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

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

PubMed Central

Carvalho, Paulo F.; Goldstone, Robert L.

2015-01-01

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

Basal ganglia and Dopamine Contributions to Probabilistic Category Learning

PubMed Central

Shohamy, D.; Myers, C.E.; Kalanithi, J.; Gluck, M.A.

2009-01-01

Studies of the medial temporal lobe and basal ganglia memory systems have recently been extended towards understanding the neural systems contributing to category learning. The basal ganglia, in particular, have been linked to probabilistic category learning in humans. A separate parallel literature in systems neuroscience has emerged, indicating a role for the basal ganglia and related dopamine inputs in reward prediction and feedback processing. Here, we review behavioral, neuropsychological, functional neuroimaging, and computational studies of basal ganglia and dopamine contributions to learning in humans. Collectively, these studies implicate the basal ganglia in incremental, feedback-based learning that involves integrating information across multiple experiences. The medial temporal lobes, by contrast, contribute to rapid encoding of relations between stimuli and support flexible generalization of learning to novel contexts and stimuli. By breaking down our understanding of the cognitive and neural mechanisms contributing to different aspects of learning, recent studies are providing insight into how, and when, these different processes support learning, how they may interact with each other, and the consequence of different forms of learning for the representation of knowledge. PMID:18061261

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

Play along: effects of music and social interaction on word learning.

PubMed

Verga, Laura; Bigand, Emmanuel; Kotz, Sonja A

2015-01-01

Learning new words is an increasingly common necessity in everyday life. External factors, among which music and social interaction are particularly debated, are claimed to facilitate this task. Due to their influence on the learner's temporal behavior, these stimuli are able to drive the learner's attention to the correct referent of new words at the correct point in time. However, do music and social interaction impact learning behavior in the same way? The current study aims to answer this question. Native German speakers (N = 80) were requested to learn new words (pseudo-words) during a contextual learning game. This learning task was performed alone with a computer or with a partner, with or without music. Results showed that music and social interaction had a different impact on the learner's behavior: Participants tended to temporally coordinate their behavior more with a partner than with music, and in both cases more than with a computer. However, when both music and social interaction were present, this temporal coordination was hindered. These results suggest that while music and social interaction do influence participants' learning behavior, they have a different impact. Moreover, impaired behavior when both music and a partner are present suggests that different mechanisms are employed to coordinate with the two types of stimuli. Whether one or the other approach is more efficient for word learning, however, is a question still requiring further investigation, as no differences were observed between conditions in a retrieval phase, which took place immediately after the learning session. This study contributes to the literature on word learning in adults by investigating two possible facilitating factors, and has important implications for situations such as music therapy, in which music and social interaction are present at the same time.

Play along: effects of music and social interaction on word learning

PubMed Central

Verga, Laura; Bigand, Emmanuel; Kotz, Sonja A.

2015-01-01

Learning new words is an increasingly common necessity in everyday life. External factors, among which music and social interaction are particularly debated, are claimed to facilitate this task. Due to their influence on the learner’s temporal behavior, these stimuli are able to drive the learner’s attention to the correct referent of new words at the correct point in time. However, do music and social interaction impact learning behavior in the same way? The current study aims to answer this question. Native German speakers (N = 80) were requested to learn new words (pseudo-words) during a contextual learning game. This learning task was performed alone with a computer or with a partner, with or without music. Results showed that music and social interaction had a different impact on the learner’s behavior: Participants tended to temporally coordinate their behavior more with a partner than with music, and in both cases more than with a computer. However, when both music and social interaction were present, this temporal coordination was hindered. These results suggest that while music and social interaction do influence participants’ learning behavior, they have a different impact. Moreover, impaired behavior when both music and a partner are present suggests that different mechanisms are employed to coordinate with the two types of stimuli. Whether one or the other approach is more efficient for word learning, however, is a question still requiring further investigation, as no differences were observed between conditions in a retrieval phase, which took place immediately after the learning session. This study contributes to the literature on word learning in adults by investigating two possible facilitating factors, and has important implications for situations such as music therapy, in which music and social interaction are present at the same time. PMID:26388818

Unique characteristics of motor adaptation during walking in young children.

PubMed

Musselman, Kristin E; Patrick, Susan K; Vasudevan, Erin V L; Bastian, Amy J; Yang, Jaynie F

2011-05-01

Children show precocious ability in the learning of languages; is this the case with motor learning? We used split-belt walking to probe motor adaptation (a form of motor learning) in children. Data from 27 children (ages 8-36 mo) were compared with those from 10 adults. Children walked with the treadmill belts at the same speed (tied belt), followed by walking with the belts moving at different speeds (split belt) for 8-10 min, followed again by tied-belt walking (postsplit). Initial asymmetries in temporal coordination (i.e., double support time) induced by split-belt walking were slowly reduced, with most children showing an aftereffect (i.e., asymmetry in the opposite direction to the initial) in the early postsplit period, indicative of learning. In contrast, asymmetries in spatial coordination (i.e., center of oscillation) persisted during split-belt walking and no aftereffect was seen. Step length, a measure of both spatial and temporal coordination, showed intermediate effects. The time course of learning in double support and step length was slower in children than in adults. Moreover, there was a significant negative correlation between the size of the initial asymmetry during early split-belt walking (called error) and the aftereffect for step length. Hence, children may have more difficulty learning when the errors are large. The findings further suggest that the mechanisms controlling temporal and spatial adaptation are different and mature at different times.

Sex differences in verbal and nonverbal learning before and after temporal lobe epilepsy surgery.

PubMed

Berger, Justus; Oltmanns, Frank; Holtkamp, Martin; Bengner, Thomas

2017-01-01

Women outperform men in a host of episodic memory tasks, yet the neuroanatomical basis for this effect is unclear. It has been suggested that the anterior temporal lobe might be especially relevant for sex differences in memory. In the current study, we investigated whether temporal lobe epilepsy (TLE) has an influence on sex effects in learning and memory and whether women and men with TLE differ in their risk for memory deficits after epilepsy surgery. 177 patients (53 women and 41 men with left TLE, 42 women and 41 men with right TLE) were neuropsychologically tested before and one year after temporal lobe resection. We found that women with TLE had better verbal, but not figural, memory than men with TLE. The female advantage in verbal memory was not affected by temporal lobe resection. The same pattern of results was found in a more homogeneous subsample of 84 patients with only hippocampal sclerosis who were seizure-free after surgery. Our findings challenge the concept that the anterior temporal lobe plays a central role in the verbal memory advantage for women. Copyright © 2016 Elsevier Inc. All rights reserved.

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).

Monitoring Makes a Difference: Quality and Temporal Variation in Teacher Education Students' Collaborative Learning

ERIC Educational Resources Information Center

Näykki, Piia; Järvenoja, Hanna; Järvelä, Sanna; Kirschner, Paul

2017-01-01

The aim of this process-oriented video-observation study is to explore how groups that perform differently differ in terms of the number, quality, and temporal variation of their content-level (knowledge co-construction) and meta-level (monitoring) activities. Five groups of teacher education students (n = 22) were observed throughout a 3-month…

Parallel Online Temporal Difference Learning for Motor Control.

PubMed

Caarls, Wouter; Schuitema, Erik

2016-07-01

Temporal difference (TD) learning, a key concept in reinforcement learning, is a popular method for solving simulated control problems. However, in real systems, this method is often avoided in favor of policy search methods because of its long learning time. But policy search suffers from its own drawbacks, such as the necessity of informed policy parameterization and initialization. In this paper, we show that TD learning can work effectively in real robotic systems as well, using parallel model learning and planning. Using locally weighted linear regression and trajectory sampled planning with 14 concurrent threads, we can achieve a speedup of almost two orders of magnitude over regular TD control on simulated control benchmarks. For a real-world pendulum swing-up task and a two-link manipulator movement task, we report a speedup of 20× to 60× , with a real-time learning speed of less than half a minute. The results are competitive with state-of-the-art policy search.

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

The Effect of Sample Duration and Cue on a Double Temporal Discrimination

ERIC Educational Resources Information Center

Oliveira, Luis; Machado, Armando

2008-01-01

To test the assumptions of two models of timing, Scalar Expectancy Theory (SET) and Learning to Time (LeT), nine pigeons were exposed to two temporal discriminations, each signaled by a different cue. On half of the trials, pigeons learned to choose a red key after a 1.5-s horizontal bar and a green key after a 6-s horizontal bar; on the other…

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.

Complementary roles for amygdala and periaqueductal gray in temporal-difference fear learning.

PubMed

Cole, Sindy; McNally, Gavan P

2009-01-01

Pavlovian fear conditioning is not a unitary process. At the neurobiological level multiple brain regions and neurotransmitters contribute to fear learning. At the behavioral level many variables contribute to fear learning including the physical salience of the events being learned about, the direction and magnitude of predictive error, and the rate at which these are learned about. These experiments used a serial compound conditioning design to determine the roles of basolateral amygdala (BLA) NMDA receptors and ventrolateral midbrain periaqueductal gray (vlPAG) mu-opioid receptors (MOR) in predictive fear learning. Rats received a three-stage design, which arranged for both positive and negative prediction errors producing bidirectional changes in fear learning within the same subjects during the test stage. Intra-BLA infusion of the NR2B receptor antagonist Ifenprodil prevented all learning. In contrast, intra-vlPAG infusion of the MOR antagonist CTAP enhanced learning in response to positive predictive error but impaired learning in response to negative predictive error--a pattern similar to Hebbian learning and an indication that fear learning had been divorced from predictive error. These findings identify complementary but dissociable roles for amygdala NMDA receptors and vlPAG MOR in temporal-difference predictive fear learning.

Temporal-difference prediction errors and Pavlovian fear conditioning: role of NMDA and opioid receptors.

PubMed

Cole, Sindy; McNally, Gavan P

2007-10-01

Three experiments studied temporal-difference (TD) prediction errors during Pavlovian fear conditioning. In Stage I, rats received conditioned stimulus A (CSA) paired with shock. In Stage II, they received pairings of CSA and CSB with shock that blocked learning to CSB. In Stage III, a serial overlapping compound, CSB --> CSA, was followed by shock. The change in intratrial durations supported fear learning to CSB but reduced fear of CSA, revealing the operation of TD prediction errors. N-methyl- D-aspartate (NMDA) receptor antagonism prior to Stage III prevented learning, whereas opioid receptor antagonism selectively affected predictive learning. These findings support a role for TD prediction errors in fear conditioning. They suggest that NMDA receptors contribute to fear learning by acting on the product of predictive error, whereas opioid receptors contribute to predictive error. (PsycINFO Database Record (c) 2007 APA, all rights reserved).

Are individuals with Parkinson's disease capable of speech-motor learning? - A preliminary evaluation.

PubMed

Kaipa, Ramesh; Jones, Richard D; Robb, Michael P

2016-07-01

The benefits of different practice conditions in limb-based rehabilitation of motor disorders are well documented. Conversely, the role of practice structure in the treatment of motor-based speech disorders has only been minimally investigated. Considering this limitation, the current study aimed to investigate the effectiveness of selected practice conditions in spatial and temporal learning of novel speech utterances in individuals with Parkinson's disease (PD). Participants included 16 individuals with PD who were randomly and equally assigned to constant, variable, random, and blocked practice conditions. Participants in all four groups practiced a speech phrase for two consecutive days, and reproduced the speech phrase on the third day without further practice or feedback. There were no significant differences (p > 0.05) between participants across the four practice conditions with respect to either spatial or temporal learning of the speech phrase. Overall, PD participants demonstrated diminished spatial and temporal learning in comparison to healthy controls. Tests of strength of association between participants' demographic/clinical characteristics and speech-motor learning outcomes did not reveal any significant correlations. The findings from the current study suggest that repeated practice facilitates speech-motor learning in individuals with PD irrespective of the type of practice. Clinicians need to be cautious in applying practice conditions to treat speech deficits associated with PD based on the findings of non-speech-motor learning tasks. Copyright © 2016 Elsevier Ltd. All rights reserved.

It doesn't matter what you say: FMRI correlates of voice learning and recognition independent of speech content.

PubMed

Zäske, Romi; Awwad Shiekh Hasan, Bashar; Belin, Pascal

2017-09-01

Listeners can recognize newly learned voices from previously unheard utterances, suggesting the acquisition of high-level speech-invariant voice representations during learning. Using functional magnetic resonance imaging (fMRI) we investigated the anatomical basis underlying the acquisition of voice representations for unfamiliar speakers independent of speech, and their subsequent recognition among novel voices. Specifically, listeners studied voices of unfamiliar speakers uttering short sentences and subsequently classified studied and novel voices as "old" or "new" in a recognition test. To investigate "pure" voice learning, i.e., independent of sentence meaning, we presented German sentence stimuli to non-German speaking listeners. To disentangle stimulus-invariant and stimulus-dependent learning, during the test phase we contrasted a "same sentence" condition in which listeners heard speakers repeating the sentences from the preceding study phase, with a "different sentence" condition. Voice recognition performance was above chance in both conditions although, as expected, performance was higher for same than for different sentences. During study phases activity in the left inferior frontal gyrus (IFG) was related to subsequent voice recognition performance and same versus different sentence condition, suggesting an involvement of the left IFG in the interactive processing of speaker and speech information during learning. Importantly, at test reduced activation for voices correctly classified as "old" compared to "new" emerged in a network of brain areas including temporal voice areas (TVAs) of the right posterior superior temporal gyrus (pSTG), as well as the right inferior/middle frontal gyrus (IFG/MFG), the right medial frontal gyrus, and the left caudate. This effect of voice novelty did not interact with sentence condition, suggesting a role of temporal voice-selective areas and extra-temporal areas in the explicit recognition of learned voice identity, independent of speech content. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fronto-temporal white matter connectivity predicts reversal learning errors

PubMed Central

Alm, Kylie H.; Rolheiser, Tyler; Mohamed, Feroze B.; Olson, Ingrid R.

2015-01-01

Each day, we make hundreds of decisions. In some instances, these decisions are guided by our innate needs; in other instances they are guided by memory. Probabilistic reversal learning tasks exemplify the close relationship between decision making and memory, as subjects are exposed to repeated pairings of a stimulus choice with a reward or punishment outcome. After stimulus–outcome associations have been learned, the associated reward contingencies are reversed, and participants are not immediately aware of this reversal. Individual differences in the tendency to choose the previously rewarded stimulus reveal differences in the tendency to make poorly considered, inflexible choices. Lesion studies have strongly linked reversal learning performance to the functioning of the orbitofrontal cortex, the hippocampus, and in some instances, the amygdala. Here, we asked whether individual differences in the microstructure of the uncinate fasciculus, a white matter tract that connects anterior and medial temporal lobe regions to the orbitofrontal cortex, predict reversal learning performance. Diffusion tensor imaging and behavioral paradigms were used to examine this relationship in 33 healthy young adults. The results of tractography revealed a significant negative relationship between reversal learning performance and uncinate axial diffusivity, but no such relationship was demonstrated in a control tract, the inferior longitudinal fasciculus. Our findings suggest that the uncinate might serve to integrate associations stored in the anterior and medial temporal lobes with expectations about expected value based on feedback history, computed in the orbitofrontal cortex. PMID:26150776

Complementary Roles for Amygdala and Periaqueductal Gray in Temporal-Difference Fear Learning

ERIC Educational Resources Information Center

Cole, Sindy; McNally, Gavan P.

2009-01-01

Pavlovian fear conditioning is not a unitary process. At the neurobiological level multiple brain regions and neurotransmitters contribute to fear learning. At the behavioral level many variables contribute to fear learning including the physical salience of the events being learned about, the direction and magnitude of predictive error, and the…

Reconciling Reinforcement Learning Models with Behavioral Extinction and Renewal: Implications for Addiction, Relapse, and Problem Gambling

ERIC Educational Resources Information Center

Redish, A. David; Jensen, Steve; Johnson, Adam; Kurth-Nelson, Zeb

2007-01-01

Because learned associations are quickly renewed following extinction, the extinction process must include processes other than unlearning. However, reinforcement learning models, such as the temporal difference reinforcement learning (TDRL) model, treat extinction as an unlearning of associated value and are thus unable to capture renewal. TDRL…

The Role of Multiple Neuromodulators in Reinforcement Learning That Is Based on Competition between Eligibility Traces.

PubMed

Huertas, Marco A; Schwettmann, Sarah E; Shouval, Harel Z

2016-01-01

The ability to maximize reward and avoid punishment is essential for animal survival. Reinforcement learning (RL) refers to the algorithms used by biological or artificial systems to learn how to maximize reward or avoid negative outcomes based on past experiences. While RL is also important in machine learning, the types of mechanistic constraints encountered by biological machinery might be different than those for artificial systems. Two major problems encountered by RL are how to relate a stimulus with a reinforcing signal that is delayed in time (temporal credit assignment), and how to stop learning once the target behaviors are attained (stopping rule). To address the first problem synaptic eligibility traces were introduced, bridging the temporal gap between a stimulus and its reward. Although, these were mere theoretical constructs, recent experiments have provided evidence of their existence. These experiments also reveal that the presence of specific neuromodulators converts the traces into changes in synaptic efficacy. A mechanistic implementation of the stopping rule usually assumes the inhibition of the reward nucleus; however, recent experimental results have shown that learning terminates at the appropriate network state even in setups where the reward nucleus cannot be inhibited. In an effort to describe a learning rule that solves the temporal credit assignment problem and implements a biologically plausible stopping rule, we proposed a model based on two separate synaptic eligibility traces, one for long-term potentiation (LTP) and one for long-term depression (LTD), each obeying different dynamics and having different effective magnitudes. The model has been shown to successfully generate stable learning in recurrent networks. Although, the model assumes the presence of a single neuromodulator, evidence indicates that there are different neuromodulators for expressing the different traces. What could be the role of different neuromodulators for expressing the LTP and LTD traces? Here we expand on our previous model to include several neuromodulators, and illustrate through various examples how different these contribute to learning reward-timing within a wide set of training paradigms and propose further roles that multiple neuromodulators can play in encoding additional information of the rewarding signal.

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.

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

Does Temporal Integration of Face Parts Reflect Holistic Processing?

PubMed Central

Cheung, Olivia S.; Richler, Jennifer J.; Phillips, W. Stewart; Gauthier, Isabel

2011-01-01

We examined whether temporal integration of face parts reflects holistic processing or response interference. Participants learned to name two faces “Fred” and two “Bob”. At test, top and bottom halves of different faces formed composites and were presented briefly separated in time. Replicating prior findings (Singer & Sheinberg, 2006), naming of the target halves for aligned composites was slowed when the irrelevant halves were from faces with a different name compared to that from the original face. However, no interference was observed when the irrelevant halves had identical names as the target halves but came from different learned faces, arguing against a true holistic effect. Instead, response interference was obtained when the target halves briefly preceded the irrelevant halves. Experiment 2 confirmed a double-dissociation between holistic processing vs. response interference for intact faces vs. temporally separated face halves, suggesting that simultaneous presentation of facial information is critical for holistic processing. PMID:21327378

Functional requirements for reward-modulated spike-timing-dependent plasticity.

PubMed

Frémaux, Nicolas; Sprekeler, Henning; Gerstner, Wulfram

2010-10-06

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.

Establishing a learning foundation in a dynamically changing world: Insights from artificial language work

NASA Astrophysics Data System (ADS)

Gonzales, Kalim

It is argued that infants build a foundation for learning about the world through their incidental acquisition of the spatial and temporal regularities surrounding them. A challenge is that learning occurs across multiple contexts whose statistics can greatly differ. Two artificial language studies with 12-month-olds demonstrate that infants come prepared to parse statistics across contexts using the temporal and perceptual features that distinguish one context from another. These results suggest that infants can organize their statistical input with a wider range of features that typically considered. Possible attention, decision making, and memory mechanisms are discussed.

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.

Characterizing Reinforcement Learning Methods through Parameterized Learning Problems

DTIC Science & Technology

2011-06-03

extraneous. The agent could potentially adapt these representational aspects by applying methods from feature selection ( Kolter and Ng, 2009; Petrik et al...611–616. AAAI Press. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature selection in least-squares temporal difference learning. In A. P

Learning and recognition of tactile temporal sequences by mice and humans

PubMed Central

Bale, Michael R; Bitzidou, Malamati; Pitas, Anna; Brebner, Leonie S; Khazim, Lina; Anagnou, Stavros T; Stevenson, Caitlin D; Maravall, Miguel

2017-01-01

The world around us is replete with stimuli that unfold over time. When we hear an auditory stream like music or speech or scan a texture with our fingertip, physical features in the stimulus are concatenated in a particular order. This temporal patterning is critical to interpreting the stimulus. To explore the capacity of mice and humans to learn tactile sequences, we developed a task in which subjects had to recognise a continuous modulated noise sequence delivered to whiskers or fingertips, defined by its temporal patterning over hundreds of milliseconds. GO and NO-GO sequences differed only in that the order of their constituent noise modulation segments was temporally scrambled. Both mice and humans efficiently learned tactile sequences. Mouse sequence recognition depended on detecting transitions in noise amplitude; animals could base their decision on the earliest information available. Humans appeared to use additional cues, including the duration of noise modulation segments. DOI: http://dx.doi.org/10.7554/eLife.27333.001 PMID:28812976

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

PubMed

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

2018-05-24

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

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

PubMed

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

2002-01-01

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

[Multi-center study of the Jenaer model of the temporal bone].

PubMed

Schneider, G; Müller, A

2004-06-01

Preparing exercises at the temporal bone are a prerequisite for the knowledge of the anatomical special features of this region and for learning the fundamentals of the tympanic cavity surgery. Since however fewer human temporal bones are available, the search for back-up models already took place in the last years. Based on the experiences of the handling and visualization of CT data for the 3D-implant construction in the ent department Jena a temporal bone model was developed. The model was sent away to surgeons of different training. On the basis of identification of anatomical structures and evaluation of general parameters by means of a point system the model was evaluated. The Jenaer temporal bone model is suitable as entrance into the preparing exercises. The anatomical structures are good to identify for the beginner. The handling with drill and chisel can be learned.

Computational Constraints in Cognitive Theories of Forgetting

PubMed Central

Ecker, Ullrich K. H.; Lewandowsky, Stephan

2012-01-01

This article highlights some of the benefits of computational modeling for theorizing in cognition. We demonstrate how computational models have been used recently to argue that (1) forgetting in short-term memory is based on interference not decay, (2) forgetting in list-learning paradigms is more parsimoniously explained by a temporal distinctiveness account than by various forms of consolidation, and (3) intrusion asymmetries that appear when information is learned in different contexts can be explained by temporal context reinstatement rather than labilization and reconsolidation processes. PMID:23091467

Computational constraints in cognitive theories of forgetting.

PubMed

Ecker, Ullrich K H; Lewandowsky, Stephan

2012-01-01

This article highlights some of the benefits of computational modeling for theorizing in cognition. We demonstrate how computational models have been used recently to argue that (1) forgetting in short-term memory is based on interference not decay, (2) forgetting in list-learning paradigms is more parsimoniously explained by a temporal distinctiveness account than by various forms of consolidation, and (3) intrusion asymmetries that appear when information is learned in different contexts can be explained by temporal context reinstatement rather than labilization and reconsolidation processes.

Learning Efficient Spatial-Temporal Gait Features with Deep Learning for Human Identification.

PubMed

Liu, Wu; Zhang, Cheng; Ma, Huadong; Li, Shuangqun

2018-02-06

The integration of the latest breakthroughs in bioinformatics technology from one side and artificial intelligence from another side, enables remarkable advances in the fields of intelligent security guard computational biology, healthcare, and so on. Among them, biometrics based automatic human identification is one of the most fundamental and significant research topic. Human gait, which is a biometric features with the unique capability, has gained significant attentions as the remarkable characteristics of remote accessed, robust and security in the biometrics based human identification. However, the existed methods cannot well handle the indistinctive inter-class differences and large intra-class variations of human gait in real-world situation. In this paper, we have developed an efficient spatial-temporal gait features with deep learning for human identification. First of all, we proposed a gait energy image (GEI) based Siamese neural network to automatically extract robust and discriminative spatial gait features for human identification. Furthermore, we exploit the deep 3-dimensional convolutional networks to learn the human gait convolutional 3D (C3D) as the temporal gait features. Finally, the GEI and C3D gait features are embedded into the null space by the Null Foley-Sammon Transform (NFST). In the new space, the spatial-temporal features are sufficiently combined with distance metric learning to drive the similarity metric to be small for pairs of gait from the same person, and large for pairs from different persons. Consequently, the experiments on the world's largest gait database show our framework impressively outperforms state-of-the-art methods.

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.

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

NASA Astrophysics Data System (ADS)

Marom, Yuval; Hayes, Gillian

2001-06-01

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

Effects of different electrical brain stimulation protocols on subcomponents of motor skill learning.

PubMed

Prichard, George; Weiller, Cornelius; Fritsch, Brita; Reis, Janine

2014-01-01

Noninvasive electrical brain stimulation (NEBS) with transcranial direct current (tDCS) or random noise stimulation (tRNS) applied to the primary motor cortex (M1) can augment motor learning. We tested whether different types of stimulation alter particular aspects of learning a tracing task over three consecutive days, namely skill acquisition (online/within session effects) or consolidation (offline/between session effects). Motor training on a tracing task over three consecutive days was combined with different types and montages of stimulation (tDCS, tRNS). Unilateral M1 stimulation using tRNS as well as unilateral and bilateral M1 tDCS all enhanced motor skill learning compared to sham stimulation. In all groups, this appeared to be driven by online effects without an additional offline effect. Unilateral tDCS resulted in large skill gains immediately following the onset of stimulation, while tRNS exerted more gradual effects. Control stimulation of the right temporal lobe did not enhance skill learning relative to sham. The mechanisms of action of tDCS and tRNS are likely different. Hence, the time course of skill improvement within sessions could point to specific and temporally distinct interactions with the physiological process of motor skill learning. Exploring the parameters of NEBS on different tasks and in patients with brain injury will allow us to maximize the benefits of NEBS for neurorehabilitation. Copyright © 2014 Elsevier Inc. All rights reserved.

The Effects of Interval Duration on Temporal Tracking and Alternation Learning

ERIC Educational Resources Information Center

Ludvig, Elliot A.; Staddon, John E. R.

2005-01-01

On cyclic-interval reinforcement schedules, animals typically show a postreinforcement pause that is a function of the immediately preceding time interval ("temporal tracking"). Animals, however, do not track single-alternation schedules--when two different intervals are presented in strict alternation on successive trials. In this experiment,…

Age Differences in Recall and Information Processing in Verbal and Spatial Learning.

ERIC Educational Resources Information Center

Mungas, Dan; And Others

1991-01-01

Three age groups of 24 people each completed verbal word list tasks and spatial learning tasks 5 times each. Significant age differences were found for total recall and type of task. Younger subjects showed increased levels of clustering--organizing information according to semantic or spatial clusters. Age was not related to temporal order of…

The Advantage of Mixing Examples in Inductive Learning: A Comparison of Three Hypotheses

ERIC Educational Resources Information Center

Guzman-Munoz, Francisco Javier

2017-01-01

Mixing examples of different categories (interleaving) has been shown to promote inductive learning as compared with presenting examples of the same category together (massing). In three studies, we tested whether the advantage of interleaving is exclusively due to the mixing of examples from different categories or to the temporal gap introduced…

Constructing Temporally Extended Actions through Incremental Community Detection

PubMed Central

Li, Ge

2018-01-01

Hierarchical reinforcement learning works on temporally extended actions or skills to facilitate learning. How to automatically form such abstraction is challenging, and many efforts tackle this issue in the options framework. While various approaches exist to construct options from different perspectives, few of them concentrate on options' adaptability during learning. This paper presents an algorithm to create options and enhance their quality online. Both aspects operate on detected communities of the learning environment's state transition graph. We first construct options from initial samples as the basis of online learning. Then a rule-based community revision algorithm is proposed to update graph partitions, based on which existing options can be continuously tuned. Experimental results in two problems indicate that options from initial samples may perform poorly in more complex environments, and our presented strategy can effectively improve options and get better results compared with flat reinforcement learning. PMID:29849543

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.

Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

PubMed

López-Barroso, Diana; Ripollés, Pablo; Marco-Pallarés, Josep; Mohammadi, Bahram; Münte, Thomas F; Bachoud-Lévi, Anne-Catherine; Rodriguez-Fornells, Antoni; de Diego-Balaguer, Ruth

2015-04-15

Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance. Copyright © 2015 Elsevier Inc. All rights reserved.

Influences of gender role and anxiety on sex differences in temporal summation of pain.

PubMed

Robinson, Michael E; Wise, Emily A; Gagnon, Christine; Fillingim, Roger B; Price, Donald D

2004-03-01

Previous research has consistently shown moderate to large differences between pain reports of men and women undergoing experimental pain testing. These differences have been shown for a variety of types of stimulation. However, only recently have sex differences been demonstrated for temporal summation of second pain. This study examined sex differences in response to temporal summation of second pain elicited by thermal stimulation of the skin. The relative influences of state anxiety and gender role expectations on temporal summation were investigated. Asymptomatic undergraduates (37 women and 30 men) underwent thermal testing of the thenar surface of the hand in a temporal summation protocol. Our results replicated those of Fillingim et al indicating that women showed increased temporal summation compared to men. We extended those findings to demonstrate that temporal summation is influenced by anxiety and gender role stereotypes about pain responding. When anxiety and gender role stereotypes are taken into account, sex is no longer a significant predictor of temporal summation. These findings highlight the contribution of social learning factors in the differences between sexes' pain perception. Results of this study demonstrate that psychosocial variables influence pain mechanisms. Temporal summation was related to gender role expectations of pain and anxiety. These variables explain a significant portion of the differences between men and women's pain processing, and may be related to differences in clinical presentation.

Hyper-Binding across Time: Age Differences in the Effect of Temporal Proximity on Paired-Associate Learning

ERIC Educational Resources Information Center

Campbell, Karen L.; Trelle, Alexandra; Hasher, Lynn

2014-01-01

Older adults show hyper- (or excessive) binding effects for simultaneously and sequentially presented distraction. Here, we addressed the potential role of hyper-binding in paired-associate learning. Older and younger adults learned a list of word pairs and then received an associative recognition task in which rearranged pairs were formed from…

Temporal contingency

PubMed Central

Gallistel, C.R.; Craig, Andrew R.; Shahan, Timothy A.

2015-01-01

Contingency, and more particularly temporal contingency, has often figured in thinking about the nature of learning. However, it has never been formally defined in such a way as to make it a measure that can be applied to most animal learning protocols. We use elementary information theory to define contingency in such a way as to make it a measurable property of almost any conditioning protocol. We discuss how making it a measurable construct enables the exploration of the role of different contingencies in the acquisition and performance of classically and operantly conditioned behavior. PMID:23994260

Modulation of competing memory systems by distraction.

PubMed

Foerde, Karin; Knowlton, Barbara J; Poldrack, Russell A

2006-08-01

Different forms of learning and memory depend on functionally and anatomically separable neural circuits [Squire, L. R. (1992) Psychol. Rev. 99, 195-231]. Declarative memory relies on a medial temporal lobe system, whereas habit learning relies on the striatum [Cohen, N. J. & Eichenbaum, H. (1993) Memory, Amnesia, and the Hippocampal System (MIT Press, Cambridge, MA)]. How these systems are engaged to optimize learning and behavior is not clear. Here, we present results from functional neuroimaging showing that the presence of a demanding secondary task during learning modulates the degree to which subjects solve a problem using either declarative memory or habit learning. Dual-task conditions did not reduce accuracy but reduced the amount of declarative learning about the task. Medial temporal lobe activity was correlated with task performance and declarative knowledge after learning under single-task conditions, whereas performance was correlated with striatal activity after dual-task learning conditions. These results demonstrate a fundamental difference in these memory systems in their sensitivity to concurrent distraction. The results are consistent with the notion that declarative and habit learning compete to mediate task performance, and they suggest that the presence of distraction can bias this competition. These results have implications for learning in multitask situations, suggesting that, even if distraction does not decrease the overall level of learning, it can result in the acquisition of knowledge that can be applied less flexibly in new situations.

Resting-state low-frequency fluctuations reflect individual differences in spoken language learning.

PubMed

Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C M

2016-03-01

A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The "competition" (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest--ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success. Copyright © 2015 Elsevier Ltd. All rights reserved.

Resting-state low-frequency fluctuations reflect individual differences in spoken language learning

PubMed Central

Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C.M.

2016-01-01

A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The “competition” (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest – ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success. PMID:26866283

A Novel Method for the In-Depth Multimodal Analysis of Student Learning Trajectories in Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Liu, Ran; Stamper, John; Davenport, Jodi

2018-01-01

Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…

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

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 effects of age on the neural correlates of episodic encoding.

PubMed

Grady, C L; McIntosh, A R; Rajah, M N; Beig, S; Craik, F I

1999-12-01

Young and old adults underwent positron emission tomographic scans while encoding pictures of objects and words using three encoding strategies: deep processing (a semantic living/nonliving judgement), shallow processing (size judgement) and intentional learning. Picture memory exceeded word memory in both young and old groups, and there was an age-related decrement only in word recognition. During the encoding tasks three brain activity patterns were found that differentiated stimulus type and the different encoding strategies. The stimulus-specific pattern was characterized by greater activity in extrastriate and medial temporal cortices during picture encoding, and greater activity in left prefrontal and temporal cortices during encoding of words. The older adults showed this pattern to a significantly lesser degree. A pattern distinguishing deep processing from intentional learning of words and pictures was identified, characterized mainly by differences in prefrontal cortex, and this pattern also was of significantly lesser magnitude in the old group. A final pattern identified areas with increased activity during deep processing and intentional learning of pictures, including left prefrontal and bilateral medial temporal regions. There was no group difference in this pattern. These results indicate age-related dysfunction in several encoding networks, with sparing of one specifically involved in more elaborate encoding of pictures. These age-related changes appear to affect verbal memory more than picture memory.

Different mechanisms in learning different second languages: Evidence from English speakers learning Chinese and Spanish.

PubMed

Cao, Fan; Sussman, Bethany L; Rios, Valeria; Yan, Xin; Wang, Zhao; Spray, Gregory J; Mack, Ryan M

2017-03-01

Word reading has been found to be associated with different neural networks in different languages, with greater involvement of the lexical pathway for opaque languages and greater invovlement of the sub-lexical pathway for transparent langauges. However, we do not know whether this language divergence can be demonstrated in second langauge learners, how learner's metalinguistic ability would modulate the langauge divergence, or whether learning method would interact with the language divergence. In this study, we attempted to answer these questions by comparing brain activations of Chinese and Spanish word reading in native English-speaking adults who learned Chinese and Spanish over a 2 week period under three learning conditions: phonological, handwriting, and passive viewing. We found that mapping orthography to phonology in Chinese had greater activation in the left inferior frontal gyrus (IFG) and left inferior temporal gyrus (ITG) than in Spanish, suggesting greater invovlement of the lexical pathway in opaque langauges. In contrast, Spanish words evoked greater activation in the left superior temporal gyrus (STG) than English, suggesting greater invovlement of the sublexical pathway for transparant languages. Furthermore, brain-behavior correlation analyses found that higher phonological awareness and rapid naming were associated with greater activation in the bilateral IFG for Chinese and in the bilateral STG for Spanish, suggesting greater language divergence in participants with higher meta-linguistic awareness. Finally, a significant interaction between the language and learning condition was found in the left STG and middle frontal gyrus (MFG), with greater activation in handwriting learning than viewing learning in the left STG only for Spanish, and greater activation in handwriting learning than phonological learning in the left MFG only for Chinese. These findings suggest that handwriting facilitates assembled phonology in Spanish and addressed phonology in Chinese. In summary, our study suggests different mechanisms in learning different L2s, providing important insights into neural plasticity and important implications in second language education. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2013-01-01

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

Functional organization of the medial temporal lobe memory system following neonatal hippocampal lesion in rhesus monkeys.

PubMed

Chareyron, Loïc J; Banta Lavenex, Pamela; Amaral, David G; Lavenex, Pierre

2017-12-01

Hippocampal damage in adult humans impairs episodic and semantic memory, whereas hippocampal damage early in life impairs episodic memory but leaves semantic learning relatively preserved. We have previously shown a similar behavioral dissociation in nonhuman primates. Hippocampal lesion in adult monkeys prevents allocentric spatial relational learning, whereas spatial learning persists following neonatal lesion. Here, we quantified the number of cells expressing the immediate-early gene c-fos, a marker of neuronal activity, to characterize the functional organization of the medial temporal lobe memory system following neonatal hippocampal lesion. Ninety minutes before brain collection, three control and four adult monkeys with bilateral neonatal hippocampal lesions explored a novel environment to activate brain structures involved in spatial learning. Three other adult monkeys with neonatal hippocampal lesions remained in their housing quarters. In unlesioned monkeys, we found high levels of c-fos expression in the intermediate and caudal regions of the entorhinal cortex, and in the perirhinal, parahippocampal, and retrosplenial cortices. In lesioned monkeys, spatial exploration induced an increase in c-fos expression in the intermediate field of the entorhinal cortex, the perirhinal, parahippocampal, and retrosplenial cortices, but not in the caudal entorhinal cortex. These findings suggest that different regions of the medial temporal lobe memory system may require different types of interaction with the hippocampus in support of memory. The caudal perirhinal cortex, the parahippocampal cortex, and the retrosplenial cortex may contribute to spatial learning in the absence of functional hippocampal circuits, whereas the caudal entorhinal cortex may require hippocampal output to support spatial learning.

Action-outcome learning and prediction shape the window of simultaneity of audiovisual outcomes.

PubMed

Desantis, Andrea; Haggard, Patrick

2016-08-01

To form a coherent representation of the objects around us, the brain must group the different sensory features composing these objects. Here, we investigated whether actions contribute in this grouping process. In particular, we assessed whether action-outcome learning and prediction contribute to audiovisual temporal binding. Participants were presented with two audiovisual pairs: one pair was triggered by a left action, and the other by a right action. In a later test phase, the audio and visual components of these pairs were presented at different onset times. Participants judged whether they were simultaneous or not. To assess the role of action-outcome prediction on audiovisual simultaneity, each action triggered either the same audiovisual pair as in the learning phase ('predicted' pair), or the pair that had previously been associated with the other action ('unpredicted' pair). We found the time window within which auditory and visual events appeared simultaneous increased for predicted compared to unpredicted pairs. However, no change in audiovisual simultaneity was observed when audiovisual pairs followed visual cues, rather than voluntary actions. This suggests that only action-outcome learning promotes temporal grouping of audio and visual effects. In a second experiment we observed that changes in audiovisual simultaneity do not only depend on our ability to predict what outcomes our actions generate, but also on learning the delay between the action and the multisensory outcome. When participants learned that the delay between action and audiovisual pair was variable, the window of audiovisual simultaneity for predicted pairs increased, relative to a fixed action-outcome pair delay. This suggests that participants learn action-based predictions of audiovisual outcome, and adapt their temporal perception of outcome events based on such predictions. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

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.

Sense of agency, associative learning, and schizotypy

PubMed Central

Moore, James W.; Dickinson, Anthony; Fletcher, Paul C.

2011-01-01

Despite the fact that the role of learning is recognised in empirical and theoretical work on sense of agency (SoA), the nature of this learning has, rather surprisingly, received little attention. In the present study we consider the contribution of associative mechanisms to SoA. SoA can be measured quantitatively as a temporal linkage between voluntary actions and their external effects. Using an outcome blocking procedure, it was shown that training action–outcome associations under conditions of increased surprise augmented this temporal linkage. Moreover, these effects of surprise were correlated with schizotypy scores, suggesting that individual differences in higher level experiences are related to associative learning and to its impact on SoA. These results are discussed in terms of models of SoA, and our understanding of disrupted SoA in certain disorders. PMID:21295497

Unique and shared validity of the "Wechsler logical memory test", the "California verbal learning test", and the "verbal learning and memory test" in patients with epilepsy.

PubMed

Helmstaedter, Christoph; Wietzke, Jennifer; Lutz, Martin T

2009-12-01

This study was set-up to evaluate the construct validity of three verbal memory tests in epilepsy patients. Sixty-one consecutively evaluated patients with temporal lobe epilepsy (TLE) or extra-temporal epilepsy (E-TLE) underwent testing with the verbal learning and memory test (VLMT, the German equivalent of the Rey auditory verbal learning test, RAVLT); the California verbal learning test (CVLT); the logical memory and digit span subtests of the Wechsler memory scale, revised (WMS-R); and testing of intelligence, attention, speech and executive functions. Factor analysis of the memory tests resulted in test-specific rather than test over-spanning factors. Parameters of the CVLT and WMS-R, and to a much lesser degree of the VLMT, were highly correlated with attention, language function and vocabulary. Delayed recall measures of logical memory and the VLMT differentiated TLE from E-TLE. Learning and memory scores off all three tests differentiated mesial temporal sclerosis from other pathologies. A lateralization of the epilepsy was possible only for a subsample of 15 patients with mesial TLE. Although the three tests provide overlapping indicators for a temporal lobe epilepsy or a mesial pathology, they can hardly be taken in exchange. The tests have different demands on semantic processing and memory organization, and they appear differentially sensitive to performance in non-memory domains. The tests capability to lateralize appears to be poor. The findings encourage the further discussion of the dependency of memory outcomes on test selection.

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

Neural networks involved in learning lexical-semantic and syntactic information in a second language.

PubMed

Mueller, Jutta L; Rueschemeyer, Shirley-Ann; Ono, Kentaro; Sugiura, Motoaki; Sadato, Norihiro; Nakamura, Akinori

2014-01-01

The present study used functional magnetic resonance imaging (fMRI) to investigate the neural correlates of language acquisition in a realistic learning environment. Japanese native speakers were trained in a miniature version of German prior to fMRI scanning. During scanning they listened to (1) familiar sentences, (2) sentences including a novel sentence structure, and (3) sentences containing a novel word while visual context provided referential information. Learning-related decreases of brain activation over time were found in a mainly left-hemispheric network comprising classical frontal and temporal language areas as well as parietal and subcortical regions and were largely overlapping for novel words and the novel sentence structure in initial stages of learning. Differences occurred at later stages of learning during which content-specific activation patterns in prefrontal, parietal and temporal cortices emerged. The results are taken as evidence for a domain-general network supporting the initial stages of language learning which dynamically adapts as learners become proficient.

Improving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis

PubMed Central

Tabelow, Karsten; König, Reinhard; Polzehl, Jörg

2016-01-01

Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning. PMID:27303809

Temporal contingency.

PubMed

Gallistel, C R; Craig, Andrew R; Shahan, Timothy A

2014-01-01

Contingency, and more particularly temporal contingency, has often figured in thinking about the nature of learning. However, it has never been formally defined in such a way as to make it a measure that can be applied to most animal learning protocols. We use elementary information theory to define contingency in such a way as to make it a measurable property of almost any conditioning protocol. We discuss how making it a measurable construct enables the exploration of the role of different contingencies in the acquisition and performance of classically and operantly conditioned behavior. Copyright © 2013 Elsevier B.V. All rights reserved.

Online selective kernel-based temporal difference learning.

PubMed

Chen, Xingguo; Gao, Yang; Wang, Ruili

2013-12-01

In this paper, an online selective kernel-based temporal difference (OSKTD) learning algorithm is proposed to deal with large scale and/or continuous reinforcement learning problems. OSKTD includes two online procedures: online sparsification and parameter updating for the selective kernel-based value function. A new sparsification method (i.e., a kernel distance-based online sparsification method) is proposed based on selective ensemble learning, which is computationally less complex compared with other sparsification methods. With the proposed sparsification method, the sparsified dictionary of samples is constructed online by checking if a sample needs to be added to the sparsified dictionary. In addition, based on local validity, a selective kernel-based value function is proposed to select the best samples from the sample dictionary for the selective kernel-based value function approximator. The parameters of the selective kernel-based value function are iteratively updated by using the temporal difference (TD) learning algorithm combined with the gradient descent technique. The complexity of the online sparsification procedure in the OSKTD algorithm is O(n). In addition, two typical experiments (Maze and Mountain Car) are used to compare with both traditional and up-to-date O(n) algorithms (GTD, GTD2, and TDC using the kernel-based value function), and the results demonstrate the effectiveness of our proposed algorithm. In the Maze problem, OSKTD converges to an optimal policy and converges faster than both traditional and up-to-date algorithms. In the Mountain Car problem, OSKTD converges, requires less computation time compared with other sparsification methods, gets a better local optima than the traditional algorithms, and converges much faster than the up-to-date algorithms. In addition, OSKTD can reach a competitive ultimate optima compared with the up-to-date algorithms.

Influence of postnatal glucocorticoids on hippocampal-dependent learning varies with elevation patterns and administration methods

DTIC Science & Technology

2017-05-22

Influence of postnatal glucocorticoids on hippocampal-dependent learning varies with elevation patterns and administration methods 5b. GRANT NUMBER...of these effects varies with the elevation patterns (level, duration, temporal fluctuation) achieved by different administration methods . In general...learning varies with elevation patterns and administration methods Dragana I. Claflin a, Kevin D. Schmidt a, Zachary D. Vallandingham b, Michal

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.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

PubMed

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

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

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

Sequential Dictionary Learning From Correlated Data: Application to fMRI Data Analysis.

PubMed

Seghouane, Abd-Krim; Iqbal, Asif

2017-03-22

Sequential dictionary learning via the K-SVD algorithm has been revealed as a successful alternative to conventional data driven methods such as independent component analysis (ICA) for functional magnetic resonance imaging (fMRI) data analysis. fMRI datasets are however structured data matrices with notions of spatio-temporal correlation and temporal smoothness. This prior information has not been included in the K-SVD algorithm when applied to fMRI data analysis. In this paper we propose three variants of the K-SVD algorithm dedicated to fMRI data analysis by accounting for this prior information. The proposed algorithms differ from the K-SVD in their sparse coding and dictionary update stages. The first two algorithms account for the known correlation structure in the fMRI data by using the squared Q, R-norm instead of the Frobenius norm for matrix approximation. The third and last algorithm account for both the known correlation structure in the fMRI data and the temporal smoothness. The temporal smoothness is incorporated in the dictionary update stage via regularization of the dictionary atoms obtained with penalization. The performance of the proposed dictionary learning algorithms are illustrated through simulations and applications on real fMRI data.

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.

The Temporal Impact and Implications of E-Learning

ERIC Educational Resources Information Center

Graham, Deryn

2014-01-01

The concept of time is a key issue incorporated in most educational theories, and the notion of time has been considered in different ways in diverse approaches, such as behaviourism, genetic epistemology, cultural psychology and didactic. In research leading to the development of a nine-stage Transnational Framework for E-Learning Technologies,…

A marching-walking hybrid induces step length adaptation and transfers to natural walking

PubMed Central

Long, Andrew W.; Finley, James M.

2015-01-01

Walking is highly adaptable to new demands and environments. We have previously studied adaptation of locomotor patterns via a split-belt treadmill, where subjects learn to walk with one foot moving faster than the other. Subjects learn to adapt their walking pattern by changing the location (spatial) and time (temporal) of foot placement. Here we asked whether we can induce adaptation of a specific walking pattern when one limb does not “walk” but instead marches in place (i.e., marching-walking hybrid). The marching leg's movement is limited during the stance phase, and thus certain sensory signals important for walking may be reduced. We hypothesized that this would produce a spatial-temporal strategy different from that of normal split-belt adaptation. Healthy subjects performed two experiments to determine whether they could adapt their spatial-temporal pattern of step lengths during the marching-walking hybrid and whether the learning transfers to over ground walking. Results showed that the hybrid group did adapt their step lengths, but the time course of adaptation and deadaption was slower than that for the split-belt group. We also observed that the hybrid group utilized a mostly spatial strategy whereas the split-belt group utilized both spatial and temporal strategies. Surprisingly, we found no significant difference between the hybrid and split-belt groups in over ground transfer. Moreover, the hybrid group retained more of the learned pattern when they returned to the treadmill. These findings suggest that physical rehabilitation with this marching-walking paradigm on conventional treadmills may produce changes in symmetry comparable to what is observed during split-belt training. PMID:25867742

A marching-walking hybrid induces step length adaptation and transfers to natural walking.

