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

PubMed Central

Simon, Dylan Alexander; Daw, Nathaniel D.

2011-01-01

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

Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

PubMed Central

Martinet, Louis-Emmanuel; Sheynikhovich, Denis; Benchenane, Karim; Arleo, Angelo

2011-01-01

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates. PMID:21625569

Anisotropic interaction rules in circular motions of pigeon flocks: An empirical study based on sparse Bayesian learning

NASA Astrophysics Data System (ADS)

Chen, Duxin; Xu, Bowen; Zhu, Tao; Zhou, Tao; Zhang, Hai-Tao

2017-08-01

Coordination shall be deemed to the result of interindividual interaction among natural gregarious animal groups. However, revealing the underlying interaction rules and decision-making strategies governing highly coordinated motion in bird flocks is still a long-standing challenge. Based on analysis of high spatial-temporal resolution GPS data of three pigeon flocks, we extract the hidden interaction principle by using a newly emerging machine learning method, namely the sparse Bayesian learning. It is observed that the interaction probability has an inflection point at pairwise distance of 3-4 m closer than the average maximum interindividual distance, after which it decays strictly with rising pairwise metric distances. Significantly, the density of spatial neighbor distribution is strongly anisotropic, with an evident lack of interactions along individual velocity. Thus, it is found that in small-sized bird flocks, individuals reciprocally cooperate with a variational number of neighbors in metric space and tend to interact with closer time-varying neighbors, rather than interacting with a fixed number of topological ones. Finally, extensive numerical investigation is conducted to verify both the revealed interaction and decision-making principle during circular flights of pigeon flocks.

Cool and hot executive function impairments in violent offenders with antisocial personality disorder with and without psychopathy.

PubMed

De Brito, Stephane A; Viding, Essi; Kumari, Veena; Blackwood, Nigel; Hodgins, Sheilagh

2013-01-01

Impairments in executive function characterize offenders with antisocial personality disorder (ASPD) and offenders with psychopathy. However, the extent to which those impairments are associated with ASPD, psychopathy, or both is unknown. The present study examined 17 violent offenders with ASPD and psychopathy (ASPD+P), 28 violent offenders with ASPD without psychopathy (ASPD-P), and 21 healthy non-offenders on tasks assessing cool (verbal working memory and alteration of motor responses to spatial locations) and hot (reversal learning, decision-making under risk, and stimulus-reinforcement-based decision-making) executive function. In comparison to healthy non-offenders, violent offenders with ASPD+P and those with ASPD-P showed similar impairments in verbal working memory and adaptive decision-making. They failed to learn from punishment cues, to change their behaviour in the face of changing contingencies, and made poorer quality decisions despite longer periods of deliberation. Intriguingly, the two groups of offenders did not differ significantly from the non-offenders in terms of their alteration of motor responses to spatial locations and their levels of risk-taking, indicated by betting, and impulsivity, measured as delay aversion. The performance of the two groups of offenders on the measures of cool and hot executive function did not differ, indicating shared deficits. These documented impairments may help to explain the persistence of antisocial behaviours despite the known risks of the negative consequences of such behaviours.

The Development of GIS Educational Resources Sharing among Central Taiwan Universities

NASA Astrophysics Data System (ADS)

Chou, T.-Y.; Yeh, M.-L.; Lai, Y.-C.

2011-09-01

Using GIS in the classroom enhance students' computer skills and explore the range of knowledge. The paper highlights GIS integration on e-learning platform and introduces a variety of abundant educational resources. This research project will demonstrate tools for e-learning environment and delivers some case studies for learning interaction from Central Taiwan Universities. Feng Chia University (FCU) obtained a remarkable academic project subsidized by Ministry of Education and developed e-learning platform for excellence in teaching/learning programs among Central Taiwan's universities. The aim of the project is to integrate the educational resources of 13 universities in central Taiwan. FCU is serving as the hub of Center University. To overcome the problem of distance, e-platforms have been established to create experiences with collaboration enhanced learning. The e-platforms provide coordination of web service access among the educational community and deliver GIS educational resources. Most of GIS related courses cover the development of GIS, principles of cartography, spatial data analysis and overlaying, terrain analysis, buffer analysis, 3D GIS application, Remote Sensing, GPS technology, and WebGIS, MobileGIS, ArcGIS manipulation. In each GIS case study, students have been taught to know geographic meaning, collect spatial data and then use ArcGIS software to analyze spatial data. On one of e-Learning platforms provide lesson plans and presentation slides. Students can learn Arc GIS online. As they analyze spatial data, they can connect to GIS hub to get data they need including satellite images, aerial photos, and vector data. Moreover, e-learning platforms provide solutions and resources. Different levels of image scales have been integrated into the systems. Multi-scale spatial development and analyses in Central Taiwan integrate academic research resources among CTTLRC partners. Thus, establish decision-making support mechanism in teaching and learning. Accelerate communication, cooperation and sharing among academic units

Navigating Monogamy: Nonapeptide Sensitivity in a Memory Neural Circuit May Shape Social Behavior and Mating Decisions

PubMed Central

Ophir, Alexander G.

2017-01-01

The role of memory in mating systems is often neglected despite the fact that most mating systems are defined in part by how animals use space. Monogamy, for example, is usually characterized by affiliative (e.g., pairbonding) and defensive (e.g., mate guarding) behaviors, but a high degree of spatial overlap in home range use is the easiest defining feature of monogamous animals in the wild. The nonapeptides vasopressin and oxytocin have been the focus of much attention for their importance in modulating social behavior, however this work has largely overshadowed their roles in learning and memory. To date, the understanding of memory systems and mechanisms governing social behavior have progressed relatively independently. Bridging these two areas will provide a deeper appreciation for understanding behavior, and in particular the mechanisms that mediate reproductive decision-making. Here, I argue that the ability to mate effectively as monogamous individuals is linked to the ability to track conspecifics in space. I discuss the connectivity across some well-known social and spatial memory nuclei, and propose that the nonapeptide receptors within these structures form a putative “socio-spatial memory neural circuit.” This purported circuit may function to integrate social and spatial information to shape mating decisions in a context-dependent fashion. The lateral septum and/or the nucleus accumbens, and neuromodulation therein, may act as an intermediary to relate socio-spatial information with social behavior. Identifying mechanisms responsible for relating information about the social world with mechanisms mediating mating tactics is crucial to fully appreciate the suite of factors driving reproductive decisions and social decision-making. PMID:28744194

a Rough Set Decision Tree Based Mlp-Cnn for Very High Resolution Remotely Sensed Image Classification

NASA Astrophysics Data System (ADS)

Zhang, C.; Pan, X.; Zhang, S. Q.; Li, H. P.; Atkinson, P. M.

2017-09-01

Recent advances in remote sensing have witnessed a great amount of very high resolution (VHR) images acquired at sub-metre spatial resolution. These VHR remotely sensed data has post enormous challenges in processing, analysing and classifying them effectively due to the high spatial complexity and heterogeneity. Although many computer-aid classification methods that based on machine learning approaches have been developed over the past decades, most of them are developed toward pixel level spectral differentiation, e.g. Multi-Layer Perceptron (MLP), which are unable to exploit abundant spatial details within VHR images. This paper introduced a rough set model as a general framework to objectively characterize the uncertainty in CNN classification results, and further partition them into correctness and incorrectness on the map. The correct classification regions of CNN were trusted and maintained, whereas the misclassification areas were reclassified using a decision tree with both CNN and MLP. The effectiveness of the proposed rough set decision tree based MLP-CNN was tested using an urban area at Bournemouth, United Kingdom. The MLP-CNN, well capturing the complementarity between CNN and MLP through the rough set based decision tree, achieved the best classification performance both visually and numerically. Therefore, this research paves the way to achieve fully automatic and effective VHR image classification.

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

NASA Astrophysics Data System (ADS)

Gonzales, Kalim

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

Proceedings for the Annual Symposium and Exhibition on Situational Awareness in the Tactical Air Environment, (2nd), Held at Patuxent River, Maryland, on 3-4 June 1997

DTIC Science & Technology

1997-06-01

made based on a learning mechanism. Traditional statistical regression and neural network approaches offer some utility, but suffer from practical...Columbus, OH. Kraiger, K., Ford, J. K., & Salas, E. (1993). Application of cognitive, skill- based , and affective theories of learning outcomes to new...and Feature Effects 151 Enhanced Spatial State Feedback for Night Vision Goggle Displays 159 Statistical Network Applications of Decision Aiding for

Cool and Hot Executive Function Impairments in Violent Offenders with Antisocial Personality Disorder with and without Psychopathy

PubMed Central

De Brito, Stephane A.; Viding, Essi; Kumari, Veena; Blackwood, Nigel; Hodgins, Sheilagh

2013-01-01

Background Impairments in executive function characterize offenders with antisocial personality disorder (ASPD) and offenders with psychopathy. However, the extent to which those impairments are associated with ASPD, psychopathy, or both is unknown. Methods The present study examined 17 violent offenders with ASPD and psychopathy (ASPD+P), 28 violent offenders with ASPD without psychopathy (ASPD−P), and 21 healthy non-offenders on tasks assessing cool (verbal working memory and alteration of motor responses to spatial locations) and hot (reversal learning, decision-making under risk, and stimulus-reinforcement-based decision-making) executive function. Results In comparison to healthy non-offenders, violent offenders with ASPD+P and those with ASPD−P showed similar impairments in verbal working memory and adaptive decision-making. They failed to learn from punishment cues, to change their behaviour in the face of changing contingencies, and made poorer quality decisions despite longer periods of deliberation. Intriguingly, the two groups of offenders did not differ significantly from the non-offenders in terms of their alteration of motor responses to spatial locations and their levels of risk-taking, indicated by betting, and impulsivity, measured as delay aversion. The performance of the two groups of offenders on the measures of cool and hot executive function did not differ, indicating shared deficits. Conclusions These documented impairments may help to explain the persistence of antisocial behaviours despite the known risks of the negative consequences of such behaviours. PMID:23840340

Task specificity of attention training: the case of probability cuing

PubMed Central

Jiang, Yuhong V.; Swallow, Khena M.; Won, Bo-Yeong; Cistera, Julia D.; Rosenbaum, Gail M.

2014-01-01

Statistical regularities in our environment enhance perception and modulate the allocation of spatial attention. Surprisingly little is known about how learning-induced changes in spatial attention transfer across tasks. In this study, we investigated whether a spatial attentional bias learned in one task transfers to another. Most of the experiments began with a training phase in which a search target was more likely to be located in one quadrant of the screen than in the other quadrants. An attentional bias toward the high-probability quadrant developed during training (probability cuing). In a subsequent, testing phase, the target's location distribution became random. In addition, the training and testing phases were based on different tasks. Probability cuing did not transfer between visual search and a foraging-like task. However, it did transfer between various types of visual search tasks that differed in stimuli and difficulty. These data suggest that different visual search tasks share a common and transferrable learned attentional bias. However, this bias is not shared by high-level, decision-making tasks such as foraging. PMID:25113853

Exploring prediction uncertainty of spatial data in geostatistical and machine learning Approaches

NASA Astrophysics Data System (ADS)

Klump, J. F.; Fouedjio, F.

2017-12-01

Geostatistical methods such as kriging with external drift as well as machine learning techniques such as quantile regression forest have been intensively used for modelling spatial data. In addition to providing predictions for target variables, both approaches are able to deliver a quantification of the uncertainty associated with the prediction at a target location. Geostatistical approaches are, by essence, adequate for providing such prediction uncertainties and their behaviour is well understood. However, they often require significant data pre-processing and rely on assumptions that are rarely met in practice. Machine learning algorithms such as random forest regression, on the other hand, require less data pre-processing and are non-parametric. This makes the application of machine learning algorithms to geostatistical problems an attractive proposition. The objective of this study is to compare kriging with external drift and quantile regression forest with respect to their ability to deliver reliable prediction uncertainties of spatial data. In our comparison we use both simulated and real world datasets. Apart from classical performance indicators, comparisons make use of accuracy plots, probability interval width plots, and the visual examinations of the uncertainty maps provided by the two approaches. By comparing random forest regression to kriging we found that both methods produced comparable maps of estimated values for our variables of interest. However, the measure of uncertainty provided by random forest seems to be quite different to the measure of uncertainty provided by kriging. In particular, the lack of spatial context can give misleading results in areas without ground truth data. These preliminary results raise questions about assessing the risks associated with decisions based on the predictions from geostatistical and machine learning algorithms in a spatial context, e.g. mineral exploration.

Image interpolation by adaptive 2-D autoregressive modeling and soft-decision estimation.

PubMed

Zhang, Xiangjun; Wu, Xiaolin

2008-06-01

The challenge of image interpolation is to preserve spatial details. We propose a soft-decision interpolation technique that estimates missing pixels in groups rather than one at a time. The new technique learns and adapts to varying scene structures using a 2-D piecewise autoregressive model. The model parameters are estimated in a moving window in the input low-resolution image. The pixel structure dictated by the learnt model is enforced by the soft-decision estimation process onto a block of pixels, including both observed and estimated. The result is equivalent to that of a high-order adaptive nonseparable 2-D interpolation filter. This new image interpolation approach preserves spatial coherence of interpolated images better than the existing methods, and it produces the best results so far over a wide range of scenes in both PSNR measure and subjective visual quality. Edges and textures are well preserved, and common interpolation artifacts (blurring, ringing, jaggies, zippering, etc.) are greatly reduced.

A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification

NASA Astrophysics Data System (ADS)

Zhang, Ce; Pan, Xin; Li, Huapeng; Gardiner, Andy; Sargent, Isabel; Hare, Jonathon; Atkinson, Peter M.

2018-06-01

The contextual-based convolutional neural network (CNN) with deep architecture and pixel-based multilayer perceptron (MLP) with shallow structure are well-recognized neural network algorithms, representing the state-of-the-art deep learning method and the classical non-parametric machine learning approach, respectively. The two algorithms, which have very different behaviours, were integrated in a concise and effective way using a rule-based decision fusion approach for the classification of very fine spatial resolution (VFSR) remotely sensed imagery. The decision fusion rules, designed primarily based on the classification confidence of the CNN, reflect the generally complementary patterns of the individual classifiers. In consequence, the proposed ensemble classifier MLP-CNN harvests the complementary results acquired from the CNN based on deep spatial feature representation and from the MLP based on spectral discrimination. Meanwhile, limitations of the CNN due to the adoption of convolutional filters such as the uncertainty in object boundary partition and loss of useful fine spatial resolution detail were compensated. The effectiveness of the ensemble MLP-CNN classifier was tested in both urban and rural areas using aerial photography together with an additional satellite sensor dataset. The MLP-CNN classifier achieved promising performance, consistently outperforming the pixel-based MLP, spectral and textural-based MLP, and the contextual-based CNN in terms of classification accuracy. This research paves the way to effectively address the complicated problem of VFSR image classification.

Forest climate change Vulnerability and Adaptation Assessment in Himalayas

NASA Astrophysics Data System (ADS)

Chitale, V. S.; Shrestha, H. L.; Agarwal, N. K.; Choudhurya, D.; Gilani, H.; Dhonju, H. K.; Murthy, M. S. R.

2014-11-01

Forests offer an important basis for creating and safeguarding more climate-resilient communities over Hindu Kush Himalayan region. The forest ecosystem vulnerability assessment to climate change and developing knowledge base to identify and support relevant adaptation strategies is realized as an urgent need. The multi scale adaptation strategies portray increasing complexity with the increasing levels in terms of data requirements, vulnerability understanding and decision making to choose a particular adaptation strategy. We present here how such complexities could be addressed and adaptation decisions could be either directly supported by open source remote sensing based forestry products or geospatial analysis and modelled products. The forest vulnerability assessment under climate change scenario coupled with increasing forest social dependence was studied using IPCC Landscape scale Vulnerability framework in Chitwan-Annapurna Landscape (CHAL) situated in Nepal. Around twenty layers of geospatial information on climate, forest biophysical and forest social dependence data was used to assess forest vulnerability and associated adaptation needs using self-learning decision tree based approaches. The increase in forest fires, evapotranspiration and reduction in productivity over changing climate scenario was observed. The adaptation measures on enhancing productivity, improving resilience, reducing or avoiding pressure with spatial specificity are identified to support suitable decision making. The study provides spatial analytical framework to evaluate multitude of parameters to understand vulnerabilities and assess scope for alternative adaptation strategies with spatial explicitness.

Dopamine D3 Receptor Availability Is Associated with Inflexible Decision Making.

PubMed

Groman, Stephanie M; Smith, Nathaniel J; Petrullli, J Ryan; Massi, Bart; Chen, Lihui; Ropchan, Jim; Huang, Yiyun; Lee, Daeyeol; Morris, Evan D; Taylor, Jane R

2016-06-22

Dopamine D2/3 receptor signaling is critical for flexible adaptive behavior; however, it is unclear whether D2, D3, or both receptor subtypes modulate precise signals of feedback and reward history that underlie optimal decision making. Here, PET with the radioligand [(11)C]-(+)-PHNO was used to quantify individual differences in putative D3 receptor availability in rodents trained on a novel three-choice spatial acquisition and reversal-learning task with probabilistic reinforcement. Binding of [(11)C]-(+)-PHNO in the midbrain was negatively related to the ability of rats to adapt to changes in rewarded locations, but not to the initial learning. Computational modeling of choice behavior in the reversal phase indicated that [(11)C]-(+)-PHNO binding in the midbrain was related to the learning rate and sensitivity to positive, but not negative, feedback. Administration of a D3-preferring agonist likewise impaired reversal performance by reducing the learning rate and sensitivity to positive feedback. These results demonstrate a previously unrecognized role for D3 receptors in select aspects of reinforcement learning and suggest that individual variation in midbrain D3 receptors influences flexible behavior. Our combined neuroimaging, behavioral, pharmacological, and computational approach implicates the dopamine D3 receptor in decision-making processes that are altered in psychiatric disorders. Flexible decision-making behavior is dependent upon dopamine D2/3 signaling in corticostriatal brain regions. However, the role of D3 receptors in adaptive, goal-directed behavior has not been thoroughly investigated. By combining PET imaging with the D3-preferring radioligand [(11)C]-(+)-PHNO, pharmacology, a novel three-choice probabilistic discrimination and reversal task and computational modeling of behavior in rats, we report that naturally occurring variation in [(11)C]-(+)-PHNO receptor availability relates to specific aspects of flexible decision making. We confirm these relationships using a D3-preferring agonist, thus identifying a unique role of midbrain D3 receptors in decision-making processes. Copyright © 2016 the authors 0270-6474/16/366732-10$15.00/0.

The profile of executive function in OCD hoarders and hoarding disorder☆

PubMed Central

Morein-Zamir, Sharon; Papmeyer, Martina; Pertusa, Alberto; Chamberlain, Samuel R.; Fineberg, Naomi A.; Sahakian, Barbara J.; Mataix-Cols, David; Robbins, Trevor W.

2014-01-01

Hoarding disorder is a new mental disorder in DSM-5. It is classified alongside OCD and other presumably related disorders in the Obsessive-Compulsive and Related Disorders chapter. We examined cognitive performance in two distinct groups comprising individuals with both OCD and severe hoarding, and individuals with hoarding disorder without comorbid OCD. Participants completed executive function tasks assessing inhibitory control, cognitive flexibility, spatial planning, probabilistic learning and reversal and decision making. Compared to a matched healthy control group, OCD hoarders showed significantly worse performance on measures of response inhibition, set shifting, spatial planning, probabilistic learning and reversal, with intact decision making. Despite having a strikingly different clinical presentation, individuals with only hoarding disorder did not differ significantly from OCD hoarders on any cognitive measure suggesting the two hoarding groups have a similar pattern of cognitive difficulties. Tests of cognitive flexibility were least similar across the groups, but differences were small and potentially reflected subtle variation in underlying brain pathology together with psychometric limitations. These results highlight both commonalities and potential differences between OCD and hoarding disorder, and together with other lines of evidence, support the inclusion of the new disorder within the new Obsessive-Compulsive and Related Disorders chapter in DSM-5. PMID:24467873

Examining the Role of the Human Hippocampus in Approach-Avoidance Decision Making Using a Novel Conflict Paradigm and Multivariate Functional Magnetic Resonance Imaging.

PubMed

O'Neil, Edward B; Newsome, Rachel N; Li, Iris H N; Thavabalasingam, Sathesan; Ito, Rutsuko; Lee, Andy C H

2015-11-11

Rodent models of anxiety have implicated the ventral hippocampus in approach-avoidance conflict processing. Few studies have, however, examined whether the human hippocampus plays a similar role. We developed a novel decision-making paradigm to examine neural activity when participants made approach/avoidance decisions under conditions of high or absent approach-avoidance conflict. Critically, our task required participants to learn the associated reward/punishment values of previously neutral stimuli and controlled for mnemonic and spatial processing demands, both important issues given approach-avoidance behavior in humans is less tied to predation and foraging compared to rodents. Participants played a points-based game where they first attempted to maximize their score by determining which of a series of previously neutral image pairs should be approached or avoided. During functional magnetic resonance imaging, participants were then presented with novel pairings of these images. These pairings consisted of images of congruent or opposing learned valences, the latter creating conditions of high approach-avoidance conflict. A data-driven partial least squares multivariate analysis revealed two reliable patterns of activity, each revealing differential activity in the anterior hippocampus, the homolog of the rodent ventral hippocampus. The first was associated with greater hippocampal involvement during trials with high as opposed to no approach-avoidance conflict, regardless of approach or avoidance behavior. The second pattern encompassed greater hippocampal activity in a more anterior aspect during approach compared to avoid responses, for conflict and no-conflict conditions. Multivoxel pattern classification analyses yielded converging findings, underlining a role of the anterior hippocampus in approach-avoidance conflict decision making. Approach-avoidance conflict has been linked to anxiety and occurs when a stimulus or situation is associated with reward and punishment. Although rodent work has implicated the hippocampus in approach-avoidance conflict processing, there is limited data on whether this role applies to learned, as opposed to innate, incentive values, and whether the human hippocampus plays a similar role. Using functional neuroimaging with a novel decision-making task that controlled for perceptual and mnemonic processing, we found that the human hippocampus was significantly active when approach-avoidance conflict was present for stimuli with learned incentive values. These findings demonstrate a role for the human hippocampus in approach-avoidance decision making that cannot be explained easily by hippocampal-dependent long-term memory or spatial cognition. Copyright © 2015 the authors 0270-6474/15/3515040-11$15.00/0.

Conflict between place and response navigation strategies: effects on vicarious trial and error (VTE) behaviors.

PubMed

Schmidt, Brandy; Papale, Andrew; Redish, A David; Markus, Etan J

2013-02-15

Navigation can be accomplished through multiple decision-making strategies, using different information-processing computations. A well-studied dichotomy in these decision-making strategies compares hippocampal-dependent "place" and dorsal-lateral striatal-dependent "response" strategies. A place strategy depends on the ability to flexibly respond to environmental cues, while a response strategy depends on the ability to quickly recognize and react to situations with well-learned action-outcome relationships. When rats reach decision points, they sometimes pause and orient toward the potential routes of travel, a process termed vicarious trial and error (VTE). VTE co-occurs with neurophysiological information processing, including sweeps of representation ahead of the animal in the hippocampus and transient representations of reward in the ventral striatum and orbitofrontal cortex. To examine the relationship between VTE and the place/response strategy dichotomy, we analyzed data in which rats were cued to switch between place and response strategies on a plus maze. The configuration of the maze allowed for place and response strategies to work competitively or cooperatively. Animals showed increased VTE on trials entailing competition between navigational systems, linking VTE with deliberative decision-making. Even in a well-learned task, VTE was preferentially exhibited when a spatial selection was required, further linking VTE behavior with decision-making associated with hippocampal processing.

Neural systems analysis of decision making during goal-directed navigation.

PubMed

Penner, Marsha R; Mizumori, Sheri J Y

2012-01-01

The ability to make adaptive decisions during goal-directed navigation is a fundamental and highly evolved behavior that requires continual coordination of perceptions, learning and memory processes, and the planning of behaviors. Here, a neurobiological account for such coordination is provided by integrating current literatures on spatial context analysis and decision-making. This integration includes discussions of our current understanding of the role of the hippocampal system in experience-dependent navigation, how hippocampal information comes to impact midbrain and striatal decision making systems, and finally the role of the striatum in the implementation of behaviors based on recent decisions. These discussions extend across cellular to neural systems levels of analysis. Not only are key findings described, but also fundamental organizing principles within and across neural systems, as well as between neural systems functions and behavior, are emphasized. It is suggested that studying decision making during goal-directed navigation is a powerful model for studying interactive brain systems and their mediation of complex behaviors. Copyright © 2011. Published by Elsevier Ltd.

Midline thalamic reuniens lesions improve executive behaviors.

PubMed

Prasad, J A; Abela, A R; Chudasama, Y

2017-03-14

The role of the thalamus in complex cognitive behavior is a topic of increasing interest. Here we demonstrate that lesions of the nucleus reuniens (NRe), a midline thalamic nucleus interconnected with both hippocampal and prefrontal circuitry, lead to enhancement of executive behaviors typically associated with the prefrontal cortex. Rats were tested on four behavioral tasks: (1) the combined attention-memory (CAM) task, which simultaneously assessed attention to a visual target and memory for that target over a variable delay; (2) spatial memory using a radial arm maze, (3) discrimination and reversal learning using a touchscreen operant platform, and (4) decision-making with delayed outcomes. Following NRe lesions, the animals became more efficient in their performance, responding with shorter reaction times but also less impulsively than controls. This change, combined with a decrease in perseverative responses, led to focused attention in the CAM task and accelerated learning in the visual discrimination task. There were no observed changes in tasks involving either spatial memory or value-based decision making. These data complement ongoing efforts to understand the role of midline thalamic structures in human cognition, including the development of thalamic stimulation as a therapeutic strategy for acquired cognitive disabilities (Schiff, 2008; Mair et al., 2011), and point to the NRe as a potential target for clinical intervention. Published by Elsevier Ltd.

A neuropsychological comparison of obsessive-compulsive disorder and trichotillomania.

PubMed

Chamberlain, Samuel R; Fineberg, Naomi A; Blackwell, Andrew D; Clark, Luke; Robbins, Trevor W; Sahakian, Barbara J

2007-03-02

Obsessive-compulsive disorder (OCD) and trichotillomania (compulsive hair-pulling) share overlapping co-morbidity, familial transmission, and phenomenology. However, the extent to which these disorders share a common cognitive phenotype has yet to be elucidated using patients without confounding co-morbidities. To compare neurocognitive functioning in co-morbidity-free patients with OCD and trichotillomania, focusing on domains of learning and memory, executive function, affective processing, reflection-impulsivity and decision-making. Twenty patients with OCD, 20 patients with trichotillomania, and 20 matched controls undertook neuropsychological assessment after meeting stringent inclusion criteria. Groups were matched for age, education, verbal IQ, and gender. The OCD and trichotillomania groups were impaired on spatial working memory. Only OCD patients showed additional impairments on executive planning and visual pattern recognition memory, and missed more responses to sad target words than other groups on an affective go/no-go task. Furthermore, OCD patients failed to modulate their behaviour between conditions on the reflection-impulsivity test, suggestive of cognitive inflexibility. Both clinical groups showed intact decision-making and probabilistic reversal learning. OCD and trichotillomania shared overlapping spatial working memory problems, but neuropsychological dysfunction in OCD spanned additional domains that were intact in trichotillomania. Findings are discussed in relation to likely fronto-striatal neural substrates and future research directions.

Prolonged Perceptual Learning of Positional Acuity in Adult Amblyopia

PubMed Central

Li, Roger W; Klein, Stanley A; Levi, Dennis M

2009-01-01

Amblyopia is a developmental abnormality that results in physiological alterations in the visual cortex and impairs form vision. It is often successfully treated by patching the sound eye in infants and young children, but is generally considered to be untreatable in adults. However, a number of recent studies suggest that repetitive practice of a visual task using the amblyopic eye results in improved performance in both children and adults with amblyopia. These perceptual learning studies have used relatively brief periods of practice; however, clinical studies have shown that the time-constant for successful patching is long. The time-constant for perceptual learning in amblyopia is still unknown. Here we show that the time-constant for perceptual learning depends on the degree of amblyopia. Severe amblyopia requires more than 50 hours (≈35,000 trials) to reach plateau, yielding as much as a five-fold improvement in performance at a rate of ≈1.5% per hour. There is significant transfer of learning from the amblyopic to the dominant eye, suggesting that the learning reflects alterations in higher decision stages of processing. Using a reverse correlation technique, we document, for the first time, a dynamic retuning of the amblyopic perceptual decision template and a substantial reduction in internal spatial distortion. These results show that the mature amblyopic brain is surprisingly malleable, and point to more intensive treatment methods for amblyopia. PMID:19109504

Web-services-based spatial decision support system to facilitate nuclear waste siting

NASA Astrophysics Data System (ADS)

Huang, L. Xinglai; Sheng, Grant

2006-10-01

The availability of spatial web services enables data sharing among managers, decision and policy makers and other stakeholders in much simpler ways than before and subsequently has created completely new opportunities in the process of spatial decision making. Though generally designed for a certain problem domain, web-services-based spatial decision support systems (WSDSS) can provide a flexible problem-solving environment to explore the decision problem, understand and refine problem definition, and generate and evaluate multiple alternatives for decision. This paper presents a new framework for the development of a web-services-based spatial decision support system. The WSDSS is comprised of distributed web services that either have their own functions or provide different geospatial data and may reside in different computers and locations. WSDSS includes six key components, namely: database management system, catalog, analysis functions and models, GIS viewers and editors, report generators, and graphical user interfaces. In this study, the architecture of a web-services-based spatial decision support system to facilitate nuclear waste siting is described as an example. The theoretical, conceptual and methodological challenges and issues associated with developing web services-based spatial decision support system are described.

Single trial decoding of belief decision making from EEG and fMRI data using independent components features

PubMed Central

Douglas, Pamela K.; Lau, Edward; Anderson, Ariana; Head, Austin; Kerr, Wesley; Wollner, Margalit; Moyer, Daniel; Li, Wei; Durnhofer, Mike; Bramen, Jennifer; Cohen, Mark S.

2013-01-01

The complex task of assessing the veracity of a statement is thought to activate uniquely distributed brain regions based on whether a subject believes or disbelieves a given assertion. In the current work, we present parallel machine learning methods for predicting a subject's decision response to a given propositional statement based on independent component (IC) features derived from EEG and fMRI data. Our results demonstrate that IC features outperformed features derived from event related spectral perturbations derived from any single spectral band, yet were similar to accuracy across all spectral bands combined. We compared our diagnostic IC spatial maps with our conventional general linear model (GLM) results, and found that informative ICs had significant spatial overlap with our GLM results, yet also revealed unique regions like amygdala that were not statistically significant in GLM analyses. Overall, these results suggest that ICs may yield a parsimonious feature set that can be used along with a decision tree structure for interpretation of features used in classifying complex cognitive processes such as belief and disbelief across both fMRI and EEG neuroimaging modalities. PMID:23914164

Modeling flash floods in ungauged mountain catchments of China: A decision tree learning approach for parameter regionalization

NASA Astrophysics Data System (ADS)

Ragettli, S.; Zhou, J.; Wang, H.; Liu, C.; Guo, L.

2017-12-01

Flash floods in small mountain catchments are one of the most frequent causes of loss of life and property from natural hazards in China. Hydrological models can be a useful tool for the anticipation of these events and the issuing of timely warnings. One of the main challenges of setting up such a system is finding appropriate model parameter values for ungauged catchments. Previous studies have shown that the transfer of parameter sets from hydrologically similar gauged catchments is one of the best performing regionalization methods. However, a remaining key issue is the identification of suitable descriptors of similarity. In this study, we use decision tree learning to explore parameter set transferability in the full space of catchment descriptors. For this purpose, a semi-distributed rainfall-runoff model is set up for 35 catchments in ten Chinese provinces. Hourly runoff data from in total 858 storm events are used to calibrate the model and to evaluate the performance of parameter set transfers between catchments. We then present a novel technique that uses the splitting rules of classification and regression trees (CART) for finding suitable donor catchments for ungauged target catchments. The ability of the model to detect flood events in assumed ungauged catchments is evaluated in series of leave-one-out tests. We show that CART analysis increases the probability of detection of 10-year flood events in comparison to a conventional measure of physiographic-climatic similarity by up to 20%. Decision tree learning can outperform other regionalization approaches because it generates rules that optimally consider spatial proximity and physical similarity. Spatial proximity can be used as a selection criteria but is skipped in the case where no similar gauged catchments are in the vicinity. We conclude that the CART regionalization concept is particularly suitable for implementation in sparsely gauged and topographically complex environments where a proximity-based regionalization concept is not applicable.

Connecting People to Place: Stories, Science, Deep Maps, and Geo-Quests for Place-Based Learning

NASA Astrophysics Data System (ADS)

Hagley, C. A.; Silbernagel, J.; Host, G.; Hart, D. A.; Axler, R.; Fortner, R. W.; Axler, M.; Smith, V.; Drewes, A.; Bartsch, W.; Danz, N.; Mathews, J.; Wagler, M.

2016-02-01

The St. Louis River Estuary project (stlouisriverestuary.org) is about connecting the stories with the science of this special place to enhance spatial awareness and stewardship of the estuary. The stories, or spatial narratives, are told through vignettes of local resource activities, framed by perspectives of local people. The spatial narratives, developed through interviews and research, target six key activities of the estuary. The science is based on stressor gradients research, incorporating factors such as population and road density, pollutant point source density, and land use. The stressor gradient developed based on these factors was used as a basis for sampling water quality and plant and macroinvertebrate communities, with the intent of quantifying relationships between land-based stressors and aquatic ecosystem indicators of condition. The stories and science are interwoven, located in place on a Deep Map, and played out in GeoQuests to illustrate the complexity and multiple perspectives within the estuary's social, economic and ecological systems. Students, decision-makers, and Lake Superior enthusiasts can engage more deeply in the complexity of the stories and science by challenging themselves with these GeoQuests played on mobile devices. We hope these place-based learning tools will be valuable in advancing spatial literacy and conversation around environmental sustainability in coastal communities.

Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing.

PubMed

Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin

2017-11-01

Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.

Treadmill Exercise Ameliorates Spatial Learning and Memory Deficits Through Improving the Clearance of Peripheral and Central Amyloid-Beta Levels.

PubMed

Khodadadi, Davar; Gharakhanlou, Reza; Naghdi, Naser; Salimi, Mona; Azimi, Mohammad; Shahed, Atabak; Heysieattalab, Soomaayeh

2018-06-11

Aggregated amyloid beta (Aβ) peptides are believed to play a decisive role in the pathology of Alzheimer's disease (AD). Previous evidence suggested that exercise contributes to the improvement of cognitive decline and slows down pathogenesis of AD; however, the exact mechanisms for this have not been fully understood. Here, we evaluated the effect of a 4-week moderate treadmill exercise on spatial memory via central and peripheral Aβ clearance mechanisms following developed AD-like neuropathology induced by intra-hippocampal Aβ 1-42 injection in male Wistar rats. We found Aβ 1-42 -treated animals showed spatial learning and memory impairment which was accompanied by increased levels of amyloid plaque load and soluble Aβ 1-42 (sAβ 1-42 ), decreased mRNA and protein expression of neprilysin (NEP), insulin degrading enzyme (IDE) and low-density lipoprotein receptor-related protein-1 (LRP-1) in the hippocampus. Aβ 1-42 -treated animals also exhibited a higher level of sAβ 1-42 and a lower level of soluble LRP-1 (sLRP-1) in plasma, as well as a decreased level of LRP-1 mRNA and protein content in the liver. However, exercise training improved the spatial learning and memory deficits, reduced both plaque load and sAβ 1-42 levels, and up-regulated expression of NEP, IDE, and LRP-1 in the hippocampus of Aβ 1-42 -treated animals. Aβ 1-42 -treated animals subjected to treadmill exercise also revealed decreased levels of sAβ 1-42 and increased levels of sLRP-1 in plasma, as well as increased levels of LRP-1 mRNA and protein in the liver. In conclusion, our findings suggest that exercise-induced improvement in both of central and peripheral Aβ clearance are likely involved in ameliorating spatial learning and memory deficits in an animal model of AD. Future studies need to determine their relative contribution.

E-Learning in Photogrammetry, Remote Sensing and Spatial Information Science

NASA Astrophysics Data System (ADS)

Vyas, Anjana; König, Gerhard

2016-06-01

Science and technology are evolving leaps and bounds. The advancements in GI-Science for natural and built environment helps in improving the quality of life. Learning through education and training needs to be at par with those advancements, which plays a vital role in utilization of technology. New technologies that creates new opportunities have enabled Geomatics to broaden the horizon (skills and competencies). Government policies and decisions support the use of geospatial science in various sectors of governance. Mapping, Land management, Urban planning, Environmental planning, Industrialization are some of the areas where the geomatics has become a baseline for decision making at national level. There is a need to bridge the gap between developments in geospatial science and its utilization and implementation. To prepare a framework for standardisation it is important to understand the theories of education and prevailing practices, with articulate goals exploring variety of teaching techniques. E-Learning is an erudition practice shaped for facilitating learning and improving performance by creating, using and managing appropriate technological processes and resources through digital and network-enabled technology. It is a shift from traditional education or training to ICT-based flexible and collaborative learning based on the community of learners, academia, professionals, experts and facilitators. Developments in e-learning is focussed on computer assisted learning which has become popular because of its potential for providing more flexible access to content and instruction at any time, from any place (Means et al, 2009). With the advent of the geo-spatial technology, fast development in the software and hardware, the demand for skilled manpower is increasing and the need is for training, education, research and dissemination. It suggests inter-organisational cooperation between academia, industry, government and international collaboration. There is a nascent need to adopt multi-specialisation approach to examine the issues and challenges of research in such a valued topic of education and training in multi-disciplinary areas. Learning involve a change in an individual's knowledge, ability to perform a skill, participate and communicate. There is considerable variation among the theories about the nature of this change. This paper derives from a scientific research grant received from ISPRS, reveals a summary result from assessing various theories and methods of evaluation of learning through education, system and structure of it for GeoInformatics.

Augmented Hebbian reweighting accounts for accuracy and induced bias in perceptual learning with reverse feedback

PubMed Central

Liu, Jiajuan; Dosher, Barbara Anne; Lu, Zhong-Lin

2015-01-01

Using an asymmetrical set of vernier stimuli (−15″, −10″, −5″, +10″, +15″) together with reverse feedback on the small subthreshold offset stimulus (−5″) induces response bias in performance (Aberg & Herzog, 2012; Herzog, Eward, Hermens, & Fahle, 2006; Herzog & Fahle, 1999). These conditions are of interest for testing models of perceptual learning because the world does not always present balanced stimulus frequencies or accurate feedback. Here we provide a comprehensive model for the complex set of asymmetric training results using the augmented Hebbian reweighting model (Liu, Dosher, & Lu, 2014; Petrov, Dosher, & Lu, 2005, 2006) and the multilocation integrated reweighting theory (Dosher, Jeter, Liu, & Lu, 2013). The augmented Hebbian learning algorithm incorporates trial-by-trial feedback, when present, as another input to the decision unit and uses the observer's internal response to update the weights otherwise; block feedback alters the weights on bias correction (Liu et al., 2014). Asymmetric training with reversed feedback incorporates biases into the weights between representation and decision. The model correctly predicts the basic induction effect, its dependence on trial-by-trial feedback, and the specificity of bias to stimulus orientation and spatial location, extending the range of augmented Hebbian reweighting accounts of perceptual learning. PMID:26418382

Augmented Hebbian reweighting accounts for accuracy and induced bias in perceptual learning with reverse feedback.

PubMed

Liu, Jiajuan; Dosher, Barbara Anne; Lu, Zhong-Lin

2015-01-01

Using an asymmetrical set of vernier stimuli (-15″, -10″, -5″, +10″, +15″) together with reverse feedback on the small subthreshold offset stimulus (-5″) induces response bias in performance (Aberg & Herzog, 2012; Herzog, Eward, Hermens, & Fahle, 2006; Herzog & Fahle, 1999). These conditions are of interest for testing models of perceptual learning because the world does not always present balanced stimulus frequencies or accurate feedback. Here we provide a comprehensive model for the complex set of asymmetric training results using the augmented Hebbian reweighting model (Liu, Dosher, & Lu, 2014; Petrov, Dosher, & Lu, 2005, 2006) and the multilocation integrated reweighting theory (Dosher, Jeter, Liu, & Lu, 2013). The augmented Hebbian learning algorithm incorporates trial-by-trial feedback, when present, as another input to the decision unit and uses the observer's internal response to update the weights otherwise; block feedback alters the weights on bias correction (Liu et al., 2014). Asymmetric training with reversed feedback incorporates biases into the weights between representation and decision. The model correctly predicts the basic induction effect, its dependence on trial-by-trial feedback, and the specificity of bias to stimulus orientation and spatial location, extending the range of augmented Hebbian reweighting accounts of perceptual learning.

Modeling flash floods in ungauged mountain catchments of China: A decision tree learning approach for parameter regionalization

NASA Astrophysics Data System (ADS)

Ragettli, S.; Zhou, J.; Wang, H.; Liu, C.

2017-12-01

Flash floods in small mountain catchments are one of the most frequent causes of loss of life and property from natural hazards in China. Hydrological models can be a useful tool for the anticipation of these events and the issuing of timely warnings. Since sub-daily streamflow information is unavailable for most small basins in China, one of the main challenges is finding appropriate parameter values for simulating flash floods in ungauged catchments. In this study, we use decision tree learning to explore parameter set transferability between different catchments. For this purpose, the physically-based, semi-distributed rainfall-runoff model PRMS-OMS is set up for 35 catchments in ten Chinese provinces. Hourly data from more than 800 storm runoff events are used to calibrate the model and evaluate the performance of parameter set transfers between catchments. For each catchment, 58 catchment attributes are extracted from several data sets available for whole China. We then use a data mining technique (decision tree learning) to identify catchment similarities that can be related to good transfer performance. Finally, we use the splitting rules of decision trees for finding suitable donor catchments for ungauged target catchments. We show that decision tree learning allows to optimally utilize the information content of available catchment descriptors and outperforms regionalization based on a conventional measure of physiographic-climatic similarity by 15%-20%. Similar performance can be achieved with a regionalization method based on spatial proximity, but decision trees offer flexible rules for selecting suitable donor catchments, not relying on the vicinity of gauged catchments. This flexibility makes the method particularly suitable for implementation in sparsely gauged environments. We evaluate the probability to detect flood events exceeding a given return period, considering measured discharge and PRMS-OMS simulated flows with regionalized parameters. Overall, the probability of detection of an event with a return period of 10 years is 62%. 44% of all 10-year flood peaks can be detected with a timing error of 2 hours or less. These results indicate that the modeling system can provide useful information about the timing and magnitude of flood events at ungauged sites.

[Learning virtual routes: what does verbal coding do in working memory?].

PubMed

Gyselinck, Valérie; Grison, Élise; Gras, Doriane

2015-03-01

Two experiments were run to complete our understanding of the role of verbal and visuospatial encoding in the construction of a spatial model from visual input. In experiment 1 a dual task paradigm was applied to young adults who learned a route in a virtual environment and then performed a series of nonverbal tasks to assess spatial knowledge. Results indicated that landmark knowledge as asserted by the visual recognition of landmarks was not impaired by any of the concurrent task. Route knowledge, assessed by recognition of directions, was impaired both by a tapping task and a concurrent articulation task. Interestingly, the pattern was modulated when no landmarks were available to perform the direction task. A second experiment was designed to explore the role of verbal coding on the construction of landmark and route knowledge. A lexical-decision task was used as a verbal-semantic dual task, and a tone decision task as a nonsemantic auditory task. Results show that these new concurrent tasks impaired differently landmark knowledge and route knowledge. Results can be interpreted as showing that the coding of route knowledge could be grounded on both a coding of the sequence of events and on a semantic coding of information. These findings also point on some limits of Baddeley's working memory model. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Exploring Deep Learning and Sparse Matrix Format Selection

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

Zhao, Y.; Liao, C.; Shen, X.

We proposed to explore the use of Deep Neural Networks (DNN) for addressing the longstanding barriers. The recent rapid progress of DNN technology has created a large impact in many fields, which has significantly improved the prediction accuracy over traditional machine learning techniques in image classifications, speech recognitions, machine translations, and so on. To some degree, these tasks resemble the decision makings in many HPC tasks, including the aforementioned format selection for SpMV and linear solver selection. For instance, sparse matrix format selection is akin to image classification—such as, to tell whether an image contains a dog or a cat;more » in both problems, the right decisions are primarily determined by the spatial patterns of the elements in an input. For image classification, the patterns are of pixels, and for sparse matrix format selection, they are of non-zero elements. DNN could be naturally applied if we regard a sparse matrix as an image and the format selection or solver selection as classification problems.« less

Designing a Hydro-Economic Collaborative Computer Decision Support System: Approaches, Best Practices, Lessons Learned, and Future Trends

NASA Astrophysics Data System (ADS)

Rosenberg, D. E.

2008-12-01

Designing and implementing a hydro-economic computer model to support or facilitate collaborative decision making among multiple stakeholders or users can be challenging and daunting. Collaborative modeling is distinguished and more difficult than non-collaborative efforts because of a large number of users with different backgrounds, disagreement or conflict among stakeholders regarding problem definitions, modeling roles, and analysis methods, plus evolving ideas of model scope and scale and needs for information and analysis as stakeholders interact, use the model, and learn about the underlying water system. This presentation reviews the lifecycle for collaborative model making and identifies some key design decisions that stakeholders and model developers must make to develop robust and trusted, verifiable and transparent, integrated and flexible, and ultimately useful models. It advances some best practices to implement and program these decisions. Among these best practices are 1) modular development of data- aware input, storage, manipulation, results recording and presentation components plus ways to couple and link to other models and tools, 2) explicitly structure both input data and the meta data that describes data sources, who acquired it, gaps, and modifications or translations made to put the data in a form usable by the model, 3) provide in-line documentation on model inputs, assumptions, calculations, and results plus ways for stakeholders to document their own model use and share results with others, and 4) flexibly program with graphical object-oriented properties and elements that allow users or the model maintainers to easily see and modify the spatial, temporal, or analysis scope as the collaborative process moves forward. We draw on examples of these best practices from the existing literature, the author's prior work, and some new applications just underway. The presentation concludes by identifying some future directions for collaborative modeling including geo-spatial display and analysis, real-time operations, and internet-based tools plus the design and programming needed to implement these capabilities.

VEGETATION COVER ANALYSIS OF HAZARDOUS WASTE SITES IN UTAH AND ARIZONA USING HYPERSPECTRAL REMOTE SENSING

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

Serrato, M.; Jungho, I.; Jensen, J.

2012-01-17

Remote sensing technology can provide a cost-effective tool for monitoring hazardous waste sites. This study investigated the usability of HyMap airborne hyperspectral remote sensing data (126 bands at 2.3 x 2.3 m spatial resolution) to characterize the vegetation at U.S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. The specific objectives of this study were to: (1) estimate leaf-area-index (LAI) of the vegetation using threemore » different methods (i.e., vegetation indices, red-edge positioning (REP), and machine learning regression trees), and (2) map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF)-derived metrics and vegetation indices. Regression trees resulted in the best calibration performance of LAI estimation (R{sup 2} > 0.80). The use of REPs failed to accurately predict LAI (R{sup 2} < 0.2). The use of the MTMF-derived metrics (matched filter scores and infeasibility) and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI) and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of 1 higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches (< 1m) found on the sites.« less

Dissociation between dorsal and ventral hippocampal theta oscillations during decision-making.

PubMed

Schmidt, Brandy; Hinman, James R; Jacobson, Tara K; Szkudlarek, Emily; Argraves, Melissa; Escabí, Monty A; Markus, Etan J

2013-04-03

Hippocampal theta oscillations are postulated to support mnemonic processes in humans and rodents. Theta oscillations facilitate encoding and spatial navigation, but to date, it has been difficult to dissociate the effects of volitional movement from the cognitive demands of a task. Therefore, we examined whether volitional movement or cognitive demands exerted a greater modulating factor over theta oscillations during decision-making. Given the anatomical, electrophysiological, and functional dissociations along the dorsal-ventral axis, theta oscillations were simultaneously recorded in the dorsal and ventral hippocampus in rats trained to switch between place and motor-response strategies. Stark differences in theta characteristics were found between the dorsal and ventral hippocampus in frequency, power, and coherence. Theta power increased in the dorsal, but decreased in the ventral hippocampus, during the decision-making epoch. Interestingly, the relationship between running speed and theta power was uncoupled during the decision-making epoch, a phenomenon limited to the dorsal hippocampus. Theta frequency increased in both the dorsal and ventral hippocampus during the decision epoch, although this effect was greater in the dorsal hippocampus. Despite these differences, ventral hippocampal theta was responsive to the navigation task; theta frequency, power, and coherence were all affected by cognitive demands. Theta coherence increased within the dorsal hippocampus during the decision-making epoch on all three tasks. However, coherence selectively increased throughout the hippocampus (dorsal to ventral) on the task with new hippocampal learning. Interestingly, most results were consistent across tasks, regardless of hippocampal-dependent learning. These data indicate increased integration and cooperation throughout the hippocampus during information processing.

Deep learning with convolutional neural networks for EEG decoding and visualization

PubMed Central

Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-01-01

Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865

Deep learning with convolutional neural networks for EEG decoding and visualization.

PubMed

Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-11-01

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Normal tissue complication probability (NTCP) modelling using spatial dose metrics and machine learning methods for severe acute oral mucositis resulting from head and neck radiotherapy.

PubMed

Dean, Jamie A; Wong, Kee H; Welsh, Liam C; Jones, Ann-Britt; Schick, Ulrike; Newbold, Kate L; Bhide, Shreerang A; Harrington, Kevin J; Nutting, Christopher M; Gulliford, Sarah L

2016-07-01

Severe acute mucositis commonly results from head and neck (chemo)radiotherapy. A predictive model of mucositis could guide clinical decision-making and inform treatment planning. We aimed to generate such a model using spatial dose metrics and machine learning. Predictive models of severe acute mucositis were generated using radiotherapy dose (dose-volume and spatial dose metrics) and clinical data. Penalised logistic regression, support vector classification and random forest classification (RFC) models were generated and compared. Internal validation was performed (with 100-iteration cross-validation), using multiple metrics, including area under the receiver operating characteristic curve (AUC) and calibration slope, to assess performance. Associations between covariates and severe mucositis were explored using the models. The dose-volume-based models (standard) performed equally to those incorporating spatial information. Discrimination was similar between models, but the RFCstandard had the best calibration. The mean AUC and calibration slope for this model were 0.71 (s.d.=0.09) and 3.9 (s.d.=2.2), respectively. The volumes of oral cavity receiving intermediate and high doses were associated with severe mucositis. The RFCstandard model performance is modest-to-good, but should be improved, and requires external validation. Reducing the volumes of oral cavity receiving intermediate and high doses may reduce mucositis incidence. Copyright © 2016 The Author(s). Published by Elsevier Ireland Ltd.. All rights reserved.

[Spatial imprinting influence on development of cognitive process in adult animals].

PubMed

Serkova, V V; Nikol'skaia, K A

2013-12-01

The influence of spatial imprinting on cognitive activity of adult mice F1 from DBA/2J C57BL/6J in a transformable multialternative maze has been studied. A control mice initially learned in a maze with "direct" and "bypass" pathway between feeders. They successfully formed a food-getting habit after 9-10 sessions using mainly direct pathway, so the final route decision was consistent with the principle of least action. Experimental mice previously placed into reduced maze with only "bypass" pathway between feeders for 1-2 trials (1-3 min), and turn up in the complete maze immediately after that. Experimental mice could not organize a food-getting behavior according a task conditions since attempted to include in final decision both "direct" and "bypass" pathways, united in a single ring-like construction. They demonstrated situational behavior running from one feeder to another one, despite of fact that therein had no feed. So it opposed the realization of least action principle, becoming a source of psycho-emotional stress. The results showed that spatial information perceiving in the first few minutes of exploring the experimental environment can manifest itself as the acquired preference and come in conflict with an instinctive one. Cognitive dissonance predetermined the direction of the cognitive process.

Sex-dependent effects of developmental exposure to different pesticides on spatial learning. The role of induced neuroinflammation in the hippocampus.

