Hebbian learning of hand-centred representations in a hierarchical neural network model of the primate visual system

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Born, Jannis; Stringer, Simon M.

2017-01-01

A subset of neurons in the posterior parietal and premotor areas of the primate brain respond to the locations of visual targets in a hand-centred frame of reference. Such hand-centred visual representations are thought to play an important role in visually-guided reaching to target locations in space. In this paper we show how a biologically plausible, Hebbian learning mechanism may account for the development of localized hand-centred representations in a hierarchical neural network model of the primate visual system, VisNet. The hand-centered neurons developed in the model use an invariance learning mechanism known as continuous transformation (CT) learning. In contrast to previous theoretical proposals for the development of hand-centered visual representations, CT learning does not need a memory trace of recent neuronal activity to be incorporated in the synaptic learning rule. Instead, CT learning relies solely on a Hebbian learning rule, which is able to exploit the spatial overlap that naturally occurs between successive images of a hand-object configuration as it is shifted across different retinal locations due to saccades. Our simulations show how individual neurons in the network model can learn to respond selectively to target objects in particular locations with respect to the hand, irrespective of where the hand-object configuration occurs on the retina. The response properties of these hand-centred neurons further generalise to localised receptive fields in the hand-centred space when tested on novel hand-object configurations that have not been explored during training. Indeed, even when the network is trained with target objects presented across a near continuum of locations around the hand during training, the model continues to develop hand-centred neurons with localised receptive fields in hand-centred space. With the help of principal component analysis, we provide the first theoretical framework that explains the behavior of Hebbian learning

Hebbian learning of hand-centred representations in a hierarchical neural network model of the primate visual system.

Science.gov (United States)

Born, Jannis; Galeazzi, Juan M; Stringer, Simon M

2017-01-01

A subset of neurons in the posterior parietal and premotor areas of the primate brain respond to the locations of visual targets in a hand-centred frame of reference. Such hand-centred visual representations are thought to play an important role in visually-guided reaching to target locations in space. In this paper we show how a biologically plausible, Hebbian learning mechanism may account for the development of localized hand-centred representations in a hierarchical neural network model of the primate visual system, VisNet. The hand-centered neurons developed in the model use an invariance learning mechanism known as continuous transformation (CT) learning. In contrast to previous theoretical proposals for the development of hand-centered visual representations, CT learning does not need a memory trace of recent neuronal activity to be incorporated in the synaptic learning rule. Instead, CT learning relies solely on a Hebbian learning rule, which is able to exploit the spatial overlap that naturally occurs between successive images of a hand-object configuration as it is shifted across different retinal locations due to saccades. Our simulations show how individual neurons in the network model can learn to respond selectively to target objects in particular locations with respect to the hand, irrespective of where the hand-object configuration occurs on the retina. The response properties of these hand-centred neurons further generalise to localised receptive fields in the hand-centred space when tested on novel hand-object configurations that have not been explored during training. Indeed, even when the network is trained with target objects presented across a near continuum of locations around the hand during training, the model continues to develop hand-centred neurons with localised receptive fields in hand-centred space. With the help of principal component analysis, we provide the first theoretical framework that explains the behavior of Hebbian learning

Neuroanatomical heterogeneity of schizophrenia revealed by semi-supervised machine learning methods.

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Honnorat, Nicolas; Dong, Aoyan; Meisenzahl-Lechner, Eva; Koutsouleris, Nikolaos; Davatzikos, Christos

2017-12-20

Schizophrenia is associated with heterogeneous clinical symptoms and neuroanatomical alterations. In this work, we aim to disentangle the patterns of neuroanatomical alterations underlying a heterogeneous population of patients using a semi-supervised clustering method. We apply this strategy to a cohort of patients with schizophrenia of varying extends of disease duration, and we describe the neuroanatomical, demographic and clinical characteristics of the subtypes discovered. We analyze the neuroanatomical heterogeneity of 157 patients diagnosed with Schizophrenia, relative to a control population of 169 subjects, using a machine learning method called CHIMERA. CHIMERA clusters the differences between patients and a demographically-matched population of healthy subjects, rather than clustering patients themselves, thereby specifically assessing disease-related neuroanatomical alterations. Voxel-Based Morphometry was conducted to visualize the neuroanatomical patterns associated with each group. The clinical presentation and the demographics of the groups were then investigated. Three subgroups were identified. The first two differed substantially, in that one involved predominantly temporal-thalamic-peri-Sylvian regions, whereas the other involved predominantly frontal regions and the thalamus. Both subtypes included primarily male patients. The third pattern was a mix of these two and presented milder neuroanatomic alterations and comprised a comparable number of men and women. VBM and statistical analyses suggest that these groups could correspond to different neuroanatomical dimensions of schizophrenia. Our analysis suggests that schizophrenia presents distinct neuroanatomical variants. This variability points to the need for a dimensional neuroanatomical approach using data-driven, mathematically principled multivariate pattern analysis methods, and should be taken into account in clinical studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Towards autonomous neuroprosthetic control using Hebbian reinforcement learning.

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Mahmoudi, Babak; Pohlmeyer, Eric A; Prins, Noeline W; Geng, Shijia; Sanchez, Justin C

2013-12-01

Our goal was to design an adaptive neuroprosthetic controller that could learn the mapping from neural states to prosthetic actions and automatically adjust adaptation using only a binary evaluative feedback as a measure of desirability/undesirability of performance. Hebbian reinforcement learning (HRL) in a connectionist network was used for the design of the adaptive controller. The method combines the efficiency of supervised learning with the generality of reinforcement learning. The convergence properties of this approach were studied using both closed-loop control simulations and open-loop simulations that used primate neural data from robot-assisted reaching tasks. The HRL controller was able to perform classification and regression tasks using its episodic and sequential learning modes, respectively. In our experiments, the HRL controller quickly achieved convergence to an effective control policy, followed by robust performance. The controller also automatically stopped adapting the parameters after converging to a satisfactory control policy. Additionally, when the input neural vector was reorganized, the controller resumed adaptation to maintain performance. By estimating an evaluative feedback directly from the user, the HRL control algorithm may provide an efficient method for autonomous adaptation of neuroprosthetic systems. This method may enable the user to teach the controller the desired behavior using only a simple feedback signal.

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

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Lindsay, Grace W.

2017-01-01

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (�

Hebbian learning of hand-centred representations in a hierarchical neural network model of the primate visual system.

Directory of Open Access Journals (Sweden)

Jannis Born

Full Text Available A subset of neurons in the posterior parietal and premotor areas of the primate brain respond to the locations of visual targets in a hand-centred frame of reference. Such hand-centred visual representations are thought to play an important role in visually-guided reaching to target locations in space. In this paper we show how a biologically plausible, Hebbian learning mechanism may account for the development of localized hand-centred representations in a hierarchical neural network model of the primate visual system, VisNet. The hand-centered neurons developed in the model use an invariance learning mechanism known as continuous transformation (CT learning. In contrast to previous theoretical proposals for the development of hand-centered visual representations, CT learning does not need a memory trace of recent neuronal activity to be incorporated in the synaptic learning rule. Instead, CT learning relies solely on a Hebbian learning rule, which is able to exploit the spatial overlap that naturally occurs between successive images of a hand-object configuration as it is shifted across different retinal locations due to saccades. Our simulations show how individual neurons in the network model can learn to respond selectively to target objects in particular locations with respect to the hand, irrespective of where the hand-object configuration occurs on the retina. The response properties of these hand-centred neurons further generalise to localised receptive fields in the hand-centred space when tested on novel hand-object configurations that have not been explored during training. Indeed, even when the network is trained with target objects presented across a near continuum of locations around the hand during training, the model continues to develop hand-centred neurons with localised receptive fields in hand-centred space. With the help of principal component analysis, we provide the first theoretical framework that explains the behavior

Anti-hebbian spike-timing-dependent plasticity and adaptive sensory processing.

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Roberts, Patrick D; Leen, Todd K

2010-01-01

Adaptive sensory processing influences the central nervous system's interpretation of incoming sensory information. One of the functions of this adaptive sensory processing is to allow the nervous system to ignore predictable sensory information so that it may focus on important novel information needed to improve performance of specific tasks. The mechanism of spike-timing-dependent plasticity (STDP) has proven to be intriguing in this context because of its dual role in long-term memory and ongoing adaptation to maintain optimal tuning of neural responses. Some of the clearest links between STDP and adaptive sensory processing have come from in vitro, in vivo, and modeling studies of the electrosensory systems of weakly electric fish. Plasticity in these systems is anti-Hebbian, so that presynaptic inputs that repeatedly precede, and possibly could contribute to, a postsynaptic neuron's firing are weakened. The learning dynamics of anti-Hebbian STDP learning rules are stable if the timing relations obey strict constraints. The stability of these learning rules leads to clear predictions of how functional consequences can arise from the detailed structure of the plasticity. Here we review the connection between theoretical predictions and functional consequences of anti-Hebbian STDP, focusing on adaptive processing in the electrosensory system of weakly electric fish. After introducing electrosensory adaptive processing and the dynamics of anti-Hebbian STDP learning rules, we address issues of predictive sensory cancelation and novelty detection, descending control of plasticity, synaptic scaling, and optimal sensory tuning. We conclude with examples in other systems where these principles may apply.

Anti-Hebbian Spike Timing Dependent Plasticity and Adaptive Sensory Processing

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Patrick D Roberts

2010-12-01

Full Text Available Adaptive processing influences the central nervous system's interpretation of incoming sensory information. One of the functions of this adaptative sensory processing is to allow the nervous system to ignore predictable sensory information so that it may focus on important new information needed to improve performance of specific tasks. The mechanism of spike timing-dependent plasticity (STDP has proven to be intriguing in this context because of its dual role in long-term memory and ongoing adaptation to maintain optimal tuning of neural responses. Some of the clearest links between STDP and adaptive sensory processing have come from in vitro, in vivo, and modeling studies of the electrosensory systems of fish. Plasticity in such systems is anti-Hebbian, i.e. presynaptic inputs that repeatedly precede and hence could contribute to a postsynaptic neuron’s firing are weakened. The learning dynamics of anti-Hebbian STDP learning rules are stable if the timing relations obey strict constraints. The stability of these learning rules leads to clear predictions of how functional consequences can arise from the detailed structure of the plasticity. Here we review the connection between theoretical predictions and functional consequences of anti-Hebbian STDP, focusing on adaptive processing in the electrosensory system of weakly electric fish. After introducing electrosensory adaptive processing and the dynamics of anti-Hebbian STDP learning rules, we address issues of predictive sensory cancellation and novelty detection, descending control of plasticity, synaptic scaling, and optimal sensory tuning. We conclude with examples in other systems where these principles may apply.

Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum

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Tjeerd V. olde Scheper

2018-01-01

Full Text Available Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized

Demystifying social cognition : a Hebbian perspective

NARCIS (Netherlands)

Keysers, C; Perrett, DI

For humans and monkeys, understanding the actions of others is central to survival. Here we review the physiological properties of three cortical areas involved in this capacity: the STS, PF and F5. Based on the anatomical connections of these areas, and the Hebbian learning rule, we propose a

A global bioheat model with self-tuning optimal regulation of body temperature using Hebbian feedback covariance learning.

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Ong, M L; Ng, E Y K

2005-12-01

In the lower brain, body temperature is continually being regulated almost flawlessly despite huge fluctuations in ambient and physiological conditions that constantly threaten the well-being of the body. The underlying control problem defining thermal homeostasis is one of great enormity: Many systems and sub-systems are involved in temperature regulation and physiological processes are intrinsically complex and intertwined. Thus the defining control system has to take into account the complications of nonlinearities, system uncertainties, delayed feedback loops as well as internal and external disturbances. In this paper, we propose a self-tuning adaptive thermal controller based upon Hebbian feedback covariance learning where the system is to be regulated continually to best suit its environment. This hypothesis is supported in part by postulations of the presence of adaptive optimization behavior in biological systems of certain organisms which face limited resources vital for survival. We demonstrate the use of Hebbian feedback covariance learning as a possible self-adaptive controller in body temperature regulation. The model postulates an important role of Hebbian covariance adaptation as a means of reinforcement learning in the thermal controller. The passive system is based on a simplified 2-node core and shell representation of the body, where global responses are captured. Model predictions are consistent with observed thermoregulatory responses to conditions of exercise and rest, and heat and cold stress. An important implication of the model is that optimal physiological behaviors arising from self-tuning adaptive regulation in the thermal controller may be responsible for the departure from homeostasis in abnormal states, e.g., fever. This was previously unexplained using the conventional "set-point" control theory.

Emotions as a Vehicle for Rationality: Rational Decision Making Models Based on Emotion-Related Valuing and Hebbian Learning

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Treur, J.; Umair, M.

2015-01-01

In this paper an adaptive decision model based on predictive loops through feeling states is analysed from the perspective of rationality. Hebbian learning is considered for different types of connections in the decision model. To assess the extent of rationality, a measure is introduced reflecting

E-I balance emerges naturally from continuous Hebbian learning in autonomous neural networks.

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Trapp, Philip; Echeveste, Rodrigo; Gros, Claudius

2018-06-12

Spontaneous brain activity is characterized in part by a balanced asynchronous chaotic state. Cortical recordings show that excitatory (E) and inhibitory (I) drivings in the E-I balanced state are substantially larger than the overall input. We show that such a state arises naturally in fully adapting networks which are deterministic, autonomously active and not subject to stochastic external or internal drivings. Temporary imbalances between excitatory and inhibitory inputs lead to large but short-lived activity bursts that stabilize irregular dynamics. We simulate autonomous networks of rate-encoding neurons for which all synaptic weights are plastic and subject to a Hebbian plasticity rule, the flux rule, that can be derived from the stationarity principle of statistical learning. Moreover, the average firing rate is regulated individually via a standard homeostatic adaption of the bias of each neuron's input-output non-linear function. Additionally, networks with and without short-term plasticity are considered. E-I balance may arise only when the mean excitatory and inhibitory weights are themselves balanced, modulo the overall activity level. We show that synaptic weight balance, which has been considered hitherto as given, naturally arises in autonomous neural networks when the here considered self-limiting Hebbian synaptic plasticity rule is continuously active.

Recruitment and Consolidation of Cell Assemblies for Words by Way of Hebbian Learning and Competition in a Multi-Layer Neural Network.

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Garagnani, Max; Wennekers, Thomas; Pulvermüller, Friedemann

2009-06-01

Current cognitive theories postulate either localist representations of knowledge or fully overlapping, distributed ones. We use a connectionist model that closely replicates known anatomical properties of the cerebral cortex and neurophysiological principles to show that Hebbian learning in a multi-layer neural network leads to memory traces (cell assemblies) that are both distributed and anatomically distinct. Taking the example of word learning based on action-perception correlation, we document mechanisms underlying the emergence of these assemblies, especially (i) the recruitment of neurons and consolidation of connections defining the kernel of the assembly along with (ii) the pruning of the cell assembly's halo (consisting of very weakly connected cells). We found that, whereas a learning rule mapping covariance led to significant overlap and merging of assemblies, a neurobiologically grounded synaptic plasticity rule with fixed LTP/LTD thresholds produced minimal overlap and prevented merging, exhibiting competitive learning behaviour. Our results are discussed in light of current theories of language and memory. As simulations with neurobiologically realistic neural networks demonstrate here spontaneous emergence of lexical representations that are both cortically dispersed and anatomically distinct, both localist and distributed cognitive accounts receive partial support.

Anti-Hebbian long-term potentiation in the hippocampal feedback inhibitory circuit.

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Lamsa, Karri P; Heeroma, Joost H; Somogyi, Peter; Rusakov, Dmitri A; Kullmann, Dimitri M

2007-03-02

Long-term potentiation (LTP), which approximates Hebb's postulate of associative learning, typically requires depolarization-dependent glutamate receptors of the NMDA (N-methyl-D-aspartate) subtype. However, in some neurons, LTP depends instead on calcium-permeable AMPA-type receptors. This is paradoxical because intracellular polyamines block such receptors during depolarization. We report that LTP at synapses on hippocampal interneurons mediating feedback inhibition is "anti-Hebbian":Itis induced by presynaptic activity but prevented by postsynaptic depolarization. Anti-Hebbian LTP may occur in interneurons that are silent during periods of intense pyramidal cell firing, such as sharp waves, and lead to their altered activation during theta activity.

Grounded understanding of abstract concepts: The case of STEM learning.

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Hayes, Justin C; Kraemer, David J M

2017-01-01

Characterizing the neural implementation of abstract conceptual representations has long been a contentious topic in cognitive science. At the heart of the debate is whether the "sensorimotor" machinery of the brain plays a central role in representing concepts, or whether the involvement of these perceptual and motor regions is merely peripheral or epiphenomenal. The domain of science, technology, engineering, and mathematics (STEM) learning provides an important proving ground for sensorimotor (or grounded) theories of cognition, as concepts in science and engineering courses are often taught through laboratory-based and other hands-on methodologies. In this review of the literature, we examine evidence suggesting that sensorimotor processes strengthen learning associated with the abstract concepts central to STEM pedagogy. After considering how contemporary theories have defined abstraction in the context of semantic knowledge, we propose our own explanation for how body-centered information, as computed in sensorimotor brain regions and visuomotor association cortex, can form a useful foundation upon which to build an understanding of abstract scientific concepts, such as mechanical force. Drawing from theories in cognitive neuroscience, we then explore models elucidating the neural mechanisms involved in grounding intangible concepts, including Hebbian learning, predictive coding, and neuronal recycling. Empirical data on STEM learning through hands-on instruction are considered in light of these neural models. We conclude the review by proposing three distinct ways in which the field of cognitive neuroscience can contribute to STEM learning by bolstering our understanding of how the brain instantiates abstract concepts in an embodied fashion.

A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation

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Fiebig, Florian

2017-01-01

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. SIGNIFICANCE STATEMENT Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and

A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models

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Alexander eHanuschkin

2013-06-01

Full Text Available Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: Random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, they allow for imitating arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions.Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird’s own song

A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models.

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Hanuschkin, A; Ganguli, S; Hahnloser, R H R

2013-01-01

Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map-desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, by allowing the imitation of arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions. Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird's own song (BOS) stimuli.

A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation.

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Fiebig, Florian; Lansner, Anders

2017-01-04

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying

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

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Burms, Jeroen; Caluwaerts, Ken; Dambre, Joni

2015-01-01

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

Logarithmic distributions prove that intrinsic learning is Hebbian [version 2; referees: 2 approved

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Gabriele Scheler

2017-10-01

Full Text Available In this paper, we present data for the lognormal distributions of spike rates, synaptic weights and intrinsic excitability (gain for neurons in various brain areas, such as auditory or visual cortex, hippocampus, cerebellum, striatum, midbrain nuclei. We find a remarkable consistency of heavy-tailed, specifically lognormal, distributions for rates, weights and gains in all brain areas examined. The difference between strongly recurrent and feed-forward connectivity (cortex vs. striatum and cerebellum, neurotransmitter (GABA (striatum or glutamate (cortex or the level of activation (low in cortex, high in Purkinje cells and midbrain nuclei turns out to be irrelevant for this feature. Logarithmic scale distribution of weights and gains appears to be a general, functional property in all cases analyzed. We then created a generic neural model to investigate adaptive learning rules that create and maintain lognormal distributions. We conclusively demonstrate that not only weights, but also intrinsic gains, need to have strong Hebbian learning in order to produce and maintain the experimentally attested distributions. This provides a solution to the long-standing question about the type of plasticity exhibited by intrinsic excitability.

Hebbian Plasticity Guides Maturation of Glutamate Receptor Fields In Vivo

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Dmitrij Ljaschenko

2013-05-01

Full Text Available Synaptic plasticity shapes the development of functional neural circuits and provides a basis for cellular models of learning and memory. Hebbian plasticity describes an activity-dependent change in synaptic strength that is input-specific and depends on correlated pre- and postsynaptic activity. Although it is recognized that synaptic activity and synapse development are intimately linked, our mechanistic understanding of the coupling is far from complete. Using Channelrhodopsin-2 to evoke activity in vivo, we investigated synaptic plasticity at the glutamatergic Drosophila neuromuscular junction. Remarkably, correlated pre- and postsynaptic stimulation increased postsynaptic sensitivity by promoting synapse-specific recruitment of GluR-IIA-type glutamate receptor subunits into postsynaptic receptor fields. Conversely, GluR-IIA was rapidly removed from synapses whose activity failed to evoke substantial postsynaptic depolarization. Uniting these results with developmental GluR-IIA dynamics provides a comprehensive physiological concept of how Hebbian plasticity guides synaptic maturation and sparse transmitter release controls the stabilization of the molecular composition of individual synapses.

Sleep: The hebbian reinforcement of the local inhibitory synapses.

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Touzet, Claude

2015-09-01

Sleep is ubiquitous among the animal realm, and represents about 30% of our lives. Despite numerous efforts, the reason behind our need for sleep is still unknown. The Theory of neuronal Cognition (TnC) proposes that sleep is the period of time during which the local inhibitory synapses (in particular the cortical ones) are replenished. Indeed, as long as the active brain stays awake, hebbian learning guarantees that efficient inhibitory synapses lose their efficiency – just because they are efficient at avoiding the activation of the targeted neurons. Since hebbian learning is the only known mechanism of synapse modification, it follows that to replenish the inhibitory synapses' efficiency, source and targeted neurons must be activated together. This is achieved by a local depolarization that may travel (wave). The period of time during which such slow waves are experienced has been named the "slow-wave sleep" (SWS). It is cut into several pieces by shorter periods of paradoxical sleep (REM) which activity resembles that of the awake state. Indeed, SWS – because it only allows local neural activation – decreases the excitatory long distance connections strength. To avoid losing the associations built during the awake state, these long distance activations are played again during the REM sleep. REM and SWS sleeps act together to guarantee that when the subject awakes again, his inhibitory synaptic efficiency is restored and his (excitatory) long distance associations are still there. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hebbian learning in a model with dynamic rate-coded neurons: an alternative to the generative model approach for learning receptive fields from natural scenes.

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Hamker, Fred H; Wiltschut, Jan

2007-09-01

Most computational models of coding are based on a generative model according to which the feedback signal aims to reconstruct the visual scene as close as possible. We here explore an alternative model of feedback. It is derived from studies of attention and thus, probably more flexible with respect to attentive processing in higher brain areas. According to this model, feedback implements a gain increase of the feedforward signal. We use a dynamic model with presynaptic inhibition and Hebbian learning to simultaneously learn feedforward and feedback weights. The weights converge to localized, oriented, and bandpass filters similar as the ones found in V1. Due to presynaptic inhibition the model predicts the organization of receptive fields within the feedforward pathway, whereas feedback primarily serves to tune early visual processing according to the needs of the task.

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

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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

The dependence of neuronal encoding efficiency on Hebbian plasticity and homeostatic regulation of neurotransmitter release

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Faghihi, Faramarz; Moustafa, Ahmed A.

2015-01-01

Synapses act as information filters by different molecular mechanisms including retrograde messenger that affect neuronal spiking activity. One of the well-known effects of retrograde messenger in presynaptic neurons is a change of the probability of neurotransmitter release. Hebbian learning describe a strengthening of a synapse between a presynaptic input onto a postsynaptic neuron when both pre- and postsynaptic neurons are coactive. In this work, a theory of homeostatic regulation of neurotransmitter release by retrograde messenger and Hebbian plasticity in neuronal encoding is presented. Encoding efficiency was measured for different synaptic conditions. In order to gain high encoding efficiency, the spiking pattern of a neuron should be dependent on the intensity of the input and show low levels of noise. In this work, we represent spiking trains as zeros and ones (corresponding to non-spike or spike in a time bin, respectively) as words with length equal to three. Then the frequency of each word (here eight words) is measured using spiking trains. These frequencies are used to measure neuronal efficiency in different conditions and for different parameter values. Results show that neurons that have synapses acting as band-pass filters show the highest efficiency to encode their input when both Hebbian mechanism and homeostatic regulation of neurotransmitter release exist in synapses. Specifically, the integration of homeostatic regulation of feedback inhibition with Hebbian mechanism and homeostatic regulation of neurotransmitter release in the synapses leads to even higher efficiency when high stimulus intensity is presented to the neurons. However, neurons with synapses acting as high-pass filters show no remarkable increase in encoding efficiency for all simulated synaptic plasticity mechanisms. This study demonstrates the importance of cooperation of Hebbian mechanism with regulation of neurotransmitter release induced by rapid diffused retrograde

The dependence of neuronal encoding efficiency on Hebbian plasticity and homeostatic regulation of neurotransmitter release

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Faramarz eFaghihi

2015-04-01

Full Text Available Synapses act as information filters by different molecular mechanisms including retrograde messenger that affect neuronal spiking activity. One of the well-known effects of retrograde messenger in presynaptic neurons is a change of the probability of neurotransmitter release. Hebbian learning describe a strengthening of a synapse between a presynaptic input onto a postsynaptic neuron when both pre- and postsynaptic neurons are coactive. In this work, a theory of homeostatic regulation of neurotransmitter release by retrograde messenger and Hebbian plasticity in neuronal encoding is presented. Encoding efficiency was measured for different synaptic conditions. In order to gain high encoding efficiency, the spiking pattern of a neuron should be dependent on the intensity of the input and show low levels of noise. In this work, we represent spiking trains as zeros and ones (corresponding to non-spike or spike in a time bin, respectively as words with length equal to three. Then the frequency of each word (here eight words is measured using spiking trains. These frequencies are used to measure neuronal efficiency in different conditions and for different parameter values. Results show that neurons that have synapses acting as band-pass filters show the highest efficiency to encode their input when both Hebbian mechanism and homeostatic regulation of neurotransmitter release exist in synapses. Specifically, the integration of homeostatic regulation of feedback inhibition with Hebbian mechanism and homeostatic regulation of neurotransmitter release in the synapses leads to even higher efficiency when high stimulus intensity is presented to the neurons. However, neurons with synapses acting as high-pass filters show no remarkable increase in encoding efficiency for all simulated synaptic plasticity mechanisms.

Logic Learning in Hopfield Networks

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Sathasivam, Saratha; Abdullah, Wan Ahmad Tajuddin Wan

2008-01-01

Synaptic weights for neurons in logic programming can be calculated either by using Hebbian learning or by Wan Abdullah's method. In other words, Hebbian learning for governing events corresponding to some respective program clauses is equivalent with learning using Wan Abdullah's method for the same respective program clauses. In this paper we will evaluate experimentally the equivalence between these two types of learning through computer simulations.

Syntactic sequencing in Hebbian cell assemblies.

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Wennekers, Thomas; Palm, Günther

2009-12-01

Hebbian cell assemblies provide a theoretical framework for the modeling of cognitive processes that grounds them in the underlying physiological neural circuits. Recently we have presented an extension of cell assemblies by operational components which allows to model aspects of language, rules, and complex behaviour. In the present work we study the generation of syntactic sequences using operational cell assemblies timed by unspecific trigger signals. Syntactic patterns are implemented in terms of hetero-associative transition graphs in attractor networks which cause a directed flow of activity through the neural state space. We provide regimes for parameters that enable an unspecific excitatory control signal to switch reliably between attractors in accordance with the implemented syntactic rules. If several target attractors are possible in a given state, noise in the system in conjunction with a winner-takes-all mechanism can randomly choose a target. Disambiguation can also be guided by context signals or specific additional external signals. Given a permanently elevated level of external excitation the model can enter an autonomous mode, where it generates temporal grammatical patterns continuously.

On-line learning through simple perceptron learning with a margin.

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Hara, Kazuyuki; Okada, Masato

2004-03-01

We analyze a learning method that uses a margin kappa a la Gardner for simple perceptron learning. This method corresponds to the perceptron learning when kappa = 0 and to the Hebbian learning when kappa = infinity. Nevertheless, we found that the generalization ability of the method was superior to that of the perceptron and the Hebbian methods at an early stage of learning. We analyzed the asymptotic property of the learning curve of this method through computer simulation and found that it was the same as for perceptron learning. We also investigated an adaptive margin control method.

Evidence from a rare case-study for Hebbian-like changes in structural connectivity induced by long-term deep brain stimulation

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Tim J Van Hartevelt

2015-06-01

Full Text Available It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e. where measurable changes in structural connectivity are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson's disease before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the structural connectivity towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in structural connectivity allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.

On-line learning through simple perceptron with a margin

OpenAIRE

Hara, Kazuyuki; Okada, Masato

2003-01-01

We analyze a learning method that uses a margin $\\kappa$ {\\it a la} Gardner for simple perceptron learning. This method corresponds to the perceptron learning when $\\kappa=0$, and to the Hebbian learning when $\\kappa \\to \\infty$. Nevertheless, we found that the generalization ability of the method was superior to that of the perceptron and the Hebbian methods at an early stage of learning. We analyzed the asymptotic property of the learning curve of this method through computer simulation and...

Cocaine Promotes Coincidence Detection and Lowers Induction Threshold during Hebbian Associative Synaptic Potentiation in Prefrontal Cortex.

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Ruan, Hongyu; Yao, Wei-Dong

2017-01-25

Addictive drugs usurp neural plasticity mechanisms that normally serve reward-related learning and memory, primarily by evoking changes in glutamatergic synaptic strength in the mesocorticolimbic dopamine circuitry. Here, we show that repeated cocaine exposure in vivo does not alter synaptic strength in the mouse prefrontal cortex during an early period of withdrawal, but instead modifies a Hebbian quantitative synaptic learning rule by broadening the temporal window and lowers the induction threshold for spike-timing-dependent LTP (t-LTP). After repeated, but not single, daily cocaine injections, t-LTP in layer V pyramidal neurons is induced at +30 ms, a normally ineffective timing interval for t-LTP induction in saline-exposed mice. This cocaine-induced, extended-timing t-LTP lasts for ∼1 week after terminating cocaine and is accompanied by an increased susceptibility to potentiation by fewer pre-post spike pairs, indicating a reduced t-LTP induction threshold. Basal synaptic strength and the maximal attainable t-LTP magnitude remain unchanged after cocaine exposure. We further show that the cocaine facilitation of t-LTP induction is caused by sensitized D1-cAMP/protein kinase A dopamine signaling in pyramidal neurons, which then pathologically recruits voltage-gated l-type Ca 2+ channels that synergize with GluN2A-containing NMDA receptors to drive t-LTP at extended timing. Our results illustrate a mechanism by which cocaine, acting on a key neuromodulation pathway, modifies the coincidence detection window during Hebbian plasticity to facilitate associative synaptic potentiation in prefrontal excitatory circuits. By modifying rules that govern activity-dependent synaptic plasticity, addictive drugs can derail the experience-driven neural circuit remodeling process important for executive control of reward and addiction. It is believed that addictive drugs often render an addict's brain reward system hypersensitive, leaving the individual more susceptible to

Binding and segmentation via a neural mass model trained with Hebbian and anti-Hebbian mechanisms.

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Cona, Filippo; Zavaglia, Melissa; Ursino, Mauro

2012-04-01

Synchronization of neural activity in the gamma band, modulated by a slower theta rhythm, is assumed to play a significant role in binding and segmentation of multiple objects. In the present work, a recent neural mass model of a single cortical column is used to analyze the synaptic mechanisms which can warrant synchronization and desynchronization of cortical columns, during an autoassociation memory task. The model considers two distinct layers communicating via feedforward connections. The first layer receives the external input and works as an autoassociative network in the theta band, to recover a previously memorized object from incomplete information. The second realizes segmentation of different objects in the gamma band. To this end, units within both layers are connected with synapses trained on the basis of previous experience to store objects. The main model assumptions are: (i) recovery of incomplete objects is realized by excitatory synapses from pyramidal to pyramidal neurons in the same object; (ii) binding in the gamma range is realized by excitatory synapses from pyramidal neurons to fast inhibitory interneurons in the same object. These synapses (both at points i and ii) have a few ms dynamics and are trained with a Hebbian mechanism. (iii) Segmentation is realized with faster AMPA synapses, with rise times smaller than 1 ms, trained with an anti-Hebbian mechanism. Results show that the model, with the previous assumptions, can correctly reconstruct and segment three simultaneous objects, starting from incomplete knowledge. Segmentation of more objects is possible but requires an increased ratio between the theta and gamma periods.

Long-Term Homeostatic Properties Complementary to Hebbian Rules in CuPc-Based Multifunctional Memristor

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Wang, Laiyuan; Wang, Zhiyong; Lin, Jinyi; Yang, Jie; Xie, Linghai; Yi, Mingdong; Li, Wen; Ling, Haifeng; Ou, Changjin; Huang, Wei

2016-10-01

Most simulations of neuroplasticity in memristors, which are potentially used to develop artificial synapses, are confined to the basic biological Hebbian rules. However, the simplex rules potentially can induce excessive excitation/inhibition, even collapse of neural activities, because they neglect the properties of long-term homeostasis involved in the frameworks of realistic neural networks. Here, we develop organic CuPc-based memristors of which excitatory and inhibitory conductivities can implement both Hebbian rules and homeostatic plasticity, complementary to Hebbian patterns and conductive to the long-term homeostasis. In another adaptive situation for homeostasis, in thicker samples, the overall excitement under periodic moderate stimuli tends to decrease and be recovered under intense inputs. Interestingly, the prototypes can be equipped with bio-inspired habituation and sensitization functions outperforming the conventional simplified algorithms. They mutually regulate each other to obtain the homeostasis. Therefore, we develop a novel versatile memristor with advanced synaptic homeostasis for comprehensive neural functions.

From sensorimotor learning to memory cells in prefrontal and temporal association cortex: a neurocomputational study of disembodiment.

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Pulvermüller, Friedemann; Garagnani, Max

2014-08-01

Memory cells, the ultimate neurobiological substrates of working memory, remain active for several seconds and are most commonly found in prefrontal cortex and higher multisensory areas. However, if correlated activity in "embodied" sensorimotor systems underlies the formation of memory traces, why should memory cells emerge in areas distant from their antecedent activations in sensorimotor areas, thus leading to "disembodiment" (movement away from sensorimotor systems) of memory mechanisms? We modelled the formation of memory circuits in six-area neurocomputational architectures, implementing motor and sensory primary, secondary and higher association areas in frontotemporal cortices along with known between-area neuroanatomical connections. Sensorimotor learning driven by Hebbian neuroplasticity led to formation of cell assemblies distributed across the different areas of the network. These action-perception circuits (APCs) ignited fully when stimulated, thus providing a neural basis for long-term memory (LTM) of sensorimotor information linked by learning. Subsequent to ignition, activity vanished rapidly from APC neurons in sensorimotor areas but persisted in those in multimodal prefrontal and temporal areas. Such persistent activity provides a mechanism for working memory for actions, perceptions and symbols, including short-term phonological and semantic storage. Cell assembly ignition and "disembodied" working memory retreat of activity to multimodal areas are documented in the neurocomputational models' activity dynamics, at the level of single cells, circuits, and cortical areas. Memory disembodiment is explained neuromechanistically by APC formation and structural neuroanatomical features of the model networks, especially the central role of multimodal prefrontal and temporal cortices in bridging between sensory and motor areas. These simulations answer the "where" question of cortical working memory in terms of distributed APCs and their inner structure

Application of neuroanatomical ontologies for neuroimaging data annotation

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Jessica A Turner

2010-06-01

Full Text Available The annotation of functional neuroimaging results for data sharing and reuse is particularly challenging, due to the diversity of terminologies of neuroanatomical structures and cortical parcellation schemes. To address this challenge, we extended the Foundational Model of Anatomy Ontology (FMA to include cytoarchitectural, Brodmann area labels, and a morphological cortical labeling scheme (e.g., the part of Brodmann area 6 in the left precentral gyrus. This representation was also used to augment the neuroanatomical axis of RadLex, the ontology for clinical imaging. The resulting neuroanatomical ontology contains explicit relationships indicating which brain regions are “part of” which other regions, across cytoarchitectural and morphological labeling schemas. We annotated a large functional neuroimaging dataset with terms from the ontology and applied a reasoning engine to analyze this dataset in conjunction with the ontology, and achieved successful inferences from the most specific level (e.g., how many subjects showed activation in a sub-part of the middle frontal gyrus to more general (how many activations were found in areas connected via a known white matter tract?. In summary, we have produced a neuroanatomical ontology that harmonizes several different terminologies of neuroanatomical structures and cortical parcellation schemes. This neuranatomical ontology is publicly available as a view of FMA at the Bioportal website at http://rest.bioontology.org/bioportal/ontologies/download/10005. The ontological encoding of anatomic knowledge can be exploited by computer reasoning engines to make inferences about neuroanatomical relationships described in imaging datasets using different terminologies. This approach could ultimately enable knowledge discovery from large, distributed fMRI studies or medical record mining.

Dynasting Theory: Lessons in learning grounded theory

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Johnben Teik-Cheok Loy, MBA, MTS, Ph.D.

2011-06-01

Full Text Available This article captures the key learning lessons gleaned from the author’s experience learning and developing a grounded theory for his doctoral dissertation using the classic methodology as conceived by Barney Glaser. The theory was developed through data gathered on founders and successors of Malaysian Chinese family-own businesses. The main concern for Malaysian Chinese family businesses emerged as dynasting . the building, maintaining, and growing the power and resources of the business within the family lineage. The core category emerged as dynasting across cultures, where founders and successors struggle to transition from traditional Chinese to hybrid cultural and modernized forms of family business from one generation to the next. The key learning lessons were categorized under five headings: (a sorting through different versions of grounded theory, (b educating and managing research stakeholders, (c embracing experiential learning, (d discovering the core category: grounded intuition, and (e recognizing limitations and possibilities.Keywords: grounded theory, learning, dynasting, family business, Chinese

Neuroanatomical correlates of personality in the elderly.

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Wright, Christopher I; Feczko, Eric; Dickerson, Bradford; Williams, Danielle

2007-03-01

Extraversion and neuroticism are two important and frequently studied dimensions of human personality. They describe individual differences in emotional responding that are quite stable across the adult lifespan. Neuroimaging research has begun to provide evidence that neuroticism and extraversion have specific neuroanatomical correlates within the cerebral cortex and amygdala of young adults. However, these brain areas undergo alterations in size with aging, which may influence the nature of these personality factor-brain structure associations in the elderly. One study in the elderly demonstrated associations between perisylvian cortex structure and measures of self transcendence [Kaasinen, V., Maguire, R.P., Kurki, T., Bruck, A., Rinne, J.O., 2005. Mapping brain structure and personality in late adulthood. NeuroImage 24, 315-322], but the neuroanatomical correlates of extraversion and neuroticism, or other measures of the Five Factor Model of personality have not been explored. The purpose of the present study was to investigate the structural correlates of neuroticism and extraversion in healthy elderly subjects (n=29) using neuroanatomic measures of the cerebral cortex and amygdala. We observed that the thickness of specific lateral prefrontal cortex (PFC) regions, but not amygdala volume, correlates with measures of extraversion and neuroticism. The results suggest differences in the regional neuroanatomic correlates of specific personality traits with aging. We speculate that this relates to the influences of age-related structural changes in the PFC.

A neuroanatomical approach to exploring organizational performance

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Gillingwater, D.

2009-01-01

Full Text Available Insights gained from studying the human brain have begun to open up promising new areas of research in the behavioural and social sciences. Neuroscience-based principles have been incorporated into areas such as business management, economics and marketing, leading to the development of artificial neural networks, neuroeconomics, neuromarketing and, most recently, organizational cognitive neuroscience. Similarly, the brain has been used as a powerful metaphor for thinking about and analysing the nature of organizations. However, no existing approach to organizational analysis has taken advantage of contemporary neuroanatomical principles, thereby missing the opportunity to translate core neuroanatomical knowledge into other, non-related areas of research. In this essentially conceptual paper, we propose several ways in which neuroanatomical approaches could be used to enhance organizational theory, practice and research. We suggest that truly interdisciplinary and collaborative research between neuroanatomists and organizational analysts is likely to provide novel approaches to exploring and improving organizational performance.

Theta coordinated error-driven learning in the hippocampus.

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Nicholas Ketz

Full Text Available The learning mechanism in the hippocampus has almost universally been assumed to be Hebbian in nature, where individual neurons in an engram join together with synaptic weight increases to support facilitated recall of memories later. However, it is also widely known that Hebbian learning mechanisms impose significant capacity constraints, and are generally less computationally powerful than learning mechanisms that take advantage of error signals. We show that the differential phase relationships of hippocampal subfields within the overall theta rhythm enable a powerful form of error-driven learning, which results in significantly greater capacity, as shown in computer simulations. In one phase of the theta cycle, the bidirectional connectivity between CA1 and entorhinal cortex can be trained in an error-driven fashion to learn to effectively encode the cortical inputs in a compact and sparse form over CA1. In a subsequent portion of the theta cycle, the system attempts to recall an existing memory, via the pathway from entorhinal cortex to CA3 and CA1. Finally the full theta cycle completes when a strong target encoding representation of the current input is imposed onto the CA1 via direct projections from entorhinal cortex. The difference between this target encoding and the attempted recall of the same representation on CA1 constitutes an error signal that can drive the learning of CA3 to CA1 synapses. This CA3 to CA1 pathway is critical for enabling full reinstatement of recalled hippocampal memories out in cortex. Taken together, these new learning dynamics enable a much more robust, high-capacity model of hippocampal learning than was available previously under the classical Hebbian model.

Learning-induced pattern classification in a chaotic neural network

International Nuclear Information System (INIS)

Li, Yang; Zhu, Ping; Xie, Xiaoping; He, Guoguang; Aihara, Kazuyuki

2012-01-01

In this Letter, we propose a Hebbian learning rule with passive forgetting (HLRPF) for use in a chaotic neural network (CNN). We then define the indices based on the Euclidean distance to investigate the evolution of the weights in a simplified way. Numerical simulations demonstrate that, under suitable external stimulations, the CNN with the proposed HLRPF acts as a fuzzy-like pattern classifier that performs much better than an ordinary CNN. The results imply relationship between learning and recognition. -- Highlights: ► Proposing a Hebbian learning rule with passive forgetting (HLRPF). ► Defining indices to investigate the evolution of the weights simply. ► The chaotic neural network with HLRPF acts as a fuzzy-like pattern classifier. ► The pattern classifier ability of the network is improved much.

Grounding word learning in space.

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Larissa K Samuelson

Full Text Available Humans and objects, and thus social interactions about objects, exist within space. Words direct listeners' attention to specific regions of space. Thus, a strong correspondence exists between where one looks, one's bodily orientation, and what one sees. This leads to further correspondence with what one remembers. Here, we present data suggesting that children use associations between space and objects and space and words to link words and objects--space binds labels to their referents. We tested this claim in four experiments, showing that the spatial consistency of where objects are presented affects children's word learning. Next, we demonstrate that a process model that grounds word learning in the known neural dynamics of spatial attention, spatial memory, and associative learning can capture the suite of results reported here. This model also predicts that space is special, a prediction supported in a fifth experiment that shows children do not use color as a cue to bind words and objects. In a final experiment, we ask whether spatial consistency affects word learning in naturalistic word learning contexts. Children of parents who spontaneously keep objects in a consistent spatial location during naming interactions learn words more effectively. Together, the model and data show that space is a powerful tool that can effectively ground word learning in social contexts.

The neuroscience of learning: beyond the Hebbian synapse.

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Gallistel, C R; Matzel, Louis D

2013-01-01

From the traditional perspective of associative learning theory, the hypothesis linking modifications of synaptic transmission to learning and memory is plausible. It is less so from an information-processing perspective, in which learning is mediated by computations that make implicit commitments to physical and mathematical principles governing the domains where domain-specific cognitive mechanisms operate. We compare the properties of associative learning and memory to the properties of long-term potentiation, concluding that the properties of the latter do not explain the fundamental properties of the former. We briefly review the neuroscience of reinforcement learning, emphasizing the representational implications of the neuroscientific findings. We then review more extensively findings that confirm the existence of complex computations in three information-processing domains: probabilistic inference, the representation of uncertainty, and the representation of space. We argue for a change in the conceptual framework within which neuroscientists approach the study of learning mechanisms in the brain.

[Nondeclarative memory--neuropsychological findings and neuroanatomic principles].

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Daum, I; Ackermann, H

1997-03-01

The contents of long-term memory will influence behaviour, even if the acquired knowledge or the original learning episode are not remembered. These phenomena have been termed "non-declarative" or "implicit" memory, and they are contrasted with "declarative" or "explicit" memory which is characterised by conscious search and retrieval procedures. Non-declarative memory encompasses non-associative learning, simple conditioning, priming effects as well as motor, perceptual and cognitive skill acquisition. The dissociation of both forms of memory is documented by studies in health subjects which indicated that experimental manipulations or drugs may differentially affect declarative and non-declarative memory processes. Damage to the medial temporal or the medial thalamic regions is known to result in declarative memory deficits whereas non-declarative memory is largely unaffected by such lesions. Animal research and clinical findings indicate that several components of non-declarative memory such as motor and cognitive skill acquisition or certain types of classical conditioning are dependent upon the integrity of the basal ganglia or the cerebellum. These issues are therefore of increasing importance for the understanding of extrapyramidal and cerebellar diseases. This paper presents recent neuropsychological findings and neuroanatomical data relating to the issue of non-declarative memory.

The NeuARt II system: a viewing tool for neuroanatomical data based on published neuroanatomical atlases

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Cheng Wei-Cheng

2006-12-01

Full Text Available Abstract Background Anatomical studies of neural circuitry describing the basic wiring diagram of the brain produce intrinsically spatial, highly complex data of great value to the neuroscience community. Published neuroanatomical atlases provide a spatial framework for these studies. We have built an informatics framework based on these atlases for the representation of neuroanatomical knowledge. This framework not only captures current methods of anatomical data acquisition and analysis, it allows these studies to be collated, compared and synthesized within a single system. Results We have developed an atlas-viewing application ('NeuARt II' in the Java language with unique functional properties. These include the ability to use copyrighted atlases as templates within which users may view, save and retrieve data-maps and annotate them with volumetric delineations. NeuARt II also permits users to view multiple levels on multiple atlases at once. Each data-map in this system is simply a stack of vector images with one image per atlas level, so any set of accurate drawings made onto a supported atlas (in vector graphics format could be uploaded into NeuARt II. Presently the database is populated with a corpus of high-quality neuroanatomical data from the laboratory of Dr Larry Swanson (consisting 64 highly-detailed maps of PHAL tract-tracing experiments, made up of 1039 separate drawings that were published in 27 primary research publications over 17 years. Herein we take selective examples from these data to demonstrate the features of NeuArt II. Our informatics tool permits users to browse, query and compare these maps. The NeuARt II tool operates within a bioinformatics knowledge management platform (called 'NeuroScholar' either as a standalone or a plug-in application. Conclusion Anatomical localization is fundamental to neuroscientific work and atlases provide an easily-understood framework that is widely used by neuroanatomists and non

Williams syndrome-specific neuroanatomical profile and its associations with behavioral features.

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Fan, Chun Chieh; Brown, Timothy T; Bartsch, Hauke; Kuperman, Joshua M; Hagler, Donald J; Schork, Andrew; Searcy, Yvonne; Bellugi, Ursula; Halgren, Eric; Dale, Anders M

2017-01-01

Williams Syndrome (WS) is a rare genetic disorder with unique behavioral features. Yet the rareness of WS has limited the number and type of studies that can be conducted in which inferences are made about how neuroanatomical abnormalities mediate behaviors. In this study, we extracted a WS-specific neuroanatomical profile from structural magnetic resonance imaging (MRI) measurements and tested its association with behavioral features of WS. Using a WS adult cohort (22 WS, 16 healthy controls), we modeled a sparse representation of a WS-specific neuroanatomical profile. The predictive performances are robust within the training cohort (10-fold cross-validation, AUC = 1.0) and accurately identify all WS individuals in an independent child WS cohort (seven WS, 59 children with diverse developmental status, AUC = 1.0). The WS-specific neuroanatomical profile includes measurements in the orbitofrontal cortex, superior parietal cortex, Sylvian fissures, and basal ganglia, and variability within these areas related to the underlying size of hemizygous deletion in patients with partial deletions. The profile intensity mediated the overall cognitive impairment as well as personality features related to hypersociability. Our results imply that the unique behaviors in WS were mediated through the constellation of abnormalities in cortical-subcortical circuitry consistent in child WS and adult WS. The robustness of the derived WS-specific neuroanatomical profile also demonstrates the potential utility of our approach in both clinical and research applications.

Constructing a Grounded Theory of E-Learning Assessment

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Alonso-Díaz, Laura; Yuste-Tosina, Rocío

2015-01-01

This study traces the development of a grounded theory of assessment in e-learning environments, a field in need of research to establish the parameters of an assessment that is both reliable and worthy of higher learning accreditation. Using grounded theory as a research method, we studied an e-assessment model that does not require physical…

Enhanced detection threshold for in vivo cortical stimulation produced by Hebbian conditioning

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Rebesco, James M.; Miller, Lee E.

2011-02-01

Normal brain function requires constant adaptation, as an organism learns to associate important sensory stimuli with the appropriate motor actions. Neurological disorders may disrupt these learned associations and require the nervous system to reorganize itself. As a consequence, neural plasticity is a crucial component of normal brain function and a critical mechanism for recovery from injury. Associative, or Hebbian, pairing of pre- and post-synaptic activity has been shown to alter stimulus-evoked responses in vivo; however, to date, such protocols have not been shown to affect the animal's subsequent behavior. We paired stimulus trains separated by a brief time delay to two electrodes in rat sensorimotor cortex, which changed the statistical pattern of spikes during subsequent behavior. These changes were consistent with strengthened functional connections from the leading electrode to the lagging electrode. We then trained rats to respond to a microstimulation cue, and repeated the paradigm using the cue electrode as the leading electrode. This pairing lowered the rat's ICMS-detection threshold, with the same dependence on intra-electrode time lag that we found for the functional connectivity changes. The timecourse of the behavioral effects was very similar to that of the connectivity changes. We propose that the behavioral changes were a consequence of strengthened functional connections from the cue electrode to other regions of sensorimotor cortex. Such paradigms might be used to augment recovery from a stroke, or to promote adaptation in a bidirectional brain-machine interface.

Grounded Learning Experience: Helping Students Learn Physics through Visuo-Haptic Priming and Instruction

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Huang, Shih-Chieh Douglas

2013-01-01

In this dissertation, I investigate the effects of a grounded learning experience on college students' mental models of physics systems. The grounded learning experience consisted of a priming stage and an instruction stage, and within each stage, one of two different types of visuo-haptic representation was applied: visuo-gestural simulation…

A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses

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Karim El-Laithy

2011-01-01

Full Text Available An integration of both the Hebbian-based and reinforcement learning (RL rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and the sign of the temporal difference in the reward signal after each trial. Applying this framework, a spiking network with spike-timing-dependent synapses is tested to learn the exclusive-OR computation on a temporally coded basis. Reward values are calculated with the distance between the output spike train of the network and a reference target one. Results show that the network is able to capture the required dynamics and that the proposed framework can reveal indeed an integrated version of Hebbian and RL. The proposed framework is tractable and less computationally expensive. The framework is applicable to a wide class of synaptic models and is not restricted to the used neural representation. This generality, along with the reported results, supports adopting the introduced approach to benefit from the biologically plausible synaptic models in a wide range of intuitive signal processing.

Planning School Grounds for Outdoor Learning

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Wagner, Cheryl; Gordon, Douglas

2010-01-01

This publication covers the planning and design of school grounds for outdoor learning in new and existing K-12 facilities. Curriculum development as well as athletic field planning and maintenance are not covered although some references on these topics are provided. It discusses the different types of outdoor learning environments that can be…

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

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Archibald, Lisa M D; Joanisse, Marc F

2013-02-01

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

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences.

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Philip J Tully

2016-05-01

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

Learning with three factors: modulating Hebbian plasticity with errors.

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Kuśmierz, Łukasz; Isomura, Takuya; Toyoizumi, Taro

2017-10-01

Synaptic plasticity is a central theme in neuroscience. A framework of three-factor learning rules provides a powerful abstraction, helping to navigate through the abundance of models of synaptic plasticity. It is well-known that the dopamine modulation of learning is related to reward, but theoretical models predict other functional roles of the modulatory third factor; it may encode errors for supervised learning, summary statistics of the population activity for unsupervised learning or attentional feedback. Specialized structures may be needed in order to generate and propagate third factors in the neural network. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Adaptive WTA with an analog VLSI neuromorphic learning chip.

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Häfliger, Philipp

2007-03-01

In this paper, we demonstrate how a particular spike-based learning rule (where exact temporal relations between input and output spikes of a spiking model neuron determine the changes of the synaptic weights) can be tuned to express rate-based classical Hebbian learning behavior (where the average input and output spike rates are sufficient to describe the synaptic changes). This shift in behavior is controlled by the input statistic and by a single time constant. The learning rule has been implemented in a neuromorphic very large scale integration (VLSI) chip as part of a neurally inspired spike signal image processing system. The latter is the result of the European Union research project Convolution AER Vision Architecture for Real-Time (CAVIAR). Since it is implemented as a spike-based learning rule (which is most convenient in the overall spike-based system), even if it is tuned to show rate behavior, no explicit long-term average signals are computed on the chip. We show the rule's rate-based Hebbian learning ability in a classification task in both simulation and chip experiment, first with artificial stimuli and then with sensor input from the CAVIAR system.

