Sample records for learning object categories
-
Mere exposure alters category learning of novel objects.
Folstein, Jonathan R; Gauthier, Isabel; Palmeri, Thomas J
2010-01-01
We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning.
-
Mere Exposure Alters Category Learning of Novel Objects
Folstein, Jonathan R.; Gauthier, Isabel; Palmeri, Thomas J.
2010-01-01
We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning. PMID:21833209
-
Fazl, Arash; Grossberg, Stephen; Mingolla, Ennio
2009-02-01
How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified mechanistic explanation of how spatial and object attention work together to search a scene and learn what is in it. The ARTSCAN model predicts how an object's surface representation generates a form-fitting distribution of spatial attention, or "attentional shroud". All surface representations dynamically compete for spatial attention to form a shroud. The winning shroud persists during active scanning of the object. The shroud maintains sustained activity of an emerging view-invariant category representation while multiple view-specific category representations are learned and are linked through associative learning to the view-invariant object category. The shroud also helps to restrict scanning eye movements to salient features on the attended object. Object attention plays a role in controlling and stabilizing the learning of view-specific object categories. Spatial attention hereby coordinates the deployment of object attention during object category learning. Shroud collapse releases a reset signal that inhibits the active view-invariant category in the What cortical processing stream. Then a new shroud, corresponding to a different object, forms in the Where cortical processing stream, and search using attention shifts and eye movements continues to learn new objects throughout a scene. The model mechanistically clarifies basic properties of attention shifts (engage, move, disengage) and inhibition of return. It simulates human reaction time data about object-based spatial attention shifts, and learns with 98.1% accuracy and a compression of 430 on a letter database whose letters vary in size, position, and orientation. The model provides a powerful framework for unifying many data about spatial and object attention, and their interactions during perception, cognition, and action.
-
Impact of feature saliency on visual category learning.
Hammer, Rubi
2015-01-01
People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the 'essence' of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies.
-
Impact of feature saliency on visual category learning
Hammer, Rubi
2015-01-01
People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the ‘essence’ of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies. PMID:25954220
-
Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics.
Chen, Chi-Hsin; Zhang, Yayun; Yu, Chen
2018-05-01
Objects in the world usually have names at different hierarchical levels (e.g., beagle, dog, animal). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use co-occurrence information to learn hierarchical labels in contexts where the labels for individual objects and labels for categories were presented in completely separated blocks, in interleaved blocks, or mixed in the same trial. Temporal presentation schedules significantly affected the learning of individual object labels, but not the learning of category labels. Learners' subsequent generalization of category labels indicated sensitivity to the structure of statistical input. Copyright © 2017 Cognitive Science Society, Inc.
-
Chen, Chi-Hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen
2017-08-01
Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership than English, were able to learn words and form object categories when trained with the same type of structures. The results indicate that both groups of learners successfully extracted multiple levels of co-occurrence and used them to learn words and object categories simultaneously. However, marked individual differences in performance were also found, suggesting possible interference and competition in processing the two concurrent streams of regularities. Copyright © 2016 Cognitive Science Society, Inc.
-
Category learning increases discriminability of relevant object dimensions in visual cortex.
Folstein, Jonathan R; Palmeri, Thomas J; Gauthier, Isabel
2013-04-01
Learning to categorize objects can transform how they are perceived, causing relevant perceptual dimensions predictive of object category to become enhanced. For example, an expert mycologist might become attuned to species-specific patterns of spacing between mushroom gills but learn to ignore cap textures attributable to varying environmental conditions. These selective changes in perception can persist beyond the act of categorizing objects and influence our ability to discriminate between them. Using functional magnetic resonance imaging adaptation, we demonstrate that such category-specific perceptual enhancements are associated with changes in the neural discriminability of object representations in visual cortex. Regions within the anterior fusiform gyrus became more sensitive to small variations in shape that were relevant during prior category learning. In addition, extrastriate occipital areas showed heightened sensitivity to small variations in shape that spanned the category boundary. Visual representations in cortex, just like our perception, are sensitive to an object's history of categorization.
-
Aversive Learning Modulates Cortical Representations of Object Categories
Dunsmoor, Joseph E.; Kragel, Philip A.; Martin, Alex; LaBar, Kevin S.
2014-01-01
Experimental studies of conditioned learning reveal activity changes in the amygdala and unimodal sensory cortex underlying fear acquisition to simple stimuli. However, real-world fears typically involve complex stimuli represented at the category level. A consequence of category-level representations of threat is that aversive experiences with particular category members may lead one to infer that related exemplars likewise pose a threat, despite variations in physical form. Here, we examined the effect of category-level representations of threat on human brain activation using 2 superordinate categories (animals and tools) as conditioned stimuli. Hemodynamic activity in the amygdala and category-selective cortex was modulated by the reinforcement contingency, leading to widespread fear of different exemplars from the reinforced category. Multivariate representational similarity analyses revealed that activity patterns in the amygdala and object-selective cortex were more similar among exemplars from the threat versus safe category. Learning to fear animate objects was additionally characterized by enhanced functional coupling between the amygdala and fusiform gyrus. Finally, hippocampal activity co-varied with object typicality and amygdala activation early during training. These findings provide novel evidence that aversive learning can modulate category-level representations of object concepts, thereby enabling individuals to express fear to a range of related stimuli. PMID:23709642
-
Attribute conjunctions and the part configuration advantage in object category learning.
Saiki, J; Hummel, J E
1996-07-01
Five experiments demonstrated that in object category learning people are particularly sensitive to conjunctions of part shapes and relative locations. Participants learned categories defined by a part's shape and color (part-color conjunctions) or by a part's shape and its location relative to another part (part-location conjunctions). The statistical properties of the categories were identical across these conditions, as were the salience of color and relative location. Participants were better at classifying objects defined by part-location conjunctions than objects defined by part-color conjunctions. Subsequent experiments revealed that this effect was not due to the specific color manipulation or the role of location per se. These results suggest that the shape bias in object categorization is at least partly due to sensitivity to part-location conjunctions and suggest a new processing constraint on category learning.
-
Layher, Georg; Schrodt, Fabian; Butz, Martin V.; Neumann, Heiko
2014-01-01
The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, both of which are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in computational neuroscience. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of additional (sub-) category representations. We demonstrate the temporal evolution of such learning and show how the proposed combination of an associative memory with a modulatory feedback integration successfully establishes category and subcategory representations. PMID:25538637
-
How category learning affects object representations: Not all morphspaces stretch alike
Folstein, Jonathan R.; Gauthier, Isabel; Palmeri, Thomas J.
2012-01-01
How does learning to categorize objects affect how we visually perceive them? Behavioral, neurophysiological, and neuroimaging studies have tested the degree to which category learning influences object representations, with conflicting results. Some studies find that objects become more visually discriminable along dimensions relevant to previously learned categories, while others find no such effect. One critical factor we explore here lies in the structure of the morphspaces used in different studies. Studies finding no increase in discriminability often use “blended” morphspaces, with morphparents lying at corners of the space. By contrast, studies finding increases in discriminability use “factorial” morphspaces, defined by separate morphlines forming axes of the space. Using the same four morphparents, we created both factorial and blended morphspaces matched in pairwise discriminability. Category learning caused a selective increase in discriminability along the relevant dimension of the factorial space, but not in the blended space, and led to the creation of functional dimensions in the factorial space, but not in the blended space. These findings demonstrate that not all morphspaces stretch alike: Only some morphspaces support enhanced discriminability to relevant object dimensions following category learning. Our results have important implications for interpreting neuroimaging studies reporting little or no effect of category learning on object representations in the visual system: Those studies may have been limited by their use of blended morphspaces. PMID:22746950
-
Large-scale weakly supervised object localization via latent category learning.
Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve
2015-04-01
Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.
-
Learning to learn causal models.
Kemp, Charles; Goodman, Noah D; Tenenbaum, Joshua B
2010-09-01
Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. Copyright © 2010 Cognitive Science Society, Inc.
-
Perceptual advantage for category-relevant perceptual dimensions: the case of shape and motion.
Folstein, Jonathan R; Palmeri, Thomas J; Gauthier, Isabel
2014-01-01
Category learning facilitates perception along relevant stimulus dimensions, even when tested in a discrimination task that does not require categorization. While this general phenomenon has been demonstrated previously, perceptual facilitation along dimensions has been documented by measuring different specific phenomena in different studies using different kinds of objects. Across several object domains, there is support for acquired distinctiveness, the stretching of a perceptual dimension relevant to learned categories. Studies using faces and studies using simple separable visual dimensions have also found evidence of acquired equivalence, the shrinking of a perceptual dimension irrelevant to learned categories, and categorical perception, the local stretching across the category boundary. These later two effects are rarely observed with complex non-face objects. Failures to find these effects with complex non-face objects may have been because the dimensions tested previously were perceptually integrated. Here we tested effects of category learning with non-face objects categorized along dimensions that have been found to be processed by different areas of the brain, shape and motion. While we replicated acquired distinctiveness, we found no evidence for acquired equivalence or categorical perception.
-
Human Factors Engineering. Student Supplement,
1981-08-01
a job TASK TAXONOMY A classification scheme for the different levels of activities in a system, i.e., job - task - sub-task, etc. TASK-AN~ALYSIS...with the classification of learning objectives by learning category so as to identify learningPhas III guidelines necessary for optimum learning to...correct. .4... .the sequencing of all dependent tasks. .1.. .the classification of learning objectives by learning category and the Identification of
-
Word Learning and Attention Allocation Based on Word Class and Category Knowledge
ERIC Educational Resources Information Center
Hupp, Julie M.
2015-01-01
Attention allocation in word learning may vary developmentally based on the novelty of the object. It has been suggested that children differentially learn verbs based on the novelty of the agent, but adults do not because they automatically infer the object's category and thus treat it like a familiar object. The current research examined…
-
Emberson, Lauren L.; Rubinstein, Dani
2016-01-01
The influence of statistical information on behavior (either through learning or adaptation) is quickly becoming foundational to many domains of cognitive psychology and cognitive neuroscience, from language comprehension to visual development. We investigate a central problem impacting these diverse fields: when encountering input with rich statistical information, are there any constraints on learning? This paper examines learning outcomes when adult learners are given statistical information across multiple levels of abstraction simultaneously: from abstract, semantic categories of everyday objects to individual viewpoints on these objects. After revealing statistical learning of abstract, semantic categories with scrambled individual exemplars (Exp. 1), participants viewed pictures where the categories as well as the individual objects predicted picture order (e.g., bird1—dog1, bird2—dog2). Our findings suggest that participants preferentially encode the relationships between the individual objects, even in the presence of statistical regularities linking semantic categories (Exps. 2 and 3). In a final experiment we investigate whether learners are biased towards learning object-level regularities or simply construct the most detailed model given the data (and therefore best able to predict the specifics of the upcoming stimulus) by investigating whether participants preferentially learn from the statistical regularities linking individual snapshots of objects or the relationship between the objects themselves (e.g., bird_picture1— dog_picture1, bird_picture2—dog_picture2). We find that participants fail to learn the relationships between individual snapshots, suggesting a bias towards object-level statistical regularities as opposed to merely constructing the most complete model of the input. This work moves beyond the previous existence proofs that statistical learning is possible at both very high and very low levels of abstraction (categories vs. individual objects) and suggests that, at least with the current categories and type of learner, there are biases to pick up on statistical regularities between individual objects even when robust statistical information is present at other levels of abstraction. These findings speak directly to emerging theories about how systems supporting statistical learning and prediction operate in our structure-rich environments. Moreover, the theoretical implications of the current work across multiple domains of study is already clear: statistical learning cannot be assumed to be unconstrained even if statistical learning has previously been established at a given level of abstraction when that information is presented in isolation. PMID:27139779
-
Chang, Hung-Cheng; Grossberg, Stephen; Cao, Yongqiang
2014-01-01
The Where’s Waldo problem concerns how individuals can rapidly learn to search a scene to detect, attend, recognize, and look at a valued target object in it. This article develops the ARTSCAN Search neural model to clarify how brain mechanisms across the What and Where cortical streams are coordinated to solve the Where’s Waldo problem. The What stream learns positionally-invariant object representations, whereas the Where stream controls positionally-selective spatial and action representations. The model overcomes deficiencies of these computationally complementary properties through What and Where stream interactions. Where stream processes of spatial attention and predictive eye movement control modulate What stream processes whereby multiple view- and positionally-specific object categories are learned and associatively linked to view- and positionally-invariant object categories through bottom-up and attentive top-down interactions. Gain fields control the coordinate transformations that enable spatial attention and predictive eye movements to carry out this role. What stream cognitive-emotional learning processes enable the focusing of motivated attention upon the invariant object categories of desired objects. What stream cognitive names or motivational drives can prime a view- and positionally-invariant object category of a desired target object. A volitional signal can convert these primes into top-down activations that can, in turn, prime What stream view- and positionally-specific categories. When it also receives bottom-up activation from a target, such a positionally-specific category can cause an attentional shift in the Where stream to the positional representation of the target, and an eye movement can then be elicited to foveate it. These processes describe interactions among brain regions that include visual cortex, parietal cortex, inferotemporal cortex, prefrontal cortex (PFC), amygdala, basal ganglia (BG), and superior colliculus (SC). PMID:24987339
-
Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization.
Gao, Shenghua; Tsang, Ivor Wai-Hung; Ma, Yi
2014-02-01
This paper targets fine-grained image categorization by learning a category-specific dictionary for each category and a shared dictionary for all the categories. Such category-specific dictionaries encode subtle visual differences among different categories, while the shared dictionary encodes common visual patterns among all the categories. To this end, we impose incoherence constraints among the different dictionaries in the objective of feature coding. In addition, to make the learnt dictionary stable, we also impose the constraint that each dictionary should be self-incoherent. Our proposed dictionary learning formulation not only applies to fine-grained classification, but also improves conventional basic-level object categorization and other tasks such as event recognition. Experimental results on five data sets show that our method can outperform the state-of-the-art fine-grained image categorization frameworks as well as sparse coding based dictionary learning frameworks. All these results demonstrate the effectiveness of our method.
-
Can Semi-Supervised Learning Explain Incorrect Beliefs about Categories?
ERIC Educational Resources Information Center
Kalish, Charles W.; Rogers, Timothy T.; Lang, Jonathan; Zhu, Xiaojin
2011-01-01
Three experiments with 88 college-aged participants explored how unlabeled experiences--learning episodes in which people encounter objects without information about their category membership--influence beliefs about category structure. Participants performed a simple one-dimensional categorization task in a brief supervised learning phase, then…
-
ERIC Educational Resources Information Center
Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen
2004-01-01
Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…
-
The effect of category learning on attentional modulation of visual cortex.
Folstein, Jonathan R; Fuller, Kelly; Howard, Dorothy; DePatie, Thomas
2017-09-01
Learning about visual object categories causes changes in the way we perceive those objects. One likely mechanism by which this occurs is the application of attention to potentially relevant objects. Here we test the hypothesis that category membership influences the allocation of attention, allowing attention to be applied not only to object features, but to entire categories. Participants briefly learned to categorize a set of novel cartoon animals after which EEG was recorded while participants distinguished between a target and non-target category. A second identical EEG session was conducted after two sessions of categorization practice. The category structure and task design allowed parametric manipulation of number of target features while holding feature frequency and category membership constant. We found no evidence that category membership influenced attentional selection: a postero-lateral negative component, labeled the selection negativity/N250, increased over time and was sensitive to number of target features, not target categories. In contrast, the right hemisphere N170 was not sensitive to target features. The P300 appeared sensitive to category in the first session, but showed a graded sensitivity to number of target features in the second session, possibly suggesting a transition from rule-based to similarity based categorization. Copyright © 2017. Published by Elsevier Ltd.
-
ERIC Educational Resources Information Center
Hammer, Rubi; Kloet, Jim; Booth, James R.
2016-01-01
As children start attending school they are more likely to face situations where they have to autonomously learn about novel object categories (e.g. by reading a picture book with descriptions of novel animals). Such autonomous observational category learning (OCL) gradually complements interactive feedback-based category learning (FBCL), where a…
-
Grossberg, Stephen
2015-09-24
This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory. Copyright © 2014 Elsevier B.V. All rights reserved.
-
Wasserman, Edward A.; Brooks, Daniel I.; McMurray, Bob
2014-01-01
Might there be parallels between category learning in animals and word learning in children? To examine this possibility, we devised a new associative learning technique for teaching pigeons to sort 128 photographs of objects into 16 human language categories. We found that pigeons learned all 16 categories in parallel, they perceived the perceptual coherence of the different object categories, and they generalized their categorization behavior to novel photographs from the training categories. More detailed analyses of the factors that predict trial-by-trial learning implicated a number of factors that may shape learning. First, we found considerable trial-by-trial dependency of pigeons’ categorization responses, consistent with several recent studies that invoke this dependency to claim that humans acquire words via symbolic or inferential mechanisms; this finding suggests that such dependencies may also arise in associative systems. Second, our trial-by-trial analyses divulged seemingly irrelevant aspects of the categorization task, like the spatial location of the report responses, which influenced learning. Third, those trial-by-trial analyses also supported the possibility that learning may be determined both by strengthening correct stimulus-response associations and by weakening incorrect stimulus-response associations. The parallel between all these findings and important aspects of human word learning suggests that associative learning mechanisms may play a much stronger part in complex human behavior than is commonly believed. PMID:25497520
-
Working memory supports inference learning just like classification learning.
Craig, Stewart; Lewandowsky, Stephan
2013-08-01
Recent research has found a positive relationship between people's working memory capacity (WMC) and their speed of category learning. To date, only classification-learning tasks have been considered, in which people learn to assign category labels to objects. It is unknown whether learning to make inferences about category features might also be related to WMC. We report data from a study in which 119 participants undertook classification learning and inference learning, and completed a series of WMC tasks. Working memory capacity was positively related to people's classification and inference learning performance.
-
Learning while Babbling: Prelinguistic Object-Directed Vocalizations Indicate a Readiness to Learn
ERIC Educational Resources Information Center
Goldstein, Michael H.; Schwade, Jennifer; Briesch, Jacquelyn; Syal, Supriya
2010-01-01
Two studies illustrate the functional significance of a new category of prelinguistic vocalizing--object-directed vocalizations (ODVs)--and show that these sounds are connected to learning about words and objects. Experiment 1 tested 12-month-old infants' perceptual learning of objects that elicited ODVs. Fourteen infants' vocalizations were…
-
ERIC Educational Resources Information Center
Davis, Tyler; Love, Bradley C.; Preston, Alison R.
2012-01-01
Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and…
-
Changes in Visual Object Recognition Precede the Shape Bias in Early Noun Learning
Yee, Meagan; Jones, Susan S.; Smith, Linda B.
2012-01-01
Two of the most formidable skills that characterize human beings are language and our prowess in visual object recognition. They may also be developmentally intertwined. Two experiments, a large sample cross-sectional study and a smaller sample 6-month longitudinal study of 18- to 24-month-olds, tested a hypothesized developmental link between changes in visual object representation and noun learning. Previous findings in visual object recognition indicate that children’s ability to recognize common basic level categories from sparse structural shape representations of object shape emerges between the ages of 18 and 24 months, is related to noun vocabulary size, and is lacking in children with language delay. Other research shows in artificial noun learning tasks that during this same developmental period, young children systematically generalize object names by shape, that this shape bias predicts future noun learning, and is lacking in children with language delay. The two experiments examine the developmental relation between visual object recognition and the shape bias for the first time. The results show that developmental changes in visual object recognition systematically precede the emergence of the shape bias. The results suggest a developmental pathway in which early changes in visual object recognition that are themselves linked to category learning enable the discovery of higher-order regularities in category structure and thus the shape bias in novel noun learning tasks. The proposed developmental pathway has implications for understanding the role of specific experience in the development of both visual object recognition and the shape bias in early noun learning. PMID:23227015
-
Mechanisms of object recognition: what we have learned from pigeons
Soto, Fabian A.; Wasserman, Edward A.
2014-01-01
Behavioral studies of object recognition in pigeons have been conducted for 50 years, yielding a large body of data. Recent work has been directed toward synthesizing this evidence and understanding the visual, associative, and cognitive mechanisms that are involved. The outcome is that pigeons are likely to be the non-primate species for which the computational mechanisms of object recognition are best understood. Here, we review this research and suggest that a core set of mechanisms for object recognition might be present in all vertebrates, including pigeons and people, making pigeons an excellent candidate model to study the neural mechanisms of object recognition. Behavioral and computational evidence suggests that error-driven learning participates in object category learning by pigeons and people, and recent neuroscientific research suggests that the basal ganglia, which are homologous in these species, may implement error-driven learning of stimulus-response associations. Furthermore, learning of abstract category representations can be observed in pigeons and other vertebrates. Finally, there is evidence that feedforward visual processing, a central mechanism in models of object recognition in the primate ventral stream, plays a role in object recognition by pigeons. We also highlight differences between pigeons and people in object recognition abilities, and propose candidate adaptive specializations which may explain them, such as holistic face processing and rule-based category learning in primates. From a modern comparative perspective, such specializations are to be expected regardless of the model species under study. The fact that we have a good idea of which aspects of object recognition differ in people and pigeons should be seen as an advantage over other animal models. From this perspective, we suggest that there is much to learn about human object recognition from studying the “simple” brains of pigeons. PMID:25352784
-
Abdul Ghaffar Al-Shaibani, Tarik A; Sachs-Robertson, Annette; Al Shazali, Hafiz O; Sequeira, Reginald P; Hamdy, Hosam; Al-Roomi, Khaldoon
2003-07-01
A problem-based learning strategy is used for curriculum planning and implementation at the Arabian Gulf University, Bahrain. Problems are constructed in a way that faculty-set objectives are expected to be identified by students during tutorials. Students in small groups, along with a tutor functioning as a facilitator, identify learning issues and define their learning objectives. We compared objectives identified by student groups with faculty-set objectives to determine extent of congruence, and identified factors that influenced students' ability at identifying faculty-set objectives. Male and female students were segregated and randomly grouped. A faculty tutor was allocated for each group. This study was based on 13 problems given to entry-level medical students. Pooled objectives of these problems were classified into four categories: structural, functional, clinical and psychosocial. Univariate analysis of variance was used for comparison, and a p > 0.05 was considered significant. The mean of overall objectives generated by the students was 54.2%, for each problem. Students identified psychosocial learning objectives more readily than structural ones. Female students identified more psychosocial objectives, whereas male students identified more of structural objectives. Tutor characteristics such as medical/non-medical background, and the years of teaching were correlated with categories of learning issues identified. Students identify part of the faculty-set learning objectives during tutorials with a faculty tutor acting as a facilitator. Students' gender influences types of learning issues identified. Content expertise of tutors does not influence identification of learning needs by students.
-
ERIC Educational Resources Information Center
Fazl, Arash; Grossberg, Stephen; Mingolla, Ennio
2009-01-01
How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified…
-
Learning, retention, and generalization of haptic categories
NASA Astrophysics Data System (ADS)
Do, Phuong T.
This dissertation explored how haptic concepts are learned, retained, and generalized to the same or different modality. Participants learned to classify objects into three categories either visually or haptically via different training procedures, followed by an immediate or delayed transfer test. Experiment I involved visual versus haptic learning and transfer. Intermodal matching between vision and haptics was investigated in Experiment II. Experiments III and IV examined intersensory conflict in within- and between-category bimodal situations to determine the degree of perceptual dominance between sight and touch. Experiment V explored the intramodal relationship between similarity and categorization in a psychological space, as revealed by MDS analysis of similarity judgments. Major findings were: (1) visual examination resulted in relatively higher performance accuracy than haptic learning; (2) systematic training produced better category learning of haptic concepts across all modality conditions; (3) the category prototypes were rated newer than any transfer stimulus followed learning both immediately and after a week delay; and, (4) although they converged at the apex of two transformational trajectories, the category prototypes became more central to their respective categories and increasingly structured as a function of learning. Implications for theories of multimodal similarity and categorization behavior are discussed in terms of discrimination learning, sensory integration, and dominance relation.
-
Cantwell, George; Riesenhuber, Maximilian; Roeder, Jessica L; Ashby, F Gregory
2017-05-01
The field of computational cognitive neuroscience (CCN) builds and tests neurobiologically detailed computational models that account for both behavioral and neuroscience data. This article leverages a key advantage of CCN-namely, that it should be possible to interface different CCN models in a plug-and-play fashion-to produce a new and biologically detailed model of perceptual category learning. The new model was created from two existing CCN models: the HMAX model of visual object processing and the COVIS model of category learning. Using bitmap images as inputs and by adjusting only a couple of learning-rate parameters, the new HMAX/COVIS model provides impressively good fits to human category-learning data from two qualitatively different experiments that used different types of category structures and different types of visual stimuli. Overall, the model provides a comprehensive neural and behavioral account of basal ganglia-mediated learning. Copyright © 2017 Elsevier Ltd. All rights reserved.
-
Conventional wisdom: negotiating conventions of reference enhances category learning.
Voiklis, John; Corter, James E
2012-01-01
Collaborators generally coordinate their activities through communication, during which they readily negotiate a shared lexicon for activity-related objects. This social-pragmatic activity both recruits and affects cognitive and social-cognitive processes ranging from selective attention to perspective taking. We ask whether negotiating reference also facilitates category learning or might private verbalization yield comparable facilitation? Participants in three referential conditions learned to classify imaginary creatures according to combinations of functional features-nutritive and destructive-that implicitly defined four categories. Remote partners communicated in the Dialogue condition. In the Monologue condition, participants recorded audio descriptions for their own later use. Controls worked silently. Dialogue yielded better category learning, with wider distribution of attention. Monologue offered no benefits over working silently. We conclude that negotiating reference compels collaborators to find communicable structure in their shared activity; this social-pragmatic constraint accelerates category learning and likely provides much of the benefit recently ascribed to learning labeled categories. Copyright © 2012 Cognitive Science Society, Inc.
-
Schapiro, Anna C; McDevitt, Elizabeth A; Chen, Lang; Norman, Kenneth A; Mednick, Sara C; Rogers, Timothy T
2017-11-01
Semantic memory encompasses knowledge about both the properties that typify concepts (e.g. robins, like all birds, have wings) as well as the properties that individuate conceptually related items (e.g. robins, in particular, have red breasts). We investigate the impact of sleep on new semantic learning using a property inference task in which both kinds of information are initially acquired equally well. Participants learned about three categories of novel objects possessing some properties that were shared among category exemplars and others that were unique to an exemplar, with exposure frequency varying across categories. In Experiment 1, memory for shared properties improved and memory for unique properties was preserved across a night of sleep, while memory for both feature types declined over a day awake. In Experiment 2, memory for shared properties improved across a nap, but only for the lower-frequency category, suggesting a prioritization of weakly learned information early in a sleep period. The increase was significantly correlated with amount of REM, but was also observed in participants who did not enter REM, suggesting involvement of both REM and NREM sleep. The results provide the first evidence that sleep improves memory for the shared structure of object categories, while simultaneously preserving object-unique information.
-
More than words: Adults learn probabilities over categories and relationships between them.
Hudson Kam, Carla L
2009-04-01
This study examines whether human learners can acquire statistics over abstract categories and their relationships to each other. Adult learners were exposed to miniature artificial languages containing variation in the ordering of the Subject, Object, and Verb constituents. Different orders (e.g. SOV, VSO) occurred in the input with different frequencies, but the occurrence of one order versus another was not predictable. Importantly, the language was constructed such that participants could only match the overall input probabilities if they were tracking statistics over abstract categories, not over individual words. At test, participants reproduced the probabilities present in the input with a high degree of accuracy. Closer examination revealed that learner's were matching the probabilities associated with individual verbs rather than the category as a whole. However, individual nouns had no impact on word orders produced. Thus, participants learned the probabilities of a particular ordering of the abstract grammatical categories Subject and Object associated with each verb. Results suggest that statistical learning mechanisms are capable of tracking relationships between abstract linguistic categories in addition to individual items.
-
ERIC Educational Resources Information Center
Chen, Chi-hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen
2017-01-01
Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories…
-
Consider the category: The effect of spacing depends on individual learning histories.
Slone, Lauren K; Sandhofer, Catherine M
2017-07-01
The spacing effect refers to increased retention following learning instances that are spaced out in time compared with massed together in time. By one account, the advantages of spaced learning should be independent of task particulars and previous learning experiences given that spacing effects have been demonstrated in a variety of tasks across the lifespan. However, by another account, spaced learning should be affected by previous learning because past learning affects the memory and attention processes that form the crux of the spacing effect. The current study investigated whether individuals' learning histories affect the role of spacing in category learning. We examined the effect of spacing on 24 2- to 3.5-year-old children's learning of categories organized by properties to which children's previous learning experiences have biased them to attend (i.e., shape) and properties to which children are less biased to attend (i.e., texture and color). Spaced presentations led to significantly better learning of shape categories, but not of texture or color categories, compared with massed presentations. In addition, generalized estimating equations analyses revealed positive relations between the size of children's "shape-side" productive vocabularies and their shape category learning and between the size of children's "against-the-system" productive vocabularies and their texture category learning. These results suggest that children's attention to and memory for novel object categories are strongly related to their individual word-learning histories. Moreover, children's learned attentional biases affected the types of categories for which spacing facilitated learning. These findings highlight the importance of considering how learners' previous experiences may influence future learning. Copyright © 2017 Elsevier Inc. All rights reserved.
-
Category Learning Research in the Interactive Online Environment Second Life
NASA Technical Reports Server (NTRS)
Andrews, Jan; Livingston, Ken; Sturm, Joshua; Bliss, Daniel; Hawthorne, Daniel
2011-01-01
The interactive online environment Second Life allows users to create novel three-dimensional stimuli that can be manipulated in a meaningful yet controlled environment. These features suggest Second Life's utility as a powerful tool for investigating how people learn concepts for unfamiliar objects. The first of two studies was designed to establish that cognitive processes elicited in this virtual world are comparable to those tapped in conventional settings by attempting to replicate the established finding that category learning systematically influences perceived similarity . From the perspective of an avatar, participants navigated a course of unfamiliar three-dimensional stimuli and were trained to classify them into two labeled categories based on two visual features. Participants then gave similarity ratings for pairs of stimuli and their responses were compared to those of control participants who did not learn the categories. Results indicated significant compression, whereby objects classified together were judged to be more similar by learning than control participants, thus supporting the validity of using Second Life as a laboratory for studying human cognition. A second study used Second Life to test the novel hypothesis that effects of learning on perceived similarity do not depend on the presence of verbal labels for categories. We presented the same stimuli but participants classified them by selecting between two complex visual patterns designed to be extremely difficult to label. While learning was more challenging in this condition , those who did learn without labels showed a compression effect identical to that found in the first study using verbal labels. Together these studies establish that at least some forms of human learning in Second Life parallel learning in the actual world and thus open the door to future studies that will make greater use of the enriched variety of objects and interactions possible in simulated environments compared to traditional experimental situations.
-
Form Follows Function: Learning about Function Helps Children Learn about Shape
ERIC Educational Resources Information Center
Ware, Elizabeth A.; Booth, Amy E.
2010-01-01
Object functions help young children to organize new artifact categories. However, the scope of their influence is unknown. We explore whether functions highlight property dimensions that are relevant to artifact categories in general. Specifically, using a longitudinal training procedure, we assessed whether experience with functions highlights…
-
Creating objects and object categories for studying perception and perceptual learning.
Hauffen, Karin; Bart, Eugene; Brady, Mark; Kersten, Daniel; Hegdé, Jay
2012-11-02
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties. Many innovative and useful methods currently exist for creating novel objects and object categories (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
-
To call a cloud 'cirrus': sound symbolism in names for categories or items.
Ković, Vanja; Sučević, Jelena; Styles, Suzy J
2017-01-01
The aim of the present paper is to experimentally test whether sound symbolism has selective effects on labels with different ranges-of-reference within a simple noun-hierarchy. In two experiments, adult participants learned the make up of two categories of unfamiliar objects ('alien life forms'), and were passively exposed to either category-labels or item-labels, in a learning-by-guessing categorization task. Following category training, participants were tested on their visual discrimination of object pairs. For different groups of participants, the labels were either congruent or incongruent with the objects. In Experiment 1, when trained on items with individual labels, participants were worse (made more errors) at detecting visual object mismatches when trained labels were incongruent. In Experiment 2, when participants were trained on items in labelled categories, participants were faster at detecting a match if the trained labels were congruent, and faster at detecting a mismatch if the trained labels were incongruent. This pattern of results suggests that sound symbolism in category labels facilitates later similarity judgments when congruent, and discrimination when incongruent, whereas for item labels incongruence generates error in judgements of visual object differences. These findings reveal that sound symbolic congruence has a different outcome at different levels of labelling within a noun hierarchy. These effects emerged in the absence of the label itself, indicating subtle but pervasive effects on visual object processing.
-
Wu, Lin; Wang, Yang; Pan, Shirui
2017-12-01
It is now well established that sparse representation models are working effectively for many visual recognition tasks, and have pushed forward the success of dictionary learning therein. Recent studies over dictionary learning focus on learning discriminative atoms instead of purely reconstructive ones. However, the existence of intraclass diversities (i.e., data objects within the same category but exhibit large visual dissimilarities), and interclass similarities (i.e., data objects from distinct classes but share much visual similarities), makes it challenging to learn effective recognition models. To this end, a large number of labeled data objects are required to learn models which can effectively characterize these subtle differences. However, labeled data objects are always limited to access, committing it difficult to learn a monolithic dictionary that can be discriminative enough. To address the above limitations, in this paper, we propose a weakly-supervised dictionary learning method to automatically learn a discriminative dictionary by fully exploiting visual attribute correlations rather than label priors. In particular, the intrinsic attribute correlations are deployed as a critical cue to guide the process of object categorization, and then a set of subdictionaries are jointly learned with respect to each category. The resulting dictionary is highly discriminative and leads to intraclass diversity aware sparse representations. Extensive experiments on image classification and object recognition are conducted to show the effectiveness of our approach.
-
Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics
ERIC Educational Resources Information Center
Chen, Chi-hsin; Zhang, Yayun; Yu, Chen
2018-01-01
Objects in the world usually have names at different hierarchical levels (e.g., "beagle," "dog," "animal"). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use…
-
A REVIEW OF EFFORTS TO ORGANIZE INFORMATION ABOUT HUMAN LEARNING, TRANSFER, AND RETENTION.
ERIC Educational Resources Information Center
GINSBERG, ROSE; AND OTHERS
FOURTEEN EFFORTS TO ORGANIZE AVAILABLE INFORMATION ON HUMAN LEARNING, TRANSFER, AND RETENTION ARE SUMMARIZED AND EVALUATED ON SIX CRITERIA--BEHAVIORAL SIGNIFICANCE OF CATEGORIES, SCOPE, OBJECTIVITY AND RELIABILITY OF CATEGORIES, PROGNOSIS FOR THE SYSTEM, LOGICAL STRUCTURE, AND HEURISTIC VALUE OF THE SYSTEM. ATTENTION IS GIVEN TO OTHER SOURCES OF…
-
Object-graphs for context-aware visual category discovery.
Lee, Yong Jae; Grauman, Kristen
2012-02-01
How can knowing about some categories help us to discover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for recurring objects without human supervision, but existing methods assume no prior information and thus tend to perform poorly for cluttered scenes with multiple objects. We propose to leverage knowledge about previously learned categories to enable more accurate discovery, and address challenges in estimating their familiarity in unsegmented, unlabeled images. We introduce two variants of a novel object-graph descriptor to encode the 2D and 3D spatial layout of object-level co-occurrence patterns relative to an unfamiliar region and show that by using them to model the interaction between an image’s known and unknown objects, we can better detect new visual categories. Rather than mine for all categories from scratch, our method identifies new objects while drawing on useful cues from familiar ones. We evaluate our approach on several benchmark data sets and demonstrate clear improvements in discovery over conventional purely appearance-based baselines.
-
The Use of a Well-Designed Instructional Guideline in Online MBA Teaching
ERIC Educational Resources Information Center
Duesing, Robert J.; Ling, Juan; Yang, Jiaqin
2016-01-01
This study investigated the positive impact of a teaching practice on student learning outcomes in an online MBA program. An instructional project guideline was developed to help online students enhance their achieving required learning objectives corresponding to five categories of Bloom's Taxonomy. The course learning objectives are based on…
-
Online Feature Transformation Learning for Cross-Domain Object Category Recognition.
Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold
2017-06-09
In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.
-
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Hauffen, Karin; Bart, Eugene; Brady, Mark; Kersten, Daniel; Hegdé, Jay
2012-01-01
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis. PMID:23149420
-
Interservice Procedures for Instructional Systems Development. Phase 3. Develop
1975-08-01
Occur at wide intervals to be learned *Reads about the actions to *Occur at the end, but before be learned tests or on-the-job performance *Watches a...the particular sub-category. Use the learning objective action statement, conditions, standards, and the test item to help select which guidelines to...objective. EXAMPLE If you have a CLASSIFYING objective like "identifying poisonous plants,’ when you get to guideline 16. "To test learning, require the
-
Cao, Yongqiang; Grossberg, Stephen; Markowitz, Jeffrey
2011-12-01
All primates depend for their survival on being able to rapidly learn about and recognize objects. Objects may be visually detected at multiple positions, sizes, and viewpoints. How does the brain rapidly learn and recognize objects while scanning a scene with eye movements, without causing a combinatorial explosion in the number of cells that are needed? How does the brain avoid the problem of erroneously classifying parts of different objects together at the same or different positions in a visual scene? In monkeys and humans, a key area for such invariant object category learning and recognition is the inferotemporal cortex (IT). A neural model is proposed to explain how spatial and object attention coordinate the ability of IT to learn invariant category representations of objects that are seen at multiple positions, sizes, and viewpoints. The model clarifies how interactions within a hierarchy of processing stages in the visual brain accomplish this. These stages include the retina, lateral geniculate nucleus, and cortical areas V1, V2, V4, and IT in the brain's What cortical stream, as they interact with spatial attention processes within the parietal cortex of the Where cortical stream. The model builds upon the ARTSCAN model, which proposed how view-invariant object representations are generated. The positional ARTSCAN (pARTSCAN) model proposes how the following additional processes in the What cortical processing stream also enable position-invariant object representations to be learned: IT cells with persistent activity, and a combination of normalizing object category competition and a view-to-object learning law which together ensure that unambiguous views have a larger effect on object recognition than ambiguous views. The model explains how such invariant learning can be fooled when monkeys, or other primates, are presented with an object that is swapped with another object during eye movements to foveate the original object. The swapping procedure is predicted to prevent the reset of spatial attention, which would otherwise keep the representations of multiple objects from being combined by learning. Li and DiCarlo (2008) have presented neurophysiological data from monkeys showing how unsupervised natural experience in a target swapping experiment can rapidly alter object representations in IT. The model quantitatively simulates the swapping data by showing how the swapping procedure fools the spatial attention mechanism. More generally, the model provides a unifying framework, and testable predictions in both monkeys and humans, for understanding object learning data using neurophysiological methods in monkeys, and spatial attention, episodic learning, and memory retrieval data using functional imaging methods in humans. Copyright © 2011 Elsevier Ltd. All rights reserved.
-
Xu, Yang; D'Lauro, Christopher; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.
2013-01-01
Humans are remarkably proficient at categorizing visually-similar objects. To better understand the cortical basis of this categorization process, we used magnetoencephalography (MEG) to record neural activity while participants learned–with feedback–to discriminate two highly-similar, novel visual categories. We hypothesized that although prefrontal regions would mediate early category learning, this role would diminish with increasing category familiarity and that regions within the ventral visual pathway would come to play a more prominent role in encoding category-relevant information as learning progressed. Early in learning we observed some degree of categorical discriminability and predictability in both prefrontal cortex and the ventral visual pathway. Predictability improved significantly above chance in the ventral visual pathway over the course of learning with the left inferior temporal and fusiform gyri showing the greatest improvement in predictability between 150 and 250 ms (M200) during category learning. In contrast, there was no comparable increase in discriminability in prefrontal cortex with the only significant post-learning effect being a decrease in predictability in the inferior frontal gyrus between 250 and 350 ms (M300). Thus, the ventral visual pathway appears to encode learned visual categories over the long term. At the same time these results add to our understanding of the cortical origins of previously reported signature temporal components associated with perceptual learning. PMID:24146656
-
Grossberg, Stephen; Srinivasan, Karthik; Yazdanbakhsh, Arash
2015-01-01
How does the brain maintain stable fusion of 3D scenes when the eyes move? Every eye movement causes each retinal position to process a different set of scenic features, and thus the brain needs to binocularly fuse new combinations of features at each position after an eye movement. Despite these breaks in retinotopic fusion due to each movement, previously fused representations of a scene in depth often appear stable. The 3D ARTSCAN neural model proposes how the brain does this by unifying concepts about how multiple cortical areas in the What and Where cortical streams interact to coordinate processes of 3D boundary and surface perception, spatial attention, invariant object category learning, predictive remapping, eye movement control, and learned coordinate transformations. The model explains data from single neuron and psychophysical studies of covert visual attention shifts prior to eye movements. The model further clarifies how perceptual, attentional, and cognitive interactions among multiple brain regions (LGN, V1, V2, V3A, V4, MT, MST, PPC, LIP, ITp, ITa, SC) may accomplish predictive remapping as part of the process whereby view-invariant object categories are learned. These results build upon earlier neural models of 3D vision and figure-ground separation and the learning of invariant object categories as the eyes freely scan a scene. A key process concerns how an object's surface representation generates a form-fitting distribution of spatial attention, or attentional shroud, in parietal cortex that helps maintain the stability of multiple perceptual and cognitive processes. Predictive eye movement signals maintain the stability of the shroud, as well as of binocularly fused perceptual boundaries and surface representations. PMID:25642198
-
Grossberg, Stephen; Srinivasan, Karthik; Yazdanbakhsh, Arash
2014-01-01
How does the brain maintain stable fusion of 3D scenes when the eyes move? Every eye movement causes each retinal position to process a different set of scenic features, and thus the brain needs to binocularly fuse new combinations of features at each position after an eye movement. Despite these breaks in retinotopic fusion due to each movement, previously fused representations of a scene in depth often appear stable. The 3D ARTSCAN neural model proposes how the brain does this by unifying concepts about how multiple cortical areas in the What and Where cortical streams interact to coordinate processes of 3D boundary and surface perception, spatial attention, invariant object category learning, predictive remapping, eye movement control, and learned coordinate transformations. The model explains data from single neuron and psychophysical studies of covert visual attention shifts prior to eye movements. The model further clarifies how perceptual, attentional, and cognitive interactions among multiple brain regions (LGN, V1, V2, V3A, V4, MT, MST, PPC, LIP, ITp, ITa, SC) may accomplish predictive remapping as part of the process whereby view-invariant object categories are learned. These results build upon earlier neural models of 3D vision and figure-ground separation and the learning of invariant object categories as the eyes freely scan a scene. A key process concerns how an object's surface representation generates a form-fitting distribution of spatial attention, or attentional shroud, in parietal cortex that helps maintain the stability of multiple perceptual and cognitive processes. Predictive eye movement signals maintain the stability of the shroud, as well as of binocularly fused perceptual boundaries and surface representations.
-
NASA Astrophysics Data System (ADS)
Madokoro, H.; Tsukada, M.; Sato, K.
2013-07-01
This paper presents an unsupervised learning-based object category formation and recognition method for mobile robot vision. Our method has the following features: detection of feature points and description of features using a scale-invariant feature transform (SIFT), selection of target feature points using one class support vector machines (OC-SVMs), generation of visual words using self-organizing maps (SOMs), formation of labels using adaptive resonance theory 2 (ART-2), and creation and classification of categories on a category map of counter propagation networks (CPNs) for visualizing spatial relations between categories. Classification results of dynamic images using time-series images obtained using two different-size robots and according to movements respectively demonstrate that our method can visualize spatial relations of categories while maintaining time-series characteristics. Moreover, we emphasize the effectiveness of our method for category formation of appearance changes of objects.
-
Holistic processing from learned attention to parts.
Chua, Kao-Wei; Richler, Jennifer J; Gauthier, Isabel
2015-08-01
Attention helps us focus on what is most relevant to our goals, and prior work has shown that aspects of attention can be learned. Learned inattention to parts can abolish holistic processing of faces, but it is unknown whether learned attention to parts is sufficient to cause a change from part-based to holistic processing with objects. We trained subjects to individuate nonface objects (Greebles) from 2 categories: Ploks and Glips. Diagnostic information was in complementary halves for the 2 categories. Holistic processing was then tested with Plok-Glip composites that combined the kind of part that was diagnostic or nondiagnostic during training. Exposure to Greeble parts resulted in general failures of selective attention for nondiagnostic composites, but face-like holistic processing was only observed for diagnostic composites. These results demonstrated a novel link between learned attentional control and the acquisition of holistic processing. (c) 2015 APA, all rights reserved).
-
On the Role of Concepts in Learning and Instructional Design
ERIC Educational Resources Information Center
Jonassen, David H.
2006-01-01
The field of instructional design has traditionally treated concepts as discrete learning outcomes. Theoretically, learning concepts requires correctly isolating and applying attributes of specific objects into their correct categories. Similarity views of concept learning are unable to account for all of the rules governing concept formation,…
-
Parts and Relations in Young Children's Shape-Based Object Recognition
ERIC Educational Resources Information Center
Augustine, Elaine; Smith, Linda B.; Jones, Susan S.
2011-01-01
The ability to recognize common objects from sparse information about geometric shape emerges during the same period in which children learn object names and object categories. Hummel and Biederman's (1992) theory of object recognition proposes that the geometric shapes of objects have two components--geometric volumes representing major object…
-
Border collie comprehends object names as verbal referents.
Pilley, John W; Reid, Alliston K
2011-02-01
Four experiments investigated the ability of a border collie (Chaser) to acquire receptive language skills. Experiment 1 demonstrated that Chaser learned and retained, over a 3-year period of intensive training, the proper-noun names of 1022 objects. Experiment 2 presented random pair-wise combinations of three commands and three names, and demonstrated that she understood the separate meanings of proper-noun names and commands. Chaser understood that names refer to objects, independent of the behavior directed toward those objects. Experiment 3 demonstrated Chaser's ability to learn three common nouns--words that represent categories. Chaser demonstrated one-to-many (common noun) and many-to-one (multiple-name) name-object mappings. Experiment 4 demonstrated Chaser's ability to learn words by inferential reasoning by exclusion--inferring the name of an object based on its novelty among familiar objects that already had names. Together, these studies indicate that Chaser acquired referential understanding of nouns, an ability normally attributed to children, which included: (a) awareness that words may refer to objects, (b) awareness of verbal cues that map words upon the object referent, and (c) awareness that names may refer to unique objects or categories of objects, independent of the behaviors directed toward those objects. Copyright © 2010 Elsevier B.V. All rights reserved.
-
Freundlieb, Nils; Ridder, Volker; Dobel, Christian; Enriquez-Geppert, Stefanie; Baumgaertner, Annette; Zwitserlood, Pienie; Gerloff, Christian; Hummel, Friedhelm C; Liuzzi, Gianpiero
2012-01-01
Despite a growing number of studies, the neurophysiology of adult vocabulary acquisition is still poorly understood. One reason is that paradigms that can easily be combined with neuroscientfic methods are rare. Here, we tested the efficiency of two paradigms for vocabulary (re-) acquisition, and compared the learning of novel words for actions and objects. Cortical networks involved in adult native-language word processing are widespread, with differences postulated between words for objects and actions. Words and what they stand for are supposed to be grounded in perceptual and sensorimotor brain circuits depending on their meaning. If there are specific brain representations for different word categories, we hypothesized behavioural differences in the learning of action-related and object-related words. Paradigm A, with the learning of novel words for body-related actions spread out over a number of days, revealed fast learning of these new action words, and stable retention up to 4 weeks after training. The single-session Paradigm B employed objects and actions. Performance during acquisition did not differ between action-related and object-related words (time*word category: p = 0.01), but the translation rate was clearly better for object-related (79%) than for action-related words (53%, p = 0.002). Both paradigms yielded robust associative learning of novel action-related words, as previously demonstrated for object-related words. Translation success differed for action- and object-related words, which may indicate different neural mechanisms. The paradigms tested here are well suited to investigate such differences with neuroscientific means. Given the stable retention and minimal requirements for conscious effort, these learning paradigms are promising for vocabulary re-learning in brain-lesioned people. In combination with neuroimaging, neuro-stimulation or pharmacological intervention, they may well advance the understanding of language learning to optimize therapeutic strategies.
-
Bobb, Susan C; Mani, Nivedita
2013-06-01
The current study investigated the interaction of implicit grammatical gender and semantic category knowledge during object identification. German-learning toddlers (24-month-olds) were presented with picture pairs and heard a noun (without a preceding article) labeling one of the pictures. Labels for target and distracter images either matched or mismatched in grammatical gender and either matched or mismatched in semantic category. When target and distracter overlapped in both semantic and gender information, target recognition was impaired compared with when target and distracter overlapped on only one dimension. Results suggest that by 24 months of age, German-learning toddlers are already forming not only semantic but also grammatical gender categories and that these sources of information are activated, and interact, during object identification. Copyright © 2013 Elsevier Inc. All rights reserved.
-
Using spoken words to guide open-ended category formation.
Chauhan, Aneesh; Seabra Lopes, Luís
2011-11-01
Naming is a powerful cognitive tool that facilitates categorization by forming an association between words and their referents. There is evidence in child development literature that strong links exist between early word-learning and conceptual development. A growing view is also emerging that language is a cultural product created and acquired through social interactions. Inspired by these studies, this paper presents a novel learning architecture for category formation and vocabulary acquisition in robots through active interaction with humans. This architecture is open-ended and is capable of acquiring new categories and category names incrementally. The process can be compared to language grounding in children at single-word stage. The robot is embodied with visual and auditory sensors for world perception. A human instructor uses speech to teach the robot the names of the objects present in a visually shared environment. The robot uses its perceptual input to ground these spoken words and dynamically form/organize category descriptions in order to achieve better categorization. To evaluate the learning system at word-learning and category formation tasks, two experiments were conducted using a simple language game involving naming and corrective feedback actions from the human user. The obtained results are presented and discussed in detail.
-
The effectiveness of physics learning material based on South Kalimantan local wisdom
NASA Astrophysics Data System (ADS)
Hartini, Sri; Misbah, Helda, Dewantara, Dewi
2017-08-01
The local wisdom is essential element incorporated into learning process. However, there are no learning materials in Physics learning process which contain South Kalimantan local wisdom. Therefore, it is necessary to develop a Physics learning material based on South Kalimantan local wisdom. The objective of this research is to produce products in the form of learning material based on South Kalimantan local wisdom that is feasible and effective based on the validity, practicality, effectiveness of learning material and achievement of waja sampai kaputing (wasaka) character. This research is a research and development which refers to the ADDIE model. Data were obtained through the validation sheet of learning material, questionnaire, the test of learning outcomes and the sheet of character assesment. The research results showed that (1) the validity category of the learning material was very valid, (2) the practicality category of the learning material was very practical, (3) the effectiveness category of thelearning material was very effective, and (4) the achivement of wasaka characters was very good. In conclusion, the Physics learning materials based on South Kalimantan local wisdom are feasible and effective to be used in learning activities.
-
2014-01-01
Neuropsychology, in press Simulating Category Learning and Set Shifting Deficits in Patients Weight-Restored from Anorexia Nervosa J...University Objective: To examine set shifting in a group of women previously diagnosed with anorexia nervosa (AN) who are now weight-restored (AN-WR...participant fails to switch to the new rule but rather persists with the previously correct rule. Adult patients with Anorexia Nervosa (AN) are often impaired
-
The cognitive capabilities of farm animals: categorisation learning in dwarf goats (Capra hircus).
Meyer, Susann; Nürnberg, Gerd; Puppe, Birger; Langbein, Jan
2012-07-01
The ability to establish categories enables organisms to classify stimuli, objects and events by assessing perceptual, associative or rational similarities and provides the basis for higher cognitive processing. The cognitive capabilities of farm animals are receiving increasing attention in applied ethology, a development driven primarily by scientifically based efforts to improve animal welfare. The present study investigated the learning of perceptual categories in Nigerian dwarf goats (Capra hircus) by using an automated learning device installed in the animals' pen. Thirteen group-housed goats were trained in a closed-economy approach to discriminate artificial two-dimensional symbols presented in a four-choice design. The symbols belonged to two categories: category I, black symbols with an open centre (rewarded) and category II, the same symbols but filled black (unrewarded). One symbol from category I and three different symbols from category II were used to define a discrimination problem. After the training of eight problems, the animals were presented with a transfer series containing the training problems interspersed with completely new problems made from new symbols belonging to the same categories. The results clearly demonstrate that dwarf goats are able to form categories based on similarities in the visual appearance of artificial symbols and to generalise across new symbols. However, the goats had difficulties in discriminating specific symbols. It is probable that perceptual problems caused these difficulties. Nevertheless, the present study suggests that goats housed under farming conditions have well-developed cognitive abilities, including learning of open-ended categories. This result could prove beneficial by facilitating animals' adaptation to housing environments that favour their cognitive capabilities.
-
Davis, Tyler; Love, Bradley C.; Preston, Alison R.