PubMed

Gómez-Giménez, Belén; Llansola, Marta; Hernández-Rabaza, Vicente; Cabrera-Pastor, Andrea; Malaguarnera, Michele; Agusti, Ana; Felipo, Vicente

2017-01-01

The use of pesticides has been associated with impaired neurodevelopment in children. The aims of this work were to assess: 1) the effects on spatial learning of developmental exposure to pesticides 2) if the effects are sex-dependent and 3) if hippocampal neuroinflammation is associated with the impairment of spatial learning. We analyzed the effects of developmental exposure to four pesticides: chlorpyrifos, carbaryl, endosulfan and cypermethrin. Exposure was from gestational day 7 to post-natal day 21 and spatial learning and memory was assessed when the rats were young adults. The effects of pesticides on spatial learning were pesticide and gender-dependent. Carbaryl did not affect spatial learning in males or females. Endosulfan and chlorpyrifos impaired learning in males but not in females. Cypermethrin improved spatial learning in the Morris water maze both in males and females while impaired learning in the radial maze only in males. Spatial learning ability was lower in control female rats than in males. All pesticides induced neuroinflammation, increasing IL-1b content in the hippocampus and there is a negative correlation between IL-1b levels in the hippocampus and spatial learning. Neuroinflammation would contribute to the effects of pesticides on spatial learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design and realization of tourism spatial decision support system based on GIS

NASA Astrophysics Data System (ADS)

Ma, Zhangbao; Qi, Qingwen; Xu, Li

2008-10-01

In this paper, the existing problems of current tourism management information system are analyzed. GIS, tourism as well as spatial decision support system are introduced, and the application of geographic information system technology and spatial decision support system to tourism management and the establishment of tourism spatial decision support system based on GIS are proposed. System total structure, system hardware and software environment, database design and structure module design of this system are introduced. Finally, realization methods of this systemic core functions are elaborated.

Decision Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability Perspective

ERIC Educational Resources Information Center

Erskine, Michael A.

2013-01-01

As many consumer and business decision makers are utilizing Spatial Decision Support Systems (SDSS), a thorough understanding of how such decisions are made is crucial for the information systems domain. This dissertation presents six chapters encompassing a comprehensive analysis of the impact of geospatial reasoning ability on…

Incidental learning speeds visual search by lowering response thresholds, not by improving efficiency: evidence from eye movements.

PubMed

Hout, Michael C; Goldinger, Stephen D

2012-02-01

When observers search for a target object, they incidentally learn the identities and locations of "background" objects in the same display. This learning can facilitate search performance, eliciting faster reaction times for repeated displays. Despite these findings, visual search has been successfully modeled using architectures that maintain no history of attentional deployments; they are amnesic (e.g., Guided Search Theory). In the current study, we asked two questions: 1) under what conditions does such incidental learning occur? And 2) what does viewing behavior reveal about the efficiency of attentional deployments over time? In two experiments, we tracked eye movements during repeated visual search, and we tested incidental memory for repeated nontarget objects. Across conditions, the consistency of search sets and spatial layouts were manipulated to assess their respective contributions to learning. Using viewing behavior, we contrasted three potential accounts for faster searching with experience. The results indicate that learning does not result in faster object identification or greater search efficiency. Instead, familiar search arrays appear to allow faster resolution of search decisions, whether targets are present or absent.

Maze learning by a hybrid brain-computer system

NASA Astrophysics Data System (ADS)

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system.

PubMed

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-13

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system

PubMed Central

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-01-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation. PMID:27619326

The Role of Low-Spatial Frequencies in Lexical Decision and Masked Priming

ERIC Educational Resources Information Center

Boden, C.; Giaschi, D.

2009-01-01

Spatial frequency filtering was used to test the hypotheses that low-spatial frequency information in printed text can: (1) lead to a rapid lexical decision or (2) facilitate word recognition. Adult proficient readers made lexical decisions in unprimed and masked repetition priming experiments with unfiltered, low-pass, high-pass and notch…

Sex effects on spatial learning but not on spatial memory retrieval in healthy young adults.

PubMed

Piber, Dominique; Nowacki, Jan; Mueller, Sven C; Wingenfeld, Katja; Otte, Christian

2018-01-15

Sex differences have been found in spatial learning and spatial memory, with several studies indicating that males outperform females. We tested in the virtual Morris Water Maze (vMWM) task, whether sex differences in spatial cognitive processes are attributable to differences in spatial learning or spatial memory retrieval in a large student sample. We tested 90 healthy students (45 women and 45 men) with a mean age of 23.5 years (SD=3.5). Spatial learning and spatial memory retrieval were measured by using the vMWM task, during which participants had to search a virtual pool for a hidden platform, facilitated by visual cues surrounding the pool. Several learning trials assessed spatial learning, while a separate probe trial assessed spatial memory retrieval. We found a significant sex effect during spatial learning, with males showing shorter latency and shorter path length, as compared to females (all p<0.001). Yet, there was no significant sex effect in spatial memory retrieval (p=0.615). Furthermore, post-hoc analyses revealed significant sex differences in spatial search strategies (p<0.05), but no difference in the number of platform crossings (p=0.375). Our results indicate that in healthy young adults, males show faster spatial learning in a virtual environment, as compared to females. Interestingly, we found no significant sex differences during spatial memory retrieval. Our study raises the question, whether men and women use different learning strategies, which nevertheless result in equal performances of spatial memory retrieval. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial decision support system for tobacco enterprise based on spatial data mining

NASA Astrophysics Data System (ADS)

Mei, Xin; Liu, Junyi; Zhang, Xuexia; Cui, Weihong

2007-11-01

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique and spatial data mining (SDM) to construct spatial decision support system (SDSS) of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision based on SDM is given. This paper describes how to use spatial analysis and data mining to realize the spatial decision processing such as monitoring tobacco planted acreage, analyzing and planning the cigarette sale network and so on.

The influence of interdisciplinary collaboration on decision making: a framework to analyse stakeholder coalitions, evolution and learning in strategic delta planning

NASA Astrophysics Data System (ADS)

Vermoolen, Myrthe; Hermans, Leon

2015-04-01

The sustained development of urbanizing deltas requires that conflicting interests are reconciled, in an environment characterized by technical complexity and knowledge limitations. However, integrating ideas and establishing cooperation between actors with different backgrounds and roles still proves a challenge. Agreeing on strategic choices is difficult and implementation of agreed plans may lead to unanticipated and unintended outcomes. How can individual disciplinary perspectives come together and establish a broadly-supported and well-informed plan, the implementation of which contributes to sustainable delta development? The growing recognition of this need to bring together different stakeholders and different disciplinary perspectives runs parallel to a paradigm shift from 'hard' hydrological engineering to multi-functional and more 'soft' hydrological engineering in water management. As a result, there is now more attention for interdisciplinary collaboration that not only takes the physical characteristics of water systems into account, but also the interaction between physical and societal components of these systems. Thus, it is important to study interdisciplinary collaboration and how this influences decision-making. Our research looks into this connection, using a case in delta planning in the Netherlands, where there have been several (attempts for) integration of spatial planning and flood risk/ water management, e.g. in the case of the Dutch Delta Programme. This means that spatial designers and their designs play an important role in the strategic delta planning process as well, next to civil engineers, etc. This study explores the roles of stakeholders, experts and policy makers in interdisciplinary decision-making in dynamic delta planning processes, using theories and methods that focus on coalitions, learning and changes over time in policy and planning processes. This requires an expansion of the existing frameworks to study interdisciplinary collaboration. The question here is how to combine policy science frameworks (e.g. the Advocacy Coalition Framework) and social network methods (e.g. Social Network Analysis) with frameworks that allow a connection with the physical delta systems. This will result in a new framework for analysing interdisciplinary stakeholder coalitions, evolution and learning in strategic delta planning. The use of this framework will be illustrated with an example from strategic delta planning in the Dutch Southwest Delta. With this, we want to see how spatial planning and water management disciplines have combined into new policies for delta management in the Netherlands over the past 25 years.

Dissociation of spatial memory systems in Williams syndrome.

PubMed

Bostelmann, Mathilde; Fragnière, Emilie; Costanzo, Floriana; Di Vara, Silvia; Menghini, Deny; Vicari, Stefano; Lavenex, Pierre; Lavenex, Pamela Banta

2017-11-01

Williams syndrome (WS), a genetic deletion syndrome, is characterized by severe visuospatial deficits affecting performance on both tabletop spatial tasks and on tasks which assess orientation and navigation. Nevertheless, previous studies of WS spatial capacities have ignored the fact that two different spatial memory systems are believed to contribute parallel spatial representations supporting navigation. The place learning system depends on the hippocampal formation and creates flexible relational representations of the environment, also known as cognitive maps. The spatial response learning system depends on the striatum and creates fixed stimulus-response representations, also known as habits. Indeed, no study assessing WS spatial competence has used tasks which selectively target these two spatial memory systems. Here, we report that individuals with WS exhibit a dissociation in their spatial abilities subserved by these two memory systems. As compared to typically developing (TD) children in the same mental age range, place learning performance was impaired in individuals with WS. In contrast, their spatial response learning performance was facilitated. Our findings in individuals with WS and TD children suggest that place learning and response learning interact competitively to control the behavioral strategies normally used to support human spatial navigation. Our findings further suggest that the neural pathways supporting place learning may be affected by the genetic deletion that characterizes WS, whereas those supporting response learning may be relatively preserved. The dissociation observed between these two spatial memory systems provides a coherent theoretical framework to characterize the spatial abilities of individuals with WS, and may lead to the development of new learning strategies based on their facilitated response learning abilities. © 2017 Wiley Periodicals, Inc.

Application GIS on university planning: building a spatial database aided spatial decision

NASA Astrophysics Data System (ADS)

Miao, Lei; Wu, Xiaofang; Wang, Kun; Nong, Yu

2007-06-01

With the development of university and its size enlarging, kinds of resource need to effective management urgently. Spacial database is the right tool to assist administrator's spatial decision. And it's ready for digital campus with integrating existing OMS. It's researched about the campus planning in detail firstly. Following instanced by south china agriculture university it is practiced that how to build the geographic database of the campus building and house for university administrator's spatial decision.

Dorsolateral prefrontal lesions do not impair tests of scene learning and decision-making that require frontal–temporal interaction

PubMed Central

Baxter, Mark G; Gaffan, David; Kyriazis, Diana A; Mitchell, Anna S

2008-01-01

Theories of dorsolateral prefrontal cortex (DLPFC) involvement in cognitive function variously emphasize its involvement in rule implementation, cognitive control, or working and/or spatial memory. These theories predict broad effects of DLPFC lesions on tests of visual learning and memory. We evaluated the effects of DLPFC lesions (including both banks of the principal sulcus) in rhesus monkeys on tests of scene learning and strategy implementation that are severely impaired following crossed unilateral lesions of frontal cortex and inferotemporal cortex. Dorsolateral lesions had no effect on learning of new scene problems postoperatively, or on the implementation of preoperatively acquired strategies. They were also without effect on the ability to adjust choice behaviour in response to a change in reinforcer value, a capacity that requires interaction between the amygdala and frontal lobe. These intact abilities following DLPFC damage support specialization of function within the prefrontal cortex, and suggest that many aspects of memory and strategic and goal-directed behaviour can survive ablation of this structure. PMID:18702721

Spatial short-term memory in children with nonverbal learning disabilities: impairment in encoding spatial configuration.

PubMed

Narimoto, Tadamasa; Matsuura, Naomi; Takezawa, Tomohiro; Mitsuhashi, Yoshinori; Hiratani, Michio

2013-01-01

The authors investigated whether impaired spatial short-term memory exhibited by children with nonverbal learning disabilities is due to a problem in the encoding process. Children with or without nonverbal learning disabilities performed a simple spatial test that required them to remember 3, 5, or 7 spatial items presented simultaneously in random positions (i.e., spatial configuration) and to decide if a target item was changed or all items including the target were in the same position. The results showed that, even when the spatial positions in the encoding and probe phases were similar, the mean proportion correct of children with nonverbal learning disabilities was 0.58 while that of children without nonverbal learning disabilities was 0.84. The authors argue with the results that children with nonverbal learning disabilities have difficulty encoding relational information between spatial items, and that this difficulty is responsible for their impaired spatial short-term memory.

Learning to choose: Cognitive aging and strategy selection learning in decision making.

PubMed

Mata, Rui; von Helversen, Bettina; Rieskamp, Jörg

2010-06-01

Decision makers often have to learn from experience. In these situations, people must use the available feedback to select the appropriate decision strategy. How does the ability to select decision strategies on the basis of experience change with age? We examined younger and older adults' strategy selection learning in a probabilistic inference task using a computational model of strategy selection learning. Older adults showed poorer decision performance compared with younger adults. In particular, older adults performed poorly in an environment favoring the use of a more cognitively demanding strategy. The results suggest that the impact of cognitive aging on strategy selection learning depends on the structure of the decision environment. (c) 2010 APA, all rights reserved

[Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

PubMed

Wu, Dehua

2016-01-01

The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian.

Spatial and reversal learning in the Morris water maze are largely resistant to six hours of REM sleep deprivation following training

PubMed Central

Walsh, Christine M.; Booth, Victoria; Poe, Gina R.

2011-01-01

This first test of the role of REM (rapid eye movement) sleep in reversal spatial learning is also the first attempt to replicate a much cited pair of papers reporting that REM sleep deprivation impairs the consolidation of initial spatial learning in the Morris water maze. We hypothesized that REM sleep deprivation following training would impair both hippocampus-dependent spatial learning and learning a new target location within a familiar environment: reversal learning. A 6-d protocol was divided into the initial spatial learning phase (3.5 d) immediately followed by the reversal phase (2.5 d). During the 6 h following four or 12 training trials/day of initial or reversal learning phases, REM sleep was eliminated and non-REM sleep left intact using the multiple inverted flowerpot method. Contrary to our hypotheses, REM sleep deprivation during four or 12 trials/day of initial spatial or reversal learning did not affect training performance. However, some probe trial measures indicated REM sleep-deprivation–associated impairment in initial spatial learning with four trials/day and enhancement of subsequent reversal learning. In naive animals, REM sleep deprivation during normal initial spatial learning was followed by a lack of preference for the subsequent reversal platform location during the probe. Our findings contradict reports that REM sleep is essential for spatial learning in the Morris water maze and newly reveal that short periods of REM sleep deprivation do not impair concurrent reversal learning. Effects on subsequent reversal learning are consistent with the idea that REM sleep serves the consolidation of incompletely learned items. PMID:21677190

From Executive Desks to the Arctic Ocean and Back: A Dynamic Framework for Natural Resource Management

NASA Astrophysics Data System (ADS)

Auad, G.

2017-12-01

The translating of observational evidence for decision- and policy-making needs to be placed within the context of specific organizational structures to achieve efficient and effective natural resource management. To reach that stage, these structures would consistently integrate governance, decision-making, and legislative and policy elements that, as a whole, can be harmoniously coupled to the natural system under consideration, while being aligned toward a high level management goal. Examples will be highlighted where communication structures found in nature connect hierarchical and spatial scales and are the core of effective living and physical systems. Based on these concepts, a framework will be described while linkages and tradeoffs will be established among the different components of the socio-ecological system being addressed. The importance for decision- and policy-makers to define a continuous learning dynamics will be highlighted as a way to ensure enhanced (scientific and traditional) knowledge over time and therefore reduced uncertainty at decision moment. The need for an overarching management goal will be addressed while its underpinnings will be described and conceptually linked through different internal and external communication models.

Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans

PubMed Central

Bornstein, Aaron M.; Daw, Nathaniel D.

2013-01-01

How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward — such as when planning routes using a cognitive map or chess moves using predicted countermoves — and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to be recalled during choice formation. PMID:24339770

Predicting explorative motor learning using decision-making and motor noise.

PubMed

Chen, Xiuli; Mohr, Kieran; Galea, Joseph M

2017-04-01

A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participant's level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning.

Predicting explorative motor learning using decision-making and motor noise

PubMed Central

Galea, Joseph M.

2017-01-01

A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participant’s level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning. PMID:28437451

A mixed integer program to model spatial wildfire behavior and suppression placement decisions

Treesearch

Erin J. Belval; Yu Wei; Michael Bevers

2015-01-01

Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...

Collaborative classification of hyperspectral and visible images with convolutional neural network

NASA Astrophysics Data System (ADS)

Zhang, Mengmeng; Li, Wei; Du, Qian

2017-10-01

Recent advances in remote sensing technology have made multisensor data available for the same area, and it is well-known that remote sensing data processing and analysis often benefit from multisource data fusion. Specifically, low spatial resolution of hyperspectral imagery (HSI) degrades the quality of the subsequent classification task while using visible (VIS) images with high spatial resolution enables high-fidelity spatial analysis. A collaborative classification framework is proposed to fuse HSI and VIS images for finer classification. First, the convolutional neural network model is employed to extract deep spectral features for HSI classification. Second, effective binarized statistical image features are learned as contextual basis vectors for the high-resolution VIS image, followed by a classifier. The proposed approach employs diversified data in a decision fusion, leading to an integration of the rich spectral information, spatial information, and statistical representation information. In particular, the proposed approach eliminates the potential problems of the curse of dimensionality and excessive computation time. The experiments evaluated on two standard data sets demonstrate better classification performance offered by this framework.

On the Science-Policy Bridge: Do Spatial Heat Vulnerability Assessment Studies Influence Policy?

PubMed

Wolf, Tanja; Chuang, Wen-Ching; McGregor, Glenn

2015-10-23

Human vulnerability to heat varies at a range of spatial scales, especially within cities where there can be noticeable intra-urban differences in heat risk factors. Mapping and visualizing intra-urban heat vulnerability offers opportunities for presenting information to support decision-making. For example the visualization of the spatial variation of heat vulnerability has the potential to enable local governments to identify hot spots of vulnerability and allocate resources and increase assistance to people in areas of greatest need. Recently there has been a proliferation of heat vulnerability mapping studies, all of which, to varying degrees, justify the process of vulnerability mapping in a policy context. However, to date, there has not been a systematic review of the extent to which the results of vulnerability mapping studies have been applied in decision-making. Accordingly we undertook a comprehensive review of 37 recently published papers that use geospatial techniques for assessing human vulnerability to heat. In addition, we conducted an anonymous survey of the lead authors of the 37 papers in order to establish the level of interaction between the researchers as science information producers and local authorities as information users. Both paper review and author survey results show that heat vulnerability mapping has been used in an attempt to communicate policy recommendations, raise awareness and induce institutional networking and learning, but has not as yet had a substantive influence on policymaking or preventive action.

Writing affects the brain network of reading in Chinese: a functional magnetic resonance imaging study.

PubMed

Cao, Fan; Vu, Marianne; Chan, Derek Ho Lung; Lawrence, Jason M; Harris, Lindsay N; Guan, Qun; Xu, Yi; Perfetti, Charles A

2013-07-01

We examined the hypothesis that learning to write Chinese characters influences the brain's reading network for characters. Students from a college Chinese class learned 30 characters in a character-writing condition and 30 characters in a pinyin-writing condition. After learning, functional magnetic resonance imaging collected during passive viewing showed different networks for reading Chinese characters and English words, suggesting accommodation to the demands of the new writing system through short-term learning. Beyond these expected differences, we found specific effects of character writing in greater activation (relative to pinyin writing) in bilateral superior parietal lobules and bilateral lingual gyri in both a lexical decision and an implicit writing task. These findings suggest that character writing establishes a higher quality representation of the visual-spatial structure of the character and its orthography. We found a greater involvement of bilateral sensori-motor cortex (SMC) for character-writing trained characters than pinyin-writing trained characters in the lexical decision task, suggesting that learning by doing invokes greater interaction with sensori-motor information during character recognition. Furthermore, we found a correlation of recognition accuracy with activation in right superior parietal lobule, right lingual gyrus, and left SMC, suggesting that these areas support the facilitative effect character writing has on reading. Finally, consistent with previous behavioral studies, we found character-writing training facilitates connections with semantics by producing greater activation in bilateral middle temporal gyri, whereas pinyin-writing training facilitates connections with phonology by producing greater activation in right inferior frontal gyrus. Copyright © 2012 Wiley Periodicals, Inc.

The Influence of Endogenous and Exogenous Spatial Attention on Decision Confidence.

PubMed

Kurtz, Phillipp; Shapcott, Katharine A; Kaiser, Jochen; Schmiedt, Joscha T; Schmid, Michael C

2017-07-25

Spatial attention allows us to make more accurate decisions about events in our environment. Decision confidence is thought to be intimately linked to the decision making process as confidence ratings are tightly coupled to decision accuracy. While both spatial attention and decision confidence have been subjected to extensive research, surprisingly little is known about the interaction between these two processes. Since attention increases performance it might be expected that confidence would also increase. However, two studies investigating the effects of endogenous attention on decision confidence found contradictory results. Here we investigated the effects of two distinct forms of spatial attention on decision confidence; endogenous attention and exogenous attention. We used an orientation-matching task, comparing the two attention conditions (endogenous and exogenous) to a control condition without directed attention. Participants performed better under both attention conditions than in the control condition. Higher confidence ratings than the control condition were found under endogenous attention but not under exogenous attention. This finding suggests that while attention can increase confidence ratings, it must be voluntarily deployed for this increase to take place. We discuss possible implications of this relative overconfidence found only during endogenous attention with respect to the theoretical background of decision confidence.

Neural correlates of object-in-place learning in hippocampus and prefrontal cortex.

PubMed

Kim, Jangjin; Delcasso, Sébastien; Lee, Inah

2011-11-23

Hippocampus and prefrontal cortex (PFC) process spatiotemporally discrete events while maintaining goal-directed task demands. Although some studies have reported that neural activities in the two regions are coordinated, such observations have rarely been reported in an object-place paired-associate (OPPA) task in which animals must learn an object-in-place rule. In this study, we recorded single units and local field potentials simultaneously from the CA1 subfield of the hippocampus and PFC as rats learned that Object A, but not Object B, was rewarded in Place 1, but not in Place 2 (vice versa for Object B). Both hippocampus and PFC are required for normal performance in this task. PFC neurons fired in association with the regularity of the occurrence of a certain type of event independent of space, whereas neuronal firing in CA1 was spatially localized for representing a discrete place. Importantly, the differential firing patterns were observed in tandem with common learning-related changes in both regions. Specifically, once OPPA learning occurred and rats used an object-in-place strategy, (1) both CA1 and PFC neurons exhibited spatially more similar and temporally more synchronized firing patterns, (2) spiking activities in both regions were more phase locked to theta rhythms, and (3) CA1-medial PFC coherence in theta oscillation was maximal before entering a critical place for decision making. The results demonstrate differential as well as common neural dynamics between hippocampus and PFC in acquiring the OPPA task and strongly suggest that both regions form a unified functional network for processing an episodic event.

Neural correlates of object-in-place learning in hippocampus and prefrontal cortex

PubMed Central

Kim, Jangjin; Delcasso, Sébastien; Lee, Inah

2011-01-01

Hippocampus and prefrontal cortex (PFC) process spatiotemporally discrete events while maintaining goal-directed task demands. Although some studies have reported that neural activities in the two regions are coordinated, such observations have rarely been reported in an object-place paired-associate (OPPA) task in which animals must learn an object-in-place rule. In this study, we recorded single units and local field potentials simultaneously from the CA1 subfield of the hippocampus and PFC as rats learned that object A, but not object B, was rewarded in place 1, but not in place 2 (vice versa for object B). Both hippocampus and PFC are required for normal performance in this task. PFC neurons fired in association with the regularity of the occurrence of a certain type of event independent of space, whereas neuronal firing in CA1 was spatially localized for representing a discrete place. Importantly, the differential firing patterns were observed in tandem with common learning-related changes in both regions. Specifically, once OPPA learning occurred and rats used an object-in-place strategy, (i) both CA1 and PFC neurons exhibited spatially more similar and temporally more synchronized firing patterns, (ii) spiking activities in both regions were more phase-locked to theta rhythms, (iii) CA1-mPFC coherence in theta oscillation was maximal before entering a critical place for decision making. The results demonstrate differential as well as common neural dynamics between hippocampus and PFC in acquiring the OPPA task and strongly suggest that both regions form a unified functional network for processing an episodic event. PMID:22114269

[The effects of case-based learning using video on clinical decision making and learning motivation in undergraduate nursing students].

PubMed

Yoo, Moon-Sook; Park, Jin-Hee; Lee, Si-Ra

2010-12-01

The purpose of this study was to examine the effects of case-base learning (CBL) using video on clinical decision-making and learning motivation. This research was conducted between June 2009 and April 2010 as a nonequivalent control group non-synchronized design. The study population was 44 third year nursing students who enrolled in a college of nursing, A University in Korea. The nursing students were divided into the CBL and the control group. The intervention was the CBL with three cases using video. The controls attended a traditional live lecture on the same topics. With questionnaires objective clinical decision-making, subjective clinical decision-making, and learning motivation were measured before the intervention, and 10 weeks after the intervention. Significant group differences were observed in clinical decision-making and learning motivation. The post-test scores of clinical decision-making in the CBL group were statistically higher than the control group. Learning motivation was also significantly higher in the CBL group than in the control group. These results indicate that CBL using video is effective in enhancing clinical decision-making and motivating students to learn by encouraging self-directed learning and creating more interest and curiosity in learning.

Spatial and Temporal Flood Risk Assessment for Decision Making Approach

NASA Astrophysics Data System (ADS)

Azizat, Nazirah; Omar, Wan-Mohd-Sabki Wan

2018-03-01

Heavy rainfall, adversely impacting inundation areas, depends on the magnitude of the flood. Significantly, location of settlements, infrastructure and facilities in floodplains result in many regions facing flooding risks. A problem faced by the decision maker in an assessment of flood vulnerability and evaluation of adaptation measures is recurrent flooding in the same areas. Identification of recurrent flooding areas and frequency of floods should be priorities for flood risk management. However, spatial and temporal variability become major factors of uncertainty in flood risk management. Therefore, dynamic and spatial characteristics of these changes in flood impact assessment are important in making decisions about the future of infrastructure development and community life. System dynamics (SD) simulation and hydrodynamic modelling are presented as tools for modelling the dynamic characteristics of flood risk and spatial variability. This paper discusses the integration between spatial and temporal information that is required by the decision maker for the identification of multi-criteria decision problems involving multiple stakeholders.

A prototype system based on visual interactive SDM called VGC

NASA Astrophysics Data System (ADS)

Jia, Zelu; Liu, Yaolin; Liu, Yanfang

2009-10-01

In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. For spatial data mining of large data sets to be effective, it is also important to include humans in the data exploration process and combine their flexibility, creativity, and general knowledge with the enormous storage capacity and computational power of today's computers. Visual spatial data mining applies human visual perception to the exploration of large data sets. Presenting data in an interactive, graphical form often fosters new insights, encouraging the information and validation of new hypotheses to the end of better problem-solving and gaining deeper domain knowledge. In this paper a visual interactive spatial data mining prototype system (visual geo-classify) based on VC++6.0 and MapObject2.0 are designed and developed, the basic algorithms of the spatial data mining is used decision tree and Bayesian networks, and data classify are used training and learning and the integration of the two to realize. The result indicates it's a practical and extensible visual interactive spatial data mining tool.

Dorsal Hippocampus Function in Learning and Expressing a Spatial Discrimination

ERIC Educational Resources Information Center

White, Norman M.; Gaskin, Stephane

2006-01-01

Learning to discriminate between spatial locations defined by two adjacent arms of a radial maze in the conditioned cue preference paradigm requires two kinds of information: latent spatial learning when the rats explore the maze with no food available, and learning about food availability in two spatial locations when the rats are then confined…

Learning to Make Decisions Through Constructive Controversy.

ERIC Educational Resources Information Center

Tjosvold, Dean

Students must make decisions about their lifestyle, future careers, academic pursuits, and classroom and school issues. Learning to make effective decisions for themselves and for society is an important aspect of competence. They can learn decision making through interacting and solving problems with others. A central ingredient for successful…

Implication of the first decision on visual information-sampling in the spatial frequency domain in pulmonary nodule recognition

NASA Astrophysics Data System (ADS)

Pietrzyk, Mariusz W.; Manning, David; Donovan, Tim; Dix, Alan

2010-02-01

Aim: To investigate the impact on visual sampling strategy and pulmonary nodule recognition of image-based properties of background locations in dwelled regions where the first overt decision was made. . Background: Recent studies in mammography show that the first overt decision (TP or FP) has an influence on further image reading including the correctness of the following decisions. Furthermore, the correlation between the spatial frequency properties of the local background following decision sites and the first decision correctness has been reported. Methods: Subjects with different radiological experience were eye tracked during detection of pulmonary nodules from PA chest radiographs. Number of outcomes and the overall quality of performance are analysed in terms of the cases where correct or incorrect decisions were made. JAFROC methodology is applied. The spatial frequency properties of selected local backgrounds related to a certain decisions were studied. ANOVA was used to compare the logarithmic values of energy carried by non redundant stationary wavelet packet coefficients. Results: A strong correlation has been found between the number of TP as a first decision and the JAFROC score (r = 0.74). The number of FP as a first decision was found negatively correlated with JAFROC (r = -0.75). Moreover, the differential spatial frequency profiles outcomes depend on the first choice correctness.

Incidental learning speeds visual search by lowering response thresholds, not by improving efficiency: Evidence from eye movements

PubMed Central

Hout, Michael C.; Goldinger, Stephen D.

2011-01-01

When observers search for a target object, they incidentally learn the identities and locations of “background” objects in the same display. This learning can facilitate search performance, eliciting faster reaction times for repeated displays (Hout & Goldinger, 2010). Despite these findings, visual search has been successfully modeled using architectures that maintain no history of attentional deployments; they are amnesic (e.g., Guided Search Theory; Wolfe, 2007). In the current study, we asked two questions: 1) under what conditions does such incidental learning occur? And 2) what does viewing behavior reveal about the efficiency of attentional deployments over time? In two experiments, we tracked eye movements during repeated visual search, and we tested incidental memory for repeated non-target objects. Across conditions, the consistency of search sets and spatial layouts were manipulated to assess their respective contributions to learning. Using viewing behavior, we contrasted three potential accounts for faster searching with experience. The results indicate that learning does not result in faster object identification or greater search efficiency. Instead, familiar search arrays appear to allow faster resolution of search decisions, whether targets are present or absent. PMID:21574743

Information gathering, management and transfering for geospacial intelligence

NASA Astrophysics Data System (ADS)

Nunes, Paulo; Correia, Anacleto; Teodoro, M. Filomena

2017-07-01

Information is a key subject in modern organization operations. The success of joint and combined operations with organizations partners depends on the accurate information and knowledge flow concerning the operations theatre: provision of resources, environment evolution, markets location, where and when an event occurred. As in the past and nowadays we cannot conceive modern operations without maps and geo-spatial information (GI). Information and knowledge management is fundamental to the success of organizational decisions in an uncertainty environment. The georeferenced information management is a process of knowledge management, it begins in the raw data and ends on generating knowledge. GI and intelligence systems allow us to integrate all other forms of intelligence and can be a main platform to process and display geo-spatial-time referenced events. Combining explicit knowledge with peoples know-how to generate a continuous learning cycle that supports real time decisions mitigates the influences of fog of everyday competition and provides the knowledge supremacy. Extending the preliminary analysis done in [1], this work applies the exploratory factor analysis to a questionnaire about the GI and intelligence management in an organization company allowing to identify future lines of action to improve information process sharing and exploration of all the potential of this important resource.

Formation of spatial and nonspatial memory in different condensed versions of short-term learning in Morris water maze.

PubMed

Zots, M A; Ivashkina, O I; Ivanova, A A; Anokhin, K V

2014-03-01

We studied the formation of spatial and nonspatial memory in mice during learning in three different condensed versions of Morris water maze task. Learning in combined version caused the formation of both spatial and nonspatial memory, whereas learning in condensed versions (spatial and nonspatial) led to memory formation specific for the version.

Search strategy selection in the Morris water maze indicates allocentric map formation during learning that underpins spatial memory formation.

PubMed

Rogers, Jake; Churilov, Leonid; Hannan, Anthony J; Renoir, Thibault

2017-03-01

Using a Matlab classification algorithm, we demonstrate that a highly salient distal cue array is required for significantly increased likelihoods of spatial search strategy selection during Morris water maze spatial learning. We hypothesized that increased spatial search strategy selection during spatial learning would be the key measure demonstrating the formation of an allocentric map to the escape location. Spatial memory, as indicated by quadrant preference for the area of the pool formally containing the hidden platform, was assessed as the main measure that this allocentric map had formed during spatial learning. Our C57BL/6J wild-type (WT) mice exhibit quadrant preference in the highly salient cue paradigm but not the low, corresponding with a 120% increase in the odds of a spatial search strategy selection during learning. In contrast, quadrant preference remains absent in serotonin 1A receptor (5-HT 1A R) knockout (KO) mice, who exhibit impaired search strategy selection during spatial learning. Additionally, we also aimed to assess the impact of the quality of the distal cue array on the spatial learning curves of both latency to platform and path length using mixed-effect regression models and found no significant associations or interactions. In contrast, we demonstrated that the spatial learning curve for search strategy selection was absent during training in the low saliency paradigm. Therefore, we propose that allocentric search strategy selection during spatial learning is the learning parameter in mice that robustly indicates the formation of a cognitive map for the escape goal location. These results also suggest that both latency to platform and path length spatial learning curves do not discriminate between allocentric and egocentric spatial learning and do not reliably predict spatial memory formation. We also show that spatial memory, as indicated by the absolute time in the quadrant formerly containing the hidden platform alone (without reference to the other areas of the pool), was not sensitive to cue saliency or impaired in 5-HT 1A R KO mice. Importantly, in the absence of a search strategy analysis, this suggests that to establish that the Morris water maze has worked (i.e. control mice have formed an allocentric map to the escape goal location), a measure of quadrant preference needs to be reported to establish spatial memory formation. This has implications for studies that claim hippocampal functioning is impaired using latency to platform or path length differences within the existing Morris water maze literature. Copyright © 2016 Elsevier Inc. All rights reserved.

A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.

PubMed

Khosravi, Khabat; Pham, Binh Thai; Chapi, Kamran; Shirzadi, Ataollah; Shahabi, Himan; Revhaug, Inge; Prakash, Indra; Tien Bui, Dieu

2018-06-15

Floods are one of the most damaging natural hazards causing huge loss of property, infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due to sudden change in climatic condition and manmade factors. However, prior identification of flood susceptible areas can be done with the help of machine learning techniques for proper timely management of flood hazards. In this study, we tested four decision trees based machine learning models namely Logistic Model Trees (LMT), Reduced Error Pruning Trees (REPT), Naïve Bayes Trees (NBT), and Alternating Decision Trees (ADT) for flash flood susceptibility mapping at the Haraz Watershed in the northern part of Iran. For this, a spatial database was constructed with 201 present and past flood locations and eleven flood-influencing factors namely ground slope, altitude, curvature, Stream Power Index (SPI), Topographic Wetness Index (TWI), land use, rainfall, river density, distance from river, lithology, and Normalized Difference Vegetation Index (NDVI). Statistical evaluation measures, the Receiver Operating Characteristic (ROC) curve, and Freidman and Wilcoxon signed-rank tests were used to validate and compare the prediction capability of the models. Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively. These techniques have proven successful in quickly determining flood susceptible areas. Copyright © 2018 Elsevier B.V. All rights reserved.

The importance of spatial ability and mental models in learning anatomy

NASA Astrophysics Data System (ADS)

Chatterjee, Allison K.

As a foundational course in medical education, gross anatomy serves to orient medical and veterinary students to the complex three-dimensional nature of the structures within the body. Understanding such spatial relationships is both fundamental and crucial for achievement in gross anatomy courses, and is essential for success as a practicing professional. Many things contribute to learning spatial relationships; this project focuses on a few key elements: (1) the type of multimedia resources, particularly computer-aided instructional (CAI) resources, medical students used to study and learn; (2) the influence of spatial ability on medical and veterinary students' gross anatomy grades and their mental models; and (3) how medical and veterinary students think about anatomy and describe the features of their mental models to represent what they know about anatomical structures. The use of computer-aided instruction (CAI) by gross anatomy students at Indiana University School of Medicine (IUSM) was assessed through a questionnaire distributed to the regional centers of the IUSM. Students reported using internet browsing, PowerPoint presentation software, and email on a daily bases to study gross anatomy. This study reveals that first-year medical students at the IUSM make limited use of CAI to study gross anatomy. Such studies emphasize the importance of examining students' use of CAI to study gross anatomy prior to development and integration of electronic media into the curriculum and they may be important in future decisions regarding the development of alternative learning resources. In order to determine how students think about anatomical relationships and describe the features of their mental models, personal interviews were conducted with select students based on students' ROT scores. Five typologies of the characteristics of students' mental models were identified and described: spatial thinking, kinesthetic approach, identification of anatomical structures, problem solving strategies, and study methods. Students with different levels of spatial ability visualize and think about anatomy in qualitatively different ways, which is reflected by the features of their mental models. Low spatial ability students thought about and used two-dimensional images from the textbook. They possessed basic two-dimensional models of anatomical structures; they placed emphasis on diagrams and drawings in their studies; and they re-read anatomical problems many times before answering. High spatial ability students thought fully in three-dimensional and imagined rotation and movement of the structures; they made use of many types of images and text as they studied and solved problems. They possessed elaborate three-dimensional models of anatomical structures which they were able to manipulate to solve problems; and they integrated diagrams, drawings, and written text in their studies. Middle spatial ability students were a mix between both low and high spatial ability students. They imagined two-dimensional images popping out of the flat paper to become more three-dimensional, but still relied on drawings and diagrams. Additionally, high spatial ability students used a higher proportion of anatomical terminology than low spatial ability or middle spatial ability students. This provides additional support to the premise that high spatial students' mental models are a complex mixture of imagistic representations and propositional representations that incorporate correct anatomical terminology. Low spatial ability students focused on the function of structures and ways to group information primarily for the purpose of recall. This supports the theory that low spatial students' mental models will be characterized by more on imagistic representations that are general in nature. (Abstract shortened by UMI.)

Cabri 3D - assisted collaborative learning to enhance junior high school students’ spatial ability

NASA Astrophysics Data System (ADS)

Muntazhimah; Miatun, A.

2018-01-01

The main purpose of this quasi-experimental study was to determine the enhancement of spatial ability of junior high school students who learned through Cabri-3D assisted collaborative learning. The methodology of this study was the nonequivalent group that was conducted to students of the eighth grade in a junior high school as a population. Samples consisted one class of the experimental group who studied with Cabri-3D assisted collaborative learning and one class as a control group who got regular learning activity. The instrument used in this study was a spatial ability test. Analyzing normalized gain of students’ spatial ability based on mathemathical prior knowledge (MPK) and its interactions was tested by two-way ANOVA at a significance level of 5% then continued with using Post Hoc Scheffe test. The research results showed that there was significant difference in enhancement of the spatial ability between students who learnt with Cabri 3D assisted collaborative learning and students who got regular learning, there was significant difference in enhancement of the spatial ability between students who learnt with cabri 3D assisted collaborative learning and students who got regular learning in terms of MPK and there is no significant interaction between learning (Cabri-3D assisted collaborative learning and regular learning) with students’ MPK (high, medium, and low) toward the enhancement of students’ spatial abilities. From the above findings, it can be seen that cabri-3D assisted collaborative learning could enhance spatial ability of junior high school students.

Testing domain general learning in an Australian lizard.

PubMed

Qi, Yin; Noble, Daniel W A; Fu, Jinzhong; Whiting, Martin J

2018-06-02

A key question in cognition is whether animals that are proficient in a specific cognitive domain (domain specific hypothesis), such as spatial learning, are also proficient in other domains (domain general hypothesis) or whether there is a trade-off. Studies testing among these hypotheses are biased towards mammals and birds. To understand constraints on the evolution of cognition more generally, we need broader taxonomic and phylogenetic coverage. We used Australian eastern water skinks (Eulamprus quoyii) with known spatial learning ability in three additional tasks: an instrumental and two discrimination tasks. Under domain specific learning we predicted that lizards that were good at spatial learning would perform less well in the discrimination tasks. Conversely, we predicted that lizards that did not meet our criterion for spatial learning would likewise perform better in discrimination tasks. Lizards with domain general learning should perform approximately equally well (or poorly) in these tasks. Lizards classified as spatial learners performed no differently to non-spatial learners in both the instrumental and discrimination learning tasks. Nevertheless, lizards were proficient in all tasks. Our results reveal two patterns: domain general learning in spatial learners and domain specific learning in non-spatial learners. We suggest that delineating learning into domain general and domain specific may be overly simplistic and we need to instead focus on individual variation in learning ability, which ultimately, is likely to play a key role in fitness. These results, in combination with previously published work on this species, suggests that this species has behavioral flexibility because they are competent across multiple cognitive domains and are capable of reversal learning.

Distinct Roles of Dopamine and Subthalamic Nucleus in Learning and Probabilistic Decision Making

ERIC Educational Resources Information Center

Coulthard, Elizabeth J.; Bogacz, Rafal; Javed, Shazia; Mooney, Lucy K.; Murphy, Gillian; Keeley, Sophie; Whone, Alan L.

2012-01-01

Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making…

Spatial attention during saccade decisions.

PubMed

Jonikaitis, Donatas; Klapetek, Anna; Deubel, Heiner

2017-07-01

Behavioral measures of decision making are usually limited to observations of decision outcomes. In the present study, we made use of the fact that oculomotor and sensory selection are closely linked to track oculomotor decision making before oculomotor responses are made. We asked participants to make a saccadic eye movement to one of two memorized target locations and observed that visual sensitivity increased at both the chosen and the nonchosen saccade target locations, with a clear bias toward the chosen target. The time course of changes in visual sensitivity was related to saccadic latency, with the competition between the chosen and nonchosen targets resolved faster before short-latency saccades. On error trials, we observed an increased competition between the chosen and nonchosen targets. Moreover, oculomotor selection and visual sensitivity were influenced by top-down and bottom-up factors as well as by selection history and predicted the direction of saccades. Our findings demonstrate that saccade decisions have direct visual consequences and show that decision making can be traced in the human oculomotor system well before choices are made. Our results also indicate a strong association between decision making, saccade target selection, and visual sensitivity. NEW & NOTEWORTHY We show that saccadic decisions can be tracked by measuring spatial attention. Spatial attention is allocated in parallel to the two competing saccade targets, and the time course of spatial attention differs for fast-slow and for correct-erroneous decisions. Saccade decisions take the form of a competition between potential saccade goals, which is associated with spatial attention allocation to those locations. Copyright © 2017 the American Physiological Society.

Multi Criteria Evaluation Module for RiskChanges Spatial Decision Support System

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; Jaboyedoff, Michel; van Westen, Cees; Bakker, Wim

2015-04-01

Multi-Criteria Evaluation (MCE) module is one of the five modules of RiskChanges spatial decision support system. RiskChanges web-based platform aims to analyze changes in hydro-meteorological risk and provides tools for selecting the best risk reduction alternative. It is developed under CHANGES framework (changes-itn.eu) and INCREO project (increo-fp7.eu). MCE tool helps decision makers and spatial planners to evaluate, sort and rank the decision alternatives. The users can choose among different indicators that are defined within the system using Risk and Cost Benefit analysis results besides they can add their own indicators. Subsequently the system standardizes and prioritizes them. Finally, the best decision alternative is selected by using the weighted sum model (WSM). The Application of this work is to facilitate the effect of MCE for analyzing changing risk over the time under different scenarios and future years by adopting a group decision making into practice and comparing the results by numeric and graphical view within the system. We believe that this study helps decision-makers to achieve the best solution by expressing their preferences for strategies under future scenarios. Keywords: Multi-Criteria Evaluation, Spatial Decision Support System, Weighted Sum Model, Natural Hazard Risk Management

Aspects of decision support in water management--example Berlin and Potsdam (Germany) I--spatially differentiated evaluation.

PubMed

Simon, Ute; Brüggemann, Rainer; Pudenz, Stefan

2004-04-01

Decisions about sustainable development demand spatially differentiated evaluations. As an example, we demonstrate the evaluation of water management strategies in the cities of Berlin and Potsdam (Germany) with respect to their ecological effects in 14 sections of the surface water system. Two decision support systems were compared, namely PROMETHEE, which is designed to obtain a clear decision (linear ranking), and Hasse Diagram Technique (HDT), normally providing more than one favourable solution (partial order). By PROMETHEE, the spatial differentiation had unwanted effects on the result, negating the stakeholders determined weighting of indicators. Therefore, the stakeholder can barely benefit from the convenience of obtaining a clear decision (linear ranking). In contrast, the result obtained by HDT was not influenced by spatial differentiation. Furthermore, HDT provided helpful tools to analyse the evaluation result, such as the concept of antagonistic indicators to discover conflicts in the evaluation process.

Texas urban triangle : creating a spatial decision support system for mobility policy and investments that shape the sustainable growth of Texas.

DOT National Transportation Integrated Search

2010-11-01

This project developed a GIS-based Spatial Decision Support System to help local, metropolitan, and state : jurisdictions and authorities in Texas understand the implications of transportation planning and : investment decisions, and plan appropriate...

Use of Inverse Reinforcement Learning for Identity Prediction

NASA Technical Reports Server (NTRS)

Hayes, Roy; Bao, Jonathan; Beling, Peter; Horowitz, Barry

2011-01-01

We adopt Markov Decision Processes (MDP) to model sequential decision problems, which have the characteristic that the current decision made by a human decision maker has an uncertain impact on future opportunity. We hypothesize that the individuality of decision makers can be modeled as differences in the reward function under a common MDP model. A machine learning technique, Inverse Reinforcement Learning (IRL), was used to learn an individual's reward function based on limited observation of his or her decision choices. This work serves as an initial investigation for using IRL to analyze decision making, conducted through a human experiment in a cyber shopping environment. Specifically, the ability to determine the demographic identity of users is conducted through prediction analysis and supervised learning. The results show that IRL can be used to correctly identify participants, at a rate of 68% for gender and 66% for one of three college major categories.

Manipulating memory efficacy affects the behavioral and neural profiles of deterministic learning and decision-making.

PubMed

Tremel, Joshua J; Ortiz, Daniella M; Fiez, Julie A

2018-06-01

When making a decision, we have to identify, collect, and evaluate relevant bits of information to ensure an optimal outcome. How we approach a given choice can be influenced by prior experience. Contextual factors and structural elements of these past decisions can cause a shift in how information is encoded and can in turn influence later decision-making. In this two-experiment study, we sought to manipulate declarative memory efficacy and decision-making in a concurrent discrimination learning task by altering the amount of information to be learned. Subjects learned correct responses to pairs of items across several repetitions of a 50- or 100-pair set and were tested for memory retention. In one experiment, this memory test interrupted learning after an initial encoding experience in order to test for early encoding differences and associate those differences with changes in decision-making. In a second experiment, we used fMRI to probe neural differences between the two list-length groups related to decision-making across learning and assessed subsequent memory retention. We found that a striatum-based system was associated with decision-making patterns when learning a longer list of items, while a medial cortical network was associated with patterns when learning a shorter list. Additionally, the hippocampus was exclusively active for the shorter list group. Altogether, these behavioral, computational, and imaging results provide evidence that multiple types of mnemonic representations contribute to experienced-based decision-making. Moreover, contextual and structural factors of the task and of prior decisions can influence what types of evidence are drawn upon during decision-making. Copyright © 2018 Elsevier Ltd. All rights reserved.

Collective learning and optimal consensus decisions in social animal groups.

PubMed

Kao, Albert B; Miller, Noam; Torney, Colin; Hartnett, Andrew; Couzin, Iain D

2014-08-01

Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context.

Collective Learning and Optimal Consensus Decisions in Social Animal Groups

PubMed Central

Kao, Albert B.; Miller, Noam; Torney, Colin; Hartnett, Andrew; Couzin, Iain D.

2014-01-01

Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context. PMID:25101642

Recent advances in environmental data mining

NASA Astrophysics Data System (ADS)

Leuenberger, Michael; Kanevski, Mikhail

2016-04-01

Due to the large amount and complexity of data available nowadays in geo- and environmental sciences, we face the need to develop and incorporate more robust and efficient methods for their analysis, modelling and visualization. An important part of these developments deals with an elaboration and application of a contemporary and coherent methodology following the process from data collection to the justification and communication of the results. Recent fundamental progress in machine learning (ML) can considerably contribute to the development of the emerging field - environmental data science. The present research highlights and investigates the different issues that can occur when dealing with environmental data mining using cutting-edge machine learning algorithms. In particular, the main attention is paid to the description of the self-consistent methodology and two efficient algorithms - Random Forest (RF, Breiman, 2001) and Extreme Learning Machines (ELM, Huang et al., 2006), which recently gained a great popularity. Despite the fact that they are based on two different concepts, i.e. decision trees vs artificial neural networks, they both propose promising results for complex, high dimensional and non-linear data modelling. In addition, the study discusses several important issues of data driven modelling, including feature selection and uncertainties. The approach considered is accompanied by simulated and real data case studies from renewable resources assessment and natural hazards tasks. In conclusion, the current challenges and future developments in statistical environmental data learning are discussed. References - Breiman, L., 2001. Random Forests. Machine Learning 45 (1), 5-32. - Huang, G.-B., Zhu, Q.-Y., Siew, C.-K., 2006. Extreme learning machine: theory and applications. Neurocomputing 70 (1-3), 489-501. - Kanevski, M., Pozdnoukhov, A., Timonin, V., 2009. Machine Learning for Spatial Environmental Data. EPFL Press; Lausanne, Switzerland, p.392. - Leuenberger, M., Kanevski, M., 2015. Extreme Learning Machines for spatial environmental data. Computers and Geosciences 85, 64-73.

A smarter way to search, share and utilize open-spatial online data for energy R&D - Custom machine learning and GIS tools in U.S. DOE's virtual data library & laboratory, EDX

NASA Astrophysics Data System (ADS)

Rose, K.; Bauer, J.; Baker, D.; Barkhurst, A.; Bean, A.; DiGiulio, J.; Jones, K.; Jones, T.; Justman, D.; Miller, R., III; Romeo, L.; Sabbatino, M.; Tong, A.

2017-12-01

As spatial datasets are increasingly accessible through open, online systems, the opportunity to use these resources to address a range of Earth system questions grows. Simultaneously, there is a need for better infrastructure and tools to find and utilize these resources. We will present examples of advanced online computing capabilities, hosted in the U.S. DOE's Energy Data eXchange (EDX), that address these needs for earth-energy research and development. In one study the computing team developed a custom, machine learning, big data computing tool designed to parse the web and return priority datasets to appropriate servers to develop an open-source global oil and gas infrastructure database. The results of this spatial smart search approach were validated against expert-driven, manual search results which required a team of seven spatial scientists three months to produce. The custom machine learning tool parsed online, open systems, including zip files, ftp sites and other web-hosted resources, in a matter of days. The resulting resources were integrated into a geodatabase now hosted for open access via EDX. Beyond identifying and accessing authoritative, open spatial data resources, there is also a need for more efficient tools to ingest, perform, and visualize multi-variate, spatial data analyses. Within the EDX framework, there is a growing suite of processing, analytical and visualization capabilities that allow multi-user teams to work more efficiently in private, virtual workspaces. An example of these capabilities are a set of 5 custom spatio-temporal models and data tools that form NETL's Offshore Risk Modeling suite that can be used to quantify oil spill risks and impacts. Coupling the data and advanced functions from EDX with these advanced spatio-temporal models has culminated with an integrated web-based decision-support tool. This platform has capabilities to identify and combine data across scales and disciplines, evaluate potential environmental, social, and economic impacts, highlight knowledge or technology gaps, and reduce uncertainty for a range of `what if' scenarios relevant to oil spill prevention efforts. These examples illustrate EDX's growing capabilities for advanced spatial data search and analysis to support geo-data science needs.

What A Long Strange Trip It's Been: Lessons Learned From NASA EOS, LTER, NEON, CZO And On To The Future With Sustainable Research Networks

NASA Astrophysics Data System (ADS)

Williams, M. W.