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

DEFF Research Database (Denmark)

Tully, Philip J; Lindén, Henrik; Hennig, Matthias H

2016-01-01

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed...... in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods...

Neuromodulated Spike-Timing-Dependent Plasticity and Theory of Three-Factor Learning Rules

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Wulfram eGerstner

2016-01-01

Full Text Available Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulatorson synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide 'when' to create new memories in response to a flow of sensory stimuli.In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discusssome experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity.We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators.

Neuroanatomical correlates of developmental dyscalculia: combined evidence from morphometry and tractography

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Elena Rykhlevskaia

2009-11-01

Full Text Available Poor mathematical abilities adversely affect academic and career opportunities. The neuroanatomical basis of developmental dyscalculia (DD, a specific learning deficit with prevalence rates exceeding 5%, is poorly understood. We used structural MRI and diffusion tensor imaging (DTI to examine macro- and micro-structural impairments in 7-9 year old children with DD, compared to a group of typically developing (TD children matched on age, gender, intelligence, reading abilities and working memory capacity. Voxel-based morphometry (VBM revealed reduced grey matter (GM bilaterally in superior parietal lobule, intra-parietal sulcus, fusiform gyrus, parahippocampal gyrus and right anterior temporal cortex in children with DD. VBM analysis also showed reduced white matter (WM volume in right temporal-parietal cortex. DTI revealed reduced fractional anisotropy (FA in this WM region, pointing to significant right hemisphere micro-structural impairments. Furthermore, FA in this region was correlated with numerical operations but not verbal mathematical reasoning or word reading. Atlas-based tract mapping identified the inferior longitudinal fasciculus, inferior fronto-occipital fasciculus and caudal forceps major as key pathways impaired in DD. DTI tractography suggests that long-range WM projection fibers linking the right fusiform gyrus with temporal-parietal WM are a specific source of vulnerability in DD. Network and classification analysis suggest that DD in children may be characterized by multiple dysfunctional circuits arising from a core WM deficit. Our findings link GM and WM abnormalities in children with DD and they point to macro- and micro-structural abnormalities in right hemisphere temporal-parietal WM, and pathways associated with it, as key neuroanatomical correlates of DD.

Robotic Assistance for Training Finger Movement Using a Hebbian Model: A Randomized Controlled Trial.

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Rowe, Justin B; Chan, Vicky; Ingemanson, Morgan L; Cramer, Steven C; Wolbrecht, Eric T; Reinkensmeyer, David J

2017-08-01

Robots that physically assist movement are increasingly used in rehabilitation therapy after stroke, yet some studies suggest robotic assistance discourages effort and reduces motor learning. To determine the therapeutic effects of high and low levels of robotic assistance during finger training. We designed a protocol that varied the amount of robotic assistance while controlling the number, amplitude, and exerted effort of training movements. Participants (n = 30) with a chronic stroke and moderate hemiparesis (average Box and Blocks Test 32 ± 18 and upper extremity Fugl-Meyer score 46 ± 12) actively moved their index and middle fingers to targets to play a musical game similar to GuitarHero 3 h/wk for 3 weeks. The participants were randomized to receive high assistance (causing 82% success at hitting targets) or low assistance (55% success). Participants performed ~8000 movements during 9 training sessions. Both groups improved significantly at the 1-month follow-up on functional and impairment-based motor outcomes, on depression scores, and on self-efficacy of hand function, with no difference between groups in the primary endpoint (change in Box and Blocks). High assistance boosted motivation, as well as secondary motor outcomes (Fugl-Meyer and Lateral Pinch Strength)-particularly for individuals with more severe finger motor deficits. Individuals with impaired finger proprioception at baseline benefited less from the training. Robot-assisted training can promote key psychological outcomes known to modulate motor learning and retention. Furthermore, the therapeutic effectiveness of robotic assistance appears to derive at least in part from proprioceptive stimulation, consistent with a Hebbian plasticity model.

Neuroanatomical profiles of personality change in frontotemporal lobar degeneration.

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Mahoney, Colin J; Rohrer, Jonathan D; Omar, Rohani; Rossor, Martin N; Warren, Jason D

2011-05-01

The neurobiological basis of personality is poorly understood. Frontotemporal lobar degeneration (FTLD) frequently presents with complex behavioural changes, and therefore potentially provides a disease model in which to investigate brain substrates of personality. To assess neuroanatomical correlates of personality change in a cohort of individuals with FTLD using voxel-based morphometry (VBM). Thirty consecutive individuals fulfilling consensus criteria for FTLD were assessed. Each participant's carer completed a Big Five Inventory (BFI) questionnaire on five key personality traits; for each trait, a change score was derived based on current compared with estimated premorbid characteristics. All participants underwent volumetric brain magnetic resonance imaging. A VBM analysis was implemented regressing change score for each trait against regional grey matter volume across the FTLD group. The FTLD group showed a significant decline in extraversion, agreeableness, conscientiousness and openness and an increase in neuroticism. Change in particular personality traits was associated with overlapping profiles of grey matter loss in more anterior cortical areas and relative preservation of grey matter in more posterior areas; the most robust neuroanatomical correlate was identified for reduced conscientiousness in the region of the posterior superior temporal gyrus. Quantitative measures of personality change in FTLD can be correlated with changes in regional grey matter. The neuroanatomical profiles for particular personality traits overlap brain circuits previously implicated in aspects of social cognition and suggest that dysfunction at the level of distributed cortical networks underpins personality change in FTLD.

ERP evidence for conflict in contingency learning.

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

2017-07-01

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

Circuit mechanisms of sensorimotor learning

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Makino, Hiroshi; Hwang, Eun Jung; Hedrick, Nathan G.; Komiyama, Takaki

2016-01-01

SUMMARY The relationship between the brain and the environment is flexible, forming the foundation for our ability to learn. Here we review the current state of our understanding of the modifications in the sensorimotor pathway related to sensorimotor learning. We divide the process in three hierarchical levels with distinct goals: 1) sensory perceptual learning, 2) sensorimotor associative learning, and 3) motor skill learning. Perceptual learning optimizes the representations of important sensory stimuli. Associative learning and the initial phase of motor skill learning are ensured by feedback-based mechanisms that permit trial-and-error learning. The later phase of motor skill learning may primarily involve feedback-independent mechanisms operating under the classic Hebbian rule. With these changes under distinct constraints and mechanisms, sensorimotor learning establishes dedicated circuitry for the reproduction of stereotyped neural activity patterns and behavior. PMID:27883902

Neuroanatomical considerations of isolated hearing loss in thalamic hemorrhage

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Nitin Agarwal, M.D.

2016-12-01

Conclusion: Presumably, this neurological deficit was caused by a hypertensive hemorrhage in the posterior right thalamus. The following case and discussion will review the potential neuroanatomical pathways that we suggest could make isolated hearing loss be part of a “thalamic syndrome.”

Learning with incomplete information in the committee machine.

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Bergmann, Urs M; Kühn, Reimer; Stamatescu, Ion-Olimpiu

2009-12-01

We study the problem of learning with incomplete information in a student-teacher setup for the committee machine. The learning algorithm combines unsupervised Hebbian learning of a series of associations with a delayed reinforcement step, in which the set of previously learnt associations is partly and indiscriminately unlearnt, to an extent that depends on the success rate of the student on these previously learnt associations. The relevant learning parameter lambda represents the strength of Hebbian learning. A coarse-grained analysis of the system yields a set of differential equations for overlaps of student and teacher weight vectors, whose solutions provide a complete description of the learning behavior. It reveals complicated dynamics showing that perfect generalization can be obtained if the learning parameter exceeds a threshold lambda ( c ), and if the initial value of the overlap between student and teacher weights is non-zero. In case of convergence, the generalization error exhibits a power law decay as a function of the number of examples used in training, with an exponent that depends on the parameter lambda. An investigation of the system flow in a subspace with broken permutation symmetry between hidden units reveals a bifurcation point lambda* above which perfect generalization does not depend on initial conditions. Finally, we demonstrate that cases of a complexity mismatch between student and teacher are optimally resolved in the sense that an over-complex student can emulate a less complex teacher rule, while an under-complex student reaches a state which realizes the minimal generalization error compatible with the complexity mismatch.

Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.

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Eduardo J Izquierdo

Full Text Available Increased efforts in the assembly and analysis of connectome data are providing new insights into the principles underlying the connectivity of neural circuits. However, despite these considerable advances in connectomics, neuroanatomical data must be integrated with neurophysiological and behavioral data in order to obtain a complete picture of neural function. Due to its nearly complete wiring diagram and large behavioral repertoire, the nematode worm Caenorhaditis elegans is an ideal organism in which to explore in detail this link between neural connectivity and behavior. In this paper, we develop a neuroanatomically-grounded model of salt klinotaxis, a form of chemotaxis in which changes in orientation are directed towards the source through gradual continual adjustments. We identify a minimal klinotaxis circuit by systematically searching the C. elegans connectome for pathways linking chemosensory neurons to neck motor neurons, and prune the resulting network based on both experimental considerations and several simplifying assumptions. We then use an evolutionary algorithm to find possible values for the unknown electrophsyiological parameters in the network such that the behavioral performance of the entire model is optimized to match that of the animal. Multiple runs of the evolutionary algorithm produce an ensemble of such models. We analyze in some detail the mechanisms by which one of the best evolved circuits operates and characterize the similarities and differences between this mechanism and other solutions in the ensemble. Finally, we propose a series of experiments to determine which of these alternatives the worm may be using.

Action Learning and Constructivist Grounded Theory: Powerfully Overlapping Fields of Practice

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Rand, Jane

2013-01-01

This paper considers the shared characteristics between action learning (AL) and the research methodology constructivist grounded theory (CGT). Mirroring Edmonstone's [2011. "Action Learning and Organisation Development: Overlapping Fields of Practice." "Action Learning: Research and Practice" 8 (2): 93-102] article, which…

Vaccination learning experiences of nursing students: a grounded theory study.

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Ildarabadi, Eshagh; Karimi Moonaghi, Hossein; Heydari, Abbas; Taghipour, Ali; Abdollahimohammad, Abdolghani

2015-01-01

This study aimed to explore the experiences of nursing students being trained to perform vaccinations. The grounded theory method was applied to gather information through semi-structured interviews. The participants included 14 undergraduate nursing students in their fifth and eighth semesters of study in a nursing school in Iran. The information was analyzed according to Strauss and Corbin's method of grounded theory. A core category of experiential learning was identified, and the following eight subcategories were extracted: students' enthusiasm, vaccination sensitivity, stress, proper educational environment, absence of prerequisites, students' responsibility for learning, providing services, and learning outcomes. The vaccination training of nursing students was found to be in an acceptable state. However, some barriers to effective learning were identified. As such, the results of this study may provide empirical support for attempts to reform vaccination education by removing these barriers.

Employees' and Managers' Accounts of Interactive Workplace Learning: A Grounded Theory of "Complex Integrative Learning"

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Armson, Genevieve; Whiteley, Alma

2010-01-01

Purpose: The purpose of this paper is to investigate employees' and managers' accounts of interactive learning and what might encourage or inhibit emergent learning. Design/methodology/approach: The approach taken was a constructivist/social constructivist ontology, interpretive epistemology and qualitative methodology, using grounded theory…

Neuroanatomical profiles of bilingual children.

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Archila-Suerte, Pilar; Woods, Elizabeth A; Chiarello, Christine; Hernandez, Arturo E

2018-02-26

The goal of the present study was to examine differences in cortical thickness, cortical surface area, and subcortical volume between bilingual children who are highly proficient in two languages (i.e., English and Spanish) and bilingual children who are mainly proficient in one of the languages (i.e., Spanish). All children (N = 49) learned Spanish as a native language (L1) at home and English as a second language (L2) at school. Proficiency of both languages was assessed using the standardized Woodcock Language Proficiency Battery. Five-minute high-resolution anatomical scans were acquired with a 3-Tesla scanner. The degree of discrepancy between L1 and L2 proficiency was used to classify the children into two groups: children with balanced proficiency and children with unbalanced proficiency. The groups were comparable on language history, parental education, and other variables except English proficiency. Values of cortical thickness and surface area of the transverse STG, IFG-pars opercularis, and MFG, as well as subcortical volume of the caudate and putamen, were extracted from FreeSurfer. Results showed that children with balanced bilingualism had thinner cortices of the left STG, left IFG, left MFG and a larger bilateral putamen, whereas unbalanced bilinguals showed thicker cortices of the same regions and a smaller putamen. Additionally, unbalanced bilinguals with stronger foreign accents in the L2 showed reduced surface areas of the MFG and STS bilaterally. The results suggest that balanced/unbalanced bilingualism is reflected in different neuroanatomical characteristics that arise from biological and/or environmental factors. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Delta Learning Rule for the Active Sites Model

OpenAIRE

Lingashetty, Krishna Chaithanya

2010-01-01

This paper reports the results on methods of comparing the memory retrieval capacity of the Hebbian neural network which implements the B-Matrix approach, by using the Widrow-Hoff rule of learning. We then, extend the recently proposed Active Sites model by developing a delta rule to increase memory capacity. Also, this paper extends the binary neural network to a multi-level (non-binary) neural network.

GP and pharmacist inter-professional learning - a grounded theory study.

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Cunningham, David E; Ferguson, Julie; Wakeling, Judy; Zlotos, Leon; Power, Ailsa

2016-05-01

Practice Based Small Group Learning (PBSGL) is an established learning resource for primary care clinicians in Scotland and is used by one-third of general practitioners (GPs). Scottish Government and UK professional bodies have called for GPs and pharmacists to work more closely together to improve care. To gain GPs' and pharmacists' perceptions and experiences of learning together in an inter-professional PBSGL pilot. Qualitative research methods involving established GP PBSGL groups in NHS Scotland recruiting one or two pharmacists to join them. A grounded theory method was used. GPs were interviewed in focus groups by a fellow GP, and pharmacists were interviewed individually by two researchers, neither being a GP or a pharmacist. Interviews were audio-recorded, transcribed and analysed using grounded theory methods. Data saturation was achieved and confirmed. Three themes were identified: GPs' and pharmacists' perceptions and experiences of inter-professional learning; Inter-professional relationships and team-working; Group identity and purpose of existing GP groups. Pharmacists were welcomed into GP groups and both professions valued inter-professional PBSGL learning. Participants learned from each other and both professions gained a wider perspective of the NHS and of each others' roles in the organisation. Inter-professional relationships, communication and team-working were strengthened and professionals regarded each other as peers and friends.

Analysis of ensemble learning using simple perceptrons based on online learning theory

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Miyoshi, Seiji; Hara, Kazuyuki; Okada, Masato

2005-03-01

Ensemble learning of K nonlinear perceptrons, which determine their outputs by sign functions, is discussed within the framework of online learning and statistical mechanics. One purpose of statistical learning theory is to theoretically obtain the generalization error. This paper shows that ensemble generalization error can be calculated by using two order parameters, that is, the similarity between a teacher and a student, and the similarity among students. The differential equations that describe the dynamical behaviors of these order parameters are derived in the case of general learning rules. The concrete forms of these differential equations are derived analytically in the cases of three well-known rules: Hebbian learning, perceptron learning, and AdaTron (adaptive perceptron) learning. Ensemble generalization errors of these three rules are calculated by using the results determined by solving their differential equations. As a result, these three rules show different characteristics in their affinity for ensemble learning, that is “maintaining variety among students.” Results show that AdaTron learning is superior to the other two rules with respect to that affinity.

The effect of STDP temporal kernel structure on the learning dynamics of single excitatory and inhibitory synapses.

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Yotam Luz

Full Text Available Spike-Timing Dependent Plasticity (STDP is characterized by a wide range of temporal kernels. However, much of the theoretical work has focused on a specific kernel - the "temporally asymmetric Hebbian" learning rules. Previous studies linked excitatory STDP to positive feedback that can account for the emergence of response selectivity. Inhibitory plasticity was associated with negative feedback that can balance the excitatory and inhibitory inputs. Here we study the possible computational role of the temporal structure of the STDP. We represent the STDP as a superposition of two processes: potentiation and depression. This allows us to model a wide range of experimentally observed STDP kernels, from Hebbian to anti-Hebbian, by varying a single parameter. We investigate STDP dynamics of a single excitatory or inhibitory synapse in purely feed-forward architecture. We derive a mean-field-Fokker-Planck dynamics for the synaptic weight and analyze the effect of STDP structure on the fixed points of the mean field dynamics. We find a phase transition along the Hebbian to anti-Hebbian parameter from a phase that is characterized by a unimodal distribution of the synaptic weight, in which the STDP dynamics is governed by negative feedback, to a phase with positive feedback characterized by a bimodal distribution. The critical point of this transition depends on general properties of the STDP dynamics and not on the fine details. Namely, the dynamics is affected by the pre-post correlations only via a single number that quantifies its overlap with the STDP kernel. We find that by manipulating the STDP temporal kernel, negative feedback can be induced in excitatory synapses and positive feedback in inhibitory. Moreover, there is an exact symmetry between inhibitory and excitatory plasticity, i.e., for every STDP rule of inhibitory synapse there exists an STDP rule for excitatory synapse, such that their dynamics is identical.

Factors Contributing to Cognitive Absorption and Grounded Learning Effectiveness in a Competitive Business Marketing Simulation

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Baker, David Scott; Underwood, James, III; Thakur, Ramendra

2017-01-01

This study aimed to establish a pedagogical positioning of a business marketing simulation as a grounded learning teaching tool and empirically assess the dimensions of cognitive absorption related to grounded learning effectiveness in an iterative business simulation environment. The method/design and sample consisted of a field study survey…

Competitive STDP Learning of Overlapping Spatial Patterns.

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Krunglevicius, Dalius

2015-08-01

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

Midwifery students learning experiences in labor wards: a grounded theory.

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Brunstad, Anne; Hjälmhult, Esther

2014-12-01

The labor ward is an important and challenging learning area for midwifery students. It is there the students learn in authentic complex situations, in intimate situations, with potential risk for the life and health of mothers and their babies. The aim of this study was to explore the main concern expressed by midwifery students in labor wards and how they handled this concern. A longitudinal study based on grounded theory methodology was used. The participants were 10 postgraduate midwifery students, from a University College in Norway. Data were gathered and analyzed throughout the 2-year postgraduate program, in the students first, third and fourth semesters. Every student was interviewed three times in a total of 15 single and three focus-group sessions. The grounded theory of "building relationships" explains how students dealt with their main concern: "how to gain access to learning experiences". This theory consisted of three strategies; a) controlling vulnerability, b) cultivating trust and c) obtaining acceptance. Clarifying discussions involving midwives and students may facilitate the process of building relationships and contribute to confident learning. Students appreciate it when the midwives initiate discussions about acute situations and state that a novice may perceive labor and childbirth as more frightening than an experienced midwife would. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Neuroanatomical Signature for Schizophrenia Across Different Ethnic Groups.

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Gong, Qiyong; Dazzan, Paola; Scarpazza, Cristina; Kasai, Kyioto; Hu, Xinyu; Marques, Tiago R; Iwashiro, Norichika; Huang, Xiaoqi; Murray, Robin M; Koike, Shinsuke; David, Anthony S; Yamasue, Hidenori; Lui, Su; Mechelli, Andrea

2015-11-01

Schizophrenia is a disabling clinical syndrome found across the world. While the incidence and clinical expression of this illness are strongly influenced by ethnic factors, it is unclear whether patients from different ethnicities show distinct brain deficits. In this multicentre study, we used structural Magnetic Resonance Imaging to investigate neuroanatomy in 126 patients with first episode schizophrenia who came from 4 ethnically distinct cohorts (White Caucasians, African-Caribbeans, Japanese, and Chinese). Each patient was individually matched with a healthy control of the same ethnicity, gender, and age (±1 year). We report a reduction in the gray matter volume of the right anterior insula in patients relative to controls (P ethnic groups despite differences in psychopathology, exposure to antipsychotic medication and image acquisition sequence. This finding provides evidence for a neuroanatomical signature of schizophrenia expressed above and beyond ethnic variations in incidence and clinical expression. In light of the existing literature, implicating the right anterior insula in bipolar disorder, depression, addiction, obsessive-compulsive disorder, and anxiety, we speculate that the neuroanatomical deficit reported here may represent a transdiagnostic feature of Axis I disorders. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

Neuroanatomical study of Galen's anastomosis (nervus laryngeus) in the dog.

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Henry, C; Cazals, Y; Gioux, M; Didier, A; Aran, J M; Traissac, L

1988-01-01

To further knowledge of the laryngeal nerves, the nerve fibers of Galen's anastomosis were studied using two neuroanatomical methods, namely nerve degeneration and horseradish peroxidase labeling. It is demonstrated that the superior laryngeal nerve forms part of the tracheal and esophageal nervous system. The value of the results in relation to physiological laryngeal studies and to human laryngeal diseases is discussed.

Multi-parameter machine learning approach to the neuroanatomical basis of developmental dyslexia.

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Płoński, Piotr; Gradkowski, Wojciech; Altarelli, Irene; Monzalvo, Karla; van Ermingen-Marbach, Muna; Grande, Marion; Heim, Stefan; Marchewka, Artur; Bogorodzki, Piotr; Ramus, Franck; Jednoróg, Katarzyna

2017-02-01

Despite decades of research, the anatomical abnormalities associated with developmental dyslexia are still not fully described. Studies have focused on between-group comparisons in which different neuroanatomical measures were generally explored in isolation, disregarding potential interactions between regions and measures. Here, for the first time a multivariate classification approach was used to investigate grey matter disruptions in children with dyslexia in a large (N = 236) multisite sample. A variety of cortical morphological features, including volumetric (volume, thickness and area) and geometric (folding index and mean curvature) measures were taken into account and generalizability of classification was assessed with both 10-fold and leave-one-out cross validation (LOOCV) techniques. Classification into control vs. dyslexic subjects achieved above chance accuracy (AUC = 0.66 and ACC = 0.65 in the case of 10-fold CV, and AUC = 0.65 and ACC = 0.64 using LOOCV) after principled feature selection. Features that discriminated between dyslexic and control children were exclusively situated in the left hemisphere including superior and middle temporal gyri, subparietal sulcus and prefrontal areas. They were related to geometric properties of the cortex, with generally higher mean curvature and a greater folding index characterizing the dyslexic group. Our results support the hypothesis that an atypical curvature pattern with extra folds in left hemispheric perisylvian regions characterizes dyslexia. Hum Brain Mapp 38:900-908, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Shaping a valued learning journey: Student satisfaction with learning in undergraduate nursing programs, a grounded theory study.

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Smith, Morgan R; Grealish, Laurie; Henderson, Saras

2018-05-01

Student satisfaction is a quality measure of increasing importance in undergraduate programs, including nursing programs. To date theories of student satisfaction have focused primarily on students' perceptions of the educational environment rather than their perceptions of learning. Understanding how students determine satisfaction with learning is necessary to facilitate student learning across a range of educational contexts and meet the expectations of diverse stakeholders. To understand undergraduate nursing students' satisfaction with learning. Constructivist grounded theory methodology was used to identify how nursing students determined satisfaction with learning. Two large, multi-campus, nursing schools in Australia. Seventeen demographically diverse undergraduate nursing students studying different stages of a three year program participated in the study. Twenty nine semi-structured interviews were conducted. Students were invited to describe situations where they had been satisfied or dissatisfied with their learning. A constructivist grounded theory approach was used to analyse the data. Students are satisfied with learning when they shape a valued learning journey that accommodates social contexts of self, university and nursing workplace. The theory has three phases. Phase 1 - orienting self to valued learning in the pedagogical landscape; phase 2 - engaging with valued learning experiences across diverse pedagogical terrain; and phase 3 - recognising valued achievement along the way. When students experience a valued learning journey they are satisfied with their learning. Student satisfaction with learning is unique to the individual, changes over time and maybe transient or sustained, mild or intense. Finding from the research indicate areas where nurse academics may facilitate satisfaction with learning in undergraduate nursing programs while mindful of the expectations of other stakeholders such as the university, nurse registering authorities

The neuroanatomical phenotype of tuberous sclerosis complex: focus on radial migration lines

International Nuclear Information System (INIS)

Eeghen, Agnies M. van; Teran, Laura Ortiz; Johnson, Jason; Caruso, Paul; Pulsifer, Margaret B.; Thiele, Elizabeth A.

2013-01-01

The contribution of radial migration lines (RMLs) to the neuroanatomical and neurocognitive phenotype of tuberous sclerosis complex (TSC) is unclear. The aim of this study was to perform a comprehensive evaluation of the neuroradiological phenotype of TSC, distinguishing RMLs from normal-appearing white matter (NAWM) using diffusion tensor imaging (DTI) and volumetric fluid-attenuated inversion recovery imaging. Magnetic resonance images of 30 patients with TSC were evaluated. The frequencies of RMLs, tubers, and subependymal nodules (SENs) were determined for every hemispheric lobe. Cerebellar lesions and subependymal giant cell tumors were counted. DTI metrics were obtained from the NAWM of every hemispheric lobe and from the largest RML and tuber. Analyses of variance and correlations were performed to investigate the associations between neuroanatomical characteristics and relationships between RML frequency and neurocognitive outcomes. NAWM DTI metrics were compared with measurements of 16 control patients. A mean of 47 RMLs, 27 tubers, and 10 SENs were found per patient, and the frequencies of these lesions were strongly correlated (p < 0.001). RML fractional anisotropy and mean diffusivity were strongly inversely correlated (p = 0.003). NAWM DTI metrics were similar to the controls (p = 0.26). RML frequency was strongly associated with age of seizure onset (p = 0.003), intelligence outcomes (p = 0.01), and level of autistic features (p = 0.007). A detailed neuroradiological phenotype is presented, showing that RMLs are the most frequent neuroanatomical lesion, are responsible for white matter DTI abnormalities, and are strongly associated with age of seizure onset, intelligence outcomes, and level of autistic features. (orig.)

The neuroanatomical phenotype of tuberous sclerosis complex: focus on radial migration lines

Energy Technology Data Exchange (ETDEWEB)

Eeghen, Agnies M. van [Massachusetts General Hospital, Department of Neurology, Carol and James Herscot Center for Tuberous Sclerosis Complex, Boston, MA (United States); Erasmus Medical Centre, ENCORE, Expertise Centre for Neurodevelopmental Disorders, Department of Neuroscience, Rotterdam (Netherlands); Teran, Laura Ortiz; Johnson, Jason; Caruso, Paul [Massachusetts General Hospital, Department of Radiology, Boston, MA (United States); Pulsifer, Margaret B. [Massachusetts General Hospital, Department of Psychiatry, Psychological Assessment Center, Boston, MA (United States); Thiele, Elizabeth A. [Massachusetts General Hospital, Department of Neurology, Carol and James Herscot Center for Tuberous Sclerosis Complex, Boston, MA (United States)

2013-08-15

The contribution of radial migration lines (RMLs) to the neuroanatomical and neurocognitive phenotype of tuberous sclerosis complex (TSC) is unclear. The aim of this study was to perform a comprehensive evaluation of the neuroradiological phenotype of TSC, distinguishing RMLs from normal-appearing white matter (NAWM) using diffusion tensor imaging (DTI) and volumetric fluid-attenuated inversion recovery imaging. Magnetic resonance images of 30 patients with TSC were evaluated. The frequencies of RMLs, tubers, and subependymal nodules (SENs) were determined for every hemispheric lobe. Cerebellar lesions and subependymal giant cell tumors were counted. DTI metrics were obtained from the NAWM of every hemispheric lobe and from the largest RML and tuber. Analyses of variance and correlations were performed to investigate the associations between neuroanatomical characteristics and relationships between RML frequency and neurocognitive outcomes. NAWM DTI metrics were compared with measurements of 16 control patients. A mean of 47 RMLs, 27 tubers, and 10 SENs were found per patient, and the frequencies of these lesions were strongly correlated (p < 0.001). RML fractional anisotropy and mean diffusivity were strongly inversely correlated (p = 0.003). NAWM DTI metrics were similar to the controls (p = 0.26). RML frequency was strongly associated with age of seizure onset (p = 0.003), intelligence outcomes (p = 0.01), and level of autistic features (p = 0.007). A detailed neuroradiological phenotype is presented, showing that RMLs are the most frequent neuroanatomical lesion, are responsible for white matter DTI abnormalities, and are strongly associated with age of seizure onset, intelligence outcomes, and level of autistic features. (orig.)

Invertebrate neurophylogeny: suggested terms and definitions for a neuroanatomical glossary

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Müller Carsten HG

2010-11-01

Full Text Available Abstract Background Invertebrate nervous systems are highly disparate between different taxa. This is reflected in the terminology used to describe them, which is very rich and often confusing. Even very general terms such as 'brain', 'nerve', and 'eye' have been used in various ways in the different animal groups, but no consensus on the exact meaning exists. This impedes our understanding of the architecture of the invertebrate nervous system in general and of evolutionary transformations of nervous system characters between different taxa. Results We provide a glossary of invertebrate neuroanatomical terms with a precise and consistent terminology, taxon-independent and free of homology assumptions. This terminology is intended to form a basis for new morphological descriptions. A total of 47 terms are defined. Each entry consists of a definition, discouraged terms, and a background/comment section. Conclusions The use of our revised neuroanatomical terminology in any new descriptions of the anatomy of invertebrate nervous systems will improve the comparability of this organ system and its substructures between the various taxa, and finally even lead to better and more robust homology hypotheses.

Optical implementations of associative networks with versatile adaptive learning capabilities.

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Fisher, A D; Lippincott, W L; Lee, J N

1987-12-01

Optical associative, parallel-processing architectures are being developed using a multimodule approach, where a number of smaller, adaptive, associative modules are nonlinearly interconnected and cascaded under the guidance of a variety of organizational principles to structure larger architectures for solving specific problems. A number of novel optical implementations with versatile adaptive learning capabilities are presented for the individual associative modules, including holographic configurations and five specific electrooptic configurations. The practical issues involved in real optical architectures are analyzed, and actual laboratory optical implementations of associative modules based on Hebbian and Widrow-Hoff learning rules are discussed, including successful experimental demonstrations of their operation.

NAPR: a Cloud-Based Framework for Neuroanatomical Age Prediction.

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Pardoe, Heath R; Kuzniecky, Ruben

2018-01-01

The availability of cloud computing services has enabled the widespread adoption of the "software as a service" (SaaS) approach for software distribution, which utilizes network-based access to applications running on centralized servers. In this paper we apply the SaaS approach to neuroimaging-based age prediction. Our system, named "NAPR" (Neuroanatomical Age Prediction using R), provides access to predictive modeling software running on a persistent cloud-based Amazon Web Services (AWS) compute instance. The NAPR framework allows external users to estimate the age of individual subjects using cortical thickness maps derived from their own locally processed T1-weighted whole brain MRI scans. As a demonstration of the NAPR approach, we have developed two age prediction models that were trained using healthy control data from the ABIDE, CoRR, DLBS and NKI Rockland neuroimaging datasets (total N = 2367, age range 6-89 years). The provided age prediction models were trained using (i) relevance vector machines and (ii) Gaussian processes machine learning methods applied to cortical thickness surfaces obtained using Freesurfer v5.3. We believe that this transparent approach to out-of-sample evaluation and comparison of neuroimaging age prediction models will facilitate the development of improved age prediction models and allow for robust evaluation of the clinical utility of these methods.

Homeostatic role of heterosynaptic plasticity: Models and experiments

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Marina eChistiakova

2015-07-01

Full Text Available Homosynaptic Hebbian-type plasticity provides a cellular mechanism of learning and refinement of connectivity during development in a variety of biological systems. In this review we argue that a complimentary form of plasticity - heterosynaptic plasticity - represents a necessary cellular component for homeostatic regulation of synaptic weights and neuronal activity. The required properties of a homeostatic mechanism which acutely constrains the runaway dynamics imposed by Hebbian associative plasticity have been well-articulated by theoretical and modeling studies. Such mechanism(s should robustly support the stability of operation of neuronal networks and synaptic competition, include changes at non-active synapses, and operate on a similar time scale to Hebbian-type plasticity. The experimentally observed properties of heterosynaptic plasticity have introduced it as a strong candidate to fulfill this homeostatic role. Subsequent modeling studies which incorporate heterosynaptic plasticity into model neurons with Hebbian synapses (utilizing an STDP learning rule have confirmed its ability to robustly provide stability and competition. In contrast, properties of homeostatic synaptic scaling, which is triggered by extreme and long lasting (hours and days changes of neuronal activity, do not fit two crucial requirements for a hypothetical homeostatic mechanism needed to provide stability of operation in the face of on-going synaptic changes driven by Hebbian-type learning rules. Both the trigger and the time scale of homeostatic synaptic scaling are fundamentally different from those of the Hebbian-type plasticity. We conclude that heterosynaptic plasticity, which is triggered by the same episodes of strong postsynaptic activity and operates on the same time scale as Hebbian-type associative plasticity, is ideally suited to serve homeostatic role during on-going synaptic plasticity.

A Learning Model for L/M Specificity in Ganglion Cells

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Ahumada, Albert J.

2016-01-01

An unsupervised learning model for developing LM specific wiring at the ganglion cell level would support the research indicating LM specific wiring at the ganglion cell level (Reid and Shapley, 2002). Removing the contributions to the surround from cells of the same cone type improves the signal-to-noise ratio of the chromatic signals. The unsupervised learning model used is Hebbian associative learning, which strengthens the surround input connections according to the correlation of the output with the input. Since the surround units of the same cone type as the center are redundant with the center, their weights end up disappearing. This process can be thought of as a general mechanism for eliminating unnecessary cells in the nervous system.

Cognitive consilience: Primate non-primary neuroanatomical circuits underlying cognition

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Soren Van Hout Solari

2011-12-01

Full Text Available Interactions between the cerebral cortex, thalamus, and basal ganglia form the basis ofcognitive information processing in the mammalian brain. Understanding the principles ofneuroanatomical organization in these structures is critical to understanding the functions theyperform and ultimately how the human brain works. We have manually distilled and synthesizedhundreds of primate neuroanatomy facts into a single interactive visualization. The resultingpicture represents the fundamental neuroanatomical blueprint upon which cognitive functionsmust be implemented. Within this framework we hypothesize and detail 7 functional circuitscorresponding to psychological perspectives on the brain: consolidated long-term declarativememory, short-term declarative memory, working memory/information processing, behavioralmemory selection, behavioral memory output, cognitive control, and cortical information flow regulation. Each circuit is described in terms of distinguishable neuronal groups including thecerebral isocortex (9 pyramidal neuronal groups, parahippocampal gyrus and hippocampus,thalamus (4 neuronal groups, basal ganglia (7 neuronal groups, metencephalon, basal forebrainand other subcortical nuclei. We focus on neuroanatomy related to primate non-primary corticalsystems to elucidate the basis underlying the distinct homotypical cognitive architecture. To dis-play the breadth of this review, we introduce a novel method of integrating and presenting datain multiple independent visualizations: an interactive website (www.cognitiveconsilience.comand standalone iPhone and iPad applications. With these tools we present a unique, annotatedview of neuroanatomical consilience (integration of knowledge.

STEPP: A Grounded Model to Assure the Quality of Instructional Activities in e-Learning Environments

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Hamdy AHMED ABDELAZIZ

2013-07-01

Full Text Available The present theoretical paper aims to develop a grounded model for designing instructional activities appropriate to e-learning and online learning environments. The suggested model is guided by learning principles of cognitivism, constructivism, and connectivism learning principles to help online learners constructing meaningful experiences and moving from knowledge acquisition to knowledge creation process. The proposed model consists of five dynamic and grounded domains that assure the quality of designing and using e-learning activities: Ø Social Domain; Ø Technological Domain; Ø Epistemological Domain; Ø Psychological domain; and Ø Pedagogical Domain. Each of these domains needs four types of presences to reflect the design and the application process of e-learning activities. These four presences are: Ø cognitive presence, Ø human presence, Ø psychological presence and Ø mental presence. Applying the proposed model (STEPP throughout all online and adaptive e-learning environments may improve the process of designing and developing e-learning activities to be used as mindtools for current and future learners.

Learning in AN Oscillatory Cortical Model

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Scarpetta, Silvia; Li, Zhaoping; Hertz, John

We study a model of generalized-Hebbian learning in asymmetric oscillatory neural networks modeling cortical areas such as hippocampus and olfactory cortex. The learning rule is based on the synaptic plasticity observed experimentally, in particular long-term potentiation and long-term depression of the synaptic efficacies depending on the relative timing of the pre- and postsynaptic activities during learning. The learned memory or representational states can be encoded by both the amplitude and the phase patterns of the oscillating neural populations, enabling more efficient and robust information coding than in conventional models of associative memory or input representation. Depending on the class of nonlinearity of the activation function, the model can function as an associative memory for oscillatory patterns (nonlinearity of class II) or can generalize from or interpolate between the learned states, appropriate for the function of input representation (nonlinearity of class I). In the former case, simulations of the model exhibits a first order transition between the "disordered state" and the "ordered" memory state.

Neurogenetic and Neurodevelopmental Pathways to Learning Disabilities.

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Mazzocco, Michele M. M.; And Others

1997-01-01

This paper reviews ongoing research designed to specify the cognitive, behavioral, and neuroanatomical phenotypes of specific genetic etiologies of learning disability. The genetic disorders at the focus of the research include reading disability, neurofibromatosis type 1, Tourette syndrome, and fragile X syndrome. Implications for identifying…

Associative Learning in Invertebrates

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Hawkins, Robert D.; Byrne, John H.

2015-01-01

This work reviews research on neural mechanisms of two types of associative learning in the marine mollusk Aplysia, classical conditioning of the gill- and siphon-withdrawal reflex and operant conditioning of feeding behavior. Basic classical conditioning is caused in part by activity-dependent facilitation at sensory neuron–motor neuron (SN–MN) synapses and involves a hybrid combination of activity-dependent presynaptic facilitation and Hebbian potentiation, which are coordinated by trans-synaptic signaling. Classical conditioning also shows several higher-order features, which might be explained by the known circuit connections in Aplysia. Operant conditioning is caused in part by a different type of mechanism, an intrinsic increase in excitability of an identified neuron in the central pattern generator (CPG) for feeding. However, for both classical and operant conditioning, adenylyl cyclase is a molecular site of convergence of the two signals that are associated. Learning in other invertebrate preparations also involves many of the same mechanisms, which may contribute to learning in vertebrates as well. PMID:25877219

The dentate gyrus: fundamental neuroanatomical organization (dentate gyrus for dummies).

OpenAIRE

Amaral David G; Scharfman Helen E; Lavenex Pierre

2007-01-01

The dentate gyrus is a simple cortical region that is an integral portion of the larger functional brain system called the hippocampal formation. In this review, the fundamental neuroanatomical organization of the dentate gyrus is described, including principal cell types and their connectivity, and a summary of the major extrinsic inputs of the dentate gyrus is provided. Together, this information provides essential information that can serve as an introduction to the dentate gyrus — a “dent...

Convergence and divergence of neuroanatomic correlates and executive task performance in healthy controls and psychiatric participants.

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Ming-Tak Chung, Dennis; Jerram, Matthew W; Lee, Jonathan K; Katz, Harvey; Gansler, David A

2013-12-30

The associations between brain matter volume in the cerebral cortex and set shifting and attentional control as operationalized by the Wisconsin Card Sort Test (WCST) and Condition Three of the Delis-Kaplan version of the Color Word Interference Test (CWIT) were investigated in 15 healthy controls and 16 heterogeneously diagnosed psychiatric patients with self-control problems using voxel based morphometry. Both groups underwent standardized magnetic resonance imaging and neuropsychological assessment. WCST and CWIT variables, and a composite, were regressed across the whole brain. Although CWIT performance levels were the same in both groups, neuroanatomic correlates for the psychiatric participants invoked the left hemisphere language system, but the bilateral dorsal attention system in the healthy controls. On its own, no neuroanatomic correlates were observed for the WCST. But when part of a composite with CWIT, neuroanatomic correlates in the dorsal attention system emerged for the psychiatric participants. Psychometric combinations of manifest executive task variables may best represent higher level latent neuro-cognitive control systems. Factor analytic studies of neuropsychological test performances suggest the constructs being measured are the same across psychiatric and non-diagnosed participants, however, imaging modalities indicate the relevant neural architecture can vary by group. © 2013 Elsevier Ireland Ltd. All rights reserved.

Nasal Consonant Production in Broca's and Wernicke's Aphasics: Speech Deficits and Neuroanatomical Correlates

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Kurowski, Kathleen M.; Blumstein, Sheila E.; Palumbo, Carole L.; Waldstein, Robin S.; Burton, Martha W.

2007-01-01

The present study investigated the articulatory implementation deficits of Broca's and Wernicke's aphasics and their potential neuroanatomical correlates. Five Broca's aphasics, two Wernicke's aphasics, and four age-matched normal speakers produced consonant-vowel-(consonant) real word tokens consisting of [m, n] followed by [i, e, a, o, u]. Three…

Designing Grounded Feedback: Criteria for Using Linked Representations to Support Learning of Abstract Symbols

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Wiese, Eliane S.; Koedinger, Kenneth R.

2017-01-01

This paper proposes "grounded feedback" as a way to provide implicit verification when students are working with a novel representation. In grounded feedback, students' responses are in the target, to-be-learned representation, and those responses are reflected in a more-accessible linked representation that is intrinsic to the domain.…

Interaction between neuroanatomical and psychological changes after mindfulness-based training.

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Emiliano Santarnecchi

Full Text Available Several cross-sectional studies have documented neuroanatomical changes in individuals with a long history of meditation, while a few evidences are available about the interaction between neuroanatomical and psychological changes even during brief exposure to meditation. Here we analyzed several morphometric indexes at both cortical and subcortical brain level, as well as multiple psychological dimensions, before and after a brief -8 weeks- Mindfulness Based Stress Reduction (MBSR training program, in a group of 23 meditation naïve-subjects compared to age-gender matched subjects. We found a significant cortical thickness increase in the right insula and the somatosensory cortex of MBSR trainees, coupled with a significant reduction of several psychological indices related to worry, state anxiety, depression and alexithymia. Most importantly, an interesting correlation between the increase in right insula thickness and the decrease in alexithymia levels during the MBSR training were observed. Moreover, a multivariate pattern classification approach allowed to identify a cluster of regions more responsive to MBSR training across subjects. Taken together, these findings documented the significant impact of a brief MBSR training on brain structures, as well as stressing the idea of MBSR as a valuable tool for alexithymia modulation, also originally providing a plausible neurobiological evidence of a major role of right insula into mediating the observed psychological changes.

Neuroanatomical circuitry associated with exploratory eye movement in schizophrenia: a voxel-based morphometric study.

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Linlin Qiu

Full Text Available Schizophrenic patients present abnormalities in a variety of eye movement tasks. Exploratory eye movement (EEM dysfunction appears to be particularly specific to schizophrenia. However, the underlying mechanisms of EEM dysfunction in schizophrenia are not clearly understood. To assess the potential neuroanatomical substrates of EEM, we recorded EEM performance and conducted a voxel-based morphometric analysis of gray matter in 33 schizophrenic patients and 29 well matched healthy controls. In schizophrenic patients, decreased responsive search score (RSS and widespread gray matter density (GMD reductions were observed. Moreover, the RSS was positively correlated with GMD in distributed brain regions in schizophrenic patients. Furthermore, in schizophrenic patients, some brain regions with neuroanatomical deficits overlapped with some ones associated with RSS. These brain regions constituted an occipito-tempro-frontal circuitry involved in visual information processing and eye movement control, including the left calcarine cortex [Brodmann area (BA 17], the left cuneus (BA 18, the left superior occipital cortex (BA 18/19, the left superior frontal gyrus (BA 6, the left cerebellum, the right lingual cortex (BA 17/18, the right middle occipital cortex (BA19, the right inferior temporal cortex (BA 37, the right dorsolateral prefrontal cortex (BA 46 and bilateral precentral gyri (BA 6 extending to the frontal eye fields (FEF, BA 8. To our knowledge, we firstly reported empirical evidence that gray matter loss in the occipito-tempro-frontal neuroanatomical circuitry of visual processing system was associated with EEM performance in schizophrenia, which may be helpful for the future effort to reveal the underlying neural mechanisms for EEM disturbances in schizophrenia.

618-10 Burial Ground Trench Remediation and 618-10 and 618-11 Burial Ground Nonintrusive Characterization of Vertical Pipe Units Lessons Learned

Energy Technology Data Exchange (ETDEWEB)

Darby, J. W.

2012-06-28

A “lessons learned” is a noteworthy practice or innovative approach that is captured and shared to promote repeat application, or an adverse work practice/experience that is captured and shared to avoid reoccurrence. This document provides the lessons learned identified by the 618-10 Burial Ground trench remediation and the 618-10 and 618-11 Burial Ground nonintrusive characterization of the vertical pipe units (VPUs).

Information Recovery Algorithm for Ground Objects in Thin Cloud Images by Fusing Guide Filter and Transfer Learning

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HU Gensheng

2018-03-01

Full Text Available Ground object information of remote sensing images covered with thin clouds is obscure. An information recovery algorithm for ground objects in thin cloud images is proposed by fusing guide filter and transfer learning. Firstly, multi-resolution decomposition of thin cloud target images and cloud-free guidance images is performed by using multi-directional nonsubsampled dual-tree complex wavelet transform. Then the decomposed low frequency subbands are processed by using support vector guided filter and transfer learning respectively. The decomposed high frequency subbands are enhanced by using modified Laine enhancement function. The low frequency subbands output by guided filter and those predicted by transfer learning model are fused by the method of selection and weighting based on regional energy. Finally, the enhanced high frequency subbands and the fused low frequency subbands are reconstructed by using inverse multi-directional nonsubsampled dual-tree complex wavelet transform to obtain the ground object information recovery images. Experimental results of Landsat-8 OLI multispectral images show that, support vector guided filter can effectively preserve the detail information of the target images, domain adaptive transfer learning can effectively extend the range of available multi-source and multi-temporal remote sensing images, and good effects for ground object information recover are obtained by fusing guide filter and transfer learning to remove thin cloud on the remote sensing images.

Thermodynamic efficiency of learning a rule in neural networks

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Goldt, Sebastian; Seifert, Udo

2017-11-01

Biological systems have to build models from their sensory input data that allow them to efficiently process previously unseen inputs. Here, we study a neural network learning a binary classification rule for these inputs from examples provided by a teacher. We analyse the ability of the network to apply the rule to new inputs, that is to generalise from past experience. Using stochastic thermodynamics, we show that the thermodynamic costs of the learning process provide an upper bound on the amount of information that the network is able to learn from its teacher for both batch and online learning. This allows us to introduce a thermodynamic efficiency of learning. We analytically compute the dynamics and the efficiency of a noisy neural network performing online learning in the thermodynamic limit. In particular, we analyse three popular learning algorithms, namely Hebbian, Perceptron and AdaTron learning. Our work extends the methods of stochastic thermodynamics to a new type of learning problem and might form a suitable basis for investigating the thermodynamics of decision-making.

Academic learning for specialist nurses: a grounded theory study.

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Millberg, Lena German; Berg, Linda; Brämberg, Elisabeth Björk; Nordström, Gun; Ohlén, Joakim

2014-11-01

The aim was to explore the major concerns of specialist nurses pertaining to academic learning during their education and initial professional career. Specialist nursing education changed in tandem with the European educational reform in 2007. At the same time, greater demands were made on the healthcare services to provide evidence-based and safe patient-care. These changes have influenced specialist nursing programmes and consequently the profession. Grounded Theory guided the study. Data were collected by means of a questionnaire with open-ended questions distributed at the end of specialist nursing programmes in 2009 and 2010. Five universities were included. Further, individual, pair and group interviews were used to collect data from 12 specialist nurses, 5-14 months after graduation. A major concern for specialist nurses was that academic learning should be "meaningful" for their professional future. The specialist nurses' "meaningful academic learning process" was characterised by an ambivalence of partly believing in and partly being hesitant about the significance of academic learning and partly receiving but also lacking support. Specialist nurses were influenced by factors in two areas: curriculum and healthcare context. They felt that the outcome of contribution to professional confidence was critical in making academic learning meaningful. Copyright © 2014 Elsevier Ltd. All rights reserved.

Learning Approach on the Ground State Energy Calculation of Helium Atom

International Nuclear Information System (INIS)

Shah, Syed Naseem Hussain

2010-01-01

This research investigated the role of learning approach on the ground state energy calculation of Helium atom in improving the concepts of science teachers at university level. As the exact solution of several particles is not possible here we used approximation methods. Using this method one can understand easily the calculation of ground state energy of any given function. Variation Method is one of the most useful approximation methods in estimating the energy eigen values of the ground state and the first few excited states of a system, which we only have a qualitative idea about the wave function.The objective of this approach is to introduce and involve university teacher in new research, to improve their class room practices and to enable teachers to foster critical thinking in students.

A re-examination of Hebbian-covariance rules and spike timing-dependent plasticity in cat visual cortex in vivo

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Yves Frégnac

2010-12-01

Full Text Available Spike-Timing-Dependent Plasticity (STDP is considered as an ubiquitous rule for associative plasticity in cortical networks in vitro. However, limited supporting evidence for its functional role has been provided in vivo. In particular, there are very few studies demonstrating the co-occurence of synaptic efficiency changes and alteration of sensory responses in adult cortex during Hebbian or STDP protocols. We addressed this issue by reviewing and comparing the functional effects of two types of cellular conditioning in cat visual cortex. The first one, referred to as the covariance protocol, obeys a generalized Hebbian framework, by imposing, for different stimuli, supervised positive and negative changes in covariance between postsynaptic and presynaptic activity rates. The second protocol, based on intracellular recordings, replicated in vivo variants of the theta-burst paradigm (TBS, proven successful in inducing long-term potentiation (LTP in vitro. Since it was shown to impose a precise correlation delay between the electrically activated thalamic input and the TBS-induced postsynaptic spike, this protocol can be seen as a probe of causal (pre-before-post STDP. By choosing a thalamic region where the visual field representation was in retinotopic overlap with the intracellularly recorded cortical receptive field as the afferent site for supervised electrical stimulation, this protocol allowed to look for possible correlates between STDP and functional reorganization of the conditioned cortical receptive field. The rate-based covariance protocol induced significant and large amplitude changes in receptive field properties, in both kitten and adult V1 cortex. The TBS STDP-like protocol produced in the adult significant changes in the synaptic gain of the electrically activated thalamic pathway, but the statistical significance of the functional correlates was detectable mostly at the population level. Comparison of our observations with the

An Efficient VLSI Architecture for Multi-Channel Spike Sorting Using a Generalized Hebbian Algorithm

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Ying-Lun Chen

2015-08-01

Full Text Available A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO, and the feature extraction is carried out by the generalized Hebbian algorithm (GHA. To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction.

An Efficient VLSI Architecture for Multi-Channel Spike Sorting Using a Generalized Hebbian Algorithm.

Science.gov (United States)

Chen, Ying-Lun; Hwang, Wen-Jyi; Ke, Chi-En

2015-08-13

A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO), and the feature extraction is carried out by the generalized Hebbian algorithm (GHA). To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction.

An Efficient VLSI Architecture for Multi-Channel Spike Sorting Using a Generalized Hebbian Algorithm

Science.gov (United States)

Chen, Ying-Lun; Hwang, Wen-Jyi; Ke, Chi-En

2015-01-01

A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO), and the feature extraction is carried out by the generalized Hebbian algorithm (GHA). To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction. PMID:26287193

AHaH Computing–From Metastable Switches to Attractors to Machine Learning

Science.gov (United States)

Nugent, Michael Alexander; Molter, Timothy Wesley

2014-01-01

Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH) plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures–all key capabilities of biological nervous systems and modern machine learning algorithms with real world application. PMID:24520315

AHaH computing-from metastable switches to attractors to machine learning.

Directory of Open Access Journals (Sweden)

Michael Alexander Nugent

Full Text Available Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures-all key capabilities of biological nervous systems and modern machine learning algorithms with real world application.

Perceptual-motor skill learning in Gilles de la Tourette syndrome. Evidence for multiple procedural learning and memory systems.

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Marsh, Rachel; Alexander, Gerianne M; Packard, Mark G; Zhu, Hongtu; Peterson, Bradley S

2005-01-01

Procedural learning and memory systems likely comprise several skills that are differentially affected by various illnesses of the central nervous system, suggesting their relative functional independence and reliance on differing neural circuits. Gilles de la Tourette syndrome (GTS) is a movement disorder that involves disturbances in the structure and function of the striatum and related circuitry. Recent studies suggest that patients with GTS are impaired in performance of a probabilistic classification task that putatively involves the acquisition of stimulus-response (S-R)-based habits. Assessing the learning of perceptual-motor skills and probabilistic classification in the same samples of GTS and healthy control subjects may help to determine whether these various forms of procedural (habit) learning rely on the same or differing neuroanatomical substrates and whether those substrates are differentially affected in persons with GTS. Therefore, we assessed perceptual-motor skill learning using the pursuit-rotor and mirror tracing tasks in 50 patients with GTS and 55 control subjects who had previously been compared at learning a task of probabilistic classifications. The GTS subjects did not differ from the control subjects in performance of either the pursuit rotor or mirror-tracing tasks, although they were significantly impaired in the acquisition of a probabilistic classification task. In addition, learning on the perceptual-motor tasks was not correlated with habit learning on the classification task in either the GTS or healthy control subjects. These findings suggest that the differing forms of procedural learning are dissociable both functionally and neuroanatomically. The specific deficits in the probabilistic classification form of habit learning in persons with GTS are likely to be a consequence of disturbances in specific corticostriatal circuits, but not the same circuits that subserve the perceptual-motor form of habit learning.

