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

PubMed

Miconi, Thomas

2017-02-23

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

Optimizing The Number Of Steps In Learning Tasks For Complex Skills

ERIC Educational Resources Information Center

Nadolski, Rob J.; Kirschner, Paul A.; van Merrienboer, Jeroen J.G.

2005-01-01

Background: Carrying out whole tasks is often too difficult for novice learners attempting to acquire complex skills. The common solution is to split up the tasks into a number of smaller steps. The number of steps must be optimized for efficient and effective learning. Aim: The aim of the study is to investigate the relation between the number of…

Deficits of long-term memory in ecstasy users are related to cognitive complexity of the task.

PubMed

Brown, John; McKone, Elinor; Ward, Jeff

2010-03-01

Despite animal evidence that methylenedioxymethamphetamine (ecstasy) causes lasting damage in brain regions related to long-term memory, results regarding human memory performance have been variable. This variability may reflect the cognitive complexity of the memory tasks. However, previous studies have tested only a limited range of cognitive complexity. Furthermore, comparisons across different studies are made difficult by regional variations in ecstasy composition and patterns of use. The objective of this study is to evaluate ecstasy-related deficits in human verbal memory over a wide range of cognitive complexity using subjects drawn from a single geographical population. Ecstasy users were compared to non-drug using controls on verbal tasks with low cognitive complexity (stem completion), moderate cognitive complexity (stem-cued recall and word list learning) and high cognitive complexity (California Verbal Learning Test, Verbal Paired Associates and a novel Verbal Triplet Associates test). Where significant differences were found, both groups were also compared to cannabis users. More cognitively complex memory tasks were associated with clearer ecstasy-related deficits than low complexity tasks. In the most cognitively demanding task, ecstasy-related deficits remained even after multiple learning opportunities, whereas the performance of cannabis users approached that of non-drug using controls. Ecstasy users also had weaker deliberate strategy use than both non-drug and cannabis controls. Results were consistent with the proposal that ecstasy-related memory deficits are more reliable on tasks with greater cognitive complexity. This could arise either because such tasks require a greater contribution from the frontal lobe or because they require greater interaction between multiple brain regions.

Non-linguistic learning in aphasia: Effects of training method and stimulus characteristics

PubMed Central

Vallila-Rohter, Sofia; Kiran, Swathi

2013-01-01

Purpose The purpose of the current study was to explore non-linguistic learning ability in patients with aphasia, examining the impact of stimulus typicality and feedback on success with learning. Method Eighteen patients with aphasia and eight healthy controls participated in this study. All participants completed four computerized, non-linguistic category-learning tasks. We probed learning ability under two methods of instruction: feedback-based (FB) and paired-associate (PA). We also examined the impact of task complexity on learning ability, comparing two stimulus conditions: typical (Typ) and atypical (Atyp). Performance was compared between groups and across conditions. Results Results demonstrated that healthy controls were able to successfully learn categories under all conditions. For our patients with aphasia, two patterns of performance arose. One subgroup of patients was able to maintain learning across task manipulations and conditions. The other subgroup of patients demonstrated a sensitivity to task complexity, learning successfully only in the typical training conditions. Conclusions Results support the hypothesis that impairments of general learning are present in aphasia. Some patients demonstrated the ability to extract category information under complex training conditions, while others learned only under conditions that were simplified and emphasized salient category features. Overall, the typical training condition facilitated learning for all participants. Findings have implications for therapy, which are discussed. PMID:23695914

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.

Incremental learning of skill collections based on intrinsic motivation

PubMed Central

Metzen, Jan H.; Kirchner, Frank

2013-01-01

Life-long learning of reusable, versatile skills is a key prerequisite for embodied agents that act in a complex, dynamic environment and are faced with different tasks over their lifetime. We address the question of how an agent can learn useful skills efficiently during a developmental period, i.e., when no task is imposed on him and no external reward signal is provided. Learning of skills in a developmental period needs to be incremental and self-motivated. We propose a new incremental, task-independent skill discovery approach that is suited for continuous domains. Furthermore, the agent learns specific skills based on intrinsic motivation mechanisms that determine on which skills learning is focused at a given point in time. We evaluate the approach in a reinforcement learning setup in two continuous domains with complex dynamics. We show that an intrinsically motivated, skill learning agent outperforms an agent which learns task solutions from scratch. Furthermore, we compare different intrinsic motivation mechanisms and how efficiently they make use of the agent's developmental period. PMID:23898265

A 1-night operant learning task without food-restriction differentiates among mouse strains in an automated home-cage environment.

PubMed

Remmelink, Esther; Loos, Maarten; Koopmans, Bastijn; Aarts, Emmeke; van der Sluis, Sophie; Smit, August B; Verhage, Matthijs

2015-04-15

Individuals are able to change their behavior based on its consequences, a process involving instrumental learning. Studying instrumental learning in mice can provide new insights in this elementary aspect of cognition. Conventional appetitive operant learning tasks that facilitate the study of this form of learning in mice, as well as more complex operant paradigms, require labor-intensive handling and food deprivation to motivate the animals. Here, we describe a 1-night operant learning protocol that exploits the advantages of automated home-cage testing and circumvents the interfering effects of food restriction. The task builds on behavior that is part of the spontaneous exploratory repertoire during the days before the task. We compared the behavior of C57BL/6J, BALB/cJ and DBA/2J mice and found various differences in behavior during this task, but no differences in learning curves. BALB/cJ mice showed the largest instrumental learning response, providing a superior dynamic range and statistical power to study instrumental learning by using this protocol. Insights gained with this home-cage-based learning protocol without food restriction will be valuable for the development of other, more complex, cognitive tasks in automated home-cages. Copyright © 2015 Elsevier B.V. All rights reserved.

Action observation versus motor imagery in learning a complex motor task: a short review of literature and a kinematics study.

PubMed

Gatti, R; Tettamanti, A; Gough, P M; Riboldi, E; Marinoni, L; Buccino, G

2013-04-12

Both motor imagery and action observation have been shown to play a role in learning or re-learning complex motor tasks. According to a well accepted view they share a common neurophysiological basis in the mirror neuron system. Neurons within this system discharge when individuals perform a specific action and when they look at another individual performing the same or a motorically related action. In the present paper, after a short review of literature on the role of action observation and motor imagery in motor learning, we report the results of a kinematics study where we directly compared motor imagery and action observation in learning a novel complex motor task. This involved movement of the right hand and foot in the same angular direction (in-phase movement), while at the same time moving the left hand and foot in an opposite angular direction (anti-phase movement), all at a frequency of 1Hz. Motor learning was assessed through kinematics recording of wrists and ankles. The results showed that action observation is better than motor imagery as a strategy for learning a novel complex motor task, at least in the fast early phase of motor learning. We forward that these results may have important implications in educational activities, sport training and neurorehabilitation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Sonification and haptic feedback in addition to visual feedback enhances complex motor task learning.

PubMed

Sigrist, Roland; Rauter, Georg; Marchal-Crespo, Laura; Riener, Robert; Wolf, Peter

2015-03-01

Concurrent augmented feedback has been shown to be less effective for learning simple motor tasks than for complex tasks. However, as mostly artificial tasks have been investigated, transfer of results to tasks in sports and rehabilitation remains unknown. Therefore, in this study, the effect of different concurrent feedback was evaluated in trunk-arm rowing. It was then investigated whether multimodal audiovisual and visuohaptic feedback are more effective for learning than visual feedback only. Naïve subjects (N = 24) trained in three groups on a highly realistic virtual reality-based rowing simulator. In the visual feedback group, the subject's oar was superimposed to the target oar, which continuously became more transparent when the deviation between the oars decreased. Moreover, a trace of the subject's trajectory emerged if deviations exceeded a threshold. The audiovisual feedback group trained with oar movement sonification in addition to visual feedback to facilitate learning of the velocity profile. In the visuohaptic group, the oar movement was inhibited by path deviation-dependent braking forces to enhance learning of spatial aspects. All groups significantly decreased the spatial error (tendency in visual group) and velocity error from baseline to the retention tests. Audiovisual feedback fostered learning of the velocity profile significantly more than visuohaptic feedback. The study revealed that well-designed concurrent feedback fosters complex task learning, especially if the advantages of different modalities are exploited. Further studies should analyze the impact of within-feedback design parameters and the transferability of the results to other tasks in sports and rehabilitation.

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

Heuristic Task Analysis on E-Learning Course Development: A Formative Research Study

ERIC Educational Resources Information Center

Lee, Ji-Yeon; Reigeluth, Charles M.

2009-01-01

Utilizing heuristic task analysis (HTA), a method developed for eliciting, analyzing, and representing expertise in complex cognitive tasks, a formative research study was conducted on the task of e-learning course development to further improve the HTA process. Three instructional designers from three different post-secondary institutions in the…

Task Complexity, the Cognition Hypothesis, and Interaction in CMC and FTF Environments

ERIC Educational Resources Information Center

Baralt, Melissa Lorrain

2010-01-01

The construct of cognitive complexity has played an increasingly important role in studies on task design, which aim to explore how increases in the cognitive complexity of tasks differentially mediate interaction and learning outcomes (Kim, 2009; Gilabert, Baron, & Llanes, 2009; Kim & Tracy-Ventura, forthcoming; Nuevo, 2006; Revesz, 2009,…

Learning to multitask: effects of video game practice on electrophysiological indices of attention and resource allocation.

PubMed

Maclin, Edward L; Mathewson, Kyle E; Low, Kathy A; Boot, Walter R; Kramer, Arthur F; Fabiani, Monica; Gratton, Gabriele

2011-09-01

Changes in attention allocation with complex task learning reflect processing automatization and more efficient control. We studied these changes using ERP and EEG spectral analyses in subjects playing Space Fortress, a complex video game comprising standard cognitive task components. We hypothesized that training would free up attentional resources for a secondary auditory oddball task. Both P3 and delta EEG showed a processing trade-off between game and oddball tasks, but only some game events showed reduced attention requirements with practice. Training magnified a transient increase in alpha power following both primary and secondary task events. This contrasted with alpha suppression observed when the oddball task was performed alone, suggesting that alpha may be related to attention switching. Hence, P3 and EEG spectral data are differentially sensitive to changes in attentional processing occurring with complex task training. Copyright © 2011 Society for Psychophysiological Research.

Sleep Consolidates Motor Learning of Complex Movement Sequences in Mice.

PubMed

Nagai, Hirotaka; de Vivo, Luisa; Bellesi, Michele; Ghilardi, Maria Felice; Tononi, Giulio; Cirelli, Chiara

2017-02-01

Sleep-dependent consolidation of motor learning has been extensively studied in humans, but it remains unclear why some, but not all, learned skills benefit from sleep. Here, we compared 2 different motor tasks, both requiring the mice to run on an accelerating device. In the rotarod task, mice learn to maintain balance while running on a small rod, while in the complex wheel task, mice run on an accelerating wheel with an irregular rung pattern. In the rotarod task, performance improved to the same extent after sleep or after sleep deprivation (SD). Overall, using 7 different experimental protocols (41 sleep deprived mice, 26 sleeping controls), we found large interindividual differences in the learning and consolidation of the rotarod task, but sleep before/after training did not account for this variability. By contrast, using the complex wheel, we found that sleep after training, relative to SD, led to better performance from the beginning of the retest session, and longer sleep was correlated with greater subsequent performance. As in humans, the effects of sleep showed large interindividual variability and varied between fast and slow learners, with sleep favoring the preservation of learned skills in fast learners and leading to a net offline gain in the performance in slow learners. Using Fos expression as a proxy for neuronal activation, we also found that complex wheel training engaged motor cortex and hippocampus more than the rotarod training. Sleep specifically consolidates a motor skill that requires complex movement sequences and strongly engages both motor cortex and hippocampus. © Sleep Research Society 2016. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Transfer of perceptual learning between different visual tasks

PubMed Central

McGovern, David P.; Webb, Ben S.; Peirce, Jonathan W.

2012-01-01

Practice in most sensory tasks substantially improves perceptual performance. A hallmark of this ‘perceptual learning' is its specificity for the basic attributes of the trained stimulus and task. Recent studies have challenged the specificity of learned improvements, although transfer between substantially different tasks has yet to be demonstrated. Here, we measure the degree of transfer between three distinct perceptual tasks. Participants trained on an orientation discrimination, a curvature discrimination, or a ‘global form' task, all using stimuli comprised of multiple oriented elements. Before and after training they were tested on all three and a contrast discrimination control task. A clear transfer of learning was observed, in a pattern predicted by the relative complexity of the stimuli in the training and test tasks. Our results suggest that sensory improvements derived from perceptual learning can transfer between very different visual tasks. PMID:23048211

Transfer of perceptual learning between different visual tasks.

PubMed

McGovern, David P; Webb, Ben S; Peirce, Jonathan W

2012-10-09

Practice in most sensory tasks substantially improves perceptual performance. A hallmark of this 'perceptual learning' is its specificity for the basic attributes of the trained stimulus and task. Recent studies have challenged the specificity of learned improvements, although transfer between substantially different tasks has yet to be demonstrated. Here, we measure the degree of transfer between three distinct perceptual tasks. Participants trained on an orientation discrimination, a curvature discrimination, or a 'global form' task, all using stimuli comprised of multiple oriented elements. Before and after training they were tested on all three and a contrast discrimination control task. A clear transfer of learning was observed, in a pattern predicted by the relative complexity of the stimuli in the training and test tasks. Our results suggest that sensory improvements derived from perceptual learning can transfer between very different visual tasks.

Task Complexity, Focus on L2 Constructions, and Individual Differences: A Classroom-Based Study

ERIC Educational Resources Information Center

Revesz, Andrea

2011-01-01

Motivated by cognitive-interactionist frameworks for task-based learning, this study explores whether task complexity affects the extent to which learners focus on form-meaning connections during task-based work in a classroom setting, and whether this relationship is modulated by 3 individual difference factors--linguistic self-confidence,…

The Impact of Cognitive Complexity on Feedback Efficacy during Online Versus Face-to-Face Interactive Tasks

ERIC Educational Resources Information Center

Baralt, Melissa

2013-01-01

Informed by the cognition hypothesis (Robinson, 2011), recent studies indicate that more cognitively complex tasks can result in better incorporation of feedback during interaction and, as a consequence, more learning. It is not known, however, how task complexity and feedback work together in computerized environments. The present study addressed…

Explicit pre-training instruction does not improve implicit perceptual-motor sequence learning

PubMed Central

Sanchez, Daniel J.; Reber, Paul J.

2012-01-01

Memory systems theory argues for separate neural systems supporting implicit and explicit memory in the human brain. Neuropsychological studies support this dissociation, but empirical studies of cognitively healthy participants generally observe that both kinds of memory are acquired to at least some extent, even in implicit learning tasks. A key question is whether this observation reflects parallel intact memory systems or an integrated representation of memory in healthy participants. Learning of complex tasks in which both explicit instruction and practice is used depends on both kinds of memory, and how these systems interact will be an important component of the learning process. Theories that posit an integrated, or single, memory system for both types of memory predict that explicit instruction should contribute directly to strengthening task knowledge. In contrast, if the two types of memory are independent and acquired in parallel, explicit knowledge should have no direct impact and may serve in a “scaffolding” role in complex learning. Using an implicit perceptual-motor sequence learning task, the effect of explicit pre-training instruction on skill learning and performance was assessed. Explicit pre-training instruction led to robust explicit knowledge, but sequence learning did not benefit from the contribution of pre-training sequence memorization. The lack of an instruction benefit suggests that during skill learning, implicit and explicit memory operate independently. While healthy participants will generally accrue parallel implicit and explicit knowledge in complex tasks, these types of information appear to be separately represented in the human brain consistent with multiple memory systems theory. PMID:23280147

Effect of tDCS on task relevant and irrelevant perceptual learning of complex objects.

PubMed

Van Meel, Chayenne; Daniels, Nicky; de Beeck, Hans Op; Baeck, Annelies

2016-01-01

During perceptual learning the visual representations in the brain are altered, but these changes' causal role has not yet been fully characterized. We used transcranial direct current stimulation (tDCS) to investigate the role of higher visual regions in lateral occipital cortex (LO) in perceptual learning with complex objects. We also investigated whether object learning is dependent on the relevance of the objects for the learning task. Participants were trained in two tasks: object recognition using a backward masking paradigm and an orientation judgment task. During both tasks, an object with a red line on top of it were presented in each trial. The crucial difference between both tasks was the relevance of the object: the object was relevant for the object recognition task, but not for the orientation judgment task. During training, half of the participants received anodal tDCS stimulation targeted at the lateral occipital cortex (LO). Afterwards, participants were tested on how well they recognized the trained objects, the irrelevant objects presented during the orientation judgment task and a set of completely new objects. Participants stimulated with tDCS during training showed larger improvements of performance compared to participants in the sham condition. No learning effect was found for the objects presented during the orientation judgment task. To conclude, this study suggests a causal role of LO in relevant object learning, but given the rather low spatial resolution of tDCS, more research on the specificity of this effect is needed. Further, mere exposure is not sufficient to train object recognition in our paradigm.

Cognitive Load Theory: A Broader View on the Role of Memory in Learning and Education

ERIC Educational Resources Information Center

Paas, Fred; Ayres, Paul

2014-01-01

According to cognitive load theory (CLT), the limitations of working memory (WM) in the learning of new tasks together with its ability to cooperate with an unlimited long-term memory (LTM) for familiar tasks enable human beings to deal effectively with complex problems and acquire highly complex knowledge and skills. With regard to WM, CLT has…

The Effect of Focus on Form and Task Complexity on L2 Learners' Oral Task Performance

ERIC Educational Resources Information Center

Salimi, Asghar

2015-01-01

Second Language learners' oral task performance has been one of interesting and research generating areas of investigations in the field of second language acquisition specially, task-based language teaching and learning. The main purpose of the present study is to investigate the effect of focus on form and task complexity on L2 learners' oral…

Learnable Interfaces--Leveraging Navigation by Design

ERIC Educational Resources Information Center

Swanson, Kari Gunvaldson

2012-01-01

Complex productivity applications that integrate tasks in the workplace are becoming more common. Usability typically focuses on short-term, immediate measures of task performance. This study incorporates a long-term goal of more durable learning, focusing on implicit learning (spontaneous, unplanned, usually unconscious learning as a result of…

Self-Control of Task Difficulty during Training Enhances Motor Learning of a Complex Coincidence-Anticipation Task

ERIC Educational Resources Information Center

Andrieux, Mathieu; Danna, Jeremy; Thon, Bernard

2012-01-01

The aim of the present work was to analyze the influence of self-controlled task difficulty on motor learning. Participants had to intercept three targets falling at different velocities by displacing a stylus above a digitizer. Task difficulty corresponded to racquet width. Half the participants (self-control condition) could choose the racquet…

Sleep-Dependent Learning and Motor-Skill Complexity

ERIC Educational Resources Information Center

Kuriyama, Kenichi; Stickgold, Robert; Walker, Matthew P.

2004-01-01

Learning of a procedural motor-skill task is known to progress through a series of unique memory stages. Performance initially improves during training, and continues to improve, without further rehearsal, across subsequent periods of sleep. Here, we investigate how this delayed sleep-dependent learning is affected when the task characteristics…

Continuously Adaptive vs. Discrete Changes of Task Difficulty in the Training of a Complex Perceptual-Motor Task.

ERIC Educational Resources Information Center

Wood, Milton E.

The purpose of the effort was to determine the benefits to be derived from the adaptive training technique of automatically adjusting task difficulty as a function of a student skill during early learning of a complex perceptual motor task. A digital computer provided the task dynamics, scoring, and adaptive control of a second-order, two-axis,…

Task Complexity, Learning Opportunities, and Korean EFL Learners' Question Development

ERIC Educational Resources Information Center

Kim, YouJin

2012-01-01

Building on the cognitive and interactive perspectives of task research, the cognition hypothesis states that increasing task complexity promotes greater interaction and feedback and thus facilitates second language (L2) development (Robinson, 2001b, 2007a). To date, very little research has explored this claim during learner-learner interactions…

Task Complexity, Student Perceptions of Vocabulary Learning in EFL, and Task Performance

ERIC Educational Resources Information Center

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

2013-01-01

Background: The study deepened our understanding of how students' self-ef?cacy beliefs contribute to the context of teaching English as a foreign language in the framework of cognitive mediational paradigm at a ?ne-tuned task-speci?c level. Aim: The aim was to examine the relationship among task complexity, self-ef?cacy beliefs, domain-related…

Conceptual and Socio-Cognitive Support for Collaborative Learning in Videoconferencing Environments

ERIC Educational Resources Information Center

Ertl, Bernhard; Fischer, Frank; Mandl, Heinz

2006-01-01

Studies have shown that videoconferencing is an effective medium for facilitating communication between parties who are separated by distance, particularly when learners are engaged in complex collaborative learning tasks. However, as in face-to-face communication, learners benefit most when they receive additional support for such learning tasks.…

A Methodology for Assessing Learning in Complex and Ill-Structured Task Domains

ERIC Educational Resources Information Center

Spector, J. Michael

2006-01-01

New information and communications technologies and research in cognitive science have led to new ways to think about and implement learning environments. Among these new approaches to instruction and new methods to support learning and performance is an interest in and emphasis on complex subject matter (e.g., complex and dynamic systems…

Effects of noise frequency on performance and annoyance for women and men

NASA Technical Reports Server (NTRS)

Key, K. F.; Payne, M. C., Jr.

1981-01-01

Effects of noise frequencies on both performance on a complex psychomotor task and annoyance were investigated for men (n = 30) and women (n = 30). Each subject performed a complex psychomotor task for 50 min in the presence of low-frequency noise, high-frequency noise, or ambient noise. Women and men learned the task at different rates. Little effect of noise was shown. Annoyance ratings were subsequently obtained from each subject for noises of various frequencies by the method of magnitude estimation. High-frequency noises were more annoying than low-frequency noises regardless of sex and immediate prior exposure to noise. Sex differences in annoyance did not occur. No direct relationship between learning to perform a complex task while exposed to noise and annoyance by that noise was demonstrated.

Preserved complex emotion-based learning in amnesia.

PubMed

Turnbull, Oliver H; Evans, Cathryn E Y

2006-01-01

An important role for emotion in decision-making has recently been highlighted by disruptions in problem solving abilities after lesion to the frontal lobes. Such complex decision-making skills appear to be based on a class of memory ability (emotion-based learning) that may be anatomically independent of hippocampally mediated episodic memory systems. There have long been reports of intact emotion-based learning in amnesia, arguably dating back to the classic report of Claparede. However, all such accounts relate to relatively simple patterns of emotional valence learning, rather than the more complex contingency patterns of emotional experience, which characterise everyday life. A patient, SL, who had a profound anterograde amnesia following posterior cerebral artery infarction, performed a measure of complex emotion-based learning (the Iowa Gambling Task) on three separate occasions. Despite his severe episodic memory impairment, he showed normal levels of performance on the Gambling Task, at levels comparable or better than controls-including learning that persisted across substantial periods of time (weeks). Thus, emotion-based learning systems appear able to encode, and sustain, more sophisticated patterns of valence learning than have previously been reported.

Implicit learning and emotional responses in nine-month-old infants.

PubMed

Angulo-Barroso, Rosa M; Peciña, Susana; Lin, Xu; Li, Mingyan; Sturza, Julia; Shao, Jie; Lozoff, Betsy

2017-08-01

To study the interplay between motor learning and emotional responses of young infants, we developed a contingent learning paradigm that included two related, difficult, operant tasks. We also coded facial expression to characterise emotional response to learning. In a sample of nine-month-old healthy Chinese infants, 44.7% achieved learning threshold during this challenging arm-conditioning test. Some evidence of learning was observed at the beginning of the second task. The lowest period of negative emotions coincided with the period of maximum movement responses after the initiation of the second task, and movement responses negatively correlated with the frequency of negative emotions. Positive emotions, while generally low throughout the task, increased during peak performance especially for learners. Peak frequency of movement responses was positively correlated with the frequency of positive emotions. Despite the weak evidence of learning this difficult task, our results from the learners would suggest that increasing positive emotions, and perhaps down-regulating negative emotional responses, may be important for improving performance and learning a complex operant task in infancy. Further studies are necessary to determine the role of emotions in learning difficult tasks in infancy.

Task Complexity, Epistemological Beliefs and Metacognitive Calibration: An Exploratory Study

ERIC Educational Resources Information Center

Stahl, Elmar; Pieschl, Stephanie; Bromme, Rainer

2006-01-01

This article presents an explorative study, which is part of a comprehensive project to examine the impact of epistemological beliefs on metacognitive calibration during learning processes within a complex hypermedia information system. More specifically, this study investigates: 1) if learners differentiate between tasks of different complexity,…

Item Mass and Complexity and the Arithmetic Computation of Students with Learning Disabilities.

ERIC Educational Resources Information Center

Cawley, John F.; Shepard, Teri; Smith, Maureen; Parmar, Rene S.

1997-01-01

The performance of 76 students (ages 10 to 15) with learning disabilities on four tasks of arithmetic computation within each of the four basic operations was examined. Tasks varied in difficulty level and number of strokes needed to complete all items. Intercorrelations between task sets and operations were examined as was the use of…

Effects of Strategy Instruction on the Learning, Use, and Vertical Transfer of Strategies.

ERIC Educational Resources Information Center

Finley, Fred N.; Smith, Edward L.

1980-01-01

Compares group differences in strategy learning, use, and transfer to a more complex task for two groups of elementary students (N=48). Asked to perform three tasks in classifying igneous rocks, the groups differed in whether they received advice on the use of a specific strategy for performing each task. (CS)

Effects of Peer-Tutor Competences on Learner Cognitive Load and Learning Performance during Knowledge Sharing

ERIC Educational Resources Information Center

Hsiao, Ya-Ping; Brouns, Francis; van Bruggen, Jan; Sloep, Peter B.

2012-01-01

In Learning Networks, learners need to share knowledge with others to build knowledge. In particular, when working on complex tasks, they often need to acquire extra cognitive resources from others to process a high task load. However, without support high task load and organizing knowledge sharing themselves might easily overload learners'…

Toward a Learning Science for Complex Crowdsourcing Tasks

ERIC Educational Resources Information Center

Doroudi, Shayan; Kamar, Ece; Brunskill, Emma; Horvitz, Eric

2016-01-01

We explore how crowdworkers can be trained to tackle complex crowdsourcing tasks. We are particularly interested in training novice workers to perform well on solving tasks in situations where the space of strategies is large and workers need to discover and try different strategies to be successful. In a first experiment, we perform a comparison…

Memory Indexing: A Novel Method for Tracing Memory Processes in Complex Cognitive Tasks

ERIC Educational Resources Information Center

Renkewitz, Frank; Jahn, Georg

2012-01-01

We validate an eye-tracking method applicable for studying memory processes in complex cognitive tasks. The method is tested with a task on probabilistic inferences from memory. It provides valuable data on the time course of processing, thus clarifying previous results on heuristic probabilistic inference. Participants learned cue values of…

Quantum Speedup for Active Learning Agents

NASA Astrophysics Data System (ADS)

Paparo, Giuseppe Davide; Dunjko, Vedran; Makmal, Adi; Martin-Delgado, Miguel Angel; Briegel, Hans J.

2014-07-01

Can quantum mechanics help us build intelligent learning agents? A defining signature of intelligent behavior is the capacity to learn from experience. However, a major bottleneck for agents to learn in real-life situations is the size and complexity of the corresponding task environment. Even in a moderately realistic environment, it may simply take too long to rationally respond to a given situation. If the environment is impatient, allowing only a certain time for a response, an agent may then be unable to cope with the situation and to learn at all. Here, we show that quantum physics can help and provide a quadratic speedup for active learning as a genuine problem of artificial intelligence. This result will be particularly relevant for applications involving complex task environments.

Clinical quality needs complex adaptive systems and machine learning.

PubMed

Marsland, Stephen; Buchan, Iain

2004-01-01

The vast increase in clinical data has the potential to bring about large improvements in clinical quality and other aspects of healthcare delivery. However, such benefits do not come without cost. The analysis of such large datasets, particularly where the data may have to be merged from several sources and may be noisy and incomplete, is a challenging task. Furthermore, the introduction of clinical changes is a cyclical task, meaning that the processes under examination operate in an environment that is not static. We suggest that traditional methods of analysis are unsuitable for the task, and identify complexity theory and machine learning as areas that have the potential to facilitate the examination of clinical quality. By its nature the field of complex adaptive systems deals with environments that change because of the interactions that have occurred in the past. We draw parallels between health informatics and bioinformatics, which has already started to successfully use machine learning methods.

Learner-controlled practice difficulty in the training of a complex task: cognitive and motivational mechanisms.

PubMed

Hughes, Michael G; Day, Eric Anthony; Wang, Xiaoqian; Schuelke, Matthew J; Arsenault, Matthew L; Harkrider, Lauren N; Cooper, Olivia D

2013-01-01

An inherent aspect of learner-controlled instructional environments is the ability of learners to affect the degree of difficulty faced during training. However, research has yet to examine how learner-controlled practice difficulty affects learning. Based on the notion of desirable difficulties (Bjork, 1994), this study examined the cognitive and motivational antecedents and outcomes of learner-controlled practice difficulty in relation to learning a complex task. Using a complex videogame involving both strong cognitive and psychomotor demands, 112 young adult males were given control over their practice difficulty, which was reflected in the complexity of the training task. Results show that general mental ability, prior experience, pre-training self-efficacy, and error encouragement were positively related to learner-controlled practice difficulty. In turn, practice difficulty was directly related to task knowledge and post-training performance, and it was related to adaptive performance through the mediating influences of task knowledge and post-training performance. In general, this study supports the notion that training difficulty operationalized in terms of task complexity is positively related to both knowledge and performance outcomes. Results are discussed with respect to the need for more research examining how task complexity and other forms of difficulty could be leveraged to advance learner-controlled instructional practices. PsycINFO Database Record (c) 2013 APA, all rights reserved.

[Reverse learning in WAG/Rij rats with depression-like behavior].

PubMed

Malyshev, A V; Zakharov, A M; Sarkisova, K Iu; Dubynin, V A

2012-01-01

Learning and reverse learning in a complex maze, behavior in the open field test, novelty-suppressed feeding test, and forced swimming test were studies in WAG/Rij and Wistar rats. As compared with Wistar rats, WAG/Rij rats more slowly learned the spatial task, more slowly performed in the learning and reverse learning tasks, and made more errors in the complex maze (18% of WAG/Rij rats didn't reach learning criterion). Moreover, WAG/Rij rats exhibited reduced grooming reactions in the open field test, longer latency of approaching to food in the novel open field, reduced amount of food consumed in the home cage in the novelty-suppressed feeding test, and increased immobility time in the forced swimming test. The results suggest cognitive impaiment in WAG/Rij rats with depression-like behavior.

Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame

PubMed Central

Basak, Chandramallika; Voss, Michelle W.; Erickson, Kirk I.; Boot, Walter R.; Kramer, Arthur F.

2015-01-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also be useful in predicting the acquisition of skill in complex tasks, such as strategy-based video games. Twenty older adults were trained for over 20 hours to play Rise of Nations, a complex real-time strategy game. These adults showed substantial improvements over the training period in game performance. MRI scans obtained prior to training revealed that the volume of a number of brain regions, which have been previously associated with subsets of the trained skills, predicted a substantial amount of variance in learning on the complex game. Thus, regional differences in brain volume can predict learning in complex tasks that entail the use of a variety of perceptual, cognitive and motor processes. PMID:21546146

Regional differences in brain volume predict the acquisition of skill in a complex real-time strategy videogame.

PubMed

Basak, Chandramallika; Voss, Michelle W; Erickson, Kirk I; Boot, Walter R; Kramer, Arthur F

2011-08-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also be useful in predicting the acquisition of skill in complex tasks, such as strategy-based video games. Twenty older adults were trained for over 20 h to play Rise of Nations, a complex real-time strategy game. These adults showed substantial improvements over the training period in game performance. MRI scans obtained prior to training revealed that the volume of a number of brain regions, which have been previously associated with subsets of the trained skills, predicted a substantial amount of variance in learning on the complex game. Thus, regional differences in brain volume can predict learning in complex tasks that entail the use of a variety of perceptual, cognitive and motor processes. Copyright © 2011 Elsevier Inc. All rights reserved.

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

PubMed Central

Marchal-Crespo, Laura; Michels, Lars; Jaeger, Lukas; López-Olóriz, Jorge; Riener, Robert

2017-01-01

Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS) in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL), i.e., precuneus, and temporal cortex. These neuroimaging findings indicate that gait-like motor learning depends on interplay between subcortical, cerebellar, and fronto-parietal brain regions. An interesting observation was the low activation observed in the brain's reward system after training with error amplification compared to training without perturbations. Our results suggest that to enhance learning of a locomotor task, errors should be augmented based on subjects' skill level. The impacts of these strategies on motor learning, brain activation, and motivation in neurological patients need further investigation. PMID:29021739

Error framing effects on performance: cognitive, motivational, and affective pathways.

PubMed

Steele-Johnson, Debra; Kalinoski, Zachary T

2014-01-01

Our purpose was to examine whether positive error framing, that is, making errors salient and cuing individuals to see errors as useful, can benefit learning when task exploration is constrained. Recent research has demonstrated the benefits of a newer approach to training, that is, error management training, that includes the opportunity to actively explore the task and framing errors as beneficial to learning complex tasks (Keith & Frese, 2008). Other research has highlighted the important role of errors in on-the-job learning in complex domains (Hutchins, 1995). Participants (N = 168) from a large undergraduate university performed a class scheduling task. Results provided support for a hypothesized path model in which error framing influenced cognitive, motivational, and affective factors which in turn differentially affected performance quantity and quality. Within this model, error framing had significant direct effects on metacognition and self-efficacy. Our results suggest that positive error framing can have beneficial effects even when tasks cannot be structured to support extensive exploration. Whereas future research can expand our understanding of error framing effects on outcomes, results from the current study suggest that positive error framing can facilitate learning from errors in real-time performance of tasks.

Learning what matters: A neural explanation for the sparsity bias.

PubMed

Hassall, Cameron D; Connor, Patrick C; Trappenberg, Thomas P; McDonald, John J; Krigolson, Olave E

2018-05-01

The visual environment is filled with complex, multi-dimensional objects that vary in their value to an observer's current goals. When faced with multi-dimensional stimuli, humans may rely on biases to learn to select those objects that are most valuable to the task at hand. Here, we show that decision making in a complex task is guided by the sparsity bias: the focusing of attention on a subset of available features. Participants completed a gambling task in which they selected complex stimuli that varied randomly along three dimensions: shape, color, and texture. Each dimension comprised three features (e.g., color: red, green, yellow). Only one dimension was relevant in each block (e.g., color), and a randomly-chosen value ranking determined outcome probabilities (e.g., green > yellow > red). Participants were faster to respond to infrequent probe stimuli that appeared unexpectedly within stimuli that possessed a more valuable feature than to probes appearing within stimuli possessing a less valuable feature. Event-related brain potentials recorded during the task provided a neurophysiological explanation for sparsity as a learning-dependent increase in optimal attentional performance (as measured by the N2pc component of the human event-related potential) and a concomitant learning-dependent decrease in prediction errors (as measured by the feedback-elicited reward positivity). Together, our results suggest that the sparsity bias guides human reinforcement learning in complex environments. Copyright © 2018 Elsevier B.V. All rights reserved.

Predicting Individuals' Learning Success from Patterns of Pre-Learning MRI Activity

PubMed Central

Vo, Loan T. K.; Walther, Dirk B.; Kramer, Arthur F.; Erickson, Kirk I.; Boot, Walter R.; Voss, Michelle W.; Prakash, Ruchika S.; Lee, Hyunkyu; Fabiani, Monica; Gratton, Gabriele; Simons, Daniel J.; Sutton, Bradley P.; Wang, Michelle Y.

2011-01-01

Performance in most complex cognitive and psychomotor tasks improves with training, yet the extent of improvement varies among individuals. Is it possible to forecast the benefit that a person might reap from training? Several behavioral measures have been used to predict individual differences in task improvement, but their predictive power is limited. Here we show that individual differences in patterns of time-averaged T2*-weighted MRI images in the dorsal striatum recorded at the initial stage of training predict subsequent learning success in a complex video game with high accuracy. These predictions explained more than half of the variance in learning success among individuals, suggesting that individual differences in neuroanatomy or persistent physiology predict whether and to what extent people will benefit from training in a complex task. Surprisingly, predictions from white matter were highly accurate, while voxels in the gray matter of the dorsal striatum did not contain any information about future training success. Prediction accuracy was higher in the anterior than the posterior half of the dorsal striatum. The link between trainability and the time-averaged T2*-weighted signal in the dorsal striatum reaffirms the role of this part of the basal ganglia in learning and executive functions, such as task-switching and task coordination processes. The ability to predict who will benefit from training by using neuroimaging data collected in the early training phase may have far-reaching implications for the assessment of candidates for specific training programs as well as the study of populations that show deficiencies in learning new skills. PMID:21264257

Patients with Parkinson's Disease Learn to Control Complex Systems via Procedural as Well as Non-Procedural Learning

ERIC Educational Resources Information Center

Osman, Magda; Wilkinson, Leonora; Beigi, Mazda; Castaneda, Cristina Sanchez; Jahanshahi, Marjan

2008-01-01

The striatum is considered to mediate some forms of procedural learning. Complex dynamic control (CDC) tasks involve an individual having to make a series of sequential decisions to achieve a specific outcome (e.g. learning to operate and control a car), and they involve procedural learning. The aim of this study was to test the hypothesis that…

Policy Transfer via Markov Logic Networks

NASA Astrophysics Data System (ADS)

Torrey, Lisa; Shavlik, Jude

We propose using a statistical-relational model, the Markov Logic Network, for knowledge transfer in reinforcement learning. Our goal is to extract relational knowledge from a source task and use it to speed up learning in a related target task. We show that Markov Logic Networks are effective models for capturing both source-task Q-functions and source-task policies. We apply them via demonstration, which involves using them for decision making in an initial stage of the target task before continuing to learn. Through experiments in the RoboCup simulated-soccer domain, we show that transfer via Markov Logic Networks can significantly improve early performance in complex tasks, and that transferring policies is more effective than transferring Q-functions.

A Developmental Learning Approach of Mobile Manipulator via Playing

PubMed Central

Wu, Ruiqi; Zhou, Changle; Chao, Fei; Zhu, Zuyuan; Lin, Chih-Min; Yang, Longzhi

2017-01-01

Inspired by infant development theories, a robotic developmental model combined with game elements is proposed in this paper. This model does not require the definition of specific developmental goals for the robot, but the developmental goals are implied in the goals of a series of game tasks. The games are characterized into a sequence of game modes based on the complexity of the game tasks from simple to complex, and the task complexity is determined by the applications of developmental constraints. Given a current mode, the robot switches to play in a more complicated game mode when it cannot find any new salient stimuli in the current mode. By doing so, the robot gradually achieves it developmental goals by playing different modes of games. In the experiment, the game was instantiated into a mobile robot with the playing task of picking up toys, and the game is designed with a simple game mode and a complex game mode. A developmental algorithm, “Lift-Constraint, Act and Saturate,” is employed to drive the mobile robot move from the simple mode to the complex one. The experimental results show that the mobile manipulator is able to successfully learn the mobile grasping ability after playing simple and complex games, which is promising in developing robotic abilities to solve complex tasks using games. PMID:29046632

Check It Out! Using Checklists to Support Student Learning

ERIC Educational Resources Information Center

Rowlands, Kathleen Dudden

2007-01-01

Kathleen Dudden Rowlands recommends using checklists to support student learning and performance. Well-designed checklists identify steps students can take to complete complex tasks, which scaffolds students' metacognitive development and fosters the confidence and independence needed for internalizing these steps for future tasks. (Contains 7…

Reinforcement learning in computer vision

NASA Astrophysics Data System (ADS)

Bernstein, A. V.; Burnaev, E. V.

2018-04-01

Nowadays, machine learning has become one of the basic technologies used in solving various computer vision tasks such as feature detection, image segmentation, object recognition and tracking. In many applications, various complex systems such as robots are equipped with visual sensors from which they learn state of surrounding environment by solving corresponding computer vision tasks. Solutions of these tasks are used for making decisions about possible future actions. It is not surprising that when solving computer vision tasks we should take into account special aspects of their subsequent application in model-based predictive control. Reinforcement learning is one of modern machine learning technologies in which learning is carried out through interaction with the environment. In recent years, Reinforcement learning has been used both for solving such applied tasks as processing and analysis of visual information, and for solving specific computer vision problems such as filtering, extracting image features, localizing objects in scenes, and many others. The paper describes shortly the Reinforcement learning technology and its use for solving computer vision problems.

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

Visualizing the Complex Process for Deep Learning with an Authentic Programming Project

ERIC Educational Resources Information Center

Peng, Jun; Wang, Minhong; Sampson, Demetrios

2017-01-01

Project-based learning (PjBL) has been increasingly used to connect abstract knowledge and authentic tasks in educational practice, including computer programming education. Despite its promising effects on improving learning in multiple aspects, PjBL remains a struggle due to its complexity. Completing an authentic programming project involves a…

Designing for Discovery Learning of Complexity Principles of Congestion by Driving Together in the TrafficJams Simulation

ERIC Educational Resources Information Center

Levy, Sharona T.; Peleg, Ran; Ofeck, Eyal; Tabor, Naamit; Dubovi, Ilana; Bluestein, Shiri; Ben-Zur, Hadar

2018-01-01

We propose and evaluate a framework supporting collaborative discovery learning of complex systems. The framework blends five design principles: (1) individual action: amidst (2) social interactions; challenged with (3) multiple tasks; set in (4) a constrained interactive learning environment that draws attention to (5) highlighted target…

Effects of Multimedia Task-Based Teaching and Learning Approach on EFL Learners' Accuracy, Fluency and Complexity of Oral Production

ERIC Educational Resources Information Center

Bava Harji, Madhubala; Gheitanchian, Mehrnaz

2017-01-01

Albeit Task-Based Language Teaching (TBLT) has been extensively researched, there appears to be limited studies that focus on the effects of multimedia technology (MT) enhanced TBLT approach on EFL development. A study was conducted to examine the effects of a MT imbued TBLT, i.e. Multimedia Task-Based Teaching and Learning (MMTBLT) approach on…

An Approach to Reduce Skill Loss of the Unrestricted Line Officer in the Venezuelan Navy.

DTIC Science & Technology

1982-03-01

actual task practice. --Jhole task learning may lead to better retention than part task learning, especially for more complex tasks. Conditions During...Oficiales), and the other is the Chief of Education (CE) (Jefe de Educacion de la Armada). The former is in charge of the...Comandancia Gral de La ’Iarina Avd. Vollmer San Bernardino Caracas, Venezuela 4. Jefatura de Educacion de la Armada 3 Comandancia Gral de La iiarina Avd

The Impact of Complexity on the Expertise Reversal Effect: Experimental Evidence from Testing Accounting Students

ERIC Educational Resources Information Center

Blayney, Paul; Kalyuga, Slava; Sweller, John

2016-01-01

Element interactivity is a central concept of cognitive load theory that defines the complexity of a learning task. The reduction of task complexity through a temporary segmentation or isolation of interacting elements was investigated with 104 students randomly assigned to an interacting elements group, where participants were required to deal…

Enhancing Automaticity through Task-Based Language Learning

ERIC Educational Resources Information Center

De Ridder, Isabelle; Vangehuchten, Lieve; Gomez, Marta Sesena

2007-01-01

In general terms automaticity could be defined as the subconscious condition wherein "we perform a complex series of tasks very quickly and efficiently, without having to think about the various components and subcomponents of action involved" (DeKeyser 2001: 125). For language learning, Segalowitz (2003) characterised automaticity as a…

Perceptual learning modules in mathematics: enhancing students' pattern recognition, structure extraction, and fluency.

PubMed

Kellman, Philip J; Massey, Christine M; Son, Ji Y

2010-04-01

Learning in educational settings emphasizes declarative and procedural knowledge. Studies of expertise, however, point to other crucial components of learning, especially improvements produced by experience in the extraction of information: perceptual learning (PL). We suggest that such improvements characterize both simple sensory and complex cognitive, even symbolic, tasks through common processes of discovery and selection. We apply these ideas in the form of perceptual learning modules (PLMs) to mathematics learning. We tested three PLMs, each emphasizing different aspects of complex task performance, in middle and high school mathematics. In the MultiRep PLM, practice in matching function information across multiple representations improved students' abilities to generate correct graphs and equations from word problems. In the Algebraic Transformations PLM, practice in seeing equation structure across transformations (but not solving equations) led to dramatic improvements in the speed of equation solving. In the Linear Measurement PLM, interactive trials involving extraction of information about units and lengths produced successful transfer to novel measurement problems and fraction problem solving. Taken together, these results suggest (a) that PL techniques have the potential to address crucial, neglected dimensions of learning, including discovery and fluent processing of relations; (b) PL effects apply even to complex tasks that involve symbolic processing; and (c) appropriately designed PL technology can produce rapid and enduring advances in learning. Copyright © 2009 Cognitive Science Society, Inc.

Tasks for Easily Modifiable Virtual Environments

ERIC Educational Resources Information Center

Swier, Robert

2014-01-01

Recent studies of learner interaction in virtual worlds have tended to select basic tasks involving open-ended communication. There is evidence that such tasks are supportive of language acquisition, however it may also be beneficial to consider more complex tasks. Research in task-based learning has identified features such as non-linguistic…

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

The Use of Feedback Systems to Improve Collaborative Text Writing: A Proposal for the Higher Education Context

ERIC Educational Resources Information Center

Mauri, Teresa; Ginesta, Anna; Rochera, Maria-José

2016-01-01

Collaborative writing is a task commonly used for learning and assessment in higher education. The complexity of this type of task requires special support for learning contents. Feedback can be used as a key element to improve students' learning and engagement. This paper presents and evaluates a teaching innovation that sought to design a model…

Braille in the Sighted: Teaching Tactile Reading to Sighted Adults.

PubMed

Bola, Łukasz; Siuda-Krzywicka, Katarzyna; Paplińska, Małgorzata; Sumera, Ewa; Hańczur, Paweł; Szwed, Marcin

2016-01-01

Blind people are known to have superior perceptual abilities in their remaining senses. Several studies suggest that these enhancements are dependent on the specific experience of blind individuals, who use those remaining senses more than sighted subjects. In line with this view, sighted subjects, when trained, are able to significantly progress in relatively simple tactile tasks. However, the case of complex tactile tasks is less obvious, as some studies suggest that visual deprivation itself could confer large advantages in learning them. It remains unclear to what extent those complex skills, such as braille reading, can be learnt by sighted subjects. Here we enrolled twenty-nine sighted adults, mostly braille teachers and educators, in a 9-month braille reading course. At the beginning of the course, all subjects were naive in tactile braille reading. After the course, almost all were able to read whole braille words at a mean speed of 6 words-per-minute. Subjects with low tactile acuity did not differ significantly in braille reading speed from the rest of the group, indicating that low tactile acuity is not a limiting factor for learning braille, at least at this early stage of learning. Our study shows that most sighted adults can learn whole-word braille reading, given the right method and a considerable amount of motivation. The adult sensorimotor system can thus adapt, to some level, to very complex tactile tasks without visual deprivation. The pace of learning in our group was comparable to congenitally and early blind children learning braille in primary school, which suggests that the blind's mastery of complex tactile tasks can, to a large extent, be explained by experience-dependent mechanisms.

Braille in the Sighted: Teaching Tactile Reading to Sighted Adults

PubMed Central

Bola, Łukasz; Siuda-Krzywicka, Katarzyna; Paplińska, Małgorzata; Sumera, Ewa; Hańczur, Paweł; Szwed, Marcin

2016-01-01

Blind people are known to have superior perceptual abilities in their remaining senses. Several studies suggest that these enhancements are dependent on the specific experience of blind individuals, who use those remaining senses more than sighted subjects. In line with this view, sighted subjects, when trained, are able to significantly progress in relatively simple tactile tasks. However, the case of complex tactile tasks is less obvious, as some studies suggest that visual deprivation itself could confer large advantages in learning them. It remains unclear to what extent those complex skills, such as braille reading, can be learnt by sighted subjects. Here we enrolled twenty-nine sighted adults, mostly braille teachers and educators, in a 9-month braille reading course. At the beginning of the course, all subjects were naive in tactile braille reading. After the course, almost all were able to read whole braille words at a mean speed of 6 words-per-minute. Subjects with low tactile acuity did not differ significantly in braille reading speed from the rest of the group, indicating that low tactile acuity is not a limiting factor for learning braille, at least at this early stage of learning. Our study shows that most sighted adults can learn whole-word braille reading, given the right method and a considerable amount of motivation. The adult sensorimotor system can thus adapt, to some level, to very complex tactile tasks without visual deprivation. The pace of learning in our group was comparable to congenitally and early blind children learning braille in primary school, which suggests that the blind’s mastery of complex tactile tasks can, to a large extent, be explained by experience-dependent mechanisms. PMID:27187496

Age, task complexity, and sex as potential moderators of attentional focus effects.

PubMed

Becker, Kevin; Smith, Peter J K

2013-08-01

The study tested whether age, sex, or task complexity moderate the effect of attentional focus on motor learning. Children (24 boys, 24 girls) and adults (24 men, 24 women) were assigned to an internal or external attentional focus, and were timed while riding either a Double Pedalo with handles (simple task) or without handles (complex task) over a distance of 7 meters. A Double Pedalo is a four-wheeled device that involves standing on two connected platforms, and alternately pushing them forward to make it move. Participants completed 20 acquisition trials, followed by a 24-hour retention test. For the simpler task, no time differences due to attentional focus emerged. With the complex task, an external focus resulted in faster times in retention than an internal focus, but only for males. These findings suggest that attentional focus affects children and adults similarly, but task complexity and sex moderate these effects.

Instructional Strategy: Administration of Injury Scripts

ERIC Educational Resources Information Center

Schilling, Jim

2016-01-01

Context: Learning how to form accurate and efficient clinical examinations is a critical factor in becoming a competent athletic training practitioner, and instructional strategies differ for this complex task. Objective: To introduce an instructional strategy consistent with complex learning to encourage improved efficiency by minimizing…

Thinking about the weather: How display salience and knowledge affect performance in a graphic inference task.

PubMed

Hegarty, Mary; Canham, Matt S; Fabrikant, Sara I

2010-01-01

Three experiments examined how bottom-up and top-down processes interact when people view and make inferences from complex visual displays (weather maps). Bottom-up effects of display design were investigated by manipulating the relative visual salience of task-relevant and task-irrelevant information across different maps. Top-down effects of domain knowledge were investigated by examining performance and eye fixations before and after participants learned relevant meteorological principles. Map design and knowledge interacted such that salience had no effect on performance before participants learned the meteorological principles; however, after learning, participants were more accurate if they viewed maps that made task-relevant information more visually salient. Effects of display design on task performance were somewhat dissociated from effects of display design on eye fixations. The results support a model in which eye fixations are directed primarily by top-down factors (task and domain knowledge). They suggest that good display design facilitates performance not just by guiding where viewers look in a complex display but also by facilitating processing of the visual features that represent task-relevant information at a given display location. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

The Effect of Contextualized Conversational Feedback in a Complex Open-Ended Learning Environment

ERIC Educational Resources Information Center

Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam

2013-01-01

Betty's Brain is an open-ended learning environment in which students learn about science topics by teaching a virtual agent named Betty through the construction of a visual causal map that represents the relevant science phenomena. The task is complex, and success requires the use of metacognitive strategies that support knowledge acquisition,…

Dribble Files: Methodologies to Evaluate Learning and Performance in Complex Environments

ERIC Educational Resources Information Center

Schrader, P. G.; Lawless, Kimberly A.

2007-01-01

Research in the area of technology learning environments is tremendously complex. Tasks performed in these contexts are highly cognitive and mostly invisible to the observer. The nature of performance in these contexts is explained not only by the outcome but also by the process. However, evaluating the learning process with respect to tasks…

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.

Different slopes for different folks: alpha and delta EEG power predict subsequent video game learning rate and improvements in cognitive control tasks.

PubMed

Mathewson, Kyle E; Basak, Chandramallika; Maclin, Edward L; Low, Kathy A; Boot, Walter R; Kramer, Arthur F; Fabiani, Monica; Gratton, Gabriele

2012-12-01

We hypothesized that control processes, as measured using electrophysiological (EEG) variables, influence the rate of learning of complex tasks. Specifically, we measured alpha power, event-related spectral perturbations (ERSPs), and event-related brain potentials during early training of the Space Fortress task, and correlated these measures with subsequent learning rate and performance in transfer tasks. Once initial score was partialled out, the best predictors were frontal alpha power and alpha and delta ERSPs, but not P300. By combining these predictors, we could explain about 50% of the learning rate variance and 10%-20% of the variance in transfer to other tasks using only pretraining EEG measures. Thus, control processes, as indexed by alpha and delta EEG oscillations, can predict learning and skill improvements. The results are of potential use to optimize training regimes. Copyright © 2012 Society for Psychophysiological Research.

