Quantifying transfer after perceptual-motor sequence learning: how inflexible is implicit learning?

PubMed Central

Sanchez, Daniel J.; Yarnik, Eric N.

2015-01-01

Studies of implicit perceptual-motor sequence learning have often shown learning to be inflexibly tied to the training conditions during learning. Since sequence learning is seen as a model task of skill acquisition, limits on the ability to transfer knowledge from the training context to a performance context indicates important constraints on skill learning approaches. Lack of transfer across contexts has been demonstrated by showing that when task elements are changed following training, this leads to a disruption in performance. These results have typically been taken as suggesting that the sequence knowledge relies on integrated representations across task elements (Abrahamse, Jiménez, Verwey, & Clegg, Psychon Bull Rev 17:603–623, 2010a). Using a relatively new sequence learning task, serial interception sequence learning, three experiments are reported that quantify this magnitude of performance disruption after selectively manipulating individual aspects of motor performance or perceptual information. In Experiment 1, selective disruption of the timing or order of sequential actions was examined using a novel response manipulandum that allowed for separate analysis of these two motor response components. In Experiments 2 and 3, transfer was examined after selective disruption of perceptual information that left the motor response sequence intact. All three experiments provided quantifiable estimates of partial transfer to novel contexts that suggest some level of information integration across task elements. However, the ability to identify quantifiable levels of successful transfer indicates that integration is not all-or-none and that measurement sensitivity is a key in understanding sequence knowledge representations. PMID:24668505

Sleep and memory consolidation: motor performance and proactive interference effects in sequence learning.

PubMed

Borragán, Guillermo; Urbain, Charline; Schmitz, Rémy; Mary, Alison; Peigneux, Philippe

2015-04-01

That post-training sleep supports the consolidation of sequential motor skills remains debated. Performance improvement and sensitivity to proactive interference are both putative measures of long-term memory consolidation. We tested sleep-dependent memory consolidation for visuo-motor sequence learning using a proactive interference paradigm. Thirty-three young adults were trained on sequence A on Day 1, then had Regular Sleep (RS) or were Sleep Deprived (SD) on the night after learning. After two recovery nights, they were tested on the same sequence A, then had to learn a novel, potentially competing sequence B. We hypothesized that proactive interference effects on sequence B due to the prior learning of sequence A would be higher in the RS condition, considering that proactive interference is an indirect marker of the robustness of sequence A, which should be better consolidated over post-training sleep. Results highlighted sleep-dependent improvement for sequence A, with faster RTs overnight for RS participants only. Moreover, the beneficial impact of sleep was specific to the consolidation of motor but not sequential skills. Proactive interference effects on learning a new material at Day 4 were similar between RS and SD participants. These results suggest that post-training sleep contributes to optimizing motor but not sequential components of performance in visuo-motor sequence learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Learned Non-Rigid Object Motion is a View-Invariant Cue to Recognizing Novel Objects

PubMed Central

Chuang, Lewis L.; Vuong, Quoc C.; Bülthoff, Heinrich H.

2012-01-01

There is evidence that observers use learned object motion to recognize objects. For instance, studies have shown that reversing the learned direction in which a rigid object rotated in depth impaired recognition accuracy. This motion reversal can be achieved by playing animation sequences of moving objects in reverse frame order. In the current study, we used this sequence-reversal manipulation to investigate whether observers encode the motion of dynamic objects in visual memory, and whether such dynamic representations are encoded in a way that is dependent on the viewing conditions. Participants first learned dynamic novel objects, presented as animation sequences. Following learning, they were then tested on their ability to recognize these learned objects when their animation sequence was shown in the same sequence order as during learning or in the reverse sequence order. In Experiment 1, we found that non-rigid motion contributed to recognition performance; that is, sequence-reversal decreased sensitivity across different tasks. In subsequent experiments, we tested the recognition of non-rigidly deforming (Experiment 2) and rigidly rotating (Experiment 3) objects across novel viewpoints. Recognition performance was affected by viewpoint changes for both experiments. Learned non-rigid motion continued to contribute to recognition performance and this benefit was the same across all viewpoint changes. By comparison, learned rigid motion did not contribute to recognition performance. These results suggest that non-rigid motion provides a source of information for recognizing dynamic objects, which is not affected by changes to viewpoint. PMID:22661939

Ego depletion impairs implicit learning.

PubMed

Thompson, Kelsey R; Sanchez, Daniel J; Wesley, Abigail H; Reber, Paul J

2014-01-01

Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing) can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL) task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent.

Ego Depletion Impairs Implicit Learning

PubMed Central

Thompson, Kelsey R.; Sanchez, Daniel J.; Wesley, Abigail H.; Reber, Paul J.

2014-01-01

Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing) can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL) task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent. PMID:25275517

The neural correlates of implicit sequence learning in schizophrenia.

PubMed

Marvel, Cherie L; Turner, Beth M; O'Leary, Daniel S; Johnson, Hans J; Pierson, Ronald K; Ponto, Laura L Boles; Andreasen, Nancy C

2007-11-01

Twenty-seven schizophrenia spectrum patients and 25 healthy controls performed a probabilistic version of the serial reaction time task (SRT) that included sequence trials embedded within random trials. Patients showed diminished, yet measurable, sequence learning. Postexperimental analyses revealed that a group of patients performed above chance when generating short spans of the sequence. This high-generation group showed SRT learning that was similar in magnitude to that of controls. Their learning was evident from the very 1st block; however, unlike controls, learning did not develop further with continued testing. A subset of 12 patients and 11 controls performed the SRT in conjunction with positron emission tomography. High-generation performance, which corresponded to SRT learning in patients, correlated to activity in the premotor cortex and parahippocampus. These areas have been associated with stimulus-driven visuospatial processing. Taken together, these results suggest that a subset of patients who showed moderate success on the SRT used an explicit stimulus-driven strategy to process the sequential stimuli. This adaptive strategy facilitated sequence learning but may have interfered with conventional implicit learning of the overall stimulus pattern. PsycINFO Database Record (c) 2007 APA, all rights reserved.

Anticipation measures of sequence learning: manual versus oculomotor versions of the serial reaction time task.

PubMed

Vakil, Eli; Bloch, Ayala; Cohen, Haggar

2017-03-01

The serial reaction time (SRT) task has generated a very large amount of research. Nevertheless the debate continues as to the exact cognitive processes underlying implicit sequence learning. Thus, the first goal of this study is to elucidate the underlying cognitive processes enabling sequence acquisition. We therefore compared reaction time (RT) in sequence learning in a standard manual activated (MA) to that in an ocular activated (OA) version of the task, within a single experimental setting. The second goal is to use eye movement measures to compare anticipation, as an additional indication of sequence learning, between the two versions of the SRT. Performance of the group given the MA version of the task (n = 29) was compared with that of the group given the OA version (n = 30). The results showed that although overall, RT was faster for the OA group, the rate of sequence learning was similar to that of the MA group performing the standard version of the SRT. Because the stimulus-response association is automatic and exists prior to training in the OA task, the decreased reaction time in this version of the task reflects a purer measure of the sequence learning that occurs in the SRT task. The results of this study show that eye tracking anticipation can be measured directly and can serve as a direct measure of sequence learning. Finally, using the OA version of the SRT to study sequence learning presents a significant methodological contribution by making sequence learning studies possible among populations that struggle to perform manual responses.

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.

Disrupted implicit motor sequence learning in schizophrenia and bipolar disorder revealed with ambidextrous Serial Reaction Time Task.

PubMed

Chrobak, Adrian Andrzej; Siuda-Krzywicka, Katarzyna; Siwek, Grzegorz Przemysław; Tereszko, Anna; Janeczko, Weronika; Starowicz-Filip, Anna; Siwek, Marcin; Dudek, Dominika

2017-10-03

Impairment of implicit motor sequence learning was shown in schizophrenia (SZ) and, most recently, in bipolar disorder (BD), and was connected to cerebellar abnormalities. The goal of this study was to compare implicit motor sequence learning in BD and SZ. We examined 33 patients with BD, 33 patients with SZ and 31 healthy controls with a use of ambidextrous Serial Reaction Time Task (SRTT), which allows exploring asymmetries in performance depending on the hand used. BD and SZ patients presented impaired implicit motor sequence learning, although the pattern of their impairments was different. While BD patients showed no signs of implicit motor sequence learning for both hands, the SZ group presented some features of motor learning when performing with the right, but not with the left hand. To our best knowledge this is the first study comparing implicit motor sequence learning in BD and SZ. We show that both diseases share impairments in this domain, however in the case of SZ this impairment differs dependently on the hand performing SRTT. We propose that implicit motor sequence learning impairments constitute an overlapping symptom in BD and SZ and suggest further neuroimaging studies to verify cerebellar underpinnings as its cause. Copyright © 2017 Elsevier Inc. All rights reserved.

Speech and Nonspeech Sequence Skill Learning in Adults Who Stutter

ERIC Educational Resources Information Center

Smits-Bandstra, Sarah; De Nil, Luc; Saint-Cyr, Jean A.

2006-01-01

Two studies compared the speech and nonspeech sequence skill learning of nine persons who stutter (PWS) and nine matched fluent speakers (PNS). Sequence skill learning was defined as a continuing process of stable improvement in speed and/or accuracy of sequencing performance over practice and was measured by comparing PWS's and PNS's performance…

Consolidating the effects of waking and sleep on motor-sequence learning.

PubMed

Brawn, Timothy P; Fenn, Kimberly M; Nusbaum, Howard C; Margoliash, Daniel

2010-10-20

Sleep is widely believed to play a critical role in memory consolidation. Sleep-dependent consolidation has been studied extensively in humans using an explicit motor-sequence learning paradigm. In this task, performance has been reported to remain stable across wakefulness and improve significantly after sleep, making motor-sequence learning the definitive example of sleep-dependent enhancement. Recent work, however, has shown that enhancement disappears when the task is modified to reduce task-related inhibition that develops over a training session, thus questioning whether sleep actively consolidates motor learning. Here we use the same motor-sequence task to demonstrate sleep-dependent consolidation for motor-sequence learning and explain the discrepancies in results across studies. We show that when training begins in the morning, motor-sequence performance deteriorates across wakefulness and recovers after sleep, whereas performance remains stable across both sleep and subsequent waking with evening training. This pattern of results challenges an influential model of memory consolidation defined by a time-dependent stabilization phase and a sleep-dependent enhancement phase. Moreover, the present results support a new account of the behavioral effects of waking and sleep on explicit motor-sequence learning that is consistent across a wide range of tasks. These observations indicate that current theories of memory consolidation that have been formulated to explain sleep-dependent performance enhancements are insufficient to explain the range of behavioral changes associated with sleep.

Operating characteristics of the implicit learning system supporting serial interception sequence learning.

PubMed

Sanchez, Daniel J; Reber, Paul J

2012-04-01

The memory system that supports implicit perceptual-motor sequence learning relies on brain regions that operate separately from the explicit, medial temporal lobe memory system. The implicit learning system therefore likely has distinct operating characteristics and information processing constraints. To attempt to identify the limits of the implicit sequence learning mechanism, participants performed the serial interception sequence learning (SISL) task with covertly embedded repeating sequences that were much longer than most previous studies: ranging from 30 to 60 (Experiment 1) and 60 to 90 (Experiment 2) items in length. Robust sequence-specific learning was observed for sequences up to 80 items in length, extending the known capacity of implicit sequence learning. In Experiment 3, 12-item repeating sequences were embedded among increasing amounts of irrelevant nonrepeating sequences (from 20 to 80% of training trials). Despite high levels of irrelevant trials, learning occurred across conditions. A comparison of learning rates across all three experiments found a surprising degree of constancy in the rate of learning regardless of sequence length or embedded noise. Sequence learning appears to be constant with the logarithm of the number of sequence repetitions practiced during training. The consistency in learning rate across experiments and conditions implies that the mechanisms supporting implicit sequence learning are not capacity-constrained by very long sequences nor adversely affected by high rates of irrelevant sequences during training.

[Transposition errors during learning to reproduce a sequence by the right- and the left-hand movements: simulation of positional and movement coding].

PubMed

Liakhovetskiĭ, V A; Bobrova, E V; Skopin, G N

2012-01-01

Transposition errors during the reproduction of a hand movement sequence make it possible to receive important information on the internal representation of this sequence in the motor working memory. Analysis of such errors showed that learning to reproduce sequences of the left-hand movements improves the system of positional coding (coding ofpositions), while learning of the right-hand movements improves the system of vector coding (coding of movements). Learning of the right-hand movements after the left-hand performance involved the system of positional coding "imposed" by the left hand. Learning of the left-hand movements after the right-hand performance activated the system of vector coding. Transposition errors during learning to reproduce movement sequences can be explained by neural network using either vector coding or both vector and positional coding.

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.

Observation learning versus physical practice leads to different consolidation outcomes in a movement timing task.

PubMed

Trempe, Maxime; Sabourin, Maxime; Rohbanfard, Hassan; Proteau, Luc

2011-03-01

Motor learning is a process that extends beyond training sessions. Specifically, physical practice triggers a series of physiological changes in the CNS that are regrouped under the term "consolidation" (Stickgold and Walker 2007). These changes can result in between-session improvement or performance stabilization (Walker 2005). In a series of three experiments, we tested whether consolidation also occurs following observation. In Experiment 1, participants observed an expert model perform a sequence of arm movements. Although we found evidence of observation learning, no significant difference was revealed between participants asked to reproduce the observed sequence either 5 min or 24 h later (no between-session improvement). In Experiment 2, two groups of participants observed an expert model perform two distinct movement sequences (A and B) either 10 min or 8 h apart; participants then physically performed both sequences after a 24-h break. Participants in the 8-h group performed Sequence B less accurately compared to participants in the 5-min group, suggesting that the memory representation of the first sequence had been stabilized and that it interfered with the learning of the second sequence. Finally, in Experiment 3, the initial observation phase was replaced by a physical practice phase. In contrast with the results of Experiment 2, participants in the 8-h group performed Sequence B significantly more accurately compared to participants in the 5-min group. Together, our results suggest that the memory representation of a skill learned through observation undergoes consolidation. However, consolidation of an observed motor skill leads to distinct behavioural outcomes in comparison with physical practice.

Primary motor and premotor cortex in implicit sequence learning--evidence for competition between implicit and explicit human motor memory systems.

PubMed

Kantak, Shailesh S; Mummidisetty, Chaithanya K; Stinear, James W

2012-09-01

Implicit and explicit memory systems for motor skills compete with each other during and after motor practice. Primary motor cortex (M1) is known to be engaged during implicit motor learning, while dorsal premotor cortex (PMd) is critical for explicit learning. To elucidate the neural substrates underlying the interaction between implicit and explicit memory systems, adults underwent a randomized crossover experiment of anodal transcranial direct current stimulation (AtDCS) applied over M1, PMd or sham stimulation during implicit motor sequence (serial reaction time task, SRTT) practice. We hypothesized that M1-AtDCS during practice will enhance online performance and offline learning of the implicit motor sequence. In contrast, we also hypothesized that PMd-AtDCS will attenuate performance and retention of the implicit motor sequence. Implicit sequence performance was assessed at baseline, at the end of acquisition (EoA), and 24 h after practice (retention test, RET). M1-AtDCS during practice significantly improved practice performance and supported offline stabilization compared with Sham tDCS. Performance change from EoA to RET revealed that PMd-AtDCS during practice attenuated offline stabilization compared with M1-AtDCS and sham stimulation. The results support the role of M1 in implementing online performance gains and offline stabilization for implicit motor sequence learning. In contrast, enhancing the activity within explicit motor memory network nodes such as the PMd during practice may be detrimental to offline stabilization of the learned implicit motor sequence. These results support the notion of competition between implicit and explicit motor memory systems and identify underlying neural substrates that are engaged in this competition. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Decrease in gamma-band activity tracks sequence learning

PubMed Central

Madhavan, Radhika; Millman, Daniel; Tang, Hanlin; Crone, Nathan E.; Lenz, Fredrick A.; Tierney, Travis S.; Madsen, Joseph R.; Kreiman, Gabriel; Anderson, William S.

2015-01-01

Learning novel sequences constitutes an example of declarative memory formation, involving conscious recall of temporal events. Performance in sequence learning tasks improves with repetition and involves forming temporal associations over scales of seconds to minutes. To further understand the neural circuits underlying declarative sequence learning over trials, we tracked changes in intracranial field potentials (IFPs) recorded from 1142 electrodes implanted throughout temporal and frontal cortical areas in 14 human subjects, while they learned the temporal-order of multiple sequences of images over trials through repeated recall. We observed an increase in power in the gamma frequency band (30–100 Hz) in the recall phase, particularly in areas within the temporal lobe including the parahippocampal gyrus. The degree of this gamma power enhancement decreased over trials with improved sequence recall. Modulation of gamma power was directly correlated with the improvement in recall performance. When presenting new sequences, gamma power was reset to high values and decreased again after learning. These observations suggest that signals in the gamma frequency band may play a more prominent role during the early steps of the learning process rather than during the maintenance of memory traces. PMID:25653598

Sequence Learning and Selection Difficulty

ERIC Educational Resources Information Center

Rowland, Lee A.; Shanks, David R.

2006-01-01

The authors studied the role of attention as a selection mechanism in implicit learning by examining the effect on primary sequence learning of performing a demanding target-selection task. Participants were trained on probabilistic sequences in a novel version of the serial reaction time (SRT) task, with dual- and triple-stimulus participants…

[Learning and Repetive Reproduction of Memorized Sequences by the Right and the Left Hand].

PubMed

Bobrova, E V; Lyakhovetskii, V A; Bogacheva, I N

2015-01-01

An important stage of learning a new skill is repetitive reproduction of one and the same sequence of movements, which plays a significant role in forming of the movement stereotypes. Two groups of right-handers repeatedly memorized (6-10 repetitions) the sequences of their hand transitions by experimenter in 6 positions, firstly by the right hand (RH), and then--by the left hand (LH) or vice versa. Random sequences previously unknown to the volunteers were reproduced in the 11 series. Modified sequences were tested in the 2nd and 3rd series, where the same elements' positions were presented in different order. The processes of repetitive sequence reproduction were similar for RH and LH. However, the learning of the modified sequences differed: Information about elements' position disregarding the reproduction order was used only when LH initiated task performing. This information was not used when LH followed RH and when RH performed the task. Consequently, the type of information coding activated by LH helped learn the positions of sequence elements, while the type of information coding activated by RH prevented learning. It is supposedly connected with the predominant role of right hemisphere in the processes of positional coding and motor learning.

Commonly-occurring polymorphisms in the COMT, DRD1 and DRD2 genes influence different aspects of motor sequence learning in humans.

PubMed

Baetu, Irina; Burns, Nicholas R; Urry, Kristi; Barbante, Girolamo Giovanni; Pitcher, Julia B

2015-11-01

Performing sequences of movements is a ubiquitous skill that involves dopamine transmission. However, it is unclear which components of the dopamine system contribute to which aspects of motor sequence learning. Here we used a genetic approach to investigate the relationship between different components of the dopamine system and specific aspects of sequence learning in humans. In particular, we investigated variations in genes that code for the catechol-O-methyltransferase (COMT) enzyme, the dopamine transporter (DAT) and dopamine D1 and D2 receptors (DRD1 and DRD2). COMT and the DAT regulate dopamine availability in the prefrontal cortex and the striatum, respectively, two key regions recruited during learning, whereas dopamine D1 and D2 receptors are thought to be involved in long-term potentiation and depression, respectively. We show that polymorphisms in the COMT, DRD1 and DRD2 genes differentially affect behavioral performance on a sequence learning task in 161 Caucasian participants. The DRD1 polymorphism predicted the ability to learn new sequences, the DRD2 polymorphism predicted the ability to perform a previously learnt sequence after performing interfering random movements, whereas the COMT polymorphism predicted the ability to switch flexibly between two sequences. We used computer simulations to explore potential mechanisms underlying these effects, which revealed that the DRD1 and DRD2 effects are possibly related to neuroplasticity. Our prediction-error algorithm estimated faster rates of connection strengthening in genotype groups with presumably higher D1 receptor densities, and faster rates of connection weakening in genotype groups with presumably higher D2 receptor densities. Consistent with current dopamine theories, these simulations suggest that D1-mediated neuroplasticity contributes to learning to select appropriate actions, whereas D2-mediated neuroplasticity is involved in learning to inhibit incorrect action plans. However, the learning algorithm did not account for the COMT effect, suggesting that prefrontal dopamine availability might affect sequence switching via other, non-learning, mechanisms. These findings provide insight into the function of the dopamine system, which is relevant to the development of treatments for disorders such as Parkinson's disease. Our results suggest that treatments targeting dopamine D1 receptors may improve learning of novel sequences, whereas those targeting dopamine D2 receptors may improve the ability to initiate previously learned sequences of movements. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Healthy older adults demonstrate generalized postural motor learning in response to variable amplitude oscillations of the support surface

PubMed Central

Van Ooteghem, Karen; Frank, James S.; Allard, Fran; Horak, Fay B

2011-01-01

Postural motor learning for dynamic balance tasks has been demonstrated in healthy older adults (Van Ooteghem et al. 2009). The purpose of this study was to investigate the type of knowledge (general or specific) obtained with balance training in this age group and to examine whether embedding perturbation regularities within a balance task masks specific learning. Two groups of older adults maintained balance on a constant frequency-variable amplitude oscillating platform. One group was trained using an embedded sequence (ES) protocol which contained the same 15-s sequence of variable amplitude oscillations in the middle of each trial. A second group was trained using a looped sequence (LS) protocol which contained a 15-s sequence repeated three times to form each trial. All trials were 45-s. Participants were not informed of any repetition. To examine learning, participants performed a retention test following a 24-h delay. LS participants also completed a transfer task. Specificity of learning was examined by comparing performance for repeated versus random sequences (ES) and training versus transfer sequences (LS). Performance was measured by deriving spatial and temporal measures of whole body centre of mass (COM), and trunk orientation. Both groups improved performance with practice as characterized by reduced COM displacement, improved COM-platform phase relationships, and decreased angular trunk motion. Improvements were also characterized by general rather than specific postural motor learning. These findings are similar to young adults (Van Ooteghem et al. 2008) and indicate that age does not influence the type of learning which occurs for balance control. PMID:20544184

Context-Dependent Learning in People With Parkinson's Disease.

PubMed

Lee, Ya-Yun; Winstein, Carolee J; Gordon, James; Petzinger, Giselle M; Zelinski, Elizabeth M; Fisher, Beth E

2016-01-01

Context-dependent learning is a phenomenon in which people demonstrate superior performance in the context in which they originally learned a skill but perform less well in a novel context. This study investigated context-dependent learning in people with Parkinson's disease (PD) and age-matched nondisabled adults. All participants practiced 3 finger sequences, each embedded within a unique context (colors and locations on a computer screen). One day after practice, the participants were tested either under the sequence-context associations remained the same as during practice, or the sequence-context associations were changed (SWITCH). Compared with nondisabled adults, people with PD demonstrated significantly greater decrement in performance (especially movement time) under the SWITCH condition, suggesting that individuals with PD are more context dependent than nondisabled adults.

The impact of cerebellar transcranial direct current stimulation (tDCS) on learning fine-motor sequences

PubMed Central

Wu, Allan D.; Samra, Jasmine K.

2017-01-01

The cerebellum has been shown to be important for skill learning, including the learning of motor sequences. We investigated whether cerebellar transcranial direct current stimulation (tDCS) would enhance learning of fine motor sequences. Because the ability to generalize or transfer to novel task variations or circumstances is a crucial goal of real world training, we also examined the effect of tDCS on performance of novel sequences after training. In Study 1, participants received either anodal, cathodal or sham stimulation while simultaneously practising three eight-element key press sequences in a non-repeating, interleaved order. Immediately after sequence practice with concurrent tDCS, a transfer session was given in which participants practised three interleaved novel sequences. No stimulation was given during transfer. An inhibitory effect of cathodal tDCS was found during practice, such that the rate of learning was slowed in comparison to the anodal and sham groups. In Study 2, participants received anodal or sham stimulation and a 24 h delay was added between the practice and transfer sessions to reduce mental fatigue. Although this consolidation period benefitted subsequent transfer for both tDCS groups, anodal tDCS enhanced transfer performance. Together, these studies demonstrate polarity-specific effects on fine motor sequence learning and generalization. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872369

The impact of cerebellar transcranial direct current stimulation (tDCS) on learning fine-motor sequences.

PubMed

Shimizu, Renee E; Wu, Allan D; Samra, Jasmine K; Knowlton, Barbara J

2017-01-05

The cerebellum has been shown to be important for skill learning, including the learning of motor sequences. We investigated whether cerebellar transcranial direct current stimulation (tDCS) would enhance learning of fine motor sequences. Because the ability to generalize or transfer to novel task variations or circumstances is a crucial goal of real world training, we also examined the effect of tDCS on performance of novel sequences after training. In Study 1, participants received either anodal, cathodal or sham stimulation while simultaneously practising three eight-element key press sequences in a non-repeating, interleaved order. Immediately after sequence practice with concurrent tDCS, a transfer session was given in which participants practised three interleaved novel sequences. No stimulation was given during transfer. An inhibitory effect of cathodal tDCS was found during practice, such that the rate of learning was slowed in comparison to the anodal and sham groups. In Study 2, participants received anodal or sham stimulation and a 24 h delay was added between the practice and transfer sessions to reduce mental fatigue. Although this consolidation period benefitted subsequent transfer for both tDCS groups, anodal tDCS enhanced transfer performance. Together, these studies demonstrate polarity-specific effects on fine motor sequence learning and generalization.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

Changes in spinal reflex excitability associated with motor sequence learning.

PubMed

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

2010-05-01

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

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

Performance of a visuomotor walking task in an augmented reality training setting.

PubMed

Haarman, Juliet A M; Choi, Julia T; Buurke, Jaap H; Rietman, Johan S; Reenalda, Jasper

2017-12-01

Visual cues can be used to train walking patterns. Here, we studied the performance and learning capacities of healthy subjects executing a high-precision visuomotor walking task, in an augmented reality training set-up. A beamer was used to project visual stepping targets on the walking surface of an instrumented treadmill. Two speeds were used to manipulate task difficulty. All participants (n = 20) had to change their step length to hit visual stepping targets with a specific part of their foot, while walking on a treadmill over seven consecutive training blocks, each block composed of 100 stepping targets. Distance between stepping targets was varied between short, medium and long steps. Training blocks could either be composed of random stepping targets (no fixed sequence was present in the distance between the stepping targets) or sequenced stepping targets (repeating fixed sequence was present). Random training blocks were used to measure non-specific learning and sequenced training blocks were used to measure sequence-specific learning. Primary outcome measures were performance (% of correct hits), and learning effects (increase in performance over the training blocks: both sequence-specific and non-specific). Secondary outcome measures were the performance and stepping-error in relation to the step length (distance between stepping target). Subjects were able to score 76% and 54% at first try for lower speed (2.3 km/h) and higher speed (3.3 km/h) trials, respectively. Performance scores did not increase over the course of the trials, nor did the subjects show the ability to learn a sequenced walking task. Subjects were better able to hit targets while increasing their step length, compared to shortening it. In conclusion, augmented reality training by use of the current set-up was intuitive for the user. Suboptimal feedback presentation might have limited the learning effects of the subjects. Copyright © 2017 Elsevier B.V. All rights reserved.

Learning by subtraction: Hippocampal activity and effects of ethanol during the acquisition and performance of response sequences.

PubMed

Ketchum, Myles J; Weyand, Theodore G; Weed, Peter F; Winsauer, Peter J

2016-05-01

Learning is believed to be reflected in the activity of the hippocampus. However, neural correlates of learning have been difficult to characterize because hippocampal activity is integrated with ongoing behavior. To address this issue, male rats (n = 5) implanted with electrodes (n = 14) in the CA1 subfield responded during two tasks within a single test session. In one task, subjects acquired a new 3-response sequence (acquisition), whereas in the other task, subjects completed a well-rehearsed 3-response sequence (performance). Both tasks though could be completed using an identical response topography and used the same sensory stimuli and schedule of reinforcement. More important, comparing neural patterns during sequence acquisition to those during sequence performance allows for a subtractive approach whereby activity associated with learning could potentially be dissociated from the activity associated with ongoing behavior. At sites where CA1 activity was closely associated with behavior, the patterns of activity were differentially modulated by key position and the serial position of a response within the schedule of reinforcement. Temporal shifts between peak activity and responding on particular keys also occurred during sequence acquisition, but not during sequence performance. Ethanol disrupted CA1 activity while producing rate-decreasing effects in both tasks and error-increasing effects that were more selective for sequence acquisition than sequence performance. Ethanol also produced alterations in the magnitude of modulations and temporal pattern of CA1 activity, although these effects were not selective for sequence acquisition. Similar to ethanol, hippocampal micro-stimulation decreased response rate in both tasks and selectively increased the percentage of errors during sequence acquisition, and provided a more direct demonstration of hippocampal involvement during sequence acquisition. Together, these results strongly support the notion that ethanol disrupts sequence acquisition by disrupting hippocampal activity and that the hippocampus is necessary for the conditioned associations required for sequence acquisition. © 2015 Wiley Periodicals, Inc.

Learning by Subtraction: Hippocampal Activity and Effects of Ethanol during the Acquisition and Performance of Response Sequences

PubMed Central

Ketchum, Myles J.; Weyand, Theodore G.; Weed, Peter F.; Winsauer, Peter J.

2015-01-01

Learning is believed to be reflected in the activity of the hippocampus. However, neural correlates of learning have been difficult to characterize because hippocampal activity is integrated with ongoing behavior. To address this issue, male rats (n=5) implanted with electrodes (n=14) in the CA1 subfield responded during two tasks within a single test session. In one task, subjects acquired a new 3-response sequence (acquisition), whereas in the other task, subjects completed a well-rehearsed 3-response sequence (performance). Both tasks though could be completed using an identical response topography and used the same sensory stimuli and schedule of reinforcement. More important, comparing neural patterns during sequence acquisition to those during sequence performance allows for a subtractive approach whereby activity associated with learning could potentially be dissociated from the activity associated with ongoing behavior. At sites where CA1 activity was closely associated with behavior, the patterns of activity were differentially modulated by key position and the serial position of a response within the schedule of reinforcement. Temporal shifts between peak activity and responding on particular keys also occurred during sequence acquisition, but not during sequence performance. Ethanol disrupted CA1 activity while producing rate-decreasing effects in both tasks and error-increasing effects that were more selective for sequence acquisition than sequence performance. Ethanol also produced alterations in the magnitude of modulations and temporal pattern of CA1 activity, although these effects were not selective for sequence acquisition. Similar to ethanol, hippocampal micro-stimulation decreased response rate in both tasks and selectively increased the percentage of errors during sequence acquisition, and provided a more direct demonstration of hippocampal involvement during sequence acquisition. Together, these results strongly support the notion that ethanol disrupts sequence acquisition by disrupting hippocampal activity and that the hippocampus is necessary for the conditioned associations required for sequence acquisition. PMID:26482846

Implicit sequence-specific motor learning after sub-cortical stroke is associated with increased prefrontal brain activations: An fMRI study

PubMed Central

Meehan, Sean K.; Randhawa, Bubblepreet; Wessel, Brenda; Boyd, Lara A.

2010-01-01

Implicit motor learning is preserved after stroke, but how the brain compensates for damage to facilitate learning is unclear. We used a random effects analysis to determine how stroke alters patterns of brain activity during implicit sequence-specific motor learning as compared to general improvements in motor control. Nine healthy participants and 9 individuals with chronic, right focal sub-cortical stroke performed a continuous joystick-based tracking task during an initial fMRI session, over 5 days of practice, and a retention test during a separate fMRI session. Sequence-specific implicit motor learning was differentiated from general improvements in motor control by comparing tracking performance on a novel, repeated tracking sequences during early practice and again at the retention test. Both groups demonstrated implicit sequence-specific motor learning at the retention test, yet substantial differences were apparent. At retention, healthy control participants demonstrated increased BOLD response in left dorsal premotor cortex (BA 6) but decreased BOLD response left dorsolateral prefrontal cortex (DLPFC; BA 9) during repeated sequence tracking. In contrast, at retention individuals with stroke did not show this reduction in DLPFC during repeated tracking. Instead implicit sequence-specific motor learning and general improvements in motor control were associated with increased BOLD response in the left middle frontal gyrus BA 8, regardless of sequence type after stroke. These data emphasize the potential importance of a prefrontal-based attentional network for implicit motor learning after stroke. The present study is the first to highlight the importance of the prefrontal cortex for implicit sequence-specific motor learning after stroke. PMID:20725908

No effects of transcranial DLPFC stimulation on implicit task sequence learning and consolidation.

PubMed

Savic, Branislav; Cazzoli, Dario; Müri, René; Meier, Beat

2017-08-29

Neurostimulation of the dorsolateral prefrontal cortex (DLPFC) can modulate performance in cognitive tasks. In a recent study, however, transcranial direct current stimulation (tDCS) of the DLPFC did not affect implicit task sequence learning and consolidation in a paradigm that involved bimanual responses. Because bimanual performance increases the coupling between homologous cortical areas of the hemispheres and left and right DLPFC were stimulated separately the null findings may have been due to the bimanual setup. The aim of the present study was to test the effect of neuro-stimulation on sequence learning in a uni-manual setup. For this purpose two experiments were conducted. In Experiment 1, the DLPFC was stimulated with tDCS. In Experiment 2 the DLPFC was stimulated with transcranial magnetic stimulation (TMS). In both experiments, consolidation was measured 24 hours later. The results showed that sequence learning was present in all conditions and sessions, but it was not influenced by stimulation. Likewise, consolidation of sequence learning was robust across sessions, but it was not influenced by stimulation. These results replicate and extend previous findings. They indicate that established tDCS and TMS protocols on the DLPFC do not influence implicit task sequence learning and consolidation.

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

cTBS disruption of the supplementary motor area perturbs cortical sequence representation but not behavioural performance.

PubMed

Solopchuk, Oleg; Alamia, Andrea; Dricot, Laurence; Duque, Julie; Zénon, Alexandre

2017-12-01

Neuroimaging studies have repeatedly emphasized the role of the supplementary motor area (SMA) in motor sequence learning, but interferential approaches have led to inconsistent findings. Here, we aimed to test the role of the SMA in motor skill learning by combining interferential and neuroimaging techniques. Sixteen subjects were trained on simple finger movement sequences for 4 days. Afterwards, they underwent two neuroimaging sessions, in which they executed both trained and novel sequences. Prior to entering the scanner, the subjects received inhibitory transcranial magnetic stimulation (TMS) over the SMA or a control site. Using multivariate fMRI analysis, we confirmed that motor training enhances the neural representation of motor sequences in the SMA, in accordance with previous findings. However, although SMA inhibition altered sequence representation (i.e. between-sequence decoding accuracy) in this area, behavioural performance remained unimpaired. Our findings question the causal link between the neuroimaging correlate of elementary motor sequence representation in the SMA and sequence generation, calling for a more thorough investigation of the role of this region in performance of learned motor sequences. Copyright © 2017 Elsevier Inc. All rights reserved.

Dispositional mindfulness is associated with reduced implicit learning.

PubMed

Stillman, Chelsea M; Feldman, Halley; Wambach, Caroline G; Howard, James H; Howard, Darlene V

2014-08-01

Behavioral and neuroimaging evidence suggest that mindfulness exerts its salutary effects by disengaging habitual processes supported by subcortical regions and increasing effortful control processes supported by the frontal lobes. Here we investigated whether individual differences in dispositional mindfulness relate to performance on implicit sequence learning tasks in which optimal learning may in fact be impeded by the engagement of effortful control processes. We report results from two studies where participants completed a widely used questionnaire assessing mindfulness and one of two implicit sequence learning tasks. Learning was quantified using two commonly used measures of sequence learning. In both studies we detected a negative relationship between mindfulness and sequence learning, and the relationship was consistent across both learning measures. Our results, the first to show a negative relationship between mindfulness and implicit sequence learning, suggest that the beneficial effects of mindfulness do not extend to all cognitive functions. Copyright © 2014 Elsevier Inc. All rights reserved.

A safety mechanism for observational learning.

PubMed

Badets, Arnaud; Boutin, Arnaud; Michelet, Thomas

2018-04-01

This empirical article presents the first evidence of a "safety mechanism" based on an observational-learning paradigm. It is accepted that during observational learning, a person can use different strategies to learn a motor skill, but it is unknown whether the learner is able to circumvent the encoding of an uncompleted observed skill. In this study, participants were tested in a dyadic protocol in which an observer watched a participant practicing two different motor sequences during a learning phase. During this phase, one of the two motor sequences was interrupted by a stop signal that precluded motor learning. The results of the subsequent retention test revealed that both groups learned the two motor sequences, but only the physical practice group showed worse performance for the interrupted sequence. The observers were consequently able to use a safety strategy to learn both sequences equally. Our findings are discussed in light of the implications of the action observation network for sequence learning and the cognitive mechanisms of error-based observation.

Effects of sleep loss, time of day, and extended mental work on implicit and explicit learning of sequences

NASA Technical Reports Server (NTRS)

Heuer, H.; Spijkers, W.; Kiesswetter, E.; Schmidtke, V.

1998-01-01

Tacit knowledge is part of many professional skills and can be studied experimentally with implicit-learning paradigms. The authors explored the effects of 2 different stressors, loss of sleep and mental fatigue, on implicit learning in a serial-response time (RT) task. In the 1st experiment, 1 night of sleep deprivation was shown to impair implicit but not explicit sequence learning. In the 2nd experiment, no impairment of both types of sequence learning was found after 1.5 hr of mental work. Serial-RT performance, in contrast, suffered from both stressors. These findings suggest that sleep deprivation induces specific risks for automatic, skill-based behavior that are not present in consciously controlled performance.

Aging does not affect generalized postural motor learning in response to variable amplitude oscillations of the support surface.

PubMed

Van Ooteghem, Karen; Frank, James S; Allard, Fran; Horak, Fay B

2010-08-01

Postural motor learning for dynamic balance tasks has been demonstrated in healthy older adults (Van Ooteghem et al. in Exp Brain Res 199(2):185-193, 2009). The purpose of this study was to investigate the type of knowledge (general or specific) obtained with balance training in this age group and to examine whether embedding perturbation regularities within a balance task masks specific learning. Two groups of older adults maintained balance on a translating platform that oscillated with variable amplitude and constant frequency. One group was trained using an embedded-sequence (ES) protocol which contained the same 15-s sequence of variable amplitude oscillations in the middle of each trial. A second group was trained using a looped-sequence (LS) protocol which contained a 15-s sequence repeated three times to form each trial. All trials were 45 s. Participants were not informed of any repetition. To examine learning, participants performed a retention test following a 24-h delay. LS participants also completed a transfer task. Specificity of learning was examined by comparing performance for repeated versus random sequences (ES) and training versus transfer sequences (LS). Performance was measured by deriving spatial and temporal measures of whole body center of mass (COM) and trunk orientation. Both groups improved performance with practice as characterized by reduced COM displacement, improved COM-platform phase relationships, and decreased angular trunk motion. Furthermore, improvements reflected general rather than specific postural motor learning regardless of training protocol (ES or LS). This finding is similar to young adults (Van Ooteghem et al. in Exp Brain Res 187(4):603-611, 2008) and indicates that age does not influence the type of learning which occurs for balance control.

Identifying Learning Behaviors by Contextualizing Differential Sequence Mining with Action Features and Performance Evolution

ERIC Educational Resources Information Center

Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Our learning-by-teaching environment, Betty's Brain, captures a wealth of data on students' learning interactions as they teach a virtual agent. This paper extends an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs sequence mining techniques to…

The transition to increased automaticity during finger sequence learning in adult males who stutter.

PubMed

Smits-Bandstra, Sarah; De Nil, Luc; Rochon, Elizabeth

2006-01-01

The present study compared the automaticity levels of persons who stutter (PWS) and persons who do not stutter (PNS) on a practiced finger sequencing task under dual task conditions. Automaticity was defined as the amount of attention required for task performance. Twelve PWS and 12 control subjects practiced finger tapping sequences under single and then dual task conditions. Control subjects performed the sequencing task significantly faster and less variably under single versus dual task conditions while PWS' performance was consistently slow and variable (comparable to the dual task performance of control subjects) under both conditions. Control subjects were significantly more accurate on a colour recognition distracter task than PWS under dual task conditions. These results suggested that control subjects transitioned to quick, accurate and increasingly automatic performance on the sequencing task after practice, while PWS did not. Because most stuttering treatment programs for adults include practice and automatization of new motor speech skills, findings of this finger sequencing study and future studies of speech sequence learning may have important implications for how to maximize stuttering treatment effectiveness. As a result of this activity, the participant will be able to: (1) Define automaticity and explain the importance of dual task paradigms to investigate automaticity; (2) Relate the proposed relationship between motor learning and automaticity as stated by the authors; (3) Summarize the reviewed literature concerning the performance of PWS on dual tasks; and (4) Explain why the ability to transition to automaticity during motor learning may have important clinical implications for stuttering treatment effectiveness.

Examining the Effectiveness of a Semi-Self-Paced Flipped Learning Format in a College General Chemistry Sequence

ERIC Educational Resources Information Center

Hibbard, Lisa; Sung, Shannon; Wells, Breche´

2016-01-01

Flipped learning has come to the forefront in education. It maximizes learning by moving content delivery online, where learning can be self-paced, allowing for class time to focus on student-centered active learning. This five-year cross-sectional study assessed student performance in a college general chemistry for majors sequence taught by a…

Inter-level Scaffolding and Sequences of Representational Activities in Teaching a Chemical System with Graphical Simulations

NASA Astrophysics Data System (ADS)

Li, Na; Black, John B.

2016-10-01

Chemistry knowledge can be represented at macro-, micro- and symbolic levels, and learning a chemistry topic requires students to engage in multiple representational activities. This study focused on scaffolding for inter-level connection-making in learning chemistry knowledge with graphical simulations. We also tested whether different sequences of representational activities produced different student learning outcomes in learning a chemistry topic. A sample of 129 seventh graders participated in this study. In a simulation-based environment, participants completed three representational activities to learn several ideal gas law concepts. We conducted a 2 × 3 factorial design experiment. We compared two scaffolding conditions: (1) the inter- level scaffolding condition in which participants received inter-level questions and experienced the dynamic link function in the simulation-based environment and (2) the intra- level scaffolding condition in which participants received intra-level questions and did not experience the dynamic link function. We also compared three different sequences of representational activities: macro-symbolic-micro, micro-symbolic-macro and symbolic-micro-macro. For the scaffolding variable, we found that the inter- level scaffolding condition produced significantly better performance in both knowledge comprehension and application, compared to the intra- level scaffolding condition. For the sequence variable, we found that the macro-symbolic-micro sequence produced significantly better knowledge comprehension performance than the other two sequences; however, it did not benefit knowledge application performance. There was a trend that the treatment group who experienced inter- level scaffolding and the micro-symbolic-macro sequence achieved the best knowledge application performance.

Dynamic mesolimbic dopamine signaling during action sequence learning and expectation violation

PubMed Central

Collins, Anne L.; Greenfield, Venuz Y.; Bye, Jeffrey K.; Linker, Kay E.; Wang, Alice S.; Wassum, Kate M.

2016-01-01

Prolonged mesolimbic dopamine concentration changes have been detected during spatial navigation, but little is known about the conditions that engender this signaling profile or how it develops with learning. To address this, we monitored dopamine concentration changes in the nucleus accumbens core of rats throughout acquisition and performance of an instrumental action sequence task. Prolonged dopamine concentration changes were detected that ramped up as rats executed each action sequence and declined after earned reward collection. With learning, dopamine concentration began to rise increasingly earlier in the execution of the sequence and ultimately backpropagated away from stereotyped sequence actions, becoming only transiently elevated by the most distal and unexpected reward predictor. Action sequence-related dopamine signaling was reactivated in well-trained rats if they became disengaged in the task and in response to an unexpected change in the value, but not identity of the earned reward. Throughout training and test, dopamine signaling correlated with sequence performance. These results suggest that action sequences can engender a prolonged mode of dopamine signaling in the nucleus accumbens core and that such signaling relates to elements of the motivation underlying sequence execution and is dynamic with learning, overtraining and violations in reward expectation. PMID:26869075

Domain-specific learning of grammatical structure in musical and phonological sequences.

PubMed

Bly, Benjamin Martin; Carrión, Ricardo E; Rasch, Björn

2009-01-01

Artificial grammar learning depends on acquisition of abstract structural representations rather than domain-specific representational constraints, or so many studies tell us. Using an artificial grammar task, we compared learning performance in two stimulus domains in which respondents have differing tacit prior knowledge. We found that despite grammatically identical sequence structures, learning was better for harmonically related chord sequences than for letter name sequences or harmonically unrelated chord sequences. We also found transfer effects within the musical and letter name tasks, but not across the domains. We conclude that knowledge acquired in implicit learning depends not only on abstract features of structured stimuli, but that the learning of regularities is in some respects domain-specific and strongly linked to particular features of the stimulus domain.

Imagery May Arise from Associations Formed through Sensory Experience: A Network of Spiking Neurons Controlling a Robot Learns Visual Sequences in Order to Perform a Mental Rotation Task

PubMed Central

McKinstry, Jeffrey L.; Fleischer, Jason G.; Chen, Yanqing; Gall, W. Einar; Edelman, Gerald M.

2016-01-01

Mental imagery occurs “when a representation of the type created during the initial phases of perception is present but the stimulus is not actually being perceived.” How does the capability to perform mental imagery arise? Extending the idea that imagery arises from learned associations, we propose that mental rotation, a specific form of imagery, could arise through the mechanism of sequence learning–that is, by learning to regenerate the sequence of mental images perceived while passively observing a rotating object. To demonstrate the feasibility of this proposal, we constructed a simulated nervous system and embedded it within a behaving humanoid robot. By observing a rotating object, the system learns the sequence of neural activity patterns generated by the visual system in response to the object. After learning, it can internally regenerate a similar sequence of neural activations upon briefly viewing the static object. This system learns to perform a mental rotation task in which the subject must determine whether two objects are identical despite differences in orientation. As with human subjects, the time taken to respond is proportional to the angular difference between the two stimuli. Moreover, as reported in humans, the system fills in intermediate angles during the task, and this putative mental rotation activates the same pathways that are activated when the system views physical rotation. This work supports the proposal that mental rotation arises through sequence learning and the idea that mental imagery aids perception through learned associations, and suggests testable predictions for biological experiments. PMID:27653977

Supervised Learning for Detection of Duplicates in Genomic Sequence Databases.

PubMed

Chen, Qingyu; Zobel, Justin; Zhang, Xiuzhen; Verspoor, Karin

2016-01-01

First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and existing automatic systems cannot detect duplicates as precisely as can experts. Supervised learning has the potential to address such problems by building automatic systems that learn from expert curation to detect duplicates precisely and efficiently. While machine learning is a mature approach in other duplicate detection contexts, it has seen only preliminary application in genomic sequence databases. We developed and evaluated a supervised duplicate detection method based on an expert curated dataset of duplicates, containing over one million pairs across five organisms derived from genomic sequence databases. We selected 22 features to represent distinct attributes of the database records, and developed a binary model and a multi-class model. Both models achieve promising performance; under cross-validation, the binary model had over 90% accuracy in each of the five organisms, while the multi-class model maintains high accuracy and is more robust in generalisation. We performed an ablation study to quantify the impact of different sequence record features, finding that features derived from meta-data, sequence identity, and alignment quality impact performance most strongly. The study demonstrates machine learning can be an effective additional tool for de-duplication of genomic sequence databases. All Data are available as described in the supplementary material.

Discrete sequence prediction and its applications

NASA Technical Reports Server (NTRS)

Laird, Philip

1992-01-01

Learning from experience to predict sequences of discrete symbols is a fundamental problem in machine learning with many applications. We apply sequence prediction using a simple and practical sequence-prediction algorithm, called TDAG. The TDAG algorithm is first tested by comparing its performance with some common data compression algorithms. Then it is adapted to the detailed requirements of dynamic program optimization, with excellent results.

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.

Attentional load and implicit sequence learning.

PubMed

Shanks, David R; Rowland, Lee A; Ranger, Mandeep S

2005-06-01

A widely employed conceptualization of implicit learning hypothesizes that it makes minimal demands on attentional resources. This conjecture was investigated by comparing learning under single-task and dual-task conditions in the sequential reaction time (SRT) task. Participants learned probabilistic sequences, with dual-task participants additionally having to perform a counting task using stimuli that were targets in the SRT display. Both groups were then tested for sequence knowledge under single-task (Experiments 1 and 2) or dual-task (Experiment 3) conditions. Participants also completed a free generation task (Experiments 2 and 3) under inclusion or exclusion conditions to determine if sequence knowledge was conscious or unconscious in terms of its access to intentional control. The experiments revealed that the secondary task impaired sequence learning and that sequence knowledge was consciously accessible. These findings disconfirm both the notion that implicit learning is able to proceed normally under conditions of divided attention, and that the acquired knowledge is inaccessible to consciousness. A unitary framework for conceptualizing implicit and explicit learning is proposed.

Active learning: learning a motor skill without a coach.

PubMed

Huang, Vincent S; Shadmehr, Reza; Diedrichsen, Jörn

2008-08-01

When we learn a new skill (e.g., golf) without a coach, we are "active learners": we have to choose the specific components of the task on which to train (e.g., iron, driver, putter, etc.). What guides our selection of the training sequence? How do choices that people make compare with choices made by machine learning algorithms that attempt to optimize performance? We asked subjects to learn the novel dynamics of a robotic tool while moving it in four directions. They were instructed to choose their practice directions to maximize their performance in subsequent tests. We found that their choices were strongly influenced by motor errors: subjects tended to immediately repeat an action if that action had produced a large error. This strategy was correlated with better performance on test trials. However, even when participants performed perfectly on a movement, they did not avoid repeating that movement. The probability of repeating an action did not drop below chance even when no errors were observed. This behavior led to suboptimal performance. It also violated a strong prediction of current machine learning algorithms, which solve the active learning problem by choosing a training sequence that will maximally reduce the learner's uncertainty about the task. While we show that these algorithms do not provide an adequate description of human behavior, our results suggest ways to improve human motor learning by helping people choose an optimal training sequence.

Event-Related Potential Correlates of Declarative and Non-Declarative Sequence Knowledge

ERIC Educational Resources Information Center

Ferdinand, Nicola K.; Runger, Dennis; Frensch, Peter A.; Mecklinger, Axel

2010-01-01

The goal of the present study was to demonstrate that declarative and non-declarative knowledge acquired in an incidental sequence learning task contributes differentially to memory retrieval and leads to dissociable ERP signatures in a recognition memory task. For this purpose, participants performed a sequence learning task and were classified…

Deficit in implicit motor sequence learning among children and adolescents with spastic cerebral palsy.

PubMed

Gofer-Levi, Moran; Silberg, Tamar; Brezner, Amichai; Vakil, Eli

2013-11-01

Skill learning (SL) is learning as a result of repeated exposure and practice, which encompasses independent explicit (response to instructions) and implicit (response to hidden regularities) processes. Little is known about the effects of developmental disorders, such as Cerebral Palsy (CP), on the ability to acquire new skills. We compared performance of CP and typically developing (TD) children and adolescents in completing the serial reaction time (SRT) task, which is a motor sequence learning task, and examined the impact of various factors on this performance as indicative of the ability to acquire motor skills. While both groups improved in performance, participants with CP were significantly slower than TD controls and did not learn the implicit sequence. Our results indicate that SL in children and adolescents with CP is qualitatively and quantitatively different than that of their peers. Understanding the unique aspects of SL in children and adolescents with CP might help plan appropriate and efficient interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

PubMed

Li, Yang; Yang, Jianyi

2017-04-24

The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.

Implicit sequence learning and contextual cueing do not compete for central cognitive resources.

PubMed

Jiménez, Luis; Vázquez, Gustavo A

2011-02-01

Sequence learning and contextual cueing explore different forms of implicit learning, arising from practice with a structured serial task, or with a search task with informative contexts. We assess whether these two learning effects arise simultaneously when both remain implicit. Experiments 1 and 2 confirm that a cueing effect can be observed under a continuous setting and that there is no interference between contextual cueing and sequence learning. Experiments 3a and 3b tested whether an interference arises specifically when the sequence becomes explicit. Results show that the expression of contextual cueing disappeared in those conditions but that context information is still acquired, and it affects performance when the sequence is removed. The results are discussed in relation to the current debates about the automaticity of implicit learning, and about the role of attention in the acquisition and expression of contextual cueing. (c) 2010 APA, all rights reserved.

Implicit and explicit motor sequence learning in children born very preterm.

PubMed

Jongbloed-Pereboom, Marjolein; Janssen, Anjo J W M; Steiner, K; Steenbergen, Bert; Nijhuis-van der Sanden, Maria W G

2017-01-01

Motor skills can be learned explicitly (dependent on working memory (WM)) or implicitly (relatively independent of WM). Children born very preterm (VPT) often have working memory deficits. Explicit learning may be compromised in these children. This study investigated implicit and explicit motor learning and the role of working memory in VPT children and controls. Three groups (6-9 years) participated: 20 VPT children with motor problems, 20 VPT children without motor problems, and 20 controls. A nine button sequence was learned implicitly (pressing the lighted button as quickly as possible) and explicitly (discovering the sequence via trial-and-error). Children learned implicitly and explicitly, evidenced by decreased movement duration of the sequence over time. In the explicit condition, children also reduced the number of errors over time. Controls made more errors than VPT children without motor problems. Visual WM had positive effects on both explicit and implicit performance. VPT birth and low motor proficiency did not negatively affect implicit or explicit learning. Visual WM was positively related to both implicit and explicit performance, but did not influence learning curves. These findings question the theoretical difference between implicit and explicit learning and the proposed role of visual WM therein. Copyright © 2016 Elsevier Ltd. All rights reserved.

Demonstration of Nondeclarative Sequence Learning in Mice: Development of an Animal Analog of the Human Serial Reaction Time Task

ERIC Educational Resources Information Center

Christie, Michael A.; Hersch, Steven M.

2004-01-01

In this paper, we demonstrate nondeclarative sequence learning in mice using an animal analog of the human serial reaction time task (SRT) that uses a within-group comparison of behavior in response to a repeating sequence versus a random sequence. Ten female B6CBA mice performed eleven 96-trial sessions containing 24 repetitions of a 4-trial…

Bilingual Performance on Nonword Repetition in Spanish and English

ERIC Educational Resources Information Center

Summers, Connie; Bohman, Thomas M.; Gillam, Ronald B.; Pena, Elizabeth D.; Bedore, Lisa M.

2010-01-01

Background: Nonword repetition (NWR) involves the ability to perceive, store, recall and reproduce phonological sequences. These same abilities play a role in word and morpheme learning. Cross-linguistic studies of performance on NWR tasks, word learning, and morpheme learning yield patterns of increased performance on all three tasks as a…

Involvement of Working Memory in College Students' Sequential Pattern Learning and Performance

ERIC Educational Resources Information Center

Kundey, Shannon M. A.; De Los Reyes, Andres; Rowan, James D.; Lee, Bern; Delise, Justin; Molina, Sabrina; Cogdill, Lindsay

2013-01-01

When learning highly organized sequential patterns of information, humans and nonhuman animals learn rules regarding the hierarchical structures of these sequences. In three experiments, we explored the role of working memory in college students' sequential pattern learning and performance in a computerized task involving a sequential…

Implicit transfer of spatial structure in visuomotor sequence learning.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2014-11-01

Implicit learning and transfer in sequence learning are essential in daily life. Here, we investigated the implicit transfer of visuomotor sequences following a spatial transformation. In the two experiments, participants used trial and error to learn a sequence consisting of several button presses, known as the m×n task (Hikosaka et al., 1995). After this learning session, participants learned another sequence in which the button configuration was spatially transformed in one of the following ways: mirrored, rotated, and random arrangement. Our results showed that even when participants were unaware of the transformation rules, accuracy of transfer session in the mirrored and rotated groups was higher than that in the random group (i.e., implicit transfer occurred). Both those who noticed the transformation rules and those who did not (i.e., explicit and implicit transfer instances, respectively) showed faster performance in the mirrored sequences than in the rotated sequences. Taken together, the present results suggest that people can use their implicit visuomotor knowledge to spatially transform sequences and that implicit transfers are modulated by a transformation cost, similar to that in explicit transfer. Copyright © 2014 Elsevier B.V. All rights reserved.

Memory and learning with rapid audiovisual sequences

PubMed Central

Keller, Arielle S.; Sekuler, Robert

2015-01-01

We examined short-term memory for sequences of visual stimuli embedded in varying multisensory contexts. In two experiments, subjects judged the structure of the visual sequences while disregarding concurrent, but task-irrelevant auditory sequences. Stimuli were eight-item sequences in which varying luminances and frequencies were presented concurrently and rapidly (at 8 Hz). Subjects judged whether the final four items in a visual sequence identically replicated the first four items. Luminances and frequencies in each sequence were either perceptually correlated (Congruent) or were unrelated to one another (Incongruent). Experiment 1 showed that, despite encouragement to ignore the auditory stream, subjects' categorization of visual sequences was strongly influenced by the accompanying auditory sequences. Moreover, this influence tracked the similarity between a stimulus's separate audio and visual sequences, demonstrating that task-irrelevant auditory sequences underwent a considerable degree of processing. Using a variant of Hebb's repetition design, Experiment 2 compared musically trained subjects and subjects who had little or no musical training on the same task as used in Experiment 1. Test sequences included some that intermittently and randomly recurred, which produced better performance than sequences that were generated anew for each trial. The auditory component of a recurring audiovisual sequence influenced musically trained subjects more than it did other subjects. This result demonstrates that stimulus-selective, task-irrelevant learning of sequences can occur even when such learning is an incidental by-product of the task being performed. PMID:26575193

Memory and learning with rapid audiovisual sequences.

PubMed

Keller, Arielle S; Sekuler, Robert

2015-01-01

We examined short-term memory for sequences of visual stimuli embedded in varying multisensory contexts. In two experiments, subjects judged the structure of the visual sequences while disregarding concurrent, but task-irrelevant auditory sequences. Stimuli were eight-item sequences in which varying luminances and frequencies were presented concurrently and rapidly (at 8 Hz). Subjects judged whether the final four items in a visual sequence identically replicated the first four items. Luminances and frequencies in each sequence were either perceptually correlated (Congruent) or were unrelated to one another (Incongruent). Experiment 1 showed that, despite encouragement to ignore the auditory stream, subjects' categorization of visual sequences was strongly influenced by the accompanying auditory sequences. Moreover, this influence tracked the similarity between a stimulus's separate audio and visual sequences, demonstrating that task-irrelevant auditory sequences underwent a considerable degree of processing. Using a variant of Hebb's repetition design, Experiment 2 compared musically trained subjects and subjects who had little or no musical training on the same task as used in Experiment 1. Test sequences included some that intermittently and randomly recurred, which produced better performance than sequences that were generated anew for each trial. The auditory component of a recurring audiovisual sequence influenced musically trained subjects more than it did other subjects. This result demonstrates that stimulus-selective, task-irrelevant learning of sequences can occur even when such learning is an incidental by-product of the task being performed.

