Learning and cognition in insects.

PubMed

Giurfa, Martin

2015-01-01

Insects possess small brains but exhibit sophisticated behavioral performances. Recent works have reported the existence of unsuspected cognitive capabilities in various insect species, which go beyond the traditional studied framework of simple associative learning. In this study, I focus on capabilities such as attention, social learning, individual recognition, concept learning, and metacognition, and discuss their presence and mechanistic bases in insects. I analyze whether these behaviors can be explained on the basis of elemental associative learning or, on the contrary, require higher-order explanations. In doing this, I highlight experimental challenges and suggest future directions for investigating the neurobiology of higher-order learning in insects, with the goal of uncovering l architectures underlying cognitive processing. © 2015 John Wiley & Sons, Ltd.

EYEBLINK CONDITIONING IN THE INFANT RAT: AN ANIMAL MODEL OF LEARNING IN DEVELOPMENTAL NEUROTOXICOLOGY

EPA Science Inventory

Classical conditioning of the eyeblink reflex is a relatively simple procedure for studying associative learning that was first developed for use with human subjects more than half a century ago. The use of this procedure in laboratory animals by psychologists and neuro-scientist...

The influence of CS-US interval on several different indices of learning in appetitive conditioning

PubMed Central

Delamater, Andrew R.; Holland, Peter C.

2010-01-01

Four experiments examined the effects of varying the CS-US interval (and US density) on learning in an appetitive magazine approach task with rats. Learning was assessed with conditioned response (CR) measures, as well as measures of sensory-specific stimulus-outcome associations (Pavlovian-instrumental transfer, potentiated feeding, and US devaluation). The results from these studies indicate that there exists an inverse relation between CS-US interval and magazine approach CRs, but that sensory-specific stimulus-outcome associations are established over a wide range of relatively long, but not short, CS-US intervals. These data suggest that simple CR measures provide us with different information about what is learned than measures of the specific stimulus-outcome association, and that time is a more critical variable for the former than latter component of learning. PMID:18426304

Using variability to guide dimensional weighting: Associative mechanisms in early word learning

PubMed Central

Apfelbaum, Keith S.; McMurray, Bob

2013-01-01

At 14 months, children appear to struggle to apply their fairly well developed speech perception abilities to learning similar sounding words (e.g. bih/dih; Stager & Werker, 1997). However, variability in non-phonetic aspects of the training stimuli seems to aid word learning at this age. Extant theories of early word learning cannot account for this benefit of variability. We offer a simple explanation for this range of effects based on associative learning. Simulations suggest that if infants encode both non-contrastive information (e.g. cues to speaker voice) and meaningful linguistic cues (e.g. place of articulation or voicing), then associative learning mechanisms predict these variability effects in early word learning. Crucially, this means that despite the importance of task variables in predicting performance, this body of work shows that phonological categories are still developing in this age, and that the structure of non-informative cues has critical influences on word learning abilities. PMID:21609356

Elemental or contextual? It depends: individual difference in the hippocampal dependence of associative learning for a simple sensory stimulus

PubMed Central

Lee, Kyung J.; Park, Seong-Beom; Lee, Inah

2014-01-01

Learning theories categorize learning systems into elemental and contextual systems, the former being processed by non-hippocampal regions and the latter being processed in the hippocampus. A set of complex stimuli such as a visual background is often considered a contextual stimulus and simple sensory stimuli such as pure tone and light are considered elemental stimuli. However, this elemental-contextual categorization scheme has only been tested in limited behavioral paradigms and it is largely unknown whether it can be generalized across different learning situations. By requiring rats to respond differently to a common object in association with various types of sensory cues including contextual and elemental stimuli, we tested whether different types of elemental and contextual sensory stimuli depended on the hippocampus to different degrees. In most rats, a surrounding visual background and a tactile stimulus served as contextual (hippocampal dependent) and elemental (non-hippocampal dependent) stimuli, respectively. However, simple tone and light stimuli frequently used as elemental cues in traditional experiments required the hippocampus to varying degrees among rats. Specifically, one group of rats showed a normal contextual bias when both contextual and elemental cues were present. These rats effectively switched to using elemental cues when the hippocampus was inactivated. The other group showed a strong contextual bias (and hippocampal dependence) because these rats were not able to use elemental cues when the hippocampus was unavailable. It is possible that the latter group of rats might have interpreted the elemental cues (light and tone) as background stimuli and depended more on the hippocampus in associating the cues with choice responses. Although exact mechanisms underlying these individual variances are unclear, our findings recommend a caution for adopting a simple sensory stimulus as a non-hippocampal sensory cue only based on the literature. PMID:24982624

Second-Order Conditioning in "Drosophila"

ERIC Educational Resources Information Center

Tabone, Christopher J.; de Belle, J. Steven

2011-01-01

Associative conditioning in "Drosophila melanogaster" has been well documented for several decades. However, most studies report only simple associations of conditioned stimuli (CS, e.g., odor) with unconditioned stimuli (US, e.g., electric shock) to measure learning or establish memory. Here we describe a straightforward second-order conditioning…

Evolution of Associative Learning in Chemical Networks

PubMed Central

McGregor, Simon; Vasas, Vera; Husbands, Phil; Fernando, Chrisantha

2012-01-01

Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ‘memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells. PMID:23133353

Value conditioning modulates visual working memory processes.

PubMed

Thomas, Paul M J; FitzGibbon, Lily; Raymond, Jane E

2016-01-01

Learning allows the value of motivationally salient events to become associated with stimuli that predict those events. Here, we asked whether value associations could facilitate visual working memory (WM), and whether such effects would be valence dependent. Our experiment was specifically designed to isolate value-based effects on WM from value-based effects on selective attention that might be expected to bias encoding. In a simple associative learning task, participants learned to associate the color of tinted faces with gaining or losing money or neither. Tinted faces then served as memoranda in a face identity WM task for which previously learned color associations were irrelevant and no monetary outcomes were forthcoming. Memory was best for faces with gain-associated tints, poorest for faces with loss-associated tints, and average for faces with no-outcome-associated tints. Value associated with 1 item in the WM array did not modulate memory for other items in the array. Eye movements when studying faces did not depend on the valence of previously learned color associations, arguing against value-based biases being due to differential encoding. This valence-sensitive value-conditioning effect on WM appears to result from modulation of WM maintenance processes. (c) 2015 APA, all rights reserved).

Lightwave Communications.

ERIC Educational Resources Information Center

Rheam, Harry

1993-01-01

Describes simple and inexpensive labs for introducing students to fiber optic communications. Students investigate light as a carrier wave; look into the difficulties associated with "light" communication; and learn about modulation, optical fibers, and critical angles. (PR)

Neural correlates of strategic reasoning during competitive games.

PubMed

Seo, Hyojung; Cai, Xinying; Donahue, Christopher H; Lee, Daeyeol

2014-10-17

Although human and animal behaviors are largely shaped by reinforcement and punishment, choices in social settings are also influenced by information about the knowledge and experience of other decision-makers. During competitive games, monkeys increased their payoffs by systematically deviating from a simple heuristic learning algorithm and thereby countering the predictable exploitation by their computer opponent. Neurons in the dorsomedial prefrontal cortex (dmPFC) signaled the animal's recent choice and reward history that reflected the computer's exploitative strategy. The strength of switching signals in the dmPFC also correlated with the animal's tendency to deviate from the heuristic learning algorithm. Therefore, the dmPFC might provide control signals for overriding simple heuristic learning algorithms based on the inferred strategies of the opponent. Copyright © 2014, American Association for the Advancement of Science.

Lesions of the rat nucleus basalis magnocellularis disrupt appetitive-to-aversive transfer learning.

PubMed

Butt, A E; Schultz, J A; Arnold, L L; Garman, E E; George, C L; Garraghty, P E

2003-01-01

Rats with selective lesions of the nucleus basalis magnocellularis (NBM) and sham-lesion control animals were tested in an operant appetitive-to-aversive transfer task. We hypothesized that NBM lesions would not affect performance in the appetitive phase, but that performance would be impaired during subsequent transfer to the aversive phase of the task. Additional groups of NBM lesion and control rats were tested in the avoidance condition only, where we hypothesized that NBM lesions would not disrupt performance. These hypotheses were based on the argument that the NBM is not necessary for simple association learning that does not tax attention. Both the appetitive phase of the transfer task and the avoidance only task depend only on simple associative learning and are argued not to tax attention. Consequently, performance in these tasks was predicted to be spared following NBM lesions. Complex, attention-demanding associative learning, however, is argued to depend on the NBM. Performance in the aversive phase of the transfer task is both attentionally demanding and associatively more complex than in either the appetitive or aversive tasks alone; thus, avoidance performance in the NBM lesion group was predicted to be impaired following transfer from prior appetitive conditioning. Results supported our hypotheses, with the NBM lesion group acquiring the appetitive response normally, but showing impaired performance following transfer to the aversive conditioning phase of the transfer task. Impairments were not attributable to disrupted avoidance learning per se, as avoidance behavior was normal in the NBM lesion group tested in the avoidance condition only.

A Simple Label Switching Algorithm for Semisupervised Structural SVMs.

PubMed

Balamurugan, P; Shevade, Shirish; Sundararajan, S

2015-10-01

In structured output learning, obtaining labeled data for real-world applications is usually costly, while unlabeled examples are available in abundance. Semisupervised structured classification deals with a small number of labeled examples and a large number of unlabeled structured data. In this work, we consider semisupervised structural support vector machines with domain constraints. The optimization problem, which in general is not convex, contains the loss terms associated with the labeled and unlabeled examples, along with the domain constraints. We propose a simple optimization approach that alternates between solving a supervised learning problem and a constraint matching problem. Solving the constraint matching problem is difficult for structured prediction, and we propose an efficient and effective label switching method to solve it. The alternating optimization is carried out within a deterministic annealing framework, which helps in effective constraint matching and avoiding poor local minima, which are not very useful. The algorithm is simple and easy to implement. Further, it is suitable for any structured output learning problem where exact inference is available. Experiments on benchmark sequence labeling data sets and a natural language parsing data set show that the proposed approach, though simple, achieves comparable generalization performance.

Learning to associate auditory and visual stimuli: behavioral and neural mechanisms.

PubMed

Altieri, Nicholas; Stevenson, Ryan A; Wallace, Mark T; Wenger, Michael J

2015-05-01

The ability to effectively combine sensory inputs across modalities is vital for acquiring a unified percept of events. For example, watching a hammer hit a nail while simultaneously identifying the sound as originating from the event requires the ability to identify spatio-temporal congruencies and statistical regularities. In this study, we applied a reaction time and hazard function measure known as capacity (e.g., Townsend and AshbyCognitive Theory 200-239, 1978) to quantify the extent to which observers learn paired associations between simple auditory and visual patterns in a model theoretic manner. As expected, results showed that learning was associated with an increase in accuracy, but more significantly, an increase in capacity. The aim of this study was to associate capacity measures of multisensory learning, with neural based measures, namely mean global field power (GFP). We observed a co-variation between an increase in capacity, and a decrease in GFP amplitude as learning occurred. This suggests that capacity constitutes a reliable behavioral index of efficient energy expenditure in the neural domain.

Acute psychophysiological stress impairs human associative learning.

PubMed

Ehlers, M R; Todd, R M

2017-11-01

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

Associative Mechanisms Allow for Social Learning and Cultural Transmission of String Pulling in an Insect

PubMed Central

Zhu, Xingfu; Ingraham, Thomas; Søvik, Eirik

2016-01-01

Social insects make elaborate use of simple mechanisms to achieve seemingly complex behavior and may thus provide a unique resource to discover the basic cognitive elements required for culture, i.e., group-specific behaviors that spread from “innovators” to others in the group via social learning. We first explored whether bumblebees can learn a nonnatural object manipulation task by using string pulling to access a reward that was presented out of reach. Only a small minority “innovated” and solved the task spontaneously, but most bees were able to learn to pull a string when trained in a stepwise manner. In addition, naïve bees learnt the task by observing a trained demonstrator from a distance. Learning the behavior relied on a combination of simple associative mechanisms and trial-and-error learning and did not require “insight”: naïve bees failed a “coiled-string experiment,” in which they did not receive instant visual feedback of the target moving closer when tugging on the string. In cultural diffusion experiments, the skill spread rapidly from a single knowledgeable individual to the majority of a colony’s foragers. We observed that there were several sequential sets (“generations”) of learners, so that previously naïve observers could first acquire the technique by interacting with skilled individuals and, subsequently, themselves become demonstrators for the next “generation” of learners, so that the longevity of the skill in the population could outlast the lives of informed foragers. This suggests that, so long as animals have a basic toolkit of associative and motor learning processes, the key ingredients for the cultural spread of unusual skills are already in place and do not require sophisticated cognition. PMID:27701411

Visual Associative Learning in Restrained Honey Bees with Intact Antennae

PubMed Central

Dobrin, Scott E.; Fahrbach, Susan E.

2012-01-01

A restrained honey bee can be trained to extend its proboscis in response to the pairing of an odor with a sucrose reward, a form of olfactory associative learning referred to as the proboscis extension response (PER). Although the ability of flying honey bees to respond to visual cues is well-established, associative visual learning in restrained honey bees has been challenging to demonstrate. Those few groups that have documented vision-based PER have reported that removing the antennae prior to training is a prerequisite for learning. Here we report, for a simple visual learning task, the first successful performance by restrained honey bees with intact antennae. Honey bee foragers were trained on a differential visual association task by pairing the presentation of a blue light with a sucrose reward and leaving the presentation of a green light unrewarded. A negative correlation was found between age of foragers and their performance in the visual PER task. Using the adaptations to the traditional PER task outlined here, future studies can exploit pharmacological and physiological techniques to explore the neural circuit basis of visual learning in the honey bee. PMID:22701575

Effects of arousal on cognitive control: empirical tests of the conflict-modulated Hebbian-learning hypothesis.

PubMed

Brown, Stephen B R E; van Steenbergen, Henk; Kedar, Tomer; Nieuwenhuis, Sander

2014-01-01

An increasing number of empirical phenomena that were previously interpreted as a result of cognitive control, turn out to reflect (in part) simple associative-learning effects. A prime example is the proportion congruency effect, the finding that interference effects (such as the Stroop effect) decrease as the proportion of incongruent stimuli increases. While this was previously regarded as strong evidence for a global conflict monitoring-cognitive control loop, recent evidence has shown that the proportion congruency effect is largely item-specific and hence must be due to associative learning. The goal of our research was to test a recent hypothesis about the mechanism underlying such associative-learning effects, the conflict-modulated Hebbian-learning hypothesis, which proposes that the effect of conflict on associative learning is mediated by phasic arousal responses. In Experiment 1, we examined in detail the relationship between the item-specific proportion congruency effect and an autonomic measure of phasic arousal: task-evoked pupillary responses. In Experiment 2, we used a task-irrelevant phasic arousal manipulation and examined the effect on item-specific learning of incongruent stimulus-response associations. The results provide little evidence for the conflict-modulated Hebbian-learning hypothesis, which requires additional empirical support to remain tenable.

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

PubMed

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

2001-08-01

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

Equilibria of perceptrons for simple contingency problems.

PubMed

Dawson, Michael R W; Dupuis, Brian

2012-08-01

The contingency between cues and outcomes is fundamentally important to theories of causal reasoning and to theories of associative learning. Researchers have computed the equilibria of Rescorla-Wagner models for a variety of contingency problems, and have used these equilibria to identify situations in which the Rescorla-Wagner model is consistent, or inconsistent, with normative models of contingency. Mathematical analyses that directly compare artificial neural networks to contingency theory have not been performed, because of the assumed equivalence between the Rescorla-Wagner learning rule and the delta rule training of artificial neural networks. However, recent results indicate that this equivalence is not as straightforward as typically assumed, suggesting a strong need for mathematical accounts of how networks deal with contingency problems. One such analysis is presented here, where it is proven that the structure of the equilibrium for a simple network trained on a basic contingency problem is quite different from the structure of the equilibrium for a Rescorla-Wagner model faced with the same problem. However, these structural differences lead to functionally equivalent behavior. The implications of this result for the relationships between associative learning, contingency theory, and connectionism are discussed.

NDRAM: nonlinear dynamic recurrent associative memory for learning bipolar and nonbipolar correlated patterns.

PubMed

Chartier, Sylvain; Proulx, Robert

2005-11-01

This paper presents a new unsupervised attractor neural network, which, contrary to optimal linear associative memory models, is able to develop nonbipolar attractors as well as bipolar attractors. Moreover, the model is able to develop less spurious attractors and has a better recall performance under random noise than any other Hopfield type neural network. Those performances are obtained by a simple Hebbian/anti-Hebbian online learning rule that directly incorporates feedback from a specific nonlinear transmission rule. Several computer simulations show the model's distinguishing properties.

The skeletons in our closet: E-learning tools and what happens when one side does not fit all.

PubMed

Van Nuland, Sonya E; Rogers, Kem A

2017-11-01

In the anatomical sciences, e-learning tools have become a critical component of teaching anatomy when physical space and cadaveric resources are limited. However, studies that use empirical evidence to compare their efficacy to visual-kinesthetic learning modalities are scarce. The study examined how a visual-kinesthetic experience, involving a physical skeleton, impacts learning when compared with virtual manipulation of a simple two-dimensional (2D) e-learning tool, A.D.A.M. Interactive Anatomy. Students from The University of Western Ontario, Canada (n = 77) participated in a dual-task study to: (1) investigate if a dual-task paradigm is an effective tool for measuring cognitive load across these different learning modalities; and (2) to assess the impact of knowledge recall and spatial ability when using them. Students were assessed using knowledge scores, Stroop task reaction times, and mental rotation test scores. Results demonstrated that the dual-task paradigm was not an effective tool for measuring cognitive load across different learning modalities with respect to kinesthetic learning. However, our study highlighted that handing physical specimens yielded major, positive impacts on performance that a simple commercial e-learning tool failed to deliver (P < 0.001). Furthermore, students with low spatial ability were significantly disadvantaged when they studied the bony joint and were tested on contralateral images (P = 0.046, R = 0.326). This suggests that, despite limbs being mirror images, students should be taught the anatomy of, as well as procedures on, both sides of the human body, enhancing the ability of all students, regardless of spatial ability, to take anatomical knowledge into the clinic and perform successfully. Anat Sci Educ 10: 570-588. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

Selective visual attention and motivation: the consequences of value learning in an attentional blink task.

PubMed

Raymond, Jane E; O'Brien, Jennifer L

2009-08-01

Learning to associate the probability and value of behavioral outcomes with specific stimuli (value learning) is essential for rational decision making. However, in demanding cognitive conditions, access to learned values might be constrained by limited attentional capacity. We measured recognition of briefly presented faces seen previously in a value-learning task involving monetary wins and losses; the recognition task was performed both with and without constraints on available attention. Regardless of available attention, recognition was substantially enhanced for motivationally salient stimuli (i.e., stimuli highly predictive of outcomes), compared with equally familiar stimuli that had weak or no motivational salience, and this effect was found regardless of valence (win or loss). However, when attention was constrained (because stimuli were presented during an attentional blink, AB), valence determined recognition; win-associated faces showed no AB, but all other faces showed large ABs. Motivational salience acts independently of attention to modulate simple perceptual decisions, but when attention is limited, visual processing is biased in favor of reward-associated stimuli.

A fundamental role for context in instrumental learning and extinction.

PubMed

Bouton, Mark E; Todd, Travis P

2014-05-01

The purpose of this article is to review recent research that has investigated the effects of context change on instrumental (operant) learning. The first part of the article discusses instrumental extinction, in which the strength of a reinforced instrumental behavior declines when reinforcers are withdrawn. The results suggest that extinction of either simple or discriminated operant behavior is relatively specific to the context in which it is learned: As in prior studies of Pavlovian extinction, ABA, ABC, and AAB renewal effects can all be observed. Further analysis supports the idea that the organism learns to refrain from making a specific response in a specific context, or in more formal terms, an inhibitory context-response association. The second part of the article then discusses research suggesting that the context also controls instrumental behavior before it is extinguished. Several experiments demonstrate that a context switch after either simple or discriminated operant training causes a decrement in the strength of the response. Over a range of conditions, the animal appears to learn a direct association between the context and the response. Under some conditions, it can also learn a hierarchical representation of context and the response-reinforcer relation. Extinction is still more context-specific than conditioning, as indicated by ABC and AAB renewal. Overall, the results establish that the context can play a significant role in both the acquisition and extinction of operant behavior. Copyright © 2014 Elsevier B.V. All rights reserved.

Orbitofrontal inactivation impairs reversal of Pavlovian learning by interfering with 'disinhibition' of responding for previously unrewarded cues.

PubMed

Burke, Kathryn A; Takahashi, Yuji K; Correll, Jessica; Brown, P Leon; Schoenbaum, Geoffrey

2009-11-01

Orbitofrontal cortex (OFC) is critical for reversal learning. Reversal deficits are typically demonstrated in complex settings that combine Pavlovian and instrumental learning. Yet recent work has implicated the OFC specifically in behaviors guided by cues and the features of the specific outcomes they predict. To test whether the OFC is important for reversing such Pavlovian associations in the absence of confounding instrumental requirements, we trained rats on a simple Pavlovian task in which two auditory cues were presented, one paired with a food pellet reward and the other presented without reward. After learning, we reversed the cue-outcome associations. For half the rats, OFC was inactivated prior to each reversal session. Inactivation of OFC impaired the ability of the rats to reverse conditioned responding. This deficit reflected the inability of inactivated rats to develop normal responding for the previously unrewarded cue; inactivation of OFC had no impact on the ability of the rats to inhibit responding to the previously rewarded cue. These data show that OFC is critical to reversal of Pavlovian responding, and that the role of OFC in this behavior cannot be explained as a simple deficit in response inhibition. Furthermore, the contrast between the normal inhibition of responding, reported here, and impaired inhibition of responding during Pavlovian over-expectation, reported previously, suggests the novel hypothesis that OFC may be particularly critical for learning (or behavior) when it requires the subject to generate predictions about outcomes by bringing together or integrating disparate pieces of associative information.

Reminder Cues Modulate the Renewal Effect in Human Predictive Learning

PubMed Central

Bustamante, Javier; Uengoer, Metin; Lachnit, Harald

2016-01-01

Associative learning refers to our ability to learn about regularities in our environment. When a stimulus is repeatedly followed by a specific outcome, we learn to expect the outcome in the presence of the stimulus. We are also able to modify established expectations in the face of disconfirming information (the stimulus is no longer followed by the outcome). Both the change of environmental regularities and the related processes of adaptation are referred to as extinction. However, extinction does not erase the initially acquired expectations. For instance, following successful extinction, the initially learned expectations can recover when there is a context change – a phenomenon called the renewal effect, which is considered as a model for relapse after exposure therapy. Renewal was found to be modulated by reminder cues of acquisition and extinction. However, the mechanisms underlying the effectiveness of reminder cues are not well understood. The aim of the present study was to investigate the impact of reminder cues on renewal in the field of human predictive learning. Experiment I demonstrated that renewal in human predictive learning is modulated by cues related to acquisition or extinction. Initially, participants received pairings of a stimulus and an outcome in one context. These stimulus-outcome pairings were preceded by presentations of a reminder cue (acquisition cue). Then, participants received extinction in a different context in which presentations of the stimulus were no longer followed by the outcome. These extinction trials were preceded by a second reminder cue (extinction cue). During a final phase conducted in a third context, participants showed stronger expectations of the outcome in the presence of the stimulus when testing was accompanied by the acquisition cue compared to the extinction cue. Experiment II tested an explanation of the reminder cue effect in terms of simple cue-outcome associations. Therefore, acquisition and extinction cues were equated for their associative histories in Experiment II, which should abolish their impact on renewal if based on simple cue-outcome associations. In contrast to this prediction, Experiment II replicated the findings from Experiment I indicating that the effectiveness of reminder cues did not require direct reminder cue-outcome associations. PMID:28066293

Disrupted Prediction Error Links Excessive Amygdala Activation to Excessive Fear.

PubMed

Sengupta, Auntora; Winters, Bryony; Bagley, Elena E; McNally, Gavan P

2016-01-13

Basolateral amygdala (BLA) is critical for fear learning, and its heightened activation is widely thought to underpin a variety of anxiety disorders. Here we used chemogenetic techniques in rats to study the consequences of heightened BLA activation for fear learning and memory, and to specifically identify a mechanism linking increased activity of BLA glutamatergic neurons to aberrant fear. We expressed the excitatory hM3Dq DREADD in rat BLA glutamatergic neurons and showed that CNO acted selectively to increase their activity, depolarizing these neurons and increasing their firing rates. This chemogenetic excitation of BLA glutamatergic neurons had no effect on the acquisition of simple fear learning, regardless of whether this learning led to a weak or strong fear memory. However, in an associative blocking task, chemogenetic excitation of BLA glutamatergic neurons yielded significant learning to a blocked conditioned stimulus, which otherwise should not have been learned about. Moreover, in an overexpectation task, chemogenetic manipulation of BLA glutamatergic neurons prevented use of negative prediction error to reduce fear learning, leading to significant impairments in fear inhibition. These effects were not attributable to the chemogenetic manipulation enhancing arousal, increasing asymptotic levels of fear learning or fear memory consolidation. Instead, chemogenetic excitation of BLA glutamatergic neurons disrupted use of prediction error to regulate fear learning. Several neuropsychiatric disorders are characterized by heightened activation of the amygdala. This heightened activation has been hypothesized to underlie increased emotional reactivity, fear over generalization, and deficits in fear inhibition. Yet the mechanisms linking heightened amygdala activation to heightened emotional learning are elusive. Here we combined chemogenetic excitation of rat basolateral amygdala glutamatergic neurons with a variety of behavioral approaches to show that, although simple fear learning is unaffected, the use of prediction error to regulate this learning is profoundly disrupted, leading to formation of inappropriate fear associations and impaired fear inhibition. Copyright © 2016 the authors 0270-6474/16/360385-11$15.00/0.

Learning rate and temperament in a high predation risk environment

USGS Publications Warehouse

DePasquale, C.; Wagner, Tyler; Archard, G.A.; Ferguson, B.; Braithwaite, V.A.

2014-01-01

Living in challenging environments can influence the behavior of animals in a number of ways. For instance, populations of prey fish that experience frequent, nonlethal interactions with predators have a high proportion of individuals that express greater reaction to risk and increased activity and exploration—collectively known as temperament traits. Temperament traits are often correlated, such that individuals that are risk-prone also tend to be active and explore more. Spatial learning, which requires the integration of many sensory cues, has also been shown to vary in fish exposed to different levels of predation threat. Fish from areas of low predation risk learn to solve spatial tasks faster than fish from high predation areas. However, it is not yet known whether simpler forms of learning, such as learning associations between two events, are similarly influenced. Simple forms of associative learning are likely to be affected by temperament because a willingness to approach and explore novel situations could provide animals with a learning advantage. However, it is possible that routine-forming and inflexible traits associated with risk-prone and increased exploratory behavior may act in the opposite way and make risk-prone individuals poorer at learning associations. To investigate this, we measured temperament in Panamanian bishop fish (Brachyrhaphis episcopi) sampled from a site known to contain many predators. The B. episcopi were then tested with an associative learning task. Within this population, fish that explored more were faster at learning a cue that predicted access to food, indicating a link between temperament and basic learning abilities.

Modeling How, When, and What Is Learned in a Simple Fault-Finding Task

ERIC Educational Resources Information Center

Ritter, Frank E.; Bibby, Peter A.

2008-01-01

We have developed a process model that learns in multiple ways while finding faults in a simple control panel device. The model predicts human participants' learning through its own learning. The model's performance was systematically compared to human learning data, including the time course and specific sequence of learned behaviors. These…

Associations of learning style with cultural values and demographics in nursing students in Iran and Malaysia

PubMed Central

Abdollahimohammad, Abdolghani; Ja’afar, Rogayah

2015-01-01

Purpose: The goal of the current study was to identify associations between the learning style of nursing students and their cultural values and demographic characteristics. Methods: A non-probability purposive sampling method was used to gather data from two populations. All 156 participants were female, Muslim, and full-time degree students. Data were collected from April to June 2010 using two reliable and validated questionnaires: the Learning Style Scales and the Values Survey Module 2008 (VSM 08). A simple linear regression was run for each predictor before conducting multiple linear regression analysis. The forward selection method was used for variable selection. P-values ≤0.05 and ≤0.1 were considered to indicate significance and marginal significance, respectively. Moreover, multi-group confirmatory factor analysis was performed to determine the invariance of the Farsi and English versions of the VSM 08. Results: The perceptive learning style was found to have a significant negative relationship with the power distance and monumentalism indices of the VSM 08. Moreover, a significant negative association was observed between the solitary learning style and the power distance index. However, no significant association was found between the analytic, competitive, and imaginative learning styles and cultural values (P>0.05). Likewise, no significant associations were observed between learning style, including the perceptive, solitary, analytic, competitive, and imaginative learning styles, and year of study or age (P>0.05). Conclusion: Students who reported low values on the power distance and monumentalism indices are more likely to prefer perceptive and solitary learning styles. Within each group of students in our study sample from the same school the year of study and age did not show any significant associations with learning style. PMID:26268831

Associations of learning style with cultural values and demographics in nursing students in Iran and Malaysia.

PubMed

Abdollahimohammad, Abdolghani; Ja'afar, Rogayah

2015-01-01

The goal of the current study was to identify associations between the learning style of nursing students and their cultural values and demographic characteristics. A non-probability purposive sampling method was used to gather data from two populations. All 156 participants were female, Muslim, and full-time degree students. Data were collected from April to June 2010 using two reliable and validated questionnaires: the Learning Style Scales and the Values Survey Module 2008 (VSM 08). A simple linear regression was run for each predictor before conducting multiple linear regression analysis. The forward selection method was used for variable selection. P-values ≤0.05 and ≤0.1 were considered to indicate significance and marginal significance, respectively. Moreover, multi-group confirmatory factor analysis was performed to determine the invariance of the Farsi and English versions of the VSM 08. The perceptive learning style was found to have a significant negative relationship with the power distance and monumentalism indices of the VSM 08. Moreover, a significant negative association was observed between the solitary learning style and the power distance index. However, no significant association was found between the analytic, competitive, and imaginative learning styles and cultural values (P>0.05). Likewise, no significant associations were observed between learning style, including the perceptive, solitary, analytic, competitive, and imaginative learning styles, and year of study or age (P>0.05). Students who reported low values on the power distance and monumentalism indices are more likely to prefer perceptive and solitary learning styles. Within each group of students in our study sample from the same school the year of study and age did not show any significant associations with learning style.

[Learning and memory in Drosophila: physiologic and genetic bases].

PubMed

Zhuravlev, A V; Nikitina, E A; Savvateeva-Popova, E V

2015-01-01

Elucidation of molecular mechanisms of cognitive functions is one of the major achievements in neurobiology. At most, this is due to the studies on the simple nervous systems, such as the CNS in Drosophila melanogaster. Many of its functional characteristics are pretty similar to higher vertebrates. Among these are: 1) evolutionary conservation of genes and molecular systems involved in the regulation of learning acquisition and memory formation; 2) presence of highly specialized and differentiated sensory, associative and motor centers; 3) utilization of similar modes of informational coding and analysis; 4) availability of major learning forms including non-associative, as well as associative learning; 5) diversity of different memories, including short-term- and protein synthesis- dependent long-term memory; 6) presence of aminergic reinforcement systems in the brain; 7) feed-back loops of circadian clocks, current organism experience and individual organism characters affecting cognitive process per se. In this review the main attention is paid to the two mostly studied Drosophila learning forms, namely to olfactory Iearning and courtship suppression conditioning (CCS). A separate consideration is given to the impacts of kynurenins and metabolite of actin remodeling signal cascade.

Modeling eating behaviors: The role of environment and positive food association learning via a Ratatouille effect.

PubMed

Murillo, Anarina L; Safan, Muntaser; Castillo-Chavez, Carlos; Phillips, Elizabeth D Capaldi; Wadhera, Devina

2016-08-01

Eating behaviors among a large population of children are studied as a dynamic process driven by nonlinear interactions in the sociocultural school environment. The impact of food association learning on diet dynamics, inspired by a pilot study conducted among Arizona children in Pre-Kindergarten to 8th grades, is used to build simple population-level learning models. Qualitatively, mathematical studies are used to highlight the possible ramifications of instruction, learning in nutrition, and health at the community level. Model results suggest that nutrition education programs at the population-level have minimal impact on improving eating behaviors, findings that agree with prior field studies. Hence, the incorporation of food association learning may be a better strategy for creating resilient communities of healthy and non-healthy eaters. A Ratatouille effect can be observed when food association learners become food preference learners, a potential sustainable behavioral change, which in turn, may impact the overall distribution of healthy eaters. In short, this work evaluates the effectiveness of population-level intervention strategies and the importance of institutionalizing nutrition programs that factor in economical, social, cultural, and environmental elements that mesh well with the norms and values in the community.

Perceptual learning: top to bottom.

PubMed

Amitay, Sygal; Zhang, Yu-Xuan; Jones, Pete R; Moore, David R

2014-06-01

Perceptual learning has traditionally been portrayed as a bottom-up phenomenon that improves encoding or decoding of the trained stimulus. Cognitive skills such as attention and memory are thought to drive, guide and modulate learning but are, with notable exceptions, not generally considered to undergo changes themselves as a result of training with simple perceptual tasks. Moreover, shifts in threshold are interpreted as shifts in perceptual sensitivity, with no consideration for non-sensory factors (such as response bias) that may contribute to these changes. Accumulating evidence from our own research and others shows that perceptual learning is a conglomeration of effects, with training-induced changes ranging from the lowest (noise reduction in the phase locking of auditory signals) to the highest (working memory capacity) level of processing, and includes contributions from non-sensory factors that affect decision making even on a "simple" auditory task such as frequency discrimination. We discuss our emerging view of learning as a process that increases the signal-to-noise ratio associated with perceptual tasks by tackling noise sources and inefficiencies that cause performance bottlenecks, and present some implications for training populations other than young, smart, attentive and highly-motivated college students. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Peripersonal Space and Margin of Safety around the Body: Learning Visuo-Tactile Associations in a Humanoid Robot with Artificial Skin.

PubMed

Roncone, Alessandro; Hoffmann, Matej; Pattacini, Ugo; Fadiga, Luciano; Metta, Giorgio

2016-01-01

This paper investigates a biologically motivated model of peripersonal space through its implementation on a humanoid robot. Guided by the present understanding of the neurophysiology of the fronto-parietal system, we developed a computational model inspired by the receptive fields of polymodal neurons identified, for example, in brain areas F4 and VIP. The experiments on the iCub humanoid robot show that the peripersonal space representation i) can be learned efficiently and in real-time via a simple interaction with the robot, ii) can lead to the generation of behaviors like avoidance and reaching, and iii) can contribute to the understanding the biological principle of motor equivalence. More specifically, with respect to i) the present model contributes to hypothesizing a learning mechanisms for peripersonal space. In relation to point ii) we show how a relatively simple controller can exploit the learned receptive fields to generate either avoidance or reaching of an incoming stimulus and for iii) we show how the robot can select arbitrary body parts as the controlled end-point of an avoidance or reaching movement.

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

PubMed

Daikhin, Luba; Ahissar, Merav

2015-07-01

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

A "Simple Query Interface" Adapter for the Discovery and Exchange of Learning Resources

ERIC Educational Resources Information Center

Massart, David

2006-01-01

Developed as part of CEN/ISSS Workshop on Learning Technology efforts to improve interoperability between learning resource repositories, the Simple Query Interface (SQI) is an Application Program Interface (API) for querying heterogeneous repositories of learning resource metadata. In the context of the ProLearn Network of Excellence, SQI is used…

Complexity, Training Paradigm Design, and the Contribution of Memory Subsystems to Grammar Learning

PubMed Central

Ettlinger, Marc; Wong, Patrick C. M.

2016-01-01

Although there is variability in nonnative grammar learning outcomes, the contributions of training paradigm design and memory subsystems are not well understood. To examine this, we presented learners with an artificial grammar that formed words via simple and complex morphophonological rules. Across three experiments, we manipulated training paradigm design and measured subjects' declarative, procedural, and working memory subsystems. Experiment 1 demonstrated that passive, exposure-based training boosted learning of both simple and complex grammatical rules, relative to no training. Additionally, procedural memory correlated with simple rule learning, whereas declarative memory correlated with complex rule learning. Experiment 2 showed that presenting corrective feedback during the test phase did not improve learning. Experiment 3 revealed that structuring the order of training so that subjects are first exposed to the simple rule and then the complex improved learning. The cumulative findings shed light on the contributions of grammatical complexity, training paradigm design, and domain-general memory subsystems in determining grammar learning success. PMID:27391085

Brain activation during anticipation of sound sequences.

PubMed

Leaver, Amber M; Van Lare, Jennifer; Zielinski, Brandon; Halpern, Andrea R; Rauschecker, Josef P

2009-02-25

Music consists of sound sequences that require integration over time. As we become familiar with music, associations between notes, melodies, and entire symphonic movements become stronger and more complex. These associations can become so tight that, for example, hearing the end of one album track can elicit a robust image of the upcoming track while anticipating it in total silence. Here, we study this predictive "anticipatory imagery" at various stages throughout learning and investigate activity changes in corresponding neural structures using functional magnetic resonance imaging. Anticipatory imagery (in silence) for highly familiar naturalistic music was accompanied by pronounced activity in rostral prefrontal cortex (PFC) and premotor areas. Examining changes in the neural bases of anticipatory imagery during two stages of learning conditional associations between simple melodies, however, demonstrates the importance of fronto-striatal connections, consistent with a role of the basal ganglia in "training" frontal cortex (Pasupathy and Miller, 2005). Another striking change in neural resources during learning was a shift between caudal PFC earlier to rostral PFC later in learning. Our findings regarding musical anticipation and sound sequence learning are highly compatible with studies of motor sequence learning, suggesting common predictive mechanisms in both domains.

Brain Activation During Anticipation of Sound Sequences

PubMed Central

Leaver, Amber M.; Van Lare, Jennifer; Zielinski, Brandon; Halpern, Andrea R.; Rauschecker, Josef P.

2010-01-01

Music consists of sound sequences that require integration over time. As we become familiar with music, associations between notes, melodies, and entire symphonic movements become stronger and more complex. These associations can become so tight that, for example, hearing the end of one album track can elicit a robust image of the upcoming track while anticipating it in total silence. Here we study this predictive “anticipatory imagery” at various stages throughout learning and investigate activity changes in corresponding neural structures using functional magnetic resonance imaging (fMRI). Anticipatory imagery (in silence) for highly familiar naturalistic music was accompanied by pronounced activity in rostral prefrontal cortex (PFC) and premotor areas. Examining changes in the neural bases of anticipatory imagery during two stages of learning conditional associations between simple melodies, however, demonstrates the importance of fronto-striatal connections, consistent with a role of the basal ganglia in “training” frontal cortex (Pasupathy and Miller, 2005). Another striking change in neural resources during learning was a shift between caudal PFC earlier to rostral PFC later in learning. Our findings regarding musical anticipation and sound sequence learning are highly compatible with studies of motor sequence learning, suggesting common predictive mechanisms in both domains. PMID:19244522

Long-term associative learning predicts verbal short-term memory performance.

PubMed

Jones, Gary; Macken, Bill

2018-02-01

Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term memory system separate from long-term knowledge. Using natural language corpora, we show experimentally and computationally that performance on three widely used measures of short-term memory (digit span, nonword repetition, and sentence recall) can be predicted from simple associative learning operating on the linguistic environment to which a typical child may have been exposed. The findings support the broad view that short-term verbal memory performance reflects the application of long-term language knowledge to the experimental setting.

Dissociations between Expectancy and Performance in Simple and Two-Choice Reaction-Time Tasks: A Test of Associative and Nonassociative Explanations

ERIC Educational Resources Information Center

Barrett, Louise C.; Livesey, Evan J.

2010-01-01

Perruchet, Cleeremans, and Destrebecqz (2006) reported a striking dissociation between trends in the conscious expectancy of an event and the speed of a response that is cued by that event. They argued that this indicates the operation of independent processes in human associative learning. However, there remains a strong possibility that this…

Modeling Cross-Situational Word–Referent Learning: Prior Questions

PubMed Central

Yu, Chen; Smith, Linda B.

2013-01-01

Both adults and young children possess powerful statistical computation capabilities—they can infer the referent of a word from highly ambiguous contexts involving many words and many referents by aggregating cross-situational statistical information across contexts. This ability has been explained by models of hypothesis testing and by models of associative learning. This article describes a series of simulation studies and analyses designed to understand the different learning mechanisms posited by the 2 classes of models and their relation to each other. Variants of a hypothesis-testing model and a simple or dumb associative mechanism were examined under different specifications of information selection, computation, and decision. Critically, these 3 components of the models interact in complex ways. The models illustrate a fundamental tradeoff between amount of data input and powerful computations: With the selection of more information, dumb associative models can mimic the powerful learning that is accomplished by hypothesis-testing models with fewer data. However, because of the interactions among the component parts of the models, the associative model can mimic various hypothesis-testing models, producing the same learning patterns but through different internal components. The simulations argue for the importance of a compositional approach to human statistical learning: the experimental decomposition of the processes that contribute to statistical learning in human learners and models with the internal components that can be evaluated independently and together. PMID:22229490

Learning in Structured Connectionist Networks

DTIC Science & Technology

1988-04-01

the structure is too rigid and learning too difficult for cognitive modeling. Two algorithms for learning simple, feature-based concept descriptions...and learning too difficult for cognitive model- ing. Two algorithms for learning simple, feature-based concept descriptions were also implemented. The...Term Goals Recent progress in connectionist research has been encouraging; networks have success- fully modeled human performance for various cognitive

Thrive or overload? The effect of task complexity on novices' simulation-based learning.

PubMed

Haji, Faizal A; Cheung, Jeffrey J H; Woods, Nicole; Regehr, Glenn; de Ribaupierre, Sandrine; Dubrowski, Adam

2016-09-01

Fidelity is widely viewed as an important element of simulation instructional design based on its purported relationship with transfer of learning. However, higher levels of fidelity may increase task complexity to a point at which novices' cognitive resources become overloaded. In this experiment, we investigate the effects of variations in task complexity on novices' cognitive load and learning during simulation-based procedural skills training. Thirty-eight medical students were randomly assigned to simulation training on a simple or complex lumbar puncture (LP) task. Participants completed four practice trials on this task (skill acquisition). After 10 days of rest, all participants completed one additional trial on their assigned task (retention) and one trial on a 'very complex' simulation designed to be similar to the complex task (transfer). We assessed LP performance and cognitive load on each trial using multiple measures. In both groups, LP performance improved significantly during skill acquisition (p ≤ 0.047, f = 0.29-0.96) and was maintained at retention. The simple task group demonstrated superior performance compared with the complex task group throughout these phases (p ≤ 0.002, d = 1.13-2.31). Cognitive load declined significantly in the simple task group (p < 0.009, f = 0.48-0.76), but not in the complex task group during skill acquisition, and remained lower at retention (p ≤ 0.024, d = 0.78-1.39). Between retention and transfer, LP performance declined and cognitive load increased in the simple task group, whereas both remained stable in the complex task group. At transfer, no group differences were observed in LP performance and cognitive load, except that the simple task group made significantly fewer breaches of sterility (p = 0.023, d = 0.80). Reduced task complexity was associated with superior LP performance and lower cognitive load during skill acquisition and retention, but mixed results on transfer to a more complex task. These results indicate that task complexity is an important factor that may mediate (via cognitive overload) the relationship between instructional design elements (e.g. fidelity) and simulation-based learning outcomes. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Algorithm Building and Learning Programming Languages Using a New Educational Paradigm

NASA Astrophysics Data System (ADS)

Jain, Anshul K.; Singhal, Manik; Gupta, Manu Sheel

2011-08-01

This research paper presents a new concept of using a single tool to associate syntax of various programming languages, algorithms and basic coding techniques. A simple framework has been programmed in Python that helps students learn skills to develop algorithms, and implement them in various programming languages. The tool provides an innovative and a unified graphical user interface for development of multimedia objects, educational games and applications. It also aids collaborative learning amongst students and teachers through an integrated mechanism based on Remote Procedure Calls. The paper also elucidates an innovative method for code generation to enable students to learn the basics of programming languages using drag-n-drop methods for image objects.

Learning viewpoint invariant perceptual representations from cluttered images.

PubMed

Spratling, Michael W

2005-05-01

In order to perform object recognition, it is necessary to form perceptual representations that are sufficiently specific to distinguish between objects, but that are also sufficiently flexible to generalize across changes in location, rotation, and scale. A standard method for learning perceptual representations that are invariant to viewpoint is to form temporal associations across image sequences showing object transformations. However, this method requires that individual stimuli be presented in isolation and is therefore unlikely to succeed in real-world applications where multiple objects can co-occur in the visual input. This paper proposes a simple modification to the learning method that can overcome this limitation and results in more robust learning of invariant representations.

Learning in a Simple Motor System

ERIC Educational Resources Information Center

Broussard, Dianne M.; Kassardjian, Charles D.

2004-01-01

Motor learning is a very basic, essential form of learning that appears to share common mechanisms across different motor systems. We evaluate and compare a few conceptual models for learning in a relatively simple neural system, the vestibulo-ocular reflex (VOR) of vertebrates. We also compare the different animal models that have been used to…

Simple Automatic File Exchange (SAFE) to Support Low-Cost Spacecraft Operation via the Internet

NASA Technical Reports Server (NTRS)

Baker, Paul; Repaci, Max; Sames, David

1998-01-01

Various issues associated with Simple Automatic File Exchange (SAFE) are presented in viewgraph form. Specific topics include: 1) Packet telemetry, Internet IP networks and cost reduction; 2) Basic functions and technical features of SAFE; 3) Project goals, including low-cost satellite transmission to data centers to be distributed via an Internet; 4) Operations with a replicated file protocol; 5) File exchange operation; 6) Ground stations as gateways; 7) Lessons learned from demonstrations and tests with SAFE; and 8) Feedback and future initiatives.

Chronic sleep deprivation differentially affects short and long-term operant memory in Aplysia.

PubMed

Krishnan, Harini C; Noakes, Eric J; Lyons, Lisa C

2016-10-01

The induction, formation and maintenance of memory represent dynamic processes modulated by multiple factors including the circadian clock and sleep. Chronic sleep restriction has become common in modern society due to occupational and social demands. Given the impact of cognitive impairments associated with sleep deprivation, there is a vital need for a simple animal model in which to study the interactions between chronic sleep deprivation and memory. We used the marine mollusk Aplysia californica, with its simple nervous system, nocturnal sleep pattern and well-characterized learning paradigms, to assess the effects of two chronic sleep restriction paradigms on short-term (STM) and long-term (LTM) associative memory. The effects of sleep deprivation on memory were evaluated using the operant learning paradigm, learning that food is inedible, in which the animal associates a specific netted seaweed with failed swallowing attempts. We found that two nights of 6h sleep deprivation occurring during the first or last half of the night inhibited both STM and LTM. Moreover, the impairment in STM persisted for more than 24h. A milder, prolonged sleep deprivation paradigm consisting of 3 consecutive nights of 4h sleep deprivation also blocked STM, but had no effect on LTM. These experiments highlight differences in the sensitivity of STM and LTM to chronic sleep deprivation. Moreover, these results establish Aplysia as a valid model for studying the interactions between chronic sleep deprivation and associative memory paving the way for future studies delineating the mechanisms through which sleep restriction affects memory formation. Copyright © 2016 Elsevier Inc. All rights reserved.

Chronic Sleep Deprivation Differentially Affects Short and Long-term Operant Memory in Aplysia

PubMed Central

Krishnan, Harini C.; Noakes, Eric J.; Lyons, Lisa C.

2016-01-01

The induction, formation and maintenance of memory represent dynamic processes modulated by multiple factors including the circadian clock and sleep. Chronic sleep restriction has become common in modern society due to occupational and social demands. Given the impact of cognitive impairments associated with sleep deprivation, there is a vital need for a simple animal model in which to study the interactions between chronic sleep deprivation and memory. We used the marine mollusk Aplysia californica, with its simple nervous system, nocturnal sleep pattern and well-characterized learning paradigms, to assess the effects of two chronic sleep restriction paradigms on short-term (STM) and long-term (LTM) associative memory. The effects of sleep deprivation on memory were evaluated using the operant learning paradigm, learning that food is inedible, in which the animal associates a specific netted seaweed with failed swallowing attempts. We found that two nights of 6 h sleep deprivation occurring during the first or last half of the night inhibited both STM and LTM. Moreover, the impairment in STM persisted for more than 24 hours. A milder, prolonged sleep deprivation paradigm consisting of 3 consecutive nights of 4 h sleep deprivation also blocked STM, but had no effect on LTM. These experiments highlight differences in the sensitivity of STM and LTM to chronic sleep deprivation. Moreover, these results establish Aplysia as a valid model for studying the interactions between chronic sleep deprivation and associative memory paving the way for future studies delineating the mechanisms through which sleep restriction affects memory formation. PMID:27555235

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

PubMed

Tempelmann, Sebastian; Kaminski, Juliane; Tomasello, Michael

2014-01-01

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

The equivalence of learning paths in early science instruction: effect of direct instruction and discovery learning.