2012-01-01
Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and adjust their representations to support behavior in future encounters. Many techniques that are available to understand the neural basis of category learning assume that the multiple processes that subserve it can be neatly separated between different trials of an experiment. Model-based functional magnetic resonance imaging offers a promising tool to separate multiple, simultaneously occurring processes and bring the analysis of neuroimaging data more in line with category learning’s dynamic and multifaceted nature. We use model-based imaging to explore the neural basis of recognition and entropy signals in the medial temporal lobe and striatum that are engaged while participants learn to categorize novel stimuli. Consistent with theories suggesting a role for the anterior hippocampus and ventral striatum in motivated learning in response to uncertainty, we find that activation in both regions correlates with a model-based measure of entropy. Simultaneously, separate subregions of the hippocampus and striatum exhibit activation correlated with a model-based recognition strength measure. Our results suggest that model-based analyses are exceptionally useful for extracting information about cognitive processes from neuroimaging data. Models provide a basis for identifying the multiple neural processes that contribute to behavior, and neuroimaging data can provide a powerful test bed for constraining and testing model predictions. PMID:22746951
-
Taniguchi, Akira; Taniguchi, Tadahiro; Cangelosi, Angelo
2017-01-01
In this paper, we propose a Bayesian generative model that can form multiple categories based on each sensory-channel and can associate words with any of the four sensory-channels (action, position, object, and color). This paper focuses on cross-situational learning using the co-occurrence between words and information of sensory-channels in complex situations rather than conventional situations of cross-situational learning. We conducted a learning scenario using a simulator and a real humanoid iCub robot. In the scenario, a human tutor provided a sentence that describes an object of visual attention and an accompanying action to the robot. The scenario was set as follows: the number of words per sensory-channel was three or four, and the number of trials for learning was 20 and 40 for the simulator and 25 and 40 for the real robot. The experimental results showed that the proposed method was able to estimate the multiple categorizations and to learn the relationships between multiple sensory-channels and words accurately. In addition, we conducted an action generation task and an action description task based on word meanings learned in the cross-situational learning scenario. The experimental results showed that the robot could successfully use the word meanings learned by using the proposed method. PMID:29311888
-
Lech, Robert K; Güntürkün, Onur; Suchan, Boris
2016-09-15
The aim of the present study was to examine the contributions of different brain structures to prototype- and exemplar-based category learning using functional magnetic resonance imaging (fMRI). Twenty-eight subjects performed a categorization task in which they had to assign prototypes and exceptions to two different families. This test procedure usually produces different learning curves for prototype and exception stimuli. Our behavioral data replicated these previous findings by showing an initially superior performance for prototypes and typical stimuli and a switch from a prototype-based to an exemplar-based categorization for exceptions in the later learning phases. Since performance varied, we divided participants into learners and non-learners. Analysis of the functional imaging data revealed that the interaction of group (learners vs. non-learners) and block (Block 5 vs. Block 1) yielded an activation of the left fusiform gyrus for the processing of prototypes, and an activation of the right hippocampus for exceptions after learning the categories. Thus, successful prototype- and exemplar-based category learning is associated with activations of complementary neural substrates that constitute object-based processes of the ventral visual stream and their interaction with unique-cue representations, possibly based on sparse coding within the hippocampus. Copyright © 2016 Elsevier B.V. All rights reserved.
-
The lasting effects of process-specific versus stimulus-specific learning during infancy.
Hadley, Hillary; Pickron, Charisse B; Scott, Lisa S
2015-09-01
The capacity to tell the difference between two faces within an infrequently experienced face group (e.g. other species, other race) declines from 6 to 9 months of age unless infants learn to match these faces with individual-level names. Similarly, the use of individual-level labels can also facilitate differentiation of a group of non-face objects (strollers). This early learning leads to increased neural specialization for previously unfamiliar face or object groups. The current investigation aimed to determine whether early conceptual learning between 6 and 9 months leads to sustained behavioral advantages and neural changes in these same children at 4-6 years of age. Results suggest that relative to a control group of children with no previous training and to children with infant category-level naming experience, children with early individual-level training exhibited faster response times to human faces. Further, individual-level training with a face group - but not an object group - led to more adult-like neural responses for human faces. These results suggest that early individual-level learning results in long-lasting process-specific effects, which benefit categories that continue to be perceived and recognized at the individual level (e.g. human faces). © 2014 John Wiley & Sons Ltd.
-
Real-world visual statistics and infants' first-learned object names
Clerkin, Elizabeth M.; Hart, Elizabeth; Rehg, James M.; Yu, Chen
2017-01-01
We offer a new solution to the unsolved problem of how infants break into word learning based on the visual statistics of everyday infant-perspective scenes. Images from head camera video captured by 8 1/2 to 10 1/2 month-old infants at 147 at-home mealtime events were analysed for the objects in view. The images were found to be highly cluttered with many different objects in view. However, the frequency distribution of object categories was extremely right skewed such that a very small set of objects was pervasively present—a fact that may substantially reduce the problem of referential ambiguity. The statistical structure of objects in these infant egocentric scenes differs markedly from that in the training sets used in computational models and in experiments on statistical word-referent learning. Therefore, the results also indicate a need to re-examine current explanations of how infants break into word learning. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872373
-
Redundancy Matters: Flexible Learning of Multiple Contingencies in Infants
ERIC Educational Resources Information Center
Sloutsky, Vladimir M.; Robinson, Christopher W.
2013-01-01
Many objects and events can be categorized in different ways, and learning multiple categories in parallel often requires flexibly attending to different stimulus dimensions in different contexts. Although infants and young children often exhibit poor attentional control, several theoretical proposals argue that such flexibility can be achieved…
-
Second Label Learning in Bilingual and Monolingual Infants
ERIC Educational Resources Information Center
Kandhadai, Padmapriya; Hall, D. Geoffrey; Werker, Janet F.
2017-01-01
"Mutual exclusivity" is the assumption that each object has only one category label. Prior research suggests that bilingual infants, unlike monolingual infants, fail to adhere to this assumption to guide word learning. Yet previous work has not addressed whether bilingual infants systematically interpret a novel word for a familiar…
-
The Magic Bullet: A Tool for Assessing and Evaluating Learning Potential in Games
ERIC Educational Resources Information Center
Becker, Katrin
2011-01-01
This paper outlines a simple and effective model that can be used to evaluate and design educational digital games. It also facilitates the formulation of strategies for using existing games in learning contexts. The model categorizes game goals and learning objectives into one or more of four possible categories. An overview of the model is…
-
Recognition-induced forgetting is not due to category-based set size.
Maxcey, Ashleigh M
2016-01-01
What are the consequences of accessing a visual long-term memory representation? Previous work has shown that accessing a long-term memory representation via retrieval improves memory for the targeted item and hurts memory for related items, a phenomenon called retrieval-induced forgetting. Recently we found a similar forgetting phenomenon with recognition of visual objects. Recognition-induced forgetting occurs when practice recognizing an object during a two-alternative forced-choice task, from a group of objects learned at the same time, leads to worse memory for objects from that group that were not practiced. An alternative explanation of this effect is that category-based set size is inducing forgetting, not recognition practice as claimed by some researchers. This alternative explanation is possible because during recognition practice subjects make old-new judgments in a two-alternative forced-choice task, and are thus exposed to more objects from practiced categories, potentially inducing forgetting due to set-size. Herein I pitted the category-based set size hypothesis against the recognition-induced forgetting hypothesis. To this end, I parametrically manipulated the amount of practice objects received in the recognition-induced forgetting paradigm. If forgetting is due to category-based set size, then the magnitude of forgetting of related objects will increase as the number of practice trials increases. If forgetting is recognition induced, the set size of exemplars from any given category should not be predictive of memory for practiced objects. Consistent with this latter hypothesis, additional practice systematically improved memory for practiced objects, but did not systematically affect forgetting of related objects. These results firmly establish that recognition practice induces forgetting of related memories. Future directions and important real-world applications of using recognition to access our visual memories of previously encountered objects are discussed.
-
First-Pass Processing of Value Cues in the Ventral Visual Pathway.
Sasikumar, Dennis; Emeric, Erik; Stuphorn, Veit; Connor, Charles E
2018-02-19
Real-world value often depends on subtle, continuously variable visual cues specific to particular object categories, like the tailoring of a suit, the condition of an automobile, or the construction of a house. Here, we used microelectrode recording in behaving monkeys to test two possible mechanisms for category-specific value-cue processing: (1) previous findings suggest that prefrontal cortex (PFC) identifies object categories, and based on category identity, PFC could use top-down attentional modulation to enhance visual processing of category-specific value cues, providing signals to PFC for calculating value, and (2) a faster mechanism would be first-pass visual processing of category-specific value cues, immediately providing the necessary visual information to PFC. This, however, would require learned mechanisms for processing the appropriate cues in a given object category. To test these hypotheses, we trained monkeys to discriminate value in four letter-like stimulus categories. Each category had a different, continuously variable shape cue that signified value (liquid reward amount) as well as other cues that were irrelevant. Monkeys chose between stimuli of different reward values. Consistent with the first-pass hypothesis, we found early signals for category-specific value cues in area TE (the final stage in monkey ventral visual pathway) beginning 81 ms after stimulus onset-essentially at the start of TE responses. Task-related activity emerged in lateral PFC approximately 40 ms later and consisted mainly of category-invariant value tuning. Our results show that, for familiar, behaviorally relevant object categories, high-level ventral pathway cortex can implement rapid, first-pass processing of category-specific value cues. Copyright © 2018 Elsevier Ltd. All rights reserved.
-
Deane-Coe, Kirsten K; Sarvary, Mark A; Owens, Thomas G
2017-01-01
In an undergraduate introductory biology laboratory course, we used a summative assessment to directly test the learning objective that students will be able to apply course material to increasingly novel and complex situations. Using a factorial framework, we developed multiple true-false questions to fall along axes of novelty and complexity, which resulted in four categories of questions: familiar content and low complexity (category A); novel content and low complexity (category B); familiar content and high complexity (category C); and novel content and high complexity (category D). On average, students scored more than 70% on all questions, indicating that the course largely met this learning objective. However, students scored highest on questions in category A, likely because they were most similar to course content, and lowest on questions in categories C and D. While we anticipated students would score equally on questions for which either novelty or complexity was altered (but not both), we observed that student scores in category C were lower than in category B. Furthermore, students performed equally poorly on all questions for which complexity was higher (categories C and D), even those containing familiar content, suggesting that application of course material to increasingly complex situations is particularly challenging to students. © 2017 K. K. Deane-Coe et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
-
Triangular model integrating clinical teaching and assessment
Abdelaziz, Adel; Koshak, Emad
2014-01-01
Structuring clinical teaching is a challenge facing medical education curriculum designers. A variety of instructional methods on different domains of learning are indicated to accommodate different learning styles. Conventional methods of clinical teaching, like training in ambulatory care settings, are prone to the factor of coincidence in having varieties of patient presentations. Accordingly, alternative methods of instruction are indicated to compensate for the deficiencies of these conventional methods. This paper presents an initiative that can be used to design a checklist as a blueprint to guide appropriate selection and implementation of teaching/learning and assessment methods in each of the educational courses and modules based on educational objectives. Three categories of instructional methods were identified, and within each a variety of methods were included. These categories are classroom-type settings, health services-based settings, and community service-based settings. Such categories have framed our triangular model of clinical teaching and assessment. PMID:24624002
-
Triangular model integrating clinical teaching and assessment.
Abdelaziz, Adel; Koshak, Emad
2014-01-01
Structuring clinical teaching is a challenge facing medical education curriculum designers. A variety of instructional methods on different domains of learning are indicated to accommodate different learning styles. Conventional methods of clinical teaching, like training in ambulatory care settings, are prone to the factor of coincidence in having varieties of patient presentations. Accordingly, alternative methods of instruction are indicated to compensate for the deficiencies of these conventional methods. This paper presents an initiative that can be used to design a checklist as a blueprint to guide appropriate selection and implementation of teaching/learning and assessment methods in each of the educational courses and modules based on educational objectives. Three categories of instructional methods were identified, and within each a variety of methods were included. These categories are classroom-type settings, health services-based settings, and community service-based settings. Such categories have framed our triangular model of clinical teaching and assessment.
-
Grossberg, Stephen; Markowitz, Jeffrey; Cao, Yongqiang
2011-12-01
Visual object recognition is an essential accomplishment of advanced brains. Object recognition needs to be tolerant, or invariant, with respect to changes in object position, size, and view. In monkeys and humans, a key area for recognition is the anterior inferotemporal cortex (ITa). Recent neurophysiological data show that ITa cells with high object selectivity often have low position tolerance. We propose a neural model whose cells learn to simulate this tradeoff, as well as ITa responses to image morphs, while explaining how invariant recognition properties may arise in stages due to processes across multiple cortical areas. These processes include the cortical magnification factor, multiple receptive field sizes, and top-down attentive matching and learning properties that may be tuned by task requirements to attend to either concrete or abstract visual features with different levels of vigilance. The model predicts that data from the tradeoff and image morph tasks emerge from different levels of vigilance in the animals performing them. This result illustrates how different vigilance requirements of a task may change the course of category learning, notably the critical features that are attended and incorporated into learned category prototypes. The model outlines a path for developing an animal model of how defective vigilance control can lead to symptoms of various mental disorders, such as autism and amnesia. Copyright © 2011 Elsevier Ltd. All rights reserved.
-
A probabilistic model of cross-categorization.
Shafto, Patrick; Kemp, Charles; Mansinghka, Vikash; Tenenbaum, Joshua B
2011-07-01
Most natural domains can be represented in multiple ways: we can categorize foods in terms of their nutritional content or social role, animals in terms of their taxonomic groupings or their ecological niches, and musical instruments in terms of their taxonomic categories or social uses. Previous approaches to modeling human categorization have largely ignored the problem of cross-categorization, focusing on learning just a single system of categories that explains all of the features. Cross-categorization presents a difficult problem: how can we infer categories without first knowing which features the categories are meant to explain? We present a novel model that suggests that human cross-categorization is a result of joint inference about multiple systems of categories and the features that they explain. We also formalize two commonly proposed alternative explanations for cross-categorization behavior: a features-first and an objects-first approach. The features-first approach suggests that cross-categorization is a consequence of attentional processes, where features are selected by an attentional mechanism first and categories are derived second. The objects-first approach suggests that cross-categorization is a consequence of repeated, sequential attempts to explain features, where categories are derived first, then features that are poorly explained are recategorized. We present two sets of simulations and experiments testing the models' predictions about human categorization. We find that an approach based on joint inference provides the best fit to human categorization behavior, and we suggest that a full account of human category learning will need to incorporate something akin to these capabilities. Copyright © 2011 Elsevier B.V. All rights reserved.
-
Children Use Object-Level Category Knowledge to Detect Changes in Complex Auditory Scenes
ERIC Educational Resources Information Center
Vanden Bosch der Nederlanden, Christina M.; Snyder, Joel S.; Hannon, Erin E.
2016-01-01
Children interact with and learn about all types of sound sources, including dogs, bells, trains, and human beings. Although it is clear that knowledge of semantic categories for everyday sights and sounds develops during childhood, there are very few studies examining how children use this knowledge to make sense of auditory scenes. We used a…
-
On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products.
Varshney, Kush R; Alemzadeh, Homa
2017-09-01
Machine learning algorithms increasingly influence our decisions and interact with us in all parts of our daily lives. Therefore, just as we consider the safety of power plants, highways, and a variety of other engineered socio-technical systems, we must also take into account the safety of systems involving machine learning. Heretofore, the definition of safety has not been formalized in a machine learning context. In this article, we do so by defining machine learning safety in terms of risk, epistemic uncertainty, and the harm incurred by unwanted outcomes. We then use this definition to examine safety in all sorts of applications in cyber-physical systems, decision sciences, and data products. We find that the foundational principle of modern statistical machine learning, empirical risk minimization, is not always a sufficient objective. We discuss how four different categories of strategies for achieving safety in engineering, including inherently safe design, safety reserves, safe fail, and procedural safeguards can be mapped to a machine learning context. We then discuss example techniques that can be adopted in each category, such as considering interpretability and causality of predictive models, objective functions beyond expected prediction accuracy, human involvement for labeling difficult or rare examples, and user experience design of software and open data.
-
Foley, Nicholas C.; Grossberg, Stephen; Mingolla, Ennio
2015-01-01
How are spatial and object attention coordinated to achieve rapid object learning and recognition during eye movement search? How do prefrontal priming and parietal spatial mechanisms interact to determine the reaction time costs of intra-object attention shifts, inter-object attention shifts, and shifts between visible objects and covertly cued locations? What factors underlie individual differences in the timing and frequency of such attentional shifts? How do transient and sustained spatial attentional mechanisms work and interact? How can volition, mediated via the basal ganglia, influence the span of spatial attention? A neural model is developed of how spatial attention in the where cortical stream coordinates view-invariant object category learning in the what cortical stream under free viewing conditions. The model simulates psychological data about the dynamics of covert attention priming and switching requiring multifocal attention without eye movements. The model predicts how “attentional shrouds” are formed when surface representations in cortical area V4 resonate with spatial attention in posterior parietal cortex (PPC) and prefrontal cortex (PFC), while shrouds compete among themselves for dominance. Winning shrouds support invariant object category learning, and active surface-shroud resonances support conscious surface perception and recognition. Attentive competition between multiple objects and cues simulates reaction-time data from the two-object cueing paradigm. The relative strength of sustained surface-driven and fast-transient motion-driven spatial attention controls individual differences in reaction time for invalid cues. Competition between surface-driven attentional shrouds controls individual differences in detection rate of peripheral targets in useful-field-of-view tasks. The model proposes how the strength of competition can be mediated, though learning or momentary changes in volition, by the basal ganglia. A new explanation of crowding shows how the cortical magnification factor, among other variables, can cause multiple object surfaces to share a single surface-shroud resonance, thereby preventing recognition of the individual objects. PMID:22425615
-
Foley, Nicholas C; Grossberg, Stephen; Mingolla, Ennio
2012-08-01
How are spatial and object attention coordinated to achieve rapid object learning and recognition during eye movement search? How do prefrontal priming and parietal spatial mechanisms interact to determine the reaction time costs of intra-object attention shifts, inter-object attention shifts, and shifts between visible objects and covertly cued locations? What factors underlie individual differences in the timing and frequency of such attentional shifts? How do transient and sustained spatial attentional mechanisms work and interact? How can volition, mediated via the basal ganglia, influence the span of spatial attention? A neural model is developed of how spatial attention in the where cortical stream coordinates view-invariant object category learning in the what cortical stream under free viewing conditions. The model simulates psychological data about the dynamics of covert attention priming and switching requiring multifocal attention without eye movements. The model predicts how "attentional shrouds" are formed when surface representations in cortical area V4 resonate with spatial attention in posterior parietal cortex (PPC) and prefrontal cortex (PFC), while shrouds compete among themselves for dominance. Winning shrouds support invariant object category learning, and active surface-shroud resonances support conscious surface perception and recognition. Attentive competition between multiple objects and cues simulates reaction-time data from the two-object cueing paradigm. The relative strength of sustained surface-driven and fast-transient motion-driven spatial attention controls individual differences in reaction time for invalid cues. Competition between surface-driven attentional shrouds controls individual differences in detection rate of peripheral targets in useful-field-of-view tasks. The model proposes how the strength of competition can be mediated, though learning or momentary changes in volition, by the basal ganglia. A new explanation of crowding shows how the cortical magnification factor, among other variables, can cause multiple object surfaces to share a single surface-shroud resonance, thereby preventing recognition of the individual objects. Copyright © 2012 Elsevier Inc. All rights reserved.
-
Real-world visual statistics and infants' first-learned object names.
Clerkin, Elizabeth M; Hart, Elizabeth; Rehg, James M; Yu, Chen; Smith, Linda B
2017-01-05
We offer a new solution to the unsolved problem of how infants break into word learning based on the visual statistics of everyday infant-perspective scenes. Images from head camera video captured by 8 1/2 to 10 1/2 month-old infants at 147 at-home mealtime events were analysed for the objects in view. The images were found to be highly cluttered with many different objects in view. However, the frequency distribution of object categories was extremely right skewed such that a very small set of objects was pervasively present-a fact that may substantially reduce the problem of referential ambiguity. The statistical structure of objects in these infant egocentric scenes differs markedly from that in the training sets used in computational models and in experiments on statistical word-referent learning. Therefore, the results also indicate a need to re-examine current explanations of how infants break into word learning.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).
-
Navarrete, Jairo A; Dartnell, Pablo
2017-08-01
Category Theory, a branch of mathematics, has shown promise as a modeling framework for higher-level cognition. We introduce an algebraic model for analogy that uses the language of category theory to explore analogy-related cognitive phenomena. To illustrate the potential of this approach, we use this model to explore three objects of study in cognitive literature. First, (a) we use commutative diagrams to analyze an effect of playing particular educational board games on the learning of numbers. Second, (b) we employ a notion called coequalizer as a formal model of re-representation that explains a property of computational models of analogy called "flexibility" whereby non-similar representational elements are considered matches and placed in structural correspondence. Finally, (c) we build a formal learning model which shows that re-representation, language processing and analogy making can explain the acquisition of knowledge of rational numbers. These objects of study provide a picture of acquisition of numerical knowledge that is compatible with empirical evidence and offers insights on possible connections between notions such as relational knowledge, analogy, learning, conceptual knowledge, re-representation and procedural knowledge. This suggests that the approach presented here facilitates mathematical modeling of cognition and provides novel ways to think about analogy-related cognitive phenomena.
-
2017-01-01
Category Theory, a branch of mathematics, has shown promise as a modeling framework for higher-level cognition. We introduce an algebraic model for analogy that uses the language of category theory to explore analogy-related cognitive phenomena. To illustrate the potential of this approach, we use this model to explore three objects of study in cognitive literature. First, (a) we use commutative diagrams to analyze an effect of playing particular educational board games on the learning of numbers. Second, (b) we employ a notion called coequalizer as a formal model of re-representation that explains a property of computational models of analogy called “flexibility” whereby non-similar representational elements are considered matches and placed in structural correspondence. Finally, (c) we build a formal learning model which shows that re-representation, language processing and analogy making can explain the acquisition of knowledge of rational numbers. These objects of study provide a picture of acquisition of numerical knowledge that is compatible with empirical evidence and offers insights on possible connections between notions such as relational knowledge, analogy, learning, conceptual knowledge, re-representation and procedural knowledge. This suggests that the approach presented here facilitates mathematical modeling of cognition and provides novel ways to think about analogy-related cognitive phenomena. PMID:28841643
-
ERIC Educational Resources Information Center
Young, Shelley Shwu-Ching; Huang, Yi-Long; Jang, Jyh-Shing Roger
2000-01-01
Describes the development and implementation process of a Web-based science museum in Taiwan. Topics include use of the Internet; lifelong distance learning; museums and the Internet; objectives of the science museum; funding; categories of exhibitions; analysis of Web users; homepage characteristics; graphics and the effect on speed; and future…
-
A Hierarchical and Contextual Model for Learning and Recognizing Highly Variant Visual Categories
2010-01-01
neighboring pattern primitives, to create our model. We also present a minimax entropy framework for automatically learning which contextual constraints are...Grammars . . . . . . . . . . . . . . . . . . 19 3.2 Markov Random Fields . . . . . . . . . . . . . . . . . . . . . . . . 23 3.3 Creating a Contextual...Compositional Boosting. . . . . 119 7.8 Top-down hallucinations of missing objects. . . . . . . . . . . . . . . 121 7.9 The bottom-up to top-down
-
Zinszer, Benjamin D; Malt, Barbara C; Ameel, Eef; Li, Ping
2014-01-01
SECOND LANGUAGE LEARNERS FACE A DUAL CHALLENGE IN VOCABULARY LEARNING: First, they must learn new names for the 100s of common objects that they encounter every day. Second, after some time, they discover that these names do not generalize according to the same rules used in their first language. Lexical categories frequently differ between languages (Malt et al., 1999), and successful language learning requires that bilinguals learn not just new words but new patterns for labeling objects. In the present study, Chinese learners of English with varying language histories and resident in two different language settings (Beijing, China and State College, PA, USA) named 67 photographs of common serving dishes (e.g., cups, plates, and bowls) in both Chinese and English. Participants' response patterns were quantified in terms of similarity to the responses of functionally monolingual native speakers of Chinese and English and showed the cross-language convergence previously observed in simultaneous bilinguals (Ameel et al., 2005). For English, bilinguals' names for each individual stimulus were also compared to the dominant name generated by the native speakers for the object. Using two statistical models, we disentangle the effects of several highly interactive variables from bilinguals' language histories and the naming norms of the native speaker community to predict inter-personal and inter-item variation in L2 (English) native-likeness. We find only a modest age of earliest exposure effect on L2 category native-likeness, but importantly, we find that classroom instruction in L2 negatively impacts L2 category native-likeness, even after significant immersion experience. We also identify a significant role of both L1 and L2 norms in bilinguals' L2 picture naming responses.
-
Zinszer, Benjamin D.; Malt, Barbara C.; Ameel, Eef; Li, Ping
2014-01-01
Second language learners face a dual challenge in vocabulary learning: First, they must learn new names for the 100s of common objects that they encounter every day. Second, after some time, they discover that these names do not generalize according to the same rules used in their first language. Lexical categories frequently differ between languages (Malt et al., 1999), and successful language learning requires that bilinguals learn not just new words but new patterns for labeling objects. In the present study, Chinese learners of English with varying language histories and resident in two different language settings (Beijing, China and State College, PA, USA) named 67 photographs of common serving dishes (e.g., cups, plates, and bowls) in both Chinese and English. Participants’ response patterns were quantified in terms of similarity to the responses of functionally monolingual native speakers of Chinese and English and showed the cross-language convergence previously observed in simultaneous bilinguals (Ameel et al., 2005). For English, bilinguals’ names for each individual stimulus were also compared to the dominant name generated by the native speakers for the object. Using two statistical models, we disentangle the effects of several highly interactive variables from bilinguals’ language histories and the naming norms of the native speaker community to predict inter-personal and inter-item variation in L2 (English) native-likeness. We find only a modest age of earliest exposure effect on L2 category native-likeness, but importantly, we find that classroom instruction in L2 negatively impacts L2 category native-likeness, even after significant immersion experience. We also identify a significant role of both L1 and L2 norms in bilinguals’ L2 picture naming responses. PMID:25386149
-
Evans, Benjamin D; Stringer, Simon M
2015-04-01
Learning to recognise objects and faces is an important and challenging problem tackled by the primate ventral visual system. One major difficulty lies in recognising an object despite profound differences in the retinal images it projects, due to changes in view, scale, position and other identity-preserving transformations. Several models of the ventral visual system have been successful in coping with these issues, but have typically been privileged by exposure to only one object at a time. In natural scenes, however, the challenges of object recognition are typically further compounded by the presence of several objects which should be perceived as distinct entities. In the present work, we explore one possible mechanism by which the visual system may overcome these two difficulties simultaneously, through segmenting unseen (artificial) stimuli using information about their category encoded in plastic lateral connections. We demonstrate that these experience-guided lateral interactions robustly organise input representations into perceptual cycles, allowing feed-forward connections trained with spike-timing-dependent plasticity to form independent, translation-invariant output representations. We present these simulations as a functional explanation for the role of plasticity in the lateral connectivity of visual cortex.
-
A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning.
Loonis, Roman F; Brincat, Scott L; Antzoulatos, Evan G; Miller, Earl K
2017-10-11
A meta-analysis of non-human primates performing three different tasks (Object-Match, Category-Match, and Category-Saccade associations) revealed signatures of explicit and implicit learning. Performance improved equally following correct and error trials in the Match (explicit) tasks, but it improved more after correct trials in the Saccade (implicit) task, a signature of explicit versus implicit learning. Likewise, error-related negativity, a marker for error processing, was greater in the Match (explicit) tasks. All tasks showed an increase in alpha/beta (10-30 Hz) synchrony after correct choices. However, only the implicit task showed an increase in theta (3-7 Hz) synchrony after correct choices that decreased with learning. In contrast, in the explicit tasks, alpha/beta synchrony increased with learning and decreased thereafter. Our results suggest that explicit versus implicit learning engages different neural mechanisms that rely on different patterns of oscillatory synchrony. Copyright © 2017 Elsevier Inc. All rights reserved.
-
Perceptual and conceptual similarities facilitate the generalization of instructed fear.
Bennett, Marc; Vervoort, Ellen; Boddez, Yannick; Hermans, Dirk; Baeyens, Frank
2015-09-01
Learned fear can generalize to neutral events due their perceptual and conceptual similarity with threat relevant stimuli. This study simultaneously examined these forms of generalization to model the expansion of fear in anxiety disorders. First, artificial categories involving sounds, nonsense words and animal-like objects were established. Next, the words from one category were paired with threatening information while the words from the other category were paired with safety information. Lastly, we examined if fear generalized to (i) the conceptually related animal-like objects and (ii) other animal like-objects that were perceptually similar. This was measured using behavioral avoidance, US expectancy ratings and self-reported stimulus valence. Animal-like objects conceptually connected to the aversive words evoked heightened fear. Perceptual variants of these animal-like objects also elicit fear. Future research would benefit from the use of online-US expectancy ratings and physiological measures of fear. Investigating the role of both perceptual and conceptual fear generalization is important to better understand the etiology of anxiety disorders symptoms. Copyright © 2015 Elsevier Ltd. All rights reserved.
-
Boz, İlkay; Özer, Zeynep; Teskereci, Gamze; Kavradim, Selma Turan
The objectives of this study were to investigate learning experiences of the nurses who participated in transnational and multinational occupational training. A qualitative descriptive methodology was used. Data are clustered into 3 categories "occupational training," "complementary care," and "intercultural interaction." This research has revealed many insights into the transnational training of nurses.
-
ERIC Educational Resources Information Center
Hall, D. Geoffrey; Williams, Sean G.; Belanger, Julie
2010-01-01
In two experiments, one hundred ninety-two 3-year-olds, 4-year-olds, and adults heard a novel word for a target object and then were asked to extend the label to one of two test objects, one matching in shape-based object category (the shape match) and the other matching in a property other than shape (the property match). We independently…
-
Barbarotto, Riccardo; Laiacona, Marcella; Macchi, Valeria; Capitani, Erminio
2002-01-01
We present a new corpus of 80 pictures of unreal objects, useful for a controlled assessment of object reality decision. The new pictures were assembled from parts of the Snodgrass and Vanderwart [J. Exp. Psychol., Hum. Learning Memory 6; 1980: 174] set and were devised for the purpose of contrasting natural categories (animals, fruits and vegetables), artefacts (tools, vehicles and furniture), body parts and musical instruments. We examined 140 normal subjects in a free-choice and a multiple-choice object decision task, assembled with 80 pictures of real objects and above 80 new pictures of unreal objects in order to obtain a difficulty index for each picture. We found that the tasks were more difficult with pictures representing natural entities than with pictures of artefacts. We found a gender by category interaction, with a female superiority with some natural categories (fruits and vegetables, but not animals), and a male advantage with artefacts. On this basis, the difficulty index we calculated for each picture is separately reported for males and females. We discuss the possible origin of the gender effect, which has been found with the same categories in other tasks and has a counterpart in the different familiarity of the stimuli for males and females. In particular, we contrast explanations based on socially determined gender differences with accounts based on evolutionary pressures. We further comment on the relationship between data from normal subjects and the domain-specific account of semantic category dissociations observed in brain-damaged patients.
-
ERIC Educational Resources Information Center
Chin-Parker, Seth; Ross, Brian H.
2004-01-01
Category knowledge allows for both the determination of category membership and an understanding of what the members of a category are like. Diagnostic information is used to determine category membership; prototypical information reflects the most likely features given category membership. Two experiments examined 2 means of category learning,…
-
Katchergin, Ofer
2014-12-01
This article aims to stimulate new thinking about learning disabilities than is customary in local literature. Previous educational and psychological studies concerning learning disabilities regarded them as if they were objective categories with formal definitions and criteria accepted in scholarly literature. Contrary to that, this article explores the various conceptions, constructions, and meanings of learning disabilities that comprise the narrative descriptions and explanations of didactic diagnosticians. For this purpose, 50 in-depth interviews were conducted. There are four sections. Part One lays out the theoretical and methodological background of the sociological and discursive debate about learning disabilities. Part Two explores the various main thematic aspects and narrative strategies that were used by the diagnosticians in their construction of their purportedly 'objective', 'a-historical', 'a-political' experts' narrative. The third part reveals the polyphonic multifaceted nature of the learning disabilities construct. The experts' narrative undermines the objective and homogeneous definitions in the literature by uncovering learning disabilities' heterogeneous meaning repertoire. This repertoire consists, among others, of conceptualizing disability as a 'disease', a 'symptom', a 'genetic defect', a 'disorder', an 'educational difficulty', a 'variance', and even a 'gift'. This part also reveals the experts' narrative reaction strategies to the aforementioned polyphonic spectacle. It is revealed that the interviewees' narrative deconstructs the 'scientific factual nature' of the clinical categories. The fourth part highlights a central paradox in the expert narrative: The tension between the narrative stigmatic-labeling aspects and the destigmatic-'liberating' aspects. The claim is made that this tension can partly explain the current popularity of the LD diagnosis. This article is the third in a series of papers that seeks to contribute to the creation of a more nuanced disability discourse by exposing its shaky scientific foundations.
-
Best, Catherine A.; Yim, Hyungwook; Sloutsky, Vladimir M.
2013-01-01
Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6–8 months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. PMID:23773914
-
Supervised and Unsupervised Learning of Multidimensional Acoustic Categories
ERIC Educational Resources Information Center
Goudbeek, Martijn; Swingley, Daniel; Smits, Roel
2009-01-01
Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributionally defined visual categories has shown that categories defined over 1 dimension are easy to learn and that learning multidimensional categories is…
-
How Category Structure Influences the Perception of Object Similarity: The Atypicality Bias
Tanaka, James William; Kantner, Justin; Bartlett, Marni
2011-01-01
Why do some faces appear more similar than others? Beyond structural factors, we speculate that similarity is governed by the organization of faces located in a multi-dimensional face space. To test this hypothesis, we morphed a typical face with an atypical face. If similarity judgments are guided purely by their physical properties, the morph should be perceived to be equally similar to its typical parent as its atypical parent. However, contrary to the structural prediction, our results showed that the morph face was perceived to be more similar to the atypical face than the typical face. Our empirical studies show that the atypicality bias is not limited to faces, but extends to other object categories (birds) whose members share common shape properties. We also demonstrate atypicality bias is malleable and can change subject to category learning and experience. Collectively, the empirical evidence indicates that perceptions of face and object similarity are affected by the distribution of stimuli in a face or object space. In this framework, atypical stimuli are located in a sparser region of the space where there is less competition for recognition and therefore, these representations capture a broader range of inputs. In contrast, typical stimuli are located in a denser region of category space where there is increased competition for recognition and hence, these representation draw a more restricted range of face inputs. These results suggest that the perceived likeness of an object is influenced by the organization of surrounding exemplars in the category space. PMID:22685441
-
Incidental Auditory Category Learning
Gabay, Yafit; Dick, Frederic K.; Zevin, Jason D.; Holt, Lori L.
2015-01-01
Very little is known about how auditory categories are learned incidentally, without instructions to search for category-diagnostic dimensions, overt category decisions, or experimenter-provided feedback. This is an important gap because learning in the natural environment does not arise from explicit feedback and there is evidence that the learning systems engaged by traditional tasks are distinct from those recruited by incidental category learning. We examined incidental auditory category learning with a novel paradigm, the Systematic Multimodal Associations Reaction Time (SMART) task, in which participants rapidly detect and report the appearance of a visual target in one of four possible screen locations. Although the overt task is rapid visual detection, a brief sequence of sounds precedes each visual target. These sounds are drawn from one of four distinct sound categories that predict the location of the upcoming visual target. These many-to-one auditory-to-visuomotor correspondences support incidental auditory category learning. Participants incidentally learn categories of complex acoustic exemplars and generalize this learning to novel exemplars and tasks. Further, learning is facilitated when category exemplar variability is more tightly coupled to the visuomotor associations than when the same stimulus variability is experienced across trials. We relate these findings to phonetic category learning. PMID:26010588
-
Syntax-induced pattern deafness
Endress, Ansgar D.; Hauser, Marc D.
2009-01-01
Perceptual systems often force systematically biased interpretations upon sensory input. These interpretations are obligatory, inaccessible to conscious control, and prevent observers from perceiving alternative percepts. Here we report a similarly impenetrable phenomenon in the domain of language, where the syntactic system prevents listeners from detecting a simple perceptual pattern. Healthy human adults listened to three-word sequences conforming to patterns readily learned even by honeybees, rats, and sleeping human neonates. Specifically, sequences either started or ended with two words from the same syntactic category (e.g., noun–noun–verb or verb–verb–noun). Although participants readily processed the categories and learned repetition patterns over nonsyntactic categories (e.g., animal–animal–clothes), they failed to learn the repetition pattern over syntactic categories, even when explicitly instructed to look for it. Further experiments revealed that participants successfully learned the repetition patterns only when they were consistent with syntactically possible structures, irrespective of whether these structures were attested in English or in other languages unknown to the participants. When the repetition patterns did not match such syntactically possible structures, participants failed to learn them. Our results suggest that when human adults hear a string of nouns and verbs, their syntactic system obligatorily attempts an interpretation (e.g., in terms of subjects, objects, and predicates). As a result, subjects fail to perceive the simpler pattern of repetitions—a form of syntax-induced pattern deafness that is reminiscent of how other perceptual systems force specific interpretations upon sensory input. PMID:19920182
-
Dual-learning systems during speech category learning
Chandrasekaran, Bharath; Yi, Han-Gyol; Maddox, W. Todd
2013-01-01
Dual-systems models of visual category learning posit the existence of an explicit, hypothesis-testing ‘reflective’ system, as well as an implicit, procedural-based ‘reflexive’ system. The reflective and reflexive learning systems are competitive and neurally dissociable. Relatively little is known about the role of these domain-general learning systems in speech category learning. Given the multidimensional, redundant, and variable nature of acoustic cues in speech categories, our working hypothesis is that speech categories are learned reflexively. To this end, we examined the relative contribution of these learning systems to speech learning in adults. Native English speakers learned to categorize Mandarin tone categories over 480 trials. The training protocol involved trial-by-trial feedback and multiple talkers. Experiment 1 and 2 examined the effect of manipulating the timing (immediate vs. delayed) and information content (full vs. minimal) of feedback. Dual-systems models of visual category learning predict that delayed feedback and providing rich, informational feedback enhance reflective learning, while immediate and minimally informative feedback enhance reflexive learning. Across the two experiments, our results show feedback manipulations that targeted reflexive learning enhanced category learning success. In Experiment 3, we examined the role of trial-to-trial talker information (mixed vs. blocked presentation) on speech category learning success. We hypothesized that the mixed condition would enhance reflexive learning by not allowing an association between talker-related acoustic cues and speech categories. Our results show that the mixed talker condition led to relatively greater accuracies. Our experiments demonstrate that speech categories are optimally learned by training methods that target the reflexive learning system. PMID:24002965
-
Attentional Bias in Human Category Learning: The Case of Deep Learning.
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. Third, we show that even BP can exhibit human like learning differences between integral and separable category structures when high dimensional stimuli (face exemplars) are used. We conclude, after visualizing the hidden unit representations, that DL appears to extend initial learning due to feature development thereby reducing destructive feature competition by incrementally refining feature detectors throughout later layers until a tipping point (in terms of error) is reached resulting in rapid asymptotic learning.
-
ERIC Educational Resources Information Center
Ohio State Univ., Columbus. National Center for Research in Vocational Education.
This second in a series of six learning modules on instructional planning is designed to give secondary and postsecondary vocational teachers skill in writing student performance objectives which spell out for teachers, students, and prospective employers exactly what is expected of students in the program. It is also intended to give experience…
-
Children's Category-Based Inferences Affect Classification
ERIC Educational Resources Information Center
Ross, Brian H.; Gelman, Susan A.; Rosengren, Karl S.
2005-01-01
Children learn many new categories and make inferences about these categories. Much work has examined how children make inferences on the basis of category knowledge. However, inferences may also affect what is learned about a category. Four experiments examine whether category-based inferences during category learning influence category knowledge…
-
The transfer of category knowledge by macaques (Macaca mulatta) and humans (Homo sapiens).
Zakrzewski, Alexandria C; Church, Barbara A; Smith, J David
2018-02-01
Cognitive psychologists distinguish implicit, procedural category learning (stimulus-response associations learned outside declarative cognition) from explicit-declarative category learning (conscious category rules). These systems are dissociated by category learning tasks with either a multidimensional, information-integration (II) solution or a unidimensional, rule-based (RB) solution. In the present experiments, humans and two monkeys learned II and RB category tasks fostering implicit and explicit learning, respectively. Then they received occasional transfer trials-never directly reinforced-drawn from untrained regions of the stimulus space. We hypothesized that implicit-procedural category learning-allied to associative learning-would transfer weakly because it is yoked to the training stimuli. This result was confirmed for humans and monkeys. We hypothesized that explicit category learning-allied to abstract category rules-would transfer robustly. This result was confirmed only for humans. That is, humans displayed explicit category knowledge that transferred flawlessly. Monkeys did not. This result illuminates the distinctive abstractness, stimulus independence, and representational portability of humans' explicit category rules. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
-
A survey study of evidence-based medicine training in US and Canadian medical schools
Blanco, Maria A.; Capello, Carol F.; Dorsch, Josephine L.; Perry, Gerald (Jerry); Zanetti, Mary L.
2014-01-01
Purpose: The authors conducted a survey examining (1) the current state of evidence-based medicine (EBM) curricula in US and Canadian medical schools and corresponding learning objectives, (2) medical educators' and librarians' participation in EBM training, and (3) barriers to EBM training. Methods: A survey instrument with thirty-four closed and open-ended questions was sent to curricular deans at US and Canadian medical schools. The survey sought information on enrollment and class size; EBM learning objectives, curricular activities, and assessment approaches by year of training; EBM faculty; EBM tools; barriers to implementing EBM curricula and possible ways to overcome them; and innovative approaches to EBM education. Both qualitative and quantitative methods were used for data analysis. Measurable learning objectives were categorized using Bloom's taxonomy. Results: One hundred fifteen medical schools (77.2%) responded. Over half (53%) of the 900 reported learning objectives were measurable. Knowledge application was the predominant category from Bloom's categories. Most schools integrated EBM into other curricular activities; activities and formal assessment decreased significantly with advanced training. EBM faculty consisted primarily of clinicians, followed by basic scientists and librarians. Various EBM tools were used, with PubMed and the Cochrane database most frequently cited. Lack of time in curricula was rated the most significant barrier. National agreement on required EBM competencies was an extremely helpful factor. Few schools shared innovative approaches. Conclusions: Schools need help in overcoming barriers related to EBM curriculum development, implementation, and assessment. Implications: Findings can provide a starting point for discussion to develop a standardized competency framework. PMID:25031556
-
A survey study of evidence-based medicine training in US and Canadian medical schools.
Blanco, Maria A; Capello, Carol F; Dorsch, Josephine L; Perry, Gerald; Zanetti, Mary L
2014-07-01
The authors conducted a survey examining (1) the current state of evidence-based medicine (EBM) curricula in US and Canadian medical schools and corresponding learning objectives, (2) medical educators' and librarians' participation in EBM training, and (3) barriers to EBM training. A survey instrument with thirty-four closed and open-ended questions was sent to curricular deans at US and Canadian medical schools. The survey sought information on enrollment and class size; EBM learning objectives, curricular activities, and assessment approaches by year of training; EBM faculty; EBM tools; barriers to implementing EBM curricula and possible ways to overcome them; and innovative approaches to EBM education. Both qualitative and quantitative methods were used for data analysis. Measurable learning objectives were categorized using Bloom's taxonomy. One hundred fifteen medical schools (77.2%) responded. Over half (53%) of the 900 reported learning objectives were measurable. Knowledge application was the predominant category from Bloom's categories. Most schools integrated EBM into other curricular activities; activities and formal assessment decreased significantly with advanced training. EBM faculty consisted primarily of clinicians, followed by basic scientists and librarians. Various EBM tools were used, with PubMed and the Cochrane database most frequently cited. Lack of time in curricula was rated the most significant barrier. National agreement on required EBM competencies was an extremely helpful factor. Few schools shared innovative approaches. Schools need help in overcoming barriers related to EBM curriculum development, implementation, and assessment. Findings can provide a starting point for discussion to develop a standardized competency framework.
-
Naming and Categorization in Young Children: IV: Listener Behavior Training and Transfer of Function
Horne, Pauline J; Hughes, J. Carl; Lowe, C. Fergus
2006-01-01
Following pretraining with everyday objects, 14 children aged from 1 to 4 years were trained, for each of three pairs of different arbitrary wooden shapes (Set 1), to select one stimulus in response to the spoken word /zog/, and the other to /vek/. When given a test for the corresponding tacts (“zog” and “vek”), 10 children passed, showing that they had learned common names for the stimuli, and 4 failed. All children were trained to clap to one stimulus of Pair 1 and wave to the other. All those who named showed either transfer of the novel functions to the remaining two pairs of stimuli in Test 1, or novel function comprehension for all three pairs in Test 2, or both. Three of these children next participated in, and passed, category match-to-sample tests. In contrast, all 4 children who had learned only listener behavior failed both the category transfer and category match-to-sample tests. When 3 of them were next trained to name the stimuli, they passed the category transfer and (for the 2 subjects tested) category match-to-sample tests. Three children were next trained on the common listener relations with another set of arbitrary stimuli (Set 2); all succeeded on the tact and category tests with the Set 2 stimuli. Taken together with the findings from the other studies in the series, the present experiment shows that (a) common listener training also establishes the corresponding names in some but not all children, and (b) only children who learn common names categorize; all those who learn only listener behavior fail. This is good evidence in support of the naming account of categorization. PMID:16673828
-
Toward a dual-learning systems model of speech category learning
Chandrasekaran, Bharath; Koslov, Seth R.; Maddox, W. T.
2014-01-01
More than two decades of work in vision posits the existence of dual-learning systems of category learning. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion, while the reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-learning systems models hypothesize that in learning natural categories, learners initially use the reflective system and, with practice, transfer control to the reflexive system. The role of reflective and reflexive systems in auditory category learning and more specifically in speech category learning has not been systematically examined. In this article, we describe a neurobiologically constrained dual-learning systems theoretical framework that is currently being developed in speech category learning and review recent applications of this framework. Using behavioral and computational modeling approaches, we provide evidence that speech category learning is predominantly mediated by the reflexive learning system. In one application, we explore the effects of normal aging on non-speech and speech category learning. Prominently, we find a large age-related deficit in speech learning. The computational modeling suggests that older adults are less likely to transition from simple, reflective, unidimensional rules to more complex, reflexive, multi-dimensional rules. In a second application, we summarize a recent study examining auditory category learning in individuals with elevated depressive symptoms. We find a deficit in reflective-optimal and an enhancement in reflexive-optimal auditory category learning. Interestingly, individuals with elevated depressive symptoms also show an advantage in learning speech categories. We end with a brief summary and description of a number of future directions. PMID:25132827
-
Best, Catherine A; Yim, Hyungwook; Sloutsky, Vladimir M
2013-10-01
Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6-8months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. Copyright © 2013 Elsevier Inc. All rights reserved.
-
Kozunov, Vladimir; Nikolaeva, Anastasia; Stroganova, Tatiana A.
2018-01-01
The brain mechanisms that integrate the separate features of sensory input into a meaningful percept depend upon the prior experience of interaction with the object and differ between categories of objects. Recent studies using representational similarity analysis (RSA) have characterized either the spatial patterns of brain activity for different categories of objects or described how category structure in neuronal representations emerges in time, but never simultaneously. Here we applied a novel, region-based, multivariate pattern classification approach in combination with RSA to magnetoencephalography data to extract activity associated with qualitatively distinct processing stages of visual perception. We asked participants to name what they see whilst viewing bitonal visual stimuli of two categories predominantly shaped by either value-dependent or sensorimotor experience, namely faces and tools, and meaningless images. We aimed to disambiguate the spatiotemporal patterns of brain activity between the meaningful categories and determine which differences in their processing were attributable to either perceptual categorization per se, or later-stage mentalizing-related processes. We have extracted three stages of cortical activity corresponding to low-level processing, category-specific feature binding, and supra-categorical processing. All face-specific spatiotemporal patterns were associated with bilateral activation of ventral occipito-temporal areas during the feature binding stage at 140–170 ms. The tool-specific activity was found both within the categorization stage and in a later period not thought to be associated with binding processes. The tool-specific binding-related activity was detected within a 210–220 ms window and was located to the intraparietal sulcus of the left hemisphere. Brain activity common for both meaningful categories started at 250 ms and included widely distributed assemblies within parietal, temporal, and prefrontal regions. Furthermore, we hypothesized and tested whether activity within face and tool-specific binding-related patterns would demonstrate oppositely acting effects following procedural perceptual learning. We found that activity in the ventral, face-specific network increased following the stimuli repetition. In contrast, tool processing in the dorsal network adapted by reducing its activity over the repetition period. Altogether, we have demonstrated that activity associated with visual processing of faces and tools during the categorization stage differ in processing timing, brain areas involved, and in their dynamics underlying stimuli learning. PMID:29379426
-
Kozunov, Vladimir; Nikolaeva, Anastasia; Stroganova, Tatiana A
2017-01-01
The brain mechanisms that integrate the separate features of sensory input into a meaningful percept depend upon the prior experience of interaction with the object and differ between categories of objects. Recent studies using representational similarity analysis (RSA) have characterized either the spatial patterns of brain activity for different categories of objects or described how category structure in neuronal representations emerges in time, but never simultaneously. Here we applied a novel, region-based, multivariate pattern classification approach in combination with RSA to magnetoencephalography data to extract activity associated with qualitatively distinct processing stages of visual perception. We asked participants to name what they see whilst viewing bitonal visual stimuli of two categories predominantly shaped by either value-dependent or sensorimotor experience, namely faces and tools, and meaningless images. We aimed to disambiguate the spatiotemporal patterns of brain activity between the meaningful categories and determine which differences in their processing were attributable to either perceptual categorization per se , or later-stage mentalizing-related processes. We have extracted three stages of cortical activity corresponding to low-level processing, category-specific feature binding, and supra-categorical processing. All face-specific spatiotemporal patterns were associated with bilateral activation of ventral occipito-temporal areas during the feature binding stage at 140-170 ms. The tool-specific activity was found both within the categorization stage and in a later period not thought to be associated with binding processes. The tool-specific binding-related activity was detected within a 210-220 ms window and was located to the intraparietal sulcus of the left hemisphere. Brain activity common for both meaningful categories started at 250 ms and included widely distributed assemblies within parietal, temporal, and prefrontal regions. Furthermore, we hypothesized and tested whether activity within face and tool-specific binding-related patterns would demonstrate oppositely acting effects following procedural perceptual learning. We found that activity in the ventral, face-specific network increased following the stimuli repetition. In contrast, tool processing in the dorsal network adapted by reducing its activity over the repetition period. Altogether, we have demonstrated that activity associated with visual processing of faces and tools during the categorization stage differ in processing timing, brain areas involved, and in their dynamics underlying stimuli learning.
-
Cao, Rui; Nosofsky, Robert M; Shiffrin, Richard M
2017-05-01
In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across trials. In item-response learning, subjects learn long-term mappings between individual items and target versus foil responses. In category learning, subjects learn high-level codes corresponding to separate sets of items and learn to attach old versus new responses to these category codes. To distinguish between these 2 forms of learning, we tested subjects in categorized varied mapping (CV) conditions: There were 2 distinct categories of items, but the assignment of categories to target versus foil responses varied across trials. In cases involving arbitrary categories, CV performance closely resembled standard varied-mapping performance without categories and departed dramatically from CM performance, supporting the item-response-learning hypothesis. In cases involving prelearned categories, CV performance resembled CM performance, as long as there was sufficient practice or steps taken to reduce trial-to-trial category-switching costs. This pattern of results supports the category-coding hypothesis for sufficiently well-learned categories. Thus, item-response learning occurs rapidly and is used early in CM training; category learning is much slower but is eventually adopted and is used to increase the efficiency of search beyond that available from item-response learning. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
-
The Role of Corticostriatal Systems in Speech Category Learning
Yi, Han-Gyol; Maddox, W. Todd; Mumford, Jeanette A.; Chandrasekaran, Bharath
2016-01-01
One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning. Keywords: category learning, fMRI, corticostriatal systems, speech, putamen PMID:25331600
-
Employing Machine-Learning Methods to Study Young Stellar Objects
NASA Astrophysics Data System (ADS)
Moore, Nicholas
2018-01-01
Vast amounts of data exist in the astronomical data archives, and yet a large number of sources remain unclassified. We developed a multi-wavelength pipeline to classify infrared sources. The pipeline uses supervised machine learning methods to classify objects into the appropriate categories. The program is fed data that is already classified to train it, and is then applied to unknown catalogues. The primary use for such a pipeline is the rapid classification and cataloging of data that would take a much longer time to classify otherwise. While our primary goal is to study young stellar objects (YSOs), the applications extend beyond the scope of this project. We present preliminary results from our analysis and discuss future applications.
-
Brockmole, James R; Le-Hoa Võ, Melissa
2010-10-01
When encountering familiar scenes, observers can use item-specific memory to facilitate the guidance of attention to objects appearing in known locations or configurations. Here, we investigated how memory for relational contingencies that emerge across different scenes can be exploited to guide attention. Participants searched for letter targets embedded in pictures of bedrooms. In a between-subjects manipulation, targets were either always on a bed pillow or randomly positioned. When targets were systematically located within scenes, search for targets became more efficient. Importantly, this learning transferred to bedrooms without pillows, ruling out learning that is based on perceptual contingencies. Learning also transferred to living room scenes, but it did not transfer to kitchen scenes, even though both scene types contained pillows. These results suggest that statistical regularities abstracted across a range of stimuli are governed by semantic expectations regarding the presence of target-predicting local landmarks. Moreover, explicit awareness of these contingencies led to a central tendency bias in recall memory for precise target positions that is similar to the spatial category effects observed in landmark memory. These results broaden the scope of conditions under which contextual cuing operates and demonstrate how semantic memory plays a causal and independent role in the learning of associations between objects in real-world scenes.
-
Individual Differences in Learning Talker Categories: The Role of Working Memory
Levi, Susannah V.
2016-01-01
The current study explores the question of how an auditory category is learned by having school-age listeners learn to categorize speech not in terms of linguistic categories, but instead in terms of talker categories (i.e., who is talking). Findings from visual-category learning indicate that working memory skills affect learning, but the literature is equivocal: sometimes better working memory is advantageous, and sometimes not. The current study examined the role of different components of working memory to test which component skills benefit, and which hinder, learning talker categories. Results revealed that the short-term storage component positively predicted learning, but that the Central Executive and Episodic Buffer negatively predicted learning. As with visual categories, better working memory is not always an advantage. PMID:25721393
-
Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition.
Grossberg, Stephen
2007-01-01
A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of preattentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.
-
STDP-based spiking deep convolutional neural networks for object recognition.
Kheradpisheh, Saeed Reza; Ganjtabesh, Mohammad; Thorpe, Simon J; Masquelier, Timothée
2018-03-01
Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively shallow architectures, and only one layer was trainable. Another line of research has demonstrated - using rate-based neural networks trained with back-propagation - that having many layers increases the recognition robustness, an approach known as deep learning. We thus designed a deep SNN, comprising several convolutional (trainable with STDP) and pooling layers. We used a temporal coding scheme where the most strongly activated neurons fire first, and less activated neurons fire later or not at all. The network was exposed to natural images. Thanks to STDP, neurons progressively learned features corresponding to prototypical patterns that were both salient and frequent. Only a few tens of examples per category were required and no label was needed. After learning, the complexity of the extracted features increased along the hierarchy, from edge detectors in the first layer to object prototypes in the last layer. Coding was very sparse, with only a few thousands spikes per image, and in some cases the object category could be reasonably well inferred from the activity of a single higher-order neuron. More generally, the activity of a few hundreds of such neurons contained robust category information, as demonstrated using a classifier on Caltech 101, ETH-80, and MNIST databases. We also demonstrate the superiority of STDP over other unsupervised techniques such as random crops (HMAX) or auto-encoders. Taken together, our results suggest that the combination of STDP with latency coding may be a key to understanding the way that the primate visual system learns, its remarkable processing speed and its low energy consumption. These mechanisms are also interesting for artificial vision systems, particularly for hardware solutions. Copyright © 2017 Elsevier Ltd. All rights reserved.