PubMed

Long, Andrew W; Finley, James M; Bastian, Amy J

2015-06-01

Walking is highly adaptable to new demands and environments. We have previously studied adaptation of locomotor patterns via a split-belt treadmill, where subjects learn to walk with one foot moving faster than the other. Subjects learn to adapt their walking pattern by changing the location (spatial) and time (temporal) of foot placement. Here we asked whether we can induce adaptation of a specific walking pattern when one limb does not "walk" but instead marches in place (i.e., marching-walking hybrid). The marching leg's movement is limited during the stance phase, and thus certain sensory signals important for walking may be reduced. We hypothesized that this would produce a spatial-temporal strategy different from that of normal split-belt adaptation. Healthy subjects performed two experiments to determine whether they could adapt their spatial-temporal pattern of step lengths during the marching-walking hybrid and whether the learning transfers to over ground walking. Results showed that the hybrid group did adapt their step lengths, but the time course of adaptation and deadaption was slower than that for the split-belt group. We also observed that the hybrid group utilized a mostly spatial strategy whereas the split-belt group utilized both spatial and temporal strategies. Surprisingly, we found no significant difference between the hybrid and split-belt groups in over ground transfer. Moreover, the hybrid group retained more of the learned pattern when they returned to the treadmill. These findings suggest that physical rehabilitation with this marching-walking paradigm on conventional treadmills may produce changes in symmetry comparable to what is observed during split-belt training. Copyright © 2015 the American Physiological Society.

Plasticity of left perisylvian white-matter tracts is associated with individual differences in math learning.

PubMed

Jolles, Dietsje; Wassermann, Demian; Chokhani, Ritika; Richardson, Jennifer; Tenison, Caitlin; Bammer, Roland; Fuchs, Lynn; Supekar, Kaustubh; Menon, Vinod

2016-04-01

Plasticity of white matter tracts is thought to be essential for cognitive development and academic skill acquisition in children. However, a dearth of high-quality diffusion tensor imaging (DTI) data measuring longitudinal changes with learning, as well as methodological difficulties in multi-time point tract identification have limited our ability to investigate plasticity of specific white matter tracts. Here, we examine learning-related changes of white matter tracts innervating inferior parietal, prefrontal and temporal regions following an intense 2-month math tutoring program. DTI data were acquired from 18 third grade children, both before and after tutoring. A novel fiber tracking algorithm based on a White Matter Query Language (WMQL) was used to identify three sections of the superior longitudinal fasciculus (SLF) linking frontal and parietal (SLF-FP), parietal and temporal (SLF-PT) and frontal and temporal (SLF-FT) cortices, from which we created child-specific probabilistic maps. The SLF-FP, SLF-FT, and SLF-PT tracts identified with the WMQL method were highly reliable across the two time points and showed close correspondence to tracts previously described in adults. Notably, individual differences in behavioral gains after 2 months of tutoring were specifically correlated with plasticity in the left SLF-FT tract. Our results extend previous findings of individual differences in white matter integrity, and provide important new insights into white matter plasticity related to math learning in childhood. More generally, our quantitative approach will be useful for future studies examining longitudinal changes in white matter integrity associated with cognitive skill development.

Deep brain stimulation of the subthalamic nucleus modulates sensitivity to decision outcome value in Parkinson’s disease

NASA Astrophysics Data System (ADS)

Seymour, Ben; Barbe, Michael; Dayan, Peter; Shiner, Tamara; Dolan, Ray; Fink, Gereon R.

2016-09-01

Deep brain stimulation (DBS) of the subthalamic nucleus in Parkinson’s disease is known to cause a subtle but important adverse impact on behaviour, with impulsivity its most widely reported manifestation. However, precisely which computational components of the decision process are modulated is not fully understood. Here we probe a number of distinct subprocesses, including temporal discount, outcome utility, instrumental learning rate, instrumental outcome sensitivity, reward-loss trade-offs, and perseveration. We tested 22 Parkinson’s Disease patients both on and off subthalamic nucleus deep brain stimulation (STN-DBS), while they performed an instrumental learning task involving financial rewards and losses, and an inter-temporal choice task for financial rewards. We found that instrumental learning performance was significantly worse following stimulation, due to modulation of instrumental outcome sensitivity. Specifically, patients became less sensitive to decision values for both rewards and losses, but without any change to the learning rate or reward-loss trade-offs. However, we found no evidence that DBS modulated different components of temporal impulsivity. In conclusion, our results implicate the subthalamic nucleus in a modulation of outcome value in experience-based learning and decision-making in Parkinson’s disease, suggesting a more pervasive role of the subthalamic nucleus in the control of human decision-making than previously thought.

Deep brain stimulation of the subthalamic nucleus modulates sensitivity to decision outcome value in Parkinson’s disease

PubMed Central

Seymour, Ben; Barbe, Michael; Dayan, Peter; Shiner, Tamara; Dolan, Ray; Fink, Gereon R.

2016-01-01

Deep brain stimulation (DBS) of the subthalamic nucleus in Parkinson’s disease is known to cause a subtle but important adverse impact on behaviour, with impulsivity its most widely reported manifestation. However, precisely which computational components of the decision process are modulated is not fully understood. Here we probe a number of distinct subprocesses, including temporal discount, outcome utility, instrumental learning rate, instrumental outcome sensitivity, reward-loss trade-offs, and perseveration. We tested 22 Parkinson’s Disease patients both on and off subthalamic nucleus deep brain stimulation (STN-DBS), while they performed an instrumental learning task involving financial rewards and losses, and an inter-temporal choice task for financial rewards. We found that instrumental learning performance was significantly worse following stimulation, due to modulation of instrumental outcome sensitivity. Specifically, patients became less sensitive to decision values for both rewards and losses, but without any change to the learning rate or reward-loss trade-offs. However, we found no evidence that DBS modulated different components of temporal impulsivity. In conclusion, our results implicate the subthalamic nucleus in a modulation of outcome value in experience-based learning and decision-making in Parkinson’s disease, suggesting a more pervasive role of the subthalamic nucleus in the control of human decision-making than previously thought. PMID:27624437

Temporal abstraction and inductive logic programming for arrhythmia recognition from electrocardiograms.

PubMed

Carrault, G; Cordier, M-O; Quiniou, R; Wang, F

2003-07-01

This paper proposes a novel approach to cardiac arrhythmia recognition from electrocardiograms (ECGs). ECGs record the electrical activity of the heart and are used to diagnose many heart disorders. The numerical ECG is first temporally abstracted into series of time-stamped events. Temporal abstraction makes use of artificial neural networks to extract interesting waves and their features from the input signals. A temporal reasoner called a chronicle recogniser processes such series in order to discover temporal patterns called chronicles which can be related to cardiac arrhythmias. Generally, it is difficult to elicit an accurate set of chronicles from a doctor. Thus, we propose to learn automatically from symbolic ECG examples the chronicles discriminating the arrhythmias belonging to some specific subset. Since temporal relationships are of major importance, inductive logic programming (ILP) is the tool of choice as it enables first-order relational learning. The approach has been evaluated on real ECGs taken from the MIT-BIH database. The performance of the different modules as well as the efficiency of the whole system is presented. The results are rather good and demonstrate that integrating numerical techniques for low level perception and symbolic techniques for high level classification is very valuable.

Implicit transfer of reversed temporal structure in visuomotor sequence learning.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2014-04-01

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

Dynamics of Learning in Cultured Neuronal Networks with Antagonists of Glutamate Receptors

PubMed Central

Li, Yanling; Zhou, Wei; Li, Xiangning; Zeng, Shaoqun; Luo, Qingming

2007-01-01

Cognitive dysfunction may result from abnormality of ionotropic glutamate receptors. Although various forms of synaptic plasticity in learning that rely on altering of glutamate receptors have been considered, the evidence is insufficient from an informatics view. Dynamics could reflect neuroinformatics encoding, including temporal pattern encoding, spatial pattern encoding, and energy distribution. Discovering informatics encoding is fundamental and crucial to understanding the working principle of the neural system. In this article, we analyzed the dynamic characteristics of response activities during learning training in cultured hippocampal networks under normal and abnormal conditions of ionotropic glutamate receptors, respectively. The rate, which is one of the temporal configurations, was decreased markedly by inhibition of α-amino-3-hydroxy-5-methylisoxazole-4-proprionic acid (AMPA) receptors. Moreover, the energy distribution in different characteristic frequencies was changed markedly by inhibition of AMPA receptors. Spatial configurations, including regularization, correlation, and synchrony, were changed significantly by inhibition of N-methyl-d-aspartate receptors. These results suggest that temporal pattern encoding and energy distribution of response activities in cultured hippocampal neuronal networks during learning training are modulated by AMPA receptors, whereas spatial pattern encoding of response activities is modulated by N-methyl-d-aspartate receptors. PMID:17766359

Human dynamics of spending: Longitudinal study of a coalition loyalty program

NASA Astrophysics Data System (ADS)

Yi, Il Gu; Jeong, Hyang Min; Choi, Woosuk; Jang, Seungkwon; Lee, Heejin; Kim, Beom Jun

2014-09-01

Large-scale data of a coalition loyalty program is analyzed in terms of the temporal dynamics of customers' behaviors. We report that the two main activities of a loyalty program, earning and redemption of points, exhibit very different behaviors. It is also found that as customers become older from their early 20's, both male and female customers increase their earning and redemption activities until they arrive at the turning points, beyond which both activities decrease. The positions of turning points as well as the maximum earned and redeemed points are found to differ for males and females. On top of these temporal behaviors, we identify that there exists a learning effect and customers learn how to earn and redeem points as their experiences accumulate in time.

Process Versus Product in Social Learning: Comparative Diffusion Tensor Imaging of Neural Systems for Action Execution–Observation Matching in Macaques, Chimpanzees, and Humans

PubMed Central

Hecht, Erin E.; Gutman, David A.; Preuss, Todd M.; Sanchez, Mar M.; Parr, Lisa A.; Rilling, James K.

2013-01-01

Social learning varies among primate species. Macaques only copy the product of observed actions, or emulate, while humans and chimpanzees also copy the process, or imitate. In humans, imitation is linked to the mirror system. Here we compare mirror system connectivity across these species using diffusion tensor imaging. In macaques and chimpanzees, the preponderance of this circuitry consists of frontal–temporal connections via the extreme/external capsules. In contrast, humans have more substantial temporal–parietal and frontal–parietal connections via the middle/inferior longitudinal fasciculi and the third branch of the superior longitudinal fasciculus. In chimpanzees and humans, but not in macaques, this circuitry includes connections with inferior temporal cortex. In humans alone, connections with superior parietal cortex were also detected. We suggest a model linking species differences in mirror system connectivity and responsivity with species differences in behavior, including adaptations for imitation and social learning of tool use. PMID:22539611

Does hearing two dialects at different times help infants learn dialect-specific rules?

PubMed Central

Gonzales, Kalim; Gerken, LouAnn; Gómez, Rebecca L.

2015-01-01

Infants might be better at teasing apart dialects with different language rules when hearing the dialects at different times, since language learners do not always combine input heard at different times. However, no previous research has independently varied the temporal distribution of conflicting language input. Twelve-month-olds heard two artificial language streams representing different dialects—a “pure stream” whose sentences adhered to abstract grammar rules like aX bY, and a “mixed stream” wherein any a- or b-word could precede any X- or Y-word. Infants were then tested for generalization of the pure stream’s rules to novel sentences. Supporting our hypothesis, infants showed generalization when the two streams’ sentences alternated in minutes-long intervals without any perceptually salient change across streams (Experiment 2), but not when all sentences from these same streams were randomly interleaved (Experiment 3). Results are interpreted in light of temporal context effects in word learning. PMID:25880342

Learning and Discrimination of Audiovisual Events in Human Infants: The Hierarchical Relation between Intersensory Temporal Synchrony and Rhythmic Pattern Cues.

ERIC Educational Resources Information Center

Lewkowicz, David J.

2003-01-01

Three experiments examined 4- to 10-month-olds' perception of audio-visual (A-V) temporal synchrony cues in the presence or absence of rhythmic pattern cues. Results established that infants of all ages could discriminate between two different audio-visual rhythmic events. Only 10-month-olds detected a desynchronization of the auditory and visual…

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.

Dynamic functional connectivity shapes individual differences in associative learning.

PubMed

Fatima, Zainab; Kovacevic, Natasha; Misic, Bratislav; McIntosh, Anthony Randal

2016-11-01

Current neuroscientific research has shown that the brain reconfigures its functional interactions at multiple timescales. Here, we sought to link transient changes in functional brain networks to individual differences in behavioral and cognitive performance by using an active learning paradigm. Participants learned associations between pairs of unrelated visual stimuli by using feedback. Interindividual behavioral variability was quantified with a learning rate measure. By using a multivariate statistical framework (partial least squares), we identified patterns of network organization across multiple temporal scales (within a trial, millisecond; across a learning session, minute) and linked these to the rate of change in behavioral performance (fast and slow). Results indicated that posterior network connectivity was present early in the trial for fast, and later in the trial for slow performers. In contrast, connectivity in an associative memory network (frontal, striatal, and medial temporal regions) occurred later in the trial for fast, and earlier for slow performers. Time-dependent changes in the posterior network were correlated with visual/spatial scores obtained from independent neuropsychological assessments, with fast learners performing better on visual/spatial subtests. No relationship was found between functional connectivity dynamics in the memory network and visual/spatial test scores indicative of cognitive skill. By using a comprehensive set of measures (behavioral, cognitive, and neurophysiological), we report that individual variations in learning-related performance change are supported by differences in cognitive ability and time-sensitive connectivity in functional neural networks. Hum Brain Mapp 37:3911-3928, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Efficient Training of Supervised Spiking Neural Network via Accurate Synaptic-Efficiency Adjustment Method.

PubMed

Xie, Xiurui; Qu, Hong; Yi, Zhang; Kurths, Jurgen

2017-06-01

The spiking neural network (SNN) is the third generation of neural networks and performs remarkably well in cognitive tasks, such as pattern recognition. The temporal neural encode mechanism found in biological hippocampus enables SNN to possess more powerful computation capability than networks with other encoding schemes. However, this temporal encoding approach requires neurons to process information serially on time, which reduces learning efficiency significantly. To keep the powerful computation capability of the temporal encoding mechanism and to overcome its low efficiency in the training of SNNs, a new training algorithm, the accurate synaptic-efficiency adjustment method is proposed in this paper. Inspired by the selective attention mechanism of the primate visual system, our algorithm selects only the target spike time as attention areas, and ignores voltage states of the untarget ones, resulting in a significant reduction of training time. Besides, our algorithm employs a cost function based on the voltage difference between the potential of the output neuron and the firing threshold of the SNN, instead of the traditional precise firing time distance. A normalized spike-timing-dependent-plasticity learning window is applied to assigning this error to different synapses for instructing their training. Comprehensive simulations are conducted to investigate the learning properties of our algorithm, with input neurons emitting both single spike and multiple spikes. Simulation results indicate that our algorithm possesses higher learning performance than the existing other methods and achieves the state-of-the-art efficiency in the training of SNN.

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

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…

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer’s Disease

PubMed Central

Jie, Biao; Liu, Mingxia; Liu, Jun

2016-01-01

Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer’s disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). However, most existing sparse learning-based studies only adopt cross-sectional analysis methods, where the sparse model is learned using data from a single time-point. Actually, multiple time-points of data are often available in brain imaging applications, which can be used in some longitudinal analysis methods to better uncover the disease progression patterns. Accordingly, in this paper we propose a novel temporally-constrained group sparse learning method aiming for longitudinal analysis with multiple time-points of data. Specifically, we learn a sparse linear regression model by using the imaging data from multiple time-points, where a group regularization term is first employed to group the weights for the same brain region across different time-points together. Furthermore, to reflect the smooth changes between data derived from adjacent time-points, we incorporate two smoothness regularization terms into the objective function, i.e., one fused smoothness term which requires that the differences between two successive weight vectors from adjacent time-points should be small, and another output smoothness term which requires the differences between outputs of two successive models from adjacent time-points should also be small. We develop an efficient optimization algorithm to solve the proposed objective function. Experimental results on ADNI database demonstrate that, compared with conventional sparse learning-based methods, our proposed method can achieve improved regression performance and also help in discovering disease-related biomarkers. PMID:27093313

Contributions of Medial Temporal Lobe and Striatal Memory Systems to Learning and Retrieving Overlapping Spatial Memories

PubMed Central

Brown, Thackery I.; Stern, Chantal E.

2014-01-01

Many life experiences share information with other memories. In order to make decisions based on overlapping memories, we need to distinguish between experiences to determine the appropriate behavior for the current situation. Previous work suggests that the medial temporal lobe (MTL) and medial caudate interact to support the retrieval of overlapping navigational memories in different contexts. The present study used functional magnetic resonance imaging (fMRI) in humans to test the prediction that the MTL and medial caudate play complementary roles in learning novel mazes that cross paths with, and must be distinguished from, previously learned routes. During fMRI scanning, participants navigated virtual routes that were well learned from prior training while also learning new mazes. Critically, some routes learned during scanning shared hallways with those learned during pre-scan training. Overlap between mazes required participants to use contextual cues to select between alternative behaviors. Results demonstrated parahippocampal cortex activity specific for novel spatial cues that distinguish between overlapping routes. The hippocampus and medial caudate were active for learning overlapping spatial memories, and increased their activity for previously learned routes when they became context dependent. Our findings provide novel evidence that the MTL and medial caudate play complementary roles in the learning, updating, and execution of context-dependent navigational behaviors. PMID:23448868

Decrease in gamma-band activity tracks sequence learning

PubMed Central

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

2015-01-01

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

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.

Improving temporal bone dissection using self-directed virtual reality simulation: results of a randomized blinded control trial.

PubMed

Zhao, Yi Chen; Kennedy, Gregor; Yukawa, Kumiko; Pyman, Brian; O'Leary, Stephen

2011-03-01

A significant benefit of virtual reality (VR) simulation is the ability to provide self-direct learning for trainees. This study aims to determine whether there are any differences in performance of cadaver temporal bone dissections between novices who received traditional teaching methods and those who received unsupervised self-directed learning in a VR temporal bone simulator. Randomized blinded control trial. Royal Victorian Eye and Ear Hospital. Twenty novice trainees. After receiving an hour lecture, participants were randomized into 2 groups to receive an additional 2 hours of training via traditional teaching methods or self-directed learning using a VR simulator with automated guidance. The simulation environment presented participants with structured training tasks, which were accompanied by real-time computer-generated feedback as well as real operative videos and photos. After the training, trainees were asked to perform a cortical mastoidectomy on a cadaveric temporal bone. The dissection was videotaped and assessed by 3 otologists blinded to participants' teaching group. The overall performance scores of the simulator-based training group were significantly higher than those of the traditional training group (67% vs 29%; P < .001), with an intraclass correlation coefficient of 0.93, indicating excellent interrater reliability. Using other assessments of performance, such as injury size, the VR simulator-based training group also performed better than the traditional group. This study indicates that self-directed learning on VR simulators can be used to improve performance on cadaver dissection in novice trainees compared with traditional teaching methods alone.

Modeling the Violation of Reward Maximization and Invariance in Reinforcement Schedules

PubMed Central

La Camera, Giancarlo; Richmond, Barry J.

2008-01-01

It is often assumed that animals and people adjust their behavior to maximize reward acquisition. In visually cued reinforcement schedules, monkeys make errors in trials that are not immediately rewarded, despite having to repeat error trials. Here we show that error rates are typically smaller in trials equally distant from reward but belonging to longer schedules (referred to as “schedule length effect”). This violates the principles of reward maximization and invariance and cannot be predicted by the standard methods of Reinforcement Learning, such as the method of temporal differences. We develop a heuristic model that accounts for all of the properties of the behavior in the reinforcement schedule task but whose predictions are not different from those of the standard temporal difference model in choice tasks. In the modification of temporal difference learning introduced here, the effect of schedule length emerges spontaneously from the sensitivity to the immediately preceding trial. We also introduce a policy for general Markov Decision Processes, where the decision made at each node is conditioned on the motivation to perform an instrumental action, and show that the application of our model to the reinforcement schedule task and the choice task are special cases of this general theoretical framework. Within this framework, Reinforcement Learning can approach contextual learning with the mixture of empirical findings and principled assumptions that seem to coexist in the best descriptions of animal behavior. As examples, we discuss two phenomena observed in humans that often derive from the violation of the principle of invariance: “framing,” wherein equivalent options are treated differently depending on the context in which they are presented, and the “sunk cost” effect, the greater tendency to continue an endeavor once an investment in money, effort, or time has been made. The schedule length effect might be a manifestation of these phenomena in monkeys. PMID:18688266

Modeling the violation of reward maximization and invariance in reinforcement schedules.

PubMed

La Camera, Giancarlo; Richmond, Barry J

2008-08-08

It is often assumed that animals and people adjust their behavior to maximize reward acquisition. In visually cued reinforcement schedules, monkeys make errors in trials that are not immediately rewarded, despite having to repeat error trials. Here we show that error rates are typically smaller in trials equally distant from reward but belonging to longer schedules (referred to as "schedule length effect"). This violates the principles of reward maximization and invariance and cannot be predicted by the standard methods of Reinforcement Learning, such as the method of temporal differences. We develop a heuristic model that accounts for all of the properties of the behavior in the reinforcement schedule task but whose predictions are not different from those of the standard temporal difference model in choice tasks. In the modification of temporal difference learning introduced here, the effect of schedule length emerges spontaneously from the sensitivity to the immediately preceding trial. We also introduce a policy for general Markov Decision Processes, where the decision made at each node is conditioned on the motivation to perform an instrumental action, and show that the application of our model to the reinforcement schedule task and the choice task are special cases of this general theoretical framework. Within this framework, Reinforcement Learning can approach contextual learning with the mixture of empirical findings and principled assumptions that seem to coexist in the best descriptions of animal behavior. As examples, we discuss two phenomena observed in humans that often derive from the violation of the principle of invariance: "framing," wherein equivalent options are treated differently depending on the context in which they are presented, and the "sunk cost" effect, the greater tendency to continue an endeavor once an investment in money, effort, or time has been made. The schedule length effect might be a manifestation of these phenomena in monkeys.

Temporal entrainment of cognitive functions: musical mnemonics induce brain plasticity and oscillatory synchrony in neural networks underlying memory.

PubMed

Thaut, Michael H; Peterson, David A; McIntosh, Gerald C

2005-12-01

In a series of experiments, we have begun to investigate the effect of music as a mnemonic device on learning and memory and the underlying plasticity of oscillatory neural networks. We used verbal learning and memory tests (standardized word lists, AVLT) in conjunction with electroencephalographic analysis to determine differences between verbal learning in either a spoken or musical (verbal materials as song lyrics) modality. In healthy adults, learning in both the spoken and music condition was associated with significant increases in oscillatory synchrony across all frequency bands. A significant difference between the spoken and music condition emerged in the cortical topography of the learning-related synchronization. When using EEG measures as predictors during learning for subsequent successful memory recall, significantly increased coherence (phase-locked synchronization) within and between oscillatory brain networks emerged for music in alpha and gamma bands. In a similar study with multiple sclerosis patients, superior learning and memory was shown in the music condition when controlled for word order recall, and subjects were instructed to sing back the word lists. Also, the music condition was associated with a significant power increase in the low-alpha band in bilateral frontal networks, indicating increased neuronal synchronization. Musical learning may access compensatory pathways for memory functions during compromised PFC functions associated with learning and recall. Music learning may also confer a neurophysiological advantage through the stronger synchronization of the neuronal cell assemblies underlying verbal learning and memory. Collectively our data provide evidence that melodic-rhythmic templates as temporal structures in music may drive internal rhythm formation in recurrent cortical networks involved in learning and memory.

Dopamine reward prediction errors reflect hidden state inference across time

PubMed Central

Starkweather, Clara Kwon; Babayan, Benedicte M.; Uchida, Naoshige; Gershman, Samuel J.

2017-01-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a ‘belief state’). In this work, we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling exhibited a striking difference between two tasks that differed only with respect to whether reward was delivered deterministically. Our results favor an associative learning rule that combines cached values with hidden state inference. PMID:28263301

Dopamine reward prediction errors reflect hidden-state inference across time.

PubMed

Starkweather, Clara Kwon; Babayan, Benedicte M; Uchida, Naoshige; Gershman, Samuel J

2017-04-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a 'belief state'). Here we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling showed a notable difference between two tasks that differed only with respect to whether reward was delivered in a deterministic manner. Our results favor an associative learning rule that combines cached values with hidden-state inference.

Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics.

PubMed

Chen, Chi-Hsin; Zhang, Yayun; Yu, Chen

2018-05-01

Objects in the world usually have names at different hierarchical levels (e.g., beagle, dog, animal). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use co-occurrence information to learn hierarchical labels in contexts where the labels for individual objects and labels for categories were presented in completely separated blocks, in interleaved blocks, or mixed in the same trial. Temporal presentation schedules significantly affected the learning of individual object labels, but not the learning of category labels. Learners' subsequent generalization of category labels indicated sensitivity to the structure of statistical input. Copyright © 2017 Cognitive Science Society, Inc.

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.

Further tests of the Scalar Expectancy Theory (SET) and the Learning-to-Time (LeT) model in a temporal bisection task.

PubMed

Machado, Armando; Arantes, Joana

2006-06-01

To contrast two models of timing, Scalar Expectancy Theory (SET) and Learning to Time (LeT), pigeons were exposed to a double temporal bisection procedure. On half of the trials, they learned to choose a red key after a 1s signal and a green key after a 4s signal; on the other half of the trials, they learned to choose a blue key after a 4-s signal and a yellow key after a 16-s signal. This was Phase A of an ABA design. On Phase B, the pigeons were divided into two groups and exposed to a new bisection task in which the signals ranged from 1 to 16s and the choice keys were blue and green. One group was reinforced for choosing blue after 1-s signals and green after 16-s signals and the other group was reinforced for the opposite mapping (green after 1-s signals and blue after 16-s signals). Whereas SET predicted no differences between the groups, LeT predicted that the former group would learn the new discrimination faster than the latter group. The results were consistent with LeT. Finally, the pigeons returned to Phase A. Only LeT made specific predictions regarding the reacquisition of the four temporal discriminations. These predictions were only partly consistent with the results.

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.

Temporal neural networks and transient analysis of complex engineering systems

NASA Astrophysics Data System (ADS)

Uluyol, Onder

A theory is introduced for a multi-layered Local Output Gamma Feedback (LOGF) neural network within the paradigm of Locally-Recurrent Globally-Feedforward neural networks. It is developed for the identification, prediction, and control tasks of spatio-temporal systems and allows for the presentation of different time scales through incorporation of a gamma memory. It is initially applied to the tasks of sunspot and Mackey-Glass series prediction as benchmarks, then it is extended to the task of power level control of a nuclear reactor at different fuel cycle conditions. The developed LOGF neuron model can also be viewed as a Transformed Input and State (TIS) Gamma memory for neural network architectures for temporal processing. The novel LOGF neuron model extends the static neuron model by incorporating into it a short-term memory structure in the form of a digital gamma filter. A feedforward neural network made up of LOGF neurons can thus be used to model dynamic systems. A learning algorithm based upon the Backpropagation-Through-Time (BTT) approach is derived. It is applicable for training a general L-layer LOGF neural network. The spatial and temporal weights and parameters of the network are iteratively optimized for a given problem using the derived learning algorithm.

The entropy reduction engine: Integrating planning, scheduling, and control

NASA Technical Reports Server (NTRS)

Drummond, Mark; Bresina, John L.; Kedar, Smadar T.

1991-01-01

The Entropy Reduction Engine, an architecture for the integration of planning, scheduling, and control, is described. The architecture is motivated, presented, and analyzed in terms of its different components; namely, problem reduction, temporal projection, and situated control rule execution. Experience with this architecture has motivated the recent integration of learning. The learning methods are described along with their impact on architecture performance.

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…

The Relationship between Spatial and Temporal Magnitude Estimation of Scientific Concepts at Extreme Scales

NASA Astrophysics Data System (ADS)

Price, Aaron; Lee, H.

2010-01-01

Many astronomical objects, processes, and events exist and occur at extreme scales of spatial and temporal magnitudes. Our research draws upon the psychological literature, replete with evidence of linguistic and metaphorical links between the spatial and temporal domains, to compare how students estimate spatial and temporal magnitudes associated with objects and processes typically taught in science class.. We administered spatial and temporal scale estimation tests, with many astronomical items, to 417 students enrolled in 12 undergraduate science courses. Results show that while the temporal test was more difficult, students’ overall performance patterns between the two tests were mostly similar. However, asymmetrical correlations between the two tests indicate that students think of the extreme ranges of spatial and temporal scales in different ways, which is likely influenced by their classroom experience. When making incorrect estimations, students tended to underestimate the difference between the everyday scale and the extreme scales on both tests. This suggests the use of a common logarithmic mental number line for both spatial and temporal magnitude estimation. However, there are differences between the two tests in the errors student make in the everyday range. Among the implications discussed is the use of spatio-temporal reference frames, instead of smooth bootstrapping, to help students maneuver between scales of magnitude and the use of logarithmic transformations between reference frames. Implications for astronomy range from learning about spectra to large scale galaxy structure.

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…

Theta oscillations promote temporal sequence learning.

PubMed

Crivelli-Decker, Jordan; Hsieh, Liang-Tien; Clarke, Alex; Ranganath, Charan

2018-05-17

Many theoretical models suggest that neural oscillations play a role in learning or retrieval of temporal sequences, but the extent to which oscillations support sequence representation remains unclear. To address this question, we used scalp electroencephalography (EEG) to examine oscillatory activity over learning of different object sequences. Participants made semantic decisions on each object as they were presented in a continuous stream. For three "Consistent" sequences, the order of the objects was always fixed. Activity during Consistent sequences was compared to "Random" sequences that consisted of the same objects presented in a different order on each repetition. Over the course of learning, participants made faster semantic decisions to objects in Consistent, as compared to objects in Random sequences. Thus, participants were able to use sequence knowledge to predict upcoming items in Consistent sequences. EEG analyses revealed decreased oscillatory power in the theta (4-7 Hz) band at frontal sites following decisions about objects in Consistent sequences, as compared with objects in Random sequences. The theta power difference between Consistent and Random only emerged in the second half of the task, as participants were more effectively able to predict items in Consistent sequences. Moreover, we found increases in parieto-occipital alpha (10-13 Hz) and beta (14-28 Hz) power during the pre-response period for objects in Consistent sequences, relative to objects in Random sequences. Linear mixed effects modeling revealed that single trial theta oscillations were related to reaction time for future objects in a sequence, whereas beta and alpha oscillations were only predictive of reaction time on the current trial. These results indicate that theta and alpha/beta activity preferentially relate to future and current events, respectively. More generally our findings highlight the importance of band-specific neural oscillations in the learning of temporal order information. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Temporal Discontiguity Is neither Necessary nor Sufficient for Learning-Induced Effects on Adult Neurogenesis

PubMed Central

Leuner, Benedetta; Waddell, Jaylyn; Gould, Elizabeth; Shors, Tracey J.

2012-01-01

Some, but not all, types of learning and memory can influence neurogenesis in the adult hippocampus. Trace eyeblink conditioning has been shown to enhance the survival of new neurons, whereas delay eyeblink conditioning has no such effect. The key difference between the two training procedures is that the conditioning stimuli are separated in time during trace but not delay conditioning. These findings raise the question of whether temporal discontiguity is necessary for enhancing the survival of new neurons. Here we used two approaches to test this hypothesis. First, we examined the influence of a delay conditioning task in which the duration of the conditioned stimulus (CS) was increased nearly twofold, a procedure that critically engages the hippocampus. Although the CS and unconditioned stimulus are contiguous, this very long delay conditioning procedure increased the number of new neurons that survived. Second, we examined the influence of learning the trace conditioned response (CR) after having acquired the CR during delay conditioning, a procedure that renders trace conditioning hippocampal-independent. In this case, trace conditioning did not enhance the survival of new neurons. Together, these results demonstrate that associative learning increases the survival of new neurons in the adult hippocampus, regardless of temporal contiguity. PMID:17192426

Acquisition of neural learning in cerebellum and cerebral cortex for smooth pursuit eye movements

PubMed Central

Li, Jennifer X.; Medina, Javier F.; Frank, Loren M.; Lisberger, Stephen G.

2011-01-01

We have evaluated the emergence of neural learning in the frontal eye fields (FEFSEM) and the floccular complex of the cerebellum while monkeys learned a precisely-timed change in the direction of pursuit eye movement. For each neuron, we measured the time course of changes in neural response across a learning session that comprised at least 100 repetitions of an instructive change in target direction. In both areas, the average population learning curves tracked the behavioral changes with high fidelity, consistent with possible roles in driving learning. However, the learning curves of individual neurons sometimes bore little relation to the smooth, monotonic progression of behavioral learning. In the FEFSEM, neural learning was episodic. For individual neurons, learning appeared at different times during the learning session and sometimes disappeared by the end of the session. Different FEFSEM neurons expressed maximal learning at different times relative to the acquisition of behavioral learning. In the floccular complex, many Purkinje cells acquired learned simple-spike responses according to the same time course as behavioral learning and retained their learned responses throughout the learning session. A minority of Purkinje cells acquired learned responses late in the learning session, after behavioral learning had reached an asymptote. We conclude that learning in single neurons can follow a very different time course from behavioral learning. Both the FEFSEM and the floccular complex contain representations of multiple temporal components of learning, with different neurons contributing to learning at different times during the acquisition of a learned movement. PMID:21900551

Learning and memory functions of the Basal Ganglia.

PubMed

Packard, Mark G; Knowlton, Barbara J

2002-01-01

Although the mammalian basal ganglia have long been implicated in motor behavior, it is generally recognized that the behavioral functions of this subcortical group of structures are not exclusively motoric in nature. Extensive evidence now indicates a role for the basal ganglia, in particular the dorsal striatum, in learning and memory. One prominent hypothesis is that this brain region mediates a form of learning in which stimulus-response (S-R) associations or habits are incrementally acquired. Support for this hypothesis is provided by numerous neurobehavioral studies in different mammalian species, including rats, monkeys, and humans. In rats and monkeys, localized brain lesion and pharmacological approaches have been used to examine the role of the basal ganglia in S-R learning. In humans, study of patients with neurodegenerative diseases that compromise the basal ganglia, as well as research using brain neuroimaging techniques, also provide evidence of a role for the basal ganglia in habit learning. Several of these studies have dissociated the role of the basal ganglia in S-R learning from those of a cognitive or declarative medial temporal lobe memory system that includes the hippocampus as a primary component. Evidence suggests that during learning, basal ganglia and medial temporal lobe memory systems are activated simultaneously and that in some learning situations competitive interference exists between these two systems.

Centrality measures in temporal networks with time series analysis

NASA Astrophysics Data System (ADS)

Huang, Qiangjuan; Zhao, Chengli; Zhang, Xue; Wang, Xiaojie; Yi, Dongyun

2017-05-01

The study of identifying important nodes in networks has a wide application in different fields. However, the current researches are mostly based on static or aggregated networks. Recently, the increasing attention to networks with time-varying structure promotes the study of node centrality in temporal networks. In this paper, we define a supra-evolution matrix to depict the temporal network structure. With using of the time series analysis, the relationships between different time layers can be learned automatically. Based on the special form of the supra-evolution matrix, the eigenvector centrality calculating problem is turned into the calculation of eigenvectors of several low-dimensional matrices through iteration, which effectively reduces the computational complexity. Experiments are carried out on two real-world temporal networks, Enron email communication network and DBLP co-authorship network, the results of which show that our method is more efficient at discovering the important nodes than the common aggregating method.

Self-regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment.

PubMed

Oblak, Ethan F; Lewis-Peacock, Jarrod A; Sulzer, James S

2017-07-01

Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different self-regulation mechanisms prefer different feedback timings, and that these factors can be effectively explored and optimized via simulation prior to deployment in the MRI scanner.

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.

Self-regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment

PubMed Central

Sulzer, James S.

2017-01-01

Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different self-regulation mechanisms prefer different feedback timings, and that these factors can be effectively explored and optimized via simulation prior to deployment in the MRI scanner. PMID:28753639

Verbal memory decline from hippocampal depth electrodes in temporal lobe surgery for epilepsy.

PubMed

Ljung, Hanna; Nordlund, Arto; Strandberg, Maria; Bengzon, Johan; Källén, Kristina

2017-12-01

To explore whether patients with refractory mesial temporal lobe epilepsy risk aggravated verbal memory loss from intracranial electroencephalography (EEG) recording with longitudinal hippocampal electrodes in the language-dominant hemisphere. A long-term neuropsychological follow-up (mean 61.5 months, range 22-111 months) was performed in 40 patients after ictal registration with left hippocampal depth electrodes (study group, n = 16) or no invasive EEG, only extracranial registration (reference group, n = 24). The groups were equal with respect to education, age at seizure onset, epilepsy duration, and prevalence of pharmacoresistant temporal lobe epilepsy (TLE; 75%) versus seizure freedom (25%). Retrospective neuropsychological data from preoperative surgical workup (T1) and prospective follow-up neuropsychological data (T2) were compared. A ≥1 SD intrapatient decline was considered as clinically relevant deterioration of verbal memory. Significant decline in verbal memory was seen in 56% of the patients in the study group compared to 21% in the reference group. At T1, there were no statistical between-group differences in memory performance. At T2, between-group comparison showed significantly greater verbal memory decline for the study group (Claeson Dahl Learning and Retention Test, Verbal Learning: p = 0.05; Rey Auditory Verbal Learning Test, Total Learning: p = 0.04; Claeson Dahl Learning and Retention Test, Verbal Retention: p = 0.04). An odds ratio (OR) of 7.1 (90% confidence interval [CI] 1.3-37.7) for verbal memory decline was seen if right temporal lobe resection (R TLR) had been performed between T1 and T2. The difference between groups remained unchanged when patients who had undergone R TLR were excluded from the analysis, with a remaining aggravated significant decline in verbal memory performance for the study group compared to the reference group. Our results suggest a risk of verbal memory deterioration after the use of depth electrodes along the longitudinal axis of the hippocampus. Until this issue is further investigated, caution regarding depth electrodes in the language-dominant hemisphere hippocampus seems advisable. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

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

Seeing is believing: effects of visual contextual cues on learning and transfer of locomotor adaptation.

PubMed

Torres-Oviedo, Gelsy; Bastian, Amy J

2010-12-15

Devices such as robots or treadmills are often used to drive motor learning because they can create novel physical environments. However, the learning (i.e., adaptation) acquired on these devices only partially generalizes to natural movements. What determines the specificity of motor learning, and can this be reliably made more general? Here we investigated the effect of visual cues on the specificity of split-belt walking adaptation. We systematically removed vision to eliminate the visual-proprioceptive mismatch that is a salient cue specific to treadmills: vision indicates that we are not moving while leg proprioception indicates that we are. We evaluated the adaptation of temporal and spatial features of gait (i.e., timing and location of foot landing), their transfer to walking over ground, and washout of adaptation when subjects returned to the treadmill. Removing vision during both training (i.e., on the treadmill) and testing (i.e., over ground) strongly improved the transfer of treadmill adaptation to natural walking. Removing vision only during training increased transfer of temporal adaptation, whereas removing vision only during testing increased the transfer of spatial adaptation. This dissociation reveals differences in adaptive mechanisms for temporal and spatial features of walking. Finally training without vision increased the amount that was learned and was linked to the variability in the behavior during adaptation. In conclusion, contextual cues can be manipulated to modulate the magnitude, transfer, and washout of device-induced learning in humans. These results bring us closer to our ultimate goal of developing rehabilitation strategies that improve movements beyond the clinical setting.

Visual statistical learning is not reliably modulated by selective attention to isolated events

PubMed Central

Musz, Elizabeth; Weber, Matthew J.; Thompson-Schill, Sharon L.

2014-01-01

Recent studies of visual statistical learning (VSL) indicate that the visual system can automatically extract temporal and spatial relationships between objects. We report several attempts to replicate and extend earlier work (Turk-Browne et al., 2005) in which observers performed a cover task on one of two interleaved stimulus sets, resulting in learning of temporal relationships that occur in the attended stream, but not those present in the unattended stream. Across four experiments, we exposed observers to a similar or identical familiarization protocol, directing attention to one of two interleaved stimulus sets; afterward, we assessed VSL efficacy for both sets using either implicit response-time measures or explicit familiarity judgments. In line with prior work, we observe learning for the attended stimulus set. However, unlike previous reports, we also observe learning for the unattended stimulus set. When instructed to selectively attend to only one of the stimulus sets and ignore the other set, observers could extract temporal regularities for both sets. Our efforts to experimentally decrease this effect by changing the cover task (Experiment 1) or the complexity of the statistical regularities (Experiment 3) were unsuccessful. A fourth experiment using a different assessment of learning likewise failed to show an attentional effect. Simulations drawing random samples our first three experiments (n=64) confirm that the distribution of attentional effects in our sample closely approximates the null. We offer several potential explanations for our failure to replicate earlier findings, and discuss how our results suggest limiting conditions on the relevance of attention to VSL. PMID:25172196

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.

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.

On the integration of reinforcement learning and approximate reasoning for control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

The author discusses the importance of strengthening the knowledge representation characteristic of reinforcement learning techniques using methods such as approximate reasoning. The ARIC (approximate reasoning-based intelligent control) architecture is an example of such a hybrid approach in which the fuzzy control rules are modified (fine-tuned) using reinforcement learning. ARIC also demonstrates that it is possible to start with an approximately correct control knowledge base and learn to refine this knowledge through further experience. On the other hand, techniques such as the TD (temporal difference) algorithm and Q-learning establish stronger theoretical foundations for their use in adaptive control and also in stability analysis of hybrid reinforcement learning and approximate reasoning-based controllers.

A reinforcement learning-based architecture for fuzzy logic control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1992-01-01

This paper introduces a new method for learning to refine a rule-based fuzzy logic controller. A reinforcement learning technique is used in conjunction with a multilayer neural network model of a fuzzy controller. The approximate reasoning based intelligent control (ARIC) architecture proposed here learns by updating its prediction of the physical system's behavior and fine tunes a control knowledge base. Its theory is related to Sutton's temporal difference (TD) method. Because ARIC has the advantage of using the control knowledge of an experienced operator and fine tuning it through the process of learning, it learns faster than systems that train networks from scratch. The approach is applied to a cart-pole balancing system.

Spatio-Temporal Story Mapping Animation Based On Structured Causal Relationships Of Historical Events

NASA Astrophysics Data System (ADS)

Inoue, Y.; Tsuruoka, K.; Arikawa, M.

2014-04-01

In this paper, we proposed a user interface that displays visual animations on geographic maps and timelines for depicting historical stories by representing causal relationships among events for time series. We have been developing an experimental software system for the spatial-temporal visualization of historical stories for tablet computers. Our proposed system makes people effectively learn historical stories using visual animations based on hierarchical structures of different scale timelines and maps.

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.

Does expert perceptual anticipation transfer to a dissimilar domain?

PubMed

Müller, Sean; McLaren, Michelle; Appleby, Brendyn; Rosalie, Simon M

2015-06-01

The purpose of this experiment was to extend theoretical understanding of transfer of learning by investigating whether expert perceptual anticipation skill transfers to a dissimilar domain. The capability of expert and near-expert rugby players as well as novices to anticipate skill type within rugby (learning sport) was first examined using a temporal occlusion paradigm. Participants watched video footage of an opponent performing rugby skill types that were temporally occluded at different points in the opponent's action and then made a written prediction. Thereafter, the capability of participants to transfer their anticipation skill to predict pitch type in baseball (transfer sport) was examined. Participants watched video footage of a pitcher throwing different pitch types that were temporally occluded and made a written prediction. Results indicated that expert and near-expert rugby players anticipated significantly better than novices across all occlusion conditions. However, none of the skill groups were able to transfer anticipation skill to predict pitch type in baseball. The findings of this paper, along with existing literature, support the theoretical prediction that transfer of perceptual anticipation is expertise dependent and restricted to similar domains. (c) 2015 APA, all rights reserved).

Time-Warp–Invariant Neuronal Processing

PubMed Central

Gütig, Robert; Sompolinsky, Haim

2009-01-01

Fluctuations in the temporal durations of sensory signals constitute a major source of variability within natural stimulus ensembles. The neuronal mechanisms through which sensory systems can stabilize perception against such fluctuations are largely unknown. An intriguing instantiation of such robustness occurs in human speech perception, which relies critically on temporal acoustic cues that are embedded in signals with highly variable duration. Across different instances of natural speech, auditory cues can undergo temporal warping that ranges from 2-fold compression to 2-fold dilation without significant perceptual impairment. Here, we report that time-warp–invariant neuronal processing can be subserved by the shunting action of synaptic conductances that automatically rescales the effective integration time of postsynaptic neurons. We propose a novel spike-based learning rule for synaptic conductances that adjusts the degree of synaptic shunting to the temporal processing requirements of a given task. Applying this general biophysical mechanism to the example of speech processing, we propose a neuronal network model for time-warp–invariant word discrimination and demonstrate its excellent performance on a standard benchmark speech-recognition task. Our results demonstrate the important functional role of synaptic conductances in spike-based neuronal information processing and learning. The biophysics of temporal integration at neuronal membranes can endow sensory pathways with powerful time-warp–invariant computational capabilities. PMID:19582146

Difference-Sensitive Communities, Networked Learning, and Higher Education: Potentialities and Risks

ERIC Educational Resources Information Center

Papastephanou, Marianna

2005-01-01

Recent emphases on prospects for difference-sensitive virtual communities rely implicity or explicity on some optimist accounts of cyberspace and globalization. It is expected that hybridity, diaspora and fluidity, marking new understandings of spatiality and temporality in a globalized postmodern era, will create new forms of belonging that will…

Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

NASA Astrophysics Data System (ADS)

Beck, J. M.; Bridges, S.; Collins, C.; Rushing, J.; Graves, S. J.

2017-12-01

Researchers at the Information Technology and Systems Center at the University of Alabama in Huntsville are using Deep Learning with Convolutional Neural Networks (CNNs) to develop a method for enhancing the spatial resolutions of moderate resolution (10-60m) multispectral satellite imagery. This enhancement will effectively match the resolutions of imagery from multiple sensors to provide increased global temporal-spatial coverage for a variety of Earth science products. Our research is centered on using Deep Learning for automatically generating transformations for increasing the spatial resolution of remotely sensed images with different spatial, spectral, and temporal resolutions. One of the most important steps in using images from multiple sensors is to transform the different image layers into the same spatial resolution, preferably the highest spatial resolution, without compromising the spectral information. Recent advances in Deep Learning have shown that CNNs can be used to effectively and efficiently upscale or enhance the spatial resolution of multispectral images with the use of an auxiliary data source such as a high spatial resolution panchromatic image. In contrast, we are using both the spatial and spectral details inherent in low spatial resolution multispectral images for image enhancement without the use of a panchromatic image. This presentation will discuss how this technology will benefit many Earth Science applications that use remotely sensed images with moderate spatial resolutions.

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.…

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

Statistical Learning, Syllable Processing, and Speech Production in Healthy Hearing and Hearing-Impaired Preschool Children: A Mismatch Negativity Study.

