriminations Are Created Equal: Evidence Contrary to a Unidimensional Account of Same-Different Learning

    Science.gov (United States)

    Gibson, Brett M.; Wasserman, Edward A.; Cook, Robert G.

    2006-01-01

    In Experiment 1, we trained four pigeons to concurrently discriminate displays of 16 same icons (16S) from displays of 16 different icons (16D) as well as between displays of same icons (16S) from displays that contained 15 same icons and one different icon (15S:1D). The birds rapidly learned to discriminate 16S vs. 16D displays, but they failed…

  3. PROBABILISTIC PROGRAMMING FOR ADVANCED MACHINE LEARNING (PPAML) DISCRIMINATIVE LEARNING FOR GENERATIVE TASKS (DILIGENT)

    Science.gov (United States)

    2017-11-29

    follows, to see the performance of the SVM Standard algorithm: python mamiStd.py --nJobs 2 --trainSize 80 where nJobs tell the computer to use ...follows: python mamiLupi.py --nJobs 2 --trainSize 80 where nJobs tell the computer to use 2 processors and trainSize tells it to run the...in the course of DARPA PPAML program. 2 INTRODUCTION As explained in Introduction , the focus of our project is to enable the use of discriminative

  4. Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans.

    Science.gov (United States)

    Oddo, Calogero Maria; Raspopovic, Stanisa; Artoni, Fiorenzo; Mazzoni, Alberto; Spigler, Giacomo; Petrini, Francesco; Giambattistelli, Federica; Vecchio, Fabrizio; Miraglia, Francesca; Zollo, Loredana; Di Pino, Giovanni; Camboni, Domenico; Carrozza, Maria Chiara; Guglielmelli, Eugenio; Rossini, Paolo Maria; Faraguna, Ugo; Micera, Silvestro

    2016-03-08

    Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we show that texture discrimination can be artificially provided in human subjects by implementing a neuromorphic real-time mechano-neuro-transduction (MNT), which emulates to some extent the firing dynamics of SA1 cutaneous afferents. The MNT process was used to modulate the temporal pattern of electrical spikes delivered to the human median nerve via percutaneous microstimulation in four intact subjects and via implanted intrafascicular stimulation in one transradial amputee. Both approaches allowed the subjects to reliably discriminate spatial coarseness of surfaces as confirmed also by a hybrid neural model of the median nerve. Moreover, MNT-evoked EEG activity showed physiologically plausible responses that were superimposable in time and topography to the ones elicited by a natural mechanical tactile stimulation. These findings can open up novel opportunities for sensory restoration in the next generation of neuro-prosthetic hands.

  5. 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.

  6. Narrowing down the conditions for extinction of Pavlovian feature-positive discriminations in humans.

    Science.gov (United States)

    van Vooren, Priya R; Franssen, Mathijs; Beckers, Tom; Hermans, Dirk; Baeyens, Frank

    2012-12-01

    The aim of this study was to delineate the minimal conditions for extinction of Pavlovian modulation in humans. Previous experiments at our lab showed that, after X-- A+/A- acquisition training, X- trials did not extinguish differential X-- A+/A- responding, while X-- A- trials did. Additionally, X-- A- extinction training seemed only to extinguish differential X-- A+/A- responding, while leaving differential responding on a concurrently trained Y [Symbol: see text] B+/B- discrimination intact. It thus seemed that the X-- A+/A- discrimination can only be extinguished by X-- A- extinction trials. (Rescorla, Journal of Experimental Psychology: Animal Behavior Processes 12, 16-24, 1986), on the other hand, found that the minimal conditions for extinction were broader in pigeons: Namely, he found that an acquired X-- A+/A- discrimination could be extinguished by presenting the original feature X in combination with a different target (B) that was minimally trained as an exciter. We thus wanted to examine whether this was also the case in humans. We found that nonreinforced X-- B- presentations did not abolish discriminative X-- A/A responding when target B was a nonreinforced stimulus. Nonreinforced X-- B- trials did extinguish the X-- A+/A- discrimination when target B had previously been trained as a target for modulation (X-- B+/B- or Y [Symbol: see text] B+/B- training) or as a reinforced exciter (B+). Our results thusf parallel and extend those in nonhuman animals (Rescorla, Journal of Experimental Psychology: Animal Behavior Processes 12, 16-24, 1986).

  7. Effects of MK-801 on vicarious trial-and-error and reversal of olfactory discrimination learning in weanling rats.

    Science.gov (United States)

    Griesbach, G S; Hu, D; Amsel, A

    1998-12-01

    The effects of dizocilpine maleate (MK-801) on vicarious trial-and-error (VTE), and on simultaneous olfactory discrimination learning and its reversal, were observed in weanling rats. The term VTE was used by Tolman (The determiners of behavior at a choice point. Psychol. Rev. 1938;46:318-336), who described it as conflict-like behavior at a choice-point in simultaneous discrimination learning. It takes the form of head movements from one stimulus to the other, and has recently been proposed by Amsel (Hippocampal function in the rat: cognitive mapping or vicarious trial-and-error? Hippocampus, 1993;3:251-256) as related to hippocampal, nonspatial function during this learning. Weanling male rats received systemic MK-801 either 30 min before the onset of olfactory discrimination training and its reversal, or only before its reversal. The MK-801-treated animals needed significantly more sessions to acquire the discrimination and showed significantly fewer VTEs in the acquisition phase of learning. Impaired reversal learning was shown only when MK-801 was administered during the reversal-learning phase, itself, and not when it was administered throughout both phases.

  8. Development of vicarious trial-and-error behavior in odor discrimination learning in the rat: relation to hippocampal function?

    Science.gov (United States)

    Hu, D; Griesbach, G; Amsel, A

    1997-06-01

    Previous work from our laboratory has suggested that hippocampal electrolytic lesions result in a deficit in simultaneous, black-white discrimination learning and reduce the frequency of vicarious trial-and-error (VTE) at a choice-point. VTE is a term Tolman used to describe the rat's conflict-like behavior, moving its head from one stimulus to the other at a choice point, and has been proposed as a major nonspatial feature of hippocampal function in both visual and olfactory discrimination learning. Simultaneous odor discrimination and VTE behavior were examined at three different ages. The results were that 16-day-old pups made fewer VTEs and learned much more slowly than 30- and 60-day-olds, a finding in accord with levels of hippocampal maturity in the rat.

  9. 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.

  10. Discourses of Roma Anti-Discrimination in Reports on Human Rights Violations

    Directory of Open Access Journals (Sweden)

    Chloë Delcour

    2015-09-01

    Full Text Available In an effort to understand the paradox between the expansion of inclusion projects for the Roma and their persisting exclusion, this article explores human rights practice in order to grasp the complexity of meanings of inclusion negotiated in this practice. In this way, we scrutinize whether there are limiting factors within the inclusionary discourse itself. Specifically, we analyze the discourse in transnational judicial, political and civil society actors’ reports on violations of human rights against Roma. A strong shared tendency to frame the violations in terms of discrimination can be discerned in the reports, demonstrating a dominant concept in the human rights discourse for Roma. However, a framing analysis of the underlying assumptions of this concept shows that not all three actors offer the same solutions for obtaining non-discrimination, which can partly explain the limited impact of the ostensibly strong and inclusive anti-discrimination discourse. In contrast, the actors do share a negative attribution of responsibility to the nation states, but the effectiveness of this shared discursive claim can be questioned. This article illustrates how inclusion discourses are actually quite complex to grasp and so it substantiates the need for greater critical understanding of such discourses in further research.

  11. Training haptic stiffness discrimination: time course of learning with or without visual information and knowledge of results.

    Science.gov (United States)

    Teodorescu, Kinneret; Bouchigny, Sylvain; Korman, Maria

    2013-08-01

    In this study, we explored the time course of haptic stiffness discrimination learning and how it was affected by two experimental factors, the addition of visual information and/or knowledge of results (KR) during training. Stiffness perception may integrate both haptic and visual modalities. However, in many tasks, the visual field is typically occluded, forcing stiffness perception to be dependent exclusively on haptic information. No studies to date addressed the time course of haptic stiffness perceptual learning. Using a virtual environment (VE) haptic interface and a two-alternative forced-choice discrimination task, the haptic stiffness discrimination ability of 48 participants was tested across 2 days. Each day included two haptic test blocks separated by a training block Additional visual information and/or KR were manipulated between participants during training blocks. Practice repetitions alone induced significant improvement in haptic stiffness discrimination. Between days, accuracy was slightly improved, but decision time performance was deteriorated. The addition of visual information and/or KR had only temporary effects on decision time, without affecting the time course of haptic discrimination learning. Learning in haptic stiffness discrimination appears to evolve through at least two distinctive phases: A single training session resulted in both immediate and latent learning. This learning was not affected by the training manipulations inspected. Training skills in VE in spaced sessions can be beneficial for tasks in which haptic perception is critical, such as surgery procedures, when the visual field is occluded. However, training protocols for such tasks should account for low impact of multisensory information and KR.

  12. Sleep Deprivation Impairs the Human Central and Peripheral Nervous System Discrimination of Social Threat.

    Science.gov (United States)

    Goldstein-Piekarski, Andrea N; Greer, Stephanie M; Saletin, Jared M; Walker, Matthew P

    2015-07-15

    Facial expressions represent one of the most salient cues in our environment. They communicate the affective state and intent of an individual and, if interpreted correctly, adaptively influence the behavior of others in return. Processing of such affective stimuli is known to require reciprocal signaling between central viscerosensory brain regions and peripheral-autonomic body systems, culminating in accurate emotion discrimination. Despite emerging links between sleep and affective regulation, the impact of sleep loss on the discrimination of complex social emotions within and between the CNS and PNS remains unknown. Here, we demonstrate in humans that sleep deprivation impairs both viscerosensory brain (anterior insula, anterior cingulate cortex, amygdala) and autonomic-cardiac discrimination of threatening from affiliative facial cues. Moreover, sleep deprivation significantly degrades the normally reciprocal associations between these central and peripheral emotion-signaling systems, most prominent at the level of cardiac-amygdala coupling. In addition, REM sleep physiology across the sleep-rested night significantly predicts the next-day success of emotional discrimination within this viscerosensory network across individuals, suggesting a role for REM sleep in affective brain recalibration. Together, these findings establish that sleep deprivation compromises the faithful signaling of, and the "embodied" reciprocity between, viscerosensory brain and peripheral autonomic body processing of complex social signals. Such impairments hold ecological relevance in professional contexts in which the need for accurate interpretation of social cues is paramount yet insufficient sleep is pervasive. Copyright © 2015 the authors 0270-6474/15/3510135-11$15.00/0.

  13. 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.

  14. Legal Provisions, Discrimination and Uncertainty on LGBT community in Albania. Laws on human rights vs exerted rights of LGBT persons

    Directory of Open Access Journals (Sweden)

    Urjana Curi

    2018-03-01

    On March 13, 2010, the Anti-Discrimination Law, one of the essential legal instruments that protects human rights in Albania, and also includes the prohibition of discrimination on the basis of sexual orientation, came into force. Albania has already the Commissioner for Protection from Discrimination. Two LGBT organizations have already been established in Albania: the Alliance against Discrimination LGBT and LGBT Pro Albania. They aim to protect the rights of sexual minorities in Albania and promote a national movement of social mobilization to protect and promote the rights of this community in Albania

  15. Go/no-go discriminated avoidance learning in prenatally x-irradiated rats

    International Nuclear Information System (INIS)

    Tamaki, Y.; Inouye, M.

    1988-01-01

    Male Fischer344 rats were exposed to x-irradiation at a dose of 200 rad on Day 17 of gestation. Irradiated and control rats were tested at 10-13 weeks of age with the paradigm of go/no-go (active-passive) discriminated avoidance conditioning for three consecutive daily sessions. During the first conditioning session, they learned only active avoidance responses to two different warning signals. During the second and third sessions, they learned active and passive avoidance responses: in response to one warning signal, rats were required to make an active response to avoid a shock, but not to run in response to the other signal in order to avoid a shock. Prenatally irradiated rats made more active avoidance responses to both warning signals than controls (first session). In the early training phase of the go/no-go task, irradiated rats performed significantly higher active and lower passive avoidance responses than controls. Irradiated rats established a strong tendency to respond actively to the no-go signal, but eventually learned to respond to it

  16. Pharmacological evidence that both cognitive memory and habit formation contribute to within-session learning of concurrent visual discriminations.

    Science.gov (United States)

    Turchi, Janita; Devan, Bryan; Yin, Pingbo; Sigrist, Emmalynn; Mishkin, Mortimer

    2010-07-01

    The monkey's ability to learn a set of visual discriminations presented concurrently just once a day on successive days (24-h ITI task) is based on habit formation, which is known to rely on a visuo-striatal circuit and to be independent of visuo-rhinal circuits that support one-trial memory. Consistent with this dissociation, we recently reported that performance on the 24-h ITI task is impaired by a striatal-function blocking agent, the dopaminergic antagonist haloperidol, and not by a rhinal-function blocking agent, the muscarinic cholinergic antagonist scopolamine. In the present study, monkeys were trained on a short-ITI form of concurrent visual discrimination learning, one in which a set of stimulus pairs is repeated not only across daily sessions but also several times within each session (in this case, at about 4-min ITIs). Asymptotic discrimination learning rates in the non-drug condition were reduced by half, from approximately 11 trials/pair on the 24-h ITI task to approximately 5 trials/pair on the 4-min ITI task, and this faster learning was impaired by systemic injections of either haloperidol or scopolamine. The results suggest that in the version of concurrent discrimination learning used here, the short ITIs within a session recruit both visuo-rhinal and visuo-striatal circuits, and that the final performance level is driven by both cognitive memory and habit formation working in concert.

  17. Separate and combined effects of the GABAA positive allosteric modulator diazepam and Δ⁹-THC in humans discriminating Δ⁹-THC.

    Science.gov (United States)

    Lile, Joshua A; Kelly, Thomas H; Hays, Lon R

    2014-10-01

    Our previous research suggested the involvement of γ-aminobutyric acid (GABA), in particular the GABAB receptor subtype, in the interoceptive effects of Δ(9)-tetrahydrocannabinol (Δ(9)-THC). The aim of the present study was to determine the potential involvement of the GABAA receptor subtype by assessing the separate and combined effects of the GABAA positive allosteric modulator diazepam and Δ(9)-THC using pharmacologically selective drug-discrimination procedures. Ten cannabis users learned to discriminate 30 mg oral Δ(9)-THC from placebo and then received diazepam (5 and 10mg), Δ(9)-THC (5, 15 and 30 mg) and placebo, alone and in combination. Self-report, task performance and physiological measures were also collected. Δ(9)-THC functioned as a discriminative stimulus, produced subjective effects typically associated with cannabinoids (e.g., High, Stoned, Like Drug) and elevated heart rate. Diazepam alone impaired performance on psychomotor performance tasks and increased ratings on a limited number of self-report questionnaire items (e.g., Any Effect, Sedated), but did not substitute for the Δ(9)-THC discriminative stimulus or alter the Δ(9)-THC discrimination dose-response function. Similarly, diazepam had limited impact on the other behavioral effects of Δ(9)-THC. These results suggest that the GABAA receptor subtype has minimal involvement in the interoceptive effects of Δ(9)-THC, and by extension cannabis, in humans. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  18. Improved neutron-gamma discrimination for a 3He neutron detector using subspace learning methods

    Science.gov (United States)

    Wang, C. L.; Funk, L. L.; Riedel, R. A.; Berry, K. D.

    2017-05-01

    3He gas based neutron Linear-Position-Sensitive Detectors (LPSDs) have been used for many neutron scattering instruments. Traditional Pulse-height Analysis (PHA) for Neutron-Gamma Discrimination (NGD) resulted in the neutron-gamma efficiency ratio (NGD ratio) on the order of 105-106. The NGD ratios of 3He detectors need to be improved for even better scientific results from neutron scattering. Digital Signal Processing (DSP) analyses of waveforms were proposed for obtaining better NGD ratios, based on features extracted from rise-time, pulse amplitude, charge integration, a simplified Wiener filter, and the cross-correlation between individual and template waveforms of neutron and gamma events. Fisher Linear Discriminant Analysis (FLDA) and three Multivariate Analyses (MVAs) of the features were performed. The NGD ratios are improved by about 102-103 times compared with the traditional PHA method. Our results indicate the NGD capabilities of 3He tube detectors can be significantly improved with subspace-learning based methods, which may result in a reduced data-collection time and better data quality for further data reduction.

  19. Activations of human auditory cortex to phonemic and nonphonemic vowels during discrimination and memory tasks.

    Science.gov (United States)

    Harinen, Kirsi; Rinne, Teemu

    2013-08-15

    We used fMRI to investigate activations within human auditory cortex (AC) to vowels during vowel discrimination, vowel (categorical n-back) memory, and visual tasks. Based on our previous studies, we hypothesized that the vowel discrimination task would be associated with increased activations in the anterior superior temporal gyrus (STG), while the vowel memory task would enhance activations in the posterior STG and inferior parietal lobule (IPL). In particular, we tested the hypothesis that activations in the IPL during vowel memory tasks are associated with categorical processing. Namely, activations due to categorical processing should be higher during tasks performed on nonphonemic (hard to categorize) than on phonemic (easy to categorize) vowels. As expected, we found distinct activation patterns during vowel discrimination and vowel memory tasks. Further, these task-dependent activations were different during tasks performed on phonemic or nonphonemic vowels. However, activations in the IPL associated with the vowel memory task were not stronger during nonphonemic than phonemic vowel blocks. Together these results demonstrate that activations in human AC to vowels depend on both the requirements of the behavioral task and the phonemic status of the vowels. Copyright © 2013 Elsevier Inc. All rights reserved.

  20. Chromatic illumination discrimination ability reveals that human colour constancy is optimised for blue daylight illuminations.

    Directory of Open Access Journals (Sweden)

    Bradley Pearce

    Full Text Available The phenomenon of colour constancy in human visual perception keeps surface colours constant, despite changes in their reflected light due to changing illumination. Although colour constancy has evolved under a constrained subset of illuminations, it is unknown whether its underlying mechanisms, thought to involve multiple components from retina to cortex, are optimised for particular environmental variations. Here we demonstrate a new method for investigating colour constancy using illumination matching in real scenes which, unlike previous methods using surface matching and simulated scenes, allows testing of multiple, real illuminations. We use real scenes consisting of solid familiar or unfamiliar objects against uniform or variegated backgrounds and compare discrimination performance for typical illuminations from the daylight chromaticity locus (approximately blue-yellow and atypical spectra from an orthogonal locus (approximately red-green, at correlated colour temperature 6700 K, all produced in real time by a 10-channel LED illuminator. We find that discrimination of illumination changes is poorer along the daylight locus than the atypical locus, and is poorest particularly for bluer illumination changes, demonstrating conversely that surface colour constancy is best for blue daylight illuminations. Illumination discrimination is also enhanced, and therefore colour constancy diminished, for uniform backgrounds, irrespective of the object type. These results are not explained by statistical properties of the scene signal changes at the retinal level. We conclude that high-level mechanisms of colour constancy are biased for the blue daylight illuminations and variegated backgrounds to which the human visual system has typically been exposed.

  1. Discriminative kernel feature extraction and learning for object recognition and detection

    DEFF Research Database (Denmark)

    Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

    2015-01-01

    Feature extraction and learning is critical for object recognition and detection. By embedding context cue of image attributes into the kernel descriptors, we propose a set of novel kernel descriptors called context kernel descriptors (CKD). The motivation of CKD is to use the spatial consistency...... even in high-dimensional space. In addition, the latent connection between Rényi quadratic entropy and the mapping data in kernel feature space further facilitates us to capture the geometric structure as well as the information about the underlying labels of the CKD using CSQMI. Thus the resulting...... codebook and reduced CKD are discriminative. We report superior performance of our algorithm for object recognition on benchmark datasets like Caltech-101 and CIFAR-10, as well as for detection on a challenging chicken feet dataset....

  2. Statistical and Machine-Learning Classifier Framework to Improve Pulse Shape Discrimination System Design

    Energy Technology Data Exchange (ETDEWEB)

    Wurtz, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kaplan, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-10-28

    Pulse shape discrimination (PSD) is a variety of statistical classifier. Fully-­realized statistical classifiers rely on a comprehensive set of tools for designing, building, and implementing. PSD advances rely on improvements to the implemented algorithm. PSD advances can be improved by using conventional statistical classifier or machine learning methods. This paper provides the reader with a glossary of classifier-­building elements and their functions in a fully-­designed and operational classifier framework that can be used to discover opportunities for improving PSD classifier projects. This paper recommends reporting the PSD classifier’s receiver operating characteristic (ROC) curve and its behavior at a gamma rejection rate (GRR) relevant for realistic applications.

  3. Deep learning in color: towards automated quark/gluon jet discrimination

    International Nuclear Information System (INIS)

    Komiske, Patrick T.; Metodiev, Eric M.; Schwartz, Matthew D.

    2017-01-01

    Artificial intelligence offers the potential to automate challenging data-processing tasks in collider physics. Here, to establish its prospects, we explore to what extent deep learning with convolutional neural networks can discriminate quark and gluon jets better than observables designed by physicists. Our approach builds upon the paradigm that a jet can be treated as an image, with intensity given by the local calorimeter deposits. We supplement this construction by adding color to the images, with red, green and blue intensities given by the transverse momentum in charged particles, transverse momentum in neutral particles, and pixel-level charged particle counts. Overall, the deep networks match or outperform traditional jet variables. We also find that, while various simulations produce different quark and gluon jets, the neural networks are surprisingly insensitive to these differences, similar to traditional observables. This suggests that the networks can extract robust physical information from imperfect simulations.

  4. 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.

  5. A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

    Science.gov (United States)

    Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

    2018-01-01

    Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

  6. A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

    Science.gov (United States)

    2018-01-01

    Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

  7. Selective increase of auditory cortico-striatal coherence during auditory-cued Go/NoGo discrimination learning.

    Directory of Open Access Journals (Sweden)

    Andreas L. Schulz

    2016-01-01

    Full Text Available Goal directed behavior and associated learning processes are tightly linked to neuronal activity in the ventral striatum. Mechanisms that integrate task relevant sensory information into striatal processing during decision making and learning are implicitly assumed in current reinforcementmodels, yet they are still weakly understood. To identify the functional activation of cortico-striatal subpopulations of connections during auditory discrimination learning, we trained Mongolian gerbils in a two-way active avoidance task in a shuttlebox to discriminate between falling and rising frequency modulated tones with identical spectral properties. We assessed functional coupling by analyzing the field-field coherence between the auditory cortex and the ventral striatum of animals performing the task. During the course of training, we observed a selective increase of functionalcoupling during Go-stimulus presentations. These results suggest that the auditory cortex functionally interacts with the ventral striatum during auditory learning and that the strengthening of these functional connections is selectively goal-directed.