PubMed

Klahr, David; Nigam, Milena

2004-10-01

In a study with 112 third- and fourth-grade children, we measured the relative effectiveness of discovery learning and direct instruction at two points in the learning process: (a) during the initial acquisition of the basic cognitive objective (a procedure for designing and interpreting simple, unconfounded experiments) and (b) during the subsequent transfer and application of this basic skill to more diffuse and authentic reasoning associated with the evaluation of science-fair posters. We found not only that many more children learned from direct instruction than from discovery learning, but also that when asked to make broader, richer scientific judgments, the many children who learned about experimental design from direct instruction performed as well as those few children who discovered the method on their own. These results challenge predictions derived from the presumed superiority of discovery approaches in teaching young children basic procedures for early scientific investigations.

Assembling old tricks for new tasks: a neural model of instructional learning and control.

PubMed

Huang, Tsung-Ren; Hazy, Thomas E; Herd, Seth A; O'Reilly, Randall C

2013-06-01

We can learn from the wisdom of others to maximize success. However, it is unclear how humans take advice to flexibly adapt behavior. On the basis of data from neuroanatomy, neurophysiology, and neuroimaging, a biologically plausible model is developed to illustrate the neural mechanisms of learning from instructions. The model consists of two complementary learning pathways. The slow-learning parietal pathway carries out simple or habitual stimulus-response (S-R) mappings, whereas the fast-learning hippocampal pathway implements novel S-R rules. Specifically, the hippocampus can rapidly encode arbitrary S-R associations, and stimulus-cued responses are later recalled into the basal ganglia-gated pFC to bias response selection in the premotor and motor cortices. The interactions between the two model learning pathways explain how instructions can override habits and how automaticity can be achieved through motor consolidation.

Towards a model of temporal attention for on-line learning in a mobile robot

NASA Astrophysics Data System (ADS)

Marom, Yuval; Hayes, Gillian

2001-06-01

We present a simple attention system, capable of bottom-up signal detection adaptive to subjective internal needs. The system is used by a robotic agent, learning to perform phototaxis and obstacle avoidance by following a teacher agent around a simulated environment, and deciding when to form associations between perceived information and imitated actions. We refer to this kind of decision-making as on-line temporal attention. The main role of the attention system is perception of change; the system is regulated through feedback about cognitive effort. We show how different levels of effort affect both the ability to learn a task, and to execute it.

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

PubMed

Orhan, A Emin; Ma, Wei Ji

2017-07-26

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

A Simple and Effective Remedial Learning System with a Fuzzy Expert System

ERIC Educational Resources Information Center

Lin, C.-C.; Guo, K.-H.; Lin, Y.-C.

2016-01-01

This study aims at implementing a simple and effective remedial learning system. Based on fuzzy inference, a remedial learning material selection system is proposed for a digital logic course. Two learning concepts of the course have been used in the proposed system: number systems and combinational logic. We conducted an experiment to validate…

Feature to prototype transition in neural networks

NASA Astrophysics Data System (ADS)

Krotov, Dmitry; Hopfield, John

Models of associative memory with higher order (higher than quadratic) interactions, and their relationship to neural networks used in deep learning are discussed. Associative memory is conventionally described by recurrent neural networks with dynamical convergence to stable points. Deep learning typically uses feedforward neural nets without dynamics. However, a simple duality relates these two different views when applied to problems of pattern classification. From the perspective of associative memory such models deserve attention because they make it possible to store a much larger number of memories, compared to the quadratic case. In the dual description, these models correspond to feedforward neural networks with one hidden layer and unusual activation functions transmitting the activities of the visible neurons to the hidden layer. These activation functions are rectified polynomials of a higher degree rather than the rectified linear functions used in deep learning. The network learns representations of the data in terms of features for rectified linear functions, but as the power in the activation function is increased there is a gradual shift to a prototype-based representation, the two extreme regimes of pattern recognition known in cognitive psychology. Simons Center for Systems Biology.

Peripersonal Space and Margin of Safety around the Body: Learning Visuo-Tactile Associations in a Humanoid Robot with Artificial Skin

PubMed Central

Roncone, Alessandro; Fadiga, Luciano; Metta, Giorgio

2016-01-01

This paper investigates a biologically motivated model of peripersonal space through its implementation on a humanoid robot. Guided by the present understanding of the neurophysiology of the fronto-parietal system, we developed a computational model inspired by the receptive fields of polymodal neurons identified, for example, in brain areas F4 and VIP. The experiments on the iCub humanoid robot show that the peripersonal space representation i) can be learned efficiently and in real-time via a simple interaction with the robot, ii) can lead to the generation of behaviors like avoidance and reaching, and iii) can contribute to the understanding the biological principle of motor equivalence. More specifically, with respect to i) the present model contributes to hypothesizing a learning mechanisms for peripersonal space. In relation to point ii) we show how a relatively simple controller can exploit the learned receptive fields to generate either avoidance or reaching of an incoming stimulus and for iii) we show how the robot can select arbitrary body parts as the controlled end-point of an avoidance or reaching movement. PMID:27711136

Focus: Elevating the Essentials to Radically Improve Student Learning

ERIC Educational Resources Information Center

Schmoker, Mike

2011-01-01

Instead of piling on one new reform fad after another, here at last is a book that boils down solutions for improved schools to the most powerful, simple actions and structures that ensure you prepare all students for college, careers, and citizenship. Best-selling ASCD (Association for Supervision and Curriculum Development) author and renowned…

Duality of Mathematical Thinking When Making Sense of Simple Word Problems: Theoretical Essay

ERIC Educational Resources Information Center

Polotskaia, Elena; Savard, Annie; Freiman, Viktor

2015-01-01

This essay proposes a reflection on the learning difficulties and teaching approaches associated with arithmetic word problem solving. We question the development of word problem solving skills in the early grades of elementary school. We are trying to revive the discussion because first, the knowledge in question--reversibility of arithmetic…

Inter-cortical Modulation from Premotor to Motor Plasticity.

PubMed

Huang, Ying-Zu; Chen, Rou-Shayn; Fong, Po-Yu; Rothwell, John C; Chuang, Wen-Li; Weng, Yi-Hsin; Lin, Wey-Yil; Lu, Chin-Song

2018-06-11

Plasticity is involved in daily activities but abnormal plasticity may be deleterious. In this study, we found that motor plasticity could be modulated by suppressing the premotor cortex with the theta burst form of repetitive transcranial magnetic stimulation. Such changes in motor plasticity were associated with reduced learning of a simple motor task. We postulate that the premotor cortex adjusts the amount of motor plasticity to modulate motor learning through heterosynaptic metaplasticity. The present results provide an insight into how the brain physiologically coordinates two different areas to bring them into a functional network. This concept could be employed to intervene in diseases with abnormal plasticity. Primary motor cortex (M1) plasticity is known to be influenced by the excitability and prior activation history of M1 itself. However, little is known about how its plasticity is influenced by other areas of the brain. In the present study on humans of either sex who were known to respond to theta burst stimulation from previous studies, we found plasticity of M1 could be modulated by suppressing the premotor cortex with the theta burst form of repetitive transcranial magnetic stimulation. Motor plasticity was distorted and disappeared 30 min and 120 min respectively after premotor excitability was suppressed. Further evaluation revealed that such changes in motor plasticity were associated with impaired learning of a simple motor task. We postulate that the premotor cortex modulates the amount of plasticity within M1 through heterosynaptic metaplasticity, and that this may impact on learning of a simple motor task previously shown to be directly affected by M1 plasticity. The present results provide an insight into how the brain physiologically coordinates two different areas to bring them into a functional network. Furthermore, such concepts could be translated into therapeutic approaches for diseases with aberrant plasticity. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Analogical-mapping-based comparison tasks as a scaffold for argumentation

NASA Astrophysics Data System (ADS)

Emig, Brandon R.

Given the centrality of the argumentation process to science and consequent importance to science education, inviting science students to engage in argumentation and scaffolding that argumentation in order that it lead to learning and not frustration is important. The present research invites small groups of science content learners (54 preservice elementary teachers at a large research university) to use analogical-mapping-based comparison tasks in service of argumentation to determine which of two possible analogues, in this case simple machines, is most closely related to a third. These activities and associated instruction scaffolded student small-groups' argumentation in four ways: (1) supporting new analogical correspondences on the heels of prior correspondences; (2) discerning definitions and descriptions for simple machine elements; (3) identifying and dealing with ambiguity in potential correspondences; and (4) making reflections on prior analogical correspondences in service of their final arguments. Analogical-mapping-based comparison activities scaffolded student small groups both in their argumentation and in content learning about simple machines. Implications, limitations, and directions for future related research are also discussed.

Spontaneous trait transference to familiar communicators: is a little knowledge a dangerous thing?

PubMed

Mae, L; Carlston, D E; Skowronski, J J

1999-08-01

In most social cognition research participants are presented with unattributed information about unfamiliar stimulus persons. However, in the real world it is more common for people to learn about others through social communication and to know something about those with whom they communicate. Such issues are explored in relation to spontaneous trait transference, a phenomenon in which communicators are perceived as having traits that they merely describe in others. Three studies show that even familiar communicators became associated with, and attributed, the traits implied by their remarks. Surprisingly, these effects occurred even when the implied traits were incongruent with participants' prior knowledge about these communicators. The results are discussed in terms of (a) the generalizability of social cognition research, (b) the automaticity of simple associative phenomena, and (c) the interplay of simple associative and higher level processes.

How Many U.S. High School Students Have a Foreign Language Reading "Disability"? Reading without Meaning and the Simple View

ERIC Educational Resources Information Center

Sparks, Richard L.; Luebbers, Julie

2018-01-01

Conventional wisdom suggests that students classified as learning disabled will exhibit difficulties with foreign language (FL) learning, but evidence has not supported a relationship between FL learning problems and learning disabilities. The simple view of reading model posits that reading comprehension is the product of word decoding and…

Learning and Recognition of a Non-conscious Sequence of Events in Human Primary Visual Cortex.

PubMed

Rosenthal, Clive R; Andrews, Samantha K; Antoniades, Chrystalina A; Kennard, Christopher; Soto, David

2016-03-21

Human primary visual cortex (V1) has long been associated with learning simple low-level visual discriminations [1] and is classically considered outside of neural systems that support high-level cognitive behavior in contexts that differ from the original conditions of learning, such as recognition memory [2, 3]. Here, we used a novel fMRI-based dichoptic masking protocol-designed to induce activity in V1, without modulation from visual awareness-to test whether human V1 is implicated in human observers rapidly learning and then later (15-20 min) recognizing a non-conscious and complex (second-order) visuospatial sequence. Learning was associated with a change in V1 activity, as part of a temporo-occipital and basal ganglia network, which is at variance with the cortico-cerebellar network identified in prior studies of "implicit" sequence learning that involved motor responses and visible stimuli (e.g., [4]). Recognition memory was associated with V1 activity, as part of a temporo-occipital network involving the hippocampus, under conditions that were not imputable to mechanisms associated with conscious retrieval. Notably, the V1 responses during learning and recognition separately predicted non-conscious recognition memory, and functional coupling between V1 and the hippocampus was enhanced for old retrieval cues. The results provide a basis for novel hypotheses about the signals that can drive recognition memory, because these data (1) identify human V1 with a memory network that can code complex associative serial visuospatial information and support later non-conscious recognition memory-guided behavior (cf. [5]) and (2) align with mouse models of experience-dependent V1 plasticity in learning and memory [6]. Copyright © 2016 Elsevier Ltd. All rights reserved.

Brain Gym. Simple Activities for Whole Brain Learning.

ERIC Educational Resources Information Center

Dennison, Paul E.; Dennison, Gail E.

This booklet contains simple movements and activities that are used with students in Educational Kinesiology to enhance their experience of whole brain learning. Whole brain learning through movement repatterning and Brain Gym activities enable students to access those parts of the brain previously unavailable to them. These movements of body and…

Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability.

PubMed

Tanaka, Takuma; Aoyagi, Toshio; Kaneko, Takeshi

2012-10-01

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

Learn about Physical Science: Simple Machines. [CD-ROM].

ERIC Educational Resources Information Center

2000

This CD-ROM, designed for students in grades K-2, explores the world of simple machines. It allows students to delve into the mechanical world and learn the ways in which simple machines make work easier. Animated demonstrations are provided of the lever, pulley, wheel, screw, wedge, and inclined plane. Activities include practical matching and…

Chaos in learning a simple two-person game

PubMed Central

Sato, Yuzuru; Akiyama, Eizo; Farmer, J. Doyne

2002-01-01

We investigate the problem of learning to play the game of rock–paper–scissors. Each player attempts to improve her/his average score by adjusting the frequency of the three possible responses, using reinforcement learning. For the zero sum game the learning process displays Hamiltonian chaos. Thus, the learning trajectory can be simple or complex, depending on initial conditions. We also investigate the non-zero sum case and show that it can give rise to chaotic transients. This is, to our knowledge, the first demonstration of Hamiltonian chaos in learning a basic two-person game, extending earlier findings of chaotic attractors in dissipative systems. As we argue here, chaos provides an important self-consistency condition for determining when players will learn to behave as though they were fully rational. That chaos can occur in learning a simple game indicates one should use caution in assuming real people will learn to play a game according to a Nash equilibrium strategy. PMID:11930020

Investigating the Impact of a LEGO(TM)-Based, Engineering-Oriented Curriculum Compared to an Inquiry-Based Curriculum on Fifth Graders' Content Learning of Simple Machines

ERIC Educational Resources Information Center

Marulcu, Ismail

2010-01-01

This mixed method study examined the impact of a LEGO-based, engineering-oriented curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines. This study takes a social constructivist theoretical stance that science learning involves learning scientific concepts and their relations to each other. From…

Do Domestic Dogs Learn Words Based on Humans’ Referential Behaviour?

PubMed Central

Tempelmann, Sebastian; Kaminski, Juliane; Tomasello, Michael

2014-01-01

Some domestic dogs learn to comprehend human words, although the nature and basis of this learning is unknown. In the studies presented here we investigated whether dogs learn words through an understanding of referential actions by humans rather than simple association. In three studies, each modelled on a study conducted with human infants, we confronted four word-experienced dogs with situations involving no spatial-temporal contiguity between the word and the referent; the only available cues were referential actions displaced in time from exposure to their referents. We found that no dogs were able to reliably link an object with a label based on social-pragmatic cues alone in all the tests. However, one dog did show skills in some tests, possibly indicating an ability to learn based on social-pragmatic cues. PMID:24646732

What You Learn is What You See: Using Eye Movements to Study Infant Cross-Situational Word Learning

PubMed Central

Smith, Linda

2016-01-01

Recent studies show that both adults and young children possess powerful statistical learning capabilities to solve the word-to-world mapping problem. However, the underlying mechanisms that make statistical learning possible and powerful are not yet known. With the goal of providing new insights into this issue, the research reported in this paper used an eye tracker to record the moment-by-moment eye movement data of 14-month-old babies in statistical learning tasks. Various measures are applied to such fine-grained temporal data, such as looking duration and shift rate (the number of shifts in gaze from one visual object to the other) trial by trial, showing different eye movement patterns between strong and weak statistical learners. Moreover, an information-theoretic measure is developed and applied to gaze data to quantify the degree of learning uncertainty trial by trial. Next, a simple associative statistical learning model is applied to eye movement data and these simulation results are compared with empirical results from young children, showing strong correlations between these two. This suggests that an associative learning mechanism with selective attention can provide a cognitively plausible model of cross-situational statistical learning. The work represents the first steps to use eye movement data to infer underlying real-time processes in statistical word learning. PMID:22213894

Stimulus Processing and Associative Learning in Wistar and WKHA Rats

PubMed Central

Chess, Amy C.; Keene, Christopher S.; Wyzik, Elizabeth C.; Bucci, David J.

2007-01-01

This study assessed basic learning and attention abilities in WKHA (Wistar-Kyoto Hyperactive) rats using appetitive conditioning preparations. Two measures of conditioned responding to a visual stimulus, orienting behavior (rearing on the hindlegs) and food cup behavior (placing the head inside the recessed food cup) were measured. In Experiment 1, simple conditioning but not extinction was impaired in WKHA rats compared to Wistar rats. In Experiment 2, non-reinforced presentations of the visual cue preceded the conditioning sessions. WKHA rats displayed less orienting behavior than Wistar rats, but comparable levels of food cup behavior. These data suggest that WKHA rats exhibit specific abnormalities in attentional processing as well as learning stimulus-reward relationships. PMID:15998198

Reactive behavior, learning, and anticipation

NASA Technical Reports Server (NTRS)

Whitehead, Steven D.; Ballard, Dana H.

1989-01-01

Reactive systems always act, thinking only long enough to 'look up' the action to execute. Traditional planning systems think a lot, and act only after generating fairly precise plans. Each represents an endpoint on a spectrum. It is argued that primitive forms of reasoning, like anticipation, play an important role in reducing the cost of learning and that the decision to act or think should be based on the uncertainty associated with the utility of executing an action in a particular situation. An architecture for an adaptable reactive system is presented and it is shown how it can be augmented with a simple anticipation mechanism that can substantially reduce the cost and time of learning.

Never forget a name: white matter connectivity predicts person memory

PubMed Central

Metoki, Athanasia; Alm, Kylie H.; Wang, Yin; Ngo, Chi T.; Olson, Ingrid R.

2018-01-01

Through learning and practice, we can acquire numerous skills, ranging from the simple (whistling) to the complex (memorizing operettas in a foreign language). It has been proposed that complex learning requires a network of brain regions that interact with one another via white matter pathways. One candidate white matter pathway, the uncinate fasciculus (UF), has exhibited mixed results for this hypothesis: some studies have shown UF involvement across a range of memory tasks, while other studies report null results. Here, we tested the hypothesis that the UF supports associative memory processes and that this tract can be parcellated into subtracts that support specific types of memory. Healthy young adults performed behavioral tasks (two face-name learning tasks, one word pair memory task) and underwent a diffusion-weighted imaging scan. Our results revealed that variation in UF microstructure was significantly associated with individual differences in performance on both face-name tasks, as well as the word association memory task. A UF sub-tract, functionally defined by its connectivity between face-selective regions in the anterior temporal lobe and orbitofrontal cortex, selectively predicted face-name learning. In contrast, connectivity between the fusiform face patch and both anterior face patches had no predictive validity. These findings suggest that there is a robust and replicable relationship between the UF and associative learning and memory. Moreover, this large white matter pathway can be subdivided to reveal discrete functional profiles. PMID:28646241

Learning Disorders: Know the Signs, How to Help

MedlinePlus

... a child to read, write or do simple math. Understand the signs and what you can do. ... Dyscalculia. Dyscalculia is a learning disorder related to math concepts. Signs include difficulty solving even simple math ...

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

PubMed

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

2017-04-01

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

The American Heart Association Life's Simple 7 and Incident Cognitive Impairment: The REasons for Geographic And Racial Differences in Stroke (REGARDS) Study

PubMed Central

Thacker, Evan L.; Gillett, Sarah R.; Wadley, Virginia G.; Unverzagt, Frederick W.; Judd, Suzanne E.; McClure, Leslie A.; Howard, Virginia J.; Cushman, Mary

2014-01-01

Background Life's Simple 7 is a new metric based on modifiable health behaviors and factors that the American Heart Association uses to promote improvements to cardiovascular health (CVH). We hypothesized that better Life's Simple 7 scores are associated with lower incidence of cognitive impairment. Methods and Results For this prospective cohort study, we included REasons for Geographic And Racial Differences in Stroke (REGARDS) participants aged 45+ who had normal global cognitive status at baseline and no history of stroke (N=17 761). We calculated baseline Life's Simple 7 score (range, 0 to 14) based on smoking, diet, physical activity, body mass index, blood pressure, total cholesterol, and fasting glucose. We identified incident cognitive impairment using a 3‐test measure of verbal learning, memory, and fluency obtained a mean of 4 years after baseline. Relative to the lowest tertile of Life's Simple 7 score (0 to 6 points), odds ratios of incident cognitive impairment were 0.65 (0.52, 0.81) in the middle tertile (7 to 8 points) and 0.63 (0.51, 0.79) in the highest tertile (9 to 14 points). The association was similar in blacks and whites, as well as outside and within the Southeastern stroke belt region of the United States. Conclusions Compared with low CVH, intermediate and high CVH were both associated with substantially lower incidence of cognitive impairment. We did not observe a dose‐response pattern; people with intermediate and high levels of CVH had similar incidence of cognitive impairment. This suggests that even when high CVH is not achieved, intermediate levels of CVH are preferable to low CVH. PMID:24919926

Effect of the Four-Step Learning Cycle Model on Students' Understanding of Concepts Related to Simple Harmonic Motion

ERIC Educational Resources Information Center

Madu, B. C.

2012-01-01

The study explored the efficacy of four-step (4-E) learning cycle approach on students understanding of concepts related to Simple Harmonic Motion (SHM). 124 students (63 for experimental group and 61 for control group) participated in the study. The students' views and ideas in simple Harmonic Achievement test were analyzed qualitatively. The…

Simple webs of natural environment theme as a result of sharing in science teacher training

NASA Astrophysics Data System (ADS)

Tapilouw, M. C.; Firman, H.; Redjeki, S.; Chandra, D. T.

2018-03-01

Thematic learning is one type of integrated science (Biology, Physics, Chemistry and Earth Science) in Science Education. This study is concerning about simple webs of natural environment theme in science learning, as one of training material in science teacher training program. Making simple web is a goal of first step in teacher training program. Every group explain their web illustration to other group. Twenty Junior High School science teacher above one education foundation participate in science teacher training program. In order to gather simple webs, sharing method was used in this first step of science teacher training. The result of this study is five different simple web of natural environment themes. These webs represent science learning in class VII/Semester I, class VII/Semester II, Class VIII, Class IX/Semester I, Class IX/Semester II based on basic competency in National Curriculum 2013. Each group discussed web of natural environment theme based on their learning experience in real class which basic competency and subject matters are linked with natural environment theme. As a conclusion, simple webs are potential to develop in the next step of science teacher training program and to be implemented in real class.

Changes in spinal reflex excitability associated with motor sequence learning.

PubMed

Lungu, Ovidiu; Frigon, Alain; Piché, Mathieu; Rainville, Pierre; Rossignol, Serge; Doyon, Julien

2010-05-01

There is ample evidence that motor sequence learning is mediated by changes in brain activity. Yet the question of whether this form of learning elicits changes detectable at the spinal cord level has not been addressed. To date, studies in humans have revealed that spinal reflex activity may be altered during the acquisition of various motor skills, but a link between motor sequence learning and changes in spinal excitability has not been demonstrated. To address this issue, we studied the modulation of H-reflex amplitude evoked in the flexor carpi radialis muscle of 14 healthy individuals between blocks of movements that involved the implicit acquisition of a sequence versus other movements that did not require learning. Each participant performed the task in three conditions: "sequence"-externally triggered, repeating and sequential movements, "random"-similar movements, but performed in an arbitrary order, and "simple"- involving alternating movements in a left-right or up-down direction only. When controlling for background muscular activity, H-reflex amplitude was significantly more reduced in the sequence (43.8 +/- 1.47%. mean +/- SE) compared with the random (38.2 +/- 1.60%) and simple (31.5 +/- 1.82%) conditions, while the M-response was not different across conditions. Furthermore, H-reflex changes were observed from the beginning of the learning process up to when subjects reached asymptotic performance on the motor task. Changes also persisted for >60 s after motor activity ceased. Such findings suggest that the excitability in some spinal reflex circuits is altered during the implicit learning process of a new motor sequence.

Foraging Ecology Predicts Learning Performance in Insectivorous Bats

PubMed Central

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

2013-01-01

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

Clicking to Learn: A Case Study of Embedding Radio-Frequency Based Clickers in an Introductory Management Information Systems Course

ERIC Educational Resources Information Center

Nelson, Matthew L.; Hauck, Roslin V.

2008-01-01

The challenges associated with teaching a core introductory management information systems (MIS) course are well known (large class sizes serving a majority of non-MIS majors, sustaining student interests, encouraging class participation, etc.). This study offers a mechanism towards managing these challenges through the use of a simple and…

Development of the Concept of Energy Conservation using Simple Experiments for Grade 10 Students

NASA Astrophysics Data System (ADS)

Rachniyom, S.; Toedtanya, K.; Wuttiprom, S.

2017-09-01

The purpose of this research was to develop students’ concept of and retention rate in relation to energy conservation. Activities included simple and easy experiments that considered energy transformation from potential to kinetic energy. The participants were 30 purposively selected grade 10 students in the second semester of the 2016 academic year. The research tools consisted of learning lesson plans and a learning achievement test. Results showed that the experiments worked well and were appropriate as learning activities. The students’ achievement scores significantly increased at the statistical level of 05, the students’ retention rates were at a high level, and learning behaviour was at a good level. These simple experiments allowed students to learn to demonstrate to their peers and encouraged them to use familiar models to explain phenomena in daily life.

Interaction of plasticity and circuit organization during the acquisition of cerebellum-dependent motor learning

PubMed Central

Yang, Yan; Lisberger, Stephen G

2013-01-01

Motor learning occurs through interactions between the cerebellar circuit and cellular plasticity at different sites. Previous work has established plasticity in brain slices and suggested plausible sites of behavioral learning. We now reveal what actually happens in the cerebellum during short-term learning. We monitor the expression of plasticity in the simple-spike firing of cerebellar Purkinje cells during trial-over-trial learning in smooth pursuit eye movements of monkeys. Our findings imply that: 1) a single complex-spike response driven by one instruction for learning causes short-term plasticity in a Purkinje cell’s mossy fiber/parallel-fiber input pathways; 2) complex-spike responses and simple-spike firing rate are correlated across the Purkinje cell population; and 3) simple-spike firing rate at the time of an instruction for learning modulates the probability of a complex-spike response, possibly through a disynaptic feedback pathway to the inferior olive. These mechanisms may participate in long-term motor learning. DOI: http://dx.doi.org/10.7554/eLife.01574.001 PMID:24381248

Musical Sequence Learning and EEG Correlates of Audiomotor Processing

PubMed Central

Schalles, Matt D.; Pineda, Jaime A.

2015-01-01

Our motor and auditory systems are functionally connected during musical performance, and functional imaging suggests that the association is strong enough that passive music listening can engage the motor system. As predictive coding constrains movement sequence selections, could the motor system contribute to sequential processing of musical passages? If this is the case, then we hypothesized that the motor system should respond preferentially to passages of music that contain similar sequential information, even if other aspects of music, such as the absolute pitch, have been altered. We trained piano naive subjects with a learn-to play-by-ear paradigm, to play a simple melodic sequence over five days. After training, we recorded EEG of subjects listening to the song they learned to play, a transposed version of that song, and a control song with different notes and sequence from the learned song. Beta band power over sensorimotor scalp showed increased suppression for the learned song, a moderate level of suppression for the transposed song, and no suppression for the control song. As beta power is associated with attention and motor processing, we interpret this as support of the motor system's activity during covert perception of music one can play and similar musical sequences. PMID:26527118

An associative model of adaptive inference for learning word-referent mappings.

PubMed

Kachergis, George; Yu, Chen; Shiffrin, Richard M

2012-04-01

People can learn word-referent pairs over a short series of individually ambiguous situations containing multiple words and referents (Yu & Smith, 2007, Cognition 106: 1558-1568). Cross-situational statistical learning relies on the repeated co-occurrence of words with their intended referents, but simple co-occurrence counts cannot explain the findings. Mutual exclusivity (ME: an assumption of one-to-one mappings) can reduce ambiguity by leveraging prior experience to restrict the number of word-referent pairings considered but can also block learning of non-one-to-one mappings. The present study first trained learners on one-to-one mappings with varying numbers of repetitions. In late training, a new set of word-referent pairs were introduced alongside pretrained pairs; each pretrained pair consistently appeared with a new pair. Results indicate that (1) learners quickly infer new pairs in late training on the basis of their knowledge of pretrained pairs, exhibiting ME; and (2) learners also adaptively relax the ME bias and learn two-to-two mappings involving both pretrained and new words and objects. We present an associative model that accounts for both results using competing familiarity and uncertainty biases.

Contributions of the hippocampus to feedback learning

PubMed Central

Dickerson, Kathryn C.; Delgado, Mauricio R.

2015-01-01

Humans learn about the world in a variety of manners, including by observation, by associating cues in the environment, and via feedback. Across species, two brain structures have been predominantly involved in these learning processes: the hippocampus—supporting learning via observation and paired association—and the striatum—critical for feedback learning. This simple dichotomy, however, has recently been challenged by reports of hippocampal engagement in feedback learning, although the role of the hippocampus is not fully understood. The purpose of this experiment was to characterize the hippocampal response during feedback learning by manipulating varying levels of memory interference. Consistent with prior reports, feedback learning recruited the striatum and midbrain. Notably, feedback learning also engaged the hippocampus. The level of activity in these regions was modulated by the degree of memory interference, such that the greatest activation occurred during the highest level of memory interference. Importantly, the accuracy of information learned via feedback correlated with hippocampal activation and was reduced by the presence of high memory interference. Taken together, these findings provide evidence of hippocampal involvement in feedback learning by demonstrating both its relevance for the accuracy of information learned via feedback and its susceptibility to interference. PMID:26055632

Biological complexity and adaptability of simple mammalian olfactory memory systems.

PubMed

Brennan, P; Keverne, E B

2015-03-01

Chemosensory systems play vital roles in the lives of most mammals, including the detection and identification of predators, as well as sex and reproductive status and the identification of individual conspecifics. All of these capabilities require a process of recognition involving a combination of innate (kairomonal/pheromonal) and learned responses. Across very different phylogenies, the mechanisms for pheromonal and odour learning have much in common. They are frequently associated with plasticity of GABA-ergic feedback at the initial level of processing the chemosensory information, which enhances its pattern separation capability. Association of odourant features into an odour object primarily involves anterior piriform cortex for non-social odours. However, the medial amygdala appears to be involved in both the recognition of social odours and their association with chemosensory information sensed by the vomeronasal system. Unusually not only the sensory neurons themselves, but also the GABA-ergic interneurons in the olfactory bulb are continually being replaced, with implications for the induction and maintenance of learned chemosensory responses. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

A simple statistical model for geomagnetic reversals

NASA Technical Reports Server (NTRS)

Constable, Catherine

1990-01-01

The diversity of paleomagnetic records of geomagnetic reversals now available indicate that the field configuration during transitions cannot be adequately described by simple zonal or standing field models. A new model described here is based on statistical properties inferred from the present field and is capable of simulating field transitions like those observed. Some insight is obtained into what one can hope to learn from paleomagnetic records. In particular, it is crucial that the effects of smoothing in the remanence acquisition process be separated from true geomagnetic field behavior. This might enable us to determine the time constants associated with the dominant field configuration during a reversal.

Computer-based auditory training (CBAT): benefits for children with language- and reading-related learning difficulties.

PubMed

Loo, Jenny Hooi Yin; Bamiou, Doris-Eva; Campbell, Nicci; Luxon, Linda M

2010-08-01

This article reviews the evidence for computer-based auditory training (CBAT) in children with language, reading, and related learning difficulties, and evaluates the extent it can benefit children with auditory processing disorder (APD). Searches were confined to studies published between 2000 and 2008, and they are rated according to the level of evidence hierarchy proposed by the American Speech-Language Hearing Association (ASHA) in 2004. We identified 16 studies of two commercially available CBAT programs (13 studies of Fast ForWord (FFW) and three studies of Earobics) and five further outcome studies of other non-speech and simple speech sounds training, available for children with language, learning, and reading difficulties. The results suggest that, apart from the phonological awareness skills, the FFW and Earobics programs seem to have little effect on the language, spelling, and reading skills of children. Non-speech and simple speech sounds training may be effective in improving children's reading skills, but only if it is delivered by an audio-visual method. There is some initial evidence to suggest that CBAT may be of benefit for children with APD. Further research is necessary, however, to substantiate these preliminary findings.

Advances and limitations of visual conditioning protocols in harnessed bees.

PubMed

Avarguès-Weber, Aurore; Mota, Theo

2016-10-01

Bees are excellent invertebrate models for studying visual learning and memory mechanisms, because of their sophisticated visual system and impressive cognitive capacities associated with a relatively simple brain. Visual learning in free-flying bees has been traditionally studied using an operant conditioning paradigm. This well-established protocol, however, can hardly be combined with invasive procedures for studying the neurobiological basis of visual learning. Different efforts have been made to develop protocols in which harnessed honey bees could associate visual cues with reinforcement, though learning performances remain poorer than those obtained with free-flying animals. Especially in the last decade, the intention of improving visual learning performances of harnessed bees led many authors to adopt distinct visual conditioning protocols, altering parameters like harnessing method, nature and duration of visual stimulation, number of trials, inter-trial intervals, among others. As a result, the literature provides data hardly comparable and sometimes contradictory. In the present review, we provide an extensive analysis of the literature available on visual conditioning of harnessed bees, with special emphasis on the comparison of diverse conditioning parameters adopted by different authors. Together with this comparative overview, we discuss how these diverse conditioning parameters could modulate visual learning performances of harnessed bees. Copyright © 2016 Elsevier Ltd. All rights reserved.

Knowledge-Integration Processes and Learning Outcomes Associated with a Self-Diagnosis Activity: The Case of 5th-Graders Studying Simple Fractions

ERIC Educational Resources Information Center

Safadi, Rafi'

2018-01-01

I examined how well a self-diagnosis activity engages students in knowledge-integration processes, and its impact on students' mathematical achievements. The self-diagnosis activity requires students to self-diagnose their solutions to problems that they have solved on their own--namely, to identify where they went wrong and to explain the nature…

Application of experiential learning model using simple physical kit to increase attitude toward physics student senior high school in fluid

NASA Astrophysics Data System (ADS)

Johari, A. H.; Muslim

2018-05-01

Experiential learning model using simple physics kit has been implemented to get a picture of improving attitude toward physics senior high school students on Fluid. This study aims to obtain a description of the increase attitudes toward physics senior high school students. The research method used was quasi experiment with non-equivalent pretest -posttest control group design. Two class of tenth grade were involved in this research 28, 26 students respectively experiment class and control class. Increased Attitude toward physics of senior high school students is calculated using an attitude scale consisting of 18 questions. Based on the experimental class test average of 86.5% with the criteria of almost all students there is an increase and in the control class of 53.75% with the criteria of half students. This result shows that the influence of experiential learning model using simple physics kit can improve attitude toward physics compared to experiential learning without using simple physics kit.

A complex mTOR response in habituation paradigms for a social signal in adult songbirds.

PubMed

Ahmadiantehrani, Somayeh; Gores, Elisa O; London, Sarah E

2018-06-01

Nonassociative learning is considered simple because it depends on presentation of a single stimulus, but it likely reflects complex molecular signaling. To advance understanding of the molecular mechanisms of one form of nonassociative learning, habituation, for ethologically relevant signals we examined song recognition learning in adult zebra finches. These colonial songbirds learn the unique song of individuals, which helps establish and maintain mate and other social bonds, and informs appropriate behavioral interactions with specific birds. We leveraged prior work demonstrating behavioral habituation for individual songs, and extended the molecular framework correlated with this behavior by investigating the mechanistic Target of Rapamycin (mTOR) signaling cascade. We hypothesized that mTOR may contribute to habituation because it integrates a variety of upstream signals and enhances associative learning, and it crosstalks with another cascade previously associated with habituation, ERK/ZENK. To begin probing for a possible role for mTOR in song recognition learning, we used a combination of song playback paradigms and bidirectional dysregulation of mTORC1 activation. We found that mTOR demonstrates the molecular signatures of a habituation mechanism, and that its manipulation reveals the complexity of processes that may be invoked during nonassociative learning. These results thus expand the molecular targets for habituation studies and raise new questions about neural processing of complex natural signals. © 2018 Ahmadiantehrani et al.; Published by Cold Spring Harbor Laboratory Press.

Abnormal experimentally- and behaviorally-induced LTP-like plasticity in focal hand dystonia.

PubMed

Belvisi, Daniele; Suppa, Antonio; Marsili, Luca; Di Stasio, Flavio; Parvez, Ahmad Khandker; Agostino, Rocco; Fabbrini, Giovanni; Berardelli, Alfredo

2013-02-01

Idiopathic focal hand dystonia (FHD) arises from abnormal plasticity in the primary motor cortex (M1) possibly reflecting abnormal sensori-motor integration processes. In this transcranial magnetic stimulation (TMS) study in FHD, we evaluated changes in motor evoked potentials (MEPs) after intermittent theta burst stimulation (iTBS) and paired associative stimulation (PAS), techniques that elicit different forms of experimentally-induced long-term potentiation (LTP)-like plasticity in M1. We also examined behaviorally-induced LTP-like plasticity as reflected by early motor learning of a simple motor task. We studied 14 patients with FHD and 14 healthy subjects. MEPs were recorded before and after iTBS and PAS at the 25 ms interstimulus interval (PAS(25)) in separate sessions. Subjects did a simple motor task entailing repetitive index finger abductions. To measure early motor learning we tested practice-related improvement in peak velocity and peak acceleration. In FHD patients iTBS failed to elicit the expected MEP changes and PAS(25) induced abnormally increased MEPs in target and non-target muscles. In the experiment testing early motor learning, patients lacked the expected practice-related changes in kinematic variables. In FHD, the degree of early motor learning correlated with patients' clinical features. We conclude that experimentally-induced (iTBS and PAS) and behaviorally-induced LTP-like plasticity are both altered in FHD. Copyright © 2012 Elsevier Inc. All rights reserved.

Responses to a simple barter task in chimpanzees, Pan troglodytes.

PubMed

Brosnan, Sarah F; de Waal, Frans B M

2005-07-01

Chimpanzees (Pan troglodytes) frequently participate in social exchange involving multiple goods and services of variable value, yet they have not been tested in a formalized situation to see whether they can barter using multiple tokens and rewards. We set up a simple barter economy with two tokens and two associated rewards and tested chimpanzees on their ability to obtain rewards by returning the matching token in situations in which their access to tokens was unlimited or limited. Chimpanzees easily learned to associate value with the tokens, as expected, and did barter, but followed a simple strategy of favoring the higher-value token, regardless of the reward proffered, instead of a more complex but more effective strategy of returning the token that matched the reward. This response is similar to that shown by capuchin monkeys in our previous study. We speculate that this response, while not ideal, may be sufficient to allow for stability of the social exchange system in these primates, and that the importance of social barter to both species may have led to this convergence of strategies.

SUSTAIN: a network model of category learning.

PubMed

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.

Investigating implicit statistical learning mechanisms through contextual cueing.

PubMed

Goujon, Annabelle; Didierjean, André; Thorpe, Simon

2015-09-01

Since its inception, the contextual cueing (CC) paradigm has generated considerable interest in various fields of cognitive sciences because it constitutes an elegant approach to understanding how statistical learning (SL) mechanisms can detect contextual regularities during a visual search. In this article we review and discuss five aspects of CC: (i) the implicit nature of learning, (ii) the mechanisms involved in CC, (iii) the mediating factors affecting CC, (iv) the generalization of CC phenomena, and (v) the dissociation between implicit and explicit CC phenomena. The findings suggest that implicit SL is an inherent component of ongoing processing which operates through clustering, associative, and reinforcement processes at various levels of sensory-motor processing, and might result from simple spike-timing-dependent plasticity. Copyright © 2015 Elsevier Ltd. All rights reserved.

PCANet: A Simple Deep Learning Baseline for Image Classification?

PubMed

Chan, Tsung-Han; Jia, Kui; Gao, Shenghua; Lu, Jiwen; Zeng, Zinan; Ma, Yi

2015-12-01

In this paper, we propose a very simple deep learning network for image classification that is based on very basic data processing components: 1) cascaded principal component analysis (PCA); 2) binary hashing; and 3) blockwise histograms. In the proposed architecture, the PCA is employed to learn multistage filter banks. This is followed by simple binary hashing and block histograms for indexing and pooling. This architecture is thus called the PCA network (PCANet) and can be extremely easily and efficiently designed and learned. For comparison and to provide a better understanding, we also introduce and study two simple variations of PCANet: 1) RandNet and 2) LDANet. They share the same topology as PCANet, but their cascaded filters are either randomly selected or learned from linear discriminant analysis. We have extensively tested these basic networks on many benchmark visual data sets for different tasks, including Labeled Faces in the Wild (LFW) for face verification; the MultiPIE, Extended Yale B, AR, Facial Recognition Technology (FERET) data sets for face recognition; and MNIST for hand-written digit recognition. Surprisingly, for all tasks, such a seemingly naive PCANet model is on par with the state-of-the-art features either prefixed, highly hand-crafted, or carefully learned [by deep neural networks (DNNs)]. Even more surprisingly, the model sets new records for many classification tasks on the Extended Yale B, AR, and FERET data sets and on MNIST variations. Additional experiments on other public data sets also demonstrate the potential of PCANet to serve as a simple but highly competitive baseline for texture classification and object recognition.

Dissociating basal forebrain and medial temporal amnesic syndromes: insights from classical conditioning.

PubMed

Myer, Catherine E; Bryant, Deborah; DeLuca, John; Gluck, Mark A

2002-01-01

In humans, anterograde amnesia can result from damage to the medial temporal (MT) lobes (including hippocampus), as well as to other brain areas such as basal forebrain. Results from animal classical conditioning studies suggest that there may be qualitative differences in the memory impairment following MT vs. basal forebrain damage. Specifically, delay eyeblink conditioning is spared after MT damage in animals and humans, but impaired in animals with basal forebrain damage. Recently, we have likewise shown delay eyeblink conditioning impairment in humans with amnesia following anterior communicating artery (ACoA) aneurysm rupture, which damages the basal forebrain. Another associative learning task, a computer-based concurrent visual discrimination, also appears to be spared in MT amnesia while ACoA amnesics are slower to learn the discriminations. Conversely, animal and computational models suggest that, even though MT amnesics may learn quickly, they may learn qualitatively differently from controls, and these differences may result in impaired transfer when familiar information is presented in novel combinations. Our initial data suggests such a two-phase learning and transfer task may provide a double dissociation between MT amnesics (spared initial learning but impaired transfer) and ACoA amnesics (slow initial learning but spared transfer). Together, these emerging data suggest that there are subtle but dissociable differences in the amnesic syndrome following damage to the MT lobes vs. basal forebrain, and that these differences may be most visible in non-declarative tasks such as eyeblink classical conditioning and simple associative learning.

Hebbian based learning with winner-take-all for spiking neural networks

NASA Astrophysics Data System (ADS)

Gupta, Ankur; Long, Lyle

2009-03-01

Learning methods for spiking neural networks are not as well developed as the traditional neural networks that widely use back-propagation training. We propose and implement a Hebbian based learning method with winner-take-all competition for spiking neural networks. This approach is spike time dependent which makes it naturally well suited for a network of spiking neurons. Homeostasis with Hebbian learning is implemented which ensures stability and quicker learning. Homeostasis implies that the net sum of incoming weights associated with a neuron remains the same. Winner-take-all is also implemented for competitive learning between output neurons. We implemented this learning rule on a biologically based vision processing system that we are developing, and use layers of leaky integrate and fire neurons. The network when presented with 4 bars (or Gabor filters) of different orientation learns to recognize the bar orientations (or Gabor filters). After training, each output neuron learns to recognize a bar at specific orientation and responds by firing more vigorously to that bar and less vigorously to others. These neurons are found to have bell shaped tuning curves and are similar to the simple cells experimentally observed by Hubel and Wiesel in the striate cortex of cat and monkey.

Transformational Learning: Reflections of an Adult Learning Story

ERIC Educational Resources Information Center

Foote, Laura S.

2015-01-01

Transformational learning, narrative learning, and spiritual learning frame adult experiences in new and exciting ways. These types of learning can involve a simple transformation of belief or opinion or a radical transformation involving one's total perspective; learning may occur abruptly or incrementally. Education should liberate students from…

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…

Effects of Toy Crane Design-Based Learning on Simple Machines

ERIC Educational Resources Information Center

Korur, Fikret; Efe, Gülfem; Erdogan, Fisun; Tunç, Berna

2017-01-01

The aim of this 2-group study was to investigate the following question: Are there significant differences between scaffolded design-based learning controlled using 7 forms and teacher-directed instruction methods for the toy crane project on grade 7 students' posttest scores on the simple machines achievement test, attitude toward simple…

Modelling unsupervised online-learning of artificial grammars: linking implicit and statistical learning.

PubMed

Rohrmeier, Martin A; Cross, Ian

2014-07-01

Humans rapidly learn complex structures in various domains. Findings of above-chance performance of some untrained control groups in artificial grammar learning studies raise questions about the extent to which learning can occur in an untrained, unsupervised testing situation with both correct and incorrect structures. The plausibility of unsupervised online-learning effects was modelled with n-gram, chunking and simple recurrent network models. A novel evaluation framework was applied, which alternates forced binary grammaticality judgments and subsequent learning of the same stimulus. Our results indicate a strong online learning effect for n-gram and chunking models and a weaker effect for simple recurrent network models. Such findings suggest that online learning is a plausible effect of statistical chunk learning that is possible when ungrammatical sequences contain a large proportion of grammatical chunks. Such common effects of continuous statistical learning may underlie statistical and implicit learning paradigms and raise implications for study design and testing methodologies. Copyright © 2014 Elsevier Inc. All rights reserved.

Some simple guides to finding useful information in exploration geochemical data

USGS Publications Warehouse

Singer, D.A.; Kouda, R.

2001-01-01

Most regional geochemistry data reflect processes that can produce superfluous bits of noise and, perhaps, information about the mineralization process of interest. There are two end-member approaches to finding patterns in geochemical data-unsupervised learning and supervised learning. In unsupervised learning, data are processed and the geochemist is given the task of interpreting and identifying possible sources of any patterns. In supervised learning, data from known subgroups such as rock type, mineralized and nonmineralized, and types of mineralization are used to train the system which then is given unknown samples to classify into these subgroups. To locate patterns of interest, it is helpful to transform the data and to remove unwanted masking patterns. With trace elements use of a logarithmic transformation is recommended. In many situations, missing censored data can be estimated using multiple regression of other uncensored variables on the variable with censored values. In unsupervised learning, transformed values can be standardized, or normalized, to a Z-score by subtracting the subset's mean and dividing by its standard deviation. Subsets include any source of differences that might be related to processes unrelated to the target sought such as different laboratories, regional alteration, analytical procedures, or rock types. Normalization removes effects of different means and measurement scales as well as facilitates comparison of spatial patterns of elements. These adjustments remove effects of different subgroups and hopefully leave on the map the simple and uncluttered pattern(s) related to the mineralization only. Supervised learning methods, such as discriminant analysis and neural networks, offer the promise of consistent and, in certain situations, unbiased estimates of where mineralization might exist. These methods critically rely on being trained with data that encompasses all populations fairly and that can possibly fall into only the identified populations. ?? 2001 International Association for Mathematical Geology.

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

NASA Astrophysics Data System (ADS)

Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; Del Giudice, Paolo

2015-10-01

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a ‘basin’ of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems.

PubMed

Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; del Giudice, Paolo

2015-10-14

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a 'basin' of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.

The Nucleus Accumbens and Pavlovian Reward Learning

PubMed Central

Day, Jeremy J.

2011-01-01

The ability to form associations between predictive environmental events and rewarding outcomes is a fundamental aspect of learned behavior. This apparently simple ability likely requires complex neural processing evolved to identify, seek, and utilize natural rewards and redirect these activities based on updated sensory information. Emerging evidence from both animal and human research suggests that this type of processing is mediated in part by the nucleus accumbens and a closely associated network of brain structures. The nucleus accumbens is required for a number of reward-related behaviors, and processes specific information about reward availability, value, and context. Additionally, this structure is critical for the acquisition and expression of most Pavlovian stimulus-reward relationships, and cues that predict rewards produce robust changes in neural activity in the nucleus accumbens. While processing within the nucleus accumbens may enable or promote Pavlovian reward learning in natural situations, it has also been implicated in aspects of human drug addiction, including the ability of drug-paired cues to control behavior. This article will provide a critical review of the existing animal and human literature concerning the role of the NAc in Pavlovian learning with non-drug rewards and consider some clinical implications of these findings. PMID:17404375

Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect

PubMed Central

Folia, Vasiliki; Petersson, Karl Magnus

2014-01-01

In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs. PMID:24550865

Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect.

PubMed

Folia, Vasiliki; Petersson, Karl Magnus

2014-01-01

In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.

Factors affecting metacognition of undergraduate nursing students in a blended learning environment.