Disruption of Boundary Encoding During Sensorimotor Sequence Learning: An MEG Study.

PubMed

Michail, Georgios; Nikulin, Vadim V; Curio, Gabriel; Maess, Burkhard; Herrojo Ruiz, María

2018-01-01

Music performance relies on the ability to learn and execute actions and their associated sounds. The process of learning these auditory-motor contingencies depends on the proper encoding of the serial order of the actions and sounds. Among the different serial positions of a behavioral sequence, the first and last (boundary) elements are particularly relevant. Animal and patient studies have demonstrated a specific neural representation for boundary elements in prefrontal cortical regions and in the basal ganglia, highlighting the relevance of their proper encoding. The neural mechanisms underlying the encoding of sequence boundaries in the general human population remain, however, largely unknown. In this study, we examined how alterations of auditory feedback, introduced at different ordinal positions (boundary or within-sequence element), affect the neural and behavioral responses during sensorimotor sequence learning. Analysing the neuromagnetic signals from 20 participants while they performed short piano sequences under the occasional effect of altered feedback (AF), we found that at around 150-200 ms post-keystroke, the neural activities in the dorsolateral prefrontal cortex (DLPFC) and supplementary motor area (SMA) were dissociated for boundary and within-sequence elements. Furthermore, the behavioral data demonstrated that feedback alterations on boundaries led to greater performance costs, such as more errors in the subsequent keystrokes. These findings jointly support the idea that the proper encoding of boundaries is critical in acquiring sensorimotor sequences. They also provide evidence for the involvement of a distinct neural circuitry in humans including prefrontal and higher-order motor areas during the encoding of the different classes of serial order.

Motor Sequence Learning Performance in Parkinson's Disease Patients Depends on the Stage of Disease

ERIC Educational Resources Information Center

Stephan, Marianne A.; Meier, Beat; Zaugg, Sabine Weber; Kaelin-Lang, Alain

2011-01-01

It is still unclear, whether patients with Parkinson's disease (PD) are impaired in the incidental learning of different motor sequences in short succession, although such a deficit might greatly impact their daily life. The aim of this study was thus to clarify the relation between disease parameters of PD and incidental motor learning of two…

The Effect of Practice Schedule on Context-Dependent Learning.

PubMed

Lee, Ya-Yun; Fisher, Beth E

2018-03-02

It is well established that random practice compared to blocked practice enhances motor learning. Additionally, while information in the environment may be incidental, learning is also enhanced when an individual performs a task within the same environmental context in which the task was originally practiced. This study aimed to disentangle the effects of practice schedule and incidental/environmental context on motor learning. Participants practiced three finger sequences under either a random or blocked practice schedule. Each sequence was associated with specific incidental context (i.e., color and location on the computer screen) during practice. The participants were tested under the conditions when the sequence-context associations remained the same or were changed from that of practice. When the sequence-context association was changed, the participants who practiced under blocked schedule demonstrated greater performance decrement than those who practiced under random schedule. The findings suggested that those participants who practiced under random schedule were more resistant to the change of environmental context.

Cerebellar activation during motor sequence learning is associated with subsequent transfer to new sequences.

PubMed

Shimizu, Renee E; Wu, Allan D; Knowlton, Barbara J

2016-12-01

Effective learning results not only in improved performance on a practiced task, but also in the ability to transfer the acquired knowledge to novel, similar tasks. Using a modified serial reaction time (RT) task, the authors examined the ability to transfer to novel sequences after practicing sequences in a repetitive order versus a nonrepeating interleaved order. Interleaved practice resulted in better performance on new sequences than repetitive practice. In a second study, participants practiced interleaved sequences in a functional MRI (fMRI) scanner and received a transfer test of novel sequences. Transfer ability was positively correlated with cerebellar blood oxygen level dependent activity during practice, indicating that greater cerebellar engagement during training resulted in better subsequent transfer performance. Interleaved practice may thus result in a more generalized representation that is robust to interference, and the degree of activation in the cerebellum may be a reflection of the instantiation and engagement of internal models. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Middle school students' learning of mechanics concepts through engagement in different sequences of physical and virtual experiments

NASA Astrophysics Data System (ADS)

Sullivan, Sarah; Gnesdilow, Dana; Puntambekar, Sadhana; Kim, Jee-Seon

2017-08-01

Physical and virtual experimentation are thought to have different affordances for supporting students' learning. Research investigating the use of physical and virtual experiments to support students' learning has identified a variety of, sometimes conflicting, outcomes. Unanswered questions remain about how physical and virtual experiments may impact students' learning and for which contexts and content areas they may be most effective. Using a quasi-experimental design, we examined eighth grade students' (N = 100) learning of physics concepts related to pulleys depending on the sequence of physical and virtual labs they engaged in. Five classes of students were assigned to either the: physical first condition (PF) (n = 55), where students performed a physical pulley experiment and then performed the same experiment virtually, or virtual first condition (VF) (n = 45), with the opposite sequence. Repeated measures ANOVA's were conducted to examine how physical and virtual labs impacted students' learning of specific physics concepts. While we did not find clear-cut support that one sequence was better, we did find evidence that participating in virtual experiments may be more beneficial for learning certain physics concepts, such as work and mechanical advantage. Our findings support the idea that if time or physical materials are limited, using virtual experiments may help students understand work and mechanical advantage.

Analysis of the Effect of Sequencing Lecture and Laboratory Instruction on Student Learning and Motivation Towards Learning Chemistry in an Organic Chemistry Lecture Course

ERIC Educational Resources Information Center

Pakhira, Deblina

2012-01-01

Exposure to organic chemistry concepts in the laboratory can positively affect student performance, learning new chemistry concepts and building motivation towards learning chemistry in the lecture. In this study, quantitative methods were employed to assess differences in student performance, learning, and motivation in an organic chemistry…

Evidence of automatic processing in sequence learning using process-dissociation

PubMed Central

Mong, Heather M.; McCabe, David P.; Clegg, Benjamin A.

2012-01-01

This paper proposes a way to apply process-dissociation to sequence learning in addition and extension to the approach used by Destrebecqz and Cleeremans (2001). Participants were trained on two sequences separated from each other by a short break. Following training, participants self-reported their knowledge of the sequences. A recognition test was then performed which required discrimination of two trained sequences, either under the instructions to call any sequence encountered in the experiment “old” (the inclusion condition), or only sequence fragments from one half of the experiment “old” (the exclusion condition). The recognition test elicited automatic and controlled process estimates using the process dissociation procedure, and suggested both processes were involved. Examining the underlying processes supporting performance may provide more information on the fundamental aspects of the implicit and explicit constructs than has been attainable through awareness testing. PMID:22679465

Recall is not necessary for verbal sequence learning.

PubMed

Kalm, Kristjan; Norris, Dennis

2016-01-01

The question of whether overt recall of to-be-remembered material accelerates learning is important in a wide range of real-world learning settings. In the case of verbal sequence learning, previous research has proposed that recall either is necessary for verbal sequence learning (Cohen & Johansson Journal of Verbal Learning and Verbal Behavior, 6, 139-143, 1967; Cunningham, Healy, & Williams Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 575-597, 1984), or at least contributes significantly to it (Glass, Krejci, & Goldman Journal of Memory and Language, 28, 189-199, 1989; Oberauer & Meyer Memory, 17, 774-781, 2009). In contrast, here we show that the amount of previous spoken recall does not predict learning and is not necessary for it. We suggest that previous research may have underestimated participants' learning by using suboptimal performance measures, or by using manual or written recall. However, we show that the amount of spoken recall predicted how much interference from other to-be-remembered sequences would be observed. In fact, spoken recall mediated most of the error learning observed in the task. Our data support the view that the learning of overlapping auditory-verbal sequences is driven by learning the phonological representations and not the articulatory motor responses. However, spoken recall seems to reinforce already learned representations, whether they are correct or incorrect, thus contributing to a participant identifying a specific stimulus as either "learned" or "new" during the presentation phase.

Learning of pitch and time structures in an artificial grammar setting.

PubMed

Prince, Jon B; Stevens, Catherine J; Jones, Mari Riess; Tillmann, Barbara

2018-04-12

Despite the empirical evidence for the power of the cognitive capacity of implicit learning of structures and regularities in several modalities and materials, it remains controversial whether implicit learning extends to the learning of temporal structures and regularities. We investigated whether (a) an artificial grammar can be learned equally well when expressed in duration sequences as when expressed in pitch sequences, (b) learning of the artificial grammar in either duration or pitch (as the primary dimension) sequences can be influenced by the properties of the secondary dimension (invariant vs. randomized), and (c) learning can be boosted when the artificial grammar is expressed in both pitch and duration. After an exposure phase with grammatical sequences, learning in a subsequent test phase was assessed in a grammaticality judgment task. Participants in both the pitch and duration conditions showed incidental (not fully implicit) learning of the artificial grammar when the secondary dimension was invariant, but randomizing the pitch sequence prevented learning of the artificial grammar in duration sequences. Expressing the artificial grammar in both pitch and duration resulted in disproportionately better performance, suggesting an interaction between the learning of pitch and temporal structure. The findings are relevant to research investigating the learning of temporal structures and the learning of structures presented simultaneously in 2 dimensions (e.g., space and time, space and objects). By investigating learning, the findings provide further insight into the potential specificity of pitch and time processing, and their integrated versus independent processing, as previously debated in music cognition research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Teaching Task Sequencing via Verbal Mediation.

ERIC Educational Resources Information Center

Rusch, Frank R.; And Others

1987-01-01

Verbal sequence training was used to teach a moderately mentally retarded woman to sequence job-related tasks. Learning to say the tasks in the proper sequence resulted in the employee performing her tasks in that sequence, and the employee was capable of mediating her own work behavior when scheduled changes occurred. (Author/JDD)

Event-related potential correlates of declarative and non-declarative sequence knowledge.

PubMed

Ferdinand, Nicola K; Rünger, Dennis; Frensch, Peter A; Mecklinger, Axel

2010-07-01

The goal of the present study was to demonstrate that declarative and non-declarative knowledge acquired in an incidental sequence learning task contributes differentially to memory retrieval and leads to dissociable ERP signatures in a recognition memory task. For this purpose, participants performed a sequence learning task and were classified as verbalizers, partial verbalizers, or nonverbalizers according to their ability to verbally report the systematic response sequence. Thereafter, ERPs were recorded in a recognition memory task time-locked to sequence triplets that were either part of the previously learned sequence or not. Although all three groups executed old sequence triplets faster than new triplets in the recognition memory task, qualitatively distinct ERP patterns were found for participants with and without reportable knowledge. Verbalizers and, to a lesser extent, partial verbalizers showed an ERP correlate of recollection for parts of the incidentally learned sequence. In contrast, nonverbalizers showed a different ERP effect with a reverse polarity that might reflect priming. This indicates that an ensemble of qualitatively different processes is at work when declarative and non-declarative sequence knowledge is retrieved. By this, our findings favor a multiple-systems view postulating that explicit and implicit learning are supported by different and functionally independent systems. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Sequence specific motor performance gains after memory consolidation in children and adolescents.

PubMed

Dorfberger, Shoshi; Adi-Japha, Esther; Karni, Avi

2012-01-01

Memory consolidation for a trained sequence of finger opposition movements, in 9- and 12-year-old children, was recently found to be significantly less susceptible to interference by a subsequent training experience, compared to that of 17-year-olds. It was suggested that, in children, the experience of training on any sequence of finger movements may affect the performance of the sequence elements, component movements, rather than the sequence as a unit; the latter has been implicated in the learning of the task by adults. This hypothesis implied a possible childhood advantage in the ability to transfer the gains from a trained to the reversed, untrained, sequence of movements. Here we report the results of transfer tests undertaken to test this proposal in 9-, 12-, and 17-year-olds after training in the finger-to-thumb opposition sequence (FOS) learning task. Our results show that the performance gains in the trained sequence partially transferred from the left, trained hand, to the untrained hand at 48-hours after a single training session in the three age-groups tested. However, there was very little transfer of the gains from the trained to the untrained, reversed, sequence performed by either hand. The results indicate sequence specific post-training gains in FOS performance, as opposed to a general improvement in performance of the individual, component, movements that comprised both the trained and untrained sequences. These results do not support the proposal that the reduced susceptibility to interference, in children before adolescence, reflects a difference in movement syntax representation after training.

Pushing the Limits of Imagination: Mental Practice for Learning Sequences

ERIC Educational Resources Information Center

Wohldmann, Erica L.; Healy, Alice F.; Bourne, Lyle E., Jr.

2007-01-01

In 2 experiments, the efficacy of motor imagery for learning to type number sequences was examined. Adults practiced typing 4-digit numbers. Then, during subsequent training, they either typed in the same or a different location, imagined typing, merely looked at each number, or performed an irrelevant task. Repetition priming (faster responses…

Is Implicit Sequence Learning Impaired in Schizophrenia? A Meta-Analysis

ERIC Educational Resources Information Center

Siegert, Richard J.; Weatherall, Mark; Bell, Elliot M.

2008-01-01

Cognition in schizophrenia seems to be characterized by impaired performance on most tests of explicit or declarative learning contrasting with relatively intact performance on most tests of implicit or procedural learning. At the same time there have been conflicting results for studies that have used the Serial Reaction Time (SRT) task to…

Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

PubMed Central

2017-01-01

We describe a fully data driven model that learns to perform a retrosynthetic reaction prediction task, which is treated as a sequence-to-sequence mapping problem. The end-to-end trained model has an encoder–decoder architecture that consists of two recurrent neural networks, which has previously shown great success in solving other sequence-to-sequence prediction tasks such as machine translation. The model is trained on 50,000 experimental reaction examples from the United States patent literature, which span 10 broad reaction types that are commonly used by medicinal chemists. We find that our model performs comparably with a rule-based expert system baseline model, and also overcomes certain limitations associated with rule-based expert systems and with any machine learning approach that contains a rule-based expert system component. Our model provides an important first step toward solving the challenging problem of computational retrosynthetic analysis. PMID:29104927

Retention of Implicit Sequence Learning in Persons who Stutter and Persons with Parkinson's Disease

PubMed Central

Smits-Bandstra, Sarah; Gracco, Vincent

2014-01-01

This study investigated the retention of implicit sequence learning in 14 persons with Parkinson's disease (PPD), 14 persons who stutter (PWS) and 14 control participants. Participants completed a nonsense syllable serial reaction time task in a 120-minute session. Participants named aloud four syllables in response to four visual stimuli. The syllables formed a repeating 8-item sequence not made known to participants. After one week, participants completed a 60-minute retention session that included an explicit learning questionnaire and a sequence generation task. PPD showed retention of general learning equivalent to controls but PWS's reaction times were significantly slower on early trials of the retention test relative to other groups. Controls showed implicit learning during the initial session that was retained on the retention test. In contrast, PPD and PWS did not demonstrate significant implicit learning until the retention test suggesting intact, but delayed, learning and retention of implicit sequencing skills. All groups demonstrated similar limited explicit sequence knowledge. Performance differences between PWS and PPD relative to controls during the initial session and on early retention trials indicated possible dysfunction of the cortico-striato-thalamo-cortical loop. The etiological implications for stuttering, and clinical implications for both populations, of this dysfunction are discussed. PMID:23844763

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

The neural correlates of statistical learning in a word segmentation task: An fMRI study

PubMed Central

Karuza, Elisabeth A.; Newport, Elissa L.; Aslin, Richard N.; Starling, Sarah J.; Tivarus, Madalina E.; Bavelier, Daphne

2013-01-01

Functional magnetic resonance imaging (fMRI) was used to assess neural activation as participants learned to segment continuous streams of speech containing syllable sequences varying in their transitional probabilities. Speech streams were presented in four runs, each followed by a behavioral test to measure the extent of learning over time. Behavioral performance indicated that participants could discriminate statistically coherent sequences (words) from less coherent sequences (partwords). Individual rates of learning, defined as the difference in ratings for words and partwords, were used as predictors of neural activation to ask which brain areas showed activity associated with these measures. Results showed significant activity in the pars opercularis and pars triangularis regions of the left inferior frontal gyrus (LIFG). The relationship between these findings and prior work on the neural basis of statistical learning is discussed, and parallels to the frontal/subcortical network involved in other forms of implicit sequence learning are considered. PMID:23312790

Speech sequence skill learning in adults who stutter.

PubMed

Bauerly, Kim R; De Nil, Luc F

2011-12-01

The present study compared the ability of 12 people who stutter (PWS) and 12 people who do not stutter (PNS) to consolidate a novel sequential speech task. Participants practiced 100 repetitions of a single, monosyllabic, nonsense word sequence during an initial practice session and returned 24-h later to perform an additional 50 repetitions. Results showed significantly slower sequence durations in the PWS compared to PNS following extensive practice and consolidation. However, the hypothesis that poor performance gains in PWS compared to PNS during practice would be maintained following a 24-h consolidation period was not supported. Further descriptive analysis revealed large within group differences in PWS which to some extent were attributed to a subgroup of PWS who failed to show any improvements in performance following practice or consolidation. The results and the possible presence of subgroups of PWS are discussed with regard to their limitations in motor learning abilities. The reader will be able to (1) explain the difference between practice and learning, (2) define consolidation and explain the importance of measuring performance following a consolidation period, (3) understand past research on PWS' performance during both speech and nonspeech motor tasks, and (4) explain why individual differences in practice effects and learning may have important implications for client variability in treatment outcome. Copyright © 2011 Elsevier Inc. All rights reserved.

Protein Sequence Classification with Improved Extreme Learning Machine Algorithms

PubMed Central

2014-01-01

Precisely classifying a protein sequence from a large biological protein sequences database plays an important role for developing competitive pharmacological products. Comparing the unseen sequence with all the identified protein sequences and returning the category index with the highest similarity scored protein, conventional methods are usually time-consuming. Therefore, it is urgent and necessary to build an efficient protein sequence classification system. In this paper, we study the performance of protein sequence classification using SLFNs. The recent efficient extreme learning machine (ELM) and its invariants are utilized as the training algorithms. The optimal pruned ELM is first employed for protein sequence classification in this paper. To further enhance the performance, the ensemble based SLFNs structure is constructed where multiple SLFNs with the same number of hidden nodes and the same activation function are used as ensembles. For each ensemble, the same training algorithm is adopted. The final category index is derived using the majority voting method. Two approaches, namely, the basic ELM and the OP-ELM, are adopted for the ensemble based SLFNs. The performance is analyzed and compared with several existing methods using datasets obtained from the Protein Information Resource center. The experimental results show the priority of the proposed algorithms. PMID:24795876

Insufficient Chunk Concatenation May Underlie Changes in Sleep-Dependent Consolidation of Motor Sequence Learning in Older Adults

ERIC Educational Resources Information Center

Bottary, Ryan; Sonni, Akshata; Wright, David; Spencer, Rebecca M. C.

2016-01-01

Sleep enhances motor sequence learning (MSL) in young adults by concatenating subsequences ("chunks") formed during skill acquisition. To examine whether this process is reduced in aging, we assessed performance changes on the MSL task following overnight sleep or daytime wake in healthy young and older adults. Young adult performance…

Reversible second-order conditional sequences in incidental sequence learning tasks.

PubMed

Pasquali, Antoine; Cleeremans, Axel; Gaillard, Vinciane

2018-06-01

In sequence learning tasks, participants' sensitivity to the sequential structure of a series of events often overshoots their ability to express relevant knowledge intentionally, as in generation tasks that require participants to produce either the next element of a sequence (inclusion) or a different element (exclusion). Comparing generation performance under inclusion and exclusion conditions makes it possible to assess the respective influences of conscious and unconscious learning. Recently, two main concerns have been expressed concerning such tasks. First, it is often difficult to design control sequences in such a way that they enable clear comparisons with the training material. Second, it is challenging to ask participants to perform appropriately under exclusion instructions, for the requirement to exclude familiar responses often leads them to adopt degenerate strategies (e.g., pushing on the same key all the time), which then need to be specifically singled out as invalid. To overcome both concerns, we introduce reversible second-order conditional (RSOC) sequences and show (a) that they elicit particularly strong transfer effects, (b) that dissociation of implicit and explicit influences becomes possible thanks to the removal of salient transitions in RSOCs, and (c) that exclusion instructions can be greatly simplified without losing sensitivity.

Explicit instruction of rules interferes with visuomotor skill transfer.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2017-06-01

In the present study, we examined the effects of explicit knowledge, obtained through instruction or spontaneous detection, on the transfer of visuomotor sequence learning. In the learning session, participants learned a visuomotor sequence, via trial and error. In the transfer session, the order of the sequence was reversed from that of the learning session. Before the commencement of the transfer session, some participants received explicit instruction regarding the reversal rule (i.e., Instruction group), while the others did not receive any information and were sorted into either an Aware or Unaware group, as assessed by interview conducted after the transfer session. Participants in the Instruction and Aware groups performed with fewer errors than the Unaware group in the transfer session. The participants in the Instruction group showed slower speed than the Aware and Unaware groups in the transfer session, and the sluggishness likely persisted even in late learning. These results suggest that explicit knowledge reduces errors in visuomotor skill transfer, but may interfere with performance speed, particularly when explicit knowledge is provided, as opposed to being spontaneously discovered.

Daytime Sleep Enhances Consolidation of the Spatial but Not Motoric Representation of Motor Sequence Memory

PubMed Central

Albouy, Geneviève; Fogel, Stuart; Pottiez, Hugo; Nguyen, Vo An; Ray, Laura; Lungu, Ovidiu; Carrier, Julie; Robertson, Edwin; Doyon, Julien

2013-01-01

Motor sequence learning is known to rely on more than a single process. As the skill develops with practice, two different representations of the sequence are formed: a goal representation built under spatial allocentric coordinates and a movement representation mediated through egocentric motor coordinates. This study aimed to explore the influence of daytime sleep (nap) on consolidation of these two representations. Through the manipulation of an explicit finger sequence learning task and a transfer protocol, we show that both allocentric (spatial) and egocentric (motor) representations of the sequence can be isolated after initial training. Our results also demonstrate that nap favors the emergence of offline gains in performance for the allocentric, but not the egocentric representation, even after accounting for fatigue effects. Furthermore, sleep-dependent gains in performance observed for the allocentric representation are correlated with spindle density during non-rapid eye movement (NREM) sleep of the post-training nap. In contrast, performance on the egocentric representation is only maintained, but not improved, regardless of the sleep/wake condition. These results suggest that motor sequence memory acquisition and consolidation involve distinct mechanisms that rely on sleep (and specifically, spindle) or simple passage of time, depending respectively on whether the sequence is performed under allocentric or egocentric coordinates. PMID:23300993

A deep learning method for lincRNA detection using auto-encoder algorithm.

PubMed

Yu, Ning; Yu, Zeng; Pan, Yi

2017-12-06

RNA sequencing technique (RNA-seq) enables scientists to develop novel data-driven methods for discovering more unidentified lincRNAs. Meantime, knowledge-based technologies are experiencing a potential revolution ignited by the new deep learning methods. By scanning the newly found data set from RNA-seq, scientists have found that: (1) the expression of lincRNAs appears to be regulated, that is, the relevance exists along the DNA sequences; (2) lincRNAs contain some conversed patterns/motifs tethered together by non-conserved regions. The two evidences give the reasoning for adopting knowledge-based deep learning methods in lincRNA detection. Similar to coding region transcription, non-coding regions are split at transcriptional sites. However, regulatory RNAs rather than message RNAs are generated. That is, the transcribed RNAs participate the biological process as regulatory units instead of generating proteins. Identifying these transcriptional regions from non-coding regions is the first step towards lincRNA recognition. The auto-encoder method achieves 100% and 92.4% prediction accuracy on transcription sites over the putative data sets. The experimental results also show the excellent performance of predictive deep neural network on the lincRNA data sets compared with support vector machine and traditional neural network. In addition, it is validated through the newly discovered lincRNA data set and one unreported transcription site is found by feeding the whole annotated sequences through the deep learning machine, which indicates that deep learning method has the extensive ability for lincRNA prediction. The transcriptional sequences of lincRNAs are collected from the annotated human DNA genome data. Subsequently, a two-layer deep neural network is developed for the lincRNA detection, which adopts the auto-encoder algorithm and utilizes different encoding schemes to obtain the best performance over intergenic DNA sequence data. Driven by those newly annotated lincRNA data, deep learning methods based on auto-encoder algorithm can exert their capability in knowledge learning in order to capture the useful features and the information correlation along DNA genome sequences for lincRNA detection. As our knowledge, this is the first application to adopt the deep learning techniques for identifying lincRNA transcription sequences.

Sensitivity to structure in action sequences: An infant event-related potential study.

PubMed

Monroy, Claire D; Gerson, Sarah A; Domínguez-Martínez, Estefanía; Kaduk, Katharina; Hunnius, Sabine; Reid, Vincent

2017-05-06

Infants are sensitive to structure and patterns within continuous streams of sensory input. This sensitivity relies on statistical learning, the ability to detect predictable regularities in spatial and temporal sequences. Recent evidence has shown that infants can detect statistical regularities in action sequences they observe, but little is known about the neural process that give rise to this ability. In the current experiment, we combined electroencephalography (EEG) with eye-tracking to identify electrophysiological markers that indicate whether 8-11-month-old infants detect violations to learned regularities in action sequences, and to relate these markers to behavioral measures of anticipation during learning. In a learning phase, infants observed an actor performing a sequence featuring two deterministic pairs embedded within an otherwise random sequence. Thus, the first action of each pair was predictive of what would occur next. One of the pairs caused an action-effect, whereas the second did not. In a subsequent test phase, infants observed another sequence that included deviant pairs, violating the previously observed action pairs. Event-related potential (ERP) responses were analyzed and compared between the deviant and the original action pairs. Findings reveal that infants demonstrated a greater Negative central (Nc) ERP response to the deviant actions for the pair that caused the action-effect, which was consistent with their visual anticipations during the learning phase. Findings are discussed in terms of the neural and behavioral processes underlying perception and learning of structured action sequences. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

ERIC Educational Resources Information Center

Ritter, Frank E.; Bibby, Peter A.

2008-01-01

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

Sleep to the beat: A nap favours consolidation of timing.

PubMed

Verweij, Ilse M; Onuki, Yoshiyuki; Van Someren, Eus J W; Van der Werf, Ysbrand D

2016-06-01

Growing evidence suggests that sleep is important for procedural learning, but few studies have investigated the effect of sleep on the temporal aspects of motor skill learning. We assessed the effect of a 90-min day-time nap on learning a motor timing task, using 2 adaptations of a serial interception sequence learning (SISL) task. Forty-two right-handed participants performed the task before and after a 90-min period of sleep or wake. Electroencephalography (EEG) was recorded throughout. The motor task consisted of a sequential spatial pattern and was performed according to 2 different timing conditions, that is, either following a sequential or a random temporal pattern. The increase in accuracy was compared between groups using a mixed linear regression model. Within the sleep group, performance improvement was modeled based on sleep characteristics, including spindle- and slow-wave density. The sleep group, but not the wake group, showed improvement in the random temporal, but especially and significantly more strongly in the sequential temporal condition. None of the sleep characteristics predicted improvement on either general of the timing conditions. In conclusion, a daytime nap improves performance on a timing task. We show that performance on the task with a sequential timing sequence benefits more from sleep than motor timing. More important, the temporal sequence did not benefit initial learning, because differences arose only after an offline period and specifically when this period contained sleep. Sleep appears to aid in the extraction of regularities for optimal subsequent performance. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning.

PubMed

Arena, Paolo; Calí, Marco; Patané, Luca; Portera, Agnese; Strauss, Roland

2016-09-01

Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies neuropile. The network devoted to context formation is able to reconstruct the learned sequence and also to trace the subsequences present in the provided input. A sensitivity analysis to parameter variation and noise is reported. Experiments on a roving robot are reported to show the capabilities of the architecture used as a neural controller.

The cortisol awakening response is associated with performance of a serial sequence reaction time task.

PubMed

Hodyl, Nicolette A; Schneider, Luke; Vallence, Ann-Maree; Clow, Angela; Ridding, Michael C; Pitcher, Julia B

2016-02-01

There is emerging evidence of a relationship between the cortisol awakening response (CAR) and the neural mechanisms underlying learning and memory. The aim of this study was to determine whether the CAR is associated with acquisition, retention and overnight consolidation or improvement of a serial sequence reaction time task. Salivary samples were collected at 0, 15, 30 and 45 min after awakening in 39 healthy adults on 2 consecutive days. The serial sequence reaction time task was repeated each afternoon. Participants completed the perceived stress scale and provided salivary samples prior to testing for cortisol assessment. While the magnitude of the CAR (Z score) was not associated with either baseline performance or the timed improvement during task acquisition of the serial sequence task, a positive correlation was observed with reaction times during the stable performance phase on day 1 (r=0.373, p=0.019). Residuals derived from the relationship between baseline and stable phase reaction times on day 1 were used as a surrogate for the degree of learning: these residuals were also correlated with the CAR mean increase on day 1 (r=0.357, p=0.048). Task performance on day 2 was not associated with the CAR obtained on this same day. No association was observed between the perceived stress score, cortisol at testing or task performance. These data indicate that a smaller CAR in healthy adults is associated with a greater degree of learning and faster performance of a serial sequence reaction time task. These results support recognition of the CAR as an important factor contributing to cognitive performance throughout the day. Copyright © 2015 Elsevier B.V. All rights reserved.

Differential working memory correlates for implicit sequence performance in young and older adults.

PubMed

Bo, Jin; Jennett, S; Seidler, R D

2012-09-01

Our recent work has revealed that visuospatial working memory (VSWM) relates to the rate of explicit motor sequence learning (Bo and Seidler in J Neurophysiol 101:3116-3125, 2009) and implicit sequence performance (Bo et al. in Exp Brain Res 214:73-81, 2011a) in young adults (YA). Although aging has a detrimental impact on many cognitive functions, including working memory, older adults (OA) still rely on their declining working memory resources in an effort to optimize explicit motor sequence learning. Here, we evaluated whether age-related differences in VSWM and/or verbal working memory (VWM) performance relates to implicit performance change in the serial reaction time (SRT) sequence task in OA. Participants performed two computerized working memory tasks adapted from change detection working memory assessments (Luck and Vogel in Nature 390:279-281, 1997), an implicit SRT task and several neuropsychological tests. We found that, although OA exhibited an overall reduction in both VSWM and VWM, both OA and YA showed similar performance in the implicit SRT task. Interestingly, while VSWM and VWM were significantly correlated with each other in YA, there was no correlation between these two working memory scores in OA. In YA, the rate of SRT performance change (exponential fit to the performance curve) was significantly correlated with both VSWM and VWM, while in contrast, OA's performance was only correlated with VWM, and not VSWM. These results demonstrate differential reliance on VSWM and VWM for SRT performance between YA and OA. OA may utilize VWM to maintain optimized performance of second-order conditional sequences.

Sleep Does Not Enhance Motor Sequence Learning

ERIC Educational Resources Information Center

Rickard, Timothy C.; Cai, Denise J.; Rieth, Cory A.; Jones, Jason; Ard, M. Colin

2008-01-01

Improvements in motor sequence performance have been observed after a delay involving sleep. This finding has been taken as evidence for an active sleep consolidation process that enhances subsequent performance. In a review of this literature, however, the authors observed 4 aspects of data analyses and experimental design that could lead to…

Procedural Memory Consolidation in the Performance of Brief Keyboard Sequences

ERIC Educational Resources Information Center

Duke, Robert A.; Davis, Carla M.

2006-01-01

Using two sequential key press sequences, we tested the extent to which subjects' performance on a digital piano keyboard changed between the end of training and retest on subsequent days. We found consistent, significant improvements attributable to sleep-based consolidation effects, indicating that learning continued after the cessation of…

Correct machine learning on protein sequences: a peer-reviewing perspective.

PubMed

Walsh, Ian; Pollastri, Gianluca; Tosatto, Silvio C E

2016-09-01

Machine learning methods are becoming increasingly popular to predict protein features from sequences. Machine learning in bioinformatics can be powerful but carries also the risk of introducing unexpected biases, which may lead to an overestimation of the performance. This article espouses a set of guidelines to allow both peer reviewers and authors to avoid common machine learning pitfalls. Understanding biology is necessary to produce useful data sets, which have to be large and diverse. Separating the training and test process is imperative to avoid over-selling method performance, which is also dependent on several hidden parameters. A novel predictor has always to be compared with several existing methods, including simple baseline strategies. Using the presented guidelines will help nonspecialists to appreciate the critical issues in machine learning. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Recurrent Neural Networks With Auxiliary Memory Units.

PubMed

Wang, Jianyong; Zhang, Lei; Guo, Quan; Yi, Zhang

2018-05-01

Memory is one of the most important mechanisms in recurrent neural networks (RNNs) learning. It plays a crucial role in practical applications, such as sequence learning. With a good memory mechanism, long term history can be fused with current information, and can thus improve RNNs learning. Developing a suitable memory mechanism is always desirable in the field of RNNs. This paper proposes a novel memory mechanism for RNNs. The main contributions of this paper are: 1) an auxiliary memory unit (AMU) is proposed, which results in a new special RNN model (AMU-RNN), separating the memory and output explicitly and 2) an efficient learning algorithm is developed by employing the technique of error flow truncation. The proposed AMU-RNN model, together with the developed learning algorithm, can learn and maintain stable memory over a long time range. This method overcomes both the learning conflict problem and gradient vanishing problem. Unlike the traditional method, which mixes the memory and output with a single neuron in a recurrent unit, the AMU provides an auxiliary memory neuron to maintain memory in particular. By separating the memory and output in a recurrent unit, the problem of learning conflicts can be eliminated easily. Moreover, by using the technique of error flow truncation, each auxiliary memory neuron ensures constant error flow during the learning process. The experiments demonstrate good performance of the proposed AMU-RNNs and the developed learning algorithm. The method exhibits quite efficient learning performance with stable convergence in the AMU-RNN learning and outperforms the state-of-the-art RNN models in sequence generation and sequence classification tasks.

An In Vivo Study of Self-Regulated Study Sequencing in Introductory Psychology Courses

PubMed Central

de Leeuw, Joshua R.; Motz, Benjamin A.; Goldstone, Robert L.

2016-01-01

Study sequence can have a profound influence on learning. In this study we investigated how students decide to sequence their study in a naturalistic context and whether their choices result in improved learning. In the study reported here, 2061 undergraduate students enrolled in an Introductory Psychology course completed an online homework tutorial on measures of central tendency, a topic relevant to an exam that counted towards their grades. One group of students was enabled to choose their own study sequence during the tutorial (Self-Regulated group), while the other group of students studied the same materials in sequences chosen by other students (Yoked group). Students who chose their sequence of study showed a clear tendency to block their study by concept, and this tendency was positively associated with subsequent exam performance. In the Yoked group, study sequence had no effect on exam performance. These results suggest that despite findings that blocked study is maladaptive when assigned by an experimenter, it may actually be adaptive when chosen by the learner in a naturalistic context. PMID:27003164

An In Vivo Study of Self-Regulated Study Sequencing in Introductory Psychology Courses.

PubMed

Carvalho, Paulo F; Braithwaite, David W; de Leeuw, Joshua R; Motz, Benjamin A; Goldstone, Robert L

2016-01-01

Study sequence can have a profound influence on learning. In this study we investigated how students decide to sequence their study in a naturalistic context and whether their choices result in improved learning. In the study reported here, 2061 undergraduate students enrolled in an Introductory Psychology course completed an online homework tutorial on measures of central tendency, a topic relevant to an exam that counted towards their grades. One group of students was enabled to choose their own study sequence during the tutorial (Self-Regulated group), while the other group of students studied the same materials in sequences chosen by other students (Yoked group). Students who chose their sequence of study showed a clear tendency to block their study by concept, and this tendency was positively associated with subsequent exam performance. In the Yoked group, study sequence had no effect on exam performance. These results suggest that despite findings that blocked study is maladaptive when assigned by an experimenter, it may actually be adaptive when chosen by the learner in a naturalistic context.

Translating visual information into action predictions: Statistical learning in action and nonaction contexts.

PubMed

Monroy, Claire D; Gerson, Sarah A; Hunnius, Sabine

2018-05-01

Humans are sensitive to the statistical regularities in action sequences carried out by others. In the present eyetracking study, we investigated whether this sensitivity can support the prediction of upcoming actions when observing unfamiliar action sequences. In two between-subjects conditions, we examined whether observers would be more sensitive to statistical regularities in sequences performed by a human agent versus self-propelled 'ghost' events. Secondly, we investigated whether regularities are learned better when they are associated with contingent effects. Both implicit and explicit measures of learning were compared between agent and ghost conditions. Implicit learning was measured via predictive eye movements to upcoming actions or events, and explicit learning was measured via both uninstructed reproduction of the action sequences and verbal reports of the regularities. The findings revealed that participants, regardless of condition, readily learned the regularities and made correct predictive eye movements to upcoming events during online observation. However, different patterns of explicit-learning outcomes emerged following observation: Participants were most likely to re-create the sequence regularities and to verbally report them when they had observed an actor create a contingent effect. These results suggest that the shift from implicit predictions to explicit knowledge of what has been learned is facilitated when observers perceive another agent's actions and when these actions cause effects. These findings are discussed with respect to the potential role of the motor system in modulating how statistical regularities are learned and used to modify behavior.

Cognitive Fatigue Facilitates Procedural Sequence Learning.

PubMed

Borragán, Guillermo; Slama, Hichem; Destrebecqz, Arnaud; Peigneux, Philippe

2016-01-01

Enhanced procedural learning has been evidenced in conditions where cognitive control is diminished, including hypnosis, disruption of prefrontal activity and non-optimal time of the day. Another condition depleting the availability of controlled resources is cognitive fatigue (CF). We tested the hypothesis that CF, eventually leading to diminished cognitive control, facilitates procedural sequence learning. In a two-day experiment, 23 young healthy adults were administered a serial reaction time task (SRTT) following the induction of high or low levels of CF, in a counterbalanced order. CF was induced using the Time load Dual-back (TloadDback) paradigm, a dual working memory task that allows tailoring cognitive load levels to the individual's optimal performance capacity. In line with our hypothesis, reaction times (RT) in the SRTT were faster in the high- than in the low-level fatigue condition, and performance improvement was higher for the sequential than the motor components. Altogether, our results suggest a paradoxical, facilitating impact of CF on procedural motor sequence learning. We propose that facilitated learning in the high-level fatigue condition stems from a reduction in the cognitive resources devoted to cognitive control processes that normally oppose automatic procedural acquisition mechanisms.

An online supervised learning method based on gradient descent for spiking neurons.

PubMed

Xu, Yan; Yang, Jing; Zhong, Shuiming

2017-09-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Task analysis in curriculum design: a hierarchically sequenced introductory mathematics curriculum1

PubMed Central

Resnick, Lauren B.; Wang, Margaret C.; Kaplan, Jerome

1973-01-01

A method of systematic task analysis is applied to the problem of designing a sequence of learning objectives that will provide an optimal match for the child's natural sequence of acquisition of mathematical skills and concepts. The authors begin by proposing an operational definition of the number concept in the form of a set of behaviors which, taken together, permit the inference that the child has an abstract concept of “number”. These are the “objectives” of the curriculum. Each behavior in the defining set is then subjected to an analysis that identifies hypothesized components of skilled performance and prerequisites for learning these components. On the basis of these analyses, specific sequences of learning objectives are proposed. The proposed sequences are hypothesized to be those that will best facilitate learning, by maximizing transfer from earlier to later objectives. Relevant literature on early learning and cognitive development is considered in conjunction with the analyses and the resulting sequences. The paper concludes with a discussion of the ways in which the curriculum can be implemented and studied in schools. Examples of data on individual children are presented, and the use of such data for improving the curriculum itself, as well as for examining the effects of other treatment variables, is considered. PMID:16795452

Mining Learning Behavioral Patterns of Students by Sequence Analysis in Cloud Classroom

ERIC Educational Resources Information Center

Liu, Sanya; Hu, Zhenfan; Peng, Xian; Liu, Zhi; Cheng, H. N. H.; Sun, Jianwen

2017-01-01

In a MOOC environment, each student's interaction with the course content is a crucial clue for learning analytics, which offers an opportunity to record learner activity of unprecedented scale. In online learning, the educators and the administrators need to get informed with students' learning states since the performance of unsupervised…

Insufficient chunk concatenation may underlie changes in sleep-dependent consolidation of motor sequence learning in older adults.

PubMed

Bottary, Ryan; Sonni, Akshata; Wright, David; Spencer, Rebecca M C

2016-09-01

Sleep enhances motor sequence learning (MSL) in young adults by concatenating subsequences ("chunks") formed during skill acquisition. To examine whether this process is reduced in aging, we assessed performance changes on the MSL task following overnight sleep or daytime wake in healthy young and older adults. Young adult performance enhancement was correlated with nREM2 sleep, and facilitated by preferential improvement of slowest within-sequence transitions. This effect was markedly reduced in older adults, and accompanied by diminished sigma power density (12-15 Hz) during nREM2 sleep, suggesting that diminished chunk concatenation following sleep may underlie reduced consolidation of MSL in older adults. © 2016 Bottary et al.; Published by Cold Spring Harbor Laboratory Press.

Musical Sequence Learning and EEG Correlates of Audiomotor Processing

PubMed Central

Schalles, Matt D.; Pineda, Jaime A.

2015-01-01

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

Brain Activation in Motor Sequence Learning Is Related to the Level of Native Cortical Excitability

PubMed Central

Lissek, Silke; Vallana, Guido S.; Güntürkün, Onur; Dinse, Hubert; Tegenthoff, Martin

2013-01-01

Cortical excitability may be subject to changes through training and learning. Motor training can increase cortical excitability in motor cortex, and facilitation of motor cortical excitability has been shown to be positively correlated with improvements in performance in simple motor tasks. Thus cortical excitability may tentatively be considered as a marker of learning and use-dependent plasticity. Previous studies focused on changes in cortical excitability brought about by learning processes, however, the relation between native levels of cortical excitability on the one hand and brain activation and behavioral parameters on the other is as yet unknown. In the present study we investigated the role of differential native motor cortical excitability for learning a motor sequencing task with regard to post-training changes in excitability, behavioral performance and involvement of brain regions. Our motor task required our participants to reproduce and improvise over a pre-learned motor sequence. Over both task conditions, participants with low cortical excitability (CElo) showed significantly higher BOLD activation in task-relevant brain regions than participants with high cortical excitability (CEhi). In contrast, CElo and CEhi groups did not exhibit differences in percentage of correct responses and improvisation level. Moreover, cortical excitability did not change significantly after learning and training in either group, with the exception of a significant decrease in facilitatory excitability in the CEhi group. The present data suggest that the native, unmanipulated level of cortical excitability is related to brain activation intensity, but not to performance quality. The higher BOLD mean signal intensity during the motor task might reflect a compensatory mechanism in CElo participants. PMID:23613956

Domain-specific and domain-general constraints on word and sequence learning.

PubMed

Archibald, Lisa M D; Joanisse, Marc F

2013-02-01

The relative influences of language-related and memory-related constraints on the learning of novel words and sequences were examined by comparing individual differences in performance of children with and without specific deficits in either language or working memory. Children recalled lists of words in a Hebbian learning protocol in which occasional lists repeated, yielding improved recall over the course of the task on the repeated lists. The task involved presentation of pictures of common nouns followed immediately by equivalent presentations of the spoken names. The same participants also completed a paired-associate learning task involving word-picture and nonword-picture pairs. Hebbian learning was observed for all groups. Domain-general working memory constrained immediate recall, whereas language abilities impacted recall in the auditory modality only. In addition, working memory constrained paired-associate learning generally, whereas language abilities disproportionately impacted novel word learning. Overall, all of the learning tasks were highly correlated with domain-general working memory. The learning of nonwords was additionally related to general intelligence, phonological short-term memory, language abilities, and implicit learning. The results suggest that distinct associations between language- and memory-related mechanisms support learning of familiar and unfamiliar phonological forms and sequences.

Deep Recurrent Neural Networks for Human Activity Recognition

PubMed Central

Murad, Abdulmajid

2017-01-01

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs. PMID:29113103

Deep Recurrent Neural Networks for Human Activity Recognition.

PubMed

Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

Deep learning methods for protein torsion angle prediction.

PubMed

Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

2017-09-18

Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

Variable Behavior and Repeated Learning in Two Mouse Strains: Developmental and Genetic Contributions.

PubMed

Arnold, Megan A; Newland, M Christopher

2018-06-16

Behavioral inflexibility is often assessed using reversal learning tasks, which require a relatively low degree of response variability. No studies have assessed sensitivity to reinforcement contingencies that specifically select highly variable response patterns in mice, let alone in models of neurodevelopmental disorders involving limited response variation. Operant variability and incremental repeated acquisition (IRA) were used to assess unique aspects of behavioral variability of two mouse strains: BALB/c, a model of some deficits in ASD, and C57Bl/6. On the operant variability task, BALB/c mice responded more repetitively during adolescence than C57Bl/6 mice when reinforcement did not require variability but responded more variably when reinforcement required variability. During IRA testing in adulthood, both strains acquired an unchanging, performance sequence equally well. Strain differences emerged, however, after novel learning sequences began alternating with the performance sequence: BALB/c mice substantially outperformed C57Bl/6 mice. Using litter-mate controls, it was found that adolescent experience with variability did not affect either learning or performance on the IRA task in adulthood. These findings constrain the use of BALB/c mice as a model of ASD, but once again reveal this strain is highly sensitive to reinforcement contingencies and they are fast and robust learners. Copyright © 2018. Published by Elsevier B.V.

Using machine learning for sequence-level automated MRI protocol selection in neuroradiology.

PubMed

Brown, Andrew D; Marotta, Thomas R

2018-05-01

Incorrect imaging protocol selection can lead to important clinical findings being missed, contributing to both wasted health care resources and patient harm. We present a machine learning method for analyzing the unstructured text of clinical indications and patient demographics from magnetic resonance imaging (MRI) orders to automatically protocol MRI procedures at the sequence level. We compared 3 machine learning models - support vector machine, gradient boosting machine, and random forest - to a baseline model that predicted the most common protocol for all observations in our test set. The gradient boosting machine model significantly outperformed the baseline and demonstrated the best performance of the 3 models in terms of accuracy (95%), precision (86%), recall (80%), and Hamming loss (0.0487). This demonstrates the feasibility of automating sequence selection by applying machine learning to MRI orders. Automated sequence selection has important safety, quality, and financial implications and may facilitate improvements in the quality and safety of medical imaging service delivery.

One hertz repetitive transcranial magnetic stimulation over dorsal premotor cortex enhances offline motor memory consolidation for sequence-specific implicit learning.

PubMed

Meehan, S K; Zabukovec, J R; Dao, E; Cheung, K L; Linsdell, M A; Boyd, L A

2013-10-01

Consolidation of motor memories associated with skilled practice can occur both online, concurrent with practice, and offline, after practice has ended. The current study investigated the role of dorsal premotor cortex (PMd) in early offline motor memory consolidation of implicit sequence-specific learning. Thirty-three participants were assigned to one of three groups of repetitive transcranial magnetic stimulation (rTMS) over left PMd (5 Hz, 1 Hz or control) immediately following practice of a novel continuous tracking task. There was no additional practice following rTMS. This procedure was repeated for 4 days. The continuous tracking task contained a repeated sequence that could be learned implicitly and random sequences that could not. On a separate fifth day, a retention test was performed to assess implicit sequence-specific motor learning of the task. Tracking error was decreased for the group who received 1 Hz rTMS over the PMd during the early consolidation period immediately following practice compared with control or 5 Hz rTMS. Enhanced sequence-specific learning with 1 Hz rTMS following practice was due to greater offline consolidation, not differences in online learning between the groups within practice days. A follow-up experiment revealed that stimulation of PMd following practice did not differentially change motor cortical excitability, suggesting that changes in offline consolidation can be largely attributed to stimulation-induced changes in PMd. These findings support a differential role for the PMd in support of online and offline sequence-specific learning of a visuomotor task and offer converging evidence for competing memory systems. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

A parallelized binary search tree

USDA-ARS?s Scientific Manuscript database

PTTRNFNDR is an unsupervised statistical learning algorithm that detects patterns in DNA sequences, protein sequences, or any natural language texts that can be decomposed into letters of a finite alphabet. PTTRNFNDR performs complex mathematical computations and its processing time increases when i...

Effects of learning with explicit elaboration on implicit transfer of visuomotor sequence learning.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2013-08-01

Intervals between stimuli and/or responses have significant influences on sequential learning. In the present study, we investigated whether transfer would occur even when the intervals and the visual configurations in a sequence were drastically changed so that participants did not notice that the required sequences of responses were identical. In the experiment, two (or three) sequential button presses comprised a "set," and nine (or six) consecutive sets comprised a "hyperset." In the first session, participants learned either a 2 × 9 or 3 × 6 hyperset by trial and error until they completed it 20 times without error. In the second block, the 2 × 9 (3 × 6) hyperset was changed into the 3 × 6 (2 × 9) hyperset, resulting in different visual configurations and intervals between stimuli and responses. Participants were assigned into two groups: the Identical and Random groups. In the Identical group, the sequence (i.e., the buttons to be pressed) in the second block was identical to that in the first block. In the Random group, a new hyperset was learned. Even in the Identical group, no participants noticed that the sequences were identical. Nevertheless, a significant transfer of performance occurred. However, in the subsequent experiment that did not require explicit trial-and-error learning in the first session, implicit transfer in the second session did not occur. These results indicate that learning with explicit elaboration strengthens the implicit representation of the sequence order as a whole; this might occur independently of the intervals between elements and enable implicit transfer.

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

PubMed Central

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

2012-01-01

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

Does Post-task Declarative Learning Have an Influence on Early Motor Memory Consolidation Over Day? An fMRI Study

PubMed Central

Rothkirch, Inken; Wolff, Stephan; Margraf, Nils G.; Pedersen, Anya; Witt, Karsten

2018-01-01

Previous studies demonstrated the influence of the post-learning period on procedural motor memory consolidation. In an early period after the acquisition, motor skills are vulnerable to modifications during wakefulness. Indeed, specific interventions such as world-list learning within this early phase of motor memory consolidation seem to enhance motor performance as an indicator for successful consolidation. This finding highlights the idea that manipulations of procedural and declarative memory systems during the early phase of memory consolidation over wakefulness may influence off-line consolidation. Using functional magnetic resonance imaging (fMRI) during initial motor sequence learning and motor sequence recall, we indirectly assess the influence of a secondary task taken place in the early phase of memory consolidation. All participants were scanned using fMRI during the learning phase of a serial reaction time task (SRTT) at 8 a.m. Afterwards, they were randomly assigned to one of five conditions. One group performed a declarative verbal, one a declarative nonverbal learning task. Two groups worked on attention tasks. A control group passed a resting condition. Participants stayed awake the whole day and performed the SRTT in the MRI scanner 12 h later at 8 p.m. At the behavioral level, the analysis of the reaction times failed to show a significant group difference. The primary analysis assessing fMRI data based on the contrast (sequence – random) between learning and retrieval also did not show any significant group differences. Therefore, our main analysis do not support the hypothesis that a secondary task influences the retrieval of the SRTT. In a more liberal fMRI analysis, we compared only the sequence blocks of the SRTT from learning to recall. BOLD signal decreased in the ipsilateral cerebellum and the supplementary motor area solely in the verbal learning group. Although our primary analysis failed to show significant changes between our groups, results of the secondary analysis could be an indication for a beneficial effect of the verbal declarative task in the early post-learning phase. A nonverbal learning task did not affect the activation within the motor network. Further studies are needed to replicate this finding and to assess the usefulness of this manipulation. PMID:29755315

Does Post-task Declarative Learning Have an Influence on Early Motor Memory Consolidation Over Day? An fMRI Study.

PubMed

Rothkirch, Inken; Wolff, Stephan; Margraf, Nils G; Pedersen, Anya; Witt, Karsten

2018-01-01

Previous studies demonstrated the influence of the post-learning period on procedural motor memory consolidation. In an early period after the acquisition, motor skills are vulnerable to modifications during wakefulness. Indeed, specific interventions such as world-list learning within this early phase of motor memory consolidation seem to enhance motor performance as an indicator for successful consolidation. This finding highlights the idea that manipulations of procedural and declarative memory systems during the early phase of memory consolidation over wakefulness may influence off-line consolidation. Using functional magnetic resonance imaging (fMRI) during initial motor sequence learning and motor sequence recall, we indirectly assess the influence of a secondary task taken place in the early phase of memory consolidation. All participants were scanned using fMRI during the learning phase of a serial reaction time task (SRTT) at 8 a.m. Afterwards, they were randomly assigned to one of five conditions. One group performed a declarative verbal, one a declarative nonverbal learning task. Two groups worked on attention tasks. A control group passed a resting condition. Participants stayed awake the whole day and performed the SRTT in the MRI scanner 12 h later at 8 p.m. At the behavioral level, the analysis of the reaction times failed to show a significant group difference. The primary analysis assessing fMRI data based on the contrast (sequence - random) between learning and retrieval also did not show any significant group differences. Therefore, our main analysis do not support the hypothesis that a secondary task influences the retrieval of the SRTT. In a more liberal fMRI analysis, we compared only the sequence blocks of the SRTT from learning to recall. BOLD signal decreased in the ipsilateral cerebellum and the supplementary motor area solely in the verbal learning group. Although our primary analysis failed to show significant changes between our groups, results of the secondary analysis could be an indication for a beneficial effect of the verbal declarative task in the early post-learning phase. A nonverbal learning task did not affect the activation within the motor network. Further studies are needed to replicate this finding and to assess the usefulness of this manipulation.

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.

Degree of Handedness Affects Intermanual Transfer of Skill Learning

PubMed Central

Chase, Cori; Seidler, Rachael

2008-01-01

Intermanual transfer of skill learning has often been used as a paradigm to study functional specialization and hemispheric interactions in relation to handedness. This literature has not evaluated whether degree of handedness impacts learning and intermanual transfer. Because handedness scores are related to factors that might influence intermanual transfer, such as engagement of the ipsilateral hemisphere during movement and corpus callosum volume, we tested whether degree of handedness is correlated with transfer magnitude. We had groups of left and right handed participants perform a sensorimotor adaptation task and a sequence learning task. Following learning with either the dominant or nondominant hand, participants transferred to task performance with the other hand. We evaluated whether the magnitude of learning and intermanual transfer were influenced by either direction and / or degree of handedness. Participants exhibited faster sensorimotor adaptation with the right hand, regardless of whether they were right or left handed. In addition, less strongly left handed individuals exhibited better intermanual transfer of sensorimotor adaptation, while less strongly right handed individuals exhibited better intermanual transfer of sequence learning. The findings suggest that involvement of the ipsilateral hemisphere during learning may influence intermanual transfer magnitude. PMID:18592225

RM-SORN: a reward-modulated self-organizing recurrent neural network.

PubMed

Aswolinskiy, Witali; Pipa, Gordon

2015-01-01

Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain.

Laminar Cortical Dynamics of Cognitive and Motor Working Memory, Sequence Learning and Performance: Toward a Unified Theory of How the Cerebral Cortex Works

ERIC Educational Resources Information Center

Grossberg, Stephen; Pearson, Lance R.

2008-01-01

How does the brain carry out working memory storage, categorization, and voluntary performance of event sequences? The LIST PARSE neural model proposes an answer that unifies the explanation of cognitive, neurophysiological, and anatomical data. It quantitatively simulates human cognitive data about immediate serial recall and free recall, and…

Process Mining Techniques for Analysing Patterns and Strategies in Students' Self-Regulated Learning

ERIC Educational Resources Information Center

Bannert, Maria; Reimann, Peter; Sonnenberg, Christoph

2014-01-01

Referring to current research on self-regulated learning, we analyse individual regulation in terms of a set of specific sequences of regulatory activities. Successful students perform regulatory activities such as analysing, planning, monitoring and evaluating cognitive and motivational aspects during learning not only with a higher frequency…

Discovering the Effects of Metacognitive Prompts on the Sequential Structure of SRL-Processes Using Process Mining Techniques

ERIC Educational Resources Information Center

Sonnenberg, Christoph; Bannert, Maria

2015-01-01

According to research examining self-regulated learning (SRL), we regard individual regulation as a specific sequence of regulatory activities. Ideally, students perform various learning activities, such as analyzing, monitoring, and evaluating cognitive and motivational aspects during learning. Metacognitive prompts can foster SRL by inducing…

Performance Based Traffic Safety Education Course. Two-Phase Program.

ERIC Educational Resources Information Center

Washington State Board of Education, Olympia.

This course for high school highway traffic safety education is intended to help students learn to make good driving decisions. It consists of twenty-one modules--ten sequenced, two not in specific sequence but intended to be completed in the earlier part of the course, and nine non-sequenced modules. Each module begins with an outline providing…

Motor set in Parkinson's disease.

PubMed Central

Robertson, C; Flowers, K A

1990-01-01

Three experiments employing a five-choice button-pressing task tested the ability of Parkinsonian patients to learn and generate sequences of movement, and to switch between alternative sequences at will. It was found that patients could learn and generate individual patterns of movement normally, even complex ones involving an incompatible stimulus-response relationship. They had difficulty, however, in maintaining a sequence if two different ones had been learnt and subjects were required to switch spontaneously from one to the other within a trial. Providing external cues at the start of each sequence to guide the ordering of movements improved the stability of patients' performance. Most errors in sequencing consisted of reverting to the alternative pattern of movement. Parkinsonian subjects thus show an impairment in motor set similar to that found previously in cognitive activity. Images PMID:2391523

SOVEREIGN: An autonomous neural system for incrementally learning planned action sequences to navigate towards a rewarded goal.

PubMed

Gnadt, William; Grossberg, Stephen

2008-06-01

How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile robots, or animats, need reactive mechanisms for exploration, and learned plans to reach goal objects once an environment becomes familiar. The SOVEREIGN (Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation) animat model embodies these capabilities, and is tested in a 3D virtual reality environment. SOVEREIGN includes several interacting subsystems which model complementary properties of cortical What and Where processing streams and which clarify similarities between mechanisms for navigation and arm movement control. As the animat explores an environment, visual inputs are processed by networks that are sensitive to visual form and motion in the What and Where streams, respectively. Position-invariant and size-invariant recognition categories are learned by real-time incremental learning in the What stream. Estimates of target position relative to the animat are computed in the Where stream, and can activate approach movements toward the target. Motion cues from animat locomotion can elicit head-orienting movements to bring a new target into view. Approach and orienting movements are alternately performed during animat navigation. Cumulative estimates of each movement are derived from interacting proprioceptive and visual cues. Movement sequences are stored within a motor working memory. Sequences of visual categories are stored in a sensory working memory. These working memories trigger learning of sensory and motor sequence categories, or plans, which together control planned movements. Predictively effective chunk combinations are selectively enhanced via reinforcement learning when the animat is rewarded. Selected planning chunks effect a gradual transition from variable reactive exploratory movements to efficient goal-oriented planned movement sequences. Volitional signals gate interactions between model subsystems and the release of overt behaviors. The model can control different motor sequences under different motivational states and learns more efficient sequences to rewarded goals as exploration proceeds.