  8. Discriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles.

    Science.gov (United States)

    Meyer, Arne F; Diepenbrock, Jan-Philipp; Happel, Max F K; Ohl, Frank W; Anemüller, Jörn

    2014-01-01

    Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and

  9. Discriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles.

    Directory of Open Access Journals (Sweden)

    Arne F Meyer

    Full Text Available Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to

  10. Discriminating Children with Autism from Children with Learning Difficulties with an Adaptation of the Short Sensory Profile

    Science.gov (United States)

    O'Brien, Justin; Tsermentseli, Stella; Cummins, Omar; Happe, Francesca; Heaton, Pamela; Spencer, Janine

    2009-01-01

    In this article, we examine the extent to which children with autism and children with learning difficulties can be discriminated from their responses to different patterns of sensory stimuli. Using an adapted version of the Short Sensory Profile (SSP), sensory processing was compared in 34 children with autism to 33 children with typical…

  11. Explosion Monitoring with Machine Learning: A LSTM Approach to Seismic Event Discrimination

    Science.gov (United States)

    Magana-Zook, S. A.; Ruppert, S. D.

    2017-12-01

    The streams of seismic data that analysts look at to discriminate natural from man- made events will soon grow from gigabytes of data per day to exponentially larger rates. This is an interesting problem as the requirement for real-time answers to questions of non-proliferation will remain the same, and the analyst pool cannot grow as fast as the data volume and velocity will. Machine learning is a tool that can solve the problem of seismic explosion monitoring at scale. Using machine learning, and Long Short-term Memory (LSTM) models in particular, analysts can become more efficient by focusing their attention on signals of interest. From a global dataset of earthquake and explosion events, a model was trained to recognize the different classes of events, given their spectrograms. Optimal recurrent node count and training iterations were found, and cross validation was performed to evaluate model performance. A 10-fold mean accuracy of 96.92% was achieved on a balanced dataset of 30,002 instances. Given that the model is 446.52 MB it can be used to simultaneously characterize all incoming signals by researchers looking at events in isolation on desktop machines, as well as at scale on all of the nodes of a real-time streaming platform. LLNL-ABS-735911

  12. A possible structural correlate of learning performance on a colour discrimination task in the brain of the bumblebee

    Science.gov (United States)

    Li, Li; MaBouDi, HaDi; Egertová, Michaela; Elphick, Maurice R.

    2017-01-01

    Synaptic plasticity is considered to be a basis for learning and memory. However, the relationship between synaptic arrangements and individual differences in learning and memory is poorly understood. Here, we explored how the density of microglomeruli (synaptic complexes) within specific regions of the bumblebee (Bombus terrestris) brain relates to both visual learning and inter-individual differences in learning and memory performance on a visual discrimination task. Using whole-brain immunolabelling, we measured the density of microglomeruli in the collar region (visual association areas) of the mushroom bodies of the bumblebee brain. We found that bumblebees which made fewer errors during training in a visual discrimination task had higher microglomerular density. Similarly, bumblebees that had better retention of the learned colour-reward associations two days after training had higher microglomerular density. Further experiments indicated experience-dependent changes in neural circuitry: learning a colour-reward contingency with 10 colours (but not two colours) does result, and exposure to many different colours may result, in changes to microglomerular density in the collar region of the mushroom bodies. These results reveal the varying roles that visual experience, visual learning and foraging activity have on neural structure. Although our study does not provide a causal link between microglomerular density and performance, the observed positive correlations provide new insights for future studies into how neural structure may relate to inter-individual differences in learning and memory. PMID:28978727

  13. A possible structural correlate of learning performance on a colour discrimination task in the brain of the bumblebee.

    Science.gov (United States)

    Li, Li; MaBouDi, HaDi; Egertová, Michaela; Elphick, Maurice R; Chittka, Lars; Perry, Clint J

    2017-10-11

    Synaptic plasticity is considered to be a basis for learning and memory. However, the relationship between synaptic arrangements and individual differences in learning and memory is poorly understood. Here, we explored how the density of microglomeruli (synaptic complexes) within specific regions of the bumblebee ( Bombus terrestris ) brain relates to both visual learning and inter-individual differences in learning and memory performance on a visual discrimination task. Using whole-brain immunolabelling, we measured the density of microglomeruli in the collar region (visual association areas) of the mushroom bodies of the bumblebee brain. We found that bumblebees which made fewer errors during training in a visual discrimination task had higher microglomerular density. Similarly, bumblebees that had better retention of the learned colour-reward associations two days after training had higher microglomerular density. Further experiments indicated experience-dependent changes in neural circuitry: learning a colour-reward contingency with 10 colours (but not two colours) does result, and exposure to many different colours may result, in changes to microglomerular density in the collar region of the mushroom bodies. These results reveal the varying roles that visual experience, visual learning and foraging activity have on neural structure. Although our study does not provide a causal link between microglomerular density and performance, the observed positive correlations provide new insights for future studies into how neural structure may relate to inter-individual differences in learning and memory. © 2017 The Authors.

  14. Magnetic field discrimination, learning, and memory in the yellow stingray (Urobatis jamaicensis).

    Science.gov (United States)

    Newton, Kyle C; Kajiura, Stephen M

    2017-07-01

    Elasmobranch fishes (sharks, skates, and rays) have been hypothesized to use the geomagnetic field as a cue for orienting and navigating across a wide range of spatial scales. Magnetoreception has been demonstrated in many invertebrate and vertebrate taxa, including elasmobranchs, but this sensory modality and the cognitive abilities of cartilaginous fishes are poorly studied. Wild caught yellow stingrays, Urobatis jamaicensis (N = 8), underwent conditioning to associate a magnetic stimulus with a food reward in order to elicit foraging behaviors. Behavioral conditioning consisted of burying magnets and non-magnetic controls at random locations within a test arena and feeding stingrays as they passed over the hidden magnets. The location of the magnets and controls was changed for each trial, and all confounding sensory cues were eliminated. The stingrays learned to discriminate the magnetic stimuli within a mean of 12.6 ± 0.7 SE training sessions of four trials per session. Memory probes were conducted at intervals between 90 and 180 days post-learning criterion, and six of eight stingrays completed the probes with a ≥75% success rate and minimum latency to complete the task. These results show the fastest rate of learning and longest memory window for any batoid (skate or ray) to date. This study demonstrates that yellow stingrays, and possibly other elasmobranchs, can use a magnetic stimulus as a geographic marker for the location of resources and is an important step toward understanding whether these fishes use geomagnetic cues during spatial navigation tasks in the natural environment.

  15. Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

    Science.gov (United States)

    Fiorini, Rodolfo A.; Dacquino, Gianfranco

    2005-03-01

    GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous

  16. Awake, long-term intranasal insulin treatment does not affect object memory, odor discrimination, or reversal learning in mice.

    Science.gov (United States)

    Bell, Genevieve A; Fadool, Debra Ann

    2017-05-15

    Intranasal insulin delivery is currently being used in clinical trials to test for improvement in human memory and cognition, and in particular, for lessening memory loss attributed to neurodegenerative diseases. Studies have reported the effects of short-term intranasal insulin treatment on various behaviors, but less have examined long-term effects. The olfactory bulb contains the highest density of insulin receptors in conjunction with the highest level of insulin transport within the brain. Previous research from our laboratory has demonstrated that acute insulin intranasal delivery (IND) enhanced both short- and long-term memory as well as increased two-odor discrimination in a two-choice paradigm. Herein, we investigated the behavioral and physiological effects of chronic insulin IND. Adult, male C57BL6/J mice were intranasally treated with 5μg/μl of insulin twice daily for 30 and 60days. Metabolic assessment indicated no change in body weight, caloric intake, or energy expenditure following chronic insulin IND, but an increase in the frequency of meal bouts selectively in the dark cycle. Unlike acute insulin IND, which has been shown to cause enhanced performance in odor habituation/dishabituation and two-odor discrimination tasks in mice, chronic insulin IND did not enhance olfactometry-based odorant discrimination or olfactory reversal learning. In an object memory recognition task, insulin IND-treated mice did not perform differently than controls, regardless of task duration. Biochemical analyses of the olfactory bulb revealed a modest 1.3 fold increase in IR kinase phosphorylation but no significant increase in Kv1.3 phosphorylation. Substrate phosphorylation of IR kinase downstream effectors (MAPK/ERK and Akt signaling) proved to be highly variable. These data indicate that chronic administration of insulin IND in mice fails to enhance olfactory ability, object memory recognition, or a majority of systems physiology metabolic factors - as reported to

  17. 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.

  18. "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…

  19. Discrimination of human and nonhuman blood using Raman spectroscopy with self-reference algorithm

    Science.gov (United States)

    Bian, Haiyi; Wang, Peng; Wang, Jun; Yin, Huancai; Tian, Yubing; Bai, Pengli; Wu, Xiaodong; Wang, Ning; Tang, Yuguo; Gao, Jing

    2017-09-01

    We report a self-reference algorithm to discriminate human and nonhuman blood by calculating the ratios of identification Raman peaks to reference Raman peaks and choosing appropriate threshold values. The influence of using different reference peaks and identification peaks was analyzed in detail. The Raman peak at 1003 cm-1 was proved to be a stable reference peak to avoid the influencing factors, such as the incident laser intensity and the amount of sample. The Raman peak at 1341 cm-1 was found to be an efficient identification peak, which indicates that the difference between human and nonhuman blood results from the C-H bend in tryptophan. The comparison between self-reference algorithm and partial least square method was made. It was found that the self-reference algorithm not only obtained the discrimination results with the same accuracy, but also provided information on the difference of chemical composition. In addition, the performance of self-reference algorithm whose true positive rate is 100% is significant for customs inspection to avoid genetic disclosure and forensic science.

  20. 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

  1. Bioelectronic tongue using heterodimeric human taste receptor for the discrimination of sweeteners with human-like performance.

    Science.gov (United States)

    Song, Hyun Seok; Jin, Hye Jun; Ahn, Sae Ryun; Kim, Daesan; Lee, Sang Hun; Kim, Un-Kyung; Simons, Christopher T; Hong, Seunghun; Park, Tai Hyun

    2014-10-28

    The sense of taste helps humans to obtain information and form a picture of the world by recognizing chemicals in their environments. Over the past decade, large advances have been made in understanding the mechanisms of taste detection and mimicking its capability using artificial sensor devices. However, the detection capability of previous artificial taste sensors has been far inferior to that of animal tongues, in terms of its sensitivity and selectivity. Herein, we developed a bioelectronic tongue using heterodimeric human sweet taste receptors for the detection and discrimination of sweeteners with human-like performance, where single-walled carbon nanotube field-effect transistors were functionalized with nanovesicles containing human sweet taste receptors and used to detect the binding of sweeteners to the taste receptors. The receptors are heterodimeric G-protein-coupled receptors (GPCRs) composed of human taste receptor type 1 member 2 (hTAS1R2) and human taste receptor type 1 member 3 (hTAS1R3), which have multiple binding sites and allow a human tongue-like broad selectivity for the detection of sweeteners. This nanovesicle-based bioelectronic tongue can be a powerful tool for the detection of sweeteners as an alternative to labor-intensive and time-consuming cell-based assays and the sensory evaluation panels used in the food and beverage industry. Furthermore, this study also allows the artificial sensor to exam the functional activity of dimeric GPCRs.

  2. Man's other best friend: domestic cats (F. silvestris catus) and their discrimination of human emotion cues.

    Science.gov (United States)

    Galvan, Moriah; Vonk, Jennifer

    2016-01-01

    The ability of domestic dogs (C. lupus famaliaris) to follow and attend to human emotion expressions is well documented. It is unknown whether domestic cats (F. silvestris catus) possess similar abilities. Because cats belong to the same order (Carnivora), but did not evolve to live in complex social groups, research with them enables us to tease apart the influence of social structure versus domestication processes on the capacity to recognize human communicative cues, such as emotions. Two experiments were conducted to determine the extent to which domestic cats discriminate between human emotion cues. The first experiment presented cats with facial and postural cues of happiness and anger from both an unfamiliar experimenter and their familiar owner in the absence of vocal cues. The second experiment presented cats with vocal cues of human emotion through a positively or negatively charged conversation between an experimenter and owner. Domestic cats were only modestly sensitive to emotion, particularly when displayed by their owner, suggesting that a history of human interaction alone may not be sufficient to shape such abilities in domestic cats.

  3. 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.

  4. 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

  5. Discriminative Structured Dictionary Learning on Grassmann Manifolds and Its Application on Image Restoration.

    Science.gov (United States)

    Pan, Han; Jing, Zhongliang; Qiao, Lingfeng; Li, Minzhe

    2017-09-25

    Image restoration is a difficult and challenging problem in various imaging applications. However, despite of the benefits of a single overcomplete dictionary, there are still several challenges for capturing the geometric structure of image of interest. To more accurately represent the local structures of the underlying signals, we propose a new problem formulation for sparse representation with block-orthogonal constraint. There are three contributions. First, a framework for discriminative structured dictionary learning is proposed, which leads to a smooth manifold structure and quotient search spaces. Second, an alternating minimization scheme is proposed after taking both the cost function and the constraints into account. This is achieved by iteratively alternating between updating the block structure of the dictionary defined on Grassmann manifold and sparsifying the dictionary atoms automatically. Third, Riemannian conjugate gradient is considered to track local subspaces efficiently with a convergence guarantee. Extensive experiments on various datasets demonstrate that the proposed method outperforms the state-of-the-art methods on the removal of mixed Gaussian-impulse noise.

  6. 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.

  7. The spontaneous replication error and the mismatch discrimination mechanisms of human DNA polymerase β

    Science.gov (United States)

    Koag, Myong-Chul; Nam, Kwangho; Lee, Seongmin

    2014-01-01

    To provide molecular-level insights into the spontaneous replication error and the mismatch discrimination mechanisms of human DNA polymerase β (polβ), we report four crystal structures of polβ complexed with dG•dTTP and dA•dCTP mismatches in the presence of Mg2+ or Mn2+. The Mg2+-bound ground-state structures show that the dA•dCTP-Mg2+ complex adopts an ‘intermediate’ protein conformation while the dG•dTTP-Mg2+ complex adopts an open protein conformation. The Mn2+-bound ‘pre-chemistry-state’ structures show that the dA•dCTP-Mn2+ complex is structurally very similar to the dA•dCTP-Mg2+ complex, whereas the dG•dTTP-Mn2+ complex undergoes a large-scale conformational change to adopt a Watson–Crick-like dG•dTTP base pair and a closed protein conformation. These structural differences, together with our molecular dynamics simulation studies, suggest that polβ increases replication fidelity via a two-stage mismatch discrimination mechanism, where one is in the ground state and the other in the closed conformation state. In the closed conformation state, polβ appears to allow only a Watson–Crick-like conformation for purine•pyrimidine base pairs, thereby discriminating the mismatched base pairs based on their ability to form the Watson–Crick-like conformation. Overall, the present studies provide new insights into the spontaneous replication error and the replication fidelity mechanisms of polβ. PMID:25200079

  8. 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.

  9. Learning and Transforming Reality: Women from Rosario's Neighborhoods Demand Access to Public Health Services Free of Discrimination

    Science.gov (United States)

    Chiarotti, Susana

    2005-01-01

    This article focuses on the activities of two women's groups in Argentina -- CLADEM and INSGENAR. CLADEM, which has a much broader presence in Latin America, aims to give a feminist perspective to the construction of real democracies with social justice, free of discrimination and with full exercise of human rights. INSGENAR is a local,…

  10. Global classification of human facial healthy skin using PLS discriminant analysis and clustering analysis.

    Science.gov (United States)

    Guinot, C; Latreille, J; Tenenhaus, M; Malvy, D J

    2001-04-01

    Today's classifications of healthy skin are predominantly based on a very limited number of skin characteristics, such as skin oiliness or susceptibility to sun exposure. The aim of the present analysis was to set up a global classification of healthy facial skin, using mathematical models. This classification is based on clinical, biophysical skin characteristics and self-reported information related to the skin, as well as the results of a theoretical skin classification assessed separately for the frontal and the malar zones of the face. In order to maximize the predictive power of the models with a minimum of variables, the Partial Least Square (PLS) discriminant analysis method was used. The resulting PLS components were subjected to clustering analyses to identify the plausible number of clusters and to group the individuals according to their proximities. Using this approach, four PLS components could be constructed and six clusters were found relevant. So, from the 36 hypothetical combinations of the theoretical skin types classification, we tended to a strengthened six classes proposal. Our data suggest that the association of the PLS discriminant analysis and the clustering methods leads to a valid and simple way to classify healthy human skin and represents a potentially useful tool for cosmetic and dermatological research.

  11. Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques

    OpenAIRE

    Guo, Doudou; Juan, Jiaxiang; Chang, Liying; Zhang, Jingjin; Huang, Danfeng

    2017-01-01

    Plant-based sensing on water stress can provide sensitive and direct reference for precision irrigation system in greenhouse. However, plant information acquisition, interpretation, and systematical application remain insufficient. This study developed a discrimination method for plant root zone water status in greenhouse by integrating phenotyping and machine learning techniques. Pakchoi plants were used and treated by three root zone moisture levels, 40%, 60%, and 80% relative water content...

  12. 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.

  13. Enhanced attentional gain as a mechanism for generalized perceptual learning in human visual cortex.

    Science.gov (United States)

    Byers, Anna; Serences, John T

    2014-09-01

    Learning to better discriminate a specific visual feature (i.e., a specific orientation in a specific region of space) has been associated with plasticity in early visual areas (sensory modulation) and with improvements in the transmission of sensory information from early visual areas to downstream sensorimotor and decision regions (enhanced readout). However, in many real-world scenarios that require perceptual expertise, observers need to efficiently process numerous exemplars from a broad stimulus class as opposed to just a single stimulus feature. Some previous data suggest that perceptual learning leads to highly specific neural modulations that support the discrimination of specific trained features. However, the extent to which perceptual learning acts to improve the discriminability of a broad class of stimuli via the modulation of sensory responses in human visual cortex remains largely unknown. Here, we used functional MRI and a multivariate analysis method to reconstruct orientation-selective response profiles based on activation patterns in the early visual cortex before and after subjects learned to discriminate small offsets in a set of grating stimuli that were rendered in one of nine possible orientations. Behavioral performance improved across 10 training sessions, and there was a training-related increase in the amplitude of orientation-selective response profiles in V1, V2, and V3 when orientation was task relevant compared with when it was task irrelevant. These results suggest that generalized perceptual learning can lead to modified responses in the early visual cortex in a manner that is suitable for supporting improved discriminability of stimuli drawn from a large set of exemplars. Copyright © 2014 the American Physiological Society.

  14. 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 ...

  15. Wavelet transform and real-time learning method for myoelectric signal in motion discrimination

    International Nuclear Information System (INIS)

    Liu Haihua; Chen Xinhao; Chen Yaguang

    2005-01-01

    This paper discusses the applicability of the Wavelet transform for analyzing an EMG signal and discriminating motion classes. In many previous works, researchers have dealt with steady EMG and have proposed suitable analyzing methods for the EMG, for example FFT and STFT. Therefore, it is difficult for the previous approaches to discriminate motions from the EMG in the different phases of muscle activity, i.e., pre-activity, in activity, postactivity phases, as well as the period of motion transition from one to another. In this paper, we introduce the Wavelet transform using the Coiflet mother wavelet into our real-time EMG prosthetic hand controller for discriminating motions from steady and unsteady EMG. A preliminary experiment to discriminate three hand motions from four channel EMG in the initial pre-activity and in activity phase is carried out to show the effectiveness of the approach. However, future research efforts are necessary to discriminate more motions much precisely

  16. Transfer of perceptual learning of depth discrimination between local and global stereograms.

    Science.gov (United States)

    Gantz, Liat; Bedell, Harold E

    2010-08-23

    Several previous studies reported differences when stereothresholds are assessed with local-contour stereograms vs. complex random-dot stereograms (RDSs). Dissimilar thresholds may be due to differences in the properties of the stereograms (e.g. spatial frequency content, contrast, inter-element separation, area) or to different underlying processing mechanisms. This study examined the transfer of perceptual learning of depth discrimination between local and global RDSs with similar properties, and vice versa. If global and local stereograms are processed by separate neural mechanisms, then the magnitude and rate of training for the two types of stimuli are likely to differ, and the transfer of training from one stimulus type to the other should be minimal. Based on previous results, we chose RDSs with element densities of 0.17% and 28.3% to serve as the local and global stereograms, respectively. Fourteen inexperienced subjects with normal binocular vision were randomly assigned to either a local- or global- RDS training group. Stereothresholds for both stimulus types were measured before and after 7700 training trials distributed over 10 sessions. Stereothresholds for the trained condition improve for approximately 3000 trials, by an average of 0.36+/-0.08 for local and 0.29+/-0.10 for global RDSs, and level off thereafter. Neither the rate nor the magnitude of improvement differ statistically between the local- and global-training groups. Further, no significant difference exists in the amount of improvement on the trained vs. the untrained targets for either training group. These results are consistent with the operation of a single mechanism to process both local and global stereograms. Copyright 2010 Elsevier Ltd. All rights reserved.

  17. 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...

  18. Kennard-Stone combined with least square support vector machine method for noncontact discriminating human blood species

    Science.gov (United States)

    Zhang, Linna; Li, Gang; Sun, Meixiu; Li, Hongxiao; Wang, Zhennan; Li, Yingxin; Lin, Ling

    2017-11-01

    Identifying whole bloods to be either human or nonhuman is an important responsibility for import-export ports and inspection and quarantine departments. Analytical methods and DNA testing methods are usually destructive. Previous studies demonstrated that visible diffuse reflectance spectroscopy method can realize noncontact human and nonhuman blood discrimination. An appropriate method for calibration set selection was very important for a robust quantitative model. In this paper, Random Selection (RS) method and Kennard-Stone (KS) method was applied in selecting samples for calibration set. Moreover, proper stoichiometry method can be greatly beneficial for improving the performance of classification model or quantification model. Partial Least Square Discrimination Analysis (PLSDA) method was commonly used in identification of blood species with spectroscopy methods. Least Square Support Vector Machine (LSSVM) was proved to be perfect for discrimination analysis. In this research, PLSDA method and LSSVM method was used for human blood discrimination. Compared with the results of PLSDA method, this method could enhance the performance of identified models. The overall results convinced that LSSVM method was more feasible for identifying human and animal blood species, and sufficiently demonstrated LSSVM method was a reliable and robust method for human blood identification, and can be more effective and accurate.