Understanding the Connection between Epistemic Beliefs and Internet Searching

ERIC Educational Resources Information Center

Ulyshen, Tianyi Zhang; Koehler, Matthew J.; Gao, Fei

2015-01-01

Within the context of exploring an ill-structured task using the Google search engine, this study examined (a) the connections between general epistemic beliefs and the complexity of learners' knowledge exploration processes (i.e., learning complexity) and (b) the role of activating learners' task-oriented epistemic beliefs (i.e., epistemic…

Instruction-First and Problem-Solving-First Approaches: Alternative Pathways to Learning Complex Tasks

ERIC Educational Resources Information Center

Likourezos, Vicki; Kalyuga, Slava

2017-01-01

According to cognitive load theory, using worked examples is an effective and efficient instructional strategy for initial cognitive skill acquisition for novice learners, as it reduces cognitive load and frees up cognitive resources to build task competence. Contrary to this, productive failure (as well as invention learning, desirable…

Prompted Journal Writing Supports Preservice History Teachers in Drawing on Multiple Knowledge Domains for Designing Learning Tasks

ERIC Educational Resources Information Center

Wäschle, Kristin; Lehmann, Thomas; Brauch, Nicola; Nückles, Matthias

2015-01-01

Becoming a history teacher requires the integration of pedagogical knowledge, pedagogical content knowledge, and content knowledge. Because the integration of knowledge from different disciplines is a complex task, we investigated prompted learning journals as a method to support teacher students' knowledge integration. Fifty-two preservice…

Extending the limits of complex learning in organic amnesia: computer training in a vocational domain.

PubMed

Glisky, E L; Schacter, D L

1989-01-01

This study explored the limits of learning that could be achieved by an amnesic patient in a complex real-world domain. Using a cuing procedure known as the method of vanishing cues, a severely amnesic encephalitic patient was taught over 250 discrete pieces of new information concerning the rules and procedures for performing a task involving data entry into a computer. Subsequently, she was able to use this acquired knowledge to perform the task accurately and efficiently in the workplace. These results suggest that amnesic patients' preserved learning abilities can be extended well beyond what has been reported previously.

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

PubMed

Carcagno, Samuele; Plack, Christopher J

2011-08-01

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

Perceptual Learning, Cognition, and Expertise

ERIC Educational Resources Information Center

Kellman, Philip J.; Massey, Christine M.

2013-01-01

Recent research indicates that perceptual learning (PL)--experience-induced changes in the way perceivers extract information--plays a larger role in complex cognitive tasks, including abstract and symbolic domains, than has been understood in theory or implemented in instruction. Here, we describe the involvement of PL in complex cognitive tasks…

Assessing Neurophysiologic Markers for Training and Simulation to Develop Expertise in Complex Cognitive Tasks

DTIC Science & Technology

2010-09-01

analysis process is to categorize the goal according to (Gagné, 2005) domains of learning . These domains are: verbal information, intellectual...to terrain features. The ability to provide a clear verbal description of a unique feature is a learned task that may be separate from the...and experts differently. The process of verbally encoding information on location and providing this description may detract from the primary task of

Are There Detrimental Effects From Proficiency-Based Training in Fundamentals of Laparoscopic Surgery Among Novices? An Exploration of Goal Theory.

PubMed

Stoller, Jeremy; Joseph, Jeremy; Parodi, Nicholas; Gardner, Aimee

2016-01-01

Goal theory states that novices may experience unintended, detrimental learning effects, with decreased performance, when given performance goals on complex tasks. In these situations, it may be more appropriate to give novices learning goals to help avoid these negative consequences. The purpose of this study was to see whether this tenant of goal theory applied to novices learning 2 tasks of fundamentals of laparoscopic surgery (FLS). Medical and physician assistant students were randomized to a performance goals group and a learning goals group. The performance goals consisted of the published proficiency standards of FLS. Both groups were pretested on perception of surgery, self-efficacy, and general affect. Each group underwent a practice session for the peg transfer task. They were tested and scored per the published standards of FLS. The participants completed NASA Task Load Index, task complexity, and postaffect questionnaires related to the peg transfer task. This was repeated with the suture with intracorporeal knot task. Posttest perception of surgery and self-efficacy questionnaires were completed. In total, 48 students participated in the study: 23 in the performance goals group and 25 in the learning goals group. Most of the participants (n = 40) were first-year medical and physician assistant students. There were no significant differences between the groups in perception of surgery, affect, goal commitment, subjective task complexity, subjective workload, and self-efficacy. There were no differences between the groups concerning overall FLS score for both the peg transfer and suturing tasks. Both groups exhibited significant increases in self-efficacy and perception of surgery (p < 0.05). FLS skills can be given to novice learners without concern for detrimental effects as might be expected by other work on goal theory. Given that performance was the same for both groups, surgical educators may have multiple pathways to educational success when incorporating goals into training programs for basic surgical skills. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Roles of Working Memory Performance and Instructional Strategy in Complex Cognitive Task Performance

ERIC Educational Resources Information Center

Cevik, V.; Altun, A.

2016-01-01

This study aims to investigate how working memory (WM) performances and instructional strategy choices affect learners' complex cognitive task performance in online environments. Three different e-learning environments were designed based on Merrill's (2006a) model of instructional strategies. The lack of experimental research on his framework is…

Similar Neural Correlates for Language and Sequential Learning: Evidence from Event-Related Brain Potentials

ERIC Educational Resources Information Center

Christiansen, Morten H.; Conway, Christopher M.; Onnis, Luca

2012-01-01

We used event-related potentials (ERPs) to investigate the time course and distribution of brain activity while adults performed (1) a sequential learning task involving complex structured sequences and (2) a language processing task. The same positive ERP deflection, the P600 effect, typically linked to difficult or ungrammatical syntactic…

Interactive effect of acute pain and motor learning acquisition on sensorimotor integration and motor learning outcomes

PubMed Central

Dancey, Erin; Andrew, Danielle; Yielder, Paul

2016-01-01

Previous work has demonstrated differential changes in early somatosensory evoked potentials (SEPs) when motor learning acquisition occurred in the presence of acute pain; however, the learning task was insufficiently complex to determine how these underlying neurophysiological differences impacted learning acquisition and retention. To address this limitation, we have utilized a complex motor task in conjunction with SEPs. Two groups of 12 participants (n = 24) were randomly assigned to either a capsaicin (capsaicin cream) or a control (inert lotion) group. SEP amplitudes were collected at baseline, after application, and after motor learning acquisition. Participants performed a motor acquisition task followed by a pain-free retention task within 24–48 h. After motor learning acquisition, the amplitude of the N20 SEP peak significantly increased (P < 0.05) and the N24 SEP peak significantly decreased (P < 0.001) for the control group while the N18 SEP peak significantly decreased (P < 0.01) for the capsaicin group. The N30 SEP peak was significantly increased (P < 0.001) after motor learning acquisition for both groups. The P25 SEP peak decreased significantly (P < 0.05) after the application of capsaicin cream. Both groups improved in accuracy after motor learning acquisition (P < 0.001). The capsaicin group outperformed the control group before motor learning acquisition (P < 0.05) and after motor learning acquisition (P < 0.05) and approached significance at retention (P = 0.06). Improved motor learning in the presence of capsaicin provides support for the enhancement of motor learning while in acute pain. In addition, the changes in SEP peak amplitudes suggest that early SEP changes reflect neurophysiological alterations accompanying both motor learning and mild acute pain. PMID:27535371

Inferring interventional predictions from observational learning data.

PubMed

Meder, Bjorn; Hagmayer, York; Waldmann, Michael R

2008-02-01

Previous research has shown that people are capable of deriving correct predictions for previously unseen actions from passive observations of causal systems (Waldmann & Hagmayer, 2005). However, these studies were limited, since learning data were presented as tabulated data only, which may have turned the task more into a reasoning rather than a learning task. In two experiments, we therefore presented learners with trial-by-trial observational learning input referring to a complex causal model consisting of four events. To test the robustness of the capacity to derive correct observational and interventional inferences, we pitted causal order against the temporal order of learning events. The results show that people are, in principle, capable of deriving correct predictions after purely observational trial-by-trial learning, even with relatively complex causal models. However, conflicting temporal information can impair performance, particularly when the inferences require taking alternative causal pathways into account.

Variable learning performance: the levels of behaviour organization.

PubMed

Csányi, V; Altbäcker, V

1990-01-01

Our experiments were focused on some special aspects of learning in the paradise fish. Passive avoidance conditioning method was used with different success depending on the complexity of the learning tasks. In the case of simple behavioural elements various "constrains" on avoidance learning were found. In a small, covered place the fish were ready to perform freezing reaction and mild punishment increased the frequency and duration of the freezing bouts very substantially. However, it was very difficult to enhance the frequency of freezing by punishment in a tank with transparent walls, where the main response to punishment was escape. The most easily learned tasks were the complex ones which had several different solutions. The fish learned to avoid either side of an aquarium very easily because they could use various behavioural elements to solve the problem. These findings could be interpreted within the framework of different organizational levels of behaviour.

Mapping and Managing Knowledge and Information in Resource-Based Learning

ERIC Educational Resources Information Center

Tergan, Sigmar-Olaf; Graber, Wolfgang; Neumann, Anja

2006-01-01

In resource-based learning scenarios, students are often overwhelmed by the complexity of task-relevant knowledge and information. Techniques for the external interactive representation of individual knowledge in graphical format may help them to cope with complex problem situations. Advanced computer-based concept-mapping tools have the potential…

A randomized controlled trial on errorless learning in goal management training: study rationale and protocol

PubMed Central

2013-01-01

Background Many brain-injured patients referred for outpatient rehabilitation have executive deficits, notably difficulties with planning, problem-solving and goal directed behaviour. Goal Management Training (GMT) has proven to be an efficacious cognitive treatment for these problems. GMT entails learning and applying an algorithm, in which daily tasks are subdivided into multiple steps. Main aim of the present study is to examine whether using an errorless learning approach (preventing the occurrence of errors during the acquisition phase of learning) contributes to the efficacy of Goal Management Training in the performance of complex daily tasks. Methods/Design The study is a double blind randomized controlled trial, in which the efficacy of Goal Management Training with an errorless learning approach will be compared with conventional Goal Management Training, based on trial and error learning. In both conditions 32 patients with acquired brain injury of mixed etiology will be examined. Main outcome measure will be the performance on two individually chosen everyday-tasks before and after treatment, using a standardized observation scale and goal attainment scaling. Discussion This is the first study that introduces errorless learning in Goal Management Training. It is expected that the GMT-errorless learning approach will improve the execution of complex daily tasks in brain-injured patients with executive deficits. The study can contribute to a better treatment of executive deficits in cognitive rehabilitation. Trial registration (Dutch Trial Register): http://NTR3567 PMID:23786651

Attention theory and training research

NASA Technical Reports Server (NTRS)

Connelly, James G., Jr.; Wickens, Christopher D.; Lintern, Gavan; Harwood, Kelly

1987-01-01

This study used elements of attention theory as a methodological basis to decompose a complex training task in order to improve training efficiency. The complex task was a microcomputer flight simulation where subjects were required to control the stability of their own helicopter while acquiring and engaging enemy helicopers in a threat enviroment. Subjects were divided into whole-task, part-task, and part/open loop adaptive task groups in a transfer of training paradigm. The effect of reducing mental workload at the early stages of learning was examined with respect to the degree that subordinate elements of the complex task could be automated through practice of consistent, learnable stimulus-response relationships. Results revealed trends suggesting the benefit of isolating consistently mapped sub-tasks for part-task training and the presence of a time-sharing skill over and above the skill required for the separate subtasks.

The effect of haptic guidance and visual feedback on learning a complex tennis task.

PubMed

Marchal-Crespo, Laura; van Raai, Mark; Rauter, Georg; Wolf, Peter; Riener, Robert

2013-11-01

While haptic guidance can improve ongoing performance of a motor task, several studies have found that it ultimately impairs motor learning. However, some recent studies suggest that the haptic demonstration of optimal timing, rather than movement magnitude, enhances learning in subjects trained with haptic guidance. Timing of an action plays a crucial role in the proper accomplishment of many motor skills, such as hitting a moving object (discrete timing task) or learning a velocity profile (time-critical tracking task). The aim of the present study is to evaluate which feedback conditions-visual or haptic guidance-optimize learning of the discrete and continuous elements of a timing task. The experiment consisted in performing a fast tennis forehand stroke in a virtual environment. A tendon-based parallel robot connected to the end of a racket was used to apply haptic guidance during training. In two different experiments, we evaluated which feedback condition was more adequate for learning: (1) a time-dependent discrete task-learning to start a tennis stroke and (2) a tracking task-learning to follow a velocity profile. The effect that the task difficulty and subject's initial skill level have on the selection of the optimal training condition was further evaluated. Results showed that the training condition that maximizes learning of the discrete time-dependent motor task depends on the subjects' initial skill level. Haptic guidance was especially suitable for less-skilled subjects and in especially difficult discrete tasks, while visual feedback seems to benefit more skilled subjects. Additionally, haptic guidance seemed to promote learning in a time-critical tracking task, while visual feedback tended to deteriorate the performance independently of the task difficulty and subjects' initial skill level. Haptic guidance outperformed visual feedback, although additional studies are needed to further analyze the effect of other types of feedback visualization on motor learning of time-critical tasks.

Vernier perceptual learning transfers to completely untrained retinal locations after double training: A “piggybacking” effect

PubMed Central

Wang, Rui; Zhang, Jun-Yun; Klein, Stanley A.; Levi, Dennis M.; Yu, Cong

2014-01-01

Perceptual learning, a process in which training improves visual discrimination, is often specific to the trained retinal location, and this location specificity is frequently regarded as an indication of neural plasticity in the retinotopic visual cortex. However, our previous studies have shown that “double training” enables location-specific perceptual learning, such as Vernier learning, to completely transfer to a new location where an irrelevant task is practiced. Here we show that Vernier learning can be actuated by less location-specific orientation or motion-direction learning to transfer to completely untrained retinal locations. This “piggybacking” effect occurs even if both tasks are trained at the same retinal location. However, piggybacking does not occur when the Vernier task is paired with a more location-specific contrast-discrimination task. This previously unknown complexity challenges the current understanding of perceptual learning and its specificity/transfer. Orientation and motion-direction learning, but not contrast and Vernier learning, appears to activate a global process that allows learning transfer to untrained locations. Moreover, when paired with orientation or motion-direction learning, Vernier learning may be “piggybacked” by the activated global process to transfer to other untrained retinal locations. How this task-specific global activation process is achieved is as yet unknown. PMID:25398974

Backwards Fading to Speed Task Learning

DTIC Science & Technology

2013-09-01

estimates.) Table 1 Finalized Task List Task Domain Task Name Knot Tying Hand Cuff Rappel First Aid Fracture Bleed Map Reading* Resection...materials used. Hand Cuff . There are 10 steps in this task. To complete this task, the learner must manipulate a short length of rope (e.g...Design for Experiment 1 – Step Fade Experiment 1 (Step Fade) Task Type: Knot Tying Task Type: First Aid Task Complexity: Low (1) Hand Cuff (10

Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia.

PubMed

Diuk, Carlos; Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew; Niv, Yael

2013-03-27

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.

Learning Radiological Appearances of Diseases: Does Comparison Help?

ERIC Educational Resources Information Center

Kok, Ellen M.; de Bruin, Anique B. H.; Robben, Simon G. F.; van Merrienboer, Jeroen J. G.

2013-01-01

Comparison learning is a promising approach for learning complex real-life visual tasks. When medical students study radiological appearances of diseases, comparison of images showing diseases with images showing no abnormalities could help them learn to discriminate relevant, disease-related information. Medical students studied 12 diseases on…

Entering into dialogue about the mathematical value of contextual mathematising tasks

NASA Astrophysics Data System (ADS)

Yoon, Caroline; Chin, Sze Looi; Moala, John Griffith; Choy, Ban Heng

2018-03-01

Our project seeks to draw attention to the rich mathematical thinking that is generated when students work on contextual mathematising tasks. We use a design-based research approach to create ways of reporting that raise the visibility of this rich mathematical thinking while retaining and respecting its complexity. These reports will be aimed for three classroom stakeholders: (1) students, who wish to reflect on and enhance their mathematical learning; (2) teachers, who wish to integrate contextual mathematising tasks into their teaching practice and (3) researchers, who seek rich tasks for generating observable instances of mathematical thinking and learning. We anticipate that these reports and the underlying theoretical framework for creating them will contribute to greater awareness of and appreciation for the mathematical value of contextual mathematising tasks in learning, teaching and research.

How well do elderly people cope with uncertainty in a learning task?

PubMed

Chasseigne, G; Grau, S; Mullet, E; Cama, V

1999-11-01

The relation between age, task complexity and learning performance in a Multiple Cue Probability Learning task was studied by systematically varying the level of uncertainty present in the task, keeping constant the direction of relationships. Four age groups were constituted: young adults (mean age = 21), middle-aged adults (45), elderly people (69) and very elderly people (81). Five uncertainty levels were considered: predictability = 0.96, 0.80, 0.64, 0.48, and 0.32. All relationships involved were direct ones. A strong effect of uncertainty on 'control', a measure of the subject's consistency with respect to a linear model, was found. This effect was essentially a linear one. To each decrement in predictability of the task corresponded an equal decrement in participants' level of control. This level of decrement was the same, regardless of the age of the participant. It can be concluded that elderly people cope with uncertainty in probability learning tasks as well as young adults.

A Skyscraping Feat

ERIC Educational Resources Information Center

Roberts, Sarah A.; Lee, Jean S.

2013-01-01

Research shows that the greatest gains in student learning in mathematics classrooms occur in classrooms in which there is sustained use of high cognitive demanding tasks throughout instruction (Boston and Smith 2009). High cognitive demanding tasks, which this article will refer to as rich tasks, are mathematics problems that are complex, less…

Multimodal Learning Analytics and Education Data Mining: Using Computational Technologies to Measure Complex Learning Tasks

ERIC Educational Resources Information Center

Blikstein, Paulo; Worsley, Marcelo

2016-01-01

New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics…

Similar Neural Correlates for Language and Sequential Learning: Evidence from Event-Related Brain Potentials

PubMed Central

Christiansen, Morten H.; Conway, Christopher M.; Onnis, Luca

2011-01-01

We used event-related potentials (ERPs) to investigate the time course and distribution of brain activity while adults performed (a) a sequential learning task involving complex structured sequences, and (b) a language processing task. The same positive ERP deflection, the P600 effect, typically linked to difficult or ungrammatical syntactic processing, was found for structural incongruencies in both sequential learning as well as natural language, and with similar topographical distributions. Additionally, a left anterior negativity (LAN) was observed for language but not for sequential learning. These results are interpreted as an indication that the P600 provides an index of violations and the cost of integration of expectations for upcoming material when processing complex sequential structure. We conclude that the same neural mechanisms may be recruited for both syntactic processing of linguistic stimuli and sequential learning of structured sequence patterns more generally. PMID:23678205

Deep Learning through Concept-Based Inquiry

ERIC Educational Resources Information Center

Donham, Jean

2010-01-01

Learning in the library should present opportunities to enrich student learning activities to address concerns of interest and cognitive complexity, but these must be tasks that call for in-depth analysis--not merely gathering facts. Library learning experiences need to demand enough of students to keep them interested and also need to be…

The evolutionary basis of human social learning

PubMed Central

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

2012-01-01

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

The evolutionary basis of human social learning.

PubMed

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

2012-02-22

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

Incidental Auditory Category Learning

PubMed Central

Gabay, Yafit; Dick, Frederic K.; Zevin, Jason D.; Holt, Lori L.

2015-01-01

Very little is known about how auditory categories are learned incidentally, without instructions to search for category-diagnostic dimensions, overt category decisions, or experimenter-provided feedback. This is an important gap because learning in the natural environment does not arise from explicit feedback and there is evidence that the learning systems engaged by traditional tasks are distinct from those recruited by incidental category learning. We examined incidental auditory category learning with a novel paradigm, the Systematic Multimodal Associations Reaction Time (SMART) task, in which participants rapidly detect and report the appearance of a visual target in one of four possible screen locations. Although the overt task is rapid visual detection, a brief sequence of sounds precedes each visual target. These sounds are drawn from one of four distinct sound categories that predict the location of the upcoming visual target. These many-to-one auditory-to-visuomotor correspondences support incidental auditory category learning. Participants incidentally learn categories of complex acoustic exemplars and generalize this learning to novel exemplars and tasks. Further, learning is facilitated when category exemplar variability is more tightly coupled to the visuomotor associations than when the same stimulus variability is experienced across trials. We relate these findings to phonetic category learning. PMID:26010588

Deficits in complex motor functions, despite no evidence of procedural learning deficits, among HIV+ individuals with history of substance dependence

PubMed Central

Gonzalez, Raul; Jacobus, Joanna; Amatya, Anup K.; Quartana, Phillip J.; Vassileva, Jasmin; Martin, Eileen M.

2008-01-01

HIV and drugs of abuse affect common neural systems underlying procedural memory, including the striatum. We compared performance of 48 HIV seropositive (HIV+) and 48 HIV seronegative (HIV−) participants with history of cocaine and/or heroin dependence across multiple Trial Blocks of three procedural learning (PL) tasks: Rotary Pursuit (RPT), Mirror Star Tracing (MST), and Weather Prediction (WPT). Groups were well matched on demographic, psychiatric, and substance use parameters, and all participants were verified abstinent from drugs. Mixed model ANOVAs revealed that the HIV+ group performed more poorly across all tasks, with a significant main effect of HIV serostatus observed on the MST and a trend toward significance obtained for the RPT. No significant differences were observed on the WPT. Both groups demonstrated significant improvements in performance across all three PL tasks. Importantly, no significant Serostatus X Trial Block interactions were observed on any task. Thus, the HIV+ group tended to perform worse than the HIV− group across all trial blocks of PL tasks with motor demands, but showed no differences in their rate of improvement across all tasks. These findings are consistent with HIV-associated deficits in complex motor skills, but not in procedural learning. PMID:18999351

Hierarchical Learning Induces Two Simultaneous, But Separable, Prediction Errors in Human Basal Ganglia

PubMed Central

Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew

2013-01-01

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously. PMID:23536092

Dissociable effects of practice variability on learning motor and timing skills.

PubMed

Caramiaux, Baptiste; Bevilacqua, Frédéric; Wanderley, Marcelo M; Palmer, Caroline

2018-01-01

Motor skill acquisition inherently depends on the way one practices the motor task. The amount of motor task variability during practice has been shown to foster transfer of the learned skill to other similar motor tasks. In addition, variability in a learning schedule, in which a task and its variations are interweaved during practice, has been shown to help the transfer of learning in motor skill acquisition. However, there is little evidence on how motor task variations and variability schedules during practice act on the acquisition of complex motor skills such as music performance, in which a performer learns both the right movements (motor skill) and the right time to perform them (timing skill). This study investigated the impact of rate (tempo) variability and the schedule of tempo change during practice on timing and motor skill acquisition. Complete novices, with no musical training, practiced a simple musical sequence on a piano keyboard at different rates. Each novice was assigned to one of four learning conditions designed to manipulate the amount of tempo variability across trials (large or small tempo set) and the schedule of tempo change (randomized or non-randomized order) during practice. At test, the novices performed the same musical sequence at a familiar tempo and at novel tempi (testing tempo transfer), as well as two novel (but related) sequences at a familiar tempo (testing spatial transfer). We found that practice conditions had little effect on learning and transfer performance of timing skill. Interestingly, practice conditions influenced motor skill learning (reduction of movement variability): lower temporal variability during practice facilitated transfer to new tempi and new sequences; non-randomized learning schedule improved transfer to new tempi and new sequences. Tempo (rate) and the sequence difficulty (spatial manipulation) affected performance variability in both timing and movement. These findings suggest that there is a dissociable effect of practice variability on learning complex skills that involve both motor and timing constraints.

Ground Truth Creation for Complex Clinical NLP Tasks - an Iterative Vetting Approach and Lessons Learned.

PubMed

Liang, Jennifer J; Tsou, Ching-Huei; Devarakonda, Murthy V

2017-01-01

Natural language processing (NLP) holds the promise of effectively analyzing patient record data to reduce cognitive load on physicians and clinicians in patient care, clinical research, and hospital operations management. A critical need in developing such methods is the "ground truth" dataset needed for training and testing the algorithms. Beyond localizable, relatively simple tasks, ground truth creation is a significant challenge because medical experts, just as physicians in patient care, have to assimilate vast amounts of data in EHR systems. To mitigate potential inaccuracies of the cognitive challenges, we present an iterative vetting approach for creating the ground truth for complex NLP tasks. In this paper, we present the methodology, and report on its use for an automated problem list generation task, its effect on the ground truth quality and system accuracy, and lessons learned from the effort.

Online incidental statistical learning of audiovisual word sequences in adults: a registered report.

PubMed

Kuppuraj, Sengottuvel; Duta, Mihaela; Thompson, Paul; Bishop, Dorothy

2018-02-01

Statistical learning has been proposed as a key mechanism in language learning. Our main goal was to examine whether adults are capable of simultaneously extracting statistical dependencies in a task where stimuli include a range of structures amenable to statistical learning within a single paradigm. We devised an online statistical learning task using real word auditory-picture sequences that vary in two dimensions: (i) predictability and (ii) adjacency of dependent elements. This task was followed by an offline recall task to probe learning of each sequence type. We registered three hypotheses with specific predictions. First, adults would extract regular patterns from continuous stream (effect of grammaticality). Second, within grammatical conditions, they would show differential speeding up for each condition as a factor of statistical complexity of the condition and exposure. Third, our novel approach to measure online statistical learning would be reliable in showing individual differences in statistical learning ability. Further, we explored the relation between statistical learning and a measure of verbal short-term memory (STM). Forty-two participants were tested and retested after an interval of at least 3 days on our novel statistical learning task. We analysed the reaction time data using a novel regression discontinuity approach. Consistent with prediction, participants showed a grammaticality effect, agreeing with the predicted order of difficulty for learning different statistical structures. Furthermore, a learning index from the task showed acceptable test-retest reliability ( r  = 0.67). However, STM did not correlate with statistical learning. We discuss the findings noting the benefits of online measures in tracking the learning process.

Online incidental statistical learning of audiovisual word sequences in adults: a registered report

PubMed Central

Duta, Mihaela; Thompson, Paul

2018-01-01

Statistical learning has been proposed as a key mechanism in language learning. Our main goal was to examine whether adults are capable of simultaneously extracting statistical dependencies in a task where stimuli include a range of structures amenable to statistical learning within a single paradigm. We devised an online statistical learning task using real word auditory–picture sequences that vary in two dimensions: (i) predictability and (ii) adjacency of dependent elements. This task was followed by an offline recall task to probe learning of each sequence type. We registered three hypotheses with specific predictions. First, adults would extract regular patterns from continuous stream (effect of grammaticality). Second, within grammatical conditions, they would show differential speeding up for each condition as a factor of statistical complexity of the condition and exposure. Third, our novel approach to measure online statistical learning would be reliable in showing individual differences in statistical learning ability. Further, we explored the relation between statistical learning and a measure of verbal short-term memory (STM). Forty-two participants were tested and retested after an interval of at least 3 days on our novel statistical learning task. We analysed the reaction time data using a novel regression discontinuity approach. Consistent with prediction, participants showed a grammaticality effect, agreeing with the predicted order of difficulty for learning different statistical structures. Furthermore, a learning index from the task showed acceptable test–retest reliability (r = 0.67). However, STM did not correlate with statistical learning. We discuss the findings noting the benefits of online measures in tracking the learning process. PMID:29515876

Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller

PubMed Central

Cyr, André; Boukadoum, Mounir; Thériault, Frédéric

2014-01-01

In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors. PMID:25120464

Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller.

PubMed

Cyr, André; Boukadoum, Mounir; Thériault, Frédéric

2014-01-01

In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors.

Seamless Connection between Learning and Assessment--Applying Progressive Learning Tasks in Mobile Ecology Inquiry

ERIC Educational Resources Information Center

Hung, Pi-Hsia; Hwang, Gwo-Jen; Lin, Yu-Fen; Wu, Tsung-Hsun; Su, I-Hsiang

2013-01-01

Mobile learning has been recommended for motivating students on field trips; nevertheless, owing to the complexity and the richness of the learning resources from both the real-world and the digital-world environments, information overload remains one of the major concerns. Most mobile learning designs provide feedback only for multiple choice…

Perceived task complexity of trunk stability exercises.

PubMed

McPhee, Megan; Tucker, Kylie J; Wan, Alan; MacDonald, David A

2017-02-01

Perceived task complexity can impact participation in an exercise programme and the level of skill acquisition resulting from participation. Although trunk stability exercises are commonly included in the management of people with low back pain, potential differences in perceived task complexity between those exercises have not been investigated previously. To investigate the perceived task complexity following first time instruction of two common stability exercises: the abdominal brace and abdominal hollow. Cross-sectional. Twenty-four naïve healthy participants received instruction in the performance of an abdominal brace and an abdominal hollow with feedback. Participants rated their perceived task complexity (mental, physical, and temporal demand, performance, effort, frustration) for each exercise on the NASA-Task Load Index. The abdominal hollow was associated with higher perceived mental demand than the abdominal brace (p = 0.01), and required more time to learn (p < 0.01). The abdominal brace was associated with greater mental demand and frustration when performed after the abdominal hollow than before. This study has provided the first evidence for differences in perceived task complexity between two commonly used trunk stability exercises. Those differences in perceived task complexity may influence the selection of exercises intended to enhance the robustness of spinal stability. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Approach for the Distance Delivery of AFIT/LS Resident Degree Curricula

DTIC Science & Technology

1991-12-01

minimal (least complex) distance education technologies appropriate for each learning topic or task. This may be the most time-consuming step in the...34 represents the least complex distance education technology that could be used to deliver the educational material for a particular learning objective. Careful...minimal technology needed to accomplish the learning objective. Look at question Q2.1 (Figure 5.15). Since the lecture offers an essential educational

Manifold regularized multitask learning for semi-supervised multilabel image classification.

PubMed

Luo, Yong; Tao, Dacheng; Geng, Bo; Xu, Chao; Maybank, Stephen J

2013-02-01

It is a significant challenge to classify images with multiple labels by using only a small number of labeled samples. One option is to learn a binary classifier for each label and use manifold regularization to improve the classification performance by exploring the underlying geometric structure of the data distribution. However, such an approach does not perform well in practice when images from multiple concepts are represented by high-dimensional visual features. Thus, manifold regularization is insufficient to control the model complexity. In this paper, we propose a manifold regularized multitask learning (MRMTL) algorithm. MRMTL learns a discriminative subspace shared by multiple classification tasks by exploiting the common structure of these tasks. It effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold. We conduct extensive experiments, on the PASCAL VOC'07 dataset with 20 classes and the MIR dataset with 38 classes, by comparing MRMTL with popular image classification algorithms. The results suggest that MRMTL is effective for image classification.

Variability and Variation of L2 Grammar: A Cross-Sectional Analysis of German Learners' Performance on Two Tasks

ERIC Educational Resources Information Center

Abrams, Zsuzsanna; Rott, Susanne

2017-01-01

Research on second language (L2) grammar in task-based language learning has yielded inconsistent results regarding the effects of task-complexity, prompting calls for more nuanced analyses of L2 development and task performance. The present cross-sectional study contributes to this discussion by comparing the performance of 245 learners of German…

Effects of Planning on Task Load, Knowledge, and Tool Preference: A Comparison of Two Tools

ERIC Educational Resources Information Center

Bonestroo, Wilco J.; de Jong, Ton

2012-01-01

Self-regulated learners are expected to plan their own learning. Because planning is a complex task, it is not self-evident that all learners can perform this task successfully. In this study, we examined the effects of two planning support tools on the quality of created plans, planning behavior, task load, and acquired knowledge. Sixty-five…

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

PubMed

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Baseline performance and learning rate of conceptual and perceptual skill-learning tasks: the effect of moderate to severe traumatic brain injury.

PubMed

Vakil, Eli; Lev-Ran Galon, Carmit

2014-01-01

Existing literature presents a complex and inconsistent picture of the specific deficiencies involved in skill learning following traumatic brain injury (TBI). In an attempt to address this difficulty, individuals with moderate to severe TBI (n = 29) and a control group (n = 29) were tested with two different skill-learning tasks: conceptual (i.e., Tower of Hanoi Puzzle, TOHP) and perceptual (i.e., mirror reading, MR). Based on previous studies of the effect of divided attention on these tasks and findings regarding the effect of TBI on conceptual and perceptual priming tasks, it was predicted that the group with TBI would show impaired baseline performance compared to controls in the TOHP task though their learning rate would be maintained, while both baseline performance and learning rate on the MR task would be maintained. Consistent with our predictions, overall baseline performance of the group with TBI was impaired in the TOHP test, while the learning rate was not. The learning rate on the MR task was preserved but, contrary to our prediction, response time of the group with TBI was slower than that of controls. The pattern of results observed in the present study was interpreted to possibly reflect an impairment of both the frontal lobes as well as that of diffuse axonal injury, which is well documented as being affected by TBI. The former impairment affects baseline performance of the conceptual learning skill, while the latter affects the overall slower performance of the perceptual learning skill.

Multisensory perceptual learning of temporal order: audiovisual learning transfers to vision but not audition.

PubMed

Alais, David; Cass, John

2010-06-23

An outstanding question in sensory neuroscience is whether the perceived timing of events is mediated by a central supra-modal timing mechanism, or multiple modality-specific systems. We use a perceptual learning paradigm to address this question. Three groups were trained daily for 10 sessions on an auditory, a visual or a combined audiovisual temporal order judgment (TOJ). Groups were pre-tested on a range TOJ tasks within and between their group modality prior to learning so that transfer of any learning from the trained task could be measured by post-testing other tasks. Robust TOJ learning (reduced temporal order discrimination thresholds) occurred for all groups, although auditory learning (dichotic 500/2000 Hz tones) was slightly weaker than visual learning (lateralised grating patches). Crossmodal TOJs also displayed robust learning. Post-testing revealed that improvements in temporal resolution acquired during visual learning transferred within modality to other retinotopic locations and orientations, but not to auditory or crossmodal tasks. Auditory learning did not transfer to visual or crossmodal tasks, and neither did it transfer within audition to another frequency pair. In an interesting asymmetry, crossmodal learning transferred to all visual tasks but not to auditory tasks. Finally, in all conditions, learning to make TOJs for stimulus onsets did not transfer at all to discriminating temporal offsets. These data present a complex picture of timing processes. The lack of transfer between unimodal groups indicates no central supramodal timing process for this task; however, the audiovisual-to-visual transfer cannot be explained without some form of sensory interaction. We propose that auditory learning occurred in frequency-tuned processes in the periphery, precluding interactions with more central visual and audiovisual timing processes. Functionally the patterns of featural transfer suggest that perceptual learning of temporal order may be optimised to object-centered rather than viewer-centered constraints.

The Development of Logical Structures for E-Learning Evaluation

ERIC Educational Resources Information Center

Tudevdagva, Uranchimeg; Hardt, Wolfram; Dolgor, Jargalmaa

2013-01-01

This paper deals with development of logical structures for e-learning evaluation. Evaluation is a complex task into which many different groups of people are involved. As a rule these groups have different understanding and varying expectations on e-learning evaluation. Using logical structures for e-learning evaluation we can join the different…

Using Radar Charts with Qualitative Evaluation: Techniques to Assess Change in Blended Learning

ERIC Educational Resources Information Center

Kaczynski, Dan; Wood, Leigh; Harding, Ansie

2008-01-01

When university academics implement changes in learning, such as introducing blended learning, it is conventional practice to examine and evaluate the impact of the resulting curriculum reform. Judging the worth and impact of an educational development is a complex task involving subtle differences in learning. Qualitative methods to explore these…

They can interact, but can they learn? Toddlers' transfer learning from touchscreens and television.

PubMed

Moser, Alecia; Zimmermann, Laura; Dickerson, Kelly; Grenell, Amanda; Barr, Rachel; Gerhardstein, Peter

2015-09-01

Despite the ubiquity of touchscreen applications and television programs for young children, developmental research suggests that learning in this context is degraded relative to face-to-face interactions. Most previous research has been limited to transfer of learning from videos, making it difficult to isolate the relative perceptual and social influences for transfer difficulty, and has not examined whether the transfer deficit persists across early childhood when task complexity increases. The current study examined whether the transfer deficit persists in older children using a complex puzzle imitation task constructed to investigate transfer from video demonstrations. The current test adapted this task to permit bidirectional transfer from touchscreens as well. To test for bidirectional transfer deficits, 2.5- and 3-year-olds were shown how to assemble a three-piece puzzle on either a three-dimensional magnetic board or a two-dimensional touchscreen (Experiment 1). Unidirectional transfer from video was also tested (Experiment 2). Results indicate that a bidirectional transfer deficit persists through 3 years, with younger children showing a greater transfer deficit; despite high perceptual similarities and social engagement, children learned less in transfer tasks, supporting the memory flexibility account of the transfer deficit. Implications of these findings for use of screen media (e.g., video, tablets) in early education are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

Transfer of Complex Skill Learning from Virtual to Real Rowing

PubMed Central

Rauter, Georg; Sigrist, Roland; Koch, Claudio; Crivelli, Francesco; van Raai, Mark; Riener, Robert; Wolf, Peter

2013-01-01

Simulators are commonly used to train complex tasks. In particular, simulators are applied to train dangerous tasks, to save costs, and to investigate the impact of different factors on task performance. However, in most cases, the transfer of simulator training to the real task has not been investigated. Without a proof for successful skill transfer, simulators might not be helpful at all or even counter-productive for learning the real task. In this paper, the skill transfer of complex technical aspects trained on a scull rowing simulator to sculling on water was investigated. We assume if a simulator provides high fidelity rendering of the interactions with the environment even without augmented feedback, training on such a realistic simulator would allow similar skill gains as training in the real environment. These learned skills were expected to transfer to the real environment. Two groups of four recreational rowers participated. One group trained on water, the other group trained on a simulator. Within two weeks, both groups performed four training sessions with the same licensed rowing trainer. The development in performance was assessed by quantitative biomechanical performance measures and by a qualitative video evaluation of an independent, blinded trainer. In general, both groups could improve their performance on water. The used biomechanical measures seem to allow only a limited insight into the rowers' development, while the independent trainer could also rate the rowers' overall impression. The simulator quality and naturalism was confirmed by the participants in a questionnaire. In conclusion, realistic simulator training fostered skill gains to a similar extent as training in the real environment and enabled skill transfer to the real environment. In combination with augmented feedback, simulator training can be further exploited to foster motor learning even to a higher extent, which is subject to future work. PMID:24376518

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

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

PubMed Central

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

2011-01-01

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

A learning scheme for reach to grasp movements: on EMG-based interfaces using task specific motion decoding models.

PubMed

Liarokapis, Minas V; Artemiadis, Panagiotis K; Kyriakopoulos, Kostas J; Manolakos, Elias S

2013-09-01

A learning scheme based on random forests is used to discriminate between different reach to grasp movements in 3-D space, based on the myoelectric activity of human muscles of the upper-arm and the forearm. Task specificity for motion decoding is introduced in two different levels: Subspace to move toward and object to be grasped. The discrimination between the different reach to grasp strategies is accomplished with machine learning techniques for classification. The classification decision is then used in order to trigger an EMG-based task-specific motion decoding model. Task specific models manage to outperform "general" models providing better estimation accuracy. Thus, the proposed scheme takes advantage of a framework incorporating both a classifier and a regressor that cooperate advantageously in order to split the task space. The proposed learning scheme can be easily used to a series of EMG-based interfaces that must operate in real time, providing data-driven capabilities for multiclass problems, that occur in everyday life complex environments.

The effects of instructional sets on reactions to and performance on an intelligent tutoring system

NASA Technical Reports Server (NTRS)

Johnson, Debra Steele

1993-01-01

The effects of a contextual factor, i.e., task instructions, on performance on and reactions to an Intellegent Tutoring System (ITS) training Remote Manipulator System (RMS) tasks were examined. The results supported the first prediction that task instructions could be used to successfully induce a mastery versus an achievement orientation. Previous research suggests that a mastery orientation can result in beneficial effects on learning and performance of complex tasks. Furthermore, the results supported the second prediction that a mastery orientation would have beneficial effects on learning and performance as well as affective and cognitive reactions to the ITS tasks. Moreover, the results indicated that a mastery orientation was especially beneficial for the more complex ITS tasks and later in task practice, i.e., when a task was performed for the second time. A mastery orientation is posited to have its beneficial effects by focusing more effort and attention on task performance. Conclusions are drawn with some caution due to the small number of subjects, although the results for these subjects were consistent across multiple trials and multiple measures of performance. ITS designers are urged to consider contextual factors such as task instructions and feedback in terms of their potential to induce a mastery versus an achievement orientation.

Changes in Cerebral Hemodynamics during Complex Motor Learning by Character Entry into Touch-Screen Terminals.

PubMed

Sagari, Akira; Iso, Naoki; Moriuchi, Takefumi; Ogahara, Kakuya; Kitajima, Eiji; Tanaka, Koji; Tabira, Takayuki; Higashi, Toshio

2015-01-01

Studies of cerebral hemodynamics during motor learning have mostly focused on neurorehabilitation interventions and their effectiveness. However, only a few imaging studies of motor learning and the underlying complex cognitive processes have been performed. We measured cerebral hemodynamics using near-infrared spectroscopy (NIRS) in relation to acquisition patterns of motor skills in healthy subjects using character entry into a touch-screen terminal. Twenty healthy, right-handed subjects who had no previous experience with character entry using a touch-screen terminal participated in this study. They were asked to enter the characters of a randomly formed Japanese syllabary into the touch-screen terminal. All subjects performed the task with their right thumb for 15 s alternating with 25 s of rest for 30 repetitions. Performance was calculated by subtracting the number of incorrect answers from the number of correct answers, and gains in motor skills were evaluated according to the changes in performance across cycles. Behavioral and oxygenated hemoglobin concentration changes across task cycles were analyzed using Spearman's rank correlations. Performance correlated positively with task cycle, thus confirming motor learning. Hemodynamic activation over the left sensorimotor cortex (SMC) showed a positive correlation with task cycle, whereas activations over the right prefrontal cortex (PFC) and supplementary motor area (SMA) showed negative correlations. We suggest that increases in finger momentum with motor learning are reflected in the activity of the left SMC. We further speculate that the right PFC and SMA were activated during the early phases of motor learning, and that this activity was attenuated with learning progress.

Neural correlates of context-dependent feature conjunction learning in visual search tasks.

PubMed

Reavis, Eric A; Frank, Sebastian M; Greenlee, Mark W; Tse, Peter U

2016-06-01

Many perceptual learning experiments show that repeated exposure to a basic visual feature such as a specific orientation or spatial frequency can modify perception of that feature, and that those perceptual changes are associated with changes in neural tuning early in visual processing. Such perceptual learning effects thus exert a bottom-up influence on subsequent stimulus processing, independent of task-demands or endogenous influences (e.g., volitional attention). However, it is unclear whether such bottom-up changes in perception can occur as more complex stimuli such as conjunctions of visual features are learned. It is not known whether changes in the efficiency with which people learn to process feature conjunctions in a task (e.g., visual search) reflect true bottom-up perceptual learning versus top-down, task-related learning (e.g., learning better control of endogenous attention). Here we show that feature conjunction learning in visual search leads to bottom-up changes in stimulus processing. First, using fMRI, we demonstrate that conjunction learning in visual search has a distinct neural signature: an increase in target-evoked activity relative to distractor-evoked activity (i.e., a relative increase in target salience). Second, we demonstrate that after learning, this neural signature is still evident even when participants passively view learned stimuli while performing an unrelated, attention-demanding task. This suggests that conjunction learning results in altered bottom-up perceptual processing of the learned conjunction stimuli (i.e., a perceptual change independent of the task). We further show that the acquired change in target-evoked activity is contextually dependent on the presence of distractors, suggesting that search array Gestalts are learned. Hum Brain Mapp 37:2319-2330, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Adaptive learning in complex reproducing kernel Hilbert spaces employing Wirtinger's subgradients.

PubMed

Bouboulis, Pantelis; Slavakis, Konstantinos; Theodoridis, Sergios

2012-03-01

This paper presents a wide framework for non-linear online supervised learning tasks in the context of complex valued signal processing. The (complex) input data are mapped into a complex reproducing kernel Hilbert space (RKHS), where the learning phase is taking place. Both pure complex kernels and real kernels (via the complexification trick) can be employed. Moreover, any convex, continuous and not necessarily differentiable function can be used to measure the loss between the output of the specific system and the desired response. The only requirement is the subgradient of the adopted loss function to be available in an analytic form. In order to derive analytically the subgradients, the principles of the (recently developed) Wirtinger's calculus in complex RKHS are exploited. Furthermore, both linear and widely linear (in RKHS) estimation filters are considered. To cope with the problem of increasing memory requirements, which is present in almost all online schemes in RKHS, the sparsification scheme, based on projection onto closed balls, has been adopted. We demonstrate the effectiveness of the proposed framework in a non-linear channel identification task, a non-linear channel equalization problem and a quadrature phase shift keying equalization scheme, using both circular and non circular synthetic signal sources.

Cathodal Transcranial Direct Current Stimulation Over Left Dorsolateral Prefrontal Cortex Area Promotes Implicit Motor Learning in a Golf Putting Task.

PubMed

Zhu, Frank F; Yeung, Andrew Y; Poolton, Jamie M; Lee, Tatia M C; Leung, Gilberto K K; Masters, Rich S W

2015-01-01

Implicit motor learning is characterized by low dependence on working memory and stable performance despite stress, fatigue, or multi-tasking. However, current paradigms for implicit motor learning are based on behavioral interventions that are often task-specific and limited when applied in practice. To investigate whether cathodal transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (DLPFC) area during motor learning suppressed working memory activity and reduced explicit verbal-analytical involvement in movement control, thereby promoting implicit motor learning. Twenty-seven healthy individuals practiced a golf putting task during a Training Phase while receiving either real cathodal tDCS stimulation over the left DLPFC area or sham stimulation. Their performance was assessed during a Test phase on another day. Verbal working memory capacity was assessed before and after the Training Phase, and before the Test Phase. Compared to sham stimulation, real stimulation suppressed verbal working memory activity after the Training Phase, but enhanced golf putting performance during the Training Phase and the Test Phase, especially when participants were required to multi-task. Cathodal tDCS over the left DLPFC may foster implicit motor learning and performance in complex real-life motor tasks that occur during sports, surgery or motor rehabilitation. Copyright © 2015 Elsevier Inc. All rights reserved.

Functional Contour-following via Haptic Perception and Reinforcement Learning.

PubMed

Hellman, Randall B; Tekin, Cem; van der Schaar, Mihaela; Santos, Veronica J

2018-01-01

Many tasks involve the fine manipulation of objects despite limited visual feedback. In such scenarios, tactile and proprioceptive feedback can be leveraged for task completion. We present an approach for real-time haptic perception and decision-making for a haptics-driven, functional contour-following task: the closure of a ziplock bag. This task is challenging for robots because the bag is deformable, transparent, and visually occluded by artificial fingertip sensors that are also compliant. A deep neural net classifier was trained to estimate the state of a zipper within a robot's pinch grasp. A Contextual Multi-Armed Bandit (C-MAB) reinforcement learning algorithm was implemented to maximize cumulative rewards by balancing exploration versus exploitation of the state-action space. The C-MAB learner outperformed a benchmark Q-learner by more efficiently exploring the state-action space while learning a hard-to-code task. The learned C-MAB policy was tested with novel ziplock bag scenarios and contours (wire, rope). Importantly, this work contributes to the development of reinforcement learning approaches that account for limited resources such as hardware life and researcher time. As robots are used to perform complex, physically interactive tasks in unstructured or unmodeled environments, it becomes important to develop methods that enable efficient and effective learning with physical testbeds.

Scaffolding Learning by Modelling: The Effects of Partially Worked-out Models

ERIC Educational Resources Information Center

Mulder, Yvonne G.; Bollen, Lars; de Jong, Ton; Lazonder, Ard W.

2016-01-01

Creating executable computer models is a potentially powerful approach to science learning. Learning by modelling is also challenging because students can easily get overwhelmed by the inherent complexities of the task. This study investigated whether offering partially worked-out models can facilitate students' modelling practices and promote…

Hybrid computing using a neural network with dynamic external memory.

PubMed

Graves, Alex; Wayne, Greg; Reynolds, Malcolm; Harley, Tim; Danihelka, Ivo; Grabska-Barwińska, Agnieszka; Colmenarejo, Sergio Gómez; Grefenstette, Edward; Ramalho, Tiago; Agapiou, John; Badia, Adrià Puigdomènech; Hermann, Karl Moritz; Zwols, Yori; Ostrovski, Georg; Cain, Adam; King, Helen; Summerfield, Christopher; Blunsom, Phil; Kavukcuoglu, Koray; Hassabis, Demis

2016-10-27

Artificial neural networks are remarkably adept at sensory processing, sequence learning and reinforcement learning, but are limited in their ability to represent variables and data structures and to store data over long timescales, owing to the lack of an external memory. Here we introduce a machine learning model called a differentiable neural computer (DNC), which consists of a neural network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer. Like a conventional computer, it can use its memory to represent and manipulate complex data structures, but, like a neural network, it can learn to do so from data. When trained with supervised learning, we demonstrate that a DNC can successfully answer synthetic questions designed to emulate reasoning and inference problems in natural language. We show that it can learn tasks such as finding the shortest path between specified points and inferring the missing links in randomly generated graphs, and then generalize these tasks to specific graphs such as transport networks and family trees. When trained with reinforcement learning, a DNC can complete a moving blocks puzzle in which changing goals are specified by sequences of symbols. Taken together, our results demonstrate that DNCs have the capacity to solve complex, structured tasks that are inaccessible to neural networks without external read-write memory.

A Cognitive Load Approach to Collaborative Learning: United Brains for Complex Tasks

ERIC Educational Resources Information Center

Kirschner, Femke; Paas, Fred; Kirschner, Paul A.

2009-01-01

This article presents a review of research comparing the effectiveness of individual learning environments with collaborative learning environments. In reviewing the literature, it was determined that there is no clear and unequivocal picture of how, when, and why the effectiveness of these two approaches to learning differ, a result which may be…

Adult Cleaner Wrasse Outperform Capuchin Monkeys, Chimpanzees and Orang-utans in a Complex Foraging Task Derived from Cleaner – Client Reef Fish Cooperation

PubMed Central

Proctor, Darby; Essler, Jennifer; Pinto, Ana I.; Wismer, Sharon; Stoinski, Tara; Brosnan, Sarah F.; Bshary, Redouan

2012-01-01

The insight that animals' cognitive abilities are linked to their evolutionary history, and hence their ecology, provides the framework for the comparative approach. Despite primates renowned dietary complexity and social cognition, including cooperative abilities, we here demonstrate that cleaner wrasse outperform three primate species, capuchin monkeys, chimpanzees and orang-utans, in a foraging task involving a choice between two actions, both of which yield identical immediate rewards, but only one of which yields an additional delayed reward. The foraging task decisions involve partner choice in cleaners: they must service visiting client reef fish before resident clients to access both; otherwise the former switch to a different cleaner. Wild caught adult, but not juvenile, cleaners learned to solve the task quickly and relearned the task when it was reversed. The majority of primates failed to perform above chance after 100 trials, which is in sharp contrast to previous studies showing that primates easily learn to choose an action that yields immediate double rewards compared to an alternative action. In conclusion, the adult cleaners' ability to choose a superior action with initially neutral consequences is likely due to repeated exposure in nature, which leads to specific learned optimal foraging decision rules. PMID:23185293

Practice reduces task relevant variance modulation and forms nominal trajectory

NASA Astrophysics Data System (ADS)

Osu, Rieko; Morishige, Ken-Ichi; Nakanishi, Jun; Miyamoto, Hiroyuki; Kawato, Mitsuo

2015-12-01

Humans are capable of achieving complex tasks with redundant degrees of freedom. Much attention has been paid to task relevant variance modulation as an indication of online feedback control strategies to cope with motor variability. Meanwhile, it has been discussed that the brain learns internal models of environments to realize feedforward control with nominal trajectories. Here we examined trajectory variance in both spatial and temporal domains to elucidate the relative contribution of these control schemas. We asked subjects to learn reaching movements with multiple via-points, and found that hand trajectories converged to stereotyped trajectories with the reduction of task relevant variance modulation as learning proceeded. Furthermore, variance reduction was not always associated with task constraints but was highly correlated with the velocity profile. A model assuming noise both on the nominal trajectory and motor command was able to reproduce the observed variance modulation, supporting an expression of nominal trajectories in the brain. The learning-related decrease in task-relevant modulation revealed a reduction in the influence of optimal feedback around the task constraints. After practice, the major part of computation seems to be taken over by the feedforward controller around the nominal trajectory with feedback added only when it becomes necessary.

Virtual reality for gait training: can it induce motor learning to enhance complex walking and reduce fall risk in patients with Parkinson's disease?