Prediction of enhancer-promoter interactions via natural language processing.

PubMed

Zeng, Wanwen; Wu, Mengmeng; Jiang, Rui

2018-05-09

Precise identification of three-dimensional genome organization, especially enhancer-promoter interactions (EPIs), is important to deciphering gene regulation, cell differentiation and disease mechanisms. Currently, it is a challenging task to distinguish true interactions from other nearby non-interacting ones since the power of traditional experimental methods is limited due to low resolution or low throughput. We propose a novel computational framework EP2vec to assay three-dimensional genomic interactions. We first extract sequence embedding features, defined as fixed-length vector representations learned from variable-length sequences using an unsupervised deep learning method in natural language processing. Then, we train a classifier to predict EPIs using the learned representations in supervised way. Experimental results demonstrate that EP2vec obtains F1 scores ranging from 0.841~ 0.933 on different datasets, which outperforms existing methods. We prove the robustness of sequence embedding features by carrying out sensitivity analysis. Besides, we identify motifs that represent cell line-specific information through analysis of the learned sequence embedding features by adopting attention mechanism. Last, we show that even superior performance with F1 scores 0.889~ 0.940 can be achieved by combining sequence embedding features and experimental features. EP2vec sheds light on feature extraction for DNA sequences of arbitrary lengths and provides a powerful approach for EPIs identification.

Relationship between perceptual learning in speech and statistical learning in younger and older adults

PubMed Central

Neger, Thordis M.; Rietveld, Toni; Janse, Esther

2014-01-01

Within a few sentences, listeners learn to understand severely degraded speech such as noise-vocoded speech. However, individuals vary in the amount of such perceptual learning and it is unclear what underlies these differences. The present study investigates whether perceptual learning in speech relates to statistical learning, as sensitivity to probabilistic information may aid identification of relevant cues in novel speech input. If statistical learning and perceptual learning (partly) draw on the same general mechanisms, then statistical learning in a non-auditory modality using non-linguistic sequences should predict adaptation to degraded speech. In the present study, 73 older adults (aged over 60 years) and 60 younger adults (aged between 18 and 30 years) performed a visual artificial grammar learning task and were presented with 60 meaningful noise-vocoded sentences in an auditory recall task. Within age groups, sentence recognition performance over exposure was analyzed as a function of statistical learning performance, and other variables that may predict learning (i.e., hearing, vocabulary, attention switching control, working memory, and processing speed). Younger and older adults showed similar amounts of perceptual learning, but only younger adults showed significant statistical learning. In older adults, improvement in understanding noise-vocoded speech was constrained by age. In younger adults, amount of adaptation was associated with lexical knowledge and with statistical learning ability. Thus, individual differences in general cognitive abilities explain listeners' variability in adapting to noise-vocoded speech. Results suggest that perceptual and statistical learning share mechanisms of implicit regularity detection, but that the ability to detect statistical regularities is impaired in older adults if visual sequences are presented quickly. PMID:25225475

Relationship between perceptual learning in speech and statistical learning in younger and older adults.

PubMed

Neger, Thordis M; Rietveld, Toni; Janse, Esther

2014-01-01

Within a few sentences, listeners learn to understand severely degraded speech such as noise-vocoded speech. However, individuals vary in the amount of such perceptual learning and it is unclear what underlies these differences. The present study investigates whether perceptual learning in speech relates to statistical learning, as sensitivity to probabilistic information may aid identification of relevant cues in novel speech input. If statistical learning and perceptual learning (partly) draw on the same general mechanisms, then statistical learning in a non-auditory modality using non-linguistic sequences should predict adaptation to degraded speech. In the present study, 73 older adults (aged over 60 years) and 60 younger adults (aged between 18 and 30 years) performed a visual artificial grammar learning task and were presented with 60 meaningful noise-vocoded sentences in an auditory recall task. Within age groups, sentence recognition performance over exposure was analyzed as a function of statistical learning performance, and other variables that may predict learning (i.e., hearing, vocabulary, attention switching control, working memory, and processing speed). Younger and older adults showed similar amounts of perceptual learning, but only younger adults showed significant statistical learning. In older adults, improvement in understanding noise-vocoded speech was constrained by age. In younger adults, amount of adaptation was associated with lexical knowledge and with statistical learning ability. Thus, individual differences in general cognitive abilities explain listeners' variability in adapting to noise-vocoded speech. Results suggest that perceptual and statistical learning share mechanisms of implicit regularity detection, but that the ability to detect statistical regularities is impaired in older adults if visual sequences are presented quickly.

A Spiking Neural Network System for Robust Sequence Recognition.

PubMed

Yu, Qiang; Yan, Rui; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2016-03-01

This paper proposes a biologically plausible network architecture with spiking neurons for sequence recognition. This architecture is a unified and consistent system with functional parts of sensory encoding, learning, and decoding. This is the first systematic model attempting to reveal the neural mechanisms considering both the upstream and the downstream neurons together. The whole system is a consistent temporal framework, where the precise timing of spikes is employed for information processing and cognitive computing. Experimental results show that the system is competent to perform the sequence recognition, being robust to noisy sensory inputs and invariant to changes in the intervals between input stimuli within a certain range. The classification ability of the temporal learning rule used in the system is investigated through two benchmark tasks that outperform the other two widely used learning rules for classification. The results also demonstrate the computational power of spiking neurons over perceptrons for processing spatiotemporal patterns. In summary, the system provides a general way with spiking neurons to encode external stimuli into spatiotemporal spikes, to learn the encoded spike patterns with temporal learning rules, and to decode the sequence order with downstream neurons. The system structure would be beneficial for developments in both hardware and software.

Restricted transfer of learning between unimanual and bimanual finger sequences

PubMed Central

Bai, Wenjun

2016-01-01

When training bimanual skills, such as playing piano, people sometimes practice each hand separately and at a later stage combine the movements of the two hands. This poses the critical question of whether motor skills can be acquired by separately practicing each subcomponent or should be trained as a whole. In the present study, we addressed this question by training human subjects for 4 days in a unimanual or bimanual version of the discrete sequence production task. Both groups were then tested on trained and untrained sequences on both unimanual and bimanual versions of the task. Surprisingly, we found no evidence of transfer from trained unimanual to bimanual or from trained bimanual to unimanual sequences. In half the participants, we also investigated whether cuing the sequences on the left and right hand with unique letters would change transfer. With these cues, untrained sequences that shared some components with the trained sequences were performed more quickly than sequences that did not. However, the amount of this transfer was limited to ∼10% of the overall sequence-specific learning gains. These results suggest that unimanual and bimanual sequences are learned in separate representations. Making participants aware of the interrelationship between sequences can induce some transferrable component, although the main component of the skill remains unique to unimanual or bimanual execution. NEW & NOTEWORTHY Studies in reaching movement demonstrated that approximately half of motor learning can transfer across unimanual and bimanual contexts, suggesting that neural representations for unimanual and bimanual movements are fairly overlapping at the level of elementary movement. In this study, we show that little or no transfer occurred across unimanual and bimanual sequential finger movements. This result suggests that bimanual sequences are represented at a level of the motor hierarchy that integrates movements of both hands. PMID:27974447

The transfer of movement sequences: effects of decreased and increased load.

PubMed

Muehlbauer, Thomas; Panzer, Stefan; Shea, Charles H

2007-06-01

A number of recent experiments have demonstrated that a movement structure develops during the course of learning a movement sequence that provides the basis for transfer. After learning a movement sequence participants have been shown to be able to effectively produce the sequence when movement demands require that the sequence be rescaled in amplitude or produced with an unpractised set of effectors. The purpose of the present experiment was to determine whether participants, after learning a complex 16-element movement sequence with a 0.567-kg load, could also effectively produce the sequence when the load was decreased (0.0 kg) or increased (1.134 kg). The results indicated that participants were able to effectively compensate for decreased and increased load with virtually no changes in performance characteristics (displacement, velocity, acceleration, and pattern of element durations) while electromyographic (EMG) signals demonstrated that smaller (reduced load) or larger forces (increased load) were spontaneously generated to compensate for the change in load. The muscle activation patterns of the biceps and triceps as well as the level of coactivation appeared to be generally upscaled to generate and dissipate the changes in force requirement needed to compensate for the increased load.

Impairment in explicit visuomotor sequence learning is related to loss of microstructural integrity of the corpus callosum in multiple sclerosis patients with minimal disability.

PubMed

Bonzano, L; Tacchino, A; Roccatagliata, L; Sormani, M P; Mancardi, G L; Bove, M

2011-07-15

Sequence learning can be investigated by serial reaction-time (SRT) paradigms. Explicit learning occurs when subjects have to recognize a test sequence and has been shown to activate the frontoparietal network in both contralateral and ipsilateral hemispheres. Thus, the left and right superior longitudinal fasciculi (SLF), connecting the intra-hemispheric frontoparietal circuits, could have a role in explicit unimanual visuomotor learning. Also, as both hemispheres are involved, we could hypothesize that the corpus callosum (CC) has a role in this process. Pathological damage in both SLF and CC has been detected in patients with Multiple Sclerosis (PwMS), and microstructural alterations can be quantified by Diffusion Tensor Imaging (DTI). In light of these findings, we inquired whether PwMS with minimal disability showed impairments in explicit visuomotor sequence learning and whether this could be due to loss of white matter integrity in these intra- and inter-hemispheric white matter pathways. Thus, we combined DTI analysis with a modified version of SRT task based on finger opposition movements in a group of PwMS with minimal disability. We found that the performance in explicit sequence learning was significantly reduced in these patients with respect to healthy subjects; the amount of sequence-specific learning was found to be more strongly correlated with fractional anisotropy (FA) in the CC (r=0.93) than in the left (r=0.28) and right SLF (r=0.27) (p for interaction=0.005 and 0.04 respectively). This finding suggests that an inter-hemispheric information exchange between the homologous areas is required to successfully accomplish the task and indirectly supports the role of the right (ipsilateral) hemisphere in explicit visuomotor learning. On the other hand, we found no significant correlation of the FA in the CC and in the SLFs with nonspecific learning (assessed when stimuli are randomly presented), supporting the hypothesis that inter-hemispheric integrity is specifically relevant for explicit sequence learning. Copyright © 2011 Elsevier Inc. 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.

Spontaneous Spatial Mapping of Learned Sequence in Chimpanzees: Evidence for a SNARC-Like Effect

PubMed Central

Adachi, Ikuma

2014-01-01

In the last couple of decades, there has been a growing number of reports on space-based representation of numbers and serial order in humans. In the present study, to explore evolutionary origins of such representations, we examined whether our closest evolutionary relatives, chimpanzees, map an acquired sequence onto space in a similar way to humans. The subjects had been trained to perform a number sequence task in which they touched a sequence of “small” to “large” Arabic numerals presented in random locations on the monitor. This task was presented in sessions that also included test trials consisting of only two numerals (1 and 9) horizontally arranged. On half of the trials 1 was located to the left of 9, whereas on the other half 1 was to the right to 9. The Chimpanzees' performance was systematically influenced by the spatial arrangement of the stimuli; specifically, they responded quicker when 1 was on the left and 9 on the right compared to the other way around. This result suggests that chimpanzees, like humans, spontaneously map a learned sequence onto space. PMID:24643044

A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks.

PubMed

Staels, Eva; Van den Broeck, Wim

2017-05-01

Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the inclusion of appropriate control conditions. The second goal of the study was to explore the role of attentional functioning in implicit and explicit learning tasks. In a 2 × 2 within-subjects design 4 tasks were administered in 30 dyslexic and 38 control children: an implicit and explicit serial reaction time (RT) task and an implicit and explicit contextual cueing task. Attentional functioning was also administered. The entire learning curves of all tasks were analyzed using latent growth curve modeling in order to compare performances between groups and to examine the role of attentional functioning on the learning curves. The amount of implicit learning was similar for both groups. However, the dyslexic group showed slower RTs throughout the entire task. This group difference reduced and became nonsignificant after controlling for attentional functioning. Both implicit learning tasks, but none of the explicit learning tasks, were significantly affected by attentional functioning. Dyslexic children do not suffer from a specific implicit sequence learning deficit. The slower RTs of the dyslexic children throughout the entire implicit sequence learning process are caused by their comorbid attention problems and overall slowness. A key finding of the present study is that, in contrast to what was assumed for a long time, implicit learning relies on attentional resources, perhaps even more than explicit learning does. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Achieving enlightenment: what do we know about the implicit learning system and its interaction with explicit knowledge?

PubMed

Vidoni, Eric D; Boyd, Lara A

2007-09-01

Two major memory and learning systems operate in the brain: one for facts and ideas (ie, the declarative or explicit system), one for habits and behaviors (ie, the procedural or implicit system). Broadly speaking these two memory systems can operate either in concert or entirely independently of one another during the performance and learning of skilled motor behaviors. This Special Issue article has two parts. In the first, we present a review of implicit motor skill learning that is largely centered on the interactions between declarative and procedural learning and memory. Because distinct neuroanatomical substrates support unique aspects of learning and memory and thus focal injury can cause impairments that are dependent on lesion location, we also broadly consider which brain regions mediate implicit and explicit learning and memory. In the second part of this article, the interactive nature of these two memory systems is illustrated by the presentation of new data that reveal that both learning implicitly and acquiring explicit knowledge through physical practice lead to motor sequence learning. In our new data, we discovered that for healthy individuals use of the implicit versus explicit memory system differently affected variability of performance during acquisition practice; variability was higher early in practice for the implicit group and later in practice for the acquired explicit group. Despite the difference in performance variability, by retention both groups demonstrated comparable change in tracking accuracy and thus, motor sequence learning. Clinicians should be aware of the potential effects of implicit and explicit interactions when designing rehabilitation interventions, particularly when delivering explicit instructions before task practice, working with individuals with focal brain damage, and/or adjusting therapeutic parameters based on acquisition performance variability.

Evidence of Anticipatory Eye Movements in the Spatial Hebb Repetition Effect: Insights for Modeling Sequence Learning

ERIC Educational Resources Information Center

Tremblay, Sebastien; Saint-Aubin, Jean

2009-01-01

In the present study, the authors offer a window onto the mechanisms that drive the Hebb repetition effect through the analysis of eye movement and recall performance. In a spatial serial recall task in which sequences of dots are to be remembered in order, when one particular series is repeated every 4 trials, memory performance markedly improves…

Affordable Hands-On DNA Sequencing and Genotyping: An Exercise for Teaching DNA Analysis to Undergraduates

ERIC Educational Resources Information Center

Shah, Kushani; Thomas, Shelby; Stein, Arnold

2013-01-01

In this report, we describe a 5-week laboratory exercise for undergraduate biology and biochemistry students in which students learn to sequence DNA and to genotype their DNA for selected single nucleotide polymorphisms (SNPs). Students use miniaturized DNA sequencing gels that require approximately 8 min to run. The students perform G, A, T, C…

Impact of Conscious Intent on Chunking during Motor Learning

ERIC Educational Resources Information Center

Song, Sunbin; Cohen, Leonardo

2014-01-01

Humans and other mammals learn sequences of movements by splitting them into smaller "chunks." Such chunks are defined by the faster speed of performance of groups of movements. The purpose of this report is to determine how conscious intent to learn impacts chunking, an issue that remains unknown. Here, we studied 80 subjects who either…

Predicting RNA-protein binding sites and motifs through combining local and global deep convolutional neural networks.

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2018-05-02

RNA-binding proteins (RBPs) take over 5∼10% of the eukaryotic proteome and play key roles in many biological processes, e.g. gene regulation. Experimental detection of RBP binding sites is still time-intensive and high-costly. Instead, computational prediction of the RBP binding sites using pattern learned from existing annotation knowledge is a fast approach. From the biological point of view, the local structure context derived from local sequences will be recognized by specific RBPs. However, in computational modeling using deep learning, to our best knowledge, only global representations of entire RNA sequences are employed. So far, the local sequence information is ignored in the deep model construction process. In this study, we present a computational method iDeepE to predict RNA-protein binding sites from RNA sequences by combining global and local convolutional neural networks (CNNs). For the global CNN, we pad the RNA sequences into the same length. For the local CNN, we split a RNA sequence into multiple overlapping fixed-length subsequences, where each subsequence is a signal channel of the whole sequence. Next, we train deep CNNs for multiple subsequences and the padded sequences to learn high-level features, respectively. Finally, the outputs from local and global CNNs are combined to improve the prediction. iDeepE demonstrates a better performance over state-of-the-art methods on two large-scale datasets derived from CLIP-seq. We also find that the local CNN run 1.8 times faster than the global CNN with comparable performance when using GPUs. Our results show that iDeepE has captured experimentally verified binding motifs. https://github.com/xypan1232/iDeepE. xypan172436@gmail.com or hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online.

Precise auditory-vocal mirroring in neurons for learned vocal communication.

PubMed

Prather, J F; Peters, S; Nowicki, S; Mooney, R

2008-01-17

Brain mechanisms for communication must establish a correspondence between sensory and motor codes used to represent the signal. One idea is that this correspondence is established at the level of single neurons that are active when the individual performs a particular gesture or observes a similar gesture performed by another individual. Although neurons that display a precise auditory-vocal correspondence could facilitate vocal communication, they have yet to be identified. Here we report that a certain class of neurons in the swamp sparrow forebrain displays a precise auditory-vocal correspondence. We show that these neurons respond in a temporally precise fashion to auditory presentation of certain note sequences in this songbird's repertoire and to similar note sequences in other birds' songs. These neurons display nearly identical patterns of activity when the bird sings the same sequence, and disrupting auditory feedback does not alter this singing-related activity, indicating it is motor in nature. Furthermore, these neurons innervate striatal structures important for song learning, raising the possibility that singing-related activity in these cells is compared to auditory feedback to guide vocal learning.

A comparison of the effects of temporary hippocampal lesions on single and dual context versions of the olfactory sequence memory task.

PubMed

Sill, Orriana C; Smith, David M

2012-08-01

In recent years, many animal models of memory have focused on one or more of the various components of episodic memory. For example, the odor sequence memory task requires subjects to remember individual items and events (the odors) and the temporal aspects of the experience (the sequence of odor presentation). The well-known spatial context coding function of the hippocampus, as exemplified by place cell firing, may reflect the "where" component of episodic memory. In the present study, we added a contextual component to the odor sequence memory task by training rats to choose the earlier odor in one context and the later odor in another context and we compared the effects of temporary hippocampal lesions on performance of the original single context task and the new dual context task. Temporary lesions significantly impaired the single context task, although performance remained significantly above chance levels. In contrast, performance dropped all the way to chance when temporary lesions were used in the dual context task. These results demonstrate that rats can learn a dual context version of the odor sequence learning task that requires the use of contextual information along with the requirement to remember the "what" and "when" components of the odor sequence. Moreover, the addition of the contextual component made the task fully dependent on the hippocampus.

Sustainable Design of EPA's Campus in Research Triangle Park, NC—Environmental Performance Specifications in Construction Contracts—Section 01450 Sequence of Finishes Installation

EPA Pesticide Factsheets

Learn more about the special construction scheduling/sequencing requirements and procedures necessary to assure achievement of designed Indoor Air Quality (IAQ) levels for the completed project required by the EPA IAQ Program.

Introduction and Assessment of a Blended-Learning Model to Teach Patient Assessment in a Doctor of Pharmacy Program

PubMed Central

Woodruff, Ashley; Prescott, Gina M.; Albanese, Nicole; Bernhardi, Christian; Doloresco, Fred

2016-01-01

Objective. To integrate a blended-learning model into a two-course patient assessment sequence in a doctor of pharmacy (PharmD) program and to assess the academic performance and perceptions of enrolled students. Design. A blended-learning model consisting of a flipped classroom format was integrated into a patient assessment (PA) course sequence. Course grades of students in the blended-learning (intervention) and traditional-classroom (control) groups were compared. A survey was administered to assess student perceptions. Assessment. The mean numeric grades of students in the intervention group were higher than those of students in the traditional group (PA1 course: 92.2±3.1 vs 90.0±4.3; and PA2 course: 90.3±4.9 vs 85.8±4.2). Eighty-six percent of the students in the intervention group agreed that the instructional methodologies used in this course facilitated understanding of the material. Conclusion. The blended-learning model was associated with improved academic performance and was well-received by students. PMID:28179725

Introduction and Assessment of a Blended-Learning Model to Teach Patient Assessment in a Doctor of Pharmacy Program.

PubMed

Prescott, William Allan; Woodruff, Ashley; Prescott, Gina M; Albanese, Nicole; Bernhardi, Christian; Doloresco, Fred

2016-12-25

Objective. To integrate a blended-learning model into a two-course patient assessment sequence in a doctor of pharmacy (PharmD) program and to assess the academic performance and perceptions of enrolled students. Design. A blended-learning model consisting of a flipped classroom format was integrated into a patient assessment (PA) course sequence. Course grades of students in the blended-learning (intervention) and traditional-classroom (control) groups were compared. A survey was administered to assess student perceptions. Assessment. The mean numeric grades of students in the intervention group were higher than those of students in the traditional group (PA1 course: 92.2±3.1 vs 90.0±4.3; and PA2 course: 90.3±4.9 vs 85.8±4.2). Eighty-six percent of the students in the intervention group agreed that the instructional methodologies used in this course facilitated understanding of the material. Conclusion. The blended-learning model was associated with improved academic performance and was well-received by students.

Deliberate practice theory: relevance, effort, and inherent enjoyment of music practice.

PubMed

Hyllegard, Randy; Bories, Tamara L

2008-10-01

This study examined three assumptions of the theory of deliberate practice for practice playing music on an electronic keyboard. 40 undergraduate students, divided into two separate groups, practiced one of two music sequences and rated the relevance of practice for improving performance on the sequences, the amount of effort needed to learn the sequences, and the inherent enjoyment of practice sessions. Findings for each assumption were consistent with those suggested by theory but also showed that perceptions are affected by the amount of practice completed and performance of the skill.

PySeqLab: an open source Python package for sequence labeling and segmentation.

PubMed

Allam, Ahmed; Krauthammer, Michael

2017-11-01

Text and genomic data are composed of sequential tokens, such as words and nucleotides that give rise to higher order syntactic constructs. In this work, we aim at providing a comprehensive Python library implementing conditional random fields (CRFs), a class of probabilistic graphical models, for robust prediction of these constructs from sequential data. Python Sequence Labeling (PySeqLab) is an open source package for performing supervised learning in structured prediction tasks. It implements CRFs models, that is discriminative models from (i) first-order to higher-order linear-chain CRFs, and from (ii) first-order to higher-order semi-Markov CRFs (semi-CRFs). Moreover, it provides multiple learning algorithms for estimating model parameters such as (i) stochastic gradient descent (SGD) and its multiple variations, (ii) structured perceptron with multiple averaging schemes supporting exact and inexact search using 'violation-fixing' framework, (iii) search-based probabilistic online learning algorithm (SAPO) and (iv) an interface for Broyden-Fletcher-Goldfarb-Shanno (BFGS) and the limited-memory BFGS algorithms. Viterbi and Viterbi A* are used for inference and decoding of sequences. Using PySeqLab, we built models (classifiers) and evaluated their performance in three different domains: (i) biomedical Natural language processing (NLP), (ii) predictive DNA sequence analysis and (iii) Human activity recognition (HAR). State-of-the-art performance comparable to machine-learning based systems was achieved in the three domains without feature engineering or the use of knowledge sources. PySeqLab is available through https://bitbucket.org/A_2/pyseqlab with tutorials and documentation. ahmed.allam@yale.edu or michael.krauthammer@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Isolating Visual and Proprioceptive Components of Motor Sequence Learning in ASD.

PubMed

Sharer, Elizabeth A; Mostofsky, Stewart H; Pascual-Leone, Alvaro; Oberman, Lindsay M

2016-05-01

In addition to defining impairments in social communication skills, individuals with autism spectrum disorder (ASD) also show impairments in more basic sensory and motor skills. Development of new skills involves integrating information from multiple sensory modalities. This input is then used to form internal models of action that can be accessed when both performing skilled movements, as well as understanding those actions performed by others. Learning skilled gestures is particularly reliant on integration of visual and proprioceptive input. We used a modified serial reaction time task (SRTT) to decompose proprioceptive and visual components and examine whether patterns of implicit motor skill learning differ in ASD participants as compared with healthy controls. While both groups learned the implicit motor sequence during training, healthy controls showed robust generalization whereas ASD participants demonstrated little generalization when visual input was constant. In contrast, no group differences in generalization were observed when proprioceptive input was constant, with both groups showing limited degrees of generalization. The findings suggest, when learning a motor sequence, individuals with ASD tend to rely less on visual feedback than do healthy controls. Visuomotor representations are considered to underlie imitative learning and action understanding and are thereby crucial to social skill and cognitive development. Thus, anomalous patterns of implicit motor learning, with a tendency to discount visual feedback, may be an important contributor in core social communication deficits that characterize ASD. Autism Res 2016, 9: 563-569. © 2015 International Society for Autism Research, Wiley Periodicals, Inc. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Three children with autism spectrum disorder learn to perform a three-step communication sequence using an iPad®-based speech-generating device.

PubMed

Waddington, Hannah; Sigafoos, Jeff; Lancioni, Giulio E; O'Reilly, Mark F; van der Meer, Larah; Carnett, Amarie; Stevens, Michelle; Roche, Laura; Hodis, Flaviu; Green, Vanessa A; Sutherland, Dean; Lang, Russell; Marschik, Peter B

2014-12-01

Many children with autism spectrum disorder (ASD) have limited or absent speech and might therefore benefit from learning to use a speech-generating device (SGD). The purpose of this study was to evaluate a procedure aimed at teaching three children with ASD to use an iPad(®)-based SGD to make a general request for access to toys, then make a specific request for one of two toys, and then communicate a thank-you response after receiving the requested toy. A multiple-baseline across participants design was used to determine whether systematic instruction involving least-to-most-prompting, time delay, error correction, and reinforcement was effective in teaching the three children to engage in this requesting and social communication sequence. Generalization and follow-up probes were conducted for two of the three participants. With intervention, all three children showed improvement in performing the communication sequence. This improvement was maintained with an unfamiliar communication partner and during the follow-up sessions. With systematic instruction, children with ASD and severe communication impairment can learn to use an iPad-based SGD to complete multi-step communication sequences that involve requesting and social communication functions. Copyright © 2014 ISDN. Published by Elsevier Ltd. All rights reserved.

Skilled memory in expert figure skaters.

PubMed

Deakin, J M; Allard, F

1991-01-01

The present studies extend skilled-memory theory to a domain involving the performance of motor sequences. Skilled figure skaters were better able than their less skilled counterparts to perform short skating sequences that were choreographed, rather than randomly constructed. Expert skaters encoded sequences for performance very differently from the way in which they encoded sequences that were verbally presented for verbal recall. Tasks interpolated between sequence and recall showed no significant influence on recall accuracy, implicating long-term memory in skating memory. There was little evidence for the use of retrieval structures when skaters learned the brief sequences used throughout these studies. Finally, expert skaters were able to judge the similarity of two skating elements faster than less skilled skaters, indicating a faster access to semantic memory for experts. The data indicate that skaters show many of the same skilled-memory characteristics as have been described in other skill domains involving memorization, such as digit span and memory for dinner orders.

Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis.

PubMed

You, Zhu-Hong; Lei, Ying-Ke; Zhu, Lin; Xia, Junfeng; Wang, Bing

2013-01-01

Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes and form the basis of biological mechanisms. Although large amount of PPIs data for different species has been generated by high-throughput experimental techniques, current PPI pairs obtained with experimental methods cover only a fraction of the complete PPI networks, and further, the experimental methods for identifying PPIs are both time-consuming and expensive. Hence, it is urgent and challenging to develop automated computational methods to efficiently and accurately predict PPIs. We present here a novel hierarchical PCA-EELM (principal component analysis-ensemble extreme learning machine) model to predict protein-protein interactions only using the information of protein sequences. In the proposed method, 11188 protein pairs retrieved from the DIP database were encoded into feature vectors by using four kinds of protein sequences information. Focusing on dimension reduction, an effective feature extraction method PCA was then employed to construct the most discriminative new feature set. Finally, multiple extreme learning machines were trained and then aggregated into a consensus classifier by majority voting. The ensembling of extreme learning machine removes the dependence of results on initial random weights and improves the prediction performance. When performed on the PPI data of Saccharomyces cerevisiae, the proposed method achieved 87.00% prediction accuracy with 86.15% sensitivity at the precision of 87.59%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Experimental results demonstrate that proposed PCA-EELM outperforms the SVM method by 5-fold cross-validation. Besides, PCA-EELM performs faster than PCA-SVM based method. Consequently, the proposed approach can be considered as a new promising and powerful tools for predicting PPI with excellent performance and less time.

One-Shot Learning of Human Activity With an MAP Adapted GMM and Simplex-HMM.

PubMed

Rodriguez, Mario; Orrite, Carlos; Medrano, Carlos; Makris, Dimitrios

2016-05-10

This paper presents a novel activity class representation using a single sequence for training. The contribution of this representation lays on the ability to train an one-shot learning recognition system, useful in new scenarios where capturing and labeling sequences is expensive or impractical. The method uses a universal background model of local descriptors obtained from source databases available on-line and adapts it to a new sequence in the target scenario through a maximum a posteriori adaptation. Each activity sample is encoded in a sequence of normalized bag of features and modeled by a new hidden Markov model formulation, where the expectation-maximization algorithm for training is modified to deal with observations consisting in vectors in a unit simplex. Extensive experiments in recognition have been performed using one-shot learning over the public datasets Weizmann, KTH, and IXMAS. These experiments demonstrate the discriminative properties of the representation and the validity of application in recognition systems, achieving state-of-the-art results.

Forgetting motor programmes: retrieval dynamics in procedural memory.

PubMed

Tempel, Tobias; Frings, Christian

2014-01-01

When motor sequences are stored in memory in a categorised manner, selective retrieval of some sequences can induce forgetting of the non-retrieved sequences. We show that such retrieval-induced forgetting (RIF) occurs not only in cued recall but also in a test assessing memory indirectly by providing novel test cues without involving recall of items. Participants learned several sequential finger movements (SFMs), each consisting of the movement of two fingers of either the left or the right hand. Subsequently, they performed retrieval practice on half of the sequences of one hand. A final task then required participants to enter letter dyads. A subset of these dyads corresponded to the previously learned sequences. RIF was present in the response times during the entering of the dyads. The finding of RIF in the slowed-down execution of motor programmes overlapping with initially trained motor sequences suggests that inhibition resolved interference between procedural representations of the acquired motor sequences of one hand during retrieval practice.

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

Time-specific contribution of the supplementary motor area to intermanual transfer of procedural knowledge

PubMed Central

Perez, MA; Tanaka, S; Wise, SP; Willingham, DT; Cohen, LG

2008-01-01

The supplementary motor area (SMA) makes a crucial contribution to intermanual transfer: the ability to use one hand to perform a skill practiced and learned with the other hand. However, the timing of this contribution relative to movement remains unknown. Here, 33 healthy volunteers performed a 12-item sequence in the serial reaction time task (SRTT). During training, each participant responded to a sequence of visual cues presented at 1 Hz by pressing one of 4 keys with their right hand. The measure of intermanual transfer was response time (RT) during repetition of the trained sequence with the left hand, which was at rest during learning. Participants were divided into 3 groups, which did not differ in their learning rates or amounts. In 2 groups, 1 Hz repetitive transcranial magnetic stimulation (rTMS) induced transient virtual lesions of the SMA during training, either 100 ms before each cue (the premovement group) or during each key press (the movement group). The third group received sham stimulation (the sham group). After training with the right hand, RTs for performance with the left (transfer) hand were longer for the premovement group than for the movement or sham groups. Thus SMA’s most crucial contribution to intermanual transfer occurs in the interval between movements, when the memory of a prior movement plays a role in encoding specific sequences. These results provide insight into frontal-lobe contributions to procedural knowledge. PMID:18815252

Is sequence awareness mandatory for perceptual sequence learning: An assessment using a pure perceptual sequence learning design.

PubMed

Deroost, Natacha; Coomans, Daphné

2018-02-01

We examined the role of sequence awareness in a pure perceptual sequence learning design. Participants had to react to the target's colour that changed according to a perceptual sequence. By varying the mapping of the target's colour onto the response keys, motor responses changed randomly. The effect of sequence awareness on perceptual sequence learning was determined by manipulating the learning instructions (explicit versus implicit) and assessing the amount of sequence awareness after the experiment. In the explicit instruction condition (n = 15), participants were instructed to intentionally search for the colour sequence, whereas in the implicit instruction condition (n = 15), they were left uninformed about the sequenced nature of the task. Sequence awareness after the sequence learning task was tested by means of a questionnaire and the process-dissociation-procedure. The results showed that the instruction manipulation had no effect on the amount of perceptual sequence learning. Based on their report to have actively applied their sequence knowledge during the experiment, participants were subsequently regrouped in a sequence strategy group (n = 14, of which 4 participants from the implicit instruction condition and 10 participants from the explicit instruction condition) and a no-sequence strategy group (n = 16, of which 11 participants from the implicit instruction condition and 5 participants from the explicit instruction condition). Only participants of the sequence strategy group showed reliable perceptual sequence learning and sequence awareness. These results indicate that perceptual sequence learning depends upon the continuous employment of strategic cognitive control processes on sequence knowledge. Sequence awareness is suggested to be a necessary but not sufficient condition for perceptual learning to take place. Copyright © 2018 Elsevier B.V. All rights reserved.

The pattern of verbal, visuospatial and procedural learning in Richardson variant of progressive supranuclear palsy in comparison to Parkinson's disease.

PubMed

Sitek, Emilia J; Wieczorek, Dariusz; Konkel, Agnieszka; Dąbrowska, Magda; Sławek, Jarosław

2017-08-29

Progressive supranuclear palsy (PSP) is regarded either within spectrum of atypical parkinsonian syndromes or frontotemporal lobar degeneration. We compared the verbal, visuospatial and procedural learning profiles in patients with PSP and Parkinson's disease (PD). Furthermore, the relationship between executive factors (initiation and inhibition) and learning outcomes was analyzed. Thirty-three patients with the clinical diagnosis of PSP-Richardson's syndrome (PSP-RS), 39 patients with PD and 29 age -and education -matched controls were administered Mini-Mental State Examination (MMSE), phonemic and semantic fluency tasks, Auditory Verbal Learning Test (AVLT), Visual Learning and Memory Test for Neuropsychological Assessment by Lamberti and Weidlich (Diagnosticum für Cerebralschädigung, DCS), Tower of Toronto (ToT) and two motor sequencing tasks. Patients with PSP-RS and PD were matched in terms of MMSE scores and mood. Performance on DCS was lower in PSP-RS than in PD. AVLT delayed recall was better in PSP-RS than PD. Motor sequencing task did not differentiate between patients. Scores on AVLT correlated positively with phonemic fluency scores in both PSP-RS and PD. ToT rule violation scores were negatively associated with DCS performance in PSP-RS and PD as well as with AVLT performance in PD. Global memory performance is relatively similar in PSP-RS and PD. Executive factors (initiation and inhibition) are closely related to memory performance in PSP-RS and PD. Visuospatial learning impairment in PSP-RS is possibly linked to impulsivity and failure to inhibit automatic responses.

Implementing and Evaluating a Peer-Led Team Learning Approach in Undergraduate Anatomy and Physiology

ERIC Educational Resources Information Center

Finn, Kevin; Campisi, Jay

2015-01-01

This article describes how a Peer-Led Team Learning (PLTL) program was implemented in a first-year, undergraduate Anatomy and Physiology course sequence to examine the student perceptions of the program and determine the effects of PLTL on student performance.

Segmented-memory recurrent neural networks.

PubMed

Chen, Jinmiao; Chaudhari, Narendra S

2009-08-01

Conventional recurrent neural networks (RNNs) have difficulties in learning long-term dependencies. To tackle this problem, we propose an architecture called segmented-memory recurrent neural network (SMRNN). A symbolic sequence is broken into segments and then presented as inputs to the SMRNN one symbol per cycle. The SMRNN uses separate internal states to store symbol-level context, as well as segment-level context. The symbol-level context is updated for each symbol presented for input. The segment-level context is updated after each segment. The SMRNN is trained using an extended real-time recurrent learning algorithm. We test the performance of SMRNN on the information latching problem, the "two-sequence problem" and the problem of protein secondary structure (PSS) prediction. Our implementation results indicate that SMRNN performs better on long-term dependency problems than conventional RNNs. Besides, we also theoretically analyze how the segmented memory of SMRNN helps learning long-term temporal dependencies and study the impact of the segment length.

Automatic classification of protein structures using physicochemical parameters.

PubMed

Mohan, Abhilash; Rao, M Divya; Sunderrajan, Shruthi; Pennathur, Gautam

2014-09-01

Protein classification is the first step to functional annotation; SCOP and Pfam databases are currently the most relevant protein classification schemes. However, the disproportion in the number of three dimensional (3D) protein structures generated versus their classification into relevant superfamilies/families emphasizes the need for automated classification schemes. Predicting function of novel proteins based on sequence information alone has proven to be a major challenge. The present study focuses on the use of physicochemical parameters in conjunction with machine learning algorithms (Naive Bayes, Decision Trees, Random Forest and Support Vector Machines) to classify proteins into their respective SCOP superfamily/Pfam family, using sequence derived information. Spectrophores™, a 1D descriptor of the 3D molecular field surrounding a structure was used as a benchmark to compare the performance of the physicochemical parameters. The machine learning algorithms were modified to select features based on information gain for each SCOP superfamily/Pfam family. The effect of combining physicochemical parameters and spectrophores on classification accuracy (CA) was studied. Machine learning algorithms trained with the physicochemical parameters consistently classified SCOP superfamilies and Pfam families with a classification accuracy above 90%, while spectrophores performed with a CA of around 85%. Feature selection improved classification accuracy for both physicochemical parameters and spectrophores based machine learning algorithms. Combining both attributes resulted in a marginal loss of performance. Physicochemical parameters were able to classify proteins from both schemes with classification accuracy ranging from 90-96%. These results suggest the usefulness of this method in classifying proteins from amino acid sequences.

Maximizing lipocalin prediction through balanced and diversified training set and decision fusion.

PubMed

Nath, Abhigyan; Subbiah, Karthikeyan

2015-12-01

Lipocalins are short in sequence length and perform several important biological functions. These proteins are having less than 20% sequence similarity among paralogs. Experimentally identifying them is an expensive and time consuming process. The computational methods based on the sequence similarity for allocating putative members to this family are also far elusive due to the low sequence similarity existing among the members of this family. Consequently, the machine learning methods become a viable alternative for their prediction by using the underlying sequence/structurally derived features as the input. Ideally, any machine learning based prediction method must be trained with all possible variations in the input feature vector (all the sub-class input patterns) to achieve perfect learning. A near perfect learning can be achieved by training the model with diverse types of input instances belonging to the different regions of the entire input space. Furthermore, the prediction performance can be improved through balancing the training set as the imbalanced data sets will tend to produce the prediction bias towards majority class and its sub-classes. This paper is aimed to achieve (i) the high generalization ability without any classification bias through the diversified and balanced training sets as well as (ii) enhanced the prediction accuracy by combining the results of individual classifiers with an appropriate fusion scheme. Instead of creating the training set randomly, we have first used the unsupervised Kmeans clustering algorithm to create diversified clusters of input patterns and created the diversified and balanced training set by selecting an equal number of patterns from each of these clusters. Finally, probability based classifier fusion scheme was applied on boosted random forest algorithm (which produced greater sensitivity) and K nearest neighbour algorithm (which produced greater specificity) to achieve the enhanced predictive performance than that of individual base classifiers. The performance of the learned models trained on Kmeans preprocessed training set is far better than the randomly generated training sets. The proposed method achieved a sensitivity of 90.6%, specificity of 91.4% and accuracy of 91.0% on the first test set and sensitivity of 92.9%, specificity of 96.2% and accuracy of 94.7% on the second blind test set. These results have established that diversifying training set improves the performance of predictive models through superior generalization ability and balancing the training set improves prediction accuracy. For smaller data sets, unsupervised Kmeans based sampling can be an effective technique to increase generalization than that of the usual random splitting method. Copyright © 2015 Elsevier Ltd. All rights reserved.

Improving Robot Motor Learning with Negatively Valenced Reinforcement Signals

PubMed Central

Navarro-Guerrero, Nicolás; Lowe, Robert J.; Wermter, Stefan

2017-01-01

Both nociception and punishment signals have been used in robotics. However, the potential for using these negatively valenced types of reinforcement learning signals for robot learning has not been exploited in detail yet. Nociceptive signals are primarily used as triggers of preprogrammed action sequences. Punishment signals are typically disembodied, i.e., with no or little relation to the agent-intrinsic limitations, and they are often used to impose behavioral constraints. Here, we provide an alternative approach for nociceptive signals as drivers of learning rather than simple triggers of preprogrammed behavior. Explicitly, we use nociception to expand the state space while we use punishment as a negative reinforcement learning signal. We compare the performance—in terms of task error, the amount of perceived nociception, and length of learned action sequences—of different neural networks imbued with punishment-based reinforcement signals for inverse kinematic learning. We contrast the performance of a version of the neural network that receives nociceptive inputs to that without such a process. Furthermore, we provide evidence that nociception can improve learning—making the algorithm more robust against network initializations—as well as behavioral performance by reducing the task error, perceived nociception, and length of learned action sequences. Moreover, we provide evidence that punishment, at least as typically used within reinforcement learning applications, may be detrimental in all relevant metrics. PMID:28420976

Constrained paths based on the Farey sequence in learning to juggle.

PubMed

Yamamoto, Kota; Tsutsui, Seijiro; Yamamoto, Yuji

2015-12-01

In this article we report the results of a study conducted to investigate the learning dynamics of three-ball juggling from the perspective of frequency locking. Based on the Farey sequence, we predicted that four stable coordination patterns, corresponding to dwell ratios of 0.83, 0.75, 0.67, and 0.50, would appear in the learning process. We examined the learning process in terms of task performance, taking into account individual differences in the amount of learning. We observed that the participants acquired individual-specific coordination patterns in a relatively early stage of learning, and that those coordination patterns were preserved in subsequent learning, even though performance in terms of number of successful consecutive throws increased substantially. This increase appeared to be related to a reduction in spatial variability of the juggling movements. Finally, the observed coordination patterns were in agreement with the predicted patterns, with the proviso that the pattern corresponding to a dwell ratio of 0.50 was not realized and only a hint of evidence was found for the dwell ratio of 0.67. This implies that the dwell ratios of 0.83 and 0.75 in particular exhibited a stable coordination structure due to strong frequency locking between the temporal variables of juggling. Copyright © 2015 Elsevier B.V. All rights reserved.

AMS 4.0: consensus prediction of post-translational modifications in protein sequences.

PubMed

Plewczynski, Dariusz; Basu, Subhadip; Saha, Indrajit

2012-08-01

We present here the 2011 update of the AutoMotif Service (AMS 4.0) that predicts the wide selection of 88 different types of the single amino acid post-translational modifications (PTM) in protein sequences. The selection of experimentally confirmed modifications is acquired from the latest UniProt and Phospho.ELM databases for training. The sequence vicinity of each modified residue is represented using amino acids physico-chemical features encoded using high quality indices (HQI) obtaining by automatic clustering of known indices extracted from AAindex database. For each type of the numerical representation, the method builds the ensemble of Multi-Layer Perceptron (MLP) pattern classifiers, each optimising different objectives during the training (for example the recall, precision or area under the ROC curve (AUC)). The consensus is built using brainstorming technology, which combines multi-objective instances of machine learning algorithm, and the data fusion of different training objects representations, in order to boost the overall prediction accuracy of conserved short sequence motifs. The performance of AMS 4.0 is compared with the accuracy of previous versions, which were constructed using single machine learning methods (artificial neural networks, support vector machine). Our software improves the average AUC score of the earlier version by close to 7 % as calculated on the test datasets of all 88 PTM types. Moreover, for the selected most-difficult sequence motifs types it is able to improve the prediction performance by almost 32 %, when compared with previously used single machine learning methods. Summarising, the brainstorming consensus meta-learning methodology on the average boosts the AUC score up to around 89 %, averaged over all 88 PTM types. Detailed results for single machine learning methods and the consensus methodology are also provided, together with the comparison to previously published methods and state-of-the-art software tools. The source code and precompiled binaries of brainstorming tool are available at http://code.google.com/p/automotifserver/ under Apache 2.0 licensing.

Successfully Carrying out Complex Learning-Tasks through Guiding Teams' Qualitative and Quantitative Reasoning

ERIC Educational Resources Information Center

Slof, B.; Erkens, G.; Kirschner, P. A.; Janssen, J.; Jaspers, J. G. M.

2012-01-01

This study investigated whether and how scripting learners' use of representational tools in a computer supported collaborative learning (CSCL)-environment fostered their collaborative performance on a complex business-economics task. Scripting the problem-solving process sequenced and made its phase-related part-task demands explicit, namely…

Learning Grasp Context Distinctions that Generalize

NASA Technical Reports Server (NTRS)

Platt, Robert; Grupen, Roderic A.; Fagg, Andrew H.

2006-01-01

Control-based approaches to grasp synthesis create grasping behavior by sequencing and combining control primitives. In the absence of any other structure, these approaches must evaluate a large number of feasible control sequences as a function of object shape, object pose, and task. This work explores a new approach to grasp synthesis that limits consideration to variations on a generalized localize-reach-grasp control policy. A new learning algorithm, known as schema structured learning, is used to learn which instantiations of the generalized policy are most likely to lead to a successful grasp in different problem contexts. Two experiments are described where Dexter, a bimanual upper torso, learns to select an appropriate grasp strategy as a function of object eccentricity and orientation. In addition, it is shown that grasp skills learned in this way can generalize to new objects. Results are presented showing that after learning how to grasp a small, representative set of objects, the robot's performance quantitatively improves for similar objects that it has not experienced before.

Reprint of: Early Behavioural Facilitation by Temporal Expectations in Complex Visual-motor Sequences.

PubMed

Heideman, Simone G; van Ede, Freek; Nobre, Anna C

2018-05-24

In daily life, temporal expectations may derive from incidental learning of recurring patterns of intervals. We investigated the incidental acquisition and utilisation of combined temporal-ordinal (spatial/effector) structure in complex visual-motor sequences using a modified version of a serial reaction time (SRT) task. In this task, not only the series of targets/responses, but also the series of intervals between subsequent targets was repeated across multiple presentations of the same sequence. Each participant completed three sessions. In the first session, only the repeating sequence was presented. During the second and third session, occasional probe blocks were presented, where a new (unlearned) spatial-temporal sequence was introduced. We first confirm that participants not only got faster over time, but that they were slower and less accurate during probe blocks, indicating that they incidentally learned the sequence structure. Having established a robust behavioural benefit induced by the repeating spatial-temporal sequence, we next addressed our central hypothesis that implicit temporal orienting (evoked by the learned temporal structure) would have the largest influence on performance for targets following short (as opposed to longer) intervals between temporally structured sequence elements, paralleling classical observations in tasks using explicit temporal cues. We found that indeed, reaction time differences between new and repeated sequences were largest for the short interval, compared to the medium and long intervals, and that this was the case, even when comparing late blocks (where the repeated sequence had been incidentally learned), to early blocks (where this sequence was still unfamiliar). We conclude that incidentally acquired temporal expectations that follow a sequential structure can have a robust facilitatory influence on visually-guided behavioural responses and that, like more explicit forms of temporal orienting, this effect is most pronounced for sequence elements that are expected at short inter-element intervals. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Restricted transfer of learning between unimanual and bimanual finger sequences.

PubMed

Yokoi, Atsushi; Bai, Wenjun; Diedrichsen, Jörn

2017-03-01

When training bimanual skills, such as playing piano, people sometimes practice each hand separately and at a later stage combine the movements of the two hands. This poses the critical question of whether motor skills can be acquired by separately practicing each subcomponent or should be trained as a whole. In the present study, we addressed this question by training human subjects for 4 days in a unimanual or bimanual version of the discrete sequence production task. Both groups were then tested on trained and untrained sequences on both unimanual and bimanual versions of the task. Surprisingly, we found no evidence of transfer from trained unimanual to bimanual or from trained bimanual to unimanual sequences. In half the participants, we also investigated whether cuing the sequences on the left and right hand with unique letters would change transfer. With these cues, untrained sequences that shared some components with the trained sequences were performed more quickly than sequences that did not. However, the amount of this transfer was limited to ∼10% of the overall sequence-specific learning gains. These results suggest that unimanual and bimanual sequences are learned in separate representations. Making participants aware of the interrelationship between sequences can induce some transferrable component, although the main component of the skill remains unique to unimanual or bimanual execution. NEW & NOTEWORTHY Studies in reaching movement demonstrated that approximately half of motor learning can transfer across unimanual and bimanual contexts, suggesting that neural representations for unimanual and bimanual movements are fairly overlapping at the level of elementary movement. In this study, we show that little or no transfer occurred across unimanual and bimanual sequential finger movements. This result suggests that bimanual sequences are represented at a level of the motor hierarchy that integrates movements of both hands. Copyright © 2017 the American Physiological Society.

Speech Sequence Skill Learning in Adults Who Stutter

ERIC Educational Resources Information Center

Bauerly, Kim R.; De Nil, Luc F.

2011-01-01

The present study compared the ability of 12 people who stutter (PWS) and 12 people who do not stutter (PNS) to consolidate a novel sequential speech task. Participants practiced 100 repetitions of a single, monosyllabic, nonsense word sequence during an initial practice session and returned 24-h later to perform an additional 50 repetitions.…

Aging reduces experience-induced sensorimotor plasticity. A magnetoencephalographic study.

PubMed

Mary, Alison; Bourguignon, Mathieu; Wens, Vincent; Op de Beeck, Marc; Leproult, Rachel; De Tiège, Xavier; Peigneux, Philippe

2015-01-01

Modulation of the mu-alpha and mu-beta spontaneous rhythms reflects plastic neural changes within the primary sensorimotor cortex (SM1). Using magnetoencephalography (MEG), we investigated how aging modifies experience-induced plasticity after learning a motor sequence, looking at post- vs. pre-learning changes in the modulation of mu rhythms during the execution of simple hand movements. Fifteen young (18-30 years) and fourteen older (65-75 years) right-handed healthy participants performed auditory-cued key presses using all four left fingers simultaneously (Simple Movement task - SMT) during two separate sessions. Following both SMT sessions, they repeatedly practiced a 5-elements sequential finger-tapping task (FTT). Mu power calculated during SMT was averaged across 18 gradiometers covering the right sensorimotor region and compared before vs. after sequence learning in the alpha (9/10/11Hz) and the beta (18/20/22Hz) bands separately. Source power maps in the mu-alpha and mu-beta bands were localized using Dynamic Statistical Parametric Mapping (dSPM). The FTT sequence was performed faster at retest than at the end of the learning session, indicating an offline boost in performance. Analyses conducted on SMT sessions revealed enhanced rebound after learning in the right SM1, 3000-3500ms after the initiation of movement, in young as compared to older participants. Source reconstruction indicated that mu-beta is located in the precentral gyrus (motor processes) and mu-alpha is located in the postcentral gyrus (somatosensory processes) in both groups. The enhanced post-movement rebound in young subjects potentially reflects post-training plastic changes in SM1. Age-related decreases in post-training modulatory effects suggest reduced experience-dependent plasticity in the aging brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Differences in Learning Volitional (Manual) and Non-Volitional (Posture) Aspects of a Complex Motor Skill in Young Adult Dyslexic and Skilled Readers

PubMed Central

Sela, Itamar; Karni, Avi

2012-01-01

The ‘Cerebellar Deficit Theory’ of developmental dyslexia proposes that a subtle developmental cerebellar dysfunction leads to deficits in attaining ‘automatic’ procedures and therefore manifests as subtle motor impairments (e.g., balance control, motor skill learning) in addition to the reading and phonological difficulties. A more recent version of the theory suggests a core deficit in motor skill acquisition. This study was undertaken to compare the time-course and the nature of practice-related changes in volitional (manual) and non-volitional (posture) motor performance in dyslexic and typical readers while learning a new movement sequence. Seventeen dyslexic and 26 skilled young adult readers underwent a three-session training program in which they practiced a novel sequence of manual movements while standing in a quiet stance position. Both groups exhibited robust and well-retained gains in speed, with no loss of accuracy, on the volitional, manual, aspects of the task, with a time-course characteristic of procedural learning. However, the dyslexic readers exhibited a pervasive slowness in the initiation of volitional performance. In addition, while typical readers showed clear and well-retained task-related adaptation of the balance and posture control system, the dyslexic readers had significantly larger sway and variance of sway throughout the three sessions and were less efficient in adapting the posture control system to support the acquisition of the novel movement sequence. These results support the notion of a non-language-related deficit in developmental dyslexia, one related to the recruitment of motor systems for effective task performance rather than to a general motor learning disability. PMID:23049736

Hippocampal Replay is Not a Simple Function of Experience

PubMed Central

Gupta, Anoopum S.; van der Meer, Matthijs A. A.; Touretzky, David S.; Redish, A. David

2015-01-01

Summary Replay of behavioral sequences in the hippocampus during sharp-wave-ripple-complexes (SWRs) provides a potential mechanism for memory consolidation and the learning of knowledge structures. Current hypotheses imply that replay should straightforwardly reflect recent experience. However, we find these hypotheses to be incompatible with the content of replay on a task with two distinct behavioral sequences (A&B). We observed forward and backward replay of B even when rats had been performing A for >10 minutes. Furthermore, replay of non-local sequence B occurred more often when B was infrequently experienced. Neither forward nor backward sequences preferentially represented highly-experienced trajectories within a session. Additionally, we observed the construction of never-experienced novel-path sequences. These observations challenge the idea that sequence activation during SWRs is a simple replay of recent experience. Instead, replay reflected all physically available trajectories within the environment, suggesting a potential role in active learning and maintenance of the cognitive map. PMID:20223204

Proactive and retroactive transfer of middle age adults in a sequential motor learning task.

PubMed

Verneau, Marion; van der Kamp, John; Savelsbergh, Geert J P; de Looze, Michiel P

2015-03-01

We assessed the effects of aging in the transfer of motor learning in a sequential manual assembly task that is representative for real working conditions. On two different days, young (18-30 years) and middle-aged adults (50-65 years) practiced to build two products that consisted of the same six components but which had to be assembled in a partly different order. Assembly accuracy and movement time during tests, which were performed before and after the practice sessions, were compared to determine proactive and retroactive transfer. The results showed proactive facilitation (i.e., benefits from having learned the first product on learning the second one) in terms of an overall shortening of movement time in both age-groups. In addition, only the middle-aged adults were found to show sequence-specific proactive facilitation, in which the shortening of movement time was limited to components that had the same the order in the two products. Most likely, however, the sequence-specific transfer was an epiphenomenon of the comparatively low rate of learning among the middle-aged adults. The results, however, did reveal genuine differences between the groups for retroactive transfer (i.e., effects from learning the second product on performance of the first). Middle-aged adults tended to show more pronounced retroactive interference in terms of a general decrease in accuracy, while younger adults showed sequence-specific retroactive facilitation (i.e., shortening of movement times for components that had the same order in the two products), but only when they were fully accurate. Together this suggests that in the learning of sequential motor tasks the effects of age are more marked for retroactive transfer than for proactive transfer. Copyright © 2015 Elsevier B.V. All rights reserved.

Differential Effects of Paced and Unpaced Responding on delayed Serial Order Recall in Schizophrenia

PubMed Central

Hill, S. Kristian; Griffin, Ginny B.; Houk, James C.; Sweeney, John A.

2011-01-01

Working memory for temporal order is a component of working memory that is especially dependent on striatal systems, but has not been extensively studied in schizophrenia. This study was designed to characterize serial order reproduction by adapting a spatial serial order task developed for nonhuman primate studies, while controlling for working memory load and whether responses were initiated freely (unpaced) or in an externally paced format. Clinically stable schizophrenia patients (n=27) and psychiatrically healthy individuals (n=25) were comparable on demographic variables and performance on standardized tests of immediate serial order recall (Digit Span, Spatial Span). No group differences were observed for serial order recall when read sequence reproduction was unpaced. However, schizophrenia patients exhibited significant impairments when responding was paced, regardless of sequence length or retention delay. Intact performance by schizophrenia patients during the unpaced condition indicates that prefrontal storage and striatal output systems are sufficiently intact to learn novel response sequences and hold them in working memory to perform serial order tasks. However, retention for newly learned response sequences was disrupted in schizophrenia patients by paced responding, when read-out of each element in the response sequence was externally controlled. The disruption of memory for serial order in paced read-out condition indicates a deficit in frontostriatal interaction characterized by an inability to update working memory stores and deconstruct ‘chunked’ information. PMID:21705197

Social intuition as a form of implicit learning: Sequences of body movements are learned less explicitly than letter sequences

PubMed Central

Norman, Elisabeth; Price, Mark C.

2012-01-01

In the current paper, we first evaluate the suitability of traditional serial reaction time (SRT) and artificial grammar learning (AGL) experiments for measuring implicit learning of social signals. We then report the results of a novel sequence learning task which combines aspects of the SRT and AGL paradigms to meet our suggested criteria for how implicit learning experiments can be adapted to increase their relevance to situations of social intuition. The sequences followed standard finite-state grammars. Sequence learning and consciousness of acquired knowledge were compared between 2 groups of 24 participants viewing either sequences of individually presented letters or sequences of body-posture pictures, which were described as series of yoga movements. Participants in both conditions showed above-chance classification accuracy, indicating that sequence learning had occurred in both stimulus conditions. This shows that sequence learning can still be found when learning procedures reflect the characteristics of social intuition. Rule awareness was measured using trial-by-trial evaluation of decision strategy (Dienes & Scott, 2005; Scott & Dienes, 2008). For letters, sequence classification was best on trials where participants reported responding on the basis of explicit rules or memory, indicating some explicit learning in this condition. For body-posture, classification was not above chance on these types of trial, but instead showed a trend to be best on those trials where participants reported that their responses were based on intuition, familiarity, or random choice, suggesting that learning was more implicit. Results therefore indicate that the use of traditional stimuli in research on sequence learning might underestimate the extent to which learning is implicit in domains such as social learning, contributing to ongoing debate about levels of conscious awareness in implicit learning. PMID:22679467

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

ComplexContact: a web server for inter-protein contact prediction using deep learning.