  19. Kosovo – UNMIK accountability: Human Rights Advisory Panel Finds Discrimination in Privatization Cases

    Directory of Open Access Journals (Sweden)

    Wolfgang Benedek

    2015-10-01

    Full Text Available ENGLISH: The Human Rights Advisory Panel (HRAP established in 2006 to strengthen the accountability of UNMIK in Kosovo so far has dealt mainly with cases regarding property and missing persons. In two recent cases of members of the Egyptian and the Serbian minority (Fillim Guga and Nevenka Ristić it also dealt with privatization of socially - owned enterprises and found discrimination on ethnic grounds by the Special Chamber of the Supreme Court, established by UNMIK for such cases, which raises the accountability of UNMIK. In doing so the panel applied Article 14 of the ECHR on prohibition of discrimination in conjunction with Article 6 ECHR on fair trial in the light of relevant jurisprudence of the European Court of Human Rights. It also pointed out that in these cases the Special Chamber did not recognize a prima facie case of indirect discrimination and did not apply the principle of reversal of proof as required by the Anti - Discrimination Law of Kosovo. On behalf of UNMIK, the Special Representative of the Secretary - General defended the findings of the Special Chamber. The conclusions and recommendations in the Opinion of the Panel hold UNMIK accountable for the violations found and require it to take immediate and effective measures including an apology and adequate compensation for non-pecuniary damage as well as urging EULEX and other competent authorities in Kosovo to reopen the case by the Special Chamber. The work of the HRAP raises wider issues of accountability of international missions like UNMIK, to which it makes an important contribution. DEUTSCH: Das menschenrechtliche Beratungspanel, welches 2006 ins Leben gerufen wurde, um die Verantwortlichkeit von UNMIK im Kosovo zu stärken, hat sich bisher hauptsächlich mit Fällen zum Eigentumsrecht und hinsichtlich verschwundener Personen beschäftigt. In zwei aktuellen Fällen, die Mitglieder der ägyptischen bzw. serbischen Minderheit betrafen (Fillim Guga und Nevenka Risti

  20. Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

    Science.gov (United States)

    Bae, Seung-Hwan; Yoon, Kuk-Jin

    2018-03-01

    Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

  1. Gendered-Caste Discrimination, Human Rights Education, and the Enforcement of the Prevention of Atrocities Act in India

    Science.gov (United States)

    Kapoor, Dip

    2007-01-01

    Despite the constitutional ban on the practice of untouchability and caste-based discrimination, this article elaborates on a gendered-caste-based discriminatory reality in rural India, the difficulties of enforcing legal remedies, and on related human rights praxis to address gendered-caste atrocities by drawing on the experiences of a Canadian…

  2. Dimensional feature weighting utilizing multiple kernel learning for single-channel talker location discrimination using the acoustic transfer function.

    Science.gov (United States)

    Takashima, Ryoichi; Takiguchi, Tetsuya; Ariki, Yasuo

    2013-02-01

    This paper presents a method for discriminating the location of the sound source (talker) using only a single microphone. In a previous work, the single-channel approach for discriminating the location of the sound source was discussed, where the acoustic transfer function from a user's position is estimated by using a hidden Markov model of clean speech in the cepstral domain. In this paper, each cepstral dimension of the acoustic transfer function is newly weighted, in order to obtain the cepstral dimensions having information that is useful for classifying the user's position. Then, this paper proposes a feature-weighting method for the cepstral parameter using multiple kernel learning, defining the base kernels for each cepstral dimension of the acoustic transfer function. The user's position is trained and classified by support vector machine. The effectiveness of this method has been confirmed by sound source (talker) localization experiments performed in different room environments.

  3. GENDER DISCRIMINATION AND THE EFFECTS ON WOMEN HUMAN RESOURCES MANAGERS CAREERS

    OpenAIRE

    BULUT, Dilvin; KIZILDAĞ, Duygu

    2017-01-01

    Working women have been faced obstacles based on gender discrimination in Turkey and inthe world at the point of career development,. Women have been exposed to gender-based obstaclesinstead of evaluating objectively with their success and competence as an employee. In this study,gender discrimination problems faced by women in their business life are evaluated. The purpose of  this study, a research was conducted to determine the effect of gender discrimination on the careers ofwomen manager...

  4. 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/

  5. 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.

  6. 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.

  7. 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.

  8. Handling conditional discrimination

    NARCIS (Netherlands)

    Zliobaite, I.; Kamiran, F.; Calders, T.G.K.

    2011-01-01

    Historical data used for supervised learning may contain discrimination. We study how to train classifiers on such data, so that they are discrimination free with respect to a given sensitive attribute, e.g., gender. Existing techniques that deal with this problem aim at removing all discrimination

  9. Label-Driven Learning Framework: Towards More Accurate Bayesian Network Classifiers through Discrimination of High-Confidence Labels

    Directory of Open Access Journals (Sweden)

    Yi Sun

    2017-12-01

    Full Text Available Bayesian network classifiers (BNCs have demonstrated competitive classification accuracy in a variety of real-world applications. However, it is error-prone for BNCs to discriminate among high-confidence labels. To address this issue, we propose the label-driven learning framework, which incorporates instance-based learning and ensemble learning. For each testing instance, high-confidence labels are first selected by a generalist classifier, e.g., the tree-augmented naive Bayes (TAN classifier. Then, by focusing on these labels, conditional mutual information is redefined to more precisely measure mutual dependence between attributes, thus leading to a refined generalist with a more reasonable network structure. To enable finer discrimination, an expert classifier is tailored for each high-confidence label. Finally, the predictions of the refined generalist and the experts are aggregated. We extend TAN to LTAN (Label-driven TAN by applying the proposed framework. Extensive experimental results demonstrate that LTAN delivers superior classification accuracy to not only several state-of-the-art single-structure BNCs but also some established ensemble BNCs at the expense of reasonable computation overhead.

  10. 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.

  11. Derivation of Human Chromatic Discrimination Ability from an Information-Theoretical Notion of Distance in Color Space.

    Science.gov (United States)

    da Fonseca, María; Samengo, Inés

    2016-12-01

    The accuracy with which humans detect chromatic differences varies throughout color space. For example, we are far more precise when discriminating two similar orange stimuli than two similar green stimuli. In order for two colors to be perceived as different, the neurons representing chromatic information must respond differently, and the difference must be larger than the trial-to-trial variability of the response to each separate color. Photoreceptors constitute the first stage in the processing of color information; many more stages are required before humans can consciously report whether two stimuli are perceived as chromatically distinguishable. Therefore, although photoreceptor absorption curves are expected to influence the accuracy of conscious discriminability, there is no reason to believe that they should suffice to explain it. Here we develop information-theoretical tools based on the Fisher metric that demonstrate that photoreceptor absorption properties explain about 87% of the variance of human color discrimination ability, as tested by previous behavioral experiments. In the context of this theory, the bottleneck in chromatic information processing is determined by photoreceptor absorption characteristics. Subsequent encoding stages modify only marginally the chromatic discriminability at the photoreceptor level.

  12. Effects of early postnatal X-irradiation of the hippocampus on discrimination learning in adult rats

    International Nuclear Information System (INIS)

    Gazzara, R.A.

    1980-01-01

    Rats with x-irradiation-produced degranulation of the hippocampal dentate gyrus were trained in the acquisition and reversal of simultaneous visual and tactile discriminations in a T-maze. These experiments employed the same treatment, apparatus, and procedure, but varied in task difficulty. In the brightness and roughness discriminations, the irradiated rats were not handicapped in acquiring or reversing discriminations of low or low-moderate task-difficulty. However, these rats were handicapped in acquiring and reversing discriminations of moderate and high task-difficulty. In a Black/White discrimination, in which the stimuli were restricted to the goal-arm walls, the irradiated rats were handicapped in the acquisition (low task-difficulty) and reversal (moderate task-difficulty) phases of the task. These results suggest that the irradiated rats were not handicapped when the noticeability of the stimuli was high, irrespective of modality used, but were handicapped when the noticeability of the stimuli was low. In addition, these results are consistent with the hypothesis that hippocampal-damaged rats are inattentive due to hyperactivity

  13. Early postnatal x-irradiation of the hippocampus and discrimination learning in adult rats

    International Nuclear Information System (INIS)

    Gazzara, R.A.; Altman, J.

    1981-01-01

    Rats with X-irradiation-produced degranulation of the hippocampal dentate gyrus were trained in the acquisition and reversal of simultaneous visual and tactile discriminations in a T-maze. These experiments employed the same treatment, apparatus, and procedure but varied in task difficulty. In the brightness and roughness discriminations, the irradiated rats were not handicapped in acquiring or reversing discriminations of low or low-moderate task difficulty. However, these rats were handicapped in acquiring and reversing discriminations of moderate and high task difficulty. In a Black/White discrimination, in which the stimuli were restricted to the goal-arm walls, the irradiated rats were handicapped in the acquisition (low task difficulty) and reversal (moderate task difficulty) phases of the task. These results suggest that the irradiated rats were not handicapped when the noticeability of the stimuli was high, irrespective of modality used, but were handicapped when the noticeability of the stimuli was low. In addition, these results are consistent with the hypothesis that rats with hippocampal damage are inattentive due to hyperactivity

  14. Testing odorant-receptor interaction theories in humans through discrimination of isotopomers

    Directory of Open Access Journals (Sweden)

    Mara Andrione

    2017-12-01

    Full Text Available Odour reception takes place on the olfactory receptor neuron membrane, where molecular receptors interact with volatile odorant molecules. This interaction is classically thought to rely on chemical and structural features of the odorant, e.g. size, shape, functional groups. However, this model does not allow formulating a correct prediction for the smell of an odorant, suggesting that other molecular properties may play a role in the odour transduction process. An alternative model of olfaction maintains that odorant receptors can probe not only the structural and chemical features, but also the molecular vibration spectrum of the odorants. This constitutes the so-called vibration model of olfaction. According to this model, two isotopomers of the same molecule, i.e. two forms of the same molecule, one unaltered and one in which one or more hydrogen atoms are substituted with deuterium – which are therefore structurally and chemically identical, but with different molecular vibration spectra – would interact differently with an olfactory receptor, producing different olfactory perceptions in the brain. Here, we report on a duo-trio discrimination experiment conducted on human subjects, testing isotopomer pairs that have recently been shown to be differentially encoded in the honeybee brain.

  15. Optical redox imaging indices discriminate human breast cancer from normal tissues

    Science.gov (United States)

    Xu, He N.; Tchou, Julia; Feng, Min; Zhao, Huaqing; Li, Lin Z.

    2016-01-01

    Abstract. Our long-term goal was to investigate the potential of incorporating redox imaging technique as a breast cancer (BC) diagnosis component to increase the positive predictive value of suspicious imaging finding and to reduce unnecessary biopsies and overdiagnosis. We previously found that precancer and cancer tissues in animal models displayed abnormal mitochondrial redox state. We also revealed abnormal mitochondrial redox state in cancerous specimens from three BC patients. Here, we extend our study to include biopsies of 16 patients. Tissue aliquots were collected from both apparently normal and cancerous tissues from the affected cancer-bearing breasts shortly after surgical resection. All specimens were snap-frozen and scanned with the Chance redox scanner, i.e., the three-dimensional cryogenic NADH/Fp (reduced nicotinamide adenine dinucleotide/oxidized flavoproteins) fluorescence imager. We found both Fp and NADH in the cancerous tissues roughly tripled that in the normal tissues (predox ratio Fp/(NADH + Fp) was ∼27% higher in the cancerous tissues (predox ratio alone could predict cancer with reasonable sensitivity and specificity. Our findings suggest that the optical redox imaging technique can provide parameters independent of clinical factors for discriminating cancer from noncancer breast tissues in human patients. PMID:27896360

  16. Dissociable contributions of the orbitofrontal and infralimbic cortex to pavlovian autoshaping and discrimination reversal learning: further evidence for the functional heterogeneity of the rodent frontal cortex.

    Science.gov (United States)

    Chudasama, Y; Robbins, Trevor W

    2003-09-24

    To examine possible heterogeneity of function within the ventral regions of the rodent frontal cortex, the present study compared the effects of excitotoxic lesions of the orbitofrontal cortex (OFC) and the infralimbic cortex (ILC) on pavlovian autoshaping and discrimination reversal learning. During the pavlovian autoshaping task, in which rats learn to approach a stimulus predictive of reward [conditional stimulus (CS+)], only the OFC group failed to acquire discriminated approach but was unimpaired when preoperatively trained. In the visual discrimination learning and reversal task, rats were initially required to discriminate a stimulus positively associated with reward. There was no effect of either OFC or ILC lesions on discrimination learning. When the stimulus-reward contingencies were reversed, both groups of animals committed more errors, but only the OFC-lesioned animals were unable to suppress the previously rewarded stimulus-reward association, committing more "stimulus perseverative" errors. In contrast, the ILC group showed a pattern of errors that was more attributable to "learning" than perseveration. These findings suggest two types of dissociation between the effects of OFC and ILC lesions: (1) OFC lesions impaired the learning processes implicated in pavlovian autoshaping but not instrumental simultaneous discrimination learning, whereas ILC lesions were unimpaired at autoshaping and their reversal learning deficit did not reflect perseveration, and (2) OFC lesions induced perseverative responding in reversal learning but did not disinhibit responses to pavlovian CS-. In contrast, the ILC lesion had no effect on response inhibitory control in either of these settings. The findings are discussed in the context of dissociable executive functions in ventral sectors of the rat prefrontal cortex.

  17. Sex differences in audiovisual discrimination learning by Bengalese finches (Lonchura striata var. domestica).

    Science.gov (United States)

    Seki, Yoshimasa; Okanoya, Kazuo

    2008-02-01

    Both visual and auditory information are important for songbirds, especially in developmental and sexual contexts. To investigate bimodal cognition in songbirds, the authors conducted audiovisual discrimination training in Bengalese finches. The authors used two types of stimulus: an "artificial stimulus," which is a combination of simple figures and sound, and a "biological stimulus," consisting of video images of singing males along with their songs. The authors found that while both sexes predominantly used visual cues in the discrimination tasks, males tended to be more dependent on auditory information for the biological stimulus. Female responses were always dependent on the visual stimulus for both stimulus types. Only males changed their discrimination strategy according to stimulus type. Although males used both visual and auditory cues for the biological stimulus, they responded to the artificial stimulus depending only on visual information, as the females did. These findings suggest a sex difference in innate auditory sensitivity. (c) 2008 APA.

  18. Very deep learning for ship discrimination in synthetic aperture radar imagery

    CSIR Research Space (South Africa)

    Schwegmann, Colin P

    2016-07-01

    Full Text Available using machine learning. Newer, advanced deep learning techniques offer a unique solution but traditionally require a large dataset to train effectively. Highway Networks allow for very deep networks that can be trained using the smaller datasets typical...

  19. Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning

    Directory of Open Access Journals (Sweden)

    Yuan Xu

    2015-01-01

    Full Text Available Very high resolution (VHR image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened, while they ignore the change pattern description (i.e., how the changes changed, which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique.

  20. An unsupervised learning algorithm: application to the discrimination of seismic events and quarry blasts in the vicinity of Istanbul

    Directory of Open Access Journals (Sweden)

    H. S. Kuyuk

    2011-01-01

    Full Text Available The results of the application of an unsupervised learning (neural network approach comprising a Self Organizing Map (SOM, to distinguish micro-earthquakes from quarry blasts in the vicinity of Istanbul, Turkey, are presented and discussed. The SOM is constructed as a neural classifier and complementary reliability estimator to distinguish seismic events, and was employed for varying map sizes. Input parameters consisting of frequency and time domain data (complexity, spectral ratio, S/P wave amplitude peak ratio and origin time of events extracted from the vertical components of digital seismograms were estimated as discriminants for 179 (1.8 < Md < 3.0 local events. The results show that complexity and amplitude peak ratio parameters of the observed velocity seismogram may suffice for a reliable discrimination, while origin time and spectral ratio were found to be fuzzy and misleading classifiers for this problem. The SOM discussed here achieved a discrimination reliability that could be employed routinely in observatory practice; however, about 6% of all events were classified as ambiguous cases. This approach was developed independently for this particular classification, but it could be applied to different earthquake regions.

  1. Double Dissociation of Pharmacologically Induced Deficits in Visual Recognition and Visual Discrimination Learning

    Science.gov (United States)

    Turchi, Janita; Buffalari, Deanne; Mishkin, Mortimer

    2008-01-01

    Monkeys trained in either one-trial recognition at 8- to 10-min delays or multi-trial discrimination habits with 24-h intertrial intervals received systemic cholinergic and dopaminergic antagonists, scopolamine and haloperidol, respectively, in separate sessions. Recognition memory was impaired markedly by scopolamine but not at all by…

  2. Gender and the right to non-discrimination in international human rights law

    OpenAIRE

    Netkova, Bistra

    2016-01-01

    Discrimination against women based on the fact that they are women is a deeply rooted practice in all societies. However, the level of discrimination varies greatly with the level of development of the given society and strongly influences and vice versa it is influenced by the status of women in a given society. Addressing this gender-based discrimination is a difficult task because it is closely linked to the concept of equality, and state’s action and inactions. The article establishes tha...

  3. 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.

  4. Development and assessment of a lysophospholipid-based deep learning model to discriminate geographical origins of white rice.

    Science.gov (United States)

    Long, Nguyen Phuoc; Lim, Dong Kyu; Mo, Changyeun; Kim, Giyoung; Kwon, Sung Won

    2017-08-17

    Geographical origin determination of white rice has become the major issue of food industry. However, there is still lack of a high-throughput method for rapidly and reproducibly differentiating the geographical origins of commercial white rice. In this study, we developed a method that employed lipidomics and deep learning to discriminate white rice from Korea to China. A total of 126 white rice of 30 cultivars from different regions were utilized for the method development and validation. By using direct infusion-mass spectrometry-based targeted lipidomics, 17 lysoglycerophospholipids were simultaneously characterized within minutes per sample. Unsupervised data exploration showed a noticeable overlap of white rice between two countries. In addition, lysophosphatidylcholines (lysoPCs) were prominent in white rice from Korea while lysophosphatidylethanolamines (lysoPEs) were enriched in white rice from China. A deep learning prediction model was built using 2014 white rice and validated using two different batches of 2015 white rice. The model accurately discriminated white rice from two countries. Among 10 selected predictors, lysoPC(18:2), lysoPC(14:0), and lysoPE(16:0) were the three most important features. Random forest and gradient boosting machine models also worked well in this circumstance. In conclusion, this study provides an architecture for high-throughput classification of white rice from different geographical origins.

  5. Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques.

    Science.gov (United States)

    Guo, Doudou; Juan, Jiaxiang; Chang, Liying; Zhang, Jingjin; Huang, Danfeng

    2017-08-15

    Plant-based sensing on water stress can provide sensitive and direct reference for precision irrigation system in greenhouse. However, plant information acquisition, interpretation, and systematical application remain insufficient. This study developed a discrimination method for plant root zone water status in greenhouse by integrating phenotyping and machine learning techniques. Pakchoi plants were used and treated by three root zone moisture levels, 40%, 60%, and 80% relative water content. Three classification models, Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM) were developed and validated in different scenarios with overall accuracy over 90% for all. SVM model had the highest value, but it required the longest training time. All models had accuracy over 85% in all scenarios, and more stable performance was observed in RF model. Simplified SVM model developed by the top five most contributing traits had the largest accuracy reduction as 29.5%, while simplified RF and NN model still maintained approximately 80%. For real case application, factors such as operation cost, precision requirement, and system reaction time should be synthetically considered in model selection. Our work shows it is promising to discriminate plant root zone water status by implementing phenotyping and machine learning techniques for precision irrigation management.

  6. SAR Target Recognition via Supervised Discriminative Dictionary Learning and Sparse Representation of the SAR-HOG Feature

    Directory of Open Access Journals (Sweden)

    Shengli Song

    2016-08-01

    Full Text Available Automatic target recognition (ATR in synthetic aperture radar (SAR images plays an important role in both national defense and civil applications. Although many methods have been proposed, SAR ATR is still very challenging due to the complex application environment. Feature extraction and classification are key points in SAR ATR. In this paper, we first design a novel feature, which is a histogram of oriented gradients (HOG-like feature for SAR ATR (called SAR-HOG. Then, we propose a supervised discriminative dictionary learning (SDDL method to learn a discriminative dictionary for SAR ATR and propose a strategy to simplify the optimization problem. Finally, we propose a SAR ATR classifier based on SDDL and sparse representation (called SDDLSR, in which both the reconstruction error and the classification error are considered. Extensive experiments are performed on the MSTAR database under standard operating conditions and extended operating conditions. The experimental results show that SAR-HOG can reliably capture the structures of targets in SAR images, and SDDL can further capture subtle differences among the different classes. By virtue of the SAR-HOG feature and SDDLSR, the proposed method achieves the state-of-the-art performance on MSTAR database. Especially for the extended operating conditions (EOC scenario “Training 17 ∘ —Testing 45 ∘ ”, the proposed method improves remarkably with respect to the previous works.

  7. Age and education adjusted normative data and discriminative validity for Rey's Auditory Verbal Learning Test in the elderly Greek population.

    Science.gov (United States)

    Messinis, Lambros; Nasios, Grigorios; Mougias, Antonios; Politis, Antonis; Zampakis, Petros; Tsiamaki, Eirini; Malefaki, Sonia; Gourzis, Phillipos; Papathanasopoulos, Panagiotis

    2016-01-01

    Rey's Auditory Verbal Learning Test (RAVLT) is a widely used neuropsychological test to assess episodic memory. In the present study we sought to establish normative and discriminative validity data for the RAVLT in the elderly population using previously adapted learning lists for the Greek adult population. We administered the test to 258 cognitively healthy elderly participants, aged 60-89 years, and two patient groups (192 with amnestic mild cognitive impairment, aMCI, and 65 with Alzheimer's disease, AD). From the statistical analyses, we found that age and education contributed significantly to most trials of the RAVLT, whereas the influence of gender was not significant. Younger elderly participants with higher education outperformed the older elderly with lower education levels. Moreover, both clinical groups performed significantly worse on most RAVLT trials and composite measures than matched cognitively healthy controls. Furthermore, the AD group performed more poorly than the aMCI group on most RAVLT variables. Receiver operating characteristic (ROC) analysis was used to examine the utility of the RAVLT trials to discriminate cognitively healthy controls from aMCI and AD patients. Area under the curve (AUC), an index of effect size, showed that most of the RAVLT measures (individual and composite) included in this study adequately differentiated between the performance of healthy elders and aMCI/AD patients. We also provide cutoff scores in discriminating cognitively healthy controls from aMCI and AD patients, based on the sensitivity and specificity of the prescribed scores. Moreover, we present age- and education-specific normative data for individual and composite scores for the Greek adapted RAVLT in elderly subjects aged between 60 and 89 years for use in clinical and research settings.

  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. Modification method to reduce the impact of blood vessel on noncontact discrimination of human blood based on ;M+N; theory

    Science.gov (United States)

    Zhang, Linna; Ding, Hongyan; Lin, Ling; Wang, Yimin; Guo, Xin

    2018-01-01

    Noncontact discriminating human blood is significantly crucial for import-export ports and inspection and quarantine departments. We had already demonstrated that visible diffuse reflectance spectroscopy combining PLS-DA method can successfully realize noncontact human blood discrimination. However, the circulated blood vessels may be produced with different materials. The use of various kinds of blood tubes may have a negative effect on the discrimination, based on ;M+N; theory (Li et al., 2016). In this research, we explored the impact of different material of blood vessels, such as glass tube and plastic tube, on the prediction ability of the discrimination model. Furthermore, we searched for the modification method to reduce the influence from the blood tubes. Our work indicated that generalized diffuse reflectance method can greatly improve the discrimination accuracy. This research can greatly facilitate the application of noncontact discrimination method based on visible and near-infrared diffuse reflectance spectroscopy.

  10. 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.

  11. Beyond human capital explanations for the gender pay gap among executives: investigating board embeddedness effects on discrimination

    OpenAIRE

    Oehmichen, Jana; Sarry, Maximilian A.; Wolff, Michael

    2014-01-01

    This paper examines the gender pay gap in top management teams and how it is affected by directors’ embeddedness. We can reconfirm the result of previous studies that differences in managerial compensation between women and men exist, even after controlling for company properties and human capital attributes. Drawing on the language theory of discrimination, we then question how the embeddedness of directors—the actual deciders on executive compensation levels— affects the p...