PubMed

Hsu, Li-Ling; Hsieh, Suh-Ing

2014-06-01

This paper is a report of a study to examine the influence of demographic, learning involvement and learning performance variables on metacognition of undergraduate nursing students in a blended learning environment. A cross-sectional, correlational survey design was adopted. Ninety-nine students invited to participate in the study were enrolled in a professional nursing ethics course at a public nursing college. The blended learning intervention is basically an assimilation of classroom learning and online learning. Simple linear regression showed significant associations between frequency of online dialogues, the Case Analysis Attitude Scale scores, the Case Analysis Self Evaluation Scale scores, the Blended Learning Satisfaction Scale scores, and Metacognition Scale scores. Multiple linear regression indicated that frequency of online dialogues, the Case Analysis Self Evaluation Scale and the Blended Learning Satisfaction Scale were significant independent predictors of metacognition. Overall, the model accounted for almost half of the variance in metacognition. The blended learning module developed in this study proved successful in the end as a catalyst for the exercising of metacognitive abilities by the sample of nursing students. Learners are able to develop metacognitive ability in comprehension, argumentation, reasoning and various forms of higher order thinking through the blended learning process. © 2013 Wiley Publishing Asia Pty Ltd.

Learning from Simple Ebooks, Online Cases or Classroom Teaching When Acquiring Complex Knowledge. A Randomized Controlled Trial in Respiratory Physiology and Pulmonology

PubMed Central

Worm, Bjarne Skjødt

2013-01-01

Background and Aims E-learning is developing fast because of the rapid increased use of smartphones, tablets and portable computers. We might not think of it as e-learning, but today many new e-books are in fact very complex electronic teaching platforms. It is generally accepted that e-learning is as effective as classroom teaching methods, but little is known about its value in relaying contents of different levels of complexity to students. We set out to investigate e-learning effects on simple recall and complex problem-solving compared to classroom teaching. Methods 63 nurses specializing in anesthesiology were evenly randomized into three groups. They were given internet-based knowledge tests before and after attending a teaching module about respiratory physiology and pulmonology. The three groups was either an e-learning group with eBook teaching material, an e-learning group with case-based teaching or a group with face-to-face case-based classroom teaching. After the module the students were required to answer a post-test. Time spent and the number of logged into the system was also measured. Results For simple recall, all methods were equally effective. For problem-solving, the eCase group achieved a comparable knowledge level to classroom teaching, while textbook learning was inferior to both (p<0.01). The textbook group also spent the least amount of time on acquiring knowledge (33 minutes, p<0.001), while the eCase group spent significantly more time on the subject (53 minutes, p<0.001) and logged into the system significantly more (2.8 vs 1.6, p<0.001). Conclusions E-learning based cases are an effective tool for teaching complex knowledge and problem-solving ability, but future studies using higher-level e-learning are encouraged.Simple recall skills, however, do not require any particular learning method. PMID:24039917

Learning from simple ebooks, online cases or classroom teaching when acquiring complex knowledge. A randomized controlled trial in respiratory physiology and pulmonology.

PubMed

Worm, Bjarne Skjødt

2013-01-01

E-learning is developing fast because of the rapid increased use of smartphones, tablets and portable computers. We might not think of it as e-learning, but today many new e-books are in fact very complex electronic teaching platforms. It is generally accepted that e-learning is as effective as classroom teaching methods, but little is known about its value in relaying contents of different levels of complexity to students. We set out to investigate e-learning effects on simple recall and complex problem-solving compared to classroom teaching. 63 nurses specializing in anesthesiology were evenly randomized into three groups. They were given internet-based knowledge tests before and after attending a teaching module about respiratory physiology and pulmonology. The three groups was either an e-learning group with eBook teaching material, an e-learning group with case-based teaching or a group with face-to-face case-based classroom teaching. After the module the students were required to answer a post-test. Time spent and the number of logged into the system was also measured. For simple recall, all methods were equally effective. For problem-solving, the eCase group achieved a comparable knowledge level to classroom teaching, while textbook learning was inferior to both (p<0.01). The textbook group also spent the least amount of time on acquiring knowledge (33 minutes, p<0.001), while the eCase group spent significantly more time on the subject (53 minutes, p<0.001) and logged into the system significantly more (2.8 vs 1.6, p<0.001). E-learning based cases are an effective tool for teaching complex knowledge and problem-solving ability, but future studies using higher-level e-learning are encouraged.Simple recall skills, however, do not require any particular learning method.

Subcellular, Cellular and Circuit Mechanisms underlying Classical Conditioning in Hermissenda crassicornis

PubMed Central

2009-01-01

A breakthrough for studying the neuronal basis of learning emerged when invertebrates with simple nervous systems, such as the sea slug Hermissenda crassicornis, were shown to exhibit classical conditioning. Hermissenda learns to associate light with turbulence: prior to learning, naive animals move toward light (phototaxis) and contract their foot in response to turbulence; after learning, conditioned animals delay phototaxis in response to light. The photoreceptors of the eye, which receive monosynaptic inputs from statocyst hair cells, are both sensory neurons and the first site of sensory convergence. The memory of light associated with turbulence is stored as changes in intrinsic and synaptic currents in these photoreceptors. The subcellular mechanisms producing these changes include activation of protein kinase C and MAP kinase, which act as coincidence detectors because they are activated by convergent signaling pathways. Pathways of interneurons and motorneurons, where additional changes in excitability and synaptic connections are found, contribute to delayed phototaxis. Bursting activity recorded at several points suggest the existence of small networks that produce complex spatio-temporal firing patterns. Thus, the change in behavior may be produced by a non-linear transformation of spatio-temporal firing patterns caused by plasticity of synaptic and intrinsic channels. The change in currents and the activation of PKC and MAPK produced by associative learning are similar to that observed in hippocampal and cerebellar neurons after rabbit classical conditioning, suggesting that these represent general mechanisms of memory storage. Thus, the knowledge gained from further study of Hermissenda will continue to illuminate mechanisms of mammalian learning. PMID:16437555

Behaviourally-inhibited temperament and female sex, two vulnerability factors for anxiety disorders, facilitate conditioned avoidance (also) in humans

PubMed Central

Sheynin, Jony; Beck, Kevin D.; Pang, Kevin C.H.; Servatius, Richard J.; Shikari, Saima; Ostovich, Jacqueline; Myers, Catherine E.

2014-01-01

Acquisition and maintenance of avoidance behaviour is a key feature of all human anxiety disorders. Animal models have been useful in understanding how anxiety vulnerability could translate into avoidance learning. For example, behaviourally-inhibited temperament and female sex, two vulnerability factors for clinical anxiety, are associated with faster acquisition of avoidance responses in rodents. However, to date, the translation of such empirical data to human populations has been limited since many features of animal avoidance paradigms are not typically captured in human research. Here, using a computer-based task that captures many features of rodent escape-avoidance learning paradigms, we investigated whether avoidance learning would be faster in humans with inhibited temperament and/or female sex and, if so, whether this facilitation would take the same form. Results showed that, as in rats, both vulnerability factors were associated with facilitated acquisition of avoidance behaviour in humans. Specifically, inhibited temperament was specifically associated with higher rate of avoidance responding, while female sex was associated with longer avoidance duration. These findings strengthen the direct link between animal avoidance work and human anxiety vulnerability, further motivating the study of animal models while also providing a simple testbed for a direct human testing. PMID:24412263

Osteoporosis risk prediction for bone mineral density assessment of postmenopausal women using machine learning.

PubMed

Yoo, Tae Keun; Kim, Sung Kean; Kim, Deok Won; Choi, Joon Yul; Lee, Wan Hyung; Oh, Ein; Park, Eun-Cheol

2013-11-01

A number of clinical decision tools for osteoporosis risk assessment have been developed to select postmenopausal women for the measurement of bone mineral density. We developed and validated machine learning models with the aim of more accurately identifying the risk of osteoporosis in postmenopausal women compared to the ability of conventional clinical decision tools. We collected medical records from Korean postmenopausal women based on the Korea National Health and Nutrition Examination Surveys. The training data set was used to construct models based on popular machine learning algorithms such as support vector machines (SVM), random forests, artificial neural networks (ANN), and logistic regression (LR) based on simple surveys. The machine learning models were compared to four conventional clinical decision tools: osteoporosis self-assessment tool (OST), osteoporosis risk assessment instrument (ORAI), simple calculated osteoporosis risk estimation (SCORE), and osteoporosis index of risk (OSIRIS). SVM had significantly better area under the curve (AUC) of the receiver operating characteristic than ANN, LR, OST, ORAI, SCORE, and OSIRIS for the training set. SVM predicted osteoporosis risk with an AUC of 0.827, accuracy of 76.7%, sensitivity of 77.8%, and specificity of 76.0% at total hip, femoral neck, or lumbar spine for the testing set. The significant factors selected by SVM were age, height, weight, body mass index, duration of menopause, duration of breast feeding, estrogen therapy, hyperlipidemia, hypertension, osteoarthritis, and diabetes mellitus. Considering various predictors associated with low bone density, the machine learning methods may be effective tools for identifying postmenopausal women at high risk for osteoporosis.

The anatomy of E-Learning tools: Does software usability influence learning outcomes?

PubMed

Van Nuland, Sonya E; Rogers, Kem A

2016-07-08

Reductions in laboratory hours have increased the popularity of commercial anatomy e-learning tools. It is critical to understand how the functionality of such tools can influence the mental effort required during the learning process, also known as cognitive load. Using dual-task methodology, two anatomical e-learning tools were examined to determine the effect of their design on cognitive load during two joint learning exercises. A.D.A.M. Interactive Anatomy is a simplistic, two-dimensional tool that presents like a textbook, whereas Netter's 3D Interactive Anatomy has a more complex three-dimensional usability that allows structures to be rotated. It was hypothesized that longer reaction times on an observation task would be associated with the more complex anatomical software (Netter's 3D Interactive Anatomy), indicating a higher cognitive load imposed by the anatomy software, which would result in lower post-test scores. Undergraduate anatomy students from Western University, Canada (n = 70) were assessed using a baseline knowledge test, Stroop observation task response times (a measure of cognitive load), mental rotation test scores, and an anatomy post-test. Results showed that reaction times and post-test outcomes were similar for both tools, whereas mental rotation test scores were positively correlated with post-test values when students used Netter's 3D Interactive Anatomy (P = 0.007), but not when they used A.D.A.M. Interactive Anatomy. This suggests that a simple e-learning tool, such as A.D.A.M. Interactive Anatomy, is as effective as more complicated tools, such as Netter's 3D Interactive Anatomy, and does not academically disadvantage those with poor spatial ability. Anat Sci Educ 9: 378-390. © 2015 American Association of Anatomists. © 2015 American Association of Anatomists.

Episodic Memory Encoding Interferes with Reward Learning and Decreases Striatal Prediction Errors

PubMed Central

Braun, Erin Kendall; Daw, Nathaniel D.

2014-01-01

Learning is essential for adaptive decision making. The striatum and its dopaminergic inputs are known to support incremental reward-based learning, while the hippocampus is known to support encoding of single events (episodic memory). Although traditionally studied separately, in even simple experiences, these two types of learning are likely to co-occur and may interact. Here we sought to understand the nature of this interaction by examining how incremental reward learning is related to concurrent episodic memory encoding. During the experiment, human participants made choices between two options (colored squares), each associated with a drifting probability of reward, with the goal of earning as much money as possible. Incidental, trial-unique object pictures, unrelated to the choice, were overlaid on each option. The next day, participants were given a surprise memory test for these pictures. We found that better episodic memory was related to a decreased influence of recent reward experience on choice, both within and across participants. fMRI analyses further revealed that during learning the canonical striatal reward prediction error signal was significantly weaker when episodic memory was stronger. This decrease in reward prediction error signals in the striatum was associated with enhanced functional connectivity between the hippocampus and striatum at the time of choice. Our results suggest a mechanism by which memory encoding may compete for striatal processing and provide insight into how interactions between different forms of learning guide reward-based decision making. PMID:25378157

One Stroke at a Time

ERIC Educational Resources Information Center

Hollibaugh, Molly

2012-01-01

At first glance, a Zentangle creation can seem intricate and complicated. But, when you learn how it is done, you realize how simple it is. Zentangles are patterns, or "tangles," that have been reduced to a simple sequence of elemental strokes. When you learn to focus on each stroke you find yourself capable of things that you may have once…

Using Simple Machines to Leverage Learning

ERIC Educational Resources Information Center

Dotger, Sharon

2008-01-01

What would your students say if you told them they could lift you off the ground using a block and a board? Using a simple machine, they'll find out they can, and they'll learn about work, energy, and motion in the process! In addition, this integrated lesson gives students the opportunity to investigate variables while practicing measurement…

Pulling My Gut out--Simple Tools for Engaging Students in Gross Anatomy Lectures

ERIC Educational Resources Information Center

Chan, Lap Ki

2010-01-01

A lecture is not necessarily a monologue, promoting only passive learning. If appropriate techniques are used, a lecture can stimulate active learning too. One such method is demonstration, which can engage learners' attention and increase the interaction between the lecturer and the learners. This article describes two simple and useful tools for…

Causal learning and inference as a rational process: the new synthesis.

PubMed

Holyoak, Keith J; Cheng, Patricia W

2011-01-01

Over the past decade, an active line of research within the field of human causal learning and inference has converged on a general representational framework: causal models integrated with bayesian probabilistic inference. We describe this new synthesis, which views causal learning and inference as a fundamentally rational process, and review a sample of the empirical findings that support the causal framework over associative alternatives. Causal events, like all events in the distal world as opposed to our proximal perceptual input, are inherently unobservable. A central assumption of the causal approach is that humans (and potentially nonhuman animals) have been designed in such a way as to infer the most invariant causal relations for achieving their goals based on observed events. In contrast, the associative approach assumes that learners only acquire associations among important observed events, omitting the representation of the distal relations. By incorporating bayesian inference over distributions of causal strength and causal structures, along with noisy-logical (i.e., causal) functions for integrating the influences of multiple causes on a single effect, human judgments about causal strength and structure can be predicted accurately for relatively simple causal structures. Dynamic models of learning based on the causal framework can explain patterns of acquisition observed with serial presentation of contingency data and are consistent with available neuroimaging data. The approach has been extended to a diverse range of inductive tasks, including category-based and analogical inferences.

Effect of reinforcement learning on coordination of multiangent systems

NASA Astrophysics Data System (ADS)

Bukkapatnam, Satish T. S.; Gao, Greg

2000-12-01

For effective coordination of distributed environments involving multiagent systems, learning ability of each agent in the environment plays a crucial role. In this paper, we develop a simple group learning method based on reinforcement, and study its effect on coordination through application to a supply chain procurement scenario involving a computer manufacturer. Here, all parties are represented by self-interested, autonomous agents, each capable of performing specific simple tasks. They negotiate with each other to perform complex tasks and thus coordinate supply chain procurement. Reinforcement learning is intended to enable each agent to reach a best negotiable price within a shortest possible time. Our simulations of the application scenario under different learning strategies reveals the positive effects of reinforcement learning on an agent's as well as the system's performance.

Too Good to be True? Ideomotor Theory from a Computational Perspective

PubMed Central

Herbort, Oliver; Butz, Martin V.

2012-01-01

In recent years, Ideomotor Theory has regained widespread attention and sparked the development of a number of theories on goal-directed behavior and learning. However, there are two issues with previous studies’ use of Ideomotor Theory. Although Ideomotor Theory is seen as very general, it is often studied in settings that are considerably more simplistic than most natural situations. Moreover, Ideomotor Theory’s claim that effect anticipations directly trigger actions and that action-effect learning is based on the formation of direct action-effect associations is hard to address empirically. We address these points from a computational perspective. A simple computational model of Ideomotor Theory was tested in tasks with different degrees of complexity. The model evaluation showed that Ideomotor Theory is a computationally feasible approach for understanding efficient action-effect learning for goal-directed behavior if the following preconditions are met: (1) The range of potential actions and effects has to be restricted. (2) Effects have to follow actions within a short time window. (3) Actions have to be simple and may not require sequencing. The first two preconditions also limit human performance and thus support Ideomotor Theory. The last precondition can be circumvented by extending the model with more complex, indirect action generation processes. In conclusion, we suggest that Ideomotor Theory offers a comprehensive framework to understand action-effect learning. However, we also suggest that additional processes may mediate the conversion of effect anticipations into actions in many situations. PMID:23162524

A novel dual-marker expression panel for easy and accurate risk stratification of patients with gastric cancer.

PubMed

Kanda, Mitsuro; Murotani, Kenta; Tanaka, Haruyoshi; Miwa, Takashi; Umeda, Shinichi; Tanaka, Chie; Kobayashi, Daisuke; Hayashi, Masamichi; Hattori, Norifumi; Suenaga, Masaya; Yamada, Suguru; Nakayama, Goro; Fujiwara, Michitaka; Kodera, Yasuhiro

2018-05-07

Development of specific biomarkers is necessary for individualized management of patients with gastric cancer. The aim of this study was to design a simple expression panel comprising novel molecular markers for precise risk stratification. Patients (n = 200) who underwent gastrectomy for gastric cancer were randomly assigned into learning and validation sets. Tissue mRNA expression levels of 15 candidate molecular markers were determined using quantitative PCR analysis. A dual-marker expression panel was created according to concordance index (C-index) values of overall survival for all 105 combinations of two markers in the learning set. The reproducibility and clinical significance of the dual-marker expression panel were evaluated in the validation set. The patient characteristics of the learning and validation sets were well balanced. The C-index values of combinations were significantly higher compared with those of single markers. The panel with the highest C-index (0.718) of the learning set comprised SYT8 and MAGED2, which clearly stratified patients into low-, intermediate-, and high-risk groups. The reproducibility of the panel was demonstrated in the validation set. High expression scores were significantly associated with larger tumor size, vascular invasion, lymph node metastasis, peritoneal metastasis, and advanced disease. The dual-marker expression panel provides a simple tool that clearly stratifies patients with gastric cancer into low-, intermediate-, and high risk after gastrectomy. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Simple yet Hidden Counterexamples in Undergraduate Real Analysis

ERIC Educational Resources Information Center

Shipman, Barbara A.; Shipman, Patrick D.

2013-01-01

We study situations in introductory analysis in which students affirmed false statements as true, despite simple counterexamples that they easily recognized afterwards. The study draws attention to how simple counterexamples can become hidden in plain sight, even in an active learning atmosphere where students proposed simple (as well as more…

A geostationary Earth orbit satellite model using Easy Java Simulation

NASA Astrophysics Data System (ADS)

Wee, Loo Kang; Hwee Goh, Giam

2013-01-01

We develop an Easy Java Simulation (EJS) model for students to visualize geostationary orbits near Earth, modelled using a Java 3D implementation of the EJS 3D library. The simplified physics model is described and simulated using a simple constant angular velocity equation. We discuss four computer model design ideas: (1) a simple and realistic 3D view and associated learning in the real world; (2) comparative visualization of permanent geostationary satellites; (3) examples of non-geostationary orbits of different rotation senses, periods and planes; and (4) an incorrect physics model for conceptual discourse. General feedback from the students has been relatively positive, and we hope teachers will find the computer model useful in their own classes.

Machine Learning Approaches in Cardiovascular Imaging.

PubMed

Henglin, Mir; Stein, Gillian; Hushcha, Pavel V; Snoek, Jasper; Wiltschko, Alexander B; Cheng, Susan

2017-10-01

Cardiovascular imaging technologies continue to increase in their capacity to capture and store large quantities of data. Modern computational methods, developed in the field of machine learning, offer new approaches to leveraging the growing volume of imaging data available for analyses. Machine learning methods can now address data-related problems ranging from simple analytic queries of existing measurement data to the more complex challenges involved in analyzing raw images. To date, machine learning has been used in 2 broad and highly interconnected areas: automation of tasks that might otherwise be performed by a human and generation of clinically important new knowledge. Most cardiovascular imaging studies have focused on task-oriented problems, but more studies involving algorithms aimed at generating new clinical insights are emerging. Continued expansion in the size and dimensionality of cardiovascular imaging databases is driving strong interest in applying powerful deep learning methods, in particular, to analyze these data. Overall, the most effective approaches will require an investment in the resources needed to appropriately prepare such large data sets for analyses. Notwithstanding current technical and logistical challenges, machine learning and especially deep learning methods have much to offer and will substantially impact the future practice and science of cardiovascular imaging. © 2017 American Heart Association, Inc.

Prediction during statistical learning, and implications for the implicit/explicit divide

PubMed Central

Dale, Rick; Duran, Nicholas D.; Morehead, J. Ryan

2012-01-01

Accounts of statistical learning, both implicit and explicit, often invoke predictive processes as central to learning, yet practically all experiments employ non-predictive measures during training. We argue that the common theoretical assumption of anticipation and prediction needs clearer, more direct evidence for it during learning. We offer a novel experimental context to explore prediction, and report results from a simple sequential learning task designed to promote predictive behaviors in participants as they responded to a short sequence of simple stimulus events. Predictive tendencies in participants were measured using their computer mouse, the trajectories of which served as a means of tapping into predictive behavior while participants were exposed to very short and simple sequences of events. A total of 143 participants were randomly assigned to stimulus sequences along a continuum of regularity. Analysis of computer-mouse trajectories revealed that (a) participants almost always anticipate events in some manner, (b) participants exhibit two stable patterns of behavior, either reacting to vs. predicting future events, (c) the extent to which participants predict relates to performance on a recall test, and (d) explicit reports of perceiving patterns in the brief sequence correlates with extent of prediction. We end with a discussion of implicit and explicit statistical learning and of the role prediction may play in both kinds of learning. PMID:22723817

Development of Computer-Based Experiment Set on Simple Harmonic Motion of Mass on Springs

ERIC Educational Resources Information Center

Musik, Panjit

2017-01-01

The development of computer-based experiment set has become necessary in teaching physics in schools so that students can learn from their real experiences. The purpose of this study is to create and to develop the computer-based experiment set on simple harmonic motion of mass on springs for teaching and learning physics. The average period of…

Changes in Purkinje cell simple spike encoding of reach kinematics during adaption to a mechanical perturbation.

PubMed

Hewitt, Angela L; Popa, Laurentiu S; Ebner, Timothy J

2015-01-21

The cerebellum is essential in motor learning. At the cellular level, changes occur in both the simple spike and complex spike firing of Purkinje cells. Because simple spike discharge reflects the main output of the cerebellar cortex, changes in simple spike firing likely reflect the contribution of the cerebellum to the adapted behavior. Therefore, we investigated in Rhesus monkeys how the representation of arm kinematics in Purkinje cell simple spike discharge changed during adaptation to mechanical perturbations of reach movements. Monkeys rapidly adapted to a novel assistive or resistive perturbation along the direction of the reach. Adaptation consisted of matching the amplitude and timing of the perturbation to minimize its effect on the reach. In a majority of Purkinje cells, simple spike firing recorded before and during adaptation demonstrated significant changes in position, velocity, and acceleration sensitivity. The timing of the simple spike representations change within individual cells, including shifts in predictive versus feedback signals. At the population level, feedback-based encoding of position increases early in learning and velocity decreases. Both timing changes reverse later in learning. The complex spike discharge was only weakly modulated by the perturbations, demonstrating that the changes in simple spike firing can be independent of climbing fiber input. In summary, we observed extensive alterations in individual Purkinje cell encoding of reach kinematics, although the movements were nearly identical in the baseline and adapted states. Therefore, adaption to mechanical perturbation of a reaching movement is accompanied by widespread modifications in the simple spike encoding. Copyright © 2015 the authors 0270-6474/15/351106-19$15.00/0.

Changes in Purkinje Cell Simple Spike Encoding of Reach Kinematics during Adaption to a Mechanical Perturbation

PubMed Central

Hewitt, Angela L.; Popa, Laurentiu S.

2015-01-01

The cerebellum is essential in motor learning. At the cellular level, changes occur in both the simple spike and complex spike firing of Purkinje cells. Because simple spike discharge reflects the main output of the cerebellar cortex, changes in simple spike firing likely reflect the contribution of the cerebellum to the adapted behavior. Therefore, we investigated in Rhesus monkeys how the representation of arm kinematics in Purkinje cell simple spike discharge changed during adaptation to mechanical perturbations of reach movements. Monkeys rapidly adapted to a novel assistive or resistive perturbation along the direction of the reach. Adaptation consisted of matching the amplitude and timing of the perturbation to minimize its effect on the reach. In a majority of Purkinje cells, simple spike firing recorded before and during adaptation demonstrated significant changes in position, velocity, and acceleration sensitivity. The timing of the simple spike representations change within individual cells, including shifts in predictive versus feedback signals. At the population level, feedback-based encoding of position increases early in learning and velocity decreases. Both timing changes reverse later in learning. The complex spike discharge was only weakly modulated by the perturbations, demonstrating that the changes in simple spike firing can be independent of climbing fiber input. In summary, we observed extensive alterations in individual Purkinje cell encoding of reach kinematics, although the movements were nearly identical in the baseline and adapted states. Therefore, adaption to mechanical perturbation of a reaching movement is accompanied by widespread modifications in the simple spike encoding. PMID:25609626

Explanatory Preferences Shape Learning and Inference.

PubMed

Lombrozo, Tania

2016-10-01

Explanations play an important role in learning and inference. People often learn by seeking explanations, and they assess the viability of hypotheses by considering how well they explain the data. An emerging body of work reveals that both children and adults have strong and systematic intuitions about what constitutes a good explanation, and that these explanatory preferences have a systematic impact on explanation-based processes. In particular, people favor explanations that are simple and broad, with the consequence that engaging in explanation can shape learning and inference by leading people to seek patterns and favor hypotheses that support broad and simple explanations. Given the prevalence of explanation in everyday cognition, understanding explanation is therefore crucial to understanding learning and inference. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Effect of Computer Game-Based Learning on FL Vocabulary Transferability

ERIC Educational Resources Information Center

Franciosi, Stephan J.

2017-01-01

In theory, computer game-based learning can support several vocabulary learning affordances that have been identified in the foreign language learning research. In the observable evidence, learning with computer games has been shown to improve performance on vocabulary recall tests. However, while simple recall can be a sign of learning,…

Investigating the impact of a LEGO(TM)-based, engineering-oriented curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines

NASA Astrophysics Data System (ADS)

Marulcu, Ismail

This mixed method study examined the impact of a LEGO-based, engineering-oriented curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines. This study takes a social constructivist theoretical stance that science learning involves learning scientific concepts and their relations to each other. From this perspective, students are active participants, and they construct their conceptual understanding through the guidance of their teacher. With the goal of better understanding the use of engineering education materials in classrooms the National Academy of Engineering and National Research Council in the book "Engineering in K-12 Education" conducted an in-depth review of the potential benefits of including engineering in K--12 schools as (a) improved learning and achievement in science and mathematics, (b) increased awareness of engineering and the work of engineers, (c) understanding of and the ability to engage in engineering design, (d) interest in pursuing engineering as a career, and (e) increased technological literacy (Katehi, Pearson, & Feder, 2009). However, they also noted a lack of reliable data and rigorous research to support these assertions. Data sources included identical written tests and interviews, classroom observations and videos, teacher interviews, and classroom artifacts. To investigate the impact of the design-based simple machines curriculum compared to the scientific inquiry-based simple machines curriculum on student learning outcomes, I compared the control and the experimental groups' scores on the tests and interviews by using ANCOVA. To analyze and characterize the classroom observation videotapes, I used Jordan and Henderson's (1995) method and divide them into episodes. My analyses revealed that the design-based Design a People Mover: Simple Machines unit was, if not better, as successful as the inquiry-based FOSS Levers and Pulleys unit in terms of students' content learning. I also found that students in the engineering group outperformed students in the control group in regards to their ability to answer open-ended questions when interviewed. Implications for students' science content learning and teachers' professional development are discussed.

Determinants of Teachers' Attitudes towards E- Learning in Tanzanian Higher Learning Institutions

ERIC Educational Resources Information Center

Kisanga, Dalton H.

2016-01-01

This survey research study presents the findings on determinants of teachers' attitudes towards e-learning in Tanzanian higher learning institutions. The study involved 258 teachers from 4 higher learning institutions obtained through stratified, simple random sampling. Questionnaires and documentary review were used in data collection. Data were…

Oscillatory neural network for pattern recognition: trajectory based classification and supervised learning.

PubMed

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.

Some new speculative ideas about the “behavioral homeostasis theory” as to how the simple learned behaviors of habituation and sensitization improve organism survival throughout phylogeny

PubMed Central

Eisenstein, Edward M.; Eisenstein, Doris L.; Sarma, Jonnalagedda Sarma M.; Knapp, Herschel; Smith, James C.

2012-01-01

This paper explores further the “behavioral homeostasis theory” (BHT) regarding the evolutionary significance for organism survival of the two simple non-associative rapidly learned behaviors of habituation and sensitization. The BHT postulates that the evolutionary function of habituation and sensitization throughout phylogeny is to rapidly maximize an organism’s overall readiness to cope with new stimuli and to minimize unnecessary energy expenditure. These behaviors have survived with remarkable similarity throughout phylogeny from aneural protozoa to humans. The concept of “behavioral homeostasis” emphasizes that the homeostatic process is more than just maintaining internal equilibrium in the face of changing internal and external conditions. It emphasizes the rapid internal and external effector system changes that occur to optimize organism readiness to cope with any new external stimulus situation. Truly life-threatening stimuli elicit instinctive behavior such as fight, flee, or hide. If the stimulus is not life-threatening, the organism rapidly learns to adjust to an appropriate level of overall responsiveness over stimulus repetitions. The rapid asymptotic level approached by those who decrease their overall responsiveness to the second stimulus (habituaters) and those who increase their overall responsiveness to an identical second stimulus (sensitizers) not only optimizes readiness to cope with any new stimulus situation but also reduces unnecessary energy expenditure. This paper is based on a retrospective analysis of data from 4 effector system responses to eight repetitive tone stimuli in adult human males. The effector systems include the galvanic skin response, finger pulse volume, muscle frontalis and heart rate. The new information provides the basis for further exploration of the BHT including new predictions and proposed relatively simple experiments to test them. PMID:22896782

Competitive STDP Learning of Overlapping Spatial Patterns.

PubMed

Krunglevicius, Dalius

2015-08-01

Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

A Learning-Style Theory for Understanding Autistic Behaviors

PubMed Central

Qian, Ning; Lipkin, Richard M.

2011-01-01

Understanding autism's ever-expanding array of behaviors, from sensation to cognition, is a major challenge. We posit that autistic and typically developing brains implement different algorithms that are better suited to learn, represent, and process different tasks; consequently, they develop different interests and behaviors. Computationally, a continuum of algorithms exists, from lookup table (LUT) learning, which aims to store experiences precisely, to interpolation (INT) learning, which focuses on extracting underlying statistical structure (regularities) from experiences. We hypothesize that autistic and typical brains, respectively, are biased toward LUT and INT learning, in low- and high-dimensional feature spaces, possibly because of their narrow and broad tuning functions. The LUT style is good at learning relationships that are local, precise, rigid, and contain little regularity for generalization (e.g., the name–number association in a phonebook). However, it is poor at learning relationships that are context dependent, noisy, flexible, and do contain regularities for generalization (e.g., associations between gaze direction and intention, language and meaning, sensory input and interpretation, motor-control signal and movement, and social situation and proper response). The LUT style poorly compresses information, resulting in inefficiency, sensory overload (overwhelm), restricted interests, and resistance to change. It also leads to poor prediction and anticipation, frequent surprises and over-reaction (hyper-sensitivity), impaired attentional selection and switching, concreteness, strong local focus, weak adaptation, and superior and inferior performances on simple and complex tasks. The spectrum nature of autism can be explained by different degrees of LUT learning among different individuals, and in different systems of the same individual. Our theory suggests that therapy should focus on training autistic LUT algorithm to learn regularities. PMID:21886617

Creating Simple Windchill Admin Tools Using Info*Engine

NASA Technical Reports Server (NTRS)

Jones, Corey; Kapatos, Dennis; Skradski, Cory

2012-01-01

Being a Windchill administrator often requires performing simple yet repetitive tasks on large sets of objects. These can include renaming, deleting, checking in, undoing checkout, and much more. This is especially true during a migration. Fortunately, PTC has provided a simple way to dynamically interact with Windchill using Info*Engine. This presentation will describe how to create simple Info*Engine tasks capable of saving Windchill 10.0 administrators hours of tedious work. It will also show how these tasks can be combined and displayed on a simple JSP page that acts as a "Windchill Administrator Dashboard/Toolbox". The attendee will learn some valuable tasks Info*Engine capable of performing. The attendee will gain a basic understanding of how to perform and implement Info*Engine tasks. The attendee will learn what's involved in creating a JSP page that displays Info*Engine tasks

The importance of training strategy adaptation: a learner-oriented approach for improving older adults' memory and transfer.

PubMed

Bottiroli, Sara; Cavallini, Elena; Dunlosky, John; Vecchi, Tomaso; Hertzog, Christopher

2013-09-01

We investigated the benefits of strategy-adaptation training for promoting transfer effects. This learner-oriented approach--which directly encourages the learner to generalize strategic behavior to new tasks--helps older adults appraise new tasks and adapt trained strategies to them. In Experiment 1, older adults in a strategy-adaptation training group used 2 strategies (imagery and sentence generation) while practicing 2 tasks (list and associative learning); they were then instructed on how to do a simple task analysis to help them adapt the trained strategies for 2 different unpracticed tasks (place learning and text learning) that were discussed during training. Two additional criterion tasks (name-face associative learning and grocery-list learning) were never mentioned during training. Two other groups were included: A strategy training group (who received strategy training and transfer instructions but not strategy-adaptation training) and a waiting-list control group. Both training procedures enhanced older adults' performance on the trained tasks and those tasks that were discussed during training, but transfer was greatest after strategy-adaptation training. Experiment 2 found that strategy-adaptation training conducted via a manual that older adults used at home also promoted transfer. These findings demonstrate the importance of adopting a learner-oriented approach to promote transfer of strategy training. PsycINFO Database Record (c) 2013 APA, all rights reserved.

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

PubMed

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

2015-01-01

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

Type 2 diabetes and impaired glucose tolerance are associated with word memory source monitoring recollection deficits but not simple recognition familiarity deficits following water, low glycaemic load, and high glycaemic load breakfasts.

PubMed

Lamport, Daniel J; Lawton, Clare L; Mansfield, Michael W; Moulin, Chris A J; Dye, Louise

2014-01-30

It has been established that type 2 diabetes, and to some extent, impaired glucose tolerance (IGT), are associated with general neuropsychological impairments in episodic memory. However, the effect of abnormalities in glucose metabolism on specific retrieval processes such as source monitoring has not been investigated. The primary aim was to investigate the impact of type 2 diabetes and IGT on simple word recognition (familiarity) and complex source monitoring (recollection). A secondary aim was to examine the effect of acute breakfast glycaemic load manipulations on episodic memory. Data are presented from two separate studies; (i) 24 adults with type 2 diabetes and 12 controls aged 45-75years, (ii) 18 females with IGT and 47 female controls aged 30-50years. Controls were matched for age, IQ, BMI, waist circumference, and depression. Recognition of previously learned words and memory for specifically which list a previously learned word had appeared in (source monitoring) was examined at two test sessions during the morning after consumption of low glycaemic load, high glycaemic load and water breakfasts according to a counterbalanced, crossover design. Type 2 diabetes (p<0.05) and IGT (p<0.01) were associated with significant source monitoring recollection deficits but not impairments in familiarity. Impairments were only observed in the late postprandial stage at the second test session. These impairments were not attenuated by the breakfast glycaemic load manipulations. Isolated source monitoring recollection deficits indicate that abnormalities in glucose metabolism are not detrimental for global episodic memory processes. This enhances our understanding of how metabolic disorders are associated with memory impairments. © 2013.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

PubMed

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity

PubMed Central

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns. PMID:26900845

Bridging Realty to Virtual Reality: Investigating Gender Effect and Student Engagement on Learning through Video Game Play in an Elementary School Classroom

ERIC Educational Resources Information Center

Annetta, Leonard; Mangrum, Jennifer; Holmes, Shawn; Collazo, Kimberly; Cheng, Meng-Tzu

2009-01-01

The purpose of this study was to examine students' learning of simple machines, a fifth-grade (ages 10-11) forces and motion unit, and student engagement using a teacher-created Multiplayer Educational Gaming Application. This mixed-method study collected pre-test/post-test results to determine student knowledge about simple machines. A survey…

A Development of Learning Widget on M-Learning and E-Learning Environments

ERIC Educational Resources Information Center

Kim, SooHwan; Kim, HyeonCheol; Han, SeonKwan

2013-01-01

This article describes the development of learning widget on m-learning and e-learning environments. A widget is a small, simple and useful application supporting user-oriented contents. The user may select and install widgets that are convenient as well as an auto-updating application including weather or calendar. These widgets are especially…

Neural networks supporting switching, hypothesis testing, and rule application

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-10-01

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

The Influence of Learning on Host Plant Preference in a Significant Phytopathogen Vector, Diaphorina citri

PubMed Central

Stockton, Dara G.; Martini, Xavier; Patt, Joseph M.; Stelinski, Lukasz L.

2016-01-01

Although specialist herbivorous insects are guided by innate responses to host plant cues, host plant preference may be influenced by experience and is not dictated by instinct alone. The effect of learning on host plant preference was examined in the Asian citrus psyllid, Diaphorina citri; vector of the causal agent of citrus greening disease or huanglongbing. We investigated: a) whether development on specific host plant species influenced host plant preference in mature D. citri; and b) the extent of associative learning in D. citri in the form of simple and compound conditioning. Learning was measured by cue selection in a 2-choice behavioral assay and compared to naïve controls. Our results showed that learned responses in D. citri are complex and diverse. The developmental host plant species influenced adult host plant preference, with female psyllids preferring the species on which they were reared. However, such preferences were subject to change with the introduction of an alternative host plant within 24–48 hrs, indicating a large degree of experience-dependent response plasticity. Additionally, learning occurred for multiple sensory modalities where novel olfactory and visual environmental cues were associated with the host plant. However, males and females displayed differing discriminatory abilities. In compound conditioning tasks, males exhibited recognition of a compound stimulus alone while females were capable of learning the individual components. These findings suggest D. citri are dynamic animals that demonstrate host plant preference based on developmental and adult experience and can learn to recognize olfactory and visual host plant stimuli in ways that may be sex specific. These experience-based associations are likely used by adults to locate and select suitable host plants for feeding and reproduction and may suggest the need for more tailored lures and traps, which reflect region-specific cultivars or predominate Rutaceae in the area being monitored. PMID:26930355

The Influence of Learning on Host Plant Preference in a Significant Phytopathogen Vector, Diaphorina citri.

PubMed

Stockton, Dara G; Martini, Xavier; Patt, Joseph M; Stelinski, Lukasz L

2016-01-01

Although specialist herbivorous insects are guided by innate responses to host plant cues, host plant preference may be influenced by experience and is not dictated by instinct alone. The effect of learning on host plant preference was examined in the Asian citrus psyllid, Diaphorina citri; vector of the causal agent of citrus greening disease or huanglongbing. We investigated: a) whether development on specific host plant species influenced host plant preference in mature D. citri; and b) the extent of associative learning in D. citri in the form of simple and compound conditioning. Learning was measured by cue selection in a 2-choice behavioral assay and compared to naïve controls. Our results showed that learned responses in D. citri are complex and diverse. The developmental host plant species influenced adult host plant preference, with female psyllids preferring the species on which they were reared. However, such preferences were subject to change with the introduction of an alternative host plant within 24-48 hrs, indicating a large degree of experience-dependent response plasticity. Additionally, learning occurred for multiple sensory modalities where novel olfactory and visual environmental cues were associated with the host plant. However, males and females displayed differing discriminatory abilities. In compound conditioning tasks, males exhibited recognition of a compound stimulus alone while females were capable of learning the individual components. These findings suggest D. citri are dynamic animals that demonstrate host plant preference based on developmental and adult experience and can learn to recognize olfactory and visual host plant stimuli in ways that may be sex specific. These experience-based associations are likely used by adults to locate and select suitable host plants for feeding and reproduction and may suggest the need for more tailored lures and traps, which reflect region-specific cultivars or predominate Rutaceae in the area being monitored.

Synaptic scaffold evolution generated components of vertebrate cognitive complexity

PubMed Central

Nithianantharajah, J.; Komiyama, N.H.; McKechanie, A.; Johnstone, M.; Blackwood, D. H.; St Clair, D.; Emes, R.D.; van de Lagemaat, L. N.; Saksida, L.M.; Bussey, T.J.; Grant, S.G.N.

2014-01-01

The origins and evolution of higher cognitive functions including complex forms of learning, attention and executive functions are unknown. A potential mechanism driving the evolution of vertebrate cognition early in the vertebrate lineage (550 My ago) was genome duplication and subsequent diversification of postsynaptic genes. Here we report the first genetic analysis of a vertebrate gene family in cognitive functions measured using computerized touchscreens. Comparison of mice carrying mutations in all four Dlg paralogs show simple associative learning required Dlg4, while Dlg2 and Dlg3 diversified to play opposing roles in complex cognitive processes. Exploiting the translational utility of touchscreens in humans and mice, testing Dlg2 mutations in both species showed Dlg2’s role in complex learning, cognitive flexibility and attention has been highly conserved over 100 My. Dlg family mutations underlie psychiatric disorders suggesting genome evolution expanded the complexity of vertebrate cognition at the cost of susceptibility to mental illness. PMID:23201973

Developing authentic clinical simulations for effective listening and communication in pediatric rehabilitation service delivery.

PubMed

King, Gillian; Shepherd, Tracy A; Servais, Michelle; Willoughby, Colleen; Bolack, Linda; Strachan, Deborah; Moodie, Sheila; Baldwin, Patricia; Knickle, Kerry; Parker, Kathryn; Savage, Diane; McNaughton, Nancy

2016-10-01

To describe the creation and validation of six simulations concerned with effective listening and interpersonal communication in pediatric rehabilitation. The simulations involved clinicians from various disciplines, were based on clinical scenarios related to client issues, and reflected core aspects of listening/communication. Each simulation had a key learning objective, thus focusing clinicians on specific listening skills. The article outlines the process used to turn written scenarios into digital video simulations, including steps taken to establish content validity and authenticity, and to establish a series of videos based on the complexity of their learning objectives, given contextual factors and associated macrocognitive processes that influence the ability to listen. A complexity rating scale was developed and used to establish a gradient of easy/simple, intermediate, and hard/complex simulations. The development process exemplifies an evidence-based, integrated knowledge translation approach to the teaching and learning of listening and communication skills.

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

PubMed Central

Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; del Giudice, Paolo

2015-01-01

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a ‘basin’ of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases. PMID:26463272

ERP evidence for conflict in contingency learning.

PubMed

Whitehead, Peter S; Brewer, Gene A; Blais, Chris

2017-07-01

The proportion congruency effect refers to the observation that the magnitude of the Stroop effect increases as the proportion of congruent trials in a block increases. Contemporary work shows that proportion effects can be driven by both context and individual items, and are referred to as context-specific proportion congruency (CSPC) and item-specific proportion congruency (ISPC) effects, respectively. The conflict-modulated Hebbian learning account posits that these effects manifest from the same mechanism, while the parallel episodic processing model posits that the ISPC can occur by simple associative learning. Our prior work showed that the neural correlates of the CSPC is an N2 over frontocentral electrode sites approximately 300 ms after stimulus onset that predicts behavioral performance. There is strong consensus in the field that this N2 signal is associated with conflict detection in the medial frontal cortex. The experiment reported here assesses whether the same qualitative electrophysiological pattern of results holds for the ISPC. We find that the spatial topography of the N2 is similar but slightly delayed with a peak onset of approximately 300 ms after stimulus onset. We argue that this provides strong evidence that a single common mechanism-conflict-modulated Hebbian learning-drives both the ISPC and CSPC. © 2017 Society for Psychophysiological Research.

Acute ethanol ingestion impairs appetitive olfactory learning and odor discrimination in the honey bee

PubMed Central

Mustard, Julie A; Wright, Geraldine A; Edgar, Elaina A; Mazade, Reece E.; Wu, Chen; Lillvis, Joshua L

2008-01-01

Invertebrates are valuable models for increasing our understanding of the effects of ethanol on the nervous system, but most studies on invertebrates and ethanol have focused on the effects of ethanol on locomotor behavior. In this work we investigate the influence of an acute dose of ethanol on appetitive olfactory learning in the honey bee (Apis mellifera), a model system for learning and memory. Adult worker honey bees were fed a range of doses (2.5, 5, 10 or 25%) of ethanol and then conditioned to associate an odor with a sucrose reward using either a simple or differential conditioning paradigm. Consumption of ethanol before conditioning significantly reduced both the rate of acquisition and the asymptotic strength of the association. Honey bees also exhibited a dose dependent reduction in arousal/attention during conditioning. Consumption of ethanol after conditioning did not affect recall 24 h later. The observed deficits in acquisition were not due to the affect of ethanol on gustatory sensitivity or motor function. However, honey bees given higher doses of ethanol had difficulty discriminating amongst different odors suggesting that ethanol consumption influences olfactory processing. Taken together, these results demonstrate that an acute dose of ethanol affects appetitive learning and olfactory perception in the honey bee. PMID:18723103

An object location memory paradigm for older adults with and without mild cognitive impairment.

PubMed

Külzow, Nadine; Kerti, Lucia; Witte, Veronica A; Kopp, Ute; Breitenstein, Caterina; Flöel, Agnes

2014-11-30

Object-location memory is critical in every-day life and known to deteriorate early in the course of neurodegenerative disease. We adapted the previously established learning paradigm "LOCATO" for use in healthy older adults and patients with mild cognitive impairment (MCI). Pictures of real-life buildings were associated with positions on a two-dimensional street map by repetitions of "correct" object-location pairings over the course of five training blocks, followed by a recall task. Correct/incorrect associations were indicated by button presses. The original two 45-item sets were reduced to 15 item-sets, and tested in healthy older adults and MCI for learning curve, recall, and re-test effects. The two 15-item versions showed comparable learning curves and recall scores within each group. While learning curves increased linearly in both groups, MCI patients performed significantly worse on learning and recall compared to healthy controls. Re-testing after 6 month showed small practice effects only. LOCATO is a simple standardized task that overcomes several limitation of previously employed visuospatial task by using real-life stimuli, minimizing verbal encoding, avoiding fine motor responses, combining explicit and implicit statistical learning, and allowing to assess learning curve in addition to recall. Results show that the shortened version of LOCATO meets the requirements for a robust and ecologically meaningful assessment of object-location memory in older adults with and without MCI. It can now be used to systematically assess acquisition of object-location memory and its modulation through adjuvant therapies like pharmacological or non-invasive brain stimulation. Copyright © 2014 Elsevier B.V. All rights reserved.

Impact of an engineering design-based curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines

NASA Astrophysics Data System (ADS)

Marulcu, Ismail; Barnett, Michael

2016-01-01

Background: Elementary Science Education is struggling with multiple challenges. National and State test results confirm the need for deeper understanding in elementary science education. Moreover, national policy statements and researchers call for increased exposure to engineering and technology in elementary science education. The basic motivation of this study is to suggest a solution to both improving elementary science education and increasing exposure to engineering and technology in it. Purpose/Hypothesis: This mixed-method study examined the impact of an engineering design-based curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines. We hypothesize that the LEGO-engineering design unit is as successful as the inquiry-based unit in terms of students' science content learning of simple machines. Design/Method: We used a mixed-methods approach to investigate our research questions; we compared the control and the experimental groups' scores from the tests and interviews by using Analysis of Covariance (ANCOVA) and compared each group's pre- and post-scores by using paired t-tests. Results: Our findings from the paired t-tests show that both the experimental and comparison groups significantly improved their scores from the pre-test to post-test on the multiple-choice, open-ended, and interview items. Moreover, ANCOVA results show that students in the experimental group, who learned simple machines with the design-based unit, performed significantly better on the interview questions. Conclusions: Our analyses revealed that the design-based Design a people mover: Simple machines unit was, if not better, as successful as the inquiry-based FOSS Levers and pulleys unit in terms of students' science content learning.

Unsupervised learning in neural networks with short range synapses

NASA Astrophysics Data System (ADS)

Brunnet, L. G.; Agnes, E. J.; Mizusaki, B. E. P.; Erichsen, R., Jr.

2013-01-01

Different areas of the brain are involved in specific aspects of the information being processed both in learning and in memory formation. For example, the hippocampus is important in the consolidation of information from short-term memory to long-term memory, while emotional memory seems to be dealt by the amygdala. On the microscopic scale the underlying structures in these areas differ in the kind of neurons involved, in their connectivity, or in their clustering degree but, at this level, learning and memory are attributed to neuronal synapses mediated by longterm potentiation and long-term depression. In this work we explore the properties of a short range synaptic connection network, a nearest neighbor lattice composed mostly by excitatory neurons and a fraction of inhibitory ones. The mechanism of synaptic modification responsible for the emergence of memory is Spike-Timing-Dependent Plasticity (STDP), a Hebbian-like rule, where potentiation/depression is acquired when causal/non-causal spikes happen in a synapse involving two neurons. The system is intended to store and recognize memories associated to spatial external inputs presented as simple geometrical forms. The synaptic modifications are continuously applied to excitatory connections, including a homeostasis rule and STDP. In this work we explore the different scenarios under which a network with short range connections can accomplish the task of storing and recognizing simple connected patterns.

Lead exposure and fear-potentiated startle in the VA Normative Aging Study: a pilot study of a novel physiological approach to investigating neurotoxicant effects.

