Modeling Time Series Data for Supervised Learning

ERIC Educational Resources Information Center

Baydogan, Mustafa Gokce

2012-01-01

Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…

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).

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.

Building a responsive teacher: how temporal contingency of gaze interaction influences word learning with virtual tutors

PubMed Central

Lee, Hanju; Kanakogi, Yasuhiro; Hiraki, Kazuo

2015-01-01

Animated pedagogical agents are lifelike virtual characters designed to augment learning. A review of developmental psychology literature led to the hypothesis that the temporal contingency of such agents would promote human learning. We developed a Pedagogical Agent with Gaze Interaction (PAGI), an experimental animated pedagogical agent that engages in gaze interaction with students. In this study, university students learned words of a foreign language, with temporally contingent PAGI (live group) or recorded version of PAGI (recorded group), which played pre-recorded sequences from live sessions. The result revealed that students in the live group scored considerably better than those in the recorded group. The finding indicates that incorporating temporal contingency of gaze interaction from a pedagogical agent has positive effect on learning. PMID:26064584

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

PubMed Central

Lindén, Henrik; Lansner, Anders

2016-01-01

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model’s feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison. PMID:27213810

Decoding the future from past experience: learning shapes predictions in early visual cortex.

PubMed

Luft, Caroline D B; Meeson, Alan; Welchman, Andrew E; Kourtzi, Zoe

2015-05-01

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory representations as early as in primary visual cortex. Copyright © 2015 the American Physiological Society.

A corticostriatal deficit promotes temporal distortion of automatic action in ageing

PubMed Central

Matamales, Miriam; Skrbis, Zala; Bailey, Matthew R; Balsam, Peter D; Balleine, Bernard W; Götz, Jürgen

2017-01-01

The acquisition of motor skills involves implementing action sequences that increase task efficiency while reducing cognitive loads. This learning capacity depends on specific cortico-basal ganglia circuits that are affected by normal ageing. Here, combining a series of novel behavioural tasks with extensive neuronal mapping and targeted cell manipulations in mice, we explored how ageing of cortico-basal ganglia networks alters the microstructure of action throughout sequence learning. We found that, after extended training, aged mice produced shorter actions and displayed squeezed automatic behaviours characterised by ultrafast oligomeric action chunks that correlated with deficient reorganisation of corticostriatal activity. Chemogenetic disruption of a striatal subcircuit in young mice reproduced age-related within-sequence features, and the introduction of an action-related feedback cue temporarily restored normal sequence structure in aged mice. Our results reveal static properties of aged cortico-basal ganglia networks that introduce temporal limits to action automaticity, something that can compromise procedural learning in ageing. PMID:29058672

Interleaved Practice in Multi-Dimensional Learning Tasks: Which Dimension Should We Interleave?

ERIC Educational Resources Information Center

Rau, Martina A.; Aleven, Vincent; Rummel, Nikol

2013-01-01

Research shows that multiple representations can enhance student learning. Many curricula use multiple representations across multiple task types. The temporal sequence of representations and task types is likely to impact student learning. Research on contextual interference shows that interleaving learning tasks leads to better learning results…

The basal ganglia is necessary for learning spectral, but not temporal features of birdsong

PubMed Central

Ali, Farhan; Fantana, Antoniu L.; Burak, Yoram; Ölveczky, Bence P.

2013-01-01

Executing a motor skill requires the brain to control which muscles to activate at what times. How these aspects of control - motor implementation and timing - are acquired, and whether the learning processes underlying them differ, is not well understood. To address this we used a reinforcement learning paradigm to independently manipulate both spectral and temporal features of birdsong, a complex learned motor sequence, while recording and perturbing activity in underlying circuits. Our results uncovered a striking dissociation in how neural circuits underlie learning in the two domains. The basal ganglia was required for modifying spectral, but not temporal structure. This functional dissociation extended to the descending motor pathway, where recordings from a premotor cortex analogue nucleus reflected changes to temporal, but not spectral structure. Our results reveal a strategy in which the nervous system employs different and largely independent circuits to learn distinct aspects of a motor skill. PMID:24075977

The Eyes Know Time: A Novel Paradigm to Reveal the Development of Temporal Memory

ERIC Educational Resources Information Center

Pathman, Thanujeni; Ghetti, Simona

2014-01-01

Temporal memory in 7-year-olds, 10-year-olds, and young adults (N = 78) was examined introducing a novel eye-movement paradigm. Participants learned object sequences and were tested under three conditions: temporal order, temporal context, and recognition. Age-related improvements in accuracy were found across conditions; accuracy in the temporal…

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.

Integration of Temporal and Ordinal Information During Serial Interception Sequence Learning

PubMed Central

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

2011-01-01

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

Simultaneous detection of landmarks and key-frame in cardiac perfusion MRI using a joint spatial-temporal context model

NASA Astrophysics Data System (ADS)

Lu, Xiaoguang; Xue, Hui; Jolly, Marie-Pierre; Guetter, Christoph; Kellman, Peter; Hsu, Li-Yueh; Arai, Andrew; Zuehlsdorff, Sven; Littmann, Arne; Georgescu, Bogdan; Guehring, Jens

2011-03-01

Cardiac perfusion magnetic resonance imaging (MRI) has proven clinical significance in diagnosis of heart diseases. However, analysis of perfusion data is time-consuming, where automatic detection of anatomic landmarks and key-frames from perfusion MR sequences is helpful for anchoring structures and functional analysis of the heart, leading toward fully automated perfusion analysis. Learning-based object detection methods have demonstrated their capabilities to handle large variations of the object by exploring a local region, i.e., context. Conventional 2D approaches take into account spatial context only. Temporal signals in perfusion data present a strong cue for anchoring. We propose a joint context model to encode both spatial and temporal evidence. In addition, our spatial context is constructed not only based on the landmark of interest, but also the landmarks that are correlated in the neighboring anatomies. A discriminative model is learned through a probabilistic boosting tree. A marginal space learning strategy is applied to efficiently learn and search in a high dimensional parameter space. A fully automatic system is developed to simultaneously detect anatomic landmarks and key frames in both RV and LV from perfusion sequences. The proposed approach was evaluated on a database of 373 cardiac perfusion MRI sequences from 77 patients. Experimental results of a 4-fold cross validation show superior landmark detection accuracies of the proposed joint spatial-temporal approach to the 2D approach that is based on spatial context only. The key-frame identification results are promising.

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

Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders

NASA Astrophysics Data System (ADS)

Rußwurm, Marc; Körner, Marco

2018-03-01

Earth observation (EO) sensors deliver data with daily or weekly temporal resolution. Most land use and land cover (LULC) approaches, however, expect cloud-free and mono-temporal observations. The increasing temporal capabilities of today's sensors enables the use of temporal, along with spectral and spatial features. Domains, such as speech recognition or neural machine translation, work with inherently temporal data and, today, achieve impressive results using sequential encoder-decoder structures. Inspired by these sequence-to-sequence models, we adapt an encoder structure with convolutional recurrent layers in order to approximate a phenological model for vegetation classes based on a temporal sequence of Sentinel 2 (S2) images. In our experiments, we visualize internal activations over a sequence of cloudy and non-cloudy images and find several recurrent cells, which reduce the input activity for cloudy observations. Hence, we assume that our network has learned cloud-filtering schemes solely from input data, which could alleviate the need for tedious cloud-filtering as a preprocessing step for many EO approaches. Moreover, using unfiltered temporal series of top-of-atmosphere (TOA) reflectance data, we achieved in our experiments state-of-the-art classification accuracies on a large number of crop classes with minimal preprocessing compared to other classification approaches.

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.

Navigating complex decision spaces: Problems and paradigms in sequential choice

PubMed Central

Walsh, Matthew M.; Anderson, John R.

2015-01-01

To behave adaptively, we must learn from the consequences of our actions. Doing so is difficult when the consequences of an action follow a delay. This introduces the problem of temporal credit assignment. When feedback follows a sequence of decisions, how should the individual assign credit to the intermediate actions that comprise the sequence? Research in reinforcement learning provides two general solutions to this problem: model-free reinforcement learning and model-based reinforcement learning. In this review, we examine connections between stimulus-response and cognitive learning theories, habitual and goal-directed control, and model-free and model-based reinforcement learning. We then consider a range of problems related to temporal credit assignment. These include second-order conditioning and secondary reinforcers, latent learning and detour behavior, partially observable Markov decision processes, actions with distributed outcomes, and hierarchical learning. We ask whether humans and animals, when faced with these problems, behave in a manner consistent with reinforcement learning techniques. Throughout, we seek to identify neural substrates of model-free and model-based reinforcement learning. The former class of techniques is understood in terms of the neurotransmitter dopamine and its effects in the basal ganglia. The latter is understood in terms of a distributed network of regions including the prefrontal cortex, medial temporal lobes cerebellum, and basal ganglia. Not only do reinforcement learning techniques have a natural interpretation in terms of human and animal behavior, but they also provide a useful framework for understanding neural reward valuation and action selection. PMID:23834192

Temporal Information Processing as a Basis for Auditory Comprehension: Clinical Evidence from Aphasic Patients

ERIC Educational Resources Information Center

Oron, Anna; Szymaszek, Aneta; Szelag, Elzbieta

2015-01-01

Background: Temporal information processing (TIP) underlies many aspects of cognitive functions like language, motor control, learning, memory, attention, etc. Millisecond timing may be assessed by sequencing abilities, e.g. the perception of event order. It may be measured with auditory temporal-order-threshold (TOT), i.e. a minimum time gap…

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

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

Implicit perceptual-motor skill learning in mild cognitive impairment and Parkinson's disease.

PubMed

Gobel, Eric W; Blomeke, Kelsey; Zadikoff, Cindy; Simuni, Tanya; Weintraub, Sandra; Reber, Paul J

2013-05-01

Implicit skill learning is hypothesized to depend on nondeclarative memory that operates independent of the medial temporal lobe (MTL) memory system and instead depends on cortico striatal circuits between the basal ganglia and cortical areas supporting motor function and planning. Research with the Serial Reaction Time (SRT) task suggests that patients with memory disorders due to MTL damage exhibit normal implicit sequence learning. However, reports of intact learning rely on observations of no group differences, leading to speculation as to whether implicit sequence learning is fully intact in these patients. Patients with Parkinson's disease (PD) often exhibit impaired sequence learning, but this impairment is not universally observed. Implicit perceptual-motor sequence learning was examined using the Serial Interception Sequence Learning (SISL) task in patients with amnestic Mild Cognitive Impairment (MCI; n = 11) and patients with PD (n = 15). Sequence learning in SISL is resistant to explicit learning and individually adapted task difficulty controls for baseline performance differences. Patients with MCI exhibited robust sequence learning, equivalent to healthy older adults (n = 20), supporting the hypothesis that the MTL does not contribute to learning in this task. In contrast, the majority of patients with PD exhibited no sequence-specific learning in spite of matched overall task performance. Two patients with PD exhibited performance indicative of an explicit compensatory strategy suggesting that impaired implicit learning may lead to greater reliance on explicit memory in some individuals. The differences in learning between patient groups provides strong evidence in favor of implicit sequence learning depending solely on intact basal ganglia function with no contribution from the MTL memory system.

Learning of spatio-temporal codes in a coupled oscillator system.

PubMed

Orosz, Gábor; Ashwin, Peter; Townley, Stuart

2009-07-01

In this paper, we consider a learning strategy that allows one to transmit information between two coupled phase oscillator systems (called teaching and learning systems) via frequency adaptation. The dynamics of these systems can be modeled with reference to a number of partially synchronized cluster states and transitions between them. Forcing the teaching system by steady but spatially nonhomogeneous inputs produces cyclic sequences of transitions between the cluster states, that is, information about inputs is encoded via a "winnerless competition" process into spatio-temporal codes. The large variety of codes can be learned by the learning system that adapts its frequencies to those of the teaching system. We visualize the dynamics using "weighted order parameters (WOPs)" that are analogous to "local field potentials" in neural systems. Since spatio-temporal coding is a mechanism that appears in olfactory systems, the developed learning rules may help to extract information from these neural ensembles.

Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences

PubMed Central

Bouchard, Kristofer E.; Ganguli, Surya; Brainard, Michael S.

2015-01-01

The majority of distinct sensory and motor events occur as temporally ordered sequences with rich probabilistic structure. Sequences can be characterized by the probability of transitioning from the current state to upcoming states (forward probability), as well as the probability of having transitioned to the current state from previous states (backward probability). Despite the prevalence of probabilistic sequencing of both sensory and motor events, the Hebbian mechanisms that mold synapses to reflect the statistics of experienced probabilistic sequences are not well understood. Here, we show through analytic calculations and numerical simulations that Hebbian plasticity (correlation, covariance, and STDP) with pre-synaptic competition can develop synaptic weights equal to the conditional forward transition probabilities present in the input sequence. In contrast, post-synaptic competition can develop synaptic weights proportional to the conditional backward probabilities of the same input sequence. We demonstrate that to stably reflect the conditional probability of a neuron's inputs and outputs, local Hebbian plasticity requires balance between competitive learning forces that promote synaptic differentiation and homogenizing learning forces that promote synaptic stabilization. The balance between these forces dictates a prior over the distribution of learned synaptic weights, strongly influencing both the rate at which structure emerges and the entropy of the final distribution of synaptic weights. Together, these results demonstrate a simple correspondence between the biophysical organization of neurons, the site of synaptic competition, and the temporal flow of information encoded in synaptic weights by Hebbian plasticity while highlighting the utility of balancing learning forces to accurately encode probability distributions, and prior expectations over such probability distributions. PMID:26257637

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.

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

Spatiotemporal topology and temporal sequence identification with an adaptive time-delay neural network

NASA Astrophysics Data System (ADS)

Lin, Daw-Tung; Ligomenides, Panos A.; Dayhoff, Judith E.

1993-08-01

Inspired from the time delays that occur in neurobiological signal transmission, we describe an adaptive time delay neural network (ATNN) which is a powerful dynamic learning technique for spatiotemporal pattern transformation and temporal sequence identification. The dynamic properties of this network are formulated through the adaptation of time-delays and synapse weights, which are adjusted on-line based on gradient descent rules according to the evolution of observed inputs and outputs. We have applied the ATNN to examples that possess spatiotemporal complexity, with temporal sequences that are completed by the network. The ATNN is able to be applied to pattern completion. Simulation results show that the ATNN learns the topology of a circular and figure eight trajectories within 500 on-line training iterations, and reproduces the trajectory dynamically with very high accuracy. The ATNN was also trained to model the Fourier series expansion of the sum of different odd harmonics. The resulting network provides more flexibility and efficiency than the TDNN and allows the network to seek optimal values for time-delays as well as optimal synapse weights.

Implicit Perceptual-Motor Skill Learning in Mild Cognitive Impairment and Parkinson's Disease

PubMed Central

Gobel, Eric W.; Blomeke, Kelsey; Zadikoff, Cindy; Simuni, Tanya; Weintraub, Sandy; Reber, Paul J.

2015-01-01

Objective Implicit skill learning is hypothesized to depend on nondeclarative memory that operates independent of the medial temporal lobe (MTL) memory system and instead depends on cortico-striatal circuits between the basal ganglia and cortical areas supporting motor function and planning. Research with the Serial Reaction Time (SRT) task suggests that patients with memory-disorders due to MTL damage exhibit normal implicit sequence learning. However, reports of intact learning rely on observations of no group differences, leading to speculation whether implicit sequence learning is fully intact in these patients. Patients with Parkinson's Disease (PD) often exhibit impaired sequence learning, but this impairment is not universally observed. Method Implicit perceptual-motor sequence learning was examined using the Serial Interception Sequence Learning (SISL) task in patients with amnestic Mild Cognitive Impairment (MCI; n=11) and patients with PD (n=15). Sequence learning in SISL is resistant to explicit learning and individually adapted task difficulty controls for baseline performance differences. Results Patients with MCI exhibited robust sequence learning, equivalent to healthy older adults (n=20), supporting the hypothesis that the MTL does not contribute to learning in this task. In contrast, the majority of patients with PD exhibited no sequence-specific learning in spite of matched overall task performance. Two patients with PD exhibited performance indicative of an explicit compensatory strategy suggesting that impaired implicit learning may lead to greater reliance on explicit memory in some individuals. Conclusion The differences in learning between patient groups provides strong evidence in favor of implicit sequence learning depending solely on intact basal ganglia function with no contribution from the MTL memory system. PMID:23688213

Formal Methods for Information Protection Technology. Task 2: Mathematical Foundations, Architecture and Principles of Implementation of Multi-Agent Learning Components for Attack Detection in Computer Networks. Part 2

DTIC Science & Technology

2003-11-01

Lafayette, IN 47907. [Lane et al-97b] T. Lane and C . E. Brodley. Sequence matching and learning in anomaly detection for computer security. Proceedings of...Mining, pp 259-263. 1998. [Lane et al-98b] T. Lane and C . E. Brodley. Temporal sequence learning and data reduction for anomaly detection ...W. Lee, C . Park, and S. Stolfo. Towards Automatic Intrusion Detection using NFR. 1st USENIX Workshop on Intrusion Detection and Network Monitoring

An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data

PubMed Central

Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

2015-01-01

This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems. PMID:26752800

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

Deep learning on temporal-spectral data for anomaly detection

NASA Astrophysics Data System (ADS)

Ma, King; Leung, Henry; Jalilian, Ehsan; Huang, Daniel

2017-05-01

Detecting anomalies is important for continuous monitoring of sensor systems. One significant challenge is to use sensor data and autonomously detect changes that cause different conditions to occur. Using deep learning methods, we are able to monitor and detect changes as a result of some disturbance in the system. We utilize deep neural networks for sequence analysis of time series. We use a multi-step method for anomaly detection. We train the network to learn spectral and temporal features from the acoustic time series. We test our method using fiber-optic acoustic data from a pipeline.

Temporal information processing in short- and long-term memory of patients with schizophrenia.

PubMed

Landgraf, Steffen; Steingen, Joerg; Eppert, Yvonne; Niedermeyer, Ulrich; van der Meer, Elke; Krueger, Frank

2011-01-01

Cognitive deficits of patients with schizophrenia have been largely recognized as core symptoms of the disorder. One neglected factor that contributes to these deficits is the comprehension of time. In the present study, we assessed temporal information processing and manipulation from short- and long-term memory in 34 patients with chronic schizophrenia and 34 matched healthy controls. On the short-term memory temporal-order reconstruction task, an incidental or intentional learning strategy was deployed. Patients showed worse overall performance than healthy controls. The intentional learning strategy led to dissociable performance improvement in both groups. Whereas healthy controls improved on a performance measure (serial organization), patients improved on an error measure (inappropriate semantic clustering) when using the intentional instead of the incidental learning strategy. On the long-term memory script-generation task, routine and non-routine events of everyday activities (e.g., buying groceries) had to be generated in either chronological or inverted temporal order. Patients were slower than controls at generating events in the chronological routine condition only. They also committed more sequencing and boundary errors in the inverted conditions. The number of irrelevant events was higher in patients in the chronological, non-routine condition. These results suggest that patients with schizophrenia imprecisely access temporal information from short- and long-term memory. In short-term memory, processing of temporal information led to a reduction in errors rather than, as was the case in healthy controls, to an improvement in temporal-order recall. When accessing temporal information from long-term memory, patients were slower and committed more sequencing, boundary, and intrusion errors. Together, these results suggest that time information can be accessed and processed only imprecisely by patients who provide evidence for impaired time comprehension. This could contribute to symptomatic cognitive deficits and strategic inefficiency in schizophrenia.

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.

ISO learning approximates a solution to the inverse-controller problem in an unsupervised behavioral paradigm.

PubMed

Porr, Bernd; von Ferber, Christian; Wörgötter, Florentin

2003-04-01

In "Isotropic Sequence Order Learning" (pp. 831-864 in this issue), we introduced a novel algorithm for temporal sequence learning (ISO learning). Here, we embed this algorithm into a formal nonevaluating (teacher free) environment, which establishes a sensor-motor feedback. The system is initially guided by a fixed reflex reaction, which has the objective disadvantage that it can react only after a disturbance has occurred. ISO learning eliminates this disadvantage by replacing the reflex-loop reactions with earlier anticipatory actions. In this article, we analytically demonstrate that this process can be understood in terms of control theory, showing that the system learns the inverse controller of its own reflex. Thereby, this system is able to learn a simple form of feedforward motor control.

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.

Ongoing behavior predicts perceptual report of interval duration

PubMed Central

Gouvêa, Thiago S.; Monteiro, Tiago; Soares, Sofia; Atallah, Bassam V.; Paton, Joseph J.

2014-01-01

The ability to estimate the passage of time is essential for adaptive behavior in complex environments. Yet, it is not known how the brain encodes time over the durations necessary to explain animal behavior. Under temporally structured reinforcement schedules, animals tend to develop temporally structured behavior, and interval timing has been suggested to be accomplished by learning sequences of behavioral states. If this is true, trial to trial fluctuations in behavioral sequences should be predictive of fluctuations in time estimation. We trained rodents in an duration categorization task while continuously monitoring their behavior with a high speed camera. Animals developed highly reproducible behavioral sequences during the interval being timed. Moreover, those sequences were often predictive of perceptual report from early in the trial, providing support to the idea that animals may use learned behavioral patterns to estimate the duration of time intervals. To better resolve the issue, we propose that continuous and simultaneous behavioral and neural monitoring will enable identification of neural activity related to time perception that is not explained by ongoing behavior. PMID:24672473

Learning to segment mouse embryo cells

NASA Astrophysics Data System (ADS)

León, Juan; Pardo, Alejandro; Arbeláez, Pablo

2017-11-01

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

An ultra-sparse code underliesthe generation of neural sequences in a songbird

NASA Astrophysics Data System (ADS)

Hahnloser, Richard H. R.; Kozhevnikov, Alexay A.; Fee, Michale S.

2002-09-01

Sequences of motor activity are encoded in many vertebrate brains by complex spatio-temporal patterns of neural activity; however, the neural circuit mechanisms underlying the generation of these pre-motor patterns are poorly understood. In songbirds, one prominent site of pre-motor activity is the forebrain robust nucleus of the archistriatum (RA), which generates stereotyped sequences of spike bursts during song and recapitulates these sequences during sleep. We show that the stereotyped sequences in RA are driven from nucleus HVC (high vocal centre), the principal pre-motor input to RA. Recordings of identified HVC neurons in sleeping and singing birds show that individual HVC neurons projecting onto RA neurons produce bursts sparsely, at a single, precise time during the RA sequence. These HVC neurons burst sequentially with respect to one another. We suggest that at each time in the RA sequence, the ensemble of active RA neurons is driven by a subpopulation of RA-projecting HVC neurons that is active only at that time. As a population, these HVC neurons may form an explicit representation of time in the sequence. Such a sparse representation, a temporal analogue of the `grandmother cell' concept for object recognition, eliminates the problem of temporal interference during sequence generation and learning attributed to more distributed representations.

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.

Higher order memories for objects encountered in different spatio-temporal contexts in mice: evidence for episodic memory.

PubMed

Dere, Ekrem; Silva, Maria A De Souza; Huston, Joseph P

2004-01-01

The ability to build higher order multi-modal memories comprising information about the spatio-temporal context of events has been termed 'episodic memory'. Deficits in episodic memory are apparent in a number of neuropsychiatric diseases. Unfortunately, the development of animal models of episodic memory has made little progress. Towards the goal of such a model we devised an object exploration task for mice, providing evidence that rodents can associate object, spatial and temporal information. In our task the mice learned the temporal sequence by which identical objects were introduced into two different contexts. The 'what' component of an episodic memory was operationalized via physically distinct objects; the 'where' component through physically different contexts, and, most importantly, the 'when' component via the context-specific inverted sequence in which four objects were presented. Our results suggest that mice are able to recollect the inverted temporal sequence in which identical objects were introduced into two distinct environments. During two consecutive test trials mice showed an inverse context-specific exploration pattern regarding identical objects that were previously encountered with even frequencies. It seems that the contexts served as discriminative stimuli signaling which of the two sequences are decisive during the two test trials.

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.

Auto-Associative Recurrent Neural Networks and Long Term Dependencies in Novelty Detection for Audio Surveillance Applications

NASA Astrophysics Data System (ADS)

Rossi, A.; Montefoschi, F.; Rizzo, A.; Diligenti, M.; Festucci, C.

2017-10-01

Machine Learning applied to Automatic Audio Surveillance has been attracting increasing attention in recent years. In spite of several investigations based on a large number of different approaches, little attention had been paid to the environmental temporal evolution of the input signal. In this work, we propose an exploration in this direction comparing the temporal correlations extracted at the feature level with the one learned by a representational structure. To this aim we analysed the prediction performances of a Recurrent Neural Network architecture varying the length of the processed input sequence and the size of the time window used in the feature extraction. Results corroborated the hypothesis that sequential models work better when dealing with data characterized by temporal order. However, so far the optimization of the temporal dimension remains an open issue.

Neural Correlates of Temporal Credit Assignment in the Parietal Lobe

PubMed Central

Eisenberg, Ian; Gottlieb, Jacqueline

2014-01-01

Empirical studies of decision making have typically assumed that value learning is governed by time, such that a reward prediction error arising at a specific time triggers temporally-discounted learning for all preceding actions. However, in natural behavior, goals must be acquired through multiple actions, and each action can have different significance for the final outcome. As is recognized in computational research, carrying out multi-step actions requires the use of credit assignment mechanisms that focus learning on specific steps, but little is known about the neural correlates of these mechanisms. To investigate this question we recorded neurons in the monkey lateral intraparietal area (LIP) during a serial decision task where two consecutive eye movement decisions led to a final reward. The underlying decision trees were structured such that the two decisions had different relationships with the final reward, and the optimal strategy was to learn based on the final reward at one of the steps (the “F” step) but ignore changes in this reward at the remaining step (the “I” step). In two distinct contexts, the F step was either the first or the second in the sequence, controlling for effects of temporal discounting. We show that LIP neurons had the strongest value learning and strongest post-decision responses during the transition after the F step regardless of the serial position of this step. Thus, the neurons encode correlates of temporal credit assignment mechanisms that allocate learning to specific steps independently of temporal discounting. PMID:24523935

The Necessity of the Medial Temporal Lobe for Statistical Learning

PubMed Central

Schapiro, Anna C.; Gregory, Emma; Landau, Barbara; McCloskey, Michael; Turk-Browne, Nicholas B.

2014-01-01

The sensory input that we experience is highly patterned, and we are experts at detecting these regularities. Although the extraction of such regularities, or statistical learning (SL), is typically viewed as a cortical process, recent studies have implicated the medial temporal lobe (MTL), including the hippocampus. These studies have employed fMRI, leaving open the possibility that the MTL is involved but not necessary for SL. Here, we examined this issue in a case study of LSJ, a patient with complete bilateral hippocampal loss and broader MTL damage. In Experiments 1 and 2, LSJ and matched control participants were passively exposed to a continuous sequence of shapes, syllables, scenes, or tones containing temporal regularities in the co-occurrence of items. In a subsequent test phase, the control groups exhibited reliable SL in all conditions, successfully discriminating regularities from recombinations of the same items into novel foil sequences. LSJ, however, exhibited no SL, failing to discriminate regularities from foils. Experiment 3 ruled out more general explanations for this failure, such as inattention during exposure or difficulty following test instructions, by showing that LSJ could discriminate which individual items had been exposed. These findings provide converging support for the importance of the MTL in extracting temporal regularities. PMID:24456393

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.

Learning Orthographic Structure With Sequential Generative Neural Networks.

PubMed

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

2016-04-01

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

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

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

A semi-Markov model for mitosis segmentation in time-lapse phase contrast microscopy image sequences of stem cell populations.

PubMed

Liu, An-An; Li, Kang; Kanade, Takeo

2012-02-01

We propose a semi-Markov model trained in a max-margin learning framework for mitosis event segmentation in large-scale time-lapse phase contrast microscopy image sequences of stem cell populations. Our method consists of three steps. First, we apply a constrained optimization based microscopy image segmentation method that exploits phase contrast optics to extract candidate subsequences in the input image sequence that contains mitosis events. Then, we apply a max-margin hidden conditional random field (MM-HCRF) classifier learned from human-annotated mitotic and nonmitotic sequences to classify each candidate subsequence as a mitosis or not. Finally, a max-margin semi-Markov model (MM-SMM) trained on manually-segmented mitotic sequences is utilized to reinforce the mitosis classification results, and to further segment each mitosis into four predefined temporal stages. The proposed method outperforms the event-detection CRF model recently reported by Huh as well as several other competing methods in very challenging image sequences of multipolar-shaped C3H10T1/2 mesenchymal stem cells. For mitosis detection, an overall precision of 95.8% and a recall of 88.1% were achieved. For mitosis segmentation, the mean and standard deviation for the localization errors of the start and end points of all mitosis stages were well below 1 and 2 frames, respectively. In particular, an overall temporal location error of 0.73 ± 1.29 frames was achieved for locating daughter cell birth events.

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

Cooperation of Deterministic Dynamics and Random Noise in Production of Complex Syntactical Avian Song Sequences: A Neural Network Model

PubMed Central

Yamashita, Yuichi; Okumura, Tetsu; Okanoya, Kazuo; Tani, Jun

2011-01-01

How the brain learns and generates temporal sequences is a fundamental issue in neuroscience. The production of birdsongs, a process which involves complex learned sequences, provides researchers with an excellent biological model for this topic. The Bengalese finch in particular learns a highly complex song with syntactical structure. The nucleus HVC (HVC), a premotor nucleus within the avian song system, plays a key role in generating the temporal structures of their songs. From lesion studies, the nucleus interfacialis (NIf) projecting to the HVC is considered one of the essential regions that contribute to the complexity of their songs. However, the types of interaction between the HVC and the NIf that can produce complex syntactical songs remain unclear. In order to investigate the function of interactions between the HVC and NIf, we have proposed a neural network model based on previous biological evidence. The HVC is modeled by a recurrent neural network (RNN) that learns to generate temporal patterns of songs. The NIf is modeled as a mechanism that provides auditory feedback to the HVC and generates random noise that feeds into the HVC. The model showed that complex syntactical songs can be replicated by simple interactions between deterministic dynamics of the RNN and random noise. In the current study, the plausibility of the model is tested by the comparison between the changes in the songs of actual birds induced by pharmacological inhibition of the NIf and the changes in the songs produced by the model resulting from modification of parameters representing NIf functions. The efficacy of the model demonstrates that the changes of songs induced by pharmacological inhibition of the NIf can be interpreted as a trade-off between the effects of noise and the effects of feedback on the dynamics of the RNN of the HVC. These facts suggest that the current model provides a convincing hypothesis for the functional role of NIf–HVC interaction. PMID:21559065

Low-abundant bacteria drive compositional changes in the gut microbiota after dietary alteration.

PubMed

Benjamino, Jacquelynn; Lincoln, Stephen; Srivastava, Ranjan; Graf, Joerg

2018-05-10

As the importance of beneficial bacteria is better recognized, understanding the dynamics of symbioses becomes increasingly crucial. In many gut symbioses, it is essential to understand whether changes in host diet play a role in the persistence of the bacterial gut community. In this study, termites were fed six dietary sources and the microbial community was monitored over a 49-day period using 16S rRNA gene sequencing. A deep backpropagation artificial neural network (ANN) was used to learn how the six different lignocellulose food sources affected the temporal composition of the hindgut microbiota of the termite as well as taxon-taxon and taxon-substrate interactions. Shifts in the termite gut microbiota after diet change in each colony were observed using 16S rRNA gene sequencing and beta diversity analyses. The artificial neural network accurately predicted the relative abundances of taxa at random points in the temporal study and showed that low-abundant taxa maintain community driving correlations in the hindgut. This combinatorial approach utilizing 16S rRNA gene sequencing and deep learning revealed that low-abundant bacteria that often do not belong to the core community are drivers of the termite hindgut bacterial community composition.

Different propagation speeds of recalled sequences in plastic spiking neural networks

NASA Astrophysics Data System (ADS)

Huang, Xuhui; Zheng, Zhigang; Hu, Gang; Wu, Si; Rasch, Malte J.

2015-03-01

Neural networks can generate spatiotemporal patterns of spike activity. Sequential activity learning and retrieval have been observed in many brain areas, and e.g. is crucial for coding of episodic memory in the hippocampus or generating temporal patterns during song production in birds. In a recent study, a sequential activity pattern was directly entrained onto the neural activity of the primary visual cortex (V1) of rats and subsequently successfully recalled by a local and transient trigger. It was observed that the speed of activity propagation in coordinates of the retinotopically organized neural tissue was constant during retrieval regardless how the speed of light stimulation sweeping across the visual field during training was varied. It is well known that spike-timing dependent plasticity (STDP) is a potential mechanism for embedding temporal sequences into neural network activity. How training and retrieval speeds relate to each other and how network and learning parameters influence retrieval speeds, however, is not well described. We here theoretically analyze sequential activity learning and retrieval in a recurrent neural network with realistic synaptic short-term dynamics and STDP. Testing multiple STDP rules, we confirm that sequence learning can be achieved by STDP. However, we found that a multiplicative nearest-neighbor (NN) weight update rule generated weight distributions and recall activities that best matched the experiments in V1. Using network simulations and mean-field analysis, we further investigated the learning mechanisms and the influence of network parameters on recall speeds. Our analysis suggests that a multiplicative STDP rule with dominant NN spike interaction might be implemented in V1 since recall speed was almost constant in an NMDA-dominant regime. Interestingly, in an AMPA-dominant regime, neural circuits might exhibit recall speeds that instead follow the change in stimulus speeds. This prediction could be tested in experiments.

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.

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.

Generation of novel motor sequences: the neural correlates of musical improvisation.

PubMed

Berkowitz, Aaron L; Ansari, Daniel

2008-06-01

While some motor behavior is instinctive and stereotyped or learned and re-executed, much action is a spontaneous response to a novel set of environmental conditions. The neural correlates of both pre-learned and cued motor sequences have been previously studied, but novel motor behavior has thus far not been examined through brain imaging. In this paper, we report a study of musical improvisation in trained pianists with functional magnetic resonance imaging (fMRI), using improvisation as a case study of novel action generation. We demonstrate that both rhythmic (temporal) and melodic (ordinal) motor sequence creation modulate activity in a network of brain regions comprised of the dorsal premotor cortex, the rostral cingulate zone of the anterior cingulate cortex, and the inferior frontal gyrus. These findings are consistent with a role for the dorsal premotor cortex in movement coordination, the rostral cingulate zone in voluntary selection, and the inferior frontal gyrus in sequence generation. Thus, the invention of novel motor sequences in musical improvisation recruits a network of brain regions coordinated to generate possible sequences, select among them, and execute the decided-upon sequence.

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.

Disentangling beat perception from sequential learning and examining the influence of attention and musical abilities on ERP responses to rhythm.

PubMed

Bouwer, Fleur L; Werner, Carola M; Knetemann, Myrthe; Honing, Henkjan

2016-05-01

Beat perception is the ability to perceive temporal regularity in musical rhythm. When a beat is perceived, predictions about upcoming events can be generated. These predictions can influence processing of subsequent rhythmic events. However, statistical learning of the order of sounds in a sequence can also affect processing of rhythmic events and must be differentiated from beat perception. In the current study, using EEG, we examined the effects of attention and musical abilities on beat perception. To ensure we measured beat perception and not absolute perception of temporal intervals, we used alternating loud and soft tones to create a rhythm with two hierarchical metrical levels. To control for sequential learning of the order of the different sounds, we used temporally regular (isochronous) and jittered rhythmic sequences. The order of sounds was identical in both conditions, but only the regular condition allowed for the perception of a beat. Unexpected intensity decrements were introduced on the beat and offbeat. In the regular condition, both beat perception and sequential learning were expected to enhance detection of these deviants on the beat. In the jittered condition, only sequential learning was expected to affect processing of the deviants. ERP responses to deviants were larger on the beat than offbeat in both conditions. Importantly, this difference was larger in the regular condition than in the jittered condition, suggesting that beat perception influenced responses to rhythmic events in addition to sequential learning. The influence of beat perception was present both with and without attention directed at the rhythm. Moreover, beat perception as measured with ERPs correlated with musical abilities, but only when attention was directed at the stimuli. Our study shows that beat perception is possible when attention is not directed at a rhythm. In addition, our results suggest that attention may mediate the influence of musical abilities on beat perception. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Heterogeneous Suppression of Sequential Effects in Random Sequence Generation, but Not in Operant Learning.

PubMed

Shteingart, Hanan; Loewenstein, Yonatan

2016-01-01

There is a long history of experiments in which participants are instructed to generate a long sequence of binary random numbers. The scope of this line of research has shifted over the years from identifying the basic psychological principles and/or the heuristics that lead to deviations from randomness, to one of predicting future choices. In this paper, we used generalized linear regression and the framework of Reinforcement Learning in order to address both points. In particular, we used logistic regression analysis in order to characterize the temporal sequence of participants' choices. Surprisingly, a population analysis indicated that the contribution of the most recent trial has only a weak effect on behavior, compared to more preceding trials, a result that seems irreconcilable with standard sequential effects that decay monotonously with the delay. However, when considering each participant separately, we found that the magnitudes of the sequential effect are a monotonous decreasing function of the delay, yet these individual sequential effects are largely averaged out in a population analysis because of heterogeneity. The substantial behavioral heterogeneity in this task is further demonstrated quantitatively by considering the predictive power of the model. We show that a heterogeneous model of sequential dependencies captures the structure available in random sequence generation. Finally, we show that the results of the logistic regression analysis can be interpreted in the framework of reinforcement learning, allowing us to compare the sequential effects in the random sequence generation task to those in an operant learning task. We show that in contrast to the random sequence generation task, sequential effects in operant learning are far more homogenous across the population. These results suggest that in the random sequence generation task, different participants adopt different cognitive strategies to suppress sequential dependencies when generating the "random" sequences.

A bio-inspired system for spatio-temporal recognition in static and video imagery

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Moore, Christopher K.; Chelian, Suhas

2007-04-01

This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.

Human action recognition based on spatial-temporal descriptors using key poses

NASA Astrophysics Data System (ADS)

Hu, Shuo; Chen, Yuxin; Wang, Huaibao; Zuo, Yaqing

2014-11-01

Human action recognition is an important area of pattern recognition today due to its direct application and need in various occasions like surveillance and virtual reality. In this paper, a simple and effective human action recognition method is presented based on the key poses of human silhouette and the spatio-temporal feature. Firstly, the contour points of human silhouette have been gotten, and the key poses are learned by means of K-means clustering based on the Euclidean distance between each contour point and the centre point of the human silhouette, and then the type of each action is labeled for further match. Secondly, we obtain the trajectories of centre point of each frame, and create a spatio-temporal feature value represented by W to describe the motion direction and speed of each action. The value W contains the information of location and temporal order of each point on the trajectories. Finally, the matching stage is performed by comparing the key poses and W between training sequences and test sequences, the nearest neighbor sequences is found and its label supplied the final result. Experiments on the public available Weizmann datasets show the proposed method can improve accuracy by distinguishing amphibious poses and increase suitability for real-time applications by reducing the computational cost.

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.

Regularity and dimensional salience in temporal grouping.

PubMed

Prince, Jon B; Rice, Tim

2018-04-30

How do pitch and duration accents combine to influence the perceived grouping of musical sequences? Sequence context influences the relative importance of these accents; for example, the presence of learned structure in pitch exaggerates the effect of pitch accents at the expense of duration accents despite being irrelevant to the task and not attributable to attention (Prince, 2014b). In the current study, two experiments examined whether the presence of temporal structure has the opposite effect. Experiment 1 tested baseline conditions, in which participants (N = 30) heard sequences with various sizes of either pitch or duration accents, which implied either duple or triple groupings (accent every two or three notes, respectively). Sequences either had regular temporal structure (isochronous) or not (irregular, via using random interonset intervals). Regularity enhanced the effect of duration accents but had negligible influence on pitch accents. The accent sizes that gave the most equivalent ratings across dimension and regularity levels were used in Experiment 2 (N = 33), in which sequences contained both pitch and duration accents that suggested either duple, triple, or neutral groupings. Despite controlling for the baseline effect of regularity by selecting equally effective accent sizes, regularity had additional effects on duration accents, but only for duple groupings. Regularity did not influence the effectiveness of pitch accents when combined with duration accents. These findings offer some support for a dimensional salience hypothesis, which proposes that the presence of temporal structure should foster duration accent effectiveness at the expense of pitch accents. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach.

PubMed

Liu, Li; Shao, Ling; Li, Xuelong; Lu, Ke

2016-01-01

Extracting discriminative and robust features from video sequences is the first and most critical step in human action recognition. In this paper, instead of using handcrafted features, we automatically learn spatio-temporal motion features for action recognition. This is achieved via an evolutionary method, i.e., genetic programming (GP), which evolves the motion feature descriptor on a population of primitive 3D operators (e.g., 3D-Gabor and wavelet). In this way, the scale and shift invariant features can be effectively extracted from both color and optical flow sequences. We intend to learn data adaptive descriptors for different datasets with multiple layers, which makes fully use of the knowledge to mimic the physical structure of the human visual cortex for action recognition and simultaneously reduce the GP searching space to effectively accelerate the convergence of optimal solutions. In our evolutionary architecture, the average cross-validation classification error, which is calculated by an support-vector-machine classifier on the training set, is adopted as the evaluation criterion for the GP fitness function. After the entire evolution procedure finishes, the best-so-far solution selected by GP is regarded as the (near-)optimal action descriptor obtained. The GP-evolving feature extraction method is evaluated on four popular action datasets, namely KTH, HMDB51, UCF YouTube, and Hollywood2. Experimental results show that our method significantly outperforms other types of features, either hand-designed or machine-learned.

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

Task-related functional connectivity of the caudate mediates the association between trait mindfulness and implicit learning in older adults.

PubMed

Stillman, Chelsea M; You, Xiaozhen; Seaman, Kendra L; Vaidya, Chandan J; Howard, James H; Howard, Darlene V

2016-08-01

Accumulating evidence shows a positive relationship between mindfulness and explicit cognitive functioning, i.e., that which occurs with conscious intent and awareness. However, recent evidence suggests that there may be a negative relationship between mindfulness and implicit types of learning, or those that occur without conscious awareness or intent. Here we examined the neural mechanisms underlying the recently reported negative relationship between dispositional mindfulness and implicit probabilistic sequence learning in both younger and older adults. We tested the hypothesis that the relationship is mediated by communication, or functional connectivity, of brain regions once traditionally considered to be central to dissociable learning systems: the caudate, medial temporal lobe (MTL), and prefrontal cortex (PFC). We first replicated the negative relationship between mindfulness and implicit learning in a sample of healthy older adults (60-90 years old) who completed three event-related runs of an implicit sequence learning task. Then, using a seed-based connectivity approach, we identified task-related connectivity associated with individual differences in both learning and mindfulness. The main finding was that caudate-MTL connectivity (bilaterally) was positively correlated with learning and negatively correlated with mindfulness. Further, the strength of task-related connectivity between these regions mediated the negative relationship between mindfulness and learning. This pattern of results was limited to the older adults. Thus, at least in healthy older adults, the functional communication between two interactive learning-relevant systems can account for the relationship between mindfulness and implicit probabilistic sequence learning.

Natural image sequences constrain dynamic receptive fields and imply a sparse code.

PubMed

Häusler, Chris; Susemihl, Alex; Nawrot, Martin P

2013-11-06

In their natural environment, animals experience a complex and dynamic visual scenery. Under such natural stimulus conditions, neurons in the visual cortex employ a spatially and temporally sparse code. For the input scenario of natural still images, previous work demonstrated that unsupervised feature learning combined with the constraint of sparse coding can predict physiologically measured receptive fields of simple cells in the primary visual cortex. This convincingly indicated that the mammalian visual system is adapted to the natural spatial input statistics. Here, we extend this approach to the time domain in order to predict dynamic receptive fields that can account for both spatial and temporal sparse activation in biological neurons. We rely on temporal restricted Boltzmann machines and suggest a novel temporal autoencoding training procedure. When tested on a dynamic multi-variate benchmark dataset this method outperformed existing models of this class. Learning features on a large dataset of natural movies allowed us to model spatio-temporal receptive fields for single neurons. They resemble temporally smooth transformations of previously obtained static receptive fields and are thus consistent with existing theories. A neuronal spike response model demonstrates how the dynamic receptive field facilitates temporal and population sparseness. We discuss the potential mechanisms and benefits of a spatially and temporally sparse representation of natural visual input. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

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

Self-expressive Dictionary Learning for Dynamic 3D Reconstruction.

PubMed

Zheng, Enliang; Ji, Dinghuang; Dunn, Enrique; Frahm, Jan-Michael

2017-08-22

We target the problem of sparse 3D reconstruction of dynamic objects observed by multiple unsynchronized video cameras with unknown temporal overlap. To this end, we develop a framework to recover the unknown structure without sequencing information across video sequences. Our proposed compressed sensing framework poses the estimation of 3D structure as the problem of dictionary learning, where the dictionary is defined as an aggregation of the temporally varying 3D structures. Given the smooth motion of dynamic objects, we observe any element in the dictionary can be well approximated by a sparse linear combination of other elements in the same dictionary (i.e. self-expression). Our formulation optimizes a biconvex cost function that leverages a compressed sensing formulation and enforces both structural dependency coherence across video streams, as well as motion smoothness across estimates from common video sources. We further analyze the reconstructability of our approach under different capture scenarios, and its comparison and relation to existing methods. Experimental results on large amounts of synthetic data as well as real imagery demonstrate the effectiveness of our approach.

Learning Predictive Statistics: Strategies and Brain Mechanisms.

PubMed

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

2017-08-30

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

Video Salient Object Detection via Fully Convolutional Networks.