PubMed

Mirelman, Anat; Maidan, Inbal; Herman, Talia; Deutsch, Judith E; Giladi, Nir; Hausdorff, Jeffrey M

2011-02-01

Gait and cognitive disturbances are common in Parkinson's disease (PD). These deficits exacerbate fall risk and difficulties with mobility, especially during complex or dual-task walking. Traditional gait training generally fails to fully address these complex gait activities. Virtual reality (VR) incorporates principles of motor learning while delivering engaging and challenging training in complex environments. We hypothesized that VR may be applied to address the multifaceted deficits associated with fall risk in PD. Twenty patients received 18 sessions (3 per week) of progressive intensive treadmill training with virtual obstacles (TT + VR). Outcome measures included gait under usual-walking and dual-task conditions and while negotiating physical obstacles. Cognitive function and functional performance were also assessed. Patients were 67.1 ± 6.5 years and had a mean disease duration of 9.8 ± 5.6 years. Posttraining, gait speed significantly improved during usual walking, during dual task, and while negotiating overground obstacles. Dual-task gait variability decreased (ie, improved) and Trail Making Test times (parts A and B) improved. Gains in functional performance measures and retention effects, 1 month later, were also observed. To our knowledge, this is the first time that TT + VR has been used for gait training in PD. The results indicate that TT + VR is viable in PD and may significantly improve physical performance, gait during complex challenging conditions, and even certain aspects of cognitive function. These findings have important implications for understanding motor learning in the presence of PD and for treating fall risk in PD, aging, and others who share a heightened risk of falls.

Students transcribing tasks: Noticing Fluency, Accuracy, and Complexity

ERIC Educational Resources Information Center

Stillwell, Christopher; Curabba, Brad; Alexander, Kamsin; Kidd, Andrew; Kim, Euna; Stone, Paul; Wyle, Christopher

2010-01-01

Student self-transcription can greatly enhance the power of tasks to promote language learning, for it allows students to re-examine their experience freed from the pressure of performing the task itself, so they can notice and reflect on the language used and encountered. This is a powerful step in language development because it allows for…

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

ERIC Educational Resources Information Center

Bole, Ronald

1976-01-01

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

Measuring learning potential in people with schizophrenia: A comparison of two tasks.

PubMed

Rempfer, Melisa V; McDowd, Joan M; Brown, Catana E

2017-12-01

Learning potential measures utilize dynamic assessment methods to capture performance changes following training on a cognitive task. Learning potential has been explored in schizophrenia research as a predictor of functional outcome and there have been calls for psychometric development in this area. Because the majority of learning potential studies have utilized the Wisconsin Card Sorting Test (WCST), we extended this work using a novel measure, the Rey Osterrieth Complex Figure Test (ROCFT). This study had the following aims: 1) to examine relationships among different learning potential indices for two dynamic assessment tasks, 2) to examine the association between WCST and ROCFT learning potential measures, and 3) to address concurrent validity with a performance-based measure of functioning (Test of Grocery Shopping Skills; TOGSS). Eighty-one adults with schizophrenia or schizoaffective disorder completed WCST and ROCFT learning measures and the TOGSS. Results indicated the various learning potential computational indices are intercorrelated and, similar to other studies, we found support for regression residuals and post-test scores as optimal indices. Further, we found modest relationships between the two learning potential measures and the TOGSS. These findings suggest learning potential includes both general and task-specific constructs but future research is needed to further explore this question. Copyright © 2017 Elsevier B.V. All rights reserved.

The Importance of Team Sex Composition in Team-Training Research Employing Complex Psychomotor Tasks.

PubMed

Jarrett, Steven M; Glaze, Ryan M; Schurig, Ira; Arthur, Winfred

2017-08-01

The relationship between team sex composition and team performance on a complex psychomotor task was examined because these types of tasks are commonly used in the lab-based teams literature. Despite well-documented sex-based differences on complex psychomotor tasks, the preponderance of studies-mainly lab based-that use these tasks makes no mention of the sex composition of teams across or within experimental conditions. A sample of 123 four-person teams with varying team sex composition learned and performed a complex psychomotor task, Steal Beasts Pro PE. Each team completed a 5-hr protocol whereby they conducted several performance missions. The results indicated significant large mean differences such that teams with larger proportions of males had higher performance scores. These findings demonstrate the potential effect of team sex composition on the validity of studies that use complex psychomotor tasks to explore and investigate team performance-related phenomena when (a) team sex composition is not a focal variable of interest and (b) it is not accounted for or controlled. Given the proclivity of complex psychomotor action-based tasks used in lab-based team studies, it is important to understand and control for the impact of team sex composition on team performance. When team sex composition is not controlled for, either methodologically or statistically, it may affect the validity of the results in teams studies using these types of tasks.

Complex Dynamic Systems View on Conceptual Change: How a Picture of Students' Intuitive Conceptions Accrue from Dynamically Robust Task Dependent Learning Outcomes

ERIC Educational Resources Information Center

Koponen, Ismo T.; Kokkonen, Tommi; Nousiainen, Maiji

2017-01-01

We discuss here conceptual change and the formation of robust learning outcomes from the viewpoint of complex dynamic systems (CDS). The CDS view considers students' conceptions as context dependent and multifaceted structures which depend on the context of their application. In the CDS view the conceptual patterns (i.e. intuitive conceptions…

Effect of Chunk Strength on the Performance of Children with Developmental Dyslexia on Artificial Grammar Learning Task May Be Related to Complexity

ERIC Educational Resources Information Center

Schiff, Rachel; Katan, Pesia; Sasson, Ayelet; Kahta, Shani

2017-01-01

There is a long held view that chunks play a crucial role in artificial grammar learning performance. We compared chunk strength influences on performance, in high and low topological entropy (a measure of complexity) grammar systems, with dyslexic children, age-matched and reading-level-matched control participants. Findings show that age-matched…

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study

PubMed Central

2010-01-01

Background Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. Results An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. Conclusions The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering of their complex mechanism. PMID:20380733

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study.

PubMed

Liu, Qi; Xu, Qian; Zheng, Vincent W; Xue, Hong; Cao, Zhiwei; Yang, Qiang

2010-04-10

Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering of their complex mechanism.

Serious games and blended learning; effects on performance and motivation in medical education.

PubMed

Dankbaar, Mary

2017-02-01

More efficient, flexible training models are needed in medical education. Information technology offers the tools to design and develop effective and more efficient training. The aims of this thesis were: 1) Compare the effectiveness of blended versus classroom training for the acquisition of knowledge; 2) Investigate the effectiveness and critical design features of serious games for performance improvement and motivation. Five empirical studies were conducted to answer the research questions and a descriptive study on an evaluation framework to assess serious games was performed. The results of the research studies indicated that: 1) For knowledge acquisition, blended learning is equally effective and attractive for learners as classroom learning; 2) A serious game with realistic, interactive cases improved complex cognitive skills for residents, with limited self-study time. Although the same game was motivating for inexperienced medical students and stimulated them to study longer, it did not improve their cognitive skills, compared with what they learned from an instructional e‑module. This indicates an 'expertise reversal effect', where a rich learning environment is effective for experts, but may be contra-productive for novices (interaction of prior knowledge and complexity of format). A blended design is equally effective and attractive as classroom training. Blended learning facilitates adaptation to the learners' knowledge level, flexibility in time and scalability of learning. Games may support skills learning, provided task complexity matches the learner's competency level. More design-based research is needed on the effects of task complexity and other design features on performance improvement, for both novices and experts.

Effects of cerebellar nuclear inactivation on the learning of a complex forelimb movement in cats.

PubMed

Wang, J J; Shimansky, Y; Bracha, V; Bloedel, J R

1998-05-01

The purpose of this study was to determine the effects of inactivating concurrently the cerebellar interposed and dentate nuclei on the capacity of cats to acquire and retain a complex, goal-directed forelimb movement. To assess the effects on acquisition, cats were required to learn to move a vertical manipulandum bar through a two-segment template with a shape approximating an inverted "L" after the injection of muscimol (saline for the control group) in the interposed and dentate cerebellar nuclei. During training periods, they were exposed progressively to more difficult templates, which were created by decreasing the angle between the two segments of the template. After determining the most difficult template the injected animals could learn within the specified time and performance constraints, the retraining phase of the experiment was initiated in which the cats were required to execute the same sequence of templates in the absence of any injection. This stage of the experiment assessed retention and determined the extent of any relearning required to execute the task at criterion levels. Next, the animals were overtrained without any injection on the most difficult template they could perform. Finally, to determine the effects of nuclear inactivation on retention after extensive retraining, their capacity to perform the same template was determined after muscimol injection in the interposed and dentate nuclei. The findings show that during the inactivation of the dentate and interposed nuclei the animals could learn to execute the more difficult templates. However, when required to execute the most difficult template learned under muscimol on the day after injections were discontinued, the cats had to "relearn" (reacquire) the movement. Finally, when the cerebellar nuclei were inactivated after the animals learned the task in the absence of any injections during the retraining phase, retention was not blocked. The data indicate that the intermediate and lateral cerebellum are not required either for learning this type of complex voluntary movement or for retaining the capacity to perform the task once it is learned. Nevertheless, when the cerebellum becomes available for executing a task learned in the absence of this structure, reacquisition of the behavior usually is necessary. It is hypothesized that the relearning observed after acquisition during muscimol inactivation reflects the tendency of the system to incorporate the cerebellum into the interactions responsible for the learning and performance of a motor sequence that is optimal for executing the task.

Programming Pluralism: Using Learning Analytics to Detect Patterns in the Learning of Computer Programming

ERIC Educational Resources Information Center

Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne

2014-01-01

New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…

The Validation Challenge: How Close Is Europe to Recognising All Learning? Briefing Note

ERIC Educational Resources Information Center

Cedefop - European Centre for the Development of Vocational Training, 2014

2014-01-01

The European inventory on validation of non-formal and informal learning provides an unrivaled source of information detailing how validation of prior learning is developing across Europe. It shows that validation strategies and legislation, despite complexity of the task before them, have been developing slowly but steadily. However, there is…

Ontology Mapping Neural Network: An Approach to Learning and Inferring Correspondences among Ontologies

ERIC Educational Resources Information Center

Peng, Yefei

2010-01-01

An ontology mapping neural network (OMNN) is proposed in order to learn and infer correspondences among ontologies. It extends the Identical Elements Neural Network (IENN)'s ability to represent and map complex relationships. The learning dynamics of simultaneous (interlaced) training of similar tasks interact at the shared connections of the…

Intervening or Ignoring: Learning about Teaching in New Times

ERIC Educational Resources Information Center

Blaise, Mindy; Elsden-Clifton, Jennifer

2007-01-01

In response to the rise of collaborative learning within education, two teacher educators redesigned their courses to explore the complexities of pedagogy within a New Learning framework. Multi-age grouping provided opportunities for pre-service teachers to work with others from different year levels on an interdisciplinary assessment task. As a…

Studying Language Learning Opportunities Afforded by a Collaborative CALL Task

ERIC Educational Resources Information Center

Leahy, Christine

2016-01-01

This research study explores the learning potential of a computer-assisted language learning (CALL) activity. Research suggests that the dual emphasis on content development and language accuracy, as well as the complexity of L2 production in natural settings, can potentially create cognitive overload. This study poses the question whether, and…

An Ontology Infrastructure for an E-Learning Scenario

ERIC Educational Resources Information Center

Guo, Wen-Ying; Chen, De-Ren

2007-01-01

Selecting appropriate learning services for a learner from a large number of heterogeneous knowledge sources is a complex and challenging task. This article illustrates and discusses how Semantic Web technologies such as RDF [resource description framework] and ontology can be applied to e-learning systems to help the learner in selecting an…

Stimulation of dopamine D₁ receptor improves learning capacity in cooperating cleaner fish.

PubMed

Messias, João P M; Santos, Teresa P; Pinto, Maria; Soares, Marta C

2016-01-27

Accurate contextual decision-making strategies are important in social environments. Specific areas in the brain are tasked to process these complex interactions and generate correct follow-up responses. The dorsolateral and dorsomedial parts of the telencephalon in the teleost fish brain are neural substrates modulated by the neurotransmitter dopamine (DA), and are part of an important neural circuitry that drives animal behaviour from the most basic actions such as learning to search for food, to properly choosing partners and managing decisions based on context. The Indo-Pacific cleaner wrasse Labroides dimidiatus is a highly social teleost fish species with a complex network of interactions with its 'client' reef fish. We asked if changes in DA signalling would affect individual learning ability by presenting cleaner fish two ecologically different tasks that simulated a natural situation requiring accurate decision-making. We demonstrate that there is an involvement of the DA system and D1 receptor pathways on cleaners' natural abilities to learn both tasks. Our results add significantly to the growing literature on the physiological mechanisms that underlie and facilitate the expression of cooperative abilities. © 2016 The Author(s).

Is Mathematical Anxiety Always Bad for Math Learning: The Role of Math Motivation

PubMed Central

Wang, Zhe; Lukowski, Sarah L.; Hart, Sara Ann; Lyons, Ian M.; Thompson, Lee A.; Kovas, Yulia; Mazzocco, Michèle M.; Plomin, Robert; Petrill, Stephen A.

2015-01-01

The linear relations between math anxiety and math cognition have been frequently studied. However, the relations between anxiety and performance on complex cognitive tasks have been repeatedly demonstrated to follow a curvilinear fashion. Given the lack of attention to the possibility of such complex interplay between emotion and cognition in the math learning literature, the current study aimed to address this gap via exploring the relations between math anxiety, math motivation, and math cognition. The current study consisted of two samples. One sample included 262 pairs of young adolescent twins and the other included 237 adult college students. Participants self-reported their math anxiety and math motivation. Math cognition was assessed using a comprehensive battery of mathematics tasks. In both samples, results showed inverted-U relations between math anxiety and math performance in students with high intrinsic math motivation, and modest negative associations between math anxiety and math performance in students with low intrinsic math motivation. However, this pattern was not observed in tasks assessing student’s nonsymbolic and symbolic number estimation. These findings may help advance our understanding of mathematics learning processes and may provide important insights for treatment programs that target improving mathematics learning experiences and mathematical skills. PMID:26518438

Faded-example as a Tool to Acquire and Automate Mathematics Knowledge

NASA Astrophysics Data System (ADS)

Retnowati, E.

2017-04-01

Students themselves accomplish Knowledge acquisition and automation. The teacher plays a role as the facilitator by creating mathematics tasks that assist students in building knowledge efficiently and effectively. Cognitive load caused by learning material presented by teachers should be considered as a critical factor. While the intrinsic cognitive load is related to the degree of complexity of the material learning ones can handle, the extraneous cognitive load is directly caused by how the material is presented. Strategies to present a learning material in computational learning domains like mathematics are a namely worked example (fully-guided task) or problem-solving (discovery task with no guidance). According to the empirical evidence, learning based on problem-solving may cause high-extraneous cognitive load for students who have limited prior knowledge, conversely learn based on worked example may cause high-extraneous cognitive load for students who have mastered the knowledge base. An alternative is a faded example consisting of the partly-completed task. Learning from faded-example can facilitate students who already acquire some knowledge about the to-be-learned material but still need more practice to automate the knowledge further. This instructional strategy provides a smooth transition from a fully-guided into an independent problem solver. Designs of faded examples for learning trigonometry are discussed.

Gaze entropy reflects surgical task load.

PubMed

Di Stasi, Leandro L; Diaz-Piedra, Carolina; Rieiro, Héctor; Sánchez Carrión, José M; Martin Berrido, Mercedes; Olivares, Gonzalo; Catena, Andrés

2016-11-01

Task (over-)load imposed on surgeons is a main contributing factor to surgical errors. Recent research has shown that gaze metrics represent a valid and objective index to asses operator task load in non-surgical scenarios. Thus, gaze metrics have the potential to improve workplace safety by providing accurate measurements of task load variations. However, the direct relationship between gaze metrics and surgical task load has not been investigated yet. We studied the effects of surgical task complexity on the gaze metrics of surgical trainees. We recorded the eye movements of 18 surgical residents, using a mobile eye tracker system, during the performance of three high-fidelity virtual simulations of laparoscopic exercises of increasing complexity level: Clip Applying exercise, Cutting Big exercise, and Translocation of Objects exercise. We also measured performance accuracy and subjective rating of complexity. Gaze entropy and velocity linearly increased with increased task complexity: Visual exploration pattern became less stereotyped (i.e., more random) and faster during the more complex exercises. Residents performed better the Clip Applying exercise and the Cutting Big exercise than the Translocation of Objects exercise and their perceived task complexity differed accordingly. Our data show that gaze metrics are a valid and reliable surgical task load index. These findings have potential impacts to improve patient safety by providing accurate measurements of surgeon task (over-)load and might provide future indices to assess residents' learning curves, independently of expensive virtual simulators or time-consuming expert evaluation.

Testing complex animal cognition: Concept learning, proactive interference, and list memory.

PubMed

Wright, Anthony A

2018-01-01

This article describes an approach for assessing and comparing complex cognition in rhesus monkeys and pigeons by training them in a sequence of synergistic tasks, each yielding a whole function for enhanced comparisons. These species were trained in similar same/different tasks with expanding training sets (8, 16, 32, 64, 128 … 1024 pictures) followed by novel-stimulus transfer eventually resulting in full abstract-concept learning. Concept-learning functions revealed better rhesus transfer throughout and full concept learning at the 128 set, versus pigeons at the 256 set. They were then tested in delayed same/different tasks for proactive interference by inserting occasional tests within trial-unique sessions where the test stimulus matched a previous sample stimulus (1, 2, 4, 8, 16 trials prior). Proactive-interference functions revealed time-based interference for pigeons (1, 10 s delays), but event-based interference for rhesus (no effect of 1, 10, 20 s delays). They were then tested in list-memory tasks by expanding the sample to four samples in trial-unique sessions (minimizing proactive interference). The four-item, list-memory functions revealed strong recency memory at short delays, gradually changing to strong primacy memory at long delays over 30 s for rhesus, and 10 s for pigeons. Other species comparisons and future directions are discussed. © 2018 Society for the Experimental Analysis of Behavior.

Age-related changes in learning across early childhood: a new imitation task.

PubMed

Dickerson, Kelly; Gerhardstein, Peter; Zack, Elizabeth; Barr, Rachel

2013-11-01

Imitation plays a critical role in social and cognitive development, but the social learning mechanisms contributing to the development of imitation are not well understood. We developed a new imitation task designed to examine social learning mechanisms across the early childhood period. The new task involves assembly of abstract-shaped puzzle pieces in an arbitrary sequence on a magnet board. Additionally, we introduce a new scoring system that extends traditional goal-directed imitation scoring to include measures of both children's success at copying gestures (sliding the puzzle pieces) and goals (connecting the puzzle pieces). In Experiment 1, we demonstrated an age-invariant baseline from 1.5 to 3.5 years of age, accompanied by age-related changes in success at copying goals and gestures from a live demonstrator. In Experiment 2, we applied our new task to learning following a video demonstration. Imitation performance in the video demonstration group lagged behind that of the live demonstration group, showing a protracted video deficit effect. Across both experiments, children were more likely to copy gestures at earlier ages, suggesting mimicry, and only later copy both goals and gestures, suggesting imitation. Taken together, the findings suggest that different social learning strategies may predominate in imitation learning dependent upon the degree of object affordance, task novelty, and task complexity. © 2012 Wiley Periodicals, Inc.

Intelligence and Changes in Regional Cerebral Glucose Metabolic Rate Following Learning.

ERIC Educational Resources Information Center

Haier, Richard J.; And Others

1992-01-01

A study of eight normal right-handed men demonstrates widespread significant decreases in brain glucose metabolic rate (GMR) following learning a complex computer task, a computer game. Correlations between magnitude of GMR change and intelligence scores are also demonstrated. (SLD)

Learning through Conversation.

ERIC Educational Resources Information Center

Kelly, Patricia R.; Klein, Adria F.; Pinnell, Gay Su

1996-01-01

Through teacher-child conversation, experts use oral language to help novices take on more complex tasks; and Reading Recovery children, who are obviously having difficulty with school-based learning, are especially in need of significant conversations with adults. Reading and writing processes are supported through conversation with Reading…

Multimodal sequence learning.

PubMed

Kemény, Ferenc; Meier, Beat

2016-02-01

While sequence learning research models complex phenomena, previous studies have mostly focused on unimodal sequences. The goal of the current experiment is to put implicit sequence learning into a multimodal context: to test whether it can operate across different modalities. We used the Task Sequence Learning paradigm to test whether sequence learning varies across modalities, and whether participants are able to learn multimodal sequences. Our results show that implicit sequence learning is very similar regardless of the source modality. However, the presence of correlated task and response sequences was required for learning to take place. The experiment provides new evidence for implicit sequence learning of abstract conceptual representations. In general, the results suggest that correlated sequences are necessary for implicit sequence learning to occur. Moreover, they show that elements from different modalities can be automatically integrated into one unitary multimodal sequence. Copyright © 2015 Elsevier B.V. All rights reserved.

An investigation of fMRI time series stationarity during motor sequence learning foot tapping tasks.

PubMed

Muhei-aldin, Othman; VanSwearingen, Jessie; Karim, Helmet; Huppert, Theodore; Sparto, Patrick J; Erickson, Kirk I; Sejdić, Ervin

2014-04-30

Understanding complex brain networks using functional magnetic resonance imaging (fMRI) is of great interest to clinical and scientific communities. To utilize advanced analysis methods such as graph theory for these investigations, the stationarity of fMRI time series needs to be understood as it has important implications on the choice of appropriate approaches for the analysis of complex brain networks. In this paper, we investigated the stationarity of fMRI time series acquired from twelve healthy participants while they performed a motor (foot tapping sequence) learning task. Since prior studies have documented that learning is associated with systematic changes in brain activation, a sequence learning task is an optimal paradigm to assess the degree of non-stationarity in fMRI time-series in clinically relevant brain areas. We predicted that brain regions involved in a "learning network" would demonstrate non-stationarity and may violate assumptions associated with some advanced analysis approaches. Six blocks of learning, and six control blocks of a foot tapping sequence were performed in a fixed order. The reverse arrangement test was utilized to investigate the time series stationarity. Our analysis showed some non-stationary signals with a time varying first moment as a major source of non-stationarity. We also demonstrated a decreased number of non-stationarities in the third block as a result of priming and repetition. Most of the current literature does not examine stationarity prior to processing. The implication of our findings is that future investigations analyzing complex brain networks should utilize approaches robust to non-stationarities, as graph-theoretical approaches can be sensitive to non-stationarities present in data. Copyright © 2014 Elsevier B.V. All rights reserved.

Automated Cognitive Health Assessment Using Smart Home Monitoring of Complex Tasks

PubMed Central

Dawadi, Prafulla N.; Cook, Diane J.; Schmitter-Edgecombe, Maureen

2014-01-01

One of the many services that intelligent systems can provide is the automated assessment of resident well-being. We hypothesize that the functional health of individuals, or ability of individuals to perform activities independently without assistance, can be estimated by tracking their activities using smart home technologies. In this paper, we introduce a machine learning-based method for assessing activity quality in smart homes. To validate our approach we quantify activity quality for 179 volunteer participants who performed a complex, interweaved set of activities in our smart home apartment. We observed a statistically significant correlation (r=0.79) between automated assessment of task quality and direct observation scores. Using machine learning techniques to predict the cognitive health of the participants based on task quality is accomplished with an AUC value of 0.64. We believe that this capability is an important step in understanding everyday functional health of individuals in their home environments. PMID:25530925

Automated Cognitive Health Assessment Using Smart Home Monitoring of Complex Tasks.

PubMed

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen

2013-11-01

One of the many services that intelligent systems can provide is the automated assessment of resident well-being. We hypothesize that the functional health of individuals, or ability of individuals to perform activities independently without assistance, can be estimated by tracking their activities using smart home technologies. In this paper, we introduce a machine learning-based method for assessing activity quality in smart homes. To validate our approach we quantify activity quality for 179 volunteer participants who performed a complex, interweaved set of activities in our smart home apartment. We observed a statistically significant correlation (r=0.79) between automated assessment of task quality and direct observation scores. Using machine learning techniques to predict the cognitive health of the participants based on task quality is accomplished with an AUC value of 0.64. We believe that this capability is an important step in understanding everyday functional health of individuals in their home environments.

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

PubMed Central

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

2012-01-01

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

A dual-learning paradigm can simultaneously train multiple characteristics of walking

PubMed Central

Toliver, Alexis; Bastian, Amy J.

2016-01-01

Impairments in human motor patterns are complex: what is often observed as a single global deficit (e.g., limping when walking) is actually the sum of several distinct abnormalities. Motor adaptation can be useful to teach patients more normal motor patterns, yet conventional training paradigms focus on individual features of a movement, leaving others unaddressed. It is known that under certain conditions, distinct movement components can be simultaneously adapted without interference. These previous “dual-learning” studies focused solely on short, planar reaching movements, yet it is unknown whether these findings can generalize to a more complex behavior like walking. Here we asked whether a dual-learning paradigm, incorporating two distinct motor adaptation tasks, can be used to simultaneously train multiple components of the walking pattern. We developed a joint-angle learning task that provided biased visual feedback of sagittal joint angles to increase peak knee or hip flexion during the swing phase of walking. Healthy, young participants performed this task independently or concurrently with another locomotor adaptation task, split-belt treadmill adaptation, where subjects adapted their step length symmetry. We found that participants were able to successfully adapt both components of the walking pattern simultaneously, without interference, and at the same rate as adapting either component independently. This leads us to the interesting possibility that combining rehabilitation modalities within a single training session could be used to help alleviate multiple deficits at once in patients with complex gait impairments. PMID:26961100

Understanding psychiatric disorder by capturing ecologically relevant features of learning and decision-making.

PubMed

Scholl, Jacqueline; Klein-Flügge, Miriam

2017-09-28

Recent research in cognitive neuroscience has begun to uncover the processes underlying increasingly complex voluntary behaviours, including learning and decision-making. Partly this success has been possible by progressing from simple experimental tasks to paradigms that incorporate more ecological features. More specifically, the premise is that to understand cognitions and brain functions relevant for real life, we need to introduce some of the ecological challenges that we have evolved to solve. This often entails an increase in task complexity, which can be managed by using computational models to help parse complex behaviours into specific component mechanisms. Here we propose that using computational models with tasks that capture ecologically relevant learning and decision-making processes may provide a critical advantage for capturing the mechanisms underlying symptoms of disorders in psychiatry. As a result, it may help develop mechanistic approaches towards diagnosis and treatment. We begin this review by mapping out the basic concepts and models of learning and decision-making. We then move on to consider specific challenges that emerge in realistic environments and describe how they can be captured by tasks. These include changes of context, uncertainty, reflexive/emotional biases, cost-benefit decision-making, and balancing exploration and exploitation. Where appropriate we highlight future or current links to psychiatry. We particularly draw examples from research on clinical depression, a disorder that greatly compromises motivated behaviours in real-life, but where simpler paradigms have yielded mixed results. Finally, we highlight several paradigms that could be used to help provide new insights into the mechanisms of psychiatric disorders. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

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.

A Comparison of Learning Environments: All That Glitters... Interim Technical Paper for Period January 1990-July 1991.

ERIC Educational Resources Information Center

Shute, Valerie J.

Aptitude-treatment interactions (ATIs) refer to the covariation between learner characteristic and instructional treatment in relation to some outcome measure. To systematically test for ATI, an intelligent tutoring system instructing in basic principles of electricity was chosen as a complex but controlled learning task. Two learning environments…

Learning to Write: Progress-Monitoring Tools for Beginning and at-Risk Writers

ERIC Educational Resources Information Center

Ritchey, Kristen D.

2006-01-01

Teachers now have a wide range of tools to help assess the beginning reading performance of kindergarten and first-grade children. However, validated procedures for assessing the beginning writing skills of kindergarten and first-grade children are less widely available. Learning to write, like learning to read, is a complex task. The ability to…

Perceptions of the Effectiveness of System Dynamics-Based Interactive Learning Environments: An Empirical Study

ERIC Educational Resources Information Center

Qudrat-Ullah, Hassan

2010-01-01

The use of simulations in general and of system dynamics simulation based interactive learning environments (SDILEs) in particular is well recognized as an effective way of improving users' decision making and learning in complex, dynamic tasks. However, the effectiveness of SDILEs in classrooms has rarely been evaluated. This article describes…

Utah Guidance and Toolkit for Student Learning Objectives: Instructions and Materials. Utah SLOs. Updated

ERIC Educational Resources Information Center

Utah State Office of Education, 2014

2014-01-01

This document is intended to help teachers understand and create Student Learning Objectives (SLOs). This resource is a practical guide intended to provide clarity to a complex but worthwhile task. This resource may also be used by administrators for professional learning. As Utah moves toward providing a "Model for Measuring Educator…

The Relevance of the Nature of Learned Associations for the Differentiation of Human Memory Systems

ERIC Educational Resources Information Center

Rose, Michael; Haider, Hilde; Weiller, Cornelius; Buchel, Christian

2004-01-01

In a previous functional magnetic resonance imaging (fMRI) study we demonstrated an involvement of the medial temporal lobe (MTL) during an implicit learning task. We concluded that the MTL was engaged because of the complex contingencies that were implicitly learned. In addition, the basal ganglia demonstrated effects of a paralleled…

Measuring reinforcement learning and motivation constructs in experimental animals: relevance to the negative symptoms of schizophrenia.

PubMed

Markou, Athina; Salamone, John D; Bussey, Timothy J; Mar, Adam C; Brunner, Daniela; Gilmour, Gary; Balsam, Peter

2013-11-01

The present review article summarizes and expands upon the discussions that were initiated during a meeting of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS; http://cntrics.ucdavis.edu) meeting. A major goal of the CNTRICS meeting was to identify experimental procedures and measures that can be used in laboratory animals to assess psychological constructs that are related to the psychopathology of schizophrenia. The issues discussed in this review reflect the deliberations of the Motivation Working Group of the CNTRICS meeting, which included most of the authors of this article as well as additional participants. After receiving task nominations from the general research community, this working group was asked to identify experimental procedures in laboratory animals that can assess aspects of reinforcement learning and motivation that may be relevant for research on the negative symptoms of schizophrenia, as well as other disorders characterized by deficits in reinforcement learning and motivation. The tasks described here that assess reinforcement learning are the Autoshaping Task, Probabilistic Reward Learning Tasks, and the Response Bias Probabilistic Reward Task. The tasks described here that assess motivation are Outcome Devaluation and Contingency Degradation Tasks and Effort-Based Tasks. In addition to describing such methods and procedures, the present article provides a working vocabulary for research and theory in this field, as well as an industry perspective about how such tasks may be used in drug discovery. It is hoped that this review can aid investigators who are conducting research in this complex area, promote translational studies by highlighting shared research goals and fostering a common vocabulary across basic and clinical fields, and facilitate the development of medications for the treatment of symptoms mediated by reinforcement learning and motivational deficits. Copyright © 2013 Elsevier Ltd. All rights reserved.

Measuring reinforcement learning and motivation constructs in experimental animals: relevance to the negative symptoms of schizophrenia

PubMed Central

Markou, Athina; Salamone, John D.; Bussey, Timothy; Mar, Adam; Brunner, Daniela; Gilmour, Gary; Balsam, Peter

2013-01-01

The present review article summarizes and expands upon the discussions that were initiated during a meeting of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS; http://cntrics.ucdavis.edu). A major goal of the CNTRICS meeting was to identify experimental procedures and measures that can be used in laboratory animals to assess psychological constructs that are related to the psychopathology of schizophrenia. The issues discussed in this review reflect the deliberations of the Motivation Working Group of the CNTRICS meeting, which included most of the authors of this article as well as additional participants. After receiving task nominations from the general research community, this working group was asked to identify experimental procedures in laboratory animals that can assess aspects of reinforcement learning and motivation that may be relevant for research on the negative symptoms of schizophrenia, as well as other disorders characterized by deficits in reinforcement learning and motivation. The tasks described here that assess reinforcement learning are the Autoshaping Task, Probabilistic Reward Learning Tasks, and the Response Bias Probabilistic Reward Task. The tasks described here that assess motivation are Outcome Devaluation and Contingency Degradation Tasks and Effort-Based Tasks. In addition to describing such methods and procedures, the present article provides a working vocabulary for research and theory in this field, as well as an industry perspective about how such tasks may be used in drug discovery. It is hoped that this review can aid investigators who are conducting research in this complex area, promote translational studies by highlighting shared research goals and fostering a common vocabulary across basic and clinical fields, and facilitate the development of medications for the treatment of symptoms mediated by reinforcement learning and motivational deficits. PMID:23994273

Task Based Language Teaching: Development of CALL

ERIC Educational Resources Information Center

Anwar, Khoirul; Arifani, Yudhi

2016-01-01

The dominant complexities of English teaching in Indonesia are about limited development of teaching methods and materials which still cannot optimally reflect students' needs (in particular of how to acquire knowledge and select the most effective learning models). This research is to develop materials with complete task-based activities by using…

Is Math Anxiety Always Bad for Math Learning? The Role of Math Motivation.

PubMed

Wang, Zhe; Lukowski, Sarah L; Hart, Sara A; Lyons, Ian M; Thompson, Lee A; Kovas, Yulia; Mazzocco, Michèle M M; Plomin, Robert; Petrill, Stephen A

2015-12-01

The linear relations between math anxiety and math cognition have been frequently studied. However, the relations between anxiety and performance on complex cognitive tasks have been repeatedly demonstrated to follow a curvilinear fashion. In the current studies, we aimed to address the lack of attention given to the possibility of such complex interplay between emotion and cognition in the math-learning literature by exploring the relations among math anxiety, math motivation, and math cognition. In two samples-young adolescent twins and adult college students-results showed inverted-U relations between math anxiety and math performance in participants with high intrinsic math motivation and modest negative associations between math anxiety and math performance in participants with low intrinsic math motivation. However, this pattern was not observed in tasks assessing participants' nonsymbolic and symbolic number-estimation ability. These findings may help advance the understanding of mathematics-learning processes and provide important insights for treatment programs that target improving mathematics-learning experiences and mathematical skills. © The Author(s) 2015.

Learning to segment mouse embryo cells

NASA Astrophysics Data System (ADS)

León, Juan; Pardo, Alejandro; Arbeláez, Pablo

2017-11-01

Recent advances in microscopy enable the capture of temporal sequences during cell development stages. However, the study of such sequences is a complex task and time consuming task. In this paper we propose an automatic strategy to adders the problem of semantic and instance segmentation of mouse embryos using NYU's Mouse Embryo Tracking Database. We obtain our instance proposals as refined predictions from the generalized hough transform, using prior knowledge of the embryo's locations and their current cell stage. We use two main approaches to learn the priors: Hand crafted features and automatic learned features. Our strategy increases the baseline jaccard index from 0.12 up to 0.24 using hand crafted features and 0.28 by using automatic learned ones.

Machine Learning in Medicine

PubMed Central

Deo, Rahul C.

2015-01-01

Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular variant of poker, learned the laws of physics from experimental data, and become experts in video games – tasks which would have been deemed impossible not too long ago. In parallel, the number of companies centered on applying complex data analysis to varying industries has exploded, and it is thus unsurprising that some analytic companies are turning attention to problems in healthcare. The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from the literature to introduce basic concepts in machine learning. It is important to note that seemingly large enough medical data sets and adequate learning algorithms have been available for many decades – and yet, although there are thousands of papers applying machine learning algorithms to medical data, very few have contributed meaningfully to clinical care. This lack of impact stands in stark contrast to the enormous relevance of machine learning to many other industries. Thus part of my effort will be to identify what obstacles there may be to changing the practice of medicine through statistical learning approaches, and discuss how these might be overcome. PMID:26572668

Lateral occipitotemporal cortex (LOTC) activity is greatest while viewing dance compared to visualization and movement: learning and expertise effects.

PubMed

Di Nota, Paula M; Levkov, Gabriella; Bar, Rachel; DeSouza, Joseph F X

2016-07-01

The lateral occipitotemporal cortex (LOTC) is comprised of subregions selectively activated by images of human bodies (extrastriate body area, EBA), objects (lateral occipital complex, LO), and motion (MT+). However, their role in motor imagery and movement processing is unclear, as are the influences of learning and expertise on its recruitment. The purpose of our study was to examine putative changes in LOTC activation during action processing following motor learning of novel choreography in professional ballet dancers. Subjects were scanned with functional magnetic resonance imaging up to four times over 34 weeks and performed four tasks: viewing and visualizing a newly learned ballet dance, visualizing a dance that was not being learned, and movement of the foot. EBA, LO, and MT+ were activated most while viewing dance compared to visualization and movement. Significant increases in activation were observed over time in left LO only during visualization of the unlearned dance, and all subregions were activated bilaterally during the viewing task after 34 weeks of performance, suggesting learning-induced plasticity. Finally, we provide novel evidence for modulation of EBA with dance experience during the motor task, with significant activation elicited in a comparison group of novice dancers only. These results provide a composite of LOTC activation during action processing of newly learned ballet choreography and movement of the foot. The role of these areas is confirmed as primarily subserving observation of complex sequences of whole-body movement, with new evidence for modification by experience and over the course of real world ballet learning.

Task-phase-specific dynamics of basal forebrain neuronal ensembles

PubMed Central

Tingley, David; Alexander, Andrew S.; Kolbu, Sean; de Sa, Virginia R.; Chiba, Andrea A.; Nitz, Douglas A.

2014-01-01

Cortically projecting basal forebrain neurons play a critical role in learning and attention, and their degeneration accompanies age-related impairments in cognition. Despite the impressive anatomical and cell-type complexity of this system, currently available data suggest that basal forebrain neurons lack complexity in their response fields, with activity primarily reflecting only macro-level brain states such as sleep and wake, onset of relevant stimuli and/or reward obtainment. The current study examined the spiking activity of basal forebrain neuron populations across multiple phases of a selective attention task, addressing, in particular, the issue of complexity in ensemble firing patterns across time. Clustering techniques applied to the full population revealed a large number of distinct categories of task-phase-specific activity patterns. Unique population firing-rate vectors defined each task phase and most categories of task-phase-specific firing had counterparts with opposing firing patterns. An analogous set of task-phase-specific firing patterns was also observed in a population of posterior parietal cortex neurons. Thus, consistent with the known anatomical complexity, basal forebrain population dynamics are capable of differentially modulating their cortical targets according to the unique sets of environmental stimuli, motor requirements, and cognitive processes associated with different task phases. PMID:25309352

Learning to Link Visual Contours

PubMed Central

Li, Wu; Piëch, Valentin; Gilbert, Charles D.

2008-01-01

SUMMARY In complex visual scenes, linking related contour elements is important for object recognition. This process, thought to be stimulus driven and hard wired, has substrates in primary visual cortex (V1). Here, however, we find contour integration in V1 to depend strongly on perceptual learning and top-down influences that are specific to contour detection. In naive monkeys the information about contours embedded in complex backgrounds is absent in V1 neuronal responses, and is independent of the locus of spatial attention. Training animals to find embedded contours induces strong contour-related responses specific to the trained retinotopic region. These responses are most robust when animals perform the contour detection task, but disappear under anesthesia. Our findings suggest that top-down influences dynamically adapt neural circuits according to specific perceptual tasks. This may serve as a general neuronal mechanism of perceptual learning, and reflect top-down mediated changes in cortical states. PMID:18255036

Serendipitous Offline Learning in a Neuromorphic Robot.

PubMed

Stewart, Terrence C; Kleinhans, Ashley; Mundy, Andrew; Conradt, Jörg

2016-01-01

We demonstrate a hybrid neuromorphic learning paradigm that learns complex sensorimotor mappings based on a small set of hard-coded reflex behaviors. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviors. All sensor data is provided via a spike-based silicon retina camera (eDVS), and all control is implemented via spiking neurons simulated on neuromorphic hardware (SpiNNaker). Given this control system, the robot is capable of simple obstacle avoidance and random exploration. To train the robot to perform more complex tasks, we observe the robot and find instances where the robot accidentally performs the desired action. Data recorded from the robot during these times is then used to update the neural control system, increasing the likelihood of the robot performing that task in the future, given a similar sensor state. As an example application of this general-purpose method of training, we demonstrate the robot learning to respond to novel sensory stimuli (a mirror) by turning right if it is present at an intersection, and otherwise turning left. In general, this system can learn arbitrary relations between sensory input and motor behavior.

The importance of witnessed agency in chimpanzee social learning of tool use☆

PubMed Central

Hopper, Lydia M.; Lambeth, Susan P.; Schapiro, Steven J.; Whiten, Andrew

2015-01-01

Social learning refers to individuals learning from others, including information gained through indirect social influences, such as the results of others’ actions and changes in the physical environment. One method to determine the relative influence of these varieties of information is the ‘ghost display’, in which no model is involved, but subjects can watch the results that a model would produce. Previous research has shown mixed success by chimpanzees (Pan troglodytes) learning from ghost displays, with some studies suggesting learning only in relatively simple tasks. To explore whether the failure of chimpanzees to learn from a ghost display may be due to neophobia when tested singly or a requirement for more detailed information for complex tasks, we presented ghost displays of a tool-use task to chimpanzees in their home social groups. Previous tests have revealed that chimpanzees are unable to easily solve this tool-use task asocially, or learn from ghost displays when tested singly, but can learn after observing conspecifics in a group setting. In the present study, despite being tested in a group situation, chimpanzees still showed no success in solving the task via trial-and-error learning, in a baseline condition, nor in learning the task from the ghost display. Simply being in the presence of their group mates and being shown the affordances of the task was not sufficient to encourage learning. Following this, in an escalating series of tests, we examined the chimpanzees’ ability to learn from a demonstration by models with agency: (1) a human; (2) video footage of a chimpanzee; (3) a live chimpanzee model. In the first two of these ‘social’ conditions, subjects showed limited success. By the end of the final open diffusion phase, which was run to determine whether this new behavior would be transmitted among the group after seeing a successful chimpanzee use the task, 83% of chimpanzees were now successful. This confirmed a marked overall effect of observing animate conspecific modeling, in contrast to the ghost condition. This article is part of a Special Issue entitled: insert SI title. PMID:25444770

The importance of witnessed agency in chimpanzee social learning of tool use.

PubMed

Hopper, Lydia M; Lambeth, Susan P; Schapiro, Steven J; Whiten, Andrew

2015-03-01

Social learning refers to individuals learning from others, including information gained through indirect social influences, such as the results of others' actions and changes in the physical environment. One method to determine the relative influence of these varieties of information is the 'ghost display', in which no model is involved, but subjects can watch the results that a model would produce. Previous research has shown mixed success by chimpanzees (Pan troglodytes) learning from ghost displays, with some studies suggesting learning only in relatively simple tasks. To explore whether the failure of chimpanzees to learn from a ghost display may be due to neophobia when tested singly or a requirement for more detailed information for complex tasks, we presented ghost displays of a tool-use task to chimpanzees in their home social groups. Previous tests have revealed that chimpanzees are unable to easily solve this tool-use task asocially, or learn from ghost displays when tested singly, but can learn after observing conspecifics in a group setting. In the present study, despite being tested in a group situation, chimpanzees still showed no success in solving the task via trial-and-error learning, in a baseline condition, nor in learning the task from the ghost display. Simply being in the presence of their group mates and being shown the affordances of the task was not sufficient to encourage learning. Following this, in an escalating series of tests, we examined the chimpanzees' ability to learn from a demonstration by models with agency: (1) a human; (2) video footage of a chimpanzee; (3) a live chimpanzee model. In the first two of these 'social' conditions, subjects showed limited success. By the end of the final open diffusion phase, which was run to determine whether this new behavior would be transmitted among the group after seeing a successful chimpanzee use the task, 83% of chimpanzees were now successful. This confirmed a marked overall effect of observing animate conspecific modeling, in contrast to the ghost condition. This article is part of a Special Issue entitled: insert SI title. Copyright © 2014 Elsevier B.V. All rights reserved.

The Role of Pictures in Learning Biology: Part 2, Picture-Text Processing.

ERIC Educational Resources Information Center

Reid, David

1990-01-01

The complex interactions between picture, text, and learner are examined, based on a 3-D model which describes the context of the learning task. The different strategies that children of various ability levels use in reading from illustrated texts are described. (KR)

Opposing effects of dopamine antagonism in a motor sequence task—tiapride increases cortical excitability and impairs motor learning

PubMed Central

Lissek, Silke; Vallana, Guido S.; Schlaffke, Lara; Lenz, Melanie; Dinse, Hubert R.; Tegenthoff, Martin

2014-01-01

The dopaminergic system is involved in learning and participates in the modulation of cortical excitability (CE). CE has been suggested as a marker of learning and use-dependent plasticity. However, results from separate studies on either motor CE or motor learning challenge this notion, suggesting opposing effects of dopaminergic modulation upon these parameters: while agonists decrease and antagonists increase CE, motor learning is enhanced by agonists and disturbed by antagonists. To examine whether this discrepancy persists when complex motor learning and motor CE are measured in the same experimental setup, we investigated the effects of dopaminergic (DA) antagonism upon both parameters and upon task-associated brain activation. Our results demonstrate that DA-antagonism has opposing effects upon motor CE and motor sequence learning. Tiapride did not alter baseline CE, but increased CE post training of a complex motor sequence while simultaneously impairing motor learning. Moreover, tiapride reduced activation in several brain regions associated with motor sequence performance, i.e., dorsolateral PFC (dlPFC), supplementary motor area (SMA), Broca's area, cingulate and caudate body. Blood-oxygenation-level-dependent (BOLD) intensity in anterior cingulate and caudate body, but not CE, correlated with performance across groups. In summary, our results do not support a concept of CE as a general marker of motor learning, since they demonstrate that a straightforward relation of increased CE and higher learning success does not apply to all instances of motor learning. At least for complex motor tasks that recruit a network of brain regions outside motor cortex, CE in primary motor cortex is probably no central determinant for learning success. PMID:24994972

Distinct responses of Purkinje neurons and roles of simple spikes during associative motor learning in larval zebrafish

PubMed Central

Harmon, Thomas C; Magaram, Uri; McLean, David L; Raman, Indira M

2017-01-01

To study cerebellar activity during learning, we made whole-cell recordings from larval zebrafish Purkinje cells while monitoring fictive swimming during associative conditioning. Fish learned to swim in response to visual stimulation preceding tactile stimulation of the tail. Learning was abolished by cerebellar ablation. All Purkinje cells showed task-related activity. Based on how many complex spikes emerged during learned swimming, they were classified as multiple, single, or zero complex spike (MCS, SCS, ZCS) cells. With learning, MCS and ZCS cells developed increased climbing fiber (MCS) or parallel fiber (ZCS) input during visual stimulation; SCS cells fired complex spikes associated with learned swimming episodes. The categories correlated with location. Optogenetically suppressing simple spikes only during visual stimulation demonstrated that simple spikes are required for acquisition and early stages of expression of learned responses, but not their maintenance, consistent with a transient, instructive role for simple spikes during cerebellar learning in larval zebrafish. DOI: http://dx.doi.org/10.7554/eLife.22537.001 PMID:28541889

Disruption of self-organized actions in monkeys with progressive MPTP-induced parkinsonism. I. Effects of task complexity.

PubMed

Pessiglione, Mathias; Guehl, Dominique; Hirsch, Etienne C; Féger, Jean; Tremblay, Léon

2004-01-01

Parkinson's disease (PD) is characterized by motor symptoms, usually accompanied by cognitive deficits. The question addressed in this study is whether complexity of routine actions can exacerbate parkinsonian disorders that are often considered to be motor symptoms. To examine this question, we trained four vervet monkeys (Cercopithecus aethiops) to perform three multiple-choice retrieval tasks. In order of ascending complexity, rewards were freely available (task 1), covered with transparent sliding plaques (task 2), and covered with opaque sliding plaques cued by symbols (task 3). Thus, from task 1 to task 2 we added a motor difficulty--the recall of context-adapted movement; and from task 2 to task 3 we added a cognitive difficulty: the recall of symbol-reward associations. The more complex the task, the longer it took to learn, but after extensive training the performance was stable in all tasks, with similar retrieval durations. The monkeys then received systemic 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) injections (0.3-0.4 mg/kg) every 4-7 days, until the first motor symptoms appeared. In the course of MPTP intoxication, the behavioural performance declined while the motor symptoms were absent or mild--the retrieval duration increased, and non-initiated choices and hesitations between choices became frequent. Interestingly, this decline was in proportion to task complexity, and was particularly pronounced with the cognitive difficulty. Furthermore, freezing appeared only with the cognitive difficulty. We therefore suggest that everyday cognitive difficulties may exacerbate hypokinesia (lack of initiation, abnormal slowness) and executive disorders (hesitations, freezing) in the early stages of human PD.

The Perception of Workload and Task Complexity and Its Influence on Students' Approaches to Learning: A Study in Higher Education

ERIC Educational Resources Information Center

Kyndt, Eva; Dochy, Filip; Struyven, Katrien; Cascallar, Eduardo

2011-01-01

Researchers have tried to induce a deeper approach to learning by means of student-centred learning environments. Findings did not always confirm the positive hypotheses. This has given rise to the question as to what the discouraging or encouraging factors are for inducing a deep approach to learning. The aim of this research study is to…

Task demand influences relationships among sex, clustering strategy, and recall: 16-word versus 9-word list learning tests.

PubMed

Sunderaraman, Preeti; Blumen, Helena M; DeMatteo, David; Apa, Zoltan L; Cosentino, Stephanie

2013-06-01

We compared the relationships among sex, clustering strategy, and recall across different task demands using the 16-word California Verbal Learning Test-Second Edition (CVLT-II) and the 9-word Philadelphia (repeatable) Verbal Learning Test (PrVLT). Women generally score higher than men on verbal memory tasks, possibly because women tend to use semantic clustering. This sex difference has been established via word-list learning tests such as the CVLT-II. In a retrospective between-group study, we compared how 2 separate groups of cognitively healthy older adults performed on a longer and a shorter verbal learning test. The group completing the CVLT-II had 36 women and 26 men; the group completing the PrVLT had 27 women and 21 men. Overall, multiple regression analyses revealed that semantic clustering was significantly associated with total recall on both tests' lists (P<0.001). Sex differences in recall and semantic clustering diminished with the shorter PrVLT word list. Semantic clustering uniquely influenced recall on both the longer and shorter word lists. However, serial clustering and sex influenced recall depending on the length of the word list (ie, the task demand). These findings suggest a complex nonlinear relationship among verbal memory, clustering strategies, and task demand.

Task Demand Influences Relationships Among Sex, Clustering Strategy, and Recall: 16-Word Versus 9-Word List Learning Tests

PubMed Central

Sunderaraman, Preeti; Blumen, Helena M.; DeMatteo, David; Apa, Zoltan; Cosentino, Stephanie

2013-01-01

Objective We compared the relationships among sex, clustering strategy, and recall across different task demands using the 16-word California Verbal Learning Test–Second Edition (CVLT-II) and the 9-word Philadelphia (repeatable) Verbal Learning Test (PrVLT). Background Women generally score higher than men on verbal memory tasks, possibly because women tend to use semantic clustering. This sex difference has been established via word-list learning tests such as the CVLT-II. Methods In a retrospective between-group study, we compared how 2 separate groups of cognitively healthy older adults performed on a longer and a shorter verbal learning test. The group completing the CVLT-II had 36 women and 26 men; the group completing the PrVLT had 27 women and 21 men. Results Overall, multiple regression analyses revealed that semantic clustering was significantly associated with total recall on both tests’ lists (P < 0.001). Sex differences in recall and semantic clustering diminished with the shorter PrVLT word list. Conclusions Semantic clustering uniquely influenced recall on both the longer and shorter word lists. However, serial clustering and sex influenced recall depending on the length of the word list (ie, the task demand). These findings suggest a complex nonlinear relationship among verbal memory, clustering strategies, and task demand. PMID:23812171

TEES 2.2: Biomedical Event Extraction for Diverse Corpora

PubMed Central

2015-01-01

Background The Turku Event Extraction System (TEES) is a text mining program developed for the extraction of events, complex biomedical relationships, from scientific literature. Based on a graph-generation approach, the system detects events with the use of a rich feature set built via dependency parsing. The TEES system has achieved record performance in several of the shared tasks of its domain, and continues to be used in a variety of biomedical text mining tasks. Results The TEES system was quickly adapted to the BioNLP'13 Shared Task in order to provide a public baseline for derived systems. An automated approach was developed for learning the underlying annotation rules of event type, allowing immediate adaptation to the various subtasks, and leading to a first place in four out of eight tasks. The system for the automated learning of annotation rules is further enhanced in this paper to the point of requiring no manual adaptation to any of the BioNLP'13 tasks. Further, the scikit-learn machine learning library is integrated into the system, bringing a wide variety of machine learning methods usable with TEES in addition to the default SVM. A scikit-learn ensemble method is also used to analyze the importances of the features in the TEES feature sets. Conclusions The TEES system was introduced for the BioNLP'09 Shared Task and has since then demonstrated good performance in several other shared tasks. By applying the current TEES 2.2 system to multiple corpora from these past shared tasks an overarching analysis of the most promising methods and possible pitfalls in the evolving field of biomedical event extraction are presented. PMID:26551925

TEES 2.2: Biomedical Event Extraction for Diverse Corpora.