Learning invariance from natural images inspired by observations in the primary visual cortex.

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Teichmann, Michael; Wiltschut, Jan; Hamker, Fred

2012-05-01

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.

Cerebellar supervised learning revisited: biophysical modeling and degrees-of-freedom control.

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Kawato, Mitsuo; Kuroda, Shinya; Schweighofer, Nicolas

2011-10-01

The biophysical models of spike-timing-dependent plasticity have explored dynamics with molecular basis for such computational concepts as coincidence detection, synaptic eligibility trace, and Hebbian learning. They overall support different learning algorithms in different brain areas, especially supervised learning in the cerebellum. Because a single spine is physically very small, chemical reactions at it are essentially stochastic, and thus sensitivity-longevity dilemma exists in the synaptic memory. Here, the cascade of excitable and bistable dynamics is proposed to overcome this difficulty. All kinds of learning algorithms in different brain regions confront with difficult generalization problems. For resolution of this issue, the control of the degrees-of-freedom can be realized by changing synchronicity of neural firing. Especially, for cerebellar supervised learning, the triangle closed-loop circuit consisting of Purkinje cells, the inferior olive nucleus, and the cerebellar nucleus is proposed as a circuit to optimally control synchronous firing and degrees-of-freedom in learning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Automatic vetting of planet candidates from ground based surveys: Machine learning with NGTS

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Armstrong, David J.; Günther, Maximilian N.; McCormac, James; Smith, Alexis M. S.; Bayliss, Daniel; Bouchy, François; Burleigh, Matthew R.; Casewell, Sarah; Eigmüller, Philipp; Gillen, Edward; Goad, Michael R.; Hodgkin, Simon T.; Jenkins, James S.; Louden, Tom; Metrailler, Lionel; Pollacco, Don; Poppenhaeger, Katja; Queloz, Didier; Raynard, Liam; Rauer, Heike; Udry, Stéphane; Walker, Simon R.; Watson, Christopher A.; West, Richard G.; Wheatley, Peter J.

2018-05-01

State of the art exoplanet transit surveys are producing ever increasing quantities of data. To make the best use of this resource, in detecting interesting planetary systems or in determining accurate planetary population statistics, requires new automated methods. Here we describe a machine learning algorithm that forms an integral part of the pipeline for the NGTS transit survey, demonstrating the efficacy of machine learning in selecting planetary candidates from multi-night ground based survey data. Our method uses a combination of random forests and self-organising-maps to rank planetary candidates, achieving an AUC score of 97.6% in ranking 12368 injected planets against 27496 false positives in the NGTS data. We build on past examples by using injected transit signals to form a training set, a necessary development for applying similar methods to upcoming surveys. We also make the autovet code used to implement the algorithm publicly accessible. autovet is designed to perform machine learned vetting of planetary candidates, and can utilise a variety of methods. The apparent robustness of machine learning techniques, whether on space-based or the qualitatively different ground-based data, highlights their importance to future surveys such as TESS and PLATO and the need to better understand their advantages and pitfalls in an exoplanetary context.

From phonemes to images : levels of representation in a recurrent neural model of visually-grounded language learning

NARCIS (Netherlands)

Gelderloos, L.J.; Chrupala, Grzegorz

2016-01-01

We present a model of visually-grounded language learning based on stacked gated recurrent neural networks which learns to predict visual features given an image description in the form of a sequence of phonemes. The learning task resembles that faced by human language learners who need to discover

Critical dynamics in associative memory networks

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Maximilian eUhlig

2013-07-01

Full Text Available Critical behavior in neural networks is characterized by scale-free avalanche size distributions and can be explained by self-regulatory mechanisms. Theoretical and experimental evidence indicates that information storage capacity reaches its maximum in the critical regime. We study the effect of structural connectivity formed by Hebbian learning on the criticality of network dynamics. The network endowed with Hebbian learning only does not allow for simultaneous information storage and criticality. However, the critical regime is can be stabilized by short-term synaptic dynamics in the form of synaptic depression and facilitation or, alternatively, by homeostatic adaptation of the synaptic weights. We show that a heterogeneous distribution of maximal synaptic strengths does not preclude criticality if the Hebbian learning is alternated with periods of critical dynamics recovery. We discuss the relevance of these findings for the flexibility of memory in aging and with respect to the recent theory of synaptic plasticity.

Shared neuroanatomical substrates of impaired phonological working memory across reading disability and autism

OpenAIRE

Lu, Chunming; Qi, Zhenghan; Harris, Adrianne; Weil, Lisa Wisman; Han, Michelle; Halverson, Kelly; Perrachione, Tyler K.; Kjelgaard, Margaret; Wexler, Kenneth; Tager-Flusberg, Helen; Gabrieli, John D. E.

2016-01-01

Background Individuals with reading disability and individuals with autism spectrum disorder (ASD) are characterized, respectively, by their difficulties in reading and social communication, but both groups often have impaired phonological working memory (PWM). It is not known whether the impaired PWM reflects distinct or shared neuroanatomical abnormalities in these two diagnostic groups. Methods White-matter structural connectivity via diffusion weighted imaging was examined in 64 children,...

Poststroke delusions: What about the neuroanatomical and neurofunctional basis?

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Torrisi, Michele; De Luca, Rosaria; Pollicino, Patrizia; Leonardi, Simona; Marino, Silvia; Maresca, Giuseppa; Maggio, Maria Grazia; Piccolo, Adriana; Bramanti, Placido; Calabrò, Rocco Salvatore

2018-01-19

Delusion is a belief about yourself, people, or events that has no accordance with reality. Although it is known that stroke could cause various psychiatric and psychological effects, including depression, anxiety, and aggressiveness, psychotic symptoms, especially delusions, are rather uncommon. The most investigated poststroke delusions are paranoid type, nihilistic, and Fregoli syndrome. We will describe two patients showing delusion symptoms (Cotard-like and erotomanic ones) that occurred after a stroke involving the right temporal lobe, the basal ganglia and insular region, persisting for a long period after the stroke onset. We have, therefore, supposed that the simultaneous involvement of these brain areas could be involved in the neuroanatomical basis of delusions, as also demonstrated by the neurofunctional evaluation.

Subsite Awareness in Neuropathology Evaluation of National Toxicology Program (NTP) Studies: A Review of Select Neuroanatomical Structures with their Functional Significance in Rodents

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Rao, Deepa B.; Little, Peter B.; Sills, Robert

2013-01-01

This review manuscript is designed to serve as an introductory guide in neuroanatomy for toxicologic pathologists evaluating general toxicity studies. The manuscript provides an overview of approximately 50 neuroanatomical subsites and their functional significance across seven coronal sections of the brain. Also reviewed are three sections of the spinal cord, cranial and peripheral nerves (trigeminal and sciatic respectively), and intestinal autonomic ganglia. The review is limited to the evaluation of hematoxylin and eosin (H&E) stained tissue sections, as light microscopic evaluation of these sections is an integral part of the first-tier toxicity screening of environmental chemicals, drugs, and other agents. Prominent neuroanatomical sites associated with major neurological disorders are noted. This guide, when used in conjunction with detailed neuroanatomic atlases may aid in an understanding of the significance of functional neuroanatomy, thereby improving the characterization of neurotoxicity in general toxicity and safety evaluation studies. PMID:24135464

Neuroanatomical Anomalies of Dyslexia: Disambiguating the Effects of Disorder, Performance, and Maturation

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Xia, Zhichao; Hoeft, Fumiko; Zhang, Linjun; Shu, Hua

2016-01-01

An increasing body of studies has revealed neuroanatomical impairments in developmental dyslexia. However, whether these structural anomalies are driven by dyslexia (disorder-specific effects), absolute reading performance (performance-dependent effects), and/or further influenced by age (maturation-sensitive effects) remains elusive. To help disentangle these sources, the current study used a novel disorder (dyslexia vs. control) by maturation (younger vs. older) factorial design in 48 Chinese children who were carefully matched. This design not only allows for direct comparison between dyslexics versus controls matched for chronological age and reading ability, but also enables examination of the influence of maturation and its interaction with dyslexia. Voxel-based morphometry (VBM) showed that dyslexic children had reduced regional gray matter volume in the left temporo-parietal cortex (spanning over Heschl’s gyrus, planum temporale and supramarginal gyrus), middle frontal gyrus, superior occipital gyrus, and reduced regional white matter in bilateral parieto-occipital regions (left cuneus and right precuneus) compared with both age-matched and reading-level matched controls. Therefore, maturational stage-invariant neurobiological signatures of dyslexia were found in brain regions that have been associated with impairments in the auditory/phonological and attentional systems. On the other hand, maturational stage-dependent effects on dyslexia were observed in three regions (left ventral occipito-temporal cortex, left dorsal pars opercularis and genu of the corpus callosum), all of which were previously reported to be involved in fluent reading and its development. These striking dissociations collectively suggest potential atypical developmental trajectories of dyslexia, where underlying mechanisms are currently unknown but may be driven by interactions between genetic and/or environmental factors. In summary, this is the first study to disambiguate

MOLECULAR MECHANISMS OF FEAR LEARNING AND MEMORY

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Johansen, Joshua P.; Cain, Christopher K.; Ostroff, Linnaea E.; LeDoux, Joseph E.

2011-01-01

Pavlovian fear conditioning is a useful behavioral paradigm for exploring the molecular mechanisms of learning and memory because a well-defined response to a specific environmental stimulus is produced through associative learning processes. Synaptic plasticity in the lateral nucleus of the amygdala (LA) underlies this form of associative learning. Here we summarize the molecular mechanisms that contribute to this synaptic plasticity in the context of auditory fear conditioning, the form of fear conditioning best understood at the molecular level. We discuss the neurotransmitter systems and signaling cascades that contribute to three phases of auditory fear conditioning: acquisition, consolidation, and reconsolidation. These studies suggest that multiple intracellular signaling pathways, including those triggered by activation of Hebbian processes and neuromodulatory receptors, interact to produce neural plasticity in the LA and behavioral fear conditioning. Together, this research illustrates the power of fear conditioning as a model system for characterizing the mechanisms of learning and memory in mammals, and potentially for understanding fear related disorders, such as PTSD and phobias. PMID:22036561

Molecular mechanisms of fear learning and memory.

Science.gov (United States)

Johansen, Joshua P; Cain, Christopher K; Ostroff, Linnaea E; LeDoux, Joseph E

2011-10-28

Pavlovian fear conditioning is a particularly useful behavioral paradigm for exploring the molecular mechanisms of learning and memory because a well-defined response to a specific environmental stimulus is produced through associative learning processes. Synaptic plasticity in the lateral nucleus of the amygdala (LA) underlies this form of associative learning. Here, we summarize the molecular mechanisms that contribute to this synaptic plasticity in the context of auditory fear conditioning, the form of fear conditioning best understood at the molecular level. We discuss the neurotransmitter systems and signaling cascades that contribute to three phases of auditory fear conditioning: acquisition, consolidation, and reconsolidation. These studies suggest that multiple intracellular signaling pathways, including those triggered by activation of Hebbian processes and neuromodulatory receptors, interact to produce neural plasticity in the LA and behavioral fear conditioning. Collectively, this body of research illustrates the power of fear conditioning as a model system for characterizing the mechanisms of learning and memory in mammals and potentially for understanding fear-related disorders, such as PTSD and phobias. Copyright © 2011 Elsevier Inc. All rights reserved.

Grounding the meanings in sensorimotor behavior using reinforcement learning

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Igor eFarkaš

2012-02-01

Full Text Available The recent outburst of interest in cognitive developmental robotics is fueled by the ambition to propose ecologically plausible mechanisms of how, among other things, a learning agent/robot could ground linguistic meanings in its sensorimotor behaviour. Along this stream, we propose a model that allows the simulated iCub robot to learn the meanings of actions (point, touch and push oriented towards objects in robot's peripersonal space. In our experiments, the iCub learns to execute motor actions and comment on them. Architecturally, the model is composed of three neural-network-based modules that are trained in different ways. The first module, a two-layer perceptron, is trained by back-propagation to attend to the target position in the visual scene, given the low-level visual information and the feature-based target information. The second module, having the form of an actor-critic architecture, is the most distinguishing part of our model, and is trained by a continuous version of reinforcement learning to execute actions as sequences, based on a linguistic command. The third module, an echo-state network, is trained to provide the linguistic description of the executed actions. The trained model generalises well in case of novel action-target combinations with randomised initial arm positions. It can also promptly adapt its behavior if the action/target suddenly changes during motor execution.

The Neuroanatomical, Neurophysiological and Psychological Basis of Memory: Current Models and Their Origins

OpenAIRE

Camina, Eduardo; Güell, Francisco

2017-01-01

This review aims to classify and clarify, from a neuroanatomical, neurophysiological, and psychological perspective, different memory models that are currently widespread in the literature as well as to describe their origins. We believe it is important to consider previous developments without which one cannot adequately understand the kinds of models that are now current in the scientific literature. This article intends to provide a comprehensive and rigorous overview for understanding and...

Collating and Curating Neuroanatomical Nomenclatures: Principles and Use of the Brain Architecture Knowledge Management System (BAMS).

Science.gov (United States)

Bota, Mihail; Swanson, Larry W

2010-01-01

Terms used to describe nervous system parts and their interconnections are rife with synonyms, partial correspondences, and even homonyms, making effective scientific communication unnecessarily difficult. To address this problem a new Topological Relations schema for the Relations module of BAMS (Brain Architecture Knowledge Management System) was created. It includes a representation of the qualitative spatial relations between nervous system parts defined in different neuroanatomical nomenclatures or atlases and is general enough to record data and metadata from the literature, regardless of description level or species. Based on this foundation a Projections Translations inference engine was developed for the BAMS interface that automatically translates neuroanatomical projection (axonal inputs and outputs) reports across nomenclatures from translated information. To make BAMS more useful to the neuroscience community three things were done. First, we implemented a simple schema for validation of the translated neuroanatomical projections. Second, more than 1,000 topological relations between brain gray matter regions for the rat were inserted, along with associated details. Finally, a case study was performed to enter all historical or legacy published information about terminology related to one relatively complex gray matter region of the rat. The bed nuclei of the stria terminalis (BST) were chosen and 21 different nomenclatures from 1923 to present were collated, along with 284 terms for parts (gray matter differentiations), 360 qualitative topological relations between parts, and more than 7,000 details about spatial relations between parts, all of which was annotated with appropriate metadata. This information was used to construct a graphical "knowledge map" of relations used in the literature to describe subdivisions of the rat BST.

Learning in shifts of transient attention improves recognition of parts of ambiguous figure-ground displays.

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Kristjánsson, Arni

2009-04-24

Previously demonstrated learning effects in shifts of transient attention have only been shown to result in beneficial effects upon secondary discrimination tasks and affect landing points of express saccades. Can such learning result in more direct effects upon perception than previously demonstrated? Observers performed a cued Vernier acuity discrimination task where the cue was one of a set of ambiguous figure-ground displays (with a black and white part). The critical measure was whether, if a target appeared consistently within a part of a cue of a certain brightness, this would result in learning effects and whether such learning would then affect recognition of the cue parts. Critically the target always appeared within the same part of each individual cue. Some cues were used in early parts of streaks of repetition of cue-part brightness, and others in latter parts of such streaks. All the observers showed learning in shifts of transient attention, with improved performance the more often the target appeared within the part of the cue of the same brightness. Subsequently the observers judged whether cue-parts had been parts of the cues used on the preceding discrimination task. Recognition of the figure parts, where the target had consistently appeared, improved strongly with increased length of streaks of repetition of cue-part brightness. Learning in shifts of transient attention leads not only to faster attention shifts but to direct effects upon perception, in this case recognition of parts of figure-ground ambiguous cues.

Occupational therapy students in the process of interprofessional collaborative learning: a grounded theory study.

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Howell, Dana

2009-01-01

The purpose of this grounded theory study was to generate a theory of the interprofessional collaborative learning process of occupational therapy (OT) students who were engaged in a collaborative learning experience with students from other allied health disciplines. Data consisted of semi-structured interviews with nine OT students from four different interprofessional collaborative learning experiences at three universities. The emergent theory explained OT students' need to build a culture of mutual respect among disciplines in order to facilitate interprofessional collaborative learning. Occupational therapy students went through a progression of learned skills that included learning how to represent the profession of OT, hold their weight within a team situation, solve problems collaboratively, work as a team, and ultimately, to work in an actual team in practice. This learning process occurred simultaneously as students also learned course content. The students had to contend with barriers and facilitators that influenced their participation and the success of their collaboration. Understanding the interprofessional learning process of OT students will help allied health faculty to design more effective, inclusive interprofessional courses.

Habit learning and brain-machine interfaces (BMI): a tribute to Valentino Braitenberg's "Vehicles".

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Birbaumer, Niels; Hummel, Friedhelm C

2014-10-01

Brain-Machine Interfaces (BMI) allow manipulation of external devices and computers directly with brain activity without involvement of overt motor actions. The neurophysiological principles of such robotic brain devices and BMIs follow Hebbian learning rules as described and realized by Valentino Braitenberg in his book "Vehicles," in the concept of a "thought pump" residing in subcortical basal ganglia structures. We describe here the application of BMIs for brain communication in totally locked-in patients and argue that the thought pump may extinguish-at least partially-in those people because of extinction of instrumentally learned cognitive responses and brain responses. We show that Pavlovian semantic conditioning may allow brain communication even in the completely paralyzed who does not show response-effect contingencies. Principles of skill learning and habit acquisition as formulated by Braitenberg are the building blocks of BMIs and neuroprostheses.

Shared neuroanatomical substrates of impaired phonological working memory across reading disability and autism.

Science.gov (United States)

Lu, Chunming; Qi, Zhenghan; Harris, Adrianne; Weil, Lisa Wisman; Han, Michelle; Halverson, Kelly; Perrachione, Tyler K; Kjelgaard, Margaret; Wexler, Kenneth; Tager-Flusberg, Helen; Gabrieli, John D E

2016-03-01

Individuals with reading disability or individuals with autism spectrum disorder (ASD) are characterized, respectively, by their difficulties in reading or social communication, but both groups often have impaired phonological working memory (PWM). It is not known whether the impaired PWM reflects distinct or shared neuroanatomical abnormalities in these two diagnostic groups. White-matter structural connectivity via diffusion weighted imaging was examined in sixty-four children, ages 5-17 years, with reading disability, ASD, or typical development (TD), who were matched in age, gender, intelligence, and diffusion data quality. Children with reading disability and children with ASD exhibited reduced PWM compared to children with TD. The two diagnostic groups showed altered white-matter microstructure in the temporo-parietal portion of the left arcuate fasciculus (AF) and in the temporo-occipital portion of the right inferior longitudinal fasciculus (ILF), as indexed by reduced fractional anisotropy and increased radial diffusivity. Moreover, the structural integrity of the right ILF was positively correlated with PWM ability in the two diagnostic groups, but not in the TD group. These findings suggest that impaired PWM is transdiagnostically associated with shared neuroanatomical abnormalities in ASD and reading disability. Microstructural characteristics in left AF and right ILF may play important roles in the development of PWM. The right ILF may support a compensatory mechanism for children with impaired PWM.

View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation

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Leibo, Joel Z.; Liao, Qianli; Freiwald, Winrich A.; Anselmi, Fabio; Poggio, Tomaso

2017-01-01

SUMMARY The primate brain contains a hierarchy of visual areas, dubbed the ventral stream, which rapidly computes object representations that are both specific for object identity and robust against identity-preserving transformations like depth-rotations [1, 2]. Current computational models of object recognition, including recent deep learning networks, generate these properties through a hierarchy of alternating selectivity-increasing filtering and tolerance-increasing pooling operations, similar to simple-complex cells operations [3, 4, 5, 6]. Here we prove that a class of hierarchical architectures and a broad set of biologically plausible learning rules generate approximate invariance to identity-preserving transformations at the top level of the processing hierarchy. However, all past models tested failed to reproduce the most salient property of an intermediate representation of a three-level face-processing hierarchy in the brain: mirror-symmetric tuning to head orientation [7]. Here we demonstrate that one specific biologically-plausible Hebb-type learning rule generates mirror-symmetric tuning to bilaterally symmetric stimuli like faces at intermediate levels of the architecture and show why it does so. Thus the tuning properties of individual cells inside the visual stream appear to result from group properties of the stimuli they encode and to reflect the learning rules that sculpted the information-processing system within which they reside. PMID:27916522

Machine learning techniques for gait biometric recognition using the ground reaction force

CERN Document Server

Mason, James Eric; Woungang, Isaac

2016-01-01

This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of ...

Neurophysiological processes and functional neuroanatomical structures underlying proactive effects of emotional conflicts.

Science.gov (United States)

Schreiter, Marie Luise; Chmielewski, Witold; Beste, Christian

2018-07-01

There is a strong inter-relation of cognitive and emotional processes as evidenced by emotional conflict monitoring processes. In the cognitive domain, proactive effects of conflicts have widely been studied; i.e. effects of conflicts in the n-1 trial on trial n. Yet, the neurophysiological processes and associated functional neuroanatomical structures underlying such proactive effects during emotional conflicts have not been investigated. This is done in the current study combining EEG recordings with signal decomposition methods and source localization approaches. We show that an emotional conflict in the n-1 trial differentially influences processing of positive and negative emotions in trial n, but not the processing of conflicts in trial n. The dual competition framework stresses the importance of dissociable 'perceptual' and 'response selection' or cognitive control levels for interactive effects of cognition and emotion. Only once these coding levels were isolated in the neurophysiological data, processes explaining the behavioral effects were detectable. The data show that there is not only a close correspondence between theoretical propositions of the dual competition framework and neurophysiological processes. Rather, processing levels conceptualized in the framework operate in overlapping time windows, but are implemented via distinct functional neuroanatomical structures; the precuneus (BA31) and the insula (BA13). It seems that decoding of information in the precuneus, as well as the integration of information during response selection in the insula is more difficult when confronted with angry facial emotions whenever cognitive control resources have been highly taxed by previous conflicts. Copyright © 2018 Elsevier Inc. All rights reserved.

Shape-specific perceptual learning in a figure-ground segregation task.

Science.gov (United States)

Yi, Do-Joon; Olson, Ingrid R; Chun, Marvin M

2006-03-01

What does perceptual experience contribute to figure-ground segregation? To study this question, we trained observers to search for symmetric dot patterns embedded in random dot backgrounds. Training improved shape segmentation, but learning did not completely transfer either to untrained locations or to untrained shapes. Such partial specificity persisted for a month after training. Interestingly, training on shapes in empty backgrounds did not help segmentation of the trained shapes in noisy backgrounds. Our results suggest that perceptual training increases the involvement of early sensory neurons in the segmentation of trained shapes, and that successful segmentation requires perceptual skills beyond shape recognition alone.

A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimer's Disease.

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Ambastha, Abhinit Kumar; Leong, Tze-Yun

2017-01-01

Alzheimer's disease (AD) is a neurological degenerative disorder that leads to progressive mental deterioration. This work introduces a computational approach to improve our understanding of the progression of AD. We use ensemble learning methods and deep neural networks to identify salient structural correlations among brain regions that degenerate together in AD; this provides an understanding of how AD progresses in the brain. The proposed technique has a classification accuracy of 81.79% for AD against healthy subjects using a single modality imaging dataset.

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

Science.gov (United States)

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

2011-01-01

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

Predictive Acoustic Tracking with an Adaptive Neural Mechanism

DEFF Research Database (Denmark)

Shaikh, Danish; Manoonpong, Poramate

2017-01-01

model of the lizard peripheral auditory system to extract information regarding sound direction. This information is utilised by a neural machinery to learn the acoustic signal’s velocity through fast and unsupervised correlation-based learning adapted from differential Hebbian learning. This approach...

Assessment of learning powered mobility use--applying grounded theory to occupational performance.

Science.gov (United States)

Nilsson, Lisbeth; Durkin, Josephine

2014-01-01

Collaboration by two grounded theory researchers, who each had developed a learning continuum instrument, led to the emergence of a new tool for assessment of learning powered mobility use. We undertook a rigorous process of comparative reanalysis that included merging, modifying, and expanding our previous research findings. A new instrument together with its facilitating strategies emerged in the course of revisits to our existing rich account of data taken from real environment powered mobility practice over an extensive time period. Instrument descriptors, categories, phases, and stages allow a facilitator to assess actual phase and plot actual occupational performance and provide a learner with the just right challenge through the learning process. Facilitating strategies are described for each of the phases and provide directions for involvement during learner performance. The learning approach is led by a belief system that the intervention is user-led, working in partnership and empowering the learner. The new assessment tool is inclusive of every potential powered mobility user because it focuses on the whole continuum of the learning process of powered mobility use from novice to expert. The new tool was appraised by clinicians and has been used successfully in clinical practice in the United Kingdom and Sweden.

Behavioural and neurophysiological study of olfactory perception and learning in honeybees

Directory of Open Access Journals (Sweden)

Jean-Christophe eSandoz

2011-12-01

Full Text Available The honeybee Apis mellifera has been a central insect model in the study of olfactory perception and learning for more than a century, starting with pioneer work by Karl von Frisch. Research on olfaction in honeybees has greatly benefited from the advent of a range of behavioural and neurophysiological paradigms in the Lab. Here I review major findings about how the honeybee brain detects, processes, and learns odours, based on behavioural, neuroanatomical and neurophysiological approaches. I first address the behavioural study of olfactory learning, from experiments on free-flying workers visiting artificial flowers to laboratory-based conditioning protocols on restrained individuals. I explain how the study of olfactory learning has allowed understanding the discrimination and generalization ability of the honeybee olfactory system, its capacity to grant special properties to olfactory mixtures as well as to retain individual component information. Next, based on the impressive amount of anatomical and immunochemical studies of the bee brain, I detail our knowledge of olfactory pathways. I then show how functional recordings of odour-evoked activity in the brain allow following the transformation of the olfactory message from the periphery until higher-order central structures. Data from extra- and intracellular electrophysiological approaches as well as from the most recent optical imaging developments are described. Lastly, I discuss results addressing how odour representation changes as a result of experience. This impressive ensemble of behavioural, neuroanatomical and neurophysiological data available in the bee make it an attractive model for future research aiming to understand olfactory perception and learning in an integrative fashion.

Neuroanatomic changes and their association with cognitive decline in mild cognitive impairment: a meta-analysis

OpenAIRE

Nickl-Jockschat, Thomas; Kleiman, Alexandra; Schulz, Jörg B.; Schneider, Frank; Laird, Angela R.; Fox, Peter T.; Eickhoff, Simon B.; Reetz, Kathrin

2011-01-01

Mild cognitive impairment (MCI) is an acquired syndrome characterised by cognitive decline not affecting activities of daily living. Using a quantitative meta-analytic approach, we aimed to identify consistent neuroanatomic correlates of MCI and how they are related to cognitive dysfunction. The meta-analysis enrols 22 studies, involving 917 MCI (848 amnestic MCI) patients and 809 healthy controls. Only studies investigating local changes in grey matter and reporting whole-brain results in st...

MRI-Based Neuroanatomical Predictors of Dysphagia, Dysarthria, and Aphasia in Patients with First Acute Ischemic Stroke
.

Science.gov (United States)

Flowers, Heather L; AlHarbi, Mohammed A; Mikulis, David; Silver, Frank L; Rochon, Elizabeth; Streiner, David; Martino, Rosemary

2017-01-01

Due to the high post-stroke frequency of dysphagia, dysarthria, and aphasia, we developed comprehensive neuroanatomical, clinical, and demographic models to predict their presence after acute ischemic stroke. The sample included 160 randomly selected first-ever stroke patients with confirmed infarction on magnetic resonance imaging from 1 tertiary stroke center. We documented acute lesions within 12 neuroanatomical regions and their associated volumes. Further, we identified concomitant chronic brain disease, including atrophy, white matter hyperintensities, and covert strokes. We developed predictive models using logistic regression with odds ratios (OR) and their 95% confidence intervals (95% CI) including demographic, clinical, and acute and chronic neuroanatomical factors. Predictors of dysphagia included medullary (OR 6.2, 95% CI 1.5-25.8), insular (OR 4.8, 95% CI 2.0-11.8), and pontine (OR 3.6, 95% CI 1.2-10.1) lesions, followed by brain atrophy (OR 3.0, 95% CI 1.04-8.6), internal capsular lesions (OR 2.9, 95% CI 1.2-6.6), and increasing age (OR 1.4, 95% CI 1.1-1.8). Predictors of dysarthria included pontine (OR 7.8, 95% CI 2.7-22.9), insular (OR 4.5, 95% CI 1.8-11.4), and internal capsular (OR 3.6, 95% CI 1.6-7.9) lesions. Predictors of aphasia included left hemisphere insular (OR 34.4, 95% CI 4.2-283.4), thalamic (OR 6.2, 95% CI 1.6-24.4), and cortical middle cerebral artery (OR 4.7, 95% CI 1.5-14.2) lesions. Predicting outcomes following acute stroke is important for treatment decisions. Determining the risk of major post-stroke impairments requires consideration of factors beyond lesion localization. Accordingly, we demonstrated interactions between localized and global brain function for dysphagia and elucidated common lesion locations across 3 debilitating impairments.
. © 2017 The Author(s)
. Published by S. Karger AG, Basel.

Bayesian Inference and Online Learning in Poisson Neuronal Networks.

Science.gov (United States)

Huang, Yanping; Rao, Rajesh P N

2016-08-01

Motivated by the growing evidence for Bayesian computation in the brain, we show how a two-layer recurrent network of Poisson neurons can perform both approximate Bayesian inference and learning for any hidden Markov model. The lower-layer sensory neurons receive noisy measurements of hidden world states. The higher-layer neurons infer a posterior distribution over world states via Bayesian inference from inputs generated by sensory neurons. We demonstrate how such a neuronal network with synaptic plasticity can implement a form of Bayesian inference similar to Monte Carlo methods such as particle filtering. Each spike in a higher-layer neuron represents a sample of a particular hidden world state. The spiking activity across the neural population approximates the posterior distribution over hidden states. In this model, variability in spiking is regarded not as a nuisance but as an integral feature that provides the variability necessary for sampling during inference. We demonstrate how the network can learn the likelihood model, as well as the transition probabilities underlying the dynamics, using a Hebbian learning rule. We present results illustrating the ability of the network to perform inference and learning for arbitrary hidden Markov models.

A ground-up construction of deep learning

CERN Multimedia

CERN. Geneva

2015-01-01

I propose to give a ground up construction of deep learning as it is in it's modern state. Starting from it's beginnings in the 90's, I plan on showing the relevant (for physics) differences in optimization, construction, activation functions, initialization, and other tricks that have been accrued over the last 20 years. In addition, I plan on showing why deeper, wider basic feedforward architectures can be used. Coupling this with MaxOut layers, modern GPUs, and including both l1 and l2 forms of regularization, we have the current "state of the art" in basic feedforward networks. I plan on discussing pre-training using deep autoencoders and RBMs, and explaining why this has fallen out of favor when you have lots of labeled data. While discussing each of these points, I propose to explain why these particular characteristics are valuable for HEP. Finally, the last topic on basic feedforward networks -- interpretation. I plan on discussing latent representations of important variables (i.e., mass, pT) that ar...

Neuroanatomical and cognitive mediators of age-related differences in perceptual priming and learning

OpenAIRE

Kennedy, Kristen M.; Rodrigue, Karen M.; Head, Denise; Gunning-Dixon, Faith; Raz, Naftali

2009-01-01

Our objectives were to assess age differences in perceptual repetition priming and perceptual skill learning, and to determine whether they are mediated by cognitive resources and regional cerebral volume differences. Fragmented picture identification paradigm allows the study of both priming and learning within the same task. We presented this task to 169 adults (ages 18–80), assessed working memory and fluid intelligence, and measured brain volumes of regions that were deemed relevant to th...

Beyond the pineal gland assumption: a neuroanatomical appraisal of dualism in Descartes' philosophy.

Science.gov (United States)

Berhouma, Moncef

2013-09-01

The problem of the substantial union of the soul and the body and therefore the mechanisms of interaction between them represents the core of the Cartesian dualistic philosophy. This philosophy is based upon a neuroanatomical obvious misconception, consisting mainly on a wrong intraventricular position of the pineal gland and its capacity of movement to act as a valve regulating the flow of animal spirits. Should we consider the Cartesian neurophysiology as a purely anatomical descriptive work and therefore totally incorrect, or rather as a theoretical conception supporting his dualistic philosophy? From the various pre-Cartesian theories on the pineal organ, we try to explain how Descartes used his original conception of neuroanatomy to serve his dualistic philosophy. Moreover, we present an appraisal of the Cartesian neuroanatomical corpus from an anatomical but also metaphysical and theological perspectives. A new interpretation of Descartes' writings and an analysis of the secondary related literature shed the light on the voluntary anatomical approximations aiming to build an ad hoc neurophysiology that allows Descartes' soul-body theory. By its central position within the brain mass and its particular shape, the pineal gland raised diverse metaphysical theories regarding its function, but the most original theory remains certainly its role as the seat of soul in René Descartes' philosophy and more precisely the organ where soul and body interact. The author emphasizes on the critics raised by Descartes' theories on the soul-body interaction through the role of the pineal gland. Copyright © 2013 Elsevier B.V. All rights reserved.

Retrograde Neuroanatomical Tracing of Phrenic Motor Neurons in Mice.

Science.gov (United States)

Vandeweerd, Jean-Michel; Hontoir, Fanny; De Knoop, Alexis; De Swert, Kathleen; Nicaise, Charles

2018-02-22

Phrenic motor neurons are cervical motor neurons originating from C3 to C6 levels in most mammalian species. Axonal projections converge into phrenic nerves innervating the respiratory diaphragm. In spinal cord slices, phrenic motor neurons cannot be identified from other motor neurons on morphological or biochemical criteria. We provide the description of procedures for visualizing phrenic motor neuron cell bodies in mice, following intrapleural injections of cholera toxin subunit beta (CTB) conjugated to a fluorophore. This fluorescent neuroanatomical tracer has the ability to be caught up at the diaphragm neuromuscular junction, be carried retrogradely along the phrenic axons and reach the phrenic cell bodies. Two methodological approaches of intrapleural CTB delivery are compared: transdiaphragmatic versus transthoracic injections. Both approaches are successful and result in similar number of CTB-labeled phrenic motor neurons. In conclusion, these techniques can be applied to visualize or quantify the phrenic motor neurons in various experimental studies such as those focused on the diaphragm-phrenic circuitry.

Ground water and energy

Energy Technology Data Exchange (ETDEWEB)

1980-11-01

This national workshop on ground water and energy was conceived by the US Department of Energy's Office of Environmental Assessments. Generally, OEA needed to know what data are available on ground water, what information is still needed, and how DOE can best utilize what has already been learned. The workshop focussed on three areas: (1) ground water supply; (2) conflicts and barriers to ground water use; and (3) alternatives or solutions to the various issues relating to ground water. (ACR)

Autonomous learning in gesture recognition by using lobe component analysis

Science.gov (United States)

Lu, Jian; Weng, Juyang

2007-02-01

Gesture recognition is a new human-machine interface method implemented by pattern recognition(PR).In order to assure robot safety when gesture is used in robot control, it is required to implement the interface reliably and accurately. Similar with other PR applications, 1) feature selection (or model establishment) and 2) training from samples, affect the performance of gesture recognition largely. For 1), a simple model with 6 feature points at shoulders, elbows, and hands, is established. The gestures to be recognized are restricted to still arm gestures, and the movement of arms is not considered. These restrictions are to reduce the misrecognition, but are not so unreasonable. For 2), a new biological network method, called lobe component analysis(LCA), is used in unsupervised learning. Lobe components, corresponding to high-concentrations in probability of the neuronal input, are orientation selective cells follow Hebbian rule and lateral inhibition. Due to the advantage of LCA method for balanced learning between global and local features, large amount of samples can be used in learning efficiently.

Neuroanatomical correlates of brain-computer interface performance.

Science.gov (United States)

Kasahara, Kazumi; DaSalla, Charles Sayo; Honda, Manabu; Hanakawa, Takashi

2015-04-15

Brain-computer interfaces (BCIs) offer a potential means to replace or restore lost motor function. However, BCI performance varies considerably between users, the reasons for which are poorly understood. Here we investigated the relationship between sensorimotor rhythm (SMR)-based BCI performance and brain structure. Participants were instructed to control a computer cursor using right- and left-hand motor imagery, which primarily modulated their left- and right-hemispheric SMR powers, respectively. Although most participants were able to control the BCI with success rates significantly above chance level even at the first encounter, they also showed substantial inter-individual variability in BCI success rate. Participants also underwent T1-weighted three-dimensional structural magnetic resonance imaging (MRI). The MRI data were subjected to voxel-based morphometry using BCI success rate as an independent variable. We found that BCI performance correlated with gray matter volume of the supplementary motor area, supplementary somatosensory area, and dorsal premotor cortex. We suggest that SMR-based BCI performance is associated with development of non-primary somatosensory and motor areas. Advancing our understanding of BCI performance in relation to its neuroanatomical correlates may lead to better customization of BCIs based on individual brain structure. Copyright © 2015 Elsevier Inc. All rights reserved.

Neuroanatomical phenotypes in mental illness: identifying convergent and divergent cortical phenotypes across autism, ADHD and schizophrenia.

Science.gov (United States)

Park, Min Tae M; Raznahan, Armin; Shaw, Philip; Gogtay, Nitin; Lerch, Jason P; Chakravarty, M Mallar

2018-05-01

There is evidence suggesting neuropsychiatric disorders share genomic, cognitive and clinical features. Here, we ask if autism-spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD) and schizophrenia share neuroanatomical variations. First, we used measures of cortical anatomy to estimate spatial overlap of neuroanatomical variation using univariate methods. Next, we developed a novel methodology to determine whether cortical deficits specifically target or are "enriched" within functional resting-state networks. We found cortical anomalies were preferentially enriched across functional networks rather than clustering spatially. Specifically, cortical thickness showed significant enrichment between patients with ASD and those with ADHD in the default mode network, between patients with ASD and those with schizophrenia in the frontoparietal and limbic networks, and between patients with ADHD and those with schizophrenia in the ventral attention network. Networks enriched in cortical thickness anomalies were also strongly represented in functional MRI results (Neurosynth; r = 0.64, p = 0.032). We did not account for variable symptom dimensions and severity in patient populations, and our cross-sectional design prevented longitudinal analyses of developmental trajectories. These findings suggest that common deficits across neuropsychiatric disorders cannot simply be characterized as arising out of local changes in cortical grey matter, but rather as entities of both local and systemic alterations targeting brain networks.

Hebbian plasticity realigns grid cell activity with external sensory cues in continuous attractor models

Directory of Open Access Journals (Sweden)

Marcello eMulas

2016-02-01

Full Text Available After the discovery of grid cells, which are an essential component to understand how the mammalian brain encodes spatial information, three main classes of computational models were proposed in order to explain their working principles. Amongst them, the one based on continuous attractor networks (CAN, is promising in terms of biological plausibility and suitable for robotic applications. However, in its current formulation, it is unable to reproduce important electrophysiological findings and cannot be used to perform path integration for long periods of time. In fact, in absence of an appropriate resetting mechanism, the accumulation of errors overtime due to the noise intrinsic in velocity estimation and neural computation prevents CAN models to reproduce stable spatial grid patterns. In this paper, we propose an extension of the CAN model using Hebbian plasticity to anchor grid cell activity to environmental landmarks. To validate our approach we used as input to the neural simulations both artificial data and real data recorded from a robotic setup. The additional neural mechanism can not only anchor grid patterns to external sensory cues but also recall grid patterns generated in previously explored environments. These results might be instrumental for next generation bio-inspired robotic navigation algorithms that take advantage of neural computation in order to cope with complex and dynamic environments.

Spinal Meninges and Their Role in Spinal Cord Injury: A Neuroanatomical Review.

Science.gov (United States)

Grassner, Lukas; Grillhösl, Andreas; Griessenauer, Christoph J; Thomé, Claudius; Bühren, Volker; Strowitzki, Martin; Winkler, Peter A

2018-02-01

Current recommendations support early surgical decompression and blood pressure augmentation after traumatic spinal cord injury (SCI). Elevated intraspinal pressure (ISP), however, has probably been underestimated in the pathophysiology of SCI. Recent studies provide some evidence that ISP measurements and durotomy may be beneficial for individuals suffering from SCI. Compression of the spinal cord against the meninges in SCI patients causes a "compartment-like" syndrome. In such cases, intentional durotomy with augmentative duroplasty to reduce ISP and improve spinal cord perfusion pressure (SCPP) may be indicated. Prior to performing these procedures routinely, profound knowledge of the spinal meninges is essential. Here, we provide an in-depth review of relevant literature along with neuroanatomical illustrations and imaging correlates.

Learning by stimulation avoidance: A principle to control spiking neural networks dynamics.

Science.gov (United States)

Sinapayen, Lana; Masumori, Atsushi; Ikegami, Takashi

2017-01-01

Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle "Learning by Stimulation Avoidance" (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system.

Unsupervised clustering with spiking neurons by sparse temporal coding and multi-layer RBF networks

NARCIS (Netherlands)

S.M. Bohte (Sander); J.A. La Poutré (Han); J.N. Kok (Joost)

2000-01-01

textabstractWe demonstrate that spiking neural networks encoding information in spike times are capable of computing and learning clusters from realistic data. We show how a spiking neural network based on spike-time coding and Hebbian learning can successfully perform unsupervised clustering on

[The interactive neuroanatomical simulation and practical application of frontotemporal transsylvian exposure in neurosurgery].

Science.gov (United States)

Balogh, Attila; Czigléczki, Gábor; Papal, Zsolt; Preul, Mark C; Banczerowski, Péter

2014-11-30

There is an increased need for new digital education tools in neurosurgical training. Illustrated textbooks offer anatomic and technical reference but do not substitute hands-on experience provided by surgery or cadaver dissection. Due to limited availability of cadaver dissections the need for development of simulation tools has been augmented. We explored simulation technology for producing virtual reality-like reconstructions of simulated surgical approaches on cadaver. Practical application of the simulation tool has been presented through frontotemporal transsylvian exposure. The dissections were performed on two cadaveric heads. Arteries and veins were prepared and injected with colorful silicon rubber. The heads were rigidly fixed in Mayfield headholder. A robotic microscope with two digital cameras in inverted cone method of image acquisition was used to capture images around a pivot point in several phases of dissections. Multilayered, high-resolution images have been built into interactive 4D environment by custom developed software. We have developed the simulation module of the frontotemporal transsylvian approach. The virtual specimens can be rotated or tilted to any selected angles and examined from different surgical perspectives at any stage of dissections. Important surgical issues such as appropriate head positioning or surgical maneuvers to expose deep situated neuroanatomic structures can be simulated and studied by using the module. The simulation module of the frontotemporal transsylvian exposure helps to examine effect of head positioning on the visibility of deep situated neuroanatomic structures and study surgical maneuvers required to achieve optimal exposure of deep situated anatomic structures. The simulation program is a powerful tool to study issues of preoperative planning and well suited for neurosurgical training.

Modeling the neuroanatomic propagation of ALS in the spinal cord

Science.gov (United States)

Drawert, Brian; Thakore, Nimish; Mitchell, Brian; Pioro, Erik; Ravits, John; Petzold, Linda R.

2017-07-01

Recent hypotheses of amyotrophic lateral sclerosis (ALS) progression have posited a point-source origin of motor neuron death with neuroanatomic propagation either contiguously to adjacent regions, or along networks via axonal and synaptic connections. Although the molecular mechanisms of propagation are unknown, one leading hypothesis is a "prion-like" spread of misfolded and aggregated proteins, including SOD1 and TDP-43. We have developed a mathematical model representing cellular and molecular spread of ALS in the human spinal cord. Our model is based on the stochastic reaction-diffusion master equation approach using a tetrahedral discretized space to capture the complex geometry of the spinal cord. Domain dimension and shape was obtained by reconstructing human spinal cord from high-resolution magnetic resonance (MR) images and known gross and histological neuroanatomy. Our preliminary results qualitatively recapitulate the clinically observed pattern of spread of ALS thorough the spinal cord.

Examination of the Combined Effects of Chondroitinase ABC, Growth Factors and Locomotor Training following Compressive Spinal Cord Injury on Neuroanatomical Plasticity and Kinematics

Science.gov (United States)

Alluin, Olivier; Fehlings, Michael G.; Rossignol, Serge; Karimi-Abdolrezaee, Soheila

2014-01-01

While several cellular and pharmacological treatments have been evaluated following spinal cord injury (SCI) in animal models, it is increasingly recognized that approaches to address the glial scar, including the use of chondroitinase ABC (ChABC), can facilitate neuroanatomical plasticity. Moreover, increasing evidence suggests that combinatorial strategies are key to unlocking the plasticity that is enabled by ChABC. Given this, we evaluated the anatomical and functional consequences of ChABC in a combinatorial approach that also included growth factor (EGF, FGF2 and PDGF-AA) treatments and daily treadmill training on the recovery of hindlimb locomotion in rats with mid thoracic clip compression SCI. Using quantitative neuroanatomical and kinematic assessments, we demonstrate that the combined therapy significantly enhanced the neuroanatomical plasticity of major descending spinal tracts such as corticospinal and serotonergic-spinal pathways. Additionally, the pharmacological treatment attenuated chronic astrogliosis and inflammation at and adjacent to the lesion with the modest synergistic effects of treadmill training. We also observed a trend for earlier recovery of locomotion accompanied by an improvement of the overall angular excursions in rats treated with ChABC and growth factors in the first 4 weeks after SCI. At the end of the 7-week recovery period, rats from all groups exhibited an impressive spontaneous recovery of the kinematic parameters during locomotion on treadmill. However, although the combinatorial treatment led to clear chronic neuroanatomical plasticity, these structural changes did not translate to an additional long-term improvement of locomotor parameters studied including hindlimb-forelimb coupling. These findings demonstrate the beneficial effects of combined ChABC, growth factors and locomotor training on the plasticity of the injured spinal cord and the potential to induce earlier neurobehavioral recovery. However, additional

Examination of the combined effects of chondroitinase ABC, growth factors and locomotor training following compressive spinal cord injury on neuroanatomical plasticity and kinematics.

Directory of Open Access Journals (Sweden)

Olivier Alluin

Full Text Available While several cellular and pharmacological treatments have been evaluated following spinal cord injury (SCI in animal models, it is increasingly recognized that approaches to address the glial scar, including the use of chondroitinase ABC (ChABC, can facilitate neuroanatomical plasticity. Moreover, increasing evidence suggests that combinatorial strategies are key to unlocking the plasticity that is enabled by ChABC. Given this, we evaluated the anatomical and functional consequences of ChABC in a combinatorial approach that also included growth factor (EGF, FGF2 and PDGF-AA treatments and daily treadmill training on the recovery of hindlimb locomotion in rats with mid thoracic clip compression SCI. Using quantitative neuroanatomical and kinematic assessments, we demonstrate that the combined therapy significantly enhanced the neuroanatomical plasticity of major descending spinal tracts such as corticospinal and serotonergic-spinal pathways. Additionally, the pharmacological treatment attenuated chronic astrogliosis and inflammation at and adjacent to the lesion with the modest synergistic effects of treadmill training. We also observed a trend for earlier recovery of locomotion accompanied by an improvement of the overall angular excursions in rats treated with ChABC and growth factors in the first 4 weeks after SCI. At the end of the 7-week recovery period, rats from all groups exhibited an impressive spontaneous recovery of the kinematic parameters during locomotion on treadmill. However, although the combinatorial treatment led to clear chronic neuroanatomical plasticity, these structural changes did not translate to an additional long-term improvement of locomotor parameters studied including hindlimb-forelimb coupling. These findings demonstrate the beneficial effects of combined ChABC, growth factors and locomotor training on the plasticity of the injured spinal cord and the potential to induce earlier neurobehavioral recovery. However

Neuroanatomical localization of endocrine control of reproductive behavior in the Japanese quail (Coturnix japonica)

International Nuclear Information System (INIS)

Watson, J.T. III.

1989-01-01

Steroid autoradiography and systematic and intracranial steroid treatment were undertaken to determine the neuroanatomical loci which are sufficient to activate steroid sensitive behaviors in the Japanese quail. (1) Autoradiographic localization of steroid binding cells was performed on male and female quail brains using tritiated ( 3 H) testosterone (T), estradiol (E2), or 5α-dihydrotestosterone (DHT). The distributions of labelled cells in the quail brain following 3 H-T or 3 H-E2 injection and autoradiography were similar to one another. The distribution of labelled cells following 3 H-DHT autoradiography was limited in comparison to that following 3 H-T autoradiography. Males were found to have more labelled cells than females in nucleus taeniae. (2) Intracranial implantation of minute pellets of testoterone propionate (TP) and estradiol benzoate (EB) was performed to determine neuroanatomical loci at which steroids activate sexual behavior. Both TP and EB implants in the preoptic area (POA) activated male copulatory behavior. (3) Systematic injection of aromatase inhibitor prior to and concurrent with implantation completely blocked copulatory behavior in males with TP implants in the POA but failed to block copulation in males with EB implants in the POA. (4) Intact males and castrated males given 5 dosages of systematic EB treatment were tested for sexual behavior, and blood samples from each group were assayed for E2 concentration. (5) Midbrain DHTP implants were activated crowing without significantly stimulating peripheral androgen-sensitive tissues, but the effect on crowing was not localized to any one nucleus

Predictive modeling of neuroanatomic structures for brain atrophy detection

Science.gov (United States)

Hu, Xintao; Guo, Lei; Nie, Jingxin; Li, Kaiming; Liu, Tianming

2010-03-01

In this paper, we present an approach of predictive modeling of neuroanatomic structures for the detection of brain atrophy based on cross-sectional MRI image. The underlying premise of applying predictive modeling for atrophy detection is that brain atrophy is defined as significant deviation of part of the anatomy from what the remaining normal anatomy predicts for that part. The steps of predictive modeling are as follows. The central cortical surface under consideration is reconstructed from brain tissue map and Regions of Interests (ROI) on it are predicted from other reliable anatomies. The vertex pair-wise distance between the predicted vertex and the true one within the abnormal region is expected to be larger than that of the vertex in normal brain region. Change of white matter/gray matter ratio within a spherical region is used to identify the direction of vertex displacement. In this way, the severity of brain atrophy can be defined quantitatively by the displacements of those vertices. The proposed predictive modeling method has been evaluated by using both simulated atrophies and MRI images of Alzheimer's disease.

The neuroanatomical basis of panic disorder and social phobia in schizophrenia: a voxel based morphometric study.

Science.gov (United States)

Picado, Marisol; Carmona, Susanna; Hoekzema, Elseline; Pailhez, Guillem; Bergé, Daniel; Mané, Anna; Fauquet, Jordi; Hilferty, Joseph; Moreno, Ana; Cortizo, Romina; Vilarroya, Oscar; Bulbena, Antoni

2015-01-01

It is known that there is a high prevalence of certain anxiety disorders among schizophrenic patients, especially panic disorder and social phobia. However, the neural underpinnings of the comorbidity of such anxiety disorders and schizophrenia remain unclear. Our study aims to determine the neuroanatomical basis of the co-occurrence of schizophrenia with panic disorder and social phobia. Voxel-based morphometry was used in order to examine brain structure and to measure between-group differences, comparing magnetic resonance images of 20 anxious patients, 20 schizophrenic patients, 20 schizophrenic patients with comorbid anxiety, and 20 healthy control subjects. Compared to the schizophrenic patients, we observed smaller grey-matter volume (GMV) decreases in the dorsolateral prefrontal cortex and precentral gyrus in the schizophrenic-anxiety group. Additionally, the schizophrenic group showed significantly reduced GMV in the dorsolateral prefrontal cortex, precentral gyrus, orbitofrontal cortex, temporal gyrus and angular/inferior parietal gyrus when compared to the control group. Our findings suggest that the comorbidity of schizophrenia with panic disorder and social phobia might be characterized by specific neuroanatomical and clinical alterations that may be related to maladaptive emotion regulation related to anxiety. Even thought our findings need to be replicated, our study suggests that the identification of neural abnormalities involved in anxiety, schizophrenia and schizophrenia-anxiety may lead to an improved diagnosis and management of these conditions.