PubMed

Wang, Wenguan; Shen, Jianbing; Shao, Ling

This paper proposes a deep learning model to efficiently detect salient regions in videos. It addresses two important issues: 1) deep video saliency model training with the absence of sufficiently large and pixel-wise annotated video data and 2) fast video saliency training and detection. The proposed deep video saliency network consists of two modules, for capturing the spatial and temporal saliency information, respectively. The dynamic saliency model, explicitly incorporating saliency estimates from the static saliency model, directly produces spatiotemporal saliency inference without time-consuming optical flow computation. We further propose a novel data augmentation technique that simulates video training data from existing annotated image data sets, which enables our network to learn diverse saliency information and prevents overfitting with the limited number of training videos. Leveraging our synthetic video data (150K video sequences) and real videos, our deep video saliency model successfully learns both spatial and temporal saliency cues, thus producing accurate spatiotemporal saliency estimate. We advance the state-of-the-art on the densely annotated video segmentation data set (MAE of .06) and the Freiburg-Berkeley Motion Segmentation data set (MAE of .07), and do so with much improved speed (2 fps with all steps).This paper proposes a deep learning model to efficiently detect salient regions in videos. It addresses two important issues: 1) deep video saliency model training with the absence of sufficiently large and pixel-wise annotated video data and 2) fast video saliency training and detection. The proposed deep video saliency network consists of two modules, for capturing the spatial and temporal saliency information, respectively. The dynamic saliency model, explicitly incorporating saliency estimates from the static saliency model, directly produces spatiotemporal saliency inference without time-consuming optical flow computation. We further propose a novel data augmentation technique that simulates video training data from existing annotated image data sets, which enables our network to learn diverse saliency information and prevents overfitting with the limited number of training videos. Leveraging our synthetic video data (150K video sequences) and real videos, our deep video saliency model successfully learns both spatial and temporal saliency cues, thus producing accurate spatiotemporal saliency estimate. We advance the state-of-the-art on the densely annotated video segmentation data set (MAE of .06) and the Freiburg-Berkeley Motion Segmentation data set (MAE of .07), and do so with much improved speed (2 fps with all steps).

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

Dynamic Sensorimotor Planning during Long-Term Sequence Learning: The Role of Variability, Response Chunking and Planning Errors

PubMed Central

Verstynen, Timothy; Phillips, Jeff; Braun, Emily; Workman, Brett; Schunn, Christian; Schneider, Walter

2012-01-01

Many everyday skills are learned by binding otherwise independent actions into a unified sequence of responses across days or weeks of practice. Here we looked at how the dynamics of action planning and response binding change across such long timescales. Subjects (N = 23) were trained on a bimanual version of the serial reaction time task (32-item sequence) for two weeks (10 days total). Response times and accuracy both showed improvement with time, but appeared to be learned at different rates. Changes in response speed across training were associated with dynamic changes in response time variability, with faster learners expanding their variability during the early training days and then contracting response variability late in training. Using a novel measure of response chunking, we found that individual responses became temporally correlated across trials and asymptoted to set sizes of approximately 7 bound responses at the end of the first week of training. Finally, we used a state-space model of the response planning process to look at how predictive (i.e., response anticipation) and error-corrective (i.e., post-error slowing) processes correlated with learning rates for speed, accuracy and chunking. This analysis yielded non-monotonic association patterns between the state-space model parameters and learning rates, suggesting that different parts of the response planning process are relevant at different stages of long-term learning. These findings highlight the dynamic modulation of response speed, variability, accuracy and chunking as multiple movements become bound together into a larger set of responses during sequence learning. PMID:23056630

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.

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.

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

TASK-RELATED FUNCTIONAL CONNECTIVITY OF THE CAUDATE MEDIATES THE ASSOCIATION BETWEEN TRAIT MINDFULNESS AND IMPLICIT LEARNING IN OLDER ADULTS

PubMed Central

Stillman, Chelsea M.; You, Xiaozhen; Seaman, Kendra L.; Vaidya, Chandan J.; Howard, James H.; Howard, Darlene V.

2016-01-01

Accumulating evidence shows a positive relationship between mindfulness and explicit cognitive functioning, i.e., that which occurs with conscious intent and awareness. However, recent evidence suggests that there may be a negative relationship between mindfulness and implicit types of learning, or those that occur without conscious awareness or intent. Here we examined the neural mechanisms underlying the recently reported negative relationship between dispositional mindfulness and implicit probabilistic sequence learning in both younger and older adults. We tested the hypothesis that the relationship is mediated by communication, or functional connectivity, of brain regions once traditionally considered to be central to dissociable learning systems: the caudate, medial temporal lobe (MTL), and prefrontal cortex (PFC). We first replicated the negative relationship between mindfulness and implicit learning in a sample of healthy older adults (60–90 years old) who completed three event-related runs of an implicit sequence learning task. Then, using a seed-based connectivity approach, we identified task-related connectivity associated with individual differences in both learning and mindfulness. The main finding was that caudate-MTL connectivity (bilaterally) was positively correlated with learning and negatively correlated with mindfulness. Further, the strength of task-related connectivity between these regions mediated the negative relationship between mindfulness and learning. This pattern of results was limited to the older adults. Thus, at least in healthy older adults, the functional communication between two interactive learning-relevant systems can account for the relationship between mindfulness and implicit probabilistic sequence learning. PMID:27121302

Short- and Long-Term Memories Formed upon Backward Conditioning in Honeybees ("Apis Mellifera")

ERIC Educational Resources Information Center

Felsenberg, Johannes; Plath, Jenny Aino; Lorang, Steven; Morgenstern, Laura; Eisenhardt, Dorothea

2014-01-01

In classical conditioning, the temporal sequence of stimulus presentations is critical for the association between the conditioned stimulus (CS) and the unconditioned stimulus (US). In forward conditioning, the CS precedes the US and is learned as a predictor for the US. Thus it acquires properties to elicit a behavioral response, defined as…

A Revised Model of Short-Term Memory and Long-Term Learning of Verbal Sequences

ERIC Educational Resources Information Center

Burgess, Neil; Hitch, Graham J.

2006-01-01

The interaction between short- and long-term memory is studied within a model in which phonemic and (temporal) contextual information have separate influences on immediate verbal serial recall via connections with short- and long-term plasticity [Burgess, N., & Hitch, G.J. (1999). Memory for serial order: a network model of the phonological loop…

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).

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.

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.

Hemispheric asymmetries of a motor memory in a recognition test after learning a movement sequence.

PubMed

Leinen, Peter; Panzer, Stefan; Shea, Charles H

2016-11-01

Two experiments utilizing a spatial-temporal movement sequence were designed to determine if the memory of the sequence is lateralized in the left or right hemisphere. In Experiment 1, dominant right-handers were randomly assigned to one of two acquisition groups: a left-hand starter and a right-hand starter group. After an acquisition phase, reaction time (RT) was measured in a recognition test by providing the learned sequential pattern in the left or right visual half-field for 150ms. In a retention test and two transfer tests the dominant coordinate system for sequence production was evaluated. In Experiment 2 dominant left-handers and dominant right-handers had to acquire the sequence with their dominant limb. The results of Experiment 1 indicated that RT was significantly shorter when the acquired sequence was provided in the right visual field during the recognition test. The same results occurred in Experiment 2 for dominant right-handers and left-handers. These results indicated a right visual field left hemisphere advantage in the recognition test for the practiced stimulus for dominant left and right-handers, when the task was practiced with the dominant limb. Copyright © 2016 Elsevier B.V. All rights reserved.

Model-free and model-based reward prediction errors in EEG.

PubMed

Sambrook, Thomas D; Hardwick, Ben; Wills, Andy J; Goslin, Jeremy

2018-05-24

Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

Computationally modeling interpersonal trust.

PubMed

Lee, Jin Joo; Knox, W Bradley; Wormwood, Jolie B; Breazeal, Cynthia; Desteno, David

2013-01-01

We present a computational model capable of predicting-above human accuracy-the degree of trust a person has toward their novel partner by observing the trust-related nonverbal cues expressed in their social interaction. We summarize our prior work, in which we identify nonverbal cues that signal untrustworthy behavior and also demonstrate the human mind's readiness to interpret those cues to assess the trustworthiness of a social robot. We demonstrate that domain knowledge gained from our prior work using human-subjects experiments, when incorporated into the feature engineering process, permits a computational model to outperform both human predictions and a baseline model built in naiveté of this domain knowledge. We then present the construction of hidden Markov models to investigate temporal relationships among the trust-related nonverbal cues. By interpreting the resulting learned structure, we observe that models built to emulate different levels of trust exhibit different sequences of nonverbal cues. From this observation, we derived sequence-based temporal features that further improve the accuracy of our computational model. Our multi-step research process presented in this paper combines the strength of experimental manipulation and machine learning to not only design a computational trust model but also to further our understanding of the dynamics of interpersonal trust.

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.

Learning Human Actions by Combining Global Dynamics and Local Appearance.

PubMed

Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J

2014-12-01

In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.

Dynamic Encoding of Speech Sequence Probability in Human Temporal Cortex

PubMed Central

Leonard, Matthew K.; Bouchard, Kristofer E.; Tang, Claire

2015-01-01

Sensory processing involves identification of stimulus features, but also integration with the surrounding sensory and cognitive context. Previous work in animals and humans has shown fine-scale sensitivity to context in the form of learned knowledge about the statistics of the sensory environment, including relative probabilities of discrete units in a stream of sequential auditory input. These statistics are a defining characteristic of one of the most important sequential signals humans encounter: speech. For speech, extensive exposure to a language tunes listeners to the statistics of sound sequences. To address how speech sequence statistics are neurally encoded, we used high-resolution direct cortical recordings from human lateral superior temporal cortex as subjects listened to words and nonwords with varying transition probabilities between sound segments. In addition to their sensitivity to acoustic features (including contextual features, such as coarticulation), we found that neural responses dynamically encoded the language-level probability of both preceding and upcoming speech sounds. Transition probability first negatively modulated neural responses, followed by positive modulation of neural responses, consistent with coordinated predictive and retrospective recognition processes, respectively. Furthermore, transition probability encoding was different for real English words compared with nonwords, providing evidence for online interactions with high-order linguistic knowledge. These results demonstrate that sensory processing of deeply learned stimuli involves integrating physical stimulus features with their contextual sequential structure. Despite not being consciously aware of phoneme sequence statistics, listeners use this information to process spoken input and to link low-level acoustic representations with linguistic information about word identity and meaning. PMID:25948269

Task-Based Core-Periphery Organization of Human Brain Dynamics

PubMed Central

Bassett, Danielle S.; Wymbs, Nicholas F.; Rombach, M. Puck; Porter, Mason A.; Mucha, Peter J.; Grafton, Scott T.

2013-01-01

As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is to identify properties that enable robust learning of a motor skill. We measure brain activity during motor sequencing and characterize network properties based on coherent activity between brain regions. Using recently developed algorithms to detect time-evolving communities, we find that the complex reconfiguration patterns of the brain's putative functional modules that control learning can be described parsimoniously by the combined presence of a relatively stiff temporal core that is composed primarily of sensorimotor and visual regions whose connectivity changes little in time and a flexible temporal periphery that is composed primarily of multimodal association regions whose connectivity changes frequently. The separation between temporal core and periphery changes over the course of training and, importantly, is a good predictor of individual differences in learning success. The core of dynamically stiff regions exhibits dense connectivity, which is consistent with notions of core-periphery organization established previously in social networks. Our results demonstrate that core-periphery organization provides an insightful way to understand how putative functional modules are linked. This, in turn, enables the prediction of fundamental human capacities, including the production of complex goal-directed behavior. PMID:24086116

Discounting of reward sequences: a test of competing formal models of hyperbolic discounting

PubMed Central

Zarr, Noah; Alexander, William H.; Brown, Joshua W.

2014-01-01

Humans are known to discount future rewards hyperbolically in time. Nevertheless, a formal recursive model of hyperbolic discounting has been elusive until recently, with the introduction of the hyperbolically discounted temporal difference (HDTD) model. Prior to that, models of learning (especially reinforcement learning) have relied on exponential discounting, which generally provides poorer fits to behavioral data. Recently, it has been shown that hyperbolic discounting can also be approximated by a summed distribution of exponentially discounted values, instantiated in the μAgents model. The HDTD model and the μAgents model differ in one key respect, namely how they treat sequences of rewards. The μAgents model is a particular implementation of a Parallel discounting model, which values sequences based on the summed value of the individual rewards whereas the HDTD model contains a non-linear interaction. To discriminate among these models, we observed how subjects discounted a sequence of three rewards, and then we tested how well each candidate model fit the subject data. The results show that the Parallel model generally provides a better fit to the human data. PMID:24639662

Functional brain networks for learning predictive statistics.

PubMed

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

2017-08-18

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

The effect of interference on temporal order memory for random and fixed sequences in nondemented older adults.

PubMed

Tolentino, Jerlyn C; Pirogovsky, Eva; Luu, Trinh; Toner, Chelsea K; Gilbert, Paul E

2012-05-21

Two experiments tested the effect of temporal interference on order memory for fixed and random sequences in young adults and nondemented older adults. The results demonstrate that temporal order memory for fixed and random sequences is impaired in nondemented older adults, particularly when temporal interference is high. However, temporal order memory for fixed sequences is comparable between older adults and young adults when temporal interference is minimized. The results suggest that temporal order memory is less efficient and more susceptible to interference in older adults, possibly due to impaired temporal pattern separation.

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.

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

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.

Fast-Spiking Interneurons Supply Feedforward Control of Bursting, Calcium, and Plasticity for Efficient Learning.

PubMed

Owen, Scott F; Berke, Joshua D; Kreitzer, Anatol C

2018-02-08

Fast-spiking interneurons (FSIs) are a prominent class of forebrain GABAergic cells implicated in two seemingly independent network functions: gain control and network plasticity. Little is known, however, about how these roles interact. Here, we use a combination of cell-type-specific ablation, optogenetics, electrophysiology, imaging, and behavior to describe a unified mechanism by which striatal FSIs control burst firing, calcium influx, and synaptic plasticity in neighboring medium spiny projection neurons (MSNs). In vivo silencing of FSIs increased bursting, calcium transients, and AMPA/NMDA ratios in MSNs. In a motor sequence task, FSI silencing increased the frequency of calcium transients but reduced the specificity with which transients aligned to individual task events. Consistent with this, ablation of FSIs disrupted the acquisition of striatum-dependent egocentric learning strategies. Together, our data support a model in which feedforward inhibition from FSIs temporally restricts MSN bursting and calcium-dependent synaptic plasticity to facilitate striatum-dependent sequence learning. Copyright © 2018 Elsevier Inc. All rights reserved.

Lifelong learning of human actions with deep neural network self-organization.

PubMed

Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan

2017-12-01

Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences. The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns. We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields. Lifelong learning is achieved in terms of prediction-driven neural dynamics in which the growth and the adaptation of the recurrent networks are driven by their capability to reconstruct temporally ordered input sequences. Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions. Additional experiments show the ability of our model to adapt to non-stationary input avoiding catastrophic interference. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. 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.

Phonological learning in semantic dementia.

PubMed

Jefferies, Elizabeth; Bott, Samantha; Ehsan, Sheeba; Lambon Ralph, Matthew A

2011-04-01

Patients with semantic dementia (SD) have anterior temporal lobe (ATL) atrophy that gives rise to a highly selective deterioration of semantic knowledge. Despite pronounced anomia and poor comprehension of words and pictures, SD patients have well-formed, fluent speech and normal digit span. Given the intimate connection between phonological STM and word learning revealed by both neuropsychological and developmental studies, SD patients might be expected to show good acquisition of new phonological forms, even though their ability to map these onto meanings is impaired. In contradiction of these predictions, a limited amount of previous research has found poor learning of new phonological forms in SD. In a series of experiments, we examined whether SD patient, GE, could learn novel phonological sequences and, if so, under which circumstances. GE showed normal benefits of phonological knowledge in STM (i.e., normal phonotactic frequency and phonological similarity effects) but reduced support from semantic memory (i.e., poor immediate serial recall for semantically degraded words, characterised by frequent item errors). Next, we demonstrated normal learning of serial order information for repeated lists of single-digit number words using the Hebb paradigm: these items were well-understood allowing them to be repeated without frequent item errors. In contrast, patient GE showed little learning of nonsense syllable sequences using the same Hebb paradigm. Detailed analysis revealed that both GE and the controls showed a tendency to learn their own errors as opposed to the target items. Finally, we showed normal learning of phonological sequences for GE when he was prevented from repeating his errors. These findings confirm that the ATL atrophy in SD disrupts phonological processing for semantically degraded words but leaves the phonological architecture intact. Consequently, when item errors are minimised, phonological STM can support the acquisition of new phoneme sequences in patients with SD. Copyright © 2011 Elsevier Ltd. All rights reserved.

Prospective Coding by Spiking Neurons

PubMed Central

Brea, Johanni; Gaál, Alexisz Tamás; Senn, Walter

2016-01-01

Animals learn to make predictions, such as associating the sound of a bell with upcoming feeding or predicting a movement that a motor command is eliciting. How predictions are realized on the neuronal level and what plasticity rule underlies their learning is not well understood. Here we propose a biologically plausible synaptic plasticity rule to learn predictions on a single neuron level on a timescale of seconds. The learning rule allows a spiking two-compartment neuron to match its current firing rate to its own expected future discounted firing rate. For instance, if an originally neutral event is repeatedly followed by an event that elevates the firing rate of a neuron, the originally neutral event will eventually also elevate the neuron’s firing rate. The plasticity rule is a form of spike timing dependent plasticity in which a presynaptic spike followed by a postsynaptic spike leads to potentiation. Even if the plasticity window has a width of 20 milliseconds, associations on the time scale of seconds can be learned. We illustrate prospective coding with three examples: learning to predict a time varying input, learning to predict the next stimulus in a delayed paired-associate task and learning with a recurrent network to reproduce a temporally compressed version of a sequence. We discuss the potential role of the learning mechanism in classical trace conditioning. In the special case that the signal to be predicted encodes reward, the neuron learns to predict the discounted future reward and learning is closely related to the temporal difference learning algorithm TD(λ). PMID:27341100

The Effect of Interference on Temporal Order Memory for Random and Fixed Sequences in Nondemented Older Adults

ERIC Educational Resources Information Center

Tolentino, Jerlyn C.; Pirogovsky, Eva; Luu, Trinh; Toner, Chelsea K.; Gilbert, Paul E.

2012-01-01

Two experiments tested the effect of temporal interference on order memory for fixed and random sequences in young adults and nondemented older adults. The results demonstrate that temporal order memory for fixed and random sequences is impaired in nondemented older adults, particularly when temporal interference is high. However, temporal order…

Robust temporal alignment of multimodal cardiac sequences

NASA Astrophysics Data System (ADS)

Perissinotto, Andrea; Queirós, Sandro; Morais, Pedro; Baptista, Maria J.; Monaghan, Mark; Rodrigues, Nuno F.; D'hooge, Jan; Vilaça, João. L.; Barbosa, Daniel

2015-03-01

Given the dynamic nature of cardiac function, correct temporal alignment of pre-operative models and intraoperative images is crucial for augmented reality in cardiac image-guided interventions. As such, the current study focuses on the development of an image-based strategy for temporal alignment of multimodal cardiac imaging sequences, such as cine Magnetic Resonance Imaging (MRI) or 3D Ultrasound (US). First, we derive a robust, modality-independent signal from the image sequences, estimated by computing the normalized cross-correlation between each frame in the temporal sequence and the end-diastolic frame. This signal is a resembler for the left-ventricle (LV) volume curve over time, whose variation indicates different temporal landmarks of the cardiac cycle. We then perform the temporal alignment of these surrogate signals derived from MRI and US sequences of the same patient through Dynamic Time Warping (DTW), allowing to synchronize both sequences. The proposed framework was evaluated in 98 patients, which have undergone both 3D+t MRI and US scans. The end-systolic frame could be accurately estimated as the minimum of the image-derived surrogate signal, presenting a relative error of 1.6 +/- 1.9% and 4.0 +/- 4.2% for the MRI and US sequences, respectively, thus supporting its association with key temporal instants of the cardiac cycle. The use of DTW reduces the desynchronization of the cardiac events in MRI and US sequences, allowing to temporally align multimodal cardiac imaging sequences. Overall, a generic, fast and accurate method for temporal synchronization of MRI and US sequences of the same patient was introduced. This approach could be straightforwardly used for the correct temporal alignment of pre-operative MRI information and intra-operative US images.

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.

a Walk Through Earth's Time

NASA Astrophysics Data System (ADS)

Turrin, B. D.; Turrin, M.

2012-12-01

After "What is this rock?" the most common questions that is asked of Geologists is "How old is this rock/fossil?" For geologists considering ages back to millions of years is routine. Sorting and cataloguing events into temporal sequences is a natural tendency for all humans. In fact, it is an everyday activity for humans, i.e., keeping track of birthdays, anniversaries, appointments, meetings, AGU abstract deadlines etc… However, the time frames that are most familiar to the non scientist (seconds, minutes, hours, days, years) generally extend to only a few decades or at most centuries. Yet the vast length of time covered by Earth's history, 4.56 billion years, greatly exceeds these timeframes and thus is commonly referred to as "Deep Time". This is a challenging concept for most students to comprehend as it involves temporal and abstract thinking, yet it is key to their successful understanding of numerous geologic principles. We have developed an outdoor learning activity for general Introductory Earth Science courses that incorporates several scientific and geologic concepts such as: linear distance or stratigraphic thickness representing time, learning about major events in Earth's history and locating them in a scaled temporal framework, field mapping, abstract thinking, scaling and dimensional analysis, and the principles of radio isotopic dating. The only supplies needed are readily available in local hardware stores i.e. a 300 ft. surveyor's tape marked in feet, and tenths and hundredths of a foot, and the student's own introductory geology textbook. The exercise employs a variety of pedagogical learning modalities, including traditional lecture-based, the use of Art/Drawing, use of Visualization, Collaborative learning, and Kinesthetic and Experiential learning. Initially the students are exposed to the concept of "Deep Time" in a short conventional introductory lecture; this is followed by a 'field day'. Prior to the field exercise, students work with their textbook selecting events is Earth History that they find interesting. Using the textbook and online resources they then draw figures that represent these events. The drawing exercise reinforces the learning by having students visualize (imprinting an image) of these geologic events. Once the students have produced their drawings, the outdoor field exercise follows. Working collaboratively, the students measure and lay out a scaled linear model representing 4.56 billion years of geologic time. They then organize and place their drawings in the proper sequence on the temporal model that they have created. Once all the drawings are in place they are able to visualize the expanse of time in Earth's history. Through comparing results from a pre-test to those from a post-test we can show the gains in student understanding of Deep Time, a concept that is central to many of our geologic understandings.

Association of Hippocampal Substructure Resting-State Functional Connectivity with Memory Performance in Older Adults.

PubMed

Smagula, Stephen F; Karim, Helmet T; Rangarajan, Anusha; Santos, Fernando Pasquini; Wood, Sossena C; Santini, Tales; Jakicic, John M; Reynolds, Charles F; Cameron, Judy L; Vallejo, Abbe N; Butters, Meryl A; Rosano, Caterina; Ibrahim, Tamer S; Erickson, Kirk I; Aizenstein, Howard J

2018-06-01

Hippocampal hyperactivation marks preclinical dementia pathophysiology, potentially due to differences in the connectivity of specific medial temporal lobe structures. Our aims were to characterize the resting-state functional connectivity of medial temporal lobe sub-structures in older adults, and evaluate whether specific substructural (rather than global) functional connectivity relates to memory function. In 15 adults (mean age: 69 years), we evaluated the resting state functional connectivity of medial temporal lobe substructures: dentate/Cornu Ammonis (CA) 4, CA1, CA2/3, subiculum, the molecular layer, entorhinal cortex, and parahippocampus. We used 7-Tesla susceptibility weighted imaging and magnetization-prepared rapid gradient echo sequences to segment substructures of the hippocampus, which were used as structural seeds for examining functional connectivity in a resting BOLD sequence. We then assessed correlations between functional connectivity with memory performance (short and long delay free recall on the California Verbal Learning Test [CVLT]). All the seed regions had significant connectivity within the temporal lobe (including the fusiform, temporal, and lingual gyri). The left CA1 was the only seed with significant functional connectivity to the amygdala. The left entorhinal cortex was the only seed to have significant functional connectivity with frontal cortex (anterior cingulate and superior frontal gyrus). Only higher left dentate-left lingual connectivity was associated with poorer CVLT performance (Spearman r = -0.81, p = 0.0003, Benjamini-Hochberg false discovery rate: 0.01) after multiple comparison correction. Rather than global hyper-connectivity of the medial temporal lobe, left dentate-lingual connectivity may provide a specific assay of medial temporal lobe hyper-connectivity relevant to memory in aging. Copyright © 2018 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

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.

Children's Representation and Imitation of Events: How Goal Organization Influences 3-Year-Old Children's Memory for Action Sequences.

PubMed

Loucks, Jeff; Mutschler, Christina; Meltzoff, Andrew N

2017-09-01

Children's imitation of adults plays a prominent role in human cognitive development. However, few studies have investigated how children represent the complex structure of observed actions which underlies their imitation. We integrate theories of action segmentation, memory, and imitation to investigate whether children's event representation is organized according to veridical serial order or a higher level goal structure. Children were randomly assigned to learn novel event sequences either through interactive hands-on experience (Study 1) or via storybook (Study 2). Results demonstrate that children's representation of observed actions is organized according to higher level goals, even at the cost of representing the veridical temporal ordering of the sequence. We argue that prioritizing goal structure enhances event memory, and that this mental organization is a key mechanism of social-cognitive development in real-world, dynamic environments. It supports cultural learning and imitation in ecologically valid settings when social agents are multitasking and not demonstrating one isolated goal at a time. Copyright © 2016 Cognitive Science Society, Inc.

Visual paired-associate learning: in search of material-specific effects in adult patients who have undergone temporal lobectomy.

PubMed

Smith, Mary Lou; Bigel, Marla; Miller, Laurie A

2011-02-01

The mesial temporal lobes are important for learning arbitrary associations. It has previously been demonstrated that left mesial temporal structures are involved in learning word pairs, but it is not yet known whether comparable lesions in the right temporal lobe impair visually mediated associative learning. Patients who had undergone left (n=16) or right (n=18) temporal lobectomy for relief of intractable epilepsy and healthy controls (n=13) were administered two paired-associate learning tasks assessing their learning and memory of pairs of abstract designs or pairs of symbols in unique locations. Both patient groups had deficits in learning the designs, but only the right temporal group was impaired in recognition. For the symbol location task, differences were not found in learning, but again a recognition deficit was found for the right temporal group. The findings implicate the mesial temporal structures in relational learning. They support a material-specific effect for recognition but not for learning and recall of arbitrary visual and visual-spatial associative information. Copyright © 2010 Elsevier Inc. All rights reserved.

Spatio-temporal alignment of pedobarographic image sequences.

PubMed

Oliveira, Francisco P M; Sousa, Andreia; Santos, Rubim; Tavares, João Manuel R S

2011-07-01

This article presents a methodology to align plantar pressure image sequences simultaneously in time and space. The spatial position and orientation of a foot in a sequence are changed to match the foot represented in a second sequence. Simultaneously with the spatial alignment, the temporal scale of the first sequence is transformed with the aim of synchronizing the two input footsteps. Consequently, the spatial correspondence of the foot regions along the sequences as well as the temporal synchronizing is automatically attained, making the study easier and more straightforward. In terms of spatial alignment, the methodology can use one of four possible geometric transformation models: rigid, similarity, affine, or projective. In the temporal alignment, a polynomial transformation up to the 4th degree can be adopted in order to model linear and curved time behaviors. Suitable geometric and temporal transformations are found by minimizing the mean squared error (MSE) between the input sequences. The methodology was tested on a set of real image sequences acquired from a common pedobarographic device. When used in experimental cases generated by applying geometric and temporal control transformations, the methodology revealed high accuracy. In addition, the intra-subject alignment tests from real plantar pressure image sequences showed that the curved temporal models produced better MSE results (P < 0.001) than the linear temporal model. This article represents an important step forward in the alignment of pedobarographic image data, since previous methods can only be applied on static images.

Joint level-set and spatio-temporal motion detection for cell segmentation.

PubMed

Boukari, Fatima; Makrogiannis, Sokratis

2016-08-10

Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan-Vese techniques, and 4 % compared to the nonlinear spatio-temporal diffusion method. Despite the wide variation in cell shape, density, mitotic events, and image quality among the datasets, our proposed method produced promising segmentation results. These results indicate the efficiency and robustness of this method especially for mitotic events and low SNR imaging, enabling the application of subsequent quantification tasks.

A time series based sequence prediction algorithm to detect activities of daily living in smart home.

PubMed

Marufuzzaman, M; Reaz, M B I; Ali, M A M; Rahman, L F

2015-01-01

The goal of smart homes is to create an intelligent environment adapting the inhabitants need and assisting the person who needs special care and safety in their daily life. This can be reached by collecting the ADL (activities of daily living) data and further analysis within existing computing elements. In this research, a very recent algorithm named sequence prediction via enhanced episode discovery (SPEED) is modified and in order to improve accuracy time component is included. The modified SPEED or M-SPEED is a sequence prediction algorithm, which modified the previous SPEED algorithm by using time duration of appliance's ON-OFF states to decide the next state. M-SPEED discovered periodic episodes of inhabitant behavior, trained it with learned episodes, and made decisions based on the obtained knowledge. The results showed that M-SPEED achieves 96.8% prediction accuracy, which is better than other time prediction algorithms like PUBS, ALZ with temporal rules and the previous SPEED. Since human behavior shows natural temporal patterns, duration times can be used to predict future events more accurately. This inhabitant activity prediction system will certainly improve the smart homes by ensuring safety and better care for elderly and handicapped people.

Music and language perception: expectations, structural integration, and cognitive sequencing.

PubMed

Tillmann, Barbara

2012-10-01

Music can be described as sequences of events that are structured in pitch and time. Studying music processing provides insight into how complex event sequences are learned, perceived, and represented by the brain. Given the temporal nature of sound, expectations, structural integration, and cognitive sequencing are central in music perception (i.e., which sounds are most likely to come next and at what moment should they occur?). This paper focuses on similarities in music and language cognition research, showing that music cognition research provides insight into the understanding of not only music processing but also language processing and the processing of other structured stimuli. The hypothesis of shared resources between music and language processing and of domain-general dynamic attention has motivated the development of research to test music as a means to stimulate sensory, cognitive, and motor processes. Copyright © 2012 Cognitive Science Society, Inc.

Learning temporal rules to forecast instability in continuously monitored patients

PubMed Central

Dubrawski, Artur; Wang, Donghan; Hravnak, Marilyn; Clermont, Gilles; Pinsky, Michael R

2017-01-01

Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appeal of rule extraction techniques stems from their ability to handle intricate problems yet produce models based on rules that can be comprehended by humans, and are therefore more transparent. Human comprehension is a factor that may improve adoption and use of data-driven decision support systems clinically via face validity. In this work, we explore whether we can reliably and informatively forecast cardiorespiratory instability (CRI) in step-down unit (SDU) patients utilizing data from continuous monitoring of physiologic vital sign (VS) measurements. We use a temporal association rule extraction technique in conjunction with a rule fusion protocol to learn how to forecast CRI in continuously monitored patients. We detail our approach and present and discuss encouraging empirical results obtained using continuous multivariate VS data from the bedside monitors of 297 SDU patients spanning 29 346 hours (3.35 patient-years) of observation. We present example rules that have been learned from data to illustrate potential benefits of comprehensibility of the extracted models, and we analyze the empirical utility of each VS as a potential leading indicator of an impending CRI event. PMID:27274020

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

PubMed Central

Folia, Vasiliki; Petersson, Karl Magnus

2014-01-01

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

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

PubMed

Folia, Vasiliki; Petersson, Karl Magnus

2014-01-01

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

Beta phase synchronization in the frontal-temporal-cerebellar network during auditory-to-motor rhythm learning.

PubMed

Edagawa, Kouki; Kawasaki, Masahiro

2017-02-22

Rhythm is an essential element of dancing and music. To investigate the neural mechanisms underlying how rhythm is learned, we recorded electroencephalographic (EEG) data during a rhythm-reproducing task that asked participants to memorize an auditory stimulus and reproduce it via tapping. Based on the behavioral results, we divided the participants into Learning and No-learning groups. EEG analysis showed that error-related negativity (ERN) in the Learning group was larger than in the No-learning group. Time-frequency analysis of the EEG data showed that the beta power in right and left temporal area at the late learning stage was smaller than at the early learning stage in the Learning group. Additionally, the beta power in the temporal and cerebellar areas in the Learning group when learning to reproduce the rhythm were larger than in the No Learning group. Moreover, phase synchronization between frontal and temporal regions and between temporal and cerebellar regions at late stages of learning were larger than at early stages. These results indicate that the frontal-temporal-cerebellar beta neural circuits might be related to auditory-motor rhythm learning.

Enhanced spatio-temporal alignment of plantar pressure image sequences using B-splines.

PubMed

Oliveira, Francisco P M; Tavares, João Manuel R S

2013-03-01

This article presents an enhanced methodology to align plantar pressure image sequences simultaneously in time and space. The temporal alignment of the sequences is accomplished using B-splines in the time modeling, and the spatial alignment can be attained using several geometric transformation models. The methodology was tested on a dataset of 156 real plantar pressure image sequences (3 sequences for each foot of the 26 subjects) that was acquired using a common commercial plate during barefoot walking. In the alignment of image sequences that were synthetically deformed both in time and space, an outstanding accuracy was achieved with the cubic B-splines. This accuracy was significantly better (p < 0.001) than the one obtained using the best solution proposed in our previous work. When applied to align real image sequences with unknown transformation involved, the alignment based on cubic B-splines also achieved superior results than our previous methodology (p < 0.001). The consequences of the temporal alignment on the dynamic center of pressure (COP) displacement was also assessed by computing the intraclass correlation coefficients (ICC) before and after the temporal alignment of the three image sequence trials of each foot of the associated subject at six time instants. The results showed that, generally, the ICCs related to the medio-lateral COP displacement were greater when the sequences were temporally aligned than the ICCs of the original sequences. Based on the experimental findings, one can conclude that the cubic B-splines are a remarkable solution for the temporal alignment of plantar pressure image sequences. These findings also show that the temporal alignment can increase the consistency of the COP displacement on related acquired plantar pressure image sequences.

Learning predictive models that use pattern discovery--a bootstrap evaluative approach applied in organ functioning sequences.

PubMed

Toma, Tudor; Bosman, Robert-Jan; Siebes, Arno; Peek, Niels; Abu-Hanna, Ameen

2010-08-01

An important problem in the Intensive Care is how to predict on a given day of stay the eventual hospital mortality for a specific patient. A recent approach to solve this problem suggested the use of frequent temporal sequences (FTSs) as predictors. Methods following this approach were evaluated in the past by inducing a model from a training set and validating the prognostic performance on an independent test set. Although this evaluative approach addresses the validity of the specific models induced in an experiment, it falls short of evaluating the inductive method itself. To achieve this, one must account for the inherent sources of variation in the experimental design. The main aim of this work is to demonstrate a procedure based on bootstrapping, specifically the .632 bootstrap procedure, for evaluating inductive methods that discover patterns, such as FTSs. A second aim is to apply this approach to find out whether a recently suggested inductive method that discovers FTSs of organ functioning status is superior over a traditional method that does not use temporal sequences when compared on each successive day of stay at the Intensive Care Unit. The use of bootstrapping with logistic regression using pre-specified covariates is known in the statistical literature. Using inductive methods of prognostic models based on temporal sequence discovery within the bootstrap procedure is however novel at least in predictive models in the Intensive Care. Our results of applying the bootstrap-based evaluative procedure demonstrate the superiority of the FTS-based inductive method over the traditional method in terms of discrimination as well as accuracy. In addition we illustrate the insights gained by the analyst into the discovered FTSs from the bootstrap samples. Copyright 2010 Elsevier Inc. All rights reserved.

Event Boundaries Trigger Rapid Memory Reinstatement of the Prior Events to Promote Their Representation in Long-Term Memory.

PubMed

Sols, Ignasi; DuBrow, Sarah; Davachi, Lila; Fuentemilla, Lluís

2017-11-20

Although everyday experiences unfold continuously over time, shifts in context, or event boundaries, can influence how those events come to be represented in memory [1-4]. Specifically, mnemonic binding across sequential representations is more challenging at context shifts, such that successful temporal associations are more likely to be formed within than across contexts [1, 2, 5-9]. However, in order to preserve a subjective sense of continuity, it is important that the memory system bridge temporally adjacent events, even if they occur in seemingly distinct contexts. Here, we used pattern similarity analysis to scalp electroencephalographic (EEG) recordings during a sequential learning task [2, 3] in humans and showed that the detection of event boundaries triggered a rapid memory reinstatement of the just-encoded sequence episode. Memory reactivation was detected rapidly (∼200-800 ms from the onset of the event boundary) and was specific to context shifts that were preceded by an event sequence with episodic content. Memory reinstatement was not observed during the sequential encoding of events within an episode, indicating that memory reactivation was induced specifically upon context shifts. Finally, the degree of neural similarity between neural responses elicited during sequence encoding and at event boundaries correlated positively with participants' ability to later link across sequences of events, suggesting a critical role in binding temporally adjacent events in long-term memory. Current results shed light onto the neural mechanisms that promote episodic encoding not only for information within the event, but also, importantly, in the ability to link across events to create a memory representation of continuous experience. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unifying Temporal and Structural Credit Assignment Problems

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2004-01-01

Single-agent reinforcement learners in time-extended domains and multi-agent systems share a common dilemma known as the credit assignment problem. Multi-agent systems have the structural credit assignment problem of determining the contributions of a particular agent to a common task. Instead, time-extended single-agent systems have the temporal credit assignment problem of determining the contribution of a particular action to the quality of the full sequence of actions. Traditionally these two problems are considered different and are handled in separate ways. In this article we show how these two forms of the credit assignment problem are equivalent. In this unified frame-work, a single-agent Markov decision process can be broken down into a single-time-step multi-agent process. Furthermore we show that Monte-Carlo estimation or Q-learning (depending on whether the values of resulting actions in the episode are known at the time of learning) are equivalent to different agent utility functions in a multi-agent system. This equivalence shows how an often neglected issue in multi-agent systems is equivalent to a well-known deficiency in multi-time-step learning and lays the basis for solving time-extended multi-agent problems, where both credit assignment problems are present.

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

Tracking down the path of memory: eye scanpaths facilitate retrieval of visuospatial information.

PubMed

Bochynska, Agata; Laeng, Bruno

2015-09-01

Recent research points to a crucial role of eye fixations on the same spatial locations where an item appeared when learned, for the successful retrieval of stored information (e.g., Laeng et al. in Cognition 131:263-283, 2014. doi: 10.1016/j.cognition.2014.01.003 ). However, evidence about whether the specific temporal sequence (i.e., scanpath) of these eye fixations is also relevant for the accuracy of memory remains unclear. In the current study, eye fixations were recorded while looking at a checkerboard-like pattern. In a recognition session (48 h later), animations were shown where each square that formed the pattern was presented one by one, either according to the same, idiosyncratic, temporal sequence in which they were originally viewed by each participant or in a shuffled sequence although the squares were, in both conditions, always in their correct positions. Afterward, participants judged whether they had seen the same pattern before or not. Showing the elements serially according to the original scanpath's sequence yielded a significantly better recognition performance than the shuffled condition. In a forced fixation condition, where the gaze was maintained on the center of the screen, the advantage of memory accuracy for same versus shuffled scanpaths disappeared. Concluding, gaze scanpaths (i.e., the order of fixations and not simply their positions) are functional to visual memory and physical reenacting of the original, embodied, perception can facilitate retrieval.

Deep RNNs for video denoising

NASA Astrophysics Data System (ADS)

Chen, Xinyuan; Song, Li; Yang, Xiaokang

2016-09-01

Video denoising can be described as the problem of mapping from a specific length of noisy frames to clean one. We propose a deep architecture based on Recurrent Neural Network (RNN) for video denoising. The model learns a patch-based end-to-end mapping between the clean and noisy video sequences. It takes the corrupted video sequences as the input and outputs the clean one. Our deep network, which we refer to as deep Recurrent Neural Networks (deep RNNs or DRNNs), stacks RNN layers where each layer receives the hidden state of the previous layer as input. Experiment shows (i) the recurrent architecture through temporal domain extracts motion information and does favor to video denoising, and (ii) deep architecture have large enough capacity for expressing mapping relation between corrupted videos as input and clean videos as output, furthermore, (iii) the model has generality to learned different mappings from videos corrupted by different types of noise (e.g., Poisson-Gaussian noise). By training on large video databases, we are able to compete with some existing video denoising methods.

Dynamic Textures Modeling via Joint Video Dictionary Learning.

PubMed

Wei, Xian; Li, Yuanxiang; Shen, Hao; Chen, Fang; Kleinsteuber, Martin; Wang, Zhongfeng

2017-04-06

Video representation is an important and challenging task in the computer vision community. In this paper, we consider the problem of modeling and classifying video sequences of dynamic scenes which could be modeled in a dynamic textures (DT) framework. At first, we assume that image frames of a moving scene can be modeled as a Markov random process. We propose a sparse coding framework, named joint video dictionary learning (JVDL), to model a video adaptively. By treating the sparse coefficients of image frames over a learned dictionary as the underlying "states", we learn an efficient and robust linear transition matrix between two adjacent frames of sparse events in time series. Hence, a dynamic scene sequence is represented by an appropriate transition matrix associated with a dictionary. In order to ensure the stability of JVDL, we impose several constraints on such transition matrix and dictionary. The developed framework is able to capture the dynamics of a moving scene by exploring both sparse properties and the temporal correlations of consecutive video frames. Moreover, such learned JVDL parameters can be used for various DT applications, such as DT synthesis and recognition. Experimental results demonstrate the strong competitiveness of the proposed JVDL approach in comparison with state-of-the-art video representation methods. Especially, it performs significantly better in dealing with DT synthesis and recognition on heavily corrupted data.

Temporal Restricted Visual Tracking Via Reverse-Low-Rank Sparse Learning.

PubMed

Yang, Yehui; Hu, Wenrui; Xie, Yuan; Zhang, Wensheng; Zhang, Tianzhu

2017-02-01

An effective representation model, which aims to mine the most meaningful information in the data, plays an important role in visual tracking. Some recent particle-filter-based trackers achieve promising results by introducing the low-rank assumption into the representation model. However, their assumed low-rank structure of candidates limits the robustness when facing severe challenges such as abrupt motion. To avoid the above limitation, we propose a temporal restricted reverse-low-rank learning algorithm for visual tracking with the following advantages: 1) the reverse-low-rank model jointly represents target and background templates via candidates, which exploits the low-rank structure among consecutive target observations and enforces the temporal consistency of target in a global level; 2) the appearance consistency may be broken when target suffers from sudden changes. To overcome this issue, we propose a local constraint via l 1,2 mixed-norm, which can not only ensures the local consistency of target appearance, but also tolerates the sudden changes between two adjacent frames; and 3) to alleviate the inference of unreasonable representation values due to outlier candidates, an adaptive weighted scheme is designed to improve the robustness of the tracker. By evaluating on 26 challenge video sequences, the experiments show the effectiveness and favorable performance of the proposed algorithm against 12 state-of-the-art visual trackers.

Transformation of temporal sequences in the zebra finch auditory system

PubMed Central

Lim, Yoonseob; Lagoy, Ryan; Shinn-Cunningham, Barbara G; Gardner, Timothy J

2016-01-01

This study examines how temporally patterned stimuli are transformed as they propagate from primary to secondary zones in the thalamorecipient auditory pallium in zebra finches. Using a new class of synthetic click stimuli, we find a robust mapping from temporal sequences in the primary zone to distinct population vectors in secondary auditory areas. We tested whether songbirds could discriminate synthetic click sequences in an operant setup and found that a robust behavioral discrimination is present for click sequences composed of intervals ranging from 11 ms to 40 ms, but breaks down for stimuli composed of longer inter-click intervals. This work suggests that the analog of the songbird auditory cortex transforms temporal patterns to sequence-selective population responses or ‘spatial codes', and that these distinct population responses contribute to behavioral discrimination of temporally complex sounds. DOI: http://dx.doi.org/10.7554/eLife.18205.001 PMID:27897971

Musical Scales in Tone Sequences Improve Temporal Accuracy.

PubMed

Li, Min S; Di Luca, Massimiliano

2018-01-01

Predicting the time of stimulus onset is a key component in perception. Previous investigations of perceived timing have focused on the effect of stimulus properties such as rhythm and temporal irregularity, but the influence of non-temporal properties and their role in predicting stimulus timing has not been exhaustively considered. The present study aims to understand how a non-temporal pattern in a sequence of regularly timed stimuli could improve or bias the detection of temporal deviations. We presented interspersed sequences of 3, 4, 5, and 6 auditory tones where only the timing of the last stimulus could slightly deviate from isochrony. Participants reported whether the last tone was 'earlier' or 'later' relative to the expected regular timing. In two conditions, the tones composing the sequence were either organized into musical scales or they were random tones. In one experiment, all sequences ended with the same tone; in the other experiment, each sequence ended with a different tone. Results indicate higher discriminability of anisochrony with musical scales and with longer sequences, irrespective of the knowledge of the final tone. Such an outcome suggests that the predictability of non-temporal properties, as enabled by the musical scale pattern, can be a factor in determining the sensitivity of time judgments.

Temporal Cyber Attack Detection.

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

Ingram, Joey Burton; Draelos, Timothy J.; Galiardi, Meghan

Rigorous characterization of the performance and generalization ability of cyber defense systems is extremely difficult, making it hard to gauge uncertainty, and thus, confidence. This difficulty largely stems from a lack of labeled attack data that fully explores the potential adversarial space. Currently, performance of cyber defense systems is typically evaluated in a qualitative manner by manually inspecting the results of the system on live data and adjusting as needed. Additionally, machine learning has shown promise in deriving models that automatically learn indicators of compromise that are more robust than analyst-derived detectors. However, to generate these models, most algorithms requiremore » large amounts of labeled data (i.e., examples of attacks). Algorithms that do not require annotated data to derive models are similarly at a disadvantage, because labeled data is still necessary when evaluating performance. In this work, we explore the use of temporal generative models to learn cyber attack graph representations and automatically generate data for experimentation and evaluation. Training and evaluating cyber systems and machine learning models requires significant, annotated data, which is typically collected and labeled by hand for one-off experiments. Automatically generating such data helps derive/evaluate detection models and ensures reproducibility of results. Experimentally, we demonstrate the efficacy of generative sequence analysis techniques on learning the structure of attack graphs, based on a realistic example. These derived models can then be used to generate more data. Additionally, we provide a roadmap for future research efforts in this area.« less

Activation and connectivity patterns of the presupplementary and dorsal premotor areas during free improvisation of melodies and rhythms.