PubMed

Grashow, Rachel; Miller, Mark W; McKinney, Ann; Nie, Linda H; Sparrow, David; Hu, Howard; Weisskopf, Marc G

2013-01-01

Physiologically-based indicators of neural plasticity in humans could provide mechanistic insights into toxicant actions on learning in the brain, and perhaps prove more objective and sensitive measures of such effects than other methods. We explored the association between lead exposure and classical conditioning of the acoustic startle reflex (ASR)-a simple form of associative learning in the brain-in a population of elderly men. Fifty-one men from the VA Normative Aging Study with cumulative bone lead exposure measurements made with K-X-Ray-Fluorescence participated in a fear-conditioning protocol. The mean age of the men was 75.5years (standard deviation [sd]=5.9) and mean patella lead concentration was 22.7μg/g bone (sd=15.9). Baseline ASR eyeblink response decreased with age, but was not associated with subsequent conditioning. Among 37 men with valid responses at the end of the protocol, higher patella lead was associated with decreased awareness of the conditioning contingency (declarative learning; adjusted odds ratio [OR] per 20μg/g patella lead=0.91, 95% confidence interval [CI]: 0.84, 0.99, p=0.03). Eyeblink conditioning (non-declarative learning) was 0.44sd less (95% CI: -0.91, 0.02; p=0.06) per 20μg/g patella lead after adjustment. Each result was stronger when correcting for the interval between lead measurement and startle testing (awareness: OR=0.88, 95% CI: 0.78, 0.99, p=0.04; conditioning: -0.79sd less, 95% CI: -1.56, 0.03, p=0.04). This initial exploration suggests that lead exposure interferes with specific neural mechanisms of learning and offers the possibility that the ASR may provide a new approach to physiologically explore the effects of neurotoxicant exposures on neural mechanisms of learning in humans with a paradigm that is directly comparable to animal models. Copyright © 2013 Elsevier Inc. All rights reserved.

Pneumovesical ureteric reimplantation using T-fastener: A modification for bladder wall anchorage.

PubMed

Lau, Chin Tung; Lan, Lawrence Chuen Leung; Wong, Kenneth Kak Yuen; Tam, Paul

2017-06-01

Bladder anchoring during pneumovesical ureteric reimplantation (PUR) can be difficult. Here we describe our new technique using a T-fastener (Kimberly Clark, Irving, TX, USA) to tackle this problem. A T-fastener has been applied to all patients who underwent PUR in our center since 2011. Seventeen consecutive cases were performed between 2011 and 2015. No bladder dislodgement or air leak was observed in any of the operations. No morbidity or mortality has been associated with the use of T-fasteners. In our experience, this technique is simple to learn and transferrable. It decreases intraoperative complications and helps to climb the learning curve. Copyright © 2017 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

Multiple subclasses of Purkinje cells in the primate floccular complex provide similar signals to guide learning in the vestibulo-ocular reflex

NASA Technical Reports Server (NTRS)

Raymond, J. L.; Lisberger, S. G.

1997-01-01

The neural "learning rules" governing the induction of plasticity in the cerebellum were analyzed by recording the patterns of neural activity in awake, behaving animals during stimuli that induce a form of cerebellum-dependent learning. We recorded the simple- and complex-spike responses of a broad sample of Purkinje cells in the floccular complex during a number of stimulus conditions that induce motor learning in the vestibulo-ocular reflex (VOR). Each subclass of Purkinje cells carried essentially the same information about required changes in the gain of the VOR. The correlation of simple-spike activity in Purkinje cells with activity in vestibular pathways could guide learning during low-frequency but not high-frequency stimuli. Climbing fiber activity could guide learning during all stimuli tested but only if compared with the activity present approximately 100 msec earlier in either vestibular pathways or Purkinje cells.

Does Variability Across Events Affect Verb Learning in English, Mandarin and Korean?

PubMed Central

Childers, Jane B.; Paik, Jae H.; Flores, Melissa; Lai, Gabrielle; Dolan, Megan

2016-01-01

Extending new verbs is important to becoming a productive speaker of a language. Prior results show children have difficulty extending verbs when they have seen events with varied agents. This paper further examines the impact of variability on verb learning, and asks whether this interacts with event complexity or differs by language. Children (aged 2 ½- to 3-years) in the U.S., China, Korea and Singapore learned verbs linked to simple and complex events. Sets of events included one or three agents, and children were asked to extend the verb at test. Children learning verbs linked to simple movements performed similarly across conditions. However, children learning verbs linked to events with multiple objects were less successful if those events were enacted by multiple agents. A follow-up study rules out an influence of event order. Overall, similar patterns of results emerged across languages, suggesting common cognitive processes support children’s verb learning. PMID:27457679

Neural learning rules for the vestibulo-ocular reflex

NASA Technical Reports Server (NTRS)

Raymond, J. L.; Lisberger, S. G.

1998-01-01

Mechanisms for the induction of motor learning in the vestibulo-ocular reflex (VOR) were evaluated by recording the patterns of neural activity elicited in the cerebellum by a range of stimuli that induce learning. Patterns of climbing-fiber, vestibular, and Purkinje cell simple-spike signals were examined during sinusoidal head movement paired with visual image movement at stimulus frequencies from 0.5 to 10 Hz. A comparison of simple-spike and vestibular signals contained the information required to guide learning only at low stimulus frequencies, and a comparison of climbing-fiber and simple-spike signals contained the information required to guide learning only at high stimulus frequencies. Learning could be guided by comparison of climbing-fiber and vestibular signals at all stimulus frequencies tested, but only if climbing fiber responses were compared with the vestibular signals present 100 msec earlier. Computational analysis demonstrated that this conclusion is valid even if there is a broad range of vestibular signals at the site of plasticity. Simulations also indicated that the comparison of vestibular and climbing-fiber signals across the 100 msec delay must be implemented by a subcellular "eligibility" trace rather than by neural circuits that delay the vestibular inputs to the site of plasticity. The results suggest two alternative accounts of learning in the VOR. Either there are multiple mechanisms of learning that use different combinations of neural signals to drive plasticity, or there is a single mechanism tuned to climbing-fiber activity that follows activity in vestibular pathways by approximately 100 msec.

Effect of Methods of Learning and Self Regulated Learning toward Outcomes of Learning Social Studies

ERIC Educational Resources Information Center

Tjalla, Awaluddin; Sofiah, Evi

2015-01-01

This research aims to reveal the influence of learning methods and self-regulated learning on students learning scores for Social Studies object. The research was done in Islamic Junior High School (MTs Manba'ul Ulum), Batuceper City Tangerang using quasi-experimental method. The research employed simple random technique to 28 students. Data were…

Toward a dual-learning systems model of speech category learning

PubMed Central

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

Liquid computing on and off the edge of chaos with a striatal microcircuit

PubMed Central

Toledo-Suárez, Carlos; Duarte, Renato; Morrison, Abigail

2014-01-01

In reinforcement learning theories of the basal ganglia, there is a need for the expected rewards corresponding to relevant environmental states to be maintained and modified during the learning process. However, the representation of these states that allows them to be associated with reward expectations remains unclear. Previous studies have tended to rely on pre-defined partitioning of states encoded by disjunct neuronal groups or sparse topological drives. A more likely scenario is that striatal neurons are involved in the encoding of multiple different states through their spike patterns, and that an appropriate partitioning of an environment is learned on the basis of task constraints, thus minimizing the number of states involved in solving a particular task. Here we show that striatal activity is sufficient to implement a liquid state, an important prerequisite for such a computation, whereby transient patterns of striatal activity are mapped onto the relevant states. We develop a simple small scale model of the striatum which can reproduce key features of the experimentally observed activity of the major cell types of the striatum. We then use the activity of this network as input for the supervised training of four simple linear readouts to learn three different functions on a plane, where the network is stimulated with the spike coded position of the agent. We discover that the network configuration that best reproduces striatal activity statistics lies on the edge of chaos and has good performance on all three tasks, but that in general, the edge of chaos is a poor predictor of network performance. PMID:25484864

Use of iPhone technology in improving acetabular component position in total hip arthroplasty.

PubMed

Tay, Xiau Wei; Zhang, Benny Xu; Gayagay, George

2017-09-01

Improper acetabular cup positioning is associated with high risk of complications after total hip arthroplasty. The aim of our study is to objectively compare 3 methods, namely (1) free hand, (2) alignment jig (Sputnik), and (3) iPhone application to identify an easy, reproducible, and accurate method in improving acetabular cup placement. We designed a simple setup and carried out a simple experiment (see Method section). Using statistical analysis, the difference in inclination angles using iPhone application compared with the freehand method was found to be statistically significant ( F [2,51] = 4.17, P = .02) in the "untrained group". There is no statistical significance detected for the other groups. This suggests a potential role for iPhone applications in junior surgeons in overcoming the steep learning curve.

The Effects of Differential Learning and Traditional Learning Trainings on Technical Development of Football Players

ERIC Educational Resources Information Center

Bozkurt, Sinan

2018-01-01

There are several different methods of learning motor skills, like traditional (linear) and differential (nonlinear) learning training. The traditional motor learning approach proposes that learners improve a skill just by repeating it. According to the teaching principles, exercises are selected along continua from easy to hard and from simple to…

[Connectionist models of social learning: a case of learning by observing a simple task].

PubMed

Paignon, A; Desrichard, O; Bollon, T

2004-03-01

This article proposes a connectionist model of the social learning theory developed by Bandura (1977). The theory posits that an individual in an interactive situation is capable of learning new behaviours merely by observing them in others. Such learning is acquired through an initial phase in which the individual memorizes what he has observed (observation phase), followed by a second phase where he puts the recorded observations to use as a guide for adjusting his own behaviour (reproduction phase). We shall refer to the two above-mentioned phases to demonstrate that it is conceivable to simulate learning by observation otherwise than through the recording of perceived information using symbolic representation. To this end we shall rely on the formalism of ecological neuron networks (Parisi, Cecconi, & Nolfi, 1990) to implement an agent provided with the major processes identified as essential to learning through observation. The connectionist model so designed shall implement an agent capable of recording perceptive information and producing motor behaviours. The learning situation we selected associates an agent demonstrating goal-achievement behaviour and an observer agent learning the same behaviour by observation. Throughout the acquisition phase, the demonstrator supervises the observer's learning process based on association between spatial information (input) and behavioural information (output). Representation thus constructed then serves as an adjustment guide during the production phase, involving production by the observer of a sequence of actions which he compares to the representation stored in distributed form as constructed through observation. An initial simulation validates model architecture by confirming the requirement for both phases identified in the literature (Bandura, 1977) to simulate learning through observation. The representation constructed over the observation phase evidences acquisition of observed behaviours, although this phase alone is not sufficient to ensure accurate reproduction and must be made functional through the production phase (Deakin & Proteau, 2000). Results obtained through a second simulation replicate those produced by Bandura & Jeffery (1973), who observed that the individual tested following the retention phase recalled recorded information better than he realized in the production phase. The outcome of a third simulation shows that, when performing the transfer task, agents performed the task all the more effectively when they were required to learn a simple path which facilitated knowledge transfer to an adjacent situation. New explanatory assumptions of the mechanics of learning through observation may be produced through OLEANNet. Thus, observed deterioration between memorization and production is caused by successive approximations which occur in the acquisition phase then in the production phase. Further, depending on the type of learning undergone by agents, use of representation as a production guide induces a more or less stringent constraint in the approximation of actual behaviour. This results, during the transfer task, in the ability to effectively generalize acquired knowledge where such knowledge is not specifically related to the task at hand. In conclusion, connectionist model architecture appears valid for modeling learning through observation as defined by Bandura (1977). However, certain limitations appear during implementation, especially in terms of the observed behaviour's availability and the planning of produced behaviours that future developments are liable to counter.

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

PubMed Central

Balcarras, Matthew; Womelsdorf, Thilo

2016-01-01

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

Enhanced appetitive learning and reversal learning in a mouse model for Prader-Willi syndrome.

PubMed

Relkovic, Dinko; Humby, Trevor; Hagan, Jim J; Wilkinson, Lawrence S; Isles, Anthony R

2012-06-01

Prader-Willi syndrome (PWS) is caused by lack of paternally derived gene expression from the imprinted gene cluster on human chromosome 15q11-q13. PWS is characterized by severe hypotonia, a failure to thrive in infancy and, on emerging from infancy, evidence of learning disabilities and overeating behavior due to an abnormal satiety response and increased motivation by food. We have previously shown that an imprinting center deletion mouse model (PWS-IC) is quicker to acquire a preference for, and consume more of a palatable food. Here we examined how the use of this palatable food as a reinforcer influences learning in PWS-IC mice performing a simple appetitive learning task. On a nonspatial maze-based task, PWS-IC mice acquired criteria much quicker, making fewer errors during initial acquisition and also reversal learning. A manipulation where the reinforcer was devalued impaired wild-type performance but had no effect on PWS-IC mice. This suggests that increased motivation for the reinforcer in PWS-IC mice may underlie their enhanced learning. This supports previous findings in PWS patients and is the first behavioral study of an animal model of PWS in which the motivation of behavior by food rewards has been examined. © 2012 American Psychological Association

QSAR modelling using combined simple competitive learning networks and RBF neural networks.

PubMed

Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

2018-04-01

The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

Effects of personality traits on collaborative performance in problem-based learning tutorials

PubMed Central

Jang, Hye Won; Park, Seung Won

2016-01-01

Objectives To examine the relationship between students’ collaborative performance in a problem-based learning (PBL) environment and their personality traits. Methods This retrospective, cross-sectional study was conducted using student data of a PBL program between 2013 and 2014 at Sungkyunkwan University School of Medicine, Seoul, South Korea. Eighty students were included in the study. Student data from the Temperament and Character Inventory were used as a measure of their personality traits. Peer evaluation scores during PBL were used as a measure of students’ collaborative performance. Results Simple regression analyses indicated that participation was negatively related to harm avoidance and positively related to persistence, whereas preparedness for the group work was negatively related to reward dependence. On multiple regression analyses, low reward dependence remained a significant predictor of preparedness. Grade-point average (GPA) was negatively associated with novelty seeking and cooperativeness and was positively associated with persistence. Conclusion Medical students who are less dependent on social reward are more likely to complete assigned independent work to prepare for the PBL tutorials. The findings of this study can help educators better understand and support medical students who are at risk of struggling in collaborative learning environments. PMID:27874153

Effects of personality traits on collaborative performance in problem-based learning tutorials.

PubMed

Jang, Hye Won; Park, Seung Won

2016-12-01

To examine the relationship between students' collaborative performance in a problem-based learning (PBL) environment and their personality traits. Methods:This retrospective, cross-sectional study was conducted using student data of a PBL program between 2013 and 2014 at Sungkyunkwan University School of Medicine, Seoul, South Korea. Eighty students were included in the study. Student data from the Temperament and Character Inventory were used as a measure of their personality traits. Peer evaluation scores during PBL were used as a measure of students' collaborative performance. Results: Simple regression analyses indicated that participation was negatively related to harm avoidance and positively related to persistence, whereas preparedness for the group work was negatively related to reward dependence. On multiple regression analyses, low reward dependence remained a significant predictor of preparedness. Grade-point average (GPA)  was negatively associated with novelty seeking and cooperativeness and was positively associated with persistence.  Conclusion: Medical students who are less dependent on social reward are more likely to complete assigned independent work to prepare for the PBL tutorials. The findings of this study can help educators better understand and support medical students who are at risk of struggling in collaborative learning environments.

Predicting Protein Relationships to Human Pathways through a Relational Learning Approach Based on Simple Sequence Features.

PubMed

García-Jiménez, Beatriz; Pons, Tirso; Sanchis, Araceli; Valencia, Alfonso

2014-01-01

Biological pathways are important elements of systems biology and in the past decade, an increasing number of pathway databases have been set up to document the growing understanding of complex cellular processes. Although more genome-sequence data are becoming available, a large fraction of it remains functionally uncharacterized. Thus, it is important to be able to predict the mapping of poorly annotated proteins to original pathway models. We have developed a Relational Learning-based Extension (RLE) system to investigate pathway membership through a function prediction approach that mainly relies on combinations of simple properties attributed to each protein. RLE searches for proteins with molecular similarities to specific pathway components. Using RLE, we associated 383 uncharacterized proteins to 28 pre-defined human Reactome pathways, demonstrating relative confidence after proper evaluation. Indeed, in specific cases manual inspection of the database annotations and the related literature supported the proposed classifications. Examples of possible additional components of the Electron transport system, Telomere maintenance and Integrin cell surface interactions pathways are discussed in detail. All the human predicted proteins in the 2009 and 2012 releases 30 and 40 of Reactome are available at http://rle.bioinfo.cnio.es.

Yes You Can! A Booklet to Help Young People with Learning Disabilities Understand and Help Themselves. Revised Edition.

ERIC Educational Resources Information Center

East, Joanne

Intended for students with learning problems, this booklet is designed to help the student deal with his/her learning disability. Presented in simple language and cartoon-like illustrations, this publication addresses the causes of and misconceptions about learning problems, how it feels to have a learning disability, what can be done, and where…

Making Information Systems Less Scrugged: Reflecting on the Processes of Change in Teaching and Learning

ERIC Educational Resources Information Center

Houghton, Luke; Ruth, Alison

2010-01-01

Deep and shallow learner approaches are useful for different purposes. Shallow learning can be good where fact memorization is appropriate, learning how to swim or play the guitar for example. Deep learning is much more appropriate when the learning material present involves going beyond simple facts and into what lies below the surface. When…

Professional Learning in the Digital Age: The Educator's Guide to User-Generated Learning

ERIC Educational Resources Information Center

Swanson, Kristen

2013-01-01

Discover how to transform your professional development and become a truly connected educator with user-generated learning! This book shows educators how to enhance their professional learning using practical tools, strategies, and online resources. With beginner-friendly, real-world examples and simple steps to get started, the author shows how…

Achieving Service-Learning Goals in a Financial Accounting Class Project

ERIC Educational Resources Information Center

Yu, Darwin D.

2011-01-01

Background: A financial accounting class in a Philippine university has a service-learning group project that involves setting up a simple accounting system for microenterprises. Aims: This paper examines the extent to which service-learning goals such as course learning, teamwork, civic responsibility, and impact on the client organization are…

A Role for Chunk Formation in Statistical Learning of Second Language Syntax

ERIC Educational Resources Information Center

Hamrick, Phillip

2014-01-01

Humans are remarkably sensitive to the statistical structure of language. However, different mechanisms have been proposed to account for such statistical sensitivities. The present study compared adult learning of syntax and the ability of two models of statistical learning to simulate human performance: Simple Recurrent Networks, which learn by…

A Simple Guide to Enhancing Learning through Web 2.0 Technologies

ERIC Educational Resources Information Center

Nichol, David; Hunter, Julie; Yaseen, Jonathan; Prescott-Clements, Linda

2012-01-01

This article describes the potential of new and emerging learning technologies to promote excellence in learning and teaching and further seeks to respond positively to the key trends in learning technologies for the higher education community. Through this article, we hope to positively enrich the student experience with technology-enhanced…

Plasticity of cortical inhibition in dystonia is impaired after motor learning and Paired-Associative Stimulation

PubMed Central

Meunier, Sabine; Russmann, Heike; Shamim, Ejaz; Lamy, Jean-Charles; Hallett, Mark

2012-01-01

Summary Artificial induction of plasticity by paired associative stimulation (PAS) in healthy subjects (HV) demonstrates Hebbian-like plasticity in selected inhibitory networks as well as excitatory ones. In a group of 17 patients with focal hand dystonia and a group of 19 HV, we evaluated how PAS and the learning of a simple motor task influence the circuits supporting long interval intracortical inhibition (LICI, reflecting activity of GABAB interneurons) and long latency afferent inhibition (LAI, reflecting activity of somatosensory inputs to the motor cortex). In HV, PAS and motor learning induced LTP-like plasticity of excitatory networks and a lasting decrease of LAI and LICI in the motor representation of the targeted or trained muscle. The better the motor performance, the larger was the decrease of LAI. Although motor performance in the patient group was similar to that of the control group, LAI did not decrease during the motor learning as it did in the control group. In contrast, LICI was normally modulated. In patients the results after PAS did not match those obtained after motor learning: LAI was paradoxically increased and LICI did not exhibit any change. In the normal situation, decreased excitability in inhibitory circuits after induction of LTP-like plasticity may help to shape the cortical maps according to the new sensorimotor task. In patients, the abnormal or absent modulation of afferent and intracortical long-interval inhibition might indicate maladaptive plasticity that possibly contributes to the difficulty that they have to learn a new sensorimotor task.“ PMID:22429246

Global adaptation in networks of selfish components: emergent associative memory at the system scale.

PubMed

Watson, Richard A; Mills, Rob; Buckley, C L

2011-01-01

In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organize into structures that enhance global adaptation, efficiency, or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology, and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalization, and optimization are well understood. Such global functions within a single agent or organism are not wholly surprising, since the mechanisms (e.g., Hebbian learning) that create these neural organizations may be selected for this purpose; but agents in a multi-agent system have no obvious reason to adhere to such a structuring protocol or produce such global behaviors when acting from individual self-interest. However, Hebbian learning is actually a very simple and fully distributed habituation or positive feedback principle. Here we show that when self-interested agents can modify how they are affected by other agents (e.g., when they can influence which other agents they interact with), then, in adapting these inter-agent relationships to maximize their own utility, they will necessarily alter them in a manner homologous with Hebbian learning. Multi-agent systems with adaptable relationships will thereby exhibit the same system-level behaviors as neural networks under Hebbian learning. For example, improved global efficiency in multi-agent systems can be explained by the inherent ability of associative memory to generalize by idealizing stored patterns and/or creating new combinations of subpatterns. Thus distributed multi-agent systems can spontaneously exhibit adaptive global behaviors in the same sense, and by the same mechanism, as with the organizational principles familiar in connectionist models of organismic learning.

A simple strategy to reduce stereotype threat for orthopedic residents.

PubMed

Gomez, Everlyne; Wright, James G

2014-04-01

Stereotype threat, defined as the predicament felt by people in either positive or negative learning experiences where they could conform to negative stereotypes associated with their own group membership, can interfere with learning. The purpose of this study was to determine if a simple orientation session could reduce stereotype threat for orthopedic residents. The intervention group received an orientation on 2 occasions focusing on their possible responses to perceived poor performance in teaching rounds and the operating room (OR). Participants completed a survey with 7 questions typical for stereotype threat evaluating responses to their experiences. The questions had 7 response options with a maximum total score of 49, where higher scores indicated greater degree of experiences typical of stereotype threat. Of the 84 eligible residents, 49 participated: 22 in the nonintervention and 27 in the intervention group. The overall scores were 29 and 29.4, and 26.2 and 25.8 in the nonintervention and intervention groups for their survey responses to perceived poor performance in teaching rounds (p = 0.85) and the OR (p = 0.84), respectively. Overall, responses typical of stereotype threat were greater for perceived poor performance at teaching rounds than in the OR (p = 0.001). Residents experience low self-esteem following perceived poor performance, particularly at rounds. A simple orientation designed to reduce stereotype threat was unsuccessful in reducing this threat overall. Future research will need to consider longer-term intervention as possible strategies to reduce perceived poor performance at teaching rounds and in the OR.

Consequence of preterm birth in early adolescence: the role of language on auditory short-term memory.

PubMed

Fraello, David; Maller-Kesselman, Jill; Vohr, Betty; Katz, Karol H; Kesler, Shelli; Schneider, Karen; Reiss, Allan; Ment, Laura; Spann, Marisa N

2011-06-01

This study tested the hypothesis that preterm early adolescents' short-term memory is compromised when presented with increasingly complex verbal information and that associated neuroanatomical volumes would differ between preterm and term groups. Forty-nine preterm and 20 term subjects were evaluated at age 12 years with neuropsychological measures and magnetic resonance imaging (MRI). There were no differences between groups in simple short-term and working memory. Preterm subjects performed lower on learning and short-term memory tests that included increased verbal complexity. They had reduced right parietal, left temporal, and right temporal white matter volumes and greater bilateral frontal gray and right frontal white matter volumes. There was a positive association between complex working memory and the left hippocampus and frontal white matter in term subjects. While not correlated, memory scores and volumes of cortical regions known to subserve language and memory were reduced in preterm subjects. This study provides evidence of possible mechanisms for learning problems in former preterm infants.

Learning molecular energies using localized graph kernels.

PubMed

Ferré, Grégoire; Haut, Terry; Barros, Kipton

2017-03-21

Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

Learning molecular energies using localized graph kernels

NASA Astrophysics Data System (ADS)

Ferré, Grégoire; Haut, Terry; Barros, Kipton

2017-03-01

Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

A neural circuit mechanism for regulating vocal variability during song learning in zebra finches.

PubMed

Garst-Orozco, Jonathan; Babadi, Baktash; Ölveczky, Bence P

2014-12-15

Motor skill learning is characterized by improved performance and reduced motor variability. The neural mechanisms that couple skill level and variability, however, are not known. The zebra finch, a songbird, presents a unique opportunity to address this question because production of learned song and induction of vocal variability are instantiated in distinct circuits that converge on a motor cortex analogue controlling vocal output. To probe the interplay between learning and variability, we made intracellular recordings from neurons in this area, characterizing how their inputs from the functionally distinct pathways change throughout song development. We found that inputs that drive stereotyped song-patterns are strengthened and pruned, while inputs that induce variability remain unchanged. A simple network model showed that strengthening and pruning of action-specific connections reduces the sensitivity of motor control circuits to variable input and neural 'noise'. This identifies a simple and general mechanism for learning-related regulation of motor variability.

Study Guide: Seven Simple Secrets

ERIC Educational Resources Information Center

Satterfield, Nancy; Breaux, Annette; Whitaker, Todd

2007-01-01

This study guide has been developed to accompany the "Seven Simple Secrets" book written by Dr. Todd Whitaker and Annette Breaux. "Seven Simple Secrets" focuses on those attributes that have been found to help teachers be their absolute best in their daily challenges of teaching and improving student learning. The study guide is divided into the…

Higher glucose levels associated with lower memory and reduced hippocampal microstructure.

PubMed

Kerti, Lucia; Witte, A Veronica; Winkler, Angela; Grittner, Ulrike; Rujescu, Dan; Flöel, Agnes

2013-11-12

For this cross-sectional study, we aimed to elucidate whether higher glycosylated hemoglobin (HbA1c) and glucose levels exert a negative impact on memory performance and hippocampal volume and microstructure in a cohort of healthy, older, nondiabetic individuals without dementia. In 141 individuals (72 women, mean age 63.1 years ± 6.9 SD), memory was tested using the Rey Auditory Verbal Learning Test. Peripheral levels of fasting HbA1c, glucose, and insulin and 3-tesla MRI scans were acquired to assess hippocampal volume and microstructure, as indicated by gray matter barrier density. Linear regression and simple mediation models were calculated to examine associations among memory, glucose metabolism, and hippocampal parameters. Lower HbA1c and glucose levels were significantly associated with better scores in delayed recall, learning ability, and memory consolidation. In multiple regression models, HbA1c remained strongly associated with memory performance. Moreover, mediation analyses indicated that beneficial effects of lower HbA1c on memory are in part mediated by hippocampal volume and microstructure. Our results indicate that even in the absence of manifest type 2 diabetes mellitus or impaired glucose tolerance, chronically higher blood glucose levels exert a negative influence on cognition, possibly mediated by structural changes in learning-relevant brain areas. Therefore, strategies aimed at lowering glucose levels even in the normal range may beneficially influence cognition in the older population, a hypothesis to be examined in future interventional trials.

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…

A Piagetian Learning Cycle for Introductory Chemical Kinetics.

ERIC Educational Resources Information Center

Batt, Russell H.

1980-01-01

Described is a Piagetian learning cycle based on Monte Carlo modeling of several simple reaction mechanisms. Included are descriptions of learning cycle phases (exploration, invention, and discovery) and four BASIC-PLUS computer programs to be used in the explanation of chemical reacting systems. (Author/DS)

Reinforcement learning in supply chains.

PubMed

Valluri, Annapurna; North, Michael J; Macal, Charles M

2009-10-01

Effective management of supply chains creates value and can strategically position companies. In practice, human beings have been found to be both surprisingly successful and disappointingly inept at managing supply chains. The related fields of cognitive psychology and artificial intelligence have postulated a variety of potential mechanisms to explain this behavior. One of the leading candidates is reinforcement learning. This paper applies agent-based modeling to investigate the comparative behavioral consequences of three simple reinforcement learning algorithms in a multi-stage supply chain. For the first time, our findings show that the specific algorithm that is employed can have dramatic effects on the results obtained. Reinforcement learning is found to be valuable in multi-stage supply chains with several learning agents, as independent agents can learn to coordinate their behavior. However, learning in multi-stage supply chains using these postulated approaches from cognitive psychology and artificial intelligence take extremely long time periods to achieve stability which raises questions about their ability to explain behavior in real supply chains. The fact that it takes thousands of periods for agents to learn in this simple multi-agent setting provides new evidence that real world decision makers are unlikely to be using strict reinforcement learning in practice.

It Makes You Think: Learning Together. Think Global Thinkpiece Series

ERIC Educational Resources Information Center

Bowden, Rob

2015-01-01

In this thinkpiece Rob Bowden argues that an East meets West project points the way for global learning to be truly transformative. The project has a simple premise--that there is much to be learned by bringing Eastern and Western perspectives and pedagogies together and that such a process not only nurtures a global learning disposition…

Stuck in the Groove: A Critique of Compulsory Schooling

ERIC Educational Resources Information Center

Hansen, Ron

2011-01-01

Learning in formal schools violates several simple principles: that no one can learn on an empty spirit; that true learning requires an absence of fear or authority; that learning is the most natural of human instincts. By making schooling compulsory, we have abandoned trust in our individual and collective experience in favour of experts and…

Computational Modeling of Statistical Learning: Effects of Transitional Probability versus Frequency and Links to Word Learning

ERIC Educational Resources Information Center

Mirman, Daniel; Estes, Katharine Graf; Magnuson, James S.

2010-01-01

Statistical learning mechanisms play an important role in theories of language acquisition and processing. Recurrent neural network models have provided important insights into how these mechanisms might operate. We examined whether such networks capture two key findings in human statistical learning. In Simulation 1, a simple recurrent network…

Time Use in Massachusetts Expanded Learning Time (ELT) Schools: Issue Brief

ERIC Educational Resources Information Center

Caven, Meghan; Checkoway, Amy; Gamse, Beth; Wu, Sally

2012-01-01

Expanded learning time seems to be a simple idea: by lengthening the school day (or year), students have more time to learn. Yet as schools revisit their schedules and decide how to allocate time in their academic calendars, they can and do face challenging decisions related to time allocations. This brief highlights lessons learned from some…

Learning to Calculate and Learning Mathematics.

ERIC Educational Resources Information Center

Fearnley-Sander, Desmond

1980-01-01

A calculator solution of a simple computational problem is discussed with emphasis on its ramifications for the understanding of some fundamental theorems of pure mathematics and techniques of computing. (Author/MK)

The Impact of Presentation Format on Younger and Older Adults' Self-Regulated Learning.

PubMed

Price, Jodi

2017-01-01

Background/Study Context: Self-regulated learning involves deciding what to study and for how long. Debate surrounds whether individuals' selections are influenced more by item complexity, point values, or if instead people select in a left-to-right reading order, ignoring item complexity and value. The present study manipulated whether point values and presentation format favored selection of simple or complex Chinese-English pairs to assess the impact on younger and older adults' selection behaviors. One hundred and five younger (M age  = 20.26, SD = 2.38) and 102 older adults (M age  = 70.28, SD = 6.37) participated in the experiment. Participants studied four different 3 × 3 grids (two per trial), each containing three simple, three medium, and three complex Chinese-English vocabulary pairs presented in either a simple-first or complex-first order, depending on condition. Point values were assigned in either a 2-4-8 or 8-4-2 order so that either simple or complex items were favored. Points did not influence the order in which either age group selected items, whereas presentation format did. Younger and older adults selected more simple or complex items when they appeared in the first column. However, older adults selected and allocated more time to simpler items but recalled less overall than did younger adults. Memory beliefs and working memory capacity predicted study time allocation, but not item selection, behaviors. Presentation format must be considered when evaluating which theory of self-regulated learning best accounts for younger and older adults' study behaviors and whether there are age-related differences in self-regulated learning. The results of the present study combine with others to support the importance of also considering the role of external factors (e.g., working memory capacity and memory beliefs) in each age group's self-regulated learning decisions.

Microcomputer-Assisted Mathematics: From Simple Interest to e.

ERIC Educational Resources Information Center

Kimberling, Clark

1985-01-01

The progression from simple interest to compound interest leads naturally and quickly to the number e, involving mathematical discovery learning through writing programs. Several programs are given, with suggestions for a teaching sequence. (MNS)

Moral foundations in an interacting neural networks society: A statistical mechanics analysis

NASA Astrophysics Data System (ADS)

Vicente, R.; Susemihl, A.; Jericó, J. P.; Caticha, N.

2014-04-01

The moral foundations theory supports that people, across cultures, tend to consider a small number of dimensions when classifying issues on a moral basis. The data also show that the statistics of weights attributed to each moral dimension is related to self-declared political affiliation, which in turn has been connected to cognitive learning styles by the recent literature in neuroscience and psychology. Inspired by these data, we propose a simple statistical mechanics model with interacting neural networks classifying vectors and learning from members of their social neighbourhood about their average opinion on a large set of issues. The purpose of learning is to reduce dissension among agents when disagreeing. We consider a family of learning algorithms parametrized by δ, that represents the importance given to corroborating (same sign) opinions. We define an order parameter that quantifies the diversity of opinions in a group with homogeneous learning style. Using Monte Carlo simulations and a mean field approximation we find the relation between the order parameter and the learning parameter δ at a temperature we associate with the importance of social influence in a given group. In concordance with data, groups that rely more strongly on corroborating evidence sustain less opinion diversity. We discuss predictions of the model and propose possible experimental tests.

Functional brain networks for learning predictive statistics.

PubMed

Giorgio, Joseph; Karlaftis, Vasilis M; Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew; Kourtzi, Zoe

2017-08-18

Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. This skill relies on extracting regular patterns in space and time by mere exposure to the environment (i.e., without explicit feedback). Yet, we know little about the functional brain networks that mediate this type of statistical learning. Here, we test whether changes in the processing and connectivity of functional brain networks due to training relate to our ability to learn temporal regularities. By combining behavioral training and functional brain connectivity analysis, we demonstrate that individuals adapt to the environment's statistics as they change over time from simple repetition to probabilistic combinations. Further, we show that individual learning of temporal structures relates to decision strategy. Our fMRI results demonstrate that learning-dependent changes in fMRI activation within and functional connectivity between brain networks relate to individual variability in strategy. In particular, extracting the exact sequence statistics (i.e., matching) relates to changes in brain networks known to be involved in memory and stimulus-response associations, while selecting the most probable outcomes in a given context (i.e., maximizing) relates to changes in frontal and striatal networks. Thus, our findings provide evidence that dissociable brain networks mediate individual ability in learning behaviorally-relevant statistics. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

A case study analysing the process of analogy-based learning in a teaching unit about simple electric circuits

NASA Astrophysics Data System (ADS)

Paatz, Roland; Ryder, James; Schwedes, Hannelore; Scott, Philip

2004-09-01

The purpose of this case study is to analyse the learning processes of a 16-year-old student as she learns about simple electric circuits in response to an analogy-based teaching sequence. Analogical thinking processes are modelled by a sequence of four steps according to Gentner's structure mapping theory (activate base domain, postulate local matches, connect them to a global match, draw candidate inferences). We consider whether Gentner's theory can be used to account for the details of this specific teaching/learning context. The case study involved video-taping teaching and learning activities in a 10th-grade high school course in Germany. Teaching used water flow through pipes as an analogy for electrical circuits. Using Gentner's theory, relational nets were created from the student's statements at different stages of her learning. Overall, these nets reflect the four steps outlined earlier. We also consider to what extent the learning processes revealed by this case study are different from previous analyses of contexts in which no analogical knowledge is available.

Learning Information Systems: Theoretical Foundations.

ERIC Educational Resources Information Center

Paul, Terrance D.

This paper uses the conceptual framework of cybernetics to understand why learning information systems such as the "Accelerated Reader" work so successfully, and to examine how this simple yet incisive concept can be used to accelerate learning at every level and in all disciplines. The first section, "Basic Concepts,"…

Learning and teaching with a computer scanner

NASA Astrophysics Data System (ADS)

Planinsic, G.; Gregorcic, B.; Etkina, E.

2014-09-01

This paper introduces the readers to simple inquiry-based activities (experiments with supporting questions) that one can do with a computer scanner to help students learn and apply the concepts of relative motion in 1 and 2D, vibrational motion and the Doppler effect. We also show how to use these activities to help students think like scientists. They will conduct simple experiments, construct different explanations for their observations, test their explanations in new experiments and represent their ideas in multiple ways.

Explorations in statistics: hypothesis tests and P values.

PubMed

Curran-Everett, Douglas

2009-06-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This second installment of Explorations in Statistics delves into test statistics and P values, two concepts fundamental to the test of a scientific null hypothesis. The essence of a test statistic is that it compares what we observe in the experiment to what we expect to see if the null hypothesis is true. The P value associated with the magnitude of that test statistic answers this question: if the null hypothesis is true, what proportion of possible values of the test statistic are at least as extreme as the one I got? Although statisticians continue to stress the limitations of hypothesis tests, there are two realities we must acknowledge: hypothesis tests are ingrained within science, and the simple test of a null hypothesis can be useful. As a result, it behooves us to explore the notions of hypothesis tests, test statistics, and P values.

A neural network prototyping package within IRAF

NASA Technical Reports Server (NTRS)

Bazell, D.; Bankman, I.

1992-01-01

We outline our plans for incorporating a Neural Network Prototyping Package into the IRAF environment. The package we are developing will allow the user to choose between different types of networks and to specify the details of the particular architecture chosen. Neural networks consist of a highly interconnected set of simple processing units. The strengths of the connections between units are determined by weights which are adaptively set as the network 'learns'. In some cases, learning can be a separate phase of the user cycle of the network while in other cases the network learns continuously. Neural networks have been found to be very useful in pattern recognition and image processing applications. They can form very general 'decision boundaries' to differentiate between objects in pattern space and they can be used for associative recall of patterns based on partial cures and for adaptive filtering. We discuss the different architectures we plan to use and give examples of what they can do.

"Orthogonality" in Learning and Assessment

ERIC Educational Resources Information Center

Leslie, David

2014-01-01

This chapter proposes a simple framework, "orthogonality," to help clarify what stakeholders think about learning in college, how we assess outcomes, and how clear assessment methods might help increase confidence in returns on investment.

Simple artificial neural networks that match probability and exploit and explore when confronting a multiarmed bandit.

PubMed

Dawson, Michael R W; Dupuis, Brian; Spetch, Marcia L; Kelly, Debbie M

2009-08-01

The matching law (Herrnstein 1961) states that response rates become proportional to reinforcement rates; this is related to the empirical phenomenon called probability matching (Vulkan 2000). Here, we show that a simple artificial neural network generates responses consistent with probability matching. This behavior was then used to create an operant procedure for network learning. We use the multiarmed bandit (Gittins 1989), a classic problem of choice behavior, to illustrate that operant training balances exploiting the bandit arm expected to pay off most frequently with exploring other arms. Perceptrons provide a medium for relating results from neural networks, genetic algorithms, animal learning, contingency theory, reinforcement learning, and theories of choice.

Flexible Learning in Teacher Education: Myths, Muddles and Models

ERIC Educational Resources Information Center

Bigum, Chris; Rowan, Leonie

2004-01-01

While there has been widespread take-up of the concept 'flexible learning' within various educational environments--and equally frequent references to the flexible 'natures' of the computer and communication technologies that often underpin flexible learning initiatives--the relationship between technologies and flexibility is not a simple one. In…

Juggling with Language Learning Theories. [Videotape

ERIC Educational Resources Information Center

Murphey, Tim

2005-01-01

Learning to juggle has become popular among corporate training programs because it shows participants how to appreciate mistakes and use "Intelligent Fast Failure" (learning quickly by daring to make a lot of simple mistakes at the beginning of a process). Big business also likes the way juggling can get executives "out of the…

Tapping the Power of Personalized Learning: A Roadmap for School Leaders

ERIC Educational Resources Information Center

Rickabaugh, James

2016-01-01

In this powerful new book, James Rickabaugh, former superintendent and current director of the Institute for Personalized Learning (IPL), presents the groundbreaking results of the Institute's half-decade of research, development, and practice: a simple but powerful model for personalizing students' learning experiences by building their levels of…

Student Attrition in Mathematics E-Learning

ERIC Educational Resources Information Center

Smith, Glenn Gordon; Ferguson, David

2005-01-01

Qualitative studies indicate that mathematics does not work well in e-learning. The current study used quantitative methods to investigate more objectively the extent of problems with mathematics in e-learning. The authors used student attrition as a simple measure of student satisfaction and course viability in two studies, one investigating…

The Biological Basis of Learning and Individuality.

ERIC Educational Resources Information Center

Kandel, Eric R.; Hawkins, Robert D.

1992-01-01

Describes the biological basis of learning and individuality. Presents an overview of recent discoveries that suggest learning engages a simple set of rules that modify the strength of connection between neurons in the brain. The changes are cited as playing an important role in making each individual unique. (MCO)

Learning Non-Adjacent Regularities at Age 0 ; 7

ERIC Educational Resources Information Center

Gervain, Judit; Werker, Janet F.

2013-01-01

One important mechanism suggested to underlie the acquisition of grammar is rule learning. Indeed, infants aged 0 ; 7 are able to learn rules based on simple identity relations (adjacent repetitions, ABB: "wo fe fe" and non-adjacent repetitions, ABA: "wo fe wo", respectively; Marcus et al., 1999). One unexplored issue is…

A Brief Discussion on Motivation and Ways to Motivate Students in English Language Learning

ERIC Educational Resources Information Center

Kong, Yuan

2009-01-01

With the requirement of economic development, English has become more and more important that people begin to learn English with fully enthusiasm even from younger age. Learning a foreign language is not a simple and easy job but sometimes it is boring and dull. Motivation is critical in English learning, thus, how to effectively motivate students…

Increase Student Engagement through Project-Based Learning. Best Practices Newsletter

ERIC Educational Resources Information Center

Southern Regional Education Board (SREB), 2015

2015-01-01

We learn by doing. This simple philosophy is at the heart of project-based learning in the 21st-century classroom. It is grounded in the belief that the stand and lecture approach to teaching, worksheets and rote memorization are not enough to move students down a path to the deep learning necessary for success in college and careers. Essential…

Community Learning Campus: It Takes a Simple Message to Build a Complex Project

ERIC Educational Resources Information Center

Pearson, George

2012-01-01

Education Canada asked Tom Thompson, president of Olds College and a prime mover behind the Community Learning Campus (CLC): What were the lessons learned from this unusually ambitious education project? Thompson mentions six lessons he learned from this complex project which include: (1) Dream big, build small, act now; (2) Keep a low profile at…

How Many U.S. High School Students Have a Foreign Language Reading "Disability"? Reading Without Meaning and the Simple View.

PubMed

Sparks, Richard L; Luebbers, Julie

Conventional wisdom suggests that students classified as learning disabled will exhibit difficulties with foreign language (FL) learning, but evidence has not supported a relationship between FL learning problems and learning disabilities. The simple view of reading model posits that reading comprehension is the product of word decoding and language comprehension and that there are good readers and 3 types of poor readers-dyslexic, hyperlexic, and garden variety-who exhibit different profiles of strengths and/or deficits in word decoding and language comprehension. In this study, a random sample of U.S. high school students completing first-, second-, and third-year Spanish courses were administered standardized measures of Spanish word decoding and reading comprehension, compared with monolingual Spanish readers from first to eleventh grades, and classified into reader types according to the simple view of reading. The majority of students fit the hyperlexic profile, and no participants fit the good reader profile until they were compared with first- and second-grade monolingual Spanish readers. Findings call into question the practice of diagnosing an FL "disability" before a student engages in FL study.

Analytical model for minority games with evolutionary learning

NASA Astrophysics Data System (ADS)

Campos, Daniel; Méndez, Vicenç; Llebot, Josep E.; Hernández, Germán A.

2010-06-01

In a recent work [D. Campos, J.E. Llebot, V. Méndez, Theor. Popul. Biol. 74 (2009) 16] we have introduced a biological version of the Evolutionary Minority Game that tries to reproduce the intraspecific competition for limited resources in an ecosystem. In comparison with the complex decision-making mechanisms used in standard Minority Games, only two extremely simple strategies ( juveniles and adults) are accessible to the agents. Complexity is introduced instead through an evolutionary learning rule that allows younger agents to learn taking better decisions. We find that this game shows many of the typical properties found for Evolutionary Minority Games, like self-segregation behavior or the existence of an oscillation phase for a certain range of the parameter values. However, an analytical treatment becomes much easier in our case, taking advantage of the simple strategies considered. Using a model consisting of a simple dynamical system, the phase diagram of the game (which differentiates three phases: adults crowd, juveniles crowd and oscillations) is reproduced.

Towards a new classification of stable phase schizophrenia into major and simple neuro-cognitive psychosis: Results of unsupervised machine learning analysis.

PubMed

Kanchanatawan, Buranee; Sriswasdi, Sira; Thika, Supaksorn; Stoyanov, Drozdstoy; Sirivichayakul, Sunee; Carvalho, André F; Geffard, Michel; Maes, Michael

2018-05-23

Deficit schizophrenia, as defined by the Schedule for Deficit Syndrome, may represent a distinct diagnostic class defined by neurocognitive impairments coupled with changes in IgA/IgM responses to tryptophan catabolites (TRYCATs). Adequate classifications should be based on supervised and unsupervised learning rather than on consensus criteria. This study used machine learning as means to provide a more accurate classification of patients with stable phase schizophrenia. We found that using negative symptoms as discriminatory variables, schizophrenia patients may be divided into two distinct classes modelled by (A) impairments in IgA/IgM responses to noxious and generally more protective tryptophan catabolites, (B) impairments in episodic and semantic memory, paired associative learning and false memory creation, and (C) psychotic, excitation, hostility, mannerism, negative, and affective symptoms. The first cluster shows increased negative, psychotic, excitation, hostility, mannerism, depression and anxiety symptoms, and more neuroimmune and cognitive disorders and is therefore called "major neurocognitive psychosis" (MNP). The second cluster, called "simple neurocognitive psychosis" (SNP) is discriminated from normal controls by the same features although the impairments are less well developed than in MNP. The latter is additionally externally validated by lowered quality of life, body mass (reflecting a leptosome body type), and education (reflecting lower cognitive reserve). Previous distinctions including "type 1" (positive)/"type 2" (negative) and DSM-IV-TR (eg, paranoid) schizophrenia could not be validated using machine learning techniques. Previous names of the illness, including schizophrenia, are not very adequate because they do not describe the features of the illness, namely, interrelated neuroimmune, cognitive, and clinical features. Stable-phase schizophrenia consists of 2 relevant qualitatively distinct categories or nosological entities with SNP being a less well-developed phenotype, while MNP is the full blown phenotype or core illness. Major neurocognitive psychosis and SNP should be added to the DSM-5 and incorporated into the Research Domain Criteria project. © 2018 John Wiley & Sons, Ltd.

Learning Predictive Statistics: Strategies and Brain Mechanisms.

PubMed

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-08-30

When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory-motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions. SIGNIFICANCE STATEMENT Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. Past work has studied how humans identify repetitive patterns and associative pairings. However, the natural environment contains regularities that vary in complexity from simple repetition to complex probabilistic combinations. Here, we combine behavior and multisession fMRI to track the brain mechanisms that mediate our ability to adapt to changes in the environment's statistics. We provide evidence for an alternate route for learning complex temporal statistics: extracting the most probable outcome in a given context is implemented by interactions between executive and motor corticostriatal mechanisms compared with visual corticostriatal circuits (including hippocampal cortex) that support learning of the exact temporal statistics. Copyright © 2017 Wang et al.

Action Centered Contextual Bandits.

PubMed

Greenewald, Kristjan; Tewari, Ambuj; Klasnja, Predrag; Murphy, Susan

2017-12-01

Contextual bandits have become popular as they offer a middle ground between very simple approaches based on multi-armed bandits and very complex approaches using the full power of reinforcement learning. They have demonstrated success in web applications and have a rich body of associated theoretical guarantees. Linear models are well understood theoretically and preferred by practitioners because they are not only easily interpretable but also simple to implement and debug. Furthermore, if the linear model is true, we get very strong performance guarantees. Unfortunately, in emerging applications in mobile health, the time-invariant linear model assumption is untenable. We provide an extension of the linear model for contextual bandits that has two parts: baseline reward and treatment effect. We allow the former to be complex but keep the latter simple. We argue that this model is plausible for mobile health applications. At the same time, it leads to algorithms with strong performance guarantees as in the linear model setting, while still allowing for complex nonlinear baseline modeling. Our theory is supported by experiments on data gathered in a recently concluded mobile health study.

Plasticity of cortical inhibition in dystonia is impaired after motor learning and paired-associative stimulation.