PubMed

Björne, Jari; Salakoski, Tapio

2015-01-01

The Turku Event Extraction System (TEES) is a text mining program developed for the extraction of events, complex biomedical relationships, from scientific literature. Based on a graph-generation approach, the system detects events with the use of a rich feature set built via dependency parsing. The TEES system has achieved record performance in several of the shared tasks of its domain, and continues to be used in a variety of biomedical text mining tasks. The TEES system was quickly adapted to the BioNLP'13 Shared Task in order to provide a public baseline for derived systems. An automated approach was developed for learning the underlying annotation rules of event type, allowing immediate adaptation to the various subtasks, and leading to a first place in four out of eight tasks. The system for the automated learning of annotation rules is further enhanced in this paper to the point of requiring no manual adaptation to any of the BioNLP'13 tasks. Further, the scikit-learn machine learning library is integrated into the system, bringing a wide variety of machine learning methods usable with TEES in addition to the default SVM. A scikit-learn ensemble method is also used to analyze the importances of the features in the TEES feature sets. The TEES system was introduced for the BioNLP'09 Shared Task and has since then demonstrated good performance in several other shared tasks. By applying the current TEES 2.2 system to multiple corpora from these past shared tasks an overarching analysis of the most promising methods and possible pitfalls in the evolving field of biomedical event extraction are presented.

Acquisition of Internal Models of Motor Tasks in Children with Autism

ERIC Educational Resources Information Center

Gidley Larson, Jennifer C.; Bastian, Amy J.; Donchin, Opher; Shadmehr, Reza; Mostofsky, Stewart H.

2008-01-01

Children with autism exhibit a host of motor disorders including poor coordination, poor tool use and delayed learning of complex motor skills like riding a tricycle. Theory suggests that one of the crucial steps in motor learning is the ability to form internal models: to predict the sensory consequences of motor commands and learn from errors to…

Unpacking the Complexity of Patient Handoffs Through the Lens of Cognitive Load Theory.

PubMed

Young, John Q; Ten Cate, Olle; O'Sullivan, Patricia S; Irby, David M

2016-01-01

The transfer of a patient from one clinician to another is a high-risk event. Errors are common and lead to patient harm. More effective methods for learning how to give and receive sign-out is an important public health priority. Performing a handoff is a complex task. Trainees must simultaneously apply and integrate clinical, communication, and systems skills into one time-limited and highly constrained activity. The task demands can easily exceed the information-processing capacity of the trainee, resulting in impaired learning and performance. Appreciating the limits of working memory can help identify the challenges that instructional techniques and research must then address. Cognitive load theory (CLT) identifies three types of load that impact working memory: intrinsic (task-essential), extraneous (not essential to task), and germane (learning related). The authors generated a list of factors that affect a trainee's learning and performance of a handoff based on CLT. The list was revised based on feedback from experts in medical education and in handoffs. By consensus, the authors associated each factor with the type of cognitive load it primarily effects. The authors used this analysis to build a conceptual model of handoffs through the lens of CLT. The resulting conceptual model unpacks the complexity of handoffs and identifies testable hypotheses for educational research and instructional design. The model identifies features of a handoff that drive extraneous, intrinsic, and germane load for both the sender and the receiver. The model highlights the importance of reducing extraneous load, matching intrinsic load to the developmental stage of the learner and optimizing germane load. Specific CLT-informed instructional techniques for handoffs are explored. Intrinsic and germane load are especially important to address and include factors such as knowledge of the learner, number of patients, time constraints, clinical uncertainties, overall patient/panel complexity, interacting comorbidities or therapeutics, experience or specialty gradients between the sender and receiver, the maturity of the evidence base for the patient's disease, and the use of metacognitive techniques. Research that identifies which cognitive load factors most significantly affect the learning and performance of handoffs can lead to novel, contextually adapted instructional techniques and handoff protocols. The application of CLT to handoffs may also help with the further development of CLT as a learning theory.

Make Your Workflows Smarter

NASA Technical Reports Server (NTRS)

Jones, Corey; Kapatos, Dennis; Skradski, Cory

2012-01-01

Do you have workflows with many manual tasks that slow down your business? Or, do you scale back workflows because there are simply too many manual tasks? Basic workflow robots can automate some common tasks, but not everything. This presentation will show how advanced robots called "expression robots" can be set up to perform everything from simple tasks such as: moving, creating folders, renaming, changing or creating an attribute, and revising, to more complex tasks like: creating a pdf, or even launching a session of Creo Parametric and performing a specific modeling task. Expression robots are able to utilize the Java API and Info*Engine to do almost anything you can imagine! Best of all, these tools are supported by PTC and will work with later releases of Windchill. Limited knowledge of Java, Info*Engine, and XML are required. The attendee will learn what task expression robots are capable of performing. The attendee will learn what is involved in setting up an expression robot. The attendee will gain a basic understanding of simple Info*Engine tasks

Cholinesterase Inhibitors Improve Both Memory and Complex Learning in Aged Beagle Dogs

PubMed Central

Araujo, Joseph A.; Greig, Nigel H.; Ingram, Donald K.; Sandin, Johan; de Rivera, Christina; Milgram, Norton W.

2016-01-01

Similar to patients with Alzheimer’s disease (AD), dogs exhibit age-dependent cognitive decline, amyloid-β (Aβ) pathology, and evidence of cholinergic hypofunction. The present study sought to further investigate the role of cholinergic hypofunction in the canine model by examining the effect of the cholinesterase inhibitors phenserine and donepezil on performance of two tasks, a delayed non-matching-to-position task (DNMP) designed to assess working memory, and an oddity discrimination learning task designed to assess complex learning, in aged dogs. Phenserine (0.5 mg/kg; PO) significantly improved performance on the DNMP at the longest delay compared to wash-out and partially attenuated scopolamine-induced deficits (15 μg/kg; SC). Phenserine also improved learning on a difficult version of an oddity discrimination task compared to placebo, but had no effect on an easier version. We also examined the effects of three doses of donepezil (0.75, 1.5, and 6 mg/kg; PO) on performance of the DNMP. Similar to the results with phenserine, 1.5 mg/kg of donepezil improved performance at the longest delay compared to baseline and wash-out, indicative of memory enhancement. These results further extend the findings of cholinergic hypofunction in aged dogs and provide pharmacological validation of the canine model with a cholinesterase inhibitor approved for use in AD. Collectively, these studies support utilizing the aged dog in future screening of therapeutics for AD, as well as for investigating the links among cholinergic function, Aβ pathology, and cognitive decline. PMID:21593569

Asymptotically Optimal Motion Planning for Learned Tasks Using Time-Dependent Cost Maps

PubMed Central

Bowen, Chris; Ye, Gu; Alterovitz, Ron

2015-01-01

In unstructured environments in people’s homes and workspaces, robots executing a task may need to avoid obstacles while satisfying task motion constraints, e.g., keeping a plate of food level to avoid spills or properly orienting a finger to push a button. We introduce a sampling-based method for computing motion plans that are collision-free and minimize a cost metric that encodes task motion constraints. Our time-dependent cost metric, learned from a set of demonstrations, encodes features of a task’s motion that are consistent across the demonstrations and, hence, are likely required to successfully execute the task. Our sampling-based motion planner uses the learned cost metric to compute plans that simultaneously avoid obstacles and satisfy task constraints. The motion planner is asymptotically optimal and minimizes the Mahalanobis distance between the planned trajectory and the distribution of demonstrations in a feature space parameterized by the locations of task-relevant objects. The motion planner also leverages the distribution of the demonstrations to significantly reduce plan computation time. We demonstrate the method’s effectiveness and speed using a small humanoid robot performing tasks requiring both obstacle avoidance and satisfaction of learned task constraints. Note to Practitioners Motivated by the desire to enable robots to autonomously operate in cluttered home and workplace environments, this paper presents an approach for intuitively training a robot in a manner that enables it to repeat the task in novel scenarios and in the presence of unforeseen obstacles in the environment. Based on user-provided demonstrations of the task, our method learns features of the task that are consistent across the demonstrations and that we expect should be repeated by the robot when performing the task. We next present an efficient algorithm for planning robot motions to perform the task based on the learned features while avoiding obstacles. We demonstrate the effectiveness of our motion planner for scenarios requiring transferring a powder and pushing a button in environments with obstacles, and we plan to extend our results to more complex tasks in the future. PMID:26279642

Learning to Manage Intergroup Dynamics in Changing Task Environments: An Experiential Exercise

ERIC Educational Resources Information Center

Hunsaker, Phillip L.

2004-01-01

This article describes an exercise that allows participants to experience the challenges of managing intergroup behavior as an organization's task environment grows and becomes more complex. The article begins with a brief review of models and concepts relating to intergroup dynamics, intergroup conflict, and interventions for effectively managing…

Over-Selectivity as a Learned Response

ERIC Educational Resources Information Center

Reed, Phil; Petrina, Neysa; McHugh, Louise

2011-01-01

An experiment investigated the effects of different levels of task complexity in pre-training on over-selectivity in a subsequent match-to-sample (MTS) task. Twenty human participants were divided into two groups; exposed either to a 3-element, or a 9-element, compound stimulus as a sample during MTS training. After the completion of training,…

The Relative Efficiency of Two Strategies for Conducting Cognitive Task Analysis

ERIC Educational Resources Information Center

Flynn, Catherine L.

2012-01-01

Cognitive task analysis (CTA) has evolved over the past half century to capture the mental decisions and analysis that experts have learned to implement when solving complex problems. Since expertise is largely automated and nonconscious, a variety of observation and interview strategies have been developed to identify the most critical cognitive…

Brain regions engaged by part- and whole-task performance in a video game: a model-based test of the decomposition hypothesis.

PubMed

Anderson, John R; Bothell, Daniel; Fincham, Jon M; Anderson, Abraham R; Poole, Ben; Qin, Yulin

2011-12-01

Part- and whole-task conditions were created by manipulating the presence of certain components of the Space Fortress video game. A cognitive model was created for two-part games that could be combined into a model that performed the whole game. The model generated predictions both for behavioral patterns and activation patterns in various brain regions. The activation predictions concerned both tonic activation that was constant in these regions during performance of the game and phasic activation that occurred when there was resource competition. The model's predictions were confirmed about how tonic and phasic activation in different regions would vary with condition. These results support the Decomposition Hypothesis that the execution of a complex task can be decomposed into a set of information-processing components and that these components combine unchanged in different task conditions. In addition, individual differences in learning gains were predicted by individual differences in phasic activation in those regions that displayed highest tonic activity. This individual difference pattern suggests that the rate of learning of a complex skill is determined by capacity limits.

Unravelling Secondary Students' Challenges in Digital Literacy: A Gender Perspective

ERIC Educational Resources Information Center

Argelagós, Esther; Pifarré, Manoli

2017-01-01

The use of the Internet to learn involves complex cognitive activities. Educational researchers claim more attention in studying the nature of students' challenges when using digital information for learning purposes. Our research investigated in depth the challenges that secondary students face when solving web information-problem tasks. We…

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…

Integrating Knowledge, Skills and Attitudes: Conceptualising Learning Processes towards Vocational Competence

ERIC Educational Resources Information Center

Baartman, Liesbeth K. J.; de Bruijn, Elly

2011-01-01

Current research focuses on competence development and complex professional tasks. However, "learning processes" towards the integration of knowledge, skills and attitudes largely remain a black box. This article conceptualises three integration processes, in analogy to theories on transfer. Knowledge, skills and attitudes are defined, reconciling…

Cognitive learning: a machine learning approach for automatic process characterization from design

NASA Astrophysics Data System (ADS)

Foucher, J.; Baderot, J.; Martinez, S.; Dervilllé, A.; Bernard, G.

2018-03-01

Cutting edge innovation requires accurate and fast process-control to obtain fast learning rate and industry adoption. Current tools available for such task are mainly manual and user dependent. We present in this paper cognitive learning, which is a new machine learning based technique to facilitate and to speed up complex characterization by using the design as input, providing fast training and detection time. We will focus on the machine learning framework that allows object detection, defect traceability and automatic measurement tools.

Rats' learning of a new motor skill: insight into the evolution of motor sequence learning.

PubMed

Hermer-Vazquez, Linda; Moshtagh, Nasim

2009-05-01

Recent behavioral and neural evidence has suggested that ethologically relevant sub-movements (movement primitives) are used by primates for more complex motor skill learning. These primitives include extending the hand, grasping an object, and holding food while moving it toward the mouth. In prior experiments with rats performing a reach-to-grasp-food task, we observed that especially during early task learning, rats appeared to have movement primitives similar to those seen in primates. Unlike primates, however, during task learning the rats performed these sub-movements in a disordered manner not seen in humans or macaques, e.g. with the rat chewing before placing the food pellet in its mouth. Here, in two experiments, we tested the hypothesis that for rats, learning this ecologically relevant skill involved learning to concatenate the sub-movements in the correct order. The results confirmed our initial observations, and suggested that several aspects of forepaw/hand use, taken for granted in primate studies, must be learned by rats to perform a logically connected and seemingly ecologically important series of sub-movements. We discuss our results from a comparative and evolutionary perspective.

Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task

PubMed Central

2017-01-01

Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of spiking neurons with multiple plastic layers. The network utilized both reward modulated and non-reward modulated STDP and implemented multiple mechanisms for homeostatic regulation of synaptic efficacy, including heterosynaptic plasticity, gain control, output balancing, activity normalization of rewarded STDP and hard limits on synaptic strength. We found that addition of a hidden layer of neurons employing non-rewarded STDP created neurons that responded to the specific combinations of inputs and thus performed basic classification of the input patterns. When combined with a following layer of neurons implementing rewarded STDP, the network was able to learn, despite the absence of labeled training data, discrimination between rewarding patterns and the patterns designated as punishing. Synaptic noise allowed for trial-and-error learning that helped to identify the goal-oriented strategies which were effective in task solving. The study predicts a critical set of properties of the spiking neuronal network with STDP that was sufficient to solve a complex foraging task involving pattern classification and decision making. PMID:28961245

Transfer of skill engendered by complex task training under conditions of variable priority.

PubMed

Boot, Walter R; Basak, Chandramallika; Erickson, Kirk I; Neider, Mark; Simons, Daniel J; Fabiani, Monica; Gratton, Gabriele; Voss, Michelle W; Prakash, Ruchika; Lee, HyunKyu; Low, Kathy A; Kramer, Arthur F

2010-11-01

We explored the theoretical underpinnings of a commonly used training strategy by examining issues of training and transfer of skill in the context of a complex video game (Space Fortress, Donchin, 1989). Participants trained using one of two training regimens: Full Emphasis Training (FET) or Variable Priority Training (VPT). Transfer of training was assessed with a large battery of cognitive and psychomotor tasks ranging from basic laboratory paradigms measuring reasoning, memory, and attention to complex real-world simulations. Consistent with previous studies, VPT accelerated learning and maximized task mastery. However, the hypothesis that VPT would result in broader transfer of training received limited support. Rather, transfer was most evident in tasks that were most similar to the Space Fortress game itself. Results are discussed in terms of potential limitations of the VPT approach. Copyright © 2010 Elsevier B.V. All rights reserved.

Robotic technology results in faster and more robust surgical skill acquisition than traditional laparoscopy.

PubMed

Moore, Lee J; Wilson, Mark R; Waine, Elizabeth; Masters, Rich S W; McGrath, John S; Vine, Samuel J

2015-03-01

Technical surgical skills are said to be acquired quicker on a robotic rather than laparoscopic platform. However, research examining this proposition is scarce. Thus, this study aimed to compare the performance and learning curves of novices acquiring skills using a robotic or laparoscopic system, and to examine if any learning advantages were maintained over time and transferred to more difficult and stressful tasks. Forty novice participants were randomly assigned to either a robotic- or laparoscopic-trained group. Following one baseline trial on a ball pick-and-drop task, participants performed 50 learning trials. Participants then completed an immediate retention trial and a transfer trial on a two-instrument rope-threading task. One month later, participants performed a delayed retention trial and a stressful multi-tasking trial. The results revealed that the robotic-trained group completed the ball pick-and-drop task more quickly and accurately than the laparoscopic-trained group across baseline, immediate retention, and delayed retention trials. Furthermore, the robotic-trained group displayed a shorter learning curve for accuracy. The robotic-trained group also performed the more complex rope-threading and stressful multi-tasking transfer trials better. Finally, in the multi-tasking trial, the robotic-trained group made fewer tone counting errors. The results highlight the benefits of using robotic technology for the acquisition of technical surgical skills.

Decision paths in complex tasks

NASA Technical Reports Server (NTRS)

Galanter, Eugene

1991-01-01

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

Deep learning for tumor classification in imaging mass spectrometry.

PubMed

Behrmann, Jens; Etmann, Christian; Boskamp, Tobias; Casadonte, Rita; Kriegsmann, Jörg; Maaß, Peter

2018-04-01

Tumor classification using imaging mass spectrometry (IMS) data has a high potential for future applications in pathology. Due to the complexity and size of the data, automated feature extraction and classification steps are required to fully process the data. Since mass spectra exhibit certain structural similarities to image data, deep learning may offer a promising strategy for classification of IMS data as it has been successfully applied to image classification. Methodologically, we propose an adapted architecture based on deep convolutional networks to handle the characteristics of mass spectrometry data, as well as a strategy to interpret the learned model in the spectral domain based on a sensitivity analysis. The proposed methods are evaluated on two algorithmically challenging tumor classification tasks and compared to a baseline approach. Competitiveness of the proposed methods is shown on both tasks by studying the performance via cross-validation. Moreover, the learned models are analyzed by the proposed sensitivity analysis revealing biologically plausible effects as well as confounding factors of the considered tasks. Thus, this study may serve as a starting point for further development of deep learning approaches in IMS classification tasks. https://gitlab.informatik.uni-bremen.de/digipath/Deep_Learning_for_Tumor_Classification_in_IMS. jbehrmann@uni-bremen.de or christianetmann@uni-bremen.de. Supplementary data are available at Bioinformatics online.

The Relationship between Training Design and Trainee Differences on Training Outcomes: An Experimental Investigation of the Treatment of Socialization and Training Content in the E-Learning Environment

ERIC Educational Resources Information Center

Yanson, Regina

2012-01-01

For e-learning initiatives to succeed, they must be designed to support a variety of trainees, methods, and content. Two important considerations in the design of any learning environment are the complexity of the tasks being learned and the socialization and connections of the trainees. Therefore, the goal of this research was to investigate how…

The effect of learning on feedback-related potentials in adolescents with dyslexia: an EEG-ERP study.

PubMed

Kraus, Dror; Horowitz-Kraus, Tzipi

2014-01-01

Individuals with dyslexia exhibit associated learning deficits and impaired executive functions. The Wisconsin Card Sorting Test (WCST) is a learning-based task that relies heavily on executive functioning, in particular, attention shift and working memory. Performance during early and late phases of a series within the task represents learning and implementation of a newly learned rule. Here, we aimed to examine two event-related potentials associated with learning, feedback-related negativity (FRN)-P300 complex, in individuals with dyslexia performing the WCST. Adolescents with dyslexia and age-matched typical readers performed the Madrid card sorting test (MCST), a computerized version of the WCST. Task performance, reading measures, and cognitive measures were collected. FRN and the P300 complex were acquired using the event-related potentials methodology and were compared in early vs late errors within a series. While performing the MCST, both groups showed a significant reduction in average reaction times and a trend toward decreased error rates. Typical readers performed consistently better than individuals with dyslexia. FRN amplitudes in early phases were significantly smaller in dyslexic readers, but were essentially equivalent to typical readers in the late phase. P300 amplitudes were initially smaller among readers with dyslexia and tended to decrease further in late phases. Differences in FRN amplitudes for early vs late phases were positively correlated with those of P300 amplitudes in the entire sample. Individuals with dyslexia demonstrate a behavioral and electrophysiological change within single series of the MCST. However, learning patterns seem to differ between individuals with dyslexia and typical readers. We attribute these differences to the lower baseline performance of individuals with dyslexia. We suggest that these changes represent a fast compensatory mechanism, demonstrating the importance of learning strategies on reading among individuals with dyslexia.

The influence of professional expertise and task complexity upon the potency of the contextual interference effect.

PubMed

Ollis, Stewart; Button, Chris; Fairweather, Malcolm

2005-03-01

The contextual interference (CI) effect has been investigated through practice schedule manipulations within both basic and applied studies. Despite extensive research activity there is little conclusive evidence regarding the optimal practice structure of real world manipulative tasks in professional training settings. The present study therefore assessed the efficacy of practising simple and complex knot-tying skills in professional fire-fighters training. Forty-eight participants were quasi-randomly assigned to various practice schedules along the CI continuum. Twenty-four participants were students selected for their novice knot-tying capabilities and 24 were experienced fire-fighters who were more 'experienced knot-tiers'. They were assessed for skill acquisition, retention and transfer effects having practiced tying knots classified as simple or complex. Surprisingly, high levels of CI scheduling enhance learning for novices even when practising a complex task. The findings also revealed that CI benefits are most apparent as learners engage in tasks high in transfer distality. In conclusion, complexity and experience are mediating factors influencing the potency of the CI training effect in real-world settings.

RACE/A: an architectural account of the interactions between learning, task control, and retrieval dynamics.

PubMed

van Maanen, Leendert; van Rijn, Hedderik; Taatgen, Niels

2012-01-01

This article discusses how sequential sampling models can be integrated in a cognitive architecture. The new theory Retrieval by Accumulating Evidence in an Architecture (RACE/A) combines the level of detail typically provided by sequential sampling models with the level of task complexity typically provided by cognitive architectures. We will use RACE/A to model data from two variants of a picture-word interference task in a psychological refractory period design. These models will demonstrate how RACE/A enables interactions between sequential sampling and long-term declarative learning, and between sequential sampling and task control. In a traditional sequential sampling model, the onset of the process within the task is unclear, as is the number of sampling processes. RACE/A provides a theoretical basis for estimating the onset of sequential sampling processes during task execution and allows for easy modeling of multiple sequential sampling processes within a task. Copyright © 2011 Cognitive Science Society, Inc.

Notes From the Field: Secondary Task Precision for Cognitive Load Estimation During Virtual Reality Surgical Simulation Training.

PubMed

Rasmussen, Sebastian R; Konge, Lars; Mikkelsen, Peter T; Sørensen, Mads S; Andersen, Steven A W

2016-03-01

Cognitive load (CL) theory suggests that working memory can be overloaded in complex learning tasks such as surgical technical skills training, which can impair learning. Valid and feasible methods for estimating the CL in specific learning contexts are necessary before the efficacy of CL-lowering instructional interventions can be established. This study aims to explore secondary task precision for the estimation of CL in virtual reality (VR) surgical simulation and also investigate the effects of CL-modifying factors such as simulator-integrated tutoring and repeated practice. Twenty-four participants were randomized for visual assistance by a simulator-integrated tutor function during the first 5 of 12 repeated mastoidectomy procedures on a VR temporal bone simulator. Secondary task precision was found to be significantly lower during simulation compared with nonsimulation baseline, p < .001. Contrary to expectations, simulator-integrated tutoring and repeated practice did not have an impact on secondary task precision. This finding suggests that even though considerable changes in CL are reflected in secondary task precision, it lacks sensitivity. In contrast, secondary task reaction time could be more sensitive, but requires substantial postprocessing of data. Therefore, future studies on the effect of CL modifying interventions should weigh the pros and cons of the various secondary task measurements. © The Author(s) 2015.

Machine Learning in Medicine.

PubMed

Deo, Rahul C

2015-11-17

Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular variant of poker, learned the laws of physics from experimental data, and become experts in video games - tasks that would have been deemed impossible not too long ago. In parallel, the number of companies centered on applying complex data analysis to varying industries has exploded, and it is thus unsurprising that some analytic companies are turning attention to problems in health care. The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from the literature to introduce basic concepts in machine learning. It is important to note that seemingly large enough medical data sets and adequate learning algorithms have been available for many decades, and yet, although there are thousands of papers applying machine learning algorithms to medical data, very few have contributed meaningfully to clinical care. This lack of impact stands in stark contrast to the enormous relevance of machine learning to many other industries. Thus, part of my effort will be to identify what obstacles there may be to changing the practice of medicine through statistical learning approaches, and discuss how these might be overcome. © 2015 American Heart Association, Inc.

Using the Context, Input, Process, and Product Evaluation Model (CIPP) as a Comprehensive Framework to Guide the Planning, Implementation, and Assessment of Service-Learning Programs

ERIC Educational Resources Information Center

Zhang, Guili; Zeller, Nancy; Griffith, Robin; Metcalf, Debbie; Williams, Jennifer; Shea, Christine; Misulis, Katherine

2011-01-01

Planning, implementing, and assessing a service-learning project can be a complex task because service-learning projects often involve multiple constituencies and aim to meet both the needs of service providers and community partners. In this article, Stufflebeam's Context, Input, Process, and Product (CIPP) evaluation model is recommended as a…

Lessons Learned from Crowdsourcing Complex Engineering Tasks.

PubMed

Staffelbach, Matthew; Sempolinski, Peter; Kijewski-Correa, Tracy; Thain, Douglas; Wei, Daniel; Kareem, Ahsan; Madey, Gregory

2015-01-01

Crowdsourcing is the practice of obtaining needed ideas, services, or content by requesting contributions from a large group of people. Amazon Mechanical Turk is a web marketplace for crowdsourcing microtasks, such as answering surveys and image tagging. We explored the limits of crowdsourcing by using Mechanical Turk for a more complicated task: analysis and creation of wind simulations. Our investigation examined the feasibility of using crowdsourcing for complex, highly technical tasks. This was done to determine if the benefits of crowdsourcing could be harnessed to accurately and effectively contribute to solving complex real world engineering problems. Of course, untrained crowds cannot be used as a mere substitute for trained expertise. Rather, we sought to understand how crowd workers can be used as a large pool of labor for a preliminary analysis of complex data. We compared the skill of the anonymous crowd workers from Amazon Mechanical Turk with that of civil engineering graduate students, making a first pass at analyzing wind simulation data. For the first phase, we posted analysis questions to Amazon crowd workers and to two groups of civil engineering graduate students. A second phase of our experiment instructed crowd workers and students to create simulations on our Virtual Wind Tunnel website to solve a more complex task. With a sufficiently comprehensive tutorial and compensation similar to typical crowd-sourcing wages, we were able to enlist crowd workers to effectively complete longer, more complex tasks with competence comparable to that of graduate students with more comprehensive, expert-level knowledge. Furthermore, more complex tasks require increased communication with the workers. As tasks become more complex, the employment relationship begins to become more akin to outsourcing than crowdsourcing. Through this investigation, we were able to stretch and explore the limits of crowdsourcing as a tool for solving complex problems.

Controlling Uncertainty: A Review of Human Behavior in Complex Dynamic Environments

ERIC Educational Resources Information Center

Osman, Magda

2010-01-01

Complex dynamic control (CDC) tasks are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research…

The relationship between intelligence and training gains is moderated by training strategy.

PubMed

Lee, Hyunkyu; Boot, Walter R; Baniqued, Pauline L; Voss, Michelle W; Prakash, Ruchika Shaurya; Basak, Chandramallika; Kramer, Arthur F

2015-01-01

We examined the relationship between training regimen and fluid intelligence in the learning of a complex video game. Fifty non-game-playing young adults were trained on a game called Space Fortress for 30 hours with one of two training regimens: (1) Hybrid Variable-Priority Training (HVT), with part-task training and a focus on improving specific skills and managing task priorities, and (2) Full Emphasis Training (FET) in which participants practiced the whole game to obtain the highest overall score. Fluid intelligence was measured with the Raven's Progressive Matrix task before training. With FET, fluid intelligence was positively associated with learning, suggesting that intellectual ability played a substantial role in determining individual differences in training success. In contrast, with HVT, fluid intelligence was not associated with learning, suggesting that individual differences in fluid intelligence do not factor into training success in a regimen that emphasizes component tasks and flexible task coordination. By analyzing training effects in terms of individual differences and training regimens, the current study offers a training approach that minimizes the potentially limiting effect of individual differences.

Dimensions of complexity in learning from interactive instruction. [for robotic systems deployed in space

NASA Technical Reports Server (NTRS)

Huffman, Scott B.; Laird, John E.

1992-01-01

Robot systems deployed in space must exhibit flexibility. In particular, an intelligent robotic agent should not have to be reprogrammed for each of the various tasks it may face during the course of its lifetime. However, pre-programming knowledge for all of the possible tasks that may be needed is extremely difficult. Therefore, a powerful notion is that of an instructible agent, one which is able to receive task-level instructions and advice from a human advisor. An agent must do more than simply memorize the instructions it is given (this would amount to programming). Rather, after mapping instructions into task constructs that it can reason with, it must determine each instruction's proper scope of applicability. In this paper, we will examine the characteristics of instruction, and the characteristics of agents, that affect learning from instruction. We find that in addition to a myriad of linguistic concerns, both the situatedness of the instructions (their placement within the ongoing execution of tasks) and the prior domain knowledge of the agent have an impact on what can be learned.

Helping reasoners succeed in the Wason selection task: when executive learning discourages heuristic response but does not necessarily encourage logic.

PubMed

Rossi, Sandrine; Cassotti, Mathieu; Moutier, Sylvain; Delcroix, Nicolas; Houdé, Olivier

2015-01-01

Reasoners make systematic logical errors by giving heuristic responses that reflect deviations from the logical norm. Influential studies have suggested first that our reasoning is often biased because we minimize cognitive effort to surpass a cognitive conflict between heuristic response from system 1 and analytic response from system 2 thinking. Additionally, cognitive control processes might be necessary to inhibit system 1 responses to activate a system 2 response. Previous studies have shown a significant effect of executive learning (EL) on adults who have transferred knowledge acquired on the Wason selection task (WST) to another isomorphic task, the rule falsification task (RFT). The original paradigm consisted of teaching participants to inhibit a classical matching heuristic that sufficed the first problem and led to significant EL transfer on the second problem. Interestingly, the reasoning tasks differed in inhibiting-heuristic metacognitive cost. Success on the WST requires half-suppression of the matching elements. In contrast, the RFT necessitates a global rejection of the matching elements for a correct answer. Therefore, metacognitive learning difficulty most likely differs depending on whether one uses the first or second task during the learning phase. We aimed to investigate this difficulty and various matching-bias inhibition effects in a new (reversed) paradigm. In this case, the transfer effect from the RFT to the WST could be more difficult because the reasoner learns to reject all matching elements in the first task. We observed that the EL leads to a significant reduction in matching selections on the WST without increasing logical performances. Interestingly, the acquired metacognitive knowledge was too "strictly" transferred and discouraged matching rather than encouraging logic. This finding underlines the complexity of learning transfer and adds new evidence to the pedagogy of reasoning.

Helping Reasoners Succeed in the Wason Selection Task: When Executive Learning Discourages Heuristic Response but Does Not Necessarily Encourage Logic

PubMed Central

Rossi, Sandrine; Cassotti, Mathieu; Moutier, Sylvain; Delcroix, Nicolas; Houdé, Olivier

2015-01-01

Reasoners make systematic logical errors by giving heuristic responses that reflect deviations from the logical norm. Influential studies have suggested first that our reasoning is often biased because we minimize cognitive effort to surpass a cognitive conflict between heuristic response from system 1 and analytic response from system 2 thinking. Additionally, cognitive control processes might be necessary to inhibit system 1 responses to activate a system 2 response. Previous studies have shown a significant effect of executive learning (EL) on adults who have transferred knowledge acquired on the Wason selection task (WST) to another isomorphic task, the rule falsification task (RFT). The original paradigm consisted of teaching participants to inhibit a classical matching heuristic that sufficed the first problem and led to significant EL transfer on the second problem. Interestingly, the reasoning tasks differed in inhibiting-heuristic metacognitive cost. Success on the WST requires half-suppression of the matching elements. In contrast, the RFT necessitates a global rejection of the matching elements for a correct answer. Therefore, metacognitive learning difficulty most likely differs depending on whether one uses the first or second task during the learning phase. We aimed to investigate this difficulty and various matching-bias inhibition effects in a new (reversed) paradigm. In this case, the transfer effect from the RFT to the WST could be more difficult because the reasoner learns to reject all matching elements in the first task. We observed that the EL leads to a significant reduction in matching selections on the WST without increasing logical performances. Interestingly, the acquired metacognitive knowledge was too “strictly” transferred and discouraged matching rather than encouraging logic. This finding underlines the complexity of learning transfer and adds new evidence to the pedagogy of reasoning. PMID:25849555

RACE/A: An Architectural Account of the Interactions between Learning, Task Control, and Retrieval Dynamics

ERIC Educational Resources Information Center

van Maanen, Leendert; van Rijn, Hedderik; Taatgen, Niels

2012-01-01

This article discusses how sequential sampling models can be integrated in a cognitive architecture. The new theory Retrieval by Accumulating Evidence in an Architecture (RACE/A) combines the level of detail typically provided by sequential sampling models with the level of task complexity typically provided by cognitive architectures. We will use…

Minimal perceptrons for memorizing complex patterns

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

EEG Beta Power but Not Background Music Predicts the Recall Scores in a Foreign-Vocabulary Learning Task.

PubMed

Küssner, Mats B; de Groot, Annette M B; Hofman, Winni F; Hillen, Marij A

2016-01-01

As tantalizing as the idea that background music beneficially affects foreign vocabulary learning may seem, there is-partly due to a lack of theory-driven research-no consistent evidence to support this notion. We investigated inter-individual differences in the effects of background music on foreign vocabulary learning. Based on Eysenck's theory of personality we predicted that individuals with a high level of cortical arousal should perform worse when learning with background music compared to silence, whereas individuals with a low level of cortical arousal should be unaffected by background music or benefit from it. Participants were tested in a paired-associate learning paradigm consisting of three immediate word recall tasks, as well as a delayed recall task one week later. Baseline cortical arousal assessed with spontaneous EEG measurement in silence prior to the learning rounds was used for the analyses. Results revealed no interaction between cortical arousal and the learning condition (background music vs. silence). Instead, we found an unexpected main effect of cortical arousal in the beta band on recall, indicating that individuals with high beta power learned more vocabulary than those with low beta power. To substantiate this finding we conducted an exact replication of the experiment. Whereas the main effect of cortical arousal was only present in a subsample of participants, a beneficial main effect of background music appeared. A combined analysis of both experiments suggests that beta power predicts the performance in the word recall task, but that there is no effect of background music on foreign vocabulary learning. In light of these findings, we discuss whether searching for effects of background music on foreign vocabulary learning, independent of factors such as inter-individual differences and task complexity, might be a red herring. Importantly, our findings emphasize the need for sufficiently powered research designs and exact replications of theory-driven experiments when investigating effects of background music and inter-individual variation on task performance.

EEG Beta Power but Not Background Music Predicts the Recall Scores in a Foreign-Vocabulary Learning Task

PubMed Central

de Groot, Annette M. B.; Hofman, Winni F.; Hillen, Marij A.

2016-01-01

As tantalizing as the idea that background music beneficially affects foreign vocabulary learning may seem, there is—partly due to a lack of theory-driven research—no consistent evidence to support this notion. We investigated inter-individual differences in the effects of background music on foreign vocabulary learning. Based on Eysenck’s theory of personality we predicted that individuals with a high level of cortical arousal should perform worse when learning with background music compared to silence, whereas individuals with a low level of cortical arousal should be unaffected by background music or benefit from it. Participants were tested in a paired-associate learning paradigm consisting of three immediate word recall tasks, as well as a delayed recall task one week later. Baseline cortical arousal assessed with spontaneous EEG measurement in silence prior to the learning rounds was used for the analyses. Results revealed no interaction between cortical arousal and the learning condition (background music vs. silence). Instead, we found an unexpected main effect of cortical arousal in the beta band on recall, indicating that individuals with high beta power learned more vocabulary than those with low beta power. To substantiate this finding we conducted an exact replication of the experiment. Whereas the main effect of cortical arousal was only present in a subsample of participants, a beneficial main effect of background music appeared. A combined analysis of both experiments suggests that beta power predicts the performance in the word recall task, but that there is no effect of background music on foreign vocabulary learning. In light of these findings, we discuss whether searching for effects of background music on foreign vocabulary learning, independent of factors such as inter-individual differences and task complexity, might be a red herring. Importantly, our findings emphasize the need for sufficiently powered research designs and exact replications of theory-driven experiments when investigating effects of background music and inter-individual variation on task performance. PMID:27537520

Learning and memory in streptozotocin-induced diabetic rats in a novel spatial/object discrimination task.

PubMed

Popoviç, M; Biessels, G J; Isaacson, R L; Gispen, W H

2001-08-01

Diabetes mellitus is associated with disturbances of cognitive functioning. The aim of this study was to examine cognitive functioning in diabetic rats using the 'Can test', a novel spatial/object learning and memory task, without the use of aversive stimuli. Rats were trained to select a single rewarded can from seven cans. Mild water deprivation provided the motivation to obtain the reward (0.3 ml of water). After 5 days of baseline training, in which the rewarded can was marked by its surface and position in an open field, the animals were divided into two groups. Diabetes was induced in one group, by an intravenous injection of streptozotocin. Retention of baseline training was tested at 2-weekly intervals for 10 weeks. Next, two adapted versions of the task were used, with 4 days of training in each version. The rewarded can was a soft-drink can with coloured print. In a 'simple visual task' the soft-drink can was placed among six white cans, whereas in a 'complex visual task' it was placed among six soft-drink cans from different brands with distinct prints. In diabetic rats the number of correct responses was lower and number of reference and working memory errors higher than in controls in the various versions of the test. Switches between tasks and increases in task complexity accentuated the performance deficits, which may reflect an inability of diabetic rats to adapt behavioural strategies to the demands of the tasks.

Theoretical Review of Phonics Instruction for Struggling/Beginning Readers of English

ERIC Educational Resources Information Center

Sitthitikul, Pragasit

2014-01-01

Learning to read is a complex task for beginners of English. They must coordinate many cognitive processes to read accurately and fluently, including recognizing words, constructing the meanings of sentences and text, and retaining the information read in memory. An essential part of the process for beginners involves learning the alphabetic…

The Complexities of Digital Storytelling: Factors Affecting Performance, Production, and Project Completion

ERIC Educational Resources Information Center

Gobel, Peter; Kano, Makimi

2016-01-01

Digital storytelling projects provide a variety of opportunities for learning in the language classroom, but along with these opportunities come a number of challenges for both pedagogy and technology. This presentation describes an ongoing multi-method study into factors involved in task-based learning using digital storytelling. Using intact…

Authentic Performance of Complex Problem-Solving Tasks with an EPSS.

ERIC Educational Resources Information Center

Leighton, Chet; McCabe, Cynthia

Just-In-Time Learning (JIT Learning) is a semester-long graduate course that teaches corporate trainers and instructional designers how to design performance improvement interventions. This course is part of a Master's program in Instructional Technology at San Francisco State University. The course has been offered three times and has been…

How High- and Low-Challenge Tasks Affect Motivation and Learning: Implications for Struggling Learners.

ERIC Educational Resources Information Center

Miller, Samuel D.

2003-01-01

Describes how most reading and writing assignments do not require the demonstration of sophisticated cognitive, social, or self-regulation skills. Describes an intervention study addressing this issue, in which students read and wrote complex prose, offered feedback to classmates, and monitored their learning progress. Focuses on how these new…

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

PubMed

Vallila-Rohter, Sofia; Kiran, Swathi

2015-08-01

Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases were calculated. To evaluate strategy use, strategy analyses were conducted over training and testing phases. Participant data were compared with model data that simulated complex multi-cue, single feature, and random pattern strategies. Learning success and strategy use were evaluated within the context of standardized cognitive-linguistic assessments. Categorization accuracy was higher among control participants than among PWA. The majority of control participants implemented suboptimal or optimal multi-cue and single-feature strategies by testing phases of the experiment. In contrast, a large subgroup of PWA implemented random patterns, or no strategy, during both training and testing phases of the experiment. Person-to-person variability arises not only in category learning ability but also in the strategies implemented to complete category learning tasks. PWA less frequently developed effective strategies during category learning tasks than control participants. Certain PWA may have impairments of strategy development or feedback processing not captured by language and currently probed cognitive abilities.

Multi-stage learning aids applied to hands-on software training.

PubMed

Rother, Kristian; Rother, Magdalena; Pleus, Alexandra; Upmeier zu Belzen, Annette

2010-11-01

Delivering hands-on tutorials on bioinformatics software and web applications is a challenging didactic scenario. The main reason is that trainees have heterogeneous backgrounds, different previous knowledge and vary in learning speed. In this article, we demonstrate how multi-stage learning aids can be used to allow all trainees to progress at a similar speed. In this technique, the trainees can utilize cards with hints and answers to guide themselves self-dependently through a complex task. We have successfully conducted a tutorial for the molecular viewer PyMOL using two sets of learning aid cards. The trainees responded positively, were able to complete the task, and the trainer had spare time to respond to individual questions. This encourages us to conclude that multi-stage learning aids overcome many disadvantages of established forms of hands-on software training.

Increase in MST activity correlates with visual motion learning: A functional MRI study of perceptual learning

PubMed Central

Larcombe, Stephanie J.; Kennard, Chris

2017-01-01

Abstract Repeated practice of a specific task can improve visual performance, but the neural mechanisms underlying this improvement in performance are not yet well understood. Here we trained healthy participants on a visual motion task daily for 5 days in one visual hemifield. Before and after training, we used functional magnetic resonance imaging (fMRI) to measure the change in neural activity. We also imaged a control group of participants on two occasions who did not receive any task training. While in the MRI scanner, all participants completed the motion task in the trained and untrained visual hemifields separately. Following training, participants improved their ability to discriminate motion direction in the trained hemifield and, to a lesser extent, in the untrained hemifield. The amount of task learning correlated positively with the change in activity in the medial superior temporal (MST) area. MST is the anterior portion of the human motion complex (hMT+). MST changes were localized to the hemisphere contralateral to the region of the visual field, where perceptual training was delivered. Visual areas V2 and V3a showed an increase in activity between the first and second scan in the training group, but this was not correlated with performance. The contralateral anterior hippocampus and bilateral dorsolateral prefrontal cortex (DLPFC) and frontal pole showed changes in neural activity that also correlated with the amount of task learning. These findings emphasize the importance of MST in perceptual learning of a visual motion task. Hum Brain Mapp 39:145–156, 2018. © 2017 Wiley Periodicals, Inc. PMID:28963815

Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks

NASA Astrophysics Data System (ADS)

Villegas, Pablo; Ruiz-Franco, José; Hidalgo, Jorge; Muñoz, Miguel A.

2016-10-01

Gene regulatory networks can be successfully modeled as Boolean networks. A much discussed hypothesis says that such model networks reproduce empirical findings the best if they are tuned to operate at criticality, i.e. at the borderline between their ordered and disordered phases. Critical networks have been argued to lead to a number of functional advantages such as maximal dynamical range, maximal sensitivity to environmental changes, as well as to an excellent tradeoff between stability and flexibility. Here, we study the effect of noise within the context of Boolean networks trained to learn complex tasks under supervision. We verify that quasi-critical networks are the ones learning in the fastest possible way -even for asynchronous updating rules- and that the larger the task complexity the smaller the distance to criticality. On the other hand, when additional sources of intrinsic noise in the network states and/or in its wiring pattern are introduced, the optimally performing networks become clearly subcritical. These results suggest that in order to compensate for inherent stochasticity, regulatory and other type of biological networks might become subcritical rather than being critical, all the most if the task to be performed has limited complexity.

Tissue Plasminogen Activator Induction in Purkinje Neurons After Cerebellar Motor Learning

NASA Astrophysics Data System (ADS)

Seeds, Nicholas W.; Williams, Brian L.; Bickford, Paula C.

1995-12-01

The cerebellar cortex is implicated in the learning of complex motor skills. This learning may require synaptic remodeling of Purkinje cell inputs. An extracellular serine protease, tissue plasminogen activator (tPA), is involved in remodeling various nonneural tissues and is associated with developing and regenerating neurons. In situ hybridization showed that expression of tPA messenger RNA was increased in the Purkinje neurons of rats within an hour of their being trained for a complex motor task. Antibody to tPA also showed the induction of tPA protein associated with cerebellar Purkinje cells. Thus, the induction of tPA during motor learning may play a role in activity-dependent synaptic plasticity.

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

PubMed

Wen, Zaidao; Hou, Biao; Jiao, Licheng

2017-05-03

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

In search for instructional techniques to maximize the use of germane cognitive resources: A case of teaching complex tasks in physics

NASA Astrophysics Data System (ADS)

Sliva, Yekaterina

The purpose of this study was to introduce an instructional technique for teaching complex tasks in physics, test its effectiveness and efficiency, and understand cognitive processes taking place in learners' minds while they are exposed to this technique. The study was based primarily on cognitive load theory (CLT). CLT determines the amount of total cognitive load imposed on a learner by a learning task as combined intrinsic (invested in comprehending task complexity) and extraneous (wasteful) cognitive load. Working memory resources associated with intrinsic cognitive load are defined as germane resources caused by element interactivity that lead to learning, in contrast to extraneous working memory resources that are devoted to dealing with extraneous cognitive load. However, the amount of learner's working memory resources actually devoted to a task depends on how well the learner is engaged in the learning environment. Since total cognitive load has to stay within limits of working memory capacity, both extraneous and intrinsic cognitive load need to be reduced. In order for effective learning to occur, the use of germane cognitive resources should be maximized. In this study, the use of germane resources was maximized for two experimental groups by providing a learning environment that combined problem-solving procedure with prompts to self-explain with and without completion problems. The study tested three hypotheses and answered two research questions. The first hypothesis predicting that experimental treatments would reduce total cognitive load was not supported. The second hypothesis predicting that experimental treatments would increase performance was supported for the self-explanation group only. The third hypothesis that tested efficiency measure as adopted from Paas and van Merrienboer (1993) was not supported. As for the research question of whether the quality of self-explanations would change with time for the two experimental conditions, it was determined that time had a positive effect on such quality. The research question that investigated learners' attitudes towards the instructions revealed that experimental groups understood the main idea behind the suggested technique and positively reacted to it. The results of the study support the conclusions that (a) prompting learners to self-explain while independently solving problems can increase performance, especially on far transfer questions; (b) better performance is achieved in combination with increased mental effort; (c) self-explanations do not increase time on task; and (d) quality of self-explanations can be improved with time. Results based on the analyses of learners' attitudes further support that learners in the experimental groups understood the main idea behind the suggested techniques and positively reacted to them. The study also raised concern about application of efficiency formula for instructional conditions that increase both performance and mental effort in CLT. As a result, an alternative model was suggested to explain the relationship between performance and mental effort based on Yerkes-Dodson law (1908). Keywords: instructional design, cognitive load, complex tasks, problem-solving, self-explanation.

Performance on the Hamilton search task, and the influence of lateralization, in captive orange-winged Amazon parrots (Amazona amazonica).

PubMed

Cussen, Victoria A; Mench, Joy A

2014-07-01

Psittacines are generally considered to possess cognitive abilities comparable to those of primates. Most psittacine research has evaluated performance on standardized complex cognition tasks, but studies of basic cognitive processes are limited. We tested orange-winged Amazon parrots (Amazona amazonica) on a spatial foraging assessment, the Hamilton search task. This task is a standardized test used in human and non-human primate studies. It has multiple phases, which require trial and error learning, learning set breaking, and spatial memory. We investigated search strategies used to complete the task, cognitive flexibility, and long-term memory for the task. We also assessed the effects of individual strength of motor lateralization (foot preference) and sex on task performance. Almost all (92%) of the parrots acquired the task. All had significant foot preferences, with 69% preferring their left foot, and showed side preferences contralateral to their preferred limb during location selection. The parrots were able to alter their search strategies when reward contingencies changed, demonstrating cognitive flexibility. They were also able to remember the task over a 6-month period. Lateralization had a significant influence on learning set acquisition but no effect on cognitive flexibility. There were no sex differences. To our knowledge, this is the first cognitive study using this particular species and one of the few studies of cognitive abilities in any Neotropical parrot species.

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.

Sensori-Motor Learning with Movement Sonification: Perspectives from Recent Interdisciplinary Studies.

PubMed

Bevilacqua, Frédéric; Boyer, Eric O; Françoise, Jules; Houix, Olivier; Susini, Patrick; Roby-Brami, Agnès; Hanneton, Sylvain

2016-01-01

This article reports on an interdisciplinary research project on movement sonification for sensori-motor learning. First, we describe different research fields which have contributed to movement sonification, from music technology including gesture-controlled sound synthesis, sonic interaction design, to research on sensori-motor learning with auditory-feedback. In particular, we propose to distinguish between sound-oriented tasks and movement-oriented tasks in experiments involving interactive sound feedback. We describe several research questions and recently published results on movement control, learning and perception. In particular, we studied the effect of the auditory feedback on movements considering several cases: from experiments on pointing and visuo-motor tracking to more complex tasks where interactive sound feedback can guide movements, or cases of sensory substitution where the auditory feedback can inform on object shapes. We also developed specific methodologies and technologies for designing the sonic feedback and movement sonification. We conclude with a discussion on key future research challenges in sensori-motor learning with movement sonification. We also point out toward promising applications such as rehabilitation, sport training or product design.

Morphological learning in a novel language: A cross-language comparison.

PubMed

Havas, Viktória; Waris, Otto; Vaquero, Lucía; Rodríguez-Fornells, Antoni; Laine, Matti

2015-01-01

Being able to extract and interpret the internal structure of complex word forms such as the English word dance+r+s is crucial for successful language learning. We examined whether the ability to extract morphological information during word learning is affected by the morphological features of one's native tongue. Spanish and Finnish adult participants performed a word-picture associative learning task in an artificial language where the target words included a suffix marking the gender of the corresponding animate object. The short exposure phase was followed by a word recognition task and a generalization task for the suffix. The participants' native tongues vary greatly in terms of morphological structure, leading to two opposing hypotheses. On the one hand, Spanish speakers may be more effective in identifying gender in a novel language because this feature is present in Spanish but not in Finnish. On the other hand, Finnish speakers may have an advantage as the abundance of bound morphemes in their language calls for continuous morphological decomposition. The results support the latter alternative, suggesting that lifelong experience on morphological decomposition provides an advantage in novel morphological learning.

Multi-Sensor Information Integration and Automatic Understanding

DTIC Science & Technology

2008-05-27

distributions for target tracks and class which are utilized by an active learning cueing management framework to optimally task the appropriate sensor...modality to cued regions of interest. Moreover, this active learning approach also facilitates analyst cueing to help resolve track ambiguities in complex...scenes. We intend to leverage SIG’s active learning with analyst cueing under future efforts with ONR and other DoD agencies. Obtaining long- term

Multi-Sensor Information Integration and Automatic Understanding

DTIC Science & Technology

2008-08-27

distributions for target tracks and class which are utilized by an active learning cueing management framework to optimally task the appropriate sensor modality...to cued regions of interest. Moreover, this active learning approach also facilitates analyst cueing to help resolve track ambiguities in complex...scenes. We intend to leverage SIG’s active learning with analyst cueing under future efforts with ONR and other DoD agencies. Obtaining long- term

Effect of episodic and working memory impairments on semantic and cognitive procedural learning at alcohol treatment entry.

PubMed

Pitel, Anne Lise; Witkowski, Thomas; Vabret, François; Guillery-Girard, Bérengère; Desgranges, Béatrice; Eustache, Francis; Beaunieux, Hélène

2007-02-01

Chronic alcoholism is known to impair the functioning of episodic and working memory, which may consequently reduce the ability to learn complex novel information. Nevertheless, semantic and cognitive procedural learning have not been properly explored at alcohol treatment entry, despite its potential clinical relevance. The goal of the present study was therefore to determine whether alcoholic patients, immediately after the weaning phase, are cognitively able to acquire complex new knowledge, given their episodic and working memory deficits. Twenty alcoholic inpatients with episodic memory and working memory deficits at alcohol treatment entry and a control group of 20 healthy subjects underwent a protocol of semantic acquisition and cognitive procedural learning. The semantic learning task consisted of the acquisition of 10 novel concepts, while subjects were administered the Tower of Toronto task to measure cognitive procedural learning. Analyses showed that although alcoholic subjects were able to acquire the category and features of the semantic concepts, albeit slowly, they presented impaired label learning. In the control group, executive functions and episodic memory predicted semantic learning in the first and second halves of the protocol, respectively. In addition to the cognitive processes involved in the learning strategies invoked by controls, alcoholic subjects seem to attempt to compensate for their impaired cognitive functions, invoking capacities of short-term passive storage. Regarding cognitive procedural learning, although the patients eventually achieved the same results as the controls, they failed to automate the procedure. Contrary to the control group, the alcoholic groups' learning performance was predicted by controlled cognitive functions throughout the protocol. At alcohol treatment entry, alcoholic patients with neuropsychological deficits have difficulty acquiring novel semantic and cognitive procedural knowledge. Compared with controls, they seem to use more costly learning strategies, which are nonetheless less efficient. These learning disabilities need to be considered when treatment requiring the acquisition of complex novel information is envisaged.