PubMed

Studer-Eichenberger, Esther; Studer-Eichenberger, Felix; Koenig, Thomas

2016-01-01

The objectives of the present study were to investigate temporal/spectral sound-feature processing in preschool children (4 to 7 years old) with peripheral hearing loss compared with age-matched controls. The results verified the presence of statistical learning, which was diminished in children with hearing impairments (HIs), and elucidated possible perceptual mediators of speech production. Perception and production of the syllables /ba/, /da/, /ta/, and /na/ were recorded in 13 children with normal hearing and 13 children with HI. Perception was assessed physiologically through event-related potentials (ERPs) recorded by EEG in a multifeature mismatch negativity paradigm and behaviorally through a discrimination task. Temporal and spectral features of the ERPs during speech perception were analyzed, and speech production was quantitatively evaluated using speech motor maximum performance tasks. Proximal to stimulus onset, children with HI displayed a difference in map topography, indicating diminished statistical learning. In later ERP components, children with HI exhibited reduced amplitudes in the N2 and early parts of the late disciminative negativity components specifically, which are associated with temporal and spectral control mechanisms. Abnormalities of speech perception were only subtly reflected in speech production, as the lone difference found in speech production studies was a mild delay in regulating speech intensity. In addition to previously reported deficits of sound-feature discriminations, the present study results reflect diminished statistical learning in children with HI, which plays an early and important, but so far neglected, role in phonological processing. Furthermore, the lack of corresponding behavioral abnormalities in speech production implies that impaired perceptual capacities do not necessarily translate into productive deficits.

Deficits in learning and memory: parahippocampal hyperactivity and frontocortical hypoactivity in cannabis users.

PubMed

Nestor, Liam; Roberts, Gloria; Garavan, Hugh; Hester, Robert

2008-04-15

The consumption of cannabis has been linked to impairments in human learning and memory, as well as aspects of executive functioning. Cannabis-related impairments in learning and memory in chronic cannabis users, it has been argued, are caused by the effects of cannabis on hippocampal functioning. The current study involved two experiments. Experiment 1 compared 35 current users of cannabis and 38 well-matched controls on a face-name task, previously shown to activate the hippocampal region. Based on the results of experiment 1, experiment 2 used fMRI and a modified version of the face-name task, to examine cortical and (para)hippocampal activity during learning and recall in 14 current users of cannabis and 14 controls. Results of experiment 1 showed that cannabis users were significantly worse with respect to learning, short and long-term memory performance. Experiment 2 showed that despite non-significant differences in learning and memory performance, cannabis users had significantly lower levels of BOLD activity in the right superior temporal gyrus, right superior frontal gyrus, right middle frontal gyrus and left superior frontal gyrus compared to controls during learning. Results also showed that cannabis users had significantly higher BOLD activity in the right parahippocampal gyrus during learning. Hypoactivity in frontal and temporal cortices, and relative hyperactivity in the parahippocampus identify functional deficits and compensatory processes in cannabis users.

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

The Temporal Attentive Observation (TAO) Scale: Development of an Instrument to Assess Attentive Behavior Sequences during Serious Gameplay

ERIC Educational Resources Information Center

Folkestad, James E.; McKernan, Brian; Train, Stephanie; Martey, Rosa Mikeal; Rhodes, Matthew G.; Kenski, Kate; Shaw, Adrienne; Stromer-Galley, Jennifer; Clegg, Benjamin A.; Strzalkowski, Tomek

2018-01-01

The engaging nature of video games has intrigued learning professionals attempting to capture and retain learners' attention. Designing learning interventions that not only capture the learner's attention, but also are designed around the natural cycle of attention will be vital for learning. This paper introduces the temporal attentive…

Basis Expansion Approaches for Regularized Sequential Dictionary Learning Algorithms With Enforced Sparsity for fMRI Data Analysis.

PubMed

Seghouane, Abd-Krim; Iqbal, Asif

2017-09-01

Sequential dictionary learning algorithms have been successfully applied to functional magnetic resonance imaging (fMRI) data analysis. fMRI data sets are, however, structured data matrices with the notions of temporal smoothness in the column direction. This prior information, which can be converted into a constraint of smoothness on the learned dictionary atoms, has seldomly been included in classical dictionary learning algorithms when applied to fMRI data analysis. In this paper, we tackle this problem by proposing two new sequential dictionary learning algorithms dedicated to fMRI data analysis by accounting for this prior information. These algorithms differ from the existing ones in their dictionary update stage. The steps of this stage are derived as a variant of the power method for computing the SVD. The proposed algorithms generate regularized dictionary atoms via the solution of a left regularized rank-one matrix approximation problem where temporal smoothness is enforced via regularization through basis expansion and sparse basis expansion in the dictionary update stage. Applications on synthetic data experiments and real fMRI data sets illustrating the performance of the proposed algorithms are provided.

Learning temporal statistics for sensory predictions in mild cognitive impairment.

PubMed

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

2015-08-01

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

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.

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

An architecture for designing fuzzy logic controllers using neural networks

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

Described here is an architecture for designing fuzzy controllers through a hierarchical process of control rule acquisition and by using special classes of neural network learning techniques. A new method for learning to refine a fuzzy logic controller is introduced. A reinforcement learning technique is used in conjunction with a multi-layer neural network model of a fuzzy controller. The model learns by updating its prediction of the plant's behavior and is related to the Sutton's Temporal Difference (TD) method. The method proposed here has the advantage of using the control knowledge of an experienced operator and fine-tuning it through the process of learning. The approach is applied to a cart-pole balancing system.

Auditory processing disorders, verbal disfluency, and learning difficulties: a case study.

PubMed

Jutras, Benoît; Lagacé, Josée; Lavigne, Annik; Boissonneault, Andrée; Lavoie, Charlen

2007-01-01

This case study reports the findings of auditory behavioral and electrophysiological measures performed on a graduate student (identified as LN) presenting verbal disfluency and learning difficulties. Results of behavioral audiological testing documented the presence of auditory processing disorders, particularly temporal processing and binaural integration. Electrophysiological test results, including middle latency, late latency and cognitive potentials, revealed that LN's central auditory system processes acoustic stimuli differently to a reference group with normal hearing.

Temporal course of gene expression during motor memory formation in primary motor cortex of rats.

PubMed

Hertler, B; Buitrago, M M; Luft, A R; Hosp, J A

2016-12-01

Motor learning is associated with plastic reorganization of neural networks in primary motor cortex (M1) that depends on changes in gene expression. Here, we investigate the temporal profile of these changes during motor memory formation in response to a skilled reaching task in rats. mRNA-levels were measured 1h, 7h and 24h after the end of a training session using microarray technique. To assure learning specificity, trained animals were compared to a control group. In response to motor learning, genes are sequentially regulated with high time-point specificity and a shift from initial suppression to later activation. The majority of regulated genes can be linked to learning-related plasticity. In the gene-expression cascade following motor learning, three different steps can be defined: (1) an initial suppression of genes influencing gene transcription. (2) Expression of genes that support translation of mRNA in defined compartments. (3) Expression of genes that immediately mediates plastic changes. Gene expression peaks after 24h - this is a much slower time-course when compared to hippocampus-dependent learning, where peaks of gene-expression can be observed 6-12h after training ended. Copyright © 2016 Elsevier Inc. All rights reserved.

Testing the scalar expectancy theory (SET) and the learning-to-time model (LeT) in a double bisection task.

PubMed

Machado, Armando; Pata, Paulo

2005-02-01

Two theories of timing, scalar expectancy theory (SET) and learning-to-time (LeT), make substantially different assumptions about what animals learn in temporal tasks. In a test of these assumptions, pigeons learned two temporal discriminations. On Type 1 trials, they learned to choose a red key after a 1-sec signal and a green key after a 4-sec signal; on Type 2 trials, they learned to choose a blue key after a 4-sec signal and a yellow key after either an 8-sec signal (Group 8) or a 16-sec signal (Group 16). Then, the birds were exposed to signals 1 sec, 4 sec, and 16 sec in length and given a choice between novel key combinations (red or green vs. blue or yellow). The choice between the green key and the blue key was of particular significance because both keys were associated with the same 4-sec signal. Whereas SET predicted no effect of the test signal duration on choice, LeT predicted that preference for green would increase monotonically with the length of the signal but would do so faster for Group 8 than for Group 16. The results were consistent with LeT, but not with SET.

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

Self-learning fuzzy controllers based on temporal back propagation

NASA Technical Reports Server (NTRS)

Jang, Jyh-Shing R.

1992-01-01

This paper presents a generalized control strategy that enhances fuzzy controllers with self-learning capability for achieving prescribed control objectives in a near-optimal manner. This methodology, termed temporal back propagation, is model-insensitive in the sense that it can deal with plants that can be represented in a piecewise-differentiable format, such as difference equations, neural networks, GMDH structures, and fuzzy models. Regardless of the numbers of inputs and outputs of the plants under consideration, the proposed approach can either refine the fuzzy if-then rules if human experts, or automatically derive the fuzzy if-then rules obtained from human experts are not available. The inverted pendulum system is employed as a test-bed to demonstrate the effectiveness of the proposed control scheme and the robustness of the acquired fuzzy controller.

Temporal sequence learning in winner-take-all networks of spiking neurons demonstrated in a brain-based device.

PubMed

McKinstry, Jeffrey L; Edelman, Gerald M

2013-01-01

Animal behavior often involves a temporally ordered sequence of actions learned from experience. Here we describe simulations of interconnected networks of spiking neurons that learn to generate patterns of activity in correct temporal order. The simulation consists of large-scale networks of thousands of excitatory and inhibitory neurons that exhibit short-term synaptic plasticity and spike-timing dependent synaptic plasticity. The neural architecture within each area is arranged to evoke winner-take-all (WTA) patterns of neural activity that persist for tens of milliseconds. In order to generate and switch between consecutive firing patterns in correct temporal order, a reentrant exchange of signals between these areas was necessary. To demonstrate the capacity of this arrangement, we used the simulation to train a brain-based device responding to visual input by autonomously generating temporal sequences of motor actions.

Neurotoxic lesions of ventrolateral prefrontal cortex impair object-in-place scene memory

PubMed Central

Wilson, Charles R E; Gaffan, David; Mitchell, Anna S; Baxter, Mark G

2007-01-01

Disconnection of the frontal lobe from the inferotemporal cortex produces deficits in a number of cognitive tasks that require the application of memory-dependent rules to visual stimuli. The specific regions of frontal cortex that interact with the temporal lobe in performance of these tasks remain undefined. One capacity that is impaired by frontal–temporal disconnection is rapid learning of new object-in-place scene problems, in which visual discriminations between two small typographic characters are learned in the context of different visually complex scenes. In the present study, we examined whether neurotoxic lesions of ventrolateral prefrontal cortex in one hemisphere, combined with ablation of inferior temporal cortex in the contralateral hemisphere, would impair learning of new object-in-place scene problems. Male macaque monkeys learned 10 or 20 new object-in-place problems in each daily test session. Unilateral neurotoxic lesions of ventrolateral prefrontal cortex produced by multiple injections of a mixture of ibotenate and N-methyl-d-aspartate did not affect performance. However, when disconnection from inferotemporal cortex was completed by ablating this region contralateral to the neurotoxic prefrontal lesion, new learning was substantially impaired. Sham disconnection (injecting saline instead of neurotoxin contralateral to the inferotemporal lesion) did not affect performance. These findings support two conclusions: first, that the ventrolateral prefrontal cortex is a critical area within the frontal lobe for scene memory; and second, the effects of ablations of prefrontal cortex can be confidently attributed to the loss of cell bodies within the prefrontal cortex rather than to interruption of fibres of passage through the lesioned area. PMID:17445247

Spatio-Temporal Simulation and Analysis of Regional Ecological Security Based on Lstm

NASA Astrophysics Data System (ADS)

Gong, C.; Qi, L.; Heming, L.; Karimian, H.; Yuqin, M.

2017-10-01

Region is a complicated system, where human, nature and society interact and influence. Quantitative modeling and simulation of ecology in the region are the key to realize the strategy of regional sustainable development. Traditional machine learning methods have made some achievements in the modeling of regional ecosystems, but it is difficult to determine the learning characteristics and to realize spatio-temporal simulation. Deep learning does not need prior identification of training characteristics, have excellent feature learning ability, can improve the accuracy of model prediction, so the use of deep learning model has a significant advantage. Therefore, we use net primary productivity (NPP), atmospheric optical depth (AOD), moderate-resolution imaging spectrometer (MODIS), Normalized Difference Vegetation Index (NDVI), landcover and population data, and use LSTM to do spatio-temporal simulation. We conduct spatial analysis and driving force analysis. The conclusions are as follows: the ecological deficit of northwestern Henan and urban communities such as Zhengzhou is higher. The reason of former lies in the weak land productivity of the Loess Plateau, the irrational crop cultivation mode. The latter lies in the high consumption of resources in the large urban agglomeration; The positive trend of Henan ecological development from 2013 is mainly due to the effective environmental protection policy in the 12th five-year plan; The main driver of the sustained ecological deficit growth of Henan in 2004-2013 is high-speed urbanization, increasing population and goods consumption. This article provides relevant basic scientific support and reference for the regional ecological scientific management and construction.

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.

From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

PubMed

Grossberg, Stephen

2015-09-24

This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory. Copyright © 2014 Elsevier B.V. All rights reserved.

Modeling Geomagnetic Variations using a Machine Learning Framework

NASA Astrophysics Data System (ADS)

Cheung, C. M. M.; Handmer, C.; Kosar, B.; Gerules, G.; Poduval, B.; Mackintosh, G.; Munoz-Jaramillo, A.; Bobra, M.; Hernandez, T.; McGranaghan, R. M.

2017-12-01

We present a framework for data-driven modeling of Heliophysics time series data. The Solar Terrestrial Interaction Neural net Generator (STING) is an open source python module built on top of state-of-the-art statistical learning frameworks (traditional machine learning methods as well as deep learning). To showcase the capability of STING, we deploy it for the problem of predicting the temporal variation of geomagnetic fields. The data used includes solar wind measurements from the OMNI database and geomagnetic field data taken by magnetometers at US Geological Survey observatories. We examine the predictive capability of different machine learning techniques (recurrent neural networks, support vector machines) for a range of forecasting times (minutes to 12 hours). STING is designed to be extensible to other types of data. We show how STING can be used on large sets of data from different sensors/observatories and adapted to tackle other problems in Heliophysics.

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

PubMed

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

2017-03-01

We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns, whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of intonation contours: Previously encountered and novel exemplars are categorized together equally often, as long as distance from the prototype is controlled. However, age-related differences in categorization performance also exist. Given the same experience, adults form narrower categories than children. In addition, adults pay more attention to the end of the contour, while children appear to pay equal attention to the beginning and the end. The age range we examine appears to capture the tail-end of the developmental trajectory for learning intonation contour categories: There is a continuous effect of age on category breadth within the child group, but the oldest children (older than 10;3) are adult-like. Copyright © 2016 Cognitive Science Society, Inc.

Perceptual learning of intonation contour categories in adults and 9 to 11-year-old children: Adults are more narrow-minded

PubMed Central

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

2015-01-01

We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of intonation contours: previously encountered and novel exemplars are categorized together equally often, as long as distance from the prototype is controlled. However, age-related differences in categorization performance also exist. Given the same experience, adults form narrower categories than children. In addition, adults pay more attention to the end of the contour while children appear to pay equal attention to the beginning and the end. The age range we examine appears to capture the tail-end of the developmental trajectory for learning intonation contour categories: there is a continuous effect of age on category breadth within the child group, but the oldest children (older than 10;3) are adult-like. PMID:26901251

A computational model of Dopamine and Acetylcholine aberrant learning in Basal Ganglia.

PubMed

Baston, Chiara; Ursino, Mauro

2015-01-01

Basal Ganglia (BG) are implied in many motor and cognitive tasks, such as action selection, and have a central role in many pathologies, primarily Parkinson Disease. In the present work, we use a recently developed biologically inspired BG model to analyze how the dopamine (DA) level can affect the temporal response during action selection, and the capacity to learn new actions following rewards and punishments. The model incorporates the 3 main pathways (direct, indirect and hyperdirect) working in BG functioning. The behavior of 2 alternative networks (the first with normal DA levels, the second with reduced DA) is analyzed both in untrained conditions, and during training performed in different epochs. The results show that reduced DA causes delayed temporal responses in the untrained network, and difficult of learning during training, characterized by the necessity of much more epochs. The results provide interesting hints to understand the behavior of healthy and dopamine depleted subjects, such as parkinsonian patients.

Mesolimbic Dopamine Signals the Value of Work

PubMed Central

Hamid, Arif A.; Pettibone, Jeffrey R.; Mabrouk, Omar S.; Hetrick, Vaughn L.; Schmidt, Robert; Vander Weele, Caitlin M.; Kennedy, Robert T.; Aragona, Brandon J.; Berke, Joshua D.

2015-01-01

Dopamine cell firing can encode errors in reward prediction, providing a learning signal to guide future behavior. Yet dopamine is also a key modulator of motivation, invigorating current behavior. Existing theories propose that fast (“phasic”) dopamine fluctuations support learning, while much slower (“tonic”) dopamine changes are involved in motivation. We examined dopamine release in the nucleus accumbens across multiple time scales, using complementary microdialysis and voltammetric methods during adaptive decision-making. We first show that minute-by-minute dopamine levels covary with reward rate and motivational vigor. We then show that second-by-second dopamine release encodes an estimate of temporally-discounted future reward (a value function). We demonstrate that changing dopamine immediately alters willingness to work, and reinforces preceding action choices by encoding temporal-difference reward prediction errors. Our results indicate that dopamine conveys a single, rapidly-evolving decision variable, the available reward for investment of effort, that is employed for both learning and motivational functions. PMID:26595651

Decision making under ambiguity and under risk in mesial temporal lobe epilepsy.

PubMed

Delazer, Margarete; Zamarian, Laura; Bonatti, Elisabeth; Kuchukhidze, Giorgi; Koppelstätter, Florian; Bodner, Thomas; Benke, Thomas; Trinka, Eugen

2010-01-01

Decision making is essential in everyday life. Though the importance of the mesial temporal lobe in emotional processing and feedback learning is generally recognized, decision making in mesial temporal lobe epilepsy (mTLE) is almost unexplored so far. Twenty-eight consecutive epilepsy patients with drug resistant mTLE and fifty healthy controls performed decision tasks under initial ambiguity (participants have to learn by feedback to make advantageous decisions) and under risk (advantageous choices may be made by estimating risks and by rational strategies). A subgroup analysis compared the performance of patients affected by MRI-verified abnormalities of the hippocampus or amygdala. The effect of lesion side was also assessed. In decision under ambiguity, mTLE patients showed marked deficits and did not improve over the task. Patients with hippocampus abnormality and patients with amygdala abnormality showed comparable deficits. No difference was found between right and left TLE groups. In decision under risk, mTLE patients performed at the same level as controls. Results suggest that mTLE patients have difficulties in learning from feedback and in making decisions in uncertain, ambiguous situations. By contrast, they are able to make advantageous decisions when full information is given and risks, possible gains and losses are exactly defined.

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

PubMed

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

2011-06-01

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

Kernel Recursive Least-Squares Temporal Difference Algorithms with Sparsification and Regularization

PubMed Central

Zhu, Qingxin; Niu, Xinzheng

2016-01-01

By combining with sparse kernel methods, least-squares temporal difference (LSTD) algorithms can construct the feature dictionary automatically and obtain a better generalization ability. However, the previous kernel-based LSTD algorithms do not consider regularization and their sparsification processes are batch or offline, which hinder their widespread applications in online learning problems. In this paper, we combine the following five techniques and propose two novel kernel recursive LSTD algorithms: (i) online sparsification, which can cope with unknown state regions and be used for online learning, (ii) L 2 and L 1 regularization, which can avoid overfitting and eliminate the influence of noise, (iii) recursive least squares, which can eliminate matrix-inversion operations and reduce computational complexity, (iv) a sliding-window approach, which can avoid caching all history samples and reduce the computational cost, and (v) the fixed-point subiteration and online pruning, which can make L 1 regularization easy to implement. Finally, simulation results on two 50-state chain problems demonstrate the effectiveness of our algorithms. PMID:27436996

Kernel Recursive Least-Squares Temporal Difference Algorithms with Sparsification and Regularization.

PubMed

Zhang, Chunyuan; Zhu, Qingxin; Niu, Xinzheng

2016-01-01

By combining with sparse kernel methods, least-squares temporal difference (LSTD) algorithms can construct the feature dictionary automatically and obtain a better generalization ability. However, the previous kernel-based LSTD algorithms do not consider regularization and their sparsification processes are batch or offline, which hinder their widespread applications in online learning problems. In this paper, we combine the following five techniques and propose two novel kernel recursive LSTD algorithms: (i) online sparsification, which can cope with unknown state regions and be used for online learning, (ii) L 2 and L 1 regularization, which can avoid overfitting and eliminate the influence of noise, (iii) recursive least squares, which can eliminate matrix-inversion operations and reduce computational complexity, (iv) a sliding-window approach, which can avoid caching all history samples and reduce the computational cost, and (v) the fixed-point subiteration and online pruning, which can make L 1 regularization easy to implement. Finally, simulation results on two 50-state chain problems demonstrate the effectiveness of our algorithms.

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.

Spike Train Auto-Structure Impacts Post-Synaptic Firing and Timing-Based Plasticity

PubMed Central

Scheller, Bertram; Castellano, Marta; Vicente, Raul; Pipa, Gordon

2011-01-01

Cortical neurons are typically driven by several thousand synapses. The precise spatiotemporal pattern formed by these inputs can modulate the response of a post-synaptic cell. In this work, we explore how the temporal structure of pre-synaptic inhibitory and excitatory inputs impact the post-synaptic firing of a conductance-based integrate and fire neuron. Both the excitatory and inhibitory input was modeled by renewal gamma processes with varying shape factors for modeling regular and temporally random Poisson activity. We demonstrate that the temporal structure of mutually independent inputs affects the post-synaptic firing, while the strength of the effect depends on the firing rates of both the excitatory and inhibitory inputs. In a second step, we explore the effect of temporal structure of mutually independent inputs on a simple version of Hebbian learning, i.e., hard bound spike-timing-dependent plasticity. We explore both the equilibrium weight distribution and the speed of the transient weight dynamics for different mutually independent gamma processes. We find that both the equilibrium distribution of the synaptic weights and the speed of synaptic changes are modulated by the temporal structure of the input. Finally, we highlight that the sensitivity of both the post-synaptic firing as well as the spike-timing-dependent plasticity on the auto-structure of the input of a neuron could be used to modulate the learning rate of synaptic modification. PMID:22203800

Encoding order and developmental dyslexia: A family of skills predicting different orthographic components

PubMed Central

Romani, Cristina; Tsouknida, Effie; Olson, Andrew

2015-01-01

We investigated order encoding in developmental dyslexia using a task that presented nonalphanumeric visual characters either simultaneously or sequentially—to tap spatial and temporal order encoding, respectively—and asked participants to reproduce their order. Dyslexic participants performed poorly in the sequential condition, but normally in the simultaneous condition, except for positions most susceptible to interference. These results are novel in demonstrating a selective difficulty with temporal order encoding in a dyslexic group. We also tested the associations between our order reconstruction tasks and: (a) lexical learning and phonological tasks; and (b) different reading and spelling tasks. Correlations were extensive when the whole group of participants was considered together. When dyslexics and controls were considered separately, different patterns of association emerged between orthographic tasks on the one side and tasks tapping order encoding, phonological processing, and written learning on the other. These results indicate that different skills support different aspects of orthographic processing and are impaired to different degrees in individuals with dyslexia. Therefore, developmental dyslexia is not caused by a single impairment, but by a family of deficits loosely related to difficulties with order. Understanding the contribution of these different deficits will be crucial to deepen our understanding of this disorder. PMID:25246235

Differences in visual vs. verbal memory impairments as a result of focal temporal lobe damage in patients with traumatic brain injury.

PubMed

Ariza, Mar; Pueyo, Roser; Junqué, Carme; Mataró, María; Poca, María Antonia; Mena, Maria Pau; Sahuquillo, Juan

2006-09-01

The aim of the present study was to determine whether the type of lesion in a sample of moderate and severe traumatic brain injury (TBI) was related to material-specific memory impairment. Fifty-nine patients with TBI were classified into three groups according to whether the site of the lesion was right temporal, left temporal or diffuse. Six-months post-injury, visual (Warrington's Facial Recognition Memory Test and Rey's Complex Figure Test) and verbal (Rey's Auditory Verbal Learning Test) memories were assessed. Visual memory deficits assessed by facial memory were associated with right temporal lobe lesion, whereas verbal memory performance assessed with a list of words was related to left temporal lobe lesion. The group with diffuse injury showed both verbal and visual memory impairment. These results suggest a material-specific memory impairment in moderate and severe TBI after focal temporal lesions and a non-specific memory impairment after diffuse damage.

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.

Differential neuropsychological test sensitivity to left temporal lobe epilepsy.

PubMed

Loring, David W; Strauss, Esther; Hermann, Bruce P; Barr, William B; Perrine, Kenneth; Trenerry, Max R; Chelune, Gordon; Westerveld, Michael; Lee, Gregory P; Meador, Kimford J; Bowden, Stephen C

2008-05-01

We examined the sensitivity of the Rey Auditory Verbal Learning Test (AVLT), California Verbal Learning Test (CVLT), Boston Naming Test (BNT), and Multilingual Aphasia Examination Visual Naming subtest (MAE VN) to lateralized temporal lobe epilepsy (TLE) in patients who subsequently underwent anterior temporal lobectomy. For the AVLT (n = 189), left TLE patients performed more poorly than their right TLE counterparts [left TLE = 42.9 (10.6), right TLE = 47.7 (9.9); p < .002 (Cohen's d = .47)]. Although statistically significant, the CVLT group difference (n = 212) was of a smaller magnitude [left LTE = 40.7 (11.1), right TLE = 43.8 (9.9); (p < .03, Cohen's d = .29)] than the AVLT. Group differences were also present for both measures of confrontation naming ability [BNT: left LTE = 43.1 (8.9), right TLE = 48.1 (8.9); p < .001 (Cohen's d = .56); MAE VN: left TLE = 42.2, right TLE = 45.6, p = .02 (Cohen's d = .36)]. When these data were modeled in independent logistic regression analyses, the AVLT and BNT both significantly predicted side of seizure focus, although the positive likelihood ratios were modest. In the subset of 108 patients receiving both BNT and AVLT, the AVLT was the only significant predictor of seizure laterality, suggesting individual patient variability regarding whether naming or memory testing may be more sensitive to lateralized TLE.

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.

Dissociating Medial Temporal and Striatal Memory Systems With a Same/Different Matching Task: Evidence for Two Neural Systems in Human Recognition.

PubMed

Sinha, Neha; Glass, Arnold Lewis

2017-01-01

The medial temporal lobe and striatum have both been implicated as brain substrates of memory and learning. Here, we show dissociation between these two memory systems using a same/different matching task, in which subjects judged whether four-letter strings were the same or different. Different RT was determined by the left-to-right location of the first letter different between the study and test string, consistent with a left-to-right comparison of the study and test strings, terminating when a difference was found. This comparison process results in same responses being slower than different responses. Nevertheless, same responses were faster than different responses. Same responses were associated with hippocampus activation. Different responses were associated with both caudate and hippocampus activation. These findings are consistent with the dual-system hypothesis of mammalian memory and extend the model to human visual recognition.

Differential effects of bihemispheric and unihemispheric transcranial direct current stimulation in young and elderly adults in verbal learning.

PubMed

Fiori, Valentina; Nitsche, Michael; Iasevoli, Luigi; Cucuzza, Gabriella; Caltagirone, Carlo; Marangolo, Paola

2017-03-15

For the past few years, the potential of transcranial direct current stimulation (tDCS) for the treatment of several pathologies has been investigated. In the language domain, several studies, in healthy and brain-damaged populations, have already shown that tDCS is effective in enhancing naming, repetition and semantic word generation. In those studies, different tDCS electrode configurations have been tested, however, a direct comparison between different montages in verbal learning has never been conducted. In this study, we aimed to explore the impact of bihemispheric and unihemispheric tDCS on verbal learning task performance in two groups (young vs. elderly). Fifteen healthy volunteers participated per group. Each participant received three stimulation conditions: unihemispheric anodal tDCS over the left temporal area, bihemispheric tDCS over the left (anodal) and right (cathodal) temporal areas and a sham condition. During active stimulation, tDCS (20min, 2mA) was applied while each participant learned twenty pseudowords (arbitrarily assigned to corresponding pictures). No significant differences were found between the three conditions for the young group with regard to accuracy and vocal reaction times. In contrast, in the elderly group, real stimulation improved performance compared to sham but bihemispheric tDCS was more efficient than unilateral stimulation. These results suggest that bihemispheric stimulation is more effective in improving language learning but this effect is age-dependent. The hypothesis is advanced that cortical changes in the course of aging might differentially impact on tDCS efficacy on behavioral performance. These data may also have implications for treatment of stroke patients with language impairment. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

When Learning Disturbs Memory – Temporal Profile of Retroactive Interference of Learning on Memory Formation

PubMed Central

Sosic-Vasic, Zrinka; Hille, Katrin; Kröner, Julia; Spitzer, Manfred; Kornmeier, Jürgen

2018-01-01

Introduction: Consolidation is defined as the time necessary for memory stabilization after learning. In the present study we focused on effects of interference during the first 12 consolidation minutes after learning. Participants had to learn a set of German – Japanese word pairs in an initial learning task and a different set of German – Japanese word pairs in a subsequent interference task. The interference task started in different experimental conditions at different time points (0, 3, 6, and 9 min) after the learning task and was followed by subsequent cued recall tests. In a control experiment the interference periods were replaced by rest periods without any interference. Results: The interference task decreased memory performance by up to 20%, with negative effects at all interference time points and large variability between participants concerning both the time point and the size of maximal interference. Further, fast learners seem to be more affected by interference than slow learners. Discussion: Our results indicate that the first 12 min after learning are highly important for memory consolidation, without a general pattern concerning the precise time point of maximal interference across individuals. This finding raises doubts about the generalized learning recipes and calls for individuality of learning schedules. PMID:29503621

Same Items, Different Order: Effects of Temporal Variability on Infant Categorization

ERIC Educational Resources Information Center

Mather, Emily; Plunkett, Kim

2011-01-01

How does variability between members of a category influence infants' category learning? We explore the impact of the order in which different items are sampled on category formation. Two groups of 10-months-olds were presented with a series of exemplars to be organized into a single category. In a low distance group, the order of presentation…

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.

Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals?

PubMed

Chen, Shi; Ilany, Amiyaal; White, Brad J; Sanderson, Michael W; Lanzas, Cristina

2015-01-01

Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system (RTLS) to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density), subgroup clustering (modularity), triadic property (transitivity), and dyadic interactions (correlation coefficient from a quadratic assignment procedure) at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level) or temporal (aggregated at daily level) resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc.) also changed substantially at different time and locations. There were certain time (feeding) and location (hay) that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect) disease transmission pathways.

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.

Back-propagation learning of infinite-dimensional dynamical systems.

PubMed

Tokuda, Isao; Tokunaga, Ryuji; Aihara, Kazuyuki

2003-10-01

This paper presents numerical studies of applying back-propagation learning to a delayed recurrent neural network (DRNN). The DRNN is a continuous-time recurrent neural network having time delayed feedbacks and the back-propagation learning is to teach spatio-temporal dynamics to the DRNN. Since the time-delays make the dynamics of the DRNN infinite-dimensional, the learning algorithm and the learning capability of the DRNN are different from those of the ordinary recurrent neural network (ORNN) having no time-delays. First, two types of learning algorithms are developed for a class of DRNNs. Then, using chaotic signals generated from the Mackey-Glass equation and the Rössler equations, learning capability of the DRNN is examined. Comparing the learning algorithms, learning capability, and robustness against noise of the DRNN with those of the ORNN and time delay neural network, advantages as well as disadvantages of the DRNN are investigated.

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.

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.

Learning Temporal Statistics for Sensory Predictions in Aging.

PubMed

Luft, Caroline Di Bernardi; Baker, Rosalind; Goldstone, Aimee; Zhang, Yang; Kourtzi, Zoe

2016-03-01

Predicting future events based on previous knowledge about the environment is critical for successful everyday interactions. Here, we ask which brain regions support our ability to predict the future based on implicit knowledge about the past in young and older age. Combining behavioral and fMRI measurements, we test whether training on structured temporal sequences improves the ability to predict upcoming sensory events; we then compare brain regions involved in learning predictive structures between young and older adults. Our behavioral results demonstrate that exposure to temporal sequences without feedback facilitates the ability of young and older adults to predict the orientation of an upcoming stimulus. Our fMRI results provide evidence for the involvement of corticostriatal regions in learning predictive structures in both young and older learners. In particular, we showed learning-dependent fMRI responses for structured sequences in frontoparietal regions and the striatum (putamen) for young adults. However, for older adults, learning-dependent activations were observed mainly in subcortical (putamen, thalamus) regions but were weaker in frontoparietal regions. Significant correlations of learning-dependent behavioral and fMRI changes in these regions suggest a strong link between brain activations and behavioral improvement rather than general overactivation. Thus, our findings suggest that predicting future events based on knowledge of temporal statistics engages brain regions involved in implicit learning in both young and older adults.

A new dynamic 3D virtual methodology for teaching the mechanics of atrial septation as seen in the human heart.

PubMed

Schleich, Jean-Marc; Dillenseger, Jean-Louis; Houyel, Lucile; Almange, Claude; Anderson, Robert H

2009-01-01

Learning embryology remains difficult, since it requires understanding of many complex phenomena. The temporal evolution of developmental events has classically been illustrated using cartoons, which create difficulty in linking spatial and temporal aspects, such correlation being the keystone of descriptive embryology. We synthesized the bibliographic data from recent studies of atrial septal development. On the basis of this synthesis, consensus on the stages of atrial septation as seen in the human heart has been reached by a group of experts in cardiac embryology and pediatric cardiology. This has permitted the preparation of three-dimensional (3D) computer graphic objects for the anatomical components involved in the different stages of normal human atrial septation. We have provided a virtual guide to the process of normal atrial septation, the animation providing an appreciation of the temporal and morphologic events necessary to separate the systemic and pulmonary venous returns. We have shown that our animations of normal human atrial septation increase significantly the teaching of the complex developmental processes involved, and provide a new dynamic for the process of learning.

Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.

PubMed

Gong, Kuang; Cheng-Liao, Jinxiu; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2018-04-01

Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information into image reconstruction. Previously, kernel learning has been successfully embedded into static and dynamic PET image reconstruction using either PET temporal or MRI information. Here, we combine both PET temporal and MRI information adaptively to improve the quality of direct Patlak reconstruction. We examined different approaches to combine the PET and MRI information in kernel learning to address the issue of potential mismatches between MRI and PET signals. Computer simulations and hybrid real-patient data acquired on a simultaneous PET/MR scanner were used to evaluate the proposed methods. Results show that the method that combines PET temporal information and MRI spatial information adaptively based on the structure similarity index has the best performance in terms of noise reduction and resolution improvement.

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.

Real-time Mainshock Forecast by Statistical Discrimination of Foreshock Clusters

NASA Astrophysics Data System (ADS)

Nomura, S.; Ogata, Y.

2016-12-01

Foreshock discremination is one of the most effective ways for short-time forecast of large main shocks. Though many large earthquakes accompany their foreshocks, discreminating them from enormous small earthquakes is difficult and only probabilistic evaluation from their spatio-temporal features and magnitude evolution may be available. Logistic regression is the statistical learning method best suited to such binary pattern recognition problems where estimates of a-posteriori probability of class membership are required. Statistical learning methods can keep learning discreminating features from updating catalog and give probabilistic recognition of forecast in real time. We estimated a non-linear function of foreshock proportion by smooth spline bases and evaluate the possibility of foreshocks by the logit function. In this study, we classified foreshocks from earthquake catalog by the Japan Meteorological Agency by single-link clustering methods and learned spatial and temporal features of foreshocks by the probability density ratio estimation. We use the epicentral locations, time spans and difference in magnitudes for learning and forecasting. Magnitudes of main shocks are also predicted our method by incorporating b-values into our method. We discuss the spatial pattern of foreshocks from the classifier composed by our model. We also implement a back test to validate predictive performance of the model by this catalog.

Evidence for age-related changes to temporal attention and memory from the choice time production task

PubMed Central

Gooch, Cynthia M.; Stern, Yaakov; Rakitin, Brian C.

2009-01-01

The effect of aging on interval timing was examined using a choice time production task, which required participants to choose a key response based on the location of the stimulus, but to delay responding until after a learned time interval. Experiment 1 varied attentional demands of the response choice portion of the task by varying difficulty of stimulus-response mapping. Choice difficulty affected temporal accuracy equally in both age groups, but older participants’ response latencies were more variable under more difficult response choice conditions. Experiment 2 tested the contribution of long-term memory to differences in choice time production between age groups over 3 days of testing. Direction of errors in time production between the two age groups diverged over the 3 sessions, but variability did not differ. Results from each experiment separately show age-related changes to attention and memory in temporal processing using different measures and manipulations in the same task. PMID:19132578

Hippocampal, amygdala, and neocortical synchronization of theta rhythms is related to an immediate recall during rey auditory verbal learning test.

PubMed

Babiloni, Claudio; Vecchio, Fabrizio; Mirabella, Giovanni; Buttiglione, Maura; Sebastiano, Fabio; Picardi, Angelo; Di Gennaro, Giancarlo; Quarato, Pier P; Grammaldo, Liliana G; Buffo, Paola; Esposito, Vincenzo; Manfredi, Mario; Cantore, Giampaolo; Eusebi, Fabrizio

2009-07-01

It is well known that theta rhythms (3-8 Hz) are the fingerprint of hippocampus, and that neural activity accompanying encoding of words differs according to whether the items are later remembered or forgotten ["subsequent memory effect" (SME)]. Here, we tested the hypothesis that temporal synchronization of theta rhythms among hippocampus, amygdala, and neocortex is related to immediate memorization of repeated words. To address this issue, intracerebral electroencephalographic (EEG) activity was recorded in five subjects with drug-resistant temporal lobe epilepsy (TLE), under presurgical monitoring routine. During the recording of the intracerebral EEG activity, the subjects performed a computerized version of Rey auditory verbal learning test (RAVLT), a popular test for the clinical evaluation of the immediate and delayed memory. They heard the same list of 15 common words for five times. Each time, immediately after listening the list, the subjects were required to repeat as many words as they could recall. Spectral coherence of the intracerebral EEG activity was computed in order to assess the temporal synchronization of the theta (about 3-8 Hz) rhythms among hippocampus, amygdala, and temporal-occipital neocortex. We found that theta coherence values between amygdala and hippocampus, and between hippocampus and occipital-temporal cortex, were higher in amplitude during successful than unsuccessful immediate recall. A control analysis showed that this was true also for a gamma band (40-45 Hz). Furthermore, these theta and gamma effects were not observed in an additional (control) subject with drug-resistant TLE and a wide lesion to hippocampus. In conclusion, a successful immediate recall to the RAVLT was associated to the enhancement of temporal synchronization of the theta (gamma) rhythms within a cerebral network including hippocampus, amygdala, and temporal-occipital neocortex. Copyright 2009 Wiley-Liss, Inc

Cognitive Risk Factors for Specific Learning Disorder: Processing Speed, Temporal Processing, and Working Memory.

PubMed

Moll, Kristina; Göbel, Silke M; Gooch, Debbie; Landerl, Karin; Snowling, Margaret J

2016-01-01

High comorbidity rates between reading disorder (RD) and mathematics disorder (MD) indicate that, although the cognitive core deficits underlying these disorders are distinct, additional domain-general risk factors might be shared between the disorders. Three domain-general cognitive abilities were investigated in children with RD and MD: processing speed, temporal processing, and working memory. Since attention problems frequently co-occur with learning disorders, the study examined whether these three factors, which are known to be associated with attention problems, account for the comorbidity between these disorders. The sample comprised 99 primary school children in four groups: children with RD, children with MD, children with both disorders (RD+MD), and typically developing children (TD controls). Measures of processing speed, temporal processing, and memory were analyzed in a series of ANCOVAs including attention ratings as covariate. All three risk factors were associated with poor attention. After controlling for attention, associations with RD and MD differed: Although deficits in verbal memory were associated with both RD and MD, reduced processing speed was related to RD, but not MD; and the association with RD was restricted to processing speed for familiar nameable symbols. In contrast, impairments in temporal processing and visuospatial memory were associated with MD, but not RD. © Hammill Institute on Disabilities 2014.

Participant Observation, Anthropology Methodology and Design Anthropology Research Inquiry

ERIC Educational Resources Information Center

Gunn, Wendy; Løgstrup, Louise B.

2014-01-01

Within the design studio, and across multiple field sites, the authors compare involvement of research tools and materials during collaborative processes of designing. Their aim is to trace temporal dimensions (shifts/ movements) of where and when learning takes place along different sites of practice. They do so by combining participant…

Abnormal Temporal Difference Reward-Learning Signals in Major Depression

ERIC Educational Resources Information Center

Kumar, P.; Waiter, G.; Ahearn, T.; Milders, M.; Reid, I.; Steele, J. D.

2008-01-01

Anhedonia is a core symptom of major depressive disorder (MDD), long thought to be associated with reduced dopaminergic function. However, most antidepressants do not act directly on the dopamine system and all antidepressants have a delayed full therapeutic effect. Recently, it has been proposed that antidepressants fail to alter dopamine…

Context effects in a temporal discrimination task" further tests of the Scalar Expectancy Theory and Learning-to-Time models.

PubMed

Arantes, Joana; Machado, Armando

2008-07-01

Pigeons were trained on two temporal bisection tasks, which alternated every two sessions. In the first task, they learned to choose a red key after a 1-s signal and a green key after a 4-s signal; in the second task, they learned to choose a blue key after a 4-s signal and a yellow key after a 16-s signal. Then the pigeons were exposed to a series of test trials in order to contrast two timing models, Learning-to-Time (LeT) and Scalar Expectancy Theory (SET). The models made substantially different predictions particularly for the test trials in which the sample duration ranged from 1 s to 16 s and the choice keys were Green and Blue, the keys associated with the same 4-s samples: LeT predicted that preference for Green should increase with sample duration, a context effect, but SET predicted that preference for Green should not vary with sample duration. The results were consistent with LeT. The present study adds to the literature the finding that the context effect occurs even when the two basic discriminations are never combined in the same session.

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…

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…

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data

NASA Astrophysics Data System (ADS)

Hagensieker, Ron; Roscher, Ribana; Rosentreter, Johannes; Jakimow, Benjamin; Waske, Björn

2017-12-01

Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain. The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.

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.

Individual variation in prey selection by sea otters: Patterns, causes and implications

USGS Publications Warehouse

Estes, J.A.; Riedman, M.L.; Staedler, M.M.; Tinker, M.T.; Lyon, B.E.

2003-01-01

1. Longitudinal records of prey selection by 10 adult female sea otters on the Monterey Peninsula, California, from 1983 to 1990 demonstrate extreme inter-individual variation in diet. Variation in prey availability cannot explain these differences as the data were obtained from a common spatial-temporal area. 2. Individual dietary patterns persisted throughout our study, thus indicating that they are life-long characteristics. 3. Individual dietary patterns in sea otters appear to be transmitted along matrilines, probably by way of learning during the period of mother-young association. 4. Efficient utilization of different prey types probably requires radically different sensory/motor skills, each of which is difficult to acquire and all of which may exceed the learning and performance capacities of any single individual. This would explain the absence of generalists and inertia against switching, but not the existence of alternative specialists. 5. Such individual variation might arise in a constant environment from frequency-dependent effects, whereby the relative benefit of a given prey specialization depends on the number of other individuals utilizing that prey. Additionally, many of the sea otter's prey fluctuate substantially in abundance through time. This temporal variation, in conjunction with matrilineal transmission of foraging skills, may act to mediate the temporal dynamics of prey specializations. 6. Regardless of the exact cause, such extreme individual variation in diet has broad ramifications for population and community ecology. 7. The published literature indicates that similar patterns occur in many other species.

Chemotherapy disrupts learning, neurogenesis and theta activity in the adult brain.

PubMed

Nokia, Miriam S; Anderson, Megan L; Shors, Tracey J

2012-12-01

Chemotherapy, especially if prolonged, disrupts attention, working memory and speed of processing in humans. Most cancer drugs that cross the blood-brain barrier also decrease adult neurogenesis. Because new neurons are generated in the hippocampus, this decrease may contribute to the deficits in working memory and related thought processes. The neurophysiological mechanisms that underlie these deficits are generally unknown. A possible mediator is hippocampal oscillatory activity within the theta range (3-12 Hz). Theta activity predicts and promotes efficient learning in healthy animals and humans. Here, we hypothesised that chemotherapy disrupts learning via decreases in hippocampal adult neurogenesis and theta activity. Temozolomide was administered to adult male Sprague-Dawley rats in a cyclic manner for several weeks. Treatment was followed by training with different types of eyeblink classical conditioning, a form of associative learning. Chemotherapy reduced both neurogenesis and endogenous theta activity, as well as disrupted learning and related theta-band responses to the conditioned stimulus. The detrimental effects of temozolomide only occurred after several weeks of treatment, and only on a task that requires the association of events across a temporal gap and not during training with temporally overlapping stimuli. Chemotherapy did not disrupt the memory for previously learned associations, a memory independent of (new neurons in) the hippocampus. In conclusion, prolonged systemic chemotherapy is associated with a decrease in hippocampal adult neurogenesis and theta activity that may explain the selective deficits in processes of learning that describe the 'chemobrain'. © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

An extended reinforcement learning model of basal ganglia to understand the contributions of serotonin and dopamine in risk-based decision making, reward prediction, and punishment learning

PubMed Central

Balasubramani, Pragathi P.; Chakravarthy, V. Srinivasa; Ravindran, Balaraman; Moustafa, Ahmed A.

2014-01-01

Although empirical and neural studies show that serotonin (5HT) plays many functional roles in the brain, prior computational models mostly focus on its role in behavioral inhibition. In this study, we present a model of risk based decision making in a modified Reinforcement Learning (RL)-framework. The model depicts the roles of dopamine (DA) and serotonin (5HT) in Basal Ganglia (BG). In this model, the DA signal is represented by the temporal difference error (δ), while the 5HT signal is represented by a parameter (α) that controls risk prediction error. This formulation that accommodates both 5HT and DA reconciles some of the diverse roles of 5HT particularly in connection with the BG system. We apply the model to different experimental paradigms used to study the role of 5HT: (1) Risk-sensitive decision making, where 5HT controls risk assessment, (2) Temporal reward prediction, where 5HT controls time-scale of reward prediction, and (3) Reward/Punishment sensitivity, in which the punishment prediction error depends on 5HT levels. Thus the proposed integrated RL model reconciles several existing theories of 5HT and DA in the BG. PMID:24795614

Collateral brain damage, a potential source of cognitive impairment after selective surgery for control of mesial temporal lobe epilepsy.

PubMed

Helmstaedter, C; Van Roost, D; Clusmann, H; Urbach, H; Elger, C E; Schramm, J

2004-02-01

Highly selective epilepsy surgery in temporal lobe epilepsy is intended to achieve seizure freedom at a lower cognitive risk than standard en bloc resections, but bears the risk of collateral cortical damage resulting from the surgical approach. To investigate cortical damage associated with selective amygdalo-hippocampectomy (SAH). 34 epileptic patients were evaluated. They were randomly assigned to SAH using either a sylvian (9 left/10 right) or a transcortical surgical approach (5 left/10 right). Postoperative MRI signal intensity changes adjacent to the approach were correlated with performance changes in serial word and design list learning. Losses in verbal learning and recognition memory were positively related to signal intensity changes, independent of the side of the resection, the surgical approach, or the extent of the mesial resection. Losses in consolidation/retrieval (memory) were greater after left sided surgery. Losses in design learning were related to right sided surgery and signal intensity changes. Seizure outcome (85% seizure-free) did not differ depending on the side or type of surgery. Collateral damage to cortical tissues adjacent to the surgical approach contributes to postoperative verbal and figural memory outcome after SAH. Controlling for collateral damage may clarify the controversial memory outcomes after SAH reported by different surgical centres.