  12. Pigeons can discriminate "good" and "bad" paintings by children.

    Science.gov (United States)

    Watanabe, Shigeru

    2010-01-01

    Humans have the unique ability to create art, but non-human animals may be able to discriminate "good" art from "bad" art. In this study, I investigated whether pigeons could be trained to discriminate between paintings that had been judged by humans as either "bad" or "good". To do this, adult human observers first classified several children's paintings as either "good" (beautiful) or "bad" (ugly). Using operant conditioning procedures, pigeons were then reinforced for pecking at "good" paintings. After the pigeons learned the discrimination task, they were presented with novel pictures of both "good" and "bad" children's paintings to test whether they had successfully learned to discriminate between these two stimulus categories. The results showed that pigeons could discriminate novel "good" and "bad" paintings. Then, to determine which cues the subjects used for the discrimination, I conducted tests of the stimuli when the paintings were of reduced size or grayscale. In addition, I tested their ability to discriminate when the painting stimuli were mosaic and partial occluded. The pigeons maintained discrimination performance when the paintings were reduced in size. However, discrimination performance decreased when stimuli were presented as grayscale images or when a mosaic effect was applied to the original stimuli in order to disrupt spatial frequency. Thus, the pigeons used both color and pattern cues for their discrimination. The partial occlusion did not disrupt the discriminative behavior suggesting that the pigeons did not attend to particular parts, namely upper, lower, left or right half, of the paintings. These results suggest that the pigeons are capable of learning the concept of a stimulus class that humans name "good" pictures. The second experiment showed that pigeons learned to discriminate watercolor paintings from pastel paintings. The subjects showed generalization to novel paintings. Then, as the first experiment, size reduction test

  13. Trial-dependent psychometric functions accounting for perceptual learning in 2-AFC discrimination tasks.

    Science.gov (United States)

    Kattner, Florian; Cochrane, Aaron; Green, C Shawn

    2017-09-01

    The majority of theoretical models of learning consider learning to be a continuous function of experience. However, most perceptual learning studies use thresholds estimated by fitting psychometric functions to independent blocks, sometimes then fitting a parametric function to these block-wise estimated thresholds. Critically, such approaches tend to violate the basic principle that learning is continuous through time (e.g., by aggregating trials into large "blocks" for analysis that each assume stationarity, then fitting learning functions to these aggregated blocks). To address this discrepancy between base theory and analysis practice, here we instead propose fitting a parametric function to thresholds from each individual trial. In particular, we implemented a dynamic psychometric function whose parameters were allowed to change continuously with each trial, thus parameterizing nonstationarity. We fit the resulting continuous time parametric model to data from two different perceptual learning tasks. In nearly every case, the quality of the fits derived from the continuous time parametric model outperformed the fits derived from a nonparametric approach wherein separate psychometric functions were fit to blocks of trials. Because such a continuous trial-dependent model of perceptual learning also offers a number of additional advantages (e.g., the ability to extrapolate beyond the observed data; the ability to estimate performance on individual critical trials), we suggest that this technique would be a useful addition to each psychophysicist's analysis toolkit.

  14. Comparison of model and human observer performance for detection and discrimination tasks using dual-energy x-ray images

    International Nuclear Information System (INIS)

    Richard, Samuel; Siewerdsen, Jeffrey H.

    2008-01-01

    Model observer performance, computed theoretically using cascaded systems analysis (CSA), was compared to the performance of human observers in detection and discrimination tasks. Dual-energy (DE) imaging provided a wide range of acquisition and decomposition parameters for which observer performance could be predicted and measured. This work combined previously derived observer models (e.g., Fisher-Hotelling and non-prewhitening) with CSA modeling of the DE image noise-equivalent quanta (NEQ) and imaging task (e.g., sphere detection, shape discrimination, and texture discrimination) to yield theoretical predictions of detectability index (d ' ) and area under the receiver operating characteristic (A Z ). Theoretical predictions were compared to human observer performance assessed using 9-alternative forced-choice tests to yield measurement of A Z as a function of DE image acquisition parameters (viz., allocation of dose between the low- and high-energy images) and decomposition technique [viz., three DE image decomposition algorithms: standard log subtraction (SLS), simple-smoothing of the high-energy image (SSH), and anti-correlated noise reduction (ACNR)]. Results showed good agreement between theory and measurements over a broad range of imaging conditions. The incorporation of an eye filter and internal noise in the observer models demonstrated improved correspondence with human observer performance. Optimal acquisition and decomposition parameters were shown to depend on the imaging task; for example, ACNR and SSH yielded the greatest performance in the detection of soft-tissue and bony lesions, respectively. This study provides encouraging evidence that Fourier-based modeling of NEQ computed via CSA and imaging task provides a good approximation to human observer performance for simple imaging tasks, helping to bridge the gap between Fourier metrics of detector performance (e.g., NEQ) and human observer performance.

  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. Fast learning of simple perceptual discriminations reduces brain activation in working memory and in high-level auditory regions.

    Science.gov (United States)

    Daikhin, Luba; Ahissar, Merav

    2015-07-01

    Introducing simple stimulus regularities facilitates learning of both simple and complex tasks. This facilitation may reflect an implicit change in the strategies used to solve the task when successful predictions regarding incoming stimuli can be formed. We studied the modifications in brain activity associated with fast perceptual learning based on regularity detection. We administered a two-tone frequency discrimination task and measured brain activation (fMRI) under two conditions: with and without a repeated reference tone. Although participants could not explicitly tell the difference between these two conditions, the introduced regularity affected both performance and the pattern of brain activation. The "No-Reference" condition induced a larger activation in frontoparietal areas known to be part of the working memory network. However, only the condition with a reference showed fast learning, which was accompanied by a reduction of activity in two regions: the left intraparietal area, involved in stimulus retention, and the posterior superior-temporal area, involved in representing auditory regularities. We propose that this joint reduction reflects a reduction in the need for online storage of the compared tones. We further suggest that this change reflects an implicit strategic shift "backwards" from reliance mainly on working memory networks in the "No-Reference" condition to increased reliance on detected regularities stored in high-level auditory networks.

  17. Context effects in a temporal discrimination task" further tests of the Scalar Expectancy Theory and Learning-to-Time models.

    Science.gov (United States)

    Arantes, Joana; Machado, Armando

    2008-07-01

    Pigeons were trained on two temporal bisection tasks, which alternated every two sessions. In the first task, they learned to choose a red key after a 1-s signal and a green key after a 4-s signal; in the second task, they learned to choose a blue key after a 4-s signal and a yellow key after a 16-s signal. Then the pigeons were exposed to a series of test trials in order to contrast two timing models, Learning-to-Time (LeT) and Scalar Expectancy Theory (SET). The models made substantially different predictions particularly for the test trials in which the sample duration ranged from 1 s to 16 s and the choice keys were Green and Blue, the keys associated with the same 4-s samples: LeT predicted that preference for Green should increase with sample duration, a context effect, but SET predicted that preference for Green should not vary with sample duration. The results were consistent with LeT. The present study adds to the literature the finding that the context effect occurs even when the two basic discriminations are never combined in the same session.

  18. 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.

  19. A learning perspective on individual differences in skilled reading: Exploring and exploiting orthographic and semantic discrimination cues.

    Science.gov (United States)

    Milin, Petar; Divjak, Dagmar; Baayen, R Harald

    2017-11-01

    The goal of the present study is to understand the role orthographic and semantic information play in the behavior of skilled readers. Reading latencies from a self-paced sentence reading experiment in which Russian near-synonymous verbs were manipulated appear well-predicted by a combination of bottom-up sublexical letter triplets (trigraphs) and top-down semantic generalizations, modeled using the Naive Discrimination Learner. The results reveal a complex interplay of bottom-up and top-down support from orthography and semantics to the target verbs, whereby activations from orthography only are modulated by individual differences. Using performance on a serial reaction time (SRT) task for a novel operationalization of the mental speed hypothesis, we explain the observed individual differences in reading behavior in terms of the exploration/exploitation hypothesis from reinforcement learning, where initially slower and more variable behavior leads to better performance overall. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  20. 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

  1. Revisiting vocal perception in non-human animals: a review of vowel discrimination, speaker voice recognition, and speaker normalization

    Directory of Open Access Journals (Sweden)

    Buddhamas eKriengwatana

    2015-01-01

    Full Text Available The extent to which human speech perception evolved by taking advantage of predispositions and pre-existing features of vertebrate auditory and cognitive systems remains a central question in the evolution of speech. This paper reviews asymmetries in vowel perception, speaker voice recognition, and speaker normalization in non-human animals – topics that have not been thoroughly discussed in relation to the abilities of non-human animals, but are nonetheless important aspects of vocal perception. Throughout this paper we demonstrate that addressing these issues in non-human animals is relevant and worthwhile because many non-human animals must deal with similar issues in their natural environment. That is, they must also discriminate between similar-sounding vocalizations, determine signaler identity from vocalizations, and resolve signaler-dependent variation in vocalizations from conspecifics. Overall, we find that, although plausible, the current evidence is insufficiently strong to conclude that directional asymmetries in vowel perception are specific to humans, or that non-human animals can use voice characteristics to recognize human individuals. However, we do find some indication that non-human animals can normalize speaker differences. Accordingly, we identify avenues for future research that would greatly improve and advance our understanding of these topics.

  2. Individual Difference Factors in the Learning and Transfer of Patterning Discriminations

    Directory of Open Access Journals (Sweden)

    Elisa Maes

    2017-07-01

    Full Text Available In an associative patterning task, some people seem to focus more on learning an overarching rule, whereas others seem to focus on acquiring specific relations between the stimuli and outcomes involved. Building on earlier work, we further investigated which cognitive factors are involved in feature- vs. rule-based learning and generalization. To this end, we measured participants' tendency to generalize according to the rule of opposites after training on negative and positive patterning problems (i.e., A+/B+/AB− and C−/D−/CD+, their tendency to attend to global aspects or local details of stimuli, their systemizing disposition and their score on the Raven intelligence test. Our results suggest that while intelligence might have some influence on patterning learning and generalization, visual processing style and systemizing disposition do not. We discuss our findings in the light of previous observations on patterning.

  3. Microarray multiplex assay for the simultaneous detection and discrimination of hepatitis B, hepatitis C, and human immunodeficiency type-1 viruses in human blood samples

    International Nuclear Information System (INIS)

    Hsia, Chu Chieh; Chizhikov, Vladimir E.; Yang, Amy X.; Selvapandiyan, Angamuthu; Hewlett, Indira; Duncan, Robert; Puri, Raj K.; Nakhasi, Hira L.; Kaplan, Gerardo G.

    2007-01-01

    Hepatitis B virus (HBV), hepatitis C virus (HCV), and human immunodeficiency virus type-1 (HIV-1) are transfusion-transmitted human pathogens that have a major impact on blood safety and public health worldwide. We developed a microarray multiplex assay for the simultaneous detection and discrimination of these three viruses. The microarray consists of 16 oligonucleotide probes, immobilized on a silylated glass slide. Amplicons from multiplex PCR were labeled with Cy-5 and hybridized to the microarray. The assay detected 1 International Unit (IU), 10 IU, 20 IU of HBV, HCV, and HIV-1, respectively, in a single multiplex reaction. The assay also detected and discriminated the presence of two or three of these viruses in a single sample. Our data represent a proof-of-concept for the possible use of highly sensitive multiplex microarray assay to screen and confirm the presence of these viruses in blood donors and patients

  4. Statistical Discriminability Estimation for Pattern Classification Based on Neural Incremental Attribute Learning

    DEFF Research Database (Denmark)

    Wang, Ting; Guan, Sheng-Uei; Puthusserypady, Sadasivan

    2014-01-01

    Feature ordering is a significant data preprocessing method in Incremental Attribute Learning (IAL), a novel machine learning approach which gradually trains features according to a given order. Previous research has shown that, similar to feature selection, feature ordering is also important based...... estimation. Moreover, a criterion that summarizes all the produced values of AD is employed with a GA (Genetic Algorithm)-based approach to obtain the optimum feature ordering for classification problems based on neural networks by means of IAL. Compared with the feature ordering obtained by other approaches...

  5. Muscarinic receptor binding increases in anterior thalamus and cingulate cortex during discriminative avoidance learning

    International Nuclear Information System (INIS)

    Vogt, B.A.; Gabriel, M.; Vogt, L.J.; Poremba, A.; Jensen, E.L.; Kubota, Y.; Kang, E.

    1991-01-01

    Training-induced neuronal activity develops in the mammalian limbic system during discriminative avoidance conditioning. This study explores behaviorally relevant changes in muscarinic ACh receptor binding in 52 rabbits that were trained to one of five stages of conditioned response acquisition. Sixteen naive and 10 animals yoked to criterion performance served as control cases. Upon reaching a particular stage of training, the brains were removed and autoradiographically assayed for 3H-oxotremorine-M binding with 50 nM pirenzepine (OxO-M/PZ) or for 3H-pirenzepine binding in nine limbic thalamic nuclei and cingulate cortex. Specific OxO-M/PZ binding increased in the parvocellular division of the anterodorsal nucleus early in training when the animals were first exposed to pairing of the conditional and unconditional stimuli. Elevated binding in this nucleus was maintained throughout subsequent training. In the parvocellular division of the anteroventral nucleus (AVp), OxO-M/PZ binding progressively increased throughout training, reached a peak at the criterion stage of performance, and returned to control values during extinction sessions. Peak OxO-M/PZ binding in AVp was significantly elevated over that for cases yoked to criterion performance. In the magnocellular division of the anteroventral nucleus (AVm), OxO-M/PZ binding was elevated only during criterion performance of the task, and it was unaltered in any other limbic thalamic nuclei. Specific OxO-M/PZ binding was also elevated in most layers in rostral area 29c when subjects first performed a significant behavioral discrimination. Training-induced alterations in OxO-M/PZ binding in AVp and layer Ia of area 29c were similar and highly correlated

  6. On combining principal components with Fisher's linear discriminants for supervised learning

    NARCIS (Netherlands)

    Pechenizkiy, M.; Tsymbal, A.; Puuronen, S.

    2006-01-01

    "The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic increase of computational complexity and classification error in high dimensions. In this paper, principal component analysis (PCA), parametric feature extraction (FE) based on Fisher’s linear

  7. Image Tracing: An Analysis of Its Effectiveness in Children's Pictorial Discrimination Learning

    Science.gov (United States)

    Levin, Joel R.; And Others

    1977-01-01

    A total of 45 fifth grade students were the subjects of an experiment offering support for a component of learning strategy (memory imagery). Various theoretical explanations of the image-tracing phenomenon are considered, including depth of processing, dual coding and frequency. (MS)

  8. Different Parameters Support Generalization and Discrimination Learning in "Drosophila" at the Flight Simulator

    Science.gov (United States)

    Brembs, Bjorn; de Ibarra, Natalie Hempel

    2006-01-01

    We have used a genetically tractable model system, the fruit fly "Drosophila melanogaster" to study the interdependence between sensory processing and associative processing on learning performance. We investigated the influence of variations in the physical and predictive properties of color stimuli in several different operant-conditioning…

  9. Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines

    NARCIS (Netherlands)

    G. van Tulder (Gijs); M. de Bruijne (Marleen)

    2016-01-01

    textabstractThe choice of features greatly influences the performance of a tissue classification system. Despite this, many systems are built with standard, predefined filter banks that are not optimized for that particular application. Representation learning methods such as restricted Boltzmann

  10. Measuring Discrimination- and Reversal Learning in Mouse Models within 4 Days and without Prior Food Deprivation

    Science.gov (United States)

    Remmelink, Esther; Smit, August B.; Verhage, Matthijs; Loos, Maarten

    2016-01-01

    Many neurological and psychiatric disorders are characterized by deficits in cognitive flexibility. Modeling cognitive flexibility in mice enables the investigation of mechanisms underlying these deficits. The majority of currently available behavioral tests targeting this cognitive domain are reversal learning tasks that require scheduled food…

  11. 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.

  12. Fos Protein Expression in Olfactory-Related Brain Areas after Learning and after Reactivation of a Slowly Acquired Olfactory Discrimination Task in the Rat

    Science.gov (United States)

    Roullet, Florence; Lienard, Fabienne; Datiche, Frederique; Cattarelli, Martine

    2005-01-01

    Fos protein immunodetection was used to investigate the neuronal activation elicited in some olfactory-related areas after either learning of an olfactory discrimination task or its reactivation 10 d later. Trained rats (T) progressively acquired the association between one odor of a pair and water-reward in a four-arm maze. Two groups of…

  13. 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.

  14. The social network of actors influencing age discrimination in the human resources recruiting process

    Directory of Open Access Journals (Sweden)

    Aurelian SOFICĂ

    2012-06-01

    Full Text Available The aim of the paper is to map the area where the social construction of age discrimination in the recruiting process is perceived as taking place, especially those individuals or organized groups with enough power and interest to influence this unethical reality. The research was carried out in 2010 and 2011 in Cluj-Napoca, Romania; it uses multiple qualitative methods (focus-group and interviews and covers three layers of perception: candidate’s perception, employer’s perception and recruiter’s perception. Usually, the main social actors publically perceived as influencing age discrimination in the recruiting process are the employers (as the main responsible, some public institutions (as guardians and the candidates (as victims. The findings of the paper show that the number of social actors perceived as interested and with power by the main social actors (employers and candidates is much higher than the number classically targeted by researchers, reaching 20 or more

  15. Discrimination of rectal cancer through human serum using surface-enhanced Raman spectroscopy

    Science.gov (United States)

    Li, Xiaozhou; Yang, Tianyue; Li, Siqi; Zhang, Su; Jin, Lili

    2015-05-01

    In this paper, surface-enhanced Raman spectroscopy (SERS) was used to detect the changes in blood serum components that accompany rectal cancer. The differences in serum SERS data between rectal cancer patients and healthy controls were examined. Postoperative rectal cancer patients also participated in the comparison to monitor the effects of cancer treatments. The results show that there are significant variations at certain wavenumbers which indicates alteration of corresponding biological substances. Principal component analysis (PCA) and parameters of intensity ratios were used on the original SERS spectra for the extraction of featured variables. These featured variables then underwent linear discriminant analysis (LDA) and classification and regression tree (CART) for the discrimination analysis. Accuracies of 93.5 and 92.4 % were obtained for PCA-LDA and parameter-CART, respectively.

  16. Discrimination of Fearful and Angry Emotional Voices in Sleeping Human Neonates: a Study of the Mismatch Brain Responses

    Directory of Open Access Journals (Sweden)

    Dandan eZhang

    2014-12-01

    Full Text Available Appropriate processing of human voices with different threat-related emotions is of evolutionarily adaptive value for the survival of individuals. Nevertheless, it is still not clear whether the sensitivity to threat-related information is present at birth. Using an oddball paradigm, the current study investigated the neural correlates underlying automatic processing of emotional voices of fear and anger in sleeping neonates. Event-related potential data showed that the frontocentral scalp distribution of the neonatal brain could discriminate fearful voices from angry voices; the mismatch response (MMR was larger in response to the deviant stimuli of anger, compared with the standard stimuli of fear. Furthermore, this fear-anger MMR discrimination was observed only when neonates were in active sleep state. Although the neonates’ sensitivity to threat-related voices is not likely associated with a conceptual understanding of fearful and angry emotions, this special discrimination in early life may provide a foundation for later emotion and social cognition development.

  17. A Report on Applying EEGnet to Discriminate Human State Effects on Task Performance

    Science.gov (United States)

    2018-01-01

    indicate that EEGNet could discriminate sleep history of a user. This could be used in future adaptive technologies to detect user fatigue and likely...is unlimited. 1. Introduction As the amount of battlefield technology continues to increase, Soldiers are faced with a daunting task of trying to...integrate diverse information across numerous devices. The growing information burden across devices has spawned a strong in- terest in “smart technology

  18. 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…

  19. Unpredictable chronic mild stress differentially impairs social and contextual discrimination learning in two inbred mouse strains.

    Science.gov (United States)

    van Boxelaere, Michiel; Clements, Jason; Callaerts, Patrick; D'Hooge, Rudi; Callaerts-Vegh, Zsuzsanna

    2017-01-01

    Alterations in the social and cognitive domain are considered important indicators for increased disability in many stress-related disorders. Similar impairments have been observed in rodents chronically exposed to stress, mimicking potential endophenotypes of stress-related psychopathologies such as major depression disorder (MDD), anxiety, conduct disorder, and posttraumatic stress disorder (PTSD). Data from numerous studies suggest that deficient plasticity mechanisms in hippocampus (HC) and prefrontal cortex (PFC) might underlie these social and cognitive deficits. Specifically, stress-induced deficiencies in neural plasticity have been associated with a hypodopaminergic state and reduced neural plasticity persistence. Here we assessed the effects of unpredictable chronic mild stress (UCMS) on exploratory, social and cognitive behavior of females of two inbred mouse strains (C57BL/6J and DBA/2J) that differ in their dopaminergic profile. Exposure to chronic stress resulted in impaired circadian rhythmicity, sociability and social cognition in both inbred strains, but differentially affected activity patterns and contextual discrimination performance. These stress-induced behavioral impairments were accompanied by reduced expression levels of brain derived neurotrophic factor (BDNF) in the prefrontal cortex. The strain-specific cognitive impairment was coexistent with enhanced plasma corticosterone levels and reduced expression of genes related to dopamine signaling in hippocampus. These results underline the importance of assessing different strains with multiple test batteries to elucidate the neural and genetic basis of social and cognitive impairments related to chronic stress.

  20. Unpredictable chronic mild stress differentially impairs social and contextual discrimination learning in two inbred mouse strains.

    Directory of Open Access Journals (Sweden)

    Michiel van Boxelaere

    Full Text Available Alterations in the social and cognitive domain are considered important indicators for increased disability in many stress-related disorders. Similar impairments have been observed in rodents chronically exposed to stress, mimicking potential endophenotypes of stress-related psychopathologies such as major depression disorder (MDD, anxiety, conduct disorder, and posttraumatic stress disorder (PTSD. Data from numerous studies suggest that deficient plasticity mechanisms in hippocampus (HC and prefrontal cortex (PFC might underlie these social and cognitive deficits. Specifically, stress-induced deficiencies in neural plasticity have been associated with a hypodopaminergic state and reduced neural plasticity persistence. Here we assessed the effects of unpredictable chronic mild stress (UCMS on exploratory, social and cognitive behavior of females of two inbred mouse strains (C57BL/6J and DBA/2J that differ in their dopaminergic profile. Exposure to chronic stress resulted in impaired circadian rhythmicity, sociability and social cognition in both inbred strains, but differentially affected activity patterns and contextual discrimination performance. These stress-induced behavioral impairments were accompanied by reduced expression levels of brain derived neurotrophic factor (BDNF in the prefrontal cortex. The strain-specific cognitive impairment was coexistent with enhanced plasma corticosterone levels and reduced expression of genes related to dopamine signaling in hippocampus. These results underline the importance of assessing different strains with multiple test batteries to elucidate the neural and genetic basis of social and cognitive impairments related to chronic stress.

  1. 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...

  2. 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)

  3. A Comparative Study of Discrimination in Education: The Learning Environment and Behaviours of Students and Teachers in Iran

    Science.gov (United States)

    Ghaffarzadeh, Mozhgan

    2016-01-01

    It is the learners' right to get an education free from discrimination. Discrimination in education ranges from gender to race, age, social class, financial status, and other characteristics. In this study the focus is on discrimination in education in regard to social class and financial status. The paper describes observations of the school…

  4. 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…

  5. 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.