-
Statistical Inference in the Learning of Novel Phonetic Categories
ERIC Educational Resources Information Center
Zhao, Yuan
2010-01-01
Learning a phonetic category (or any linguistic category) requires integrating different sources of information. A crucial unsolved problem for phonetic learning is how this integration occurs: how can we update our previous knowledge about a phonetic category as we hear new exemplars of the category? One model of learning is Bayesian Inference,…
-
Matsumoto, Narihisa; Eldridge, Mark A G; Saunders, Richard C; Reoli, Rachel; Richmond, Barry J
2016-01-06
In primates, visual recognition of complex objects depends on the inferior temporal lobe. By extension, categorizing visual stimuli based on similarity ought to depend on the integrity of the same area. We tested three monkeys before and after bilateral anterior inferior temporal cortex (area TE) removal. Although mildly impaired after the removals, they retained the ability to assign stimuli to previously learned categories, e.g., cats versus dogs, and human versus monkey faces, even with trial-unique exemplars. After the TE removals, they learned in one session to classify members from a new pair of categories, cars versus trucks, as quickly as they had learned the cats versus dogs before the removals. As with the dogs and cats, they generalized across trial-unique exemplars of cars and trucks. However, as seen in earlier studies, these monkeys with TE removals had difficulty learning to discriminate between two simple black and white stimuli. These results raise the possibility that TE is needed for memory of simple conjunctions of basic features, but that it plays only a small role in generalizing overall configural similarity across a large set of stimuli, such as would be needed for perceptual categorical assignment. The process of seeing and recognizing objects is attributed to a set of sequentially connected brain regions stretching forward from the primary visual cortex through the temporal lobe to the anterior inferior temporal cortex, a region designated area TE. Area TE is considered the final stage for recognizing complex visual objects, e.g., faces. It has been assumed, but not tested directly, that this area would be critical for visual generalization, i.e., the ability to place objects such as cats and dogs into their correct categories. Here, we demonstrate that monkeys rapidly and seemingly effortlessly categorize large sets of complex images (cats vs dogs, cars vs trucks), surprisingly, even after removal of area TE, leaving a puzzle about how this generalization is done. Copyright © 2016 the authors 0270-6474/16/360043-11$15.00/0.
-
Classification versus inference learning contrasted with real-world categories.
Jones, Erin L; Ross, Brian H
2011-07-01
Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories--what each category is like--while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.
-
Janssens, Thomas; Caris, Eva; Van Diest, Ilse; Van den Bergh, Omer
2017-01-01
Background: In asthma and allergic rhinitis, beliefs about what triggers allergic reactions often do not match objective allergy tests. This may be due to insensitivity for expectancy violations as a result of holding trigger beliefs based on conceptual relationships among triggers. In this laboratory experiment, we aimed to investigate how pre-existing beliefs and conceptual relationships among triggers interact with actual experience when learning differential symptom expectations. Methods: Healthy participants (N = 48) received information that allergic reactions were a result of specific sensitivities versus general allergic vulnerability. Next, they performed a trigger learning task using a differential conditioning paradigm: brief inhalation of CO2 enriched air was used to induce symptoms, while participants were led to believe that the symptoms came about as a result of inhaled allergens (conditioned stimuli, CS’s; CS+ followed by symptoms, CS- not followed by symptoms). CS+ and CS- stimuli either shared (e.g., birds-mammals) or did not share (e.g. birds-fungi) category membership. During Acquisition, participants reported symptom expectancy and symptom intensity for all triggers. During a Test 1 day later, participants rated symptom expectancies for old CS+/CS- triggers, for novel triggers within categories, and for exemplars of novel trigger categories. Data were analyzed using multilevel models. Findings: Only a subgroup of participants (n = 22) showed differences between CO2 and room air symptoms. In this group of responders, analysis of symptom expectancies during acquisition did not result in significant differential symptom CS+/CS- acquisition. A retention test 1 day later showed differential CS+/CS- symptom expectancies: When CS categories did not share category membership, specific sensitivity beliefs improved retention of CS+/CS- differentiation. However, when CS categories shared category membership, general vulnerability beliefs improved retention of CS+/CS- differentiation. Furthermore, participants showed some selectivity in generalization of symptom expectancies to novel categories, as symptom expectancies did not generalize to novel categories that were unrelated to CS+ or CS- categories. Generalization to novel categories was not affected by information about general vulnerability or specific sensitivities. Discussion: Pre-existing vulnerability beliefs and conceptual relationships between trigger categories influence differential symptom expectancies to allergic triggers. PMID:28638358
-
Learning about the internal structure of categories through classification and feature inference.
Jee, Benjamin D; Wiley, Jennifer
2014-01-01
Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.
-
Conventional Wisdom: Negotiating Conventions of Reference Enhances Category Learning
ERIC Educational Resources Information Center
Voiklis, John; Corter, James E.
2012-01-01
Collaborators generally coordinate their activities through communication, during which they readily negotiate a shared lexicon for activity-related objects. This social-pragmatic activity both recruits and affects cognitive and social-cognitive processes ranging from selective attention to perspective taking. We ask whether negotiating reference…
-
Assessing the Benefits of NASA Category 3, Low Cost Class C/D Missions
NASA Technical Reports Server (NTRS)
Bitten, Robert E.; Shinn, Steven A.; Mahr, Eric M.
2013-01-01
Category 3, Class C/D missions have the benefit of delivering worthwhile science at minimal cost which is increasingly important in NASA's constrained budget environment. Although higher cost Category 1 and 2 missions are necessary to achieve NASA's science objectives, Category 3 missions are shown to be an effective way to provide significant science return at a low cost. Category 3 missions, however, are often reviewed the same as the more risk averse Category 1 and 2 missions. Acknowledging that reviews are not the only aspect of a total engineering effort, reviews are still a significant concern for NASA programs. This can unnecessarily increase the cost and schedule of Category 3 missions. This paper quantifies the benefit and performance of Category 3 missions by looking at the cost vs. capability relative to Category 1 and 2 missions. Lessons learned from successful organizations that develop low cost Category 3, Class C/D missions are also investigated to help provide the basis for suggestions to streamline the review of NASA Category 3 missions.
-
The Effects of Concurrent Verbal and Visual Tasks on Category Learning
ERIC Educational Resources Information Center
Miles, Sarah J.; Minda, John Paul
2011-01-01
Current theories of category learning posit separate verbal and nonverbal learning systems. Past research suggests that the verbal system relies on verbal working memory and executive functioning and learns rule-defined categories; the nonverbal system does not rely on verbal working memory and learns non-rule-defined categories (E. M. Waldron…
-
Davis, Tyler; Goldwater, Micah; Giron, Josue
2017-04-01
The ability to form relational categories for objects that share few features in common is a hallmark of human cognition. For example, anything that can play a preventative role, from a boulder to poverty, can be a "barrier." However, neurobiological research has focused solely on how people acquire categories defined by features. The present functional magnetic resonance imaging study examines how relational and feature-based category learning compare in well-matched learning tasks. Using a computational model-based approach, we observed a cluster in left rostrolateral prefrontal cortex (rlPFC) that tracked quantitative predictions for the representational distance between test and training examples during relational categorization. Contrastingly, medial and dorsal PFC exhibited graded activation that tracked decision evidence during both feature-based and relational categorization. The results suggest that rlPFC computes an alignment signal that is critical for integrating novel examples during relational categorization whereas other PFC regions support more general decision functions. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
-
Development of learning objectives for neurology in a veterinary curriculum: part I: undergraduates.
Lin, Yu-Wei; Volk, Holger A; Penderis, Jacques; Tipold, Andrea; Ehlers, Jan P
2015-01-13
With an increasing caseload of veterinary neurology patients in first opinion practice, there is a requirement to establish relevant learning objectives for veterinary neurology encompassing knowledge, skills and attitudes for veterinary undergraduate students in Europe. With help of experts in veterinary neurology from the European College of Veterinary Neurology (ECVN) and the European Society of Veterinary Neurology (ESVN) a survey of veterinary neurologic learning objectives using a modified Delphi method was conducted. The first phase comprised the development of a draft job description and learning objectives by a working group established by the ECVN. In the second phase, a quantitative questionnaire (multiple choice, Likert scale and free text) covering 140 learning objectives and subdivided into 8 categories was sent to 341 ESVN and ECVN members and a return rate of 62% (n = 213/341) was achieved. Of these 140 learning objectives ECVN Diplomates and ESVN members considered 42 (30%) objectives as not necessary for standard clinical veterinary neurology training, 94 (67%) were graded to be learned at a beginner level and 4 (3%) at an advanced level. The following objectives were interpreted as the most important day one skills: interpret laboratory tests, perform a neurological examination and establish a neuroanatomical localization. In this survey the three most important diseases of the central nervous system included epilepsy, intervertebral disc disease and inflammatory diseases. The three most important diseases of the peripheral nervous system included polyradiculoneuritis, myasthenia gravis and toxic neuropathies. The results of this study should help to reform the veterinary curriculum regarding neurology and may reduce the phenomenon of "Neurophobia".
-
Minda, John P; Rabi, Rahel
2015-01-01
Considerable research on category learning has suggested that many cognitive and environmental factors can have a differential effect on the learning of rule-defined (RD) categories as opposed to the learning of non-rule-defined (NRD) categories. Prior research has also suggested that ego depletion can temporarily reduce the capacity for executive functioning and cognitive flexibility. The present study examined whether temporarily reducing participants' executive functioning via a resource depletion manipulation would differentially impact RD and NRD category learning. Participants were either asked to write a story with no restrictions (the control condition), or without using two common letters (the ego depletion condition). Participants were then asked to learn either a set of RD categories or a set of NRD categories. Resource depleted participants performed more poorly than controls on the RD task, but did not differ from controls on the NRD task, suggesting that self regulatory resources are required for successful RD category learning. These results lend support to multiple systems theories and clarify the role of self-regulatory resources within this theory.
-
Minda, John P.; Rabi, Rahel
2015-01-01
Considerable research on category learning has suggested that many cognitive and environmental factors can have a differential effect on the learning of rule-defined (RD) categories as opposed to the learning of non-rule-defined (NRD) categories. Prior research has also suggested that ego depletion can temporarily reduce the capacity for executive functioning and cognitive flexibility. The present study examined whether temporarily reducing participants’ executive functioning via a resource depletion manipulation would differentially impact RD and NRD category learning. Participants were either asked to write a story with no restrictions (the control condition), or without using two common letters (the ego depletion condition). Participants were then asked to learn either a set of RD categories or a set of NRD categories. Resource depleted participants performed more poorly than controls on the RD task, but did not differ from controls on the NRD task, suggesting that self regulatory resources are required for successful RD category learning. These results lend support to multiple systems theories and clarify the role of self-regulatory resources within this theory. PMID:25688220
-
Velocity-based motion categorization by pigeons.
Cook, Robert G; Beale, Kevin; Koban, Angie
2011-04-01
To examine if animals could learn action-like categorizations in a manner similar to noun-based categories, eight pigeons were trained to categorize rates of object motion. Testing 40 different objects in a go/no-go discrimination, pigeons were first trained to discriminate between fast and slow rates of object rotation around their central y-axis. They easily learned this velocity discrimination and transferred it to novel objects and rates. This discrimination also transferred to novel types of motions including the other two axes of rotation and two new translations around the display. Comparable tests with rapid and slow changes in the objects' size, color, and shape failed to support comparable transfer. This difference in discrimination transfer between motion-based and property-based changes suggests the pigeons had learned motion concept rather than one based on change per se. The results provide evidence that pigeons can acquire an understanding of motion-based actions, at least with regard to the property of object velocity. This may be similar to our use of verbs and adverbs to categorize different classes of behavior or motion (e.g., walking, jogging, or running slow vs. fast).
-
Feature Inference Learning and Eyetracking
ERIC Educational Resources Information Center
Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.
2009-01-01
Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…
-
Chromatic Perceptual Learning but No Category Effects without Linguistic Input.
Grandison, Alexandra; Sowden, Paul T; Drivonikou, Vicky G; Notman, Leslie A; Alexander, Iona; Davies, Ian R L
2016-01-01
Perceptual learning involves an improvement in perceptual judgment with practice, which is often specific to stimulus or task factors. Perceptual learning has been shown on a range of visual tasks but very little research has explored chromatic perceptual learning. Here, we use two low level perceptual threshold tasks and a supra-threshold target detection task to assess chromatic perceptual learning and category effects. Experiment 1 investigates whether chromatic thresholds reduce as a result of training and at what level of analysis learning effects occur. Experiment 2 explores the effect of category training on chromatic thresholds, whether training of this nature is category specific and whether it can induce categorical responding. Experiment 3 investigates the effect of category training on a higher level, lateralized target detection task, previously found to be sensitive to category effects. The findings indicate that performance on a perceptual threshold task improves following training but improvements do not transfer across retinal location or hue. Therefore, chromatic perceptual learning is category specific and can occur at relatively early stages of visual analysis. Additionally, category training does not induce category effects on a low level perceptual threshold task, as indicated by comparable discrimination thresholds at the newly learned hue boundary and adjacent test points. However, category training does induce emerging category effects on a supra-threshold target detection task. Whilst chromatic perceptual learning is possible, learnt category effects appear to be a product of left hemisphere processing, and may require the input of higher level linguistic coding processes in order to manifest.
-
SUSTAIN: a network model of category learning.
Love, Bradley C; Medin, Douglas L; Gureckis, Todd M
2004-04-01
SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.
-
Weickert, Thomas W.; Goldberg, Terry E.; Egan, Michael F.; Apud, Jose A.; Meeter, Martijn; Myers, Catherine E.; Gluck, Mark A; Weinberger, Daniel R.
2010-01-01
Background While patients with schizophrenia display an overall probabilistic category learning performance deficit, the extent to which this deficit occurs in unaffected siblings of patients with schizophrenia is unknown. There are also discrepant findings regarding probabilistic category learning acquisition rate and performance in patients with schizophrenia. Methods A probabilistic category learning test was administered to 108 patients with schizophrenia, 82 unaffected siblings, and 121 healthy participants. Results Patients with schizophrenia displayed significant differences from their unaffected siblings and healthy participants with respect to probabilistic category learning acquisition rates. Although siblings on the whole failed to differ from healthy participants on strategy and quantitative indices of overall performance and learning acquisition, application of a revised learning criterion enabling classification into good and poor learners based on individual learning curves revealed significant differences between percentages of sibling and healthy poor learners: healthy (13.2%), siblings (34.1%), patients (48.1%), yielding a moderate relative risk. Conclusions These results clarify previous discrepant findings pertaining to probabilistic category learning acquisition rate in schizophrenia and provide the first evidence for the relative risk of probabilistic category learning abnormalities in unaffected siblings of patients with schizophrenia, supporting genetic underpinnings of probabilistic category learning deficits in schizophrenia. These findings also raise questions regarding the contribution of antipsychotic medication to the probabilistic category learning deficit in schizophrenia. The distinction between good and poor learning may be used to inform genetic studies designed to detect schizophrenia risk alleles. PMID:20172502
-
Gong, Xianmin; Xiao, Hongrui; Wang, Dahua
2016-11-01
False recognition results from the interplay of multiple cognitive processes, including verbatim memory, gist memory, phantom recollection, and response bias. In the current study, we modified the simplified Conjoint Recognition (CR) paradigm to investigate the way in which the valence of emotional stimuli affects the cognitive process and behavioral outcome of false recognition. In Study 1, we examined the applicability of the modification to the simplified CR paradigm and model. Twenty-six undergraduate students (13 females, aged 21.00±2.30years) learned and recognized both the large and small categories of photo objects. The applicability of the paradigm and model was confirmed by a fair goodness-of-fit of the model to the observational data and by their competence in detecting the memory differences between the large- and small-category conditions. In Study 2, we recruited another sample of 29 undergraduate students (14 females, aged 22.60±2.74years) to learn and recognize the categories of photo objects that were emotionally provocative. The results showed that negative valence increased false recognition, particularly the rate of false "remember" responses, by facilitating phantom recollection; positive valence did not influence false recognition significantly though enhanced gist processing. Copyright © 2016 Elsevier B.V. All rights reserved.
-
Yildirim, Ilker; Jacobs, Robert A
2015-06-01
If a person is trained to recognize or categorize objects or events using one sensory modality, the person can often recognize or categorize those same (or similar) objects and events via a novel modality. This phenomenon is an instance of cross-modal transfer of knowledge. Here, we study the Multisensory Hypothesis which states that people extract the intrinsic, modality-independent properties of objects and events, and represent these properties in multisensory representations. These representations underlie cross-modal transfer of knowledge. We conducted an experiment evaluating whether people transfer sequence category knowledge across auditory and visual domains. Our experimental data clearly indicate that we do. We also developed a computational model accounting for our experimental results. Consistent with the probabilistic language of thought approach to cognitive modeling, our model formalizes multisensory representations as symbolic "computer programs" and uses Bayesian inference to learn these representations. Because the model demonstrates how the acquisition and use of amodal, multisensory representations can underlie cross-modal transfer of knowledge, and because the model accounts for subjects' experimental performances, our work lends credence to the Multisensory Hypothesis. Overall, our work suggests that people automatically extract and represent objects' and events' intrinsic properties, and use these properties to process and understand the same (and similar) objects and events when they are perceived through novel sensory modalities.
-
Incremental Bayesian Category Learning From Natural Language.
Frermann, Lea; Lapata, Mirella
2016-08-01
Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words (e.g., chair is a member of the furniture category). We present a Bayesian model that, unlike previous work, learns both categories and their features in a single process. We model category induction as two interrelated subproblems: (a) the acquisition of features that discriminate among categories, and (b) the grouping of concepts into categories based on those features. Our model learns categories incrementally using particle filters, a sequential Monte Carlo method commonly used for approximate probabilistic inference that sequentially integrates newly observed data and can be viewed as a plausible mechanism for human learning. Experimental results show that our incremental learner obtains meaningful categories which yield a closer fit to behavioral data compared to related models while at the same time acquiring features which characterize the learned categories. (An earlier version of this work was published in Frermann and Lapata .). Copyright © 2015 Cognitive Science Society, Inc.
-
The contribution of temporary storage and executive processes to category learning.
Wang, Tengfei; Ren, Xuezhu; Schweizer, Karl
2015-09-01
Three distinctly different working memory processes, temporary storage, mental shifting and inhibition, were proposed to account for individual differences in category learning. A sample of 213 participants completed a classic category learning task and two working memory tasks that were experimentally manipulated for tapping specific working memory processes. Fixed-links models were used to decompose data of the category learning task into two independent components representing basic performance and improvement in performance in category learning. Processes of working memory were also represented by fixed-links models. In a next step the three working memory processes were linked to components of category learning. Results from modeling analyses indicated that temporary storage had a significant effect on basic performance and shifting had a moderate effect on improvement in performance. In contrast, inhibition showed no effect on any component of the category learning task. These results suggest that temporary storage and the shifting process play different roles in the course of acquiring new categories. Copyright © 2015 Elsevier B.V. All rights reserved.
-
The Role of Corticostriatal Systems in Speech Category Learning.
Yi, Han-Gyol; Maddox, W Todd; Mumford, Jeanette A; Chandrasekaran, Bharath
2016-04-01
One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
-
Caring and the Elementary Curriculum.
ERIC Educational Resources Information Center
Ediger, Marlow
In light of the amount of violence reported in public media and increasing rudeness of public behavior, it is imperative that elementary school students learn to care for other human beings. This paper makes recommendations for developing an elementary school curriculum of caring. The paper recommends three categories of objectives--knowledge,…
-
Standard Systems Group (SSG) Technology Adoption Planning Workshop
2004-04-01
11 Figure 2: Map of SEI Technologies Against SSG (Cluster Focused on Customer Issues...them could be consolidated. The objectives were grouped into three categories ( customer focused, internal operations, and innovation & learning... customers ! • Streamlined organization with agile processes • Recognized expertise in exploring and exploiting leading IT technologies • Enterprise
-
Category transfer in sequential causal learning: the unbroken mechanism hypothesis.
Hagmayer, York; Meder, Björn; von Sydow, Momme; Waldmann, Michael R
2011-07-01
The goal of the present set of studies is to explore the boundary conditions of category transfer in causal learning. Previous research has shown that people are capable of inducing categories based on causal learning input, and they often transfer these categories to new causal learning tasks. However, occasionally learners abandon the learned categories and induce new ones. Whereas previously it has been argued that transfer is only observed with essentialist categories in which the hidden properties are causally relevant for the target effect in the transfer relation, we here propose an alternative explanation, the unbroken mechanism hypothesis. This hypothesis claims that categories are transferred from a previously learned causal relation to a new causal relation when learners assume a causal mechanism linking the two relations that is continuous and unbroken. The findings of two causal learning experiments support the unbroken mechanism hypothesis. Copyright © 2011 Cognitive Science Society, Inc.
-
Label consistent K-SVD: learning a discriminative dictionary for recognition.
Jiang, Zhuolin; Lin, Zhe; Davis, Larry S
2013-11-01
A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse coding is presented. In addition to using class labels of training data, we also associate label information with each dictionary item (columns of the dictionary matrix) to enforce discriminability in sparse codes during the dictionary learning process. More specifically, we introduce a new label consistency constraint called "discriminative sparse-code error" and combine it with the reconstruction error and the classification error to form a unified objective function. The optimal solution is efficiently obtained using the K-SVD algorithm. Our algorithm learns a single overcomplete dictionary and an optimal linear classifier jointly. The incremental dictionary learning algorithm is presented for the situation of limited memory resources. It yields dictionaries so that feature points with the same class labels have similar sparse codes. Experimental results demonstrate that our algorithm outperforms many recently proposed sparse-coding techniques for face, action, scene, and object category recognition under the same learning conditions.
-
Chromatic Perceptual Learning but No Category Effects without Linguistic Input
Grandison, Alexandra; Sowden, Paul T.; Drivonikou, Vicky G.; Notman, Leslie A.; Alexander, Iona; Davies, Ian R. L.
2016-01-01
Perceptual learning involves an improvement in perceptual judgment with practice, which is often specific to stimulus or task factors. Perceptual learning has been shown on a range of visual tasks but very little research has explored chromatic perceptual learning. Here, we use two low level perceptual threshold tasks and a supra-threshold target detection task to assess chromatic perceptual learning and category effects. Experiment 1 investigates whether chromatic thresholds reduce as a result of training and at what level of analysis learning effects occur. Experiment 2 explores the effect of category training on chromatic thresholds, whether training of this nature is category specific and whether it can induce categorical responding. Experiment 3 investigates the effect of category training on a higher level, lateralized target detection task, previously found to be sensitive to category effects. The findings indicate that performance on a perceptual threshold task improves following training but improvements do not transfer across retinal location or hue. Therefore, chromatic perceptual learning is category specific and can occur at relatively early stages of visual analysis. Additionally, category training does not induce category effects on a low level perceptual threshold task, as indicated by comparable discrimination thresholds at the newly learned hue boundary and adjacent test points. However, category training does induce emerging category effects on a supra-threshold target detection task. Whilst chromatic perceptual learning is possible, learnt category effects appear to be a product of left hemisphere processing, and may require the input of higher level linguistic coding processes in order to manifest. PMID:27252669
-
Two Pathways to Stimulus Encoding in Category Learning?
Davis, Tyler; Love, Bradley C.; Maddox, W. Todd
2008-01-01
Category learning theorists tacitly assume that stimuli are encoded by a single pathway. Motivated by theories of object recognition, we evaluate a dual-pathway account of stimulus encoding. The part-based pathway establishes mappings between sensory input and symbols that encode discrete stimulus features, whereas the image-based pathway applies holistic templates to sensory input. Our experiments use rule-plus-exception structures in which one exception item in each category violates a salient regularity and must be distinguished from other items. In Experiment 1, we find that discrete representations are crucial for recognition of exceptions following brief training. Experiments 2 and 3 involve multi-session training regimens designed to encourage either part or image-based encoding. We find that both pathways are able to support exception encoding, but have unique characteristics. We speculate that one advantage of the part-based pathway is the ability to generalize across domains, whereas the image-based pathway provides faster and more effortless recognition. PMID:19460948
-
A survey on object detection in optical remote sensing images
NASA Astrophysics Data System (ADS)
Cheng, Gong; Han, Junwei
2016-07-01
Object detection in optical remote sensing images, being a fundamental but challenging problem in the field of aerial and satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. While enormous methods exist, a deep review of the literature concerning generic object detection is still lacking. This paper aims to provide a review of the recent progress in this field. Different from several previously published surveys that focus on a specific object class such as building and road, we concentrate on more generic object categories including, but are not limited to, road, building, tree, vehicle, ship, airport, urban-area. Covering about 270 publications we survey (1) template matching-based object detection methods, (2) knowledge-based object detection methods, (3) object-based image analysis (OBIA)-based object detection methods, (4) machine learning-based object detection methods, and (5) five publicly available datasets and three standard evaluation metrics. We also discuss the challenges of current studies and propose two promising research directions, namely deep learning-based feature representation and weakly supervised learning-based geospatial object detection. It is our hope that this survey will be beneficial for the researchers to have better understanding of this research field.
-
Learning and transfer of category knowledge in an indirect categorization task.
Helie, Sebastien; Ashby, F Gregory
2012-05-01
Knowledge representations acquired during category learning experiments are 'tuned' to the task goal. A useful paradigm to study category representations is indirect category learning. In the present article, we propose a new indirect categorization task called the "same"-"different" categorization task. The same-different categorization task is a regular same-different task, but the question asked to the participants is about the stimulus category membership instead of stimulus identity. Experiment 1 explores the possibility of indirectly learning rule-based and information-integration category structures using the new paradigm. The results suggest that there is little learning about the category structures resulting from an indirect categorization task unless the categories can be separated by a one-dimensional rule. Experiment 2 explores whether a category representation learned indirectly can be used in a direct classification task (and vice versa). The results suggest that previous categorical knowledge acquired during a direct classification task can be expressed in the same-different categorization task only when the categories can be separated by a rule that is easily verbalized. Implications of these results for categorization research are discussed.
-
Huang, Lijie; Song, Yiying; Li, Jingguang; Zhen, Zonglei; Yang, Zetian; Liu, Jia
2014-01-01
In functional magnetic resonance imaging studies, object selectivity is defined as a higher neural response to an object category than other object categories. Importantly, object selectivity is widely considered as a neural signature of a functionally-specialized area in processing its preferred object category in the human brain. However, the behavioral significance of the object selectivity remains unclear. In the present study, we used the individual differences approach to correlate participants' face selectivity in the face-selective regions with their behavioral performance in face recognition measured outside the scanner in a large sample of healthy adults. Face selectivity was defined as the z score of activation with the contrast of faces vs. non-face objects, and the face recognition ability was indexed as the normalized residual of the accuracy in recognizing previously-learned faces after regressing out that for non-face objects in an old/new memory task. We found that the participants with higher face selectivity in the fusiform face area (FFA) and the occipital face area (OFA), but not in the posterior part of the superior temporal sulcus (pSTS), possessed higher face recognition ability. Importantly, the association of face selectivity in the FFA and face recognition ability cannot be accounted for by FFA response to objects or behavioral performance in object recognition, suggesting that the association is domain-specific. Finally, the association is reliable, confirmed by the replication from another independent participant group. In sum, our finding provides empirical evidence on the validity of using object selectivity as a neural signature in defining object-selective regions in the human brain. PMID:25071513
-
Mercado, Eduardo; Church, Barbara A.; Coutinho, Mariana V. C.; Dovgopoly, Alexander; Lopata, Christopher J.; Toomey, Jennifer A.; Thomeer, Marcus L.
2015-01-01
Previous research suggests that high functioning (HF) children with autism spectrum disorder (ASD) sometimes have problems learning categories, but often appear to perform normally in categorization tasks. The deficits that individuals with ASD show when learning categories have been attributed to executive dysfunction, general deficits in implicit learning, atypical cognitive strategies, or abnormal perceptual biases and abilities. Several of these psychological explanations for category learning deficits have been associated with neural abnormalities such as cortical underconnectivity. The present study evaluated how well existing neurally based theories account for atypical perceptual category learning shown by HF children with ASD across multiple category learning tasks involving novel, abstract shapes. Consistent with earlier results, children’s performances revealed two distinct patterns of learning and generalization associated with ASD: one was indistinguishable from performance in typically developing children; the other revealed dramatic impairments. These two patterns were evident regardless of training regimen or stimulus set. Surprisingly, some children with ASD showed both patterns. Simulations of perceptual category learning could account for the two observed patterns in terms of differences in neural plasticity. However, no current psychological or neural theory adequately explains why a child with ASD might show such large fluctuations in category learning ability across training conditions or stimulus sets. PMID:26157368
-
A role for the developing lexicon in phonetic category acquisition
Feldman, Naomi H.; Griffiths, Thomas L.; Goldwater, Sharon; Morgan, James L.
2013-01-01
Infants segment words from fluent speech during the same period when they are learning phonetic categories, yet accounts of phonetic category acquisition typically ignore information about the words in which sounds appear. We use a Bayesian model to illustrate how feedback from segmented words might constrain phonetic category learning by providing information about which sounds occur together in words. Simulations demonstrate that word-level information can successfully disambiguate overlapping English vowel categories. Learning patterns in the model are shown to parallel human behavior from artificial language learning tasks. These findings point to a central role for the developing lexicon in phonetic category acquisition and provide a framework for incorporating top-down constraints into models of category learning. PMID:24219848
-
Carvalho, Paulo F.; Goldstone, Robert L.
2015-01-01
Inductive category learning takes place across time. As such, it is not surprising that the sequence in which information is studied has an impact in what is learned and how efficient learning is. In this paper we review research on different learning sequences and how this impacts learning. We analyze different aspects of interleaved (frequent alternation between categories during study) and blocked study (infrequent alternation between categories during study) that might explain how and when one sequence of study results in improved learning. While these different sequences of study differ in the amount of temporal spacing and temporal juxtaposition between items of different categories, these aspects do not seem to account for the majority of the results available in the literature. However, differences in the type of category being studied and the duration of the retention interval between study and test may play an important role. We conclude that there is no single aspect that is able to account for all the evidence available. Understanding learning as a process of sequential comparisons in time and how different sequences fundamentally alter the statistics of this experience offers a promising framework for understanding sequencing effects in category learning. We use this framework to present novel predictions and hypotheses for future research on sequencing effects in inductive category learning. PMID:25983699
-
ERIC Educational Resources Information Center
Sweller, Naomi
2015-01-01
Individuals with autism have difficulty generalising information from one situation to another, a process that requires the learning of categories and concepts. Category information may be learned through: (1) classifying items into categories, or (2) predicting missing features of category items. Predicting missing features has to this point been…
-
When more is less: Feedback effects in perceptual category learning ☆
Maddox, W. Todd; Love, Bradley C.; Glass, Brian D.; Filoteo, J. Vincent
2008-01-01
Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether their response was correct or incorrect, but are not informed of the correct category assignment. With full feedback subjects are informed of the correctness of their response and are also informed of the correct category assignment. An examination of the distinct neural circuits that subserve rule-based and information-integration category learning leads to the counterintuitive prediction that full feedback should facilitate rule-based learning but should also hinder information-integration learning. This prediction was supported in the experiment reported below. The implications of these results for theories of learning are discussed. PMID:18455155
-
Discontinuous categories affect information-integration but not rule-based category learning.
Maddox, W Todd; Filoteo, J Vincent; Lauritzen, J Scott; Connally, Emily; Hejl, Kelli D
2005-07-01
Three experiments were conducted that provide a direct examination of within-category discontinuity manipulations on the implicit, procedural-based learning and the explicit, hypothesis-testing systems proposed in F. G. Ashby, L. A. Alfonso-Reese, A. U. Turken, and E. M. Waldron's (1998) competition between verbal and implicit systems model. Discontinuous categories adversely affected information-integration but not rule-based category learning. Increasing the magnitude of the discontinuity did not lead to a significant decline in performance. The distance to the bound provides a reasonable description of the generalization profile associated with the hypothesis-testing system, whereas the distance to the bound plus the distance to the trained response region provides a reasonable description of the generalization profile associated with the procedural-based learning system. These results suggest that within-category discontinuity differentially impacts information-integration but not rule-based category learning and provides information regarding the detailed processing characteristics of each category learning system. ((c) 2005 APA, all rights reserved).
-
Grimm, Lisa R; Maddox, W Todd
2013-11-01
Research has identified multiple category-learning systems with each being "tuned" for learning categories with different task demands and each governed by different neurobiological systems. Rule-based (RB) classification involves testing verbalizable rules for category membership while information-integration (II) classification requires the implicit learning of stimulus-response mappings. In the first study to directly test rule priming with RB and II category learning, we investigated the influence of the availability of information presented at the beginning of the task. Participants viewed lines that varied in length, orientation, and position on the screen, and were primed to focus on stimulus dimensions that were relevant or irrelevant to the correct classification rule. In Experiment 1, we used an RB category structure, and in Experiment 2, we used an II category structure. Accuracy and model-based analyses suggested that a focus on relevant dimensions improves RB task performance later in learning while a focus on an irrelevant dimension improves II task performance early in learning. © 2013.
-
When It Hurts (and Helps) to Try: The Role of Effort in Language Learning
Finn, Amy S.; Lee, Taraz; Kraus, Allison; Hudson Kam, Carla L.
2014-01-01
Compared to children, adults are bad at learning language. This is counterintuitive; adults outperform children on most measures of cognition, especially those that involve effort (which continue to mature into early adulthood). The present study asks whether these mature effortful abilities interfere with language learning in adults and further, whether interference occurs equally for aspects of language that adults are good (word-segmentation) versus bad (grammar) at learning. Learners were exposed to an artificial language comprised of statistically defined words that belong to phonologically defined categories (grammar). Exposure occurred under passive or effortful conditions. Passive learners were told to listen while effortful learners were instructed to try to 1) learn the words, 2) learn the categories, or 3) learn the category-order. Effortful learners showed an advantage for learning words while passive learners showed an advantage for learning the categories. Effort can therefore hurt the learning of categories. PMID:25047901
-
When it hurts (and helps) to try: the role of effort in language learning.
Finn, Amy S; Lee, Taraz; Kraus, Allison; Hudson Kam, Carla L
2014-01-01
Compared to children, adults are bad at learning language. This is counterintuitive; adults outperform children on most measures of cognition, especially those that involve effort (which continue to mature into early adulthood). The present study asks whether these mature effortful abilities interfere with language learning in adults and further, whether interference occurs equally for aspects of language that adults are good (word-segmentation) versus bad (grammar) at learning. Learners were exposed to an artificial language comprised of statistically defined words that belong to phonologically defined categories (grammar). Exposure occurred under passive or effortful conditions. Passive learners were told to listen while effortful learners were instructed to try to 1) learn the words, 2) learn the categories, or 3) learn the category-order. Effortful learners showed an advantage for learning words while passive learners showed an advantage for learning the categories. Effort can therefore hurt the learning of categories.
-
Principle-Based Inferences in Preschoolers' Categorization of Novel Artifacts.
ERIC Educational Resources Information Center
Nelson, Deborah G. Kemler; And Others
Two parallel studies investigated the influence of principle-based and attribute-based similarity relations on new category learning by preschoolers. One of two possible functions of a single novel artifact (which differed between studies) was modeled for children and practiced by children. Children then judged which test objects received the same…
-
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.
-
Scaffolding in geometry based on self regulated learning
NASA Astrophysics Data System (ADS)
Bayuningsih, A. S.; Usodo, B.; Subanti, S.
2017-12-01
This research aim to know the influence of problem based learning model by scaffolding technique on junior high school student’s learning achievement. This research took location on the junior high school in Banyumas. The research data obtained through mathematic learning achievement test and self-regulated learning (SRL) questioner. Then, the data analysis used two ways ANOVA. The results showed that scaffolding has positive effect to the mathematic learning achievement. The mathematic learning achievement use PBL-Scaffolding model is better than use PBL. The high SRL category student has better mathematic learning achievement than middle and low SRL categories, and then the middle SRL category has better than low SRL category. So, there are interactions between learning model with self-regulated learning in increasing mathematic learning achievement.
-
Feature highlighting enhances learning of a complex natural-science category.
Miyatsu, Toshiya; Gouravajhala, Reshma; Nosofsky, Robert M; McDaniel, Mark A
2018-04-26
Learning naturalistic categories, which tend to have fuzzy boundaries and vary on many dimensions, can often be harder than learning well defined categories. One method for facilitating the category learning of naturalistic stimuli may be to provide explicit feature descriptions that highlight the characteristic features of each category. Although this method is commonly used in textbooks and classrooms, theoretically it remains uncertain whether feature descriptions should advantage learning complex natural-science categories. In three experiments, participants were trained on 12 categories of rocks, either without or with a brief description highlighting key features of each category. After training, they were tested on their ability to categorize both old and new rocks from each of the categories. Providing feature descriptions as a caption under a rock image failed to improve category learning relative to providing only the rock image with its category label (Experiment 1). However, when these same feature descriptions were presented such that they were explicitly linked to the relevant parts of the rock image (feature highlighting), participants showed significantly higher performance on both immediate generalization to new rocks (Experiment 2) and generalization after a 2-day delay (Experiment 3). Theoretical and practical implications are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
-
Ell, Shawn W; Smith, David B; Peralta, Gabriela; Hélie, Sébastien
2017-08-01
When interacting with categories, representations focused on within-category relationships are often learned, but the conditions promoting within-category representations and their generalizability are unclear. We report the results of three experiments investigating the impact of category structure and training methodology on the learning and generalization of within-category representations (i.e., correlational structure). Participants were trained on either rule-based or information-integration structures using classification (Is the stimulus a member of Category A or Category B?), concept (e.g., Is the stimulus a member of Category A, Yes or No?), or inference (infer the missing component of the stimulus from a given category) and then tested on either an inference task (Experiments 1 and 2) or a classification task (Experiment 3). For the information-integration structure, within-category representations were consistently learned, could be generalized to novel stimuli, and could be generalized to support inference at test. For the rule-based structure, extended inference training resulted in generalization to novel stimuli (Experiment 2) and inference training resulted in generalization to classification (Experiment 3). These data help to clarify the conditions under which within-category representations can be learned. Moreover, these results make an important contribution in highlighting the impact of category structure and training methodology on the generalization of categorical knowledge.
-
On Learning Natural-Science Categories That Violate the Family-Resemblance Principle.
Nosofsky, Robert M; Sanders, Craig A; Gerdom, Alex; Douglas, Bruce J; McDaniel, Mark A
2017-01-01
The general view in psychological science is that natural categories obey a coherent, family-resemblance principle. In this investigation, we documented an example of an important exception to this principle: Results of a multidimensional-scaling study of igneous, metamorphic, and sedimentary rocks (Experiment 1) suggested that the structure of these categories is disorganized and dispersed. This finding motivated us to explore what might be the optimal procedures for teaching dispersed categories, a goal that is likely critical to science education in general. Subjects in Experiment 2 learned to classify pictures of rocks into compact or dispersed high-level categories. One group learned the categories through focused high-level training, whereas a second group was required to simultaneously learn classifications at a subtype level. Although high-level training led to enhanced performance when the categories were compact, subtype training was better when the categories were dispersed. We provide an interpretation of the results in terms of an exemplar-memory model of category learning.
-
Discovery learning model with geogebra assisted for improvement mathematical visual thinking ability
NASA Astrophysics Data System (ADS)
Juandi, D.; Priatna, N.
2018-05-01
The main goal of this study is to improve the mathematical visual thinking ability of high school student through implementation the Discovery Learning Model with Geogebra Assisted. This objective can be achieved through study used quasi-experimental method, with non-random pretest-posttest control design. The sample subject of this research consist of 62 senior school student grade XI in one of school in Bandung district. The required data will be collected through documentation, observation, written tests, interviews, daily journals, and student worksheets. The results of this study are: 1) Improvement students Mathematical Visual Thinking Ability who obtain learning with applied the Discovery Learning Model with Geogebra assisted is significantly higher than students who obtain conventional learning; 2) There is a difference in the improvement of students’ Mathematical Visual Thinking ability between groups based on prior knowledge mathematical abilities (high, medium, and low) who obtained the treatment. 3) The Mathematical Visual Thinking Ability improvement of the high group is significantly higher than in the medium and low groups. 4) The quality of improvement ability of high and low prior knowledge is moderate category, in while the quality of improvement ability in the high category achieved by student with medium prior knowledge.
-
Neumann, Asger
2016-06-01
As a perspective on Mammen and Miroenkos the article is reflecting on the possibility of Activity Theory being a foundation on which Psychology could be integrated. Mammen and Miroenkos point that directed activity not only is towards objects "defined as a sum of qualities, but by individual reference" is a starting point. As a specific example the phenomenon Love, as "significant object relations", is related to the concept "choice categories". It is stated that relations of affection and love can't be understood independent of history of common activity, and that this makes the concept "choice categories" central in a psychological understanding of what love is.
-
Event-Related fMRI of Category Learning: Differences in Classification and Feedback Networks
ERIC Educational Resources Information Center
Little, Deborah M.; Shin, Silvia S.; Sisco, Shannon M.; Thulborn, Keith R.
2006-01-01
Eighteen healthy young adults underwent event-related (ER) functional magnetic resonance imaging (fMRI) of the brain while performing a visual category learning task. The specific category learning task required subjects to extract the rules that guide classification of quasi-random patterns of dots into categories. Following each classification…
-
Category learning in the color-word contingency learning paradigm.
Schmidt, James R; Augustinova, Maria; De Houwer, Jan
2018-04-01
In the typical color-word contingency learning paradigm, participants respond to the print color of words where each word is presented most often in one color. Learning is indicated by faster and more accurate responses when a word is presented in its usual color, relative to another color. To eliminate the possibility that this effect is driven exclusively by the familiarity of item-specific word-color pairings, we examine whether contingency learning effects can be observed also when colors are related to categories of words rather than to individual words. To this end, the reported experiments used three categories of words (animals, verbs, and professions) that were each predictive of one color. Importantly, each individual word was presented only once, thus eliminating individual color-word contingencies. Nevertheless, for the first time, a category-based contingency effect was observed, with faster and more accurate responses when a category item was presented in the color in which most of the other items of that category were presented. This finding helps to constrain episodic learning models and sets the stage for new research on category-based contingency learning.
-
Machine-Learning Algorithms to Code Public Health Spending Accounts
Leider, Jonathon P.; Resnick, Beth A.; Alfonso, Y. Natalia; Bishai, David
2017-01-01
Objectives: Government public health expenditure data sets require time- and labor-intensive manipulation to summarize results that public health policy makers can use. Our objective was to compare the performances of machine-learning algorithms with manual classification of public health expenditures to determine if machines could provide a faster, cheaper alternative to manual classification. Methods: We used machine-learning algorithms to replicate the process of manually classifying state public health expenditures, using the standardized public health spending categories from the Foundational Public Health Services model and a large data set from the US Census Bureau. We obtained a data set of 1.9 million individual expenditure items from 2000 to 2013. We collapsed these data into 147 280 summary expenditure records, and we followed a standardized method of manually classifying each expenditure record as public health, maybe public health, or not public health. We then trained 9 machine-learning algorithms to replicate the manual process. We calculated recall, precision, and coverage rates to measure the performance of individual and ensembled algorithms. Results: Compared with manual classification, the machine-learning random forests algorithm produced 84% recall and 91% precision. With algorithm ensembling, we achieved our target criterion of 90% recall by using a consensus ensemble of ≥6 algorithms while still retaining 93% coverage, leaving only 7% of the summary expenditure records unclassified. Conclusions: Machine learning can be a time- and cost-saving tool for estimating public health spending in the United States. It can be used with standardized public health spending categories based on the Foundational Public Health Services model to help parse public health expenditure information from other types of health-related spending, provide data that are more comparable across public health organizations, and evaluate the impact of evidence-based public health resource allocation. PMID:28363034
-
NASA Astrophysics Data System (ADS)
Samigulina, Galina A.; Shayakhmetova, Assem S.
2016-11-01
Research objective is the creation of intellectual innovative technology and information Smart-system of distance learning for visually impaired people. The organization of the available environment for receiving quality education for visually impaired people, their social adaptation in society are important and topical issues of modern education.The proposed Smart-system of distance learning for visually impaired people can significantly improve the efficiency and quality of education of this category of people. The scientific novelty of proposed Smart-system is using intelligent and statistical methods of processing multi-dimensional data, and taking into account psycho-physiological characteristics of perception and awareness learning information by visually impaired people.
-
A Metro Network for Educational Futures: State of the Process.
ERIC Educational Resources Information Center
Bleedorn, Berenice D.
This paper presents a history and description of an introductory college level survey course on the future. The objective of the course is to help students recognize the importance of considering the future in every category of learning. A new futures study curriculum at Metropolitan State University, St. Paul, Minnesota, was introduced in 1975.…
-
Learning Multisensory Representations
2016-05-23
public release. Erdogan , G., Yildirim, I., & Jacobs, R. A. (2014). Transfer of object shape knowledge across visual and haptic modalities. Proceedings...2014). The adaptive nature of visual working memory. Current Directions in Psychological Science, 23, 164-170. Erdogan , G., Yildirim, I...sequence category knowledge: A probabilistic language of thought approach. Psychonomic Bulletin and Review, 22, 673-686. Erdogan , G., Chen, Q., Garcea, F
-
Beyond the Egg Carton Alligator: To Recycle Is To Recall and Restore.
ERIC Educational Resources Information Center
Congdon, Kristin G.
2000-01-01
States that the art of recycling has more to do with connecting people with objects, traditions, and rituals than sustaining the natural environment. Discusses some lessons learned in four categories: (1) recycling as self-sufficiency; (2) recycling as renewal; (3) recycling as a spiritual activity; and (4) recycling as aesthetic transformation.…
-
ERIC Educational Resources Information Center
Durmusoglu, Mine Canan
2017-01-01
This study was aimed to make a historical review by collecting and comparing teachers' opinions on target-behaviors/learning-objectives outcomes, content, plans, activities, practices and assessment of the Ministry of National Education (MoNE), Turkey 2002, 2006, and 2013 preschool education curricula (PEC) in six categories. The sample group of…
-
ERIC Educational Resources Information Center
Bumpus, Minnette A.
2005-01-01
Motion pictures and television shows can provide mediums to facilitate the learning of management and organizational behavior theories and concepts. Although the motion pictures and television shows cited in the literature cover a broad range of cinematic categories, racial inclusion is limited. The objectives of this article are to document the…
-
ERIC Educational Resources Information Center
Bobb, Susan C.; Mani, Nivedita
2013-01-01
The current study investigated the interaction of implicit grammatical gender and semantic category knowledge during object identification. German-learning toddlers (24-month-olds) were presented with picture pairs and heard a noun (without a preceding article) labeling one of the pictures. Labels for target and distracter images either matched or…
-
Rule-Based and Information-Integration Category Learning in Normal Aging
ERIC Educational Resources Information Center
Maddox, W. Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M.
2010-01-01
The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated…
-
Metacognitive monitoring during category learning: how success affects future behaviour.
Doyle, Mario E; Hourihan, Kathleen L
2016-10-01
The purpose of this study was to see how people perceive their own learning during a category learning task, and whether their perceptions matched their performance. In two experiments, participants were asked to learn natural categories, of both high and low variability, and make category learning judgements (CLJs). Variability was manipulated by varying the number of exemplars and the number of times each exemplar was presented within each category. Experiment 1 showed that participants were generally overconfident in their knowledge of low variability families, suggesting that they considered repetition to be more useful for learning than it actually was. Also, a correct trial, for a particular category, was more likely to occur if the previous trial was correct. CLJs had the largest increase when a trial was correct following an incorrect trial and the largest decrease when an incorrect trial followed a correct trial. Experiment 2 replicated these results, but also demonstrated that global CLJ ratings showed the same bias towards repetition. These results indicate that we generally identify success as being the biggest determinant of learning, but do not always recognise cues, such as variability, that enhance learning.
-
Observation versus classification in supervised category learning.
Levering, Kimery R; Kurtz, Kenneth J
2015-02-01
The traditional supervised classification paradigm encourages learners to acquire only the knowledge needed to predict category membership (a discriminative approach). An alternative that aligns with important aspects of real-world concept formation is learning with a broader focus to acquire knowledge of the internal structure of each category (a generative approach). Our work addresses the impact of a particular component of the traditional classification task: the guess-and-correct cycle. We compare classification learning to a supervised observational learning task in which learners are shown labeled examples but make no classification response. The goals of this work sit at two levels: (1) testing for differences in the nature of the category representations that arise from two basic learning modes; and (2) evaluating the generative/discriminative continuum as a theoretical tool for understand learning modes and their outcomes. Specifically, we view the guess-and-correct cycle as consistent with a more discriminative approach and therefore expected it to lead to narrower category knowledge. Across two experiments, the observational mode led to greater sensitivity to distributional properties of features and correlations between features. We conclude that a relatively subtle procedural difference in supervised category learning substantially impacts what learners come to know about the categories. The results demonstrate the value of the generative/discriminative continuum as a tool for advancing the psychology of category learning and also provide a valuable constraint for formal models and associated theories.
-
Nomura, Emi M.; Reber, Paul J.
2012-01-01
Considerable evidence has argued in favor of multiple neural systems supporting human category learning, one based on conscious rule inference and one based on implicit information integration. However, there have been few attempts to study potential system interactions during category learning. The PINNACLE (Parallel Interactive Neural Networks Active in Category Learning) model incorporates multiple categorization systems that compete to provide categorization judgments about visual stimuli. Incorporating competing systems requires inclusion of cognitive mechanisms associated with resolving this competition and creates a potential credit assignment problem in handling feedback. The hypothesized mechanisms make predictions about internal mental states that are not always reflected in choice behavior, but may be reflected in neural activity. Two prior functional magnetic resonance imaging (fMRI) studies of category learning were re-analyzed using PINNACLE to identify neural correlates of internal cognitive states on each trial. These analyses identified additional brain regions supporting the two types of category learning, regions particularly active when the systems are hypothesized to be in maximal competition, and found evidence of covert learning activity in the “off system” (the category learning system not currently driving behavior). These results suggest that PINNACLE provides a plausible framework for how competing multiple category learning systems are organized in the brain and shows how computational modeling approaches and fMRI can be used synergistically to gain access to cognitive processes that support complex decision-making machinery. PMID:24962771
-
Toward a unified model of face and object recognition in the human visual system
Wallis, Guy
2013-01-01
Our understanding of the mechanisms and neural substrates underlying visual recognition has made considerable progress over the past 30 years. During this period, accumulating evidence has led many scientists to conclude that objects and faces are recognised in fundamentally distinct ways, and in fundamentally distinct cortical areas. In the psychological literature, in particular, this dissociation has led to a palpable disconnect between theories of how we process and represent the two classes of object. This paper follows a trend in part of the recognition literature to try to reconcile what we know about these two forms of recognition by considering the effects of learning. Taking a widely accepted, self-organizing model of object recognition, this paper explains how such a system is affected by repeated exposure to specific stimulus classes. In so doing, it explains how many aspects of recognition generally regarded as unusual to faces (holistic processing, configural processing, sensitivity to inversion, the other-race effect, the prototype effect, etc.) are emergent properties of category-specific learning within such a system. Overall, the paper describes how a single model of recognition learning can and does produce the seemingly very different types of representation associated with faces and objects. PMID:23966963
-
Learning and retention through predictive inference and classification.
Sakamoto, Yasuaki; Love, Bradley C
2010-12-01
Work in category learning addresses how humans acquire knowledge and, thus, should inform classroom practices. In two experiments, we apply and evaluate intuitions garnered from laboratory-based research in category learning to learning tasks situated in an educational context. In Experiment 1, learning through predictive inference and classification were compared for fifth-grade students using class-related materials. Making inferences about properties of category members and receiving feedback led to the acquisition of both queried (i.e., tested) properties and nonqueried properties that were correlated with a queried property (e.g., even if not queried, students learned about a species' habitat because it correlated with a queried property, like the species' size). In contrast, classifying items according to their species and receiving feedback led to knowledge of only the property most diagnostic of category membership. After multiple-day delay, the fifth-graders who learned through inference selectively retained information about the queried properties, and the fifth-graders who learned through classification retained information about the diagnostic property, indicating a role for explicit evaluation in establishing memories. Overall, inference learning resulted in fewer errors, better retention, and more liking of the categories than did classification learning. Experiment 2 revealed that querying a property only a few times was enough to manifest the full benefits of inference learning in undergraduate students. These results suggest that classroom teaching should emphasize reasoning from the category to multiple properties rather than from a set of properties to the category. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
-
Incidental learning of sound categories is impaired in developmental dyslexia.
Gabay, Yafit; Holt, Lori L
2015-12-01
Developmental dyslexia is commonly thought to arise from specific phonological impairments. However, recent evidence is consistent with the possibility that phonological impairments arise as symptoms of an underlying dysfunction of procedural learning. The nature of the link between impaired procedural learning and phonological dysfunction is unresolved. Motivated by the observation that speech processing involves the acquisition of procedural category knowledge, the present study investigates the possibility that procedural learning impairment may affect phonological processing by interfering with the typical course of phonetic category learning. The present study tests this hypothesis while controlling for linguistic experience and possible speech-specific deficits by comparing auditory category learning across artificial, nonlinguistic sounds among dyslexic adults and matched controls in a specialized first-person shooter videogame that has been shown to engage procedural learning. Nonspeech auditory category learning was assessed online via within-game measures and also with a post-training task involving overt categorization of familiar and novel sound exemplars. Each measure reveals that dyslexic participants do not acquire procedural category knowledge as effectively as age- and cognitive-ability matched controls. This difference cannot be explained by differences in perceptual acuity for the sounds. Moreover, poor nonspeech category learning is associated with slower phonological processing. Whereas phonological processing impairments have been emphasized as the cause of dyslexia, the current results suggest that impaired auditory category learning, general in nature and not specific to speech signals, could contribute to phonological deficits in dyslexia with subsequent negative effects on language acquisition and reading. Implications for the neuro-cognitive mechanisms of developmental dyslexia are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.
-
Incidental Learning of Sound Categories is Impaired in Developmental Dyslexia
Gabay, Yafit; Holt, Lori L.