PubMed

de Manzano, Örjan; Ullén, Fredrik

2012-10-15

Free, i.e. non-externally cued generation of movement sequences is fundamental to human behavior. We have earlier hypothesized that the dorsal premotor cortex (PMD), which has been consistently implicated in cognitive aspects of planning and selection of spatial motor sequences may be particularly important for the free generation of spatial movement sequences, whereas the pre-supplementary motor area (pre-SMA), which shows increased activation during perception, learning and reproduction of temporal sequences, may contribute more to the generation of temporal structures. Here we test this hypothesis using fMRI and musical improvisation in professional pianists as a model behavior. We employed a 2 × 2 factorial design with the factors Melody (Specified/Improvised) and Rhythm (Specified/Improvised). The main effect analyses partly confirmed our hypothesis: there was a main effect of Melody in the PMD; the pre-SMA was present in the main effect of Rhythm, as predicted, as well as in the main effect of Melody. A psychophysiological interaction analysis of functional connectivity demonstrated that the correlation in activity between the pre-SMA and cerebellum was higher during rhythmic improvisation than during the other conditions. In summary, there were only subtle differences in activity level between the pre-SMA and PMD during improvisation, regardless of condition. Consequently, the free generation of rhythmic and melodic structures, appears to be largely integrated processes but the functional connectivity between premotor areas and other regions may change during free generation in response to sequence-specific spatiotemporal demands. Copyright © 2012 Elsevier Inc. All rights reserved.

Attentional awakening: gradual modulation of temporal attention in rapid serial visual presentation.

PubMed

Ariga, Atsunori; Yokosawa, Kazuhiko

2008-03-01

Orienting attention to a point in time facilitates processing of an item within rapidly changing surroundings. We used a one-target RSVP task to look for differences in accuracy in reporting a target related to when the target temporally appeared in the sequence. The results show that observers correctly report a target early in the sequence less frequently than later in the sequence. Previous RSVP studies predicted equivalently accurate performances for one target wherever it appeared in the sequence. We named this new phenomenon attentional awakening, which reflects a gradual modulation of temporal attention in a rapid sequence.

BNU-LSVED: a multimodal spontaneous expression database in educational environment

NASA Astrophysics Data System (ADS)

Sun, Bo; Wei, Qinglan; He, Jun; Yu, Lejun; Zhu, Xiaoming

2016-09-01

In the field of pedagogy or educational psychology, emotions are treated as very important factors, which are closely associated with cognitive processes. Hence, it is meaningful for teachers to analyze students' emotions in classrooms, thus adjusting their teaching activities and improving students ' individual development. To provide a benchmark for different expression recognition algorithms, a large collection of training and test data in classroom environment has become an acute problem that needs to be resolved. In this paper, we present a multimodal spontaneous database in real learning environment. To collect the data, students watched seven kinds of teaching videos and were simultaneously filmed by a camera. Trained coders made one of the five learning expression labels for each image sequence extracted from the captured videos. This subset consists of 554 multimodal spontaneous expression image sequences (22,160 frames) recorded in real classrooms. There are four main advantages in this database. 1) Due to recorded in the real classroom environment, viewer's distance from the camera and the lighting of the database varies considerably between image sequences. 2) All the data presented are natural spontaneous responses to teaching videos. 3) The multimodal database also contains nonverbal behavior including eye movement, head posture and gestures to infer a student ' s affective state during the courses. 4) In the video sequences, there are different kinds of temporal activation patterns. In addition, we have demonstrated the labels for the image sequences are in high reliability through Cronbach's alpha method.

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

A theoretical framework for the incorporation of history in science education

NASA Astrophysics Data System (ADS)

Klassen, James Stephen

This thesis formulates a theoretical framework for the incorporation of history of science in science teaching, which, it is argued, is essential to laying a stable foundation for instructional design and future empirical studies. It is assumed that the historical approach to teaching science no longer needs defending and that contextual methods are a pedagogically sound approach to learning. Various cognitive and learning theories suggest that there are five distinct contexts that are important in engaging learners: the theoretical, practical, social, historical, and affective. On the basis of these five contexts, a model for teaching and learning is constructed, in which the story assumes a major role in engaging the learner affectively. This model is named the Story-Driven Contextual Approach (SDCA). The SDCA is introduced to students by means of a narrative, encouraging students to become actively engaged with the five contexts. In the SDCA, students are seen as novice researchers and the teacher as a research director. The place and nature of the historical science story in science education is a relatively undeveloped area in the literature. This thesis argues that the development of the events in a story proceed in the same fashion as the steps in learning a concept. A structural model of a story consisting of a three-stage temporal sequence, which includes a causative element, is presented and developed. It is argued that the conceptual change process, from a temporal perspective, can also be viewed as a three-stage sequence similar to the story. The story can, in this light, be thought of as the re-enactment of a particular type of learning process. This knowledge about the nature of stories can serve as a guiding principle in the designing and writing of effective stories based on the history of science, which are to be incorporated with the SDCA. The SDCA was tested in a university physics class using a constructed story which portrays the heroic personal and scientific efforts of the nineteenth century physicist Lord Kelvin in laying the first successful trans-Atlantic cable. Students designed and undertook various practical and theoretical exercises in the SDCA and observations on its implementation are reported.

Recovering time-varying networks of dependencies in social and biological studies.

PubMed

Ahmed, Amr; Xing, Eric P

2009-07-21

A plausible representation of the relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network that is topologically rewiring and semantically evolving over time. Although there is a rich literature in modeling static or temporally invariant networks, little has been done toward recovering the network structure when the networks are not observable in a dynamic context. In this article, we present a machine learning method called TESLA, which builds on a temporally smoothed l(1)-regularized logistic regression formalism that can be cast as a standard convex-optimization problem and solved efficiently by using generic solvers scalable to large networks. We report promising results on recovering simulated time-varying networks and on reverse engineering the latent sequence of temporally rewiring political and academic social networks from longitudinal data, and the evolving gene networks over >4,000 genes during the life cycle of Drosophila melanogaster from a microarray time course at a resolution limited only by sample frequency.

Team Learning: New Insights Through a Temporal Lens.

PubMed

Lehmann-Willenbrock, Nale

2017-04-01

Team learning is a complex social phenomenon that develops and changes over time. Hence, to promote understanding of the fine-grained dynamics of team learning, research should account for the temporal patterns of team learning behavior. Taking important steps in this direction, this special issue offers novel insights into the dynamics of team learning by advocating a temporal perspective. Based on a symposium presented at the 2016 Interdisciplinary Network for Group Research (INGRoup) Conference in Helsinki, the four empirical articles in this special issue showcase four different and innovative approaches to implementing a temporal perspective in team learning research. Specifically, the contributions highlight team learning dynamics in student teams, self-managing teams, teacher teams, and command and control teams. The articles cover a broad range of methods and designs, including both qualitative and quantitative methodologies, and longitudinal as well as micro-temporal approaches. The contributors represent four countries and five different disciplines in group research.

Temporal maps and informativeness in associative learning.

PubMed

Balsam, Peter D; Gallistel, C Randy

2009-02-01

Neurobiological research on learning assumes that temporal contiguity is essential for association formation, but what constitutes temporal contiguity has never been specified. We review evidence that learning depends, instead, on learning a temporal map. Temporal relations between events are encoded even from single experiences. The speed with which an anticipatory response emerges is proportional to the informativeness of the encoded relation between a predictive stimulus or event and the event it predicts. This principle yields a quantitative account of the heretofore undefined, but theoretically crucial, concept of temporal pairing, an account in quantitative accord with surprising experimental findings. The same principle explains the basic results in the cue competition literature, which motivated the Rescorla-Wagner model and most other contemporary models of associative learning. The essential feature of a memory mechanism in this account is its ability to encode quantitative information.

Temporal maps and informativeness in associative learning

PubMed Central

Balsam, Peter D; Gallistel, C. Randy

2009-01-01

Neurobiological research on learning assumes that temporal contiguity is essential for association formation, but what constitutes temporal contiguity has never been specified. We review evidence that learning depends, instead, on learning a temporal map. Temporal relations between events are encoded even from single experiences. The speed with which an anticipatory response emerges is proportional to the informativeness of the encoded relation between a predictive stimulus or event and the event it predicts. This principle yields a quantitative account of the heretofore undefined, but theoretically crucial, concept of temporal pairing, an account in quantitative accord with surprising experimental findings. The same principle explains the basic results in the cue competition literature, which motivated the Rescorla–Wagner model and most other contemporary models of associative learning. The essential feature of a memory mechanism in this account is its ability to encode quantitative information. PMID:19136158

Effects of inactivating individual cerebellar nuclei on the performance and retention of an operantly conditioned forelimb movement.

PubMed

Milak, M S; Shimansky, Y; Bracha, V; Bloedel, J R

1997-08-01

These experiments were designed to examine the effects of inactivating separately each of the major cerebellar nuclear regions in cats on the execution and retention of a previously learned, operantly conditioned volitional forelimb movement. The experiments test the postulates that the cerebellar nuclei, and particularly the interposed nuclei, contribute substantially to the spatial and temporal features of the interjoint coordination required to execute the task and that the engram necessary for the retention of this task is not located in any one of the cerebellar nuclei. All cats were trained to perform a task in which they were required to reach for and grasp a vertical bar at the sound of a tone and move the bar to a reward zone through a template consisting of two straight grooves in the shape of an inverted "L." After the task was learned, the effects of inactivating separately each nuclear region (the fastigial, interposed, and dentate nuclei) using muscimol microinjections were determined. Data were analyzed by quantifying several features of the movement's kinematics and by determining changes in the organization of the reaching component of the movement using an application of dimensionality analysis, an analysis that examines the correlation among the changes in joint angles and limb segment positions during the task. The retention of the previously learned task also was assessed after each injection. Injections of each nuclear region affected temporal and spatial features of the learned movement. However, the largest effects resulted from inactivating the interposed nuclei. These effects included an increased length of the reach trajectory, an accentuated deviation of the wrist trajectory from a straight line, cyclic movement of the distal extremity as the target was approached, a difficulty in grasping the bar, altered temporal features of the movement, and a highly characteristic change in the dimensionality measurements. The changes in dimensionality reflected a decreased correlation (linear interdependence) of the joint angular velocities coupled with an increased correlation among the linear velocities of markers located on the joints themselves. Related but less consistent changes in dimensionality resulted from fastigial injections. The motor sequence required to negotiate the template could be executed after the nuclear microinjections, indicating that retention of the motor sequence was not affected by the inactivation of any of the cerebellar nuclei. However, in two of the five animals, some decreases in performance were observed after dentate injection that were not characteristic of changes related to an effect on retention. These data suggest that the cerebellum plays an important role in regulating the consistent, stereotypic organization of complex goal-directed movements, including the temporal correlation among joint angle velocities. The data also indicate that the retention of the task is not dependent on any of the individual cerebellar nuclear regions. Consequently, these structures are unlikely to be critical storage sites for the engram established during the learning of this task.

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.

Temporal Learning Analytics for Adaptive Assessment

ERIC Educational Resources Information Center

Papamitsiou, Zacharoula; Economides, Anastasios A.

2014-01-01

Accurate and early predictions of student performance could significantly affect interventions during teaching and assessment, which gradually could lead to improved learning outcomes. In our research, we seek to identify and formalize temporal parameters as predictors of performance ("temporal learning analytics" or TLA) and examine…

The relative temporal sequence of decline in mobility and cognition among initially unimpaired older adults: Results from the Baltimore Longitudinal Study of Aging.

PubMed

Tian, Qu; An, Yang; Resnick, Susan M; Studenski, Stephanie

2017-05-01

most older individuals who experience mobility decline, also show cognitive decline, but whether cognitive decline precedes or follows mobility limitation is not well understood. examine the temporal sequence of mobility and cognition among initially unimpaired older adults. mobility and cognition were assessed every 2 years for 6 years in 412 participants aged ≥60 with initially unimpaired cognition and gait speed. Using autoregressive models, accounting for the dependent variable from the prior assessment, baseline age, sex, body mass index and education, we examine the temporal sequence of change in mobility (6 m usual gait speed, 400 m fast walk time) and executive function (visuoperceptual speed: Digit Symbol Substitution Test (DSST); cognitive flexibility: Trail Making Test part B (TMT-B)) or memory (California Verbal Learning Test (CVLT) immediate, short-delay, long-delay). there was a bidirectional relationship over time between slower usual gait speed and both poorer DSST and TMT-B scores (Bonferroni-corrected P < 0.005). In contrast, slower 400 m fast walk time predicted subsequent poorer DSST, TMT-B, CVLT immediate recall and CVLT short-delay scores (P < 0.005), while these measures did not predict subsequent 400 m fast walk time (P > 0.005). among initially unimpaired older adults, the temporal relationship between usual gait speed and executive function is bidirectional, with each predicting change in the other, while poor fast walking performance predicts future executive function and memory changes but not vice versa. Challenging tasks like the 400 m walk appear superior to usual gait speed for predicting executive function and memory change in unimpaired older adults. Published by Oxford University Press on behalf of the British Geriatrics Society 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Probabilistic Motor Sequence Yields Greater Offline and Less Online Learning than Fixed Sequence

PubMed Central

Du, Yue; Prashad, Shikha; Schoenbrun, Ilana; Clark, Jane E.

2016-01-01

It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the fast learning stage, we asked four groups of young adults to perform the serial reaction time (SRT) task with either a fixed or probabilistic sequence and with or without preliminary knowledge (PK) of the presence of a sequence. The sequence and PK were manipulated to emphasize either procedural (probabilistic sequence; no preliminary knowledge (NPK)) or declarative (fixed sequence; with PK) memory that were found to either facilitate or inhibit offline learning. In the SRT task, there were six learning blocks with a 2 min break between each consecutive block. Throughout the session, stimuli followed the same fixed or probabilistic pattern except in Block 5, in which stimuli appeared in a random order. We found that PK facilitated the learning of a fixed sequence, but not a probabilistic sequence. In addition to overall learning measured by the mean reaction time (RT), we examined the progressive changes in RT within and between blocks (i.e., online and offline learning, respectively). It was found that the two groups who performed the fixed sequence, regardless of PK, showed greater online learning than the other two groups who performed the probabilistic sequence. The groups who performed the probabilistic sequence, regardless of PK, did not display online learning, as indicated by a decline in performance within the learning blocks. However, they did demonstrate remarkably greater offline improvement in RT, which suggests that they are learning the probabilistic sequence offline. These results suggest that in the SRT task, the fast acquisition of a motor sequence is driven by concurrent online and offline learning. In addition, as the acquisition of a probabilistic sequence requires greater procedural memory compared to the acquisition of a fixed sequence, our results suggest that offline learning is more likely to take place in a procedural sequence learning task. PMID:26973502

Probabilistic Motor Sequence Yields Greater Offline and Less Online Learning than Fixed Sequence.

PubMed

Du, Yue; Prashad, Shikha; Schoenbrun, Ilana; Clark, Jane E

2016-01-01

It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the fast learning stage, we asked four groups of young adults to perform the serial reaction time (SRT) task with either a fixed or probabilistic sequence and with or without preliminary knowledge (PK) of the presence of a sequence. The sequence and PK were manipulated to emphasize either procedural (probabilistic sequence; no preliminary knowledge (NPK)) or declarative (fixed sequence; with PK) memory that were found to either facilitate or inhibit offline learning. In the SRT task, there were six learning blocks with a 2 min break between each consecutive block. Throughout the session, stimuli followed the same fixed or probabilistic pattern except in Block 5, in which stimuli appeared in a random order. We found that PK facilitated the learning of a fixed sequence, but not a probabilistic sequence. In addition to overall learning measured by the mean reaction time (RT), we examined the progressive changes in RT within and between blocks (i.e., online and offline learning, respectively). It was found that the two groups who performed the fixed sequence, regardless of PK, showed greater online learning than the other two groups who performed the probabilistic sequence. The groups who performed the probabilistic sequence, regardless of PK, did not display online learning, as indicated by a decline in performance within the learning blocks. However, they did demonstrate remarkably greater offline improvement in RT, which suggests that they are learning the probabilistic sequence offline. These results suggest that in the SRT task, the fast acquisition of a motor sequence is driven by concurrent online and offline learning. In addition, as the acquisition of a probabilistic sequence requires greater procedural memory compared to the acquisition of a fixed sequence, our results suggest that offline learning is more likely to take place in a procedural sequence learning task.

Influence of spatial and temporal spot distribution on the ocular surface quality and maximum ablation depth after photoablation with a 1050 Hz excimer laser system.

PubMed

Mrochen, Michael; Schelling, Urs; Wuellner, Christian; Donitzky, Christof

2009-02-01

To investigate the effect of temporal and spatial distributions of laser spots (scan sequences) on the corneal surface quality after ablation and the maximum ablation of a given refractive correction after photoablation with a high-repetition-rate scanning-spot laser. IROC AG, Zurich, Switzerland, and WaveLight AG, Erlangen, Germany. Bovine corneas and poly(methyl methacrylate) (PMMA) plates were photoablated using a 1050 Hz excimer laser prototype for corneal laser surgery. Four temporal and spatial spot distributions (scan sequences) with different temporal overlapping factors were created for 3 myopic, 3 hyperopic, and 3 phototherapeutic keratectomy ablation profiles. Surface quality and maximum ablation depth were measured using a surface profiling system. The surface quality factor increased (rough surfaces) as the amount of temporal overlapping in the scan sequence and the amount of correction increased. The rise in surface quality factor was less for bovine corneas than for PMMA. The scan sequence might cause systematic substructures at the surface of the ablated material depending on the overlapping factor. The maximum ablation varied within the scan sequence. The temporal and spatial distribution of the laser spots (scan sequence) during a corneal laser procedure affected the surface quality and maximum ablation depth of the ablation profile. Corneal laser surgery could theoretically benefit from smaller spot sizes and higher repetition rates. The temporal and spatial spot distributions are relevant to achieving these aims.

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.

Short-term memory stores organized by information domain.

PubMed

Noyce, Abigail L; Cestero, Nishmar; Shinn-Cunningham, Barbara G; Somers, David C

2016-04-01

Vision and audition have complementary affinities, with vision excelling in spatial resolution and audition excelling in temporal resolution. Here, we investigated the relationships among the visual and auditory modalities and spatial and temporal short-term memory (STM) using change detection tasks. We created short sequences of visual or auditory items, such that each item within a sequence arose at a unique spatial location at a unique time. On each trial, two successive sequences were presented; subjects attended to either space (the sequence of locations) or time (the sequence of inter item intervals) and reported whether the patterns of locations or intervals were identical. Each subject completed blocks of unimodal trials (both sequences presented in the same modality) and crossmodal trials (Sequence 1 visual, Sequence 2 auditory, or vice versa) for both spatial and temporal tasks. We found a strong interaction between modality and task: Spatial performance was best on unimodal visual trials, whereas temporal performance was best on unimodal auditory trials. The order of modalities on crossmodal trials also mattered, suggesting that perceptual fidelity at encoding is critical to STM. Critically, no cost was attributable to crossmodal comparison: In both tasks, performance on crossmodal trials was as good as or better than on the weaker unimodal trials. STM representations of space and time can guide change detection in either the visual or the auditory modality, suggesting that the temporal or spatial organization of STM may supersede sensory-specific organization.

Spatiotemporal clustering of the epigenome reveals rules of dynamic gene regulation

PubMed Central

Yu, Pengfei; Xiao, Shu; Xin, Xiaoyun; Song, Chun-Xiao; Huang, Wei; McDee, Darina; Tanaka, Tetsuya; Wang, Ting; He, Chuan; Zhong, Sheng

2013-01-01

Spatial organization of different epigenomic marks was used to infer functions of the epigenome. It remains unclear what can be learned from the temporal changes of the epigenome. Here, we developed a probabilistic model to cluster genomic sequences based on the similarity of temporal changes of multiple epigenomic marks during a cellular differentiation process. We differentiated mouse embryonic stem (ES) cells into mesendoderm cells. At three time points during this differentiation process, we used high-throughput sequencing to measure seven histone modifications and variants—H3K4me1/2/3, H3K27ac, H3K27me3, H3K36me3, and H2A.Z; two DNA modifications—5-mC and 5-hmC; and transcribed mRNAs and noncoding RNAs (ncRNAs). Genomic sequences were clustered based on the spatiotemporal epigenomic information. These clusters not only clearly distinguished gene bodies, promoters, and enhancers, but also were predictive of bidirectional promoters, miRNA promoters, and piRNAs. This suggests specific epigenomic patterns exist on piRNA genes much earlier than germ cell development. Temporal changes of H3K4me2, unmethylated CpG, and H2A.Z were predictive of 5-hmC changes, suggesting unmethylated CpG and H3K4me2 as potential upstream signals guiding TETs to specific sequences. Several rules on combinatorial epigenomic changes and their effects on mRNA expression and ncRNA expression were derived, including a simple rule governing the relationship between 5-hmC and gene expression levels. A Sox17 enhancer containing a FOXA2 binding site and a Foxa2 enhancer containing a SOX17 binding site were identified, suggesting a positive feedback loop between the two mesendoderm transcription factors. These data illustrate the power of using epigenome dynamics to investigate regulatory functions. PMID:23033340

Can We Improve Structured Sequence Processing? Exploring the Direct and Indirect Effects of Computerized Training Using a Mediational Model

PubMed Central

Smith, Gretchen N. L.; Conway, Christopher M.; Bauernschmidt, Althea; Pisoni, David B.

2015-01-01

Recent research suggests that language acquisition may rely on domain-general learning abilities, such as structured sequence processing, which is the ability to extract, encode, and represent structured patterns in a temporal sequence. If structured sequence processing supports language, then it may be possible to improve language function by enhancing this foundational learning ability. The goal of the present study was to use a novel computerized training task as a means to better understand the relationship between structured sequence processing and language function. Participants first were assessed on pre-training tasks to provide baseline behavioral measures of structured sequence processing and language abilities. Participants were then quasi-randomly assigned to either a treatment group involving adaptive structured visuospatial sequence training, a treatment group involving adaptive non-structured visuospatial sequence training, or a control group. Following four days of sequence training, all participants were assessed with the same pre-training measures. Overall comparison of the post-training means revealed no group differences. However, in order to examine the potential relations between sequence training, structured sequence processing, and language ability, we used a mediation analysis that showed two competing effects. In the indirect effect, adaptive sequence training with structural regularities had a positive impact on structured sequence processing performance, which in turn had a positive impact on language processing. This finding not only identifies a potential novel intervention to treat language impairments but also may be the first demonstration that structured sequence processing can be improved and that this, in turn, has an impact on language processing. However, in the direct effect, adaptive sequence training with structural regularities had a direct negative impact on language processing. This unexpected finding suggests that adaptive training with structural regularities might potentially interfere with language processing. Taken together, these findings underscore the importance of pursuing designs that promote a better understanding of the mechanisms underlying training-related changes, so that regimens can be developed that help reduce these types of negative effects while simultaneously maximizing the benefits to outcome measures of interest. PMID:25946222

Can we improve structured sequence processing? Exploring the direct and indirect effects of computerized training using a mediational model.

PubMed

Smith, Gretchen N L; Conway, Christopher M; Bauernschmidt, Althea; Pisoni, David B

2015-01-01

Recent research suggests that language acquisition may rely on domain-general learning abilities, such as structured sequence processing, which is the ability to extract, encode, and represent structured patterns in a temporal sequence. If structured sequence processing supports language, then it may be possible to improve language function by enhancing this foundational learning ability. The goal of the present study was to use a novel computerized training task as a means to better understand the relationship between structured sequence processing and language function. Participants first were assessed on pre-training tasks to provide baseline behavioral measures of structured sequence processing and language abilities. Participants were then quasi-randomly assigned to either a treatment group involving adaptive structured visuospatial sequence training, a treatment group involving adaptive non-structured visuospatial sequence training, or a control group. Following four days of sequence training, all participants were assessed with the same pre-training measures. Overall comparison of the post-training means revealed no group differences. However, in order to examine the potential relations between sequence training, structured sequence processing, and language ability, we used a mediation analysis that showed two competing effects. In the indirect effect, adaptive sequence training with structural regularities had a positive impact on structured sequence processing performance, which in turn had a positive impact on language processing. This finding not only identifies a potential novel intervention to treat language impairments but also may be the first demonstration that structured sequence processing can be improved and that this, in turn, has an impact on language processing. However, in the direct effect, adaptive sequence training with structural regularities had a direct negative impact on language processing. This unexpected finding suggests that adaptive training with structural regularities might potentially interfere with language processing. Taken together, these findings underscore the importance of pursuing designs that promote a better understanding of the mechanisms underlying training-related changes, so that regimens can be developed that help reduce these types of negative effects while simultaneously maximizing the benefits to outcome measures of interest.

Application of Geostatistical Methods and Machine Learning for spatio-temporal Earthquake Cluster Analysis

NASA Astrophysics Data System (ADS)

Schaefer, A. M.; Daniell, J. E.; Wenzel, F.

2014-12-01

Earthquake clustering tends to be an increasingly important part of general earthquake research especially in terms of seismic hazard assessment and earthquake forecasting and prediction approaches. The distinct identification and definition of foreshocks, aftershocks, mainshocks and secondary mainshocks is taken into account using a point based spatio-temporal clustering algorithm originating from the field of classic machine learning. This can be further applied for declustering purposes to separate background seismicity from triggered seismicity. The results are interpreted and processed to assemble 3D-(x,y,t) earthquake clustering maps which are based on smoothed seismicity records in space and time. In addition, multi-dimensional Gaussian functions are used to capture clustering parameters for spatial distribution and dominant orientations. Clusters are further processed using methodologies originating from geostatistics, which have been mostly applied and developed in mining projects during the last decades. A 2.5D variogram analysis is applied to identify spatio-temporal homogeneity in terms of earthquake density and energy output. The results are mitigated using Kriging to provide an accurate mapping solution for clustering features. As a case study, seismic data of New Zealand and the United States is used, covering events since the 1950s, from which an earthquake cluster catalogue is assembled for most of the major events, including a detailed analysis of the Landers and Christchurch sequences.

Temporal Coordination and Adaptation to Rate Change in Music Performance

ERIC Educational Resources Information Center

Loehr, Janeen D.; Large, Edward W.; Palmer, Caroline

2011-01-01

People often coordinate their actions with sequences that exhibit temporal variability and unfold at multiple periodicities. We compared oscillator- and timekeeper-based accounts of temporal coordination by examining musicians' coordination of rhythmic musical sequences with a metronome that gradually changed rate at the end of a musical phrase…

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.

Mind the gap: Neural coding of species identity in birdsong prosody.

PubMed

Araki, Makoto; Bandi, M M; Yazaki-Sugiyama, Yoko

2016-12-09

Juvenile songbirds learn vocal communication from adult tutors of the same species but not from adults of other species. How species-specific learning emerges from the basic features of song prosody remains unknown. In the zebra finch auditory cortex, we discovered a class of neurons that register the silent temporal gaps between song syllables and are distinct from neurons encoding syllable morphology. Behavioral learning and neuronal coding of temporal gap structure resisted song tutoring from other species: Zebra finches fostered by Bengalese finch parents learned Bengalese finch song morphology transposed onto zebra finch temporal gaps. During the vocal learning period, temporal gap neurons fired selectively to zebra finch song. The innate temporal coding of intersyllable silent gaps suggests a neuronal barcode for conspecific vocal learning and social communication in acoustically diverse environments. Copyright © 2016, American Association for the Advancement of Science.

Framing Reinforcement Learning from Human Reward: Reward Positivity, Temporal Discounting, Episodicity, and Performance

DTIC Science & Technology

2014-09-29

Framing Reinforcement Learning from Human Reward: Reward Positivity, Temporal Discounting, Episodicity , and Performance W. Bradley Knox...positive a trainer’s reward values are; temporal discounting, the extent to which future reward is discounted in value; episodicity , whether task...learning occurs in discrete learning episodes instead of one continuing session; and task performance, the agent’s performance on the task the trainer

Tensor-based Dictionary Learning for Dynamic Tomographic Reconstruction

PubMed Central

Tan, Shengqi; Zhang, Yanbo; Wang, Ge; Mou, Xuanqin; Cao, Guohua; Wu, Zhifang; Yu, Hengyong

2015-01-01

In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction. PMID:25779991

View-invariant gait recognition method by three-dimensional convolutional neural network

NASA Astrophysics Data System (ADS)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

Adaptive metric learning with deep neural networks for video-based facial expression recognition

NASA Astrophysics Data System (ADS)

Liu, Xiaofeng; Ge, Yubin; Yang, Chao; Jia, Ping

2018-01-01

Video-based facial expression recognition has become increasingly important for plenty of applications in the real world. Despite that numerous efforts have been made for the single sequence, how to balance the complex distribution of intra- and interclass variations well between sequences has remained a great difficulty in this area. We propose the adaptive (N+M)-tuplet clusters loss function and optimize it with the softmax loss simultaneously in the training phrase. The variations introduced by personal attributes are alleviated using the similarity measurements of multiple samples in the feature space with many fewer comparison times as conventional deep metric learning approaches, which enables the metric calculations for large data applications (e.g., videos). Both the spatial and temporal relations are well explored by a unified framework that consists of an Inception-ResNet network with long short term memory and the two fully connected layer branches structure. Our proposed method has been evaluated with three well-known databases, and the experimental results show that our method outperforms many state-of-the-art approaches.

Continuous Chinese sign language recognition with CNN-LSTM

NASA Astrophysics Data System (ADS)

Yang, Su; Zhu, Qing

2017-07-01

The goal of sign language recognition (SLR) is to translate the sign language into text, and provide a convenient tool for the communication between the deaf-mute and the ordinary. In this paper, we formulate an appropriate model based on convolutional neural network (CNN) combined with Long Short-Term Memory (LSTM) network, in order to accomplish the continuous recognition work. With the strong ability of CNN, the information of pictures captured from Chinese sign language (CSL) videos can be learned and transformed into vector. Since the video can be regarded as an ordered sequence of frames, LSTM model is employed to connect with the fully-connected layer of CNN. As a recurrent neural network (RNN), it is suitable for sequence learning tasks with the capability of recognizing patterns defined by temporal distance. Compared with traditional RNN, LSTM has performed better on storing and accessing information. We evaluate this method on our self-built dataset including 40 daily vocabularies. The experimental results show that the recognition method with CNN-LSTM can achieve a high recognition rate with small training sets, which will meet the needs of real-time SLR system.

Hemispheric Asymmetries in Repetition Enhancement and Suppression Effects in the Newborn Brain

PubMed Central

Bouchon, Camillia; Nazzi, Thierry; Gervain, Judit

2015-01-01

Background The repeated presentation of stimuli typically attenuates neural responses (repetition suppression) or, less commonly, increases them (repetition enhancement) when stimuli are highly complex, degraded or presented under noisy conditions. In adult functional neuroimaging research, these repetition effects are considered as neural correlates of habituation. The development and respective functional significance of these effects in infancy remain largely unknown. Objective This study investigates repetition effects in newborns using functional near-infrared spectroscopy, and specifically the role of stimulus complexity in evoking a repetition enhancement vs. a repetition suppression response, following up on Gervain et al. (2008). In that study, abstract rule-learning was found at birth in cortical areas specific to speech processing, as evidenced by a left-lateralized repetition enhancement of the hemodynamic response to highly variable speech sequences conforming to a repetition-based ABB artificial grammar, but not to a random ABC grammar. Methods Here, the same paradigm was used to investigate how simpler stimuli (12 different sequences per condition as opposed to 140), and simpler presentation conditions (blocked rather than interleaved) would influence repetition effects at birth. Results Results revealed that the two grammars elicited different dynamics in the two hemispheres. In left fronto-temporal areas, we reproduce the early perceptual discrimination of the two grammars, with ABB giving rise to a greater response at the beginning of the experiment than ABC. In addition, the ABC grammar evoked a repetition enhancement effect over time, whereas a stable response was found for the ABB grammar. Right fronto-temporal areas showed neither initial discrimination, nor change over time to either pattern. Conclusion Taken together with Gervain et al. (2008), this is the first evidence that manipulating methodological factors influences the presence or absence of neural repetition enhancement effects in newborns and stimulus variability appears a particularly important factor. Further, this temporal modulation is restricted to the left hemisphere, confirming its specialization for learning linguistic regularities from birth. PMID:26485434

Hemispheric Asymmetries in Repetition Enhancement and Suppression Effects in the Newborn Brain.

PubMed

Bouchon, Camillia; Nazzi, Thierry; Gervain, Judit

2015-01-01

The repeated presentation of stimuli typically attenuates neural responses (repetition suppression) or, less commonly, increases them (repetition enhancement) when stimuli are highly complex, degraded or presented under noisy conditions. In adult functional neuroimaging research, these repetition effects are considered as neural correlates of habituation. The development and respective functional significance of these effects in infancy remain largely unknown. This study investigates repetition effects in newborns using functional near-infrared spectroscopy, and specifically the role of stimulus complexity in evoking a repetition enhancement vs. a repetition suppression response, following up on Gervain et al. (2008). In that study, abstract rule-learning was found at birth in cortical areas specific to speech processing, as evidenced by a left-lateralized repetition enhancement of the hemodynamic response to highly variable speech sequences conforming to a repetition-based ABB artificial grammar, but not to a random ABC grammar. Here, the same paradigm was used to investigate how simpler stimuli (12 different sequences per condition as opposed to 140), and simpler presentation conditions (blocked rather than interleaved) would influence repetition effects at birth. Results revealed that the two grammars elicited different dynamics in the two hemispheres. In left fronto-temporal areas, we reproduce the early perceptual discrimination of the two grammars, with ABB giving rise to a greater response at the beginning of the experiment than ABC. In addition, the ABC grammar evoked a repetition enhancement effect over time, whereas a stable response was found for the ABB grammar. Right fronto-temporal areas showed neither initial discrimination, nor change over time to either pattern. Taken together with Gervain et al. (2008), this is the first evidence that manipulating methodological factors influences the presence or absence of neural repetition enhancement effects in newborns and stimulus variability appears a particularly important factor. Further, this temporal modulation is restricted to the left hemisphere, confirming its specialization for learning linguistic regularities from birth.

Learning temporal rules to forecast instability in continuously monitored patients.

PubMed

Guillame-Bert, Mathieu; Dubrawski, Artur; Wang, Donghan; Hravnak, Marilyn; Clermont, Gilles; Pinsky, Michael R

2017-01-01

Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appeal of rule extraction techniques stems from their ability to handle intricate problems yet produce models based on rules that can be comprehended by humans, and are therefore more transparent. Human comprehension is a factor that may improve adoption and use of data-driven decision support systems clinically via face validity. In this work, we explore whether we can reliably and informatively forecast cardiorespiratory instability (CRI) in step-down unit (SDU) patients utilizing data from continuous monitoring of physiologic vital sign (VS) measurements. We use a temporal association rule extraction technique in conjunction with a rule fusion protocol to learn how to forecast CRI in continuously monitored patients. We detail our approach and present and discuss encouraging empirical results obtained using continuous multivariate VS data from the bedside monitors of 297 SDU patients spanning 29 346 hours (3.35 patient-years) of observation. We present example rules that have been learned from data to illustrate potential benefits of comprehensibility of the extracted models, and we analyze the empirical utility of each VS as a potential leading indicator of an impending CRI event. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

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.

Classification and Weakly Supervised Pain Localization using Multiple Segment Representation.

PubMed

Sikka, Karan; Dhall, Abhinav; Bartlett, Marian Stewart

2014-10-01

Automatic pain recognition from videos is a vital clinical application and, owing to its spontaneous nature, poses interesting challenges to automatic facial expression recognition (AFER) research. Previous pain vs no-pain systems have highlighted two major challenges: (1) ground truth is provided for the sequence, but the presence or absence of the target expression for a given frame is unknown, and (2) the time point and the duration of the pain expression event(s) in each video are unknown. To address these issues we propose a novel framework (referred to as MS-MIL) where each sequence is represented as a bag containing multiple segments, and multiple instance learning (MIL) is employed to handle this weakly labeled data in the form of sequence level ground-truth. These segments are generated via multiple clustering of a sequence or running a multi-scale temporal scanning window, and are represented using a state-of-the-art Bag of Words (BoW) representation. This work extends the idea of detecting facial expressions through 'concept frames' to 'concept segments' and argues through extensive experiments that algorithms such as MIL are needed to reap the benefits of such representation. The key advantages of our approach are: (1) joint detection and localization of painful frames using only sequence-level ground-truth, (2) incorporation of temporal dynamics by representing the data not as individual frames but as segments, and (3) extraction of multiple segments, which is well suited to signals with uncertain temporal location and duration in the video. Extensive experiments on UNBC-McMaster Shoulder Pain dataset highlight the effectiveness of the approach by achieving competitive results on both tasks of pain classification and localization in videos. We also empirically evaluate the contributions of different components of MS-MIL. The paper also includes the visualization of discriminative facial patches, important for pain detection, as discovered by our algorithm and relates them to Action Units that have been associated with pain expression. We conclude the paper by demonstrating that MS-MIL yields a significant improvement on another spontaneous facial expression dataset, the FEEDTUM dataset.

Time and Associative Learning.

PubMed

Balsam, Peter D; Drew, Michael R; Gallistel, C R

2010-01-01

In a basic associative learning paradigm, learning is said to have occurred when the conditioned stimulus evokes an anticipatory response. This learning is widely believed to depend on the contiguous presentation of conditioned and unconditioned stimulus. However, what it means to be contiguous has not been rigorously defined. Here we examine the empirical bases for these beliefs and suggest an alternative view based on the hypothesis that learning about the temporal relationships between events determines the speed of emergence, vigor and form of conditioned behavior. This temporal learning occurs very rapidly and prior to the appearance of the anticipatory response. The temporal relations are learned even when no anticipatory response is evoked. The speed with which an anticipatory response emerges is proportional to the informativeness of the predictive cue (CS) regarding the rate of occurrence of the predicted event (US). This analysis gives an account of what we mean by "temporal pairing" and is in accord with the data on speed of acquisition and basic findings in the cue competition literature. In this account, learning depends on perceiving and encoding temporal regularities rather than stimulus contiguities.

Time and Associative Learning

PubMed Central

Balsam, Peter D; Drew, Michael R.; Gallistel, C.R.

2010-01-01

In a basic associative learning paradigm, learning is said to have occurred when the conditioned stimulus evokes an anticipatory response. This learning is widely believed to depend on the contiguous presentation of conditioned and unconditioned stimulus. However, what it means to be contiguous has not been rigorously defined. Here we examine the empirical bases for these beliefs and suggest an alternative view based on the hypothesis that learning about the temporal relationships between events determines the speed of emergence, vigor and form of conditioned behavior. This temporal learning occurs very rapidly and prior to the appearance of the anticipatory response. The temporal relations are learned even when no anticipatory response is evoked. The speed with which an anticipatory response emerges is proportional to the informativeness of the predictive cue (CS) regarding the rate of occurrence of the predicted event (US). This analysis gives an account of what we mean by “temporal pairing” and is in accord with the data on speed of acquisition and basic findings in the cue competition literature. In this account, learning depends on perceiving and encoding temporal regularities rather than stimulus contiguities. PMID:21359131

A scale-invariant internal representation of time.

PubMed

Shankar, Karthik H; Howard, Marc W

2012-01-01

We propose a principled way to construct an internal representation of the temporal stimulus history leading up to the present moment. A set of leaky integrators performs a Laplace transform on the stimulus function, and a linear operator approximates the inversion of the Laplace transform. The result is a representation of stimulus history that retains information about the temporal sequence of stimuli. This procedure naturally represents more recent stimuli more accurately than less recent stimuli; the decrement in accuracy is precisely scale invariant. This procedure also yields time cells that fire at specific latencies following the stimulus with a scale-invariant temporal spread. Combined with a simple associative memory, this representation gives rise to a moment-to-moment prediction that is also scale invariant in time. We propose that this scale-invariant representation of temporal stimulus history could serve as an underlying representation accessible to higher-level behavioral and cognitive mechanisms. In order to illustrate the potential utility of this scale-invariant representation in a variety of fields, we sketch applications using minimal performance functions to problems in classical conditioning, interval timing, scale-invariant learning in autoshaping, and the persistence of the recency effect in episodic memory across timescales.

Profiles of cognitive dysfunction in chronic amphetamine and heroin abusers.

PubMed

Ornstein, T J; Iddon, J L; Baldacchino, A M; Sahakian, B J; London, M; Everitt, B J; Robbins, T W

2000-08-01

Groups of subjects whose primary drug of abuse was amphetamine or heroin were compared, together with age- and IQ-matched control subjects. The study consisted of a neuropsychological test battery which included both conventional tests and also computerised tests of recognition memory, spatial working memory, planning, sequence generation, visual discrimination learning, and attentional set-shifting. Many of these tests have previously been shown to be sensitive to cortical damage (including selective lesions of the temporal or frontal lobes) and to cognitive deficits in dementia, basal ganglia disease, and neuropsychiatric disorder. Qualitative differences, as well as some commonalities, were found in the profile of cognitive impairment between the two groups. The chronic amphetamine abusers were significantly impaired in performance on the extra-dimensional shift task (a core component of the Wisconsin Card Sort Test) whereas in contrast, the heroin abusers were impaired in learning the normally easier intra-dimensional shift component. Both groups were impaired in some of tests of spatial working memory. However, the amphetamine group, unlike the heroin group, were not deficient in an index of strategic performance on this test. The heroin group failed to show significant improvement between two blocks of a sequence generation task after training and additionally exhibited more perseverative behavior on this task. The two groups were profoundly, but equivalently impaired on a test of pattern recognition memory sensitive to temporal lobe dysfunction. These results indicate that chronic drug use may lead to distinct patterns of cognitive impairment that may be associated with dysfunction of different components of cortico-striatal circuitry.

Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies

NASA Astrophysics Data System (ADS)

Fournier-Viger, Philippe; Nkambou, Roger; Faghihi, Usef; Nguifo, Engelbert Mephu

We propose two mechanisms for agent learning based on the idea of mining temporal patterns from agent behavior. The first one consists of extracting temporal patterns from the perceived behavior of other agents accomplishing a task, to learn the task. The second learning mechanism consists in extracting temporal patterns from an agent's own behavior. In this case, the agent then reuses patterns that brought self-satisfaction. In both cases, no assumption is made on how the observed agents' behavior is internally generated. A case study with a real application is presented to illustrate each learning mechanism.

Age effects on discrimination of timing in auditory sequences

NASA Astrophysics Data System (ADS)

Fitzgibbons, Peter J.; Gordon-Salant, Sandra

2004-08-01

The experiments examined age-related changes in temporal sensitivity to increments in the interonset intervals (IOI) of components in tonal sequences. Discrimination was examined using reference sequences consisting of five 50-ms tones separated by silent intervals; tone frequencies were either fixed at 4 kHz or varied within a 2-4-kHz range to produce spectrally complex patterns. The tonal IOIs within the reference sequences were either equal (200 or 600 ms) or varied individually with an average value of 200 or 600 ms to produce temporally complex patterns. The difference limen (DL) for increments of IOI was measured. Comparison sequences featured either equal increments in all tonal IOIs or increments in a single target IOI, with the sequential location of the target changing randomly across trials. Four groups of younger and older adults with and without sensorineural hearing loss participated. Results indicated that DLs for uniform changes of sequence rate were smaller than DLs for single target intervals, with the largest DLs observed for single targets embedded within temporally complex sequences. Older listeners performed more poorly than younger listeners in all conditions, but the largest age-related differences were observed for temporally complex stimulus conditions. No systematic effects of hearing loss were observed.

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.

Emergence of spike correlations in periodically forced excitable systems

NASA Astrophysics Data System (ADS)

Reinoso, José A.; Torrent, M. C.; Masoller, Cristina

2016-09-01

In sensory neurons the presence of noise can facilitate the detection of weak information-carrying signals, which are encoded and transmitted via correlated sequences of spikes. Here we investigate the relative temporal order in spike sequences induced by a subthreshold periodic input in the presence of white Gaussian noise. To simulate the spikes, we use the FitzHugh-Nagumo model and to investigate the output sequence of interspike intervals (ISIs), we use the symbolic method of ordinal analysis. We find different types of relative temporal order in the form of preferred ordinal patterns that depend on both the strength of the noise and the period of the input signal. We also demonstrate a resonancelike behavior, as certain periods and noise levels enhance temporal ordering in the ISI sequence, maximizing the probability of the preferred patterns. Our findings could be relevant for understanding the mechanisms underlying temporal coding, by which single sensory neurons represent in spike sequences the information about weak periodic stimuli.

Structure-preserving interpolation of temporal and spatial image sequences using an optical flow-based method.

PubMed

Ehrhardt, J; Säring, D; Handels, H

2007-01-01

Modern tomographic imaging devices enable the acquisition of spatial and temporal image sequences. But, the spatial and temporal resolution of such devices is limited and therefore image interpolation techniques are needed to represent images at a desired level of discretization. This paper presents a method for structure-preserving interpolation between neighboring slices in temporal or spatial image sequences. In a first step, the spatiotemporal velocity field between image slices is determined using an optical flow-based registration method in order to establish spatial correspondence between adjacent slices. An iterative algorithm is applied using the spatial and temporal image derivatives and a spatiotemporal smoothing step. Afterwards, the calculated velocity field is used to generate an interpolated image at the desired time by averaging intensities between corresponding points. Three quantitative measures are defined to evaluate the performance of the interpolation method. The behavior and capability of the algorithm is demonstrated by synthetic images. A population of 17 temporal and spatial image sequences are utilized to compare the optical flow-based interpolation method to linear and shape-based interpolation. The quantitative results show that the optical flow-based method outperforms the linear and shape-based interpolation statistically significantly. The interpolation method presented is able to generate image sequences with appropriate spatial or temporal resolution needed for image comparison, analysis or visualization tasks. Quantitative and qualitative measures extracted from synthetic phantoms and medical image data show that the new method definitely has advantages over linear and shape-based interpolation.