Multi-Instance Learning Models for Automated Support of Analysts in Simulated Surveillance Environments

NASA Technical Reports Server (NTRS)

Birisan, Mihnea; Beling, Peter

2011-01-01

New generations of surveillance drones are being outfitted with numerous high definition cameras. The rapid proliferation of fielded sensors and supporting capacity for processing and displaying data will translate into ever more capable platforms, but with increased capability comes increased complexity and scale that may diminish the usefulness of such platforms to human operators. We investigate methods for alleviating strain on analysts by automatically retrieving content specific to their current task using a machine learning technique known as Multi-Instance Learning (MIL). We use MIL to create a real time model of the analysts' task and subsequently use the model to dynamically retrieve relevant content. This paper presents results from a pilot experiment in which a computer agent is assigned analyst tasks such as identifying caravanning vehicles in a simulated vehicle traffic environment. We compare agent performance between MIL aided trials and unaided trials.

Lions (Panthera leo) solve, learn, and remember a novel resource acquisition problem.

PubMed

Borrego, Natalia; Dowling, Brian

2016-09-01

The social intelligence hypothesis proposes that the challenges of complex social life bolster the evolution of intelligence, and accordingly, advanced cognition has convergently evolved in several social lineages. Lions (Panthera leo) offer an ideal model system for cognitive research in a highly social species with an egalitarian social structure. We investigated cognition in lions using a novel resource task: the suspended puzzle box. The task required lions (n = 12) to solve a novel problem, learn the techniques used to solve the problem, and remember techniques for use in future trials. The majority of lions demonstrated novel problem-solving and learning; lions (11/12) solved the task, repeated success in multiple trials, and significantly reduced the latency to success across trials. Lions also demonstrated cognitive abilities associated with memory and solved the task after up to a 7-month testing interval. We also observed limited evidence for social facilitation of the task solution. Four of five initially unsuccessful lions achieved success after being partnered with a successful lion. Overall, our results support the presence of cognition associated with novel problem-solving, learning, and memory in lions. To date, our study is only the second experimental investigation of cognition in lions and further supports expanding cognitive research to lions.

The Hebb repetition effect in simple and complex memory span.

PubMed

Oberauer, Klaus; Jones, Timothy; Lewandowsky, Stephan

2015-08-01

The Hebb repetition effect refers to the finding that immediate serial recall is improved over trials for memory lists that are surreptitiously repeated across trials, relative to new lists. We show in four experiments that the Hebb repetition effect is also observed with a complex-span task, in which encoding or retrieval of list items alternates with an unrelated processing task. The interruption of encoding or retrieval by the processing task did not reduce the size of the Hebb effect, demonstrating that incidental long-term learning forms integrated representations of lists, excluding the interleaved processing events. Contrary to the assumption that complex-span performance relies more on long-term memory than standard immediate serial recall (simple span), the Hebb effect was not larger in complex-span than in simple-span performance. The Hebb effect in complex span was also not modulated by the opportunity for refreshing list items, questioning a role of refreshing for the acquisition of the long-term memory representations underlying the effect.

Inverted-U Function Relating Cortical Plasticity and Task Difficulty

PubMed Central

Engineer, Navzer D.; Engineer, Crystal T.; Reed, Amanda C.; Pandya, Pritesh K.; Jakkamsetti, Vikram; Moucha, Raluca; Kilgard, Michael P.

2012-01-01

Many psychological and physiological studies with simple stimuli have suggested that perceptual learning specifically enhances the response of primary sensory cortex to task-relevant stimuli. The aim of this study was to determine whether auditory discrimination training on complex tasks enhances primary auditory cortex responses to a target sequence relative to non-target and novel sequences. We collected responses from more than 2,000 sites in 31 rats trained on one of six discrimination tasks that differed primarily in the similarity of the target and distractor sequences. Unlike training with simple stimuli, long-term training with complex stimuli did not generate target specific enhancement in any of the groups. Instead, cortical receptive field size decreased, latency decreased, and paired pulse depression decreased in rats trained on the tasks of intermediate difficulty while tasks that were too easy or too difficult either did not alter or degraded cortical responses. These results suggest an inverted-U function relating neural plasticity and task difficulty. PMID:22249158

The influence of cue-task association and location on switch cost and alternating-switch cost.

PubMed

Arbuthnott, Katherine D; Woodward, Todd S

2002-03-01

Task-switching performance is strongly influenced by whether the imperative stimulus uniquely specifies which task to perform: Switch cost is substantial with bivalent stimuli but is greatly reduced with univalent stimuli, suggesting that available contextual information influences processing in task-switching situations. The present study examined whether task-relevant information provided by task cues influences the magnitude of switch cost in a parallel manner. Cues presented 500 ms prior to a trivalent stimulus indicated which of three tasks to perform. These cues either had a preexisting association with the to-be-performed task (verbal cues), or a recently learned association with the task (spatial and shape cues). The results paralleled the effects of stimulus bivalence: substantial switch cost with recently learned cue-task associations and greatly reduced switch cost with preexisting cue-task associations. This suggests that both stimulus-based and cue-based information can activate the relevant task set, possibly providing external support to endogenous control processes. Alternating-switch cost, a greater cost for switching back to a recently abandoned task, was also observed with both preexisting and recently learned cue-task associations, but only when all tasks were presented in a consistent spatial location. When spatial location was used to cue the to-be-performed tasks, no alternating-switch cost was observed, suggesting that different processes may be involved when tasks are uniquely located in space. Specification of the nature of these processes may prove to be complex, as post-hoc inspection of the data suggested that for the spatial cue condition, the alternating-switch cost may oscillate between cost and benefit, depending on the relevant task.

Requiring collaboration: Hippocampal-prefrontal networks needed in spatial working memory and ageing. A multivariate analysis approach.

PubMed

Zancada-Menendez, C; Alvarez-Suarez, P; Sampedro-Piquero, P; Cuesta, M; Begega, A

2017-04-01

Ageing is characterized by a decline in the processes of retention and storage of spatial information. We have examined the behavioural performance of adult rats (3months old) and aged rats (18months old) in a spatial complex task (delayed match to sample). The spatial task was performed in the Morris water maze and consisted of three sessions per day over a period of three consecutive days. Each session consisted of two trials (one sample and retention) and inter-session intervals of 5min. Behavioural results showed that the spatial task was difficult for middle aged group. This worse execution could be associated with impairments of processing speed and spatial information retention. We examined the changes in the neuronal metabolic activity of different brain regions through cytochrome C oxidase histochemistry. Then, we performed MANOVA and Discriminant Function Analyses to determine the functional profile of the brain networks that are involved in the spatial learning of the adult and middle-aged groups. This multivariate analysis showed two principal functional networks that necessarily participate in this spatial learning. The first network was composed of the supramammillary nucleus, medial mammillary nucleus, CA3, and CA1. The second one included the anterior cingulate, prelimbic, and infralimbic areas of the prefrontal cortex, dentate gyrus, and amygdala complex (basolateral l and central subregions). There was a reduction in the hippocampal-supramammilar network in both learning groups, whilst there was an overactivation in the executive network, especially in the aged group. This response could be due to a higher requirement of the executive control in a complex spatial memory task in older animals. Copyright © 2017 Elsevier Inc. All rights reserved.

How do task characteristics affect learning and performance? The roles of variably mapped and dynamic tasks.

PubMed

Macnamara, Brooke N; Frank, David J

2018-05-01

For well over a century, scientists have investigated individual differences in performance. The majority of studies have focused on either differences in practice, or differences in cognitive resources. However, the predictive ability of either practice or cognitive resources varies considerably across tasks. We are the first to examine task characteristics' impact on learning and performance in a complex task while controlling for other task characteristics. In 2 experiments we test key theoretical task characteristic thought to moderate the relationship between practice, cognitive resources, and performance. We devised a task where each of several key task characteristics can be manipulated independently. Participants played 5 rounds of a game similar to the popular tower defense videogame Plants vs. Zombies where both cognitive load and game characteristics were manipulated. In Experiment 1, participants either played a consistently mapped version-the stimuli and the associated meaning of their properties were constant across the 5 rounds-or played a variably mapped version-the stimuli and the associated meaning of their properties changed every few minutes. In Experiment 2, participants either played a static version-that is, turn taking with no time pressure-or played a dynamic version-that is, the stimuli moved regardless of participants' response rates. In Experiment 1, participants' accuracy and efficiency were substantially hindered in the variably mapped conditions. In Experiment 2, learning and performance accuracy were hindered in the dynamic conditions, especially when under cognitive load. Our results suggest that task characteristics impact the relative importance of cognitive resources and practice on predicting learning and performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The Role of Awareness for Complex Planning Task Performance: A Microgaming Study

ERIC Educational Resources Information Center

Lukosch, Heide; Groen, Daan; Kurapati, Shalini; Klemke, Roland; Verbraeck, Alexander

2016-01-01

This study introduces the concept of microgames to support situated learning in order to foster situational awareness (SA) of planners in seaport container terminals. In today's complex working environments, it is often difficult to develop the required level of understanding of a given situation, described as situational awareness. A container…

Fostering Self-Regulation in Training Complex Cognitive Tasks

ERIC Educational Resources Information Center

van Meeuwen, Ludo W.; Brand-Gruwel, Saskia; Kirschner, Paul A.; de Bock, Jeano J. P. R.; van Merriënboer, Jeroen J. G.

2018-01-01

In complex cognitive domains such as air traffic control, professionals must be able to adapt to and act upon continuing changes in a highly advanced technological work environment. To function optimally in such an environment, the controllers must be able to regulate their learning. Although these regulation skills should be part of their…

Influence of Stimulus Symmetry and Complexity upon Haptic Scanning Strategies During Detection, Learning and Recognition Tasks.

ERIC Educational Resources Information Center

Locher, Paul J.; Simmons, Roger W.

Two experiments were conducted to investigate the perceptual processes involved in haptic exploration of randomly generated shapes. Experiment one required subjects to detect symmetrical or asymmetrical characteristics of individually presented plastic shapes, also varying in complexity. Scanning time for both symmetrical and asymmetrical shapes…

You Cannot Do This Alone! Increasing Task Interdependence in Cooperative Educational Videogames to Encourage Collaboration

ERIC Educational Resources Information Center

Nebel, Steve; Schneider, Sascha; Beege, Maik; Kolda, Franziska; Mackiewicz, Valerie; Rey, Günter Daniel

2017-01-01

Complex, multimedia software such as educational videogames offer a wide range of elements to modify learner behavior. The adjustment of such software might support learning, especially in complex settings like collaborative or cooperative scenarios. Coming from a theoretical background of educational psychology, our experiment seeks to implement…

Abrupt Strategy Change Underlies Gradual Performance Change: Bayesian Hierarchical Models of Component and Aggregate Strategy Use

ERIC Educational Resources Information Center

Wynton, Sarah K. A.; Anglim, Jeromy

2017-01-01

While researchers have often sought to understand the learning curve in terms of multiple component processes, few studies have measured and mathematically modeled these processes on a complex task. In particular, there remains a need to reconcile how abrupt changes in strategy use can co-occur with gradual changes in task completion time. Thus,…

Task Effects on Linguistic Complexity and Accuracy: A Large-Scale Learner Corpus Analysis Employing Natural Language Processing Techniques

ERIC Educational Resources Information Center

Alexopoulou, Theodora; Michel, Marije; Murakami, Akira; Meurers, Detmar

2017-01-01

Large-scale learner corpora collected from online language learning platforms, such as the EF-Cambridge Open Language Database (EFCAMDAT), provide opportunities to analyze learner data at an unprecedented scale. However, interpreting the learner language in such corpora requires a precise understanding of tasks: How does the prompt and input of a…

REM Restriction Persistently Alters Strategy Used to Solve a Spatial Task

ERIC Educational Resources Information Center

Bjorness, Theresa E.; Tysor, Michael K.; Poe, Gina R.; Riley, Brett T.

2005-01-01

We tested the hypothesis that rapid eye movement (REM) sleep is important for complex associative learning by restricting rats from entering REM sleep for 4 h either immediately after training on an eight-box spatial task (0-4 REMr) or 4 h following training (4-8 REMr). Both groups of REM-restricted rats eventually reached the same overall…

Assessing Understanding of Complex Learning Outcomes and Real-World Skills Using an Authentic Software Tool: A Study from Biomedical Sciences

ERIC Educational Resources Information Center

Dermo, John; Boyne, James

2014-01-01

We describe a study conducted during 2009-12 into innovative assessment practice, evaluating an assessed coursework task on a final year Medical Genetics module for Biomedical Science undergraduates. An authentic e-assessment coursework task was developed, integrating objectively marked online questions with an online DNA sequence analysis tool…

Brain Regions Engaged by Part- and Whole-task Performance in a Video Game: A Model-based Test of the Decomposition Hypothesis

PubMed Central

Anderson, John R.; Bothell, Daniel; Fincham, Jon M.; Anderson, Abraham R.; Poole, Ben; Qin, Yulin

2013-01-01

Part- and whole-task conditions were created by manipulating the presence of certain components of the Space Fortress video game. A cognitive model was created for two-part games that could be combined into a model that performed the whole game. The model generated predictions both for behavioral patterns and activation patterns in various brain regions. The activation predictions concerned both tonic activation that was constant in these regions during performance of the game and phasic activation that occurred when there was resource competition. The model’s predictions were confirmed about how tonic and phasic activation in different regions would vary with condition. These results support the Decomposition Hypothesis that the execution of a complex task can be decomposed into a set of information-processing components and that these components combine unchanged in different task conditions. In addition, individual differences in learning gains were predicted by individual differences in phasic activation in those regions that displayed highest tonic activity. This individual difference pattern suggests that the rate of learning of a complex skill is determined by capacity limits. PMID:21557648

Auditory Learning Using a Portable Real-Time Vocoder: Preliminary Findings

PubMed Central

Pisoni, David B.

2015-01-01

Purpose Although traditional study of auditory training has been in controlled laboratory settings, interest has been increasing in more interactive options. The authors examine whether such interactive training can result in short-term perceptual learning, and the range of perceptual skills it impacts. Method Experiments 1 (N = 37) and 2 (N = 21) used pre- and posttest measures of speech and nonspeech recognition to find evidence of learning (within subject) and to compare the effects of 3 kinds of training (between subject) on the perceptual abilities of adults with normal hearing listening to simulations of cochlear implant processing. Subjects were given interactive, standard lab-based, or control training experience for 1 hr between the pre- and posttest tasks (unique sets across Experiments 1 & 2). Results Subjects receiving interactive training showed significant learning on sentence recognition in quiet task (Experiment 1), outperforming controls but not lab-trained subjects following training. Training groups did not differ significantly on any other task, even those directly involved in the interactive training experience. Conclusions Interactive training has the potential to produce learning in 1 domain (sentence recognition in quiet), but the particulars of the present training method (short duration, high complexity) may have limited benefits to this single criterion task. PMID:25674884

Connecting Teaching and Learning: History, Evolution, and Case Studies of Teacher Work Sample Methodology

ERIC Educational Resources Information Center

Rosselli, Hilda, Ed.; Girod, Mark, Ed.; Brodsky, Meredith, Ed.

2011-01-01

As accountability in education has become an increasingly prominent topic, teacher preparation programs are being asked to provide credible evidence that their teacher candidates can impact student learning. Teacher Work Samples, first developed 30 years ago, have emerged as an effective method of quantifying the complex set of tasks that comprise…

Learning Problem-Solving through Making Games at the Game Design and Learning Summer Program

ERIC Educational Resources Information Center

Akcaoglu, Mete

2014-01-01

Today's complex and fast-evolving world necessitates young students to possess design and problem-solving skills more than ever. One alternative method of teaching children problem-solving or thinking skills has been using computer programming, and more recently, game-design tasks. In this pre-experimental study, a group of middle school…

Incorporating Risk Assessment into the Formative Evaluation of an Authentic e-Learning Program

ERIC Educational Resources Information Center

Vesper, James L.; Kartoglu, Ümit; Herrington, Jan; Reeves, Thomas C.

2016-01-01

This paper describes the use of two different risk assessment strategies during the design and development of a complex authentic task-based e-learning program developed by the World Health Organization (WHO). The first strategy involved the use of expert reviewers and the second strategy employed the engagement of a risk assessment expert…

An Effective Online Teaching Method: The Combination of Collaborative Learning with Initiation and Self-Regulation Learning with Feedback

ERIC Educational Resources Information Center

Tsai, Chia-Wen

2013-01-01

In modern business environments, work and tasks have become more complex and require more interdisciplinary skills to complete, including collaborative and computing skills for website design. However, the computing education in Taiwan can hardly be recognised as effective in developing and transforming students into competitive employees. In this…

Educational Supervisors' Metaphorical Roots of Beliefs about Teaching and Learning

ERIC Educational Resources Information Center

Buaraphan, Khajornsak

2012-01-01

Beliefs are a complex psychological construct that have potential to drive a person to make decisions and act. A person's metaphors can serve as roots of their beliefs. In this study, the metaphor construction task (MCT) was utilized to uncover beliefs about teaching and learning held by 216 educational supervisors from 10 provinces in the central…

Practical and Pedagogical Aspects of Learning through Participation: The LTP Assessment Design Framework

ERIC Educational Resources Information Center

Mackaway, Jacqueline A.; Winchester-Seeto, Theresa; Coulson, Debra; Harvey, Marina

2011-01-01

Assessment of student learning in experience-based education is recognised as being a complex but important task. Practitioners are faced with a myriad of practical and pedagogical issues that influence what and how they assess, and can severely impact the effectiveness of assessment strategies. This paper presents a synthesised overview of the…

Attitudes towards Online Feedback on Writing: Why Students Mistrust the Learning Potential of Models

ERIC Educational Resources Information Center

Strobl, Carola

2015-01-01

This exploratory study sheds new light on students' perceptions of online feedback types for a complex writing task, summary writing from spoken input in a foreign language (L2), and investigates how these correlate with their actual learning to write. Students tend to favour clear-cut, instructivist rather than constructivist feedback, and guided…

A Mixed Methods Approach to Investigating Cognitive Load and Cognitive Presence in an Online and Face-to-Face College Algebra Course

ERIC Educational Resources Information Center

Mills, Jodi Jean

2016-01-01

Most research on Cognitive Load Theory (Sweller, 1988) has uncovered many instructional design considerations for learning complex tasks. Additionally, the Community of Inquiry (Garrison, Anderson, & Archer, 2000) framework describes many of the learning experiences in online education. A gap existed in the literature for investigating…

Nonformal and Informal Adult Learning in Museums: A Literature Review

ERIC Educational Resources Information Center

Dudzinska-Przesmitzki, Dana; Grenier, Robin S.

2008-01-01

The taking up of an "educative" mantle has proven to be a complex task for museums, filled with many unknown and/or misunderstood factors. Of the vast assortment of educational opportunities museums afford their adult patrons and staff, the majority fall into one or two learning categories: either they are nonformal or informal. In effort to…

Productive Group Engagement in Cognitive Activity and Metacognitive Regulation during Collaborative Learning: Can It Explain Differences in Students' Conceptual Understanding?

ERIC Educational Resources Information Center

Khosa, Deep K.; Volet, Simone E.

2014-01-01

This paper addresses the nature and significance of productive engagement in cognitive activity and metacognitive regulation in collaborative learning tasks that involve complex scientific knowledge. A situative framework, combining the constructs of social regulation and content processing, provided the theoretical basis for the development of a…

Educational Games in Practice: The Challenges Involved in Conducting a Game-Based Curriculum

ERIC Educational Resources Information Center

Marklund, Björn Berg; Taylor, Anna-Sofia Alklind

2016-01-01

The task of integrating games into an educational setting is a demanding one, and integrating games as a harmonious part of a bigger ecosystem of learning requires teachers to orchestrate a myriad of complex organizational resources. Historically, research on digital game-based learning has focused heavily on the coupling between game designs,…

Medical students' reflective writing about a task-based learning experience on public health communication.

PubMed

Koh, Yang Huang; Wong, Mee Lian; Lee, Jeanette Jen-Mai

2014-02-01

Medical educators constantly face the challenge of preparing students for public health practice. This study aimed to analyze students' reflections to gain insight into their task-based experiences in the public health communication selective. We have also examined their self-reported learning outcomes and benefits with regard to application of public health communication. Each student wrote a semi-structured reflective journal about his or her experiences leading to the delivery of a public health talk by the group. Records from 41 students were content-analyzed for recurring themes and sub-themes. Students reported a wide range of personal and professional issues. Their writings were characterized by a deep sense of self-awareness and social relatedness such as increased self-worth, communications skills, and collaborative learning. The learning encounter challenged assumptions, and enhanced awareness of the complexity of behaviour change Students also wrote about learning being more enjoyable and how the selective had forced them to adopt a more thoughtful stance towards knowledge acquisition and assimilation. Task-based learning combined with a process for reflection holds promise as an educational strategy for teaching public health communication, and cultivating the habits of reflective practice.

Varied Practice in Laparoscopy Training: Beneficial Learning Stimulation or Cognitive Overload?

PubMed

Spruit, Edward N; Kleijweg, Luca; Band, Guido P H; Hamming, Jaap F

2016-01-01

Determining the optimal design for surgical skills training is an ongoing research endeavor. In education literature, varied practice is listed as a positive intervention to improve acquisition of knowledge and motor skills. In the current study we tested the effectiveness of a varied practice intervention during laparoscopy training. Twenty-four trainees (control group) without prior experience received a 3 weeks laparoscopic skills training utilizing four basic and one advanced training task. Twenty-eight trainees (experimental group) received the same training with a random training task schedule, more frequent task switching and inverted viewing conditions on the four basic training tasks, but not the advanced task. Results showed inferior performance of the experimental group on the four basic laparoscopy tasks during training, at the end of training and at a 2 months retention session. We assume the inverted viewing conditions have led to the deterioration of learning in the experimental group because no significant differences were found between groups on the only task that had not been practiced under inverted viewing conditions; the advanced laparoscopic task. Potential moderating effects of inter-task similarity, task complexity, and trainee characteristics are discussed.

Varied Practice in Laparoscopy Training: Beneficial Learning Stimulation or Cognitive Overload?

PubMed Central

Spruit, Edward N.; Kleijweg, Luca; Band, Guido P. H.; Hamming, Jaap F.

2016-01-01

Determining the optimal design for surgical skills training is an ongoing research endeavor. In education literature, varied practice is listed as a positive intervention to improve acquisition of knowledge and motor skills. In the current study we tested the effectiveness of a varied practice intervention during laparoscopy training. Twenty-four trainees (control group) without prior experience received a 3 weeks laparoscopic skills training utilizing four basic and one advanced training task. Twenty-eight trainees (experimental group) received the same training with a random training task schedule, more frequent task switching and inverted viewing conditions on the four basic training tasks, but not the advanced task. Results showed inferior performance of the experimental group on the four basic laparoscopy tasks during training, at the end of training and at a 2 months retention session. We assume the inverted viewing conditions have led to the deterioration of learning in the experimental group because no significant differences were found between groups on the only task that had not been practiced under inverted viewing conditions; the advanced laparoscopic task. Potential moderating effects of inter-task similarity, task complexity, and trainee characteristics are discussed. PMID:27242599

Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching.

PubMed

Edwards, Ann L; Dawson, Michael R; Hebert, Jacqueline S; Sherstan, Craig; Sutton, Richard S; Chan, K Ming; Pilarski, Patrick M

2016-10-01

Myoelectric prostheses currently used by amputees can be difficult to control. Machine learning, and in particular learned predictions about user intent, could help to reduce the time and cognitive load required by amputees while operating their prosthetic device. The goal of this study was to compare two switching-based methods of controlling a myoelectric arm: non-adaptive (or conventional) control and adaptive control (involving real-time prediction learning). Case series study. We compared non-adaptive and adaptive control in two different experiments. In the first, one amputee and one non-amputee subject controlled a robotic arm to perform a simple task; in the second, three able-bodied subjects controlled a robotic arm to perform a more complex task. For both tasks, we calculated the mean time and total number of switches between robotic arm functions over three trials. Adaptive control significantly decreased the number of switches and total switching time for both tasks compared with the conventional control method. Real-time prediction learning was successfully used to improve the control interface of a myoelectric robotic arm during uninterrupted use by an amputee subject and able-bodied subjects. Adaptive control using real-time prediction learning has the potential to help decrease both the time and the cognitive load required by amputees in real-world functional situations when using myoelectric prostheses. © The International Society for Prosthetics and Orthotics 2015.

Augmenting Instructional Animations with a Body Analogy to Help Children Learn about Physical Systems

PubMed Central

Pouw, Wim T. J. L.; van Gog, Tamara; Zwaan, Rolf A.; Paas, Fred

2016-01-01

We investigated whether augmenting instructional animations with a body analogy (BA) would improve 10- to 13-year-old children’s learning about class-1 levers. Children with a lower level of general math skill who learned with an instructional animation that provided a BA of the physical system, showed higher accuracy on a lever problem-solving reaction time task than children studying the instructional animation without this BA. Additionally, learning with a BA led to a higher speed–accuracy trade-off during the transfer task for children with a lower math skill, which provided additional evidence that especially this group is likely to be affected by learning with a BA. However, overall accuracy and solving speed on the transfer task was not affected by learning with or without this BA. These results suggest that providing children with a BA during animation study provides a stepping-stone for understanding mechanical principles of a physical system, which may prove useful for instructional designers. Yet, because the BA does not seem effective for all children, nor for all tasks, the degree of effectiveness of body analogies should be studied further. Future research, we conclude, should be more sensitive to the necessary degree of analogous mapping between the body and physical systems, and whether this mapping is effective for reasoning about more complex instantiations of such physical systems. PMID:27375538

A neural learning classifier system with self-adaptive constructivism for mobile robot control.

PubMed

Hurst, Jacob; Bull, Larry

2006-01-01

For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.

Adaptive robotic control driven by a versatile spiking cerebellar network.

PubMed

Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Carrillo, Richard R; Luque, Niceto R; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio

2014-01-01

The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.

Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation

NASA Astrophysics Data System (ADS)

Chen, Tianyi; Mokhtari, Aryan; Wang, Xin; Ribeiro, Alejandro; Giannakis, Georgios B.

2017-06-01

Existing approaches to resource allocation for nowadays stochastic networks are challenged to meet fast convergence and tolerable delay requirements. The present paper leverages online learning advances to facilitate stochastic resource allocation tasks. By recognizing the central role of Lagrange multipliers, the underlying constrained optimization problem is formulated as a machine learning task involving both training and operational modes, with the goal of learning the sought multipliers in a fast and efficient manner. To this end, an order-optimal offline learning approach is developed first for batch training, and it is then generalized to the online setting with a procedure termed learn-and-adapt. The novel resource allocation protocol permeates benefits of stochastic approximation and statistical learning to obtain low-complexity online updates with learning errors close to the statistical accuracy limits, while still preserving adaptation performance, which in the stochastic network optimization context guarantees queue stability. Analysis and simulated tests demonstrate that the proposed data-driven approach improves the delay and convergence performance of existing resource allocation schemes.

Autism: Too eager to learn? Event related potential findings of increased dependency on intentional learning in a serial reaction time task.

PubMed

Zwart, Fenny S; Vissers, Constance Th W M; van der Meij, Roemer; Kessels, Roy P C; Maes, Joseph H R

2017-09-01

It has been suggested that people with autism spectrum disorder (ASD) have an increased tendency to use explicit (or intentional) learning strategies. This altered learning may play a role in the development of the social communication difficulties characterizing ASD. In the current study, we investigated incidental and intentional sequence learning using a Serial Reaction Time (SRT) task in an adult ASD population. Response times and event related potentials (ERP) components (N2b and P3) were assessed as indicators of learning and knowledge. Findings showed that behaviorally, sequence learning and ensuing explicit knowledge were similar in ASD and typically developing (TD) controls. However, ERP findings showed that learning in the TD group was characterized by an enhanced N2b, while learning in the ASD group was characterized by an enhanced P3. These findings suggest that learning in the TD group might be more incidental in nature, whereas learning in the ASD group is more intentional or effortful. Increased intentional learning might serve as a strategy for individuals with ASD to control an overwhelming environment. Although this led to similar behavioral performances on the SRT task, it is very plausible that this intentional learning has adverse effects in more complex social situations, and hence contributes to the social impairments found in ASD. Autism Res 2017, 10: 1533-1543. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Increase in MST activity correlates with visual motion learning: A functional MRI study of perceptual learning.

PubMed

Larcombe, Stephanie J; Kennard, Chris; Bridge, Holly

2018-01-01

Repeated practice of a specific task can improve visual performance, but the neural mechanisms underlying this improvement in performance are not yet well understood. Here we trained healthy participants on a visual motion task daily for 5 days in one visual hemifield. Before and after training, we used functional magnetic resonance imaging (fMRI) to measure the change in neural activity. We also imaged a control group of participants on two occasions who did not receive any task training. While in the MRI scanner, all participants completed the motion task in the trained and untrained visual hemifields separately. Following training, participants improved their ability to discriminate motion direction in the trained hemifield and, to a lesser extent, in the untrained hemifield. The amount of task learning correlated positively with the change in activity in the medial superior temporal (MST) area. MST is the anterior portion of the human motion complex (hMT+). MST changes were localized to the hemisphere contralateral to the region of the visual field, where perceptual training was delivered. Visual areas V2 and V3a showed an increase in activity between the first and second scan in the training group, but this was not correlated with performance. The contralateral anterior hippocampus and bilateral dorsolateral prefrontal cortex (DLPFC) and frontal pole showed changes in neural activity that also correlated with the amount of task learning. These findings emphasize the importance of MST in perceptual learning of a visual motion task. Hum Brain Mapp 39:145-156, 2018. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Science and Sandy: Lessons Learned

NASA Astrophysics Data System (ADS)

Werner, K.

2013-12-01

Following Hurricane Sandy's impact on the mid-Atlantic region, President Obama established a Task Force to '...ensure that the Federal Government continues to provide appropriate resources to support affected State, local, and tribal communities to improve the region's resilience, health, and prosperity by building for the future.' The author was detailed from NOAA to the Task Force between January and June 2013. As the Task Force and others began to take stock of the region's needs and develop plans to address them, many diverse approaches emerged from different areas of expertise including: infrastructure, management and construction, housing, public health, and others. Decision making in this environment was complex with many interests and variables to consider and balance. Although often relevant, science and technical expertise was not always at the forefront of this process. This talk describes the author's experience with the Sandy Task Force focusing on organizing scientific expertise to support the work of the Task Force. This includes a description of federal activity supporting Sandy recovery efforts, the role of the Task Force, and lessons learned from developing a science support function within the Task Force.

Network mechanisms of intentional learning

PubMed Central

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

2016-01-01

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

An Examination of Strategy Implementation During Abstract Nonlinguistic Category Learning in Aphasia

PubMed Central

Kiran, Swathi

2015-01-01

Purpose Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Method Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases were calculated. To evaluate strategy use, strategy analyses were conducted over training and testing phases. Participant data were compared with model data that simulated complex multi-cue, single feature, and random pattern strategies. Learning success and strategy use were evaluated within the context of standardized cognitive–linguistic assessments. Results Categorization accuracy was higher among control participants than among PWA. The majority of control participants implemented suboptimal or optimal multi-cue and single-feature strategies by testing phases of the experiment. In contrast, a large subgroup of PWA implemented random patterns, or no strategy, during both training and testing phases of the experiment. Conclusions Person-to-person variability arises not only in category learning ability but also in the strategies implemented to complete category learning tasks. PWA less frequently developed effective strategies during category learning tasks than control participants. Certain PWA may have impairments of strategy development or feedback processing not captured by language and currently probed cognitive abilities. PMID:25908438

Learning of Temporal and Spatial Movement Aspects: A Comparison of Four Types of Haptic Control and Concurrent Visual Feedback.

PubMed

Rauter, Georg; Sigrist, Roland; Riener, Robert; Wolf, Peter

2015-01-01

In literature, the effectiveness of haptics for motor learning is controversially discussed. Haptics is believed to be effective for motor learning in general; however, different types of haptic control enhance different movement aspects. Thus, in dependence on the movement aspects of interest, one type of haptic control may be effective whereas another one is not. Therefore, in the current work, it was investigated if and how different types of haptic controllers affect learning of spatial and temporal movement aspects. In particular, haptic controllers that enforce active participation of the participants were expected to improve spatial aspects. Only haptic controllers that provide feedback about the task's velocity profile were expected to improve temporal aspects. In a study on learning a complex trunk-arm rowing task, the effect of training with four different types of haptic control was investigated: position control, path control, adaptive path control, and reactive path control. A fifth group (control) trained with visual concurrent augmented feedback. As hypothesized, the position controller was most effective for learning of temporal movement aspects, while the path controller was most effective in teaching spatial movement aspects of the rowing task. Visual feedback was also effective for learning temporal and spatial movement aspects.

Integration of Temporal and Ordinal Information During Serial Interception Sequence Learning

PubMed Central

Gobel, Eric W.; Sanchez, Daniel J.; Reber, Paul J.

2011-01-01

The expression of expert motor skills typically involves learning to perform a precisely timed sequence of movements (e.g., language production, music performance, athletic skills). Research examining incidental sequence learning has previously relied on a perceptually-cued task that gives participants exposure to repeating motor sequences but does not require timing of responses for accuracy. Using a novel perceptual-motor sequence learning task, learning a precisely timed cued sequence of motor actions is shown to occur without explicit instruction. Participants learned a repeating sequence through practice and showed sequence-specific knowledge via a performance decrement when switched to an unfamiliar sequence. In a second experiment, the integration of representation of action order and timing sequence knowledge was examined. When either action order or timing sequence information was selectively disrupted, performance was reduced to levels similar to completely novel sequences. Unlike prior sequence-learning research that has found timing information to be secondary to learning action sequences, when the task demands require accurate action and timing information, an integrated representation of these types of information is acquired. These results provide the first evidence for incidental learning of fully integrated action and timing sequence information in the absence of an independent representation of action order, and suggest that this integrative mechanism may play a material role in the acquisition of complex motor skills. PMID:21417511

Accessing FMS Functionality: The Impact of Design on Learning

NASA Technical Reports Server (NTRS)

Fennell, Karl; Sherry, Lance; Roberts, Ralph, Jr.

2004-01-01

In modern commercial and military aircraft, the Flight Management System (FMS) lies at the heart of the functionality of the airplane. The nature of the FMS has also caused great difficulties learning and accessing this functionality. This study examines actual Air Force pilots who were qualified on the newly introduced advanced FMS and shows that the design of the system itself is a primary source of difficulty learning the system. Twenty representative tasks were selected which the pilots could be expected to accomplish on an ' actual flight. These tasks were analyzed using the RAFIV stage model (Sherry, Polson, et al. 2002). This analysis demonstrates that a great burden is placed on remembering complex reformulation of the task to function mapping. 65% of the tasks required retaining one access steps in memory to accomplish the task, 20% required two memorized access steps, and 15% required zero memorized access steps. The probability that a participant would make an access error on the tasks was: two memorized access steps - 74%, one memorized access step - 13%, and zero memorized access steps - 6%. Other factors were analyzed as well, including experience with the system and frequency of use. This completed the picture of a system with many memorized steps causing difficulty with the new system, especially when trying to fine where to access the correct function.

The Effects of Audio-Visual Recorded and Audio Recorded Listening Tasks on the Accuracy of Iranian EFL Learners' Oral Production

ERIC Educational Resources Information Center

Drood, Pooya; Asl, Hanieh Davatgari

2016-01-01

The ways in which task in classrooms has developed and proceeded have receive great attention in the field of language teaching and learning in the sense that they draw attention of learners to the competing features such as accuracy, fluency, and complexity. English audiovisual and audio recorded materials have been widely used by teachers and…

Emotion-Based Learning and Central Executive Resources: An Investigation of Intuition and the Iowa Gambling Task

ERIC Educational Resources Information Center

Turnbull, O.H.; Evans, C.E.Y.; Bunce, A.; Carzolio, B.; O'Connor, J.

2005-01-01

The role of emotion in complex decision-making can be assessed on the Iowa Gambling Task (IGT), a widely used neuropsychological measure that may tap a different aspect of executive function than that assessed by conventional measures. Most notably, the 'feeling' about which decks are good or bad, often described in relation to IGT performance,…

Coordinating Procedural and Conceptual Knowledge to Make Sense of Word Equations: Understanding the Complexity of a "Simple" Completion Task at the Learner's Resolution

ERIC Educational Resources Information Center

Taber, Keith S.; Bricheno, Pat

2009-01-01

The present paper discusses the conceptual demands of an apparently straightforward task set to secondary-level students--completing chemical word equations with a single omitted term. Chemical equations are of considerable importance in chemistry, and school students are expected to learn to be able to write and interpret them. However, it is…

Machine learning in cardiovascular medicine: are we there yet?

PubMed

Shameer, Khader; Johnson, Kipp W; Glicksberg, Benjamin S; Dudley, Joel T; Sengupta, Partho P

2018-01-19

Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from data, allowing computers to find hidden insights without being explicitly programmed where to look. These include a family of operations encompassing several terms like machine learning, cognitive learning, deep learning and reinforcement learning-based methods that can be used to integrate and interpret complex biomedical and healthcare data in scenarios where traditional statistical methods may not be able to perform. In this review article, we discuss the basics of machine learning algorithms and what potential data sources exist; evaluate the need for machine learning; and examine the potential limitations and challenges of implementing machine in the context of cardiovascular medicine. The most promising avenues for AI in medicine are the development of automated risk prediction algorithms which can be used to guide clinical care; use of unsupervised learning techniques to more precisely phenotype complex disease; and the implementation of reinforcement learning algorithms to intelligently augment healthcare providers. The utility of a machine learning-based predictive model will depend on factors including data heterogeneity, data depth, data breadth, nature of modelling task, choice of machine learning and feature selection algorithms, and orthogonal evidence. A critical understanding of the strength and limitations of various methods and tasks amenable to machine learning is vital. By leveraging the growing corpus of big data in medicine, we detail pathways by which machine learning may facilitate optimal development of patient-specific models for improving diagnoses, intervention and outcome in cardiovascular medicine. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Applying the PDCA Cycle to the Complex Task of Teaching and Assessing Public Relations Writing

ERIC Educational Resources Information Center

Knight, John E.; Allen, Sandra

2012-01-01

Teaching skills, knowledge and abilities appropriate for career-ready graduates and assessing learning are complex issues. Developing a valid and reliable approach is often by trial and error. Instead, the authors employed Deming's PDCA Cycle of continuous improvement as a systematic procedure to incrementally move closer to their goal. This paper…

Supporting Individuals with Autism Spectrum Disorder in Understanding and Coping with Complex Social Emotional Issues

ERIC Educational Resources Information Center

Ahlers, Kaitlyn P.; Gabrielsen, Terisa P.; Lewis, Danielle; Brady, Anna M.; Litchford, April

2017-01-01

Core deficits in autism spectrum disorder (ASD) center around social communication and behavior. For those with ASD, these deficits complicate the task of learning how to cope with and manage complex social emotional issues. Although individuals with ASD may receive sufficient academic and basic behavioral support in school settings, supports for…

Effectiveness of Podcasts as Laboratory Instructional Support: Learner Perceptions of Machine Shop and Welding Students

ERIC Educational Resources Information Center

Lauritzen, Louis Dee

2014-01-01

Machine shop students face the daunting task of learning the operation of complex three-dimensional machine tools, and welding students must develop specific motor skills in addition to understanding the complexity of material types and characteristics. The use of consumer technology by the Millennial generation of vocational students, the…

Rules for Adaptive Learning and Assistance on the Shop Floor

ERIC Educational Resources Information Center

Ullrich, Carsten

2016-01-01

Today's shop floor, the area of a factory where operatives assemble products, is a complex and demanding work environment. The employed and produced technology becomes ever more complex, and employees are responsible for an increasing amount of tasks. As a consequence, the employee is under constant pressure to solve problems occurring on the shop…

Live Action Role Play and the Development of Teacher Competences: Evaluation of "Everyday Life in the Classroom"

ERIC Educational Resources Information Center

Imhof, Margarete; Starker, Ulrike; Spaude, Elena

2016-01-01

Building on Dörner's (1996) theory of complex problem-solving, a learning scenario for teacher students was created and tested. Classroom management is interpreted as a complex problem, which requires the integration of competing interests and tackling multiple, simultaneous tasks under time pressure and with limited information. In addition,…

Cooperative outcome interdependence, task reflexivity, and team effectiveness: a motivated information processing perspective.

PubMed

De Dreu, Carsten K W

2007-05-01

A motivated information processing perspective (C. K. W. De Dreu & P. J. D. Carnevale, 2003; see also V. B. Hinsz, R. S. Tindale, & D. A. Vollrath, 1997) was used to predict that perceived cooperative outcome interdependence interacts with team-level reflexivity to predict information sharing, learning, and team effectiveness. A cross-sectional field study involving management and cross-functional teams (N = 46) performing nonroutine, complex tasks corroborated predictions: The more team members perceived cooperative outcome interdependence, the better they shared information, the more they learned and the more effective they were, especially when task reflexivity was high. When task reflexivity was low, no significant relationship was found between cooperative outcome interdependence and team processes and performance. The author concludes that the motivated information processing perspective is valid outside the confines of the laboratory and can be extended toward teamwork in organizations. 2007 APA, all rights reserved

Gaze training enhances laparoscopic technical skill acquisition and multi-tasking performance: a randomized, controlled study.

PubMed

Wilson, Mark R; Vine, Samuel J; Bright, Elizabeth; Masters, Rich S W; Defriend, David; McGrath, John S

2011-12-01

The operating room environment is replete with stressors and distractions that increase the attention demands of what are already complex psychomotor procedures. Contemporary research in other fields (e.g., sport) has revealed that gaze training interventions may support the development of robust movement skills. This current study was designed to examine the utility of gaze training for technical laparoscopic skills and to test performance under multitasking conditions. Thirty medical trainees with no laparoscopic experience were divided randomly into one of three treatment groups: gaze trained (GAZE), movement trained (MOVE), and discovery learning/control (DISCOVERY). Participants were fitted with a Mobile Eye gaze registration system, which measures eye-line of gaze at 25 Hz. Training consisted of ten repetitions of the "eye-hand coordination" task from the LAP Mentor VR laparoscopic surgical simulator while receiving instruction and video feedback (specific to each treatment condition). After training, all participants completed a control test (designed to assess learning) and a multitasking transfer test, in which they completed the procedure while performing a concurrent tone counting task. Not only did the GAZE group learn more quickly than the MOVE and DISCOVERY groups (faster completion times in the control test), but the performance difference was even more pronounced when multitasking. Differences in gaze control (target locking fixations), rather than tool movement measures (tool path length), underpinned this performance advantage for GAZE training. These results suggest that although the GAZE intervention focused on training gaze behavior only, there were indirect benefits for movement behaviors and performance efficiency. Additionally, focusing on a single external target when learning, rather than on complex movement patterns, may have freed-up attentional resources that could be applied to concurrent cognitive tasks.

Classroom learning and achievement: how the complexity of classroom interaction impacts students' learning

NASA Astrophysics Data System (ADS)

Podschuweit, Sören; Bernholt, Sascha; Brückmann, Maja

2016-05-01

Background: Complexity models have provided a suitable framework in various domains to assess students' educational achievement. Complexity is often used as the analytical focus when regarding learning outcomes, i.e. when analyzing written tests or problem-centered interviews. Numerous studies reveal negative correlations between the complexity of a task and the probability of a student solving it. Purpose: Thus far, few detailed investigations explore the importance of complexity in actual classroom lessons. Moreover, the few efforts made so far revealed inconsistencies. Hence, the present study sheds light on the influence the complexity of students' and teachers' class contributions have on students' learning outcomes. Sample: Videos of 10 German 8th grade physics courses covering three consecutive lessons on two topics each (electricity, mechanics) have been analyzed. The sample includes 10 teachers and 290 students. Design and methods: Students' and teachers' verbal contributions were coded manual-based according to the level of complexity. Additionally, pre-post testing of knowledge in electricity and mechanics was applied to assess the students' learning gain. ANOVA analysis was used to characterize the influence of the complexity on the learning gain. Results: Results indicate that the mean level of complexity in classroom contributions explains a large portion of variance in post-test results on class level. Despite this overarching trend, taking classroom activities into account as well reveals even more fine-grained patterns, leading to more specific relations between the complexity in the classroom and students' achievement. Conclusions: In conclusion, we argue for more reflected teaching approaches intended to gradually increase class complexity to foster students' level of competency.

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

Emotional reactivity and cognitive performance in aversively motivated tasks: a comparison between four rat strains.

PubMed

van der Staay, F Josef; Schuurman, Teun; van Reenen, Cornelis G; Korte, S Mechiel

2009-12-15

Cognitive function might be affected by the subjects' emotional reactivity. We assessed whether behavior in different tests of emotional reactivity is correlated with performance in aversively motivated learning tasks, using four strains of rats generally considered to have a different emotional reactivity. The performance of male Brown Norway, Lewis, Fischer 344, and Wistar Kyoto rats in open field (OF), elevated plus-maze (EPM), and circular light-dark preference box (cLDB) tasks, which are believed to provide measures of emotional reactivity, was evaluated. Spatial working and reference memory were assessed in two aversively motivated learning and memory tasks: the standard and the "repeated acquisition" versions of the Morris water maze escape task, respectively. All rats were also tested in a passive avoidance task. At the end of the study, levels of serotonin (5-HT) and 5-hydroxyindoleacetic acid, and 5-HT turnover in the hippocampus and frontal cortex were determined. Strain differences showed a complex pattern across behavioral tests and serotonergic measures. Fischer 344 rats had the poorest performance in both versions of the Morris water escape task, whereas Brown Norway rats performed these tasks very well but the passive avoidance task poorly. Neither correlation analysis nor principal component analysis provided convincing support for the notion that OF, EPM, and cLDB tasks measure the same underlying trait. Our findings do not support the hypothesis that the level of emotional reactivity modulates cognitive performance in aversively motivated tasks. Concepts such as "emotional reactivity" and "learning and memory" cannot adequately be tapped with only one behavioral test. Our results emphasize the need for multiple testing.

More Time or Better Tools? A Large-Scale Retrospective Comparison of Pedagogical Approaches to Teach Programming

ERIC Educational Resources Information Center

Silva-Maceda, Gabriela; Arjona-Villicaña, P. David; Castillo-Barrera, F. Edgar

2016-01-01

Learning to program is a complex task, and the impact of different pedagogical approaches to teach this skill has been hard to measure. This study examined the performance data of seven cohorts of students (N = 1168) learning programming under three different pedagogical approaches. These pedagogical approaches varied either in the length of the…

Can Teacher Collaboration Overcome Barriers to Interdisciplinary Learning in a Disciplinary University? A Case Study Using Climate Change

ERIC Educational Resources Information Center

Pharo, E. J.; Davison, A.; Warr, K.; Nursey-Bray, M.; Beswick, K.; Wapstra, E.; Jones, C.

2012-01-01

A teacher network was formed at an Australian university in order to better promote interdisciplinary student learning on the complex social-environmental problem of climate change. Rather than leaving it to students to piece together disciplinary responses, eight teaching academics collaborated on the task of exposing students to different types…

Master's Thesis Supervision: Relations between Perceptions of the Supervisor-Student Relationship, Final Grade, Perceived Supervisor Contribution to Learning and Student Satisfaction

ERIC Educational Resources Information Center

de Kleijn, Renske A. M.; Mainhard, M. Tim; Meijer, Paulien C.; Pilot, Albert; Brekelmans, Mieke

2012-01-01

Master's thesis supervision is a complex task given the two-fold goal of the thesis (learning and assessment). An important aspect of supervision is the supervisor-student relationship. This quantitative study (N = 401) investigates how perceptions of the supervisor-student relationship are related to three dependent variables: final grade,…

Self-paced model learning for robust visual tracking

NASA Astrophysics Data System (ADS)

Huang, Wenhui; Gu, Jason; Ma, Xin; Li, Yibin

2017-01-01

In visual tracking, learning a robust and efficient appearance model is a challenging task. Model learning determines both the strategy and the frequency of model updating, which contains many details that could affect the tracking results. Self-paced learning (SPL) has recently been attracting considerable interest in the fields of machine learning and computer vision. SPL is inspired by the learning principle underlying the cognitive process of humans, whose learning process is generally from easier samples to more complex aspects of a task. We propose a tracking method that integrates the learning paradigm of SPL into visual tracking, so reliable samples can be automatically selected for model learning. In contrast to many existing model learning strategies in visual tracking, we discover the missing link between sample selection and model learning, which are combined into a single objective function in our approach. Sample weights and model parameters can be learned by minimizing this single objective function. Additionally, to solve the real-valued learning weight of samples, an error-tolerant self-paced function that considers the characteristics of visual tracking is proposed. We demonstrate the robustness and efficiency of our tracker on a recent tracking benchmark data set with 50 video sequences.

The Effect of Cerebellar Transcranial Direct Current Stimulation on A Throwing Task Depends on Individual Level of Task Performance.

PubMed

Mizuguchi, Nobuaki; Katayama, Takashi; Kanosue, Kazuyuki

2018-02-10

The effect of cerebellar transcranial direct current stimulation (tDCS) on motor performance remains controversial. Some studies suggest that the effect of tDCS depends upon task-difficulty and individual level of task performance. Here, we investigated whether the effect of cerebellar tDCS on the motor performance depends upon the individual's level of performance. Twenty-four naïve participants practiced dart throwing while receiving a 2-mA cerebellar tDCS for 20 min under three stimulus conditions (anodal-, cathodal-, and sham-tDCS) on separate days with a double-blind, counter-balanced cross-over design. Task performance was assessed by measuring the distance between the center of the bull's eye and the dart's position. Although task performance tended to improve throughout the practice under all stimulus conditions, improvement within a given day was not significant as compared to the first no-stimulus block. In addition, improvement did not differ among stimulation conditions. However, the magnitude of improvement was associated with an individual's level of task performance only under cathodal tDCS condition (p < 0.05). This resulted in a significant performance improvement only for the sub-group of participants with lower performance levels as compared to that with sham-tDCS (p < 0.05). These findings suggest that the facilitation effect of cerebellar cathodal tDCS on motor skill learning of complex whole-body movements depends on the level of an individual's task performance. Thus, cerebellar tDCS would facilitate learning of a complex motor skill task only in a subset of individuals. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Lessons Learned from Crowdsourcing Complex Engineering Tasks

PubMed Central

Kijewski-Correa, Tracy; Thain, Douglas; Kareem, Ahsan; Madey, Gregory

2015-01-01

Crowdsourcing Crowdsourcing is the practice of obtaining needed ideas, services, or content by requesting contributions from a large group of people. Amazon Mechanical Turk is a web marketplace for crowdsourcing microtasks, such as answering surveys and image tagging. We explored the limits of crowdsourcing by using Mechanical Turk for a more complicated task: analysis and creation of wind simulations. Harnessing Crowdworkers for Engineering Our investigation examined the feasibility of using crowdsourcing for complex, highly technical tasks. This was done to determine if the benefits of crowdsourcing could be harnessed to accurately and effectively contribute to solving complex real world engineering problems. Of course, untrained crowds cannot be used as a mere substitute for trained expertise. Rather, we sought to understand how crowd workers can be used as a large pool of labor for a preliminary analysis of complex data. Virtual Wind Tunnel We compared the skill of the anonymous crowd workers from Amazon Mechanical Turk with that of civil engineering graduate students, making a first pass at analyzing wind simulation data. For the first phase, we posted analysis questions to Amazon crowd workers and to two groups of civil engineering graduate students. A second phase of our experiment instructed crowd workers and students to create simulations on our Virtual Wind Tunnel website to solve a more complex task. Conclusions With a sufficiently comprehensive tutorial and compensation similar to typical crowd-sourcing wages, we were able to enlist crowd workers to effectively complete longer, more complex tasks with competence comparable to that of graduate students with more comprehensive, expert-level knowledge. Furthermore, more complex tasks require increased communication with the workers. As tasks become more complex, the employment relationship begins to become more akin to outsourcing than crowdsourcing. Through this investigation, we were able to stretch and explore the limits of crowdsourcing as a tool for solving complex problems. PMID:26383029

Compliant Task Execution and Learning for Safe Mixed-Initiative Human-Robot Operations

NASA Technical Reports Server (NTRS)

Dong, Shuonan; Conrad, Patrick R.; Shah, Julie A.; Williams, Brian C.; Mittman, David S.; Ingham, Michel D.; Verma, Vandana

2011-01-01

We introduce a novel task execution capability that enhances the ability of in-situ crew members to function independently from Earth by enabling safe and efficient interaction with automated systems. This task execution capability provides the ability to (1) map goal-directed commands from humans into safe, compliant, automated actions, (2) quickly and safely respond to human commands and actions during task execution, and (3) specify complex motions through teaching by demonstration. Our results are applicable to future surface robotic systems, and we have demonstrated these capabilities on JPL's All-Terrain Hex-Limbed Extra-Terrestrial Explorer (ATHLETE) robot.