Thiamine Deficiency Induced Neurochemical, Neuroanatomical, and Neuropsychological Alterations: A Reappraisal

Directory of Open Access Journals (Sweden)

Raffaele Nardone

2013-01-01

Full Text Available Nutritional deficiency can cause, mainly in chronic alcoholic subjects, the Wernicke encephalopathy and its chronic neurological sequela, the Wernicke-Korsakoff syndrome (WKS. Long-term chronic ethanol abuse results in hippocampal and cortical cell loss. Thiamine deficiency also alters principally hippocampal- and frontal cortical-dependent neurochemistry; moreover in WKS patients, important pathological damage to the diencephalon can occur. In fact, the amnesic syndrome typical for WKS is mainly due to the damage in the diencephalic-hippocampal circuitry, including thalamic nuclei and mammillary bodies. The loss of cholinergic cells in the basal forebrain region results in decreased cholinergic input to the hippocampus and the cortex and reduced choline acetyltransferase and acetylcholinesterase activities and function, as well as in acetylcholine receptor downregulation within these brain regions. In this narrative review, we will focus on the neurochemical, neuroanatomical, and neuropsychological studies shedding light on the effects of thiamine deficiency in experimental models and in humans.

Rapid motor learning in the translational vestibulo-ocular reflex

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Zhou, Wu; Weldon, Patrick; Tang, Bingfeng; King, W. M.; Shelhamer, M. J. (Principal Investigator)

2003-01-01

Motor learning was induced in the translational vestibulo-ocular reflex (TVOR) when monkeys were repeatedly subjected to a brief (0.5 sec) head translation while they tried to maintain binocular fixation on a visual target for juice rewards. If the target was world-fixed, the initial eye speed of the TVOR gradually increased; if the target was head-fixed, the initial eye speed of the TVOR gradually decreased. The rate of learning acquisition was very rapid, with a time constant of approximately 100 trials, which was equivalent to or=1 d without any reinforcement, indicating induction of long-term synaptic plasticity. Although the learning generalized to targets with different viewing distances and to head translations with different accelerations, it was highly specific for the particular combination of head motion and evoked eye movement associated with the training. For example, it was specific to the modality of the stimulus (translation vs rotation) and the direction of the evoked eye movement in the training. Furthermore, when one eye was aligned with the heading direction so that it remained motionless during training, learning was not expressed in this eye, but only in the other nonaligned eye. These specificities show that the learning sites are neither in the sensory nor the motor limb of the reflex but in the sensory-motor transformation stage of the reflex. The dependence of the learning on both head motion and evoked eye movement suggests that Hebbian learning may be one of the underlying cellular mechanisms.

Anticipation by multi-modal association through an artificial mental imagery process

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Gaona, Wilmer; Escobar, Esaú; Hermosillo, Jorge; Lara, Bruno

2015-01-01

Mental imagery has become a central issue in research laboratories seeking to emulate basic cognitive abilities in artificial agents. In this work, we propose a computational model to produce an anticipatory behaviour by means of a multi-modal off-line hebbian association. Unlike the current state of the art, we propose to apply hebbian learning during an internal sensorimotor simulation, emulating a process of mental imagery. We associate visual and tactile stimuli re-enacted by a long-term predictive simulation chain motivated by covert actions. As a result, we obtain a neural network which provides a robot with a mechanism to produce a visually conditioned obstacle avoidance behaviour. We developed our system in a physical Pioneer 3-DX robot and realised two experiments. In the first experiment we test our model on one individual navigating in two different mazes. In the second experiment we assess the robustness of the model by testing in a single environment five individuals trained under different conditions. We believe that our work offers an underpinning mechanism in cognitive robotics for the study of motor control strategies based on internal simulations. These strategies can be seen analogous to the mental imagery process known in humans, opening thus interesting pathways to the construction of upper-level grounded cognitive abilities.

Neuroanatomical Markers of Social Hierarchy Recognition in Humans: A Combined ERP/MRI Study.

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Santamaría-García, Hernando; Burgaleta, Miguel; Sebastián-Gallés, Nuria

2015-07-29

Social hierarchy is an ubiquitous principle of social organization across animal species. Although some progress has been made in our understanding of how humans infer hierarchical identity, the neuroanatomical basis for perceiving key social dimensions of others remains unexplored. Here, we combined event-related potentials and structural MRI to reveal the neuroanatomical substrates of early status recognition. We designed a covertly simulated hierarchical setting in which participants performed a task either with a superior or with an inferior player. Participants showed higher amplitude in the N170 component when presented with a picture of a superior player compared with an inferior player. Crucially, the magnitude of this effect correlated with brain morphology of the posterior cingulate cortex, superior temporal gyrus, insula, fusiform gyrus, and caudate nucleus. We conclude that early recognition of social hierarchies relies on the structural properties of a network involved in the automatic recognition of social identity. Humans can perceive social hierarchies very rapidly, an ability that is key for social interactions. However, some individuals are more sensitive to hierarchical information than others. Currently, it is unknown how brain structure supports such fast-paced processes of social hierarchy perception and their individual differences. Here, we addressed this issue for the first time by combining the high temporal resolution of event-related potentials (ERPs) and the high spatial resolution of structural MRI. This methodological approach allowed us to unveil a novel association between ERP neuromarkers of social hierarchy perception and the morphology of several cortical and subcortical brain regions typically assumed to play a role in automatic processes of social cognition. Our results are a step forward in our understanding of the human social brain. Copyright © 2015 the authors 0270-6474/15/3510843-08$15.00/0.

Sensorimotor learning biases choice behavior: a learning neural field model for decision making.

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Christian Klaes

Full Text Available According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action

Continuous Online Sequence Learning with an Unsupervised Neural Network Model.

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Cui, Yuwei; Ahmad, Subutar; Hawkins, Jeff

2016-09-14

The ability to recognize and predict temporal sequences of sensory inputs is vital for survival in natural environments. Based on many known properties of cortical neurons, hierarchical temporal memory (HTM) sequence memory recently has been proposed as a theoretical framework for sequence learning in the cortex. In this letter, we analyze properties of HTM sequence memory and apply it to sequence learning and prediction problems with streaming data. We show the model is able to continuously learn a large number of variableorder temporal sequences using an unsupervised Hebbian-like learning rule. The sparse temporal codes formed by the model can robustly handle branching temporal sequences by maintaining multiple predictions until there is sufficient disambiguating evidence. We compare the HTM sequence memory with other sequence learning algorithms, including statistical methods: autoregressive integrated moving average; feedforward neural networks-time delay neural network and online sequential extreme learning machine; and recurrent neural networks-long short-term memory and echo-state networks on sequence prediction problems with both artificial and real-world data. The HTM model achieves comparable accuracy to other state-of-the-art algorithms. The model also exhibits properties that are critical for sequence learning, including continuous online learning, the ability to handle multiple predictions and branching sequences with high-order statistics, robustness to sensor noise and fault tolerance, and good performance without task-specific hyperparameter tuning. Therefore, the HTM sequence memory not only advances our understanding of how the brain may solve the sequence learning problem but is also applicable to real-world sequence learning problems from continuous data streams.

Traditional behaviour and fidelity to caribou calving grounds by barren-ground caribou

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Anne Gunn

1986-06-01

Full Text Available Evidence for the fidelity of female barren-ground caribou (Rangifer tarandus spp. of each herd to specific calving grounds is convincing. Involvement of learned behaviour in the annual return of those cows to the same calving grounds implies such actions are a form of «traditional» behaviour. Even wide variations in population size have not yet knowingly led to marked changes in size or location of calving grounds or prolonged abandonment of established ones. Rarely is the adoption of new calving grounds reported and emigration to another herd's calving ground or interchange between calving grounds has not yet been unequivocally documented. The calving experience of individual caribou and environmental pressures may modify the cow's use patterns of her calving grounds. The current definition of herds based on traditional calving grounds may require modification, if increasing caribou numbers result in changes in traditions. However, current data do not contradict either the fidelity to traditional calving grounds or the concept of herd identity based on that fidelity.

Neuroanatomical and Neurochemical Basis of Impulsivity

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Kemal Yazici

2010-08-01

tis paradigm, the tendency to prefer small immediate rewards over larger, more delayed reinforcers is measured. İmpulsive choice is defined by a greater tendency to value or choose smaller, more immediate reinforcers. Impulsivity is a multi-faceted behaviour. This behaviour may be studied by subdividing it into different processes neuroanatomically and neurochemically. Neuroanatomical data support the suggestion that behavioral disinhibition (impulsive action / motoric impulsivity and delay-discounting (impulsive choice / decision making differ in the degree to which various components of frontostriatal loops are implicated in their regulation. The dorsal prefrontal cortex does not appear to be involved in mediating impulsive choice, yet does have some role in regulating inhibitory processes. In contrast, there appears to be a pronounced role for the orbitofrontal cortex and basolateral amygdala in controlling impulsive choice. Other structures, however, such as the nucleus accumbens and subthalamic nucleus may be common to both circuits. From the neurochemical perspective, dopamine system and dopamine- 2 (D2 receptors in particular, seems to be closely involved in making impulsive choice. When the noradrenaline system does not function optimally, it might contribute to increased impulsivity. Serotonin might act upon prefrontal cortex to decrease impulsive choices. Interactions between the serotonin and the dopamine systems are important in the regulation of impulsive behaviour. It is possible that various receptor subtypes of the serotonin system may exert differing and even contrasting effects on impulsive behaviour. Although it is very informative to study neurotransmitter systems separately, it should be kept in mind that there are very intimate interactions between the neurotransmitter systems mentioned above. Based on the fact that impulsivity is regulated through multiple neurotransmitters and even more receptors, one may suggest that pharmacotherapy of

Teaching Theory Construction With Initial Grounded Theory Tools: A Reflection on Lessons and Learning.

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Charmaz, Kathy

2015-12-01

This article addresses criticisms of qualitative research for spawning studies that lack analytic development and theoretical import. It focuses on teaching initial grounded theory tools while interviewing, coding, and writing memos for the purpose of scaling up the analytic level of students' research and advancing theory construction. Adopting these tools can improve teaching qualitative methods at all levels although doctoral education is emphasized here. What teachers cover in qualitative methods courses matters. The pedagogy presented here requires a supportive environment and relies on demonstration, collective participation, measured tasks, progressive analytic complexity, and accountability. Lessons learned from using initial grounded theory tools are exemplified in a doctoral student's coding and memo-writing excerpts that demonstrate progressive analytic development. The conclusion calls for increasing the number and depth of qualitative methods courses and for creating a cadre of expert qualitative methodologists. © The Author(s) 2015.

Dissemination of an innovative mastery learning curriculum grounded in implementation science principles: a case study.

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McGaghie, William C; Barsuk, Jeffrey H; Cohen, Elaine R; Kristopaitis, Theresa; Wayne, Diane B

2015-11-01

Dissemination of a medical education innovation, such as mastery learning, from a setting where it has been used successfully to a new and different medical education environment is not easy. This article describes the uneven yet successful dissemination of a simulation-based mastery learning (SBML) curriculum on central venous catheter (CVC) insertion for internal medicine and emergency medicine residents across medical education settings. The dissemination program was grounded in implementation science principles. The article begins by describing implementation science which addresses the mechanisms of medical education and health care delivery. The authors then present a mastery learning case study in two phases: (1) the development, implementation, and evaluation of the SBML CVC curriculum at a tertiary care academic medical center; and (2) the dissemination of the SBML CVC curriculum to an academic community hospital setting. Contextual information about the drivers and barriers that affected the SBML CVC curriculum dissemination is presented. This work demonstrates that dissemination of mastery learning curricula, like all other medical education innovations, will fail without active educational leadership, personal contacts, dedication, hard work, rigorous measurement, and attention to implementation science principles. The article concludes by presenting a set of lessons learned about disseminating an SBML CVC curriculum across different medical education settings.

Learning tinnitus

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van Hemmen, J. Leo

Tinnitus, implying the perception of sound without the presence of any acoustical stimulus, is a chronic and serious problem for about 2% of the human population. In many cases, tinnitus is a pitch-like sensation associated with a hearing loss that confines the tinnitus frequency to an interval of the tonotopic axis. Even in patients with a normal audiogram the presence of tinnitus may be associated with damage of hair-cell function in this interval. It has been suggested that homeostatic regulation and, hence, increase of activity leads to the emergence of tinnitus. For patients with hearing loss, we present spike-timing-dependent Hebbian plasticity (STDP) in conjunction with homeostasis as a mechanism for ``learning'' tinnitus in a realistic neuronal network with tonotopically arranged synaptic excitation and inhibition. In so doing we use both dynamical scaling of the synaptic strengths and altering the resting potential of the cells. The corresponding simulations are robust to parameter changes. Understanding the mechanisms of tinnitus induction, such as here, may help improving therapy. Work done in collaboration with Julie Goulet and Michael Schneider. JLvH has been supported partially by BCCN - Munich.

Gamma/hadron segregation for a ground based imaging atmospheric Cherenkov telescope using machine learning methods: Random Forest leads

International Nuclear Information System (INIS)

Sharma Mradul; Koul Maharaj Krishna; Mitra Abhas; Nayak Jitadeepa; Bose Smarajit

2014-01-01

A detailed case study of γ-hadron segregation for a ground based atmospheric Cherenkov telescope is presented. We have evaluated and compared various supervised machine learning methods such as the Random Forest method, Artificial Neural Network, Linear Discriminant method, Naive Bayes Classifiers, Support Vector Machines as well as the conventional dynamic supercut method by simulating triggering events with the Monte Carlo method and applied the results to a Cherenkov telescope. It is demonstrated that the Random Forest method is the most sensitive machine learning method for γ-hadron segregation. (research papers)

Neuroanatomic alterations and social and communication deficits in monozygotic twins discordant for autism disorder.

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Mitchell, Shanti R; Reiss, Allan L; Tatusko, Danielle H; Ikuta, Ichiro; Kazmerski, Dana B; Botti, Jo-Anna C; Burnette, Courtney P; Kates, Wendy R

2009-08-01

Investigating neuroanatomic differences in monozygotic twins who are discordant for autism can help unravel the relative contributions of genetics and environment to this pervasive developmental disorder. The authors used magnetic resonance imaging (MRI) to investigate several brain regions of interest in monozygotic twins who varied in degree of phenotypic discordance for narrowly defined autism. The subjects were 14 pairs of monozygotic twins between the ages of 5 and 14 years old and 14 singleton age- and gender-matched typically developing comparison subjects. The monozygotic twin group was a cohort of children with narrowly defined autistic deficits and their co-twins who presented with varying levels of autistic deficits. High-resolution MRIs were acquired and volumetric/area measurements obtained for the frontal lobe, amygdala, and hippocampus and subregions of the prefrontal cortex, corpus callosum, and cerebellar vermis. No neurovolumetric/area differences were found between twin pairs. Relative to typically developing comparison subjects, dorsolateral prefrontal cortex volumes and anterior areas of the corpus callosum were significantly altered in autistic twins, and volumes of the posterior vermis were altered in both autistic twins and co-twins. Intraclass correlation analysis of brain volumes between children with autism and their co-twins indicated that the degree of within-pair neuroanatomic concordance varied with brain region. In the group of subjects with narrowly defined autism only, dorsolateral prefrontal cortex, amygdala, and posterior vermis volumes were significantly associated with the severity of autism based on scores from the Autism Diagnostic Observation Schedule-Generic. These findings support previous research demonstrating alterations in the prefrontal cortex, corpus callosum, and posterior vermis in children with autism and further suggest that alterations are associated with the severity of the autism phenotype. Continued research

A Neuroanatomical Model of Prefrontal Inhibitory Modulation of Memory Retrieval

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Depue, Brendan E.

2012-01-01

Memory of past experience is essential for guiding goal-related behavior. Being able to control accessibility of memory through modulation of retrieval enables humans to flexibly adapt to their environment. Understanding the specific neural pathways of how this control is achieved has largely eluded cognitive neuroscience. Accordingly, in the current paper I review literature that examines the overt control over retrieval in order to reduce accessibility. I first introduce three hypotheses of inhibition of retrieval. These hypotheses involve: i) attending to other stimuli as a form of diversionary attention, ii) inhibiting the specific individual neural representation of the memory, and iii) inhibiting the hippocampus and retrieval process more generally to prevent reactivation of the representation. I then analyze literature taken from the White Bear Suppression, Directed Forgetting and Think/No-Think tasks to provide evidence for these hypotheses. Finally, a neuroanatomical model is developed to indicate three pathways from PFC to the hippocampal complex that support inhibition of memory retrieval. Describing these neural pathways increases our understanding of control over memory in general. PMID:22374224

Incremental learning of perceptual and conceptual representations and the puzzle of neural repetition suppression.

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Gotts, Stephen J

2016-08-01

Incremental learning models of long-term perceptual and conceptual knowledge hold that neural representations are gradually acquired over many individual experiences via Hebbian-like activity-dependent synaptic plasticity across cortical connections of the brain. In such models, variation in task relevance of information, anatomic constraints, and the statistics of sensory inputs and motor outputs lead to qualitative alterations in the nature of representations that are acquired. Here, the proposal that behavioral repetition priming and neural repetition suppression effects are empirical markers of incremental learning in the cortex is discussed, and research results that both support and challenge this position are reviewed. Discussion is focused on a recent fMRI-adaptation study from our laboratory that shows decoupling of experience-dependent changes in neural tuning, priming, and repetition suppression, with representational changes that appear to work counter to the explicit task demands. Finally, critical experiments that may help to clarify and resolve current challenges are outlined.

Learning Experiences and Practices of Elementary Teacher Candidates on the Use of Emerging Technology: A Grounded Theory Approach

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Bahng, EunJin; Lee, Mimi

2017-01-01

The purpose of this study is to understand the phenomenon of the "professional journey" of elementary teacher candidates (ETC) both as learners and as teachers by exploring their learning experiences and practices regarding the virtual reality (VR) platform called Second Life (SL). Using the grounded theory approach, we designed an…

Word learning emerges from the interaction of online referent selection and slow associative learning

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McMurray, Bob; Horst, Jessica S.; Samuelson, Larissa K.

2013-01-01

Classic approaches to word learning emphasize the problem of referential ambiguity: in any naming situation the referent of a novel word must be selected from many possible objects, properties, actions, etc. To solve this problem, researchers have posited numerous constraints, and inference strategies, but assume that determining the referent of a novel word is isomorphic to learning. We present an alternative model in which referent selection is an online process that is independent of long-term learning. This two timescale approach creates significant power in the developing system. We illustrate this with a dynamic associative model in which referent selection is simulated as dynamic competition between competing referents, and learning is simulated using associative (Hebbian) learning. This model can account for a range of findings including the delay in expressive vocabulary relative to receptive vocabulary, learning under high degrees of referential ambiguity using cross-situational statistics, accelerating (vocabulary explosion) and decelerating (power-law) learning rates, fast-mapping by mutual exclusivity (and differences in bilinguals), improvements in familiar word recognition with development, and correlations between individual differences in speed of processing and learning. Five theoretical points are illustrated. 1) Word learning does not require specialized processes – general association learning buttressed by dynamic competition can account for much of the literature. 2) The processes of recognizing familiar words are not different than those that support novel words (e.g., fast-mapping). 3) Online competition may allow the network (or child) to leverage information available in the task to augment performance or behavior despite what might be relatively slow learning or poor representations. 4) Even associative learning is more complex than previously thought – a major contributor to performance is the pruning of incorrect associations

Transformative Learning and Professional Identity Formation During International Health Electives: A Qualitative Study Using Grounded Theory.

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Sawatsky, Adam P; Nordhues, Hannah C; Merry, Stephen P; Bashir, M Usmaan; Hafferty, Frederic W

2018-03-27

International health electives (IHEs) are widely available during residency and provide unique experiences for trainees. Theoretical models of professional identity formation and transformative learning may provide insight into residents' experiences during IHEs. The purpose of this study was to explore transformative learning and professional identity formation during resident IHEs and characterize the relationship between transformative learning and professional identity formation. The authors used a constructivist grounded theory approach, with the sensitizing concepts of transformative learning and professional identity formation to analyze narrative reflective reports of residents' IHEs. The Mayo International Health Program supports residents from all specialties across three Mayo Clinic sites. In 2015, the authors collected narrative reflective reports from 377 IHE participants dating from 2001-2014. Reflections were coded and themes were organized into a model for transformative learning during IHEs, focusing on professional identity. Five components of transformative learning were identified during IHEs: a disorienting experience; an emotional response; critical reflection; perspective change; and a commitment to future action. Within the component of critical reflection three domains relating to professional identity were identified: making a difference; the doctor-patient relationship; and medicine in its "purest form." Transformation was demonstrated through perspective change and a commitment to future action, including continued service, education, and development. IHEs provide rich experiences for transformative learning and professional identity formation. Understanding the components of transformative learning may provide insight into the interaction between learner, experiences, and the influence of mentors in the process of professional identity formation.

Lessons learned on the Ground Test Accelerator control system

International Nuclear Information System (INIS)

Kozubal, A.J.; Weiss, R.E.

1994-01-01

When we initiated the control system design for the Ground Test Accelerator (GTA), we envisioned a system that would be flexible enough to handle the changing requirements of an experimental project. This control system would use a developers' toolkit to reduce the cost and time to develop applications for GTA, and through the use of open standards, the system would accommodate unforeseen requirements as they arose. Furthermore, we would attempt to demonstrate on GTA a level of automation far beyond that achieved by existing accelerator control systems. How well did we achieve these goals? What were the stumbling blocks to deploying the control system, and what assumptions did we make about requirements that turned out to be incorrect? In this paper we look at the process of developing a control system that evolved into what is now the ''Experimental Physics and Industrial Control System'' (EPICS). Also, we assess the impact of this system on the GTA project, as well as the impact of GTA on EPICS. The lessons learned on GTA will be valuable for future projects

NEUROANATOMICAL ASSOCIATION OF HYPOTHALAMIC HSD2-CONTAINING NEURONS WITH ERα, CATECHOLAMINES, OR OXYTOCIN: IMPLICATIONS FOR FEEDING?

Directory of Open Access Journals (Sweden)

Maegan L. Askew

2015-06-01

Full Text Available This study used immunohistochemical methods to investigate the possibility that hypothalamic neurons that contain 11-β-hydroxysteroid dehydrogenase type 2 (HSD2 are involved in the control of feeding by rats via neuroanatomical associations with the α subtype of estrogen receptor (ERα, catecholamines, and/or oxytocin. An aggregate of HSD2-containing neurons is located laterally in the hypothalamus, and the numbers of these neurons were greatly increased by estradiol treatment in ovariectomized rats compared to numbers in male rats and in ovariectomized rats that were not given estradiol. However, HSD2-containing neurons were anatomically segregated from ERα-containing neurons in the Ventromedial Hypothalamus and the Arcuate Nucleus. There was an absence of oxytocin-immunolabeled fibers in the area of HSD2-labeled neurons. Taken together, these findings provide no support for direct associations between hypothalamic HSD2 and ERα or oxytocin neurons in the control of feeding. In contrast, there was catecholamine-fiber labeling in the area of HSD2-labeled neurons, and these fibers occasionally were in close apposition to HSD2-labeled neurons. Therefore, we cannot rule out interactions between HSD2 and catecholamines in the control of feeding; however, given the relative sparseness of the appositions, any such interaction would appear to be modest. Thus, these studies do not conclusively identify a neuroanatomical substrate by which HSD2-containing neurons in the hypothalamus may alter feeding, and leave the functional role of hypothalamic HSD2-containing neurons subject to further investigation.

Genetic attack on neural cryptography.

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Ruttor, Andreas; Kinzel, Wolfgang; Naeh, Rivka; Kanter, Ido

2006-03-01

Different scaling properties for the complexity of bidirectional synchronization and unidirectional learning are essential for the security of neural cryptography. Incrementing the synaptic depth of the networks increases the synchronization time only polynomially, but the success of the geometric attack is reduced exponentially and it clearly fails in the limit of infinite synaptic depth. This method is improved by adding a genetic algorithm, which selects the fittest neural networks. The probability of a successful genetic attack is calculated for different model parameters using numerical simulations. The results show that scaling laws observed in the case of other attacks hold for the improved algorithm, too. The number of networks needed for an effective attack grows exponentially with increasing synaptic depth. In addition, finite-size effects caused by Hebbian and anti-Hebbian learning are analyzed. These learning rules converge to the random walk rule if the synaptic depth is small compared to the square root of the system size.

Genetic attack on neural cryptography

International Nuclear Information System (INIS)

Ruttor, Andreas; Kinzel, Wolfgang; Naeh, Rivka; Kanter, Ido

2006-01-01

Different scaling properties for the complexity of bidirectional synchronization and unidirectional learning are essential for the security of neural cryptography. Incrementing the synaptic depth of the networks increases the synchronization time only polynomially, but the success of the geometric attack is reduced exponentially and it clearly fails in the limit of infinite synaptic depth. This method is improved by adding a genetic algorithm, which selects the fittest neural networks. The probability of a successful genetic attack is calculated for different model parameters using numerical simulations. The results show that scaling laws observed in the case of other attacks hold for the improved algorithm, too. The number of networks needed for an effective attack grows exponentially with increasing synaptic depth. In addition, finite-size effects caused by Hebbian and anti-Hebbian learning are analyzed. These learning rules converge to the random walk rule if the synaptic depth is small compared to the square root of the system size

Genetic attack on neural cryptography

Science.gov (United States)

Ruttor, Andreas; Kinzel, Wolfgang; Naeh, Rivka; Kanter, Ido

2006-03-01

Different scaling properties for the complexity of bidirectional synchronization and unidirectional learning are essential for the security of neural cryptography. Incrementing the synaptic depth of the networks increases the synchronization time only polynomially, but the success of the geometric attack is reduced exponentially and it clearly fails in the limit of infinite synaptic depth. This method is improved by adding a genetic algorithm, which selects the fittest neural networks. The probability of a successful genetic attack is calculated for different model parameters using numerical simulations. The results show that scaling laws observed in the case of other attacks hold for the improved algorithm, too. The number of networks needed for an effective attack grows exponentially with increasing synaptic depth. In addition, finite-size effects caused by Hebbian and anti-Hebbian learning are analyzed. These learning rules converge to the random walk rule if the synaptic depth is small compared to the square root of the system size.

Topological self-organization and prediction learning support both action and lexical chains in the brain.

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Chersi, Fabian; Ferro, Marcello; Pezzulo, Giovanni; Pirrelli, Vito

2014-07-01

A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or linguistic units, the network develops independent neuronal chains, formed by dedicated nodes encoding only context-specific stimuli. Moreover, neurons responding to the same stimulus or class of stimuli tend to cluster together to form topologically connected areas similar to those observed in the brain cortex. Simulations support a unitary explanatory framework reconciling neurophysiological motor data with established behavioral evidence on lexical acquisition, access, and recall. Copyright © 2014 Cognitive Science Society, Inc.

Facilitating classroom based interprofessional learning: a grounded theory study of university educators' perceptions of their role adequacy as facilitators.

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Derbyshire, Julie A; Machin, Alison I; Crozier, Suzanne

2015-01-01

The provision of inter professional learning (IPL) within undergraduate programmes is now well established within many Higher Education Institutions (HEIs). IPL aims to better equip nurses and other health professionals with effective collaborative working skills and knowledge to improve the quality of patient care. Although there is still ambiguity in relation to the optimum timing and method for delivering IPL, effective facilitation is seen as essential. This paper reports on a grounded theory study of university educators' perceptions of the knowledge and skills needed for their role adequacy as IPL facilitators. Data was collected using semi structured interviews with nine participants who were theoretically sampled from a range of professional backgrounds, with varied experiences of education and involvement in facilitating IPL. Constant comparative analysis was used to generate four data categories: creating and sustaining an IPL group culture through transformational IPL leadership (core category), readiness for IPL facilitation, drawing on past interprofessional learning and working experiences and role modelling an interprofessional approach. The grounded theory generated from this study, although propositional, suggests that role adequacy for IPL facilitation is dependent on facilitator engagement in a process of 'transformational interprofessional learning leadership' to create and sustain a group culture. Copyright © 2014 Elsevier Ltd. All rights reserved.

Parcellating the neuroanatomical basis of impaired decision-making in traumatic brain injury.

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Newcombe, Virginia F J; Outtrim, Joanne G; Chatfield, Doris A; Manktelow, Anne; Hutchinson, Peter J; Coles, Jonathan P; Williams, Guy B; Sahakian, Barbara J; Menon, David K

2011-03-01

Cognitive dysfunction is a devastating consequence of traumatic brain injury that affects the majority of those who survive with moderate-to-severe injury, and many patients with mild head injury. Disruption of key monoaminergic neurotransmitter systems, such as the dopaminergic system, may play a key role in the widespread cognitive dysfunction seen after traumatic axonal injury. Manifestations of injury to this system may include impaired decision-making and impulsivity. We used the Cambridge Gambling Task to characterize decision-making and risk-taking behaviour, outside of a learning context, in a cohort of 44 patients at least six months post-traumatic brain injury. These patients were found to have broadly intact processing of risk adjustment and probability judgement, and to bet similar amounts to controls. However, a patient preference for consistently early bets indicated a higher level of impulsiveness. These behavioural measures were compared with imaging findings on diffusion tensor magnetic resonance imaging. Performance in specific domains of the Cambridge Gambling Task correlated inversely and specifically with the severity of diffusion tensor imaging abnormalities in regions that have been implicated in these cognitive processes. Thus, impulsivity was associated with increased apparent diffusion coefficient bilaterally in the orbitofrontal gyrus, insula and caudate; abnormal risk adjustment with increased apparent diffusion coefficient in the right thalamus and dorsal striatum and left caudate; and impaired performance on rational choice with increased apparent diffusion coefficient in the bilateral dorsolateral prefrontal cortices, and the superior frontal gyri, right ventrolateral prefrontal cortex, the dorsal and ventral striatum, and left hippocampus. Importantly, performance in specific cognitive domains of the task did not correlate with diffusion tensor imaging abnormalities in areas not implicated in their performance. The ability to

Grounded Object and Grasp Representations in a Cognitive Architecture

DEFF Research Database (Denmark)

Kraft, Dirk

developed. This work presents a system that is able to learn autonomously about objects and applicable grasps in an unknown environment through exploratory manipulation and to then use this grounded knowledge in a planning setup to address complex tasks. A set of different subsystems is needed to achieve....... The topics are ordered so that we proceed from the more general integration works towards the works describing the individual components. The first chapter gives an overview over the system that is able to learn a grounded visual object representation and a grounded grasp representation. In the following...... part, we describe how this grounding procedures can be embedded in a three cognitive level architecture. Our initial work to use a tactile sensor to enrichen the object representations as well as allow for more complex actions is presented here as well. Since our system is concerned with learning about...

Neuroanatomical Substrates of Rodent Social Behavior: The Medial Prefrontal Cortex and Its Projection Patterns

Science.gov (United States)

Ko, Jaewon

2017-01-01

Social behavior encompasses a number of distinctive and complex constructs that form the core elements of human imitative culture, mainly represented as either affiliative or antagonistic interactions with conspecifics. Traditionally considered in the realm of psychology, social behavior research has benefited from recent advancements in neuroscience that have accelerated identification of the neural systems, circuits, causative genes and molecular mechanisms that underlie distinct social cognitive traits. In this review article, I summarize recent findings regarding the neuroanatomical substrates of key social behaviors, focusing on results from experiments conducted in rodent models. In particular, I will review the role of the medial prefrontal cortex (mPFC) and downstream subcortical structures in controlling social behavior, and discuss pertinent future research perspectives. PMID:28659766

Criterion learning in rule-based categorization: simulation of neural mechanism and new data.

Science.gov (United States)

Helie, Sebastien; Ell, Shawn W; Filoteo, J Vincent; Maddox, W Todd

2015-04-01

In perceptual categorization, rule selection consists of selecting one or several stimulus-dimensions to be used to categorize the stimuli (e.g., categorize lines according to their length). Once a rule has been selected, criterion learning consists of defining how stimuli will be grouped using the selected dimension(s) (e.g., if the selected rule is line length, define 'long' and 'short'). Very little is known about the neuroscience of criterion learning, and most existing computational models do not provide a biological mechanism for this process. In this article, we introduce a new model of rule learning called Heterosynaptic Inhibitory Criterion Learning (HICL). HICL includes a biologically-based explanation of criterion learning, and we use new category-learning data to test key aspects of the model. In HICL, rule selective cells in prefrontal cortex modulate stimulus-response associations using pre-synaptic inhibition. Criterion learning is implemented by a new type of heterosynaptic error-driven Hebbian learning at inhibitory synapses that uses feedback to drive cell activation above/below thresholds representing ionic gating mechanisms. The model is used to account for new human categorization data from two experiments showing that: (1) changing rule criterion on a given dimension is easier if irrelevant dimensions are also changing (Experiment 1), and (2) showing that changing the relevant rule dimension and learning a new criterion is more difficult, but also facilitated by a change in the irrelevant dimension (Experiment 2). We conclude with a discussion of some of HICL's implications for future research on rule learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Novel insights into early neuroanatomical evolution in penguins from the oldest described penguin brain endocast.

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Proffitt, J V; Clarke, J A; Scofield, R P

2016-08-01

Digital methodologies for rendering the gross morphology of the brain from X-ray computed tomography data have expanded our current understanding of the origin and evolution of avian neuroanatomy and provided new perspectives on the cognition and behavior of birds in deep time. However, fossil skulls germane to extracting digital endocasts from early stem members of extant avian lineages remain exceptionally rare. Data from early-diverging species of major avian subclades provide key information on ancestral morphologies in Aves and shifts in gross neuroanatomical structure that have occurred within those groups. Here we describe data on the gross morphology of the brain from a mid-to-late Paleocene penguin fossil from New Zealand. This most basal and geochronologically earliest-described endocast from the penguin clade indicates that described neuroanatomical features of early stem penguins, such as lower telencephalic lateral expansion, a relatively wider cerebellum, and lack of cerebellar folding, were present far earlier in penguin history than previously inferred. Limited dorsal expansion of the wulst in the new fossil is a feature seen in outgroup waterbird taxa such as Gaviidae (Loons) and diving Procellariiformes (Shearwaters, Diving Petrels, and allies), indicating that loss of flight may not drastically affect neuroanatomy in diving taxa. Wulst enlargement in the penguin lineage is first seen in the late Eocene, at least 25 million years after loss of flight and cooption of the flight stroke for aquatic diving. Similar to the origin of avian flight, major shifts in gross brain morphology follow, but do not appear to evolve quickly after, acquisition of a novel locomotor mode. Enlargement of the wulst shows a complex pattern across waterbirds, and may be linked to sensory modifications related to prey choice and foraging strategy. © 2016 Anatomical Society.

Methods for reducing interference in the Complementary Learning Systems model: oscillating inhibition and autonomous memory rehearsal.

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Norman, Kenneth A; Newman, Ehren L; Perotte, Adler J

2005-11-01

The stability-plasticity problem (i.e. how the brain incorporates new information into its model of the world, while at the same time preserving existing knowledge) has been at the forefront of computational memory research for several decades. In this paper, we critically evaluate how well the Complementary Learning Systems theory of hippocampo-cortical interactions addresses the stability-plasticity problem. We identify two major challenges for the model: Finding a learning algorithm for cortex and hippocampus that enacts selective strengthening of weak memories, and selective punishment of competing memories; and preventing catastrophic forgetting in the case of non-stationary environments (i.e. when items are temporarily removed from the training set). We then discuss potential solutions to these problems: First, we describe a recently developed learning algorithm that leverages neural oscillations to find weak parts of memories (so they can be strengthened) and strong competitors (so they can be punished), and we show how this algorithm outperforms other learning algorithms (CPCA Hebbian learning and Leabra at memorizing overlapping patterns. Second, we describe how autonomous re-activation of memories (separately in cortex and hippocampus) during REM sleep, coupled with the oscillating learning algorithm, can reduce the rate of forgetting of input patterns that are no longer present in the environment. We then present a simple demonstration of how this process can prevent catastrophic interference in an AB-AC learning paradigm.

A model of self-directed learning in internal medicine residency: a qualitative study using grounded theory.

Science.gov (United States)

Sawatsky, Adam P; Ratelle, John T; Bonnes, Sara L; Egginton, Jason S; Beckman, Thomas J

2017-02-02

Existing theories of self-directed learning (SDL) have emphasized the importance of process, personal, and contextual factors. Previous medical education research has largely focused on the process of SDL. We explored the experience with and perception of SDL among internal medicine residents to gain understanding of the personal and contextual factors of SDL in graduate medical education. Using a constructivist grounded theory approach, we conducted 7 focus group interviews with 46 internal medicine residents at an academic medical center. We processed the data by using open coding and writing analytic memos. Team members organized open codes to create axial codes, which were applied to all transcripts. Guided by a previous model of SDL, we developed a theoretical model that was revised through constant comparison with new data as they were collected, and we refined the theory until it had adequate explanatory power and was appropriately grounded in the experiences of residents. We developed a theoretical model of SDL to explain the process, personal, and contextual factors affecting SDL during residency training. The process of SDL began with a trigger that uncovered a knowledge gap. Residents progressed to formulating learning objectives, using resources, applying knowledge, and evaluating learning. Personal factors included motivations, individual characteristics, and the change in approach to SDL over time. Contextual factors included the need for external guidance, the influence of residency program structure and culture, and the presence of contextual barriers. We developed a theoretical model of SDL in medical education that can be used to promote and assess resident SDL through understanding the process, person, and context of SDL.

Neuroanatomic correlates of stroke-related myocardial injury.

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Ay, H; Koroshetz, W J; Benner, T; Vangel, M G; Melinosky, C; Arsava, E M; Ayata, C; Zhu, M; Schwamm, L H; Sorensen, A G

2006-05-09

Myocardial injury can occur after ischemic stroke in the absence of primary cardiac causes. The neuroanatomic basis of stroke-related myocardial injury is not well understood. To identify regions of brain infarction associated with myocardial injury using a method free of the bias of an a priori hypothesis as to any specific location. Of 738 consecutive patients with acute ischemic stroke, the authors identified 50 patients in whom serum cardiac troponin T (cTnT) elevation occurred in the absence of any apparent cause within 3 days of symptom onset. Fifty randomly selected, age- and sex-matched patients with ischemic stroke without cTnT elevation served as controls. Diffusion-weighted images with outlines of infarction were co-registered to a template, averaged, and then subtracted to find voxels that differed between the two groups. Voxel-wise p values were determined using a nonparametric permutation test to identify specific regions of infarction that were associated with cTnT elevation. The study groups were well balanced with respect to stroke risk factors, history of coronary artery disease, infarction volume, and frequency of right and left middle cerebral artery territory involvement. Brain regions that were a priori associated with cTnT elevation included the right posterior, superior, and medial insula and the right inferior parietal lobule. Among patients with right middle cerebral artery infarction, the insular cluster was involved in 88% of patients with and 33% without cTnT elevation (odds ratio: 15.00; 95% CI: 2.65 to 84.79). Infarctions in specific brain regions including the right insula are associated with elevated serum cardiac troponin T level indicative of myocardial injury.

14 CFR Appendix H to Part 141 - Ground Instructor Certification Course

Science.gov (United States)

2010-01-01

... planning; and (6) Classroom training techniques. (c) Ground training for a basic ground instructor..., required under this part, for the following ratings: (a) Ground Instructor—Basic. (b) Ground Instructor...) Ground training must include the following aeronautical knowledge areas: (1) Learning process; (2...

A Reinforcement-Based Learning Paradigm Increases Anatomical Learning and Retention-A Neuroeducation Study.

Science.gov (United States)

Anderson, Sarah J; Hecker, Kent G; Krigolson, Olave E; Jamniczky, Heather A

2018-01-01

In anatomy education, a key hurdle to engaging in higher-level discussion in the classroom is recognizing and understanding the extensive terminology used to identify and describe anatomical structures. Given the time-limited classroom environment, seeking methods to impart this foundational knowledge to students in an efficient manner is essential. Just-in-Time Teaching (JiTT) methods incorporate pre-class exercises (typically online) meant to establish foundational knowledge in novice learners so subsequent instructor-led sessions can focus on deeper, more complex concepts. Determining how best do we design and assess pre-class exercises requires a detailed examination of learning and retention in an applied educational context. Here we used electroencephalography (EEG) as a quantitative dependent variable to track learning and examine the efficacy of JiTT activities to teach anatomy. Specifically, we examined changes in the amplitude of the N250 and reward positivity event-related brain potential (ERP) components alongside behavioral performance as novice students participated in a series of computerized reinforcement-based learning modules to teach neuroanatomical structures. We found that as students learned to identify anatomical structures, the amplitude of the N250 increased and reward positivity amplitude decreased in response to positive feedback. Both on a retention and transfer exercise when learners successfully remembered and translated their knowledge to novel images, the amplitude of the reward positivity remained decreased compared to early learning. Our findings suggest ERPs can be used as a tool to track learning, retention, and transfer of knowledge and that employing the reinforcement learning paradigm is an effective educational approach for developing anatomical expertise.

Peeling the layers: a grounded theory of interprofessional co-learning with residents of a homeless shelter.

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E Rutherford, Gayle

2011-09-01

Clients, patients, families, and communities must be conceived as partners in care delivery, not just as recipients (D'Amour, D. & Oandasan, I. (2005). Journal of Interprofessional Care, 19(Suppl.), 8-20). Health-care students need an opportunity to understand community member self-determination, partnership, and empowerment (Scheyett, A., & Diehl, M. ( 2004 ). Social Work Education, 23(4), 435-450), within the frame of interprofessional education (IPE) where community members are involved as teachers and learners. The aim of this grounded theory research was to determine the conditions that support health-care students to learn with, from, and about community members. This study took place in a shelter for the homeless where nursing and social work students learned interprofessionally along with residents and clients of the shelter. Data were gathered through 7 months of participant observation, interviews, and focus groups. The interprofessional co-learning theory that emerged introduces the three phases of entering, engaging, and emerging, which co-learners experienced at different levels of intensity. This article outlines the conditions that support each of these phases of the co-learning process. This interprofessional co-learning theory provides a basis for further development and evaluation of IPE programs that strive to actively include community members as teachers and learners, experts, and novices together with service providers, students, and faculty members.

How characteristic routines of clinical departments influence students' self-regulated learning: A grounded theory study.

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Berkhout, J J; Slootweg, I A; Helmich, E; Teunissen, P W; van der Vleuten, C P M; Jaarsma, A D C

2017-11-01

In clerkships, students are expected to self-regulate their learning. How clinical departments and their routine approach on clerkships influences students' self-regulated learning (SRL) is unknown. This study explores how characteristic routines of clinical departments influence medical students' SRL. Six focus groups including 39 purposively sampled participants from one Dutch university were organized to study how characteristic routines of clinical departments influenced medical students' SRL from a constructivist paradigm, using grounded theory methodology. The focus groups were audio recorded, transcribed verbatim and were analyzed iteratively using constant comparison and open, axial and interpretive coding. Students described that clinical departments influenced their SRL through routines which affected the professional relationships they could engage in and affected their perception of a department's invested effort in them. Students' SRL in a clerkship can be supported by enabling them to engage others in their SRL and by having them feel that effort is invested in their learning. Our study gives a practical insight in how clinical departments influenced students' SRL. Clinical departments can affect students' motivation to engage in SRL, influence the variety of SRL strategies that students can use and how meaningful students perceive their SRL experiences to be.

Bidirectional Hebbian Plasticity Induced by Low-Frequency Stimulation in Basal Dendrites of Rat Barrel Cortex Layer 5 Pyramidal Neurons.

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Díez-García, Andrea; Barros-Zulaica, Natali; Núñez, Ángel; Buño, Washington; Fernández de Sevilla, David

2017-01-01

According to Hebb's original hypothesis (Hebb, 1949), synapses are reinforced when presynaptic activity triggers postsynaptic firing, resulting in long-term potentiation (LTP) of synaptic efficacy. Long-term depression (LTD) is a use-dependent decrease in synaptic strength that is thought to be due to synaptic input causing a weak postsynaptic effect. Although the mechanisms that mediate long-term synaptic plasticity have been investigated for at least three decades not all question have as yet been answered. Therefore, we aimed at determining the mechanisms that generate LTP or LTD with the simplest possible protocol. Low-frequency stimulation of basal dendrite inputs in Layer 5 pyramidal neurons of the rat barrel cortex induces LTP. This stimulation triggered an EPSP, an action potential (AP) burst, and a Ca 2+ spike. The same stimulation induced LTD following manipulations that reduced the Ca 2+ spike and Ca 2+ signal or the AP burst. Low-frequency whisker deflections induced similar bidirectional plasticity of action potential evoked responses in anesthetized rats. These results suggest that both in vitro and in vivo similar mechanisms regulate the balance between LTP and LTD. This simple induction form of bidirectional hebbian plasticity could be present in the natural conditions to regulate the detection, flow, and storage of sensorimotor information.

Bidirectional Hebbian Plasticity Induced by Low-Frequency Stimulation in Basal Dendrites of Rat Barrel Cortex Layer 5 Pyramidal Neurons

Science.gov (United States)

Díez-García, Andrea; Barros-Zulaica, Natali; Núñez, Ángel; Buño, Washington; Fernández de Sevilla, David

2017-01-01

According to Hebb's original hypothesis (Hebb, 1949), synapses are reinforced when presynaptic activity triggers postsynaptic firing, resulting in long-term potentiation (LTP) of synaptic efficacy. Long-term depression (LTD) is a use-dependent decrease in synaptic strength that is thought to be due to synaptic input causing a weak postsynaptic effect. Although the mechanisms that mediate long-term synaptic plasticity have been investigated for at least three decades not all question have as yet been answered. Therefore, we aimed at determining the mechanisms that generate LTP or LTD with the simplest possible protocol. Low-frequency stimulation of basal dendrite inputs in Layer 5 pyramidal neurons of the rat barrel cortex induces LTP. This stimulation triggered an EPSP, an action potential (AP) burst, and a Ca2+ spike. The same stimulation induced LTD following manipulations that reduced the Ca2+ spike and Ca2+ signal or the AP burst. Low-frequency whisker deflections induced similar bidirectional plasticity of action potential evoked responses in anesthetized rats. These results suggest that both in vitro and in vivo similar mechanisms regulate the balance between LTP and LTD. This simple induction form of bidirectional hebbian plasticity could be present in the natural conditions to regulate the detection, flow, and storage of sensorimotor information. PMID:28203145

Deepening Learning through Learning-by-Inventing

OpenAIRE

Apiola, Mikko; Tedre, Matti

2013-01-01

It has been shown that deep approaches to learning, intrinsic motivation, and self-regulated learning have strong positive effects on learning. How those pedagogical theories can be integrated in computing curricula is, however, still lacking empirically grounded analyses. This study integrated, in a robotics-based programming class, a method of learning-by-inventing, and studied its qualitative effects on students’ learning through 144 interviews. Five findings were related with learning the...

Brain-like associative learning using a nanoscale non-volatile phase change synaptic device array

Directory of Open Access Journals (Sweden)

Sukru Burc Eryilmaz

2014-07-01

Full Text Available Recent advances in neuroscience together with nanoscale electronic device technology have resulted in huge interests in realizing brain-like computing hardwares using emerging nanoscale memory devices as synaptic elements. Although there has been experimental work that demonstrated the operation of nanoscale synaptic element at the single device level, network level studies have been limited to simulations. In this work, we demonstrate, using experiments, array level associative learning using phase change synaptic devices connected in a grid like configuration similar to the organization of the biological brain. Implementing Hebbian learning with phase change memory cells, the synaptic grid was able to store presented patterns and recall missing patterns in an associative brain-like fashion. We found that the system is robust to device variations, and large variations in cell resistance states can be accommodated by increasing the number of training epochs. We illustrated the tradeoff between variation tolerance of the network and the overall energy consumption, and found that energy consumption is decreased significantly for lower variation tolerance.

Morphing Wing Structural Optimization Using Opposite-Based Population-Based Incremental Learning and Multigrid Ground Elements

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S. Sleesongsom

2015-01-01

Full Text Available This paper has twin aims. Firstly, a multigrid design approach for optimization of an unconventional morphing wing is proposed. The structural design problem is assigned to optimize wing mass, lift effectiveness, and buckling factor subject to structural safety requirements. Design variables consist of partial topology, nodal positions, and component sizes of a wing internal structure. Such a design process can be accomplished by using multiple resolutions of ground elements, which is called a multigrid approach. Secondly, an opposite-based multiobjective population-based incremental learning (OMPBIL is proposed for comparison with the original multiobjective population-based incremental learning (MPBIL. Multiobjective design problems with single-grid and multigrid design variables are then posed and tackled by OMPBIL and MPBIL. The results show that using OMPBIL in combination with a multigrid design approach is the best design strategy. OMPBIL is superior to MPBIL since the former provides better population diversity. Aeroelastic trim for an elastic morphing wing is also presented.

Burst-induced anti-Hebbian depression acts through short-term synaptic dynamics to cancel redundant sensory signals.

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Harvey-Girard, Erik; Lewis, John; Maler, Leonard

2010-04-28

Weakly electric fish can enhance the detection and localization of important signals such as those of prey in part by cancellation of redundant spatially diffuse electric signals due to, e.g., their tail bending. The cancellation mechanism is based on descending input, conveyed by parallel fibers emanating from cerebellar granule cells, that produces a negative image of the global low-frequency signals in pyramidal cells within the first-order electrosensory region, the electrosensory lateral line lobe (ELL). Here we demonstrate that the parallel fiber synaptic input to ELL pyramidal cell undergoes long-term depression (LTD) whenever both parallel fiber afferents and their target cells are stimulated to produce paired burst discharges. Paired large bursts (4-4) induce robust LTD over pre-post delays of up to +/-50 ms, whereas smaller bursts (2-2) induce weaker LTD. Single spikes (either presynaptic or postsynaptic) paired with bursts did not induce LTD. Tetanic presynaptic stimulation was also ineffective in inducing LTD. Thus, we have demonstrated a form of anti-Hebbian LTD that depends on the temporal correlation of burst discharge. We then demonstrated that the burst-induced LTD is postsynaptic and requires the NR2B subunit of the NMDA receptor, elevation of postsynaptic Ca(2+), and activation of CaMKIIbeta. A model incorporating local inhibitory circuitry and previously identified short-term presynaptic potentiation of the parallel fiber synapses further suggests that the combination of burst-induced LTD, presynaptic potentiation, and local inhibition may be sufficient to explain the generation of the negative image and cancellation of redundant sensory input by ELL pyramidal cells.

Neuropsychology of learning and memory in teleost fish.

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Salas, Cosme; Broglio, Cristina; Durán, Emilio; Gómez, Antonia; Ocaña, Francisco M; Jiménez-Moya, Fernando; Rodríguez, Fernando

2006-01-01

Traditionally, brain and behavior evolution was viewed as an anagenetic process that occurred in successive stages of increasing complexity and advancement. Fishes, considered the most primitive vertebrates, were supposed to have a scarcely differentiated telencephalon, and limited learning capabilities. However, recent developmental, neuroanatomical, and functional data indicate that the evolution of brain and behavior may have been more conservative than previously thought. Experimental data suggest that the properties and neural basis of learning and memory are notably similar among teleost fish and land vertebrates. For example, lesion studies show that the teleost cerebellum is essential in classical conditioning of discrete motor responses. The lateral telencephalic pallium of the teleost fish, proposed as homologous to the hippocampus, is selectively involved in spatial learning and memory, and in trace classical conditioning. In contrast, the medial pallium, considered homologous to the amygdala, is involved in emotional conditioning in teleost fish. The data reviewed here show a remarkable parallelism between mammals and teleost fish concerning the role of different brain centers in learning and memory and cognitive processes. These evidences suggest that these separate memory systems could have appeared early during the evolution of vertebrates, having been conserved through phylogenesis.

A BCM theory of meta-plasticity for online self-reorganizing fuzzy-associative learning.

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Tan, Javan; Quek, Chai

2010-06-01

Self-organizing neurofuzzy approaches have matured in their online learning of fuzzy-associative structures under time-invariant conditions. To maximize their operative value for online reasoning, these self-sustaining mechanisms must also be able to reorganize fuzzy-associative knowledge in real-time dynamic environments. Hence, it is critical to recognize that they would require self-reorganizational skills to rebuild fluid associative structures when their existing organizations fail to respond well to changing circumstances. In this light, while Hebbian theory (Hebb, 1949) is the basic computational framework for associative learning, it is less attractive for time-variant online learning because it suffers from stability limitations that impedes unlearning. Instead, this paper adopts the Bienenstock-Cooper-Munro (BCM) theory of neurological learning via meta-plasticity principles (Bienenstock et al., 1982) that provides for both online associative and dissociative learning. For almost three decades, BCM theory has been shown to effectively brace physiological evidence of synaptic potentiation (association) and depression (dissociation) into a sound mathematical framework for computational learning. This paper proposes an interpretation of the BCM theory of meta-plasticity for an online self-reorganizing fuzzy-associative learning system to realize online-reasoning capabilities. Experimental findings are twofold: 1) the analysis using S&P-500 stock index illustrated that the self-reorganizing approach could follow the trajectory shifts in the time-variant S&P-500 index for about 60 years, and 2) the benchmark profiles showed that the fuzzy-associative approach yielded comparable results with other fuzzy-precision models with similar online objectives.