  6. 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...

  7. Identification of Discriminating Metabolic Pathways and Metabolites in Human PBMCs Stimulated by Various Pathogenic Agents

    Directory of Open Access Journals (Sweden)

    Xiang Zhang

    2018-02-01

    Full Text Available Immunity and cellular metabolism are tightly interconnected but it is not clear whether different pathogens elicit specific metabolic responses. To address this issue, we studied differential metabolic regulation in peripheral blood mononuclear cells (PBMCs of healthy volunteers challenged by Candida albicans, Borrelia burgdorferi, lipopolysaccharide, and Mycobacterium tuberculosis in vitro. By integrating gene expression data of stimulated PBMCs of healthy individuals with the KEGG pathways, we identified both common and pathogen-specific regulated pathways depending on the time of incubation. At 4 h of incubation, pathogenic agents inhibited expression of genes involved in both the glycolysis and oxidative phosphorylation pathways. In contrast, at 24 h of incubation, particularly glycolysis was enhanced while genes involved in oxidative phosphorylation remained unaltered in the PBMCs. In general, differential gene expression was less pronounced at 4 h compared to 24 h of incubation. KEGG pathway analysis allowed differentiation between effects induced by Candida and bacterial stimuli. Application of genome-scale metabolic model further generated a Candida-specific set of 103 reporter metabolites (e.g., desmosterol that might serve as biomarkers discriminating Candida-stimulated PBMCs from bacteria-stimuated PBMCs. Our analysis also identified a set of 49 metabolites that allowed discrimination between the effects of Borrelia burgdorferi, lipopolysaccharide and Mycobacterium tuberculosis. We conclude that analysis of pathogen-induced effects on PBMCs by a combination of KEGG pathways and genome-scale metabolic model provides deep insight in the metabolic changes coupled to host defense.

  8. 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.

  9. Learning discriminative features from RGB-D images for gender and ethnicity identification

    Science.gov (United States)

    Azzakhnini, Safaa; Ballihi, Lahoucine; Aboutajdine, Driss

    2016-11-01

    The development of sophisticated sensor technologies gave rise to an interesting variety of data. With the appearance of affordable devices, such as the Microsoft Kinect, depth-maps and three-dimensional data became easily accessible. This attracted many computer vision researchers seeking to exploit this information in classification and recognition tasks. In this work, the problem of face classification in the context of RGB images and depth information (RGB-D images) is addressed. The purpose of this paper is to study and compare some popular techniques for gender recognition and ethnicity classification to understand how much depth data can improve the quality of recognition. Furthermore, we investigate which combination of face descriptors, feature selection methods, and learning techniques is best suited to better exploit RGB-D images. The experimental results show that depth data improve the recognition accuracy for gender and ethnicity classification applications in many use cases.

  10. Predators or prey? Spatio-temporal discrimination of human-derived risk by brown bears.

    Science.gov (United States)

    Ordiz, Andrés; Støen, Ole-Gunnar; Delibes, Miguel; Swenson, Jon E

    2011-05-01

    Prey usually adjust anti-predator behavior to subtle variations in perceived risk. However, it is not clear whether adult large carnivores that are virtually free of natural predation adjust their behavior to subtle variations in human-derived risk, even when living in human-dominated landscapes. As a model, we studied resting-site selection by a large carnivore, the brown bear (Ursus arctos), under different spatial and temporal levels of human activity. We quantified horizontal and canopy cover at 440 bear beds and 439 random sites at different distances from human settlements, seasons, and times of the day. We hypothesized that beds would be more concealed than random sites and that beds would be more concealed in relation to human-derived risk. Although human densities in Scandinavia are the lowest within bear ranges in Western Europe, we found an effect of human activity; bears chose beds with higher horizontal and canopy cover during the day (0700-1900 hours), especially when resting closer to human settlements, than at night (2200-0600 hours). In summer/fall (the berry season), with more intensive and dispersed human activity, including hunting, bears rested further from human settlements during the day than in spring (pre-berry season). Additionally, day beds in the summer/fall were the most concealed. Large carnivores often avoid humans at a landscape scale, but total avoidance in human-dominated areas is not possible. Apparently, bears adjust their behavior to avoid human encounters, which resembles the way prey avoid their predators. Bears responded to fine-scale variations in human-derived risk, both on a seasonal and a daily basis.

  11. 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.

  12. Simplifying the human serum proteome for discriminating patients with bipolar disorder of other psychiatry conditions.

    Science.gov (United States)

    de Jesus, Jemmyson Romário; Galazzi, Rodrigo Moretto; de Lima, Tatiani Brenelli; Banzato, Cláudio Eduardo Muller; de Almeida Lima E Silva, Luiz Fernando; de Rosalmeida Dantas, Clarissa; Gozzo, Fábio Cézar; Arruda, Marco Aurélio Zezzi

    2017-12-01

    An exploratory analysis using proteomic strategies in blood serum of patients with bipolar disorder (BD), and with other psychiatric conditions such as Schizophrenia (SCZ), can provide a better understanding of this disorder, as well as their discrimination based on their proteomic profile. The proteomic profile of blood serum samples obtained from patients with BD using lithium or other drugs (N=14), healthy controls, including non-family (HCNF; N=3) and family (HCF; N=9), patients with schizophrenia (SCZ; N=23), and patients using lithium for other psychiatric conditions (OD; N=4) were compared. Four methods for simplifying the serum samples proteome were evaluated for both removing the most abundant proteins and for enriching those of lower-abundance: protein depletion with acetonitrile (ACN), dithiothreitol (DTT), sequential depletion using DTT and ACN, and protein equalization using commercial ProteoMiner® kit (PM). For proteomic evaluation, 2-D DIGE and nanoLC-MS/MS analysis were employed. PM method was the best strategy for removing proteins of high abundance. Through 2-D DIGE gel image comparison, 37 protein spots were found differentially abundant (p<0.05, Student's t-test), which exhibited ≥2.0-fold change of the average value of normalized spot intensities in the serum of SCZ, BD and OD patients compared to subject controls (HCF and HCNF). From these spots detected, 13 different proteins were identified: ApoA1, ApoE, ApoC3, ApoA4, Samp, SerpinA1, TTR, IgK, Alb, VTN, TR, C4A and C4B. Proteomic analysis allowed the discrimination of patients with BD from patients with other mental disorders, such as SCZ. The findings in this exploratory study may also contribute for better understanding the pathophysiology of these disorders and finding potential serum biomarkers for these conditions. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  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. Fuzziness-based active learning framework to enhance hyperspectral image classification performance for discriminative and generative classifiers.

    Directory of Open Access Journals (Sweden)

    Muhammad Ahmad

    Full Text Available Hyperspectral image classification with a limited number of training samples without loss of accuracy is desirable, as collecting such data is often expensive and time-consuming. However, classifiers trained with limited samples usually end up with a large generalization error. To overcome the said problem, we propose a fuzziness-based active learning framework (FALF, in which we implement the idea of selecting optimal training samples to enhance generalization performance for two different kinds of classifiers, discriminative and generative (e.g. SVM and KNN. The optimal samples are selected by first estimating the boundary of each class and then calculating the fuzziness-based distance between each sample and the estimated class boundaries. Those samples that are at smaller distances from the boundaries and have higher fuzziness are chosen as target candidates for the training set. Through detailed experimentation on three publically available datasets, we showed that when trained with the proposed sample selection framework, both classifiers achieved higher classification accuracy and lower processing time with the small amount of training data as opposed to the case where the training samples were selected randomly. Our experiments demonstrate the effectiveness of our proposed method, which equates favorably with the state-of-the-art methods.

  15. Quantifying explainable discrimination and removing illegal discrimination in automated decision making

    NARCIS (Netherlands)

    Kamiran, F.; Zliobaite, I.; Calders, T.G.K.

    2013-01-01

    Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train

  16. 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

  17. 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.…

  18. 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…

  19. Long Noncoding RNA Identification: Comparing Machine Learning Based Tools for Long Noncoding Transcripts Discrimination

    Directory of Open Access Journals (Sweden)

    Siyu Han

    2016-01-01

    Full Text Available Long noncoding RNA (lncRNA is a kind of noncoding RNA with length more than 200 nucleotides, which aroused interest of people in recent years. Lots of studies have confirmed that human genome contains many thousands of lncRNAs which exert great influence over some critical regulators of cellular process. With the advent of high-throughput sequencing technologies, a great quantity of sequences is waiting for exploitation. Thus, many programs are developed to distinguish differences between coding and long noncoding transcripts. Different programs are generally designed to be utilised under different circumstances and it is sensible and practical to select an appropriate method according to a certain situation. In this review, several popular methods and their advantages, disadvantages, and application scopes are summarised to assist people in employing a suitable method and obtaining a more reliable result.

  20. 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

  1. Structural Discrimination

    DEFF Research Database (Denmark)

    Thorsen, Mira Skadegård

    discrimination as two ways of articulating particular, opaque forms of racial discrimination that occur in everyday Danish (and other) contexts, and have therefore become normalized. I present and discuss discrimination as it surfaces in data from my empirical studies of discrimination in Danish contexts...

  2. Syllabic discrimination in premature human infants prior to complete formation of cortical layers

    OpenAIRE

    Mahmoudzadeh, Mahdi; Dehaene-Lambertz, Ghislaine; Fournier, Marc; Kongolo, Guy; Goudjil, Sabrina; Dubois, Jessica; Grebe, Reinhard; Wallois, Fabrice

    2013-01-01

    The ontogeny of linguistic functions in the human brain remains elusive. Although some auditory capacities are described before term, whether and how such immature cortical circuits might process speech are unknown. Here we used functional optical imaging to evaluate the cerebral responses to syllables at the earliest age at which cortical responses to external stimuli can be recorded in humans (28- to 32-wk gestational age). At this age, the cortical organization in layers is not completed. ...

  3. 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…

  4. 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…

  5. Discrimination against Black Students

    Science.gov (United States)

    Aloud, Ashwaq; Alsulayyim, Maryam

    2016-01-01

    Discrimination is a structured way of abusing people based on racial differences, hence barring them from accessing wealth, political participation and engagement in many spheres of human life. Racism and discrimination are inherently rooted in institutions in the society, the problem has spread across many social segments of the society including…

  6. Discrimination of timbre in early auditory responses of the human brain.

    Directory of Open Access Journals (Sweden)

    Jaeho Seol

    Full Text Available BACKGROUND: The issue of how differences in timbre are represented in the neural response still has not been well addressed, particularly with regard to the relevant brain mechanisms. Here we employ phasing and clipping of tones to produce auditory stimuli differing to describe the multidimensional nature of timbre. We investigated the auditory response and sensory gating as well, using by magnetoencephalography (MEG. METHODOLOGY/PRINCIPAL FINDINGS: Thirty-five healthy subjects without hearing deficit participated in the experiments. Two different or same tones in timbre were presented through conditioning (S1-testing (S2 paradigm as a pair with an interval of 500 ms. As a result, the magnitudes of auditory M50 and M100 responses were different with timbre in both hemispheres. This result might support that timbre, at least by phasing and clipping, is discriminated in the auditory early processing. The second response in a pair affected by S1 in the consecutive stimuli occurred in M100 of the left hemisphere, whereas both M50 and M100 responses to S2 only in the right hemisphere reflected whether two stimuli in a pair were the same or not. Both M50 and M100 magnitudes were different with the presenting order (S1 vs. S2 for both same and different conditions in the both hemispheres. CONCLUSIONS/SIGNIFICANCES: Our results demonstrate that the auditory response depends on timbre characteristics. Moreover, it was revealed that the auditory sensory gating is determined not by the stimulus that directly evokes the response, but rather by whether or not the two stimuli are identical in timbre.

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. Narrowing down the conditions for extinction of Pavlovian feature-positive discriminations in humans

    NARCIS (Netherlands)

    van Vooren, P.R.; Franssen, M.; Beckers, T.; Hermans, D.; Baeyens, F.

    2012-01-01

    The aim of this study was to delineate the minimal conditions for extinction of Pavlovian modulation in humans. Previous experiments at our lab showed that, after X-- A+/A- acquisition training, X- trials did not extinguish differential X-- A+/A- responding, while X-- A- trials did. Additionally,

  13. Discrimination of human cytotoxic lymphocytes from regulatory and B-lymphocytes by orthogonal light scattering

    NARCIS (Netherlands)

    Terstappen, Leonardus Wendelinus Mathias Marie; de Grooth, B.G.; ten Napel, C.H.H.; van Berkel, W.; Greve, Jan

    1986-01-01

    Light scattering properties of human lymphocyte subpopulations selected by immunofluorescence were studied with a flow cytometer. Regulatory and B-lymphocytes showed a low orthogonal light scatter signal, whereas cytotoxic lymphocytes identified with leu-7, leu-11 and leu-15 revealed a large

  14. 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.

  15. Effects of subchronic phencyclidine (PCP treatment on social behaviors, and operant discrimination and reversal learning in C57BL/6J mice

    Directory of Open Access Journals (Sweden)

    Jonathan L Brigman

    2009-02-01

    Full Text Available Subchronic treatment with the psychotomimetic phencyclidine (PCP has been proposed as a rodent model of the negative and cognitive/executive symptoms of schizophrenia. There has, however, been a paucity of studies on this model in mice, despite the growing use of the mouse as a subject in genetic and molecular studies of schizophrenia. In the present study, we evaluated the effects of subchronic PCP treatment (5 mg/kg twice daily x 7 days, followed by 7 days withdrawal in C57BL/6J mice on 1 social behaviors using a sociability/social novelty-preference paradigm, and 2 pairwise visual discrimination and reversal learning using a touchscreen-based operant system. Results showed that mice subchronically treated with PCP made more visits to (but did not spend more time with a social stimulus relative to an inanimate one, and made more visits and spent more time investigating a novel social stimulus over a familiar one. Subchronic PCP treatment did not significantly affect behavior in either the discrimination or reversal learning tasks. These data encourage further analysis of the potential utility of mouse subchronic PCP treatment for modeling the social withdrawal component of schizophrenia. They also indicate that the treatment regimen employed was insufficient to impair our measures of discrimination and reversal learning in the C57BL/6J strain. Further work will be needed to identify alternative methods (e.g., repeated cycles of subchronic PCP treatment, use of different mouse strains that produce discrimination and/or reversal impairment, as well as other cognitive/executive measures that are sensitive to chronic PCP treatment in mice.

  16. 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

  17. 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.

  18. Multimodal Discrimination of Schizophrenia Using Hybrid Weighted Feature Concatenation of Brain Functional Connectivity and Anatomical Features with an Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Muhammad Naveed Iqbal Qureshi

    2017-09-01

    Full Text Available Multimodal features of structural and functional magnetic resonance imaging (MRI of the human brain can assist in the diagnosis of schizophrenia. We performed a classification study on age, sex, and handedness-matched subjects. The dataset we used is publicly available from the Center for Biomedical Research Excellence (COBRE and it consists of two groups: patients with schizophrenia and healthy controls. We performed an independent component analysis and calculated global averaged functional connectivity-based features from the resting-state functional MRI data for all the cortical and subcortical anatomical parcellation. Cortical thickness along with standard deviation, surface area, volume, curvature, white matter volume, and intensity measures from the cortical parcellation, as well as volume and intensity from sub-cortical parcellation and overall volume of cortex features were extracted from the structural MRI data. A novel hybrid weighted feature concatenation method was used to acquire maximal 99.29% (P < 0.0001 accuracy which preserves high discriminatory power through the weight of the individual feature type. The classification was performed by an extreme learning machine, and its efficiency was compared to linear and non-linear (radial basis function support vector machines, linear discriminant analysis, and random forest bagged tree ensemble algorithms. This article reports the predictive accuracy of both unimodal and multimodal features after 10-by-10-fold nested cross-validation. A permutation test followed the classification experiment to assess the statistical significance of the classification results. It was concluded that, from a clinical perspective, this feature concatenation approach may assist the clinicians in schizophrenia diagnosis.

  19. 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.

  20. Second-order conditioning and conditioned inhibition: influences of speed versus accuracy on human causal learning.

    Directory of Open Access Journals (Sweden)

    Jessica C Lee

    Full Text Available In human causal learning, excitatory and inhibitory learning effects can sometimes be found in the same paradigm by altering the learning conditions. This study aims to explore whether learning in the feature negative paradigm can be dissociated by emphasising speed over accuracy. In two causal learning experiments, participants were given a feature negative discrimination in which the outcome caused by one cue was prevented by the addition of another. Participants completed training trials either in a self-paced fashion with instructions emphasising accuracy, or under strict time constraints with instructions emphasising speed. Using summation tests in which the preventative cue was paired with another causal cue, participants in the accuracy groups correctly rated the preventative cue as if it reduced the probability of the outcome. However, participants in the speed groups rated the preventative cue as if it increased the probability of the outcome. In Experiment 1, both speed and accuracy groups later judged the same cue to be preventative in a reasoned inference task. Experiment 2 failed to find evidence of similar dissociations in retrospective revaluation (release from overshadowing vs. mediated extinction or learning about a redundant cue (blocking vs. augmentation. However in the same experiment, the tendency for the accuracy group to show conditioned inhibition and the speed group to show second-order conditioning was consistent even across sub-sets of the speed and accuracy groups with equivalent accuracy in training, suggesting that second-order conditioning is not merely a consequence of poorer acquisition. This dissociation mirrors the trade-off between second-order conditioning and conditioned inhibition observed in animal conditioning when training is extended.

  1. 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.

  2. 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…

  3. 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.

  4. Efficient discrimination and removal of phospholipids during electromembrane extraction from human plasma samples

    DEFF Research Database (Denmark)

    Vårdal, Linda; Gjelstad, Astrid; Huang, Chuixiu

    2017-01-01

    to be highly efficient for providing phospholipid-free extracts. CONCLUSION: Ultra-HPLC-MS/MS analysis of the donor solutions revealed that the phospholipids principally remained in the plasma samples. This proved that the phospholipids did not migrate in the electrical field and they were prevented from......AIM: For the first time, extracts obtained from human plasma samples by electromembrane extraction (EME) were investigated comprehensively with particular respect to phospholipids using ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS). Thhe purpose...

  5. The importance of surface-based cues for face discrimination in non-human primates.

    Science.gov (United States)

    Parr, Lisa A; Taubert, Jessica

    2011-07-07

    Understanding how individual identity is processed from faces remains a complex problem. Contrast reversal, showing faces in photographic negative, impairs face recognition in humans and demonstrates the importance of surface-based information (shading and pigmentation) in face recognition. We tested the importance of contrast information for face encoding in chimpanzees and rhesus monkeys using a computerized face-matching task. Results showed that contrast reversal (positive to negative) selectively impaired face processing in these two species, although the impairment was greater for chimpanzees. Unlike chimpanzees, however, monkeys performed just as well matching negative to positive faces, suggesting that they retained some ability to extract identity information from negative faces. A control task showed that chimpanzees, but not rhesus monkeys, performed significantly better matching face parts compared with whole faces after a contrast reversal, suggesting that contrast reversal acts selectively on face processing, rather than general visual-processing mechanisms. These results confirm the importance of surface-based cues for face processing in chimpanzees and humans, while the results were less salient for rhesus monkeys. These findings make a significant contribution to understanding the evolution of cognitive specializations for face processing among primates, and suggest potential differences between monkeys and apes.

  6. 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.

  7. 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.

  8. 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.

  9. 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…

  10. Intra-individual gait patterns across different time-scales as revealed by means of a supervised learning model using kernel-based discriminant regression.

    Directory of Open Access Journals (Sweden)

    Fabian Horst

    Full Text Available Traditionally, gait analysis has been centered on the idea of average behavior and normality. On one hand, clinical diagnoses and therapeutic interventions typically assume that average gait patterns remain constant over time. On the other hand, it is well known that all our movements are accompanied by a certain amount of variability, which does not allow us to make two identical steps. The purpose of this study was to examine changes in the intra-individual gait patterns across different time-scales (i.e., tens-of-mins, tens-of-hours.Nine healthy subjects performed 15 gait trials at a self-selected speed on 6 sessions within one day (duration between two subsequent sessions from 10 to 90 mins. For each trial, time-continuous ground reaction forces and lower body joint angles were measured. A supervised learning model using a kernel-based discriminant regression was applied for classifying sessions within individual gait patterns.Discernable characteristics of intra-individual gait patterns could be distinguished between repeated sessions by classification rates of 67.8 ± 8.8% and 86.3 ± 7.9% for the six-session-classification of ground reaction forces and lower body joint angles, respectively. Furthermore, the one-on-one-classification showed that increasing classification rates go along with increasing time durations between two sessions and indicate that changes of gait patterns appear at different time-scales.Discernable characteristics between repeated sessions indicate continuous intrinsic changes in intra-individual gait patterns and suggest a predominant role of deterministic processes in human motor control and learning. Natural changes of gait patterns without any externally induced injury or intervention may reflect continuous adaptations of the motor system over several time-scales. Accordingly, the modelling of walking by means of average gait patterns that are assumed to be near constant over time needs to be reconsidered in the

  11. Intra-individual gait patterns across different time-scales as revealed by means of a supervised learning model using kernel-based discriminant regression.

    Science.gov (United States)

    Horst, Fabian; Eekhoff, Alexander; Newell, Karl M; Schöllhorn, Wolfgang I

    2017-01-01

    Traditionally, gait analysis has been centered on the idea of average behavior and normality. On one hand, clinical diagnoses and therapeutic interventions typically assume that average gait patterns remain constant over time. On the other hand, it is well known that all our movements are accompanied by a certain amount of variability, which does not allow us to make two identical steps. The purpose of this study was to examine changes in the intra-individual gait patterns across different time-scales (i.e., tens-of-mins, tens-of-hours). Nine healthy subjects performed 15 gait trials at a self-selected speed on 6 sessions within one day (duration between two subsequent sessions from 10 to 90 mins). For each trial, time-continuous ground reaction forces and lower body joint angles were measured. A supervised learning model using a kernel-based discriminant regression was applied for classifying sessions within individual gait patterns. Discernable characteristics of intra-individual gait patterns could be distinguished between repeated sessions by classification rates of 67.8 ± 8.8% and 86.3 ± 7.9% for the six-session-classification of ground reaction forces and lower body joint angles, respectively. Furthermore, the one-on-one-classification showed that increasing classification rates go along with increasing time durations between two sessions and indicate that changes of gait patterns appear at different time-scales. Discernable characteristics between repeated sessions indicate continuous intrinsic changes in intra-individual gait patterns and suggest a predominant role of deterministic processes in human motor control and learning. Natural changes of gait patterns without any externally induced injury or intervention may reflect continuous adaptations of the motor system over several time-scales. Accordingly, the modelling of walking by means of average gait patterns that are assumed to be near constant over time needs to be reconsidered in the context of

  12. International and Regional Institutional Dialogues for Human Rights for LGBT persons: The quest for recognition, anti-discrimination, and marriage in Southeast Asia

    OpenAIRE

    Holzhacker, Ronald

    2016-01-01

    There is a rich interplay between civil society organizations and institutions involved in human rights norm diffusion and the ‘ricochet’ of ideas at the regional level across Southeast Asia. There is a broad discussion occurring about human rights for LGBT persons and SOGI rights (Sexual Orientation and Gender Identity) including recognition, non-discrimination in employment, education, and housing, and partnership recognition and same-sex marriage. We focus on four countries, Thailand, Viet...