Differences in Early Stages of Tactile ERP Temporal Sequence (P100) in Cortical Organization during Passive Tactile Stimulation in Children with Blindness and Controls.

PubMed

Ortiz Alonso, Tomás; Santos, Juan Matías; Ortiz Terán, Laura; Borrego Hernández, Mayelin; Poch Broto, Joaquín; de Erausquin, Gabriel Alejandro

2015-01-01

Compared to their seeing counterparts, people with blindness have a greater tactile capacity. Differences in the physiology of object recognition between people with blindness and seeing people have been well documented, but not when tactile stimuli require semantic processing. We used a passive vibrotactile device to focus on the differences in spatial brain processing evaluated with event related potentials (ERP) in children with blindness (n = 12) vs. normally seeing children (n = 12), when learning a simple spatial task (lines with different orientations) or a task involving recognition of letters, to describe the early stages of its temporal sequence (from 80 to 220 msec) and to search for evidence of multi-modal cortical organization. We analysed the P100 of the ERP. Children with blindness showed earlier latencies for cognitive (perceptual) event related potentials, shorter reaction times, and (paradoxically) worse ability to identify the spatial direction of the stimulus. On the other hand, they are equally proficient in recognizing stimuli with semantic content (letters). The last observation is consistent with the role of P100 on somatosensory-based recognition of complex forms. The cortical differences between seeing control and blind groups, during spatial tactile discrimination, are associated with activation in visual pathway (occipital) and task-related association (temporal and frontal) areas. The present results show that early processing of tactile stimulation conveying cross modal information differs in children with blindness or with normal vision.

Differences in Early Stages of Tactile ERP Temporal Sequence (P100) in Cortical Organization during Passive Tactile Stimulation in Children with Blindness and Controls

PubMed Central

Ortiz Alonso, Tomás; Santos, Juan Matías; Ortiz Terán, Laura; Borrego Hernández, Mayelin; Poch Broto, Joaquín; de Erausquin, Gabriel Alejandro

2015-01-01

Compared to their seeing counterparts, people with blindness have a greater tactile capacity. Differences in the physiology of object recognition between people with blindness and seeing people have been well documented, but not when tactile stimuli require semantic processing. We used a passive vibrotactile device to focus on the differences in spatial brain processing evaluated with event related potentials (ERP) in children with blindness (n = 12) vs. normally seeing children (n = 12), when learning a simple spatial task (lines with different orientations) or a task involving recognition of letters, to describe the early stages of its temporal sequence (from 80 to 220 msec) and to search for evidence of multi-modal cortical organization. We analysed the P100 of the ERP. Children with blindness showed earlier latencies for cognitive (perceptual) event related potentials, shorter reaction times, and (paradoxically) worse ability to identify the spatial direction of the stimulus. On the other hand, they are equally proficient in recognizing stimuli with semantic content (letters). The last observation is consistent with the role of P100 on somatosensory-based recognition of complex forms. The cortical differences between seeing control and blind groups, during spatial tactile discrimination, are associated with activation in visual pathway (occipital) and task-related association (temporal and frontal) areas. The present results show that early processing of tactile stimulation conveying cross modal information differs in children with blindness or with normal vision. PMID:26225827

A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks.

PubMed

Zhang, Haitao; Wu, Chenxue; Chen, Zewei; Liu, Zhao; Zhu, Yunhong

2017-01-01

Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules.

A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks

PubMed Central

Wu, Chenxue; Liu, Zhao; Zhu, Yunhong

2017-01-01

Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules. PMID:28767687

Temporality of Features in Near-Death Experience Narratives

PubMed Central

Martial, Charlotte; Cassol, Héléna; Antonopoulos, Georgios; Charlier, Thomas; Heros, Julien; Donneau, Anne-Françoise; Charland-Verville, Vanessa; Laureys, Steven

2017-01-01

Background: After an occurrence of a Near-Death Experience (NDE), Near-Death Experiencers (NDErs) usually report extremely rich and detailed narratives. Phenomenologically, a NDE can be described as a set of distinguishable features. Some authors have proposed regular patterns of NDEs, however, the actual temporality sequence of NDE core features remains a little explored area. Objectives: The aim of the present study was to investigate the frequency distribution of these features (globally and according to the position of features in narratives) as well as the most frequently reported temporality sequences of features. Methods: We collected 154 French freely expressed written NDE narratives (i.e., Greyson NDE scale total score ≥ 7/32). A text analysis was conducted on all narratives in order to infer temporal ordering and frequency distribution of NDE features. Results: Our analyses highlighted the following most frequently reported sequence of consecutive NDE features: Out-of-Body Experience, Experiencing a tunnel, Seeing a bright light, Feeling of peace. Yet, this sequence was encountered in a very limited number of NDErs. Conclusion: These findings may suggest that NDEs temporality sequences can vary across NDErs. Exploring associations and relationships among features encountered during NDEs may complete the rigorous definition and scientific comprehension of the phenomenon. PMID:28659779

Temporality of Features in Near-Death Experience Narratives.

PubMed

Martial, Charlotte; Cassol, Héléna; Antonopoulos, Georgios; Charlier, Thomas; Heros, Julien; Donneau, Anne-Françoise; Charland-Verville, Vanessa; Laureys, Steven

2017-01-01

Background: After an occurrence of a Near-Death Experience (NDE), Near-Death Experiencers (NDErs) usually report extremely rich and detailed narratives. Phenomenologically, a NDE can be described as a set of distinguishable features. Some authors have proposed regular patterns of NDEs, however, the actual temporality sequence of NDE core features remains a little explored area. Objectives: The aim of the present study was to investigate the frequency distribution of these features (globally and according to the position of features in narratives) as well as the most frequently reported temporality sequences of features. Methods: We collected 154 French freely expressed written NDE narratives (i.e., Greyson NDE scale total score ≥ 7/32). A text analysis was conducted on all narratives in order to infer temporal ordering and frequency distribution of NDE features. Results: Our analyses highlighted the following most frequently reported sequence of consecutive NDE features: Out-of-Body Experience, Experiencing a tunnel, Seeing a bright light, Feeling of peace. Yet, this sequence was encountered in a very limited number of NDErs. Conclusion: These findings may suggest that NDEs temporality sequences can vary across NDErs. Exploring associations and relationships among features encountered during NDEs may complete the rigorous definition and scientific comprehension of the phenomenon.

Amphetamine sensitisation and memory in healthy human volunteers: a functional magnetic resonance imaging study.

PubMed

O'Daly, Owen G; Joyce, Daniel; Tracy, Derek K; Stephan, Klaas E; Murray, Robin M; Shergill, Sukhwinder

2014-09-01

Amphetamine sensitisation (AS) is an established animal model of the hypersensitivity to psychostimulants seen in patients with schizophrenia. AS also models the dysregulation of mesolimbic dopamine signalling which has been implicated in the development of psychotic symptoms. Recent data suggest that the enhanced excitability of mesolimbic dopamine neurons in AS is driven by a hyperactivity of hippocampal (subiculum) neurons, consistent with a strong association between hippocampal dysfunction and schizophrenia. While AS can be modelled in human volunteers, its functional consequences on dopaminoceptive brain regions (i.e. striatum and hippocampus) remains unclear. Here we describe the effects of a sensitising dosage pattern of dextroamphetamine on the neural correlates of motor sequence learning in healthy volunteers, within a randomised, double-blind, parallel-groups design. Behaviourally, sensitisation was characterised by enhanced subjective responses to amphetamine but did not change performance (i.e. learning rate) during an explicit sequence learning task. In contrast, functional magnetic resonance imaging (fMRI) measurements showed that repeated intermittent amphetamine exposure was associated with increased blood-oxygen-level dependent (BOLD) signal within the medial temporal lobe (MTL) (subiculum/entorhinal cortex) and midbrain, in the vicinity of the substantia nigra/ventral tegmental area (SN/VTA) during sequence encoding. Importantly, MTL hyperactivity correlated with the sensitisation of amphetamine-induced attentiveness. The MTL-midbrain hyperactivity reported here mirrors observations in sensitised rodents and is consistent with contemporary models of schizophrenia and behavioural sensitisation. These findings of meso-hippocampal hyperactivity during AS thus link pathophysiological concepts of dopamine dysregulation to cognitive models of psychosis. © The Author(s) 2014.

Exploring the spatio-temporal neural basis of face learning

PubMed Central

Yang, Ying; Xu, Yang; Jew, Carol A.; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

2017-01-01

Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150–250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150–250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces. PMID:28570739

Exploring the spatio-temporal neural basis of face learning.

PubMed

Yang, Ying; Xu, Yang; Jew, Carol A; Pyles, John A; Kass, Robert E; Tarr, Michael J

2017-06-01

Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150-250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150-250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces.

Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning

PubMed Central

Turk-Browne, Nicholas B.; Botvinick, Matthew M.; Norman, Kenneth A.

2017-01-01

A growing literature suggests that the hippocampus is critical for the rapid extraction of regularities from the environment. Although this fits with the known role of the hippocampus in rapid learning, it seems at odds with the idea that the hippocampus specializes in memorizing individual episodes. In particular, the Complementary Learning Systems theory argues that there is a computational trade-off between learning the specifics of individual experiences and regularities that hold across those experiences. We asked whether it is possible for the hippocampus to handle both statistical learning and memorization of individual episodes. We exposed a neural network model that instantiates known properties of hippocampal projections and subfields to sequences of items with temporal regularities. We found that the monosynaptic pathway—the pathway connecting entorhinal cortex directly to region CA1—was able to support statistical learning, while the trisynaptic pathway—connecting entorhinal cortex to CA1 through dentate gyrus and CA3—learned individual episodes, with apparent representations of regularities resulting from associative reactivation through recurrence. Thus, in paradigms involving rapid learning, the computational trade-off between learning episodes and regularities may be handled by separate anatomical pathways within the hippocampus itself. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872368

Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning.

PubMed

Schapiro, Anna C; Turk-Browne, Nicholas B; Botvinick, Matthew M; Norman, Kenneth A

2017-01-05

A growing literature suggests that the hippocampus is critical for the rapid extraction of regularities from the environment. Although this fits with the known role of the hippocampus in rapid learning, it seems at odds with the idea that the hippocampus specializes in memorizing individual episodes. In particular, the Complementary Learning Systems theory argues that there is a computational trade-off between learning the specifics of individual experiences and regularities that hold across those experiences. We asked whether it is possible for the hippocampus to handle both statistical learning and memorization of individual episodes. We exposed a neural network model that instantiates known properties of hippocampal projections and subfields to sequences of items with temporal regularities. We found that the monosynaptic pathway-the pathway connecting entorhinal cortex directly to region CA1-was able to support statistical learning, while the trisynaptic pathway-connecting entorhinal cortex to CA1 through dentate gyrus and CA3-learned individual episodes, with apparent representations of regularities resulting from associative reactivation through recurrence. Thus, in paradigms involving rapid learning, the computational trade-off between learning episodes and regularities may be handled by separate anatomical pathways within the hippocampus itself.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

Genetic evidence supports song learning in the three-wattled bellbird Procnias tricarunculata (Cotingidae).

PubMed

Saranathan, Vinodkumar; Hamilton, Deborah; Powell, George V N; Kroodsma, Donald E; Prum, Richard O

2007-09-01

Vocal learning is thought to have evolved in three clades of birds (parrots, hummingbirds, and oscine passerines), and three clades of mammals (whales, bats, and primates). Behavioural data indicate that, unlike other suboscine passerines, the three-wattled bellbird Procnias tricarunculata (Cotingidae) is capable of vocal learning. Procnias tricarunculata shows conspicuous vocal ontogeny, striking geographical variation in song, and rapid temporal change in song within a population. Deprivation studies of vocal development in P. tricarunculata are impractical. Here, we report evidence from mitochondrial DNA sequences and nuclear microsatellite loci that genetic variation within and among the four allopatric breeding populations of P. tricarunculata is not congruent with variation in vocal behaviour. Sequences of the mitochondrial DNA control region document extensive haplotype sharing among localities and song types, and no phylogenetic resolution of geographical populations or behavioural groups. The vocally differentiated, allopatric breeding populations of P. tricarunculata are only weakly genetically differentiated populations, and are not distinct taxa. Mitochondrial DNA and microsatellite variation show small (2.9% and 13.5%, respectively) but significant correlation with geographical distance, but no significant residual variation by song type. Estimates of the strength of selection that would be needed to maintain the observed geographical pattern in vocal differentiation if songs were genetically based are unreasonably high, further discrediting the hypothesis of a genetic origin of vocal variation. These data support a fourth, phylogenetically independent origin of avian vocal learning in Procnias. Geographical variations in P. tricarunculata vocal behaviour are likely culturally evolved dialects.

Decoding semantic information from human electrocorticographic (ECoG) signals.

PubMed

Wang, Wei; Degenhart, Alan D; Sudre, Gustavo P; Pomerleau, Dean A; Tyler-Kabara, Elizabeth C

2011-01-01

This study examined the feasibility of decoding semantic information from human cortical activity. Four human subjects undergoing presurgical brain mapping and seizure foci localization participated in this study. Electrocorticographic (ECoG) signals were recorded while the subjects performed simple language tasks involving semantic information processing, such as a picture naming task where subjects named pictures of objects belonging to different semantic categories. Robust high-gamma band (60-120 Hz) activation was observed at the left inferior frontal gyrus (LIFG) and the posterior portion of the superior temporal gyrus (pSTG) with a temporal sequence corresponding to speech production and perception. Furthermore, Gaussian Naïve Bayes and Support Vector Machine classifiers, two commonly used machine learning algorithms for pattern recognition, were able to predict the semantic category of an object using cortical activity captured by ECoG electrodes covering the frontal, temporal and parietal cortices. These findings have implications for both basic neuroscience research and development of semantic-based brain-computer interface systems (BCI) that can help individuals with severe motor or communication disorders to express their intention and thoughts.

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

PubMed

Alais, David; Cass, John

2010-06-23

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

Toward a real-time system for temporal enhanced ultrasound-guided prostate biopsy.

PubMed

Azizi, Shekoofeh; Van Woudenberg, Nathan; Sojoudi, Samira; Li, Ming; Xu, Sheng; Abu Anas, Emran M; Yan, Pingkun; Tahmasebi, Amir; Kwak, Jin Tae; Turkbey, Baris; Choyke, Peter; Pinto, Peter; Wood, Bradford; Mousavi, Parvin; Abolmaesumi, Purang

2018-03-27

We have previously proposed temporal enhanced ultrasound (TeUS) as a new paradigm for tissue characterization. TeUS is based on analyzing a sequence of ultrasound data with deep learning and has been demonstrated to be successful for detection of cancer in ultrasound-guided prostate biopsy. Our aim is to enable the dissemination of this technology to the community for large-scale clinical validation. In this paper, we present a unified software framework demonstrating near-real-time analysis of ultrasound data stream using a deep learning solution. The system integrates ultrasound imaging hardware, visualization and a deep learning back-end to build an accessible, flexible and robust platform. A client-server approach is used in order to run computationally expensive algorithms in parallel. We demonstrate the efficacy of the framework using two applications as case studies. First, we show that prostate cancer detection using near-real-time analysis of RF and B-mode TeUS data and deep learning is feasible. Second, we present real-time segmentation of ultrasound prostate data using an integrated deep learning solution. The system is evaluated for cancer detection accuracy on ultrasound data obtained from a large clinical study with 255 biopsy cores from 157 subjects. It is further assessed with an independent dataset with 21 biopsy targets from six subjects. In the first study, we achieve area under the curve, sensitivity, specificity and accuracy of 0.94, 0.77, 0.94 and 0.92, respectively, for the detection of prostate cancer. In the second study, we achieve an AUC of 0.85. Our results suggest that TeUS-guided biopsy can be potentially effective for the detection of prostate cancer.

Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network

PubMed Central

Del Papa, Bruno; Priesemann, Viola

2017-01-01

Many experiments have suggested that the brain operates close to a critical state, based on signatures of criticality such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes information processing capacities, e.g. sensitivity to input, dynamical range and storage capacity, which makes it a favorable candidate state for brain function. Although models that self-organize towards a critical state have been proposed, the relation between criticality signatures and learning is still unclear. Here, we investigate signatures of criticality in a self-organizing recurrent neural network (SORN). Investigating criticality in the SORN is of particular interest because it has not been developed to show criticality. Instead, the SORN has been shown to exhibit spatio-temporal pattern learning through a combination of neural plasticity mechanisms and it reproduces a number of biological findings on neural variability and the statistics and fluctuations of synaptic efficacies. We show that, after a transient, the SORN spontaneously self-organizes into a dynamical state that shows criticality signatures comparable to those found in experiments. The plasticity mechanisms are necessary to attain that dynamical state, but not to maintain it. Furthermore, onset of external input transiently changes the slope of the avalanche distributions – matching recent experimental findings. Interestingly, the membrane noise level necessary for the occurrence of the criticality signatures reduces the model’s performance in simple learning tasks. Overall, our work shows that the biologically inspired plasticity and homeostasis mechanisms responsible for the SORN’s spatio-temporal learning abilities can give rise to criticality signatures in its activity when driven by random input, but these break down under the structured input of short repeating sequences. PMID:28552964

Temporal tuning in the bat auditory cortex is sharper when studied with natural echolocation sequences.

PubMed

Beetz, M Jerome; Hechavarría, Julio C; Kössl, Manfred

2016-06-30

Precise temporal coding is necessary for proper acoustic analysis. However, at cortical level, forward suppression appears to limit the ability of neurons to extract temporal information from natural sound sequences. Here we studied how temporal processing can be maintained in the bats' cortex in the presence of suppression evoked by natural echolocation streams that are relevant to the bats' behavior. We show that cortical neurons tuned to target-distance actually profit from forward suppression induced by natural echolocation sequences. These neurons can more precisely extract target distance information when they are stimulated with natural echolocation sequences than during stimulation with isolated call-echo pairs. We conclude that forward suppression does for time domain tuning what lateral inhibition does for selectivity forms such as auditory frequency tuning and visual orientation tuning. When talking about cortical processing, suppression should be seen as a mechanistic tool rather than a limiting element.

Situation models and memory: the effects of temporal and causal information on recall sequence.

PubMed

Brownstein, Aaron L; Read, Stephen J

2007-10-01

Participants watched an episode of the television show Cheers on video and then reported free recall. Recall sequence followed the sequence of events in the story; if one concept was observed immediately after another, it was recalled immediately after it. We also made a causal network of the show's story and found that recall sequence followed causal links; effects were recalled immediately after their causes. Recall sequence was more likely to follow causal links than temporal sequence, and most likely to follow causal links that were temporally sequential. Results were similar at 10-minute and 1-week delayed recall. This is the most direct and detailed evidence reported on sequential effects in recall. The causal network also predicted probability of recall; concepts with more links and concepts on the main causal chain were most likely to be recalled. This extends the causal network model to more complex materials than previous research.

The Temporal and Dynamic Nature of Self-Regulatory Processes during Independent and Externally Assisted Hypermedia Learning

ERIC Educational Resources Information Center

Johnson, Amy M.; Azevedo, Roger; D'Mello, Sidney K.

2011-01-01

This study examined the temporal and dynamic nature of students' self-regulatory processes while learning about the circulatory system with hypermedia. A total of 74 undergraduate students were randomly assigned to 1 of 2 conditions: independent learning or externally assisted learning. Participants in the independent learning condition used a…

Neural correlates of contextual cueing are modulated by explicit learning.

PubMed

Westerberg, Carmen E; Miller, Brennan B; Reber, Paul J; Cohen, Neal J; Paller, Ken A

2011-10-01

Contextual cueing refers to the facilitated ability to locate a particular visual element in a scene due to prior exposure to the same scene. This facilitation is thought to reflect implicit learning, as it typically occurs without the observer's knowledge that scenes repeat. Unlike most other implicit learning effects, contextual cueing can be impaired following damage to the medial temporal lobe. Here we investigated neural correlates of contextual cueing and explicit scene memory in two participant groups. Only one group was explicitly instructed about scene repetition. Participants viewed a sequence of complex scenes that depicted a landscape with five abstract geometric objects. Superimposed on each object was a letter T or L rotated left or right by 90°. Participants responded according to the target letter (T) orientation. Responses were highly accurate for all scenes. Response speeds were faster for repeated versus novel scenes. The magnitude of this contextual cueing did not differ between the two groups. Also, in both groups repeated scenes yielded reduced hemodynamic activation compared with novel scenes in several regions involved in visual perception and attention, and reductions in some of these areas were correlated with response-time facilitation. In the group given instructions about scene repetition, recognition memory for scenes was superior and was accompanied by medial temporal and more anterior activation. Thus, strategic factors can promote explicit memorization of visual scene information, which appears to engage additional neural processing beyond what is required for implicit learning of object configurations and target locations in a scene. Copyright © 2011 Elsevier Ltd. All rights reserved.

Neural correlates of contextual cueing are modulated by explicit learning

PubMed Central

Westerberg, Carmen E.; Miller, Brennan B.; Reber, Paul J.; Cohen, Neal J.; Paller, Ken A.

2011-01-01

Contextual cueing refers to the facilitated ability to locate a particular visual element in a scene due to prior exposure to the same scene. This facilitation is thought to reflect implicit learning, as it typically occurs without the observer’s knowledge that scenes repeat. Unlike most other implicit learning effects, contextual cueing can be impaired following damage to the medial temporal lobe. Here we investigated neural correlates of contextual cueing and explicit scene memory in two participant groups. Only one group was explicitly instructed about scene repetition. Participants viewed a sequence of complex scenes that depicted a landscape with five abstract geometric objects. Superimposed on each object was a letter T or L rotated left or right by 90°. Participants responded according to the target letter (T) orientation. Responses were highly accurate for all scenes. Response speeds were faster for repeated versus novel scenes. The magnitude of this contextual cueing did not differ between the two groups. Also, in both groups repeated scenes yielded reduced hemodynamic activation compared with novel scenes in several regions involved in visual perception and attention, and reductions in some of these areas were correlated with response-time facilitation. In the group given instructions about scene repetition, recognition memory for scenes was superior and was accompanied by medial temporal and more anterior activation. Thus, strategic factors can promote explicit memorization of visual scene information, which appears to engage additional neural processing beyond what is required for implicit learning of object configurations and target locations in a scene. PMID:21889947

Analysis of noise-induced temporal correlations in neuronal spike sequences

NASA Astrophysics Data System (ADS)

Reinoso, José A.; Torrent, M. C.; Masoller, Cristina

2016-11-01

We investigate temporal correlations in sequences of noise-induced neuronal spikes, using a symbolic method of time-series analysis. We focus on the sequence of time-intervals between consecutive spikes (inter-spike-intervals, ISIs). The analysis method, known as ordinal analysis, transforms the ISI sequence into a sequence of ordinal patterns (OPs), which are defined in terms of the relative ordering of consecutive ISIs. The ISI sequences are obtained from extensive simulations of two neuron models (FitzHugh-Nagumo, FHN, and integrate-and-fire, IF), with correlated noise. We find that, as the noise strength increases, temporal order gradually emerges, revealed by the existence of more frequent ordinal patterns in the ISI sequence. While in the FHN model the most frequent OP depends on the noise strength, in the IF model it is independent of the noise strength. In both models, the correlation time of the noise affects the OP probabilities but does not modify the most probable pattern.

Iterative free-energy optimization for recurrent neural networks (INFERNO).

PubMed

Pitti, Alexandre; Gaussier, Philippe; Quoy, Mathias

2017-01-01

The intra-parietal lobe coupled with the Basal Ganglia forms a working memory that demonstrates strong planning capabilities for generating robust yet flexible neuronal sequences. Neurocomputational models however, often fails to control long range neural synchrony in recurrent spiking networks due to spontaneous activity. As a novel framework based on the free-energy principle, we propose to see the problem of spikes' synchrony as an optimization problem of the neurons sub-threshold activity for the generation of long neuronal chains. Using a stochastic gradient descent, a reinforcement signal (presumably dopaminergic) evaluates the quality of one input vector to move the recurrent neural network to a desired activity; depending on the error made, this input vector is strengthened to hill-climb the gradient or elicited to search for another solution. This vector can be learned then by one associative memory as a model of the basal-ganglia to control the recurrent neural network. Experiments on habit learning and on sequence retrieving demonstrate the capabilities of the dual system to generate very long and precise spatio-temporal sequences, above two hundred iterations. Its features are applied then to the sequential planning of arm movements. In line with neurobiological theories, we discuss its relevance for modeling the cortico-basal working memory to initiate flexible goal-directed neuronal chains of causation and its relation to novel architectures such as Deep Networks, Neural Turing Machines and the Free-Energy Principle.

A neural model of hierarchical reinforcement learning

PubMed Central

Rasmussen, Daniel; 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. PMID:28683111

Temporal BYY encoding, Markovian state spaces, and space dimension determination.

PubMed

Xu, Lei

2004-09-01

As a complementary to those temporal coding approaches of the current major stream, this paper aims at the Markovian state space temporal models from the perspective of the temporal Bayesian Ying-Yang (BYY) learning with both new insights and new results on not only the discrete state featured Hidden Markov model and extensions but also the continuous state featured linear state spaces and extensions, especially with a new learning mechanism that makes selection of the state number or the dimension of state space either automatically during adaptive learning or subsequently after learning via model selection criteria obtained from this mechanism. Experiments are demonstrated to show how the proposed approach works.

Distinct Effects of Memory Retrieval and Articulatory Preparation when Learning and Accessing New Word Forms

PubMed Central

Nora, Anni; Renvall, Hanna; Kim, Jeong-Young; Service, Elisabet; Salmelin, Riitta

2015-01-01

Temporal and frontal activations have been implicated in learning of novel word forms, but their specific roles remain poorly understood. The present magnetoencephalography (MEG) study examines the roles of these areas in processing newly-established word form representations. The cortical effects related to acquiring new phonological word forms during incidental learning were localized. Participants listened to and repeated back new word form stimuli that adhered to native phonology (Finnish pseudowords) or were foreign (Korean words), with a subset of the stimuli recurring four times. Subsequently, a modified 1-back task and a recognition task addressed whether the activations modulated by learning were related to planning for overt articulation, while parametrically added noise probed reliance on developing memory representations during effortful perception. Learning resulted in decreased left superior temporal and increased bilateral frontal premotor activation for familiar compared to new items. The left temporal learning effect persisted in all tasks and was strongest when stimuli were embedded in intermediate noise. In the noisy conditions, native phonotactics evoked overall enhanced left temporal activation. In contrast, the frontal learning effects were present only in conditions requiring overt repetition and were more pronounced for the foreign language. The results indicate a functional dissociation between temporal and frontal activations in learning new phonological word forms: the left superior temporal responses reflect activation of newly-established word-form representations, also during degraded sensory input, whereas the frontal premotor effects are related to planning for articulation and are not preserved in noise. PMID:25961571

Distinct effects of memory retrieval and articulatory preparation when learning and accessing new word forms.

PubMed

Nora, Anni; Renvall, Hanna; Kim, Jeong-Young; Service, Elisabet; Salmelin, Riitta

2015-01-01

Temporal and frontal activations have been implicated in learning of novel word forms, but their specific roles remain poorly understood. The present magnetoencephalography (MEG) study examines the roles of these areas in processing newly-established word form representations. The cortical effects related to acquiring new phonological word forms during incidental learning were localized. Participants listened to and repeated back new word form stimuli that adhered to native phonology (Finnish pseudowords) or were foreign (Korean words), with a subset of the stimuli recurring four times. Subsequently, a modified 1-back task and a recognition task addressed whether the activations modulated by learning were related to planning for overt articulation, while parametrically added noise probed reliance on developing memory representations during effortful perception. Learning resulted in decreased left superior temporal and increased bilateral frontal premotor activation for familiar compared to new items. The left temporal learning effect persisted in all tasks and was strongest when stimuli were embedded in intermediate noise. In the noisy conditions, native phonotactics evoked overall enhanced left temporal activation. In contrast, the frontal learning effects were present only in conditions requiring overt repetition and were more pronounced for the foreign language. The results indicate a functional dissociation between temporal and frontal activations in learning new phonological word forms: the left superior temporal responses reflect activation of newly-established word-form representations, also during degraded sensory input, whereas the frontal premotor effects are related to planning for articulation and are not preserved in noise.

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

An Adaptive Deghosting Method in Neural Network-Based Infrared Detectors Nonuniformity Correction

PubMed Central

Li, Yiyang; Jin, Weiqi; Zhu, Jin; Zhang, Xu; Li, Shuo

2018-01-01

The problems of the neural network-based nonuniformity correction algorithm for infrared focal plane arrays mainly concern slow convergence speed and ghosting artifacts. In general, the more stringent the inhibition of ghosting, the slower the convergence speed. The factors that affect these two problems are the estimated desired image and the learning rate. In this paper, we propose a learning rate rule that combines adaptive threshold edge detection and a temporal gate. Through the noise estimation algorithm, the adaptive spatial threshold is related to the residual nonuniformity noise in the corrected image. The proposed learning rate is used to effectively and stably suppress ghosting artifacts without slowing down the convergence speed. The performance of the proposed technique was thoroughly studied with infrared image sequences with both simulated nonuniformity and real nonuniformity. The results show that the deghosting performance of the proposed method is superior to that of other neural network-based nonuniformity correction algorithms and that the convergence speed is equivalent to the tested deghosting methods. PMID:29342857

An Adaptive Deghosting Method in Neural Network-Based Infrared Detectors Nonuniformity Correction.

PubMed

Li, Yiyang; Jin, Weiqi; Zhu, Jin; Zhang, Xu; Li, Shuo

2018-01-13

The problems of the neural network-based nonuniformity correction algorithm for infrared focal plane arrays mainly concern slow convergence speed and ghosting artifacts. In general, the more stringent the inhibition of ghosting, the slower the convergence speed. The factors that affect these two problems are the estimated desired image and the learning rate. In this paper, we propose a learning rate rule that combines adaptive threshold edge detection and a temporal gate. Through the noise estimation algorithm, the adaptive spatial threshold is related to the residual nonuniformity noise in the corrected image. The proposed learning rate is used to effectively and stably suppress ghosting artifacts without slowing down the convergence speed. The performance of the proposed technique was thoroughly studied with infrared image sequences with both simulated nonuniformity and real nonuniformity. The results show that the deghosting performance of the proposed method is superior to that of other neural network-based nonuniformity correction algorithms and that the convergence speed is equivalent to the tested deghosting methods.

Song copying by humpback whales: themes and variations.

PubMed

Mercado, Eduardo; Herman, Louis M; Pack, Adam A

2005-04-01

Male humpback whales (Megaptera novaeangliae) produce long, structured sequences of sound underwater, commonly called "songs." Humpbacks progressively modify their songs over time in ways that suggest that individuals are copying song elements that they hear being used by other singers. Little is known about the factors that determine how whales learn from their auditory experiences. Song learning in birds is better understood and appears to be constrained by stable core attributes such as species-specific sound repertoires and song syntax. To clarify whether similar constraints exist for song learning by humpbacks, we analyzed changes over 14 years in the sounds used by humpback whales singing in Hawaiian waters. We found that although the properties of individual sounds within songs are quite variable over time, the overall distribution of certain acoustic features within the repertoire appears to be stable. In particular, our findings suggest that species-specific constraints on temporal features of song sounds determine song form, whereas spectral variability allows whales to flexibly adapt song elements.

Effects of learning duration on implicit transfer.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2015-10-01

Implicit learning and transfer in sequence acquisition play important roles in daily life. Several previous studies have found that even when participants are not aware that a transfer sequence has been transformed from the learning sequence, they are able to perform the transfer sequence faster and more accurately; this suggests implicit transfer of visuomotor sequences. Here, we investigated whether implicit transfer could be modulated by the number of trials completed in a learning session. Participants learned a sequence through trial and error, known as the m × n task (Hikosaka et al. in J Neurophysiol 74:1652-1661, 1995). In the learning session, participants were required to successfully perform the same sequence 4, 12, 16, or 20 times. In the transfer session, participants then learned one of two other sequences: one where the button configuration Vertically Mirrored the learning sequence, or a randomly generated sequence. Our results show that even when participants did not notice the alternation rule (i.e., vertical mirroring), their total working time was less and their total number of errors was lower in the transfer session compared with those who performed a Random sequence, irrespective of the number of trials completed in the learning session. This result suggests that implicit transfer likely occurs even over a shorter learning duration.

Temporal and Spatial Predictability of an Irrelevant Event Differently Affect Detection and Memory of Items in a Visual Sequence

PubMed Central

Ohyama, Junji; Watanabe, Katsumi

2016-01-01

We examined how the temporal and spatial predictability of a task-irrelevant visual event affects the detection and memory of a visual item embedded in a continuously changing sequence. Participants observed 11 sequentially presented letters, during which a task-irrelevant visual event was either present or absent. Predictabilities of spatial location and temporal position of the event were controlled in 2 × 2 conditions. In the spatially predictable conditions, the event occurred at the same location within the stimulus sequence or at another location, while, in the spatially unpredictable conditions, it occurred at random locations. In the temporally predictable conditions, the event timing was fixed relative to the order of the letters, while in the temporally unpredictable condition; it could not be predicted from the letter order. Participants performed a working memory task and a target detection reaction time (RT) task. Memory accuracy was higher for a letter simultaneously presented at the same location as the event in the temporally unpredictable conditions, irrespective of the spatial predictability of the event. On the other hand, the detection RTs were only faster for a letter simultaneously presented at the same location as the event when the event was both temporally and spatially predictable. Thus, to facilitate ongoing detection processes, an event must be predictable both in space and time, while memory processes are enhanced by temporally unpredictable (i.e., surprising) events. Evidently, temporal predictability has differential effects on detection and memory of a visual item embedded in a sequence of images. PMID:26869966

Temporal and Spatial Predictability of an Irrelevant Event Differently Affect Detection and Memory of Items in a Visual Sequence.

PubMed

Ohyama, Junji; Watanabe, Katsumi

2016-01-01

We examined how the temporal and spatial predictability of a task-irrelevant visual event affects the detection and memory of a visual item embedded in a continuously changing sequence. Participants observed 11 sequentially presented letters, during which a task-irrelevant visual event was either present or absent. Predictabilities of spatial location and temporal position of the event were controlled in 2 × 2 conditions. In the spatially predictable conditions, the event occurred at the same location within the stimulus sequence or at another location, while, in the spatially unpredictable conditions, it occurred at random locations. In the temporally predictable conditions, the event timing was fixed relative to the order of the letters, while in the temporally unpredictable condition; it could not be predicted from the letter order. Participants performed a working memory task and a target detection reaction time (RT) task. Memory accuracy was higher for a letter simultaneously presented at the same location as the event in the temporally unpredictable conditions, irrespective of the spatial predictability of the event. On the other hand, the detection RTs were only faster for a letter simultaneously presented at the same location as the event when the event was both temporally and spatially predictable. Thus, to facilitate ongoing detection processes, an event must be predictable both in space and time, while memory processes are enhanced by temporally unpredictable (i.e., surprising) events. Evidently, temporal predictability has differential effects on detection and memory of a visual item embedded in a sequence of images.

Addition of fornix transection to frontal-temporal disconnection increases the impairment in object-in-place memory in macaque monkeys.

PubMed

Wilson, C R E; Baxter, M G; Easton, A; Gaffan, D

2008-04-01

Both frontal-inferotemporal disconnection and fornix transection (Fx) in the monkey impair object-in-place scene learning, a model of human episodic memory. If the contribution of the fornix to scene learning is via interaction with or modulation of frontal-temporal interaction--that is, if they form a unitary system--then Fx should have no further effect when added to frontal-temporal disconnection. However, if the contribution of the fornix is to some extent distinct, then fornix lesions may produce an additional deficit in scene learning beyond that caused by frontal-temporal disconnection. To distinguish between these possibilities, we trained three male rhesus monkeys on the object-in-place scene-learning task. We tested their learning on the task following frontal-temporal disconnection, achieved by crossed unilateral aspiration of the frontal cortex in one hemisphere and the inferotemporal cortex in the other, and again following the addition of Fx. The monkeys were significantly impaired in scene learning following frontal-temporal disconnection, and furthermore showed a significant increase in this impairment following the addition of Fx, from 32.8% error to 40.5% error (chance = 50%). The increased impairment following the addition of Fx provides evidence that the fornix and frontal-inferotemporal interaction make distinct contributions to episodic memory.

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…

Expectation, information processing, and subjective duration.

PubMed

Simchy-Gross, Rhimmon; Margulis, Elizabeth Hellmuth

2018-01-01

In research on psychological time, it is important to examine the subjective duration of entire stimulus sequences, such as those produced by music (Teki, Frontiers in Neuroscience, 10, 2016). Yet research on the temporal oddball illusion (according to which oddball stimuli seem longer than standard stimuli of the same duration) has examined only the subjective duration of single events contained within sequences, not the subjective duration of sequences themselves. Does the finding that oddballs seem longer than standards translate to entire sequences, such that entire sequences that contain oddballs seem longer than those that do not? Is this potential translation influenced by the mode of information processing-whether people are engaged in direct or indirect temporal processing? Two experiments aimed to answer both questions using different manipulations of information processing. In both experiments, musical sequences either did or did not contain oddballs (auditory sliding tones). To manipulate information processing, we varied the task (Experiment 1), the sequence event structure (Experiments 1 and 2), and the sequence familiarity (Experiment 2) independently within subjects. Overall, in both experiments, the sequences that contained oddballs seemed shorter than those that did not when people were engaged in direct temporal processing, but longer when people were engaged in indirect temporal processing. These findings support the dual-process contingency model of time estimation (Zakay, Attention, Perception & Psychophysics, 54, 656-664, 1993). Theoretical implications for attention-based and memory-based models of time estimation, the pacemaker accumulator and coding efficiency hypotheses of time perception, and dynamic attending theory are discussed.

The Impact of Students' Temporal Perspectives on Time-on-Task and Learning Performance in Game Based Learning

ERIC Educational Resources Information Center

Romero, Margarida; Usart, Mireia

2013-01-01

The use of games for educational purposes has been considered as a learning methodology that attracts the students' attention and may allow focusing individuals on the learning activity through the [serious games] SG game dynamic. Based on the hypothesis that students' Temporal Perspective has an impact on learning performance and time-on-task,…

Stress time-dependently influences the acquisition and retrieval of unrelated information by producing a memory of its own.

PubMed

Cadle, Chelsea E; Zoladz, Phillip R

2015-01-01

Stress induces several temporally guided "waves" of psychobiological responses that differentially influence learning and memory. One way to understand how the temporal dynamics of stress influence these cognitive processes is to consider stress, itself, as a learning experience that influences additional learning and memory. Indeed, research has shown that stress results in electrophysiological and biochemical activity that is remarkably similar to the activity observed as a result of learning. In this review, we will present the idea that when a stressful episode immediately precedes or follows learning, such learning is enhanced because the learned information becomes a part of the stress context and is tagged by the emotional memory being formed. In contrast, when a stressful episode is temporally separated from learning or is experienced prior to retrieval, such learning or memory is impaired because the learning or memory is experienced outside the context of the stress episode or subsequent to a saturation of synaptic plasticity, which renders the retrieval of information improbable. The temporal dynamics of emotional memory formation, along with the neurobiological correlates of the stress response, are discussed to support these hypotheses.

On the asymptotic equivalence between differential Hebbian and temporal difference learning.

PubMed

Kolodziejski, Christoph; Porr, Bernd; Wörgötter, Florentin

2009-04-01

In this theoretical contribution, we provide mathematical proof that two of the most important classes of network learning-correlation-based differential Hebbian learning and reward-based temporal difference learning-are asymptotically equivalent when timing the learning with a modulatory signal. This opens the opportunity to consistently reformulate most of the abstract reinforcement learning framework from a correlation-based perspective more closely related to the biophysics of neurons.

Benefits of fading in perceptual learning are driven by more than dimensional attention.

PubMed

Wisniewski, Matthew G; Radell, Milen L; Church, Barbara A; Mercado, Eduardo

2017-01-01

Individuals learn to classify percepts effectively when the task is initially easy and then gradually increases in difficulty. Some suggest that this is because easy-to-discriminate events help learners focus attention on discrimination-relevant dimensions. Here, we tested whether such attentional-spotlighting accounts are sufficient to explain easy-to-hard effects in auditory perceptual learning. In two experiments, participants were trained to discriminate periodic, frequency-modulated (FM) tones in two separate frequency ranges (300-600 Hz or 3000-6000 Hz). In one frequency range, sounds gradually increased in similarity as training progressed. In the other, stimulus similarity was constant throughout training. After training, participants showed better performance in their progressively trained frequency range, even though the discrimination-relevant dimension across ranges was the same. Learning theories that posit experience-dependent changes in stimulus representations and/or the strengthening of associations with differential responses, predict the observed specificity of easy-to-hard effects, whereas attentional-spotlighting theories do not. Calibrating the difficulty and temporal sequencing of training experiences to support more incremental representation-based learning can enhance the effectiveness of practice beyond any benefits gained from explicitly highlighting relevant dimensions.

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).

A Psychological Perspective on the Temporal Dimensions of E-Learning

ERIC Educational Resources Information Center

Terras, Melody M.; Ramsay, Judith

2014-01-01

Psychological perspectives have long been reflected in educational theory and practice. Therefore, we expect psychology to contribute to our understanding of the impact of technology on the temporal aspects of teaching and learning in this digital age. Understanding how we learn, and how learning and teaching can be facilitated, are key to…

Training in rapid auditory processing ameliorates auditory comprehension in aphasic patients: a randomized controlled pilot study.

PubMed

Szelag, Elzbieta; Lewandowska, Monika; Wolak, Tomasz; Seniow, Joanna; Poniatowska, Renata; Pöppel, Ernst; Szymaszek, Aneta

2014-03-15

Experimental studies have often reported close associations between rapid auditory processing and language competency. The present study was aimed at improving auditory comprehension in aphasic patients following specific training in the perception of temporal order (TO) of events. We tested 18 aphasic patients showing both comprehension and TO perception deficits. Auditory comprehension was assessed by the Token Test, phonemic awareness and Voice-Onset-Time Test. The TO perception was assessed using auditory Temporal-Order-Threshold, defined as the shortest interval between two consecutive stimuli, necessary to report correctly their before-after relation. Aphasic patients participated in eight 45-minute sessions of either specific temporal training (TT, n=11) aimed to improve sequencing abilities, or control non-temporal training (NT, n=7) focussed on volume discrimination. The TT yielded improved TO perception; moreover, a transfer of improvement was observed from the time domain to the language domain, which was untrained during the training. The NT did not improve either the TO perception or comprehension in any language test. These results are in agreement with previous literature studies which proved ameliorated language competency following the TT in language-learning-impaired or dyslexic children. Our results indicated for the first time such benefits also in aphasic patients. Copyright © 2013 Elsevier B.V. All rights reserved.

Spatiotemporal information during unsupervised learning enhances viewpoint invariant object recognition

PubMed Central

Tian, Moqian; Grill-Spector, Kalanit

2015-01-01

Recognizing objects is difficult because it requires both linking views of an object that can be different and distinguishing objects with similar appearance. Interestingly, people can learn to recognize objects across views in an unsupervised way, without feedback, just from the natural viewing statistics. However, there is intense debate regarding what information during unsupervised learning is used to link among object views. Specifically, researchers argue whether temporal proximity, motion, or spatiotemporal continuity among object views during unsupervised learning is beneficial. Here, we untangled the role of each of these factors in unsupervised learning of novel three-dimensional (3-D) objects. We found that after unsupervised training with 24 object views spanning a 180° view space, participants showed significant improvement in their ability to recognize 3-D objects across rotation. Surprisingly, there was no advantage to unsupervised learning with spatiotemporal continuity or motion information than training with temporal proximity. However, we discovered that when participants were trained with just a third of the views spanning the same view space, unsupervised learning via spatiotemporal continuity yielded significantly better recognition performance on novel views than learning via temporal proximity. These results suggest that while it is possible to obtain view-invariant recognition just from observing many views of an object presented in temporal proximity, spatiotemporal information enhances performance by producing representations with broader view tuning than learning via temporal association. Our findings have important implications for theories of object recognition and for the development of computational algorithms that learn from examples. PMID:26024454

Statistical Features of the 2010 Beni-Ilmane, Algeria, Aftershock Sequence

NASA Astrophysics Data System (ADS)

Hamdache, M.; Peláez, J. A.; Gospodinov, D.; Henares, J.

2018-03-01

The aftershock sequence of the 2010 Beni-Ilmane ( M W 5.5) earthquake is studied in depth to analyze the spatial and temporal variability of seismicity parameters of the relationships modeling the sequence. The b value of the frequency-magnitude distribution is examined rigorously. A threshold magnitude of completeness equal to 2.1, using the maximum curvature procedure or the changing point algorithm, and a b value equal to 0.96 ± 0.03 have been obtained for the entire sequence. Two clusters have been identified and characterized by their faulting type, exhibiting b values equal to 0.99 ± 0.05 and 1.04 ± 0.05. Additionally, the temporal decay of the aftershock sequence was examined using a stochastic point process. The analysis was done through the restricted epidemic-type aftershock sequence (RETAS) stochastic model, which allows the possibility to recognize the prevailing clustering pattern of the relaxation process in the examined area. The analysis selected the epidemic-type aftershock sequence (ETAS) model to offer the most appropriate description of the temporal distribution, which presumes that all events in the sequence can cause secondary aftershocks. Finally, the fractal dimensions are estimated using the integral correlation. The obtained D 2 values are 2.15 ± 0.01, 2.23 ± 0.01 and 2.17 ± 0.02 for the entire sequence, and for the first and second cluster, respectively. An analysis of the temporal evolution of the fractal dimensions D -2, D 0, D 2 and the spectral slope has been also performed to derive and characterize the different clusters included in the sequence.