PubMed

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

The Sequence of Learning Cycle Activities in High School Chemistry.

ERIC Educational Resources Information Center

Abraham, Michael R.; Renner, John W.

1986-01-01

Different learning cycle sequences were investigated to determine factors accounting for success of the cycle, compared learning with conventional instruction, and examined relationships between Piaget's theory and learning cycles. Results show that the normal learning cycle sequence is the optimum sequence for achievement of content knowledge in…

Effector-independent motor sequence representations exist in extrinsic and intrinsic reference frames.

PubMed

Wiestler, Tobias; Waters-Metenier, Sheena; Diedrichsen, Jörn

2014-04-02

Many daily activities rely on the ability to produce meaningful sequences of movements. Motor sequences can be learned in an effector-specific fashion (such that benefits of training are restricted to the trained hand) or an effector-independent manner (meaning that learning also facilitates performance with the untrained hand). Effector-independent knowledge can be represented in extrinsic/world-centered or in intrinsic/body-centered coordinates. Here, we used functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis to determine the distribution of intrinsic and extrinsic finger sequence representations across the human neocortex. Participants practiced four sequences with one hand for 4 d, and then performed these sequences during fMRI with both left and right hand. Between hands, these sequences were equivalent in extrinsic or intrinsic space, or were unrelated. In dorsal premotor cortex (PMd), we found that sequence-specific activity patterns correlated higher for extrinsic than for unrelated pairs, providing evidence for an extrinsic sequence representation. In contrast, primary sensory and motor cortices showed effector-independent representations in intrinsic space, with considerable overlap of the two reference frames in caudal PMd. These results suggest that effector-independent representations exist not only in world-centered, but also in body-centered coordinates, and that PMd may be involved in transforming sequential knowledge between the two. Moreover, although effector-independent sequence representations were found bilaterally, they were stronger in the hemisphere contralateral to the trained hand. This indicates that intermanual transfer relies on motor memories that are laid down during training in both hemispheres, but preferentially draws upon sequential knowledge represented in the trained hemisphere.

Effector-Independent Motor Sequence Representations Exist in Extrinsic and Intrinsic Reference Frames

PubMed Central

Wiestler, Tobias; Waters-Metenier, Sheena

2014-01-01

Many daily activities rely on the ability to produce meaningful sequences of movements. Motor sequences can be learned in an effector-specific fashion (such that benefits of training are restricted to the trained hand) or an effector-independent manner (meaning that learning also facilitates performance with the untrained hand). Effector-independent knowledge can be represented in extrinsic/world-centered or in intrinsic/body-centered coordinates. Here, we used functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis to determine the distribution of intrinsic and extrinsic finger sequence representations across the human neocortex. Participants practiced four sequences with one hand for 4 d, and then performed these sequences during fMRI with both left and right hand. Between hands, these sequences were equivalent in extrinsic or intrinsic space, or were unrelated. In dorsal premotor cortex (PMd), we found that sequence-specific activity patterns correlated higher for extrinsic than for unrelated pairs, providing evidence for an extrinsic sequence representation. In contrast, primary sensory and motor cortices showed effector-independent representations in intrinsic space, with considerable overlap of the two reference frames in caudal PMd. These results suggest that effector-independent representations exist not only in world-centered, but also in body-centered coordinates, and that PMd may be involved in transforming sequential knowledge between the two. Moreover, although effector-independent sequence representations were found bilaterally, they were stronger in the hemisphere contralateral to the trained hand. This indicates that intermanual transfer relies on motor memories that are laid down during training in both hemispheres, but preferentially draws upon sequential knowledge represented in the trained hemisphere. PMID:24695723

NREM2 and Sleep Spindles Are Instrumental to the Consolidation of Motor Sequence Memories

PubMed Central

Laventure, Samuel; Fogel, Stuart; Lungu, Ovidiu; Albouy, Geneviève; Sévigny-Dupont, Pénélope; Vien, Catherine; Sayour, Chadi; Carrier, Julie; Benali, Habib; Doyon, Julien

2016-01-01

Although numerous studies have convincingly demonstrated that sleep plays a critical role in motor sequence learning (MSL) consolidation, the specific contribution of the different sleep stages in this type of memory consolidation is still contentious. To probe the role of stage 2 non-REM sleep (NREM2) in this process, we used a conditioning protocol in three different groups of participants who either received an odor during initial training on a motor sequence learning task and were re-exposed to this odor during different sleep stages of the post-training night (i.e., NREM2 sleep [Cond-NREM2], REM sleep [Cond-REM], or were not conditioned during learning but exposed to the odor during NREM2 [NoCond]). Results show that the Cond-NREM2 group had significantly higher gains in performance at retest than both the Cond-REM and NoCond groups. Also, only the Cond-NREM2 group yielded significant changes in sleep spindle characteristics during cueing. Finally, we found that a change in frequency of sleep spindles during cued-memory reactivation mediated the relationship between the experimental groups and gains in performance the next day. These findings strongly suggest that cued-memory reactivation during NREM2 sleep triggers an increase in sleep spindle activity that is then related to the consolidation of motor sequence memories. PMID:27032084

Learning to predict is spared in mild cognitive impairment due to Alzheimer's disease.

PubMed

Baker, Rosalind; Bentham, Peter; Kourtzi, Zoe

2015-10-01

Learning the statistics of the environment is critical for predicting upcoming events. However, little is known about how we translate previous knowledge about scene regularities to sensory predictions. Here, we ask whether patients with mild cognitive impairment due to Alzheimer's disease (MCI-AD) that are known to have spared implicit but impaired explicit recognition memory are able to learn temporal regularities and predict upcoming events. We tested the ability of MCI-AD patients and age-matched controls to predict the orientation of a test stimulus following exposure to sequences of leftwards or rightwards oriented gratings. Our results demonstrate that exposure to temporal sequences without feedback facilitates the ability to predict an upcoming stimulus in both MCI-AD patients and controls. Further, we show that executive cognitive control may account for individual variability in predictive learning. That is, we observed significant positive correlations of performance in attentional and working memory tasks with post-training performance in the prediction task. Taken together, these results suggest a mediating role of circuits involved in cognitive control (i.e. frontal circuits) that may support the ability for predictive learning in MCI-AD.

First-order and higher order sequence learning in specific language impairment.

PubMed

Clark, Gillian M; Lum, Jarrad A G

2017-02-01

A core claim of the procedural deficit hypothesis of specific language impairment (SLI) is that the disorder is associated with poor implicit sequence learning. This study investigated whether implicit sequence learning problems in SLI are present for first-order conditional (FOC) and higher order conditional (HOC) sequences. Twenty-five children with SLI and 27 age-matched, nonlanguage-impaired children completed 2 serial reaction time tasks. On 1 version, the sequence to be implicitly learnt comprised a FOC sequence and on the other a HOC sequence. Results showed that the SLI group learned the HOC sequence (η p ² = .285, p = .005) but not the FOC sequence (η p ² = .099, p = .118). The control group learned both sequences (FOC η p ² = .497, HOC η p 2= .465, ps < .001). The SLI group's difficulty learning the FOC sequence is consistent with the procedural deficit hypothesis. However, the study provides new evidence that multiple mechanisms may underpin the learning of FOC and HOC sequences. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

NASA Astrophysics Data System (ADS)

Su, X.

2017-12-01

A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

Multi-level machine learning prediction of protein-protein interactions in Saccharomyces cerevisiae.

PubMed

Zubek, Julian; Tatjewski, Marcin; Boniecki, Adam; Mnich, Maciej; Basu, Subhadip; Plewczynski, Dariusz

2015-01-01

Accurate identification of protein-protein interactions (PPI) is the key step in understanding proteins' biological functions, which are typically context-dependent. Many existing PPI predictors rely on aggregated features from protein sequences, however only a few methods exploit local information about specific residue contacts. In this work we present a two-stage machine learning approach for prediction of protein-protein interactions. We start with the carefully filtered data on protein complexes available for Saccharomyces cerevisiae in the Protein Data Bank (PDB) database. First, we build linear descriptions of interacting and non-interacting sequence segment pairs based on their inter-residue distances. Secondly, we train machine learning classifiers to predict binary segment interactions for any two short sequence fragments. The final prediction of the protein-protein interaction is done using the 2D matrix representation of all-against-all possible interacting sequence segments of both analysed proteins. The level-I predictor achieves 0.88 AUC for micro-scale, i.e., residue-level prediction. The level-II predictor improves the results further by a more complex learning paradigm. We perform 30-fold macro-scale, i.e., protein-level cross-validation experiment. The level-II predictor using PSIPRED-predicted secondary structure reaches 0.70 precision, 0.68 recall, and 0.70 AUC, whereas other popular methods provide results below 0.6 threshold (recall, precision, AUC). Our results demonstrate that multi-scale sequence features aggregation procedure is able to improve the machine learning results by more than 10% as compared to other sequence representations. Prepared datasets and source code for our experimental pipeline are freely available for download from: http://zubekj.github.io/mlppi/ (open source Python implementation, OS independent).

A single bout of high-intensity aerobic exercise facilitates response to paired associative stimulation and promotes sequence-specific implicit motor learning

PubMed Central

Mang, Cameron S.; Snow, Nicholas J.; Campbell, Kristin L.; Ross, Colin J. D.

2014-01-01

The objectives of the present study were to evaluate the impact of a single bout of high-intensity aerobic exercise on 1) long-term potentiation (LTP)-like neuroplasticity via response to paired associative stimulation (PAS) and 2) the temporal and spatial components of sequence-specific implicit motor learning. Additionally, relationships between exercise-induced increases in systemic brain-derived neurotrophic factor (BDNF) and response to PAS and motor learning were evaluated. Sixteen young healthy participants completed six experimental sessions, including the following: 1) rest followed by PAS; 2) aerobic exercise followed by PAS; 3) rest followed by practice of a continuous tracking (CT) task and 4) a no-exercise 24-h retention test; and 5) aerobic exercise followed by CT task practice and 6) a no-exercise 24-h retention test. The CT task included an embedded repeated sequence allowing for evaluation of sequence-specific implicit learning. Slope of motor-evoked potential recruitment curves generated with transcranial magnetic stimulation showed larger increases when PAS was preceded by aerobic exercise (59.8% increase) compared with rest (14.2% increase, P = 0.02). Time lag of CT task performance on the repeated sequence improved under the aerobic exercise condition from early (−100.8 ms) to late practice (−75.2 ms, P < 0.001) and was maintained at retention (−79.2 ms, P = 0.004) but did not change under the rest condition (P > 0.16). Systemic BDNF increased on average by 3.4-fold following aerobic exercise (P = 0.003), but the changes did not relate to neurophysiological or behavioral measures (P > 0.42). These results indicate that a single bout of high-intensity aerobic exercise can prime LTP-like neuroplasticity and promote sequence-specific implicit motor learning. PMID:25257866

Recognizing human actions by learning and matching shape-motion prototype trees.

PubMed

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2012-03-01

A shape-motion prototype-based approach is introduced for action recognition. The approach represents an action as a sequence of prototypes for efficient and flexible action matching in long video sequences. During training, an action prototype tree is learned in a joint shape and motion space via hierarchical K-means clustering and each training sequence is represented as a labeled prototype sequence; then a look-up table of prototype-to-prototype distances is generated. During testing, based on a joint probability model of the actor location and action prototype, the actor is tracked while a frame-to-prototype correspondence is established by maximizing the joint probability, which is efficiently performed by searching the learned prototype tree; then actions are recognized using dynamic prototype sequence matching. Distance measures used for sequence matching are rapidly obtained by look-up table indexing, which is an order of magnitude faster than brute-force computation of frame-to-frame distances. Our approach enables robust action matching in challenging situations (such as moving cameras, dynamic backgrounds) and allows automatic alignment of action sequences. Experimental results demonstrate that our approach achieves recognition rates of 92.86 percent on a large gesture data set (with dynamic backgrounds), 100 percent on the Weizmann action data set, 95.77 percent on the KTH action data set, 88 percent on the UCF sports data set, and 87.27 percent on the CMU action data set.

Mood induction effects on motor sequence learning and stop signal reaction time.

PubMed

Greeley, Brian; Seidler, Rachael D

2017-01-01

The neurobiological theory of positive affect proposes that positive mood states may benefit cognitive performance due to an increase of dopamine throughout the brain. However, the results of many positive affect studies are inconsistent; this may be due to individual differences. The relationship between dopamine and performance is not linear, but instead follows an inverted "U" shape. Given this, we hypothesized that individuals with high working memory capacity, a proxy measure for dopaminergic transmission, would not benefit from positive mood induction and in fact performance in dopamine-mediated tasks would decline. In contrast, we predicted that individuals with low working memory capacities would receive the most benefit after positive mood induction. Here, we explored the effect of positive affect on two dopamine-mediated tasks, an explicit serial reaction time sequence learning task and the stop signal task, predicting that an individual's performance is modulated not only by working memory capacity, but also on the type of mood. Improvements in explicit sequence learning from pre- to post-positive mood induction were associated with working memory capacity; performance declined in individuals with higher working memory capacities following positive mood induction, but improved in individuals with lower working memory capacities. This was not the case for negative or neutral mood induction. Moreover, there was no relationship between the change in stop signal reaction time with any of the mood inductions and individual differences in working memory capacity. These results provide partial support for the neurobiological theory of positive affect and highlight the importance of taking into account individual differences in working memory when examining the effects of positive mood induction.

Structured Semantic Knowledge Can Emerge Automatically from Predicting Word Sequences in Child-Directed Speech

PubMed Central

Huebner, Philip A.; Willits, Jon A.

2018-01-01

Previous research has suggested that distributional learning mechanisms may contribute to the acquisition of semantic knowledge. However, distributional learning mechanisms, statistical learning, and contemporary “deep learning” approaches have been criticized for being incapable of learning the kind of abstract and structured knowledge that many think is required for acquisition of semantic knowledge. In this paper, we show that recurrent neural networks, trained on noisy naturalistic speech to children, do in fact learn what appears to be abstract and structured knowledge. We trained two types of recurrent neural networks (Simple Recurrent Network, and Long Short-Term Memory) to predict word sequences in a 5-million-word corpus of speech directed to children ages 0–3 years old, and assessed what semantic knowledge they acquired. We found that learned internal representations are encoding various abstract grammatical and semantic features that are useful for predicting word sequences. Assessing the organization of semantic knowledge in terms of the similarity structure, we found evidence of emergent categorical and hierarchical structure in both models. We found that the Long Short-term Memory (LSTM) and SRN are both learning very similar kinds of representations, but the LSTM achieved higher levels of performance on a quantitative evaluation. We also trained a non-recurrent neural network, Skip-gram, on the same input to compare our results to the state-of-the-art in machine learning. We found that Skip-gram achieves relatively similar performance to the LSTM, but is representing words more in terms of thematic compared to taxonomic relations, and we provide reasons why this might be the case. Our findings show that a learning system that derives abstract, distributed representations for the purpose of predicting sequential dependencies in naturalistic language may provide insight into emergence of many properties of the developing semantic system. PMID:29520243

Sequence Learning Is Preserved in Individuals with Cerebellar Degeneration when the Movements Are Directly Cued

ERIC Educational Resources Information Center

Spencer, Rebecca M. C.; Ivry, Richard B.

2009-01-01

Cerebellar pathology is associated with impairments on a range of motor learning tasks including sequence learning. However, various lines of evidence are at odds with the idea that the cerebellum plays a central role in the associative processes underlying sequence learning. Behavioral studies indicate that sequence learning, at least with short…

A Comparison of the Effects of Temporary Hippocampal Lesions on Single and Dual Context Versions of the Olfactory Sequence Memory Task

PubMed Central

Sill, Orriana C.; Smith, David M.

2012-01-01

In recent years, many animal models of memory have focused on one or more of the various components of episodic memory. For example, the odor sequence memory task requires subjects to remember individual items and events (the odors) and the temporal aspects of the experience (the sequence of odor presentation). The well-known spatial context coding function of the hippocampus, as exemplified by place cell firing, may reflect the ‘where’ component of episodic memory. In the present study, we added a contextual component to the odor sequence memory task by training rats to choose the earlier odor in one context and the later odor in another context and we compared the effects of temporary hippocampal lesions on performance of the original single context task and the new dual context task. Temporary lesions significantly impaired the single context task, although performance remained significantly above chance levels. In contrast, performance dropped all the way to chance when temporary lesions were used in the dual context task. These results demonstrate that rats can learn a dual context version of the odor sequence learning task which requires the use of contextual information along with the requirement to remember the ‘what’ and ‘when’ components of the odor sequence. Moreover, the additional requirement of context-dependent expression of the ‘what-when’ memory made the task fully dependent on the hippocampus. Moreover, the addition of the contextual component made the task fully dependent on the hippocampus. PMID:22687149

PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

PubMed

Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I

2018-04-14

Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Social Cues Alter Implicit Motor Learning in a Serial Reaction Time Task.

PubMed

Geiger, Alexander; Cleeremans, Axel; Bente, Gary; Vogeley, Kai

2018-01-01

Learning is a central ability for human development. Many skills we learn, such as language, are learned through observation or imitation in social contexts. Likewise, many skills are learned implicitly, that is, without an explicit intent to learn and without full awareness of the acquired knowledge. Here, we asked whether performance in a motor learning task is modulated by social vs. object cues of varying validity. To address this question, we asked participants to carry out a serial reaction time (SRT) task in which, on each trial, people have to respond as fast and as accurately as possible to the appearance of a stimulus at one of four possible locations. Unbeknownst to participants, the sequence of successive locations was sequentially structured, so that knowledge of the sequence facilitates anticipation of the next stimulus and hence faster motor responses. Crucially, each trial also contained a cue pointing to the next stimulus location. Participants could thus learn based on the cue, or on learning about the sequence of successive locations, or on a combination of both. Results show an interaction between cue type and cue validity for the motor responses: social cues (vs. object cues) led to faster responses in the low validity (LV) condition only. Concerning the extent to which learning was implicit, results show that in the cued blocks only, the highly valid social cue led to implicit learning. In the uncued blocks, participants showed no implicit learning in the highly valid social cue condition, but did in all other combinations of stimulus type and cueing validity. In conclusion, our results suggest that implicit learning is context-dependent and can be influenced by the cue type, e.g., social and object cues.

An Evolutionary Machine Learning Framework for Big Data Sequence Mining

ERIC Educational Resources Information Center

Kamath, Uday Krishna

2014-01-01

Sequence classification is an important problem in many real-world applications. Unlike other machine learning data, there are no "explicit" features or signals in sequence data that can help traditional machine learning algorithms learn and predict from the data. Sequence data exhibits inter-relationships in the elements that are…

Learning Communities for Students in Developmental Math: Impact Studies at Queensborough and Houston Community Colleges. Executive Summary

ERIC Educational Resources Information Center

Weissman, Evan; Butcher, Kristin F.; Schneider, Emily; Teres, Jedediah; Collado, Herbert; Greenberg, David

2011-01-01

Queensborough Community College and Houston Community College are two large, urban institutions that offer learning communities for their developmental math students, with the goals of accelerating students' progress through the math sequence and of helping them to perform better in college and ultimately earn degrees or certificates. They are…

Learning Communities for Students in Developmental Math: Impact Studies at Queensborough and Houston Community Colleges

ERIC Educational Resources Information Center

Weissman, Evan; Butcher, Kristin F.; Schneider, Emily; Teres, Jedediah; Collado, Herbert; Greenberg, David

2011-01-01

Queensborough Community College and Houston Community College are two large, urban institutions that offer learning communities for their developmental math students, with the goals of accelerating students' progress through the math sequence and of helping them to perform better in college and ultimately earn degrees or certificates. They are…

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…

Construction of Graphic Symbol Sequences by Preschool-Aged Children: Learning, Training, and Maintenance

ERIC Educational Resources Information Center

Poupart, Annick; Trudeau, Natacha; Sutton, Ann

2013-01-01

The use of augmentative and alternative communication systems based on graphic symbols requires children to learn to combine symbols to convey utterances. The current study investigated how children without disabilities aged 4 to 6 years (n = 74) performed on a simple sentence (subject-verb and subject-verb-object) transposition task (i.e., spoken…

Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis

PubMed Central

2013-01-01

Background Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes and form the basis of biological mechanisms. Although large amount of PPIs data for different species has been generated by high-throughput experimental techniques, current PPI pairs obtained with experimental methods cover only a fraction of the complete PPI networks, and further, the experimental methods for identifying PPIs are both time-consuming and expensive. Hence, it is urgent and challenging to develop automated computational methods to efficiently and accurately predict PPIs. Results We present here a novel hierarchical PCA-EELM (principal component analysis-ensemble extreme learning machine) model to predict protein-protein interactions only using the information of protein sequences. In the proposed method, 11188 protein pairs retrieved from the DIP database were encoded into feature vectors by using four kinds of protein sequences information. Focusing on dimension reduction, an effective feature extraction method PCA was then employed to construct the most discriminative new feature set. Finally, multiple extreme learning machines were trained and then aggregated into a consensus classifier by majority voting. The ensembling of extreme learning machine removes the dependence of results on initial random weights and improves the prediction performance. Conclusions When performed on the PPI data of Saccharomyces cerevisiae, the proposed method achieved 87.00% prediction accuracy with 86.15% sensitivity at the precision of 87.59%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Experimental results demonstrate that proposed PCA-EELM outperforms the SVM method by 5-fold cross-validation. Besides, PCA-EELM performs faster than PCA-SVM based method. Consequently, the proposed approach can be considered as a new promising and powerful tools for predicting PPI with excellent performance and less time. PMID:23815620

Convolutional neural network architectures for predicting DNA–protein binding

PubMed Central

Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

2016-01-01

Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

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.

Extracting features from protein sequences to improve deep extreme learning machine for protein fold recognition.

PubMed

Ibrahim, Wisam; Abadeh, Mohammad Saniee

2017-05-21

Protein fold recognition is an important problem in bioinformatics to predict three-dimensional structure of a protein. One of the most challenging tasks in protein fold recognition problem is the extraction of efficient features from the amino-acid sequences to obtain better classifiers. In this paper, we have proposed six descriptors to extract features from protein sequences. These descriptors are applied in the first stage of a three-stage framework PCA-DELM-LDA to extract feature vectors from the amino-acid sequences. Principal Component Analysis PCA has been implemented to reduce the number of extracted features. The extracted feature vectors have been used with original features to improve the performance of the Deep Extreme Learning Machine DELM in the second stage. Four new features have been extracted from the second stage and used in the third stage by Linear Discriminant Analysis LDA to classify the instances into 27 folds. The proposed framework is implemented on the independent and combined feature sets in SCOP datasets. The experimental results show that extracted feature vectors in the first stage could improve the performance of DELM in extracting new useful features in second stage. Copyright © 2017 Elsevier Ltd. All rights reserved.

TRACX2: a connectionist autoencoder using graded chunks to model infant visual statistical learning.

PubMed

Mareschal, Denis; French, Robert M

2017-01-05

Even newborn infants are able to extract structure from a stream of sensory inputs; yet how this is achieved remains largely a mystery. We present a connectionist autoencoder model, TRACX2, that learns to extract sequence structure by gradually constructing chunks, storing these chunks in a distributed manner across its synaptic weights and recognizing these chunks when they re-occur in the input stream. Chunks are graded rather than all-or-nothing in nature. As chunks are learnt their component parts become more and more tightly bound together. TRACX2 successfully models the data from five experiments from the infant visual statistical learning literature, including tasks involving forward and backward transitional probabilities, low-salience embedded chunk items, part-sequences and illusory items. The model also captures performance differences across ages through the tuning of a single-learning rate parameter. These results suggest that infant statistical learning is underpinned by the same domain-general learning mechanism that operates in auditory statistical learning and, potentially, in adult artificial grammar learning.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

TRACX2: a connectionist autoencoder using graded chunks to model infant visual statistical learning

PubMed Central

French, Robert M.

2017-01-01

Even newborn infants are able to extract structure from a stream of sensory inputs; yet how this is achieved remains largely a mystery. We present a connectionist autoencoder model, TRACX2, that learns to extract sequence structure by gradually constructing chunks, storing these chunks in a distributed manner across its synaptic weights and recognizing these chunks when they re-occur in the input stream. Chunks are graded rather than all-or-nothing in nature. As chunks are learnt their component parts become more and more tightly bound together. TRACX2 successfully models the data from five experiments from the infant visual statistical learning literature, including tasks involving forward and backward transitional probabilities, low-salience embedded chunk items, part-sequences and illusory items. The model also captures performance differences across ages through the tuning of a single-learning rate parameter. These results suggest that infant statistical learning is underpinned by the same domain-general learning mechanism that operates in auditory statistical learning and, potentially, in adult artificial grammar learning. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872375

Sleep spindles: a physiological marker of age-related changes in gray matter in brain regions supporting motor skill memory consolidation.

PubMed

Fogel, Stuart; Vien, Catherine; Karni, Avi; Benali, Habib; Carrier, Julie; Doyon, Julien

2017-01-01

Sleep is necessary for the optimal consolidation of procedural learning, and in particular, for motor sequential skills. Motor sequence learning remains intact with age, but sleep-dependent consolidation is impaired, suggesting that memory deficits for procedural skills are specifically impacted by age-related changes in sleep. Age-related changes in spindles may be responsible for impaired motor sequence learning consolidation, but the morphological basis for this deficit is unknown. Here, we found that gray matter in the hippocampus and cerebellum was positively correlated with both sleep spindles and offline improvements in performance in young participants but not in older participants. These results suggest that age-related changes in gray matter in the hippocampus relate to spindles and may underlie age-related deficits in sleep-related motor sequence memory consolidation. In this way, spindles can serve as a biological marker for structural brain changes and the related memory deficits in older adults. Copyright © 2016 Elsevier Inc. All rights reserved.

Using Video Game Telemetry Data to Research Motor Chunking, Action Latencies, and Complex Cognitive-Motor Skill Learning.

PubMed

Thompson, Joseph J; McColeman, C M; Stepanova, Ekaterina R; Blair, Mark R

2017-04-01

Many theories of complex cognitive-motor skill learning are built on the notion that basic cognitive processes group actions into easy-to-perform sequences. The present work examines predictions derived from laboratory-based studies of motor chunking and motor preparation using data collected from the real-time strategy video game StarCraft 2. We examined 996,163 action sequences in the telemetry data of 3,317 players across seven levels of skill. As predicted, the latency to the first action (thought to be the beginning of a chunked sequence) is delayed relative to the other actions in the group. Other predictions, inspired by the memory drum theory of Henry and Rogers, received only weak support. Copyright © 2017 Cognitive Science Society, Inc.

Identification of tissue-specific targeting peptide

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Lee, Nam Kyung; Kang, Sang-Kee; Choi, Seung-Hoon; Kim, Daejin; Park, Kisoo; Choi, Kihang; Choi, Yun-Jaie; Jung, Dong Hyun

2012-11-01

Using phage display technique, we identified tissue-targeting peptide sets that recognize specific tissues (bone-marrow dendritic cell, kidney, liver, lung, spleen and visceral adipose tissue). In order to rapidly evaluate tissue-specific targeting peptides, we performed machine learning studies for predicting the tissue-specific targeting activity of peptides on the basis of peptide sequence information using four machine learning models and isolated the groups of peptides capable of mediating selective targeting to specific tissues. As a representative liver-specific targeting sequence, the peptide "DKNLQLH" was selected by the sequence similarity analysis. This peptide has a high degree of homology with protein ligands which can interact with corresponding membrane counterparts. We anticipate that our models will be applicable to the prediction of tissue-specific targeting peptides which can recognize the endothelial markers of target tissues.

Children benefit differently from night- and day-time sleep in motor learning.

PubMed

Yan, Jin H

2017-08-01

Motor skill acquisition occurs while practicing (on-line) and when asleep or awake (off-line). However, developmental questions still remain about whether children of various ages benefit similarly or differentially from night- and day-time sleeping. The likely circadian effects (time-of-day) and the possible between-test-interference (order effects) associated with children's off-line motor learning are currently unknown. Therefore, this study examines the contributions of over-night sleeping and mid-day napping to procedural skill learning. One hundred and eight children were instructed to practice a finger sequence task using computer keyboards. After an equivalent 11-h interval in one of the three states (sleep, nap, wakefulness), children performed the same sequence in retention tests and a novel sequence in transfer tests. Changes in the movement time and sequence accuracy were evaluated between ages (6-7, 8-9, 10-11years) during practice, and from skill training to retrievals across three states. Results suggest that night-time sleeping and day-time napping improved the tapping speed, especially for the 6-year-olds. The circadian factor did not affect off-line motor learning in children. The interference between the two counter-balanced retrieval tests was not found for the off-line motor learning. This research offers possible evidence about the age-related motor learning characteristics in children and a potential means for enhancing developmental motor skills. The dynamics between age, experience, memory formation, and the theoretical implications of motor skill acquisition are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin.

PubMed

Bokulich, Nicholas A; Kaehler, Benjamin D; Rideout, Jai Ram; Dillon, Matthew; Bolyen, Evan; Knight, Rob; Huttley, Gavin A; Gregory Caporaso, J

2018-05-17

Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

Questioning short-term memory and its measurement: Why digit span measures long-term associative learning.

PubMed

Jones, Gary; Macken, Bill

2015-11-01

Traditional accounts of verbal short-term memory explain differences in performance for different types of verbal material by reference to inherent characteristics of the verbal items making up memory sequences. The role of previous experience with sequences of different types is ostensibly controlled for either by deliberate exclusion or by presenting multiple trials constructed from different random permutations. We cast doubt on this general approach in a detailed analysis of the basis for the robust finding that short-term memory for digit sequences is superior to that for other sequences of verbal material. Specifically, we show across four experiments that this advantage is not due to inherent characteristics of digits as verbal items, nor are individual digits within sequences better remembered than other types of individual verbal items. Rather, the advantage for digit sequences stems from the increased frequency, compared to other verbal material, with which digits appear in random sequences in natural language, and furthermore, relatively frequent digit sequences support better short-term serial recall than less frequent ones. We also provide corpus-based computational support for the argument that performance in a short-term memory setting is a function of basic associative learning processes operating on the linguistic experience of the rememberer. The experimental and computational results raise questions not only about the role played by measurement of digit span in cognition generally, but also about the way in which long-term memory processes impact on short-term memory functioning. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Learning piano melodies in visuo-motor or audio-motor training conditions and the neural correlates of their cross-modal transfer.

PubMed

Engel, Annerose; Bangert, Marc; Horbank, David; Hijmans, Brenda S; Wilkens, Katharina; Keller, Peter E; Keysers, Christian

2012-11-01

To investigate the cross-modal transfer of movement patterns necessary to perform melodies on the piano, 22 non-musicians learned to play short sequences on a piano keyboard by (1) merely listening and replaying (vision of own fingers occluded) or (2) merely observing silent finger movements and replaying (on a silent keyboard). After training, participants recognized with above chance accuracy (1) audio-motor learned sequences upon visual presentation (89±17%), and (2) visuo-motor learned sequences upon auditory presentation (77±22%). The recognition rates for visual presentation significantly exceeded those for auditory presentation (p<.05). fMRI revealed that observing finger movements corresponding to audio-motor trained melodies is associated with stronger activation in the left rolandic operculum than observing untrained sequences. This region was also involved in silent execution of sequences, suggesting that a link to motor representations may play a role in cross-modal transfer from audio-motor training condition to visual recognition. No significant differences in brain activity were found during listening to visuo-motor trained compared to untrained melodies. Cross-modal transfer was stronger from the audio-motor training condition to visual recognition and this is discussed in relation to the fact that non-musicians are familiar with how their finger movements look (motor-to-vision transformation), but not with how they sound on a piano (motor-to-sound transformation). Copyright © 2012 Elsevier Inc. All rights reserved.

Motor strategies and bilateral transfer in sensorimotor learning of patients with subacute stroke and healthy subjects. A randomized controlled trial.

PubMed

Iosa, M; Morone, G; Ragaglini, M R; Fusco, A; Paolucci, S

2013-06-01

Bilateral transfer, i.e. the capacity to transfer from one to the other hand a learned motor skill, may help the recovery of upper limb functions after stroke. To investigate the motor strategies at the basis of sensorimotor learning involved in bilateral transfer. Randomized controlled trial. Neurorehabilitation Hospital. Eighty right-handed participants (65 ± 13 years old): 40 patients with subacute stroke, 40 control healthy subjects. Subjects performed the 9 hole-peg-test twice in an order defined by random allocation: first with low and then with high skilled hand (LS-HS) or the reverse (HS-LS). Time spent to complete the test and filling sequence were recorded, together with maximum pinch force (assessed using a dynamometer), upper limb functioning (Motricity Index), spasticity (modified Ashworth Scale), limb dominance (Edinburgh Handeness Inventory). As expected, in patients, the performance was found related to the residual pinch force (P<0.001), upper limb motricity (P=0.006) and side of hemiparesis (P=0.016). The performances of all subjects improved more in HS-LS than in LS-HS subgroups (P=0.043). The strategy adopted in the first trial influenced the velocity in the second one (P=0.030). Bilateral transfer was observed from high to low skilled hand. Learning was not due to a mere sequence repetition, but on a strategy chosen on the basis of the previous performance. The affected hand of patients with subacute stroke may benefit from sensorimotor learning occurred with the un-affected hand.

Affordable hands-on DNA sequencing and genotyping: an exercise for teaching DNA analysis to undergraduates.

PubMed

Shah, Kushani; Thomas, Shelby; Stein, Arnold

2013-01-01

In this report, we describe a 5-week laboratory exercise for undergraduate biology and biochemistry students in which students learn to sequence DNA and to genotype their DNA for selected single nucleotide polymorphisms (SNPs). Students use miniaturized DNA sequencing gels that require approximately 8 min to run. The students perform G, A, T, C Sanger sequencing reactions. They prepare and run the gels, perform Southern blots (which require only 10 min), and detect sequencing ladders using a colorimetric detection system. Students enlarge their sequencing ladders from digital images of their small nylon membranes, and read the sequence manually. They compare their reads with the actual DNA sequence using BLAST2. After mastering the DNA sequencing system, students prepare their own DNA from a cheek swab, polymerase chain reaction-amplify a region of their DNA that encompasses a SNP of interest, and perform sequencing to determine their genotype at the SNP position. A family pedigree can also be constructed. The SNP chosen by the instructor was rs17822931, which is in the ABCC11 gene and is the determinant of human earwax type. Genotypes at the rs178229931 site vary in different ethnic populations. © 2013 by The International Union of Biochemistry and Molecular Biology.

Solving the Curriculum Sequencing Problem with DNA Computing Approach

ERIC Educational Resources Information Center

Debbah, Amina; Ben Ali, Yamina Mohamed

2014-01-01

In the e-learning systems, a learning path is known as a sequence of learning materials linked to each others to help learners achieving their learning goals. As it is impossible to have the same learning path that suits different learners, the Curriculum Sequencing problem (CS) consists of the generation of a personalized learning path for each…

On the Modularity of Implicit Sequence Learning: Independent Acquisition of Spatial, Symbolic, and Manual Sequences

ERIC Educational Resources Information Center

Goschke, Thomas; Bolte, Annette

2012-01-01

Learning sequential structures is of fundamental importance for a wide variety of human skills. While it has long been debated whether implicit sequence learning is perceptual or response-based, here we propose an alternative framework that cuts across this dichotomy and assumes that sequence learning rests on associative changes that can occur…

The Sequence of Study Changes What Information Is Attended to, Encoded, and Remembered during Category Learning

ERIC Educational Resources Information Center

Carvalho, Paulo F.; Goldstone, Robert L.

2017-01-01

The sequence of study influences how we learn. Previous research has identified different sequences as potentially beneficial for learning in different contexts and with different materials. Here we investigate the mechanisms involved in inductive category learning that give rise to these sequencing effects. Across 3 experiments we show evidence…

Compensatory Motor Network Connectivity is Associated with Motor Sequence Learning after Subcortical Stroke

PubMed Central

Wadden, Katie P.; Woodward, Todd S.; Metzak, Paul D.; Lavigne, Katie M.; Lakhani, Bimal; Auriat, Angela M.; Boyd, Lara A.

2015-01-01

Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behaviour within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke. PMID:25757996

What you learn is more than what you see: what can sequencing effects tell us about inductive category learning?

PubMed Central

Carvalho, Paulo F.; Goldstone, Robert L.

2015-01-01

Inductive category learning takes place across time. As such, it is not surprising that the sequence in which information is studied has an impact in what is learned and how efficient learning is. In this paper we review research on different learning sequences and how this impacts learning. We analyze different aspects of interleaved (frequent alternation between categories during study) and blocked study (infrequent alternation between categories during study) that might explain how and when one sequence of study results in improved learning. While these different sequences of study differ in the amount of temporal spacing and temporal juxtaposition between items of different categories, these aspects do not seem to account for the majority of the results available in the literature. However, differences in the type of category being studied and the duration of the retention interval between study and test may play an important role. We conclude that there is no single aspect that is able to account for all the evidence available. Understanding learning as a process of sequential comparisons in time and how different sequences fundamentally alter the statistics of this experience offers a promising framework for understanding sequencing effects in category learning. We use this framework to present novel predictions and hypotheses for future research on sequencing effects in inductive category learning. PMID:25983699

QUICR-learning for Multi-Agent Coordination

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2006-01-01

Coordinating multiple agents that need to perform a sequence of actions to maximize a system level reward requires solving two distinct credit assignment problems. First, credit must be assigned for an action taken at time step t that results in a reward at time step t > t. Second, credit must be assigned for the contribution of agent i to the overall system performance. The first credit assignment problem is typically addressed with temporal difference methods such as Q-learning. The second credit assignment problem is typically addressed by creating custom reward functions. To address both credit assignment problems simultaneously, we propose the "Q Updates with Immediate Counterfactual Rewards-learning" (QUICR-learning) designed to improve both the convergence properties and performance of Q-learning in large multi-agent problems. QUICR-learning is based on previous work on single-time-step counterfactual rewards described by the collectives framework. Results on a traffic congestion problem shows that QUICR-learning is significantly better than a Q-learner using collectives-based (single-time-step counterfactual) rewards. In addition QUICR-learning provides significant gains over conventional and local Q-learning. Additional results on a multi-agent grid-world problem show that the improvements due to QUICR-learning are not domain specific and can provide up to a ten fold increase in performance over existing methods.

Prediction of protein tertiary structure from sequences using a very large back-propagation neural network

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

Liu, X.; Wilcox, G.L.

1993-12-31

We have implemented large scale back-propagation neural networks on a 544 node Connection Machine, CM-5, using the C language in MIMD mode. The program running on 512 processors performs backpropagation learning at 0.53 Gflops, which provides 76 million connection updates per second. We have applied the network to the prediction of protein tertiary structure from sequence information alone. A neural network with one hidden layer and 40 million connections is trained to learn the relationship between sequence and tertiary structure. The trained network yields predicted structures of some proteins on which it has not been trained given only their sequences.more » Presentation of the Fourier transform of the sequences accentuates periodicity in the sequence and yields good generalization with greatly increased training efficiency. Training simulations with a large, heterologous set of protein structures (111 proteins from CM-5 time) to solutions with under 2% RMS residual error within the training set (random responses give an RMS error of about 20%). Presentation of 15 sequences of related proteins in a testing set of 24 proteins yields predicted structures with less than 8% RMS residual error, indicating good apparent generalization.« less

Sleep benefits consolidation of visuo-motor adaptation learning in older adults.

PubMed

Mantua, Janna; Baran, Bengi; Spencer, Rebecca M C

2016-02-01

Sleep is beneficial for performance across a range of memory tasks in young adults, but whether memories are similarly consolidated in older adults is less clear. Performance benefits have been observed following sleep in older adults for declarative learning tasks, but this benefit may be reduced for non-declarative, motor skill learning tasks. To date, studies of sleep-dependent consolidation of motor learning in older adults are limited to motor sequence tasks. To examine whether reduced sleep-dependent consolidation in older adults is generalizable to other forms of motor skill learning, we examined performance changes over intervals of sleep and wake in young (n = 62) and older adults (n = 61) using a mirror-tracing task, which assesses visuo-motor adaptation learning. Participants learned the task either in the morning or in evening, and performance was assessed following a 12-h interval containing overnight sleep or daytime wake. Contrary to our prediction, both young adults and older adults exhibited sleep-dependent gains in visuo-motor adaptation. There was a correlation between performance improvement over sleep and percent of the night in non-REM stage 2 sleep. These results indicate that motor skill consolidation remains intact with increasing age although this relationship may be limited to specific forms of motor skill learning.

Mental Effort and Performance as Determinants for the Dynamic Selection of Learning Tasks in Air Traffic Control Training

ERIC Educational Resources Information Center

Salden, Ron J.C.M.; Paas, Fred; Broers, Nick J.; van Merrienboer, Jeroen J. G.

2004-01-01

The differential effects of four task selection methods on training efficiency and transfer in computer-based training for Air Traffic Control were investigated. A non-dynamic condition, in which the learning tasks were presented to the participants in a fixed, predetermined sequence, was compared to three dynamic conditions, in which learning…

Transforming Undergraduate Students into Junior Researchers: Oxidation-Reduction Sequence as a Problem-Based Case Study

ERIC Educational Resources Information Center

Saloranta, Tiina; Lo¨nnqvist, Jan-Erik; Eklund, Patrik C.

2016-01-01

In our upper-level undergraduate laboratory course in organic chemistry we focus on a research-oriented task in a context-based and problem-based learning approach. The course starts with a preliminary training period where the students learn how to safely and independently perform synthesis and purification procedures and to operate the most…

Pure Perceptual-Based Sequence Learning: A Role for Visuospatial Attention

ERIC Educational Resources Information Center

Remillard, Gilbert

2009-01-01

Learning the structure of a sequence of target locations when target location is not the response dimension and the sequence of target locations is uncorrelated with the sequence of responses is called pure perceptual-based sequence learning. The paradigm introduced by G. Remillard (2003) was used to determine whether orienting of visuospatial…

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.

Team-based learning to improve learning outcomes in a therapeutics course sequence.

PubMed

Bleske, Barry E; Remington, Tami L; Wells, Trisha D; Dorsch, Michael P; Guthrie, Sally K; Stumpf, Janice L; Alaniz, Marissa C; Ellingrod, Vicki L; Tingen, Jeffrey M

2014-02-12

To compare the effectiveness of team-based learning (TBL) to that of traditional lectures on learning outcomes in a therapeutics course sequence. A revised TBL curriculum was implemented in a therapeutic course sequence. Multiple choice and essay questions identical to those used to test third-year students (P3) taught using a traditional lecture format were administered to the second-year pharmacy students (P2) taught using the new TBL format. One hundred thirty-one multiple-choice questions were evaluated; 79 tested recall of knowledge and 52 tested higher level, application of knowledge. For the recall questions, students taught through traditional lectures scored significantly higher compared to the TBL students (88%±12% vs. 82%±16%, p=0.01). For the questions assessing application of knowledge, no differences were seen between teaching pedagogies (81%±16% vs. 77%±20%, p=0.24). Scores on essay questions and the number of students who achieved 100% were also similar between groups. Transition to a TBL format from a traditional lecture-based pedagogy allowed P2 students to perform at a similar level as students with an additional year of pharmacy education on application of knowledge type questions. However, P3 students outperformed P2 students regarding recall type questions and overall. Further assessment of long-term learning outcomes is needed to determine if TBL produces more persistent learning and improved application in clinical settings.

Magnifying visual target information and the role of eye movements in motor sequence learning.

PubMed

Massing, Matthias; Blandin, Yannick; Panzer, Stefan

2016-01-01

An experiment investigated the influence of eye movements on learning a simple motor sequence task when the visual display was magnified. The task was to reproduce a 1300 ms spatial-temporal pattern of elbow flexions and extensions. The spatial-temporal pattern was displayed in front of the participants. Participants were randomly assigned to four groups differing on eye movements (free to use their eyes/instructed to fixate) and the visual display (small/magnified). All participants had to perform a pre-test, an acquisition phase, a delayed retention test, and a transfer test. The results indicated that participants in each practice condition increased their performance during acquisition. The participants who were permitted to use their eyes in the magnified visual display outperformed those who were instructed to fixate on the magnified visual display. When a small visual display was used, the instruction to fixate induced no performance decrements compared to participants who were permitted to use their eyes during acquisition. The findings demonstrated that a spatial-temporal pattern can be learned without eye movements, but being permitting to use eye movements facilitates the response production when the visual angle is increased. Copyright © 2015 Elsevier B.V. All rights reserved.

Sequences show rapid motor transfer and spatial translation in the oculomotor system.

PubMed

Stainer, Matthew J; Carpenter, R H S; Brotchie, Peter; Anderson, Andrew J

2016-07-01

Every day we perform learnt sequences of actions that seem to happen almost without awareness. It has been argued that for learning such sequences parallel learning networks exist - one using spatial coordinates and one using motor coordinates - with sequence acquisition involving a progressive shift from the former to the latter as a sequence is rehearsed. When sequences are interrupted by an out-of-sequence target, there is a delay in the response to the target, and so here we transiently interrupt oculomotor sequences to probe the influence of oculomotor rehearsal and spatial coordinates in sequence acquisition. For our main experiments, we used a repeating sequences of eight targets in length that was first learnt either using saccadic eye movements (left/right), manual responses (left/right or up/down) or as a sequence of colour (blue/red) requiring no motor response. The sequence was immediately repeated for saccadic eye movements, during which the influence of on out-of-sequence target (an interruption) was assessed. When a sequence is learnt beforehand in an abstract way (for example, as a sequence of colours or of orthogonally mapped manual responses), interruptions are immediately disruptive to latency, suggesting neither motor rehearsal nor specific spatial coordinates are essential for encoding sequences of actions and that sequences - no matter how they are encoded - can be rapidly translated into oculomotor coordinates. The magnitude of a disruption does, however, correspond to how well a sequence is learnt: introducing an interruption to an extended sequence before it was reliably learnt reduces the magnitude of the latency disruption. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis and Prediction of Myristoylation Sites Using the mRMR Method, the IFS Method and an Extreme Learning Machine Algorithm.

PubMed

Wang, ShaoPeng; Zhang, Yu-Hang; Huang, GuoHua; Chen, Lei; Cai, Yu-Dong

2017-01-01

Myristoylation is an important hydrophobic post-translational modification that is covalently bound to the amino group of Gly residues on the N-terminus of proteins. The many diverse functions of myristoylation on proteins, such as membrane targeting, signal pathway regulation and apoptosis, are largely due to the lipid modification, whereas abnormal or irregular myristoylation on proteins can lead to several pathological changes in the cell. To better understand the function of myristoylated sites and to correctly identify them in protein sequences, this study conducted a novel computational investigation on identifying myristoylation sites in protein sequences. A training dataset with 196 positive and 84 negative peptide segments were obtained. Four types of features derived from the peptide segments following the myristoylation sites were used to specify myristoylatedand non-myristoylated sites. Then, feature selection methods including maximum relevance and minimum redundancy (mRMR), incremental feature selection (IFS), and a machine learning algorithm (extreme learning machine method) were adopted to extract optimal features for the algorithm to identify myristoylation sites in protein sequences, thereby building an optimal prediction model. As a result, 41 key features were extracted and used to build an optimal prediction model. The effectiveness of the optimal prediction model was further validated by its performance on a test dataset. Furthermore, detailed analyses were also performed on the extracted 41 features to gain insight into the mechanism of myristoylation modification. This study provided a new computational method for identifying myristoylation sites in protein sequences. We believe that it can be a useful tool to predict myristoylation sites from protein sequences. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding.

PubMed

Min, Xu; Zeng, Wanwen; Chen, Ning; Chen, Ting; Jiang, Rui

2017-07-15

Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k -mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k -mer co-occurrence information with recent advances in deep learning. We fill this gap by addressing the problem of chromatin accessibility prediction with a convolutional Long Short-Term Memory (LSTM) network with k -mer embedding. We first split DNA sequences into k -mers and pre-train k -mer embedding vectors based on the co-occurrence matrix of k -mers by using an unsupervised representation learning approach. We then construct a supervised deep learning architecture comprised of an embedding layer, three convolutional layers and a Bidirectional LSTM (BLSTM) layer for feature learning and classification. We demonstrate that our method gains high-quality fixed-length features from variable-length sequences and consistently outperforms baseline methods. We show that k -mer embedding can effectively enhance model performance by exploring different embedding strategies. We also prove the efficacy of both the convolution and the BLSTM layers by comparing two variations of the network architecture. We confirm the robustness of our model to hyper-parameters by performing sensitivity analysis. We hope our method can eventually reinforce our understanding of employing deep learning in genomic studies and shed light on research regarding mechanisms of chromatin accessibility. The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm . tingchen@tsinghua.edu.cn or ruijiang@tsinghua.edu.cn. Supplementary materials are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding

PubMed Central

Min, Xu; Zeng, Wanwen; Chen, Ning; Chen, Ting; Jiang, Rui

2017-01-01

Abstract Motivation: Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k-mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k-mer co-occurrence information with recent advances in deep learning. Results: We fill this gap by addressing the problem of chromatin accessibility prediction with a convolutional Long Short-Term Memory (LSTM) network with k-mer embedding. We first split DNA sequences into k-mers and pre-train k-mer embedding vectors based on the co-occurrence matrix of k-mers by using an unsupervised representation learning approach. We then construct a supervised deep learning architecture comprised of an embedding layer, three convolutional layers and a Bidirectional LSTM (BLSTM) layer for feature learning and classification. We demonstrate that our method gains high-quality fixed-length features from variable-length sequences and consistently outperforms baseline methods. We show that k-mer embedding can effectively enhance model performance by exploring different embedding strategies. We also prove the efficacy of both the convolution and the BLSTM layers by comparing two variations of the network architecture. We confirm the robustness of our model to hyper-parameters by performing sensitivity analysis. We hope our method can eventually reinforce our understanding of employing deep learning in genomic studies and shed light on research regarding mechanisms of chromatin accessibility. Availability and implementation: The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm. Contact: tingchen@tsinghua.edu.cn or ruijiang@tsinghua.edu.cn Supplementary information: Supplementary materials are available at Bioinformatics online. PMID:28881969

Smoothing of cost function leads to faster convergence of neural network learning

NASA Astrophysics Data System (ADS)

Xu, Li-Qun; Hall, Trevor J.

1994-03-01

One of the major problems in supervised learning of neural networks is the inevitable local minima inherent in the cost function f(W,D). This often makes classic gradient-descent-based learning algorithms that calculate the weight updates for each iteration according to (Delta) W(t) equals -(eta) (DOT)$DELwf(W,D) powerless. In this paper we describe a new strategy to solve this problem, which, adaptively, changes the learning rate and manipulates the gradient estimator simultaneously. The idea is to implicitly convert the local- minima-laden cost function f((DOT)) into a sequence of its smoothed versions {f(beta t)}Ttequals1, which, subject to the parameter (beta) t, bears less details at time t equals 1 and gradually more later on, the learning is actually performed on this sequence of functionals. The corresponding smoothed global minima obtained in this way, {Wt}Ttequals1, thus progressively approximate W-the desired global minimum. Experimental results on a nonconvex function minimization problem and a typical neural network learning task are given, analyses and discussions of some important issues are provided.

The Consolidation of Implicit Sequence Memory in Obstructive Sleep Apnea

PubMed Central

Malecek, Nick

2014-01-01

Obstructive Sleep Apnea (OSA) Syndrome is a relatively frequent sleep disorder characterized by disrupted sleep patterns. It is a well-established fact that sleep has beneficial effect on memory consolidation by enhancing neural plasticity. Implicit sequence learning is a prominent component of skill learning. However, the formation and consolidation of this fundamental learning mechanism remains poorly understood in OSA. In the present study we examined the consolidation of different aspects of implicit sequence learning in patients with OSA. We used the Alternating Serial Reaction Time task to measure general skill learning and sequence-specific learning. There were two sessions: a learning phase and a testing phase, separated by a 10-hour offline period with sleep. Our data showed differences in offline changes of general skill learning between the OSA and control group. The control group demonstrated offline improvement from evening to morning, while the OSA group did not. In contrast, we did not observe differences between the groups in offline changes in sequence-specific learning. Our findings suggest that disrupted sleep in OSA differently affects neural circuits involved in the consolidation of sequence learning. PMID:25329462

Auditory and motor imagery modulate learning in music performance

PubMed Central

Brown, Rachel M.; Palmer, Caroline

2013-01-01

Skilled performers such as athletes or musicians can improve their performance by imagining the actions or sensory outcomes associated with their skill. Performers vary widely in their auditory and motor imagery abilities, and these individual differences influence sensorimotor learning. It is unknown whether imagery abilities influence both memory encoding and retrieval. We examined how auditory and motor imagery abilities influence musicians' encoding (during Learning, as they practiced novel melodies), and retrieval (during Recall of those melodies). Pianists learned melodies by listening without performing (auditory learning) or performing without sound (motor learning); following Learning, pianists performed the melodies from memory with auditory feedback (Recall). During either Learning (Experiment 1) or Recall (Experiment 2), pianists experienced either auditory interference, motor interference, or no interference. Pitch accuracy (percentage of correct pitches produced) and temporal regularity (variability of quarter-note interonset intervals) were measured at Recall. Independent tests measured auditory and motor imagery skills. Pianists' pitch accuracy was higher following auditory learning than following motor learning and lower in motor interference conditions (Experiments 1 and 2). Both auditory and motor imagery skills improved pitch accuracy overall. Auditory imagery skills modulated pitch accuracy encoding (Experiment 1): Higher auditory imagery skill corresponded to higher pitch accuracy following auditory learning with auditory or motor interference, and following motor learning with motor or no interference. These findings suggest that auditory imagery abilities decrease vulnerability to interference and compensate for missing auditory feedback at encoding. Auditory imagery skills also influenced temporal regularity at retrieval (Experiment 2): Higher auditory imagery skill predicted greater temporal regularity during Recall in the presence of auditory interference. Motor imagery aided pitch accuracy overall when interference conditions were manipulated at encoding (Experiment 1) but not at retrieval (Experiment 2). Thus, skilled performers' imagery abilities had distinct influences on encoding and retrieval of musical sequences. PMID:23847495

Performance of amplicon-based next generation DNA sequencing for diagnostic gene mutation profiling in oncopathology.

PubMed

Sie, Daoud; Snijders, Peter J F; Meijer, Gerrit A; Doeleman, Marije W; van Moorsel, Marinda I H; van Essen, Hendrik F; Eijk, Paul P; Grünberg, Katrien; van Grieken, Nicole C T; Thunnissen, Erik; Verheul, Henk M; Smit, Egbert F; Ylstra, Bauke; Heideman, Daniëlle A M

2014-10-01

Next generation DNA sequencing (NGS) holds promise for diagnostic applications, yet implementation in routine molecular pathology practice requires performance evaluation on DNA derived from routine formalin-fixed paraffin-embedded (FFPE) tissue specimens. The current study presents a comprehensive analysis of TruSeq Amplicon Cancer Panel-based NGS using a MiSeq Personal sequencer (TSACP-MiSeq-NGS) for somatic mutation profiling. TSACP-MiSeq-NGS (testing 212 hotspot mutation amplicons of 48 genes) and a data analysis pipeline were evaluated in a retrospective learning/test set approach (n = 58/n = 45 FFPE-tumor DNA samples) against 'gold standard' high-resolution-melting (HRM)-sequencing for the genes KRAS, EGFR, BRAF and PIK3CA. Next, the performance of the validated test algorithm was assessed in an independent, prospective cohort of FFPE-tumor DNA samples (n = 75). In the learning set, a number of minimum parameter settings was defined to decide whether a FFPE-DNA sample is qualified for TSACP-MiSeq-NGS and for calling mutations. The resulting test algorithm revealed 82% (37/45) compliance to the quality criteria and 95% (35/37) concordant assay findings for KRAS, EGFR, BRAF and PIK3CA with HRM-sequencing (kappa = 0.92; 95% CI = 0.81-1.03) in the test set. Subsequent application of the validated test algorithm to the prospective cohort yielded a success rate of 84% (63/75), and a high concordance with HRM-sequencing (95% (60/63); kappa = 0.92; 95% CI = 0.84-1.01). TSACP-MiSeq-NGS detected 77 mutations in 29 additional genes. TSACP-MiSeq-NGS is suitable for diagnostic gene mutation profiling in oncopathology.

Learning temporal statistics for sensory predictions in mild cognitive impairment.

PubMed

Di Bernardi Luft, Caroline; Baker, Rosalind; Bentham, Peter; Kourtzi, Zoe

2015-08-01

Training is known to improve performance in a variety of perceptual and cognitive skills. However, there is accumulating evidence that mere exposure (i.e. without supervised training) to regularities (i.e. patterns that co-occur in the environment) facilitates our ability to learn contingencies that allow us to interpret the current scene and make predictions about future events. Recent neuroimaging studies have implicated fronto-striatal and medial temporal lobe brain regions in the learning of spatial and temporal statistics. Here, we ask whether patients with mild cognitive impairment due to Alzheimer's disease (MCI-AD) that are characterized by hippocampal dysfunction are able to learn temporal regularities and predict upcoming events. We tested the ability of MCI-AD patients and age-matched controls to predict the orientation of a test stimulus following exposure to sequences of leftwards or rightwards orientated gratings. Our results demonstrate that exposure to temporal sequences without feedback facilitates the ability to predict an upcoming stimulus in both MCI-AD patients and controls. However, our fMRI results demonstrate that MCI-AD patients recruit an alternate circuit to hippocampus to succeed in learning of predictive structures. In particular, we observed stronger learning-dependent activations for structured sequences in frontal, subcortical and cerebellar regions for patients compared to age-matched controls. Thus, our findings suggest a cortico-striatal-cerebellar network that may mediate the ability for predictive learning despite hippocampal dysfunction in MCI-AD. Copyright © 2015 Elsevier Ltd. All rights reserved.

Congruency sequence effect without feature integration and contingency learning.

PubMed

Kim, Sanga; Cho, Yang Seok

2014-06-01

The magnitude of congruency effects, such as the flanker-compatibility effects, has been found to vary as a function of the congruency of the previous trial. Some studies have suggested that this congruency sequence effect is attributable to stimulus and/or response priming, and/or contingency learning, whereas other studies have suggested that the control process triggered by conflict modulates the congruency effect. The present study examined whether sequential modulation can occur without stimulus and response repetitions and contingency learning. Participants were asked to perform two color flanker-compatibility tasks alternately in a trial-by-trial manner, with four fingers of one hand in Experiment 1 and with the index and middle fingers of two hands in Experiment 2, to avoid stimulus and response repetitions and contingency learning. A significant congruency sequence effect was obtained between the congruencies of the two tasks in Experiment 1 but not in Experiment 2. These results provide evidence for the idea that the sequential modulation is, at least in part, an outcome of the top-down control process triggered by conflict, which is specific to response mode. Copyright © 2014 Elsevier B.V. All rights reserved.