A Reinforcement-Based Learning Paradigm Increases Anatomical Learning and Retention—A Neuroeducation Study

Science.gov (United States)

Anderson, Sarah J.; Hecker, Kent G.; Krigolson, Olave E.; Jamniczky, Heather A.

2018-01-01

In anatomy education, a key hurdle to engaging in higher-level discussion in the classroom is recognizing and understanding the extensive terminology used to identify and describe anatomical structures. Given the time-limited classroom environment, seeking methods to impart this foundational knowledge to students in an efficient manner is essential. Just-in-Time Teaching (JiTT) methods incorporate pre-class exercises (typically online) meant to establish foundational knowledge in novice learners so subsequent instructor-led sessions can focus on deeper, more complex concepts. Determining how best do we design and assess pre-class exercises requires a detailed examination of learning and retention in an applied educational context. Here we used electroencephalography (EEG) as a quantitative dependent variable to track learning and examine the efficacy of JiTT activities to teach anatomy. Specifically, we examined changes in the amplitude of the N250 and reward positivity event-related brain potential (ERP) components alongside behavioral performance as novice students participated in a series of computerized reinforcement-based learning modules to teach neuroanatomical structures. We found that as students learned to identify anatomical structures, the amplitude of the N250 increased and reward positivity amplitude decreased in response to positive feedback. Both on a retention and transfer exercise when learners successfully remembered and translated their knowledge to novel images, the amplitude of the reward positivity remained decreased compared to early learning. Our findings suggest ERPs can be used as a tool to track learning, retention, and transfer of knowledge and that employing the reinforcement learning paradigm is an effective educational approach for developing anatomical expertise. PMID:29467638

A Reinforcement-Based Learning Paradigm Increases Anatomical Learning and Retention—A Neuroeducation Study

Directory of Open Access Journals (Sweden)

Sarah J. Anderson

2018-02-01

Full Text Available In anatomy education, a key hurdle to engaging in higher-level discussion in the classroom is recognizing and understanding the extensive terminology used to identify and describe anatomical structures. Given the time-limited classroom environment, seeking methods to impart this foundational knowledge to students in an efficient manner is essential. Just-in-Time Teaching (JiTT methods incorporate pre-class exercises (typically online meant to establish foundational knowledge in novice learners so subsequent instructor-led sessions can focus on deeper, more complex concepts. Determining how best do we design and assess pre-class exercises requires a detailed examination of learning and retention in an applied educational context. Here we used electroencephalography (EEG as a quantitative dependent variable to track learning and examine the efficacy of JiTT activities to teach anatomy. Specifically, we examined changes in the amplitude of the N250 and reward positivity event-related brain potential (ERP components alongside behavioral performance as novice students participated in a series of computerized reinforcement-based learning modules to teach neuroanatomical structures. We found that as students learned to identify anatomical structures, the amplitude of the N250 increased and reward positivity amplitude decreased in response to positive feedback. Both on a retention and transfer exercise when learners successfully remembered and translated their knowledge to novel images, the amplitude of the reward positivity remained decreased compared to early learning. Our findings suggest ERPs can be used as a tool to track learning, retention, and transfer of knowledge and that employing the reinforcement learning paradigm is an effective educational approach for developing anatomical expertise.

Student Performance and Success Factors in Learning Business Statistics in Online vs. On-Ground Classes Using a Web-Based Assessment Platform

Science.gov (United States)

Shotwell, Mary; Apigian, Charles H.

2015-01-01

This study aimed to quantify the influence of student attributes, coursework resources, and online assessments on student learning in business statistics. Surveys were administered to students at the completion of both online and on-ground classes, covering student perception and utilization of internal and external academic resources, as well as…

The Neuroanatomical, Neurophysiological and Psychological Basis of Memory: Current Models and Their Origins

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Camina, Eduardo; Güell, Francisco

2017-01-01

This review aims to classify and clarify, from a neuroanatomical, neurophysiological, and psychological perspective, different memory models that are currently widespread in the literature as well as to describe their origins. We believe it is important to consider previous developments without which one cannot adequately understand the kinds of models that are now current in the scientific literature. This article intends to provide a comprehensive and rigorous overview for understanding and ordering the latest scientific advances related to this subject. The main forms of memory presented include sensory memory, short-term memory, and long-term memory. Information from the world around us is first stored by sensory memory, thus enabling the storage and future use of such information. Short-term memory (or memory) refers to information processed in a short period of time. Long-term memory allows us to store information for long periods of time, including information that can be retrieved consciously (explicit memory) or unconsciously (implicit memory). PMID:28713278

The Neuroanatomical, Neurophysiological and Psychological Basis of Memory: Current Models and Their Origins.

Science.gov (United States)

Camina, Eduardo; Güell, Francisco

2017-01-01

This review aims to classify and clarify, from a neuroanatomical, neurophysiological, and psychological perspective, different memory models that are currently widespread in the literature as well as to describe their origins. We believe it is important to consider previous developments without which one cannot adequately understand the kinds of models that are now current in the scientific literature. This article intends to provide a comprehensive and rigorous overview for understanding and ordering the latest scientific advances related to this subject. The main forms of memory presented include sensory memory, short-term memory, and long-term memory. Information from the world around us is first stored by sensory memory, thus enabling the storage and future use of such information. Short-term memory (or memory) refers to information processed in a short period of time. Long-term memory allows us to store information for long periods of time, including information that can be retrieved consciously (explicit memory) or unconsciously (implicit memory).

The Neuroanatomical, Neurophysiological and Psychological Basis of Memory: Current Models and Their Origins

Directory of Open Access Journals (Sweden)

Eduardo Camina

2017-06-01

Full Text Available This review aims to classify and clarify, from a neuroanatomical, neurophysiological, and psychological perspective, different memory models that are currently widespread in the literature as well as to describe their origins. We believe it is important to consider previous developments without which one cannot adequately understand the kinds of models that are now current in the scientific literature. This article intends to provide a comprehensive and rigorous overview for understanding and ordering the latest scientific advances related to this subject. The main forms of memory presented include sensory memory, short-term memory, and long-term memory. Information from the world around us is first stored by sensory memory, thus enabling the storage and future use of such information. Short-term memory (or memory refers to information processed in a short period of time. Long-term memory allows us to store information for long periods of time, including information that can be retrieved consciously (explicit memory or unconsciously (implicit memory.

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

Science.gov (United States)

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

2014-02-01

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

The autism puzzle: Diffuse but not pervasive neuroanatomical abnormalities in children with ASD

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D. Sussman

2015-01-01

Full Text Available Autism Spectrum Disorder (ASD is a clinically diagnosed, heterogeneous, neurodevelopmental condition, whose underlying causes have yet to be fully determined. A variety of studies have investigated either cortical, subcortical, or cerebellar anatomy in ASD, but none have conducted a complete examination of all neuroanatomical parameters on a single, large cohort. The current study provides a comprehensive examination of brain development of children with ASD between the ages of 4 and 18 years who are carefully matched for age and sex with typically developing controls at a ratio of one-to-two. Two hundred and ten magnetic resonance images were examined from 138 Control (116 males and 22 females and 72 participants with ASD (61 males and 11 females. Cortical segmentation into 78 brain-regions and 81,924 vertices was conducted with CIVET which facilitated a region-of-interest- (ROI- and vertex-based analysis, respectively. Volumes for the cerebellum, hippocampus, striatum, pallidum, and thalamus and many associated subregions were derived using the MAGeT Brain algorithm. The study reveals cortical, subcortical and cerebellar differences between ASD and Control group participants. Diagnosis, diagnosis-by-age, and diagnosis-by-sex interaction effects were found to significantly impact total brain volume but not total surface area or mean cortical thickness of the ASD participants. Localized (vertex-based analysis of cortical thickness revealed no significant group differences, even when age, age-range, and sex were used as covariates. Nonetheless, the region-based cortical thickness analysis did reveal regional changes in the left orbitofrontal cortex and left posterior cingulate gyrus, both of which showed reduced age-related cortical thinning in ASD. Our finding of region-based differences without significant vertex-based results likely indicates non-focal effects spanning the entirety of these regions. The hippocampi, thalamus, and globus

Can Cognitive Neuroscience Ground a Science of Learning?

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Kelly, Anthony E.

2011-01-01

In this article, I review recent findings in cognitive neuroscience in learning, particularly in the learning of mathematics and of reading. I argue that while cognitive neuroscience is in its infancy as a field, theories of learning will need to incorporate and account for this growing body of empirical data.

Neuroanatomical heterogeneity of essential tremor according to propranolol response.

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Seok Jong Chung

Full Text Available BACKGROUND: Recent studies have suggested that essential tremor (ET is a more complex and heterogeneous clinical entity than initially thought. In the present study, we assessed the pattern of cortical thickness and diffusion tensor white matter (WM changes in patients with ET according to the response to propranolol to explore the pathogenesis underlying the clinical heterogeneity of ET. METHODS: A total of 32 patients with drug naive ET were recruited prospectively from the Movement Disorders outpatient clinic. The patients were divided into a propranolol-responder group (n = 18 and a non-responder group (n = 14. We analyzed the pattern of cortical thickness and diffusion tensor WM changes between these two groups and performed correlation analysis between imaging and clinical parameters. RESULTS: There were no significant differences in demographic characteristics, general cognition, or results of detailed neuropsychological tests between the groups. The non-responder group showed more severe cortical atrophy in the left orbitofrontal cortex and right temporal cortex relative to responders. However, the responders exhibited significantly lower fractional anisotropy values in the bilateral frontal, corpus callosal, and right parietotemporal WM compared with the non-responder group. There were no significant clusters where the cortical thickness or WM alterations were significantly correlated with initial tremor severity or disease duration. CONCLUSIONS: The present data suggest that patients with ET have heterogeneous cortical thinning and WM alteration with respect to responsiveness to propranolol, suggesting that propranolol responsiveness may be a predictive factor to determine ET subtypes in terms of neuroanatomical heterogeneity.

Towards an understanding of the attributes of simulation that enable learning in undergraduate nurse education: A grounded theory study.

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Bland, Andrew J; Tobbell, Jane

2016-09-01

Simulation has become an established feature of nurse education yet little is understood about the mechanisms that lead to learning. To explore the attributes of simulation-based education that enable student learning in undergraduate nurse education. Final year students drawn from one UK University (n=46) participated in a grounded theory study. First, nonparticipant observation and video recording of student activity was undertaken. Following initial analysis, recordings and observations were deconstructed during focus group interviews that enabled both the researcher and participants to unpack meaning. Lastly emergent findings were verified with final year students drawn from a second UK University (n=6). A staged approach to learning emerged from engagement in simulation. This began with initial hesitation as students moved through nonlinear stages to making connections and thinking like a nurse. Core findings suggest that simulation enables curiosity and intellect (main concern) through doing (core category) and interaction with others identified as social collaboration (category). This study offers a theoretical basis for understanding simulation-based education and integration of strategies that maximise the potential for learning. Additionally it offers direction for further research, particularly with regards to how the application of theory to practice is accelerated through learning by doing and working collaboratively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Embedding responses in spontaneous neural activity shaped through sequential learning.

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Tomoki Kurikawa

Full Text Available Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in

Improving buried threat detection in ground-penetrating radar with transfer learning and metadata analysis

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Colwell, Kenneth A.; Torrione, Peter A.; Morton, Kenneth D.; Collins, Leslie M.

2015-05-01

Ground-penetrating radar (GPR) technology has proven capable of detecting buried threats. The system relies on a binary classifier that is trained to distinguish between two classes: a target class, encompassing many types of buried threats and their components; and a nontarget class, which includes false alarms from the system prescreener. Typically, the training process involves a simple partition of the data into these two classes, which allows for straightforward application of standard classifiers. However, since training data is generally collected in fully controlled environments, it includes auxiliary information about each example, such as the specific type of threat, its purpose, its components, and its depth. Examples from the same specific or general type may be expected to exhibit similarities in their GPR data, whereas examples from different types may differ greatly. This research aims to leverage this additional information to improve overall classification performance by fusing classifier concepts for multiple groups, and to investigate whether structure in this information can be further utilized for transfer learning, such that the amount of expensive training data necessary to learn a new, previously-unseen target type may be reduced. Methods for accomplishing these goals are presented with results from a dataset containing a variety of target types.

Neuroanatomical correlates of time perspective: A voxel-based morphometry study.

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Chen, Zhiyi; Guo, Yiqun; Feng, Tingyong

2018-02-26

Previous studies indicated that time perspective can affect many behaviors, such as decisions, risk taking, substance abuse and health behaviors. However, very little is known about the neural substrates of time perspective (TP). To address this question, we characterized different dimensions of TP (including the Past, Present, and Future TP) using standardized Zimbardo Time Perspective Inventory (ZTPI), and quantified the gray matter volume using voxel-based morphometry (VBM) method across two independent samples. Our whole-brain analysis (sample 1, N=150) revealed Past-Negative TP was positively correlated with the GMV of a cluster in LPFC whereas Past-Positive was negatively correlated with the GMV in OFC, and Future TP was negatively correlated with GMV in mPFC. Moreover, two present scales (Present-Hedonistic and Present-Fatalistic TPs) were positively correlated with the GMV of regions in MTG and precuneus, respectively. We further examined the reliability of these correlations between multidimensional TPs and neuroanatomical structures in another independent sample (sample 2, N=58). Results verified our findings that GMV in LPFC could predict Past-Negative TP while GMV in OFC could predict Past-Positive TP, and the GMV in MTG could predict Present-Hedonistic while the GMV in presuneus could predict Present-Fatalistic, as well as the GMV in mPFC could predict Future TP. Thus, our findings suggest that the existence of selective neural basis underlying TPs, and further provide the stable biomarkers for multidimensional TPs. Copyright © 2017 Elsevier B.V. All rights reserved.

Binary Factorization in Hopfield-Like Neural Networks: Single-Step Approximation and Computer Simulations

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Sirota, A.M.; Húsek, Dušan; Muraviev, I. P.

2004-01-01

Roč. 14, č. 2 (2004), s. 139-152 ISSN 1210-0552 R&D Projects: GA ČR GA201/01/1192 Grant - others:BARRANDE(EU) 99010-2/99053; Intellectual computer Systems(EU) Grant 2.45 Institutional research plan: CEZ:AV0Z1030915 Keywords : nonlinear binary factor analysis * feature extraction * recurrent neural network * Single-Step approximation * neurodynamics simulation * attraction basins * Hebbian learning * unsupervised learning * neuroscience * brain function modeling Subject RIV: BA - General Mathematics

Modulation of Host Learning in Aedes aegypti Mosquitoes.

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Vinauger, Clément; Lahondère, Chloé; Wolff, Gabriella H; Locke, Lauren T; Liaw, Jessica E; Parrish, Jay Z; Akbari, Omar S; Dickinson, Michael H; Riffell, Jeffrey A

2018-02-05

How mosquitoes determine which individuals to bite has important epidemiological consequences. This choice is not random; most mosquitoes specialize in one or a few vertebrate host species, and some individuals in a host population are preferred over others. Mosquitoes will also blood feed from other hosts when their preferred is no longer abundant, but the mechanisms mediating these shifts between hosts, and preferences for certain individuals within a host species, remain unclear. Here, we show that olfactory learning may contribute to Aedes aegypti mosquito biting preferences and host shifts. Training and testing to scents of humans and other host species showed that mosquitoes can aversively learn the scent of specific humans and single odorants and learn to avoid the scent of rats (but not chickens). Using pharmacological interventions, RNAi, and CRISPR gene editing, we found that modification of the dopamine-1 receptor suppressed their learning abilities. We further show through combined electrophysiological and behavioral recordings from tethered flying mosquitoes that these odors evoke changes in both behavior and antennal lobe (AL) neuronal responses and that dopamine strongly modulates odor-evoked responses in AL neurons. Not only do these results provide direct experimental evidence that olfactory learning in mosquitoes can play an epidemiological role, but collectively, they also provide neuroanatomical and functional demonstration of the role of dopamine in mediating this learning-induced plasticity, for the first time in a disease vector insect. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unsupervised learning in neural networks with short range synapses

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

2013-01-01

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

The 'wayfinding' experience of family carers who learn to manage technical health procedures at home: a grounded theory study.

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McDonald, Janet; McKinlay, Eileen; Keeling, Sally; Levack, William

2017-12-01

With more care taking place in the home, family carers play an important role in supporting patients. Some family carers undertake technical health procedures generally managed by health professionals in hospital settings (e.g. managing a tracheostomy or enteral feeding). To explore how family carers learn to manage technical health procedures in order to help health professionals better understand and support this process. A grounded theory study using data from interviews with 26 New Zealand family carers who managed technical health procedures including nasogastric or gastrostomy feeding, stoma care, urinary catheterisation, tracheostomy management, intravenous therapy, diabetes management and complex wound dressings. Most (20 participants) were caring for their child and the remaining six for their spouse, parent or grandparent. Following grounded theory methods, each interview was coded soon after completion. Additional data were compared with existing material, and as analysis proceeded, initial codes were grouped into higher order concepts until a core concept was developed. Interviewing continued until no new ideas emerged and concepts were well defined. The core concept of 'wayfinding' indicates that the learning process for family carers is active, individualised and multi-influenced, developing over time as a response to lived experience. Health professional support was concentrated on the initial phase of carers' training, reducing and becoming more reactive as carers took responsibility for day-to-day management. Wayfinding involves self-navigation by carers, in contrast to patient navigator models which provide continuing professional assistance to patients receiving cancer or chronic care services. Wayfinding by carers raises questions about how carers should be best supported in their initial and ongoing learning as the management of these procedures changes over time. © 2017 Nordic College of Caring Science.

A Theory of How Columns in the Neocortex Enable Learning the Structure of the World

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Jeff Hawkins

2017-10-01

Full Text Available Neocortical regions are organized into columns and layers. Connections between layers run mostly perpendicular to the surface suggesting a columnar functional organization. Some layers have long-range excitatory lateral connections suggesting interactions between columns. Similar patterns of connectivity exist in all regions but their exact role remain a mystery. In this paper, we propose a network model composed of columns and layers that performs robust object learning and recognition. Each column integrates its changing input over time to learn complete predictive models of observed objects. Excitatory lateral connections across columns allow the network to more rapidly infer objects based on the partial knowledge of adjacent columns. Because columns integrate input over time and space, the network learns models of complex objects that extend well beyond the receptive field of individual cells. Our network model introduces a new feature to cortical columns. We propose that a representation of location relative to the object being sensed is calculated within the sub-granular layers of each column. The location signal is provided as an input to the network, where it is combined with sensory data. Our model contains two layers and one or more columns. Simulations show that using Hebbian-like learning rules small single-column networks can learn to recognize hundreds of objects, with each object containing tens of features. Multi-column networks recognize objects with significantly fewer movements of the sensory receptors. Given the ubiquity of columnar and laminar connectivity patterns throughout the neocortex, we propose that columns and regions have more powerful recognition and modeling capabilities than previously assumed.

Strong systematicity through sensorimotor conceptual grounding: an unsupervised, developmental approach to connectionist sentence processing

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Jansen, Peter A.; Watter, Scott

2012-03-01

Connectionist language modelling typically has difficulty with syntactic systematicity, or the ability to generalise language learning to untrained sentences. This work develops an unsupervised connectionist model of infant grammar learning. Following the semantic boostrapping hypothesis, the network distils word category using a developmentally plausible infant-scale database of grounded sensorimotor conceptual representations, as well as a biologically plausible semantic co-occurrence activation function. The network then uses this knowledge to acquire an early benchmark clausal grammar using correlational learning, and further acquires separate conceptual and grammatical category representations. The network displays strongly systematic behaviour indicative of the general acquisition of the combinatorial systematicity present in the grounded infant-scale language stream, outperforms previous contemporary models that contain primarily noun and verb word categories, and successfully generalises broadly to novel untrained sensorimotor grounded sentences composed of unfamiliar nouns and verbs. Limitations as well as implications to later grammar learning are discussed.

Group-focused morality is associated with limited conflict detection and resolution capacity: Neuroanatomical evidence.

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Nash, Kyle; Baumgartner, Thomas; Knoch, Daria

2017-02-01

Group-focused moral foundations (GMFs) - moral values that help protect the group's welfare - sharply divide conservatives from liberals and religiously devout from non-believers. However, there is little evidence about what drives this divide. Moral foundations theory and the model of motivated social cognition both associate group-focused moral foundations with differences in conflict detection and resolution capacity, but in opposing directions. Individual differences in conflict detection and resolution implicate specific neuroanatomical differences. Examining neuroanatomy thus affords an objective and non-biased opportunity to contrast these influential theories. Here, we report that increased adherence to group-focused moral foundations was strongly associated (whole-brain corrected) with reduced gray matter volume in key regions of the conflict detection and resolution system (anterior cingulate cortex and lateral prefrontal cortex). Because reduced gray matter is reliably associated with reduced neural and cognitive capacity, these findings support the idea outlined in the model of motivated social cognition that belief in group-focused moral values is associated with reduced conflict detection and resolution capacity. Copyright © 2017 Elsevier B.V. All rights reserved.

iPad Learning Ecosystem: Developing Challenge-Based Learning Using Design Thinking

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Marin, Catalina; Hargis, Jace; Cavanaugh, Cathy

2013-01-01

In order to maximize college English language students' learning, product development, 21st Century skills and engagement with real world meaningful challenges, a course was designed to integrate Challenge Based Learning (CBL) and iPad mobile learning technology. This article describes the course design, which was grounded in design thinking, and…

Artificial intelligence costs, benefits, risks for selected spacecraft ground system automation scenarios

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Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

1988-01-01

In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline), (2) standalone expert systems, (3) standardized, reusable knowledge base management systems (KBMS), and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

Development of Deep Learning Based Data Fusion Approach for Accurate Rainfall Estimation Using Ground Radar and Satellite Precipitation Products

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Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.

2016-12-01

Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is

Adventure Learning: Theory and Implementation of Hybrid Learning

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Doering, A.

2008-12-01

Adventure Learning (AL), a hybrid distance education approach, provides students and teachers with the opportunity to learn about authentic curricular content areas while interacting with adventurers, students, and content experts at various locations throughout the world within an online learning environment (Doering, 2006). An AL curriculum and online environment provides collaborative community spaces where traditional hierarchical classroom roles are blurred and learning is transformed. AL has most recently become popular in K-12 classrooms nationally and internationally with millions of students participating online. However, in the literature, the term "adventure learning" many times gets confused with phrases such as "virtual fieldtrip" and activities where someone "exploring" is posting photos and text. This type of "adventure learning" is not "Adventure Learning" (AL), but merely a slideshow of their activities. The learning environment may not have any curricular and/or social goals, and if it does, the environment design many times does not support these objectives. AL, on the other hand, is designed so that both teachers and students understand that their online and curriculum activities are in synch and supportive of the curricular goals. In AL environments, there are no disparate activities as the design considers the educational, social, and technological affordances (Kirschner, Strijbos, Kreijns, & Beers, 2004); in other words, the artifacts of the learning environment encourage and support the instructional goals, social interactions, collaborative efforts, and ultimately learning. AL is grounded in two major theoretical approaches to learning - experiential and inquiry-based learning. As Kolb (1984) noted, in experiential learning, a learner creates meaning from direct experiences and reflections. Such is the goal of AL within the classroom. Additionally, AL affords learners a real-time authentic online learning experience concurrently as they

From the Reality of Work to Grounded Work-Based Learning in German Vocational Education and Training: Background, Concept and Tools

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Michael Gessler

2015-12-01

Full Text Available The "Riga Conclusions" of the European Ministries of Education of 22 June 2015 for the orientation of vocational education and training in Europe are promoting work-based learning as one of five "medium-term deliverables" for the next five years. But: How should and can work-based teaching and learning be designed? Our approach was developed within the German Dual VET System. Therefore it is not surprising that the work reality is for us the major principle for designing curricula and learning settings. As a starting point for developing didactical measures in the field of vocational education and training it is crucial in this approach to identify practices, routines and experiences of skilled workers that are experts for what they are doing. What are those people doing when handling a task, how are they acting, what work objects and tools are they operating with, and what requirements do they have to be aware of? To answer these kinds of questions, the real work in practice must be explored. A useful approach for doing this is a vocational work process analysis. The next step comprises developing a workbased learning project for the classroom. These two steps, vocational work process analysis and work-based learning projects, build the core of the article and enable a grounded work-based learning. Additional the changing priorities of curriculum design in the last century are introduced to reach a better understanding of the background and the actual work-oriented focus in German Dual VET. Our key proposition is: If work-based learning in vocational schools is wanted, the gap between the reality of work and the formal learning settings has to be closed.

Pronounced prefronto-temporal cortical thinning in schizophrenia: Neuroanatomical correlate of suicidal behavior?

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Besteher, Bianca; Wagner, Gerd; Koch, Kathrin; Schachtzabel, Claudia; Reichenbach, Jürgen R; Schlösser, Ralf; Sauer, Heinrich; Schultz, C Christoph

2016-10-01

Schizophrenia is characterized by increased mortality for which suicidality is the decisive factor. An analysis of cortical thickness and folding to further elucidate neuroanatomical correlates of suicidality in schizophrenia has not yet been performed. We searched for relevant brain regions with such differences between patients with suicide-attempts, patients without any suicidal thoughts and healthy controls. 37 schizophrenia patients (14 suicide-attempters and 23 non-suicidal) and 50 age- and gender-matched healthy controls were included. Suicidality was documented through clinical interview and chart review. All participants underwent T1-weighted MRI scans. Whole brain node-by-node cortical thickness and folding were estimated (FreeSurfer Software) and compared. Additionally a three group comparison for prefrontal regions-of-interest was performed in SPSS using a multifactorial GLM. Compared with the healthy controls patients showed a typical pattern of cortical thinning in prefronto-temporal regions and altered cortical folding in the right medial temporal cortex. Patients with suicidal behavior compared with non-suicidal patients demonstrated pronounced (psuicidal patients with non-suicidal patients significant (psuicidal behaviour in schizophrenia. We identified cortical thinning in a network strongly involved in regulation of impulsivity, emotions and planning of behaviour in suicide attempters, which might lead to neuronal dysregulation in this network and consequently to a higher risk of suicidal behavior. Copyright © 2016 Elsevier B.V. All rights reserved.

Ciliates learn to diagnose and correct classical error syndromes in mating strategies.

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Clark, Kevin B

2013-01-01

Preconjugal ciliates learn classical repetition error-correction codes to safeguard mating messages and replies from corruption by "rivals" and local ambient noise. Because individual cells behave as memory channels with Szilárd engine attributes, these coding schemes also might be used to limit, diagnose, and correct mating-signal errors due to noisy intracellular information processing. The present study, therefore, assessed whether heterotrich ciliates effect fault-tolerant signal planning and execution by modifying engine performance, and consequently entropy content of codes, during mock cell-cell communication. Socially meaningful serial vibrations emitted from an ambiguous artificial source initiated ciliate behavioral signaling performances known to advertise mating fitness with varying courtship strategies. Microbes, employing calcium-dependent Hebbian-like decision making, learned to diagnose then correct error syndromes by recursively matching Boltzmann entropies between signal planning and execution stages via "power" or "refrigeration" cycles. All eight serial contraction and reversal strategies incurred errors in entropy magnitude by the execution stage of processing. Absolute errors, however, subtended expected threshold values for single bit-flip errors in three-bit replies, indicating coding schemes protected information content throughout signal production. Ciliate preparedness for vibrations selectively and significantly affected the magnitude and valence of Szilárd engine performance during modal and non-modal strategy corrective cycles. But entropy fidelity for all replies mainly improved across learning trials as refinements in engine efficiency. Fidelity neared maximum levels for only modal signals coded in resilient three-bit repetition error-correction sequences. Together, these findings demonstrate microbes can elevate survival/reproductive success by learning to implement classical fault-tolerant information processing in social

Ciliates learn to diagnose and correct classical error syndromes in mating strategies

Directory of Open Access Journals (Sweden)

Kevin Bradley Clark

2013-08-01

Full Text Available Preconjugal ciliates learn classical repetition error-correction codes to safeguard mating messages and replies from corruption by rivals and local ambient noise. Because individual cells behave as memory channels with Szilárd engine attributes, these coding schemes also might be used to limit, diagnose, and correct mating-signal errors due to noisy intracellular information processing. The present study, therefore, assessed whether heterotrich ciliates effect fault-tolerant signal planning and execution by modifying engine performance, and consequently entropy content of codes, during mock cell-cell communication. Socially meaningful serial vibrations emitted from an ambiguous artificial source initiated ciliate behavioral signaling performances known to advertise mating fitness with varying courtship strategies. Microbes, employing calcium-dependent Hebbian-like decision making, learned to diagnose then correct error syndromes by recursively matching Boltzmann entropies between signal planning and execution stages via power or refrigeration cycles. All eight serial contraction and reversal strategies incurred errors in entropy magnitude by the execution stage of processing. Absolute errors, however, subtended expected threshold values for single bit-flip errors in three-bit replies, indicating coding schemes protected information content throughout signal production. Ciliate preparedness for vibrations selectively and significantly affected the magnitude and valence of Szilárd engine performance during modal and nonmodal strategy corrective cycles. But entropy fidelity for all replies mainly improved across learning trials as refinements in engine efficiency. Fidelity neared maximum levels for only modal signals coded in resilient three-bit repetition error-correction sequences. Together, these findings demonstrate microbes can elevate survival/reproductive success by learning to implement classical fault-tolerant information processing in

Clustering autism: using neuroanatomical differences in 26 mouse models to gain insight into the heterogeneity.

Science.gov (United States)

Ellegood, J; Anagnostou, E; Babineau, B A; Crawley, J N; Lin, L; Genestine, M; DiCicco-Bloom, E; Lai, J K Y; Foster, J A; Peñagarikano, O; Geschwind, D H; Pacey, L K; Hampson, D R; Laliberté, C L; Mills, A A; Tam, E; Osborne, L R; Kouser, M; Espinosa-Becerra, F; Xuan, Z; Powell, C M; Raznahan, A; Robins, D M; Nakai, N; Nakatani, J; Takumi, T; van Eede, M C; Kerr, T M; Muller, C; Blakely, R D; Veenstra-VanderWeele, J; Henkelman, R M; Lerch, J P

2015-02-01

Autism is a heritable disorder, with over 250 associated genes identified to date, yet no single gene accounts for >1-2% of cases. The clinical presentation, behavioural symptoms, imaging and histopathology findings are strikingly heterogeneous. A more complete understanding of autism can be obtained by examining multiple genetic or behavioural mouse models of autism using magnetic resonance imaging (MRI)-based neuroanatomical phenotyping. Twenty-six different mouse models were examined and the consistently found abnormal brain regions across models were parieto-temporal lobe, cerebellar cortex, frontal lobe, hypothalamus and striatum. These models separated into three distinct clusters, two of which can be linked to the under and over-connectivity found in autism. These clusters also identified previously unknown connections between Nrxn1α, En2 and Fmr1; Nlgn3, BTBR and Slc6A4; and also between X monosomy and Mecp2. With no single treatment for autism found, clustering autism using neuroanatomy and identifying these strong connections may prove to be a crucial step in predicting treatment response.

Ventromedial prefrontal cortex damage does not impair the development and use of common ground in social interaction: implications for cognitive theory of mind.

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Gupta, Rupa; Tranel, Daniel; Duff, Melissa C

2012-01-01

During conversation, interactants draw on their shared communicative context and history ("common ground") to help decide what to say next, tailoring utterances based on their knowledge of what the listener knows. The use of common ground draws on an understanding of the thoughts and feelings of others to create and update a model of what is known by the other person, employing cognitive processes such as theory of mind. We tested the hypothesis that the ventromedial prefrontal cortex (vmPFC), a neural region involved in processing and interpreting social and emotional information, would be critical for the development and use of common ground. We studied seven patients with bilateral vmPFC damage and seven age-, sex-, and education-matched healthy comparison participants, each interacting with a familiar partner. Across 24 trials, participants verbally directed their partners how to arrange a set of 12 abstract tangram cards. Our hypothesis was not supported: the vmPFC and healthy comparison groups showed similar development and use of common ground, evident in reduction in time and words used to describe the cards, similar increases in the use of definite references (e.g., the horse), and comparable use of verbal play (playful language) in their interactions. These results argue against the idea that the vmPFC is critical for the development and use of common ground in social interaction. We propose that a cognitive and neuroanatomical bifurcation in theory of mind processes may explain this outcome. The vmPFC may be important for affective theory of mind (the ability to understand another's feelings); however, the development and use of common ground in social interaction may place higher demands on the ability to understand another's knowledge, or cognitive theory of mind, which may not require the vmPFC. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Neuroanatomical Basis for Posterior Superior Parietal Lobule Control Lateralization of visuospatial Attention

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Yan eWu

2016-03-01

Full Text Available The right hemispheric dominance in visuospatial attention in human brain has been well established. Converging evidence has documented that ventral posterior parietal cortex (PPC plays an important role in visuospatial attention. The role of dorsal PPC subregions, especially the superior parietal lobule (SPL in visuospatial attention is still controversial. In the current study, we used repetitive transcranial magnetic stimulation (rTMS and diffusion magnetic resonance imaging (MRI techniques to test the role of posterior SPL in visuospatial attention and to investigate the potential neuroanatomical basis for right hemisphere dominance in visuospatial function. TMS results unraveled that the right SPL predominantly mediated visuospatial attention compared to left SPL. Anatomical connections analyses between the posterior SPL and the intrahemispheric frontal subregions and the contralateral PPC revealed that right posterior SPL has stronger anatomical connections with the ipsilateral middle frontal gyrus, with the ipsilateral inferior frontal gyrus, and with contralateral PPC than that of the left posterior SPL. Furthermore, these asymmetric anatomical connections were closely related to behavioral performances. Our findings indicate that SPL plays a crucial role in regulating visuospatial attention, and dominance of visuospatial attention results from unbalanced interactions between the bilateral fronto-parietal networks and the interhemispheric parietal network.

Morvan's syndrome and the sustained absence of all sleep rhythms for months or years: An hypothesis.

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Touzet, Claude

2016-09-01

Despite the predation costs, sleep is ubiquitous in the animal realm. Humans spend a third of their life sleeping, and the quality of sleep has been related to co-morbidity, Alzheimer disease, etc. Excessive wakefulness induces rapid changes in cognitive performances, and it is claimed that one could die of sleep deprivation as quickly as by absence of water. In this context, the fact that a few people are able to go without sleep for months, even years, without displaying any cognitive troubles requires explanations. Theories ascribing sleep to memory consolidation are unable to explain such observations. It is not the case of the theory of sleep as the hebbian reinforcement of the inhibitory synapses (ToS-HRIS). Hebbian learning (Long Term Depression - LTD) guarantees that an efficient inhibitory synapse will lose its efficiency just because it is efficient at avoiding the activation of the post-synaptic neuron. This erosion of the inhibition is replenished by hebbian learning (Long Term Potentiation - LTP) when pre and post-synaptic neurons are active together - which is exactly what happens with the travelling depolarization waves of the slow-wave sleep (SWS). The best documented cases of months-long insomnia are reports of patients with Morvan's syndrome. This syndrome has an autoimmune cause that impedes - among many things - the potassium channels of the post-synaptic neurons, increasing LTP and decreasing LTD. We hypothesize that the absence of inhibitory efficiency erosion during wakefulness (thanks to a decrease of inhibitory LTD) is the cause for an absence of slow-wave sleep (SWS), which results also in the absence of REM sleep. Copyright © 2016 Elsevier Ltd. All rights reserved.

Stochastic correlative firing for figure-ground segregation.

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Chen, Zhe

2005-03-01

Segregation of sensory inputs into separate objects is a central aspect of perception and arises in all sensory modalities. The figure-ground segregation problem requires identifying an object of interest in a complex scene, in many cases given binaural auditory or binocular visual observations. The computations required for visual and auditory figure-ground segregation share many common features and can be cast within a unified framework. Sensory perception can be viewed as a problem of optimizing information transmission. Here we suggest a stochastic correlative firing mechanism and an associative learning rule for figure-ground segregation in several classic sensory perception tasks, including the cocktail party problem in binaural hearing, binocular fusion of stereo images, and Gestalt grouping in motion perception.

Artificial intelligence costs, benefits, and risks for selected spacecraft ground system automation scenarios

Science.gov (United States)

Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

1988-01-01

In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline); (2) standalone expert systems; (3) standardized, reusable knowledge base management systems (KBMS); and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

Games for learning

NARCIS (Netherlands)

Slussareff, Michaela; Braad, Eelco; Wilkinson, Philip; Strååt, Björn; Dörner, Ralf; Göbel, Stefan; Kickmeier-Rust, Michael; Masuch, Maic; Zweig, Katharina

This chapter discusses educational aspects and possibilities of serious games. For researchers as well as game designers we describe key learning theories to ground their work in theoretical framework. We draw on recent metareviews to offer an exhaustive inventory of known learning and affective

Integrative and Deep Learning through a Learning Community: A Process View of Self

Science.gov (United States)

Mahoney, Sandra; Schamber, Jon

2011-01-01

This study investigated deep learning produced in a community of general education courses. Student speeches on liberal education were analyzed for discovering a grounded theory of ideas about self. The study found that learning communities cultivate deep, integrative learning that makes the value of a liberal education relevant to students.…

Learning Mobility: Adaptive Control Algorithms for the Novel Unmanned Ground Vehicle (NUGV)

National Research Council Canada - National Science Library

Blackburn, Mike

2003-01-01

Mobility is a serious limiting factor in the usefulness of unmanned ground vehicles, This paper contains a description of our approach to develop control algorithms for the Novel Unmanned Ground Vehicle (NUGV...

How synapses can enhance sensibility of a neural network

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Protachevicz, P. R.; Borges, F. S.; Iarosz, K. C.; Caldas, I. L.; Baptista, M. S.; Viana, R. L.; Lameu, E. L.; Macau, E. E. N.; Batista, A. M.

2018-02-01

In this work, we study the dynamic range in a neural network modelled by cellular automaton. We consider deterministic and non-deterministic rules to simulate electrical and chemical synapses. Chemical synapses have an intrinsic time-delay and are susceptible to parameter variations guided by learning Hebbian rules of behaviour. The learning rules are related to neuroplasticity that describes change to the neural connections in the brain. Our results show that chemical synapses can abruptly enhance sensibility of the neural network, a manifestation that can become even more predominant if learning rules of evolution are applied to the chemical synapses.

Concurrent TMS to the primary motor cortex augments slow motor learning

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Narayana, Shalini; Zhang, Wei; Rogers, William; Strickland, Casey; Franklin, Crystal; Lancaster, Jack L.; Fox, Peter T.

2013-01-01

Transcranial magnetic stimulation (TMS) has shown promise as a treatment tool, with one FDA approved use. While TMS alone is able to up- (or down-) regulate a targeted neural system, we argue that TMS applied as an adjuvant is more effective for repetitive physical, behavioral and cognitive therapies, that is, therapies which are designed to alter the network properties of neural systems through Hebbian learning. We tested this hypothesis in the context of a slow motor learning paradigm. Healthy right-handed individuals were assigned to receive 5 Hz TMS (TMS group) or sham TMS (sham group) to the right primary motor cortex (M1) as they performed daily motor practice of a digit sequence task with their non-dominant hand for 4 weeks. Resting cerebral blood flow (CBF) was measured by H215O PET at baseline and after 4 weeks of practice. Sequence performance was measured daily as the number of correct sequences performed, and modeled using a hyperbolic function. Sequence performance increased significantly at 4 weeks relative to baseline in both groups. The TMS group had a significant additional improvement in performance, specifically, in the rate of skill acquisition. In both groups, an improvement in sequence timing and transfer of skills to non-trained motor domains was also found. Compared to the sham group, the TMS group demonstrated increases in resting CBF specifically in regions known to mediate skill learning namely, the M1, cingulate cortex, putamen, hippocampus, and cerebellum. These results indicate that TMS applied concomitantly augments behavioral effects of motor practice, with corresponding neural plasticity in motor sequence learning network. These findings are the first demonstration of the behavioral and neural enhancing effects of TMS on slow motor practice and have direct application in neurorehabilitation where TMS could be applied in conjunction with physical therapy. PMID:23867557

ATHENS SEASONAL VARIATION OF GROUND RESISTANCE PREDICTION USING NEURAL NETWORKS

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S. Anbazhagan

2015-10-01

Full Text Available The objective in ground resistance is to attain the most minimal ground safety esteem conceivable that bodes well monetarily and physically. An application of artificial neural networks (ANN to presage and relegation has been growing rapidly due to sundry unique characteristics of ANN models. A decent forecast is able to capture the dubiousness associated with those ground resistance. A portion of the key instabilities are soil composition, moisture content, temperature, ground electrodes and spacing of the electrodes. Propelled by this need, this paper endeavors to develop a generalized regression neural network (GRNN to predict the ground resistance. The GRNN has a single design parameter and expeditious learning and efficacious modeling for nonlinear time series. The precision of the forecast is applied to the Athens seasonal variation of ground resistance that shows the efficacy of the proposed approach.

Classroom Habit(us): Digital Learning Tools in a Blended Learning Program

DEFF Research Database (Denmark)

Borsotti, Valeria; Møllenbach, Emilie

2016-01-01

In this exploratory case study we map the educational practice of teachers and students in a professional master of Interaction Design. Through a grounded analysis of the context we describe and reflect on: 1) the use of digital learning tools in a blended learning environment, 2) co...

How learning might strengthen existing visual object representations in human object-selective cortex.

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Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

2016-02-15

Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

Extension and Higher Education Service-Learning: Toward a Community Development Service-Learning Model

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Stoecker, Randy

2014-01-01

This article explores how on-the-ground Extension educators interface with higher education service-learning. Most service-learning in Extension has focused on precollege youth and 4-H. When we look at higher education service-learning and Extension in Wisconsin, we see that there is not as much connection as might be expected. County-based…

A software system for evaluation and training of spatial reasoning and neuroanatomical knowledge in a virtual environment.

Science.gov (United States)

Armstrong, Ryan; de Ribaupierre, Sandrine; Eagleson, Roy

2014-04-01

This paper describes the design and development of a software tool for the evaluation and training of surgical residents using an interactive, immersive, virtual environment. Our objective was to develop a tool to evaluate user spatial reasoning skills and knowledge in a neuroanatomical context, as well as to augment their performance through interactivity. In the visualization, manually segmented anatomical surface images of MRI scans of the brain were rendered using a stereo display to improve depth cues. A magnetically tracked wand was used as a 3D input device for localization tasks within the brain. The movement of the wand was made to correspond to movement of a spherical cursor within the rendered scene, providing a reference for localization. Users can be tested on their ability to localize structures within the 3D scene, and their ability to place anatomical features at the appropriate locations within the rendering. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Eficacia de la utilización de estilos de aprendizaje en conjunto con mapas conceptuales y aprendizaje basado en la resolución de problemas para el aprendizaje de neuroanatomía Effectiveness of using learning styles in conjunction with conceptual maps based learning and problem solving for teaching neuroanatomy

Directory of Open Access Journals (Sweden)

J.O. Ayala-Pimentel

2009-03-01

Full Text Available Introducción. La utilización combinada de estilos de aprendizaje en conjunto con mapas conceptuales y el empleo de aprendizaje basado en la resolución de problemas (EMCRP es una nueva estrategia educativa. Objetivo. Evaluar la eficacia de la utilización del método EMCRP en la adquisición de aprendizaje significativo de neuroanatomía, comparado con el método usual de aprendizaje en estudiantes de fisioterapia, que cursaron la asignatura morfofisiología general en la Universidad Industrial de Santander (UIS entre los años 2004 y 2007. Sujetos y métodos. Se utilizó un diseño experimental con participantes aleatorizados asignados a dos grupos con una relación 1 a 1. En el grupo intervenido se empleó el método EMCRP y en el control el método tradicional de enseñanza. Después de un año se evaluó la adquisición de aprendizaje significativo para determinar el rendimiento del método EMCRP. Resultados. Se estudiaron 55 estudiantes. La edad media fue de 23 años y la razón mujer-hombre fue de 3 a 1. Al evaluar a los estudiantes después de un año de la intervención, 15 del grupo intervenido reprobaron el examen frente a 26 del grupo control (55 frente a 92%; p = 0,002. Se determinó una reducción del riesgo absoluto de 0,37 (intervalo de confianza al 95% = 0,16-0,56 y número necesario para tratar de 2,7 (intervalo de confianza al 95% = 1,7-6,3. Conclusión. La adquisición de un aprendizaje significativo fue mayor en el grupo intervenido, evidenciado por una menor proporción de suspendidos importante en comparación con el grupo control, con un número de estudiantes bajo a intervenir para que se produzcan resultados favorables.Introduction. The use of learning styles combined with concept maps and the use of learning based on the resolution of problems (LSCMLRP are a new educational strategy. Aim. To evaluate the effectiveness of the method LSCMLRP in the acquisition of significant learning of neuroanatomy, compared with the

Adding Theoretical Grounding to Grounded Theory: Toward Multi-Grounded Theory

OpenAIRE

Göran Goldkuhl; Stefan Cronholm

2010-01-01

The purpose of this paper is to challenge some of the cornerstones of the grounded theory approach and propose an extended and alternative approach for data analysis and theory development, which the authors call multi-grounded theory (MGT). A multi-grounded theory is not only empirically grounded; it is also grounded in other ways. Three different grounding processes are acknowledged: theoretical, empirical, and internal grounding. The authors go beyond the pure inductivist approach in GT an...

Behavioral and functional neuroanatomical correlates of anterograde autobiographical memory in isolated retrograde amnesic patient M.L.

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Levine, Brian; Svoboda, Eva; Turner, Gary R; Mandic, Marina; Mackey, Allison

2009-09-01

Patient M.L. [Levine, B., Black, S. E., Cabeza, R., Sinden, M., Mcintosh, A. R., Toth, J. P., et al. (1998). Episodic memory and the self in a case of isolated retrograde amnesia. Brain, 121, 1951-1973], lost memory for events occurring before his severe traumatic brain injury, yet his anterograde (post-injury) learning and memory appeared intact, a syndrome known as isolated or focal retrograde amnesia. Studies with M.L. demonstrated a dissociation between episodic and semantic memory. His retrograde amnesia was specific to episodic autobiographical memory. Convergent behavioral and functional imaging data suggested that his anterograde memory, while appearing normal, was accomplished with reduced autonoetic awareness (awareness of the self as a continuous entity across time that is a crucial element of episodic memory). While previous research on M.L. focused on anterograde memory of laboratory stimuli, in this study, M.L.'s autobiographical memory for post-injury events or anterograde autobiographical memory was examined using prospective collection of autobiographical events via audio diary with detailed behavioral and functional neuroanatomical analysis. Consistent with his reports of subjective disconnection from post-injury autobiographical events, M.L. assigned fewer "remember" ratings to his autobiographical events than comparison subjects. His generation of event-specific details using the Autobiographical Interview [Levine, B., Svoboda, E., Hay, J., Winocur, G., & Moscovitch, M. (2002). Aging and autobiographical memory: dissociating episodic from semantic retrieval. Psychology and Aging, 17, 677-689] was low, but not significantly so, suggesting that it is possible to generate episodic-like details even when re-experiencing of those details is compromised. While listening to the autobiographical audio diary segments, M.L. showed reduced activation relative to comparison subjects in midline frontal and posterior nodes previously identified as part of the

Age-related changes in sleep and circadian rhythms: impact on cognitive performance and underlying neuroanatomical networks

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Christina eSchmidt

2012-07-01

Full Text Available Circadian and homeostatic sleep-wake regulatory processes interact in a fine tuned manner to modulate human cognitive performance. Dampening of the circadian alertness signal and attenuated deterioration of psychomotor vigilance in response to elevated sleep pressure with aging change this interaction pattern. As evidenced by neuroimaging studies, both homeostatic sleep pressure and circadian sleep-wake promotion impact on cognition-related cortical and arousal-promoting subcortical brain regions including the thalamus, the anterior hypothalamus and the brainstem locus coeruleus (LC. However, how age- related changes in circadian and homeostatic processes impact on the cerebral activity subtending waking performance remains largely unexplored. Post-mortem studies point to neuronal degeneration in the SCN and age-related modifications to aging in the arousal-promoting LC. Alongside, cortical frontal brain areas are particularly susceptible both to aging and misalignment between circadian and homeostatic processes. In this perspective, we summarise and discuss here the potential neuroanatomical networks underlying age-related changes in circadian and homeostatic modulation of waking performance, ranging from basic arousal to higher order cognitive behaviours.

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

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Christian Albers

Full Text Available 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.

Science.gov (United States)

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.

Neuroticism related differences in the functional neuroanatomical correlates of multitasking. An fMRI study.

Science.gov (United States)

Szameitat, Andre J; Saylik, Rahmi; Parton, Andrew

2016-12-02

It is known that neuroticism impairs cognitive performance mostly in difficult tasks, but not so much in easier tasks. One pervasive situation of this type is multitasking, in which the combination of two simple tasks creates a highly demanding dual-task, and consequently high neurotics show higher dual-task costs than low neurotics. However, the functional neuroanatomical correlates of these additional performance impairments in high neurotics are unknown. To test for this, we assessed brain activity by means of functional magnetic resonance imaging (fMRI) in 17 low and 15 high neurotics while they were performing a demanding dual-task and the less demanding component tasks as single-tasks. Behavioural results showed that performance (response times and error rates) was lower in the dual-task than in the single-tasks (dual-task costs), and that these dual-task costs were significantly higher in high neurotics. Imaging data showed that high neurotics showed less dual-task specific activation in lateral (mainly middle frontal gyrus) and medial prefrontal cortices. We conclude that high levels of neuroticism impair behavioural performance in demanding tasks, and that this impairment is accompanied by reduced activation of the task-associated brain areas. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Sex-specific neuroanatomical correlates of fear expression in prefrontal-amygdala circuits.

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Gruene, Tina M; Roberts, Elian; Thomas, Virginia; Ronzio, Ashley; Shansky, Rebecca M

2015-08-01

The neural projections from the infralimbic region of the prefrontal cortex to the amygdala are important for the maintenance of conditioned fear extinction. Neurons in this pathway exhibit a unique pattern of structural plasticity that is sex-dependent, but the relationship between the morphologic characteristics of these neurons and successful extinction in male and female subjects is unknown. Using classic cued fear conditioning and an extinction paradigm in large cohorts of male and female rats, we identified subpopulations of both sexes that exhibited high (HF) or low (LF) levels of freezing on an extinction retrieval test, representing failed or successful extinction maintenance, respectively. We combined retrograde tracing with fluorescent intracellular microinjections to perform three-dimensional reconstructions of infralimbic neurons that project to the basolateral amygdala in these groups. The HF and LF male rats exhibited neuroanatomical distinctions that were not observed in HF or LF female rats. A retrospective analysis of behavior during fear conditioning and extinction revealed that despite no overall sex differences in freezing behavior, HF and LF phenotypes emerged in male rats during extinction and in female rats during fear conditioning, which does not involve infralimbic-basolateral amygdala neurons. Our results suggest that the neural processes underlying successful or failed extinction maintenance may be sex-specific. These findings are relevant not only to future basic research on sex differences in fear conditioning and extinction but also to exposure-based clinical therapies, which are similar in premise to fear extinction and which are primarily used to treat disorders that are more common in women than in men. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Organizing Blended Learning for Students on the Basis of Learning Roadmaps

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Andreeva, Nadezhda M.; Artyukhov, Ivan P.; Myagkova, Elena G.; Pak, Nikolay I.; Akkasynova, Zhamilya K.

2018-01-01

The relevance of the problem of organizing blended learning for students is related to the sharpening contradiction between the high potential of this educational technology and the poor methodological elaboration of its use in actual learning practice. With regard to this, the paper is aimed at providing grounds for the methodological system of…

The IXV Ground Segment design, implementation and operations

Science.gov (United States)

Martucci di Scarfizzi, Giovanni; Bellomo, Alessandro; Musso, Ivano; Bussi, Diego; Rabaioli, Massimo; Santoro, Gianfranco; Billig, Gerhard; Gallego Sanz, José María

2016-07-01

The Intermediate eXperimental Vehicle (IXV) is an ESA re-entry demonstrator that performed, on the 11th February of 2015, a successful re-entry demonstration mission. The project objectives were the design, development, manufacturing and on ground and in flight verification of an autonomous European lifting and aerodynamically controlled re-entry system. For the IXV mission a dedicated Ground Segment was provided. The main subsystems of the IXV Ground Segment were: IXV Mission Control Center (MCC), from where monitoring of the vehicle was performed, as well as support during pre-launch and recovery phases; IXV Ground Stations, used to cover IXV mission by receiving spacecraft telemetry and forwarding it toward the MCC; the IXV Communication Network, deployed to support the operations of the IXV mission by interconnecting all remote sites with MCC, supporting data, voice and video exchange. This paper describes the concept, architecture, development, implementation and operations of the ESA Intermediate Experimental Vehicle (IXV) Ground Segment and outlines the main operations and lessons learned during the preparation and successful execution of the IXV Mission.

Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity.