  13. 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.

  14. 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.

  15. Individually identifiable body odors are produced by the gorilla and discriminated by humans.

    Science.gov (United States)

    Hepper, Peter G; Wells, Deborah L

    2010-05-01

    Many species produce odor cues that enable them to be identified individually, as well as providing other socially relevant information. Study of the role of odor cues in the social behavior of great apes is noticeable by its absence. Olfaction has been viewed as having little role in guiding behavior in these species. This study examined whether Western lowland gorillas produce an individually identifiable odor. Odor samples were obtained by placing cloths in the gorilla's den. A delayed matching to sample task was used with human participants (n = 100) to see if they were able to correctly match a target odor sample to a choice of either: 2 odors (the target sample and another, Experiment 1) and 6 odors (the target sample and 5 others, Experiment 2). Participants were correctly able to identify the target odor when given either 2 or 6 matches. Subjects made fewest errors when matching the odor of the silverback, whereas matching the odors of the young gorillas produced most errors. The results indicate that gorillas do produce individually identifiable body odors and introduce the possibility that odor cues may play a role in gorilla social behavior.

  16. Differential discriminator

    International Nuclear Information System (INIS)

    Dukhanov, V.I.; Mazurov, I.B.

    1981-01-01

    A principal flowsheet of a differential discriminator intended for operation in a spectrometric circuit with statistical time distribution of pulses is described. The differential discriminator includes four integrated discriminators and a channel of piled-up signal rejection. The presence of the rejection channel enables the discriminator to operate effectively at loads of 14x10 3 pulse/s. The temperature instability of the discrimination thresholds equals 250 μV/ 0 C. The discrimination level changes within 0.1-5 V, the level shift constitutes 0.5% for the filling ratio of 1:10. The rejection coefficient is not less than 90%. Alpha spectrum of the 228 Th source is presented to evaluate the discriminator operation with the rejector. The rejector provides 50 ns time resolution

  17. 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...

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. Discriminating the hemolytic risk of blood type A plasmas using the complement hemolysis using human erythrocytes (CHUHE) assay.

    Science.gov (United States)

    Cunnion, Kenji M; Hair, Pamela S; Krishna, Neel K; Sass, Megan A; Enos, Clinton W; Whitley, Pamela H; Maes, Lanne Y; Goldberg, Corinne L

    2017-03-01

    The agglutination-based cross-matching method is sensitive for antibody binding to red blood cells but is only partially predictive of complement-mediated hemolysis, which is important in many acute hemolytic transfusion reactions. Here, we describe complement hemolysis using human erythrocytes (CHUHE) assays that directly evaluate complement-mediated hemolysis between individual serum-plasma and red blood cell combinations. The CHUHE assay is used to evaluate correlations between agglutination titers and complement-mediated hemolysis as well as the hemolytic potential of plasma from type A blood donors. Plasma or serum from each type A blood donor was incubated with AB or B red blood cells in the CHUHE assay and measured for free hemoglobin release. CHUHE assays for serum or plasma demonstrate a wide, dynamic range and high sensitivity for complement-mediated hemolysis for individual serum/plasma and red blood cell combinations. CHUHE results suggest that agglutination assays alone are only moderately predictive of complement-mediated hemolysis. CHUHE results also suggest that plasma from particular type A blood donors produce minimal complement-mediated hemolysis, whereas plasma from other type A blood donors produce moderate to high-level complement-mediated hemolysis, depending on the red blood cell donor. The current results indicate that the CHUHE assay can be used to assess complement-mediated hemolysis for plasma or serum from a type A blood donor, providing additional risk discrimination over agglutination titers alone. © 2016 AABB.

  3. 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.

  4. Performance of four different rat strains in the autoshaping, two-object discrimination, and swim maze tests of learning and memory.

    Science.gov (United States)

    Andrews, J S; Jansen, J H; Linders, S; Princen, A; Broekkamp, C L

    1995-04-01

    The performance of four strains of rats commonly used in behavioural research was assessed in three different tests of learning and memory. The four strains included three outbred lines (Long-Evans, Sprague-Dawley, Wistar) and one inbred strain (S3). Learning and memory were tested using three different paradigms: autoshaping of a lever press, a two-object discrimination test, and performance in a two-island swim maze task. The pigmented strains showed better performance in the autoshaping procedure: the majority of the Long-Evans and the S3 rats acquired the response, and the majority of the Wistar and Sprague-Dawley failed to acquire the response in the set time. The albino strains were slightly better in the swim maze than the pigmented strains. There appeared to be a speed/accuracy trade-off in the strategy used to solve the task. This was also evident following treatment with the cholinergic-depleting agent hemicholinium-3. The performance of the Long-Evans rats was most affected by the treatment in terms of accuracy and the Wistar and Sprague-Dawleys in terms of speed. In the two-object discrimination test only the Long-Evans showed satisfactory performance and were able to discriminate a novel from a known object a short interval after initial exposure. These results show large task- and strain-dependent differences in performance in tests of learning and memory. Some of the performance variation may be due to emotional differences between the strains and may be alleviated by extra training. However, the response to pharmacological manipulation may require more careful evaluation.(ABSTRACT TRUNCATED AT 250 WORDS)

  5. 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…

  6. 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.

  7. [Effect of space flight factors simulated in ground-based experiments on the behavior, discriminant learning, and exchange of monoamines in different brain structures of rats].

    Science.gov (United States)

    Shtemberg, A S; Lebedeva-Georgievskaia, K V; Matveeva, M I; Kudrin, V S; Narkevich, V B; Klodt, P M; Bazian, A S

    2014-01-01

    Experimental treatment (long-term fractionated γ-irradiation, antiorthostatic hypodynamia, and the combination of these factors) simulating the effect of space flight in ground-based experiments rapidly restored the motor and orienting-investigative activity of animals (rats) in "open-field" tests. The study of the dynamics of discriminant learning of rats of experimental groups did not show significant differences from the control animals. It was found that the minor effect of these factors on the cognitive performance of animals correlated with slight changes in the concentration ofmonoamines in the brain structures responsible for the cognitive, emotional, and motivational functions.

  8. 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.

  9. 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

  10. 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…

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. "Human immunodeficiency virus serostatus disclosure-Rate, reactions, and discrimination": A cross-sectional study at a rural tertiary care hospital

    Directory of Open Access Journals (Sweden)

    Umesh S Joge

    2013-01-01

    Full Text Available Background: From the moment scientists identified Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS, social responses of fear, denial, stigma, and discrimination have accompanied the epidemic. Aims: To assess the rate of disclosure of HIV serostatus, reactions by the HIV/AIDS patients and their spouse, and discrimination faced by the patients. Methods: The present cross-sectional study was conducted at Antiretroviral Therapy (ART center of a rural tertiary care hospital, situated in Marathawada region of Maharashtra state from November 2008 to October 2010. Totally, 801 HIV-positive patients coming to ART center for treatment were included after ensuring confidentiality and taking informed consent. A preformed questionnaire was used to enquire about reaction after diagnosis, disclosure, and discrimination faced by the patients. The data analyzed using descriptive statistics and Chi-square test. Results: The most common immediate reaction by the HIV patients after getting diagnosed as seropositive was fear (593, 74.03% followed by depression (385, 48.06% and suicidal thoughts (98, 12.25%. Out of 801 patients, 769 (96% had spouse and of these maximum number of patients (653, 84.92% had disclosed HIV status to their spouses. Most common immediate reaction by spouse after disclosure was crime (324, 42.13% followed by horror (294, 38.23% and anger (237, 36.29%. Maximum number of patients were discriminated by friends (120, 71.01% followed by discrimination at workplace (49, 67.12%, by neighbors (32, 56.14%, and by relatives (53, 43.80%. Conclusion: Male positives were granted greater acceptance, care, and support by their spouses. More percentage of females discriminated by neighbors, relatives, and friends and at workplace which might be due to factors like customs, morals, and taboos.

  17. "Human Immunodeficiency Virus serostatus disclosure-Rate, reactions, and discrimination": a cross-sectional study at a rural tertiary care hospital.

    Science.gov (United States)

    Joge, Umesh S; Deo, Deepali S; Choudhari, Sonali G; Malkar, Vilas R; Ughade, Harshada M

    2013-01-01

    From the moment scientists identified Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS), social responses of fear, denial, stigma, and discrimination have accompanied the epidemic. To assess the rate of disclosure of HIV serostatus, reactions by the HIV/AIDS patients and their spouse, and discrimination faced by the patients. The present cross-sectional study was conducted at Antiretroviral Therapy (ART) center of a rural tertiary care hospital, situated in Marathawada region of Maharashtra state from November 2008 to October 2010. Totally, 801 HIV-positive patients coming to ART center for treatment were included after ensuring confidentiality and taking informed consent. A preformed questionnaire was used to enquire about reaction after diagnosis, disclosure, and discrimination faced by the patients. The data analyzed using descriptive statistics and Chi-square test. The most common immediate reaction by the HIV patients after getting diagnosed as seropositive was fear (593, 74.03%) followed by depression (385, 48.06%) and suicidal thoughts (98, 12.25%). Out of 801 patients, 769 (96%) had spouse and of these maximum number of patients (653, 84.92%) had disclosed HIV status to their spouses. Most common immediate reaction by spouse after disclosure was crime (324, 42.13%) followed by horror (294, 38.23%) and anger (237, 36.29%). Maximum number of patients were discriminated by friends (120, 71.01%) followed by discrimination at workplace (49, 67.12%), by neighbors (32, 56.14%), and by relatives (53, 43.80%). Male positives were granted greater acceptance, care, and support by their spouses. More percentage of females discriminated by neighbors, relatives, and friends and at workplace which might be due to factors like customs, morals, and taboos.

  18. Toward Accountable Discrimination-Aware Data Mining: The Importance of Keeping the Human in the Loop-and Under the Looking Glass.

    Science.gov (United States)

    Berendt, Bettina; Preibusch, Sören

    2017-06-01

    "Big Data" and data-mined inferences are affecting more and more of our lives, and concerns about their possible discriminatory effects are growing. Methods for discrimination-aware data mining and fairness-aware data mining aim at keeping decision processes supported by information technology free from unjust grounds. However, these formal approaches alone are not sufficient to solve the problem. In the present article, we describe reasons why discrimination with data can and typically does arise through the combined effects of human and machine-based reasoning, and argue that this requires a deeper understanding of the human side of decision-making with data mining. We describe results from a large-scale human-subjects experiment that investigated such decision-making, analyzing the reasoning that participants reported during their task to assess whether a loan request should or would be granted. We derive data protection by design strategies for making decision-making discrimination-aware in an accountable way, grounding these requirements in the accountability principle of the European Union General Data Protection Regulation, and outline how their implementations can integrate algorithmic, behavioral, and user interface factors.

  19. Medical students’ perception of lesbian, gay, bisexual, and transgender (LGBT) discrimination in their learning environment and their self-reported comfort level for caring for LGBT patients: a survey study

    OpenAIRE

    Nama, Nassr; MacPherson, Paul; Sampson, Margaret; McMillan, Hugh J.

    2017-01-01

    ABSTRACT Background: Historically, medical students who are lesbian, gay, bisexual or transgendered (LGBT) report higher rates of social stress, depression, and anxiety, while LGBT patients have reported discrimination and poorer access to healthcare. Objective: The objectives of this study were: (1) to assess if medical students have perceived discrimination in their learning environment and; (2) to determine self-reported comfort level for caring for LGBT patients. Design: Medical students ...

  20. 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

  1. A multiplicative reinforcement learning model capturing learning dynamics and interindividual variability in mice

    OpenAIRE

    Bathellier, Brice; Tee, Sui Poh; Hrovat, Christina; Rumpel, Simon

    2013-01-01

    Learning speed can strongly differ across individuals. This is seen in humans and animals. Here, we measured learning speed in mice performing a discrimination task and developed a theoretical model based on the reinforcement learning framework to account for differences between individual mice. We found that, when using a multiplicative learning rule, the starting connectivity values of the model strongly determine the shape of learning curves. This is in contrast to current learning models ...

  2. 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.

  3. Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Jinhee Park

    2016-11-01

    Full Text Available Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on water using radar has not been extensively studied, unlike the case on dry ground, due to its unique challenge. Namely, not only is the radar cross section of a human on water small, but the micro-Doppler signatures are much noisier due to water drops and waves. In this paper, we first investigate whether discriminative signatures could be obtained for activities on water through a simulation study. Then, we show how we can effectively achieve high classification accuracy by applying deep convolutional neural networks (DCNN directly to the spectrogram of real measurement data. From the five-fold cross-validation on our dataset, which consists of five aquatic activities, we report that the conventional feature-based scheme only achieves an accuracy of 45.1%. In contrast, the DCNN trained using only the collected data attains 66.7%, and the transfer learned DCNN, which takes a DCNN pre-trained on a RGB image dataset and fine-tunes the parameters using the collected data, achieves a much higher 80.3%, which is a significant performance boost.

  4. Mass discrimination

    Energy Technology Data Exchange (ETDEWEB)

    Broeckman, A. [Rijksuniversiteit Utrecht (Netherlands)

    1978-12-15

    In thermal ionization mass spectrometry the phenomenon of mass discrimination has led to the use of a correction factor for isotope ratio-measurements. The correction factor is defined as the measured ratio divided by the true or accepted value of this ratio. In fact this factor corrects for systematic errors of the whole procedure; however mass discrimination is often associated just with the mass spectrometer.

  5. 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)

  6. 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)

  7. How discriminating are discriminative instruments?

    Science.gov (United States)

    Hankins, Matthew

    2008-05-27

    The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL). The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness), but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta) is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

  8. How discriminating are discriminative instruments?

    Directory of Open Access Journals (Sweden)

    Hankins Matthew

    2008-05-01

    Full Text Available Abstract The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL. The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness, but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

  9. 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…

  10. 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.

  11. 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.

  12. 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…

  13. 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…

  14. 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

  15. 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.

  16. Separate and combined effects of the cannabinoid agonists nabilone and Δ⁹-THC in humans discriminating Δ⁹-THC.

    Science.gov (United States)

    Lile, Joshua A; Kelly, Thomas H; Hays, Lon R

    2011-07-01

    Agonist replacement treatment is a promising strategy to manage cannabis-use disorders. The aim of this study was to assess the combined effects of the synthetic cannabinoid agonist nabilone and Δ⁹-tetrahydrocannabinol (Δ⁹-THC) using drug-discrimination procedures, which are sensitive to drug interactions. Testing the concurrent administration of nabilone and Δ⁹-THC was also conducted to provide initial safety and tolerability data, which is important because cannabis users will likely lapse during treatment. Six cannabis users learned to discriminate 30 mg oral Δ⁹-THC from placebo and then received nabilone (0, 1 and 3mg) and Δ⁹-THC (0, 5, 15 and 30 mg), alone and in combination. Subjects completed the multiple-choice procedure to assess drug reinforcement, and self-report, task performance and physiological measures were collected. Δ⁹-THC and nabilone alone shared discriminative-stimulus effects with the training dose of Δ⁹-THC, increased crossover point on the multiple-choice procedure, produced overlapping subject ratings and decreased skin temperature. Nabilone alone also elevated heart rate. In combination, nabilone shifted the discriminative-stimulus effects of Δ⁹-THC leftward/upward and enhanced Δ⁹-THC effects on the other outcome measures. These results replicate a previous study demonstrating that nabilone shares agonist effects with the active constituent of cannabis in cannabis users, and contribute further by indicating that nabilone would likely be safe and well tolerated when combined with cannabis. These data support the conduct of future studies to determine if nabilone treatment would produce cross-tolerance to the abuse-related effects of cannabis and reduce cannabis use. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  17. 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...

  18. Non-discrimination and equality of women

    NARCIS (Netherlands)

    Oostland, Rolanda Carina

    2006-01-01

    Non-discrimination is considered to be a cornerstone of the human rights framework of the United Nations. Already in the UN Charter of 1945 it is stated that human rights should be promoted without discrimination as to, amongst other things, sex. This principle of non-discrimination on the ground of

  19. 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.

  20. 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."

  1. 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.

  2. Associations and propositions: the case for a dual-process account of learning in humans.

    Science.gov (United States)

    McLaren, I P L; Forrest, C L D; McLaren, R P; Jones, F W; Aitken, M R F; Mackintosh, N J

    2014-02-01

    We review evidence that supports the conclusion that people can and do learn in two distinct ways - one associative, the other propositional. No one disputes that we solve problems by testing hypotheses and inducing underlying rules, so the issue amounts to deciding whether there is evidence that we (and other animals) also rely on a simpler, associative system, that detects the frequency of occurrence of different events in our environment and the contingencies between them. There is neuroscientific evidence that associative learning occurs in at least some animals (e.g., Aplysia californica), so it must be the case that associative learning has evolved. Since both associative and propositional theories can in principle account for many instances of successful learning, the problem is then to show that there are at least some cases where the two classes of theory predict different outcomes. We offer a demonstration of cue competition effects in humans under incidental conditions as evidence against the argument that all such effects are based on cognitive inference. The latter supposition would imply that if the necessary information is unavailable to inference then no cue competition should occur. We then discuss the case of unblocking by reinforcer omission, where associative theory predicts an irrational solution to the problem, and consider the phenomenon of the Perruchet effect, in which conscious expectancy and conditioned response dissociate. Further discussion makes use of evidence that people will sometimes provide one solution to a problem when it is presented to them in summary form, and another when they are presented in rapid succession with trial-by trial information. We also demonstrate that people trained on a discrimination may show a peak shift (predicted by associative theory), but given the time and opportunity to detect the relationships between S+ and S-, show rule-based behavior instead. Finally, we conclude by presenting evidence that

  3. Discrimination in Employment

    Science.gov (United States)

    Abzug, Bella

    1975-01-01

    This testimony, before a public hearing of the New York City Commission on Human Rights in May 1974, expressly focuses on discrimination in employment, asserting that this has had the most direct effect on minorities and women in the country; while legal protections have grown stronger, they have not been used effectively. (Author/JM)

  4. Varieties of perceptual learning.

    Science.gov (United States)

    Mackintosh, N J

    2009-05-01

    Although most studies of perceptual learning in human participants have concentrated on the changes in perception assumed to be occurring, studies of nonhuman animals necessarily measure discrimination learning and generalization and remain agnostic on the question of whether changes in behavior reflect changes in perception. On the other hand, animal studies do make it easier to draw a distinction between supervised and unsupervised learning. Differential reinforcement will surely teach animals to attend to some features of a stimulus array rather than to others. But it is an open question as to whether such changes in attention underlie the enhanced discrimination seen after unreinforced exposure to such an array. I argue that most instances of unsupervised perceptual learning observed in animals (and at least some in human animals) are better explained by appeal to well-established principles and phenomena of associative learning theory: excitatory and inhibitory associations between stimulus elements, latent inhibition, and habituation.

  5. Human detection and discrimination of tactile repeatability, mechanical backlash, and temporal delay in a combined tactile-kinesthetic haptic display system.

    Science.gov (United States)

    Doxon, Andrew J; Johnson, David E; Tan, Hong Z; Provancher, William R

    2013-01-01

    Many of the devices used in haptics research are over-engineered for the task and are designed with capabilities that go far beyond human perception levels. Designing devices that more closely match the limits of human perception will make them smaller, less expensive, and more useful. However, many device-centric perception thresholds have yet to be evaluated. To this end, three experiments were conducted, using one degree-of-freedom contact location feedback device in combination with a kinesthetic display, to provide a more explicit set of specifications for similar tactile-kinesthetic haptic devices. The first of these experiments evaluated the ability of humans to repeatedly localize tactile cues across the fingerpad. Subjects could localize cues to within 1.3 mm and showed bias toward the center of the fingerpad. The second experiment evaluated the minimum perceptible difference of backlash at the tactile element. Subjects were able to discriminate device backlash in excess of 0.46 mm on low-curvature models and 0.93 mm on high-curvature models. The last experiment evaluated the minimum perceptible difference of system delay between user action and device reaction. Subjects were able to discriminate delays in excess of 61 ms. The results from these studies can serve as the maximum (i.e., most demanding) device specifications for most tactile-kinesthetic haptic systems.

  6. 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.

  7. The effects of incidentally learned temporal and spatial predictability on response times and visual fixations during target detection and discrimination.

    Directory of Open Access Journals (Sweden)

    Melissa R Beck

    Full Text Available Responses are quicker to predictable stimuli than if the time and place of appearance is uncertain. Studies that manipulate target predictability often involve overt cues to speed up response times. However, less is known about whether individuals will exhibit faster response times when target predictability is embedded within the inter-trial relationships. The current research examined the combined effects of spatial and temporal target predictability on reaction time (RT and allocation of overt attention in a sustained attention task. Participants responded as quickly as possible to stimuli while their RT and eye movements were measured. Target temporal and spatial predictability were manipulated by altering the number of: 1 different time intervals between a response and the next target; and 2 possible spatial locations of the target. The effects of target predictability on target detection (Experiment 1 and target discrimination (Experiment 2 were tested. For both experiments, shorter RTs as target predictability increased across both space and time were found. In addition, the influences of spatial and temporal target predictability on RT and the overt allocation of attention were task dependent; suggesting that effective orienting of attention relies on both spatial and temporal predictability. These results indicate that stimulus predictability can be increased without overt cues and detected purely through inter-trial relationships over the course of repeated stimulus presentations.

  8. 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...

  9. 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.

  10. Theta-burst stimulation-induced plasticity over primary somatosensory cortex changes somatosensory temporal discrimination in healthy humans.

    Directory of Open Access Journals (Sweden)

    Antonella Conte

    Full Text Available BACKGROUND: The somatosensory temporal discrimination threshold (STDT measures the ability to perceive two stimuli as being sequential. Precisely how the single cerebral structures contribute in controlling the STDT is partially known and no information is available about whether STDT can be modulated by plasticity-inducing protocols. METHODOLOGY/PRINCIPAL FINDINGS: To investigate how the cortical and cerebellar areas contribute to the STDT we used transcranial magnetic stimulation and a neuronavigation system. We enrolled 18 healthy volunteers and 10 of these completed all the experimental sessions, including the control experiments. STDT was measured on the left hand before and after applying continuous theta-burst stimulation (cTBS on the right primary somatosensory area (S1, pre-supplementary motor area (pre-SMA, right dorsolateral prefrontal cortex (DLPFC and left cerebellar hemisphere. We then investigated whether intermittent theta-burst stimulation (iTBS on the right S1 improved the STDT. After right S1 cTBS, STDT values increased whereas after iTBS to the same cortical site they decreased. cTBS over the DLPFC and left lateral cerebellum left the STDT statistically unchanged. cTBS over the pre-SMA also left the STDT statistically unchanged, but it increased the number of errors subjects made in distinguishing trials testing a single stimulus and those testing paired stimuli. CONCLUSIONS/SIGNIFICANCE: Our findings obtained by applying TBS to the cortical areas involved in processing sensory discrimination show that the STDT is encoded in S1, possibly depends on intrinsic S1 neural circuit properties, and can be modulated by plasticity-inducing TBS protocols delivered over S1. Our findings, giving further insight into mechanisms involved in somatosensory temporal discrimination, help interpret STDT abnormalities in movement disorders including dystonia and Parkinson's disease.