IDEPI: rapid prediction of HIV-1 antibody epitopes and other phenotypic features from sequence data using a flexible machine learning platform.

PubMed

Hepler, N Lance; Scheffler, Konrad; Weaver, Steven; Murrell, Ben; Richman, Douglas D; Burton, Dennis R; Poignard, Pascal; Smith, Davey M; Kosakovsky Pond, Sergei L

2014-09-01

Since its identification in 1983, HIV-1 has been the focus of a research effort unprecedented in scope and difficulty, whose ultimate goals--a cure and a vaccine--remain elusive. One of the fundamental challenges in accomplishing these goals is the tremendous genetic variability of the virus, with some genes differing at as many as 40% of nucleotide positions among circulating strains. Because of this, the genetic bases of many viral phenotypes, most notably the susceptibility to neutralization by a particular antibody, are difficult to identify computationally. Drawing upon open-source general-purpose machine learning algorithms and libraries, we have developed a software package IDEPI (IDentify EPItopes) for learning genotype-to-phenotype predictive models from sequences with known phenotypes. IDEPI can apply learned models to classify sequences of unknown phenotypes, and also identify specific sequence features which contribute to a particular phenotype. We demonstrate that IDEPI achieves performance similar to or better than that of previously published approaches on four well-studied problems: finding the epitopes of broadly neutralizing antibodies (bNab), determining coreceptor tropism of the virus, identifying compartment-specific genetic signatures of the virus, and deducing drug-resistance associated mutations. The cross-platform Python source code (released under the GPL 3.0 license), documentation, issue tracking, and a pre-configured virtual machine for IDEPI can be found at https://github.com/veg/idepi.

Implicit Sequence Learning in Dyslexia: A Within-Sequence Comparison of First- and Higher-Order Information

ERIC Educational Resources Information Center

Du, Wenchong; Kelly, Steve W.

2013-01-01

The present study examines implicit sequence learning in adult dyslexics with a focus on comparing sequence transitions with different statistical complexities. Learning of a 12-item deterministic sequence was assessed in 12 dyslexic and 12 non-dyslexic university students. Both groups showed equivalent standard reaction time increments when the…

Motor Sequence Learning-Induced Neural Efficiency in Functional Brain Connectivity

PubMed Central

Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M

2016-01-01

Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. PMID:27845228

A single session of prefrontal cortex transcranial direct current stimulation does not modulate implicit task sequence learning and consolidation.

PubMed

Savic, Branislav; Müri, René; Meier, Beat

Transcranial direct current stimulation (tDCS) is assumed to affect cortical excitability and dependent on the specific stimulation conditions either to increase or decrease learning. The purpose of this study was to modulate implicit task sequence learning with tDCS. As cortico-striatal loops are critically involved in implicit task sequence learning, tDCS was applied above the dorsolateral prefrontal cortex (DLPFC). In Experiment 1, anodal, cathodal, or sham tDCS was applied before the start of the sequence learning task. In Experiment 2, stimulation was applied during the sequence learning task. Consolidation of learning was assessed after 24 h. The results of both experiments showed that implicit task sequence learning occurred consistently but it was not modulated by different tDCS conditions. Similarly, consolidation measured after a 24 h-interval including sleep was also not affected by stimulation. These results indicate that a single session of DLPFC tDCS is not sufficient to modulate implicit task sequence learning. This study adds to the accumulating evidence that tDCS may not be as effective as originally thought. Copyright © 2017 Elsevier Inc. All rights reserved.

Genome sequencing of Ewing sarcoma patients reveals genetic predisposition | Center for Cancer Research

Cancer.gov

The largest and most comprehensive genomic analysis of individuals with Ewing sarcoma performed to date reveals that some patients are genetically predisposed to developing the cancer.  Learn more...

Changes in Striatal Dopamine Release Associated with Human Motor-Skill Acquisition

PubMed Central

Kawashima, Shoji; Ueki, Yoshino; Kato, Takashi; Matsukawa, Noriyuki; Mima, Tatsuya; Hallett, Mark; Ito, Kengo; Ojika, Kosei

2012-01-01

The acquisition of new motor skills is essential throughout daily life and involves the processes of learning new motor sequence and encoding elementary aspects of new movement. Although previous animal studies have suggested a functional importance for striatal dopamine release in the learning of new motor sequence, its role in encoding elementary aspects of new movement has not yet been investigated. To elucidate this, we investigated changes in striatal dopamine levels during initial skill-training (Day 1) compared with acquired conditions (Day 2) using 11C-raclopride positron-emission tomography. Ten volunteers learned to perform brisk contractions using their non-dominant left thumbs with the aid of visual feedback. On Day 1, the mean acceleration of each session was improved through repeated training sessions until performance neared asymptotic levels, while improved motor performance was retained from the beginning on Day 2. The 11C-raclopride binding potential (BP) in the right putamen was reduced during initial skill-training compared with under acquired conditions. Moreover, voxel-wise analysis revealed that 11C-raclopride BP was particularly reduced in the right antero-dorsal to the lateral part of the putamen. Based on findings from previous fMRI studies that show a gradual shift of activation within the striatum during the initial processing of motor learning, striatal dopamine may play a role in the dynamic cortico-striatal activation during encoding of new motor memory in skill acquisition. PMID:22355391

Generalized lessons about sequence learning from the study of the serial reaction time task

PubMed Central

Schwarb, Hillary; Schumacher, Eric H.

2012-01-01

Over the last 20 years researchers have used the serial reaction time (SRT) task to investigate the nature of spatial sequence learning. They have used the task to identify the locus of spatial sequence learning, identify situations that enhance and those that impair learning, and identify the important cognitive processes that facilitate this type of learning. Although controversies remain, the SRT task has been integral in enhancing our understanding of implicit sequence learning. It is important, however, to ask what, if anything, the discoveries made using the SRT task tell us about implicit learning more generally. This review analyzes the state of the current spatial SRT sequence learning literature highlighting the stimulus-response rule hypothesis of sequence learning which we believe provides a unifying account of discrepant SRT data. It also challenges researchers to use the vast body of knowledge acquired with the SRT task to understand other implicit learning literatures too often ignored in the context of this particular task. This broad perspective will make it possible to identify congruences among data acquired using various different tasks that will allow us to generalize about the nature of implicit learning. PMID:22723815

The comparison between motor imagery and verbal rehearsal on the learning of sequential movements

PubMed Central

Saimpont, Arnaud; Lafleur, Martin F.; Malouin, Francine; Richards, Carol L.; Doyon, Julien; Jackson, hb Philip L.

2013-01-01

Mental practice refers to the cognitive rehearsal of a physical activity. It is widely used by athletes to enhance their performance and its efficiency to help train motor function in people with physical disabilities is now recognized. Mental practice is generally based on motor imagery (MI), i.e., the conscious simulation of a movement without its actual execution. It may also be based on verbal rehearsal (VR), i.e., the silent rehearsal of the labels associated with an action. In this study, the effect of MI training or VR on the learning and retention of a foot-sequence task was investigated. Thirty right-footed subjects, aged between 22 and 37 years old (mean: 27.4 ± 4.1 years) and randomly assigned to one of three groups, practiced a serial reaction time task involving a sequence of three dorsiflexions and three plantar flexions with the left foot. One group (n = 10) mentally practiced the sequence with MI for 5 weeks, another group (n = 10) mentally practiced the sequence with VR of the foot positions for the same duration, and a control group (n = 10) did not practice the sequence mentally. The time to perform the practiced sequence as well as an unpracticed sequence was recorded before training, immediately after training and 6 months after training (retention). The main results showed that the speed improvement after training was significantly greater in the MI group compared to the control group and tended to be greater in the VR group compared to the control group. The improvement in performance did not differ in the MI and VR groups. At retention, however, no difference in response times was found among the three groups, indicating that the effect of mental practice did not last over a long period without training. Interestingly, this pattern of results was similar for the practiced and non-practiced sequence. Overall, these results suggest that both MI training and VR help to improve motor performance and that mental practice may induce non-specific effects. PMID:24302905

Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

PubMed

Kim, Hui Kwon; Min, Seonwoo; Song, Myungjae; Jung, Soobin; Choi, Jae Woo; Kim, Younggwang; Lee, Sangeun; Yoon, Sungroh; Kim, Hyongbum Henry

2018-03-01

We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

Predicting ICU mortality: a comparison of stationary and nonstationary temporal models.

PubMed Central

Kayaalp, M.; Cooper, G. F.; Clermont, G.

2000-01-01

OBJECTIVE: This study evaluates the effectiveness of the stationarity assumption in predicting the mortality of intensive care unit (ICU) patients at the ICU discharge. DESIGN: This is a comparative study. A stationary temporal Bayesian network learned from data was compared to a set of (33) nonstationary temporal Bayesian networks learned from data. A process observed as a sequence of events is stationary if its stochastic properties stay the same when the sequence is shifted in a positive or negative direction by a constant time parameter. The temporal Bayesian networks forecast mortalities of patients, where each patient has one record per day. The predictive performance of the stationary model is compared with nonstationary models using the area under the receiver operating characteristics (ROC) curves. RESULTS: The stationary model usually performed best. However, one nonstationary model using large data sets performed significantly better than the stationary model. CONCLUSION: Results suggest that using a combination of stationary and nonstationary models may predict better than using either alone. PMID:11079917

Taking the brakes off the learning curve.

PubMed

Gheysen, Freja; Lasne, Gabriel; Pélégrini-Issac, Mélanie; Albouy, Genevieve; Meunier, Sabine; Benali, Habib; Doyon, Julien; Popa, Traian

2017-03-01

Motor learning is characterized by patterns of cerebello-striato-cortical activations shifting in time, yet the early dynamic and function of these activations remains unclear. Five groups of subjects underwent either continuous or intermittent theta-burst stimulation of one cerebellar hemisphere, or no stimulation just before learning a new motor sequence during fMRI scanning. We identified three phases during initial learning: one rapid, one slow, and one quasi-asymptotic performance phase. These phases were not changed by left cerebellar stimulation. Right cerebellar inhibition, however, accelerated learning and enhanced brain activation in critical motor learning-related areas during the first phase, continuing with reduced brain activation but high-performance in late phase. Right cerebellar excitation did not affect the early learning process, but slowed learning significantly in late phase, along with increased brain activation. We conclude that the right cerebellum is a key factor coordinating other neuronal loops in the early acquisition of an explicit motor sequential skill. Hum Brain Mapp 38:1676-1691, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Differentiating Visual from Response Sequencing during Long-term Skill Learning.

PubMed

Lynch, Brighid; Beukema, Patrick; Verstynen, Timothy

2017-01-01

The dual-system model of sequence learning posits that during early learning there is an advantage for encoding sequences in sensory frames; however, it remains unclear whether this advantage extends to long-term consolidation. Using the serial RT task, we set out to distinguish the dynamics of learning sequential orders of visual cues from learning sequential responses. On each day, most participants learned a new mapping between a set of symbolic cues and responses made with one of four fingers, after which they were exposed to trial blocks of either randomly ordered cues or deterministic ordered cues (12-item sequence). Participants were randomly assigned to one of four groups (n = 15 per group): Visual sequences (same sequence of visual cues across training days), Response sequences (same order of key presses across training days), Combined (same serial order of cues and responses on all training days), and a Control group (a novel sequence each training day). Across 5 days of training, sequence-specific measures of response speed and accuracy improved faster in the Visual group than any of the other three groups, despite no group differences in explicit awareness of the sequence. The two groups that were exposed to the same visual sequence across days showed a marginal improvement in response binding that was not found in the other groups. These results indicate that there is an advantage, in terms of rate of consolidation across multiple days of training, for learning sequences of actions in a sensory representational space, rather than as motoric representations.

Academic performance in a pharmacotherapeutics course sequence taught synchronously on two campuses using distance education technology.

PubMed

Steinberg, Michael; Morin, Anna K

2011-10-10

To compare the academic performance of campus-based students in a pharmacotherapeutics course with that of students at a distant campus taught via synchronous teleconferencing. Examination scores and final course grades for campus-based and distant students completing the case-based pharmacotherapeutics course sequence over a 5-year period were collected and analyzed. The mean examination scores and final course grades were not significantly different between students on the 2 campuses. The use of synchronous distance education technology to teach students does not affect students' academic performance when used in an active-learning, case-based pharmacotherapeutics course.

Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

PubMed

Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

2016-01-01

Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

Drinking from the Fire Hose: Why the Flight Management System Can Be Hard to Train and Difficult to Use

NASA Technical Reports Server (NTRS)

Sherry, Lance; Feary, Michael; Polson, Peter; Fennell, Karl

2003-01-01

The Flight Management Computer (FMC) and its interface, the Multi-function Control and Display Unit (MCDU) have been identified by researchers and airlines as difficult to train and use. Specifically, airline pilots have described the "drinking from the fire-hose" effect during training. Previous research has identified memorized action sequences as a major factor in a user s ability to learn and operate complex devices. This paper discusses the use of a method to examine the quantity of memorized action sequences required to perform a sample of 102 tasks, using features of the Boeing 777 Flight Management Computer Interface. The analysis identified a large number of memorized action sequences that must be learned during training and then recalled during line operations. Seventy-five percent of the tasks examined require recall of at least one memorized action sequence. Forty-five percent of the tasks require recall of a memorized action sequence and occur infrequently. The large number of memorized action sequences may provide an explanation for the difficulties in training and usage of the automation. Based on these findings, implications for training and the design of new user-interfaces are discussed.

An Exploration of Rhythmic Grouping of Speech Sequences by French- and German-Learning Infants

PubMed Central

Abboub, Nawal; Boll-Avetisyan, Natalie; Bhatara, Anjali; Höhle, Barbara; Nazzi, Thierry

2016-01-01

Rhythm in music and speech can be characterized by a constellation of several acoustic cues. Individually, these cues have different effects on rhythmic perception: sequences of sounds alternating in duration are perceived as short-long pairs (weak-strong/iambic pattern), whereas sequences of sounds alternating in intensity or pitch are perceived as loud-soft, or high-low pairs (strong-weak/trochaic pattern). This perceptual bias—called the Iambic-Trochaic Law (ITL)–has been claimed to be an universal property of the auditory system applying in both the music and the language domains. Recent studies have shown that language experience can modulate the effects of the ITL on rhythmic perception of both speech and non-speech sequences in adults, and of non-speech sequences in 7.5-month-old infants. The goal of the present study was to explore whether language experience also modulates infants’ grouping of speech. To do so, we presented sequences of syllables to monolingual French- and German-learning 7.5-month-olds. Using the Headturn Preference Procedure (HPP), we examined whether they were able to perceive a rhythmic structure in sequences of syllables that alternated in duration, pitch, or intensity. Our findings show that both French- and German-learning infants perceived a rhythmic structure when it was cued by duration or pitch but not intensity. Our findings also show differences in how these infants use duration and pitch cues to group syllable sequences, suggesting that pitch cues were the easier ones to use. Moreover, performance did not differ across languages, failing to reveal early language effects on rhythmic perception. These results contribute to our understanding of the origin of rhythmic perception and perceptual mechanisms shared across music and speech, which may bootstrap language acquisition. PMID:27378887

Learning effect of computerized cognitive tests in older adults

PubMed Central

de Oliveira, Rafaela Sanches; Trezza, Beatriz Maria; Busse, Alexandre Leopold; Jacob-Filho, Wilson

2014-01-01

ABSTRACT Objective: To evaluate the learning effect of computerized cognitive testing in the elderly. Methods: Cross-sectional study with 20 elderly, 10 women and 10 men, with average age of 77.5 (±4.28) years. The volunteers performed two series of computerized cognitive tests in sequence and their results were compared. The applied tests were: Trail Making A and B, Spatial Recognition, Go/No Go, Memory Span, Pattern Recognition Memory and Reverse Span. Results: Based on the comparison of the results, learning effects were observed only in the Trail Making A test (p=0.019). Other tests performed presented no significant performance improvements. There was no correlation between learning effect and age (p=0.337) and education (p=0.362), as well as differences between genders (p=0.465). Conclusion: The computerized cognitive tests repeated immediately afterwards, for elderly, revealed no change in their performance, with the exception of the Trail Making test, demonstrating high clinical applicability, even in short intervals. PMID:25003917

Supervised DNA Barcodes species classification: analysis, comparisons and results

PubMed Central

2014-01-01

Background Specific fragments, coming from short portions of DNA (e.g., mitochondrial, nuclear, and plastid sequences), have been defined as DNA Barcode and can be used as markers for organisms of the main life kingdoms. Species classification with DNA Barcode sequences has been proven effective on different organisms. Indeed, specific gene regions have been identified as Barcode: COI in animals, rbcL and matK in plants, and ITS in fungi. The classification problem assigns an unknown specimen to a known species by analyzing its Barcode. This task has to be supported with reliable methods and algorithms. Methods In this work the efficacy of supervised machine learning methods to classify species with DNA Barcode sequences is shown. The Weka software suite, which includes a collection of supervised classification methods, is adopted to address the task of DNA Barcode analysis. Classifier families are tested on synthetic and empirical datasets belonging to the animal, fungus, and plant kingdoms. In particular, the function-based method Support Vector Machines (SVM), the rule-based RIPPER, the decision tree C4.5, and the Naïve Bayes method are considered. Additionally, the classification results are compared with respect to ad-hoc and well-established DNA Barcode classification methods. Results A software that converts the DNA Barcode FASTA sequences to the Weka format is released, to adapt different input formats and to allow the execution of the classification procedure. The analysis of results on synthetic and real datasets shows that SVM and Naïve Bayes outperform on average the other considered classifiers, although they do not provide a human interpretable classification model. Rule-based methods have slightly inferior classification performances, but deliver the species specific positions and nucleotide assignments. On synthetic data the supervised machine learning methods obtain superior classification performances with respect to the traditional DNA Barcode classification methods. On empirical data their classification performances are at a comparable level to the other methods. Conclusions The classification analysis shows that supervised machine learning methods are promising candidates for handling with success the DNA Barcoding species classification problem, obtaining excellent performances. To conclude, a powerful tool to perform species identification is now available to the DNA Barcoding community. PMID:24721333

Robust sensorimotor representation to physical interaction changes in humanoid motion learning.

PubMed

Shimizu, Toshihiko; Saegusa, Ryo; Ikemoto, Shuhei; Ishiguro, Hiroshi; Metta, Giorgio

2015-05-01

This paper proposes a learning from demonstration system based on a motion feature, called phase transfer sequence. The system aims to synthesize the knowledge on humanoid whole body motions learned during teacher-supported interactions, and apply this knowledge during different physical interactions between a robot and its surroundings. The phase transfer sequence represents the temporal order of the changing points in multiple time sequences. It encodes the dynamical aspects of the sequences so as to absorb the gaps in timing and amplitude derived from interaction changes. The phase transfer sequence was evaluated in reinforcement learning of sitting-up and walking motions conducted by a real humanoid robot and compatible simulator. In both tasks, the robotic motions were less dependent on physical interactions when learned by the proposed feature than by conventional similarity measurements. Phase transfer sequence also enhanced the convergence speed of motion learning. Our proposed feature is original primarily because it absorbs the gaps caused by changes of the originally acquired physical interactions, thereby enhancing the learning speed in subsequent interactions.

Motor sequence learning-induced neural efficiency in functional brain connectivity.

PubMed

Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M

2017-02-15

Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. Copyright © 2016 Elsevier B.V. All rights reserved.

Learning procedures from interactive natural language instructions

NASA Technical Reports Server (NTRS)

Huffman, Scott B.; Laird, John E.

1994-01-01

Despite its ubiquity in human learning, very little work has been done in artificial intelligence on agents that learn from interactive natural language instructions. In this paper, the problem of learning procedures from interactive, situated instruction is examined in which the student is attempting to perform tasks within the instructional domain, and asks for instruction when it is needed. Presented is Instructo-Soar, a system that behaves and learns in response to interactive natural language instructions. Instructo-Soar learns completely new procedures from sequences of instruction, and also learns how to extend its knowledge of previously known procedures to new situations. These learning tasks require both inductive and analytic learning. Instructo-Soar exhibits a multiple execution learning process in which initial learning has a rote, episodic flavor, and later executions allow the initially learned knowledge to be generalized properly.

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.

Rank-order-selective neurons form a temporal basis set for the generation of motor sequences.

PubMed

Salinas, Emilio

2009-04-08

Many behaviors are composed of a series of elementary motor actions that must occur in a specific order, but the neuronal mechanisms by which such motor sequences are generated are poorly understood. In particular, if a sequence consists of a few motor actions, a primate can learn to replicate it from memory after practicing it for just a few trials. How do the motor and premotor areas of the brain assemble motor sequences so fast? The network model presented here reveals part of the solution to this problem. The model is based on experiments showing that, during the performance of motor sequences, some cortical neurons are always activated at specific times, regardless of which motor action is being executed. In the model, a population of such rank-order-selective (ROS) cells drives a layer of downstream motor neurons so that these generate specific movements at different times in different sequences. A key ingredient of the model is that the amplitude of the ROS responses must be modulated by sequence identity. Because of this modulation, which is consistent with experimental reports, the network is able not only to produce multiple sequences accurately but also to learn a new sequence with minimal changes in connectivity. The ROS neurons modulated by sequence identity thus serve as a basis set for constructing arbitrary sequences of motor responses downstream. The underlying mechanism is analogous to the mechanism described in parietal areas for generating coordinate transformations in the spatial domain.

RANK-ORDER-SELECTIVE NEURONS FORM A TEMPORAL BASIS SET FOR THE GENERATION OF MOTOR SEQUENCES

PubMed Central

Salinas, Emilio

2009-01-01

Many behaviors are composed of a series of elementary motor actions that must occur in a specific order, but the neuronal mechanisms by which such motor sequences are generated are poorly understood. In particular, if a sequence consists of a few motor actions, a primate can learn to replicate it from memory after practicing it for just a few trials. How do the motor and premotor areas of the brain assemble motor sequences so fast? The network model presented here reveals part of the solution to this problem. The model is based on experiments showing that, during the performance of motor sequences, some cortical neurons are always activated at specific times, regardless of which motor action is being executed. In the model, a population of such rank-order-selective (ROS) cells drives a layer of downstream motor neurons so that these generate specific movements at different times in different sequences. A key ingredient of the model is that the amplitude of the ROS responses must be modulated by sequence identity. Because of this modulation, which is consistent with experimental reports, the network is able not only to produce multiple sequences accurately but also to learn a new sequence with minimal changes in connectivity. The ROS neurons modulated by sequence identity thus serve as a basis set for constructing arbitrary sequences of motor responses downstream. The underlying mechanism is analogous to the mechanism described in parietal areas for generating coordinate transformations in the spatial domain. PMID:19357265

Schizophrenia patients demonstrate a dissociation on declarative and non-declarative memory tests.

PubMed

Perry, W; Light, G A; Davis, H; Braff, D L

2000-12-15

Declarative memory refers to the recall and recognition of factual information. In contrast, non-declarative memory entails a facilitation of memory based on prior exposure and is typically assessed with priming and perceptual-motor sequencing tasks. In this study, schizophrenia patients were compared to normal comparison subjects on two computerized memory tasks: the Word-stem Priming Test (n=30) and the Pattern Sequence Learning Test (n=20). Word-stem Priming includes recall, recognition (declarative) and priming (non-declarative) components of memory. The schizophrenia patients demonstrated an impaired performance on recall of words with relative improvement during the recognition portion of the test. Furthermore, they performed normally on the priming portion of the test. Thus, on tests of declarative memory, the patients had retrieval deficits with intact performance on the non-declarative memory component. The Pattern Sequence Learning Test utilizes a serial reaction time paradigm to assess non-declarative memory. The schizophrenia patients' serial reaction time was significantly slower than that of comparison subjects. However, the patients' rate of acquisition was not different from the normal comparison group. The data suggest that patients with schizophrenia process more slowly than normal, but have an intact non-declarative memory. The schizophrenia patients' dissociation on declarative vs. non-declarative memory tests is discussed in terms of possible underlying structural impairment.

Discrete Circuits Support Generalized versus Context-Specific Vocal Learning in the Songbird.

PubMed

Tian, Lucas Y; Brainard, Michael S

2017-12-06

Motor skills depend on the reuse of individual gestures in multiple sequential contexts (e.g., a single phoneme in different words). Yet optimal performance requires that a given gesture be modified appropriately depending on the sequence in which it occurs. To investigate the neural architecture underlying such context-dependent modifications, we studied Bengalese finch song, which, like speech, consists of variable sequences of "syllables." We found that when birds are instructed to modify a syllable in one sequential context, learning generalizes across contexts; however, if unique instruction is provided in different contexts, learning is specific for each context. Using localized inactivation of a cortical-basal ganglia circuit specialized for song, we show that this balance between generalization and specificity reflects a hierarchical organization of neural substrates. Primary motor circuitry encodes a core syllable representation that contributes to generalization, while top-down input from cortical-basal ganglia circuitry biases this representation to enable context-specific learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Tracking-by-detection of surgical instruments in minimally invasive surgery via the convolutional neural network deep learning-based method.

PubMed

Zhao, Zijian; Voros, Sandrine; Weng, Ying; Chang, Faliang; Li, Ruijian

2017-12-01

Worldwide propagation of minimally invasive surgeries (MIS) is hindered by their drawback of indirect observation and manipulation, while monitoring of surgical instruments moving in the operated body required by surgeons is a challenging problem. Tracking of surgical instruments by vision-based methods is quite lucrative, due to its flexible implementation via software-based control with no need to modify instruments or surgical workflow. A MIS instrument is conventionally split into a shaft and end-effector portions, while a 2D/3D tracking-by-detection framework is proposed, which performs the shaft tracking followed by the end-effector one. The former portion is described by line features via the RANSAC scheme, while the latter is depicted by special image features based on deep learning through a well-trained convolutional neural network. The method verification in 2D and 3D formulation is performed through the experiments on ex-vivo video sequences, while qualitative validation on in-vivo video sequences is obtained. The proposed method provides robust and accurate tracking, which is confirmed by the experimental results: its 3D performance in ex-vivo video sequences exceeds those of the available state-of -the-art methods. Moreover, the experiments on in-vivo sequences demonstrate that the proposed method can tackle the difficult condition of tracking with unknown camera parameters. Further refinements of the method will refer to the occlusion and multi-instrumental MIS applications.

Hybrid generative-discriminative human action recognition by combining spatiotemporal words with supervised topic models

NASA Astrophysics Data System (ADS)

Sun, Hao; Wang, Cheng; Wang, Boliang

2011-02-01

We present a hybrid generative-discriminative learning method for human action recognition from video sequences. Our model combines a bag-of-words component with supervised latent topic models. A video sequence is represented as a collection of spatiotemporal words by extracting space-time interest points and describing these points using both shape and motion cues. The supervised latent Dirichlet allocation (sLDA) topic model, which employs discriminative learning using labeled data under a generative framework, is introduced to discover the latent topic structure that is most relevant to action categorization. The proposed algorithm retains most of the desirable properties of generative learning while increasing the classification performance though a discriminative setting. It has also been extended to exploit both labeled data and unlabeled data to learn human actions under a unified framework. We test our algorithm on three challenging data sets: the KTH human motion data set, the Weizmann human action data set, and a ballet data set. Our results are either comparable to or significantly better than previously published results on these data sets and reflect the promise of hybrid generative-discriminative learning approaches.

A dissociation between engagement and learning: Enthusiastic instructions fail to reliably improve performance on a memory task.

PubMed

Motz, Benjamin A; de Leeuw, Joshua R; Carvalho, Paulo F; Liang, Kaley L; Goldstone, Robert L

2017-01-01

Despite widespread assertions that enthusiasm is an important quality of effective teaching, empirical research on the effect of enthusiasm on learning and memory is mixed and largely inconclusive. To help resolve these inconsistencies, we conducted a carefully-controlled laboratory experiment, investigating whether enthusiastic instructions for a memory task would improve recall accuracy. Scripted videos, either enthusiastic or neutral, were used to manipulate the delivery of task instructions. We also manipulated the sequence of learning items, replicating the spacing effect, a known cognitive technique for memory improvement. Although spaced study reliably improved test performance, we found no reliable effect of enthusiasm on memory performance across two experiments. We did, however, find that enthusiastic instructions caused participants to respond to more item prompts, leaving fewer test questions blank, an outcome typically associated with increased task motivation. We find no support for the popular claim that enthusiastic instruction will improve learning, although it may still improve engagement. This dissociation between motivation and learning is discussed, as well as its implications for education and future research on student learning.

A dissociation between engagement and learning: Enthusiastic instructions fail to reliably improve performance on a memory task

PubMed Central

de Leeuw, Joshua R.; Carvalho, Paulo F.; Liang, Kaley L.; Goldstone, Robert L.

2017-01-01

Despite widespread assertions that enthusiasm is an important quality of effective teaching, empirical research on the effect of enthusiasm on learning and memory is mixed and largely inconclusive. To help resolve these inconsistencies, we conducted a carefully-controlled laboratory experiment, investigating whether enthusiastic instructions for a memory task would improve recall accuracy. Scripted videos, either enthusiastic or neutral, were used to manipulate the delivery of task instructions. We also manipulated the sequence of learning items, replicating the spacing effect, a known cognitive technique for memory improvement. Although spaced study reliably improved test performance, we found no reliable effect of enthusiasm on memory performance across two experiments. We did, however, find that enthusiastic instructions caused participants to respond to more item prompts, leaving fewer test questions blank, an outcome typically associated with increased task motivation. We find no support for the popular claim that enthusiastic instruction will improve learning, although it may still improve engagement. This dissociation between motivation and learning is discussed, as well as its implications for education and future research on student learning. PMID:28732087

ProtDec-LTR2.0: an improved method for protein remote homology detection by combining pseudo protein and supervised Learning to Rank.

PubMed

Chen, Junjie; Guo, Mingyue; Li, Shumin; Liu, Bin

2017-11-01

As one of the most important tasks in protein sequence analysis, protein remote homology detection is critical for both basic research and practical applications. Here, we present an effective web server for protein remote homology detection called ProtDec-LTR2.0 by combining ProtDec-Learning to Rank (LTR) and pseudo protein representation. Experimental results showed that the detection performance is obviously improved. The web server provides a user-friendly interface to explore the sequence and structure information of candidate proteins and find their conserved domains by launching a multiple sequence alignment tool. The web server is free and open to all users with no login requirement at http://bioinformatics.hitsz.edu.cn/ProtDec-LTR2.0/. bliu@hit.edu.cn. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Evaluating and Redesigning Teaching Learning Sequences at the Introductory Physics Level

ERIC Educational Resources Information Center

Guisasola, Jenaro; Zuza, Kristina; Ametller, Jaume; Gutierrez-Berraondo, José

2017-01-01

In this paper we put forward a proposal for the design and evaluation of teaching and learning sequences in upper secondary school and university. We will connect our proposal with relevant contributions on the design of teaching sequences, ground it on the design-based research methodology, and discuss how teaching and learning sequences designed…

Incidental Sequence Learning across the Lifespan

ERIC Educational Resources Information Center

Weiermann, Brigitte; Meier, Beat

2012-01-01

The purpose of the present study was to investigate incidental sequence learning across the lifespan. We tested 50 children (aged 7-16), 50 young adults (aged 20-30), and 50 older adults (aged >65) with a sequence learning paradigm that involved both a task and a response sequence. After several blocks of practice, all age groups slowed down…

Time-Extended Policies in Mult-Agent Reinforcement Learning

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian K.

2004-01-01

Reinforcement learning methods perform well in many domains where a single agent needs to take a sequence of actions to perform a task. These methods use sequences of single-time-step rewards to create a policy that tries to maximize a time-extended utility, which is a (possibly discounted) sum of these rewards. In this paper we build on our previous work showing how these methods can be extended to a multi-agent environment where each agent creates its own policy that works towards maximizing a time-extended global utility over all agents actions. We show improved methods for creating time-extended utilities for the agents that are both "aligned" with the global utility and "learnable." We then show how to crate single-time-step rewards while avoiding the pi fall of having rewards aligned with the global reward leading to utilities not aligned with the global utility. Finally, we apply these reward functions to the multi-agent Gridworld problem. We explicitly quantify a utility's learnability and alignment, and show that reinforcement learning agents using the prescribed reward functions successfully tradeoff learnability and alignment. As a result they outperform both global (e.g., team games ) and local (e.g., "perfectly learnable" ) reinforcement learning solutions by as much as an order of magnitude.

Learning of Chunking Sequences in Cognition and Behavior

PubMed Central

Rabinovich, Mikhail

2015-01-01

We often learn and recall long sequences in smaller segments, such as a phone number 858 534 22 30 memorized as four segments. Behavioral experiments suggest that humans and some animals employ this strategy of breaking down cognitive or behavioral sequences into chunks in a wide variety of tasks, but the dynamical principles of how this is achieved remains unknown. Here, we study the temporal dynamics of chunking for learning cognitive sequences in a chunking representation using a dynamical model of competing modes arranged to evoke hierarchical Winnerless Competition (WLC) dynamics. Sequential memory is represented as trajectories along a chain of metastable fixed points at each level of the hierarchy, and bistable Hebbian dynamics enables the learning of such trajectories in an unsupervised fashion. Using computer simulations, we demonstrate the learning of a chunking representation of sequences and their robust recall. During learning, the dynamics associates a set of modes to each information-carrying item in the sequence and encodes their relative order. During recall, hierarchical WLC guarantees the robustness of the sequence order when the sequence is not too long. The resulting patterns of activities share several features observed in behavioral experiments, such as the pauses between boundaries of chunks, their size and their duration. Failures in learning chunking sequences provide new insights into the dynamical causes of neurological disorders such as Parkinson’s disease and Schizophrenia. PMID:26584306

On the specificity of sequential congruency effects in implicit learning of motor and perceptual sequences.

PubMed

D'Angelo, Maria C; Jiménez, Luis; Milliken, Bruce; Lupiáñez, Juan

2013-01-01

Individuals experience less interference from conflicting information following events that contain conflicting information. Recently, Jiménez, Lupiáñez, and Vaquero (2009) demonstrated that such adaptations to conflict occur even when the source of conflict arises from implicit knowledge of sequences. There is accumulating evidence that momentary changes in adaptations made in response to conflicting information are conflict-type specific (e.g., Funes, Lupiáñez, & Humphreys, 2010a), suggesting that there are multiple modes of control. The current study examined whether conflict-specific sequential congruency effects occur when the 2 sources of conflict are implicitly learned. Participants implicitly learned a motor sequence while simultaneously learning a perceptual sequence. In a first experiment, after learning the 2 orthogonal sequences, participants expressed knowledge of the 2 sequences independently of each other in a transfer phase. In Experiments 2 and 3, within each sequence, the presence of a single control trial disrupted the expression of this specific type of learning on the following trial. There was no evidence of cross-conflict modulations in the expression of sequence learning. The results suggest that the mechanisms involved in transient shifts in conflict-specific control, as reflected in sequential congruency effects, are also engaged when the source of conflict is implicit. (c) 2013 APA, all rights reserved.

Dissociation between the Procedural Learning of Letter Names and Motor Sequences in Developmental Dyslexia

ERIC Educational Resources Information Center

Gabay, Yafit; Schiff, Rachel; Vakil, Eli

2012-01-01

Motor sequence learning has been studied extensively in Developmental dyslexia (DD). The purpose of the present research was to examine procedural learning of letter names and motor sequences in individuals with DD and control groups. Both groups completed the Serial Search Task which enabled the assessment of learning of letter names and motor…

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.

Acquisition of a socially learned tool use sequence in chimpanzees: Implications for cumulative culture

PubMed Central

Vale, Gillian L.; Davis, Sarah J.; Lambeth, Susan P.; Schapiro, Steven J.; Whiten, Andrew

2017-01-01

Cumulative culture underpins humanity’s enormous success as a species. Claims that other animals are incapable of cultural ratcheting are prevalent, but are founded on just a handful of empirical studies. Whether cumulative culture is unique to humans thus remains a controversial and understudied question that has far-reaching implications for our understanding of the evolution of this phenomenon. We investigated whether one of human’s two closest living primate relatives, chimpanzees, are capable of a degree of cultural ratcheting by exposing captive populations to a novel juice extraction task. We found that groups (N = 3) seeded with a model trained to perform a tool modification that built upon simpler, unmodified tool use developed the seeded tool method that allowed greater juice returns than achieved by groups not exposed to a trained model (non-seeded controls; N = 3). One non-seeded group also discovered the behavioral sequence, either by coupling asocial and social learning or by repeated invention. This behavioral sequence was found to be beyond what an additional control sample of chimpanzees (N = 1 group) could discover for themselves without a competent model and lacking experience with simpler, unmodified tool behaviors. Five chimpanzees tested individually with no social information, but with experience of simple unmodified tool use, invented part, but not all, of the behavioral sequence. Our findings indicate that (i) social learning facilitated the propagation of the model-demonstrated tool modification technique, (ii) experience with simple tool behaviors may facilitate individual discovery of more complex tool manipulations, and (iii) a subset of individuals were capable of learning relatively complex behaviors either by learning asocially and socially or by repeated invention over time. That chimpanzees learn increasingly complex behaviors through social and asocial learning suggests that humans’ extraordinary ability to do so was built on such prior foundations. PMID:29333058

Synchronized tapping facilitates learning sound sequences as indexed by the P300.

PubMed

Kamiyama, Keiko S; Okanoya, Kazuo

2014-01-01

The purpose of the present study was to determine whether and how single finger tapping in synchrony with sound sequences contributed to the auditory processing of them. The participants learned two unfamiliar sound sequences via different methods. In the tapping condition, they learned an auditory sequence while they tapped in synchrony with each sound onset. In the no tapping condition, they learned another sequence while they kept pressing a key until the sequence ended. After these learning sessions, we presented the two melodies again and recorded event-related potentials (ERPs). During the ERP recordings, 10% of the tones within each melody deviated from the original tones. An analysis of the grand average ERPs showed that deviant stimuli elicited a significant P300 in the tapping but not in the no-tapping condition. In addition, the significance of the P300 effect in the tapping condition increased as the participants showed highly synchronized tapping behavior during the learning sessions. These results indicated that single finger tapping promoted the conscious detection and evaluation of deviants within the learned sequences. The effect was related to individuals' musical ability to coordinate their finger movements along with external auditory events.

Synchronized tapping facilitates learning sound sequences as indexed by the P300

PubMed Central

Kamiyama, Keiko S.; Okanoya, Kazuo

2014-01-01

The purpose of the present study was to determine whether and how single finger tapping in synchrony with sound sequences contributed to the auditory processing of them. The participants learned two unfamiliar sound sequences via different methods. In the tapping condition, they learned an auditory sequence while they tapped in synchrony with each sound onset. In the no tapping condition, they learned another sequence while they kept pressing a key until the sequence ended. After these learning sessions, we presented the two melodies again and recorded event-related potentials (ERPs). During the ERP recordings, 10% of the tones within each melody deviated from the original tones. An analysis of the grand average ERPs showed that deviant stimuli elicited a significant P300 in the tapping but not in the no-tapping condition. In addition, the significance of the P300 effect in the tapping condition increased as the participants showed highly synchronized tapping behavior during the learning sessions. These results indicated that single finger tapping promoted the conscious detection and evaluation of deviants within the learned sequences. The effect was related to individuals’ musical ability to coordinate their finger movements along with external auditory events. PMID:25400564

Navy LPD-17 Amphibious Ship Procurement: Background, Issues, and Options for Congress

DTIC Science & Technology

2010-07-01

Background, Issues, and Options for Congress 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e . TASK...performed out of sequence and significant rework has been required, disrupting the optimal construction sequence and application of lessons learned...deeply concerned about Northrop Grumman Ship Systems’ ( NGSS ) ability to recover in the aftermath of Hurricane Katrina, particularly in regard to

Navy LPD-17 Amphibious Ship Procurement: Background, Issues, and Options for Congress

DTIC Science & Technology

2010-03-29

and Options for Congress 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e . TASK NUMBER 5f...performed out of sequence and significant rework has been required, disrupting the optimal construction sequence and application of lessons learned...deeply concerned about Northrop Grumman Ship Systems’ ( NGSS ) ability to recover in the aftermath of Hurricane Katrina, particularly in regard to

Lung dynamic MRI deblurring using low-rank decomposition and dictionary learning.

PubMed

Gou, Shuiping; Wang, Yueyue; Wu, Jiaolong; Lee, Percy; Sheng, Ke

2015-04-01

Lung dynamic MRI (dMRI) has emerged to be an appealing tool to quantify lung motion for both planning and treatment guidance purposes. However, this modality can result in blurry images due to intrinsically low signal-to-noise ratio in the lung and spatial/temporal interpolation. The image blurring could adversely affect the image processing that depends on the availability of fine landmarks. The purpose of this study is to reduce dMRI blurring using image postprocessing. To enhance the image quality and exploit the spatiotemporal continuity of dMRI sequences, a low-rank decomposition and dictionary learning (LDDL) method was employed to deblur lung dMRI and enhance the conspicuity of lung blood vessels. Fifty frames of continuous 2D coronal dMRI frames using a steady state free precession sequence were obtained from five subjects including two healthy volunteer and three lung cancer patients. In LDDL, the lung dMRI was decomposed into sparse and low-rank components. Dictionary learning was employed to estimate the blurring kernel based on the whole image, low-rank or sparse component of the first image in the lung MRI sequence. Deblurring was performed on the whole image sequences using deconvolution based on the estimated blur kernel. The deblurring results were quantified using an automated blood vessel extraction method based on the classification of Hessian matrix filtered images. Accuracy of automated extraction was calculated using manual segmentation of the blood vessels as the ground truth. In the pilot study, LDDL based on the blurring kernel estimated from the sparse component led to performance superior to the other ways of kernel estimation. LDDL consistently improved image contrast and fine feature conspicuity of the original MRI without introducing artifacts. The accuracy of automated blood vessel extraction was on average increased by 16% using manual segmentation as the ground truth. Image blurring in dMRI images can be effectively reduced using a low-rank decomposition and dictionary learning method using kernels estimated by the sparse component.

Implicit chaining in cotton-top tamarins (Saguinus oedipus) with elements equated for probability of reinforcement

PubMed Central

Dillon, Laura; Collins, Meaghan; Conway, Maura; Cunningham, Kate

2013-01-01

Three experiments examined the implicit learning of sequences under conditions in which the elements comprising a sequence were equated in terms of reinforcement probability. In Experiment 1 cotton-top tamarins (Saguinus oedipus) experienced a five-element sequence displayed serially on a touch screen in which reinforcement probability was equated across elements at .16 per element. Tamarins demonstrated learning of this sequence with higher latencies during a random test as compared to baseline sequence training. In Experiments 2 and 3, manipulations of the procedure used in the first experiment were undertaken to rule out a confound owing to the fact that the elements in Experiment 1 bore different temporal relations to the intertrial interval (ITI), an inhibitory period. The results of Experiments 2 and 3 indicated that the implicit learning observed in Experiment 1 was not due to temporal proximity between some elements and the inhibitory ITI. The results taken together support two conclusion: First that tamarins engaged in sequence learning whether or not there was contingent reinforcement for learning the sequence, and second that this learning was not due to subtle differences in associative strength between the elements of the sequence. PMID:23344718

Implicit sequence learning in deaf children with cochlear implants.

PubMed

Conway, Christopher M; Pisoni, David B; Anaya, Esperanza M; Karpicke, Jennifer; Henning, Shirley C

2011-01-01

Deaf children with cochlear implants (CIs) represent an intriguing opportunity to study neurocognitive plasticity and reorganization when sound is introduced following a period of auditory deprivation early in development. Although it is common to consider deafness as affecting hearing alone, it may be the case that auditory deprivation leads to more global changes in neurocognitive function. In this paper, we investigate implicit sequence learning abilities in deaf children with CIs using a novel task that measured learning through improvement to immediate serial recall for statistically consistent visual sequences. The results demonstrated two key findings. First, the deaf children with CIs showed disturbances in their visual sequence learning abilities relative to the typically developing normal-hearing children. Second, sequence learning was significantly correlated with a standardized measure of language outcome in the CI children. These findings suggest that a period of auditory deprivation has secondary effects related to general sequencing deficits, and that disturbances in sequence learning may at least partially explain why some deaf children still struggle with language following cochlear implantation. © 2010 Blackwell Publishing Ltd.

A machine learning approach for viral genome classification.

PubMed

Remita, Mohamed Amine; Halioui, Ahmed; Malick Diouara, Abou Abdallah; Daigle, Bruno; Kiani, Golrokh; Diallo, Abdoulaye Baniré

2017-04-11

Advances in cloning and sequencing technology are yielding a massive number of viral genomes. The classification and annotation of these genomes constitute important assets in the discovery of genomic variability, taxonomic characteristics and disease mechanisms. Existing classification methods are often designed for specific well-studied family of viruses. Thus, the viral comparative genomic studies could benefit from more generic, fast and accurate tools for classifying and typing newly sequenced strains of diverse virus families. Here, we introduce a virus classification platform, CASTOR, based on machine learning methods. CASTOR is inspired by a well-known technique in molecular biology: restriction fragment length polymorphism (RFLP). It simulates, in silico, the restriction digestion of genomic material by different enzymes into fragments. It uses two metrics to construct feature vectors for machine learning algorithms in the classification step. We benchmark CASTOR for the classification of distinct datasets of human papillomaviruses (HPV), hepatitis B viruses (HBV) and human immunodeficiency viruses type 1 (HIV-1). Results reveal true positive rates of 99%, 99% and 98% for HPV Alpha species, HBV genotyping and HIV-1 M subtyping, respectively. Furthermore, CASTOR shows a competitive performance compared to well-known HIV-1 specific classifiers (REGA and COMET) on whole genomes and pol fragments. The performance of CASTOR, its genericity and robustness could permit to perform novel and accurate large scale virus studies. The CASTOR web platform provides an open access, collaborative and reproducible machine learning classifiers. CASTOR can be accessed at http://castor.bioinfo.uqam.ca .

Sequence skill learning in persons who stutter: implications for cortico-striato-thalamo-cortical dysfunction.

PubMed

Smits-Bandstra, Sarah; De Nil, Luc F

2007-01-01

The basal ganglia and cortico-striato-thalamo-cortical connections are known to play a critical role in sequence skill learning and increasing automaticity over practice. The current paper reviews four studies comparing the sequence skill learning and the transition to automaticity of persons who stutter (PWS) and fluent speakers (PNS) over practice. Studies One and Two found PWS to have poor finger tap sequencing skill and nonsense syllable sequencing skill after practice, and on retention and transfer tests relative to PNS. Studies Three and Four found PWS to be significantly less accurate and/or significantly slower after practice on dual tasks requiring concurrent sequencing and colour recognition over practice relative to PNS. Evidence of PWS' deficits in sequence skill learning and automaticity development support the hypothesis that dysfunction in cortico-striato-thalamo-cortical connections may be one etiological component in the development and maintenance of stuttering. As a result of this activity, the reader will: (1) be able to articulate the research regarding the basal ganglia system relating to sequence skill learning; (2) be able to summarize the research on stuttering with indications of sequence skill learning deficits; and (3) be able to discuss basal ganglia mechanisms with relevance for theory of stuttering.

Association of Amine-Receptor DNA Sequence Variants with Associative Learning in the Honeybee.

PubMed

Lagisz, Malgorzata; Mercer, Alison R; de Mouzon, Charlotte; Santos, Luana L S; Nakagawa, Shinichi

2016-03-01

Octopamine- and dopamine-based neuromodulatory systems play a critical role in learning and learning-related behaviour in insects. To further our understanding of these systems and resulting phenotypes, we quantified DNA sequence variations at six loci coding octopamine-and dopamine-receptors and their association with aversive and appetitive learning traits in a population of honeybees. We identified 79 polymorphic sequence markers (mostly SNPs and a few insertions/deletions) located within or close to six candidate genes. Intriguingly, we found that levels of sequence variation in the protein-coding regions studied were low, indicating that sequence variation in the coding regions of receptor genes critical to learning and memory is strongly selected against. Non-coding and upstream regions of the same genes, however, were less conserved and sequence variations in these regions were weakly associated with between-individual differences in learning-related traits. While these associations do not directly imply a specific molecular mechanism, they suggest that the cross-talk between dopamine and octopamine signalling pathways may influence olfactory learning and memory in the honeybee.

Implicit transfer of reversed temporal structure in visuomotor sequence learning.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2014-04-01

Some spatio-temporal structures are easier to transfer implicitly in sequential learning. In this study, we investigated whether the consistent reversal of triads of learned components would support the implicit transfer of their temporal structure in visuomotor sequence learning. A triad comprised three sequential button presses ([1][2][3]) and seven consecutive triads comprised a sequence. Participants learned sequences by trial and error, until they could complete it 20 times without error. Then, they learned another sequence, in which each triad was reversed ([3][2][1]), partially reversed ([2][1][3]), or switched so as not to overlap with the other conditions ([2][3][1] or [3][1][2]). Even when the participants did not notice the alternation rule, the consistent reversal of the temporal structure of each triad led to better implicit transfer; this was confirmed in a subsequent experiment. These results suggest that the implicit transfer of the temporal structure of a learned sequence can be influenced by both the structure and consistency of the change. Copyright © 2013 Cognitive Science Society, Inc.

GOLabeler: Improving Sequence-based Large-scale Protein Function Prediction by Learning to Rank.

PubMed

You, Ronghui; Zhang, Zihan; Xiong, Yi; Sun, Fengzhu; Mamitsuka, Hiroshi; Zhu, Shanfeng

2018-03-07

Gene Ontology (GO) has been widely used to annotate functions of proteins and understand their biological roles. Currently only <1% of more than 70 million proteins in UniProtKB have experimental GO annotations, implying the strong necessity of automated function prediction (AFP) of proteins, where AFP is a hard multilabel classification problem due to one protein with a diverse number of GO terms. Most of these proteins have only sequences as input information, indicating the importance of sequence-based AFP (SAFP: sequences are the only input). Furthermore homology-based SAFP tools are competitive in AFP competitions, while they do not necessarily work well for so-called difficult proteins, which have <60% sequence identity to proteins with annotations already. Thus the vital and challenging problem now is how to develop a method for SAFP, particularly for difficult proteins. The key of this method is to extract not only homology information but also diverse, deep- rooted information/evidence from sequence inputs and integrate them into a predictor in a both effective and efficient manner. We propose GOLabeler, which integrates five component classifiers, trained from different features, including GO term frequency, sequence alignment, amino acid trigram, domains and motifs, and biophysical properties, etc., in the framework of learning to rank (LTR), a paradigm of machine learning, especially powerful for multilabel classification. The empirical results obtained by examining GOLabeler extensively and thoroughly by using large-scale datasets revealed numerous favorable aspects of GOLabeler, including significant performance advantage over state-of-the-art AFP methods. http://datamining-iip.fudan.edu.cn/golabeler. zhusf@fudan.edu.cn. Supplementary data are available at Bioinformatics online.

Simultaneously learning DNA motif along with its position and sequence rank preferences through expectation maximization algorithm.

PubMed

Zhang, ZhiZhuo; Chang, Cheng Wei; Hugo, Willy; Cheung, Edwin; Sung, Wing-Kin

2013-03-01

Although de novo motifs can be discovered through mining over-represented sequence patterns, this approach misses some real motifs and generates many false positives. To improve accuracy, one solution is to consider some additional binding features (i.e., position preference and sequence rank preference). This information is usually required from the user. This article presents a de novo motif discovery algorithm called SEME (sampling with expectation maximization for motif elicitation), which uses pure probabilistic mixture model to model the motif's binding features and uses expectation maximization (EM) algorithms to simultaneously learn the sequence motif, position, and sequence rank preferences without asking for any prior knowledge from the user. SEME is both efficient and accurate thanks to two important techniques: the variable motif length extension and importance sampling. Using 75 large-scale synthetic datasets, 32 metazoan compendium benchmark datasets, and 164 chromatin immunoprecipitation sequencing (ChIP-Seq) libraries, we demonstrated the superior performance of SEME over existing programs in finding transcription factor (TF) binding sites. SEME is further applied to a more difficult problem of finding the co-regulated TF (coTF) motifs in 15 ChIP-Seq libraries. It identified significantly more correct coTF motifs and, at the same time, predicted coTF motifs with better matching to the known motifs. Finally, we show that the learned position and sequence rank preferences of each coTF reveals potential interaction mechanisms between the primary TF and the coTF within these sites. Some of these findings were further validated by the ChIP-Seq experiments of the coTFs. The application is available online.

Learning and inference in a nonequilibrium Ising model with hidden nodes.

PubMed

Dunn, Benjamin; Roudi, Yasser

2013-02-01

We study inference and reconstruction of couplings in a partially observed kinetic Ising model. With hidden spins, calculating the likelihood of a sequence of observed spin configurations requires performing a trace over the configurations of the hidden ones. This, as we show, can be represented as a path integral. Using this representation, we demonstrate that systematic approximate inference and learning rules can be derived using dynamical mean-field theory. Although naive mean-field theory leads to an unstable learning rule, taking into account Gaussian corrections allows learning the couplings involving hidden nodes. It also improves learning of the couplings between the observed nodes compared to when hidden nodes are ignored.

Musical Experience Influences Statistical Learning of a Novel Language

PubMed Central

Shook, Anthony; Marian, Viorica; Bartolotti, James; Schroeder, Scott R.

2014-01-01

Musical experience may benefit learning a new language by enhancing the fidelity with which the auditory system encodes sound. In the current study, participants with varying degrees of musical experience were exposed to two statistically-defined languages consisting of auditory Morse-code sequences which varied in difficulty. We found an advantage for highly-skilled musicians, relative to less-skilled musicians, in learning novel Morse-code based words. Furthermore, in the more difficult learning condition, performance of lower-skilled musicians was mediated by their general cognitive abilities. We suggest that musical experience may lead to enhanced processing of statistical information and that musicians’ enhanced ability to learn statistical probabilities in a novel Morse-code language may extend to natural language learning. PMID:23505962

Motor programming when sequencing multiple elements of the same duration.

PubMed

Magnuson, Curt E; Robin, Donald A; Wright, David L

2008-11-01

Motor programming at the self-select paradigm was adopted in 2 experiments to examine the processing demands of independent processes. One process (INT) is responsible for organizing the internal features of the individual elements in a movement (e.g., response duration). The 2nd process (SEQ) is responsible for placing the elements into the proper serial order before execution. Participants in Experiment 1 performed tasks involving 1 key press or sequences of 4 key presses of the same duration. Implementing INT and SEQ was more time consuming for key-pressing sequences than for single key-press tasks. Experiment 2 examined whether the INT costs resulting from the increase in sequence length observed in Experiment 1 resulted from independent planning of each sequence element or via a separate "multiplier" process that handled repetitions of elements of the same duration. Findings from Experiment 2, in which participants performed single key presses or double or triple key sequences of the same duration, suggested that INT is involved with the independent organization of each element contained in the sequence. Researchers offer an elaboration of the 2-process account of motor programming to incorporate the present findings and the findings from other recent sequence-learning research.

A model of human motor sequence learning explains facilitation and interference effects based on spike-timing dependent plasticity.

PubMed

Wang, Quan; Rothkopf, Constantin A; Triesch, Jochen

2017-08-01

The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN) model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP) with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP) and synaptic normalization (SN). When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network's changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network's sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that STDP, IP, and SN may be the driving forces behind our ability to learn complex action sequences.

Perceived ambiguity as a barrier to intentions to learn genome sequencing results

PubMed Central

Taber, Jennifer M.; Klein, William M.P.; Ferrer, Rebecca A.; Han, Paul K. J.; Lewis, Katie L.; Biesecker, Leslie G.; Biesecker, Barbara B.

2015-01-01

Many variants that could be returned from genome sequencing may be perceived as ambiguous—lacking reliability, credibility, or adequacy. Little is known about how perceived ambiguity influences thoughts about sequencing results. Participants (n=494) in an NIH genome sequencing study completed a baseline survey before sequencing results were available. We examined how perceived ambiguity regarding sequencing results and individual differences in medical ambiguity aversion and tolerance for uncertainty were associated with cognitions and intentions concerning sequencing results. Perceiving sequencing results as more ambiguous was associated with less favorable cognitions about results and lower intentions to learn and share results. Among participants low in tolerance for uncertainty or optimism, greater perceived ambiguity was associated with lower intentions to learn results for non-medically actionable diseases; medical ambiguity aversion did not moderate any associations. Results are consistent with the phenomenon of “ambiguity aversion” and may influence whether people learn and communicate genomic information. PMID:26003053

Perceived ambiguity as a barrier to intentions to learn genome sequencing results.

PubMed

Taber, Jennifer M; Klein, William M P; Ferrer, Rebecca A; Han, Paul K J; Lewis, Katie L; Biesecker, Leslie G; Biesecker, Barbara B

2015-10-01

Many variants that could be returned from genome sequencing may be perceived as ambiguous-lacking reliability, credibility, or adequacy. Little is known about how perceived ambiguity influences thoughts about sequencing results. Participants (n = 494) in an NIH genome sequencing study completed a baseline survey before sequencing results were available. We examined how perceived ambiguity regarding sequencing results and individual differences in medical ambiguity aversion and tolerance for uncertainty were associated with cognitions and intentions concerning sequencing results. Perceiving sequencing results as more ambiguous was associated with less favorable cognitions about results and lower intentions to learn and share results. Among participants low in tolerance for uncertainty or optimism, greater perceived ambiguity was associated with lower intentions to learn results for non-medically actionable diseases; medical ambiguity aversion did not moderate any associations. Results are consistent with the phenomenon of "ambiguity aversion" and may influence whether people learn and communicate genomic information.

The Necessity of the Hippocampus for Statistical Learning

PubMed Central

Covington, Natalie V.; Brown-Schmidt, Sarah; Duff, Melissa C.

2018-01-01

Converging evidence points to a role for the hippocampus in statistical learning, but open questions about its necessity remain. Evidence for necessity comes from Schapiro and colleagues who report that a single patient with damage to hippocampus and broader medial temporal lobe cortex was unable to discriminate new from old sequences in several statistical learning tasks. The aim of the current study was to replicate these methods in a larger group of patients who have either damage localized to hippocampus or a broader medial temporal lobe damage, to ascertain the necessity of the hippocampus in statistical learning. Patients with hippocampal damage consistently showed less learning overall compared with healthy comparison participants, consistent with an emerging consensus for hippocampal contributions to statistical learning. Interestingly, lesion size did not reliably predict performance. However, patients with hippocampal damage were not uniformly at chance and demonstrated above-chance performance in some task variants. These results suggest that hippocampus is necessary for statistical learning levels achieved by most healthy comparison participants but significant hippocampal pathology alone does not abolish such learning. PMID:29308986

Classification of G-protein coupled receptors based on a rich generation of convolutional neural network, N-gram transformation and multiple sequence alignments.