2015-01-01
Developmental dyslexia is commonly thought to arise from specific phonological impairments. However, recent evidence is consistent with the possibility that phonological impairments arise as symptoms of an underlying dysfunction of procedural learning. The nature of the link between impaired procedural learning and phonological dysfunction is unresolved. Motivated by the observation that speech processing involves the acquisition of procedural category knowledge, the present study investigates the possibility that procedural learning impairment may affect phonological processing by interfering with the typical course of phonetic category learning. The present study tests this hypothesis while controlling for linguistic experience and possible speech-specific deficits by comparing auditory category learning across artificial, nonlinguistic sounds among dyslexic adults and matched controls in a specialized first-person shooter videogame that has been shown to engage procedural learning. Nonspeech auditory category learning was assessed online via within-game measures and also with a post-training task involving overt categorization of familiar and novel sound exemplars. Each measure reveals that dyslexic participants do not acquire procedural category knowledge as effectively as age- and cognitive-ability matched controls. This difference cannot be explained by differences in perceptual acuity for the sounds. Moreover, poor nonspeech category learning is associated with slower phonological processing. Whereas phonological processing impairments have been emphasized as the cause of dyslexia, the current results suggest that impaired auditory category learning, general in nature and not specific to speech signals, could contribute to phonological deficits in dyslexia with subsequent negative effects on language acquisition and reading. Implications for the neuro-cognitive mechanisms of developmental dyslexia are discussed. PMID:26409017
-
Neural Network for Nanoscience Scanning Electron Microscope Image Recognition.
Modarres, Mohammad Hadi; Aversa, Rossella; Cozzini, Stefano; Ciancio, Regina; Leto, Angelo; Brandino, Giuseppe Piero
2017-10-16
In this paper we applied transfer learning techniques for image recognition, automatic categorization, and labeling of nanoscience images obtained by scanning electron microscope (SEM). Roughly 20,000 SEM images were manually classified into 10 categories to form a labeled training set, which can be used as a reference set for future applications of deep learning enhanced algorithms in the nanoscience domain. The categories chosen spanned the range of 0-Dimensional (0D) objects such as particles, 1D nanowires and fibres, 2D films and coated surfaces, and 3D patterned surfaces such as pillars. The training set was used to retrain on the SEM dataset and to compare many convolutional neural network models (Inception-v3, Inception-v4, ResNet). We obtained compatible results by performing a feature extraction of the different models on the same dataset. We performed additional analysis of the classifier on a second test set to further investigate the results both on particular cases and from a statistical point of view. Our algorithm was able to successfully classify around 90% of a test dataset consisting of SEM images, while reduced accuracy was found in the case of images at the boundary between two categories or containing elements of multiple categories. In these cases, the image classification did not identify a predominant category with a high score. We used the statistical outcomes from testing to deploy a semi-automatic workflow able to classify and label images generated by the SEM. Finally, a separate training was performed to determine the volume fraction of coherently aligned nanowires in SEM images. The results were compared with what was obtained using the Local Gradient Orientation method. This example demonstrates the versatility and the potential of transfer learning to address specific tasks of interest in nanoscience applications.
-
Discovery learning with SAVI approach in geometry learning
NASA Astrophysics Data System (ADS)
Sahara, R.; Mardiyana; Saputro, D. R. S.
2018-05-01
Geometry is one branch of mathematics that an important role in learning mathematics in the schools. This research aims to find out about Discovery Learning with SAVI approach to achievement of learning geometry. This research was conducted at Junior High School in Surakarta city. Research data were obtained through test and questionnaire. Furthermore, the data was analyzed by using two-way Anova. The results showed that Discovery Learning with SAVI approach gives a positive influence on mathematics learning achievement. Discovery Learning with SAVI approach provides better mathematics learning outcomes than direct learning. In addition, students with high self-efficacy categories have better mathematics learning achievement than those with moderate and low self-efficacy categories, while student with moderate self-efficacy categories are better mathematics learning achievers than students with low self-efficacy categories. There is an interaction between Discovery Learning with SAVI approach and self-efficacy toward student's mathematics learning achievement. Therefore, Discovery Learning with SAVI approach can improve mathematics learning achievement.
-
Elevated depressive symptoms enhance reflexive but not reflective auditory category learning.
Maddox, W Todd; Chandrasekaran, Bharath; Smayda, Kirsten; Yi, Han-Gyol; Koslov, Seth; Beevers, Christopher G
2014-09-01
In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.
-
Elevated Depressive Symptoms Enhance Reflexive but not Reflective Auditory Category Learning
Maddox, W. Todd; Chandrasekaran, Bharath; Smayda, Kirsten; Yi, Han-Gyol; Koslov, Seth; Beevers, Christopher G.
2014-01-01
In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed. PMID:25041936
-
Timing of quizzes during learning: Effects on motivation and retention.
Healy, Alice F; Jones, Matt; Lalchandani, Lakshmi A; Tack, Lindsay Anderson
2017-06-01
This article investigates how the timing of quizzes given during learning impacts retention of studied material. We investigated the hypothesis that interspersing quizzes among study blocks increases student engagement, thus improving learning. Participants learned 8 artificial facts about each of 8 plant categories, with the categories blocked during learning. Quizzes about 4 of the 8 facts from each category occurred either immediately after studying the facts for that category (standard) or after studying the facts from all 8 categories (postponed). In Experiment 1, participants were given tests shortly after learning and several days later, including both the initially quizzed and unquizzed facts. Test performance was better in the standard than in the postponed condition, especially for categories learned later in the sequence. This result held even for the facts not quizzed during learning, suggesting that the advantage cannot be due to any direct testing effects. Instead the results support the hypothesis that interrupting learning with quiz questions is beneficial because it can enhance learner engagement. Experiment 2 provided further support for this hypothesis, based on participants' retrospective ratings of their task engagement during the learning phase. These findings have practical implications for when to introduce quizzes in the classroom. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
-
Linguistic labels, dynamic visual features, and attention in infant category learning.
Deng, Wei Sophia; Sloutsky, Vladimir M
2015-06-01
How do words affect categorization? According to some accounts, even early in development words are category markers and are different from other features. According to other accounts, early in development words are part of the input and are akin to other features. The current study addressed this issue by examining the role of words and dynamic visual features in category learning in 8- to 12-month-old infants. Infants were familiarized with exemplars from one category in a label-defined or motion-defined condition and then tested with prototypes from the studied category and from a novel contrast category. Eye-tracking results indicated that infants exhibited better category learning in the motion-defined condition than in the label-defined condition, and their attention was more distributed among different features when there was a dynamic visual feature compared with the label-defined condition. These results provide little evidence for the idea that linguistic labels are category markers that facilitate category learning. Copyright © 2015 Elsevier Inc. All rights reserved.
-
Linguistic Labels, Dynamic Visual Features, and Attention in Infant Category Learning
Deng, Wei (Sophia); Sloutsky, Vladimir M.
2015-01-01
How do words affect categorization? According to some accounts, even early in development, words are category markers and are different from other features. According to other accounts, early in development, words are part of the input and are akin to other features. The current study addressed this issue by examining the role of words and dynamic visual features in category learning in 8- to 12- month infants. Infants were familiarized with exemplars from one category in a label-defined or motion-defined condition and then tested with prototypes from the studied category and from a novel contrast category. Eye tracking results indicated that infants exhibited better category learning in the motion-defined than in the label-defined condition and their attention was more distributed among different features when there was a dynamic visual feature compared to the label-defined condition. These results provide little evidence for the idea that linguistic labels are category markers that facilitate category learning. PMID:25819100
-
Analyse von Unterrichtsmaterialien der Menschenrechtsbildung
NASA Astrophysics Data System (ADS)
Lenhart, Volker
2002-07-01
This article surveys five manuals on human rights education, examining and comparing them according to a set of basic categories such as the educational level of the target audience, the learning objectives and the educational content. This approach is used to establish the overall curricular orientation of the manuals. In addition, one teaching unit from each manual is selected for special analysis. Based on the results of this survey, the author argues that the tradition of moral education elaborated by Lawrence Kohlberg should be integrated into our concept of human rights teaching and learning.
-
Explanation and Prior Knowledge Interact to Guide Learning
ERIC Educational Resources Information Center
Williams, Joseph J.; Lombrozo, Tania
2013-01-01
How do explaining and prior knowledge contribute to learning? Four experiments explored the relationship between explanation and prior knowledge in category learning. The experiments independently manipulated whether participants were prompted to explain the category membership of study observations and whether category labels were informative in…
-
Sweller, Naomi; Hayes, Brett K
2010-08-01
Three studies examined how task demands that impact on attention to typical or atypical category features shape the category representations formed through classification learning and inference learning. During training categories were learned via exemplar classification or by inferring missing exemplar features. In the latter condition inferences were made about missing typical features alone (typical feature inference) or about both missing typical and atypical features (mixed feature inference). Classification and mixed feature inference led to the incorporation of typical and atypical features into category representations, with both kinds of features influencing inferences about familiar (Experiments 1 and 2) and novel (Experiment 3) test items. Those in the typical inference condition focused primarily on typical features. Together with formal modelling, these results challenge previous accounts that have characterized inference learning as producing a focus on typical category features. The results show that two different kinds of inference learning are possible and that these are subserved by different kinds of category representations.
-
Deep Neural Networks as a Computational Model for Human Shape Sensitivity
Op de Beeck, Hans P.
2016-01-01
Theories of object recognition agree that shape is of primordial importance, but there is no consensus about how shape might be represented, and so far attempts to implement a model of shape perception that would work with realistic stimuli have largely failed. Recent studies suggest that state-of-the-art convolutional ‘deep’ neural networks (DNNs) capture important aspects of human object perception. We hypothesized that these successes might be partially related to a human-like representation of object shape. Here we demonstrate that sensitivity for shape features, characteristic to human and primate vision, emerges in DNNs when trained for generic object recognition from natural photographs. We show that these models explain human shape judgments for several benchmark behavioral and neural stimulus sets on which earlier models mostly failed. In particular, although never explicitly trained for such stimuli, DNNs develop acute sensitivity to minute variations in shape and to non-accidental properties that have long been implicated to form the basis for object recognition. Even more strikingly, when tested with a challenging stimulus set in which shape and category membership are dissociated, the most complex model architectures capture human shape sensitivity as well as some aspects of the category structure that emerges from human judgments. As a whole, these results indicate that convolutional neural networks not only learn physically correct representations of object categories but also develop perceptually accurate representational spaces of shapes. An even more complete model of human object representations might be in sight by training deep architectures for multiple tasks, which is so characteristic in human development. PMID:27124699
-
Inferential Learning of Serial Order of Perceptual Categories by Rhesus Monkeys (Macaca mulatta)
2017-01-01
Category learning in animals is typically trained explicitly, in most instances by varying the exemplars of a single category in a matching-to-sample task. Here, we show that male rhesus macaques can learn categories by a transitive inference paradigm in which novel exemplars of five categories were presented throughout training. Instead of requiring decisions about a constant set of repetitively presented stimuli, we studied the macaque's ability to determine the relative order of multiple exemplars of particular stimuli that were rarely repeated. Ordinal decisions generalized both to novel stimuli and, as a consequence, to novel pairings. Thus, we showed that rhesus monkeys could learn to categorize on the basis of implied ordinal position, without prior matching-to-sample training, and that they could then make inferences about category order. Our results challenge the plausibility of association models of category learning and broaden the scope of the transitive inference paradigm. SIGNIFICANCE STATEMENT The cognitive abilities of nonhuman animals are of enduring interest to scientists and the general public because they blur the dividing line between human and nonhuman intelligence. Categorization and sequence learning are highly abstract cognitive abilities each in their own right. This study is the first to provide evidence that visual categories can be ordered serially by macaque monkeys using a behavioral paradigm that provides no explicit feedback about category or serial order. These results strongly challenge accounts of learning based on stimulus–response associations. PMID:28546309
-
Carpenter, Kathryn L; Wills, Andy J; Benattayallah, Abdelmalek; Milton, Fraser
2016-10-01
The influential competition between verbal and implicit systems (COVIS) model proposes that category learning is driven by two competing neural systems-an explicit, verbal, system, and a procedural-based, implicit, system. In the current fMRI study, participants learned either a conjunctive, rule-based (RB), category structure that is believed to engage the explicit system, or an information-integration category structure that is thought to preferentially recruit the implicit system. The RB and information-integration category structures were matched for participant error rate, the number of relevant stimulus dimensions, and category separation. Under these conditions, considerable overlap in brain activation, including the prefrontal cortex, basal ganglia, and the hippocampus, was found between the RB and information-integration category structures. Contrary to the predictions of COVIS, the medial temporal lobes and in particular the hippocampus, key regions for explicit memory, were found to be more active in the information-integration condition than in the RB condition. No regions were more activated in RB than information-integration category learning. The implications of these results for theories of category learning are discussed. Hum Brain Mapp 37:3557-3574, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
-
ERIC Educational Resources Information Center
Maddox, W. Todd; Ing, A. David
2005-01-01
W. T. Maddox, F. G. Ashby, and C. J. Bohil (2003) found that delayed feedback adversely affects information-integration but not rule-based category learning in support of a multiple-systems approach to category learning. However, differences in the number of stimulus dimensions relevant to solving the task and perceptual similarity failed to rule…
-
Problem based learning with scaffolding technique on geometry
NASA Astrophysics Data System (ADS)
Bayuningsih, A. S.; Usodo, B.; Subanti, S.
2018-05-01
Geometry as one of the branches of mathematics has an important role in the study of mathematics. This research aims to explore the effectiveness of Problem Based Learning (PBL) with scaffolding technique viewed from self-regulation learning toward students’ achievement learning in mathematics. The research data obtained through mathematics learning achievement test and self-regulated learning (SRL) questionnaire. This research employed quasi-experimental research. The subjects of this research are students of the junior high school in Banyumas Central Java. The result of the research showed that problem-based learning model with scaffolding technique is more effective to generate students’ mathematics learning achievement than direct learning (DL). This is because in PBL model students are more able to think actively and creatively. The high SRL category student has better mathematic learning achievement than middle and low SRL categories, and then the middle SRL category has better than low SRL category. So, there are interactions between learning model with self-regulated learning in increasing mathematic learning achievement.
-
Impairments in part-whole representations of objects in two cases of integrative visual agnosia.
Behrmann, Marlene; Williams, Pepper
2007-10-01
How complex multipart visual objects are represented perceptually remains a subject of ongoing investigation. One source of evidence that has been used to shed light on this issue comes from the study of individuals who fail to integrate disparate parts of visual objects. This study reports a series of experiments that examine the ability of two such patients with this form of agnosia (integrative agnosia; IA), S.M. and C.R., to discriminate and categorize exemplars of a rich set of novel objects, "Fribbles", whose visual similarity (number of shared parts) and category membership (shared overall shape) can be manipulated. Both patients performed increasingly poorly as the number of parts required for differentiating one Fribble from another increased. Both patients were also impaired at determining when two Fribbles belonged in the same category, a process that relies on abstracting spatial relations between parts. C.R., the less impaired of the two, but not S.M., eventually learned to categorize the Fribbles but required substantially more training than normal perceivers. S.M.'s failure is not attributable to a problem in learning to use a label for identification nor is it obviously attributable to a visual memory deficit. Rather, the findings indicate that, although the patients may be able to represent a small number of parts independently, in order to represent multipart images, the parts need to be integrated or chunked into a coherent whole. It is this integrative process that is impaired in IA and appears to play a critical role in the normal object recognition of complex images.
-
The competency of internists in holistic global care to support healthy Indonesia 2010.
Rudijanto, Achmad
2006-01-01
All patients are entitled to good standards of practice and care from their doctors. The improved health of all peoples is the main goal of medical education, including for the education of internal medicine registrars. The future development of the direction and goal of education, the level of competence of internal medicine specialists, and the process of learning will be related to preparing the internal medicine specialist to have global competitive advantage. Identification of general competencies is the first step in a long-term effort designed to emphasize educational outcome, for assessment in residency programs, and in the accreditation process. To achieve that competence, a variety of learning opportunities need to be provided in order that the resident can achieve the necessary knowledge, skills, attitude, and behaviors. Identification of the role and function of internal medicine specialists is needed prior to the development of the general competencies. As educational objectives, the competencies fall into two main categories: knowledge-based and performance-based. Knowledge-based competency has two components, medical knowledge (bio-science and clinical medicine) and contextual knowledge (epidemiology, health service organization, and human behavior). The performance base has two components, intellectual skills and the interpersonal skills. Besides the two main categories of educational objectives, there are behavioral objectives that residents must achieve through the educational program, to ensure that residents are able to deal with a range of prescribed clinical situations effectively, safely, humanely, and economically. The achievement of behavioral objectives will ensure, at least in part, that the doctor will implement good medical practice. The index clinical/community situations (ICS) on which the educational objectives will be based are taken from diseases and illnesses that occur in clinical and community settings. No resident can master all medicine there is to know, as there are no limits to what can be known about medicine. It is important to make choices in selecting what residents should learn by analyzing the ICS.
-
ERIC Educational Resources Information Center
Ohio State Univ., Columbus. National Center for Research in Vocational Education.
This module is one of a series of 127 performance-based teacher education (PBTE) learning packages focusing upon specific professional competencies of vocational teachers. The competencies upon which these modules are based were identified and verified through research as being important to successful vocational teaching at both the secondary and…
-
ERIC Educational Resources Information Center
Ohio State Univ., Columbus. National Center for Research in Vocational Education.
This second in a series of six learning modules on instructional evaluation is designed to give secondary and postsecondary vocational teachers help in assessing student performance as it relates to knowledge of the facts, data, related information, and procedures taught in their vocational courses. The terminal objective for the module is to…
-
Feature saliency and feedback information interactively impact visual category learning
Hammer, Rubi; Sloutsky, Vladimir; Grill-Spector, Kalanit
2015-01-01
Visual category learning (VCL) involves detecting which features are most relevant for categorization. VCL relies on attentional learning, which enables effectively redirecting attention to object’s features most relevant for categorization, while ‘filtering out’ irrelevant features. When features relevant for categorization are not salient, VCL relies also on perceptual learning, which enables becoming more sensitive to subtle yet important differences between objects. Little is known about how attentional learning and perceptual learning interact when VCL relies on both processes at the same time. Here we tested this interaction. Participants performed VCL tasks in which they learned to categorize novel stimuli by detecting the feature dimension relevant for categorization. Tasks varied both in feature saliency (low-saliency tasks that required perceptual learning vs. high-saliency tasks), and in feedback information (tasks with mid-information, moderately ambiguous feedback that increased attentional load, vs. tasks with high-information non-ambiguous feedback). We found that mid-information and high-information feedback were similarly effective for VCL in high-saliency tasks. This suggests that an increased attentional load, associated with the processing of moderately ambiguous feedback, has little effect on VCL when features are salient. In low-saliency tasks, VCL relied on slower perceptual learning; but when the feedback was highly informative participants were able to ultimately attain the same performance as during the high-saliency VCL tasks. However, VCL was significantly compromised in the low-saliency mid-information feedback task. We suggest that such low-saliency mid-information learning scenarios are characterized by a ‘cognitive loop paradox’ where two interdependent learning processes have to take place simultaneously. PMID:25745404
-
An Examination of Strategy Implementation during Abstract Nonlinguistic Category Learning in Aphasia
ERIC Educational Resources Information Center
Vallila-Rohter, Sofia; Kiran, Swathi
2015-01-01
Purpose: Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Method: Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases…
-
Semantic Categories and Context in L2 Vocabulary Learning
ERIC Educational Resources Information Center
Bolger, Patrick; Zapata, Gabriela
2011-01-01
This article extends recent findings that presenting semantically related vocabulary simultaneously inhibits learning. It does so by adding story contexts. Participants learned 32 new labels for known concepts from four different semantic categories in stories that were either semantically related (one category per story) or semantically unrelated…
-
Rule-Based Category Learning in Down Syndrome
ERIC Educational Resources Information Center
Phillips, B. Allyson; Conners, Frances A.; Merrill, Edward; Klinger, Mark R.
2014-01-01
Rule-based category learning was examined in youths with Down syndrome (DS), youths with intellectual disability (ID), and typically developing (TD) youths. Two tasks measured category learning: the Modified Card Sort task (MCST) and the Concept Formation test of the Woodcock-Johnson-III (Woodcock, McGrew, & Mather, 2001). In regression-based…
-
Study preferences for exemplar variability in self-regulated category learning.
Wahlheim, Christopher N; DeSoto, K Andrew
2017-02-01
Increasing exemplar variability during category learning can enhance classification of novel exemplars from studied categories. Four experiments examined whether participants preferred variability when making study choices with the goal of later classifying novel exemplars. In Experiments 1-3, participants were familiarised with exemplars of birds from multiple categories prior to making category-level assessments of learning and subsequent choices about whether to receive more variability or repetitions of exemplars during study. After study, participants classified novel exemplars from studied categories. The majority of participants showed a consistent preference for variability in their study, but choices were not related to category-level assessments of learning. Experiment 4 provided evidence that study preferences were based primarily on theoretical beliefs in that most participants indicated a preference for variability on questionnaires that did not include prior experience with exemplars. Potential directions for theoretical development and applications to education are discussed.
-
Brady, Timothy F; Oliva, Aude
2008-07-01
Recent work has shown that observers can parse streams of syllables, tones, or visual shapes and learn statistical regularities in them without conscious intent (e.g., learn that A is always followed by B). Here, we demonstrate that these statistical-learning mechanisms can operate at an abstract, conceptual level. In Experiments 1 and 2, observers incidentally learned which semantic categories of natural scenes covaried (e.g., kitchen scenes were always followed by forest scenes). In Experiments 3 and 4, category learning with images of scenes transferred to words that represented the categories. In each experiment, the category of the scenes was irrelevant to the task. Together, these results suggest that statistical-learning mechanisms can operate at a categorical level, enabling generalization of learned regularities using existing conceptual knowledge. Such mechanisms may guide learning in domains as disparate as the acquisition of causal knowledge and the development of cognitive maps from environmental exploration.
-
Exploiting range imagery: techniques and applications
NASA Astrophysics Data System (ADS)
Armbruster, Walter
2009-07-01
Practically no applications exist for which automatic processing of 2D intensity imagery can equal human visual perception. This is not the case for range imagery. The paper gives examples of 3D laser radar applications, for which automatic data processing can exceed human visual cognition capabilities and describes basic processing techniques for attaining these results. The examples are drawn from the fields of helicopter obstacle avoidance, object detection in surveillance applications, object recognition at high range, multi-object-tracking, and object re-identification in range image sequences. Processing times and recognition performances are summarized. The techniques used exploit the bijective continuity of the imaging process as well as its independence of object reflectivity, emissivity and illumination. This allows precise formulations of the probability distributions involved in figure-ground segmentation, feature-based object classification and model based object recognition. The probabilistic approach guarantees optimal solutions for single images and enables Bayesian learning in range image sequences. Finally, due to recent results in 3D-surface completion, no prior model libraries are required for recognizing and re-identifying objects of quite general object categories, opening the way to unsupervised learning and fully autonomous cognitive systems.
-
ERIC Educational Resources Information Center
Hui, W.; Hu, P. J.-H.; Clark, T. H. K.; Tam, K. Y.; Milton, J.
2008-01-01
A field experiment compares the effectiveness and satisfaction associated with technology-assisted learning with that of face-to-face learning. The empirical evidence suggests that technology-assisted learning effectiveness depends on the target knowledge category. Building on Kolb's experiential learning model, we show that technology-assisted…
-
Makino, Hiroshi; Jitsumori, Masako
2007-02-01
Adult humans (Homo sapiens) and pigeons (Columba livia) were trained to discriminate artificial categories that the authors created by mimicking 2 properties of natural categories. One was a family resemblance relationship: The highly variable exemplars, including those that did not have features in common, were structured by a similarity network with the features correlating to one another in each category. The other was a polymorphous rule: No single feature was essential for distinguishing the categories, and all the features overlapped between the categories. Pigeons learned the categories with ease and then showed a prototype effect in accord with the degrees of family resemblance for novel stimuli. Some evidence was also observed for interactive effects of learning of individual exemplars and feature frequencies. Humans had difficulty in learning the categories. The participants who learned the categories generally responded to novel stimuli in an all-or-none fashion on the basis of their acquired classification decision rules. The processes that underlie the classification performances of the 2 species are discussed.
-
When does fading enhance perceptual category learning?
Pashler, Harold; Mozer, Michael C
2013-07-01
Training that uses exaggerated versions of a stimulus discrimination (fading) has sometimes been found to enhance category learning, mostly in studies involving animals and impaired populations. However, little is known about whether and when fading facilitates learning for typical individuals. This issue was explored in 7 experiments. In Experiments 1 and 2, observers discriminated stimuli based on a single sensory continuum (time duration and line length, respectively). Adaptive fading dramatically improved performance in training (unsurprisingly) but did not enhance learning as assessed in a final test. The same was true for nonadaptive linear fading (Experiment 3). However, when variation in length (predicting category membership) was embedded among other (category-irrelevant) variation, fading dramatically enhanced not only performance in training but also learning as assessed in a final test (Experiments 4 and 5). Fading also helped learners to acquire a color saturation discrimination amid category-irrelevant variation in hue and brightness, although this learning proved transitory after feedback was withdrawn (Experiment 7). Theoretical implications are discussed, and we argue that fading should have practical utility in naturalistic category learning tasks, which involve extremely high dimensional stimuli and many irrelevant dimensions. PsycINFO Database Record (c) 2013 APA, all rights reserved.
-
Vallila-Rohter, Sofia; Kiran, Swathi
2015-08-01
Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases were calculated. To evaluate strategy use, strategy analyses were conducted over training and testing phases. Participant data were compared with model data that simulated complex multi-cue, single feature, and random pattern strategies. Learning success and strategy use were evaluated within the context of standardized cognitive-linguistic assessments. Categorization accuracy was higher among control participants than among PWA. The majority of control participants implemented suboptimal or optimal multi-cue and single-feature strategies by testing phases of the experiment. In contrast, a large subgroup of PWA implemented random patterns, or no strategy, during both training and testing phases of the experiment. Person-to-person variability arises not only in category learning ability but also in the strategies implemented to complete category learning tasks. PWA less frequently developed effective strategies during category learning tasks than control participants. Certain PWA may have impairments of strategy development or feedback processing not captured by language and currently probed cognitive abilities.
-
Learning Vowel Categories from Maternal Speech in Gurindji Kriol
ERIC Educational Resources Information Center
Jones, Caroline; Meakins, Felicity; Muawiyath, Shujau
2012-01-01
Distributional learning is a proposal for how infants might learn early speech sound categories from acoustic input before they know many words. When categories in the input differ greatly in relative frequency and overlap in acoustic space, research in bilingual development suggests that this affects the course of development. In the present…
-
Characterizing Rule-Based Category Learning Deficits in Patients with Parkinson's Disease
ERIC Educational Resources Information Center
Filoteo, J. Vincent; Maddox, W. Todd; Ing, A. David; Song, David D.
2007-01-01
Parkinson's disease (PD) patients and normal controls were tested in three category learning experiments to determine if previously observed rule-based category learning impairments in PD patients were due to deficits in selective attention or working memory. In Experiment 1, optimal categorization required participants to base their decision on a…
-
Toddlers’ referential understanding of pictures
Ganea, Patricia A.; Preissler, Melissa Allen; Butler, Lucas; Carey, Susan; DeLoache, Judy S.
2010-01-01
Pictures are referential in that they can represent objects in the real world. Here we explore the emergence of understanding of the referential potential of pictures in the second year of life. In Study 1, 15-, 18-, and 24-month-old children learned a word for a picture of a novel object (e.g., “blicket”) in the context of a picture-book interaction. Later they were presented with the picture of a blicket along with the real object it depicted and asked to indicate “a blicket.” Many of the 24-, 18-month-olds and even 15-month-olds indicated the real object as an instance of a “blicket”, consistent with an understanding of the referential relation between pictures and objects. In Study 2, children were tested with an exemplar object that differed in color from the depicted object to determine if they would extend the label they had learned for the depicted object to a slightly different category member. The 15-, 18- and 24-month-old participants failed to make a consistent referential response. The results are discussed in terms of whether pictorial understanding at this age is associative or symbolic. PMID:19560783
-
Franz, A; Triesch, J
2010-12-01
The perception of the unity of objects, their permanence when out of sight, and the ability to perceive continuous object trajectories even during occlusion belong to the first and most important capacities that infants have to acquire. Despite much research a unified model of the development of these abilities is still missing. Here we make an attempt to provide such a unified model. We present a recurrent artificial neural network that learns to predict the motion of stimuli occluding each other and that develops representations of occluded object parts. It represents completely occluded, moving objects for several time steps and successfully predicts their reappearance after occlusion. This framework allows us to account for a broad range of experimental data. Specifically, the model explains how the perception of object unity develops, the role of the width of the occluders, and it also accounts for differences between data for moving and stationary stimuli. We demonstrate that these abilities can be acquired by learning to predict the sensory input. The model makes specific predictions and provides a unifying framework that has the potential to be extended to other visual event categories. Copyright © 2010 Elsevier Inc. All rights reserved.
-
Nahinsky, Irwin D; Lucas, Barbara A; Edgell, Stephen E; Overfelt, Joseph; Loeb, Richard
2004-01-01
We investigated the effect of learning one category structure on the learning of a related category structure. Photograph-name combinations, called identifiers, were associated with values of four demographic attributes. Two problems were related by analogous demographic attributes, common identifiers, or both to examine the impact of common identifier, related general characteristics, and the interaction of the two variables in mediating learning transfer from one category structure to another. Problems sharing the same identifier information prompted greater positive transfer than those not sharing the same identifier information. In contrast, analogous defining characteristics in the two problems did not facilitate transfer. We computed correlations between responses to first-problem stimuli and responses to analogous second-problem stimuli for each participant. The analogous characteristics produced a tendency to respond in the same way to corresponding stimuli in the two problems. The results support an alignment between category structures related by analogous defining characteristics, which is facilitated by specific identifier information shared by two category structures.
-
When More Is Less: Feedback Effects in Perceptual Category Learning
ERIC Educational Resources Information Center
Maddox, W. Todd; Love, Bradley C.; Glass, Brian D.; Filoteo, J. Vincent
2008-01-01
Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether…
-
Incremental Bayesian Category Learning from Natural Language
ERIC Educational Resources Information Center
Frermann, Lea; Lapata, Mirella
2016-01-01
Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words (e.g., "chair" is a member of the furniture category). We present a Bayesian model that, unlike…
-
Analogical reasoning in amazons.
Obozova, Tanya; Smirnova, Anna; Zorina, Zoya; Wasserman, Edward
2015-11-01
Two juvenile orange-winged amazons (Amazona amazonica) were initially trained to match visual stimuli by color, shape, and number of items, but not by size. After learning these three identity matching-to-sample tasks, the parrots transferred discriminative responding to new stimuli from the same categories that had been used in training (other colors, shapes, and numbers of items) as well as to stimuli from a different category (stimuli varying in size). In the critical testing phase, both parrots exhibited reliable relational matching-to-sample (RMTS) behavior, suggesting that they perceived and compared the relationship between objects in the sample stimulus pair to the relationship between objects in the comparison stimulus pairs, even though no physical matches were possible between items in the sample and comparison pairs. The parrots spontaneously exhibited this higher-order relational responding without having ever before been trained on RMTS tasks, therefore joining apes and crows in displaying this abstract cognitive behavior.
-
NASA Astrophysics Data System (ADS)
Durner, Maximilian; Márton, Zoltán.; Hillenbrand, Ulrich; Ali, Haider; Kleinsteuber, Martin
2017-03-01
In this work, a new ensemble method for the task of category recognition in different environments is presented. The focus is on service robotic perception in an open environment, where the robot's task is to recognize previously unseen objects of predefined categories, based on training on a public dataset. We propose an ensemble learning approach to be able to flexibly combine complementary sources of information (different state-of-the-art descriptors computed on color and depth images), based on a Markov Random Field (MRF). By exploiting its specific characteristics, the MRF ensemble method can also be executed as a Dynamic Classifier Selection (DCS) system. In the experiments, the committee- and topology-dependent performance boost of our ensemble is shown. Despite reduced computational costs and using less information, our strategy performs on the same level as common ensemble approaches. Finally, the impact of large differences between datasets is analyzed.
-
Schweizer, Tom A; Dixon, Mike J; Desmarais, Geneviève; Smith, Stephen D
2002-01-01
Identification deficits were investigated in ELM, a temporal lobe stroke patient with category-specific deficits. We replicated previous work done on FS, a patient with category specific deficits as a result of herpes viral encephalitis. ELM was tested using novel, computer generated shapes that were paired with artifact labels. We paired semantically close or disparate labels to shapes and ELM attempted to learn these pairings. Overall, ELM's shape-label confusions were most detrimentally affected when we used labels that referred to objects that were visually and semantically close. However, as with FS, ELM had as many errors when shapes were paired with the labels "donut," "tire," and "washer" as he did when they were paired with visually and semantically close artifact labels. Two explanations are put forth to account for the anomalous performance by both patients on the triad of donut-tire-washer.
-
Gnadt, William; Grossberg, Stephen
2008-06-01
How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile robots, or animats, need reactive mechanisms for exploration, and learned plans to reach goal objects once an environment becomes familiar. The SOVEREIGN (Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation) animat model embodies these capabilities, and is tested in a 3D virtual reality environment. SOVEREIGN includes several interacting subsystems which model complementary properties of cortical What and Where processing streams and which clarify similarities between mechanisms for navigation and arm movement control. As the animat explores an environment, visual inputs are processed by networks that are sensitive to visual form and motion in the What and Where streams, respectively. Position-invariant and size-invariant recognition categories are learned by real-time incremental learning in the What stream. Estimates of target position relative to the animat are computed in the Where stream, and can activate approach movements toward the target. Motion cues from animat locomotion can elicit head-orienting movements to bring a new target into view. Approach and orienting movements are alternately performed during animat navigation. Cumulative estimates of each movement are derived from interacting proprioceptive and visual cues. Movement sequences are stored within a motor working memory. Sequences of visual categories are stored in a sensory working memory. These working memories trigger learning of sensory and motor sequence categories, or plans, which together control planned movements. Predictively effective chunk combinations are selectively enhanced via reinforcement learning when the animat is rewarded. Selected planning chunks effect a gradual transition from variable reactive exploratory movements to efficient goal-oriented planned movement sequences. Volitional signals gate interactions between model subsystems and the release of overt behaviors. The model can control different motor sequences under different motivational states and learns more efficient sequences to rewarded goals as exploration proceeds.
-
The time course of explicit and implicit categorization.
Smith, J David; Zakrzewski, Alexandria C; Herberger, Eric R; Boomer, Joseph; Roeder, Jessica L; Ashby, F Gregory; Church, Barbara A
2015-10-01
Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization.
-
Learning and Retention through Predictive Inference and Classification
ERIC Educational Resources Information Center
Sakamoto, Yasuaki; Love, Bradley C.
2010-01-01
Work in category learning addresses how humans acquire knowledge and, thus, should inform classroom practices. In two experiments, we apply and evaluate intuitions garnered from laboratory-based research in category learning to learning tasks situated in an educational context. In Experiment 1, learning through predictive inference and…
-
Testing Prepares Students to Learn Better: The Forward Effect of Testing in Category Learning
ERIC Educational Resources Information Center
Lee, Hee Seung; Ahn, Dahwi
2018-01-01
The forward effect of testing occurs when testing on previously studied information facilitates subsequent learning. The present research investigated whether interim testing on initially studied materials enhances the learning of new materials in category learning and examined the metacognitive judgments of such learning. Across the 4…
-
Normal Aging and the Dissociable Prototype Learning Systems
Glass, Brian D.; Chotibut, Tanya; Pacheco, Jennifer; Schnyer, David M.; Maddox, W. Todd
2011-01-01
Dissociable prototype learning systems have been demonstrated behaviorally and with neuroimaging in younger adults as well as with patient populations. In A/not-A (AN) prototype learning, participants are shown members of category A during training, and during test are asked to decide whether novel items are in category A or are not in category A. Research suggests that AN learning is mediated by a perceptual learning system. In A/B (AB) prototype learning, participants are shown members of category A and B during training, and during test are asked to decide whether novel items are in category A or category B. In contrast to AN, research suggests that AB learning is mediated by a declarative memory system. The current study examined the effects of normal aging on AN and AB prototype learning. We observed an age-related deficit in AB learning, but an age-related advantage in AN learning. Computational modeling supports one possible interpretation based on narrower selective attentional focus in older adults in the AB task and broader selective attention in the AN task. Neuropsychological testing in older participants suggested that executive functioning and attentional control were associated with better performance in both tasks. However, nonverbal memory was associated with better AN performance, while visual attention was associated with worse AB performance. The results support an interactive memory systems approach and suggest that age-related declines in one memory system can lead to deficits in some tasks, but to enhanced performance in others. PMID:21875215
-
Object detection in natural scenes: Independent effects of spatial and category-based attention.
Stein, Timo; Peelen, Marius V
2017-04-01
Humans are remarkably efficient in detecting highly familiar object categories in natural scenes, with evidence suggesting that such object detection can be performed in the (near) absence of attention. Here we systematically explored the influences of both spatial attention and category-based attention on the accuracy of object detection in natural scenes. Manipulating both types of attention additionally allowed for addressing how these factors interact: whether the requirement for spatial attention depends on the extent to which observers are prepared to detect a specific object category-that is, on category-based attention. The results showed that the detection of targets from one category (animals or vehicles) was better than the detection of targets from two categories (animals and vehicles), demonstrating the beneficial effect of category-based attention. This effect did not depend on the semantic congruency of the target object and the background scene, indicating that observers attended to visual features diagnostic of the foreground target objects from the cued category. Importantly, in three experiments the detection of objects in scenes presented in the periphery was significantly impaired when observers simultaneously performed an attentionally demanding task at fixation, showing that spatial attention affects natural scene perception. In all experiments, the effects of category-based attention and spatial attention on object detection performance were additive rather than interactive. Finally, neither spatial nor category-based attention influenced metacognitive ability for object detection performance. These findings demonstrate that efficient object detection in natural scenes is independently facilitated by spatial and category-based attention.
-
Word-level information influences phonetic learning in adults and infants
Feldman, Naomi H.; Myers, Emily B.; White, Katherine S.; Griffiths, Thomas L.; Morgan, James L.
2013-01-01
Infants begin to segment words from fluent speech during the same time period that they learn phonetic categories. Segmented words can provide a potentially useful cue for phonetic learning, yet accounts of phonetic category acquisition typically ignore the contexts in which sounds appear. We present two experiments to show that, contrary to the assumption that phonetic learning occurs in isolation, learners are sensitive to the words in which sounds appear and can use this information to constrain their interpretation of phonetic variability. Experiment 1 shows that adults use word-level information in a phonetic category learning task, assigning acoustically similar vowels to different categories more often when those sounds consistently appear in different words. Experiment 2 demonstrates that eight-month-old infants similarly pay attention to word-level information and that this information affects how they treat phonetic contrasts. These findings suggest that phonetic category learning is a rich, interactive process that takes advantage of many different types of cues that are present in the input. PMID:23562941
-
INCREASES IN FUNCTIONAL CONNECTIVITY BETWEEN PREFRONTAL CORTEX AND STRIATUM DURING CATEGORY LEARNING
Antzoulatos, Evan G.; Miller, Earl K.
2014-01-01
SUMMARY Functional connectivity between the prefrontal cortex (PFC) and striatum (STR) is thought critical for cognition, and has been linked to conditions like autism and schizophrenia. We recorded from multiple electrodes in PFC and STR while monkeys acquired new categories. Category learning was accompanied by an increase in beta-band synchronization of LFPs between, but not within, the PFC and STR. After learning, different pairs of PFC-STR electrodes showed stronger synchrony for one or the other category, suggesting category-specific functional circuits. This category-specific synchrony was also seen between PFC spikes and STR LFPs, but not the reverse, reflecting the direct monosynaptic connections from the PFC to STR. However, causal connectivity analyses suggested that the polysynaptic connections from STR to the PFC exerted a stronger overall influence. This supports models positing that the basal ganglia “train” the PFC. Category learning may depend on the formation of functional circuits between the PFC and STR. PMID:24930701
-
Ashby, F. Gregory; Maddox, W. Todd
2010-01-01
During the 1990’s and early 2000’s, cognitive neuroscience investigations of human category learning focused on the primary goal of showing that humans have multiple category learning systems and on the secondary goals of identifying key qualitative properties of each system and of roughly mapping out the neural networks that mediate each system. Many researchers now accept the strength of the evidence supporting multiple systems, and as a result, during the past few years, work has begun on the second generation of research questions – that is, on questions that begin with the assumption that humans have multiple category learning systems. This article reviews much of this second generation of research. Topics covered include: 1) How do the various systems interact? 2) Are there different neural systems for categorization and category representation? 3) How does automaticity develop in each system?, and 4) Exactly how does each system learn? PMID:21182535
-
Ashby, F Gregory; Maddox, W Todd
2011-04-01
During the 1990s and early 2000s, cognitive neuroscience investigations of human category learning focused on the primary goal of showing that humans have multiple category-learning systems and on the secondary goals of identifying key qualitative properties of each system and of roughly mapping out the neural networks that mediate each system. Many researchers now accept the strength of the evidence supporting multiple systems, and as a result, during the past few years, work has begun on the second generation of research questions-that is, on questions that begin with the assumption that humans have multiple category-learning systems. This article reviews much of this second generation of research. Topics covered include (1) How do the various systems interact? (2) Are there different neural systems for categorization and category representation? (3) How does automaticity develop in each system? and (4) Exactly how does each system learn? © 2010 New York Academy of Sciences.
-
Williams, Julia; O'Connor, Mórna; Windle, Richard; Wharrad, Heather J
2015-12-01
Clinical skills are a critical component of pre-registration nurse education in the United Kingdom, yet there is widespread concern about the clinical skills displayed by newly-qualified nurses. Novel means of supporting clinical skills education are required to address this. A package of Reusable Learning Objects (RLOs) was developed to supplement pre-registration teaching on the clinical skill of administering injection medication. RLOs are electronic resources addressing a single learning objective whose interactivity facilitates learning. This article evaluates a package of five injection RLOs across three studies: (1) questionnaires administered to pre-registration nursing students at University of Nottingham (UoN) (n=46) evaluating the RLO package as a whole; (2) individual RLOs evaluated in online questionnaires by educators and students from UoN; from other national and international institutions; and healthcare professionals (n=265); (3) qualitative evaluation of the RLO package by UoN injection skills tutors (n=6). Data from all studies were assessed for (1) access to, (2) usefulness, (3) impact and (4) integration of the RLOs. Study one found that pre-registration nursing students rate the RLO package highly across all categories, particularly underscoring the value of their self-test elements. Study two found high ratings in online assessments of individual RLOs by multiple users. The global reach is particularly encouraging here. Tutors reported insufficient levels of student-RLO access, which might be explained by the timing of their student exposure. Tutors integrate RLOs into teaching and agree on their use as teaching supplements, not substitutes for face-to-face education. This evaluation encompasses the first years postpackage release. Encouraging data on evaluative categories in this early review suggest that future evaluations are warranted to track progress as the package is adopted and evaluated more widely. Copyright © 2015 Elsevier Ltd. All rights reserved.
-
Generics license 30-month-olds’ inferences about the atypical properties of novel kinds
Graham, Susan A.; Gelman, Susan A.; Clarke, Jessica
2016-01-01
We examined whether the distinction between generic and nongeneric language provides toddlers with a rapid and efficient means to learn about kinds. In Experiment 1, we examined 30-month-olds’ willingness to extend atypical properties to members of an unfamiliar category when the properties were introduced in one of three ways: a) using a generic noun phrase (“Blicks drink ketchup”); b) using a nongeneric noun phrase (“These blicks drink ketchup”); and c) using an attentional phrase (“Look at this”). Hearing a generic noun phrase boosted toddlers’ extension of properties to both the model exemplars and to novel members of the same category, relative to when a property had been introduced with a nongeneric noun phrase or an attentional phrase. In Experiment 2, properties were introduced with a generic noun phrase and toddlers extended novel properties to members of the same-category, but not to an out-of-category object. Taken together, these findings demonstrate that generics highlight the stability of a feature and foster generalization of the property to novel within-category exemplars. PMID:27505699
-
Johnson, Heather A.; Barrett, Laura
2017-01-01
Objective The purpose of this study was to compare two pedagogical methods, active learning and passive instruction, to determine which is more useful in helping students to achieve the learning outcomes in a one-hour research skills instructional session. Methods Two groups of high school students attended an instructional session to learn about consumer health resources and strategies to enhance their searching skills. The first group received passive instruction, and the second engaged in active learning. We assessed both groups’ learning using 2 methods with differing complexity. A total of 59 students attended the instructional sessions (passive instruction, n=28; active learning, n=31). Results We found that the active learning group scored more favorably in four assessment categories. Conclusions Active learning may help students engage with and develop a meaningful understanding of several resources in a single session. Moreover, when using a complex teaching strategy, librarians should be mindful to gauge learning using an equally complex assessment method. PMID:28096745
-
Visual variability affects early verb learning.
Twomey, Katherine E; Lush, Lauren; Pearce, Ruth; Horst, Jessica S
2014-09-01
Research demonstrates that within-category visual variability facilitates noun learning; however, the effect of visual variability on verb learning is unknown. We habituated 24-month-old children to a novel verb paired with an animated star-shaped actor. Across multiple trials, children saw either a single action from an action category (identical actions condition, for example, travelling while repeatedly changing into a circle shape) or multiple actions from that action category (variable actions condition, for example, travelling while changing into a circle shape, then a square shape, then a triangle shape). Four test trials followed habituation. One paired the habituated verb with a new action from the habituated category (e.g., 'dacking' + pentagon shape) and one with a completely novel action (e.g., 'dacking' + leg movement). The others paired a new verb with a new same-category action (e.g., 'keefing' + pentagon shape), or a completely novel category action (e.g., 'keefing' + leg movement). Although all children discriminated novel verb/action pairs, children in the identical actions condition discriminated trials that included the completely novel verb, while children in the variable actions condition discriminated the out-of-category action. These data suggest that - as in noun learning - visual variability affects verb learning and children's ability to form action categories. © 2014 The British Psychological Society.
-
An Examination of Strategy Implementation During Abstract Nonlinguistic Category Learning in Aphasia
Kiran, Swathi
2015-01-01
Purpose Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Method Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases were calculated. To evaluate strategy use, strategy analyses were conducted over training and testing phases. Participant data were compared with model data that simulated complex multi-cue, single feature, and random pattern strategies. Learning success and strategy use were evaluated within the context of standardized cognitive–linguistic assessments. Results Categorization accuracy was higher among control participants than among PWA. The majority of control participants implemented suboptimal or optimal multi-cue and single-feature strategies by testing phases of the experiment. In contrast, a large subgroup of PWA implemented random patterns, or no strategy, during both training and testing phases of the experiment. Conclusions Person-to-person variability arises not only in category learning ability but also in the strategies implemented to complete category learning tasks. PWA less frequently developed effective strategies during category learning tasks than control participants. Certain PWA may have impairments of strategy development or feedback processing not captured by language and currently probed cognitive abilities. PMID:25908438
-
Effect of explicit dimension instruction on speech category learning
Chandrasekaran, Bharath; Yi, Han-Gyol; Smayda, Kirsten E.; Maddox, W. Todd
2015-01-01
Learning non-native speech categories is often considered a challenging task in adulthood. This difficulty is driven by cross-language differences in weighting critical auditory dimensions that differentiate speech categories. For example, previous studies have shown that differentiating Mandarin tonal categories requires attending to dimensions related to pitch height and direction. Relative to native speakers of Mandarin, the pitch direction dimension is under-weighted by native English speakers. In the current study, we examined the effect of explicit instructions (dimension instruction) on native English speakers' Mandarin tone category learning within the framework of a dual-learning systems (DLS) model. This model predicts that successful speech category learning is initially mediated by an explicit, reflective learning system that frequently utilizes unidimensional rules, with an eventual switch to a more implicit, reflexive learning system that utilizes multidimensional rules. Participants were explicitly instructed to focus and/or ignore the pitch height dimension, the pitch direction dimension, or were given no explicit prime. Our results show that instruction instructing participants to focus on pitch direction, and instruction diverting attention away from pitch height resulted in enhanced tone categorization. Computational modeling of participant responses suggested that instruction related to pitch direction led to faster and more frequent use of multidimensional reflexive strategies, and enhanced perceptual selectivity along the previously underweighted pitch direction dimension. PMID:26542400
-
ERIC Educational Resources Information Center
French, Robert M.; Mareschal, Denis; Mermillod, Martial; Quinn, Paul C.
2004-01-01
Disentangling bottom-up and top-down processing in adult category learning is notoriously difficult. Studying category learning in infancy provides a simple way of exploring category learning while minimizing the contribution of top-down information. Three- to 4-month-old infants presented with cat or dog images will form a perceptual category…
-
The Time Course of Explicit and Implicit Categorization
Zakrzewski, Alexandria C.; Herberger, Eric; Boomer, Joseph; Roeder, Jessica; Ashby, F. Gregory; Church, Barbara A.
2015-01-01
Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization. PMID:26025556
-
Adults' and Children's Understanding of How Expertise Influences Learning.
Danovitch, Judith H; Shenouda, Christine K
2018-01-01
Adults and children use information about expertise to infer what a person is likely to know, but it is unclear whether they realize that expertise also has implications for learning. We explore adults' and children's understanding that expertise in a particular category supports learning about a closely related category. In four experiments, 5-year-olds and adults (n = 160) judged which of two people would be better at learning about a new category. When faced with an expert and a nonexpert, adults consistently indicated that expertise supports learning in a closely related category; however, children's judgments were inconsistent and were strongly influenced by the description of the nonexpert. The results suggest that although children understand what it means to be an expert, they may judge an individual's learning capacity based on different considerations than adults.
-
Models as Relational Categories
NASA Astrophysics Data System (ADS)
Kokkonen, Tommi
2017-11-01
Model-based learning (MBL) has an established position within science education. It has been found to enhance conceptual understanding and provide a way for engaging students in authentic scientific activity. Despite ample research, few studies have examined the cognitive processes regarding learning scientific concepts within MBL. On the other hand, recent research within cognitive science has examined the learning of so-called relational categories. Relational categories are categories whose membership is determined on the basis of the common relational structure. In this theoretical paper, I argue that viewing models as relational categories provides a well-motivated cognitive basis for MBL. I discuss the different roles of models and modeling within MBL (using ready-made models, constructive modeling, and generative modeling) and discern the related cognitive aspects brought forward by the reinterpretation of models as relational categories. I will argue that relational knowledge is vital in learning novel models and in the transfer of learning. Moreover, relational knowledge underlies the coherent, hierarchical knowledge of experts. Lastly, I will examine how the format of external representations may affect the learning of models and the relevant relations. The nature of the learning mechanisms underlying students' mental representations of models is an interesting open question to be examined. Furthermore, the ways in which the expert-like knowledge develops and how to best support it is in need of more research. The discussion and conceptualization of models as relational categories allows discerning students' mental representations of models in terms of evolving relational structures in greater detail than previously done.
-
NASA Astrophysics Data System (ADS)
Andrini, V. S.
2018-05-01
The objectives of the research are to develop the learning video for the flipped classroom model for Open University’s student and to know the effectiveness of the video. The development of the video used Research and Development ADDIE design (Analyses, Design, Development, Implementation, Evaluation). The sampling used purposive sampling was 28 students in Open University of Nganjuk. The techniques of data collection were the observation data to know the problems of the students, and learning facilities, the test (pre-test and post-test) to know a knowledge aspect, a questionnaire to know advisability of video learning, a structured interview to confirm their answer. The result of the expert of matter and media showed that the average product score was 3.75 of 4 or very good, the small-scale test showed that the average score was 3.60 of 4 and the large-scale test showed that the average score was 3.80 of 4, it had a very good category. The t-test with paired sample test showed that sig. (2-tailed) < 0.05. The N-gain score of pre and post test was 0.55, it had the medium category. It can be concluded that the development of the learning video for flipped classroom was effective to be implemented.
-
ERIC Educational Resources Information Center
Tharp, Ian J.; Pickering, Alan D.
2009-01-01
DeCaro et al. [DeCaro, M. S., Thomas, R. D., & Beilock, S. L. (2008). "Individual differences in category learning: Sometimes less working memory capacity is better than more." "Cognition, 107"(1), 284-294] explored how individual differences in working memory capacity differentially mediate the learning of distinct category structures.…
-
Montoye, Alexander H K; Pivarnik, James M; Mudd, Lanay M; Biswas, Subir; Pfeiffer, Karin A
2016-01-01
Recent evidence suggests that physical activity (PA) and sedentary behavior (SB) exert independent effects on health. Therefore, measurement methods that can accurately assess both constructs are needed. To compare the accuracy of accelerometers placed on the hip, thigh, and wrists, coupled with machine learning models, for measurement of PA intensity category (SB, light-intensity PA [LPA], and moderate- to vigorous-intensity PA [MVPA]) and breaks in SB. Forty young adults (21 female; age 22.0 ± 4.2 years) participated in a 90-minute semi-structured protocol, performing 13 activities (three sedentary, 10 non-sedentary) for 3-10 minutes each. Participants chose activity order, duration, and intensity. Direct observation (DO) was used as a criterion measure of PA intensity category, and transitions from SB to a non-sedentary activity were breaks in SB. Participants wore four accelerometers (right hip, right thigh, and both wrists), and a machine learning model was created for each accelerometer to predict PA intensity category. Sensitivity and specificity for PA intensity category classification were calculated and compared across accelerometers using repeated measures analysis of variance, and the number of breaks in SB was compared using repeated measures analysis of variance. Sensitivity and specificity values for the thigh-worn accelerometer were higher than for wrist- or hip-worn accelerometers, > 99% for all PA intensity categories. Sensitivity and specificity for the hip-worn accelerometer were 87-95% and 93-97%. The left wrist-worn accelerometer had sensitivities and specificities of > 97% for SB and LPA and 91-95% for MVPA, whereas the right wrist-worn accelerometer had sensitivities and specificities of 93-99% for SB and LPA but 67-84% for MVPA. The thigh-worn accelerometer had high accuracy for breaks in SB; all other accelerometers overestimated breaks in SB. Coupled with machine learning modeling, the thigh-worn accelerometer should be considered when objectively assessing PA and SB.
-
Machine learning for real time remote detection
NASA Astrophysics Data System (ADS)
Labbé, Benjamin; Fournier, Jérôme; Henaff, Gilles; Bascle, Bénédicte; Canu, Stéphane
2010-10-01
Infrared systems are key to providing enhanced capability to military forces such as automatic control of threats and prevention from air, naval and ground attacks. Key requirements for such a system to produce operational benefits are real-time processing as well as high efficiency in terms of detection and false alarm rate. These are serious issues since the system must deal with a large number of objects and categories to be recognized (small vehicles, armored vehicles, planes, buildings, etc.). Statistical learning based algorithms are promising candidates to meet these requirements when using selected discriminant features and real-time implementation. This paper proposes a new decision architecture benefiting from recent advances in machine learning by using an effective method for level set estimation. While building decision function, the proposed approach performs variable selection based on a discriminative criterion. Moreover, the use of level set makes it possible to manage rejection of unknown or ambiguous objects thus preserving the false alarm rate. Experimental evidences reported on real world infrared images demonstrate the validity of our approach.