PubMed

Meunier, Sabine; Russmann, Heike; Shamim, Ejaz; Lamy, Jean-Charles; Hallett, Mark

2012-03-01

Artificial induction of plasticity by paired associative stimulation (PAS) in healthy volunteers (HV) demonstrates Hebbian-like plasticity in selected inhibitory networks as well as excitatory networks. In a group of 17 patients with focal hand dystonia and a group of 19 HV, we evaluated how PAS and the learning of a simple motor task influence the circuits supporting long-interval intracortical inhibition (LICI, reflecting activity of GABA(B) interneurons) and long-latency afferent inhibition (LAI, reflecting activity of somatosensory inputs to the motor cortex). In HV, PAS and motor learning induced long-term potentiation (LTP)-like plasticity of excitatory networks and a lasting decrease of LAI and LICI in the motor representation of the targeted or trained muscle. The better the motor performance, the larger was the decrease of LAI. Although motor performance in the patient group was similar to that of the control group, LAI did not decrease during the motor learning as it did in the control group. In contrast, LICI was normally modulated. In patients the results after PAS did not match those obtained after motor learning: LAI was paradoxically increased and LICI did not exhibit any change. In the normal situation, decreased excitability in inhibitory circuits after induction of LTP-like plasticity may help to shape the cortical maps according to the new sensorimotor task. In patients, the abnormal or absent modulation of afferent and intracortical long-interval inhibition might indicate maladaptive plasticity that possibly contributes to the difficulty that they have to learn a new sensorimotor task. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Big Data Tools as Applied to ATLAS Event Data

NASA Astrophysics Data System (ADS)

Vukotic, I.; Gardner, R. W.; Bryant, L. A.

2017-10-01

Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Logfiles, database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and associated analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data. Such modes would simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of machine learning environments and tools like Spark, Jupyter, R, SciPy, Caffe, TensorFlow, etc. Machine learning challenges such as the Higgs Boson Machine Learning Challenge, the Tracking challenge, Event viewers (VP1, ATLANTIS, ATLASrift), and still to be developed educational and outreach tools would be able to access the data through a simple REST API. In this preliminary investigation we focus on derived xAOD data sets. These are much smaller than the primary xAODs having containers, variables, and events of interest to a particular analysis. Being encouraged with the performance of Elasticsearch for the ADC analytics platform, we developed an algorithm for indexing derived xAOD event data. We have made an appropriate document mapping and have imported a full set of standard model W/Z datasets. We compare the disk space efficiency of this approach to that of standard ROOT files, the performance in simple cut flow type of data analysis, and will present preliminary results on its scaling characteristics with different numbers of clients, query complexity, and size of the data retrieved.

When Simple Harmonic Motion Is Not that Simple: Managing Epistemological Complexity by Using Computer-Based Representations

ERIC Educational Resources Information Center

Parnafes, Orit

2010-01-01

Many real-world phenomena, even "simple" physical phenomena such as natural harmonic motion, are complex in the sense that they require coordinating multiple subtle foci of attention to get the required information when experiencing them. Moreover, for students to develop sound understanding of a concept or a phenomenon, they need to learn to get…

Basic guidelines to introduce electric circuit simulation software in a general physics course

NASA Astrophysics Data System (ADS)

Moya, A. A.

2018-05-01

The introduction of electric circuit simulation software for undergraduate students in a general physics course is proposed in order to contribute to the constructive learning of electric circuit theory. This work focuses on the lab exercises based on dc, transient and ac analysis in electric circuits found in introductory physics courses, and shows how students can use the simulation software to do simple activities associated with a lab exercise itself and with related topics. By introducing electric circuit simulation programs in a general physics course as a brief activitiy complementing lab exercise, students develop basic skills in using simulation software, improve their knowledge on the topology of electric circuits and perceive that the technology contributes to their learning, all without reducing the time spent on the actual content of the course.

Interpolated memory tests reduce mind wandering and improve learning of online lectures.

PubMed

Szpunar, Karl K; Khan, Novall Y; Schacter, Daniel L

2013-04-16

The recent emergence and popularity of online educational resources brings with it challenges for educators to optimize the dissemination of online content. Here we provide evidence that points toward a solution for the difficulty that students frequently report in sustaining attention to online lectures over extended periods. In two experiments, we demonstrate that the simple act of interpolating online lectures with memory tests can help students sustain attention to lecture content in a manner that discourages task-irrelevant mind wandering activities, encourages task-relevant note-taking activities, and improves learning. Importantly, frequent testing was associated with reduced anxiety toward a final cumulative test and also with reductions in subjective estimates of cognitive demand. Our findings suggest a potentially key role for interpolated testing in the development and dissemination of online educational content.

Adaptive filtering with the self-organizing map: a performance comparison.

PubMed

Barreto, Guilherme A; Souza, Luís Gustavo M

2006-01-01

In this paper we provide an in-depth evaluation of the SOM as a feasible tool for nonlinear adaptive filtering. A comprehensive survey of existing SOM-based and related architectures for learning input-output mappings is carried out and the application of these architectures to nonlinear adaptive filtering is formulated. Then, we introduce two simple procedures for building RBF-based nonlinear filters using the Vector-Quantized Temporal Associative Memory (VQTAM), a recently proposed method for learning dynamical input-output mappings using the SOM. The aforementioned SOM-based adaptive filters are compared with standard FIR/LMS and FIR/LMS-Newton linear transversal filters, as well as with powerful MLP-based filters in nonlinear channel equalization and inverse modeling tasks. The obtained results in both tasks indicate that SOM-based filters can consistently outperform powerful MLP-based ones.

Interpolated memory tests reduce mind wandering and improve learning of online lectures

PubMed Central

Szpunar, Karl K.; Khan, Novall Y.; Schacter, Daniel L.

2013-01-01

The recent emergence and popularity of online educational resources brings with it challenges for educators to optimize the dissemination of online content. Here we provide evidence that points toward a solution for the difficulty that students frequently report in sustaining attention to online lectures over extended periods. In two experiments, we demonstrate that the simple act of interpolating online lectures with memory tests can help students sustain attention to lecture content in a manner that discourages task-irrelevant mind wandering activities, encourages task-relevant note-taking activities, and improves learning. Importantly, frequent testing was associated with reduced anxiety toward a final cumulative test and also with reductions in subjective estimates of cognitive demand. Our findings suggest a potentially key role for interpolated testing in the development and dissemination of online educational content. PMID:23576743

Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation.

PubMed

Shimizu, Renee E; Connolly, Patrick M; Cellini, Nicola; Armstrong, Diana M; Hernandez, Lexus T; Estrada, Rolando; Aguilar, Mario; Weisend, Michael P; Mednick, Sara C; Simons, Stephen B

2018-01-01

Sounds associated with newly learned information that are replayed during non-rapid eye movement (NREM) sleep can improve recall in simple tasks. The mechanism for this improvement is presumed to be reactivation of the newly learned memory during sleep when consolidation takes place. We have developed an EEG-based closed-loop system to precisely deliver sensory stimulation at the time of down-state to up-state transitions during NREM sleep. Here, we demonstrate that applying this technology to participants performing a realistic navigation task in virtual reality results in a significant improvement in navigation efficiency after sleep that is accompanied by increases in the spectral power especially in the fast (12-15 Hz) sleep spindle band. Our results show promise for the application of sleep-based interventions to drive improvement in real-world tasks.

A simple strategy to reduce stereotype threat for orthopedic residents

PubMed Central

Gomez, Everlyne; Wright, James G.

2014-01-01

Background Stereotype threat, defined as the predicament felt by people in either positive or negative learning experiences where they could conform to negative stereotypes associated with their own group membership, can interfere with learning. The purpose of this study was to determine if a simple orientation session could reduce stereotype threat for orthopedic residents. Methods The intervention group received an orientation on 2 occasions focusing on their possible responses to perceived poor performance in teaching rounds and the operating room (OR). Participants completed a survey with 7 questions typical for stereotype threat evaluating responses to their experiences. The questions had 7 response options with a maximum total score of 49, where higher scores indicated greater degree of experiences typical of stereotype threat. Results Of the 84 eligible residents, 49 participated: 22 in the nonintervention and 27 in the intervention group. The overall scores were 29 and 29.4, and 26.2 and 25.8 in the nonintervention and intervention groups for their survey responses to perceived poor performance in teaching rounds (p = 0.85) and the OR (p = 0.84), respectively. Overall, responses typical of stereotype threat were greater for perceived poor performance at teaching rounds than in the OR (p = 0.001). Conclusion Residents experience low self-esteem following perceived poor performance, particularly at rounds. A simple orientation designed to reduce stereotype threat was unsuccessful in reducing this threat overall. Future research will need to consider longer-term intervention as possible strategies to reduce perceived poor performance at teaching rounds and in the OR. PMID:24666454

Learning molecular energies using localized graph kernels

DOE PAGES

Ferré, Grégoire; Haut, Terry Scot; Barros, Kipton Marcos

2017-03-21

We report that recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturallymore » incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. Finally, we benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.« less

Learning molecular energies using localized graph kernels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferré, Grégoire; Haut, Terry Scot; Barros, Kipton Marcos

We report that recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturallymore » incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. Finally, we benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.« less

The relationship of learning motivation, achievement and satisfaction for nurses learning simple excel VBA information systems programming.

PubMed

Lee, Ying Li; Chien, Tsai Feng; Kuo, Ming Chuan; Chang, Polun

2014-01-01

This study aims to understand the relationship between participating nurses' motivation, achievement and satisfaction before and after they learned to program in Excel Visual Basic for Applications (Excel VBA). We held a workshop to train nurses in developing simple Excel VBA information systems to support their clinical or administrative practices. Before and after the workshop, the participants were evaluated on their knowledge of Excel VBA, and a questionnaire was given to survey their learning motivation and satisfaction. Statistics softwares Winsteps and SPSS were used for data analysis. Results show that the participants are more knowledgeable about VBA as well as more motivated in learning VBA after the workshop. Participants were highly satisfied with the overall arrangement of the workshop and instructors, but didn't have enough confidence in promoting the application of Excel VBA themselves. In addition, we were unable to predict the participants' achievement by their demographic characteristics or pre-test motivation level.

The effects of sleep deprivation on dissociable prototype learning systems.

PubMed

Maddox, W Todd; Glass, Brian D; Zeithamova, Dagmar; Savarie, Zachary R; Bowen, Christopher; Matthews, Michael D; Schnyer, David M

2011-03-01

The cognitive neural underpinnings of prototype learning are becoming clear. Evidence points to 2 different neural systems, depending on the learning parameters. A/not-A (AN) prototype learning is mediated by posterior brain regions that are involved in early perceptual learning, whereas A/B (AB) is mediated by frontal and medial temporal lobe regions. To investigate the effects of sleep deprivation on AN and AB prototype learning and to use established prototype models to provide insights into the cognitive-processing locus of sleep-deprivation deficits. Participants performed an AN and an AB prototype learning task twice, separated by a 24-hour period, with or without sleep between testing sessions. Eighteen West Point cadets participated in the sleep-deprivation group, and 17 West Point cadets participated in a control group. Sleep deprivation led to an AN, but not an AB, performance deficit. Prototype model analyses indicated that the AN deficit was due to changes in attentional focus and a decrease in confidence that is reflected in an increased bias to respond non-A. The findings suggest that AN, but not AB, prototype learning is affected by sleep deprivation. Prototype model analyses support the notion that the effect of sleep deprivation on AN is consistent with lapses in attentional focus that are more detrimental to AN than to AB. This finding adds to a growing body of work that suggests that different performance changes associated with sleep deprivation can be attributed to a common mechanism of changes in simple attention and vigilance.

Self-Directed Learning with Web-Based Sites: How Well Do Students' Perceptions and Thinking Match with Their Teachers?

ERIC Educational Resources Information Center

Ng, Wan

2008-01-01

With research consistently showing that students can be motivated to learn with ICT, this case study sought to investigate Year 7 students' learning about simple machines in an ICT-enhanced environment where they could self-direct their own learning with minimal intervention from the teacher. The study is focused on how well do students and…

Instructor Fluency Leads to Higher Confidence in Learning, but Not Better Learning

ERIC Educational Resources Information Center

Toftness, Alexander R.; Carpenter, Shana K.; Geller, Jason; Lauber, Sierra; Johnson, Madeline; Armstrong, Patrick I.

2018-01-01

Students' judgements of their own learning often exceed their knowledge on a given topic. One source of this pervasive overconfidence is fluency, the perceived ease with which information is acquired. Though effects of fluency on metacognitive judgments have been explored by manipulating relatively simple stimuli such as font style, few studies…

It's in the Bag: Digital Backpacks for Project-Based Learning

ERIC Educational Resources Information Center

Basham, James D.; Perry, Ernest; Meyer, Helen

2011-01-01

When it comes to technology, many schools know what they want. They want targeted and scalable solutions that enhance learning and meet the NETS.S. And the teachers in those schools want simple, strategic instructional frameworks for developing their students' basic and digital age skills while meeting diverse learning needs. But as many…

Reasons and Methods to Learn the Management

ERIC Educational Resources Information Center

Li, Hongxin; Ding, Mengchun

2010-01-01

Reasons for learning the management include (1) perfecting the knowledge structure, (2) the management is the base of all organizations, (3) one person may be the manager or the managed person, (4) the management is absolutely not simple knowledge, and (5) the learning of the theoretical knowledge of the management can not be replaced by the…

Developing an Assessment of Learning Process: The Importance of Pre-Testing

ERIC Educational Resources Information Center

Sheran, Michelle; Sarbaum, Jeffrey

2012-01-01

Colleges and universities are increasingly being held accountable for assessing and reporting student learning. Recently there has been increased focus on using assessment to improve learning over time. In this paper we present a simple, step-by-step assessment process that will deliver meaningful results to achieve these ends. We emphasize the…

Identifying Simple Numerical Stimuli: Processing Inefficiencies Exhibited by Arithmetic Learning Disabled Children.

ERIC Educational Resources Information Center

Koontz, Kristine L.; Berch, Daniel B.

1996-01-01

Children with arithmetic learning disabilities (n=16) and normally achieving controls (n=16) in grades 3-5 were administered a battery of computerized tasks. Memory spans for both letters and digits were found to be smaller among the arithmetic learning disabled children. Implications for teaching are discussed. (Author/CMS)

The Benefits of Testing for Learning on Later Performance

ERIC Educational Resources Information Center

McConnell, Meghan M.; St-Onge, Christina; Young, Meredith E.

2015-01-01

Testing has been shown to enhance retention of learned information beyond simple studying, a phenomena known as test-enhanced learning (TEL). Research has shown that TEL effects are greater for tests that require the production of responses [e.g., short-answer questions (SAQs)] relative to tests that require the recognition of correct answers…

Curiosity + Kindergarten = Future Scientists

ERIC Educational Resources Information Center

Flannagan, Jenny Sue; Rockenbaugh, Liesl

2010-01-01

Carefully crafted experiences in the early childhood classroom can create learning opportunities for children that allow one curiosity to lead to another. Learning how to find out answers to fascinating questions is what science is all about. In fact, it can be as simple as learning how an ordinary egg can be changed. For the past year, the…

A Complex mTOR Response in Habituation Paradigms for a Social Signal in Adult Songbirds

ERIC Educational Resources Information Center

Ahmadiantehrani, Somayeh; Gores, Elisa O.; London, Sarah E.

2018-01-01

Nonassociative learning is considered simple because it depends on presentation of a single stimulus, but it likely reflects complex molecular signaling. To advance understanding of the molecular mechanisms of one form of nonassociative learning, habituation, for ethologically relevant signals we examined song recognition learning in adult zebra…

A Study of a "Model of School Learning." Monograph Number 4.

ERIC Educational Resources Information Center

Carroll, John B.; Spearritt, Donald

A booklet of a programmed-instruction type was developed to obtain the measures needed to test Carroll's model of school learning, including ability, aptitude, quality of instruction, opportunity for learning, perserverance, and time criterion. Simple rules in an artificial foreign language were taught by means of the booklet to sixth-grade…

Disruptive Technology Enhanced Learning: The Use and Misuse of Digital Technologies in Higher Education

ERIC Educational Resources Information Center

Flavin, Michael

2017-01-01

This book is about how technologies are used in practice to support learning and teaching in higher education. Despite digitization and e-learning becoming ever-increasingly popular in university teaching settings, this book convincingly argues instead in favour of simple and convenient technologies, thus disrupting traditional patterns of…

Learning, Empowerment and Judgement

ERIC Educational Resources Information Center

Luntley, Michael

2007-01-01

Here is a distinction that appears very simple, looks compelling and seems to be deeply rooted in our reflections on learning. The distinction is between activities of learning that involve training and those that involve reasoning. In the former, the pupil is a passive recipient of habits of mind and action. The mechanism by which they acquire…

Model-Based Reinforcement Learning under Concurrent Schedules of Reinforcement in Rodents

ERIC Educational Resources Information Center

Huh, Namjung; Jo, Suhyun; Kim, Hoseok; Sul, Jung Hoon; Jung, Min Whan

2009-01-01

Reinforcement learning theories postulate that actions are chosen to maximize a long-term sum of positive outcomes based on value functions, which are subjective estimates of future rewards. In simple reinforcement learning algorithms, value functions are updated only by trial-and-error, whereas they are updated according to the decision-maker's…

Cognitive Addition: Comparison of Learning Disabled and Academically Normal Children.

ERIC Educational Resources Information Center

Geary, David C.; And Others

To isolate the process deficits underlying a specific learning disability in mathematics achievement, 77 academically normal and 46 learning disabled (LD) students in second, fourth or sixth grade were presented 140 simple addition problems using a true-false reaction time verification paradigm. (The problems were on a video screen controlled by…

A Computer Model of Simple Forms of Learning.

ERIC Educational Resources Information Center

Jones, Thomas L.

A basic unsolved problem in science is that of understanding learning, the process by which people and machines use their experience in a situation to guide future action in similar situations. The ideas of Piaget, Pavlov, Hull, and other learning theorists, as well as previous heuristic programing models of human intelligence, stimulated this…

Acquiring New Spatial Intuitions: Learning to Reason about Rotations

ERIC Educational Resources Information Center

Pani, John R.; Chariker, Julia H.; Dawson, Thomas E.; Johnson, Nathan

2005-01-01

There are certain simple rotations of objects that most people cannot reason about accurately. Reliable gaps in the understanding of a fundamental physical domain raise the question of how learning to reason in that domain might proceed. Using virtual reality techniques, this project investigated the nature of learning to reason across the domain…

Connect the Dots: A Dedicated System for Learning Links Teacher Teams to Student Outcomes

ERIC Educational Resources Information Center

Ermeling, Bradley A.

2012-01-01

Establishing school-based professional learning appears so simple and straightforward during inspiring presentations at summer workshops, but keeping collaborative work focused on teaching and learning in such a way that it produces consistent results is a highly underestimated task. Investigations and experience from a group of researchers at the…

Distinct Roles of Dopamine and Subthalamic Nucleus in Learning and Probabilistic Decision Making

ERIC Educational Resources Information Center

Coulthard, Elizabeth J.; Bogacz, Rafal; Javed, Shazia; Mooney, Lucy K.; Murphy, Gillian; Keeley, Sophie; Whone, Alan L.

2012-01-01

Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making…

Flight Research into Simple Adaptive Control on the NASA FAST Aircraft

NASA Technical Reports Server (NTRS)

Hanson, Curtis E.

2011-01-01

A series of simple adaptive controllers with varying levels of complexity were designed, implemented and flight tested on the NASA Full-Scale Advanced Systems Testbed (FAST) aircraft. Lessons learned from the development and flight testing are presented.

A simple automated system for appetitive conditioning of zebrafish in their home tanks.

PubMed

Doyle, Jillian M; Merovitch, Neil; Wyeth, Russell C; Stoyek, Matthew R; Schmidt, Michael; Wilfart, Florentin; Fine, Alan; Croll, Roger P

2017-01-15

We describe here an automated apparatus that permits rapid conditioning paradigms for zebrafish. Arduino microprocessors were used to control the delivery of auditory or visual stimuli to groups of adult or juvenile zebrafish in their home tanks in a conventional zebrafish facility. An automatic feeder dispensed precise amounts of food immediately after the conditioned stimuli, or at variable delays for controls. Responses were recorded using inexpensive cameras, with the video sequences analysed with ImageJ or Matlab. Fish showed significant conditioned responses in as few as 5 trials, learning that the conditioned stimulus was a predictor of food presentation at the water surface and at the end of the tank where the food was dispensed. Memories of these conditioned associations persisted for at least 2days after training when fish were tested either as groups or as individuals. Control fish, for which the auditory or visual stimuli were specifically unpaired with food, showed no comparable responses. This simple, low-cost, automated system permits scalable conditioning of zebrafish with minimal human intervention, greatly reducing both variability and labour-intensiveness. It will be useful for studies of the neural basis of learning and memory, and for high-throughput screening of compounds modifying those processes. Copyright © 2016 Elsevier B.V. All rights reserved.

Effectiveness and Adoption of a Drawing-to-Learn Study Tool for Recall and Problem Solving: Minute Sketches with Folded Lists

PubMed Central

Heideman, Paul D.; Flores, K. Adryan; Sevier, Lu M.; Trouton, Kelsey E.

2017-01-01

Drawing by learners can be an effective way to develop memory and generate visual models for higher-order skills in biology, but students are often reluctant to adopt drawing as a study method. We designed a nonclassroom intervention that instructed introductory biology college students in a drawing method, minute sketches in folded lists (MSFL), and allowed them to self-assess their recall and problem solving, first in a simple recall task involving non-European alphabets and later using unfamiliar biology content. In two preliminary ex situ experiments, students had greater recall on the simple learning task, non-European alphabets with associated phonetic sounds, using MSFL in comparison with a preferred method, visual review (VR). In the intervention, students studying using MSFL and VR had ∼50–80% greater recall of content studied with MSFL and, in a subset of trials, better performance on problem-solving tasks on biology content. Eight months after beginning the intervention, participants had shifted self-reported use of drawing from 2% to 20% of study time. For a small subset of participants, MSFL had become a preferred study method, and 70% of participants reported continued use of MSFL. This brief, low-cost intervention resulted in enduring changes in study behavior. PMID:28495932

Learning Abstract Physical Concepts from Experience: Design and Use of an RC Circuit

NASA Astrophysics Data System (ADS)

Parra, Alfredo; Ordenes, Jorge; de la Fuente, Milton

2018-05-01

Science learning for undergraduate students requires grasping a great number of theoretical concepts in a rather short time. In our experience, this is especially difficult when students are required to simultaneously use abstract concepts, mathematical reasoning, and graphical analysis, such as occurs when learning about RC circuits. We present a simple experimental model in this work that allows students to easily design, build, and analyze RC circuits, thus providing an opportunity to test personal ideas, build graphical descriptions, and explore the meaning of the respective mathematical models, ultimately gaining a better grasp of the concepts involved. The result suggests that the simple setup indeed helps untrained students to visualize the essential points of this kind of circuit.

Aggregative Learning Method and Its Application for Communication Quality Evaluation

NASA Astrophysics Data System (ADS)

Akhmetov, Dauren F.; Kotaki, Minoru

2007-12-01

In this paper, so-called Aggregative Learning Method (ALM) is proposed to improve and simplify the learning and classification abilities of different data processing systems. It provides a universal basis for design and analysis of mathematical models of wide class. A procedure was elaborated for time series model reconstruction and analysis for linear and nonlinear cases. Data approximation accuracy (during learning phase) and data classification quality (during recall phase) are estimated from introduced statistic parameters. The validity and efficiency of the proposed approach have been demonstrated through its application for monitoring of wireless communication quality, namely, for Fixed Wireless Access (FWA) system. Low memory and computation resources were shown to be needed for the procedure realization, especially for data classification (recall) stage. Characterized with high computational efficiency and simple decision making procedure, the derived approaches can be useful for simple and reliable real-time surveillance and control system design.

Personality traits associated with intrinsic academic motivation in medical students.

PubMed

Tanaka, Masaaki; Mizuno, Kei; Fukuda, Sanae; Tajima, Seiki; Watanabe, Yasuyoshi

2009-04-01

Motivation is one of the most important psychological concepts in education and is related to academic outcomes in medical students. In this study, the relationships between personality traits and intrinsic academic motivation were examined in medical students. The study group consisted of 119 Year 2 medical students at Osaka City University Graduate School of Medicine. They completed questionnaires dealing with intrinsic academic motivation (the Intrinsic Motivation Scale toward Learning) and personality (the Temperament and Character Inventory [TCI]). On simple regression analyses, the TCI dimensions of persistence, self-directedness, co-operativeness and self-transcendence were positively associated with intrinsic academic motivation. On multiple regression analysis adjusted for age and gender, the TCI dimensions of persistence, self-directedness and self-transcendence were positively associated with intrinsic academic motivation. The temperament dimension of persistence and the character dimensions of self-directedness and self-transcendence are associated with intrinsic academic motivation in medical students.

m-Learning and holography: Compatible techniques?

NASA Astrophysics Data System (ADS)

Calvo, Maria L.

2014-07-01

Since the last decades, cell phones have become increasingly popular and are nowadays ubiquitous. New generations of cell phones are now equipped with text messaging, internet, and camera features. They are now making their way into the classroom. This is creating a new teaching and learning technique, the so called m-Learning (or mobile-Learning). Because of the many benefits that cell phones offer, teachers could easily use them as a teaching and learning tool. However, an additional work from the teachers for introducing their students into the m-Learning in the classroom needs to be defined and developed. As an example, optical techniques, based upon interference and diffraction phenomena, such as holography, appear to be convenient topics for m-Learning. They can be approached with simple examples and experiments within the cell phones performances and classroom accessibility. We will present some results carried out at the Faculty of Physical Sciences in UCM to obtain very simple holographic recordings via cell phones. The activities were carried out inside the course on Optical Coherence and Laser, offered to students in the fourth course of the Grade in Physical Sciences. Some open conclusions and proposals will be presented.

Minor neurological dysfunction in five year old very preterm children is associated with lower processing speed.

PubMed

Kurpershoek, Tinka; Potharst-Sirag, Eva S; Aarnoudse-Moens, Cornelieke S H; van Wassenaer-Leemhuis, Aleid G

2016-12-01

Minor neurological dysfunction (MND) is present in one quarter to one third of children born very preterm (VP). The more severe form, complex (c)-MND has been associated with learning disabilities, behavioural and motor problems. To study the association between c-MND and neurocognitive and motor disabilities at age five in VP children without CP. Ninety-four children born with gestational age<30weeks and/or a birth weight<1000g were assessed at five years corrected age. MND was classified according to Touwen. The Wechsler Preschool and Primary School Scale of Intelligence (WPPSI-III-NL) was used to measure intelligence. Simple reaction time, focused attention and visuomotor coordination were measured using the Amsterdam Neuropsychological Tasks, and working memory using a Digit Span Task. For motor skills the Movement Assessment Battery for children (M-ABC2) was used. Eighty-one percent was classified as 'normal' (no or simple (s-)-MND) and 19% as 'abnormal'(c-MND or mild CP). The abnormal group had a significantly lower processing speed quotient (PSQ), M-ABC percentile score and slower simple Reaction Time than the normal group. Verbal IQ, Performance IQ, working memory, focused attention and visuomotor coordination did not differ between groups. Exclusion of the mild CP cases (n=4) led to similar results. Five year old VP children with c-MND have lower PSQ, slower reaction time, and poorer motor skills, than those without c-MND. Neurological examination should include identification of MND to help identify children at risk for neurocognitive disabilities. Copyright © 2016. Published by Elsevier Ireland Ltd.

Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels

PubMed Central

Afshar, Saeed; George, Libin; Tapson, Jonathan; van Schaik, André; Hamilton, Tara J.

2014-01-01

This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotemporal spike patterns. SKAN is the first proposed neuron model to investigate the effects of dynamic synapto-dendritic kernels and demonstrate their computational power even at the single neuron scale. The rule-set defining the neuron is simple: there are no complex mathematical operations such as normalization, exponentiation or even multiplication. The functionalities of SKAN emerge from the real-time interaction of simple additive and binary processes. Like a biological neuron, SKAN is robust to signal and parameter noise, and can utilize both in its operations. At the network scale neurons are locked in a race with each other with the fastest neuron to spike effectively “hiding” its learnt pattern from its neighbors. The robustness to noise, high speed, and simple building blocks not only make SKAN an interesting neuron model in computational neuroscience, but also make it ideal for implementation in digital and analog neuromorphic systems which is demonstrated through an implementation in a Field Programmable Gate Array (FPGA). Matlab, Python, and Verilog implementations of SKAN are available at: http://www.uws.edu.au/bioelectronics_neuroscience/bens/reproducible_research. PMID:25505378

Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels.

PubMed

Afshar, Saeed; George, Libin; Tapson, Jonathan; van Schaik, André; Hamilton, Tara J

2014-01-01

This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotemporal spike patterns. SKAN is the first proposed neuron model to investigate the effects of dynamic synapto-dendritic kernels and demonstrate their computational power even at the single neuron scale. The rule-set defining the neuron is simple: there are no complex mathematical operations such as normalization, exponentiation or even multiplication. The functionalities of SKAN emerge from the real-time interaction of simple additive and binary processes. Like a biological neuron, SKAN is robust to signal and parameter noise, and can utilize both in its operations. At the network scale neurons are locked in a race with each other with the fastest neuron to spike effectively "hiding" its learnt pattern from its neighbors. The robustness to noise, high speed, and simple building blocks not only make SKAN an interesting neuron model in computational neuroscience, but also make it ideal for implementation in digital and analog neuromorphic systems which is demonstrated through an implementation in a Field Programmable Gate Array (FPGA). Matlab, Python, and Verilog implementations of SKAN are available at: http://www.uws.edu.au/bioelectronics_neuroscience/bens/reproducible_research.

Concrete Condition Assessment Using Impact-Echo Method and Extreme Learning Machines

PubMed Central

Zhang, Jing-Kui; Yan, Weizhong; Cui, De-Mi

2016-01-01

The impact-echo (IE) method is a popular non-destructive testing (NDT) technique widely used for measuring the thickness of plate-like structures and for detecting certain defects inside concrete elements or structures. However, the IE method is not effective for full condition assessment (i.e., defect detection, defect diagnosis, defect sizing and location), because the simple frequency spectrum analysis involved in the existing IE method is not sufficient to capture the IE signal patterns associated with different conditions. In this paper, we attempt to enhance the IE technique and enable it for full condition assessment of concrete elements by introducing advanced machine learning techniques for performing comprehensive analysis and pattern recognition of IE signals. Specifically, we use wavelet decomposition for extracting signatures or features out of the raw IE signals and apply extreme learning machine, one of the recently developed machine learning techniques, as classification models for full condition assessment. To validate the capabilities of the proposed method, we build a number of specimens with various types, sizes, and locations of defects and perform IE testing on these specimens in a lab environment. Based on analysis of the collected IE signals using the proposed machine learning based IE method, we demonstrate that the proposed method is effective in performing full condition assessment of concrete elements or structures. PMID:27023563

Pitfalls of Counterfactual Thinking in Medical Practice: Preventing Errors by Using More Functional Reference Points

PubMed Central

Petrocelli, John V.

2013-01-01

Background Counterfactual thinking involves mentally simulating alternatives to reality. The current article reviews literature pertaining to the relevance counterfactual thinking has for the quality of medical decision making. Although earlier counterfactual thought research concluded that counterfactuals have important benefits for the individual, there are reasons to believe that counterfactual thinking is also associated with dysfunctional consequences. Of particular focus is whether or not medical experience, and its influence on counterfactual thinking, actually informs or improves medical practice. It is hypothesized that relatively more probable decision alternatives, followed by undesirable outcomes and counterfactual thought responses, can be abandoned for relatively less probable decision alternatives. Design and Methods Building on earlier research demonstrating that counterfactual thinking can impede memory and learning in a decision paradigm with undergraduate students, the current study examines the extent to which earlier findings can be generalized to practicing physicians (N=10). Participants were asked to complete 60 trials of a computerized Monty Hall Problem simulation. Learning by experience was operationalized as the frequency of switch-decisions. Results Although some learning was evidenced by a general increase in switch-decision frequency across block trials, the extent of learning demonstrated was not ideal, nor practical. Conclusions A simple, multiple-trial, decision paradigm demonstrated that doctors fail to learn basic decision-outcome associations through experience. An agenda for future research, which tests the functionality of reference points (other than counterfactual alternatives) for the purposes of medical decision making, is proposed. Significance for public health The quality of healthcare depends heavily on the judgments and decisions made by doctors and other medical professionals. Findings from this research indicate that doctors fail to learn basic decision-outcome associations through experience, as evidenced by the sample’s tendency to select the optimal decision strategy in only 50% of 60 trials (each of which was followed by veridical feedback). These findings suggest that professional experience is unlikely to enhance the quality of medical decision making. Thus, this research has implications for understanding how doctors’ reactions to medical outcomes shape their judgments and affect the degree to which their future treatment intentions are consistent with clinical practice guidelines. The current research is integrated with earlier research on counter-factual thinking, which appears to be a primary element inhibiting the learning of decision-outcome associations. An agenda for future research is proposed. PMID:25170495

Finger agnosia and cognitive deficits in patients with Alzheimer's disease.

PubMed

Davis, Andrew S; Trotter, Jeffrey S; Hertza, Jeremy; Bell, Christopher D; Dean, Raymond S

2012-01-01

The purpose of this study was to examine the presence of finger agnosia in patients with Alzheimer's disease (AD) and to determine if level of finger agnosia was related to cognitive impairment. Finger agnosia is a sensitive measure of cerebral impairment and is associated with neurofunctional areas implicated in AD. Using a standardized and norm-referenced approach, results indicated that patients with AD evidenced significantly decreased performance on tests of bilateral finger agnosia compared with healthy age-matched controls. Finger agnosia was predictive of cognitive dysfunction on four of seven domains, including: Crystallized Language, Fluid Processing, Associative Learning, and Processing Speed. Results suggest that measures of finger agnosia, a short and simple test, may be useful in the early detection of AD.

Emotion processing fails to modulate putative mirror neuron response to trained visuomotor associations.

PubMed

Fitzgibbon, Bernadette M; Kirkovski, Melissa; Fornito, Alex; Paton, Bryan; Fitzgerald, Paul B; Enticott, Peter G

2016-04-01

Recent neuroimaging studies have demonstrated that activation of the putative human mirror neuron system (MNS) can be elicited via visuomotor training. This is generally interpreted as supporting an associative learning account of the mirror neuron system (MNS) that argues against the ontogeny of the MNS to be an evolutionary adaptation for social cognition. The current study assessed whether a central component of social cognition, emotion processing, would influence the MNS activity to trained visuomotor associations, which could support a broader role of the MNS in social cognition. Using functional magnetic resonance imaging (fMRI), we assessed repetition suppression to the presentation of stimulus pairs involving a simple hand action and a geometric shape that was either congruent or incongruent with earlier association training. Each pair was preceded by an image of positive, negative, or neutral emotionality. In support of an associative learning account of the MNS, repetition suppression was greater for trained pairs compared with untrained pairs in several regions, primarily supplementary motor area (SMA) and right inferior frontal gyrus (rIFG). This response, however, was not modulated by the valence of the emotional images. These findings argue against a fundamental role of emotion processing in the mirror neuron response, and are inconsistent with theoretical accounts linking mirror neurons to social cognition. Copyright © 2016 Elsevier Ltd. All rights reserved.

Enhancing Learning Objectives by Use of Simple Virtual Microscopic Slides in Cellular Physiology and Histology: Impact and Attitudes

ERIC Educational Resources Information Center

Anyanwu, Godson Emeka; Agu, Augustine Uchechukwu; Anyaehie, Ugochukwu Bond

2012-01-01

The impact and perception of students on the use of a simple, low technology-driven version of a virtual microscope in teaching and assessments in cellular physiology and histology were studied. Its impact on the time and resources of the faculty were also assessed. Simple virtual slides and conventional microscopes were used to conduct the same…

The use of educational comics in learning anatomy among multiple student groups.

PubMed

Kim, Jiyoon; Chung, Min Suk; Jang, Hae Gwon; Chung, Beom Sun

2017-01-01

Understanding basic human anatomy can be beneficial for all students, regardless of when, or if, they will later undertake a formal course in the subject. For students who are preparing to undertake a formal anatomy course, educational comics on basic anatomy can serve as a concise and approachable review of the material. For other students, these comics can serve as a helpful and fun introduction to the human body. The objective of the comics in this study was to promote an understanding of fundamental human anatomy through self-learning among students. Based on the authors' previous teaching experience, these anatomy comics were produced in a simple, direct style. The comics were titled after the two main characters, "Anna" (a girl) and "Tommy" (a boy). These comics were then presented to groups of elementary school students, high school students, premedical students, and medical students to assess the comics' ability to enhance student interest and comprehension of basic anatomy. Quiz scores among high school students and premedical students were significantly higher among participants who read the educational comics, indicating a deeper comprehension of the subject. Among medical students, close reading of the comics was associated with improved course grades. These educational anatomy comics may be helpful tools to enrich a broad spectrum of different students in learning basic human anatomy. Anat Sci Educ 10: 79-86. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

Inter-Individual Variation in Fronto-Temporal Connectivity Predicts the Ability to Learn Different Types of Associations

PubMed Central

Alm, Kylie H.; Rolheiser, Tyler; Olson, Ingrid R.

2016-01-01

The uncinate fasciculus connects portions of the anterior and medial temporal lobes to the lateral orbitofrontal cortex, so it has long been thought that this limbic fiber pathway plays an important role in episodic memory. Some types of episodic memory are impaired after damage to the uncinate, while others remain intact. Because of this, the specific role played by the uncinate fasciculus in episodic memory remains undetermined. In the present study, we tested the hypothesis that the uncinate fasciculus is involved in episodic memory tasks that have high competition between representations at retrieval. To test this hypothesis, healthy young adults performed three tasks: Experiment 1 in which they learned to associate names with faces through feedback provided at the end of each trial; Experiment 2 in which they learned to associate fractals with cued locations through feedback provided at the end of each trial; and Experiment 3 in which unique faces were remembered in a paradigm with low retrieval competition. Diffusion tensor imaging and deterministic tractography methods were used to extract measures of uncinate fasciculus microstructure. Results revealed that microstructural properties of the uncinate, but not a control tract, the inferior longitudinal fasciculus, significantly predicted individual differences in performance on the face-name and fractal-location tasks. However, no relationship was observed for simple face memory (Experiment 3). These findings suggest that the uncinate fasciculus may be important for adjudicating between competing memory representations at the time of episodic retrieval. PMID:26908315

Causal reasoning versus associative learning: A useful dichotomy or a strawman battle in comparative psychology?

PubMed

Hanus, Daniel

2016-08-01

The debate about whether or not one could/should ascribe reasoning abilities to animals has deep historical roots and seems very up-to-date in the light of the immense body of new empirical data originating from various species and research paradigms. Associative learning (AL) seems to be a ubiquitous low-level contender for any cognitive interpretation of animal behavior, mostly because of the assumed mechanistic simplicity and phylogenetic prevalence. However, the implicit assumption that AL is simple and therefore the most parsimonious mechanism to describe seemingly complex behavior can and must be questioned on various grounds. Using recent empirical findings with chimpanzees as an example, I argue that at times inferential reasoning might be the most likely candidate to account for performance differences between experimental and control conditions. Finally, a general conclusion drawn from the current debate(s) in the field of comparative psychology could be that a dichotomist battle of 2 conceptual camps-each of which is lacking a clear and homogeneous theoretical framework-is a scientific deadlock. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Using spoken words to guide open-ended category formation.

PubMed

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.

Conditioning to colors: a population assay for visual learning in Drosophila.

PubMed

van Swinderen, Bruno

2011-11-01

Vision is a major sensory modality in Drosophila behavior, with more than one-half of the Drosophila brain devoted to visual processing. The mechanisms of vision in Drosophila can be studied in individuals and in populations of flies by using various paradigms. Although there has never been a widely used population assay for visual learning in Drosophila, some population paradigms have shown significant visual learning. These studies use colors as conditioned stimuli (CS) and shaking as the unconditioned stimulus (US). A simple version of the paradigm, conditioning to colors using a shaking device, is described here. A conditioning chamber, called a crab, is designed to center the flies after shaking by having them tumble down to the lowest point between joined glass tubes forming a V. Thus, vibration should be just strong enough to center most flies. After shaking, flies display a geotactic response and climb up either side of the V, and their choice of which side to climb is influenced by color displays on either side. The proportion of flies on either side determines the flies' natural preference or their learned avoidance of a color associated with shaking.

Easy-to-learn cardiopulmonary resuscitation training programme: a randomised controlled trial on laypeople's resuscitation performance.

PubMed

Ko, Rachel Jia Min; Lim, Swee Han; Wu, Vivien Xi; Leong, Tak Yam; Liaw, Sok Ying

2018-04-01

Simplifying the learning of cardiopulmonary resuscitation (CPR) is advocated to improve skill acquisition and retention. A simplified CPR training programme focusing on continuous chest compression, with a simple landmark tracing technique, was introduced to laypeople. The study aimed to examine the effectiveness of the simplified CPR training in improving lay rescuers' CPR performance as compared to standard CPR. A total of 85 laypeople (aged 21-60 years) were recruited and randomly assigned to undertake either a two-hour simplified or standard CPR training session. They were tested two months after the training on a simulated cardiac arrest scenario. Participants' performance on the sequence of CPR steps was observed and evaluated using a validated CPR algorithm checklist. The quality of chest compression and ventilation was assessed from the recording manikins. The simplified CPR group performed significantly better on the CPR algorithm when compared to the standard CPR group (p < 0.01). No significant difference was found between the groups in time taken to initiate CPR. However, a significantly higher number of compressions and proportion of adequate compressions was demonstrated by the simplified group than the standard group (p < 0.01). Hands-off time was significantly shorter in the simplified CPR group than in the standard CPR group (p < 0.001). Simplifying the learning of CPR by focusing on continuous chest compressions, with simple hand placement for chest compression, could lead to better acquisition and retention of CPR algorithms, and better quality of chest compressions than standard CPR. Copyright: © Singapore Medical Association.

E-Learning Quality Standards for Consumer Protection and Consumer Confidence: A Canadian Case Study in E-Learning Quality Assurance

ERIC Educational Resources Information Center

Barker, Kathryn Chang

2007-01-01

Emerging concerns about quality of e-learning products and services animated a project in Canada to create quality standards that derived primarily from the needs of consumer, that could be used to guide the development and choice of e-learning at all levels of education and training, and that could be implemented in a simple manner. A set of…

Preparing for the Worst: Psychological Excellence of First Responders - A Katrina Lessons Learned Study

DTIC Science & Technology

2008-01-01

cases on human cognition and performance. For instance, when you learn to fly an airplane, you will be instructed to use a simple rule to avoid...Existing Training Technologies; First Responders; Katrina; Lesson Learned 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER... student . Based in Maryland, the training institute prepares first responders using online learning courses or training exercises. Such topics

Learning Humanoid Arm Gestures

DTIC Science & Technology

2005-01-01

for a visual target with some accuracy ( Marjanovic , learning new gestures. Scassellati, and Williamson, 1996), this simple spring law system has some...coefficients of the reactions established in Marjanovic , M., Scassellati, B. and Williamson, M. 1996. meso. Other long-term metabolic changes could

Instant transformation of learned repulsion into motivational "wanting".

PubMed

Robinson, Mike J F; Berridge, Kent C

2013-02-18

Learned cues for pleasant reward often elicit desire, which, in addicts, may become compulsive. According to the dominant view in addiction neuroscience and reinforcement modeling, such desires are the simple products of learning, coming from a past association with reward outcome. We demonstrate that cravings are more than merely the products of accumulated pleasure memories-even a repulsive learned cue for unpleasantness can become suddenly desired via the activation of mesocorticolimbic circuitry. Rats learned repulsion toward a Pavlovian cue (a briefly-inserted metal lever) that always predicted an unpleasant Dead Sea saltiness sensation. Yet, upon first reencounter in a novel sodium-depletion state to promote mesocorticolimbic reactivity (reflected by elevated Fos activation in ventral tegmentum, nucleus accumbens, ventral pallidum, and the orbitofrontal prefrontal cortex), the learned cue was instantly transformed into an attractive and powerful motivational magnet. Rats jumped and gnawed on the suddenly attractive Pavlovian lever cue, despite never having tasted intense saltiness as anything other than disgusting. Instant desire transformation of a learned cue contradicts views that Pavlovian desires are essentially based on previously learned values (e.g., prediction error or temporal difference models). Instead desire is recomputed at reencounter by integrating Pavlovian information with the current brain/physiological state. This powerful brain transformation reverses strong learned revulsion into avid attraction. When applied to addiction, related mesocorticolimbic transformations (e.g., drugs or neural sensitization) of cues for already-pleasant drug experiences could create even more intense cravings. This cue/state transformation helps define what it means to say that addiction hijacks brain limbic circuits of natural reward. Copyright © 2013 Elsevier Ltd. All rights reserved.

Learning Problem-Solving Rules as Search through a Hypothesis Space

ERIC Educational Resources Information Center

Lee, Hee Seung; Betts, Shawn; Anderson, John R.

2016-01-01

Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem…

Research Says / Tap ELLs' Strengths to Spur Success

ERIC Educational Resources Information Center

Goodwin, Bryan; Hein, Heather

2016-01-01

On the surface, learning a second language may seem to be a simple one- to two-year undertaking. Research shows, however, that it's a far more complex endeavor. This article considers the depth of learning required to become academically proficient in a second language. For instance, language learners learn the basics of reading in a second…

Modularization and Structured Markup for Learning Content in an Academic Environment

ERIC Educational Resources Information Center

Schluep, Samuel; Bettoni, Marco; Schar, Sissel Guttormsen

2006-01-01

This article aims to present a flexible component model for modular, web-based learning content, and a simple structured markup schema for the separation of content and presentation. The article will also contain an overview of the dynamic Learning Content Management System (dLCMS) project, which implements these concepts. Content authors are a…

Antecedents of Employees' Involvement in Work-Related Learning: A Systematic Review

ERIC Educational Resources Information Center

Kyndt, Eva; Baert, Herman

2013-01-01

Involvement in work-related learning seems to be more complex than a simple supply-demand fit. An interplay of several factors can influence this involvement at different stages of the decision-making process of the employee. The aim of this systematic review is to examine which antecedents of work-related learning have been identified in previous…

Does Sleep Facilitate the Consolidation of Allocentric or Egocentric Representations of Implicitly Learned Visual-Motor Sequence Learning?

ERIC Educational Resources Information Center

Viczko, Jeremy; Sergeeva, Valya; Ray, Laura B.; Owen, Adrian M.; Fogel, Stuart M.

2018-01-01

Sleep facilitates the consolidation (i.e., enhancement) of simple, explicit (i.e., conscious) motor sequence learning (MSL). MSL can be dissociated into egocentric (i.e., motor) or allocentric (i.e., spatial) frames of reference. The consolidation of the allocentric memory representation is sleep-dependent, whereas the egocentric consolidation…

Observational Learning in Mice Can Be Prevented by Medial Prefrontal Cortex Stimulation and Enhanced by Nucleus Accumbens Stimulation

ERIC Educational Resources Information Center

Jurado-Parras, M. Teresa; Gruart, Agnes; Delgado-Garcia, Jose M.

2012-01-01

The neural structures involved in ongoing appetitive and/or observational learning behaviors remain largely unknown. Operant conditioning and observational learning were evoked and recorded in a modified Skinner box provided with an on-line video recording system. Mice improved their acquisition of a simple operant conditioning task by…

The Ghost in the Machine: Are "Teacherless" CALL Programs Really Possible?

ERIC Educational Resources Information Center

Davies, Ted; Williamson, Rodney

1998-01-01

Reflects critically on pedagogical issues in the production of computer-assisted language learning (CALL) courseware and ways CALL has affected the practice of language learning. Concludes that if CALL is to reach full potential, it must be more than a simple medium of information; it should provide a teaching/learning process, with the real…

Learning in tele-autonomous systems using Soar

NASA Technical Reports Server (NTRS)

Laird, John E.; Yager, Eric S.; Tuck, Christopher M.; Hucka, Michael

1989-01-01

Robo-Soar is a high-level robot arm control system implemented in Soar. Robo-Soar learns to perform simple block manipulation tasks using advice from a human. Following learning, the system is able to perform similar tasks without external guidance. It can also learn to correct its knowledge, using its own problem solving in addition to outside guidance. Robo-Soar corrects its knowledge by accepting advice about relevance of features in its domain, using a unique integration of analytic and empirical learning techniques.

Introducing Stereochemistry to Non-science Majors

NASA Astrophysics Data System (ADS)

Luján-Upton, Hannia

2001-04-01

Stereochemistry is often a difficult topic for both science and non-science majors to learn. The topics covered in most undergraduate textbooks, although fundamental, seem very abstract to most students. This manuscript describes two simple exercises that can be used to introduce concepts associated with stereochemistry such as "sameness", superimposability, chirality, enantiomers, optical activity, polarimetry, and racemic mixtures. One exercise compares chirality in hands with the achiral nature of two textbooks. The other exercise involves a murder mystery, the solution of which hinges upon understanding the concept of optical activity, specifically in natural products such as toxins from poisonous mushrooms.