PubMed

Li, Man; Ling, Cheng; Xu, Qi; Gao, Jingyang

2018-02-01

Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithms. To improve prediction accuracy, these algorithms must confront the key challenge of extracting valuable features. In this work, we propose a feature-enhanced protein classification approach, considering the rich generation of multiple sequence alignment algorithms, N-gram probabilistic language model and the deep learning technique. The essence behind the proposed method is that if each group of sequences can be represented by one feature sequence, composed of homologous sites, there should be less loss when the sequence is rebuilt, when a more relevant sequence is added to the group. On the basis of this consideration, the prediction becomes whether a query sequence belonging to a group of sequences can be transferred to calculate the probability that the new feature sequence evolves from the original one. The proposed work focuses on the hierarchical classification of G-protein Coupled Receptors (GPCRs), which begins by extracting the feature sequences from the multiple sequence alignment results of the GPCRs sub-subfamilies. The N-gram model is then applied to construct the input vectors. Finally, these vectors are imported into a convolutional neural network to make a prediction. The experimental results elucidate that the proposed method provides significant performance improvements. The classification error rate of the proposed method is reduced by at least 4.67% (family level I) and 5.75% (family Level II), in comparison with the current state-of-the-art methods. The implementation program of the proposed work is freely available at: https://github.com/alanFchina/CNN .

Intelligent fault diagnosis of rolling bearings using an improved deep recurrent neural network

NASA Astrophysics Data System (ADS)

Jiang, Hongkai; Li, Xingqiu; Shao, Haidong; Zhao, Ke

2018-06-01

Traditional intelligent fault diagnosis methods for rolling bearings heavily depend on manual feature extraction and feature selection. For this purpose, an intelligent deep learning method, named the improved deep recurrent neural network (DRNN), is proposed in this paper. Firstly, frequency spectrum sequences are used as inputs to reduce the input size and ensure good robustness. Secondly, DRNN is constructed by the stacks of the recurrent hidden layer to automatically extract the features from the input spectrum sequences. Thirdly, an adaptive learning rate is adopted to improve the training performance of the constructed DRNN. The proposed method is verified with experimental rolling bearing data, and the results confirm that the proposed method is more effective than traditional intelligent fault diagnosis methods.

Striatal and Hippocampal Involvement in Motor Sequence Chunking Depends on the Learning Strategy

PubMed Central

Lungu, Ovidiu; Monchi, Oury; Albouy, Geneviève; Jubault, Thomas; Ballarin, Emanuelle; Burnod, Yves; Doyon, Julien

2014-01-01

Motor sequences can be learned using an incremental approach by starting with a few elements and then adding more as training evolves (e.g., learning a piano piece); conversely, one can use a global approach and practice the whole sequence in every training session (e.g., shifting gears in an automobile). Yet, the neural correlates associated with such learning strategies in motor sequence learning remain largely unexplored to date. Here we used functional magnetic resonance imaging to measure the cerebral activity of individuals executing the same 8-element sequence after they completed a 4-days training regimen (2 sessions each day) following either a global or incremental strategy. A network comprised of striatal and fronto-parietal regions was engaged significantly regardless of the learning strategy, whereas the global training regimen led to additional cerebellar and temporal lobe recruitment. Analysis of chunking/grouping of sequence elements revealed a common prefrontal network in both conditions during the chunk initiation phase, whereas execution of chunk cores led to higher mediotemporal activity (involving the hippocampus) after global than incremental training. The novelty of our results relate to the recruitment of mediotemporal regions conditional of the learning strategy. Thus, the present findings may have clinical implications suggesting that the ability of patients with lesions to the medial temporal lobe to learn and consolidate new motor sequences may benefit from using an incremental strategy. PMID:25148078

Striatal and hippocampal involvement in motor sequence chunking depends on the learning strategy.

PubMed

Lungu, Ovidiu; Monchi, Oury; Albouy, Geneviève; Jubault, Thomas; Ballarin, Emanuelle; Burnod, Yves; Doyon, Julien

2014-01-01

Motor sequences can be learned using an incremental approach by starting with a few elements and then adding more as training evolves (e.g., learning a piano piece); conversely, one can use a global approach and practice the whole sequence in every training session (e.g., shifting gears in an automobile). Yet, the neural correlates associated with such learning strategies in motor sequence learning remain largely unexplored to date. Here we used functional magnetic resonance imaging to measure the cerebral activity of individuals executing the same 8-element sequence after they completed a 4-days training regimen (2 sessions each day) following either a global or incremental strategy. A network comprised of striatal and fronto-parietal regions was engaged significantly regardless of the learning strategy, whereas the global training regimen led to additional cerebellar and temporal lobe recruitment. Analysis of chunking/grouping of sequence elements revealed a common prefrontal network in both conditions during the chunk initiation phase, whereas execution of chunk cores led to higher mediotemporal activity (involving the hippocampus) after global than incremental training. The novelty of our results relate to the recruitment of mediotemporal regions conditional of the learning strategy. Thus, the present findings may have clinical implications suggesting that the ability of patients with lesions to the medial temporal lobe to learn and consolidate new motor sequences may benefit from using an incremental strategy.

Learning to learn: From within-modality to cross-modality transfer during infancy.

PubMed

Hupp, Julie M; Sloutsky, Vladimir M

2011-11-01

One critical aspect of learning is the ability to apply learned knowledge to new situations. This ability to transfer is often limited, and its development is not well understood. The current research investigated the development of transfer between 8 and 16 months of age. In Experiment 1, 8- and 16-month-olds (who were established to have a preference to the beginning of a visual sequence) were trained to attend to the end of a sequence. They were then tested on novel visual sequences. Results indicated transfer of learning, with both groups changing baseline preferences as a result of training. In Experiment 2, participants were trained to attend to the end of a visual sequence and were then tested on an auditory sequence. Unlike Experiment 1, only older participants exhibited transfer of learning by changing baseline preferences. These findings suggest that the generalization of learning becomes broader with development, with transfer across modalities developing later than transfer within a modality. Copyright © 2011 Elsevier Inc. All rights reserved.

Learning to Learn: From Within-Modality to Cross-Modality Transfer in Infancy

PubMed Central

Hupp, Julie M.; Sloutsky, Vladimir M.

2011-01-01

One critical aspect of learning is the ability to apply learned knowledge to new situations. This ability to transfer is often limited, and its development is not well understood. The current research investigated the development of transfer between 8- and 16-months of age. In Experiment 1, 8- and 16-month-olds (who were established to have a preference to the beginning of a visual sequence) were trained to attend to the end of a sequence. They were then tested on novel visual sequences. Results indicated transfer of learning, as both groups changed baseline preferences as a result of training. In Experiment 2, participants were trained to attend to the end of a visual sequence and then tested on an auditory sequence. Unlike Experiment 1, only older participants exhibited transfer of learning by changing baseline preferences. These findings suggest that the generalization of learning becomes broader with development, with transfer across modalities developing later than transfer within a modality. PMID:21663920

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.

Adaptive Learning Resources Sequencing in Educational Hypermedia Systems

ERIC Educational Resources Information Center

Karampiperis, Pythagoras; Sampson, Demetrios

2005-01-01

Adaptive learning resources selection and sequencing is recognized as among the most interesting research questions in adaptive educational hypermedia systems (AEHS). In order to adaptively select and sequence learning resources in AEHS, the definition of adaptation rules contained in the Adaptation Model, is required. Although, some efforts have…

Using data from the Microsoft Kinect 2 to determine postural stability in healthy subjects: A feasibility trial

PubMed Central

Smeragliuolo, Anna H.; Long, John Davis; Bumanlag, Silverio Joseph; He, Victor; Lampe, Anna

2017-01-01

The objective of this study was to determine whether kinematic data collected by the Microsoft Kinect 2 (MK2) could be used to quantify postural stability in healthy subjects. Twelve subjects were recruited for the project, and were instructed to perform a sequence of simple postural stability tasks. The movement sequence was performed as subjects were seated on top of a force platform, and the MK2 was positioned in front of them. This sequence of tasks was performed by each subject under three different postural conditions: “both feet on the ground” (1), “One foot off the ground” (2), and “both feet off the ground” (3). We compared force platform and MK2 data to quantify the degree to which the MK2 was returning reliable data across subjects. We then applied a novel machine-learning paradigm to the MK2 data in order to determine the extent to which data from the MK2 could be used to reliably classify different postural conditions. Our initial comparison of force plate and MK2 data showed a strong agreement between the two devices, with strong Pearson correlations between the trunk centroids “Spine_Mid” (0.85 ± 0.06), “Neck” (0.86 ± 0.07) and “Head” (0.87 ± 0.07), and the center of pressure centroid inferred by the force platform. Mean accuracy for the machine learning classifier from MK2 was 97.0%, with a specific classification accuracy breakdown of 90.9%, 100%, and 100% for conditions 1 through 3, respectively. Mean accuracy for the machine learning classifier derived from the force platform data was lower at 84.4%. We conclude that data from the MK2 has sufficient information content to allow us to classify sequences of tasks being performed under different levels of postural stability. Future studies will focus on validating this protocol on large populations of individuals with actual balance impairments in order to create a toolkit that is clinically validated and available to the medical community. PMID:28196139

Using data from the Microsoft Kinect 2 to determine postural stability in healthy subjects: A feasibility trial.

PubMed

Dehbandi, Behdad; Barachant, Alexandre; Smeragliuolo, Anna H; Long, John Davis; Bumanlag, Silverio Joseph; He, Victor; Lampe, Anna; Putrino, David

2017-01-01

The objective of this study was to determine whether kinematic data collected by the Microsoft Kinect 2 (MK2) could be used to quantify postural stability in healthy subjects. Twelve subjects were recruited for the project, and were instructed to perform a sequence of simple postural stability tasks. The movement sequence was performed as subjects were seated on top of a force platform, and the MK2 was positioned in front of them. This sequence of tasks was performed by each subject under three different postural conditions: "both feet on the ground" (1), "One foot off the ground" (2), and "both feet off the ground" (3). We compared force platform and MK2 data to quantify the degree to which the MK2 was returning reliable data across subjects. We then applied a novel machine-learning paradigm to the MK2 data in order to determine the extent to which data from the MK2 could be used to reliably classify different postural conditions. Our initial comparison of force plate and MK2 data showed a strong agreement between the two devices, with strong Pearson correlations between the trunk centroids "Spine_Mid" (0.85 ± 0.06), "Neck" (0.86 ± 0.07) and "Head" (0.87 ± 0.07), and the center of pressure centroid inferred by the force platform. Mean accuracy for the machine learning classifier from MK2 was 97.0%, with a specific classification accuracy breakdown of 90.9%, 100%, and 100% for conditions 1 through 3, respectively. Mean accuracy for the machine learning classifier derived from the force platform data was lower at 84.4%. We conclude that data from the MK2 has sufficient information content to allow us to classify sequences of tasks being performed under different levels of postural stability. Future studies will focus on validating this protocol on large populations of individuals with actual balance impairments in order to create a toolkit that is clinically validated and available to the medical community.

Learning of goal-relevant and -irrelevant complex visual sequences in human V1.

PubMed

Rosenthal, Clive R; Mallik, Indira; Caballero-Gaudes, Cesar; Sereno, Martin I; Soto, David

2018-06-12

Learning and memory are supported by a network involving the medial temporal lobe and linked neocortical regions. Emerging evidence indicates that primary visual cortex (i.e., V1) may contribute to recognition memory, but this has been tested only with a single visuospatial sequence as the target memorandum. The present study used functional magnetic resonance imaging to investigate whether human V1 can support the learning of multiple, concurrent complex visual sequences involving discontinous (second-order) associations. Two peripheral, goal-irrelevant but structured sequences of orientated gratings appeared simultaneously in fixed locations of the right and left visual fields alongside a central, goal-relevant sequence that was in the focus of spatial attention. Pseudorandom sequences were introduced at multiple intervals during the presentation of the three structured visual sequences to provide an online measure of sequence-specific knowledge at each retinotopic location. We found that a network involving the precuneus and V1 was involved in learning the structured sequence presented at central fixation, whereas right V1 was modulated by repeated exposure to the concurrent structured sequence presented in the left visual field. The same result was not found in left V1. These results indicate for the first time that human V1 can support the learning of multiple concurrent sequences involving complex discontinuous inter-item associations, even peripheral sequences that are goal-irrelevant. Copyright © 2018. Published by Elsevier Inc.

A Structural Approach to the Validation of Hierarchical Training Sequences

DTIC Science & Technology

1981-06-01

consideration as can be examinedI -11- within existing constraints on time and resources. Second, for each con- nection to be studied, identify groups ... one group of learners who are taught all skills in a linear sequence whereas many groups learning different skills are needed to implement the White...meability. For example, suppose that a group of item sets were used to assess performance on three academic tasks, A, B, and C. Assume that task A was

Task Demands in OSCEs Influence Learning Strategies.

PubMed

Lafleur, Alexandre; Laflamme, Jonathan; Leppink, Jimmie; Côté, Luc

2017-01-01

Models on pre-assessment learning effects confirmed that task demands stand out among the factors assessors can modify in an assessment to influence learning. However, little is known about which tasks in objective structured clinical examinations (OSCEs) improve students' cognitive and metacognitive processes. Research is needed to support OSCE designs that benefit students' metacognitive strategies when they are studying, reinforcing a hypothesis-driven approach. With that intent, hypothesis-driven physical examination (HDPE) assessments ask students to elicit and interpret findings of the physical exam to reach a diagnosis ("Examine this patient with a painful shoulder to reach a diagnosis"). When studying for HDPE, students will dedicate more time to hypothesis-driven discussions and practice than when studying for a part-task OSCE ("Perform the shoulder exam"). It is expected that the whole-task nature of HDPE will lead to a hypothesis-oriented use of the learning resources, a frequent use of adjustment strategies, and persistence with learning. In a mixed-methods study, 40 medical students were randomly paired and filmed while studying together for two hypothetical OSCE stations. Each 25-min study period began with video cues asking to study for either a part-task OSCE or an HDPE. In a crossover design, sequences were randomized for OSCEs and contents (shoulder or spine). Time-on-task for discussions or practice were categorized as "hypothesis-driven" or "sequence of signs and maneuvers." Content analysis of focus group interviews summarized students' perception of learning resources, adjustment strategies, and persistence with learning. When studying for HDPE, students allocate significantly more time for hypothesis-driven discussions and practice. Students use resources contrasting diagnoses and report persistence with learning. When studying for part-task OSCEs, time-on-task is reversed, spent on rehearsing a sequence of signs and maneuvers. OSCEs with similar contents but different task demands lead to opposite learning strategies regarding how students manage their study time. Measuring pre-assessment effects from a metacognitive perspective provides empirical evidence to redesign assessments for learning.

GARFIELD-NGS: Genomic vARiants FIltering by dEep Learning moDels in NGS.

PubMed

Ravasio, Viola; Ritelli, Marco; Legati, Andrea; Giacopuzzi, Edoardo

2018-04-14

Exome sequencing approach is extensively used in research and diagnostic laboratories to discover pathological variants and study genetic architecture of human diseases. However, a significant proportion of identified genetic variants are actually false positive calls, and this pose serious challenges for variants interpretation. Here, we propose a new tool named GARFIELD-NGS (Genomic vARiants FIltering by dEep Learning moDels in NGS), which rely on deep learning models to dissect false and true variants in exome sequencing experiments performed with Illumina or ION platforms. GARFIELD-NGS showed strong performances for both SNP and INDEL variants (AUC 0.71 - 0.98) and outperformed established hard filters. The method is robust also at low coverage down to 30X and can be applied on data generated with the recent Illumina two-colour chemistry. GARFIELD-NGS processes standard VCF file and produces a regular VCF output. Thus, it can be easily integrated in existing analysis pipeline, allowing application of different thresholds based on desired level of sensitivity and specificity. GARFIELD-NGS available at https://github.com/gedoardo83/GARFIELD-NGS. edoardo.giacopuzzi@unibs.it. Supplementary data are available at Bioinformatics online.

A Foxp2 Mutation Implicated in Human Speech Deficits Alters Sequencing of Ultrasonic Vocalizations in Adult Male Mice.

PubMed

Chabout, Jonathan; Sarkar, Abhra; Patel, Sheel R; Radden, Taylor; Dunson, David B; Fisher, Simon E; Jarvis, Erich D

2016-01-01

Development of proficient spoken language skills is disrupted by mutations of the FOXP2 transcription factor. A heterozygous missense mutation in the KE family causes speech apraxia, involving difficulty producing words with complex learned sequences of syllables. Manipulations in songbirds have helped to elucidate the role of this gene in vocal learning, but findings in non-human mammals have been limited or inconclusive. Here, we performed a systematic study of ultrasonic vocalizations (USVs) of adult male mice carrying the KE family mutation. Using novel statistical tools, we found that Foxp2 heterozygous mice did not have detectable changes in USV syllable acoustic structure, but produced shorter sequences and did not shift to more complex syntax in social contexts where wildtype animals did. Heterozygous mice also displayed a shift in the position of their rudimentary laryngeal motor cortex (LMC) layer-5 neurons. Our findings indicate that although mouse USVs are mostly innate, the underlying contributions of FoxP2 to sequencing of vocalizations are conserved with humans.

A Foxp2 Mutation Implicated in Human Speech Deficits Alters Sequencing of Ultrasonic Vocalizations in Adult Male Mice

PubMed Central

Chabout, Jonathan; Sarkar, Abhra; Patel, Sheel R.; Radden, Taylor; Dunson, David B.; Fisher, Simon E.; Jarvis, Erich D.

2016-01-01

Development of proficient spoken language skills is disrupted by mutations of the FOXP2 transcription factor. A heterozygous missense mutation in the KE family causes speech apraxia, involving difficulty producing words with complex learned sequences of syllables. Manipulations in songbirds have helped to elucidate the role of this gene in vocal learning, but findings in non-human mammals have been limited or inconclusive. Here, we performed a systematic study of ultrasonic vocalizations (USVs) of adult male mice carrying the KE family mutation. Using novel statistical tools, we found that Foxp2 heterozygous mice did not have detectable changes in USV syllable acoustic structure, but produced shorter sequences and did not shift to more complex syntax in social contexts where wildtype animals did. Heterozygous mice also displayed a shift in the position of their rudimentary laryngeal motor cortex (LMC) layer-5 neurons. Our findings indicate that although mouse USVs are mostly innate, the underlying contributions of FoxP2 to sequencing of vocalizations are conserved with humans. PMID:27812326

How to find the way out from four rooms? The learning of "chaining" associations may shed light on the neuropsychology of the deficit syndrome of schizophrenia.

PubMed

Polgár, Patricia; Farkas, Márta; Nagy, Orsolya; Kelemen, Oguz; Réthelyi, János; Bitter, István; Myers, Catherine E; Gluck, Mark A; Kéri, Szabolcs

2008-02-01

Recent meta-analytic evidence suggests that clinical neuropsychological methods are not likely to uncover circumscribed cognitive impairments in the deficit syndrome of schizophrenia. To overcome this issue, we adapted a cognitive neuroscience perspective and used a new "chaining" habit learning task. Participants were requested to navigate a cartoon character through a sequence of 4 rooms by learning to choose the open door from 3 colored doors in each room. The aim of the game was to learn the full sequence of rooms until the character reached the outside. In the training phase, each stimulus leading to reward (open door in each room) was trained via feedback until the complete sequence was learned. In the probe phase, the context of rewarded stimuli was manipulated: in a given room, in addition to the correct door of that room, there also appeared a door which was open in another room. Whereas the training phase is dominantly related to basal ganglia circuits, the context-dependent probe phase requires intact medial-temporal lobe functioning. Results revealed that deficit and non-deficit patients were similarly impaired on the probe phase compared with controls. However, the training phase was only compromised in deficit patients. More severe negative symptoms were associated with more errors on the training phase. Executive functions were unrelated to performance on the "chaining" task. These results indicate that the deficit syndrome is associated with prominently impaired stimulus-response reinforcement learning, which may indicate abnormal functioning of basal ganglia circuits.

Learning and memory for sequences of pictures, words, and spatial locations: an exploration of serial position effects.

PubMed

Bonk, William J; Healy, Alice F

2010-01-01

A serial reproduction of order with distractors task was developed to make it possible to observe successive snapshots of the learning process at each serial position. The new task was used to explore the effect of several variables on serial memory performance: stimulus content (words, blanks, and pictures), presentation condition (spatial information vs. none), semantically categorized item clustering (grouped vs. ungrouped), and number of distractors relative to targets (none, equal, double). These encoding and retrieval variables, along with learning attempt number, affected both overall performance levels and the shape of the serial position function, although a large and extensive primacy advantage and a small 1-item recency advantage were found in each case. These results were explained well by a version of the scale-independent memory, perception, and learning model that accounted for improved performance by increasing the value of only a single parameter that reflects reduced interference from distant items.

Learning of Grammar-Like Visual Sequences by Adults with and without Language-Learning Disabilities

ERIC Educational Resources Information Center

Aguilar, Jessica M.; Plante, Elena

2014-01-01

Purpose: Two studies examined learning of grammar-like visual sequences to determine whether a general deficit in statistical learning characterizes this population. Furthermore, we tested the hypothesis that difficulty in sustaining attention during the learning task might account for differences in statistical learning. Method: In Study 1,…

Neural changes associated to procedural learning and automatization process in Developmental Coordination Disorder and/or Developmental Dyslexia.

PubMed

Biotteau, Maëlle; Péran, Patrice; Vayssière, Nathalie; Tallet, Jessica; Albaret, Jean-Michel; Chaix, Yves

2017-03-01

Recent theories hypothesize that procedural learning may support the frequent overlap between neurodevelopmental disorders. The neural circuitry supporting procedural learning includes, among others, cortico-cerebellar and cortico-striatal loops. Alteration of these loops may account for the frequent comorbidity between Developmental Coordination Disorder (DCD) and Developmental Dyslexia (DD). The aim of our study was to investigate cerebral changes due to the learning and automatization of a sequence learning task in children with DD, or DCD, or both disorders. fMRI on 48 children (aged 8-12) with DD, DCD or DD + DCD was used to explore their brain activity during procedural tasks, performed either after two weeks of training or in the early stage of learning. Firstly, our results indicate that all children were able to perform the task with the same level of automaticity, but recruit different brain processes to achieve the same performance. Secondly, our fMRI results do not appear to confirm Nicolson and Fawcett's model. The neural correlates recruited for procedural learning by the DD and the comorbid groups are very close, while the DCD group presents distinct characteristics. This provide a promising direction on the neural mechanisms associated with procedural learning in neurodevelopmental disorders and for understanding comorbidity. Published by Elsevier Ltd.

Learning strategy preference of 5XFAD transgenic mice depends on the sequence of place/spatial and cued training in the water maze task.

PubMed

Cho, Woo-Hyun; Park, Jung-Cheol; Chung, ChiHye; Jeon, Won Kyung; Han, Jung-Soo

2014-10-15

Learning strategy preference was assessed in 5XFAD mice, which carry 5 familial Alzheimer's disease (AD) mutations. Mice were sequentially trained in cued and place/spatial versions of the water maze task. After training, a strategy preference test was conducted in which mice were required to choose between the spatial location where the platform had previously been during the place/spatial training, and a visible platform in a new location. 5XFAD and non-transgenic control mice showed equivalent escape performance in both training tasks. However, in the strategy preference test, 5XFAD mice preferred a cued strategy relative to control mice. When the training sequence was presented in the reverse order (i.e., place/spatial training before cued training), 5XFAD mice showed impairments in place/spatial training, but no differences in cued training or in the strategy preference test comparing to control. Analysis of regional Aβ42 deposition in brains of 5XFAD mice showed that the hippocampus, which is involved in the place/spatial learning strategy, had the highest levels of Aβ42 and the dorsal striatum, which is involved in cued learning strategy, showed a small increase in Aβ42 levels. The effect of training protocol order on performance, and regional differences in Aβ42 deposition observed in 5XFAD mice, suggest differential functional recruitment of brain structures related to learning in healthy and AD individuals. Copyright © 2014 Elsevier B.V. All rights reserved.

Predicting human protein function with multi-task deep neural networks.

PubMed

Fa, Rui; Cozzetto, Domenico; Wan, Cen; Jones, David T

2018-01-01

Machine learning methods for protein function prediction are urgently needed, especially now that a substantial fraction of known sequences remains unannotated despite the extensive use of functional assignments based on sequence similarity. One major bottleneck supervised learning faces in protein function prediction is the structured, multi-label nature of the problem, because biological roles are represented by lists of terms from hierarchically organised controlled vocabularies such as the Gene Ontology. In this work, we build on recent developments in the area of deep learning and investigate the usefulness of multi-task deep neural networks (MTDNN), which consist of upstream shared layers upon which are stacked in parallel as many independent modules (additional hidden layers with their own output units) as the number of output GO terms (the tasks). MTDNN learns individual tasks partially using shared representations and partially from task-specific characteristics. When no close homologues with experimentally validated functions can be identified, MTDNN gives more accurate predictions than baseline methods based on annotation frequencies in public databases or homology transfers. More importantly, the results show that MTDNN binary classification accuracy is higher than alternative machine learning-based methods that do not exploit commonalities and differences among prediction tasks. Interestingly, compared with a single-task predictor, the performance improvement is not linearly correlated with the number of tasks in MTDNN, but medium size models provide more improvement in our case. One of advantages of MTDNN is that given a set of features, there is no requirement for MTDNN to have a bootstrap feature selection procedure as what traditional machine learning algorithms do. Overall, the results indicate that the proposed MTDNN algorithm improves the performance of protein function prediction. On the other hand, there is still large room for deep learning techniques to further enhance prediction ability.

A Unified Theoretical Framework for Cognitive Sequencing.

PubMed

Savalia, Tejas; Shukla, Anuj; Bapi, Raju S

2016-01-01

The capacity to sequence information is central to human performance. Sequencing ability forms the foundation stone for higher order cognition related to language and goal-directed planning. Information related to the order of items, their timing, chunking and hierarchical organization are important aspects in sequencing. Past research on sequencing has emphasized two distinct and independent dichotomies: implicit vs. explicit and goal-directed vs. habits. We propose a theoretical framework unifying these two streams. Our proposal relies on brain's ability to implicitly extract statistical regularities from the stream of stimuli and with attentional engagement organizing sequences explicitly and hierarchically. Similarly, sequences that need to be assembled purposively to accomplish a goal require engagement of attentional processes. With repetition, these goal-directed plans become habits with concomitant disengagement of attention. Thus, attention and awareness play a crucial role in the implicit-to-explicit transition as well as in how goal-directed plans become automatic habits. Cortico-subcortical loops basal ganglia-frontal cortex and hippocampus-frontal cortex loops mediate the transition process. We show how the computational principles of model-free and model-based learning paradigms, along with a pivotal role for attention and awareness, offer a unifying framework for these two dichotomies. Based on this framework, we make testable predictions related to the potential influence of response-to-stimulus interval (RSI) on developing awareness in implicit learning tasks.

A Unified Theoretical Framework for Cognitive Sequencing

PubMed Central

Savalia, Tejas; Shukla, Anuj; Bapi, Raju S.

2016-01-01

The capacity to sequence information is central to human performance. Sequencing ability forms the foundation stone for higher order cognition related to language and goal-directed planning. Information related to the order of items, their timing, chunking and hierarchical organization are important aspects in sequencing. Past research on sequencing has emphasized two distinct and independent dichotomies: implicit vs. explicit and goal-directed vs. habits. We propose a theoretical framework unifying these two streams. Our proposal relies on brain's ability to implicitly extract statistical regularities from the stream of stimuli and with attentional engagement organizing sequences explicitly and hierarchically. Similarly, sequences that need to be assembled purposively to accomplish a goal require engagement of attentional processes. With repetition, these goal-directed plans become habits with concomitant disengagement of attention. Thus, attention and awareness play a crucial role in the implicit-to-explicit transition as well as in how goal-directed plans become automatic habits. Cortico-subcortical loops basal ganglia-frontal cortex and hippocampus-frontal cortex loops mediate the transition process. We show how the computational principles of model-free and model-based learning paradigms, along with a pivotal role for attention and awareness, offer a unifying framework for these two dichotomies. Based on this framework, we make testable predictions related to the potential influence of response-to-stimulus interval (RSI) on developing awareness in implicit learning tasks. PMID:27917146

Songs as an aid for language acquisition.

PubMed

Schön, Daniele; Boyer, Maud; Moreno, Sylvain; Besson, Mireille; Peretz, Isabelle; Kolinsky, Régine

2008-02-01

In previous research, Saffran and colleagues [Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274, 1926-1928; Saffran, J. R., Newport, E. L., & Aslin, R. N. (1996). Word segmentation: The role of distributional cues. Journal of Memory and Language, 35, 606-621.] have shown that adults and infants can use the statistical properties of syllable sequences to extract words from continuous speech. They also showed that a similar learning mechanism operates with musical stimuli [Saffran, J. R., Johnson, R. E. K., Aslin, N., & Newport, E. L. (1999). Abstract Statistical learning of tone sequences by human infants and adults. Cognition, 70, 27-52.]. In this work we combined linguistic and musical information and we compared language learning based on speech sequences to language learning based on sung sequences. We hypothesized that, compared to speech sequences, a consistent mapping of linguistic and musical information would enhance learning. Results confirmed the hypothesis showing a strong learning facilitation of song compared to speech. Most importantly, the present results show that learning a new language, especially in the first learning phase wherein one needs to segment new words, may largely benefit of the motivational and structuring properties of music in song.

Resting-state Functional Connectivity is an Age-dependent Predictor of Motor Learning Abilities.

PubMed

Mary, Alison; Wens, Vincent; Op de Beeck, Marc; Leproult, Rachel; De Tiège, Xavier; Peigneux, Philippe

2017-10-01

This magnetoencephalography study investigates how ageing modulates the relationship between pre-learning resting-state functional connectivity (rsFC) and subsequent learning. Neuromagnetic resting-state activity was recorded 5 min before motor sequence learning in 14 young (19-30 years) and 14 old (66-70 years) participants. We used a seed-based beta-band power envelope correlation approach to estimate rsFC maps, with the seed located in the right primary sensorimotor cortex. In each age group, the relation between individual rsFC and learning performance was investigated using Pearson's correlation analyses. Our results show that rsFC is predictive of subsequent motor sequence learning but involves different cross-network interactions in the two age groups. In young adults, decreased coupling between the sensorimotor network and the cortico-striato-cerebellar network is associated with better motor learning, whereas a similar relation is found in old adults between the sensorimotor, the dorsal-attentional and the DMNs. Additionally, age-related correlational differences were found in the dorsolateral prefrontal cortex, known to subtend attentional and controlled processes. These findings suggest that motor skill learning depends-in an age-dependent manner-on subtle interactions between resting-state networks subtending motor activity on the one hand, and controlled and attentional processes on the other hand. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Learning cellular sorting pathways using protein interactions and sequence motifs.

PubMed

Lin, Tien-Ho; Bar-Joseph, Ziv; Murphy, Robert F

2011-11-01

Proper subcellular localization is critical for proteins to perform their roles in cellular functions. Proteins are transported by different cellular sorting pathways, some of which take a protein through several intermediate locations until reaching its final destination. The pathway a protein is transported through is determined by carrier proteins that bind to specific sequence motifs. In this article, we present a new method that integrates protein interaction and sequence motif data to model how proteins are sorted through these sorting pathways. We use a hidden Markov model (HMM) to represent protein sorting pathways. The model is able to determine intermediate sorting states and to assign carrier proteins and motifs to the sorting pathways. In simulation studies, we show that the method can accurately recover an underlying sorting model. Using data for yeast, we show that our model leads to accurate prediction of subcellular localization. We also show that the pathways learned by our model recover many known sorting pathways and correctly assign proteins to the path they utilize. The learned model identified new pathways and their putative carriers and motifs and these may represent novel protein sorting mechanisms. Supplementary results and software implementation are available from http://murphylab.web.cmu.edu/software/2010_RECOMB_pathways/.

How Incidental Sequence Learning Creates Reportable Knowledge: The Role of Unexpected Events

ERIC Educational Resources Information Center

Runger, Dennis; Frensch, Peter A.

2008-01-01

Research on incidental sequence learning typically is concerned with the characteristics of implicit or nonconscious learning. In this article, the authors aim to elucidate the cognitive mechanisms that contribute to the generation of explicit, reportable sequence knowledge. According to the unexpected-event hypothesis (P. A. Frensch, H. Haider,…

Visual Sequence Learning in Infancy: Domain-General and Domain-Specific Associations with Language

ERIC Educational Resources Information Center

Shafto, Carissa L.; Conway, Christopher M.; Field, Suzanne L.; Houston, Derek M.

2012-01-01

Research suggests that nonlinguistic sequence learning abilities are an important contributor to language development (Conway, Bauernschmidt, Huang, & Pisoni, 2010). The current study investigated visual sequence learning (VSL) as a possible predictor of vocabulary development in infants. Fifty-eight 8.5-month-old infants were presented with a…

Neural Correlates of Sequence Learning with Stochastic Feedback

ERIC Educational Resources Information Center

Averbeck, Bruno B.; Kilner, James; Frith, Christopher D.

2011-01-01

Although much is known about decision making under uncertainty when only a single step is required in the decision process, less is known about sequential decision making. We carried out a stochastic sequence learning task in which subjects had to use noisy feedback to learn sequences of button presses. We compared flat and hierarchical behavioral…

Formulaic Sequences and the Implications for Second Language Learning

ERIC Educational Resources Information Center

Xu, Qi

2016-01-01

The present paper is a review of literature in relation to formulaic sequences and the implications for second language learning. The formulaic sequence is a significant part of our language, and plays an essential role in both first and second language learning. The paper first introduces the definition, classifications, and major features of…

Serial Reaction Time Learning in Preschool- and School-Age Children.

ERIC Educational Resources Information Center

Thomas, Kathleen M.; Nelson, Charles A.

2001-01-01

Two experiments assessed visuomotor sequence learning in 4- to 10-year-olds using a serial reaction time (SRT) task with random and sequenced trials. Found that children demonstrated sequence-specific decreases in RT. Participants with explicit awareness of the sequence at the session's end showed larger sequence-specific RT decrements than…

Perceived facial expressions of emotion as motivational incentives: evidence from a differential implicit learning paradigm.

PubMed

Schultheiss, Oliver C; Pang, Joyce S; Torges, Cynthia M; Wirth, Michelle M; Treynor, Wendy; Derryberry, Douglas

2005-03-01

Participants (N = 216) were administered a differential implicit learning task during which they were trained and tested on 3 maximally distinct 2nd-order visuomotor sequences, with sequence color serving as discriminative stimulus. During training, 1 sequence each was followed by an emotional face, a neutral face, and no face, using backward masking. Emotion (joy, surprise, anger), face gender, and exposure duration (12 ms, 209 ms) were varied between participants; implicit motives were assessed with a picture-story exercise. For power-motivated individuals, low-dominance facial expressions enhanced and high-dominance expressions impaired learning. For affiliation-motivated individuals, learning was impaired in the context of hostile faces. These findings did not depend on explicit learning of fixed sequences or on awareness of sequence-face contingencies. Copyright 2005 APA, all rights reserved.

Embedded interruptions and task complexity influence schema-related cognitive load progression in an abstract learning task.

PubMed

Wirzberger, Maria; Esmaeili Bijarsari, Shirin; Rey, Günter Daniel

2017-09-01

Cognitive processes related to schema acquisition comprise an essential source of demands in learning situations. Since the related amount of cognitive load is supposed to change over time, plausible temporal models of load progression based on different theoretical backgrounds are inspected in this study. A total of 116 student participants completed a basal symbol sequence learning task, which provided insights into underlying cognitive dynamics. Two levels of task complexity were determined by the amount of elements within the symbol sequence. In addition, interruptions due to an embedded secondary task occurred at five predefined stages over the task. Within the resulting 2x5-factorial mixed between-within design, the continuous monitoring of efficiency in learning performance enabled assumptions on relevant resource investment. From the obtained results, a nonlinear change of learning efficiency over time seems most plausible in terms of cognitive load progression. Moreover, different effects of the induced interruptions show up in conditions of task complexity, which indicate the activation of distinct cognitive mechanisms related to structural aspects of the task. Findings are discussed in the light of evidence from research on memory and information processing. Copyright © 2017 Elsevier B.V. All rights reserved.

Gradations of awareness in a modified sequence learning task.

PubMed

Norman, Elisabeth; Price, Mark C; Duff, Simon C; Mentzoni, Rune A

2007-12-01

We argue performance in the serial reaction time (SRT) task is associated with gradations of awareness that provide examples of fringe consciousness [Mangan, B. (1993b). Taking phenomenology seriously: the "fringe" and its implications for cognitive research. Consciousness and Cognition, 2, 89-108, Mangan, B. (2003). The conscious "fringe": Bringing William James up to date. In B. J. Baars, W. P. Banks & J. B. Newman (Eds.), Essential sources in the scientific study of consciousness (pp. 741-759). Cambridge, MA: The MIT Press.], and address limitations of the traditional SRT procedure, including criticism of exclusion generation tasks. Two experiments are conducted with a modified SRT procedure where irrelevant stimulus attributes obscure the sequence rule. Our modified paradigm, which includes a novel exclusion task, makes it easier to demonstrate a previously controversial influence of response stimulus interval (RSI) on awareness. It also allows identification of participants showing fringe consciousness rather than explicit sequence knowledge, as reflected by dissociations between different awareness measures. The NEO-PI-R variable Openness to Feelings influenced the diversity of subjective feelings reported during two awareness measures, but not the degree of learning and awareness as previously found with traditional SRT tasks [Norman, E., Price, M. C., & Duff, S. C. (2006). Fringe consciousness in sequence learning: the influence of individual differences. Consciousness and Cognition, 15(4), 723-760.]. This suggests possible distinctions between two components of fringe consciousness.

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task.

PubMed

Du, Yue; Clark, Jane E

2018-05-03

This protocol describes a modified serial reaction time (SRT) task used to study implicit motor sequence learning. Unlike the classic SRT task that involves finger-pressing movements while sitting, the modified SRT task requires participants to step with both feet while maintaining a standing posture. This stepping task necessitates whole body actions that impose postural challenges. The foot-stepping task complements the classic SRT task in several ways. The foot-stepping SRT task is a better proxy for the daily activities that require ongoing postural control, and thus may help us better understand sequence learning in real-life situations. In addition, response time serves as an indicator of sequence learning in the classic SRT task, but it is unclear whether response time, reaction time (RT) representing mental process, or movement time (MT) reflecting the movement itself, is a key player in motor sequence learning. The foot-stepping SRT task allows researchers to disentangle response time into RT and MT, which may clarify how motor planning and movement execution are involved in sequence learning. Lastly, postural control and cognition are interactively related, but little is known about how postural control interacts with learning motor sequences. With a motion capture system, the movement of the whole body (e.g., the center of mass (COM)) can be recorded. Such measures allow us to reveal the dynamic processes underlying discrete responses measured by RT and MT, and may aid in elucidating the relationship between postural control and the explicit and implicit processes involved in sequence learning. Details of the experimental set-up, procedure, and data processing are described. The representative data are adopted from one of our previous studies. Results are related to response time, RT, and MT, as well as the relationship between the anticipatory postural response and the explicit processes involved in implicit motor sequence learning.

Learning curves for transapical transcatheter aortic valve replacement in the PARTNER-I trial: Technical performance, success, and safety.

PubMed

Suri, Rakesh M; Minha, Sa'ar; Alli, Oluseun; Waksman, Ron; Rihal, Charanjit S; Satler, Lowell P; Greason, Kevin L; Torguson, Rebecca; Pichard, Augusto D; Mack, Michael; Svensson, Lars G; Rajeswaran, Jeevanantham; Lowry, Ashley M; Ehrlinger, John; Mick, Stephanie L; Tuzcu, E Murat; Thourani, Vinod H; Makkar, Raj; Holmes, David; Leon, Martin B; Blackstone, Eugene H

2016-09-01

Introduction of hybrid techniques, such as transapical transcatheter aortic valve replacement (TA-TAVR), requires skills that a heart team must master to achieve technical efficiency: the technical performance learning curve. To date, the learning curve for TA-TAVR remains unknown. We therefore evaluated the rate at which technical performance improved, assessed change in occurrence of adverse events in relation to technical performance, and determined whether adverse events after TA-TAVR were linked to acquiring technical performance efficiency (the learning curve). From April 2007 to February 2012, 1100 patients, average age 85.0 ± 6.4 years, underwent TA-TAVR in the PARTNER-I trial. Learning curves were defined by institution-specific patient sequence number using nonlinear mixed modeling. Mean procedure time decreased from 131 to 116 minutes within 30 cases (P = .06) and device success increased to 90% by case 45 (P = .0007). Within 30 days, 354 patients experienced a major adverse event (stroke in 29, death in 96), with possibly decreased complications over time (P ∼ .08). Although longer procedure time was associated with more adverse events (P < .0001), these events were associated with change in patient risk profile, not the technical performance learning curve (P = .8). The learning curve for TA-TAVR was 30 to 45 procedures performed, and technical efficiency was achieved without compromising patient safety. Although fewer patients are now undergoing TAVR via nontransfemoral access, understanding TA-TAVR learning curves and their relationship with outcomes is important as the field moves toward next-generation devices, such as those to replace the mitral valve, delivered via the left ventricular apex. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Evolutionary neural networks for anomaly detection based on the behavior of a program.

PubMed

Han, Sang-Jun; Cho, Sung-Bae

2006-06-01

The process of learning the behavior of a given program by using machine-learning techniques (based on system-call audit data) is effective to detect intrusions. Rule learning, neural networks, statistics, and hidden Markov models (HMMs) are some of the kinds of representative methods for intrusion detection. Among them, neural networks are known for good performance in learning system-call sequences. In order to apply this knowledge to real-world problems successfully, it is important to determine the structures and weights of these call sequences. However, finding the appropriate structures requires very long time periods because there are no suitable analytical solutions. In this paper, a novel intrusion-detection technique based on evolutionary neural networks (ENNs) is proposed. One advantage of using ENNs is that it takes less time to obtain superior neural networks than when using conventional approaches. This is because they discover the structures and weights of the neural networks simultaneously. Experimental results with the 1999 Defense Advanced Research Projects Agency (DARPA) Intrusion Detection Evaluation (IDEVAL) data confirm that ENNs are promising tools for intrusion detection.

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

PubMed Central

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-01-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. PMID:29652405

Is Motor Learning Mediated by tDCS Intensity?

PubMed Central

van den Berg, Femke E.; Nitsche, Michael A.; Thijs, Herbert; Wenderoth, Nicole; Meesen, Raf L. J.

2013-01-01

Although tDCS has been shown to improve motor learning, previous studies reported rather small effects. Since physiological effects of tDCS depend on intensity, the present study evaluated this parameter in order to enhance the effect of tDCS on skill acquisition. The effect of different stimulation intensities of anodal tDCS (atDCS) was investigated in a double blind, sham controlled crossover design. In each condition, thirteen healthy subjects were instructed to perform a unimanual motor (sequence) learning task. Our results showed (1) a significant increase in the slope of the learning curve and (2) a significant improvement in motor performance at retention for 1.5 mA atDCS as compared to sham tDCS. No significant differences were reported between 1 mA atDCS and sham tDCS; and between 1.5 mA atDCS and 1 mA atDCS. PMID:23826272

Simulation-Based Evaluation of Learning Sequences for Instructional Technologies

ERIC Educational Resources Information Center

McEneaney, John E.

2016-01-01

Instructional technologies critically depend on systematic design, and learning hierarchies are a commonly advocated tool for designing instructional sequences. But hierarchies routinely allow numerous sequences and choosing an optimal sequence remains an unsolved problem. This study explores a simulation-based approach to modeling learning…

Tracking Plasticity: Effects of Long-Term Rehearsal in Expert Dancers Encoding Music to Movement

PubMed Central

Bar, Rachel J.; DeSouza, Joseph F. X.

2016-01-01

Our knowledge of neural plasticity suggests that neural networks show adaptation to environmental and intrinsic change. In particular, studies investigating the neuroplastic changes associated with learning and practicing motor tasks have shown that practicing such tasks results in an increase in neural activation in several specific brain regions. However, studies comparing experts and non-experts suggest that experts employ less neuronal activation than non-experts when performing a familiar motor task. Here, we aimed to determine the long-term changes in neural networks associated with learning a new dance in professional ballet dancers over 34 weeks. Subjects visualized dance movements to music while undergoing fMRI scanning at four time points over 34-weeks. Results demonstrated that initial learning and performance at seven weeks led to increases in activation in cortical regions during visualization compared to the first week. However, at 34 weeks, the cortical networks showed reduced activation compared to week seven. Specifically, motor learning and performance over the 34 weeks showed the typical inverted-U-shaped function of learning. Further, our result demonstrate that learning of a motor sequence of dance movements to music in the real world can be visualized by expert dancers using fMRI and capture highly significant modeled fits of the brain network variance of BOLD signals from early learning to expert level performance. PMID:26824475

Development of a State Machine Sequencer for the Keck Interferometer: Evolution, Development and Lessons Learned using a CASE Tool Approach

NASA Technical Reports Server (NTRS)

Rede, Leonard J.; Booth, Andrew; Hsieh, Jonathon; Summer, Kellee

2004-01-01

This paper presents a discussion of the evolution of a sequencer from a simple EPICS (Experimental Physics and Industrial Control System) based sequencer into a complex implementation designed utilizing UML (Unified Modeling Language) methodologies and a CASE (Computer Aided Software Engineering) tool approach. The main purpose of the sequencer (called the IF Sequencer) is to provide overall control of the Keck Interferometer to enable science operations be carried out by a single operator (and/or observer). The interferometer links the two 10m telescopes of the W. M. Keck Observatory at Mauna Kea, Hawaii. The IF Sequencer is a high-level, multi-threaded, Hare1 finite state machine, software program designed to orchestrate several lower-level hardware and software hard real time subsystems that must perform their work in a specific and sequential order. The sequencing need not be done in hard real-time. Each state machine thread commands either a high-speed real-time multiple mode embedded controller via CORB A, or slower controllers via EPICS Channel Access interfaces. The overall operation of the system is simplified by the automation. The UML is discussed and our use of it to implement the sequencer is presented. The decision to use the Rhapsody product as our CASE tool is explained and reflected upon. Most importantly, a section on lessons learned is presented and the difficulty of integrating CASE tool automatically generated C++ code into a large control system consisting of multiple infrastructures is presented.

Development of a state machine sequencer for the Keck Interferometer: evolution, development, and lessons learned using a CASE tool approach

NASA Astrophysics Data System (ADS)

Reder, Leonard J.; Booth, Andrew; Hsieh, Jonathan; Summers, Kellee R.

2004-09-01

This paper presents a discussion of the evolution of a sequencer from a simple Experimental Physics and Industrial Control System (EPICS) based sequencer into a complex implementation designed utilizing UML (Unified Modeling Language) methodologies and a Computer Aided Software Engineering (CASE) tool approach. The main purpose of the Interferometer Sequencer (called the IF Sequencer) is to provide overall control of the Keck Interferometer to enable science operations to be carried out by a single operator (and/or observer). The interferometer links the two 10m telescopes of the W. M. Keck Observatory at Mauna Kea, Hawaii. The IF Sequencer is a high-level, multi-threaded, Harel finite state machine software program designed to orchestrate several lower-level hardware and software hard real-time subsystems that must perform their work in a specific and sequential order. The sequencing need not be done in hard real-time. Each state machine thread commands either a high-speed real-time multiple mode embedded controller via CORBA, or slower controllers via EPICS Channel Access interfaces. The overall operation of the system is simplified by the automation. The UML is discussed and our use of it to implement the sequencer is presented. The decision to use the Rhapsody product as our CASE tool is explained and reflected upon. Most importantly, a section on lessons learned is presented and the difficulty of integrating CASE tool automatically generated C++ code into a large control system consisting of multiple infrastructures is presented.

The key to success in elite athletes? Explicit and implicit motor learning in youth elite and non-elite soccer players.

PubMed

Verburgh, L; Scherder, E J A; van Lange, P A M; Oosterlaan, J

2016-09-01

In sports, fast and accurate execution of movements is required. It has been shown that implicitly learned movements might be less vulnerable than explicitly learned movements to stressful and fast changing circumstances that exist at the elite sports level. The present study provides insight in explicit and implicit motor learning in youth soccer players with different expertise levels. Twenty-seven youth elite soccer players and 25 non-elite soccer players (aged 10-12) performed a serial reaction time task (SRTT). In the SRTT, one of the sequences must be learned explicitly, the other was implicitly learned. No main effect of group was found for implicit and explicit learning on mean reaction time (MRT) and accuracy. However, for MRT, an interaction was found between learning condition, learning phase and group. Analyses showed no group effects for the explicit learning condition, but youth elite soccer players showed better learning in the implicit learning condition. In particular, during implicit motor learning youth elite soccer showed faster MRTs in the early learning phase and earlier reached asymptote performance in terms of MRT. Present findings may be important for sports because children with superior implicit learning abilities in early learning phases may be able to learn more (durable) motor skills in a shorter time period as compared to other children.

A single night of sleep loss impairs objective but not subjective working memory performance in a sex-dependent manner.

PubMed

Rångtell, Frida H; Karamchedu, Swathy; Andersson, Peter; Liethof, Lisanne; Olaya Búcaro, Marcela; Lampola, Lauri; Schiöth, Helgi B; Cedernaes, Jonathan; Benedict, Christian

2018-01-31

Acute sleep deprivation can lead to judgement errors and thereby increases the risk of accidents, possibly due to an impaired working memory. However, whether the adverse effects of acute sleep loss on working memory are modulated by auditory distraction in women and men are not known. Additionally, it is unknown whether sleep loss alters the way in which men and women perceive their working memory performance. Thus, 24 young adults (12 women using oral contraceptives at the time of investigation) participated in two experimental conditions: nocturnal sleep (scheduled between 22:30 and 06:30 hours) versus one night of total sleep loss. Participants were administered a digital working memory test in which eight-digit sequences were learned and retrieved in the morning after each condition. Learning of digital sequences was accompanied by either silence or auditory distraction (equal distribution among trials). After sequence retrieval, each trial ended with a question regarding how certain participants were of the correctness of their response, as a self-estimate of working memory performance. We found that sleep loss impaired objective but not self-estimated working memory performance in women. In contrast, both measures remained unaffected by sleep loss in men. Auditory distraction impaired working memory performance, without modulation by sleep loss or sex. Being unaware of cognitive limitations when sleep-deprived, as seen in our study, could lead to undesirable consequences in, for example, an occupational context. Our findings suggest that sleep-deprived young women are at particular risk for overestimating their working memory performance. © 2018 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.

Evaluating and redesigning teaching learning sequences at the introductory physics level

NASA Astrophysics Data System (ADS)

Guisasola, Jenaro; Zuza, Kristina; Ametller, Jaume; Gutierrez-Berraondo, José

2017-12-01

In this paper we put forward a proposal for the design and evaluation of teaching and learning sequences in upper secondary school and university. We will connect our proposal with relevant contributions on the design of teaching sequences, ground it on the design-based research methodology, and discuss how teaching and learning sequences designed according to our proposal relate to learning progressions. An iterative methodology for evaluating and redesigning the teaching and learning sequence (TLS) is presented. The proposed assessment strategy focuses on three aspects: (a) evaluation of the activities of the TLS, (b) evaluation of learning achieved by students in relation to the intended objectives, and (c) a document for gathering the difficulties found when implementing the TLS to serve as a guide to teachers. Discussion of this guide with external teachers provides feedback used for the TLS redesign. The context of our implementation and evaluation is an innovative calculus-based physics course for first-year engineering and science degree students at the University of the Basque Country.

Domain-general sequence learning deficit in specific language impairment.

PubMed

Lukács, Agnes; Kemény, Ferenc

2014-05-01

Grammar-specific accounts of specific language impairment (SLI) have been challenged by recent claims that language problems are a consequence of impairments in domain-general mechanisms of learning that also play a key role in the process of language acquisition. Our studies were designed to test the generality and nature of this learning deficit by focusing on both sequential and nonsequential, and on verbal and nonverbal, domains. Twenty-nine children with SLI were compared with age-matched typically developing (TD) control children using (a) a serial reaction time task (SRT), testing the learning of motor sequences; (b) an artificial grammar learning (AGL) task, testing the extraction of regularities from auditory sequences; and (c) a weather prediction task (WP), testing probabilistic category learning in a nonsequential task. For the 2 sequence learning tasks, a significantly smaller proportion of children showed evidence of learning in the SLI than in the TD group (χ2 tests, p < .001 for the SRT task, p < .05 for the AGL task), whereas the proportion of learners on the WP task was the same in the 2 groups. The level of learning for SLI learners was comparable with that of TD children on all tasks (with great individual variation). Taken together, these findings suggest that domain-general processes of implicit sequence learning tend to be impaired in SLI. Further research is needed to clarify the relationship of deficits in implicit learning and language.

Incidental and Intentional Sequence Learning in Youth-Onset Psychosis and Attention-Deficit/Hyperactivity Disorder (ADHD)

PubMed Central

Karatekin, Canan; White, Tonya; Bingham, Christopher

2009-01-01

The goal was to compare incidental and intentional spatial sequence learning in youth-onset psychosis and ADHD. We tested 8- to 19-year-olds with psychosis or ADHD and healthy controls on a serial reaction time (RT) task and used manual and oculomotor measures to examine learning. Participants were also administered a block in which they were explicitly instructed to learn a sequence. As in our previous studies with healthy adults and children, oculomotor anticipations and RTs showed learning effects similar to those in the manual modality. Results showed intact sequence-specific learning but fewer oculomotor anticipations in both clinical groups during incidental learning. In intentional learning, only the psychosis group showed impairments compared to controls. There were no interactions between age and diagnosis. Thus, the psychosis group showed relatively preserved incidental learning despite impairments in intentional learning. Additionally, both clinical groups showed impairments in the ability to search for, extract, and anticipate regularities (whether the regularities were there or not), but not in the ability to respond to these regularities when they were there. PMID:19586209

Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites

PubMed Central

Meinicke, Peter; Tech, Maike; Morgenstern, Burkhard; Merkl, Rainer

2004-01-01

Background Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying biological signals. Results We propose a kernel-based approach to datamining on biological sequences. With our method it is possible to model and analyze positional variability of oligomers of any length in a natural way. On one hand this is achieved by mapping the sequences to an intuitive but high-dimensional feature space, well-suited for interpretation of the learnt models. On the other hand, by means of the kernel trick we can provide a general learning algorithm for that high-dimensional representation because all required statistics can be computed without performing an explicit feature space mapping of the sequences. By introducing a kernel parameter that controls the degree of position-dependency, our feature space representation can be tailored to the characteristics of the biological problem at hand. A regularized learning scheme enables application even to biological problems for which only small sets of example sequences are available. Our approach includes a visualization method for transparent representation of characteristic sequence features. Thereby importance of features can be measured in terms of discriminative strength with respect to classification of the underlying sequences. To demonstrate and validate our concept on a biochemically well-defined case, we analyze E. coli translation initiation sites in order to show that we can find biologically relevant signals. For that case, our results clearly show that the Shine-Dalgarno sequence is the most important signal upstream a start codon. The variability in position and composition we found for that signal is in accordance with previous biological knowledge. We also find evidence for signals downstream of the start codon, previously introduced as transcriptional enhancers. These signals are mainly characterized by occurrences of adenine in a region of about 4 nucleotides next to the start codon. Conclusions We showed that the oligo kernel can provide a valuable tool for the analysis of relevant signals in biological sequences. In the case of translation initiation sites we could clearly deduce the most discriminative motifs and their positional variation from example sequences. Attractive features of our approach are its flexibility with respect to oligomer length and position conservation. By means of these two parameters oligo kernels can easily be adapted to different biological problems. PMID:15511290

Teaching for adaptive expertise in biomedical engineering ethics.

PubMed

Martin, Taylor; Rayne, Karen; Kemp, Nate J; Hart, Jack; Diller, Kenneth R

2005-04-01

This paper considers an approach to teaching ethics in bioengineering based on the How People Learn (HPL) framework. Curricula based on this framework have been effective in mathematics and science instruction from the kindergarten to the college levels. This framework is well suited to teaching bioengineering ethics because it helps learners develop "adaptive expertise". Adaptive expertise refers to the ability to use knowledge and experience in a domain to learn in unanticipated situations. It differs from routine expertise, which requires using knowledge appropriately to solve routine problems. Adaptive expertise is an important educational objective for bioengineers because the regulations and knowledge base in the discipline are likely to change significantly over the course of their careers. This study compares the performance of undergraduate bioengineering students who learned about ethics for stem cell research using the HPL method of instruction to the performance of students who learned following a standard lecture sequence. Both groups learned the factual material equally well, but the HPL group was more prepared to act adaptively when presented with a novel situation.

Frontostriatal and Mediotemporal Lobe Contributions to Implicit Higher-Order Spatial Sequence Learning Declines in Aging and Parkinson’s Disease

PubMed Central

Schendan, Haline E.; Tinaz, Sule; Maher, Stephen M.; Stern, Chantal E.

2015-01-01

Sequence learning depends on the striatal system, but recent findings also implicate the mediotemporal lobe (MTL) system. Schendan, Searl, Melrose, & Stern (2003) found higher-order associative, learning-related activation in the striatum, dorsolateral prefrontal cortex, and the MTL during the early acquisition phase of both implicit and explicit variants of a serial response time task. This functional magnetic resonance imaging (fMRI) study capitalized on this task to determine how changes in MTL function observed in aging and compromised frontostriatal function characteristic of Parkinson’s disease (PD) patients impacts sequence learning and memory under implicit instructions. Brain activity was compared between “Sequence” and “Random” conditions in 12 non-demented PD patients and education and gender matched healthy control participants of whom 12 were age matched (MC) and 14 were younger (YC). Behaviorally, sequence-specific learning of higher-order associations was reduced with aging and changed further with PD and resulted primarily in implicit knowledge in the older participants. FMRI revealed reduced intensity and extent of sequence learning-related activation in older relative to younger people in frontostriatal circuits and the MTL. This was because signal was greater for the Sequence than Random condition in younger people, whereas older people, especially those with PD, showed the opposite pattern. Both older groups also showed increased activation to the task itself relative to baseline fixation. In addition, right MTL showed hypoactivation and left MTL hyperactivation in PD relative to the MC group. The results suggest changes in frontostriatal and MTL activity occur during aging that affect task-related activity and the initial acquisition phase of implicit higher-order sequence learning. In addition, the results suggest that Parkinson’s disease adversely affects processes in the MTL including sequence learning and memory. PMID:23565935

On the Search for Retrotransposons: Alternative Protocols to Obtain Sequences to Learn Profile Hidden Markov Models.