Temporal Discounting and Inter-Temporal Choice in Rhesus Monkeys

PubMed Central

Hwang, Jaewon; Kim, Soyoun; Lee, Daeyeol

2009-01-01

Humans and animals are more likely to take an action leading to an immediate reward than actions with delayed rewards of similar magnitudes. Although such devaluation of delayed rewards has been almost universally described by hyperbolic discount functions, the rate of this temporal discounting varies substantially among different animal species. This might be in part due to the differences in how the information about reward is presented to decision makers. In previous animal studies, reward delays or magnitudes were gradually adjusted across trials, so the animals learned the properties of future rewards from the rewards they waited for and consumed previously. In contrast, verbal cues have been used commonly in human studies. In the present study, rhesus monkeys were trained in a novel inter-temporal choice task in which the magnitude and delay of reward were indicated symbolically using visual cues and varied randomly across trials. We found that monkeys could extract the information about reward delays from visual symbols regardless of the number of symbols used to indicate the delay. The rate of temporal discounting observed in the present study was comparable to the previous estimates in other mammals, and the animal's choice behavior was largely consistent with hyperbolic discounting. Our results also suggest that the rate of temporal discounting might be influenced by contextual factors, such as the novelty of the task. The flexibility furnished by this new inter-temporal choice task might be useful for future neurobiological investigations on inter-temporal choice in non-human primates. PMID:19562091

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

Transfer effects of manipulating temporal constraints on learning a two-choice reaction time task with low stimulus-response compatibility.

PubMed

Chen, David D; Pei, Laura; Chan, John S Y; Yan, Jin H

2012-10-01

Recent research using deliberate amplification of spatial errors to increase motor learning leads to the question of whether amplifying temporal errors may also facilitate learning. We investigated transfer effects caused by manipulating temporal constraints on learning a two-choice reaction time (CRT) task with varying degrees of stimulus-response compatibility. Thirty-four participants were randomly assigned to one of the three groups and completed 120 trials during acquisition. For every fourth trial, one group was instructed to decrease CRT by 50 msec. relative to the previous trial and a second group was instructed to increase CRT by 50 msec. The third group (the control) was told not to change their responses. After a 5-min. break, participants completed a 40-trial no-feedback transfer test. A 40-trial delayed transfer test was administered 24 hours later. During acquisition, the Decreased Reaction Time group responded faster than the two other groups, but this group also made more errors than the other two groups. In the 5-min. delayed test (immediate transfer), the Decreased Reaction Time group had faster reaction times than the other two groups, while for the 24-hr. delayed test (delayed transfer), both the Decreased Reaction Time group and Increased Reaction Time group had significantly faster reaction times than the control. For delayed transfer, both Decreased and Increased Reaction Time groups reacted significantly faster than the control group. Analyses of error scores in the transfer tests indicated revealed no significant group differences. Results were discussed with regard to the notion of practice variability and goal-setting benefits.

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,…

Temporal Dynamics in Auditory Perceptual Learning: Impact of Sequencing and Incidental Learning

ERIC Educational Resources Information Center

Church, Barbara A.; Mercado, Eduardo, III; Wisniewski, Matthew G.; Liu, Estella H.

2013-01-01

Training can improve perceptual sensitivities. We examined whether the temporal dynamics and the incidental versus intentional nature of training are important. Within the context of a birdsong rate discrimination task, we examined whether the sequencing of pretesting exposure to the stimuli mattered. Easy-to-hard (progressive) sequencing of…

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.

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…

Synchrony detection and amplification by silicon neurons with STDP synapses.

PubMed

Bofill-i-petit, Adria; Murray, Alan F

2004-09-01

Spike-timing dependent synaptic plasticity (STDP) is a form of plasticity driven by precise spike-timing differences between presynaptic and postsynaptic spikes. Thus, the learning rules underlying STDP are suitable for learning neuronal temporal phenomena such as spike-timing synchrony. It is well known that weight-independent STDP creates unstable learning processes resulting in balanced bimodal weight distributions. In this paper, we present a neuromorphic analog very large scale integration (VLSI) circuit that contains a feedforward network of silicon neurons with STDP synapses. The learning rule implemented can be tuned to have a moderate level of weight dependence. This helps stabilise the learning process and still generates binary weight distributions. From on-chip learning experiments we show that the chip can detect and amplify hierarchical spike-timing synchrony structures embedded in noisy spike trains. The weight distributions of the network emerging from learning are bimodal.

Dopamine, reward learning, and active inference

PubMed Central

FitzGerald, Thomas H. B.; Dolan, Raymond J.; Friston, Karl

2015-01-01

Temporal difference learning models propose phasic dopamine signaling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behavior. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings. PMID:26581305

Dopamine, reward learning, and active inference.

PubMed

FitzGerald, Thomas H B; Dolan, Raymond J; Friston, Karl

2015-01-01

Temporal difference learning models propose phasic dopamine signaling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behavior. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings.

Biologically Inspired SNN for Robot Control.

PubMed

Nichols, Eric; McDaid, Liam J; Siddique, Nazmul

2013-02-01

This paper proposes a spiking-neural-network-based robot controller inspired by the control structures of biological systems. Information is routed through the network using facilitating dynamic synapses with short-term plasticity. Learning occurs through long-term synaptic plasticity which is implemented using the temporal difference learning rule to enable the robot to learn to associate the correct movement with the appropriate input conditions. The network self-organizes to provide memories of environments that the robot encounters. A Pioneer robot simulator with laser and sonar proximity sensors is used to verify the performance of the network with a wall-following task, and the results are presented.

Network Supervision of Adult Experience and Learning Dependent Sensory Cortical Plasticity.

PubMed

Blake, David T

2017-06-18

The brain is capable of remodeling throughout life. The sensory cortices provide a useful preparation for studying neuroplasticity both during development and thereafter. In adulthood, sensory cortices change in the cortical area activated by behaviorally relevant stimuli, by the strength of response within that activated area, and by the temporal profiles of those responses. Evidence supports forms of unsupervised, reinforcement, and fully supervised network learning rules. Studies on experience-dependent plasticity have mostly not controlled for learning, and they find support for unsupervised learning mechanisms. Changes occur with greatest ease in neurons containing α-CamKII, which are pyramidal neurons in layers II/III and layers V/VI. These changes use synaptic mechanisms including long term depression. Synaptic strengthening at NMDA-containing synapses does occur, but its weak association with activity suggests other factors also initiate changes. Studies that control learning find support of reinforcement learning rules and limited evidence of other forms of supervised learning. Behaviorally associating a stimulus with reinforcement leads to a strengthening of cortical response strength and enlarging of response area with poor selectivity. Associating a stimulus with omission of reinforcement leads to a selective weakening of responses. In some preparations in which these associations are not as clearly made, neurons with the most informative discharges are relatively stronger after training. Studies analyzing the temporal profile of responses associated with omission of reward, or of plasticity in studies with different discriminanda but statistically matched stimuli, support the existence of limited supervised network learning. © 2017 American Physiological Society. Compr Physiol 7:977-1008, 2017. Copyright © 2017 John Wiley & Sons, Inc.

Music mnemonics aid Verbal Memory and Induce Learning – Related Brain Plasticity in Multiple Sclerosis

PubMed Central

Thaut, Michael H.; Peterson, David A.; McIntosh, Gerald C.; Hoemberg, Volker

2014-01-01

Recent research on music and brain function has suggested that the temporal pattern structure in music and rhythm can enhance cognitive functions. To further elucidate this question specifically for memory, we investigated if a musical template can enhance verbal learning in patients with multiple sclerosis (MS) and if music-assisted learning will also influence short-term, system-level brain plasticity. We measured systems-level brain activity with oscillatory network synchronization during music-assisted learning. Specifically, we measured the spectral power of 128-channel electroencephalogram (EEG) in alpha and beta frequency bands in 54 patients with MS. The study sample was randomly divided into two groups, either hearing a spoken or a musical (sung) presentation of Rey’s auditory verbal learning test. We defined the “learning-related synchronization” (LRS) as the percent change in EEG spectral power from the first time the word was presented to the average of the subsequent word encoding trials. LRS differed significantly between the music and the spoken conditions in low alpha and upper beta bands. Patients in the music condition showed overall better word memory and better word order memory and stronger bilateral frontal alpha LRS than patients in the spoken condition. The evidence suggests that a musical mnemonic recruits stronger oscillatory network synchronization in prefrontal areas in MS patients during word learning. It is suggested that the temporal structure implicit in musical stimuli enhances “deep encoding” during verbal learning and sharpens the timing of neural dynamics in brain networks degraded by demyelination in MS. PMID:24982626

A computational model of the development of separate representations of facial identity and expression in the primate visual system.

PubMed

Tromans, James Matthew; Harris, Mitchell; Stringer, Simon Maitland

2011-01-01

Experimental studies have provided evidence that the visual processing areas of the primate brain represent facial identity and facial expression within different subpopulations of neurons. For example, in non-human primates there is evidence that cells within the inferior temporal gyrus (TE) respond primarily to facial identity, while cells within the superior temporal sulcus (STS) respond to facial expression. More recently, it has been found that the orbitofrontal cortex (OFC) of non-human primates contains some cells that respond exclusively to changes in facial identity, while other cells respond exclusively to facial expression. How might the primate visual system develop physically separate representations of facial identity and expression given that the visual system is always exposed to simultaneous combinations of facial identity and expression during learning? In this paper, a biologically plausible neural network model, VisNet, of the ventral visual pathway is trained on a set of carefully-designed cartoon faces with different identities and expressions. The VisNet model architecture is composed of a hierarchical series of four Self-Organising Maps (SOMs), with associative learning in the feedforward synaptic connections between successive layers. During learning, the network develops separate clusters of cells that respond exclusively to either facial identity or facial expression. We interpret the performance of the network in terms of the learning properties of SOMs, which are able to exploit the statistical indendependence between facial identity and expression.

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.

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

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

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.

Region-Specific Involvement of Actin Rearrangement-Related Synaptic Structure Alterations in Conditioned Taste Aversion Memory

ERIC Educational Resources Information Center

Bi, Ai-Ling; Wang, Yue; Li, Bo-Qin; Wang, Qian-Qian; Ma, Ling; Yu, Hui; Zhao, Ling; Chen, Zhe-Yu

2010-01-01

Actin rearrangement plays an essential role in learning and memory; however, the spatial and temporal regulation of actin dynamics in different phases of associative memory has not been fully understood. Here, using the conditioned taste aversion (CTA) paradigm, we investigated the region-specific involvement of actin rearrangement-related…

Individual Differences and Auditory Conditioning in Neonates.

ERIC Educational Resources Information Center

Franz, W. K.; And Others

The purposes of this study are (1) to analyze learning ability in newborns using heart rate responses to auditory temporal conditioning and (2) to correlate these with measures on the Brazelton Neonatal Behavioral Assessment Scale. Twenty normal neonates were tested using the Brazelton Scale on the third day of life. They were also given a…

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

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.

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…

Verbal learning and memory outcome in selective amygdalohippocampectomy versus temporal lobe resection in patients with hippocampal sclerosis.

PubMed

Foged, Mette Thrane; Vinter, Kirsten; Stauning, Louise; Kjær, Troels W; Ozenne, Brice; Beniczky, Sándor; Paulson, Olaf B; Madsen, Flemming Find; Pinborg, Lars H

2018-02-01

With the advent of new very selective techniques like thermal laser ablation to treat drug-resistant focal epilepsy, the controversy of resection size in relation to seizure outcome versus cognitive deficits has gained new relevance. The purpose of this study was to test the influence of the selective amygdalohippocampectomy (SAH) versus nonselective temporal lobe resection (TLR) on seizure outcome and cognition in patients with mesial temporal lobe epilepsy (MTLE) and histopathological verified hippocampal sclerosis (HS). We identified 108 adults (>16years) with HS, operated between 1995 and 2009 in Denmark. Exclusion criteria are the following: Intelligence below normal range, right hemisphere dominance, other native languages than Danish, dual pathology, and missing follow-up data. Thus, 56 patients were analyzed. The patients were allocated to SAH (n=22) or TLR (n=34) based on intraoperative electrocorticography. Verbal learning and verbal memory were tested pre- and postsurgery. Seizure outcome did not differ between patients operated using the SAH versus the TLR at 1year (p=0.951) nor at 7years (p=0.177). Verbal learning was more affected in patients resected in the left hemisphere than in the right (p=0.002). In patients with left-sided TLR, a worsening in verbal memory performance was found (p=0.011). Altogether, 73% were seizure-free for 1year and 64% for 7years after surgery. In patients with drug-resistant focal MTLE, HS and no magnetic resonance imaging (MRI) signs of dual pathology, selective amygdalohippocampectomy results in sustained seizure freedom and better memory function compared with patients operated with nonselective temporal lobe resection. Copyright © 2017 Elsevier Inc. All rights reserved.

Policy improvement by a model-free Dyna architecture.

PubMed

Hwang, Kao-Shing; Lo, Chia-Yue

2013-05-01

The objective of this paper is to accelerate the process of policy improvement in reinforcement learning. The proposed Dyna-style system combines two learning schemes, one of which utilizes a temporal difference method for direct learning; the other uses relative values for indirect learning in planning between two successive direct learning cycles. Instead of establishing a complicated world model, the approach introduces a simple predictor of average rewards to actor-critic architecture in the simulation (planning) mode. The relative value of a state, defined as the accumulated differences between immediate reward and average reward, is used to steer the improvement process in the right direction. The proposed learning scheme is applied to control a pendulum system for tracking a desired trajectory to demonstrate its adaptability and robustness. Through reinforcement signals from the environment, the system takes the appropriate action to drive an unknown dynamic to track desired outputs in few learning cycles. Comparisons are made between the proposed model-free method, a connectionist adaptive heuristic critic, and an advanced method of Dyna-Q learning in the experiments of labyrinth exploration. The proposed method outperforms its counterparts in terms of elapsed time and convergence rate.

Nothing is safe: Intolerance of uncertainty is associated with compromised fear extinction learning.

PubMed

Morriss, Jayne; Christakou, Anastasia; van Reekum, Carien M

2016-12-01

Extinction-resistant fear is considered to be a central feature of pathological anxiety. Here we sought to determine if individual differences in Intolerance of Uncertainty (IU), a potential risk factor for anxiety disorders, underlies compromised fear extinction. We tested this hypothesis by recording electrodermal activity in 38 healthy participants during fear acquisition and extinction. We assessed the temporality of fear extinction, by examining early and late extinction learning. During early extinction, low IU was associated with larger skin conductance responses to learned threat vs. safety cues, whereas high IU was associated with skin conductance responding to both threat and safety cues, but no cue discrimination. During late extinction, low IU showed no difference in skin conductance between learned threat and safety cues, whilst high IU predicted continued fear expression to learned threat, indexed by larger skin conductance to threat vs. safety cues. These findings suggest a critical role of uncertainty-based mechanisms in the maintenance of learned fear. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Novelty and Inductive Generalization in Human Reinforcement Learning

PubMed Central

Gershman, Samuel J.; Niv, Yael

2015-01-01

In reinforcement learning, a decision maker searching for the most rewarding option is often faced with the question: what is the value of an option that has never been tried before? One way to frame this question is as an inductive problem: how can I generalize my previous experience with one set of options to a novel option? We show how hierarchical Bayesian inference can be used to solve this problem, and describe an equivalence between the Bayesian model and temporal difference learning algorithms that have been proposed as models of reinforcement learning in humans and animals. According to our view, the search for the best option is guided by abstract knowledge about the relationships between different options in an environment, resulting in greater search efficiency compared to traditional reinforcement learning algorithms previously applied to human cognition. In two behavioral experiments, we test several predictions of our model, providing evidence that humans learn and exploit structured inductive knowledge to make predictions about novel options. In light of this model, we suggest a new interpretation of dopaminergic responses to novelty. PMID:25808176

Dynamic functional brain networks involved in simple visual discrimination learning.

PubMed

Fidalgo, Camino; Conejo, Nélida María; González-Pardo, Héctor; Arias, Jorge Luis

2014-10-01

Visual discrimination tasks have been widely used to evaluate many types of learning and memory processes. However, little is known about the brain regions involved at different stages of visual discrimination learning. We used cytochrome c oxidase histochemistry to evaluate changes in regional brain oxidative metabolism during visual discrimination learning in a water-T maze at different time points during training. As compared with control groups, the results of the present study reveal the gradual activation of cortical (prefrontal and temporal cortices) and subcortical brain regions (including the striatum and the hippocampus) associated to the mastery of a simple visual discrimination task. On the other hand, the brain regions involved and their functional interactions changed progressively over days of training. Regions associated with novelty, emotion, visuo-spatial orientation and motor aspects of the behavioral task seem to be relevant during the earlier phase of training, whereas a brain network comprising the prefrontal cortex was found along the whole learning process. This study highlights the relevance of functional interactions among brain regions to investigate learning and memory processes. Copyright © 2014 Elsevier Inc. All rights reserved.

Cortical Activation Patterns Evoked by Temporally Asymmetric Sounds and Their Modulation by Learning

PubMed Central

Horikawa, Junsei

2017-01-01

When complex sounds are reversed in time, the original and reversed versions are perceived differently in spectral and temporal dimensions despite their identical duration and long-term spectrum-power profiles. Spatiotemporal activation patterns evoked by temporally asymmetric sound pairs demonstrate how the temporal envelope determines the readout of the spectrum. We examined the patterns of activation evoked by a temporally asymmetric sound pair in the primary auditory field (AI) of anesthetized guinea pigs and determined how discrimination training modified these patterns. Optical imaging using a voltage-sensitive dye revealed that a forward ramped-down natural sound (F) consistently evoked much stronger responses than its time-reversed, ramped-up counterpart (revF). The spatiotemporal maximum peak (maxP) of F-evoked activation was always greater than that of revF-evoked activation, and these maxPs were significantly separated within the AI. Although discrimination training did not affect the absolute magnitude of these maxPs, the revF-to-F ratio of the activation peaks calculated at the location where hemispheres were maximally activated (i.e., F-evoked maxP) was significantly smaller in the trained group. The F-evoked activation propagated across the AI along the temporal axis to the ventroanterior belt field (VA), with the local activation peak within the VA being significantly larger in the trained than in the naïve group. These results suggest that the innate network is more responsive to natural sounds of ramped-down envelopes than their time-reversed, unnatural sounds. The VA belt field activation might play an important role in emotional learning of sounds through its connections with amygdala. PMID:28451640

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

PubMed

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

2018-04-12

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

The DA antagonist tiapride impairs context-related extinction learning in a novel context without affecting renewal

PubMed Central

Lissek, Silke; Glaubitz, Benjamin; Wolf, Oliver T.; Tegenthoff, Martin

2015-01-01

Renewal describes the recovery of an extinguished response if recall is tested in a context different from the extinction context. Behavioral studies demonstrated that attention to relevant context strengthens renewal. Neurotransmitters mediating attention and learning such as the dopaminergic (DA) system presumably modulate extinction learning and renewal. However, the role of DA for non-fear-based extinction learning and renewal in humans has not yet been investigated. This fMRI study investigated effects of DA-antagonism upon context-related extinction in a predictive learning task in which extinction occurred either in a novel (ABA) or an unchanged (AAA) context. The tiapride-treated group (TIA) showed significantly impaired ABA extinction learning and a significant within-group difference between ABA and AAA extinction, compared to placebo (PLAC). Groups did not differ in their level of ABA renewal. In ABA extinction, TIA showed reduced activation in dlPFC and OFC, hippocampus, and temporal regions. Across groups, activation in PFC and hippocampus correlated negatively with ABA extinction errors. Results suggest that in context-related extinction learning DA in PFC and hippocampus is involved in readjusting the cue-outcome relationship in the presence of a novel context. However, relating context to the appropriate association during recall does not appear to rely exclusively on DA signaling. PMID:26388752

Late Maturation of Adult-Born Neurons in the Temporal Dentate Gyrus

PubMed Central

Snyder, Jason S.; Ferrante, Sarah C.; Cameron, Heather A.

2012-01-01

Hippocampal function varies along its septotemporal axis, with the septal (dorsal) pole more frequently involved in spatial learning and memory and the temporal (ventral) pole playing a greater role in emotional behaviors. One feature that varies across these subregions is adult neurogenesis. New neurons are more numerous in the septal hippocampus but are more active in the temporal hippocampus during water maze training. However, many other aspects of adult neurogenesis remain unexplored in the context of septal versus temporal subregions. In addition, the dentate gyrus contains another functionally important anatomical division along the transverse axis, with the suprapyramidal blade showing greater experience-related activity than the infrapyramidal blade. Here we ask whether new neurons differ in their rates of survival and maturation along the septotemporal and transverse axes. We found that neurogenesis is initially higher in the infrapyramidal than suprapyramidal blade, but these cells are less likely to survive, resulting in similar densities of neurons in the two blades by four weeks. Across the septotemporal axis, neurogenesis was higher in septal than temporal pole, while the survival rate of new neurons did not differ. Maturation was assessed by immunostaining for the neuronal marker, NeuN, which increases in expression level with maturation, and for the immediate-early gene, Arc, which suggests a neuron is capable of undergoing activity-dependent synaptic plasticity. Maturation occurred approximately 1–2 weeks earlier in the septal pole than in the temporal pole. This suggests that septal neurons may contribute to function sooner; however, the prolonged maturation of new temporal neurons may endow them with a longer window of plasticity during which their functions could be distinct from those of the mature granule cell population. These data point to subregional differences in new neuron maturation and suggest that changes in neurogenesis could alter different hippocampus-dependent behaviors with different time courses. PMID:23144957

Visuocortical Changes During Delay and Trace Aversive Conditioning: Evidence From Steady-State Visual Evoked Potentials

PubMed Central

Miskovic, Vladimir; Keil, Andreas

2015-01-01

The visual system is biased towards sensory cues that have been associated with danger or harm through temporal co-occurrence. An outstanding question about conditioning-induced changes in visuocortical processing is the extent to which they are driven primarily by top-down factors such as expectancy or by low-level factors such as the temporal proximity between conditioned stimuli and aversive outcomes. Here, we examined this question using two different differential aversive conditioning experiments: participants learned to associate a particular grating stimulus with an aversive noise that was presented either in close temporal proximity (delay conditioning experiment) or after a prolonged stimulus-free interval (trace conditioning experiment). In both experiments we probed cue-related cortical responses by recording steady-state visual evoked potentials (ssVEPs). Although behavioral ratings indicated that all participants successfully learned to discriminate between the grating patterns that predicted the presence versus absence of the aversive noise, selective amplification of population-level responses in visual cortex for the conditioned danger signal was observed only when the grating and the noise were temporally contiguous. Our findings are in line with notions purporting that changes in the electrocortical response of visual neurons induced by aversive conditioning are a product of Hebbian associations among sensory cell assemblies rather than being driven entirely by expectancy-based, declarative processes. PMID:23398582

Using machine learning and surface reconstruction to accurately differentiate different trajectories of mood and energy dysregulation in youth.

PubMed

Versace, Amelia; Sharma, Vinod; Bertocci, Michele A; Bebko, Genna; Iyengar, Satish; Dwojak, Amanda; Bonar, Lisa; Perlman, Susan B; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Diwadkar, Vaibhav A; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Frazier, Thomas W; Arnold, L Eugene; Fristad, Mary A; Youngstrom, Eric A; Horwitz, Sarah M; Findling, Robert L; Phillips, Mary L

2017-01-01

Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy regulation in youth. Recent studies indicate that machine learning techniques can help elucidate the role of neuroimaging measures in classifying individual subjects by specific symptom trajectory. Cortical thickness measures were extracted in sixty-eight anatomical regions covering the entire brain in 115 participants from the Longitudinal Assessment of Manic Symptoms (LAMS) study and 31 healthy comparison youth (12.5 y/o;-Male/Female = 15/16;-IQ = 104;-Right/Left handedness = 24/5). Using a combination of trajectories analyses, surface reconstruction, and machine learning techniques, the present study aims to identify the extent to which measures of cortical thickness can accurately distinguish youth with higher (n = 18) from those with lower (n = 34) trajectories of manic-like behaviors in a large sample of LAMS youth (n = 115; 13.6 y/o; M/F = 68/47, IQ = 100.1, R/L = 108/7). Machine learning analyses revealed that widespread cortical thickening in portions of the left dorsolateral prefrontal cortex, right inferior and middle temporal gyrus, bilateral precuneus, and bilateral paracentral gyri and cortical thinning in portions of the right dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, and right parahippocampal gyrus accurately differentiate (Area Under Curve = 0.89;p = 0.03) youth with different (higher vs lower) trajectories of positive mood and energy dysregulation over a period up to 5years, as measured by the Parent General Behavior Inventory-10 Item Mania Scale. Our findings suggest that specific patterns of cortical thickness may reflect transdiagnostic neural mechanisms associated with different temporal trajectories of positive mood and energy dysregulation in youth. This approach has potential to identify patterns of neural markers of future clinical course.

A new dynamic 3D virtual methodology for teaching the mechanics of atrial septation as seen in the human heart

PubMed Central

Schleich, Jean-Marc; Dillenseger, Jean-Louis; Houyel, Lucile; Almange, Claude; Anderson, Robert H.

2009-01-01

Background Learning embryology remains difficult, since it requires understanding of many complex phenomena. The temporal evolution of developmental events has classically been illustrated using cartoons, which create difficulty in linking spatial and temporal aspects, such correlation being the keystone of descriptive embryology. Methods We synthesized the bibliographic data from recent studies of atrial septal development. On the basis of this synthesis, consensus on the stages of atrial septation as seen in the human heart has been reached by a group of experts in cardiac embryology and paediatric cardiology. This has permitted the preparation of three-dimensional (3-D) computer graphic objects for the anatomical components involved in the different stages of normal human atrial septation. Results We have provided a virtual guide to the process of normal atrial septation, the animation providing an appreciation of the temporal and morphologic events necessary to separate the systemic and pulmonary venous returns. Conclusion We have shown that our animations of normal human atrial septation increase significantly the teaching of the complex developmental processes involved, and provide a new dynamic for the process of learning. PMID:19363807

Updating of aversive memories after temporal error detection is differentially modulated by mTOR across development

PubMed Central

Tallot, Lucille; Diaz-Mataix, Lorenzo; Perry, Rosemarie E.; Wood, Kira; LeDoux, Joseph E.; Mouly, Anne-Marie; Sullivan, Regina M.; Doyère, Valérie

2017-01-01

The updating of a memory is triggered whenever it is reactivated and a mismatch from what is expected (i.e., prediction error) is detected, a process that can be unraveled through the memory's sensitivity to protein synthesis inhibitors (i.e., reconsolidation). As noted in previous studies, in Pavlovian threat/aversive conditioning in adult rats, prediction error detection and its associated protein synthesis-dependent reconsolidation can be triggered by reactivating the memory with the conditioned stimulus (CS), but without the unconditioned stimulus (US), or by presenting a CS–US pairing with a different CS–US interval than during the initial learning. Whether similar mechanisms underlie memory updating in the young is not known. Using similar paradigms with rapamycin (an mTORC1 inhibitor), we show that preweaning rats (PN18–20) do form a long-term memory of the CS–US interval, and detect a 10-sec versus 30-sec temporal prediction error. However, the resulting updating/reconsolidation processes become adult-like after adolescence (PN30–40). Our results thus show that while temporal prediction error detection exists in preweaning rats, specific infant-type mechanisms are at play for associative learning and memory. PMID:28202715

Very Similar Spacing-Effect Patterns in Very Different Learning/Practice Domains

PubMed Central

Kornmeier, Jürgen; Spitzer, Manfred; Sosic-Vasic, Zrinka

2014-01-01

Temporally distributed (“spaced”) learning can be twice as efficient as massed learning. This “spacing effect” occurs with a broad spectrum of learning materials, with humans of different ages, with non-human vertebrates and also invertebrates. This indicates, that very basic learning mechanisms are at work (“generality”). Although most studies so far focused on very narrow spacing interval ranges, there is some evidence for a non-monotonic behavior of this “spacing effect” (“nonlinearity”) with optimal spacing intervals at different time scales. In the current study we focused both the nonlinearity aspect by using a broad range of spacing intervals and the generality aspect by using very different learning/practice domains: Participants learned German-Japanese word pairs and performed visual acuity tests. For each of six groups we used a different spacing interval between learning/practice units from 7 min to 24 h in logarithmic steps. Memory retention was studied in three consecutive final tests, one, seven and 28 days after the final learning unit. For both the vocabulary learning and visual acuity performance we found a highly significant effect of the factor spacing interval on the final test performance. In the 12 h-spacing-group about 85% of the learned words stayed in memory and nearly all of the visual acuity gain was preserved. In the 24 h-spacing-group, in contrast, only about 33% of the learned words were retained and the visual acuity gain dropped to zero. The very similar patterns of results from the two very different learning/practice domains point to similar underlying mechanisms. Further, our results indicate spacing in the range of 12 hours as optimal. A second peak may be around a spacing interval of 20 min but here the data are less clear. We discuss relations between our results and basic learning at the neuronal level. PMID:24609081

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.

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

Improving Pediatric Basic Life Support Performance Through Blended Learning With Web-Based Virtual Patients: Randomized Controlled Trial.

PubMed

Lehmann, Ronny; Thiessen, Christiane; Frick, Barbara; Bosse, Hans Martin; Nikendei, Christoph; Hoffmann, Georg Friedrich; Tönshoff, Burkhard; Huwendiek, Sören

2015-07-02

E-learning and blended learning approaches gain more and more popularity in emergency medicine curricula. So far, little data is available on the impact of such approaches on procedural learning and skill acquisition and their comparison with traditional approaches. This study investigated the impact of a blended learning approach, including Web-based virtual patients (VPs) and standard pediatric basic life support (PBLS) training, on procedural knowledge, objective performance, and self-assessment. A total of 57 medical students were randomly assigned to an intervention group (n=30) and a control group (n=27). Both groups received paper handouts in preparation of simulation-based PBLS training. The intervention group additionally completed two Web-based VPs with embedded video clips. Measurements were taken at randomization (t0), after the preparation period (t1), and after hands-on training (t2). Clinical decision-making skills and procedural knowledge were assessed at t0 and t1. PBLS performance was scored regarding adherence to the correct algorithm, conformance to temporal demands, and the quality of procedural steps at t1 and t2. Participants' self-assessments were recorded in all three measurements. Procedural knowledge of the intervention group was significantly superior to that of the control group at t1. At t2, the intervention group showed significantly better adherence to the algorithm and temporal demands, and better procedural quality of PBLS in objective measures than did the control group. These aspects differed between the groups even at t1 (after VPs, prior to practical training). Self-assessments differed significantly only at t1 in favor of the intervention group. Training with VPs combined with hands-on training improves PBLS performance as judged by objective measures.

Neural correlates of forward planning in a spatial decision task in humans

PubMed Central

Simon, Dylan Alexander; Daw, Nathaniel D.

2011-01-01

Although reinforcement learning (RL) theories have been influential in characterizing the brain’s mechanisms for reward-guided choice, the predominant temporal difference (TD) algorithm cannot explain many flexible or goal-directed actions that have been demonstrated behaviorally. We investigate such actions by contrasting an RL algorithm that is model-based, in that it relies on learning a map or model of the task and planning within it, to traditional model-free TD learning. To distinguish these approaches in humans, we used fMRI in a continuous spatial navigation task, in which frequent changes to the layout of the maze forced subjects continually to relearn their favored routes, thereby exposing the RL mechanisms employed. We sought evidence for the neural substrates of such mechanisms by comparing choice behavior and BOLD signals to decision variables extracted from simulations of either algorithm. Both choices and value-related BOLD signals in striatum, though most often associated with TD learning, were better explained by the model-based theory. Further, predecessor quantities for the model-based value computation were correlated with BOLD signals in the medial temporal lobe and frontal cortex. These results point to a significant extension of both the computational and anatomical substrates for RL in the brain. PMID:21471389

The Role of the Posterior Temporal and Medial Prefrontal Cortices in Mediating Learning from Romantic Interest and Rejection

PubMed Central

Cooper, Jeffrey C.; Dunne, Simon; Furey, Teresa; O'Doherty, John P.

2014-01-01

Romantic interest or rejection can be powerful incentives not merely for their emotional impact, but for their potential to transform, in a single interaction, what we think we know about another person—or ourselves. Little is known, though, about how the brain computes expectations for, and learns from, real-world romantic signals. In a novel “speed-dating” paradigm, we had participants meet potential romantic partners in a series of 5-min “dates,” and decide whether they would be interested in seeing each partner again. Afterward, participants were scanned with functional magnetic resonance imaging while they were told, for the first time, whether that partner was interested in them or rejected them. Expressions of interest and rejection activated regions previously associated with “mentalizing,” including the posterior superior temporal sulcus (pSTS) and rostromedial prefrontal cortex (RMPFC); while pSTS responded to differences from the participant's own decision, RMPFC responded to prediction errors from a reinforcement-learning model of personal desirability. Responses in affective regions were also highly sensitive to participants' expectations. Far from being inscrutable, then, responses to romantic expressions seem to involve a quantitative learning process, rooted in distinct sources of expectations, and encoded in neural networks that process both affective value and social beliefs. PMID:23599165

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.

Temporal components of the motor patterns expressed by the human spinal cord reflect foot kinematics.

PubMed

Ivanenko, Yuri P; Grasso, Renato; Zago, Myrka; Molinari, Marco; Scivoletto, Giorgio; Castellano, Vincenzo; Macellari, Velio; Lacquaniti, Francesco

2003-11-01

What are the building blocks with which the human spinal cord constructs the motor patterns of locomotion? In principle, they could correspond to each individual activity pattern in dozens of different muscles. Alternatively, there could exist a small set of constituent temporal components that are common to all activation patterns and reflect global kinematic goals. To address this issue, we studied patients with spinal injury trained to step on a treadmill with body weight support. Patients learned to produce foot kinematics similar to that of healthy subjects but with activity patterns of individual muscles generally different from the control group. Hidden in the muscle patterns, we found a basic set of five temporal components, whose flexible combination accounted for the wide range of muscle patterns recorded in both controls and patients. Furthermore, two of the components were systematically related to foot kinematics across different stepping speeds and loading conditions. We suggest that the components are related to control signals output by spinal pattern generators, normally under the influence of descending and afferent inputs.

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

A novel model for examining recovery of phonation after vocal nerve damage.

PubMed

Bhama, Prabhat K; Hillel, Allen D; Merati, Albert L; Perkel, David J

2011-05-01

Recurrent laryngeal nerve injury remains a dominant clinical issue in laryngology. To date, no animal model of laryngeal reinnervation has offered an outcome measure that can reflect the degree of recovery based on vocal function. We present an avian model system for studying recovery of learned vocalizations after nerve injury. Prospective animal study. Digital recordings of bird song were made from 11 adult male zebra finches; nine birds underwent bilateral crushing of the nerve supplying the vocal organ, and two birds underwent sham surgery. Songs from all the birds were then recorded regularly and analyzed based on temporal and spectral characteristics using computer software. Indices were calculated to indicate the degree of similarity between preoperative and postoperative song. Nerve crush caused audible differences in song quality and significant drops (P<0.05) in measured spectral and, to a lesser degree, temporal indices. Spectral indices recovered significantly (mean=43.0%; standard deviation [SD]=40.7; P<0.02), and there was an insignificant trend toward recovery of temporal index (mean=28.0%; SD=41.4; P=0.0771). In five of the nine (56%) birds, there was a greater than 50% recovery of spectral indices within a 4-week period. Two birds exhibited substantially less recovery of spectral indices and two birds had a persistent decline in spectral indices. Recovery of temporal index was highly variable as well, ranging from persistent further declines of 45.1% to recovery of 87%. Neither sham bird exhibited significant (P>0.05) differences in song after nerve crush. The songbird model system allows functional analysis of learned vocalization after surgical damage to vocal nerves. Copyright © 2011 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Virtual reality simulation training of mastoidectomy - studies on novice performance.

PubMed

Andersen, Steven Arild Wuyts

2016-08-01

Virtual reality (VR) simulation-based training is increasingly used in surgical technical skills training including in temporal bone surgery. The potential of VR simulation in enabling high-quality surgical training is great and VR simulation allows high-stakes and complex procedures such as mastoidectomy to be trained repeatedly, independent of patients and surgical tutors, outside traditional learning environments such as the OR or the temporal bone lab, and with fewer of the constraints of traditional training. This thesis aims to increase the evidence-base of VR simulation training of mastoidectomy and, by studying the final-product performances of novices, investigates the transfer of skills to the current gold-standard training modality of cadaveric dissection, the effect of different practice conditions and simulator-integrated tutoring on performance and retention of skills, and the role of directed, self-regulated learning. Technical skills in mastoidectomy were transferable from the VR simulation environment to cadaveric dissection with significant improvement in performance after directed, self-regulated training in the VR temporal bone simulator. Distributed practice led to a better learning outcome and more consolidated skills than massed practice and also resulted in a more consistent performance after three months of non-practice. Simulator-integrated tutoring accelerated the initial learning curve but also caused over-reliance on tutoring, which resulted in a drop in performance when the simulator-integrated tutor-function was discontinued. The learning curves were highly individual but often plateaued early and at an inadequate level, which related to issues concerning both the procedure and the VR simulator, over-reliance on the tutor function and poor self-assessment skills. Future simulator-integrated automated assessment could potentially resolve some of these issues and provide trainees with both feedback during the procedure and immediate assessment following each procedure. Standard setting by establishing a proficiency level that can be used for mastery learning with deliberate practice could also further sophisticate directed, self-regulated learning in VR simulation-based training. VR simulation-based training should be embedded in a systematic and competency-based training curriculum for high-quality surgical skills training, ultimately leading to improved safety and patient care.

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…

Temporal stability of visually selective responses in intracranial field potentials recorded from human occipital and temporal lobes

PubMed Central

Bansal, Arjun K.; Singer, Jedediah M.; Anderson, William S.; Golby, Alexandra; Madsen, Joseph R.

2012-01-01

The cerebral cortex needs to maintain information for long time periods while at the same time being capable of learning and adapting to changes. The degree of stability of physiological signals in the human brain in response to external stimuli over temporal scales spanning hours to days remains unclear. Here, we quantitatively assessed the stability across sessions of visually selective intracranial field potentials (IFPs) elicited by brief flashes of visual stimuli presented to 27 subjects. The interval between sessions ranged from hours to multiple days. We considered electrodes that showed robust visual selectivity to different shapes; these electrodes were typically located in the inferior occipital gyrus, the inferior temporal cortex, and the fusiform gyrus. We found that IFP responses showed a strong degree of stability across sessions. This stability was evident in averaged responses as well as single-trial decoding analyses, at the image exemplar level as well as at the category level, across different parts of visual cortex, and for three different visual recognition tasks. These results establish a quantitative evaluation of the degree of stationarity of visually selective IFP responses within and across sessions and provide a baseline for studies of cortical plasticity and for the development of brain-machine interfaces. PMID:22956795

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.

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.

Circadian timed episodic-like memory - a bee knows what to do when, and also where.

PubMed

Pahl, Mario; Zhu, Hong; Pix, Waltraud; Tautz, Juergen; Zhang, Shaowu

2007-10-01

This study investigates how the colour, shape and location of patterns could be memorized within a time frame. Bees were trained to visit two Y-mazes, one of which presented yellow vertical (rewarded) versus horizontal (non-rewarded) gratings at one site in the morning, while another presented blue horizontal (rewarded) versus vertical (non-rewarded) gratings at another site in the afternoon. The bees could perform well in the learning tests and various transfer tests, in which (i) all contextual cues from the learning test were present; (ii) the colour cues of the visual patterns were removed, but the location cue, the orientation of the visual patterns and the temporal cue still existed; (iii) the location cue was removed, but other contextual cues, i.e. the colour and orientation of the visual patterns and the temporal cue still existed; (iv) the location cue and the orientation cue of the visual patterns were removed, but the colour cue and temporal cue still existed; (v) the location cue, and the colour cue of the visual patterns were removed, but the orientation cue and the temporal cue still existed. The results reveal that the honeybee can recall the memory of the correct visual patterns by using spatial and/or temporal information. The relative importance of different contextual cues is compared and discussed. The bees' ability to integrate elements of circadian time, place and visual stimuli is akin to episodic-like memory; we have therefore named this kind of memory circadian timed episodic-like memory.

Electroencephalographic characterization of subgroups of children with learning disorders

PubMed Central

Roca-Stappung, Milene; Bosch-Bayard, Jorge; Harmony, Thalía; Ricardo-Garcell, Josefina

2017-01-01

Electroencephalographic alterations have been reported in subjects with learning disorders, but there is no consensus on what characterizes their electroencephalogram findings. Our objective was to determine if there were subgroups within a group of scholars with not otherwise specified learning disorders and if they had specific electroencephalographic patterns. Eighty-five subjects (31 female, 8–11 years) who scored low in at least two subscales -reading, writing and arithmetic- of the Infant Neuropsychological Evaluation were included. Electroencephalograms were recorded in 19 leads during rest with eyes closed; absolute power was obtained every 0.39 Hz. Three subgroups were formed according to children’s performance: Group 1 (G1, higher scores than Group 2 in reading speed and reading and writing accuracy), Group 2 (G2, better performance than G1 in composition) and Group 3 (G3, lower scores than Groups 1 and 2 in the three subscales). G3 had higher absolute power in frequencies in the delta and theta range at left frontotemporal sites than G1 and G2. G2 had higher absolute power within alpha frequencies than G3 and G1 at the left occipital site. G3 had higher absolute power in frequencies in the beta range than G1 in parietotemporal areas and than G2 in left frontopolar and temporal sites. G1 had higher absolute power within beta frequencies than G2 in the left frontopolar site. G3 had lower gamma absolute power values than the other groups in the left hemisphere, and gamma activity was higher in G1 than in G2 in frontopolar and temporal areas. This group of children with learning disorders is very heterogeneous. Three subgroups were found with different cognitive profiles, as well as a different electroencephalographic pattern. It is important to consider these differences when planning interventions for children with learning disorders. PMID:28708890

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…

Spatio-Temporal Information Analysis of Event-Related BOLD Responses

PubMed Central

Alpert, Galit Fuhrmann; Handwerker, Dan; Sun, Felice T.; D’Esposito, Mark; Knight, Robert T.

2009-01-01

A new approach for analysis of event related fMRI (BOLD) signals is proposed. The technique is based on measures from information theory and is used both for spatial localization of task related activity, as well as for extracting temporal information regarding the task dependent propagation of activation across different brain regions. This approach enables whole brain visualization of voxels (areas) most involved in coding of a specific task condition, the time at which they are most informative about the condition, as well as their average amplitude at that preferred time. The approach does not require prior assumptions about the shape of the hemodynamic response function (HRF), nor about linear relations between BOLD response and presented stimuli (or task conditions). We show that relative delays between different brain regions can also be computed without prior knowledge of the experimental design, suggesting a general method that could be applied for analysis of differential time delays that occur during natural, uncontrolled conditions. Here we analyze BOLD signals recorded during performance of a motor learning task. We show that during motor learning, the BOLD response of unimodal motor cortical areas precedes the response in higher-order multimodal association areas, including posterior parietal cortex. Brain areas found to be associated with reduced activity during motor learning, predominantly in prefrontal brain regions, are informative about the task typically at significantly later times. PMID:17188515

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.

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.

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…

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.

Non-accidental properties, metric invariance, and encoding by neurons in a model of ventral stream visual object recognition, VisNet.

PubMed

Rolls, Edmund T; Mills, W Patrick C

2018-05-01

When objects transform into different views, some properties are maintained, such as whether the edges are convex or concave, and these non-accidental properties are likely to be important in view-invariant object recognition. The metric properties, such as the degree of curvature, may change with different views, and are less likely to be useful in object recognition. It is shown that in a model of invariant visual object recognition in the ventral visual stream, VisNet, non-accidental properties are encoded much more than metric properties by neurons. Moreover, it is shown how with the temporal trace rule training in VisNet, non-accidental properties of objects become encoded by neurons, and how metric properties are treated invariantly. We also show how VisNet can generalize between different objects if they have the same non-accidental property, because the metric properties are likely to overlap. VisNet is a 4-layer unsupervised model of visual object recognition trained by competitive learning that utilizes a temporal trace learning rule to implement the learning of invariance using views that occur close together in time. A second crucial property of this model of object recognition is, when neurons in the level corresponding to the inferior temporal visual cortex respond selectively to objects, whether neurons in the intermediate layers can respond to combinations of features that may be parts of two or more objects. In an investigation using the four sides of a square presented in every possible combination, it was shown that even though different layer 4 neurons are tuned to encode each feature or feature combination orthogonally, neurons in the intermediate layers can respond to features or feature combinations present is several objects. This property is an important part of the way in which high capacity can be achieved in the four-layer ventral visual cortical pathway. These findings concerning non-accidental properties and the use of neurons in intermediate layers of the hierarchy help to emphasise fundamental underlying principles of the computations that may be implemented in the ventral cortical visual stream used in object recognition. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Temporal optimisation of image acquisition for land cover classification with Random Forest and MODIS time-series

NASA Astrophysics Data System (ADS)

Nitze, Ingmar; Barrett, Brian; Cawkwell, Fiona

2015-02-01

The analysis and classification of land cover is one of the principal applications in terrestrial remote sensing. Due to the seasonal variability of different vegetation types and land surface characteristics, the ability to discriminate land cover types changes over time. Multi-temporal classification can help to improve the classification accuracies, but different constraints, such as financial restrictions or atmospheric conditions, may impede their application. The optimisation of image acquisition timing and frequencies can help to increase the effectiveness of the classification process. For this purpose, the Feature Importance (FI) measure of the state-of-the art machine learning method Random Forest was used to determine the optimal image acquisition periods for a general (Grassland, Forest, Water, Settlement, Peatland) and Grassland specific (Improved Grassland, Semi-Improved Grassland) land cover classification in central Ireland based on a 9-year time-series of MODIS Terra 16 day composite data (MOD13Q1). Feature Importances for each acquisition period of the Enhanced Vegetation Index (EVI) and Normalised Difference Vegetation Index (NDVI) were calculated for both classification scenarios. In the general land cover classification, the months December and January showed the highest, and July and August the lowest separability for both VIs over the entire nine-year period. This temporal separability was reflected in the classification accuracies, where the optimal choice of image dates outperformed the worst image date by 13% using NDVI and 5% using EVI on a mono-temporal analysis. With the addition of the next best image periods to the data input the classification accuracies converged quickly to their limit at around 8-10 images. The binary classification schemes, using two classes only, showed a stronger seasonal dependency with a higher intra-annual, but lower inter-annual variation. Nonetheless anomalous weather conditions, such as the cold winter of 2009/2010 can alter the temporal separability pattern significantly. Due to the extensive use of the NDVI for land cover discrimination, the findings of this study should be transferrable to data from other optical sensors with a higher spatial resolution. However, the high impact of outliers from the general climatic pattern highlights the limitation of spatial transferability to locations with different climatic and land cover conditions. The use of high-temporal, moderate resolution data such as MODIS in conjunction with machine-learning techniques proved to be a good base for the prediction of image acquisition timing for optimal land cover classification results.