Integrating the behavioral and neural dynamics of response selection in a dual-task paradigm: a dynamic neural field model of Dux et al. (2009).

PubMed

Buss, Aaron T; Wifall, Tim; Hazeltine, Eliot; Spencer, John P

2014-02-01

People are typically slower when executing two tasks than when only performing a single task. These dual-task costs are initially robust but are reduced with practice. Dux et al. (2009) explored the neural basis of dual-task costs and learning using fMRI. Inferior frontal junction (IFJ) showed a larger hemodynamic response on dual-task trials compared with single-task trial early in learning. As dual-task costs were eliminated, dual-task hemodynamics in IFJ reduced to single-task levels. Dux and colleagues concluded that the reduction of dual-task costs is accomplished through increased efficiency of information processing in IFJ. We present a dynamic field theory of response selection that addresses two questions regarding these results. First, what mechanism leads to the reduction of dual-task costs and associated changes in hemodynamics? We show that a simple Hebbian learning mechanism is able to capture the quantitative details of learning at both the behavioral and neural levels. Second, is efficiency isolated to cognitive control areas such as IFJ, or is it also evident in sensory motor areas? To investigate this, we restrict Hebbian learning to different parts of the neural model. None of the restricted learning models showed the same reductions in dual-task costs as the unrestricted learning model, suggesting that efficiency is distributed across cognitive control and sensory motor processing systems.

An Experiment in Programmed Learning in Physical Chemistry for Metallurgists.

ERIC Educational Resources Information Center

Hinchliffe, Philip R.

1982-01-01

Substantially self-paced programed learning at Sheffield City Polytechnic Metallurgy Department was found to be better than conventional lectures, provided that new topic areas covered were relatively small, as demonstrated by using inexpensive, simple instructional materials. (Author/JN)

Measuring CO[subscript 2

ERIC Educational Resources Information Center

Taterka, Bruce; Cory, Rose M.

2016-01-01

This article presents simple tools and concepts to engage students in inquiry-based learning about the carbon cycle, thawing permafrost, and climate change. The lessons focus on learning in Earth science, environmental science, chemistry, and biology and align with the "Next Generation Science Standards".

Neural substrates underlying stimulation-enhanced motor skill learning after stroke

PubMed Central

Lefebvre, Stéphanie; Dricot, Laurence; Laloux, Patrice; Gradkowski, Wojciech; Desfontaines, Philippe; Evrard, Frédéric; Peeters, André; Jamart, Jacques

2015-01-01

Motor skill learning is one of the key components of motor function recovery after stroke, especially recovery driven by neurorehabilitation. Transcranial direct current stimulation can enhance neurorehabilitation and motor skill learning in stroke patients. However, the neural mechanisms underlying the retention of stimulation-enhanced motor skill learning involving a paretic upper limb have not been resolved. These neural substrates were explored by means of functional magnetic resonance imaging. Nineteen chronic hemiparetic stroke patients participated in a double-blind, cross-over randomized, sham-controlled experiment with two series. Each series consisted of two sessions: (i) an intervention session during which dual transcranial direct current stimulation or sham was applied during motor skill learning with the paretic upper limb; and (ii) an imaging session 1 week later, during which the patients performed the learned motor skill. The motor skill learning task, called the ‘circuit game’, involves a speed/accuracy trade-off and consists of moving a pointer controlled by a computer mouse along a complex circuit as quickly and accurately as possible. Relative to the sham series, dual transcranial direct current stimulation applied bilaterally over the primary motor cortex during motor skill learning with the paretic upper limb resulted in (i) enhanced online motor skill learning; (ii) enhanced 1-week retention; and (iii) superior transfer of performance improvement to an untrained task. The 1-week retention’s enhancement driven by the intervention was associated with a trend towards normalization of the brain activation pattern during performance of the learned motor skill relative to the sham series. A similar trend towards normalization relative to sham was observed during performance of a simple, untrained task without a speed/accuracy constraint, despite a lack of behavioural difference between the dual transcranial direct current stimulation and sham series. Finally, dual transcranial direct current stimulation applied during the first session enhanced continued learning with the paretic limb 1 week later, relative to the sham series. This lasting behavioural enhancement was associated with more efficient recruitment of the motor skill learning network, that is, focused activation on the motor-premotor areas in the damaged hemisphere, especially on the dorsal premotor cortex. Dual transcranial direct current stimulation applied during motor skill learning with a paretic upper limb resulted in prolonged shaping of brain activation, which supported behavioural enhancements in stroke patients. PMID:25488186

Compressive Hyperspectral Imaging and Anomaly Detection

DTIC Science & Technology

2010-02-01

Level Set Systems 1058 Embury Street Pacific Palisades , CA 90272 8. PERFORMING ORGANIZATION REPORT NUMBER 1A-2010 9. SPONSORING/MONITORING...were obtained from a simple algorithm, namely, the atoms in the trained image were very similar to the simple cell receptive fields in early vision...Field, "Emergence of simple- cell receptive field properties by learning a sparse code for natural images,’" Nature 381(6583), pp. 607-609, 1996. M

Engineering Design Theory: Applying the Success of the Modern World to Campaign Creation

DTIC Science & Technology

2009-05-21

and school of thought) to the simple methods of design.6 This progression is analogous to Peter Senge’s levels of learning disciplines.7 Senge...iterative learning and adaptive action that develops and employs critical and creative thinking , enabling leaders to apply the necessary logic to...overcome mental rigidity and develop group insight, the Army must learn to utilize group learning and thinking , through a fluid and creative open process

Learning through Play for School Readiness: A Training Program for Parents and Other Caregivers of Preschool Children. Learning Games To Strengthen Children's School Readiness Skills. [Videotape with Facilitator's Manual].

ERIC Educational Resources Information Center

Singer, Jerome; Singer, Dorothy

This video-based program trains parents and other child caregivers to engage 3- to 5-year-olds in simple, motivating learning games to strengthen cognitive, social, and motor school-readiness skills. The training materials consist of a manual for training facilitators and a training video demonstrating how to play each learning game with preschool…

Expectancy-related changes in firing of dopamine neurons depend on orbitofrontal cortex.

PubMed

Takahashi, Yuji K; Roesch, Matthew R; Wilson, Robert C; Toreson, Kathy; O'Donnell, Patricio; Niv, Yael; Schoenbaum, Geoffrey

2011-10-30

The orbitofrontal cortex has been hypothesized to carry information regarding the value of expected rewards. Such information is essential for associative learning, which relies on comparisons between expected and obtained reward for generating instructive error signals. These error signals are thought to be conveyed by dopamine neurons. To test whether orbitofrontal cortex contributes to these error signals, we recorded from dopamine neurons in orbitofrontal-lesioned rats performing a reward learning task. Lesions caused marked changes in dopaminergic error signaling. However, the effect of lesions was not consistent with a simple loss of information regarding expected value. Instead, without orbitofrontal input, dopaminergic error signals failed to reflect internal information about the impending response that distinguished externally similar states leading to differently valued future rewards. These results are consistent with current conceptualizations of orbitofrontal cortex as supporting model-based behavior and suggest an unexpected role for this information in dopaminergic error signaling.

Hooke's law: applications of a recurring principle.

PubMed

Giuliodori, Mauricio J; Lujan, Heidi L; Briggs, Whitney S; Palani, Gurunanthan; DiCarlo, Stephen E

2009-12-01

Students generally approach topics in physiology as a series of unrelated phenomena that share few underlying principles. However, if students recognized that the same underlying principles can be used to explain many physiological phenomena, they may gain a more unified understanding of physiological systems. To address this concern, we developed a simple, inexpensive, and easy to build model to demonstrate the underlying principles regarding Starling's Law of the Heart as well as lung and arterial elastic recoil. A model was chosen because models significantly enhance student understanding. Working with models also encourages research-oriented learning and helps our students understand complex ideas. Students are drawn into discussion by the power of learning that is associated with manipulating and thinking about objects. Recognizing that the same underlying principles can be used to explain many physiological phenomena may help students gain a more complete understanding of physiological systems.

Learning a locomotor task: with or without errors?

PubMed

Marchal-Crespo, Laura; Schneider, Jasmin; Jaeger, Lukas; Riener, Robert

2014-03-04

Robotic haptic guidance is the most commonly used robotic training strategy to reduce performance errors while training. However, research on motor learning has emphasized that errors are a fundamental neural signal that drive motor adaptation. Thus, researchers have proposed robotic therapy algorithms that amplify movement errors rather than decrease them. However, to date, no study has analyzed with precision which training strategy is the most appropriate to learn an especially simple task. In this study, the impact of robotic training strategies that amplify or reduce errors on muscle activation and motor learning of a simple locomotor task was investigated in twenty two healthy subjects. The experiment was conducted with the MAgnetic Resonance COmpatible Stepper (MARCOS) a special robotic device developed for investigations in the MR scanner. The robot moved the dominant leg passively and the subject was requested to actively synchronize the non-dominant leg to achieve an alternating stepping-like movement. Learning with four different training strategies that reduce or amplify errors was evaluated: (i) Haptic guidance: errors were eliminated by passively moving the limbs, (ii) No guidance: no robot disturbances were presented, (iii) Error amplification: existing errors were amplified with repulsive forces, (iv) Noise disturbance: errors were evoked intentionally with a randomly-varying force disturbance on top of the no guidance strategy. Additionally, the activation of four lower limb muscles was measured by the means of surface electromyography (EMG). Strategies that reduce or do not amplify errors limit muscle activation during training and result in poor learning gains. Adding random disturbing forces during training seems to increase attention, and therefore improve motor learning. Error amplification seems to be the most suitable strategy for initially less skilled subjects, perhaps because subjects could better detect their errors and correct them. Error strategies have a great potential to evoke higher muscle activation and provoke better motor learning of simple tasks. Neuroimaging evaluation of brain regions involved in learning can provide valuable information on observed behavioral outcomes related to learning processes. The impacts of these strategies on neurological patients need further investigations.

Generative Models in Deep Learning: Constraints for Galaxy Evolution

NASA Astrophysics Data System (ADS)

Turp, Maximilian Dennis; Schawinski, Kevin; Zhang, Ce; Weigel, Anna K.

2018-01-01

New techniques are essential to make advances in the field of galaxy evolution. Recent developments in the field of artificial intelligence and machine learning have proven that these tools can be applied to problems far more complex than simple image recognition. We use these purely data driven approaches to investigate the process of star formation quenching. We show that Variational Autoencoders provide a powerful method to forward model the process of galaxy quenching. Our results imply that simple changes in specific star formation rate and bulge to disk ratio cannot fully describe the properties of the quenched population.

The cerebellum for jocks and nerds alike.

PubMed

Popa, Laurentiu S; Hewitt, Angela L; Ebner, Timothy J

2014-01-01

Historically the cerebellum has been implicated in the control of movement. However, the cerebellum's role in non-motor functions, including cognitive and emotional processes, has also received increasing attention. Starting from the premise that the uniform architecture of the cerebellum underlies a common mode of information processing, this review examines recent electrophysiological findings on the motor signals encoded in the cerebellar cortex and then relates these signals to observations in the non-motor domain. Simple spike firing of individual Purkinje cells encodes performance errors, both predicting upcoming errors as well as providing feedback about those errors. Further, this dual temporal encoding of prediction and feedback involves a change in the sign of the simple spike modulation. Therefore, Purkinje cell simple spike firing both predicts and responds to feedback about a specific parameter, consistent with computing sensory prediction errors in which the predictions about the consequences of a motor command are compared with the feedback resulting from the motor command execution. These new findings are in contrast with the historical view that complex spikes encode errors. Evaluation of the kinematic coding in the simple spike discharge shows the same dual temporal encoding, suggesting this is a common mode of signal processing in the cerebellar cortex. Decoding analyses show the considerable accuracy of the predictions provided by Purkinje cells across a range of times. Further, individual Purkinje cells encode linearly and independently a multitude of signals, both kinematic and performance errors. Therefore, the cerebellar cortex's capacity to make associations across different sensory, motor and non-motor signals is large. The results from studying how Purkinje cells encode movement signals suggest that the cerebellar cortex circuitry can support associative learning, sequencing, working memory, and forward internal models in non-motor domains.

The cerebellum for jocks and nerds alike

PubMed Central

Popa, Laurentiu S.; Hewitt, Angela L.; Ebner, Timothy J.

2014-01-01

Historically the cerebellum has been implicated in the control of movement. However, the cerebellum's role in non-motor functions, including cognitive and emotional processes, has also received increasing attention. Starting from the premise that the uniform architecture of the cerebellum underlies a common mode of information processing, this review examines recent electrophysiological findings on the motor signals encoded in the cerebellar cortex and then relates these signals to observations in the non-motor domain. Simple spike firing of individual Purkinje cells encodes performance errors, both predicting upcoming errors as well as providing feedback about those errors. Further, this dual temporal encoding of prediction and feedback involves a change in the sign of the simple spike modulation. Therefore, Purkinje cell simple spike firing both predicts and responds to feedback about a specific parameter, consistent with computing sensory prediction errors in which the predictions about the consequences of a motor command are compared with the feedback resulting from the motor command execution. These new findings are in contrast with the historical view that complex spikes encode errors. Evaluation of the kinematic coding in the simple spike discharge shows the same dual temporal encoding, suggesting this is a common mode of signal processing in the cerebellar cortex. Decoding analyses show the considerable accuracy of the predictions provided by Purkinje cells across a range of times. Further, individual Purkinje cells encode linearly and independently a multitude of signals, both kinematic and performance errors. Therefore, the cerebellar cortex's capacity to make associations across different sensory, motor and non-motor signals is large. The results from studying how Purkinje cells encode movement signals suggest that the cerebellar cortex circuitry can support associative learning, sequencing, working memory, and forward internal models in non-motor domains. PMID:24987338

A Phenomenology Study of First-Year Teachers Looking at the Shared Lived Experience of Learning to Grade

ERIC Educational Resources Information Center

Yost, Brandon Lee

2015-01-01

This study describes the phenomenon of how first-year teachers learn to evaluate students learning by (letter) grades. Grades seem simple enough; but in reality, each grade carries serious consequences with it--for either good or bad. For example, grades affect benefits/consequences at home; they affect placement in remedial or advanced courses;…

A Learning Center on the Lever for Young Children.

ERIC Educational Resources Information Center

Keislar, Evan R.; Luckenbill, Maryann

This document describes a project designed to explore the possibilities of children's learning in mechanics. The principle of the lever, one example of a simple machine, was used in the form of a balance toy. The apparatus was set up as a game in a specially devised learning center. The children made non-verbal predictions as to which way the bar…

Guiding Students to the Right Questions: Adaptive Navigation Support in an E-Learning System for Java Programming

ERIC Educational Resources Information Center

Hsiao, I.-H.; Sosnovsky, S.; Brusilovsky, P.

2010-01-01

Rapid growth of the volume of interactive questions available to the students of modern E-Learning courses placed the problem of personalized guidance on the agenda of E-Learning researchers. Without proper guidance, students frequently select too simple or too complicated problems and ended either bored or discouraged. This paper explores a…

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…

Fracturing Opportunity: Mexican Migrant Students and College-Going Literacy. Counterpoints: Studies in the Postmodern Theory of Education. Volume 362

ERIC Educational Resources Information Center

Gildersleeve, R. Evely

2010-01-01

"Fracturing Opportunity" demonstrates a simple yet profound idea--that educational opportunity is learned. And if it is learned, then it can be taught and taught more equitably. This book brings sociocultural theories of learning and development to bear on the persistent problems of inequality in college access, and presents an innovative…

The Role of Bottom-Up Processing in Perceptual Categorization by 3- to 4-Month-Old Infants: Simulations and Data

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…

"Cast Your Net Widely": Three Steps to Expanding and Refining Your Problem before Action Learning Application

ERIC Educational Resources Information Center

Reese, Simon R.

2015-01-01

This paper reflects upon a three-step process to expand the problem definition in the early stages of an action learning project. The process created a community-powered problem-solving approach within the action learning context. The simple three steps expanded upon in the paper create independence, dependence, and inter-dependence to aid the…

Teaching about Complex Systems Is No Simple Matter: Building Effective Professional Development for Computer-Supported Complex Systems Instruction

ERIC Educational Resources Information Center

Yoon, Susan A.; Anderson, Emma; Koehler-Yom, Jessica; Evans, Chad; Park, Miyoung; Sheldon, Josh; Schoenfeld, Ilana; Wendel, Daniel; Scheintaub, Hal; Klopfer, Eric

2017-01-01

The recent next generation science standards in the United States have emphasized learning about complex systems as a core feature of science learning. Over the past 15 years, a number of educational tools and theories have been investigated to help students learn about complex systems; but surprisingly, little research has been devoted to…

Baby and Toddler Learning Fun: 50 Interactive and Developmental Activities To Enjoy with Your Child.

ERIC Educational Resources Information Center

Goldberg, Sally

Based on the view that almost every interaction a parent has with an infant is an opportunity to help the baby learn more about the world, this book provides parents with simple and effective ways to enrich their infant's environment and to boost their childs language, motor, and social skills. Introductory remarks describe the learning areas…

Perception-action map learning in controlled multiscroll systems applied to robot navigation.

PubMed

Arena, Paolo; De Fiore, Sebastiano; Fortuna, Luigi; Patané, Luca

2008-12-01

In this paper a new technique for action-oriented perception in robots is presented. The paper starts from exploiting the successful implementation of the basic idea that perceptual states can be embedded into chaotic attractors whose dynamical evolution can be associated with sensorial stimuli. In this way, it can be possible to encode, into the chaotic dynamics, environment-dependent patterns. These have to be suitably linked to an action, executed by the robot, to fulfill an assigned mission. This task is addressed here: the action-oriented perception loop is closed by introducing a simple unsupervised learning stage, implemented via a bio-inspired structure based on the motor map paradigm. In this way, perceptual meanings, useful for solving a given task, can be autonomously learned, based on the environment-dependent patterns embedded into the controlled chaotic dynamics. The presented framework has been tested on a simulated robot and the performance have been successfully compared with other traditional navigation control paradigms. Moreover an implementation of the proposed architecture on a Field Programmable Gate Array is briefly outlined and preliminary experimental results on a roving robot are also reported.

Modeled changes of cerebellar activity in mutant mice are predictive of their learning impairments

NASA Astrophysics Data System (ADS)

Badura, Aleksandra; Clopath, Claudia; Schonewille, Martijn; de Zeeuw, Chris I.

2016-11-01

Translating neuronal activity to measurable behavioral changes has been a long-standing goal of systems neuroscience. Recently, we have developed a model of phase-reversal learning of the vestibulo-ocular reflex, a well-established, cerebellar-dependent task. The model, comprising both the cerebellar cortex and vestibular nuclei, reproduces behavioral data and accounts for the changes in neural activity during learning in wild type mice. Here, we used our model to predict Purkinje cell spiking as well as behavior before and after learning of five different lines of mutant mice with distinct cell-specific alterations of the cerebellar cortical circuitry. We tested these predictions by obtaining electrophysiological data depicting changes in neuronal spiking. We show that our data is largely consistent with the model predictions for simple spike modulation of Purkinje cells and concomitant behavioral learning in four of the mutants. In addition, our model accurately predicts a shift in simple spike activity in a mutant mouse with a brainstem specific mutation. This combination of electrophysiological and computational techniques opens a possibility of predicting behavioral impairments from neural activity.

Modeled changes of cerebellar activity in mutant mice are predictive of their learning impairments

PubMed Central

Badura, Aleksandra; Clopath, Claudia; Schonewille, Martijn; De Zeeuw, Chris I.

2016-01-01

Translating neuronal activity to measurable behavioral changes has been a long-standing goal of systems neuroscience. Recently, we have developed a model of phase-reversal learning of the vestibulo-ocular reflex, a well-established, cerebellar-dependent task. The model, comprising both the cerebellar cortex and vestibular nuclei, reproduces behavioral data and accounts for the changes in neural activity during learning in wild type mice. Here, we used our model to predict Purkinje cell spiking as well as behavior before and after learning of five different lines of mutant mice with distinct cell-specific alterations of the cerebellar cortical circuitry. We tested these predictions by obtaining electrophysiological data depicting changes in neuronal spiking. We show that our data is largely consistent with the model predictions for simple spike modulation of Purkinje cells and concomitant behavioral learning in four of the mutants. In addition, our model accurately predicts a shift in simple spike activity in a mutant mouse with a brainstem specific mutation. This combination of electrophysiological and computational techniques opens a possibility of predicting behavioral impairments from neural activity. PMID:27805050

Learned helplessness and learned prevalence: exploring the causal relations among perceived controllability, reward prevalence, and exploration.

PubMed

Teodorescu, Kinneret; Erev, Ido

2014-10-01

Exposure to uncontrollable outcomes has been found to trigger learned helplessness, a state in which the agent, because of lack of exploration, fails to take advantage of regained control. Although the implications of this phenomenon have been widely studied, its underlying cause remains undetermined. One can learn not to explore because the environment is uncontrollable, because the average reinforcement for exploring is low, or because rewards for exploring are rare. In the current research, we tested a simple experimental paradigm that contrasts the predictions of these three contributors and offers a unified psychological mechanism that underlies the observed phenomena. Our results demonstrate that learned helplessness is not correlated with either the perceived controllability of one's environment or the average reward, which suggests that reward prevalence is a better predictor of exploratory behavior than the other two factors. A simple computational model in which exploration decisions were based on small samples of past experiences captured the empirical phenomena while also providing a cognitive basis for feelings of uncontrollability. © The Author(s) 2014.

Traveling with Science

ERIC Educational Resources Information Center

Fast, Danene; Wild, Tiffany

2018-01-01

For early elementary students with vision loss, these seemingly simple questions can pose great difficulty, especially when conceptual development is being established. Because students with vision loss are unable to observe non-verbal cues within environmental settings, supplemental learning techniques must be utilized for learning. In science,…

Task complexity, student perceptions of vocabulary learning in EFL, and task performance.

PubMed

Wu, Xiaoli; Lowyck, Joost; Sercu, Lies; Elen, Jan

2013-03-01

The study deepened our understanding of how students' self-efficacy beliefs contribute to the context of teaching English as a foreign language in the framework of cognitive mediational paradigm at a fine-tuned task-specific level. The aim was to examine the relationship among task complexity, self-efficacy beliefs, domain-related prior knowledge, learning strategy use, and task performance as they were applied to English vocabulary learning from reading tasks. Participants were 120 second-year university students (mean age 21) from a Chinese university. This experiment had two conditions (simple/complex). A vocabulary level test was first conducted to measure participants' prior knowledge of English vocabulary. Participants were then randomly assigned to one of the learning tasks. Participants were administered task booklets together with the self-efficacy scales, measures of learning strategy use, and post-tests. Data obtained were submitted to multivariate analysis of variance (MANOVA) and path analysis. Results from the MANOVA model showed a significant effect of vocabulary level on self-efficacy beliefs, learning strategy use, and task performance. Task complexity showed no significant effect; however, an interaction effect between vocabulary level and task complexity emerged. Results from the path analysis showed self-efficacy beliefs had an indirect effect on performance. Our results highlighted the mediating role of self-efficacy beliefs and learning strategy use. Our findings indicate that students' prior knowledge plays a crucial role on both self-efficacy beliefs and task performance, and the predictive power of self-efficacy on task performance may lie in its association with learning strategy use. © 2011 The British Psychological Society.

Modulation of Complex-Spike Duration and Probability during Cerebellar Motor Learning in Visually Guided Smooth-Pursuit Eye Movements of Monkeys

PubMed Central

2017-01-01

Abstract Activation of an inferior olivary neuron powerfully excites Purkinje cells via its climbing fiber input and triggers a characteristic high-frequency burst, known as the complex spike (CS). The theory of cerebellar learning postulates that the CS induces long-lasting depression of the strength of synapses from active parallel fibers onto Purkinje cells, and that synaptic depression leads to changes in behavior. Prior reports showed that a CS on one learning trial is linked to a properly timed depression of simple spikes on the subsequent trial, as well as a learned change in pursuit eye movement. Further, the duration of a CS is a graded instruction for single-trial plasticity and behavioral learning. We now show across multiple learning paradigms that both the probability and duration of CS responses are correlated with the magnitudes of neural and behavioral learning in awake behaving monkeys. When the direction of the instruction for learning repeatedly was in the same direction or alternated directions, the duration and probability of CS responses decreased over a learning block along with the magnitude of trial-over-trial neural learning. When the direction of the instruction was randomized, CS duration, CS probability, and neural and behavioral learning remained stable across time. In contrast to depression, potentiation of simple-spike firing rate for ON-direction learning instructions follows a longer time course and plays a larger role as depression wanes. Computational analysis provides a model that accounts fully for the detailed statistics of a complex set of data. PMID:28698888

Trends in free WWW-based E-learning Modules seen from the Learning Resource Server Medicine (LRSMed).

PubMed

Stausberg, Jürgen; Geueke, Martin; Bludßat, Kevin

2005-01-01

Despite the lost enthusiasm concerning E-learning a lot of material is available on the World Wide Web (WWW) free of charge. This material is collected and systematically described by services like the Learning Resource Server Medicine (LRSMed) at http://mmedia.medizin.uni-essen.de/portal/. With the LRSMed E-learning modules are made available for medical students by means of a metadata description that can be used for a catalogue search. The number of resources included has risen enormously from 100 in 1999 up to 805 today. Especially in 2004 there was an exponential increase in the LRSMed's content. Anatomy is still the field with the highest amount of available material, but general medicine has improved its position over the years and is now the second one. Technically and didactically simple material as scripts, textbooks, and link lists (called info services) is still dominating. Similar to 1999, there is not one module which could be truly referred to as tutorial dialogue. Simple material can not replace face-to-face-teaching. But it could be combined with conventional courses to establish some kind of blending learning. The scene of free E-learning modules on the WWW is ready to meet current challenges for efficient training of students and continuing education in medicine.

Reading Aloud and Solving Simple Arithmetic Calculation Intervention (Learning Therapy) Improves Inhibition, Verbal Episodic Memory, Focus Attention and Processing Speed in Healthy Elderly People: Evidence from a Randomized Controlled Trial

PubMed Central

Nouchi, Rui; Taki, Yasuyuki; Takeuchi, Hikaru; Nozawa, Takayuki; Sekiguchi, Atsushi; Kawashima, Ryuta

2016-01-01

Background: Previous reports have described that simple cognitive training using reading aloud and solving simple arithmetic calculations, so-called “learning therapy”, can improve executive functions and processing speed in the older adults. Nevertheless, it is not well-known whether learning therapy improve a wide range of cognitive functions or not. We investigated the beneficial effects of learning therapy on various cognitive functions in healthy older adults. Methods: We used a single-blinded intervention with two groups (learning therapy group: LT and waiting list control group: WL). Sixty-four elderly were randomly assigned to LT or WL. In LT, participants performed reading Japanese aloud and solving simple calculations training tasks for 6 months. WL did not participate in the intervention. We measured several cognitive functions before and after 6 months intervention periods. Results: Compared to WL, results revealed that LT improved inhibition performance in executive functions (Stroop: LT (Mean = 3.88) vs. WL (Mean = 1.22), adjusted p = 0.013 and reverse Stroop LT (Mean = 3.22) vs. WL (Mean = 1.59), adjusted p = 0.015), verbal episodic memory (Logical Memory (LM): LT (Mean = 4.59) vs. WL (Mean = 2.47), adjusted p = 0.015), focus attention (D-CAT: LT (Mean = 2.09) vs. WL (Mean = −0.59), adjusted p = 0.010) and processing speed compared to the WL control group (digit symbol coding: LT (Mean = 5.00) vs. WL (Mean = 1.13), adjusted p = 0.015 and Symbol Search (SS): LT (Mean = 3.47) vs. WL (Mean = 1.81), adjusted p = 0.014). Discussion: This randomized controlled trial (RCT) can be showed the benefit of LT on inhibition of executive functions, verbal episodic memory, focus attention and processing speed in healthy elderly people. Our results were discussed under overlapping hypothesis. PMID:27242481

Reading Aloud and Solving Simple Arithmetic Calculation Intervention (Learning Therapy) Improves Inhibition, Verbal Episodic Memory, Focus Attention and Processing Speed in Healthy Elderly People: Evidence from a Randomized Controlled Trial.

PubMed

Nouchi, Rui; Taki, Yasuyuki; Takeuchi, Hikaru; Nozawa, Takayuki; Sekiguchi, Atsushi; Kawashima, Ryuta

2016-01-01

Previous reports have described that simple cognitive training using reading aloud and solving simple arithmetic calculations, so-called "learning therapy", can improve executive functions and processing speed in the older adults. Nevertheless, it is not well-known whether learning therapy improve a wide range of cognitive functions or not. We investigated the beneficial effects of learning therapy on various cognitive functions in healthy older adults. We used a single-blinded intervention with two groups (learning therapy group: LT and waiting list control group: WL). Sixty-four elderly were randomly assigned to LT or WL. In LT, participants performed reading Japanese aloud and solving simple calculations training tasks for 6 months. WL did not participate in the intervention. We measured several cognitive functions before and after 6 months intervention periods. Compared to WL, results revealed that LT improved inhibition performance in executive functions (Stroop: LT (Mean = 3.88) vs. WL (Mean = 1.22), adjusted p = 0.013 and reverse Stroop LT (Mean = 3.22) vs. WL (Mean = 1.59), adjusted p = 0.015), verbal episodic memory (Logical Memory (LM): LT (Mean = 4.59) vs. WL (Mean = 2.47), adjusted p = 0.015), focus attention (D-CAT: LT (Mean = 2.09) vs. WL (Mean = -0.59), adjusted p = 0.010) and processing speed compared to the WL control group (digit symbol coding: LT (Mean = 5.00) vs. WL (Mean = 1.13), adjusted p = 0.015 and Symbol Search (SS): LT (Mean = 3.47) vs. WL (Mean = 1.81), adjusted p = 0.014). This randomized controlled trial (RCT) can be showed the benefit of LT on inhibition of executive functions, verbal episodic memory, focus attention and processing speed in healthy elderly people. Our results were discussed under overlapping hypothesis.

Learning Simple Machines through Cross-Age Collaborations

ERIC Educational Resources Information Center

Lancor, Rachael; Schiebel, Amy

2008-01-01

In this project, introductory college physics students (noneducation majors) were asked to teach simple machines to a class of second graders. This nontraditional activity proved to be a successful way to encourage college students to think critically about physics and how it applied to their everyday lives. The noneducation majors benefited by…

Correcting the SIMPLE Model of Free Recall

ERIC Educational Resources Information Center

Lee, Michael D.; Pooley, James P.

2013-01-01

The scale-invariant memory, perception, and learning (SIMPLE) model developed by Brown, Neath, and Chater (2007) formalizes the theoretical idea that scale invariance is an important organizing principle across numerous cognitive domains and has made an influential contribution to the literature dealing with modeling human memory. In the context…

Using Algorithms in Solving Synapse Transmission Problems.

ERIC Educational Resources Information Center

Stencel, John E.

1992-01-01

Explains how a simple three-step algorithm can aid college students in solving synapse transmission problems. Reports that all of the students did not completely understand the algorithm. However, many learn a simple working model of synaptic transmission and understand why an impulse will pass across a synapse quantitatively. Students also see…

Gravity: Simple Experiments for Young Scientists.

ERIC Educational Resources Information Center

White, Larry

This book contains 12 simple experiments through which students can learn about gravity and its implications. Some of the topics included are weight, weightlessness, artificial gravity, the pull of gravity on different shapes, center of gravity, the universal law of gravity, and balancing. Experiments include: finding the balancing point; weighing…

Acquisition of Simple and Complex Knowledge; A Knowledge Gap Perspective

ERIC Educational Resources Information Center

Le Heron, Judy; Sligo, Frank

2005-01-01

This paper assesses university students' acquisition of simple and complex knowledge, in exploring whether the knowledge gap hypothesis (KGH) with its origins in community-based research into people's informal learning from mass media, provides insights into students' acquisition and retention of information. The KGH posits that attempts to…

Energy: Simple Experiments for Young Scientists.

ERIC Educational Resources Information Center

White, Larry

This book contains simple experiments through which students can learn about the properties of energy. These experiments include making a kitchen "volcano," a soda-pop "cannon," and a puffed-rice "scooter." Topics include: energy and work, fossil fuels, solar energy, kinetic energy, potential energy, mechanical energy, heat energy, sound energy,…

The Box-and-Dot Method: A Simple Strategy for Counting Significant Figures

NASA Astrophysics Data System (ADS)

Stephenson, W. Kirk

2009-08-01

A visual method for counting significant digits is presented. This easy-to-learn (and easy-to-teach) method, designated the box-and-dot method, uses the device of "boxing" significant figures based on two simple rules, then counting the number of digits in the boxes.

Institutional Effects in a Simple Model of Educational Production

ERIC Educational Resources Information Center

Bishop, John H.; Wobmann, Ludger

2004-01-01

This paper presents a model of educational production that tries to make sense of recent evidence on effects of institutional arrangements on student performance. In a simple principal-agent framework, students choose their learning effort to maximize their net benefits, while the government chooses educational spending to maximize its net…

Phonological Concept Learning.

PubMed

Moreton, Elliott; Pater, Joe; Pertsova, Katya

2017-01-01

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by the same models. We test GMECCS (Gradual Maximum Entropy with a Conjunctive Constraint Schema), an implementation of the Configural Cue Model (Gluck & Bower, ) in a Maximum Entropy phonotactic-learning framework (Goldwater & Johnson, ; Hayes & Wilson, ) with a single free parameter, against the alternative hypothesis that learners seek featurally simple algebraic rules ("rule-seeking"). We study the full typology of patterns introduced by Shepard, Hovland, and Jenkins () ("SHJ"), instantiated as both phonotactic patterns and visual analogs, using unsupervised training. Unlike SHJ, Experiments 1 and 2 found that both phonotactic and visual patterns that depended on fewer features could be more difficult than those that depended on more features, as predicted by GMECCS but not by rule-seeking. GMECCS also correctly predicted performance differences between stimulus subclasses within each pattern. A third experiment tried supervised training (which can facilitate rule-seeking in visual learning) to elicit simple rule-seeking phonotactic learning, but cue-based behavior persisted. We conclude that similar cue-based cognitive processes are available for phonological and visual concept learning, and hence that studying either kind of learning can lead to significant insights about the other. Copyright © 2015 Cognitive Science Society, Inc.

Extinction of Chained Instrumental Behaviors: Effects of Procurement Extinction on Consumption Responding

PubMed Central

Thrailkill, Eric A.; Bouton, Mark E.

2015-01-01

Instrumental behavior often consists of sequences or chains of responses that minimally include procurement behaviors that enable subsequent consumption behaviors. In such chains, behavioral units are linked by access to one another and eventually to a primary reinforcer, such as food or a drug. The present experiments examined the effects of extinguishing procurement responding on consumption responding after training of a discriminated heterogeneous instrumental chain. Rats learned to make a procurement response (e.g., pressing a lever) in the presence of a distinctive discriminative stimulus; making that response led to the presentation of a second discriminative stimulus that set the occasion for a consumption response (e.g., pulling a chain), which then produced a food-pellet reinforcer. Experiment 1 showed that extinction of either the full procurement-consumption chain or procurement alone weakened the consumption response tested in isolation. Experiment 2 replicated the procurement extinction effect and further demonstrated that the opportunity to make the procurement response, as opposed to simple exposure to the procurement stimulus alone, was required. In Experiment 3, rats learned 2 distinct discriminated heterogeneous chains; extinction of 1 procurement response specifically weakened the consumption response that had been associated with it. The results suggest that learning to inhibit the procurement response may produce extinction of consumption responding through mediated extinction. The experiments suggest the importance of an associative analysis of instrumental behavior chains. PMID:25915751

Demons of the Mind.

ERIC Educational Resources Information Center

Ivie, Stanley D.

1987-01-01

Analysis of the key educational concepts of behaviorism contrasts those concepts with parallel thoughts drawn from more humanistic educators and concludes that behaviorist psychology's attempts to reduce complex human learning to simple animal learning prevents educators from recognizing and helping humans to develop their unique inner resources.…

Forecasting: Exercises to Enhance Learning from Business Simulations

ERIC Educational Resources Information Center

Clark, Timothy S.; Kent, Brian M.

2013-01-01

Forecasting the outputs of dynamic systems develops a richer understanding of relevant inputs and their interrelationships than merely observing them ex post. Academic business simulations foster students' development of this critical competency, but learning outcomes can be significantly augmented with relatively simple, complementary exercises…

Eyes Closed for Learning

ERIC Educational Resources Information Center

Statham, Mick

2016-01-01

A constructivist philosophy underpinning science teaching and learning for over 100 years in United Kingdom (UK) classrooms places "conceptual change" at the heart of classroom work in which children's scientific ideas form, strengthen and change. In this article, the author explains how the simple, effective method of "eyes…

A new simple /spl infin/OH neuron model as a biologically plausible principal component analyzer.

PubMed

Jankovic, M V

2003-01-01

A new approach to unsupervised learning in a single-layer neural network is discussed. An algorithm for unsupervised learning based upon the Hebbian learning rule is presented. A simple neuron model is analyzed. A dynamic neural model, which contains both feed-forward and feedback connections between the input and the output, has been adopted. The, proposed learning algorithm could be more correctly named self-supervised rather than unsupervised. The solution proposed here is a modified Hebbian rule, in which the modification of the synaptic strength is proportional not to pre- and postsynaptic activity, but instead to the presynaptic and averaged value of postsynaptic activity. It is shown that the model neuron tends to extract the principal component from a stationary input vector sequence. Usually accepted additional decaying terms for the stabilization of the original Hebbian rule are avoided. Implementation of the basic Hebbian scheme would not lead to unrealistic growth of the synaptic strengths, thanks to the adopted network structure.

Classroom Activities: Simple Strategies to Incorporate Student-Centered Activities within Undergraduate Science Lectures

PubMed Central

Lom, Barbara

2012-01-01

The traditional science lecture, where an instructor delivers a carefully crafted monolog to a large audience of students who passively receive the information, has been a popular mode of instruction for centuries. Recent evidence on the science of teaching and learning indicates that learner-centered, active teaching strategies can be more effective learning tools than traditional lectures. Yet most colleges and universities retain lectures as their central instructional method. This article highlights several simple collaborative teaching techniques that can be readily deployed within traditional lecture frameworks to promote active learning. Specifically, this article briefly introduces the techniques of: reader’s theatre, think-pair-share, roundtable, jigsaw, in-class quizzes, and minute papers. Each technique is broadly applicable well beyond neuroscience courses and easily modifiable to serve an instructor’s specific pedagogical goals. The benefits of each technique are described along with specific examples of how each technique might be deployed within a traditional lecture to create more active learning experiences. PMID:23494568

The dynamic relationship between cerebellar Purkinje cell simple spikes and the spikelet number of complex spikes

PubMed Central

Burroughs, Amelia; Wise, Andrew K.; Xiao, Jianqiang; Houghton, Conor; Tang, Tianyu; Suh, Colleen Y.; Lang, Eric J.

2016-01-01

Key points Purkinje cells are the sole output of the cerebellar cortex and fire two distinct types of action potential: simple spikes and complex spikes.Previous studies have mainly considered complex spikes as unitary events, even though the waveform is composed of varying numbers of spikelets.The extent to which differences in spikelet number affect simple spike activity (and vice versa) remains unclear.We found that complex spikes with greater numbers of spikelets are preceded by higher simple spike firing rates but, following the complex spike, simple spikes are reduced in a manner that is graded with spikelet number.This dynamic interaction has important implications for cerebellar information processing, and suggests that complex spike spikelet number may maintain Purkinje cells within their operational range. Abstract Purkinje cells are central to cerebellar function because they form the sole output of the cerebellar cortex. They exhibit two distinct types of action potential: simple spikes and complex spikes. It is widely accepted that interaction between these two types of impulse is central to cerebellar cortical information processing. Previous investigations of the interactions between simple spikes and complex spikes have mainly considered complex spikes as unitary events. However, complex spikes are composed of an initial large spike followed by a number of secondary components, termed spikelets. The number of spikelets within individual complex spikes is highly variable and the extent to which differences in complex spike spikelet number affects simple spike activity (and vice versa) remains poorly understood. In anaesthetized adult rats, we have found that Purkinje cells recorded from the posterior lobe vermis and hemisphere have high simple spike firing frequencies that precede complex spikes with greater numbers of spikelets. This finding was also evident in a small sample of Purkinje cells recorded from the posterior lobe hemisphere in awake cats. In addition, complex spikes with a greater number of spikelets were associated with a subsequent reduction in simple spike firing rate. We therefore suggest that one important function of spikelets is the modulation of Purkinje cell simple spike firing frequency, which has implications for controlling cerebellar cortical output and motor learning. PMID:27265808

Low-level sensory plasticity during task-irrelevant perceptual learning: Evidence from conventional and double training procedures

PubMed Central

Pilly, Praveen K.; Grossberg, Stephen; Seitz, Aaron R.

2009-01-01

Studies of perceptual learning have focused on aspects of learning that are related to early stages of sensory processing. However, conclusions that perceptual learning results in low-level sensory plasticity are controversial, since such learning may also be attributed to plasticity in later stages of sensory processing or in readout from sensory to decision stages, or to changes in high-level central processing. To address this controversy, we developed a novel random dot motion (RDM) stimulus to target motion cells selective to contrast polarity by ensuring the motion direction information arises only from signal dot onsets and not their offsets, and used these stimuli in the paradigm of task-irrelevant perceptual learning (TIPL). In TIPL, learning is achieved in response to a stimulus by subliminally pairing that stimulus with the targets of an unrelated training task. In this manner, we are able to probe learning for an aspect of motion processing thought to be a function of directional V1 simple cells with a learning procedure that dissociates the learned stimulus from the decision processes relevant to the training task. Our results show direction-selective learning for the designated contrast polarity that does not transfer to the opposite contrast polarity. This polarity specificity was replicated in a double training procedure in which subjects were additionally exposed to the opposite polarity. Taken together, these results suggest that TIPL for motion stimuli may occur at the stage of directional V1 simple cells. Finally, a theoretical explanation is provided to understand the data. PMID:19800358

Project MAPP. The Vocabulary Booklet # 1. Implementing the Instructional Program: A Competency-Based Adult Education Learning System.

ERIC Educational Resources Information Center

Maryland State Dept. of Education, Baltimore.

This booklet is intended to help adults master the basic and life skill vocabulary needed to meet the simple communication demands of daily life. It is designed to assist adult basic education (ABE) teachers in the implementation of a competency-based learning system that emphasizes the integration of basic and life skills learning. The booklet…

Second Graders' Emerging Particle Models of Matter in the Context of Learning through Model-Based Inquiry

ERIC Educational Resources Information Center

Samarapungavan, Ala; Bryan, Lynn; Wills, Jamison

2017-01-01

In this paper, we present a study of second graders' learning about the nature of matter in the context of content-rich, model-based inquiry instruction. The goal of instruction was to help students learn to use simple particle models to explain states of matter and phase changes. We examined changes in students' ideas about matter, the coherence…

Pre-Service Elementary School Teachers' Ability to Account for the Operation of Simple Physical Systems Using the Energy Conservation Law

ERIC Educational Resources Information Center

Papadouris, Nicos; Hadjigeorgiou, Angela; Constantinou, Constantinos P.

2014-01-01

Energy is recognized as a core idea in science and, hence, a significant learning objective of science education. The effective promotion of this learning objective posits that teachers themselves possess sound conceptual understanding. This is needed for enabling them to organize effective learning environments for their students. In this study,…

Beneficial effects of reading aloud and solving simple arithmetic calculations (learning therapy) on a wide range of cognitive functions in the healthy elderly: study protocol for a randomized controlled trial

PubMed Central

2012-01-01

Background Almost all cognitive functions decline with age. Results of previous studies have shown that cognitive training related to everyday life (reading aloud and solving simple arithmetic calculations), namely learning therapy, can improve two cognitive function (executive functions and processing speed) in elderly people. However, it remains unclear whether learning therapy engenders improvement of various cognitive functions or not. We investigate the impact of learning therapy on various cognitive functions (executive functions, episodic memory, short-term memory, working memory, attention, reading ability, and processing speed) in healthy older adults. Methods We use a single-blinded intervention with two parallel groups (a learning therapy group and a waiting list control group). Testers are blind to the study hypothesis and the group membership of participants. Through an advertisement in local newspaper, 64 healthy older adults are recruited. They will be assigned randomly to a learning therapy group or a waiting list control group. In the learning therapy group, participants are required to perform two cognitive tasks for 6 months: reading Japanese aloud and solving simple calculations. The waiting list group does not participate in the intervention. The primary outcome measure is the Stroop test score: a measure of executive function. Secondary outcome measures are assessments including the following: verbal fluency task, logical memory, first and second names, digit span forward, digit span backward, Japanese reading test, digit cancellation task, digit symbol coding, and symbol search. We assess these outcome measures before and after the intervention. Discussion This report is the first study which investigates the beneficial effects of learning therapy on a wide range of cognitive functions of elderly people. Our study provides sufficient evidence of learning therapy effectiveness. Most cognitive functions, which are correlated strongly with daily life activities, decrease with age. These study results can elucidate effects of cognitive training on elderly people. Trial registration This trial was registered in The University Hospital Medical Information Network Clinical Trials Registry (No. UMIN000006998). PMID:22483196

Beneficial effects of reading aloud and solving simple arithmetic calculations (learning therapy) on a wide range of cognitive functions in the healthy elderly: study protocol for a randomized controlled trial.

PubMed

Nouchi, Rui; Taki, Yasuyuki; Takeuchi, Hikaru; Hashizume, Hiroshi; Nozawa, Takayuki; Sekiguchi, Atsushi; Nouchi, Haruka; Kawashima, Ryuta

2012-04-06

Almost all cognitive functions decline with age. Results of previous studies have shown that cognitive training related to everyday life (reading aloud and solving simple arithmetic calculations), namely learning therapy, can improve two cognitive function (executive functions and processing speed) in elderly people. However, it remains unclear whether learning therapy engenders improvement of various cognitive functions or not. We investigate the impact of learning therapy on various cognitive functions (executive functions, episodic memory, short-term memory, working memory, attention, reading ability, and processing speed) in healthy older adults. We use a single-blinded intervention with two parallel groups (a learning therapy group and a waiting list control group). Testers are blind to the study hypothesis and the group membership of participants. Through an advertisement in local newspaper, 64 healthy older adults are recruited. They will be assigned randomly to a learning therapy group or a waiting list control group. In the learning therapy group, participants are required to perform two cognitive tasks for 6 months: reading Japanese aloud and solving simple calculations. The waiting list group does not participate in the intervention. The primary outcome measure is the Stroop test score: a measure of executive function. Secondary outcome measures are assessments including the following: verbal fluency task, logical memory, first and second names, digit span forward, digit span backward, Japanese reading test, digit cancellation task, digit symbol coding, and symbol search. We assess these outcome measures before and after the intervention. This report is the first study which investigates the beneficial effects of learning therapy on a wide range of cognitive functions of elderly people. Our study provides sufficient evidence of learning therapy effectiveness. Most cognitive functions, which are correlated strongly with daily life activities, decrease with age. These study results can elucidate effects of cognitive training on elderly people. This trial was registered in The University Hospital Medical Information Network Clinical Trials Registry (No. UMIN000006998).

Retrieval practice as an effective memory strategy in children and adolescents with traumatic brain injury.

PubMed

Coyne, Julia H; Borg, Jacquelyn M; DeLuca, John; Glass, Leslie; Sumowski, James F

2015-04-01

To investigate whether retrieval practice (RP) is a more effective memory strategy than restudy in children and adolescents with traumatic brain injury (TBI). Three × two within-subjects experiment: 3 (learning condition: massed restudy [MR], spaced restudy [SR], retrieval practice [RP]) × 2 (stimulus type: verbal paired associates [VPAs] and face-name pairs [FNPs]). The dependent measure was delayed recall of VPAs and FNPs. Subacute pediatric neurorehabilitation center. Pediatric survivors of TBI (N=15) aged 8 to 16 years with below-average memory. During RP, participants were quizzed on to-be-learned information (VPAs and FNPs) shortly after it was presented, such that they practiced retrieval during the learning phase. MR consisted of repeated restudy (tantamount to cramming). SR consisted of restudy trials separated in time (ie, distributed learning). Delayed recall of 24 VPAs and 24 FNPs after a 25-minute delay. VPAs and FNPs were equally divided across 3 learning conditions (16 per condition). There was a large main effect of learning condition on delayed recall (P<.001; ηp(2)=.84), with better mean recall of VPAs and FNPs studied through RP (6.23±1.39) relative to MR (3.60±1.53; P<.001) and SR (4.77±1.39; P<.001). Moreover, RP was the single best learning strategy for every participant. Memory problems and related academic learning difficulties are common after pediatric TBI. Herein, we identify RP as a promising and simple strategy to support learning and improve memory in children and adolescents with TBI. Our experimental findings were quite robust and set the stage for subsequent randomized controlled trials of RP in pediatric TBI. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

The Effects of Sleep Deprivation on Dissociable Prototype Learning Systems

PubMed Central

Maddox, W. Todd; Glass, Brian D.; Zeithamova, Dagmar; Savarie, Zachary R.; Bowen, Christopher; Matthews, Michael D.; Schnyer, David M.