  11. Theta-Burst Stimulation-Induced Plasticity over Primary Somatosensory Cortex Changes Somatosensory Temporal Discrimination in Healthy Humans

    Science.gov (United States)

    Conte, Antonella; Rocchi, Lorenzo; Nardella, Andrea; Dispenza, Sabrina; Scontrini, Alessandra; Khan, Nashaba; Berardelli, Alfredo

    2012-01-01

    Background The somatosensory temporal discrimination threshold (STDT) measures the ability to perceive two stimuli as being sequential. Precisely how the single cerebral structures contribute in controlling the STDT is partially known and no information is available about whether STDT can be modulated by plasticity-inducing protocols. Methodology/Principal Findings To investigate how the cortical and cerebellar areas contribute to the STDT we used transcranial magnetic stimulation and a neuronavigation system. We enrolled 18 healthy volunteers and 10 of these completed all the experimental sessions, including the control experiments. STDT was measured on the left hand before and after applying continuous theta-burst stimulation (cTBS) on the right primary somatosensory area (S1), pre-supplementary motor area (pre-SMA), right dorsolateral prefrontal cortex (DLPFC) and left cerebellar hemisphere. We then investigated whether intermittent theta-burst stimulation (iTBS) on the right S1 improved the STDT. After right S1 cTBS, STDT values increased whereas after iTBS to the same cortical site they decreased. cTBS over the DLPFC and left lateral cerebellum left the STDT statistically unchanged. cTBS over the pre-SMA also left the STDT statistically unchanged, but it increased the number of errors subjects made in distinguishing trials testing a single stimulus and those testing paired stimuli. Conclusions/Significance Our findings obtained by applying TBS to the cortical areas involved in processing sensory discrimination show that the STDT is encoded in S1, possibly depends on intrinsic S1 neural circuit properties, and can be modulated by plasticity-inducing TBS protocols delivered over S1. Our findings, giving further insight into mechanisms involved in somatosensory temporal discrimination, help interpret STDT abnormalities in movement disorders including dystonia and Parkinson's disease. PMID:22412964

  12. 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.

  13. 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…

  14. 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

  15. 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…

  16. 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…

  17. Comparison of learning ability and memory retention in altricial (Bengalese finch, Lonchura striata var. domestica) and precocial (blue-breasted quail, Coturnix chinensis) birds using a color discrimination task.

    Science.gov (United States)

    Ueno, Aki; Suzuki, Kaoru

    2014-02-01

    The present study sought to assess the potential application of avian models with different developmental modes to studies on cognition and neuroscience. Six altricial Bengalese finches (Lonchura striata var. domestica), and eight precocial blue-breasted quails (Coturnix chinensis) were presented with color discrimination tasks to compare their respective faculties for learning and memory retention within the context of the two developmental modes. Tasks consisted of presenting birds with discriminative cues in the form of colored feeder lids, and birds were considered to have learned a task when 80% of their attempts at selecting the correctly colored lid in two consecutive blocks of 10 trials were successful. All of the finches successfully performed the required experimental tasks, whereas only half of the quails were able to execute the same tasks. In the learning test, finches required significantly fewer trials than quails to learn the task (finches: 13.5 ± 9.14 trials, quails: 45.8 ± 4.35 trials, P memory retention tests, which were conducted 45 days after the learning test, finches retained the ability to discriminate between colors correctly (95.0 ± 4.47%), whereas quails did not retain any memory of the experimental procedure and so could not be tested. These results suggested that altricial and precocial birds both possess the faculty for learning and retaining discrimination-type tasks, but that altricial birds perform better than precocial birds in both faculties. The present findings imply that developmental mode is an important consideration for assessing the suitability of bird species for particular experiments. © 2013 Japanese Society of Animal Science.

  18. 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

  19. 45 CFR 1151.21 - Discrimination prohibited.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 3 2010-10-01 2010-10-01 false Discrimination prohibited. 1151.21 Section 1151.21... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination Prohibited Accessibility § 1151.21 Discrimination prohibited. No qualified handicapped person shall, because...

  20. 45 CFR 1110.3 - Discrimination prohibited.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 3 2010-10-01 2010-10-01 false Discrimination prohibited. 1110.3 Section 1110.3... HUMANITIES GENERAL NONDISCRIMINATION IN FEDERALLY ASSISTED PROGRAMS § 1110.3 Discrimination prohibited. (a... from participation in, be denied the benefits of, or be otherwise subjected, to discrimination under...

  1. 45 CFR 1151.31 - Discrimination prohibited.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 3 2010-10-01 2010-10-01 false Discrimination prohibited. 1151.31 Section 1151.31... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination Prohibited Employment § 1151.31 Discrimination prohibited. (a) No qualified handicapped person shall, on the...

  2. The use of discriminant analysis for evaluation of early-response multiple biomarkers of radiation exposure using non-human primate 6-Gy whole-body radiation model

    Energy Technology Data Exchange (ETDEWEB)

    Ossetrova, N.I. [Armed Forces Radiobiology Research Institute, 8901 Wisconsin Avenue, Bethesda, MD 20889-5603 (United States)], E-mail: ossetrova@afrri.usuhs.mil; Farese, A.M.; MacVittie, T.J. [Marlene and Stewart Greenebaum Cancer Center, Bressler Research Building, Room 7-039, University of Maryland-Baltimore, 655 West Baltimore Street, Baltimore, MD 21201 (United States); Manglapus, G.L.; Blakely, W.F. [Armed Forces Radiobiology Research Institute, 8901 Wisconsin Avenue, Bethesda, MD 20889-5603 (United States)

    2007-07-15

    The present need to rapidly identify severely irradiated individuals in mass-casualty and population-monitoring scenarios prompted an evaluation of potential protein biomarkers to provide early diagnostic information after exposure. The level of specific proteins measured using immunodiagnostic technologies may be useful as protein biomarkers to provide early diagnostic information for acute radiation exposures. Herein we present results from on-going studies using a non-human primate (NHP) 6-Gy X-rays ( 0.13Gymin{sup -1}) whole-body radiation model. Protein targets were measured by enzyme-linked immunosorbent assay (ELISA) in blood plasma before, 1, and 2 days after exposure. Exposure of 10 NHPs to 6 Gy resulted in the up-regulation of plasma levels of (a) p21 WAF1/CIP1, (b) interleukin 6 (IL-6), (c) tissue enzyme salivary {alpha}-amylase, and (d) C-reactive protein. Data presented show the potential utility of protein biomarkers selected from distinctly different pathways to detect radiation exposure. A correlation analysis demonstrated strong correlations among different combinations of four candidate radiation-responsive blood protein biomarkers. Data analyzed with use of multivariate discriminant analysis established very successful separation of NHP groups: 100% discrimination power for animals with correct classification for separation between groups before and 1 day after irradiation, and 95% discrimination power for separation between groups before and 2 days after irradiation. These results also demonstrate proof-in-concept that multiple protein biomarkers provide early diagnostic information to the medical community, along with classical biodosimetric methodologies, to effectively manage radiation casualty incidents.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. Selected Gray Matter Volumes and Gender but Not Basal Ganglia nor Cerebellum Gyri Discriminate Left Versus Right Cerebral Hemispheres: Multivariate Analyses in human Brains at 3T.

    Science.gov (United States)

    Roldan-Valadez, Ernesto; Suarez-May, Marcela A; Favila, Rafael; Aguilar-Castañeda, Erika; Rios, Camilo

    2015-07-01

    Interest in the lateralization of the human brain is evident through a multidisciplinary number of scientific studies. Understanding volumetric brain asymmetries allows the distinction between normal development stages and behavior, as well as brain diseases. We aimed to evaluate volumetric asymmetries in order to select the best gyri able to classify right- versus left cerebral hemispheres. A cross-sectional study performed in 47 right-handed young-adults healthy volunteers. SPM-based software performed brain segmentation, automatic labeling and volumetric analyses for 54 regions involving the cerebral lobes, basal ganglia and cerebellum from each cerebral hemisphere. Multivariate discriminant analysis (DA) allowed the assembling of a predictive model. DA revealed one discriminant function that significantly differentiated left vs. right cerebral hemispheres: Wilks' λ = 0.008, χ(2) (9) = 238.837, P brain gyri are able to accurately classify left vs. right cerebral hemispheres by using a multivariate approach; the selected regions correspond to key brain areas involved in attention, internal thought, vision and language; our findings favored the concept that lateralization has been evolutionary favored by mental processes increasing cognitive efficiency and brain capacity. © 2015 Wiley Periodicals, Inc.

  8. 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 ...

  9. 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,...

  10. Medical students’ perception of lesbian, gay, bisexual, and transgender (LGBT) discrimination in their learning environment and their self-reported comfort level for caring for LGBT patients: a survey study

    Science.gov (United States)

    Nama, Nassr; MacPherson, Paul; Sampson, Margaret; McMillan, Hugh J.

    2017-01-01

    ABSTRACT Background: Historically, medical students who are lesbian, gay, bisexual or transgendered (LGBT) report higher rates of social stress, depression, and anxiety, while LGBT patients have reported discrimination and poorer access to healthcare. Objective: The objectives of this study were: (1) to assess if medical students have perceived discrimination in their learning environment and; (2) to determine self-reported comfort level for caring for LGBT patients. Design: Medical students at the University of Ottawa (N = 671) were contacted via email and invited to complete a confidential web-based survey. Results: Response rate was 15.4% (103/671). This included 66 cis-gender heterosexuals (64.1%) and 37 LGBT students (35.9%). Anti-LGBT discrimination had been witnessed by 14.6% and heterosexism by 31.1% of respondents. Anti-LGBT discrimination most often originated from fellow medical students. Respondents who self-identified as LGBT were more likely to have perceived heterosexism (favoring opposite-sex relationships) (OR = 8.2, p LGBT discrimination (OR = 6.6, p = 0.002). While half of LGBT students shared their status with all classmates (51.4%), they were more likely to conceal this from staff physicians (OR = 27.2, p = 0.002). Almost half of medical students (41.7%) reported anti-LGBT jokes, rumors, and/or bullying by fellow medical students and/or other members of the healthcare team. Still, most respondents indicated that they felt comfortable with and capable of providing medical care to LGBT patients (≥83.5%), and were interested in further education around LGBT health issues (84.5%). Conclusion: Anti-LGBT discrimination and heterosexism are noted by medical students, indicating a suboptimal learning environment for LGBT students. Nonetheless, students report a high level of comfort and confidence providing health care to LGBT patients. PMID:28853327

  11. Medical students' perception of lesbian, gay, bisexual, and transgender (LGBT) discrimination in their learning environment and their self-reported comfort level for caring for LGBT patients: a survey study.

    Science.gov (United States)

    Nama, Nassr; MacPherson, Paul; Sampson, Margaret; McMillan, Hugh J

    2017-01-01

    Historically, medical students who are lesbian, gay, bisexual or transgendered (LGBT) report higher rates of social stress, depression, and anxiety, while LGBT patients have reported discrimination and poorer access to healthcare. The objectives of this study were: (1) to assess if medical students have perceived discrimination in their learning environment and; (2) to determine self-reported comfort level for caring for LGBT patients. Medical students at the University of Ottawa (N = 671) were contacted via email and invited to complete a confidential web-based survey. Response rate was 15.4% (103/671). This included 66 cis-gender heterosexuals (64.1%) and 37 LGBT students (35.9%). Anti-LGBT discrimination had been witnessed by 14.6% and heterosexism by 31.1% of respondents. Anti-LGBT discrimination most often originated from fellow medical students. Respondents who self-identified as LGBT were more likely to have perceived heterosexism (favoring opposite-sex relationships) (OR = 8.2, p LGBT discrimination (OR = 6.6, p = 0.002). While half of LGBT students shared their status with all classmates (51.4%), they were more likely to conceal this from staff physicians (OR = 27.2, p = 0.002). Almost half of medical students (41.7%) reported anti-LGBT jokes, rumors, and/or bullying by fellow medical students and/or other members of the healthcare team. Still, most respondents indicated that they felt comfortable with and capable of providing medical care to LGBT patients (≥83.5%), and were interested in further education around LGBT health issues (84.5%). Anti-LGBT discrimination and heterosexism are noted by medical students, indicating a suboptimal learning environment for LGBT students. Nonetheless, students report a high level of comfort and confidence providing health care to LGBT patients.

  12. 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.

  13. 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.

  14. 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

  15. 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....

  16. 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.

  17. Multimodal optical analysis discriminates freshly extracted human sample of gliomas, metastases and meningiomas from their appropriate controls

    Science.gov (United States)

    Zanello, Marc; Poulon, Fanny; Pallud, Johan; Varlet, Pascale; Hamzeh, H.; Abi Lahoud, Georges; Andreiuolo, Felipe; Ibrahim, Ali; Pages, Mélanie; Chretien, Fabrice; di Rocco, Federico; Dezamis, Edouard; Nataf, François; Turak, Baris; Devaux, Bertrand; Abi Haidar, Darine

    2017-02-01

    Delineating tumor margins as accurately as possible is of primordial importance in surgical oncology: extent of resection is associated with survival but respect of healthy surrounding tissue is necessary for preserved quality of life. The real-time analysis of the endogeneous fluorescence signal of brain tissues is a promising tool for defining margins of brain tumors. The present study aims to demonstrate the feasibility of multimodal optical analysis to discriminate fresh samples of gliomas, metastases and meningiomas from their appropriate controls. Tumor samples were studied on an optical fibered endoscope using spectral and fluorescence lifetime analysis and then on a multimodal set-up for acquiring spectral, one and two-photon fluorescence images, second harmonic generation signals and two-photon fluorescence lifetime datasets. The obtained data allowed us to differentiate healthy samples from tumor samples. These results confirmed the possible clinical relevance of this real-time multimodal optical analysis. This technique can be easily applied to neurosurgical procedures for a better delineation of surgical margins.

  18. An Endogenous Electron Spin Resonance (ESR signal discriminates nevi from melanomas in human specimens: a step forward in its diagnostic application.

    Directory of Open Access Journals (Sweden)

    Eleonora Cesareo

    Full Text Available Given the specific melanin-associated paramagnetic features, the Electron Spin Resonance (ESR, called also Electron Paramagnetic Resonance, EPR analysis has been proposed as a potential tool for non-invasive melanoma diagnosis. However, studies comparing human melanoma tissues to the most appropriate physiological counterpart (nevi have not been performed, and ESR direct correlation with melanoma clinical features has never been investigated. ESR spectrum was obtained from melanoma and non-melanoma cell-cultures as well as mouse melanoma and non-melanoma tissues and an endogenous ESR signal (g = 2.005 was found in human melanoma cells and in primary melanoma tissues explanted from mice, while it was always absent in non-melanoma samples. These characteristics of the measured ESR signal strongly suggested its connection with melanin. Quantitative analyses were then performed on paraffin-embedded human melanoma and nevus sections, and validated on an independent larger validation set, for a total of 112 sections (52 melanomas, 60 nevi. The ESR signal was significantly higher in melanomas (p = 0.0002 and was significantly different between "Low Breslow's and "High Breslow's" depth melanomas (p<0.0001. A direct correlation between ESR signal and Breslow's depth, expressed in millimetres, was found (R = 0.57; p<0.0001. The eu/pheomelanin ratio was found to be significantly different in melanomas "Low Breslow's" vs melanomas "High Breslow's" depth and in nevi vs melanomas "High Breslow's depth". Finally, ROC analysis using ESR data discriminated melanomas sections from nevi sections with up to 90% accuracy and p<0.0002. In the present study we report for the first time that ESR signal in human paraffin-embedded nevi is significantly lower than signal in human melanomas suggesting that spectrum variations may be related to qualitative melanin differences specifically occurring in melanoma cells. We therefore conclude that this ESR signal

  19. 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,…

  20. 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.

  1. Allele specific hybridization using oligonucleotide probes of very high specific activity: Discrimination of the human β/sup A/ and β/sup S/-globin genes

    International Nuclear Information System (INIS)

    Studencki, A.B.; Wallace, R.B.

    1984-01-01

    The repair activity of E. coli DNA polymerase I (Klenow fragment) was used to prepare nonadecanucleotide hybridization probes which were complementary either to the normal human β-globin (β/sup A/) or to the sickle cell human β-globin (β/sup S/) gene. Template directed polymerization of highly radiolabeled α-/sup 32/P-deoxyribonucleoside triphosphates (3200, 5000 and/or 7800 Ci/mmol) onto nonamer and decamer primers produced probes with specific activities ranging from 1.0 - 2.0 x 10/sup 10/ dpm/μg. The extremely high specific activities of these probes made it possible to detect the β/sup A/ and β/sup S/ single copy gene sequences in as little as 1 μg of total human genomic DNA as well as to discriminate between the homozygous and heterozygous states. This means that it was possible to detect 0.5 - 1.0 x 10/sup -18/ moles of a given single copy sequence

  2. 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…

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Discrimination of Rhythmic Pattern at 4 Months and Language Performance at 5 Years: A Longitudinal Analysis of Data from German-Learning Children

    Science.gov (United States)

    Höhle, Barbara; Pauen, Sabina; Hesse, Volker; Weissenborn, Jürgen

    2014-01-01

    In this article we report on early rhythmic discrimination performance of children who participated in a longitudinal study following children from birth to their 6th year of life. Thirty-four children including 8 children with a family risk for developmental language impairment were tested on the discrimination of trochaic and iambic disyllabic…

  11. Legal Provisions, Discrimination and Uncertainty on LGBT community in Albania. Laws on human rights vs exerted rights of LGBT persons

    OpenAIRE

    Urjana Curi

    2018-01-01

    During the communist regime and until 1995 homosexual relations were senteced by law in Albania as a criminal offense. Membership in the Council of Europe and the ratification of the European Convention on Human Rights brought as a result the improvement of the legal framework and the abolition of the condemnation of homosexual relations. The first attempts of activism were shown in the form of meetings on joint activities organized by the Gay community in public spaces or cruising areas. In ...

  12. Data preprocessing techniques for classification without discrimination

    NARCIS (Netherlands)

    Kamiran, F.; Calders, T.G.K.

    2012-01-01

    Recently, the following Discrimination-Aware Classification Problem was introduced: Suppose we are given training data that exhibit unlawful discrimination; e.g., toward sensitive attributes such as gender or ethnicity. The task is to learn a classifier that optimizes accuracy, but does not have

  13. Pattern recognition in bees : orientation discrimination

    NARCIS (Netherlands)

    Hateren, J.H. van; Srinivasan, M.V.; Wait, P.B.

    1990-01-01

    Honey bees (Apis mellifera, worker) were trained to discriminate between two random gratings oriented perpendicularly to each other. This task was quickly learned with vertical, horizontal, and oblique gratings. After being trained on perpendicularly-oriented random gratings, bees could discriminate

  14. Effects of differential postnatal exposure of the rat cerebellum to x-rays on spatial discrimination learning as a function of age and position preference

    International Nuclear Information System (INIS)

    Peters, K.B.

    1979-01-01

    The aim of the present research was to analyze the effects of postnatal exposure of the cerebellum to x-irradiation on the use of proprioceptive feedback in spatial learning. A total of 337 naive male Long-Evans hooded rats were assigned at birth to one of four treatments: 12-15x, 4-5x, 4-15x and control. Subjects assigned to the 12-15x treatment were exposed to 200R at 12 and 13 days of age, and to 150R at 15 days of age. The subjects exposed to the 4-5x schedule received 200R on days 4 and 5. The 4-15x subjects are exposed to 200R on days 4 and 5, and to 150R on days 7, 9, 11, 13, 15. Subjects from each treatment started spatial discrimination testing in a T-shaped water maze at 30 to 31, 60 to 63, or 180 to 185 days of age. A preference effect was evident in the control, 12-15x and 4-5x subjects, but not in the 4-15x subjects during acquisition testing. Those control, 12-15x and 4-5x subjects trained against their preference made more errors and required more trials to attain acquisition criterion than did those subjects trained toward their preference. The absence of a position preference in the 4-15x subjects is attributed to the absence of the mossy fiber channel of input to the Purkinje cells in this preparation. Deficits in spatial learning were evident in both the 12-15x and 4-15x subjects, the former differing significantly from control subjects and the latter from the 4-5x subjects in the number of trials needed to complete reversal testing and/or the number of errors made during this phase of the testing. It is the upper portion of the molecular layer, absent in the 12-15x and 4-15x preparations, which receives afferent input from the spinal cord

  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. Large number discrimination by mosquitofish.

    Directory of Open Access Journals (Sweden)

    Christian Agrillo

    Full Text Available BACKGROUND: Recent studies have demonstrated that fish display rudimentary numerical abilities similar to those observed in mammals and birds. The mechanisms underlying the discrimination of small quantities (<4 were recently investigated while, to date, no study has examined the discrimination of large numerosities in fish. METHODOLOGY/PRINCIPAL FINDINGS: Subjects were trained to discriminate between two sets of small geometric figures using social reinforcement. In the first experiment mosquitofish were required to discriminate 4 from 8 objects with or without experimental control of the continuous variables that co-vary with number (area, space, density, total luminance. Results showed that fish can use the sole numerical information to compare quantities but that they preferentially use cumulative surface area as a proxy of the number when this information is available. A second experiment investigated the influence of the total number of elements to discriminate large quantities. Fish proved to be able to discriminate up to 100 vs. 200 objects, without showing any significant decrease in accuracy compared with the 4 vs. 8 discrimination. The third experiment investigated the influence of the ratio between the numerosities. Performance was found to decrease when decreasing the numerical distance. Fish were able to discriminate numbers when ratios were 1:2 or 2:3 but not when the ratio was 3:4. The performance of a sample of undergraduate students, tested non-verbally using the same sets of stimuli, largely overlapped that of fish. CONCLUSIONS/SIGNIFICANCE: Fish are able to use pure numerical information when discriminating between quantities larger than 4 units. As observed in human and non-human primates, the numerical system of fish appears to have virtually no upper limit while the numerical ratio has a clear effect on performance. These similarities further reinforce the view of a common origin of non-verbal numerical systems in all

  17. 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

  18. 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…

  19. 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…

  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

    2016-01-01

    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…

  1. 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…

  2. 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

  3. Efficiency of PCR-based methods in discriminating Bifidobacterium longum ssp. longum and Bifidobacterium longum ssp. infantis strains of human origin.

    Science.gov (United States)

    Srůtková, Dagmar; Spanova, Alena; Spano, Miroslav; Dráb, Vladimír; Schwarzer, Martin; Kozaková, Hana; Rittich, Bohuslav

    2011-10-01

    Bifidobacterium longum is considered to play an important role in health maintenance of the human gastrointestinal tract. Probiotic properties of bifidobacterial isolates are strictly strain-dependent and reliable methods for the identification and discrimination of this species at both subspecies and strain levels are thus required. Differentiation between B. longum ssp. longum and B. longum ssp. infantis is difficult due to high genomic similarities. In this study, four molecular-biological methods (species- and subspecies-specific PCRs, random amplified polymorphic DNA (RAPD) method using 5 primers, repetitive sequence-based (rep)-PCR with BOXA1R and (GTG)(5) primers and amplified ribosomal DNA restriction analysis (ARDRA)) and biochemical analysis, were compared for the classification of 30 B. longum strains (28 isolates and 2 collection strains) on subspecies level. Strains originally isolated from the faeces of breast-fed healthy infants (25) and healthy adults (3) showed a high degree of genetic homogeneity by PCR with subspecies-specific primers and rep-PCR. When analysed by RAPD, the strains formed many separate clusters without any potential for subspecies discrimination. These methods together with arabionose/melezitose fermentation analysis clearly differentiated only the collection strains into B. longum ssp. longum and B. longum ssp. infantis at the subspecies level. On the other hand, ARDRA analysis differentiated the strains into the B. longum/infantis subspecies using the cleavage analysis of genus-specific amplicon with just one enzyme, Sau3AI. According to our results the majority of the strains belong to the B. longum ssp. infantis (75%). Therefore we suggest ARDRA using Sau3AI restriction enzyme as the first method of choice for distinguishing between B. longum ssp. longum and B. longum ssp. infantis. Copyright © 2011 Elsevier B.V. All rights reserved.