Fine-grained temporal coding of visually-similar categories in the ventral visual pathway and prefrontal cortex

PubMed Central

Xu, Yang; D'Lauro, Christopher; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

2013-01-01

Humans are remarkably proficient at categorizing visually-similar objects. To better understand the cortical basis of this categorization process, we used magnetoencephalography (MEG) to record neural activity while participants learned–with feedback–to discriminate two highly-similar, novel visual categories. We hypothesized that although prefrontal regions would mediate early category learning, this role would diminish with increasing category familiarity and that regions within the ventral visual pathway would come to play a more prominent role in encoding category-relevant information as learning progressed. Early in learning we observed some degree of categorical discriminability and predictability in both prefrontal cortex and the ventral visual pathway. Predictability improved significantly above chance in the ventral visual pathway over the course of learning with the left inferior temporal and fusiform gyri showing the greatest improvement in predictability between 150 and 250 ms (M200) during category learning. In contrast, there was no comparable increase in discriminability in prefrontal cortex with the only significant post-learning effect being a decrease in predictability in the inferior frontal gyrus between 250 and 350 ms (M300). Thus, the ventral visual pathway appears to encode learned visual categories over the long term. At the same time these results add to our understanding of the cortical origins of previously reported signature temporal components associated with perceptual learning. PMID:24146656

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.

The functional neuroanatomy of verbal memory in Alzheimer's disease: [18F]-Fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) correlates of recency and recognition memory.

PubMed

Staffaroni, Adam M; Melrose, Rebecca J; Leskin, Lorraine P; Riskin-Jones, Hannah; Harwood, Dylan; Mandelkern, Mark; Sultzer, David L

2017-09-01

The objective of this study was to distinguish the functional neuroanatomy of verbal learning and recognition in Alzheimer's disease (AD) using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word Learning task. In 81 Veterans diagnosed with dementia due to AD, we conducted a cluster-based correlation analysis to assess the relationships between recency and recognition memory scores from the CERAD Word Learning Task and cortical metabolic activity measured using [ 18 F]-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET). AD patients (Mini-Mental State Examination, MMSE mean = 20.2) performed significantly better on the recall of recency items during learning trials than of primacy and middle items. Recency memory was associated with cerebral metabolism in the left middle and inferior temporal gyri and left fusiform gyrus (p < .05 at the corrected cluster level). In contrast, recognition memory was correlated with metabolic activity in two clusters: (a) a large cluster that included the left hippocampus, parahippocampal gyrus, entorhinal cortex, anterior temporal lobe, and inferior and middle temporal gyri; (b) the bilateral orbitofrontal cortices (OFC). The present study further informs our understanding of the disparate functional neuroanatomy of recency memory and recognition memory in AD. We anticipated that the recency effect would be relatively preserved and associated with temporoparietal brain regions implicated in short-term verbal memory, while recognition memory would be associated with the medial temporal lobe and possibly the OFC. Consistent with our a priori hypotheses, list learning in our AD sample was characterized by a reduced primacy effect and a relatively spared recency effect; however, recency memory was associated with cerebral metabolism in inferior and lateral temporal regions associated with the semantic memory network, rather than regions associated with short-term verbal memory. The correlates of recognition memory included the medial temporal lobe and OFC, replicating prior studies.

Associative-memory representations emerge as shared spatial patterns of theta activity spanning the primate temporal cortex

PubMed Central

Nakahara, Kiyoshi; Adachi, Ken; Kawasaki, Keisuke; Matsuo, Takeshi; Sawahata, Hirohito; Majima, Kei; Takeda, Masaki; Sugiyama, Sayaka; Nakata, Ryota; Iijima, Atsuhiko; Tanigawa, Hisashi; Suzuki, Takafumi; Kamitani, Yukiyasu; Hasegawa, Isao

2016-01-01

Highly localized neuronal spikes in primate temporal cortex can encode associative memory; however, whether memory formation involves area-wide reorganization of ensemble activity, which often accompanies rhythmicity, or just local microcircuit-level plasticity, remains elusive. Using high-density electrocorticography, we capture local-field potentials spanning the monkey temporal lobes, and show that the visual pair-association (PA) memory is encoded in spatial patterns of theta activity in areas TE, 36, and, partially, in the parahippocampal cortex, but not in the entorhinal cortex. The theta patterns elicited by learned paired associates are distinct between pairs, but similar within pairs. This pattern similarity, emerging through novel PA learning, allows a machine-learning decoder trained on theta patterns elicited by a particular visual item to correctly predict the identity of those elicited by its paired associate. Our results suggest that the formation and sharing of widespread cortical theta patterns via learning-induced reorganization are involved in the mechanisms of associative memory representation. PMID:27282247

Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2017-12-01

The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hypermedia in Vocational Learning: A Hypermedia Learning Environment for Training Management Skills

ERIC Educational Resources Information Center

Konradt, Udo

2004-01-01

A learning environment is defined as an arrangement of issues, methods, techniques, and media in a given domain. Besides temporal and spatial features a learning environment considers the social situation in which learning takes place. In (hypermedia) learning environments the concept of exploration and the active role of the learner is…

Operational Interoperable Web Coverage Service for Earth Observing Satellite Data: Issues and Lessons Learned

NASA Astrophysics Data System (ADS)

Yang, W.; Min, M.; Bai, Y.; Lynnes, C.; Holloway, D.; Enloe, Y.; di, L.

2008-12-01

In the past few years, there have been growing interests, among major earth observing satellite (EOS) data providers, in serving data through the interoperable Web Coverage Service (WCS) interface protocol, developed by the Open Geospatial Consortium (OGC). The interface protocol defined in WCS specifications allows client software to make customized requests of multi-dimensional EOS data, including spatial and temporal subsetting, resampling and interpolation, and coordinate reference system (CRS) transformation. A WCS server describes an offered coverage, i.e., a data product, through a response to a client's DescribeCoverage request. The description includes the offered coverage's spatial/temporal extents and resolutions, supported CRSs, supported interpolation methods, and supported encoding formats. Based on such information, a client can request the entire or a subset of coverage in any spatial/temporal resolutions and in any one of the supported CRSs, formats, and interpolation methods. When implementing a WCS server, a data provider has different approaches to present its data holdings to clients. One of the most straightforward, and commonly used, approaches is to offer individual physical data files as separate coverages. Such implementation, however, will result in too many offered coverages for large data holdings and it also cannot fully present the relationship among different, but spatially and/or temporally associated, data files. It is desirable to disconnect offered coverages from physical data files so that the former is more coherent, especially in spatial and temporal domains. Therefore, some servers offer one single coverage for a set of spatially coregistered time series data files such as a daily global precipitation coverage linked to many global single- day precipitation files; others offer one single coverage for multiple temporally coregistered files together forming a large spatial extent. In either case, a server needs to assemble an output coverage real-time by combining potentially large number of physical files, which can be operationally difficult. The task becomes more challenging if an offered coverage involves spatially and temporally un-registered physical files. In this presentation, we will discuss issues and lessons learned in providing NASA's AIRS Level 2 atmospheric products, which are in satellite swath CRS and in 6-minute segment granule files, as virtual global coverages. We"ll discuss the WCS server's on- the-fly georectification, mosaicking, quality screening, performance, and scalability.

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.

Multidimensional Learner Model In Intelligent Learning System

NASA Astrophysics Data System (ADS)

Deliyska, B.; Rozeva, A.

2009-11-01

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

Space, relations, and the learning of science

NASA Astrophysics Data System (ADS)

Roth, Wolff-Michael; Hsu, Pei-Ling

2014-03-01

In the literature on the situated and distributed nature of cognition, the coordination of spatial organization and the structure of human practices and relations is accepted as a fact. To date, science educators have yet to build on such research. Drawing on an ethnographic study of high school students during an internship in a scientific research laboratory, which we understand as a "perspicuous setting" and a "smart setting," in which otherwise invisible dimensions of human practices become evident, we analyze the relationship between spatial configurations of the setting and the nature and temporal organization of knowing and learning in science. Our analyses show that spatial aspects of the laboratory projectively organize how participants act and can serve as resources to help the novices to participate in difficult and unfamiliar tasks. First, existing spatial relations projectively organize the language involving interns and lab members. In particular, spatial relations projectively organize where and when pedagogical language should happen; and there are specific discursive mechanisms that produce cohesion in language across different places in the laboratory. Second, the spatial arrangements projectively organize the temporal dimensions of action. These findings allow science educators to think explicitly about organizing "smart contexts" that help learners participate in and learn complex scientific laboratory practices.

Felder-Soloman's Index of Learning Styles: internal consistency, temporal stability, and factor structure.

PubMed

Hosford, Charles C; Siders, William A

2010-10-01

Strategies to facilitate learning include using knowledge of students' learning style preferences to inform students and their teachers. Aims of this study were to evaluate the factor structure, internal consistency, and temporal stability of medical student responses to the Index of Learning Styles (ILS) and determine its appropriateness as an instrument for medical education. The ILS assesses preferences on four dimensions: sensing/intuitive information perceiving, visual/verbal information receiving, active/reflective information processing, and sequential/global information understanding. Students entering the 2002-2007 classes completed the ILS; some completed the ILS again after 2 and 4 years. Analyses of responses supported the ILS's intended structure and moderate reliability. Students had moderate preferences for sensing and visual learning. This study provides evidence supporting the appropriateness of the ILS for assessing learning style preferences in medical students.

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…

Learning and retrieval behavior in recurrent neural networks with pre-synaptic dependent homeostatic plasticity

NASA Astrophysics Data System (ADS)

Mizusaki, Beatriz E. P.; Agnes, Everton J.; Erichsen, Rubem; Brunnet, Leonardo G.

2017-08-01

The plastic character of brain synapses is considered to be one of the foundations for the formation of memories. There are numerous kinds of such phenomenon currently described in the literature, but their role in the development of information pathways in neural networks with recurrent architectures is still not completely clear. In this paper we study the role of an activity-based process, called pre-synaptic dependent homeostatic scaling, in the organization of networks that yield precise-timed spiking patterns. It encodes spatio-temporal information in the synaptic weights as it associates a learned input with a specific response. We introduce a correlation measure to evaluate the precision of the spiking patterns and explore the effects of different inhibitory interactions and learning parameters. We find that large learning periods are important in order to improve the network learning capacity and discuss this ability in the presence of distinct inhibitory currents.

Solving and Learning Soft Temporal Constraints: Experimental Setting and Results

NASA Technical Reports Server (NTRS)

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

2002-01-01

Soft temporal constraints 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. Machine learning techniques can be useful in this respect. In this paper we describe two solvers (one more general and the other one more efficient) for tractable subclasses 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 representational power. Finally, we present a learning module and we show its behavior on randomly-generated examples.

Learning Temporal Patterns of Risk in a Predator-Diverse Environment

PubMed Central

Bosiger, Yoland J.; Lonnstedt, Oona M.; McCormick, Mark I.; Ferrari, Maud C. O.

2012-01-01

Predation plays a major role in shaping prey behaviour. Temporal patterns of predation risk have been shown to drive daily activity and foraging patterns in prey. Yet the ability to respond to temporal patterns of predation risk in environments inhabited by highly diverse predator communities, such as rainforests and coral reefs, has received surprisingly little attention. In this study, we investigated whether juvenile marine fish, Pomacentrus moluccensis (lemon damselfish), have the ability to learn to adjust the intensity of their antipredator response to match the daily temporal patterns of predation risk they experience. Groups of lemon damselfish were exposed to one of two predictable temporal risk patterns for six days. “Morning risk” treatment prey were exposed to the odour of Cephalopholis cyanostigma (rockcod) paired with conspecific chemical alarm cues (simulating a rockcod present and feeding) during the morning, and rockcod odour only in the evening (simulating a rockcod present but not feeding). “Evening risk” treatment prey had the two stimuli presented to them in the opposite order. When tested individually for their response to rockcod odour alone, lemon damselfish from the morning risk treatment responded with a greater antipredator response intensity in the morning than in the evening. In contrast, those lemon damselfish previously exposed to the evening risk treatment subsequently responded with a greater antipredator response when tested in the evening. The results of this experiment demonstrate that P. moluccensis have the ability to learn temporal patterns of predation risk and can adjust their foraging patterns to match the threat posed by predators at a given time of day. Our results provide the first experimental demonstration of a mechanism by which prey in a complex, multi-predator environment can learn and respond to daily patterns of predation risk. PMID:22493699

Effects of prenatal methamphetamine exposure on verbal memory revealed with fMRI

PubMed Central

Lu, Lisa H.; Johnson, Arianne; O’Hare, Elizabeth D.; Bookheimer, Susan Y.; Smith, Lynne M.; O’Connor, Mary J.; Sowell, Elizabeth R.

2009-01-01

Objective Efforts to understand specific effects of prenatal methamphetamine exposure on cognitive processing are hampered by high rates of concomitant alcohol use during pregnancy. We examined whether neurocognitive systems differed among children with differing prenatal teratogenic exposures when they engaged in a verbal memory task. Patients and Methods Participants (7-15 years old) engaged in a verbal paired associate learning task while undergoing functional magnetic resonance imaging. The MA group included 14 children with prenatal methamphetamine exposure, 12 of whom had concomitant alcohol exposure. They were compared to 9 children with prenatal alcohol but not methamphetamine exposure (ALC) and 20 unexposed controls (CON). Groups did not differ in age, gender, or socioeconomic status. Participants’ IQ and verbal learning performance were measured using standardized instruments. Results The MA group activated more diffuse brain regions, including bilateral medial temporal structures known to be important for memory, than both the ALC and the CON groups. These group differences remained after IQ was covaried. More activation in medial temporal structures by the MA group compared to the ALC group cannot be explained by performance differences because both groups performed at similar levels on the verbal memory task. Conclusions More diffuse activation in the MA group during verbal memory may reflect recruitment of compensatory systems to support a weak verbal memory network. Differences in activation patterns between the MA and ALC groups suggest that prenatal MA exposure influences the development of the verbal memory system above and beyond effects of prenatal alcohol exposure. PMID:19525715

Rapid language-related plasticity: microstructural changes in the cortex after a short session of new word learning.

PubMed

Hofstetter, Shir; Friedmann, Naama; Assaf, Yaniv

2017-04-01

Human brain imaging revealed that the brain can undergo structural plasticity following new learning experiences. Most magnetic resonance imaging (MRI) uncovered morphometric alternation in cortical density after the long-term training of weeks to months. A recent diffusion tensor imaging (DTI) study has found changes in diffusion indices after 2 h of training, primarily in the hippocampus. However, whether a short learning experience can induce microstructural changes in the neocortex is still unclear. Here, we used diffusion MRI, a method sensitive to tissue microstructure, to study cortical plasticity. To attain cortical involvement, we used a short language task (under 1 h) of introducing new lexical items (flower names) to the lexicon. We have found significant changes in diffusivity in cortical regions involved in language and reading (inferior frontal gyrus, middle temporal gyrus, and inferior parietal lobule). In addition, the difference in the values of diffusivity correlated with the lexical learning rate in the task. Moreover, significant changes were found in white matter tracts near the cortex, and the extent of change correlated with behavioral measures of lexical learning rate. These findings provide first evidence of short-term cortical plasticity in the human brain after a short language learning task. It seems that short training of less than an hour of high cognitive demand can induce microstructural changes in the cortex, suggesting a rapid time scale of neuroplasticity and providing additional evidence of the power of MRI to investigate the temporal and spatial progressions of this process.

Learning, worsening, and generalization in response to auditory perceptual training during adolescencea

PubMed Central

Huyck, Julia Jones; Wright, Beverly A.

2013-01-01

While it is commonly held that the capacity to learn is greatest in the young, there have been few direct comparisons of the response to training across age groups. Here, adolescents (11–17 years, n = 20) and adults (≥18 years, n = 11) practiced detecting a backward-masked tone for ∼1 h/day for 10 days. Nearly every adult, but only half of the adolescents improved across sessions, and the adolescents who learned did so more slowly than adults. Nevertheless, the adolescent and adult learners showed the same generalization pattern, improving on untrained backward- but not forward- or simultaneous-masking conditions. Another subset of adolescents (n = 6) actually got worse on the trained condition. This worsening, unlike learning, generalized to an untrained forward-masking, but not backward-masking condition. Within sessions, both age groups got worse, but the worsening was greater for adolescents. These maturational changes in the response to training largely followed those previously reported for temporal-interval discrimination. Overall, the results suggest that late-maturing processes affect the response to perceptual training and that some of these processes may be shared between tasks. Further, the different developmental rates for learning and generalization, and different generalization patterns for learning and worsening imply that learning, generalization, and worsening may have different origins. PMID:23927116

Brain Behavior Evolution during Learning: Emergence of Hierarchical Temporal Memory

DTIC Science & Technology

2013-08-30

organization and synapse strengthening and reconnection operating within and upon the existing processing structures[2]. To say the least, the brain is...that it is a tree increases, then we say its hierarchy in- creases. We explore different starting values and different thresholds and find that...impulses from two neuronal columns ( say i and k) to reach column j at the exact same time. This means when column j is analyzing whether or not to

Working toward a Neurobiological Account of ADHD: Commentary on Gail Tripp and Jeff Wickens, Dopamine Transfer Deficit

ERIC Educational Resources Information Center

Williams, Jonathan

2008-01-01

The dopamine transfer deficit model of attention deficit hyperactivity disorder (ADHD) is compared and contrasted with the existing dynamic developmental theory and the extended temporal difference (TD) model. The first two both identify learning deficits as a key problem in ADHD, but this mechanism would seem at least as likely to cause other…

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.

Dynamical principles in neuroscience

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.; Abarbanel, Henry D. I.

2006-10-01

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only a few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?

Dynamical principles in neuroscience

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

Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only amore » few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?.« less

Integrated Analysis of Alzheimer's Disease and Schizophrenia Dataset Revealed Different Expression Pattern in Learning and Memory.

PubMed

Li, Wen-Xing; Dai, Shao-Xing; Liu, Jia-Qian; Wang, Qian; Li, Gong-Hua; Huang, Jing-Fei

2016-01-01

Alzheimer's disease (AD) and schizophrenia (SZ) are both accompanied by impaired learning and memory functions. This study aims to explore the expression profiles of learning or memory genes between AD and SZ. We downloaded 10 AD and 10 SZ datasets from GEO-NCBI for integrated analysis. These datasets were processed using RMA algorithm and a global renormalization for all studies. Then Empirical Bayes algorithm was used to find the differentially expressed genes between patients and controls. The results showed that most of the differentially expressed genes were related to AD whereas the gene expression profile was little affected in the SZ. Furthermore, in the aspects of the number of differentially expressed genes, the fold change and the brain region, there was a great difference in the expression of learning or memory related genes between AD and SZ. In AD, the CALB1, GABRA5, and TAC1 were significantly downregulated in whole brain, frontal lobe, temporal lobe, and hippocampus. However, in SZ, only two genes CRHBP and CX3CR1 were downregulated in hippocampus, and other brain regions were not affected. The effect of these genes on learning or memory impairment has been widely studied. It was suggested that these genes may play a crucial role in AD or SZ pathogenesis. The different gene expression patterns between AD and SZ on learning and memory functions in different brain regions revealed in our study may help to understand the different mechanism between two diseases.

Episodic and semantic memory in children with mesial temporal sclerosis.

PubMed

Rzezak, Patricia; Guimarães, Catarina; Fuentes, Daniel; Guerreiro, Marilisa M; Valente, Kette Dualibi Ramos

2011-07-01

The aim of this study was to analyze semantic and episodic memory deficits in children with mesial temporal sclerosis (MTS) and their correlation with clinical epilepsy variables. For this purpose, 19 consecutive children and adolescents with MTS (8 to 16 years old) were evaluated and their performance on five episodic memory tests (short- and long-term memory and learning) and four semantic memory tests was compared with that of 28 healthy volunteers. Patients performed worse on tests of immediate and delayed verbal episodic memory, visual episodic memory, verbal and visual learning, mental scanning for semantic clues, object naming, word definition, and repetition of sentences. Clinical variables such as early age at seizure onset, severity of epilepsy, and polytherapy impaired distinct types of memory. These data confirm that children with MTS have episodic memory deficits and add new information on semantic memory. The data also demonstrate that clinical variables contribute differently to episodic and semantic memory performance. Copyright © 2011 Elsevier Inc. All rights reserved.

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

PubMed

Zenke, Friedemann; Ganguli, Surya

2018-06-01

A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.

Temporal and Statistical Information in Causal Structure Learning

ERIC Educational Resources Information Center

McCormack, Teresa; Frosch, Caren; Patrick, Fiona; Lagnado, David

2015-01-01

Three experiments examined children's and adults' abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a 3-variable mechanical…

Temporal Processing, Attention, and Learning Disorders

ERIC Educational Resources Information Center

Landerl, Karin; Willburger, Edith

2010-01-01

In a large sample (N = 439) of literacy impaired and unimpaired elementary school children the predictions of the temporal processing theory of dyslexia were tested while controlling for (sub)clininal attentional deficits. Visual and Auditory Temporal Order Judgement were administered as well as three subtests of a standardized attention test. The…

Learning temporal context shapes prestimulus alpha oscillations and improves visual discrimination performance.

PubMed

Toosi, Tahereh; K Tousi, Ehsan; Esteky, Hossein

2017-08-01

Time is an inseparable component of every physical event that we perceive, yet it is not clear how the brain processes time or how the neuronal representation of time affects our perception of events. Here we asked subjects to perform a visual discrimination task while we changed the temporal context in which the stimuli were presented. We collected electroencephalography (EEG) signals in two temporal contexts. In predictable blocks stimuli were presented after a constant delay relative to a visual cue, and in unpredictable blocks stimuli were presented after variable delays relative to the visual cue. Four subsecond delays of 83, 150, 400, and 800 ms were used in the predictable and unpredictable blocks. We observed that predictability modulated the power of prestimulus alpha oscillations in the parieto-occipital sites: alpha power increased in the 300-ms window before stimulus onset in the predictable blocks compared with the unpredictable blocks. This modulation only occurred in the longest delay period, 800 ms, in which predictability also improved the behavioral performance of the subjects. Moreover, learning the temporal context shaped the prestimulus alpha power: modulation of prestimulus alpha power grew during the predictable block and correlated with performance enhancement. These results suggest that the brain is able to learn the subsecond temporal context of stimuli and use this to enhance sensory processing. Furthermore, the neural correlate of this temporal prediction is reflected in the alpha oscillations. NEW & NOTEWORTHY It is not well understood how the uncertainty in the timing of an external event affects its processing, particularly at subsecond scales. Here we demonstrate how a predictable timing scheme improves visual processing. We found that learning the predictable scheme gradually shaped the prestimulus alpha power. These findings indicate that the human brain is able to extract implicit subsecond patterns in the temporal context of events. Copyright © 2017 the American Physiological Society.

Evolution of learning strategies in temporally and spatially variable environments: A review of theory

PubMed Central

Aoki, Kenichi; Feldman, Marcus W.

2013-01-01

The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change – coevolutionary, two-timescale, and information decay – are compared and shown to sometimes yield contradictory results. The so-called Rogers’ paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers’ paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. PMID:24211681

Evolution of learning strategies in temporally and spatially variable environments: a review of theory.

PubMed

Aoki, Kenichi; Feldman, Marcus W

2014-02-01

The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change--coevolutionary, two-timescale, and information decay--are compared and shown to sometimes yield contradictory results. The so-called Rogers' paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers' paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Decoding the Formation of New Semantics: MVPA Investigation of Rapid Neocortical Plasticity during Associative Encoding through Fast Mapping.

PubMed

Atir-Sharon, Tali; Gilboa, Asaf; Hazan, Hananel; Koilis, Ester; Manevitz, Larry M

2015-01-01

Neocortical structures typically only support slow acquisition of declarative memory; however, learning through fast mapping may facilitate rapid learning-induced cortical plasticity and hippocampal-independent integration of novel associations into existing semantic networks. During fast mapping the meaning of new words and concepts is inferred, and durable novel associations are incidentally formed, a process thought to support early childhood's exuberant learning. The anterior temporal lobe, a cortical semantic memory hub, may critically support such learning. We investigated encoding of semantic associations through fast mapping using fMRI and multivoxel pattern analysis. Subsequent memory performance following fast mapping was more efficiently predicted using anterior temporal lobe than hippocampal voxels, while standard explicit encoding was best predicted by hippocampal activity. Searchlight algorithms revealed additional activity patterns that predicted successful fast mapping semantic learning located in lateral occipitotemporal and parietotemporal neocortex and ventrolateral prefrontal cortex. By contrast, successful explicit encoding could be classified by activity in medial and dorsolateral prefrontal and parahippocampal cortices. We propose that fast mapping promotes incidental rapid integration of new associations into existing neocortical semantic networks by activating related, nonoverlapping conceptual knowledge. In healthy adults, this is better captured by unique anterior and lateral temporal lobe activity patterns, while hippocampal involvement is less predictive of this kind of learning.

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.

A Spiking Neural Network System for Robust Sequence Recognition.

PubMed

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

2016-03-01

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

Application of Deep Learning of Multi-Temporal SENTINEL-1 Images for the Classification of Coastal Vegetation Zone of the Danube Delta

NASA Astrophysics Data System (ADS)

Niculescu, S.; Ienco, D.; Hanganu, J.

2018-04-01

Land cover is a fundamental variable for regional planning, as well as for the study and understanding of the environment. This work propose a multi-temporal approach relying on a fusion of radar multi-sensor data and information collected by the latest sensor (Sentinel-1) with a view to obtaining better results than traditional image processing techniques. The Danube Delta is the site for this work. The spatial approach relies on new spatial analysis technologies and methodologies: Deep Learning of multi-temporal Sentinel-1. We propose a deep learning network for image classification which exploits the multi-temporal characteristic of Sentinel-1 data. The model we employ is a Gated Recurrent Unit (GRU) Network, a recurrent neural network that explicitly takes into account the time dimension via a gated mechanism to perform the final prediction. The main quality of the GRU network is its ability to consider only the important part of the information coming from the temporal data discarding the irrelevant information via a forgetting mechanism. We propose to use such network structure to classify a series of images Sentinel-1 (20 Sentinel-1 images acquired between 9.10.2014 and 01.04.2016). The results are compared with results of the classification of Random Forest.

Inferring interventional predictions from observational learning data.

PubMed

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

2008-02-01

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

Assessment of nonverbal learning and memory using the Design Learning Test.

PubMed

Foster, Paul S; Drago, Valeria; Harrison, David W

2009-05-01

The laterality of verbal and nonverbal learning and memory to the left and right temporal lobes, respectively, has received much empirical support. Researchers have often used the Rey Auditory Verbal Learning Test (RAVLT) as a measure of verbal learning and memory in these investigations. However, a precise analog of the RAVLT that uses stimuli difficult to encode verbally has not been reported. Further, although researchers have developed some measures that are essentially visuospatial analogs of the RAVLT, no correlational data have been reported attesting to the relation between the measures. The authors report the development of a nonverbal analog of the RAVLT, referred to as the Design Learning Test (DLT). Also, the authors present correlational data supporting a relation between the DLT and RAVLT, and they hope that the present study will stimulate research investigating whether the DLT is sensitive to right temporal lobe functioning.

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

Dissociating hippocampal and striatal contributions to sequential prediction learning

PubMed Central

Bornstein, Aaron M.; Daw, Nathaniel D.

2011-01-01

Behavior may be generated on the basis of many different kinds of learned contingencies. For instance, responses could be guided by the direct association between a stimulus and response, or by sequential stimulus-stimulus relationships (as in model-based reinforcement learning or goal-directed actions). However, the neural architecture underlying sequential predictive learning is not well-understood, in part because it is difficult to isolate its effect on choice behavior. To track such learning more directly, we examined reaction times (RTs) in a probabilistic sequential picture identification task. We used computational learning models to isolate trial-by-trial effects of two distinct learning processes in behavior, and used these as signatures to analyze the separate neural substrates of each process. RTs were best explained via the combination of two delta rule learning processes with different learning rates. To examine neural manifestations of these learning processes, we used functional magnetic resonance imaging to seek correlates of timeseries related to expectancy or surprise. We observed such correlates in two regions, hippocampus and striatum. By estimating the learning rates best explaining each signal, we verified that they were uniquely associated with one of the two distinct processes identified behaviorally. These differential correlates suggest that complementary anticipatory functions drive each region's effect on behavior. Our results provide novel insights as to the quantitative computational distinctions between medial temporal and basal ganglia learning networks and enable experiments that exploit trial-by-trial measurement of the unique contributions of both hippocampus and striatum to response behavior. PMID:22487032

Declarative long-term memory and the mesial temporal lobe: Insights from a 5-year postsurgery follow-up study on refractory temporal lobe epilepsy.

PubMed

Salvato, Gerardo; Scarpa, Pina; Francione, Stefano; Mai, Roberto; Tassi, Laura; Scarano, Elisa; Lo Russo, Giorgio; Bottini, Gabriella

2016-11-01

It is largely recognized that the mesial temporal lobe and its substructure support declarative long-term memory (LTM). So far, different theories have been suggested, and the organization of declarative verbal LTM in the brain is still a matter of debate. In the current study, we retrospectively selected 151 right-handed patients with temporal lobe epilepsy with and without hippocampal sclerosis, with a homogeneous (seizure-free) clinical outcome. We analyzed verbal memory performance within a normalized scores context, by means of prose recall and word paired-associate learning tasks. Patients were tested at presurgical baseline, 6months, 2 and 5years after anteromesial temporal lobe surgery, using parallel versions of the neuropsychological tests. Our main finding revealed a key involvement of the left temporal lobe and, in particular, of the left hippocampus in prose recall rather than word paired-associate task. We also confirmed that shorter duration of epilepsy, younger age, and withdrawal of antiepileptic drugs would predict a better memory outcome. When individual memory performance was taken into account, data showed that females affected by left temporal lobe epilepsy for longer duration were more at risk of presenting a clinically pathologic LTM at 5years after surgery. Taken together, these findings shed new light on verbal declarative memory in the mesial temporal lobe and on the behavioral signature of the functional reorganization after the surgical treatment of temporal lobe epilepsy. Copyright © 2016 Elsevier Inc. All rights reserved.

Cognitive and Learning Strategies for Longstanding Temporal Lobe Lesions in a Child Who Suffered from "Herpes Simplex" Virus Encephalitis: A Case Study over 10 Years

ERIC Educational Resources Information Center

van Schoor, A. N.; Naude, H.; van Rensburg, M.; Pretorius, E.; Boon, J. M.

2005-01-01

This article presents a case study indicating that "Herpes simplex" virus (HSV) encephalitis may cause permanent learning disabilities due to damage to the temporal lobes as it discusses the results of a case study extending over 10 years to determine the long-term effects on both the anatomy of the brain and the intellectual functioning of the…

Cognitive and Learning Strategies for Longstanding Temporal Lobe Lesions in a Child Who Suffered from "Herpes Simplex" Virus Encephalitis: A Case Study over 10 Years

ERIC Educational Resources Information Center

van Schoor, A. N.; Naude, H.; van Rensburg, M.; Pretorius, E.; Boon, J. M.

2004-01-01

This article presents a case study indicating that "Herpes simplex" virus (HSV) encephalitis may cause permanent learning disabilities due to damage to the temporal lobes, as it discusses the results of a case study extending over 10 years to determine the long-term effects on both the anatomy of the brain and the intellectual functioning of the…

Intelligent Fault Diagnosis of Rotary Machinery Based on Unsupervised Multiscale Representation Learning

NASA Astrophysics Data System (ADS)

Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun

2017-11-01

The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.

Real time eye tracking using Kalman extended spatio-temporal context learning

NASA Astrophysics Data System (ADS)

Munir, Farzeen; Minhas, Fayyaz ul Amir Asfar; Jalil, Abdul; Jeon, Moongu

2017-06-01

Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.

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

PubMed Central

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

2016-01-01

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

Cortical ensemble activity increasingly predicts behaviour outcomes during learning of a motor task

NASA Astrophysics Data System (ADS)

Laubach, Mark; Wessberg, Johan; Nicolelis, Miguel A. L.

2000-06-01

When an animal learns to make movements in response to different stimuli, changes in activity in the motor cortex seem to accompany and underlie this learning. The precise nature of modifications in cortical motor areas during the initial stages of motor learning, however, is largely unknown. Here we address this issue by chronically recording from neuronal ensembles located in the rat motor cortex, throughout the period required for rats to learn a reaction-time task. Motor learning was demonstrated by a decrease in the variance of the rats' reaction times and an increase in the time the animals were able to wait for a trigger stimulus. These behavioural changes were correlated with a significant increase in our ability to predict the correct or incorrect outcome of single trials based on three measures of neuronal ensemble activity: average firing rate, temporal patterns of firing, and correlated firing. This increase in prediction indicates that an association between sensory cues and movement emerged in the motor cortex as the task was learned. Such modifications in cortical ensemble activity may be critical for the initial learning of motor tasks.

Apprenticeship Learning: Learning to Schedule from Human Experts

DTIC Science & Technology

2016-06-09

approaches to learning such models are based on Markov models, such as reinforcement learning or inverse reinforcement learning (Busoniu, Babuska, and De...via inverse reinforcement learning. In ICML. Barto, A. G., and Mahadevan, S. 2003. Recent advances in hierarchical reinforcement learning. Discrete...of tasks with temporal constraints. In Proc. AAAI, 2110–2116. Odom, P., and Natarajan, S. 2015. Active advice seeking for inverse reinforcement

Effects of neonatal inferior prefrontal and medial temporal lesions on learning the rule for delayed nonmatching-to-sample.

PubMed

Málková, L; Bachevalier, J; Webster, M; Mishkin, M

2000-01-01

The ability of rhesus monkeys to master the rule for delayed nonmatching-to-sample (DNMS) has a protracted ontogenetic development, reaching adult levels of proficiency around 4 to 5 years of age (Bachevalier, 1990). To test the possibility that this slow development could be due, at least in part, to immaturity of the prefrontal component of a temporo-prefrontal circuit important for DNMS rule learning (Kowalska, Bachevalier, & Mishkin, 1991; Weinstein, Saunders, & Mishkin, 1988), monkeys with neonatal lesions of the inferior prefrontal convexity were compared on DNMS with both normal controls and animals given neonatal lesions of the medial temporal lobe. Consistent with our previous results (Bachevalier & Mishkin, 1994; Málková, Mishkin, & Bachevalier, 1995), the neonatal medial temporal lesions led to marked impairment in rule learning (as well as in recognition memory with long delays and list lengths) at both 3 months and 2 years of age. By contrast, the neonatal inferior convexity lesions yielded no impairment in rule-learning at 3 months and only a mild impairment at 2 years, a finding that also contrasts sharply with the marked effects of the same lesion made in adulthood. This pattern of sparing closely resembles the one found earlier after neonatal lesions to the cortical visual area TE (Bachevalier & Mishkin, 1994; Málková et al., 1995). The functional sparing at 3 months probably reflects the fact that the temporo-prefrontal circuit is nonfunctional at this early age, resulting in a total dependency on medial temporal contributions to rule learning. With further development, however, this circuit begins to provide a supplementary route for learning.

The perception of regularity in an isochronous stimulus in zebra finches (Taeniopygia guttata) and humans.

PubMed

van der Aa, Jeroen; Honing, Henkjan; ten Cate, Carel

2015-06-01

Perceiving temporal regularity in an auditory stimulus is considered one of the basic features of musicality. Here we examine whether zebra finches can detect regularity in an isochronous stimulus. Using a go/no go paradigm we show that zebra finches are able to distinguish between an isochronous and an irregular stimulus. However, when the tempo of the isochronous stimulus is changed, it is no longer treated as similar to the training stimulus. Training with three isochronous and three irregular stimuli did not result in improvement of the generalization. In contrast, humans, exposed to the same stimuli, readily generalized across tempo changes. Our results suggest that zebra finches distinguish the different stimuli by learning specific local temporal features of each individual stimulus rather than attending to the global structure of the stimuli, i.e., to the temporal regularity. Copyright © 2015 Elsevier B.V. All rights reserved.

High-resolution Temporal Representations of Alcohol and Tobacco Behaviors from Social Media Data.

PubMed

Huang, Tom; Elghafari, Anas; Relia, Kunal; Chunara, Rumi

2017-11-01

Understanding tobacco- and alcohol-related behavioral patterns is critical for uncovering risk factors and potentially designing targeted social computing intervention systems. Given that we make choices multiple times per day, hourly and daily patterns are critical for better understanding behaviors. Here, we combine natural language processing, machine learning and time series analyses to assess Twitter activity specifically related to alcohol and tobacco consumption and their sub-daily, daily and weekly cycles. Twitter self-reports of alcohol and tobacco use are compared to other data streams available at similar temporal resolution. We assess if discussion of drinking by inferred underage versus legal age people or discussion of use of different types of tobacco products can be differentiated using these temporal patterns. We find that time and frequency domain representations of behaviors on social media can provide meaningful and unique insights, and we discuss the types of behaviors for which the approach may be most useful.

Decoding of finger trajectory from ECoG using deep learning.

PubMed

Xie, Ziqian; Schwartz, Odelia; Prasad, Abhishek

2018-06-01

Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes it difficult to make the whole system adaptive. The goal was to create an adaptive online system with a single objective function and a single learning algorithm so that the whole system can be trained in parallel to increase the decoding performance. Here, we used deep neural networks consisting of convolutional neural networks (CNN) and a special kind of recurrent neural network (RNN) called long short term memory (LSTM) to address these needs. We used electrocorticography (ECoG) data collected by Kubanek et al. The task consisted of individual finger flexions upon a visual cue. Our model combined a hierarchical feature extractor CNN and a RNN that was able to process sequential data and recognize temporal dynamics in the neural data. CNN was used as the feature extractor and LSTM was used as the regression algorithm to capture the temporal dynamics of the signal. We predicted the finger trajectory using ECoG signals and compared results for the least angle regression (LARS), CNN-LSTM, random forest, LSTM model (LSTM_HC, for using hard-coded features) and a decoding pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. This study demonstrated a decoding network for BMI that involved a convolutional and recurrent neural network model. It integrated the feature extraction pipeline into the convolution and pooling layer and used LSTM layer to capture the state transitions. The discussed network eliminated the need to separately train the model at each step in the decoding pipeline. The whole system can be jointly optimized using stochastic gradient descent and is capable of online learning.

Decoding of finger trajectory from ECoG using deep learning

NASA Astrophysics Data System (ADS)

Xie, Ziqian; Schwartz, Odelia; Prasad, Abhishek

2018-06-01

Objective. Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes it difficult to make the whole system adaptive. The goal was to create an adaptive online system with a single objective function and a single learning algorithm so that the whole system can be trained in parallel to increase the decoding performance. Here, we used deep neural networks consisting of convolutional neural networks (CNN) and a special kind of recurrent neural network (RNN) called long short term memory (LSTM) to address these needs. Approach. We used electrocorticography (ECoG) data collected by Kubanek et al. The task consisted of individual finger flexions upon a visual cue. Our model combined a hierarchical feature extractor CNN and a RNN that was able to process sequential data and recognize temporal dynamics in the neural data. CNN was used as the feature extractor and LSTM was used as the regression algorithm to capture the temporal dynamics of the signal. Main results. We predicted the finger trajectory using ECoG signals and compared results for the least angle regression (LARS), CNN-LSTM, random forest, LSTM model (LSTM_HC, for using hard-coded features) and a decoding pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. Significance. This study demonstrated a decoding network for BMI that involved a convolutional and recurrent neural network model. It integrated the feature extraction pipeline into the convolution and pooling layer and used LSTM layer to capture the state transitions. The discussed network eliminated the need to separately train the model at each step in the decoding pipeline. The whole system can be jointly optimized using stochastic gradient descent and is capable of online learning.

Unsupervised learning of discriminative edge measures for vehicle matching between nonoverlapping cameras.

PubMed

Shan, Ying; Sawhney, Harpreet S; Kumar, Rakesh

2008-04-01

This paper proposes a novel unsupervised algorithm learning discriminative features in the context of matching road vehicles between two non-overlapping cameras. The matching problem is formulated as a same-different classification problem, which aims to compute the probability of vehicle images from two distinct cameras being from the same vehicle or different vehicle(s). We employ a novel measurement vector that consists of three independent edge-based measures and their associated robust measures computed from a pair of aligned vehicle edge maps. The weight of each measure is determined by an unsupervised learning algorithm that optimally separates the same-different classes in the combined measurement space. This is achieved with a weak classification algorithm that automatically collects representative samples from same-different classes, followed by a more discriminative classifier based on Fisher' s Linear Discriminants and Gibbs Sampling. The robustness of the match measures and the use of unsupervised discriminant analysis in the classification ensures that the proposed method performs consistently in the presence of missing/false features, temporally and spatially changing illumination conditions, and systematic misalignment caused by different camera configurations. Extensive experiments based on real data of over 200 vehicles at different times of day demonstrate promising results.

Different effects of anterior temporal lobectomy and selective amygdalohippocampectomy on verbal memory performance of patients with epilepsy.

PubMed

Boucher, Olivier; Dagenais, Emmanuelle; Bouthillier, Alain; Nguyen, Dang Khoa; Rouleau, Isabelle

2015-11-01

The advantage of selective amygdalohippocampectomy (SAH) over anterior temporal lobectomy (ATL) for the treatment of temporal lobe epilepsy (TLE) remains controversial. Because ATL is more extensive and involves the lateral and medial parts of the temporal lobe, it may be predicted that its impact on memory is more important than SAH, which involves resection of medial temporal structures only. However, several studies do not support this assumption. Possible explanations include task-specific factors such as the extent of semantic and syntactic information to be memorized and failure to control for main confounders. We compared preoperative vs. postoperative memory performance in 13 patients with SAH with 26 patients who underwent ATL matched on side of surgery, IQ, age at seizure onset, and age at surgery. Memory function was assessed using the Logical Memory subtest from the Wechsler Memory Scales - 3rd edition (LM-WMS), the Rey Auditory Verbal Learning Test (RAVLT), the Digit Span subtest from the Wechsler Adult Intelligence Scale, and the Rey-Osterrieth Complex Figure Test. Repeated measures analyses of variance revealed opposite effects of SAH and ATL on the two verbal learning memory tests. On the immediate recall trial of the LM-WMS, performance deteriorated after ATL in comparison with that after SAH. By contrast, on the delayed recognition trial of the RAVLT, performance deteriorated after SAH compared with that after ATL. However, additional analyses revealed that the latter finding was only observed when surgery was conducted in the right hemisphere. No interaction effects were found on other memory outcomes. The results are congruent with the view that tasks involving rich semantic content and syntactical structure are more sensitive to the effects of lateral temporal cortex resection as compared with mesiotemporal resection. The findings highlight the importance of task selection in the assessment of memory in patients undergoing TLE surgery. Copyright © 2015 Elsevier Inc. All rights reserved.

Improved Adjoint-Operator Learning For A Neural Network

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad; Barhen, Jacob

1995-01-01

Improved method of adjoint-operator learning reduces amount of computation and associated computational memory needed to make electronic neural network learn temporally varying pattern (e.g., to recognize moving object in image) in real time. Method extension of method described in "Adjoint-Operator Learning for a Neural Network" (NPO-18352).

Operating Characteristics of the Implicit Learning System Supporting Serial Interception Sequence Learning

ERIC Educational Resources Information Center

Sanchez, Daniel J.; Reber, Paul J.

2012-01-01

The memory system that supports implicit perceptual-motor sequence learning relies on brain regions that operate separately from the explicit, medial temporal lobe memory system. The implicit learning system therefore likely has distinct operating characteristics and information processing constraints. To attempt to identify the limits of the…

E-Learning, Time and Unconscious Thinking

ERIC Educational Resources Information Center

Mathew, David

2014-01-01

This article views the temporal dimensions of e-learning through a psychoanalytic lens, and asks the reader to consider links between online learning and psychoanalysis. It argues that time and its associated philosophical puzzles impinge on both psychoanalytic theory and on e-learning at two specific points. The first is in the distinction…

Perceptual Real-Time 2D-to-3D Conversion Using Cue Fusion.

PubMed

Leimkuhler, Thomas; Kellnhofer, Petr; Ritschel, Tobias; Myszkowski, Karol; Seidel, Hans-Peter

2018-06-01

We propose a system to infer binocular disparity from a monocular video stream in real-time. Different from classic reconstruction of physical depth in computer vision, we compute perceptually plausible disparity, that is numerically inaccurate, but results in a very similar overall depth impression with plausible overall layout, sharp edges, fine details and agreement between luminance and disparity. We use several simple monocular cues to estimate disparity maps and confidence maps of low spatial and temporal resolution in real-time. These are complemented by spatially-varying, appearance-dependent and class-specific disparity prior maps, learned from example stereo images. Scene classification selects this prior at runtime. Fusion of prior and cues is done by means of robust MAP inference on a dense spatio-temporal conditional random field with high spatial and temporal resolution. Using normal distributions allows this in constant-time, parallel per-pixel work. We compare our approach to previous 2D-to-3D conversion systems in terms of different metrics, as well as a user study and validate our notion of perceptually plausible disparity.

Multiple anatomical systems embedded within the primate medial temporal lobe: implications for hippocampal function.

PubMed

Aggleton, John P

2012-08-01

A review of medial temporal lobe connections reveals three distinct groupings of hippocampal efferents. These efferent systems and their putative memory functions are: (1) The 'extended-hippocampal system' for episodic memory, which involves the anterior thalamic nuclei, mammillary bodies and retrosplenial cortex, originates in the subicular cortices, and has a largely laminar organisation; (2) The 'rostral hippocampal system' for affective and social learning, which involves prefrontal cortex, amygdala and nucleus accumbens, has a columnar organisation, and originates from rostral CA1 and subiculum; (3) The 'reciprocal hippocampal-parahippocampal system' for sensory processing and integration, which originates from the length of CA1 and the subiculum, and is characterised by columnar, connections with reciprocal topographies. A fourth system, the 'parahippocampal-prefrontal system' that supports familiarity signalling and retrieval processing, has more widespread prefrontal connections than those of the hippocampus, along with different thalamic inputs. Despite many interactions between these four systems, they may retain different roles in memory which when combined explain the importance of the medial temporal lobe for the formation of declarative memories. Copyright © 2011 Elsevier Ltd. All rights reserved.

[Social learning as an uncertainty-reduction strategy: an adaptationist approach].

PubMed

Nakanishi, Daisuke; Kameda, Tatsuya; Shinada, Mizuho

2003-04-01

Social learning is an effective mechanism to reduce uncertainty about environmental knowledge, helping individuals adopt an adaptive behavior in the environment at small cost. Although this is evident for learning about temporally stable targets (e.g., acquiring avoidance of toxic foods culturally), the functional value of social learning in a temporally unstable environment is less clear; knowledge acquired by social learning may be outdated. This paper addressed adaptive values of social learning in a non-stationary environment empirically. When individual learning about the non-stationary environment is costly, a hawk-dove-game-like equilibrium is expected to emerge in the population, where members who engage in costly individual learning and members who skip the information search and free-ride on other members' search efforts coexist at a stable ratio. Such a "producer-scrounger" structure should qualify effectiveness of social/cultural learning severely, especially "conformity bias" when using social information (Boyd & Richerson, 1985). We tested these predictions by an experiment implementing a non-stationary uncertain environment in a laboratory. The results supported our thesis. Implications of these findings and some future directions were discussed.

Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

NASA Astrophysics Data System (ADS)

Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

2017-07-01

Ternary change detection aims to detect changes and group the changes into positive change and negative change. It is of great significance in the joint interpretation of spatial-temporal synthetic aperture radar images. In this study, sparse autoencoder, convolutional neural networks (CNN) and unsupervised clustering are combined to solve ternary change detection problem without any supervison. Firstly, sparse autoencoder is used to transform log-ratio difference image into a suitable feature space for extracting key changes and suppressing outliers and noise. And then the learned features are clustered into three classes, which are taken as the pseudo labels for training a CNN model as change feature classifier. The reliable training samples for CNN are selected from the feature maps learned by sparse autoencoder with certain selection rules. Having training samples and the corresponding pseudo labels, the CNN model can be trained by using back propagation with stochastic gradient descent. During its training procedure, CNN is driven to learn the concept of change, and more powerful model is established to distinguish different types of changes. Unlike the traditional methods, the proposed framework integrates the merits of sparse autoencoder and CNN to learn more robust difference representations and the concept of change for ternary change detection. Experimental results on real datasets validate the effectiveness and superiority of the proposed framework.

The immediate and short-term effects of bilateral intrahippocampal depth electrodes on verbal memory.

PubMed

Helmstaedter, Christoph; Gielen, Gerrit H; Witt, Juri-Alexander

2018-06-01

In contrast to previous studies, Ljung et al. provide evidence of permanent cognitive consequences of bilateral intrahippocampal depth electrodes for verbal memory in patients who were not operated or operated in the right temporal lobe. Stimulated by this, we provide historical confirmatory and supplementary evidence of the detrimental effect of bilateral depth electrodes implanted along the longitudinal axis of the hippocampus on verbal learning and especially on delayed verbal memory and recognition performance. This is demonstrated in 31 patients with memory assessments before implantation, after explantation, and 3 months later after left/right temporal lobe surgery. After surgery, significant recovery from postimplantation impairment is found in right temporal patients. Left temporal resection patients stay on the level seen after implantation and do not recover. Surgery, however, has its own effects in addition to the implantation. Intracranial electrodes for electroencephalographic monitoring or electrical stimulation are commonly and increasingly used for diagnosis or treatment in pharmacoresistant epilepsies. Thus, the monitoring of invasive stereotactic approaches is recommended to find safe procedures for the patients. In response to the findings, we restricted indications and used different implantation schemes, different trajectories, and targets to minimize the risk of additional damage. Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.

Perception of Filtered Speech by Children with Developmental Dyslexia and Children with Specific Language Impairments

PubMed Central

Goswami, Usha; Cumming, Ruth; Chait, Maria; Huss, Martina; Mead, Natasha; Wilson, Angela M.; Barnes, Lisa; Fosker, Tim

2016-01-01

Here we use two filtered speech tasks to investigate children’s processing of slow (<4 Hz) versus faster (∼33 Hz) temporal modulations in speech. We compare groups of children with either developmental dyslexia (Experiment 1) or speech and language impairments (SLIs, Experiment 2) to groups of typically-developing (TD) children age-matched to each disorder group. Ten nursery rhymes were filtered so that their modulation frequencies were either low-pass filtered (<4 Hz) or band-pass filtered (22 – 40 Hz). Recognition of the filtered nursery rhymes was tested in a picture recognition multiple choice paradigm. Children with dyslexia aged 10 years showed equivalent recognition overall to TD controls for both the low-pass and band-pass filtered stimuli, but showed significantly impaired acoustic learning during the experiment from low-pass filtered targets. Children with oral SLIs aged 9 years showed significantly poorer recognition of band pass filtered targets compared to their TD controls, and showed comparable acoustic learning effects to TD children during the experiment. The SLI samples were also divided into children with and without phonological difficulties. The children with both SLI and phonological difficulties were impaired in recognizing both kinds of filtered speech. These data are suggestive of impaired temporal sampling of the speech signal at different modulation rates by children with different kinds of developmental language disorder. Both SLI and dyslexic samples showed impaired discrimination of amplitude rise times. Implications of these findings for a temporal sampling framework for understanding developmental language disorders are discussed. PMID:27303348

Comparison of Scalar Expectancy Theory (SET) and the Learning-to-Time (LeT) model in a successive temporal bisection task.

PubMed

Arantes, Joana

2008-06-01

The present research tested the generality of the "context effect" previously reported in experiments using temporal double bisection tasks [e.g., Arantes, J., Machado, A. Context effects in a temporal discrimination task: Further tests of the Scalar Expectancy Theory and Learning-to-Time models. J. Exp. Anal. Behav., in press]. Pigeons learned two temporal discriminations in which all the stimuli appear successively: 1s (red) vs. 4s (green) and 4s (blue) vs. 16s (yellow). Then, two tests were conducted to compare predictions of two timing models, Scalar Expectancy Theory (SET) and the Learning-to-Time (LeT) model. In one test, two psychometric functions were obtained by presenting pigeons with intermediate signal durations (1-4s and 4-16s). Results were mixed. In the critical test, pigeons were exposed to signals ranging from 1 to 16s and followed by the green or the blue key. Whereas SET predicted that the relative response rate to each of these keys should be independent of the signal duration, LeT predicted that the relative response rate to the green key (compared with the blue key) should increase with the signal duration. Results were consistent with LeT's predictions, showing that the context effect is obtained even when subjects do not need to make a choice between two keys presented simultaneously.

Influence of temporal context on value in the multiple-chains and successive-encounters procedures.

PubMed

O'Daly, Matthew; Angulo, Samuel; Gipson, Cassandra; Fantino, Edmund

2006-05-01

This set of studies explored the influence of temporal context across multiple-chain and multiple-successive-encounters procedures. Following training with different temporal contexts, the value of stimuli sharing similar reinforcement schedules was assessed by presenting these stimuli in concurrent probes. The results for the multiple-chain schedule indicate that temporal context does impact the value of a conditioned reinforcer consistent with delay-reduction theory, such that a stimulus signaling a greater reduction in delay until reinforcement has greater value. Further, nonreinforced stimuli that are concurrently presented with the preferred terminal link also have greater value, consistent with value transfer. The effects of context on value for conditions with the multiple-successive-encounters procedure, however, appear to depend on whether the search schedule or alternate handling schedule was manipulated, as well as on whether the tested stimuli were the rich or lean schedules in their components. Overall, the results help delineate the conditions under which temporal context affects conditioned-reinforcement value (acting as a learning variable) and the conditions under which it does not (acting as a performance variable), an issue of relevance to theories of choice.

Dynamical genetic programming in XCSF.

PubMed

Preen, Richard J; Bull, Larry

2013-01-01

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to artificial neural networks. This paper presents results from an investigation into using a temporally dynamic symbolic representation within the XCSF learning classifier system. In particular, dynamical arithmetic networks are used to represent the traditional condition-action production system rules to solve continuous-valued reinforcement learning problems and to perform symbolic regression, finding competitive performance with traditional genetic programming on a number of composite polynomial tasks. In addition, the network outputs are later repeatedly sampled at varying temporal intervals to perform multistep-ahead predictions of a financial time series.

Hidden word learning capacity through orthography in aphasia.

PubMed

Tuomiranta, Leena M; Càmara, Estela; Froudist Walsh, Seán; Ripollés, Pablo; Saunavaara, Jani P; Parkkola, Riitta; Martin, Nadine; Rodríguez-Fornells, Antoni; Laine, Matti

2014-01-01

The ability to learn to use new words is thought to depend on the integrity of the left dorsal temporo-frontal speech processing pathway. We tested this assumption in a chronic aphasic individual (AA) with an extensive left temporal lesion using a new-word learning paradigm. She exhibited severe phonological problems and Magnetic Resonance Imaging (MRI) suggested a complete disconnection of this left-sided white-matter pathway comprising the arcuate fasciculus (AF). Diffusion imaging tractography confirmed the disconnection of the direct segment and the posterior indirect segment of her left AF, essential components of the left dorsal speech processing pathway. Despite her left-hemispheric damage and moderate aphasia, AA learned to name and maintain the novel words in her active vocabulary on par with healthy controls up to 6 months after learning. This exceeds previous demonstrations of word learning ability in aphasia. Interestingly, AA's preserved word learning ability was modality-specific as it was observed exclusively for written words. Functional magnetic resonance imaging (fMRI) revealed that in contrast to normals, AA showed a significantly right-lateralized activation pattern in the temporal and parietal regions when engaged in reading. Moreover, learning of visually presented novel word-picture pairs also activated the right temporal lobe in AA. Both AA and the controls showed increased activation during learning of novel versus familiar word-picture pairs in the hippocampus, an area critical for associative learning. AA's structural and functional imaging results suggest that in a literate person, a right-hemispheric network can provide an effective alternative route for learning of novel active vocabulary. Importantly, AA's previously undetected word learning ability translated directly into therapy, as she could use written input also to successfully re-learn and maintain familiar words that she had lost due to her left hemisphere lesion. Copyright © 2013 Elsevier Ltd. All rights reserved.

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…

Extraction of temporally correlated features from dynamic vision sensors with spike-timing-dependent plasticity.

PubMed

Bichler, Olivier; Querlioz, Damien; Thorpe, Simon J; Bourgoin, Jean-Philippe; Gamrat, Christian

2012-08-01

A biologically inspired approach to learning temporally correlated patterns from a spiking silicon retina is presented. Spikes are generated from the retina in response to relative changes in illumination at the pixel level and transmitted to a feed-forward spiking neural network. Neurons become sensitive to patterns of pixels with correlated activation times, in a fully unsupervised scheme. This is achieved using a special form of Spike-Timing-Dependent Plasticity which depresses synapses that did not recently contribute to the post-synaptic spike activation, regardless of their activation time. Competitive learning is implemented with lateral inhibition. When tested with real-life data, the system is able to extract complex and overlapping temporally correlated features such as car trajectories on a freeway, after only 10 min of traffic learning. Complete trajectories can be learned with a 98% detection rate using a second layer, still with unsupervised learning, and the system may be used as a car counter. The proposed neural network is extremely robust to noise and it can tolerate a high degree of synaptic and neuronal variability with little impact on performance. Such results show that a simple biologically inspired unsupervised learning scheme is capable of generating selectivity to complex meaningful events on the basis of relatively little sensory experience. Copyright © 2012 Elsevier Ltd. All rights reserved.

Statistical learning of multisensory regularities is enhanced in musicians: An MEG study.

PubMed

Paraskevopoulos, Evangelos; Chalas, Nikolas; Kartsidis, Panagiotis; Wollbrink, Andreas; Bamidis, Panagiotis

2018-07-15

The present study used magnetoencephalography (MEG) to identify the neural correlates of audiovisual statistical learning, while disentangling the differential contributions of uni- and multi-modal statistical mismatch responses in humans. The applied paradigm was based on a combination of a statistical learning paradigm and a multisensory oddball one, combining an audiovisual, an auditory and a visual stimulation stream, along with the corresponding deviances. Plasticity effects due to musical expertise were investigated by comparing the behavioral and MEG responses of musicians to non-musicians. The behavioral results indicated that the learning was successful for both musicians and non-musicians. The unimodal MEG responses are consistent with previous studies, revealing the contribution of Heschl's gyrus for the identification of auditory statistical mismatches and the contribution of medial temporal and visual association areas for the visual modality. The cortical network underlying audiovisual statistical learning was found to be partly common and partly distinct from the corresponding unimodal networks, comprising right temporal and left inferior frontal sources. Musicians showed enhanced activation in superior temporal and superior frontal gyrus. Connectivity and information processing flow amongst the sources comprising the cortical network of audiovisual statistical learning, as estimated by transfer entropy, was reorganized in musicians, indicating enhanced top-down processing. This neuroplastic effect showed a cross-modal stability between the auditory and audiovisual modalities. Copyright © 2018 Elsevier Inc. All rights reserved.

Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning.

PubMed

Kia, Seyed Mostafa; Pedregosa, Fabian; Blumenthal, Anna; Passerini, Andrea

2017-06-15

The use of machine learning models to discriminate between patterns of neural activity has become in recent years a standard analysis approach in neuroimaging studies. Whenever these models are linear, the estimated parameters can be visualized in the form of brain maps which can aid in understanding how brain activity in space and time underlies a cognitive function. However, the recovered brain maps often suffer from lack of interpretability, especially in group analysis of multi-subject data. To facilitate the application of brain decoding in group-level analysis, we present an application of multi-task joint feature learning for group-level multivariate pattern recovery in single-trial magnetoencephalography (MEG) decoding. The proposed method allows for recovering sparse yet consistent patterns across different subjects, and therefore enhances the interpretability of the decoding model. Our experimental results demonstrate that the mutli-task joint feature learning framework is capable of recovering more meaningful patterns of varying spatio-temporally distributed brain activity across individuals while still maintaining excellent generalization performance. We compare the performance of the multi-task joint feature learning in terms of generalization, reproducibility, and quality of pattern recovery against traditional single-subject and pooling approaches on both simulated and real MEG datasets. These results can facilitate the usage of brain decoding for the characterization of fine-level distinctive patterns in group-level inference. Considering the importance of group-level analysis, the proposed approach can provide a methodological shift towards more interpretable brain decoding models. Copyright © 2017 Elsevier B.V. All rights reserved.

Compressive sensing of electrocardiogram signals by promoting sparsity on the second-order difference and by using dictionary learning.

PubMed

Pant, Jeevan K; Krishnan, Sridhar

2014-04-01

A new algorithm for the reconstruction of electrocardiogram (ECG) signals and a dictionary learning algorithm for the enhancement of its reconstruction performance for a class of signals are proposed. The signal reconstruction algorithm is based on minimizing the lp pseudo-norm of the second-order difference, called as the lp(2d) pseudo-norm, of the signal. The optimization involved is carried out using a sequential conjugate-gradient algorithm. The dictionary learning algorithm uses an iterative procedure wherein a signal reconstruction and a dictionary update steps are repeated until a convergence criterion is satisfied. The signal reconstruction step is implemented by using the proposed signal reconstruction algorithm and the dictionary update step is implemented by using the linear least-squares method. Extensive simulation results demonstrate that the proposed algorithm yields improved reconstruction performance for temporally correlated ECG signals relative to the state-of-the-art lp(1d)-regularized least-squares and Bayesian learning based algorithms. Also for a known class of signals, the reconstruction performance of the proposed algorithm can be improved by applying it in conjunction with a dictionary obtained using the proposed dictionary learning algorithm.

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.

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

Novelty and Inductive Generalization in Human Reinforcement Learning.

PubMed

Gershman, Samuel J; Niv, Yael

2015-07-01

In reinforcement learning (RL), a decision maker searching for the most rewarding option is often faced with the question: What is the value of an option that has never been tried before? One way to frame this question is as an inductive problem: How can I generalize my previous experience with one set of options to a novel option? We show how hierarchical Bayesian inference can be used to solve this problem, and we describe an equivalence between the Bayesian model and temporal difference learning algorithms that have been proposed as models of RL in humans and animals. According to our view, the search for the best option is guided by abstract knowledge about the relationships between different options in an environment, resulting in greater search efficiency compared to traditional RL algorithms previously applied to human cognition. In two behavioral experiments, we test several predictions of our model, providing evidence that humans learn and exploit structured inductive knowledge to make predictions about novel options. In light of this model, we suggest a new interpretation of dopaminergic responses to novelty. Copyright © 2015 Cognitive Science Society, Inc.

Fuzzy Sarsa with Focussed Replacing Eligibility Traces for Robust and Accurate Control

NASA Astrophysics Data System (ADS)

Kamdem, Sylvain; Ohki, Hidehiro; Sueda, Naomichi

Several methods of reinforcement learning in continuous state and action spaces that utilize fuzzy logic have been proposed in recent years. This paper introduces Fuzzy Sarsa(λ), an on-policy algorithm for fuzzy learning that relies on a novel way of computing replacing eligibility traces to accelerate the policy evaluation. It is tested against several temporal difference learning algorithms: Sarsa(λ), Fuzzy Q(λ), an earlier fuzzy version of Sarsa and an actor-critic algorithm. We perform detailed evaluations on two benchmark problems : a maze domain and the cart pole. Results of various tests highlight the strengths and weaknesses of these algorithms and show that Fuzzy Sarsa(λ) outperforms all other algorithms tested for a larger granularity of design and under noisy conditions. It is a highly competitive method of learning in realistic noisy domains where a denser fuzzy design over the state space is needed for a more precise control.

Self-Paced Prioritized Curriculum Learning With Coverage Penalty in Deep Reinforcement Learning.

PubMed

Ren, Zhipeng; Dong, Daoyi; Li, Huaxiong; Chen, Chunlin; Zhipeng Ren; Daoyi Dong; Huaxiong Li; Chunlin Chen; Dong, Daoyi; Li, Huaxiong; Chen, Chunlin; Ren, Zhipeng

2018-06-01

In this paper, a new training paradigm is proposed for deep reinforcement learning using self-paced prioritized curriculum learning with coverage penalty. The proposed deep curriculum reinforcement learning (DCRL) takes the most advantage of experience replay by adaptively selecting appropriate transitions from replay memory based on the complexity of each transition. The criteria of complexity in DCRL consist of self-paced priority as well as coverage penalty. The self-paced priority reflects the relationship between the temporal-difference error and the difficulty of the current curriculum for sample efficiency. The coverage penalty is taken into account for sample diversity. With comparison to deep Q network (DQN) and prioritized experience replay (PER) methods, the DCRL algorithm is evaluated on Atari 2600 games, and the experimental results show that DCRL outperforms DQN and PER on most of these games. More results further show that the proposed curriculum training paradigm of DCRL is also applicable and effective for other memory-based deep reinforcement learning approaches, such as double DQN and dueling network. All the experimental results demonstrate that DCRL can achieve improved training efficiency and robustness for deep reinforcement learning.

Dealing with delays does not transfer across sensorimotor tasks.

PubMed

de la Malla, Cristina; López-Moliner, Joan; Brenner, Eli

2014-10-09

It is known that people can learn to deal with delays between their actions and the consequences of such actions. We wondered whether they do so by adjusting their anticipations about the sensory consequences of their actions or whether they simply learn to move in certain ways when performing specific tasks. To find out, we examined details of how people learn to intercept a moving target with a cursor that follows the hand with a delay and examined the transfer of learning between this task and various other tasks that require temporal precision. Subjects readily learned to intercept the moving target with the delayed cursor. The compensation for the delay generalized across modifications of the task, so subjects did not simply learn to move in a certain way in specific circumstances. The compensation did not generalize to completely different timing tasks, so subjects did not generally expect the consequences of their motor commands to be delayed. We conclude that people specifically learn to control the delayed visual consequences of their actions to perform certain tasks. © 2014 ARVO.

Clipping in neurocontrol by adaptive dynamic programming.

PubMed

Fairbank, Michael; Prokhorov, Danil; Alonso, Eduardo

2014-10-01

In adaptive dynamic programming, neurocontrol, and reinforcement learning, the objective is for an agent to learn to choose actions so as to minimize a total cost function. In this paper, we show that when discretized time is used to model the motion of the agent, it can be very important to do clipping on the motion of the agent in the final time step of the trajectory. By clipping, we mean that the final time step of the trajectory is to be truncated such that the agent stops exactly at the first terminal state reached, and no distance further. We demonstrate that when clipping is omitted, learning performance can fail to reach the optimum, and when clipping is done properly, learning performance can improve significantly. The clipping problem we describe affects algorithms that use explicit derivatives of the model functions of the environment to calculate a learning gradient. These include backpropagation through time for control and methods based on dual heuristic programming. However, the clipping problem does not significantly affect methods based on heuristic dynamic programming, temporal differences learning, or policy-gradient learning algorithms.

The effect of encoding strategy on the neural correlates of memory for faces.

PubMed

Bernstein, Lori J; Beig, Sania; Siegenthaler, Amy L; Grady, Cheryl L

2002-01-01

Encoding and recognition of unfamiliar faces in young adults were examined using positron emission tomography to determine whether different encoding strategies would lead to encoding/retrieval differences in brain activity. Three types of encoding were compared: a 'deep' task (judging pleasantness/unpleasantness), a 'shallow' task (judging right/left orientation), and an intentional learning task in which subjects were instructed to learn the faces for a subsequent memory test but were not provided with a specific strategy. Memory for all faces was tested with an old/new recognition test. A modest behavioral effect was obtained, with deeply-encoded faces being recognized more accurately than shallowly-encoded or intentionally-learned faces. Regardless of encoding strategy, encoding activated a primarily ventral system including bilateral temporal and fusiform regions and left prefrontal cortices, whereas recognition activated a primarily dorsal set of regions including right prefrontal and parietal areas. Within encoding, the type of strategy produced different brain activity patterns, with deep encoding being characterized by left amygdala and left anterior cingulate activation. There was no effect of encoding strategy on brain activity during the recognition conditions. Posterior fusiform gyrus activation was related to better recognition accuracy in those conditions encouraging perceptual strategies, whereas activity in left frontal and temporal areas correlated with better performance during the 'deep' condition. Results highlight three important aspects of face memory: (1) the effect of encoding strategy was seen only at encoding and not at recognition; (2) left inferior prefrontal cortex was engaged during encoding of faces regardless of strategy; and (3) differential activity in fusiform gyrus was found, suggesting that activity in this area is not only a result of automatic face processing but is modulated by controlled processes.

Age of second language acquisition in multilinguals has an impact on gray matter volume in language-associated brain areas.

PubMed

Kaiser, Anelis; Eppenberger, Leila S; Smieskova, Renata; Borgwardt, Stefan; Kuenzli, Esther; Radue, Ernst-Wilhelm; Nitsch, Cordula; Bendfeldt, Kerstin

2015-01-01

Numerous structural studies have established that experience shapes and reshapes the brain throughout a lifetime. The impact of early development, however, is still a matter of debate. Further clues may come from studying multilinguals who acquired their second language at different ages. We investigated adult multilinguals who spoke three languages fluently, where the third language was learned in classroom settings, not before the age of 9 years. Multilinguals exposed to two languages simultaneously from birth (SiM) were contrasted with multinguals who acquired their first two languages successively (SuM). Whole brain voxel based morphometry revealed that, relative to SuM, SiM have significantly lower gray matter volume in several language-associated cortical areas in both hemispheres: bilaterally in medial and inferior frontal gyrus, in the right medial temporal gyrus and inferior posterior parietal gyrus, as well as in the left inferior temporal gyrus. Thus, as shown by others, successive language learning increases the volume of language-associated cortical areas. In brains exposed early on and simultaneously to more than one language, however, learning of additional languages seems to have less impact. We conclude that - at least with respect to language acquisition - early developmental influences are maintained and have an effect on experience-dependent plasticity well into adulthood.

Neural activation during imitation with or without performance feedback: An fMRI study.

PubMed

Zhang, Kaihua; Wang, Hui; Dong, Guangheng; Wang, Mengxing; Zhang, Jilei; Zhang, Hui; Meng, Weixia; Du, Xiaoxia

2016-08-26

In our daily lives, we often receive performance feedback (PF) during imitative learning, and we adjust our behaviors accordingly to improve performance. However, little is known regarding the neural mechanisms underlying this learning process. We hypothesized that appropriate PF would enhance neural activation or recruit additional brain areas during subsequent action imitation. Pictures of 20 different finger gestures without any social meaning were shown to participants from the first-person perspective. Imitation with or without PF was investigated by functional magnetic resonance imaging in 30 healthy subjects. The PF was given by a real person or by a computer. PF from a real person induced hyperactivation of the parietal lobe (precuneus and cuneus), cingulate cortex (posterior and anterior), temporal lobe (superior and transverse temporal gyri), and cerebellum (posterior and anterior lobes) during subsequent imitation. The positive PF and negative PF from a real person, induced the activation of more brain areas during the following imitation. The hyperactivation of the cerebellum, posterior cingulate cortex, precuneus, and cuneus suggests that the subjects exhibited enhanced motor control and visual attention during imitation after PF. Additionally, random PF from a computer had a small effect on the next imitation. We suggest that positive and accurate PF may be helpful for imitation learning. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A Measurement Model of Gestures in an Embodied Learning Environment: Accounting for Temporal Dependencies

ERIC Educational Resources Information Center

Andrade, Alejandro; Danish, Joshua A.; Maltese, Adam V.

2017-01-01

Interactive learning environments with body-centric technologies lie at the intersection of the design of embodied learning activities and multimodal learning analytics. Sensing technologies can generate large amounts of fine-grained data automatically captured from student movements. Researchers can use these fine-grained data to create a…

Temporal Patterns and Dynamics of E-Learning Usage in Medical Education

ERIC Educational Resources Information Center

Panzarasa, Pietro; Kujawski, Bernard; Hammond, Edward J.; Roberts, C. Michael

2016-01-01

Despite the increasing popularity of e-learning systems across a variety of educational programmes, there is relatively little understanding of how students and trainees distribute their learning efforts over time. This study aimed to analyse the usage patterns of an e-learning resource designed to support specialty training. Data were collected…

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

Should I trust you? Learning and memory of social interactions in dementia.

PubMed

Wong, Stephanie; Irish, Muireann; O'Callaghan, Claire; Kumfor, Fiona; Savage, Greg; Hodges, John R; Piguet, Olivier; Hornberger, Michael

2017-09-01

Social relevance has an enhancing effect on learning and subsequent memory retrieval. The ability to learn from and remember social interactions may impact on susceptibility to financial exploitation, which is elevated in individuals with dementia. The current study aimed to investigate learning and memory of social interactions, the relationship between performance and financial vulnerability and the neural substrates underpinning performance in 14 Alzheimer's disease (AD) and 20 behavioural-variant frontotemporal dementia (bvFTD) patients and 20 age-matched healthy controls. On a "trust game" task, participants invested virtual money with counterparts who acted either in a trustworthy or untrustworthy manner over repeated interactions. A non-social "lottery" condition was also included. Participants' learning of trust/distrust responses and subsequent memory for the counterparts and nature of the interactions was assessed. Carer-rated profiles of financial vulnerability were also collected. Relative to controls, both patient groups showed attenuated learning of trust/distrust responses, and lower overall memory for social interactions. Despite poor learning performance, both AD and bvFTD patients showed better memory of social compared to non-social interactions. Importantly, better memory for social interactions was associated with lower financial vulnerability in AD, but not bvFTD. Learning and memory of social interactions was associated with medial temporal and temporoparietal atrophy in AD, whereas a wider network of frontostriatal, insular, fusiform and medial temporal regions was implicated in bvFTD. Our findings suggest that although social relevance influences memory to an extent in both AD and bvFTD, this is associated with vulnerability to financial exploitation in AD only, and is underpinned by changes to different neural substrates. Theoretically, these findings provide novel insights into potential mechanisms that give rise to vulnerability in people with dementia, and open avenues for possible interventions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Anodal transcranial direct current stimulation over the primary motor cortex does not enhance the learning benefits of self-controlled feedback schedules.

PubMed

Carter, Michael J; Smith, Victoria; Carlsen, Anthony N; Ste-Marie, Diane M

2018-05-01

A distinct learning advantage has been shown when participants control their knowledge of results (KR) scheduling during practice compared to when the same KR schedule is imposed on the learner without choice (i.e., yoked schedules). Although the learning advantages of self-controlled KR schedules are well-documented, the brain regions contributing to these advantages remain unknown. Identifying key brain regions would not only advance our theoretical understanding of the mechanisms underlying self-controlled learning advantages, but would also highlight regions that could be targeted in more applied settings to boost the already beneficial effects of self-controlled KR schedules. Here, we investigated whether applying anodal transcranial direct current stimulation (tDCS) to the primary motor cortex (M1) would enhance the typically found benefits of learning a novel motor skill with a self-controlled KR schedule. Participants practiced a spatiotemporal task in one of four groups using a factorial combination of KR schedule (self-controlled vs. yoked) and tDCS (anodal vs. sham). Testing occurred on two consecutive days with spatial and temporal accuracy measured on both days and learning was assessed using 24-h retention and transfer tests without KR. All groups improved their performance in practice and a significant effect for practicing with a self-controlled KR schedule compared to a yoked schedule was found for temporal accuracy in transfer, but a similar advantage was not evident in retention. There were no significant differences as a function of KR schedule or tDCS for spatial accuracy in retention or transfer. The lack of a significant tDCS effect suggests that M1 may not strongly contribute to self-controlled KR learning advantages; however, caution is advised with this interpretation as typical self-controlled learning benefits were not strongly replicated in the present experiment.

Dictionary learning and time sparsity in dynamic MRI.

PubMed

Caballero, Jose; Rueckert, Daniel; Hajnal, Joseph V

2012-01-01

Sparse representation methods have been shown to tackle adequately the inherent speed limits of magnetic resonance imaging (MRI) acquisition. Recently, learning-based techniques have been used to further accelerate the acquisition of 2D MRI. The extension of such algorithms to dynamic MRI (dMRI) requires careful examination of the signal sparsity distribution among the different dimensions of the data. Notably, the potential of temporal gradient (TG) sparsity in dMRI has not yet been explored. In this paper, a novel method for the acceleration of cardiac dMRI is presented which investigates the potential benefits of enforcing sparsity constraints on patch-based learned dictionaries and TG at the same time. We show that an algorithm exploiting sparsity on these two domains can outperform previous sparse reconstruction techniques.

An fMRI investigation of the fronto-striatal learning system in women who exhibit eating disorder behaviors

PubMed Central

Celone, Kim A.; Thompson-Brenner, Heather; Ross, Robert S.; Pratt, Elizabeth M.; Stern, Chantal E.

2013-01-01

In the present study, we sought to examine whether the fronto-striatal learning system, which has been implicated in bulimia nervosa, would demonstrate altered BOLD activity during probabilistic category learning in women who met subthreshold criteria for bulimia nervosa (Sub-BN). Sub-BN, which falls within the clinical category of Eating Disorder Not Otherwise Specified (EDNOS), is comprised of individuals who demonstrate recurrent binge eating, efforts to minimize their caloric intake and caloric retention, and elevated levels of concern about shape, weight, and/or eating, but just fail to meet the diagnostic threshold for bulimia nervosa (BN). fMRI data were collected from eighteen women with subthreshold-BN (Sub-BN) and nineteen healthy control women group-matched for age, education and body mass index (MC) during the weather prediction task. Sub-BN participants demonstrated increased caudate nucleus and dorsolateral prefrontal cortex (DLPFC) activation during the learning of probabilistic categories. Though the two subject groups did not differ in behavioral performance, over the course of learning, Sub-BN participants showed a dynamic pattern of brain activity differences when compared to matched control participants. Regions implicated in episodic memory, including the medial temporal lobe (MTL), retrosplenial cortex, middle frontal gyrus, and anterior and posterior cingulate cortex showed decreased activity in the Sub-BN participants compared to MCs during early learning which was followed by increased involvement of the DLPFC during later learning. These findings demonstrate that women with Sub-BN demonstrate differences in fronto-striatal learning system activity, as well as a distinct functional pattern between fronto-striatal and MTL learning systems during the course of implicit probabilistic category learning. PMID:21419229

Auditory Magnetoencephalographic Frequency-Tagged Responses Mirror the Ongoing Segmentation Processes Underlying Statistical Learning.

PubMed

Farthouat, Juliane; Franco, Ana; Mary, Alison; Delpouve, Julie; Wens, Vincent; Op de Beeck, Marc; De Tiège, Xavier; Peigneux, Philippe

2017-03-01

Humans are highly sensitive to statistical regularities in their environment. This phenomenon, usually referred as statistical learning, is most often assessed using post-learning behavioural measures that are limited by a lack of sensibility and do not monitor the temporal dynamics of learning. In the present study, we used magnetoencephalographic frequency-tagged responses to investigate the neural sources and temporal development of the ongoing brain activity that supports the detection of regularities embedded in auditory streams. Participants passively listened to statistical streams in which tones were grouped as triplets, and to random streams in which tones were randomly presented. Results show that during exposure to statistical (vs. random) streams, tritone frequency-related responses reflecting the learning of regularities embedded in the stream increased in the left supplementary motor area and left posterior superior temporal sulcus (pSTS), whereas tone frequency-related responses decreased in the right angular gyrus and right pSTS. Tritone frequency-related responses rapidly developed to reach significance after 3 min of exposure. These results suggest that the incidental extraction of novel regularities is subtended by a gradual shift from rhythmic activity reflecting individual tone succession toward rhythmic activity synchronised with triplet presentation, and that these rhythmic processes are subtended by distinct neural sources.

Personal semantic memory: insights from neuropsychological research on amnesia.

PubMed

Grilli, Matthew D; Verfaellie, Mieke

2014-08-01

This paper provides insight into the cognitive and neural mechanisms of personal semantic memory, knowledge that is specific and unique to individuals, by reviewing neuropsychological research on stable amnesia secondary to medial temporal lobe damage. The results reveal that personal semantic memory does not depend on a unitary set of cognitive and neural mechanisms. Findings show that autobiographical fact knowledge reflects an experience-near type of personal semantic memory that relies on the medial temporal lobe for retrieval, albeit less so than personal episodic memory. Additional evidence demonstrates that new autobiographical fact learning likely relies on the medial temporal lobe, but the extent to which remains unclear. Other findings show that retrieval of personal traits/roles and new learning of personal traits/roles and thoughts/beliefs are independent of the medial temporal lobe and thus may represent highly conceptual types of personal semantic memory that are stored in the neocortex. Published by Elsevier Ltd.

Learning a trajectory using adjoint functions and teacher forcing

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad B.; Barhen, Jacob

1992-01-01

A new methodology for faster supervised temporal learning in nonlinear neural networks is presented which builds upon the concept of adjoint operators to allow fast computation of the gradients of an error functional with respect to all parameters of the neural architecture, and exploits the concept of teacher forcing to incorporate information on the desired output into the activation dynamics. The importance of the initial or final time conditions for the adjoint equations is discussed. A new algorithm is presented in which the adjoint equations are solved simultaneously (i.e., forward in time) with the activation dynamics of the neural network. We also indicate how teacher forcing can be modulated in time as learning proceeds. The results obtained show that the learning time is reduced by one to two orders of magnitude with respect to previously published results, while trajectory tracking is significantly improved. The proposed methodology makes hardware implementation of temporal learning attractive for real-time applications.

The neural circuit basis of learning

NASA Astrophysics Data System (ADS)

Patrick, Kaifosh William John

The astounding capacity for learning ranks among the nervous system's most impressive features. This thesis comprises studies employing varied approaches to improve understanding, at the level of neural circuits, of the brain's capacity for learning. The first part of the thesis contains investigations of hippocampal circuitry -- both theoretical work and experimental work in the mouse Mus musculus -- as a model system for declarative memory. To begin, Chapter 2 presents a theory of hippocampal memory storage and retrieval that reflects nonlinear dendritic processing within hippocampal pyramidal neurons. As a prelude to the experimental work that comprises the remainder of this part, Chapter 3 describes an open source software platform that we have developed for analysis of data acquired with in vivo Ca2+ imaging, the main experimental technique used throughout the remainder of this part of the thesis. As a first application of this technique, Chapter 4 characterizes the content of signaling at synapses between GABAergic neurons of the medial septum and interneurons in stratum oriens of hippocampal area CA1. Chapter 5 then combines these techniques with optogenetic, pharmacogenetic, and pharmacological manipulations to uncover inhibitory circuit mechanisms underlying fear learning. The second part of this thesis focuses on the cerebellum-like electrosensory lobe in the weakly electric mormyrid fish Gnathonemus petersii, as a model system for non-declarative memory. In Chapter 6, we study how short-duration EOD motor commands are recoded into a complex temporal basis in the granule cell layer, which can be used to cancel Purkinje-like cell firing to the longer duration and temporally varying EOD-driven sensory responses. In Chapter 7, we consider not only the temporal aspects of the granule cell code, but also the encoding of body position provided from proprioceptive and efference copy sources. Together these studies clarify how the cerebellum-like circuitry of the electrosensory lobe combines information of different forms and then uses this combined information to predict the complex dependence of sensory responses on body position and timing relative to electric organ discharge.

The role of the basal ganglia in learning and memory: Insight from Parkinson's disease

PubMed Central

2013-01-01

It has long been known that memory is not a single process. Rather, there are different kinds of memory that are supported by distinct neural systems. This idea stemmed from early findings of dissociable patterns of memory impairments in patients with selective damage to different brain regions. These studies highlighted the role of the basal ganglia in non-declarative memory, such as procedural or habit learning, contrasting it with the known role of the medial temporal lobes in declarative memory. In recent years, major advances across multiple areas of neuroscience have revealed an important role for the basal ganglia in motivation and decision making. These findings have led to new discoveries about the role of the basal ganglia in learning and highlighted the essential role of dopamine in specific forms of learning. Here we review these recent advances with an emphasis on novel discoveries from studies of learning in patients with Parkinson's disease. We discuss how these findings promote the development of current theories away from accounts that emphasize the verbalizability of the contents of memory and towards a focus on the specific computations carried out by distinct brain regions. Finally, we discuss new challenges that arise in the face of accumulating evidence for dynamic and interconnected memory systems that jointly contribute to learning. PMID:21945835

A Novel Connectionist Network for Solving Long Time-Lag Prediction Tasks

NASA Astrophysics Data System (ADS)

Johnson, Keith; MacNish, Cara

Traditional Recurrent Neural Networks (RNNs) perform poorly on learning tasks involving long time-lag dependencies. More recent approaches such as LSTM and its variants significantly improve on RNNs ability to learn this type of problem. We present an alternative approach to encoding temporal dependencies that associates temporal features with nodes rather than state values, where the nodes explicitly encode dependencies over variable time delays. We show promising results comparing the network's performance to LSTM variants on an extended Reber grammar task.

Nature vs Nurture: Effects of Learning on Evolution

NASA Astrophysics Data System (ADS)

Nagrani, Nagina

In the field of Evolutionary Robotics, the design, development and application of artificial neural networks as controllers have derived their inspiration from biology. Biologists and artificial intelligence researchers are trying to understand the effects of neural network learning during the lifetime of the individuals on evolution of these individuals by qualitative and quantitative analyses. The conclusion of these analyses can help develop optimized artificial neural networks to perform any given task. The purpose of this thesis is to study the effects of learning on evolution. This has been done by applying Temporal Difference Reinforcement Learning methods to the evolution of Artificial Neural Tissue controller. The controller has been assigned the task to collect resources in a designated area in a simulated environment. The performance of the individuals is measured by the amount of resources collected. A comparison has been made between the results obtained by incorporating learning in evolution and evolution alone. The effects of learning parameters: learning rate, training period, discount rate, and policy on evolution have also been studied. It was observed that learning delays the performance of the evolving individuals over the generations. However, the non zero learning rate throughout the evolution process signifies natural selection preferring individuals possessing plasticity.

Multichannel microformulators for massively parallel machine learning and automated design of biological experiments

NASA Astrophysics Data System (ADS)

Wikswo, John; Kolli, Aditya; Shankaran, Harish; Wagoner, Matthew; Mettetal, Jerome; Reiserer, Ronald; Gerken, Gregory; Britt, Clayton; Schaffer, David

Genetic, proteomic, and metabolic networks describing biological signaling can have 102 to 103 nodes. Transcriptomics and mass spectrometry can quantify 104 different dynamical experimental variables recorded from in vitro experiments with a time resolution approaching 1 s. It is difficult to infer metabolic and signaling models from such massive data sets, and it is unlikely that causality can be determined simply from observed temporal correlations. There is a need to design and apply specific system perturbations, which will be difficult to perform manually with 10 to 102 externally controlled variables. Machine learning and optimal experimental design can select an experiment that best discriminates between multiple conflicting models, but a remaining problem is to control in real time multiple variables in the form of concentrations of growth factors, toxins, nutrients and other signaling molecules. With time-division multiplexing, a microfluidic MicroFormulator (μF) can create in real time complex mixtures of reagents in volumes suitable for biological experiments. Initial 96-channel μF implementations control the exposure profile of cells in a 96-well plate to different temporal profiles of drugs; future experiments will include challenge compounds. Funded in part by AstraZeneca, NIH/NCATS HHSN271201600009C and UH3TR000491, and VIIBRE.

Learning to Recognize Actions From Limited Training Examples Using a Recurrent Spiking Neural Model

PubMed Central

Panda, Priyadarshini; Srinivasa, Narayan

2018-01-01

A fundamental challenge in machine learning today is to build a model that can learn from few examples. Here, we describe a reservoir based spiking neural model for learning to recognize actions with a limited number of labeled videos. First, we propose a novel encoding, inspired by how microsaccades influence visual perception, to extract spike information from raw video data while preserving the temporal correlation across different frames. Using this encoding, we show that the reservoir generalizes its rich dynamical activity toward signature action/movements enabling it to learn from few training examples. We evaluate our approach on the UCF-101 dataset. Our experiments demonstrate that our proposed reservoir achieves 81.3/87% Top-1/Top-5 accuracy, respectively, on the 101-class data while requiring just 8 video examples per class for training. Our results establish a new benchmark for action recognition from limited video examples for spiking neural models while yielding competitive accuracy with respect to state-of-the-art non-spiking neural models. PMID:29551962

Gaussian process based independent analysis for temporal source separation in fMRI.

PubMed

Hald, Ditte Høvenhoff; Henao, Ricardo; Winther, Ole

2017-05-15

Functional Magnetic Resonance Imaging (fMRI) gives us a unique insight into the processes of the brain, and opens up for analyzing the functional activation patterns of the underlying sources. Task-inferred supervised learning with restrictive assumptions in the regression set-up, restricts the exploratory nature of the analysis. Fully unsupervised independent component analysis (ICA) algorithms, on the other hand, can struggle to detect clear classifiable components on single-subject data. We attribute this shortcoming to inadequate modeling of the fMRI source signals by failing to incorporate its temporal nature. fMRI source signals, biological stimuli and non-stimuli-related artifacts are all smooth over a time-scale compatible with the sampling time (TR). We therefore propose Gaussian process ICA (GPICA), which facilitates temporal dependency by the use of Gaussian process source priors. On two fMRI data sets with different sampling frequency, we show that the GPICA-inferred temporal components and associated spatial maps allow for a more definite interpretation than standard temporal ICA methods. The temporal structures of the sources are controlled by the covariance of the Gaussian process, specified by a kernel function with an interpretable and controllable temporal length scale parameter. We propose a hierarchical model specification, considering both instantaneous and convolutive mixing, and we infer source spatial maps, temporal patterns and temporal length scale parameters by Markov Chain Monte Carlo. A companion implementation made as a plug-in for SPM can be downloaded from https://github.com/dittehald/GPICA. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Fast adaptation of the internal model of gravity for manual interceptions: evidence for event-dependent learning.

PubMed

Zago, Myrka; Bosco, Gianfranco; Maffei, Vincenzo; Iosa, Marco; Ivanenko, Yuri P; Lacquaniti, Francesco

2005-02-01

We studied how subjects learn to deal with two conflicting sensory environments as a function of the probability of each environment and the temporal distance between repeated events. Subjects were asked to intercept a visual target moving downward on a screen with randomized laws of motion. We compared five protocols that differed in the probability of constant speed (0g) targets and accelerated (1g) targets. Probability ranged from 9 to 100%, and the time interval between consecutive repetitions of the same target ranged from about 1 to 20 min. We found that subjects systematically timed their responses consistent with the assumption of gravity effects, for both 1 and 0g trials. With training, subjects rapidly adapted to 0g targets by shifting the time of motor activation. Surprisingly, the adaptation rate was independent of both the probability of 0g targets and their temporal distance. Very few 0g trials sporadically interspersed as catch trials during immersive practice with 1g trials were sufficient for learning and consolidation in long-term memory, as verified by retesting after 24 h. We argue that the memory store for adapted states of the internal gravity model is triggered by individual events and can be sustained for prolonged periods of time separating sporadic repetitions. This form of event-related learning could depend on multiple-stage memory, with exponential rise and decay in the initial stages followed by a sample-and-hold module.

Modelling the effect of religion on human empathy based on an adaptive temporal-causal network model.

PubMed

van Ments, Laila; Roelofsma, Peter; Treur, Jan

2018-01-01

Religion is a central aspect of many individuals' lives around the world, and its influence on human behaviour has been extensively studied from many different perspectives. The current study integrates a number of these perspectives into one adaptive temporal-causal network model describing the mental states involved, their mutual relations, and the adaptation of some of these relations over time due to learning. By first developing a conceptual representation of a network model based on the literature, and then formalizing this model into a numerical representation, simulations can be done for almost any kind of religion and person, showing different behaviours for persons with different religious backgrounds and characters. The focus was mainly on the influence of religion on human empathy and dis-empathy, a topic very relevant today. The developed model could be valuable for many uses, involving support for a better understanding, and even prediction, of the behaviour of religious individuals. It is illustrated for a number of different scenarios based on different characteristics of the persons and of the religion.

Spatiotemporal Thinking in the Geosciences

NASA Astrophysics Data System (ADS)

Shipley, T. F.; Manduca, C. A.; Ormand, C. J.; Tikoff, B.

2011-12-01

Reasoning about spatial relations is a critical skill for geoscientists. Within the geosciences different disciplines may reason about different sorts of relationships. These relationships may span vastly different spatial and temporal scales (from the spatial alignment in atoms in crystals to the changes in the shape of plates). As part of work in a research center on spatial thinking in STEM education, we have been working to classify the spatial skills required in geology, develop tests for each spatial skill, and develop the cognitive science tools to promote the critical spatial reasoning skills. Research in psychology, neurology and linguistics supports a broad classification of spatial skills along two dimensions: one versus many objects (which roughly translates to object- focused and navigation focused skills) and static versus dynamic spatial relations. The talk will focus on the interaction of space and time in spatial cognition in the geosciences. We are working to develop measures of skill in visualizing spatiotemporal changes. A new test developed to measure visualization of brittle deformations will be presented. This is a skill that has not been clearly recognized in the cognitive science research domain and thus illustrates the value of interdisciplinary work that combines geosciences with cognitive sciences. Teaching spatiotemporal concepts can be challenging. Recent theoretical work suggests analogical reasoning can be a powerful tool to aid student learning to reason about temporal relations using spatial skills. Recent work in our lab has found that progressive alignment of spatial and temporal scales promotes accurate reasoning about temporal relations at geological time scales.

Space-TimeScapes as Ecopedagogy

ERIC Educational Resources Information Center

Dunkley, Ria Ann

2018-01-01

This emergent field of ecopedagogy gives little conceptual, methodological, and empirical consideration to the significance of spatial and temporal elements of environmental learning. This article focuses on both spatial and temporal components of three ecopedagogic instances, examining experiences from participant's perspective. Specific…

Principal component reconstruction (PCR) for cine CBCT with motion learning from 2D fluoroscopy.

PubMed

Gao, Hao; Zhang, Yawei; Ren, Lei; Yin, Fang-Fang

2018-01-01

This work aims to generate cine CT images (i.e., 4D images with high-temporal resolution) based on a novel principal component reconstruction (PCR) technique with motion learning from 2D fluoroscopic training images. In the proposed PCR method, the matrix factorization is utilized as an explicit low-rank regularization of 4D images that are represented as a product of spatial principal components and temporal motion coefficients. The key hypothesis of PCR is that temporal coefficients from 4D images can be reasonably approximated by temporal coefficients learned from 2D fluoroscopic training projections. For this purpose, we can acquire fluoroscopic training projections for a few breathing periods at fixed gantry angles that are free from geometric distortion due to gantry rotation, that is, fluoroscopy-based motion learning. Such training projections can provide an effective characterization of the breathing motion. The temporal coefficients can be extracted from these training projections and used as priors for PCR, even though principal components from training projections are certainly not the same for these 4D images to be reconstructed. For this purpose, training data are synchronized with reconstruction data using identical real-time breathing position intervals for projection binning. In terms of image reconstruction, with a priori temporal coefficients, the data fidelity for PCR changes from nonlinear to linear, and consequently, the PCR method is robust and can be solved efficiently. PCR is formulated as a convex optimization problem with the sum of linear data fidelity with respect to spatial principal components and spatiotemporal total variation regularization imposed on 4D image phases. The solution algorithm of PCR is developed based on alternating direction method of multipliers. The implementation is fully parallelized on GPU with NVIDIA CUDA toolbox and each reconstruction takes about a few minutes. The proposed PCR method is validated and compared with a state-of-art method, that is, PICCS, using both simulation and experimental data with the on-board cone-beam CT setting. The results demonstrated the feasibility of PCR for cine CBCT and significantly improved reconstruction quality of PCR from PICCS for cine CBCT. With a priori estimated temporal motion coefficients using fluoroscopic training projections, the PCR method can accurately reconstruct spatial principal components, and then generate cine CT images as a product of temporal motion coefficients and spatial principal components. © 2017 American Association of Physicists in Medicine.