Framework for robot skill learning using reinforcement learning

NASA Astrophysics Data System (ADS)

Wei, Yingzi; Zhao, Mingyang

2003-09-01

Robot acquiring skill is a process similar to human skill learning. Reinforcement learning (RL) is an on-line actor critic method for a robot to develop its skill. The reinforcement function has become the critical component for its effect of evaluating the action and guiding the learning process. We present an augmented reward function that provides a new way for RL controller to incorporate prior knowledge and experience into the RL controller. Also, the difference form of augmented reward function is considered carefully. The additional reward beyond conventional reward will provide more heuristic information for RL. In this paper, we present a strategy for the task of complex skill learning. Automatic robot shaping policy is to dissolve the complex skill into a hierarchical learning process. The new form of value function is introduced to attain smooth motion switching swiftly. We present a formal, but practical, framework for robot skill learning and also illustrate with an example the utility of method for learning skilled robot control on line.

The performance of ravens on simple discrimination tasks: a preliminary study

PubMed Central

Range, Friederike; Bugnyar, Thomas; Kotrschal, Kurt

2015-01-01

Recent studies suggest the existence of primate-like cognitive abilities in corvids. Although the learning abilities of corvids in comparison to other species have been investigated before, little is known on how corvids perform on simple discrimination tasks if tested in experimental settings comparable to those that have been used for studying complex cognitive abilities. In this study, we tested a captive group of 12 ravens (Corvus corax) on four discrimination problems and their reversals. In contrast to other studies investigating learning abilities, our ravens were not food deprived and participation in experiments was voluntary. This preliminary study showed that all ravens successfully solved feature and position discriminations and several of the ravens could solve new tasks in a few trials, making very few mistakes. PMID:25948877

Reversal learning as a measure of impulsive and compulsive behavior in addictions.

PubMed

Izquierdo, Alicia; Jentsch, J David

2012-01-01

Our ability to measure the cognitive components of complex decision-making across species has greatly facilitated our understanding of its neurobiological mechanisms. One task in particular, reversal learning, has proven valuable in assessing the inhibitory processes that are central to executive control. Reversal learning measures the ability to actively suppress reward-related responding and to disengage from ongoing behavior, phenomena that are biologically and descriptively related to impulsivity and compulsivity. Consequently, reversal learning could index vulnerability for disorders characterized by impulsivity such as proclivity for initial substance abuse as well as the compulsive aspects of dependence. Though we describe common variants and similar tasks, we pay particular attention to discrimination reversal learning, its supporting neural circuitry, neuropharmacology and genetic determinants. We also review the utility of this task in measuring impulsivity and compulsivity in addictions. We restrict our review to instrumental, reward-related reversal learning studies as they are most germane to addiction. The research reviewed here suggests that discrimination reversal learning may be used as a diagnostic tool for investigating the neural mechanisms that mediate impulsive and compulsive aspects of pathological reward-seeking and -taking behaviors. Two interrelated mechanisms are posited for the neuroadaptations in addiction that often translate to poor reversal learning: frontocorticostriatal circuitry dysregulation and poor dopamine (D2 receptor) modulation of this circuitry. These data suggest new approaches to targeting inhibitory control mechanisms in addictions.

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

PubMed

Dowsett, S M; Livesey, D J

2000-03-01

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

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

PubMed

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

2014-04-01

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

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

PubMed Central

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

2013-01-01

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

Reduction of nocturnal slow-wave activity affects daytime vigilance lapses and memory encoding but not reaction time or implicit learning.

PubMed

Van Der Werf, Ysbrand D; Altena, Ellemarije; Vis, José C; Koene, Teddy; Van Someren, Eus J W

2011-01-01

Total sleep deprivation in healthy subjects has a profound effect on the performance on tasks measuring sustained attention or vigilance. We here report how a selective disruption of deep sleep only, that is, selective slow-wave activity (SWA) reduction, affects the performance of healthy well-sleeping subjects on several tasks: a "simple" and a "complex" vigilance task, a declarative learning task, and an implicit learning task despite unchanged duration of sleep. We used automated electroencephalogram (EEG) dependent acoustic feedback aimed at selective interference with-and reduction of-SWA. In a within-subject repeated measures crossover design, performance on the tasks was assessed in 13 elderly adults without sleep complaints after either SWA-reduction or after normal sleep. The number of vigilance lapses increased as a result of SWA reduction, irrespective of the type of vigilance task. Recognition on the declarative memory task was also affected by SWA reduction, associated with a decreased activation of the right hippocampus on encoding (measured with fMRI) suggesting a weaker memory trace. SWA reduction, however, did not affect reaction time on either of the vigilance tasks or implicit memory task performance. These findings suggest a specific role of slow oscillations in the subsequent daytime ability to maintain sustained attention and to encode novel declarative information but not to maintain response speed or to build implicit memories. Of particular interest is that selective SWA reduction can mimic some of the effects of total sleep deprivation, while not affecting sleep duration. Copyright © 2011 Elsevier B.V. All rights reserved.

An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning

PubMed Central

Potjans, Wiebke; Diesmann, Markus; Morrison, Abigail

2011-01-01

An open problem in the field of computational neuroscience is how to link synaptic plasticity to system-level learning. A promising framework in this context is temporal-difference (TD) learning. Experimental evidence that supports the hypothesis that the mammalian brain performs temporal-difference learning includes the resemblance of the phasic activity of the midbrain dopaminergic neurons to the TD error and the discovery that cortico-striatal synaptic plasticity is modulated by dopamine. However, as the phasic dopaminergic signal does not reproduce all the properties of the theoretical TD error, it is unclear whether it is capable of driving behavior adaptation in complex tasks. Here, we present a spiking temporal-difference learning model based on the actor-critic architecture. The model dynamically generates a dopaminergic signal with realistic firing rates and exploits this signal to modulate the plasticity of synapses as a third factor. The predictions of our proposed plasticity dynamics are in good agreement with experimental results with respect to dopamine, pre- and post-synaptic activity. An analytical mapping from the parameters of our proposed plasticity dynamics to those of the classical discrete-time TD algorithm reveals that the biological constraints of the dopaminergic signal entail a modified TD algorithm with self-adapting learning parameters and an adapting offset. We show that the neuronal network is able to learn a task with sparse positive rewards as fast as the corresponding classical discrete-time TD algorithm. However, the performance of the neuronal network is impaired with respect to the traditional algorithm on a task with both positive and negative rewards and breaks down entirely on a task with purely negative rewards. Our model demonstrates that the asymmetry of a realistic dopaminergic signal enables TD learning when learning is driven by positive rewards but not when driven by negative rewards. PMID:21589888

Intelligent tutoring systems as tools for investigating individual differences in learning

NASA Technical Reports Server (NTRS)

Shute, Valerie J.

1987-01-01

The ultimate goal of this research is to build an improved model-based selection and classification system for the United States Air Force. Researchers are developing innovative approaches to ability testing. The Learning Abilities Measurement Program (LAMP) examines individual differences in learning abilities, seeking answers to the questions of why some people learn more and better than others and whether there are basic cognitive processes applicable across tasks and domains that are predictive of successful performance (or whether there are more complex problem solving behaviors involved).

Multiple systems for motor skill learning.

PubMed

Clark, Dav; Ivry, Richard B

2010-07-01

Motor learning is a ubiquitous feature of human competence. This review focuses on two particular classes of model tasks for studying skill acquisition. The serial reaction time (SRT) task is used to probe how people learn sequences of actions, while adaptation in the context of visuomotor or force field perturbations serves to illustrate how preexisting movements are recalibrated in novel environments. These tasks highlight important issues regarding the representational changes that occur during the course of motor learning. One important theme is that distinct mechanisms vary in their information processing costs during learning and performance. Fast learning processes may require few trials to produce large changes in performance but impose demands on cognitive resources. Slower processes are limited in their ability to integrate complex information but minimally demanding in terms of attention or processing resources. The representations derived from fast systems may be accessible to conscious processing and provide a relatively greater measure of flexibility, while the representations derived from slower systems are more inflexible and automatic in their behavior. In exploring these issues, we focus on how multiple neural systems may interact and compete during the acquisition and consolidation of new behaviors. Copyright © 2010 John Wiley & Sons, Ltd. This article is categorized under: Psychology > Motor Skill and Performance. Copyright © 2010 John Wiley & Sons, Ltd.

Teaching psychomotor skills in the twenty-first century: Revisiting and reviewing instructional approaches through the lens of contemporary literature.

PubMed

Nicholls, Delwyn; Sweet, Linda; Muller, Amanda; Hyett, Jon

2016-10-01

A diverse range of health professionals use psychomotor skills as part of their professional practice roles. Most health disciplines use large or complex psychomotor skills. These skills are first taught by the educator then acquired, performed, and lastly learned. Psychomotor skills may be taught using a variety of widely-accepted and published teaching models. The number of teaching steps used in these models varies from two to seven. However, the utility of these models to teach skill acquisition and skill retention are disputable when teaching complex skills, in contrast to simple skills. Contemporary motor learning and cognition literature frames instructional practices which may assist the teaching and learning of complex task-based skills. This paper reports 11 steps to be considered when teaching psychomotor skills.

A Study of Cognitive Load for Enhancing Student’s Quantitative Literacy in Inquiry Lab Learning

NASA Astrophysics Data System (ADS)

Nuraeni, E.; Rahman, T.; Alifiani, D. P.; Khoerunnisa, R. S.

2017-09-01

Students often find it difficult to appreciate the relevance of the role of quantitative analysis and concept attainment in the science class. This study measured student cognitive load during the inquiry lab of the respiratory system to improve quantitative literacy. Participants in this study were 40 11th graders from senior high school in Indonesia. After students learned, their feelings about the degree of mental effort that it took to complete the learning tasks were measured by 28 self-report on a 4-point Likert scale. The Task Complexity Worksheet were used to asses processing quantitative information and paper based test were applied to assess participants’ concept achievements. The results showed that inquiry instructional induced a relatively low mental effort, high processing information and high concept achievments.

Skill learning from kinesthetic feedback.

PubMed

Pinzon, David; Vega, Roberto; Sanchez, Yerly Paola; Zheng, Bin

2017-10-01

It is important for a surgeon to perform surgical tasks under appropriate guidance from visual and kinesthetic feedback. However, our knowledge on kinesthetic (muscle) memory and its role in learning motor skills remains elementary. To discover the effect of exclusive kinesthetic training on kinesthetic memory in both performance and learning. In Phase 1, a total of twenty participants duplicated five 2 dimensional movements of increasing complexity via passive kinesthetic guidance, without visual or auditory stimuli. Five participants were asked to repeat the task in the Phase 2 over a period of three weeks, for a total of nine sessions. Subjects accurately recalled movement direction using kinesthetic memory, but recalling movement length was less precise. Over the nine training sessions, error occurrence dropped after the sixth session. Muscle memory constructs the foundation for kinesthetic training. Knowledge gained helps surgeons learn skills from kinesthetic information in the condition where visual feedback is limited. Copyright © 2016 Elsevier Inc. All rights reserved.

Exploring the Neural Representation of Novel Words Learned through Enactment in a Word Recognition Task

PubMed Central

Macedonia, Manuela; Mueller, Karsten

2016-01-01

Vocabulary learning in a second language is enhanced if learners enrich the learning experience with self-performed iconic gestures. This learning strategy is called enactment. Here we explore how enacted words are functionally represented in the brain and which brain regions contribute to enhance retention. After an enactment training lasting 4 days, participants performed a word recognition task in the functional Magnetic Resonance Imaging (fMRI) scanner. Data analysis suggests the participation of different and partially intertwined networks that are engaged in higher cognitive processes, i.e., enhanced attention and word recognition. Also, an experience-related network seems to map word representation. Besides core language regions, this latter network includes sensory and motor cortices, the basal ganglia, and the cerebellum. On the basis of its complexity and the involvement of the motor system, this sensorimotor network might explain superior retention for enactment. PMID:27445918

Controlling uncertainty: a review of human behavior in complex dynamic environments.

PubMed

Osman, Magda

2010-01-01

Complex dynamic control (CDC) tasks are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research (economics, engineering, ergonomics, human-computer interaction, management, psychology), but they remain largely disconnected from each other. The objective of this article is to review theoretical developments and empirical work on CDC tasks, and to introduce a novel framework (monitoring and control framework) as a tool for integrating theory and findings. The main thesis of the monitoring and control framework is that CDC tasks are characteristically uncertain environments, and subjective judgments of uncertainty guide the way in which monitoring and control behaviors attempt to reduce it. The article concludes by discussing new insights into continuing debates and future directions for research on CDC tasks.

Storytelling with Chemistry and Related Hands-on Activities: Informal Learning Experiences to Prevent "Chemophobia" and Promote Young Children's Scientific Literacy

ERIC Educational Resources Information Center

Morais, Carla

2015-01-01

The dissemination of chemistry has been experienced as a difficult task, largely because of the negative image that the public has of this science, but also because of its inherent complexity and its own semantics and symbolism. Science centers, as informal learning environments, can contribute to a more effective dissemination of chemistry to an…

Multi-segmental movement patterns reflect juggling complexity and skill level.

PubMed

Zago, Matteo; Pacifici, Ilaria; Lovecchio, Nicola; Galli, Manuela; Federolf, Peter Andreas; Sforza, Chiarella

2017-08-01

The juggling action of six experts and six intermediates jugglers was recorded with a motion capture system and decomposed into its fundamental components through Principal Component Analysis. The aim was to quantify trends in movement dimensionality, multi-segmental patterns and rhythmicity as a function of proficiency level and task complexity. Dimensionality was quantified in terms of Residual Variance, while the Relative Amplitude was introduced to account for individual differences in movement components. We observed that: experience-related modifications in multi-segmental actions exist, such as the progressive reduction of error-correction movements, especially in complex task condition. The systematic identification of motor patterns sensitive to the acquisition of specific experience could accelerate the learning process. Copyright © 2017 Elsevier B.V. All rights reserved.

Emotional reactivity and cognitive performance in aversively motivated tasks: a comparison between four rat strains

PubMed Central

2009-01-01

Background Cognitive function might be affected by the subjects' emotional reactivity. We assessed whether behavior in different tests of emotional reactivity is correlated with performance in aversively motivated learning tasks, using four strains of rats generally considered to have a different emotional reactivity. Methods The performance of male Brown Norway, Lewis, Fischer 344, and Wistar Kyoto rats in open field (OF), elevated plus-maze (EPM), and circular light-dark preference box (cLDB) tasks, which are believed to provide measures of emotional reactivity, was evaluated. Spatial working and reference memory were assessed in two aversively motivated learning and memory tasks: the standard and the "repeated acquisition" versions of the Morris water maze escape task, respectively. All rats were also tested in a passive avoidance task. At the end of the study, levels of serotonin (5-HT) and 5-hydroxyindoleacetic acid, and 5-HT turnover in the hippocampus and frontal cortex were determined. Results Strain differences showed a complex pattern across behavioral tests and serotonergic measures. Fischer 344 rats had the poorest performance in both versions of the Morris water escape task, whereas Brown Norway rats performed these tasks very well but the passive avoidance task poorly. Neither correlation analysis nor principal component analysis provided convincing support for the notion that OF, EPM, and cLDB tasks measure the same underlying trait. Conclusions Our findings do not support the hypothesis that the level of emotional reactivity modulates cognitive performance in aversively motivated tasks. Concepts such as "emotional reactivity" and "learning and memory" cannot adequately be tapped with only one behavioral test. Our results emphasize the need for multiple testing. PMID:20003525

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-10-11

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

A preliminary study of the effects of individual response to challenge tests and stress induced by humans on learning performance of weaned piglets (Sus scrofa).

PubMed

Brajon, Sophie; Laforest, Jean-Paul; Schmitt, Océane; Devillers, Nicolas

2016-08-01

This study investigated whether individual behavioural characteristics of piglets and stress induced by experience with humans can influence learning performance. After weaning, piglets received a chronic experience with humans to modulate their emotional state: rough (ROU), gentle (GEN), or minimal (MIN) experience. Simultaneously, they were trained on a discrimination task. Afterward, their behaviour during challenge tests was assessed. The first learning step of the task involved associating a positive sound cue with a response (approach a trough) and success of piglets depended mostly on motivation to seek for reward. Although the experience with humans did not have direct effect, the degree of fear of handler, measured based on their reactivity to a human approach test, was related to motivation to seek rewards and learning speed of this first step in stressed ROU piglets, but not in MIN and GEN piglets. In contrast, the second learning step was more cognitively challenging, since it involved discrimination learning, including negative cues during which piglets had to learn to avoid the trough. Locomotion activity, measured during an open-field test, was associated with performance of the discrimination learning. To conclude, fearfulness towards humans and locomotion activity are linked with learning performance in relation to task complexity, highlighting the necessity to take into account these factors in animal research and management. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Feature reliability determines specificity and transfer of perceptual learning in orientation search.

PubMed

Yashar, Amit; Denison, Rachel N

2017-12-01

Training can modify the visual system to produce a substantial improvement on perceptual tasks and therefore has applications for treating visual deficits. Visual perceptual learning (VPL) is often specific to the trained feature, which gives insight into processes underlying brain plasticity, but limits VPL's effectiveness in rehabilitation. Under what circumstances VPL transfers to untrained stimuli is poorly understood. Here we report a qualitatively new phenomenon: intrinsic variation in the representation of features determines the transfer of VPL. Orientations around cardinal are represented more reliably than orientations around oblique in V1, which has been linked to behavioral consequences such as visual search asymmetries. We studied VPL for visual search of near-cardinal or oblique targets among distractors of the other orientation while controlling for other display and task attributes, including task precision, task difficulty, and stimulus exposure. Learning was the same in all training conditions; however, transfer depended on the orientation of the target, with full transfer of learning from near-cardinal to oblique targets but not the reverse. To evaluate the idea that representational reliability was the key difference between the orientations in determining VPL transfer, we created a model that combined orientation-dependent reliability, improvement of reliability with learning, and an optimal search strategy. Modeling suggested that not only search asymmetries but also the asymmetric transfer of VPL depended on preexisting differences between the reliability of near-cardinal and oblique representations. Transfer asymmetries in model behavior also depended on having different learning rates for targets and distractors, such that greater learning for low-reliability distractors facilitated transfer. These findings suggest that training on sensory features with intrinsically low reliability may maximize the generalizability of learning in complex visual environments.

Lexical orthography acquisition: Is handwriting better than spelling aloud?

PubMed Central

Bosse, Marie-Line; Chaves, Nathalie; Valdois, Sylviane

2014-01-01

Lexical orthography acquisition is currently described as the building of links between the visual forms and the auditory forms of whole words. However, a growing body of data suggests that a motor component could further be involved in orthographic acquisition. A few studies support the idea that reading plus handwriting is a better lexical orthographic learning situation than reading alone. However, these studies did not explore which of the cognitive processes involved in handwriting enhanced lexical orthographic acquisition. Some findings suggest that the specific movements memorized when learning to write may participate in the establishment of orthographic representations in memory. The aim of the present study was to assess this hypothesis using handwriting and spelling aloud as two learning conditions. In two experiments, fifth graders were asked to read complex pseudo-words embedded in short sentences. Immediately after reading, participants had to recall the pseudo-words' spellings either by spelling them aloud or by handwriting them down. One week later, orthographic acquisition was tested using two post-tests: a pseudo-word production task (spelling by hand in Experiment 1 or spelling aloud in Experiment 2) and a pseudo-word recognition task. Results showed no significant difference in pseudo-word recognition between the two learning conditions. In the pseudo-word production task, orthography learning improved when the learning and post-test conditions were similar, thus showing a massive encoding-retrieval match effect in the two experiments. However, a mixed model analysis of the pseudo-word production results revealed a significant learning condition effect which remained after control of the encoding-retrieval match effect. This later finding suggests that orthography learning is more efficient when mediated by handwriting than by spelling aloud, whatever the post-test production task. PMID:24575058

Lexical orthography acquisition: Is handwriting better than spelling aloud?

PubMed

Bosse, Marie-Line; Chaves, Nathalie; Valdois, Sylviane

2014-01-01

Lexical orthography acquisition is currently described as the building of links between the visual forms and the auditory forms of whole words. However, a growing body of data suggests that a motor component could further be involved in orthographic acquisition. A few studies support the idea that reading plus handwriting is a better lexical orthographic learning situation than reading alone. However, these studies did not explore which of the cognitive processes involved in handwriting enhanced lexical orthographic acquisition. Some findings suggest that the specific movements memorized when learning to write may participate in the establishment of orthographic representations in memory. The aim of the present study was to assess this hypothesis using handwriting and spelling aloud as two learning conditions. In two experiments, fifth graders were asked to read complex pseudo-words embedded in short sentences. Immediately after reading, participants had to recall the pseudo-words' spellings either by spelling them aloud or by handwriting them down. One week later, orthographic acquisition was tested using two post-tests: a pseudo-word production task (spelling by hand in Experiment 1 or spelling aloud in Experiment 2) and a pseudo-word recognition task. Results showed no significant difference in pseudo-word recognition between the two learning conditions. In the pseudo-word production task, orthography learning improved when the learning and post-test conditions were similar, thus showing a massive encoding-retrieval match effect in the two experiments. However, a mixed model analysis of the pseudo-word production results revealed a significant learning condition effect which remained after control of the encoding-retrieval match effect. This later finding suggests that orthography learning is more efficient when mediated by handwriting than by spelling aloud, whatever the post-test production task.

Conditional High-Order Boltzmann Machines for Supervised Relation Learning.

PubMed

Huang, Yan; Wang, Wei; Wang, Liang; Tan, Tieniu

2017-09-01

Relation learning is a fundamental problem in many vision tasks. Recently, high-order Boltzmann machine and its variants have shown their great potentials in learning various types of data relation in a range of tasks. But most of these models are learned in an unsupervised way, i.e., without using relation class labels, which are not very discriminative for some challenging tasks, e.g., face verification. In this paper, with the goal to perform supervised relation learning, we introduce relation class labels into conventional high-order multiplicative interactions with pairwise input samples, and propose a conditional high-order Boltzmann Machine (CHBM), which can learn to classify the data relation in a binary classification way. To be able to deal with more complex data relation, we develop two improved variants of CHBM: 1) latent CHBM, which jointly performs relation feature learning and classification, by using a set of latent variables to block the pathway from pairwise input samples to output relation labels and 2) gated CHBM, which untangles factors of variation in data relation, by exploiting a set of latent variables to multiplicatively gate the classification of CHBM. To reduce the large number of model parameters generated by the multiplicative interactions, we approximately factorize high-order parameter tensors into multiple matrices. Then, we develop efficient supervised learning algorithms, by first pretraining the models using joint likelihood to provide good parameter initialization, and then finetuning them using conditional likelihood to enhance the discriminant ability. We apply the proposed models to a series of tasks including invariant recognition, face verification, and action similarity labeling. Experimental results demonstrate that by exploiting supervised relation labels, our models can greatly improve the performance.

Feature reliability determines specificity and transfer of perceptual learning in orientation search

PubMed Central

2017-01-01

Training can modify the visual system to produce a substantial improvement on perceptual tasks and therefore has applications for treating visual deficits. Visual perceptual learning (VPL) is often specific to the trained feature, which gives insight into processes underlying brain plasticity, but limits VPL’s effectiveness in rehabilitation. Under what circumstances VPL transfers to untrained stimuli is poorly understood. Here we report a qualitatively new phenomenon: intrinsic variation in the representation of features determines the transfer of VPL. Orientations around cardinal are represented more reliably than orientations around oblique in V1, which has been linked to behavioral consequences such as visual search asymmetries. We studied VPL for visual search of near-cardinal or oblique targets among distractors of the other orientation while controlling for other display and task attributes, including task precision, task difficulty, and stimulus exposure. Learning was the same in all training conditions; however, transfer depended on the orientation of the target, with full transfer of learning from near-cardinal to oblique targets but not the reverse. To evaluate the idea that representational reliability was the key difference between the orientations in determining VPL transfer, we created a model that combined orientation-dependent reliability, improvement of reliability with learning, and an optimal search strategy. Modeling suggested that not only search asymmetries but also the asymmetric transfer of VPL depended on preexisting differences between the reliability of near-cardinal and oblique representations. Transfer asymmetries in model behavior also depended on having different learning rates for targets and distractors, such that greater learning for low-reliability distractors facilitated transfer. These findings suggest that training on sensory features with intrinsically low reliability may maximize the generalizability of learning in complex visual environments. PMID:29240813

Pigeons and humans use action and pose information to categorize complex human behaviors.

PubMed

Qadri, Muhammad A J; Cook, Robert G

2017-02-01

The biological mechanisms used to categorize and recognize behaviors are poorly understood in both human and non-human animals. Using animated digital models, we have recently shown that pigeons can categorize different locomotive animal gaits and types of complex human behaviors. In the current experiments, pigeons (go/no-go task) and humans (choice task) both learned to conditionally categorize two categories of human behaviors that did not repeat and were comprised of the coordinated motions of multiple limbs. These "martial arts" and "Indian dance" action sequences were depicted by a digital human model. Depending upon whether the model was in motion or not, each species was required to engage in different and opposing responses to the two behavioral categories. Both species learned to conditionally and correctly act on this dynamic and static behavioral information, indicating that both species use a combination of static pose cues that are available from stimulus onset in addition to less rapidly available action information in order to successfully discriminate between the behaviors. Human participants additionally demonstrated a bias towards the dynamic information in the display when re-learning the task. Theories that rely on generalized, non-specific visual mechanisms involving channels for motion and static cues offer a parsimonious account of how humans and pigeons recognize and categorize behaviors within and across species. Copyright © 2016 Elsevier Ltd. All rights reserved.

Preliminary Work for Examining the Scalability of Reinforcement Learning

NASA Technical Reports Server (NTRS)

Clouse, Jeff

1998-01-01

Researchers began studying automated agents that learn to perform multiple-step tasks early in the history of artificial intelligence (Samuel, 1963; Samuel, 1967; Waterman, 1970; Fikes, Hart & Nilsonn, 1972). Multiple-step tasks are tasks that can only be solved via a sequence of decisions, such as control problems, robotics problems, classic problem-solving, and game-playing. The objective of agents attempting to learn such tasks is to use the resources they have available in order to become more proficient at the tasks. In particular, each agent attempts to develop a good policy, a mapping from states to actions, that allows it to select actions that optimize a measure of its performance on the task; for example, reducing the number of steps necessary to complete the task successfully. Our study focuses on reinforcement learning, a set of learning techniques where the learner performs trial-and-error experiments in the task and adapts its policy based on the outcome of those experiments. Much of the work in reinforcement learning has focused on a particular, simple representation, where every problem state is represented explicitly in a table, and associated with each state are the actions that can be chosen in that state. A major advantage of this table lookup representation is that one can prove that certain reinforcement learning techniques will develop an optimal policy for the current task. The drawback is that the representation limits the application of reinforcement learning to multiple-step tasks with relatively small state-spaces. There has been a little theoretical work that proves that convergence to optimal solutions can be obtained when using generalization structures, but the structures are quite simple. The theory says little about complex structures, such as multi-layer, feedforward artificial neural networks (Rumelhart & McClelland, 1986), but empirical results indicate that the use of reinforcement learning with such structures is promising. These empirical results make no theoretical claims, nor compare the policies produced to optimal policies. A goal of our work is to be able to make the comparison between an optimal policy and one stored in an artificial neural network. A difficulty of performing such a study is finding a multiple-step task that is small enough that one can find an optimal policy using table lookup, yet large enough that, for practical purposes, an artificial neural network is really required. We have identified a limited form of the game OTHELLO as satisfying these requirements. The work we report here is in the very preliminary stages of research, but this paper provides background for the problem being studied and a description of our initial approach to examining the problem. In the remainder of this paper, we first describe reinforcement learning in more detail. Next, we present the game OTHELLO. Finally we argue that a restricted form of the game meets the requirements of our study, and describe our preliminary approach to finding an optimal solution to the problem.

Complex-learning Induced Modifications in Synaptic Inhibition: Mechanisms and Functional Significance.

PubMed

Reuveni, Iris; Lin, Longnian; Barkai, Edi

2018-06-15

Following training in a difficult olfactory-discrimination (OD) task rats acquire the capability to perform the task easily, with little effort. This new acquired skill, of 'learning how to learn' is termed 'rule learning'. At the single-cell level, rule learning is manifested in long-term enhancement of intrinsic neuronal excitability of piriform cortex (PC) pyramidal neurons, and in excitatory synaptic connections between these neurons to maintain cortical stability, such long-lasting increase in excitability must be accompanied by paralleled increase in inhibitory processes that would prevent hyper-excitable activation. In this review we describe the cellular and molecular mechanisms underlying complex-learning-induced long-lasting modifications in GABA A -receptors and GABA B -receptor-mediated synaptic inhibition. Subsequently we discuss how such modifications support the induction and preservation of long-term memories in the in the mammalian brain. Based on experimental results, computational analysis and modeling, we propose that rule learning is maintained by doubling the strength of synaptic inputs, excitatory as well as inhibitory, in a sub-group of neurons. This enhanced synaptic transmission, which occurs in all (or almost all) synaptic inputs onto these neurons, activates specific stored memories. At the molecular level, such rule-learning-relevant synaptic strengthening is mediated by doubling the conductance of synaptic channels, but not their numbers. This post synaptic process is controlled by a whole-cell mechanism via particular second messenger systems. This whole-cell mechanism enables memory amplification when required and memory extinction when not relevant. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Collaborative training with a more experienced partner: remediating low pretraining self-efficacy in complex skill acquisition.

PubMed

Day, Eric Anthony; Boatman, Paul R; Kowollik, Vanessa; Espejo, Jazmine; McEntire, Lauren E; Sherwin, Rachel E

2007-12-01

This study examined the effectiveness of collaborative training for individuals with low pretraining self-efficacy versus individuals with high pretraining self-efficacy regarding the acquisition of a complex skill that involved strong cognitive and psychomotor demands. Despite support for collaborative learning from the educational literature and the similarities between collaborative learning and interventions designed to remediate low self-efficacy, no research has addressed how self-efficacy and collaborative learning interact in contexts concerning complex skills and human-machine interactions. One hundred fifty-five young male adults trained either individually or collaboratively with a more experienced partner on a complex computer task that simulated the demands of a dynamic aviation environment. Participants also completed a task-specific measure of self-efficacy before, during, and after training. Collaborative training enhanced skill acquisition significantly more for individuals with low pretraining self-efficacy than for individuals with high pretraining self-efficacy. However, collaborative training did not bring the skill acquisition levels of those persons with low pretraining self-efficacy to the levels found for persons with high pretraining self-efficacy. Moreover, tests of mediation suggested that collaborative training may have enhanced appropriate skill development strategies without actually raising self-efficacy. Although collaborative training can facilitate the skill acquisition process for trainees with low self-efficacy, future research is needed that examines how the negative effects of low pretraining self-efficacy on complex skill acquisition can be more fully remediated. The differential effects of collaborative training as a function of self-efficacy highlight the importance of person analysis and tailoring training to meet differing trainee needs.

Machine learning in heart failure: ready for prime time.

PubMed

Awan, Saqib Ejaz; Sohel, Ferdous; Sanfilippo, Frank Mario; Bennamoun, Mohammed; Dwivedi, Girish

2018-03-01

The aim of this review is to present an up-to-date overview of the application of machine learning methods in heart failure including diagnosis, classification, readmissions and medication adherence. Recent studies have shown that the application of machine learning techniques may have the potential to improve heart failure outcomes and management, including cost savings by improving existing diagnostic and treatment support systems. Recently developed deep learning methods are expected to yield even better performance than traditional machine learning techniques in performing complex tasks by learning the intricate patterns hidden in big medical data. The review summarizes the recent developments in the application of machine and deep learning methods in heart failure management.

A Macro-Level Analysis of SRL Processes and Their Relations to the Acquisition of a Sophisticated Mental Model of a Complex System

ERIC Educational Resources Information Center

Greene, Jeffrey Alan; Azevedo, Roger

2009-01-01

In this study, we used think-aloud verbal protocols to examine how various macro-level processes of self-regulated learning (SRL; e.g., planning, monitoring, strategy use, handling of task difficulty and demands) were associated with the acquisition of a sophisticated mental model of a complex biological system. Numerous studies examine how…

Abrupt strategy change underlies gradual performance change: Bayesian hierarchical models of component and aggregate strategy use.

PubMed

Wynton, Sarah K A; Anglim, Jeromy

2017-10-01

While researchers have often sought to understand the learning curve in terms of multiple component processes, few studies have measured and mathematically modeled these processes on a complex task. In particular, there remains a need to reconcile how abrupt changes in strategy use can co-occur with gradual changes in task completion time. Thus, the current study aimed to assess the degree to which strategy change was abrupt or gradual, and whether strategy aggregation could partially explain gradual performance change. It also aimed to show how Bayesian methods could be used to model the effect of practice on strategy use. To achieve these aims, 162 participants completed 15 blocks of practice on a complex computer-based task-the Wynton-Anglim booking (WAB) task. The task allowed for multiple component strategies (i.e., memory retrieval, information reduction, and insight) that could also be aggregated to a global measure of strategy use. Bayesian hierarchical models were used to compare abrupt and gradual functions of component and aggregate strategy use. Task completion time was well-modeled by a power function, and global strategy use explained substantial variance in performance. Change in component strategy use tended to be abrupt, whereas change in global strategy use was gradual and well-modeled by a power function. Thus, differential timing of component strategy shifts leads to gradual changes in overall strategy efficiency, and this provides one reason for why smooth learning curves can co-occur with abrupt changes in strategy use. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Contextual Interference in Complex Bimanual Skill Learning Leads to Better Skill Persistence

PubMed Central

Pauwels, Lisa; Swinnen, Stephan P.; Beets, Iseult A. M.

2014-01-01

The contextual interference (CI) effect is a robust phenomenon in the (motor) skill learning literature. However, CI has yielded mixed results in complex task learning. The current study addressed whether the CI effect is generalizable to bimanual skill learning, with a focus on the temporal evolution of memory processes. In contrast to previous studies, an extensive training schedule, distributed across multiple days of practice, was provided. Participants practiced three frequency ratios across three practice days following either a blocked or random practice schedule. During the acquisition phase, better overall performance for the blocked practice group was observed, but this difference diminished as practice progressed. At immediate and delayed retention, the random practice group outperformed the blocked practice group, except for the most difficult frequency ratio. Our main finding is that the random practice group showed superior performance persistence over a one week time interval in all three frequency ratios compared to the blocked practice group. This study contributes to our understanding of learning, consolidation and memory of complex motor skills, which helps optimizing training protocols in future studies and rehabilitation settings. PMID:24960171

The effects of cholesterol on learning and memory.

PubMed

Schreurs, Bernard G

2010-07-01

Cholesterol is vital to normal brain function including learning and memory but that involvement is as complex as the synthesis, metabolism and excretion of cholesterol itself. Dietary cholesterol influences learning tasks from water maze to fear conditioning even though cholesterol does not cross the blood brain barrier. Excess cholesterol has many consequences including peripheral pathology that can signal brain via cholesterol metabolites, pro-inflammatory mediators and antioxidant processes. Manipulations of cholesterol within the central nervous system through genetic, pharmacological, or metabolic means circumvent the blood brain barrier and affect learning and memory but often in animals already otherwise compromised. The human literature is no less complex. Cholesterol reduction using statins improves memory in some cases but not others. There is also controversy over statin use to alleviate memory problems in Alzheimer's disease. Correlations of cholesterol and cognitive function are mixed and association studies find some genetic polymorphisms are related to cognitive function but others are not. In sum, the field is in flux with a number of seemingly contradictory results and many complexities. Nevertheless, understanding cholesterol effects on learning and memory is too important to ignore.

The Effect of Variability of Practice at Execution Redundancy Level in Skilled and Novice Basketball Players.

PubMed

Taheri, Hamidreza; Fazeli, Davoud; Poureghbali, Sogand

2017-04-01

We investigated the effect of practice variability through execution redundancy in skilled and novice basketball players on free throw skills. Twelve skilled basketball players and 12 novices (mean age = 25.4 years, SD = 4.3) were divided into four groups (skilled constant, skilled variable, novice constant, and novice variable). After a pretest, participants practiced free throw action. The variable groups threw the ball over an obstacle of varying heights on each trial in random order, whereas the obstacle's height was fixed for the constant groups. After 7 and 14 consecutive days of practice, participants performed two posttests with constant and variable distances from the basket. The results showed that practicing different solutions of a task did not affect the performance of skilled players but had an immediate negative effect on the performance of novice players. Learning a complex task is the result of learning task-related parameters, and practice variability can create a mismatch between task difficulty and new learner skill levels.

Psychological distance reduces literal imitation: Evidence from an imitation-learning paradigm.

PubMed

Hansen, Jochim; Alves, Hans; Trope, Yaacov

2016-03-01

The present experiments tested the hypothesis that observers engage in more literal imitation of a model when the model is psychologically near to (vs. distant from) the observer. Participants learned to fold a dog out of towels by watching a model performing this task. Temporal (Experiment 1) and spatial (Experiment 2) distance from the model were manipulated. As predicted, participants copied more of the model's specific movements when the model was near (vs. distant). Experiment 3 replicated this finding with a paper-folding task, suggesting that distance from a model also affects imitation of less complex tasks. Perceived task difficulty, motivation, and the quality of the end product were not affected by distance. We interpret the findings as reflecting different levels of construal of the model's performance: When the model is psychologically distant, social learners focus more on the model's goal and devise their own means for achieving the goal, and as a result show less literal imitation of the model. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Motor learning from virtual reality to natural environments in individuals with Duchenne muscular dystrophy.

PubMed

Quadrado, Virgínia Helena; Silva, Talita Dias da; Favero, Francis Meire; Tonks, James; Massetti, Thais; Monteiro, Carlos Bandeira de Mello

2017-11-10

To examine whether performance improvements in the virtual environment generalize to the natural environment. we had 64 individuals, 32 of which were individuals with DMD and 32 were typically developing individuals. The groups practiced two coincidence timing tasks. In the more tangible button-press task, the individuals were required to 'intercept' a falling virtual object at the moment it reached the interception point by pressing a key on the computer. In the more abstract task, they were instructed to 'intercept' the virtual object by making a hand movement in a virtual environment using a webcam. For individuals with DMD, conducting a coincidence timing task in a virtual environment facilitated transfer to the real environment. However, we emphasize that a task practiced in a virtual environment should have higher rates of difficulties than a task practiced in a real environment. IMPLICATIONS FOR REHABILITATION Virtual environments can be used to promote improved performance in ?real-world? environments. Virtual environments offer the opportunity to create paradigms similar ?real-life? tasks, however task complexity and difficulty levels can be manipulated, graded and enhanced to increase likelihood of success in transfer of learning and performance. Individuals with DMD, in particular, showed immediate performance benefits after using virtual reality.

Short-term effects of using verbal instructions and demonstration at the beginning of learning a complex skill in figure skating.

PubMed

Haguenauer, Marianne; Fargier, Patrick; Legreneur, Pierre; Dufour, Anne-Béatrice; Cogerino, Geneviève; Begon, Mickaël; Monteil, Karine M

2005-02-01

This study examined whether providing verbal instructions plus demonstration and task repetition facilitates the early acquisition of a sport skill for which learners had a prior knowledge of the individual motor components. After one demonstration of the task by an expert, 18 novice skaters practiced a figure skating jump during a 15-min. period. Subjects were randomly assigned to one of 3 groups: a group provided with a verbal instruction that specified the subgoals of the task (Subgoals group), a group provided with a verbal instruction that used a metaphor (Metaphoric group), and a group not receiving any specific instruction during training (Control group). Subjects were filmed prior to and immediately following the practice session. Analysis indicated that the modifications of performance were related to the demonstration and the subsequent task repetitions only. Providing additional verbal instructions generated no effect. Therefore, guiding the learner toward a solution to the task problem by means of verbal instruction seems to be ineffective if done too early in the course of learning.

Place versus response learning in fish: a comparison between species.

PubMed

McAroe, Claire L; Craig, Cathy M; Holland, Richard A

2016-01-01

Place learning is thought to be an adaptive and flexible facet of navigation. Due to the flexibility of this learning, it is thought to be more complex than the simpler strategies such as learning a particular route or navigating through the use of cues. Place learning is crucial in a familiar environment as it allows an individual to successfully navigate to the same endpoint, regardless of where in the environment the journey begins. Much of the research to date focusing on different strategies employed for navigation has used human subjects or other mammals such as rodents. In this series of experiments, the spatial memory of four different species of fish (goldfish, killifish, zebrafish and Siamese fighting fish) was analysed using a plus maze set-up. Results suggest that three of the species showed a significant preference for the adoption of a place strategy during this task, whereas zebrafish showed no significant preference. Furthermore, zebrafish took significantly longer to learn the task than the other species. Finally, results suggest that zebrafish took the least amount of time (seconds) to complete trials both during training and probe.

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning

PubMed Central

Raza, Meher; Ivry, Richard B.

2016-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. NEW & NOTEWORTHY We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the alternating serial reaction time task, exhibited good test-retest reliability in measures of learning and performance. However, the learning measures did not correlate between the two tasks, arguing against a shared process for implicit motor learning. PMID:27832611

When money is not enough: awareness, success, and variability in motor learning.

PubMed

Manley, Harry; Dayan, Peter; Diedrichsen, Jörn

2014-01-01

When performing a skill such as throwing a dart, many different combinations of joint motions suffice to hit the target. The motor system adapts rapidly to reduce bias in the desired outcome (i.e., the first-order moment of the error); however, the essence of skill is to produce movements with less variability (i.e., to reduce the second-order moment). It is easy to see how feedback about success or failure could sculpt performance to achieve this aim. However, it is unclear whether the dimensions responsible for success or failure need to be known explicitly by the subjects, or whether learning can proceed without explicit awareness of the movement parameters that need to change. Here, we designed a redundant, two-dimensional reaching task in which we could selectively manipulate task success and the variability of action outcomes, whilst also manipulating awareness of the dimension along which performance could be improved. Variability was manipulated either by amplifying natural errors, leaving the correlation between the executed movement and the visual feedback intact, or by adding extrinsic noise, decorrelating movement and feedback. We found that explicit, binary, feedback about success or failure was only sufficient for learning when participants were aware of the dimension along which motor behavior had to change. Without such awareness, learning was only present when extrinsic noise was added to the feedback, but not when task success or variability was manipulated in isolation; learning was also much slower. Our results highlight the importance of conscious awareness of the relevant dimension during motor learning, and suggest that higher-order moments of outcome signals are likely to play a significant role in skill learning in complex tasks.

Enhancement of motor learning by focal intermittent theta burst stimulation (iTBS) of either the primary motor (M1) or somatosensory area (S1) in healthy human subjects.

PubMed

Platz, Thomas; Adler-Wiebe, Marija; Roschka, Sybille; Lotze, Martin

2018-01-01

Motor rehabilitation after brain damage relies on motor re-learning as induced by specific training. Non-invasive brain stimulation (NIBS) can alter cortical excitability and thereby has a potential to enhance subsequent training-induced learning. Knowledge about any priming effects of NIBS on motor learning in healthy subjects can help to design targeted therapeutic applications in brain-damaged subjects. To examine whether complex motor learning in healthy subjects can be enhanced by intermittent theta burst stimulation (iTBS) to primary motor or sensory cortical areas. Eighteen young healthy subjects trained eight different arm motor tasks (arm ability training, AAT) once a day for 5 days using their left non-dominant arm. Except for day 1 (baseline), training was performed after applying an excitatory form of repetitive transcranial magnetic stimulation (iTBS) to either (I) right M1 or (II) S1, or (III) sham stimulation to the right M1. Subjects were randomly assigned to conditions I, II, or III. A principal component analysis of the motor behaviour data suggested eight independent motor abilities corresponding to the 8 trained tasks. AAT induced substantial motor learning across abilities with generalisation to a non-trained test of finger dexterity (Nine-Hole-Peg-Test, NHPT). Participants receiving iTBS (to either M1 or S1) showed better performance with the AAT tasks over the period of training compared to sham stimulation as well as a bigger improvement with the generalisation task (NHPT) for the trained left hand after training completion. Priming with an excitatory repetitive transcranial magnetic stimulation as iTBS of either M1 or S1 can enhance motor learning across different sensorimotor abilities.

Post learning sleep improves cognitive-emotional decision-making: evidence for a 'deck B sleep effect' in the Iowa Gambling Task.

PubMed

Seeley, Corrine J; Beninger, Richard J; Smith, Carlyle T

2014-01-01

The Iowa Gambling Task (IGT) is widely used to assess real life decision-making impairment in a wide variety of clinical populations. Our study evaluated how IGT learning occurs across two sessions, and whether a period of intervening sleep between sessions can enhance learning. Furthermore, we investigate whether pre-sleep learning is necessary for this improvement. A 200-trial version of the IGT was administered at two sessions separated by wake, sleep or sleep and wake (time-of-day control). Participants were categorized as learners and non-learners based on initial performance in session one. In session one, participants initially preferred the high-frequency reward decks B and D, however, a subset of learners decreased choice from negative expected value 'bad' deck B and increased choices towards with a positive expected value 'good' decks (decks C and D). The learners who had a period of sleep (sleep and sleep/wake control conditions) between sessions showed significantly larger reduction in choices from deck B and increase in choices from good decks compared to learners that had intervening wake. Our results are the first to show that post-learning sleep can improve performance on a complex decision-making task such as the IGT. These results provide new insights into IGT learning and have important implications for understanding the neural mechanisms of "sleeping on" a decision.

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

PubMed

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

2005-01-01

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

Prenatal complex rhythmic music sound stimulation facilitates postnatal spatial learning but transiently impairs memory in the domestic chick.

PubMed

Kauser, H; Roy, S; Pal, A; Sreenivas, V; Mathur, R; Wadhwa, S; Jain, S

2011-01-01

Early experience has a profound influence on brain development, and the modulation of prenatal perceptual learning by external environmental stimuli has been shown in birds, rodents and mammals. In the present study, the effect of prenatal complex rhythmic music sound stimulation on postnatal spatial learning, memory and isolation stress was observed. Auditory stimulation with either music or species-specific sounds or no stimulation (control) was provided to separate sets of fertilized eggs from day 10 of incubation. Following hatching, the chicks at age 24, 72 and 120 h were tested on a T-maze for spatial learning and the memory of the learnt task was assessed 24 h after training. In the posthatch chicks at all ages, the plasma corticosterone levels were estimated following 10 min of isolation. The chicks of all ages in the three groups took less (p < 0.001) time to navigate the maze over the three trials thereby showing an improvement with training. In both sound-stimulated groups, the total time taken to reach the target decreased significantly (p < 0.01) in comparison to the unstimulated control group, indicating the facilitation of spatial learning. However, this decline was more at 24 h than at later posthatch ages. When tested for memory after 24 h of training, only the music-stimulated chicks at posthatch age 24 h took a significantly longer (p < 0.001) time to traverse the maze, suggesting a temporary impairment in their retention of the learnt task. In both sound-stimulated groups at 24 h, the plasma corticosterone levels were significantly decreased (p < 0.001) and increased thereafter at 72 h (p < 0.001) and 120 h which may contribute to the differential response in spatial learning. Thus, prenatal auditory stimulation with either species-specific or complex rhythmic music sounds facilitates spatial learning, though the music stimulation transiently impairs postnatal memory. 2011 S. Karger AG, Basel.

Immunology for physicists

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

Perelson, A.S.; Weisbuch, G.

1997-10-01

The immune system is a complex system of cells and molecules that can provide us with a basic defense against pathogenic organisms. Like the nervous system, the immune system performs pattern recognition tasks, learns, and retains a memory of the antigens that it has fought. The immune system contains more than 10{sup 7} different clones of cells that communicate via cell-cell contact and the secretion of molecules. Performing complex tasks such as learning and memory involves cooperation among large numbers of components of the immune system and hence there is interest in using methods and concepts from statistical physics. Furthermore,more » the immune response develops in time and the description of its time evolution is an interesting problem in dynamical systems. In this paper, the authors provide a brief introduction to the biology of the immune system and discuss a number of immunological problems in which the use of physical concepts and mathematical methods has increased our understanding. {copyright} {ital 1997} {ital The American Physical Society}« less

Learning redundant motor tasks with and without overlapping dimensions: facilitation and interference effects.

PubMed

Ranganathan, Rajiv; Wieser, Jon; Mosier, Kristine M; Mussa-Ivaldi, Ferdinando A; Scheidt, Robert A

2014-06-11

Prior learning of a motor skill creates motor memories that can facilitate or interfere with learning of new, but related, motor skills. One hypothesis of motor learning posits that for a sensorimotor task with redundant degrees of freedom, the nervous system learns the geometric structure of the task and improves performance by selectively operating within that task space. We tested this hypothesis by examining if transfer of learning between two tasks depends on shared dimensionality between their respective task spaces. Human participants wore a data glove and learned to manipulate a computer cursor by moving their fingers. Separate groups of participants learned two tasks: a prior task that was unique to each group and a criterion task that was common to all groups. We manipulated the mapping between finger motions and cursor positions in the prior task to define task spaces that either shared or did not share the task space dimensions (x-y axes) of the criterion task. We found that if the prior task shared task dimensions with the criterion task, there was an initial facilitation in criterion task performance. However, if the prior task did not share task dimensions with the criterion task, there was prolonged interference in learning the criterion task due to participants finding inefficient task solutions. These results show that the nervous system learns the task space through practice, and that the degree of shared task space dimensionality influences the extent to which prior experience transfers to subsequent learning of related motor skills. Copyright © 2014 the authors 0270-6474/14/348289-11$15.00/0.

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

PubMed Central

Taniguchi, Akira; Taniguchi, Tadahiro; Cangelosi, Angelo

2017-01-01

In this paper, we propose a Bayesian generative model that can form multiple categories based on each sensory-channel and can associate words with any of the four sensory-channels (action, position, object, and color). This paper focuses on cross-situational learning using the co-occurrence between words and information of sensory-channels in complex situations rather than conventional situations of cross-situational learning. We conducted a learning scenario using a simulator and a real humanoid iCub robot. In the scenario, a human tutor provided a sentence that describes an object of visual attention and an accompanying action to the robot. The scenario was set as follows: the number of words per sensory-channel was three or four, and the number of trials for learning was 20 and 40 for the simulator and 25 and 40 for the real robot. The experimental results showed that the proposed method was able to estimate the multiple categorizations and to learn the relationships between multiple sensory-channels and words accurately. In addition, we conducted an action generation task and an action description task based on word meanings learned in the cross-situational learning scenario. The experimental results showed that the robot could successfully use the word meanings learned by using the proposed method. PMID:29311888

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning.

PubMed

Stark-Inbar, Alit; Raza, Meher; Taylor, Jordan A; Ivry, Richard B

2017-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the alternating serial reaction time task, exhibited good test-retest reliability in measures of learning and performance. However, the learning measures did not correlate between the two tasks, arguing against a shared process for implicit motor learning. Copyright © 2017 the American Physiological Society.

Variability and reduced performance of preschool- and early school-aged children on psychoacoustic tasks: What are the relevant factors?

NASA Astrophysics Data System (ADS)

Allen, Prudence

2003-04-01

Young children typically perform more poorly on psychoacoustic tasks than do adults, with large individual differences. When performance is averaged across children within age groups, the data suggest a gradual change in performance with increasing age. However, an examination of individual data suggests that the performance matures more rapidly, although at different times for different children. The mechanisms of development responsible for these changes are likely very complex, involving both sensory and cognitive processes. This paper will discuss some previously suggested mechanisms including attention and cue weighting, as well as possibilities suggested from more recent studies in which learning effects were examined. In one task, a simple frequency discrimination was required, while in another the listener was required to extract regularities in complex sequences of sounds that varied from trial to trial. Results suggested that the ability to select and consistently employ an effective listening strategy was especially important in the performance of the more complex task, while simple stimulus exposure and motivation contributed to the simpler task. These factors are important for understanding the perceptual development and for the subsequent application of psychoacoustic findings to clinical populations. [Work supported by the NSERC and the Canadian Language and Literacy Research Network.

Collaborative Learning in Higher Education: Evoking Positive Interdependence

PubMed Central

Scager, Karin; Boonstra, Johannes; Peeters, Ton; Vulperhorst, Jonne; Wiegant, Fred

2016-01-01

Collaborative learning is a widely used instructional method, but the learning potential of this instructional method is often underused in practice. Therefore, the importance of various factors underlying effective collaborative learning should be determined. In the current study, five different life sciences undergraduate courses with successful collaborative-learning results were selected. This study focuses on factors that increased the effectiveness of collaboration in these courses, according to the students. Nine focus group interviews were conducted and analyzed. Results show that factors evoking effective collaboration were student autonomy and self-regulatory behavior, combined with a challenging, open, and complex group task that required the students to create something new and original. The design factors of these courses fostered a sense of responsibility and of shared ownership of both the collaborative process and the end product of the group assignment. In addition, students reported the absence of any free riders in these group assignments. Interestingly, it was observed that students seemed to value their sense of achievement, their learning processes, and the products they were working on more than their grades. It is concluded that collaborative learning in higher education should be designed using challenging and relevant tasks that build shared ownership with students. PMID:27909019

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.