2014-12-01

The traditional, small-scale, incremental approach to environmental science is changing as researchers embrace a more integrated and multi-disciplinary approach to understanding how our natural systems work today and how they may respond in the future to forcings such as climate change. In situ networks are evolving in response to these challenges so as to provide the appropriate measurements to develop high-resolution spatial and temporal data sets across a wide range of platforms from microbial measurements to remote sensing. These large programs provide a unique set of challenges when compared to more traditional programs. Here I provide insights learned from my participation in a number of large programs, including NASA EOS, LTER, CZO, NEON, and WSC and how those experiences in environmental science can help us move forward towards more applied applications of environmental science, including sustainability initiatives. I'll chat about the importance of managerial and management skills, which most of us scientists prefer to avoid. I'll also chat about making decisions about what long-term measurements to make and when to stop. Data management is still the weakest part of environmental networks; what needs to be done. We have learned that these networks provide an important knowledge base that can lead to informed decisions leading to environmental, energy, social and cultural sustainability.

Categorization = Decision Making + Generalization

PubMed Central

Seger, Carol A; Peterson, Erik J.

2013-01-01

We rarely, if ever, repeatedly encounter exactly the same situation. This makes generalization crucial for real world decision making. We argue that categorization, the study of generalizable representations, is a type of decision making, and that categorization learning research would benefit from approaches developed to study the neuroscience of decision making. Similarly, methods developed to examine generalization and learning within the field of categorization may enhance decision making research. We first discuss perceptual information processing and integration, with an emphasis on accumulator models. We then examine learning the value of different decision making choices via experience, emphasizing reinforcement learning modeling approaches. Next we discuss how value is combined with other factors in decision making, emphasizing the effects of uncertainty. Finally, we describe how a final decision is selected via thresholding processes implemented by the basal ganglia and related regions. We also consider how memory related functions in the hippocampus may be integrated with decision making mechanisms and contribute to categorization. PMID:23548891

Active and Passive Spatial Learning in Human Navigation: Acquisition of Graph Knowledge

ERIC Educational Resources Information Center

Chrastil, Elizabeth R.; Warren, William H.

2015-01-01

It is known that active exploration of a new environment leads to better spatial learning than does passive visual exposure. We ask whether specific components of active learning differentially contribute to particular forms of spatial knowledge--the "exploration-specific learning hypothesis". Previously, we found that idiothetic…

Spatial Contiguity and Incidental Learning in Multimedia Environments

ERIC Educational Resources Information Center

Paek, Seungoh; Hoffman, Daniel L.; Saravanos, Antonios

2017-01-01

Drawing on dual-process theories of cognitive function, the degree to which spatial contiguity influences incidental learning outcomes was examined. It was hypothesized that spatial contiguity would mediate what was learned even in the absence of an explicit learning goal. To test this hypothesis, 149 adults completed a multimedia-related task…

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

A study on spatial decision support systems for HIV/AIDS prevention based on COM GIS technology

NASA Astrophysics Data System (ADS)

Yang, Kun; Luo, Huasong; Peng, Shungyun; Xu, Quanli

2007-06-01

Based on the deeply analysis of the current status and the existing problems of GIS technology applications in Epidemiology, this paper has proposed the method and process for establishing the spatial decision support systems of AIDS epidemic prevention by integrating the COM GIS, Spatial Database, GPS, Remote Sensing, and Communication technologies, as well as ASP and ActiveX software development technologies. One of the most important issues for constructing the spatial decision support systems of AIDS epidemic prevention is how to integrate the AIDS spreading models with GIS. The capabilities of GIS applications in the AIDS epidemic prevention have been described here in this paper firstly. Then some mature epidemic spreading models have also been discussed for extracting the computation parameters. Furthermore, a technical schema has been proposed for integrating the AIDS spreading models with GIS and relevant geospatial technologies, in which the GIS and model running platforms share a common spatial database and the computing results can be spatially visualized on Desktop or Web GIS clients. Finally, a complete solution for establishing the decision support systems of AIDS epidemic prevention has been offered in this paper based on the model integrating methods and ESRI COM GIS software packages. The general decision support systems are composed of data acquisition sub-systems, network communication sub-systems, model integrating sub-systems, AIDS epidemic information spatial database sub-systems, AIDS epidemic information querying and statistical analysis sub-systems, AIDS epidemic dynamic surveillance sub-systems, AIDS epidemic information spatial analysis and decision support sub-systems, as well as AIDS epidemic information publishing sub-systems based on Web GIS.

Learning to make collective decisions: the impact of confidence escalation.

PubMed

Mahmoodi, Ali; Bang, Dan; Ahmadabadi, Majid Nili; Bahrami, Bahador

2013-01-01

Little is known about how people learn to take into account others' opinions in joint decisions. To address this question, we combined computational and empirical approaches. Human dyads made individual and joint visual perceptual decision and rated their confidence in those decisions (data previously published). We trained a reinforcement (temporal difference) learning agent to get the participants' confidence level and learn to arrive at a dyadic decision by finding the policy that either maximized the accuracy of the model decisions or maximally conformed to the empirical dyadic decisions. When confidences were shared visually without verbal interaction, RL agents successfully captured social learning. When participants exchanged confidences visually and interacted verbally, no collective benefit was achieved and the model failed to predict the dyadic behaviour. Behaviourally, dyad members' confidence increased progressively and verbal interaction accelerated this escalation. The success of the model in drawing collective benefit from dyad members was inversely related to confidence escalation rate. The findings show an automated learning agent can, in principle, combine individual opinions and achieve collective benefit but the same agent cannot discount the escalation suggesting that one cognitive component of collective decision making in human may involve discounting of overconfidence arising from interactions.

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

NASA Technical Reports Server (NTRS)

Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

2005-01-01

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Learning outdoors: male lizards show flexible spatial learning under semi-natural conditions

PubMed Central

Noble, Daniel W. A.; Carazo, Pau; Whiting, Martin J.

2012-01-01

Spatial cognition is predicted to be a fundamental component of fitness in many lizard species, and yet some studies suggest that it is relatively slow and inflexible. However, such claims are based on work conducted using experimental designs or in artificial contexts that may underestimate their cognitive abilities. We used a biologically realistic experimental procedure (using simulated predatory attacks) to study spatial learning and its flexibility in the lizard Eulamprus quoyii in semi-natural outdoor enclosures under similar conditions to those experienced by lizards in the wild. To evaluate the flexibility of spatial learning, we conducted a reversal spatial-learning task in which positive and negative reinforcements of learnt spatial stimuli were switched. Nineteen (32%) male lizards learnt both tasks within 10 days (spatial task mean: 8.16 ± 0.69 (s.e.) and reversal spatial task mean: 10.74 ± 0.98 (s.e.) trials). We demonstrate that E. quoyii are capable of flexible spatial learning and suggest that future studies focus on a range of lizard species which differ in phylogeny and/or ecology, using biologically relevant cognitive tasks, in an effort to bridge the cognitive divide between ecto- and endotherms. PMID:23075525

Is Order the Defining Feature of Magnitude Representation? An ERP Study on Learning Numerical Magnitude and Spatial Order of Artificial Symbols

PubMed Central

Zhao, Hui; Chen, Chuansheng; Zhang, Hongchuan; Zhou, Xinlin; Mei, Leilei; Chen, Chunhui; Chen, Lan; Cao, Zhongyu; Dong, Qi

2012-01-01

Using an artificial-number learning paradigm and the ERP technique, the present study investigated neural mechanisms involved in the learning of magnitude and spatial order. 54 college students were divided into 2 groups matched in age, gender, and school major. One group was asked to learn the associations between magnitude (dot patterns) and the meaningless Gibson symbols, and the other group learned the associations between spatial order (horizontal positions on the screen) and the same set of symbols. Results revealed differentiated neural mechanisms underlying the learning processes of symbolic magnitude and spatial order. Compared to magnitude learning, spatial-order learning showed a later and reversed distance effect. Furthermore, an analysis of the order-priming effect showed that order was not inherent to the learning of magnitude. Results of this study showed a dissociation between magnitude and order, which supports the numerosity code hypothesis of mental representations of magnitude. PMID:23185363

Linking climate change and fish conservation efforts using spatially explicit decision support tools

Treesearch

Douglas P. Peterson; Seth J. Wenger; Bruce E. Rieman; Daniel J. Isaak

2013-01-01

Fisheries professionals are increasingly tasked with incorporating climate change projections into their decisions. Here we demonstrate how a structured decision framework, coupled with analytical tools and spatial data sets, can help integrate climate and biological information to evaluate management alternatives. We present examples that link downscaled climate...

On the Science-Policy Bridge: Do Spatial Heat Vulnerability Assessment Studies Influence Policy?

PubMed Central

Wolf, Tanja; Chuang, Wen-Ching; McGregor, Glenn

2015-01-01

Human vulnerability to heat varies at a range of spatial scales, especially within cities where there can be noticeable intra-urban differences in heat risk factors. Mapping and visualizing intra-urban heat vulnerability offers opportunities for presenting information to support decision-making. For example the visualization of the spatial variation of heat vulnerability has the potential to enable local governments to identify hot spots of vulnerability and allocate resources and increase assistance to people in areas of greatest need. Recently there has been a proliferation of heat vulnerability mapping studies, all of which, to varying degrees, justify the process of vulnerability mapping in a policy context. However, to date, there has not been a systematic review of the extent to which the results of vulnerability mapping studies have been applied in decision-making. Accordingly we undertook a comprehensive review of 37 recently published papers that use geospatial techniques for assessing human vulnerability to heat. In addition, we conducted an anonymous survey of the lead authors of the 37 papers in order to establish the level of interaction between the researchers as science information producers and local authorities as information users. Both paper review and author survey results show that heat vulnerability mapping has been used in an attempt to communicate policy recommendations, raise awareness and induce institutional networking and learning, but has not as yet had a substantive influence on policymaking or preventive action. PMID:26512681

Overcoming Learning Aversion in Evaluating and Managing Uncertain Risks.

PubMed

Cox, Louis Anthony Tony

2015-10-01

Decision biases can distort cost-benefit evaluations of uncertain risks, leading to risk management policy decisions with predictably high retrospective regret. We argue that well-documented decision biases encourage learning aversion, or predictably suboptimal learning and premature decision making in the face of high uncertainty about the costs, risks, and benefits of proposed changes. Biases such as narrow framing, overconfidence, confirmation bias, optimism bias, ambiguity aversion, and hyperbolic discounting of the immediate costs and delayed benefits of learning, contribute to deficient individual and group learning, avoidance of information seeking, underestimation of the value of further information, and hence needlessly inaccurate risk-cost-benefit estimates and suboptimal risk management decisions. In practice, such biases can create predictable regret in selection of potential risk-reducing regulations. Low-regret learning strategies based on computational reinforcement learning models can potentially overcome some of these suboptimal decision processes by replacing aversion to uncertain probabilities with actions calculated to balance exploration (deliberate experimentation and uncertainty reduction) and exploitation (taking actions to maximize the sum of expected immediate reward, expected discounted future reward, and value of information). We discuss the proposed framework for understanding and overcoming learning aversion and for implementing low-regret learning strategies using regulation of air pollutants with uncertain health effects as an example. © 2015 Society for Risk Analysis.

Making Sense of Space: Distributed Spatial Sensemaking in a Middle School Summer Engineering Camp

ERIC Educational Resources Information Center

Ramey, Kay E.; Uttal, David H.

2017-01-01

Spatial thinking is important for success in engineering. However, little is known about "how" students learn and apply spatial skills, particularly in kindergarten to Grade 12 engineering learning. The present study investigated the role of spatial thinking in engineering learning at a middle school summer camp. Participants were 26…

The Uncertainties on the GIS Based Land Suitability Assessment for Urban and Rural Planning

NASA Astrophysics Data System (ADS)

Liu, H.; Zhan, Q.; Zhan, M.

2017-09-01

The majority of the research on the uncertainties of spatial data and spatial analysis focuses on some specific data feature or analysis tool. Few have accomplished the uncertainties of the whole process of an application like planning, making the research of uncertainties detached from practical applications. The paper discusses the uncertainties of the geographical information systems (GIS) based land suitability assessment in planning on the basis of literature review. The uncertainties considered range from index system establishment to the classification of the final result. Methods to reduce the uncertainties arise from the discretization of continuous raster data and the index weight determination are summarized. The paper analyzes the merits and demerits of the "Nature Breaks" method which is broadly used by planners. It also explores the other factors which impact the accuracy of the final classification like the selection of class numbers, intervals and the autocorrelation of the spatial data. In the conclusion part, the paper indicates that the adoption of machine learning methods should be modified to integrate the complexity of land suitability assessment. The work contributes to the application of spatial data and spatial analysis uncertainty research on land suitability assessment, and promotes the scientific level of the later planning and decision-making.

Neural correlates of reward-based spatial learning in persons with cocaine dependence.

PubMed

Tau, Gregory Z; Marsh, Rachel; Wang, Zhishun; Torres-Sanchez, Tania; Graniello, Barbara; Hao, Xuejun; Xu, Dongrong; Packard, Mark G; Duan, Yunsuo; Kangarlu, Alayar; Martinez, Diana; Peterson, Bradley S

2014-02-01

Dysfunctional learning systems are thought to be central to the pathogenesis of and impair recovery from addictions. The functioning of the brain circuits for episodic memory or learning that support goal-directed behavior has not been studied previously in persons with cocaine dependence (CD). Thirteen abstinent CD and 13 healthy participants underwent MRI scanning while performing a task that requires the use of spatial cues to navigate a virtual-reality environment and find monetary rewards, allowing the functional assessment of the brain systems for spatial learning, a form of episodic memory. Whereas both groups performed similarly on the reward-based spatial learning task, we identified disturbances in brain regions involved in learning and reward in CD participants. In particular, CD was associated with impaired functioning of medial temporal lobe (MTL), a brain region that is crucial for spatial learning (and episodic memory) with concomitant recruitment of striatum (which normally participates in stimulus-response, or habit, learning), and prefrontal cortex. CD was also associated with enhanced sensitivity of the ventral striatum to unexpected rewards but not to expected rewards earned during spatial learning. We provide evidence that spatial learning in CD is characterized by disturbances in functioning of an MTL-based system for episodic memory and a striatum-based system for stimulus-response learning and reward. We have found additional abnormalities in distributed cortical regions. Consistent with findings from animal studies, we provide the first evidence in humans describing the disruptive effects of cocaine on the coordinated functioning of multiple neural systems for learning and memory.

Reinforcement Learning Multi-Agent Modeling of Decision-Making Agents for the Study of Transboundary Surface Water Conflicts with Application to the Syr Darya River Basin

NASA Astrophysics Data System (ADS)

Riegels, N.; Siegfried, T.; Pereira Cardenal, S. J.; Jensen, R. A.; Bauer-Gottwein, P.

2008-12-01

In most economics--driven approaches to optimizing water use at the river basin scale, the system is modelled deterministically with the goal of maximizing overall benefits. However, actual operation and allocation decisions must be made under hydrologic and economic uncertainty. In addition, river basins often cross political boundaries, and different states may not be motivated to cooperate so as to maximize basin- scale benefits. Even within states, competing agents such as irrigation districts, municipal water agencies, and large industrial users may not have incentives to cooperate to realize efficiency gains identified in basin- level studies. More traditional simulation--optimization approaches assume pre-commitment by individual agents and stakeholders and unconditional compliance on each side. While this can help determine attainable gains and tradeoffs from efficient management, such hardwired policies do not account for dynamic feedback between agents themselves or between agents and their environments (e.g. due to climate change etc.). In reality however, we are dealing with an out-of-equilibrium multi-agent system, where there is neither global knowledge nor global control, but rather continuous strategic interaction between decision making agents. Based on the theory of stochastic games, we present a computational framework that allows for studying the dynamic feedback between decision--making agents themselves and an inherently uncertain environment in a spatially and temporally distributed manner. Agents with decision-making control over water allocation such as countries, irrigation districts, and municipalities are represented by reinforcement learning agents and coupled to a detailed hydrologic--economic model. This approach emphasizes learning by agents from their continuous interaction with other agents and the environment. It provides a convenient framework for the solution of the problem of dynamic decision-making in a mixed cooperative / non-cooperative environment with which different institutional setups and incentive systems can be studied so to identify reasonable ways to reach desirable, Pareto--optimal allocation outcomes. Preliminary results from an application to the Syr Darya river basin in Central Asia will be presented and discussed. The Syr Darya River is a classic example of a transboundary river basin in which basin-wide efficiency gains identified in optimization studies have not been sufficient to induce cooperative management of the river by the riparian states.

Multicriteria decision model for retrofitting existing buildings

NASA Astrophysics Data System (ADS)

Bostenaru Dan, B.

2003-04-01

In this paper a model to decide which buildings from an urban area should be retrofitted is presented. The model has been cast into existing ones by choosing the decision rule, criterion weighting and decision support system types most suitable for the spatial problem of reducing earthquake risk in urban areas, considering existing spatial multiatributive and multiobjective decision methods and especially collaborative issues. Due to the participative character of the group decision problem "retrofitting existing buildings" the decision making model is based on interactivity. Buildings have been modeled following the criteria of spatial decision support systems. This includes identifying the corresponding spatial elements of buildings according to the information needs of actors from different sphaeres like architects, construction engineers and economists. The decision model aims to facilitate collaboration between this actors. The way of setting priorities interactivelly will be shown, by detailing the two phases: judgemental and computational, in this case site analysis, collection and evaluation of the unmodified data and converting survey data to information with computational methods using additional expert support. Buildings have been divided into spatial elements which are characteristic for the survey, present typical damages in case of an earthquake and are decisive for a better seismic behaviour in case of retrofitting. The paper describes the architectural and engineering characteristics as well as the structural damage for constuctions of different building ages on the example of building types in Bucharest, Romania in compressible and interdependent charts, based on field observation, reports from the 1977 earthquake and detailed studies made by the author together with a local engineer for the EERI Web Housing Encyclopedia. On this base criteria for setting priorities flow into the expert information contained in the system.

Interactive Inverse Groundwater Modeling - Addressing User Fatigue

NASA Astrophysics Data System (ADS)

Singh, A.; Minsker, B. S.

2006-12-01

This paper builds on ongoing research on developing an interactive and multi-objective framework to solve the groundwater inverse problem. In this work we solve the classic groundwater inverse problem of estimating a spatially continuous conductivity field, given field measurements of hydraulic heads. The proposed framework is based on an interactive multi-objective genetic algorithm (IMOGA) that not only considers quantitative measures such as calibration error and degree of regularization, but also takes into account expert knowledge about the structure of the underlying conductivity field expressed as subjective rankings of potential conductivity fields by the expert. The IMOGA converges to the optimal Pareto front representing the best trade- off among the qualitative as well as quantitative objectives. However, since the IMOGA is a population-based iterative search it requires the user to evaluate hundreds of solutions. This leads to the problem of 'user fatigue'. We propose a two step methodology to combat user fatigue in such interactive systems. The first step is choosing only a few highly representative solutions to be shown to the expert for ranking. Spatial clustering is used to group the search space based on the similarity of the conductivity fields. Sampling is then carried out from different clusters to improve the diversity of solutions shown to the user. Once the expert has ranked representative solutions from each cluster a machine learning model is used to 'learn user preference' and extrapolate these for the solutions not ranked by the expert. We investigate different machine learning models such as Decision Trees, Bayesian learning model, and instance based weighting to model user preference. In addition, we also investigate ways to improve the performance of these models by providing information about the spatial structure of the conductivity fields (which is what the expert bases his or her rank on). Results are shown for each of these machine learning models and the advantages and disadvantages for each approach are discussed. These results indicate that using the proposed two-step methodology leads to significant reduction in user-fatigue without deteriorating the solution quality of the IMOGA.

Tuned by experience: How orientation probability modulates early perceptual processing.

PubMed

Jabar, Syaheed B; Filipowicz, Alex; Anderson, Britt

2017-09-01

Probable stimuli are more often and more quickly detected. While stimulus probability is known to affect decision-making, it can also be explained as a perceptual phenomenon. Using spatial gratings, we have previously shown that probable orientations are also more precisely estimated, even while participants remained naive to the manipulation. We conducted an electrophysiological study to investigate the effect that probability has on perception and visual-evoked potentials. In line with previous studies on oddballs and stimulus prevalence, low-probability orientations were associated with a greater late positive 'P300' component which might be related to either surprise or decision-making. However, the early 'C1' component, thought to reflect V1 processing, was dampened for high-probability orientations while later P1 and N1 components were unaffected. Exploratory analyses revealed a participant-level correlation between C1 and P300 amplitudes, suggesting a link between perceptual processing and decision-making. We discuss how these probability effects could be indicative of sharpening of neurons preferring the probable orientations, due either to perceptual learning, or to feature-based attention. Copyright © 2017 Elsevier Ltd. All rights reserved.

The drift diffusion model as the choice rule in reinforcement learning.

PubMed

Pedersen, Mads Lund; Frank, Michael J; Biele, Guido

2017-08-01

Current reinforcement-learning models often assume simplified decision processes that do not fully reflect the dynamic complexities of choice processes. Conversely, sequential-sampling models of decision making account for both choice accuracy and response time, but assume that decisions are based on static decision values. To combine these two computational models of decision making and learning, we implemented reinforcement-learning models in which the drift diffusion model describes the choice process, thereby capturing both within- and across-trial dynamics. To exemplify the utility of this approach, we quantitatively fit data from a common reinforcement-learning paradigm using hierarchical Bayesian parameter estimation, and compared model variants to determine whether they could capture the effects of stimulant medication in adult patients with attention-deficit hyperactivity disorder (ADHD). The model with the best relative fit provided a good description of the learning process, choices, and response times. A parameter recovery experiment showed that the hierarchical Bayesian modeling approach enabled accurate estimation of the model parameters. The model approach described here, using simultaneous estimation of reinforcement-learning and drift diffusion model parameters, shows promise for revealing new insights into the cognitive and neural mechanisms of learning and decision making, as well as the alteration of such processes in clinical groups.

The drift diffusion model as the choice rule in reinforcement learning

PubMed Central

Frank, Michael J.

2017-01-01

Current reinforcement-learning models often assume simplified decision processes that do not fully reflect the dynamic complexities of choice processes. Conversely, sequential-sampling models of decision making account for both choice accuracy and response time, but assume that decisions are based on static decision values. To combine these two computational models of decision making and learning, we implemented reinforcement-learning models in which the drift diffusion model describes the choice process, thereby capturing both within- and across-trial dynamics. To exemplify the utility of this approach, we quantitatively fit data from a common reinforcement-learning paradigm using hierarchical Bayesian parameter estimation, and compared model variants to determine whether they could capture the effects of stimulant medication in adult patients with attention-deficit hyper-activity disorder (ADHD). The model with the best relative fit provided a good description of the learning process, choices, and response times. A parameter recovery experiment showed that the hierarchical Bayesian modeling approach enabled accurate estimation of the model parameters. The model approach described here, using simultaneous estimation of reinforcement-learning and drift diffusion model parameters, shows promise for revealing new insights into the cognitive and neural mechanisms of learning and decision making, as well as the alteration of such processes in clinical groups. PMID:27966103

Spatial Object Recognition Enables Endogenous LTD that Curtails LTP in the Mouse Hippocampus

PubMed Central

Goh, Jinzhong Jeremy

2013-01-01

Although synaptic plasticity is believed to comprise the cellular substrate for learning and memory, limited direct evidence exists that hippocampus-dependent learning actually triggers synaptic plasticity. It is likely, however, that long-term potentiation (LTP) works in concert with its counterpart, long-term depression (LTD) in the creation of spatial memory. It has been reported in rats that weak synaptic plasticity is facilitated into persistent plasticity if afferent stimulation is coupled with a novel spatial learning event. It is not known if this phenomenon also occurs in other species. We recorded from the hippocampal CA1 of freely behaving mice and observed that novel spatial learning triggers endogenous LTD. Specifically, we observed that LTD is enabled when test-pulse afferent stimulation is given during the learning of object constellations or during a spatial object recognition task. Intriguingly, LTP is significantly impaired by the same tasks, suggesting that LTD is the main cellular substrate for this type of learning. These data indicate that learning-facilitated plasticity is not exclusive to rats and that spatial learning leads to endogenous LTD in the hippocampus, suggesting an important role for this type of synaptic plasticity in the creation of hippocampus-dependent memory. PMID:22510536

Neural Correlates of Sequence Learning with Stochastic Feedback

ERIC Educational Resources Information Center

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

2011-01-01

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

The Three-Part Harmony of Adult Learning, Critical Thinking, and Decision-Making

ERIC Educational Resources Information Center

Moore, Kyle

2010-01-01

Adult learning, critical thinking, and decision-making are fields that receive attention individually, although they are interspersed with elements of each other's theories and philosophies. In addressing adult learning precepts, it is essential to include critical thinking and decision-making. One without the other creates weakness; all must be…

Ageing and spatial reversal learning in humans: findings from a virtual water maze.

PubMed

Schoenfeld, R; Foreman, N; Leplow, B

2014-08-15

Deterioration in spatial memory with normal ageing is well accepted. Animal research has shown spatial reversal learning to be most vulnerable to pathological changes in the brain, but this has never been tested in humans. We studied ninety participants (52% females, 20-80 yrs) in a virtual water maze with a reversal learning procedure. Neuropsychological functioning, mood and personality were assessed to control moderator effects. For data analysis, participants were subdivided post hoc into groups aged 20-24, 25-34, 35-44, 45-64 and 65-80 yrs. Initial spatial learning occurred in all age groups but 65-80-yrs-olds never reached the level of younger participants. When tested for delayed recall of spatial memory, younger people frequented the target area but those over 65 yrs did not. In spatial reversal learning, age groups over 45 yrs were deficient and the 65-80-yrs-olds showed no evidence of reversal. Spatial measures were associated with neuropsychological functioning. Extraversion and measures of depression moderated the age effect on the learning index with older introverted and non-depressed individuals showing better results. Measures of anxiety moderated the age effect on reversal learning with older people having higher anxiety scores showing a preserved reversal learning capability. Results confirmed age to be a major factor in spatial tasks but further showed neuropsychological functioning, psycho-affective determinants and personality traits to be significant predictors of individual differences. Copyright © 2014 Elsevier B.V. All rights reserved.

Low Cognitive Impulsivity Is Associated with Better Gain and Loss Learning in a Probabilistic Decision-Making Task

PubMed Central

Cáceres, Pablo; San Martín, René

2017-01-01

Many advances have been made over the last decades in describing, on the one hand, the link between reward-based learning and decision-making, and on the other hand, the link between impulsivity and decision-making. However, the association between reward-based learning and impulsivity remains poorly understood. In this study, we evaluated the association between individual differences in loss-minimizing and gain-maximizing behavior in a learning-based probabilistic decision-making task and individual differences in cognitive impulsivity. We found that low cognitive impulsivity was associated both with a better performance minimizing losses and maximizing gains during the task. These associations remained significant after controlling for mathematical skills and gender as potential confounders. We discuss potential mechanisms through which cognitive impulsivity might interact with reward-based learning and decision-making. PMID:28261137

Low Cognitive Impulsivity Is Associated with Better Gain and Loss Learning in a Probabilistic Decision-Making Task.

PubMed

Cáceres, Pablo; San Martín, René

2017-01-01

Many advances have been made over the last decades in describing, on the one hand, the link between reward-based learning and decision-making, and on the other hand, the link between impulsivity and decision-making. However, the association between reward-based learning and impulsivity remains poorly understood. In this study, we evaluated the association between individual differences in loss-minimizing and gain-maximizing behavior in a learning-based probabilistic decision-making task and individual differences in cognitive impulsivity. We found that low cognitive impulsivity was associated both with a better performance minimizing losses and maximizing gains during the task. These associations remained significant after controlling for mathematical skills and gender as potential confounders. We discuss potential mechanisms through which cognitive impulsivity might interact with reward-based learning and decision-making.

Towards an integrated approach to natural hazards risk assessment using GIS: with reference to bushfires.

PubMed

Chen, Keping; Blong, Russell; Jacobson, Carol

2003-04-01

This paper develops a GIS-based integrated approach to risk assessment in natural hazards, with reference to bushfires. The challenges for undertaking this approach have three components: data integration, risk assessment tasks, and risk decision-making. First, data integration in GIS is a fundamental step for subsequent risk assessment tasks and risk decision-making. A series of spatial data integration issues within GIS such as geographical scales and data models are addressed. Particularly, the integration of both physical environmental data and socioeconomic data is examined with an example linking remotely sensed data and areal census data in GIS. Second, specific risk assessment tasks, such as hazard behavior simulation and vulnerability assessment, should be undertaken in order to understand complex hazard risks and provide support for risk decision-making. For risk assessment tasks involving heterogeneous data sources, the selection of spatial analysis units is important. Third, risk decision-making concerns spatial preferences and/or patterns, and a multicriteria evaluation (MCE)-GIS typology for risk decision-making is presented that incorporates three perspectives: spatial data types, data models, and methods development. Both conventional MCE methods and artificial intelligence-based methods with GIS are identified to facilitate spatial risk decision-making in a rational and interpretable way. Finally, the paper concludes that the integrated approach can be used to assist risk management of natural hazards, in theory and in practice.

The impact of fornix lesions in rats on spatial learning tasks sensitive to anterior thalamic and hippocampal damage

PubMed Central

Dumont, Julie R.; Amin, Eman; Wright, Nicholas F.; Dillingham, Christopher M.; Aggleton, John P.

2015-01-01

The present study sought to understand how the hippocampus and anterior thalamic nuclei are conjointly required for spatial learning by examining the impact of cutting a major tract (the fornix) that interconnects these two sites. The initial experiments examined the consequences of fornix lesions in rats on spatial biconditional discrimination learning. The rationale arose from previous findings showing that fornix lesions spare the learning of spatial biconditional tasks, despite the same task being highly sensitive to both hippocampal and anterior thalamic nuclei lesions. In the present study, fornix lesions only delayed acquisition of the spatial biconditional task, pointing to additional contributions from non-fornical routes linking the hippocampus with the anterior thalamic nuclei. The same fornix lesions spared the learning of an analogous nonspatial biconditional task that used local contextual cues. Subsequent tests, including T-maze place alternation, place learning in a cross-maze, and a go/no-go place discrimination, highlighted the impact of fornix lesions when distal spatial information is used flexibly to guide behaviour. The final experiment examined the ability to learn incidentally the spatial features of a square water-maze that had differently patterned walls. Fornix lesions disrupted performance but did not stop the rats from distinguishing the various corners of the maze. Overall, the results indicate that interconnections between the hippocampus and anterior thalamus, via the fornix, help to resolve problems with flexible spatial and temporal cues, but the results also signal the importance of additional, non-fornical contributions to hippocampal-anterior thalamic spatial processing, particularly for problems with more stable spatial solutions. PMID:25453745

Cardiovascular Fitness and Cognitive Spatial Learning in Rodents and in Humans.

PubMed

Barak, Boaz; Feldman, Noa; Okun, Eitan

2015-09-01

The association between cardiovascular fitness and cognitive functions in both animals and humans is intensely studied. Research in rodents shows that a higher cardiovascular fitness has beneficial effects on hippocampus-dependent spatial abilities, and the underlying mechanisms were largely teased out. Research into the impact of cardiovascular fitness on spatial learning in humans, however, is more limited, and involves mostly behavioral and imaging studies. Herein, we point out the state of the art in the field of spatial learning and cardiovascular fitness. The differences between the methodologies utilized to study spatial learning in humans and rodents are emphasized along with the neuronal basis of these tasks. Critical gaps in the study of spatial learning in the context of cardiovascular fitness between the two species are discussed. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America.

A Tribute to Charlie Chaplin: Induced Positive Affect Improves Reward-Based Decision-Learning in Parkinson’s Disease

PubMed Central

Ridderinkhof, K. Richard; van Wouwe, Nelleke C.; Band, Guido P. H.; Wylie, Scott A.; Van der Stigchel, Stefan; van Hees, Pieter; Buitenweg, Jessika; van de Vijver, Irene; van den Wildenberg, Wery P. M.

2012-01-01

Reward-based decision-learning refers to the process of learning to select those actions that lead to rewards while avoiding actions that lead to punishments. This process, known to rely on dopaminergic activity in striatal brain regions, is compromised in Parkinson’s disease (PD). We hypothesized that such decision-learning deficits are alleviated by induced positive affect, which is thought to incur transient boosts in midbrain and striatal dopaminergic activity. Computational measures of probabilistic reward-based decision-learning were determined for 51 patients diagnosed with PD. Previous work has shown these measures to rely on the nucleus caudatus (outcome evaluation during the early phases of learning) and the putamen (reward prediction during later phases of learning). We observed that induced positive affect facilitated learning, through its effects on reward prediction rather than outcome evaluation. Viewing a few minutes of comedy clips served to remedy dopamine-related problems associated with frontostriatal circuitry and, consequently, learning to predict which actions will yield reward. PMID:22707944

Risky decision-making in children with and without ADHD: A prospective study.

PubMed

Humphreys, Kathryn L; Tottenham, Nim; Lee, Steve S

2018-02-01

Learning from past decisions can enhance successful decision-making. It is unclear whether difficulties in learning from experience may contribute to risky decision-making, which may be altered among individuals with attention-deficit/hyperactivity disorder (ADHD). This study follows 192 children with and without ADHD aged 5 to 10 years for approximately 2.5 years and examines their risky decision-making using the Balloon Emotional Learning Task (BELT), a computerized assessment of sequential risky decision-making in which participants pump up a series of virtual balloons for points. The BELT contains three task conditions: one with a variable explosion point, one with a stable and early explosion point, and one with a stable and late explosion point. These conditions may be learned via experience on the task. Contrary to expectations, ADHD status was not found to be related to greater risk-taking on the BELT, and among younger children ADHD status is in fact associated with reduced risk-taking. In addition, the typically-developing children without ADHD showed significant learning-related gains on both stable task conditions. However, the children with ADHD demonstrated learning on the condition with a stable and early explosion point, but not on the condition with the stable and late explosion point, in which more pumps are required before learning when the balloon will explode. Learning during decision-making may be more difficult for children with ADHD. Because adapting to changing environmental demands requires the use of feedback to guide future behavior, negative outcomes associated with childhood ADHD may partially reflect difficulties in learning from experience.

What do decision makers learn from public forums on climate-related hazards and resilience?

NASA Astrophysics Data System (ADS)

Weller, N.; Farooque, M.; Sittenfeld, D.

2017-12-01

Public engagement around climate resilience efforts can foster learning for both public audiences and decision makers. On the one hand, public audiences learn about environmental hazards and strategies to increase community resilience through effective public engagement. On the other, decision makers and scientists learn about community members' values and priorities and their relation to environmental hazards and resilience strategies. Evidence from other public engagement efforts involving decision makers suggests that decision maker involvement results in reflection by officials on their own values, capacities, and roles. However, few public engagement exercises evaluate impacts on decision makers. As part of the Science Center Public Forums project, which aims to conduct public forums in eight cities across the country on resiliency to drought, heat, extreme precipitation, and sea level rise, we sought to 1) build partnerships with local decision makers and scientists around public forums and 2) explore how decision makers and scientists interacted with the planning and undertaking of those public forums. We held workshops with decision makers and scientists to inform forum content and identify local resilience issues. We will conduct interviews with local decision makers regarding their involvement in forum planning, their reflections and takeaways from the forum itself, and their perspectives on the value of public engagement for policy making. We will present our model of engagement with decision makers, initial findings from interviews, and lessons learned from connecting decision makers and scientists to public engagement efforts.

[Effect of object consistency in a spatial contextual cueing paradigm].

PubMed

Takeda, Yuji

2008-04-01

Previous studies demonstrated that attention can be quickly guided to a target location in a visual search task when the spatial configurations of search items and/or the object identities were repeated in the previous trials. This phenomenon is termed contextual cueing. Recently, it was reported that spatial configuration learning and object identity learning occurred independently, when novel contours were used as search items. The present study examined whether this learning occurred independently even when the search items were meaningful. The results showed that the contextual cueing effect was observed even if the relationships between the spatial locations and object identities were jumbled (Experiment 1). However, it disappeared when the search items were changed into geometric patterns (Experiment 2). These results suggest that the spatial configuration can be learned independent of the object identities; however, the use of the learned configuration is restricted by the learning situations.

Spatial Dependence and Determinants of Dairy Farmers' Adoption of Best Management Practices for Water Protection in New Zealand

NASA Astrophysics Data System (ADS)

Yang, Wei; Sharp, Basil

2017-04-01

This paper analyses spatial dependence and determinants of the New Zealand dairy farmers' adoption of best management practices to protect water quality. A Bayesian spatial durbin probit model is used to survey data collected from farmers in the Waikato region of New Zealand. The results show that farmers located near each other exhibit similar choice behaviour, indicating the importance of farmer interactions in adoption decisions. The results also address that information acquisition is the most important determinant of farmers' adoption of best management practices. Financial problems are considered a significant barrier to adopting best management practices. Overall, the existence of distance decay effect and spatial dependence in farmers' adoption decisions highlights the importance of accounting for spatial effects in farmers' decision-making, which emerges as crucial to the formulation of sustainable agriculture policy.

Spatial Dependence and Determinants of Dairy Farmers' Adoption of Best Management Practices for Water Protection in New Zealand.

PubMed

Yang, Wei; Sharp, Basil

2017-04-01

This paper analyses spatial dependence and determinants of the New Zealand dairy farmers' adoption of best management practices to protect water quality. A Bayesian spatial durbin probit model is used to survey data collected from farmers in the Waikato region of New Zealand. The results show that farmers located near each other exhibit similar choice behaviour, indicating the importance of farmer interactions in adoption decisions. The results also address that information acquisition is the most important determinant of farmers' adoption of best management practices. Financial problems are considered a significant barrier to adopting best management practices. Overall, the existence of distance decay effect and spatial dependence in farmers' adoption decisions highlights the importance of accounting for spatial effects in farmers' decision-making, which emerges as crucial to the formulation of sustainable agriculture policy.

SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

An Environmental Decision Support System for Spatial Assessment and Selective Remediation

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates environmental assessment tools for effective problem-solving. The software integrates modules for GIS, visualization, geospatial analysis, statistical analysis, human health and ecolog...

Neural signatures of experience-based improvements in deterministic decision-making.

PubMed

Tremel, Joshua J; Laurent, Patryk A; Wolk, David A; Wheeler, Mark E; Fiez, Julie A

2016-12-15

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. Copyright © 2016 Elsevier B.V. All rights reserved.

Neural signatures of experience-based improvements in deterministic decision-making

PubMed Central

Tremel, Joshua J.; Laurent, Patryk A.; Wolk, David A.; Wheeler, Mark E.; Fiez, Julie A.

2016-01-01

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. PMID:27523644

A Bayesian Framework for Analysis of Pseudo-Spatial Models of Comparable Engineered Systems with Application to Spacecraft Anomaly Prediction Based on Precedent Data

NASA Astrophysics Data System (ADS)

Ndu, Obibobi Kamtochukwu

To ensure that estimates of risk and reliability inform design and resource allocation decisions in the development of complex engineering systems, early engagement in the design life cycle is necessary. An unfortunate constraint on the accuracy of such estimates at this stage of concept development is the limited amount of high fidelity design and failure information available on the actual system under development. Applying the human ability to learn from experience and augment our state of knowledge to evolve better solutions mitigates this limitation. However, the challenge lies in formalizing a methodology that takes this highly abstract, but fundamentally human cognitive, ability and extending it to the field of risk analysis while maintaining the tenets of generalization, Bayesian inference, and probabilistic risk analysis. We introduce an integrated framework for inferring the reliability, or other probabilistic measures of interest, of a new system or a conceptual variant of an existing system. Abstractly, our framework is based on learning from the performance of precedent designs and then applying the acquired knowledge, appropriately adjusted based on degree of relevance, to the inference process. This dissertation presents a method for inferring properties of the conceptual variant using a pseudo-spatial model that describes the spatial configuration of the family of systems to which the concept belongs. Through non-metric multidimensional scaling, we formulate the pseudo-spatial model based on rank-ordered subjective expert perception of design similarity between systems that elucidate the psychological space of the family. By a novel extension of Kriging methods for analysis of geospatial data to our "pseudo-space of comparable engineered systems", we develop a Bayesian inference model that allows prediction of the probabilistic measure of interest.

Decision tree and ensemble learning algorithms with their applications in bioinformatics.

PubMed

Che, Dongsheng; Liu, Qi; Rasheed, Khaled; Tao, Xiuping

2011-01-01

Machine learning approaches have wide applications in bioinformatics, and decision tree is one of the successful approaches applied in this field. In this chapter, we briefly review decision tree and related ensemble algorithms and show the successful applications of such approaches on solving biological problems. We hope that by learning the algorithms of decision trees and ensemble classifiers, biologists can get the basic ideas of how machine learning algorithms work. On the other hand, by being exposed to the applications of decision trees and ensemble algorithms in bioinformatics, computer scientists can get better ideas of which bioinformatics topics they may work on in their future research directions. We aim to provide a platform to bridge the gap between biologists and computer scientists.

Sharpening coarse-to-fine stereo vision by perceptual learning: asymmetric transfer across the spatial frequency spectrum

PubMed Central

Tran, Truyet T.; Craven, Ashley P.; Leung, Tsz-Wing; Chat, Sandy W.; Levi, Dennis M.

2016-01-01

Neurons in the early visual cortex are finely tuned to different low-level visual features, forming a multi-channel system analysing the visual image formed on the retina in a parallel manner. However, little is known about the potential ‘cross-talk’ among these channels. Here, we systematically investigated whether stereoacuity, over a large range of target spatial frequencies, can be enhanced by perceptual learning. Using narrow-band visual stimuli, we found that practice with coarse (low spatial frequency) targets substantially improves performance, and that the improvement spreads from coarse to fine (high spatial frequency) three-dimensional perception, generalizing broadly across untrained spatial frequencies and orientations. Notably, we observed an asymmetric transfer of learning across the spatial frequency spectrum. The bandwidth of transfer was broader when training was at a high spatial frequency than at a low spatial frequency. Stereoacuity training is most beneficial when trained with fine targets. This broad transfer of stereoacuity learning contrasts with the highly specific learning reported for other basic visual functions. We also revealed strategies to boost learning outcomes ‘beyond-the-plateau’. Our investigations contribute to understanding the functional properties of the network subserving stereovision. The ability to generalize may provide a key principle for restoring impaired binocular vision in clinical situations. PMID:26909178

Arginine vasopressin prevents against Abeta(25-35)-induced impairment of spatial learning and memory in rats.

PubMed

Pan, Yan-Fang; Chen, Xiao-Rong; Wu, Mei-Na; Ma, Cun-Gen; Qi, Jin-Shun

2010-04-01

Amyloid beta protein (Abeta) is thought to be responsible for loss of memory in Alzheimer's disease (AD). A significant decrease in [Arg(8)]-vasopressin (AVP) has been found in the AD brain and in plasma; however, it is unclear whether this decrease in AVP is involved in Abeta-induced impairment of spatial cognition and whether AVP can protect against Abeta-induced deficits in cognitive function. The present study examined the effects of intracerebroventricular (i.c.v.) injection of AVP on spatial learning and memory in the Morris water maze test and investigated the potential protective function of AVP against Abeta-induced impairment in spatial cognition. The results were as follows: (1) i.c.v. injection of 25 nmol Abeta(25-35) resulted in a significant decline in spatial learning and memory; (2) 1 nmol and 10 nmol, but not 0.1 nmol, AVP injections markedly improved learning and memory; (3) pretreatment with 1 nmol or 10 nmol, but not 0.1 nmol, AVP effectively reversed the impairment in spatial learning and memory induced by Abeta(25-35); and (4) none of the drugs, including Abeta(25-35) and different concentrations of AVP, affected the vision or swimming speed of the rats. These results indicate that Abeta(25-35) could significantly impair spatial learning and memory in rats, and pretreatment with AVP centrally can enhance spatial learning and effectively prevent the behavioral impairment induced by neurotoxic Abeta(25-35). Thus, the present study provides further insight into the mechanisms by which Abeta impairs spatial learning and memory, suggesting that up-regulation of central AVP might be beneficial in the prevention and treatment of AD. Copyright 2010 Elsevier Inc. All rights reserved.

Toward a Multilingual, Experiential Environment for Learning Decision Technology.

ERIC Educational Resources Information Center

Yeo, Gee Kin; Tan, Seng Teen

1999-01-01

Describes work at the National University of Singapore on the Internet in expanding a simulation game used in supporting a course in decision technology. Topics include decision support systems, multilingual support for cross-cultural decision studies, process support in a World Wide Web-enhanced multiuser domain (MUD) learning environment, and…

Research on tobacco enterprise spatial decision support system based on GIS

NASA Astrophysics Data System (ADS)

Mei, Xin; Cui, Weihong

2006-10-01

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique taking GIS as representation to construct spatial decision support system of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision is given. At last the example of tobacco enterprise spatial CRM (client relation management) system is set up.

Acute social stress increases biochemical and self report markers of stress without altering spatial learning in humans.

PubMed

Klopp, Christine; Garcia, Carlos; Schulman, Allan H; Ward, Christopher P; Tartar, Jaime L

2012-01-01

Spatial learning is shown to be influenced by acute stress in both human and other animals. However, the intricacies of this relationship are unclear. Based on prior findings we hypothesized that compared to a control condition, a social stress condition would not affect spatial learning performance despite elevated biochemical markers of stress. The present study tested the effects of social stress in human males and females on a subsequent spatial learning task. Social stress induction consisted of evaluative stress (the Trier Social Stress Test, TSST) compared to a placebo social stress. Compared to the placebo condition, the TSST resulted in significantly elevated cortisol and alpha amylase levels at multiple time points following stress induction. In accord, cognitive appraisal measures also showed that participants in the TSST group experienced greater perceived stress compared to the placebo group. However, there were no group differences in performance on a spatial learning task. Our findings suggest that unlike physiological stress, social stress does not result in alterations in spatial learning in humans. It is possible that moderate social evaluative stress in humans works to prevent acute stress-mediated alterations in hippocampal learning processes..

Modulation of spatial attention by goals, statistical learning, and monetary reward.

PubMed

Jiang, Yuhong V; Sha, Li Z; Remington, Roger W

2015-10-01

This study documented the relative strength of task goals, visual statistical learning, and monetary reward in guiding spatial attention. Using a difficult T-among-L search task, we cued spatial attention to one visual quadrant by (i) instructing people to prioritize it (goal-driven attention), (ii) placing the target frequently there (location probability learning), or (iii) associating that quadrant with greater monetary gain (reward-based attention). Results showed that successful goal-driven attention exerted the strongest influence on search RT. Incidental location probability learning yielded a smaller though still robust effect. Incidental reward learning produced negligible guidance for spatial attention. The 95 % confidence intervals of the three effects were largely nonoverlapping. To understand these results, we simulated the role of location repetition priming in probability cuing and reward learning. Repetition priming underestimated the strength of location probability cuing, suggesting that probability cuing involved long-term statistical learning of how to shift attention. Repetition priming provided a reasonable account for the negligible effect of reward on spatial attention. We propose a multiple-systems view of spatial attention that includes task goals, search habit, and priming as primary drivers of top-down attention.

Modulation of spatial attention by goals, statistical learning, and monetary reward

PubMed Central

Sha, Li Z.; Remington, Roger W.

2015-01-01

This study documented the relative strength of task goals, visual statistical learning, and monetary reward in guiding spatial attention. Using a difficult T-among-L search task, we cued spatial attention to one visual quadrant by (i) instructing people to prioritize it (goal-driven attention), (ii) placing the target frequently there (location probability learning), or (iii) associating that quadrant with greater monetary gain (reward-based attention). Results showed that successful goal-driven attention exerted the strongest influence on search RT. Incidental location probability learning yielded a smaller though still robust effect. Incidental reward learning produced negligible guidance for spatial attention. The 95 % confidence intervals of the three effects were largely nonoverlapping. To understand these results, we simulated the role of location repetition priming in probability cuing and reward learning. Repetition priming underestimated the strength of location probability cuing, suggesting that probability cuing involved long-term statistical learning of how to shift attention. Repetition priming provided a reasonable account for the negligible effect of reward on spatial attention. We propose a multiple-systems view of spatial attention that includes task goals, search habit, and priming as primary drivers of top-down attention. PMID:26105657

Towards a conceptual multi-agent-based framework to simulate the spatial group decision-making process

NASA Astrophysics Data System (ADS)

Ghavami, Seyed Morsal; Taleai, Mohammad

2017-04-01

Most spatial problems are multi-actor, multi-issue and multi-phase in nature. In addition to their intrinsic complexity, spatial problems usually involve groups of actors from different organizational and cognitive backgrounds, all of whom participate in a social structure to resolve or reduce the complexity of a given problem. Hence, it is important to study and evaluate what different aspects influence the spatial problem resolution process. Recently, multi-agent systems consisting of groups of separate agent entities all interacting with each other have been put forward as appropriate tools to use to study and resolve such problems. In this study, then in order to generate a better level of understanding regarding the spatial problem group decision-making process, a conceptual multi-agent-based framework is used that represents and specifies all the necessary concepts and entities needed to aid group decision making, based on a simulation of the group decision-making process as well as the relationships that exist among the different concepts involved. The study uses five main influencing entities as concepts in the simulation process: spatial influence, individual-level influence, group-level influence, negotiation influence and group performance measures. Further, it explains the relationship among different concepts in a descriptive rather than explanatory manner. To illustrate the proposed framework, the approval process for an urban land use master plan in Zanjan—a provincial capital in Iran—is simulated using MAS, the results highlighting the effectiveness of applying an MAS-based framework when wishing to study the group decision-making process used to resolve spatial problems.

Different Perspectives: Spatial Ability Influences Where Individuals Look on a Timed Spatial Test

ERIC Educational Resources Information Center

Roach, Victoria A.; Fraser, Graham M.; Kryklywy, James H.; Mitchell, Derek G. V.; Wilson, Timothy D.

2017-01-01

Learning in anatomy can be both spatially and visually complex. Pedagogical investigations have begun exploration as to how spatial ability may mitigate learning. Emerging hypotheses suggests individuals with higher spatial reasoning may attend to images differently than those who are lacking. To elucidate attentional patterns associated with…

How spatial abilities and dynamic visualizations interplay when learning functional anatomy with 3D anatomical models.

PubMed

Berney, Sandra; Bétrancourt, Mireille; Molinari, Gaëlle; Hoyek, Nady

2015-01-01

The emergence of dynamic visualizations of three-dimensional (3D) models in anatomy curricula may be an adequate solution for spatial difficulties encountered with traditional static learning, as they provide direct visualization of change throughout the viewpoints. However, little research has explored the interplay between learning material presentation formats, spatial abilities, and anatomical tasks. First, to understand the cognitive challenges a novice learner would be faced with when first exposed to 3D anatomical content, a six-step cognitive task analysis was developed. Following this, an experimental study was conducted to explore how presentation formats (dynamic vs. static visualizations) support learning of functional anatomy, and affect subsequent anatomical tasks derived from the cognitive task analysis. A second aim was to investigate the interplay between spatial abilities (spatial visualization and spatial relation) and presentation formats when the functional anatomy of a 3D scapula and the associated shoulder flexion movement are learned. Findings showed no main effect of the presentation formats on performances, but revealed the predictive influence of spatial visualization and spatial relation abilities on performance. However, an interesting interaction between presentation formats and spatial relation ability for a specific anatomical task was found. This result highlighted the influence of presentation formats when spatial abilities are involved as well as the differentiated influence of spatial abilities on anatomical tasks. © 2015 American Association of Anatomists.

Research on the decision-making model of land-use spatial optimization

NASA Astrophysics Data System (ADS)

He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu

2009-10-01

Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.

Active and Passive Spatial Learning in Human Navigation: Acquisition of Survey Knowledge

ERIC Educational Resources Information Center

Chrastil, Elizabeth R.; Warren, William H.

2013-01-01

It seems intuitively obvious that active exploration of a new environment would lead to better spatial learning than would passive visual exposure. It is unclear, however, which components of active learning contribute to spatial knowledge, and previous literature is decidedly mixed. This experiment tests the contributions of 4 components to…

Guidance of Spatial Attention by Incidental Learning and Endogenous Cuing

ERIC Educational Resources Information Center

Jiang, Yuhong V.; Swallow, Khena M.; Rosenbaum, Gail M.