PubMed

Fischer, Carlos N; Campos, Victor De A; Barella, Victor H

2018-05-01

Profile hidden Markov models (pHMMs) have been used to search for transposable elements (TEs) in genomes. For the learning of pHMMs aimed to search for TEs of the retrotransposon class, the conventional protocol is to use the whole internal nucleotide portions of these elements as representative sequences. To further explore the potential of pHMMs in such a search, we propose five alternative ways to obtain the sets of representative sequences of TEs other than the conventional protocol. In this study, we are interested in Bel-PAO, Copia, Gypsy, and DIRS superfamilies from the retrotransposon class. We compared the pHMMs of all six protocols. The test results show that, for each TE superfamily, the pHMMs of at least two of the proposed protocols performed better than the conventional one and that the number of correct predictions provided by the latter can be improved by considering together the results of one or more of the alternative protocols.

A Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data.

PubMed

Pandey, Gaurav; Pandey, Om P; Rogers, Angela J; Ahsen, Mehmet E; Hoffman, Gabriel E; Raby, Benjamin A; Weiss, Scott T; Schadt, Eric E; Bunyavanich, Supinda

2018-06-11

Asthma is a common, under-diagnosed disease affecting all ages. We sought to identify a nasal brush-based classifier of mild/moderate asthma. 190 subjects with mild/moderate asthma and controls underwent nasal brushing and RNA sequencing of nasal samples. A machine learning-based pipeline identified an asthma classifier consisting of 90 genes interpreted via an L2-regularized logistic regression classification model. This classifier performed with strong predictive value and sensitivity across eight test sets, including (1) a test set of independent asthmatic and control subjects profiled by RNA sequencing (positive and negative predictive values of 1.00 and 0.96, respectively; AUC of 0.994), (2) two independent case-control cohorts of asthma profiled by microarray, and (3) five cohorts with other respiratory conditions (allergic rhinitis, upper respiratory infection, cystic fibrosis, smoking), where the classifier had a low to zero misclassification rate. Following validation in large, prospective cohorts, this classifier could be developed into a nasal biomarker of asthma.

Learning predictive statistics from temporal sequences: Dynamics and strategies

PubMed Central

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

2017-01-01

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

Learning predictive statistics from temporal sequences: Dynamics and strategies.

PubMed

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

2017-10-01

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

Learning multiple variable-speed sequences in striatum via cortical tutoring.

PubMed

Murray, James M; Escola, G Sean

2017-05-08

Sparse, sequential patterns of neural activity have been observed in numerous brain areas during timekeeping and motor sequence tasks. Inspired by such observations, we construct a model of the striatum, an all-inhibitory circuit where sequential activity patterns are prominent, addressing the following key challenges: (i) obtaining control over temporal rescaling of the sequence speed, with the ability to generalize to new speeds; (ii) facilitating flexible expression of distinct sequences via selective activation, concatenation, and recycling of specific subsequences; and (iii) enabling the biologically plausible learning of sequences, consistent with the decoupling of learning and execution suggested by lesion studies showing that cortical circuits are necessary for learning, but that subcortical circuits are sufficient to drive learned behaviors. The same mechanisms that we describe can also be applied to circuits with both excitatory and inhibitory populations, and hence may underlie general features of sequential neural activity pattern generation in the brain.

The effects of learning on event-related potential correlates of musical expectancy.

PubMed

Carrión, Ricardo E; Bly, Benjamin Martin

2008-09-01

Musical processing studies have shown that unexpected endings in familiar musical sequences produce extended latencies of the P300 component. The present study sought to identify event-related potential (ERP) correlates of musical expectancy by entraining participants with rule-governed chord sequences and testing whether unexpected endings created similar responses. Two experiments were conducted in which participants performed grammaticality classifications without training (Experiment 1) and with training (Experiment 2). In both experiments, deviant chords differing in instrumental timbre elicited a MMN/P3a waveform complex. Violations related to learned patterns elicited an early right anterior negativity and P3b. Latency and amplitude of peak components were modulated by the physical characteristics of the chords, expectations due to prior knowledge of musical harmony, and contextually defined expectations developed through entrainment.

Verbal implicit sequence learning in persons who stutter and persons with Parkinson's disease.

PubMed

Smits-Bandstra, Sarah; Gracco, Vincent

2013-01-01

The authors investigated the integrity of implicit learning systems in 14 persons with Parkinson's disease (PPD), 14 persons who stutter (PWS), and 14 control participants. In a 120-min session participants completed a verbal serial reaction time task, naming aloud 4 syllables in response to 4 visual stimuli. Unbeknownst to participants, the syllables formed a repeating 8-item sequence. PWS and PPD demonstrated slower reaction times for early but not late learning trials relative to controls reflecting delays but not deficiencies in general learning. PPD also demonstrated less accuracy in general learning relative to controls. All groups demonstrated similar limited explicit sequence knowledge. Both PWS and PPD demonstrated significantly less implicit sequence learning relative to controls, suggesting that stuttering may be associated with compromised functional integrity of the cortico-striato-thalamo-cortical loop.

Procedural learning: A developmental study of motor sequence learning and probabilistic classification learning in school-aged children.

PubMed

Mayor-Dubois, Claire; Zesiger, Pascal; Van der Linden, Martial; Roulet-Perez, Eliane

2016-01-01

In this study, we investigated motor and cognitive procedural learning in typically developing children aged 8-12 years with a serial reaction time (SRT) task and a probabilistic classification learning (PCL) task. The aims were to replicate and extend the results of previous SRT studies, to investigate PCL in school-aged children, to explore the contribution of declarative knowledge to SRT and PCL performance, to explore the strategies used by children in the PCL task via a mathematical model, and to see whether performances obtained in motor and cognitive tasks correlated. The results showed similar learning effects in the three age groups in the SRT and in the first half of the PCL tasks. Participants did not develop explicit knowledge in the SRT task whereas declarative knowledge of the cue-outcome associations correlated with the performances in the second half of the PCL task, suggesting a participation of explicit knowledge after some time of exposure in PCL. An increasing proportion of the optimal strategy use with increasing age was observed in the PCL task. Finally, no correlation appeared between cognitive and motor performance. In conclusion, we extended the hypothesis of age invariance from motor to cognitive procedural learning, which had not been done previously. The ability to adopt more efficient learning strategies with age may rely on the maturation of the fronto-striatal loops. The lack of correlation between performance in the SRT task and the first part of the PCL task suggests dissociable developmental trajectories within the procedural memory system.

Learning viewpoint invariant perceptual representations from cluttered images.

PubMed

Spratling, Michael W

2005-05-01

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

Visual Perceptual Echo Reflects Learning of Regularities in Rapid Luminance Sequences.

PubMed

Chang, Acer Y-C; Schwartzman, David J; VanRullen, Rufin; Kanai, Ryota; Seth, Anil K

2017-08-30

A novel neural signature of active visual processing has recently been described in the form of the "perceptual echo", in which the cross-correlation between a sequence of randomly fluctuating luminance values and occipital electrophysiological signals exhibits a long-lasting periodic (∼100 ms cycle) reverberation of the input stimulus (VanRullen and Macdonald, 2012). As yet, however, the mechanisms underlying the perceptual echo and its function remain unknown. Reasoning that natural visual signals often contain temporally predictable, though nonperiodic features, we hypothesized that the perceptual echo may reflect a periodic process associated with regularity learning. To test this hypothesis, we presented subjects with successive repetitions of a rapid nonperiodic luminance sequence, and examined the effects on the perceptual echo, finding that echo amplitude linearly increased with the number of presentations of a given luminance sequence. These data suggest that the perceptual echo reflects a neural signature of regularity learning.Furthermore, when a set of repeated sequences was followed by a sequence with inverted luminance polarities, the echo amplitude decreased to the same level evoked by a novel stimulus sequence. Crucially, when the original stimulus sequence was re-presented, the echo amplitude returned to a level consistent with the number of presentations of this sequence, indicating that the visual system retained sequence-specific information, for many seconds, even in the presence of intervening visual input. Altogether, our results reveal a previously undiscovered regularity learning mechanism within the human visual system, reflected by the perceptual echo. SIGNIFICANCE STATEMENT How the brain encodes and learns fast-changing but nonperiodic visual input remains unknown, even though such visual input characterizes natural scenes. We investigated whether the phenomenon of "perceptual echo" might index such learning. The perceptual echo is a long-lasting reverberation between a rapidly changing visual input and evoked neural activity, apparent in cross-correlations between occipital EEG and stimulus sequences, peaking in the alpha (∼10 Hz) range. We indeed found that perceptual echo is enhanced by repeatedly presenting the same visual sequence, indicating that the human visual system can rapidly and automatically learn regularities embedded within fast-changing dynamic sequences. These results point to a previously undiscovered regularity learning mechanism, operating at a rate defined by the alpha frequency. Copyright © 2017 the authors 0270-6474/17/378486-12$15.00/0.

Animation control of surface motion capture.

PubMed

Tejera, Margara; Casas, Dan; Hilton, Adrian

2013-12-01

Surface motion capture (SurfCap) of actor performance from multiple view video provides reconstruction of the natural nonrigid deformation of skin and clothing. This paper introduces techniques for interactive animation control of SurfCap sequences which allow the flexibility in editing and interactive manipulation associated with existing tools for animation from skeletal motion capture (MoCap). Laplacian mesh editing is extended using a basis model learned from SurfCap sequences to constrain the surface shape to reproduce natural deformation. Three novel approaches for animation control of SurfCap sequences, which exploit the constrained Laplacian mesh editing, are introduced: 1) space–time editing for interactive sequence manipulation; 2) skeleton-driven animation to achieve natural nonrigid surface deformation; and 3) hybrid combination of skeletal MoCap driven and SurfCap sequence to extend the range of movement. These approaches are combined with high-level parametric control of SurfCap sequences in a hybrid surface and skeleton-driven animation control framework to achieve natural surface deformation with an extended range of movement by exploiting existing MoCap archives. Evaluation of each approach and the integrated animation framework are presented on real SurfCap sequences for actors performing multiple motions with a variety of clothing styles. Results demonstrate that these techniques enable flexible control for interactive animation with the natural nonrigid surface dynamics of the captured performance and provide a powerful tool to extend current SurfCap databases by incorporating new motions from MoCap sequences.

Development of self-compressing BLSOM for comprehensive analysis of big sequence data.

PubMed

Kikuchi, Akihito; Ikemura, Toshimichi; Abe, Takashi

2015-01-01

With the remarkable increase in genomic sequence data from various organisms, novel tools are needed for comprehensive analyses of available big sequence data. We previously developed a Batch-Learning Self-Organizing Map (BLSOM), which can cluster genomic fragment sequences according to phylotype solely dependent on oligonucleotide composition and applied to genome and metagenomic studies. BLSOM is suitable for high-performance parallel-computing and can analyze big data simultaneously, but a large-scale BLSOM needs a large computational resource. We have developed Self-Compressing BLSOM (SC-BLSOM) for reduction of computation time, which allows us to carry out comprehensive analysis of big sequence data without the use of high-performance supercomputers. The strategy of SC-BLSOM is to hierarchically construct BLSOMs according to data class, such as phylotype. The first-layer BLSOM was constructed with each of the divided input data pieces that represents the data subclass, such as phylotype division, resulting in compression of the number of data pieces. The second BLSOM was constructed with a total of weight vectors obtained in the first-layer BLSOMs. We compared SC-BLSOM with the conventional BLSOM by analyzing bacterial genome sequences. SC-BLSOM could be constructed faster than BLSOM and cluster the sequences according to phylotype with high accuracy, showing the method's suitability for efficient knowledge discovery from big sequence data.

Sequence-specific bias correction for RNA-seq data using recurrent neural networks.

PubMed

Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2017-01-25

The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.

Effects of antiepileptic drugs on learning as assessed by a repeated acquisition of response sequences task in rats.

PubMed

Shannon, Harlan E; Love, Patrick L

2007-02-01

Patients with epilepsy can have impaired cognitive abilities. Antiepileptic drugs (AEDs) may contribute to the cognitive deficits observed in patients with epilepsy, and have been shown to induce cognitive impairments in healthy individuals. However, there are few systematic data on the effects of AEDs on specific cognitive domains. We have previously demonstrated that a number of AEDs can impair working memory and attention. The purpose of the present study was to evaluate the effects of AEDs on learning as measured by a repeated acquisition of response sequences task in nonepileptic rats. The GABA-related AEDs phenobarbital and chlordiazepoxide significantly disrupted performance by shifting the learning curve to the right and increasing errors, whereas tiagabine and valproate did not. The sodium channel blockers carbamazepine and phenytoin suppressed responding at higher doses, whereas lamotrigine shifted the learning curve to the right and increased errors, and topiramate was without significant effect. Levetiracetam also shifted the learning curve to the right and increased errors. The disruptions produced by triazolam, chlordiazepoxide, lamotrigine, and levetiracetam were qualitatively similar to the effects of the muscarinic cholinergic receptor antagonist scopolamine. The present results indicate that AEDs can impair learning, but there are differences among AEDs in the magnitude of the disruption in nonepileptic rats, with drugs that enhance GABA receptor function and some that block sodium channels producing the most consistent impairment of learning.

Preferences for learning different types of genome sequencing results among young breast cancer patients: Role of psychological and clinical factors.

PubMed

Kaphingst, Kimberly A; Ivanovich, Jennifer; Lyons, Sarah; Biesecker, Barbara; Dresser, Rebecca; Elrick, Ashley; Matsen, Cindy; Goodman, Melody

2018-01-29

The growing importance of genome sequencing means that patients will increasingly face decisions regarding what results they would like to learn. The present study examined psychological and clinical factors that might affect these preferences. 1,080 women diagnosed with breast cancer at age 40 or younger completed an online survey. We assessed their interest in learning various types of genome sequencing results: risk of preventable disease or unpreventable disease, cancer treatment response, uncertain meaning, risk to relatives' health, and ancestry/physical traits. Multivariable logistic regression was used to examine whether being "very" interested in each result type was associated with clinical factors: BRCA1/2 mutation status, prior genetic testing, family history of breast cancer, and psychological factors: cancer recurrence worry, genetic risk worry, future orientation, health information orientation, and genome sequencing knowledge. The proportion of respondents who were very interested in learning each type of result ranged from 16% to 77%. In all multivariable models, those who were very interested in learning a result type had significantly higher knowledge about sequencing benefits, greater genetic risks worry, and stronger health information orientation compared to those with less interest (p-values < .05). Our findings indicate that high interest in return of various types of genome sequencing results was more closely related to psychological factors. Shared decision-making approaches that increase knowledge about genome sequencing and incorporate patient preferences for health information and learning about genetic risks may help support patients' informed choices about learning different types of sequencing results. © Society of Behavioral Medicine 2018.

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

PubMed

Rohrmeier, Martin A; Cross, Ian

2014-07-01

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

The Effect of Old Age on Supra-Span Learning of Visuo-Spatial Sequences under Incidental and Intentional Encoding Instructions

ERIC Educational Resources Information Center

Gagnon, Sylvain; Bedard, Marie-Josee; Turcotte, Josee

2005-01-01

Recent findings [Turcotte, Gagnon, & Poirier, 2005. The effect of old age on the learning of supra-span sequences. "Psychology and Aging," 20, 251-260.] indicate that incidental learning of visuo-spatial supra-span sequences through immediate serial recall declines with old age (Hebb's paradigm). In this study, we examined whether…

A deep learning pipeline for Indian dance style classification

NASA Astrophysics Data System (ADS)

Dewan, Swati; Agarwal, Shubham; Singh, Navjyoti

2018-04-01

In this paper, we address the problem of dance style classification to classify Indian dance or any dance in general. We propose a 3-step deep learning pipeline. First, we extract 14 essential joint locations of the dancer from each video frame, this helps us to derive any body region location within the frame, we use this in the second step which forms the main part of our pipeline. Here, we divide the dancer into regions of important motion in each video frame. We then extract patches centered at these regions. Main discriminative motion is captured in these patches. We stack the features from all such patches of a frame into a single vector and form our hierarchical dance pose descriptor. Finally, in the third step, we build a high level representation of the dance video using the hierarchical descriptors and train it using a Recurrent Neural Network (RNN) for classification. Our novelty also lies in the way we use multiple representations for a single video. This helps us to: (1) Overcome the RNN limitation of learning small sequences over big sequences such as dance; (2) Extract more data from the available dataset for effective deep learning by training multiple representations. Our contributions in this paper are three-folds: (1) We provide a deep learning pipeline for classification of any form of dance; (2) We prove that a segmented representation of a dance video works well with sequence learning techniques for recognition purposes; (3) We extend and refine the ICD dataset and provide a new dataset for evaluation of dance. Our model performs comparable or better in some cases than the state-of-the-art on action recognition benchmarks.

FrameD: A flexible program for quality check and gene prediction in prokaryotic genomes and noisy matured eukaryotic sequences.

PubMed

Schiex, Thomas; Gouzy, Jérôme; Moisan, Annick; de Oliveira, Yannick

2003-07-01

We describe FrameD, a program that predicts coding regions in prokaryotic and matured eukaryotic sequences. Initially targeted at gene prediction in bacterial GC rich genomes, the gene model used in FrameD also allows to predict genes in the presence of frameshifts and partially undetermined sequences which makes it also very suitable for gene prediction and frameshift correction in unfinished sequences such as EST and EST cluster sequences. Like recent eukaryotic gene prediction programs, FrameD also includes the ability to take into account protein similarity information both in its prediction and its graphical output. Its performances are evaluated on different bacterial genomes. The web site (http://genopole.toulouse.inra.fr/bioinfo/FrameD/FD) allows direct prediction, sequence correction and translation and the ability to learn new models for new organisms.

Strategic cognitive sequencing: a computational cognitive neuroscience approach.

PubMed

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

2013-01-01

We address strategic cognitive sequencing, the "outer loop" of human cognition: how the brain decides what cognitive process to apply at a given moment to solve complex, multistep cognitive tasks. We argue that this topic has been neglected relative to its importance for systematic reasons but that recent work on how individual brain systems accomplish their computations has set the stage for productively addressing how brain regions coordinate over time to accomplish our most impressive thinking. We present four preliminary neural network models. The first addresses how the prefrontal cortex (PFC) and basal ganglia (BG) cooperate to perform trial-and-error learning of short sequences; the next, how several areas of PFC learn to make predictions of likely reward, and how this contributes to the BG making decisions at the level of strategies. The third models address how PFC, BG, parietal cortex, and hippocampus can work together to memorize sequences of cognitive actions from instruction (or "self-instruction"). The last shows how a constraint satisfaction process can find useful plans. The PFC maintains current and goal states and associates from both of these to find a "bridging" state, an abstract plan. We discuss how these processes could work together to produce strategic cognitive sequencing and discuss future directions in this area.

Human Splice-Site Prediction with Deep Neural Networks.

PubMed

Naito, Tatsuhiko

2018-04-18

Accurate splice-site prediction is essential to delineate gene structures from sequence data. Several computational techniques have been applied to create a system to predict canonical splice sites. For classification tasks, deep neural networks (DNNs) have achieved record-breaking results and often outperformed other supervised learning techniques. In this study, a new method of splice-site prediction using DNNs was proposed. The proposed system receives an input sequence data and returns an answer as to whether it is splice site. The length of input is 140 nucleotides, with the consensus sequence (i.e., "GT" and "AG" for the donor and acceptor sites, respectively) in the middle. Each input sequence model is applied to the pretrained DNN model that determines the probability that an input is a splice site. The model consists of convolutional layers and bidirectional long short-term memory network layers. The pretraining and validation were conducted using the data set tested in previously reported methods. The performance evaluation results showed that the proposed method can outperform the previous methods. In addition, the pattern learned by the DNNs was visualized as position frequency matrices (PFMs). Some of PFMs were very similar to the consensus sequence. The trained DNN model and the brief source code for the prediction system are uploaded. Further improvement will be achieved following the further development of DNNs.

Consciousness and the Consolidation of Motor Learning

PubMed Central

Song, Sunbin

2009-01-01

It is no secret that motor learning benefits from repetition. For example, pianists devote countless hours to performing complicated sequences of key presses, and golfers practice their swings thousands of times to reach a level of proficiency. Interestingly, the subsequent waking and sleeping hours after practice also play important roles in motor learning. During this time, a motor skill can consolidate into a more stable form that can lead to improved future performance without intervening practice. Though it is widely believed that sleep is crucial for this consolidation of motor learning, this is not generally true. In many instances only day-time consolidates motor learning, while in other instances neither day-time nor sleep consolidates learning. Recent studies have suggested that conscious awareness during motor training can determine whether sleep or day-time plays a role in consolidation. However, ongoing studies suggest that this explanation is also incomplete. In addition to conscious awareness, attention is an important factor to consider. This review discusses how attention and conscious awareness interact with day and night processes to consolidate a motor memory. PMID:18951924

Starting with Worldviews: A Five-Step Preparatory Approach to Integrative Interdisciplinary Learning

ERIC Educational Resources Information Center

Augsburg, Tanya; Chitewere, Tendai

2013-01-01

In this article we propose a five-step sequenced approach to integrative interdisciplinary learning in undergraduate gateway courses. Drawing from the literature of interdisciplinarity, transformative learning theory, and theories of reflective learning, we utilize a sequence of five steps early in our respective undergraduate gateway courses to…

Operating Characteristics of the Implicit Learning System Supporting Serial Interception Sequence Learning

ERIC Educational Resources Information Center

Sanchez, Daniel J.; Reber, Paul J.

2012-01-01

The memory system that supports implicit perceptual-motor sequence learning relies on brain regions that operate separately from the explicit, medial temporal lobe memory system. The implicit learning system therefore likely has distinct operating characteristics and information processing constraints. To attempt to identify the limits of the…

Improving Adaptive Learning Technology through the Use of Response Times

ERIC Educational Resources Information Center

Mettler, Everett; Massey, Christine M.; Kellman, Philip J.

2011-01-01

Adaptive learning techniques have typically scheduled practice using learners' accuracy and item presentation history. We describe an adaptive learning system (Adaptive Response Time Based Sequencing--ARTS) that uses both accuracy and response time (RT) as direct inputs into sequencing. Response times are used to assess learning strength and…

A Contextualized, Differential Sequence Mining Method to Derive Students' Learning Behavior Patterns

ERIC Educational Resources Information Center

Kinnebrew, John S.; Loretz, Kirk M.; Biswas, Gautam

2013-01-01

Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…

Predictive Caching Using the TDAG Algorithm

NASA Technical Reports Server (NTRS)

Laird, Philip; Saul, Ronald

1992-01-01

We describe how the TDAG algorithm for learning to predict symbol sequences can be used to design a predictive cache store. A model of a two-level mass storage system is developed and used to calculate the performance of the cache under various conditions. Experimental simulations provide good confirmation of the model.

Math 3008--Developmental Mathematics II. Course Outline.

ERIC Educational Resources Information Center

New York Inst. of Tech., Old Westbury.

This document contains the course syllabus and 12 independent practice modules for an introductory college algebra course designed to develop student proficiency in the basic algebraic skills. This is designed as the second of a two-semester sequence. Topics include performing operations with radicals and exponents; learning to solve equations;…

Algebraic Procedures and Creative Thinking

ERIC Educational Resources Information Center

Tabach, Michal; Friedlander, Alex

2017-01-01

Simplifying symbolic expressions is usually perceived in middle school algebra as an algorithmic activity, achieved by performing sequences of short drill-and-practice tasks, which have little to do with conceptual learning or with creative mathematical thinking. The aim of this study is to explore possible ways by which ninth-grade students can…

Melodic Priming of Motor Sequence Performance: The Role of the Dorsal Premotor Cortex.

PubMed

Stephan, Marianne A; Brown, Rachel; Lega, Carlotta; Penhune, Virginia

2016-01-01

The purpose of this study was to determine whether exposure to specific auditory sequences leads to the induction of new motor memories and to investigate the role of the dorsal premotor cortex (dPMC) in this crossmodal learning process. Fifty-two young healthy non-musicians were familiarized with the sound to key-press mapping on a computer keyboard and tested on their baseline motor performance. Each participant received subsequently either continuous theta burst stimulation (cTBS) or sham stimulation over the dPMC and was then asked to remember a 12-note melody without moving. For half of the participants, the contour of the melody memorized was congruent to a subsequently performed, but never practiced, finger movement sequence (Congruent group). For the other half, the melody memorized was incongruent to the subsequent finger movement sequence (Incongruent group). Hearing a congruent melody led to significantly faster performance of a motor sequence immediately thereafter compared to hearing an incongruent melody. In addition, cTBS speeded up motor performance in both groups, possibly by relieving motor consolidation from interference by the declarative melody memorization task. Our findings substantiate recent evidence that exposure to a movement-related tone sequence can induce specific, crossmodal encoding of a movement sequence representation. They further suggest that cTBS over the dPMC may enhance early offline procedural motor skill consolidation in cognitive states where motor consolidation would normally be disturbed by concurrent declarative memory processes. These findings may contribute to a better understanding of auditory-motor system interactions and have implications for the development of new motor rehabilitation approaches using sound and non-invasive brain stimulation as neuromodulatory tools.

Deep ART Neural Model for Biologically Inspired Episodic Memory and Its Application to Task Performance of Robots.

PubMed

Park, Gyeong-Moon; Yoo, Yong-Ho; Kim, Deok-Hwa; Kim, Jong-Hwan; Gyeong-Moon Park; Yong-Ho Yoo; Deok-Hwa Kim; Jong-Hwan Kim; Yoo, Yong-Ho; Park, Gyeong-Moon; Kim, Jong-Hwan; Kim, Deok-Hwa

2018-06-01

Robots are expected to perform smart services and to undertake various troublesome or difficult tasks in the place of humans. Since these human-scale tasks consist of a temporal sequence of events, robots need episodic memory to store and retrieve the sequences to perform the tasks autonomously in similar situations. As episodic memory, in this paper we propose a novel Deep adaptive resonance theory (ART) neural model and apply it to the task performance of the humanoid robot, Mybot, developed in the Robot Intelligence Technology Laboratory at KAIST. Deep ART has a deep structure to learn events, episodes, and even more like daily episodes. Moreover, it can retrieve the correct episode from partial input cues robustly. To demonstrate the effectiveness and applicability of the proposed Deep ART, experiments are conducted with the humanoid robot, Mybot, for performing the three tasks of arranging toys, making cereal, and disposing of garbage.

Guidelines for Instructional Sequencing in Emotional Literacy Learning Using PATHS Curriculum as an Example.

ERIC Educational Resources Information Center

Wu, Yann-Shya

The purpose of this paper is to provide guidance for instructional sequencing in emotional literacy curricula. First, the concepts of instructional sequence and the problems involved with instructional sequence in the affective domain of learning are addressed. Then, through the analysis of the emotional literacy curriculum, Promoting Alternative…

Integrated and Independent Learning of Hand-Related Constituent Sequences

ERIC Educational Resources Information Center

Berner, Michael P.; Hoffmann, Joachim

2009-01-01

In almost all daily activities fingers of both hands are used in coordinated succession. The present experiments explored whether learning in such tasks pertains not only to the overall sequence spanning both hands but also to the constituent sequences of each hand. In a serial reaction time task, 2 repeating hand-related sequences were…

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

An investigation of the impact of science course sequencing on student performance in high school science and math

NASA Astrophysics Data System (ADS)

Mary, Michael Todd

High school students in the United States for the past century have typically taken science courses in a sequence of biology followed by chemistry and concluding with physics. An alternative sequence, typically referred to as "physics first" inverts the traditional sequence by having students begin with physics and end with biology. Proponents of physics first cite advances in biological sciences that have dramatically changed the nature of high school biology and the potential benefit to student learning in math that would accompany taking an algebra-based physics course in the early years of high school to support changing the sequence. Using a quasi-experimental, quantitative research design, the purpose of this study was to investigate the impact of science course sequencing on student achievement in math and science at a school district that offered both course sequences. The Texas state end-of-course exams in biology, chemistry, physics, algebra I and geometry were used as the instruments measuring student achievement in math and science at the end of each academic year. Various statistical models were used to analyze these achievement data. The conclusion was, for students in this study, the sequence in which students took biology, chemistry, and physics had little or no impact on performance on the end-of-course assessments in each of these courses. Additionally there was only a minimal effect found with respect to math performance, leading to the conclusion that neither the traditional or "physics first" science course sequence presented an advantage for student achievement in math or science.

Auditory and visual sequence learning in humans and monkeys using an artificial grammar learning paradigm.

PubMed

Milne, Alice E; Petkov, Christopher I; Wilson, Benjamin

2017-07-05

Language flexibly supports the human ability to communicate using different sensory modalities, such as writing and reading in the visual modality and speaking and listening in the auditory domain. Although it has been argued that nonhuman primate communication abilities are inherently multisensory, direct behavioural comparisons between human and nonhuman primates are scant. Artificial grammar learning (AGL) tasks and statistical learning experiments can be used to emulate ordering relationships between words in a sentence. However, previous comparative work using such paradigms has primarily investigated sequence learning within a single sensory modality. We used an AGL paradigm to evaluate how humans and macaque monkeys learn and respond to identically structured sequences of either auditory or visual stimuli. In the auditory and visual experiments, we found that both species were sensitive to the ordering relationships between elements in the sequences. Moreover, the humans and monkeys produced largely similar response patterns to the visual and auditory sequences, indicating that the sequences are processed in comparable ways across the sensory modalities. These results provide evidence that human sequence processing abilities stem from an evolutionarily conserved capacity that appears to operate comparably across the sensory modalities in both human and nonhuman primates. The findings set the stage for future neurobiological studies to investigate the multisensory nature of these sequencing operations in nonhuman primates and how they compare to related processes in humans. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Use of low frequency repetitive transcranial magnetic stimulation to reduce context-dependent learning in people with Parkinson's disease.

PubMed

Lee, Ya-Yun; Fisher, Beth E

2017-05-22

Compared with age-matched non-disabled adults, people with Parkinson's disease (PD) demonstrated greater context-dependent learning, a phenomenon in which an individual shows inferior motor performance when the testing environmental context is different from the original practice context. Additionally, enhanced context- dependency has been shown to be associated with an increased activation of the dorsolateral prefrontal cortex (DLPFC). This study aimed to determine whether context-dependent learning in people with PD could be reduced by decreasing DLPFC activation with low frequency repetitive transcranial magnetic stimulation (rTMS). Quasi-experimental pre-post test controlled study. University laboratory. Twenty-seven participants (18 individuals with PD and 9 age-matched non- disabled adults) were recruited into the PD, PD_rTMS (PD participants who received low frequency rTMS), and Control groups. All participants practiced a finger sequence task containing 3 sequences embedded within specific contexts (colored circles and spatial location on a computer screen) on the first day. On day 2, the participants were tested under the SWITCH and SAME conditions. In the SWITCH condition, the sequence-context association changed from that of practice; in the SAME condition, the sequence-context association remained the same as practice. The PD_rTMS group received 1 Hz rTMS applied over the left DLPFC on the second day before the testing conditions. Switch cost, the performance difference between the SWITCH and SAME conditions, was calculated to indicate context-dependency. All participants improved throughout practice on the first day. Analysis of the switch cost revealed a significant group main effect (p = 0.050). Post-hoc analysis revealed that the PD_rTMS group had significantly smaller switch cost than the PD group (p = 0.031) but not the Control group. Low frequency rTMS applied over DLPFC reduced context-dependency in people with PD. The findings provide a preliminary evidence of using low frequency rTMS as an adjuvant intervention approach to facilitate individuals with PD to generalize a learned motor task from one environmental context to another.

Oculomotor and Manual Indexes of Incidental and Intentional Spatial Sequence Learning during Middle Childhood and Adolescence

ERIC Educational Resources Information Center

Karatekin, Canan; Marcus, David J.; White, Tonya

2007-01-01

The goal of this study was to examine incidental and intentional spatial sequence learning during middle childhood and adolescence. We tested four age groups (8-10 years, 11-13 years, 14-17 years, and young adults [18+ years]) on a serial reaction time task and used manual and oculomotor measures to examine incidental sequence learning.…

Scaling of theory-of-mind understandings in Chinese children.

PubMed

Wellman, Henry M; Fang, Fuxi; Liu, David; Zhu, Liqi; Liu, Guoxiong

2006-12-01

Prior research demonstrates that understanding of theory of mind develops at different paces in children raised in different cultures. Are these differences simply differences in timing, or do they represent different patterns of cultural learning? That is, to what extent are sequences of theory-of-mind understanding universal, and to what extent are they culture-specific? We addressed these questions by using a theory-of-mind scale to examine performance of 140 Chinese children living in Beijing and to compare their performance with that of 135 English-speaking children living in the United States and Australia. Results reveal a common sequence of understanding, as well as sociocultural differences in children's developing theories of mind.

Development of a water-escape motivated version of the Stone T-maze for mice

PubMed Central

Pistell, Paul J.; Ingram, Donald K.

2014-01-01

Mice provide a highly valuable resource for investigating learning and memory processes; however, many of the established tasks for evaluating learning and memory were developed for rats. Behaviors of mice in these tasks appear to be driven by different motivational factors, and as a result, they often do not perform reliably on tasks involving rewards traditionally used for rats. Because of difficulties in measuring learning and memory in mice as well as the need to have a task that can reliably measure these behavioral processes, we have developed a mouse version of the Stone T-maze utilizing what appears to be the primary motivation of mice, escape to a safe location. Specifically, we have constructed a task that requires the mouse to wade through water to reach a dark and dry goal box. To escape this aversive environment, the Stone T-maze requires learning the correct sequence of 13 left and right turns to reach the goal box. Through a series of experiments examining a variety of protocols, it was found that mice will reliably perform this task. This task can be used to assess learning and memory without the potential performance confounds that can affect performance of mice in other tasks. We believe this task offers a valuable new tool for evaluating learning and memory in mice not previously available to researchers. PMID:20026250

The Impact of Protein Structure and Sequence Similarity on the Accuracy of Machine-Learning Scoring Functions for Binding Affinity Prediction

PubMed Central

Peng, Jiangjun; Leung, Yee; Leung, Kwong-Sak; Wong, Man-Hon; Lu, Gang; Ballester, Pedro J.

2018-01-01

It has recently been claimed that the outstanding performance of machine-learning scoring functions (SFs) is exclusively due to the presence of training complexes with highly similar proteins to those in the test set. Here, we revisit this question using 24 similarity-based training sets, a widely used test set, and four SFs. Three of these SFs employ machine learning instead of the classical linear regression approach of the fourth SF (X-Score which has the best test set performance out of 16 classical SFs). We have found that random forest (RF)-based RF-Score-v3 outperforms X-Score even when 68% of the most similar proteins are removed from the training set. In addition, unlike X-Score, RF-Score-v3 is able to keep learning with an increasing training set size, becoming substantially more predictive than X-Score when the full 1105 complexes are used for training. These results show that machine-learning SFs owe a substantial part of their performance to training on complexes with dissimilar proteins to those in the test set, against what has been previously concluded using the same data. Given that a growing amount of structural and interaction data will be available from academic and industrial sources, this performance gap between machine-learning SFs and classical SFs is expected to enlarge in the future. PMID:29538331

The Impact of Protein Structure and Sequence Similarity on the Accuracy of Machine-Learning Scoring Functions for Binding Affinity Prediction.

PubMed

Li, Hongjian; Peng, Jiangjun; Leung, Yee; Leung, Kwong-Sak; Wong, Man-Hon; Lu, Gang; Ballester, Pedro J

2018-03-14

It has recently been claimed that the outstanding performance of machine-learning scoring functions (SFs) is exclusively due to the presence of training complexes with highly similar proteins to those in the test set. Here, we revisit this question using 24 similarity-based training sets, a widely used test set, and four SFs. Three of these SFs employ machine learning instead of the classical linear regression approach of the fourth SF (X-Score which has the best test set performance out of 16 classical SFs). We have found that random forest (RF)-based RF-Score-v3 outperforms X-Score even when 68% of the most similar proteins are removed from the training set. In addition, unlike X-Score, RF-Score-v3 is able to keep learning with an increasing training set size, becoming substantially more predictive than X-Score when the full 1105 complexes are used for training. These results show that machine-learning SFs owe a substantial part of their performance to training on complexes with dissimilar proteins to those in the test set, against what has been previously concluded using the same data. Given that a growing amount of structural and interaction data will be available from academic and industrial sources, this performance gap between machine-learning SFs and classical SFs is expected to enlarge in the future.

Implicit learning of non-spatial sequences in schizophrenia

PubMed Central

MARVEL, CHERIE L.; SCHWARTZ, BARBARA L.; HOWARD, DARLENE V.; HOWARD, JAMES H.

2006-01-01

Recent studies have reported abnormal implicit learning of sequential patterns in patients with schizophrenia. Because these studies were based on visuospatial cues, the question remained whether patients were impaired simply due to the demands of spatial processing. This study examined implicit sequence learning in 24 patients with schizophrenia and 24 healthy controls using a non-spatial variation of the serial reaction time test (SRT) in which pattern stimuli alternated with random stimuli on every other trial. Both groups showed learning by responding faster and more accurately to pattern trials than to random trials. Patients, however, showed a smaller magnitude of sequence learning. Both groups were unable to demonstrate explicit knowledge of the nature of the pattern, confirming that learning occurred without awareness. Clinical variables were not correlated with the patients' learning deficits. Patients with schizophrenia have a decreased ability to develop sensitivity to regularly occurring sequences of events within their environment. This type of deficit may affect an array of cognitive and motor functions that rely on the perception of event regularity. PMID:16248901

Improving Protein Fold Recognition by Deep Learning Networks.

PubMed

Jo, Taeho; Hou, Jie; Eickholt, Jesse; Cheng, Jianlin

2015-12-04

For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl's benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.

Implicit Learning of Predictive Relationships in Three-element Visual Sequences by Young and Old Adults

PubMed Central

Howard, James H.; Howard, Darlene V.; Dennis, Nancy A.; Kelly, Andrew J.

2008-01-01

Knowledge of sequential relationships enables future events to be anticipated and processed efficiently. Research with the serial reaction time task (SRTT) has shown that sequence learning often occurs implicitly without effort or awareness. Here we report four experiments that use a triplet-learning task (TLT) to investigate sequence learning in young and older adults. In the TLT people respond only to the last target event in a series of discrete, three-event sequences or triplets. Target predictability is manipulated by varying the triplet frequency (joint probability) and/or the statistical relationships (conditional probabilities) among events within the triplets. Results revealed that both groups learned, though older adults showed less learning of both joint and conditional probabilities. Young people used the statistical information in both cues, but older adults relied primarily on information in the second cue alone. We conclude that the TLT complements and extends the SRTT and other tasks by offering flexibility in the kinds of sequential statistical regularities that may be studied as well as by controlling event timing and eliminating motor response sequencing. PMID:18763897

Abstract feature codes: The building blocks of the implicit learning system.

PubMed

Eberhardt, Katharina; Esser, Sarah; Haider, Hilde

2017-07-01

According to the Theory of Event Coding (TEC; Hommel, Müsseler, Aschersleben, & Prinz, 2001), action and perception are represented in a shared format in the cognitive system by means of feature codes. In implicit sequence learning research, it is still common to make a conceptual difference between independent motor and perceptual sequences. This supposedly independent learning takes place in encapsulated modules (Keele, Ivry, Mayr, Hazeltine, & Heuer 2003) that process information along single dimensions. These dimensions have remained underspecified so far. It is especially not clear whether stimulus and response characteristics are processed in separate modules. Here, we suggest that feature dimensions as they are described in the TEC should be viewed as the basic content of modules of implicit learning. This means that the modules process all stimulus and response information related to certain feature dimensions of the perceptual environment. In 3 experiments, we investigated by means of a serial reaction time task the nature of the basic units of implicit learning. As a test case, we used stimulus location sequence learning. The results show that a stimulus location sequence and a response location sequence cannot be learned without interference (Experiment 2) unless one of the sequences can be coded via an alternative, nonspatial dimension (Experiment 3). These results support the notion that spatial location is one module of the implicit learning system and, consequently, that there are no separate processing units for stimulus versus response locations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Progressive Dictionary Learning with Hierarchical Predictive Structure for Scalable Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Xiong, Hongkai; Jiang, Xiaoqian; Zou, Junni; Taubman, David

2017-04-12

Dictionary learning has emerged as a promising alternative to the conventional hybrid coding framework. However, the rigid structure of sequential training and prediction degrades its performance in scalable video coding. This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers (ELs) with a guarantee of reconstruction performance. The overcomplete dictionary is trained to adaptively capture local structures along motion trajectories as well as exploit the correlations between neighboring layers of resolutions. Furthermore, progressive dictionary learning is developed to enable the scalability in temporal domain and restrict the error propagation in a close-loop predictor. Under the hierarchical predictive structure, online learning is leveraged to guarantee the training and prediction performance with an improved convergence rate. To accommodate with the stateof- the-art scalable extension of H.264/AVC and latest HEVC, standardized codec cores are utilized to encode the base and enhancement layers. Experimental results show that the proposed method outperforms the latest SHVC and HEVC simulcast over extensive test sequences with various resolutions.

Spiking neural network model for memorizing sequences with forward and backward recall.

PubMed

Borisyuk, Roman; Chik, David; Kazanovich, Yakov; da Silva Gomes, João

2013-06-01

We present an oscillatory network of conductance based spiking neurons of Hodgkin-Huxley type as a model of memory storage and retrieval of sequences of events (or objects). The model is inspired by psychological and neurobiological evidence on sequential memories. The building block of the model is an oscillatory module which contains excitatory and inhibitory neurons with all-to-all connections. The connection architecture comprises two layers. A lower layer represents consecutive events during their storage and recall. This layer is composed of oscillatory modules. Plastic excitatory connections between the modules are implemented using an STDP type learning rule for sequential storage. Excitatory neurons in the upper layer project star-like modifiable connections toward the excitatory lower layer neurons. These neurons in the upper layer are used to tag sequences of events represented in the lower layer. Computer simulations demonstrate good performance of the model including difficult cases when different sequences contain overlapping events. We show that the model with STDP type or anti-STDP type learning rules can be applied for the simulation of forward and backward replay of neural spikes respectively. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Lost in Time and Space: States of High Arousal Disrupt Implicit Acquisition of Spatial and Sequential Context Information

PubMed Central

Maran, Thomas; Sachse, Pierre; Martini, Markus; Weber, Barbara; Pinggera, Jakob; Zuggal, Stefan; Furtner, Marco

2017-01-01

Biased cognition during high arousal states is a relevant phenomenon in a variety of topics: from the development of post-traumatic stress disorders or stress-triggered addictive behaviors to forensic considerations regarding crimes of passion. Recent evidence indicates that arousal modulates the engagement of a hippocampus-based “cognitive” system in favor of a striatum-based “habit” system in learning and memory, promoting a switch from flexible, contextualized to more rigid, reflexive responses. Existing findings appear inconsistent, therefore it is unclear whether and which type of context processing is disrupted by enhanced arousal. In this behavioral study, we investigated such arousal-triggered cognitive-state shifts in human subjects. We validated an arousal induction procedure (three experimental conditions: violent scene, erotic scene, neutral control scene) using pupillometry (Preliminary Experiment, n = 13) and randomly administered this method to healthy young adults to examine whether high arousal states affect performance in two core domains of contextual processing, the acquisition of spatial (spatial discrimination paradigm; Experiment 1, n = 66) and sequence information (learned irrelevance paradigm; Experiment 2, n = 84). In both paradigms, spatial location and sequences were encoded incidentally and both displacements when retrieving spatial position as well as the predictability of the target by a cue in sequence learning changed stepwise. Results showed that both implicit spatial and sequence learning were disrupted during high arousal states, regardless of valence. Compared to the control group, participants in the arousal conditions showed impaired discrimination of spatial positions and abolished learning of associative sequences. Furthermore, Bayesian analyses revealed evidence against the null models. In line with recent models of stress effects on cognition, both experiments provide evidence for decreased engagement of flexible, cognitive systems supporting encoding of context information in active cognition during acute arousal, promoting reduced sensitivity for contextual details. We argue that arousal fosters cognitive adaptation towards less demanding, more present-oriented information processing, which prioritizes a current behavioral response set at the cost of contextual cues. This transient state of behavioral perseverance might reduce reliance on context information in unpredictable environments and thus represent an adaptive response in certain situations. PMID:29170634

Theta oscillations promote temporal sequence learning.

PubMed

Crivelli-Decker, Jordan; Hsieh, Liang-Tien; Clarke, Alex; Ranganath, Charan

2018-05-17

Many theoretical models suggest that neural oscillations play a role in learning or retrieval of temporal sequences, but the extent to which oscillations support sequence representation remains unclear. To address this question, we used scalp electroencephalography (EEG) to examine oscillatory activity over learning of different object sequences. Participants made semantic decisions on each object as they were presented in a continuous stream. For three "Consistent" sequences, the order of the objects was always fixed. Activity during Consistent sequences was compared to "Random" sequences that consisted of the same objects presented in a different order on each repetition. Over the course of learning, participants made faster semantic decisions to objects in Consistent, as compared to objects in Random sequences. Thus, participants were able to use sequence knowledge to predict upcoming items in Consistent sequences. EEG analyses revealed decreased oscillatory power in the theta (4-7 Hz) band at frontal sites following decisions about objects in Consistent sequences, as compared with objects in Random sequences. The theta power difference between Consistent and Random only emerged in the second half of the task, as participants were more effectively able to predict items in Consistent sequences. Moreover, we found increases in parieto-occipital alpha (10-13 Hz) and beta (14-28 Hz) power during the pre-response period for objects in Consistent sequences, relative to objects in Random sequences. Linear mixed effects modeling revealed that single trial theta oscillations were related to reaction time for future objects in a sequence, whereas beta and alpha oscillations were only predictive of reaction time on the current trial. These results indicate that theta and alpha/beta activity preferentially relate to future and current events, respectively. More generally our findings highlight the importance of band-specific neural oscillations in the learning of temporal order information. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

A model linking immediate serial recall, the Hebb repetition effect and the learning of phonological word forms

PubMed Central

Page, M. P. A.; Norris, D.

2009-01-01

We briefly review the considerable evidence for a common ordering mechanism underlying both immediate serial recall (ISR) tasks (e.g. digit span, non-word repetition) and the learning of phonological word forms. In addition, we discuss how recent work on the Hebb repetition effect is consistent with the idea that learning in this task is itself a laboratory analogue of the sequence-learning component of phonological word-form learning. In this light, we present a unifying modelling framework that seeks to account for ISR and Hebb repetition effects, while being extensible to word-form learning. Because word-form learning is performed in the service of later word recognition, our modelling framework also subsumes a mechanism for word recognition from continuous speech. Simulations of a computational implementation of the modelling framework are presented and are shown to be in accordance with data from the Hebb repetition paradigm. PMID:19933143

Sequenced Integration and the Identification of a Problem-Solving Approach through a Learning Process

ERIC Educational Resources Information Center

Cormas, Peter C.

2016-01-01

Preservice teachers (N = 27) in two sections of a sequenced, methodological and process integrated mathematics/science course solved a levers problem with three similar learning processes and a problem-solving approach, and identified a problem-solving approach through one different learning process. Similar learning processes used included:…

Modeling effects of intrinsic and extrinsic rewards on the competition between striatal learning systems.

PubMed

Boedecker, Joschka; Lampe, Thomas; Riedmiller, Martin

2013-01-01

A common assumption in psychology, economics, and other fields holds that higher performance will result if extrinsic rewards (such as money) are offered as an incentive. While this principle seems to work well for tasks that require the execution of the same sequence of steps over and over, with little uncertainty about the process, in other cases, especially where creative problem solving is required due to the difficulty in finding the optimal sequence of actions, external rewards can actually be detrimental to task performance. Furthermore, they have the potential to undermine intrinsic motivation to do an otherwise interesting activity. In this work, we extend a computational model of the dorsomedial and dorsolateral striatal reinforcement learning systems to account for the effects of extrinsic and intrinsic rewards. The model assumes that the brain employs both a goal-directed and a habitual learning system, and competition between both is based on the trade-off between the cost of the reasoning process and value of information. The goal-directed system elicits internal rewards when its models of the environment improve, while the habitual system, being model-free, does not. Our results account for the phenomena that initial extrinsic reward leads to reduced activity after extinction compared to the case without any initial extrinsic rewards, and that performance in complex task settings drops when higher external rewards are promised. We also test the hypothesis that external rewards bias the competition in favor of the computationally efficient, but cruder and less flexible habitual system, which can negatively influence intrinsic motivation and task performance in the class of tasks we consider.

Learning to generate combinatorial action sequences utilizing the initial sensitivity of deterministic dynamical systems.

PubMed

Nishimoto, Ryu; Tani, Jun

2004-09-01

This study shows how sensory-action sequences of imitating finite state machines (FSMs) can be learned by utilizing the deterministic dynamics of recurrent neural networks (RNNs). Our experiments indicated that each possible combinatorial sequence can be recalled by specifying its respective initial state value and also that fractal structures appear in this initial state mapping after the learning converges. We also observed that the sequences of mimicking FSMs are encoded utilizing the transient regions rather than the invariant sets of the evolved dynamical systems of the RNNs.

Impaired Statistical Learning in Developmental Dyslexia

PubMed Central

Thiessen, Erik D.; Holt, Lori L.

2015-01-01

Purpose Developmental dyslexia (DD) is commonly thought to arise from phonological impairments. However, an emerging perspective is that a more general procedural learning deficit, not specific to phonological processing, may underlie DD. The current study examined if individuals with DD are capable of extracting statistical regularities across sequences of passively experienced speech and nonspeech sounds. Such statistical learning is believed to be domain-general, to draw upon procedural learning systems, and to relate to language outcomes. Method DD and control groups were familiarized with a continuous stream of syllables or sine-wave tones, the ordering of which was defined by high or low transitional probabilities across adjacent stimulus pairs. Participants subsequently judged two 3-stimulus test items with either high or low statistical coherence as being the most similar to the sounds heard during familiarization. Results As with control participants, the DD group was sensitive to the transitional probability structure of the familiarization materials as evidenced by above-chance performance. However, the performance of participants with DD was significantly poorer than controls across linguistic and nonlinguistic stimuli. In addition, reading-related measures were significantly correlated with statistical learning performance of both speech and nonspeech material. Conclusion Results are discussed in light of procedural learning impairments among participants with DD. PMID:25860795

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.

Learning Cellular Sorting Pathways Using Protein Interactions and Sequence Motifs

PubMed Central

Lin, Tien-Ho; Bar-Joseph, Ziv

2011-01-01

Abstract Proper subcellular localization is critical for proteins to perform their roles in cellular functions. Proteins are transported by different cellular sorting pathways, some of which take a protein through several intermediate locations until reaching its final destination. The pathway a protein is transported through is determined by carrier proteins that bind to specific sequence motifs. In this article, we present a new method that integrates protein interaction and sequence motif data to model how proteins are sorted through these sorting pathways. We use a hidden Markov model (HMM) to represent protein sorting pathways. The model is able to determine intermediate sorting states and to assign carrier proteins and motifs to the sorting pathways. In simulation studies, we show that the method can accurately recover an underlying sorting model. Using data for yeast, we show that our model leads to accurate prediction of subcellular localization. We also show that the pathways learned by our model recover many known sorting pathways and correctly assign proteins to the path they utilize. The learned model identified new pathways and their putative carriers and motifs and these may represent novel protein sorting mechanisms. Supplementary results and software implementation are available from http://murphylab.web.cmu.edu/software/2010_RECOMB_pathways/. PMID:21999284

SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity.

PubMed

Li, Ying Hong; Xu, Jing Yu; Tao, Lin; Li, Xiao Feng; Li, Shuang; Zeng, Xian; Chen, Shang Ying; Zhang, Peng; Qin, Chu; Zhang, Cheng; Chen, Zhe; Zhu, Feng; Chen, Yu Zong

2016-01-01

Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine learning method for predicting protein functional families from protein sequences irrespective of similarity, which complemented those similarity-based and other methods in predicting diverse classes of proteins including the distantly-related proteins and homologous proteins of different functions. Since its publication in 2003, we made major improvements to SVM-Prot with (1) expanded coverage from 54 to 192 functional families, (2) more diverse protein descriptors protein representation, (3) improved predictive performances due to the use of more enriched training datasets and more variety of protein descriptors, (4) newly integrated BLAST analysis option for assessing proteins in the SVM-Prot predicted functional families that were similar in sequence to a query protein, and (5) newly added batch submission option for supporting the classification of multiple proteins. Moreover, 2 more machine learning approaches, K nearest neighbor and probabilistic neural networks, were added for facilitating collective assessment of protein functions by multiple methods. SVM-Prot can be accessed at http://bidd2.nus.edu.sg/cgi-bin/svmprot/svmprot.cgi.

Definition and Analysis of a System for the Automated Comparison of Curriculum Sequencing Algorithms in Adaptive Distance Learning

ERIC Educational Resources Information Center

Limongelli, Carla; Sciarrone, Filippo; Temperini, Marco; Vaste, Giulia

2011-01-01

LS-Lab provides automatic support to comparison/evaluation of the Learning Object Sequences produced by different Curriculum Sequencing Algorithms. Through this framework a teacher can verify the correspondence between the behaviour of different sequencing algorithms and her pedagogical preferences. In fact the teacher can compare algorithms…

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

PubMed

Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

2018-02-01

Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The DeepARG models and database are available as a command line version and as a Web service at http://bench.cs.vt.edu/deeparg .

Developmental Approach for Behavior Learning Using Primitive Motion Skills.

PubMed

Dawood, Farhan; Loo, Chu Kiong

2018-05-01

Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet the discussion on the origin of primitive imitative abilities is often neglected, referring instead to the possibility of its innateness. This paper presents a developmental model of imitation learning based on the hypothesis that humanoid robot acquires imitative abilities as induced by sensorimotor associative learning through self-exploration. In designing such learning system, several key issues will be addressed: automatic segmentation of the observed actions into motion primitives using raw images acquired from the camera without requiring any kinematic model; incremental learning of spatio-temporal motion sequences to dynamically generates a topological structure in a self-stabilizing manner; organization of the learned data for easy and efficient retrieval using a dynamic associative memory; and utilizing segmented motion primitives to generate complex behavior by the combining these motion primitives. In our experiment, the self-posture is acquired through observing the image of its own body posture while performing the action in front of a mirror through body babbling. The complete architecture was evaluated by simulation and real robot experiments performed on DARwIn-OP humanoid robot.

Growth and splitting of neural sequences in songbird vocal development

PubMed Central

Okubo, Tatsuo S.; Mackevicius, Emily L.; Payne, Hannah L.; Lynch, Galen F.; Fee, Michale S.

2015-01-01

Neural sequences are a fundamental feature of brain dynamics underlying diverse behaviors, but the mechanisms by which they develop during learning remain unknown. Songbirds learn vocalizations composed of syllables; in adult birds, each syllable is produced by a different sequence of action potential bursts in the premotor cortical area HVC. Here we carried out recordings of large populations of HVC neurons in singing juvenile birds throughout learning to examine the emergence of neural sequences. Early in vocal development, HVC neurons begin producing rhythmic bursts, temporally locked to a ‘prototype’ syllable. Different neurons are active at different latencies relative to syllable onset to form a continuous sequence. Through development, as new syllables emerge from the prototype syllable, initially highly overlapping burst sequences become increasingly distinct. We propose a mechanistic model in which multiple neural sequences can emerge from the growth and splitting of a common precursor sequence. PMID:26618871

Recurrent neural networks for breast lesion classification based on DCE-MRIs

NASA Astrophysics Data System (ADS)

Antropova, Natasha; Huynh, Benjamin; Giger, Maryellen

2018-02-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays a significant role in breast cancer screening, cancer staging, and monitoring response to therapy. Recently, deep learning methods are being rapidly incorporated in image-based breast cancer diagnosis and prognosis. However, most of the current deep learning methods make clinical decisions based on 2-dimentional (2D) or 3D images and are not well suited for temporal image data. In this study, we develop a deep learning methodology that enables integration of clinically valuable temporal components of DCE-MRIs into deep learning-based lesion classification. Our work is performed on a database of 703 DCE-MRI cases for the task of distinguishing benign and malignant lesions, and uses the area under the ROC curve (AUC) as the performance metric in conducting that task. We train a recurrent neural network, specifically a long short-term memory network (LSTM), on sequences of image features extracted from the dynamic MRI sequences. These features are extracted with VGGNet, a convolutional neural network pre-trained on a large dataset of natural images ImageNet. The features are obtained from various levels of the network, to capture low-, mid-, and high-level information about the lesion. Compared to a classification method that takes as input only images at a single time-point (yielding an AUC = 0.81 (se = 0.04)), our LSTM method improves lesion classification with an AUC of 0.85 (se = 0.03).

Is it better to select or to receive? Learning via active and passive hypothesis testing.

PubMed

Markant, Douglas B; Gureckis, Todd M

2014-02-01

People can test hypotheses through either selection or reception. In a selection task, the learner actively chooses observations to test his or her beliefs, whereas in reception tasks data are passively encountered. People routinely use both forms of testing in everyday life, but the critical psychological differences between selection and reception learning remain poorly understood. One hypothesis is that selection learning improves learning performance by enhancing generic cognitive processes related to motivation, attention, and engagement. Alternatively, we suggest that differences between these 2 learning modes derives from a hypothesis-dependent sampling bias that is introduced when a person collects data to test his or her own individual hypothesis. Drawing on influential models of sequential hypothesis-testing behavior, we show that such a bias (a) can lead to the collection of data that facilitates learning compared with reception learning and (b) can be more effective than observing the selections of another person. We then report a novel experiment based on a popular category learning paradigm that compares reception and selection learning. We additionally compare selection learners to a set of "yoked" participants who viewed the exact same sequence of observations under reception conditions. The results revealed systematic differences in performance that depended on the learner's role in collecting information and the abstract structure of the problem.

Development of a sugar-binding residue prediction system from protein sequences using support vector machine.

PubMed

Banno, Masaki; Komiyama, Yusuke; Cao, Wei; Oku, Yuya; Ueki, Kokoro; Sumikoshi, Kazuya; Nakamura, Shugo; Terada, Tohru; Shimizu, Kentaro

2017-02-01

Several methods have been proposed for protein-sugar binding site prediction using machine learning algorithms. However, they are not effective to learn various properties of binding site residues caused by various interactions between proteins and sugars. In this study, we classified sugars into acidic and nonacidic sugars and showed that their binding sites have different amino acid occurrence frequencies. By using this result, we developed sugar-binding residue predictors dedicated to the two classes of sugars: an acid sugar binding predictor and a nonacidic sugar binding predictor. We also developed a combination predictor which combines the results of the two predictors. We showed that when a sugar is known to be an acidic sugar, the acidic sugar binding predictor achieves the best performance, and showed that when a sugar is known to be a nonacidic sugar or is not known to be either of the two classes, the combination predictor achieves the best performance. Our method uses only amino acid sequences for prediction. Support vector machine was used as a machine learning algorithm and the position-specific scoring matrix created by the position-specific iterative basic local alignment search tool was used as the feature vector. We evaluated the performance of the predictors using five-fold cross-validation. We have launched our system, as an open source freeware tool on the GitHub repository (https://doi.org/10.5281/zenodo.61513). Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

When global structure "Explains Away" local grammar: a Bayesian account of rule-induction in tone sequences.