2011-01-01

Background: The cognitive neural underpinnings of prototype learning are becoming clear. Evidence points to 2 different neural systems, depending on the learning parameters. A/not-A (AN) prototype learning is mediated by posterior brain regions that are involved in early perceptual learning, whereas A/B (AB) is mediated by frontal and medial temporal lobe regions. Study Objectives: To investigate the effects of sleep deprivation on AN and AB prototype learning and to use established prototype models to provide insights into the cognitive-processing locus of sleep-deprivation deficits. Design: Participants performed an AN and an AB prototype learning task twice, separated by a 24-hour period, with or without sleep between testing sessions. Participants: Eighteen West Point cadets participated in the sleep-deprivation group, and 17 West Point cadets participated in a control group. Measurements and Results: Sleep deprivation led to an AN, but not an AB, performance deficit. Prototype model analyses indicated that the AN deficit was due to changes in attentional focus and a decrease in confidence that is reflected in an increased bias to respond non-A. Conclusions: The findings suggest that AN, but not AB, prototype learning is affected by sleep deprivation. Prototype model analyses support the notion that the effect of sleep deprivation on AN is consistent with lapses in attentional focus that are more detrimental to AN than to AB. This finding adds to a growing body of work that suggests that different performance changes associated with sleep deprivation can be attributed to a common mechanism of changes in simple attention and vigilance. Citation: Maddox WT; Glass BD; Zeithamova D; Savarie ZR; Bowen C; Matthews MD; Schnyer DM. The effects of sleep deprivation on dissociable prototype learning systems. SLEEP 2011;34(3):253-260. PMID:21358842

Learning to play the violin: motor control by freezing, not freeing degrees of freedom.

PubMed

Konczak, Jürgen; Vander Velden, Heidi; Jaeger, Lukas

2009-05-01

Playing a violin requires precise patterns of limb coordination that are acquired over years of practice. In the present study, the authors investigated how motion at proximal arm joints influenced the precision of bow movements in novice learners and experts. The authors evaluated the performances of 11 children (4-12 years old), 3 beginning-to-advanced level adult players, and 2 adult concert violinists, using a musical work that all had mastered as their first violin piece. The authors found that learning to play the violin was not associated with a release or freeing of joint degrees of freedom. Instead, learning was characterized by an experience-dependent suppression of sagittal shoulder motion, as documented by an observed reduction in joint angular amplitude. This reduction in the amplitude of shoulder flexion-extension correlated highly with a decrease of bow-movement variability. The remaining mechanical degrees of freedom at the elbow and shoulder showed patterns of neither suppression nor freeing. Only violinists with more than 700 practice hr achieved sagittal shoulder range of motion comparable to experts. The findings imply that restricting joint amplitude at selected joint degrees of freedom, while leaving other degrees of freedom unconstrained, constitutes an appropriate strategy for learning complex, high-precision motor patterns in children and adults. The findings also highlight that mastering even seemingly simple bowing movements constitutes a prolonged learning process.

The Simple Act of Choosing Influences Declarative Memory

PubMed Central

Murty, Vishnu P.; DuBrow, Sarah

2015-01-01

Individuals value the opportunity to make choices and exert control over their environment. This perceived sense of agency has been shown to have broad influences on cognition, including preference, decision-making, and valuation. However, it is unclear whether perceived control influences memory. Using a combined behavioral and functional magnetic resonance imaging approach, we investigated whether imbuing individuals with a sense of agency over their learning experience influences novel memory encoding. Participants encoded objects during a task that manipulated the opportunity to choose. Critically, unlike previous work on active learning, there was no relationship between individuals' choices and the content of memoranda. Despite this, we found that the opportunity to choose resulted in robust, reliable enhancements in declarative memory. Neuroimaging results revealed that anticipatory activation of the striatum, a region associated with decision-making, valuation, and exploration, correlated with choice-induced memory enhancements in behavior. These memory enhancements were further associated with interactions between the striatum and hippocampus. Specifically, anticipatory signals in the striatum when participants are alerted to the fact that they will have to choose one of two memoranda were associated with encoding success effects in the hippocampus on a trial-by-trial basis. The precedence of the striatal signal in these interactions suggests a modulatory relationship of the striatum over the hippocampus. These findings not only demonstrate enhanced declarative memory when individuals have perceived control over their learning but also support a novel mechanism by which these enhancements emerge. Furthermore, they demonstrate a novel context in which mesolimbic and declarative memory systems interact. PMID:25904779

The simple act of choosing influences declarative memory.

PubMed

Murty, Vishnu P; DuBrow, Sarah; Davachi, Lila

2015-04-22

Individuals value the opportunity to make choices and exert control over their environment. This perceived sense of agency has been shown to have broad influences on cognition, including preference, decision-making, and valuation. However, it is unclear whether perceived control influences memory. Using a combined behavioral and functional magnetic resonance imaging approach, we investigated whether imbuing individuals with a sense of agency over their learning experience influences novel memory encoding. Participants encoded objects during a task that manipulated the opportunity to choose. Critically, unlike previous work on active learning, there was no relationship between individuals' choices and the content of memoranda. Despite this, we found that the opportunity to choose resulted in robust, reliable enhancements in declarative memory. Neuroimaging results revealed that anticipatory activation of the striatum, a region associated with decision-making, valuation, and exploration, correlated with choice-induced memory enhancements in behavior. These memory enhancements were further associated with interactions between the striatum and hippocampus. Specifically, anticipatory signals in the striatum when participants are alerted to the fact that they will have to choose one of two memoranda were associated with encoding success effects in the hippocampus on a trial-by-trial basis. The precedence of the striatal signal in these interactions suggests a modulatory relationship of the striatum over the hippocampus. These findings not only demonstrate enhanced declarative memory when individuals have perceived control over their learning but also support a novel mechanism by which these enhancements emerge. Furthermore, they demonstrate a novel context in which mesolimbic and declarative memory systems interact. Copyright © 2015 the authors 0270-6474/15/356255-10$15.00/0.

Assessment under Resource Constraints

ERIC Educational Resources Information Center

Lovett, Steve; Curtis, Mary G.

2015-01-01

Assessment and the measurement of learning are receiving increasing emphasis in American higher education. This is a case study that demonstrates a simple, inexpensive method of measuring freshman to senior "gains" or learning using a cross-sectional methodology. Seniors and freshmen within a four-year business program were both given…

Active Learning Strategies for the Mathematics Classroom

ERIC Educational Resources Information Center

Kerrigan, John

2018-01-01

Active learning involves students engaging with course content beyond lecture: through writing, applets, simulations, games, and more (Prince, 2004). As mathematics is often viewed as a subject area that is taught using more traditional methods (Goldsmith & Mark, 1999), there are actually many simple ways to make undergraduate mathematics…

Information-Processing Correlates of Computer-Assisted Word Learning by Mentally Retarded Students.

ERIC Educational Resources Information Center

Conners, Frances A.; Detterman, Douglas K.

1987-01-01

Nineteen moderately/severely retarded students (ages 9-22) completed ten 15-minute computer-assisted instruction sessions and seven basic cognitive tasks measuring simple learning, choice reaction time, relearning, probed recall, stimulus discrimination, tachictoscopic threshold, and recognition memory. Stimulus discrimination, probed recall, and…

A VLSI recurrent network of integrate-and-fire neurons connected by plastic synapses with long-term memory.

PubMed

Chicca, E; Badoni, D; Dante, V; D'Andreagiovanni, M; Salina, G; Carota, L; Fusi, S; Del Giudice, P

2003-01-01

Electronic neuromorphic devices with on-chip, on-line learning should be able to modify quickly the synaptic couplings to acquire information about new patterns to be stored (synaptic plasticity) and, at the same time, preserve this information on very long time scales (synaptic stability). Here, we illustrate the electronic implementation of a simple solution to this stability-plasticity problem, recently proposed and studied in various contexts. It is based on the observation that reducing the analog depth of the synapses to the extreme (bistable synapses) does not necessarily disrupt the performance of the device as an associative memory, provided that 1) the number of neurons is large enough; 2) the transitions between stable synaptic states are stochastic; and 3) learning is slow. The drastic reduction of the analog depth of the synaptic variable also makes this solution appealing from the point of view of electronic implementation and offers a simple methodological alternative to the technological solution based on floating gates. We describe the full custom analog very large-scale integration (VLSI) realization of a small network of integrate-and-fire neurons connected by bistable deterministic plastic synapses which can implement the idea of stochastic learning. In the absence of stimuli, the memory is preserved indefinitely. During the stimulation the synapse undergoes quick temporary changes through the activities of the pre- and postsynaptic neurons; those changes stochastically result in a long-term modification of the synaptic efficacy. The intentionally disordered pattern of connectivity allows the system to generate a randomness suited to drive the stochastic selection mechanism. We check by a suitable stimulation protocol that the stochastic synaptic plasticity produces the expected pattern of potentiation and depression in the electronic network.

Changes in Simple Spike Activity of some Purkinje cells in the Oculomotor Vermis during Saccade Adaptation are Appropriate to Participate in Motor Learning

PubMed Central

Kojima, Yoshiko; Soetedjo, Robijanto; Fuchs, Albert F.

2010-01-01

Adaptation of saccadic eye movements provides an excellent motor learning model to study theories of neuronal plasticity. When primates make saccades to a jumping target, a backward step of the target during the saccade can make it appear to overshoot. If this deception continues for many trials, saccades gradually decrease in amplitude to go directly to the back-stepped target location. We used this adaptation paradigm to evaluate the Marr-Albus hypothesis that such motor learning occurs at the Purkinje (P-) cell of the cerebellum. We recorded the activity of identified P-cells in the oculomotor vermis, lobules VIc and VII. After determining the on and off error directions of a P-cell’s complex spike activity, we determined whether its saccade-related simple spike (SS) activity changed during saccade adaptation in those two directions. Before adaptation, 57 of 61 P-cells exhibited a clear burst, pause or a combination of both for saccades in one or both directions. Sixty-two percent of all cells, including 2 of the 4 initially unresponsive ones, behaved differently for saccades whose size changed because of adaptation than for saccades of similar sizes gathered before adaptation. In at least 42% of these, the changes were appropriate to decrease saccade amplitude based on our current knowledge of cerebellum and brain stem saccade circuitry. Changes in activity during adaptation were not compensating for the potential fatigue associated with performing many saccades. Therefore, many P-cells in the oculomotor vermis exhibit changes in SS activity specific to adapted saccades and therefore appropriate to induce adaptation. PMID:20220005

Multiple effects of circadian dysfunction induced by photoperiod shifts: alterations in context memory and food metabolism in the same subjects.

PubMed

McDonald, Robert J; Zelinski, Erin L; Keeley, Robin J; Sutherland, Dylan; Fehr, Leah; Hong, Nancy S

2013-06-13

Humans exposed to shiftwork conditions have been reported to have increased susceptibility to various health problems including various forms of dementia, cancer, heart disease, and metabolic disorders related to obesity. The present experiments assessed the effects of circadian disruption on learning and memory function and various food related processes including diet consumption rates, food metabolism, and changes in body weight. These experiments utilized a novel variant of the conditioned place preference task (CPP) that is normally used to assess Pavlovian associative learning and memory processes produced via repeated context-reward pairings. For the present experiments, the standard CPP paradigm was modified in that both contexts were paired with food, but the dietary constituents of the food were different. In particular, we were interested in whether rats could differentiate between two types of carbohydrates, simple (dextrose) and complex (starch). Consumption rates for each type of carbohydrate were measured throughout training. A test of context preference without the food present was also conducted. At the end of behavioral testing, a fasting glucose test and a glucose challenge test were administered. Chronic photoperiod shifting resulted in impaired context learning and memory processes thought to be mediated by a neural circuit centered on the hippocampus. The results also showed that preferences for the different carbohydrate diets were altered in rats experiencing photoperiod shifting in that they maintained an initial preference for the simple carbohydrate throughout training. Lastly, photoperiod shifting resulted in changes in fasting blood glucose levels and elicited weight gain. These results show that chronic photoperiod shifting, which likely resulted in circadian dysfunction, impairs multiple functions of the brain and/or body in the same individual. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

Water: Simple Experiments for Young Scientists.

ERIC Educational Resources Information Center

White, Larry

This book contains simple experiments and projects through which students can learn about water and its properties. Some of the topics discussed include acid rain, dehydration, distillation, electrons, tidal waves, and the water cycle. Experiments include: finding out about the amount of water in the body; why there is water in the body; how to…

Bootstrapping Cognition from Behavior--A Computerized Thought Experiment

ERIC Educational Resources Information Center

Moller, Ralf; Schenck, Wolfram

2008-01-01

We show that simple perceptual competences can emerge from an internal simulation of action effects and are thus grounded in behavior. A simulated agent learns to distinguish between dead ends and corridors without the necessity to represent these concepts in the sensory domain. Initially, the agent is only endowed with a simple value system and…

New From Online: Toying With Chemistry

ERIC Educational Resources Information Center

Harris, Julie; Kehoe, Steven

2005-01-01

Toys which can help to learn the basics and more in-depth chemistry concept are investigated and explained, which are also available online on the website. Some of the examples are simple LCD clock powered by citric acid of lemon, crystal radio made from simple household materials, firework, homemade snow globe, which explains the properties of…

The Box-and-Dot Method: A Simple Strategy for Counting Significant Figures

ERIC Educational Resources Information Center

Stephenson, W. Kirk

2009-01-01

A visual method for counting significant digits is presented. This easy-to-learn (and easy-to-teach) method, designated the box-and-dot method, uses the device of "boxing" significant figures based on two simple rules, then counting the number of digits in the boxes. (Contains 4 notes.)

Nature versus Nurture: The Simple Contrast

ERIC Educational Resources Information Center

Davidoff, Jules; Goldstein, Julie; Roberson, Debi

2009-01-01

We respond to the commentary of Franklin, Wright, and Davies ("Journal of Experimental Child Psychology, 102", 239-245 [2009]) by returning to the simple contrast between nature and nurture. We find no evidence from the toddler data that makes us revise our ideas that color categories are learned and never innate. (Contains 1 figure.)

Learning to Read: Should We Keep Things Simple?

ERIC Educational Resources Information Center

Reading Research Quarterly, 2015

2015-01-01

The simple view of reading describes reading comprehension as the product of decoding and listening comprehension and the relative contribution of each to reading comprehension across development. We present a cross-sectional analysis of first, second, and third graders (N = 123-125 in each grade) to assess the adequacy of the basic model.…

Simple modification of Oja rule limits L1-norm of weight vector and leads to sparse connectivity.

PubMed

Aparin, Vladimir

2012-03-01

This letter describes a simple modification of the Oja learning rule, which asymptotically constrains the L1-norm of an input weight vector instead of the L2-norm as in the original rule. This constraining is local as opposed to commonly used instant normalizations, which require the knowledge of all input weights of a neuron to update each one of them individually. The proposed rule converges to a weight vector that is sparser (has more zero weights) than the vector learned by the original Oja rule with or without the zero bound, which could explain the developmental synaptic pruning.

Brain-wide maps of Fos expression during fear learning and recall.

PubMed

Cho, Jin-Hyung; Rendall, Sam D; Gray, Jesse M

2017-04-01

Fos induction during learning labels neuronal ensembles in the hippocampus that encode a specific physical environment, revealing a memory trace. In the cortex and other regions, the extent to which Fos induction during learning reveals specific sensory representations is unknown. Here we generate high-quality brain-wide maps of Fos mRNA expression during auditory fear conditioning and recall in the setting of the home cage. These maps reveal a brain-wide pattern of Fos induction that is remarkably similar among fear conditioning, shock-only, tone-only, and fear recall conditions, casting doubt on the idea that Fos reveals auditory-specific sensory representations. Indeed, novel auditory tones lead to as much gene induction in visual as in auditory cortex, while familiar (nonconditioned) tones do not appreciably induce Fos anywhere in the brain. Fos expression levels do not correlate with physical activity, suggesting that they are not determined by behavioral activity-driven alterations in sensory experience. In the thalamus, Fos is induced more prominently in limbic than in sensory relay nuclei, suggesting that Fos may be most sensitive to emotional state. Thus, our data suggest that Fos expression during simple associative learning labels ensembles activated generally by arousal rather than specifically by a particular sensory cue. © 2017 Cho et al.; Published by Cold Spring Harbor Laboratory Press.

Brain-wide maps of Fos expression during fear learning and recall

PubMed Central

Cho, Jin-Hyung; Rendall, Sam D.; Gray, Jesse M.

2017-01-01

Fos induction during learning labels neuronal ensembles in the hippocampus that encode a specific physical environment, revealing a memory trace. In the cortex and other regions, the extent to which Fos induction during learning reveals specific sensory representations is unknown. Here we generate high-quality brain-wide maps of Fos mRNA expression during auditory fear conditioning and recall in the setting of the home cage. These maps reveal a brain-wide pattern of Fos induction that is remarkably similar among fear conditioning, shock-only, tone-only, and fear recall conditions, casting doubt on the idea that Fos reveals auditory-specific sensory representations. Indeed, novel auditory tones lead to as much gene induction in visual as in auditory cortex, while familiar (nonconditioned) tones do not appreciably induce Fos anywhere in the brain. Fos expression levels do not correlate with physical activity, suggesting that they are not determined by behavioral activity-driven alterations in sensory experience. In the thalamus, Fos is induced more prominently in limbic than in sensory relay nuclei, suggesting that Fos may be most sensitive to emotional state. Thus, our data suggest that Fos expression during simple associative learning labels ensembles activated generally by arousal rather than specifically by a particular sensory cue. PMID:28331016

Sleep and memory in healthy children and adolescents - a critical review.

PubMed

Kopasz, Marta; Loessl, Barbara; Hornyak, Magdolna; Riemann, Dieter; Nissen, Christoph; Piosczyk, Hannah; Voderholzer, Ulrich

2010-06-01

There is mounting evidence that sleep is important for learning, memory and the underlying neural plasticity. This article aims to review published studies that evaluate the association between sleep, its distinct stages and memory systems in healthy children and adolescents. Furthermore it intends to suggest directions for future research. A computerised search of the literature for relevant articles published between 1966 and March 2008 was performed using the keywords "sleep", "memory", "learn", "child", "adolescents", "adolescence" and "teenager". Fifteen studies met the inclusion criteria. Published studies focused on the impact of sleep on working memory and memory consolidation. In summary, most studies support the hypothesis that sleep facilitates working memory as well as memory consolidation in children and adolescents. There is evidence that performance in abstract and complex tasks involving higher brain functions declines more strongly after sleep deprivation than the performance in simple memory tasks. Future studies are needed to better understand the impact of a variety of variables potentially modulating the interplay between sleep and memory, such as developmental stage, socioeconomic burden, circadian factors, or the level of post-learning sensory and motor activity (interference). This line of research can provide valuable input relevant to teaching, learning and public health policy. Copyright 2009 Elsevier Ltd. All rights reserved.

Effects of Different Student Response Modes on Science Learning

ERIC Educational Resources Information Center

Kho, Lee Sze; Chen, Chwen Jen

2017-01-01

Student response systems (SRSs) are wireless answering devices that enable students to provide simple real-time feedback to instructors. This study aims to evaluate the effects of different SRS interaction modes on elementary school students' science learning. Three interaction modes which include SRS Individual, SRS Collaborative, and Classroom…

Methods & Strategies: I Wonder...

ERIC Educational Resources Information Center

Stevenson, Anne

2013-01-01

"I Wonder" boards are a teaching strategy that can be used in the classroom, as well as during science learning opportunities in nonformal settings, such as after-school science programs or summer camps.This simple strategy has led to deeper science exploration in 4-H, as young people learn alongside program staff, teachers, or…

Analyzing Multimodal Interaction within a Classroom Setting

ERIC Educational Resources Information Center

Moura, Heloisa

2006-01-01

Human interactions are multimodal in nature. From simple to complex forms of transferal of information, human beings draw on a multiplicity of communicative modes, such as intonation and gaze, to make sense of everyday experiences. Likewise, the learning process, either within traditional classrooms or Virtual Learning Environments, is shaped by…

Adjective Identification in Television Advertisements

ERIC Educational Resources Information Center

Abd Rahim, Normaliza

2013-01-01

Learning the Malay language has been a challenging task for foreign language learners. Learners have to learn Malay grammar structure rules in order to write simple sentences. The word choice is important in constructing a sentence. Therefore, the study focuses on the use of adjectives in television advertisements among Korean learners at Hankuk…

Learning Activity Package, Physical Science. LAP Numbers 8, 9, 10, and 11.

ERIC Educational Resources Information Center

Williams, G. J.

These four units of the Learning Activity Packages (LAPs) for individualized instruction in physical science cover nuclear reactions, alpha and beta particles, atomic radiation, medical use of nuclear energy, fission, fusion, simple machines, Newton's laws of motion, electricity, currents, electromagnetism, Oersted's experiment, sound, light,…

Comprehension of Architectural Construction through Multimedia Active Learning

ERIC Educational Resources Information Center

Mas, Ángeles; Blasco, Vicente; Lerma, Carlos; Angulo, Quiteria

2013-01-01

This study presents an investigation about the use of multimedia procedures applied to architectural construction teaching. We have applied current technological resources, aiming to rationalize and optimize the active learning process. The experience presented to students is very simple and yet very effective. It has consisted in a simulation of…

Foods and Families Learning Package: An Educational Supplement to Early Childhood News.

ERIC Educational Resources Information Center

General Mills, Inc., Minneapolis, Minn.

This resource guide for the early childhood professional contains creative art activities, active learning experiences, interactive bulletin boards, teacher-made materials, simple cooking projects, inviting fingerplays, songs, and music. The activities are planned to stimulate children's curiosity and senses. Through experiencing these activities,…

Verbal and Behavioral Cues: Creating an Autonomy-Supportive Classroom

ERIC Educational Resources Information Center

Young-Jones, Adena; Cara, Kelly Copeland; Levesque-Bristol, Chantal

2014-01-01

Teaching practices can create a range of autonomy-supportive or controlling learning environments. Research shows that autonomy-supportive techniques are more conducive to positive learning outcomes than controlling techniques. This study focused on simple verbal and behavioral cues that any teacher could use to create a positive learning…

Captioning Effects on Television News Learning.

ERIC Educational Resources Information Center

Reese, Stephen D.; Davie, William R.

Noting that the use of captions in television newscasts has grown from simple labeling of newsmakers to more complicated titling of graphics and enumerating important points in a script, a study examined the extent to which captioning assisted viewers in learning from different types of television news stories. Subjects, 100 undergraduate…

After Access: Divergent Learning Profiles in Vietnam and India

ERIC Educational Resources Information Center

Rolleston, Caine; James, Zoe

2015-01-01

In recent decades, both India and Vietnam have successfully expanded access to schooling to near-universal levels and have shifted their focus to quality-oriented policy reform. Yet, international and national evidence shows strongly contrasting learning profiles for children within the two systems. Simple indicators of numeracy suggest similar…

Instruction, Rationality and Learning to be Moral.

ERIC Educational Resources Information Center

Hyland, J. T.

1986-01-01

Defines rationality and morality and contends that learning to be moral must be based on more than value-neutral approaches which stress process over content. Argues that instruction in moral principles need not be simple bald exposition, but must include proofs, evidences, and arguments, making it nondogmatic and fully compatible with the…

Discover the Possibilities

ERIC Educational Resources Information Center

Celeste, Eric

2016-01-01

The purpose of professional learning is for educators to develop the knowledge, skills, practices, and dispositions they need to help students perform at higher levels. It is not a simple matter to connect the dots between high quality professional learning and student outcomes. However, the theory of action that drives the standards, and indeed…

Guiding Children's Reading through Experiences. Second Edition.

ERIC Educational Resources Information Center

Gans, Roma

This discussion of methods, experiences, and theory provides educators and parents with an approach to learning to read that emphasizes learning to think and becoming a functional reader who can enjoy using this skill throughout life. Included are simple, inexpensive suggestions for improving reading, such as more attention to regular school…

Preparing to Prescribe: How Do Clerkship Students Learn in the Midst of Complexity?

ERIC Educational Resources Information Center

McLellan, Lucy; Yardley, Sarah; Norris, Ben; de Bruin, Anique; Tully, Mary P.; Dornan, Tim

2015-01-01

Prescribing tasks, which involve pharmacological knowledge, clinical decision-making and practical skill, take place within unpredictable social environments and involve interactions within and between endlessly changing health care teams. Despite this, curriculum designers commonly assume them to be simple to learn and perform. This research used…

Wild Children

ERIC Educational Resources Information Center

Trotman, Helen

2010-01-01

In this article, the author, a Forest School Leader with Shropshire Wildlife Trust, shows how nature is the best teacher. She describes a new approach to out-of-classroom learning during which qualified leaders use simple challenges and achievable tasks to encourage child-initiated learning in the great outdoors. At Forest School, children are…

Learning Research and Community Decision Making

ERIC Educational Resources Information Center

Allison, Bradford; Schumacher, Gary

2011-01-01

This case presents a situation in which a reformist superintendent attempts to achieve a systemwide, yet simple change in the school time schedule to incorporate well-established neurocognitive sleep research to enhance student learning. The public discussion of the reform proposal brought forth a very negative, single issue group who took over…

Reducing Cultural Barriers via Internet Courses

ERIC Educational Resources Information Center

Xing, Minjie; Spencer, Ken

2008-01-01

A Web-based learning environment has been developed to support students from China who are studying in the UK and are confronted by many cultural barriers, which may impede their academic studies. The electronic environment incorporates a number of approaches to support learning, ranging from a simple text-based presentation to more active…

The Role of Simple Semantics in the Process of Artificial Grammar Learning

ERIC Educational Resources Information Center

Öttl, Birgit; Jäger, Gerhard; Kaup, Barbara

2017-01-01

This study investigated the effect of semantic information on artificial grammar learning (AGL). Recursive grammars of different complexity levels (regular language, mirror language, copy language) were investigated in a series of AGL experiments. In the with-semantics condition, participants acquired semantic information prior to the AGL…

Spatial Probability Cuing and Right Hemisphere Damage

ERIC Educational Resources Information Center

Shaqiri, Albulena; Anderson, Britt

2012-01-01

In this experiment we studied statistical learning, inter-trial priming, and visual attention. We assessed healthy controls and right brain damaged (RBD) patients with and without neglect, on a simple visual discrimination task designed to measure priming effects and probability learning. All participants showed a preserved priming effect for item…

Computer-Assisted Language Learning Authoring Issues

ERIC Educational Resources Information Center

Otto, Sue E. K.; Pusack, James P.

2009-01-01

Computer-assisted language learning (CALL) authoring refers to a wide variety of creative development activities using software tools that run the gamut from simple templates (easy-to-use predefined forms into which content is typed) to complex authoring environments (flexible but harder-to-use systems, requiring advanced skills and a great deal…

E-Learning Systems Requirements Elicitation: Perspectives and Considerations

ERIC Educational Resources Information Center

AlKhuder, Shaikha B.; AlAli, Fatma H.

2017-01-01

Training and education have evolved far beyond black boards and chalk boxes. The environment of knowledge exchange requires more than simple materials and assessments. This article is an attempt of parsing through the different aspects of e-learning, understanding the real needs, and conducting the right requirements to build the appropriate…

Easing student transition to graduate nurse: a SIMulated Professional Learning Environment (SIMPLE) for final year student nurses.

PubMed

Liaw, Sok Ying; Koh, Yiwen; Dawood, Rabiah; Kowitlawakul, Yanika; Zhou, Wentao; Lau, Siew Tiang

2014-03-01

Preparing nursing students for making the transition to graduate nurse is crucial for entry into practice. Final year student nurses at the National University of Singapore (NUS) are required to undergo a consolidated clinical practice to prepare them for their transition to graduate nurse. To describe the development, implementation and evaluation of a simulation program known as SIMulated Professional Learning Environment (SIMPLE) in preparing the final year student nurses for their clinical practicum in transition to graduate nurse practice. A set of simulation features and best practices were used as conceptual framework to develop and implement the simulation program. 94 final year student nurses participated in the 15-hour SIMPLE program that incorporated multiple simulation scenarios based on actual ward clinical practices. Pre and post-tests were conducted to assess the students' preparedness for their clinical practice in transition to graduate nurse practice. The students also completed a satisfaction questionnaire and open questions to evaluate their simulation experiences. The student nurses demonstrated a significant improvement (t=12.06, p<0.01) on post-test score (mean=117.21, SD=15.17) from pre-test score (mean=97.86, SD=15.08) for their perceived preparedness towards their clinical practicum in transition to graduate nurse practice. They were highly satisfied with their simulation learning. Themes emerged from the comments on the most valuable aspects of the SIMPLE program and ways to improve the program. The study provided evidences on the effectiveness of the SIMPLE program in enhancing the students' preparedness for their transition to graduate nurse practice. A key success of the SIMPLE program was the used of simulation strategy and the involvement of practicing nurses that closely linked the students with the realities of current nursing practice to prepare them for the role of staff nurses. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mirror neuron system: basic findings and clinical applications.

PubMed

Iacoboni, Marco; Mazziotta, John C

2007-09-01

In primates, ventral premotor and rostral inferior parietal neurons fire during the execution of hand and mouth actions. Some cells (called mirror neurons) also fire when hand and mouth actions are just observed. Mirror neurons provide a simple neural mechanism for understanding the actions of others. In humans, posterior inferior frontal and rostral inferior parietal areas have mirror properties. These human areas are relevant to imitative learning and social behavior. Indeed, the socially isolating condition of autism is associated with a deficit in mirror neuron areas. Strategies inspired by mirror neuron research recently have been used in the treatment of autism and in motor rehabilitation after stroke.

ICPL: Intelligent Cooperative Planning and Learning for Multi-agent Systems

DTIC Science & Technology

2012-02-29

objective was to develop a new planning approach for teams!of multiple UAVs that tightly integrates learning and cooperative!control algorithms at... algorithms at multiple levels of the planning architecture. The research results enabled a team of mobile agents to learn to adapt and react to uncertainty in...expressive representation that incorporates feature conjunctions. Our algorithm is simple to implement, fast to execute, and can be combined with any

Developing a Mobile Physics Learning Environment Based on Physics Misconception Research and E-Learning Design Principles

ERIC Educational Resources Information Center

Lee, Young-Jin

2010-01-01

With a rapid increase in the number of people who own a handheld device, such as an iPod, education researchers and administrators started looking for a way to use a handheld device to foster student learning. However, the current use of a mobile device in education is quite limited. With few exceptions, it is mostly used as a simple media player…

Oh! What a Smart Baby: What You Need to Know about Children's Brain Development

ERIC Educational Resources Information Center

Arnold, Renea; Colburn, Nell

2005-01-01

Brain research is complicated, but its message is simple: babies are born learning and what they learn is up to us. New research on infant brain development shows that a child's experiences in the first three years of life have a distinct impact on her later development and learning. Here's why. All babies are born with one organ that is not fully…

Lifelong Transfer Learning for Heterogeneous Teams of Agents in Sequential Decision Processes

DTIC Science & Technology

2016-06-01

making (SDM) tasks in dynamic environments with simulated and physical robots . 15. SUBJECT TERMS Sequential decision making, lifelong learning, transfer...sequential decision-making (SDM) tasks in dynamic environments with both simple benchmark tasks and more complex aerial and ground robot tasks. Our work...and ground robots in the presence of disturbances: We applied our methods to the problem of learning controllers for robots with novel disturbances in

Slow feature analysis: unsupervised learning of invariances.

PubMed

Wiskott, Laurenz; Sejnowski, Terrence J

2002-04-01

Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

Learning predictive statistics from temporal sequences: Dynamics and strategies

PubMed Central

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E.; Kourtzi, Zoe

2017-01-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics—that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments. PMID:28973111

Reward-Modulated Hebbian Plasticity as Leverage for Partially Embodied Control in Compliant Robotics

PubMed Central

Burms, Jeroen; Caluwaerts, Ken; Dambre, Joni

2015-01-01

In embodied computation (or morphological computation), part of the complexity of motor control is offloaded to the body dynamics. We demonstrate that a simple Hebbian-like learning rule can be used to train systems with (partial) embodiment, and can be extended outside of the scope of traditional neural networks. To this end, we apply the learning rule to optimize the connection weights of recurrent neural networks with different topologies and for various tasks. We then apply this learning rule to a simulated compliant tensegrity robot by optimizing static feedback controllers that directly exploit the dynamics of the robot body. This leads to partially embodied controllers, i.e., hybrid controllers that naturally integrate the computations that are performed by the robot body into a neural network architecture. Our results demonstrate the universal applicability of reward-modulated Hebbian learning. Furthermore, they demonstrate the robustness of systems trained with the learning rule. This study strengthens our belief that compliant robots should or can be seen as computational units, instead of dumb hardware that needs a complex controller. This link between compliant robotics and neural networks is also the main reason for our search for simple universal learning rules for both neural networks and robotics. PMID:26347645

Learning Orthographic Structure With Sequential Generative Neural Networks.

PubMed

Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

2016-04-01

Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.

Learning predictive statistics from temporal sequences: Dynamics and strategies.

PubMed

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-10-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.

Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks

PubMed Central

Clune, Jeff

2017-01-01

A long-term goal of AI is to produce agents that can learn a diversity of skills throughout their lifetimes and continuously improve those skills via experience. A longstanding obstacle towards that goal is catastrophic forgetting, which is when learning new information erases previously learned information. Catastrophic forgetting occurs in artificial neural networks (ANNs), which have fueled most recent advances in AI. A recent paper proposed that catastrophic forgetting in ANNs can be reduced by promoting modularity, which can limit forgetting by isolating task information to specific clusters of nodes and connections (functional modules). While the prior work did show that modular ANNs suffered less from catastrophic forgetting, it was not able to produce ANNs that possessed task-specific functional modules, thereby leaving the main theory regarding modularity and forgetting untested. We introduce diffusion-based neuromodulation, which simulates the release of diffusing, neuromodulatory chemicals within an ANN that can modulate (i.e. up or down regulate) learning in a spatial region. On the simple diagnostic problem from the prior work, diffusion-based neuromodulation 1) induces task-specific learning in groups of nodes and connections (task-specific localized learning), which 2) produces functional modules for each subtask, and 3) yields higher performance by eliminating catastrophic forgetting. Overall, our results suggest that diffusion-based neuromodulation promotes task-specific localized learning and functional modularity, which can help solve the challenging, but important problem of catastrophic forgetting. PMID:29145413

Solving ordinary differential equations by electrical analogy: a multidisciplinary teaching tool

NASA Astrophysics Data System (ADS)

Sanchez Perez, J. F.; Conesa, M.; Alhama, I.

2016-11-01

Ordinary differential equations are the mathematical formulation for a great variety of problems in science and engineering, and frequently, two different problems are equivalent from a mathematical point of view when they are formulated by the same equations. Students acquire the knowledge of how to solve these equations (at least some types of them) using protocols and strict algorithms of mathematical calculation without thinking about the meaning of the equation. The aim of this work is that students learn to design network models or circuits in this way; with simple knowledge of them, students can establish the association of electric circuits and differential equations and their equivalences, from a formal point of view, that allows them to associate knowledge of two disciplines and promote the use of this interdisciplinary approach to address complex problems. Therefore, they learn to use a multidisciplinary tool that allows them to solve these kinds of equations, even students of first course of engineering, whatever the order, grade or type of non-linearity. This methodology has been implemented in numerous final degree projects in engineering and science, e.g., chemical engineering, building engineering, industrial engineering, mechanical engineering, architecture, etc. Applications are presented to illustrate the subject of this manuscript.

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

PubMed Central

Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

2015-01-01

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT (“face patches”) did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. SIGNIFICANCE STATEMENT We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887

From modulated Hebbian plasticity to simple behavior learning through noise and weight saturation.

PubMed

Soltoggio, Andrea; Stanley, Kenneth O

2012-10-01

Synaptic plasticity is a major mechanism for adaptation, learning, and memory. Yet current models struggle to link local synaptic changes to the acquisition of behaviors. The aim of this paper is to demonstrate a computational relationship between local Hebbian plasticity and behavior learning by exploiting two traditionally unwanted features: neural noise and synaptic weight saturation. A modulation signal is employed to arbitrate the sign of plasticity: when the modulation is positive, the synaptic weights saturate to express exploitative behavior; when it is negative, the weights converge to average values, and neural noise reconfigures the network's functionality. This process is demonstrated through simulating neural dynamics in the autonomous emergence of fearful and aggressive navigating behaviors and in the solution to reward-based problems. The neural model learns, memorizes, and modifies different behaviors that lead to positive modulation in a variety of settings. The algorithm establishes a simple relationship between local plasticity and behavior learning by demonstrating the utility of noise and weight saturation. Moreover, it provides a new tool to simulate adaptive behavior, and contributes to bridging the gap between synaptic changes and behavior in neural computation. Copyright © 2012 Elsevier Ltd. All rights reserved.

All for one and one for all: understanding health professionals' experience in individual versus collaborative online learning.

PubMed

MacNeill, Heather; Telner, Deanna; Sparaggis-Agaliotis, Alexandra; Hanna, Elizabeth

2014-01-01

Computer-supported collaborative learning (CSCL) may facilitate continuing interprofessional education while overcoming barriers of time and place for busy health care professionals. The purpose of this study was to understand the experiences, advantages, and challenges of group versus individual online learning. Fifteen multidisciplinary health professionals participated in a 12-week online course on either diabetes or traumatic brain injury. This consisted of background e-modules and a longitudinal build-a-case exercise, done either individually or as a group. Focus group sessions exploring participants' experiences after course completion and at 4 months were conducted, transcribed, and analyzed for recurring themes. Participant reflection homework and video-recorded group sessions were used for triangulation of results. Individual learners appreciated the flexibility and control, but experienced decreased motivation. Group learners appreciated the immediate feedback from their co-learners and felt social pressure to come to the weekly sessions prepared but expressed challenges in determining group goal-setting for the session. Both groups felt they learned about interprofessional roles; however, group learners described a richer learning experience and understanding of interprofessional roles through the online collaboration exercise. The intense resources necessary for interprofessional CSCL, including time, faculty development, and technological issues, are described. CSCL is a valuable educational strategy in online learning. While individual online learning may be better suited for short and simple educational interventions such as knowledge acquisition, CSCL seems to allow for richer and deeper learning in complex and interprofessional educational experiences. However, strategies, resources, and faculty development required to enhance CSCL need to be addressed carefully. © 2014 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on Continuing Medical Education, Association for Hospital Medical Education.

New Learning of Music after Bilateral Medial Temporal Lobe Damage: Evidence from an Amnesic Patient

PubMed Central

Valtonen, Jussi; Gregory, Emma; Landau, Barbara; McCloskey, Michael

2014-01-01

Damage to the hippocampus impairs the ability to acquire new declarative memories, but not the ability to learn simple motor tasks. An unresolved question is whether hippocampal damage affects learning for music performance, which requires motor processes, but in a cognitively complex context. We studied learning of novel musical pieces by sight-reading in a newly identified amnesic, LSJ, who was a skilled amateur violist prior to contracting herpes simplex encephalitis. LSJ has suffered virtually complete destruction of the hippocampus bilaterally, as well as extensive damage to other medial temporal lobe structures and the left anterior temporal lobe. Because of LSJ’s rare combination of musical training and near-complete hippocampal destruction, her case provides a unique opportunity to investigate the role of the hippocampus for complex motor learning processes specifically related to music performance. Three novel pieces of viola music were composed and closely matched for factors contributing to a piece’s musical complexity. LSJ practiced playing two of the pieces, one in each of the two sessions during the same day. Relative to a third unpracticed control piece, LSJ showed significant pre- to post-training improvement for the two practiced pieces. Learning effects were observed both with detailed analyses of correctly played notes, and with subjective whole-piece performance evaluations by string instrument players. The learning effects were evident immediately after practice and 14 days later. The observed learning stands in sharp contrast to LSJ’s complete lack of awareness that the same pieces were being presented repeatedly, and to the profound impairments she exhibits in other learning tasks. Although learning in simple motor tasks has been previously observed in amnesic patients, our results demonstrate that non-hippocampal structures can support complex learning of novel musical sequences for music performance. PMID:25232312

Working Memory Load Strengthens Reward Prediction Errors.

PubMed

Collins, Anne G E; Ciullo, Brittany; Frank, Michael J; Badre, David

2017-04-19

Reinforcement learning (RL) in simple instrumental tasks is usually modeled as a monolithic process in which reward prediction errors (RPEs) are used to update expected values of choice options. This modeling ignores the different contributions of different memory and decision-making systems thought to contribute even to simple learning. In an fMRI experiment, we investigated how working memory (WM) and incremental RL processes interact to guide human learning. WM load was manipulated by varying the number of stimuli to be learned across blocks. Behavioral results and computational modeling confirmed that learning was best explained as a mixture of two mechanisms: a fast, capacity-limited, and delay-sensitive WM process together with slower RL. Model-based analysis of fMRI data showed that striatum and lateral prefrontal cortex were sensitive to RPE, as shown previously, but, critically, these signals were reduced when the learning problem was within capacity of WM. The degree of this neural interaction related to individual differences in the use of WM to guide behavioral learning. These results indicate that the two systems do not process information independently, but rather interact during learning. SIGNIFICANCE STATEMENT Reinforcement learning (RL) theory has been remarkably productive at improving our understanding of instrumental learning as well as dopaminergic and striatal network function across many mammalian species. However, this neural network is only one contributor to human learning and other mechanisms such as prefrontal cortex working memory also play a key role. Our results also show that these other players interact with the dopaminergic RL system, interfering with its key computation of reward prediction errors. Copyright © 2017 the authors 0270-6474/17/374332-11$15.00/0.

Implicit Learning of Arithmetic Regularities Is Facilitated by Proximal Contrast

PubMed Central

Prather, Richard W.

2012-01-01

Natural number arithmetic is a simple, powerful and important symbolic system. Despite intense focus on learning in cognitive development and educational research many adults have weak knowledge of the system. In current study participants learn arithmetic principles via an implicit learning paradigm. Participants learn not by solving arithmetic equations, but through viewing and evaluating example equations, similar to the implicit learning of artificial grammars. We expand this to the symbolic arithmetic system. Specifically we find that exposure to principle-inconsistent examples facilitates the acquisition of arithmetic principle knowledge if the equations are presented to the learning in a temporally proximate fashion. The results expand on research of the implicit learning of regularities and suggest that contrasting cases, show to facilitate explicit arithmetic learning, is also relevant to implicit learning of arithmetic. PMID:23119101

Neural substrates underlying stimulation-enhanced motor skill learning after stroke.

PubMed

Lefebvre, Stéphanie; Dricot, Laurence; Laloux, Patrice; Gradkowski, Wojciech; Desfontaines, Philippe; Evrard, Frédéric; Peeters, André; Jamart, Jacques; Vandermeeren, Yves

2015-01-01

Motor skill learning is one of the key components of motor function recovery after stroke, especially recovery driven by neurorehabilitation. Transcranial direct current stimulation can enhance neurorehabilitation and motor skill learning in stroke patients. However, the neural mechanisms underlying the retention of stimulation-enhanced motor skill learning involving a paretic upper limb have not been resolved. These neural substrates were explored by means of functional magnetic resonance imaging. Nineteen chronic hemiparetic stroke patients participated in a double-blind, cross-over randomized, sham-controlled experiment with two series. Each series consisted of two sessions: (i) an intervention session during which dual transcranial direct current stimulation or sham was applied during motor skill learning with the paretic upper limb; and (ii) an imaging session 1 week later, during which the patients performed the learned motor skill. The motor skill learning task, called the 'circuit game', involves a speed/accuracy trade-off and consists of moving a pointer controlled by a computer mouse along a complex circuit as quickly and accurately as possible. Relative to the sham series, dual transcranial direct current stimulation applied bilaterally over the primary motor cortex during motor skill learning with the paretic upper limb resulted in (i) enhanced online motor skill learning; (ii) enhanced 1-week retention; and (iii) superior transfer of performance improvement to an untrained task. The 1-week retention's enhancement driven by the intervention was associated with a trend towards normalization of the brain activation pattern during performance of the learned motor skill relative to the sham series. A similar trend towards normalization relative to sham was observed during performance of a simple, untrained task without a speed/accuracy constraint, despite a lack of behavioural difference between the dual transcranial direct current stimulation and sham series. Finally, dual transcranial direct current stimulation applied during the first session enhanced continued learning with the paretic limb 1 week later, relative to the sham series. This lasting behavioural enhancement was associated with more efficient recruitment of the motor skill learning network, that is, focused activation on the motor-premotor areas in the damaged hemisphere, especially on the dorsal premotor cortex. Dual transcranial direct current stimulation applied during motor skill learning with a paretic upper limb resulted in prolonged shaping of brain activation, which supported behavioural enhancements in stroke patients. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Reinforcement learning: Solving two case studies

NASA Astrophysics Data System (ADS)

Duarte, Ana Filipa; Silva, Pedro; dos Santos, Cristina Peixoto

2012-09-01

Reinforcement Learning algorithms offer interesting features for the control of autonomous systems, such as the ability to learn from direct interaction with the environment, and the use of a simple reward signalas opposed to the input-outputs pairsused in classic supervised learning. The reward signal indicates the success of failure of the actions executed by the agent in the environment. In this work, are described RL algorithmsapplied to two case studies: the Crawler robot and the widely known inverted pendulum. We explore RL capabilities to autonomously learn a basic locomotion pattern in the Crawler, andapproach the balancing problem of biped locomotion using the inverted pendulum.

Error Analysis of Present Simple Tense in the Interlanguage of Adult Arab English Language Learners

ERIC Educational Resources Information Center

Muftah, Muneera; Rafik-Galea, Shameem

2013-01-01

The present study analyses errors on present simple tense among adult Arab English language learners. It focuses on the error on 3sg "-s" (the third person singular present tense agreement morpheme "-s"). The learners are undergraduate adult Arabic speakers learning English as a foreign language. The study gathered data from…

Consecutive Course Modules Developed with Simple Materials to Facilitate the Learning of Basic Concepts in Astronomy

ERIC Educational Resources Information Center

Okulu, Hasan Zuhtu; Oguz-Unver, Ayse

2015-01-01

From the perspective of teaching, the huge natural laboratory that astronomy provides constitutes the most prominent connection between astronomy and other branches of science. The purpose of this research was to provide educators with activities of observation using simple materials that were developed to facilitate the teaching of basic concepts…

In Defense of the Formula Essay

ERIC Educational Resources Information Center

Haluska, Jan Charles

2007-01-01

In 1970, the author learned a simple step in making essays from his advisor. His advisor used a drawing of the Parthenon to illustrate the creation of a five-paragraph essay. It was obvious that his advisor was hesitant on teaching them a very simple concept of essay writing because it was pretty mechanical. Like his advisor, a lot of teachers…

Design Features of a Friendly Software Environment for Novice Programmers. Technical Report No. 3.

ERIC Educational Resources Information Center

Eisenstadt, Marc

This paper describes the results of a 6-year period of design, implementation, testing, and iterative redesign of a programming language, user aids, and curriculum materials for use by psychology students learning how to write simple computer programs. The SOLO language, which was the resulting product, is primarily a simple, database…

A Simple Computer-Aided Three-Dimensional Molecular Modeling for the Octant Rule

ERIC Educational Resources Information Center

Kang, Yinan; Kang, Fu-An

2011-01-01

The Moffitt-Woodward-Moscowitz-Klyne-Djerassi octant rule is one of the most successful empirical rules in organic chemistry. However, the lack of a simple effective modeling method for the octant rule in the past 50 years has posed constant difficulties for researchers, teachers, and students, particularly the young generations, to learn and…

Tips, Tricks & Techniques: Creating & Teaching with Simple Animation: Making Biology Instruction Come Alive

ERIC Educational Resources Information Center

Zanin, Mary K. B.

2015-01-01

Over the years, many of my students have reported that they enjoy lectures that include short, simple animations. To keep students engaged, I have developed a small set of teaching animations using PowerPoint and Camtasia Studio software packages. A survey of students who learned four difficult topics with traditional written lessons and with…

Simple System to Measure the Earth's Magnetic Field

ERIC Educational Resources Information Center

Akoglu, R.; Halilsoy, M.; Mazharimousavi, S. Habib

2010-01-01

Our aim in this proposal is to use Faraday's law of induction as a simple lecture demonstration to measure the Earths magnetic field (B). This will also enable the students to learn about how electric power is generated from rotational motion. Obviously the idea is not original, yet it may be attractive in the sense that no sophisticated devices…

"FORCE" learning in recurrent neural networks as data assimilation

NASA Astrophysics Data System (ADS)

Duane, Gregory S.

2017-12-01

It is shown that the "FORCE" algorithm for learning in arbitrarily connected networks of simple neuronal units can be cast as a Kalman Filter, with a particular state-dependent form for the background error covariances. The resulting interpretation has implications for initialization of the learning algorithm, leads to an extension to include interactions between the weight updates for different neurons, and can represent relationships within groups of multiple target output signals.

Learning through Geography. Pathways in Geography Series, Title No. 7.