Fast convergence of learning requires plasticity between inferior olive and deep cerebellar nuclei in a manipulation task: a closed-loop robotic simulation

PubMed Central

Luque, Niceto R.; Garrido, Jesús A.; Carrillo, Richard R.; D'Angelo, Egidio; Ros, Eduardo

2014-01-01

The cerebellum is known to play a critical role in learning relevant patterns of activity for adaptive motor control, but the underlying network mechanisms are only partly understood. The classical long-term synaptic plasticity between parallel fibers (PFs) and Purkinje cells (PCs), which is driven by the inferior olive (IO), can only account for limited aspects of learning. Recently, the role of additional forms of plasticity in the granular layer, molecular layer and deep cerebellar nuclei (DCN) has been considered. In particular, learning at DCN synapses allows for generalization, but convergence to a stable state requires hundreds of repetitions. In this paper we have explored the putative role of the IO-DCN connection by endowing it with adaptable weights and exploring its implications in a closed-loop robotic manipulation task. Our results show that IO-DCN plasticity accelerates convergence of learning by up to two orders of magnitude without conflicting with the generalization properties conferred by DCN plasticity. Thus, this model suggests that multiple distributed learning mechanisms provide a key for explaining the complex properties of procedural learning and open up new experimental questions for synaptic plasticity in the cerebellar network. PMID:25177290

Learning Universal Computations with Spikes

PubMed Central

Thalmeier, Dominik; Uhlmann, Marvin; Kappen, Hilbert J.; Memmesheimer, Raoul-Martin

2016-01-01

Providing the neurobiological basis of information processing in higher animals, spiking neural networks must be able to learn a variety of complicated computations, including the generation of appropriate, possibly delayed reactions to inputs and the self-sustained generation of complex activity patterns, e.g. for locomotion. Many such computations require previous building of intrinsic world models. Here we show how spiking neural networks may solve these different tasks. Firstly, we derive constraints under which classes of spiking neural networks lend themselves to substrates of powerful general purpose computing. The networks contain dendritic or synaptic nonlinearities and have a constrained connectivity. We then combine such networks with learning rules for outputs or recurrent connections. We show that this allows to learn even difficult benchmark tasks such as the self-sustained generation of desired low-dimensional chaotic dynamics or memory-dependent computations. Furthermore, we show how spiking networks can build models of external world systems and use the acquired knowledge to control them. PMID:27309381

Stilt walking: how do we learn those first steps?

PubMed

Akram, Sakineh B; Frank, James S

2009-09-01

This study examined how young healthy adults learn stilt walking. Ten healthy male university students attended two sessions of testing held on two consecutive days. In each session participants performed three blocks of 10 stilt-walking trials. Angular movements of head and trunk and the spatial and temporal gait parameters were recorded. When walking on stilts young adults improved their gait velocity through modifications of step parameters while maintaining trunk movements close to that observed during normal over-ground walking. Participants improved their performance by increasing their step frequency and step length and reducing the double support percentage of the gait cycle. Stilts are often used for drywall installation, painting over-the-head areas and raising workers above the ground without the burden of erecting scaffolding. This research examines the locomotor adaptation as young healthy adults learn the complex motor task of stilt walking; a task that is frequently used in the construction industry.

node2vec: Scalable Feature Learning for Networks

PubMed Central

Grover, Aditya; Leskovec, Jure

2016-01-01

Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to significant progress in automating prediction by learning the features themselves. However, present feature learning approaches are not expressive enough to capture the diversity of connectivity patterns observed in networks. Here we propose node2vec, an algorithmic framework for learning continuous feature representations for nodes in networks. In node2vec, we learn a mapping of nodes to a low-dimensional space of features that maximizes the likelihood of preserving network neighborhoods of nodes. We define a flexible notion of a node’s network neighborhood and design a biased random walk procedure, which efficiently explores diverse neighborhoods. Our algorithm generalizes prior work which is based on rigid notions of network neighborhoods, and we argue that the added flexibility in exploring neighborhoods is the key to learning richer representations. We demonstrate the efficacy of node2vec over existing state-of-the-art techniques on multi-label classification and link prediction in several real-world networks from diverse domains. Taken together, our work represents a new way for efficiently learning state-of-the-art task-independent representations in complex networks. PMID:27853626

Towards a cognitive robotics methodology for reward-based decision-making: dynamical systems modelling of the Iowa Gambling Task

NASA Astrophysics Data System (ADS)

Lowe, Robert; Ziemke, Tom

2010-09-01

The somatic marker hypothesis (SMH) posits that the role of emotions and mental states in decision-making manifests through bodily responses to stimuli of import to the organism's welfare. The Iowa Gambling Task (IGT), proposed by Bechara and Damasio in the mid-1990s, has provided the major source of empirical validation to the role of somatic markers in the service of flexible and cost-effective decision-making in humans. In recent years the IGT has been the subject of much criticism concerning: (1) whether measures of somatic markers reveal that they are important for decision-making as opposed to behaviour preparation; (2) the underlying neural substrate posited as critical to decision-making of the type relevant to the task; and (3) aspects of the methodological approach used, particularly on the canonical version of the task. In this paper, a cognitive robotics methodology is proposed to explore a dynamical systems approach as it applies to the neural computation of reward-based learning and issues concerning embodiment. This approach is particularly relevant in light of a strongly emerging alternative hypothesis to the SMH, the reversal learning hypothesis, which links, behaviourally and neurocomputationally, a number of more or less complex reward-based decision-making tasks, including the 'A-not-B' task - already subject to dynamical systems investigations with a focus on neural activation dynamics. It is also suggested that the cognitive robotics methodology may be used to extend systematically the IGT benchmark to more naturalised, but nevertheless controlled, settings that might better explore the extent to which the SMH, and somatic states per se, impact on complex decision-making.

A workflow learning model to improve geovisual analytics utility

PubMed Central

Roth, Robert E; MacEachren, Alan M; McCabe, Craig A

2011-01-01

Introduction This paper describes the design and implementation of the G-EX Portal Learn Module, a web-based, geocollaborative application for organizing and distributing digital learning artifacts. G-EX falls into the broader context of geovisual analytics, a new research area with the goal of supporting visually-mediated reasoning about large, multivariate, spatiotemporal information. Because this information is unprecedented in amount and complexity, GIScientists are tasked with the development of new tools and techniques to make sense of it. Our research addresses the challenge of implementing these geovisual analytics tools and techniques in a useful manner. Objectives The objective of this paper is to develop and implement a method for improving the utility of geovisual analytics software. The success of software is measured by its usability (i.e., how easy the software is to use?) and utility (i.e., how useful the software is). The usability and utility of software can be improved by refining the software, increasing user knowledge about the software, or both. It is difficult to achieve transparent usability (i.e., software that is immediately usable without training) of geovisual analytics software because of the inherent complexity of the included tools and techniques. In these situations, improving user knowledge about the software through the provision of learning artifacts is as important, if not more so, than iterative refinement of the software itself. Therefore, our approach to improving utility is focused on educating the user. Methodology The research reported here was completed in two steps. First, we developed a model for learning about geovisual analytics software. Many existing digital learning models assist only with use of the software to complete a specific task and provide limited assistance with its actual application. To move beyond task-oriented learning about software use, we propose a process-oriented approach to learning based on the concept of scientific workflows. Second, we implemented an interface in the G-EX Portal Learn Module to demonstrate the workflow learning model. The workflow interface allows users to drag learning artifacts uploaded to the G-EX Portal onto a central whiteboard and then annotate the workflow using text and drawing tools. Once completed, users can visit the assembled workflow to get an idea of the kind, number, and scale of analysis steps, view individual learning artifacts associated with each node in the workflow, and ask questions about the overall workflow or individual learning artifacts through the associated forums. An example learning workflow in the domain of epidemiology is provided to demonstrate the effectiveness of the approach. Results/Conclusions In the context of geovisual analytics, GIScientists are not only responsible for developing software to facilitate visually-mediated reasoning about large and complex spatiotemporal information, but also for ensuring that this software works. The workflow learning model discussed in this paper and demonstrated in the G-EX Portal Learn Module is one approach to improving the utility of geovisual analytics software. While development of the G-EX Portal Learn Module is ongoing, we expect to release the G-EX Portal Learn Module by Summer 2009. PMID:21983545

A workflow learning model to improve geovisual analytics utility.

PubMed

Roth, Robert E; Maceachren, Alan M; McCabe, Craig A

2009-01-01

INTRODUCTION: This paper describes the design and implementation of the G-EX Portal Learn Module, a web-based, geocollaborative application for organizing and distributing digital learning artifacts. G-EX falls into the broader context of geovisual analytics, a new research area with the goal of supporting visually-mediated reasoning about large, multivariate, spatiotemporal information. Because this information is unprecedented in amount and complexity, GIScientists are tasked with the development of new tools and techniques to make sense of it. Our research addresses the challenge of implementing these geovisual analytics tools and techniques in a useful manner. OBJECTIVES: The objective of this paper is to develop and implement a method for improving the utility of geovisual analytics software. The success of software is measured by its usability (i.e., how easy the software is to use?) and utility (i.e., how useful the software is). The usability and utility of software can be improved by refining the software, increasing user knowledge about the software, or both. It is difficult to achieve transparent usability (i.e., software that is immediately usable without training) of geovisual analytics software because of the inherent complexity of the included tools and techniques. In these situations, improving user knowledge about the software through the provision of learning artifacts is as important, if not more so, than iterative refinement of the software itself. Therefore, our approach to improving utility is focused on educating the user. METHODOLOGY: The research reported here was completed in two steps. First, we developed a model for learning about geovisual analytics software. Many existing digital learning models assist only with use of the software to complete a specific task and provide limited assistance with its actual application. To move beyond task-oriented learning about software use, we propose a process-oriented approach to learning based on the concept of scientific workflows. Second, we implemented an interface in the G-EX Portal Learn Module to demonstrate the workflow learning model. The workflow interface allows users to drag learning artifacts uploaded to the G-EX Portal onto a central whiteboard and then annotate the workflow using text and drawing tools. Once completed, users can visit the assembled workflow to get an idea of the kind, number, and scale of analysis steps, view individual learning artifacts associated with each node in the workflow, and ask questions about the overall workflow or individual learning artifacts through the associated forums. An example learning workflow in the domain of epidemiology is provided to demonstrate the effectiveness of the approach. RESULTS/CONCLUSIONS: In the context of geovisual analytics, GIScientists are not only responsible for developing software to facilitate visually-mediated reasoning about large and complex spatiotemporal information, but also for ensuring that this software works. The workflow learning model discussed in this paper and demonstrated in the G-EX Portal Learn Module is one approach to improving the utility of geovisual analytics software. While development of the G-EX Portal Learn Module is ongoing, we expect to release the G-EX Portal Learn Module by Summer 2009.

Workforce, learners, competencies, and the learning environment: Research in Medical Education 2014 and the way forward.

PubMed

West, Daniel C; Robins, Lynne; Gruppen, Larry D

2014-11-01

Medicine in the United States is changing as a result of many factors, including the needs and demands of 21st-century society. In this commentary, the authors review the 2014 Research in Medical Education (RIME) articles in the context of these changes and with an eye toward the future. The authors organized the 12 RIME articles into four broad themes: career development and workforce issues; competency and assessment; admissions, wellness, and the learning environment; and intended and unintended learning. Although the articles represent a broad range of issues, the authors identified three key take-home points from the collection: (1) Schools may be able to address the looming shortage of primary care physicians through admission selection criteria and targeted curricular activities; (2) better understanding of the competencies required to perform complex physician tasks could lead to more effective ways to teach and assess these tasks; and (3) the intended and unintended learning that take place in the medical learning environment require careful attention in order to produce physicians who are both skilled enough and well enough to meet the needs of society.

EEG-based cognitive load of processing events in 3D virtual worlds is lower than processing events in 2D displays.

PubMed

Dan, Alex; Reiner, Miriam

2017-12-01

Interacting with 2D displays, such as computer screens, smartphones, and TV, is currently a part of our daily routine; however, our visual system is built for processing 3D worlds. We examined the cognitive load associated with a simple and a complex task of learning paper-folding (origami) by observing 2D or stereoscopic 3D displays. While connected to an electroencephalogram (EEG) system, participants watched a 2D video of an instructor demonstrating the paper-folding tasks, followed by a stereoscopic 3D projection of the same instructor (a digital avatar) illustrating identical tasks. We recorded the power of alpha and theta oscillations and calculated the cognitive load index (CLI) as the ratio of the average power of frontal theta (Fz.) and parietal alpha (Pz). The results showed a significantly higher cognitive load index associated with processing the 2D projection as compared to the 3D projection; additionally, changes in the average theta Fz power were larger for the 2D conditions as compared to the 3D conditions, while alpha average Pz power values were similar for 2D and 3D conditions for the less complex task and higher in the 3D state for the more complex task. The cognitive load index was lower for the easier task and higher for the more complex task in 2D and 3D. In addition, participants with lower spatial abilities benefited more from the 3D compared to the 2D display. These findings have implications for understanding cognitive processing associated with 2D and 3D worlds and for employing stereoscopic 3D technology over 2D displays in designing emerging virtual and augmented reality applications. Copyright © 2016 Elsevier B.V. All rights reserved.

Studying Different Tasks of Implicit Learning across Multiple Test Sessions Conducted on the Web

PubMed Central

Sævland, Werner; Norman, Elisabeth

2016-01-01

Implicit learning is usually studied through individual performance on a single task, with the most common tasks being the Serial Reaction Time (SRT) task, the Dynamic System Control (DSC) task, and Artificial Grammar Learning (AGL). Few attempts have been made to compare performance across different implicit learning tasks within the same study. The current study was designed to explore the relationship between performance on the DSC Sugar factory task and the Alternating Serial Reaction Time (ASRT) task. We also addressed another limitation of traditional implicit learning experiments, namely that implicit learning is usually studied in laboratory settings over a restricted time span lasting for less than an hour. In everyday situations, implicit learning is assumed to involve a gradual accumulation of knowledge across several learning episodes over a longer time span. One way to increase the ecological validity of implicit learning experiments could be to present the learning material repeatedly across shorter test sessions. This can most easily be done by using a web-based setup in which participants can access the material from home. We therefore created an online web-based system for measuring implicit learning that could be administered in either single or multiple sessions. Participants (n = 66) were assigned to either a single session or a multiple session condition. Learning occurred on both tasks, and awareness measures suggested that acquired knowledge was not fully conscious on either of the tasks. Learning and the degree of conscious awareness of the learned regularities were compared across conditions and tasks. On the DSC task, performance was not affected by whether learning had taken place in one or over multiple sessions. On the ASRT task, RT improvement across blocks was larger in the multiple-session condition. Learning in the two tasks was not related. PMID:27375512

Effect of transcranial direct current stimulation (tDCS) during complex whole body motor skill learning.

PubMed

Kaminski, Elisabeth; Hoff, Maike; Sehm, Bernhard; Taubert, Marco; Conde, Virginia; Steele, Christopher J; Villringer, Arno; Ragert, Patrick

2013-09-27

The aim of the study was to investigate tDCS effects on motor skill learning in a complex whole body dynamic balance task (DBT). We hypothesized that tDCS over the supplementary motor area (SMA), a region that is known to be involved in the control of multi-joint whole body movements, will result in polarity specific changes in DBT learning. In a randomized sham-controlled, double-blinded parallel design, we applied 20 min of tDCS over the supplementary motor area (SMA) and prefrontal cortex (PFC) while subjects performed a DBT. Anodal tDCS over SMA with the cathode placed over contralateral PFC impaired motor skill learning of the DBT compared to sham. This effect was still present on the second day of training. Reversing the polarity (cathode over SMA, anode over PFC) did not affect motor skill learning neither on the first nor on the second day of training. To better disentangle whether the impaired motor skill learning was due to a modulation of SMA or PFC, we performed an additional control experiment. Here, we applied anodal tDCS over SMA together with a larger and presumably more ineffective electrode (cathode) over PFC. Interestingly this alternative tDCS electrode setup did not affect the outcome of DBT learning. Our results provide novel evidence that a modulation of the (right) PFC seems to impair complex multi-joint motor skill learning. Hence, future studies should take the positioning of both tDCS electrodes into account when investigating complex motor skill learning. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Learning to Search. From Weak Methods to Domain-Specific Heuristics.

DTIC Science & Technology

1984-09-01

move as undesirable. The remaining productions interact with MARKED-BAD, providing the labeling of states it requires for application. One of these, NOTE...to previously visited states, it did not attempt to learn from this knowledge, and simply abandoned dese undesirable pads. From the two remaining...the search strategy that SAGE employs. Many problems (such as winning a chess game ) are so complex that they can only be solved by breaking the task up

Wolves, dogs, rearing and reinforcement: complex interactions underlying species differences in training and problem-solving performance.

PubMed

Frank, Harry

2011-11-01

Frank and Frank et al. (1982-1987) administered a series of age-graded training and problem-solving tasks to samples of Eastern timber wolf (C. lupus lycaon) and Alaskan Malamute (C. familiaris) pups to test Frank's (Zeitschrift für Tierpsychologie 53:389-399, 1980) model of the evolution of information processing under conditions of natural and artificial selection. Results confirmed the model's prediction that wolves should perform better than dogs on problem-solving tasks and that dogs should perform better than wolves on training tasks. Further data collected at the University of Connecticut in 1983 revealed a more complex and refined picture, indicating that species differences can be mediated by a number of factors influencing wolf performance, including socialization regimen (hand-rearing vs. mother-rearing), interactive effects of socialization on the efficacy of both rewards and punishments, and the flexibility to select learning strategies that experimenters might not anticipate.

The Benefit of Being Naïve and Knowing It: The Unfavourable Impact of Perceived Context Familiarity on Learning in Complex Problem Solving Tasks

ERIC Educational Resources Information Center

Beckmann, Jens F.; Goode, Natassia

2014-01-01

Previous research has found that embedding a problem into a familiar context does not necessarily confer an advantage over a novel context in the acquisition of new knowledge about a complex, dynamic system. In fact, it has been shown that a semantically familiar context can be detrimental to knowledge acquisition. This has been described as the…

Classification of Complex Nonspeech Sounds. Panel on Classification of Complex Nonspeech Sounds

DTIC Science & Technology

1989-04-14

learning of the discrimination task. Since reports on many of these studies have not yet been published, brief summaries of the studies are included below...tonal signal with a noise- producing auditory induction and introduced an intensity ramp that increased the intensity of the tone just before the onset... recorded hand clap signals . The physical properties of the hand claps can be altered (along the lines suggested by the multidimensional analysis

Surfing the implicit wave.

PubMed

Shea, C H; Wulf, G; Whitacre, C A; Park, J H

2001-08-01

Implicit learning was investigated in two experiments involving a complex motor task. Participants were required to balance on a stabilometer and to move the platform on which they were standing to match a constantly changing target position. Experiment 1 examined whether a segment (middle third) that was repeated on each trial would be learned without participants becoming aware of the repetitions (i.e., implicitly). The purpose of Experiment 2 was to determine the relative effectiveness of explicit versus implicit learning. Here, two identical segments were presented on each trial (first and last thirds), with participants only being informed that one segment (either first or last) was repeated. The acquisition results from both experiments indicated large improvements in performance across 4 days of practice, with performance on the repeated segments being generally superior to that on the non-repeated segment. On the retention tests on Day 5, errors on the repeated segment(s) were smaller than those on the random segment(s). Furthermore, in Experiment 2, the errors on the repeated-known segment, although smaller than those on the random segment, were larger than those on the repeated-unknown segment. Interview results indicated that participants were not consciously aware that a segment was repeated unless they were informed. These results suggest that implicit learning can occur for relatively complex motor tasks and that withholding information concerning the regularities is more beneficial than providing this information.

Using complexity theory to develop a student-directed interprofessional learning activity for 1220 healthcare students.

PubMed

Jorm, Christine; Nisbet, Gillian; Roberts, Chris; Gordon, Christopher; Gentilcore, Stacey; Chen, Timothy F

2016-08-08

More and better interprofessional practice is predicated to be necessary to deliver good care to the patients of the future. However, universities struggle to create authentic learning activities that enable students to experience the dynamic interprofessional interactions common in healthcare and that can accommodate large interprofessional student cohorts. We investigated a large-scale mandatory interprofessional learning (IPL) activity for health professional students designed to promote social learning. A mixed methods research approach determined feasibility, acceptability and the extent to which student IPL outcomes were met. We developed an IPL activity founded in complexity theory to prepare students for future practice by engaging them in a self-directed (self-organised) learning activity with a diverse team, whose assessable products would be emergent creations. Complicated but authentic clinical cases (n = 12) were developed to challenge student teams (n = 5 or 6). Assessment consisted of a written management plan (academically marked) and a five-minute video (peer marked) designed to assess creative collaboration as well as provide evidence of integrated collective knowledge; the cohesive patient-centred management plan. All students (including the disciplines of diagnostic radiology, exercise physiology, medicine, nursing, occupational therapy, pharmacy, physiotherapy and speech pathology), completed all tasks successfully. Of the 26 % of students who completed the evaluation survey, 70 % agreed or strongly agreed that the IPL activity was worthwhile, and 87 % agreed or strongly agreed that their case study was relevant. Thematic analysis found overarching themes of engagement and collaboration-in-action suggesting that the IPL activity enabled students to achieve the intended learning objectives. Students recognised the contribution of others and described negotiation, collaboration and creation of new collective knowledge after working together on the complicated patient case studies. The novel video assessment was challenging to many students and contextual issues limited engagement for some disciplines. We demonstrated the feasibility and acceptability of a large scale IPL activity where design of cases, format and assessment tasks was founded in complexity theory. This theoretically based design enabled students to achieve complex IPL outcomes relevant to future practice. Future research could establish the psychometric properties of assessments of student performance in large-scale IPL events.

Skills for Children Entering Kindergarten

ERIC Educational Resources Information Center

Tindal, Gerald; Irvin, P. Shawn; Nese, Joseph F. T.; Slater, Steve

2015-01-01

Assessing kindergarten entry skills is complex, requiring attention to skill proficiency and interactive behaviors deemed critical for learning to occur. In our analysis of a state initiative, pilot data were collected on early literacy and numeracy and 2 aspects of important student interactions in the classroom (social and task behaviors) within…

Should Your School Offer Apprenticeship Training?

ERIC Educational Resources Information Center

Lewis, Morgan V.; Stone, James R., III

2011-01-01

Apprenticeship is one of several approaches to work-based learning (WBL). Apprenticeships have all the features needed to prepare workers for occupations that require extended study to attain competence. Apprentices begin with relatively simple tasks and progress to those requiring more complex skills. Apprenticeship has had a long history in the…

Dumbing Down or Smartening Up?

ERIC Educational Resources Information Center

BCEL Newsletter for the Business Community, 1988

1988-01-01

Critics call computerized innovations and other changes in the workplace examples of the employers'"dumbing down" of jobs for illiterate workers. Others disagree and say the changes free workers from routine, monotonous tasks and permit them to learn more complex procedures and to take on more responsibility. Findings of a survey of business…

Design and Implementation of the Game-Design and Learning Program

ERIC Educational Resources Information Center

Akcaoglu, Mete

2016-01-01

Design involves solving complex, ill-structured problems. Design tasks are consequently, appropriate contexts for children to exercise higher-order thinking and problem-solving skills. Although creating engaging and authentic design contexts for young children is difficult within the confines of traditional schooling, recently, game-design has…

Technology Leadership Preparedness: Principals' Perceptions

ERIC Educational Resources Information Center

Metcalf, Wendy; LaFrance, Jason

2013-01-01

Adopting technology in the K-12 classroom is evolving from adapting lessons that highlight a technology to pervasive use of interactive and handheld devices. In this environment, school leaders have the complex task of incorporating technologies to enhance teaching and learning. The purpose of this quasi-experimental quantitative study was to…

Fractions, Number Lines, Third Graders

ERIC Educational Resources Information Center

Cramer, Kathleen; Ahrendt, Sue; Monson, Debra; Wyberg, Terry; Colum, Karen

2017-01-01

The Common Core State Standards for Mathematics (CCSSM) (CCSSI 2010) outlines ambitious goals for fraction learning, starting in third grade, that include the use of the number line model. Understanding and constructing fractions on a number line are particularly complex tasks. The current work of the authors centers on ways to successfully…

Classroom Factors Affecting Students: Self-Evaluation: An Interactional Model.

ERIC Educational Resources Information Center

Marshall, Hermine H.; Weinstein, Rhona S.

1984-01-01

A complex interactional model of classroom factors that contribute to the development of students' self-evaluations is presented. Factors described are: (1) task structure; (2) grouping practices; (3) feedback and evaluation procedures and information about ability; (4) motivational strategies; (5) locus of responsibility for learning; and (6) the…

Rethinking the Boundaries of Cognitive Load Theory in Complex Learning

ERIC Educational Resources Information Center

Kalyuga, Slava; Singh, Anne-Marie

2016-01-01

In the traditional framework of cognitive load theory, it is assumed that the acquisition of domain-specific knowledge structures (or schemas) is the only instructional goal, and therefore, the theory is applicable to any instructional task. Accordingly, the basic concepts of intrinsic (productive) and extraneous (unproductive) types of cognitive…

Working Memory Intervention: A Reading Comprehension Approach

ERIC Educational Resources Information Center

Perry, Tracy L.; Malaia, Evguenia

2013-01-01

For any complex mental task, people rely on working memory. Working memory capacity (WMC) is one predictor of success in learning. Historically, attempts to improve verbal WM through training have not been effective. This study provided elementary students with WM consolidation efficiency training to answer the question, Can reading comprehension…

Microworlds for Learning Object-Oriented Programming: Considerations from Research to Practice

ERIC Educational Resources Information Center

Djelil, Fahima; Albouy-Kissi, Adelaide; Albouy-Kissi, Benjamin; Sanchez, Eric; Lavest, Jean-Marc

2016-01-01

Object-Oriented paradigm is a common paradigm for introductory programming courses. However, many teachers find that transitioning to teaching this paradigm is a difficult task. To overcome this complexity, many experienced teachers use microworlds to give beginner students an intuitive and rapid understanding of fundamental abstract concepts of…

Assessment Using Multi-Criteria Decision Approach for "Higher Order Skills" Learning Domains

ERIC Educational Resources Information Center

Ramakishnan, Sadhu Balasundaram; Ramadoss, Balakrishnan

2009-01-01

Over the past several decades, a wider range of assessment strategies has gained prominence in classrooms, including complex assessment items such as individual or group projects, student journals and other creative writing tasks, graphic/artistic representations of knowledge, clinical interviews, student presentations and performances, peer- and…

What is an Objective Structured Practical Examination in Anatomy?

ERIC Educational Resources Information Center

Yaqinuddin, Ahmed; Zafar, Muhammad; Ikram, Muhammad Faisal; Ganguly, Paul

2013-01-01

Assessing teaching-learning outcomes in anatomical knowledge is a complex task that requires the evaluation of multiple domains: theoretical, practical, and clinical knowledge. In general, theoretical knowledge is tested by a written examination system constituted by multiple choice questions (MCQs) and/or short answer questions (SAQ). The…

The Effects of Study Tasks in a Computer-Based Chemistry Learning Environment

NASA Astrophysics Data System (ADS)

Urhahne, Detlef; Nick, Sabine; Poepping, Anna Christin; Schulz, Sarah Jayne

2013-12-01

The present study examines the effects of different study tasks on the acquisition of knowledge about acids and bases in a computer-based learning environment. Three different task formats were selected to create three treatment conditions: learning with gap-fill and matching tasks, learning with multiple-choice tasks, and learning only from text and figures without any additional tasks. Participants were 196 ninth-grade students who learned with a self-developed multimedia program in a pretest-posttest control group design. Research results reveal that gap-fill and matching tasks were most effective in promoting knowledge acquisition, followed by multiple-choice tasks, and no tasks at all. The findings are in line with previous research on this topic. The effects can possibly be explained by the generation-recognition model, which predicts that gap-fill and matching tasks trigger more encompassing learning processes than multiple-choice tasks. It is concluded that instructional designers should incorporate more challenging study tasks for enhancing the effectiveness of computer-based learning environments.

Didactical determinants use of information and communication technology in process of training of future specialists.

PubMed

Palamar, Borys I; Vaskivska, Halyna O; Palamar, Svitlana P

In the article the author touches upon the subject of significance of computer equipment for organization of cooperation of professor and future specialists. Such subject-subject interaction may be directed to forming of professional skills of future specialists. By using information and communication technologies in education system range of didactic tasks can be solved. Improving of process of teaching of subjects in high school, self-learning future specialists, motivating to learning and self-learning, the development of reflection in the learning process. The authors considers computer equipment as instrument for development of intellectual skills, potential and willingness of future specialists to solve communicative and communication tasks and problems on the creative basis. Based on results of researches the author comes to certain conclusions about the effectiveness of usage of computer technologies in process of teaching future specialists and their self-learning. Improper supplying of high schools with computer equipment, lack of appropriate educational programs, professors' teachers' poor knowledge and usage of computers have negative impact on organization of process of teaching disciplines in high schools. Computer equipment and ICT in general are the instruments of development of intellectual skills, potential and willingness of future specialists to solve communicative and communication tasks and problems. So, the formation of psychosocial environment of development of future specialist is multifaceted, complex and didactically important issue.

Effect of chunk strength on the performance of children with developmental dyslexia on artificial grammar learning task may be related to complexity.

PubMed

Schiff, Rachel; Katan, Pesia; Sasson, Ayelet; Kahta, Shani

2017-07-01

There's a long held view that chunks play a crucial role in artificial grammar learning performance. We compared chunk strength influences on performance, in high and low topological entropy (a measure of complexity) grammar systems, with dyslexic children, age-matched and reading-level-matched control participants. Findings show that age-matched control participants' performance reflected equivalent influence of chunk strength in the two topological entropy conditions, as typically found in artificial grammar learning experiments. By contrast, dyslexic children and reading-level-matched controls' performance reflected knowledge of chunk strength only under the low topological entropy condition. In the low topological entropy grammar system, they appeared completely unable to utilize chunk strength to make appropriate test item selections. In line with previous research, this study suggests that for typically developing children, it is the chunks that are attended during artificial grammar learning and create a foundation on which implicit associative learning mechanisms operate, and these chunks are unitized to different strengths. However, for children with dyslexia, it is complexity that may influence the subsequent memorability of chunks, independently of their strength.

Multi-task feature learning by using trace norm regularization

NASA Astrophysics Data System (ADS)

Jiangmei, Zhang; Binfeng, Yu; Haibo, Ji; Wang, Kunpeng

2017-11-01

Multi-task learning can extract the correlation of multiple related machine learning problems to improve performance. This paper considers applying the multi-task learning method to learn a single task. We propose a new learning approach, which employs the mixture of expert model to divide a learning task into several related sub-tasks, and then uses the trace norm regularization to extract common feature representation of these sub-tasks. A nonlinear extension of this approach by using kernel is also provided. Experiments conducted on both simulated and real data sets demonstrate the advantage of the proposed approach.

Comparison of robotics, functional electrical stimulation, and motor learning methods for treatment of persistent upper extremity dysfunction after stroke: a randomized controlled trial.

PubMed

McCabe, Jessica; Monkiewicz, Michelle; Holcomb, John; Pundik, Svetlana; Daly, Janis J

2015-06-01

To compare response to upper-limb treatment using robotics plus motor learning (ML) versus functional electrical stimulation (FES) plus ML versus ML alone, according to a measure of complex functional everyday tasks for chronic, severely impaired stroke survivors. Single-blind, randomized trial. Medical center. Enrolled subjects (N=39) were >1 year postsingle stroke (attrition rate=10%; 35 completed the study). All groups received treatment 5d/wk for 5h/d (60 sessions), with unique treatment as follows: ML alone (n=11) (5h/d partial- and whole-task practice of complex functional tasks), robotics plus ML (n=12) (3.5h/d of ML and 1.5h/d of shoulder/elbow robotics), and FES plus ML (n=12) (3.5h/d of ML and 1.5h/d of FES wrist/hand coordination training). Primary measure: Arm Motor Ability Test (AMAT), with 13 complex functional tasks; secondary measure: upper-limb Fugl-Meyer coordination scale (FM). There was no significant difference found in treatment response across groups (AMAT: P≥.584; FM coordination: P≥.590). All 3 treatment groups demonstrated clinically and statistically significant improvement in response to treatment (AMAT and FM coordination: P≤.009). A group treatment paradigm of 1:3 (therapist/patient) ratio proved feasible for provision of the intensive treatment. No adverse effects. Severely impaired stroke survivors with persistent (>1y) upper-extremity dysfunction can make clinically and statistically significant gains in coordination and functional task performance in response to robotics plus ML, FES plus ML, and ML alone in an intensive and long-duration intervention; no group differences were found. Additional studies are warranted to determine the effectiveness of these methods in the clinical setting. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Risky decision making from childhood through adulthood: Contributions of learning and sensitivity to negative feedback.

PubMed

Humphreys, Kathryn L; Telzer, Eva H; Flannery, Jessica; Goff, Bonnie; Gabard-Durnam, Laurel; Gee, Dylan G; Lee, Steve S; Tottenham, Nim

2016-02-01

Decision making in the context of risk is a complex and dynamic process that changes across development. Here, we assessed the influence of sensitivity to negative feedback (e.g., loss) and learning on age-related changes in risky decision making, both of which show unique developmental trajectories. In the present study, we examined risky decision making in 216 individuals, ranging in age from 3-26 years, using the balloon emotional learning task (BELT), a computerized task in which participants pump up a series of virtual balloons to earn points, but risk balloon explosion on each trial, which results in no points. It is important to note that there were 3 balloon conditions, signified by different balloon colors, ranging from quick- to slow-to-explode, and participants could learn the color-condition pairings through task experience. Overall, we found age-related increases in pumps made and points earned. However, in the quick-to-explode condition, there was a nonlinear adolescent peak for points earned. Follow-up analyses indicated that this adolescent phenotype occurred at the developmental intersection of linear age-related increases in learning and decreases in sensitivity to negative feedback. Adolescence was marked by intermediate values on both these processes. These findings show that a combination of linearly changing processes can result in nonlinear changes in risky decision making, the adolescent-specific nature of which is associated with developmental improvements in learning and reduced sensitivity to negative feedback. (c) 2016 APA, all rights reserved).

Usability of Computerized Lung Auscultation-Sound Software (CLASS) for learning pulmonary auscultation.

PubMed

Machado, Ana; Oliveira, Ana; Jácome, Cristina; Pereira, Marco; Moreira, José; Rodrigues, João; Aparício, José; Jesus, Luis M T; Marques, Alda

2018-04-01

The mastering of pulmonary auscultation requires complex acoustic skills. Computer-assisted learning tools (CALTs) have potential to enhance the learning of these skills; however, few have been developed for this purpose and do not integrate all the required features. Thus, this study aimed to assess the usability of a new CALT for learning pulmonary auscultation. Computerized Lung Auscultation-Sound Software (CLASS) usability was assessed by eight physiotherapy students using computer screen recordings, think-aloud reports, and facial expressions. Time spent in each task, frequency of messages and facial expressions, number of clicks and problems reported were counted. The timelines of the three methods used were matched/synchronized and analyzed. The tasks exercises and annotation of respiratory sounds were the ones requiring more clicks (median 132, interquartile range [23-157]; 93 [53-155]; 91 [65-104], respectively) and where most errors (19; 37; 15%, respectively) and problems (n = 7; 6; 3, respectively) were reported. Each participant reported a median of 6 problems, with a total of 14 different problems found, mainly related with CLASS functionalities (50%). Smile was the only facial expression presented in all tasks (n = 54). CLASS is the only CALT available that meets all the required features for learning pulmonary auscultation. The combination of the three usability methods identified advantages/disadvantages of CLASS and offered guidance for future developments, namely in annotations and exercises. This will allow the improvement of CLASS and enhance students' activities for learning pulmonary auscultation skills.

Making clinical case-based learning in veterinary medicine visible: analysis of collaborative concept-mapping processes and reflections.

PubMed

Khosa, Deep K; Volet, Simone E; Bolton, John R

2014-01-01

The value of collaborative concept mapping in assisting students to develop an understanding of complex concepts across a broad range of basic and applied science subjects is well documented. Less is known about students' learning processes that occur during the construction of a concept map, especially in the context of clinical cases in veterinary medicine. This study investigated the unfolding collaborative learning processes that took place in real-time concept mapping of a clinical case by veterinary medical students and explored students' and their teacher's reflections on the value of this activity. This study had two parts. The first part investigated the cognitive and metacognitive learning processes of two groups of students who displayed divergent learning outcomes in a concept mapping task. Meaningful group differences were found in their level of learning engagement in terms of the extent to which they spent time understanding and co-constructing knowledge along with completing the task at hand. The second part explored students' and their teacher's views on the value of concept mapping as a learning and teaching tool. The students' and their teacher's perceptions revealed congruent and contrasting notions about the usefulness of concept mapping. The relevance of concept mapping to clinical case-based learning in veterinary medicine is discussed, along with directions for future research.

Influence of Procedural Learning on Iowa Gambling Task Performance Among HIV+ Individuals with History of Substance Dependence

PubMed Central

Gonzalez, Raul; Wardle, Margaret; Jacobus, Joanna; Vassileva, Jasmin; Martin-Thormeyer, Eileen M.

2010-01-01

HIV+ individuals have been shown to demonstrate deficits on the Iowa Gambling Task (IGT), a complex measure of “decision-making.” Little remains known about what other neurocognitive processes may account for variability in IGT performance among HIV+ samples or the role of procedural learning (PL) in IGT performance. A sample of 49 HIV+ individuals with a history of substance use disorders was examined to explore the relationship between IGT performance and three measures of PL: The Rotary Pursuit, Mirror Star Tracing, and Weather Prediction tasks. We found no statistically significant relationships between IGT performance and any of the PL tasks, despite finding significant correlations among the PL tasks. This pattern of results persisted when analyzing IGT performance in various ways (e.g., performance on earlier trial blocks or impairment classifications). Although other nondeclarative processes (e.g., somatic markers) may be important for IGT performance, these findings do not support PL as an important component neurocognitive process for the IGT. Similarly, these results suggest that differences in PL performance does not account for the decision-making deficits or variability in performances observed on the IGT among HIV+ individuals with a history of substance dependence. PMID:19939850

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

PubMed

Zenke, Friedemann; Ganguli, Surya

2018-06-01

A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.

Mice with a fra-1 knock-in into the c-fos locus show impaired spatial but regular contextual learning and normal LTP.

PubMed

Gass, Peter; Fleischmann, Alexander; Hvalby, Oivind; Jensen, Vidar; Zacher, Christiane; Strekalova, Tatyana; Kvello, Ane; Wagner, Erwin F; Sprengel, Rolf

2004-11-04

The immediate early gene c-fos is part of the AP-1 transcription factor complex, which is involved in molecular mechanisms underlying learning and memory. Mice that lack c-Fos in the brain show impairments in spatial reference and contextual learning, and also exhibit a reduced long-term potentiation of synaptic transmission (LTP) at CA3-to-CA1 synapses. In the present study, we investigated mice in which c-fos was deleted and replaced by fra-1 (c-fos(fra-1) mice) to determine whether other members of the c-fos gene family can substitute for the functions of the c-fos gene. In c-fos(fra-1) mice, both CA3-to-CA1 LTP and contextual learning in a Pavlovian fear conditioning task were similar to wild-type littermates, indicating that Fra-1 expression restored the impairments caused by brain-specific c-Fos depletion. However, c-Fos-mediated learning deficits in a reference memory task of the Morris watermaze were also present in c-fos(fra-1) mice. These findings suggest that different c-Fos target genes are involved in LTP, contextual learning, and spatial reference memory formation.

Sleep-dependent learning and motor-skill complexity

PubMed Central

Kuriyama, Kenichi; Stickgold, Robert; Walker, Matthew P.

2004-01-01

Learning of a procedural motor-skill task is known to progress through a series of unique memory stages. Performance initially improves during training, and continues to improve, without further rehearsal, across subsequent periods of sleep. Here, we investigate how this delayed sleep-dependent learning is affected when the task characteristics are varied across several degrees of difficulty, and whether this improvement differentially enhances individual transitions of the motor-sequence pattern being learned. We report that subjects show similar overnight improvements in speed whether learning a five-element unimanual sequence (17.7% improvement), a nine-element unimanual sequence (20.2%), or a five-element bimanual sequence (17.5%), but show markedly increased overnight improvement (28.9%) with a nine-element bimanual sequence. In addition, individual transitions within the motor-sequence pattern that appeared most difficult at the end of training showed a significant 17.8% increase in speed overnight, whereas those transitions that were performed most rapidly at the end of training showed only a non-significant 1.4% improvement. Together, these findings suggest that the sleep-dependent learning process selectively provides maximum benefit to motor-skill procedures that proved to be most difficult prior to sleep. PMID:15576888

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

PubMed

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

2009-02-01

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

Physical Realization of a Supervised Learning System Built with Organic Memristive Synapses

NASA Astrophysics Data System (ADS)

Lin, Yu-Pu; Bennett, Christopher H.; Cabaret, Théo; Vodenicarevic, Damir; Chabi, Djaafar; Querlioz, Damien; Jousselme, Bruno; Derycke, Vincent; Klein, Jacques-Olivier

2016-09-01

Multiple modern applications of electronics call for inexpensive chips that can perform complex operations on natural data with limited energy. A vision for accomplishing this is implementing hardware neural networks, which fuse computation and memory, with low cost organic electronics. A challenge, however, is the implementation of synapses (analog memories) composed of such materials. In this work, we introduce robust, fastly programmable, nonvolatile organic memristive nanodevices based on electrografted redox complexes that implement synapses thanks to a wide range of accessible intermediate conductivity states. We demonstrate experimentally an elementary neural network, capable of learning functions, which combines four pairs of organic memristors as synapses and conventional electronics as neurons. Our architecture is highly resilient to issues caused by imperfect devices. It tolerates inter-device variability and an adaptable learning rule offers immunity against asymmetries in device switching. Highly compliant with conventional fabrication processes, the system can be extended to larger computing systems capable of complex cognitive tasks, as demonstrated in complementary simulations.

Physical Realization of a Supervised Learning System Built with Organic Memristive Synapses.

PubMed

Lin, Yu-Pu; Bennett, Christopher H; Cabaret, Théo; Vodenicarevic, Damir; Chabi, Djaafar; Querlioz, Damien; Jousselme, Bruno; Derycke, Vincent; Klein, Jacques-Olivier

2016-09-07

Multiple modern applications of electronics call for inexpensive chips that can perform complex operations on natural data with limited energy. A vision for accomplishing this is implementing hardware neural networks, which fuse computation and memory, with low cost organic electronics. A challenge, however, is the implementation of synapses (analog memories) composed of such materials. In this work, we introduce robust, fastly programmable, nonvolatile organic memristive nanodevices based on electrografted redox complexes that implement synapses thanks to a wide range of accessible intermediate conductivity states. We demonstrate experimentally an elementary neural network, capable of learning functions, which combines four pairs of organic memristors as synapses and conventional electronics as neurons. Our architecture is highly resilient to issues caused by imperfect devices. It tolerates inter-device variability and an adaptable learning rule offers immunity against asymmetries in device switching. Highly compliant with conventional fabrication processes, the system can be extended to larger computing systems capable of complex cognitive tasks, as demonstrated in complementary simulations.

Improving fluid intelligence with training on working memory.

PubMed

Jaeggi, Susanne M; Buschkuehl, Martin; Jonides, John; Perrig, Walter J

2008-05-13

Fluid intelligence (Gf) refers to the ability to reason and to solve new problems independently of previously acquired knowledge. Gf is critical for a wide variety of cognitive tasks, and it is considered one of the most important factors in learning. Moreover, Gf is closely related to professional and educational success, especially in complex and demanding environments. Although performance on tests of Gf can be improved through direct practice on the tests themselves, there is no evidence that training on any other regimen yields increased Gf in adults. Furthermore, there is a long history of research into cognitive training showing that, although performance on trained tasks can increase dramatically, transfer of this learning to other tasks remains poor. Here, we present evidence for transfer from training on a demanding working memory task to measures of Gf. This transfer results even though the trained task is entirely different from the intelligence test itself. Furthermore, we demonstrate that the extent of gain in intelligence critically depends on the amount of training: the more training, the more improvement in Gf. That is, the training effect is dosage-dependent. Thus, in contrast to many previous studies, we conclude that it is possible to improve Gf without practicing the testing tasks themselves, opening a wide range of applications.

Improving fluid intelligence with training on working memory

PubMed Central

Jaeggi, Susanne M.; Buschkuehl, Martin; Jonides, John; Perrig, Walter J.

2008-01-01

Fluid intelligence (Gf) refers to the ability to reason and to solve new problems independently of previously acquired knowledge. Gf is critical for a wide variety of cognitive tasks, and it is considered one of the most important factors in learning. Moreover, Gf is closely related to professional and educational success, especially in complex and demanding environments. Although performance on tests of Gf can be improved through direct practice on the tests themselves, there is no evidence that training on any other regimen yields increased Gf in adults. Furthermore, there is a long history of research into cognitive training showing that, although performance on trained tasks can increase dramatically, transfer of this learning to other tasks remains poor. Here, we present evidence for transfer from training on a demanding working memory task to measures of Gf. This transfer results even though the trained task is entirely different from the intelligence test itself. Furthermore, we demonstrate that the extent of gain in intelligence critically depends on the amount of training: the more training, the more improvement in Gf. That is, the training effect is dosage-dependent. Thus, in contrast to many previous studies, we conclude that it is possible to improve Gf without practicing the testing tasks themselves, opening a wide range of applications. PMID:18443283

Narrative Skill in Children with Early Unilateral Brain Injury: A Possible Limit to Functional Plasticity

PubMed Central

Demir, Özlem Ece; Levine, Susan C.; Goldin-Meadow, Susan

2009-01-01

Children with pre- or perinatal brain injury (PL) exhibit marked plasticity for language learning. Previous work mostly focused on the emergence of earlier developing skills, such as vocabulary and syntax. Here we ask whether this plasticity for earlier developing aspects of language extends to more complex, later-developing language functions by examining the narrative production of children with PL. Using an elicitation technique that involves asking children to create stories de novo in response to a story stem, we collected narratives from 11 children with PL and 20 typically-developing (TD) children. Narratives were analyzed for length, diversity of the vocabulary used, use of complex syntax, complexity of the macro-level narrative structure and use of narrative evaluation. Children’s language performance on vocabulary and syntax tasks outside of the narrative context was also measured. Findings show that children with PL produced shorter stories, used less diverse vocabulary, produced structurally less complex stories at the macro-level, and made fewer inferences regarding the cognitive states of the story characters. These differences in the narrative task emerged even though children with PL did not differ from TD children on vocabulary and syntax tasks outside of the narrative context. Thus, findings suggest that there may be limitations to the plasticity for language functions displayed by children with PL, and that these limitations may be most apparent in complex, decontextualized language tasks such as narrative production. PMID:20590727

Environmental influences on neural systems of relational complexity

PubMed Central

Kalbfleisch, M. Layne; deBettencourt, Megan T.; Kopperman, Rebecca; Banasiak, Meredith; Roberts, Joshua M.; Halavi, Maryam

2013-01-01

Constructivist learning theory contends that we construct knowledge by experience and that environmental context influences learning. To explore this principle, we examined the cognitive process relational complexity (RC), defined as the number of visual dimensions considered during problem solving on a matrix reasoning task and a well-documented measure of mature reasoning capacity. We sought to determine how the visual environment influences RC by examining the influence of color and visual contrast on RC in a neuroimaging task. To specify the contributions of sensory demand and relational integration to reasoning, our participants performed a non-verbal matrix task comprised of color, no-color line, or black-white visual contrast conditions parametrically varied by complexity (relations 0, 1, 2). The use of matrix reasoning is ecologically valid for its psychometric relevance and for its potential to link the processing of psychophysically specific visual properties with various levels of RC during reasoning. The role of these elements is important because matrix tests assess intellectual aptitude based on these seemingly context-less exercises. This experiment is a first step toward examining the psychophysical underpinnings of performance on these types of problems. The importance of this is increased in light of recent evidence that intelligence can be linked to visual discrimination. We submit three main findings. First, color and black-white visual contrast (BWVC) add demand at a basic sensory level, but contributions from color and from BWVC are dissociable in cortex such that color engages a “reasoning heuristic” and BWVC engages a “sensory heuristic.” Second, color supports contextual sense-making by boosting salience resulting in faster problem solving. Lastly, when visual complexity reaches 2-relations, color and visual contrast relinquish salience to other dimensions of problem solving. PMID:24133465

Human Factors Engineering. Student Supplement,

DTIC Science & Technology

1981-08-01

a job TASK TAXONOMY A classification scheme for the different levels of activities in a system, i.e., job - task - sub-task, etc. TASK-AN~ALYSIS...with the classification of learning objectives by learning category so as to identify learningPhas III guidelines necessary for optimum learning to...correct. .4... .the sequencing of all dependent tasks. .1.. .the classification of learning objectives by learning category and the Identification of

Supervised Extraction of Diagnosis Codes from EMRs: Role of Feature Selection, Data Selection, and Probabilistic Thresholding.

PubMed

Rios, Anthony; Kavuluru, Ramakanth

2013-09-01

Extracting diagnosis codes from medical records is a complex task carried out by trained coders by reading all the documents associated with a patient's visit. With the popularity of electronic medical records (EMRs), computational approaches to code extraction have been proposed in the recent years. Machine learning approaches to multi-label text classification provide an important methodology in this task given each EMR can be associated with multiple codes. In this paper, we study the the role of feature selection, training data selection, and probabilistic threshold optimization in improving different multi-label classification approaches. We conduct experiments based on two different datasets: a recent gold standard dataset used for this task and a second larger and more complex EMR dataset we curated from the University of Kentucky Medical Center. While conventional approaches achieve results comparable to the state-of-the-art on the gold standard dataset, on our complex in-house dataset, we show that feature selection, training data selection, and probabilistic thresholding provide significant gains in performance.

The Effects of Study Tasks in a Computer-Based Chemistry Learning Environment

ERIC Educational Resources Information Center

Urhahne, Detlef; Nick, Sabine; Poepping, Anna Christin; Schulz , Sarah Jayne

2013-01-01

The present study examines the effects of different study tasks on the acquisition of knowledge about acids and bases in a computer-based learning environment. Three different task formats were selected to create three treatment conditions: learning with gap-fill and matching tasks, learning with multiple-choice tasks, and learning only from text…

Efficient Grammar Induction Algorithm with Parse Forests from Real Corpora

NASA Astrophysics Data System (ADS)

Kurihara, Kenichi; Kameya, Yoshitaka; Sato, Taisuke

The task of inducing grammar structures has received a great deal of attention. The reasons why researchers have studied are different; to use grammar induction as the first stage in building large treebanks or to make up better language models. However, grammar induction has inherent computational complexity. To overcome it, some grammar induction algorithms add new production rules incrementally. They refine the grammar while keeping their computational complexity low. In this paper, we propose a new efficient grammar induction algorithm. Although our algorithm is similar to algorithms which learn a grammar incrementally, our algorithm uses the graphical EM algorithm instead of the Inside-Outside algorithm. We report results of learning experiments in terms of learning speeds. The results show that our algorithm learns a grammar in constant time regardless of the size of the grammar. Since our algorithm decreases syntactic ambiguities in each step, our algorithm reduces required time for learning. This constant-time learning considerably affects learning time for larger grammars. We also reports results of evaluation of criteria to choose nonterminals. Our algorithm refines a grammar based on a nonterminal in each step. Since there can be several criteria to decide which nonterminal is the best, we evaluate them by learning experiments.

Measurement of functional task difficulty during motor learning: What level of difficulty corresponds to the optimal challenge point?

PubMed

Akizuki, Kazunori; Ohashi, Yukari

2015-10-01

The relationship between task difficulty and learning benefit was examined, as was the measurability of task difficulty. Participants were required to learn a postural control task on an unstable surface at one of four different task difficulty levels. Results from the retention test showed an inverted-U relationship between task difficulty during acquisition and motor learning. The second-highest level of task difficulty was the most effective for motor learning, while learning was delayed at the most and least difficult levels. Additionally, the results indicate that salivary α-amylase and the performance dimension of the National Aeronautics and Space Administration-Task Load Index (NASA-TLX) are useful indices of task difficulty. Our findings suggested that instructors may be able to adjust task difficulty based on salivary α-amylase and the performance dimension of the NASA-TLX to enhance learning. Copyright © 2015 Elsevier B.V. All rights reserved.

Articulatory Control in Childhood Apraxia of Speech in a Novel Word-Learning Task.

PubMed

Case, Julie; Grigos, Maria I

2016-12-01

Articulatory control and speech production accuracy were examined in children with childhood apraxia of speech (CAS) and typically developing (TD) controls within a novel word-learning task to better understand the influence of planning and programming deficits in the production of unfamiliar words. Participants included 16 children between the ages of 5 and 6 years (8 CAS, 8 TD). Short- and long-term changes in lip and jaw movement, consonant and vowel accuracy, and token-to-token consistency were measured for 2 novel words that differed in articulatory complexity. Children with CAS displayed short- and long-term changes in consonant accuracy and consistency. Lip and jaw movements did not change over time. Jaw movement duration was longer in children with CAS than in TD controls. Movement stability differed between low- and high-complexity words in both groups. Children with CAS displayed a learning effect for consonant accuracy and consistency. Lack of change in movement stability may indicate that children with CAS require additional practice to demonstrate changes in speech motor control, even within production of novel word targets with greater consonant and vowel accuracy and consistency. The longer movement duration observed in children with CAS is believed to give children additional time to plan and program movements within a novel skill.