-
ERIC Educational Resources Information Center
Ohio State Univ., Columbus. National Center for Research in Vocational Education.
This fifth in a series of ten learning modules on school-community relations is designed to give secondary and postsecondary vocational teachers help in developing the skills needed to prepare news releases and articles for publication. The terminal objective for the module is to prepare news releases and articles concerning a vocational program…
-
Verb Learning in 14- and 18-Month-Old English-Learning Infants
ERIC Educational Resources Information Center
He, Angela Xiaoxue; Lidz, Jeffrey
2017-01-01
The present study investigates English-learning infants' early understanding of the link between the grammatical category "verb" and the conceptual category "event," and their ability to recruit morphosyntactic information online to learn novel verb meanings. We report two experiments using an infant-controlled…
-
Blanco, Nathaniel J; Saucedo, Celeste L; Gonzalez-Lima, F
2017-03-01
This is the first randomized, controlled study comparing the cognitive effects of transcranial laser stimulation on category learning tasks. Transcranial infrared laser stimulation is a new non-invasive form of brain stimulation that shows promise for wide-ranging experimental and neuropsychological applications. It involves using infrared laser to enhance cerebral oxygenation and energy metabolism through upregulation of the respiratory enzyme cytochrome oxidase, the primary infrared photon acceptor in cells. Previous research found that transcranial infrared laser stimulation aimed at the prefrontal cortex can improve sustained attention, short-term memory, and executive function. In this study, we directly investigated the influence of transcranial infrared laser stimulation on two neurobiologically dissociable systems of category learning: a prefrontal cortex mediated reflective system that learns categories using explicit rules, and a striatally mediated reflexive learning system that forms gradual stimulus-response associations. Participants (n=118) received either active infrared laser to the lateral prefrontal cortex or sham (placebo) stimulation, and then learned one of two category structures-a rule-based structure optimally learned by the reflective system, or an information-integration structure optimally learned by the reflexive system. We found that prefrontal rule-based learning was substantially improved following transcranial infrared laser stimulation as compared to placebo (treatment X block interaction: F(1, 298)=5.117, p=0.024), while information-integration learning did not show significant group differences (treatment X block interaction: F(1, 288)=1.633, p=0.202). These results highlight the exciting potential of transcranial infrared laser stimulation for cognitive enhancement and provide insight into the neurobiological underpinnings of category learning. Copyright © 2017 Elsevier Inc. All rights reserved.
-
Mercado, Eduardo; Church, Barbara A
2016-08-01
Children with autism spectrum disorder (ASD) sometimes have difficulties learning categories. Past computational work suggests that such deficits may result from atypical representations in cortical maps. Here we use neural networks to show that idiosyncratic transformations of inputs can result in the formation of feature maps that impair category learning for some inputs, but not for other closely related inputs. These simulations suggest that large inter- and intra-individual variations in learning capacities shown by children with ASD across similar categorization tasks may similarly result from idiosyncratic perceptual encoding that is resistant to experience-dependent changes. If so, then both feedback- and exposure-based category learning should lead to heterogeneous, stimulus-dependent deficits in children with ASD.
-
NASA Astrophysics Data System (ADS)
Kumar, David Devraj; Dunn, Jessica
2018-03-01
Analysis of self-reflections of undergraduate education students in a project involving web-supported counterintuitive science demonstrations is reported in this paper. Participating students (N = 19) taught science with counterintuitive demonstrations in local elementary school classrooms and used web-based resources accessed via wireless USB adapters. Student reflections to seven questions were analyzed qualitatively using four components of reflection (meeting objectives/perception of learning, dynamics of pedagogy, special needs accommodations, improving teaching) deriving 27 initial data categories and 12 emergent themes. Overall the undergraduates reported meeting objectives, engaging students in pedagogically relevant learning tasks including, providing accommodations to students with special needs, and gaining practice and insight to improve their own teaching. Additional research is needed to arrive at generalizable findings concerning teaching with web-supported counterintuitive science demonstrations in elementary classrooms.
-
The legacy of care as reflexive learning
García, Marta Rodríguez; Moya, Jose Luis Medina
2016-01-01
Abstract Objective: to analyze whether the tutor's use of reflexive strategies encourages the students to reflect. The goal is to discover what type of strategies can help to achieve this and how tutors and students behave in the practical context. Method: a qualitative and ethnographic focus was adopted. Twenty-seven students and 15 tutors from three health centers participated. The latter had received specific training on reflexive clinical tutoring. The analysis was developed through constant comparisons of the categories. Results: the results demonstrate that the tutors' use of reflexive strategies such as didactic questioning, didactic empathy and pedagogical silence contributes to encourage the students' reflection and significant learning. Conclusions: reflexive practice is key to tutors' training and students' learning. PMID:27305180
-
Deep Learning for Extreme Weather Detection
NASA Astrophysics Data System (ADS)
Prabhat, M.; Racah, E.; Biard, J.; Liu, Y.; Mudigonda, M.; Kashinath, K.; Beckham, C.; Maharaj, T.; Kahou, S.; Pal, C.; O'Brien, T. A.; Wehner, M. F.; Kunkel, K.; Collins, W. D.
2017-12-01
We will present our latest results from the application of Deep Learning methods for detecting, localizing and segmenting extreme weather patterns in climate data. We have successfully applied supervised convolutional architectures for the binary classification tasks of detecting tropical cyclones and atmospheric rivers in centered, cropped patches. We have subsequently extended our architecture to a semi-supervised formulation, which is capable of learning a unified representation of multiple weather patterns, predicting bounding boxes and object categories, and has the capability to detect novel patterns (w/ few, or no labels). We will briefly present our efforts in scaling the semi-supervised architecture to 9600 nodes of the Cori supercomputer, obtaining 15PF performance. Time permitting, we will highlight our efforts in pixel-level segmentation of weather patterns.
-
Field-Dependence/Independence and Active Learning of Verbal and Geometric Material.
ERIC Educational Resources Information Center
Reardon, Richard; And Others
1982-01-01
Field-dependent and independent subjects sorted geometric and verbal material according to category exemplars, forcing active learning, and then recalled the category locations. Field-independent individuals generally performed better on learning and memory tasks with a more active approach. Active versus passive learning styles are discussed.…
-
Associations between Chinese EFL Graduate Students' Beliefs and Language Learning Strategies
ERIC Educational Resources Information Center
Tang, Mailing; Tian, Jianrong
2015-01-01
This study, using Horwitz's Beliefs about Language Learning Inventory and Oxford's Strategy Inventory for Language Learning, investigated learners' beliefs about language learning and their choice of strategy categories among 546 graduate students in China. The correlation between learners' beliefs and their strategy categories use was examined.…
-
A Novel Clustering Method Curbing the Number of States in Reinforcement Learning
NASA Astrophysics Data System (ADS)
Kotani, Naoki; Nunobiki, Masayuki; Taniguchi, Kenji
We propose an efficient state-space construction method for a reinforcement learning. Our method controls the number of categories with improving the clustering method of Fuzzy ART which is an autonomous state-space construction method. The proposed method represents weight vector as the mean value of input vectors in order to curb the number of new categories and eliminates categories whose state values are low to curb the total number of categories. As the state value is updated, the size of category becomes small to learn policy strictly. We verified the effectiveness of the proposed method with simulations of a reaching problem for a two-link robot arm. We confirmed that the number of categories was reduced and the agent achieved the complex task quickly.
-
Redmond, Catherine; Davies, Carmel; Cornally, Deirdre; Adam, Ewa; Daly, Orla; Fegan, Marianne; O'Toole, Margaret
2018-01-01
Both nationally and internationally concerns have been expressed over the adequacy of preparation of undergraduate nurses for the clinical skill of wound care. This project describes the educational evaluation of a series of Reusable Learning Objects (RLOs) as a blended learning approach to facilitate undergraduate nursing students learning of wound care for competence development. Constructivism Learning Theory and Cognitive Theory of Multimedia Learning informed the design of the RLOs, promoting active learner approaches. Clinically based case studies and visual data from two large university teaching hospitals provided the authentic learning materials required. Interactive exercises and formative feedback were incorporated into the educational resource. Evaluation of student perceived learning gains in terms of knowledge, ability and attitudes were measured using a quantitative pre and posttest Wound Care Competency Outcomes Questionnaire. The RLO CETL Questionnaire was used to identify perceived learning enablers. Statistical and deductive thematic analyses inform the findings. Students (n=192) reported that their ability to meet the competency outcomes for wound care had increased significantly after engaging with the RLOs. Students rated the RLOs highly across all categories of perceived usefulness, impact, access and integration. These findings provide evidence that the use of RLOs for both knowledge-based and performance-based learning is effective. RLOs when designed using clinically real case scenarios reflect the true complexities of wound care and offer innovative interventions in nursing curricula. Copyright © 2017 Elsevier Ltd. All rights reserved.
-
Al-Kloub, Manal Ibrahim; Salameh, Taghreed Nayel; Froelicher, Erika Sivarajan
2014-03-01
This study evaluates students' learning experiences in a clinical pediatric nursing course adopting Problem Based Learning (PBL) and investigates how students' cultural background impacts on self directed learning. A mixed-methods approach combining quantitative and qualitative methods was utilized to answer the research objectives. An observational technique for the PBL teaching sessions was employed; and 226 third-year students were asked to complete PBL evaluation questionnaire. Fifty seven percent (n = 130) responses to the questionnaire were analyzed. Overall, students considered PBL to be moderately effective in their learning experience, with a mean of 3.64 (S.D = 1.18). Students qualitative responses fell within four thematic categories including: developing cognitive abilities, independent learning, motivation to learn, and group learning. Difficulties encountered by students were: it is time-consuming, it has unclear objectives, it is a stressful process, and it results in an increased workload. A small number of students indicated that PBL tutorials were boring and complained about lack of contribution from instructors and limited recourses. Learning is intertwined with culture; students' previous educational experiences, uncertainty, English language proficiency, computer resources, gender, and achievement were identified as the most important cultural issues that impact the learning process and outcomes. Successful implementation of PBL does not come easily; teachers should be alert to the issues of culture in designing curriculum. Copyright © 2013 Elsevier Ltd. All rights reserved.
-
Perceived Frequency of Peer-Assisted Learning in the Laboratory and Collegiate Clinical Settings
Henning, Jolene M.; Weidner, Thomas G.; Snyder, Melissa; Dudley, William N.
2012-01-01
Context: Peer-assisted learning (PAL) has been recommended as an educational strategy to improve students' skill acquisition and supplement the role of the clinical instructor (CI). How frequently students actually engage in PAL in different settings is unknown. Objective: To determine the perceived frequency of planned and unplanned PAL (peer modeling, peer feedback and assessment, peer mentoring) in different settings. Design: Cross-sectional study. Setting: Laboratory and collegiate clinical settings. Patients or Other Participants: A total of 933 students, 84 administrators, and 208 CIs representing 52 (15%) accredited athletic training education programs. Intervention(s): Three versions (student, CI, administrator) of the Athletic Training Peer Assisted Learning Survey (AT-PALS) were administered. Cronbach α values ranged from .80 to .90. Main Outcome Measure(s): Administrators' and CIs' perceived frequency of 3 PAL categories under 2 conditions (planned, unplanned) and in 2 settings (instructional laboratory, collegiate clinical). Self-reported frequency of students' engagement in 3 categories of PAL in 2 settings. Results: Administrators and CIs perceived that unplanned PAL (0.39 ± 0.22) occurred more frequently than planned PAL (0.29 ± 0.19) regardless of category or setting (F1,282 = 83.48, P < .001). They perceived that PAL occurred more frequently in the collegiate clinical (0.46 ± 0.22) than laboratory (0.21 ± 0.24) setting regardless of condition or category (F1,282 = 217.17, P < .001). Students reported engaging in PAL more frequently in the collegiate clinical (3.31 ± 0.56) than laboratory (3.26 ± 0.62) setting regardless of category (F1,860 = 13.40, P < .001). We found a main effect for category (F2,859 = 1318.02, P < .001), with students reporting they engaged in peer modeling (4.01 ± 0.60) more frequently than peer mentoring (2.99 ± 0.88) (P < .001) and peer assessment and feedback (2.86 ± 0.64) (P < .001). Conclusions: Participants perceived that students engage in unplanned PAL in the collegiate clinical setting with a stronger inclination toward engagement in peer modeling. Educators should develop planned PAL activities to capitalize on the inherent desire of the students to collaborate with their peers. PMID:22488288
-
Distributional Language Learning: Mechanisms and Models of ategory Formation.
Aslin, Richard N; Newport, Elissa L
2014-09-01
In the past 15 years, a substantial body of evidence has confirmed that a powerful distributional learning mechanism is present in infants, children, adults and (at least to some degree) in nonhuman animals as well. The present article briefly reviews this literature and then examines some of the fundamental questions that must be addressed for any distributional learning mechanism to operate effectively within the linguistic domain. In particular, how does a naive learner determine the number of categories that are present in a corpus of linguistic input and what distributional cues enable the learner to assign individual lexical items to those categories? Contrary to the hypothesis that distributional learning and category (or rule) learning are separate mechanisms, the present article argues that these two seemingly different processes---acquiring specific structure from linguistic input and generalizing beyond that input to novel exemplars---actually represent a single mechanism. Evidence in support of this single-mechanism hypothesis comes from a series of artificial grammar-learning studies that not only demonstrate that adults can learn grammatical categories from distributional information alone, but that the specific patterning of distributional information among attested utterances in the learning corpus enables adults to generalize to novel utterances or to restrict generalization when unattested utterances are consistently absent from the learning corpus. Finally, a computational model of distributional learning that accounts for the presence or absence of generalization is reviewed and the implications of this model for linguistic-category learning are summarized.
-
Early object labels: the case for a developmental lexical principles framework.
Golinkoff, R M; Mervis, C B; Hirsh-Pasek, K
1994-02-01
Universally, object names make up the largest proportion of any word type found in children's early lexicons. Here we present and critically evaluate a set of six lexical principles (some previously proposed and some new) for making object label learning a manageable task. Overall, the principles have the effect of reducing the amount of information that language-learning children must consider for what a new word might mean. These principles are constructed by children in a two-tiered developmental sequence, as a function of their sensitivity to linguistic input, contextual information, and social-interactional cues. Thus, the process of lexical acquisition changes as a result of the particular principles a given child has at his or her disposal. For children who have only the principles of the first tier (reference, extendibility, and object scope), word learning has a deliberate and laborious look. The principles of the second tier (categorical scope, novel name-nameless category' or N3C, and conventionality) enable the child to acquire many new labels rapidly. The present unified account is argued to have a number of advantages over treating such principles separately and non-developmentally. Further, the explicit recognition that the acquisition and operation of these principles is influenced by the child's interpretation of both linguistic and non-linguistic input is seen as an advance.
-
Auditory working memory predicts individual differences in absolute pitch learning.
Van Hedger, Stephen C; Heald, Shannon L M; Koch, Rachelle; Nusbaum, Howard C
2015-07-01
Absolute pitch (AP) is typically defined as the ability to label an isolated tone as a musical note in the absence of a reference tone. At first glance the acquisition of AP note categories seems like a perceptual learning task, since individuals must assign a category label to a stimulus based on a single perceptual dimension (pitch) while ignoring other perceptual dimensions (e.g., loudness, octave, instrument). AP, however, is rarely discussed in terms of domain-general perceptual learning mechanisms. This is because AP is typically assumed to depend on a critical period of development, in which early exposure to pitches and musical labels is thought to be necessary for the development of AP precluding the possibility of adult acquisition of AP. Despite this view of AP, several previous studies have found evidence that absolute pitch category learning is, to an extent, trainable in a post-critical period adult population, even if the performance typically achieved by this population is below the performance of a "true" AP possessor. The current studies attempt to understand the individual differences in learning to categorize notes using absolute pitch cues by testing a specific prediction regarding cognitive capacity related to categorization - to what extent does an individual's general auditory working memory capacity (WMC) predict the success of absolute pitch category acquisition. Since WMC has been shown to predict performance on a wide variety of other perceptual and category learning tasks, we predict that individuals with higher WMC should be better at learning absolute pitch note categories than individuals with lower WMC. Across two studies, we demonstrate that auditory WMC predicts the efficacy of learning absolute pitch note categories. These results suggest that a higher general auditory WMC might underlie the formation of absolute pitch categories for post-critical period adults. Implications for understanding the mechanisms that underlie the phenomenon of AP are also discussed. Copyright © 2015. Published by Elsevier B.V.
-
Sporrong, Sofia Kälvemark; Gustavsson, Maria; Lindblad, Åsa Kettis; Johansson, Markus; Ring, Lena
2011-01-01
Objective. To identify what pharmacy students learn during the 6-month advanced pharmacy practice experience (APPE) in Sweden. Methods. Semi-structured interviews were conducted with 18 pharmacy APPE students and 17 pharmacist preceptors and analyzed in a qualitative directed content analysis using a defined workplace learning typology for categories. Results. The Swedish APPE provides students with task performance skills for work at pharmacies and social and professional knowledge, such as teamwork, how to learn while in a work setting, self-evaluation, understanding of the pharmacist role, and decision making and problem solving skills. Many of these skills and knowledge are not accounted for in the curricula in Sweden. Using a workplace learning typology to identify learning outcomes, as in this study, could be useful for curricula development. Conclusions. Exploring the learning that takes place during the APPE in a pharmacy revealed a broad range of skills and knowledge that students acquire. PMID:22345716
-
Effect of between-category similarity on basic-level superiority in pigeons
Lazareva, Olga F.; Soto, Fabián A.; Wasserman, Edward A.
2010-01-01
Children categorize stimuli at the basic level faster than at the superordinate level. We hypothesized that between-category similarity may affect this basic-level superiority effect. Dissimilar categories may be easy to distinguish at the basic level but be difficult to group at the superordinate level, whereas similar categories may be easy to group at the superordinate level but be difficult to distinguish at the basic level. Consequently, similar basic-level categories may produce a superordinate-before-basic learning trend, whereas dissimilar basic-level categories may result in a basic-before-superordinate learning trend. We tested this hypothesis in pigeons by constructing superordinate-level categories out of basic-level categories with known similarity. In Experiment 1, we experimentally evaluated the between-category similarity of four basic-level photographic categories using multiple fixed interval-extinction training (Astley & Wasserman, 1992). We used the resultant similarity matrices in Experiment 2 to construct two superordinate-level categories from basic-level categories with high between-category similarity (cars and persons; chairs and flowers). We then trained pigeons to concurrently classify those photographs into either the proper basic-level category or the proper superordinate-level category. Under these conditions, the pigeons learned the superordinate-level discrimination faster than the basic-level discrimination, confirming our hypothesis that basic-level superiority is affected by between-category similarity. PMID:20600696
-
Tomasello, Rosario; Garagnani, Max; Wennekers, Thomas; Pulvermüller, Friedemann
2017-04-01
Neuroimaging and patient studies show that different areas of cortex respectively specialize for general and selective, or category-specific, semantic processing. Why are there both semantic hubs and category-specificity, and how come that they emerge in different cortical regions? Can the activation time-course of these areas be predicted and explained by brain-like network models? In this present work, we extend a neurocomputational model of human cortical function to simulate the time-course of cortical processes of understanding meaningful concrete words. The model implements frontal and temporal cortical areas for language, perception, and action along with their connectivity. It uses Hebbian learning to semantically ground words in aspects of their referential object- and action-related meaning. Compared with earlier proposals, the present model incorporates additional neuroanatomical links supported by connectivity studies and downscaled synaptic weights in order to control for functional between-area differences purely due to the number of in- or output links of an area. We show that learning of semantic relationships between words and the objects and actions these symbols are used to speak about, leads to the formation of distributed circuits, which all include neuronal material in connector hub areas bridging between sensory and motor cortical systems. Therefore, these connector hub areas acquire a role as semantic hubs. By differentially reaching into motor or visual areas, the cortical distributions of the emergent 'semantic circuits' reflect aspects of the represented symbols' meaning, thus explaining category-specificity. The improved connectivity structure of our model entails a degree of category-specificity even in the 'semantic hubs' of the model. The relative time-course of activation of these areas is typically fast and near-simultaneous, with semantic hubs central to the network structure activating before modality-preferential areas carrying semantic information. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
-
Lexical competition in young children’s word learning
Swingley, Daniel; Aslin, Richard N.
2008-01-01
In two experiments, 1.5 year olds were taught novel words whose sound patterns were phonologically similar to familiar words (novel neighbors) or were not (novel nonneighbors). Learning was tested using a picture fixation task. In both experiments, children learned the novel nonneighbors but not the novel neighbors. In addition, exposure to the novel neighbors impaired recognition performance on familiar neighbors. Finally, children did not spontaneously use phonological differences to infer that a novel word referred to a novel object. Thus, lexical competition—inhibitory interaction among words in speech comprehension—can prevent children from using their full phonological sensitivity in judging words as novel. These results suggest that word learning in young children, as in adults, relies not only on the discrimination and identification of phonetic categories, but also on evaluating the likelihood that an utterance conveys a new word. PMID:17054932
-
Non-linguistic learning in aphasia: Effects of training method and stimulus characteristics
Vallila-Rohter, Sofia; Kiran, Swathi
2013-01-01
Purpose The purpose of the current study was to explore non-linguistic learning ability in patients with aphasia, examining the impact of stimulus typicality and feedback on success with learning. Method Eighteen patients with aphasia and eight healthy controls participated in this study. All participants completed four computerized, non-linguistic category-learning tasks. We probed learning ability under two methods of instruction: feedback-based (FB) and paired-associate (PA). We also examined the impact of task complexity on learning ability, comparing two stimulus conditions: typical (Typ) and atypical (Atyp). Performance was compared between groups and across conditions. Results Results demonstrated that healthy controls were able to successfully learn categories under all conditions. For our patients with aphasia, two patterns of performance arose. One subgroup of patients was able to maintain learning across task manipulations and conditions. The other subgroup of patients demonstrated a sensitivity to task complexity, learning successfully only in the typical training conditions. Conclusions Results support the hypothesis that impairments of general learning are present in aphasia. Some patients demonstrated the ability to extract category information under complex training conditions, while others learned only under conditions that were simplified and emphasized salient category features. Overall, the typical training condition facilitated learning for all participants. Findings have implications for therapy, which are discussed. PMID:23695914
-
What's in a Name? Typicality and Relatedness Effects in Children
ERIC Educational Resources Information Center
Jerger, Susan; Damian, Markus F.
2005-01-01
We studied how category typicality and out-of-category relatedness affect speeded category verification (vote ''yes'' if pictured object is clothing) in typically developing 4- to 14-year-olds and adults. Stimuli were typical and atypical category objects (e.g., pants, glove) and related and unrelated out-of-category objects (e.g., necklace,…
-
Category vs. Object Knowledge in Category-Based Induction
ERIC Educational Resources Information Center
Murphy, Gregory L.; Ross, Brian H.
2010-01-01
In one form of category-based induction, people make predictions about unknown properties of objects. There is a tension between predictions made based on the object's specific features (e.g., objects above a certain size tend not to fly) and those made by reference to category-level knowledge (e.g., birds fly). Seven experiments with artificial…
-
The helpfulness of category labels in semi-supervised learning depends on category structure.
Vong, Wai Keen; Navarro, Daniel J; Perfors, Amy
2016-02-01
The study of semi-supervised category learning has generally focused on how additional unlabeled information with given labeled information might benefit category learning. The literature is also somewhat contradictory, sometimes appearing to show a benefit to unlabeled information and sometimes not. In this paper, we frame the problem differently, focusing on when labels might be helpful to a learner who has access to lots of unlabeled information. Using an unconstrained free-sorting categorization experiment, we show that labels are useful to participants only when the category structure is ambiguous and that people's responses are driven by the specific set of labels they see. We present an extension of Anderson's Rational Model of Categorization that captures this effect.
-
Similarity-Dissimilarity Competition in Disjunctive Classification Tasks
Mathy, Fabien; Haladjian, Harry H.; Laurent, Eric; Goldstone, Robert L.
2013-01-01
Typical disjunctive artificial classification tasks require participants to sort stimuli according to rules such as “x likes cars only when black and coupe OR white and SUV.” For categories like this, increasing the salience of the diagnostic dimensions has two simultaneous effects: increasing the distance between members of the same category and increasing the distance between members of opposite categories. Potentially, these two effects respectively hinder and facilitate classification learning, leading to competing predictions for learning. Increasing saliency may lead to members of the same category to be considered less similar, while the members of separate categories might be considered more dissimilar. This implies a similarity-dissimilarity competition between two basic classification processes. When focusing on sub-category similarity, one would expect more difficult classification when members of the same category become less similar (disregarding the increase of between-category dissimilarity); however, the between-category dissimilarity increase predicts a less difficult classification. Our categorization study suggests that participants rely more on using dissimilarities between opposite categories than finding similarities between sub-categories. We connect our results to rule- and exemplar-based classification models. The pattern of influences of within- and between-category similarities are challenging for simple single-process categorization systems based on rules or exemplars. Instead, our results suggest that either these processes should be integrated in a hybrid model, or that category learning operates by forming clusters within each category. PMID:23403979
-
Muntinga, M E; Krajenbrink, V Q E; Peerdeman, S M; Croiset, G; Verdonk, P
2016-08-01
Recent years have seen a rise in the efforts to implement diversity topics into medical education, using either a 'narrow' or a 'broad' definition of culture. These developments urge that outcomes of such efforts are systematically evaluated by mapping the curriculum for diversity-responsive content. This study was aimed at using an intersectionality-based approach to define diversity-related learning objectives and to evaluate how biomedical and sociocultural aspects of diversity were integrated into a medical curriculum in the Netherlands. We took a three-phase mixed methods approach. In phase one and two, we defined essential learning objectives based on qualitative interviews with school stakeholders and diversity literature. In phase three, we screened the written curriculum for diversity content (culture, sex/gender and class) and related the results to learning objectives defined in phase two. We identified learning objectives in three areas of education (medical knowledge and skills, patient-physician communication, and reflexivity). Most diversity content pertained to biomedical knowledge and skills. Limited attention was paid to sociocultural issues as determinants of health and healthcare use. Intersections of culture, sex/gender and class remained mostly unaddressed. The curriculum's diversity-responsiveness could be improved by an operationalization of diversity that goes beyond biomedical traits of assumed homogeneous social groups. Future efforts to take an intersectionality-based approach to curriculum evaluations should include categories of difference other than culture, sex/gender and class as separate, equally important patient identities or groups.
-
Developing physics learning media using 3D cartoon
NASA Astrophysics Data System (ADS)
Wati, M.; Hartini, S.; Hikmah, N.; Mahtari, S.
2018-03-01
This study focuses on developing physics learning media using 3D cartoon on the static fluid topic. The purpose of this study is to describe: (1) the validity of the learning media, (2) the practicality of the learning media, and (3) the effectiveness of the learning media. This study is a research and development using ADDIE model. The subject of the implementation of media used class XI Science of SMAN 1 Pulau Laut Timur. The data were obtained from the validation sheet of the learning media, questionnaire, and the test of learning outcomes. The results showed that: (1) the validity of the media category is valid, (2) the practicality of the media category is practice, and (3) the effectiveness of the media category is effective. It is concluded that the learning using 3D cartoon on the static fluid topic is eligible to use in learning.
-
ERIC Educational Resources Information Center
Gureckis, Todd M.; James, Thomas W.; Nosofsky, Robert M.
2011-01-01
Recent fMRI studies have found that distinct neural systems may mediate perceptual category learning under implicit and explicit learning conditions. In these previous studies, however, different stimulus-encoding processes may have been associated with implicit versus explicit learning. The present design was aimed at decoupling the influence of…
-
ERIC Educational Resources Information Center
Kalish, Michael L.; Newell, Ben R.; Dunn, John C.
2017-01-01
It is sometimes supposed that category learning involves competing explicit and procedural systems, with only the former reliant on working memory capacity (WMC). In 2 experiments participants were trained for 3 blocks on both filtering (often said to be learned explicitly) and condensation (often said to be learned procedurally) category…
-
ERIC Educational Resources Information Center
Carvalho, Paulo F.; Goldstone, Robert L.
2017-01-01
The sequence of study influences how we learn. Previous research has identified different sequences as potentially beneficial for learning in different contexts and with different materials. Here we investigate the mechanisms involved in inductive category learning that give rise to these sequencing effects. Across 3 experiments we show evidence…
-
Comparison Promotes Learning and Transfer of Relational Categories
ERIC Educational Resources Information Center
Kurtz, Kenneth J.; Boukrina, Olga; Gentner, Dedre
2013-01-01
We investigated the effect of co-presenting training items during supervised classification learning of novel relational categories. Strong evidence exists that comparison induces a structural alignment process that renders common relational structure more salient. We hypothesized that comparisons between exemplars would facilitate learning and…
-
Category Representation for Classification and Feature Inference
ERIC Educational Resources Information Center
Johansen, Mark K.; Kruschke, John K.
2005-01-01
This research's purpose was to contrast the representations resulting from learning of the same categories by either classifying instances or inferring instance features. Prior inference learning research, particularly T. Yamauchi and A. B. Markman (1998), has suggested that feature inference learning fosters prototype representation, whereas…
-
Comparison of k-means related clustering methods for nuclear medicine images segmentation
NASA Astrophysics Data System (ADS)
Borys, Damian; Bzowski, Pawel; Danch-Wierzchowska, Marta; Psiuk-Maksymowicz, Krzysztof
2017-03-01
In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.
-
High resolution satellite image indexing and retrieval using SURF features and bag of visual words
NASA Astrophysics Data System (ADS)
Bouteldja, Samia; Kourgli, Assia
2017-03-01
In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.
-
SUSTAIN: A Network Model of Category Learning
ERIC Educational Resources Information Center
Love, Bradley C.; Medin, Douglas L.; Gureckis, Todd M.
2004-01-01
SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN…
-
Identifying Strategy Use in Category Learning Tasks: A Case for More Diagnostic Data and Models
ERIC Educational Resources Information Center
Donkin, Chris; Newell, Ben R.; Kalish, Mike; Dunn, John C.; Nosofsky, Robert M.
2015-01-01
The strength of conclusions about the adoption of different categorization strategies--and their implications for theories about the cognitive and neural bases of category learning--depend heavily on the techniques for identifying strategy use. We examine performance in an often-used "information-integration" category structure and…
-
Sadeghi, Zahra
2016-09-01
In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.
-
Miles, Sarah J; Matsuki, Kazunaga; Minda, John Paul
2014-07-01
Category learning is often characterized as being supported by two separate learning systems. A verbal system learns rule-defined (RD) categories that can be described using a verbal rule and relies on executive functions (EFs) to learn via hypothesis testing. A nonverbal system learns non-rule-defined (NRD) categories that cannot be described by a verbal rule and uses automatic, procedural learning. The verbal system is dominant in that adults tend to use it during initial learning but may switch to the nonverbal system when the verbal system is unsuccessful. The nonverbal system has traditionally been thought to operate independently of EFs, but recent studies suggest that EFs may play a role in the nonverbal system-specifically, to facilitate the transition away from the verbal system. Accordingly, continuously interfering with EFs during the categorization process, so that EFs are never fully available to facilitate the transition, may be more detrimental to the nonverbal system than is temporary EF interference. Participants learned an NRD or an RD category while EFs were untaxed, taxed temporarily, or taxed continuously. When EFs were continuously taxed during NRD categorization, participants were less likely to use a nonverbal categorization strategy than when EFs were temporarily taxed, suggesting that when EFs were unavailable, the transition to the nonverbal system was hindered. For the verbal system, temporary and continuous interference had similar effects on categorization performance and on strategy use, illustrating that EFs play an important but different role in each of the category-learning systems.
-
Breadth versus volume: Neurology outpatient clinic cases in medical education.
Albert, Dara V; Blood, Angela D; Park, Yoon Soo; Brorson, James R; Lukas, Rimas V
2016-06-01
This study examined how volume in certain patient case types and breadth across patient case types in the outpatient clinic setting are related to Neurology Clerkship student performance. Case logs from the outpatient clinic experience of 486 students from The University of Chicago Pritzker School of Medicine, USA, participating in the 4week Neurology Clerkship from July 2008 to June 2013 were reviewed. A total of 12,381 patient encounters were logged and then classified into 13 diagnostic categories. How volume of cases within categories and the breadth of cases across categories relate to the National Board of Medical Examiners Clinical Subject Examination for Neurology and a Neurology Clerkship Objective Structured Clinical Examination was analyzed. Volume of cases was significantly correlated with the National Board of Medical Examiners Clinical Subject Examination for Neurology (r=.290, p<.001), the Objective Structured Clinical Examination physical examination (r=.236, p=.011), and the Objective Structured Clinical Examination patient note (r=.238, p=.010). Breadth of cases was significantly correlated with the National Board of Medical Examiners Clinical Subject Examination for Neurology (r=.231, p=.017), however was not significantly correlated with any component of the Objective Structured Clinical Examination. Volume of cases correlated with higher performance on measures of specialty knowledge and clinical skill. Fewer relationships emerged correlating breadth of cases and performance on the same measures. This study provides guidance to educators who must decide how much emphasis to place on volume versus breadth of cases in outpatient clinic learning experiences. Copyright © 2016 Elsevier Ltd. All rights reserved.
-
Distributional learning aids linguistic category formation in school-age children.
Hall, Jessica; Owen VAN Horne, Amanda; Farmer, Thomas
2018-05-01
The goal of this study was to determine if typically developing children could form grammatical categories from distributional information alone. Twenty-seven children aged six to nine listened to an artificial grammar which contained strategic gaps in its distribution. At test, we compared how children rated novel sentences that fit the grammar to sentences that were ungrammatical. Sentences could be distinguished only through the formation of categories of words with shared distributional properties. Children's ratings revealed that they could discriminate grammatical and ungrammatical sentences. These data lend support to the hypothesis that distributional learning is a potential mechanism for learning grammatical categories in a first language.
-
When Does Fading Enhance Perceptual Category Learning?
ERIC Educational Resources Information Center
Pashler, Harold; Mozer, Michael C.
2013-01-01
Training that uses exaggerated versions of a stimulus discrimination (fading) has sometimes been found to enhance category learning, mostly in studies involving animals and impaired populations. However, little is known about whether and when fading facilitates learning for typical individuals. This issue was explored in 7 experiments. In…
-
Chalmers, Iain; Atkinson, Patricia; Badenoch, Douglas; Oxman, Andrew D.; Austvoll-Dahlgren, Astrid; Nordheim, Lena; Krause, L. Kendall; Schwartz, Lisa M.; Woloshin, Steven; Burls, Amanda; Mosconi, Paola; Hoffmann, Tammy; Cusack, Leila; Albarqouni, Loai; Glasziou, Paul
2017-01-01
Background People are frequently confronted with untrustworthy claims about the effects of treatments. Uncritical acceptance of these claims can lead to poor, and sometimes dangerous, treatment decisions, and wasted time and money. Resources to help people learn to think critically about treatment claims are scarce, and they are widely scattered. Furthermore, very few learning-resources have been assessed to see if they improve knowledge and behavior. Objectives Our objectives were to develop the Critical thinking and Appraisal Resource Library (CARL). This library was to be in the form of a database containing learning resources for those who are responsible for encouraging critical thinking about treatment claims, and was to be made available online. We wished to include resources for groups we identified as ‘intermediaries’ of knowledge, i.e. teachers of schoolchildren, undergraduates and graduates, for example those teaching evidence-based medicine, or those communicating treatment claims to the public. In selecting resources, we wished to draw particular attention to those resources that had been formally evaluated, for example, by the creators of the resource or independent research groups. Methods CARL was populated with learning-resources identified from a variety of sources—two previously developed but unmaintained inventories; systematic reviews of learning-interventions; online and database searches; and recommendations by members of the project group and its advisors. The learning-resources in CARL were organised by ‘Key Concepts’ needed to judge the trustworthiness of treatment claims, and were made available online by the James Lind Initiative in Testing Treatments interactive (TTi) English (www.testingtreatments.org/category/learning-resources).TTi English also incorporated the database of Key Concepts and the Claim Evaluation Tools developed through the Informed Healthcare Choices (IHC) project (informedhealthchoices.org). Results We have created a database of resources called CARL, which currently contains over 500 open-access learning-resources in a variety of formats: text, audio, video, webpages, cartoons, and lesson materials. These are aimed primarily at ‘Intermediaries’, that is, ‘teachers’, ‘communicators’, ‘advisors’, ‘researchers’, as well as for independent ‘learners’. The resources included in CARL are currently accessible at www.testingtreatments.org/category/learning-resources Conclusions We hope that ready access to CARL will help to promote the critical thinking about treatment claims, needed to help improve healthcare choices. PMID:28738058
-
Do infant Japanese macaques ( Macaca fuscata) categorize objects without specific training?
Murai, Chizuko; Tomonaga, Masaki; Kamegai, Kimi; Terazawa, Naoko; Yamaguchi, Masami K
2004-01-01
In the present study, we examined whether infant Japanese macaques categorize objects without any training, using a similar technique also used with human infants (the paired-preference method). During the familiarization phase, subjects were presented twice with two pairs of different objects from one global-level category. During the test phase, they were presented twice with a pair consisting of a novel familiar-category object and a novel global-level category object. The subjects were tested with three global-level categories (animal, furniture, and vehicle). It was found that they showed significant novelty preferences as a whole, indicating that they processed similarities between familiarization objects and novel familiar-category objects. These results suggest that subjects responded distinctively to objects without training, indicating the possibility that infant macaques possess the capacity for categorization.
-
A Preliminary Analysis of the Theoretical Parameters of Organizaational Learning.
1995-09-01
PARAMETERS OF ORGANIZATIONAL LEARNING THESIS Presented to the Faculty of the Graduate School of Logistics and Acquisition Management of the Air...Organizational Learning Parameters in the Knowledge Acquisition Category 2~™ 2-3. Organizational Learning Parameters in the Information Distribution Category...Learning Refined Scale 4-94 4-145. Composition of Refined Scale 4 Knowledge Flow 4-95 4-146. Cronbach’s Alpha Statistics for the Complete Knowledge Flow
-
The Role of Age and Executive Function in Auditory Category Learning
Reetzke, Rachel; Maddox, W. Todd; Chandrasekaran, Bharath
2015-01-01
Auditory categorization is a natural and adaptive process that allows for the organization of high-dimensional, continuous acoustic information into discrete representations. Studies in the visual domain have identified a rule-based learning system that learns and reasons via a hypothesis-testing process that requires working memory and executive attention. The rule-based learning system in vision shows a protracted development, reflecting the influence of maturing prefrontal function on visual categorization. The aim of the current study is two-fold: (a) to examine the developmental trajectory of rule-based auditory category learning from childhood through adolescence, into early adulthood; and (b) to examine the extent to which individual differences in rule-based category learning relate to individual differences in executive function. Sixty participants with normal hearing, 20 children (age range, 7–12), 21 adolescents (age range, 13–19), and 19 young adults (age range, 20–23), learned to categorize novel dynamic ripple sounds using trial-by-trial feedback. The spectrotemporally modulated ripple sounds are considered the auditory equivalent of the well-studied Gabor patches in the visual domain. Results revealed that auditory categorization accuracy improved with age, with young adults outperforming children and adolescents. Computational modeling analyses indicated that the use of the task-optimal strategy (i.e. a conjunctive rule-based learning strategy) improved with age. Notably, individual differences in executive flexibility significantly predicted auditory category learning success. The current findings demonstrate a protracted development of rule-based auditory categorization. The results further suggest that executive flexibility coupled with perceptual processes play important roles in successful rule-based auditory category learning. PMID:26491987
-
Fera, Francesco; Passamonti, Luca; Herzallah, Mohammad M; Myers, Catherine E; Veltri, Pierangelo; Morganti, Giuseppina; Quattrone, Aldo; Gluck, Mark A
2014-07-01
To test a prediction of our previous computational model of cortico-hippocampal interaction (Gluck and Myers [1993, 2001]) for characterizing individual differences in category learning, we studied young healthy subjects using an fMRI-adapted category-learning task that has two phases, an initial phase in which associations are learned through trial-and-error feedback followed by a generalization phase in which previously learned rules can be applied to novel associations (Myers et al. [2003]). As expected by our model, we found a negative correlation between learning-related hippocampal responses and accuracy during transfer, demonstrating that hippocampal adaptation during learning is associated with better behavioral scores during transfer generalization. In addition, we found an inverse relationship between Blood Oxygenation Level Dependent (BOLD) activity in the striatum and that in the hippocampal formation and the orbitofrontal cortex during the initial learning phase. Conversely, activity in the dorsolateral prefrontal cortex, orbitofrontal cortex and parietal lobes dominated over that of the hippocampal formation during the generalization phase. These findings provide evidence in support of theories of the neural substrates of category learning which argue that the hippocampal region plays a critical role during learning for appropriately encoding and representing newly learned information so that that this learning can be successfully applied and generalized to subsequent novel task demands. Copyright © 2013 Wiley Periodicals, Inc.
-
Tracy, J I; Pinsk, M; Helverson, J; Urban, G; Dietz, T; Smith, D J
2001-08-01
The link between automatic and effortful processing and nonanalytic and analytic category learning was evaluated in a sample of 29 college undergraduates using declarative memory, semantic category search, and pseudoword categorization tasks. Automatic and effortful processing measures were hypothesized to be associated with nonanalytic and analytic categorization, respectively. Results suggested that contrary to prediction strong criterion-attribute (analytic) responding on the pseudoword categorization task was associated with strong automatic, implicit memory encoding of frequency-of-occurrence information. Data are discussed in terms of the possibility that criterion-attribute category knowledge, once established, may be expressed with few attentional resources. The data indicate that attention resource requirements, even for the same stimuli and task, vary depending on the category rule system utilized. Also, the automaticity emerging from familiarity with analytic category exemplars is very different from the automaticity arising from extensive practice on a semantic category search task. The data do not support any simple mapping of analytic and nonanalytic forms of category learning onto the automatic and effortful processing dichotomy and challenge simple models of brain asymmetries for such procedures. Copyright 2001 Academic Press.
-
Machine learning-based coreference resolution of concepts in clinical documents
Ware, Henry; Mullett, Charles J; El-Rawas, Oussama
2012-01-01
Objective Coreference resolution of concepts, although a very active area in the natural language processing community, has not yet been widely applied to clinical documents. Accordingly, the 2011 i2b2 competition focusing on this area is a timely and useful challenge. The objective of this research was to collate coreferent chains of concepts from a corpus of clinical documents. These concepts are in the categories of person, problems, treatments, and tests. Design A machine learning approach based on graphical models was employed to cluster coreferent concepts. Features selected were divided into domain independent and domain specific sets. Training was done with the i2b2 provided training set of 489 documents with 6949 chains. Testing was done on 322 documents. Results The learning engine, using the un-weighted average of three different measurement schemes, resulted in an F measure of 0.8423 where no domain specific features were included and 0.8483 where the feature set included both domain independent and domain specific features. Conclusion Our machine learning approach is a promising solution for recognizing coreferent concepts, which in turn is useful for practical applications such as the assembly of problem and medication lists from clinical documents. PMID:22582205
-
ERIC Educational Resources Information Center
Dunn, John C.; Newell, Ben R.; Kalish, Michael L.
2012-01-01
Evidence that learning rule-based (RB) and information-integration (II) category structures can be dissociated across different experimental variables has been used to support the view that such learning is supported by multiple learning systems. Across 4 experiments, we examined the effects of 2 variables, the delay between response and feedback…
-
Enhanced procedural learning of speech sound categories in a genetic variant of FOXP2.
Chandrasekaran, Bharath; Yi, Han-Gyol; Blanco, Nathaniel J; McGeary, John E; Maddox, W Todd
2015-05-20
A mutation of the forkhead box protein P2 (FOXP2) gene is associated with severe deficits in human speech and language acquisition. In rodents, the humanized form of FOXP2 promotes faster switching from declarative to procedural learning strategies when the two learning systems compete. Here, we examined a polymorphism of FOXP2 (rs6980093) in humans (214 adults; 111 females) for associations with non-native speech category learning success. Neurocomputational modeling results showed that individuals with the GG genotype shifted faster to procedural learning strategies, which are optimal for the task. These findings support an adaptive role for the FOXP2 gene in modulating the function of neural learning systems that have a direct bearing on human speech category learning. Copyright © 2015 the authors 0270-6474/15/357808-05$15.00/0.
-
Toward Medical Documentation That Enhances Situational Awareness Learning
Lenert, Leslie A.
2016-01-01
The purpose of writing medical notes in a computer system goes beyond documentation for medical-legal purposes or billing. The structure of documentation is a checklist that serves as a cognitive aid and a potential index to retrieve information for learning from the record. For the past 50 years, one of the primary organizing structures for physicians’ clinical documentation have been the SOAP note (Subjective, Objective, Assessment, Plan). The cognitive check list is well-suited to differential diagnosis but may not support detection of changes in systems and/or learning from cases. We describe an alternative cognitive checklist called the OODA Loop (Observe, Orient, Decide, Act. Through incorporation of projections of anticipated course events with and without treatment and by making “Decisions” an explicit category of documentation in the medical record in the context of a variable temporal cycle for observations, OODA may enhance opportunities to learn from clinical care. PMID:28269872
-
Prefrontal Contributions to Rule-Based and Information-Integration Category Learning
ERIC Educational Resources Information Center
Schnyer, David M.; Maddox, W. Todd; Ell, Shawn; Davis, Sarah; Pacheco, Jenni; Verfaellie, Mieke
2009-01-01
Previous research revealed that the basal ganglia play a critical role in category learning [Ell, S. W., Marchant, N. L., & Ivry, R. B. (2006). "Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks." "Neuropsychologia", 44(10), 1737-1751; Maddox, W. T. & Filoteo, J.…
-
Learning Problems and Classroom Instruction.
ERIC Educational Resources Information Center
Adelman, Howard S.
Defined are categories of learning disabilities (LD) that can be remediated in regular public school classes, and offered are remedial approaches. Stressed in four studies is the heterogeneity of LD problems. Suggested is grouping LD children into three categories: no disorder (problem is from the learning environment); minor disorder (problem is…
-
Statistical Learning of Phonetic Categories: Insights from a Computational Approach
ERIC Educational Resources Information Center
McMurray, Bob; Aslin, Richard N.; Toscano, Joseph C.
2009-01-01
Recent evidence (Maye, Werker & Gerken, 2002) suggests that statistical learning may be an important mechanism for the acquisition of phonetic categories in the infant's native language. We examined the sufficiency of this hypothesis and its implications for development by implementing a statistical learning mechanism in a computational model…
-
Lim, Sung-joo; Holt, Lori L
2011-01-01
Although speech categories are defined by multiple acoustic dimensions, some are perceptually weighted more than others and there are residual effects of native-language weightings in non-native speech perception. Recent research on nonlinguistic sound category learning suggests that the distribution characteristics of experienced sounds influence perceptual cue weights: Increasing variability across a dimension leads listeners to rely upon it less in subsequent category learning (Holt & Lotto, 2006). The present experiment investigated the implications of this among native Japanese learning English /r/-/l/ categories. Training was accomplished using a videogame paradigm that emphasizes associations among sound categories, visual information, and players' responses to videogame characters rather than overt categorization or explicit feedback. Subjects who played the game for 2.5h across 5 days exhibited improvements in /r/-/l/ perception on par with 2-4 weeks of explicit categorization training in previous research and exhibited a shift toward more native-like perceptual cue weights. Copyright © 2011 Cognitive Science Society, Inc.
-
Lim, Sung-joo; Holt, Lori L.
2011-01-01
Although speech categories are defined by multiple acoustic dimensions, some are perceptually-weighted more than others and there are residual effects of native-language weightings in non-native speech perception. Recent research on nonlinguistic sound category learning suggests that the distribution characteristics of experienced sounds influence perceptual cue weights: increasing variability across a dimension leads listeners to rely upon it less in subsequent category learning (Holt & Lotto, 2006). The present experiment investigated the implications of this among native Japanese learning English /r/-/l/ categories. Training was accomplished using a videogame paradigm that emphasizes associations among sound categories, visual information and players’ responses to videogame characters rather than overt categorization or explicit feedback. Subjects who played the game for 2.5 hours across 5 days exhibited improvements in /r/-/l/ perception on par with 2–4 weeks of explicit categorization training in previous research and exhibited a shift toward more native-like perceptual cue weights. PMID:21827533
-
Compensatory processing during rule-based category learning in older adults.
Bharani, Krishna L; Paller, Ken A; Reber, Paul J; Weintraub, Sandra; Yanar, Jorge; Morrison, Robert G
2016-01-01
Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex.
-
Compensatory Processing During Rule-Based Category Learning in Older Adults
Bharani, Krishna L.; Paller, Ken A.; Reber, Paul J.; Weintraub, Sandra; Yanar, Jorge; Morrison, Robert G.
2016-01-01
Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex. PMID:26422522
-
ERIC Educational Resources Information Center
Liu, Ran; Holt, Lori L.
2011-01-01
Native language experience plays a critical role in shaping speech categorization, but the exact mechanisms by which it does so are not well understood. Investigating category learning of nonspeech sounds with which listeners have no prior experience allows their experience to be systematically controlled in a way that is impossible to achieve by…
-
The Advantage of Mixing Examples in Inductive Learning: A Comparison of Three Hypotheses
ERIC Educational Resources Information Center
Guzman-Munoz, Francisco Javier
2017-01-01
Mixing examples of different categories (interleaving) has been shown to promote inductive learning as compared with presenting examples of the same category together (massing). In three studies, we tested whether the advantage of interleaving is exclusively due to the mixing of examples from different categories or to the temporal gap introduced…
-
Basic level category structure emerges gradually across human ventral visual cortex.
Iordan, Marius Cătălin; Greene, Michelle R; Beck, Diane M; Fei-Fei, Li
2015-07-01
Objects can be simultaneously categorized at multiple levels of specificity ranging from very broad ("natural object") to very distinct ("Mr. Woof"), with a mid-level of generality (basic level: "dog") often providing the most cognitively useful distinction between categories. It is unknown, however, how this hierarchical representation is achieved in the brain. Using multivoxel pattern analyses, we examined how well each taxonomic level (superordinate, basic, and subordinate) of real-world object categories is represented across occipitotemporal cortex. We found that, although in early visual cortex objects are best represented at the subordinate level (an effect mostly driven by low-level feature overlap between objects in the same category), this advantage diminishes compared to the basic level as we move up the visual hierarchy, disappearing in object-selective regions of occipitotemporal cortex. This pattern stems from a combined increase in within-category similarity (category cohesion) and between-category dissimilarity (category distinctiveness) of neural activity patterns at the basic level, relative to both subordinate and superordinate levels, suggesting that successive visual areas may be optimizing basic level representations.
-
The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex
Leibo, Joel Z.; Liao, Qianli; Anselmi, Fabio; Poggio, Tomaso
2015-01-01
Is visual cortex made up of general-purpose information processing machinery, or does it consist of a collection of specialized modules? If prior knowledge, acquired from learning a set of objects is only transferable to new objects that share properties with the old, then the recognition system’s optimal organization must be one containing specialized modules for different object classes. Our analysis starts from a premise we call the invariance hypothesis: that the computational goal of the ventral stream is to compute an invariant-to-transformations and discriminative signature for recognition. The key condition enabling approximate transfer of invariance without sacrificing discriminability turns out to be that the learned and novel objects transform similarly. This implies that the optimal recognition system must contain subsystems trained only with data from similarly-transforming objects and suggests a novel interpretation of domain-specific regions like the fusiform face area (FFA). Furthermore, we can define an index of transformation-compatibility, computable from videos, that can be combined with information about the statistics of natural vision to yield predictions for which object categories ought to have domain-specific regions in agreement with the available data. The result is a unifying account linking the large literature on view-based recognition with the wealth of experimental evidence concerning domain-specific regions. PMID:26496457
-
How may the basal ganglia contribute to auditory categorization and speech perception?
Lim, Sung-Joo; Fiez, Julie A.; Holt, Lori L.
2014-01-01
Listeners must accomplish two complementary perceptual feats in extracting a message from speech. They must discriminate linguistically-relevant acoustic variability and generalize across irrelevant variability. Said another way, they must categorize speech. Since the mapping of acoustic variability is language-specific, these categories must be learned from experience. Thus, understanding how, in general, the auditory system acquires and represents categories can inform us about the toolbox of mechanisms available to speech perception. This perspective invites consideration of findings from cognitive neuroscience literatures outside of the speech domain as a means of constraining models of speech perception. Although neurobiological models of speech perception have mainly focused on cerebral cortex, research outside the speech domain is consistent with the possibility of significant subcortical contributions in category learning. Here, we review the functional role of one such structure, the basal ganglia. We examine research from animal electrophysiology, human neuroimaging, and behavior to consider characteristics of basal ganglia processing that may be advantageous for speech category learning. We also present emerging evidence for a direct role for basal ganglia in learning auditory categories in a complex, naturalistic task intended to model the incidental manner in which speech categories are acquired. To conclude, we highlight new research questions that arise in incorporating the broader neuroscience research literature in modeling speech perception, and suggest how understanding contributions of the basal ganglia can inform attempts to optimize training protocols for learning non-native speech categories in adulthood. PMID:25136291
-
Incidental category learning and cognitive load in a multisensory environment across childhood.
Broadbent, H J; Osborne, T; Rea, M; Peng, A; Mareschal, D; Kirkham, N Z
2018-06-01
Multisensory information has been shown to facilitate learning (Bahrick & Lickliter, 2000; Broadbent, White, Mareschal, & Kirkham, 2017; Jordan & Baker, 2011; Shams & Seitz, 2008). However, although research has examined the modulating effect of unisensory and multisensory distractors on multisensory processing, the extent to which a concurrent unisensory or multisensory cognitive load task would interfere with or support multisensory learning remains unclear. This study examined the role of concurrent task modality on incidental category learning in 6- to 10-year-olds. Participants were engaged in a multisensory learning task while also performing either a unisensory (visual or auditory only) or multisensory (audiovisual) concurrent task (CT). We found that engaging in an auditory CT led to poorer performance on incidental category learning compared with an audiovisual or visual CT, across groups. In 6-year-olds, category test performance was at chance in the auditory-only CT condition, suggesting auditory concurrent tasks may interfere with learning in younger children, but the addition of visual information may serve to focus attention. These findings provide novel insight into the use of multisensory concurrent information on incidental learning. Implications for the deployment of multisensory learning tasks within education across development and developmental changes in modality dominance and ability to switch flexibly across modalities are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
-
General object recognition is specific: Evidence from novel and familiar objects.