  4. Genetic Discrimination

    Science.gov (United States)

    ... Care Genomic Medicine Working Group New Horizons and Research Patient Management Policy and Ethics Issues Quick Links for Patient Care Education All About the Human Genome Project Fact Sheets Genetic Education Resources for ...

  5. 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…

  6. 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…

  7. 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…

  8. 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

  9. 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.

  10. Decision theory for discrimination-aware classification

    KAUST Repository

    Kamiran, Faisal; Karim, Asim A.; Zhang, Xiangliang

    2012-01-01

    Social discrimination (e.g., against females) arising from data mining techniques is a growing concern worldwide. In recent years, several methods have been proposed for making classifiers learned over discriminatory data discriminationaware

  11. Fighting discrimination.

    Science.gov (United States)

    Wientjens, Wim; Cairns, Douglas

    2012-10-01

    In the fight against discrimination, the IDF launched the first ever International Charter of Rights and Responsibilities of People with Diabetes in 2011: a balance between rights and duties to optimize health and quality of life, to enable as normal a life as possible and to reduce/eliminate the barriers which deny realization of full potential as members of society. It is extremely frustrating to suffer blanket bans and many examples exist, including insurance, driving licenses, getting a job, keeping a job and family affairs. In this article, an example is given of how pilots with insulin treated diabetes are allowed to fly by taking the responsibility of using special blood glucose monitoring protocols. At this time the systems in the countries allowing flying for pilots with insulin treated diabetes are applauded, particularly the USA for private flying, and Canada for commercial flying. Encouraging developments may be underway in the UK for commercial flying and, if this materializes, could be used as an example for other aviation authorities to help adopt similar protocols. However, new restrictions implemented by the new European Aviation Authority take existing privileges away for National Private Pilot Licence holders with insulin treated diabetes in the UK. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  12. A study on the discrimination of human skeletons using X-ray fluorescence and chemometric tools in chemical anthropology.

    Science.gov (United States)

    Gonzalez-Rodriguez, J; Fowler, G

    2013-09-10

    Forensic anthropological investigations are often restricted in their outcomes by the resources allocated to them, especially in terms of positively identifying the victims exhumed from commingled mass graves. Commingled mass graves can be defined as those graves that contain a number of disarticulated human remains from different individuals that have been mixed by either natural processes or human interventions. The research developed aimed to apply the technique of non-destructive XRF analysis to test whether there is substantial differentiation within the trace elemental composition and their ratios of individuals to separate them using chemometric analysis. The results of the different atomic spectroscopic analyses combined with the use of multivariate analysis on a set of 5 skeletons produced a series of plots using Principal Component Analysis that helped to separate them with a high percentage of accuracy when two, three or four skeletons needed to be separated. Also, two new elemental ratios, Zn/Fe related to metabolic activities and K/Fe related to blood flow into the bone, have been defined for their use in forensic anthropology for the first time to aid in the separation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  13. Discrimination of skin sensitizers from non-sensitizers by interleukin-1α and interleukin-6 production on cultured human keratinocytes.

    Science.gov (United States)

    Jung, Daun; Che, Jeong-Hwan; Lim, Kyung-Min; Chun, Young-Jin; Heo, Yong; Seok, Seung Hyeok

    2016-09-01

    In vitro testing methods for classifying sensitizers could be valuable alternatives to in vivo sensitization testing using animal models, such as the murine local lymph node assay (LLNA) and the guinea pig maximization test (GMT), but there remains a need for in vitro methods that are more accurate and simpler to distinguish skin sensitizers from non-sensitizers. Thus, the aim of our study was to establish an in vitro assay as a screening tool for detecting skin sensitizers using the human keratinocyte cell line, HaCaT. HaCaT cells were exposed to 16 relevant skin sensitizers and 6 skin non-sensitizers. The highest dose used was the dose causing 75% cell viability (CV75) that we determined by an MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assay. The levels of extracellular production of interleukin-1α (IL-1α) and IL-6 were measured. The sensitivity of IL-1α was 63%, specificity was 83% and accuracy was 68%. In the case of IL-6, sensitivity: 69%, specificity: 83% and accuracy: 73%. Thus, this study suggests that measuring extracellular production of pro-inflammatory cytokines IL-1α and IL-6 by human HaCaT cells may potentially classify skin sensitizers from non-sensitizers. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

  14. Discriminative learning after uncontrollable shocks

    Directory of Open Access Journals (Sweden)

    Angelica Capelari

    2009-10-01

    Full Text Available O objetivo desse estudo foi investigar se estímulos aversivos não contingentes (incontroláveis produzem interferência em um processo de aprendizagem discriminativa reforçada positivamente. Vinte e quatro ratos foram distribuídos em três grupos (n=8 que diferiram entre si quanto ao tratamento recebido na primeira sessão: choques controláveis (C, incontroláveis (I ou nenhum choque (N. Posteriormente, todos foram submetidos a 10 sessões de treino discriminativo com reforço positivo, em esquema múltiplo-concorrente FR-6/Extinção. Os resultados do treino discriminativo mostraram que, na primeira sessão, a exposição prévia a choques produziu menor frequência de respostas, sendo esse efeito levemente mais acentuado no grupo I; na décima sessão, os grupos não diferiram entre si quanto à frequência de respostas e ao índice discriminativo, que ficou acima de 0,80. O efeito transitório do tratamento com choques incontroláveis, sem interferência a longo prazo no estabelecimento do controle de estímulos por reforçamento positivo, é contrário à generalidade do desamparo aprendido para contextos não aversivos.   Palavras-chave: desamparo aprendido; incontrolabilidade; controle de estímulos.

  15. Discriminative learning after uncontrollable shocks

    OpenAIRE

    Angelica Capelari; Maria Helena Leite Hunziker

    2009-01-01

    O objetivo desse estudo foi investigar se estímulos aversivos não contingentes (incontroláveis) produzem interferência em um processo de aprendizagem discriminativa reforçada positivamente. Vinte e quatro ratos foram distribuídos em três grupos (n=8) que diferiram entre si quanto ao tratamento recebido na primeira sessão: choques controláveis (C), incontroláveis (I) ou nenhum choque (N). Posteriormente, todos foram submetidos a 10 sessões de treino discriminativo com reforço positivo, em esqu...

  16. Hippocampal-cortical contributions to strategic exploration during perceptual discrimination.

    Science.gov (United States)

    Voss, Joel L; Cohen, Neal J

    2017-06-01

    The hippocampus is crucial for long-term memory; its involvement in short-term or immediate expressions of memory is more controversial. Rodent hippocampus has been implicated in an expression of memory that occurs on-line during exploration termed "vicarious trial-and-error" (VTE) behavior. VTE occurs when rodents iteratively explore options during perceptual discrimination or at choice points. It is strategic in that it accelerates learning and improves later memory. VTE has been associated with activity of rodent hippocampal neurons, and lesions of hippocampus disrupt VTE and associated learning and memory advantages. Analogous findings of VTE in humans would support the role of hippocampus in active use of short-term memory to guide strategic behavior. We therefore measured VTE using eye-movement tracking during perceptual discrimination and identified relevant neural correlates with functional magnetic resonance imaging. A difficult perceptual-discrimination task was used that required visual information to be maintained during a several second trial, but with no long-term memory component. VTE accelerated discrimination. Neural correlates of VTE included robust activity of hippocampus and activity of a network of medial prefrontal and lateral parietal regions involved in memory-guided behavior. This VTE-related activity was distinct from activity associated with simply viewing visual stimuli and making eye movements during the discrimination task, which occurred in regions frequently associated with visual processing and eye-movement control. Subjects were mostly unaware of performing VTE, thus further distancing VTE from explicit long-term memory processing. These findings bridge the rodent and human literatures on neural substrates of memory-guided behavior, and provide further support for the role of hippocampus and a hippocampal-centered network of cortical regions in the immediate use of memory in on-line processing and the guidance of behavior. © 2017

  17. 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…

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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 ...

  3. 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…

  4. 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.

  5. Discriminant forest classification method and system

    Science.gov (United States)

    Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

    2012-11-06

    A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

  6. Discrimination and Anti-discrimination in Denmark

    DEFF Research Database (Denmark)

    Olsen, Tore Vincents

    The purpose of this report is to describe and analyse Danish anti-discrimination legislation and the debate about discrimination in Denmark in order to identify present and future legal challenges. The main focus is the implementation of the EU anti-discrimination directives in Danish law...

  7. 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.

  8. 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…

  9. Discriminating the endogenous and exogenous urinary estrogens in human by isotopic ratio mass spectrometry and its potential clinical value.

    Science.gov (United States)

    Yang, Sheng; Zhang, Dapeng; Xu, Youxuan; Wang, Xiaobing; Liu, Xin; Wang, Shan; Wang, Jingzhu; Wu, Moutian; He, Zhenwen; Zhao, Jian; Yuan, Hong

    2013-02-01

    Estrogens were prohibited in the food producing animals by European Union (96/22/EC directive) and added to the Report on Carcinogens in United States since 2002. Due to very low concentration in serum or urine (~pg/mL), the method of control its abuse had not been fully developed. The endogenous estrogens were separated from urines of 18 adult men and women. The exogenous estrogens were chemical reference standards and over the counter preparations. Two patients of dysfunctional uterine bleeding (DUB) administered exogenous estradiol and the urines were collected for 72 h. The urinary estrogens were separated by high-performance liquid chromatography (HPLC) and confirmed. The exogenous and exogenous estrogens were analyzed by gas chromatography combustion isotope ratio mass spectrometry (GC-C-IRMS) to determine the (13)C/(12)C ratio (δ(13)C‰). The δ(13)C‰ values of reference standard of E1, E2, and E3 were -29.36±0.72, -27.98±0.35, -27.62±0.51, respectively. The δ(13)C‰ values of the endogenous E1, E2, and E3 were -21.62±1.07, -22.14±0.98, and -21.88±1.16, with Pendogenous and exogenous urinary estrogen in human. Copyright © 2012 Elsevier Inc. All rights reserved.

  10. Imaging Features that Discriminate between Foci Induced by High- and Low-LET Radiation in Human Fibroblasts

    International Nuclear Information System (INIS)

    Costes, Sylvain V.; Boissiere, Arnaud; Ravani, Shraddha; Romano, Raquel; Parvin, Bahram; Barcellos-Hoff, Mary Helen

    2006-01-01

    In this study, we investigated the formation of radiation-induced foci in normal human fibroblasts exposed to X rays or 130 keV/mum nitrogen ions using antibodies to phosphorylated protein kinase ataxia telangiectasia mutated (ATMp) and histone H2AX(gamma-H2AX). High-content automatic image analysis was used to quantify the immunofluorescence of radiation-induced foci. The size of radiation-induced foci increased for both proteins over a 2-h period after nitrogen-ion irradiation, while the size of radiation-induced foci did not change after exposure to low-LET radiation. The number of radiation-induced ATMp foci showed a more rapid rise and greater frequency after X-ray exposure and was resolved more rapidly such that the frequency of radiation-induced foci decreased by 90 percent compared to 60 percent after exposure to high-LET radiation 2 h after 30 cGy. In contrast, the kinetics of radiation-induced gamma-H2AX focus formation was similar for high- and low-LET radiation in that it reached a plateau early and remained constant for up to 2 h. High-resolution 3D images of radiation-induced gamma-H2AX foci and dosimetry computation suggest that multiple double-strand breaks from nitrogen ions are encompassed within large nuclear domains of 4.4 Mbp. Our work shows that the size and frequency of radiation-induced foci vary as a function of radiation quality, dose, time and protein target. Thus, even though double-strand breaks and radiation-induced foci are correlated, the dynamic nature of both contradicts their accepted equivalence for low doses of different radiation qualities

  11. Imaging Features that Discriminate between Foci Induced by High-and Low-LET Radiation in Human Fibroblasts

    Energy Technology Data Exchange (ETDEWEB)

    Costes, Sylvain V.; Boissiere, Arnaud; Ravani, Shraddha; Romano,Raquel; Parvin, Bahram; Barcellos-Hoff, Mary Helen

    2006-10-08

    In this study, we investigated the formation ofradiation-induced foci in normal human fibroblasts exposed to X rays or130 keV/mum nitrogen ions using antibodies to phosphorylated proteinkinase ataxia telangiectasia mutated (ATMp) and histone H2AX(gamma-H2AX). High-content automatic image analysis was used to quantifythe immunofluorescence of radiation-induced foci. The size ofradiation-induced foci increased for both proteins over a 2-h periodafter nitrogen-ion irradiation, while the size of radiation-induced focidid not change after exposure to low-LET radiation. The number ofradiation-induced ATMp foci showed a more rapid rise and greaterfrequency after X-ray exposure and was resolved more rapidly such thatthe frequency of radiation-induced foci decreased by 90 percent comparedto 60 percent after exposure to high-LET radiation 2 h after 30 cGy. Incontrast, the kinetics of radiation-induced gamma-H2AX focus formationwas similar for high- and low-LET radiation in that it reached a plateauearly and remained constant for up to 2 h. High-resolution 3D images ofradiation-induced gamma-H2AX foci and dosimetry computation suggest thatmultiple double-strand breaks from nitrogen ions are encompassed withinlarge nuclear domains of 4.4 Mbp. Our work shows that the size andfrequency of radiation-induced foci vary as a function of radiationquality, dose, time and protein target. Thus, even though double-strandbreaks and radiation-induced foci are correlated, the dynamic nature ofboth contradicts their accepted equivalence for low doses of differentradiation qualities.

  12. 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...

  13. 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…

  14. 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…

  15. 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

  16. 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.

  17. 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...

  18. Visual learning alters the spontaneous activity of the resting human brain: an fNIRS study.

    Science.gov (United States)

    Niu, Haijing; Li, Hao; Sun, Li; Su, Yongming; Huang, Jing; Song, Yan

    2014-01-01

    Resting-state functional connectivity (RSFC) has been widely used to investigate spontaneous brain activity that exhibits correlated fluctuations. RSFC has been found to be changed along the developmental course and after learning. Here, we investigated whether and how visual learning modified the resting oxygenated hemoglobin (HbO) functional brain connectivity by using functional near-infrared spectroscopy (fNIRS). We demonstrate that after five days of training on an orientation discrimination task constrained to the right visual field, resting HbO functional connectivity and directed mutual interaction between high-level visual cortex and frontal/central areas involved in the top-down control were significantly modified. Moreover, these changes, which correlated with the degree of perceptual learning, were not limited to the trained left visual cortex. We conclude that the resting oxygenated hemoglobin functional connectivity could be used as a predictor of visual learning, supporting the involvement of high-level visual cortex and the involvement of frontal/central cortex during visual perceptual learning.

  19. Development of the Human Factors Skills for Healthcare Instrument: a valid and reliable tool for assessing interprofessional learning across healthcare practice settings.

    Science.gov (United States)

    Reedy, Gabriel B; Lavelle, Mary; Simpson, Thomas; Anderson, Janet E

    2017-10-01

    A central feature of clinical simulation training is human factors skills, providing staff with the social and cognitive skills to cope with demanding clinical situations. Although these skills are critical to safe patient care, assessing their learning is challenging. This study aimed to develop, pilot and evaluate a valid and reliable structured instrument to assess human factors skills, which can be used pre- and post-simulation training, and is relevant across a range of healthcare professions. Through consultation with a multi-professional expert group, we developed and piloted a 39-item survey with 272 healthcare professionals attending training courses across two large simulation centres in London, one specialising in acute care and one in mental health, both serving healthcare professionals working across acute and community settings. Following psychometric evaluation, the final 12-item instrument was evaluated with a second sample of 711 trainees. Exploratory factor analysis revealed a 12-item, one-factor solution with good internal consistency (α=0.92). The instrument had discriminant validity, with newly qualified trainees scoring significantly lower than experienced trainees ( t (98)=4.88, pSkills for Healthcare Instrument provides a reliable and valid method of assessing trainees' human factors skills self-efficacy across acute and mental health settings. This instrument has the potential to improve the assessment and evaluation of human factors skills learning in both uniprofessional and interprofessional clinical simulation training.

  20. 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.

  1. Concentration profiling of minerals in iliac crest bone tissue of opium addicted humans using inductively coupled plasma and discriminant analysis techniques.

    Science.gov (United States)

    Mani-Varnosfaderani, Ahmad; Jamshidi, Mahbobeh; Yeganeh, Ali; Mahmoudi, Mani

    2016-02-20

    Opium addiction is one of the main health problems in developing countries and induces serious defects on the human body. In this work, the concentrations of 32 minerals including alkaline, heavy and toxic metals have been determined in the iliac crest bone tissue of 22 opium addicted individuals using inductively coupled plasma-optical emission spectroscopy (ICP-OES). The bone tissues of 30 humans with no physiological and metabolomic diseases were used as the control group. For subsequent analyses, the linear and quadratic discriminant analysis techniques have been used for classification of the data into "addicted" and "non-addicted" groups. Moreover, the counter-propagation artificial neural network (CPANN) has been used for clustering of the data. The results revealed that the CPANN is a robust model and thoroughly classifies the data. The area under the curve for the receiver operating characteristic curve for this model was more than 0.91. Investigation of the results revealed that the opium consumption causes a deficiency in the level of Calcium, Phosphate, Potassium and Sodium in iliac crest bone tissue. Moreover, this type of addiction induces an increment in the level of toxic and heavy metals such as Co, Cr, Mo and Ni in iliac crest tissue. The correlation analysis revealed that there were no significant dependencies between the age of the samples and the mineral content of their iliac crest, in this study. The results of this work suggest that the opium addicted individuals need thorough and restricted dietary and medical care programs after recovery phases, in order to have healthy bones. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. 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

  3. Hierarchical Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Di Lu

    2018-01-01

    Full Text Available The Internet of Things (IoT generates lots of high-dimensional sensor intelligent data. The processing of high-dimensional data (e.g., data visualization and data classification is very difficult, so it requires excellent subspace learning algorithms to learn a latent subspace to preserve the intrinsic structure of the high-dimensional data, and abandon the least useful information in the subsequent processing. In this context, many subspace learning algorithms have been presented. However, in the process of transforming the high-dimensional data into the low-dimensional space, the huge difference between the sum of inter-class distance and the sum of intra-class distance for distinct data may cause a bias problem. That means that the impact of intra-class distance is overwhelmed. To address this problem, we propose a novel algorithm called Hierarchical Discriminant Analysis (HDA. It minimizes the sum of intra-class distance first, and then maximizes the sum of inter-class distance. This proposed method balances the bias from the inter-class and that from the intra-class to achieve better performance. Extensive experiments are conducted on several benchmark face datasets. The results reveal that HDA obtains better performance than other dimensionality reduction algorithms.

  4. 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.

  5. 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.

  6. 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,…

  7. 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.…

  8. 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...

  9. Discriminative Relational Topic Models.

    Science.gov (United States)

    Chen, Ning; Zhu, Jun; Xia, Fei; Zhang, Bo

    2015-05-01

    Relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents for document networks, and they have shown promise on predicting network structures and discovering latent topic representations. However, existing RTMs have limitations in both the restricted model expressiveness and incapability of dealing with imbalanced network data. To expand the scope and improve the inference accuracy of RTMs, this paper presents three extensions: 1) unlike the common link likelihood with a diagonal weight matrix that allows the-same-topic interactions only, we generalize it to use a full weight matrix that captures all pairwise topic interactions and is applicable to asymmetric networks; 2) instead of doing standard Bayesian inference, we perform regularized Bayesian inference (RegBayes) with a regularization parameter to deal with the imbalanced link structure issue in real networks and improve the discriminative ability of learned latent representations; and 3) instead of doing variational approximation with strict mean-field assumptions, we present collapsed Gibbs sampling algorithms for the generalized relational topic models by exploring data augmentation without making restricting assumptions. Under the generic RegBayes framework, we carefully investigate two popular discriminative loss functions, namely, the logistic log-loss and the max-margin hinge loss. Experimental results on several real network datasets demonstrate the significance of these extensions on improving prediction performance.

  10. Pulse duration discriminator

    International Nuclear Information System (INIS)

    Kosakovskij, L.F.

    1980-01-01

    Basic circuits of a discriminator for discrimination of pulses with the duration greater than the preset one, and of a multifunctional discriminator allowing to discriminate pulses with the duration greater (tsub(p)>tsub(s)) and lesser (tsub(p) tsub(s) and with the duration tsub(p) [ru

  11. Paintings discrimination by mice: Different strategies for different paintings.

    Science.gov (United States)

    Watanabe, Shigeru

    2017-09-01

    C57BL/6 mice were trained on simultaneous discrimination of paintings with multiple exemplars, using an operant chamber with a touch screen. The number of exemplars was successively increased up to six. Those mice trained in Kandinsky/Mondrian discrimination showed improved learning and generalization, whereas those trained in Picasso/Renoir discrimination showed no improvements in learning or generalization. These results suggest category-like discrimination in the Kandinsky/Mondrian task, but item-to-item discrimination in the Picasso/Renoir task. Mice maintained their discriminative behavior in a pixelization test with various paintings; however, mice in the Picasso/Renoir task showed poor performance in a test that employed scrambling processing. These results do not indicate that discrimination strategy for any Kandinsky/Mondrian combinations differed from that for any Picasso/Monet combinations but suggest the mice employed different strategies of discrimination tasks depending upon stimuli. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. 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.

  13. Introduction to multivariate discrimination

    Science.gov (United States)

    Kégl, Balázs

    2013-07-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  14. Introduction to multivariate discrimination

    International Nuclear Information System (INIS)

    Kegl, B.

    2013-01-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyper-parameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Limited taste discrimination in Drosophila.

    Science.gov (United States)

    Masek, Pavel; Scott, Kristin

    2010-08-17

    In the gustatory systems of mammals and flies, different populations of sensory cells recognize different taste modalities, such that there are cells that respond selectively to sugars and others to bitter compounds. This organization readily allows animals to distinguish compounds of different modalities but may limit the ability to distinguish compounds within one taste modality. Here, we developed a behavioral paradigm in Drosophila melanogaster to evaluate directly the tastes that a fly distinguishes. These studies reveal that flies do not discriminate among different sugars, or among different bitter compounds, based on chemical identity. Instead, flies show a limited ability to distinguish compounds within a modality based on intensity or palatability. Taste associative learning, similar to olfactory learning, requires the mushroom bodies, suggesting fundamental similarities in brain mechanisms underlying behavioral plasticity. Overall, these studies provide insight into the discriminative capacity of the Drosophila gustatory system and the modulation of taste behavior.

  20. 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.