Analysis of Memory Codes and Cumulative Rehearsal in Observational Learning

ERIC Educational Resources Information Center

Bandura, Albert; And Others

1974-01-01

The present study examined the influence of memory codes varying in meaningfulness and retrievability and cumulative rehearsal on retention of observationally learned responses over increasing temporal intervals. (Editor)

Enhancing memory for lists by grouped presentation and rehearsal: a pilot study in healthy subjects with unexpected results.

PubMed

Hoppe, Christian; Stojanovic, Jelena; Elger, Christian E

2009-12-01

List learning is probably the most established paradigm for the psychometric evaluation of episodic memory deficits in different neuropsychiatric conditions including epilepsy. Strategies which are capable of increasing the test performance might be promising candidates for a therapeutic improvement of daily memory performance. Based on the classical 'temporal grouping effect' we wanted to evaluate the memory-enhancing potential of disentangling perceiving, rehearsing and encoding by temporally grouped presentation and group-wise reproduction during acquisition. According to the ethical principle of subsidiary the study was performed in healthy adolescents (N=126) before setting-up a patient study. Subjects had to learn a list of 12 semantically unrelated nouns and a list of 12 figures during two acquisition trials under one of four experimental conditions defined by the size of presented item groups (GS): GS=1 (single items, i.e., 12 x 1 item), GS=3 (4 x 3 items), GS=6 (2 x 6 items), and GS=12 (standard presentation mode, i.e., 1 x 12 items). Repeated measures MANOVA confirmed a positive effect of smaller GS on acquisition performance but the grouping condition obtained no effect on immediate and delayed free recall or on yes/no recognition. For verbal retention, GS=12 even showed a tendency toward an advantage as compared to GS=3. Although appearing reasonable and promising, facilitating acquisition during list learning by temporal grouping and grouped overt rehearsal turned out to be ineffective with regard to long-term memory encoding and retrieval. A strategy however which fails in healthy subjects is unlikely to obtain a therapeutic potential in patients with memory deficits.

Presynaptic D2 dopamine receptors control long-term depression expression and memory processes in the temporal hippocampus.

PubMed

Rocchetti, Jill; Isingrini, Elsa; Dal Bo, Gregory; Sagheby, Sara; Menegaux, Aurore; Tronche, François; Levesque, Daniel; Moquin, Luc; Gratton, Alain; Wong, Tak Pan; Rubinstein, Marcelo; Giros, Bruno

2015-03-15

Dysfunctional mesocorticolimbic dopamine signaling has been linked to alterations in motor and reward-based functions associated with psychiatric disorders. Converging evidence from patients with psychiatric disorders and use of antipsychotics suggests that imbalance of dopamine signaling deeply alters hippocampal functions. However, given the lack of full characterization of a functional mesohippocampal pathway, the precise role of dopamine transmission in memory deficits associated with these disorders and their dedicated therapies is unknown. In particular, the positive outcome of antipsychotic treatments, commonly antagonizing D2 dopamine receptors (D2Rs), on cognitive deficits and memory impairments remains questionable. Following pharmacologic and genetic manipulation of dopamine transmission, we performed anatomic, neurochemical, electrophysiologic, and behavioral investigations to uncover the role of D2Rs in hippocampal-dependent plasticity and learning. Naïve mice (n = 4-21) were used in the different procedures. Dopamine modulated both long-term potentiation and long-term depression in the temporal hippocampus as well as spatial and recognition learning and memory in mice through D2Rs. Although genetic deletion or pharmacologic blockade of D2Rs led to the loss of long-term potentiation expression, the specific genetic removal of presynaptic D2Rs impaired long-term depression and performances on spatial memory tasks. Presynaptic D2Rs in dopamine fibers of the temporal hippocampus tightly modulate long-term depression expression and play a major role in the regulation of hippocampal learning and memory. This direct role of mesohippocampal dopamine input as uncovered here adds a new dimension to dopamine involvement in the physiology underlying deficits associated with neuropsychiatric disorders. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Auditory rhythmic cueing in movement rehabilitation: findings and possible mechanisms

PubMed Central

Schaefer, Rebecca S.

2014-01-01

Moving to music is intuitive and spontaneous, and music is widely used to support movement, most commonly during exercise. Auditory cues are increasingly also used in the rehabilitation of disordered movement, by aligning actions to sounds such as a metronome or music. Here, the effect of rhythmic auditory cueing on movement is discussed and representative findings of cued movement rehabilitation are considered for several movement disorders, specifically post-stroke motor impairment, Parkinson's disease and Huntington's disease. There are multiple explanations for the efficacy of cued movement practice. Potentially relevant, non-mutually exclusive mechanisms include the acceleration of learning; qualitatively different motor learning owing to an auditory context; effects of increased temporal skills through rhythmic practices and motivational aspects of musical rhythm. Further considerations of rehabilitation paradigm efficacy focus on specific movement disorders, intervention methods and complexity of the auditory cues. Although clinical interventions using rhythmic auditory cueing do not show consistently positive results, it is argued that internal mechanisms of temporal prediction and tracking are crucial, and further research may inform rehabilitation practice to increase intervention efficacy. PMID:25385780

Neural dynamics of reward probability coding: a Magnetoencephalographic study in humans

PubMed Central

Thomas, Julie; Vanni-Mercier, Giovanna; Dreher, Jean-Claude

2013-01-01

Prediction of future rewards and discrepancy between actual and expected outcomes (prediction error) are crucial signals for adaptive behavior. In humans, a number of fMRI studies demonstrated that reward probability modulates these two signals in a large brain network. Yet, the spatio-temporal dynamics underlying the neural coding of reward probability remains unknown. Here, using magnetoencephalography, we investigated the neural dynamics of prediction and reward prediction error computations while subjects learned to associate cues of slot machines with monetary rewards with different probabilities. We showed that event-related magnetic fields (ERFs) arising from the visual cortex coded the expected reward value 155 ms after the cue, demonstrating that reward value signals emerge early in the visual stream. Moreover, a prediction error was reflected in ERF peaking 300 ms after the rewarded outcome and showing decreasing amplitude with higher reward probability. This prediction error signal was generated in a network including the anterior and posterior cingulate cortex. These findings pinpoint the spatio-temporal characteristics underlying reward probability coding. Together, our results provide insights into the neural dynamics underlying the ability to learn probabilistic stimuli-reward contingencies. PMID:24302894

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.

Context and Time in Causal Learning: Contingency and Mood Dependent Effects

PubMed Central

Msetfi, Rachel M.; Wade, Caroline; Murphy, Robin A.

2013-01-01

Defining cues for instrumental causality are the temporal, spatial and contingency relationships between actions and their effects. In this study, we carried out a series of causal learning experiments that systematically manipulated time and context in positive and negative contingency conditions. In addition, we tested participants categorized as non-dysphoric and mildly dysphoric because depressed mood has been shown to affect the processing of all these causal cues. Findings showed that causal judgements made by non-dysphoric participants were contextualized at baseline and were affected by the temporal spacing of actions and effects only with generative, but not preventative, contingency relationships. Participants categorized as dysphoric made less contextualized causal ratings at baseline but were more sensitive than others to temporal manipulations across the contingencies. These effects were consistent with depression affecting causal learning through the effects of slowed time experience on accrued exposure to the context in which causal events took place. Taken together, these findings are consistent with associative approaches to causal judgement. PMID:23691147

Learned Attention in Adult Language Acquisition: A Replication and Generalization Study and Meta-Analysis

ERIC Educational Resources Information Center

Ellis, Nick C.; Sagarra, Nuria

2011-01-01

This study investigates associative learning explanations of the limited attainment of adult compared to child language acquisition in terms of learned attention to cues. It replicates and extends Ellis and Sagarra (2010) in demonstrating short- and long-term learned attention in the acquisition of temporal reference in Latin. In Experiment 1,…

Video-based convolutional neural networks for activity recognition from robot-centric videos

NASA Astrophysics Data System (ADS)

Ryoo, M. S.; Matthies, Larry

2016-05-01

In this evaluation paper, we discuss convolutional neural network (CNN)-based approaches for human activity recognition. In particular, we investigate CNN architectures designed to capture temporal information in videos and their applications to the human activity recognition problem. There have been multiple previous works to use CNN-features for videos. These include CNNs using 3-D XYT convolutional filters, CNNs using pooling operations on top of per-frame image-based CNN descriptors, and recurrent neural networks to learn temporal changes in per-frame CNN descriptors. We experimentally compare some of these different representatives CNNs while using first-person human activity videos. We especially focus on videos from a robots viewpoint, captured during its operations and human-robot interactions.

Spectrotemporal Modulation Detection and Speech Perception by Cochlear Implant Users

PubMed Central

Won, Jong Ho; Moon, Il Joon; Jin, Sunhwa; Park, Heesung; Woo, Jihwan; Cho, Yang-Sun; Chung, Won-Ho; Hong, Sung Hwa

2015-01-01

Spectrotemporal modulation (STM) detection performance was examined for cochlear implant (CI) users. The test involved discriminating between an unmodulated steady noise and a modulated stimulus. The modulated stimulus presents frequency modulation patterns that change in frequency over time. In order to examine STM detection performance for different modulation conditions, two different temporal modulation rates (5 and 10 Hz) and three different spectral modulation densities (0.5, 1.0, and 2.0 cycles/octave) were employed, producing a total 6 different STM stimulus conditions. In order to explore how electric hearing constrains STM sensitivity for CI users differently from acoustic hearing, normal-hearing (NH) and hearing-impaired (HI) listeners were also tested on the same tasks. STM detection performance was best in NH subjects, followed by HI subjects. On average, CI subjects showed poorest performance, but some CI subjects showed high levels of STM detection performance that was comparable to acoustic hearing. Significant correlations were found between STM detection performance and speech identification performance in quiet and in noise. In order to understand the relative contribution of spectral and temporal modulation cues to speech perception abilities for CI users, spectral and temporal modulation detection was performed separately and related to STM detection and speech perception performance. The results suggest that that slow spectral modulation rather than slow temporal modulation may be important for determining speech perception capabilities for CI users. Lastly, test–retest reliability for STM detection was good with no learning. The present study demonstrates that STM detection may be a useful tool to evaluate the ability of CI sound processing strategies to deliver clinically pertinent acoustic modulation information. PMID:26485715

Focalised stimulation using high definition transcranial direct current stimulation (HD-tDCS) to investigate declarative verbal learning and memory functioning.

PubMed

Nikolin, Stevan; Loo, Colleen K; Bai, Siwei; Dokos, Socrates; Martin, Donel M

2015-08-15

Declarative verbal learning and memory are known to be lateralised to the dominant hemisphere and to be subserved by a network of structures, including those located in frontal and temporal regions. These structures support critical components of verbal memory, including working memory, encoding, and retrieval. Their relative functional importance in facilitating declarative verbal learning and memory, however, remains unclear. To investigate the different functional roles of these structures in subserving declarative verbal learning and memory performance by applying a more focal form of transcranial direct current stimulation, "High Definition tDCS" (HD-tDCS). Additionally, we sought to examine HD-tDCS effects and electrical field intensity distributions using computer modelling. HD-tDCS was administered to the left dorsolateral prefrontal cortex (LDLPFC), planum temporale (PT), and left medial temporal lobe (LMTL) to stimulate the hippocampus, during learning on a declarative verbal memory task. Sixteen healthy participants completed a single blind, intra-individual cross-over, sham-controlled study which used a Latin Square experimental design. Cognitive effects on working memory and sustained attention were additionally examined. HD-tDCS to the LDLPFC significantly improved the rate of verbal learning (p=0.03, η(2)=0.29) and speed of responding during working memory performance (p=0.02, η(2)=0.35), but not accuracy (p=0.12, η(2)=0.16). No effect of tDCS on verbal learning, retention, or retrieval was found for stimulation targeted to the LMTL or the PT. Secondary analyses revealed that LMTL stimulation resulted in increased recency (p=0.02, η(2)=0.31) and reduced mid-list learning effects (p=0.01, η(2)=0.39), suggesting an inhibitory effect on learning. HD-tDCS to the LDLPFC facilitates the rate of verbal learning and improved efficiency of working memory may underlie performance effects. This focal method of administrating tDCS has potential for probing and enhancing cognitive functioning. Copyright © 2015 Elsevier Inc. All rights reserved.

E-learning task analysis making temporal evolution graphics on symptoms of waves and the ability to solve problems

NASA Astrophysics Data System (ADS)

Rosdiana, L.; Widodo, W.; Nurita, T.; Fauziah, A. N. M.

2018-04-01

This study aimed to describe the ability of pre-service teachers to create graphs, solve the problem of spatial and temporal evolution on the symptoms of vibrations and waves. The learning was conducted using e-learning method. The research design is a quasi-experimental design with one-shot case study. The e-learning contained learning materials and tasks involving answering tasks, making questions, solving their own questions, and making graphs. The participants of the study was 28 students of Science Department, Universitas Negeri Surabaya. The results obtained by using the e-learning were that the students’ ability increase gradually from task 1 to task 3 (the tasks consisted of three tasks). Additionally, based on the questionnaire with 28 respondents, it showed that 24 respondents stated that making graphs via e-learning were still difficult. Four respondents said that it was easy to make graphs via e-learning. Nine respondents stated that the e-learning did not help them in making graphs and 19 respondents stated that the e-learning help in creating graphs. The conclusion of the study is that the students was able to make graphs on paper sheet, but they got difficulty to make the graphs in e-learning (the virtual form).

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

PubMed

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

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

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

PubMed Central

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

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

Brain signal complexity rises with repetition suppression in visual learning.

PubMed

Lafontaine, Marc Philippe; Lacourse, Karine; Lina, Jean-Marc; McIntosh, Anthony R; Gosselin, Frédéric; Théoret, Hugo; Lippé, Sarah

2016-06-21

Neuronal activity associated with visual processing of an unfamiliar face gradually diminishes when it is viewed repeatedly. This process, known as repetition suppression (RS), is involved in the acquisition of familiarity. Current models suggest that RS results from interactions between visual information processing areas located in the occipito-temporal cortex and higher order areas, such as the dorsolateral prefrontal cortex (DLPFC). Brain signal complexity, which reflects information dynamics of cortical networks, has been shown to increase as unfamiliar faces become familiar. However, the complementarity of RS and increases in brain signal complexity have yet to be demonstrated within the same measurements. We hypothesized that RS and brain signal complexity increase occur simultaneously during learning of unfamiliar faces. Further, we expected alteration of DLPFC function by transcranial direct current stimulation (tDCS) to modulate RS and brain signal complexity over the occipito-temporal cortex. Participants underwent three tDCS conditions in random order: right anodal/left cathodal, right cathodal/left anodal and sham. Following tDCS, participants learned unfamiliar faces, while an electroencephalogram (EEG) was recorded. Results revealed RS over occipito-temporal electrode sites during learning, reflected by a decrease in signal energy, a measure of amplitude. Simultaneously, as signal energy decreased, brain signal complexity, as estimated with multiscale entropy (MSE), increased. In addition, prefrontal tDCS modulated brain signal complexity over the right occipito-temporal cortex during the first presentation of faces. These results suggest that although RS may reflect a brain mechanism essential to learning, complementary processes reflected by increases in brain signal complexity, may be instrumental in the acquisition of novel visual information. Such processes likely involve long-range coordinated activity between prefrontal and lower order visual areas. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Multimodal data and machine learning for surgery outcome prediction in complicated cases of mesial temporal lobe epilepsy.

PubMed

Memarian, Negar; Kim, Sally; Dewar, Sandra; Engel, Jerome; Staba, Richard J

2015-09-01

This study sought to predict postsurgical seizure freedom from pre-operative diagnostic test results and clinical information using a rapid automated approach, based on supervised learning methods in patients with drug-resistant focal seizures suspected to begin in temporal lobe. We applied machine learning, specifically a combination of mutual information-based feature selection and supervised learning classifiers on multimodal data, to predict surgery outcome retrospectively in 20 presurgical patients (13 female; mean age±SD, in years 33±9.7 for females, and 35.3±9.4 for males) who were diagnosed with mesial temporal lobe epilepsy (MTLE) and subsequently underwent standard anteromesial temporal lobectomy. The main advantage of the present work over previous studies is the inclusion of the extent of ipsilateral neocortical gray matter atrophy and spatiotemporal properties of depth electrode-recorded seizures as training features for individual patient surgery planning. A maximum relevance minimum redundancy (mRMR) feature selector identified the following features as the most informative predictors of postsurgical seizure freedom in this study's sample of patients: family history of epilepsy, ictal EEG onset pattern (positive correlation with seizure freedom), MRI-based gray matter thickness reduction in the hemisphere ipsilateral to seizure onset, proportion of seizures that first appeared in ipsilateral amygdala to total seizures, age, epilepsy duration, delay in the spread of ipsilateral ictal discharges from site of onset, gender, and number of electrode contacts at seizure onset (negative correlation with seizure freedom). Using these features in combination with a least square support vector machine (LS-SVM) classifier compared to other commonly used classifiers resulted in very high surgical outcome prediction accuracy (95%). Supervised machine learning using multimodal compared to unimodal data accurately predicted postsurgical outcome in patients with atypical MTLE. Published by Elsevier Ltd.

Lateralization of temporal lobe epilepsy and learning disabilities, as defined by disability-related civil rights law.

PubMed

Butterbaugh, Grant; Olejniczak, Piotr; Roques, Betsy; Costa, Richard; Rose, Marcy; Fisch, Bruce; Carey, Michael; Thomson, Jessica; Skinner, John

2004-08-01

Epilepsy research has identified higher rates of learning disorders in patients with temporal lobe epilepsy (TLE). However, most studies have not adequately assessed complex functional adult learning skills, such as reading comprehension and written language. We designed this study to evaluate our predictions that higher rates of reading comprehension, written language, and calculation disabilities would be associated with left TLE versus right TLE. Reading comprehension, written language, and calculation skills were assessed by using selected subtests from the Woodcock-Johnson Psycho-Educational Tests of Achievement-Revised in a consecutive series of 31 presurgical patients with TLE. Learning disabilities were defined by one essential criterion consistent with the Americans with Disabilities Act of 1990. Patients had left hemisphere language dominance based on Wada results, left or right TLE based on inpatient EEG monitoring, and negative magnetic resonance imaging (MRI), other than MRI correlates of mesial temporal sclerosis. Higher rates of reading comprehension, written language, and calculation disabilities were associated with left TLE, as compared with right TLE. Nearly 75% of patients with left TLE, whereas fewer than 10% of those with right TLE, had at least one learning disability. Seizure onset in the language-dominant hemisphere, as compared with the nondominant hemisphere, was associated with higher rates of specific learning disabilities and a history of poor literacy or career development or both. These results support the potential clinical benefits of using lateralization of seizure onset as a predictor of the risk of learning disabilities that, once evaluated, could be accommodated to increase the participation of patients with epilepsy in work and educational settings.

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

PubMed

Tanaka, Takuma; Aoyagi, Toshio; Kaneko, Takeshi

2012-10-01

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

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

Sparse Representation with Spatio-Temporal Online Dictionary Learning for Efficient Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Tang, Xin; Zou, Junni; Xiong, Hongkai; Chen, Chang Wen

2016-07-27

Classical dictionary learning methods for video coding suer from high computational complexity and interfered coding eciency by disregarding its underlying distribution. This paper proposes a spatio-temporal online dictionary learning (STOL) algorithm to speed up the convergence rate of dictionary learning with a guarantee of approximation error. The proposed algorithm incorporates stochastic gradient descents to form a dictionary of pairs of 3-D low-frequency and highfrequency spatio-temporal volumes. In each iteration of the learning process, it randomly selects one sample volume and updates the atoms of dictionary by minimizing the expected cost, rather than optimizes empirical cost over the complete training data like batch learning methods, e.g. K-SVD. Since the selected volumes are supposed to be i.i.d. samples from the underlying distribution, decomposition coecients attained from the trained dictionary are desirable for sparse representation. Theoretically, it is proved that the proposed STOL could achieve better approximation for sparse representation than K-SVD and maintain both structured sparsity and hierarchical sparsity. It is shown to outperform batch gradient descent methods (K-SVD) in the sense of convergence speed and computational complexity, and its upper bound for prediction error is asymptotically equal to the training error. With lower computational complexity, extensive experiments validate that the STOL based coding scheme achieves performance improvements than H.264/AVC or HEVC as well as existing super-resolution based methods in ratedistortion performance and visual quality.

Face processing in different brain areas, and critical band masking.

PubMed

Rolls, Edmund T

2008-09-01

Neurophysiological evidence is described showing that some neurons in the macaque inferior temporal visual cortex have responses that are invariant with respect to the position, size, view, and spatial frequency of faces and objects, and that these neurons show rapid processing and rapid learning. Critical band spatial frequency masking is shown to be a property of these face-selective neurons and of the human visual perception of faces. Which face or object is present is encoded using a distributed representation in which each neuron conveys independent information in its firing rate, with little information evident in the relative time of firing of different neurons. This ensemble encoding has the advantages of maximizing the information in the representation useful for discrimination between stimuli using a simple weighted sum of the neuronal firing by the receiving neurons, generalization, and graceful degradation. These invariant representations are ideally suited to provide the inputs to brain regions such as the orbitofrontal cortex and amygdala that learn the reinforcement associations of an individual's face, for then the learning, and the appropriate social and emotional responses generalize to other views of the same face. A theory is described of how such invariant representations may be produced by self-organizing learning in a hierarchically organized set of visual cortical areas with convergent connectivity. The theory utilizes either temporal or spatial continuity with an associative synaptic modification rule. Another population of neurons in the cortex in the superior temporal sulcus encodes other aspects of faces such as face expression, eye-gaze, face view, and whether the head is moving. These neurons thus provide important additional inputs to parts of the brain such as the orbitofrontal cortex and amygdala that are involved in social communication and emotional behaviour. Outputs of these systems reach the amygdala, in which face-selective neurons are found, and also the orbitofrontal cortex, in which some neurons are tuned to face identity and others to face expression. In humans, activation of the orbitofrontal cortex is found when a change of face expression acts as a social signal that behaviour should change; and damage to the human orbitofrontal and pregenual cingulate cortex can impair face and voice expression identification, and also the reversal of emotional behaviour that normally occurs when reinforcers are reversed.

Impaired Verbal Associative Learning after Resection of Left Perirhinal Cortex

ERIC Educational Resources Information Center

Weintrob, David L.; Saling, Michael M.; Berkovic, Samuel F.; Reutens, David C.

2007-01-01

Some patients considered for left temporal lobectomy for epilepsy present with normal verbal learning and no MRI evidence of hippocampal pathology. In order to preserve learning function, the surgical approach in these cases often aims at sparing the hippocampus. Parahippocampal structures, including the left perirhinal region, however, also…

Engagement in Classroom Learning: Creating Temporal Participation Incentives for Extrinsically Motivated Students through Bonus Credits

ERIC Educational Resources Information Center

Rassuli, Ali

2012-01-01

Extrinsic inducements to adjust students' learning motivations have evolved within 2 opposing paradigms. Cognitive evaluation theories claim that controlling factors embedded in extrinsic rewards dissipate intrinsic aspirations. Behavioral theorists contend that if engagement is voluntary, extrinsic reinforcements enhance learning without ill…

Facilitation of learning induced by both random and gradual visuomotor task variation

PubMed Central

Braun, Daniel A.; Wolpert, Daniel M.

2012-01-01

Motor task variation has been shown to be a key ingredient in skill transfer, retention, and structural learning. However, many studies only compare training of randomly varying tasks to either blocked or null training, and it is not clear how experiencing different nonrandom temporal orderings of tasks might affect the learning process. Here we study learning in human subjects who experience the same set of visuomotor rotations, evenly spaced between −60° and +60°, either in a random order or in an order in which the rotation angle changed gradually. We compared subsequent learning of three test blocks of +30°→−30°→+30° rotations. The groups that underwent either random or gradual training showed significant (P < 0.01) facilitation of learning in the test blocks compared with a control group who had not experienced any visuomotor rotations before. We also found that movement initiation times in the random group during the test blocks were significantly (P < 0.05) lower than for the gradual or the control group. When we fit a state-space model with fast and slow learning processes to our data, we found that the differences in performance in the test block were consistent with the gradual or random task variation changing the learning and retention rates of only the fast learning process. Such adaptation of learning rates may be a key feature of ongoing meta-learning processes. Our results therefore suggest that both gradual and random task variation can induce meta-learning and that random learning has an advantage in terms of shorter initiation times, suggesting less reliance on cognitive processes. PMID:22131385

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

The effects of sleep deprivation on dissociable prototype learning systems.

PubMed

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

2011-03-01

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

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.

From the Invisible Hand to the Invisible Handshake: Marketing Higher Education.

ERIC Educational Resources Information Center

Gibbs, Paul

2002-01-01

Business marketing principles do not meet the needs of higher education. An alternative, humanistic marketing philosophy, includes a reconceptualization of the marketing mix as temporality (learning as a temporal activity), existential trust, and learner self-confidence. (Contains 60 references.) (SK)

Same items, different order: effects of temporal variability on infant categorization.

PubMed

Mather, Emily; Plunkett, Kim

2011-06-01

How does variability between members of a category influence infants' category learning? We explore the impact of the order in which different items are sampled on category formation. Two groups of 10-months-olds were presented with a series of exemplars to be organized into a single category. In a low distance group, the order of presentation minimized the perceptual distance between consecutive exemplars. In a high distance group, the order of presentation maximized the distance between successive exemplars. At test, only infants in the High Distance condition reliably discriminated between the category prototype and an atypical exemplar. Hence, the order in which infants learnt about the exemplars impacted their categorization performance. Our findings demonstrate the importance of moment-to-moment variations in similarity during infants' category learning. Copyright © 2011 Elsevier B.V. All rights reserved.

Sex differences in the representation of call stimuli in a songbird secondary auditory area

PubMed Central

Giret, Nicolas; Menardy, Fabien; Del Negro, Catherine

2015-01-01

Understanding how communication sounds are encoded in the central auditory system is critical to deciphering the neural bases of acoustic communication. Songbirds use learned or unlearned vocalizations in a variety of social interactions. They have telencephalic auditory areas specialized for processing natural sounds and considered as playing a critical role in the discrimination of behaviorally relevant vocal sounds. The zebra finch, a highly social songbird species, forms lifelong pair bonds. Only male zebra finches sing. However, both sexes produce the distance call when placed in visual isolation. This call is sexually dimorphic, is learned only in males and provides support for individual recognition in both sexes. Here, we assessed whether auditory processing of distance calls differs between paired males and females by recording spiking activity in a secondary auditory area, the caudolateral mesopallium (CLM), while presenting the distance calls of a variety of individuals, including the bird itself, the mate, familiar and unfamiliar males and females. In males, the CLM is potentially involved in auditory feedback processing important for vocal learning. Based on both the analyses of spike rates and temporal aspects of discharges, our results clearly indicate that call-evoked responses of CLM neurons are sexually dimorphic, being stronger, lasting longer, and conveying more information about calls in males than in females. In addition, how auditory responses vary among call types differ between sexes. In females, response strength differs between familiar male and female calls. In males, temporal features of responses reveal a sensitivity to the bird's own call. These findings provide evidence that sexual dimorphism occurs in higher-order processing areas within the auditory system. They suggest a sexual dimorphism in the function of the CLM, contributing to transmit information about the self-generated calls in males and to storage of information about the bird's auditory experience in females. PMID:26578918

Sex differences in the representation of call stimuli in a songbird secondary auditory area.

PubMed

Giret, Nicolas; Menardy, Fabien; Del Negro, Catherine

2015-01-01

Understanding how communication sounds are encoded in the central auditory system is critical to deciphering the neural bases of acoustic communication. Songbirds use learned or unlearned vocalizations in a variety of social interactions. They have telencephalic auditory areas specialized for processing natural sounds and considered as playing a critical role in the discrimination of behaviorally relevant vocal sounds. The zebra finch, a highly social songbird species, forms lifelong pair bonds. Only male zebra finches sing. However, both sexes produce the distance call when placed in visual isolation. This call is sexually dimorphic, is learned only in males and provides support for individual recognition in both sexes. Here, we assessed whether auditory processing of distance calls differs between paired males and females by recording spiking activity in a secondary auditory area, the caudolateral mesopallium (CLM), while presenting the distance calls of a variety of individuals, including the bird itself, the mate, familiar and unfamiliar males and females. In males, the CLM is potentially involved in auditory feedback processing important for vocal learning. Based on both the analyses of spike rates and temporal aspects of discharges, our results clearly indicate that call-evoked responses of CLM neurons are sexually dimorphic, being stronger, lasting longer, and conveying more information about calls in males than in females. In addition, how auditory responses vary among call types differ between sexes. In females, response strength differs between familiar male and female calls. In males, temporal features of responses reveal a sensitivity to the bird's own call. These findings provide evidence that sexual dimorphism occurs in higher-order processing areas within the auditory system. They suggest a sexual dimorphism in the function of the CLM, contributing to transmit information about the self-generated calls in males and to storage of information about the bird's auditory experience in females.

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.

Is "Learning" episodic memory? Distinct cognitive and neuroanatomic correlates of immediate recall during learning trials in neurologically normal aging and neurodegenerative cohorts.

PubMed

Casaletto, K B; Marx, G; Dutt, S; Neuhaus, J; Saloner, R; Kritikos, L; Miller, B; Kramer, J H

2017-07-28

Although commonly interpreted as a marker of episodic memory during neuropsychological exams, relatively little is known regarding the neurobehavior of "total learning" immediate recall scores. Medial temporal lobes are clearly associated with delayed recall performances, yet immediate recall may necessitate networks beyond traditional episodic memory. We aimed to operationalize cognitive and neuroanatomic correlates of total immediate recall in several aging syndromes. Demographically-matched neurologically normal adults (n=91), individuals with Alzheimer's disease (n=566), logopenic variant primary progressive aphasia (PPA) (n=34), behavioral variant frontotemporal dementia (n=97), semantic variant PPA (n=71), or nonfluent/agrammatic variant PPA (n=39) completed a neurocognitive battery, including the CVLT-Short Form trials 1-4 Total Immediate Recall; a majority subset also completed a brain MRI. Regressions covaried for age and sex, and MMSE in cognitive and total intracranial volume in neuroanatomic models. Neurologically normal adults demonstrated a heterogeneous pattern of cognitive associations with total immediate recall (executive, speed, delayed recall), such that no singular cognitive or neuroanatomic correlate uniquely predicted performance. Within the clinical cohorts, there were syndrome-specific cognitive and neural associations with total immediate recall; e.g., semantic processing was the strongest cognitive correlate in svPPA (partial r=0.41), while frontal volumes was the only meaningful neural correlate in bvFTD (partial r=0.20). Medial temporal lobes were not independently associated with total immediate recall in any group (ps>0.05). Multiple neurobehavioral systems are associated with "total learning" immediate recall scores that importantly differ across distinct clinical syndromes. Conventional memory networks may not be sufficient or even importantly contribute to total immediate recall in many syndromes. Interpreting learning scores as equivalent to episodic memory may be erroneous. Copyright © 2017 Elsevier Ltd. All rights reserved.

The neuropsychology of the Klüver-Bucy syndrome in children.

PubMed

Lippe, S; Gonin-Flambois, C; Jambaqué, I

2013-01-01

The Klüver-Bucy syndrome (KBS) is characterized by a number of peculiar behavioral symptoms. The syndrome was first observed in 1939 by Heinrich Klüver and Paul Bucy in the rhesus monkey following removal of the greater portion of the monkey's temporal lobes and rhinencephalon. The animal showed (a) visual agnosia (inability to recognize objects without general loss of visual discrimination), (b) excessive oral tendency (oral exploration of objects), (c) hypermetamorphosis (excessive visual attentiveness), (d) placidity with loss of normal fear and anger responses, (e) altered sexual behavior manifesting mainly as marked and indiscriminate hypersexuality, and (f) changes in eating behavior. In humans, KBS can be complete or incomplete. It occurs as a consequence of neurological disorders that essentially cause destruction or dysfunction of bilateral mesial temporal lobe structures (i.e., Pick disease, Alzheimer disease, cerebral trauma, cerebrovascular accidents, temporal lobe epilepsy, herpetic encephalopathy, heat stroke). As for epilepsy, complete and incomplete KBS are well documented in temporal lobe epilepsy, temporal lobectomy, and partial status epilepticus. KBS can occur at any age. Children seem to show similar symptoms to adults, although some differences in the manifestations of symptoms may be related to the fact that children have not yet learned certain behaviors. Copyright © 2013 Elsevier B.V. All rights reserved.

Strategic allocation of attention reduces temporally predictable stimulus conflict

PubMed Central

Appelbaum, L. Gregory; Boehler, Carsten N.; Won, Robert; Davis, Lauren; Woldorff, Marty G.

2013-01-01

Humans are able to continuously monitor environmental situations and adjust their behavioral strategies to optimize performance. Here we investigate the behavioral and brain adjustments that occur when conflicting stimulus elements are, or are not, temporally predictable. Event-related potentials (ERPs) were collected while manual-response variants of the Stroop task were performed in which the stimulus onset asynchronies (SOAs) between the relevant-color and irrelevant-word stimulus components were either randomly intermixed, or held constant, within each experimental run. Results indicated that the size of both the neural and behavioral effects of stimulus incongruency varied with the temporal arrangement of the stimulus components, such that the random-SOA arrangements produced the greatest incongruency effects at the earliest irrelevant-first SOA (−200 ms) and the constant-SOA arrangements produced the greatest effects with simultaneous presentation. These differences in conflict processing were accompanied by rapid (~150 ms) modulations of the sensory ERPs to the irrelevant distracter components when they occurred consistently first. These effects suggest that individuals are able to strategically allocate attention in time to mitigate the influence of a temporally predictable distracter. As these adjustments are instantiated by the subjects without instruction, they reveal a form of rapid strategic learning for dealing with temporally predictable stimulus incongruency. PMID:22360623

Anticipation of delayed action-effects: learning when an effect occurs, without knowing what this effect will be.

PubMed

Dignath, David; Janczyk, Markus

2017-09-01

According to the ideomotor principle, behavior is controlled via a retrieval of the sensory consequences that will follow from the respective movement ("action-effects"). These consequences include not only what will happen, but also when something will happen. In fact, recollecting the temporal duration between response and effect takes time and prolongs the initiation of the response. We investigated the associative structure of action-effect learning with delayed effects and asked whether participants acquire integrated action-time-effect episodes that comprise a compound of all three elements or whether they acquire separate traces that connect actions to the time until an effect occurs and actions to the effects that follow them. In three experiments, results showed that participants retrieve temporal intervals that follow from their actions even when the identity of the effect could not be learned. Furthermore, retrieval of temporal intervals in isolation was not inferior to retrieval of temporal intervals that were consistently followed by predictable action-effects. More specifically, when tested under extinction, retrieval of action-time and action-identity associations seems to compete against each other, similar to overshadowing effects reported for stimulus-response conditioning. Together, these results suggest that people anticipate when the consequences of their action will occur, independently from what the consequences will be.

Combining feature extraction and classification for fNIRS BCIs by regularized least squares optimization.

PubMed

Heger, Dominic; Herff, Christian; Schultz, Tanja

2014-01-01

In this paper, we show that multiple operations of the typical pattern recognition chain of an fNIRS-based BCI, including feature extraction and classification, can be unified by solving a convex optimization problem. We formulate a regularized least squares problem that learns a single affine transformation of raw HbO(2) and HbR signals. We show that this transformation can achieve competitive results in an fNIRS BCI classification task, as it significantly improves recognition of different levels of workload over previously published results on a publicly available n-back data set. Furthermore, we visualize the learned models and analyze their spatio-temporal characteristics.

Illusory Reversal of Causality between Touch and Vision has No Effect on Prism Adaptation Rate.

PubMed

Tanaka, Hirokazu; Homma, Kazuhiro; Imamizu, Hiroshi

2012-01-01

Learning, according to Oxford Dictionary, is "to gain knowledge or skill by studying, from experience, from being taught, etc." In order to learn from experience, the central nervous system has to decide what action leads to what consequence, and temporal perception plays a critical role in determining the causality between actions and consequences. In motor adaptation, causality between action and consequence is implicitly assumed so that a subject adapts to a new environment based on the consequence caused by her action. Adaptation to visual displacement induced by prisms is a prime example; the visual error signal associated with the motor output contributes to the recovery of accurate reaching, and a delayed feedback of visual error can decrease the adaptation rate. Subjective feeling of temporal order of action and consequence, however, can be modified or even reversed when her sense of simultaneity is manipulated with an artificially delayed feedback. Our previous study (Tanaka et al., 2011; Exp. Brain Res.) demonstrated that the rate of prism adaptation was unaffected when the subjective delay of visual feedback was shortened. This study asked whether subjects could adapt to prism adaptation and whether the rate of prism adaptation was affected when the subjective temporal order was illusory reversed. Adapting to additional 100 ms delay and its sudden removal caused a positive shift of point of simultaneity in a temporal order judgment experiment, indicating an illusory reversal of action and consequence. We found that, even in this case, the subjects were able to adapt to prism displacement with the learning rate that was statistically indistinguishable to that without temporal adaptation. This result provides further evidence to the dissociation between conscious temporal perception and motor adaptation.

The effect of white matter hyperintensities on verbal memory: Mediation by temporal lobe atrophy.

PubMed

Swardfager, Walter; Cogo-Moreira, Hugo; Masellis, Mario; Ramirez, Joel; Herrmann, Nathan; Edwards, Jodi D; Saleem, Mahwesh; Chan, Parco; Yu, Di; Nestor, Sean M; Scott, Christopher J M; Holmes, Melissa F; Sahlas, Demetrios J; Kiss, Alexander; Oh, Paul I; Strother, Stephen C; Gao, Fuqiang; Stefanovic, Bojana; Keith, Julia; Symons, Sean; Swartz, Richard H; Lanctôt, Krista L; Stuss, Donald T; Black, Sandra E

2018-02-20

To determine the relationship between white matter hyperintensities (WMH) presumed to indicate disease of the cerebral small vessels, temporal lobe atrophy, and verbal memory deficits in Alzheimer disease (AD) and other dementias. We recruited groups of participants with and without AD, including strata with extensive WMH and minimal WMH, into a cross-sectional proof-of-principle study (n = 118). A consecutive case series from a memory clinic was used as an independent validation sample (n = 702; Sunnybrook Dementia Study; NCT01800214). We assessed WMH volume and left temporal lobe atrophy (measured as the brain parenchymal fraction) using structural MRI and verbal memory using the California Verbal Learning Test. Using path modeling with an inferential bootstrapping procedure, we tested an indirect effect of WMH on verbal recall that depends sequentially on temporal lobe atrophy and verbal learning. In both samples, WMH predicted poorer verbal recall, specifically due to temporal lobe atrophy and poorer verbal learning (proof-of-principle -1.53, 95% bootstrap confidence interval [CI] -2.45 to -0.88; and confirmation -0.66, 95% CI [-0.95 to -0.41] words). This pathway was significant in subgroups with (-0.20, 95% CI [-0.38 to -0.07] words, n = 363) and without (-0.71, 95% CI [-1.12 to -0.37] words, n = 339) AD. Via the identical pathway, WMH contributed to deficits in recognition memory (-1.82%, 95% CI [-2.64% to -1.11%]), a sensitive and specific sign of AD. Across dementia syndromes, WMH contribute indirectly to verbal memory deficits considered pathognomonic of Alzheimer disease, specifically by contributing to temporal lobe atrophy. © 2018 American Academy of Neurology.

Automatic temporal segment detection via bilateral long short-term memory recurrent neural networks

NASA Astrophysics Data System (ADS)

Sun, Bo; Cao, Siming; He, Jun; Yu, Lejun; Li, Liandong

2017-03-01

Constrained by the physiology, the temporal factors associated with human behavior, irrespective of facial movement or body gesture, are described by four phases: neutral, onset, apex, and offset. Although they may benefit related recognition tasks, it is not easy to accurately detect such temporal segments. An automatic temporal segment detection framework using bilateral long short-term memory recurrent neural networks (BLSTM-RNN) to learn high-level temporal-spatial features, which synthesizes the local and global temporal-spatial information more efficiently, is presented. The framework is evaluated in detail over the face and body database (FABO). The comparison shows that the proposed framework outperforms state-of-the-art methods for solving the problem of temporal segment detection.

High-resolution Temporal Representations of Alcohol and Tobacco Behaviors from Social Media Data

PubMed Central

Huang, Tom; Elghafari, Anas; Relia, Kunal; Chunara, Rumi

2017-01-01

Understanding tobacco- and alcohol-related behavioral patterns is critical for uncovering risk factors and potentially designing targeted social computing intervention systems. Given that we make choices multiple times per day, hourly and daily patterns are critical for better understanding behaviors. Here, we combine natural language processing, machine learning and time series analyses to assess Twitter activity specifically related to alcohol and tobacco consumption and their sub-daily, daily and weekly cycles. Twitter self-reports of alcohol and tobacco use are compared to other data streams available at similar temporal resolution. We assess if discussion of drinking by inferred underage versus legal age people or discussion of use of different types of tobacco products can be differentiated using these temporal patterns. We find that time and frequency domain representations of behaviors on social media can provide meaningful and unique insights, and we discuss the types of behaviors for which the approach may be most useful. PMID:29264592

ERP measures of partial semantic knowledge: left temporal indices of skill differences and lexical quality.

PubMed

Frishkoff, Gwen A; Perfetti, Charles A; Westbury, Chris

2009-01-01

This study examines the sensitivity of early event-related potentials (ERPs) to degrees of word semantic knowledge. Participants with strong, average, or weak vocabulary skills made speeded lexical decisions to letter strings. To represent the full spectrum of word knowledge among adult native-English speakers, we used rare words that were orthographically matched with more familiar words and with pseudowords. Since the lexical decision could not reliably be made on the basis of word form, subjects were obliged to use semantic knowledge to perform the task. A d' analysis suggested that high-skilled subjects adopted a more conservative strategy in response to rare versus more familiar words. Moreover, the high-skilled participants showed a trend towards an enhanced "N2c" to rare words, and a similar posterior temporal effect reached significance approximately 650 ms. Generators for these effects were localized to left temporal cortex. We discuss implications of these results for word learning and for theories of lexical semantic access.

Autocorrelation structure at rest predicts value correlates of single neurons during reward-guided choice

PubMed Central

Cavanagh, Sean E; Wallis, Joni D; Kennerley, Steven W; Hunt, Laurence T

2016-01-01

Correlates of value are routinely observed in the prefrontal cortex (PFC) during reward-guided decision making. In previous work (Hunt et al., 2015), we argued that PFC correlates of chosen value are a consequence of varying rates of a dynamical evidence accumulation process. Yet within PFC, there is substantial variability in chosen value correlates across individual neurons. Here we show that this variability is explained by neurons having different temporal receptive fields of integration, indexed by examining neuronal spike rate autocorrelation structure whilst at rest. We find that neurons with protracted resting temporal receptive fields exhibit stronger chosen value correlates during choice. Within orbitofrontal cortex, these neurons also sustain coding of chosen value from choice through the delivery of reward, providing a potential neural mechanism for maintaining predictions and updating stored values during learning. These findings reveal that within PFC, variability in temporal specialisation across neurons predicts involvement in specific decision-making computations. DOI: http://dx.doi.org/10.7554/eLife.18937.001 PMID:27705742

Focal versus distributed temporal cortex activity for speech sound category assignment

PubMed Central

Bouton, Sophie; Chambon, Valérian; Tyrand, Rémi; Seeck, Margitta; Karkar, Sami; van de Ville, Dimitri; Giraud, Anne-Lise

2018-01-01

Percepts and words can be decoded from distributed neural activity measures. However, the existence of widespread representations might conflict with the more classical notions of hierarchical processing and efficient coding, which are especially relevant in speech processing. Using fMRI and magnetoencephalography during syllable identification, we show that sensory and decisional activity colocalize to a restricted part of the posterior superior temporal gyrus (pSTG). Next, using intracortical recordings, we demonstrate that early and focal neural activity in this region distinguishes correct from incorrect decisions and can be machine-decoded to classify syllables. Crucially, significant machine decoding was possible from neuronal activity sampled across different regions of the temporal and frontal lobes, despite weak or absent sensory or decision-related responses. These findings show that speech-sound categorization relies on an efficient readout of focal pSTG neural activity, while more distributed activity patterns, although classifiable by machine learning, instead reflect collateral processes of sensory perception and decision. PMID:29363598

Learned saliency transformations for gaze guidance

NASA Astrophysics Data System (ADS)

Vig, Eleonora; Dorr, Michael; Barth, Erhardt

2011-03-01

The saliency of an image or video region indicates how likely it is that the viewer of the image or video fixates that region due to its conspicuity. An intriguing question is how we can change the video region to make it more or less salient. Here, we address this problem by using a machine learning framework to learn from a large set of eye movements collected on real-world dynamic scenes how to alter the saliency level of the video locally. We derive saliency transformation rules by performing spatio-temporal contrast manipulations (on a spatio-temporal Laplacian pyramid) on the particular video region. Our goal is to improve visual communication by designing gaze-contingent interactive displays that change, in real time, the saliency distribution of the scene.

Effects of practice and experience on the arcuate fasciculus: comparing singers, instrumentalists, and non-musicians.

PubMed

Halwani, Gus F; Loui, Psyche; Rüber, Theodor; Schlaug, Gottfried

2011-01-01

Structure and function of the human brain are affected by training in both linguistic and musical domains. Individuals with intensive vocal musical training provide a useful model for investigating neural adaptations of learning in the vocal-motor domain and can be compared with learning in a more general musical domain. Here we confirm general differences in macrostructure (tract volume) and microstructure (fractional anisotropy, FA) of the arcuate fasciculus (AF), a prominent white-matter tract connecting temporal and frontal brain regions, between singers, instrumentalists, and non-musicians. Both groups of musicians differed from non-musicians in having larger tract volume and higher FA values of the right and left AF. The AF was then subdivided in a dorsal (superior) branch connecting the superior temporal gyrus and the inferior frontal gyrus (STG ↔ IFG), and ventral (inferior) branch connecting the middle temporal gyrus and the inferior frontal gyrus (MTG ↔ IFG). Relative to instrumental musicians, singers had a larger tract volume but lower FA values in the left dorsal AF (STG ↔ IFG), and a similar trend in the left ventral AF (MTG ↔ IFG). This between-group comparison controls for the general effects of musical training, although FA was still higher in singers compared to non-musicians. Both musician groups had higher tract volumes in the right dorsal and ventral tracts compared to non-musicians, but did not show a significant difference between each other. Furthermore, in the singers' group, FA in the left dorsal branch of the AF was inversely correlated with the number of years of participants' vocal training. Our findings suggest that long-term vocal-motor training might lead to an increase in volume and microstructural complexity of specific white-matter tracts connecting regions that are fundamental to sound perception, production, and its feedforward and feedback control which can be differentiated from a more general musician effect.