The Impact of Participation in Music on Learning Mathematics

ERIC Educational Resources Information Center

Holmes, Sylwia; Hallam, Susan

2017-01-01

Music psychologists have established that some forms of musical activity improve intellectual performance, spatial-temporal reasoning and other skills advantageous for learning. In this research, the potential of active music-making for improving pupils' achievement in spatial- temporal reasoning was investigated. As spatial-temporal skills are…

Temporal plasticity in auditory cortex improves neural discrimination of speech sounds

PubMed Central

Engineer, Crystal T.; Shetake, Jai A.; Engineer, Navzer D.; Vrana, Will A.; Wolf, Jordan T.; Kilgard, Michael P.

2017-01-01

Background Many individuals with language learning impairments exhibit temporal processing deficits and degraded neural responses to speech sounds. Auditory training can improve both the neural and behavioral deficits, though significant deficits remain. Recent evidence suggests that vagus nerve stimulation (VNS) paired with rehabilitative therapies enhances both cortical plasticity and recovery of normal function. Objective/Hypothesis We predicted that pairing VNS with rapid tone trains would enhance the primary auditory cortex (A1) response to unpaired novel speech sounds. Methods VNS was paired with tone trains 300 times per day for 20 days in adult rats. Responses to isolated speech sounds, compressed speech sounds, word sequences, and compressed word sequences were recorded in A1 following the completion of VNS-tone train pairing. Results Pairing VNS with rapid tone trains resulted in stronger, faster, and more discriminable A1 responses to speech sounds presented at conversational rates. Conclusion This study extends previous findings by documenting that VNS paired with rapid tone trains altered the neural response to novel unpaired speech sounds. Future studies are necessary to determine whether pairing VNS with appropriate auditory stimuli could potentially be used to improve both neural responses to speech sounds and speech perception in individuals with receptive language disorders. PMID:28131520

Time fluctuation analysis of forest fire sequences

NASA Astrophysics Data System (ADS)

Vega Orozco, Carmen D.; Kanevski, Mikhaïl; Tonini, Marj; Golay, Jean; Pereira, Mário J. G.

2013-04-01

Forest fires are complex events involving both space and time fluctuations. Understanding of their dynamics and pattern distribution is of great importance in order to improve the resource allocation and support fire management actions at local and global levels. This study aims at characterizing the temporal fluctuations of forest fire sequences observed in Portugal, which is the country that holds the largest wildfire land dataset in Europe. This research applies several exploratory data analysis measures to 302,000 forest fires occurred from 1980 to 2007. The applied clustering measures are: Morisita clustering index, fractal and multifractal dimensions (box-counting), Ripley's K-function, Allan Factor, and variography. These algorithms enable a global time structural analysis describing the degree of clustering of a point pattern and defining whether the observed events occur randomly, in clusters or in a regular pattern. The considered methods are of general importance and can be used for other spatio-temporal events (i.e. crime, epidemiology, biodiversity, geomarketing, etc.). An important contribution of this research deals with the analysis and estimation of local measures of clustering that helps understanding their temporal structure. Each measure is described and executed for the raw data (forest fires geo-database) and results are compared to reference patterns generated under the null hypothesis of randomness (Poisson processes) embedded in the same time period of the raw data. This comparison enables estimating the degree of the deviation of the real data from a Poisson process. Generalizations to functional measures of these clustering methods, taking into account the phenomena, were also applied and adapted to detect time dependences in a measured variable (i.e. burned area). The time clustering of the raw data is compared several times with the Poisson processes at different thresholds of the measured function. Then, the clustering measure value depends on the threshold which helps to understand the time pattern of the studied events. Our findings detected the presence of overdensity of events in particular time periods and showed that the forest fire sequences in Portugal can be considered as a multifractal process with a degree of time-clustering of the events. Key words: time sequences, Morisita index, fractals, multifractals, box-counting, Ripley's K-function, Allan Factor, variography, forest fires, point process. Acknowledgements This work was partly supported by the SNFS Project No. 200021-140658, "Analysis and Modelling of Space-Time Patterns in Complex Regions". References - Kanevski M. (Editor). 2008. Advanced Mapping of Environmental Data: Geostatistics, Machine Learning and Bayesian Maximum Entropy. London / Hoboken: iSTE / Wiley. - Telesca L. and Pereira M.G. 2010. Time-clustering investigation of fire temporal fluctuations in Portugal, Nat. Hazards Earth Syst. Sci., vol. 10(4): 661-666. - Vega Orozco C., Tonini M., Conedera M., Kanevski M. (2012) Cluster recognition in spatial-temporal sequences: the case of forest fires, Geoinformatica, vol. 16(4): 653-673.

Nonspatial Sequence Coding in CA1 Neurons

PubMed Central

Allen, Timothy A.; Salz, Daniel M.; McKenzie, Sam

2016-01-01

The hippocampus is critical to the memory for sequences of events, a defining feature of episodic memory. However, the fundamental neuronal mechanisms underlying this capacity remain elusive. While considerable research indicates hippocampal neurons can represent sequences of locations, direct evidence of coding for the memory of sequential relationships among nonspatial events remains lacking. To address this important issue, we recorded neural activity in CA1 as rats performed a hippocampus-dependent sequence-memory task. Briefly, the task involves the presentation of repeated sequences of odors at a single port and requires rats to identify each item as “in sequence” or “out of sequence”. We report that, while the animals' location and behavior remained constant, hippocampal activity differed depending on the temporal context of items—in this case, whether they were presented in or out of sequence. Some neurons showed this effect across items or sequence positions (general sequence cells), while others exhibited selectivity for specific conjunctions of item and sequence position information (conjunctive sequence cells) or for specific probe types (probe-specific sequence cells). We also found that the temporal context of individual trials could be accurately decoded from the activity of neuronal ensembles, that sequence coding at the single-cell and ensemble level was linked to sequence memory performance, and that slow-gamma oscillations (20–40 Hz) were more strongly modulated by temporal context and performance than theta oscillations (4–12 Hz). These findings provide compelling evidence that sequence coding extends beyond the domain of spatial trajectories and is thus a fundamental function of the hippocampus. SIGNIFICANCE STATEMENT The ability to remember the order of life events depends on the hippocampus, but the underlying neural mechanisms remain poorly understood. Here we addressed this issue by recording neural activity in hippocampal region CA1 while rats performed a nonspatial sequence memory task. We found that hippocampal neurons code for the temporal context of items (whether odors were presented in the correct or incorrect sequential position) and that this activity is linked with memory performance. The discovery of this novel form of temporal coding in hippocampal neurons advances our fundamental understanding of the neurobiology of episodic memory and will serve as a foundation for our cross-species, multitechnique approach aimed at elucidating the neural mechanisms underlying memory impairments in aging and dementia. PMID:26843637

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.

Inferring action structure and causal relationships in continuous sequences of human action.

PubMed

Buchsbaum, Daphna; Griffiths, Thomas L; Plunkett, Dillon; Gopnik, Alison; Baldwin, Dare

2015-02-01

In the real world, causal variables do not come pre-identified or occur in isolation, but instead are embedded within a continuous temporal stream of events. A challenge faced by both human learners and machine learning algorithms is identifying subsequences that correspond to the appropriate variables for causal inference. A specific instance of this problem is action segmentation: dividing a sequence of observed behavior into meaningful actions, and determining which of those actions lead to effects in the world. Here we present a Bayesian analysis of how statistical and causal cues to segmentation should optimally be combined, as well as four experiments investigating human action segmentation and causal inference. We find that both people and our model are sensitive to statistical regularities and causal structure in continuous action, and are able to combine these sources of information in order to correctly infer both causal relationships and segmentation boundaries. Copyright © 2014. Published by Elsevier Inc.

RNA sequencing from neural ensembles activated during fear conditioning in the mouse temporal association cortex

PubMed Central

Cho, Jin-Hyung; Huang, Ben S.; Gray, Jesse M.

2016-01-01

The stable formation of remote fear memories is thought to require neuronal gene induction in cortical ensembles that are activated during learning. However, the set of genes expressed specifically in these activated ensembles is not known; knowledge of such transcriptional profiles may offer insights into the molecular program underlying stable memory formation. Here we use RNA-Seq to identify genes whose expression is enriched in activated cortical ensembles labeled during associative fear learning. We first establish that mouse temporal association cortex (TeA) is required for remote recall of auditory fear memories. We then perform RNA-Seq in TeA neurons that are labeled by the activity reporter Arc-dVenus during learning. We identify 944 genes with enriched expression in Arc-dVenus+ neurons. These genes include markers of L2/3, L5b, and L6 excitatory neurons but not glial or inhibitory markers, confirming Arc-dVenus to be an excitatory neuron-specific but non-layer-specific activity reporter. Cross comparisons to other transcriptional profiles show that 125 of the enriched genes are also activity-regulated in vitro or induced by visual stimulus in the visual cortex, suggesting that they may be induced generally in the cortex in an experience-dependent fashion. Prominent among the enriched genes are those encoding potassium channels that down-regulate neuronal activity, suggesting the possibility that part of the molecular program induced by fear conditioning may initiate homeostatic plasticity. PMID:27557751

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

PubMed

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

2015-01-01

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

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…

How actions shape perception: learning action-outcome relations and predicting sensory outcomes promote audio-visual temporal binding

PubMed Central

Desantis, Andrea; Haggard, Patrick

2016-01-01

To maintain a temporally-unified representation of audio and visual features of objects in our environment, the brain recalibrates audio-visual simultaneity. This process allows adjustment for both differences in time of transmission and time for processing of audio and visual signals. In four experiments, we show that the cognitive processes for controlling instrumental actions also have strong influence on audio-visual recalibration. Participants learned that right and left hand button-presses each produced a specific audio-visual stimulus. Following one action the audio preceded the visual stimulus, while for the other action audio lagged vision. In a subsequent test phase, left and right button-press generated either the same audio-visual stimulus as learned initially, or the pair associated with the other action. We observed recalibration of simultaneity only for previously-learned audio-visual outcomes. Thus, learning an action-outcome relation promotes temporal grouping of the audio and visual events within the outcome pair, contributing to the creation of a temporally unified multisensory object. This suggests that learning action-outcome relations and the prediction of perceptual outcomes can provide an integrative temporal structure for our experiences of external events. PMID:27982063

How actions shape perception: learning action-outcome relations and predicting sensory outcomes promote audio-visual temporal binding.

PubMed

Desantis, Andrea; Haggard, Patrick

2016-12-16

To maintain a temporally-unified representation of audio and visual features of objects in our environment, the brain recalibrates audio-visual simultaneity. This process allows adjustment for both differences in time of transmission and time for processing of audio and visual signals. In four experiments, we show that the cognitive processes for controlling instrumental actions also have strong influence on audio-visual recalibration. Participants learned that right and left hand button-presses each produced a specific audio-visual stimulus. Following one action the audio preceded the visual stimulus, while for the other action audio lagged vision. In a subsequent test phase, left and right button-press generated either the same audio-visual stimulus as learned initially, or the pair associated with the other action. We observed recalibration of simultaneity only for previously-learned audio-visual outcomes. Thus, learning an action-outcome relation promotes temporal grouping of the audio and visual events within the outcome pair, contributing to the creation of a temporally unified multisensory object. This suggests that learning action-outcome relations and the prediction of perceptual outcomes can provide an integrative temporal structure for our experiences of external events.

High resolution tempo-spatial ozone prediction with SVM and LSTM

NASA Astrophysics Data System (ADS)

Gao, D.; Zhang, Y.; Qu, Z.; Sadighi, K.; Coffey, E.; LIU, Q.; Hannigan, M.; Henze, D. K.; Dick, R.; Shang, L.; Lv, Q.

2017-12-01

To investigate and predict the exposure of ozone and other pollutants in urban areas, we utilize data from various infrastructures including EPA, NOAA and RIITS from government of Los Angeles and construct statistical models to conduct ozone concentration prediction in Los Angeles areas at finer spatial and temporal granularity. Our work involves cyber data such as traffic, roads and population data as features for prediction. Two statistical models, Support Vector Machine (SVM) and Long Short-term Memory (LSTM, deep learning method) are used for prediction. . Our experiments show that kernelized SVM gains better prediction performance when taking traffic counts, road density and population density as features, with a prediction RMSE of 7.99 ppb for all-time ozone and 6.92 ppb for peak-value ozone. With simulated NOx from Chemical Transport Model(CTM) as features, SVM generates even better prediction performance, with a prediction RMSE of 6.69ppb. We also build LSTM, which has shown great advantages at dealing with temporal sequences, to predict ozone concentration by treating ozone concentration as spatial-temporal sequences. Trained by ozone concentration measurements from the 13 EPA stations in LA area, the model achieves 4.45 ppb RMSE. Besides, we build a variant of this model which adds spatial dynamics into the model in the form of transition matrix that reveals new knowledge on pollutant transition. The forgetting gate of the trained LSTM is consistent with the delay effect of ozone concentration and the trained transition matrix shows spatial consistency with the common direction of winds in LA area.

Knowing what to respond in the future does not cancel the influence of past events.

PubMed

Tubau, Elisabet; López-Moliner, Joan

2009-05-29

Everyday tasks seldom involve isolate actions but sequences of them. We can see whether previous actions influence the current one by exploring the response time to controlled sequences of stimuli. Specifically, depending on the response-stimulus temporal interval (RSI), different mechanisms have been proposed to explain sequential effects in two-choice serial response tasks. Whereas an automatic facilitation mechanism is thought to produce a benefit for response repetitions at short RSIs, subjective expectancies are considered to replace the automatic facilitation at longer RSIs, producing a cost-benefit pattern: repetitions are faster after other repetitions but they are slower after alternations. However, there is not direct evidence showing the impact of subjective expectancies on sequential effects. By using a fixed sequence, the results of the reported experiment showed that the repetition effect was enhanced in participants who acquired complete knowledge of the order. Nevertheless, a similar cost-benefit pattern was observed in all participants and in all learning blocks. Therefore, results of the experiment suggest that sequential effects, including the cost-benefit pattern, are the consequence of automatic mechanisms which operate independently of (and simultaneously with) explicit knowledge of the sequence or other subjective expectancies.

Dance experience sculpts aesthetic perception and related brain circuits

PubMed Central

Kirsch, Louise P; Dawson, Kelvin; Cross, Emily S

2015-01-01

Previous research on aesthetic preferences demonstrates that people are more likely to judge a stimulus as pleasing if it is familiar. Although general familiarity and liking are related, it is less clear how motor familiarity, or embodiment, relates to a viewer's aesthetic appraisal. This study directly compared how learning to embody an action impacts the neural response when watching and aesthetically evaluating the same action. Twenty-two participants trained for 4 days on dance sequences. Each day they physically rehearsed one set of sequences, passively watched a second set, listened to the music of a third set, and a fourth set remained untrained. Functional MRI was obtained prior to and immediately following the training period, as were affective and physical ability ratings for each dance sequence. This approach enabled precise comparison of self-report methods of embodiment with nonbiased, empirical measures of action performance. Results suggest that after experience, participants most enjoy watching those dance sequences they danced or observed. Moreover, brain regions involved in mediating the aesthetic response shift from subcortical regions associated with dopaminergic reward processing to posterior temporal regions involved in processing multisensory integration, emotion, and biological motion. PMID:25773627

Event-related brain potentials in memory: correlates of episodic, semantic and implicit memory.

PubMed

Wieser, Stephan; Wieser, Heinz Gregor

2003-06-01

To study cognitive evoked potentials, recorded from scalp EEG and foramen ovale electrodes, during activation of explicit and implicit memory. The subgroups of explicit memory, episodic and semantic memory, are looked at separately. A word-learning task was used, which has been shown to activate hippocampus in H(2)(15)O positron emission tomography studies. Subjects had to study and remember word pairs using different learning strategies: (i) associative word learning (AWL), which activates the episodic memory, (ii) deep single word encoding (DSWE), which activates the semantic memory, and (iii) shallow single word encoding (SSWE), which activates the implicit memory and serves as a baseline. The test included the 'remember/know' paradigm as a behavioural learning control. During the task condition, a 10-20 scalp EEG with additional electrodes in both temporal lobes regions was recorded from 11 healthy volunteers. In one patient with mesiotemporal lobe epilepsy, the EEG was recorded from bilateral foramen ovale electrodes directly from mesial temporal lobe structures. Event-related potentials (ERPs) were calculated off-line and visual and statistical analyses were made. Associative learning strategy produced the best memory performance and the best noetic awareness experience, whereas shallow single word encoding produced the worst performance and the smallest noetic awareness. Deep single word encoding performance was in between. ERPs differed according to the test condition, during both encoding and retrieval, from both the scalp EEG and the foramen ovale electrode recordings. Encoding showed significant differences between the shallow single word encoding (SSWE), which is mainly a function of graphical characteristics, and the other two strategies, deep single word (DSWE) and associative learning (AWL), in which there is a semantic processing of the meaning. ERPs generated by these two categories, which are both functions of explicit memory, differed as well, indicating the presence or the absence of associative binding. Retrieval showed a significant test effect between the word pairs learned by association (AWL) and the ones learned by encoding the words in isolation of each other (DSWE and SSWE). The comparison of the ERPs generated by autonoetic awareness ('remember') and noetic awareness ('know') exhibited a significant test effect as well. The results of behavioural data, in particular that of the 'remember/know' procedure, are evidence that the task paradigm was efficient in activating different kinds of memory. Associative word learning generated a high degree of autonoetic awareness, which is a result of the episodic memory, whereas both kinds of single word learning generated less. AWL, DSWE and SSWE resulted in different electrophysiological correlates, both for encoding as well as retrieval, indicating that different brain structures were activated in different temporal sequence.

Tracing cell lineages in videos of lens-free microscopy.

PubMed

Rempfler, Markus; Stierle, Valentin; Ditzel, Konstantin; Kumar, Sanjeev; Paulitschke, Philipp; Andres, Bjoern; Menze, Bjoern H

2018-06-05

In vitro experiments with cultured cells are essential for studying their growth and migration pattern and thus, for gaining a better understanding of cancer progression and its treatment. Recent progress in lens-free microscopy (LFM) has rendered it an inexpensive tool for label-free, continuous live cell imaging, yet there is only little work on analysing such time-lapse image sequences. We propose (1) a cell detector for LFM images based on fully convolutional networks and residual learning, and (2) a probabilistic model based on moral lineage tracing that explicitly handles multiple detections and temporal successor hypotheses by clustering and tracking simultaneously. (3) We benchmark our method in terms of detection and tracking scores on a dataset of three annotated sequences of several hours of LFM, where we demonstrate our method to produce high quality lineages. (4) We evaluate its performance on a somewhat more challenging problem: estimating cell lineages from the LFM sequence as would be possible from a corresponding fluorescence microscopy sequence. We present experiments on 16 LFM sequences for which we acquired fluorescence microscopy in parallel and generated annotations from them. Finally, (5) we showcase our methods effectiveness for quantifying cell dynamics in an experiment with skin cancer cells. Copyright © 2018 Elsevier B.V. All rights reserved.

Arbitrary digital pulse sequence generator with delay-loop timing

NASA Astrophysics Data System (ADS)

Hošák, Radim; Ježek, Miroslav

2018-04-01

We propose an idea of an electronic multi-channel arbitrary digital sequence generator with temporal granularity equal to two clock cycles. We implement the generator with 32 channels using a low-cost ARM microcontroller and demonstrate its capability to produce temporal delays ranging from tens of nanoseconds to hundreds of seconds, with 24 ns timing granularity and linear scaling of delay with respect to the number of delay loop iterations. The generator is optionally synchronized with an external clock source to provide 100 ps jitter and overall sequence repeatability within the whole temporal range. The generator is fully programmable and able to produce digital sequences of high complexity. The concept of the generator can be implemented using different microcontrollers and applied for controlling of various optical, atomic, and nuclear physics measurement setups.

Increased fMRI Sensitivity at Equal Data Burden Using Averaged Shifted Echo Acquisition

PubMed Central

Witt, Suzanne T.; Warntjes, Marcel; Engström, Maria

2016-01-01

There is growing evidence as to the benefits of collecting BOLD fMRI data with increased sampling rates. However, many of the newly developed acquisition techniques developed to collect BOLD data with ultra-short TRs require hardware, software, and non-standard analytic pipelines that may not be accessible to all researchers. We propose to incorporate the method of shifted echo into a standard multi-slice, gradient echo EPI sequence to achieve a higher sampling rate with a TR of <1 s with acceptable spatial resolution. We further propose to incorporate temporal averaging of consecutively acquired EPI volumes to both ameliorate the reduced temporal signal-to-noise inherent in ultra-fast EPI sequences and reduce the data burden. BOLD data were collected from 11 healthy subjects performing a simple, event-related visual-motor task with four different EPI sequences: (1) reference EPI sequence with TR = 1440 ms, (2) shifted echo EPI sequence with TR = 700 ms, (3) shifted echo EPI sequence with every two consecutively acquired EPI volumes averaged and effective TR = 1400 ms, and (4) shifted echo EPI sequence with every four consecutively acquired EPI volumes averaged and effective TR = 2800 ms. Both the temporally averaged sequences exhibited increased temporal signal-to-noise over the shifted echo EPI sequence. The shifted echo sequence with every two EPI volumes averaged also had significantly increased BOLD signal change compared with the other three sequences, while the shifted echo sequence with every four EPI volumes averaged had significantly decreased BOLD signal change compared with the other three sequences. The results indicated that incorporating the method of shifted echo into a standard multi-slice EPI sequence is a viable method for achieving increased sampling rate for collecting event-related BOLD data. Further, consecutively averaging every two consecutively acquired EPI volumes significantly increased the measured BOLD signal change and the subsequently calculated activation map statistics. PMID:27932947

Student Mental Models of the Greenhouse Effect: Retention Months After Interventions

NASA Astrophysics Data System (ADS)

Harris, S. E.; Gold, A. U.

2013-12-01

Individual understanding of climate science, and the greenhouse effect in particular, is one factor important for societal decision-making. Ideally, learning opportunities about the greenhouse effect will not only move people toward expert-like ideas but will also have long-lasting effects for those individuals. We assessed university students' mental models of the greenhouse effect before and after specific learning experiences, on a final exam, then again a few months later. Our aim was to measure retention after students had not necessarily been thinking about, nor studying, the greenhouse effect recently. How sticky were the ideas learned? 164 students in an introductory science course participated in a sequence of two learning activities and assessments regarding the greenhouse effect. The first lesson involved the full class, then, for the second lesson, half the students completed a simulation-based activity and the other half completed a data-driven activity. We assessed student thinking through concept sketches, multiple choice and short answer questions. All students generated concept sketches four times, and completed a set of multiple choice (MCQs) and short answer questions twice. Later, 3-4 months after the course ended, 27 students ('retention students') completed an additional concept sketch and answered the questions again, as a retention assessment. These 27 students were nearly evenly split between the two contrasting second lessons in the sequence and included both high and low-achieving students. We then compared student sketches and scores to 'expert' answers. The general pattern over time showed a significant increase in student scores from before the lesson sequence to after, both on concept sketches and MCQs, then an additional increase in concept sketch score on the final exam (MCQs were not asked on the final exam). The scores for the retention students were not significantly different from the full class. Within the retention group, there was also no difference in scores based on which contrasting lesson a student did. Students in both of the contrasting lessons scored significantly higher on the retention test than on the initial pre-test. Their concept sketch scores on the retention test were slightly lower than their scores on the final exam (not significantly), but matched their post-lesson-sequence scores. Their MCQ scores were slightly higher on the retention test than on the post-lesson-sequence test (also not significantly). These results imply that students both learned and retained new ideas about the greenhouse effect for at least a few months after the end of the course and did not regress to their pre-lesson ideas. Further analysis should show which particular aspects of student mental models changed over the full temporal sequence.

Fast and slow spindles during the sleep slow oscillation: disparate coalescence and engagement in memory processing.

PubMed

Mölle, Matthias; Bergmann, Til O; Marshall, Lisa; Born, Jan

2011-10-01

Thalamo-cortical spindles driven by the up-state of neocortical slow (< 1 Hz) oscillations (SOs) represent a candidate mechanism of memory consolidation during sleep. We examined interactions between SOs and spindles in human slow wave sleep, focusing on the presumed existence of 2 kinds of spindles, i.e., slow frontocortical and fast centro-parietal spindles. Two experiments were performed in healthy humans (24.5 ± 0.9 y) investigating undisturbed sleep (Experiment I) and the effects of prior learning (word paired associates) vs. non-learning (Experiment II) on multichannel EEG recordings during sleep. Only fast spindles (12-15 Hz) were synchronized to the depolarizing SO up-state. Slow spindles (9-12 Hz) occurred preferentially at the transition into the SO down-state, i.e., during waning depolarization. Slow spindles also revealed a higher probability to follow rather than precede fast spindles. For sequences of individual SOs, fast spindle activity was largest for "initial" SOs, whereas SO amplitude and slow spindle activity were largest for succeeding SOs. Prior learning enhanced this pattern. The finding that fast and slow spindles occur at different times of the SO cycle points to disparate generating mechanisms for the 2 kinds of spindles. The reported temporal relationships during SO sequences suggest that fast spindles, driven by the SO up-state feed back to enhance the likelihood of succeeding SOs together with slow spindles. By enforcing such SO-spindle cycles, particularly after prior learning, fast spindles possibly play a key role in sleep-dependent memory processing.

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…

Temporally Coordinated Deep Brain Stimulation in the Dorsal and Ventral Striatum Synergistically Enhances Associative Learning.

PubMed

Katnani, Husam A; Patel, Shaun R; Kwon, Churl-Su; Abdel-Aziz, Samer; Gale, John T; Eskandar, Emad N

2016-01-04

The primate brain has the remarkable ability of mapping sensory stimuli into motor behaviors that can lead to positive outcomes. We have previously shown that during the reinforcement of visual-motor behavior, activity in the caudate nucleus is correlated with the rate of learning. Moreover, phasic microstimulation in the caudate during the reinforcement period was shown to enhance associative learning, demonstrating the importance of temporal specificity to manipulate learning related changes. Here we present evidence that extends upon our previous finding by demonstrating that temporally coordinated phasic deep brain stimulation across both the nucleus accumbens and caudate can further enhance associative learning. Monkeys performed a visual-motor associative learning task and received stimulation at time points critical to learning related changes. Resulting performance revealed an enhancement in the rate, ceiling, and reaction times of learning. Stimulation of each brain region alone or at different time points did not generate the same effect.

Temporal and Region-Specific Requirements of αCaMKII in Spatial and Contextual Learning

PubMed Central

Achterberg, Katharina G.; Buitendijk, Gabriëlle H.S.; Kool, Martijn J.; Goorden, Susanna M.I.; Post, Laura; Slump, Denise E.; Silva, Alcino J.; van Woerden, Geeske M.

2014-01-01

The α isoform of the calcium/calmodulin-dependent protein kinase II (αCaMKII) has been implicated extensively in molecular and cellular mechanisms underlying spatial and contextual learning in a wide variety of species. Germline deletion of Camk2a leads to severe deficits in spatial and contextual learning in mice. However, the temporal and region-specific requirements for αCaMKII have remained largely unexplored. Here, we generated conditional Camk2a mutants to examine the influence of spatially restricted and temporally controlled expression of αCaMKII. Forebrain-specific deletion of the Camk2a gene resulted in severe deficits in water maze and contextual fear learning, whereas mice with deletion restricted to the cerebellum learned normally. Furthermore, we found that temporally controlled deletion of the Camk2a gene in adult mice is as detrimental as germline deletion for learning and synaptic plasticity. Together, we confirm the requirement for αCaMKII in the forebrain, but not the cerebellum, in spatial and contextual learning. Moreover, we highlight the absolute requirement for intact αCaMKII expression at the time of learning. PMID:25143599

The role of RT carry-over for congruence sequence effects in masked priming.

PubMed

Huber-Huber, Christoph; Ansorge, Ulrich

2017-05-01

The present study disentangles 2 sources of the congruence sequence effect with masked primes: congruence and response time of the previous trial (reaction time [RT] carry-over). Using arrows as primes and targets and a metacontrast masking procedure we found congruence as well as congruence sequence effects. In addition, congruence sequence effects decreased when RT carry-over was accounted for in a mixed model analysis, suggesting that RT carry-over contributes to congruence sequence effects in masked priming. Crucially, effects of previous trial congruence were not cancelled out completely indicating that RT carry-over and previous trial congruence are 2 sources feeding into the congruence sequence effect. A secondary task requiring response speed judgments demonstrated general awareness of response speed (Experiments 1), but removing this secondary task (Experiment 2) showed that RT carry-over effects were also present in single-task conditions. During (dual-task) prime-awareness test parts of both experiments, however, RT carry-over failed to modulate congruence effects, suggesting that some task sets of the participants can prevent the effect. The basic RT carry-over effects are consistent with the conflict adaptation account, with the adaptation to the statistics of the environment (ASE) model, and possibly with the temporal learning explanation. Additionally considering the task-dependence of RT carry-over, the results are most compatible with the conflict adaptation account. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The Temporal Sequencing of Problem Gambling and Comorbid Disorders

ERIC Educational Resources Information Center

Holdsworth, Louise; Haw, John; Hing, Nerilee

2012-01-01

Two qualitative studies were undertaken to identify the prevalent comorbid mental disorders in treatment seeking problem gamblers and to also identify the temporal sequencing of the disorders. A forum with problem gambling counsellors and interviews with 24 mental health experts were undertaken. There was general agreement that the most commonly…

Advances in Temporal Analysis in Learning and Instruction

ERIC Educational Resources Information Center

Molenaar, Inge

2014-01-01

This paper focuses on a trend to analyse temporal characteristics of constructs important to learning and instruction. Different researchers have indicated that we should pay more attention to time in our research to enhance explanatory power and increase validity. Constructs formerly viewed as personal traits, such as self-regulated learning and…

Event-related potentials in response to violations of content and temporal event knowledge.

PubMed

Drummer, Janna; van der Meer, Elke; Schaadt, Gesa

2016-01-08

Scripts that store knowledge of everyday events are fundamentally important for managing daily routines. Content event knowledge (i.e., knowledge about which events belong to a script) and temporal event knowledge (i.e., knowledge about the chronological order of events in a script) constitute qualitatively different forms of knowledge. However, there is limited information about each distinct process and the time course involved in accessing content and temporal event knowledge. Therefore, we analyzed event-related potentials (ERPs) in response to either correctly presented event sequences or event sequences that contained a content or temporal error. We found an N400, which was followed by a posteriorly distributed P600 in response to content errors in event sequences. By contrast, we did not find an N400 but an anteriorly distributed P600 in response to temporal errors in event sequences. Thus, the N400 seems to be elicited as a response to a general mismatch between an event and the established event model. We assume that the expectancy violation of content event knowledge, as indicated by the N400, induces the collapse of the established event model, a process indicated by the posterior P600. The expectancy violation of temporal event knowledge is assumed to induce an attempt to reorganize the event model in working memory, a process indicated by the frontal P600. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural correlates of skill acquisition: decreased cortical activity during a serial interception sequence learning task.

PubMed

Gobel, Eric W; Parrish, Todd B; Reber, Paul J

2011-10-15

Learning of complex motor skills requires learning of component movements as well as the sequential structure of their order and timing. Using a Serial Interception Sequence Learning (SISL) task, participants learned a sequence of precisely timed interception responses through training with a repeating sequence. Following initial implicit learning of the repeating sequence, functional MRI data were collected during performance of that known sequence and compared with activity evoked during novel sequences of actions, novel timing patterns, or both. Reduced activity was observed during the practiced sequence in a distributed bilateral network including extrastriate occipital, parietal, and premotor cortical regions. These reductions in evoked activity likely reflect improved efficiency in visuospatial processing, spatio-motor integration, motor planning, and motor execution for the trained sequence, which is likely supported by nondeclarative skill learning. In addition, the practiced sequence evoked increased activity in the left ventral striatum and medial prefrontal cortex, while the posterior cingulate was more active during periods of better performance. Many prior studies of perceptual-motor skill learning have found increased activity in motor areas of the frontal cortex (e.g., motor and premotor cortex, SMA) and striatal areas (e.g., the putamen). The change in activity observed here (i.e., decreased activity across a cortical network) may reflect skill learning that is predominantly expressed through more accurate performance rather than decreased reaction time. Copyright © 2011 Elsevier Inc. All rights reserved.

Neural Correlates of Skill Acquisition: Decreased Cortical Activity During a Serial Interception Sequence Learning Task

PubMed Central

Gobel, Eric W.; Parrish, Todd B.; Reber, Paul J.

2011-01-01

Learning of complex motor skills requires learning of component movements as well as the sequential structure of their order and timing. Using a Serial Interception Sequence Learning (SISL) task, participants learned a sequence of precisely timed interception responses through training with a repeating sequence. Following initial implicit learning of the repeating sequence, functional MRI data were collected during performance of that known sequence and compared with activity evoked during novel sequences of actions, novel timing patterns, or both. Reduced activity was observed during the practiced sequence in a distributed bilateral network including extrastriate occipital, parietal, and premotor cortical regions. These reductions in evoked activity likely reflect improved efficiency in visuospatial processing, spatio-motor integration, motor planning, and motor execution for the trained sequence, which is likely supported by nondeclarative skill learning. In addition, the practiced sequence evoked increased activity in the left ventral striatum and medial prefrontal cortex, while the posterior cingulate was more active during periods of better performance. Many prior studies of perceptual-motor skill learning have found increased activity in motor areas of frontal cortex (e.g., motor and premotor cortex, SMA) and striatal areas (e.g., the putamen). The change in activity observed here (i.e., decreased activity across a cortical network) may reflect skill learning that is predominantly expressed through more accurate performance rather than decreased reaction time. PMID:21771663

Sequence learning in Parkinson's disease: Focusing on action dynamics and the role of dopaminergic medication.

PubMed

Ruitenberg, Marit F L; Duthoo, Wout; Santens, Patrick; Seidler, Rachael D; Notebaert, Wim; Abrahamse, Elger L

2016-12-01

Previous studies on movement sequence learning in Parkinson's disease (PD) have produced mixed results. A possible explanation for the inconsistent findings is that some studies have taken dopaminergic medication into account while others have not. Additionally, in previous studies the response modalities did not allow for an investigation of the action dynamics of sequential movements as they unfold over time. In the current study we investigated sequence learning in PD by specifically considering the role of medication status in a sequence learning task where mouse movements were performed. The focus on mouse movements allowed us to examine the action dynamics of sequential movement in terms of initiation time, movement time, movement accuracy, and velocity. PD patients performed the sequence learning task once on their regular medication, and once after overnight withdrawal from their medication. Results showed that sequence learning as reflected in initiation times was impaired when PD patients performed the task ON medication compared to OFF medication. In contrast, sequence learning as reflected in the accuracy of movement trajectories was enhanced when performing the task ON compared to OFF medication. Our findings suggest that while medication enhances execution processes of movement sequence learning, it may at the same time impair planning processes that precede actual execution. Overall, the current study extends earlier findings on movement sequence learning in PD by differentiating between various components of performance, and further refines previous dopamine overdose effects in sequence learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Influence of Cognitive Functioning on Age-Related Performance Declines in Visuospatial Sequence Learning.

PubMed

Krüger, Melanie; Hinder, Mark R; Puri, Rohan; Summers, Jeffery J

2017-01-01

Objectives: The aim of this study was to investigate how age-related performance differences in a visuospatial sequence learning task relate to age-related declines in cognitive functioning. Method: Cognitive functioning of 18 younger and 18 older participants was assessed using a standardized test battery. Participants then undertook a perceptual visuospatial sequence learning task. Various relationships between sequence learning and participants' cognitive functioning were examined through correlation and factor analysis. Results: Older participants exhibited significantly lower performance than their younger counterparts in the sequence learning task as well as in multiple cognitive functions. Factor analysis revealed two independent subsets of cognitive functions associated with performance in the sequence learning task, related to either the processing and storage of sequence information (first subset) or problem solving (second subset). Age-related declines were only found for the first subset of cognitive functions, which also explained a significant degree of the performance differences in the sequence learning task between age-groups. Discussion: The results suggest that age-related performance differences in perceptual visuospatial sequence learning can be explained by declines in the ability to process and store sequence information in older adults, while a set of cognitive functions related to problem solving mediates performance differences independent of age.

Capturing the Temporal Sequence of Interaction in Young Siblings

PubMed Central

Steele, Fiona; Jenkins, Jennifer

2015-01-01

We explored whether young children exhibit subtypes of behavioral sequences during sibling interaction. Ten-minute, free-play observations of over 300 sibling dyads were coded for positivity, negativity and disengagement. The data were analyzed using growth mixture modeling (GMM). Younger (18-month-old) children’s temporal behavioral sequences showed a harmonious (53%) and a casual (47%) class. Older (approximately four-year-old) children’s behavior was more differentiated revealing a harmonious (25%), a deteriorating (31%), a recovery (22%) and a casual (22%) class. A more positive maternal affective climate was associated with more positive patterns. Siblings’ sequential behavioral patterns tended to be complementary rather than reciprocal in nature. The study illustrates a novel use of GMM and makes a theoretical contribution by showing that young children exhibit distinct types of temporal behavioral sequences that are related to parenting processes. PMID:25996957

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…

Neural Encoding and Integration of Learned Probabilistic Sequences in Avian Sensory-Motor Circuitry

PubMed Central

Brainard, Michael S.

2013-01-01

Many complex behaviors, such as human speech and birdsong, reflect a set of categorical actions that can be flexibly organized into variable sequences. However, little is known about how the brain encodes the probabilities of such sequences. Behavioral sequences are typically characterized by the probability of transitioning from a given action to any subsequent action (which we term “divergence probability”). In contrast, we hypothesized that neural circuits might encode the probability of transitioning to a given action from any preceding action (which we term “convergence probability”). The convergence probability of repeatedly experienced sequences could naturally become encoded by Hebbian plasticity operating on the patterns of neural activity associated with those sequences. To determine whether convergence probability is encoded in the nervous system, we investigated how auditory-motor neurons in vocal premotor nucleus HVC of songbirds encode different probabilistic characterizations of produced syllable sequences. We recorded responses to auditory playback of pseudorandomly sequenced syllables from the bird's repertoire, and found that variations in responses to a given syllable could be explained by a positive linear dependence on the convergence probability of preceding sequences. Furthermore, convergence probability accounted for more response variation than other probabilistic characterizations, including divergence probability. Finally, we found that responses integrated over >7–10 syllables (∼700–1000 ms) with the sign, gain, and temporal extent of integration depending on convergence probability. Our results demonstrate that convergence probability is encoded in sensory-motor circuitry of the song-system, and suggest that encoding of convergence probability is a general feature of sensory-motor circuits. PMID:24198363

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.

Temporal Issues in the Design of Virtual Learning Environments.

ERIC Educational Resources Information Center

Bergeron, Bryan; Obeid, Jihad

1995-01-01

Describes design methods used to influence user perception of time in virtual learning environments. Examines the use of temporal cues in medical education and clinical competence testing. Finds that user perceptions of time affects user acceptance, ease of use, and the level of realism of a virtual learning environment. Contains 51 references.…

The Chronotron: A Neuron That Learns to Fire Temporally Precise Spike Patterns

PubMed Central

Florian, Răzvan V.

2012-01-01

In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons), one that provides high memory capacity (E-learning), and one that has a higher biological plausibility (I-learning). With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm. PMID:22879876

Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data.

PubMed Central

Drummond, Alexei J; Nicholls, Geoff K; Rodrigo, Allen G; Solomon, Wiremu

2002-01-01

Molecular sequences obtained at different sampling times from populations of rapidly evolving pathogens and from ancient subfossil and fossil sources are increasingly available with modern sequencing technology. Here, we present a Bayesian statistical inference approach to the joint estimation of mutation rate and population size that incorporates the uncertainty in the genealogy of such temporally spaced sequences by using Markov chain Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the time structure of the ancestral tree. We recover information about the unknown true ancestral coalescent tree, population size, and the overall mutation rate from temporally spaced data, that is, from nucleotide sequences gathered at different times, from different individuals, in an evolving haploid population. We briefly discuss the methodological implications and show what can be inferred, in various practically relevant states of prior knowledge. We develop extensions for exponentially growing population size and joint estimation of substitution model parameters. We illustrate some of the important features of this approach on a genealogy of HIV-1 envelope (env) partial sequences. PMID:12136032

Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data.

PubMed

Drummond, Alexei J; Nicholls, Geoff K; Rodrigo, Allen G; Solomon, Wiremu

2002-07-01

Molecular sequences obtained at different sampling times from populations of rapidly evolving pathogens and from ancient subfossil and fossil sources are increasingly available with modern sequencing technology. Here, we present a Bayesian statistical inference approach to the joint estimation of mutation rate and population size that incorporates the uncertainty in the genealogy of such temporally spaced sequences by using Markov chain Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the time structure of the ancestral tree. We recover information about the unknown true ancestral coalescent tree, population size, and the overall mutation rate from temporally spaced data, that is, from nucleotide sequences gathered at different times, from different individuals, in an evolving haploid population. We briefly discuss the methodological implications and show what can be inferred, in various practically relevant states of prior knowledge. We develop extensions for exponentially growing population size and joint estimation of substitution model parameters. We illustrate some of the important features of this approach on a genealogy of HIV-1 envelope (env) partial sequences.

Sooner Versus Later: Factors Associated with Temporal Sequencing of Suicide

ERIC Educational Resources Information Center

Kaplan, Mark S.; McFarland, Bentson H.; Huguet, Nathalie; Newsom, Jason T.

2006-01-01

There are few (if any) population-based prospective studies that provide information on factors associated with temporal sequencing of suicide. In this prospective population-based study, the National Health Interview Survey (NHIS), 1986-1994, was linked to the National Death Index (NDI), 1986-1997, to assess factors that predict recent (within 12…

Influenza A virus evolution and spatio-temporal dynamics in Eurasian wild birds: a phylogenetic and phylogeographical study of whole-genome sequence data

PubMed Central

Lewis, Nicola S.; Verhagen, Josanne H.; Javakhishvili, Zurab; Russell, Colin A.; Lexmond, Pascal; Westgeest, Kim B.; Bestebroer, Theo M.; Halpin, Rebecca A.; Lin, Xudong; Ransier, Amy; Fedorova, Nadia B.; Stockwell, Timothy B.; Latorre-Margalef, Neus; Olsen, Björn; Smith, Gavin; Bahl, Justin; Wentworth, David E.; Waldenström, Jonas; Fouchier, Ron A. M.

2015-01-01

Low pathogenic avian influenza A viruses (IAVs) have a natural host reservoir in wild waterbirds and the potential to spread to other host species. Here, we investigated the evolutionary, spatial and temporal dynamics of avian IAVs in Eurasian wild birds. We used whole-genome sequences collected as part of an intensive long-term Eurasian wild bird surveillance study, and combined this genetic data with temporal and spatial information to explore the virus evolutionary dynamics. Frequent reassortment and co-circulating lineages were observed for all eight genomic RNA segments over time. There was no apparent species-specific effect on the diversity of the avian IAVs. There was a spatial and temporal relationship between the Eurasian sequences and significant viral migration of avian IAVs from West Eurasia towards Central Eurasia. The observed viral migration patterns differed between segments. Furthermore, we discuss the challenges faced when analysing these surveillance and sequence data, and the caveats to be borne in mind when drawing conclusions from the apparent results of such analyses. PMID:25904147

Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic Focus.

PubMed

Fan Du; Shneiderman, Ben; Plaisant, Catherine; Malik, Sana; Perer, Adam

2017-06-01

The growing volume and variety of data presents both opportunities and challenges for visual analytics. Addressing these challenges is needed for big data to provide valuable insights and novel solutions for business, security, social media, and healthcare. In the case of temporal event sequence analytics it is the number of events in the data and variety of temporal sequence patterns that challenges users of visual analytic tools. This paper describes 15 strategies for sharpening analytic focus that analysts can use to reduce the data volume and pattern variety. Four groups of strategies are proposed: (1) extraction strategies, (2) temporal folding, (3) pattern simplification strategies, and (4) iterative strategies. For each strategy, we provide examples of the use and impact of this strategy on volume and/or variety. Examples are selected from 20 case studies gathered from either our own work, the literature, or based on email interviews with individuals who conducted the analyses and developers who observed analysts using the tools. Finally, we discuss how these strategies might be combined and report on the feedback from 10 senior event sequence analysts.

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…

Temporal and Motor Representation of Rhythm in Fronto-Parietal Cortical Areas: An fMRI Study

PubMed Central

Konoike, Naho; Kotozaki, Yuka; Jeong, Hyeonjeong; Miyazaki, Atsuko; Sakaki, Kohei; Shinada, Takamitsu; Sugiura, Motoaki; Kawashima, Ryuta; Nakamura, Katsuki

2015-01-01

When sounds occur with temporally structured patterns, we can feel a rhythm. To memorize a rhythm, perception of its temporal patterns and organization of them into a hierarchically structured sequence are necessary. On the other hand, rhythm perception can often cause unintentional body movements. Thus, we hypothesized that rhythm information can be manifested in two different ways; temporal and motor representations. The motor representation depends on effectors, such as the finger or foot, whereas the temporal representation is effector-independent. We tested our hypothesis with a working memory paradigm to elucidate neuronal correlates of temporal or motor representation of rhythm and to reveal the neural networks associated with these representations. We measured brain activity by fMRI while participants memorized rhythms and reproduced them by tapping with the right finger, left finger, or foot, or by articulation. The right inferior frontal gyrus and the inferior parietal lobule exhibited significant effector-independent activations during encoding and retrieval of rhythm information, whereas the left inferior parietal lobule and supplementary motor area (SMA) showed effector-dependent activations during retrieval. These results suggest that temporal sequences of rhythm are probably represented in the right fronto-parietal network, whereas motor sequences of rhythm can be represented in the SMA-parietal network. PMID:26076024

Kernel Temporal Differences for Neural Decoding

PubMed Central

Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2015-01-01

We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces. PMID:25866504

Denoising Algorithm for CFA Image Sensors Considering Inter-Channel Correlation.