Richler, Jennifer J; Wilmer, Jeremy B; Gauthier, Isabel
2017-09-01
In tests of object recognition, individual differences typically correlate modestly but nontrivially across familiar categories (e.g. cars, faces, shoes, birds, mushrooms). In theory, these correlations could reflect either global, non-specific mechanisms, such as general intelligence (IQ), or more specific mechanisms. Here, we introduce two separate methods for effectively capturing category-general performance variation, one that uses novel objects and one that uses familiar objects. In each case, we show that category-general performance variance is unrelated to IQ, thereby implicating more specific mechanisms. The first approach examines three newly developed novel object memory tests (NOMTs). We predicted that NOMTs would exhibit more shared, category-general variance than familiar object memory tests (FOMTs) because novel objects, unlike familiar objects, lack category-specific environmental influences (e.g. exposure to car magazines or botany classes). This prediction held, and remarkably, virtually none of the substantial shared variance among NOMTs was explained by IQ. Also, while NOMTs correlated nontrivially with two FOMTs (faces, cars), these correlations were smaller than among NOMTs and no larger than between the face and car tests themselves, suggesting that the category-general variance captured by NOMTs is specific not only relative to IQ, but also, to some degree, relative to both face and car recognition. The second approach averaged performance across multiple FOMTs, which we predicted would increase category-general variance by averaging out category-specific factors. This prediction held, and as with NOMTs, virtually none of the shared variance among FOMTs was explained by IQ. Overall, these results support the existence of object recognition mechanisms that, though category-general, are specific relative to IQ and substantially separable from face and car recognition. They also add sensitive, well-normed NOMTs to the tools available to study object recognition. Copyright © 2017 Elsevier B.V. All rights reserved.
-
Experience moderates overlap between object and face recognition, suggesting a common ability
Gauthier, Isabel; McGugin, Rankin W.; Richler, Jennifer J.; Herzmann, Grit; Speegle, Magen; Van Gulick, Ana E.
2014-01-01
Some research finds that face recognition is largely independent from the recognition of other objects; a specialized and innate ability to recognize faces could therefore have little or nothing to do with our ability to recognize objects. We propose a new framework in which recognition performance for any category is the product of domain-general ability and category-specific experience. In Experiment 1, we show that the overlap between face and object recognition depends on experience with objects. In 256 subjects we measured face recognition, object recognition for eight categories, and self-reported experience with these categories. Experience predicted neither face recognition nor object recognition but moderated their relationship: Face recognition performance is increasingly similar to object recognition performance with increasing object experience. If a subject has a lot of experience with objects and is found to perform poorly, they also prove to have a low ability with faces. In a follow-up survey, we explored the dimensions of experience with objects that may have contributed to self-reported experience in Experiment 1. Different dimensions of experience appear to be more salient for different categories, with general self-reports of expertise reflecting judgments of verbal knowledge about a category more than judgments of visual performance. The complexity of experience and current limitations in its measurement support the importance of aggregating across multiple categories. Our findings imply that both face and object recognition are supported by a common, domain-general ability expressed through experience with a category and best measured when accounting for experience. PMID:24993021
-
Experience moderates overlap between object and face recognition, suggesting a common ability.
Gauthier, Isabel; McGugin, Rankin W; Richler, Jennifer J; Herzmann, Grit; Speegle, Magen; Van Gulick, Ana E
2014-07-03
Some research finds that face recognition is largely independent from the recognition of other objects; a specialized and innate ability to recognize faces could therefore have little or nothing to do with our ability to recognize objects. We propose a new framework in which recognition performance for any category is the product of domain-general ability and category-specific experience. In Experiment 1, we show that the overlap between face and object recognition depends on experience with objects. In 256 subjects we measured face recognition, object recognition for eight categories, and self-reported experience with these categories. Experience predicted neither face recognition nor object recognition but moderated their relationship: Face recognition performance is increasingly similar to object recognition performance with increasing object experience. If a subject has a lot of experience with objects and is found to perform poorly, they also prove to have a low ability with faces. In a follow-up survey, we explored the dimensions of experience with objects that may have contributed to self-reported experience in Experiment 1. Different dimensions of experience appear to be more salient for different categories, with general self-reports of expertise reflecting judgments of verbal knowledge about a category more than judgments of visual performance. The complexity of experience and current limitations in its measurement support the importance of aggregating across multiple categories. Our findings imply that both face and object recognition are supported by a common, domain-general ability expressed through experience with a category and best measured when accounting for experience. © 2014 ARVO.
-
NASA Astrophysics Data System (ADS)
Du, Shihong; Zhang, Fangli; Zhang, Xiuyuan
2015-07-01
While most existing studies have focused on extracting geometric information on buildings, only a few have concentrated on semantic information. The lack of semantic information cannot satisfy many demands on resolving environmental and social issues. This study presents an approach to semantically classify buildings into much finer categories than those of existing studies by learning random forest (RF) classifier from a large number of imbalanced samples with high-dimensional features. First, a two-level segmentation mechanism combining GIS and VHR image produces single image objects at a large scale and intra-object components at a small scale. Second, a semi-supervised method chooses a large number of unbiased samples by considering the spatial proximity and intra-cluster similarity of buildings. Third, two important improvements in RF classifier are made: a voting-distribution ranked rule for reducing the influences of imbalanced samples on classification accuracy and a feature importance measurement for evaluating each feature's contribution to the recognition of each category. Fourth, the semantic classification of urban buildings is practically conducted in Beijing city, and the results demonstrate that the proposed approach is effective and accurate. The seven categories used in the study are finer than those in existing work and more helpful to studying many environmental and social problems.
-
Physical Experience Leads to Enhanced Object Perception in Parietal Cortex: Insights from Knot Tying
ERIC Educational Resources Information Center
Cross, Emily S.; Cohen, Nichola Rice; de C. Hamilton, Antonia F.; Ramsey, Richard; Wolford, George; Grafton, Scott T.
2012-01-01
What does it mean to "know" what an object is? Viewing objects from different categories (e.g., tools vs. animals) engages distinct brain regions, but it is unclear whether these differences reflect object categories themselves or the tendency to interact differently with objects from different categories (grasping tools, not animals). Here we…
-
The roles of perceptual and conceptual information in face recognition.
Schwartz, Linoy; Yovel, Galit
2016-11-01
The representation of familiar objects is comprised of perceptual information about their visual properties as well as the conceptual knowledge that we have about them. What is the relative contribution of perceptual and conceptual information to object recognition? Here, we examined this question by designing a face familiarization protocol during which participants were either exposed to rich perceptual information (viewing each face in different angles and illuminations) or with conceptual information (associating each face with a different name). Both conditions were compared with single-view faces presented with no labels. Recognition was tested on new images of the same identities to assess whether learning generated a view-invariant representation. Results showed better recognition of novel images of the learned identities following association of a face with a name label, but no enhancement following exposure to multiple face views. Whereas these findings may be consistent with the role of category learning in object recognition, face recognition was better for labeled faces only when faces were associated with person-related labels (name, occupation), but not with person-unrelated labels (object names or symbols). These findings suggest that association of meaningful conceptual information with an image shifts its representation from an image-based percept to a view-invariant concept. They further indicate that the role of conceptual information should be considered to account for the superior recognition that we have for familiar faces and objects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
-
Learning in and from brain-based devices.
Edelman, Gerald M
2007-11-16
Biologically based mobile devices have been constructed that differ from robots based on artificial intelligence. These brain-based devices (BBDs) contain simulated brains that autonomously categorize signals from the environment without a priori instruction. Two such BBDs, Darwin VII and Darwin X, are described here. Darwin VII recognizes objects and links categories to behavior through instrumental conditioning. Darwin X puts together the "what,"when," and "where" from cues in the environment into an episodic memory that allows it to find a desired target. Although these BBDs are designed to provide insights into how the brain works, their principles may find uses in building hybrid machines. These machines would combine the learning ability of BBDs with explicitly programmed control systems.
-
Schematic Influences on Category Learning and Recognition Memory
ERIC Educational Resources Information Center
Sakamoto, Yasuaki; Love, Bradley C.
2004-01-01
The results from 3 category learning experiments suggest that items are better remembered when they violate a salient knowledge structure such as a rule. The more salient the knowledge structure, the stronger the memory for deviant items. The effect of learning errors on subsequent recognition appears to be mediated through the imposed knowledge…
-
Categorical Structure among Shared Features in Networks of Early-Learned Nouns
ERIC Educational Resources Information Center
Hills, Thomas T.; Maouene, Mounir; Maouene, Josita; Sheya, Adam; Smith, Linda
2009-01-01
The shared features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the…
-
Comparison promotes learning and transfer of relational categories.
Kurtz, Kenneth J; Boukrina, Olga; Gentner, Dedre
2013-07-01
We investigated the effect of co-presenting training items during supervised classification learning of novel relational categories. Strong evidence exists that comparison induces a structural alignment process that renders common relational structure more salient. We hypothesized that comparisons between exemplars would facilitate learning and transfer of categories that cohere around a common relational property. The effect of comparison was investigated using learning trials that elicited a separate classification response for each item in presentation pairs that could be drawn from the same or different categories. This methodology ensures consideration of both items and invites comparison through an implicit same-different judgment inherent in making the two responses. In a test phase measuring learning and transfer, the comparison group significantly outperformed a control group receiving an equivalent training session of single-item classification learning. Comparison-based learners also outperformed the control group on a test of far transfer, that is, the ability to accurately classify items from a novel domain that was relationally alike, but surface-dissimilar, to the training materials. Theoretical and applied implications of this comparison advantage are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.
-
Mental Health Risk Adjustment with Clinical Categories and Machine Learning.
Shrestha, Akritee; Bergquist, Savannah; Montz, Ellen; Rose, Sherri
2017-12-15
To propose nonparametric ensemble machine learning for mental health and substance use disorders (MHSUD) spending risk adjustment formulas, including considering Clinical Classification Software (CCS) categories as diagnostic covariates over the commonly used Hierarchical Condition Category (HCC) system. 2012-2013 Truven MarketScan database. We implement 21 algorithms to predict MHSUD spending, as well as a weighted combination of these algorithms called super learning. The algorithm collection included seven unique algorithms that were supplied with three differing sets of MHSUD-related predictors alongside demographic covariates: HCC, CCS, and HCC + CCS diagnostic variables. Performance was evaluated based on cross-validated R 2 and predictive ratios. Results show that super learning had the best performance based on both metrics. The top single algorithm was random forests, which improved on ordinary least squares regression by 10 percent with respect to relative efficiency. CCS categories-based formulas were generally more predictive of MHSUD spending compared to HCC-based formulas. Literature supports the potential benefit of implementing a separate MHSUD spending risk adjustment formula. Our results suggest there is an incentive to explore machine learning for MHSUD-specific risk adjustment, as well as considering CCS categories over HCCs. © Health Research and Educational Trust.
-
Adaptive categorization of ART networks in robot behavior learning using game-theoretic formulation.
Fung, Wai-keung; Liu, Yun-hui
2003-12-01
Adaptive Resonance Theory (ART) networks are employed in robot behavior learning. Two of the difficulties in online robot behavior learning, namely, (1) exponential memory increases with time, (2) difficulty for operators to specify learning tasks accuracy and control learning attention before learning. In order to remedy the aforementioned difficulties, an adaptive categorization mechanism is introduced in ART networks for perceptual and action patterns categorization in this paper. A game-theoretic formulation of adaptive categorization for ART networks is proposed for vigilance parameter adaptation for category size control on the categories formed. The proposed vigilance parameter update rule can help improving categorization performance in the aspect of category number stability and solve the problem of selecting initial vigilance parameter prior to pattern categorization in traditional ART networks. Behavior learning using physical robot is conducted to demonstrate the effectiveness of the proposed adaptive categorization mechanism in ART networks.
-
Unconscious symmetrical inferences: A role of consciousness in event integration.
Alonso, Diego; Fuentes, Luis J; Hommel, Bernhard
2006-06-01
Explicit and implicit learning have been attributed to different learning processes that create different types of knowledge structures. Consistent with that claim, our study provides evidence that people integrate stimulus events differently when consciously aware versus unaware of the relationship between the events. In a first, acquisition phase participants sorted words into two categories (A and B), which were fully predicted by task-irrelevant primes-the labels of two other, semantically unrelated categories (C and D). In a second, test phase participants performed a lexical decision task, in which all word stimuli stemmed from the previous prime categories (C and D) and the (now nonpredictive) primes were the labels of the previous target categories (A and B). Reliable priming effects in the second phase demonstrated that bidirectional associations between the respective categories had been formed in the acquisition phase (A<-->C and B<-->D), but these effects were found only in participants that were unaware of the relationship between the categories! We suggest that unconscious, implicit learning of event relationships results in the rather unsophisticated integration (i.e., bidirectional association) of the underlying event representations, whereas explicit learning takes the meaning of the order of the events into account, and thus creates unidirectional associations.
-
Pashaeypoor, Shahzad; Ashktorab, Tahereh; Rassouli, Maryam; Alavi Majd, Hamid
2017-10-01
Evidence based practice (EBP) education is essential in promoting of clinical care, but an effective educational strategy for teaching EBP in nursing faculties is not available. The aim of this study was to explore the experiences of nursing students of EBP Education according to Rogers' Diffusion of Innovation Model. This qualitative study was carried out using a directed content analysis method and purposeful sampling. Data were collected until saturation by fourteen semi-structured face-to-face individual interviews and two focus group discussions with nursing students from two nursing faculties in Tehran, Iran. Rogers' Model was used in this study. Data were classified into five themes and 11 categories according to the Rogers's Model. Themes and main categories were knowledge (educational enrichment, new strategy for education), persuasion (internalization of education, improvement of motivation), decision (acceptance, use in the future), implementation (objectivity, consolidation of learning) and confirmation (learning and teaching, achieving a goal, self-confidence). EBP Education, based on the teaching strategy of Rogers's Model, leads to an improved EBP learning. All the necessary steps for a better education of it are included in this educational approach which can be used to teach any new subject like EBP.
-
The role of feedback contingency in perceptual category learning.
Ashby, F Gregory; Vucovich, Lauren E
2016-11-01
Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how feedback contingency affects category learning, and current theories assign little or no importance to this variable. Two experiments examined the effects of contingency degradation on rule-based and information-integration category learning. In rule-based tasks, optimal accuracy is possible with a simple explicit rule, whereas optimal accuracy in information-integration tasks requires integrating information from 2 or more incommensurable perceptual dimensions. In both experiments, participants each learned rule-based or information-integration categories under either high or low levels of feedback contingency. The exact same stimuli were used in all 4 conditions, and optimal accuracy was identical in every condition. Learning was good in both high-contingency conditions, but most participants showed little or no evidence of learning in either low-contingency condition. Possible causes of these effects, as well as their theoretical implications, are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
-
The Role of Feedback Contingency in Perceptual Category Learning
Ashby, F. Gregory; Vucovich, Lauren E.
2016-01-01
Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how feedback contingency affects category learning, and current theories assign little or no importance to this variable. Two experiments examined the effects of contingency degradation on rule-based and information-integration category learning. In rule-based tasks, optimal accuracy is possible with a simple explicit rule, whereas optimal accuracy in information-integration tasks requires integrating information from two or more incommensurable perceptual dimensions. In both experiments, participants each learned rule-based or information-integration categories under either high or low levels of feedback contingency. The exact same stimuli were used in all four conditions and optimal accuracy was identical in every condition. Learning was good in both high-contingency conditions, but most participants showed little or no evidence of learning in either low-contingency condition. Possible causes of these effects are discussed, as well as their theoretical implications. PMID:27149393
-
The effectiveness of flipped classroom learning model in secondary physics classroom setting
NASA Astrophysics Data System (ADS)
Prasetyo, B. D.; Suprapto, N.; Pudyastomo, R. N.
2018-03-01
The research aimed to describe the effectiveness of flipped classroom learning model on secondary physics classroom setting during Fall semester of 2017. The research object was Secondary 3 Physics group of Singapore School Kelapa Gading. This research was initiated by giving a pre-test, followed by treatment setting of the flipped classroom learning model. By the end of the learning process, the pupils were given a post-test and questionnaire to figure out pupils' response to the flipped classroom learning model. Based on the data analysis, 89% of pupils had passed the minimum criteria of standardization. The increment level in the students' mark was analysed by normalized n-gain formula, obtaining a normalized n-gain score of 0.4 which fulfil medium category range. Obtains from the questionnaire distributed to the students that 93% of students become more motivated to study physics and 89% of students were very happy to carry on hands-on activity based on the flipped classroom learning model. Those three aspects were used to generate a conclusion that applying flipped classroom learning model in Secondary Physics Classroom setting is effectively applicable.
-
Baxter, Mark G; Gaffan, David; Kyriazis, Diana A; Mitchell, Anna S
2007-10-17
The orbital prefrontal cortex is thought to be involved in behavioral flexibility in primates, and human neuroimaging studies have identified orbital prefrontal activation during episodic memory encoding. The goal of the present study was to ascertain whether deficits in strategy implementation and episodic memory that occur after ablation of the entire prefrontal cortex can be ascribed to damage to the orbital prefrontal cortex. Rhesus monkeys were preoperatively trained on two behavioral tasks, the performance of both of which is severely impaired by the disconnection of frontal cortex from inferotemporal cortex. In the strategy implementation task, monkeys were required to learn about two categories of objects, each associated with a different strategy that had to be performed to obtain food reward. The different strategies had to be applied flexibly to optimize the rate of reward delivery. In the scene memory task, monkeys learned 20 new object-in-place discrimination problems in each session. Monkeys were tested on both tasks before and after bilateral ablation of orbital prefrontal cortex. These lesions impaired new scene learning but had no effect on strategy implementation. This finding supports a role for the orbital prefrontal cortex in memory but places limits on the involvement of orbital prefrontal cortex in the representation and implementation of behavioral goals and strategies.
-
Decoding human mental states by whole-head EEG+fNIRS during category fluency task performance
NASA Astrophysics Data System (ADS)
Omurtag, Ahmet; Aghajani, Haleh; Onur Keles, Hasan
2017-12-01
Objective. Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system’s ability to decode mental states and compare it with its unimodal components. Approach. We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. Main results. EEG+fNIRS’s decoding accuracy was greater than that of its subsystems, partly due to the new type of neurovascular features made available by hybrid data. Significance. Availability of an accurate and practical decoding method has potential implications for medical diagnosis, brain-computer interface design, and neuroergonomics.
-
Objects and categories: feature statistics and object processing in the ventral stream.
Tyler, Lorraine K; Chiu, Shannon; Zhuang, Jie; Randall, Billi; Devereux, Barry J; Wright, Paul; Clarke, Alex; Taylor, Kirsten I
2013-10-01
Recognizing an object involves more than just visual analyses; its meaning must also be decoded. Extensive research has shown that processing the visual properties of objects relies on a hierarchically organized stream in ventral occipitotemporal cortex, with increasingly more complex visual features being coded from posterior to anterior sites culminating in the perirhinal cortex (PRC) in the anteromedial temporal lobe (aMTL). The neurobiological principles of the conceptual analysis of objects remain more controversial. Much research has focused on two neural regions-the fusiform gyrus and aMTL, both of which show semantic category differences, but of different types. fMRI studies show category differentiation in the fusiform gyrus, based on clusters of semantically similar objects, whereas category-specific deficits, specifically for living things, are associated with damage to the aMTL. These category-specific deficits for living things have been attributed to problems in differentiating between highly similar objects, a process that involves the PRC. To determine whether the PRC and the fusiform gyri contribute to different aspects of an object's meaning, with differentiation between confusable objects in the PRC and categorization based on object similarity in the fusiform, we carried out an fMRI study of object processing based on a feature-based model that characterizes the degree of semantic similarity and difference between objects and object categories. Participants saw 388 objects for which feature statistic information was available and named the objects at the basic level while undergoing fMRI scanning. After controlling for the effects of visual information, we found that feature statistics that capture similarity between objects formed category clusters in fusiform gyri, such that objects with many shared features (typical of living things) were associated with activity in the lateral fusiform gyri whereas objects with fewer shared features (typical of nonliving things) were associated with activity in the medial fusiform gyri. Significantly, a feature statistic reflecting differentiation between highly similar objects, enabling object-specific representations, was associated with bilateral PRC activity. These results confirm that the statistical characteristics of conceptual object features are coded in the ventral stream, supporting a conceptual feature-based hierarchy, and integrating disparate findings of category responses in fusiform gyri and category deficits in aMTL into a unifying neurocognitive framework.
-
Category-based attentional guidance can operate in parallel for multiple target objects.
Jenkins, Michael; Grubert, Anna; Eimer, Martin
2018-05-01
The question whether the control of attention during visual search is always feature-based or can also be based on the category of objects remains unresolved. Here, we employed the N2pc component as an on-line marker for target selection processes to compare the efficiency of feature-based and category-based attentional guidance. Two successive displays containing pairs of real-world objects (line drawings of kitchen or clothing items) were separated by a 10 ms SOA. In Experiment 1, target objects were defined by their category. In Experiment 2, one specific visual object served as target (exemplar-based search). On different trials, targets appeared either in one or in both displays, and participants had to report the number of targets (one or two). Target N2pc components were larger and emerged earlier during exemplar-based search than during category-based search, demonstrating the superior efficiency of feature-based attentional guidance. On trials where target objects appeared in both displays, both targets elicited N2pc components that overlapped in time, suggesting that attention was allocated in parallel to these target objects. Critically, this was the case not only in the exemplar-based task, but also when targets were defined by their category. These results demonstrate that attention can be guided by object categories, and that this type of category-based attentional control can operate concurrently for multiple target objects. Copyright © 2018 Elsevier B.V. All rights reserved.
-
Interactions between statistical and semantic information in infant language development
Lany, Jill; Saffran, Jenny R.
2013-01-01
Infants can use statistical regularities to form rudimentary word categories (e.g. noun, verb), and to learn the meanings common to words from those categories. Using an artificial language methodology, we probed the mechanisms by which two types of statistical cues (distributional and phonological regularities) affect word learning. Because linking distributional cues vs. phonological information to semantics make different computational demands on learners, we also tested whether their use is related to language proficiency. We found that 22-month-old infants with smaller vocabularies generalized using phonological cues; however, infants with larger vocabularies showed the opposite pattern of results, generalizing based on distributional cues. These findings suggest that both phonological and distributional cues marking word categories promote early word learning. Moreover, while correlations between these cues are important to forming word categories, we found infants’ weighting of these cues in subsequent word-learning tasks changes over the course of early language development. PMID:21884336
-
Word Learning: Homophony and the Distribution of Learning Exemplars
ERIC Educational Resources Information Center
Dautriche, Isabelle; Chemla, Emmanuel; Christophe, Anne
2016-01-01
How do children infer the meaning of a word? Current accounts of word learning assume that children expect a word to map onto exactly one concept whose members form a coherent category. If this assumption was strictly true, children should infer that a homophone, such as "bat," refers to a single superordinate category that encompasses…
-
The Impact of Personality Traits on the Affective Category of English Language Learning Strategies
ERIC Educational Resources Information Center
Fazeli, Seyed Hossein
2011-01-01
The present study aims at discovering the impact of personality traits in the prediction use of the Affective English Language Learning Strategies (AELLSs) for learners of English as a foreign language. Four instruments were used, which were Adapted Inventory for Affective English Language Learning Strategies based on Affective category of…
-
Wang, Changming; Xiong, Shi; Hu, Xiaoping; Yao, Li; Zhang, Jiacai
2012-10-01
Categorization of images containing visual objects can be successfully recognized using single-trial electroencephalograph (EEG) measured when subjects view images. Previous studies have shown that task-related information contained in event-related potential (ERP) components could discriminate two or three categories of object images. In this study, we investigated whether four categories of objects (human faces, buildings, cats and cars) could be mutually discriminated using single-trial EEG data. Here, the EEG waveforms acquired while subjects were viewing four categories of object images were segmented into several ERP components (P1, N1, P2a and P2b), and then Fisher linear discriminant analysis (Fisher-LDA) was used to classify EEG features extracted from ERP components. Firstly, we compared the classification results using features from single ERP components, and identified that the N1 component achieved the highest classification accuracies. Secondly, we discriminated four categories of objects using combining features from multiple ERP components, and showed that combination of ERP components improved four-category classification accuracies by utilizing the complementarity of discriminative information in ERP components. These findings confirmed that four categories of object images could be discriminated with single-trial EEG and could direct us to select effective EEG features for classifying visual objects.
-
Category Learning Strategies in Younger and Older Adults: Rule Abstraction and Memorization
Wahlheim, Christopher N.; McDaniel, Mark A.; Little, Jeri L.
2016-01-01
Despite the fundamental role of category learning in cognition, few studies have examined how this ability differs between younger and older adults. The present experiment examined possible age differences in category learning strategies and their effects on learning. Participants were trained on a category determined by a disjunctive rule applied to relational features. The utilization of rule- and exemplar-based strategies was indexed by self-reports and transfer performance. Based on self-reported strategies, both age groups had comparable frequencies of rule- and exemplar-based learners, but older adults had a higher frequency of intermediate learners (i.e., learners not identifying with a reliance on either rule- or exemplar-based strategies). Training performance was higher for younger than older adults regardless of the strategy utilized, showing that older adults were impaired in their ability to learn the correct rule or to remember exemplar-label associations. Transfer performance converged with strategy reports in showing higher fidelity category representations for younger adults. Younger adults with high working memory capacity were more likely to use an exemplar-based strategy, and older adults with high working memory capacity showed better training performance. Age groups did not differ in their self-reported memory beliefs, and these beliefs did not predict training strategies or performance. Overall, the present results contradict earlier findings that older adults prefer rule- to exemplar-based learning strategies, presumably to compensate for memory deficits. PMID:26950225
-
Attribute-based classification for zero-shot visual object categorization.
Lampert, Christoph H; Nickisch, Hannes; Harmeling, Stefan
2014-03-01
We study the problem of object recognition for categories for which we have no training examples, a task also called zero--data or zero-shot learning. This situation has hardly been studied in computer vision research, even though it occurs frequently; the world contains tens of thousands of different object classes, and image collections have been formed and suitably annotated for only a few of them. To tackle the problem, we introduce attribute-based classification: Objects are identified based on a high-level description that is phrased in terms of semantic attributes, such as the object's color or shape. Because the identification of each such property transcends the specific learning task at hand, the attribute classifiers can be prelearned independently, for example, from existing image data sets unrelated to the current task. Afterward, new classes can be detected based on their attribute representation, without the need for a new training phase. In this paper, we also introduce a new data set, Animals with Attributes, of over 30,000 images of 50 animal classes, annotated with 85 semantic attributes. Extensive experiments on this and two more data sets show that attribute-based classification indeed is able to categorize images without access to any training images of the target classes.
-
van de Steeg, Lotte; IJkema, Roelie; Wagner, Cordula; Langelaan, Maaike
2015-02-05
Delirium is a common condition in hospitalized patients, associated with adverse outcomes such as longer hospital stay, functional decline and higher mortality, as well as higher rates of nursing home placement. Nurses often fail to recognize delirium in hospitalized patients, which might be due to a lack of knowledge of delirium diagnosis and treatment. The objective of the study was to test the effectiveness of an e-learning course on nurses' delirium knowledge, describe nursing staff's baseline knowledge about delirium, and describe demographic factors associated with baseline delirium knowledge and the effectiveness of the e-learning course. A before-and-after study design, using an e-learning course on delirium. The course was introduced to all nursing staff of internal medicine and surgical wards of 17 Dutch hospitals. 1,196 invitations for the e-learning course were sent to nursing staff, which included nurses, nursing students and healthcare assistants. Test scores on the final knowledge test (mean 87.4, 95% CI 86.7 to 88.2) were significantly higher than those on baseline (mean 79.3, 95% CI 78.5 to 80.1). At baseline, nursing staff had the most difficulty with questions related to the definition of delirium: what are its symptoms, course, consequences and which patients are at risk. The mean score for this category was 74.3 (95% CI 73.1 to 75.5). The e-learning course significantly improved nursing staff's knowledge of delirium in all subgroups of participants and for all question categories. Contrary to other studies, the baseline knowledge assessment showed that, overall, nursing staff was relatively knowledgeable regarding delirium. The Netherlands National Trial Register (NTR). NTR 2885 , 19 April 2011.
-
Machine-Learning Algorithms to Code Public Health Spending Accounts.
Brady, Eoghan S; Leider, Jonathon P; Resnick, Beth A; Alfonso, Y Natalia; Bishai, David
Government public health expenditure data sets require time- and labor-intensive manipulation to summarize results that public health policy makers can use. Our objective was to compare the performances of machine-learning algorithms with manual classification of public health expenditures to determine if machines could provide a faster, cheaper alternative to manual classification. We used machine-learning algorithms to replicate the process of manually classifying state public health expenditures, using the standardized public health spending categories from the Foundational Public Health Services model and a large data set from the US Census Bureau. We obtained a data set of 1.9 million individual expenditure items from 2000 to 2013. We collapsed these data into 147 280 summary expenditure records, and we followed a standardized method of manually classifying each expenditure record as public health, maybe public health, or not public health. We then trained 9 machine-learning algorithms to replicate the manual process. We calculated recall, precision, and coverage rates to measure the performance of individual and ensembled algorithms. Compared with manual classification, the machine-learning random forests algorithm produced 84% recall and 91% precision. With algorithm ensembling, we achieved our target criterion of 90% recall by using a consensus ensemble of ≥6 algorithms while still retaining 93% coverage, leaving only 7% of the summary expenditure records unclassified. Machine learning can be a time- and cost-saving tool for estimating public health spending in the United States. It can be used with standardized public health spending categories based on the Foundational Public Health Services model to help parse public health expenditure information from other types of health-related spending, provide data that are more comparable across public health organizations, and evaluate the impact of evidence-based public health resource allocation.
-
Higher order thinking skills: using e-portfolio in project-based learning
NASA Astrophysics Data System (ADS)
Lukitasari, M.; Handhika, J.; Murtafiah, W.
2018-03-01
The purpose of this research is to describe students' higher-order thinking skills through project-based learning using e-portfolio. The method used in this research is descriptive qualitative method. The research instruments used were test, unstructured interview, and documentation. Research subjects were students of mathematics, physics and biology education department who take the Basics Physics course. The result shows that through project-based learning using e-portfolio the students’ ability to: analyze (medium category, N-Gain 0.67), evaluate (medium category, N-Gain 0.51), and create (medium Category, N-Gain 0.44) are improved.
-
From Statistics to Meaning: Infants’ Acquisition of Lexical Categories
Lany, Jill; Saffran, Jenny R.
2013-01-01
Infants are highly sensitive to statistical patterns in their auditory language input that mark word categories (e.g., noun and verb). However, it is unknown whether experience with these cues facilitates the acquisition of semantic properties of word categories. In a study testing this hypothesis, infants first listened to an artificial language in which word categories were reliably distinguished by statistical cues (experimental group) or in which these properties did not cue category membership (control group). Both groups were then trained on identical pairings between the words and pictures from two categories (animals and vehicles). Only infants in the experimental group learned the trained associations between specific words and pictures. Moreover, these infants generalized the pattern to include novel pairings. These results suggest that experience with statistical cues marking lexical categories sets the stage for learning the meanings of individual words and for generalizing meanings to new category members. PMID:20424058
-
Category-Specificity in Visual Object Recognition
ERIC Educational Resources Information Center
Gerlach, Christian
2009-01-01
Are all categories of objects recognized in the same manner visually? Evidence from neuropsychology suggests they are not: some brain damaged patients are more impaired in recognizing natural objects than artefacts whereas others show the opposite impairment. Category-effects have also been demonstrated in neurologically intact subjects, but the…
-
Pitch enhancement facilitates word learning across visual contexts
Filippi, Piera; Gingras, Bruno; Fitch, W. Tecumseh
2014-01-01
This study investigates word-learning using a new experimental paradigm that integrates three processes: (a) extracting a word out of a continuous sound sequence, (b) inferring its referential meanings in context, (c) mapping the segmented word onto its broader intended referent, such as other objects of the same semantic category, and to novel utterances. Previous work has examined the role of statistical learning and/or of prosody in each of these processes separately. Here, we combine these strands of investigation into a single experimental approach, in which participants viewed a photograph belonging to one of three semantic categories while hearing a complex, five-word utterance containing a target word. Six between-subjects conditions were tested with 20 adult participants each. In condition 1, the only cue to word-meaning mapping was the co-occurrence of word and referents. This statistical cue was present in all conditions. In condition 2, the target word was sounded at a higher pitch. In condition 3, random words were sounded at a higher pitch, creating an inconsistent cue. In condition 4, the duration of the target word was lengthened. In conditions 5 and 6, an extraneous acoustic cue and a visual cue were associated with the target word, respectively. Performance in this word-learning task was significantly higher than that observed with simple co-occurrence only when pitch prominence consistently marked the target word. We discuss implications for the pragmatic value of pitch marking as well as the relevance of our findings to language acquisition and language evolution. PMID:25566144
-
What Counts as Knowledge: Learning to Use Categories in Computer Environments
ERIC Educational Resources Information Center
Ludvigsen, Sten R.
2012-01-01
In this article, I develop a perspective on learning as multilayered phenomena. I take a socio-genetic approach in order to understand human activity and to show how categories are a fundamental part of learning in a specific type of institutional practice. In the empirical section, student dialogue is analysed in relation to a set of categories…
-
ERIC Educational Resources Information Center
Daniel, Reka; Wagner, Gerd; Koch, Kathrin; Reichenbach, Jurgen R.; Sauer, Heinrich; Schlosser, Ralf G. M.
2011-01-01
The formation of new perceptual categories involves learning to extract that information from a wide range of often noisy sensory inputs, which is critical for selecting between a limited number of responses. To identify brain regions involved in visual classification learning under noisy conditions, we developed a task on the basis of the…
-
ERIC Educational Resources Information Center
Langguth, Berthold; Juttner, Martin; Landis, Theodor; Regard, Marianne; Rentschler, Ingo
2009-01-01
Hemispheric differences in the learning and generalization of pattern categories were explored in two experiments involving sixteen patients with unilateral posterior, cerebral lesions in the left (LH) or right (RH) hemisphere. In each experiment participants were first trained to criterion in a supervised learning paradigm to categorize a set of…
-
What do medical residents learn on a rural Japanese island?
Ohta, Ryuichi; Son, Daisuke
2018-01-01
Objective: Community-based medical education (CBME) serves as a complement to university medical education, and it is practiced in several urban undergraduate and postgraduate curriculums. However, there are few reports on CBME learning content in rural Japanese settings. Materials and Methods: This research aimed to clarify learning content through semi-structured interviews and qualitative analysis of second-year residents who studied on a remote, rural island located 400 km from the mainland of Okinawa, Japan. Analysis was based on Steps for Coding and Theorization (SCAT). Results: Fifteen concepts were extracted, and four categories were generated: a strong connection among the islanders, the necessary abilities for rural physicians, islander-centered care, and the differences between rural and hospital medicine. In contrast to hospital medicine, various kinds of learning occurred in deep relationships with the islanders. Conclusion: Through CBME on a remote island, the residents learned not only about medical aspects, but also the importance of community health through the social and cultural aspects, whole-person medical care in a remote location, and the importance of reflection in their self-directed learning. PMID:29875892
-
Basal ganglia and Dopamine Contributions to Probabilistic Category Learning
Shohamy, D.; Myers, C.E.; Kalanithi, J.; Gluck, M.A.
2009-01-01
Studies of the medial temporal lobe and basal ganglia memory systems have recently been extended towards understanding the neural systems contributing to category learning. The basal ganglia, in particular, have been linked to probabilistic category learning in humans. A separate parallel literature in systems neuroscience has emerged, indicating a role for the basal ganglia and related dopamine inputs in reward prediction and feedback processing. Here, we review behavioral, neuropsychological, functional neuroimaging, and computational studies of basal ganglia and dopamine contributions to learning in humans. Collectively, these studies implicate the basal ganglia in incremental, feedback-based learning that involves integrating information across multiple experiences. The medial temporal lobes, by contrast, contribute to rapid encoding of relations between stimuli and support flexible generalization of learning to novel contexts and stimuli. By breaking down our understanding of the cognitive and neural mechanisms contributing to different aspects of learning, recent studies are providing insight into how, and when, these different processes support learning, how they may interact with each other, and the consequence of different forms of learning for the representation of knowledge. PMID:18061261
-
Decoding semantic information from human electrocorticographic (ECoG) signals.
Wang, Wei; Degenhart, Alan D; Sudre, Gustavo P; Pomerleau, Dean A; Tyler-Kabara, Elizabeth C
2011-01-01
This study examined the feasibility of decoding semantic information from human cortical activity. Four human subjects undergoing presurgical brain mapping and seizure foci localization participated in this study. Electrocorticographic (ECoG) signals were recorded while the subjects performed simple language tasks involving semantic information processing, such as a picture naming task where subjects named pictures of objects belonging to different semantic categories. Robust high-gamma band (60-120 Hz) activation was observed at the left inferior frontal gyrus (LIFG) and the posterior portion of the superior temporal gyrus (pSTG) with a temporal sequence corresponding to speech production and perception. Furthermore, Gaussian Naïve Bayes and Support Vector Machine classifiers, two commonly used machine learning algorithms for pattern recognition, were able to predict the semantic category of an object using cortical activity captured by ECoG electrodes covering the frontal, temporal and parietal cortices. These findings have implications for both basic neuroscience research and development of semantic-based brain-computer interface systems (BCI) that can help individuals with severe motor or communication disorders to express their intention and thoughts.
-
Lexical leverage: Category knowledge boosts real-time novel word recognition in two-year- olds
Borovsky, Arielle; Ellis, Erica M.; Evans, Julia L.; Elman, Jeffrey L.
2016-01-01
Recent research suggests that infants tend to add words to their vocabulary that are semantically related to other known words, though it is not clear why this pattern emerges. In this paper, we explore whether infants to leverage their existing vocabulary and semantic knowledge when interpreting novel label-object mappings in real-time. We initially identified categorical domains for which individual 24-month-old infants have relatively higher and lower levels of knowledge, irrespective of overall vocabulary size. Next, we taught infants novel words in these higher and lower knowledge domains and then asked if their subsequent real-time recognition of these items varied as a function of their category knowledge. While our participants successfully acquired the novel label -object mappings in our task, there were important differences in the way infants recognized these words in real time. Namely, infants showed more robust recognition of high (vs. low) domain knowledge words. These findings suggest that dense semantic structure facilitates early word learning and real-time novel word recognition. PMID:26452444
-
NASA Astrophysics Data System (ADS)
Mayasari, F.; Raharjo; Supardi, Z. A. I.
2018-01-01
This research aims to develop the material eligibility to complete the inquiry learning of student in the material organization system of junior high school students. Learning materials developed include syllabi, lesson plans, students’ textbook, worksheets, and learning achievement test. This research is the developmental research which employ Dick and Carey model to develop learning material. The experiment was done in Junior High School 4 Lamongan regency using One Group Pretest-Posttest Design. The data collection used validation, observation, achievement test, questionnaire administration, and documentation. Data analysis techniques used quantitative and qualitative descriptive.The results showed that the developed learning material was valid and can be used. Learning activity accomplished with good category, where student activities were observed. The aspects of attitudes were observed during the learning process are honest, responsible, and confident. Student learning achievement gained an average of 81, 85 in complete category, with N-Gain 0, 75 for a high category. The activities and student response to learning was very well categorized. Based on the results, this researcher concluded that the device classified as feasible of inquiry-based learning (valid, practical, and effective) system used on the material organization of junior high school students.
-
NASA Astrophysics Data System (ADS)
Shih, D.-T.; Lin, C. L.; Tseng, C.-Y.
2015-08-01
This paper presents an interdisciplinary to develop content-aware application that combines game with learning on specific categories of digital archives. The employment of content-oriented game enhances the gamification and efficacy of learning in culture education on architectures and history of Hsinchu County, Taiwan. The gamified form of the application is used as a backbone to support and provide a strong stimulation to engage users in learning art and culture, therefore this research is implementing under the goal of "The Digital ARt/ARchitecture Project". The purpose of the abovementioned project is to develop interactive serious game approaches and applications for Hsinchu County historical archives and architectures. Therefore, we present two applications, "3D AR for Hukou Old " and "Hsinchu County History Museum AR Tour" which are in form of augmented reality (AR). By using AR imaging techniques to blend real object and virtual content, the users can immerse in virtual exhibitions of Hukou Old Street and Hsinchu County History Museum, and to learn in ubiquitous computing environment. This paper proposes a content system that includes tools and materials used to create representations of digitized cultural archives including historical artifacts, documents, customs, religion, and architectures. The Digital ARt / ARchitecture Project is based on the concept of serious game and consists of three aspects: content creation, target management, and AR presentation. The project focuses on developing a proper approach to serve as an interactive game, and to offer a learning opportunity for appreciating historic architectures by playing AR cards. Furthermore, the card game aims to provide multi-faceted understanding and learning experience to help user learning through 3D objects, hyperlinked web data, and the manipulation of learning mode, and then effectively developing their learning levels on cultural and historical archives in Hsinchu County.
-
Behavioral demand modulates object category representation in the inferior temporal cortex
Emadi, Nazli
2014-01-01
Visual object categorization is a critical task in our daily life. Many studies have explored category representation in the inferior temporal (IT) cortex at the level of single neurons and population. However, it is not clear how behavioral demands modulate this category representation. Here, we recorded from the IT single neurons in monkeys performing two different tasks with identical visual stimuli: passive fixation and body/object categorization. We found that category selectivity of the IT neurons was improved in the categorization compared with the passive task where reward was not contingent on image category. The category improvement was the result of larger rate enhancement for the preferred category and smaller response variability for both preferred and nonpreferred categories. These specific modulations in the responses of IT category neurons enhanced signal-to-noise ratio of the neural responses to discriminate better between the preferred and nonpreferred categories. Our results provide new insight into the adaptable category representation in the IT cortex, which depends on behavioral demands. PMID:25080572
-
Category-based guidance of spatial attention during visual search for feature conjunctions.
Nako, Rebecca; Grubert, Anna; Eimer, Martin
2016-10-01
The question whether alphanumerical category is involved in the control of attentional target selection during visual search remains a contentious issue. We tested whether category-based attentional mechanisms would guide the allocation of attention under conditions where targets were defined by a combination of alphanumerical category and a basic visual feature, and search displays could contain both targets and partially matching distractor objects. The N2pc component was used as an electrophysiological marker of attentional object selection in tasks where target objects were defined by a conjunction of color and category (Experiment 1) or shape and category (Experiment 2). Some search displays contained the target or a nontarget object that matched either the target color/shape or its category among 3 nonmatching distractors. In other displays, the target and a partially matching nontarget object appeared together. N2pc components were elicited not only by targets and by color- or shape-matching nontargets, but also by category-matching nontarget objects, even on trials where a target was present in the same display. On these trials, the summed N2pc components to the 2 types of partially matching nontargets were initially equal in size to the target N2pc, suggesting that attention was allocated simultaneously and independently to all objects with target-matching features during the early phase of attentional processing. Results demonstrate that alphanumerical category is a genuine guiding feature that can operate in parallel with color or shape information to control the deployment of attention during visual search. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
-
Dynamics of feature categorization.
Martí, Daniel; Rinzel, John
2013-01-01
In visual and auditory scenes, we are able to identify shared features among sensory objects and group them according to their similarity. This grouping is preattentive and fast and is thought of as an elementary form of categorization by which objects sharing similar features are clustered in some abstract perceptual space. It is unclear what neuronal mechanisms underlie this fast categorization. Here we propose a neuromechanistic model of fast feature categorization based on the framework of continuous attractor networks. The mechanism for category formation does not rely on learning and is based on biologically plausible assumptions, for example, the existence of populations of neurons tuned to feature values, feature-specific interactions, and subthreshold-evoked responses upon the presentation of single objects. When the network is presented with a sequence of stimuli characterized by some feature, the network sums the evoked responses and provides a running estimate of the distribution of features in the input stream. If the distribution of features is structured into different components or peaks (i.e., is multimodal), recurrent excitation amplifies the response of activated neurons, and categories are singled out as emerging localized patterns of elevated neuronal activity (bumps), centered at the centroid of each cluster. The emergence of bump states through sequential, subthreshold activation and the dependence on input statistics is a novel application of attractor networks. We show that the extraction and representation of multiple categories are facilitated by the rich attractor structure of the network, which can sustain multiple stable activity patterns for a robust range of connectivity parameters compatible with cortical physiology.
-
Educational Objectives of International Medical Electives – a narrative literature review
Cherniak, William A.; Drain, Paul K.; Brewer, Timothy F.
2014-01-01
Purpose Most medical schools and residency programs offer international medical electives [IMEs], but there is little guidance on educational objectives for these rotations. We reviewed the literature to compile and categorize a comprehensive set of educational objectives for IMEs. Methods We conducted a narrative literature review with specified search criteria using SciVerse Scopus online, which includes Embase and Medline databases. From manuscripts that met inclusion criteria, we extracted data on educational objectives and sorted them into pre-elective, intra-elective, and post-elective categories. Results We identified and reviewed 255 articles, of which 11 (4%) manuscripts described 22 unique educational objectives. Among those, 5 (23%), 15 (68%), and 2 (9%) objectives were categorized in the pre-elective, intra-elective, and post-elective periods, respectively. Among pre-elective objectives, only cultural awareness was listed by more than two articles (3/11, 27%). Among intra-elective objectives, the most commonly defined objectives for students were enhancing clinical skills and understanding different health care systems (9/11, 82%). Learning to manage diseases rarely seen at home and increasing cultural awareness were described by nearly half (5/11, 46%) of all papers. Among post-elective objectives, reflecting on experiences through a written project was most common (9/11, 82%). Conclusions We identified 22 unique educational objectives for IMEs in the published literature, some of which were consistent. These consistencies can be used as a framework upon which institutions can build their own IME curriculums, ultimately helping to ensure that their students have a meaningful learning experience while abroad. PMID:24072105
-
Representations of abstract grammatical feature agreement in young children.
Melançon, Andréane; Shi, Rushen
2015-11-01
A fundamental question in language acquisition research is whether young children have abstract grammatical representations. We tested this question experimentally. French-learning 30-month-olds were first taught novel word-object pairs in the context of a gender-marked determiner (e.g., un MASC ravole 'a ravole'). Test trials presented the objects side-by-side while one of them was named in new phrases containing other determiners and an adjective (e.g., le MASC joli ravole MASC 'the pretty ravole'). The gender agreement between the new determiner and the non-adjacent noun was manipulated in different test trials (e.g., le MASC __ravole MASC; *la FEM __ravole MASC). We found that online comprehension of the named target was facilitated in gender-matched trials but impeded in gender-mismatched trials. That is, children assigned the determiner genders to the novel nouns during word learning. They then processed the non-adjacent gender agreement between the two categories (Det, Noun) during test. The results demonstrate abstract featural representation and grammatical productivity in young children.
-
The effect of training methodology on knowledge representation in categorization.
Hélie, Sébastien; Shamloo, Farzin; Ell, Shawn W
2017-01-01
Category representations can be broadly classified as containing within-category information or between-category information. Although such representational differences can have a profound impact on decision-making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule-based (RB) category structures thought to promote between-category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between-category representations whereas concept training resulted in a bias toward within-category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within-category representations. With II structures, there was a bias toward within-category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within-category representations could support generalization during the test phase. These data suggest that within-category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization.
-
The effect of training methodology on knowledge representation in categorization
Shamloo, Farzin; Ell, Shawn W.
2017-01-01
Category representations can be broadly classified as containing within–category information or between–category information. Although such representational differences can have a profound impact on decision–making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule–based (RB) category structures thought to promote between–category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between–category representations whereas concept training resulted in a bias toward within–category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within–category representations. With II structures, there was a bias toward within–category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within–category representations could support generalization during the test phase. These data suggest that within–category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization. PMID:28846732
-
Lancaster, Matthew E; Shelhamer, Ryan; Homa, Donald
2013-04-01
Two experiments investigated category inference when categories were composed of correlated or uncorrelated dimensions and the categories overlapped minimally or moderately. When the categories minimally overlapped, the dimensions were strongly correlated with the category label. Following a classification learning phase, subsequent transfer required the selection of either a category label or a feature when one, two, or three features were missing. Experiments 1 and 2 differed primarily in the number of learning blocks prior to transfer. In each experiment, the inference of the category label or category feature was influenced by both dimensional and category correlations, as well as their interaction. The number of cues available at test impacted performance more when the dimensional correlations were zero and category overlap was high. However, a minimal number of cues were sufficient to produce high levels of inference when the dimensions were highly correlated; additional cues had a positive but reduced impact, even when overlap was high. Subjects were generally more accurate in inferring the category label than a category feature regardless of dimensional correlation, category overlap, or number of cues available at test. Whether the category label functioned as a special feature or not was critically dependent upon these embedded correlations, with feature inference driven more strongly by dimensional correlations.
-
ERIC Educational Resources Information Center
Kurtz, Kenneth J.; Levering, Kimery R.; Stanton, Roger D.; Romero, Joshua; Morris, Steven N.
2013-01-01
The findings of Shepard, Hovland, and Jenkins (1961) on the relative ease of learning 6 elemental types of 2-way classifications have been deeply influential 2 times over: 1st, as a rebuke to pure stimulus generalization accounts, and again as the leading benchmark for evaluating formal models of human category learning. The litmus test for models…
-
Miller, Vonda H; Jansen, Ben H
2008-12-01
Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.
-
One Giant Leap for Categorizers: One Small Step for Categorization Theory
Smith, J. David; Ell, Shawn W.
2015-01-01
We explore humans’ rule-based category learning using analytic approaches that highlight their psychological transitions during learning. These approaches confirm that humans show qualitatively sudden psychological transitions during rule learning. These transitions contribute to the theoretical literature contrasting single vs. multiple category-learning systems, because they seem to reveal a distinctive learning process of explicit rule discovery. A complete psychology of categorization must describe this learning process, too. Yet extensive formal-modeling analyses confirm that a wide range of current (gradient-descent) models cannot reproduce these transitions, including influential rule-based models (e.g., COVIS) and exemplar models (e.g., ALCOVE). It is an important theoretical conclusion that existing models cannot explain humans’ rule-based category learning. The problem these models have is the incremental algorithm by which learning is simulated. Humans descend no gradient in rule-based tasks. Very different formal-modeling systems will be required to explain humans’ psychology in these tasks. An important next step will be to build a new generation of models that can do so. PMID:26332587
-
NASA Astrophysics Data System (ADS)
Handhika, J.; Cari, C.; Sunarno, W.; Suparmi, A.; Kurniadi, E.
2018-05-01
This research revealed the influence of project-based learning (PjBL) to increasing the level of the conception. The research method used the pre-experimental design with one group pre-test post-test. PjBL applied to students of physics education program of IKIP PGRI Madiun (23 Students). The test used to determine the level of conception is multiple choice tests and index of certainty. Activities on PjBL described. Obtained that the PjBL model can increase the level of conception and Critical thinking skills with the average normalized gain 0.49 and 0.57 (Medium category). It can be concluded that the PjBL could improve the level of conception and critical thinking ability of the students. Implementation of each model phase following learning objectives and needs analysis is the key to improve both.
-
Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation
Khaligh-Razavi, Seyed-Mahdi; Kriegeskorte, Nikolaus
2014-01-01
Inferior temporal (IT) cortex in human and nonhuman primates serves visual object recognition. Computational object-vision models, although continually improving, do not yet reach human performance. It is unclear to what extent the internal representations of computational models can explain the IT representation. Here we investigate a wide range of computational model representations (37 in total), testing their categorization performance and their ability to account for the IT representational geometry. The models include well-known neuroscientific object-recognition models (e.g. HMAX, VisNet) along with several models from computer vision (e.g. SIFT, GIST, self-similarity features, and a deep convolutional neural network). We compared the representational dissimilarity matrices (RDMs) of the model representations with the RDMs obtained from human IT (measured with fMRI) and monkey IT (measured with cell recording) for the same set of stimuli (not used in training the models). Better performing models were more similar to IT in that they showed greater clustering of representational patterns by category. In addition, better performing models also more strongly resembled IT in terms of their within-category representational dissimilarities. Representational geometries were significantly correlated between IT and many of the models. However, the categorical clustering observed in IT was largely unexplained by the unsupervised models. The deep convolutional network, which was trained by supervision with over a million category-labeled images, reached the highest categorization performance and also best explained IT, although it did not fully explain the IT data. Combining the features of this model with appropriate weights and adding linear combinations that maximize the margin between animate and inanimate objects and between faces and other objects yielded a representation that fully explained our IT data. Overall, our results suggest that explaining IT requires computational features trained through supervised learning to emphasize the behaviorally important categorical divisions prominently reflected in IT. PMID:25375136
-
Segmentation precedes face categorization under suboptimal conditions.
Van Den Boomen, Carlijn; Fahrenfort, Johannes J; Snijders, Tineke M; Kemner, Chantal
2015-01-01
Both categorization and segmentation processes play a crucial role in face perception. However, the functional relation between these subprocesses is currently unclear. The present study investigates the temporal relation between segmentation-related and category-selective responses in the brain, using electroencephalography (EEG). Surface segmentation and category content were both manipulated using texture-defined objects, including faces. This allowed us to study brain activity related to segmentation and to categorization. In the main experiment, participants viewed texture-defined objects for a duration of 800 ms. EEG results revealed that segmentation-related responses precede category-selective responses. Three additional experiments revealed that the presence and timing of categorization depends on stimulus properties and presentation duration. Photographic objects were presented for a long and short (92 ms) duration and evoked fast category-selective responses in both cases. On the other hand, presentation of texture-defined objects for a short duration only evoked segmentation-related but no category-selective responses. Category-selective responses were much slower when evoked by texture-defined than by photographic objects. We suggest that in case of categorization of objects under suboptimal conditions, such as when low-level stimulus properties are not sufficient for fast object categorization, segmentation facilitates the slower categorization process.
-
Segmentation precedes face categorization under suboptimal conditions
Van Den Boomen, Carlijn; Fahrenfort, Johannes J.; Snijders, Tineke M.; Kemner, Chantal
2015-01-01
Both categorization and segmentation processes play a crucial role in face perception. However, the functional relation between these subprocesses is currently unclear. The present study investigates the temporal relation between segmentation-related and category-selective responses in the brain, using electroencephalography (EEG). Surface segmentation and category content were both manipulated using texture-defined objects, including faces. This allowed us to study brain activity related to segmentation and to categorization. In the main experiment, participants viewed texture-defined objects for a duration of 800 ms. EEG results revealed that segmentation-related responses precede category-selective responses. Three additional experiments revealed that the presence and timing of categorization depends on stimulus properties and presentation duration. Photographic objects were presented for a long and short (92 ms) duration and evoked fast category-selective responses in both cases. On the other hand, presentation of texture-defined objects for a short duration only evoked segmentation-related but no category-selective responses. Category-selective responses were much slower when evoked by texture-defined than by photographic objects. We suggest that in case of categorization of objects under suboptimal conditions, such as when low-level stimulus properties are not sufficient for fast object categorization, segmentation facilitates the slower categorization process. PMID:26074838
-
[Which learning methods are expected for ultrasound training? Blended learning on trial].