2013-01-01

Our visual system is highly sensitive to regularities in the environment. Locations that were important in one's previous experience are often prioritized during search, even though observers may not be aware of the learning. In this study we characterized the guidance of spatial attention by incidental learning of a target's spatial probability,…

A Cognitive Component Analysis Approach for Developing Game-Based Spatial Learning Tools

ERIC Educational Resources Information Center

Hung, Pi-Hsia; Hwang, Gwo-Jen; Lee, Yueh-Hsun; Su, I-Hsiang

2012-01-01

Spatial ability has been recognized as one of the most important factors affecting the mathematical performance of students. Previous studies on spatial learning have mainly focused on developing strategies to shorten the problem-solving time of learners for very specific learning tasks. Such an approach usually has limited effects on improving…

Dynamic Educational e-Content Selection Using Multiple Criteria in Web-Based Personalized Learning Environments.

ERIC Educational Resources Information Center

Manouselis, Nikos; Sampson, Demetrios

This paper focuses on the way a multi-criteria decision making methodology is applied in the case of agent-based selection of offered learning objects. The problem of selection is modeled as a decision making one, with the decision variables being the learner model and the learning objects' educational description. In this way, selection of…

Prenatal Stress Impairs Spatial Learning and Memory Associated with Lower mRNA Level of the CAMKII and CREB in the Adult Female Rat Hippocampus.

PubMed

Sun, Hongli; Wu, Haibin; Liu, Jianping; Wen, Jun; Zhu, Zhongliang; Li, Hui

2017-05-01

Prenatal stress (PS) results in various behavioral and emotional alterations observed in later life. In particular, PS impairs spatial learning and memory processes but the underlying mechanism involved in this pathogenesis still remains unknown. Here, we reported that PS lowered the body weight in offspring rats, particularly in female rats, and impaired spatial learning and memory of female offspring rats in the Morris water maze. Correspondingly, the decreased CaMKII and CREB mRNA in the hippocampus were detected in prenatally stressed female offspring, which partially explained the effect of PS on the spatial learning and memory. Our findings suggested that CaMKII and CREB may be involved in spatial learning and memory processes in the prenatally stressed adult female offspring.

Learning from Failed Decisions

ERIC Educational Resources Information Center

Nutt, Paul C.

2010-01-01

The consequences and dilemmas posed by learning issues for decision making are discussed. Learning requires both awareness of barriers and a coping strategy. The motives to hold back information essential for learning stem from perverse incentives, obscure outcomes, and the hindsight bias. There is little awareness of perverse incentives that…

Estimates of Single Sensor Error Statistics for the MODIS Matchup Database Using Machine Learning

NASA Astrophysics Data System (ADS)

Kumar, C.; Podesta, G. P.; Minnett, P. J.; Kilpatrick, K. A.

2017-12-01

Sea surface temperature (SST) is a fundamental quantity for understanding weather and climate dynamics. Although sensors aboard satellites provide global and repeated SST coverage, a characterization of SST precision and bias is necessary for determining the suitability of SST retrievals in various applications. Guidance on how to derive meaningful error estimates is still being developed. Previous methods estimated retrieval uncertainty based on geophysical factors, e.g. season or "wet" and "dry" atmospheres, but the discrete nature of these bins led to spatial discontinuities in SST maps. Recently, a new approach clustered retrievals based on the terms (excluding offset) in the statistical algorithm used to estimate SST. This approach resulted in over 600 clusters - too many to understand the geophysical conditions that influence retrieval error. Using MODIS and buoy SST matchups (2002 - 2016), we use machine learning algorithms (recursive and conditional trees, random forests) to gain insight into geophysical conditions leading to the different signs and magnitudes of MODIS SST residuals (satellite SSTs minus buoy SSTs). MODIS retrievals were first split into three categories: < -0.4 C, -0.4 C ≤ residual ≤ 0.4 C, and > 0.4 C. These categories are heavily unbalanced, with residuals > 0.4 C being much less frequent. Performance of classification algorithms is affected by imbalance, thus we tested various rebalancing algorithms (oversampling, undersampling, combinations of the two). We consider multiple features for the decision tree algorithms: regressors from the MODIS SST algorithm, proxies for temperature deficit, and spatial homogeneity of brightness temperatures (BTs), e.g., the range of 11 μm BTs inside a 25 km2 area centered on the buoy location. These features and a rebalancing of classes led to an 81.9% accuracy when classifying SST retrievals into the < -0.4 C and -0.4 C ≤ residual ≤ 0.4 C categories. Spatial homogeneity in BTs consistently appears as a very important variable for classification, suggesting that unidentified cloud contamination still is one of the causes leading to negative SST residuals. Precision and accuracy of error estimates from our decision tree classifier are enhanced using this knowledge.

Sex Differences in Using Spatial and Verbal Abilities Influence Route Learning Performance in a Virtual Environment: A Comparison of 6- to 12-Year Old Boys and Girls.

PubMed

Merrill, Edward C; Yang, Yingying; Roskos, Beverly; Steele, Sara

2016-01-01

Previous studies have reported sex differences in wayfinding performance among adults. Men are typically better at using Euclidean information and survey strategies while women are better at using landmark information and route strategies. However, relatively few studies have examined sex differences in wayfinding in children. This research investigated relationships between route learning performance and two general abilities: spatial ability and verbal memory in 153 boys and girls between 6- to 12-years-old. Children completed a battery of spatial ability tasks (a two-dimension mental rotation task, a paper folding task, a visuo-spatial working memory task, and a Piagetian water level task) and a verbal memory task. In the route learning task, they had to learn a route through a series of hallways presented via computer. Boys had better overall route learning performance than did girls. In fact, the difference between boys and girls was constant across the age range tested. Structural equation modeling of the children's performance revealed that spatial abilities and verbal memory were significant contributors to route learning performance. However, there were different patterns of correlates for boys and girls. For boys, spatial abilities contributed to route learning while verbal memory did not. In contrast, for girls both spatial abilities and verbal memory contributed to their route learning performance. This difference may reflect the precursor of a strategic difference between boys and girls in wayfinding that is commonly observed in adults.

Local dynamics in decision making: The evolution of preference within and across decisions

NASA Astrophysics Data System (ADS)

O'Hora, Denis; Dale, Rick; Piiroinen, Petri T.; Connolly, Fionnuala

2013-07-01

Within decisions, perceived alternatives compete until one is preferred. Across decisions, the playing field on which these alternatives compete evolves to favor certain alternatives. Mouse cursor trajectories provide rich continuous information related to such cognitive processes during decision making. In three experiments, participants learned to choose symbols to earn points in a discrimination learning paradigm and the cursor trajectories of their responses were recorded. Decisions between two choices that earned equally high-point rewards exhibited far less competition than decisions between choices that earned equally low-point rewards. Using positional coordinates in the trajectories, it was possible to infer a potential field in which the choice locations occupied areas of minimal potential. These decision spaces evolved through the experiments, as participants learned which options to choose. This visualisation approach provides a potential framework for the analysis of local dynamics in decision-making that could help mitigate both theoretical disputes and disparate empirical results.

Use of spatial information and search strategies in a water maze analog in Drosophila melanogaster.

PubMed

Foucaud, Julien; Burns, James G; Mery, Frederic

2010-12-03

Learning the spatial organization of the environment is crucial to fitness in most animal species. Understanding proximate and ultimate factors underpinning spatial memory is thus a major goal in the study of animal behavior. Despite considerable interest in various aspects of its behavior and biology, the model species Drosophila melanogaster lacks a standardized apparatus to investigate spatial learning and memory. We propose here a novel apparatus, the heat maze, conceptually based on the Morris water maze used in rodents. Using the heat maze, we demonstrate that D. melanogaster flies are able to use either proximal or distal visual cues to increase their performance in navigating to a safe zone. We also show that flies are actively using the orientation of distal visual cues when relevant in targeting the safe zone, i.e., Drosophila display spatial learning. Parameter-based classification of search strategies demonstrated the progressive use of spatially precise search strategies during learning. We discuss the opportunity to unravel the mechanistic and evolutionary bases of spatial learning in Drosophila using the heat maze.

Combining ecosystem services assessment with structured decision making to support ecological restoration planning.

PubMed

Martin, David M; Mazzotta, Marisa; Bousquin, Justin

2018-04-10

Accounting for ecosystem services in environmental decision making is an emerging research topic. Modern frameworks for ecosystem services assessment emphasize evaluating the social benefits of ecosystems, in terms of who benefits and by how much, to aid in comparing multiple courses of action. Structured methods that use decision analytic-approaches are emerging for the practice of ecological restoration. In this article, we combine ecosystem services assessment with structured decision making to estimate and evaluate measures of the potential benefits of ecological restoration with a case study in the Woonasquatucket River watershed, Rhode Island, USA. We partnered with a local watershed management organization to analyze dozens of candidate wetland restoration sites for their abilities to supply five ecosystem services-flood water retention, scenic landscapes, learning opportunities, recreational opportunities, and birds. We developed 22 benefit indicators related to the ecosystem services as well as indicators for social equity and reliability that benefits will sustain in the future. We applied conceptual modeling and spatial analysis to estimate indicator values for each candidate restoration site. Lastly, we developed a decision support tool to score and aggregate the values for the organization to screen the restoration sites. Results show that restoration sites in urban areas can provide greater social benefits than sites in less urban areas. Our research approach is general and can be used to investigate other restoration planning studies that perform ecosystem services assessment and fit into a decision-making process.

Gbm.auto: A software tool to simplify spatial modelling and Marine Protected Area planning

PubMed Central

Officer, Rick; Clarke, Maurice; Reid, David G.; Brophy, Deirdre

2017-01-01

Boosted Regression Trees. Excellent for data-poor spatial management but hard to use Marine resource managers and scientists often advocate spatial approaches to manage data-poor species. Existing spatial prediction and management techniques are either insufficiently robust, struggle with sparse input data, or make suboptimal use of multiple explanatory variables. Boosted Regression Trees feature excellent performance and are well suited to modelling the distribution of data-limited species, but are extremely complicated and time-consuming to learn and use, hindering access for a wide potential user base and therefore limiting uptake and usage. BRTs automated and simplified for accessible general use with rich feature set We have built a software suite in R which integrates pre-existing functions with new tailor-made functions to automate the processing and predictive mapping of species abundance data: by automating and greatly simplifying Boosted Regression Tree spatial modelling, the gbm.auto R package suite makes this powerful statistical modelling technique more accessible to potential users in the ecological and modelling communities. The package and its documentation allow the user to generate maps of predicted abundance, visualise the representativeness of those abundance maps and to plot the relative influence of explanatory variables and their relationship to the response variables. Databases of the processed model objects and a report explaining all the steps taken within the model are also generated. The package includes a previously unavailable Decision Support Tool which combines estimated escapement biomass (the percentage of an exploited population which must be retained each year to conserve it) with the predicted abundance maps to generate maps showing the location and size of habitat that should be protected to conserve the target stocks (candidate MPAs), based on stakeholder priorities, such as the minimisation of fishing effort displacement. Gbm.auto for management in various settings By bridging the gap between advanced statistical methods for species distribution modelling and conservation science, management and policy, these tools can allow improved spatial abundance predictions, and therefore better management, decision-making, and conservation. Although this package was built to support spatial management of a data-limited marine elasmobranch fishery, it should be equally applicable to spatial abundance modelling, area protection, and stakeholder engagement in various scenarios. PMID:29216310

Using Cognitive Conflict to Promote the Use of Dialectical Learning for Strategic Decision-Makers

ERIC Educational Resources Information Center

Woods, Jeffrey G.

2012-01-01

Purpose: The purpose of this paper is to develop a conceptual model that uses dialectical inquiry (DI) to create cognitive conflict in strategic decision-makers for the purpose of improving strategic decisions. Activation of the dialectical learning process using DI requires strategic decision-makers to integrate conflicting information causing…

A GIS-based Spatial Decision Support System for environmentally valuable areas in the context of sustainable development of Poland

NASA Astrophysics Data System (ADS)

Kubacka, Marta

2013-04-01

The issue of spatial development, and thus proper environmental management and protection at naturally valuable areas is today considered a major hazard to the stability of the World ecological system. The increasing demand for areas with substantial environmental and landscape assets, incorrect spatial development, improper implementation of law as well as low citizen awareness bring about significant risk of irrevocable loss of naturally valuable areas. The elaboration of a Decision Support System in the form of collection of spatial data will facilitate solving complex problems concerning spatial development. The elaboration of a model utilizing a number of IT tools will boost the effectiveness of taking spatial decisions by decision-makers. Proper spatial data management becomes today a key element in management based on knowledge, namely sustainable development. Decision Support Systems are definied as model-based sets of procedures for processing data and judgments to assist a manager in his decision-making. The main purpose of the project was to elaborate the spatial decision support system for the Sieraków Landscape Park. A landscape park in Poland comprises a protected area due to environmental, historic and cultural values as well as landscape assets for the purpose of maintaining and popularizing these values in the conditions of sustainable development. It also defines the forms of protected area management and introduces bans concerning activity at these areas by means of the obligation to prepare and implement environmental protection plans by a director of the complex of landscape parks. As opposed to national parks and reserves, natural landscape parks are not the areas free from economic activity, thus agricultural lands, forest lands and other real properties located within the boundaries of natural landscape parks are subject to economic utilization Research area was subject to the analysis with respect to the implementation of investment actions consisting mainly in the agricultural economy. Versatile relief, diversified geological formations as well as the depth of depositing ground water and the risk of flooding have impact on diversified possibilities of the land use. Intensive agricultural economy at large field area and forestry constitute the major human activity at the area of the Park. The criteria which may be in the form of factors (e.g. soil with much agricultural suitability or very low slopes) or limitations (e.g. soils with little agricultural suitability, forest areas in close vicinity of water bodies) constitute the grounds for taking a decision on determining the areas for agricultural economy. The thesis presents the possibilities which Geographic Information Systems provide at the stage of taking spatial decisions at environmentally valuable areas. The pressure on environmentally valuable areas is growing all over the world and it may be assumed that spatial conflicts between the development of agricultural areas and the natural environment will intensify. Spatial planning is the best possibilities of reducing and mitigating this pressure. This process should take into consideration the provisions of the European Landscape Convention which is the basic instrument for landscape preservation and nature protection.

Spatial modeling and classification of corneal shape.

PubMed

Marsolo, Keith; Twa, Michael; Bullimore, Mark A; Parthasarathy, Srinivasan

2007-03-01

One of the most promising applications of data mining is in biomedical data used in patient diagnosis. Any method of data analysis intended to support the clinical decision-making process should meet several criteria: it should capture clinically relevant features, be computationally feasible, and provide easily interpretable results. In an initial study, we examined the feasibility of using Zernike polynomials to represent biomedical instrument data in conjunction with a decision tree classifier to distinguish between the diseased and non-diseased eyes. Here, we provide a comprehensive follow-up to that work, examining a second representation, pseudo-Zernike polynomials, to determine whether they provide any increase in classification accuracy. We compare the fidelity of both methods using residual root-mean-square (rms) error and evaluate accuracy using several classifiers: neural networks, C4.5 decision trees, Voting Feature Intervals, and Naïve Bayes. We also examine the effect of several meta-learning strategies: boosting, bagging, and Random Forests (RFs). We present results comparing accuracy as it relates to dataset and transformation resolution over a larger, more challenging, multi-class dataset. They show that classification accuracy is similar for both data transformations, but differs by classifier. We find that the Zernike polynomials provide better feature representation than the pseudo-Zernikes and that the decision trees yield the best balance of classification accuracy and interpretability.

Designing a Web-Based Learning Portal for Geographic Visualization and Analysis in Public Health

PubMed Central

Robinson, Anthony C.; Roth, Robert E.; MacEachren, Alan M.

2011-01-01

Interactive mapping and spatial analysis tools are underutilized by health researchers and decision-makers due to scarce training materials, few examples demonstrating the successful use of geographic visualization, and poor mechanisms for sharing results generated by geovisualization. We report here on the development of the Geovisual EXplication (G-EX) Portal, a web-based application designed to connect researchers in geovisualization and related mapping sciences to users who are working in public health and epidemiology. This paper focuses on the design and development of the G-EX Portal Learn module, a set of tools intended to disseminate learning artifacts. Initial design and development of the G-EX Portal has been guided by our past research on use and usability of geovisualization in public health. As part of the iterative design and development process, we conducted a needs assessment survey with targeted end-users that we report on here. The survey focused on users’ current learning habits, their preferred kind of learning artifacts, and issues they may have with contributing learning artifacts to web portals. Survey results showed that users desire a diverse set of learning artifacts in terms of both formats and topics covered. Results also revealed a willingness of users to contribute both learning artifacts and personal information that would help other users to evaluate the credibility of the learning artifact source. We include a detailed description of the G-EX Portal Learn module and focus on modifications to the design of the Learn module as a result from feedback we received from our survey. PMID:21937462

Connecting mathematics learning through spatial reasoning

NASA Astrophysics Data System (ADS)

Mulligan, Joanne; Woolcott, Geoffrey; Mitchelmore, Michael; Davis, Brent

2018-03-01

Spatial reasoning, an emerging transdisciplinary area of interest to mathematics education research, is proving integral to all human learning. It is particularly critical to science, technology, engineering and mathematics (STEM) fields. This project will create an innovative knowledge framework based on spatial reasoning that identifies new pathways for mathematics learning, pedagogy and curriculum. Novel analytical tools will map the unknown complex systems linking spatial and mathematical concepts. It will involve the design, implementation and evaluation of a Spatial Reasoning Mathematics Program (SRMP) in Grades 3 to 5. Benefits will be seen through development of critical spatial skills for students, increased teacher capability and informed policy and curriculum across STEM education.

Consumer Decision-Making Styles as a Function of Individual Learning Styles.

ERIC Educational Resources Information Center

Sproles, Elizabeth Kendall; Sproles, George B.

1990-01-01

The Secondary Learning Styles Inventory and the Consumer Styles Inventory were administered to 501 secondary home economics students. Factor analysis of the learning style characteristics from the sample of 482 found significant correlations between 21 of the 48 pairs of learning and decision-making characteristics. (SK)

Map for Decision Making in Operating Distance Learning System--Research Results.

ERIC Educational Resources Information Center

Offir, Baruch

2000-01-01

Examines decision-making aspects of the introduction of distance learning into university instruction and learning based on experiences in Israel. Discusses the introduction of information technology into the classroom; examines teacher/student interactions; and suggests a model for introducing distance learning that focuses on the role of the…

Computational prediction of multidisciplinary team decision-making for adjuvant breast cancer drug therapies: a machine learning approach.

PubMed

Lin, Frank P Y; Pokorny, Adrian; Teng, Christina; Dear, Rachel; Epstein, Richard J

2016-12-01

Multidisciplinary team (MDT) meetings are used to optimise expert decision-making about treatment options, but such expertise is not digitally transferable between centres. To help standardise medical decision-making, we developed a machine learning model designed to predict MDT decisions about adjuvant breast cancer treatments. We analysed MDT decisions regarding adjuvant systemic therapy for 1065 breast cancer cases over eight years. Machine learning classifiers with and without bootstrap aggregation were correlated with MDT decisions (recommended, not recommended, or discussable) regarding adjuvant cytotoxic, endocrine and biologic/targeted therapies, then tested for predictability using stratified ten-fold cross-validations. The predictions so derived were duly compared with those based on published (ESMO and NCCN) cancer guidelines. Machine learning more accurately predicted adjuvant chemotherapy MDT decisions than did simple application of guidelines. No differences were found between MDT- vs. ESMO/NCCN- based decisions to prescribe either adjuvant endocrine (97%, p = 0.44/0.74) or biologic/targeted therapies (98%, p = 0.82/0.59). In contrast, significant discrepancies were evident between MDT- and guideline-based decisions to prescribe chemotherapy (87%, p < 0.01, representing 43% and 53% variations from ESMO/NCCN guidelines, respectively). Using ten-fold cross-validation, the best classifiers achieved areas under the receiver operating characteristic curve (AUC) of 0.940 for chemotherapy (95% C.I., 0.922-0.958), 0.899 for the endocrine therapy (95% C.I., 0.880-0.918), and 0.977 for trastuzumab therapy (95% C.I., 0.955-0.999) respectively. Overall, bootstrap aggregated classifiers performed better among all evaluated machine learning models. A machine learning approach based on clinicopathologic characteristics can predict MDT decisions about adjuvant breast cancer drug therapies. The discrepancy between MDT- and guideline-based decisions regarding adjuvant chemotherapy implies that certain non-clincopathologic criteria, such as patient preference and resource availability, are factored into clinical decision-making by local experts but not captured by guidelines.

Altered Risk-Based Decision Making following Adolescent Alcohol Use Results from an Imbalance in Reinforcement Learning in Rats

PubMed Central

Hart, Andrew S.; Collins, Anne L.; Bernstein, Ilene L.; Phillips, Paul E. M.

2012-01-01

Alcohol use during adolescence has profound and enduring consequences on decision-making under risk. However, the fundamental psychological processes underlying these changes are unknown. Here, we show that alcohol use produces over-fast learning for better-than-expected, but not worse-than-expected, outcomes without altering subjective reward valuation. We constructed a simple reinforcement learning model to simulate altered decision making using behavioral parameters extracted from rats with a history of adolescent alcohol use. Remarkably, the learning imbalance alone was sufficient to simulate the divergence in choice behavior observed between these groups of animals. These findings identify a selective alteration in reinforcement learning following adolescent alcohol use that can account for a robust change in risk-based decision making persisting into later life. PMID:22615989

Pitfalls of Counterfactual Thinking in Medical Practice: Preventing Errors by Using More Functional Reference Points

PubMed Central

Petrocelli, John V.

2013-01-01

Background Counterfactual thinking involves mentally simulating alternatives to reality. The current article reviews literature pertaining to the relevance counterfactual thinking has for the quality of medical decision making. Although earlier counterfactual thought research concluded that counterfactuals have important benefits for the individual, there are reasons to believe that counterfactual thinking is also associated with dysfunctional consequences. Of particular focus is whether or not medical experience, and its influence on counterfactual thinking, actually informs or improves medical practice. It is hypothesized that relatively more probable decision alternatives, followed by undesirable outcomes and counterfactual thought responses, can be abandoned for relatively less probable decision alternatives. Design and Methods Building on earlier research demonstrating that counterfactual thinking can impede memory and learning in a decision paradigm with undergraduate students, the current study examines the extent to which earlier findings can be generalized to practicing physicians (N=10). Participants were asked to complete 60 trials of a computerized Monty Hall Problem simulation. Learning by experience was operationalized as the frequency of switch-decisions. Results Although some learning was evidenced by a general increase in switch-decision frequency across block trials, the extent of learning demonstrated was not ideal, nor practical. Conclusions A simple, multiple-trial, decision paradigm demonstrated that doctors fail to learn basic decision-outcome associations through experience. An agenda for future research, which tests the functionality of reference points (other than counterfactual alternatives) for the purposes of medical decision making, is proposed. Significance for public health The quality of healthcare depends heavily on the judgments and decisions made by doctors and other medical professionals. Findings from this research indicate that doctors fail to learn basic decision-outcome associations through experience, as evidenced by the sample’s tendency to select the optimal decision strategy in only 50% of 60 trials (each of which was followed by veridical feedback). These findings suggest that professional experience is unlikely to enhance the quality of medical decision making. Thus, this research has implications for understanding how doctors’ reactions to medical outcomes shape their judgments and affect the degree to which their future treatment intentions are consistent with clinical practice guidelines. The current research is integrated with earlier research on counter-factual thinking, which appears to be a primary element inhibiting the learning of decision-outcome associations. An agenda for future research is proposed. PMID:25170495

Texas Urban Triangle : pilot study to implement a spatial decision support system (SDSS) for sustainable mobility.

DOT National Transportation Integrated Search

2011-03-01

This project addressed sustainable transportation in the Texas Urban Triangle (TUT) by conducting a pilot : project at the county scale. The project tested and developed the multi-attribute Spatial Decision Support : System (SDSS) developed in 2009 u...

Practice guidelines in the context of primary care, learning and usability in the physicians' decision-making process--a qualitative study.

PubMed

Ingemansson, Maria; Bastholm-Rahmner, Pia; Kiessling, Anna

2014-08-20

Decision-making is central for general practitioners (GP). Practice guidelines are important tools in this process but implementation of them in the complex context of primary care is a challenge. The purpose of this study was to explore how GPs approach, learn from and use practice guidelines in their day-to-day decision-making process in primary care. A qualitative approach using focus-group interviews was chosen in order to provide in-depth information. The participants were 22 GPs with a median of seven years of experience in primary care, representing seven primary healthcare centres in Stockholm, Sweden in 2011. The interviews focused on how the GPs use guidelines in their decision-making, factors that influence their decision how to approach these guidelines, and how they could encourage the learning process in routine practice.Data were analysed by qualitative content analysis. Meaning units were condensed and grouped in categories. After interpreting the content in the categories, themes were created. Three themes were conceptualized. The first theme emphasized to use guidelines by interactive contextualized dialogues. The categories underpinning this theme: 1. Feedback by peer-learning 2. Feedback by collaboration, mutual learning, and equality between specialties, identified important ways to achieve this learning dialogue. Confidence was central in the second theme, learning that establishes confidence to provide high quality care. Three aspects of confidence were identified in the categories of this theme: 1. Confidence by confirmation, 2. Confidence by reliability and 3. Confidence by evaluation of own results. In the third theme, learning by use of relevant evidence in the decision-making process, we identified two categories: 1. Design and lay-out visualizing the evidence 2. Accessibility adapted to the clinical decision-making process as prerequisites for using the practice guidelines. Decision-making in primary care is a dual process that involves use of intuitive and analytic thinking in a balanced way in order to provide high quality care. Key aspects of effective learning in this clinical decision-making process were: contextualized dialogue, which was based on the GPs' own experiences, feedback on own results and easy access to short guidelines perceived as trustworthy.

Analysing malaria incidence at the small area level for developing a spatial decision support system: A case study in Kalaburagi, Karnataka, India.

PubMed

Shekhar, S; Yoo, E-H; Ahmed, S A; Haining, R; Kadannolly, S

2017-02-01

Spatial decision support systems have already proved their value in helping to reduce infectious diseases but to be effective they need to be designed to reflect local circumstances and local data availability. We report the first stage of a project to develop a spatial decision support system for infectious diseases for Karnataka State in India. The focus of this paper is on malaria incidence and we draw on small area data on new cases of malaria analysed in two-monthly time intervals over the period February 2012 to January 2016 for Kalaburagi taluk, a small area in Karnataka. We report the results of data mapping and cluster detection (identifying areas of excess risk) including evaluating the temporal persistence of excess risk and the local conditions with which high counts are statistically associated. We comment on how this work might feed into a practical spatial decision support system. Copyright © 2017 Elsevier Ltd. All rights reserved.

The role of low-spatial frequencies in lexical decision and masked priming.

PubMed

Boden, C; Giaschi, D

2009-04-01

Spatial frequency filtering was used to test the hypotheses that low-spatial frequency information in printed text can: (1) lead to a rapid lexical decision or (2) facilitate word recognition. Adult proficient readers made lexical decisions in unprimed and masked repetition priming experiments with unfiltered, low-pass, high-pass and notch filtered letter strings. In the unprimed experiments, a filtered target was presented for 105 or 400 ms followed by a pattern mask. Sensitivity (d') was lowest for the low-pass filtered targets at both durations with a bias towards a 'non-word' response. Sensitivity was higher in the high-pass and notch filter conditions. In the priming experiments, a forward mask was followed by a filtered prime then an unfiltered target. Primed words, but not non-words, were identified faster than unprimed words in both the low-pass and high-pass filtered conditions. These results do not support a unique role for low-spatial frequency information in either facilitating or making rapid lexical decisions.

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

PubMed Central

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

2014-01-01

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

Joint Extraction of Entities and Relations Using Reinforcement Learning and Deep Learning.

PubMed

Feng, Yuntian; Zhang, Hongjun; Hao, Wenning; Chen, Gang

2017-01-01

We use both reinforcement learning and deep learning to simultaneously extract entities and relations from unstructured texts. For reinforcement learning, we model the task as a two-step decision process. Deep learning is used to automatically capture the most important information from unstructured texts, which represent the state in the decision process. By designing the reward function per step, our proposed method can pass the information of entity extraction to relation extraction and obtain feedback in order to extract entities and relations simultaneously. Firstly, we use bidirectional LSTM to model the context information, which realizes preliminary entity extraction. On the basis of the extraction results, attention based method can represent the sentences that include target entity pair to generate the initial state in the decision process. Then we use Tree-LSTM to represent relation mentions to generate the transition state in the decision process. Finally, we employ Q -Learning algorithm to get control policy π in the two-step decision process. Experiments on ACE2005 demonstrate that our method attains better performance than the state-of-the-art method and gets a 2.4% increase in recall-score.

Joint Extraction of Entities and Relations Using Reinforcement Learning and Deep Learning

PubMed Central

Zhang, Hongjun; Chen, Gang

2017-01-01

We use both reinforcement learning and deep learning to simultaneously extract entities and relations from unstructured texts. For reinforcement learning, we model the task as a two-step decision process. Deep learning is used to automatically capture the most important information from unstructured texts, which represent the state in the decision process. By designing the reward function per step, our proposed method can pass the information of entity extraction to relation extraction and obtain feedback in order to extract entities and relations simultaneously. Firstly, we use bidirectional LSTM to model the context information, which realizes preliminary entity extraction. On the basis of the extraction results, attention based method can represent the sentences that include target entity pair to generate the initial state in the decision process. Then we use Tree-LSTM to represent relation mentions to generate the transition state in the decision process. Finally, we employ Q-Learning algorithm to get control policy π in the two-step decision process. Experiments on ACE2005 demonstrate that our method attains better performance than the state-of-the-art method and gets a 2.4% increase in recall-score. PMID:28894463

Spatial Downscaling of Alien Species Presences using Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis N.; Katsanevakis, Stelios; Moustakas, Aristides

2017-07-01

Large scale, high-resolution data on alien species distributions are essential for spatially explicit assessments of their environmental and socio-economic impacts, and management interventions for mitigation. However, these data are often unavailable. This paper presents a method that relies on Random Forest (RF) models to distribute alien species presence counts at a finer resolution grid, thus achieving spatial downscaling. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The method is tested with an approximately 8×8 km2 grid containing floral alien species presence and several indices of climatic, habitat, land use covariates for the Mediterranean island of Crete, Greece. Alien species presence is aggregated at 16×16 km2 and used as a predictor of presence at the original resolution, thus simulating spatial downscaling. Potential explanatory variables included habitat types, land cover richness, endemic species richness, soil type, temperature, precipitation, and freshwater availability. Uncertainty assessment of the spatial downscaling of alien species’ occurrences was also performed and true/false presences and absences were quantified. The approach is promising for downscaling alien species datasets of larger spatial scale but coarse resolution, where the underlying environmental information is available at a finer resolution than the alien species data. Furthermore, the RF architecture allows for tuning towards operationally optimal sensitivity and specificity, thus providing a decision support tool for designing a resource efficient alien species census.

Interactive Management and Updating of Spatial Data Bases

NASA Technical Reports Server (NTRS)

French, P.; Taylor, M.

1982-01-01

The decision making process, whether for power plant siting, load forecasting or energy resource planning, invariably involves a blend of analytical methods and judgement. Management decisions can be improved by the implementation of techniques which permit an increased comprehension of results from analytical models. Even where analytical procedures are not required, decisions can be aided by improving the methods used to examine spatially and temporally variant data. How the use of computer aided planning (CAP) programs and the selection of a predominant data structure, can improve the decision making process is discussed.

Visual Perceptual Learning and Models.

PubMed

Dosher, Barbara; Lu, Zhong-Lin

2017-09-15

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

Development of Critical Spatial Thinking through GIS Learning

ERIC Educational Resources Information Center

Kim, Minsung; Bednarz, Robert

2013-01-01

This study developed an interview-based critical spatial thinking oral test and used the test to investigate the effects of Geographic Information System (GIS) learning on three components of critical spatial thinking: evaluating data reliability, exercising spatial reasoning, and assessing problem-solving validity. Thirty-two students at a large…

Think3d!: Improving Mathematics Learning through Embodied Spatial Training

ERIC Educational Resources Information Center

Burte, Heather; Gardony, Aaron L.; Hutton, Allyson; Taylor, Holly A.

2017-01-01

Spatial thinking skills positively relate to Science, Technology, Engineering, and Math (STEM) outcomes, but spatial training is largely absent in elementary school. Elementary school is a time when children develop foundational cognitive skills that will support STEM learning throughout their education. Spatial thinking should be considered a…

Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Students’ Spatial Ability through Open-Ended Approach Aided by Cabri 3D

NASA Astrophysics Data System (ADS)

Priatna, N.

2017-09-01

The use of computer software such as Cabri 3D for learning activities is very unlimited. Students can adjust their learning speed according to their level of ability. Open-ended approach strongly supports the use of computer software in learning, because the goal of open-ended learning is to help developing creative activities and mathematical mindset of students through problem solving simultaneously. In other words, creative activities and mathematical mindset of students should be developed as much as possible in accordance with the ability of spatial ability of each student. Spatial ability is the ability of students in constructing and representing geometry models. This study aims to determine the improvement of spatial ability of junior high school students who obtained learning with open-ended approach aided by Cabri 3D. It adopted a quasi-experimental method with the non-randomized control group pretest-posttest design and the 2×3 factorial model. The instrument of the study is spatial ability test. Based on analysis of the data, it is found that the improvement of spatial ability of students who received open-ended learning aided by Cabri 3D was greater than students who received expository learning, both as a whole and based on the categories of students’ initial mathematical ability.

Enhancing Decision-Making in STSE Education by Inducing Reflection and Self-Regulated Learning

NASA Astrophysics Data System (ADS)

Gresch, Helge; Hasselhorn, Marcus; Bögeholz, Susanne

2017-02-01

Thoughtful decision-making to resolve socioscientific issues is central to science, technology, society, and environment (STSE) education. One approach for attaining this goal involves fostering students' decision-making processes. Thus, the present study explores whether the application of decision-making strategies, combined with reflections on the decision-making processes of others, enhances decision-making competence. In addition, this study examines whether this process is supported by elements of self-regulated learning, i.e., self-reflection regarding one's own performance and the setting of goals for subsequent tasks. A computer-based training program which involves the resolution of socioscientific issues related to sustainable development was developed in two versions: with and without elements of self-regulated learning. Its effects on decision-making competence were analyzed using a pre test-post test follow-up control-group design ( N = 242 high school students). Decision-making competence was assessed using an open-ended questionnaire that focused on three facets: consideration of advantages and disadvantages, metadecision aspects, and reflection on the decision-making processes of others. The findings suggest that students in both training groups incorporated aspects of metadecision into their statements more often than students in the control group. Furthermore, both training groups were more successful in reflecting on the decision-making processes of others. The students who received additional training in self-regulated learning showed greater benefits in terms of metadecision aspects and reflection, and these effects remained significant two months later. Overall, our findings demonstrate that the application of decision-making strategies, combined with reflections on the decision-making process and elements of self-regulated learning, is a fruitful approach in STSE education.

Discovering Decision Knowledge from Web Log Portfolio for Managing Classroom Processes by Applying Decision Tree and Data Cube Technology.

ERIC Educational Resources Information Center

Chen, Gwo-Dong; Liu, Chen-Chung; Ou, Kuo-Liang; Liu, Baw-Jhiune

2000-01-01

Discusses the use of Web logs to record student behavior that can assist teachers in assessing performance and making curriculum decisions for distance learning students who are using Web-based learning systems. Adopts decision tree and data cube information processing methodologies for developing more effective pedagogical strategies. (LRW)

Developmental changes in spatial learning in the Morris water-maze in young meadow voles, Microtus pennsylvanicus.

PubMed

Galea, L A; Ossenkopp, K P; Kavaliers, M

1994-01-31

Spatial learning in pre- and postweaning meadow voles, (Microtus pennsylvanicus) was examined in a Morris water-maze task. The learning performance of 10-day-old (preweaning) and 15-, 20- and 25-day-old (postweaning) male and female voles was assessed by measuring the latency to reach a hidden platform by each animal twice a day for 5 days. Voles of all age groups were able to learn the spatial task with Day 10 and Day 15 voles acquiring the task more slowly than did Day 20 and Day 25 voles. There were no significant sex differences in task acquisition in any of the four age groups. In addition, although swimming speed was related to age, with older animals swimming faster than younger ones, differences in swim speed did not account for the faster acquisition by the older animals. These results show that both preweaning and postweaning voles can successfully learn a spatial task. This is in contrast to preweaning laboratory rats which cannot successfully acquire a similar spatial task. These findings indicate that there are species differences in the ontogeny of spatial learning, which are likely related to the ecological and behavioural developmental characteristics of the species. Furthermore, in contrast to the sex difference in water-maze performance obtained in adult, breeding meadow voles who demonstrate a sex difference, there were no significant sex differences in the spatial performance of the juvenile voles. This suggests that sex differences in spatial learning in the meadow vole do not appear until voles reach reproductive adulthood.

Containment and Support: Core and Complexity in Spatial Language Learning.

PubMed

Landau, Barbara; Johannes, Kristen; Skordos, Dimitrios; Papafragou, Anna

2017-04-01

Containment and support have traditionally been assumed to represent universal conceptual foundations for spatial terms. This assumption can be challenged, however: English in and on are applied across a surprisingly broad range of exemplars, and comparable terms in other languages show significant variation in their application. We propose that the broad domains of both containment and support have internal structure that reflects different subtypes, that this structure is reflected in basic spatial term usage across languages, and that it constrains children's spatial term learning. Using a newly developed battery, we asked how adults and 4-year-old children speaking English or Greek distribute basic spatial terms across subtypes of containment and support. We found that containment showed similar distributions of basic terms across subtypes among all groups while support showed such similarity only among adults, with striking differences between children learning English versus Greek. We conclude that the two domains differ considerably in the learning problems they present, and that learning in and on is remarkably complex. Together, our results point to the need for a more nuanced view of spatial term learning. Copyright © 2016 Cognitive Science Society, Inc.

Hippocampus-dependent place learning enables spatial flexibility in C57BL6/N mice

PubMed Central

Kleinknecht, Karl R.; Bedenk, Benedikt T.; Kaltwasser, Sebastian F.; Grünecker, Barbara; Yen, Yi-Chun; Czisch, Michael; Wotjak, Carsten T.

2012-01-01

Spatial navigation is a fundamental capability necessary in everyday life to locate food, social partners, and shelter. It results from two very different strategies: (1) place learning which enables for flexible way finding and (2) response learning that leads to a more rigid “route following.” Despite the importance of knockout techniques that are only available in mice, little is known about mice' flexibility in spatial navigation tasks. Here we demonstrate for C57BL6/N mice in a water-cross maze (WCM) that only place learning enables spatial flexibility and relearning of a platform position, whereas response learning does not. This capability depends on an intact hippocampal formation, since hippocampus lesions by ibotenic acid (IA) disrupted relearning. In vivo manganese-enhanced magnetic resonance imaging revealed a volume loss of ≥60% of the hippocampus as a critical threshold for relearning impairments. In particular the changes in the left ventral hippocampus were indicative of relearning deficits. In summary, our findings establish the importance of hippocampus-dependent place learning for spatial flexibility and provide a first systematic analysis on spatial flexibility in mice. PMID:23293591

Sex Differences in Using Spatial and Verbal Abilities Influence Route Learning Performance in a Virtual Environment: A Comparison of 6- to 12-Year Old Boys and Girls

PubMed Central

Merrill, Edward C.; Yang, Yingying; Roskos, Beverly; Steele, Sara

2016-01-01

Previous studies have reported sex differences in wayfinding performance among adults. Men are typically better at using Euclidean information and survey strategies while women are better at using landmark information and route strategies. However, relatively few studies have examined sex differences in wayfinding in children. This research investigated relationships between route learning performance and two general abilities: spatial ability and verbal memory in 153 boys and girls between 6- to 12-years-old. Children completed a battery of spatial ability tasks (a two-dimension mental rotation task, a paper folding task, a visuo-spatial working memory task, and a Piagetian water level task) and a verbal memory task. In the route learning task, they had to learn a route through a series of hallways presented via computer. Boys had better overall route learning performance than did girls. In fact, the difference between boys and girls was constant across the age range tested. Structural equation modeling of the children’s performance revealed that spatial abilities and verbal memory were significant contributors to route learning performance. However, there were different patterns of correlates for boys and girls. For boys, spatial abilities contributed to route learning while verbal memory did not. In contrast, for girls both spatial abilities and verbal memory contributed to their route learning performance. This difference may reflect the precursor of a strategic difference between boys and girls in wayfinding that is commonly observed in adults. PMID:26941701

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

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

Wanderer, Thomas, E-mail: thomas.wanderer@dlr.de; Herle, Stefan, E-mail: stefan.herle@rwth-aachen.de

2015-04-15

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sitesmore » are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.« less

Lifelong Transfer Learning for Heterogeneous Teams of Agents in Sequential Decision Processes

DTIC Science & Technology

2016-06-01

making (SDM) tasks in dynamic environments with simulated and physical robots . 15. SUBJECT TERMS Sequential decision making, lifelong learning, transfer...sequential decision-making (SDM) tasks in dynamic environments with both simple benchmark tasks and more complex aerial and ground robot tasks. Our work...and ground robots in the presence of disturbances: We applied our methods to the problem of learning controllers for robots with novel disturbances in

Reduced spatial learning in mice infected with the nematode, Heligmosomoides polygyrus.

PubMed

Kavaliers, M; Colwell, D D

1995-06-01

Parasite modification of host behaviour influences a number of critical responses, but little is known about the effects on host spatial abilities. This study examined the effects of infection with the intestinal trichostrongylid nematode, Heligmosomoides polygyrus, on spatial water maze learning by male laboratory mice, Mus musculus. In this task individual mice had to learn the spatial location of a submerged hidden platform using extramaze visual cues. Determinations of spatial performance were made on day 19 post-infection with mice that had been administered either 50 or 200 infective larvae of H. polygyrus. The infected mice displayed over 1 day of testing (6 blocks of 4 trials) significantly poorer acquisition and retention of the water maze task than either sham-infected or control mice, with mice that had received 200 infective larvae displaying significantly poorer spatial performance than individuals receiving 50 larvae. The decrease in spatial learning occurred in the absence of either any symptoms of illness and malaise, or any evident motor, visual and motivational impairments. It is suggested that in this single host system the parasitic infection-induced decrease in spatial learning arises as a side-effect of the host's immunological and neuromodulatory responses and represents a fitness cost of response to infection.

Spatial frequency discrimination learning in normal and developmentally impaired human vision

PubMed Central

Astle, Andrew T.; Webb, Ben S.; McGraw, Paul V.

2010-01-01

Perceptual learning effects demonstrate that the adult visual system retains neural plasticity. If perceptual learning holds any value as a treatment tool for amblyopia, trained improvements in performance must generalise. Here we investigate whether spatial frequency discrimination learning generalises within task to other spatial frequencies, and across task to contrast sensitivity. Before and after training, we measured contrast sensitivity and spatial frequency discrimination (at a range of reference frequencies 1, 2, 4, 8, 16 c/deg). During training, normal and amblyopic observers were divided into three groups. Each group trained on a spatial frequency discrimination task at one reference frequency (2, 4, or 8 c/deg). Normal and amblyopic observers who trained at lower frequencies showed a greater rate of within task learning (at their reference frequency) compared to those trained at higher frequencies. Compared to normals, amblyopic observers showed greater within task learning, at the trained reference frequency. Normal and amblyopic observers showed asymmetrical transfer of learning from high to low spatial frequencies. Both normal and amblyopic subjects showed transfer to contrast sensitivity. The direction of transfer for contrast sensitivity measurements was from the trained spatial frequency to higher frequencies, with the bandwidth and magnitude of transfer greater in the amblyopic observers compared to normals. The findings provide further support for the therapeutic efficacy of this approach and establish general principles that may help develop more effective protocols for the treatment of developmental visual deficits. PMID:20832416

A Deep Similarity Metric Learning Model for Matching Text Chunks to Spatial Entities

NASA Astrophysics Data System (ADS)

Ma, K.; Wu, L.; Tao, L.; Li, W.; Xie, Z.

2017-12-01

The matching of spatial entities with related text is a long-standing research topic that has received considerable attention over the years. This task aims at enrich the contents of spatial entity, and attach the spatial location information to the text chunk. In the data fusion field, matching spatial entities with the corresponding describing text chunks has a big range of significance. However, the most traditional matching methods often rely fully on manually designed, task-specific linguistic features. This work proposes a Deep Similarity Metric Learning Model (DSMLM) based on Siamese Neural Network to learn similarity metric directly from the textural attributes of spatial entity and text chunk. The low-dimensional feature representation of the space entity and the text chunk can be learned separately. By employing the Cosine distance to measure the matching degree between the vectors, the model can make the matching pair vectors as close as possible. Mearnwhile, it makes the mismatching as far apart as possible through supervised learning. In addition, extensive experiments and analysis on geological survey data sets show that our DSMLM model can effectively capture the matching characteristics between the text chunk and the spatial entity, and achieve state-of-the-art performance.

Hyperspectral imagery super-resolution by compressive sensing inspired dictionary learning and spatial-spectral regularization.

PubMed

Huang, Wei; Xiao, Liang; Liu, Hongyi; Wei, Zhihui

2015-01-19

Due to the instrumental and imaging optics limitations, it is difficult to acquire high spatial resolution hyperspectral imagery (HSI). Super-resolution (SR) imagery aims at inferring high quality images of a given scene from degraded versions of the same scene. This paper proposes a novel hyperspectral imagery super-resolution (HSI-SR) method via dictionary learning and spatial-spectral regularization. The main contributions of this paper are twofold. First, inspired by the compressive sensing (CS) framework, for learning the high resolution dictionary, we encourage stronger sparsity on image patches and promote smaller coherence between the learned dictionary and sensing matrix. Thus, a sparsity and incoherence restricted dictionary learning method is proposed to achieve higher efficiency sparse representation. Second, a variational regularization model combing a spatial sparsity regularization term and a new local spectral similarity preserving term is proposed to integrate the spectral and spatial-contextual information of the HSI. Experimental results show that the proposed method can effectively recover spatial information and better preserve spectral information. The high spatial resolution HSI reconstructed by the proposed method outperforms reconstructed results by other well-known methods in terms of both objective measurements and visual evaluation.

SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CHICAGO: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND ENVIRONMENTAL RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

E-learning based distance education programme on Remote Sensing and Geoinformation Science - An initiative of IIRS

NASA Astrophysics Data System (ADS)

Karnatak, H.; Raju, P. L. N.; Krishna Murthy, Y. V. N.; Srivastav, S. K.; Gupta, P. K.

2014-11-01

IIRS has initiated its interactive distance education based capacity building under IIRS outreach programme in year 2007 where more than 15000+ students were trained in the field of geospatial technology using Satellite based interactive terminals and internet based learning using A-View software. During last decade the utilization of Internet technology by different user groups in the society is emerged as a technological revaluation which has directly affect the life of human being. The Internet is used extensively in India for various purposes right from entrainment to critical decision making in government machinery. The role of internet technology is very important for capacity building in any discipline which can satisfy the needs of maximum users in minimum time. Further to enhance the outreach of geospatial science and technology, IIRS has initiated e-learning based certificate courses of different durations. The contents for e-learning based capacity building programme are developed for various target user groups including mid-career professionals, researchers, academia, fresh graduates, and user department professionals from different States and Central Government ministries. The official website of IIRS e-learning is hosted at http://elearning.iirs.gov.in. The contents of IIRS e-learning programme are flexible for anytime, anywhere learning keeping in mind the demands of geographically dispersed audience and their requirements. The program is comprehensive with variety of online delivery modes with interactive, easy to learn and having a proper blend of concepts and practical to elicit students' full potential. The course content of this programme includes Image Statistics, Basics of Remote Sensing, Photogrammetry and Cartography, Digital Image Processing, Geographical Information System, Global Positioning System, Customization of Geospatial tools and Applications of Geospatial Technologies. The syllabus of the courses is as per latest developments and trends in geo-spatial science and technologies with specific focus on Indian case studies for geo-spatial applications. The learning is made available through interactive 2D and 3D animations, audio, video for practical demonstrations, software operations with free data applications. The learning methods are implemented to make it more interactive and learner centric application with practical examples of real world problems.

The effect of subjective awareness measures on performance in artificial grammar learning task.

PubMed

Ivanchei, Ivan I; Moroshkina, Nadezhda V

2018-01-01

Systematic research into implicit learning requires well-developed awareness-measurement techniques. Recently, trial-by-trial measures have been widely used. However, they can increase complexity of a study because they are an additional experimental variable. We tested the effects of these measures on performance in artificial grammar learning study. Four groups of participants were assigned to different awareness measures conditions: confidence ratings, post-decision wagering, decision strategy attribution or none. Decision-strategy-attribution participants demonstrated better grammar learning and longer response times compared to controls. They also exhibited a conservative bias. Grammaticality by itself was a stronger predictor of strings endorsement in decision-strategy-attribution group compared to other groups. Confidence ratings and post-decision wagering only affected the response times. These results were supported by an additional experiment that used a balanced chunk strength design. We conclude that a decision-strategy-attribution procedure may force participants to adopt an analytical decision-making strategy and rely mostly on conscious knowledge of artificial grammar. Copyright © 2017 Elsevier Inc. All rights reserved.

Spatial Integration under Contextual Control in a Virtual Environment

ERIC Educational Resources Information Center

Molet, Mikael; Gambet, Boris; Bugallo, Mehdi; Miller, Ralph R.

2012-01-01

The role of context was examined in the selection and integration of independently learned spatial relationships. Using a dynamic 3D virtual environment, participants learned one spatial relationship between landmarks A and B which was established in one virtual context (e.g., A is left of B) and a different spatial relationship which was…

Effects of a cognitive training on spatial learning and associated functional brain activations

PubMed Central

2013-01-01

Background Both cognitive and physical exercise have been discussed as promising interventions for healthy cognitive aging. The present study assessed the effects of cognitive training (spatial vs. perceptual training) and physical training (endurance training vs. non-endurance training) on spatial learning and associated brain activation in 33 adults (40–55 years). Spatial learning was assessed with a virtual maze task, and at the same time neural correlates were measured with functional magnetic resonance imaging (fMRI). Results Only the spatial training improved performance in the maze task. These behavioral gains were accompanied by a decrease in frontal and temporal lobe activity. At posttest, participants of the spatial training group showed lower activity than participants of the perceptual training group in a network of brain regions associated with spatial learning, including the hippocampus and parahippocampal gyrus. No significant differences were observed between the two physical intervention groups. Conclusions Functional changes in neural systems associated with spatial navigation can be induced by cognitive interventions and seem to be stronger than effects of physical exercise in middle-aged adults. PMID:23870447

Using Mobile Devices to Enhance the Interactive Learning for Spatial Geometry

ERIC Educational Resources Information Center

Chang, Kuo-En; Wu, Lin-Jung; Lai, Shing-Chuang; Sung, Yao-Ting

2016-01-01

The purpose of this research is to develop a hands-on spatial geometry learning system to facilitate the learning of geometry. The development of this system was based on Duval's four critical elements of geometric learning: perceptual apprehension, sequential apprehension, operative apprehension, and discursive apprehension. The system offers…

Weather to Make a Decision

ERIC Educational Resources Information Center

Hoyle, Julie E.; Mjelde, James W.; Litzenberg, Kerry K.

2006-01-01

DECIDE is a teacher-friendly, integrated approach designed to stimulate learning by allowing students to make decisions about situations they face in their lives while using scientific weather principles. This learning unit integrates weather science, decision theory, mathematics, statistics, geography, and reading in a context of decision…

Dissociation of emotional decision-making from cognitive decision-making in chronic schizophrenia.

PubMed

Lee, Yanghyun; Kim, Yang-Tae; Seo, Eugene; Park, Oaktae; Jeong, Sung-Hun; Kim, Sang Heon; Lee, Seung-Jae

2007-08-30

Recent studies have examined the decision-making ability of schizophrenic patients using the Iowa Gambling Task (IGT). These studies, however, were restricted to the assessment of emotional decision-making. Decision-making depends on cognitive functions as well as on emotion. The purpose of this study was to examine the performance of schizophrenic patients on the IGT and the Game of Dice Task (GDT), a decision-making task with explicit rules for gains and losses. In addition, it was intended to test whether poor performance on IGT is attributable to impairments in reversal learning within the schizophrenia group using the Simple Reversal Learning Task (SRLT), which is sensitive to measure the deficit of reversal learning following ventromedial prefrontal cortex damage. A group of 23 stable schizophrenic patients and 28 control subjects performed computerized versions of the IGT, GDT, SRLT and Wisconsin Card Sorting Test (WCST). While schizophrenic patients performed poorly on the IGT relative to normal controls, there was no significant difference between the two groups on GDT performance. The performance of the schizophrenia group on the SRLT was poorer than that of controls, but was not related to IGT performance. These data suggest that schizophrenic patients have impaired emotional decision-making but intact cognitive decision-making, suggesting that these two processes of decision-making are different. Furthermore, the impairments in reversal learning did not contribute to poor performance on the IGT in schizophrenia. Therefore, schizophrenic patients have difficulty in making decisions under ambiguous and uncertain situations whereas they make choices easily in clear and unequivocal ones. The emotional decision-making deficits in schizophrenia might be attributable more to another mechanism such as a somatic marker hypothesis than to an impairment in reversal learning.