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Sadra Sadeh

2015-06-01

Full Text Available In rodent visual cortex, synaptic connections between orientation-selective neurons are unspecific at the time of eye opening, and become to some degree functionally specific only later during development. An explanation for this two-stage process was proposed in terms of Hebbian plasticity based on visual experience that would eventually enhance connections between neurons with similar response features. For this to work, however, two conditions must be satisfied: First, orientation selective neuronal responses must exist before specific recurrent synaptic connections can be established. Second, Hebbian learning must be compatible with the recurrent network dynamics contributing to orientation selectivity, and the resulting specific connectivity must remain stable for unspecific background activity. Previous studies have mainly focused on very simple models, where the receptive fields of neurons were essentially determined by feedforward mechanisms, and where the recurrent network was small, lacking the complex recurrent dynamics of large-scale networks of excitatory and inhibitory neurons. Here we studied the emergence of functionally specific connectivity in large-scale recurrent networks with synaptic plasticity. Our results show that balanced random networks, which already exhibit highly selective responses at eye opening, can develop feature-specific connectivity if appropriate rules of synaptic plasticity are invoked within and between excitatory and inhibitory populations. If these conditions are met, the initial orientation selectivity guides the process of Hebbian learning and, as a result, functionally specific and a surplus of bidirectional connections emerge. Our results thus demonstrate the cooperation of synaptic plasticity and recurrent dynamics in large-scale functional networks with realistic receptive fields, highlight the role of inhibition as a critical element in this process, and paves the road for further computational

Radical-Local Teaching and Learning

DEFF Research Database (Denmark)

Hedegaard, Mariane; Chaiklin, Seth

Radical-Local Teaching and Learning presents a theoretical perspective for analyzing and planning educational programmes for schoolchildren. To realize both general societal interests and worthwhile personal development, the content of educational programmes for children must be grounded in the l......Radical-Local Teaching and Learning presents a theoretical perspective for analyzing and planning educational programmes for schoolchildren. To realize both general societal interests and worthwhile personal development, the content of educational programmes for children must be grounded...... radical-local teaching and learning approach. The first half of the book introduces the idea of radical-local teaching and learning and develops the theoretical background for this perspective, drawing on the cultural-historical research tradition, particularly from Vygotsky, El'konin, Davydov......, and Aidarova. The second half of the book addresses the central concern of radical-local teaching and learning - how to relate educational practices to children's specific historical and cultural conditions. The experiment was conducted for an academic year in an afterschool programme in the East Harlem...

A Computational Agent Model for Hebbian Learning of Social Interaction

NARCIS (Netherlands)

Treur, J.

2011-01-01

In social interaction between two persons usually a person displays understanding of the other person. This may involve both nonverbal and verbal elements, such as bodily expressing a similar emotion and verbally expressing beliefs about the other person. Such social interaction relates to an

The Credentials of Brain-Based Learning

Science.gov (United States)

Davis, Andrew

2004-01-01

This paper discusses the current fashion for brain-based learning, in which value-laden claims about learning are grounded in neurophysiology. It argues that brain science cannot have the authority about learning that some seek to give it. It goes on to discuss whether the claim that brain science is relevant to learning involves a category…

The Use of Hebbian Cell Assemblies for Nonlinear Computation

DEFF Research Database (Denmark)

Tetzlaff, Christian; Dasgupta, Sakyasingha; Kulvicius, Tomas

2015-01-01

When learning a complex task our nervous system self-organizes large groups of neurons into coherent dynamic activity patterns. During this, a network with multiple, simultaneously active, and computationally powerful cell assemblies is created. How such ordered structures are formed while preser...... computing complex non-linear transforms and - for execution - must cooperate with each other without interference. This mechanism, thus, permits the self-organization of computationally powerful sub-structures in dynamic networks for behavior control....

Ground engineering principles and practices for underground coal mining

CERN Document Server

Galvin, J M

2016-01-01

This book teaches readers ground engineering principles and related mining and risk management practices associated with underground coal mining. It establishes the basic elements of risk management and the fundamental principles of ground behaviour and then applies these to the essential building blocks of any underground coal mining system, comprising excavations, pillars, and interactions between workings. Readers will also learn about types of ground support and reinforcement systems and their operating mechanisms. These elements provide the platform whereby the principles can be applied to mining practice and risk management, directed primarily to bord and pillar mining, pillar extraction, longwall mining, sub-surface and surface subsidence, and operational hazards. The text concludes by presenting the framework of risk-based ground control management systems for achieving safe workplaces and efficient mining operations. In addition, a comprehensive reference list provides additional sources of informati...

Comparison of Seven Methods for Boolean Factor Analysis and Their Evaluation by Information Gain

Czech Academy of Sciences Publication Activity Database

Frolov, A.; Húsek, Dušan; Polyakov, P.Y.

2016-01-01

Roč. 27, č. 3 (2016), s. 538-550 ISSN 2162-237X R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:67985807 Keywords : associative memory * bars problem (BP) * Boolean factor analysis (BFA) * data mining * dimension reduction * Hebbian learning rule * information gain * likelihood maximization (LM) * neural network application * recurrent neural network * statistics Subject RIV: IN - Informatics, Computer Science Impact factor: 6.108, year: 2016

Postmortem changes in the neuroanatomical characteristics of the primate brain: hippocampal formation.

Science.gov (United States)

Lavenex, Pierre; Lavenex, Pamela Banta; Bennett, Jeffrey L; Amaral, David G

2009-01-01

Comparative studies of the structural organization of the brain are fundamental to our understanding of human brain function. However, whereas brains of experimental animals are fixed by perfusion of a fixative through the vasculature, human or ape brains are fixed by immersion after varying postmortem intervals. Although differential treatments might affect the fundamental characteristics of the tissue, this question has not been evaluated empirically in primate brains. Monkey brains were either perfused or acquired after varying postmortem intervals before immersion-fixation in 4% paraformaldehyde. We found that the fixation method affected the neuroanatomical characteristics of the monkey hippocampal formation. Soma size was smaller in Nissl-stained, immersion-fixed tissue, although overall brain volume was larger as compared to perfusion-fixed tissue. Nonphosphorylated high-molecular-weight neurofilament immunoreactivity was lower in CA3 pyramidal neurons, dentate mossy cells, and the entorhinal cortex, whereas it was higher in the mossy fiber pathway in immersion-fixed tissue. Serotonin-immunoreactive fibers were well stained in perfused tissue but were undetectable in immersion-fixed tissue. Although regional immunoreactivity patterns for calcium-binding proteins were not affected, intracellular staining degraded with increasing postmortem intervals. Somatostatin-immunoreactive clusters of large axonal varicosities, previously reported only in humans, were observed in immersion-fixed monkey tissue. In addition, calretinin-immunoreactive multipolar neurons, previously observed only in rodents, were found in the rostral dentate gyrus in both perfused and immersion-fixed brains. In conclusion, comparative studies of the brain must evaluate the effects of fixation on the staining pattern of each marker in every structure of interest before drawing conclusions about species differences.

The parametric, psychological, neuropsychological, and neuroanatomical properties of self and world evaluation.

Science.gov (United States)

Simmons, Alan N; Thayer, Rachel E; Spadoni, Andrea D; Matthews, Scott C; Strigo, Irina A; Tapert, Susan F

2012-01-01

As an individual moves from adolescence to adulthood, they need to form a new sense of self as their environment changes from a limited to a more expansive structure. During this critical stage in development the last dramatic steps of neural development occur and numerous psychiatric conditions begin to manifest. Currently, there is no measure that aids in the quantification of how the individual is adapting to, and conceptualizing their role in, these new structures. To fill this gap we created the Self and World Evaluation Expressions Test(SWEET). Sixty-five young adults (20.6 years-old), 36 with a history of drug use, completed the SWEET. A factor analysis was performed on the SWEET and the resultant factors were correlated with psychological, neuropsychological, and neuroanatomical battery that included both T1-wieghted and diffusion tensor magnetic resonance imaging scans. WE DERIVED FOUR FACTORS: Self, Social-Emotional, Financial-Intellectual, and Spirituality. While showing limited relationships to psychological and neuropsychological measures, both white matter integrity and gray matter density showed significant relationships with SWEET factors. These findings suggest that while individual responses may not be indicative of psychological or cognitive processes they may relate to changes in brain structure. Several of these structures, such as the negative correlation of the affective impact of world with the dorsal anterior corpus callosum white matter integrity have been observed in psychiatric conditions (e.g., obsessive-compulsive disorder). Further longitudinal research using the SWEET may help understand the impact of dramatic shifts in self/world conceptualization and potentially link these shifts to underlying changes in brain structure.

Model-Based Knowing: How Do Students Ground Their Understanding About Climate Systems in Agent-Based Computer Models?

Science.gov (United States)

Markauskaite, Lina; Kelly, Nick; Jacobson, Michael J.

2017-12-01

This paper gives a grounded cognition account of model-based learning of complex scientific knowledge related to socio-scientific issues, such as climate change. It draws on the results from a study of high school students learning about the carbon cycle through computational agent-based models and investigates two questions: First, how do students ground their understanding about the phenomenon when they learn and solve problems with computer models? Second, what are common sources of mistakes in students' reasoning with computer models? Results show that students ground their understanding in computer models in five ways: direct observation, straight abstraction, generalisation, conceptualisation, and extension. Students also incorporate into their reasoning their knowledge and experiences that extend beyond phenomena represented in the models, such as attitudes about unsustainable carbon emission rates, human agency, external events, and the nature of computational models. The most common difficulties of the students relate to seeing the modelled scientific phenomenon and connecting results from the observations with other experiences and understandings about the phenomenon in the outside world. An important contribution of this study is the constructed coding scheme for establishing different ways of grounding, which helps to understand some challenges that students encounter when they learn about complex phenomena with agent-based computer models.

Pedagogical quality in e-learning

DEFF Research Database (Denmark)

Dalsgaard, Christian

2005-01-01

The article is concerned with design and use of e-learning technology to develop education qualitatively. The purpose is to develop a framework for a pedagogical evaluation of e-learning technology. The approach is that evaluation and design must be grounded in a learning theoretical approach....... Finally, on the basis of the frameworks, the article discusses e-learning technology and, more specifically, design of virtual learning environments and learning objects. It is argued that e-learning technology is not pedagogically neutral, and that it is therefore necessary to focus on design...

Effective Strategies for Sustaining Professional Learning Communities

Science.gov (United States)

Bennett, Patricia R.

2010-01-01

Professional Learning Communities (PLCs), in which educators work collaboratively to improve learning for students, need effective strategies to sustain them. PLCs promote continuous improvement in student learning and build academic success with increased teacher expertise. Grounded in organizational systems theory, participative leadership…

Psychology for the Classroom: E-Learning

Science.gov (United States)

Woollard, John

2011-01-01

"Psychology for the Classroom: E-Learning" is a lively and accessible introduction to the field of technology-supported teaching and learning and the educational psychology associated with those developments. Offering a substantial and useful analysis of e-learning, this practical book includes current research, offers a grounding in both theory…

Teachers’ Learning Design Practice for Students as Learning Designers

DEFF Research Database (Denmark)

Levinsen, Karin Tweddell; Sørensen, Birgitte Holm

2018-01-01

This paper contributes with elements of an emerging learning design methodology. The paper takes as its starting point the theory of Students as Learning Designers, which was developed by Sørensen and Levinsen and based on more than a decade of research-and-development projects in Danish primary...... schools (first to 10th grade). The research focussed on information and communication technology (ICT) within the Scandinavian tradition of Problem Oriented Project Pedagogy (POPP), Problem Based Learning (PBL) and students’ production. In recent years, the projects that provide the grounding...... for the theory have focussed specifically on learning designs that constitute students as learning designers of digital productions (both multimodal and coded productions). This includes learning designs that contribute to students’ empowerment, involvement and autonomy within the teacher-designed frameworks...

Analysis of Learning Tools in the study of Developmental of Interactive Multimedia Based Physic Learning Charged in Problem Solving

Science.gov (United States)

Manurung, Sondang; Demonta Pangabean, Deo

2017-05-01

The main purpose of this study is to produce needs analysis, literature review, and learning tools in the study of developmental of interactive multimedia based physic learning charged in problem solving to improve thinking ability of physic prospective student. The first-year result of the study is: result of the draft based on a needs analysis of the facts on the ground, the conditions of existing learning and literature studies. Following the design of devices and instruments performed as well the development of media. Result of the second study is physics learning device -based interactive multimedia charged problem solving in the form of textbooks and scientific publications. Previous learning models tested in a limited sample, then in the evaluation and repair. Besides, the product of research has an economic value on the grounds: (1) a virtual laboratory to offer this research provides a solution purchases physics laboratory equipment is expensive; (2) address the shortage of teachers of physics in remote areas as a learning tool can be accessed offline and online; (3). reducing material or consumables as tutorials can be done online; Targeted research is the first year: i.e story board learning physics that have been scanned in a web form CD (compact disk) and the interactive multimedia of gas Kinetic Theory concept. This draft is based on a needs analysis of the facts on the ground, the existing learning conditions, and literature studies. Previous learning models tested in a limited sample, then in the evaluation and repair.

Distance learning, problem based learning and dynamic knowledge networks.

Science.gov (United States)

Giani, U; Martone, P

1998-06-01

This paper is an attempt to develop a distance learning model grounded upon a strict integration of problem based learning (PBL), dynamic knowledge networks (DKN) and web tools, such as hypermedia documents, synchronous and asynchronous communication facilities, etc. The main objective is to develop a theory of distance learning based upon the idea that learning is a highly dynamic cognitive process aimed at connecting different concepts in a network of mutually supporting concepts. Moreover, this process is supposed to be the result of a social interaction that has to be facilitated by the web. The model was tested by creating a virtual classroom of medical and nursing students and activating a learning session on the concept of knowledge representation in health sciences.

Motivation and Engagement in Authorship Learning

Science.gov (United States)

Donaldson, Jonan Phillip; Bucy, Mary

2016-01-01

Constructionist principles provide fertile ground for developing innovative approaches to learning. Using a grounded theory qualitative research design, we analyzed participant reports of their experience in an online course in which they collaboratively authored a book. Our qualitative analysis suggested that participants experienced…

A qualitative study of middle school students' perceptions of factors facilitating the learning of science: Grounded theory and existing theory

Science.gov (United States)

Spector, Barbara S.; Gibson, Charles W.

The purpose of this study was to explore middle school students' perceptions of what factors facilitated their learning of science. Florida's Educational Reform Act of 1983 funded programs providing the state's precollege students with summer learning opportunities in science. mathematics, and computers. The programs were intended to encourage the development of creative approaches to the teaching of these disciplines. Under this program, between 50 and 60 high-achieving middle school students were in residence on the University of South Florida campus for 12 consecutive days of study in the World of Water (WOW) program. There were two sessions per summer involving a total of 572 participants. Eighi specially trained teachers were in residence with the students. Between 50 and 70 experts from the university, government. business, and industry interacted with the students each year in an innovative science/technology/society (STS) program. An assignment toward the close of the program asked students to reflect on their experiences in residence at the university and write an essay comparing learning in the WOW program to learning in their schools. Those essays were the base for this study. This was a qualitative study using a discursive approach to emergent design to generate grounded theory. Document review, participant observation, and open-ended interviews were used to gather and triangulate data in five phases. Some of the factors that middle school students perceived as helpful to learning science were (a) experiencing the situations about which they were learning; (b) having live presentations by professional experts; (c) doing hands-on activities: (d) being active learners; (e) using inductive reasoning to generate new knowledge; (f) exploring transdisciplinary approaches to problem solving; (g) having adult mentors; (h) interacting with peers and adults; (i) establishing networks; (j) having close personal friends who shared their interest in learning; (k

Functional Neuroanatomical Correlates of The Frontal Assessment Battery Performance in Alzheimer Disease: A FDG-PET Study.

Science.gov (United States)

Lee, Jun Ho; Byun, Min Soo; Sohn, Bo Kyung; Choe, Young Min; Yi, Dahyun; Han, Ji Young; Choi, Hyo Jung; Baek, Hyewon; Woo, Jong Inn; Lee, Dong Young

2015-09-01

We aimed to elucidate the functional neuroanatomical correlates of Frontal Assessment Battery (FAB) performances by applying [(18)F]fluorodeoxyglucose positron emission tomography (FDG-PET) to a large population of patients with Alzheimer disease (AD). The FAB was administered to 177 patients with AD, and regional cerebral glucose metabolism (rCMglc) was measured by FDG-PET scan. Correlations between FAB scores and rCMglc were explored using both region-of-interest-based (ROI-based) and voxel-based approaches. The ROI-based analysis showed that FAB scores correlated with the rCMglc of the dorsolateral prefrontal cortices. Voxel-based approach revealed significant positive correlations between FAB scores and rCMglc which were in various cortical regions including the temporal and parietal cortices as well as frontal regions, independent of age, gender, and education. After controlling the effect of global disease severity with Mini-Mental State Examination score, significant positive correlation was found only in the bilateral prefrontal regions. Although FAB scores are influenced by temporoparietal dysfunction due to the overall progression of AD, it likely reflects prefrontal dysfunction specifically regardless of global cognitive state or disease severity in patients with AD. © The Author(s) 2015.

Neuroanatomical Alterations in Patients with Early Stage of Unilateral Pulsatile Tinnitus: A Voxel-Based Morphometry Study

Directory of Open Access Journals (Sweden)

Yawen Liu

2018-01-01

Full Text Available During the past several years, the rapid development of neuroimaging techniques has contributed greatly in the noninvasive imaging studies of tinnitus. The aim of the present study was to explore the brain anatomical alterations in patients with right-sided unilateral pulsatile tinnitus (PT in the early stage of PT symptom using voxel-based morphometry (VBM analysis. Twenty-four patients with right-sided pulsatile tinnitus and 24 age- and gender-matched normal controls were recruited to this study. Structural image data preprocessing was performed using VBM8 toolbox. Tinnitus Handicap Inventory (THI score was acquired in the tinnitus group to assess the severity of tinnitus and tinnitus-related distress. Two-sample t-test and Pearson’s correlation analysis were used in statistical analysis. Patients with unilateral pulsatile tinnitus had significantly increased gray matter (GM volume in bilateral superior temporal gyrus compared with the normal controls. However, the left cerebellum posterior lobe, left frontal superior orbital lobe (gyrus rectus, right middle occipital gyrus (MOG, and bilateral putamen showed significantly decreased brain volumes. This was the first study which demonstrated the features of neuroanatomical changes in patients with unilateral PT during their early stages of the symptom.

Grounding line processes on the Totten Glacier

Science.gov (United States)

Cook, S.; Watson, C. S.; Galton-Fenzi, B.; Peters, L. E.; Coleman, R.

2017-12-01

The Totten Glacier has been an area of recent interest due to its large drainage basin, much of which is grounded below sea level and has a history of large scale grounding line movement. Reports that warm water reaches the sub-ice shelf cavity have led to speculation that it could be vulnerable to future grounding line retreat. Over the Antarctic summer 2016/17 an array of 6 GPS and autonomous phase-sensitive radar (ApRES) units were deployed in the grounding zone of the Totten Glacier. These instruments measure changes in ice velocity and thickness which can be used to investigate both ice dynamics across the grounding line, and the interaction between ice and ocean in the subglacial cavity. Basal melt rates calculated from the ApRES units on floating ice range from 1 to 17 m/a. These values are significantly lower than previous estimates of basal melt rate produced by ocean modelling of the subglacial cavity. Meanwhile, GPS-derived velocity and elevation on the surface of the ice show a strong tidal signal, as does the vertical strain rate within the ice derived from internal layering from the ApRES instruments. These results demonstrate the significance of the complex grounding pattern of the Totten Glacier. The presence of re-grounding points has significant implications for the dynamics of the glacier and the ocean circulation within the subglacial cavity. We discuss what can be learned from our in situ measurements, and how they can be used to improve models of the glacier's future behaviour.

Of mice, birds, and men: the mouse ultrasonic song system has some features similar to humans and song-learning birds.

Directory of Open Access Journals (Sweden)

Gustavo Arriaga

Full Text Available Humans and song-learning birds communicate acoustically using learned vocalizations. The characteristic features of this social communication behavior include vocal control by forebrain motor areas, a direct cortical projection to brainstem vocal motor neurons, and dependence on auditory feedback to develop and maintain learned vocalizations. These features have so far not been found in closely related primate and avian species that do not learn vocalizations. Male mice produce courtship ultrasonic vocalizations with acoustic features similar to songs of song-learning birds. However, it is assumed that mice lack a forebrain system for vocal modification and that their ultrasonic vocalizations are innate. Here we investigated the mouse song system and discovered that it includes a motor cortex region active during singing, that projects directly to brainstem vocal motor neurons and is necessary for keeping song more stereotyped and on pitch. We also discovered that male mice depend on auditory feedback to maintain some ultrasonic song features, and that sub-strains with differences in their songs can match each other's pitch when cross-housed under competitive social conditions. We conclude that male mice have some limited vocal modification abilities with at least some neuroanatomical features thought to be unique to humans and song-learning birds. To explain our findings, we propose a continuum hypothesis of vocal learning.

Behavioural and neuroanatomical correlates of auditory speech analysis in primary progressive aphasias.

Science.gov (United States)

Hardy, Chris J D; Agustus, Jennifer L; Marshall, Charles R; Clark, Camilla N; Russell, Lucy L; Bond, Rebecca L; Brotherhood, Emilie V; Thomas, David L; Crutch, Sebastian J; Rohrer, Jonathan D; Warren, Jason D

2017-07-27

Non-verbal auditory impairment is increasingly recognised in the primary progressive aphasias (PPAs) but its relationship to speech processing and brain substrates has not been defined. Here we addressed these issues in patients representing the non-fluent variant (nfvPPA) and semantic variant (svPPA) syndromes of PPA. We studied 19 patients with PPA in relation to 19 healthy older individuals. We manipulated three key auditory parameters-temporal regularity, phonemic spectral structure and prosodic predictability (an index of fundamental information content, or entropy)-in sequences of spoken syllables. The ability of participants to process these parameters was assessed using two-alternative, forced-choice tasks and neuroanatomical associations of task performance were assessed using voxel-based morphometry of patients' brain magnetic resonance images. Relative to healthy controls, both the nfvPPA and svPPA groups had impaired processing of phonemic spectral structure and signal predictability while the nfvPPA group additionally had impaired processing of temporal regularity in speech signals. Task performance correlated with standard disease severity and neurolinguistic measures. Across the patient cohort, performance on the temporal regularity task was associated with grey matter in the left supplementary motor area and right caudate, performance on the phoneme processing task was associated with grey matter in the left supramarginal gyrus, and performance on the prosodic predictability task was associated with grey matter in the right putamen. Our findings suggest that PPA syndromes may be underpinned by more generic deficits of auditory signal analysis, with a distributed cortico-subcortical neuraoanatomical substrate extending beyond the canonical language network. This has implications for syndrome classification and biomarker development.

Online unsupervised formation of cell assemblies for the encoding of multiple cognitive maps.

Science.gov (United States)

Salihoglu, Utku; Bersini, Hugues; Yamaguchi, Yoko; Molter, Colin

2009-01-01

Since their introduction sixty years ago, cell assemblies have proved to be a powerful paradigm for brain information processing. After their introduction in artificial intelligence, cell assemblies became commonly used in computational neuroscience as a neural substrate for content addressable memories. However, the mechanisms underlying their formation are poorly understood and, so far, there is no biologically plausible algorithms which can explain how external stimuli can be online stored in cell assemblies. We addressed this question in a previous paper [Salihoglu, U., Bersini, H., Yamaguchi, Y., Molter, C., (2009). A model for the cognitive map formation: Application of the retroaxonal theory. In Proc. IEEE international joint conference on neural networks], were, based on biologically plausible mechanisms, a novel unsupervised algorithm for online cell assemblies' creation was developed. The procedure involved simultaneously, a fast Hebbian/anti-Hebbian learning of the network's recurrent connections for the creation of new cell assemblies, and a slower feedback signal which stabilized the cell assemblies by learning the feedforward input connections. Here, we first quantify the role played by the retroaxonal feedback mechanism. Then, we show how multiple cognitive maps, composed by a set of orthogonal input stimuli, can be encoded in the network. As a result, when facing a previously learned input, the system is able to retrieve the cognitive map it belongs to. As a consequence, ambiguous inputs which could belong to multiple cognitive maps can be disambiguated by the knowledge of the context, i.e. the cognitive map.

Teachers’ Learning Design Practice for Students as Learning Designers

DEFF Research Database (Denmark)

Levinsen, Karin Tweddell; Sørensen, Birgitte Holm

2018-01-01

schools (first to 10th grade). The research focussed on information and communication technology (ICT) within the Scandinavian tradition of Problem Oriented Project Pedagogy (POPP), Problem Based Learning (PBL) and students’ production. In recent years, the projects that provide the grounding...

Learning from nuclear waste repository design: the ground-control plan

International Nuclear Information System (INIS)

Schmidt, B.

1988-01-01

At present, under a U.S. Department of Energy program, three repositories for commercial spent fuel-in salt, tuff and basalt-are in the phase of site characterization and conceptual design, and one pilot project for defense waste in salt is under development. Because of strict quality assurance requirements throughout design and construction, and the need to predict and ascertain in advance the satisfactory performance of the underground openings, underground openings in the unusual circumstances of the repository environment have been analysed. This will lead to an improved understanding of rock behavior and improved methods of underground analysis and design. A formalized ground control plan was developed, the principles of which may be applied to other types of projects. This paper summarizes the status of underground design and construction for nuclear waste repositories and presents some details of the ground control plan and its individual elements. (author)

Teachers’ Learning Design Practice for Students as Learning Designers

DEFF Research Database (Denmark)

Levinsen, Karin Tweddell; Sørensen, Birgitte Holm

2018-01-01

that simultaneously scaffold students’ subject-related inquiry, agency, reflection and learning. Research studies have documented that this approach constitutes arenas that support students’ deep learning and mastery of both transdisciplinary and subject matter, along with their acquisition of digital literacy and 21......This paper contributes with elements of an emerging learning design methodology. The paper takes as its starting point the theory of Students as Learning Designers, which was developed by Sørensen and Levinsen and based on more than a decade of research-and-development projects in Danish primary...... schools (first to 10th grade). The research focussed on information and communication technology (ICT) within the Scandinavian tradition of Problem Oriented Project Pedagogy (POPP), Problem Based Learning (PBL) and students’ production. In recent years, the projects that provide the grounding...

Reflections from Graduate Adult Learners about Service Learning

Science.gov (United States)

Alston, Geleana Drew; Clegg, T. E.; Clodfelter, Roy J., Jr.; Drye, Kimberly C.; Farrer, J. V.; Gould, Derek; Mohsin, Nidhal M.; Rankin, Tomiko N.; Ray, Sherri L.

2016-01-01

Adult education is grounded in responding to the needs of others, and the field places emphasis on adult learning theories such as transformative learning and experiential learning. Service learning is an educational approach that balances formal instruction and direction with the opportunity for adult learners to serve in the community as a…

Beyond Assessment: Conducting Theoretically Grounded Research on Service-Learning in Gerontology Courses.

Science.gov (United States)

Kruger, Tina M; Pearl, Andrew J

2016-01-01

Service-learning is a useful pedagogical tool and high-impact practice, providing multiple benefits. Gerontology (and other) courses frequently include service-learning activities but lack theory-based, intentional research on outcomes. Here, the authors define service-learning and contextualize it in higher education, provide an overview of research and assessment in service-learning and gerontology courses, demonstrate the shortcomings of program evaluations, and offer suggestions for future research to advance and generate theory.

No middle ground, but many mansions: design features | Pratt ...

African Journals Online (AJOL)

The model also suggests that blended learning should be viewed as a multiplicity of combinations rather than 'middle ground' in a continuum of wholesale adoption or rejection of ICT. The tentative hypotheses outlined in this paper are illustrated with reference to doctoral research on communication in written mode and ...

Change detection and change monitoring of natural and man-made features in multispectral and hyperspectral satellite imagery

Science.gov (United States)

Moody, Daniela Irina

2018-04-17

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

TFTR grounding scheme and ground-monitor system

International Nuclear Information System (INIS)

Viola, M.

1983-01-01

The Tokamak Fusion Test Reactor (TFTR) grounding system utilizes a single-point ground. It is located directly under the machine, at the basement floor level, and is tied to the building perimeter ground. Wired to this single-point ground, via individual 500 MCM insulated cables, are: the vacuum vessel; four toroidal field coil cases/inner support structure quadrants; umbrella structure halves; the substructure ring girder; radial beams and columns; and the diagnostic systems. Prior to the first machine operation, a ground-loop removal program was initiated. It required insulation of all hangers and supports (within a 35-foot radius of the center of the machine) of the various piping, conduits, cable trays, and ventilation systems. A special ground-monitor system was designed and installed. It actively monitors each of the individual machine grounds to insure that there are no inadvertent ground loops within the machine structure or its ground and that the machine grounds are intact prior to each pulse. The TFTR grounding system has proven to be a very manageable system and one that is easy to maintain

Transformative Learning: A Case for Using Grounded Theory as an Assessment Analytic

Science.gov (United States)

Patterson, Barbara A. B.; Munoz, Leslie; Abrams, Leah; Bass, Caroline

2015-01-01

Transformative Learning Theory and pedagogies leverage disruptive experiences as catalysts for learning and teaching. By facilitating processes of critical analysis and reflection that challenge assumptions, transformative learning reframes what counts as knowledge and the sources and processes for gaining and producing it. Students develop a…

Predicting ground contact events for a continuum of gait types: An application of targeted machine learning using principal component analysis.

Science.gov (United States)

Osis, Sean T; Hettinga, Blayne A; Ferber, Reed

2016-05-01

An ongoing challenge in the application of gait analysis to clinical settings is the standardized detection of temporal events, with unobtrusive and cost-effective equipment, for a wide range of gait types. The purpose of the current study was to investigate a targeted machine learning approach for the prediction of timing for foot strike (or initial contact) and toe-off, using only kinematics for walking, forefoot running, and heel-toe running. Data were categorized by gait type and split into a training set (∼30%) and a validation set (∼70%). A principal component analysis was performed, and separate linear models were trained and validated for foot strike and toe-off, using ground reaction force data as a gold-standard for event timing. Results indicate the model predicted both foot strike and toe-off timing to within 20ms of the gold-standard for more than 95% of cases in walking and running gaits. The machine learning approach continues to provide robust timing predictions for clinical use, and may offer a flexible methodology to handle new events and gait types. Copyright © 2016 Elsevier B.V. All rights reserved.

38 TOWARDS A STUDENT-CENTRED LEARNING IN NIGERIAN ...

African Journals Online (AJOL)

Prof Alex C Asigbo

knowledge. These ideas were grounded in a theory of learning that ... For example, research suggests that learners ... as creative dramatics class, interactive method of teaching, ...... International Journal of Historical Learning, Thinking, and.

[Prospective memory - concepts, methods of assessment, neuroanatomical bases and its deficits in mental disorders].

Science.gov (United States)

Wiłkość, Monika; Izdebski, Paweł; Zajac-Lamparska, Ludmiła

2013-01-01

In the last two decades of the last century there has been a shift in the studies on memory. In psychology of memory the criticism of the laboratory approach resulted in development of the ecological approach. One of the effects of this change was to initiate researches on memory that includes plans for the future, which has resulted in the distinction of the concept of prospective memory. Prospective memory is used in many aspects of everyday life. It deals with remembering intentions and plans, it is connected with remembering about specific task or activity in the future. There are three types of PM: event-based prospective memory, time-based prospective memory and activity-based prospective memory. Current research in this field have already established its own paradigm and tools measuring PM and there is still increasing scientific interest in this issue. Prospective memory assessment may be carried out in various ways. Among them, the most frequently used are: a) questionnaires, b) psychological tests, c) experimental procedures. Within the latter, the additional distinction can be introduced for: the experiments conducted under natural conditions and the laboratory procedures. In Polish literature, there are only a few articles on PM. The aim of this work is to review studies on assessment methods of PM. Its neuroanatomical bases and its functioning in different mental disorders are analyzed. The work is aimed to focus clinicians attention on prospective memory as an area which is important for complex diagnosis of cognitive processes.

Action control processes in autism spectrum disorder--insights from a neurobiological and neuroanatomical perspective.

Science.gov (United States)

Chmielewski, Witold X; Beste, Christian

2015-01-01

Autism spectrum disorders (ASDs) encompass a range of syndromes that are characterized by social interaction impairments, verbal and nonverbal communication difficulties, and stereotypic or repetitive behaviours. Although there has been considerable progress in understanding the mechanisms underlying the changes in the 'social' and 'communicative' aspects of ASD, the neurofunctional architecture of repetitive and stereotypic behaviours, as well as other cognitive domains related to response and action control, remain poorly understood. Based on the findings of neurobiological and neuroanatomical alterations in ASD and the functional neuroanatomy and neurobiology of different action control functions, we emphasize that changes in action control processes, including response inhibition, conflict and response monitoring, task switching, dual-tasking, motor timing, and error monitoring, are important facets of ASD. These processes must be examined further to understand the executive control deficits in ASD that are related to stereotypic or repetitive behaviours as a major facet of ASD. The review shows that not all domains of action control are strongly affected in ASD. Several factors seem to determine the consistency with which alterations in cognitive control are reported. These factors relate to the relevance of neurobiological changes in ASD for the cognitive domains examined and in how far action control relies upon the adjustment of prior experience. Future directions and hypotheses are outlined that may guide basic and clinical research on action control in ASD. Copyright © 2014 Elsevier Ltd. All rights reserved.

Neuroanatomical circuitry between kidney and rostral elements of brain: a virally mediated transsynaptic tracing study in mice.

Science.gov (United States)

Zhou, Ye-Ting; He, Zhi-Gang; Liu, Tao-Tao; Feng, Mao-Hui; Zhang, Ding-Yu; Xiang, Hong-Bing

2017-02-01

The identity of higher-order neurons and circuits playing an associative role to control renal function is not well understood. We identified specific neural populations of rostral elements of brain regions that project multisynaptically to the kidneys in 3-6 days after injecting a retrograde tracer pseudorabies virus (PRV)-614 into kidney of 13 adult male C57BL/6J strain mice. PRV-614 infected neurons were detected in a number of mesencephalic (e.g. central amygdala nucleus), telencephalic regions and motor cortex. These divisions included the preoptic area (POA), dorsomedial hypothalamus (DMH), lateral hypothalamus, arcuate nucleus (Arc), suprachiasmatic nucleus (SCN), periventricular hypothalamus (PeH), and rostral and caudal subdivision of the paraventricular nucleus of the hypothalamus (PVN). PRV-614/Tyrosine hydroxylase (TH) double-labeled cells were found within DMH, Arc, SCN, PeH, PVN, the anterodorsal and medial POA. A subset of neurons in PVN that participated in regulating sympathetic outflow to kidney was catecholaminergic or serotonergic. PRV-614 infected neurons within the PVN also contained arginine vasopressin or oxytocin. These data demonstrate the rostral elements of brain innervate the kidney by the neuroanatomical circuitry.

New BFA Method Based on Attractor Neural Network and Likelihood Maximization

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.; Snášel, V.

2014-01-01

Roč. 132, 20 May (2014), s. 14-29 ISSN 0925-2312 Grant - others:GA MŠk(CZ) ED1.1.00/02.0070; GA MŠk(CZ) EE.2.3.20.0073 Program:ED Institutional support: RVO:67985807 Keywords : recurrent neural network * associative memory * Hebbian learning rule * neural network application * data mining * statistics * Boolean factor analysis * information gain * dimension reduction * likelihood-maximization * bars problem Subject RIV: IN - Informatics, Computer Science Impact factor: 2.083, year: 2014

Discrete capacity limits and neuroanatomical correlates of visual short-term memory for objects and spatial locations.

Science.gov (United States)

Konstantinou, Nikos; Constantinidou, Fofi; Kanai, Ryota

2017-02-01

Working memory is responsible for keeping information in mind when it is no longer in view, linking perception with higher cognitive functions. Despite such crucial role, short-term maintenance of visual information is severely limited. Research suggests that capacity limits in visual short-term memory (VSTM) are correlated with sustained activity in distinct brain areas. Here, we investigated whether variability in the structure of the brain is reflected in individual differences of behavioral capacity estimates for spatial and object VSTM. Behavioral capacity estimates were calculated separately for spatial and object information using a novel adaptive staircase procedure and were found to be unrelated, supporting domain-specific VSTM capacity limits. Voxel-based morphometry (VBM) analyses revealed dissociable neuroanatomical correlates of spatial versus object VSTM. Interindividual variability in spatial VSTM was reflected in the gray matter density of the inferior parietal lobule. In contrast, object VSTM was reflected in the gray matter density of the left insula. These dissociable findings highlight the importance of considering domain-specific estimates of VSTM capacity and point to the crucial brain regions that limit VSTM capacity for different types of visual information. Hum Brain Mapp 38:767-778, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale.

Directory of Open Access Journals (Sweden)

Jason W Bohland

2009-03-01

Full Text Available In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is critical, however, for both basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brainwide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brainwide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open-access data repository; compatibility with existing resources; and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.

Marshaling Resources: A Classic Grounded Theory Study of Online Learners

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Barbara Yalof

2014-06-01

Full Text Available Classic grounded theory (CGT was used to identify a main concern of online students in higher education. One of the main impediments to studying online is a sense of isolation and lack of access to support systems as students navigate through complex requirements of their online programs. Hypothetical probability statements illustrate the imbalance between heightened needs of virtual learners and perceived inadequate support provided by educational institutions. The core variable, marshaling resources, explains how peer supports sustain motivation toward successful program completion. Understanding the critical contribution virtual interpersonal networks make towards maximizing resources by group problem solving is a significant aspect of this theory. Keywords: Online learning, e-learning, personal learning networks, peer networks

Breaking Ground on the University Garden: Service-Learning and Action Research

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Davis, Bryce Collin

2014-01-01

The purpose of this dissertation was to document, analyze, understand, and describe how the environmental virtue ethics of undergraduate students were impacted after participating in a service-learning project designed to establish a new university garden. This service-learning project occurred during the fall semester of 2011, on the campus of…

Grounding theories of W(e)Learn: a framework for online interprofessional education.

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Casimiro, Lynn; MacDonald, Colla J; Thompson, Terrie Lynn; Stodel, Emma J

2009-07-01

Interprofessional care (IPC) is a prerequisite for enhanced communication between healthcare team members, improved quality of care, and better outcomes for patients. A move to an IPC model requires changing the learning experiences of healthcare providers during and after their qualification program. With the rapid growth of online and blended approaches to learning, an educational framework that explains how to construct quality learning events to provide IPC is pressing. Such a framework would offer a quality standard to help educators design, develop, deliver, and evaluate online interprofessional education (IPE) programs. IPE is an extremely delicate process due to issues related to knowledge, status, power, accountability, personality traits, and culture that surround IPC. In this paper, a review of the pertinent literature that would inform the development of such a framework is presented. The review covers IPC, IPE, learning theories, and eLearning in healthcare.

What Role Does Knowledge Quality Play in Online Students' Satisfaction, Learning and Loyalty? An Empirical Investigation in an eLearning Context

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Waheed, M.; Kaur, K.; Kumar, S.

2016-01-01

Quality knowledge has an impact on online students learning outcomes and loyalty. A framework that delineates the perceived eLearning knowledge quality (KQ) and its relationship with learning outcomes and loyalty is currently absent. Grounded in the KQ and information system success framework--this study presents the indicators of perceived…

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition.

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Johannes Bill

Full Text Available During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input.

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

Science.gov (United States)

Bill, Johannes; Buesing, Lars; Habenschuss, Stefan; Nessler, Bernhard; Maass, Wolfgang; Legenstein, Robert

2015-01-01

During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input. PMID:26284370

Improving self-regulated learning junior high school students through computer-based learning

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Nurjanah; Dahlan, J. A.

2018-05-01

This study is back grounded by the importance of self-regulated learning as an affective aspect that determines the success of students in learning mathematics. The purpose of this research is to see how the improvement of junior high school students' self-regulated learning through computer based learning is reviewed in whole and school level. This research used a quasi-experimental research method. This is because individual sample subjects are not randomly selected. The research design used is Pretest-and-Posttest Control Group Design. Subjects in this study were students of grade VIII junior high school in Bandung taken from high school (A) and middle school (B). The results of this study showed that the increase of the students' self-regulated learning who obtain learning with computer-based learning is higher than students who obtain conventional learning. School-level factors have a significant effect on increasing of the students' self-regulated learning.

Postmortem changes in the neuroanatomical characteristics of the primate brain: the hippocampal formation

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Lavenex, Pierre; Lavenex, Pamela Banta; Bennett, Jeffrey L.; Amaral, David G.

2009-01-01

Comparative studies of the structural organization of the brain are fundamental to our understanding of human brain function. However, whereas brains of experimental animals are fixed by perfusion of a fixative through the vasculature, human or ape brains are fixed by immersion after varying postmortem intervals. Although differential treatments might affect the fundamental characteristics of the tissue, this question has not been evaluated empirically in primate brains. Monkey brains were either perfused, or acquired after varying postmortem intervals before immersion-fixation in 4% paraformaldehyde. We found that the fixation method affected the neuroanatomical characteristics of the monkey hippocampal formation. Soma size was smaller in Nissl-stained, immersion-fixed tissue, although overall brain volume was larger, as compared to perfusion-fixed tissue. Non-phosphorylated high-molecular-weight neurofilament immunoreactivity was lower in CA3 pyramidal neurons, dentate mossy cells and the entorhinal cortex, whereas it was higher in the mossy fiber pathway in immersion-fixed tissue. Serotonin-immunoreactive fibers were well-stained in perfused tissue but were undetectable in immersion-fixed tissue. Although regional immunoreactivity patterns for calcium-binding proteins were not affected, intracellular staining degraded with increasing postmortem intervals. Somatostatin-immunoreactive clusters of large axonal varicosities, previously reported only in humans, were observed in immersion-fixed monkey tissue. In addition, calretinin-immunoreactive multipolar neurons, previously observed only in rodents, were found in the rostral dentate gyrus in both perfused and immersion-fixed brains. In conclusion, comparative studies of the brain must evaluate the effects of fixation on the staining pattern of each marker in every structure of interest before drawing conclusions about species differences. PMID:18972553

Learning e-Learning

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Gabriel ZAMFIR

2009-01-01

Full Text Available What You Understand Is What Your Cognitive Integrates. Scientific research develops, as a native environment, knowledge. This environment consists of two interdependent divisions: theory and technology. First division occurs as a recursive research, while the second one becomes an application of the research activity. Over time, theories integrate methodologies and technology extends as infrastructure. The engine of this environment is learning, as the human activity of knowledge work. The threshold term of this model is the concepts map; it is based on Bloom’ taxonomy for the cognitive domain and highlights the notion of software scaffolding which is grounded in Vygotsky’s Social Development Theory with its major theme, Zone of Proximal Development. This article is designed as a conceptual paper, which analyzes specific structures of this type of educational research: the model reflects a foundation for a theory and finally, the theory evolves as groundwork for a system. The outcomes of this kind of approach are the examples, which are, theoretically, learning outcomes, and practically exist as educational objects, so-called e-learning.

Recognition of abstract objects via neural oscillators: interaction among topological organization, associative memory and gamma band synchronization.

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Ursino, Mauro; Magosso, Elisa; Cuppini, Cristiano

2009-02-01

Synchronization of neural activity in the gamma band is assumed to play a significant role not only in perceptual processing, but also in higher cognitive functions. Here, we propose a neural network of Wilson-Cowan oscillators to simulate recognition of abstract objects, each represented as a collection of four features. Features are ordered in topological maps of oscillators connected via excitatory lateral synapses, to implement a similarity principle. Experience on previous objects is stored in long-range synapses connecting the different topological maps, and trained via timing dependent Hebbian learning (previous knowledge principle). Finally, a downstream decision network detects the presence of a reliable object representation, when all features are oscillating in synchrony. Simulations performed giving various simultaneous objects to the network (from 1 to 4), with some missing and/or modified properties suggest that the network can reconstruct objects, and segment them from the other simultaneously present objects, even in case of deteriorated information, noise, and moderate correlation among the inputs (one common feature). The balance between sensitivity and specificity depends on the strength of the Hebbian learning. Achieving a correct reconstruction in all cases, however, requires ad hoc selection of the oscillation frequency. The model represents an attempt to investigate the interactions among topological maps, autoassociative memory, and gamma-band synchronization, for recognition of abstract objects.

Pragmatism, Pedagogy, and Community Service Learning

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Yoder, Scot D.

2016-01-01

In this paper I explore Goodwin Liu's proposal to ground the pedagogy of service-learning in the epistemology of pragmatism from the perspective of a reflective practitioner. I review Liu's epistemology and his claim that from within it three features common to service-learning--community, diversity, and engagement--become pedagogical virtues. I…

The ventral nerve cord in Cephalocarida (Crustacea): new insights into the ground pattern of Tetraconata.

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Stegner, Martin E J; Brenneis, Georg; Richter, Stefan

2014-03-01

Cephalocarida are Crustacea with many anatomical features that have been interpreted as plesiomorphic with respect to crustaceans or Tetraconata. While the ventral nerve cord (VNC) has been investigated in many other arthropods to address phylogenetic and evolutionary questions, the few studies that exist on the cephalocarid VNC date back 20 years, and data pertaining to neuroactive substances in particular are too sparse for comparison. We reinvestigated the VNC of adult Hutchinsoniella macracantha in detail, combining immunolabeling (tubulin, serotonin, RFamide, histamine) and nuclear stains with confocal laser microscopy, complemented by 3D-reconstructions based on serial semithin sections. The subesophageal ganglion in Cephalocarida comprises three segmental neuromeres (Md, Mx1, Mx2), while a separate ganglion occurs in all thoracic segments and abdominal segments 1-8. Abdominal segments 9 and 10 and the telson are free of ganglia. The maxillar neuromere and the thoracic ganglia correspond closely in their limb innervation pattern, their pattern of mostly four segmental commissures and in displaying up to six individually identified serotonin-like immunoreactive neurons per body side, which exceeds the number found in most other tetraconates. Only two commissures and two serotonin-like immunoreactive neurons per side are present in abdominal ganglia. The stomatogastric nervous system in H. macracantha corresponds to that in other crustaceans and includes, among other structures, a pair of lateral neurite bundles. These innervate the gut as well as various trunk muscles and are, uniquely, linked to the unpaired median neurite bundle. We propose that most features of the cephalocarid ventral nerve cord (VNC) are plesiomorphic with respect to the tetraconate ground pattern. Further, we suggest that this ground pattern includes more serotonin-like neurons than hitherto assumed, and argue that a sister-group relationship between Cephalocarida and Remipedia, as

Fathers' Orientation to Their Children's Autism Diagnosis: A Grounded Theory Study

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Hannon, Michael D.; Hannon, LaChan V.

2017-01-01

Sixteen fathers of individuals with autism were interviewed to develop a grounded theory explaining how they learned about their children's autism diagnosis. Results suggest the orientation process entails at least two phases: orienting oneself and orienting others. The orienting oneself phase entailed fathers having suspicion of developmental…

'Proactive' use of cue-context congruence for building reinforcement learning's reward function.

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Zsuga, Judit; Biro, Klara; Tajti, Gabor; Szilasi, Magdolna Emma; Papp, Csaba; Juhasz, Bela; Gesztelyi, Rudolf

2016-10-28

Reinforcement learning is a fundamental form of learning that may be formalized using the Bellman equation. Accordingly an agent determines the state value as the sum of immediate reward and of the discounted value of future states. Thus the value of state is determined by agent related attributes (action set, policy, discount factor) and the agent's knowledge of the environment embodied by the reward function and hidden environmental factors given by the transition probability. The central objective of reinforcement learning is to solve these two functions outside the agent's control either using, or not using a model. In the present paper, using the proactive model of reinforcement learning we offer insight on how the brain creates simplified representations of the environment, and how these representations are organized to support the identification of relevant stimuli and action. Furthermore, we identify neurobiological correlates of our model by suggesting that the reward and policy functions, attributes of the Bellman equitation, are built by the orbitofrontal cortex (OFC) and the anterior cingulate cortex (ACC), respectively. Based on this we propose that the OFC assesses cue-context congruence to activate the most context frame. Furthermore given the bidirectional neuroanatomical link between the OFC and model-free structures, we suggest that model-based input is incorporated into the reward prediction error (RPE) signal, and conversely RPE signal may be used to update the reward-related information of context frames and the policy underlying action selection in the OFC and ACC, respectively. Furthermore clinical implications for cognitive behavioral interventions are discussed.

Facilitating vocabulary learning through metacognitive strategy training and learning journals

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Carmen Luz Trujillo Becerra

2015-10-01

Full Text Available This paper reports on a mixed- method action research study carried out with participants from three public high schools in different regions in Colombia: Bogotá, Orito and Tocaima.  The overall aim of this study was to analyze whether training in the use of metacognitive strategies (MS through learning journals could improve the participants’ vocabulary learning. The data, collected mainly through students’ learning journals, teachers’ field notes, questionnaires and mind maps, was analyzed following the principles of grounded theory. The results suggested that the training helped participants to develop metacognitive awareness of their vocabulary learning process and their lexical competence regarding daily routines.  Participants also displayed some improvements in critical thinking and self-directed attitudes that could likewise benefit their vocabulary learning. Finally, the study proposes that training in metacognitive and vocabulary strategies should be implemented in language classrooms to promote a higher degree of student control over learning and to facilitate the transference of these strategies to other areas of knowledge.

Learning about health: The pupils' and the school health nurses' assessment of the health dialogue

DEFF Research Database (Denmark)

Borup, Ina K.

Public health, health promotion, empowerment, experiential learning, health behaviour in school-aged children (HBSC), health survey, qualitative interviews, grounded theory, school children......Public health, health promotion, empowerment, experiential learning, health behaviour in school-aged children (HBSC), health survey, qualitative interviews, grounded theory, school children...

Learning about health: The pupils' and the school health nurses assessment of the health dialogue

DEFF Research Database (Denmark)

Borup, Ina K.

Public health, health promotion, empowerment, experiental learning, HBSC, health survey, qualitative interviews, grounded theory, school children, adolescents, health dialogue, school health nurse......Public health, health promotion, empowerment, experiental learning, HBSC, health survey, qualitative interviews, grounded theory, school children, adolescents, health dialogue, school health nurse...

Project-Based Learning Not Just for STEM Anymore

Science.gov (United States)

Duke, Nell K.; Halvorsen, Anne-Lise; Strachan, Stephanie L.

2016-01-01

The popularity of project-based learning has been driven in part by a growing number of STEM schools and programs. But STEM subjects are not the only fertile ground for project-based learning (PBL). Social studies and literacy content, too, can be adapted into PBL units to benefit teaching and learning, the authors argue. They review key studies…

Zero to Integration in Eight Months, the Dawn Ground Data System Engineering Challange

Science.gov (United States)

Dubon, Lydia P.

2006-01-01

of the intermediate products to an integrated final product. In addition, this paper will highlight the role of lessons learned from the integration experience. The lessons learned from an early GDS deployment have served as the foundation for the design and implementation of the Dawn Ground Data System.

Artillery localization using networked wireless ground sensors

Science.gov (United States)

Swanson, David C.

2002-08-01

This paper presents the results of an installation of four acoustic/seismic ground sensors built using COTS computers and networking gear and operating on a continuous basis at Yuma Proving Grounds, Arizona. A description of the design can be found as well, which is essentially a Windows 2000 PC with 24-bit data acquisition, GPS timing, and environmental sensors for wind and temperature. A 4-element square acoustic array 1.8m on a side can be used to detect the time and angle of arrival of the muzzle blast and the impact explosion. A 3-component geophone allows the seismic wave direction to be estimated. The 8th channel of the 24-bit data acquisition system has a 1-pulse-per-second time signal from the GPS. This allows acoustic/seismic 'snapshots' to be coherently related from multiple disconnected ground sensor nodes. COTS 2.4 GHz frequency hopping radios (802.11 standard) are used with either omni or yagi antennas depending on the location on the range. Localization of the artillery or impact can be done by using the time and angle of arrival of the waves at 2 or more ground sensor locations. However, this straightforward analysis can be significantly complicated by weather and wind noise and is also the subject of another research contract. This work will present a general description of the COTS ground sensor installation, show example data autonomously collected including agent-based atmospheric data, and share some of the lessons learned from operating a Windows 2000 based system continuously outdoors.

Mapping, Navigation, and Learning for Off-Road Traversal

DEFF Research Database (Denmark)

Konolige, Kurt; Agrawal, Motilal; Blas, Morten Rufus

2009-01-01

The challenge in the DARPA Learning Applied to Ground Robots (LAGR) project is to autonomously navigate a small robot using stereo vision as the main sensor. During this project, we demonstrated a complete autonomous system for off-road navigation in unstructured environments, using stereo vision......, online terrain traversability learning, visual odometry, map registration, planning, and control. At the end of 3 years, the system we developed outperformed all nine other teams in final blind tests over previously unseen terrain.......The challenge in the DARPA Learning Applied to Ground Robots (LAGR) project is to autonomously navigate a small robot using stereo vision as the main sensor. During this project, we demonstrated a complete autonomous system for off-road navigation in unstructured environments, using stereo vision...