Visual Memory in Post-Anterior Right Temporal Lobectomy Patients and Adult Normative Data for the Brown Location Test (BLT)

PubMed Central

Brown, Franklin C.; Tuttle, Erin; Westerveld, Michael; Ferraro, F. Richard; Chmielowiec, Teresa; Vandemore, Michelle; Gibson-Beverly, Gina; Bemus, Lisa; Roth, Robert M.; Blumenfeld, Hal; Spencer, Dennis D.; Spencer, Susan S

2010-01-01

Several large and meta-analytic studies have failed to support a consistent relationship between visual or “nonverbal” memory deficits and right mesial temporal lobe changes. However, the Brown Location Test (BLT) is a recently developed dot location learning and memory test that uses a nonsymmetrical array and provides control over many of the confounding variables (e.g., verbal influence and drawing requirements) inherent in other measures of visual memory. In the present investigation, we evaluated the clinical utility of the BLT in patients who had undergone left or right anterior mesial temporal lobectomies. We also provide adult normative data of 298 healthy adults in order to provide standardized scores. Results revealed significantly worse performance on the BLT in the right as compared to left lobectomy group and the healthy adult normative sample. The present findings support a role for the right anterior-mesial temporal lobe in dot location learning and memory. PMID:20056493

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

Probing interval timing with scalp-recorded electroencephalography (EEG).

PubMed

Ng, Kwun Kei; Penney, Trevor B

2014-01-01

Humans, and other animals, are able to easily learn the durations of events and the temporal relationships among them in spite of the absence of a dedicated sensory organ for time. This chapter summarizes the investigation of timing and time perception using scalp-recorded electroencephalography (EEG), a non-invasive technique that measures brain electrical potentials on a millisecond time scale. Over the past several decades, much has been learned about interval timing through the examination of the characteristic features of averaged EEG signals (i.e., event-related potentials, ERPs) elicited in timing paradigms. For example, the mismatch negativity (MMN) and omission potential (OP) have been used to study implicit and explicit timing, respectively, the P300 has been used to investigate temporal memory updating, and the contingent negative variation (CNV) has been used as an index of temporal decision making. In sum, EEG measures provide biomarkers of temporal processing that allow researchers to probe the cognitive and neural substrates underlying time perception.

Hippocampal Metaplasticity Is Required for the Formation of Temporal Associative Memories

PubMed Central

Xu, Jian; Antion, Marcia D.; Nomura, Toshihiro; Kraniotis, Stephen; Zhu, Yongling

2014-01-01

Metaplasticity regulates the threshold for modification of synaptic strength and is an important regulator of learning rules; however, it is not known whether these cellular mechanisms for homeostatic regulation of synapses contribute to particular forms of learning. Conditional ablation of mGluR5 in CA1 pyramidal neurons resulted in the inability of low-frequency trains of afferent activation to prime synapses for subsequent theta burst potentiation. Priming-induced metaplasticity requires mGluR5-mediated mobilization of endocannabinoids during the priming train to induce long-term depression of inhibition (I-LTD). Mice lacking priming-induced plasticity had no deficit in spatial reference memory tasks, but were impaired in an associative task with a temporal component. Conversely, enhancing endocannabinoid signaling facilitated temporal associative memory acquisition and, after training animals in these tasks, ex vivo I-LTD was partially occluded and theta burst LTP was enhanced. Together, these results suggest a link between metaplasticity mechanisms in the hippocampus and the formation of temporal associative memories. PMID:25505329

Sub-processes of motor learning revealed by a robotic manipulandum for rodents.

PubMed

Lambercy, O; Schubring-Giese, M; Vigaru, B; Gassert, R; Luft, A R; Hosp, J A

2015-02-01

Rodent models are widely used to investigate neural changes in response to motor learning. Usually, the behavioral readout of motor learning tasks used for this purpose is restricted to a binary measure of performance (i.e. "successful" movement vs. "failure"). Thus, the assignability of research in rodents to concepts gained in human research - implying diverse internal models that constitute motor learning - is still limited. To solve this problem, we recently introduced a three-degree-of-freedom robotic platform designed for rats (the ETH-Pattus) that combines an accurate behavioral readout (in the form of kinematics) with the possibility to invasively assess learning related changes within the brain (e.g. by performing immunohistochemistry or electrophysiology in acute slice preparations). Here, we validate this platform as a tool to study motor learning by establishing two forelimb-reaching paradigms that differ in degree of skill. Both conditions can be precisely differentiated in terms of their temporal pattern and performance levels. Based on behavioral data, we hypothesize the presence of several sub-processes contributing to motor learning. These share close similarities with concepts gained in humans or primates. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatiotemporal neurodynamics of automatic temporal expectancy in 9-month old infants.

PubMed

Mento, Giovanni; Valenza, Eloisa

2016-11-04

Anticipating events occurrence (Temporal Expectancy) is a crucial capacity for survival. Yet, there is little evidence about the presence of cortical anticipatory activity from infancy. In this study we recorded the High-density electrophysiological activity in 9 month-old infants and adults undergoing an audio-visual S1-S2 paradigm simulating a lifelike "Peekaboo" game inducing automatic temporal expectancy of smiling faces. The results indicate in the S2-preceding Contingent Negative Variation (CNV) an early electrophysiological signature of expectancy-based anticipatory cortical activity. Moreover, the progressive CNV amplitude increasing across the task suggested that implicit temporal rule learning is at the basis of expectancy building-up over time. Cortical source reconstruction suggested a common CNV generator between adults and infants in the right prefrontal cortex. The decrease in the activity of this area across the task (time-on-task effect) further implied an early, core role of this region in implicit temporal rule learning. By contrast, a time-on-task activity boost was found in the supplementary motor area (SMA) in adults and in the temporoparietal regions in infants. Altogether, our findings suggest that the capacity of the human brain to translate temporal predictions into anticipatory neural activity emerges ontogenetically early, although the underlying spatiotemporal cortical dynamics change across development.

Cognitive Characteristics of Children with Genetic Syndromes

PubMed Central

Simon, Tony J.

2008-01-01

The cognitive profile of several different populations of children, each with a distinct neurogenetic disorder that has been described as fitting the pattern of a “nonverbal learning disorder”, is examined. In particular, this paper presents the view that a cognitive endophenotype, specified in terms of specific cognitive processes involving the spatial, temporal and attentional domains, can be used to generate an explanation of the neurocognitive foundation of the common impairments found in these disorders. Methods for evaluating cognitive impairments are first compared and contrasted and the concept of “nonverbal learning disorders” is described. The paper then examines data from experimental tests of spatiotemporal and executive cognitive function acquired from children with one of several disorders to determine whether such a cognitive endophenotype holds promise for moving from descriptions of to explanations for the impairments observed and whether prescriptions for therapeutic interventions might flow from such an account. Synopsis This paper presents the cognitive profile observed in children with one of several common genetic syndromes associated with “nonverbal learning disorders”. It introduces the concept of a cognitive endophenotype in order to help explain the similar pattern of impairments across the syndromes. It explores the explanation of diverse impairments in higher-order visual, spatial, temporal, numerical and executive cognitive competencies deriving from origins in more basic attentional and spatial cognitive dysfunctions. The importance of a developmental approach to understanding dysfunction is stressed. PMID:17562581

Construction of a 3-D anatomical model for teaching temporal lobectomy.

PubMed

de Ribaupierre, Sandrine; Wilson, Timothy D

2012-06-01

Although we live and work in 3 dimensional space, most of the anatomical teaching during medical school is done on 2-D (books, TV and computer screens, etc). 3-D spatial abilities are essential for a surgeon but teaching spatial skills in a non-threatening and safe educational environment is a much more difficult pedagogical task. Currently, initial anatomical knowledge formation or specific surgical anatomy techniques, are taught either in the OR itself, or in cadaveric labs; which means that the trainee has only limited exposure. 3-D computer models incorporated into virtual learning environments may provide an intermediate and key step in a blended learning approach for spatially challenging anatomical knowledge formation. Specific anatomical structures and their spatial orientation can be further clinically contextualized through demonstrations of surgical procedures in the 3-D digital environments. Recordings of digital models enable learner reviews, taking as much time as they want, stopping the demonstration, and/or exploring the model to understand the anatomical relation of each structure. We present here how a temporal lobectomy virtual model has been developed to aid residents and fellows conceptualization of the anatomical relationships between different cerebral structures during that procedure. We suggest in comparison to cadaveric dissection, such virtual models represent a cost effective pedagogical methodology providing excellent support for anatomical learning and surgical technique training. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modeling and Intervening across Time in Scientific Inquiry Exploratory Learning Environment

ERIC Educational Resources Information Center

Ting, Choo-Yee; Phon-Amnuaisuk, Somnuk; Chong, Yen-Kuan

2008-01-01

This article aims at discussing how Dynamic Decision Network (DDN) can be employed to tackle the challenges in modeling temporally variable scientific inquiry skills and provision of adaptive pedagogical interventions in INQPRO, a scientific inquiry exploratory learning environment for learning O'level Physics. We begin with an overview of INQPRO…

Learning Space for Food: Exploring Three Home Economics Classrooms

ERIC Educational Resources Information Center

Höijer, Karin; Fjellström, Christina; Hjälmeskog, Karin

2013-01-01

Studies on children's learning about food commonly focus on socialisation within a temporal perspective taking an interest in linear and developmental issues, where the home is assumed as the primary place for learning food skills that should be deepened through education in Home Economics. Home Economics concern topics that are related to our…

Causal Structure Learning over Time: Observations and Interventions

ERIC Educational Resources Information Center

Rottman, Benjamin M.; Keil, Frank C.

2012-01-01

Seven studies examined how people learn causal relationships in scenarios when the variables are temporally dependent--the states of variables are stable over time. When people intervene on X, and Y subsequently changes state compared to before the intervention, people infer that X influences Y. This strategy allows people to learn causal…

Measuring Cognitive and Metacognitive Regulatory Processes during Hypermedia Learning: Issues and Challenges

ERIC Educational Resources Information Center

Azevedo, Roger; Moos, Daniel C.; Johnson, Amy M.; Chauncey, Amber D.

2010-01-01

Self-regulated learning (SRL) with hypermedia environments involves a complex cycle of temporally unfolding cognitive and metacognitive processes that impact students' learning. We present several methodological issues related to treating SRL as an event and strengths and challenges of using online trace methodologies to detect, trace, model, and…

Learning with Hyperlinked Videos--Design Criteria and Efficient Strategies for Using Audiovisual Hypermedia

ERIC Educational Resources Information Center

Zahn, Carmen; Barquero, Beatriz; Schwan, Stephan

2004-01-01

In this article, we discuss the results of an experiment in which we studied two apparently conflicting classes of design principles for instructional hypervideos: (1) those principles derived from work on multimedia learning that emphasize spatio-temporal contiguity and (2) those originating from work on hypermedia learning that favour…

Multi-modal imaging predicts memory performance in normal aging and cognitive decline.

PubMed

Walhovd, K B; Fjell, A M; Dale, A M; McEvoy, L K; Brewer, J; Karow, D S; Salmon, D P; Fennema-Notestine, C

2010-07-01

This study (n=161) related morphometric MR imaging, FDG-PET and APOE genotype to memory scores in normal controls (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD). Stepwise regression analyses focused on morphometric and metabolic characteristics of the episodic memory network: hippocampus, entorhinal, parahippocampal, retrosplenial, posterior cingulate, precuneus, inferior parietal, and lateral orbitofrontal cortices. In NC, hippocampal metabolism predicted learning; entorhinal metabolism predicted recognition; and hippocampal metabolism predicted recall. In MCI, thickness of the entorhinal and precuneus cortices predicted learning, while parahippocampal metabolism predicted recognition. In AD, posterior cingulate cortical thickness predicted learning, while APOE genotype predicted recognition. In the total sample, hippocampal volume and metabolism, cortical thickness of the precuneus, and inferior parietal metabolism predicted learning; hippocampal volume and metabolism, parahippocampal thickness and APOE genotype predicted recognition. Imaging methods appear complementary and differentially sensitive to memory in health and disease. Medial temporal and parietal metabolism and morphometry best explained memory variance. Medial temporal characteristics were related to learning, recall and recognition, while parietal structures only predicted learning. Copyright 2008. Published by Elsevier Inc.

Neural correlates of face gender discrimination learning.

PubMed

Su, Junzhu; Tan, Qingleng; Fang, Fang

2013-04-01

Using combined psychophysics and event-related potentials (ERPs), we investigated the effect of perceptual learning on face gender discrimination and probe the neural correlates of the learning effect. Human subjects were trained to perform a gender discrimination task with male or female faces. Before and after training, they were tested with the trained faces and other faces with the same and opposite genders. ERPs responding to these faces were recorded. Psychophysical results showed that training significantly improved subjects' discrimination performance and the improvement was specific to the trained gender, as well as to the trained identities. The training effect indicates that learning occurs at two levels-the category level (gender) and the exemplar level (identity). ERP analyses showed that the gender and identity learning was associated with the N170 latency reduction at the left occipital-temporal area and the N170 amplitude reduction at the right occipital-temporal area, respectively. These findings provide evidence for the facilitation model and the sharpening model on neuronal plasticity from visual experience, suggesting a faster processing speed and a sparser representation of face induced by perceptual learning.

Individual differences in spatial configuration learning predict the occurrence of intrusive memories.

PubMed

Meyer, Thomas; Smeets, Tom; Giesbrecht, Timo; Quaedflieg, Conny W E M; Girardelli, Marta M; Mackay, Georgina R N; Merckelbach, Harald

2013-03-01

The dual-representation model of posttraumatic stress disorder (PTSD; Brewin, Gregory, Lipton, & Burgess, Psychological Review, 117, 210-232 2010) argues that intrusions occur when people fail to construct context-based representations during adverse experiences. The present study tested a specific prediction flowing from this model. In particular, we investigated whether the efficiency of temporal-lobe-based spatial configuration learning would account for individual differences in intrusive experiences and physiological reactivity in the laboratory. Participants (N = 82) completed the contextual cuing paradigm, which assesses spatial configuration learning that is believed to depend on associative encoding in the parahippocampus. They were then shown a trauma film. Afterward, startle responses were quantified during presentation of trauma reminder pictures versus unrelated neutral and emotional pictures. PTSD symptoms were recorded in the week following participation. Better configuration learning performance was associated with fewer perceptual intrusions, r = -.33, p < .01, but was unrelated to physiological responses to trauma reminder images (ps > .46) and had no direct effect on intrusion-related distress and overall PTSD symptoms, rs > -.12, ps > .29. However, configuration learning performance tended to be associated with reduced physiological responses to unrelated negative images, r = -.20, p = .07. Thus, while spatial configuration learning appears to be unrelated to affective responding to trauma reminders, our overall findings support the idea that the context-based memory system helps to reduce intrusions.

The role of the basal ganglia in learning and memory: insight from Parkinson's disease.

PubMed

Foerde, Karin; Shohamy, Daphna

2011-11-01

It has long been known that memory is not a single process. Rather, there are different kinds of memory that are supported by distinct neural systems. This idea stemmed from early findings of dissociable patterns of memory impairments in patients with selective damage to different brain regions. These studies highlighted the role of the basal ganglia in non-declarative memory, such as procedural or habit learning, contrasting it with the known role of the medial temporal lobes in declarative memory. In recent years, major advances across multiple areas of neuroscience have revealed an important role for the basal ganglia in motivation and decision making. These findings have led to new discoveries about the role of the basal ganglia in learning and highlighted the essential role of dopamine in specific forms of learning. Here we review these recent advances with an emphasis on novel discoveries from studies of learning in patients with Parkinson's disease. We discuss how these findings promote the development of current theories away from accounts that emphasize the verbalizability of the contents of memory and towards a focus on the specific computations carried out by distinct brain regions. Finally, we discuss new challenges that arise in the face of accumulating evidence for dynamic and interconnected memory systems that jointly contribute to learning. Copyright © 2011 Elsevier Inc. All rights reserved.

Implicit and Explicit Contributions to Object Recognition: Evidence from Rapid Perceptual Learning

PubMed Central

Hassler, Uwe; Friese, Uwe; Gruber, Thomas

2012-01-01

The present study investigated implicit and explicit recognition processes of rapidly perceptually learned objects by means of steady-state visual evoked potentials (SSVEP). Participants were initially exposed to object pictures within an incidental learning task (living/non-living categorization). Subsequently, degraded versions of some of these learned pictures were presented together with degraded versions of unlearned pictures and participants had to judge, whether they recognized an object or not. During this test phase, stimuli were presented at 15 Hz eliciting an SSVEP at the same frequency. Source localizations of SSVEP effects revealed for implicit and explicit processes overlapping activations in orbito-frontal and temporal regions. Correlates of explicit object recognition were additionally found in the superior parietal lobe. These findings are discussed to reflect facilitation of object-specific processing areas within the temporal lobe by an orbito-frontal top-down signal as proposed by bi-directional accounts of object recognition. PMID:23056558

Identification of a motor to auditory pathway important for vocal learning

PubMed Central

Roberts, Todd F.; Hisey, Erin; Tanaka, Masashi; Kearney, Matthew; Chattree, Gaurav; Yang, Cindy F.; Shah, Nirao M.; Mooney, Richard

2017-01-01

Summary Learning to vocalize depends on the ability to adaptively modify the temporal and spectral features of vocal elements. Neurons that convey motor-related signals to the auditory system are theorized to facilitate vocal learning, but the identity and function of such neurons remain unknown. Here we identify a previously unknown neuron type in the songbird brain that transmits vocal motor signals to the auditory cortex. Genetically ablating these neurons in juveniles disrupted their ability to imitate features of an adult tutor’s song. Ablating these neurons in adults had little effect on previously learned songs, but interfered with their ability to adaptively modify the duration of vocal elements and largely prevented the degradation of song’s temporal features normally caused by deafening. These findings identify a motor to auditory circuit essential to vocal imitation and to the adaptive modification of vocal timing. PMID:28504672

In a year, memory will benefit from learning, tomorrow it won't: distance and construal level effects on the basis of metamemory judgments.

PubMed

Halamish, Vered; Nussinson, Ravit; Ben-Ari, Liat

2013-09-01

Metamemory judgments may rely on 2 bases of information: subjective experience and abstract theories about memory. On the basis of construal level theory, we predicted that psychological distance and construal level (i.e., concrete vs. abstract thinking) would have a qualitative impact on the relative reliance on these 2 bases: When considering learning from proximity or under a low-construal mindset, learners would rely more heavily on their experience, whereas when considering learning from a distance or under a high-construal mindset, they would rely more heavily on their abstract theories. Consistent with this prediction, results of 2 experiments revealed that temporal distance (Experiment 1) and construal level (Experiment 2) affected the stability bias--the failure to predict the benefits of learning. When considering learning from proximity or using a low-construal mindset, participants relied less heavily on their theory regarding the benefits of learning and were therefore insensitive to future learning. However, when considering learning from temporal distance or using a high-construal mindset, participants relied more heavily on their theory and were therefore better able to predict the benefits of future learning, thus overcoming the stability bias. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Effects of feedback delay on learning from positive and negative feedback in patients with Parkinson's disease off medication.

PubMed

Weismüller, Benjamin; Ghio, Marta; Logmin, Kazimierz; Hartmann, Christian; Schnitzler, Alfons; Pollok, Bettina; Südmeyer, Martin; Bellebaum, Christian

2018-05-11

Phasic dopamine (DA) signals conveyed from the substantia nigra to the striatum and the prefrontal cortex crucially affect learning from feedback, with DA bursts facilitating learning from positive feedback and DA dips facilitating learning from negative feedback. Consequently, diminished nigro-striatal dopamine levels as in unmedicated patients suffering from Parkinson's Disease (PD) have been shown to lead to a negative learning bias. Recent studies suggested a diminished striatal contribution to feedback processing when the outcome of an action is temporally delayed. This study investigated whether the bias towards negative feedback learning induced by a lack of DA in PD patients OFF medication is modulated by feedback delay. To this end, PD patients OFF medication and healthy controls completed a probabilistic selection task, in which feedback was given immediately (after 800 ms) or delayed (after 6800 ms). PD patients were impaired in immediate but not delayed feedback learning. However, differences in the preference for positive/negative learning between patients and controls were seen for both learning from immediate and delayed feedback, with evidence of stronger negative learning in patients than controls. A Bayesian analysis of the data supports the conclusion that feedback timing did not affect the learning bias in the patients. These results hint at reduced, but still relevant nigro-striatal contribution to feedback learning, when feedback is delayed. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Effects of Theta Precession on Spatial Learning and Simplicial Complex Dynamics in a Topological Model of the Hippocampal Spatial Map

PubMed Central

Arai, Mamiko; Brandt, Vicky; Dabaghian, Yuri

2014-01-01

Learning arises through the activity of large ensembles of cells, yet most of the data neuroscientists accumulate is at the level of individual neurons; we need models that can bridge this gap. We have taken spatial learning as our starting point, computationally modeling the activity of place cells using methods derived from algebraic topology, especially persistent homology. We previously showed that ensembles of hundreds of place cells could accurately encode topological information about different environments (“learn” the space) within certain values of place cell firing rate, place field size, and cell population; we called this parameter space the learning region. Here we advance the model both technically and conceptually. To make the model more physiological, we explored the effects of theta precession on spatial learning in our virtual ensembles. Theta precession, which is believed to influence learning and memory, did in fact enhance learning in our model, increasing both speed and the size of the learning region. Interestingly, theta precession also increased the number of spurious loops during simplicial complex formation. We next explored how downstream readout neurons might define co-firing by grouping together cells within different windows of time and thereby capturing different degrees of temporal overlap between spike trains. Our model's optimum coactivity window correlates well with experimental data, ranging from ∼150–200 msec. We further studied the relationship between learning time, window width, and theta precession. Our results validate our topological model for spatial learning and open new avenues for connecting data at the level of individual neurons to behavioral outcomes at the neuronal ensemble level. Finally, we analyzed the dynamics of simplicial complex formation and loop transience to propose that the simplicial complex provides a useful working description of the spatial learning process. PMID:24945927

Learning alters theta amplitude, theta-gamma coupling and neuronal synchronization in inferotemporal cortex.

PubMed

Kendrick, Keith M; Zhan, Yang; Fischer, Hanno; Nicol, Alister U; Zhang, Xuejuan; Feng, Jianfeng

2011-06-09

How oscillatory brain rhythms alone, or in combination, influence cortical information processing to support learning has yet to be fully established. Local field potential and multi-unit neuronal activity recordings were made from 64-electrode arrays in the inferotemporal cortex of conscious sheep during and after visual discrimination learning of face or object pairs. A neural network model has been developed to simulate and aid functional interpretation of learning-evoked changes. Following learning the amplitude of theta (4-8 Hz), but not gamma (30-70 Hz) oscillations was increased, as was the ratio of theta to gamma. Over 75% of electrodes showed significant coupling between theta phase and gamma amplitude (theta-nested gamma). The strength of this coupling was also increased following learning and this was not simply a consequence of increased theta amplitude. Actual discrimination performance was significantly correlated with theta and theta-gamma coupling changes. Neuronal activity was phase-locked with theta but learning had no effect on firing rates or the magnitude or latencies of visual evoked potentials during stimuli. The neural network model developed showed that a combination of fast and slow inhibitory interneurons could generate theta-nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity in the model similar changes were produced as in inferotemporal cortex after learning. The model showed that these changes could potentiate the firing of downstream neurons by a temporal desynchronization of excitatory neuron output without increasing the firing frequencies of the latter. This desynchronization effect was confirmed in IT neuronal activity following learning and its magnitude was correlated with discrimination performance. Face discrimination learning produces significant increases in both theta amplitude and the strength of theta-gamma coupling in the inferotemporal cortex which are correlated with behavioral performance. A network model which can reproduce these changes suggests that a key function of such learning-evoked alterations in theta and theta-nested gamma activity may be increased temporal desynchronization in neuronal firing leading to optimal timing of inputs to downstream neural networks potentiating their responses. In this way learning can produce potentiation in neural networks simply through altering the temporal pattern of their inputs.

Learning alters theta amplitude, theta-gamma coupling and neuronal synchronization in inferotemporal cortex

PubMed Central

2011-01-01

Background How oscillatory brain rhythms alone, or in combination, influence cortical information processing to support learning has yet to be fully established. Local field potential and multi-unit neuronal activity recordings were made from 64-electrode arrays in the inferotemporal cortex of conscious sheep during and after visual discrimination learning of face or object pairs. A neural network model has been developed to simulate and aid functional interpretation of learning-evoked changes. Results Following learning the amplitude of theta (4-8 Hz), but not gamma (30-70 Hz) oscillations was increased, as was the ratio of theta to gamma. Over 75% of electrodes showed significant coupling between theta phase and gamma amplitude (theta-nested gamma). The strength of this coupling was also increased following learning and this was not simply a consequence of increased theta amplitude. Actual discrimination performance was significantly correlated with theta and theta-gamma coupling changes. Neuronal activity was phase-locked with theta but learning had no effect on firing rates or the magnitude or latencies of visual evoked potentials during stimuli. The neural network model developed showed that a combination of fast and slow inhibitory interneurons could generate theta-nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity in the model similar changes were produced as in inferotemporal cortex after learning. The model showed that these changes could potentiate the firing of downstream neurons by a temporal desynchronization of excitatory neuron output without increasing the firing frequencies of the latter. This desynchronization effect was confirmed in IT neuronal activity following learning and its magnitude was correlated with discrimination performance. Conclusions Face discrimination learning produces significant increases in both theta amplitude and the strength of theta-gamma coupling in the inferotemporal cortex which are correlated with behavioral performance. A network model which can reproduce these changes suggests that a key function of such learning-evoked alterations in theta and theta-nested gamma activity may be increased temporal desynchronization in neuronal firing leading to optimal timing of inputs to downstream neural networks potentiating their responses. In this way learning can produce potentiation in neural networks simply through altering the temporal pattern of their inputs. PMID:21658251

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.

Arterial spin labeling reveals relationships between resting cerebral perfusion and motor learning in Parkinson's disease.

PubMed

Barzgari, Amy; Sojkova, Jitka; Maritza Dowling, N; Pozorski, Vincent; Okonkwo, Ozioma C; Starks, Erika J; Oh, Jennifer; Thiesen, Frances; Wey, Alexandra; Nicholas, Christopher R; Johnson, Sterling; Gallagher, Catherine L

2018-05-09

Parkinson's disease (PD) is an age-related neurodegenerative disease that produces changes in movement, cognition, sleep, and autonomic function. Motor learning involves acquisition of new motor skills through practice, and is affected by PD. The purpose of the present study was to evaluate regional differences in resting cerebral blood flow (rCBF), measured using arterial spin labeling (ASL) MRI, during a finger-typing task of motor skill acquisition in PD patients compared to age- and gender-matched controls. Voxel-wise multiple linear regression models were used to examine the relationship between rCBF and several task variables, including initial speed, proficiency gain, and accuracy. In these models, a task-by-disease group interaction term was included to investigate where the relationship between rCBF and task performance was influenced by PD. At baseline, perfusion was lower in PD subjects than controls in the right occipital cortex. The task-by-disease group interaction for initial speed was significantly related to rCBF (p < 0.05, corrected) in several brain regions involved in motor learning, including the occipital, parietal, and temporal cortices, cerebellum, anterior cingulate, and the superior and middle frontal gyri. In these regions, PD patients showed higher rCBF, and controls lower rCBF, with improved performance. Within the control group, proficiency gain over 12 typing trials was related to greater rCBF in cerebellar, occipital, and temporal cortices. These results suggest that higher rCBF within networks involved in motor learning enable PD patients to compensate for disease-related deficits.

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

Adrenergic Transmission Facilitates Extinction of Conditional Fear in Mice

ERIC Educational Resources Information Center

Barad, Mark; Cain, Christopher K.; Blouin, Ashley M.

2004-01-01

Extinction of classically conditioned fear, like its acquisition, is active learning, but little is known about its molecular mechanisms. We recently reported that temporal massing of conditional stimulus (CS) presentations improves extinction memory acquisition, and suggested that temporal spacing was less effective because individual CS…

HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition.

PubMed

James, Alex Pappachen; Fedorova, Irina; Ibrayev, Timur; Kudithipudi, Dhireesha

2017-06-01

Hierarchical Temporal Memory (HTM) is an online machine learning algorithm that emulates the neo-cortex. The development of a scalable on-chip HTM architecture is an open research area. The two core substructures of HTM are spatial pooler and temporal memory. In this work, we propose a new Spatial Pooler circuit design with parallel memristive crossbar arrays for the 2D columns. The proposed design was validated on two different benchmark datasets, face recognition, and speech recognition. The circuits are simulated and analyzed using a practical memristor device model and 0.18 μm IBM CMOS technology model. The databases AR, YALE, ORL, and UFI, are used to test the performance of the design in face recognition. TIMIT dataset is used for the speech recognition.

Temporally contiguous pencast instruction promotes meaningful learning for dental and dental hygiene students in physiology.

PubMed

Roesch, Darren M

2014-01-01

Smartpens allow for the creation of computerized "pencasts" that combine voice narration with handwritten notes and illustrations. The purpose of this study was to test the effects of voluntary participation in extracurricular instruction with a pencast on student learning. Dental and dental hygiene students were given instruction in a complex physiological topic using lecture and static slides. An Internet link to a pencast that covered the complex topic in a more temporally contiguous fashion was also provided for voluntary review. The students were given a multiple-choice exam that consisted of retention and transfer test questions. Sixty-nine percent of the students who did not watch the pencast and 89 percent of the students who watched the pencast answered the retention test question correctly (p=0.08). Fifty-four percent of the students who did not watch the pencast and 90 percent of the students who watched the pencast answered the transfer test question correctly (p=0.005). This finding indicates that students who watched the pencast performed better on a transfer test, a measurement of meaningful learning, than students who received only the narrated instruction with static images. This supports the hypothesis that temporally contiguous instruction promotes more meaningful learning than lecture accompanied only by static slide images.

Learning Spatially-Smooth Mappings in Non-Rigid Structure from Motion

PubMed Central

Hamsici, Onur C.; Gotardo, Paulo F.U.; Martinez, Aleix M.

2013-01-01

Non-rigid structure from motion (NRSFM) is a classical underconstrained problem in computer vision. A common approach to make NRSFM more tractable is to constrain 3D shape deformation to be smooth over time. This constraint has been used to compress the deformation model and reduce the number of unknowns that are estimated. However, temporal smoothness cannot be enforced when the data lacks temporal ordering and its benefits are less evident when objects undergo abrupt deformations. This paper proposes a new NRSFM method that addresses these problems by considering deformations as spatial variations in shape space and then enforcing spatial, rather than temporal, smoothness. This is done by modeling each 3D shape coefficient as a function of its input 2D shape. This mapping is learned in the feature space of a rotation invariant kernel, where spatial smoothness is intrinsically defined by the mapping function. As a result, our model represents shape variations compactly using custom-built coefficient bases learned from the input data, rather than a pre-specified set such as the Discrete Cosine Transform. The resulting kernel-based mapping is a by-product of the NRSFM solution and leads to another fundamental advantage of our approach: for a newly observed 2D shape, its 3D shape is recovered by simply evaluating the learned function. PMID:23946937

Learning Spatially-Smooth Mappings in Non-Rigid Structure from Motion.

PubMed

Hamsici, Onur C; Gotardo, Paulo F U; Martinez, Aleix M

2012-01-01

Non-rigid structure from motion (NRSFM) is a classical underconstrained problem in computer vision. A common approach to make NRSFM more tractable is to constrain 3D shape deformation to be smooth over time. This constraint has been used to compress the deformation model and reduce the number of unknowns that are estimated. However, temporal smoothness cannot be enforced when the data lacks temporal ordering and its benefits are less evident when objects undergo abrupt deformations. This paper proposes a new NRSFM method that addresses these problems by considering deformations as spatial variations in shape space and then enforcing spatial, rather than temporal, smoothness. This is done by modeling each 3D shape coefficient as a function of its input 2D shape. This mapping is learned in the feature space of a rotation invariant kernel, where spatial smoothness is intrinsically defined by the mapping function. As a result, our model represents shape variations compactly using custom-built coefficient bases learned from the input data, rather than a pre-specified set such as the Discrete Cosine Transform. The resulting kernel-based mapping is a by-product of the NRSFM solution and leads to another fundamental advantage of our approach: for a newly observed 2D shape, its 3D shape is recovered by simply evaluating the learned function.

Neurons with two sites of synaptic integration learn invariant representations.

PubMed

Körding, K P; König, P

2001-12-01

Neurons in mammalian cerebral cortex combine specific responses with respect to some stimulus features with invariant responses to other stimulus features. For example, in primary visual cortex, complex cells code for orientation of a contour but ignore its position to a certain degree. In higher areas, such as the inferotemporal cortex, translation-invariant, rotation-invariant, and even view point-invariant responses can be observed. Such properties are of obvious interest to artificial systems performing tasks like pattern recognition. It remains to be resolved how such response properties develop in biological systems. Here we present an unsupervised learning rule that addresses this problem. It is based on a neuron model with two sites of synaptic integration, allowing qualitatively different effects of input to basal and apical dendritic trees, respectively. Without supervision, the system learns to extract invariance properties using temporal or spatial continuity of stimuli. Furthermore, top-down information can be smoothly integrated in the same framework. Thus, this model lends a physiological implementation to approaches of unsupervised learning of invariant-response properties.

A model of color vision with a robot system

NASA Astrophysics Data System (ADS)

Wang, Haihui

2006-01-01

In this paper, we propose to generalize the saccade target method and state that perceptual stability in general arises by learning the effects one's actions have on sensor responses. The apparent visual stability of color percept across saccadic eye movements can be explained by positing that perception involves observing how sensory input changes in response to motor activities. The changes related to self-motion can be learned, and once learned, used to form stable percepts. The variation of sensor data in response to a motor act is therefore a requirement for stable perception rather than something that has to be compensated for in order to perceive a stable world. In this paper, we have provided a simple implementation of this sensory-motor contingency view of perceptual stability. We showed how a straightforward application of the temporal difference enhancement learning technique yielding color percepts that are stable across saccadic eye movements, even though the raw sensor input may change radically.

Neural correlates of reinforcement learning and social preferences in competitive bidding.

PubMed

van den Bos, Wouter; Talwar, Arjun; McClure, Samuel M

2013-01-30

In competitive social environments, people often deviate from what rational choice theory prescribes, resulting in losses or suboptimal monetary gains. We investigate how competition affects learning and decision-making in a common value auction task. During the experiment, groups of five human participants were simultaneously scanned using MRI while playing the auction task. We first demonstrate that bidding is well characterized by reinforcement learning with biased reward representations dependent on social preferences. Indicative of reinforcement learning, we found that estimated trial-by-trial prediction errors correlated with activity in the striatum and ventromedial prefrontal cortex. Additionally, we found that individual differences in social preferences were related to activity in the temporal-parietal junction and anterior insula. Connectivity analyses suggest that monetary and social value signals are integrated in the ventromedial prefrontal cortex and striatum. Based on these results, we argue for a novel mechanistic account for the integration of reinforcement history and social preferences in competitive decision-making.

Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology.

PubMed

VoPham, Trang; Hart, Jaime E; Laden, Francine; Chiang, Yao-Yi

2018-04-17

Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.

β-Adrenergic Receptors Regulate the Acquisition and Consolidation Phases of Aversive Memory Formation Through Distinct, Temporally Regulated Signaling Pathways

PubMed Central

Schiff, Hillary C; Johansen, Joshua P; Hou, Mian; Bush, David E A; Smith, Emily K; Klein, JoAnna E; LeDoux, Joseph E; Sears, Robert M

2017-01-01

Memory formation requires the temporal coordination of molecular events and cellular processes following a learned event. During Pavlovian threat (fear) conditioning (PTC), sensory and neuromodulatory inputs converge on post-synaptic neurons within the lateral nucleus of the amygdala (LA). By activating an intracellular cascade of signaling molecules, these G-protein-coupled neuromodulatory receptors are capable of recruiting a diverse profile of plasticity-related proteins. Here we report that norepinephrine, through its actions on β-adrenergic receptors (βARs), modulates aversive memory formation following PTC through two molecularly and temporally distinct signaling mechanisms. Specifically, using behavioral pharmacology and biochemistry in adult rats, we determined that βAR activity during, but not after PTC training initiates the activation of two plasticity-related targets: AMPA receptors (AMPARs) for memory acquisition and short-term memory and extracellular regulated kinase (ERK) for consolidating the learned association into a long-term memory. These findings reveal that βAR activity during, but not following PTC sets in motion cascading molecular events for the acquisition (AMPARs) and subsequent consolidation (ERK) of learned associations. PMID:27762270

β-Adrenergic Receptors Regulate the Acquisition and Consolidation Phases of Aversive Memory Formation Through Distinct, Temporally Regulated Signaling Pathways.

PubMed

Schiff, Hillary C; Johansen, Joshua P; Hou, Mian; Bush, David E A; Smith, Emily K; Klein, JoAnna E; LeDoux, Joseph E; Sears, Robert M

2017-03-01

Memory formation requires the temporal coordination of molecular events and cellular processes following a learned event. During Pavlovian threat (fear) conditioning (PTC), sensory and neuromodulatory inputs converge on post-synaptic neurons within the lateral nucleus of the amygdala (LA). By activating an intracellular cascade of signaling molecules, these G-protein-coupled neuromodulatory receptors are capable of recruiting a diverse profile of plasticity-related proteins. Here we report that norepinephrine, through its actions on β-adrenergic receptors (βARs), modulates aversive memory formation following PTC through two molecularly and temporally distinct signaling mechanisms. Specifically, using behavioral pharmacology and biochemistry in adult rats, we determined that βAR activity during, but not after PTC training initiates the activation of two plasticity-related targets: AMPA receptors (AMPARs) for memory acquisition and short-term memory and extracellular regulated kinase (ERK) for consolidating the learned association into a long-term memory. These findings reveal that βAR activity during, but not following PTC sets in motion cascading molecular events for the acquisition (AMPARs) and subsequent consolidation (ERK) of learned associations.

Distributed practice can boost evaluative conditioning by increasing memory for the stimulus pairs.

PubMed

Richter, Jasmin; Gast, Anne

2017-09-01

When presenting a neutral stimulus (CS) in close temporal and spatial proximity to a positive or negative stimulus (US) the former is often observed to adopt the valence of the latter, a phenomenon named evaluative conditioning (EC). It is already well established that under most conditions, contingency awareness is important for an EC effect to occur. In addition to that, some findings suggest that awareness of the stimulus pairs is not only relevant during the learning phase, but that it is also relevant whether memory for the pairings is still available during the measurement phase. As previous research has shown that memory is better after temporally distributed than after contiguous (massed) repetitions, it seems plausible that also EC effects are moderated by distributed practice manipulations. This was tested in the current studies. In two experiments with successful distributed practice manipulations on memory, we show that also the magnitude of the EC effect was larger for pairs learned under spaced compared to massed conditions. Both effects, on memory and on EC, are found after a within-participant and after a between-participant manipulation. However, we did not find significant differences in the EC effect for different conditions of spaced practice. These findings are in line with the assumption that EC is based on similar processes as memory for the pairings. Copyright © 2017 Elsevier B.V. All rights reserved.

Neural Correlates of Letter Reversal in Children and Adults

PubMed Central

Kalra, Priya; Yee, Debbie; Sinha, Pawan; Gabrieli, John D. E.

2014-01-01

Children often make letter reversal errors when first learning to read and write, even for letters whose reversed forms do not appear in normal print. However, the brain basis of such letter reversal in children learning to read is unknown. The present study compared the neuroanatomical correlates (via functional magnetic resonance imaging) and the electrophysiological correlates (via event-related potentials or ERPs) of this phenomenon in children, ages 5–12, relative to young adults. When viewing reversed letters relative to typically oriented letters, adults exhibited widespread occipital, parietal, and temporal lobe activations, including activation in the functionally localized visual word form area (VWFA) in left occipito-temporal cortex. Adults exhibited significantly greater activation than children in all of these regions; children only exhibited such activation in a limited frontal region. Similarly, on the P1 and N170 ERP components, adults exhibited significantly greater differences between typical and reversed letters than children, who failed to exhibit significant differences between typical and reversed letters. These findings indicate that adults distinguish typical and reversed letters in the early stages of specialized brain processing of print, but that children do not recognize this distinction during the early stages of processing. Specialized brain processes responsible for early stages of letter perception that distinguish between typical and reversed letters may develop slowly and remain immature even in older children who no longer produce letter reversals in their writing. PMID:24859328

Human motion tracking by temporal-spatial local gaussian process experts.

PubMed

Zhao, Xu; Fu, Yun; Liu, Yuncai

2011-04-01

Human pose estimation via motion tracking systems can be considered as a regression problem within a discriminative framework. It is always a challenging task to model the mapping from observation space to state space because of the high-dimensional characteristic in the multimodal conditional distribution. In order to build the mapping, existing techniques usually involve a large set of training samples in the learning process which are limited in their capability to deal with multimodality. We propose, in this work, a novel online sparse Gaussian Process (GP) regression model to recover 3-D human motion in monocular videos. Particularly, we investigate the fact that for a given test input, its output is mainly determined by the training samples potentially residing in its local neighborhood and defined in the unified input-output space. This leads to a local mixture GP experts system composed of different local GP experts, each of which dominates a mapping behavior with the specific covariance function adapting to a local region. To handle the multimodality, we combine both temporal and spatial information therefore to obtain two categories of local experts. The temporal and spatial experts are integrated into a seamless hybrid system, which is automatically self-initialized and robust for visual tracking of nonlinear human motion. Learning and inference are extremely efficient as all the local experts are defined online within very small neighborhoods. Extensive experiments on two real-world databases, HumanEva and PEAR, demonstrate the effectiveness of our proposed model, which significantly improve the performance of existing models.

A simple computational algorithm of model-based choice preference.

PubMed

Toyama, Asako; Katahira, Kentaro; Ohira, Hideki

2017-08-01

A broadly used computational framework posits that two learning systems operate in parallel during the learning of choice preferences-namely, the model-free and model-based reinforcement-learning systems. In this study, we examined another possibility, through which model-free learning is the basic system and model-based information is its modulator. Accordingly, we proposed several modified versions of a temporal-difference learning model to explain the choice-learning process. Using the two-stage decision task developed by Daw, Gershman, Seymour, Dayan, and Dolan (2011), we compared their original computational model, which assumes a parallel learning process, and our proposed models, which assume a sequential learning process. Choice data from 23 participants showed a better fit with the proposed models. More specifically, the proposed eligibility adjustment model, which assumes that the environmental model can weight the degree of the eligibility trace, can explain choices better under both model-free and model-based controls and has a simpler computational algorithm than the original model. In addition, the forgetting learning model and its variation, which assume changes in the values of unchosen actions, substantially improved the fits to the data. Overall, we show that a hybrid computational model best fits the data. The parameters used in this model succeed in capturing individual tendencies with respect to both model use in learning and exploration behavior. This computational model provides novel insights into learning with interacting model-free and model-based components.

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

PubMed Central

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

2014-01-01

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

Electrophysiological evidence of statistical learning of long-distance dependencies in 8-month-old preterm and full-term infants.

PubMed

Kabdebon, C; Pena, M; Buiatti, M; Dehaene-Lambertz, G

2015-09-01

Using electroencephalography, we examined 8-month-old infants' ability to discover a systematic dependency between the first and third syllables of successive words, concatenated into a monotonous speech stream, and to subsequently generalize this regularity to new items presented in isolation. Full-term and preterm infants, while exposed to the stream, displayed a significant entrainment (phase-locking) to the syllabic and word frequencies, demonstrating that they were sensitive to the word unit. The acquisition of the systematic dependency defining words was confirmed by the significantly different neural responses to rule-words and part-words subsequently presented during the test phase. Finally, we observed a correlation between syllabic entrainment during learning and the difference in phase coherence between the test conditions (rule-words vs part-words) suggesting that temporal processing of the syllable unit might be crucial in linguistic learning. No group difference was observed suggesting that non-adjacent statistical computations are already robust at 8 months, even in preterm infants, and thus develop during the first year of life, earlier than expected from behavioral studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Moments of Teaching and Learning in a Children's Hospital: Affects, Textures, and Temporalities

ERIC Educational Resources Information Center

Ehret, Christian

2018-01-01

Although nonrepresentational theory has enriched anthropologists' understanding of affect in social and cultural life, it has a short history in education research, where representational paradigms dominate. This article develops nonrepresentational theories of moments, temporal textures, and affective pedagogies in order to evoke affects of…

Time, Space, and Dialogue in a Distance-Learning Class Discussion Board

ERIC Educational Resources Information Center

Kabat, Katalin J.

2014-01-01

The present study investigates the temporal elements affecting asynchronous discussion board messages over a semester, ways in which time is contextualized in space and content, and students' spatio-temporal practices within fixed frames. The theoretical framework uses Lefebvre's rhythm analysis, Bakhtin's chronotope, and…

Effects of Cueing in Auditory Temporal Masking

ERIC Educational Resources Information Center

Zhang, Ting; Formby, Craig

2007-01-01

Purpose: In a landmark study, B. A. Wright et al. (1997) reported an apparent backward-masking deficit in language-learning-impaired children. Subsequently, the controversial interpretation of those results has been influential in guiding treatments for childhood language problems. This study revisited the temporal-masking paradigm reported by B.…

Route Learning Impairment in Temporal Lobe Epilepsy

PubMed Central

Bell, Brian D.

2012-01-01

Memory impairment on neuropsychological tests is relatively common in temporal lobe epilepsy (TLE) patients. But memory rarely has been evaluated in more naturalistic settings. This study assessed TLE (n = 19) and control (n = 32) groups on a real-world route learning (RL) test. Compared to the controls, the TLE group committed significantly more total errors across the three RL test trials. RL errors correlated significantly with standardized auditory and visual memory and visual-perceptual test scores in the TLE group. In the TLE subset for whom hippocampal data were available (n = 14), RL errors also correlated significantly with left hippocampal volume. This is one of the first studies to demonstrate real-world memory impairment in TLE patients and its association with both mesial temporal lobe integrity and standardized memory test performance. The results support the ecological validity of clinical neuropsychological assessment. PMID:23041173

Prereader to beginning reader: changes induced by reading acquisition in print and speech brain networks.

PubMed

Chyl, Katarzyna; Kossowski, Bartosz; Dębska, Agnieszka; Łuniewska, Magdalena; Banaszkiewicz, Anna; Żelechowska, Agata; Frost, Stephen J; Mencl, William Einar; Wypych, Marek; Marchewka, Artur; Pugh, Kenneth R; Jednoróg, Katarzyna

2018-01-01

Literacy acquisition is a demanding process that induces significant changes in the brain, especially in the spoken and written language networks. Nevertheless, large-scale paediatric fMRI studies are still limited. We analyzed fMRI data to show how individual differences in reading performance correlate with brain activation for speech and print in 111 children attending kindergarten or first grade and examined group differences between a matched subset of emergent-readers and prereaders. Across the entire cohort, individual differences analysis revealed that reading skill was positively correlated with the magnitude of activation difference between words and symbol strings in left superior temporal, inferior frontal and fusiform gyri. Group comparisons of the matched subset of pre- and emergent-readers showed higher activity for emergent-readers in left inferior frontal, precentral, and postcentral gyri. Individual differences in activation for natural versus vocoded speech were also positively correlated with reading skill, primarily in the left temporal cortex. However, in contrast to studies on adult illiterates, group comparisons revealed higher activity in prereaders compared to readers in the frontal lobes. Print-speech coactivation was observed only in readers and individual differences analyses revealed a positive correlation between convergence and reading skill in the left superior temporal sulcus. These results emphasise that a child's brain undergoes several modifications to both visual and oral language systems in the process of learning to read. They also suggest that print-speech convergence is a hallmark of acquiring literacy. © 2017 Association for Child and Adolescent Mental Health.