PubMed

Lee, Min Seok; Park, Sang Wook; Kang, Moon Gi

2017-05-28

In this paper, a spatio-spectral-temporal filter considering an inter-channel correlation is proposed for the denoising of a color filter array (CFA) sequence acquired by CCD/CMOS image sensors. Owing to the alternating under-sampled grid of the CFA pattern, the inter-channel correlation must be considered in the direct denoising process. The proposed filter is applied in the spatial, spectral, and temporal domain, considering the spatio-tempo-spectral correlation. First, nonlocal means (NLM) spatial filtering with patch-based difference (PBD) refinement is performed by considering both the intra-channel correlation and inter-channel correlation to overcome the spatial resolution degradation occurring with the alternating under-sampled pattern. Second, a motion-compensated temporal filter that employs inter-channel correlated motion estimation and compensation is proposed to remove the noise in the temporal domain. Then, a motion adaptive detection value controls the ratio of the spatial filter and the temporal filter. The denoised CFA sequence can thus be obtained without motion artifacts. Experimental results for both simulated and real CFA sequences are presented with visual and numerical comparisons to several state-of-the-art denoising methods combined with a demosaicing method. Experimental results confirmed that the proposed frameworks outperformed the other techniques in terms of the objective criteria and subjective visual perception in CFA sequences.

A hypothetical universal model of cerebellar function: reconsideration of the current dogma.

PubMed

Magal, Ari

2013-10-01

The cerebellum is commonly studied in the context of the classical eyeblink conditioning model, which attributes an adaptive motor function to cerebellar learning processes. This model of cerebellar function has quite a few shortcomings and may in fact be somewhat deficient in explaining the myriad functions attributed to the cerebellum, functions ranging from motor sequencing to emotion and cognition. The involvement of the cerebellum in these motor and non-motor functions has been demonstrated in both animals and humans in electrophysiological, behavioral, tracing, functional neuroimaging, and PET studies, as well as in clinical human case studies. A closer look at the cerebellum's evolutionary origin provides a clue to its underlying purpose as a tool which evolved to aid predation rather than as a tool for protection. Based upon this evidence, an alternative model of cerebellar function is proposed, one which might more comprehensively account both for the cerebellum's involvement in a myriad of motor, affective, and cognitive functions and for the relative simplicity and ubiquitous repetitiveness of its circuitry. This alternative model suggests that the cerebellum has the ability to detect coincidences of events, be they sensory, motor, affective, or cognitive in nature, and, after having learned to associate these, it can then trigger (or "mirror") these events after having temporally adjusted their onset based on positive/negative reinforcement. The model also provides for the cerebellum's direction of the proper and uninterrupted sequence of events resulting from this learning through the inhibition of efferent structures (as demonstrated in our lab).

Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations

PubMed Central

Wei, Yina; Krishnan, Giri P.

2016-01-01

Sleep is critical for regulation of synaptic efficacy, memories, and learning. However, the underlying mechanisms of how sleep rhythms contribute to consolidating memories acquired during wakefulness remain unclear. Here we studied the role of slow oscillations, 0.2–1 Hz rhythmic transitions between Up and Down states during stage 3/4 sleep, on dynamics of synaptic connectivity in the thalamocortical network model implementing spike-timing-dependent synaptic plasticity. We found that the spatiotemporal pattern of Up-state propagation determines the changes of synaptic strengths between neurons. Furthermore, an external input, mimicking hippocampal ripples, delivered to the cortical network results in input-specific changes of synaptic weights, which persisted after stimulation was removed. These synaptic changes promoted replay of specific firing sequences of the cortical neurons. Our study proposes a neuronal mechanism on how an interaction between hippocampal input, such as mediated by sharp wave-ripple events, cortical slow oscillations, and synaptic plasticity, may lead to consolidation of memories through preferential replay of cortical cell spike sequences during slow-wave sleep. SIGNIFICANCE STATEMENT Sleep is critical for memory and learning. Replay during sleep of temporally ordered spike sequences related to a recent experience was proposed to be a neuronal substrate of memory consolidation. However, specific mechanisms of replay or how spike sequence replay leads to synaptic changes that underlie memory consolidation are still poorly understood. Here we used a detailed computational model of the thalamocortical system to report that interaction between slow cortical oscillations and synaptic plasticity during deep sleep can underlie mapping hippocampal memory traces to persistent cortical representation. This study provided, for the first time, a mechanistic explanation of how slow-wave sleep may promote consolidation of recent memory events. PMID:27076422

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

A system for learning statistical motion patterns.

PubMed

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

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…

Performing the unexplainable: Implicit task performance reveals individually reliable sequence learning without explicit knowledge

PubMed Central

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

2015-01-01

Memory-impaired patients express intact implicit perceptual–motor sequence learning, but it has been difficult to obtain a similarly clear dissociation in healthy participants. When explicit memory is intact, participants acquire some explicit knowledge and performance improvements from implicit learning may be subtle. Therefore, it is difficult to determine whether performance exceeds what could be expected on the basis of the concomitant explicit knowledge. Using a challenging new sequence-learning task, robust implicit learning was found in healthy participants with virtually no associated explicit knowledge. Participants trained on a repeating sequence that was selected randomly from a set of five. On a performance test of all five sequences, performance was best on the trained sequence, and two-thirds of the participants exhibited individually reliable improvement (by chi-square analysis). Participants could not reliably indicate which sequence had been trained by either recognition or recall. Only by expressing their knowledge via performance were participants able to indicate which sequence they had learned. PMID:21169570

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

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 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.

Impacts of visuomotor sequence learning methods on speed and accuracy: Starting over from the beginning or from the point of error.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2016-02-01

The present study examined whether sequence learning led to more accurate and shorter performance time if people who are learning a sequence start over from the beginning when they make an error (i.e., practice the whole sequence) or only from the point of error (i.e., practice a part of the sequence). We used a visuomotor sequence learning paradigm with a trial-and-error procedure. In Experiment 1, we found fewer errors, and shorter performance time for those who restarted their performance from the beginning of the sequence as compared to those who restarted from the point at which an error occurred, indicating better learning of spatial and motor representations of the sequence. This might be because the learned elements were repeated when the next performance started over from the beginning. In subsequent experiments, we increased the occasions for the repetitions of learned elements by modulating the number of fresh start points in the sequence after errors. The results showed that fewer fresh start points were likely to lead to fewer errors and shorter performance time, indicating that the repetitions of learned elements enabled participants to develop stronger spatial and motor representations of the sequence. Thus, a single or two fresh start points in the sequence (i.e., starting over only from the beginning or from the beginning or midpoint of the sequence after errors) is likely to lead to more accurate and faster performance. Copyright © 2016 Elsevier B.V. All rights reserved.

Lessons Learned from Dependency Usage in HERA: Implications for THERP-Related HRA Methods

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

April M. Whaley; Ronald L. Boring; Harold S. Blackman

Dependency occurs when the probability of success or failure on one action changes the probability of success or failure on a subsequent action. Dependency may serve as a modifier on the human error probabilities (HEPs) for successive actions in human reliability analysis (HRA) models. Discretion should be employed when determining whether or not a dependency calculation is warranted: dependency should not be assigned without strongly grounded reasons. Human reliability analysts may sometimes assign dependency in cases where it is unwarranted. This inappropriate assignment is attributed to a lack of clear guidance to encompass the range of scenarios human reliability analystsmore » are addressing. Inappropriate assignment of dependency produces inappropriately elevated HEP values. Lessons learned about dependency usage in the Human Event Repository and Analysis (HERA) system may provide clarification and guidance for analysts using first-generation HRA methods. This paper presents the HERA approach to dependency assessment and discusses considerations for dependency usage in HRA, including the cognitive basis for dependency, direction for determining when dependency should be assessed, considerations for determining the dependency level, temporal issues to consider when assessing dependency, (e.g., considering task sequence versus overall event sequence, and dependency over long periods of time), and diagnosis and action influences on dependency.« less

Circuit mechanisms of hippocampal reactivation during sleep.

PubMed

Malerba, Paola; Bazhenov, Maxim

2018-05-01

The hippocampus is important for memory and learning, being a brain site where initial memories are formed and where sharp wave - ripples (SWR) are found, which are responsible for mapping recent memories to long-term storage during sleep-related memory replay. While this conceptual schema is well established, specific intrinsic and network-level mechanisms driving spatio-temporal patterns of hippocampal activity during sleep, and specifically controlling off-line memory reactivation are unknown. In this study, we discuss a model of hippocampal CA1-CA3 network generating spontaneous characteristic SWR activity. Our study predicts the properties of CA3 input which are necessary for successful CA1 ripple generation and the role of synaptic interactions and intrinsic excitability in spike sequence replay during SWRs. Specifically, we found that excitatory synaptic connections promote reactivation in both CA3 and CA1, but the different dynamics of sharp waves in CA3 and ripples in CA1 result in a differential role for synaptic inhibition in modulating replay: promoting spike sequence specificity in CA3 but not in CA1 areas. Finally, we describe how awake learning of spatial trajectories leads to synaptic changes sufficient to drive hippocampal cells' reactivation during sleep, as required for sleep-related memory consolidation. Copyright © 2018 Elsevier Inc. All rights reserved.

Learning and disrupting invariance in visual recognition with a temporal association rule

PubMed Central

Isik, Leyla; Leibo, Joel Z.; Poggio, Tomaso

2012-01-01

Learning by temporal association rules such as Foldiak's trace rule is an attractive hypothesis that explains the development of invariance in visual recognition. Consistent with these rules, several recent experiments have shown that invariance can be broken at both the psychophysical and single cell levels. We show (1) that temporal association learning provides appropriate invariance in models of object recognition inspired by the visual cortex, (2) that we can replicate the “invariance disruption” experiments using these models with a temporal association learning rule to develop and maintain invariance, and (3) that despite dramatic single cell effects, a population of cells is very robust to these disruptions. We argue that these models account for the stability of perceptual invariance despite the underlying plasticity of the system, the variability of the visual world and expected noise in the biological mechanisms. PMID:22754523

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

Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks.

PubMed

Hefron, Ryan; Borghetti, Brett; Schubert Kabban, Christine; Christensen, James; Estepp, Justin

2018-04-26

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three important contributions: (1) The performance of ensembles of individually-trained models is statistically indistinguishable from group-trained methods at most sequence lengths. These ensembles can be trained for a fraction of the computational cost compared to group-trained methods and enable simpler model updates. (2) While increasing temporal sequence length improves mean accuracy, it is not sufficient to overcome distributional dissimilarities between individuals’ EEG data, as it results in statistically significant increases in cross-participant variance. (3) Compared to all other networks evaluated, a novel convolutional-recurrent model using multi-path subnetworks and bi-directional, residual recurrent layers resulted in statistically significant increases in predictive accuracy and decreases in cross-participant variance.

Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks

PubMed Central

Hefron, Ryan; Borghetti, Brett; Schubert Kabban, Christine; Christensen, James; Estepp, Justin

2018-01-01

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three important contributions: (1) The performance of ensembles of individually-trained models is statistically indistinguishable from group-trained methods at most sequence lengths. These ensembles can be trained for a fraction of the computational cost compared to group-trained methods and enable simpler model updates. (2) While increasing temporal sequence length improves mean accuracy, it is not sufficient to overcome distributional dissimilarities between individuals’ EEG data, as it results in statistically significant increases in cross-participant variance. (3) Compared to all other networks evaluated, a novel convolutional-recurrent model using multi-path subnetworks and bi-directional, residual recurrent layers resulted in statistically significant increases in predictive accuracy and decreases in cross-participant variance. PMID:29701668

Temporal Sequence of Hemispheric Network Activation during Semantic Processing: A Functional Network Connectivity Analysis

ERIC Educational Resources Information Center

Assaf, Michal; Jagannathan, Kanchana; Calhoun, Vince; Kraut, Michael; Hart, John, Jr.; Pearlson, Godfrey

2009-01-01

To explore the temporal sequence of, and the relationship between, the left and right hemispheres (LH and RH) during semantic memory (SM) processing we identified the neural networks involved in the performance of functional MRI semantic object retrieval task (SORT) using group independent component analysis (ICA) in 47 healthy individuals. SORT…

Behavioral and Single-Neuron Sensitivity to Millisecond Variations in Temporally Patterned Communication Signals

PubMed Central

Baker, Christa A.; Ma, Lisa; Casareale, Chelsea R.

2016-01-01

In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8–12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. SIGNIFICANCE STATEMENT The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals. PMID:27559179

Behavioral and Single-Neuron Sensitivity to Millisecond Variations in Temporally Patterned Communication Signals.

PubMed

Baker, Christa A; Ma, Lisa; Casareale, Chelsea R; Carlson, Bruce A

2016-08-24

In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8-12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals. Copyright © 2016 the authors 0270-6474/16/368985-16$15.00/0.

Physical fitness modulates incidental but not intentional statistical learning of simultaneous auditory sequences during concurrent physical exercise.

PubMed

Daikoku, Tatsuya; Takahashi, Yuji; Futagami, Hiroko; Tarumoto, Nagayoshi; Yasuda, Hideki

2017-02-01

In real-world auditory environments, humans are exposed to overlapping auditory information such as those made by human voices and musical instruments even during routine physical activities such as walking and cycling. The present study investigated how concurrent physical exercise affects performance of incidental and intentional learning of overlapping auditory streams, and whether physical fitness modulates the performances of learning. Participants were grouped with 11 participants with lower and higher fitness each, based on their Vo 2 max value. They were presented simultaneous auditory sequences with a distinct statistical regularity each other (i.e. statistical learning), while they were pedaling on the bike and seating on a bike at rest. In experiment 1, they were instructed to attend to one of the two sequences and ignore to the other sequence. In experiment 2, they were instructed to attend to both of the two sequences. After exposure to the sequences, learning effects were evaluated by familiarity test. In the experiment 1, performance of statistical learning of ignored sequences during concurrent pedaling could be higher in the participants with high than low physical fitness, whereas in attended sequence, there was no significant difference in performance of statistical learning between high than low physical fitness. Furthermore, there was no significant effect of physical fitness on learning while resting. In the experiment 2, the both participants with high and low physical fitness could perform intentional statistical learning of two simultaneous sequences in the both exercise and rest sessions. The improvement in physical fitness might facilitate incidental but not intentional statistical learning of simultaneous auditory sequences during concurrent physical exercise.

Multivariate temporal dictionary learning for EEG.

PubMed

Barthélemy, Q; Gouy-Pailler, C; Isaac, Y; Souloumiac, A; Larue, A; Mars, J I

2013-04-30

This article addresses the issue of representing electroencephalographic (EEG) signals in an efficient way. While classical approaches use a fixed Gabor dictionary to analyze EEG signals, this article proposes a data-driven method to obtain an adapted dictionary. To reach an efficient dictionary learning, appropriate spatial and temporal modeling is required. Inter-channels links are taken into account in the spatial multivariate model, and shift-invariance is used for the temporal model. Multivariate learned kernels are informative (a few atoms code plentiful energy) and interpretable (the atoms can have a physiological meaning). Using real EEG data, the proposed method is shown to outperform the classical multichannel matching pursuit used with a Gabor dictionary, as measured by the representative power of the learned dictionary and its spatial flexibility. Moreover, dictionary learning can capture interpretable patterns: this ability is illustrated on real data, learning a P300 evoked potential. Copyright © 2013 Elsevier B.V. All rights reserved.

Time to rethink the neural mechanisms of learning and memory

PubMed Central

Gallistel, Charles R.; Balsam, Peter D

2014-01-01

Most studies in the neurobiology of learning assume that the underlying learning process is a pairing – dependent change in synaptic strength that requires repeated experience of events presented in close temporal contiguity. However, much learning is rapid and does not depend on temporal contiguity which has never been precisely defined. These points are well illustrated by studies showing that temporal relationships between events are rapidly learned-even over long delays- and this knowledge governs the form and timing of behavior. The speed with which anticipatory responses emerge in conditioning paradigms is determined by the information that cues provide about the timing of rewards. The challenge for understanding the neurobiology of learning is to understand the mechanisms in the nervous system that encode information from even a single experience, the nature of the memory mechanisms that can encode quantities such as time, and how the brain can flexibly perform computations based on this information. PMID:24309167

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.

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.

Fast and Slow Spindles during the Sleep Slow Oscillation: Disparate Coalescence and Engagement in Memory Processing

PubMed Central

Mölle, Matthias; Bergmann, Til O.; Marshall, Lisa; Born, Jan

2011-01-01

Study Objectives: Thalamo-cortical spindles driven by the up-state of neocortical slow (< 1 Hz) oscillations (SOs) represent a candidate mechanism of memory consolidation during sleep. We examined interactions between SOs and spindles in human slow wave sleep, focusing on the presumed existence of 2 kinds of spindles, i.e., slow frontocortical and fast centro-parietal spindles. Design: Two experiments were performed in healthy humans (24.5 ± 0.9 y) investigating undisturbed sleep (Experiment I) and the effects of prior learning (word paired associates) vs. non-learning (Experiment II) on multichannel EEG recordings during sleep. Measurements and Results: Only fast spindles (12-15 Hz) were synchronized to the depolarizing SO up-state. Slow spindles (9-12 Hz) occurred preferentially at the transition into the SO down-state, i.e., during waning depolarization. Slow spindles also revealed a higher probability to follow rather than precede fast spindles. For sequences of individual SOs, fast spindle activity was largest for “initial” SOs, whereas SO amplitude and slow spindle activity were largest for succeeding SOs. Prior learning enhanced this pattern. Conclusions: The finding that fast and slow spindles occur at different times of the SO cycle points to disparate generating mechanisms for the 2 kinds of spindles. The reported temporal relationships during SO sequences suggest that fast spindles, driven by the SO up-state feed back to enhance the likelihood of succeeding SOs together with slow spindles. By enforcing such SO-spindle cycles, particularly after prior learning, fast spindles possibly play a key role in sleep-dependent memory processing. Citation: Mölle M; Bergmann TO; Marshall L; Born J. Fast and slow spindles during the sleep slow oscillation: disparate coalescence and engagement in memory processing. SLEEP 2011;34(10):1411–1421. PMID:21966073

Temporal Integration of Auditory Information Is Invariant to Temporal Grouping Cues

PubMed

Liu, Andrew S K; Tsunada, Joji; Gold, Joshua I; Cohen, Yale E

2015-01-01

Auditory perception depends on the temporal structure of incoming acoustic stimuli. Here, we examined whether a temporal manipulation that affects the perceptual grouping also affects the time dependence of decisions regarding those stimuli. We designed a novel discrimination task that required human listeners to decide whether a sequence of tone bursts was increasing or decreasing in frequency. We manipulated temporal perceptual-grouping cues by changing the time interval between the tone bursts, which led to listeners hearing the sequences as a single sound for short intervals or discrete sounds for longer intervals. Despite these strong perceptual differences, this manipulation did not affect the efficiency of how auditory information was integrated over time to form a decision. Instead, the grouping manipulation affected subjects' speed-accuracy trade-offs. These results indicate that the temporal dynamics of evidence accumulation for auditory perceptual decisions can be invariant to manipulations that affect the perceptual grouping of the evidence.

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.

Study on memories of temporal lobes and the principles of lateralization using near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Kamakura, Katsutoshi

2007-01-01

In this study we measured the variation of brain blood quantity (Oxy-Hb, Deoxy-Hb and Total-Hb) in the temporal lobes using near infrared spectroscopy (NIRS) when the tasks of the memories were presented to the subjects. The memories are classified into the short-term memory (STM) and the long-term memory (LTM) including the episodic and semantic memories. The subjects joined in this study are 11 persons who are university students including graduate students. We used the language task of letter-number sequencing, also reverse sequencing to measure STM and the task of the episodic memory to measure LTM. As a result of analysis, concerning the episodic memory, the variation of Oxy-Hb in the left temporal lobe was larger than that of Oxy-Hb in the right temporal lobe. The result might suggest that the episodic memory has a relationship with cerebral dominance concerning language area in the left temporal lobe. It seems that the episodic memory meditated with the function of language used in this study is much stored in the left temporal lobe than in the right temporal lobe. This result coincides with the principles of lateralization. The variation of Oxy-Hb in the language task of letter-number sequencing was smaller than that of Oxy-Hb in the language task of the episodic memory.

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…

Effects of Temporal Sequencing and Auditory Discrimination on Children's Memory Patterns for Tones, Numbers, and Nonsense Words

ERIC Educational Resources Information Center

Gromko, Joyce Eastlund; Hansen, Dee; Tortora, Anne Halloran; Higgins, Daniel; Boccia, Eric

2009-01-01

The purpose of this study was to determine whether children's recall of tones, numbers, and words was supported by a common temporal sequencing mechanism; whether children's patterns of memory for tones, numbers, and nonsense words were the same despite differences in symbol systems; and whether children's recall of tones, numbers, and nonsense…

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.

Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen).

PubMed

Rambaut, Andrew; Lam, Tommy T; Max Carvalho, Luiz; Pybus, Oliver G

2016-01-01

Gene sequences sampled at different points in time can be used to infer molecular phylogenies on a natural timescale of months or years, provided that the sequences in question undergo measurable amounts of evolutionary change between sampling times. Data sets with this property are termed heterochronous and have become increasingly common in several fields of biology, most notably the molecular epidemiology of rapidly evolving viruses. Here we introduce the cross-platform software tool, TempEst (formerly known as Path-O-Gen), for the visualization and analysis of temporally sampled sequence data. Given a molecular phylogeny and the dates of sampling for each sequence, TempEst uses an interactive regression approach to explore the association between genetic divergence through time and sampling dates. TempEst can be used to (1) assess whether there is sufficient temporal signal in the data to proceed with phylogenetic molecular clock analysis, and (2) identify sequences whose genetic divergence and sampling date are incongruent. Examination of the latter can help identify data quality problems, including errors in data annotation, sample contamination, sequence recombination, or alignment error. We recommend that all users of the molecular clock models implemented in BEAST first check their data using TempEst prior to analysis.

Temporal evolution of brain reorganization under cross-modal training: insights into the functional architecture of encoding and retrieval networks

NASA Astrophysics Data System (ADS)

Likova, Lora T.

2015-03-01

This study is based on the recent discovery of massive and well-structured cross-modal memory activation generated in the primary visual cortex (V1) of totally blind people as a result of novel training in drawing without any vision (Likova, 2012). This unexpected functional reorganization of primary visual cortex was obtained after undergoing only a week of training by the novel Cognitive-Kinesthetic Method, and was consistent across pilot groups of different categories of visual deprivation: congenitally blind, late-onset blind and blindfolded (Likova, 2014). These findings led us to implicate V1 as the implementation of the theoretical visuo-spatial 'sketchpad' for working memory in the human brain. Since neither the source nor the subsequent 'recipient' of this non-visual memory information in V1 is known, these results raise a number of important questions about the underlying functional organization of the respective encoding and retrieval networks in the brain. To address these questions, an individual totally blind from birth was given a week of Cognitive-Kinesthetic training, accompanied by functional magnetic resonance imaging (fMRI) both before and just after training, and again after a two-month consolidation period. The results revealed a remarkable temporal sequence of training-based response reorganization in both the hippocampal complex and the temporal-lobe object processing hierarchy over the prolonged consolidation period. In particular, a pattern of profound learning-based transformations in the hippocampus was strongly reflected in V1, with the retrieval function showing massive growth as result of the Cognitive-Kinesthetic memory training and consolidation, while the initially strong hippocampal response during tactile exploration and encoding became non-existent. Furthermore, after training, an alternating patch structure in the form of a cascade of discrete ventral regions underwent radical transformations to reach complete functional specialization in terms of either encoding or retrieval as a function of the stage of learning. Moreover, several distinct patterns of learning-evolution within the patches as a function of their anatomical location, implying a complex reorganization of the object processing sub-networks through the learning period. These first findings of complex patterns of training-based encoding/retrieval reorganization thus have broad implications for a newly emerging view of the perception/memory interactions and their reorganization through the learning process. Note that the temporal evolution of these forms of extended functional reorganization could not be uncovered with conventional assessment paradigms used in the traditional approaches to functional mapping, which may therefore have to be revisited. Moreover, as the present results are obtained in learning under life-long blindness, they imply modality-independent operations, transcending the usual tight association with visual processing. The present approach of memory drawing training in blindness, has the dual-advantage of being both non-visual and causal intervention, which makes it a promising 'scalpel' to disentangle interactions among diverse cognitive functions.

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.

Multisensory perceptual learning is dependent upon task difficulty.

PubMed

De Niear, Matthew A; Koo, Bonhwang; Wallace, Mark T

2016-11-01

There has been a growing interest in developing behavioral tasks to enhance temporal acuity as recent findings have demonstrated changes in temporal processing in a number of clinical conditions. Prior research has demonstrated that perceptual training can enhance temporal acuity both within and across different sensory modalities. Although certain forms of unisensory perceptual learning have been shown to be dependent upon task difficulty, this relationship has not been explored for multisensory learning. The present study sought to determine the effects of task difficulty on multisensory perceptual learning. Prior to and following a single training session, participants completed a simultaneity judgment (SJ) task, which required them to judge whether a visual stimulus (flash) and auditory stimulus (beep) presented in synchrony or at various stimulus onset asynchronies (SOAs) occurred synchronously or asynchronously. During the training session, participants completed the same SJ task but received feedback regarding the accuracy of their responses. Participants were randomly assigned to one of three levels of difficulty during training: easy, moderate, and hard, which were distinguished based on the SOAs used during training. We report that only the most difficult (i.e., hard) training protocol enhanced temporal acuity. We conclude that perceptual training protocols for enhancing multisensory temporal acuity may be optimized by employing audiovisual stimuli for which it is difficult to discriminate temporal synchrony from asynchrony.

Solving and Learning Soft Temporal Constraints: Experimental Scenario and Examples

NASA Technical Reports Server (NTRS)

Rossi, F.; Venable, K. B.; Sperduti, A.; Khatib, L.; Morris, P.; Morris, R.; Koga, Dennis (Technical Monitor)

2001-01-01

Soft temporal constraint problems allow to describe in a natural way scenarios where events happen over time and preferences are associated to event distances and durations. However, sometimes such local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem. To model everything in a uniform way via local preferences only, and also to take advantage of the existing constraint solvers which exploit only local preference use machine learning techniques which learn the local preferences from the global ones. In this paper we describe the existing framework for both solving and learning preferences in temporal constraint problems, the implemented modules, the experimental scenario, and preliminary results on some examples.

Effects of Frequency Separation and Diotic/Dichotic Presentations on the Alternation Frequency Limits in Audition Derived from a Temporal Phase Discrimination Task.

PubMed

Kanaya, Shoko; Fujisaki, Waka; Nishida, Shin'ya; Furukawa, Shigeto; Yokosawa, Kazuhiko

2015-02-01

Temporal phase discrimination is a useful psychophysical task to evaluate how sensory signals, synchronously detected in parallel, are perceptually bound by human observers. In this task two stimulus sequences synchronously alternate between two states (say, A-B-A-B and X-Y-X-Y) in either of two temporal phases (ie A and B are respectively paired with X and Y, or vice versa). The critical alternation frequency beyond which participants cannot discriminate the temporal phase is measured as an index characterizing the temporal property of the underlying binding process. This task has been used to reveal the mechanisms underlying visual and cross-modal bindings. To directly compare these binding mechanisms with those in another modality, this study used the temporal phase discrimination task to reveal the processes underlying auditory bindings. The two sequences were alternations between two pitches. We manipulated the distance between the two sequences by changing intersequence frequency separation, or presentation ears (diotic vs dichotic). Results showed that the alternation frequency limit ranged from 7 to 30 Hz, becoming higher as the intersequence distance decreased, as is the case with vision. However, unlike vision, auditory phase discrimination limits were higher and more variable across participants. © 2015 SAGE Publications.

A Tentative Application Of Morphological Filters To Time-Varying Images

NASA Astrophysics Data System (ADS)

Billard, D.; Poquillon, B.

1989-03-01

In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.

In vivo Proton Electron Double Resonance Imaging of Mice with Fast Spin Echo Pulse Sequence

PubMed Central

Sun, Ziqi; Li, Haihong; Petryakov, Sergey; Samouilov, Alex; Zweier, Jay L.

2011-01-01

Purpose To develop and evaluate a 2D fast spin echo (FSE) pulse sequence for enhancing temporal resolution and reducing tissue heating for in vivo proton electron double resonance imaging (PEDRI) of mice. Materials and Methods A four-compartment phantom containing 2 mM TEMPONE was imaged at 20.1 mT using 2D FSE-PEDRI and regular gradient echo (GRE)-PEDRI pulse sequences. Control mice were infused with TEMPONE over ∼1 min followed by time-course imaging using the 2D FSE-PEDRI sequence at intervals of 10 – 30 s between image acquisitions. The average signal intensity from the time-course images was analyzed using a first-order kinetics model. Results Phantom experiments demonstrated that EPR power deposition can be greatly reduced using the FSE-PEDRI pulse sequence compared to the conventional gradient echo pulse sequence. High temporal resolution was achieved at ∼4 s per image acquisition using the FSE-PEDRI sequence with a good image SNR in the range of 233-266 in the phantom study. The TEMPONE half-life measured in vivo was ∼72 s. Conclusion Thus, the FSE-PEDRI pulse sequence enables fast in vivo functional imaging of free radical probes in small animals greatly reducing EPR irradiation time with decreased power deposition and provides increased temporal resolution. PMID:22147559

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.

A Temporal Pattern Mining Approach for Classifying Electronic Health Record Data

PubMed Central

Batal, Iyad; Valizadegan, Hamed; Cooper, Gregory F.; Hauskrecht, Milos

2013-01-01

We study the problem of learning classification models from complex multivariate temporal data encountered in electronic health record systems. The challenge is to define a good set of features that are able to represent well the temporal aspect of the data. Our method relies on temporal abstractions and temporal pattern mining to extract the classification features. Temporal pattern mining usually returns a large number of temporal patterns, most of which may be irrelevant to the classification task. To address this problem, we present the Minimal Predictive Temporal Patterns framework to generate a small set of predictive and non-spurious patterns. We apply our approach to the real-world clinical task of predicting patients who are at risk of developing heparin induced thrombocytopenia. The results demonstrate the benefit of our approach in efficiently learning accurate classifiers, which is a key step for developing intelligent clinical monitoring systems. PMID:25309815

Multi-temporal Land Use Mapping of Coastal Wetlands Area using Machine Learning in Google Earth Engine

NASA Astrophysics Data System (ADS)

Farda, N. M.

2017-12-01

Coastal wetlands provide ecosystem services essential to people and the environment. Changes in coastal wetlands, especially on land use, are important to monitor by utilizing multi-temporal imagery. The Google Earth Engine (GEE) provides many machine learning algorithms (10 algorithms) that are very useful for extracting land use from imagery. The research objective is to explore machine learning in Google Earth Engine and its accuracy for multi-temporal land use mapping of coastal wetland area. Landsat 3 MSS (1978), Landsat 5 TM (1991), Landsat 7 ETM+ (2001), and Landsat 8 OLI (2014) images located in Segara Anakan lagoon are selected to represent multi temporal images. The input for machine learning are visible and near infrared bands, PCA band, invers PCA bands, bare soil index, vegetation index, wetness index, elevation from ASTER GDEM, and GLCM (Harralick) texture, and also polygon samples in 140 locations. There are 10 machine learning algorithms applied to extract coastal wetlands land use from Landsat imagery. The algorithms are Fast Naive Bayes, CART (Classification and Regression Tree), Random Forests, GMO Max Entropy, Perceptron (Multi Class Perceptron), Winnow, Voting SVM, Margin SVM, Pegasos (Primal Estimated sub-GrAdient SOlver for Svm), IKPamir (Intersection Kernel Passive Aggressive Method for Information Retrieval, SVM). Machine learning in Google Earth Engine are very helpful in multi-temporal land use mapping, the highest accuracy for land use mapping of coastal wetland is CART with 96.98 % Overall Accuracy using K-Fold Cross Validation (K = 10). GEE is particularly useful for multi-temporal land use mapping with ready used image and classification algorithms, and also very challenging for other applications.

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

PubMed

Sanchez, Daniel J; Yarnik, Eric N; Reber, Paul J

2015-03-01

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.

Online Object Tracking, Learning and Parsing with And-Or Graphs.

PubMed

Wu, Tianfu; Lu, Yang; Zhu, Song-Chun

2017-12-01

This paper presents a method, called AOGTracker, for simultaneously tracking, learning and parsing (TLP) of unknown objects in video sequences with a hierarchical and compositional And-Or graph (AOG) representation. The TLP method is formulated in the Bayesian framework with a spatial and a temporal dynamic programming (DP) algorithms inferring object bounding boxes on-the-fly. During online learning, the AOG is discriminatively learned using latent SVM [1] to account for appearance (e.g., lighting and partial occlusion) and structural (e.g., different poses and viewpoints) variations of a tracked object, as well as distractors (e.g., similar objects) in background. Three key issues in online inference and learning are addressed: (i) maintaining purity of positive and negative examples collected online, (ii) controling model complexity in latent structure learning, and (iii) identifying critical moments to re-learn the structure of AOG based on its intrackability. The intrackability measures uncertainty of an AOG based on its score maps in a frame. In experiments, our AOGTracker is tested on two popular tracking benchmarks with the same parameter setting: the TB-100/50/CVPR2013 benchmarks  , [3] , and the VOT benchmarks [4] -VOT 2013, 2014, 2015 and TIR2015 (thermal imagery tracking). In the former, our AOGTracker outperforms state-of-the-art tracking algorithms including two trackers based on deep convolutional network   [5] , [6] . In the latter, our AOGTracker outperforms all other trackers in VOT2013 and is comparable to the state-of-the-art methods in VOT2014, 2015 and TIR2015.

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…

Auditory temporal perceptual learning and transfer in Chinese-speaking children with developmental dyslexia.

PubMed

Zhang, Manli; Xie, Weiyi; Xu, Yanzhi; Meng, Xiangzhi

2018-03-01

Perceptual learning refers to the improvement of perceptual performance as a function of training. Recent studies found that auditory perceptual learning may improve phonological skills in individuals with developmental dyslexia in alphabetic writing system. However, whether auditory perceptual learning could also benefit the reading skills of those learning the Chinese logographic writing system is, as yet, unknown. The current study aimed to investigate the remediation effect of auditory temporal perceptual learning on Mandarin-speaking school children with developmental dyslexia. Thirty children with dyslexia were screened from a large pool of students in 3th-5th grades. They completed a series of pretests and then were assigned to either a non-training control group or a training group. The training group worked on a pure tone duration discrimination task for 7 sessions over 2 weeks with thirty minutes per session. Post-tests immediately after training and a follow-up test 2 months later were conducted. Analyses revealed a significant training effect in the training group relative to non-training group, as well as near transfer to the temporal interval discrimination task and far transfer to phonological awareness, character recognition and reading fluency. Importantly, the training effect and all the transfer effects were stable at the 2-month follow-up session. Further analyses found that a significant correlation between character recognition performance and learning rate mainly existed in the slow learning phase, the consolidation stage of perceptual learning, and this effect was modulated by an individuals' executive function. These findings indicate that adaptive auditory temporal perceptual learning can lead to learning and transfer effects on reading performance, and shed further light on the potential role of basic perceptual learning in the remediation and prevention of developmental dyslexia. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Speech Motor Sequence Learning: Acquisition and Retention in Parkinson Disease and Normal Aging.

PubMed

Whitfield, Jason A; Goberman, Alexander M

2017-06-10

The aim of the current investigation was to examine speech motor sequence learning in neurologically healthy younger adults, neurologically healthy older adults, and individuals with Parkinson disease (PD) over a 2-day period. A sequential nonword repetition task was used to examine learning over 2 days. Participants practiced a sequence of 6 monosyllabic nonwords that was retested following nighttime sleep. The speed and accuracy of the nonword sequence were measured, and learning was inferred by examining performance within and between sessions. Though all groups exhibited comparable improvements of the nonword sequence performance during the initial session, between-session retention of the nonword sequence differed between groups. Younger adult controls exhibited offline gains, characterized by an increase in the speed and accuracy of nonword sequence performance across sessions, whereas older adults exhibited stable between-session performance. Individuals with PD exhibited offline losses, marked by an increase in sequence duration between sessions. The current results demonstrate that both PD and normal aging affect retention of speech motor learning. Furthermore, these data suggest that basal ganglia dysfunction associated with PD may affect the later stages of speech motor learning. Findings from the current investigation are discussed in relation to studies examining consolidation of nonspeech motor learning.

Enhanced timing abilities in percussionists generalize to rhythms without a musical beat.

PubMed

Cameron, Daniel J; Grahn, Jessica A

2014-01-01

The ability to entrain movements to music is arguably universal, but it is unclear how specialized training may influence this. Previous research suggests that percussionists have superior temporal precision in perception and production tasks. Such superiority may be limited to temporal sequences that resemble real music or, alternatively, may generalize to musically implausible sequences. To test this, percussionists and nonpercussionists completed two tasks that used rhythmic sequences varying in musical plausibility. In the beat tapping task, participants tapped with the beat of a rhythmic sequence over 3 stages: finding the beat (as an initial sequence played), continuation of the beat (as a second sequence was introduced and played simultaneously), and switching to a second beat (the initial sequence finished, leaving only the second). The meters of the two sequences were either congruent or incongruent, as were their tempi (minimum inter-onset intervals). In the rhythm reproduction task, participants reproduced rhythms of four types, ranging from high to low musical plausibility: Metric simple rhythms induced a strong sense of the beat, metric complex rhythms induced a weaker sense of the beat, nonmetric rhythms had no beat, and jittered nonmetric rhythms also had no beat as well as low temporal predictability. For both tasks, percussionists performed more accurately than nonpercussionists. In addition, both groups were better with musically plausible than implausible conditions. Overall, the percussionists' superior abilities to entrain to, and reproduce, rhythms generalized to musically implausible sequences.

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…

"Bird Song Metronomics": Isochronous Organization of Zebra Finch Song Rhythm.

PubMed

Norton, Philipp; Scharff, Constance

2016-01-01

The human capacity for speech and vocal music depends on vocal imitation. Songbirds, in contrast to non-human primates, share this vocal production learning with humans. The process through which birds and humans learn many of their vocalizations as well as the underlying neural system exhibit a number of striking parallels and have been widely researched. In contrast, rhythm, a key feature of language, and music, has received surprisingly little attention in songbirds. Investigating temporal periodicity in bird song has the potential to inform the relationship between neural mechanisms and behavioral output and can also provide insight into the biology and evolution of musicality. Here we present a method to analyze birdsong for an underlying rhythmic regularity. Using the intervals from one note onset to the next as input, we found for each bird an isochronous sequence of time stamps, a "signal-derived pulse," or pulse(S), of which a subset aligned with all note onsets of the bird's song. Fourier analysis corroborated these results. To determine whether this finding was just a byproduct of the duration of notes and intervals typical for zebra finches but not dependent on the individual duration of elements and the sequence in which they are sung, we compared natural songs to models of artificial songs. Note onsets of natural song deviated from the pulse(S) significantly less than those of artificial songs with randomized note and gap durations. Thus, male zebra finch song has the regularity required for a listener to extract a perceived pulse (pulse(P)), as yet untested. Strikingly, in our study, pulses(S) that best fit note onsets often also coincided with the transitions between sub-note elements within complex notes, corresponding to neuromuscular gestures. Gesture durations often equaled one or more pulse(S) periods. This suggests that gesture duration constitutes the basic element of the temporal hierarchy of zebra finch song rhythm, an interesting parallel to the hierarchically structured components of regular rhythms in human music.

“Bird Song Metronomics”: Isochronous Organization of Zebra Finch Song Rhythm

PubMed Central

Norton, Philipp; Scharff, Constance

2016-01-01

The human capacity for speech and vocal music depends on vocal imitation. Songbirds, in contrast to non-human primates, share this vocal production learning with humans. The process through which birds and humans learn many of their vocalizations as well as the underlying neural system exhibit a number of striking parallels and have been widely researched. In contrast, rhythm, a key feature of language, and music, has received surprisingly little attention in songbirds. Investigating temporal periodicity in bird song has the potential to inform the relationship between neural mechanisms and behavioral output and can also provide insight into the biology and evolution of musicality. Here we present a method to analyze birdsong for an underlying rhythmic regularity. Using the intervals from one note onset to the next as input, we found for each bird an isochronous sequence of time stamps, a “signal-derived pulse,” or pulseS, of which a subset aligned with all note onsets of the bird's song. Fourier analysis corroborated these results. To determine whether this finding was just a byproduct of the duration of notes and intervals typical for zebra finches but not dependent on the individual duration of elements and the sequence in which they are sung, we compared natural songs to models of artificial songs. Note onsets of natural song deviated from the pulseS significantly less than those of artificial songs with randomized note and gap durations. Thus, male zebra finch song has the regularity required for a listener to extract a perceived pulse (pulseP), as yet untested. Strikingly, in our study, pulsesS that best fit note onsets often also coincided with the transitions between sub-note elements within complex notes, corresponding to neuromuscular gestures. Gesture durations often equaled one or more pulseS periods. This suggests that gesture duration constitutes the basic element of the temporal hierarchy of zebra finch song rhythm, an interesting parallel to the hierarchically structured components of regular rhythms in human music. PMID:27458334

Learning complex temporal patterns with resource-dependent spike timing-dependent plasticity.

PubMed

Hunzinger, Jason F; Chan, Victor H; Froemke, Robert C

2012-07-01

Studies of spike timing-dependent plasticity (STDP) have revealed that long-term changes in the strength of a synapse may be modulated substantially by temporal relationships between multiple presynaptic and postsynaptic spikes. Whereas long-term potentiation (LTP) and long-term depression (LTD) of synaptic strength have been modeled as distinct or separate functional mechanisms, here, we propose a new shared resource model. A functional consequence of our model is fast, stable, and diverse unsupervised learning of temporal multispike patterns with a biologically consistent spiking neural network. Due to interdependencies between LTP and LTD, dendritic delays, and proactive homeostatic aspects of the model, neurons are equipped to learn to decode temporally coded information within spike bursts. Moreover, neurons learn spike timing with few exposures in substantial noise and jitter. Surprisingly, despite having only one parameter, the model also accurately predicts in vitro observations of STDP in more complex multispike trains, as well as rate-dependent effects. We discuss candidate commonalities in natural long-term plasticity mechanisms.

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.

Temporal guidance of musicians' performance movement is an acquired skill.

PubMed

Rodger, M W M; O'Modhrain, S; Craig, C M

2013-04-01

The ancillary (non-sounding) body movements made by expert musicians during performance have been shown to indicate expressive, emotional, and structural features of the music to observers, even if the sound of the performance is absent. If such ancillary body movements are a component of skilled musical performance, then it should follow that acquiring the temporal control of such movements is a feature of musical skill acquisition. This proposition is tested using measures derived from a theory of temporal guidance of movement, "General Tau Theory" (Lee in Ecol Psychol 10:221-250, 1998; Lee et al. in Exp Brain Res 139:151-159, 2001), to compare movements made during performances of intermediate-level clarinetists before and after learning a new piece of music. Results indicate that the temporal control of ancillary body movements made by participants was stronger in performances after the music had been learned and was closer to the measures of temporal control found for an expert musician's movements. These findings provide evidence that the temporal control of musicians' ancillary body movements develops with musical learning. These results have implications for other skillful behaviors and nonverbal communication.

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

Classifying Cognitive Profiles Using Machine Learning with Privileged Information in Mild Cognitive Impairment.

PubMed

Alahmadi, Hanin H; Shen, Yuan; Fouad, Shereen; Luft, Caroline Di B; Bentham, Peter; Kourtzi, Zoe; Tino, Peter

2016-01-01

Early diagnosis of dementia is critical for assessing disease progression and potential treatment. State-or-the-art machine learning techniques have been increasingly employed to take on this diagnostic task. In this study, we employed Generalized Matrix Learning Vector Quantization (GMLVQ) classifiers to discriminate patients with Mild Cognitive Impairment (MCI) from healthy controls based on their cognitive skills. Further, we adopted a "Learning with privileged information" approach to combine cognitive and fMRI data for the classification task. The resulting classifier operates solely on the cognitive data while it incorporates the fMRI data as privileged information (PI) during training. This novel classifier is of practical use as the collection of brain imaging data is not always possible with patients and older participants. MCI patients and healthy age-matched controls were trained to extract structure from temporal sequences. We ask whether machine learning classifiers can be used to discriminate patients from controls and whether differences between these groups relate to individual cognitive profiles. To this end, we tested participants in four cognitive tasks: working memory, cognitive inhibition, divided attention, and selective attention. We also collected fMRI data before and after training on a probabilistic sequence learning task and extracted fMRI responses and connectivity as features for machine learning classifiers. Our results show that the PI guided GMLVQ classifiers outperform the baseline classifier that only used the cognitive data. In addition, we found that for the baseline classifier, divided attention is the only relevant cognitive feature. When PI was incorporated, divided attention remained the most relevant feature while cognitive inhibition became also relevant for the task. Interestingly, this analysis for the fMRI GMLVQ classifier suggests that (1) when overall fMRI signal is used as inputs to the classifier, the post-training session is most relevant; and (2) when the graph feature reflecting underlying spatiotemporal fMRI pattern is used, the pre-training session is most relevant. Taken together these results suggest that brain connectivity before training and overall fMRI signal after training are both diagnostic of cognitive skills in MCI.

Equilibrium point control of a monkey arm simulator by a fast learning tree structured artificial neural network.

PubMed

Dornay, M; Sanger, T D

1993-01-01

A planar 17 muscle model of the monkey's arm based on realistic biomechanical measurements was simulated on a Symbolics Lisp Machine. The simulator implements the equilibrium point hypothesis for the control of arm movements. Given initial and final desired positions, it generates a minimum-jerk desired trajectory of the hand and uses the backdriving algorithm to determine an appropriate sequence of motor commands to the muscles (Flash 1987; Mussa-Ivaldi et al. 1991; Dornay 1991b). These motor commands specify a temporal sequence of stable (attractive) equilibrium positions which lead to the desired hand movement. A strong disadvantage of the simulator is that it has no memory of previous computations. Determining the desired trajectory using the minimum-jerk model is instantaneous, but the laborious backdriving algorithm is slow, and can take up to one hour for some trajectories. The complexity of the required computations makes it a poor model for biological motor control. We propose a computationally simpler and more biologically plausible method for control which achieves the benefits of the backdriving algorithm. A fast learning, tree-structured network (Sanger 1991c) was trained to remember the knowledge obtained by the backdriving algorithm. The neural network learned the nonlinear mapping from a 2-dimensional cartesian planar hand position (x,y) to a 17-dimensional motor command space (u1, . . ., u17). Learning 20 training trajectories, each composed of 26 sample points [[x,y], [u1, . . ., u17] took only 20 min on a Sun-4 Sparc workstation. After the learning stage, new, untrained test trajectories as well as the original trajectories of the hand were given to the neural network as input. The network calculated the required motor commands for these movements. The resulting movements were close to the desired ones for both the training and test cases.