Röhrig, S; Hempel, D; Stenger, T; Armbruster, W; Seibel, A; Walcher, F; Breitkreutz, R
2014-10-01
Current teaching methods in graduate and postgraduate training often include frontal presentations. Especially in ultrasound education not only knowledge but also sensomotory and visual skills need to be taught. This requires new learning methods. This study examined which types of teaching methods are preferred by participants in ultrasound training courses before, during and after the course by analyzing a blended learning concept. It also investigated how much time trainees are willing to spend on such activities. A survey was conducted at the end of a certified ultrasound training course. Participants were asked to complete a questionnaire based on a visual analogue scale (VAS) in which three categories were defined: category (1) vote for acceptance with a two thirds majority (VAS 67-100%), category (2) simple acceptance (50-67%) and category (3) rejection (< 50%). A total of 176 trainees participated in this survey. Participants preferred an e-learning program with interactive elements, short presentations (less than 20 min), incorporating interaction with the audience, hands-on sessions in small groups, an alternation between presentations and hands-on-sessions, live demonstrations and quizzes. For post-course learning, interactive and media-assisted approaches were preferred, such as e-learning, films of the presentations and the possibility to stay in contact with instructors in order to discuss the results. Participants also voted for maintaining a logbook for documentation of results. The results of this study indicate the need for interactive learning concepts and blended learning activities. Directors of ultrasound courses may consider these aspects and are encouraged to develop sustainable learning pathways.
-
Kapatsinski, Vsevolod; Olejarczuk, Paul; Redford, Melissa A
2017-03-01
We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns, whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of intonation contours: Previously encountered and novel exemplars are categorized together equally often, as long as distance from the prototype is controlled. However, age-related differences in categorization performance also exist. Given the same experience, adults form narrower categories than children. In addition, adults pay more attention to the end of the contour, while children appear to pay equal attention to the beginning and the end. The age range we examine appears to capture the tail-end of the developmental trajectory for learning intonation contour categories: There is a continuous effect of age on category breadth within the child group, but the oldest children (older than 10;3) are adult-like. Copyright © 2016 Cognitive Science Society, Inc.
-
Kapatsinski, Vsevolod; Olejarczuk, Paul; Redford, Melissa A.
2015-01-01
We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of intonation contours: previously encountered and novel exemplars are categorized together equally often, as long as distance from the prototype is controlled. However, age-related differences in categorization performance also exist. Given the same experience, adults form narrower categories than children. In addition, adults pay more attention to the end of the contour while children appear to pay equal attention to the beginning and the end. The age range we examine appears to capture the tail-end of the developmental trajectory for learning intonation contour categories: there is a continuous effect of age on category breadth within the child group, but the oldest children (older than 10;3) are adult-like. PMID:26901251
-
Reeder, Patricia A.; Newport, Elissa L.; Aslin, Richard N.
2012-01-01
A fundamental component of language acquisition involves organizing words into grammatical categories. Previous literature has suggested a number of ways in which this categorization task might be accomplished. Here we ask whether the patterning of the words in a corpus of linguistic input (distributional information) is sufficient, along with a small set of learning biases, to extract these underlying structural categories. In a series of experiments, we show that learners can acquire linguistic form-classes, generalizing from instances of the distributional contexts of individual words in the exposure set to the full range of contexts for all the words in the set. Crucially, we explore how several specific distributional variables enable learners to form a category of lexical items and generalize to novel words, yet also allow for exceptions that maintain lexical specificity. We suggest that learners are sensitive to the contexts of individual words, the overlaps among contexts across words, the non-overlap of contexts (or systematic gaps in information), and the size of the exposure set. We also ask how learners determine the category membership of a new word for which there is very sparse contextual information. We find that, when there are strong category cues and robust category learning of other words, adults readily generalize the distributional properties of the learned category to a new word that shares just one context with the other category members. However, as the distributional cues regarding the category become sparser and contain more consistent gaps, learners show more conservatism in generalizing distributional properties to the novel word. Taken together, these results show that learners are highly systematic in their use of the distributional properties of the input corpus, using them in a principled way to determine when to generalize and when to preserve lexical specificity. PMID:23089290
-
Reeder, Patricia A; Newport, Elissa L; Aslin, Richard N
2013-02-01
A fundamental component of language acquisition involves organizing words into grammatical categories. Previous literature has suggested a number of ways in which this categorization task might be accomplished. Here we ask whether the patterning of the words in a corpus of linguistic input (distributional information) is sufficient, along with a small set of learning biases, to extract these underlying structural categories. In a series of experiments, we show that learners can acquire linguistic form-classes, generalizing from instances of the distributional contexts of individual words in the exposure set to the full range of contexts for all the words in the set. Crucially, we explore how several specific distributional variables enable learners to form a category of lexical items and generalize to novel words, yet also allow for exceptions that maintain lexical specificity. We suggest that learners are sensitive to the contexts of individual words, the overlaps among contexts across words, the non-overlap of contexts (or systematic gaps in information), and the size of the exposure set. We also ask how learners determine the category membership of a new word for which there is very sparse contextual information. We find that, when there are strong category cues and robust category learning of other words, adults readily generalize the distributional properties of the learned category to a new word that shares just one context with the other category members. However, as the distributional cues regarding the category become sparser and contain more consistent gaps, learners show more conservatism in generalizing distributional properties to the novel word. Taken together, these results show that learners are highly systematic in their use of the distributional properties of the input corpus, using them in a principled way to determine when to generalize and when to preserve lexical specificity. Copyright © 2012 Elsevier Inc. All rights reserved.
-
Gabay, Yafit; Vakil, Eli; Schiff, Rachel; Holt, Lori L.
2015-01-01
Objective Developmental dyslexia is presumed to arise from specific phonological impairments. However, an emerging theoretical framework suggests that phonological impairments may be symptoms stemming from an underlying dysfunction of procedural learning. Method We tested procedural learning in adults with dyslexia (n=15) and matched-controls (n=15) using two versions of the Weather Prediction Task: Feedback (FB) and Paired-associate (PA). In the FB-based task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of response. In the PA-based learning task, participants viewed the cue and its associated outcome simultaneously without overt response or feedback. In both versions, participants trained across 150 trials. Learning was assessed in a subsequent test without presentation of the outcome, or corrective feedback. Results The Dyslexia group exhibited impaired learning compared with the Control group on both the FB and PA versions of the weather prediction task. Conclusions The results indicate that the ability to learn by feedback is not selectively impaired in dyslexia. Rather it seems that the probabilistic nature of the task, shared by the FB and PA versions of the weather prediction task, hampers learning in those with dyslexia. Results are discussed in light of procedural learning impairments among participants with dyslexia. PMID:25730732
-
NASA Astrophysics Data System (ADS)
Sari, Dwi Ivayana; Hermanto, Didik
2017-08-01
This research is a developmental research of probabilistic thinking-oriented learning tools for probability materials at ninth grade students. This study is aimed to produce a good probabilistic thinking-oriented learning tools. The subjects were IX-A students of MTs Model Bangkalan. The stages of this development research used 4-D development model which has been modified into define, design and develop. Teaching learning tools consist of lesson plan, students' worksheet, learning teaching media and students' achievement test. The research instrument used was a sheet of learning tools validation, a sheet of teachers' activities, a sheet of students' activities, students' response questionnaire and students' achievement test. The result of those instruments were analyzed descriptively to answer research objectives. The result was teaching learning tools in which oriented to probabilistic thinking of probability at ninth grade students which has been valid. Since teaching and learning tools have been revised based on validation, and after experiment in class produced that teachers' ability in managing class was effective, students' activities were good, students' responses to the learning tools were positive and the validity, sensitivity and reliability category toward achievement test. In summary, this teaching learning tools can be used by teacher to teach probability for develop students' probabilistic thinking.
-
Cognitive changes in conjunctive rule-based category learning: An ERP approach.
Rabi, Rahel; Joanisse, Marc F; Zhu, Tianshu; Minda, John Paul
2018-06-25
When learning rule-based categories, sufficient cognitive resources are needed to test hypotheses, maintain the currently active rule in working memory, update rules after feedback, and to select a new rule if necessary. Prior research has demonstrated that conjunctive rules are more complex than unidimensional rules and place greater demands on executive functions like working memory. In our study, event-related potentials (ERPs) were recorded while participants performed a conjunctive rule-based category learning task with trial-by-trial feedback. In line with prior research, correct categorization responses resulted in a larger stimulus-locked late positive complex compared to incorrect responses, possibly indexing the updating of rule information in memory. Incorrect trials elicited a pronounced feedback-locked P300 elicited which suggested a disconnect between perception, and the rule-based strategy. We also examined the differential processing of stimuli that were able to be correctly classified by the suboptimal single-dimensional rule ("easy" stimuli) versus those that could only be correctly classified by the optimal, conjunctive rule ("difficult" stimuli). Among strong learners, a larger, late positive slow wave emerged for difficult compared with easy stimuli, suggesting differential processing of category items even though strong learners performed well on the conjunctive category set. Overall, the findings suggest that ERP combined with computational modelling can be used to better understand the cognitive processes involved in rule-based category learning.
-
Parrado-Hernández, Emilio; Gómez-Sánchez, Eduardo; Dimitriadis, Yannis A
2003-09-01
An evaluation of distributed learning as a means to attenuate the category proliferation problem in Fuzzy ARTMAP based neural systems is carried out, from both qualitative and quantitative points of view. The study involves two original winner-take-all (WTA) architectures, Fuzzy ARTMAP and FasArt, and their distributed versions, dARTMAP and dFasArt. A qualitative analysis of the distributed learning properties of dARTMAP is made, focusing on the new elements introduced to endow Fuzzy ARTMAP with distributed learning. In addition, a quantitative study on a selected set of classification problems points out that problems have to present certain features in their output classes in order to noticeably reduce the number of recruited categories and achieve an acceptable classification accuracy. As part of this analysis, distributed learning was successfully adapted to a member of the Fuzzy ARTMAP family, FasArt, and similar procedures can be used to extend distributed learning capabilities to other Fuzzy ARTMAP based systems.
-
Analyzing Distributional Learning of Phonemic Categories in Unsupervised Deep Neural Networks
Räsänen, Okko; Nagamine, Tasha; Mesgarani, Nima
2017-01-01
Infants’ speech perception adapts to the phonemic categories of their native language, a process assumed to be driven by the distributional properties of speech. This study investigates whether deep neural networks (DNNs), the current state-of-the-art in distributional feature learning, are capable of learning phoneme-like representations of speech in an unsupervised manner. We trained DNNs with unlabeled and labeled speech and analyzed the activations of each layer with respect to the phones in the input segments. The analyses reveal that the emergence of phonemic invariance in DNNs is dependent on the availability of phonemic labeling of the input during the training. No increased phonemic selectivity of the hidden layers was observed in the purely unsupervised networks despite successful learning of low-dimensional representations for speech. This suggests that additional learning constraints or more sophisticated models are needed to account for the emergence of phone-like categories in distributional learning operating on natural speech. PMID:29359204
-
Evaluation and construction of diagnostic criteria for inclusion body myositis
Mammen, Andrew L.; Amato, Anthony A.; Weiss, Michael D.; Needham, Merrilee
2014-01-01
Objective: To use patient data to evaluate and construct diagnostic criteria for inclusion body myositis (IBM), a progressive disease of skeletal muscle. Methods: The literature was reviewed to identify all previously proposed IBM diagnostic criteria. These criteria were applied through medical records review to 200 patients diagnosed as having IBM and 171 patients diagnosed as having a muscle disease other than IBM by neuromuscular specialists at 2 institutions, and to a validating set of 66 additional patients with IBM from 2 other institutions. Machine learning techniques were used for unbiased construction of diagnostic criteria. Results: Twenty-four previously proposed IBM diagnostic categories were identified. Twelve categories all performed with high (≥97%) specificity but varied substantially in their sensitivities (11%–84%). The best performing category was European Neuromuscular Centre 2013 probable (sensitivity of 84%). Specialized pathologic features and newly introduced strength criteria (comparative knee extension/hip flexion strength) performed poorly. Unbiased data-directed analysis of 20 features in 371 patients resulted in construction of higher-performing data-derived diagnostic criteria (90% sensitivity and 96% specificity). Conclusions: Published expert consensus–derived IBM diagnostic categories have uniformly high specificity but wide-ranging sensitivities. High-performing IBM diagnostic category criteria can be developed directly from principled unbiased analysis of patient data. Classification of evidence: This study provides Class II evidence that published expert consensus–derived IBM diagnostic categories accurately distinguish IBM from other muscle disease with high specificity but wide-ranging sensitivities. PMID:24975859
-
Freedberg, Michael; Glass, Brian; Filoteo, J Vincent; Hazeltine, Eliot; Maddox, W Todd
2017-01-01
Categorical learning is dependent on feedback. Here, we compare how positive and negative feedback affect information-integration (II) category learning. Ashby and O'Brien (2007) demonstrated that both positive and negative feedback are required to solve II category problems when feedback was not guaranteed on each trial, and reported no differences between positive-only and negative-only feedback in terms of their effectiveness. We followed up on these findings and conducted 3 experiments in which participants completed 2,400 II categorization trials across three days under 1 of 3 conditions: positive feedback only (PFB), negative feedback only (NFB), or both types of feedback (CP; control partial). An adaptive algorithm controlled the amount of feedback given to each group so that feedback was nearly equated. Using different feedback control procedures, Experiments 1 and 2 demonstrated that participants in the NFB and CP group were able to engage II learning strategies, whereas the PFB group was not. Additionally, the NFB group was able to achieve significantly higher accuracy than the PFB group by Day 3. Experiment 3 revealed that these differences remained even when we equated the information received on feedback trials. Thus, negative feedback appears significantly more effective for learning II category structures. This suggests that the human implicit learning system may be capable of learning in the absence of positive feedback.
-
Soto, Fabian A.; Bassett, Danielle S.; Ashby, F. Gregory
2016-01-01
Recent work has shown that multimodal association areas–including frontal, temporal and parietal cortex–are focal points of functional network reconfiguration during human learning and performance of cognitive tasks. On the other hand, neurocomputational theories of category learning suggest that the basal ganglia and related subcortical structures are focal points of functional network reconfiguration during early learning of some categorization tasks, but become less so with the development of automatic categorization performance. Using a combination of network science and multilevel regression, we explore how changes in the connectivity of small brain regions can predict behavioral changes during training in a visual categorization task. We find that initial category learning, as indexed by changes in accuracy, is predicted by increasingly efficient integrative processing in subcortical areas, with higher functional specialization, more efficient integration across modules, but a lower cost in terms of redundancy of information processing. The development of automaticity, as indexed by changes in the speed of correct responses, was predicted by lower clustering (particularly in subcortical areas), higher strength (highest in cortical areas) and higher betweenness centrality. By combining neurocomputational theories and network scientific methods, these results synthesize the dissociative roles of multimodal association areas and subcortical structures in the development of automaticity during category learning. PMID:27453156
-
Contrastive Constraints Guide Explanation-Based Category Learning
ERIC Educational Resources Information Center
Chin-Parker, Seth; Cantelon, Julie
2017-01-01
This paper provides evidence for a contrastive account of explanation that is motivated by pragmatic theories that recognize the contribution that context makes to the interpretation of a prompt for explanation. This study replicates the primary findings of previous work in explanation-based category learning (Williams & Lombrozo, 2010),…
-
Dewey, Peirce, and the Categories of Learning
ERIC Educational Resources Information Center
Wojcikiewicz, Steven K.
2010-01-01
John Dewey proposes the "educative" experience as the goal of instruction. Yet, in focusing on the educative experience, Dewey may discount other sorts of learning which occur in school, and indeed in life. This piece proposes a recapitulation of Dewey's theory through Peirce's categorical system of experience, leading to three categories of…
-
Discriminative Bayesian Dictionary Learning for Classification.
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.
-
Validity of "Hi_Science" as instructional media based-android refer to experiential learning model
NASA Astrophysics Data System (ADS)
Qamariah, Jumadi, Senam, Wilujeng, Insih
2017-08-01
Hi_Science is instructional media based-android in learning science on material environmental pollution and global warming. This study is aimed: (a) to show the display of Hi_Science that will be applied in Junior High School, and (b) to describe the validity of Hi_Science. Hi_Science as instructional media created with colaboration of innovative learning model and development of technology at the current time. Learning media selected is based-android and collaborated with experiential learning model as an innovative learning model. Hi_Science had adapted student worksheet by Taufiq (2015). Student worksheet had very good category by two expert lecturers and two science teachers (Taufik, 2015). This student worksheet is refined and redeveloped in android as an instructional media which can be used by students for learning science not only in the classroom, but also at home. Therefore, student worksheet which has become instructional media based-android must be validated again. Hi_Science has been validated by two experts. The validation is based on assessment of meterials aspects and media aspects. The data collection was done by media assessment instrument. The result showed the assessment of material aspects has obtained the average value 4,72 with percentage of agreement 96,47%, that means Hi_Science on the material aspects is in excellent category or very valid category. The assessment of media aspects has obtained the average value 4,53 with percentage of agreement 98,70%, that means Hi_Science on the media aspects is in excellent category or very valid category. It was concluded that Hi_Science as instructional media can be applied in the junior high school.
-
Decoding word and category-specific spatiotemporal representations from MEG and EEG
Chan, Alexander M.; Halgren, Eric; Marinkovic, Ksenija; Cash, Sydney S.
2010-01-01
The organization and localization of lexico-semantic information in the brain has been debated for many years. Specifically, lesion and imaging studies have attempted to map the brain areas representing living versus non-living objects, however, results remain variable. This may be due, in part, to the fact that the univariate statistical mapping analyses used to detect these brain areas are typically insensitive to subtle, but widespread, effects. Decoding techniques, on the other hand, allow for a powerful multivariate analysis of multichannel neural data. In this study, we utilize machine-learning algorithms to first demonstrate that semantic category, as well as individual words, can be decoded from EEG and MEG recordings of subjects performing a language task. Mean accuracies of 76% (chance = 50%) and 83% (chance = 20%) were obtained for the decoding of living vs. non-living category or individual words respectively. Furthermore, we utilize this decoding analysis to demonstrate that the representations of words and semantic category are highly distributed both spatially and temporally. In particular, bilateral anterior temporal, bilateral inferior frontal, and left inferior temporal-occipital sensors are most important for discrimination. Successful intersubject and intermodality decoding shows that semantic representations between stimulus modalities and individuals are reasonably consistent. These results suggest that both word and category-specific information are present in extracranially recorded neural activity and that these representations may be more distributed, both spatially and temporally, than previous studies suggest. PMID:21040796
-
Same items, different order: effects of temporal variability on infant categorization.
Mather, Emily; Plunkett, Kim
2011-06-01
How does variability between members of a category influence infants' category learning? We explore the impact of the order in which different items are sampled on category formation. Two groups of 10-months-olds were presented with a series of exemplars to be organized into a single category. In a low distance group, the order of presentation minimized the perceptual distance between consecutive exemplars. In a high distance group, the order of presentation maximized the distance between successive exemplars. At test, only infants in the High Distance condition reliably discriminated between the category prototype and an atypical exemplar. Hence, the order in which infants learnt about the exemplars impacted their categorization performance. Our findings demonstrate the importance of moment-to-moment variations in similarity during infants' category learning. Copyright © 2011 Elsevier B.V. All rights reserved.
-
Grossberg, Stephen
2017-01-01
Adaptive Resonance Theory, or ART, is a neural model that explains how normal and abnormal brains may learn to categorize and recognize objects and events in a changing world, and how these learned categories may be remembered for a long time. This article uses ART to propose and unify the explanation of diverse data about normal and abnormal modulation of learning and memory by acetylcholine (ACh). In ART, vigilance control determines whether learned categories will be general and abstract, or specific and concrete. ART models how vigilance may be regulated by ACh release in layer 5 neocortical cells by influencing after-hyperpolarization (AHP) currents. This phasic ACh release is mediated by cells in the nucleus basalis (NB) of Meynert that are activated by unexpected events. The article additionally discusses data about ACh-mediated tonic control of vigilance. ART proposes that there are often dynamic breakdowns of tonic control in mental disorders such as autism, where vigilance remains high, and medial temporal amnesia, where vigilance remains low. Tonic control also occurs during sleep-wake cycles. Properties of Up and Down states during slow wave sleep arise in ACh-modulated laminar cortical ART circuits that carry out processes in awake individuals of contrast normalization, attentional modulation, decision-making, activity-dependent habituation, and mismatch-mediated reset. These slow wave sleep circuits interact with circuits that control circadian rhythms and memory consolidation. Tonic control properties also clarify how Alzheimer’s disease symptoms follow from a massive structural degeneration that includes undermining vigilance control by ACh in cortical layers 3 and 5. Sleep disruptions before and during Alzheimer’s disease, and how they contribute to a vicious cycle of plaque formation in layers 3 and 5, are also clarified from this perspective. PMID:29163063
-
The Neural Correlates of Desire
Kawabata, Hideaki; Zeki, Semir
2008-01-01
In an event-related fMRI study, we scanned eighteen normal human subjects while they viewed three categories of pictures (events, objects and persons) which they classified according to desirability (desirable, indifferent or undesirable). Each category produced activity in a distinct part of the visual brain, thus reflecting its functional specialization. We used conjunction analysis to learn whether there is a brain area which is always active when a desirable picture is viewed, regardless of the category to which it belongs. The conjunction analysis of the contrast desirable > undesirable revealed activity in the superior orbito-frontal cortex. This activity bore a positive linear relationship to the declared level of desirability. The conjunction analysis of desirable > indifferent revealed activity in the mid-cingulate cortex and in the anterior cingulate cortex. In the former, activity was greater for desirable and undesirable stimuli than for stimuli classed as indifferent. Other conjunction analyses produced no significant effects. These results show that categorizing any stimulus according to its desirability activates three different brain areas: the superior orbito-frontal, the mid-cingulate, and the anterior cingulate cortices. PMID:18728753
-
Striem-Amit, Ella; Cohen, Laurent; Dehaene, Stanislas; Amedi, Amir
2012-11-08
Using a visual-to-auditory sensory-substitution algorithm, congenitally fully blind adults were taught to read and recognize complex images using "soundscapes"--sounds topographically representing images. fMRI was used to examine key questions regarding the visual word form area (VWFA): its selectivity for letters over other visual categories without visual experience, its feature tolerance for reading in a novel sensory modality, and its plasticity for scripts learned in adulthood. The blind activated the VWFA specifically and selectively during the processing of letter soundscapes relative to both textures and visually complex object categories and relative to mental imagery and semantic-content controls. Further, VWFA recruitment for reading soundscapes emerged after 2 hr of training in a blind adult on a novel script. Therefore, the VWFA shows category selectivity regardless of input sensory modality, visual experience, and long-term familiarity or expertise with the script. The VWFA may perform a flexible task-specific rather than sensory-specific computation, possibly linking letter shapes to phonology. Copyright © 2012 Elsevier Inc. All rights reserved.
-
The neural network classification of false killer whale (Pseudorca crassidens) vocalizations.
Murray, S O; Mercado, E; Roitblat, H L
1998-12-01
This study reports the use of unsupervised, self-organizing neural network to categorize the repertoire of false killer whale vocalizations. Self-organizing networks are capable of detecting patterns in their input and partitioning those patterns into categories without requiring that the number or types of categories be predefined. The inputs for the neural networks were two-dimensional characterization of false killer whale vocalization, where each vocalization was characterized by a sequence of short-time measurements of duty cycle and peak frequency. The first neural network used competitive learning, where units in a competitive layer distributed themselves to recognize frequently presented input vectors. This network resulted in classes representing typical patterns in the vocalizations. The second network was a Kohonen feature map which organized the outputs topologically, providing a graphical organization of pattern relationships. The networks performed well as measured by (1) the average correlation between the input vectors and the weight vectors for each category, and (2) the ability of the networks to classify novel vocalizations. The techniques used in this study could easily be applied to other species and facilitate the development of objective, comprehensive repertoire models.
-
Ware, Elizabeth A.; Gelman, Susan A.; Kleinberg, Felicia
2013-01-01
An important developmental task is learning to organize experience by forming conceptual relations among entities (e.g., a lion and a snake can be linked because both are animals; a lion and a cage can be linked because the lion lives in the cage). We propose that representational medium (i.e., pictures vs. objects) plays an important role in influencing which relations children consider. Prior work has demonstrated that pictures more readily evoke broader categories, whereas objects more readily call attention to specific individuals. We therefore predicted that pictures would encourage taxonomic and shared-property relations, whereas objects would encourage thematic and slot-filler relations. We observed 32 mother-child dyads (M child ages = 2.9 and 4.3) playing with pictures and objects, and identified utterances in which they made taxonomic, thematic, shared-property, or slot-filler links between items. The results confirmed our predictions and thus support representational medium as an important factor that influences the conceptual relations expressed during dyadic conversations. PMID:24273367
-
Grossberg, Stephen; Palma, Jesse; Versace, Massimiliano
2015-01-01
Freely behaving organisms need to rapidly calibrate their perceptual, cognitive, and motor decisions based on continuously changing environmental conditions. These plastic changes include sharpening or broadening of cognitive and motor attention and learning to match the behavioral demands that are imposed by changing environmental statistics. This article proposes that a shared circuit design for such flexible decision-making is used in specific cognitive and motor circuits, and that both types of circuits use acetylcholine to modulate choice selectivity. Such task-sensitive control is proposed to control thalamocortical choice of the critical features that are cognitively attended and that are incorporated through learning into prototypes of visual recognition categories. A cholinergically-modulated process of vigilance control determines if a recognition category and its attended features are abstract (low vigilance) or concrete (high vigilance). Homologous neural mechanisms of cholinergic modulation are proposed to focus attention and learn a multimodal map within the deeper layers of superior colliculus. This map enables visual, auditory, and planned movement commands to compete for attention, leading to selection of a winning position that controls where the next saccadic eye movement will go. Such map learning may be viewed as a kind of attentive motor category learning. The article hereby explicates a link between attention, learning, and cholinergic modulation during decision making within both cognitive and motor systems. Homologs between the mammalian superior colliculus and the avian optic tectum lead to predictions about how multimodal map learning may occur in the mammalian and avian brain and how such learning may be modulated by acetycholine.
-
Grossberg, Stephen; Palma, Jesse; Versace, Massimiliano
2016-01-01
Freely behaving organisms need to rapidly calibrate their perceptual, cognitive, and motor decisions based on continuously changing environmental conditions. These plastic changes include sharpening or broadening of cognitive and motor attention and learning to match the behavioral demands that are imposed by changing environmental statistics. This article proposes that a shared circuit design for such flexible decision-making is used in specific cognitive and motor circuits, and that both types of circuits use acetylcholine to modulate choice selectivity. Such task-sensitive control is proposed to control thalamocortical choice of the critical features that are cognitively attended and that are incorporated through learning into prototypes of visual recognition categories. A cholinergically-modulated process of vigilance control determines if a recognition category and its attended features are abstract (low vigilance) or concrete (high vigilance). Homologous neural mechanisms of cholinergic modulation are proposed to focus attention and learn a multimodal map within the deeper layers of superior colliculus. This map enables visual, auditory, and planned movement commands to compete for attention, leading to selection of a winning position that controls where the next saccadic eye movement will go. Such map learning may be viewed as a kind of attentive motor category learning. The article hereby explicates a link between attention, learning, and cholinergic modulation during decision making within both cognitive and motor systems. Homologs between the mammalian superior colliculus and the avian optic tectum lead to predictions about how multimodal map learning may occur in the mammalian and avian brain and how such learning may be modulated by acetycholine. PMID:26834535
-
Category learning strategies in younger and older adults: Rule abstraction and memorization.
Wahlheim, Christopher N; McDaniel, Mark A; Little, Jeri L
2016-06-01
Despite the fundamental role of category learning in cognition, few studies have examined how this ability differs between younger and older adults. The present experiment examined possible age differences in category learning strategies and their effects on learning. Participants were trained on a category determined by a disjunctive rule applied to relational features. The utilization of rule- and exemplar-based strategies was indexed by self-reports and transfer performance. Based on self-reported strategies, the frequencies of rule- and exemplar-based learners were not significantly different between age groups, but there was a significantly higher frequency of intermediate learners (i.e., learners not identifying with a reliance on either rule- or exemplar-based strategies) in the older than younger adult group. Training performance was higher for younger than older adults regardless of the strategy utilized, showing that older adults were impaired in their ability to learn the correct rule or to remember exemplar-label associations. Transfer performance converged with strategy reports in showing higher fidelity category representations for younger adults. Younger adults with high working memory capacity were more likely to use an exemplar-based strategy, and older adults with high working memory capacity showed better training performance. Age groups did not differ in their self-reported memory beliefs, and these beliefs did not predict training strategies or performance. Overall, the present results contradict earlier findings that older adults prefer rule- to exemplar-based learning strategies, presumably to compensate for memory deficits. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
-
Conceptual Distinctiveness Supports Detailed Visual Long-Term Memory for Real-World Objects
Konkle, Talia; Brady, Timothy F.; Alvarez, George A.; Oliva, Aude
2012-01-01
Humans have a massive capacity to store detailed information in visual long-term memory. The present studies explored the fidelity of these visual long-term memory representations and examined how conceptual and perceptual features of object categories support this capacity. Observers viewed 2,800 object images with a different number of exemplars presented from each category. At test, observers indicated which of 2 exemplars they had previously studied. Memory performance was high and remained quite high (82% accuracy) with 16 exemplars from a category in memory, demonstrating a large memory capacity for object exemplars. However, memory performance decreased as more exemplars were held in memory, implying systematic categorical interference. Object categories with conceptually distinctive exemplars showed less interference in memory as the number of exemplars increased. Interference in memory was not predicted by the perceptual distinctiveness of exemplars from an object category, though these perceptual measures predicted visual search rates for an object target among exemplars. These data provide evidence that observers’ capacity to remember visual information in long-term memory depends more on conceptual structure than perceptual distinctiveness. PMID:20677899
-
Decoding visual object categories in early somatosensory cortex.
Smith, Fraser W; Goodale, Melvyn A
2015-04-01
Neurons, even in the earliest sensory areas of cortex, are subject to a great deal of contextual influence from both within and across modality connections. In the present work, we investigated whether the earliest regions of somatosensory cortex (S1 and S2) would contain content-specific information about visual object categories. We reasoned that this might be possible due to the associations formed through experience that link different sensory aspects of a given object. Participants were presented with visual images of different object categories in 2 fMRI experiments. Multivariate pattern analysis revealed reliable decoding of familiar visual object category in bilateral S1 (i.e., postcentral gyri) and right S2. We further show that this decoding is observed for familiar but not unfamiliar visual objects in S1. In addition, whole-brain searchlight decoding analyses revealed several areas in the parietal lobe that could mediate the observed context effects between vision and somatosensation. These results demonstrate that even the first cortical stages of somatosensory processing carry information about the category of visually presented familiar objects. © The Author 2013. Published by Oxford University Press.
-
Decoding Visual Object Categories in Early Somatosensory Cortex
Smith, Fraser W.; Goodale, Melvyn A.
2015-01-01
Neurons, even in the earliest sensory areas of cortex, are subject to a great deal of contextual influence from both within and across modality connections. In the present work, we investigated whether the earliest regions of somatosensory cortex (S1 and S2) would contain content-specific information about visual object categories. We reasoned that this might be possible due to the associations formed through experience that link different sensory aspects of a given object. Participants were presented with visual images of different object categories in 2 fMRI experiments. Multivariate pattern analysis revealed reliable decoding of familiar visual object category in bilateral S1 (i.e., postcentral gyri) and right S2. We further show that this decoding is observed for familiar but not unfamiliar visual objects in S1. In addition, whole-brain searchlight decoding analyses revealed several areas in the parietal lobe that could mediate the observed context effects between vision and somatosensation. These results demonstrate that even the first cortical stages of somatosensory processing carry information about the category of visually presented familiar objects. PMID:24122136
-
Lesson plan profile of senior high school biology teachers in Subang
NASA Astrophysics Data System (ADS)
Rohayati, E.; Diana, S. W.; Priyandoko, D.
2018-05-01
Lesson plan have important role for biology teachers in teaching and learning process. The aim of this study was intended to gain an overview of lesson plan of biology teachers’ at Senior High Schools in Subang which were the members of biology teachers association in Subang. The research method was descriptive method. Data was collected from 30 biology teachers. The result of study showed that lesson plan profile in terms of subject’s identity had good category with 83.33 % of average score. Analysis on basic competence in fair category with 74.45 % of average score. The compatibility of method/strategy was in fair category with average score 72.22 %. The compatibility of instrument, media, and learning resources in fair category with 71.11 % of average score. Learning scenario was in good category with 77.00 % of average score. The compatibility of evaluation was in low category with 56.39 % of average score. It can be concluded that biology teachers in Subang were good enough in making lesson plan, however in terms of the compatibility of evaluation needed to be fixed. Furthermore, teachers’ training for biology teachers’ association was recommended to increasing teachers’ skill to be professional teachers.
-
Implementation of ICARE learning model using visualization animation on biotechnology course
NASA Astrophysics Data System (ADS)
Hidayat, Habibi
2017-12-01
ICARE is a learning model that directly ensure the students to actively participate in the learning process using animation media visualization. ICARE have five key elements of learning experience from children and adult that is introduction, connection, application, reflection and extension. The use of Icare system to ensure that participants have opportunity to apply what have been they learned. So that, the message delivered by lecture to students can be understood and recorded by students in a long time. Learning model that was deemed capable of improving learning outcomes and interest to learn in following learning process Biotechnology with applying the ICARE learning model using visualization animation. This learning model have been giving motivation to participate in the learning process and learning outcomes obtained becomes more increased than before. From the results of student learning in subjects Biotechnology by applying the ICARE learning model using Visualization Animation can improving study results of student from the average value of middle test amounted to 70.98 with the percentage of 75% increased value of final test to be 71.57 with the percentage of 68.63%. The interest to learn from students more increasing visits of student activities at each cycle, namely the first cycle obtained average value by 33.5 with enough category. The second cycle is obtained an average value of 36.5 to good category and third cycle the average value of 36.5 with a student activity to good category.
-
Celone, Kim A.; Thompson-Brenner, Heather; Ross, Robert S.; Pratt, Elizabeth M.; Stern, Chantal E.
2013-01-01
In the present study, we sought to examine whether the fronto-striatal learning system, which has been implicated in bulimia nervosa, would demonstrate altered BOLD activity during probabilistic category learning in women who met subthreshold criteria for bulimia nervosa (Sub-BN). Sub-BN, which falls within the clinical category of Eating Disorder Not Otherwise Specified (EDNOS), is comprised of individuals who demonstrate recurrent binge eating, efforts to minimize their caloric intake and caloric retention, and elevated levels of concern about shape, weight, and/or eating, but just fail to meet the diagnostic threshold for bulimia nervosa (BN). fMRI data were collected from eighteen women with subthreshold-BN (Sub-BN) and nineteen healthy control women group-matched for age, education and body mass index (MC) during the weather prediction task. Sub-BN participants demonstrated increased caudate nucleus and dorsolateral prefrontal cortex (DLPFC) activation during the learning of probabilistic categories. Though the two subject groups did not differ in behavioral performance, over the course of learning, Sub-BN participants showed a dynamic pattern of brain activity differences when compared to matched control participants. Regions implicated in episodic memory, including the medial temporal lobe (MTL), retrosplenial cortex, middle frontal gyrus, and anterior and posterior cingulate cortex showed decreased activity in the Sub-BN participants compared to MCs during early learning which was followed by increased involvement of the DLPFC during later learning. These findings demonstrate that women with Sub-BN demonstrate differences in fronto-striatal learning system activity, as well as a distinct functional pattern between fronto-striatal and MTL learning systems during the course of implicit probabilistic category learning. PMID:21419229
-
Out of sight, out of mind: Categorization learning and normal aging.
Schenk, Sabrina; Minda, John P; Lech, Robert K; Suchan, Boris
2016-10-01
The present combined EEG and eye tracking study examined the process of categorization learning at different age ranges and aimed to investigate to which degree categorization learning is mediated by visual attention and perceptual strategies. Seventeen young subjects and ten elderly subjects had to perform a visual categorization task with two abstract categories. Each category consisted of prototypical stimuli and an exception. The categorization of prototypical stimuli was learned very early during the experiment, while the learning of exceptions was delayed. The categorization of exceptions was accompanied by higher P150, P250 and P300 amplitudes. In contrast to younger subjects, elderly subjects had problems in the categorization of exceptions, but showed an intact categorization performance for prototypical stimuli. Moreover, elderly subjects showed higher fixation rates for important stimulus features and higher P150 amplitudes, which were positively correlated with the categorization performances. These results indicate that elderly subjects compensate for cognitive decline through enhanced perceptual and attentional processing of individual stimulus features. Additionally, a computational approach has been applied and showed a transition away from purely abstraction-based learning to an exemplar-based learning in the middle block for both groups. However, the calculated models provide a better fit for younger subjects than for elderly subjects. The current study demonstrates that human categorization learning is based on early abstraction-based processing followed by an exemplar-memorization stage. This strategy combination facilitates the learning of real world categories with a nuanced category structure. In addition, the present study suggests that categorization learning is affected by normal aging and modulated by perceptual processing and visual attention. Copyright © 2016 Elsevier Ltd. All rights reserved.
-
Is Statistical Learning Constrained by Lower Level Perceptual Organization?
Emberson, Lauren L.; Liu, Ran; Zevin, Jason D.
2013-01-01
In order for statistical information to aid in complex developmental processes such as language acquisition, learning from higher-order statistics (e.g. across successive syllables in a speech stream to support segmentation) must be possible while perceptual abilities (e.g. speech categorization) are still developing. The current study examines how perceptual organization interacts with statistical learning. Adult participants were presented with multiple exemplars from novel, complex sound categories designed to reflect some of the spectral complexity and variability of speech. These categories were organized into sequential pairs and presented such that higher-order statistics, defined based on sound categories, could support stream segmentation. Perceptual similarity judgments and multi-dimensional scaling revealed that participants only perceived three perceptual clusters of sounds and thus did not distinguish the four experimenter-defined categories, creating a tension between lower level perceptual organization and higher-order statistical information. We examined whether the resulting pattern of learning is more consistent with statistical learning being “bottom-up,” constrained by the lower levels of organization, or “top-down,” such that higher-order statistical information of the stimulus stream takes priority over the perceptual organization, and perhaps influences perceptual organization. We consistently find evidence that learning is constrained by perceptual organization. Moreover, participants generalize their learning to novel sounds that occupy a similar perceptual space, suggesting that statistical learning occurs based on regions of or clusters in perceptual space. Overall, these results reveal a constraint on learning of sound sequences, such that statistical information is determined based on lower level organization. These findings have important implications for the role of statistical learning in language acquisition. PMID:23618755
-
Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming
2018-02-28
The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to predict cortical responses to natural movies. Using this predictive model, we mapped human cortical representations to 64,000 visual objects from 80 categories with high throughput and accuracy. Such representations covered both the ventral and dorsal pathways, reflected multiple levels of object features, and preserved semantic relationships between categories. In the entire visual cortex, object representations were organized into three clusters of categories: biological objects, non-biological objects, and background scenes. In a finer scale specific to each cluster, object representations revealed sub-clusters for further categorization. Such hierarchical clustering of category representations was mostly contributed by cortical representations of object features from middle to high levels. In summary, this study demonstrates a useful computational strategy to characterize the cortical organization and representations of visual features for rapid categorization.
-
Cognitive Bias for Learning Speech Sounds From a Continuous Signal Space Seems Nonlinguistic.
van der Ham, Sabine; de Boer, Bart
2015-10-01
When learning language, humans have a tendency to produce more extreme distributions of speech sounds than those observed most frequently: In rapid, casual speech, vowel sounds are centralized, yet cross-linguistically, peripheral vowels occur almost universally. We investigate whether adults' generalization behavior reveals selective pressure for communication when they learn skewed distributions of speech-like sounds from a continuous signal space. The domain-specific hypothesis predicts that the emergence of sound categories is driven by a cognitive bias to make these categories maximally distinct, resulting in more skewed distributions in participants' reproductions. However, our participants showed more centered distributions, which goes against this hypothesis, indicating that there are no strong innate linguistic biases that affect learning these speech-like sounds. The centralization behavior can be explained by a lack of communicative pressure to maintain categories.
-
Cognitive Bias for Learning Speech Sounds From a Continuous Signal Space Seems Nonlinguistic
de Boer, Bart
2015-01-01
When learning language, humans have a tendency to produce more extreme distributions of speech sounds than those observed most frequently: In rapid, casual speech, vowel sounds are centralized, yet cross-linguistically, peripheral vowels occur almost universally. We investigate whether adults’ generalization behavior reveals selective pressure for communication when they learn skewed distributions of speech-like sounds from a continuous signal space. The domain-specific hypothesis predicts that the emergence of sound categories is driven by a cognitive bias to make these categories maximally distinct, resulting in more skewed distributions in participants’ reproductions. However, our participants showed more centered distributions, which goes against this hypothesis, indicating that there are no strong innate linguistic biases that affect learning these speech-like sounds. The centralization behavior can be explained by a lack of communicative pressure to maintain categories. PMID:27648212
-
Bogus Concerns about the False Prototype Enhancement Effect
ERIC Educational Resources Information Center
Homa, Donald; Hout, Michael C.; Milliken, Laura; Milliken, Ann Marie
2011-01-01
Two experiments addressed the mechanism responsible for the false prototype effect, the phenomenon in which a prototype gradient can be obtained in the absence of learning. Previous demonstrations of this effect have occurred solely in a single-category paradigm in which transfer patterns are assigned or not to the learning category. We tested the…
-
ERIC Educational Resources Information Center
Nelson, Deborah G. Kemler
1995-01-01
Three studies investigated the influence of principle-based inferences and unprincipled similarity relations on new category learning by three- to six-year-old children. Results indicated that categorization into newly learned categories may activate self-initiated, principle-based reasoning in young children, suggesting that spontaneous…
-
ERIC Educational Resources Information Center
Little, Daniel R.; Lewandowsky, Stephan
2009-01-01
Despite the fact that categories are often composed of correlated features, the evidence that people detect and use these correlations during intentional category learning has been overwhelmingly negative to date. Nonetheless, on other categorization tasks, such as feature prediction, people show evidence of correlational sensitivity. A…
-
Drift in Children's Categories: When Experienced Distributions Conflict with Prior Learning
ERIC Educational Resources Information Center
Kalish, Charles W.; Zhu, XiaoJin; Rogers, Timothy T.
2015-01-01
Psychological intuitions about natural category structure do not always correspond to the true structure of the world. The current study explores young children's responses to conflict between intuitive structure and authoritative feedback using a semi-supervised learning (Zhu et al., 2007) paradigm. In three experiments, 160 children between the…
-
Learning Phonemes with a Proto-Lexicon
ERIC Educational Resources Information Center
Martin, Andrew; Peperkamp, Sharon; Dupoux, Emmanuel
2013-01-01
Before the end of the first year of life, infants begin to lose the ability to perceive distinctions between sounds that are not phonemic in their native language. It is typically assumed that this developmental change reflects the construction of language-specific phoneme categories, but how these categories are learned largely remains a mystery.…
-
Differences in Developmental Experiences for Commonly Used Categories of Organized Youth Activities
ERIC Educational Resources Information Center
Hansen, David M.; Skorupski, William P.; Arrington, Tiffany L.
2010-01-01
The coherence of adolescents' self-reported learning experiences between subgroups of organized youth activities within five commonly used categories was evaluated. Data for the present study come from a representative sample of eleventh grade adolescents' reports on learning experiences in an organized youth activity using the Youth Experience…
-
Adaptable Learning Assistant for Item Bank Management
ERIC Educational Resources Information Center
Nuntiyagul, Atorn; Naruedomkul, Kanlaya; Cercone, Nick; Wongsawang, Damras
2008-01-01
We present PKIP, an adaptable learning assistant tool for managing question items in item banks. PKIP is not only able to automatically assist educational users to categorize the question items into predefined categories by their contents but also to correctly retrieve the items by specifying the category and/or the difficulty level. PKIP adapts…
-
Effects of childhood hearing loss on organization of semantic memory: typicality and relatedness.
Jerger, Susan; Damian, Markus F; Tye-Murray, Nancy; Dougherty, Meaghan; Mehta, Jyutika; Spence, Melanie
2006-12-01
The purpose of this research was to study how early childhood hearing loss affects development of concepts and categories, aspects of semantic knowledge that allow us to group and make inferences about objects with common properties, such as dogs versus cats. We assessed category typicality and out-of-category relatedness effects. The typicality effect refers to performance advantage (faster reaction times, fewer errors) for objects with a higher number of a category's characteristic properties; the out-of-category relatedness effect refers to performance disadvantage (slower reaction times and more errors) for out-of-category objects that share some properties with category members. We applied a new children's speeded category-verification task (vote "yes" if the pictured object is clothing). Stimuli were pictures of typical and atypical category objects (e.g., pants, glove) and related and unrelated out-of-category objects (e.g., necklace, soup). Participants were 30 children with hearing impairment (HI) who were considered successful hearing aid users and who attended regular classes (mainstreamed) with some support services. Ages ranged from 5 to 15 yr (mean = 10 yr 8 mo). Results were related to normative data from . Typical objects consistently showed preferential processing (faster reaction times, fewer errors), and related out-of-category objects consistently showed the converse. Overall, results between HI and normative groups exhibited striking similarity. Variation in speed of classification was influenced primarily by age and age-related competencies, such as vocabulary skill. Audiological status, however, independently influenced performance to a lesser extent, with positive responses becoming faster as degree of hearing loss decreased and negative responses becoming faster as age of identification/amplification/education decreased. There were few errors overall. The presence of a typicality effect indicates that 1) the structure of conceptual representations for at least one category in the HI group was based on characteristic properties with an uneven distribution among members, and 2) typical objects with a higher number of characteristic properties were more easily accessed and/or retrieved. The presence of a relatedness effect indicates that the structure of representational knowledge in the HI group allowed them to appreciate semantic properties and understand that properties may be shared between categories. Speculations linked the association 1) between positive responses and degree of hearing loss to an increase in the quality, accessibility, and retrievability of conceptual representations with better hearing; and 2) between negative responses and age of identification/amplification/education to an improvement in effortful, postretrieval decision-making proficiencies with more schooling and amplified auditory experience. This research establishes the value of our new approach to assessing the organization of semantic memory in children with HI.
-
Frings, Christian; Göbel, Ariane; Mast, Frank; Sutter, Julia; Bermeitinger, Christina; Wentura, Dirk
2011-08-01
Marginally perceptible prototypes as primes lead to slowed reactions to related category exemplars as compared to unrelated ones. This at first glance counterintuitive finding has been interpreted as evidence for a particular mechanism of lateral inhibition, namely the centre surround inhibition mechanism. We investigated the semantic surround of category labels by experimentally manipulating the prototypicality of stimuli. Participants first learned two new categories of fantasy creatures in a 5-day-long learning phase before they worked through a semantic priming task with the category prototypes as primes and category exemplars as targets. For high-prototypical targets we observed benefit effects from related primes, whereas for low-prototypical targets we observed cost effects. The results define when the centre surround inhibition mechanism is applied, and furthermore might explain why previous studies with word stimuli (i.e., material that prevents experimental manipulation of prototypicality) observed mixed results concerning the prototypicality of targets.
-
Dovgopoly, Alexander; Mercado, Eduardo
2013-06-01
Individuals with autism spectrum disorder (ASD) show atypical patterns of learning and generalization. We explored the possible impacts of autism-related neural abnormalities on perceptual category learning using a neural network model of visual cortical processing. When applied to experiments in which children or adults were trained to classify complex two-dimensional images, the model can account for atypical patterns of perceptual generalization. This is only possible, however, when individual differences in learning are taken into account. In particular, analyses performed with a self-organizing map suggested that individuals with high-functioning ASD show two distinct generalization patterns: one that is comparable to typical patterns, and a second in which there is almost no generalization. The model leads to novel predictions about how individuals will generalize when trained with simplified input sets and can explain why some researchers have failed to detect learning or generalization deficits in prior studies of category learning by individuals with autism. On the basis of these simulations, we propose that deficits in basic neural plasticity mechanisms may be sufficient to account for the atypical patterns of perceptual category learning and generalization associated with autism, but they do not account for why only a subset of individuals with autism would show such deficits. If variations in performance across subgroups reflect heterogeneous neural abnormalities, then future behavioral and neuroimaging studies of individuals with ASD will need to account for such disparities.
-
Applying Machine Learning to Star Cluster Classification
NASA Astrophysics Data System (ADS)
Fedorenko, Kristina; Grasha, Kathryn; Calzetti, Daniela; Mahadevan, Sridhar
2016-01-01
Catalogs describing populations of star clusters are essential in investigating a range of important issues, from star formation to galaxy evolution. Star cluster catalogs are typically created in a two-step process: in the first step, a catalog of sources is automatically produced; in the second step, each of the extracted sources is visually inspected by 3-to-5 human classifiers and assigned a category. Classification by humans is labor-intensive and time consuming, thus it creates a bottleneck, and substantially slows down progress in star cluster research.We seek to automate the process of labeling star clusters (the second step) through applying supervised machine learning techniques. This will provide a fast, objective, and reproducible classification. Our data is HST (WFC3 and ACS) images of galaxies in the distance range of 3.5-12 Mpc, with a few thousand star clusters already classified by humans as a part of the LEGUS (Legacy ExtraGalactic UV Survey) project. The classification is based on 4 labels (Class 1 - symmetric, compact cluster; Class 2 - concentrated object with some degree of asymmetry; Class 3 - multiple peak system, diffuse; and Class 4 - spurious detection). We start by looking at basic machine learning methods such as decision trees. We then proceed to evaluate performance of more advanced techniques, focusing on convolutional neural networks and other Deep Learning methods. We analyze the results, and suggest several directions for further improvement.
-
Huang-Pollock, Cynthia L; Maddox, W Todd; Tam, Helen
2014-07-01
Suboptimal functioning of the basal ganglia is implicated in attention-deficit/hyperactivity disorder (ADHD). These structures are important to the acquisition of associative knowledge, leading some to theorize that associative learning deficits might be expected, despite the fact that most extant research in ADHD has focused on effortful control. We present 2 studies that examined the acquisition of explicit rule-based (RB) and associative information integration (II) category learning among school-age children with ADHD. In Study 1, we found deficits in both RB and II category learning tasks among children with ADHD (n = 81) versus controls (n = 42). Children with ADHD tended to sort by the more salient but irrelevant dimension (in the RB paradigm) and were unable to acquire a consistent sorting strategy (in the II paradigm). To disentangle whether the deficit was localized to II category learning versus a generalized inability to consider more than 1 stimulus dimension, in Study 2 children completed a conjunctive RB paradigm that required consideration of 2 stimulus dimensions. Children with ADHD (n = 50) continued to underperform controls (n = 33). Results provide partial support for neurocognitive developmental theories of ADHD that suggest that associative learning deficits should be found, and highlight the importance of using analytic approaches that go beyond asking whether an ADHD-related deficit exists to why such deficits exist.
-
Finding faults: analogical comparison supports spatial concept learning in geoscience.
Jee, Benjamin D; Uttal, David H; Gentner, Dedre; Manduca, Cathy; Shipley, Thomas F; Sageman, Bradley
2013-05-01
A central issue in education is how to support the spatial thinking involved in learning science, technology, engineering, and mathematics (STEM). We investigated whether and how the cognitive process of analogical comparison supports learning of a basic spatial concept in geoscience, fault. Because of the high variability in the appearance of faults, it may be difficult for students to learn the category-relevant spatial structure. There is abundant evidence that comparing analogous examples can help students gain insight into important category-defining features (Gentner in Cogn Sci 34(5):752-775, 2010). Further, comparing high-similarity pairs can be especially effective at revealing key differences (Sagi et al. 2012). Across three experiments, we tested whether comparison of visually similar contrasting examples would help students learn the fault concept. Our main findings were that participants performed better at identifying faults when they (1) compared contrasting (fault/no fault) cases versus viewing each case separately (Experiment 1), (2) compared similar as opposed to dissimilar contrasting cases early in learning (Experiment 2), and (3) viewed a contrasting pair of schematic block diagrams as opposed to a single block diagram of a fault as part of an instructional text (Experiment 3). These results suggest that comparison of visually similar contrasting cases helped distinguish category-relevant from category-irrelevant features for participants. When such comparisons occurred early in learning, participants were more likely to form an accurate conceptual representation. Thus, analogical comparison of images may provide one powerful way to enhance spatial learning in geoscience and other STEM disciplines.
-
Neuronal integration in visual cortex elevates face category tuning to conscious face perception
Fahrenfort, Johannes J.; Snijders, Tineke M.; Heinen, Klaartje; van Gaal, Simon; Scholte, H. Steven; Lamme, Victor A. F.
2012-01-01
The human brain has the extraordinary capability to transform cluttered sensory input into distinct object representations. For example, it is able to rapidly and seemingly without effort detect object categories in complex natural scenes. Surprisingly, category tuning is not sufficient to achieve conscious recognition of objects. What neural process beyond category extraction might elevate neural representations to the level where objects are consciously perceived? Here we show that visible and invisible faces produce similar category-selective responses in the ventral visual cortex. The pattern of neural activity evoked by visible faces could be used to decode the presence of invisible faces and vice versa. However, only visible faces caused extensive response enhancements and changes in neural oscillatory synchronization, as well as increased functional connectivity between higher and lower visual areas. We conclude that conscious face perception is more tightly linked to neural processes of sustained information integration and binding than to processes accommodating face category tuning. PMID:23236162
-
Category-based predictions: influence of uncertainty and feature associations.
Ross, B H; Murphy, G L
1996-05-01
Four experiments examined how people make inductive inferences using categories. Subjects read stories in which 2 categories were mentioned as possible identities of an object. The less likely category was varied to determine if people were using it, as well as the most likely category, in making predictions about the object. Experiment 1 showed that even when categorization uncertainty was emphasized, subjects used only 1 category as the basis for their prediction. Experiments 2-4 examined whether people would use multiple categories for making predictions when the feature to be predicted was associated to the less likely category. Multiple categories were used in this case, but only in limited circumstances; furthermore, using multiple categories in 1 prediction did not cause subjects to use them for subsequent predictions. The results increase the understanding of how categories are used in inductive inference.