Ground Processing Affordability for Space Vehicles

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Ingalls, John; Scott, Russell

2011-01-01

Launch vehicles and most of their payloads spend the majority of their time on the ground. The cost of ground operations is very high. So, why so often is so little attention given to ground processing during development? The current global space industry and economic environment are driving more need for efficiencies to save time and money. Affordability and sustainability are more important now than ever. We can not continue to treat space vehicles as mere science projects. More RLV's (Reusable Launch Vehicles) are being developed for the gains of reusability which are not available for ELV's (Expendable Launch Vehicles). More human-rated vehicles are being developed, with the retirement of the Space Shuttles, and for a new global space race, yet these cost more than the many unmanned vehicles of today. We can learn many lessons on affordability from RLV's. DFO (Design for Operations) considers ground operations during design, development, and manufacturing-before the first flight. This is often minimized for space vehicles, but is very important. Vehicles are designed for launch and mission operations. You will not be able to do it again if it is too slow or costly to get there. Many times, technology changes faster than space products such that what is launched includes outdated features, thus reducing competitiveness. Ground operations must be considered for the full product Lifecycle, from concept to retirement. Once manufactured, launch vehicles along with their payloads and launch systems require a long path of processing before launch. Initial assembly and testing always discover problems to address. A solid integration program is essential to minimize these impacts, as was seen in the Constellation Ares I-X test rocket. For RLV's, landing/recovery and post-flight turnaround activities are performed. Multi-use vehicles require reconfiguration. MRO (Maintenance, Repair, and Overhaul) must be well-planned--- even for the unplanned problems. Defect limits and

Learning Disabilities and the School Health Worker

Science.gov (United States)

Freeman, Stephen W.

1973-01-01

This article offers three listings of signs and symptoms useful in detection of learning and perceptual deficiencies. The first list presents symptoms of the learning-disabled child; the second gives specific visual perceptual deficits (poor discrimination, figure-ground problems, reversals, etc.); and the third gives auditory perceptual deficits…

The Feasibility of Detecting Neuropsychologic and Neuroanatomic Effects of Type 1 Diabetes in Young Children

Science.gov (United States)

Aye, Tandy; Reiss, Allan L.; Kesler, Shelli; Hoang, Sherry; Drobny, Jessica; Park, Yaena; Schleifer, Kristin; Baumgartner, Heidi; Wilson, Darrell M.; Buckingham, Bruce A.

2011-01-01

OBJECTIVE To determine if frequent exposures to hypoglycemia and hyperglycemia during early childhood lead to neurocognitive deficits and changes in brain anatomy. RESEARCH DESIGN AND METHODS In this feasibility, cross-sectional study, young children, aged 3 to 10 years, with type 1 diabetes and age- and sex-matched healthy control (HC) subjects completed neuropsychologic (NP) testing and magnetic resonance imaging (MRI) scans of the brain. RESULTS NP testing and MRI scanning was successfully completed in 98% of the type 1 diabetic and 93% of the HC children. A significant negative relationship between HbA1c and Wechsler Intelligence Scale for Children (WISC) verbal comprehension was observed. WISC index scores were significantly reduced in type 1 diabetic subjects who had experienced seizures. White matter volume did not show the expected increase with age in children with type 1 diabetes compared with HC children (diagnosis by age interaction, P = 0.005). A similar trend was detected for hippocampal volume. Children with type 1 diabetes who had experienced seizures showed significantly reduced gray matter and white matter volumes relative to children with type 1 diabetes who had not experienced seizures. CONCLUSIONS It is feasible to perform MRI and NP testing in young children with type 1 diabetes. Further, early signs of neuroanatomic variation may be present in this population. Larger cross-sectional and longitudinal studies of neurocognitive function and neuroanatomy are needed to define the effect of type 1 diabetes on the developing brain. PMID:21562318

Living on the edge of asthma: A grounded theory exploration.

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Shaw, Michele R; Oneal, Gail

2014-10-01

Most asthma-related emergency department (ED) visits and hospitalizations for asthma are preventable. Our purpose was to develop a grounded theory to guide interventions to reduce unnecessary hospitalizations and ED visits. Grounded theory inquiry guided interviews of 20 participants, including 13 parents and 7 children. Living on the edge of asthma was the emergent theory. Categories included: balancing, losing control, seeking control, and transforming. The theory provides the means for nurses to understand the dynamic process that families undergo in trying to prevent and then deal with and learn from an acute asthma attack requiring hospitalization or an ED visit. © 2014, Wiley Periodicals, Inc.

Network Enabled - Unresolved Residual Analysis and Learning (NEURAL)

Science.gov (United States)

Temple, D.; Poole, M.; Camp, M.

Since the advent of modern computational capacity, machine learning algorithms and techniques have served as a method through which to solve numerous challenging problems. However, for machine learning methods to be effective and robust, sufficient data sets must be available; specifically, in the space domain, these are generally difficult to acquire. Rapidly evolving commercial space-situational awareness companies boast the capability to collect hundreds of thousands nightly observations of resident space objects (RSOs) using a ground-based optical sensor network. This provides the ability to maintain custody of and characterize thousands of objects persistently. With this information available, novel deep learning techniques can be implemented. The technique discussed in this paper utilizes deep learning to make distinctions between nightly data collects with and without maneuvers. Implementation of these techniques will allow the data collected from optical ground-based networks to enable well informed and timely the space domain decision making.

A Personal Journey with Grounded Theory Methodology. Kathy Charmaz in Conversation With Reiner Keller

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Kathy Charmaz

2016-01-01

Full Text Available Kathy CHARMAZ is one of the most important thinkers in grounded theory methodology today. Her trailblazing work on constructivist grounded theory continues to inspire research across many disciplines and around the world. In this interview, she reflects on the aura surrounding qualitative inquiry that existed in California in the late 1960s to early 1970s and the lessons she learned from her first forays into empirical research. She comments on the trajectory that grounded theory research has followed since then and gives an account of her own perspective on constructivist grounded theory. In doing so, she underlines the importance of the Chicago School and symbolic interactionist tradition for grounded theory research work today and shows where the latter is positioned in the current field of qualitative fieldwork. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs1601165

Physical Activity and Fitness Knowledge Learning in Physical Education: Seeking a Common Ground

Science.gov (United States)

Chen, Senlin; Chen, Ang; Sun, Haichun; Zhu, Xihe

2013-01-01

Motivation to learn is a disposition developed through exposure to learning opportunities. Guided by the expectancy-value theory of Eccles and Wigfield (1995), this study examined the extent to which expectancy belief and task value influenced elementary school students' physical activity and knowledge learning in physical education (PE).…

Advances in intelligent diagnosis methods for pulmonary ground-glass opacity nodules.

Science.gov (United States)

Yang, Jing; Wang, Hailin; Geng, Chen; Dai, Yakang; Ji, Jiansong

2018-02-07

Pulmonary nodule is one of the important lesions of lung cancer, mainly divided into two categories of solid nodules and ground glass nodules. The improvement of diagnosis of lung cancer has significant clinical significance, which could be realized by machine learning techniques. At present, there have been a lot of researches focusing on solid nodules. But the research on ground glass nodules started late, and lacked research results. This paper summarizes the research progress of the method of intelligent diagnosis for pulmonary nodules since 2014. It is described in details from four aspects: nodular signs, data analysis methods, prediction models and system evaluation. This paper aims to provide the research material for researchers of the clinical diagnosis and intelligent analysis of lung cancer, and further improve the precision of pulmonary ground glass nodule diagnosis.

Learning In Landscapes of Practice: Boundaries, Identity and Knowledgeability in Practice-Based Learning

OpenAIRE

Wolfenden, Freda

2015-01-01

This short book is the latest output from Etienne Wenger-Trayner and collaborators,  an engaging conversation on professional learning firmly grounded in the work and voices of practitioners and those teaching or researching with practitioners across diverse fields, disciplines, professions and contexts – education, health, social care, environment, public relations and management. Over thirty contributors contribute stories of learning in their own practice, those in the first part of the bo...

Communication grounding facility

International Nuclear Information System (INIS)

Lee, Gye Seong

1998-06-01

It is about communication grounding facility, which is made up twelve chapters. It includes general grounding with purpose, materials thermal insulating material, construction of grounding, super strength grounding method, grounding facility with grounding way and building of insulating, switched grounding with No. 1A and LCR, grounding facility of transmission line, wireless facility grounding, grounding facility in wireless base station, grounding of power facility, grounding low-tenton interior power wire, communication facility of railroad, install of arrester in apartment and house, install of arrester on introduction and earth conductivity and measurement with introduction and grounding resistance.

Neuroanatomical and Symptomatic Sex Differences in Individuals at Clinical High Risk for Psychosis

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Elisa Guma

2017-12-01

Full Text Available Sex differences have been widely observed in clinical presentation, functional outcome and neuroanatomy in individuals with a first-episode of psychosis, and chronic patients suffering from schizophrenia. However, little is known about sex differences in the high-risk stages for psychosis. The present study investigated sex differences in cortical and subcortical neuroanatomy in individuals at clinical high risk (CHR for psychosis and healthy controls (CTL, and the relationship between anatomy and clinical symptoms in males at CHR. Magnetic resonance images were collected in 26 individuals at CHR (13 men and 29 CTLs (15 men to determine total and regional brain volumes and morphology, cortical thickness, and surface area (SA. Clinical symptoms were assessed with the brief psychiatric rating scale. Significant sex-by-diagnosis interactions were observed with opposite directions of effect in male and female CHR subjects relative to their same-sex controls in multiple cortical and subcortical areas. The right postcentral, left superior parietal, inferior parietal supramarginal, and angular gyri [<5% false discovery rate (FDR] were thicker in male and thinner in female CHR subjects compared with their same-sex CTLs. The same pattern was observed in the right superior parietal gyrus SA at the regional and vertex level. Using a recently developed surface-based morphology pipeline, we observed sex-specific shape differences in the left hippocampus (<5% FDR and amygdala (<10% FDR. Negative symptom burden was significantly higher in male compared with female CHR subjects (p = 0.04 and was positively associated with areal expansion of the left amygdala in males (<5% FDR. Some limitations of the study include the sample size, and data acquisition at 1.5 T. This study demonstrates neuroanatomical sex differences in CHR subjects, which may be associated with variations in symptomatology in men and women with psychotic symptoms.

Holistic Approach to Learning and Teaching Introductory Object-Oriented Programming

Science.gov (United States)

Thota, Neena; Whitfield, Richard

2010-01-01

This article describes a holistic approach to designing an introductory, object-oriented programming course. The design is grounded in constructivism and pedagogy of phenomenography. We use constructive alignment as the framework to align assessments, learning, and teaching with planned learning outcomes. We plan learning and teaching activities,…

Towards Autonomous Agriculture: Automatic Ground Detection Using Trinocular Stereovision

Directory of Open Access Journals (Sweden)

Annalisa Milella

2012-09-01

Full Text Available Autonomous driving is a challenging problem, particularly when the domain is unstructured, as in an outdoor agricultural setting. Thus, advanced perception systems are primarily required to sense and understand the surrounding environment recognizing artificial and natural structures, topology, vegetation and paths. In this paper, a self-learning framework is proposed to automatically train a ground classifier for scene interpretation and autonomous navigation based on multi-baseline stereovision. The use of rich 3D data is emphasized where the sensor output includes range and color information of the surrounding environment. Two distinct classifiers are presented, one based on geometric data that can detect the broad class of ground and one based on color data that can further segment ground into subclasses. The geometry-based classifier features two main stages: an adaptive training stage and a classification stage. During the training stage, the system automatically learns to associate geometric appearance of 3D stereo-generated data with class labels. Then, it makes predictions based on past observations. It serves as well to provide training labels to the color-based classifier. Once trained, the color-based classifier is able to recognize similar terrain classes in stereo imagery. The system is continuously updated online using the latest stereo readings, thus making it feasible for long range and long duration navigation, over changing environments. Experimental results, obtained with a tractor test platform operating in a rural environment, are presented to validate this approach, showing an average classification precision and recall of 91.0% and 77.3%, respectively.

Learning nitrogen-vacancy electron spin dynamics on a silicon quantum photonic simulator

NARCIS (Netherlands)

Wang, J.; Paesani, S.; Santagati, R.; Knauer, S.; Gentile, A. A.; Wiebe, N.; Petruzzella, M.; Laing, A.; Rarity, J. G.; O'Brien, J. L.; Thompson, M. G.

2017-01-01

We present the experimental demonstration of quantum Hamiltonian learning. Using an integrated silicon-photonics quantum simulator with the classical machine learning technique, we successfully learn the Hamiltonian dynamics of a diamond nitrogen-vacancy center's electron ground-state spin.

[Effect of space flight factors simulated in ground-based experiments on the behavior, discriminant learning, and exchange of monoamines in different brain structures of rats].

Science.gov (United States)

Shtemberg, A S; Lebedeva-Georgievskaia, K V; Matveeva, M I; Kudrin, V S; Narkevich, V B; Klodt, P M; Bazian, A S

2014-01-01

Experimental treatment (long-term fractionated γ-irradiation, antiorthostatic hypodynamia, and the combination of these factors) simulating the effect of space flight in ground-based experiments rapidly restored the motor and orienting-investigative activity of animals (rats) in "open-field" tests. The study of the dynamics of discriminant learning of rats of experimental groups did not show significant differences from the control animals. It was found that the minor effect of these factors on the cognitive performance of animals correlated with slight changes in the concentration ofmonoamines in the brain structures responsible for the cognitive, emotional, and motivational functions.

Ground Control for Emplacement Drifts for SR

International Nuclear Information System (INIS)

Y. Sun

2000-01-01

This analysis demonstrates that a satisfactory ground control system can be designed for the Yucca Mountain site, and provides the technical basis for the design of ground support systems to be used in repository emplacement and non-emplacement drifts. The repository ground support design was based on analytical methods using acquired computer codes, and focused on the final support systems. A literature review of case histories, including the lessons learned from the design and construction of the ESF, the studies on the seismic damages of underground openings, and the use of rock mass classification systems in the ground support design, was conducted (Sections 6.3.4 and 6.4). This review provided some basis for determining the inputs and methodologies used in this analysis. Stability of the supported and unsupported emplacement and non-emplacement drifts was evaluated in this analysis. The excavation effects (i.e., state of the stress change due to excavation), thermal effects (i.e., due to heat output from waste packages), and seismic effects (i.e., from potential earthquake events) were evaluated, and stress controlled modes of failure were examined for two in situ stress conditions (k 0 =0.3 and 1.0) using rock properties representing rock mass categories of 1 and 5. Variation of rock mass units such as the non-lithophysal (Tptpmn) and lithophysal (Tptpll) was considered in the analysis. The focus was on the non-lithophysal unit because this unit appears to be relatively weaker and has much smaller joint spacing. Therefore, the drift stability and ground support needs were considered to be controlled by the design for this rock unit. The ground support systems for both emplacement and non-emplacement drifts were incorporated into the models to assess their performance under in situ, thermal, and seismic loading conditions. Both continuum and discontinuum modeling approaches were employed in the analyses of the rock mass behavior and in the evaluation of the

Towards a general theory of neural computation based on prediction by single neurons.

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Christopher D Fiorillo

Full Text Available Although there has been tremendous progress in understanding the mechanics of the nervous system, there has not been a general theory of its computational function. Here I present a theory that relates the established biophysical properties of single generic neurons to principles of Bayesian probability theory, reinforcement learning and efficient coding. I suggest that this theory addresses the general computational problem facing the nervous system. Each neuron is proposed to mirror the function of the whole system in learning to predict aspects of the world related to future reward. According to the model, a typical neuron receives current information about the state of the world from a subset of its excitatory synaptic inputs, and prior information from its other inputs. Prior information would be contributed by synaptic inputs representing distinct regions of space, and by different types of non-synaptic, voltage-regulated channels representing distinct periods of the past. The neuron's membrane voltage is proposed to signal the difference between current and prior information ("prediction error" or "surprise". A neuron would apply a Hebbian plasticity rule to select those excitatory inputs that are the most closely correlated with reward but are the least predictable, since unpredictable inputs provide the neuron with the most "new" information about future reward. To minimize the error in its predictions and to respond only when excitation is "new and surprising," the neuron selects amongst its prior information sources through an anti-Hebbian rule. The unique inputs of a mature neuron would therefore result from learning about spatial and temporal patterns in its local environment, and by extension, the external world. Thus the theory describes how the structure of the mature nervous system could reflect the structure of the external world, and how the complexity and intelligence of the system might develop from a population of

Ground Pollution Science

International Nuclear Information System (INIS)

Oh, Jong Min; Bae, Jae Geun

1997-08-01

This book deals with ground pollution science and soil science, classification of soil and fundamentals, ground pollution and human, ground pollution and organic matter, ground pollution and city environment, environmental problems of the earth and ground pollution, soil pollution and development of geological features of the ground, ground pollution and landfill of waste, case of measurement of ground pollution.

Different Futures of Adaptive Collaborative Learning Support

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Rummel, Nikol; Walker, Erin; Aleven, Vincent

2016-01-01

In this position paper we contrast a Dystopian view of the future of adaptive collaborative learning support (ACLS) with a Utopian scenario that--due to better-designed technology, grounded in research--avoids the pitfalls of the Dystopian version and paints a positive picture of the practice of computer-supported collaborative learning 25 years…

E-Learning Course Design from a Cross Cultural Perspective

DEFF Research Database (Denmark)

Fahmy, Sandra Safwat Youssef

national, cultural and linguistic borders. The study attempts to shed a light on the differences in the learning practices of students in different countries, by using a mix between ethnography and grounded theory methodologies, to explore the different educational systems and learning practices...

Building machine learning systems with Python

CERN Document Server

Richert, Willi

2013-01-01

This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Python developers who want to learn about and build Machine Learning into their projects, or who want to pro

Adding the Human Touch to Asynchronous Online Learning

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Glenn, Cynthia Wheatley

2018-01-01

For learners to actively accept responsibility in a virtual classroom platform, it is necessary to provide special motivation extending across the traditional classroom setting into asynchronous online learning. This article explores specific ways to do this that bridge the gap between ground and online students' learning experiences, and how…

Specialized motor-driven dusp1 expression in the song systems of multiple lineages of vocal learning birds.

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Haruhito Horita

Full Text Available Mechanisms for the evolution of convergent behavioral traits are largely unknown. Vocal learning is one such trait that evolved multiple times and is necessary in humans for the acquisition of spoken language. Among birds, vocal learning is evolved in songbirds, parrots, and hummingbirds. Each time similar forebrain song nuclei specialized for vocal learning and production have evolved. This finding led to the hypothesis that the behavioral and neuroanatomical convergences for vocal learning could be associated with molecular convergence. We previously found that the neural activity-induced gene dual specificity phosphatase 1 (dusp1 was up-regulated in non-vocal circuits, specifically in sensory-input neurons of the thalamus and telencephalon; however, dusp1 was not up-regulated in higher order sensory neurons or motor circuits. Here we show that song motor nuclei are an exception to this pattern. The song nuclei of species from all known vocal learning avian lineages showed motor-driven up-regulation of dusp1 expression induced by singing. There was no detectable motor-driven dusp1 expression throughout the rest of the forebrain after non-vocal motor performance. This pattern contrasts with expression of the commonly studied activity-induced gene egr1, which shows motor-driven expression in song nuclei induced by singing, but also motor-driven expression in adjacent brain regions after non-vocal motor behaviors. In the vocal non-learning avian species, we found no detectable vocalizing-driven dusp1 expression in the forebrain. These findings suggest that independent evolutions of neural systems for vocal learning were accompanied by selection for specialized motor-driven expression of the dusp1 gene in those circuits. This specialized expression of dusp1 could potentially lead to differential regulation of dusp1-modulated molecular cascades in vocal learning circuits.

Leading Critically: A Grounded Theory of Applied Critical Thinking in Leadership Studies

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Jekins, Daniel M.; Cutchens, Amanda B.

2011-01-01

This study describes the development of a grounded theory of applied critical thinking in leadership studies and examines how student-centered experiential learning in leadership education bridged critical thinking with action. Over three semester undergraduate students in an upper level leadership studies course at a large four-year public…

Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

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Piastra, Marco

2013-05-01

Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise. Copyright © 2012 Elsevier Ltd. All rights reserved.

Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

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Li, Tongwen; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Xuechen; Zhang, Liangpei

2017-12-01

Fusing satellite observations and station measurements to estimate ground-level PM2.5 is promising for monitoring PM2.5 pollution. A geo-intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM2.5. Specifically, it considers geographical distance and spatiotemporally correlated PM2.5 in a deep belief network (denoted as Geoi-DBN). Geoi-DBN can capture the essential features associated with PM2.5 from latent factors. It was trained and tested with data from China in 2015. The results show that Geoi-DBN performs significantly better than the traditional neural network. The out-of-sample cross-validation R2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03 μg/m3. On the basis of the derived PM2.5 distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM2.5 of greater than 35 μg/m3. This study provides a new perspective for air pollution monitoring in large geographic regions.

Effectiveness of an e-Learning Platform for Image Interpretation Education of Medical Staff and Students.

Science.gov (United States)

Ogura, Akio; Hayashi, Norio; Negishi, Tohru; Watanabe, Haruyuki

2018-05-09

Medical staff must be able to perform accurate initial interpretations of radiography to prevent diagnostic errors. Education in medical image interpretation is an ongoing need that is addressed by text-based and e-learning platforms. The effectiveness of these methods has been previously reported. Here, we describe the effectiveness of an e-learning platform used for medical image interpretation education. Ten third-year medical students without previous experience in chest radiography interpretation were provided with e-learning instructions. Accuracy of diagnosis using chest radiography was provided before and after e-learning education. We measured detection accuracy for two image groups: nodular shadow and ground-glass shadow. We also distributed the e-learning system to the two groups and analyzed the effectiveness of education for both types of image shadow. The mean correct answer rate after the 2-week e-learning period increased from 34.5 to 72.7%. Diagnosis of the ground glass shadow improved significantly more than that of the mass shadow. Education using the e-leaning platform is effective for interpretation of chest radiography results. E-learning is particularly effective for the interpretation of chest radiography images containing ground glass shadow.

A Learning Activity Design Framework for Supporting Mobile Learning

Directory of Open Access Journals (Sweden)

Jalal Nouri

2016-01-01

Full Text Available This article introduces the Learning Activity Design (LEAD framework for the development and implementation of mobile learning activities in primary schools. The LEAD framework draws on methodological perspectives suggested by design-based research and interaction design in the specific field of technology-enhanced learning (TEL. The LEAD framework is grounded in four design projects conducted over a period of six years. It contributes a new understanding of the intricacies and multifaceted aspects of the design-process characterizing the development and implementation of mobile devices (i.e. smart phones and tablets in curricular activities conducted in Swedish primary schools. This framework is intended to provide both designers and researchers with methodological tools that take account of the pedagogical foundations of technologically-based educational interventions, usability issues related to the interaction with the mobile application developed, multiple data streams generated during the design project, multiple stakeholders involved in the design process and sustainability aspects of the mobile learning activities implemented in the school classroom.

Bilingualism yields language-specific plasticity in left hemisphere's circuitry for learning to read in young children.

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Jasińska, K K; Berens, M S; Kovelman, I; Petitto, L A

2017-04-01

How does bilingual exposure impact children's neural circuitry for learning to read? Theories of bilingualism suggests that exposure to two languages may yield a functional and neuroanatomical adaptation to support the learning of two languages (Klein et al., 2014). To test the hypothesis that this neural adaptation may vary as a function of structural and orthographic characteristics of bilinguals' two languages, we compared Spanish-English and French-English bilingual children, and English monolingual children, using functional Near Infrared Spectroscopy neuroimaging (fNIRS, ages 6-10, N =26). Spanish offers consistent sound-to-print correspondences ("phonologically transparent" or "shallow"); such correspondences are more opaque in French and even more opaque in English (which has both transparent and "phonologically opaque" or "deep" correspondences). Consistent with our hypothesis, both French- and Spanish-English bilinguals showed hyperactivation in left posterior temporal regions associated with direct sound-to-print phonological analyses and hypoactivation in left frontal regions associated with assembled phonology analyses. Spanish, but not French, bilinguals showed a similar effect when reading Irregular words. The findings inform theories of bilingual and cross-linguistic literacy acquisition by suggesting that structural characteristics of bilinguals' two languages and their orthographies have a significant impact on children's neuro-cognitive architecture for learning to read. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Joint Regulation of Radionuclides at Connecticut Yankee Haddam Neck Plant - Finding Common Ground and Lessons Learned

International Nuclear Information System (INIS)

Peters, J.; Glucksberg, N.; Fogg, A.; Couture, B.

2006-01-01

During the site closure of nuclear facilities where both radionuclides and chemicals are present in environmental media, state and federal regulatory agencies other than the Nuclear Regulatory Commission often have a stake in the regulation of the site closure process. At the Connecticut Yankee Atomic Power Company (CYAPCO) Haddam Neck Plant in Haddam, Connecticut, the site closure process includes both radiological and chemical cleanup which is regulated by two separate divisions within the state and two federal agencies. Each of the regulatory agencies has unique closure criteria which pertain to radionuclides and, consequently, there is overlapping and in some cases disparate regulation of radionuclides. Considerable effort has been expended by CYAPCO to find common ground in meeting the site closure requirements for radionuclides required by each of the agencies. This paper discusses the approaches that have been used by CYAPCO to address radionuclide site closure requirements. Significant lessons learned from these approaches include the demonstration that public health cleanup criteria for most radionuclides of concern at nuclear power generation facilities are protective for chemical toxicity concerns and are protective for ecological receptors and, consequently, performing a baseline ecological risk assessment for radionuclides at power generation facilities is not generally necessary. (authors)

Virtual patient design: exploring what works and why. A grounded theory study.

Science.gov (United States)

Bateman, James; Allen, Maggie; Samani, Dipti; Kidd, Jane; Davies, David

2013-06-01

Virtual patients (VPs) are online representations of clinical cases used in medical education. Widely adopted, they are well placed to teach clinical reasoning skills. International technology standards mean VPs can be created, shared and repurposed between institutions. A systematic review has highlighted the lack of evidence to support which of the numerous VP designs may be effective, and why. We set out to research the influence of VP design on medical undergraduates. This is a grounded theory study into the influence of VP design on undergraduate medical students. Following a review of the literature and publicly available VP cases, we identified important design properties. We integrated them into two substantial VPs produced for this research. Using purposeful iterative sampling, 46 medical undergraduates were recruited to participate in six focus groups. Participants completed both VPs, an evaluation and a 1-hour focus group discussion. These were digitally recorded, transcribed and analysed using grounded theory, supported by computer-assisted analysis. Following open, axial and selective coding, we produced a theoretical model describing how students learn from VPs. We identified a central core phenomenon designated 'learning from the VP'. This had four categories: VP Construction; External Preconditions; Student-VP Interaction, and Consequences. From these, we constructed a three-layer model describing the interactions of students with VPs. The inner layer consists of the student's cognitive and behavioural preconditions prior to sitting a case. The middle layer considers the VP as an 'encoded object', an e-learning artefact and as a 'constructed activity', with associated pedagogic and organisational elements. The outer layer describes cognitive and behavioural change. This is the first grounded theory study to explore VP design. This original research has produced a model which enhances understanding of how and why the delivery and design of VPs

Classic Grounded Theory to Analyse Secondary Data: Reality and Reflections

Directory of Open Access Journals (Sweden)

Lorraine Andrews

2012-06-01

Full Text Available This paper draws on the experiences of two researchers and discusses how they conducted a secondary data analysis using classic grounded theory. The aim of the primary study was to explore first-time parents’ postnatal educational needs. A subset of the data from the primary study (eight transcripts from interviews with fathers was used for the secondary data analysis. The objectives of the secondary data analysis were to identify the challenges of using classic grounded theory with secondary data and to explore whether the re-analysis of primary data using a different methodology would yield a different outcome. Through the process of re-analysis a tentative theory emerged on ‘developing competency as a father’. Challenges encountered during this re-analysis included the small dataset, the pre-framed data, and limited ability for theoretical sampling. This re-analysis proved to be a very useful learning tool for author 1(LA, who was a novice with classic grounded theory.

Constructive biology and approaches to temporal grounding in postreactive robotics

Science.gov (United States)

Nehaniv, Chrystopher L.; Dautenhahn, Kerstin; Loomes, Martin J.

1999-08-01

Constructive Biology means understanding biological mechanisms through building systems that exhibit life-like properties. Applications include learning engineering tricks from biological system, as well as the validation in biological modeling. In particular, biological system in the course of development and experience become temporally grounded. Researchers attempting to transcend mere reactivity have been inspired by the drives, motivations, homeostasis, hormonal control, and emotions of animals. In order to contextualize and modulate behavior, these ideas have been introduced into robotics and synthetic agents, while further flexibility is achieved by introducing learning. Broadening scope of the temporal horizon further requires post-reactive techniques that address not only the action in the now, although such action may perhaps be modulated by drives and affect. Support is needed for expressing and benefitting from pats experiences, predictions of the future, and form interaction histories of the self with the world and with other agents. Mathematical methods provide a new way to support such grounding in the construction of post-reactive systems. Moreover, the communication of such mathematical encoded histories of experience between situated agents opens a route to narrative intelligence, analogous to communication or story telling in societies.

Generating Ground Reference Data for a Global Impervious Surface Survey

Science.gov (United States)

Tilton, James C.; deColstoun, Eric Brown; Wolfe, Robert E.; Tan, Bin; Huang, Chengquan

2012-01-01

We are engaged in a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. The GLS data from Landsat provide an unprecedented opportunity to map global urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such as buildings, roads and parking lots. Finally, with GLS data available for the 1975, 1990, 2000, and 2005 time periods, and soon for the 2010 period, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. Our approach works across spatial scales using very high spatial resolution commercial satellite data to both produce and evaluate continental scale products at the 30m spatial resolution of Landsat data. We are developing continental scale training data at 1m or so resolution and aggregating these to 30m for training a regression tree algorithm. Because the quality of the input training data are critical, we have developed an interactive software tool, called HSegLearn, to facilitate the photo-interpretation of high resolution imagery data, such as Quickbird or Ikonos data, into an impervious versus non-impervious map. Previous work has shown that photo-interpretation of high resolution data at 1 meter resolution will generate an accurate 30m resolution ground reference when coarsened to that resolution. Since this process can be very time consuming when using standard clustering classification algorithms, we are looking at image segmentation as a potential avenue to not only improve the training process but also provide a semi-automated approach for generating the ground reference data. HSegLearn takes as its input a hierarchical set of image segmentations produced by the HSeg image segmentation program [1, 2]. HSegLearn lets an analyst specify pixel locations as being

Autonomous dynamics in neural networks: the dHAN concept and associative thought processes

Science.gov (United States)

Gros, Claudius

2007-02-01

The neural activity of the human brain is dominated by self-sustained activities. External sensory stimuli influence this autonomous activity but they do not drive the brain directly. Most standard artificial neural network models are however input driven and do not show spontaneous activities. It constitutes a challenge to develop organizational principles for controlled, self-sustained activity in artificial neural networks. Here we propose and examine the dHAN concept for autonomous associative thought processes in dense and homogeneous associative networks. An associative thought-process is characterized, within this approach, by a time-series of transient attractors. Each transient state corresponds to a stored information, a memory. The subsequent transient states are characterized by large associative overlaps, which are identical to acquired patterns. Memory states, the acquired patterns, have such a dual functionality. In this approach the self-sustained neural activity has a central functional role. The network acquires a discrimination capability, as external stimuli need to compete with the autonomous activity. Noise in the input is readily filtered-out. Hebbian learning of external patterns occurs coinstantaneous with the ongoing associative thought process. The autonomous dynamics needs a long-term working-point optimization which acquires within the dHAN concept a dual functionality: It stabilizes the time development of the associative thought process and limits runaway synaptic growth, which generically occurs otherwise in neural networks with self-induced activities and Hebbian-type learning rules.

Structure Mapping for Social Learning.

Science.gov (United States)

Christie, Stella

2017-07-01

Analogical reasoning is a foundational tool for human learning, allowing learners to recognize relational structures in new events and domains. Here I sketch some grounds for understanding and applying analogical reasoning in social learning. The social world is fundamentally characterized by relations between people, with common relational structures-such as kinships and social hierarchies-forming social units that dictate social behaviors. Just as young learners use analogical reasoning for learning relational structures in other domains-spatial relations, verbs, relational categories-analogical reasoning ought to be a useful cognitive tool for acquiring social relations and structures. Copyright © 2017 Cognitive Science Society, Inc.

PAL driven organizational learning theory and practices a light on learning journey of organizations

CERN Document Server

Chuah, Kong

2015-01-01

Presenting an innovative concept and approach for organization management, this book serves to document an organization’s journey towards the ultimate goal of learning organization. This book also shares the experience on how a OL framework built on established learning theories, could be used effectively, overcoming many of the barriers in a real industrial setting. Utilizing a ready-to-use tool called Project Action Learning (PAL) to analyze real life case studies, the authors introduce a framework that allows teams of people to work and learn over the course of business projects. Equal emphasis is placed on the achievement of pre-set project outcomes and the learning objectives of the participants. In addition, a long term organizational learning strategy is put forward and the necessary supporting infrastructure, in the form of four ‘PAL Pillars’, is described. The concepts and development of the PAL driven Organizational Learning model are inspired by, and grounded in, Western and Eastern business ...

RELATIONSHIP BETWEEN PERCEPTION AND LEARNING IN THE MENTALLY RETARDED.

Science.gov (United States)

JOHNSON, G. ORVILLE

SUPPORTIVE EVIDENCE IS GIVEN AGAINST PERCEPTUAL DISORDERS CREATING INTERFERENCE IN LEARNING. THE CONTENTION THAT A PERCEPTUAL FIGURE GROUND DISTURBANCE NECESSARILY INTERFERES WITH THE LEARNING PROCESS IS NOT SUPPORTED BY THE EVIDENCE. THERE ARE INDICATIONS, HOWEVER, THAT BACKGROUND INTERFERENCE SEEMS TO AFFECT SOME CHILDREN MORE THAN OTHERS. TWO…

Ground beef handling and cooking practices in restaurants in eight States.

Science.gov (United States)

Bogard, April K; Fuller, Candace C; Radke, Vincent; Selman, Carol A; Smith, Kirk E

2013-12-01

Eating in table-service restaurants has been implicated as a risk factor for Escherichia coli O157:H7 infection. To explore this association and learn about the prevalence of risky ground beef preparation practices in restaurants, the Environmental Health Specialists Network (EHS-Net) assessed ground beef handling policies and practices in restaurants in California, Colorado, Connecticut, Georgia, Minnesota, New York, Oregon, and Tennessee. Eligible restaurants prepared and served hamburgers. EHS-Net specialists interviewed a restaurant employee with authority over the kitchen (defined as the manager) using a standard questionnaire about food safety policies, hamburger preparation policies, and use of irradiated ground beef. Interviews were followed by observations of ground beef preparation. Data from 385 restaurants were analyzed: 67% of the restaurants were independently owned and 33% were chain restaurants; 75% of the restaurants were sit down, 19% were quick service or fast food, and 6% were cafeteria or buffet restaurants. Eighty-one percent of restaurants reported determining doneness of hamburgers by one or more subjective measures, and 49% reported that they never measure the final cook temperatures of hamburgers. At least two risky ground beef handling practices were observed in 53% of restaurants. Only 1% of restaurants reported purchasing irradiated ground beef, and 29% were unfamiliar with irradiated ground beef. Differences in risky ground beef handling policies and practices were noted for type of restaurant ownership (independently owned versus chain) and type of food service style (sit down versus quick service or fast food). This study revealed the pervasiveness of risky ground beef handling policies and practices in restaurants and the need for educational campaigns targeting food workers and managers. These results highlight the importance of continued efforts to reduce the prevalence of E. coli O157:H7 in ground beef.

Computer-Mediated Counter-Arguments and Individual Learning

Science.gov (United States)

Hsu, Jack Shih-Chieh; Huang, Hsieh-Hong; Linden, Lars P.

2011-01-01

This study explores a de-bias function for a decision support systems (DSS) that is designed to help a user avoid confirmation bias by increasing the user's learning opportunities. Grounded upon the theory of mental models, the use of DSS is viewed as involving a learning process, whereby a user is directed to build mental models so as to reduce…

The effectiveness of E- learning in learning: A review of the literature

Directory of Open Access Journals (Sweden)

Mousazadeh Somayeh

2016-02-01

Full Text Available Entry to the information age and effective life in information-oriented society requires an understanding of its characteristics. One of the social institutions that will undergo extensive changes at this age is general and higher education and training institutions. The aim of this review study is to evaluate the effectiveness of e learning in learning. This paper is a review study carried out using Medline and CINAHL databases and Google search engine. The studies used include review articles and English meta-analysis of language.Of the retrieved results,38 documents including articles, books and web sites were investigated and classified. At first, the background of e learning was studied history and in the next section its effectiveness in learning was briefly examined. The overall benefits of e-learning include the promotion of learning, independence and individual satisfaction, learning at anytime, anywhere and with any background, learning without the same prerequisites, speed and process of learning due to individual needs, individual learning along with cooperative learning, saving time and costs significantly, the possibility of teaching and learning for all people, mutual teaching and learning, getting quick results in learning, learning more by using multimedia and maintaining resources and reducing environmental and audio pollution. The results of studies suggest positive effects of e-learning on learning thus it is suggested that this approach be used more in education, which requires building the required grounds.

Working abroad, working with others: How firms learn to operate international joint ventures

NARCIS (Netherlands)

H.G. Barkema (Harry); O. Shenkar (Oded); G.A.M. Vermeulen (Freek); J.H.J. Bell (John)

1997-01-01

textabstractSuccessful international joint ventures entail both learning to operate across national boundaries and learning to cooperate. Hypotheses grounded in organizational learning theory were tested with event-history analysis and data on 1,493 expansions of 25 large Dutch firms between 1966

Grounded theory.

Science.gov (United States)

Harris, Tina

2015-04-29

Grounded theory is a popular research approach in health care and the social sciences. This article provides a description of grounded theory methodology and its key components, using examples from published studies to demonstrate practical application. It aims to demystify grounded theory for novice nurse researchers, by explaining what it is, when to use it, why they would want to use it and how to use it. It should enable nurse researchers to decide if grounded theory is an appropriate approach for their research, and to determine the quality of any grounded theory research they read.

Ground cross-modal impedance as a tool for analyzing ground/plate interaction and ground wave propagation.

Science.gov (United States)

Grau, L; Laulagnet, B

2015-05-01

An analytical approach is investigated to model ground-plate interaction based on modal decomposition and the two-dimensional Fourier transform. A finite rectangular plate subjected to flexural vibration is coupled with the ground and modeled with the Kirchhoff hypothesis. A Navier equation represents the stratified ground, assumed infinite in the x- and y-directions and free at the top surface. To obtain an analytical solution, modal decomposition is applied to the structure and a Fourier Transform is applied to the ground. The result is a new tool for analyzing ground-plate interaction to resolve this problem: ground cross-modal impedance. It allows quantifying the added-stiffness, added-mass, and added-damping from the ground to the structure. Similarity with the parallel acoustic problem is highlighted. A comparison between the theory and the experiment shows good matching. Finally, specific cases are investigated, notably the influence of layer depth on plate vibration.

Understanding Interorganizational Learning Based on Social Spaces and Learning Episodes

Directory of Open Access Journals (Sweden)

Anelise Rebelato Mozzato

2014-07-01

Full Text Available Different organizational settings have been gaining ground in the world economy, resulting in a proliferation of different forms of strategic alliances that translate into a growth in the number of organizations that have started to deal with interorganizational relationships with different actors. These circumstances reinforce Crossan, Lane, White and Djurfeldt (1995 and Crossan, Mauer and White (2011 in exploring what authors refer to as the fourth, interorganizational, level of learning. These authors, amongst others, suggest that the process of interorganizational learning (IOL warrants investigation, as its scope of analysis needs widening and deepening. Therefore, this theoretical essay is an attempt to understand IOL as a dynamic process found in interorganizational cooperative relationships that can take place in different structured and unstructured social spaces and that can generate learning episodes. According to this view, IOL is understood as part of an organizational learning continuum and is analyzed within the framework of practical rationality in an approach that is less cognitive and more social-behavioral.

Competition-strength-dependent ground suppression in figure-ground perception.

Science.gov (United States)

Salvagio, Elizabeth; Cacciamani, Laura; Peterson, Mary A

2012-07-01

Figure-ground segregation is modeled as inhibitory competition between objects that might be perceived on opposite sides of borders. The winner is the figure; the loser is suppressed, and its location is perceived as shapeless ground. Evidence of ground suppression would support inhibitory competition models and would contribute to explaining why grounds are shapeless near borders shared with figures, yet such evidence is scarce. We manipulated whether competition from potential objects on the ground side of figures was high (i.e., portions of familiar objects were potentially present there) or low (novel objects were potentially present). We predicted that greater competition would produce more ground suppression. The results of two experiments in which suppression was assessed via judgments of the orientation of target bars confirmed this prediction; a third experiment showed that ground suppression is short-lived. Our findings support inhibitory competition models of figure assignment, in particular, and models of visual perception entailing feedback, in general.

Regional analysis of ground and above-ground climate

Science.gov (United States)

1981-12-01

The regional suitability of underground construction as a climate control technique is discussed with reference to (1) a bioclimatic analysis of long term weather data for 29 locations in the United States to determine appropriate above ground climate control techniques, (2) a data base of synthesized ground temperatures for the coterminous United States, and (3) monthly dew point ground temperature comparisons for identifying the relative likelihood of condensation from one region to another. It is concluded that the suitability of Earth tempering as a practice and of specific Earth sheltered design stereotypes varies geographically; while the subsurface almost always provides a thermal advantage on its own terms when compared to above ground climatic data, it can, nonetheless, compromise the effectiveness of other, regionally more important climate control techniques. Reviews of above and below ground climate mapping schemes related to human comfort and architectural design, and detailed description of a theoretical model of ground temperature, heat flow, and heat storage in the ground are included. Strategies of passive climate control are presented in a discussion of the building bioclimatic analysis procedure which has been applied in a computer analysis of 30 years of weather data for each of 20 locations in the United States.

Regional analysis of ground and above-ground climate

Energy Technology Data Exchange (ETDEWEB)

1981-12-01

The regional suitability of underground construction as a climate control technique is discussed with reference to (1) a bioclimatic analysis of long-term weather data for 29 locations in the United States to determine appropriate above ground climate control techniques, (2) a data base of synthesized ground temperatures for the coterminous United States, and (3) monthly dew point ground temperature comparisons for identifying the relative likelihood of condensation from one region to another. It is concluded that the suitability of earth tempering as a practice and of specific earth-sheltered design stereotypes varies geographically; while the subsurface almost always provides a thermal advantage on its own terms when compared to above ground climatic data, it can, nonetheless, compromise the effectiveness of other, regionally more important climate control techniques. Also contained in the report are reviews of above and below ground climate mapping schemes related to human comfort and architectural design, and detailed description of a theoretical model of ground temperature, heat flow, and heat storage in the ground. Strategies of passive climate control are presented in a discussion of the building bioclimatic analysis procedure which has been applied in a computer analysis of 30 years of weather data for each of 29 locations in the United States.

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

Science.gov (United States)

Southern Regional Education Board (SREB), 2015

2015-01-01

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

Using Appreciative Inquiry and Dialogical Learning to Explore Dominant Paradigms

Science.gov (United States)

Neville, Mary Grace

2008-01-01

Experiential learning theory, conversational learning, and seminar practices combine to shape an educational experience that is grounded in principles of appreciative inquiry. The seminar, taught to undergraduate business majors, seeks to encourage students to explore their underlying assumptions about business in society. Because postindustrial…

Parenting as a Vocation: Lifelong Learning Can Begin in the Home.

Science.gov (United States)

Stehlik, Tom

2003-01-01

Reviews theories of adult learning over the lifespan grounded in anthroposophy, the philosophy of Rudolf Steiner's Waldorf Schools. Examines parenting as a vocation through this perspective and the implications for the learning needs of parents. (Contains 35 references.) (SK)

Theoretically Based Pedagogical Strategies Leading to Deep Learning in Asynchronous Online Gerontology Courses

Science.gov (United States)

Majeski, Robin; Stover, Merrily

2007-01-01

Online learning has enjoyed increasing popularity in gerontology. This paper presents instructional strategies grounded in Fink's (2003) theory of significant learning designed for the completely asynchronous online gerontology classroom. It links these components with the development of mastery learning goals and provides specific guidelines for…

Data Mining Practical Machine Learning Tools and Techniques

CERN Document Server

Witten, Ian H; Hall, Mark A

2011-01-01

Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place

Radical-Local Teaching and Learning

DEFF Research Database (Denmark)

Hedegaard, Mariane; Chaiklin, Seth

radical-local teaching and learning approach. The first half of the book introduces the idea of radical-local teaching and learning and develops the theoretical background for this perspective, drawing on the cultural-historical research tradition, particularly from Vygotsky, El'konin, Davydov......, and Aidarova. The second half of the book addresses the central concern of radical-local teaching and learning - how to relate educational practices to children's specific historical and cultural conditions. The experiment was conducted for an academic year in an afterschool programme in the East Harlem......Radical-Local Teaching and Learning presents a theoretical perspective for analyzing and planning educational programmes for schoolchildren. To realize both general societal interests and worthwhile personal development, the content of educational programmes for children must be grounded...

Facilitating learning through an international virtual collaborative practice: A case study.

Science.gov (United States)

Wihlborg, Monne; Friberg, Elizabeth E; Rose, Karen M; Eastham, Linda

2018-02-01

Internationalisation of higher education involving information and communication technology such as e-learning opens opportunities for innovative learning approaches across nations and cultures. Describe a case in practice of collaborative and transformative learning in relation to 'internationalisation on home grounds' with the broader learning objective of 'becoming aware and knowledgeable'. A mutually developed project established a virtual international collaborative exchange for faculty and students using a course management software (MOODLE) and open access technology (Adobe CONNECT). Two research universities in Sweden and the United States. Approximately 90 nursing students from each university per semester over several semesters. A collaborative process to develop a joint learning community to construct a virtual module and learning activity involving academics and nursing students in two countries using principles of meaning construction and negotiated learning. Developed possibilities for dealing with the challenges and finding strategies for a future higher education system that opens dialogues worldwide. Virtual international exchanges open innovative communication and learning contexts across nations and cultures. Internationalisation is so much more than students and teachers' mobility. 'Internationalisation on home grounds' (internationalisation for all) should receive more attention to support faculty and student collaboration, learning, and professional development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computational neuroanatomy using brain deformations: From brain parcellation to multivariate pattern analysis and machine learning.

Science.gov (United States)

Davatzikos, Christos

2016-10-01

The past 20 years have seen a mushrooming growth of the field of computational neuroanatomy. Much of this work has been enabled by the development and refinement of powerful, high-dimensional image warping methods, which have enabled detailed brain parcellation, voxel-based morphometric analyses, and multivariate pattern analyses using machine learning approaches. The evolution of these 3 types of analyses over the years has overcome many challenges. We present the evolution of our work in these 3 directions, which largely follows the evolution of this field. We discuss the progression from single-atlas, single-registration brain parcellation work to current ensemble-based parcellation; from relatively basic mass-univariate t-tests to optimized regional pattern analyses combining deformations and residuals; and from basic application of support vector machines to generative-discriminative formulations of multivariate pattern analyses, and to methods dealing with heterogeneity of neuroanatomical patterns. We conclude with discussion of some of the future directions and challenges. Copyright © 2016. Published by Elsevier B.V.

The amygdala as a neurobiological target for ghrelin in rats: neuroanatomical, electrophysiological and behavioral evidence.

Directory of Open Access Journals (Sweden)

Mayte Alvarez-Crespo

Full Text Available Here, we sought to demonstrate that the orexigenic circulating hormone, ghrelin, is able to exert neurobiological effects (including those linked to feeding control at the level of the amygdala, involving neuroanatomical, electrophysiological and behavioural studies. We found that ghrelin receptors (GHS-R are densely expressed in several subnuclei of the amygdala, notably in ventrolateral (LaVL and ventromedial (LaVM parts of the lateral amygdaloid nucleus. Using whole-cell patch clamp electrophysiology to record from cells in the lateral amygdaloid nucleus, we found that ghrelin reduced the frequency of mEPSCs recorded from large pyramidal-like neurons, an effect that could be blocked by co-application of a ghrelin receptor antagonist. In ad libitum fed rats, intra-amygdala administration of ghrelin produced a large orexigenic response that lasted throughout the 4 hr of testing. Conversely, in hungry, fasted rats ghrelin receptor blockade in the amygdala significantly reduced food intake. Finally, we investigated a possible interaction between ghrelin's effects on feeding control and emotional reactivity exerted at the level of the amygdala. In rats allowed to feed during a 1-hour period between ghrelin injection and anxiety testing (elevated plus maze and open field, intra-amygdala ghrelin had no effect on anxiety-like behavior. By contrast, if the rats were not given access to food during this 1-hour period, a decrease in anxiety-like behavior was observed in both tests. Collectively, these data indicate that the amygdala is a valid target brain area for ghrelin where its neurobiological effects are important for food intake and for the suppression of emotional (anxiety-like behaviors if food is not available.

Environmental enrichment protects spatial learning and hippocampal neurons from the long-lasting effects of protein malnutrition early in life.

Science.gov (United States)

Soares, Roberto O; Horiquini-Barbosa, Everton; Almeida, Sebastião S; Lachat, João-José

2017-09-29

As early protein malnutrition has a critically long-lasting impact on the hippocampal formation and its role in learning and memory, and environmental enrichment has demonstrated great success in ameliorating functional deficits, here we ask whether exposure to an enriched environment could be employed to prevent spatial memory impairment and neuroanatomical changes in the hippocampus of adult rats maintained on a protein deficient diet during brain development (P0-P35). To elucidate the protective effects of environmental enrichment, we used the Morris water task and neuroanatomical analysis to determine whether changes in spatial memory and number and size of CA1 neurons differed significantly among groups. Protein malnutrition and environmental enrichment during brain development had significant effects on the spatial memory and hippocampal anatomy of adult rats. Malnourished but non-enriched rats (MN) required more time to find the hidden platform than well-nourished but non-enriched rats (WN). Malnourished but enriched rats (ME) performed better than the MN and similarly to the WN rats. There was no difference between well-nourished but non-enriched and enriched rats (WE). Anatomically, fewer CA1 neurons were found in the hippocampus of MN rats than in those of WN rats. However, it was also observed that ME and WN rats retained a similar number of neurons. These results suggest that environmental enrichment during brain development alters cognitive task performance and hippocampal neuroanatomy in a manner that is neuroprotective against malnutrition-induced brain injury. These results could have significant implications for malnourished infants expected to be at risk of disturbed brain development. Copyright © 2017 Elsevier B.V. All rights reserved.

A cognitively grounded measure of pronunciation distance.

Directory of Open Access Journals (Sweden)

Martijn Wieling

Full Text Available In this study we develop pronunciation distances based on naive discriminative learning (NDL. Measures of pronunciation distance are used in several subfields of linguistics, including psycholinguistics, dialectology and typology. In contrast to the commonly used Levenshtein algorithm, NDL is grounded in cognitive theory of competitive reinforcement learning and is able to generate asymmetrical pronunciation distances. In a first study, we validated the NDL-based pronunciation distances by comparing them to a large set of native-likeness ratings given by native American English speakers when presented with accented English speech. In a second study, the NDL-based pronunciation distances were validated on the basis of perceptual dialect distances of Norwegian speakers. Results indicated that the NDL-based pronunciation distances matched perceptual distances reasonably well with correlations ranging between 0.7 and 0.8. While the correlations were comparable to those obtained using the Levenshtein distance, the NDL-based approach is more flexible as it is also able to incorporate acoustic information other than sound segments.

Grounded in Theory: Immersing Preservice Teachers in Technology-Mediated Learning

Science.gov (United States)

DeGennaro, Donna

2010-01-01

The integration of technology into preservice teacher education continues to be emphasized as important. The hope is that if future teachers obtain technology skills they will design meaningful technology-mediated learning experiences for their students. However, gaining technology skills alone does not ensure the ability to envision and employ…

Implications of an assessment of potential organic contamination of ground water at an inactive uranium mill

International Nuclear Information System (INIS)

Price, J.B.

1986-01-01

Laws and regulations concerning remedial actions at inactive uranium mills explicitly recognize radiological and nonradiological hazards and may implicitly recognize the potential presence of hazardous wastes at these mill sites. Ground-water studies at the sites have placed an increasing emphasis on screening for priority pollutants. The Grand Junction, Colorado, mill site was deemed to have a high potential for the presence of organic compounds in ground water, and was chosen as a prototype for assessing the presence of organic compounds in ground water at inactive sites. Lessons learned from the assessment of organics at the Grand Junction site were used to develop a screening procedure for other inactive mill sites

Attitudes of health care students about computer-aided neuroanatomy instruction.