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.

[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.

Time to rethink the neural mechanisms of learning and memory.

PubMed

Gallistel, Charles R; Balsam, Peter D

2014-02-01

Most studies in the neurobiology of learning assume that the underlying learning process is a pairing - dependent change in synaptic strength that requires repeated experience of events presented in close temporal contiguity. However, much learning is rapid and does not depend on temporal contiguity, which has never been precisely defined. These points are well illustrated by studies showing that the temporal relations between events are rapidly learned- even over long delays- and that this knowledge governs the form and timing of behavior. The speed with which anticipatory responses emerge in conditioning paradigms is determined by the information that cues provide about the timing of rewards. The challenge for understanding the neurobiology of learning is to understand the mechanisms in the nervous system that encode information from even a single experience, the nature of the memory mechanisms that can encode quantities such as time, and how the brain can flexibly perform computations based on this information. Copyright © 2013 Elsevier Inc. All rights reserved.

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

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.

Bioorthogonal Metabolic Labeling of Nascent RNA in Neurons Improves the Sensitivity of Transcriptome-Wide Profiling.

PubMed

Zajaczkowski, Esmi L; Zhao, Qiong-Yi; Zhang, Zong Hong; Li, Xiang; Wei, Wei; Marshall, Paul R; Leighton, Laura J; Nainar, Sarah; Feng, Chao; Spitale, Robert C; Bredy, Timothy W

2018-06-15

Transcriptome-wide expression profiling of neurons has provided important insights into the underlying molecular mechanisms and gene expression patterns that transpire during learning and memory formation. However, there is a paucity of tools for profiling stimulus-induced RNA within specific neuronal cell populations. A bioorthogonal method to chemically label nascent (i.e., newly transcribed) RNA in a cell-type-specific and temporally controlled manner, which is also amenable to bioconjugation via click chemistry, was recently developed and optimized within conventional immortalized cell lines. However, its value within a more fragile and complicated cellular system such as neurons, as well as for transcriptome-wide expression profiling, has yet to be demonstrated. Here, we report the visualization and sequencing of activity-dependent nascent RNA derived from neurons using this labeling method. This work has important implications for improving transcriptome-wide expression profiling and visualization of nascent RNA in neurons, which has the potential to provide valuable insights into the mechanisms underlying neural plasticity, learning, and memory.

Object class segmentation of RGB-D video using recurrent convolutional neural networks.

PubMed

Pavel, Mircea Serban; Schulz, Hannes; Behnke, Sven

2017-04-01

Object class segmentation is a computer vision task which requires labeling each pixel of an image with the class of the object it belongs to. Deep convolutional neural networks (DNN) are able to learn and take advantage of local spatial correlations required for this task. They are, however, restricted by their small, fixed-sized filters, which limits their ability to learn long-range dependencies. Recurrent Neural Networks (RNN), on the other hand, do not suffer from this restriction. Their iterative interpretation allows them to model long-range dependencies by propagating activity. This property is especially useful when labeling video sequences, where both spatial and temporal long-range dependencies occur. In this work, a novel RNN architecture for object class segmentation is presented. We investigate several ways to train such a network. We evaluate our models on the challenging NYU Depth v2 dataset for object class segmentation and obtain competitive results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sequential neuromodulation of Hebbian plasticity offers mechanism for effective reward-based navigation

PubMed Central

Brzosko, Zuzanna; Zannone, Sara; Schultz, Wolfram

2017-01-01

Spike timing-dependent plasticity (STDP) is under neuromodulatory control, which is correlated with distinct behavioral states. Previously, we reported that dopamine, a reward signal, broadens the time window for synaptic potentiation and modulates the outcome of hippocampal STDP even when applied after the plasticity induction protocol (Brzosko et al., 2015). Here, we demonstrate that sequential neuromodulation of STDP by acetylcholine and dopamine offers an efficacious model of reward-based navigation. Specifically, our experimental data in mouse hippocampal slices show that acetylcholine biases STDP toward synaptic depression, whilst subsequent application of dopamine converts this depression into potentiation. Incorporating this bidirectional neuromodulation-enabled correlational synaptic learning rule into a computational model yields effective navigation toward changing reward locations, as in natural foraging behavior. Thus, temporally sequenced neuromodulation of STDP enables associations to be made between actions and outcomes and also provides a possible mechanism for aligning the time scales of cellular and behavioral learning. DOI: http://dx.doi.org/10.7554/eLife.27756.001 PMID:28691903

Training echo state networks for rotation-invariant bone marrow cell classification.

PubMed

Kainz, Philipp; Burgsteiner, Harald; Asslaber, Martin; Ahammer, Helmut

2017-01-01

The main principle of diagnostic pathology is the reliable interpretation of individual cells in context of the tissue architecture. Especially a confident examination of bone marrow specimen is dependent on a valid classification of myeloid cells. In this work, we propose a novel rotation-invariant learning scheme for multi-class echo state networks (ESNs), which achieves very high performance in automated bone marrow cell classification. Based on representing static images as temporal sequence of rotations, we show how ESNs robustly recognize cells of arbitrary rotations by taking advantage of their short-term memory capacity. The performance of our approach is compared to a classification random forest that learns rotation-invariance in a conventional way by exhaustively training on multiple rotations of individual samples. The methods were evaluated on a human bone marrow image database consisting of granulopoietic and erythropoietic cells in different maturation stages. Our ESN approach to cell classification does not rely on segmentation of cells or manual feature extraction and can therefore directly be applied to image data.

Collaborative learning using Internet2 and remote collections of stereo dissection images.

PubMed

Dev, Parvati; Srivastava, Sakti; Senger, Steven

2006-04-01

We have investigated collaborative learning of anatomy over Internet2, using an application called remote stereo viewer (RSV). This application offers a unique method of teaching anatomy, using high-resolution stereoscopic images, in a client-server architecture. Rotated sequences of stereo image pairs were produced by volumetric rendering of the Visible female and by dissecting and photographing a cadaveric hand. A client-server application (RSV) was created to provide access to these image sets, using a highly interactive interface. The RSV system was used to provide a "virtual anatomy" session for students in the Stanford Medical School Gross Anatomy course. The RSV application allows both independent and collaborative modes of viewing. The most appealing aspects of the RSV application were the capacity for stereoscopic viewing and the potential to access the content remotely within a flexible temporal framework. The RSV technology, used over Internet2, thus serves as an effective complement to traditional methods of teaching gross anatomy. (c) 2006 Wiley-Liss, Inc.

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.

Cerebellum, temporal predictability and the updating of a mental model.

PubMed

Kotz, Sonja A; Stockert, Anika; Schwartze, Michael

2014-12-19

We live in a dynamic and changing environment, which necessitates that we adapt to and efficiently respond to changes of stimulus form ('what') and stimulus occurrence ('when'). Consequently, behaviour is optimal when we can anticipate both the 'what' and 'when' dimensions of a stimulus. For example, to perceive a temporally expected stimulus, a listener needs to establish a fairly precise internal representation of its external temporal structure, a function ascribed to classical sensorimotor areas such as the cerebellum. Here we investigated how patients with cerebellar lesions and healthy matched controls exploit temporal regularity during auditory deviance processing. We expected modulations of the N2b and P3b components of the event-related potential in response to deviant tones, and also a stronger P3b response when deviant tones are embedded in temporally regular compared to irregular tone sequences. We further tested to what degree structural damage to the cerebellar temporal processing system affects the N2b and P3b responses associated with voluntary attention to change detection and the predictive adaptation of a mental model of the environment, respectively. Results revealed that healthy controls and cerebellar patients display an increased N2b response to deviant tones independent of temporal context. However, while healthy controls showed the expected enhanced P3b response to deviant tones in temporally regular sequences, the P3b response in cerebellar patients was significantly smaller in these sequences. The current data provide evidence that structural damage to the cerebellum affects the predictive adaptation to the temporal structure of events and the updating of a mental model of the environment under voluntary attention. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Cerebellum, temporal predictability and the updating of a mental model

PubMed Central

Kotz, Sonja A.; Stockert, Anika; Schwartze, Michael

2014-01-01

We live in a dynamic and changing environment, which necessitates that we adapt to and efficiently respond to changes of stimulus form (‘what’) and stimulus occurrence (‘when’). Consequently, behaviour is optimal when we can anticipate both the ‘what’ and ‘when’ dimensions of a stimulus. For example, to perceive a temporally expected stimulus, a listener needs to establish a fairly precise internal representation of its external temporal structure, a function ascribed to classical sensorimotor areas such as the cerebellum. Here we investigated how patients with cerebellar lesions and healthy matched controls exploit temporal regularity during auditory deviance processing. We expected modulations of the N2b and P3b components of the event-related potential in response to deviant tones, and also a stronger P3b response when deviant tones are embedded in temporally regular compared to irregular tone sequences. We further tested to what degree structural damage to the cerebellar temporal processing system affects the N2b and P3b responses associated with voluntary attention to change detection and the predictive adaptation of a mental model of the environment, respectively. Results revealed that healthy controls and cerebellar patients display an increased N2b response to deviant tones independent of temporal context. However, while healthy controls showed the expected enhanced P3b response to deviant tones in temporally regular sequences, the P3b response in cerebellar patients was significantly smaller in these sequences. The current data provide evidence that structural damage to the cerebellum affects the predictive adaptation to the temporal structure of events and the updating of a mental model of the environment under voluntary attention. PMID:25385781

Adaptive social learning strategies in temporally and spatially varying environments : how temporal vs. spatial variation, number of cultural traits, and costs of learning influence the evolution of conformist-biased transmission, payoff-biased transmission, and individual learning.

PubMed

Nakahashi, Wataru; Wakano, Joe Yuichiro; Henrich, Joseph

2012-12-01

Long before the origins of agriculture human ancestors had expanded across the globe into an immense variety of environments, from Australian deserts to Siberian tundra. Survival in these environments did not principally depend on genetic adaptations, but instead on evolved learning strategies that permitted the assembly of locally adaptive behavioral repertoires. To develop hypotheses about these learning strategies, we have modeled the evolution of learning strategies to assess what conditions and constraints favor which kinds of strategies. To build on prior work, we focus on clarifying how spatial variability, temporal variability, and the number of cultural traits influence the evolution of four types of strategies: (1) individual learning, (2) unbiased social learning, (3) payoff-biased social learning, and (4) conformist transmission. Using a combination of analytic and simulation methods, we show that spatial-but not temporal-variation strongly favors the emergence of conformist transmission. This effect intensifies when migration rates are relatively high and individual learning is costly. We also show that increasing the number of cultural traits above two favors the evolution of conformist transmission, which suggests that the assumption of only two traits in many models has been conservative. We close by discussing how (1) spatial variability represents only one way of introducing the low-level, nonadaptive phenotypic trait variation that so favors conformist transmission, the other obvious way being learning errors, and (2) our findings apply to the evolution of conformist transmission in social interactions. Throughout we emphasize how our models generate empirical predictions suitable for laboratory testing.

Time Determines the Neural Circuit Underlying Associative Fear Learning

PubMed Central

Guimarãis, Marta; Gregório, Ana; Cruz, Andreia; Guyon, Nicolas; Moita, Marta A.

2011-01-01

Ultimately associative learning is a function of the temporal features and relationships between experienced stimuli. Nevertheless how time affects the neural circuit underlying this form of learning remains largely unknown. To address this issue, we used single-trial auditory trace fear conditioning and varied the length of the interval between tone and foot-shock. Through temporary inactivation of the amygdala, medial prefrontal-cortex (mPFC), and dorsal-hippocampus in rats, we tested the hypothesis that different temporal intervals between the tone and the shock influence the neuronal structures necessary for learning. With this study we provide the first experimental evidence showing that temporarily inactivating the amygdala before training impairs auditory fear learning when there is a temporal gap between the tone and the shock. Moreover, imposing a short interval (5 s) between the two stimuli also relies on the mPFC, while learning the association across a longer interval (40 s) becomes additionally dependent on a third structure, the dorsal-hippocampus. Thus, our results suggest that increasing the interval length between tone and shock leads to the involvement of an increasing number of brain areas in order for the association between the two stimuli to be acquired normally. These findings demonstrate that the temporal relationship between events is a key factor in determining the neuronal mechanisms underlying associative fear learning. PMID:22207842

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.

Differential gene expression in dentate granule cells in mesial temporal lobe epilepsy with and without hippocampal sclerosis.

PubMed

Griffin, Nicole G; Wang, Yu; Hulette, Christine M; Halvorsen, Matt; Cronin, Kenneth D; Walley, Nicole M; Haglund, Michael M; Radtke, Rodney A; Skene, J H Pate; Sinha, Saurabh R; Heinzen, Erin L

2016-03-01

Hippocampal sclerosis is the most common neuropathologic finding in cases of medically intractable mesial temporal lobe epilepsy. In this study, we analyzed the gene expression profiles of dentate granule cells of patients with mesial temporal lobe epilepsy with and without hippocampal sclerosis to show that next-generation sequencing methods can produce interpretable genomic data from RNA collected from small homogenous cell populations, and to shed light on the transcriptional changes associated with hippocampal sclerosis. RNA was extracted, and complementary DNA (cDNA) was prepared and amplified from dentate granule cells that had been harvested by laser capture microdissection from surgically resected hippocampi from patients with mesial temporal lobe epilepsy with and without hippocampal sclerosis. Sequencing libraries were sequenced, and the resulting sequencing reads were aligned to the reference genome. Differential expression analysis was used to ascertain expression differences between patients with and without hippocampal sclerosis. Greater than 90% of the RNA-Seq reads aligned to the reference. There was high concordance between transcriptional profiles obtained for duplicate samples. Principal component analysis revealed that the presence or absence of hippocampal sclerosis was the main determinant of the variance within the data. Among the genes up-regulated in the hippocampal sclerosis samples, there was significant enrichment for genes involved in oxidative phosphorylation. By analyzing the gene expression profiles of dentate granule cells from surgically resected hippocampal specimens from patients with mesial temporal lobe epilepsy with and without hippocampal sclerosis, we have demonstrated the utility of next-generation sequencing methods for producing biologically relevant results from small populations of homogeneous cells, and have provided insight on the transcriptional changes associated with this pathology. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Sequence-specific procedural learning deficits in children with specific language impairment.

PubMed

Hsu, Hsinjen Julie; Bishop, Dorothy V M

2014-05-01

This study tested the procedural deficit hypothesis of specific language impairment (SLI) by comparing children's performance in two motor procedural learning tasks and an implicit verbal sequence learning task. Participants were 7- to 11-year-old children with SLI (n = 48), typically developing age-matched children (n = 20) and younger typically developing children matched for receptive grammar (n = 28). In a serial reaction time task, the children with SLI performed at the same level as the grammar-matched children, but poorer than age-matched controls in learning motor sequences. When tested with a motor procedural learning task that did not involve learning sequential relationships between discrete elements (i.e. pursuit rotor), the children with SLI performed comparably with age-matched children and better than younger grammar-matched controls. In addition, poor implicit learning of word sequences in a verbal memory task (the Hebb effect) was found in the children with SLI. Together, these findings suggest that SLI might be characterized by deficits in learning sequence-specific information, rather than generally weak procedural learning. © 2014 The Authors. Developmental Science Published by John Wiley & Sons Ltd.

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

Two distinct modes of forebrain circuit dynamics underlie temporal patterning in the vocalizations of young songbirds

PubMed Central

Aronov, Dmitriy; Veit, Lena; Goldberg, Jesse H.; Fee, Michale S.

2011-01-01

Accurate timing is a critical aspect of motor control, yet the temporal structure of many mature behaviors emerges during learning from highly variable exploratory actions. How does a developing brain acquire the precise control of timing in behavioral sequences? To investigate the development of timing, we analyzed the songs of young juvenile zebra finches. These highly variable vocalizations, akin to human babbling, gradually develop into temporally-stereotyped adult songs. We find that the durations of syllables and silences in juvenile singing are formed by a mixture of two distinct modes of timing – a random mode producing broadly-distributed durations early in development, and a stereotyped mode underlying the gradual emergence of stereotyped durations. Using lesions, inactivations, and localized brain cooling we investigated the roles of neural dynamics within two premotor cortical areas in the production of these temporal modes. We find that LMAN (lateral magnocellular nucleus of the nidopallium) is required specifically for the generation of the random mode of timing, and that mild cooling of LMAN causes an increase in the durations produced by this mode. On the contrary, HVC (used as a proper name) is required specifically for producing the stereotyped mode of timing, and its cooling causes a slowing of all stereotyped components. These results show that two neural pathways contribute to the timing of juvenile songs, and suggest an interesting organization in the forebrain, whereby different brain areas are specialized for the production of distinct forms of neural dynamics. PMID:22072687

Face processing regions are sensitive to distinct aspects of temporal sequence in facial dynamics.

PubMed

Reinl, Maren; Bartels, Andreas

2014-11-15

Facial movement conveys important information for social interactions, yet its neural processing is poorly understood. Computational models propose that shape- and temporal sequence sensitive mechanisms interact in processing dynamic faces. While face processing regions are known to respond to facial movement, their sensitivity to particular temporal sequences has barely been studied. Here we used fMRI to examine the sensitivity of human face-processing regions to two aspects of directionality in facial movement trajectories. We presented genuine movie recordings of increasing and decreasing fear expressions, each of which were played in natural or reversed frame order. This two-by-two factorial design matched low-level visual properties, static content and motion energy within each factor, emotion-direction (increasing or decreasing emotion) and timeline (natural versus artificial). The results showed sensitivity for emotion-direction in FFA, which was timeline-dependent as it only occurred within the natural frame order, and sensitivity to timeline in the STS, which was emotion-direction-dependent as it only occurred for decreased fear. The occipital face area (OFA) was sensitive to the factor timeline. These findings reveal interacting temporal sequence sensitive mechanisms that are responsive to both ecological meaning and to prototypical unfolding of facial dynamics. These mechanisms are temporally directional, provide socially relevant information regarding emotional state or naturalness of behavior, and agree with predictions from modeling and predictive coding theory. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Temporal Integration of Auditory Information Is Invariant to Temporal Grouping Cues1,2,3

PubMed Central

Tsunada, Joji

2015-01-01

Abstract Auditory perception depends on the temporal structure of incoming acoustic stimuli. Here, we examined whether a temporal manipulation that affects the perceptual grouping also affects the time dependence of decisions regarding those stimuli. We designed a novel discrimination task that required human listeners to decide whether a sequence of tone bursts was increasing or decreasing in frequency. We manipulated temporal perceptual-grouping cues by changing the time interval between the tone bursts, which led to listeners hearing the sequences as a single sound for short intervals or discrete sounds for longer intervals. Despite these strong perceptual differences, this manipulation did not affect the efficiency of how auditory information was integrated over time to form a decision. Instead, the grouping manipulation affected subjects’ speed−accuracy trade-offs. These results indicate that the temporal dynamics of evidence accumulation for auditory perceptual decisions can be invariant to manipulations that affect the perceptual grouping of the evidence. PMID:26464975

Integral reinforcement learning for continuous-time input-affine nonlinear systems with simultaneous invariant explorations.

PubMed

Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho

2015-05-01

This paper focuses on a class of reinforcement learning (RL) algorithms, named integral RL (I-RL), that solve continuous-time (CT) nonlinear optimal control problems with input-affine system dynamics. First, we extend the concepts of exploration, integral temporal difference, and invariant admissibility to the target CT nonlinear system that is governed by a control policy plus a probing signal called an exploration. Then, we show input-to-state stability (ISS) and invariant admissibility of the closed-loop systems with the policies generated by integral policy iteration (I-PI) or invariantly admissible PI (IA-PI) method. Based on these, three online I-RL algorithms named explorized I-PI and integral Q -learning I, II are proposed, all of which generate the same convergent sequences as I-PI and IA-PI under the required excitation condition on the exploration. All the proposed methods are partially or completely model free, and can simultaneously explore the state space in a stable manner during the online learning processes. ISS, invariant admissibility, and convergence properties of the proposed methods are also investigated, and related with these, we show the design principles of the exploration for safe learning. Neural-network-based implementation methods for the proposed schemes are also presented in this paper. Finally, several numerical simulations are carried out to verify the effectiveness of the proposed methods.

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.

On the nature of phase attraction in sensorimotor synchronization with interleaved auditory sequences.

PubMed

Repp, Bruno H

2004-10-01

In a task that requires in-phase synchronization of finger taps with an isochronous sequence of target tones that is interleaved with a sequence of distractor tones at various fixed phase relationships, the taps tend to be attracted to the distractor tones, especially when the distractor tones closely precede the target tones [Repp, B. H. (2003a). Phase attraction in sensorimotor synchronization with auditory sequences: Effects of single and periodic distractors on synchronization accuracy. Journal of Experimental Psychology: Human Perception and Performance, 29, 290-309]. The present research addressed two related questions about this distractor effect: (1) Is it a function of the absolute temporal separation or of the relative phase of the two stimulus sequences? (2) Is it the result of perceptual grouping (integration) of target and distractor tones or of simultaneous attraction to two independent sequences? In three experiments, distractor effects were compared across two different sequence rates. The results suggest that absolute temporal separation, not relative phase, is the critical variable. Experiment 3 also included an anti-phase tapping task that addressed the second question directly. The results suggest that the attraction of taps to distractor tones is caused mainly by temporal integration of target and distractor tones within a fixed window of 100-150 ms duration, with the earlier-occurring tone being weighted more strongly than the later-occurring one.

The Temporal Properties of E-Learning: An Exploratory Study of Academics' Conceptions

ERIC Educational Resources Information Center

Martins, Jorge; Nunes, Miguel Baptista

2016-01-01

Purpose: The purpose of this paper is to present the results of an exploratory study that investigates Portuguese academics' conceptions concerning the temporal properties of e-learning, in the context of traditional Higher Education Institutions. Design/methodology/approach: Grounded Theory methodology was used to systematically analyse data…

Abnormal development of sensory-motor, visual temporal and parahippocampal cortex in children with learning disabilities and borderline intellectual functioning

PubMed Central

Baglio, Francesca; Cabinio, Monia; Ricci, Cristian; Baglio, Gisella; Lipari, Susanna; Griffanti, Ludovica; Preti, Maria G.; Nemni, Raffaello; Clerici, Mario; Zanette, Michela; Blasi, Valeria

2014-01-01

Borderline intellectual functioning (BIF) is a condition characterized by an intelligence quotient (IQ) between 70 and 85. BIF children present with cognitive, motor, social, and adaptive limitations that result in learning disabilities and are more likely to develop psychiatric disorders later in life. The aim of this study was to investigate brain morphometry and its relation to IQ level in BIF children. Thirteen children with BIF and 14 age- and sex-matched typically developing (TD) children were enrolled. All children underwent a full IQ assessment (WISC-III scale) and a magnetic resonance (MR) examination including conventional sequences to assess brain structural abnormalities and high resolution 3D images for voxel-based morphometry analysis. To investigate to what extent the group influenced gray matter (GM) volumes, both univariate and multivariate generalized linear model analysis of variance were used, and the varimax factor analysis was used to explore variable correlations and clusters among subjects. Results showed that BIF children, compared to controls have increased regional GM volume in bilateral sensorimotor and right posterior temporal cortices and decreased GM volume in the right parahippocampal gyrus. GM volumes were highly correlated with IQ indices. The present work is a case study of a group of BIF children showing that BIF is associated with abnormal cortical development in brain areas that have a pivotal role in motor, learning, and behavioral processes. Our findings, although allowing for little generalization to the general population, contribute to the very limited knowledge in this field. Future longitudinal MR studies will be useful in verifying whether cortical features can be modified over time even in association with rehabilitative intervention. PMID:25360097

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.

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).

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.

[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.

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

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

Everyday robotic action: lessons from human action control

PubMed Central

de Kleijn, Roy; Kachergis, George; Hommel, Bernhard

2014-01-01

Robots are increasingly capable of performing everyday human activities such as cooking, cleaning, and doing the laundry. This requires the real-time planning and execution of complex, temporally extended sequential actions under high degrees of uncertainty, which provides many challenges to traditional approaches to robot action control. We argue that important lessons in this respect can be learned from research on human action control. We provide a brief overview of available psychological insights into this issue and focus on four principles that we think could be particularly beneficial for robot control: the integration of symbolic and subsymbolic planning of action sequences, the integration of feedforward and feedback control, the clustering of complex actions into subcomponents, and the contextualization of action-control structures through goal representations. PMID:24672474

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…

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…

Strength of Temporal White Matter Pathways Predicts Semantic Learning.

PubMed

Ripollés, Pablo; Biel, Davina; Peñaloza, Claudia; Kaufmann, Jörn; Marco-Pallarés, Josep; Noesselt, Toemme; Rodríguez-Fornells, Antoni

2017-11-15

Learning the associations between words and meanings is a fundamental human ability. Although the language network is cortically well defined, the role of the white matter pathways supporting novel word-to-meaning mappings remains unclear. Here, by using contextual and cross-situational word learning, we tested whether learning the meaning of a new word is related to the integrity of the language-related white matter pathways in 40 adults (18 women). The arcuate, uncinate, inferior-fronto-occipital and inferior-longitudinal fasciculi were virtually dissected using manual and automatic deterministic fiber tracking. Critically, the automatic method allowed assessing the white matter microstructure along the tract. Results demonstrate that the microstructural properties of the left inferior-longitudinal fasciculus predict contextual learning, whereas the left uncinate was associated with cross-situational learning. In addition, we identified regions of special importance within these pathways: the posterior middle temporal gyrus, thought to serve as a lexical interface and specifically related to contextual learning; the anterior temporal lobe, known to be an amodal hub for semantic processing and related to cross-situational learning; and the white matter near the hippocampus, a structure fundamental for the initial stages of new-word learning and, remarkably, related to both types of word learning. No significant associations were found for the inferior-fronto-occipital fasciculus or the arcuate. While previous results suggest that learning new phonological word forms is mediated by the arcuate fasciculus, these findings show that the temporal pathways are the crucial neural substrate supporting one of the most striking human abilities: our capacity to identify correct associations between words and meanings under referential indeterminacy. SIGNIFICANCE STATEMENT The language-processing network is cortically (i.e., gray matter) well defined. However, the role of the white matter pathways that support novel word learning within this network remains unclear. In this work, we dissected language-related (arcuate, uncinate, inferior-fronto-occipital, and inferior-longitudinal) fasciculi using manual and automatic tracking. We found the left inferior-longitudinal fasciculus to be predictive of word-learning success in two word-to-meaning tasks: contextual and cross-situational learning paradigms. The left uncinate was predictive of cross-situational word learning. No significant correlations were found for the arcuate or the inferior-fronto-occipital fasciculus. While previous results showed that learning new phonological word forms is supported by the arcuate fasciculus, these findings demonstrate that learning new word-to-meaning associations is mainly dependent on temporal white matter pathways. Copyright © 2017 the authors 0270-6474/17/3711102-13$15.00/0.

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

Temporal motifs reveal homophily, gender-specific patterns, and group talk in call sequences.

PubMed

Kovanen, Lauri; Kaski, Kimmo; Kertész, János; Saramäki, Jari

2013-11-05

Recent studies on electronic communication records have shown that human communication has complex temporal structure. We study how communication patterns that involve multiple individuals are affected by attributes such as sex and age. To this end, we represent the communication records as a colored temporal network where node color is used to represent individuals' attributes, and identify patterns known as temporal motifs. We then construct a null model for the occurrence of temporal motifs that takes into account the interaction frequencies and connectivity between nodes of different colors. This null model allows us to detect significant patterns in call sequences that cannot be observed in a static network that uses interaction frequencies as link weights. We find sex-related differences in communication patterns in a large dataset of mobile phone records and show the existence of temporal homophily, the tendency of similar individuals to participate in communication patterns beyond what would be expected on the basis of their average interaction frequencies. We also show that temporal patterns differ between dense and sparse neighborhoods in the network. Because also this result is independent of interaction frequencies, it can be seen as an extension of Granovetter's hypothesis to temporal networks.

Temporal motifs reveal homophily, gender-specific patterns, and group talk in call sequences

PubMed Central

Kovanen, Lauri; Kaski, Kimmo; Kertész, János; Saramäki, Jari

2013-01-01

Recent studies on electronic communication records have shown that human communication has complex temporal structure. We study how communication patterns that involve multiple individuals are affected by attributes such as sex and age. To this end, we represent the communication records as a colored temporal network where node color is used to represent individuals’ attributes, and identify patterns known as temporal motifs. We then construct a null model for the occurrence of temporal motifs that takes into account the interaction frequencies and connectivity between nodes of different colors. This null model allows us to detect significant patterns in call sequences that cannot be observed in a static network that uses interaction frequencies as link weights. We find sex-related differences in communication patterns in a large dataset of mobile phone records and show the existence of temporal homophily, the tendency of similar individuals to participate in communication patterns beyond what would be expected on the basis of their average interaction frequencies. We also show that temporal patterns differ between dense and sparse neighborhoods in the network. Because also this result is independent of interaction frequencies, it can be seen as an extension of Granovetter’s hypothesis to temporal networks. PMID:24145424

The Neural Correlates of Implicit Sequence Learning in Schizophrenia

PubMed Central

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

2009-01-01

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. PMID:17983290

Identification of memory reactivation during sleep by EEG classification.

PubMed

Belal, Suliman; Cousins, James; El-Deredy, Wael; Parkes, Laura; Schneider, Jules; Tsujimura, Hikaru; Zoumpoulaki, Alexia; Perapoch, Marta; Santamaria, Lorena; Lewis, Penelope

2018-04-17

Memory reactivation during sleep is critical for consolidation, but also extremely difficult to measure as it is subtle, distributed and temporally unpredictable. This article reports a novel method for detecting such reactivation in standard sleep recordings. During learning, participants produced a complex sequence of finger presses, with each finger cued by a distinct audio-visual stimulus. Auditory cues were then re-played during subsequent sleep to trigger neural reactivation through a method known as targeted memory reactivation (TMR). Next, we used electroencephalography data from the learning session to train a machine learning classifier, and then applied this classifier to sleep data to determine how successfully each tone had elicited memory reactivation. Neural reactivation was classified above chance in all participants when TMR was applied in SWS, and in 5 of the 14 participants to whom TMR was applied in N2. Classification success reduced across numerous repetitions of the tone cue, suggesting either a gradually reducing responsiveness to such cues or a plasticity-related change in the neural signature as a result of cueing. We believe this method will be valuable for future investigations of memory consolidation. Copyright © 2018 Elsevier Inc. All rights reserved.

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,…

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.

Temporal Learning in 4 1/2- and 6-Year-Old Children: Role of Instructions and Prior Knowledge.

ERIC Educational Resources Information Center

Droit, Sylvie; And Others

1990-01-01

Examined the role of prior temporal knowledge of 4 1/2- and 6-year-olds through the use of high-rate, interval, and minimal instructions in a fixed-interval training schedule. Determined that the subjects' learning depended on their verbal self-control skills. (BC)

Intersensory Redundancy and Seven-Month-Old Infants' Memory for Arbitrary Syllable-Object Relations.

ERIC Educational Resources Information Center

Gogate, Lakshmi J.; Bahrick, Lorraine E.

Seven-month-old infants require redundant information such as temporal synchrony to learn arbitrary syllable-object relations. Infants learned the relations between spoken syllables, /a/ and /i/, and two moving objects only when temporal synchrony was present during habituation. Two experiments examined infants' memory for these relations. In…

The Development of Invariant Object Recognition Requires Visual Experience with Temporally Smooth Objects

ERIC Educational Resources Information Center

Wood, Justin N.; Wood, Samantha M. W.

2018-01-01

How do newborns learn to recognize objects? According to temporal learning models in computational neuroscience, the brain constructs object representations by extracting smoothly changing features from the environment. To date, however, it is unknown whether newborns depend on smoothly changing features to build invariant object representations.…

Time and Temporality as Mediators of Science Learning

ERIC Educational Resources Information Center

Roth, Wolff-Michael; Tobin, Kenneth; Ritchie, Stephen M.

2008-01-01

Few studies have focused on understanding how teaching and learning in classrooms are mediated by other dimensions of the organizational systems of which education is an integral part. Our 7-year ethnographic study of an urban high school shows how time and temporality constitute key practical and theoretical resources to the actors in the…

Fluoxetine Restores Spatial Learning but Not Accelerated Forgetting in Mesial Temporal Lobe Epilepsy

ERIC Educational Resources Information Center

Barkas, Lisa; Redhead, Edward; Taylor, Matthew; Shtaya, Anan; Hamilton, Derek A.; Gray, William P.

2012-01-01

Learning and memory dysfunction is the most common neuropsychological effect of mesial temporal lobe epilepsy, and because the underlying neurobiology is poorly understood, there are no pharmacological strategies to help restore memory function in these patients. We have demonstrated impairments in the acquisition of an allocentric spatial task,…

Gaining Insight by Transforming between Temporal Representations of Human Interaction

ERIC Educational Resources Information Center

Lund, Kristine; Quignard, Matthieu; Shaffer, David Williamson

2017-01-01

Recordings of human interaction data can be organized into temporal representations with different affordances. We use audio data of a learning-related discussion analyzed for its low-level emotional indicators and divided into four phases, each characterized by an overarching emotion. After arguing for the relevance of emotion to learning, we…

Temporal order and processing acuity of visual, auditory, and tactile perception in developmentally dyslexic young adults.

PubMed

Laasonen, M; Service, E; Virsu, V

2001-12-01

We studied the temporal acuity of 16 developmentally dyslexic young adults in three perceptual modalities. The control group consisted of 16 age- and IQ-matched normal readers. Two methods were used. In the temporal order judgment (TOJ) method, the stimuli were spatially separate fingertip indentations in the tactile system, tone bursts of different pitches in audition, and light flashes in vision. Participants indicated which one of two stimuli appeared first. To test temporal processing acuity (TPA), the same 8-msec nonspeech stimuli were presented as two parallel sequences of three stimulus pulses. Participants indicated, without order judgments, whether the pulses of the two sequences were simultaneous or nonsimultaneous. The dyslexic readers were somewhat inferior to the normal readers in all six temporal acuity tasks on average. Thus, our results agreed with the existence of a pansensory temporal processing deficit associated with dyslexia in a language with shallow orthography (Finnish) and in well-educated adults. The dyslexic and normal readers' temporal acuities overlapped so much, however, that acuity deficits alone would not allow dyslexia diagnoses. It was irrelevant whether or not the acuity task required order judgments. The groups did not differ in the nontemporal aspects of our experiments. Correlations between temporal acuity and reading-related tasks suggested that temporal acuity is associated with phonological awareness.

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.

On the limits of statistical learning: Intertrial contextual cueing is confined to temporally close contingencies.

PubMed

Thomas, Cyril; Didierjean, André; Maquestiaux, François; Goujon, Annabelle

2018-04-12

Since the seminal study by Chun and Jiang (Cognitive Psychology, 36, 28-71, 1998), a large body of research based on the contextual-cueing paradigm has shown that the cognitive system is capable of extracting statistical contingencies from visual environments. Most of these studies have focused on how individuals learn regularities found within an intratrial temporal window: A context predicts the target position within a given trial. However, Ono, Jiang, and Kawahara (Journal of Experimental Psychology, 31, 703-712, 2005) provided evidence of an intertrial implicit-learning effect when a distractor configuration in preceding trials N - 1 predicted the target location in trials N. The aim of the present study was to gain further insight into this effect by examining whether it occurs when predictive relationships are impeded by interfering task-relevant noise (Experiments 2 and 3) or by a long delay (Experiments 1, 4, and 5). Our results replicated the intertrial contextual-cueing effect, which occurred in the condition of temporally close contingencies. However, there was no evidence of integration across long-range spatiotemporal contingencies, suggesting a temporal limitation of statistical learning.

Bio-Inspired Computation: Clock-Free, Grid-Free, Scale-Free and Symbol Free

DTIC Science & Technology

2015-06-11

for Prediction Tasks in Spiking Neural Networks ." Artificial Neural Networks and Machine Learning–ICANN 2014. Springer, 2014. pp 635-642. Gibson, T...Henderson, JA and Wiles, J. "Predicting temporal sequences using an event-based spiking neural network incorporating learnable delays." IEEE...Adelaide (2014 Jan). Gibson, T and Wiles, J "Predicting temporal sequences using an event-based spiking neural network incorporating learnable delays" at

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…

Event related potentials to digit learning: tracking neurophysiologic changes accompanying recall performance.

PubMed

Jongsma, Marijtje L A; Gerrits, Niels J H M; van Rijn, Clementina M; Quiroga, Rodrigo Quian; Maes, Joseph H R

2012-07-01

The aim of this study was to track recall performance and event-related potentials (ERPs) across multiple trials in a digit-learning task. When a sequence is practiced by repetition, the number of errors typically decreases and a learning curve emerges. Until now, almost all ERP learning and memory research has focused on effects after a single presentation and, therefore, fails to capture the dynamic changes that characterize a learning process. However, the current study used a free-recall task in which a sequence of ten auditory digits was presented repeatedly. Auditory sequences of ten digits were presented in a logical order (control sequences) or in a random order (experimental sequences). Each sequence was presented six times. Participants had to reproduce the sequence after each presentation. EEG recordings were made at the time of the digit presentations. Recall performance for the control sequences was close to asymptote right after the first learning trial, whereas performance for the experimental sequences initially displayed primacy and recency effects. However, these latter effects gradually disappeared over the six repetitions, resulting in near-asymptotic recall performance for all digits. The performance improvement for the middle items of the list was accompanied by an increase in P300 amplitude, implying a close correspondence between this ERP component and the behavioral data. These results, which were discussed in the framework of theories on the functional significance of the P300 amplitude, add to the scarce empirical data on the dynamics of ERP responses in the process of intentional learning. Copyright © 2011 Elsevier B.V. All rights reserved.

Supporting Children in Mastering Temporal Relations of Stories: The TERENCE Learning Approach

ERIC Educational Resources Information Center

Di Mascio, Tania; Gennari, Rosella; Melonio, Alessandra; Tarantino, Laura

2016-01-01

Though temporal reasoning is a key factor for text comprehension, existing proposals for visualizing temporal information and temporal connectives proves to be inadequate for children, not only for their levels of abstraction and detail, but also because they rely on pre-existing mental models of time and temporal connectives, while in the case of…

Automated extraction and validation of children's gait parameters with the Kinect.

PubMed

Motiian, Saeid; Pergami, Paola; Guffey, Keegan; Mancinelli, Corrie A; Doretto, Gianfranco

2015-12-02

Gait analysis for therapy regimen prescription and monitoring requires patients to physically access clinics with specialized equipment. The timely availability of such infrastructure at the right frequency is especially important for small children. Besides being very costly, this is a challenge for many children living in rural areas. This is why this work develops a low-cost, portable, and automated approach for in-home gait analysis, based on the Microsoft Kinect. A robust and efficient method for extracting gait parameters is introduced, which copes with the high variability of noisy Kinect skeleton tracking data experienced across the population of young children. This is achieved by temporally segmenting the data with an approach based on coupling a probabilistic matching of stride template models, learned offline, with the estimation of their global and local temporal scaling. A preliminary study conducted on healthy children between 2 and 4 years of age is performed to analyze the accuracy, precision, repeatability, and concurrent validity of the proposed method against the GAITRite when measuring several spatial and temporal children's gait parameters. The method has excellent accuracy and good precision, with segmenting temporal sequences of body joint locations into stride and step cycles. Also, the spatial and temporal gait parameters, estimated automatically, exhibit good concurrent validity with those provided by the GAITRite, as well as very good repeatability. In particular, on a range of nine gait parameters, the relative and absolute agreements were found to be good and excellent, and the overall agreements were found to be good and moderate. This work enables and validates the automated use of the Kinect for children's gait analysis in healthy subjects. In particular, the approach makes a step forward towards developing a low-cost, portable, parent-operated in-home tool for clinicians assisting young children.

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.

It's time to fear! Interval timing in odor fear conditioning in rats

PubMed Central

Shionoya, Kiseko; Hegoburu, Chloé; Brown, Bruce L.; Sullivan, Regina M.; Doyère, Valérie; Mouly, Anne-Marie

2013-01-01

Time perception is crucial to goal attainment in humans and other animals, and interval timing also guides fundamental animal behaviors. Accumulating evidence has made it clear that in associative learning, temporal relations between events are encoded, and a few studies suggest this temporal learning occurs very rapidly. Most of these studies, however, have used methodologies that do not permit investigating the emergence of this temporal learning. In the present study we monitored respiration, ultrasonic vocalization (USV) and freezing behavior in rats in order to perform fine-grain analysis of fear responses during odor fear conditioning. In this paradigm an initially neutral odor (the conditioned stimulus, CS) predicted the arrival of an aversive unconditioned stimulus (US, footshock) at a fixed 20-s time interval. We first investigated the development of a temporal pattern of responding related to CS-US interval duration. The data showed that during acquisition with odor-shock pairings, a temporal response pattern of respiration rate was observed. Changing the CS-US interval duration from 20-s to 30-s resulted in a shift of the temporal response pattern appropriate to the new duration thus demonstrating that the pattern reflected the learning of the CS-US interval. A temporal pattern was also observed during a retention test 24 h later for both respiration and freezing measures, suggesting that the animals had stored the interval duration in long-term memory. We then investigated the role of intra-amygdalar dopaminergic transmission in interval timing. For this purpose, the D1 dopaminergic receptors antagonist SCH23390 was infused in the basolateral amygdala before conditioning. This resulted in an alteration of timing behavior, as reflected in differential temporal patterns between groups observed in a 24 h retention test off drug. The present data suggest that D1 receptor dopaminergic transmission within the amygdala is involved in temporal processing. PMID:24098277

Temporally Regular Musical Primes Facilitate Subsequent Syntax Processing in Children with Specific Language Impairment.

PubMed

Bedoin, Nathalie; Brisseau, Lucie; Molinier, Pauline; Roch, Didier; Tillmann, Barbara

2016-01-01

Children with developmental language disorders have been shown to be also impaired in rhythm and meter perception. Temporal processing and its link to language processing can be understood within the dynamic attending theory. An external stimulus can stimulate internal oscillators, which orient attention over time and drive speech signal segmentation to provide benefits for syntax processing, which is impaired in various patient populations. For children with Specific Language Impairment (SLI) and dyslexia, previous research has shown the influence of an external rhythmic stimulation on subsequent language processing by comparing the influence of a temporally regular musical prime to that of a temporally irregular prime. Here we tested whether the observed rhythmic stimulation effect is indeed due to a benefit provided by the regular musical prime (rather than a cost subsequent to the temporally irregular prime). Sixteen children with SLI and 16 age-matched controls listened to either a regular musical prime sequence or an environmental sound scene (without temporal regularities in event occurrence; i.e., referred to as "baseline condition") followed by grammatically correct and incorrect sentences. They were required to perform grammaticality judgments for each auditorily presented sentence. Results revealed that performance for the grammaticality judgments was better after the regular prime sequences than after the baseline sequences. Our findings are interpreted in the theoretical framework of the dynamic attending theory (Jones, 1976) and the temporal sampling (oscillatory) framework for developmental language disorders (Goswami, 2011). Furthermore, they encourage the use of rhythmic structures (even in non-verbal materials) to boost linguistic structure processing and outline perspectives for rehabilitation.

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.

An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning

PubMed Central

Potjans, Wiebke; Diesmann, Markus; Morrison, Abigail

2011-01-01

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

Learned value and object perception: Accelerated perception or biased decisions?

PubMed

Rajsic, Jason; Perera, Harendri; Pratt, Jay

2017-02-01

Learned value is known to bias visual search toward valued stimuli. However, some uncertainty exists regarding the stage of visual processing that is modulated by learned value. Here, we directly tested the effect of learned value on preattentive processing using temporal order judgments. Across four experiments, we imbued some stimuli with high value and some with low value, using a nonmonetary reward task. In Experiment 1, we replicated the value-driven distraction effect, validating our nonmonetary reward task. Experiment 2 showed that high-value stimuli, but not low-value stimuli, exhibit a prior-entry effect. Experiment 3, which reversed the temporal order judgment task (i.e., reporting which stimulus came second), showed no prior-entry effect, indicating that although a response bias may be present for high-value stimuli, they are still reported as appearing earlier. However, Experiment 4, using a simultaneity judgment task, showed no shift in temporal perception. Overall, our results support the conclusion that learned value biases perceptual decisions about valued stimuli without speeding preattentive stimulus processing.

Distributed Fading Memory for Stimulus Properties in the Primary Visual Cortex

PubMed Central

Singer, Wolf; Maass, Wolfgang

2009-01-01

It is currently not known how distributed neuronal responses in early visual areas carry stimulus-related information. We made multielectrode recordings from cat primary visual cortex and applied methods from machine learning in order to analyze the temporal evolution of stimulus-related information in the spiking activity of large ensembles of around 100 neurons. We used sequences of up to three different visual stimuli (letters of the alphabet) presented for 100 ms and with intervals of 100 ms or larger. Most of the information about visual stimuli extractable by sophisticated methods of machine learning, i.e., support vector machines with nonlinear kernel functions, was also extractable by simple linear classification such as can be achieved by individual neurons. New stimuli did not erase information about previous stimuli. The responses to the most recent stimulus contained about equal amounts of information about both this and the preceding stimulus. This information was encoded both in the discharge rates (response amplitudes) of the ensemble of neurons and, when using short time constants for integration (e.g., 20 ms), in the precise timing of individual spikes (≤∼20 ms), and persisted for several 100 ms beyond the offset of stimuli. The results indicate that the network from which we recorded is endowed with fading memory and is capable of performing online computations utilizing information about temporally sequential stimuli. This result challenges models assuming frame-by-frame analyses of sequential inputs. PMID:20027205

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…

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.

Phonological memory in sign language relies on the visuomotor neural system outside the left hemisphere language network.