Spatial affect learning restricted in major depression relative to anxiety disorders and healthy controls.

PubMed

Gollan, Jackie K; Norris, Catherine J; Hoxha, Denada; Irick, John Stockton; Hawkley, Louise C; Cacioppo, John T

2014-01-01

Detecting and learning the location of unpleasant or pleasant scenarios, or spatial affect learning, is an essential skill that safeguards well-being (Crawford & Cacioppo, 2002). Potentially altered by psychiatric illness, this skill has yet to be measured in adults with and without major depressive disorder (MDD) and anxiety disorders (AD). This study enrolled 199 adults diagnosed with MDD and AD (n=53), MDD (n=47), AD (n=54), and no disorders (n=45). Measures included clinical interviews, self-reports, and a validated spatial affect task using affective pictures (IAPS; Lang, Bradley, & Cuthbert, 2005). Participants with MDD showed impaired spatial affect learning of negative stimuli and irrelevant learning of pleasant pictures compared with non-depressed adults. Adults with MDD may use a "GOOD is UP" heuristic reflected by their impaired learning of the opposite correlation (i.e., "BAD is UP") and performance in the pleasant version of the task.

Conditional responding is impaired in chronic alcoholics.

PubMed

Hildebrandt, Helmut; Brokate, B; Hoffmann, E; Kröger, B; Eling, P

2006-07-01

Bechara (2003) describes a model for disturbances in executive functions related to addiction. This model involves deficits in decision-making and in suppressing pre-potent representations or response patterns. We tested this model in 29 individuals with long-term heavy alcohol dependency and compared their performance with that of 20 control subjects. Only individuals without memory impairment, with normal intelligence and normal visual response times were included. We examined word fluency, object alternation, spatial stimulus-response incompatibility, extra-dimensional shift learning and decision-making using the Gambling task. We subtracted the performance in a control condition from that of the executive condition, in order to focus specifically on the executive component of each task. Only the object alternation and incompatibility tasks revealed significant differences between the group of alcoholics and the control group. Moreover, response times in the object alternation task correlated with duration of alcohol dependency. The results do not argue in favor of a specific deficit in decision-making or in shifting between relevant representations. We conclude that long-term alcohol abuse leads to an impairment in conditional responding, provided the response depends on former reactions or the inhibition of pre-potent response patterns.

Understanding human visual systems and its impact on our intelligent instruments

NASA Astrophysics Data System (ADS)

Strojnik Scholl, Marija; Páez, Gonzalo; Scholl, Michelle K.

2013-09-01

We review the evolution of machine vision and comment on the cross-fertilization from the neural sciences onto flourishing fields of neural processing, parallel processing, and associative memory in optical sciences and computing. Then we examine how the intensive efforts in mapping the human brain have been influenced by concepts in computer sciences, control theory, and electronic circuits. We discuss two neural paths that employ the input from the vision sense to determine the navigational options and object recognition. They are ventral temporal pathway for object recognition (what?) and dorsal parietal pathway for navigation (where?), respectively. We describe the reflexive and conscious decision centers in cerebral cortex involved with visual attention and gaze control. Interestingly, these require return path though the midbrain for ocular muscle control. We find that the cognitive psychologists currently study human brain employing low-spatial-resolution fMRI with temporal response on the order of a second. In recent years, the life scientists have concentrated on insect brains to study neural processes. We discuss how reflexive and conscious gaze-control decisions are made in the frontal eye field and inferior parietal lobe, constituting the fronto-parietal attention network. We note that ethical and experiential learnings impact our conscious decisions.

Adapting environmental management to uncertain but inevitable change.

PubMed

Nicol, Sam; Fuller, Richard A; Iwamura, Takuya; Chadès, Iadine

2015-06-07

Implementation of adaptation actions to protect biodiversity is limited by uncertainty about the future. One reason for this is the fear of making the wrong decisions caused by the myriad future scenarios presented to decision-makers. We propose an adaptive management (AM) method for optimally managing a population under uncertain and changing habitat conditions. Our approach incorporates multiple future scenarios and continually learns the best management strategy from observations, even as conditions change. We demonstrate the performance of our AM approach by applying it to the spatial management of migratory shorebird habitats on the East Asian-Australasian flyway, predicted to be severely impacted by future sea-level rise. By accounting for non-stationary dynamics, our solution protects 25,000 more birds per year than the current best stationary approach. Our approach can be applied to many ecological systems that require efficient adaptation strategies for an uncertain future. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Spatial Thinking: Precept for Understanding Operational Environments

DTIC Science & Technology

2016-06-10

A Computer Movie Simulating Urban Growth in the Detroit Region,” 236. 29 U.S. National Research Council, Learning to Think Spatially: GIS as a... children and spatial language, the article focuses on the use of geospatial information systems (GIS) as a support mechanism for learning to think...Thinking, Cognition, Learning , Geospatial, Operating Environment, Space Perception 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18

A Decision-Tree-Oriented Guidance Mechanism for Conducting Nature Science Observation Activities in a Context-Aware Ubiquitous Learning

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Chu, Hui-Chun; Shih, Ju-Ling; Huang, Shu-Hsien; Tsai, Chin-Chung

2010-01-01

A context-aware ubiquitous learning environment is an authentic learning environment with personalized digital supports. While showing the potential of applying such a learning environment, researchers have also indicated the challenges of providing adaptive and dynamic support to individual students. In this paper, a decision-tree-oriented…

Age-Related Differences in Associative Learning of Landmarks and Heading Directions in a Virtual Navigation Task.

PubMed

Zhong, Jimmy Y; Moffat, Scott D

2016-01-01

Previous studies have showed that spatial memory declines with age but have not clarified the relevance of different landmark cues for specifying heading directions among different age groups. This study examined differences between younger, middle-aged and older adults in route learning and memory tasks after they navigated a virtual maze that contained: (a) critical landmarks that were located at decision points (i.e., intersections) and (b) non-critical landmarks that were located at non-decision points (i.e., the sides of the route). Participants were given a recognition memory test for critical and non-critical landmarks and also given a landmark-direction associative learning task. Compared to younger adults, older adults committed more navigation errors during route learning and were poorer at associating the correct heading directions with both critical and non-critical landmarks. Notably, older adults exhibited a landmark-direction associative memory deficit at decision points; this was the first finding to show that an associative memory deficit exist among older adults in a navigational context for landmarks that are pertinent for reaching a goal, and suggest that older adults may expend more cognitive resources on the encoding of landmark/object features than on the binding of landmark and directional information. This study is also the first to show that older adults did not have a tendency to process non-critical landmarks, which were regarded as distractors/irrelevant cues for specifying the directions to reach the goal, to an equivalent or larger extent than younger adults. We explain this finding in view of the low number of non-critical cues in our virtual maze (relative to a real-world urban environment) that might not have evoked older adults' usual tendency toward processing or encoding distractors. We explain the age differences in navigational and cognitive performance with regards to functional and structural changes in the hippocampus and parahippocampus, and recommend further investigations into the functional connectivity between the prefrontal cortex and hippocampus for a better understanding of the landmark-direction associative learning among the elderly. Finally, it is hoped that the current behavioral findings will facilitate efforts to identify the neural markers of Alzheimer's disease, a disease that commonly involves navigational deficits.

Spatial parameters at the basis of social transfer of learning.

PubMed

Lugli, Luisa; Iani, Cristina; Milanese, Nadia; Sebanz, Natalie; Rubichi, Sandro

2015-06-01

Recent research indicates that practicing on a joint spatial compatibility task with an incompatible stimulus-response mapping affects subsequent joint Simon task performance, eliminating the social Simon effect. It has been well established that in individual contexts, for transfer of learning to occur, participants need to practice an incompatible association between stimulus and response positions. The mechanisms underlying transfer of learning in joint task performance are, however, less well understood. The present study was aimed at assessing the relative contribution of 3 different spatial relations characterizing the joint practice context: stimulus-response, stimulus-participant, and participant-response relations. In 3 experiments, the authors manipulated the stimulus-response, stimulus-participant, and response-participant associations. We found that learning from the practice task did not transfer to the subsequent task when during practice stimulus-response associations were spatially incompatible and stimulus-participant associations were compatible (Experiment 1). However, a transfer of learning was evident when stimulus-participant associations were spatially incompatible. This occurred both when response-participant associations were incompatible (Experiment 2) and when they were compatible (Experiment 3). These results seem to support an agent corepresentation account of correspondence effects emerging in joint settings since they suggest that, in social contexts, critical to obtain transfer-of-learning effects is the spatial relation between stimulus and participant positions while the spatial relation between stimulus and response positions is irrelevant. (c) 2015 APA, all rights reserved).

Six Myths About Spatial Thinking

NASA Astrophysics Data System (ADS)

Newcombe, Nora S.; Stieff, Mike

2012-04-01

Visualizations are an increasingly important part of scientific education and discovery. However, users often do not gain knowledge from them in a complete or efficient way. This article aims to direct research on visualizations in science education in productive directions by reviewing the evidence for widespread assumptions that learning styles, sex differences, developmental stages, and spatial language determine the impact of visualizations on science learning. First, we examine the assumption that people differ in their verbal versus visual learning style. Due to the lack of rigorous evaluation, there is no current support for this distinction. Future research should distinguish between two different kinds of visual learning style. Second, we consider the belief that there are large and intractable sex differences in spatial ability resultant from immutable biological reasons. Although there are some spatial sex differences (in some types of spatial tests although not all), there is actually only very mixed support for biological causation. Most important, there is conclusive evidence that spatial skills can be improved through training and education. Third, we explore educators' use of Piaget's ideas about spatial development to draw conclusions about 'developmental appropriateness'. However, recent research on spatial development has focused on identifying sequences that begin with early starting points of skill, and spatial education is possible in some form at all ages. Fourth, although spatial language does not determine spatial thought, it does frame attention in a way that can have impact on learning and understanding. We examine the empirical support for each assumption and its relevance to future research on visualizations in science education.

Understanding How to Build Long-Lived Learning Collaborators

DTIC Science & Technology

2016-03-16

discrimination in learning, and dynamic encoding strategies to improve visual encoding for learning via analogical generalization. We showed that spatial concepts...a 20,000 sketch corpus to examine the tradeoffs involved in visual representation and analogical generalization. 15. SUBJECT TERMS...strategies to improve visual encoding for learning via analogical generalization. We showed that spatial concepts can be learned via analogical

Using a natural abilities battery for academic and career guidance: a ten-year study.

PubMed

Brown, Corrie C; Harvey, Stephen B; Stiles, Dori

2011-01-01

Over a period of 10 years, first-year students from 11 consecutive veterinary classes conducted a self-assessment using a natural abilities survey. The present study analyzes the data compiled from students' self-assessment results. As a group, veterinary students are exceptional problem solvers, either through inductive or deductive reasoning, and have strong spatial relations capacities. Veterinary students have a range of learning styles with design memory being the primary vehicle for information delivery and tonal memory being the least frequently used style overall. Information gained on each student's natural abilities can be used to guide effective career decision making and enhance prospects for long-term career satisfaction.

[The study of functional status in the perception of visual information depending on the method of technical color mixing on LCD and DLP projectors technology].

PubMed

Merkulova, A G; Osokina, E S; Bukhtiiarov, I V

2014-10-01

The case of compare two ways of projection color visual images, characterized by different spatial-temporal characteristics of visual stimuli, presents the methodology and the set of techniques. Received comparative data, identifying risks of regulation disorder of the functional state and development general, mental and visual fatigue during prolonged strenuous visual activity, according to two types of test tasks, which are the most typical for the use of modern projectors to work with the audience, both inthe process of implementation of learning technologies and the collective take responsible decisions by expert groups that control of complex technological processes.

Neurocognition in College-Aged Daily Marijuana Users

PubMed Central

Becker, Mary P.; Collins, Paul F.; Luciana, Monica

2014-01-01

Background Marijuana is the most commonly used illicit substance in the United States. Use, particularly when it occurs early, has been associated with cognitive impairments in executive functioning, learning, and memory. Methods This study comprehensively measured cognitive ability as well as comorbid psychopathology and substance use history to determine the neurocognitive profile associated with young adult marijuana use. College-aged marijuana users who initiated use prior to age 17 (n=35) were compared to demographically-matched controls (n=35). Results Marijuana users were high functioning, demonstrating comparable IQs to controls and relatively better processing speed. Marijuana users demonstrated relative cognitive impairments in verbal memory, spatial working memory, spatial planning, and motivated decision-making. Comorbid use of alcohol, which was heavier in marijuana users, was unexpectedly found to be associated with better performance in some of these areas. Conclusions This study provides additional evidence of neurocognitive impairment in the context of adolescent and young adult marijuana use. Findings are discussed in relation to marijuana’s effects on intrinsic motivation and discrete aspects of cognition. PMID:24620756

Cautious strategy update promotes cooperation in spatial prisoner’s dilemma game

NASA Astrophysics Data System (ADS)

Liu, Yongkui; Zhang, Lin; Chen, Xiaojie; Ren, Lei; Wang, Long

2013-09-01

In the realistic world, individual cautiousness can be often involved or observed when a rational individual makes a decision. However, it remains unclear how such individual cautiousness influences the evolution of cooperative behavior. To this end, we consider a Fermi strategy updating rule, where each individual is assigned a cautiousness index that controls its learning activity, and then study the evolution of cooperation in the spatial prisoner’s dilemma game. Interestingly, it is found that cooperation can be significantly promoted when individuals’ cautiousness is considered. In particular, there exists an optimal range of the degree of cautiousness resulting in the highest cooperation level. The remarkable promotion of cooperation, as well as the emerging phase transition is explained by configurational analysis. The sensitivity of cooperation to initial states with different fractions of cooperators is also discussed. The result illustrates that high densities of cooperators can be established at small initial fractions of cooperators. The detailed mechanism for such phenomenon is explained by analyzing the typical initial configurations.

View-invariant object category learning, recognition, and search: how spatial and object attention are coordinated using surface-based attentional shrouds.

PubMed

Fazl, Arash; Grossberg, Stephen; Mingolla, Ennio

2009-02-01

How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified mechanistic explanation of how spatial and object attention work together to search a scene and learn what is in it. The ARTSCAN model predicts how an object's surface representation generates a form-fitting distribution of spatial attention, or "attentional shroud". All surface representations dynamically compete for spatial attention to form a shroud. The winning shroud persists during active scanning of the object. The shroud maintains sustained activity of an emerging view-invariant category representation while multiple view-specific category representations are learned and are linked through associative learning to the view-invariant object category. The shroud also helps to restrict scanning eye movements to salient features on the attended object. Object attention plays a role in controlling and stabilizing the learning of view-specific object categories. Spatial attention hereby coordinates the deployment of object attention during object category learning. Shroud collapse releases a reset signal that inhibits the active view-invariant category in the What cortical processing stream. Then a new shroud, corresponding to a different object, forms in the Where cortical processing stream, and search using attention shifts and eye movements continues to learn new objects throughout a scene. The model mechanistically clarifies basic properties of attention shifts (engage, move, disengage) and inhibition of return. It simulates human reaction time data about object-based spatial attention shifts, and learns with 98.1% accuracy and a compression of 430 on a letter database whose letters vary in size, position, and orientation. The model provides a powerful framework for unifying many data about spatial and object attention, and their interactions during perception, cognition, and action.

Work-Based Learning: A Practical Approach for Learning to Work and Working to Learn. A Case Study on Decision-Makers' Professional Development in Iran

ERIC Educational Resources Information Center

Arani, Mohammad Reza Sarkar; Alagamandan, Jafar; Tourani, Heidar

2004-01-01

The work-based learning model of human resource development has captured a great deal of attention and has gained increasing importance in higher education in recent years. Work-based learning is a powerful phenomenon that attempts to help policy-makers, managers and curriculum developers improve the quality of the decision and organizational…

Multiple kernel learning using single stage function approximation for binary classification problems

NASA Astrophysics Data System (ADS)

Shiju, S.; Sumitra, S.

2017-12-01

In this paper, the multiple kernel learning (MKL) is formulated as a supervised classification problem. We dealt with binary classification data and hence the data modelling problem involves the computation of two decision boundaries of which one related with that of kernel learning and the other with that of input data. In our approach, they are found with the aid of a single cost function by constructing a global reproducing kernel Hilbert space (RKHS) as the direct sum of the RKHSs corresponding to the decision boundaries of kernel learning and input data and searching that function from the global RKHS, which can be represented as the direct sum of the decision boundaries under consideration. In our experimental analysis, the proposed model had shown superior performance in comparison with that of existing two stage function approximation formulation of MKL, where the decision functions of kernel learning and input data are found separately using two different cost functions. This is due to the fact that single stage representation helps the knowledge transfer between the computation procedures for finding the decision boundaries of kernel learning and input data, which inturn boosts the generalisation capacity of the model.

Decision Making Impairment: A Shared Vulnerability in Obesity, Gambling Disorder and Substance Use Disorders?

PubMed Central

Mallorquí-Bagué, Nuria; Fagundo, Ana B.; Jimenez-Murcia, Susana; de la Torre, Rafael; Baños, Rosa M.; Botella, Cristina; Casanueva, Felipe F.; Crujeiras, Ana B.; Fernández-García, Jose C.; Fernández-Real, Jose M.; Frühbeck, Gema; Granero, Roser; Rodríguez, Amaia; Tolosa-Sola, Iris; Ortega, Francisco J.; Tinahones, Francisco J.; Alvarez-Moya, Eva; Ochoa, Cristian; Menchón, Jose M.

2016-01-01

Introduction Addictions are associated with decision making impairments. The present study explores decision making in Substance use disorder (SUD), Gambling disorder (GD) and Obesity (OB) when assessed by Iowa Gambling Task (IGT) and compares them with healthy controls (HC). Methods For the aims of this study, 591 participants (194 HC, 178 GD, 113 OB, 106 SUD) were assessed according to DSM criteria, completed a sociodemographic interview and conducted the IGT. Results SUD, GD and OB present impaired decision making when compared to the HC in the overall task and task learning, however no differences are found for the overall performance in the IGT among the clinical groups. Results also reveal some specific learning across the task patterns within the clinical groups: OB maintains negative scores until the third set where learning starts but with a less extend to HC, SUD presents an early learning followed by a progressive although slow improvement and GD presents more random choices with no learning. Conclusions Decision making impairments are present in the studied clinical samples and they display individual differences in the task learning. Results can help understanding the underlying mechanisms of OB and addiction behaviors as well as improve current clinical treatments. PMID:27690367

Teachers' Spatial Anxiety Relates to 1st-and 2nd-Graders' Spatial Learning

ERIC Educational Resources Information Center

Gunderson, Elizabeth A.; Ramirez, Gerardo; Beilock, Sian L.; Levine, Susan C.

2013-01-01

Teachers' anxiety about an academic domain, such as math, can impact students' learning in that domain. We asked whether this relation held in the domain of spatial skill, given the importance of spatial skill for success in math and science and its malleability at a young age. We measured 1st-and 2nd-grade teachers' spatial anxiety…

Three dimensions of learning: experiential activity for engineering innovation education and research

NASA Astrophysics Data System (ADS)

Killen, Catherine P.

2015-09-01

This paper outlines a novel approach to engineering education research that provides three dimensions of learning through an experiential class activity. A simulated decision activity brought current research into the classroom, explored the effect of experiential activity on learning outcomes and contributed to the research on innovation decision making. The 'decision task' was undertaken by more than 480 engineering students. It increased their reported measures of learning and retention by an average of 0.66 on a five-point Likert scale, and revealed positive correlations between attention, enjoyment, ongoing interest and learning and retention. The study also contributed to innovation management research by revealing the influence of different data visualisation methods on decision quality, providing an example of research-integrated education that forms part of the research process. Such a dovetailing of different research studies demonstrates how engineering educators can enhance educational impact while multiplying the outcomes from their research efforts.

Active Learning Environments with Robotic Tangibles: Children's Physical and Virtual Spatial Programming Experiences

ERIC Educational Resources Information Center

Burleson, Winslow S.; Harlow, Danielle B.; Nilsen, Katherine J.; Perlin, Ken; Freed, Natalie; Jensen, Camilla Nørgaard; Lahey, Byron; Lu, Patrick; Muldner, Kasia

2018-01-01

As computational thinking becomes increasingly important for children to learn, we must develop interfaces that leverage the ways that young children learn to provide opportunities for them to develop these skills. Active Learning Environments with Robotic Tangibles (ALERT) and Robopad, an analogous on-screen virtual spatial programming…

The Role of Cognitive Abilities in Laparoscopic Simulator Training

ERIC Educational Resources Information Center

Groenier, M.; Schraagen, J. M. C.; Miedema, H. A. T.; Broeders, I. A. J. M.

2014-01-01

Learning minimally invasive surgery (MIS) differs substantially from learning open surgery and trainees differ in their ability to learn MIS. Previous studies mainly focused on the role of visuo-spatial ability (VSA) on the learning curve for MIS. In the current study, the relationship between spatial memory, perceptual speed, and general…

A constructivist approach to studying the bullwhip effect by simulating the supply chain

NASA Astrophysics Data System (ADS)

González-Torre, Pilar L.; Adenso-Díaz, B.; Moreno, Plácido

2015-11-01

The Cider Game is a simulator for a supply chain-related learning environment. Its main feature is that it provides support to students in the constructivist discovery process when learning how to make logistics decisions, at the same time as noting the occurrence of the bullwhip phenomenon. This learning environment seeks a balance between direct instruction in the learning process on the part of the tutor, and a suitable and sufficient degree of freedom to regulate independent learning on the part of students. This article describes the basic learning mechanisms using the Cider Game and the graphical learning environments that it provides. We describe the functionality provided by this application, and analyse the effect over the rational understanding of the bullwhip phenomenon by the students and whether they are able to make decisions to minimise its impact, studying the differences when that decision-making learning is done individually or in groups.

Anatomy of a Decision: Striato-Orbitofrontal Interactions in Reinforcement Learning, Decision Making, and Reversal

ERIC Educational Resources Information Center

Frank, Michael J.; Claus, Eric D.

2006-01-01

The authors explore the division of labor between the basal ganglia-dopamine (BG-DA) system and the orbitofrontal cortex (OFC) in decision making. They show that a primitive neural network model of the BG-DA system slowly learns to make decisions on the basis of the relative probability of rewards but is not as sensitive to (a) recency or (b) the…

Functional Equivalence of Spatial Images from Touch and Vision: Evidence from Spatial Updating in Blind and Sighted Individuals

PubMed Central

Giudice, Nicholas A.; Betty, Maryann R.; Loomis, Jack M.

2012-01-01

This research examines whether visual and haptic map learning yield functionally equivalent spatial images in working memory, as evidenced by similar encoding bias and updating performance. In three experiments, participants learned four-point routes either by seeing or feeling the maps. At test, blindfolded participants made spatial judgments about the maps from imagined perspectives that were either aligned or misaligned with the maps as represented in working memory. Results from Experiments 1 and 2 revealed a highly similar pattern of latencies and errors between visual and haptic conditions. These findings extend the well known alignment biases for visual map learning to haptic map learning, provide further evidence of haptic updating, and most importantly, show that learning from the two modalities yields very similar performance across all conditions. Experiment 3 found the same encoding biases and updating performance with blind individuals, demonstrating that functional equivalence cannot be due to visual recoding and is consistent with an amodal hypothesis of spatial images. PMID:21299331

Contextual cueing: implicit learning and memory of visual context guides spatial attention.

PubMed

Chun, M M; Jiang, Y

1998-06-01

Global context plays an important, but poorly understood, role in visual tasks. This study demonstrates that a robust memory for visual context exists to guide spatial attention. Global context was operationalized as the spatial layout of objects in visual search displays. Half of the configurations were repeated across blocks throughout the entire session, and targets appeared within consistent locations in these arrays. Targets appearing in learned configurations were detected more quickly. This newly discovered form of search facilitation is termed contextual cueing. Contextual cueing is driven by incidentally learned associations between spatial configurations (context) and target locations. This benefit was obtained despite chance performance for recognizing the configurations, suggesting that the memory for context was implicit. The results show how implicit learning and memory of visual context can guide spatial attention towards task-relevant aspects of a scene.

Distance-Based and Distributed Learning: A Decision Tool for Education Leaders.

ERIC Educational Resources Information Center

McGraw, Tammy M.; Ross, John D.

This decision tool presents a progression of data collection and decision-making strategies that can increase the effectiveness of distance-based or distributed learning instruction. A narrative and flow chart cover the following steps: (1) basic assumptions, including purpose of instruction, market scan, and financial resources; (2) needs…

Myopic Regret Avoidance: Feedback Avoidance and Learning in Repeated Decision Making

ERIC Educational Resources Information Center

Reb, Jochen; Connolly, Terry

2009-01-01

Decision makers can become trapped by "myopic regret avoidance" in which rejecting feedback to avoid short-term "outcome regret" (regret associated with counterfactual outcome comparisons) leads to reduced learning and greater long-term regret over continuing poor decisions. In a series of laboratory experiments involving repeated choices among…

Hyperammonemia induces glial activation, neuroinflammation and alters neurotransmitter receptors in hippocampus, impairing spatial learning: reversal by sulforaphane.

PubMed

Hernández-Rabaza, Vicente; Cabrera-Pastor, Andrea; Taoro-González, Lucas; Malaguarnera, Michele; Agustí, Ana; Llansola, Marta; Felipo, Vicente

2016-02-16

Patients with liver cirrhosis and minimal hepatic encephalopathy (MHE) show mild cognitive impairment and spatial learning dysfunction. Hyperammonemia acts synergistically with inflammation to induce cognitive impairment in MHE. Hyperammonemia-induced neuroinflammation in hippocampus could contribute to spatial learning impairment in MHE. Two main aims of this work were: (1) to assess whether chronic hyperammonemia increases inflammatory factors in the hippocampus and if this is associated with microglia and/or astrocytes activation and (2) to assess whether hyperammonemia-induced neuroinflammation in the hippocampus is associated with altered membrane expression of glutamate and GABA receptors and spatial learning impairment. There are no specific treatments for cognitive alterations in patients with MHE. A third aim was to assess whether treatment with sulforaphane enhances endogenous the anti-inflammatory system, reduces neuroinflammation in the hippocampus of hyperammonemic rats, and restores spatial learning and if normalization of receptor membrane expression is associated with learning improvement. We analyzed the following in control and hyperammonemic rats, treated or not with sulforaphane: (1) microglia and astrocytes activation by immunohistochemistry, (2) markers of pro-inflammatory (M1) (IL-1β, IL-6) and anti-inflammatory (M2) microglia (Arg1, YM-1) by Western blot, (3) membrane expression of GABA, AMPA, and NMDA receptors using the BS3 cross-linker, and (4) spatial learning using the radial maze. The results reported show that hyperammonemia induces astrocytes and microglia activation in the hippocampus, increasing pro-inflammatory cytokines IL-1β and IL-6. This is associated with altered membrane expression of AMPA, NMDA, and GABA receptors which would be responsible for altered neurotransmission and impairment of spatial learning in the radial maze. Treatment with sulforaphane promotes microglia differentiation from pro-inflammatory M1 to anti-inflammatory M2 phenotype and reduces activation of astrocytes in hyperammonemic rats. This reduces neuroinflammation, normalizes membrane expression of glutamate and GABA receptors, and restores spatial learning in hyperammonemic rats. Hyperammonemia-induced neuroinflammation impairs glutamatergic and GABAergic neurotransmission by altering membrane expression of glutamate and GABA receptors, resulting in impaired spatial learning. Sulforaphane reverses all these effects. Treatment with sulforaphane could be useful to improve cognitive function in cirrhotic patients with minimal or clinical hepatic encephalopathy.

Spatial and Reversal Learning in the Morris Water Maze Are Largely Resistant to Six Hours of REM Sleep Deprivation Following Training

ERIC Educational Resources Information Center

Walsh, Christine M.; Booth, Victoria; Poe, Gina R.

2011-01-01

This first test of the role of REM (rapid eye movement) sleep in reversal spatial learning is also the first attempt to replicate a much cited pair of papers reporting that REM sleep deprivation impairs the consolidation of initial spatial learning in the Morris water maze. We hypothesized that REM sleep deprivation following training would impair…

Hysteresis as an Implicit Prior in Tactile Spatial Decision Making

PubMed Central

Thiel, Sabrina D.; Bitzer, Sebastian; Nierhaus, Till; Kalberlah, Christian; Preusser, Sven; Neumann, Jane; Nikulin, Vadim V.; van der Meer, Elke; Villringer, Arno; Pleger, Burkhard

2014-01-01

Perceptual decisions not only depend on the incoming information from sensory systems but constitute a combination of current sensory evidence and internally accumulated information from past encounters. Although recent evidence emphasizes the fundamental role of prior knowledge for perceptual decision making, only few studies have quantified the relevance of such priors on perceptual decisions and examined their interplay with other decision-relevant factors, such as the stimulus properties. In the present study we asked whether hysteresis, describing the stability of a percept despite a change in stimulus property and known to occur at perceptual thresholds, also acts as a form of an implicit prior in tactile spatial decision making, supporting the stability of a decision across successively presented random stimuli (i.e., decision hysteresis). We applied a variant of the classical 2-point discrimination task and found that hysteresis influenced perceptual decision making: Participants were more likely to decide ‘same’ rather than ‘different’ on successively presented pin distances. In a direct comparison between the influence of applied pin distances (explicit stimulus property) and hysteresis, we found that on average, stimulus property explained significantly more variance of participants’ decisions than hysteresis. However, when focusing on pin distances at threshold, we found a trend for hysteresis to explain more variance. Furthermore, the less variance was explained by the pin distance on a given decision, the more variance was explained by hysteresis, and vice versa. Our findings suggest that hysteresis acts as an implicit prior in tactile spatial decision making that becomes increasingly important when explicit stimulus properties provide decreasing evidence. PMID:24587045

The ampakine, Org 26576, bolsters early spatial reference learning and retrieval in the Morris water maze: a subchronic, dose-ranging study in rats.

PubMed

Hamlyn, Eugene; Brand, Linda; Shahid, Mohammed; Harvey, Brian H

2009-10-01

Ampakines have shown beneficial effects on cognition in selected animal models of learning. However, their ability to modify long-term spatial memory tasks has not been studied yet. This would lend credence to their possible value in treating disorders of cognition. We evaluated the actions of subchronic Org 26576 administration on spatial reference memory performance in the 5-day Morris water maze task in male Sprague-Dawley rats, at doses of 1, 3 and 10 mg/kg twice daily through intraperitoneal injection over 12 days. Org 26576 exerted a dose and time-dependent effect on spatial learning, with dosages of 3 and 10 mg/kg significantly enhancing acquisition on day 1. Globally, escape latency decreased significantly as the training days progressed in the saline and Org 26576-treated groups, indicating that significant and equal learning had taken place over the learning period. However, at the end of the learning period, all doses of Org 26576 significantly improved spatial memory storage/retrieval without confounding effects in the cued version of the task. Org 26576 offers early phase spatial memory benefits in rats, but particularly enhances search accuracy during reference memory retrieval. These results support its possible utility in treating disorders characterized by deficits in cognitive performance.

Design and Development Computer-Based E-Learning Teaching Material for Improving Mathematical Understanding Ability and Spatial Sense of Junior High School Students

NASA Astrophysics Data System (ADS)

Nurjanah; Dahlan, J. A.; Wibisono, Y.

2017-02-01

This paper aims to make a design and development computer-based e-learning teaching material for improving mathematical understanding ability and spatial sense of junior high school students. Furthermore, the particular aims are (1) getting teaching material design, evaluation model, and intrument to measure mathematical understanding ability and spatial sense of junior high school students; (2) conducting trials computer-based e-learning teaching material model, asessment, and instrument to develop mathematical understanding ability and spatial sense of junior high school students; (3) completing teaching material models of computer-based e-learning, assessment, and develop mathematical understanding ability and spatial sense of junior high school students; (4) resulting research product is teaching materials of computer-based e-learning. Furthermore, the product is an interactive learning disc. The research method is used of this study is developmental research which is conducted by thought experiment and instruction experiment. The result showed that teaching materials could be used very well. This is based on the validation of computer-based e-learning teaching materials, which is validated by 5 multimedia experts. The judgement result of face and content validity of 5 validator shows that the same judgement result to the face and content validity of each item test of mathematical understanding ability and spatial sense. The reliability test of mathematical understanding ability and spatial sense are 0,929 and 0,939. This reliability test is very high. While the validity of both tests have a high and very high criteria.

Interpretable Decision Sets: A Joint Framework for Description and Prediction

PubMed Central

Lakkaraju, Himabindu; Bach, Stephen H.; Jure, Leskovec

2016-01-01

One of the most important obstacles to deploying predictive models is the fact that humans do not understand and trust them. Knowing which variables are important in a model’s prediction and how they are combined can be very powerful in helping people understand and trust automatic decision making systems. Here we propose interpretable decision sets, a framework for building predictive models that are highly accurate, yet also highly interpretable. Decision sets are sets of independent if-then rules. Because each rule can be applied independently, decision sets are simple, concise, and easily interpretable. We formalize decision set learning through an objective function that simultaneously optimizes accuracy and interpretability of the rules. In particular, our approach learns short, accurate, and non-overlapping rules that cover the whole feature space and pay attention to small but important classes. Moreover, we prove that our objective is a non-monotone submodular function, which we efficiently optimize to find a near-optimal set of rules. Experiments show that interpretable decision sets are as accurate at classification as state-of-the-art machine learning techniques. They are also three times smaller on average than rule-based models learned by other methods. Finally, results of a user study show that people are able to answer multiple-choice questions about the decision boundaries of interpretable decision sets and write descriptions of classes based on them faster and more accurately than with other rule-based models that were designed for interpretability. Overall, our framework provides a new approach to interpretable machine learning that balances accuracy, interpretability, and computational efficiency. PMID:27853627

Learning Theory Expertise in the Design of Learning Spaces: Who Needs a Seat at the Table?

ERIC Educational Resources Information Center

Rook, Michael M.; Choi, Koun; McDonald, Scott P.

2015-01-01

This study highlights the impact of including stakeholders with expertise in learning theory in a learning space design process. We present the decision-making process during the design of the Krause Innovation Studio on the campus of the Pennsylvania State University to draw a distinction between the architect and faculty member's decision-making…

Examining Civil Servants' Decisions to Use Web 2.0 Tools for Learning, Based on the Decomposed Theory of Planned Behavior

ERIC Educational Resources Information Center

Lai, Horng-Ji

2017-01-01

The purpose of this study was to investigate the decisions of civil servants to use Web 2.0 applications while engaging in online learning. The participants were 439 civil servants enrolled in asynchronous online learning programs, using an e-learning portal provided by Taiwan's Regional Civil Service Development Institute. The participants…

Q-learning residual analysis: application to the effectiveness of sequences of antipsychotic medications for patients with schizophrenia.

PubMed

Ertefaie, Ashkan; Shortreed, Susan; Chakraborty, Bibhas

2016-06-15

Q-learning is a regression-based approach that uses longitudinal data to construct dynamic treatment regimes, which are sequences of decision rules that use patient information to inform future treatment decisions. An optimal dynamic treatment regime is composed of a sequence of decision rules that indicate how to optimally individualize treatment using the patients' baseline and time-varying characteristics to optimize the final outcome. Constructing optimal dynamic regimes using Q-learning depends heavily on the assumption that regression models at each decision point are correctly specified; yet model checking in the context of Q-learning has been largely overlooked in the current literature. In this article, we show that residual plots obtained from standard Q-learning models may fail to adequately check the quality of the model fit. We present a modified Q-learning procedure that accommodates residual analyses using standard tools. We present simulation studies showing the advantage of the proposed modification over standard Q-learning. We illustrate this new Q-learning approach using data collected from a sequential multiple assignment randomized trial of patients with schizophrenia. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Caloric restriction and spatial learning in old mice.

PubMed

Bellush, L L; Wright, A M; Walker, J P; Kopchick, J; Colvin, R A

1996-08-01

Spatial learning in old mice (19 or 24 months old), some of which had been calorically restricted beginning at 14 weeks of age, was compared to that of young mice, in two separate experiments using a Morris water maze. In the first experiment, only old mice reaching criterion performance on a cued learning task were tested in a subsequent spatial task. Thus, all old mice tested for spatial learning had achieved escape latencies equivalent to those of young controls. Despite equivalent swimming speeds, only about half the old mice in each diet group achieved criterion performance in the spatial task. In the second experiment, old and young mice all received the same number of training trials in a cued task and then in a spatial task. Immediately following spatial training, they were given a 60-s probe trial, with no platform in the pool. Both groups of old mice spent significantly less time in the quadrant where the platform had been and made significantly fewer direct crosses over the previous platform location than did the young control group. As in Experiment 1, calorie restriction failed to provide protection against aging-related deficits. However, in both experiments, some individual old mice evidenced performance in spatial learning indistinguishable from that of young controls. Separate comparisons of "age-impaired" and "age-unimpaired" old mice with young controls may facilitate the identification of neurobiological mechanisms underlying age-related cognitive decline.

Altering spatial priority maps via reward-based learning.

PubMed

Chelazzi, Leonardo; Eštočinová, Jana; Calletti, Riccardo; Lo Gerfo, Emanuele; Sani, Ilaria; Della Libera, Chiara; Santandrea, Elisa

2014-06-18

Spatial priority maps are real-time representations of the behavioral salience of locations in the visual field, resulting from the combined influence of stimulus driven activity and top-down signals related to the current goals of the individual. They arbitrate which of a number of (potential) targets in the visual scene will win the competition for attentional resources. As a result, deployment of visual attention to a specific spatial location is determined by the current peak of activation (corresponding to the highest behavioral salience) across the map. Here we report a behavioral study performed on healthy human volunteers, where we demonstrate that spatial priority maps can be shaped via reward-based learning, reflecting long-lasting alterations (biases) in the behavioral salience of specific spatial locations. These biases exert an especially strong influence on performance under conditions where multiple potential targets compete for selection, conferring competitive advantage to targets presented in spatial locations associated with greater reward during learning relative to targets presented in locations associated with lesser reward. Such acquired biases of spatial attention are persistent, are nonstrategic in nature, and generalize across stimuli and task contexts. These results suggest that reward-based attentional learning can induce plastic changes in spatial priority maps, endowing these representations with the "intelligent" capacity to learn from experience. Copyright © 2014 the authors 0270-6474/14/348594-11$15.00/0.

Information and communication technologies in tomorrow's digital classroom

NASA Astrophysics Data System (ADS)

Bogoeva, Asya

2014-05-01

Education has to respond to the new challenges and opportunities offered by the 21-th Century as well as to the main trend in the world community development related to a creation of Knowledge Society. Implementation of ICT at school is a priority of the Global education and helps to develop the four pillars of learning - learning to know, learning to do, learning to be and learning to live together. Digital competence of the students is also a part of the European Union key competences. The essential elements in geographical study are: spatial analysis, with an emphasis on location; ecological analysis, with an emphasis on people-environment relationships; and regional analysis, with an emphasis on areal differentiation. Modern geography is best characterized as the study of distributions and relationships among different natural and social patterns of distributions. Viewing the world from a spatial perspective and employing a holistic approach are important characteristics of contemporary and future Geography learning. Using innovative methods for presenting the global aspects of distribution patterns and their changes is a priority of teaching geosciences at our school. The use of geo-media in classroom helps learners develop their ICT competences. Geolocalised information is used everywhere in society and it is therefore essential for students to learn how to use different forms of geographic media Geo-media is now being used in scientific researches and reasoning. One of the geo-media tools that I use in my classes is Google Earth for presenting different geographic processes and phenomena like visualization of current global weather conditions, global warming, deforestation areas, earthquake areas, etc. Using Geographic Information systems for presenting and studying geographical processes is also one way to identify, analyze, and understand the locations. Our school is a part of digital-earth.eu network which is under development now. The European Centers of Excellence at national level promote innovative approaches of teaching and learning environments including the active use of geo-media and GIS is started to develop. The main objectives of the Bulgarian Center of Excellence are to create in collaboration with teachers and ESRI organization learning materials for school education. Students learn how to use ArcGIS in order to create their own interactive maps related to the Bulgarian geography education. They have already used ArcGIS software to study and analyze changes in the Bulgarian geographical location, boundaries and border controls, as well as Pan European transport corridors and define positive and negative aspects of crossroad location of Bulgaria. There is also available software about the Bulgarian water resources as well as about the Bulgarian population and its demographic characteristics. During the classes students create their own map according to given tasks, analyze maps elicit certain information for decision making and in that way they develop their spatial thinking skills. Interdisciplinary approach in teaching geosciences at comprehensive school by using ICT is another innovative method that can be used in the classroom. Chemistry and geography as geosciences have common objects of investigation - minerals, rocks and ores as raw materials for industry. Subject objectives for both disciplines can be achieved in a binary lesson. Students make their own preliminary web-based investigation and in the classroom they discuss characteristics of a certain metallic ores, their global distribution and local deposits, their significance for economic development and environmental issues related to their extraction. Implementation of ICT in tomorrow's digital classroom will help students to understand the complexity of the world around us, show them different examples of our changing planet and develop their spatial thinking knowledge.

Post-traumatic stress symptoms are associated with better performance on a delayed match-to-position task

PubMed Central

2018-01-01

Many individuals with posttraumatic stress disorder (PTSD) report experiencing frequent intrusive memories of the original traumatic event (e.g., flashbacks). These memories can be triggered by situations or stimuli that reflect aspects of the trauma and may reflect basic processes in learning and memory, such as generalization. It is possible that, through increased generalization, non-threatening stimuli that once evoked normal memories become associated with traumatic memories. Previous research has reported increased generalization in PTSD, but the role of visual discrimination processes has not been examined. To investigate visual discrimination in PTSD, 143 participants (Veterans and civilians) self-assessed for symptom severity were grouped according to the presence of severe PTSD symptoms (PTSS) vs. few/no symptoms (noPTSS). Participants were given a visual match-to-sample pattern separation task that varied trials by spatial separation (Low, Medium, High) and temporal delays (5, 10, 20, 30 s). Unexpectedly, the PTSS group demonstrated better discrimination performance than the noPTSS group at the most difficult spatial trials (Low spatial separation). Further assessment of accuracy and reaction time using diffusion drift modeling indicated that the better performance by the PTSS group on the hardest trials was not explained by slower reaction times, but rather a faster accumulation of evidence during decision making in conjunction with a reduced threshold, indicating a tendency in the PTSS group to decide quickly rather than waiting for additional evidence to support the decision. This result supports the need for future studies examining the precise role of discrimination and generalization in PTSD, and how these cognitive processes might contribute to expression and maintenance of PTSD symptoms. PMID:29736339

Spatial decision support system to evaluate crop residue energy potential by anaerobic digestion.

PubMed

Escalante, Humberto; Castro, Liliana; Gauthier-Maradei, Paola; Rodríguez De La Vega, Reynel

2016-11-01

Implementing anaerobic digestion (AD) in energy production from crop residues requires development of decision tools to assess its feasibility and sustainability. A spatial decision support system (SDSS) was constructed to assist decision makers to select appropriate feedstock according to biomethanation potential, identify the most suitable location for biogas facilities, determine optimum plant capacity and supply chain, and evaluate associated risks and costs. SDSS involves a spatially explicit analysis, fuzzy multi-criteria analysis, and statistical and optimization models. The tool was validated on seven crop residues located in Santander, Colombia. For example, fique bagasse generates about 0.21millionm(3)CH4year(-1) (0.329m(3)CH4kg(-1) volatile solids) with a minimum profitable plant of about 2000tonyear(-1) and an internal rate of return of 10.5%. SDSS can be applied to evaluate other biomass resources, availability periods, and co-digestion potential. Copyright © 2016. Published by Elsevier Ltd.

Theoretical Approaches in the Context of Spatial Planning Decisions and the Relation with Urban Sustainability

NASA Astrophysics Data System (ADS)

Kumlu, Kadriye Burcu Yavuz; Tüdeş, Şule

2017-10-01

The sustainability agenda has maintained its importance since the days, when the production system took its capitalist form, as well as the population in the urban areas started to rise. Increasing number of both goods and the people have caused the degradation of the certain systems, which generate the urban areas. These systems could mainly be classified as social, environmental, physical and economical systems. Today, urban areas still have difficulty to protect those systems, due to the significant demand of the population. Therefore, studies related with the sustainable issues are significant in the sense of continuity of the urban systems. Therefore, in this paper, those studies in the context of the effects of physical decisions taken in the spatial planning process on urban sustainability, will be examined. The components of the physical decisions are limited to land use, density and design. Land use decisions will be examined in the context of mixed land use. On the other hand, decisions related with density will be analyzed in the sense of population density and floor area ratio (FAR). Besides, design decisions will be examined, by linking them with neighborhood design criteria. Additionally, the term of urban sustainability will only be limited to its social and environmental contexts in this study. Briefly stated, studies in the sustainable literature concerned with the effects of land use, density and design decisions taken in the spatial planning process on the social and environmental sustainability will be examined in this paper. After the compilation and the analyze of those studies, a theoretical approach will be proposed to determine social and environmental sustainability in the context of land use, density and design decisions, taken in the spatial planning process.

A Successful Implementation Strategy to Support Adoption of Decision Making in Mental Health Services.

PubMed

MacDonald-Wilson, Kim L; Hutchison, Shari L; Karpov, Irina; Wittman, Paul; Deegan, Patricia E

2017-04-01

Individual involvement in treatment decisions with providers, often through the use of decision support aids, improves quality of care. This study investigates an implementation strategy to bring decision support to community mental health centers (CMHC). Fifty-two CMHCs implemented a decision support toolkit supported by a 12-month learning collaborative using the Breakthrough Series model. Participation in learning collaborative activities was high, indicating feasibility of the implementation model. Progress by staff in meeting process aims around utilization of components of the toolkit improved significantly over time (p < .0001). Survey responses by individuals in service corroborate successful implementation. Community-based providers were able to successfully implement decision support in mental health services as evidenced by improved process outcomes and sustained practices over 1 year through the structure of the learning collaborative model.

A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations

USGS Publications Warehouse

Nicol, Sam; Wiederholt, Ruscena; Diffendorfer, James E.; Mattsson, Brady; Thogmartin, Wayne E.; Semmens, Darius J.; Laura Lopez-Hoffman,; Norris, Ryan

2016-01-01

Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources.

GIS-based spatial decision support system for grain logistics management

NASA Astrophysics Data System (ADS)

Zhen, Tong; Ge, Hongyi; Jiang, Yuying; Che, Yi

2010-07-01

Grain logistics is the important component of the social logistics, which can be attributed to frequent circulation and the great quantity. At present time, there is no modern grain logistics distribution management system, and the logistics cost is the high. Geographic Information Systems (GIS) have been widely used for spatial data manipulation and model operations and provide effective decision support through its spatial database management capabilities and cartographic visualization. In the present paper, a spatial decision support system (SDSS) is proposed to support policy makers and to reduce the cost of grain logistics. The system is composed of two major components: grain logistics goods tracking model and vehicle routing problem optimization model and also allows incorporation of data coming from external sources. The proposed system is an effective tool to manage grain logistics in order to increase the speed of grain logistics and reduce the grain circulation cost.

Connecting Mathematics Learning through Spatial Reasoning

ERIC Educational Resources Information Center

Mulligan, Joanne; Woolcott, Geoffrey; Mitchelmore, Michael; Davis, Brent

2018-01-01

Spatial reasoning, an emerging transdisciplinary area of interest to mathematics education research, is proving integral to all human learning. It is particularly critical to science, technology, engineering and mathematics (STEM) fields. This project will create an innovative knowledge framework based on spatial reasoning that identifies new…

Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology.

PubMed

VoPham, Trang; Hart, Jaime E; Laden, Francine; Chiang, Yao-Yi

2018-04-17

Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.

Functional Equivalence of Spatial Images from Touch and Vision: Evidence from Spatial Updating in Blind and Sighted Individuals

ERIC Educational Resources Information Center

Giudice, Nicholas A.; Betty, Maryann R.; Loomis, Jack M.

2011-01-01

This research examined whether visual and haptic map learning yield functionally equivalent spatial images in working memory, as evidenced by similar encoding bias and updating performance. In 3 experiments, participants learned 4-point routes either by seeing or feeling the maps. At test, blindfolded participants made spatial judgments about the…

Involving the public in spatial decision making using Internet GIS

NASA Astrophysics Data System (ADS)

Liu, Zhengrong; Sheng, Grant; Wang, Lei

2006-10-01

Public participation is an integral part of legislation or decision making processes. Traditionally, public participation took place through face-to-face encounters such as public meetings and other fora. However, some important factors limiting the efficiency and effectiveness of this mode of public participation include: geographic separation of participants, scheduling and financial constraints in attending meetings, and limited duration of meetings. These led to the awareness that public participation requires new methods in order to achieve a better democratic decision making. On the other hand, GIS has in the past been accused of being an elitist technology, giving more power to those people already possessing it and depriving those, namely the general public, who more often lack such direct forms of information access. Public participation GIS (PPGIS) is emerging as a distinct subset of two previously separate activities: technology-based spatial analysis and participatory democracy. The paper considers both traditional methods and Internet-based technologies of public participation and argues that new Internet-based technologies have the potential to widen participation by using online spatial decision support systems. GIS and the Internet can be used together to provide the general public with a powerful mechanism for becoming more involved in decision problems. Provision of full access to spatial and non-spatial data, along with the appropriate tools with which to use it, may greatly empower the general public. PPGIS focuses on engaging the public to participate and become involved in a particular subject of interest. It empowers GIS users from all walks of life and enabling them to use the technology purposefully to capture their local knowledge and advance their goals. In the project of public participatory Ontario nuclear waste siting, we focused on developing an Internet based PPGIS prototype to help the public to participate online from inception to the final phase of site decision-making. It shows that in certain siting problems and policy formulation processes, participatory online systems are a useful means of implementing public participation through informing and engaging the public to participate in spatial decision making. Web based PPGIS can involve more participants and higher degree of participation among experts, officials and the pblic than traditional means.

The Domains for the Multi-Criteria Decisions about E-Learning Systems

ERIC Educational Resources Information Center

Uysal, Murat Pasa

2012-01-01

Developments in computer and information technologies continue to give opportunities for designing advanced E-learning systems while entailing objective and technical evaluation methodologies. Design and development of E-learning systems require time-consuming and labor-intensive processes; therefore any decision about these systems and their…

Decision Making and Learning while Taking Sequential Risks

ERIC Educational Resources Information Center

Pleskac, Timothy J.

2008-01-01

A sequential risk-taking paradigm used to identify real-world risk takers invokes both learning and decision processes. This article expands the paradigm to a larger class of tasks with different stochastic environments and different learning requirements. Generalizing a Bayesian sequential risk-taking model to the larger set of tasks clarifies…

Sharing Power with Parents: Improving Educational Decision Making for Students with Learning Disabilities

ERIC Educational Resources Information Center

Connor, David J.; Cavendish, Wendy

2018-01-01

In this closing commentary to the special edition of "Learning Disability Quarterly" ("LDQ") on parent voice in educational decision making for students with learning disabilities, we briefly survey main topics from each article, illuminating important findings from the authors, along with several questions they raise, and…

4SPPIces: A Case Study of Factors in a Scripted Collaborative-Learning Blended Course across Spatial Locations

ERIC Educational Resources Information Center

Perez-Sanagustin, Mar; Santos, Patricia; Hernandez-Leo, Davinia; Blat, Josep

2012-01-01

Computer-Supported Collaborative Blended Learning (CSCBL) scripts are complex learning situations in which formal and informal activities conducted at different spatial locations are coordinated and integrated into one unique learning setting through the use of technology. We define a conceptual model identifying four factors to be considered when…

Spatial Visualization Learning in Engineering: Traditional Methods vs. a Web-Based Tool

ERIC Educational Resources Information Center

Pedrosa, Carlos Melgosa; Barbero, Basilio Ramos; Miguel, Arturo Román

2014-01-01

This study compares an interactive learning manager for graphic engineering to develop spatial vision (ILMAGE_SV) to traditional methods. ILMAGE_SV is an asynchronous web-based learning tool that allows the manipulation of objects with a 3D viewer, self-evaluation, and continuous assessment. In addition, student learning may be monitored, which…

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain.