PubMed

Dawson, Colin; Gerken, Louann

2011-09-01

While many constraints on learning must be relatively experience-independent, past experience provides a rich source of guidance for subsequent learning. Discovering structure in some domain can inform a learner's future hypotheses about that domain. If a general property accounts for particular sub-patterns, a rational learner should not stipulate separate explanations for each detail without additional evidence, as the general structure has "explained away" the original evidence. In a grammar-learning experiment using tone sequences, manipulating learners' prior exposure to a tone environment affects their sensitivity to the grammar-defining feature, in this case consecutive repeated tones. Grammar-learning performance is worse if context melodies are "smooth" -- when small intervals occur more than large ones -- as Smoothness is a general property accounting for a high rate of repetition. We present an idealized Bayesian model as a "best case" benchmark for learning repetition grammars. When context melodies are Smooth, the model places greater weight on the small-interval constraint, and does not learn the repetition rule as well as when context melodies are not Smooth, paralleling the human learners. These findings support an account of abstract grammar-induction in which learners rationally assess the statistical evidence for underlying structure based on a generative model of the environment. Copyright © 2010 Elsevier B.V. All rights reserved.

Designing Better Scaffolding in Teaching Complex Systems with Graphical Simulations

NASA Astrophysics Data System (ADS)

Li, Na

Complex systems are an important topic in science education today, but they are usually difficult for secondary-level students to learn. Although graphic simulations have many advantages in teaching complex systems, scaffolding is a critical factor for effective learning. This dissertation study was conducted around two complementary research questions on scaffolding: (1) How can we chunk and sequence learning activities in teaching complex systems? (2) How can we help students make connections among system levels across learning activities (level bridging)? With a sample of 123 seventh-graders, this study employed a 3x2 experimental design that factored sequencing methods (independent variable 1; three levels) with level-bridging scaffolding (independent variable 2; two levels) and compared the effectiveness of each combination. The study measured two dependent variables: (1) knowledge integration (i.e., integrating and connecting content-specific normative concepts and providing coherent scientific explanations); (2) understanding of the deep causal structure (i.e., being able to grasp and transfer the causal knowledge of a complex system). The study used a computer-based simulation environment as the research platform to teach the ideal gas law as a system. The ideal gas law is an emergent chemical system that has three levels: (1) experiential macro level (EM) (e.g., an aerosol can explodes when it is thrown into the fire); (2) abstract macro level (AM) (i.e., the relationships among temperature, pressure and volume); (3) micro level (Mi) (i.e., molecular activity). The sequencing methods of these levels were manipulated by changing the order in which they were delivered with three possibilities: (1) EM-AM-Mi; (2) Mi-AM-EM; (3) AM-Mi-EM. The level-bridging scaffolding variable was manipulated on two aspects: (1) inserting inter-level questions among learning activities; (2) two simulations dynamically linked in the final learning activity. Addressing the first research question, the Experiential macro-Abstract macro-Micro (EM-AM-Mi) sequencing method, following the "concrete to abstract" principle, produced better knowledge integration while the Micro-Abstract macro-Experiential macro (Mi-AM-EM) sequencing method, congruent with the causal direction of the emergent system, produced better understanding of the deep causal structure only when level-bridging scaffolding was provided. The Abstract macro-Micro-Experiential macro (AM-Mi-EM) sequencing method produced worse performance in general, because it did not follow the "concrete to abstract" principle, nor did it align with the causal structure of the emergent system. As to the second research question, the results showed that level-bridging scaffolding was important for both knowledge integration and understanding of the causal structure in learning the ideal gas law system.

Phonological and Semantic Cues to Learning from Word-Types

PubMed Central

Richtsmeier, Peter

2017-01-01

Word-types represent the primary form of data for many models of phonological learning, and they often predict performance in psycholinguistic tasks. Word-types are often tacitly defined as phonologically unique words. Yet, an explicit test of this definition is lacking, and natural language patterning suggests that word meaning could also act as a cue to word-type status. This possibility was tested in a statistical phonotactic learning experiment in which phonological and semantic properties of word-types varied. During familiarization, the learning targets—word-medial consonant sequences—were instantiated either by four related word-types or by just one word-type (the experimental frequency factor). The expectation was that more word-types would lead participants to generalize the target sequences. Regarding semantic cues, related word-types were either associated with different referents or all with a single referent. Regarding phonological cues, related word-types differed from each other by one, two, or more phonemes. At test, participants rated novel wordforms for their similarity to the familiarization words. When participants heard four related word-types, they gave higher ratings to test words with the same consonant sequences, irrespective of the phonological and semantic manipulations. The results support the existing phonological definition of word-types. PMID:29187914

Differences in performance and learning proficiency on the Wisconsin Card Sorting Test in schizophrenia: do they reflect distinct neurocognitive subtypes with distinct functional profiles?

PubMed

Kurtz, Matthew M; Wexler, Bruce E

2006-01-31

The aim of this study was two-fold: 1) to determine whether a priori subtyping of patients with schizophrenia based on both overall performance on a measure of executive-function, the Wisconsin Card Sorting Test (WCST), and ability to learn the task with expanded instruction, could be confirmed with other, independent measures of executive-function and learning, and, if so, 2) to determine whether these groups have different neurocognitive profiles and show differences in functional capacity. Fifty-four outpatients with schizophrenia were divided by WCST performance into three groups: intact executive-function (n=28), "good learner" (n=13), and "poor learner" (n=13) groups. These groups were then assessed with a comprehensive neurocognitive test battery and a performance-based measure of functional status, the UCSD Performance-based Skills Assessment (UPSA). The WCST-intact subgroup performed significantly better than other groups on a second measure of executive-function and in working memory, and speeded motor sequencing. Impaired WCST patients who benefited from expanded WCST instruction ("good learners") also showed better performance than patients who did not benefit from instruction ("poor-learners") on a second measure of learning, as well as on a measure of auditory divided attention. The intact WCST subgroup had greater functional capacity than either "strong" or "poor" learners. These subtypes may have implications for response to behavioral treatment interventions.

Implicit Sequence Learning and Contextual Cueing Do Not Compete for Central Cognitive Resources

ERIC Educational Resources Information Center

Jimenez, Luis; Vazquez, Gustavo A.

2011-01-01

Sequence learning and contextual cueing explore different forms of implicit learning, arising from practice with a structured serial task, or with a search task with informative contexts. We assess whether these two learning effects arise simultaneously when both remain implicit. Experiments 1 and 2 confirm that a cueing effect can be observed…

Effects of Programmed Learning Sequences on the Mathematics Test Scores of Bermudian Middle School Students

ERIC Educational Resources Information Center

Tully, Derek; Dunn, Rita; Hlawaty, Heide

2006-01-01

This research compared the effects of a Programmed Learning Sequence (PLS) (Dunn & Dunn, 1993) versus Traditional Teaching (TT) on 100 sixth-grade Bermudian students' test scores on a Fractions Unit. Fifty-three males' and forty-seven females' learning styles were identified with the "Learning Style Inventory" (LSI) (Dunn, Dunn,…

Frost Bite: A Dramatic Tale of Research in Aesthetic Education

ERIC Educational Resources Information Center

Hirsch, Miriam

2008-01-01

This article follows the author's research on the integration of an aesthetic arts initiative in a private elementary school with an established traditional arts program. The narrative describes the sequence of events, interpersonal interactions, and learning experiences in the format of a full-length dramatic performance. Informed by Ben Peretz's…

The Effect of Principle-Procedure and Procedure-Principle Sequencing on Learning Outcomes. IDD&E Working Paper No. 19.

ERIC Educational Resources Information Center

Lim-Quek, Muriel; And Others

This study tested the effects of two instructional sequences--principle-procedure and procedure-principle--on the application and transfer of learning. It was hypothesized that a principle-procedure sequence would result in better near-transfer and far-transfer and that students would prefer this sequence. The 38 freshmen enrolled in a business…

Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks

PubMed Central

Panda, Priyadarshini; Roy, Kaushik

2017-01-01

Synaptic Plasticity, the foundation for learning and memory formation in the human brain, manifests in various forms. Here, we combine the standard spike timing correlation based Hebbian plasticity with a non-Hebbian synaptic decay mechanism for training a recurrent spiking neural model to generate sequences. We show that inclusion of the adaptive decay of synaptic weights with standard STDP helps learn stable contextual dependencies between temporal sequences, while reducing the strong attractor states that emerge in recurrent models due to feedback loops. Furthermore, we show that the combined learning scheme suppresses the chaotic activity in the recurrent model substantially, thereby enhancing its' ability to generate sequences consistently even in the presence of perturbations. PMID:29311774

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

NASA Astrophysics Data System (ADS)

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-03-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to classify and rank binding affinities. Using simplified data sets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified data sets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems.

A neural model of hierarchical reinforcement learning.

PubMed

Rasmussen, Daniel; Voelker, Aaron; Eliasmith, Chris

2017-01-01

We develop a novel, biologically detailed neural model of reinforcement learning (RL) processes in the brain. This model incorporates a broad range of biological features that pose challenges to neural RL, such as temporally extended action sequences, continuous environments involving unknown time delays, and noisy/imprecise computations. Most significantly, we expand the model into the realm of hierarchical reinforcement learning (HRL), which divides the RL process into a hierarchy of actions at different levels of abstraction. Here we implement all the major components of HRL in a neural model that captures a variety of known anatomical and physiological properties of the brain. We demonstrate the performance of the model in a range of different environments, in order to emphasize the aim of understanding the brain's general reinforcement learning ability. These results show that the model compares well to previous modelling work and demonstrates improved performance as a result of its hierarchical ability. We also show that the model's behaviour is consistent with available data on human hierarchical RL, and generate several novel predictions.

Research and application of a novel hybrid decomposition-ensemble learning paradigm with error correction for daily PM10 forecasting

NASA Astrophysics Data System (ADS)

Luo, Hongyuan; Wang, Deyun; Yue, Chenqiang; Liu, Yanling; Guo, Haixiang

2018-03-01

In this paper, a hybrid decomposition-ensemble learning paradigm combining error correction is proposed for improving the forecast accuracy of daily PM10 concentration. The proposed learning paradigm is consisted of the following two sub-models: (1) PM10 concentration forecasting model; (2) error correction model. In the proposed model, fast ensemble empirical mode decomposition (FEEMD) and variational mode decomposition (VMD) are applied to disassemble original PM10 concentration series and error sequence, respectively. The extreme learning machine (ELM) model optimized by cuckoo search (CS) algorithm is utilized to forecast the components generated by FEEMD and VMD. In order to prove the effectiveness and accuracy of the proposed model, two real-world PM10 concentration series respectively collected from Beijing and Harbin located in China are adopted to conduct the empirical study. The results show that the proposed model performs remarkably better than all other considered models without error correction, which indicates the superior performance of the proposed model.

Statistical learning in social action contexts.

PubMed

Monroy, Claire; Meyer, Marlene; Gerson, Sarah; Hunnius, Sabine

2017-01-01

Sensitivity to the regularities and structure contained within sequential, goal-directed actions is an important building block for generating expectations about the actions we observe. Until now, research on statistical learning for actions has solely focused on individual action sequences, but many actions in daily life involve multiple actors in various interaction contexts. The current study is the first to investigate the role of statistical learning in tracking regularities between actions performed by different actors, and whether the social context characterizing their interaction influences learning. That is, are observers more likely to track regularities across actors if they are perceived as acting jointly as opposed to in parallel? We tested adults and toddlers to explore whether social context guides statistical learning and-if so-whether it does so from early in development. In a between-subjects eye-tracking experiment, participants were primed with a social context cue between two actors who either shared a goal of playing together ('Joint' condition) or stated the intention to act alone ('Parallel' condition). In subsequent videos, the actors performed sequential actions in which, for certain action pairs, the first actor's action reliably predicted the second actor's action. We analyzed predictive eye movements to upcoming actions as a measure of learning, and found that both adults and toddlers learned the statistical regularities across actors when their actions caused an effect. Further, adults with high statistical learning performance were sensitive to social context: those who observed actors with a shared goal were more likely to correctly predict upcoming actions. In contrast, there was no effect of social context in the toddler group, regardless of learning performance. These findings shed light on how adults and toddlers perceive statistical regularities across actors depending on the nature of the observed social situation and the resulting effects.

Statistical learning in social action contexts

PubMed Central

Meyer, Marlene; Gerson, Sarah; Hunnius, Sabine

2017-01-01

Sensitivity to the regularities and structure contained within sequential, goal-directed actions is an important building block for generating expectations about the actions we observe. Until now, research on statistical learning for actions has solely focused on individual action sequences, but many actions in daily life involve multiple actors in various interaction contexts. The current study is the first to investigate the role of statistical learning in tracking regularities between actions performed by different actors, and whether the social context characterizing their interaction influences learning. That is, are observers more likely to track regularities across actors if they are perceived as acting jointly as opposed to in parallel? We tested adults and toddlers to explore whether social context guides statistical learning and—if so—whether it does so from early in development. In a between-subjects eye-tracking experiment, participants were primed with a social context cue between two actors who either shared a goal of playing together (‘Joint’ condition) or stated the intention to act alone (‘Parallel’ condition). In subsequent videos, the actors performed sequential actions in which, for certain action pairs, the first actor’s action reliably predicted the second actor’s action. We analyzed predictive eye movements to upcoming actions as a measure of learning, and found that both adults and toddlers learned the statistical regularities across actors when their actions caused an effect. Further, adults with high statistical learning performance were sensitive to social context: those who observed actors with a shared goal were more likely to correctly predict upcoming actions. In contrast, there was no effect of social context in the toddler group, regardless of learning performance. These findings shed light on how adults and toddlers perceive statistical regularities across actors depending on the nature of the observed social situation and the resulting effects. PMID:28475619

Learning invariance from natural images inspired by observations in the primary visual cortex.

PubMed

Teichmann, Michael; Wiltschut, Jan; Hamker, Fred

2012-05-01

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.

A hybrid model based on neural networks for biomedical relation extraction.

PubMed

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Zhang, Shaowu; Sun, Yuanyuan; Yang, Liang

2018-05-01

Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutional neural networks (CNNs) are two major neural network models for biomedical relation extraction. Neural network-based methods for biomedical relation extraction typically focus on the sentence sequence and employ RNNs or CNNs to learn the latent features from sentence sequences separately. However, RNNs and CNNs have their own advantages for biomedical relation extraction. Combining RNNs and CNNs may improve biomedical relation extraction. In this paper, we present a hybrid model for the extraction of biomedical relations that combines RNNs and CNNs. First, the shortest dependency path (SDP) is generated based on the dependency graph of the candidate sentence. To make full use of the SDP, we divide the SDP into a dependency word sequence and a relation sequence. Then, RNNs and CNNs are employed to automatically learn the features from the sentence sequence and the dependency sequences, respectively. Finally, the output features of the RNNs and CNNs are combined to detect and extract biomedical relations. We evaluate our hybrid model using five public (protein-protein interaction) PPI corpora and a (drug-drug interaction) DDI corpus. The experimental results suggest that the advantages of RNNs and CNNs in biomedical relation extraction are complementary. Combining RNNs and CNNs can effectively boost biomedical relation extraction performance. Copyright © 2018 Elsevier Inc. All rights reserved.

Implicit learning of sequential bias in a guessing task: failure to demonstrate effects of dopamine administration and paranormal belief.

PubMed

Palmer, John; Mohr, Christine; Krummenacher, Peter; Brugger, Peter

2007-06-01

Previous research suggests that implicit sequence learning (ISL) is superior for believers in the paranormal and individuals with increased cerebral dopamine. Thirty-five healthy participants performed feedback-guided anticipations of four arrow directions. A 100-trial random sequence preceded two 100-trial biased sequences in which visual targets (arrows) on trial t tended to be displaced 90 degrees clockwise (CW) or counter-clockwise (CCW) from those on t - 1. ISL was defined as a positive change during the course of the biased run in the difference between pro-bias and counter-bias responses. It was hypothesized that this difference would be greater for believers in the paranormal than for skeptics, for those who received dopamine than for those who received placebo, and for believers who received dopamine than for the other groups. None of the hypotheses were supported by the data. It is suggested that a simple binary guessing task with a focus on prediction accuracy during early trials should be considered for future explorations.

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods.

PubMed

Li, Yifeng; Shi, Wenqiang; Wasserman, Wyeth W

2018-05-31

In the human genome, 98% of DNA sequences are non-protein-coding regions that were previously disregarded as junk DNA. In fact, non-coding regions host a variety of cis-regulatory regions which precisely control the expression of genes. Thus, Identifying active cis-regulatory regions in the human genome is critical for understanding gene regulation and assessing the impact of genetic variation on phenotype. The developments of high-throughput sequencing and machine learning technologies make it possible to predict cis-regulatory regions genome wide. Based on rich data resources such as the Encyclopedia of DNA Elements (ENCODE) and the Functional Annotation of the Mammalian Genome (FANTOM) projects, we introduce DECRES based on supervised deep learning approaches for the identification of enhancer and promoter regions in the human genome. Due to their ability to discover patterns in large and complex data, the introduction of deep learning methods enables a significant advance in our knowledge of the genomic locations of cis-regulatory regions. Using models for well-characterized cell lines, we identify key experimental features that contribute to the predictive performance. Applying DECRES, we delineate locations of 300,000 candidate enhancers genome wide (6.8% of the genome, of which 40,000 are supported by bidirectional transcription data), and 26,000 candidate promoters (0.6% of the genome). The predicted annotations of cis-regulatory regions will provide broad utility for genome interpretation from functional genomics to clinical applications. The DECRES model demonstrates potentials of deep learning technologies when combined with high-throughput sequencing data, and inspires the development of other advanced neural network models for further improvement of genome annotations.

Finishing and Special Motifs: Lessons Learned from CRISPR Analysis Using Next-Generation Draft Sequences (7th Annual SFAF Meeting, 2012)

ScienceCinema

Campbell, Catherine

2018-01-22

Catherine Campbell on "Finishing and Special Motifs: Lessons learned from CRISPR analysis using next-generation draft sequences" at the 2012 Sequencing, Finishing, Analysis in the Future Meeting held June 5-7, 2012 in Santa Fe, New Mexico.

Finishing and Special Motifs: Lessons Learned from CRISPR Analysis Using Next-Generation Draft Sequences (7th Annual SFAF Meeting, 2012)

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

Campbell, Catherine

Catherine Campbell on "Finishing and Special Motifs: Lessons learned from CRISPR analysis using next-generation draft sequences" at the 2012 Sequencing, Finishing, Analysis in the Future Meeting held June 5-7, 2012 in Santa Fe, New Mexico.

Learning Portfolio Analysis and Mining for SCORM Compliant Environment

ERIC Educational Resources Information Center

Su, Jun-Ming; Tseng, Shian-Shyong; Wang, Wei; Weng, Jui-Feng; Yang, Jin Tan David; Tsai, Wen-Nung

2006-01-01

With vigorous development of the Internet, e-learning system has become more and more popular. Sharable Content Object Reference Model (SCORM) 2004 provides the Sequencing and Navigation (SN) Specification to define the course sequencing behavior, control the sequencing, selecting and delivering of course, and organize the content into a…

Identification of DNA-binding proteins by combining auto-cross covariance transformation and ensemble learning.

PubMed

Liu, Bin; Wang, Shanyi; Dong, Qiwen; Li, Shumin; Liu, Xuan

2016-04-20

DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. With the rapid development of next generation of sequencing technique, the number of protein sequences is unprecedentedly increasing. Thus it is necessary to develop computational methods to identify the DNA-binding proteins only based on the protein sequence information. In this study, a novel method called iDNA-KACC is presented, which combines the Support Vector Machine (SVM) and the auto-cross covariance transformation. The protein sequences are first converted into profile-based protein representation, and then converted into a series of fixed-length vectors by the auto-cross covariance transformation with Kmer composition. The sequence order effect can be effectively captured by this scheme. These vectors are then fed into Support Vector Machine (SVM) to discriminate the DNA-binding proteins from the non DNA-binding ones. iDNA-KACC achieves an overall accuracy of 75.16% and Matthew correlation coefficient of 0.5 by a rigorous jackknife test. Its performance is further improved by employing an ensemble learning approach, and the improved predictor is called iDNA-KACC-EL. Experimental results on an independent dataset shows that iDNA-KACC-EL outperforms all the other state-of-the-art predictors, indicating that it would be a useful computational tool for DNA binding protein identification. .

Enhanced learning of natural visual sequences in newborn chicks.

PubMed

Wood, Justin N; Prasad, Aditya; Goldman, Jason G; Wood, Samantha M W

2016-07-01

To what extent are newborn brains designed to operate over natural visual input? To address this question, we used a high-throughput controlled-rearing method to examine whether newborn chicks (Gallus gallus) show enhanced learning of natural visual sequences at the onset of vision. We took the same set of images and grouped them into either natural sequences (i.e., sequences showing different viewpoints of the same real-world object) or unnatural sequences (i.e., sequences showing different images of different real-world objects). When raised in virtual worlds containing natural sequences, newborn chicks developed the ability to recognize familiar images of objects. Conversely, when raised in virtual worlds containing unnatural sequences, newborn chicks' object recognition abilities were severely impaired. In fact, the majority of the chicks raised with the unnatural sequences failed to recognize familiar images of objects despite acquiring over 100 h of visual experience with those images. Thus, newborn chicks show enhanced learning of natural visual sequences at the onset of vision. These results indicate that newborn brains are designed to operate over natural visual input.

Incidental orthographic learning during a color detection task.

PubMed

Protopapas, Athanassios; Mitsi, Anna; Koustoumbardis, Miltiadis; Tsitsopoulou, Sofia M; Leventi, Marianna; Seitz, Aaron R

2017-09-01

Orthographic learning refers to the acquisition of knowledge about specific spelling patterns forming words and about general biases and constraints on letter sequences. It is thought to occur by strengthening simultaneously activated visual and phonological representations during reading. Here we demonstrate that a visual perceptual learning procedure that leaves no time for articulation can result in orthographic learning evidenced in improved reading and spelling performance. We employed task-irrelevant perceptual learning (TIPL), in which the stimuli to be learned are paired with an easy task target. Assorted line drawings and difficult-to-spell words were presented in red color among sequences of other black-colored words and images presented in rapid succession, constituting a fast-TIPL procedure with color detection being the explicit task. In five experiments, Greek children in Grades 4-5 showed increased recognition of words and images that had appeared in red, both during and after the training procedure, regardless of within-training testing, and also when targets appeared in blue instead of red. Significant transfer to reading and spelling emerged only after increased training intensity. In a sixth experiment, children in Grades 2-3 showed generalization to words not presented during training that carried the same derivational affixes as in the training set. We suggest that reinforcement signals related to detection of the target stimuli contribute to the strengthening of orthography-phonology connections beyond earlier levels of visually-based orthographic representation learning. These results highlight the potential of perceptual learning procedures for the reinforcement of higher-level orthographic representations. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Measuring preschool learning engagement in the laboratory.

PubMed

Halliday, Simone E; Calkins, Susan D; Leerkes, Esther M

2018-03-01

Learning engagement is a critical factor for academic achievement and successful school transitioning. However, current methods of assessing learning engagement in young children are limited to teacher report or classroom observation, which may limit the types of research questions one could assess about this construct. The current study investigated the validity of a novel assessment designed to measure behavioral learning engagement among young children in a standardized laboratory setting and examined how learning engagement in the laboratory relates to future classroom adjustment. Preschool-aged children (N = 278) participated in a learning-based Tangrams task and Story sequencing task and were observed based on seven behavioral indicators of engagement. Confirmatory factor analysis supported the construct validity for a behavioral engagement factor composed of six of the original behavioral indicators: attention to instructions, on-task behavior, enthusiasm/energy, persistence, monitoring progress/strategy use, and negative affect. Concurrent validity for this behavioral engagement factor was established through its associations with parent-reported mastery motivation and pre-academic skills in math and literacy measured in the laboratory, and predictive validity was demonstrated through its associations with teacher-reported classroom learning behaviors and performance in math and reading in kindergarten. These associations were found when behavioral engagement was observed during both the nonverbal task and the verbal story sequencing tasks and persisted even after controlling for child minority status, gender, and maternal education. Learning engagement in preschool appears to be successfully measurable in a laboratory setting. This finding has implications for future research on the mechanisms that support successful academic development. Copyright © 2017 Elsevier Inc. All rights reserved.

Intact implicit statistical learning in borderline personality disorder.

PubMed

Unoka, Zsolt; Vizin, Gabriella; Bjelik, Anna; Radics, Dóra; Nemeth, Dezso; Janacsek, Karolina

2017-09-01

Wide-spread neuropsychological deficits have been identified in borderline personality disorder (BPD). Previous research found impairments in decision making, declarative memory, working memory and executive functions; however, no studies have focused on implicit learning in BPD yet. The aim of our study was to investigate implicit statistical learning by comparing learning performance of 19 BPD patients and 19 healthy, age-, education- and gender-matched controls on a probabilistic sequence learning task. Moreover, we also tested whether participants retain the acquired knowledge after a delay period. To this end, participants were retested on a shorter version of the same task 24h after the learning phase. We found intact implicit statistical learning as well as retention of the acquired knowledge in this personality disorder. BPD patients seem to be able to extract and represent regularities implicitly, which is in line with the notion that implicit learning is less susceptible to illness compared to the more explicit processes. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Probabilistic learning and inference in schizophrenia

PubMed Central

Averbeck, Bruno B.; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S.

2010-01-01

Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behaviour remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behaviour, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. PMID:20810252

Probabilistic learning and inference in schizophrenia.

PubMed

Averbeck, Bruno B; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S

2011-04-01

Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behavior remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behavior, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving a noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. Published by Elsevier B.V.

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

PubMed Central

Kazerounian, Sohrob; Grossberg, Stephen

2014-01-01

How are sequences of events that are temporarily stored in a cognitive working memory unitized, or chunked, through learning? Such sequential learning is needed by the brain in order to enable language, spatial understanding, and motor skills to develop. In particular, how does the brain learn categories, or list chunks, that become selectively tuned to different temporal sequences of items in lists of variable length as they are stored in working memory, and how does this learning process occur in real time? The present article introduces a neural model that simulates learning of such list chunks. In this model, sequences of items are temporarily stored in an Item-and-Order, or competitive queuing, working memory before learning categorizes them using a categorization network, called a Masking Field, which is a self-similar, multiple-scale, recurrent on-center off-surround network that can weigh the evidence for variable-length sequences of items as they are stored in the working memory through time. A Masking Field hereby activates the learned list chunks that represent the most predictive item groupings at any time, while suppressing less predictive chunks. In a network with a given number of input items, all possible ordered sets of these item sequences, up to a fixed length, can be learned with unsupervised or supervised learning. The self-similar multiple-scale properties of Masking Fields interacting with an Item-and-Order working memory provide a natural explanation of George Miller's Magical Number Seven and Nelson Cowan's Magical Number Four. The article explains why linguistic, spatial, and action event sequences may all be stored by Item-and-Order working memories that obey similar design principles, and thus how the current results may apply across modalities. Item-and-Order properties may readily be extended to Item-Order-Rank working memories in which the same item can be stored in multiple list positions, or ranks, as in the list ABADBD. Comparisons with other models, including TRACE, MERGE, and TISK, are made. PMID:25339918

Cognitive and neural foundations of discrete sequence skill: a TMS study.

PubMed

Ruitenberg, Marit F L; Verwey, Willem B; Schutter, Dennis J L G; Abrahamse, Elger L

2014-04-01

Executing discrete movement sequences typically involves a shift with practice from a relatively slow, stimulus-based mode to a fast mode in which performance is based on retrieving and executing entire motor chunks. The dual processor model explains the performance of (skilled) discrete key-press sequences in terms of an interplay between a cognitive processor and a motor system. In the present study, we tested and confirmed the core assumptions of this model at the behavioral level. In addition, we explored the involvement of the pre-supplementary motor area (pre-SMA) in discrete sequence skill by applying inhibitory 20 min 1-Hz off-line repetitive transcranial magnetic stimulation (rTMS). Based on previous work, we predicted pre-SMA involvement in the selection/initiation of motor chunks, and this was confirmed by our results. The pre-SMA was further observed to be more involved in more complex than in simpler sequences, while no evidence was found for pre-SMA involvement in direct stimulus-response translations or associative learning processes. In conclusion, support is provided for the dual processor model, and for pre-SMA involvement in the initiation of motor chunks. Copyright © 2014 Elsevier Ltd. All rights reserved.

A statistical approach to detection of copy number variations in PCR-enriched targeted sequencing data.

PubMed

Demidov, German; Simakova, Tamara; Vnuchkova, Julia; Bragin, Anton

2016-10-22

Multiplex polymerase chain reaction (PCR) is a common enrichment technique for targeted massive parallel sequencing (MPS) protocols. MPS is widely used in biomedical research and clinical diagnostics as the fast and accurate tool for the detection of short genetic variations. However, identification of larger variations such as structure variants and copy number variations (CNV) is still being a challenge for targeted MPS. Some approaches and tools for structural variants detection were proposed, but they have limitations and often require datasets of certain type, size and expected number of amplicons affected by CNVs. In the paper, we describe novel algorithm for high-resolution germinal CNV detection in the PCR-enriched targeted sequencing data and present accompanying tool. We have developed a machine learning algorithm for the detection of large duplications and deletions in the targeted sequencing data generated with PCR-based enrichment step. We have performed verification studies and established the algorithm's sensitivity and specificity. We have compared developed tool with other available methods applicable for the described data and revealed its higher performance. We showed that our method has high specificity and sensitivity for high-resolution copy number detection in targeted sequencing data using large cohort of samples.

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences

PubMed Central

Zhang, Long; Jia, Lianyin; Ren, Yazhou

2017-01-01

Protein-protein interactions (PPIs) play crucial roles in almost all cellular processes. Although a large amount of PPIs have been verified by high-throughput techniques in the past decades, currently known PPIs pairs are still far from complete. Furthermore, the wet-lab experiments based techniques for detecting PPIs are time-consuming and expensive. Hence, it is urgent and essential to develop automatic computational methods to efficiently and accurately predict PPIs. In this paper, a sequence-based approach called DNN-LCTD is developed by combining deep neural networks (DNNs) and a novel local conjoint triad description (LCTD) feature representation. LCTD incorporates the advantage of local description and conjoint triad, thus, it is capable to account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. DNNs can not only learn suitable features from the data by themselves, but also learn and discover hierarchical representations of data. When performing on the PPIs data of Saccharomyces cerevisiae, DNN-LCTD achieves superior performance with accuracy as 93.12%, precision as 93.75%, sensitivity as 93.83%, area under the receiver operating characteristic curve (AUC) as 97.92%, and it only needs 718 s. These results indicate DNN-LCTD is very promising for predicting PPIs. DNN-LCTD can be a useful supplementary tool for future proteomics study. PMID:29117139

Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences.

PubMed

Wang, Jun; Zhang, Long; Jia, Lianyin; Ren, Yazhou; Yu, Guoxian

2017-11-08

Protein-protein interactions (PPIs) play crucial roles in almost all cellular processes. Although a large amount of PPIs have been verified by high-throughput techniques in the past decades, currently known PPIs pairs are still far from complete. Furthermore, the wet-lab experiments based techniques for detecting PPIs are time-consuming and expensive. Hence, it is urgent and essential to develop automatic computational methods to efficiently and accurately predict PPIs. In this paper, a sequence-based approach called DNN-LCTD is developed by combining deep neural networks (DNNs) and a novel local conjoint triad description (LCTD) feature representation. LCTD incorporates the advantage of local description and conjoint triad, thus, it is capable to account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. DNNs can not only learn suitable features from the data by themselves, but also learn and discover hierarchical representations of data. When performing on the PPIs data of Saccharomyces cerevisiae , DNN-LCTD achieves superior performance with accuracy as 93.12%, precision as 93.75%, sensitivity as 93.83%, area under the receiver operating characteristic curve (AUC) as 97.92%, and it only needs 718 s. These results indicate DNN-LCTD is very promising for predicting PPIs. DNN-LCTD can be a useful supplementary tool for future proteomics study.

Learning Orthographic Structure with Sequential Generative Neural Networks

ERIC Educational Resources Information Center

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

2016-01-01

Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in…

Learning Progressions and Teaching Sequences: A Review and Analysis

ERIC Educational Resources Information Center

Duschl, Richard; Maeng, Seungho; Sezen, Asli

2011-01-01

Our paper is an analytical review of the design, development and reporting of learning progressions and teaching sequences. Research questions are: (1) what criteria are being used to propose a "hypothetical learning progression/trajectory" and (2) what measurements/evidence are being used to empirically define and refine a "hypothetical learning…

Different Levels of Learning Interact to Shape the Congruency Sequence Effect

ERIC Educational Resources Information Center

Weissman, Daniel H.; Hawks, Zoë W.; Egner, Tobias

2016-01-01

The congruency effect in distracter interference tasks is often reduced after incongruent relative to congruent trials. Moreover, this "congruency sequence effect" (CSE) is influenced by learning related to concrete stimulus and response features as well as by learning related to abstract cognitive control processes. There is an ongoing…

Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification

ERIC Educational Resources Information Center

Emond, Bruno; Buffett, Scott

2015-01-01

This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and…

Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

PubMed

Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

2016-01-01

3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

"I know your name, but not your number"--Patients with verbal short-term memory deficits are impaired in learning sequences of digits.

PubMed

Bormann, Tobias; Seyboth, Margret; Umarova, Roza; Weiller, Cornelius

2015-06-01

Studies on verbal learning in patients with impaired verbal short-term memory (vSTM) have revealed dissociations among types of verbal information. Patients with impaired vSTM are able to learn lists of known words but fail to acquire new word forms. This suggests that vSTM is involved in new word learning. The present study assessed both new word learning and the learning of digit sequences in two patients with impaired vSTM. In two experiments, participants were required to learn people's names, ages and professions, or their four digit 'phone numbers'. The STM patients were impaired on learning unknown family names and phone numbers, but managed to acquire other verbal information. In contrast, a patient with a severe verbal episodic memory impairment was impaired across information types. These results indicate verbal STM involvement in the learning of digit sequences. Copyright © 2015 Elsevier Ltd. All rights reserved.

The effect of presentation rate on implicit sequence learning in aging.

PubMed

Foster, Chris M; Giovanello, Kelly S

2017-02-01

Implicit sequence learning is thought to be preserved in aging when the to-be learned associations are first-order; however, when associations are second-order, older adults (OAs) tend to experience deficits as compared to young adults (YAs). Two experiments were conducted using a first (Experiment 1) and second-order (Experiment 2) serial-reaction time task. Stimuli were presented at a constant rate of either 800 milliseconds (fast) or 1200 milliseconds (slow). Results indicate that both age groups learned first-order dependencies equally in both conditions. OAs and YAs also learned second-order dependencies, but the learning of lag-2 information was significantly impacted by the rate of presentation for both groups. OAs showed significant lag-2 learning in slow condition while YAs showed significant lag-2 learning in the fast condition. The sensitivity of implicit sequence learning to the rate of presentation supports the idea that OAs and YAs different processing speeds impact the ability to build complex associations across time and intervening events.

Learning of serial digits leads to frontal activation in functional MR imaging.

PubMed

Karakaş, Hakki Muammer; Karakaş, Sirel

2006-03-01

Clinical studies have shown that performance on the serial digit learning test (SDLT) is dependent upon the mesial temporal lobes, which are responsible for learning and its consolidation. However, an effective SDLT performance is also dependent upon sequencing, temporal ordering, and the utilization of mnemonic strategies. All of these processes are among the functions of the frontal lobes; in spite of this, the relationship between SDLT performance and the frontal lobes has not been demonstrated with previously used mapping techniques. The aim of this study was to investigate the areas of the brain that are activated by SDLT performance. Ten healthy, right handed volunteers (mean age, 20.1 years; SD: 3.3) who had 12 years of education were studied with a 1.0 T MR imaging scanner. BOLD (blood oxygen level dependent) contrast and a modified SDLT were used. Activated loci were automatically mapped using a proportional grid. In learning, the most consistent activation was observed in B-a-7 of the right (80%) and the left hemispheres (50%). In recall, the most consistent activation was observed in B-a-7 of the right hemisphere (60%). Activations were observed in 2.5+/-0.97 Talairach volumes in learning, whereas they encompassed 1.7+/-0.95 volumes in recall. The difference between both phases (learning and recall) regarding total activated volume was significant (p < 0.05). The prefrontal activation during SDLT performance was not related to learning or to recall, but to a function that is common to both of these cognitive processes. A candidate for this common factor may be the executive functions, which also include serial position processing and temporal ordering.

Dynamics of EEG functional connectivity during statistical learning.

PubMed

Tóth, Brigitta; Janacsek, Karolina; Takács, Ádám; Kóbor, Andrea; Zavecz, Zsófia; Nemeth, Dezso

2017-10-01

Statistical learning is a fundamental mechanism of the brain, which extracts and represents regularities of our environment. Statistical learning is crucial in predictive processing, and in the acquisition of perceptual, motor, cognitive, and social skills. Although previous studies have revealed competitive neurocognitive processes underlying statistical learning, the neural communication of the related brain regions (functional connectivity, FC) has not yet been investigated. The present study aimed to fill this gap by investigating FC networks that promote statistical learning in humans. Young adults (N=28) performed a statistical learning task while 128-channels EEG was acquired. The task involved probabilistic sequences, which enabled to measure incidental/implicit learning of conditional probabilities. Phase synchronization in seven frequency bands was used to quantify FC between cortical regions during the first, second, and third periods of the learning task, respectively. Here we show that statistical learning is negatively correlated with FC of the anterior brain regions in slow (theta) and fast (beta) oscillations. These negative correlations increased as the learning progressed. Our findings provide evidence that dynamic antagonist brain networks serve a hallmark of statistical learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Chromatin accessibility prediction via a hybrid deep convolutional neural network.

PubMed

Liu, Qiao; Xia, Fei; Yin, Qijin; Jiang, Rui

2018-03-01

A majority of known genetic variants associated with human-inherited diseases lie in non-coding regions that lack adequate interpretation, making it indispensable to systematically discover functional sites at the whole genome level and precisely decipher their implications in a comprehensive manner. Although computational approaches have been complementing high-throughput biological experiments towards the annotation of the human genome, it still remains a big challenge to accurately annotate regulatory elements in the context of a specific cell type via automatic learning of the DNA sequence code from large-scale sequencing data. Indeed, the development of an accurate and interpretable model to learn the DNA sequence signature and further enable the identification of causative genetic variants has become essential in both genomic and genetic studies. We proposed Deopen, a hybrid framework mainly based on a deep convolutional neural network, to automatically learn the regulatory code of DNA sequences and predict chromatin accessibility. In a series of comparison with existing methods, we show the superior performance of our model in not only the classification of accessible regions against background sequences sampled at random, but also the regression of DNase-seq signals. Besides, we further visualize the convolutional kernels and show the match of identified sequence signatures and known motifs. We finally demonstrate the sensitivity of our model in finding causative noncoding variants in the analysis of a breast cancer dataset. We expect to see wide applications of Deopen with either public or in-house chromatin accessibility data in the annotation of the human genome and the identification of non-coding variants associated with diseases. Deopen is freely available at https://github.com/kimmo1019/Deopen. ruijiang@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Prose memory deficits associated with schizophrenia.

PubMed

Lee, Tatia M C; Chan, Michelle W C; Chan, Chetwyn C H; Gao, Junling; Wang, Kai; Chen, Eric Y H

2006-01-31

Memory of contextual information is essential to one's quality of living. This study investigated if the different components of prose memory, across three recall conditions: first learning trial immediate recall, fifth learning trial immediate recall, and 30-min delayed recall, are differentially impaired in people with schizophrenia, relative to healthy controls. A total of 39 patients with schizophrenia and 39 matched healthy controls were recruited. Their prose memory, in terms of recall accuracy, temporal sequence, recognition accuracy and false positives, commission of distortions, and rates of learning, forgetting, and retention were tested and compared. After controlling for the level of intelligence and depression, the patients with schizophrenia were found to commit more distortions. Furthermore, they performed poorer on recall accuracy and temporal sequence accuracy only during the first initial immediate recall. On the other hand, the rates of forgetting/retention and recognition accuracy were comparable between the two groups. These findings suggest that people with schizophrenia could be benefited by repeated exposure to the materials to be remembered. These results may have important implications for rehabilitation of verbal declarative memory deficits in schizophrenia.

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.

PubMed

Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T

2017-10-01

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.

Machine learning methods can replace 3D profile method in classification of amyloidogenic hexapeptides.

PubMed

Stanislawski, Jerzy; Kotulska, Malgorzata; Unold, Olgierd

2013-01-17

Amyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods. We generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%). The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile) to 0.5 CPU-hours (simplified 3D profile) to seconds (machine learning). We showed that the simplified profile generation method does not introduce an error with regard to the original method, while increasing the computational efficiency. Our new dataset proved representative enough to use simple statistical methods for testing the amylogenicity based only on six letter sequences. Statistical machine learning methods such as Alternating Decision Tree and Multilayer Perceptron can replace the energy based classifier, with advantage of very significantly reduced computational time and simplicity to perform the analysis. Additionally, a decision tree provides a set of very easily interpretable rules.

Expertise Reversal Effect and Sequencing of Learning Tasks in Online English as a Second Language Learning Environment

ERIC Educational Resources Information Center

Song, Donggil

2016-01-01

The aim of this paper is to examine the effects of sequencing instructional materials and learners' prior knowledge on learning ESL (English as a second language) through an online learning course. 121 fifth-grade students from an elementary school in Korea participated in the study. Each participant was allocated to one cell of a 2 × 2…

To What Extent Can Motor Imagery Replace Motor Execution While Learning a Fine Motor Skill?

PubMed Central

Sobierajewicz, Jagna; Szarkiewicz, Sylwia; Przekoracka-Krawczyk, Anna; Jaśkowski, Wojciech; van der Lubbe, Rob

2016-01-01

Motor imagery is generally thought to share common mechanisms with motor execution. In the present study, we examined to what extent learning a fine motor skill by motor imagery may substitute physical practice. Learning effects were assessed by manipulating the proportion of motor execution and motor imagery trials. Additionally, learning effects were compared between participants with an explicit motor imagery instruction and a control group. A Go/NoGo discrete sequence production (DSP) task was employed, wherein a five-stimulus sequence presented on each trial indicated the required sequence of finger movements after a Go signal. In the case of a NoGo signal, participants either had to imagine carrying out the response sequence (the motor imagery group), or the response sequence had to be withheld (the control group). Two practice days were followed by a final test day on which all sequences had to be executed. Learning effects were assessed by computing response times (RTs) and the percentages of correct responses (PCs). The electroencephalogram (EEG ) was additionally measured on this test day to examine whether motor preparation and the involvement of visual short term memory (VST M) depended on the amount of physical/mental practice. Accuracy data indicated strong learning effects. However, a substantial amount of physical practice was required to reach an optimal speed. EEG results suggest the involvement of VST M for sequences that had less or no physical practice in both groups. The absence of differences between the motor imagery and the control group underlines the possibility that motor preparation may actually resemble motor imagery. PMID:28154614

To What Extent Can Motor Imagery Replace Motor Execution While Learning a Fine Motor Skill?

PubMed

Sobierajewicz, Jagna; Szarkiewicz, Sylwia; Przekoracka-Krawczyk, Anna; Jaśkowski, Wojciech; van der Lubbe, Rob

2016-01-01

Motor imagery is generally thought to share common mechanisms with motor execution. In the present study, we examined to what extent learning a fine motor skill by motor imagery may substitute physical practice. Learning effects were assessed by manipulating the proportion of motor execution and motor imagery trials. Additionally, learning effects were compared between participants with an explicit motor imagery instruction and a control group. A Go/NoGo discrete sequence production (DSP) task was employed, wherein a five-stimulus sequence presented on each trial indicated the required sequence of finger movements after a Go signal. In the case of a NoGo signal, participants either had to imagine carrying out the response sequence (the motor imagery group), or the response sequence had to be withheld (the control group). Two practice days were followed by a final test day on which all sequences had to be executed. Learning effects were assessed by computing response times (RTs) and the percentages of correct responses (PCs). The electroencephalogram (EEG ) was additionally measured on this test day to examine whether motor preparation and the involvement of visual short term memory (VST M) depended on the amount of physical/mental practice. Accuracy data indicated strong learning effects. However, a substantial amount of physical practice was required to reach an optimal speed. EEG results suggest the involvement of VST M for sequences that had less or no physical practice in both groups. The absence of differences between the motor imagery and the control group underlines the possibility that motor preparation may actually resemble motor imagery.

Domain general learning: Infants use social and non-social cues when learning object statistics

PubMed Central

Barry, Ryan A.; Graf Estes, Katharine; Rivera, Susan M.

2015-01-01

Previous research has shown that infants can learn from social cues. But is a social cue more effective at directing learning than a non-social cue? This study investigated whether 9-month-old infants (N = 55) could learn a visual statistical regularity in the presence of a distracting visual sequence when attention was directed by either a social cue (a person) or a non-social cue (a rectangle). The results show that both social and non-social cues can guide infants’ attention to a visual shape sequence (and away from a distracting sequence). The social cue more effectively directed attention than the non-social cue during the familiarization phase, but the social cue did not result in significantly stronger learning than the non-social cue. The findings suggest that domain general attention mechanisms allow for the comparable learning seen in both conditions. PMID:25999879

Interaction with Machine Improvisation

NASA Astrophysics Data System (ADS)

Assayag, Gerard; Bloch, George; Cont, Arshia; Dubnov, Shlomo

We describe two multi-agent architectures for an improvisation oriented musician-machine interaction systems that learn in real time from human performers. The improvisation kernel is based on sequence modeling and statistical learning. We present two frameworks of interaction with this kernel. In the first, the stylistic interaction is guided by a human operator in front of an interactive computer environment. In the second framework, the stylistic interaction is delegated to machine intelligence and therefore, knowledge propagation and decision are taken care of by the computer alone. The first framework involves a hybrid architecture using two popular composition/performance environments, Max and OpenMusic, that are put to work and communicate together, each one handling the process at a different time/memory scale. The second framework shares the same representational schemes with the first but uses an Active Learning architecture based on collaborative, competitive and memory-based learning to handle stylistic interactions. Both systems are capable of processing real-time audio/video as well as MIDI. After discussing the general cognitive background of improvisation practices, the statistical modelling tools and the concurrent agent architecture are presented. Then, an Active Learning scheme is described and considered in terms of using different improvisation regimes for improvisation planning. Finally, we provide more details about the different system implementations and describe several performances with the system.

Gift from statistical learning: Visual statistical learning enhances memory for sequence elements and impairs memory for items that disrupt regularities.

PubMed

Otsuka, Sachio; Saiki, Jun

2016-02-01

Prior studies have shown that visual statistical learning (VSL) enhances familiarity (a type of memory) of sequences. How do statistical regularities influence the processing of each triplet element and inserted distractors that disrupt the regularity? Given that increased attention to triplets induced by VSL and inhibition of unattended triplets, we predicted that VSL would promote memory for each triplet constituent, and degrade memory for inserted stimuli. Across the first two experiments, we found that objects from structured sequences were more likely to be remembered than objects from random sequences, and that letters (Experiment 1) or objects (Experiment 2) inserted into structured sequences were less likely to be remembered than those inserted into random sequences. In the subsequent two experiments, we examined an alternative account for our results, whereby the difference in memory for inserted items between structured and random conditions is due to individuation of items within random sequences. Our findings replicated even when control letters (Experiment 3A) or objects (Experiment 3B) were presented before or after, rather than inserted into, random sequences. Our findings suggest that statistical learning enhances memory for each item in a regular set and impairs memory for items that disrupt the regularity. Copyright © 2015 Elsevier B.V. All rights reserved.

Modeling effects of intrinsic and extrinsic rewards on the competition between striatal learning systems

PubMed Central

Boedecker, Joschka; Lampe, Thomas; Riedmiller, Martin

2013-01-01

A common assumption in psychology, economics, and other fields holds that higher performance will result if extrinsic rewards (such as money) are offered as an incentive. While this principle seems to work well for tasks that require the execution of the same sequence of steps over and over, with little uncertainty about the process, in other cases, especially where creative problem solving is required due to the difficulty in finding the optimal sequence of actions, external rewards can actually be detrimental to task performance. Furthermore, they have the potential to undermine intrinsic motivation to do an otherwise interesting activity. In this work, we extend a computational model of the dorsomedial and dorsolateral striatal reinforcement learning systems to account for the effects of extrinsic and intrinsic rewards. The model assumes that the brain employs both a goal-directed and a habitual learning system, and competition between both is based on the trade-off between the cost of the reasoning process and value of information. The goal-directed system elicits internal rewards when its models of the environment improve, while the habitual system, being model-free, does not. Our results account for the phenomena that initial extrinsic reward leads to reduced activity after extinction compared to the case without any initial extrinsic rewards, and that performance in complex task settings drops when higher external rewards are promised. We also test the hypothesis that external rewards bias the competition in favor of the computationally efficient, but cruder and less flexible habitual system, which can negatively influence intrinsic motivation and task performance in the class of tasks we consider. PMID:24137146

Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts.

PubMed

Cocos, Anne; Fiks, Alexander G; Masino, Aaron J

2017-07-01

Social media is an important pharmacovigilance data source for adverse drug reaction (ADR) identification. Human review of social media data is infeasible due to data quantity, thus natural language processing techniques are necessary. Social media includes informal vocabulary and irregular grammar, which challenge natural language processing methods. Our objective is to develop a scalable, deep-learning approach that exceeds state-of-the-art ADR detection performance in social media. We developed a recurrent neural network (RNN) model that labels words in an input sequence with ADR membership tags. The only input features are word-embedding vectors, which can be formed through task-independent pretraining or during ADR detection training. Our best-performing RNN model used pretrained word embeddings created from a large, non-domain-specific Twitter dataset. It achieved an approximate match F-measure of 0.755 for ADR identification on the dataset, compared to 0.631 for a baseline lexicon system and 0.65 for the state-of-the-art conditional random field model. Feature analysis indicated that semantic information in pretrained word embeddings boosted sensitivity and, combined with contextual awareness captured in the RNN, precision. Our model required no task-specific feature engineering, suggesting generalizability to additional sequence-labeling tasks. Learning curve analysis showed that our model reached optimal performance with fewer training examples than the other models. ADR detection performance in social media is significantly improved by using a contextually aware model and word embeddings formed from large, unlabeled datasets. The approach reduces manual data-labeling requirements and is scalable to large social media datasets. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Hierarchical Traces for Reduced NSM Memory Requirements

NASA Astrophysics Data System (ADS)

Dahl, Torbjørn S.

This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based reinforcement learning algorithm. A hierarchical memory representation reduces the memory requirements by allowing traces to share common sub-sequences. We present moderated mechanisms for estimating discounted future rewards and for dealing with hidden state using hierarchical memory. We also present an experimental analysis of how the sub-sequence length affects the memory compression achieved and show that the reduced memory requirements do not effect the speed of learning. Finally, we analyse and discuss the persistence of the sub-sequences independent of specific trace instances.

Visual Prediction in Infancy: What Is the Association with Later Vocabulary?

ERIC Educational Resources Information Center

Ellis, Erica M.; Gonzalez, Marybel Robledo; Deák, Gedeon O.

2014-01-01

Young infants can learn statistical regularities and patterns in sequences of events. Studies have demonstrated a relationship between early sequence learning skills and later development of cognitive and language skills. We investigated the relation between infants' visual response speed to novel event sequences, and their later receptive and…

Study Sequence Matters for the Inductive Learning of Cognitive Concepts

ERIC Educational Resources Information Center

Sana, Faria; Yan, Veronica X.; Kim, Joseph A.

2017-01-01

The sequence in which problems of different concepts are studied during instruction impacts concept learning. For example, several problems of a given concept can be studied together (blocking) or several problems of different concepts can be studied together (interleaving). In the current study, we demonstrate that the 2 sequences impact concept…

Temporal Dynamics in Auditory Perceptual Learning: Impact of Sequencing and Incidental Learning

ERIC Educational Resources Information Center

Church, Barbara A.; Mercado, Eduardo, III; Wisniewski, Matthew G.; Liu, Estella H.

2013-01-01

Training can improve perceptual sensitivities. We examined whether the temporal dynamics and the incidental versus intentional nature of training are important. Within the context of a birdsong rate discrimination task, we examined whether the sequencing of pretesting exposure to the stimuli mattered. Easy-to-hard (progressive) sequencing of…

Knowledge-transfer learning for prediction of matrix metalloprotease substrate-cleavage sites.

PubMed

Wang, Yanan; Song, Jiangning; Marquez-Lago, Tatiana T; Leier, André; Li, Chen; Lithgow, Trevor; Webb, Geoffrey I; Shen, Hong-Bin

2017-07-18

Matrix Metalloproteases (MMPs) are an important family of proteases that play crucial roles in key cellular and disease processes. Therefore, MMPs constitute important targets for drug design, development and delivery. Advanced proteomic technologies have identified type-specific target substrates; however, the complete repertoire of MMP substrates remains uncharacterized. Indeed, computational prediction of substrate-cleavage sites associated with MMPs is a challenging problem. This holds especially true when considering MMPs with few experimentally verified cleavage sites, such as for MMP-2, -3, -7, and -8. To fill this gap, we propose a new knowledge-transfer computational framework which effectively utilizes the hidden shared knowledge from some MMP types to enhance predictions of other, distinct target substrate-cleavage sites. Our computational framework uses support vector machines combined with transfer machine learning and feature selection. To demonstrate the value of the model, we extracted a variety of substrate sequence-derived features and compared the performance of our method using both 5-fold cross-validation and independent tests. The results show that our transfer-learning-based method provides a robust performance, which is at least comparable to traditional feature-selection methods for prediction of MMP-2, -3, -7, -8, -9 and -12 substrate-cleavage sites on independent tests. The results also demonstrate that our proposed computational framework provides a useful alternative for the characterization of sequence-level determinants of MMP-substrate specificity.

The Intention Superiority Effect in Motor Skill Learning

ERIC Educational Resources Information Center

Badets, Arnaud; Blandin, Yannick; Bouquet, Cedric A.; Shea, Charles H.

2006-01-01

Three experiments were conducted to determine if the intention to perform motor sequences in the future results in similar patterns of activation and inhibition as observed for verbal scripts. In Experiments 1 and 2, intention was induced by informing one group that they would be tested on the tasks following acquisition; the other group was not…

The Effect of Extraversion and Presentation Order on Learning from Picture-Commentary Sequences by Children.

ERIC Educational Resources Information Center

Riding, R. J.; Wicks, B. J.

1978-01-01

Groups of extrovert, ambivert, and introvert children, aged 8, saw pictures with a taped commentary about each. On an immediate recall test, extroverts recalled most if given the commentary before the picture, introverts did best when the picture came first, and ambiverts performed similarly in both conditions. (Author/SJL)

Non-Symbolic Arithmetic Abilities and Mathematics Achievement in the First Year of Formal Schooling

ERIC Educational Resources Information Center

Gilmore, Camilla K.; McCarthy, Shannon E.; Spelke, Elizabeth S.

2010-01-01

Children take years to learn symbolic arithmetic. Nevertheless, non-human animals, human adults with no formal education, and human infants represent approximate number in arrays of objects and sequences of events, and they use these capacities to perform approximate addition and subtraction. Do children harness these abilities when they begin to…

Standards for Technological Literacy and STEM Education Delivery through Career and Technical Education Programs

ERIC Educational Resources Information Center

Asunda, Paul A.

2012-01-01

At a minimum, employers rely on career and technical education (CTE) and workforce training systems to supply workers able to perform in their jobs. In CTE classes that seek to integrate science, technology, engineering, and mathematics (STEM) concepts, it falls to the instructors to design and sequence the learning experiences that will promote…

Should bilingual children learn reading in two languages at the same time or in sequence?

PubMed Central

Berens, Melody S.; Kovelman, Ioulia; Petitto, Laura-Ann

2013-01-01

Is it best to learn reading in two languages simultaneously or sequentially? We observed 2nd and 3rd grade children in two-way dual-language learning contexts: (i) 50:50 or Simultaneous dual-language (two languages within same developmental period) and (ii) 90:10 or Sequential dual-language (one language, followed gradually by the other). They were compared to matched monolingual English-only children in single-language English schools. Bilinguals (home language was Spanish only, English-only, or Spanish and English in dual-language schools), were tested in both languages, and monolingual children were tested in English using standardized reading and language tasks. Bilinguals in 50:50 programs performed better than bilinguals in 90:10 programs on English Irregular Words and Passage Comprehension tasks, suggesting language and reading facilitation for underlying grammatical class and linguistic structure analyses. By contrast, bilinguals in 90:10 programs performed better than bilinguals in the 50:50 programs on English Phonological Awareness and Reading Decoding tasks, suggesting language and reading facilitation for surface phonological regularity analysis. Notably, children from English-only homes in dual-language learning contexts performed equally well, or better than, children from monolingual English-only homes in single-language learning contexts. Overall, the findings provide tantalizing evidence that dual-language learning during the same developmental period may provide bilingual reading advantages. PMID:23794952

Later learning stages in procedural memory are impaired in children with Specific Language Impairment.

PubMed

Desmottes, Lise; Meulemans, Thierry; Maillart, Christelle

2016-01-01

According to the Procedural Deficit Hypothesis (PDH), difficulties in the procedural memory system may contribute to the language difficulties encountered by children with Specific Language Impairment (SLI). Most studies investigating the PDH have used the sequence learning paradigm; however these studies have principally focused on initial sequence learning in a single practice session. The present study sought to extend these investigations by assessing the consolidation stage and longer-term retention of implicit sequence-specific knowledge in 42 children with or without SLI. Both groups of children completed a serial reaction time task and were tested 24h and one week after practice. Results showed that children with SLI succeeded as well as children with typical development (TD) in the early acquisition stage of the sequence learning task. However, as training blocks progressed, only TD children improved their sequence knowledge while children with SLI did not appear to evolve any more. Moreover, children with SLI showed a lack of the consolidation gains in sequence knowledge displayed by the TD children. Overall, these results were in line with the predictions of the PDH and suggest that later learning stages in procedural memory are impaired in SLI. Copyright © 2015 Elsevier Ltd. All rights reserved.