PubMed

Kanazawa, Yuji; Nakamura, Kimihiro; Ishii, Toru; Aso, Toshihiko; Yamazaki, Hiroshi; Omori, Koichi

2017-01-01

Sign language is an essential medium for everyday social interaction for deaf people and plays a critical role in verbal learning. In particular, language development in those people should heavily rely on the verbal short-term memory (STM) via sign language. Most previous studies compared neural activations during signed language processing in deaf signers and those during spoken language processing in hearing speakers. For sign language users, it thus remains unclear how visuospatial inputs are converted into the verbal STM operating in the left-hemisphere language network. Using functional magnetic resonance imaging, the present study investigated neural activation while bilinguals of spoken and signed language were engaged in a sequence memory span task. On each trial, participants viewed a nonsense syllable sequence presented either as written letters or as fingerspelling (4-7 syllables in length) and then held the syllable sequence for 12 s. Behavioral analysis revealed that participants relied on phonological memory while holding verbal information regardless of the type of input modality. At the neural level, this maintenance stage broadly activated the left-hemisphere language network, including the inferior frontal gyrus, supplementary motor area, superior temporal gyrus and inferior parietal lobule, for both letter and fingerspelling conditions. Interestingly, while most participants reported that they relied on phonological memory during maintenance, direct comparisons between letters and fingers revealed strikingly different patterns of neural activation during the same period. Namely, the effortful maintenance of fingerspelling inputs relative to letter inputs activated the left superior parietal lobule and dorsal premotor area, i.e., brain regions known to play a role in visuomotor analysis of hand/arm movements. These findings suggest that the dorsal visuomotor neural system subserves verbal learning via sign language by relaying gestural inputs to the classical left-hemisphere language network.

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.

Knowledge-rich temporal relation identification and classification in clinical notes

PubMed Central

D’Souza, Jennifer; Ng, Vincent

2014-01-01

Motivation: We examine the task of temporal relation classification for the clinical domain. Our approach to this task departs from existing ones in that it is (i) ‘knowledge-rich’, employing sophisticated knowledge derived from discourse relations as well as both domain-independent and domain-dependent semantic relations, and (ii) ‘hybrid’, combining the strengths of rule-based and learning-based approaches. Evaluation results on the i2b2 Clinical Temporal Relations Challenge corpus show that our approach yields a 17–24% and 8–14% relative reduction in error over a state-of-the-art learning-based baseline system when gold-standard and automatically identified temporal relations are used, respectively. Database URL: http://www.hlt.utdallas.edu/~jld082000/temporal-relations/ PMID:25414383

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

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.

Conceptual knowledge in the interpretation of idioms.

PubMed

Nayak, N P; Gibbs, R W

1990-09-01

The authors examined how people determine the contextual appropriateness of idioms. In Experiment 1, idioms referring to the same temporal stage of a conceptual prototype were judged to be more similar in meaning than idioms referring to different temporal stages. In Experiment 2, idioms in a prototypical temporal sequence were more meaningful than idioms in sentences that violated the temporal sequence. In Experiment 3, idioms referring to the same stage of a conceptual prototype were differentiable on the basis of conceptual information. The conceptual coherence between idioms and contexts facilitated the processing speed of idioms in Experiment 4. Experiment 5 showed that speakers can recover the underlying conceptual metaphors that link an idiom to its figurative meaning. Experiment 6 showed that the metaphoric information reflected in the lexical makeup of idioms also determined the metaphoric appropriateness of idioms in certain contexts.

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

The Perceptions of Temporal Path Analysis of Learners' Self-Regulation on Learning Stress and Social Relationships in Junior High School

ERIC Educational Resources Information Center

Chang, Hsiu-Ju

2016-01-01

This research focus on the temporal path analysis of learning stress, test anxiety, peer stress (classmate relatedness), teacher relatedness, autonomy, and self-regulative performance in junior high school. Owing to the processes of self-determination always combines several negotiations with the interactive perceptions of personal experiences and…

Perceptual Learning of Intonation Contour Categories in Adults and 9- to 11-Year-Old Children: Adults Are More Narrow-Minded

ERIC Educational Resources Information Center

Kapatsinski, Vsevolod; Olejarczuk, Paul; Redford, Melissa A.

2017-01-01

We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns, whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of…

SSCC TD: A Serial and Simultaneous Configural-Cue Compound Stimuli Representation for Temporal Difference Learning

PubMed Central

Mondragón, Esther; Gray, Jonathan; Alonso, Eduardo; Bonardi, Charlotte; Jennings, Dómhnall J.

2014-01-01

This paper presents a novel representational framework for the Temporal Difference (TD) model of learning, which allows the computation of configural stimuli – cumulative compounds of stimuli that generate perceptual emergents known as configural cues. This Simultaneous and Serial Configural-cue Compound Stimuli Temporal Difference model (SSCC TD) can model both simultaneous and serial stimulus compounds, as well as compounds including the experimental context. This modification significantly broadens the range of phenomena which the TD paradigm can explain, and allows it to predict phenomena which traditional TD solutions cannot, particularly effects that depend on compound stimuli functioning as a whole, such as pattern learning and serial structural discriminations, and context-related effects. PMID:25054799

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.

Randomized controlled trial evaluating the temporal effects of high-intensity exercise on learning, short-term and long-term memory, and prospective memory.

PubMed

Frith, Emily; Sng, Eveleen; Loprinzi, Paul D

2017-11-01

The broader purpose of this study was to examine the temporal effects of high-intensity exercise on learning, short-term and long-term retrospective memory and prospective memory. Among a sample of 88 young adult participants, 22 were randomized into one of four different groups: exercise before learning, control group, exercise during learning, and exercise after learning. The retrospective assessments (learning, short-term and long-term memory) were assessed using the Rey Auditory Verbal Learning Test. Long-term memory including a 20-min and 24-hr follow-up assessment. Prospective memory was assessed using a time-based procedure by having participants contact (via phone) the researchers at a follow-up time period. The exercise stimulus included a 15-min bout of progressive maximal exertion treadmill exercise. High-intensity exercise prior to memory encoding (vs. exercise during memory encoding or consolidation) was effective in enhancing long-term memory (for both 20-min and 24-h follow-up assessments). We did not observe a differential temporal effect of high-intensity exercise on short-term memory (immediate post-memory encoding), learning or prospective memory. The timing of high-intensity exercise may play an important role in facilitating long-term memory. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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

Optimized two-frequency phase-measuring-profilometry light-sensor temporal-noise sensitivity.

PubMed

Li, Jielin; Hassebrook, Laurence G; Guan, Chun

2003-01-01

Temporal frame-to-frame noise in multipattern structured light projection can significantly corrupt depth measurement repeatability. We present a rigorous stochastic analysis of phase-measuring-profilometry temporal noise as a function of the pattern parameters and the reconstruction coefficients. The analysis is used to optimize the two-frequency phase measurement technique. In phase-measuring profilometry, a sequence of phase-shifted sine-wave patterns is projected onto a surface. In two-frequency phase measurement, two sets of pattern sequences are used. The first, low-frequency set establishes a nonambiguous depth estimate, and the second, high-frequency set is unwrapped, based on the low-frequency estimate, to obtain an accurate depth estimate. If the second frequency is too low, then depth error is caused directly by temporal noise in the phase measurement. If the second frequency is too high, temporal noise triggers ambiguous unwrapping, resulting in depth measurement error. We present a solution for finding the second frequency, where intensity noise variance is at its minimum.

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.

Corticostriatal circuit mechanisms of value-based action selection: Implementation of reinforcement learning algorithms and beyond.

PubMed

Morita, Kenji; Jitsev, Jenia; Morrison, Abigail

2016-09-15

Value-based action selection has been suggested to be realized in the corticostriatal local circuits through competition among neural populations. In this article, we review theoretical and experimental studies that have constructed and verified this notion, and provide new perspectives on how the local-circuit selection mechanisms implement reinforcement learning (RL) algorithms and computations beyond them. The striatal neurons are mostly inhibitory, and lateral inhibition among them has been classically proposed to realize "Winner-Take-All (WTA)" selection of the maximum-valued action (i.e., 'max' operation). Although this view has been challenged by the revealed weakness, sparseness, and asymmetry of lateral inhibition, which suggest more complex dynamics, WTA-like competition could still occur on short time scales. Unlike the striatal circuit, the cortical circuit contains recurrent excitation, which may enable retention or temporal integration of information and probabilistic "soft-max" selection. The striatal "max" circuit and the cortical "soft-max" circuit might co-implement an RL algorithm called Q-learning; the cortical circuit might also similarly serve for other algorithms such as SARSA. In these implementations, the cortical circuit presumably sustains activity representing the executed action, which negatively impacts dopamine neurons so that they can calculate reward-prediction-error. Regarding the suggested more complex dynamics of striatal, as well as cortical, circuits on long time scales, which could be viewed as a sequence of short WTA fragments, computational roles remain open: such a sequence might represent (1) sequential state-action-state transitions, constituting replay or simulation of the internal model, (2) a single state/action by the whole trajectory, or (3) probabilistic sampling of state/action. Copyright © 2016. Published by Elsevier B.V.

Learning by observation: insights from Williams syndrome.

PubMed

Foti, Francesca; Menghini, Deny; Mandolesi, Laura; Federico, Francesca; Vicari, Stefano; Petrosini, Laura

2013-01-01

Observing another person performing a complex action accelerates the observer's acquisition of the same action and limits the time-consuming process of learning by trial and error. Observational learning makes an interesting and potentially important topic in the developmental domain, especially when disorders are considered. The implications of studies aimed at clarifying whether and how this form of learning is spared by pathology are manifold. We focused on a specific population with learning and intellectual disabilities, the individuals with Williams syndrome. The performance of twenty-eight individuals with Williams syndrome was compared with that of mental age- and gender-matched thirty-two typically developing children on tasks of learning of a visuo-motor sequence by observation or by trial and error. Regardless of the learning modality, acquiring the correct sequence involved three main phases: a detection phase, in which participants discovered the correct sequence and learned how to perform the task; an exercise phase, in which they reproduced the sequence until performance was error-free; an automatization phase, in which by repeating the error-free sequence they became accurate and speedy. Participants with Williams syndrome beneficiated of observational training (in which they observed an actor detecting the visuo-motor sequence) in the detection phase, while they performed worse than typically developing children in the exercise and automatization phases. Thus, by exploiting competencies learned by observation, individuals with Williams syndrome detected the visuo-motor sequence, putting into action the appropriate procedural strategies. Conversely, their impaired performances in the exercise phases appeared linked to impaired spatial working memory, while their deficits in automatization phases to deficits in processes increasing efficiency and speed of the response. Overall, observational experience was advantageous for acquiring competencies, since it primed subjects' interest in the actions to be performed and functioned as a catalyst for executed action.

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.

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…

Influence of motion on face recognition.

PubMed

Bonfiglio, Natale S; Manfredi, Valentina; Pessa, Eliano

2012-02-01

The influence of motion information and temporal associations on recognition of non-familiar faces was investigated using two groups which performed a face recognition task. One group was presented with regular temporal sequences of face views designed to produce the impression of motion of the face rotating in depth, the other group with random sequences of the same views. In one condition, participants viewed the sequences of the views in rapid succession with a negligible interstimulus interval (ISI). This condition was characterized by three different presentation times. In another condition, participants were presented a sequence with a 1-sec. ISI among the views. That regular sequences of views with a negligible ISI and a shorter presentation time were hypothesized to give rise to better recognition, related to a stronger impression of face rotation. Analysis of data from 45 participants showed a shorter presentation time was associated with significantly better accuracy on the recognition task; however, differences between performances associated with regular and random sequences were not significant.

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

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

Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding

PubMed Central

Gardner, Brian; Grüning, André

2016-01-01

Precise spike timing as a means to encode information in neural networks is biologically supported, and is advantageous over frequency-based codes by processing input features on a much shorter time-scale. For these reasons, much recent attention has been focused on the development of supervised learning rules for spiking neural networks that utilise a temporal coding scheme. However, despite significant progress in this area, there still lack rules that have a theoretical basis, and yet can be considered biologically relevant. Here we examine the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. As part of our analysis we examine two spike-based learning methods: one of which relies on an instantaneous error signal to modify synaptic weights in a network (INST rule), and the other one relying on a filtered error signal for smoother synaptic weight modifications (FILT rule). We test the accuracy of the solutions provided by each rule with respect to their temporal encoding precision, and then measure the maximum number of input patterns they can learn to memorise using the precise timings of individual spikes as an indication of their storage capacity. Our results demonstrate the high performance of the FILT rule in most cases, underpinned by the rule’s error-filtering mechanism, which is predicted to provide smooth convergence towards a desired solution during learning. We also find the FILT rule to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision. In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule, but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism. PMID:27532262

Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding.

PubMed

Gardner, Brian; Grüning, André

2016-01-01

Precise spike timing as a means to encode information in neural networks is biologically supported, and is advantageous over frequency-based codes by processing input features on a much shorter time-scale. For these reasons, much recent attention has been focused on the development of supervised learning rules for spiking neural networks that utilise a temporal coding scheme. However, despite significant progress in this area, there still lack rules that have a theoretical basis, and yet can be considered biologically relevant. Here we examine the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. As part of our analysis we examine two spike-based learning methods: one of which relies on an instantaneous error signal to modify synaptic weights in a network (INST rule), and the other one relying on a filtered error signal for smoother synaptic weight modifications (FILT rule). We test the accuracy of the solutions provided by each rule with respect to their temporal encoding precision, and then measure the maximum number of input patterns they can learn to memorise using the precise timings of individual spikes as an indication of their storage capacity. Our results demonstrate the high performance of the FILT rule in most cases, underpinned by the rule's error-filtering mechanism, which is predicted to provide smooth convergence towards a desired solution during learning. We also find the FILT rule to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision. In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule, but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.

Constraint-based Temporal Reasoning with Preferences

NASA Technical Reports Server (NTRS)

Khatib, Lina; Morris, Paul; Morris, Robert; Rossi, Francesca; Sperduti, Alessandro; Venable, K. Brent

2005-01-01

Often we need to work in scenarios where events happen over time and preferences are associated to event distances and durations. Soft temporal constraints allow one to describe in a natural way problems arising in such scenarios. In general, solving soft temporal problems require exponential time in the worst case, but there are interesting subclasses of problems which are polynomially solvable. In this paper we identify one of such subclasses giving tractability results. Moreover, we describe two solvers for this class of soft temporal problems, and we show some experimental results. The random generator used to build the problems on which tests are performed is also described. We also compare the two solvers highlighting the tradeoff between performance and robustness. Sometimes, however, temporal local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem. To model everything in a uniform way via local preferences only, and also to take advantage of the existing constraint solvers which exploit only local preferences, we show that machine learning techniques can be useful in this respect. In particular, we present a learning module based on a gradient descent technique which induces local temporal preferences from global ones. We also show the behavior of the learning module on randomly-generated examples.

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…

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…

New Semantic Learning in Patients With Large Medial Temporal Lobe Lesions

PubMed Central

Bayley, P.J.; O'Reilly, R.C.; Curran, T.; Squire, L.R.

2008-01-01

Two patients with large lesions of the medial temporal lobe were given four tests of semantic knowledge that could only have been acquired after the onset of their amnesia. In contrast to previous studies of postmorbid semantic learning, correct answers could be based on a simple, nonspecific sense of familiarity about single words, faces, or objects. According to recent computational models (for example, Norman and O'Reilly (2003) Psychol Rev 110:611–646), this characteristic should be optimal for detecting the kind of semantic learning that might be supported directly by the neocortex. Both patients exhibited some capacity for new learning, albeit at a level substantially below control performances. Notably, the correct answers appeared to reflect declarative memory. It was not the case that the correct answers simply popped out in some automatic way in the absence of any additional knowledge about the items. Rather, the few correct choices made by the patients tended to be accompanied by additional information about the chosen items, and the available knowledge appeared to be similar qualitatively to the kind of factual knowledge that healthy individuals gradually acquire over the years. The results are consistent with the idea that neocortical structures outside the medial temporal lobe are able to support some semantic learning, albeit to a very limited extent. Alternatively, the small amount of learning detected in the present study could depend on tissue within the posterior medial temporal lobe that remains intact in both patients. PMID:18306299

Learning of Syllable-Object Relations by Preverbal Infants: The Role of Temporal Synchrony and Syllable Distinctiveness

ERIC Educational Resources Information Center

Gogate, Lakshmi J.

2010-01-01

The role of temporal synchrony and syllable distinctiveness in preverbal infants' learning of word-object relations was investigated. In Experiment 1, 7- and 8-month-olds (N=64) were habituated under conditions where two "similar-sounding" syllables, /tah/ and /gah/, were spoken simultaneously with the motions of one of two sets of…

Lossless Video Sequence Compression Using Adaptive Prediction

NASA Technical Reports Server (NTRS)

Li, Ying; Sayood, Khalid

2007-01-01

We present an adaptive lossless video compression algorithm based on predictive coding. The proposed algorithm exploits temporal, spatial, and spectral redundancies in a backward adaptive fashion with extremely low side information. The computational complexity is further reduced by using a caching strategy. We also study the relationship between the operational domain for the coder (wavelet or spatial) and the amount of temporal and spatial redundancy in the sequence being encoded. Experimental results show that the proposed scheme provides significant improvements in compression efficiencies.

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…

Use of Unpalatable Forages by Ruminants: The Influence of Experience with the Biophysical and Social Environment.

PubMed

Distel, Roberto A; Villalba, Juan J

2018-04-14

Unpalatable forage resources (low nutrient density, potentially toxic metabolites) are widespread and represent a challenge for ruminant nutrition, health, and welfare. Our objective was to synthesize the role of biophysical and social experience on the use of unpalatable forages by ruminants, and highlight derived behavioural solutions for the well-being of soils, plants, and animals. Environmental experiences early in life modulate gene expression and promote learning, which alters morpho-physiological and psychological mechanisms that modify behavioural responses and change food and habitat selection. In this process, ruminants can become better adapted to the habitat where they are reared. Moreover, experiential learning provides flexibility in diet selection, which is critical for changing foraging environments. Learned associations between unpalatable and palatable foods, if ingested in appropriate amounts, sequence, and close temporal association, induce the development of preference for the former type of food. In this way, a more uniform use of resources can be achieved from the landscape level down to the individual plant, with the associated benefits to ecosystem integrity and stability. Ruminants can also learn the medicinal benefits of ingesting foods with toxins (e.g., condensed tannins and saponins with antiparasitic properties). This knowledge on behavioural processes can be translated into behavioural applications that provide low-cost solutions to many challenges that producers face in managing sustainable livestock production systems.

A new supervised learning algorithm for spiking neurons.

PubMed

Xu, Yan; Zeng, Xiaoqin; Zhong, Shuiming

2013-06-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by the precise firing times of spikes. If only running time is considered, the supervised learning for a spiking neuron is equivalent to distinguishing the times of desired output spikes and the other time during the running process of the neuron through adjusting synaptic weights, which can be regarded as a classification problem. Based on this idea, this letter proposes a new supervised learning method for spiking neurons with temporal encoding; it first transforms the supervised learning into a classification problem and then solves the problem by using the perceptron learning rule. The experiment results show that the proposed method has higher learning accuracy and efficiency over the existing learning methods, so it is more powerful for solving complex and real-time problems.

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.

The Temporal Dynamics of Arc Expression Regulate Cognitive Flexibility.

PubMed

Wall, Mark J; Collins, Dawn R; Chery, Samantha L; Allen, Zachary D; Pastuzyn, Elissa D; George, Arlene J; Nikolova, Viktoriya D; Moy, Sheryl S; Philpot, Benjamin D; Shepherd, Jason D; Müller, Jürgen; Ehlers, Michael D; Mabb, Angela M; Corrêa, Sonia A L

2018-06-27

Neuronal activity regulates the transcription and translation of the immediate-early gene Arc/Arg3.1, a key mediator of synaptic plasticity. Proteasome-dependent degradation of Arc tightly limits its temporal expression, yet the significance of this regulation remains unknown. We disrupted the temporal control of Arc degradation by creating an Arc knockin mouse (ArcKR) where the predominant Arc ubiquitination sites were mutated. ArcKR mice had intact spatial learning but showed specific deficits in selecting an optimal strategy during reversal learning. This cognitive inflexibility was coupled to changes in Arc mRNA and protein expression resulting in a reduced threshold to induce mGluR-LTD and enhanced mGluR-LTD amplitude. These findings show that the abnormal persistence of Arc protein limits the dynamic range of Arc signaling pathways specifically during reversal learning. Our work illuminates how the precise temporal control of activity-dependent molecules, such as Arc, regulates synaptic plasticity and is crucial for cognition. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Deriving video content type from HEVC bitstream semantics

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos; Goma, Sergio R.

2014-05-01

As network service providers seek to improve customer satisfaction and retention levels, they are increasingly moving from traditional quality of service (QoS) driven delivery models to customer-centred quality of experience (QoE) delivery models. QoS models only consider metrics derived from the network however, QoE models also consider metrics derived from within the video sequence itself. Various spatial and temporal characteristics of a video sequence have been proposed, both individually and in combination, to derive methods of classifying video content either on a continuous scale or as a set of discrete classes. QoE models can be divided into three broad categories, full reference, reduced reference and no-reference models. Due to the need to have the original video available at the client for comparison, full reference metrics are of limited practical value in adaptive real-time video applications. Reduced reference metrics often require metadata to be transmitted with the bitstream, while no-reference metrics typically operate in the decompressed domain at the client side and require significant processing to extract spatial and temporal features. This paper proposes a heuristic, no-reference approach to video content classification which is specific to HEVC encoded bitstreams. The HEVC encoder already makes use of spatial characteristics to determine partitioning of coding units and temporal characteristics to determine the splitting of prediction units. We derive a function which approximates the spatio-temporal characteristics of the video sequence by using the weighted averages of the depth at which the coding unit quadtree is split and the prediction mode decision made by the encoder to estimate spatial and temporal characteristics respectively. Since the video content type of a sequence is determined by using high level information parsed from the video stream, spatio-temporal characteristics are identified without the need for full decoding and can be used in a timely manner to aid decision making in QoE oriented adaptive real time streaming.

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.…

Attentional episodes in visual perception

PubMed Central

Wyble, Brad; Potter, Mary C; Bowman, Howard; Nieuwenstein, Mark

2011-01-01

Is one's temporal perception of the world truly as seamless as it appears? This paper presents a computationally motivated theory suggesting that visual attention samples information from temporal episodes (episodic Simultaneous Type/ Serial Token model or eSTST; Wyble et al 2009a). Breaks between these episodes are punctuated by periods of suppressed attention, better known as the attentional blink (Raymond, Shapiro & Arnell 1992). We test predictions from this model and demonstrate that subjects are able to report more letters from a sequence of four targets presented in a dense temporal cluster, than from a sequence of four targets that are interleaved with non-targets. However, this superior report accuracy comes at a cost in impaired temporal order perception. Further experiments explore the dynamics of multiple episodes, and the boundary conditions that trigger episodic breaks. Finally, we contrast the importance of attentional control, limited resources and memory capacity constructs in the model. PMID:21604913

GA-based fuzzy reinforcement learning for control of a magnetic bearing system.

PubMed

Lin, C T; Jou, C P

2000-01-01

This paper proposes a TD (temporal difference) and GA (genetic algorithm)-based reinforcement (TDGAR) learning method and applies it to the control of a real magnetic bearing system. The TDGAR learning scheme is a new hybrid GA, which integrates the TD prediction method and the GA to perform the reinforcement learning task. The TDGAR learning system is composed of two integrated feedforward networks. One neural network acts as a critic network to guide the learning of the other network (the action network) which determines the outputs (actions) of the TDGAR learning system. The action network can be a normal neural network or a neural fuzzy network. Using the TD prediction method, the critic network can predict the external reinforcement signal and provide a more informative internal reinforcement signal to the action network. The action network uses the GA to adapt itself according to the internal reinforcement signal. The key concept of the TDGAR learning scheme is to formulate the internal reinforcement signal as the fitness function for the GA such that the GA can evaluate the candidate solutions (chromosomes) regularly, even during periods without external feedback from the environment. This enables the GA to proceed to new generations regularly without waiting for the arrival of the external reinforcement signal. This can usually accelerate the GA learning since a reinforcement signal may only be available at a time long after a sequence of actions has occurred in the reinforcement learning problem. The proposed TDGAR learning system has been used to control an active magnetic bearing (AMB) system in practice. A systematic design procedure is developed to achieve successful integration of all the subsystems including magnetic suspension, mechanical structure, and controller training. The results show that the TDGAR learning scheme can successfully find a neural controller or a neural fuzzy controller for a self-designed magnetic bearing system.

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…

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

Transforming e-Learning into ee-Learning: The Centrality of Sociocultural Participation

ERIC Educational Resources Information Center

Schneider, Sandra B.; Evans, Michael A.

2008-01-01

Traditional e-learning efforts use information communication technologies to create and support educational opportunities that are not constrained by temporal and spatial considerations. The focus of ee-learning is to couple e-learning's approach with experiential education models that employ service-learning methodologies and with…

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

A neural model of normal and abnormal learning and memory consolidation: adaptively timed conditioning, hippocampus, amnesia, neurotrophins, and consciousness.

PubMed

Franklin, Daniel J; Grossberg, Stephen

2017-02-01

How do the hippocampus and amygdala interact with thalamocortical systems to regulate cognitive and cognitive-emotional learning? Why do lesions of thalamus, amygdala, hippocampus, and cortex have differential effects depending on the phase of learning when they occur? In particular, why is the hippocampus typically needed for trace conditioning, but not delay conditioning, and what do the exceptions reveal? Why do amygdala lesions made before or immediately after training decelerate conditioning while those made later do not? Why do thalamic or sensory cortical lesions degrade trace conditioning more than delay conditioning? Why do hippocampal lesions during trace conditioning experiments degrade recent but not temporally remote learning? Why do orbitofrontal cortical lesions degrade temporally remote but not recent or post-lesion learning? How is temporally graded amnesia caused by ablation of prefrontal cortex after memory consolidation? How are attention and consciousness linked during conditioning? How do neurotrophins, notably brain-derived neurotrophic factor (BDNF), influence memory formation and consolidation? Is there a common output path for learned performance? A neural model proposes a unified answer to these questions that overcome problems of alternative memory models.

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).

UML and Model Checking

NASA Technical Reports Server (NTRS)

Schneider, F.

1999-01-01

UML use cases conceptually identify function points or major requirements that a software system must satisfy. Sequence diagrams expand each use case to show in temporal sequence a more detailed notion of intended system behavior.

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.

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

Towards an explicit account of implicit learning.

PubMed

Forkstam, Christian; Petersson, Karl Magnus

2005-08-01

The human brain supports acquisition mechanisms that can extract structural regularities implicitly from experience without the induction of an explicit model. Reber defined the process by which an individual comes to respond appropriately to the statistical structure of the input ensemble as implicit learning. He argued that the capacity to generalize to new input is based on the acquisition of abstract representations that reflect underlying structural regularities in the acquisition input. We focus this review of the implicit learning literature on studies published during 2004 and 2005. We will not review studies of repetition priming ('implicit memory'). Instead we focus on two commonly used experimental paradigms: the serial reaction time task and artificial grammar learning. Previous comprehensive reviews can be found in Seger's 1994 article and the Handbook of Implicit Learning. Emerging themes include the interaction between implicit and explicit processes, the role of the medial temporal lobe, developmental aspects of implicit learning, age-dependence, the role of sleep and consolidation. The attempts to characterize the interaction between implicit and explicit learning are promising although not well understood. The same can be said about the role of sleep and consolidation. Despite the fact that lesion studies have relatively consistently suggested that the medial temporal lobe memory system is not necessary for implicit learning, a number of functional magnetic resonance studies have reported medial temporal lobe activation in implicit learning. This issue merits further research. Finally, the clinical relevance of implicit learning remains to be determined.

Mathematical Modeling and Evaluation of Human Motions in Physical Therapy Using Mixture Density Neural Networks

PubMed Central

Vakanski, A; Ferguson, JM; Lee, S

2016-01-01

Objective The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient’s exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient’s physician with recommendations for improvement. Methods The modeling approach employs an artificial neural network, consisting of layers of recurrent neuron units and layers of neuron units for estimating a mixture density function over the spatio-temporal dependencies within the human motion sequences. Input data are sequences of motions related to a prescribed exercise by a physiotherapist to a patient, and recorded with a motion capture system. An autoencoder subnet is employed for reducing the dimensionality of captured sequences of human motions, complemented with a mixture density subnet for probabilistic modeling of the motion data using a mixture of Gaussian distributions. Results The proposed neural network architecture produced a model for sets of human motions represented with a mixture of Gaussian density functions. The mean log-likelihood of observed sequences was employed as a performance metric in evaluating the consistency of a subject’s performance relative to the reference dataset of motions. A publically available dataset of human motions captured with Microsoft Kinect was used for validation of the proposed method. Conclusion The article presents a novel approach for modeling and evaluation of human motions with a potential application in home-based physical therapy and rehabilitation. The described approach employs the recent progress in the field of machine learning and neural networks in developing a parametric model of human motions, by exploiting the representational power of these algorithms to encode nonlinear input-output dependencies over long temporal horizons. PMID:28111643

Mathematical Modeling and Evaluation of Human Motions in Physical Therapy Using Mixture Density Neural Networks.

PubMed

Vakanski, A; Ferguson, J M; Lee, S

2016-12-01

The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient's exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient's physician with recommendations for improvement. The modeling approach employs an artificial neural network, consisting of layers of recurrent neuron units and layers of neuron units for estimating a mixture density function over the spatio-temporal dependencies within the human motion sequences. Input data are sequences of motions related to a prescribed exercise by a physiotherapist to a patient, and recorded with a motion capture system. An autoencoder subnet is employed for reducing the dimensionality of captured sequences of human motions, complemented with a mixture density subnet for probabilistic modeling of the motion data using a mixture of Gaussian distributions. The proposed neural network architecture produced a model for sets of human motions represented with a mixture of Gaussian density functions. The mean log-likelihood of observed sequences was employed as a performance metric in evaluating the consistency of a subject's performance relative to the reference dataset of motions. A publically available dataset of human motions captured with Microsoft Kinect was used for validation of the proposed method. The article presents a novel approach for modeling and evaluation of human motions with a potential application in home-based physical therapy and rehabilitation. The described approach employs the recent progress in the field of machine learning and neural networks in developing a parametric model of human motions, by exploiting the representational power of these algorithms to encode nonlinear input-output dependencies over long temporal horizons.

Processing of Natural Echolocation Sequences in the Inferior Colliculus of Seba’s Fruit Eating Bat, Carollia perspicillata

PubMed Central

Kordes, Sebastian; Kössl, Manfred

2017-01-01

Abstract For the purpose of orientation, echolocating bats emit highly repetitive and spatially directed sonar calls. Echoes arising from call reflections are used to create an acoustic image of the environment. The inferior colliculus (IC) represents an important auditory stage for initial processing of echolocation signals. The present study addresses the following questions: (1) how does the temporal context of an echolocation sequence mimicking an approach flight of an animal affect neuronal processing of distance information to echo delays? (2) how does the IC process complex echolocation sequences containing echo information from multiple objects (multiobject sequence)? Here, we conducted neurophysiological recordings from the IC of ketamine-anaesthetized bats of the species Carollia perspicillata and compared the results from the IC with the ones from the auditory cortex (AC). Neuronal responses to an echolocation sequence was suppressed when compared to the responses to temporally isolated and randomized segments of the sequence. The neuronal suppression was weaker in the IC than in the AC. In contrast to the cortex, the time course of the acoustic events is reflected by IC activity. In the IC, suppression sharpens the neuronal tuning to specific call-echo elements and increases the signal-to-noise ratio in the units’ responses. When presenting multiple-object sequences, despite collicular suppression, the neurons responded to each object-specific echo. The latter allows parallel processing of multiple echolocation streams at the IC level. Altogether, our data suggests that temporally-precise neuronal responses in the IC could allow fast and parallel processing of multiple acoustic streams. PMID:29242823

Processing of Natural Echolocation Sequences in the Inferior Colliculus of Seba's Fruit Eating Bat, Carollia perspicillata.

PubMed

Beetz, M Jerome; Kordes, Sebastian; García-Rosales, Francisco; Kössl, Manfred; Hechavarría, Julio C

2017-01-01

For the purpose of orientation, echolocating bats emit highly repetitive and spatially directed sonar calls. Echoes arising from call reflections are used to create an acoustic image of the environment. The inferior colliculus (IC) represents an important auditory stage for initial processing of echolocation signals. The present study addresses the following questions: (1) how does the temporal context of an echolocation sequence mimicking an approach flight of an animal affect neuronal processing of distance information to echo delays? (2) how does the IC process complex echolocation sequences containing echo information from multiple objects (multiobject sequence)? Here, we conducted neurophysiological recordings from the IC of ketamine-anaesthetized bats of the species Carollia perspicillata and compared the results from the IC with the ones from the auditory cortex (AC). Neuronal responses to an echolocation sequence was suppressed when compared to the responses to temporally isolated and randomized segments of the sequence. The neuronal suppression was weaker in the IC than in the AC. In contrast to the cortex, the time course of the acoustic events is reflected by IC activity. In the IC, suppression sharpens the neuronal tuning to specific call-echo elements and increases the signal-to-noise ratio in the units' responses. When presenting multiple-object sequences, despite collicular suppression, the neurons responded to each object-specific echo. The latter allows parallel processing of multiple echolocation streams at the IC level. Altogether, our data suggests that temporally-precise neuronal responses in the IC could allow fast and parallel processing of multiple acoustic streams.

Object-location training elicits an overlapping but temporally distinct transcriptional profile from contextual fear conditioning.

PubMed

Poplawski, Shane G; Schoch, Hannah; Wimmer, Mathieu; Hawk, Joshua D; Walsh, Jennifer L; Giese, Karl P; Abel, Ted

2014-12-01

Hippocampus-dependent learning is known to induce changes in gene expression, but information on gene expression differences between different learning paradigms that require the hippocampus is limited. The bulk of studies investigating RNA expression after learning use the contextual fear conditioning task, which couples a novel environment with a footshock. Although contextual fear conditioning has been useful in discovering gene targets, gene expression after spatial memory tasks has received less attention. In this study, we used the object-location memory task and studied gene expression at two time points after learning in a high-throughput manner using a microfluidic qPCR approach. We found that expression of the classic immediate-early genes changes after object-location training in a fashion similar to that observed after contextual fear conditioning. However, the temporal dynamics of gene expression are different between the two tasks, with object-location memory producing gene expression changes that last at least 2 hours. Our findings indicate that different training paradigms may give rise to distinct temporal dynamics of gene expression after learning. Copyright © 2014 Elsevier Inc. All rights reserved.

Object-Location Training Elicits an Overlapping but Temporally Distinct Transcriptional Profile from Contextual Fear Conditioning

PubMed Central

Wimmer, Mathieu; Hawk, Joshua D.; Walsh, Jennifer L.; Giese, Karl P.; Abel, Ted

2014-01-01

Hippocampus-dependent learning is known to induce changes in gene expression, but information on gene expression differences between different learning paradigms that require the hippocampus is limited. The bulk of studies investigating RNA expression after learning use the contextual fear conditioning task, which couples a novel environment with a footshock. Although contextual fear conditioning has been useful in discovering gene targets, gene expression after spatial memory tasks has received less attention. In this study, we used the object-location memory task and studied gene expression at two time points after learning in a high-throughput manner using a microfluidic qPCR approach. We found that expression of the classic immediate-early genes changes after object-location training in a fashion similar to that observed after contextual fear conditioning. However, the temporal dynamics of gene expression are different between the two tasks, with object-location memory producing gene expression changes that last at least 2 hours. Our findings indicate that different training paradigms may give rise to distinct temporal dynamics of gene expression after learning. PMID:25242102

The neural dynamics of song syntax in songbirds

NASA Astrophysics Data System (ADS)

Jin, Dezhe

2010-03-01

Songbird is ``the hydrogen atom'' of the neuroscience of complex, learned vocalizations such as human speech. Songs of Bengalese finch consist of sequences of syllables. While syllables are temporally stereotypical, syllable sequences can vary and follow complex, probabilistic syntactic rules, which are rudimentarily similar to grammars in human language. Songbird brain is accessible to experimental probes, and is understood well enough to construct biologically constrained, predictive computational models. In this talk, I will discuss the structure and dynamics of neural networks underlying the stereotypy of the birdsong syllables and the flexibility of syllable sequences. Recent experiments and computational models suggest that a syllable is encoded in a chain network of projection neurons in premotor nucleus HVC (proper name). Precisely timed spikes propagate along the chain, driving vocalization of the syllable through downstream nuclei. Through a computational model, I show that that variable syllable sequences can be generated through spike propagations in a network in HVC in which the syllable-encoding chain networks are connected into a branching chain pattern. The neurons mutually inhibit each other through the inhibitory HVC interneurons, and are driven by external inputs from nuclei upstream of HVC. At a branching point that connects the final group of a chain to the first groups of several chains, the spike activity selects one branch to continue the propagation. The selection is probabilistic, and is due to the winner-take-all mechanism mediated by the inhibition and noise. The model predicts that the syllable sequences statistically follow partially observable Markov models. Experimental results supporting this and other predictions of the model will be presented. We suggest that the syntax of birdsong syllable sequences is embedded in the connection patterns of HVC projection neurons.

Temporal structure of motor variability is dynamically regulated and predicts motor learning ability.

PubMed

Wu, Howard G; Miyamoto, Yohsuke R; Gonzalez Castro, Luis Nicolas; Ölveczky, Bence P; Smith, Maurice A

2014-02-01

Individual differences in motor learning ability are widely acknowledged, yet little is known about the factors that underlie them. Here we explore whether movement-to-movement variability in motor output, a ubiquitous if often unwanted characteristic of motor performance, predicts motor learning ability. Surprisingly, we found that higher levels of task-relevant motor variability predicted faster learning both across individuals and across tasks in two different paradigms, one relying on reward-based learning to shape specific arm movement trajectories and the other relying on error-based learning to adapt movements in novel physical environments. We proceeded to show that training can reshape the temporal structure of motor variability, aligning it with the trained task to improve learning. These results provide experimental support for the importance of action exploration, a key idea from reinforcement learning theory, showing that motor variability facilitates motor learning in humans and that our nervous systems actively regulate it to improve learning.

Temporal structure of motor variability is dynamically regulated and predicts motor learning ability

PubMed Central

Wu, Howard G; Miyamoto, Yohsuke R; Castro, Luis Nicolas Gonzalez; Ölveczky, Bence P; Smith, Maurice A

2015-01-01

Individual differences in motor learning ability are widely acknowledged, yet little is known about the factors that underlie them. Here we explore whether movement-to-movement variability in motor output, a ubiquitous if often unwanted characteristic of motor performance, predicts motor learning ability. Surprisingly, we found that higher levels of task-relevant motor variability predicted faster learning both across individuals and across tasks in two different paradigms, one relying on reward-based learning to shape specific arm movement trajectories and the other relying on error-based learning to adapt movements in novel physical environments. We proceeded to show that training can reshape the temporal structure of motor variability, aligning it with the trained task to improve learning. These results provide experimental support for the importance of action exploration, a key idea from reinforcement learning theory, showing that motor variability facilitates motor learning in humans and that our nervous systems actively regulate it to improve learning. PMID:24413700

Spatiotemporal Processing in Crossmodal Interactions for Perception of the External World: A Review

PubMed Central

Hidaka, Souta; Teramoto, Wataru; Sugita, Yoichi

2015-01-01

Research regarding crossmodal interactions has garnered much interest in the last few decades. A variety of studies have demonstrated that multisensory information (vision, audition, tactile sensation, and so on) can perceptually interact with each other in the spatial and temporal domains. Findings regarding crossmodal interactions in the spatiotemporal domain (i.e., motion processing) have also been reported, with updates in the last few years. In this review, we summarize past and recent findings on spatiotemporal processing in crossmodal interactions regarding perception of the external world. A traditional view regarding crossmodal interactions holds that vision is superior to audition in spatial processing, but audition is dominant over vision in temporal processing. Similarly, vision is considered to have dominant effects over the other sensory modalities (i.e., visual capture) in spatiotemporal processing. However, recent findings demonstrate that sound could have a driving effect on visual motion perception. Moreover, studies regarding perceptual associative learning reported that, after association is established between a sound sequence without spatial information and visual motion information, the sound sequence could trigger visual motion perception. Other sensory information, such as motor action or smell, has also exhibited similar driving effects on visual motion perception. Additionally, recent brain imaging studies demonstrate that similar activation patterns could be observed in several brain areas, including the motion processing areas, between spatiotemporal information from different sensory modalities. Based on these findings, we suggest that multimodal information could mutually interact in spatiotemporal processing in the percept of the external world and that common perceptual and neural underlying mechanisms would exist for spatiotemporal processing. PMID:26733827

MapMyFlu: visualizing spatio-temporal relationships between related influenza sequences

PubMed Central

Nolte, Nicholas; Kurzawa, Nils; Eils, Roland; Herrmann, Carl

2015-01-01

Understanding the molecular dynamics of viral spreading is crucial for anticipating the epidemiological implications of disease outbreaks. In the case of influenza, reassortments or point mutations affect the adaption to new hosts or resistance to anti-viral drugs and can determine whether a new strain will result in a pandemic infection or a less severe progression. To this end, tools integrating molecular information with epidemiological parameters are important to understand how molecular characteristics reflect in the infection dynamics. We present a new web tool, MapMyFlu, which allows to spatially and temporally display influenza viruses related to a query sequence on a Google Map based on BLAST results against the NCBI Influenza Database. Temporal and geographical trends appear clearly and may help in reconstructing the evolutionary history of a particular sequence. The tool is accessible through a web server, hence without the need for local installation. The website has an intuitive design and provides an easy-to-use service, and is available at http://mapmyflu.ipmb.uni-heidelberg.de PMID:25940623

On resolving the 180 deg ambiguity for a temporal sequence of vector magnetograms

NASA Astrophysics Data System (ADS)

Cheung, M. C.

2008-05-01

The solar coronal magnetic field evolves in response to the underlying photospheric driving. To study this connection by means of data-driven modeling, an accurate knowledge of the evolution of the photospheric vector field is essential. While there is a large body of work on attempts to resolve the 180 deg ambiguity in the component of the magnetic field transverse to the line of sight, most of these methods are applicable only to individual frames. With the imminent launch of the Solar Dynamics Observatory, it is especially timely for us to develop possible automated methods to resolve the ambiguity for temporal sequences of magnetograms. We present here the temporal acute angle method, which makes use of preceding disambiguated magnetograms as reference solutions for resolving the ambiguity in subsequent frames. To find the strengths and weaknesses of this method, we have carried out tests (1) on idealized magnetogram sequences involving simple rotating, shearing and straining flows and (2) on a synthetic magnetogram sequence from a 3D radiative MHD simulation of an buoyant magnetic flux tube emerging through granular convection. A metric for automatically picking out regions where the method is likely to fail is also presented.

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:…

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…

Perceptual learning shapes multisensory causal inference via two distinct mechanisms

PubMed Central

McGovern, David P.; Roudaia, Eugenie; Newell, Fiona N.; Roach, Neil W.

2016-01-01

To accurately represent the environment, our brains must integrate sensory signals from a common source while segregating those from independent sources. A reasonable strategy for performing this task is to restrict integration to cues that coincide in space and time. However, because multisensory signals are subject to differential transmission and processing delays, the brain must retain a degree of tolerance for temporal discrepancies. Recent research suggests that the width of this ‘temporal binding window’ can be reduced through perceptual learning, however, little is known about the mechanisms underlying these experience-dependent effects. Here, in separate experiments, we measure the temporal and spatial binding windows of human participants before and after training on an audiovisual temporal discrimination task. We show that training leads to two distinct effects on multisensory integration in the form of (i) a specific narrowing of the temporal binding window that does not transfer to spatial binding and (ii) a general reduction in the magnitude of crossmodal interactions across all spatiotemporal disparities. These effects arise naturally from a Bayesian model of causal inference in which learning improves the precision of audiovisual timing estimation, whilst concomitantly decreasing the prior expectation that stimuli emanate from a common source. PMID:27091411

Perceptual learning shapes multisensory causal inference via two distinct mechanisms.

PubMed

McGovern, David P; Roudaia, Eugenie; Newell, Fiona N; Roach, Neil W

2016-04-19

To accurately represent the environment, our brains must integrate sensory signals from a common source while segregating those from independent sources. A reasonable strategy for performing this task is to restrict integration to cues that coincide in space and time. However, because multisensory signals are subject to differential transmission and processing delays, the brain must retain a degree of tolerance for temporal discrepancies. Recent research suggests that the width of this 'temporal binding window' can be reduced through perceptual learning, however, little is known about the mechanisms underlying these experience-dependent effects. Here, in separate experiments, we measure the temporal and spatial binding windows of human participants before and after training on an audiovisual temporal discrimination task. We show that training leads to two distinct effects on multisensory integration in the form of (i) a specific narrowing of the temporal binding window that does not transfer to spatial binding and (ii) a general reduction in the magnitude of crossmodal interactions across all spatiotemporal disparities. These effects arise naturally from a Bayesian model of causal inference in which learning improves the precision of audiovisual timing estimation, whilst concomitantly decreasing the prior expectation that stimuli emanate from a common source.

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.

Self-Exciting Point Process Modeling of Conversation Event Sequences

NASA Astrophysics Data System (ADS)

Masuda, Naoki; Takaguchi, Taro; Sato, Nobuo; Yano, Kazuo

Self-exciting processes of Hawkes type have been used to model various phenomena including earthquakes, neural activities, and views of online videos. Studies of temporal networks have revealed that sequences of social interevent times for individuals are highly bursty. We examine some basic properties of event sequences generated by the Hawkes self-exciting process to show that it generates bursty interevent times for a wide parameter range. Then, we fit the model to the data of conversation sequences recorded in company offices in Japan. In this way, we can estimate relative magnitudes of the self excitement, its temporal decay, and the base event rate independent of the self excitation. These variables highly depend on individuals. We also point out that the Hawkes model has an important limitation that the correlation in the interevent times and the burstiness cannot be independently modulated.

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…