ERIC Educational Resources Information Center

Slater, Frances

This teacher's guide is to enable the teacher to promote thinking through the use of geography. The book lays out the rationale in learning theory for an issues-based, question-driven inquiry method and proceeds through a simple model of progression from identifying key questions to developing generalizations. Students study issues of geographic…

Coloring in the Emotional Language of Place

ERIC Educational Resources Information Center

Haigh, Martin

2008-01-01

Making educational places more inviting to learners is a key aspect of Invitational Theory. This paper introduces a simple technique for sensitizing learners and instructors to how their environment affects their feelings and ability to learn. It describes a learning exercise that may be used to assess, evaluate and transform places, to promote…

Methods for Maximizing the Learning Process: A Theoretical and Experimental Analysis.

ERIC Educational Resources Information Center

Atkinson, Richard C.

This research deals with optimizing the instructional process. The approach adopted was to limit consideration to simple learning tasks for which adequate mathematical models could be developed. Optimal or suitable suboptimal instructional strategies were developed for the models. The basic idea was to solve for strategies that either maximize the…

Learning and Understanding System Stability Using Illustrative Dynamic Texture Examples

ERIC Educational Resources Information Center

Liu, Huaping; Xiao, Wei; Zhao, Hongyan; Sun, Fuchun

2014-01-01

System stability is a basic concept in courses on dynamic system analysis and control for undergraduate students with computer science backgrounds. Typically, this was taught using a simple simulation example of an inverted pendulum. Unfortunately, many difficult issues arise in the learning and understanding of the concepts of stability,…

Simple Solutions to Complex Problems--MOOCs as a Panacea?

ERIC Educational Resources Information Center

Bass, Scott A.

2014-01-01

This article is critical of the implementation of massive open online courses (MOOCs) by institutions seeking the deep student learning often found in general education learning outcomes. Customized student interaction with an expert in the field is rendered impossible by the scale of mooc enrollment. Concerns are also raised about the economic…

The Genesis of Language: A Psycholinguistic Approach.

ERIC Educational Resources Information Center

Smith, Frank, Ed.; Miller, George A., Ed.

The fourteen papers are: "Developmental Psycholinguistics," by David McNeill; "Comments on 'Developmental Psycholinguistics'," by Dan I. Slobin; "How to Learn to Talk: Some Simple Ways," by Jerry A. Fodor; "The Acquisition of Russian as a Native Language, " by Dan I. Slobin; "Some Questions on the Child's Learning of Phonology," by Ruth H. Weir;…

e-Learning Business Research Methods

ERIC Educational Resources Information Center

Cowie, Jonathan

2004-01-01

This paper outlines the development of a generic Business Research Methods course from a simple name in a box to a full e-Learning web based module. It highlights particular issues surrounding the nature of the discipline and the integration of a large number of cross faculty subject specific research methods courses into a single generic module.…

20 CFR 416.968 - Skill requirements.

Code of Federal Regulations, 2011 CFR

2011-04-01

... which needs little or no judgment to do simple duties that can be learned on the job in a short period... materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30 days, and little specific vocational preparation and judgment are needed...

20 CFR 416.968 - Skill requirements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... which needs little or no judgment to do simple duties that can be learned on the job in a short period... materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30 days, and little specific vocational preparation and judgment are needed...

Assessment for Learning: An Endangered Species?

ERIC Educational Resources Information Center

Popham, W. James

2006-01-01

Assessment for learning involves the frequent, continual use of both formal and informal classroom assessments. It can be as simple as requiring students to respond to a lesson-embedded, one-item quiz as a way of gauging student understanding of what is being taught. Ideally, this innovative approach to classroom assessment is based on a careful…

Using Inquiry-Based Instruction for Teaching Science to Students with Learning Disabilities

ERIC Educational Resources Information Center

Aydeniz, Mehmet; Cihak, David F.; Graham, Shannon C.; Retinger, Larryn

2012-01-01

The purpose of this study was to examine the effects of inquiry-based science instruction for five elementary students with learning disabilities (LD). Students participated in a series of inquiry-based activities targeting conceptual and application-based understanding of simple electric circuits, conductors and insulators, parallel circuits, and…

Still Learning after All These Years

ERIC Educational Resources Information Center

Stanistreet, Paul

2012-01-01

Adult Learners' Week is based on a simple idea--that extolling the achievements of adult learners and promoting the benefits of learning will encourage others to take the plunge. Each year, through thousands of events and award ceremonies, and in media coverage that would cost millions of pounds if purchased as advertising, Adult Learners' Week…

When the Fire's Out: Learning from Adversity.

ERIC Educational Resources Information Center

Holden, Tom

1997-01-01

After a $7 million arson fire destroyed part of a Virginia Beach high school, about 1,200 students were temporarily relocated to a refurbished former mini-mall, and a 16-month recovery project was initiated. The new design improved library and art facilities. School officials have since learned to fight fire with simple precautions, such as…

Posing Problems to Understand Children's Learning of Fractions

ERIC Educational Resources Information Center

Cheng, Lu Pien

2013-01-01

In this study, ways in which problem posing activities aid our understanding of children's learning of addition of unlike fractions and product of proper fractions was examined. In particular, how a simple problem posing activity helps teachers take a second, deeper look at children's understanding of fraction concepts will be discussed. The…

Transformation through Expeditionary Change Using Online Learning and Competence-Building Technologies

ERIC Educational Resources Information Center

Norris, Donald M.; Lefrere, Paul

2011-01-01

This paper presents a patterns-based model of the evolution of learning and competence-building technologies, grounded in examples of current practice. The model imagines five simple stages in how institutions use "expeditionary change" to innovate more nimbly. It builds upon three assertions. First, the pervasiveness of web-based…

Watching Learning Happen: Results of a Longitudinal Study of Journalism Students

ERIC Educational Resources Information Center

MacMillan, Margy

2009-01-01

The results from a five-year study of the information skills of journalism students provide insights into what students use and how that usage evolves, and have implications for information literacy instruction. Using a simple tool, the author watched learning happen in response to classes, work, and the changing information environment. (Contains…

Real time on-chip sequential adaptive principal component analysis for data feature extraction and image compression

NASA Technical Reports Server (NTRS)

Duong, T. A.

2004-01-01

In this paper, we present a new, simple, and optimized hardware architecture sequential learning technique for adaptive Principle Component Analysis (PCA) which will help optimize the hardware implementation in VLSI and to overcome the difficulties of the traditional gradient descent in learning convergence and hardware implementation.

A Web-Based Tutor for Java™: Evidence of Meaningful Learning

ERIC Educational Resources Information Center

Emurian, Henry H.

2006-01-01

Students in a graduate class and an undergraduate class in Information Systems completed a Web-based programmed instruction tutor that taught a simple Java applet as the first technical training exercise in a computer programming course. The tutor is a competency-based instructional system for individualized distance learning. When a student…

Talk Like a Scientist! Simple "Frames" to Scaffold the Language of Science

ERIC Educational Resources Information Center

Hoffman, Lisa

2013-01-01

This article shares a teaching strategy for science teachers to use when supporting language development among English language learners. Students from other language backgrounds who are learning English need to learn both grade-level academic content and the language necessary to express scientific concepts. However, most science teachers are not…

PDAs: Revolutionizing the Way We Learn and Teach

ERIC Educational Resources Information Center

McDonough, Kimberly; Berge, Zane L.

2006-01-01

Miniature handheld computers called PDAs are not only bombarding corporate America, but they are also noticeably making their mark on college campuses. The question is, how much impact are they making on the way students learn and instructors teach. These devices were born from a simple calculator and over two decades have transformed into a…

The Effective Utilization of an Instructional Film in a Learning Sequence

ERIC Educational Resources Information Center

Thomas, Ian D.

1973-01-01

Summarizes some of the main research findings relating to the utilization of instructional films in classroom situations. Reports the confirmation of a number of these findings in a survey conducted to investigate the teaching and learning practices used in acquiring the ability to solve simple problems using Coulomb's Law. (Author/JR)

The Impact of Uncertainty and Irreversibility on Investments in Online Learning

ERIC Educational Resources Information Center

Oslington, Paul

2004-01-01

Uncertainty and irreversibility are central to online learning projects, but have been neglected in the existing educational cost-benefit analysis literature. This paper builds some simple illustrative models of the impact of irreversibility and uncertainty, and shows how different types of cost and demand uncertainty can have substantial impacts…

Helping Your Child Learn Science.

ERIC Educational Resources Information Center

Paulu, Nancy; Martin, Margery

This book provides examples of a few simple activities that parents can do with their children. Being "scientific" is defined as being curious, observing, asking how things happen, and learning how to find the answers. This book suggests ways parents can interest their children from about 3 to 10 years of age in science. Included are (1)…

Teaching Young Children How to Sing: One School's Experience

ERIC Educational Resources Information Center

Kenney, Susan

2011-01-01

In many schools, classroom teachers are responsible for the music experiences of young children. Children may learn songs, but may not learn "how" to sing. This article outlines simple teaching strategies to help young children develop listening and vocal habits leading to beautiful singing. The article discusses how the kindergarten classes at…

Transition Matrices: A Tool to Assess Student Learning and Improve Instruction

ERIC Educational Resources Information Center

Morris, Gary A.; Walter, Paul; Skees, Spencer; Schwartz, Samantha

2017-01-01

This paper introduces a new spreadsheet tool for adoption by high school or college-level physics teachers who use common assessments in a pre-instruction/post-instruction mode to diagnose student learning and teaching effectiveness. The spreadsheet creates a simple matrix that identifies the percentage of students who select each possible…

Identifying What Matters

ERIC Educational Resources Information Center

Wardrip, Peter; Evancho, Jeffrey; McNamara, Annie

2018-01-01

A question like "what do you want your children to be like when they leave your class?" seems simple on the surface, but it quickly becomes complex when teachers are asked to name, prioritize, and document the kinds of student learning and engagement they value most. This article shares the ongoing work of a regional learning community…

Your Personal Learning Network: Professional Development on Demand

ERIC Educational Resources Information Center

Bauer, William I.

2010-01-01

Web 2.0 tools and resources can enhance our efficiency and effectiveness as music educators, supporting personal learning networks for ongoing professional growth and development. This article includes (a) an explanation of Really Simple Syndication (RSS) and the use of an RSS reader/aggregator; (b) a discussion of blogs, podcasts, wikis,…

Home and Away: The Use of Institutional and Non-Institutional Technologies to Support Learning and Teaching

ERIC Educational Resources Information Center

Flavin, Michael

2016-01-01

This paper examines the usage of institutional and non-institutional technologies to support learning and teaching in UK higher education. Previous work on disruptive technology and disruptive innovation has argued that users prefer simple and convenient technologies, and often repurpose technologies from designers' intentions; this paper…

20 CFR 416.968 - Skill requirements.

Code of Federal Regulations, 2014 CFR

2014-04-01

... which needs little or no judgment to do simple duties that can be learned on the job in a short period... materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30 days, and little specific vocational preparation and judgment are needed...

20 CFR 416.968 - Skill requirements.

Code of Federal Regulations, 2013 CFR

2013-04-01

... which needs little or no judgment to do simple duties that can be learned on the job in a short period... materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30 days, and little specific vocational preparation and judgment are needed...

20 CFR 416.968 - Skill requirements.

Code of Federal Regulations, 2012 CFR

2012-04-01

... which needs little or no judgment to do simple duties that can be learned on the job in a short period... materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30 days, and little specific vocational preparation and judgment are needed...

Physics Exams That Promote Collaborative Learning

ERIC Educational Resources Information Center

Wieman, Carl E.; Rieger, Georg W.; Heiner, Cynthia E.

2014-01-01

The two-stage exam is a relatively simple way to introduce collaborative learning and formative assessment into an exam. Their use is rapidly growing in the physics department at the University of British Columbia, as both students and faculty find them rewarding. In a two-stage exam students first complete and turn in the exam individually, and…

Learning and recall of form discriminations during reversible cooling deactivation of ventral-posterior suprasylvian cortex in the cat.

PubMed Central

Lomber, S G; Payne, B R; Cornwell, P

1996-01-01

Extrastriate visual cortex of the ventral-posterior suprasylvian gyrus (vPS cortex) of freely behaving cats was reversibly deactivated with cooling to determine its role in performance on a battery of simple or masked two-dimensional pattern discriminations, and three-dimensional object discriminations. Deactivation of vPS cortex by cooling profoundly impaired the ability of the cats to recall the difference between all previously learned pattern and object discriminations. However, the cats' ability to learn or relearn pattern and object discriminations while vPS was deactivated depended upon the nature of the pattern or object and the cats' prior level of exposure to them. During cooling of vPS cortex, the cats could neither learn the novel object discriminations nor relearn a highly familiar masked or partially occluded pattern discrimination, although they could relearn both the highly familiar object and simple pattern discriminations. These cooling-induced deficits resemble those induced by cooling of the topologically equivalent inferotemporal cortex of monkeys and provides evidence that the equivalent regions contribute to visual processing in similar ways. Images Fig. 1 Fig. 3 PMID:8643686

Development of Experience-based Visible-type Electromagnetic Teaching Materials

NASA Astrophysics Data System (ADS)

Suzuki, Masayoshi; Shima, Kenzou

Electromagnetism is the base of electrical engineering, however, it is one of the most difficult subjects to learn. The small experiments which show the principles of electricity visibly are useful technique to promote these comprehension. For classroom experimental materials to learn basic electromagnetism, we developed rotating magnetic field visualizer, gravity-use generators, simple motors, and electric-field visualizer. We report how we visualized the principles of motors and generators in classroom experiments. In particular, we discuss in detail how to visualize the mechanism of very simple motors. We have been demonstrating the motors in children science classes conducted all over Japan. We developed these experimental materials, and we achieved remarkable results using these materials in the electromagnetism class.

The beneficial effects of cognitive training with simple calculation and reading aloud in an elderly postsurgical population: study protocol for a randomized controlled trial.

PubMed

Kulason, Kay; Nouchi, Rui; Hoshikawa, Yasushi; Noda, Masafumi; Okada, Yoshinori; Kawashima, Ryuta

2016-07-22

This project proposes a pilot study to investigate the positive healing effects of cognitive training with simple arithmetic and reading aloud on elderly postsurgical patients. Elderly patients undergoing surgery have an increased risk of Postoperative Cognitive Decline (POCD), a condition in which learning, memory, and processing speed is greatly reduced after surgery. Since elderly patients are more likely to exhibit symptoms of POCD, the incidence is increasing as the population receiving surgery has aged. Little effort has been expended, however, to find treatments for POCD. Learning therapy, which consists of a combination of reading aloud and solving simple arithmetic problems, was developed in Japan as a treatment for Alzheimer's Disease to improve cognitive functions. Because patients with Alzheimer's Disease experience similar issues as those with POCD in learning, memory, and processing speed, a cognitive intervention based on the learning-therapy treatments used for Alzheimer's Disease could show advantageous outcomes for those at risk of POCD. Cognitive function will be measured before and after surgery using three different tests (Mini-Mental Status Exam, Frontal Assessment Battery, and Cogstate computerized tests). Subjects will be randomly divided into two groups-one that receives a Simple Calculation and Reading Aloud intervention (SCRA) and a waitlisted control group that does not receive SCRA. To measure cognition before and after the intervention, the previously mentioned three tests will be used. The obtained data will be analyzed using statistical tests such as ANCOVA to indicate whether the cognitive intervention group has made improvements in their cognitive functions. In addition, questionnaires will also be administered to collect data on mental and emotional statuses. This report will be the first pilot study to investigate the beneficial effects of SCRA on elderly surgical patients. Previous studies have shown sufficient evidence on the effectiveness of learning therapy in healthy elderly people and in those with Dementia. Therefore, this study will clarify whether SCRA can improve cognitive function in the more specialized group of elderly surgical patients. University Hospital Medical Information Network Clinical Trial Registry, UMIN000019832 . Registered on 18 November 2015.

Improving care for people with learning disabilities.

PubMed

Turner, Sue

2014-11-25

People with learning disabilities have poorer health than the general population and experience health inequalities - partly as a result of problems with accessing health services. Health services have a duty to address health inequalities, by making reasonable adjustments to their services so they are more accessible to people with learning disabilities, but this does not always happen. Failure to make reasonable adjustments can have significant adverse effects for people with learning disabilities and their families. Nurses are well placed to implement reasonable adjustments, many of which are simple to do and can save lives.

Acute effects of aerobic exercise promote learning

PubMed Central

Perini, Renza; Bortoletto, Marta; Capogrosso, Michela; Fertonani, Anna; Miniussi, Carlo

2016-01-01

The benefits that physical exercise confers on cardiovascular health are well known, whereas the notion that physical exercise can also improve cognitive performance has only recently begun to be explored and has thus far yielded only controversial results. In the present study, we used a sample of young male subjects to test the effects that a single bout of aerobic exercise has on learning. Two tasks were run: the first was an orientation discrimination task involving the primary visual cortex, and the second was a simple thumb abduction motor task that relies on the primary motor cortex. Forty-four and forty volunteers participated in the first and second experiments, respectively. We found that a single bout of aerobic exercise can significantly facilitate learning mechanisms within visual and motor domains and that these positive effects can persist for at least 30 minutes following exercise. This finding suggests that physical activity, at least of moderate intensity, might promote brain plasticity. By combining physical activity–induced plasticity with specific cognitive training–induced plasticity, we favour a gradual up-regulation of a functional network due to a steady increase in synaptic strength, promoting associative Hebbian-like plasticity. PMID:27146330

How much of reinforcement learning is working memory, not reinforcement learning? A behavioral, computational, and neurogenetic analysis

PubMed Central

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

2012-01-01

Instrumental learning involves corticostriatal circuitry and the dopaminergic system. This system is typically modeled in the reinforcement learning (RL) framework by incrementally accumulating reward values of states and actions. However, human learning also implicates prefrontal cortical mechanisms involved in higher level cognitive functions. The interaction of these systems remains poorly understood, and models of human behavior often ignore working memory (WM) and therefore incorrectly assign behavioral variance to the RL system. Here we designed a task that highlights the profound entanglement of these two processes, even in simple learning problems. By systematically varying the size of the learning problem and delay between stimulus repetitions, we separately extracted WM-specific effects of load and delay on learning. We propose a new computational model that accounts for the dynamic integration of RL and WM processes observed in subjects' behavior. Incorporating capacity-limited WM into the model allowed us to capture behavioral variance that could not be captured in a pure RL framework even if we (implausibly) allowed separate RL systems for each set size. The WM component also allowed for a more reasonable estimation of a single RL process. Finally, we report effects of two genetic polymorphisms having relative specificity for prefrontal and basal ganglia functions. Whereas the COMT gene coding for catechol-O-methyl transferase selectively influenced model estimates of WM capacity, the GPR6 gene coding for G-protein-coupled receptor 6 influenced the RL learning rate. Thus, this study allowed us to specify distinct influences of the high-level and low-level cognitive functions on instrumental learning, beyond the possibilities offered by simple RL models. PMID:22487033

Active learning strategies for the deduplication of electronic patient data using classification trees.

PubMed

Sariyar, M; Borg, A; Pommerening, K

2012-10-01

Supervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether a simple active learning strategy using binary comparison patterns is sufficient or if string metrics together with a more sophisticated algorithm are necessary to achieve high accuracies with a small training set. Based on medical registry data with different numbers of attributes, we used active learning to acquire training sets for classification trees, which were then used to classify the remaining data. Active learning for binary patterns means that every distinct comparison pattern represents a stratum from which one item is sampled. Active learning for patterns consisting of the Levenshtein string metric values uses an iterative process where the most informative and representative examples are added to the training set. In this context, we extended the active learning strategy by Sarawagi and Bhamidipaty (2002). On the original data set, active learning based on binary comparison patterns leads to the best results. When dropping four or six attributes, using string metrics leads to better results. In both cases, not more than 200 manually reviewed training examples are necessary. In record linkage applications where only forename, name and birthday are available as attributes, we suggest the sophisticated active learning strategy based on string metrics in order to achieve highly accurate results. We recommend the simple strategy if more attributes are available, as in our study. In both cases, active learning significantly reduces the amount of manual involvement in training data selection compared to usual record linkage settings. Copyright © 2012 Elsevier Inc. All rights reserved.

Behavioral semantics of learning and crossmodal processing in auditory cortex: the semantic processor concept.

PubMed

Scheich, Henning; Brechmann, André; Brosch, Michael; Budinger, Eike; Ohl, Frank W; Selezneva, Elena; Stark, Holger; Tischmeyer, Wolfgang; Wetzel, Wolfram

2011-01-01

Two phenomena of auditory cortex activity have recently attracted attention, namely that the primary field can show different types of learning-related changes of sound representation and that during learning even this early auditory cortex is under strong multimodal influence. Based on neuronal recordings in animal auditory cortex during instrumental tasks, in this review we put forward the hypothesis that these two phenomena serve to derive the task-specific meaning of sounds by associative learning. To understand the implications of this tenet, it is helpful to realize how a behavioral meaning is usually derived for novel environmental sounds. For this purpose, associations with other sensory, e.g. visual, information are mandatory to develop a connection between a sound and its behaviorally relevant cause and/or the context of sound occurrence. This makes it plausible that in instrumental tasks various non-auditory sensory and procedural contingencies of sound generation become co-represented by neuronal firing in auditory cortex. Information related to reward or to avoidance of discomfort during task learning, that is essentially non-auditory, is also co-represented. The reinforcement influence points to the dopaminergic internal reward system, the local role of which for memory consolidation in auditory cortex is well-established. Thus, during a trial of task performance, the neuronal responses to the sounds are embedded in a sequence of representations of such non-auditory information. The embedded auditory responses show task-related modulations of auditory responses falling into types that correspond to three basic logical classifications that may be performed with a perceptual item, i.e. from simple detection to discrimination, and categorization. This hierarchy of classifications determine the semantic "same-different" relationships among sounds. Different cognitive classifications appear to be a consequence of learning task and lead to a recruitment of different excitatory and inhibitory mechanisms and to distinct spatiotemporal metrics of map activation to represent a sound. The described non-auditory firing and modulations of auditory responses suggest that auditory cortex, by collecting all necessary information, functions as a "semantic processor" deducing the task-specific meaning of sounds by learning. © 2010. Published by Elsevier B.V.

Conflict-triggered top-down control: default mode, last resort, or no such thing?

PubMed

Bugg, Julie M

2014-03-01

The conflict monitoring account posits that globally high levels of conflict trigger engagement of top-down control; however, recent findings point to the mercurial nature of top-down control in high conflict contexts. The current study examined the potential moderating effect of associative learning on conflict-triggered top-down control engagement by testing the Associations as Antagonists to Top-Down Control (AATC) hypothesis. In 4 experiments, list-wide proportion congruence was manipulated, and conflict-triggered top-down control engagement was examined by comparing interference for frequency-matched, 50% congruent items across mostly congruent (low conflict) and mostly incongruent (high conflict) lists. Despite the fact that global levels of conflict were varied identically across experiments, evidence of conflict-triggered top-down control engagement was selective to those experiments in which responses could not be predicted on the majority of trials via simple associative learning, consistent with the AATC hypothesis. In a 5th experiment, older adults showed no evidence of top-down control engagement under conditions in which young adults did, a finding that refined the interpretation of the patterns observed in the prior experiments. Collectively, these findings suggest that top-down control engagement in high conflict contexts is neither the default mode nor an unused (or nonexistent) strategy. Top-down control is best characterized as a last resort that is engaged when reliance on one's environment, and in particular associative responding, is unproductive for achieving task goals.

Conflict-Triggered Top-Down Control: Default Mode, Last Resort, or No Such Thing?

PubMed Central

Bugg, Julie M.

2014-01-01

The conflict monitoring account posits that globally high levels of conflict trigger engagement of top-down control; however, recent findings point to the mercurial nature of top-down control in high conflict contexts. The current study examined the potential moderating effect of associative learning on conflict-triggered top-down control engagement by testing the Associations as Antagonists to Top-Down Control (AATC) hypothesis. In 4 experiments, list-wide proportion congruence was manipulated, and conflict-triggered top-down control engagement was examined by comparing interference for 50% congruent items across mostly congruent (low conflict) and mostly incongruent (high conflict) lists. Despite the fact that global levels of conflict were varied identically across experiments, evidence of conflict-triggered top-down control engagement was selective to those experiments in which responses could not be predicted on the majority of trials via simple associative learning, consistent with the AATC hypothesis. In a fifth experiment, older adults showed no evidence of top-down control engagement under conditions in which young adults did, a finding that refined the interpretation of the patterns observed in the prior experiments. Collectively, these findings suggest that top-down control engagement in high conflict contexts is neither the default mode nor an unused (or non-existent) strategy. Top-down control is best characterized as a last resort that is engaged when reliance on one’s environment, and in particular associative responding, is unproductive for achieving task goals. PMID:24274385

Classifying seismic noise and sources from OBS data using unsupervised machine learning

NASA Astrophysics Data System (ADS)

Mosher, S. G.; Audet, P.

2017-12-01

The paradigm of plate tectonics was established mainly by recognizing the central role of oceanic plates in the production and destruction of tectonic plates at their boundaries. Since that realization, however, seismic studies of tectonic plates and their associated deformation have slowly shifted their attention toward continental plates due to the ease of installation and maintenance of high-quality seismic networks on land. The result has been a much more detailed understanding of the seismicity patterns associated with continental plate deformation in comparison with the low-magnitude deformation patterns within oceanic plates and at their boundaries. While the number of high-quality ocean-bottom seismometer (OBS) deployments within the past decade has demonstrated the potential to significantly increase our understanding of tectonic systems in oceanic settings, OBS data poses significant challenges to many of the traditional data processing techniques in seismology. In particular, problems involving the detection, location, and classification of seismic sources occurring within oceanic settings are much more difficult due to the extremely noisy seafloor environment in which data are recorded. However, classifying data without a priori constraints is a problem that is routinely pursued via unsupervised machine learning algorithms, which remain robust even in cases involving complicated datasets. In this research, we apply simple unsupervised machine learning algorithms (e.g., clustering) to OBS data from the Cascadia Initiative in an attempt to classify and detect a broad range of seismic sources, including various noise sources and tremor signals occurring within ocean settings.

Acute Sleep Deprivation Blocks Short- and Long-Term Operant Memory in Aplysia.

PubMed

Krishnan, Harini C; Gandour, Catherine E; Ramos, Joshua L; Wrinkle, Mariah C; Sanchez-Pacheco, Joseph J; Lyons, Lisa C

2016-12-01

Insufficient sleep in individuals appears increasingly common due to the demands of modern work schedules and technology use. Consequently, there is a growing need to understand the interactions between sleep deprivation and memory. The current study determined the effects of acute sleep deprivation on short and long-term associative memory using the marine mollusk Aplysia californica , a relatively simple model system well known for studies of learning and memory. Aplysia were sleep deprived for 9 hours using context changes and tactile stimulation either prior to or after training for the operant learning paradigm, learning that food is inedible (LFI). The effects of sleep deprivation on short-term (STM) and long-term memory (LTM) were assessed. Acute sleep deprivation prior to LFI training impaired the induction of STM and LTM with persistent effects lasting at least 24 h. Sleep deprivation immediately after training blocked the consolidation of LTM. However, sleep deprivation following the period of molecular consolidation did not affect memory recall. Memory impairments were independent of handling-induced stress, as daytime handled control animals demonstrated no memory deficits. Additional training immediately after sleep deprivation failed to rescue the induction of memory, but additional training alleviated the persistent impairment in memory induction when training occurred 24 h following sleep deprivation. Acute sleep deprivation inhibited the induction and consolidation, but not the recall of memory. These behavioral studies establish Aplysia as an effective model system for studying the interactions between sleep and memory formation. © 2016 Associated Professional Sleep Societies, LLC.

Renewal after the punishment of free operant behavior.

PubMed

Bouton, Mark E; Schepers, Scott T

2015-01-01

Three experiments examined the role of context in punishment learning. In Experiment 1, rats were trained to lever press for food in Context A and then punished for responding in Context B (by presenting response-contingent footshock). Punishment led to complete suppression of the response. However, when responding was tested (in extinction) in Contexts A and B, a strong renewal of responding occurred in Context A. In Experiment 2, renewal also occurred when initial reinforcement occurred in Context A, punishment occurred in Context B, and testing occurred in a new context (Context C). In both experiments, behavioral suppression and renewal were not observed in groups that received noncontingent (yoked) footshocks in Context B. In Experiment 3, 2 responses (lever press and chain pull) were separately reinforced in Contexts A and B and then punished in the opposite context. Although the procedure equated the contexts on their association with reinforcement and punishment, renewal of each response was observed when it was tested in its nonpunished context. The contexts also influenced response choice. Overall, the results suggest that punishment is specific to the context in which it is learned, and establish that its context-specificity does not depend on a simple association between the context and shock. Like extinction, punishment may involve learning to inhibit a specific response in a specific context. Implications for theories of punishment and for understanding the cessation of problematic operant behavior (e.g., drug abuse) are discussed. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Learning styles, academic achievement, and mental health problems among medical students in Thailand.

PubMed

Paiboonsithiwong, Salilthip; Kunanitthaworn, Natchaya; Songtrijuck, Natchaphon; Wongpakaran, Nahathai; Wongpakaran, Tinakon

2016-01-01

This study aimed to investigate the prevalence of various learning styles among medical students and their correlations with academic achievement and mental health problems in these students. This study was conducted among 140 first-year medical students of Chiang Mai University, Thailand in 2014. The participants completed the visual-aural-read/write-kinesthetic (VARK) questionnaire, the results of which can be categorized into 4 modes, corresponding to how many of the 4 types are preferred by a respondent. The 10-item Perceived Stress Scale (PSS-10) and the 21-item Outcome Inventory (OI-21) were also used. The participants' demographic data, grade point average (GPA), and scores of all measurements are presented using simple statistics. Correlation and regression analysis were employed to analyze differences in the scores and to determine the associations among them. Sixty percent of the participants were female. The mean age was 18.86±0.74 years old. Quadmodal was found to be the most preferred VARK mode (43.6%). Unimodal, bimodal, and trimodal modes were preferred by 35%, 12.9%, and 18.6% of the participants, respectively. Among the strong unimodal learners, visual, aural, read/write, and kinesthetic preferences were reported by 4.3%, 7.1%, 11.4%, and 12.1% of participants, respectively. No difference was observed in the PSS-10, OI-anxiety, OI-depression, and OI-somatization scores according to the VARK modes, although a significant effect was found for OI-interpersonal (F=2.788, P=0.043). Moreover, neither VARK modes nor VARK types were correlated with GPA. The most preferred VARK learning style among medical students was quadmodal. Learning styles were not associated with GPA or mental health problems, except for interpersonal problems.

Learning styles, academic achievement, and mental health problems among medical students in Thailand

PubMed Central

2016-01-01

Purpose This study aimed to investigate the prevalence of various learning styles among medical students and their correlations with academic achievement and mental health problems in these students. Methods This study was conducted among 140 first-year medical students of Chiang Mai University, Thailand in 2014. The participants completed the visual-aural-read/write-kinesthetic (VARK) questionnaire, the results of which can be categorized into 4 modes, corresponding to how many of the 4 types are preferred by a respondent. The 10-item Perceived Stress Scale (PSS-10) and the 21-item Outcome Inventory (OI-21) were also used. The participants’ demographic data, grade point average (GPA), and scores of all measurements are presented using simple statistics. Correlation and regression analysis were employed to analyze differences in the scores and to determine the associations among them. Results Sixty percent of the participants were female. The mean age was 18.86±0.74 years old. Quadmodal was found to be the most preferred VARK mode (43.6%). Unimodal, bimodal, and trimodal modes were preferred by 35%, 12.9%, and 18.6% of the participants, respectively. Among the strong unimodal learners, visual, aural, read/write, and kinesthetic preferences were reported by 4.3%, 7.1%, 11.4%, and 12.1% of participants, respectively. No difference was observed in the PSS-10, OI-anxiety, OI-depression, and OI-somatization scores according to the VARK modes, although a significant effect was found for OI-interpersonal (F=2.788, P=0.043). Moreover, neither VARK modes nor VARK types were correlated with GPA. Conclusion The most preferred VARK learning style among medical students was quadmodal. Learning styles were not associated with GPA or mental health problems, except for interpersonal problems. PMID:27804284

[Depressive symptoms among medical intern students in a Brazilian public university].

PubMed

Costa, Edméa Fontes de Oliva; Santana, Ygo Santos; Santos, Ana Teresa Rodrigues de Abreu; Martins, Luiz Antonio Nogueira; Melo, Enaldo Vieira de; Andrade, Tarcísio Matos de

2012-01-01

To estimate, among Medical School intern students, the prevalence of depressive symptoms and their severity, as well as associated factors. Cross-sectional study in May 2008, with a representative sample of medical intern students (n = 84) from Universidade Federal de Sergipe (UFS). Beck Depression Inventory (BDI) and a structured questionnaire containing information on sociodemographic variables, teaching-learning process, and personal aspects were used. The exploratory data analysis was performed by descriptive and inferential statistics. Finally, the analysis of multiple variables by logistic regression and the calculation of simple and adjusted ORs with their respective 95% confidence intervals were performed. The general prevalence was 40.5%, with 1.2% (95% CI: 0.0-6.5) of severe depressive symptoms; 4.8% (95% CI: 1.3-11.7) of moderate depressive symptoms; and 34.5% (95% CI: 24.5-45.7) of mild depressive symptoms. The logistic regression revealed the variables with a major impact associated with the emergence of depressive symptoms: thoughts of dropping out (OR 6.24; p = 0.002); emotional stress (OR 7.43;p = 0.0004); and average academic performance (OR 4.74; p = 0.0001). The high prevalence of depressive symptoms in the study population was associated with variables related to the teaching-learning process and personal aspects, suggesting immediate preemptive measures regarding Medical School graduation and student care are required.

Case studies in pathophysiology: The development and evaluation of an interactive online learning environment to develop higher order thinking and argumentation

NASA Astrophysics Data System (ADS)

Titterington, Lynda C.

2007-12-01

This study presents a framework for examining the effects of higher order thinking on the achievement of allied health students enrolled in a pathophysiology course. A series of clinical case studies was developed and published in an enriched online environment that guided students through the process of developing a solution and supporting it through data analysis and interpretation. The series of case study modules scaffolded argumentation through question prompts. The modules began with a simple, direct problem and they became progressively more complex throughout the quarter. A control group was assigned a pencil-and-paper case study based upon recall. The case studies were scored for content accuracy and evidence of higher order thinking skills. Higher order thinking was measured using a rubric based upon the Toulmin argumentation pattern. The results indicated implementing a case study of either online or traditional format was associated with significant gains in achievement. The Web-enhanced case studies were associated with modest gains in knowledge acquisition. The argumentation scores across the series followed two trends: directed case studies were associated with higher levels of argumentation than ill-structured case studies, and there appeared to be an inverse relationship between the students' argumentation and content scores. The protocols developed for this study can serve as a template for a larger, extended investigation into student learning in the online environment.

Relationships between music training, speech processing, and word learning: a network perspective.

PubMed

Elmer, Stefan; Jäncke, Lutz

2018-03-15

Numerous studies have documented the behavioral advantages conferred on professional musicians and children undergoing music training in processing speech sounds varying in the spectral and temporal dimensions. These beneficial effects have previously often been associated with local functional and structural changes in the auditory cortex (AC). However, this perspective is oversimplified, in that it does not take into account the intrinsic organization of the human brain, namely, neural networks and oscillatory dynamics. Therefore, we propose a new framework for extending these previous findings to a network perspective by integrating multimodal imaging, electrophysiology, and neural oscillations. In particular, we provide concrete examples of how functional and structural connectivity can be used to model simple neural circuits exerting a modulatory influence on AC activity. In addition, we describe how such a network approach can be used for better comprehending the beneficial effects of music training on more complex speech functions, such as word learning. © 2018 New York Academy of Sciences.

The Parallel Episodic Processing (PEP) model: dissociating contingency and conflict adaptation in the item-specific proportion congruent paradigm.

PubMed

Schmidt, James R

2013-01-01

The present work introduces a computational model, the Parallel Episodic Processing (PEP) model, which demonstrates that contingency learning achieved via simple storage and retrieval of episodic memories can explain the item-specific proportion congruency effect in the colour-word Stroop paradigm. The current work also presents a new experimental procedure to more directly dissociate contingency biases from conflict adaptation (i.e., proportion congruency). This was done with three different types of incongruent words that allow a comparison of: (a) high versus low contingency while keeping proportion congruency constant, and (b) high versus low proportion congruency while keeping contingency constant. Results demonstrated a significant contingency effect, but no effect of proportion congruence. It was further shown that the proportion congruency associated with the colour does not matter, either. Thus, the results quite directly demonstrate that ISPC effects are not due to conflict adaptation, but instead to contingency learning biases. Copyright © 2012 Elsevier B.V. All rights reserved.

People use the memory for past-test heuristic as an explicit cue for judgments of learning.

PubMed

Serra, Michael J; Ariel, Robert

2014-11-01

When people estimate their memory for to-be-learned material over multiple study-test trials, they tend to base their judgments of learning (JOLs) on their test performance for those materials on the previous trial. Their use of this information-known as the memory for past-test (MPT) heuristic-is believed to be responsible for improvements in the relative accuracy (resolution) of people's JOLs across learning trials. Although participants seem to use past-test information as a major basis for their JOLs, little is known about how learners translate this information into a judgment of learning. Toward this end, in two experiments, we examined whether participants factored past-test performance into their JOLs in either an explicit, theory-based way or an implicit way. To do so, we had one group of participants (learners) study paired associates, make JOLs, and take a test on two study-test trials. Other participants (observers) viewed learners' protocols and made JOLs for the learners. Presumably, observers could only use theory-based information to make JOLs for the learners, which allowed us to estimate the contribution of explicit and implicit information to learners' JOLs. Our analyses suggest that all participants factored simple past-test performance into their JOLs in an explicit, theory-based way but that this information made limited contributions to improvements in relative accuracy across trials. In contrast, learners also used other privileged, implicit information about their learning to inform their judgments (that observers had no access to) that allowed them to achieve further improvements in relative accuracy across trials.

Simple and efficient machine learning frameworks for identifying protein-protein interaction relevant articles and experimental methods used to study the interactions.

PubMed

Agarwal, Shashank; Liu, Feifan; Yu, Hong

2011-10-03

Protein-protein interaction (PPI) is an important biomedical phenomenon. Automatically detecting PPI-relevant articles and identifying methods that are used to study PPI are important text mining tasks. In this study, we have explored domain independent features to develop two open source machine learning frameworks. One performs binary classification to determine whether the given article is PPI relevant or not, named "Simple Classifier", and the other one maps the PPI relevant articles with corresponding interaction method nodes in a standardized PSI-MI (Proteomics Standards Initiative-Molecular Interactions) ontology, named "OntoNorm". We evaluated our system in the context of BioCreative challenge competition using the standardized data set. Our systems are amongst the top systems reported by the organizers, attaining 60.8% F1-score for identifying relevant documents, and 52.3% F1-score for mapping articles to interaction method ontology. Our results show that domain-independent machine learning frameworks can perform competitively well at the tasks of detecting PPI relevant articles and identifying the methods that were used to study the interaction in such articles. Simple Classifier is available at http://sourceforge.net/p/simpleclassify/home/ and OntoNorm at http://sourceforge.net/p/ontonorm/home/.

English Spelling: The Simple, The Fancy, The Insane, The Tricky, and The Scrunched Up. "Great Idea" Reprint Series #612.

ERIC Educational Resources Information Center

McCabe, Don

The author explains the five-pronged approach to reading and spelling through classifying words into "simple,""fancy,""insane,""tricky," and "scrunched up" categories, and reports average gains of two grade levels in one semester by junior high school students with severe behavioral problems who learned the approach. Examples of the five word…

Physical Pendulum Experiments to Enhance the Understanding of Moments of Inertia and Simple Harmonic Motion

ERIC Educational Resources Information Center

Richardson, Tim H.; Brittle, Stuart A.

2012-01-01

This paper describes a set of experiments aimed at overcoming some of the difficulties experienced by students learning about the topics of moments of inertia and simple harmonic motion, both of which are often perceived to be complex topics amongst students during their first-year university courses. By combining both subjects in a discussion…

Simple and Inexpensive 3D Printed Filter Fluorometer Designs: User-Friendly Instrument Models for Laboratory Learning and Outreach Activities

ERIC Educational Resources Information Center

Porter, Lon A., Jr.; Chapman, Cole A.; Alaniz, Jacob A.

2017-01-01

In this work, a versatile and user-friendly selection of stereolithography (STL) files and computer-aided design (CAD) models are shared to assist educators and students in the production of simple and inexpensive 3D printed filter fluorometer instruments. These devices are effective resources for supporting active learners in the exploration of…

Some Key Issues in Creating Inquiry-Based Instructional Practices that Aim at the Understanding of Simple Electric Circuits

ERIC Educational Resources Information Center

Kock, Zeger-Jan; Taconis, Ruurd; Bolhuis, Sanneke; Gravemeijer, Koeno

2013-01-01

Many students in secondary schools consider the sciences difficult and unattractive. This applies to physics in particular, a subject in which students attempt to learn and understand numerous theoretical concepts, often without much success. A case in point is the understanding of the concepts current, voltage and resistance in simple electric…

Teach Deflection Concepts with Hacksaw Blades and Rubber Bands

ERIC Educational Resources Information Center

Roman, Harry T.

2013-01-01

Technology and engineering educators can use a simple hacksaw blade to help students learn about deflection, as that which occurs in a beam. Here the beam is fixed at one end and allowed to deflect in a manner that is easy to see and measure--the hacksaw blade represents a cantilever, an overhanging structure. This simple and very inexpensive…

Helping Graduate Teaching Assistants Lead Discussions with Undergraduate Students: A Few Simple Teaching Strategies

ERIC Educational Resources Information Center

Jensen, Murray; Farrand, Kirsten; Redman, Leanne; Varcoe, Tamara; Coleman, Leana

2005-01-01

Graduate Teaching Assistants (GTAs) are frequently asked to lead discussion groups. These groups generally take the form of tutorials, review sessions, or problem-based learning classes. In their preparation, what to teach is often emphasized over how to teach. The primary intent of this article is to provide a few simple teaching strategies for…

Enhancement of face recognition learning in patients with brain injury using three cognitive training procedures.

PubMed

Powell, Jane; Letson, Susan; Davidoff, Jules; Valentine, Tim; Greenwood, Richard

2008-04-01

Twenty patients with impairments of face recognition, in the context of a broader pattern of cognitive deficits, were administered three new training procedures derived from contemporary theories of face processing to enhance their learning of new faces: semantic association (being given additional verbal information about the to-be-learned faces); caricaturing (presentation of caricatured versions of the faces during training and veridical versions at recognition testing); and part recognition (focusing patients on distinctive features during the training phase). Using a within-subjects design, each training procedure was applied to a different set of 10 previously unfamiliar faces and entailed six presentations of each face. In a "simple exposure" control procedure (SE), participants were given six presentations of another set of faces using the same basic protocol but with no further elaboration. Order of the four procedures was counterbalanced, and each condition was administered on a different day. A control group of 12 patients with similar levels of face recognition impairment were trained on all four sets of faces under SE conditions. Compared to the SE condition, all three training procedures resulted in more accurate discrimination between the 10 studied faces and 10 distractor faces in a post-training recognition test. This did not reflect any intrinsic lesser memorability of the faces used in the SE condition, as evidenced by the comparable performance across face sets by the control group. At the group level, the three experimental procedures were of similar efficacy, and associated cognitive deficits did not predict which technique would be most beneficial to individual patients; however, there was limited power to detect such associations. Interestingly, a pure prosopagnosic patient who was tested separately showed benefit only from the part recognition technique. Possible mechanisms for the observed effects, and implications for rehabilitation, are discussed.

Fifth Graders' Learning About Simple Machines Through Engineering Design-Based Instruction Using LEGO™ Materials

NASA Astrophysics Data System (ADS)

Marulcu, Ismail; Barnett, Mike

2013-10-01

This study is part of a 5-year National Science Foundation-funded project, Transforming Elementary Science Learning Through LEGO™ Engineering Design. In this study, we report on the successes and challenges of implementing an engineering design-based and LEGO™-oriented unit in an urban classroom setting and we focus on the impact of the unit on students' content understanding of simple machines. The LEGO™ engineering-based simple machines module, which was developed for fifth graders by our research team, was implemented in an urban school in a large city in the Northeastern region of the USA. Thirty-three fifth grade students participated in the study, and they showed significant growth in content understanding. We measured students' content knowledge by using identical paper tests and semistructured interviews before and after instruction. Our paired t test analysis results showed that students significantly improved their test and interview scores (t = -3.62, p < 0.001 for multiple-choice items and t = -9.06, p < 0.000 for the open-ended items in the test and t = -12.11, p < 0.000 for the items in interviews). We also identified several alternative conceptions that are held by students on simple machines.

Distinct cerebellar engrams in short-term and long-term motor learning.

PubMed

Wang, Wen; Nakadate, Kazuhiko; Masugi-Tokita, Miwako; Shutoh, Fumihiro; Aziz, Wajeeha; Tarusawa, Etsuko; Lorincz, Andrea; Molnár, Elek; Kesaf, Sebnem; Li, Yun-Qing; Fukazawa, Yugo; Nagao, Soichi; Shigemoto, Ryuichi

2014-01-07

Cerebellar motor learning is suggested to be caused by long-term plasticity of excitatory parallel fiber-Purkinje cell (PF-PC) synapses associated with changes in the number of synaptic AMPA-type glutamate receptors (AMPARs). However, whether the AMPARs decrease or increase in individual PF-PC synapses occurs in physiological motor learning and accounts for memory that lasts over days remains elusive. We combined quantitative SDS-digested freeze-fracture replica labeling for AMPAR and physical dissector electron microscopy with a simple model of cerebellar motor learning, adaptation of horizontal optokinetic response (HOKR) in mouse. After 1-h training of HOKR, short-term adaptation (STA) was accompanied with transient decrease in AMPARs by 28% in target PF-PC synapses. STA was well correlated with AMPAR decrease in individual animals and both STA and AMPAR decrease recovered to basal levels within 24 h. Surprisingly, long-term adaptation (LTA) after five consecutive daily trainings of 1-h HOKR did not alter the number of AMPARs in PF-PC synapses but caused gradual and persistent synapse elimination by 45%, with corresponding PC spine loss by the fifth training day. Furthermore, recovery of LTA after 2 wk was well correlated with increase of PF-PC synapses to the control level. Our findings indicate that the AMPARs decrease in PF-PC synapses and the elimination of these synapses are in vivo engrams in short- and long-term motor learning, respectively, showing a unique type of synaptic plasticity that may contribute to memory consolidation.

ETHNOPRED: a novel machine learning method for accurate continental and sub-continental ancestry identification and population stratification correction.

PubMed

Hajiloo, Mohsen; Sapkota, Yadav; Mackey, John R; Robson, Paula; Greiner, Russell; Damaraju, Sambasivarao

2013-02-22

Population stratification is a systematic difference in allele frequencies between subpopulations. This can lead to spurious association findings in the case-control genome wide association studies (GWASs) used to identify single nucleotide polymorphisms (SNPs) associated with disease-linked phenotypes. Methods such as self-declared ancestry, ancestry informative markers, genomic control, structured association, and principal component analysis are used to assess and correct population stratification but each has limitations. We provide an alternative technique to address population stratification. We propose a novel machine learning method, ETHNOPRED, which uses the genotype and ethnicity data from the HapMap project to learn ensembles of disjoint decision trees, capable of accurately predicting an individual's continental and sub-continental ancestry. To predict an individual's continental ancestry, ETHNOPRED produced an ensemble of 3 decision trees involving a total of 10 SNPs, with 10-fold cross validation accuracy of 100% using HapMap II dataset. We extended this model to involve 29 disjoint decision trees over 149 SNPs, and showed that this ensemble has an accuracy of ≥ 99.9%, even if some of those 149 SNP values were missing. On an independent dataset, predominantly of Caucasian origin, our continental classifier showed 96.8% accuracy and improved genomic control's λ from 1.22 to 1.11. We next used the HapMap III dataset to learn classifiers to distinguish European subpopulations (North-Western vs. Southern), East Asian subpopulations (Chinese vs. Japanese), African subpopulations (Eastern vs. Western), North American subpopulations (European vs. Chinese vs. African vs. Mexican vs. Indian), and Kenyan subpopulations (Luhya vs. Maasai). In these cases, ETHNOPRED produced ensembles of 3, 39, 21, 11, and 25 disjoint decision trees, respectively involving 31, 502, 526, 242 and 271 SNPs, with 10-fold cross validation accuracy of 86.5% ± 2.4%, 95.6% ± 3.9%, 95.6% ± 2.1%, 98.3% ± 2.0%, and 95.9% ± 1.5%. However, ETHNOPRED was unable to produce a classifier that can accurately distinguish Chinese in Beijing vs. Chinese in Denver. ETHNOPRED is a novel technique for producing classifiers that can identify an individual's continental and sub-continental heritage, based on a small number of SNPs. We show that its learned classifiers are simple, cost-efficient, accurate, transparent, flexible, fast, applicable to large scale GWASs, and robust to missing values.