PubMed

Dominkovics, Pau; Granell, Carlos; Pérez-Navarro, Antoni; Casals, Martí; Orcau, Angels; Caylà, Joan A

2011-11-29

Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information. Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database. The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts. In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios.

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain

PubMed Central

2011-01-01

Background Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information. Methods Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database. Results The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts. Conclusions In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios. PMID:22126392

Individual variations in dose response for spatial memory learning among outbred wistar rats exposed from 5 to 20 cGy of (56) Fe particles.

PubMed

Wyrobek, Andrew J; Britten, Richard A

2016-06-01

Exposures of brain tissue to ionizing radiation can lead to persistent deficits in cognitive functions and behaviors. However, little is known about the quantitative relationships between exposure dose and neurological risks, especially for lower doses and among genetically diverse individuals. We investigated the dose relationship for spatial memory learning among genetically outbred male Wistar rats exposed to graded doses of (56) Fe particles (sham, 5, 10, 15, and 20 cGy; 1 GeV/n). Spatial memory learning was assessed on a Barnes maze using REL3 ratios measured at three months after exposure. Irradiated animals showed dose-dependent declines in spatial memory learning that were fit by a linear regression (P for slope <0.0002). The irradiated animals showed significantly impaired learning at 10 cGy exposures, no detectable learning between 10 and 15 cGy, and worsened performances between 15 and 20 cGy. The proportions of poor learners and the magnitude of their impairment were fit by linear regressions with doubling doses of ∼10 cGy. In contrast, there were no detectable deficits in learning among the good learners in this dose range. Our findings suggest that genetically diverse individuals can vary substantially in their spatial memory learning, and that exposures at low doses appear to preferentially impact poor learners. This hypothesis invites future investigations of the genetic and physiological mechanisms of inter-individual variations in brain function related to spatial memory learning after low-dose HZE radiation exposures and to determine whether it also applies to physical trauma to brain tissue and exposures to chemical neurotoxicants. Environ. Mol. Mutagen. 57:331-340, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Teaching a Rational Approach to Career Decision Making: Who Benefits Most?

ERIC Educational Resources Information Center

Krumboltz, John D.; And Others

1986-01-01

Rational, intuitive, fatalistic, and dependent decision makers were compared on how much they learned from a rational decision-making training intervention. Individuals who had been highly impulsive, dependent, or fatalistic in prior course selections and those who exhibited dependency in prior job choices appeared to learn most from the rational…

Interdisciplinary Collaborative Learning: Using Decision Analysts to Enhance Undergraduate International Management Education

ERIC Educational Resources Information Center

Palocsay, Susan W.; White, Marion M.; Zimmerman, D. Kent

2004-01-01

This article describes an experiential learning activity designed to promote the development of decision-making skills in international management students at the undergraduate level. Students from an undergraduate management science course in decision analysis served as consultants on a case assigned to teams in an international management class.…

Free-Choice Learning Suited to Women's Participation Needs in Environmental Decision-Making Processes

ERIC Educational Resources Information Center

Skanavis, Constantina; Sakellari, Maria

2012-01-01

United Nations mandates recognize the need to promote the full participation of women in environmental decision-making processes on the basis of gender equality. But, there remains a profound lack of effective women's participation in some sectors of environmental decision-making. Free-choice environmental learning offers an effective educational…

Preschool Teaching Students' Prediction of Decision Making Strategies and Academic Achievement on Learning Motivations

ERIC Educational Resources Information Center

Acat, M. Bahaddin; Dereli, Esra

2012-01-01

The purpose of this study was to identify problems and motivation sources and strategies of decision-making of the students' attending preschool education teacher department, was to determine the relationship between learning motivation and strategies of decision-making, academic achievement of students, was to determine whether strategies of…

The perirhinal cortex of the rat is necessary for spatial memory retention long after but not soon after learning.

PubMed

Ramos, Juan M J; Vaquero, Joaquín M M

2005-09-15

Many observations in humans and experimental animals support the view that the hippocampus is critical immediately after learning in order for long-term memory formation to take place. However, exactly when the medial temporal cortices adjacent to the hippocampus are necessary for this process to occur normally is not yet well known. Using a spatial task, we studied whether the perirhinal cortex of rats is necessary to establish representations in long-term memory. Results showed that, in a spatial task sensitive to hippocampal lesions, control and perirhinal lesioned rats can both learn at the same rate (Experiment 1). Interestingly, a differential involvement of the perirhinal cortex in memory retention was observed as time passes after learning. Thus, 24 days following the end of learning, lesioned and control rats remembered the task perfectly as measured by a retraining test. In contrast, 74 days after the learning the perirhinal animals showed a profound impairment in the retention of the spatial information (Experiment 2). Taken together, these results suggest that the perirhinal region is critical for the formation of long-term spatial memory. However, its contribution to memory formation and retention is time-dependent, it being necessary only long after learning takes place and not during the phase immediately following acquisition.

Sex and boldness explain individual differences in spatial learning in a lizard.

PubMed

Carazo, Pau; Noble, Daniel W A; Chandrasoma, Dani; Whiting, Martin J

2014-05-07

Understanding individual differences in cognitive performance is a major challenge to animal behaviour and cognition studies. We used the Eastern water skink (Eulamprus quoyii) to examine associations between exploration, boldness and individual variability in spatial learning, a dimension of lizard cognition with important bearing on fitness. We show that males perform better than females in a biologically relevant spatial learning task. This is the first evidence for sex differences in learning in a reptile, and we argue that it is probably owing to sex-specific selective pressures that may be widespread in lizards. Across the sexes, we found a clear association between boldness after a simulated predatory attack and the probability of learning the spatial task. In contrast to previous studies, we found a nonlinear association between boldness and learning: both 'bold' and 'shy' behavioural types were more successful learners than intermediate males. Our results do not fit with recent predictions suggesting that individual differences in learning may be linked with behavioural types via high-low-risk/reward trade-offs. We suggest the possibility that differences in spatial cognitive performance may arise in lizards as a consequence of the distinct environmental variability and complexity experienced by individuals as a result of their sex and social tactics.

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

PubMed

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

2015-01-01

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

How to enhance route learning and visuo-spatial working memory in aging: a training for residential care home residents.

PubMed

Mitolo, Micaela; Borella, Erika; Meneghetti, Chiara; Carbone, Elena; Pazzaglia, Francesca

2017-05-01

This study aimed to assess the efficacy of a route-learning training in a group of older adults living in a residential care home. We verified the presence of training-specific effects in tasks similar to those trained - route-learning tasks - as well as transfer effects on related cognitive processes - visuo-spatial short-term memory (VSSTM; Corsi Blocks Test (CBT), forward version), visuo-spatial working memory (VSWM; CBT, backward version; Pathway Span Tasks; Jigsaw Puzzle Test) - and in self-report measures. The maintenance of training benefits was examined after 3 months. Thirty 70-90-year-old residential care home residents were randomly assigned to the route-learning training group or to an active control group (involved in non-visuo-spatial activities). The trained group performed better than the control group in the route-learning tasks, retaining this benefit 3 months later. Immediate transfer effects were also seen in visuo-spatial span tasks (i.e., CBT forward and backward version and Pathway Span Task); these benefits had been substantially maintained at the 3-month follow-up. These findings suggest that a training on route learning is a promising approach to sustain older adults' environmental learning and some related abilities (e.g., VSSTM and VSWM), even in residential care home residents.

[Effects of the neurogenesis stimulator Ro 25-6981 upon formation of spatial skill in adult rats depend on the term of its administration and the animals' ability to learn].

PubMed

Solov'eva, O A; Storozheva, Z I; Proshin, A T; Sherstnev, V V

2011-02-01

Effect of administration of selective N-methyl-D-aspartate (NMDA) receptor antagonist Ro 25-6981 on learning and memory in a dose which is known to stimulate neoneurogenesis was assessed in adult rats with different abilities to formation of spatial skills in different time periods after the antagonist injection. Wistar male rats were trained to find hidden platform in the Morris water maze for 5 consecutive days. Rats' learning ability for spatial skill formation was evaluated depending on platform speed achievements. In re-training sessions (cues and platform location changed), it was found that all rats received Ro 25-6981 13 days before the re-training demonstrated impaired spatial memory. At the same time the inhibitor injected 29 days before re-training selectively facilitated the formation of spatial skill in animals with initially low learning abilities.

[Learning to solve a spatial task in a water maze in aggressive and submissive mice].

PubMed

Dubrovina, N I; Tomilenko, R A

2007-01-01

Learning and retention of the spatial memory were studied in mice with alternative under conditions of various experimental protocols. Visible and hidden platform acquisition in a simple model of the water maze was similarly fast both in aggressive and submissive mice, but extinction differed. Retention of the platform location preference persisted in aggressive mice in four testing trials. In submissive mice, extiction of the spatial memory was accompanied with a prolongation of search with parallel production of episodes of "passive drift". Differences in spatial learning between aggressive and submissive mice were revealed in a water maze complicated with partitions. In this case, aggressors were able to learn the position of a hidden platform (in contrast to submissive mice with the dominant response of "passive drift"). During testing the response, aggressive mice longer retained the spatial preference without extinction.

Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

PubMed Central

Hansen, James W

2005-01-01

Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

The Impact of Participation in Music on Learning Mathematics

ERIC Educational Resources Information Center

Holmes, Sylwia; Hallam, Susan

2017-01-01

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

Resting-State fMRI Activity Predicts Unsupervised Learning and Memory in an Immersive Virtual Reality Environment

PubMed Central

Wong, Chi Wah; Olafsson, Valur; Plank, Markus; Snider, Joseph; Halgren, Eric; Poizner, Howard; Liu, Thomas T.

2014-01-01

In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment. PMID:25286145

A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

NASA Astrophysics Data System (ADS)

Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

2015-12-01

Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

Reliability and Validity Study of the Mobile Learning Adoption Scale Developed Based on the Diffusion of Innovations Theory

ERIC Educational Resources Information Center

Celik, Ismail; Sahin, Ismail; Aydin, Mustafa

2014-01-01

In this study, a mobile learning adoption scale (MLAS) was developed on the basis of Rogers' (2003) Diffusion of Innovations Theory. The scale that was developed consists of four sections. These sections are as follows: Stages in the innovation-decision process, Types of m-learning decision, Innovativeness level and attributes of m-learning. There…

Reliability and Validity Study of the Mobile Learning Adoption Scale Developed Based on the Diffusion of Innovations Theory

ERIC Educational Resources Information Center

Celik, Ismail; Sahin, Ismail; Aydin, Mustafa

2014-01-01

In this study, a mobile learning adoption scale (MLAS) was developed on the basis of Rogers' (2003) Diffusion of Innovations Theory. The scale that was developed consists of four sections. These sections are as follows: Stages in the innovation-decision process, Types of m-learning decision, Innovativeness level and attributes of m-learning.…

Concurrent Learning of Control in Multi agent Sequential Decision Tasks

DTIC Science & Technology

2018-04-17

Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement...learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable...shall be subject to any oenalty for failing to comply with a collection of information if it does not display a currently valid OMB control number

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

PubMed Central

Arai, Mamiko; Brandt, Vicky; Dabaghian, Yuri

2014-01-01

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

Cross-Sensory Transfer of Reference Frames in Spatial Memory

ERIC Educational Resources Information Center

Kelly, Jonathan W.; Avraamides, Marios N.

2011-01-01

Two experiments investigated whether visual cues influence spatial reference frame selection for locations learned through touch. Participants experienced visual cues emphasizing specific environmental axes and later learned objects through touch. Visual cues were manipulated and haptic learning conditions were held constant. Imagined perspective…

A web-based multicriteria evaluation of spatial trade-offs between environmental and economic implications from hydraulic fracturing in a shale gas region in Ohio.

PubMed

Liu, X; Gorsevski, P V; Yacobucci, M M; Onasch, C M

2016-06-01

Planning of shale gas infrastructure and drilling sites for hydraulic fracturing has important spatial implications. The evaluation of conflicting and competing objectives requires an explicit consideration of multiple criteria as they have important environmental and economic implications. This study presents a web-based multicriteria spatial decision support system (SDSS) prototype with a flexible and user-friendly interface that could provide educational or decision-making capabilities with respect to hydraulic fracturing site selection in eastern Ohio. One of the main features of this SDSS is to emphasize potential trade-offs between important factors of environmental and economic ramifications from hydraulic fracturing activities using a weighted linear combination (WLC) method. In the prototype, the GIS-enabled analytical components allow spontaneous visualization of available alternatives on maps which provide value-added features for decision support processes and derivation of final decision maps. The SDSS prototype also facilitates nonexpert participation capabilities using a mapping module, decision-making tool, group decision module, and social media sharing tools. The logical flow of successively presented forms and standardized criteria maps is used to generate visualization of trade-off scenarios and alternative solutions tailored to individual user's preferences that are graphed for subsequent decision-making.

Learning relative values in the striatum induces violations of normative decision making

PubMed Central

Klein, Tilmann A.; Ullsperger, Markus; Jocham, Gerhard

2017-01-01

To decide optimally between available options, organisms need to learn the values associated with these options. Reinforcement learning models offer a powerful explanation of how these values are learnt from experience. However, human choices often violate normative principles. We suggest that seemingly counterintuitive decisions may arise as a natural consequence of the learning mechanisms deployed by humans. Here, using fMRI and a novel behavioural task, we show that, when suddenly switched to novel choice contexts, participants’ choices are incongruent with values learnt by standard learning algorithms. Instead, behaviour is compatible with the decisions of an agent learning how good an option is relative to an option with which it had previously been paired. Striatal activity exhibits the characteristics of a prediction error used to update such relative option values. Our data suggest that choices can be biased by a tendency to learn option values with reference to the available alternatives. PMID:28631734

A cyber-enabled spatial decision support system to inventory Mangroves in Mozambique: coupling scientific workflows and cloud computing

Treesearch

Wenwu Tang; Wenpeng Feng; Meijuan Jia; Jiyang Shi; Huifang Zuo; Christina E. Stringer; Carl C. Trettin

2017-01-01

Mangroves are an important terrestrial carbon reservoir with numerous ecosystem services. Yet, it is difficult to inventory mangroves because of their low accessibility. A sampling approach that produces accurate assessment while maximizing logistical integrity of inventory operation is often required. Spatial decision support systems (SDSSs) provide support for...

Reinforcement learning signals in the human striatum distinguish learners from nonlearners during reward-based decision making.

PubMed

Schönberg, Tom; Daw, Nathaniel D; Joel, Daphna; O'Doherty, John P

2007-11-21

The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed bandit task in which subjects are almost evenly split into two groups on the basis of their performance: those who do learn to favor choice of the optimal action and those who do not. Using models of reinforcement learning we sought to determine the neural basis of these intrinsic differences in performance by scanning both groups with functional magnetic resonance imaging. We scanned 29 subjects while they performed the reward-based decision-making task. Our results suggest that these two groups differ markedly in the degree to which reinforcement learning signals in the striatum are engaged during task performance. While the learners showed robust prediction error signals in both the ventral and dorsal striatum during learning, the nonlearner group showed a marked absence of such signals. Moreover, the magnitude of prediction error signals in a region of dorsal striatum correlated significantly with a measure of behavioral performance across all subjects. These findings support a crucial role of prediction error signals, likely originating from dopaminergic midbrain neurons, in enabling learning of action selection preferences on the basis of obtained rewards. Thus, spontaneously observed individual differences in decision making performance demonstrate the suggested dependence of this type of learning on the functional integrity of the dopaminergic striatal system in humans.

Application of GIS in foreign direct investment decision support system

NASA Astrophysics Data System (ADS)

Zhou, Jianlan; Sun, Koumei

2007-06-01

It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.

SPATIAL PREDICTION USING COMBINED SOURCES OF DATA

EPA Science Inventory

For improved environmental decision-making, it is important to develop new models for spatial prediction that accurately characterize important spatial and temporal patterns of air pollution. As the U .S. Environmental Protection Agency begins to use spatial prediction in the reg...

Modeling spatial decisions with graph theory: logging roads and forest fragmentation in the Brazilian Amazon.

PubMed

Walker, Robert; Arima, Eugenio; Messina, Joe; Soares-Filho, Britaldo; Perz, Stephen; Vergara, Dante; Sales, Marcio; Pereira, Ritaumaria; Castro, Williams

2013-01-01

This article addresses the spatial decision-making of loggers and implications for forest fragmentation in the Amazon basin. It provides a behavioral explanation for fragmentation by modeling how loggers build road networks, typically abandoned upon removal of hardwoods. Logging road networks provide access to land, and the settlers who take advantage of them clear fields and pastures that accentuate their spatial signatures. In shaping agricultural activities, these networks organize emergent patterns of forest fragmentation, even though the loggers move elsewhere. The goal of the article is to explicate how loggers shape their road networks, in order to theoretically explain an important type of forest fragmentation found in the Amazon basin, particularly in Brazil. This is accomplished by adapting graph theory to represent the spatial decision-making of loggers, and by implementing computational algorithms that build graphs interpretable as logging road networks. The economic behavior of loggers is conceptualized as a profit maximization problem, and translated into spatial decision-making by establishing a formal correspondence between mathematical graphs and road networks. New computational approaches, adapted from operations research, are used to construct graphs and simulate spatial decision-making as a function of discount rates, land tenure, and topographic constraints. The algorithms employed bracket a range of behavioral settings appropriate for areas of terras de volutas, public lands that have not been set aside for environmental protection, indigenous peoples, or colonization. The simulation target sites are located in or near so-called Terra do Meio, once a major logging frontier in the lower Amazon Basin. Simulation networks are compared to empirical ones identified by remote sensing and then used to draw inferences about factors influencing the spatial behavior of loggers. Results overall suggest that Amazonia's logging road networks induce more fragmentation than necessary to access fixed quantities of wood. The paper concludes by considering implications of the approach and findings for Brazil's move to a system of concession logging.

Pedestrian recognition using automotive radar sensors

NASA Astrophysics Data System (ADS)

Bartsch, A.; Fitzek, F.; Rasshofer, R. H.

2012-09-01

The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.

Learning of Rule Ensembles for Multiple Attribute Ranking Problems

NASA Astrophysics Data System (ADS)

Dembczyński, Krzysztof; Kotłowski, Wojciech; Słowiński, Roman; Szeląg, Marcin

In this paper, we consider the multiple attribute ranking problem from a Machine Learning perspective. We propose two approaches to statistical learning of an ensemble of decision rules from decision examples provided by the Decision Maker in terms of pairwise comparisons of some objects. The first approach consists in learning a preference function defining a binary preference relation for a pair of objects. The result of application of this function on all pairs of objects to be ranked is then exploited using the Net Flow Score procedure, giving a linear ranking of objects. The second approach consists in learning a utility function for single objects. The utility function also gives a linear ranking of objects. In both approaches, the learning is based on the boosting technique. The presented approaches to Preference Learning share good properties of the decision rule preference model and have good performance in the massive-data learning problems. As Preference Learning and Multiple Attribute Decision Aiding share many concepts and methodological issues, in the introduction, we review some aspects bridging these two fields. To illustrate the two approaches proposed in this paper, we solve with them a toy example concerning the ranking of a set of cars evaluated by multiple attributes. Then, we perform a large data experiment on real data sets. The first data set concerns credit rating. Since recent research in the field of Preference Learning is motivated by the increasing role of modeling preferences in recommender systems and information retrieval, we chose two other massive data sets from this area - one comes from movie recommender system MovieLens, and the other concerns ranking of text documents from 20 Newsgroups data set.

Grade 7 students' normative decision making in science learning about global warming through science technology and society (STS) approach

NASA Astrophysics Data System (ADS)

Luengam, Piyanuch; Tupsai, Jiraporn; Yuenyong, Chokchai

2018-01-01

This study reported Grade 7 students' normative decision making in teaching and learning about global warming through science technology and society (STS) approach. The participants were 43 Grade 7 students in Sungkom, Nongkhai, Thailand. The teaching and learning about global warming through STS approach had carried out for 5 weeks. The global warming unit through STS approach was developed based on framework of Yuenyong (2006) that consisted of five stages including (1) identification of social issues, (2) identification of potential solutions, (3) need for knowledge, (4) decision-making, and (5) socialization stage. Students' normative decision making was collected during their learning by questionnaire, participant observation, and students' tasks. Students' normative decision making were analyzed from both pre-and post-intervention and students' ideas during the intervention. The aspects of normative include influences of global warming on technology and society; influences of values, culture, and society on global warming; and influences of technology on global warming. The findings revealed that students have chance to learn science concerning with the relationship between science, technology, and society through their giving reasons about issues related to global warming. The paper will discuss implications of these for science teaching and learning through STS in Thailand.

Contextual Cueing: Implicit Learning and Memory of Visual Context Guides Spatial Attention.

ERIC Educational Resources Information Center

Chun, Marvin M.; Jiang, Yuhong

1998-01-01

Six experiments involving a total of 112 college students demonstrate that a robust memory for visual context exists to guide spatial attention. Results show how implicit learning and memory of visual context can guide spatial attention toward task-relevant aspects of a scene. (SLD)

MICROINJECTION OF DYNORPHIN INTO THE HIPPOCAMPUS IMPAIRS SPATIAL LEARNING IN RATS

EPA Science Inventory

The effect of hippocampal dynorphin administration on learning and memory was examined in spatial and nonspatial tasks. ilateral infusion of dynorphin A(1-8)(DYN; 10 or 20 ug in one ul) into the dorsal hippocampus resulted in dose-related impairment of spatial working memory in a...

Biologically-inspired robust and adaptive multi-sensor fusion and active control

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Dow, Paul A.; Huber, David J.

2009-04-01

In this paper, we describe a method and system for robust and efficient goal-oriented active control of a machine (e.g., robot) based on processing, hierarchical spatial understanding, representation and memory of multimodal sensory inputs. This work assumes that a high-level plan or goal is known a priori or is provided by an operator interface, which translates into an overall perceptual processing strategy for the machine. Its analogy to the human brain is the download of plans and decisions from the pre-frontal cortex into various perceptual working memories as a perceptual plan that then guides the sensory data collection and processing. For example, a goal might be to look for specific colored objects in a scene while also looking for specific sound sources. This paper combines three key ideas and methods into a single closed-loop active control system. (1) Use high-level plan or goal to determine and prioritize spatial locations or waypoints (targets) in multimodal sensory space; (2) collect/store information about these spatial locations at the appropriate hierarchy and representation in a spatial working memory. This includes invariant learning of these spatial representations and how to convert between them; and (3) execute actions based on ordered retrieval of these spatial locations from hierarchical spatial working memory and using the "right" level of representation that can efficiently translate into motor actions. In its most specific form, the active control is described for a vision system (such as a pantilt- zoom camera system mounted on a robotic head and neck unit) which finds and then fixates on high saliency visual objects. We also describe the approach where the goal is to turn towards and sequentially foveate on salient multimodal cues that include both visual and auditory inputs.

Lean production tools and decision latitude enable conditions for innovative learning in organizations: a multilevel analysis.

PubMed

Fagerlind Ståhl, Anna-Carin; Gustavsson, Maria; Karlsson, Nadine; Johansson, Gun; Ekberg, Kerstin

2015-03-01

The effect of lean production on conditions for learning is debated. This study aimed to investigate how tools inspired by lean production (standardization, resource reduction, visual monitoring, housekeeping, value flow analysis) were associated with an innovative learning climate and with collective dispersion of ideas in organizations, and whether decision latitude contributed to these associations. A questionnaire was sent out to employees in public, private, production and service organizations (n = 4442). Multilevel linear regression analyses were used. Use of lean tools and decision latitude were positively associated with an innovative learning climate and collective dispersion of ideas. A low degree of decision latitude was a modifier in the association to collective dispersion of ideas. Lean tools can enable shared understanding and collective spreading of ideas, needed for the development of work processes, especially when decision latitude is low. Value flow analysis played a pivotal role in the associations. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Student decisions about lecture attendance: do electronic course materials matter?

PubMed

Billings-Gagliardi, Susan; Mazor, Kathleen M

2007-10-01

This study explored whether first-year medical students make deliberate decisions about attending nonrequired lectures. If so, it sought to identify factors that influence these decisions, specifically addressing the potential impact of electronic materials. Medical students who completed first-year studies between 2004 and 2006 responded to an open-ended survey question about their own lecture-attendance decisions. Responses were coded to capture major themes. Students' ratings of the electronic materials were also examined. Most respondents made deliberate attendance decisions. Decisions were influenced by previous experiences with the lecturer, predictions of what would occur during the session itself, personal learning preferences, and learning needs at that particular time, with the overriding goal of maximizing learning. Access to electronic materials did not influence students' choices. Fears that the increasing availability of technology-enhanced educational materials has a negative impact on lecture attendance seem unfounded.

Comprehensive decision tree models in bioinformatics.

PubMed

Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics.

Comprehensive Decision Tree Models in Bioinformatics

PubMed Central

Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Purpose Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. Methods This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. Results The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. Conclusions The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics. PMID:22479449

The Predictive Power of Fifth Graders' Learning Styles on Their Mathematical Reasoning and Spatial Ability

ERIC Educational Resources Information Center

Danisman, Sahin; Erginer, Ergin

2017-01-01

The purpose of this study was to examine fifth graders' mathematical reasoning and spatial ability, to identify a correlation with their learning styles, and to determine the predictive power of their learning styles on their mathematical learning profiles. This causal study was conducted with 97 fifth graders (60 females, 61.9% and 37 males,…

Mobile Devices and Spatial Enactments of Learning: iPads in Lower Secondary Schools

ERIC Educational Resources Information Center

Meyer, Bente

2016-01-01

Based on ethnographic studies of students' learning, this paper investigates how new spatial enactments of learning that include mobile technologies engage students in specific ways that enable them to learn. Data used in the paper have been collected in three lower secondary schools (7-9th form, ages 13-15) where students and teachers have been…

Spatial Learning and Computer Simulations in Science

ERIC Educational Resources Information Center

Lindgren, Robb; Schwartz, Daniel L.

2009-01-01

Interactive simulations are entering mainstream science education. Their effects on cognition and learning are often framed by the legacy of information processing, which emphasized amodal problem solving and conceptual organization. In contrast, this paper reviews simulations from the vantage of research on perception and spatial learning,…

Learning Anatomy Enhances Spatial Ability

ERIC Educational Resources Information Center

Vorstenbosch, Marc A. T. M.; Klaassen, Tim P. F. M.; Donders, A. R. T.; Kooloos, Jan G. M.; Bolhuis, Sanneke M.; Laan, Roland F. J. M.

2013-01-01

Spatial ability is an important factor in learning anatomy. Students with high scores on a mental rotation test (MRT) systematically score higher on anatomy examinations. This study aims to investigate if learning anatomy also oppositely improves the MRT-score. Five hundred first year students of medicine ("n" = 242, intervention) and…

[Influence of stimulation and blockade of α4β2 nicotinic acetylcholine receptors on learning of female rats in basic phases of ovary cycle].

PubMed

Fedotova, Iu O

2014-03-01

The present work was devoted to the comparative analysis of α4β2 nicotinic acetylcholine receptors (nAChRs) in learning/memory processes during ovary cycle in the adult female rats. RJR-2403 (1.0 mg/kg, i. p.), α4β2 nAChRs agonist and mecamylamine (1.0 mg/kg, i. p.), α4β2 nAChRs antagonist were injected chronically during 14 days. The processes of learning/memory were assessed in different models of learning: passive avoidance performance and Morris water maze. Chronic RJR-2403 administration to females improved the passive avoidance performance in proestrous and estrous as compared to the control animals. Also, RJR-2403 restored spatial learning of rats during proestrous phases in Morris water maze, and stimulated the dynamics of spatial learning during estrous phases. On the contrary, the chronic mecamylamine administration impaired non-spatial, and especially, spatial learning in females during key phases of ovary cycle. The results of the study suggest positive effect of α4β2 nAChRs stimulation in learning/memory processes during ovary cycle in the adult female rats.

Interprofessional learning at work: what spatial theory can tell us about workplace learning in an acute care ward.

PubMed

Gregory, Linda Rosemary; Hopwood, Nick; Boud, David

2014-05-01

It is widely recognized that every workplace potentially provides a rich source of learning. Studies focusing on health care contexts have shown that social interaction within and between professions is crucial in enabling professionals to learn through work, address problems and cope with challenges of clinical practice. While hospital environments are beginning to be understood in spatial terms, the links between space and interprofessional learning at work have not been explored. This paper draws on Lefebvre's tri-partite theoretical framework of perceived, conceived and lived space to enrich understandings of interprofessional learning on an acute care ward in an Australian teaching hospital. Qualitative analysis was undertaken using data from observations of Registered Nurses at work and semi-structured interviews linked to observed events. The paper focuses on a ward round, the medical workroom and the Registrar's room, comparing and contrasting the intended (conceived), practiced (perceived) and pedagogically experienced (lived) spatial dimensions. The paper concludes that spatial theory has much to offer understandings of interprofessional learning in work, and the features of work environments and daily practices that produce spaces that enable or constrain learning.

Withdrawal from Cocaine Self-Administration Produces Long-Lasting Deficits in Orbitofrontal-Dependent Reversal Learning in Rats

ERIC Educational Resources Information Center

Calu, Donna J.; Stalnaker, Thomas A.; Franz, Theresa M.; Singh, Teghpal; Shaham, Yavin; Schoenbaum, Geoffrey

2007-01-01

Drug addicts make poor decisions. These decision-making deficits have been modeled in addicts and laboratory animals using reversal-learning tasks. However, persistent reversal-learning impairments have been shown in rats and monkeys only after noncontingent cocaine injections. Current thinking holds that to represent the human condition…

Learning Styles: A Pivotal Point for Retention and Career Decision Guidance.

ERIC Educational Resources Information Center

Jenkins, Jeannette

The importance of learning styles to student retention and career decision guidance is considered. Learning style is the way people process information and solve problems. Research on right and left brain processing, which indicates that the left hemisphere controls thoughts that are predominately rational and the right hemisphere controls…

Deep learning aided decision support for pulmonary nodules diagnosing: a review.

PubMed

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping; He, Jianxing; Liu, Bo

2018-04-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing.

Easy rider: monkeys learn to drive a wheelchair to navigate through a complex maze.

PubMed

Etienne, Stephanie; Guthrie, Martin; Goillandeau, Michel; Nguyen, Tho Hai; Orignac, Hugues; Gross, Christian; Boraud, Thomas

2014-01-01

The neurological bases of spatial navigation are mainly investigated in rodents and seldom in primates. The few studies led on spatial navigation in both human and non-human primates are performed in virtual, not in real environments. This is mostly because of methodological difficulties inherent in conducting research on freely-moving monkeys in real world environments. There is some incertitude, however, regarding the extrapolation of rodent spatial navigation strategies to primates. Here we present an entirely new platform for investigating real spatial navigation in rhesus monkeys. We showed that monkeys can learn a pathway by using different strategies. In these experiments three monkeys learned to drive the wheelchair and to follow a specified route through a real maze. After learning the route, probe tests revealed that animals successively use three distinct navigation strategies based on i) the place of the reward, ii) the direction taken to obtain reward or iii) a cue indicating reward location. The strategy used depended of the options proposed and the duration of learning. This study reveals that monkeys, like rodents and humans, switch between different spatial navigation strategies with extended practice, implying well-conserved brain learning systems across different species. This new task with freely driving monkeys provides a good support for the electrophysiological and pharmacological investigation of spatial navigation in the real world by making possible electrophysiological and pharmacological investigations.

Neural Correlates of Temporal Credit Assignment in the Parietal Lobe

PubMed Central

Eisenberg, Ian; Gottlieb, Jacqueline

2014-01-01

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

Role of the medial prefrontal cortex in impaired decision making in juvenile attention-deficit/hyperactivity disorder.

PubMed

Hauser, Tobias U; Iannaccone, Reto; Ball, Juliane; Mathys, Christoph; Brandeis, Daniel; Walitza, Susanne; Brem, Silvia

2014-10-01

Attention-deficit/hyperactivity disorder (ADHD) has been associated with deficient decision making and learning. Models of ADHD have suggested that these deficits could be caused by impaired reward prediction errors (RPEs). Reward prediction errors are signals that indicate violations of expectations and are known to be encoded by the dopaminergic system. However, the precise learning and decision-making deficits and their neurobiological correlates in ADHD are not well known. To determine the impaired decision-making and learning mechanisms in juvenile ADHD using advanced computational models, as well as the related neural RPE processes using multimodal neuroimaging. Twenty adolescents with ADHD and 20 healthy adolescents serving as controls (aged 12-16 years) were examined using a probabilistic reversal learning task while simultaneous functional magnetic resonance imaging and electroencephalogram were recorded. Learning and decision making were investigated by contrasting a hierarchical Bayesian model with an advanced reinforcement learning model and by comparing the model parameters. The neural correlates of RPEs were studied in functional magnetic resonance imaging and electroencephalogram. Adolescents with ADHD showed more simplistic learning as reflected by the reinforcement learning model (exceedance probability, Px = .92) and had increased exploratory behavior compared with healthy controls (mean [SD] decision steepness parameter β: ADHD, 4.83 [2.97]; controls, 6.04 [2.53]; P = .02). The functional magnetic resonance imaging analysis revealed impaired RPE processing in the medial prefrontal cortex during cue as well as during outcome presentation (P < .05, family-wise error correction). The outcome-related impairment in the medial prefrontal cortex could be attributed to deficient processing at 200 to 400 milliseconds after feedback presentation as reflected by reduced feedback-related negativity (ADHD, 0.61 [3.90] μV; controls, -1.68 [2.52] μV; P = .04). The combination of computational modeling of behavior and multimodal neuroimaging revealed that impaired decision making and learning mechanisms in adolescents with ADHD are driven by impaired RPE processing in the medial prefrontal cortex. This novel, combined approach furthers the understanding of the pathomechanisms in ADHD and may advance treatment strategies.

"Decisions, decisions, decisions": transfer and specificity of decision-making skill between sports.

PubMed

Causer, Joe; Ford, Paul R

2014-08-01

The concept of transfer of learning holds that previous practice or experience in one task or domain will enable successful performance in another related task or domain. In contrast, specificity of learning holds that previous practice or experience in one task or domain does not transfer to other related tasks or domains. The aim of the current study is to examine whether decision-making skill transfers between sports that share similar elements, or whether it is specific to a sport. Participants (n = 205) completed a video-based temporal occlusion decision-making test in which they were required to decide on which action to execute across a series of 4 versus 4 soccer game situations. A sport engagement questionnaire was used to identify 106 soccer players, 43 other invasion sport players and 58 other sport players. Positive transfer of decision-making skill occurred between soccer and other invasion sports, which are related and have similar elements, but not from volleyball, supporting the concept of transfer of learning.

People learn other people's preferences through inverse decision-making.

PubMed

Jern, Alan; Lucas, Christopher G; Kemp, Charles

2017-11-01

People are capable of learning other people's preferences by observing the choices they make. We propose that this learning relies on inverse decision-making-inverting a decision-making model to infer the preferences that led to an observed choice. In Experiment 1, participants observed 47 choices made by others and ranked them by how strongly each choice suggested that the decision maker had a preference for a specific item. An inverse decision-making model generated predictions that were in accordance with participants' inferences. Experiment 2 replicated and extended a previous study by Newtson (1974) in which participants observed pairs of choices and made judgments about which choice provided stronger evidence for a preference. Inverse decision-making again predicted the results, including a result that previous accounts could not explain. Experiment 3 used the same method as Experiment 2 and found that participants did not expect decision makers to be perfect utility-maximizers. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

2012-12-01

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

Design Decisions in Developing Learning Trajectories-Based Assessments in Mathematics: A Case Study

ERIC Educational Resources Information Center

Penuel, William R.; Confrey, Jere; Maloney, Alan; Rupp, André A.

2014-01-01

This article analyzes the design decisions of a team developing diagnostic assessments for a learning trajectory focused on rational number reasoning. The analysis focuses on the design rationale for key decisions about how to develop the cognitive assessments and related validity arguments within a fluid state and national policy context. The…

Lesions of the fornix and anterior thalamic nuclei dissociate different aspects of hippocampal-dependent spatial learning: implications for the neural basis of scene learning.

PubMed

Aggleton, John P; Poirier, Guillaume L; Aggleton, Hugh S; Vann, Seralynne D; Pearce, John M

2009-06-01

The present study used 2 different discrimination tasks designed to isolate distinct components of visuospatial learning: structural learning and geometric learning. Structural learning refers to the ability to learn the precise combination of stimulus identity with stimulus location. Rats with anterior thalamic lesions and fornix lesions were unimpaired on a configural learning task in which the rats learned 3 concurrent mirror-image discriminations (structural learning). Indeed, both lesions led to facilitated learning. In contrast, anterior thalamic lesions impaired the geometric discrimination (e.g., swim to the corner with the short wall to the right of the long wall). Finally, both the fornix and anterior thalamic lesions severely impaired T-maze alternation, a task that taxes an array of spatial strategies including allocentric learning. This pattern of dissociations and double dissociations highlights how distinct classes of spatial learning rely on different systems, even though they may converge on the hippocampus. Consequently, the findings suggest that structural learning is heavily dependent on cortico-hippocampal interactions. In contrast, subcortical inputs (such as those from the anterior thalamus) contribute to geometric learning. Copyright (c) 2009 APA, all rights reserved.

The experiment of cooperative learning model type team assisted individualization (TAI) on three-dimensional space subject viewed from spatial intelligence

NASA Astrophysics Data System (ADS)

Manapa, I. Y. H.; Budiyono; Subanti, S.

2018-03-01

The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.

Supporting Student Differences in Listening Comprehension and Vocabulary Learning with Multimedia Annotations

ERIC Educational Resources Information Center

Jones, Linda C.

2009-01-01

This article describes how effectively multimedia learning environments can assist second language (L2) students of different spatial and verbal abilities with listening comprehension and vocabulary learning. In particular, it explores how written and pictorial annotations interacted with high/low spatial and verbal ability learners and thus…

Robust Blind Learning Algorithm for Nonlinear Equalization Using Input Decision Information.

PubMed

Xu, Lu; Huang, Defeng David; Guo, Yingjie Jay

2015-12-01

In this paper, we propose a new blind learning algorithm, namely, the Benveniste-Goursat input-output decision (BG-IOD), to enhance the convergence performance of neural network-based equalizers for nonlinear channel equalization. In contrast to conventional blind learning algorithms, where only the output of the equalizer is employed for updating system parameters, the BG-IOD exploits a new type of extra information, the input decision information obtained from the input of the equalizer, to mitigate the influence of the nonlinear equalizer structure on parameters learning, thereby leading to improved convergence performance. We prove that, with the input decision information, a desirable convergence capability that the output symbol error rate (SER) is always less than the input SER if the input SER is below a threshold, can be achieved. Then, the BG soft-switching technique is employed to combine the merits of both input and output decision information, where the former is used to guarantee SER convergence and the latter is to improve SER performance. Simulation results show that the proposed algorithm outperforms conventional blind learning algorithms, such as stochastic quadratic distance and dual mode constant modulus algorithm, in terms of both convergence performance and SER performance, for nonlinear equalization.

Machine learning for predicting soil classes in three semi-arid landscapes

USGS Publications Warehouse

Brungard, Colby W.; Boettinger, Janis L.; Duniway, Michael C.; Wills, Skye A.; Edwards, Thomas C.

2015-01-01

Mapping the spatial distribution of soil taxonomic classes is important for informing soil use and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial distribution of soil taxonomic classes. Key components of DSM are the method and the set of environmental covariates used to predict soil classes. Machine learning is a general term for a broad set of statistical modeling techniques. Many different machine learning models have been applied in the literature and there are different approaches for selecting covariates for DSM. However, there is little guidance as to which, if any, machine learning model and covariate set might be optimal for predicting soil classes across different landscapes. Our objective was to compare multiple machine learning models and covariate sets for predicting soil taxonomic classes at three geographically distinct areas in the semi-arid western United States of America (southern New Mexico, southwestern Utah, and northeastern Wyoming). All three areas were the focus of digital soil mapping studies. Sampling sites at each study area were selected using conditioned Latin hypercube sampling (cLHS). We compared models that had been used in other DSM studies, including clustering algorithms, discriminant analysis, multinomial logistic regression, neural networks, tree based methods, and support vector machine classifiers. Tested machine learning models were divided into three groups based on model complexity: simple, moderate, and complex. We also compared environmental covariates derived from digital elevation models and Landsat imagery that were divided into three different sets: 1) covariates selected a priori by soil scientists familiar with each area and used as input into cLHS, 2) the covariates in set 1 plus 113 additional covariates, and 3) covariates selected using recursive feature elimination. Overall, complex models were consistently more accurate than simple or moderately complex models. Random forests (RF) using covariates selected via recursive feature elimination was consistently the most accurate, or was among the most accurate, classifiers between study areas and between covariate sets within each study area. We recommend that for soil taxonomic class prediction, complex models and covariates selected by recursive feature elimination be used. Overall classification accuracy in each study area was largely dependent upon the number of soil taxonomic classes and the frequency distribution of pedon observations between taxonomic classes. Individual subgroup class accuracy was generally dependent upon the number of soil pedon observations in each taxonomic class. The number of soil classes is related to the inherent variability of a given area. The imbalance of soil pedon observations between classes is likely related to cLHS. Imbalanced frequency distributions of soil pedon observations between classes must be addressed to improve model accuracy. Solutions include increasing the number of soil pedon observations in classes with few observations or decreasing the number of classes. Spatial predictions using the most accurate models generally agree with expected soil–landscape relationships. Spatial prediction uncertainty was lowest in areas of relatively low relief for each study area.

Evaluation of Alternative Conceptual Models Using Interdisciplinary Information: An Application in Shallow Groundwater Recharge and Discharge

NASA Astrophysics Data System (ADS)

Lin, Y.; Bajcsy, P.; Valocchi, A. J.; Kim, C.; Wang, J.

2007-12-01

Natural systems are complex, thus extensive data are needed for their characterization. However, data acquisition is expensive; consequently we develop models using sparse, uncertain information. When all uncertainties in the system are considered, the number of alternative conceptual models is large. Traditionally, the development of a conceptual model has relied on subjective professional judgment. Good judgment is based on experience in coordinating and understanding auxiliary information which is correlated to the model but difficult to be quantified into the mathematical model. For example, groundwater recharge and discharge (R&D) processes are known to relate to multiple information sources such as soil type, river and lake location, irrigation patterns and land use. Although hydrologists have been trying to understand and model the interaction between each of these information sources and R&D processes, it is extremely difficult to quantify their correlations using a universal approach due to the complexity of the processes, the spatiotemporal distribution and uncertainty. There is currently no single method capable of estimating R&D rates and patterns for all practical applications. Chamberlin (1890) recommended use of "multiple working hypotheses" (alternative conceptual models) for rapid advancement in understanding of applied and theoretical problems. Therefore, cross analyzing R&D rates and patterns from various estimation methods and related field information will likely be superior to using only a single estimation method. We have developed the Pattern Recognition Utility (PRU), to help GIS users recognize spatial patterns from noisy 2D image. This GIS plug-in utility has been applied to help hydrogeologists establish alternative R&D conceptual models in a more efficient way than conventional methods. The PRU uses numerical methods and image processing algorithms to estimate and visualize shallow R&D patterns and rates. It can provide a fast initial estimate prior to planning labor intensive and time consuming field R&D measurements. Furthermore, the Spatial Pattern 2 Learn (SP2L) was developed to cross analyze results from the PRU with ancillary field information, such as land coverage, soil type, topographic maps and previous estimates. The learning process of SP2L cross examines each initially recognized R&D pattern with the ancillary spatial dataset, and then calculates a quantifiable reliability index for each R&D map using a supervised machine learning technique called decision tree. This JAVA based software package is capable of generating alternative R&D maps if the user decides to apply certain conditions recognized by the learning process. The reliability indices from SP2L will improve the traditionally subjective approach to initiating conceptual models by providing objectively quantifiable conceptual bases for further probabilistic and uncertainty analyses. Both the PRU and SP2L have been designed to be user-friendly and universal utilities for pattern recognition and learning to improve model predictions from sparse measurements by computer-assisted integration of spatially dense geospatial image data and machine learning of model dependencies.

An Active Learning Framework for Hyperspectral Image Classification Using Hierarchical Segmentation

NASA Technical Reports Server (NTRS)

Zhang, Zhou; Pasolli, Edoardo; Crawford, Melba M.; Tilton, James C.

2015-01-01

Augmenting spectral data with spatial information for image classification has recently gained significant attention, as classification accuracy can often be improved by extracting spatial information from neighboring pixels. In this paper, we propose a new framework in which active learning (AL) and hierarchical segmentation (HSeg) are combined for spectral-spatial classification of hyperspectral images. The spatial information is extracted from a best segmentation obtained by pruning the HSeg tree using a new supervised strategy. The best segmentation is updated at each iteration of the AL process, thus taking advantage of informative labeled samples provided by the user. The proposed strategy incorporates spatial information in two ways: 1) concatenating the extracted spatial features and the original spectral features into a stacked vector and 2) extending the training set using a self-learning-based semi-supervised learning (SSL) approach. Finally, the two strategies are combined within an AL framework. The proposed framework is validated with two benchmark hyperspectral datasets. Higher classification accuracies are obtained by the proposed framework with respect to five other state-of-the-art spectral-spatial classification approaches. Moreover, the effectiveness of the proposed pruning strategy is also demonstrated relative to the approaches based on a fixed segmentation.

"Wherever You Go, You Will Be a Polis": Spatial Practices and Political Education in Computer-Supported Collaborative Learning Discussions

ERIC Educational Resources Information Center

Slakmon, Benzi; Schwarz, Baruch B.

2017-01-01

The aim of this article is to increase understanding of the development of spatial practices in virtual learning environments. The spatial change and development in 38 small-group e-discussions taken from a data set of a yearlong 8th-grade humanities course are described and analyzed. We show that the focus on spatial changes in computer-supported…

Spatial learning in the genetically heterogeneous NIH-HS rat stock and RLA-I/RHA-I rats: revisiting the relationship with unconditioned and conditioned anxiety.

PubMed

Martínez-Membrives, Esther; López-Aumatell, Regina; Blázquez, Gloria; Cañete, Toni; Tobeña, Adolf; Fernández-Teruel, Alberto

2015-05-15

To characterize learning/memory profiles for the first time in the genetically heterogeneous NIH-HS rat stock, and to examine whether these are associated with anxiety, we evaluated NIH-HS rats for spatial learning/memory in the Morris water maze (MWM) and in the following anxiety/fear tests: the elevated zero-maze (ZM; unconditioned anxiety), a context-conditioned fear test and the acquisition of two-way active avoidance (conditioned anxiety). NIH-HS rats were compared with the Roman High- (RHA-I) and Low-Avoidance (RLA-I) rat strains, given the well-known differences between the Roman strains/lines in anxiety-related behavior and in spatial learning/memory. The results show that: (i) As expected, RLA-I rats were more anxious in the ZM test, displayed more frequent context-conditioned freezing episodes and fewer avoidances than RHA-I rats. (ii) Scores of NIH-HS rats in these tests/tasks mostly fell in between those of the Roman rat strains, and were usually closer to the values of the RLA-I strain. (iii) Pigmented NIH-HS (only a small part of NIH-HS rats were albino) rats were the best spatial learners and displayed better spatial memory than the other three (RHA-I, RLA-I and NIH-HS albino) groups. (iv) Albino NIH-HS and RLA-I rats also showed better learning/memory than the RHA-I strain. (v) Within the NIH-HS stock, the most anxious rats in the ZM test presented the best learning and/or memory efficiency (regardless of pigmentation). In summary, NIH-HS rats display a high performance in spatial learning/memory tasks and a passive coping strategy when facing conditioned conflict situations. In addition, unconditioned anxiety in NIH-HS rats predicts better spatial learning/memory. Copyright © 2015 Elsevier Inc. All rights reserved.

Biphasic effect of citral, a flavoring and scenting agent, on spatial learning and memory in rats.

PubMed

Yang, Zheqiong; Xi, Jinlei; Li, Jihong; Qu, Wen

2009-10-01

Although some central effects of citral have been reported, cognitive effects on spatial memory have not been investigated. The evidence showed that citral can regulate the synthesis of retinoic acid (RA), which exerts a vital function in the development and maintenance of spatial memory. In this study, we applied Morris water maze to test the effect of citral on animals' spatial learning and memory. To elucidate the mechanism of this effect, we also measured the retinoic acid concentration in rats' hippocampus by high performance liquid chromatography (HPLC). Our data implied biphasic effects of citral. The low dose (0.1 mg/kg) of citral improved the spatial learning capability, and enhanced the spatial reference memory of rats, whereas the high dose (1.0 mg/kg) was like to produce the opposite effects. Meanwhile, the low dose of citral increased the hippocampal retinoic acid concentration, while the high dose decreased it. Due to the quick elimination and non-bioaccumulation in the body, effects of citral on spatial memory in this study seemed to be indirect actions. The change in hippocampal retinoic acid concentration induced by different doses of citral might be responsible for the biphasic effect of citral on spatial learning and memory.

Consortium for Atlantic Regional Assessment: information tools for community adaptation to changes in climate or land use.

PubMed

Dempsey, Rachael; Fisher, Ann

2005-12-01

To inform local and regional decisions about protecting short-term and long-term quality of life, the Consortium for Atlantic Regional Assessment (CARA) provides data and tools (for the northeastern United States) that can help decision makers understand how outcomes of their decisions could be affected by potential changes in both climate and land use. On an interactive, user-friendly website, CARA has amassed data on climate (historical records and future projections for seven global climate models), land cover, and socioeconomic and environmental variables, along with tools to help decision makers tailor the data for their own decision types and locations. CARA Advisory Council stakeholders help identify what information and tools stakeholders would find most useful and how to present these; they also provide in-depth feedback for subregion case studies. General lessons include: (1) decision makers want detailed local projections for periods short enough to account for extreme events, in contrast to the broader spatial and temporal observations and projections that are available or consistent at a regional level; (2) stakeholders will not use such a website unless it is visually appealing and easy to find the information they want; (3) some stakeholders need background while others want to go immediately to data, and some want maps while others want text or tables. This article also compares what has been learned across case studies of Cape May County, New Jersey, Cape Cod, Massachusetts, and Hampton Roads, Virginia, relating specifically to sea-level rise. Lessons include: (1) groups can be affected differently by physical dangers compared with economic dangers; (2) decisions will differ according to decision makers' preferences about waiting and risk tolerance; (3) future scenarios and maps can help assess the impacts of dangers to emergency evacuation routes, homes, and infrastructure, and the natural environment; (4) residents' and decision makers' perceptions are affected by information about potential local impacts from global climate change.

On acquiring decision making skills for endovascular interventions.

PubMed

Lanzer, Peter; Prechelt, Lutz

2008-11-01

To improve interventional training we propose a staged rational approach for decision making and skill acquisition. Education and training for endovascular interventions should start to develop the learners' decision-making skills by learning from explicit representations of master interventionist's tacit decision-making knowledge through implementation of the notions of generic interventional modules, interventional strategic and tactical designs. We hope that these suggestions will encourage action, stimulate dialogue and advance the precision of our learning, procedures, practice and patient care.

Visual scanning with or without spatial uncertainty and time-sharing performance

NASA Technical Reports Server (NTRS)

Liu, Yili; Wickens, Christopher D.

1989-01-01

An experiment is reported that examines the pattern of task interference between visual scanning as a sequential and selective attention process and other concurrent spatial or verbal processing tasks. A distinction is proposed between visual scanning with or without spatial uncertainty regarding the possible differential effects of these two types of scanning on interference with other concurrent processes. The experiment required the subject to perform a simulated primary tracking task, which was time-shared with a secondary spatial or verbal decision task. The relevant information that was needed to perform the decision tasks were displayed with or without spatial uncertainty. The experiment employed a 2 x 2 x 2 design with types of scanning (with or without spatial uncertainty), expected scanning distance (low/high), and codes of concurrent processing (spatial/verbal) as the three experimental factors. The results provide strong evidence that visual scanning as a spatial exploratory activity produces greater task interference with concurrent spatial tasks than with concurrent verbal tasks. Furthermore, spatial uncertainty in visual scanning is identified to be the crucial factor in producing this differential effect.