The clinical relevance of advanced artificial feedback in the control of a multi-functional myoelectric prosthesis.

PubMed

Markovic, Marko; Schweisfurth, Meike A; Engels, Leonard F; Bentz, Tashina; Wüstefeld, Daniela; Farina, Dario; Dosen, Strahinja

2018-03-27

To effectively replace the human hand, a prosthesis should seamlessly respond to user intentions but also convey sensory information back to the user. Restoration of sensory feedback is rated highly by the prosthesis users, and feedback is critical for grasping in able-bodied subjects. Nonetheless, the benefits of feedback in prosthetics are still debated. The lack of consensus is likely due to the complex nature of sensory feedback during prosthesis control, so that its effectiveness depends on multiple factors (e.g., task complexity, user learning). We evaluated the impact of these factors with a longitudinal assessment in six amputee subjects, using a clinical setup (socket, embedded control) and a range of tasks (box and blocks, block turn, clothespin and cups relocation). To provide feedback, we have proposed a novel vibrotactile stimulation scheme capable of transmitting multiple variables from a multifunction prosthesis. The subjects wore a bracelet with four by two uniformly placed vibro-tactors providing information on contact, prosthesis state (active function), and grasping force. The subjects also completed a questionnaire for the subjective evaluation of the feedback. The tests demonstrated that feedback was beneficial only in the complex tasks (block turn, clothespin and cups relocation), and that the training had an important, task-dependent impact. In the clothespin relocation and block turn tasks, training allowed the subjects to establish successful feedforward control, and therefore, the feedback became redundant. In the cups relocation task, however, the subjects needed some training to learn how to properly exploit the feedback. The subjective evaluation of the feedback was consistently positive, regardless of the objective benefits. These results underline the multifaceted nature of closed-loop prosthesis control as, depending on the context, the same feedback interface can have different impact on performance. Finally, even if the closed-loop control does not improve the performance, it could be beneficial as it seems to improve the subjective experience. Therefore, in this study we demonstrate, for the first time, the relevance of an advanced, multi-variable feedback interface for dexterous, multi-functional prosthesis control in a clinically relevant setting.

Short-term total sleep deprivation alters delay-conditioned memory in the rat.

PubMed

Tripathi, Shweta; Jha, Sushil K

2016-06-01

Short-term sleep deprivation soon after training may impair memory consolidation. Also, a particular sleep stage or its components increase after learning some tasks, such as negative and positive reinforcement tasks, avoidance tasks, and spatial learning tasks, and so forth. It suggests that discrete memory types may require specific sleep stage or its components for their optimal processing. The classical conditioning paradigms are widely used to study learning and memory but the role of sleep in a complex conditioned learning is unclear. Here, we have investigated the effects of short-term sleep deprivation on the consolidation of delay-conditioned memory and the changes in sleep architecture after conditioning. Rats were trained for the delay-conditioned task (for conditioning, house-light [conditioned stimulus] was paired with fruit juice [unconditioned stimulus]). Animals were divided into 3 groups: (a) sleep deprived (SD); (b) nonsleep deprived (NSD); and (c) stress control (SC) groups. Two-way ANOVA revealed a significant interaction between groups and days (training and testing) during the conditioned stimulus-unconditioned stimulus presentation. Further, Tukey post hoc comparison revealed that the NSD and SC animals exhibited significant increase in performances during testing. The SD animals, however, performed significantly less during testing. Further, we observed that wakefulness and NREM sleep did not change after training and testing. Interestingly, REM sleep increased significantly on both days compared to baseline more specifically during the initial 4-hr time window after conditioning. Our results suggest that the consolidation of delay-conditioned memory is sleep-dependent and requires augmented REM sleep during an explicit time window soon after training. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A machine learning approach to identify functional biomarkers in human prefrontal cortex for individuals with traumatic brain injury using functional near-infrared spectroscopy.

PubMed

Karamzadeh, Nader; Amyot, Franck; Kenney, Kimbra; Anderson, Afrouz; Chowdhry, Fatima; Dashtestani, Hadis; Wassermann, Eric M; Chernomordik, Victor; Boccara, Claude; Wegman, Edward; Diaz-Arrastia, Ramon; Gandjbakhche, Amir H

2016-11-01

We have explored the potential prefrontal hemodynamic biomarkers to characterize subjects with Traumatic Brain Injury (TBI) by employing the multivariate machine learning approach and introducing a novel task-related hemodynamic response detection followed by a heuristic search for optimum set of hemodynamic features. To achieve this goal, the hemodynamic response from a group of 31 healthy controls and 30 chronic TBI subjects were recorded as they performed a complexity task. To determine the optimum hemodynamic features, we considered 11 features and their combinations in characterizing TBI subjects. We investigated the significance of the features by utilizing a machine learning classification algorithm to score all the possible combinations of features according to their predictive power. The identified optimum feature elements resulted in classification accuracy, sensitivity, and specificity of 85%, 85%, and 84%, respectively. Classification improvement was achieved for TBI subject classification through feature combination. It signified the major advantage of the multivariate analysis over the commonly used univariate analysis suggesting that the features that are individually irrelevant in characterizing the data may become relevant when used in combination. We also conducted a spatio-temporal classification to identify regions within the prefrontal cortex (PFC) that contribute in distinguishing between TBI and healthy subjects. As expected, Brodmann areas (BA) 10 within the PFC were isolated as the region that healthy subjects (unlike subjects with TBI), showed major hemodynamic activity in response to the High Complexity task. Overall, our results indicate that identified temporal and spatio-temporal features from PFC's hemodynamic activity are promising biomarkers in classifying subjects with TBI.

Learning the Task Management Space of an Aircraft Approach Model

NASA Technical Reports Server (NTRS)

Krall, Joseph; Menzies, Tim; Davies, Misty

2014-01-01

Validating models of airspace operations is a particular challenge. These models are often aimed at finding and exploring safety violations, and aim to be accurate representations of real-world behavior. However, the rules governing the behavior are quite complex: nonlinear physics, operational modes, human behavior, and stochastic environmental concerns all determine the responses of the system. In this paper, we present a study on aircraft runway approaches as modeled in Georgia Tech's Work Models that Compute (WMC) simulation. We use a new learner, Genetic-Active Learning for Search-Based Software Engineering (GALE) to discover the Pareto frontiers defined by cognitive structures. These cognitive structures organize the prioritization and assignment of tasks of each pilot during approaches. We discuss the benefits of our approach, and also discuss future work necessary to enable uncertainty quantification.

Performing Complex Tasks by Users With Upper-Extremity Disabilities Using a 6-DOF Robotic Arm: A Study.

PubMed

Al-Halimi, Reem K; Moussa, Medhat

2017-06-01

In this paper, we report on the results of a study that was conducted to examine how users suffering from severe upper-extremity disabilities can control a 6 degrees-of-freedom (DOF) robotics arm to complete complex activities of daily living. The focus of the study is not on assessing the robot arm but on examining the human-robot interaction patterns. Three participants were recruited. Each participant was asked to perform three tasks: eating three pieces of pre-cut bread from a plate, drinking three sips of soup from a bowl, and opening a right-handed door with lever handle. Each of these tasks was repeated three times. The arm was mounted on the participant's wheelchair, and the participants were free to move the arm as they wish to complete these tasks. Each task consisted of a sequence of modes where a mode is defined as arm movement in one DOF. Results show that participants used a total of 938 mode movements with an average of 75.5 (std 10.2) modes for the eating task, 70 (std 8.8) modes for the soup task, and 18.7 (std 4.5) modes for the door opening task. Tasks were then segmented into smaller subtasks. It was found that there are patterns of usage per participant and per subtask. These patterns can potentially allow a robot to learn from user's demonstration what is the task being executed and by whom and respond accordingly to reduce user effort.

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.

PubMed

Lindsay, Grace W; Rigotti, Mattia; Warden, Melissa R; Miller, Earl K; Fusi, Stefano

2017-11-08

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear "mixed" selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli-and in particular, to combinations of stimuli ("mixed selectivity")-is a topic of interest. Even though models with random feedforward connectivity are capable of creating computationally relevant mixed selectivity, such a model does not match the levels of mixed selectivity seen in the data analyzed in this study. Adding simple Hebbian learning to the model increases mixed selectivity to the correct level and makes the model match the data on several other relevant measures. This study thus offers predictions on how mixed selectivity and other properties evolve with training. Copyright © 2017 the authors 0270-6474/17/3711021-16$15.00/0.

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

PubMed Central

Lindsay, Grace W.

2017-01-01

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (“mixed selectivity”)—is a topic of interest. Even though models with random feedforward connectivity are capable of creating computationally relevant mixed selectivity, such a model does not match the levels of mixed selectivity seen in the data analyzed in this study. Adding simple Hebbian learning to the model increases mixed selectivity to the correct level and makes the model match the data on several other relevant measures. This study thus offers predictions on how mixed selectivity and other properties evolve with training. PMID:28986463

Sex and boldness explain individual differences in spatial learning in a lizard.

PubMed

Carazo, Pau; Noble, Daniel W A; Chandrasoma, Dani; Whiting, Martin J

2014-05-07

Understanding individual differences in cognitive performance is a major challenge to animal behaviour and cognition studies. We used the Eastern water skink (Eulamprus quoyii) to examine associations between exploration, boldness and individual variability in spatial learning, a dimension of lizard cognition with important bearing on fitness. We show that males perform better than females in a biologically relevant spatial learning task. This is the first evidence for sex differences in learning in a reptile, and we argue that it is probably owing to sex-specific selective pressures that may be widespread in lizards. Across the sexes, we found a clear association between boldness after a simulated predatory attack and the probability of learning the spatial task. In contrast to previous studies, we found a nonlinear association between boldness and learning: both 'bold' and 'shy' behavioural types were more successful learners than intermediate males. Our results do not fit with recent predictions suggesting that individual differences in learning may be linked with behavioural types via high-low-risk/reward trade-offs. We suggest the possibility that differences in spatial cognitive performance may arise in lizards as a consequence of the distinct environmental variability and complexity experienced by individuals as a result of their sex and social tactics.

Causal Learning in Gambling Disorder: Beyond the Illusion of Control.

PubMed

Perales, José C; Navas, Juan F; Ruiz de Lara, Cristian M; Maldonado, Antonio; Catena, Andrés

2017-06-01

Causal learning is the ability to progressively incorporate raw information about dependencies between events, or between one's behavior and its outcomes, into beliefs of the causal structure of the world. In spite of the fact that some cognitive biases in gambling disorder can be described as alterations of causal learning involving gambling-relevant cues, behaviors, and outcomes, general causal learning mechanisms in gamblers have not been systematically investigated. In the present study, we compared gambling disorder patients against controls in an instrumental causal learning task. Evidence of illusion of control, namely, overestimation of the relationship between one's behavior and an uncorrelated outcome, showed up only in gamblers with strong current symptoms. Interestingly, this effect was part of a more complex pattern, in which gambling disorder patients manifested a poorer ability to discriminate between null and positive contingencies. Additionally, anomalies were related to gambling severity and current gambling disorder symptoms. Gambling-related biases, as measured by a standard psychometric tool, correlated with performance in the causal learning task, but not in the expected direction. Indeed, performance of gamblers with stronger biases tended to resemble the one of controls, which could imply that anomalies of causal learning processes play a role in gambling disorder, but do not seem to underlie gambling-specific biases, at least in a simple, direct way.

The Impact of Deliberative Strategy Dissociates ERP Components Related to Conflict Processing vs. Reinforcement Learning

PubMed Central

Warren, Christopher M.; Holroyd, Clay B.

2012-01-01

We applied the event-related brain potential (ERP) technique to investigate the involvement of two neuromodulatory systems in learning and decision making: The locus coeruleus–norepinephrine system (NE system) and the mesencephalic dopamine system (DA system). We have previously presented evidence that the N2, a negative deflection in the ERP elicited by task-relevant events that begins approximately 200 ms after onset of the eliciting stimulus and that is sensitive to low-probability events, is a manifestation of cortex-wide noradrenergic modulation recruited to facilitate the processing of unexpected stimuli. Further, we hold that the impact of DA reinforcement learning signals on the anterior cingulate cortex (ACC) produces a component of the ERP called the feedback-related negativity (FRN). The N2 and the FRN share a similar time range, a similar topography, and similar antecedent conditions. We varied factors related to the degree of cognitive deliberation across a series of experiments to dissociate these two ERP components. Across four experiments we varied the demand for a deliberative strategy, from passively watching feedback, to more complex/challenging decision tasks. Consistent with our predictions, the FRN was largest in the experiment involving active learning and smallest in the experiment involving passive learning whereas the N2 exhibited the opposite effect. Within each experiment, when subjects attended to color, the N2 was maximal at frontal–central sites, and when they attended to gender it was maximal over lateral-occipital areas, whereas the topology of the FRN was frontal–central in both task conditions. We conclude that both the DA system and the NE system act in concert when learning from rewards that vary in expectedness, but that the DA system is relatively more exercised when subjects are relatively more engaged by the learning task. PMID:22493568

Using Formative Assessment to Support Complex Learning in Conditions of Social Adversity

ERIC Educational Resources Information Center

Crossouard, Barbara

2011-01-01

This article reports on research into formative assessment within a task design that produces multiple opportunities for teacher and pupil dialogue. It draws upon in-depth case studies conducted in schools in socially deprived areas of Scotland, using policy and documentary analysis, video-observation, and an iterative series of interviews with…

GiveMe Shelter: A People-Centred Design Process for Promoting Independent Inquiry-Led Learning in Engineering

ERIC Educational Resources Information Center

Dyer, Mark; Grey, Thomas; Kinnane, Oliver

2017-01-01

It has become increasingly common for tasks traditionally carried out by engineers to be undertaken by technicians and technologist with access to sophisticated computers and software that can often perform complex calculations that were previously the responsibility of engineers. Not surprisingly, this development raises serious questions about…

Development of a Handbook for Educators: Addressing Working Memory Capacity in Elementary Students

ERIC Educational Resources Information Center

Fernandez, Julie Marie

2013-01-01

Working Memory (WM) refers to a brain system that provides temporary storage and manipulation of the information necessary for complex cognitive tasks such as language comprehension, learning, and reasoning. WM also requires the simultaneous storage and processing of information. WM is directly related to academic performance in the classroom.…

Crossword Puzzles for Chemistry Education: Learning Goals beyond Vocabulary

ERIC Educational Resources Information Center

Yuriev, Elizabeth; Capuano, Ben; Short, Jennifer L.

2016-01-01

Chemistry is a technical scientific discipline strongly underpinned by its own complex and diverse language. To be successful in the problem-solving aspects of chemistry, students must master the language of chemistry, and in particular, the definition of terms and concepts. To assist students in this challenging task, a variety of instructional…

Making Sense of Learner Performance on Tests of Productive Vocabulary Knowledge

ERIC Educational Resources Information Center

Fitzpatrick, Tess; Clenton, Jon

2017-01-01

This article offers a solution to a significant problem for teachers and researchers of language learning that confounds their interpretations and expectations of test data: The apparent simplicity of tests of vocabulary knowledge masks the complexity of the constructs they claim to measure. The authors first scrutinise task elements in two widely…

Interesting and Difficult Mathematical Problems: Changing Teachers' Views by Employing Multiple-Solution Tasks

ERIC Educational Resources Information Center

Guberman, Raisa; Leikin, Roza

2013-01-01

The study considers mathematical problem solving to be at the heart of mathematics teaching and learning, while mathematical challenge is a core element of any educational process. The study design addresses the complexity of teachers' knowledge. It is aimed at exploring the development of teachers' mathematical and pedagogical conceptions…

A Framework for Semantic Group Formation in Education

ERIC Educational Resources Information Center

Ounnas, Asma; Davis, Hugh C.; Millard, David E.

2009-01-01

Collaboration has long been considered an effective approach to learning. However, forming optimal groups can be a time consuming and complex task. Different approaches have been developed to assist teachers allocate students to groups based on a set of constraints. However, existing tools often fail to assign some students to groups creating a…

Keep it Simple

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

Wiley, H. S.

2010-05-01

Creating a story for a particular audience is one of the most difficult tasks for anyone to learn. This is true for scientists and writers as well as any creative artist who tries to understand the complexity of the world and explain it to other people. Telling a good story always takes skill. Telling a popular story, however, requires simplification.

Integrated STEM: Focus on Informal Education and Community Collaboration through Engineering

ERIC Educational Resources Information Center

Burrows, Andrea; Lockwood, Meghan; Borowczak, Mike; Janak, Edward; Barber, Brian

2018-01-01

This article showcases STEM as an interdisciplinary field in which the disciplines strengthen and support each other (not as separate science, technology, engineering, and mathematics disciplines). The authors focus on an open-ended, complex problem--water quality--as the primary teaching and learning task. The participants, middle school female…

The Effects of Reinvestment of Conscious Processing on Switching Focus of Attention

ERIC Educational Resources Information Center

Weiss, Stephen M.

2011-01-01

The effects of switching focusing strategies on complex motor skill learning were investigated using a dart-throwing task. Participants were screened for reinvestment of conscious processing by completing the Reinvestment Scale (RS) of Masters, Polman, and Hammond (1993). After an initial baseline phase, two focusing strategies were described. Low…

Coral-View: A Network-Based Design Environment for Collaborative Learning

ERIC Educational Resources Information Center

Sun, Chuen-Tsai; Lin, Sunny S. J.

2004-01-01

The vast majority of complex engineering tasks in today's business world are completed using a team-oriented approach. Therefore, teaching collaborative skills to university students can be viewed as a practical means of enhancing their employability. With these goals in mind, the authors developed a network environment that helps Taiwanese…

Learner-Controlled Practice Difficulty in the Training of a Complex Task: Cognitive and Motivational Mechanisms

ERIC Educational Resources Information Center

Hughes, Michael G.; Day, Eric Anthony; Wang, Xiaoqian; Schuelke, Matthew J.; Arsenault, Matthew L.; Harkrider, Lauren N.; Cooper, Olivia D.

2013-01-01

An inherent aspect of learner-controlled instructional environments is the ability of learners to affect the degree of difficulty faced during training. However, research has yet to examine how learner-controlled practice difficulty affects learning. Based on the notion of "desirable difficulties" (Bjork, 1994), this study examined the…

Seeing the Forest and the Trees: Mapping Curricula to Enhance Student Success

ERIC Educational Resources Information Center

Parks, Rodney; Parrish, Jesse; Whitesell, Blake

2017-01-01

For today's registrar, disentangling the institutional curriculum can be a daunting task. The complex and interconnected learning that higher education institutions now strive for is highly desirable among millennial students, but even the most articulate curricula sometimes fail to represent it clearly. Whether navigating the registration system,…

Assessment Based on Serious Gaming Interactive Questions (SGIQ)

ERIC Educational Resources Information Center

Šimic, G.; Jevremovic, A.; Kostic, Z.; Ðordevic, D.

2015-01-01

The case study presented in this paper describes the pedagogical aspects and collected experience in using e-learning tool named IPA-PBL. Improving assessments in the preparation for AMET's (Air Medical Evacuation and Transport) complex task of transfer of injured or sick patients from the place of accident to the hospital or between hospitals…

Pitch Systems and Curwen Hand Signs: A Review of Literature

ERIC Educational Resources Information Center

Frey-Clark, Marta

2017-01-01

Learning to sing from notation is a complex task, and accurately performing pitches without an external reference can be particularly challenging. As such, the use of mnemonic devices to reinforce tonal relationships is a long-standing practice among musicians. Chief among these mnemonic devices are pitch syllable systems and Curwen hand signs.…

Changes in Information Processing with Aging: Implications for Teaching Motor Skills.

ERIC Educational Resources Information Center

Anshel, Mark H.

Although there are marked individual differences in the effect of aging on learning and performing motor skills, there is agreement that humans process information less efficiently with advanced age. Significant decrements have been found specifically with motor tasks that are characterized as externally-paced, rapid, complex, and requiring rapid…

An integrated utility-based model of conflict evaluation and resolution in the Stroop task.

PubMed

Chuderski, Adam; Smolen, Tomasz

2016-04-01

Cognitive control allows humans to direct and coordinate their thoughts and actions in a flexible way, in order to reach internal goals regardless of interference and distraction. The hallmark test used to examine cognitive control is the Stroop task, which elicits both the weakly learned but goal-relevant and the strongly learned but goal-irrelevant response tendencies, and requires people to follow the former while ignoring the latter. After reviewing the existing computational models of cognitive control in the Stroop task, its novel, integrated utility-based model is proposed. The model uses 3 crucial control mechanisms: response utility reinforcement learning, utility-based conflict evaluation using the Festinger formula for assessing the conflict level, and top-down adaptation of response utility in service of conflict resolution. Their complex, dynamic interaction led to replication of 18 experimental effects, being the largest data set explained to date by 1 Stroop model. The simulations cover the basic congruency effects (including the response latency distributions), performance dynamics and adaptation (including EEG indices of conflict), as well as the effects resulting from manipulations applied to stimulation and responding, which are yielded by the extant Stroop literature. (c) 2016 APA, all rights reserved).

Deep learning in pharmacogenomics: from gene regulation to patient stratification.

PubMed

Kalinin, Alexandr A; Higgins, Gerald A; Reamaroon, Narathip; Soroushmehr, Sayedmohammadreza; Allyn-Feuer, Ari; Dinov, Ivo D; Najarian, Kayvan; Athey, Brian D

2018-05-01

This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: identification of novel regulatory variants located in noncoding domains of the genome and their function as applied to pharmacoepigenomics; patient stratification from medical records; and the mechanistic prediction of drug response, targets and their interactions. Deep learning encapsulates a family of machine learning algorithms that has transformed many important subfields of artificial intelligence over the last decade, and has demonstrated breakthrough performance improvements on a wide range of tasks in biomedicine. We anticipate that in the future, deep learning will be widely used to predict personalized drug response and optimize medication selection and dosing, using knowledge extracted from large and complex molecular, epidemiological, clinical and demographic datasets.

TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

PubMed Central

2017-01-01

Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

Paradoxical effects of injection stress and nicotine exposure experienced during adolescence on learning in a serial multiple choice (SMC) task in adult female rats.

PubMed

Renaud, Samantha M; Pickens, Laura R G; Fountain, Stephen B

2015-01-01

Nicotine exposure in adolescent rats has been shown to cause learning impairments that persist into adulthood long after nicotine exposure has ended. This study was designed to assess the extent to which the effects of adolescent nicotine exposure on learning in adulthood can be accounted for by adolescent injection stress experienced concurrently with adolescent nicotine exposure. Female rats received either 0.033 mg/h nicotine (expressed as the weight of the free base) or bacteriostatic water vehicle by osmotic pump infusion on postnatal days 25-53 (P25-53). Half of the nicotine-exposed rats and half of the vehicle rats also received twice-daily injection stress consisting of intraperitoneal saline injections on P26-53. Together these procedures produced 4 groups: No Nicotine/No Stress, Nicotine/No Stress, No Nicotine/Stress, and Nicotine/Stress. On P65-99, rats were trained to perform a structurally complex 24-element serial pattern of responses in the serial multiple choice (SMC) task. Four general results were obtained in the current study. First, learning for within-chunk elements was not affected by either adolescent nicotine exposure, consistent with past work (Pickens, Rowan, Bevins, and Fountain, 2013), or adolescent injection stress. Thus, there were no effects of adolescent nicotine exposure or injection stress on adult within-chunk learning typically attributed to rule learning in the SMC task. Second, adolescent injection stress alone (i.e., without concurrent nicotine exposure) caused transient but significant facilitation of adult learning restricted to a single element of the 24-element pattern, namely, the "violation element," that was the only element of the pattern that was inconsistent with pattern structure. Thus, adolescent injection stress alone facilitated violation element acquisition in adulthood. Third, also consistent with past work (Pickens et al., 2013), adolescent nicotine exposure, in this case both with and without adolescent injection stress, caused a learning impairment in adulthood for the violation element in female rats. Thus, adolescent nicotine impaired adult violation element learning typically attributed to multiple-item learning in the SMC task. Fourth, a paradoxical interaction of injection stress and nicotine exposure in acquisition was observed. In the same female rats in which violation-element learning was impaired by adolescent nicotine exposure, adolescent nicotine experienced without adolescent injection stress produced better learning for chunk-boundary elements in adulthood compared to all other conditions. Thus, adolescent nicotine without concurrent injection stress facilitated adult chunk-boundary element learning typically attributed to concurrent stimulus-response discrimination learning and serial-position learning in the SMC task. To the best of our knowledge, the current study is the first to demonstrate facilitation of adult learning caused by adolescent nicotine exposure. Copyright © 2015 Elsevier Inc. All rights reserved.

Paradoxical Effects of Injection Stress and Nicotine Exposure Experienced During Adolescence on Learning in a Serial Multiple Choice (SMC) Task in Adult Female Rats

PubMed Central

Renaud, Samantha M.; Pickens, Laura R. G.; Fountain, Stephen B.

2015-01-01

Nicotine exposure in adolescent rats has been shown to cause learning impairments that persist into adulthood long after nicotine exposure has ended. This study was designed to assess the extent to which the effects of adolescent nicotine exposure on learning in adulthood can be accounted for by adolescent injection stress experienced concurrently with adolescent nicotine exposure. Female rats received either 0.033 mg/hr nicotine (expressed as the weight of the free base) or bacteriostatic water vehicle by osmotic pump infusion on postnatal days 25-53 (P25-53). Half of the nicotine-exposed rats and half of the vehicle rats also received twice-daily injection stress consisting of intraperitoneal saline injections on P26-53. Together these procedures produced 4 groups: No Nicotine / No Stress, Nicotine / No Stress, No Nicotine / Stress, and Nicotine / Stress. On P65-99, rats were trained to perform a structurally complex 24-element serial pattern of responses in the serial multiple choice (SMC) task. Four general results were obtained in the current study. First, learning for within-chunk elements was not affected by either adolescent nicotine exposure, consistent with past work (Pickens, Rowan, Bevins, & Fountain, 2013), or adolescent injection stress. Thus, there were no effects of adolescent nicotine exposure or injection stress on adult within-chunk learning typically attributed to rule learning in the SMC task. Second, adolescent injection stress alone (i.e., without concurrent nicotine exposure) caused transient but significant facilitation of adult learning restricted to a single element of the 24-element pattern, namely, the “violation element,” that was the only element of the pattern that was inconsistent with pattern structure. Thus, adolescent injection stress alone facilitated violation element acquisition in adulthood. Third, also consistent with past work (Pickens et al., 2013), adolescent nicotine exposure, in this case both with and without adolescent injection stress, caused a learning impairment in adulthood for the violation element in female rats. Thus, adolescent nicotine impaired adult violation element learning typically attributed to multiple-item learning in the SMC task. Fourth, a paradoxical interaction of injection stress and nicotine exposure in acquisition was observed. In the same female rats in which violation-element learning was impaired by adolescent nicotine exposure, adolescent nicotine experienced without adolescent injection stress produced better learning for chunk-boundary elements in adulthood compared to all other conditions. Thus, adolescent nicotine without concurrent injection stress facilitated adult chunk-boundary element learning typically attributed to concurrent stimulus-response discrimination learning and serial-position learning in the SMC task. To the best of our knowledge, the current study is the first to demonstrate facilitation of adult learning caused by adolescent nicotine exposure. PMID:25527003

Neural correlates of skill acquisition: decreased cortical activity during a serial interception sequence learning task.

PubMed

Gobel, Eric W; Parrish, Todd B; Reber, Paul J

2011-10-15

Learning of complex motor skills requires learning of component movements as well as the sequential structure of their order and timing. Using a Serial Interception Sequence Learning (SISL) task, participants learned a sequence of precisely timed interception responses through training with a repeating sequence. Following initial implicit learning of the repeating sequence, functional MRI data were collected during performance of that known sequence and compared with activity evoked during novel sequences of actions, novel timing patterns, or both. Reduced activity was observed during the practiced sequence in a distributed bilateral network including extrastriate occipital, parietal, and premotor cortical regions. These reductions in evoked activity likely reflect improved efficiency in visuospatial processing, spatio-motor integration, motor planning, and motor execution for the trained sequence, which is likely supported by nondeclarative skill learning. In addition, the practiced sequence evoked increased activity in the left ventral striatum and medial prefrontal cortex, while the posterior cingulate was more active during periods of better performance. Many prior studies of perceptual-motor skill learning have found increased activity in motor areas of the frontal cortex (e.g., motor and premotor cortex, SMA) and striatal areas (e.g., the putamen). The change in activity observed here (i.e., decreased activity across a cortical network) may reflect skill learning that is predominantly expressed through more accurate performance rather than decreased reaction time. Copyright © 2011 Elsevier Inc. All rights reserved.

Neural Correlates of Skill Acquisition: Decreased Cortical Activity During a Serial Interception Sequence Learning Task

PubMed Central

Gobel, Eric W.; Parrish, Todd B.; Reber, Paul J.

2011-01-01

Learning of complex motor skills requires learning of component movements as well as the sequential structure of their order and timing. Using a Serial Interception Sequence Learning (SISL) task, participants learned a sequence of precisely timed interception responses through training with a repeating sequence. Following initial implicit learning of the repeating sequence, functional MRI data were collected during performance of that known sequence and compared with activity evoked during novel sequences of actions, novel timing patterns, or both. Reduced activity was observed during the practiced sequence in a distributed bilateral network including extrastriate occipital, parietal, and premotor cortical regions. These reductions in evoked activity likely reflect improved efficiency in visuospatial processing, spatio-motor integration, motor planning, and motor execution for the trained sequence, which is likely supported by nondeclarative skill learning. In addition, the practiced sequence evoked increased activity in the left ventral striatum and medial prefrontal cortex, while the posterior cingulate was more active during periods of better performance. Many prior studies of perceptual-motor skill learning have found increased activity in motor areas of frontal cortex (e.g., motor and premotor cortex, SMA) and striatal areas (e.g., the putamen). The change in activity observed here (i.e., decreased activity across a cortical network) may reflect skill learning that is predominantly expressed through more accurate performance rather than decreased reaction time. PMID:21771663

Implications of complex adaptive systems theory for interpreting research about health care organizations.

PubMed

Jordon, Michelle; Lanham, Holly Jordan; Anderson, Ruth A; McDaniel, Reuben R

2010-02-01

Data about health care organizations (HCOs) are not useful until they are interpreted. Such interpretations are influenced by the theoretical lenses used by the researcher. Our purpose was to suggest the usefulness of theories of complex adaptive systems (CASs) in guiding research interpretation. Specifically, we addressed two questions: (1) What are the implications for interpreting research observations in HCOs of the fact that we are observing relationships among diverse agents? (2) What are the implications for interpreting research observations in HCOs of the fact that we are observing relationships among agents that learn? We defined diversity and learning and the implications of the non-linear relationships among agents from a CAS perspective. We then identified some common analytical practices that were problematic and may lead to conceptual and methodological errors. Then we described strategies for interpreting the results of research observations. We suggest that the task of interpreting research observations of HCOs could be improved if researchers take into account that the systems they study are CASs with non-linear relationships among diverse, learning agents. Our analysis points out how interpretation of research results might be shaped by the fact that HCOs are CASs. We described how learning is, in fact, the result of interactions among diverse agents and that learning can, by itself, reduce or increase agent diversity. We encouraged researchers to be persistent in their attempts to reason about complex systems and learn to attend not only to structures, but also to processes and functions of complex systems.

Virtual navigation performance: the relationship to field of view and prior video gaming experience.

PubMed

Richardson, Anthony E; Collaer, Marcia L

2011-04-01

Two experiments examined whether learning a virtual environment was influenced by field of view and how it related to prior video gaming experience. In the first experiment, participants (42 men, 39 women; M age = 19.5 yr., SD = 1.8) performed worse on a spatial orientation task displayed with a narrow field of view in comparison to medium and wide field-of-view displays. Counter to initial hypotheses, wide field-of-view displays did not improve performance over medium displays, and this was replicated in a second experiment (30 men, 30 women; M age = 20.4 yr., SD = 1.9) presenting a more complex learning environment. Self-reported video gaming experience correlated with several spatial tasks: virtual environment pointing and tests of Judgment of Line Angle and Position, mental rotation, and Useful Field of View (with correlations between .31 and .45). When prior video gaming experience was included as a covariate, sex differences in spatial tasks disappeared.

Multiple memory stores and operant conditioning: a rationale for memory's complexity.

PubMed

Meeter, Martijn; Veldkamp, Rob; Jin, Yaochu

2009-02-01

Why does the brain contain more than one memory system? Genetic algorithms can play a role in elucidating this question. Here, model animals were constructed containing a dorsal striatal layer that controlled actions, and a ventral striatal layer that controlled a dopaminergic learning signal. Both layers could gain access to three modeled memory stores, but such access was penalized as energy expenditure. Model animals were then selected on their fitness in simulated operant conditioning tasks. Results suggest that having access to multiple memory stores and their representations is important in learning to regulate dopamine release, as well as in contextual discrimination. For simple operant conditioning, as well as stimulus discrimination, hippocampal compound representations turned out to suffice, a counterintuitive result given findings that hippocampal lesions tend not to affect performance in such tasks. We argue that there is in fact evidence to support a role for compound representations and the hippocampus in even the simplest conditioning tasks.

Motor Task Variation Induces Structural Learning

PubMed Central

Braun, Daniel A.; Aertsen, Ad; Wolpert, Daniel M.; Mehring, Carsten

2009-01-01

Summary When we have learned a motor skill, such as cycling or ice-skating, we can rapidly generalize to novel tasks, such as motorcycling or rollerblading [1–8]. Such facilitation of learning could arise through two distinct mechanisms by which the motor system might adjust its control parameters. First, fast learning could simply be a consequence of the proximity of the original and final settings of the control parameters. Second, by structural learning [9–14], the motor system could constrain the parameter adjustments to conform to the control parameters' covariance structure. Thus, facilitation of learning would rely on the novel task parameters' lying on the structure of a lower-dimensional subspace that can be explored more efficiently. To test between these two hypotheses, we exposed subjects to randomly varying visuomotor tasks of fixed structure. Although such randomly varying tasks are thought to prevent learning, we show that when subsequently presented with novel tasks, subjects exhibit three key features of structural learning: facilitated learning of tasks with the same structure, strong reduction in interference normally observed when switching between tasks that require opposite control strategies, and preferential exploration along the learned structure. These results suggest that skill generalization relies on task variation and structural learning. PMID:19217296

Motor task variation induces structural learning.

PubMed

Braun, Daniel A; Aertsen, Ad; Wolpert, Daniel M; Mehring, Carsten

2009-02-24

When we have learned a motor skill, such as cycling or ice-skating, we can rapidly generalize to novel tasks, such as motorcycling or rollerblading [1-8]. Such facilitation of learning could arise through two distinct mechanisms by which the motor system might adjust its control parameters. First, fast learning could simply be a consequence of the proximity of the original and final settings of the control parameters. Second, by structural learning [9-14], the motor system could constrain the parameter adjustments to conform to the control parameters' covariance structure. Thus, facilitation of learning would rely on the novel task parameters' lying on the structure of a lower-dimensional subspace that can be explored more efficiently. To test between these two hypotheses, we exposed subjects to randomly varying visuomotor tasks of fixed structure. Although such randomly varying tasks are thought to prevent learning, we show that when subsequently presented with novel tasks, subjects exhibit three key features of structural learning: facilitated learning of tasks with the same structure, strong reduction in interference normally observed when switching between tasks that require opposite control strategies, and preferential exploration along the learned structure. These results suggest that skill generalization relies on task variation and structural learning.

BDNF Val66Met polymorphism is associated with abnormal interhemispheric transfer of a newly acquired motor skill.

PubMed

Morin-Moncet, Olivier; Beaumont, Vincent; de Beaumont, Louis; Lepage, Jean-Francois; Théoret, Hugo

2014-05-01

Recent data suggest that the Val66Met polymorphism of the brain-derived neurotrophic factor (BDNF) gene can alter cortical plasticity within the motor cortex of carriers, which exhibits abnormally low rates of cortical reorganization after repetitive motor tasks. To verify whether long-term retention of a motor skill is also modulated by the presence of the polymorphism, 20 participants (10 Val66Val, 10 Val66Met) were tested twice at a 1-wk interval. During each visit, excitability of the motor cortex was measured by transcranial magnetic stimulations (TMS) before and after performance of a procedural motor learning task (serial reaction time task) designed to study sequence-specific learning of the right hand and sequence-specific transfer from the right to the left hand. Behavioral results showed a motor learning effect that persisted for at least a week and task-related increases in corticospinal excitability identical for both sessions and without distinction for genetic group. Sequence-specific transfer of the motor skill from the right hand to the left hand was greater in session 2 than in session 1 only in the Val66Met genetic group. Further analysis revealed that the sequence-specific transfer occurred equally at both sessions in the Val66Val genotype group. In the Val66Met genotype group, sequence-specific transfer did not occur at session 1 but did at session 2. These data suggest a limited impact of Val66Met polymorphism on the learning and retention of a complex motor skill and its associated changes in corticospinal excitability over time, and a possible modulation of the interhemispheric transfer of procedural learning. Copyright © 2014 the American Physiological Society.

Improving Grasp Skills Using Schema Structured Learning

NASA Technical Reports Server (NTRS)

Platt, Robert; Grupen, ROderic A.; Fagg, Andrew H.

2006-01-01

Abstract In the control-based approach to robotics, complex behavior is created by sequencing and combining control primitives. While it is desirable for the robot to autonomously learn the correct control sequence, searching through the large number of potential solutions can be time consuming. This paper constrains this search to variations of a generalized solution encoded in a framework known as an action schema. A new algorithm, SCHEMA STRUCTURED LEARNING, is proposed that repeatedly executes variations of the generalized solution in search of instantiations that satisfy action schema objectives. This approach is tested in a grasping task where Dexter, the UMass humanoid robot, learns which reaching and grasping controllers maximize the probability of grasp success.

Amplifying human ability through autonomics and machine learning in IMPACT

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Interleaved Practice in Multi-Dimensional Learning Tasks: Which Dimension Should We Interleave?

ERIC Educational Resources Information Center

Rau, Martina A.; Aleven, Vincent; Rummel, Nikol

2013-01-01

Research shows that multiple representations can enhance student learning. Many curricula use multiple representations across multiple task types. The temporal sequence of representations and task types is likely to impact student learning. Research on contextual interference shows that interleaving learning tasks leads to better learning results…

A deep learning approach for fetal QRS complex detection.

PubMed

Zhong, Wei; Liao, Lijuan; Guo, Xuemei; Wang, Guoli

2018-04-20

Non-invasive foetal electrocardiography (NI-FECG) has the potential to provide more additional clinical information for detecting and diagnosing fetal diseases. We propose and demonstrate a deep learning approach for fetal QRS complex detection from raw NI-FECG signals by using a convolutional neural network (CNN) model. The main objective is to investigate whether reliable fetal QRS complex detection performance can still be obtained from features of single-channel NI-FECG signals, without canceling maternal ECG (MECG) signals. A deep learning method is proposed for recognizing fetal QRS complexes. Firstly, we collect data from set-a of the PhysioNet/computing in Cardiology Challenge database. The sample entropy method is used for signal quality assessment. Part of the bad quality signals is excluded in the further analysis. Secondly, in the proposed method, the features of raw NI-FECG signals are normalized before they are fed to a CNN classifier to perform fetal QRS complex detection. We use precision, recall, F-measure and accuracy as the evaluation metrics to assess the performance of fetal QRS complex detection. The proposed deep learning method can achieve relatively high precision (75.33%), recall (80.54%), and F-measure scores (77.85%) compared with three other well-known pattern classification methods, namely KNN, naive Bayes and SVM. the proposed deep learning method can attain reliable fetal QRS complex detection performance from the raw NI-FECG signals without canceling MECG signals. In addition, the influence of different activation functions and signal quality assessment on classification performance are evaluated, and results show that Relu outperforms the Sigmoid and Tanh on this particular task, and better classification performance is obtained with the signal quality assessment step in this study.

Speech Motor Sequence Learning: Effect of Parkinson Disease and Normal Aging on Dual-Task Performance.

PubMed

Whitfield, Jason A; Goberman, Alexander M

2017-06-22

Everyday communication is carried out concurrently with other tasks. Therefore, determining how dual tasks interfere with newly learned speech motor skills can offer insight into the cognitive mechanisms underlying speech motor learning in Parkinson disease (PD). The current investigation examines a recently learned speech motor sequence under dual-task conditions. A previously learned sequence of 6 monosyllabic nonwords was examined using a dual-task paradigm. Participants repeated the sequence while concurrently performing a visuomotor task, and performance on both tasks was measured in single- and dual-task conditions. The younger adult group exhibited little to no dual-task interference on the accuracy and duration of the sequence. The older adult group exhibited variability in dual-task costs, with the group as a whole exhibiting an intermediate, though significant, amount of dual-task interference. The PD group exhibited the largest degree of bidirectional dual-task interference among all the groups. These data suggest that PD affects the later stages of speech motor learning, as the dual-task condition interfered with production of the recently learned sequence beyond the effect of normal aging. Because the basal ganglia is critical for the later stages of motor sequence learning, the observed deficits may result from the underlying neural dysfunction associated with PD.

ACTIVIS: Visual Exploration of Industry-Scale Deep Neural Network Models.

PubMed

Kahng, Minsuk; Andrews, Pierre Y; Kalro, Aditya; Polo Chau, Duen Horng

2017-08-30

While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ACTIVIS, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance- and subset-level. ACTIVIS has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ACTIVIS may work with different models.

Context transfer in reinforcement learning using action-value functions.

PubMed

Mousavi, Amin; Nadjar Araabi, Babak; Nili Ahmadabadi, Majid

2014-01-01

This paper discusses the notion of context transfer in reinforcement learning tasks. Context transfer, as defined in this paper, implies knowledge transfer between source and target tasks that share the same environment dynamics and reward function but have different states or action spaces. In other words, the agents learn the same task while using different sensors and actuators. This requires the existence of an underlying common Markov decision process (MDP) to which all the agents' MDPs can be mapped. This is formulated in terms of the notion of MDP homomorphism. The learning framework is Q-learning. To transfer the knowledge between these tasks, the feature space is used as a translator and is expressed as a partial mapping between the state-action spaces of different tasks. The Q-values learned during the learning process of the source tasks are mapped to the sets of Q-values for the target task. These transferred Q-values are merged together and used to initialize the learning process of the target task. An interval-based approach is used to represent and merge the knowledge of the source tasks. Empirical results show that the transferred initialization can be beneficial to the learning process of the target task.

Context Transfer in Reinforcement Learning Using Action-Value Functions

PubMed Central

Mousavi, Amin; Nadjar Araabi, Babak; Nili Ahmadabadi, Majid

2014-01-01

This paper discusses the notion of context transfer in reinforcement learning tasks. Context transfer, as defined in this paper, implies knowledge transfer between source and target tasks that share the same environment dynamics and reward function but have different states or action spaces. In other words, the agents learn the same task while using different sensors and actuators. This requires the existence of an underlying common Markov decision process (MDP) to which all the agents' MDPs can be mapped. This is formulated in terms of the notion of MDP homomorphism. The learning framework is Q-learning. To transfer the knowledge between these tasks, the feature space is used as a translator and is expressed as a partial mapping between the state-action spaces of different tasks. The Q-values learned during the learning process of the source tasks are mapped to the sets of Q-values for the target task. These transferred Q-values are merged together and used to initialize the learning process of the target task. An interval-based approach is used to represent and merge the knowledge of the source tasks. Empirical results show that the transferred initialization can be beneficial to the learning process of the target task. PMID:25610457

The Brain as an Efficient and Robust Adaptive Learner.

PubMed

Denève, Sophie; Alemi, Alireza; Bourdoukan, Ralph

2017-06-07

Understanding how the brain learns to compute functions reliably, efficiently, and robustly with noisy spiking activity is a fundamental challenge in neuroscience. Most sensory and motor tasks can be described as dynamical systems and could presumably be learned by adjusting connection weights in a recurrent biological neural network. However, this is greatly complicated by the credit assignment problem for learning in recurrent networks, e.g., the contribution of each connection to the global output error cannot be determined based only on locally accessible quantities to the synapse. Combining tools from adaptive control theory and efficient coding theories, we propose that neural circuits can indeed learn complex dynamic tasks with local synaptic plasticity rules as long as they associate two experimentally established neural mechanisms. First, they should receive top-down feedbacks driving both their activity and their synaptic plasticity. Second, inhibitory interneurons should maintain a tight balance between excitation and inhibition in the circuit. The resulting networks could learn arbitrary dynamical systems and produce irregular spike trains as variable as those observed experimentally. Yet, this variability in single neurons may hide an extremely efficient and robust computation at the population level. Copyright © 2017 Elsevier Inc. All rights reserved.

A stable biologically motivated learning mechanism for visual feature extraction to handle facial categorization.

PubMed

Rajaei, Karim; Khaligh-Razavi, Seyed-Mahdi; Ghodrati, Masoud; Ebrahimpour, Reza; Shiri Ahmad Abadi, Mohammad Ebrahim

2012-01-01

The brain mechanism of extracting visual features for recognizing various objects has consistently been a controversial issue in computational models of object recognition. To extract visual features, we introduce a new, biologically motivated model for facial categorization, which is an extension of the Hubel and Wiesel simple-to-complex cell hierarchy. To address the synaptic stability versus plasticity dilemma, we apply the Adaptive Resonance Theory (ART) for extracting informative intermediate level visual features during the learning process, which also makes this model stable against the destruction of previously learned information while learning new information. Such a mechanism has been suggested to be embedded within known laminar microcircuits of the cerebral cortex. To reveal the strength of the proposed visual feature learning mechanism, we show that when we use this mechanism in the training process of a well-known biologically motivated object recognition model (the HMAX model), it performs better than the HMAX model in face/non-face classification tasks. Furthermore, we demonstrate that our proposed mechanism is capable of following similar trends in performance as humans in a psychophysical experiment using a face versus non-face rapid categorization task.

Nonlinear pedagogy: an effective approach to cater for individual differences in learning a sports skill.

PubMed

Lee, Miriam Chang Yi; Chow, Jia Yi; Komar, John; Tan, Clara Wee Keat; Button, Chris

2014-01-01

Learning a sports skill is a complex process in which practitioners are challenged to cater for individual differences. The main purpose of this study was to explore the effectiveness of a Nonlinear Pedagogy approach for learning a sports skill. Twenty-four 10-year-old females participated in a 4-week intervention involving either a Nonlinear Pedagogy (i.e.,manipulation of task constraints including equipment and rules) or a Linear Pedagogy (i.e., prescriptive, repetitive drills) approach to learn a tennis forehand stroke. Performance accuracy scores, movement criterion scores and kinematic data were measured during pre-intervention, post-intervention and retention tests. While both groups showed improvements in performance accuracy scores over time, the Nonlinear Pedagogy group displayed a greater number of movement clusters at post-test indicating the presence of degeneracy (i.e., many ways to achieve the same outcome). The results suggest that degeneracy is effective for learning a sports skill facilitated by a Nonlinear Pedagogy approach. These findings challenge the common misconception that there must be only one ideal movement solution for a task and thus have implications for coaches and educators when designing instructions for skill acquisition.

Nonlinear Pedagogy: An Effective Approach to Cater for Individual Differences in Learning a Sports Skill

PubMed Central

Lee, Miriam Chang Yi; Chow, Jia Yi; Komar, John; Tan, Clara Wee Keat; Button, Chris

2014-01-01

Learning a sports skill is a complex process in which practitioners are challenged to cater for individual differences. The main purpose of this study was to explore the effectiveness of a Nonlinear Pedagogy approach for learning a sports skill. Twenty-four 10-year-old females participated in a 4-week intervention involving either a Nonlinear Pedagogy (i.e.,manipulation of task constraints including equipment and rules) or a Linear Pedagogy (i.e., prescriptive, repetitive drills) approach to learn a tennis forehand stroke. Performance accuracy scores, movement criterion scores and kinematic data were measured during pre-intervention, post-intervention and retention tests. While both groups showed improvements in performance accuracy scores over time, the Nonlinear Pedagogy group displayed a greater number of movement clusters at post-test indicating the presence of degeneracy (i.e., many ways to achieve the same outcome). The results suggest that degeneracy is effective for learning a sports skill facilitated by a Nonlinear Pedagogy approach. These findings challenge the common misconception that there must be only one ideal movement solution for a task and thus have implications for coaches and educators when designing instructions for skill acquisition. PMID:25140822

A comparative study of deep learning models for medical image classification

NASA Astrophysics Data System (ADS)

Dutta, Suvajit; Manideep, B. C. S.; Rai, Shalva; Vijayarajan, V.

2017-11-01

Deep Learning(DL) techniques are conquering over the prevailing traditional approaches of neural network, when it comes to the huge amount of dataset, applications requiring complex functions demanding increase accuracy with lower time complexities. Neurosciences has already exploited DL techniques, thus portrayed itself as an inspirational source for researchers exploring the domain of Machine learning. DL enthusiasts cover the areas of vision, speech recognition, motion planning and NLP as well, moving back and forth among fields. This concerns with building models that can successfully solve variety of tasks requiring intelligence and distributed representation. The accessibility to faster CPUs, introduction of GPUs-performing complex vector and matrix computations, supported agile connectivity to network. Enhanced software infrastructures for distributed computing worked in strengthening the thought that made researchers suffice DL methodologies. The paper emphases on the following DL procedures to traditional approaches which are performed manually for classifying medical images. The medical images are used for the study Diabetic Retinopathy(DR) and computed tomography (CT) emphysema data. Both DR and CT data diagnosis is difficult task for normal image classification methods. The initial work was carried out with basic image processing along with K-means clustering for identification of image severity levels. After determining image severity levels ANN has been applied on the data to get the basic classification result, then it is compared with the result of DNNs (Deep Neural Networks), which performed efficiently because of its multiple hidden layer features basically which increases accuracy factors, but the problem of vanishing gradient in DNNs made to consider Convolution Neural Networks (CNNs) as well for better results. The CNNs are found to be providing better outcomes when compared to other learning models aimed at classification of images. CNNs are favoured as they provide better visual processing models successfully classifying the noisy data as well. The work centres on the detection on Diabetic Retinopathy-loss in vision and recognition of computed tomography (CT) emphysema data measuring the severity levels for both cases. The paper discovers how various Machine Learning algorithms can be implemented ensuing a supervised approach, so as to get accurate results with less complexity possible.

Sustained increase in hippocampal sharp-wave ripple activity during slow-wave sleep after learning

PubMed Central

Eschenko, Oxana; Ramadan, Wiâm; Mölle, Matthias; Born, Jan; Sara, Susan J.

2008-01-01

High-frequency oscillations, known as sharp-wave/ripple (SPW-R) complexes occurring in hippocampus during slow-wave sleep (SWS), have been proposed to promote synaptic plasticity necessary for memory consolidation. We recorded sleep for 3 h after rats were trained on an odor-reward association task. Learning resulted in an increased number SPW-Rs during the first hour of post-learning SWS. The magnitude of ripple events and their duration were also elevated for up to 2 h after the newly formed memory. Rats that did not learn the discrimination during the training session did not show any change in SPW-Rs. Successful retrieval from remote memory was likewise accompanied by an increase in SPW-R density and magnitude, relative to the previously recorded baseline, but the effects were much shorter lasting and did not include increases in ripple duration and amplitude. A short-lasting increase of ripple activity was also observed when rats were rewarded for performing a motor component of the task only. There were no increases in ripple activity after habituation to the experimental environment. These experiments show that the characteristics of hippocampal high-frequency oscillations during SWS are affected by prior behavioral experience. Associative learning induces robust and sustained (up to 2 h) changes in several SPW-R characteristics, while after retrieval from remote memory or performance of a well-trained procedural aspect of the task, only transient changes in ripple density were induced. PMID:18385477

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.

Computational Modeling for Language Acquisition: A Tutorial With Syntactic Islands.

PubMed

Pearl, Lisa S; Sprouse, Jon

2015-06-01

Given the growing prominence of computational modeling in the acquisition research community, we present a tutorial on how to use computational modeling to investigate learning strategies that underlie the acquisition process. This is useful for understanding both typical and atypical linguistic development. We provide a general overview of why modeling can be a particularly informative tool and some general considerations when creating a computational acquisition model. We then review a concrete example of a computational acquisition model for complex structural knowledge referred to as syntactic islands. This includes an overview of syntactic islands knowledge, a precise definition of the acquisition task being modeled, the modeling results, and how to meaningfully interpret those results in a way that is relevant for questions about knowledge representation and the learning process. Computational modeling is a powerful tool that can be used to understand linguistic development. The general approach presented here can be used to investigate any acquisition task and any learning strategy, provided both are precisely defined.