-
Cross-Cultural Differences in Children's Beliefs about the Objectivity of Social Categories
ERIC Educational Resources Information Center
Diesendruck, Gil; Goldfein-Elbaz, Rebecca; Rhodes, Marjorie; Gelman, Susan; Neumark, Noam
2013-01-01
The present study compared 5-and 10-year-old North American and Israeli children's beliefs about the objectivity of different categories (n = 109). Children saw picture triads composed of two exemplars of the same category (e.g., two women) and an exemplar of a contrasting category (e.g., a man). Children were asked whether it would be acceptable…
-
Memory Errors Reveal a Bias to Spontaneously Generalize to Categories
ERIC Educational Resources Information Center
Sutherland, Shelbie L.; Cimpian, Andrei; Leslie, Sarah-Jane; Gelman, Susan A.
2015-01-01
Much evidence suggests that, from a young age, humans are able to generalize information learned about a subset of a category to the category itself. Here, we propose that--beyond simply being able to perform such generalizations--people are "biased" to generalize to categories, such that they routinely make spontaneous, implicit…
-
Discriminative region extraction and feature selection based on the combination of SURF and saliency
NASA Astrophysics Data System (ADS)
Deng, Li; Wang, Chunhong; Rao, Changhui
2011-08-01
The objective of this paper is to provide a possible optimization on salient region algorithm, which is extensively used in recognizing and learning object categories. Salient region algorithm owns the superiority of intra-class tolerance, global score of features and automatically prominent scale selection under certain range. However, the major limitation behaves on performance, and that is what we attempt to improve. By reducing the number of pixels involved in saliency calculation, it can be accelerated. We use interest points detected by fast-Hessian, the detector of SURF, as the candidate feature for saliency operation, rather than the whole set in image. This implementation is thereby called Saliency based Optimization over SURF (SOSU for short). Experiment shows that bringing in of such a fast detector significantly speeds up the algorithm. Meanwhile, Robustness of intra-class diversity ensures object recognition accuracy.
-
Rule-Based Category Learning in Children: The Role of Age and Executive Functioning
Rabi, Rahel; Minda, John Paul
2014-01-01
Rule-based category learning was examined in 4–11 year-olds and adults. Participants were asked to learn a set of novel perceptual categories in a classification learning task. Categorization performance improved with age, with younger children showing the strongest rule-based deficit relative to older children and adults. Model-based analyses provided insight regarding the type of strategy being used to solve the categorization task, demonstrating that the use of the task appropriate strategy increased with age. When children and adults who identified the correct categorization rule were compared, the performance deficit was no longer evident. Executive functions were also measured. While both working memory and inhibitory control were related to rule-based categorization and improved with age, working memory specifically was found to marginally mediate the age-related improvements in categorization. When analyses focused only on the sample of children, results showed that working memory ability and inhibitory control were associated with categorization performance and strategy use. The current findings track changes in categorization performance across childhood, demonstrating at which points performance begins to mature and resemble that of adults. Additionally, findings highlight the potential role that working memory and inhibitory control may play in rule-based category learning. PMID:24489658
-
Multi-level discriminative dictionary learning with application to large scale image classification.
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.
-
Task-relevant perceptual features can define categories in visual memory too.
Antonelli, Karla B; Williams, Carrick C
2017-11-01
Although Konkle, Brady, Alvarez, and Oliva (2010, Journal of Experimental Psychology: General, 139(3), 558) claim that visual long-term memory (VLTM) is organized on underlying conceptual, not perceptual, information, visual memory results from visual search tasks are not well explained by this theory. We hypothesized that when viewing an object, any task-relevant visual information is critical to the organizational structure of VLTM. In two experiments, we examined the organization of VLTM by measuring the amount of retroactive interference created by objects possessing different combinations of task-relevant features. Based on task instructions, only the conceptual category was task relevant or both the conceptual category and a perceptual object feature were task relevant. Findings indicated that when made task relevant, perceptual object feature information, along with conceptual category information, could affect memory organization for objects in VLTM. However, when perceptual object feature information was task irrelevant, it did not contribute to memory organization; instead, memory defaulted to being organized around conceptual category information. These findings support the theory that a task-defined organizational structure is created in VLTM based on the relevance of particular object features and information.
-
Structure Mapping and Relational Language Support Children's Learning of Relational Categories
ERIC Educational Resources Information Center
Gentner, Dedre; Anggoro, Florencia K.; Klibanoff, Raquel S.
2011-01-01
Learning relational categories--whose membership is defined not by intrinsic properties but by extrinsic relations with other entities--poses a challenge to young children. The current work showed 3-, 4- to 5-, and 6-year-olds pairs of cards exemplifying familiar relations (e.g., a nest and a bird exemplifying "home for") and then tested whether…
-
ERIC Educational Resources Information Center
Edmunds, Charlotte E. R.; Milton, Fraser; Wills, Andy J.
2018-01-01
Behavioral evidence for the COVIS dual-process model of category learning has been widely reported in over a hundred publications (Ashby & Valentin, 2016). It is generally accepted that the validity of such evidence depends on the accurate identification of individual participants' categorization strategies, a task that usually falls to…
-
Visual Imagery, Lifecourse Structure and Lifelong Learning
ERIC Educational Resources Information Center
Schuller, Tom
2004-01-01
Imagery could add an extra dimension to analyses of lifelong learning, which need to draw on diverse sources and techniques. This article has two principal components. First I suggest that the use of images might be divided into three categories: as illustration; as evidence; and as heuristic. I go on to explore the latter two categories, first by…
-
ERIC Educational Resources Information Center
Kapatsinski, Vsevolod; Olejarczuk, Paul; Redford, Melissa A.
2017-01-01
We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns, whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of…
-
ERIC Educational Resources Information Center
Schuler, Kathryn D.; Reeder, Patricia A.; Newport, Elissa L.; Aslin, Richard N.
2017-01-01
Successful language acquisition hinges on organizing individual words into grammatical categories and learning the relationships between them, but the method by which children accomplish this task has been debated in the literature. One proposal is that learners use the shared distributional contexts in which words appear as a cue to their…
-
Long-term care planning study: strengths and learning needs of nursing staff.
Cruttenden, Kathleen E
2006-01-01
This planning study was designed and conducted in a predominantly rural Canadian province to examine the strengths and learning needs of four categories of nursing staff practising in New Brunswick nursing homes. Participants included directors of care, registered nurses, licensed practical nurses, and resident attendants. The nursing homes ranged in size from 38 to 196 beds and were located throughout the province. In health and planning studies, ethnography conveys a coherent statement of peoples' local knowledge as culture-sharing groups (Muecke, 1994). The study derived information from the Nursing Home Act, reports, the literature, key informants, and direct observations of and interviews with participants. Leadership strengths defined the roles for categories of staff and supported the capacity of each category to identify their learning needs. In conclusion, nurses practising in nursing homes can and must take an active role in decision making for their learning.
-
Amnesic patients show superior generalization in category learning.
O'Connell, Garret; Myers, Catherine E; Hopkins, Ramona O; McLaren, R P; Gluck, Mark A; Wills, Andy J
2016-11-01
Generalization is the application of existing knowledge to novel situations. Questions remain about the precise role of the hippocampus in this facet of learning, but a connectionist model by Gluck and Myers (1993) predicts that generalization should be enhanced following hippocampal damage. In a two-category learning task, a group of amnesic patients (n = 9) learned the training items to a similar level of accuracy as matched controls (n = 9). Both groups then classified new items at various levels of distortion. The amnesic group showed significantly more accurate generalization to high-distortion novel items, a difference also present compared to a larger group of unmatched controls (n = 33). The model prediction of a broadening of generalization gradients in amnesia, at least for items near category boundaries, was supported by the results. Our study shows for the first time that amnesia can sometimes improve generalization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
-
NASA Astrophysics Data System (ADS)
Jansen, Peter A.; Watter, Scott
2012-03-01
Connectionist language modelling typically has difficulty with syntactic systematicity, or the ability to generalise language learning to untrained sentences. This work develops an unsupervised connectionist model of infant grammar learning. Following the semantic boostrapping hypothesis, the network distils word category using a developmentally plausible infant-scale database of grounded sensorimotor conceptual representations, as well as a biologically plausible semantic co-occurrence activation function. The network then uses this knowledge to acquire an early benchmark clausal grammar using correlational learning, and further acquires separate conceptual and grammatical category representations. The network displays strongly systematic behaviour indicative of the general acquisition of the combinatorial systematicity present in the grounded infant-scale language stream, outperforms previous contemporary models that contain primarily noun and verb word categories, and successfully generalises broadly to novel untrained sensorimotor grounded sentences composed of unfamiliar nouns and verbs. Limitations as well as implications to later grammar learning are discussed.
-
Montecinos, P; Rodewald, A M
1994-06-01
The aim this work was to assess and compare the achievements of medical students, subjected to problem based learning methodology. The information and comprehension categories of Bloom were tested in 17 medical students in four different occasions during the physiopathology course, using a multiple choice knowledge test. There was a significant improvement in the number of correct answers towards the end of the course. It is concluded that these medical students obtained adequate learning achievements in the information subcategory of Bloom using problem based learning methodology, during the physiopathology course.
-
Systematicity and a Categorical Theory of Cognitive Architecture: Universal Construction in Context
Phillips, Steven; Wilson, William H.
2016-01-01
Why does the capacity to think certain thoughts imply the capacity to think certain other, structurally related, thoughts? Despite decades of intensive debate, cognitive scientists have yet to reach a consensus on an explanation for this property of cognitive architecture—the basic processes and modes of composition that together afford cognitive capacity—called systematicity. Systematicity is generally considered to involve a capacity to represent/process common structural relations among the equivalently cognizable entities. However, the predominant theoretical approaches to the systematicity problem, i.e., classical (symbolic) and connectionist (subsymbolic), require arbitrary (ad hoc) assumptions to derive systematicity. That is, their core principles and assumptions do not provide the necessary and sufficient conditions from which systematicity follows, as required of a causal theory. Hence, these approaches fail to fully explain why systematicity is a (near) universal property of human cognition, albeit in restricted contexts. We review an alternative, category theory approach to the systematicity problem. As a mathematical theory of structure, category theory provides necessary and sufficient conditions for systematicity in the form of universal construction: each systematically related cognitive capacity is composed of a common component and a unique component. Moreover, every universal construction can be viewed as the optimal construction in the given context (category). From this view, universal constructions are derived from learning, as an optimization. The ultimate challenge, then, is to explain the determination of context. If context is a category, then a natural extension toward addressing this question is higher-order category theory, where categories themselves are the objects of construction. PMID:27524975
-
Systematicity and a Categorical Theory of Cognitive Architecture: Universal Construction in Context.
Phillips, Steven; Wilson, William H
2016-01-01
Why does the capacity to think certain thoughts imply the capacity to think certain other, structurally related, thoughts? Despite decades of intensive debate, cognitive scientists have yet to reach a consensus on an explanation for this property of cognitive architecture-the basic processes and modes of composition that together afford cognitive capacity-called systematicity. Systematicity is generally considered to involve a capacity to represent/process common structural relations among the equivalently cognizable entities. However, the predominant theoretical approaches to the systematicity problem, i.e., classical (symbolic) and connectionist (subsymbolic), require arbitrary (ad hoc) assumptions to derive systematicity. That is, their core principles and assumptions do not provide the necessary and sufficient conditions from which systematicity follows, as required of a causal theory. Hence, these approaches fail to fully explain why systematicity is a (near) universal property of human cognition, albeit in restricted contexts. We review an alternative, category theory approach to the systematicity problem. As a mathematical theory of structure, category theory provides necessary and sufficient conditions for systematicity in the form of universal construction: each systematically related cognitive capacity is composed of a common component and a unique component. Moreover, every universal construction can be viewed as the optimal construction in the given context (category). From this view, universal constructions are derived from learning, as an optimization. The ultimate challenge, then, is to explain the determination of context. If context is a category, then a natural extension toward addressing this question is higher-order category theory, where categories themselves are the objects of construction.
-
Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment
Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...
-
Methods for detecting long-term CNS dysfunction after prenatal exposure to neurotoxins.
Vorhees, C V
1997-11-01
Current U.S. Environmental Protection Agency regulatory guidelines for developmental neurotoxicity emphasize functional categories such as motor activity, auditory startle, and learning and memory. A single test of some simple form of learning and memory is accepted to meet the latter category. The rationale for this emphasis has been that sensitive and reliable methods for assessing complex learning and memory are either not available or are too burdensome, and that insufficient data exist to endorse one approach over another. There has been little discussion of the fact that learning and memory is not a single identifiable functional category and no single test can assess all types of learning and memory. Three methods for assessing complex learning and memory are presented that assess two different types of learning and memory, are relatively efficient to conduct, and are sensitive to several known neurobehavioral teratogens. The tests are a 9-unit multiple-T swimming maze, and the Morris and Barnes mazes. The first of these assesses sequential learning, while the latter two assess spatial learning. A description of each test is provided, along with procedures for their use, and data exemplifying effects obtained using developmental exposure to phenytoin, methamphetamine, and MDMA. It is argued that multiple tests of learning and memory are required to ascertain cognitive deficits; something no single method can accomplish. Methods for acoustic startle are also presented.
-
Ingemansson, Maria; Bastholm-Rahmner, Pia; Kiessling, Anna
2014-08-20
Decision-making is central for general practitioners (GP). Practice guidelines are important tools in this process but implementation of them in the complex context of primary care is a challenge. The purpose of this study was to explore how GPs approach, learn from and use practice guidelines in their day-to-day decision-making process in primary care. A qualitative approach using focus-group interviews was chosen in order to provide in-depth information. The participants were 22 GPs with a median of seven years of experience in primary care, representing seven primary healthcare centres in Stockholm, Sweden in 2011. The interviews focused on how the GPs use guidelines in their decision-making, factors that influence their decision how to approach these guidelines, and how they could encourage the learning process in routine practice.Data were analysed by qualitative content analysis. Meaning units were condensed and grouped in categories. After interpreting the content in the categories, themes were created. Three themes were conceptualized. The first theme emphasized to use guidelines by interactive contextualized dialogues. The categories underpinning this theme: 1. Feedback by peer-learning 2. Feedback by collaboration, mutual learning, and equality between specialties, identified important ways to achieve this learning dialogue. Confidence was central in the second theme, learning that establishes confidence to provide high quality care. Three aspects of confidence were identified in the categories of this theme: 1. Confidence by confirmation, 2. Confidence by reliability and 3. Confidence by evaluation of own results. In the third theme, learning by use of relevant evidence in the decision-making process, we identified two categories: 1. Design and lay-out visualizing the evidence 2. Accessibility adapted to the clinical decision-making process as prerequisites for using the practice guidelines. Decision-making in primary care is a dual process that involves use of intuitive and analytic thinking in a balanced way in order to provide high quality care. Key aspects of effective learning in this clinical decision-making process were: contextualized dialogue, which was based on the GPs' own experiences, feedback on own results and easy access to short guidelines perceived as trustworthy.
-
Thirty years of collaboration with Gabriel Horn.
Bateson, Patrick
2015-03-01
All the collaborative work described in this review was on the process of behavioural imprinting occurring early in the life of domestic chicks. Finding a link between learning and a change in the brain was only a first step in establishing a representation of the imprinting object. A series of overlapping experiments were necessary to eliminate alternative explanations. Once completed, a structure, the intermediate and medial mesopallium (IMM), was found to be strongly linked to the formation of a neural representation of the object used for imprinting the birds. With the site identified, lesion experiments showed that it was necessary for imprinting but not associative learning. Also the two sides of the brain responded differently with the left IMM acting as a permanent store and the right side acting as a way station to other parts of the brain. The collaborative work led to many studies by Gabriel Horn with others on the molecular and cellular bases of imprinting, and also to neural net modelling and behavioural studies with me on the nature of category formation in intact animals. Copyright © 2014 Elsevier Ltd. All rights reserved.
-
Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan
2016-01-01
It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.
-
Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan
2016-01-01
It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning. PMID:27445958
-
Concept mapping learning strategy to enhance students' mathematical connection ability
NASA Astrophysics Data System (ADS)
Hafiz, M.; Kadir, Fatra, Maifalinda
2017-05-01
The concept mapping learning strategy in teaching and learning mathematics has been investigated by numerous researchers. However, there are still less researchers who have scrutinized about the roles of map concept which is connected to the mathematical connection ability. Being well understood on map concept, it may help students to have ability to correlate one concept to other concept in order that the student can solve mathematical problems faced. The objective of this research was to describe the student's mathematical connection ability and to analyze the effect of using concept mapping learning strategy to the students' mathematical connection ability. This research was conducted at senior high school in Jakarta. The method used a quasi-experimental with randomized control group design with the total number was 72 students as the sample. Data obtained through using test in the post-test after giving the treatment. The results of the research are: 1) Students' mathematical connection ability has reached the good enough level category; 2) Students' mathematical connection ability who had taught with concept mapping learning strategy is higher than who had taught with conventional learning strategy. Based on the results above, it can be concluded that concept mapping learning strategycould enhance the students' mathematical connection ability, especially in trigonometry.
-
ERIC Educational Resources Information Center
Ivanova, Tamara N.; Gross, Christina; Mappus, Rudolph C.; Kwon, Yong Jun; Bassell, Gary J.; Liu, Robert C.
2017-01-01
Learning to recognize a stimulus category requires experience with its many natural variations. However, the mechanisms that allow a category's sensorineural representation to be updated after experiencing new exemplars are not well understood, particularly at the molecular level. Here we investigate how a natural vocal category induces expression…
-
Testing the Efficiency of Markov Chain Monte Carlo with People Using Facial Affect Categories
ERIC Educational Resources Information Center
Martin, Jay B.; Griffiths, Thomas L.; Sanborn, Adam N.
2012-01-01
Exploring how people represent natural categories is a key step toward developing a better understanding of how people learn, form memories, and make decisions. Much research on categorization has focused on artificial categories that are created in the laboratory, since studying natural categories defined on high-dimensional stimuli such as…
-
ERIC Educational Resources Information Center
Deng, Wei; Sloutsky, Vladimir M.
2015-01-01
Does category representation change in the course of development? And if so, how and why? The current study attempted to answer these questions by examining category learning and category representation. In Experiment 1, 4-year-olds, 6-year-olds, and adults were trained with either a classification task or an inference task and their…
-
Dimension-Based Statistical Learning Affects Both Speech Perception and Production
ERIC Educational Resources Information Center
Lehet, Matthew; Holt, Lori L.
2017-01-01
Multiple acoustic dimensions signal speech categories. However, dimensions vary in their informativeness; some are more diagnostic of category membership than others. Speech categorization reflects these dimensional regularities such that diagnostic dimensions carry more "perceptual weight" and more effectively signal category membership…
-
Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...
-
Emerging Object Representations in the Visual System Predict Reaction Times for Categorization
Ritchie, J. Brendan; Tovar, David A.; Carlson, Thomas A.
2015-01-01
Recognizing an object takes just a fraction of a second, less than the blink of an eye. Applying multivariate pattern analysis, or “brain decoding”, methods to magnetoencephalography (MEG) data has allowed researchers to characterize, in high temporal resolution, the emerging representation of object categories that underlie our capacity for rapid recognition. Shortly after stimulus onset, object exemplars cluster by category in a high-dimensional activation space in the brain. In this emerging activation space, the decodability of exemplar category varies over time, reflecting the brain’s transformation of visual inputs into coherent category representations. How do these emerging representations relate to categorization behavior? Recently it has been proposed that the distance of an exemplar representation from a categorical boundary in an activation space is critical for perceptual decision-making, and that reaction times should therefore correlate with distance from the boundary. The predictions of this distance hypothesis have been born out in human inferior temporal cortex (IT), an area of the brain crucial for the representation of object categories. When viewed in the context of a time varying neural signal, the optimal time to “read out” category information is when category representations in the brain are most decodable. Here, we show that the distance from a decision boundary through activation space, as measured using MEG decoding methods, correlates with reaction times for visual categorization during the period of peak decodability. Our results suggest that the brain begins to read out information about exemplar category at the optimal time for use in choice behaviour, and support the hypothesis that the structure of the representation for objects in the visual system is partially constitutive of the decision process in recognition. PMID:26107634
-
Minasian-Batmanian, Laura C; Lingard, Jennifer; Prosser, Michael
2005-11-01
Student approaches to learning vary from surface approaches to meaningful, deep learning practices. Differences in approach may be related to students' conceptions of the subject, perceptions of the learning environment, prior study experiences and performance on assessment. This study aims to explore entering students' conceptions of the unit they are about to study and how they intend to approach their studies. It involved a survey of 203 (of 250) first year students in a cross disciplinary unit in the Faculty of Health Sciences. They were asked to complete an open-ended response survey, including questions on what they thought they needed to do to learn biochemistry and what they thought the study of biochemistry was about. A phenomenographic methodology was used to identify categories of description for the questions. The paper will describe the categories in detail, the structural relationship between the categories and the distribution of responses within categories. The study reports a relationship between conception of the topic and approaches to learning. Students with more complex and coherent conceptions of the topic report that they were more likely to adopt deeper approaches to study than those with more fragmented conceptions. However, compared to previous studies, a surprisingly high proportion of students with more cohesive conceptions still intended to adopt more surface approaches. This may reflect the particular context of their learning, namely in a compulsory unit involving material for which most students have minimal background and difficulty seeing its relevance. Implications for teaching such foundation material are discussed.
-
Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina
2012-01-01
Functional MRI studies have uncovered a number of brain areas that demonstrate highly specific functional patterns. In the case of visual object recognition, small, focal regions have been characterized with selectivity for visual categories such as human faces. In this paper, we develop an algorithm that automatically learns patterns of functional specificity from fMRI data in a group of subjects. The method does not require spatial alignment of functional images from different subjects. The algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to learn the patterns of functional specificity shared across the group, which we call functional systems, and estimate the number of these systems. Inference based on our model enables automatic discovery and characterization of dominant and consistent functional systems. We apply the method to data from a visual fMRI study comprised of 69 distinct stimulus images. The discovered system activation profiles correspond to selectivity for a number of image categories such as faces, bodies, and scenes. Among systems found by our method, we identify new areas that are deactivated by face stimuli. In empirical comparisons with perviously proposed exploratory methods, our results appear superior in capturing the structure in the space of visual categories of stimuli. PMID:21884803
-
The Use of Category Information by 2- and 3-Year-Olds.
ERIC Educational Resources Information Center
Dunn, Lynne Anne
This study examined the ability of preschool children to process and use conceptual category information in a disrcimination learning task. A total of 60 boys and girls between the ages of 2 1/2 and 4 years completed a 3-choice discrimination learning task. On each of 12 trials, a child was presented with three magazine photographs: one of an…
-
ERIC Educational Resources Information Center
Bucks County Public Schools, Doylestown, PA.
Categories of effective and ineffective behavior in regard to Goal Four of the Quality Education Program (regarding interest in school and learning) are listed. Both the rationales for areas of effective student behavior and the categories of teacher strategies are also included. (See TM 001 375 for project description.) (MS)
-
ERIC Educational Resources Information Center
Mercado, Eduardo, III; Church, Barbara A.
2016-01-01
Children with autism spectrum disorder (ASD) sometimes have difficulties learning categories. Past computational work suggests that such deficits may result from atypical representations in cortical maps. Here we use neural networks to show that idiosyncratic transformations of inputs can result in the formation of feature maps that impair…
-
ERIC Educational Resources Information Center
Wilburn, Catherine; Feeney, Aidan
2008-01-01
In a recently published study, Sloutsky and Fisher [Sloutsky, V. M., & Fisher, A.V. (2004a). When development and learning decrease memory: Evidence against category-based induction in children. "Psychological Science", 15, 553-558; Sloutsky, V. M., & Fisher, A. V. (2004b). Induction and categorization in young children: A similarity-based model.…
-
Choi, Joon Yul; Yoo, Tae Keun; Seo, Jeong Gi; Kwak, Jiyong; Um, Terry Taewoong; Rim, Tyler Hyungtaek
2017-01-01
Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has emerged as a new method. We applied deep learning convolutional neural network by using MatConvNet for an automated detection of multiple retinal diseases with fundus photographs involved in STructured Analysis of the REtina (STARE) database. Dataset was built by expanding data on 10 categories, including normal retina and nine retinal diseases. The optimal outcomes were acquired by using a random forest transfer learning based on VGG-19 architecture. The classification results depended greatly on the number of categories. As the number of categories increased, the performance of deep learning models was diminished. When all 10 categories were included, we obtained results with an accuracy of 30.5%, relative classifier information (RCI) of 0.052, and Cohen's kappa of 0.224. Considering three integrated normal, background diabetic retinopathy, and dry age-related macular degeneration, the multi-categorical classifier showed accuracy of 72.8%, 0.283 RCI, and 0.577 kappa. In addition, several ensemble classifiers enhanced the multi-categorical classification performance. The transfer learning incorporated with ensemble classifier of clustering and voting approach presented the best performance with accuracy of 36.7%, 0.053 RCI, and 0.225 kappa in the 10 retinal diseases classification problem. First, due to the small size of datasets, the deep learning techniques in this study were ineffective to be applied in clinics where numerous patients suffering from various types of retinal disorders visit for diagnosis and treatment. Second, we found that the transfer learning incorporated with ensemble classifiers can improve the classification performance in order to detect multi-categorical retinal diseases. Further studies should confirm the effectiveness of algorithms with large datasets obtained from hospitals.
-
Beyond common features: The role of roles in determining similarity1
Jones, Matt; Love, Bradley C.
2007-01-01
Historically, accounts of object representation and perceived similarity have focused on intrinsic features. Although more recent accounts have explored how objects, scenes, and situations containing common relational structures come to be perceived as similar, less is known about how the perceived similarity of parts or objects embedded within these relational systems is affected. The current studies test the hypothesis that objects situated in common relational systems come to be perceived as more similar. Similarity increases most for objects playing the same role within a relation (e.g., predator), but also increases for objects playing different roles within the same relation (e.g., the predator or prey role in the hunts relation) regardless of whether the objects participate in the same instance of the relation. This pattern of results can be captured by extending existing models that extract meaning from text corpora so that they are sensitive to the verb-specific thematic roles that objects fill. Alternative explanations based on analogical and inferential processes are also considered, as well as the implications of the current findings to research in language processing, personality and person perception, decision making, and category learning. PMID:17094958
-
An evaluation of training of teachers in medical education in four medical schools of Nepal.
Baral, Nirmal; Paudel, Bishnu Hari; Das, Binod Kumar Lal; Aryal, Madhukar; Das, Balbhadra Prasad; Jha, Nilambar; Lamsal, Madhab
2007-09-01
Effective teaching is a concern of all teachers. Therefore, regular teachers' training is emphasized globally. B. P. Koirala Institute of Health Sciences (BPKIHS), a health science deemed university situated in eastern region of Nepal has an established Medical Education unit which attempts to improve teaching-learning skills by training faculty members through organizing regular medical education training programs. The aim of the present study was to assess the effectiveness of 3-day training workshop on "Teaching-learning methodology and Evaluation" held in four different medical colleges of Nepal. The workshop was targeted at middle and entry level of health profession teachers who had not been previously exposed to any teacher's training program. The various components, such as teaching-learning principles, writing educational objectives, organizing and sequencing education materials, teaching-learning methods, microteaching and assessment techniques, were incorporated in the workshop. A team of resource persons from BPKIHS were involved in all the four medical institutions. The collection data had two categories of responses: (1) a questionnaire survey of participants at the beginning and end of the workshop to determine their gain in knowledge and (2) a semi-structured questionnaire survey of participants at the end of workshop to evaluate their perception on usefulness of the workshop. The later category had items with three-point likert scale (very useful, useful and not useful) and responses to open-ended questions/ statements to document participants general views. The response was entered into a spreadsheet and analyzed using SPSS. The result showed that all participants (n = 92) improved their scores after attending the workshop (p < 0.001). Majority of respondents expressed that the teaching-learning methods, media, microteaching and evaluation techniques were useful in teaching-learning. The workshop was perceived as an acceptable way of acquiring teaching-learning skills but 39.4% participants expressed that the duration of the workshop was too short. The overall impression about trainers was very positive. Therefore, regular organization of such workshops with addition of new advances in medical education would be highly beneficial to improve teaching learning skill of medical teachers.
-
Both younger and older adults have difficulty updating emotional memories.
Nashiro, Kaoru; Sakaki, Michiko; Huffman, Derek; Mather, Mara
2013-03-01
The main purpose of the study was to examine whether emotion impairs associative memory for previously seen items in older adults, as previously observed in younger adults. Thirty-two younger adults and 32 older adults participated. The experiment consisted of 2 parts. In Part 1, participants learned picture-object associations for negative and neutral pictures. In Part 2, they learned picture-location associations for negative and neutral pictures; half of these pictures were seen in Part 1 whereas the other half were new. The dependent measure was how many locations of negative versus neutral items in the new versus old categories participants remembered in Part 2. Both groups had more difficulty learning the locations of old negative pictures than of new negative pictures. However, this pattern was not observed for neutral items. Despite the fact that older adults showed overall decline in associative memory, the impairing effect of emotion on updating associative memory was similar between younger and older adults.
-
Model-based choices involve prospective neural activity
Doll, Bradley B.; Duncan, Katherine D.; Simon, Dylan A.; Shohamy, Daphna; Daw, Nathaniel D.
2015-01-01
Decisions may arise via “model-free” repetition of previously reinforced actions, or by “model-based” evaluation, which is widely thought to follow from prospective anticipation of action consequences using a learned map or model. While choices and neural correlates of decision variables sometimes reflect knowledge of their consequences, it remains unclear whether this actually arises from prospective evaluation. Using functional MRI and a sequential reward-learning task in which paths contained decodable object categories, we found that humans’ model-based choices were associated with neural signatures of future paths observed at decision time, suggesting a prospective mechanism for choice. Prospection also covaried with the degree of model-based influences on neural correlates of decision variables, and was inversely related to prediction error signals thought to underlie model-free learning. These results dissociate separate mechanisms underlying model-based and model-free evaluation and support the hypothesis that model-based influences on choices and neural decision variables result from prospection. PMID:25799041
-
He, Angela Xiaoxue; Arunachalam, Sudha
2017-07-01
How do children acquire the meanings of words? Many word learning mechanisms have been proposed to guide learners through this challenging task. Despite the availability of rich information in the learner's linguistic and extralinguistic input, the word-learning task is insurmountable without such mechanisms for filtering through and utilizing that information. Different kinds of words, such as nouns denoting object concepts and verbs denoting event concepts, require to some extent different kinds of information and, therefore, access to different kinds of mechanisms. We review some of these mechanisms to examine the relationship between the input that is available to learners and learners' intake of that input-that is, the organized, interpreted, and stored representations they form. We discuss how learners segment individual words from the speech stream and identify their grammatical categories, how they identify the concepts denoted by these words, and how they refine their initial representations of word meanings. WIREs Cogn Sci 2017, 8:e1435. doi: 10.1002/wcs.1435 This article is categorized under: Linguistics > Language Acquisition Psychology > Language. © 2017 Wiley Periodicals, Inc.
-
Langheinrich, Jessica; Bogner, Franz X
2015-01-01
As non-scientific conceptions interfere with learning processes, teachers need both, to know about them and to address them in their classrooms. For our study, based on 182 eleventh graders, we analyzed the level of conceptual understanding by implementing the "draw and write" technique during a computer-supported gene technology module. To give participants the hierarchical organizational level which they have to draw, was a specific feature of our study. We introduced two objective category systems for analyzing drawings and inscriptions. Our results indicated a long- as well as a short-term increase in the level of conceptual understanding and in the number of drawn elements and their grades concerning the DNA structure. Consequently, we regard the "draw and write" technique as a tool for a teacher to get to know students' alternative conceptions. Furthermore, our study points the modification potential of hands-on and computer-supported learning modules. © 2015 The International Union of Biochemistry and Molecular Biology.
-
Framework for Conducting Empirical Observations of Learning Processes.
ERIC Educational Resources Information Center
Fischer, Hans Ernst; von Aufschnaiter, Stephan
1993-01-01
Reviews four hypotheses about learning: Comenius's transmission-reception theory, information processing theory, Gestalt theory, and Piagetian theory. Uses the categories preunderstanding, conceptual change, and learning processes to classify and assess investigations on learning processes. (PR)
-
Learning in Mental Retardation: A Comprehensive Bibliography.
ERIC Educational Resources Information Center
Gardner, James M.; And Others
The bibliography on learning in mentally handicapped persons is divided into the following topic categories: applied behavior change, classical conditioning, discrimination, generalization, motor learning, reinforcement, verbal learning, and miscellaneous. An author index is included. (KW)
-
A New Zero-Inflated Negative Binomial Methodology for Latent Category Identification
ERIC Educational Resources Information Center
Blanchard, Simon J.; DeSarbo, Wayne S.
2013-01-01
We introduce a new statistical procedure for the identification of unobserved categories that vary between individuals and in which objects may span multiple categories. This procedure can be used to analyze data from a proposed sorting task in which individuals may simultaneously assign objects to multiple piles. The results of a synthetic…
-
ERIC Educational Resources Information Center
Weisberg, Paul
2003-01-01
Six preschool children, mostly from poverty-level backgrounds, were taught to make descriptive statements about objects. The category-descriptor statements were organized and sequenced into four clusters. As sets of new statements were successively taught and evaluated, the number and diversity of probed category and descriptor terms steadily and…
-
Encodings of implied motion for animate and inanimate object categories in the two visual pathways.
Lu, Zhengang; Li, Xueting; Meng, Ming
2016-01-15
Previous research has proposed two separate pathways for visual processing: the dorsal pathway for "where" information vs. the ventral pathway for "what" information. Interestingly, the middle temporal cortex (MT) in the dorsal pathway is involved in representing implied motion from still pictures, suggesting an interaction between motion and object related processing. However, the relationship between how the brain encodes implied motion and how the brain encodes object/scene categories is unclear. To address this question, fMRI was used to measure activity along the two pathways corresponding to different animate and inanimate categories of still pictures with different levels of implied motion speed. In the visual areas of both pathways, activity induced by pictures of humans and animals was hardly modulated by the implied motion speed. By contrast, activity in these areas correlated with the implied motion speed for pictures of inanimate objects and scenes. The interaction between implied motion speed and stimuli category was significant, suggesting different encoding mechanisms of implied motion for animate-inanimate distinction. Further multivariate pattern analysis of activity in the dorsal pathway revealed significant effects of stimulus category that are comparable to the ventral pathway. Moreover, still pictures of inanimate objects/scenes with higher implied motion speed evoked activation patterns that were difficult to differentiate from those evoked by pictures of humans and animals, indicating a functional role of implied motion in the representation of object categories. These results provide novel evidence to support integrated encoding of motion and object categories, suggesting a rethink of the relationship between the two visual pathways. Copyright © 2015 Elsevier Inc. All rights reserved.
-
A new zero-inflated negative binomial methodology for latent category identification.
Blanchard, Simon J; DeSarbo, Wayne S
2013-04-01
We introduce a new statistical procedure for the identification of unobserved categories that vary between individuals and in which objects may span multiple categories. This procedure can be used to analyze data from a proposed sorting task in which individuals may simultaneously assign objects to multiple piles. The results of a synthetic example and a consumer psychology study involving categories of restaurant brands illustrate how the application of the proposed methodology to the new sorting task can account for a variety of categorization phenomena including multiple category memberships and for heterogeneity through individual differences in the saliency of latent category structures.
-
Category Learning in the Brain
Seger, Carol A.; Miller, Earl K.
2013-01-01
The ability to group items and events into functional categories is a fundamental characteristic of sophisticated thought. It is subserved by plasticity in many neural systems, including neocortical regions (sensory, prefrontal, parietal, and motor cortex), the medial temporal lobe, the basal ganglia, and midbrain dopaminergic systems. These systems interact during category learning. Corticostriatal loops may mediate recursive, bootstrapping interactions between fast reward-gated plasticity in the basal ganglia and slow reward-shaded plasticity in the cortex. This can provide a balance between acquisition of details of experiences and generalization across them. Interactions between the corticostriatal loops can integrate perceptual, response, and feedback-related aspects of the task and mediate the shift from novice to skilled performance. The basal ganglia and medial temporal lobe interact competitively or cooperatively, depending on the demands of the learning task. PMID:20572771
-
Barnard-Ashton, Paula; Rothberg, Alan; McInerney, Patricia
2017-08-17
This paper presents a critical reflection of the integration of Blended Learning (BL) into an undergraduate occupational therapy curriculum which was delivered through Problem Based Learning (PBL). This is a qualitative reflection of a Participatory Action Research (PAR) study using Brookfield's model for critical reflection of an educator's practice. The model uses four 'lenses' through which to focus enquiry: Lens 1) our autobiography as a learner of practice; Lens 2) our learners' eyes; Lens 3) our colleagues' experiences; and Lens 4) the theoretical literature. Grounded theory analysis was applied to the data. The factors that contributed to successful integration of technology and e-Learning into an existing curriculum, the hurdles that were navigated along the way, and how these influenced decisions and innovation are explored. The core categories identified in the data were "drivers of change" and "outcomes of BL integration". Key situations and pivotal events are highlighted for their role in the process that led to the project maturing. Each lens reflects the successes and hurdles experienced during the study. Brookfield's model provides an objective method of reflection which showed that despite the hurdles, e-Learning was successfully integrated into the curriculum.
-
Influence of Emotionally Charged Information on Category-Based Induction
Zhu, Jennifer; Murphy, Gregory L.
2013-01-01
Categories help us make predictions, or inductions, about new objects. However, we cannot always be certain that a novel object belongs to the category we are using to make predictions. In such cases, people should use multiple categories to make inductions. Past research finds that people often use only the most likely category to make inductions, even if it is not certain. In two experiments, subjects read stories and answered questions about items whose categorization was uncertain. In Experiment 1, the less likely category was either emotionally neutral or dangerous (emotionally charged or likely to pose a threat). Subjects used multiple categories in induction when one of the categories was dangerous but not when they were all neutral. In Experiment 2, the most likely category was dangerous. Here, people used multiple categories, but there was also an effect of avoidance, in which people denied that dangerous categories were the most likely. The attention-grabbing power of dangerous categories may be balanced by a higher-level strategy to reject them. PMID:23372700
-
Jiang, Xiong; Chevillet, Mark A; Rauschecker, Josef P; Riesenhuber, Maximilian
2018-04-18
Grouping auditory stimuli into common categories is essential for a variety of auditory tasks, including speech recognition. We trained human participants to categorize auditory stimuli from a large novel set of morphed monkey vocalizations. Using fMRI-rapid adaptation (fMRI-RA) and multi-voxel pattern analysis (MVPA) techniques, we gained evidence that categorization training results in two distinct sets of changes: sharpened tuning to monkey call features (without explicit category representation) in left auditory cortex and category selectivity for different types of calls in lateral prefrontal cortex. In addition, the sharpness of neural selectivity in left auditory cortex, as estimated with both fMRI-RA and MVPA, predicted the steepness of the categorical boundary, whereas categorical judgment correlated with release from adaptation in the left inferior frontal gyrus. These results support the theory that auditory category learning follows a two-stage model analogous to the visual domain, suggesting general principles of perceptual category learning in the human brain. Copyright © 2018 Elsevier Inc. All rights reserved.
-
Teaching children with autism spectrum disorder to tact olfactory stimuli.
Dass, Tina K; Kisamore, April N; Vladescu, Jason C; Reeve, Kenneth F; Reeve, Sharon A; Taylor-Santa, Catherine
2018-05-28
Research on tact acquisition by children with autism spectrum disorder (ASD) has often focused on teaching participants to tact visual stimuli. It is important to evaluate procedures for teaching tacts of nonvisual stimuli (e.g., olfactory, tactile). The purpose of the current study was to extend the literature on secondary target instruction and tact training by evaluating the effects of a discrete-trial instruction procedure involving (a) echoic prompts, a constant prompt delay, and error correction for primary targets; (b) inclusion of secondary target stimuli in the consequent portion of learning trials; and (c) multiple exemplar training on the acquisition of item tacts of olfactory stimuli, emergence of category tacts of olfactory stimuli, generalization of category tacts, and emergence of category matching, with three children diagnosed with ASD. Results showed that all participants learned the item and category tacts following teaching, participants demonstrated generalization across category tacts, and category matching emerged for all participants. © 2018 Society for the Experimental Analysis of Behavior.
-
The home care teaching and learning process in undergraduate health care degree courses.
Hermann, Ana Paula; Lacerda, Maria Ribeiro; Maftum, Mariluci Alves; Bernardino, Elizabeth; Mello, Ana Lúcia Schaefer Ferreira de
2017-07-01
Home care, one of the services provided by the health system, requires health practitioners who are capable of understanding its specificities. This study aimed to build a substantive theory that describes experiences of home care teaching and learning during undergraduate degree courses in nursing, pharmacy, medicine, nutrition, dentistry and occupational therapy. A qualitative analysis was performed using the grounded theory approach based on the results of 63 semistructured interviews conducted with final year students, professors who taught subjects related to home care, and recent graduates working with home care, all participants in the above courses. The data was analyzed in three stages - open coding, axial coding and selective coding - resulting in the phenomenon Experiences of home care teaching and learning during the undergraduate health care degree courses. Its causes were described in the category Articulating knowledge of home care, strategies in the category Experiencing the unique nature of home care, intervening conditions in the category Understanding the multidimensional characteristics of home care, consequences in the category Changing thinking about home care training, and context in the category Understanding home care in the health system. Home care contributes towards the decentralization of hospital care.
-
NASA Astrophysics Data System (ADS)
Zuhaida, A.
2018-04-01
Implementation of the experiment have the three aspects of the goal: 1) develop basic skills of experimenting; 2) develop problem-solving skills with a scientific approach; 3) improve understanding of the subject matter. On the implementation of the experiment, students have some weaknesses include: observing, identifying problems, managing information, analyzing, and evaluating. This weakness is included in the metacognition indicator.The objective of the research is to implementation of Basic Chemistry Experiment based on metacognition to increase problem-solving skills and build concept understanding for students of Science Education Department. The method of this research is a quasi- experimental method with pretest-posttest control group design. Problem-solving skills are measured through performance assessments using rubrics from problem solving reports, and results presentation. The conceptual mastery is measured through a description test. The result of the research: (1) improve the problem solving skills of the students with very high category; (2) increase the students’ concept understanding better than the conventional experiment with the result of N-gain in medium category, and (3) increase student's response positively for learning implementation. The contribution of this research is to extend the implementation of practical learning for some subjects, and to improve the students' competence in science.
-
Deficits in Category Learning in Older Adults: Rule-Based Versus Clustering Accounts
2017-01-01
Memory research has long been one of the key areas of investigation for cognitive aging researchers but only in the last decade or so has categorization been used to understand age differences in cognition. Categorization tasks focus more heavily on the grouping and organization of items in memory, and often on the process of learning relationships through trial and error. Categorization studies allow researchers to more accurately characterize age differences in cognition: whether older adults show declines in the way in which they represent categories with simple rules or declines in representing categories by similarity to past examples. In the current study, young and older adults participated in a set of classic category learning problems, which allowed us to distinguish between three hypotheses: (a) rule-complexity: categories were represented exclusively with rules and older adults had differential difficulty when more complex rules were required, (b) rule-specific: categories could be represented either by rules or by similarity, and there were age deficits in using rules, and (c) clustering: similarity was mainly used and older adults constructed a less-detailed representation by lumping more items into fewer clusters. The ordinal levels of performance across different conditions argued against rule-complexity, as older adults showed greater deficits on less complex categories. The data also provided evidence against rule-specificity, as single-dimensional rules could not explain age declines. Instead, computational modeling of the data indicated that older adults utilized fewer conceptual clusters of items in memory than did young adults. PMID:28816474
-
Same Items, Different Order: Effects of Temporal Variability on Infant Categorization
ERIC Educational Resources Information Center
Mather, Emily; Plunkett, Kim
2011-01-01
How does variability between members of a category influence infants' category learning? We explore the impact of the order in which different items are sampled on category formation. Two groups of 10-months-olds were presented with a series of exemplars to be organized into a single category. In a low distance group, the order of presentation…
-
Unsupervised active learning based on hierarchical graph-theoretic clustering.
Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve
2009-10-01
Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.
-
Ways of dealing with science learning: a study based on Swedish early childhood education practice
NASA Astrophysics Data System (ADS)
Gustavsson, Laila; Jonsson, Agneta; Ljung-Djärf, Agneta; Thulin, Susanne
2016-07-01
The Swedish school system offers curriculum-based early childhood education (ECE) organised as preschool (for 0-5-year-olds) and preschool class (for 6-year-olds). The intention to create a playful and educational environment based on children's perspectives, interests, and questions is strongly based on historical and cultural traditions. This article develops knowledge of ECE teachers' approaches to science-learning situations. The study applies a phenomenographic approach. The analysis is based on approximately 9.5 hours of video documentation of teacher-led and child-initiated Swedish ECE science activities. We identified two descriptive categories and four subcategories dealing with science-learning situations: (A) making anything visible, containing the three subcategories (Aa) addressing everyone, (Ab) addressing everything, and (Ac) addressing play and fantasy; and (B) creating a shared space for learning (Ba) addressing common content. These categories are related to how efforts to take advantage of children's perspectives are interpreted and addressed in educational practice. The article discusses and exemplifies the use of various categories and their potential implications for ECE learning practice.
-
Similarity relations in visual search predict rapid visual categorization
Mohan, Krithika; Arun, S. P.
2012-01-01
How do we perform rapid visual categorization?It is widely thought that categorization involves evaluating the similarity of an object to other category items, but the underlying features and similarity relations remain unknown. Here, we hypothesized that categorization performance is based on perceived similarity relations between items within and outside the category. To this end, we measured the categorization performance of human subjects on three diverse visual categories (animals, vehicles, and tools) and across three hierarchical levels (superordinate, basic, and subordinate levels among animals). For the same subjects, we measured their perceived pair-wise similarities between objects using a visual search task. Regardless of category and hierarchical level, we found that the time taken to categorize an object could be predicted using its similarity to members within and outside its category. We were able to account for several classic categorization phenomena, such as (a) the longer times required to reject category membership; (b) the longer times to categorize atypical objects; and (c) differences in performance across tasks and across hierarchical levels. These categorization times were also accounted for by a model that extracts coarse structure from an image. The striking agreement observed between categorization and visual search suggests that these two disparate tasks depend on a shared coarse object representation. PMID:23092947
-
A neurocomputational account of taxonomic responding and fast mapping in early word learning.
Mayor, Julien; Plunkett, Kim
2010-01-01
We present a neurocomputational model with self-organizing maps that accounts for the emergence of taxonomic responding and fast mapping in early word learning, as well as a rapid increase in the rate of acquisition of words observed in late infancy. The quality and efficiency of generalization of word-object associations is directly related to the quality of prelexical, categorical representations in the model. We show how synaptogenesis supports coherent generalization of word-object associations and show that later synaptic pruning minimizes metabolic costs without being detrimental to word learning. The role played by joint-attentional activities is identified in the model, both at the level of selecting efficient cross-modal synapses and at the behavioral level, by accelerating and refining overall vocabulary acquisition. The model can account for the qualitative shift in the way infants use words, from an associative to a referential-like use, for the pattern of overextension errors in production and comprehension observed during early childhood and typicality effects observed in lexical development. Interesting by-products of the model include a potential explanation of the shift from prototype to exemplar-based effects reported for adult category formation, an account of mispronunciation effects in early lexical development, and extendability to include accounts of individual differences in lexical development and specific disorders such as Williams syndrome. The model demonstrates how an established constraint on lexical learning, which has often been regarded as domain-specific, can emerge from domain-general learning principles that are simultaneously biologically, psychologically, and socially plausible.
-
Categories and Music Transmission
ERIC Educational Resources Information Center
Gatien, Greg
2009-01-01
Lucy Green's (2008) "Music, Informal Learning, and the School: A New Classroom Pedagogy" gives rise to an interesting corollary. Does the manner of music's transmission inform one's understanding of a musical category? While categories of music can be difficult to define according to strict musical characteristics, a better understanding of…
-
Phoenix Violence Prevention Initiative.
ERIC Educational Resources Information Center
Waits, Mary Jo; Johnson, Ryan; Silverstein, Rustin
This report describes seven categories of violent crime in Phoenix, Arizona, and provides causes, facts, preventative programs, and lessons learned pertaining to each category of violence. The categories are: (1) prenatal and early childhood; (2) families; (3) individual youth; (4) schools; (5) neighborhood and community; (6) workplace; and (7)…
-
ERIC Educational Resources Information Center
Chou, Pao-Nan; Chang, Chi-Cheng
2011-01-01
This study examines the effects of reflection category and reflection quality on learning outcomes during Web-based portfolio assessment process. Experimental subjects consist of forty-five eight-grade students in a "Computer Application" course. Through the Web-based portfolio assessment system, these students write reflection, and join…
-
ERIC Educational Resources Information Center
Fazeli, Seyed Hossein
2012-01-01
This study aims to rank types of English language learning strategies that are used by Iranian female university level learners of English language as a university major. The results show that except for the Metacognitive Strategies category, the mean score for each of the five categories fell in the range of medium strategy use.
-
Auditory-visual object recognition time suggests specific processing for animal sounds.
Suied, Clara; Viaud-Delmon, Isabelle
2009-01-01
Recognizing an object requires binding together several cues, which may be distributed across different sensory modalities, and ignoring competing information originating from other objects. In addition, knowledge of the semantic category of an object is fundamental to determine how we should react to it. Here we investigate the role of semantic categories in the processing of auditory-visual objects. We used an auditory-visual object-recognition task (go/no-go paradigm). We compared recognition times for two categories: a biologically relevant one (animals) and a non-biologically relevant one (means of transport). Participants were asked to react as fast as possible to target objects, presented in the visual and/or the auditory modality, and to withhold their response for distractor objects. A first main finding was that, when participants were presented with unimodal or bimodal congruent stimuli (an image and a sound from the same object), similar reaction times were observed for all object categories. Thus, there was no advantage in the speed of recognition for biologically relevant compared to non-biologically relevant objects. A second finding was that, in the presence of a biologically relevant auditory distractor, the processing of a target object was slowed down, whether or not it was itself biologically relevant. It seems impossible to effectively ignore an animal sound, even when it is irrelevant to the task. These results suggest a specific and mandatory processing of animal sounds, possibly due to phylogenetic memory and consistent with the idea that hearing is particularly efficient as an alerting sense. They also highlight the importance of taking into account the auditory modality when investigating the way object concepts of biologically relevant categories are stored and retrieved.
-
NASA Technical Reports Server (NTRS)
Xu, Kuan-Man; Wong, Takmeng; Wielicki, Bruce a.; Parker, Lindsay; Lin, Bing; Eitzen, Zachary A.; Branson, Mark
2006-01-01
Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January-August 1998 are examined using the Tropical Rainfall Measuring Mission/ Clouds and the Earth s Radiant Energy System single scanner footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud-object size, sea surface temperature (SST), and satellite precessing cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the Earth composed of satellite footprints within a single dominant cloud-system type. It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100 - 150 km (small), 150 - 300 km (medium), and > 300 km (large), respectively, except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed towards high SSTs, high cloud tops, low cloud-top temperature, large ice water path, high cloud optical depth, low outgoing longwave (LW) radiation, and high albedo than the smaller-size category. As SST varied from one satellite precessing cycle to another, the changes in macrophysical properties of cloud objects over the entire tropical Pacific were small for the large-size category of cloud objects, relative to those of the small- and medium-size categories. This result suggests that the fixed anvil temperature hypothesis of Hartmann and Larson may be valid for the large-size category. Combining with the result that a higher percentage of the large-size category of cloud objects occurs during higher SST subperiods, this implies that macrophysical properties of cloud objects would be less sensitive to further warming of the climate. On the other hand, when cloud objects are classified according to SSTs where large-scale dynamics plays important roles, statistical characteristics of cloud microphysical properties, optical depth and albedo are not sensitive to the SST, but those of cloud macrophysical properties are strongly dependent upon the SST. Frequency distributions of vertical velocity from the European Center for Medium-range Weather Forecasts model that is matched to each cloud object are used to interpret some of the findings in this study.
-
[Categorization in infancy: differentiation of global object classes].
Pauen, S
1996-01-01
Two studies tested whether preverbal children distinguish global categories (animal and furniture) on a conceptual basis. A total of 59 eleven-month-olds solved an object examination task. During habituation, infants freely explored different natural-looking toy models from the same category. In Study 1, the same series of four different examplars was presented twice. In Study 2, ten different exemplares were presented. In both cases, a significant habituation effect could be observed. When a perceptually new object of the same category was presented on the first test trial after habituation, a significant increase in examination time from the last habituation trial to the first test trial could be observed in Study 1. When a new object of the contrasting category was presented on the second test trial, examination times increased significantly from the first to the second test trial in both studies. These results support earlier findings suggesting that preverbal infants are able to distinguish global categories on a conceptual basis.
-
Bennett, Marc P.; Meulders, Ann; Baeyens, Frank; Vlaeyen, Johan W. S.
2015-01-01
Patients with chronic pain are often fearful of movements that never featured in painful episodes. This study examined whether a neutral movement’s conceptual relationship with pain-relevant stimuli could precipitate pain-related fear; a process known as symbolic generalization. As a secondary objective, we also compared experiential and verbal fear learning in the generalization of pain-related fear. We conducted an experimental study with 80 healthy participants who were recruited through an online experimental management system (Mage = 23.04 years, SD = 6.80 years). First, two artificial categories were established wherein nonsense words and joystick arm movements were equivalent. Using a between-groups design, nonsense words from one category were paired with either an electrocutaneous stimulus (pain-US) or threatening information, while nonsense words from the other category were paired with no pain-US or safety information. During a final testing phase, participants were prompted to perform specific joystick arm movements that were never followed by a pain-US, although they were informed that it could occur. The results showed that movements equivalent to the pain-relevant nonsense words evoked heightened pain-related fear as measured by pain-US expectancy, fear of pain, and unpleasantness ratings. Also, experience with the pain-US evinced stronger acquisition and generalization compared to experience with threatening information. The clinical importance and theoretical implications of these findings are discussed. PMID:25983704
-
Collaborative project-based learning: an integrative science and technological education project
NASA Astrophysics Data System (ADS)
Baser, Derya; Ozden, M. Yasar; Karaarslan, Hasan
2017-04-01
Background: Blending collaborative learning and project-based learning (PBL) based on Wolff (2003) design categories, students interacted in a learning environment where they developed their technology integration practices as well as their technological and collaborative skills.