Science.gov (United States)

McKeough, D Michael; Bagatell, Nancy

2009-01-01

This study examined students' attitudes toward computer-aided instruction (CAI), specifically neuroanatomy learning modules, to assess which components were primary in establishing these attitudes and to discuss the implications of these attitudes for successfully incorporating CAI in the preparation of health care providers. Seventy-seven masters degree, entry-level, health care professional students matriculated in an introductory neuroanatomy course volunteered as subjects for this study. Students independently reviewed the modules as supplements to lecture and completed a survey to evaluate teaching effectiveness. Responses to survey statements were compared across the learning modules to determine if students viewed the modules differently. Responses to individual survey statements were averaged to measure the strength of agreement or disagreement with the statement. Responses to open-ended questions were theme coded, and frequencies and percentages were calculated for each. Students saw no differences between the learning modules. Students perceived the learning modules as valuable; they enjoyed using the modules but did not prefer CAI over traditional lecture format. The modules were useful in learning or reinforcing neuroanatomical concepts and improving clinical problem-solving skills. Students reported that the visual representation of the neuroanatomical systems, computer animation, ability to control the use of the modules, and navigational fidelity were key factors in determining attitudes. The computer-based learning modules examined in this study were effective as adjuncts to lecture in helping entry-level health care students learn and make clinical applications of neuroanatomy information.

iPads in K-12 Schools: A Grounded Theory Study of Value

Science.gov (United States)

Townsend, Mary Beth

2017-01-01

This qualitative grounded theory study investigated the value of iPads in K-12 schools when used in one-to-one ratios. The purpose of the study was to understand the perspectives of teachers using iPads in one-to-one ratios for teaching and learning in the classroom and administrators responsible for the implementation of these devices. The…

An attempt to model the relationship between MMI attenuation and engineering ground-motion parameters using artificial neural networks and genetic algorithms

Directory of Open Access Journals (Sweden)

G-A. Tselentis

2010-12-01

Full Text Available Complex application domains involve difficult pattern classification problems. This paper introduces a model of MMI attenuation and its dependence on engineering ground motion parameters based on artificial neural networks (ANNs and genetic algorithms (GAs. The ultimate goal of this investigation is to evaluate the target-region applicability of ground-motion attenuation relations developed for a host region based on training an ANN using the seismic patterns of the host region. This ANN learning is based on supervised learning using existing data from past earthquakes. The combination of these two learning procedures (that is, GA and ANN allows us to introduce a new method for pattern recognition in the context of seismological applications. The performance of this new GA-ANN regression method has been evaluated using a Greek seismological database with satisfactory results.

Ground water '89

International Nuclear Information System (INIS)

1989-01-01

The proceedings of the 5th biennial symposium of the Ground Water Division of the Geological Society of South Africa are presented. The theme of the symposium was ground water and mining. Papers were presented on the following topics: ground water resources; ground water contamination; chemical analyses of ground water and mining and its influece on ground water. Separate abstracts were prepared for 5 of the papers presented. The remaining papers were considered outside the subject scope of INIS

Retrieval evaluation and distance learning from perceived similarity between endomicroscopy videos.

Science.gov (United States)

André, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2011-01-01

Evaluating content-based retrieval (CBR) is challenging because it requires an adequate ground-truth. When the available groundtruth is limited to textual metadata such as pathological classes, retrieval results can only be evaluated indirectly, for example in terms of classification performance. In this study we first present a tool to generate perceived similarity ground-truth that enables direct evaluation of endomicroscopic video retrieval. This tool uses a four-points Likert scale and collects subjective pairwise similarities perceived by multiple expert observers. We then evaluate against the generated ground-truth a previously developed dense bag-of-visual-words method for endomicroscopic video retrieval. Confirming the results of previous indirect evaluation based on classification, our direct evaluation shows that this method significantly outperforms several other state-of-the-art CBR methods. In a second step, we propose to improve the CBR method by learning an adjusted similarity metric from the perceived similarity ground-truth. By minimizing a margin-based cost function that differentiates similar and dissimilar video pairs, we learn a weight vector applied to the visual word signatures of videos. Using cross-validation, we demonstrate that the learned similarity distance is significantly better correlated with the perceived similarity than the original visual-word-based distance.

Soft Computing Approach to Evaluate and Predict Blast-Induced Ground Vibration

Science.gov (United States)

Khandelwal, Manoj

2010-05-01

the same excavation site, different predictors give different values of safe PPV vis-à-vis safe charge per delay. There is no uniformity in the predicted result by different predictors. All vibration predictor equations have their site specific constants. Therefore, they cannot be used in a generalized way with confidence and zero level of risk. To overcome on this aspect new soft computing tools like artificial neural network (ANN) has attracted because of its ability to learn from the pattern acquainted before. ANN has the ability to learn from patterns acquainted before. It is a highly interconnected network of a large number of processing elements called neurons in an architecture inspired by the brain. ANN can be massively parallel and hence said to exhibit parallel distributed processing. Once, the network has been trained, with sufficient number of sample data sets, it can make reliable and trustworthy predictions on the basis of its previous learning, about the output related to new input data set of similar pattern. This paper deals the application of ANN for the prediction of ground vibration by taking into consideration of maximum charge per delay and distance between blast face to monitoring point. To investigate the appropriateness of this approach, the predictions by ANN have been also compared with other vibration predictor equations.

A Lifespan Perspective on Cooperative Education Learning: A Grounded Theory

Science.gov (United States)

Linn, Patricia

2015-01-01

This qualitative study sits at the intersection of two trends in vocational education. The first trend is a narrative approach to understanding cooperative education learning; the second is a movement away from career development theories toward the view that individuals use work experiences to help construct their lives. Both trends view learning…

Socially Challenged Collaborative Learning of Secondary School Students in Singapore

Science.gov (United States)

Pang, Christopher; Lau, Jesslyn; Seah, Chong Poh; Cheong, Linda; Low, Audrey

2018-01-01

Using a grounded theory research design, this paper examined the collaborative learning experiences of secondary school students in Singapore. The core phenomenon that emerged was the need for social interactions in collaborative learning, both in classroom and online settings. Educators often take for granted that effective collaborative learning…

Neural network regulation driven by autonomous neural firings

Science.gov (United States)

Cho, Myoung Won

2016-07-01

Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

Compositional symbol grounding for motor patterns.

Science.gov (United States)

Greco, Alberto; Caneva, Claudio

2010-01-01

We developed a new experimental and simulative paradigm to study the establishing of compositional grounded representations for motor patterns. Participants learned to associate non-sense arm motor patterns, performed in three different hand postures, with non-sense words. There were two group conditions: in the first (compositional), each pattern was associated with a two-word (verb-adverb) sentence; in the second (holistic), each same pattern was associated with a unique word. Two experiments were performed. In the first, motor pattern recognition and naming were tested in the two conditions. Results showed that verbal compositionality had no role in recognition and that the main source of confusability in this task came from discriminating hand postures. As the naming task resulted too difficult, some changes in the learning procedure were implemented in the second experiment. In this experiment, the compositional group achieved better results in naming motor patterns especially for patterns where hand postures discrimination was relevant. In order to ascertain the differential effect, upon this result, of memory load and of systematic grounding, neural network simulations were also made. After a basic simulation that worked as a good model of subjects performance, in following simulations the number of stimuli (motor patterns and words) was increased and the systematic association between words and patterns was disrupted, while keeping the same number of words and syntax. Results showed that in both conditions the advantage for the compositional condition significantly increased. These simulations showed that the advantage for this condition may be more related to the systematicity rather than to the mere informational gain. All results are discussed in connection to the possible support of the hypothesis of a compositional motor representation and toward a more precise explanation of the factors that make compositional representations working.

Compositional symbol grounding for motor patterns

Directory of Open Access Journals (Sweden)

Alberto eGreco

2010-11-01

Full Text Available We developed a new experimental and simulative paradigm to study the establishing of compositional grounded representations for motor patterns. Participants learned to associate nonsense arm motor patterns, performed in three different hand postures, with nonsense words. There were two group conditions: in the first (compositional, each pattern was associated with a two-word (verb-adverb sentence; in the second (holistic, each same pattern was associated with a unique word. Two experiments were performed. In the first, motor pattern recognition and naming were tested in the two conditions. Results showed that verbal compositionality had no role in recognition and that the main source of confusability in this task came from discriminating hand postures. As the naming task resulted too difficult, some changes in the learning procedure were implemented in the second experiment. In this experiment, the compositional group achieved better results in naming motor patterns especially for patterns where hand postures discrimination was relevant. In order to ascertain the differential effect, upon this result, of memory load and of systematic grounding, neural network simulations were also made. After a basic simulation that worked as a good model of subjects performance, in following simulations the number of stimuli (motor patterns and words was increased and the systematic association between words and patterns was disrupted, while keeping the same number of words and syntax. Results showed that in both conditions the advantage for the compositional condition significantly increased. These simulations showed that the advantage for this condition may be more related to the systematicity rather than to the mere informational gain. All results are discussed in connection to the possible support of the hypothesis of a compositional motor representation and towards a more precise explanation of the factors that make compositional representations working.

Access to E-learning in the Nigerian university system (NUS): a case ...

African Journals Online (AJOL)

In developing countries, the application of electronic learning (e-learning) in the educational system is yet to gain much ground. This study therefore seeks to survey the extent to which elearning is applied in University of Calabar for effective teaching and learning processes. The purpose of this paper is to give a brief insight ...

Real-Time and Seamless Monitoring of Ground-Level PM2.5 Using Satellite Remote Sensing

Science.gov (United States)

Li, Tongwen; Zhang, Chengyue; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei

2018-04-01

Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is still challenging. First, the previously used polar-orbiting satellite observations, which can be usually acquired only once per day, are hard to monitor PM2.5 in real time. Second, many data gaps exist in satellitederived PM2.5 due to the cloud contamination. In this paper, the hourly geostationary satellite (i.e., Harawari-8) observations were adopted for the real-time monitoring of PM2.5 in a deep learning architecture. On this basis, the satellite-derived PM2.5 in conjunction with ground PM2.5 measurements are incorporated into a spatio-temporal fusion model to fill the data gaps. Using Wuhan Urban Agglomeration as an example, we have successfully derived the real-time and seamless PM2.5 distributions. The results demonstrate that Harawari-8 satellite-based deep learning model achieves a satisfactory performance (out-of-sample cross-validation R2 = 0.80, RMSE = 17.49 μg/m3) for the estimation of PM2.5. The missing data in satellite-derive PM2.5 are accurately recovered, with R2 between recoveries and ground measurements of 0.75. Overall, this study has inherently provided an effective strategy for the realtime and seamless monitoring of ground-level PM2.5.

Merging Problem-Based Learning with Simulation-Based Learning in the Medical Undergraduate Curriculum: The PAIRED Framework for Enhancing Lifelong Learning

Science.gov (United States)

Koh, Jansen

2016-01-01

Lifelong learning is an essential trait that is expected of every physician. The CanMeds 2005 Physician Competency Framework emphasizes lifelong learning as a key competency that physicians must achieve in becoming better physicians. However, many physicians are not competent at engaging in lifelong learning. The current medical education system is deficient in preparing medical students to develop and carry out their own lifelong learning curriculum upon graduation. Despite understanding how physicians learn at work, medical students are not trained to learn while working. Similarly, although barriers to lifelong learning are known, medical students are not adequately skilled in overcoming these barriers. Learning to learn is just as important, if not more, as acquiring the skills and knowledge required of a physician. The medical undergraduate curriculum lacks a specific learning strategy to prepare medical students in becoming an adept lifelong learner. In this article, we propose a learning strategy for lifelong learning at the undergraduate level. In developing this novel strategy, we paid particular attention to two parameters. First, this strategy should be grounded on literature describing a physician’s lifelong learning process. Second, the framework for implementing this strategy must be based on existing undergraduate learning strategies to obviate the need for additional resources, learner burden, and faculty time. In this paper, we propose a Problem, Analysis, Independent Research Reporting, Experimentation Debriefing (PAIRED) framework that follows the learning process of a physician and serves to synergize the components of problem-based learning and simulation-based learning in specifically targeting the barriers to lifelong learning. PMID:27446767

Reframing Photovoice to Boost Its Potential for Learning Research

Directory of Open Access Journals (Sweden)

Lucian Ciolan

2017-04-01

Full Text Available Visual methods are not new within education research field, but they are certainly an innovative approach, especially in higher education where students’ voice is understood as a central need. In this positional article, the authors intend to accomplish two key objectives. First, the article aims to emphasize that visual method, especially photovoice, can be enriching for studying the ways students engage in learning activities and support authentic conversations about how learning takes place and what students are thinking about this process (metacognition. The second objective is to set theoretical and methodological grounds to apply visually based methods such as photovoice and bubble dialogue in education research, particularly in learning research area. The considerations regarding specific methodological aspects are based on the discussion of a study conducted by using photovoice methodology. The authors suggest that participatory analysis and particularly interpretative phenomenological analysis are appropriate to complete the process of data analysis. The article, therefore, contributes to expanding knowledge about specific visual methods and set the ground for methodological innovation in learning research.

Eyes On the Ground: Year 2 Assessment.

Energy Technology Data Exchange (ETDEWEB)

Brost, Randolph; Little, Charles Q.; McDaniel, Michael; McLendon, William C.,; Wade, James Rokwel

2018-03-01

The goal of the Eyes On the Ground project is to develop tools to aid IAEA inspectors. Our original vision was to produce a tool that would take three-dimensional measurements of an unknown piece of equipment, construct a semantic representation of the measured object, and then use the resulting data to infer possible explanations of equipment function. We report our tests of a 3-d laser scanner to obtain 3-d point cloud data, and subsequent tests of software to convert the resulting point clouds into primitive geometric objects such as planes and cylinders. These tests successfully identified pipes of moderate diameter and planar surfaces, but also incurred significant noise. We also investigated the IAEA inspector task context, and learned that task constraints may present significant obstacles to using 3-d laser scanners. We further learned that equipment scale and enclosing cases may confound our original goal of equipment diagnosis. Meanwhile, we also surveyed the rapidly evolving field of 3-d measurement technology, and identified alternative sensor modalities that may prove more suitable for inspector use in a safeguards context. We conclude with a detailed discussion of lessons learned and the resulting implications for project goals. Approved for public release; further dissemination unlimited.

Does perceptual learning require consciousness or attention?

Science.gov (United States)

Meuwese, Julia D I; Post, Ruben A G; Scholte, H Steven; Lamme, Victor A F

2013-10-01

It has been proposed that visual attention and consciousness are separate [Koch, C., & Tsuchiya, N. Attention and consciousness: Two distinct brain processes. Trends in Cognitive Sciences, 11, 16-22, 2007] and possibly even orthogonal processes [Lamme, V. A. F. Why visual attention and awareness are different. Trends in Cognitive Sciences, 7, 12-18, 2003]. Attention and consciousness converge when conscious visual percepts are attended and hence become available for conscious report. In such a view, a lack of reportability can have two causes: the absence of attention or the absence of a conscious percept. This raises an important question in the field of perceptual learning. It is known that learning can occur in the absence of reportability [Gutnisky, D. A., Hansen, B. J., Iliescu, B. F., & Dragoi, V. Attention alters visual plasticity during exposure-based learning. Current Biology, 19, 555-560, 2009; Seitz, A. R., Kim, D., & Watanabe, T. Rewards evoke learning of unconsciously processed visual stimuli in adult humans. Neuron, 61, 700-707, 2009; Seitz, A. R., & Watanabe, T. Is subliminal learning really passive? Nature, 422, 36, 2003; Watanabe, T., Náñez, J. E., & Sasaki, Y. Perceptual learning without perception. Nature, 413, 844-848, 2001], but it is unclear which of the two ingredients-consciousness or attention-is not necessary for learning. We presented textured figure-ground stimuli and manipulated reportability either by masking (which only interferes with consciousness) or with an inattention paradigm (which only interferes with attention). During the second session (24 hr later), learning was assessed neurally and behaviorally, via differences in figure-ground ERPs and via a detection task. Behavioral and neural learning effects were found for stimuli presented in the inattention paradigm and not for masked stimuli. Interestingly, the behavioral learning effect only became apparent when performance feedback was given on the task to measure learning

Learning through Music Festivals

Science.gov (United States)

Karlsen, Sidsel

2009-01-01

This article explores one particular music festival, the Festspel i Pite Alvdal, as a source of musical learning. It is grounded in the empirical data of a case study that was gathered through observation, a survey, in-depth interviews, documentation and archival records. The theoretical framework was taken from modernity theory, and the study's…

Paramedic Learning Style Preferences and Continuing Medical Education Activities: A Cross-Sectional Survey Study.

Science.gov (United States)

Staple, Louis; Carter, Alix; Jensen, Jan L; Walker, Mark

2018-01-01

Paramedics participate in continuing medical education (CME) to maintain their skills and knowledge. An understanding of learning styles is important for education to be effective. This study examined the preferred learning styles of ground ambulance paramedics and describes how their preferred learning styles relate to the elective CME activities these paramedics attend. All paramedics (n=1,036) employed in a provincial ground ambulance service were invited to participate in a survey containing three parts: demographics, learning style assessed by the Kolb Learning Style Inventory (LSI), and elective CME activity. 260 paramedics (25%) participated in the survey. Preferred learning styles were: assimilator, 28%; diverger, 25%; converger, 24%; and accommodator, 23%. Advanced life support (ALS) providers had a higher proportion of assimilators (36%), and basic life support (BLS) providers had a higher proportion of divergers (30%). The learning style categories of CME activities attended by paramedics were: assimilators, 25%; divergers, 26%; convergers, 25%; and accommodators, 24%. These results suggest that paramedics are a diverse group of learners, and learning style differs within their demographics. Paramedics attend CME activities that complement all learning styles. Organizations providing education opportunities to paramedics should consider paramedics a diverse learning group when designing their CME programs.

Stochastic Variational Learning in Recurrent Spiking Networks

Directory of Open Access Journals (Sweden)

Danilo eJimenez Rezende

2014-04-01

Full Text Available The ability to learn and perform statistical inference with biologically plausible recurrent network of spiking neurons is an important step towards understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators conveying information about ``novelty on a statistically rigorous ground.Simulations show that our model is able to learn bothstationary and non-stationary patterns of spike trains.We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.

Stochastic variational learning in recurrent spiking networks.

Science.gov (United States)

Jimenez Rezende, Danilo; Gerstner, Wulfram

2014-01-01

The ability to learn and perform statistical inference with biologically plausible recurrent networks of spiking neurons is an important step toward understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators) conveying information about "novelty" on a statistically rigorous ground. Simulations show that our model is able to learn both stationary and non-stationary patterns of spike trains. We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.

The arcuate fasciculus network and verbal deficits in psychosis

Directory of Open Access Journals (Sweden)

Kenney Joanne P.M.

2017-11-01

Full Text Available Verbal learning (VL and fluency (VF are prominent cognitive deficits in psychosis, of which the precise neuroanatomical contributions are not fully understood. We investigated the arcuate fasciculus (AF and its associated cortical regions to identify structural abnormalities contributing to these verbal impairments in early stages of psychotic illness.

The Impact of Labelling and Segregation on Adolescent Literacy Learning

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McCloskey, Erin

2011-01-01

This qualitative case study, grounded in disability studies in education, explores the literacy development of an adolescent student, described by school officials as learning disabled and a non-reader. The researcher highlights how this student learned to connect to books based on an apprenticeship model. Additionally, the acknowledgement of the…

Can E-learning change work practices?

DEFF Research Database (Denmark)

Noesgaard, Signe Schack

2016-01-01

Stand-alone e-learning is unlikely to change work practices. This claim contrasts with a comprehensive body of research arguing that e-learning is at least as effective as face-to-face instruction in improving work performance. Such a comparison is, however, problematic. On the one hand, it relies...... on the premise that face-to-face instruction is effective in changing work behaviors. This article argues that instruction—whether e-learning, face-to-face, or a blend of both—cannot stand alone. Individualized on-the-job scaffolding of employees is needed for meaningful learning transfer and sustainable...... behavior change to occur. On the other hand, e-learning can be as important as face-to-face instruction in preparing the ground for advancing work practices, when e-learning is designed in acknowledgement of its strength and limitations. In outlining the above arguments, this article contributes a four...

A New Design Approach to Game-Based learning

DEFF Research Database (Denmark)

Larsen, Lasse Juel

2012-01-01

to ground the student’s reason to learn. This paper proposes a different approach: using visualisation in immersive 3D worlds as both documentation of learning progress and as a reward system which motivates further learning. The overall design idea is to build a game based learning system from three......This paper puts forward a new design perspective for gamebased learning. The general idea is to abandon the long sought-after dream of designing a closed learning system, where students in both primary and secondary school could learn – without the interference of teachers – whatever subject......-based learning system, but will also confront aspects of modern learning theory, especially the notion of reference between the content of an assignment and the reality with which it should or could be connected (situated learning). The second idea promotes a way of tackling the common experience of the average...

Social media marketing as an entrepreneurial learning process

OpenAIRE

Lagrosen, Stefan; Josefsson, Pernilla

2011-01-01

The purpose for this paper is to explore social media marketing fromthe perspective of entrepreneurial learning. The theoretical basis consists ofcontributions from the fields of organisational learning and entrepreneurship.An empirical study involving ten companies has been carried out. Thedata were analysed with methods inspired by grounded theory. Categoriesdescribing the companies’ social media presence from an entrepreneuriallearning perspective are provided. The value of using organisat...

Zoology Students' Experiences of Collaborative Enquiry in Problem-Based Learning

Science.gov (United States)

Harland, Tony

2002-01-01

This paper presents an action-research case study that focuses on experiences of collaboration in a problem-based learning (PBL) course in Zoology. Our PBL model was developed as a research activity in partnership with a commercial organisation. Consequently, learning was grounded in genuine situations of practice in which a high degree of…

Defining a middle ground for philosophers and production: bioethics.

Science.gov (United States)

Davis, S L; Croney, C C

2004-03-01

From the perspective of most animal scientists and producers, animal agriculture has become increasingly contentious over the last 10 to 20 years. Furthermore, our critics seem to be extremists whose views are biased and unreasonable. But guess what? The critics say the same thing about animal producers and scientists (us). So where is the middle ground and how do we get there? Should we even worry about trying to define the middle ground? Are these contentious issues a fad that will go away? Are these "extremist" critics so far outside reason that they will be ignored by society? Ignoring "them" is not likely to work because we have seen society changing its mind (developing a new social ethic) with regard to farm animals, in part because of what these critics are saying. As a result, it is vitally important for us to know and understand what is happening and why. For example, there isn't just one voice among the critics. There is actually a spectrum of opinion among the group which conventional agriculturalists usually call their critics. The WCC-204 committee generally agrees that the key to finding the middle ground between what is perceived as a polarized set of issues between "us" (animal scientists and producers) and "them" (philosopher critics) is for both sides to learn about the reasons why each side says what they do. Only then can all parties rationally begin to identify where the middle ground lies.

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

Science.gov (United States)

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.

Enhancing in-Museum Informal Learning by Augmenting Artworks with Gesture Interactions and AIED Paradigms

DEFF Research Database (Denmark)

Blanchard, Emmanuel G.; Zanciu, Alin-Nicolae; Mahmoud, Haydar

2014-01-01

This paper presents a computer-supported approach for providing ‘enhanced’ discovery learning in informal settings like museums. It is grounded on a combination of gesture-based interactions and artwork-embedded AIED paradigms, and is implemented through a distributed architecture.......This paper presents a computer-supported approach for providing ‘enhanced’ discovery learning in informal settings like museums. It is grounded on a combination of gesture-based interactions and artwork-embedded AIED paradigms, and is implemented through a distributed architecture....

3-D vision and figure-ground separation by visual cortex.

Science.gov (United States)

Grossberg, S

1994-01-01

A neural network theory of three-dimensional (3-D) vision, called FACADE theory, is described. The theory proposes a solution of the classical figure-ground problem for biological vision. It does so by suggesting how boundary representations and surface representations are formed within a boundary contour system (BCS) and a feature contour system (FCS). The BCS and FCS interact reciprocally to form 3-D boundary and surface representations that are mutually consistent. Their interactions generate 3-D percepts wherein occluding and occluded object parts are separated, completed, and grouped. The theory clarifies how preattentive processes of 3-D perception and figure-ground separation interact reciprocally with attentive processes of spatial localization, object recognition, and visual search. A new theory of stereopsis is proposed that predicts how cells sensitive to multiple spatial frequencies, disparities, and orientations are combined by context-sensitive filtering, competition, and cooperation to form coherent BCS boundary segmentations. Several factors contribute to figure-ground pop-out, including: boundary contrast between spatially contiguous boundaries, whether due to scenic differences in luminance, color, spatial frequency, or disparity; partially ordered interactions from larger spatial scales and disparities to smaller scales and disparities; and surface filling-in restricted to regions surrounded by a connected boundary. Phenomena such as 3-D pop-out from a 2-D picture, Da Vinci stereopsis, 3-D neon color spreading, completion of partially occluded objects, and figure-ground reversals are analyzed. The BCS and FCS subsystems model aspects of how the two parvocellular cortical processing streams that join the lateral geniculate nucleus to prestriate cortical area V4 interact to generate a multiplexed representation of Form-And-Color-And-DEpth, or FACADE, within area V4. Area V4 is suggested to support figure-ground separation and to interact with

The Promise of Lifelong Learning

Science.gov (United States)

Gouthro, Patricia A.

2017-01-01

This paper explores how Peter Jarvis's work offers a comprehensive grounding in many of the key principles and insights offered through the field of adult education. His work directs us to the different factors--psychological, social, economic and political required for understanding lifelong learning contexts. As scholars and educators, he…

The Activity Theory Approach to Learning

Directory of Open Access Journals (Sweden)

Ritva Engeström

2014-12-01

Full Text Available In this paper the author offers a practical view of the theory-grounded research on education action. She draws on studies carried out at the Center for Research on Activity, Development and Learning (CRADLE at the University of Helsinki in Finland. In its work, the Center draws on cultural-historical activity theory (CHAT and is well-known for the theory of Expansive Learning and its more practical application called Developmental Work Research (DWR. These approaches are widely used to understand professional learning and have served as a theoreticaland methodological foundation for studies examining change and professional development in various human activities.

An e-learning approach to informed problem solving

Directory of Open Access Journals (Sweden)

Georg Weichhart

2012-06-01

Full Text Available When taking into account individualized learning processes not only content and interaction facilities need to be re-considered, but also the design of learning processes per se. Besides explicitness of learning objectives, interactive means of education need to enable intertwining content and communication elements as basic elements of active learning in a flexible way while preserving a certain structure of the learning process. Intelligibility Catchers are a theoretically grounded framework to enable such individualized processes. It allows learners and teachers agreeing and determining a desired learning outcome in written form. This type of e-learning contract enables students to individually explore content and participate in social interactions, while being guided by a transparent learning process structure. The developed implementation empowers learners in terms of creative problem-solving capabilities, and requires adaptation of classroom situations. The framework and its supporting semantic e-learning environment not only enables diverse learning and problem solving processes, but also supports the collaborative construction of e-learning contracts.

Reconstructing Constructivism: Causal Models, Bayesian Learning Mechanisms, and the Theory Theory

Science.gov (United States)

Gopnik, Alison; Wellman, Henry M.

2012-01-01

We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework…

Common Ground Between Three Cultures

Directory of Open Access Journals (Sweden)

Gloria Dunnivan

2009-12-01

Full Text Available The Triwizard program with Israel brought together students from three different communities: an Israeli Arab school, an Israeli Jewish school, and an American public school with few Jews and even fewer Muslims. The two Israeli groups met in Israel to find common ground and overcome their differences through dialogue and understanding. They communicated with the American school via technology such as video-conferencing, Skype, and emails. The program culminated with a visit to the U.S. The goal of the program was to embark upon a process that would bring about intercultural awareness and acceptance at the subjective level, guiding all involved to develop empathy and an insider's view of the other's culture. It was an attempt to have a group of Israeli high school students and a group of Arab Israeli students who had a fearful, distrustful perception of each other find common ground and become friends. TriWizard was designed to have participants begin a dialogue about issues, beliefs, and emotions based on the premise that cross-cultural training strategies that are effective in changing knowledge are those that engage the emotions, and actively develop empathy and an insider's views of another culture focused on what they have in common. Participants learned that they could become friends despite their cultural differences.

Structuring and Regulating Collaborative Learning in Higher Education with Wireless Networks and Mobile Tools

Science.gov (United States)

Jarvela, Sanna; Naykki, Piia; Laru, Jari; Luokkanen, Tiina

2007-01-01

In our recent research we have explored possibilities to scaffold collaborative learning in higher education with wireless networks and mobile tools. The pedagogical ideas are grounded on concepts of collaborative learning, including the socially shared origin of cognition, as well as self-regulated learning theory. This paper presents our three…

Design, Participation, and Social Change: What Design in Grassroots Spaces Can Teach Learning Scientists

Science.gov (United States)

Zavala, Miguel

2016-01-01

While a science of design (and theory of learning) is certainly useful in design-based research, a participatory design research framework presents an opening for learning scientists to rethink design and learning as processes. Grounded in the autoethnographic investigation of a grassroots organization's design of a local campaign, the author…

Secondary dystonia in a botulinum toxin clinic: clinical characteristics, neuroanatomical substrate and comparison with idiopathic dystonia.

Science.gov (United States)

Strader, Scott; Rodnitzky, Robert L; Gonzalez-Alegre, Pedro

2011-12-01

The analysis of patients with secondary dystonia has been valuable to explore the anatomical, pharmacological and physiological bases of this disorder. The goal of this study is to compare the clinical characteristics of patients with primary and secondary dystonia and analyze the neuroanatomical bases of a subgroup of patients with lesion-induced dystonia. We identified patients evaluated in our Botulinum Toxin Clinic from 1/2000 to 7/2009 with an ICD code for "dystonia". Medical records of all subjects were reviewed, recording demographic, clinical, therapeutic and neuroimaging data. A total of 230 patients were included in the study. Idiopathic/primary dystonia was diagnosed in 162 and secondary dystonia in 58, while in 10 the etiology was uncertain. We found a female predominance (2.4:1 and 1.9:1 for primary and secondary dystonia, respectively). The cervical region was most commonly affected in primary dystonia and the limbs in secondary cases. The age at presentation was higher in primary (54.4 ± 14.1) than secondary (49 ± 17.9) dystonia. Among patients with secondary dystonia, a focal lesion was the presumed etiology in 32, with localizing diagnostic studies available in 16. The most common lesions were strokes involving the corticospinal pathway. All of those patients exhibited limb dystonia, except one with cervical dystonia following a thalamic infarct. In conclusion, primary and secondary dystonias are more prevalent in women, suggesting a sex-related predisposition to the development of this movement disorder. Lesion-induced dystonia most frequently involves the limbs and is caused by lesions in the cerebral cortex and subcortical white matter. Copyright © 2011 Elsevier Ltd. All rights reserved.

Learning through Experience: The Transition from Doctoral Student to Social Work Educator

Science.gov (United States)

Oktay, Julianne S.; Jacobson, Jodi M.; Fisher, Elizabeth

2013-01-01

The researchers conducted an exploratory study using grounded theory qualitative research methods to examine experiences of social work doctoral students as they learned to teach ("N"?=?14). A core category, "learning through experience," representing a basic social process, was identified. The doctoral students experienced…

Investigating the neuroanatomical substrate of pathological laughing and crying in amyotrophic lateral sclerosis with multimodal neuroimaging techniques.

Science.gov (United States)

Christidi, Foteini; Karavasilis, Efstratios; Ferentinos, Panagiotis; Xirou, Sophia; Velonakis, Georgios; Rentzos, Michalis; Zouvelou, Vasiliki; Zalonis, Ioannis; Efstathopoulos, Efstathios; Kelekis, Nikolaos; Evdokimidis, Ioannis

2018-02-01

Pathological laughing and crying (PLC) is common in several neurological and psychiatric diseases and is associated with a distributed network involving the frontal cortex, the brainstem and cortico-pontine-cerebellar circuits. By applying multimodal neuroimaging approach, we examined the neuroanatomical substrate of PLC in a sample of patients with amyotrophic lateral sclerosis (ALS). We studied 56 non-demented ALS patients and 25 healthy controls (HC). PLC was measured in ALS using the Center of Neurologic Study Lability Scale (CNS-LS; cutoff score: 13). All participants underwent 3D-T1-weighted and 30-directional diffusion-weighted imaging at 3T. Voxel-based morphometry and tract-based spatial-statistics analysis was used to examine gray matter (GM) and white matter (WM) differences between ALS patients with and without PLC (ALS-PLC and ALS-nonPLC, respectively). Comparisons were restricted to regions with detected differences between ALS and HC, controlling for age, gender, total intracranial volume and depressive symptoms. In regions with significant differences between ALS and HC, ALS-PLC patients showed decreased GM volume in left orbitofrontal cortex, frontal operculum, and putamen and bilateral frontal poles, compared to ALS-nonPLC. They also had decreased fractional anisotropy in left cingulum bundle and posterior corona radiata. WM abnormalities were additionally detected in WM associative and ponto-cerebellar tracts (using a more liberal threshold). PLC in ALS is driven by both GM and WM abnormalities which highlight the role of circuits rather than isolated centers in the emergence of this condition. ALS is suggested as a useful natural experimental model to study PLC.

Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior

Science.gov (United States)

2006-09-28

navigate in an unstructured environment to a specific target or location. 15. SUBJECT TERMS autonomous vehicles , fuzzy logic, learning behavior...ANSI-Std Z39-18 Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior FINAL REPORT 9/28/2006 Dean B. Edwards Department...the future, as greater numbers of autonomous vehicles are employed, it is hoped that lower LONG-TERM GOALS Use LAGR (Learning Applied to Ground Robots

Functional neuroanatomy of amygdalohippocampal interconnections and their role in learning and memory.

Science.gov (United States)

McDonald, Alexander J; Mott, David D

2017-03-01

The amygdalar nuclear complex and hippocampal/parahippocampal region are key components of the limbic system that play a critical role in emotional learning and memory. This Review discusses what is currently known about the neuroanatomy and neurotransmitters involved in amygdalo-hippocampal interconnections, their functional roles in learning and memory, and their involvement in mnemonic dysfunctions associated with neuropsychiatric and neurological diseases. Tract tracing studies have shown that the interconnections between discrete amygdalar nuclei and distinct layers of individual hippocampal/parahippocampal regions are robust and complex. Although it is well established that glutamatergic pyramidal cells in the amygdala and hippocampal region are the major players mediating interconnections between these regions, recent studies suggest that long-range GABAergic projection neurons are also involved. Whereas neuroanatomical studies indicate that the amygdala only has direct interconnections with the ventral hippocampal region, electrophysiological studies and behavioral studies investigating fear conditioning and extinction, as well as amygdalar modulation of hippocampal-dependent mnemonic functions, suggest that the amygdala interacts with dorsal hippocampal regions via relays in the parahippocampal cortices. Possible pathways for these indirect interconnections, based on evidence from previous tract tracing studies, are discussed in this Review. Finally, memory disorders associated with dysfunction or damage to the amygdala, hippocampal region, and/or their interconnections are discussed in relation to Alzheimer's disease, posttraumatic stress disorder (PTSD), and temporal lobe epilepsy. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Classroom Habit(us) and Physical Co-presence in a Blended Learning Environment

DEFF Research Database (Denmark)

Borsotti, Valeria; Møllenbach, Emilie

2016-01-01

In this exploratory case study we map the educational practice of teachers and students in a professional master of Interaction Design. Through a grounded analysis of the context we describe and reflect on: 1) the use of digital learning tools in a blended learning environment, 2) co...

Medium-Based Design: Extending a Medium to Create an Exploratory Learning Environment

Science.gov (United States)

Rick, Jochen; Lamberty, K. K.

2005-01-01

This article introduces "medium-based" design -- an approach to creating "exploratory learning environments" using the method of "extending a medium". First, the characteristics of exploratory learning environments and medium-based design are described and grounded in related work. Particular attention is given to "extending a medium" --…

“What and How do we learn from LinkedIn Forums?”

DEFF Research Database (Denmark)

Broillet, Alexandra; Kampf, Constance Elizabeth; Emad, Sabine

2014-01-01

new interfaces and features, and c) social networking. These three interactions offer a preliminary understanding of the potential for LinkedIn forums as a lifelong learning space, and an innovation space where weak ties and transactive memory systems have the potential to affect multidisciplinary......This study examines several academic and professional LinkedIn forums, and using a grounded theory perspective, observes three key lifelong learning interactions for participants—a) problem solving through shared learning and helping processes,” b) a technical features learning center for learning...

A model of e-learning uptake and continuance in Higher Educational Institutions

OpenAIRE

Pinpathomrat, Nakarin

2015-01-01

To predict and explain E-learning usage in higher educational institutes (HEIs) better, this research conceptualized E-learning usage as two steps, E-learning uptake and continuance. The aim was to build a model of effective uptake and continuance of E-learning in HEIs, or ‘EUCH’.The EUCH model was constructed by applying five grounded theories: Unified Theory of Acceptance and Use of Technology (UTAUT); Keller’s ARCS model; Theory of Reasoned Action (TRA); Cognitive Dissonance Theory (CDT); ...

[Learning about social determinants of health through chronicles, using a virtual learning environment].

Science.gov (United States)

Restrepo-Palacio, Sonia; Amaya-Guio, Jairo

2016-01-01

To describe the contributions of a pedagogical strategy based on the construction of chronicles, using a Virtual Learning Environment for training medical students from Universidad de La Sabana on social determinants of health. Descriptive study with a qualitative approach. Design and implementation of a Virtual Learning Environment based on the ADDIE instructional model. A Virtual Learning Environment was implemented with an instructional design based on the five phases of the ADDIE model, on the grounds of meaningful learning and social constructivism, and through the narration of chronicles or life stories as a pedagogical strategy. During the course, the structural determinants and intermediaries were addressed, and nine chronicles were produced by working groups made up of four or five students, who demonstrated meaningful learning from real life stories, presented a coherent sequence, and kept a thread; 82% of these students incorporated in their contents most of the social determinants of health, emphasizing on the concepts of equity or inequity, equality or inequality, justice or injustice and social cohesion. A Virtual Learning Environment, based on an appropriate instructional design, allows to facilitate learning of social determinants of health through a constructivist pedagogical approach by analyzing chronicles or life stories created by ninth-semester students of medicine from Universidad de La Sabana.

Taylorism and the Logic of Learning Outcomes

Science.gov (United States)

Stoller, Aaron

2015-01-01

This essay examines the shared philosophical foundations of Fredrick W. Taylor's scientific management principles and the contemporary learning outcomes movement (LOM). It analyses the shared philosophical ground between the focal point of Taylor's system--"the task"--and the conceptualization and deployment of "learning…

Collaborative Learning Using a Project across Multiple Business Courses: A Cognitive Load and Knowledge Convergence Approach

Science.gov (United States)

Bhowmick, Sandeep; Chandra, Aruna; Harper, Jeffrey S.; Sweetin, Vernon

2015-01-01

Four business professors at a state university in the Midwestern United States launched a collaborative learning project grounded in cognitive learning theory and knowledge convergence theory with the objective of assessing student learning gains in cross-functional knowledge (CFK), course-related knowledge (CRK), and overall satisfaction with…

Large developing receptive fields using a distributed and locally reprogrammable address-event receiver.

Science.gov (United States)

Bamford, Simeon A; Murray, Alan F; Willshaw, David J

2010-02-01

A distributed and locally reprogrammable address-event receiver has been designed, in which incoming address-events are monitored simultaneously by all synapses, allowing for arbitrarily large axonal fan-out without reducing channel capacity. Synapses can change the address of their presynaptic neuron, allowing the distributed implementation of a biologically realistic learning rule, with both synapse formation and elimination (synaptic rewiring). Probabilistic synapse formation leads to topographic map development, made possible by a cross-chip current-mode calculation of Euclidean distance. As well as synaptic plasticity in rewiring, synapses change weights using a competitive Hebbian learning rule (spike-timing-dependent plasticity). The weight plasticity allows receptive fields to be modified based on spatio-temporal correlations in the inputs, and the rewiring plasticity allows these modifications to become embedded in the network topology.

GROUNDED THEORY METHODOLOGY and GROUNDED THEORY RESEARCH in TURKEY

OpenAIRE

ARIK, Ferhat; ARIK, Işıl Avşar

2016-01-01

This research discusses the historical development of the Grounded Theory Methodology, which is one of the qualitative research method, its transformation over time and how it is used as a methodology in Turkey. The Grounded Theory which was founded by Strauss and Glaser, is a qualitative methodology based on inductive logic to discover theories in contrast with the deductive understanding which is based on testing an existing theory in sociology. It is possible to examine the Grounded Theory...

Cooperation-Induced Topological Complexity: A Promising Road to Fault Tolerance and Hebbian Learning

Science.gov (United States)

2012-03-16

Information Science Directorate, United States Army Research Office, Durham, NC, USA 4 Istituto di Fisiologia Clinica del Consiglio Nazionale delle...Vadim Uritsky, Catholic University of America at NASA Goddard Space Flight Center, USA *Correspondence: Paolo Allegrini , Istituto di Fisiologia Clinica

Driving to learn in a powered wheelchair: the process of learning joystick use in people with profound cognitive disabilities.

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Nilsson, Lisbeth; Eklund, Mona; Nyberg, Per; Thulesius, Hans

2011-01-01

The Driving to Learn project explored ways to help people with profound cognitive disabilities practice operating a joystick-operated powered wheelchair. The project used a grounded theory approach with constant comparative analysis and was carried out over 12 yr. The participants were 45 children and adults with profound cognitive disabilities. Reference groups included 17 typically developing infants and 64 participants with lesser degrees of cognitive disability. The data sources included video recordings, field notes, open interviews, and a rich mixture of literature. The findings that emerged yielded strategies for facilitating achievements, an 8-phase learning process, an assessment tool, and a grounded theory of deplateauing explaining the properties necessary for participants to exceed expected limitations and plateaus. Eight participants with profound cognitive disabilities reached goal-directed driving or higher. Participants were empowered by attaining increased control over tool use, improving their autonomy and quality of life.

Evaluating and Redesigning Teaching Learning Sequences at the Introductory Physics Level

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

2017-01-01

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

Principles of e-learning systems engineering

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Gilbert, Lester

2008-01-01

The book integrates the principles of software engineering with the principles of educational theory, and applies them to the problems of e-learning development, thus establishing the discipline of E-learning systems engineering. For the first time, these principles are collected and organised into the coherent framework that this book provides. Both newcomers to and established practitioners in the field are provided with integrated and grounded advice on theory and practice. The book presents strong practical and theoretical frameworks for the design and development of technology-based mater

A Review of Adventure Learning

Directory of Open Access Journals (Sweden)

George Veletsianos

2009-12-01

Full Text Available Adventure learning (AL is an approach for the design of digitally-enhanced teaching and learning environments driven by a framework of guidelines grounded on experiential and inquiry-based education. The purpose of this paper is to review the adventure learning literature and to describe the status quo of the practice by identifying the current knowledge, misconceptions, and future opportunities in adventure learning. Specifically, the authors present an integrative analysis of the adventure learning literature, identify knowledge gaps, present future research directions, and discuss research methods and approaches that may improve the AL approach.The authors engaged in a systematic search strategy to identify adventure learning studies then applied a set of criteria to decide whether to include or exclude each study. Results from the systematic review were combined, analyzed, and critiqued inductively using the constant comparative method and weaved together using the qualitative metasynthesis approach.Results indicate the appeal and promise of the adventure learning approach. Nevertheless, the authors recommend further investigation of the approach. Along with studies that investigate learning outcomes, aspects of the AL approach that are engaging, and the nature of expert-learner collaboration, future adventure learning projects that focus on higher education and are (a small and (b diverse can yield significant knowledge into adventure learning. Research and design in this area will benefit by taking an activity theory and design-based research perspective.

Differential associations between types of verbal memory and prefrontal brain structure in healthy aging and late life depression.

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Lamar, Melissa; Charlton, Rebecca; Zhang, Aifeng; Kumar, Anand

2012-07-01

Verbal memory deficits attributed to late life depression (LLD) may result from executive dysfunction that is more detrimental to list-learning than story-based recall when compared to healthy aging. Despite these behavioral dissociations, little work has been done investigating related neuroanatomical dissociations across types of verbal memory performance in LLD. We compared list-learning to story-based memory performance in 24 non-demented individuals with LLD (age ~ 66.1 ± 7.8) and 41 non-demented/non-depressed healthy controls (HC; age ~ 67.6 ± 5.3). We correlated significant results of between-group analyses across memory performance variables with brain volumes of frontal, temporal and parietal regions known to be involved with verbal learning and memory. When compared to the HC group, the LLD group showed significantly lower verbal memory performance for spontaneous recall after repeated exposure and after a long-delay but only for the list-learning task; groups did not differ on story-based memory performance. Despite equivalent brain volumes across regions, only the LLD group showed brain associations with verbal memory performance and only for the list-learning task. Specifically, frontal volumes important for subjective organization and response monitoring correlated with list-learning performance in the LLD group. This study is the first to demonstrate neuroanatomical dissociations across types of verbal memory performance in individuals with LLD. Results provide structural evidence for the behavioral dissociations between list-learning and story-based recall in LLD when compared to healthy aging. More specifically, it points toward a network of predominantly anterior brain regions that may underlie the executive contribution to list-learning in older adults with depression. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Chicken or the Egg? Investigating the Transformational Impact of Learning Technology

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Buchan, Janet F.

2011-01-01

This study aimed to investigate the transformational impact of introducing significant new learning technology in an Australian university over the time period 2007-2009. The exploration of this transformation is grounded in a social-ecological systems approach to the management of technology enhanced learning environments in the face of constant…

Organizational Transformation from the Inside Out: Reinventing the MIT Center for Organizational Learning.

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Clanon, Jeff

1999-01-01

The 2-year process by which the Massachusetts Institute of Technology's Center for Organizational Learning transformed into the self-governed Society for Organizational Learning illustrates new ways of conceiving organizations, the capabilities required for change, and critical elements of the process: diverse representation, grounding in business…

Learning and Cognition - The interplay between the Subject and the Group

DEFF Research Database (Denmark)

Møller, Kim Malmbak; Fast, Alf Michael

2017-01-01

emphasis on the knowledge - practice discussion, and thereby on some of the values required to progress in science as a field and to develop knowledge. This article focuses on how to describe the dialectical interplay between the individual’s learning and the groups’ learning process, in the development......, and the contradictions that appear in learning contexts. The grounds for the development of an intersubjectivity, which is required in the engagement of interaction, seems therefore as an important part of learning. The article will look upon those questions and themes from a broad phenomenological and dialectical...

Building a New Generation of Learning: Conversations to Catalyze Our Construction

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Milliron, Mark David; Plinske, Kathleen; Noonan-Terry, Coral

2008-01-01

Rather than focus primarily on the next generation of learners, the authors argue we are best served to focus on building out our on-ground and online infrastructures for a new generation of learning--blending multiple learning modes, technologies, and techniques over the course of the next 15-20 years to serve the diverse array of students from…

Chemical Education Research: Improving Chemistry Learning

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Dudley Herron, J.; Nurrenbern, Susan C.

1999-10-01

Chemical education research is the systematic investigation of learning grounded in a theoretical foundation that focuses on understanding and improving learning of chemistry. This article reviews many activities, changes, and accomplishments that have taken place in this area of scholarly activity despite its relatively recent emergence as a research area. The article describes how the two predominant broad perspectives of learning, behaviorism and constructivism, have shaped and influenced chemical education research design, analysis, and interpretation during the 1900s. Selected research studies illustrate the range of research design strategies and results that have contributed to an increased understanding of learning in chemistry. The article also provides a perspective of current and continuing challenges that researchers in this area face as they strive to bridge the gap between chemistry and education - disciplines with differing theoretical bases and research paradigms.

A New Design Approach to game or play based learning

DEFF Research Database (Denmark)

Larsen, Lasse Juel

to ground the students sense of meaning. This paper proposes another approach: using visualization in immersive 3D-worlds as documentation of learning progress while at the same time constituting a reward system which motivate further learning. The overall design idea is to build a game based learning......Abstract: The present paper proposes a new design perspective for game based learning. The general idea is to abandon the long and sought after dream of designing a closed learning system, where students from elementary school to high school without teachers’ interference could learn whatever...... game based learning system, but also confront aspects of modern learning theory especially the notion of reference between content of an assignment and the reality with which it should or could be connected (situated learning). The second idea promotes a way to tackle the common experience...

How characteristic routines of clinical departments influence students' self-regulated learning : A grounded theory study

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Berkhout, J J; Slootweg, I. A.; Helmich, Esther; Teunissen, P W; van der Vleuten, C. P. M.; Jaarsma, A. D. C.

2017-01-01

Background: In clerkships, students are expected to self-regulate their learning. How clinical departments and their routine approach on clerkships influences students' self-regulated learning (SRL) is unknown.Aim: This study explores how characteristic routines of clinical departments influence

Learning strategies of public health nursing students: conquering operational space.

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Hjälmhult, Esther

2009-11-01

To develop understanding of how public health nursing students learn in clinical practice and explore the main concern for the students and how they acted to resolve this main concern. How professionals perform their work directly affects individuals, but knowledge is lacking in understanding how learning is connected to clinical practice in public health nursing and in other professions. Grounded theory. Grounded theory was used in gathering and analysing data from 55 interviews and 108 weekly reports. The participants were 21 registered nurses who were public health nursing students. The grounded theory of conquering operational space explains how the students work to resolve their main concern. A social process with three identified phases, positioning, involving and integrating, was generated from analysing the data. Their subcategories and dimensions are related to the student role, relations with a supervisor, student activity and the consequences of each phase. Public health nursing students had to work towards gaining independence, often working against 'the system' and managing the tension by taking a risk. Many of them lost, changed and expanded their professional identity during practical placements. Public health nursing students' learning processes in clinical training are complex and dynamic and the theory of 'Conquering operational space' can assist supervisors in further developing their role in relation to guiding students in practice. Relationships are one key to opening or closing access to situations of learning and directly affect the students' achievement of mastering. The findings are pertinent to supervisors and educators as they prepare students for practice. Good relationships are elementary and supervisors can support students in conquering the field by letting students obtain operational space and gain independence. This may create a dialectical process that drives learning forward.

Listening to Our Students: Understanding How They Learn Research Methods in Geography

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Keenan, Kevin; Fontaine, Danielle

2012-01-01

How undergraduate students learn research methods in geography has been understudied. Existing work has focused on course description from the instructor's perspective. This study, however, uses a grounded theory approach to allow students' voices to shape a new theory of how they themselves say that they learn research methods. Data from two…

The Learning Leader: Reflecting, Modeling, and Sharing

Science.gov (United States)

Jacobs, Jacqueline E.; O'Gorman, Kevin L.

2012-01-01

With this book, principals, principals-in-training, and other school leaders get practical, easy-to-implement strategies for professional growth, strengthening relationships with faculty and staff, and making the necessary changes to improve K-12 learning environments. Grounded in specific, real-world examples and personal experiences, "The…

DCS-Neural-Network Program for Aircraft Control and Testing

Science.gov (United States)

Jorgensen, Charles C.

2006-01-01

A computer program implements a dynamic-cell-structure (DCS) artificial neural network that can perform such tasks as learning selected aerodynamic characteristics of an airplane from wind-tunnel test data and computing real-time stability and control derivatives of the airplane for use in feedback linearized control. A DCS neural network is one of several types of neural networks that can incorporate additional nodes in order to rapidly learn increasingly complex relationships between inputs and outputs. In the DCS neural network implemented by the present program, the insertion of nodes is based on accumulated error. A competitive Hebbian learning rule (a supervised-learning rule in which connection weights are adjusted to minimize differences between actual and desired outputs for training examples) is used. A Kohonen-style learning rule (derived from a relatively simple training algorithm, implements a Delaunay triangulation layout of neurons) is used to adjust node positions during training. Neighborhood topology determines which nodes are used to estimate new values. The network learns, starting with two nodes, and adds new nodes sequentially in locations chosen to maximize reductions in global error. At any given time during learning, the error becomes homogeneously distributed over all nodes.

Acquisition of automatic imitation is sensitive to sensorimotor contingency.

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Cook, Richard; Press, Clare; Dickinson, Anthony; Heyes, Cecilia

2010-08-01

The associative sequence learning model proposes that the development of the mirror system depends on the same mechanisms of associative learning that mediate Pavlovian and instrumental conditioning. To test this model, two experiments used the reduction of automatic imitation through incompatible sensorimotor training to assess whether mirror system plasticity is sensitive to contingency (i.e., the extent to which activation of one representation predicts activation of another). In Experiment 1, residual automatic imitation was measured following incompatible training in which the action stimulus was a perfect predictor of the response (contingent) or not at all predictive of the response (noncontingent). A contingency effect was observed: There was less automatic imitation indicative of more learning in the contingent group. Experiment 2 replicated this contingency effect and showed that, as predicted by associative learning theory, it can be abolished by signaling trials in which the response occurs in the absence of an action stimulus. These findings support the view that mirror system development depends on associative learning and indicate that this learning is not purely Hebbian. If this is correct, associative learning theory could be used to explain, predict, and intervene in mirror system development.

Lessons Learned from Biosphere 2: When Viewed as a Ground Simulation/Analogue for Long Duration Human Space Exploration and Settlement

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