Reference Frames during the Acquisition and Development of Spatial Memories

ERIC Educational Resources Information Center

Kelly, Jonathan W.; McNamara, Timothy P.

2010-01-01

Four experiments investigated the role of reference frames during the acquisition and development of spatial knowledge, when learning occurs incrementally across views. In two experiments, participants learned overlapping spatial layouts. Layout 1 was first studied in isolation, and Layout 2 was later studied in the presence of Layout 1. The…

Learning to Think Spatially: What Do Students "See" in Numeracy Test Items?

ERIC Educational Resources Information Center

Diezmann, Carmel M.; Lowrie, Tom

2012-01-01

Learning to think spatially in mathematics involves developing proficiency with graphics. This paper reports on 2 investigations of spatial thinking and graphics. The first investigation explored the importance of graphics as 1 of 3 communication systems (i.e. text, symbols, graphics) used to provide information in numeracy test items. The results…

Rhesus Monkeys (Macaca Mulatta) Maintain Learning Set Despite Second-Order Stimulus-Response Spatial Discontiguity

ERIC Educational Resources Information Center

Beran, Michael J.; Washburn, David A.; Rumbaugh, Duane M.

2007-01-01

In many discrimination-learning tests, spatial separation between stimuli and response loci disrupts performance in rhesus macaques. However, monkeys are unaffected by such stimulus-response spatial discontiguity when responses occur through joystick-based computerized movement of a cursor. To examine this discrepancy, five monkeys were tested on…

Effective Teaching Strategies for Gifted/Learning-Disabled Students with Spatial Strengths

ERIC Educational Resources Information Center

Mann, Rebecca L.

2006-01-01

This study sought to determine effective teaching strategies for use with high-ability students who have spatial strengths and sequential weaknesses. Gifted students with spatial strengths and weak verbal skills often struggle in the traditional classroom. Their learning style enables them to grasp complex systems and excel at higher levels of…

Visual-Spatial Art and Design Literacy as a Prelude to Aesthetic Growth

ERIC Educational Resources Information Center

Lerner, Fern

2018-01-01

In bridging ideas from the forum of visual-spatial learning with those of art and design learning, inspiration is taken from Piaget who explained that the evolution of spatial cognition occurs through perception, as well as through thought and imagination. Insights are embraced from interdisciplinary educational theorists, intertwining and…

Why do lesions in the rodent anterior thalamic nuclei cause such severe spatial deficits?

PubMed Central

Aggleton, John P.; Nelson, Andrew J.D.

2015-01-01

Lesions of the rodent anterior thalamic nuclei cause severe deficits to multiple spatial learning tasks. Possible explanations for these effects are examined, with particular reference to T-maze alternation. Anterior thalamic lesions not only impair allocentric place learning but also disrupt other spatial processes, including direction learning, path integration, and relative length discriminations, as well as aspects of nonspatial learning, e.g., temporal discriminations. Working memory tasks, such as T-maze alternation, appear particularly sensitive as they combine an array of these spatial and nonspatial demands. This sensitivity partly reflects the different functions supported by individual anterior thalamic nuclei, though it is argued that anterior thalamic lesion effects also arise from covert pathology in sites distal to the thalamus, most critically in the retrosplenial cortex and hippocampus. This two-level account, involving both local and distal lesion effects, explains the range and severity of the spatial deficits following anterior thalamic lesions. These findings highlight how the anterior thalamic nuclei form a key component in a series of interdependent systems that support multiple spatial functions. PMID:25195980

Diverting the tourists: a spatial decision-support system for tourism planning on a developing island

NASA Astrophysics Data System (ADS)

Beedasy, Jaishree; Whyatt, Duncan

Mauritius is a small island (1865 km 2) in the Indian Ocean. Tourism is the third largest economic sector of the country, after manufacturing and agriculture. A limitation of space and the island's vulnerable ecosystem warrants a rational approach to tourism development. The main problems so far have been to manipulate and integrate all the factors affecting tourism planning and to match spatial data with their relevant attributes. A Spatial Decision Support System (SDSS) for sustainable tourism planning is therefore proposed. The proposed SDSS design would include a GIS as its core component. A first GIS model has already been constructed with available data. Supporting decision-making in a spatial context is implicit in the use of GIS. However the analytical capability of the GIS has to be enhanced to solve semi-structured problems, where subjective judgements come into play. The second part of the paper deals with the choice, implementation and customisation of a relevant model to develop a specialised SDSS. Different types of models and techniques are discussed, in particular a comparison of compensatory and non-compensatory approaches to multicriteria evaluation (MCE). It is concluded that compensatory multicriteria evaluation techniques increase the scope of the present GIS model as a decision-support tool. This approach gives the user or decision-maker the flexibility to change the importance of each criterion depending on relevant objectives.

Geoscience Education Research: The Role of Collaborations with Education Researchers and Cognitive Scientists

NASA Astrophysics Data System (ADS)

Manduca, C. A.; Mogk, D. W.; Kastens, K. A.; Tikoff, B.; Shipley, T. F.; Ormand, C. J.; Mcconnell, D. A.

2011-12-01

Geoscience Education Research aims to improve geoscience teaching and learning by understanding clearly the characteristics of geoscience expertise, the path from novice to expert, and the educational practices that can speed students along this path. In addition to expertise in geoscience and education, this research requires an understanding of learning -the domain of cognitive scientists. Beginning in 2002, a series of workshops and events focused on bringing together geoscientists, education researchers, and cognitive scientists to facilitate productive geoscience education research collaborations. These activities produced reports, papers, books, websites and a blog developing a research agenda for geoscience education research at a variety of scales: articulating the nature of geoscience expertise, and the overall importance of observation and a systems approach; focusing attention on geologic time, spatial skills, field work, and complex systems; and identifying key research questions in areas where new technology is changing methods in geoscience research and education. Cognitive scientists and education researchers played critical roles in developing this agenda. Where geoscientists ask questions that spring from their rich understanding of the discipline, cognitive scientists and education researchers ask questions from their experience with teaching and learning in a wide variety of disciplines and settings. These interactions tend to crystallize the questions of highest importance in addressing challenges of geoscience learning and to identify productive targets for collaborative research. Further, they serve as effective mechanisms for bringing research techniques and results from other fields into geoscience education. Working productively at the intersection of these fields requires teams of cognitive scientists, geoscientists, and education reserachers who share enough knowledge of all three domains to have a common articulation of the research problem, to make collaborative decisions, and to collectively problem solve. The development of this shared understanding is a primary result of the past decade of work. It has been developed through geoscience hosted events like the On the Cutting Edge emerging theme workshops and the Synthesis of Research on Thinking and Learning in the Geosciences project, complementary events in cognitive science and education that include geoscientists like the Gordon Conferences on Visualization in Science & Education or the Spatial Cognition conference series, and the interactions within and among geoscience education research projects like the Spatial Intelligence and Learning Center, the GARNET project, and many others. With this common ground in place, effective collaborations that bring together deep knowledge of psychology and brain function, of educational design and testing, and of time tested learning goals, teaching methods, and measures of success can flourish. A strong and accelerating research field has emerged that spans from work on basic cognitive skills important in geoscience, to studies of specific teaching strategies.

Spatial frequency characteristics at image decision-point locations for observers with different radiological backgrounds in lung nodule detection

NASA Astrophysics Data System (ADS)

Pietrzyk, Mariusz W.; Manning, David J.; Dix, Alan; Donovan, Tim

2009-02-01

Aim: The goal of the study is to determine the spatial frequency characteristics at locations in the image of overt and covert observers' decisions and find out if there are any similarities in different observers' groups: the same radiological experience group or the same accuracy scored level. Background: The radiological task is described as a visual searching decision making procedure involving visual perception and cognitive processing. Humans perceive the world through a number of spatial frequency channels, each sensitive to visual information carried by different spatial frequency ranges and orientations. Recent studies have shown that particular physical properties of local and global image-based elements are correlated with the performance and the level of experience of human observers in breast cancer and lung nodule detections. Neurological findings in visual perception were an inspiration for wavelet applications in vision research because the methodology tries to mimic the brain processing algorithms. Methods: The wavelet approach to the set of postero-anterior chest radiographs analysis has been used to characterize perceptual preferences observers with different levels of experience in the radiological task. Psychophysical methodology has been applied to track eye movements over the image, where particular ROIs related to the observers' fixation clusters has been analysed in the spaces frame by Daubechies functions. Results: Significance differences have been found between the spatial frequency characteristics at the location of different decisions.

Selective cognitive impairments associated with NMDA receptor blockade in humans.

PubMed

Rowland, Laura M; Astur, Robert S; Jung, Rex E; Bustillo, Juan R; Lauriello, John; Yeo, Ronald A

2005-03-01

Hypofunction of the N-methyl-D-aspartate receptor (NMDAR) may be involved in the pathophysiology of schizophrenia. NMDAR antagonists like ketamine induce schizophrenia-like features in humans. In rodent studies, NMDAR antagonism impairs learning by disrupting long-term potentiation (LTP) in the hippocampus. This study investigated the effects of ketamine on spatial learning (acquisition) vs retrieval in a virtual Morris water task in humans. Verbal fluency, working memory, and learning and memory of verbal information were also assessed. Healthy human subjects participated in this double-blinded, placebo-controlled study. On two separate occasions, ketamine/placebo was administered and cognitive tasks were assessed in association with behavioral ratings. Ketamine impaired learning of spatial and verbal information but retrieval of information learned prior to drug administration was preserved. Schizophrenia-like symptoms were significantly related to spatial and verbal learning performance. Ketamine did not significantly impair attention, verbal fluency, or verbal working memory task performance. Spatial working memory was slightly impaired. In conclusion, these results provide evidence for ketamine's differential impairment of verbal and spatial learning vs retrieval. By using the Morris water task, which is hippocampal-dependent, this study helps bridge the gap between nonhuman animal and human NMDAR antagonism research. Impaired cognition is a core feature of schizophrenia. A better understanding of NMDA antagonism, its physiological and cognitive consequences, may provide improved models of psychosis and cognitive therapeutics.

The Teaching Decisions Simulation: An Interactive Vehicle for Mapping Teaching Decisions.

ERIC Educational Resources Information Center

Strang, Harold R.

1996-01-01

Describes the Teaching Decisions Simulation, a program that allows participants to make decisions regarding lesson plan activities and student and teacher spatial arrangement or interactions. Postlesson feedback includes variables such as completion time and performance measures. Experienced teachers exhibited more deliberation in completing the…

Road Network State Estimation Using Random Forest Ensemble Learning

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

Hou, Yi; Edara, Praveen; Chang, Yohan

Network-scale travel time prediction not only enables traffic management centers (TMC) to proactively implement traffic management strategies, but also allows travelers make informed decisions about route choices between various origins and destinations. In this paper, a random forest estimator was proposed to predict travel time in a network. The estimator was trained using two years of historical travel time data for a case study network in St. Louis, Missouri. Both temporal and spatial effects were considered in the modeling process. The random forest models predicted travel times accurately during both congested and uncongested traffic conditions. The computational times for themore » models were low, thus useful for real-time traffic management and traveler information applications.« less

Enhancing Learning Outcomes with an Interactive Knowledge-Based Learning Environment Providing Narrative Feedback

ERIC Educational Resources Information Center

Stranieri, Andrew; Yearwood, John

2008-01-01

This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a…

Understanding Teachers' Professional Learning Goals from Their Current Professional Concerns

ERIC Educational Resources Information Center

Louws, Monika L.; Meirink, Jacobiene A.; van Veen, Klaas; van Driel, Jan H.

2018-01-01

In the day-to-day workplace teachers direct their own learning, but little is known about what drives their decisions about what they would like to learn. These decisions are assumed to be influenced by teachers' current professional concerns. Also, teachers in different professional life phases have different reasons for engaging in professional…

Becoming a high-fidelity - super - imitator: what are the contributions of social and individual learning?

PubMed

Subiaul, Francys; Patterson, Eric M; Schilder, Brian; Renner, Elizabeth; Barr, Rachel

2015-11-01

In contrast to other primates, human children's imitation performance goes from low to high fidelity soon after infancy. Are such changes associated with the development of other forms of learning? We addressed this question by testing 215 children (26-59 months) on two social conditions (imitation, emulation) - involving a demonstration - and two asocial conditions (trial-and-error, recall) - involving individual learning - using two touchscreen tasks. The tasks required responding to either three different pictures in a specific picture order (Cognitive: Airplane→Ball→Cow) or three identical pictures in a specific spatial order (Motor-Spatial: Up→Down→Right). There were age-related improvements across all conditions and imitation, emulation and recall performance were significantly better than trial-and-error learning. Generalized linear models demonstrated that motor-spatial imitation fidelity was associated with age and motor-spatial emulation performance, but cognitive imitation fidelity was only associated with age. While this study provides evidence for multiple imitation mechanisms, the development of one of those mechanisms - motor-spatial imitation - may be bootstrapped by the development of another social learning skill - motor-spatial emulation. Together, these findings provide important clues about the development of imitation, which is arguably a distinctive feature of the human species. © 2014 John Wiley & Sons Ltd.

Smad4 SUMOylation is essential for memory formation through upregulation of the skeletal myopathy gene TPM2.

PubMed

Hsu, Wei L; Ma, Yun L; Liu, Yen C; Lee, Eminy H Y

2017-11-28

Smad4 is a critical effector of TGF-β signaling that regulates a variety of cellular functions. However, its role in the brain has rarely been studied. Here, we examined the molecular mechanisms underlying the post-translational regulation of Smad4 function by SUMOylation, and its role in spatial memory formation. In the hippocampus, Smad4 is SUMOylated by the E3 ligase PIAS1 at Lys-113 and Lys-159. Both spatial training and NMDA injection enhanced Smad4 SUMOylation. Inhibition of Smad4 SUMOylation impaired spatial learning and memory in rats by downregulating TPM2, a gene associated with skeletal myopathies. Similarly, knockdown of TPM2 expression impaired spatial learning and memory, while TPM2 mRNA and protein expression increased after spatial training. Among the TPM2 mutations associated with skeletal myopathies, the TPM2E122K mutation was found to reduce TPM2 expression and impair spatial learning and memory in rats. We have identified a novel role of Smad4 SUMOylation and TPM2 in learning and memory formation. These results suggest that patients with skeletal myopathies who carry the TPM2E122K mutation may also have deficits in learning and memory functions.

Decision making under uncertainty in a spiking neural network model of the basal ganglia.

PubMed

Héricé, Charlotte; Khalil, Radwa; Moftah, Marie; Boraud, Thomas; Guthrie, Martin; Garenne, André

2016-12-01

The mechanisms of decision-making and action selection are generally thought to be under the control of parallel cortico-subcortical loops connecting back to distinct areas of cortex through the basal ganglia and processing motor, cognitive and limbic modalities of decision-making. We have used these properties to develop and extend a connectionist model at a spiking neuron level based on a previous rate model approach. This model is demonstrated on decision-making tasks that have been studied in primates and the electrophysiology interpreted to show that the decision is made in two steps. To model this, we have used two parallel loops, each of which performs decision-making based on interactions between positive and negative feedback pathways. This model is able to perform two-level decision-making as in primates. We show here that, before learning, synaptic noise is sufficient to drive the decision-making process and that, after learning, the decision is based on the choice that has proven most likely to be rewarded. The model is then submitted to lesion tests, reversal learning and extinction protocols. We show that, under these conditions, it behaves in a consistent manner and provides predictions in accordance with observed experimental data.

Excitotoxic lesions of the infralimbic, but not prelimbic cortex facilitate reversal of appetitive discriminative context conditioning: the role of the infralimbic cortex in context generalization

PubMed Central

Ashwell, Rachel; Ito, Rutsuko

2014-01-01

The prelimbic and infralimbic regions of the rat medial prefrontal cortex (mPFC) are important components of the limbic cortico-striatal circuit, receiving converging projections from the hippocampus (HPC) and amygdala. Mounting evidence points to these regions having opposing roles in the regulation of the expression of contextual fear and context-induced cocaine-seeking. To investigate this functional differentiation in motivated behavior further, this study employed a novel radial maze task previously shown to be dependent on the integrity of the hippocampus and its functional connection to the nucleus accumbens (NAc) shell, to investigate the effects of selective excitotoxic lesions of the prelimbic (PL) and infralimbic (IL) upon the spatial contextual control over reward learning. To this end, rats were trained to develop discriminative responding towards a reward-associated discrete cue presented in three out of six spatial locations (3 arms out of 6 radial maze arms), and to avoid the same discrete cue presented in the other three spatial locations. Once acquired, the reward contingencies of the spatial locations were reversed, such that responding to the cue presented in a previously rewarded location was no longer rewarded. Furthermore, the acquisition of spatial learning was probed separately using conditioned place preference (CPP) and the monitoring of arm selection at the beginning of each training session. Lesions of the PL transiently attenuated the acquisition of the initial cue approach training and spatial learning, while leaving reversal learning intact. In contrast, IL lesions led to a significantly superior performance of spatial context-dependent discriminative cue approach and reversal learning, in the absence of a significant preference for the new reward-associated spatial locations. These results indicate that the PL and IL have functionally dissociative, and potentially opposite roles in the regulation of spatial contextual control over appetitive learning. PMID:24616678

Developing an Initial Learning Progression for the Use of Evidence in Decision-Making Contexts

ERIC Educational Resources Information Center

Bravo-Torija, Beatriz; Jiménez-Aleixandre, María-Pilar

2018-01-01

This paper outlines an initial learning progression for the use of evidence to support scientific arguments in the context of decision-making. Use of evidence is a central feature of knowledge evaluation and, therefore, of argumentation. The proposal is based on the literature on argumentation and use of evidence in decision-making contexts. The…

An Examination of the Effects of Career Development Courses on Career Decision-Making Self-Efficacy, Adjustment to College, Learning Integration, and Academic Success

ERIC Educational Resources Information Center

Hansen, Michele J.; Pedersen, Joan S.

2012-01-01

This study investigated the effects of career development courses on career decision-making self-efficacy (CDMSE), college adjustment, learning integration, academic achievement, and retention among undecided undergraduates. It also investigated the effects of course format on career decision-making abilities and academic success outcomes and…

Exploring the Learning from an Enterprise Simulation.

ERIC Educational Resources Information Center

Sawyer, John E.; Gopinath, C.

1999-01-01

A computer simulation used in teams by 151 business students tested their ability to translate strategy into decisions. Over eight weeks, the experiential learning activity encouraged strategic decision making and group behavior consistent with long-term strategy. (SK)

Spatial learning while navigating with severely degraded viewing: The role of attention and mobility monitoring

PubMed Central

Rand, Kristina M.; Creem-Regehr, Sarah H.; Thompson, William B.

2015-01-01

The ability to navigate without getting lost is an important aspect of quality of life. In five studies, we evaluated how spatial learning is affected by the increased demands of keeping oneself safe while walking with degraded vision (mobility monitoring). We proposed that safe low-vision mobility requires attentional resources, providing competition for those needed to learn a new environment. In Experiments 1 and 2 participants navigated along paths in a real-world indoor environment with simulated degraded vision or normal vision. Memory for object locations seen along the paths was better with normal compared to degraded vision. With degraded vision, memory was better when participants were guided by an experimenter (low monitoring demands) versus unguided (high monitoring demands). In Experiments 3 and 4, participants walked while performing an auditory task. Auditory task performance was superior with normal compared to degraded vision. With degraded vision, auditory task performance was better when guided compared to unguided. In Experiment 5, participants performed both the spatial learning and auditory tasks under degraded vision. Results showed that attention mediates the relationship between mobility-monitoring demands and spatial learning. These studies suggest that more attention is required and spatial learning is impaired when navigating with degraded viewing. PMID:25706766

Structural and functional neuroplasticity in human learning of spatial routes.

PubMed

Keller, Timothy A; Just, Marcel Adam

2016-01-15

Recent findings with both animals and humans suggest that decreases in microscopic movements of water in the hippocampus reflect short-term neuroplasticity resulting from learning. Here we examine whether such neuroplastic structural changes concurrently alter the functional connectivity between hippocampus and other regions involved in learning. We collected both diffusion-weighted images and fMRI data before and after humans performed a 45min spatial route-learning task. Relative to a control group with equal practice time, there was decreased diffusivity in the posterior-dorsal dentate gyrus of the left hippocampus in the route-learning group accompanied by increased synchronization of fMRI-measured BOLD signal between this region and cortical areas, and by changes in behavioral performance. These concurrent changes characterize the multidimensionality of neuroplasticity as it enables human spatial learning. Copyright © 2015 Elsevier Inc. All rights reserved.

How Spatial Abilities and Dynamic Visualizations Interplay When Learning Functional Anatomy with 3D Anatomical Models

ERIC Educational Resources Information Center

Berney, Sandra; Bétrancourt, Mireille; Molinari, Gaëlle; Hoyek, Nady

2015-01-01

The emergence of dynamic visualizations of three-dimensional (3D) models in anatomy curricula may be an adequate solution for spatial difficulties encountered with traditional static learning, as they provide direct visualization of change throughout the viewpoints. However, little research has explored the interplay between learning material…

Attending Globally or Locally: Incidental Learning of Optimal Visual Attention Allocation

ERIC Educational Resources Information Center

Beck, Melissa R.; Goldstein, Rebecca R.; van Lamsweerde, Amanda E.; Ericson, Justin M.

2018-01-01

Attention allocation determines the information that is encoded into memory. Can participants learn to optimally allocate attention based on what types of information are most likely to change? The current study examined whether participants could incidentally learn that changes to either high spatial frequency (HSF) or low spatial frequency (LSF)…

Sharp wave ripples during learning stabilize hippocampal spatial map

PubMed Central

Roux, Lisa; Hu, Bo; Eichler, Ronny; Stark, Eran; Buzsáki, György

2017-01-01

Cognitive representation of the environment requires a stable hippocampal map but the mechanisms maintaining map representation are unknown. Because sharp wave-ripples (SPW-R) orchestrate both retrospective and prospective spatial information, we hypothesized that disrupting neuronal activity during SPW-Rs affects spatial representation. Mice learned daily a new set of three goal locations on a multi-well maze. We used closed-loop SPW-R detection at goal locations to trigger optogenetic silencing of a subset of CA1 pyramidal neurons. Control place cells (non-silenced or silenced outside SPW-Rs) largely maintained the location of their place fields after learning and showed increased spatial information content. In contrast, the place fields of SPW-R-silenced place cells remapped, and their spatial information remained unaltered. SPW-R silencing did not impact the firing rates or the proportions of place cells. These results suggest that interference with SPW-R-associated activity during learning prevents the stabilization and refinement of the hippocampal map. PMID:28394323

Cognitive styles and mental rotation ability in map learning.

PubMed

Pazzaglia, Francesca; Moè, Angelica

2013-11-01

In inspecting, learning and reproducing a map, a wide range of abilities is potentially involved. This study examined the role of mental rotation (MR) and verbal ability, together with that of cognitive styles in map learning. As regards cognitive styles, the traditional distinction between verbalizers and visualizers has been taken into account, together with a more recent distinction between two styles of visualization: spatial and object. One hundred and seven participants filled in two questionnaires on cognitive styles: the Verbalizer-Visualizer Questionnaire (Richardson in J Ment Imag 1:109-125, 1977) and the Object-Spatial Imagery Questionnaire (Blajenkova et al. in Appl Cogn Psych 20:239-263, 2006), performed MR and verbal tests, learned two maps, and were then tested for their recall. It was found that MR ability and cognitive styles played a role in predicting map learning, with some distinctions within cognitive styles: verbal style favoured learning of one of the two maps (the one rich in verbal labels), which in turn was disadvantaged by the adoption of spatial style. Conversely, spatial style predicted learning of the other map, rich in visual features. The discussion focuses on implications for cognitive psychology and everyday cognition.

Information gathering, management and transferring for geospatial intelligence - A conceptual approach to create a spatial data infrastructure

NASA Astrophysics Data System (ADS)

Nunes, Paulo; Correia, Anacleto; Teodoro, M. Filomena

2017-06-01

Since long ago, information is a key factor for military organizations. In military context the success of joint and combined operations depends on the accurate information and knowledge flow concerning the operational theatre: provision of resources, environment evolution, targets' location, where and when an event will occur. Modern military operations cannot be conceive without maps and geospatial information. Staffs and forces on the field request large volume of information during the planning and execution process, horizontal and vertical geospatial information integration is critical for decision cycle. Information and knowledge management are fundamental to clarify an environment full of uncertainty. Geospatial information (GI) management rises as a branch of information and knowledge management, responsible for the conversion process from raw data collect by human or electronic sensors to knowledge. Geospatial information and intelligence systems allow us to integrate all other forms of intelligence and act as a main platform to process and display geospatial-time referenced events. Combining explicit knowledge with person know-how to generate a continuous learning cycle that supports real time decisions, mitigates the influences of fog of war and provides the knowledge supremacy. This paper presents the analysis done after applying a questionnaire and interviews about the GI and intelligence management in a military organization. The study intended to identify the stakeholder's requirements for a military spatial data infrastructure as well as the requirements for a future software system development.

The role of visualization in learning from computer-based images

NASA Astrophysics Data System (ADS)

Piburn, Michael D.; Reynolds, Stephen J.; McAuliffe, Carla; Leedy, Debra E.; Birk, James P.; Johnson, Julia K.

2005-05-01

Among the sciences, the practice of geology is especially visual. To assess the role of spatial ability in learning geology, we designed an experiment using: (1) web-based versions of spatial visualization tests, (2) a geospatial test, and (3) multimedia instructional modules built around QuickTime Virtual Reality movies. Students in control and experimental sections were administered measures of spatial orientation and visualization, as well as a content-based geospatial examination. All subjects improved significantly in their scores on spatial visualization and the geospatial examination. There was no change in their scores on spatial orientation. A three-way analysis of variance, with the geospatial examination as the dependent variable, revealed significant main effects favoring the experimental group and a significant interaction between treatment and gender. These results demonstrate that spatial ability can be improved through instruction, that learning of geological content will improve as a result, and that differences in performance between the genders can be eliminated.

Learning Low-Rank Decomposition for Pan-Sharpening With Spatial-Spectral Offsets.

PubMed

Yang, Shuyuan; Zhang, Kai; Wang, Min

2017-08-25

Finding accurate injection components is the key issue in pan-sharpening methods. In this paper, a low-rank pan-sharpening (LRP) model is developed from a new perspective of offset learning. Two offsets are defined to represent the spatial and spectral differences between low-resolution multispectral and high-resolution multispectral (HRMS) images, respectively. In order to reduce spatial and spectral distortions, spatial equalization and spectral proportion constraints are designed and cast on the offsets, to develop a spatial and spectral constrained stable low-rank decomposition algorithm via augmented Lagrange multiplier. By fine modeling and heuristic learning, our method can simultaneously reduce spatial and spectral distortions in the fused HRMS images. Moreover, our method can efficiently deal with noises and outliers in source images, for exploring low-rank and sparse characteristics of data. Extensive experiments are taken on several image data sets, and the results demonstrate the efficiency of the proposed LRP.

Learning from the Past, Looking to the Future: Modeling Social Unrest in Karachi, Pakistan

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

Olson, Jarrod; Kurzrok, Andrew J.; Hund, Gretchen

Social unrest represents a major challenge for policy makers around the globe, as it can quickly escalate from small scale disturbances to highly public protests, riots and even civil war. This research was motivated by a need to understand social instability and to unpack the comments made during a spring 2013 conference hosted by Pacific Northwest National Laboratory’s Center for Global Security and the U.S. Institute for Peace, where policymakers noted that models considering social instability are often not suitable for decision-making. This analysis shows that existing state level models of instability could be improved in spatial scale to themore » city level, even without significantly improved data access. Better data would make this analysis more complete and likely improve the quality of the model. Another challenge with incorporating modeling into decision-making is the need to understand uncertainty in a model. Policy makers are frequently tasked with making decisions without a clear outcome, so characterization of uncertainty is critical. This report describes the work and findings of the project. It took place in three phases: a literature review of social stability research, a “hindsight scan” that looked at historical data, and a “foresight scan” looking at future scenarios.« less

Spatial effects on hybrid electric vehicle adoption

DOE PAGES

Liu, Xiaoli; Roberts, Matthew C.; Sioshansi, Ramteen

2017-03-08

This paper examines spatial effects on hybrid-electric vehicle (HEV) adoption. This is in contrast to most existing analyses, which concentrate on analyzing socioeconomic factors and demographics. This paper uses a general spatial model to estimate the strength of ‘neighbor effects’ on HEV adoption—namely that each consumer’s HEV-adoption decision can be influenced by the HEV-adoption decisions of geographic neighbors. We use detailed census tract-level demographic data from the 2010 United States Census and the 2012 American Community Survey and vehicle registration data collected by the Ohio Bureau of Motor Vehicles. We find that HEV adoption exhibits significant spatial effects. We furthermore » conduct a time-series analysis and show that historical HEV adoption has a spatial effect on future adoption. Lastly, these results suggest that HEVs may appear in more dense clusters than models that do not consider spatial effects predict.« less

Interpatch foraging in honeybees-rational decision making at secondary hubs based upon time and motivation.

PubMed

Najera, Daniel A; McCullough, Erin L; Jander, Rudolf

2012-11-01

For honeybees, Apis mellifera, the hive has been well known to function as a primary decision-making hub, a place from which foragers decide among various directions, distances, and times of day to forage efficiently. Whether foraging honeybees can make similarly complex navigational decisions from locations away from the hive is unknown. To examine whether or not such secondary decision-making hubs exist, we trained bees to forage at four different locations. Specifically, we trained honeybees to first forage to a distal site "CT" 100 m away from the hive; if food was present, they fed and then chose to go home. If food was not present, the honeybees were trained to forage to three auxiliary sites, each at a different time of the day: A in the morning, B at noon, and C in the afternoon. The foragers learned to check site CT for food first and then efficiently depart to the correct location based upon the time of day if there was no food at site CT. Thus, the honeybees were able to cognitively map motivation, time, and five different locations (Hive, CT, A, B, and C) in two spatial dimensions; these are the contents of the cognitive map used by the honeybees here. While at site CT, we verified that the honeybees could choose between 4 different directions (to A, B, C, and the Hive) and thus label it as a secondary decision-making hub. The observed decision making uncovered here is inferred to constitute genuine logical operations, involving a branched structure, based upon the premises of motivational state, and spatiotemporal knowledge.

Effects of testosterone on spatial learning and memory in adult male rats

PubMed Central

Spritzer, Mark D.; Daviau, Emily D.; Coneeny, Meagan K.; Engelman, Shannon M.; Prince, W. Tyler; Rodriguez-Wisdom, Karlye N.

2011-01-01

A male advantage over females for spatial tasks has been well documented in both humans and rodents, but it remains unclear how the activational effects of testosterone influence spatial ability in males. In a series of experiments, we tested how injections of testosterone influenced the spatial working and reference memory of castrated male rats. In the eight-arm radial maze, testosterone injections (0.500 mg/rat) reduced the number of working memory errors during the early blocks of testing but had no effect on the number of reference memory errors relative to the castrated control group. In a reference memory version of the Morris water maze, injections of a wide range of testosterone doses (0.0625-1.000 mg/rat) reduced path lengths to the hidden platform, indicative of improved spatial learning. This improved learning was independent of testosterone dose, with all treatment groups showing better performance than the castrated control males. Furthermore, this effect was only observed when rats were given testosterone injections starting seven days prior to water maze testing and not when injections were given only on the testing days. We also observed that certain doses of testosterone (0.250 and 1.000 mg/rat) increased perseverative behavior in a reversal-learning task. Finally, testosterone did not have a clear effect on spatial working memory in the Morris water maze, although intermediate doses seemed to optimize performance. Overall, the results indicate that testosterone can have positive activational effects on spatial learning and memory, but the duration of testosterone replacement and the nature of the spatial task modify these effects. PMID:21295035

Reference frames in allocentric representations are invariant across static and active encoding

PubMed Central

Chan, Edgar; Baumann, Oliver; Bellgrove, Mark A.; Mattingley, Jason B.

2013-01-01

An influential model of spatial memory—the so-called reference systems account—proposes that relationships between objects are biased by salient axes (“frames of reference”) provided by environmental cues, such as the geometry of a room. In this study, we sought to examine the extent to which a salient environmental feature influences the formation of spatial memories when learning occurs via a single, static viewpoint and via active navigation, where information has to be integrated across multiple viewpoints. In our study, participants learned the spatial layout of an object array that was arranged with respect to a prominent environmental feature within a virtual arena. Location memory was tested using judgments of relative direction. Experiment 1A employed a design similar to previous studies whereby learning of object-location information occurred from a single, static viewpoint. Consistent with previous studies, spatial judgments were significantly more accurate when made from an orientation that was aligned, as opposed to misaligned, with the salient environmental feature. In Experiment 1B, a fresh group of participants learned the same object-location information through active exploration, which required integration of spatial information over time from a ground-level perspective. As in Experiment 1A, object-location information was organized around the salient environmental cue. Taken together, the findings suggest that the learning condition (static vs. active) does not affect the reference system employed to encode object-location information. Spatial reference systems appear to be a ubiquitous property of spatial representations, and might serve to reduce the cognitive demands of spatial processing. PMID:24009595

Distinct discrimination learning strategies and their relation with spatial memory and attentional control in 4- to 14-year-olds.

PubMed

Schmittmann, Verena D; van der Maas, Han L J; Raijmakers, Maartje E J

2012-04-01

Behavioral, psychophysiological, and neuropsychological studies have revealed large developmental differences in various learning paradigms where learning from positive and negative feedback is essential. The differences are possibly due to the use of distinct strategies that may be related to spatial working memory and attentional control. In this study, strategies in performing a discrimination learning task were distinguished in a cross-sectional sample of 302 children from 4 to 14 years of age. The trial-by-trial accuracy data were analyzed with mathematical learning models. The best-fitting model revealed three learning strategies: hypothesis testing, slow abrupt learning, and nonlearning. The proportion of hypothesis-testing children increased with age. Nonlearners were present only in the youngest age group. Feature preferences for the irrelevant dimension had a detrimental effect on performance in the youngest age group. The executive functions spatial working memory and attentional control significantly predicted posterior learning strategy probabilities after controlling for age. Copyright © 2011 Elsevier Inc. All rights reserved.

Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention and oscillations.

PubMed

Grossberg, Stephen; Pilly, Praveen K

2014-02-05

A neural model proposes how entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps (SOMs). The model responds to realistic rat navigational trajectories by learning both grid cells with hexagonal grid firing fields of multiple spatial scales, and place cells with one or more firing fields, that match neurophysiological data about their development in juvenile rats. Both grid and place cells can develop by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model's parsimonious properties include: similar ring attractor mechanisms process linear and angular path integration inputs that drive map learning; the same SOM mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus (HC) may use mechanisms homologous to those for temporal learning through lateral entorhinal cortex to HC ('neural relativity'). The model clarifies how top-down HC-to-entorhinal attentional mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells, and explains data about theta, beta and gamma oscillations. The article also compares the three main types of grid cell models in the light of recent data.

Neurobiological and Endocrine Correlates of Individual Differences in Spatial Learning Ability

PubMed Central

Sandi, Carmen; Cordero, M. Isabel; Merino, José J.; Kruyt, Nyika D.; Regan, Ciaran M.; Murphy, Keith J.

2004-01-01

The polysialylated neural cell adhesion molecule (PSA-NCAM) has been implicated in activity-dependent synaptic remodeling and memory formation. Here, we questioned whether training-induced modulation of PSA-NCAM expression might be related to individual differences in spatial learning abilities. At 12 h posttraining, immunohistochemical analyses revealed a learning-induced up-regulation of PSA-NCAM in the hippocampal dentate gyrus that was related to the spatial learning abilities displayed by rats during training. Specifically, a positive correlation was found between latency to find the platform and subsequent activated PSA levels, indicating that greater induction of polysialylation was observed in rats with the slower acquisition curve. At posttraining times when no learning-associated activation of PSA was observed, no such correlation was found. Further experiments revealed that performance in the massed water maze training is related to a pattern of spatial learning and memory abilities, and to learning-related glucocorticoid responsiveness. Taken together, our findings suggest that the learning-related neural circuits of fast learners are better suited to solving the water maze task than those of slow learners, the latter relying more on structural reorganization to form memory, rather than the relatively economic mechanism of altering synaptic efficacy that is likely used by the former. PMID:15169853

Neurobiological and endocrine correlates of individual differences in spatial learning ability.

PubMed

Sandi, Carmen; Cordero, M Isabel; Merino, José J; Kruyt, Nyika D; Regan, Ciaran M; Murphy, Keith J

2004-01-01

The polysialylated neural cell adhesion molecule (PSA-NCAM) has been implicated in activity-dependent synaptic remodeling and memory formation. Here, we questioned whether training-induced modulation of PSA-NCAM expression might be related to individual differences in spatial learning abilities. At 12 h posttraining, immunohistochemical analyses revealed a learning-induced up-regulation of PSA-NCAM in the hippocampal dentate gyrus that was related to the spatial learning abilities displayed by rats during training. Specifically, a positive correlation was found between latency to find the platform and subsequent activated PSA levels, indicating that greater induction of polysialylation was observed in rats with the slower acquisition curve. At posttraining times when no learning-associated activation of PSA was observed, no such correlation was found. Further experiments revealed that performance in the massed water maze training is related to a pattern of spatial learning and memory abilities, and to learning-related glucocorticoid responsiveness. Taken together, our findings suggest that the learning-related neural circuits of fast learners are better suited to solving the water maze task than those of slow learners, the latter relying more on structural reorganization to form memory, rather than the relatively economic mechanism of altering synaptic efficacy that is likely used by the former.

Web-based GIS for spatial pattern detection: application to malaria incidence in Vietnam.

PubMed

Bui, Thanh Quang; Pham, Hai Minh

2016-01-01

There is a great concern on how to build up an interoperable health information system of public health and health information technology within the development of public information and health surveillance programme. Technically, some major issues remain regarding to health data visualization, spatial processing of health data, health information dissemination, data sharing and the access of local communities to health information. In combination with GIS, we propose a technical framework for web-based health data visualization and spatial analysis. Data was collected from open map-servers and geocoded by open data kit package and data geocoding tools. The Web-based system is designed based on Open-source frameworks and libraries. The system provides Web-based analyst tool for pattern detection through three spatial tests: Nearest neighbour, K function, and Spatial Autocorrelation. The result is a web-based GIS, through which end users can detect disease patterns via selecting area, spatial test parameters and contribute to managers and decision makers. The end users can be health practitioners, educators, local communities, health sector authorities and decision makers. This web-based system allows for the improvement of health related services to public sector users as well as citizens in a secure manner. The combination of spatial statistics and web-based GIS can be a solution that helps empower health practitioners in direct and specific intersectional actions, thus provide for better analysis, control and decision-making.

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

PubMed

Grossberg, Stephen

2015-09-24

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

N-methyl-d-aspartate receptors, learning and memory: chronic intraventricular infusion of the NMDA receptor antagonist d-AP5 interacts directly with the neural mechanisms of spatial learning.

PubMed

Morris, R G M; Steele, R J; Bell, J E; Martin, S J

2013-03-01

Three experiments were conducted to contrast the hypothesis that hippocampal N-methyl-d-aspartate (NMDA) receptors participate directly in the mechanisms of hippocampus-dependent learning with an alternative view that apparent impairments of learning induced by NMDA receptor antagonists arise because of drug-induced neuropathological and/or sensorimotor disturbances. In experiment 1, rats given a chronic i.c.v. infusion of d-AP5 (30 mm) at 0.5 μL/h were selectively impaired, relative to aCSF-infused animals, in place but not cued navigation learning when they were trained during the 14-day drug infusion period, but were unimpaired on both tasks if trained 11 days after the minipumps were exhausted. d-AP5 caused sensorimotor disturbances in the spatial task, but these gradually worsened as the animals failed to learn. Histological assessment of potential neuropathological changes revealed no abnormalities in d-AP5-treated rats whether killed during or after chronic drug infusion. In experiment 2, a deficit in spatial learning was also apparent in d-AP5-treated rats trained on a spatial reference memory task involving two identical but visible platforms, a task chosen and shown to minimise sensorimotor disturbances. HPLC was used to identify the presence of d-AP5 in selected brain areas. In Experiment 3, rats treated with d-AP5 showed a delay-dependent deficit in spatial memory in the delayed matching-to-place protocol for the water maze. These data are discussed with respect to the learning mechanism and sensorimotor accounts of the impact of NMDA receptor antagonists on brain function. We argue that NMDA receptor mechanisms participate directly in spatial learning. © 2013 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

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

ERIC Educational Resources Information Center

Mungas, Dan; And Others

1991-01-01

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

Spatial abstraction for autonomous robot navigation.

PubMed

Epstein, Susan L; Aroor, Anoop; Evanusa, Matthew; Sklar, Elizabeth I; Parsons, Simon

2015-09-01

Optimal navigation for a simulated robot relies on a detailed map and explicit path planning, an approach problematic for real-world robots that are subject to noise and error. This paper reports on autonomous robots that rely on local spatial perception, learning, and commonsense rationales instead. Despite realistic actuator error, learned spatial abstractions form a model that supports effective travel.

Rectangular Array Model Supporting Students' Spatial Structuring in Learning Multiplication

ERIC Educational Resources Information Center

Shanty, Nenden Octavarulia; Wijaya, Surya

2012-01-01

We examine how rectangular array model can support students' spatial structuring in learning multiplication. To begin, we define what we mean by spatial structuring as the mental operation of constructing an organization or form for an object or set of objects. For that reason, the eggs problem was chosen as the starting point in which the…

Spatial Thinking Concepts in Early Grade-Level Geography Standards

ERIC Educational Resources Information Center

Anthamatten, Peter

2010-01-01

Research in the cognition and learning sciences has demonstrated that the human brain contains basic structures whose functions are to perform a variety of specific spatial reasoning tasks and that children are capable of learning basic spatial concepts at an early age. There has been a call from within geography to recognize research on spatial…

Stills, Not Full Motion, for Interactive Spatial Training: American, Turkish and Taiwanese Female Pre-Service Teachers Learn Spatial Visualization

ERIC Educational Resources Information Center

Smith, Glenn Gordon; Gerretson, Helen; Olkun, Sinan; Yuan, Yuan; Dogbey, James; Erdem, Aliye

2009-01-01

This study investigated how female elementary education pre-service teachers in the United States, Turkey and Taiwan learned spatial skills from structured activities involving discrete, as opposed to continuous, transformations in interactive computer programs, and how these activities transferred to non-related standardized tests of spatial…

Using the van Hiele K-12 Geometry Learning Theory to Modify Engineering Mechanics Instruction

ERIC Educational Resources Information Center

Sharp, Janet M.; Zachary, Loren W.

2004-01-01

Engineering students use spatial thinking when examining diagrams or models to study structure design. It is expected that most engineering students have solidified spatial thinking skills during K-12 schooling. However, according to what we know about geometry learning and teaching, spatial thinking probably needs to be explicitly taught within…

Near or far: The effect of spatial distance and vocabulary knowledge on word learning.

PubMed

Axelsson, Emma L; Perry, Lynn K; Scott, Emilly J; Horst, Jessica S

2016-01-01

The current study investigated the role of spatial distance in word learning. Two-year-old children saw three novel objects named while the objects were either in close proximity to each other or spatially separated. Children were then tested on their retention for the name-object associations. Keeping the objects spatially separated from each other during naming was associated with increased retention for children with larger vocabularies. Children with a lower vocabulary size demonstrated better retention if they saw objects in close proximity to each other during naming. This demonstrates that keeping a clear view of objects during naming improves word learning for children who have already learned many words, but keeping objects within close proximal range is better for children at earlier stages of vocabulary acquisition. The effect of distance is therefore not equal across varying vocabulary sizes. The influences of visual crowding, cognitive load, and vocabulary size on word learning are discussed. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Effects of peptides from Phascolosoma esculenta on spatial learning and memory via anti-oxidative character in mice.

PubMed

Liu, Lianliang; Cao, Jinxuan; Chen, Jiong; Zhang, Xin; Wu, Zufang; Xiang, Huan

2016-09-19

This study was aimed to evaluate effects of peptides from Phascolosoma esculenta and its ferrous-chelating peptides on spatial learning and memory in mice by Morris water maze test. 100mg/kg peptide on spatial learning and memory function about quadrant time and passing times through the platform better than 50 and 150mg/kg group during exploration period (P<0.05), without body weight between the weight and visual ability. 100mg/kg ferrous-chelating peptide group performed better ability of spatial learning and memory than 100mg/kg peptide group (P<0.05). qRT-PCR results showed that 50 and 100mg/kg administration peptide and 100mg/kg ferrous-chelating peptide can significantly improve mRNA expression of NR2A, NR2B and BDNF with oxidative stress status (GSH-Px, SOD, TAC and MDA), which explained mechanism for improving learning and memory ability in mice via anti-oxidative character. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task

PubMed Central

Mochizuki, Kei

2015-01-01

While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. PMID:26490287

The Impact of Cooperative Learning on Developing the Sixth Grade Students Decision-Making Skill and Academic Achievement

ERIC Educational Resources Information Center

Asha, Intisar K.; Al Hawi, Asma M.

2016-01-01

This study aimed at investigating the effect of cooperative learning on developing the sixth graders' decision making skill and their academic achievement. The study sample, which was selected randomly, consisted of (46) students and divided into two groups: the experimental group that taught using the cooperative learning strategy and the control…

A web-based spatial decision support system for spatial planning and governance in the Guangdong Province

NASA Astrophysics Data System (ADS)

Wu, Qitao; Zhang, Hong-ou; Chen, Fengui; Dou, Jie

2008-10-01

After three decades' rapid economic development, Guangdong province faces to thorny problems related to pollution, resource shortage and environmental deterioration. What is worse, the future accelerated development, urbanization and industrialization also comes at the cost of regional imbalance with economic gaps growing and the quality of life in different regions degrading. Development and Reform Commission of Guangdong Province (GDDRC) started a spatial planning project under the national frame in 2007. The prospective project is expected to enhance the equality of different regions and balance the economic development with environmental protection and improved sustainability. This manuscript presents the results of scientific research aiming to develop a Spatial Decision Support System (SDSS) for this spatial planning project. The system composes four modules include the User interface module (UIM), Spatial Analyze module (SAM), Database management module (DMM) and Help module (HM) base on ArcInfo, JSP/Servlet, JavaScript, MapServer, Visual C++ and Visual Basic technologies. The web-based SDSS provides a user-friendly tool for local decision makers, regional planners and other stakeholders in understanding and visualizing the different territorial dimensions of economic development against sustainable environmental and exhausted resources, and in defining, comparing and prioritizing specific territorially-based actions in order to prevent non-sustainable development and implement relevant politics.

Strategic Decision-Making Learning from Label Distributions: An Approach for Facial Age Estimation.

PubMed

Zhao, Wei; Wang, Han

2016-06-28

Nowadays, label distribution learning is among the state-of-the-art methodologies in facial age estimation. It takes the age of each facial image instance as a label distribution with a series of age labels rather than the single chronological age label that is commonly used. However, this methodology is deficient in its simple decision-making criterion: the final predicted age is only selected at the one with maximum description degree. In many cases, different age labels may have very similar description degrees. Consequently, blindly deciding the estimated age by virtue of the highest description degree would miss or neglect other valuable age labels that may contribute a lot to the final predicted age. In this paper, we propose a strategic decision-making label distribution learning algorithm (SDM-LDL) with a series of strategies specialized for different types of age label distribution. Experimental results from the most popular aging face database, FG-NET, show the superiority and validity of all the proposed strategic decision-making learning algorithms over the existing label distribution learning and other single-label learning algorithms for facial age estimation. The inner properties of SDM-LDL are further explored with more advantages.

Strategic Decision-Making Learning from Label Distributions: An Approach for Facial Age Estimation

PubMed Central

Zhao, Wei; Wang, Han

2016-01-01

Nowadays, label distribution learning is among the state-of-the-art methodologies in facial age estimation. It takes the age of each facial image instance as a label distribution with a series of age labels rather than the single chronological age label that is commonly used. However, this methodology is deficient in its simple decision-making criterion: the final predicted age is only selected at the one with maximum description degree. In many cases, different age labels may have very similar description degrees. Consequently, blindly deciding the estimated age by virtue of the highest description degree would miss or neglect other valuable age labels that may contribute a lot to the final predicted age. In this paper, we propose a strategic decision-making label distribution learning algorithm (SDM-LDL) with a series of strategies specialized for different types of age label distribution. Experimental results from the most popular aging face database, FG-NET, show the superiority and validity of all the proposed strategic decision-making learning algorithms over the existing label distribution learning and other single-label learning algorithms for facial age estimation. The inner properties of SDM-LDL are further explored with more advantages. PMID:27367691

Deep learning aided decision support for pulmonary nodules diagnosing: a review

PubMed Central

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping

2018-01-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing. PMID:29780633

Effects of dorsal hippocampus catecholamine depletion on paired-associates learning and place learning in rats.

PubMed

Roschlau, Corinna; Hauber, Wolfgang

2017-04-14

Growing evidence suggests that the catecholamine (CA) neurotransmitters dopamine and noradrenaline support hippocampus-mediated learning and memory. However, little is known to date about which forms of hippocampus-mediated spatial learning are modulated by CA signaling in the hippocampus. Therefore, in the current study we examined the effects of 6-hydroxydopamine-induced CA depletion in the dorsal hippocampus on two prominent forms of hippocampus-based spatial learning, that is learning of object-location associations (paired-associates learning) as well as learning and choosing actions based on a representation of the context (place learning). Results show that rats with CA depletion of the dorsal hippocampus were able to learn object-location associations in an automated touch screen paired-associates learning (PAL) task. One possibility to explain this negative result is that object-location learning as tested in the touchscreen PAL task seems to require relatively little hippocampal processing. Results further show that in rats with CA depletion of the dorsal hippocampus the use of a response strategy was facilitated in a T-maze spatial learning task. We suspect that impaired hippocampus CA signaling may attenuate hippocampus-based place learning and favor dorsolateral striatum-based response learning. Copyright © 2017 Elsevier B.V. All rights reserved.

Transferring control demands across incidental learning tasks – stronger sequence usage in serial reaction task after shortcut option in letter string checking

PubMed Central

Gaschler, Robert; Marewski, Julian N.; Wenke, Dorit; Frensch, Peter A.

2014-01-01

After incidentally learning about a hidden regularity, participants can either continue to solve the task as instructed or, alternatively, apply a shortcut. Past research suggests that the amount of conflict implied by adopting a shortcut seems to bias the decision for vs. against continuing instruction-coherent task processing. We explored whether this decision might transfer from one incidental learning task to the next. Theories that conceptualize strategy change in incidental learning as a learning-plus-decision phenomenon suggest that high demands to adhere to instruction-coherent task processing in Task 1 will impede shortcut usage in Task 2, whereas low control demands will foster it. We sequentially applied two established incidental learning tasks differing in stimuli, responses and hidden regularity (the alphabet verification task followed by the serial reaction task, SRT). While some participants experienced a complete redundancy in the task material of the alphabet verification task (low demands to adhere to instructions), for others the redundancy was only partial. Thus, shortcut application would have led to errors (high demands to follow instructions). The low control demand condition showed the strongest usage of the fixed and repeating sequence of responses in the SRT. The transfer results are in line with the learning-plus-decision view of strategy change in incidental learning, rather than with resource theories of self-control. PMID:25506336

Lateral, not medial, prefrontal cortex contributes to punishment and aversive instrumental learning

PubMed Central

Jean-Richard-dit-Bressel, Philip

2016-01-01

Aversive outcomes punish behaviors that cause their occurrence. The prefrontal cortex (PFC) has been implicated in punishment learning and behavior, although the exact roles for different PFC regions in instrumental aversive learning and decision-making remain poorly understood. Here, we assessed the role of the orbitofrontal (OFC), rostral agranular insular (RAIC), prelimbic (PL), and infralimbic (IL) cortex in instrumental aversive learning and decision-making. Rats that pressed two individually presented levers for pellet rewards rapidly suppressed responding to one lever if it also caused mild punishment (punished lever) but continued pressing the other lever that did not cause punishment (unpunished lever). Inactivations of OFC, RAIC, IL, or PL via the GABA agonists baclofen and muscimol (BM) had no effect on the acquisition of instrumental learning. OFC inactivations increased responding on the punished lever during expression of well-learned instrumental aversive learning, whereas RAIC inactivations increased responding on the punished lever when both levers were presented simultaneously in an unpunished choice test. There were few effects of medial PFC (PL and IL) inactivation. These results suggest that lateral PFC, notably OFC and RAIC, have complementary functions in aversive instrumental learning and decision-making; OFC is important for using established aversive instrumental memories to guide behavior away from actions that cause punishment, whereas RAIC is important for aversive decision-making under conditions of choice. PMID:27918280

Mice lacking hippocampal left-right asymmetry show non-spatial learning deficits.

PubMed

Shimbo, Akihiro; Kosaki, Yutaka; Ito, Isao; Watanabe, Shigeru

2018-01-15

Left-right asymmetry is known to exist at several anatomical levels in the brain and recent studies have provided further evidence to show that it also exists at a molecular level in the hippocampal CA3-CA1 circuit. The distribution of N-methyl-d-aspartate (NMDA) receptor NR2B subunits in the apical and basal synapses of CA1 pyramidal neurons is asymmetrical if the input arrives from the left or right CA3 pyramidal neurons. In the present study, we examined the role of hippocampal asymmetry in cognitive function using β2-microglobulin knock-out (β2m KO) mice, which lack hippocampal asymmetry. We tested β2m KO mice in a series of spatial and non-spatial learning tasks and compared the performances of β2m KO and C57BL6/J wild-type (WT) mice. The β2m KO mice appeared normal in both spatial reference memory and spatial working memory tasks but they took more time than WT mice in learning the two non-spatial learning tasks (i.e., a differential reinforcement of lower rates of behavior (DRL) task and a straight runway task). The β2m KO mice also showed less precision in their response timing in the DRL task and showed weaker spontaneous recovery during extinction in the straight runway task. These results indicate that hippocampal asymmetry is important for certain characteristics of non-spatial learning. Copyright © 2017 Elsevier B.V. All rights reserved.

Environment learning using descriptions or navigation: The involvement of working memory in young and older adults.

PubMed

Meneghetti, Chiara; Borella, Erika; Carbone, Elena; Martinelli, Massimiliano; De Beni, Rossana

2016-05-01

This study examined age-related differences between young and older adults in the involvement of verbal and visuo-spatial components of working memory (WM) when paths are learned from verbal and visuo-spatial inputs. A sample of 60 young adults (20-30 years old) and 58 older adults (60-75 years old) learned two paths from the person's point of view, one displayed in the form of a video showing the path, the other presenting the path in a verbal description. During the learning phase, participants concurrently performed a verbal task (articulatory suppression, AS group), or a visuo-spatial task (spatial tapping, ST group), or no secondary task (control, C group). After learning each path, participants completed tasks that involved the following: (1) recalling the sequential order and the location of landmarks; and (2) judging spatial sentences as true or false (verification test). The results showed that young adults outperformed older adults in all recall tasks. In both age groups performance in all types of task was worse in the AS and ST groups than in the C group, irrespective of the type of input. Overall, these findings suggest that verbal and visuo-spatial components of WM underpin the processing of environmental information in both young and older adults. The results are discussed in terms of age-related differences and according to the spatial cognition framework. © 2015 The British Psychological Society.

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

PubMed

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

2014-10-15

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

Can 28-Month-Old Children Learn Spatial Prepositions Robustly from Pictures? Yes, When Narrative Input Is Provided

PubMed Central

Rohlfing, Katharina J.; Nachtigäller, Kerstin

2016-01-01

The learning of spatial prepositions is assumed to be based on experience in space. In a slow mapping study, we investigated whether 31 German 28-month-old children could robustly learn the German spatial prepositions hinter [behind] and neben [next to] from pictures, and whether a narrative input can compensate for a lack of immediate experience in space. One group of children received pictures with a narrative input as a training to understand spatial prepositions. In two further groups, we controlled (a) for the narrative input by providing unconnected speech during the training and (b) for the learning material by training the children on toys rather than pictures. We assessed children’s understanding of spatial prepositions at three different time points: pretest, immediate test, and delayed posttest. Results showed improved word retention in children from the narrative but not the control group receiving unconnected speech. Neither of the trained groups succeeded in generalization to novel referents. Finally, all groups were instructed to deal with untrained material in the test to investigate the robustness of learning across tasks. None of the groups succeeded in this task transfer. PMID:27471479

Infants learn better from left to right: a directional bias in infants' sequence learning.

PubMed

Bulf, Hermann; de Hevia, Maria Dolores; Gariboldi, Valeria; Macchi Cassia, Viola

2017-05-26

A wealth of studies show that human adults map ordered information onto a directional spatial continuum. We asked whether mapping ordinal information into a directional space constitutes an early predisposition, already functional prior to the acquisition of symbolic knowledge and language. While it is known that preverbal infants represent numerical order along a left-to-right spatial continuum, no studies have investigated yet whether infants, like adults, organize any kind of ordinal information onto a directional space. We investigated whether 7-month-olds' ability to learn high-order rule-like patterns from visual sequences of geometric shapes was affected by the spatial orientation of the sequences (left-to-right vs. right-to-left). Results showed that infants readily learn rule-like patterns when visual sequences were presented from left to right, but not when presented from right to left. This result provides evidence that spatial orientation critically determines preverbal infants' ability to perceive and learn ordered information in visual sequences, opening to the idea that a left-to-right spatially organized mental representation of ordered dimensions might be rooted in biologically-determined constraints on human brain development.

Developing an Analytical Framework: Incorporating Ecosystem Services into Decision Making - Proceedings of a Workshop

USGS Publications Warehouse

Hogan, Dianna; Arthaud, Greg; Pattison, Malka; Sayre, Roger G.; Shapiro, Carl

2010-01-01

The analytical framework for understanding ecosystem services in conservation, resource management, and development decisions is multidisciplinary, encompassing a combination of the natural and social sciences. This report summarizes a workshop on 'Developing an Analytical Framework: Incorporating Ecosystem Services into Decision Making,' which focused on the analytical process and on identifying research priorities for assessing ecosystem services, their production and use, their spatial and temporal characteristics, their relationship with natural systems, and their interdependencies. Attendees discussed research directions and solutions to key challenges in developing the analytical framework. The discussion was divided into two sessions: (1) the measurement framework: quantities and values, and (2) the spatial framework: mapping and spatial relationships. This workshop was the second of three preconference workshops associated with ACES 2008 (A Conference on Ecosystem Services): Using Science for Decision Making in Dynamic Systems. These three workshops were designed to explore the ACES 2008 theme on decision making and how the concept of ecosystem services can be more effectively incorporated into conservation, restoration, resource management, and development decisions. Preconference workshop 1, 'Developing a Vision: Incorporating Ecosystem Services into Decision Making,' was held on April 15, 2008, in Cambridge, MA. In preconference workshop 1, participants addressed what would have to happen to make ecosystem services be used more routinely and effectively in conservation, restoration, resource management, and development decisions, and they identified some key challenges in developing the analytical framework. Preconference workshop 3, 'Developing an Institutional Framework: Incorporating Ecosystem Services into Decision Making,' was held on October 30, 2008, in Albuquerque, NM; participants examined the relationship between the institutional framework and the use of ecosystem services in decision making.

Integrating advice and experience: learning and decision making with social and nonsocial cues.

PubMed

Collins, Elizabeth C; Percy, Elise J; Smith, Eliot R; Kruschke, John K

2011-06-01

When making decisions, people typically gather information from both social and nonsocial sources, such as advice from others and direct experience. This research adapted a cognitive learning paradigm to examine the process by which people learn what sources of information are credible. When participants relied on advice alone to make decisions, their learning of source reliability proceeded in a manner analogous to traditional cue learning processes and replicated the established learning phenomena. However, when advice and nonsocial cues were encountered together as an established phenomenon, blocking (ignoring redundant information) did not occur. Our results suggest that extant cognitive learning models can accommodate either advice or nonsocial cues in isolation. However, the combination of advice and nonsocial cues (a context more typically encountered in daily life) leads to different patterns of learning, in which mutually supportive information from different types of sources is not regarded as redundant and may be particularly compelling. For these situations, cognitive learning models still constitute a promising explanatory tool but one that must be expanded. As such, these findings have important implications for social psychological theory and for cognitive models of learning. 2011 APA, all rights reserved

Distinct roles of dopamine and subthalamic nucleus in learning and probabilistic decision making.

PubMed

Coulthard, Elizabeth J; Bogacz, Rafal; Javed, Shazia; Mooney, Lucy K; Murphy, Gillian; Keeley, Sophie; Whone, Alan L

2012-12-01

Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making predict that learning individual stimulus-response associations and rapid combination of information from multiple stimuli are dependent on different components of basal ganglia circuitry. In particular, learning and retention of memory, required for optimal response choice, are significantly reliant on dopamine, whereas integrating information probabilistically is critically dependent upon functioning of the glutamatergic subthalamic nucleus (computing the 'normalization term' in Bayes' theorem). Here, we test these theories by investigating 22 patients with Parkinson's disease either treated with deep brain stimulation to the subthalamic nucleus and dopaminergic therapy or managed with dopaminergic therapy alone. We use computerized tasks that probe three cognitive functions-information acquisition (learning), memory over a delay and information integration when multiple pieces of sequentially presented information have to be combined. Patients performed the tasks ON or OFF deep brain stimulation and/or ON or OFF dopaminergic therapy. Consistent with the computational theories, we show that stopping dopaminergic therapy impairs memory for probabilistic information over a delay, whereas deep brain stimulation to the region of the subthalamic nucleus disrupts decision making when multiple pieces of acquired information must be combined. Furthermore, we found that when participants needed to update their decision on the basis of the last piece of information presented in the decision-making task, patients with deep brain stimulation of the subthalamic nucleus region did not slow down appropriately to revise their plan, a pattern of behaviour that mirrors the impulsivity described clinically in some patients with subthalamic nucleus deep brain stimulation. Thus, we demonstrate distinct mechanisms for two important facets of human decision making: first, a role for dopamine in memory consolidation, and second, the critical importance of the subthalamic nucleus in successful decision making when multiple pieces of information must be combined.

Endogenous hippocampal LTD that is enabled by spatial object recognition requires activation of NMDA receptors and the metabotropic glutamate receptor, mGlu5.

PubMed

Goh, Jinzhong Jeremy; Manahan-Vaughan, Denise

2013-02-01

Learning-facilitated synaptic plasticity describes the ability of hippocampal synapses to respond with persistent plasticity to afferent stimulation when coupled with a spatial learning event, whereby the afferent stimulation normally produces short-term plasticity or no change in synaptic strength if given in the absence of novel learning. Recently, it was reported that in the mouse hippocampus intrinsic long-term depression (LTD > 24 h) occurs when test-pulse afferent stimulation is coupled with a novel spatial learning. It is not known to what extent this phenomenon shares molecular properties with synaptic plasticity that is typically induced by means of patterned electrical afferent stimulation. In previous work, we showed that a novel spatial object recognition task facilitates LTD at the Schaffer collateral-CA1 synapse of freely behaving adult mice, whereas reexposure to the familiar spatial configuration ∼24 h later elicited no such facilitation. Here we report that treatment with the NMDA receptor antagonist, (±)-3-(2-Carboxypiperazin-4-yl)-propanephosphonic acid (CPP), or antagonism of metabotropic glutamate (mGlu) receptor, mGlu5, using 2-methyl-6-(phenylethynyl) pyridine (MPEP), completely prevented LTD under the novel learning conditions. Behavioral assessment during re-exposure after application of the antagonists revealed that the animals did not remember the object during novel exposure and treated them as if they were novel. Under these circumstances, where the acquisition of novel spatial information was involved, LTD was facilitated. Our data support that the endogenous LTD that is enabled through novel spatial learning in adult mice is critically dependent on the activation of both the NMDA receptors and mGlu5. Copyright © 2012 Wiley Periodicals, Inc.

Decision technologies and the independent professional: the future's challenge to learning and leadership

PubMed Central

Dowie, J.

2001-01-01

Most references to "leadership" and "learning" as sources of quality improvement in medical care reflect an implicit commitment to the decision technology of "clinical judgement". All attempts to sustain this waning decision technology by clinical guidelines, care pathways, "evidence based practice", problem based curricula, and other stratagems only increase the gap between what is expected of doctors in today's clinical situation and what is humanly possible, hence the morale, stress, and health problems they are increasingly experiencing. Clinical guidance programmes based on decision analysis represent the coming decision technology, and proactive adaptation will produce independent doctors who can deliver excellent evidence based and preference driven care while concentrating on the human aspects of the therapeutic relation, having been relieved of the unbearable burdens of knowledge and information processing currently laid on them. History is full of examples of the incumbents of dominant technologies preferring to die than to adapt, and medicine needs both learning and leadership if it is to avoid repeating this mistake. Key Words: decision technology; clinical guidance programmes; decision analysis PMID:11700381

An information theory analysis of spatial decisions in cognitive development

PubMed Central

Scott, Nicole M.; Sera, Maria D.; Georgopoulos, Apostolos P.

2015-01-01

Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of “cognitive entropy” were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured “chunking” of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework. PMID:25698915

Development of a GIService based on spatial data mining for location choice of convenience stores in Taipei City

NASA Astrophysics Data System (ADS)

Jung, Chinte; Sun, Chih-Hong

2006-10-01

Motivated by the increasing accessibility of technology, more and more spatial data are being made digitally available. How to extract the valuable knowledge from these large (spatial) databases is becoming increasingly important to businesses, as well. It is essential to be able to analyze and utilize these large datasets, convert them into useful knowledge, and transmit them through GIS-enabled instruments and the Internet, conveying the key information to business decision-makers effectively and benefiting business entities. In this research, we combine the techniques of GIS, spatial decision support system (SDSS), spatial data mining (SDM), and ArcGIS Server to achieve the following goals: (1) integrate databases from spatial and non-spatial datasets about the locations of businesses in Taipei, Taiwan; (2) use the association rules, one of the SDM methods, to extract the knowledge from the integrated databases; and (3) develop a Web-based SDSS GIService as a location-selection tool for business by the product of ArcGIS Server.

Hippocampal 5-HT1A Receptor and Spatial Learning and Memory

PubMed Central

Glikmann-Johnston, Yifat; Saling, Michael M.; Reutens, David C.; Stout, Julie C.

2015-01-01

Spatial cognition is fundamental for survival in the topographically complex environments inhabited by humans and other animals. The hippocampus, which has a central role in spatial cognition, is characterized by high concentration of serotonin (5-hydroxytryptamine; 5-HT) receptor binding sites, particularly of the 1A receptor (5-HT1A) subtype. This review highlights converging evidence for the role of hippocampal 5-HT1A receptors in spatial learning and memory. We consider studies showing that activation or blockade of the 5-HT1A receptors using agonists or antagonists, respectively, lead to changes in spatial learning and memory. For example, pharmacological manipulation to induce 5-HT release, or to block 5-HT uptake, have indicated that increased extracellular 5-HT concentrations maintain or improve memory performance. In contrast, reduced levels of 5-HT have been shown to impair spatial memory. Furthermore, the lack of 5-HT1A receptor subtype in single gene knockout mice is specifically associated with spatial memory impairments. These findings, along with evidence from recent cognitive imaging studies using positron emission tomography (PET) with 5-HT1A receptor ligands, and studies of individual genetic variance in 5-HT1A receptor availability, strongly suggests that 5-HT, mediated by the 5-HT1A receptor subtype, plays a key role in spatial learning and memory. PMID:26696889

The Association Between Effective Dose of Magnesium and Mild Compulsive Exercise on Spatial Learning, Memory, and Motor Activity of Adult Male Rats.

PubMed

Hajizade Ghonsulakandi, Shahnaz; Sheikh, Mahmuod; Dehghan Shasaltaneh, Marzieh; Chopani, Samira; Naghdi, Nasser

2017-08-01

One of the most important survival mechanisms is learning and memory processes. To emphasize the role of physical exercises and magnesium (Mg) in improvement of cognitive performance, we planned to investigate the effect of Mg and mild compulsive exercise on spatial learning and memory of adult male rats. Accordingly, we divided male Wistar rats into four groups: (I) control, (II) Mg treatment, (III) exercise, and (IV) Mg-exercise in the different dosages of Mg (0.5, 1, 1.5, and 2 mmol/kbw) were injected in the form of gavage during 1 week. Also, 1-week mild running on treadmill was used for exercise treatment. The Morris water maze (MWM) test and open field tool were used to evaluate spatial learning, memory, and motor activity, respectively. Our results clearly showed that 1 mmol/kbw Mg was applied as an effective dosage. Strikingly, 1-week mild exercise on treadmill had no significant effect on spatial motor activity, learning, and memory. Feeding 1 mmol/kbw Mg for a week showed a significant difference in learning and exploration stages. Compared to control animals, these results reveal exercise and Mg simultaneously had effect on learning and reminding. As a consequence, although mild exercise had no effect on motor activity and memory, Mg intake improved spatial learning, memory, and locomotor activity. The Mg feeding could be a promising supplemental treatment in the neurodegenerative disease. It is worthwhile to mention consumption of Mg leads to enhancement of memory, so animals find the hidden platform with the highest velocity.

Finding faults: analogical comparison supports spatial concept learning in geoscience.

PubMed

Jee, Benjamin D; Uttal, David H; Gentner, Dedre; Manduca, Cathy; Shipley, Thomas F; Sageman, Bradley

2013-05-01

A central issue in education is how to support the spatial thinking involved in learning science, technology, engineering, and mathematics (STEM). We investigated whether and how the cognitive process of analogical comparison supports learning of a basic spatial concept in geoscience, fault. Because of the high variability in the appearance of faults, it may be difficult for students to learn the category-relevant spatial structure. There is abundant evidence that comparing analogous examples can help students gain insight into important category-defining features (Gentner in Cogn Sci 34(5):752-775, 2010). Further, comparing high-similarity pairs can be especially effective at revealing key differences (Sagi et al. 2012). Across three experiments, we tested whether comparison of visually similar contrasting examples would help students learn the fault concept. Our main findings were that participants performed better at identifying faults when they (1) compared contrasting (fault/no fault) cases versus viewing each case separately (Experiment 1), (2) compared similar as opposed to dissimilar contrasting cases early in learning (Experiment 2), and (3) viewed a contrasting pair of schematic block diagrams as opposed to a single block diagram of a fault as part of an instructional text (Experiment 3). These results suggest that comparison of visually similar contrasting cases helped distinguish category-relevant from category-irrelevant features for participants. When such comparisons occurred early in learning, participants were more likely to form an accurate conceptual representation. Thus, analogical comparison of images may provide one powerful way to enhance spatial learning in geoscience and other STEM disciplines.

Hippocampal Modulation of Associative Learning

DTIC Science & Technology

1992-01-01

Improvement of Visual Communication and Its Impact on Spatial Learning. Third Annual Argonne Symposium for Undergraduates in Science, Engineering and...baseline for these observations. PUBLICATIONS: Goldbogen, G., Lerman, Z., Morton, D. and Wallisky, M. An Investigation of the Improvement of Visual ... Communication and Its Impact on Spatial Learning. Third Annual Argonne Symposium for Undergraduates in Science, Engineering and Mathematics (Submitted

Comparison of Visual-Spatial Performance Strategy Training in Children with Turner Syndrome and Learning Disabilities.

ERIC Educational Resources Information Center

Williams, Janet K.; And Others

1992-01-01

Thirteen females with Turner syndrome, 13 females with nonverbal learning disabilities, and 14 males with nonverbal learning disabilities, ages 7-14, were taught via a cognitive behavioral modification approach to verbally mediate a spatial matching task. All three groups showed significant task improvement after the training, with no significant…

Building of fuzzy decision trees using ID3 algorithm

NASA Astrophysics Data System (ADS)

Begenova, S. B.; Avdeenko, T. V.

2018-05-01

Decision trees are widely used in the field of machine learning and artificial intelligence. Such popularity is due to the fact that with the help of decision trees graphic models, text rules can be built and they are easily understood by the final user. Because of the inaccuracy of observations, uncertainties, the data, collected in the environment, often take an unclear form. Therefore, fuzzy decision trees becoming popular in the field of machine learning. This article presents a method that includes the features of the two above-mentioned approaches: a graphical representation of the rules system in the form of a tree and a fuzzy representation of the data. The approach uses such advantages as high comprehensibility of decision trees and the ability to cope with inaccurate and uncertain information in fuzzy representation. The received learning method is suitable for classifying problems with both numerical and symbolic features. In the article, solution illustrations and numerical results are given.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

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

PubMed Central

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

2016-01-01

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

Using basic geographic information systems functionality to support sustainable forest management decision making and post-decision assessments

Treesearch

Ronald E. McRoberts; R. James Barbour; Krista M. Gebert; Greg C. Liknes; Mark D. Nelson; Dacia M. Meneguzzo; et al.

2006-01-01

Sustainable management of natural resources requires informed decision making and post-decision assessments of the results of those decisions. Increasingly, both activities rely on analyses of spatial data in the forms of maps and digital data layers. Fortunately, a variety of supporting maps and data layers rapidly are becoming available. Unfortunately, however, user-...

Probabilistic learning and inference in schizophrenia

PubMed Central

Averbeck, Bruno B.; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S.

2010-01-01

Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behaviour remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behaviour, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. PMID:20810252

Probabilistic learning and inference in schizophrenia.

PubMed

Averbeck, Bruno B; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S

2011-04-01

Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behavior remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behavior, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving a noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. Published by Elsevier B.V.

Semantic Metadata for Heterogeneous Spatial Planning Documents

NASA Astrophysics Data System (ADS)

Iwaniak, A.; Kaczmarek, I.; Łukowicz, J.; Strzelecki, M.; Coetzee, S.; Paluszyński, W.

2016-09-01

Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa). The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

Prenatal stress changes learning strategies in adulthood.

PubMed

Schwabe, Lars; Bohbot, Veronique D; Wolf, Oliver T

2012-11-01

It is well known that stressful experiences may shape hippocampus-dependent learning and memory processes. However, although most studies focused on the impact of stress at the time of learning or memory testing, very little is known about how stress during critical periods of brain development affects learning and memory later in life. In this study, we asked whether prenatal stress exposure may influence the engagement of hippocampus-dependent spatial learning strategies and caudate nucleus-dependent response learning strategies in later life. To this end, we tested healthy participants whose mothers had experienced major negative life events during their pregnancy in a virtual navigation task that can be solved by spatial and response strategies. We found that young adults with prenatal stress used rigid response learning strategies more often than flexible spatial learning strategies compared with participants whose mothers did not experience major negative life events during pregnancy. Individual differences in acute or chronic stress do not account for these findings. Our data suggest that the engagement of hippocampal and nonhippocampal learning strategies may be influenced by stress very early in life. Copyright © 2012 Wiley Periodicals, Inc.

Multivariate temporal dictionary learning for EEG.

PubMed

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

2013-04-30

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

[Stimulation of D1-receptors improves passive avoidance learning of female rats during ovary cycle].

PubMed

Fedotova, Iu O; Sapronov, N S

2012-01-01

The involvement of D1-receptors in learning/memory processes during ovary cycle was assessed in the adult female rats. SKF-38393 (0,1 mg/kg, i.p.), D1-receptor agonist and SCH-23390 (0,1 mg/kg, i.p.), D1-receptor antagonist were injected chronically to adult female rats. Learning of these animals was assessed in different models: passive avoidance performance and Morris water maze. Chronic SKF-3839 administration to females resulted in the appearance of the passive avoidance performance in proestrous and estrous, as distinct from the control animals, but failed to change the dynamics of spatial learning in Morris water maze. Chronic SCH-23390 administration similarly impaired non-spatial and spatial learning in females during all phases of ovary cycle. The results of the study suggest modulating role of D1-receptors in learning/memory processes during ovary cycle in the adult female rats.

[Stimulation of D2-receptors improves passive avoidance learning in female rats].

PubMed

Fedotova, Iu O

2012-01-01

The involvement of D2-receptors in learning/memory processes during ovary cycle was assessed in the adult female rats. Quinperole (0,1 mg/kg, i.p.), D2-receptor agonist and sulpiride (10,0 mg/kg, i.p.), D2-receptor antagonist were injected chronically to adult female rats. Learning of these animals was assessed in different models: passive avoidance performance and Morris water maze. Chronic quinperole administration to females resulted in the appearance of the passive avoidance performance in proestrous and estrous, as distinct from the control animals. Also, quinperole improved spatial learning in proestrous and stimulated it in estrous in Morris water maze. Chronic sulpiride administration similarly impaired non-spatial and spatial learning in females during all phases of ovary cycle. The results of the study suggest modulating role of D2-receptors in learning/memory processes during ovary cycle in the adult female rats.

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

PubMed Central

Schwarb, Hillary; Schumacher, Eric H.

2012-01-01

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

Immersive 3D geovisualisation in higher education

NASA Astrophysics Data System (ADS)

Philips, Andrea; Walz, Ariane; Bergner, Andreas; Graeff, Thomas; Heistermann, Maik; Kienzler, Sarah; Korup, Oliver; Lipp, Torsten; Schwanghart, Wolfgang; Zeilinger, Gerold

2014-05-01

Through geovisualisation we explore spatial data, we analyse it towards a specific questions, we synthesise results, and we present and communicate them to a specific audience (MacEachren & Kraak 1997). After centuries of paper maps, the means to represent and visualise our physical environment and its abstract qualities have changed dramatically since the 1990s - and accordingly the methods how to use geovisualisation in teaching. Whereas some people might still consider the traditional classroom as ideal setting for teaching and learning geographic relationships and its mapping, we used a 3D CAVE (computer-animated virtual environment) as environment for a problem-oriented learning project called "GEOSimulator". Focussing on this project, we empirically investigated, if such a technological advance like the CAVE make 3D visualisation, including 3D geovisualisation, not only an important tool for businesses (Abulrub et al. 2012) and for the public (Wissen et al. 2008), but also for educational purposes, for which it had hardly been used yet. The 3D CAVE is a three-sided visualisation platform, that allows for immersive and stereoscopic visualisation of observed and simulated spatial data. We examined the benefits of immersive 3D visualisation for geographic research and education and synthesized three fundamental technology-based visual aspects: First, the conception and comprehension of space and location does not need to be generated, but is instantaneously and intuitively present through stereoscopy. Second, optical immersion into virtual reality strengthens this spatial perception which is in particular important for complex 3D geometries. And third, a significant benefit is interactivity, which is enhanced through immersion and allows for multi-discursive and dynamic data exploration and knowledge transfer. Based on our problem-oriented learning project, which concentrates on a case study on flood risk management at the Wilde Weisseritz in Germany, a river that significantly contributed to the hundred-year flooding in Dresden in 2002, we empirically evaluated the usefulness of this immersive 3D technology towards learning success. Results show that immersive 3D geovisualisation have educational and content-related advantages compared to 2D geovisualisations through the mentioned benefits. This innovative way of geovisualisation is thus not only entertaining and motivating for students, but can also be constructive for research studies by, for instance, facilitating the study of complex environments or decision-making processes.

CHANGES SDSS: the development of a Spatial Decision Support System for analysing changing hydro-meteorological risk

NASA Astrophysics Data System (ADS)

van Westen, Cees; Bakker, Wim; Zhang, Kaixi; Jäger, Stefan; Assmann, Andre; Kass, Steve; Andrejchenko, Vera; Olyazadeh, Roya; Berlin, Julian; Cristal, Irina

2014-05-01

Within the framework of the EU FP7 Marie Curie Project CHANGES (www.changes-itn.eu) and the EU FP7 Copernicus project INCREO (http://www.increo-fp7.eu) a spatial decision support system is under development with the aim to analyse the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. The Spatial Decision Support System will be composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and spatial planning) and links back to the risk assessment module to calculate the new level of risk if the measure is implemented, and a cost-benefit (or cost-effectiveness/ Spatial Multi Criteria Evaluation) component to compare the alternatives and make decision on the optimal one. The third component of the SDSS is a temporal scenario component, which allows to define future scenarios in terms of climate change, land use change and population change, and the time periods for which these scenarios will be made. The component doesn't generate these scenarios but uses input maps for the effect of the scenarios on the hazard and assets maps. The last component is a communication and visualization component, which can compare scenarios and alternatives, not only in the form of maps, but also in other forms (risk curves, tables, graphs). The envisaged users of the platform are organizations involved in planning of risk reduction measures, and that have staff capable of visualizing and analysing spatial data at a municipal scale.

Ship Detection in Optical Satellite Image Based on RX Method and PCAnet

NASA Astrophysics Data System (ADS)

Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting

2017-12-01

In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.

Sustainable Remediation of Legacy Mine Drainage: A Case Study of the Flight 93 National Memorial.

PubMed

Emili, Lisa A; Pizarchik, Joseph; Mahan, Carolyn G

2016-03-01

Pollution from mining activities is a global environmental concern, not limited to areas of current resource extraction, but including a broader geographic area of historic (legacy) and abandoned mines. The pollution of surface waters from acid mine drainage is a persistent problem and requires a holistic and sustainable approach to addressing the spatial and temporal complexity of mining-specific problems. In this paper, we focus on the environmental, socio-economic, and legal challenges associated with the concurrent activities to remediate a coal mine site and to develop a national memorial following a catastrophic event. We provide a conceptual construct of a socio-ecological system defined at several spatial, temporal, and organizational scales and a critical synthesis of the technical and social learning processes necessary to achieving sustainable environmental remediation. Our case study is an example of a multi-disciplinary management approach, whereby collaborative interaction of stakeholders, the emergence of functional linkages for information exchange, and mediation led to scientifically informed decision making, creative management solutions, and ultimately environmental policy change.

Age-related changes in rostral basal forebrain cholinergic and GABAergic projection neurons: Relationship with spatial impairment

PubMed Central

Bañuelos, C.; LaSarge, C. L.; McQuail, J. A.; Hartman, J. J.; Gilbert, R. J.; Ormerod, B. K.; Bizon, J. L.

2013-01-01

Both cholinergic and GABAergic projections from the rostral basal forebrain have been implicated in hippocampal function and mnemonic abilities. While dysfunction of cholinergic neurons has been heavily implicated in age-related memory decline, significantly less is known regarding how age-related changes in co-distributed GABAergic projection neurons contribute to a decline in hippocampal-dependent spatial learning. In the current study, confocal stereology was used to quantify cholinergic (choline acetyltransferase (ChAT) immunopositive) neurons, GABAergic projection (glutamic decarboxylase 67 (GAD67) immunopositive) neurons, and total (NeuN immunopositive) neurons in the rostral basal forebrain of young and aged rats that were first characterized on a spatial learning task. ChAT immunopositive neurons were significantly but modestly reduced in aged rats. Although ChAT immunopositive neuron number was strongly correlated with spatial learning abilities among young rats, the reduction of ChAT immunopositive neurons was not associated with impaired spatial learning in aged rats. In contrast, the number of GAD67 immunopositive neurons was robustly and selectively elevated in aged rats that exhibited impaired spatial learning. Interestingly, the total number of rostral basal forebrain neurons was comparable in young and aged rats, regardless of their cognitive status. These data demonstrate differential effects of age on phenotypically distinct rostral basal forebrain projection neurons, and implicate dysregulated cholinergic and GABAergic septohippocampal circuitry in age-related mnemonic decline. PMID:22817834

Effects of Gender Differences and Spatial Abilities within a Digital Pentominoes Game

ERIC Educational Resources Information Center

Yang, Jie Chi; Chen, Sherry Y.

2010-01-01

Spatial ability is a critical skill in geometric learning. Several studies investigate how to use digital games to improve spatial abilities. However, not every learner favors this kind of support. To this end, there is a need to examine how human factors affect learners' reactions to the use of a digital game to support geometric learning. In…

Probing the Relationship between Process of Spatial Problems Solving and Science Learning: An Eye Tracking Approach

ERIC Educational Resources Information Center

Chen, Yi-Chun; Yang, Fang-Ying

2014-01-01

There were two purposes in the study. One was to explore the cognitive activities during spatial problem solving and the other to probe the relationship between spatial ability and science concept learning. Twenty university students participated in the study. The Purdue Visualization of Rotations Test (PVRT) was used to assess the spatial…

Spaces in between Us: A Qualitative Study into the Impact of Spatial Practice when Learning in "Second Life"

ERIC Educational Resources Information Center

Savin-Baden, Maggi

2013-01-01

This paper will present a study that explored the perceived impact of spatial practice in "Second Life" (SL) on teaching and learning from the point of view of participants in higher education (lecturers, developers and researchers). Narrative inquiry was used to access stories and experiences of space and spatial practice from staff…

Spatial Abilities in an Elective Course of Applied Anatomy after a Problem-Based Learning Curriculum

ERIC Educational Resources Information Center

Langlois, Jean; Wells, George A.; Lecourtois, Marc; Bergeron, Germain; Yetisir, Elizabeth; Martin, Marcel

2009-01-01

A concern on the level of anatomy knowledge reached after a problem-based learning curriculum has been documented in the literature. Spatial anatomy, arguably the highest level in anatomy knowledge, has been related to spatial abilities. Our first objective was to test the hypothesis that residents are interested in a course of applied anatomy…

Interactions of spatial strategies producing generalization gradient and blocking: A computational approach

PubMed Central

Dollé, Laurent; Chavarriaga, Ricardo

2018-01-01

We present a computational model of spatial navigation comprising different learning mechanisms in mammals, i.e., associative, cognitive mapping and parallel systems. This model is able to reproduce a large number of experimental results in different variants of the Morris water maze task, including standard associative phenomena (spatial generalization gradient and blocking), as well as navigation based on cognitive mapping. Furthermore, we show that competitive and cooperative patterns between different navigation strategies in the model allow to explain previous apparently contradictory results supporting either associative or cognitive mechanisms for spatial learning. The key computational mechanism to reconcile experimental results showing different influences of distal and proximal cues on the behavior, different learning times, and different abilities of individuals to alternatively perform spatial and response strategies, relies in the dynamic coordination of navigation strategies, whose performance is evaluated online with a common currency through a modular approach. We provide a set of concrete experimental predictions to further test the computational model. Overall, this computational work sheds new light on inter-individual differences in navigation learning, and provides a formal and mechanistic approach to test various theories of spatial cognition in mammals. PMID:29630600

Spatial cues more salient than color cues in cotton-top tamarins (Saguinus oedipus) reversal learning.

PubMed

Gaudio, Jennifer L; Snowdon, Charles T

2008-11-01

Animals living in stable home ranges have many potential cues to locate food. Spatial and color cues are important for wild Callitrichids (marmosets and tamarins). Field studies have assigned the highest priority to distal spatial cues for determining the location of food resources with color cues serving as a secondary cue to assess relative ripeness, once a food source is located. We tested two hypotheses with captive cotton-top tamarins: (a) Tamarins will demonstrate higher rates of initial learning when rewarded for attending to spatial cues versus color cues. (b) Tamarins will show higher rates of correct responses when transferred from color cues to spatial cues than from spatial cues to color cues. The results supported both hypotheses. Tamarins rewarded based on spatial location made significantly more correct choices and fewer errors than tamarins rewarded based on color cues during initial learning. Furthermore, tamarins trained on color cues showed significantly increased correct responses and decreased errors when cues were reversed to reward spatial cues. Subsequent reversal to color cues induced a regression in performance. For tamarins spatial cues appear more salient than color cues in a foraging task. (PsycINFO Database Record (c) 2008 APA, all rights reserved).

Publically accessible decision support system of the spatially referenced regressions on watershed attributes (SPARROW) model and model enhancements in South Carolina

Treesearch

Celeste Journey; Anne B. Hoos; David E. Ladd; John W. brakebill; Richard A. Smith

2016-01-01

The U.S. Geological Survey (USGS) National Water Quality Assessment program has developed a web-based decision support system (DSS) to provide free public access to the steady-stateSPAtially Referenced Regressions On Watershed attributes (SPARROW) model simulation results on nutrient conditions in streams and rivers and to offer scenario testing capabilities for...

The Effects of Cognitive Process and Decision Making Training in Reading Experience on Meaningful Learning with Underachieving College Students

ERIC Educational Resources Information Center

Dean, Rebecca J.

2010-01-01

The ability of underprepared college students to read and learn from their reading is essential to their academic success and to their ability to persist towards completing their degree. The purposes of this study were to (a) assess the relationship between the cognitive processes of reading-based decision making and meaningful learning and (b)…

IDESSA: An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Authmann, Christian; Dreber, Niels; Hess, Bastian; Kellner, Klaus; Morgenthal, Theunis; Nauss, Thomas; Seeger, Bernhard; Tsvuura, Zivanai; Wiegand, Kerstin

2017-04-01

Bush encroachment is a syndrome of land degradation that occurs in many savannas including those of southern Africa. The increase in density, cover or biomass of woody vegetation often has negative effects on a range of ecosystem functions and services, which are hardly reversible. However, despite its importance, neither the causes of bush encroachment, nor the consequences of different resource management strategies to combat or mitigate related shifts in savanna states are fully understood. The project "IDESSA" (An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas) aims to improve the understanding of the complex interplays between land use, climate patterns and vegetation dynamics and to implement an integrative monitoring and decision-support system for the sustainable management of different savanna types. For this purpose, IDESSA follows an innovative approach that integrates local knowledge, botanical surveys, remote-sensing and machine-learning based time-series of atmospheric and land-cover dynamics, spatially explicit simulation modeling and analytical database management. The integration of the heterogeneous data will be implemented in a user oriented database infrastructure and scientific workflow system. Accessible via web-based interfaces, this database and analysis system will allow scientists to manage and analyze monitoring data and scenario computations, as well as allow stakeholders (e. g. land users, policy makers) to retrieve current ecosystem information and seasonal outlooks. We present the concept of the project and show preliminary results of the realization steps towards the integrative savanna management and decision-support system.

Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model.

PubMed

Yang, Weichao; Xu, Kui; Lian, Jijian; Bin, Lingling; Ma, Chao

2018-05-01

Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision. Copyright © 2018 Elsevier Ltd. All rights reserved.

Rapid Benefit Indicators (RBI) Spatial Analysis Tools

EPA Science Inventory

The Rapid Benefit Indicators (RBI) approach consists of five steps and is outlined in Assessing the Benefits of Wetland Restoration - A Rapid Benefits Indicators Approach for Decision Makers. This spatial analysis tool is intended to be used to analyze existing spatial informatio...

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

PubMed

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

2010-01-01

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

Sex-specific effects of prenatal chronic mild stress on adult spatial learning capacity and regional glutamate receptor expression profiles.

PubMed

Wang, Yan; Ma, Yuchao; Hu, Jingmin; Zhang, Xinxin; Cheng, Wenwen; Jiang, Han; Li, Min; Ren, Jintao; Zhang, Xiaosong; Liu, Mengxi; Sun, Anji; Wang, Qi; Li, Xiaobai

2016-07-01

Both animal experiments and clinical studies have demonstrated that prenatal stress can cause cognitive disorders in offspring. To explore the scope of these deficits and identify potential underlying mechanisms, we examined the spatial learning and memory performance and glutamate receptor (GluR) expression patterns of adult rats exposed to prenatal chronic mild stress (PCMS). Principal component analysis (PCA) was employed to reveal the interrelationships among spatial learning indices and GluR expression changes. Female PCMS-exposed offspring exhibited markedly impaired spatial learning and memory in the Morris water maze (MWM) task compared to control females, while PCMS-exposed males showed better initial spatial learning in the MWM compared to control males. PCMS also altered basal and post-MWM glutamate receptor expression patterns, but these effects differed markedly between sexes. Male PCMS-exposed offspring exhibited elevated basal expression of NR1, mGluR5, and mGluR2/3 in the prefrontal cortex (PFC), whereas females showed no basal expression changes. Following MWM training, PCMS-exposed males expressed higher NR1 in the PFC and mammillary body (MB), higher mGluR2/3 in PFC, and lower NR2B in the hippocampus (HIP), PFC, and MB compared to unstressed MWM-trained males. Female PCMS-exposed offspring showed strongly reduced NR1 in MB and NR2B in the HIP, PFC, and MB, and increased mGluR2/3 in PFC compared to unstressed MWM-trained females. This is the first report suggesting that NMDA subunits in the MB are involved in spatial learning. Additionally, PCA further suggests that the NR1-NR2B form is the most important for spatial memory formation. These results reveal long-term sex-specific effects of PCMS on spatial learning and memory performance in adulthood and implicate GluR expression changes within HIP, PFC, and MB as possible molecular mechanisms underlying cognitive dysfunction in offspring exposed to prenatal stress. Copyright © 2016 Elsevier Inc. All rights reserved.

Correlates of individual, and age-related, differences in short-term learning.

PubMed

Zhang, Zhiyong; Davis, Hasker P; Salthouse, Timothy A; Tucker-Drob, Elliot M

2007-07-01

Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individual differences in both initial level of performance and subsequent learning were found in both tasks, age differences were found only in mean initial level, and not in mean learning. In neither task was fluid or crystallized intelligence associated with learning. Although there were moderate correlations among the level parameters across the verbal and spatial tasks, the learning parameters were not significantly correlated with one another across task modalities. These results are inconsistent with the existence of a general (e.g., material-independent) learning ability.

Implicit learning of non-spatial sequences in schizophrenia

PubMed Central

MARVEL, CHERIE L.; SCHWARTZ, BARBARA L.; HOWARD, DARLENE V.; HOWARD, JAMES H.

2006-01-01

Recent studies have reported abnormal implicit learning of sequential patterns in patients with schizophrenia. Because these studies were based on visuospatial cues, the question remained whether patients were impaired simply due to the demands of spatial processing. This study examined implicit sequence learning in 24 patients with schizophrenia and 24 healthy controls using a non-spatial variation of the serial reaction time test (SRT) in which pattern stimuli alternated with random stimuli on every other trial. Both groups showed learning by responding faster and more accurately to pattern trials than to random trials. Patients, however, showed a smaller magnitude of sequence learning. Both groups were unable to demonstrate explicit knowledge of the nature of the pattern, confirming that learning occurred without awareness. Clinical variables were not correlated with the patients' learning deficits. Patients with schizophrenia have a decreased ability to develop sensitivity to regularly occurring sequences of events within their environment. This type of deficit may affect an array of cognitive and motor functions that rely on the perception of event regularity. PMID:16248901

Cloud E-Learning Service Strategies for Improving E-Learning Innovation Performance in a Fuzzy Environment by Using a New Hybrid Fuzzy Multiple Attribute Decision-Making Model

ERIC Educational Resources Information Center

Su, Chiu Hung; Tzeng, Gwo-Hshiung; Hu, Shu-Kung

2016-01-01

The purpose of this study was to address this problem by applying a new hybrid fuzzy multiple criteria decision-making model including (a) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique to construct the fuzzy scope influential network relationship map (FSINRM) and determine the fuzzy influential weights of the…

Deciphering mirror neurons: rational decision versus associative learning.

PubMed

Khalil, Elias L

2014-04-01

The rational-decision approach is superior to the associative-learning approach of Cook et al. at explaining why mirror neurons fire or do not fire - even when the stimulus is the same. The rational-decision approach is superior because it starts with the analysis of the intention of the organism, that is, with the identification of the specific objective or goal that the organism is trying to maximize.

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

PubMed

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

2017-12-01

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

Game theory and neural basis of social decision making

PubMed Central

Lee, Daeyeol

2008-01-01

Decision making in a social group displays two unique features. First, humans and other animals routinely alter their behaviors in response to changes in their physical and social environment. As a result, the outcomes of decisions that depend on the behaviors of multiple decision makers are difficult to predict, and this requires highly adaptive decision-making strategies. Second, decision makers may have other-regarding preferences and therefore choose their actions to improve or reduce the well-beings of others. Recently, many neurobiological studies have exploited game theory to probe the neural basis of decision making, and found that these unique features of social decision making might be reflected in the functions of brain areas involved in reward evaluation and reinforcement learning. Molecular genetic studies have also begun to identify genetic mechanisms for personal traits related to reinforcement learning and complex social decision making, further illuminating the biological basis of social behavior. PMID:18368047

New Interoperable Tools to Facilitate Decision-Making to Support Community Sustainability

EPA Science Inventory

Communities, regional planning authorities, regulatory agencies, and other decision-making bodies do not currently have adequate access to spatially explicit information crucial to making decisions that allow them to consider a full accounting of the costs, benefits, and trade-of...

Risky decision making from childhood through adulthood: Contributions of learning and sensitivity to negative feedback.

PubMed

Humphreys, Kathryn L; Telzer, Eva H; Flannery, Jessica; Goff, Bonnie; Gabard-Durnam, Laurel; Gee, Dylan G; Lee, Steve S; Tottenham, Nim

2016-02-01

Decision making in the context of risk is a complex and dynamic process that changes across development. Here, we assessed the influence of sensitivity to negative feedback (e.g., loss) and learning on age-related changes in risky decision making, both of which show unique developmental trajectories. In the present study, we examined risky decision making in 216 individuals, ranging in age from 3-26 years, using the balloon emotional learning task (BELT), a computerized task in which participants pump up a series of virtual balloons to earn points, but risk balloon explosion on each trial, which results in no points. It is important to note that there were 3 balloon conditions, signified by different balloon colors, ranging from quick- to slow-to-explode, and participants could learn the color-condition pairings through task experience. Overall, we found age-related increases in pumps made and points earned. However, in the quick-to-explode condition, there was a nonlinear adolescent peak for points earned. Follow-up analyses indicated that this adolescent phenotype occurred at the developmental intersection of linear age-related increases in learning and decreases in sensitivity to negative feedback. Adolescence was marked by intermediate values on both these processes. These findings show that a combination of linearly changing processes can result in nonlinear changes in risky decision making, the adolescent-specific nature of which is associated with developmental improvements in learning and reduced sensitivity to negative feedback. (c) 2016 APA, all rights reserved).

Dynamic adaptive learning for decision-making supporting systems

NASA Astrophysics Data System (ADS)

He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.

2008-03-01

This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.

Blue colour preference in honeybees distracts visual attention for learning closed shapes.

PubMed

Morawetz, Linde; Svoboda, Alexander; Spaethe, Johannes; Dyer, Adrian G

2013-10-01

Spatial vision is an important cue for how honeybees (Apis mellifera) find flowers, and previous work has suggested that spatial learning in free-flying bees is exclusively mediated by achromatic input to the green photoreceptor channel. However, some data suggested that bees may be able to use alternative channels for shape processing, and recent work shows conditioning type and training length can significantly influence bee learning and cue use. We thus tested the honeybees' ability to discriminate between two closed shapes considering either absolute or differential conditioning, and using eight stimuli differing in their spectral characteristics. Consistent with previous work, green contrast enabled reliable shape learning for both types of conditioning, but surprisingly, we found that bees trained with appetitive-aversive differential conditioning could additionally use colour and/or UV contrast to enable shape discrimination. Interestingly, we found that a high blue contrast initially interferes with bee shape learning, probably due to the bees innate preference for blue colours, but with increasing experience bees can learn a variety of spectral and/or colour cues to facilitate spatial learning. Thus, the relationship between bee pollinators and the spatial and spectral cues that they use to find rewarding flowers appears to be a more rich visual environment than previously thought.

The selective serotonin reuptake inhibitor, escitalopram, enhances inhibition of prepotent responding and spatial reversal learning

PubMed Central

Brown, Holden D.; Amodeo, Dionisio A.; Sweeney, John A.; Ragozzino, Michael E.

2011-01-01

Previous findings indicate treatment with a selective serotonin reuptake inhibitor (SSRI) facilitates behavioral flexibility when conditions require inhibition of a learned response pattern. The present experiment investigated whether acute treatment with the SSRI, escitalopram, affects behavioral flexibility when conditions require inhibition of a naturally-biased response pattern (elevated conflict test) and/or reversal of a learned response pattern (spatial reversal learning). An additional experiment was carried out to determine whether escitalopram, at doses that affected behavioral flexibility, also reduced anxiety as tested in the elevated plus-maze. In each experiment, Long-Evans rats received an intraperitoneal injection of either saline or escitalopram (0.03, 0.3 or 1.0 mg/kg) 30 minutes prior to behavioral testing. Escitalopram, at all doses tested, enhanced acquisition in the elevated conflict test, but did not affect performance in the elevated plus-maze. Escitalopram (0.3 and 1.0 mg/kg) did not alter acquisition of the spatial discrimination, but facilitated reversal learning. In the elevated conflict and spatial reversal learning test, escitalopram enhanced the ability to maintain the relevant strategy after being initially selected. The present findings suggest that enhancing serotonin transmission with a SSRI facilitates inhibitory processes when conditions require a shift away from either a naturally-biased response pattern or a learned choice pattern. PMID:22219222

Route-Learning Strategies in Typical and Atypical Development; Eye Tracking Reveals Atypical Landmark Selection in Williams Syndrome

ERIC Educational Resources Information Center

Farran, E. K.; Formby, S.; Daniyal, F.; Holmes, T.; Van Herwegen, J.

2016-01-01

Background: Successful navigation is crucial to everyday life. Individuals with Williams syndrome (WS) have impaired spatial abilities. This includes a deficit in spatial navigation abilities such as learning the route from A to B. To-date, to determine whether participants attend to landmarks when learning a route, landmark recall tasks have been…

The Effect of Old Age on Supra-Span Learning of Visuo-Spatial Sequences under Incidental and Intentional Encoding Instructions

ERIC Educational Resources Information Center

Gagnon, Sylvain; Bedard, Marie-Josee; Turcotte, Josee

2005-01-01

Recent findings [Turcotte, Gagnon, & Poirier, 2005. The effect of old age on the learning of supra-span sequences. "Psychology and Aging," 20, 251-260.] indicate that incidental learning of visuo-spatial supra-span sequences through immediate serial recall declines with old age (Hebb's paradigm). In this study, we examined whether…

The Synergetic Effect of Learning Styles on the Interaction between Virtual Environments and the Enhancement of Spatial Thinking

ERIC Educational Resources Information Center

Hauptman, Hanoch; Cohen, Arie

2011-01-01

Students have difficulty learning 3D geometry; spatial thinking is an important aspect of the learning processes in this academic area. In light of the unique features of virtual environments and the influence of metacognitive processes (e.g., self-regulating questions) on the teaching of mathematics, we assumed that a combination of…

The Computational Development of Reinforcement Learning during Adolescence

PubMed Central

Palminteri, Stefano; Coricelli, Giorgio; Blakemore, Sarah-Jayne

2016-01-01

Adolescence is a period of life characterised by changes in learning and decision-making. Learning and decision-making do not rely on a unitary system, but instead require the coordination of different cognitive processes that can be mathematically formalised as dissociable computational modules. Here, we aimed to trace the developmental time-course of the computational modules responsible for learning from reward or punishment, and learning from counterfactual feedback. Adolescents and adults carried out a novel reinforcement learning paradigm in which participants learned the association between cues and probabilistic outcomes, where the outcomes differed in valence (reward versus punishment) and feedback was either partial or complete (either the outcome of the chosen option only, or the outcomes of both the chosen and unchosen option, were displayed). Computational strategies changed during development: whereas adolescents’ behaviour was better explained by a basic reinforcement learning algorithm, adults’ behaviour integrated increasingly complex computational features, namely a counterfactual learning module (enabling enhanced performance in the presence of complete feedback) and a value contextualisation module (enabling symmetrical reward and punishment learning). Unlike adults, adolescent performance did not benefit from counterfactual (complete) feedback. In addition, while adults learned symmetrically from both reward and punishment, adolescents learned from reward but were less likely to learn from punishment. This tendency to rely on rewards and not to consider alternative consequences of actions might contribute to our understanding of decision-making in adolescence. PMID:27322574

Implicit transfer of spatial structure in visuomotor sequence learning.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2014-11-01

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

Rats with ventral hippocampal damage are impaired at various forms of learning including conditioned inhibition, spatial navigation, and discriminative fear conditioning to similar contexts.

PubMed

McDonald, Robert J; Balog, R J; Lee, Justin Q; Stuart, Emily E; Carrels, Brianna B; Hong, Nancy S

2018-10-01

The ventral hippocampus (vHPC) has been implicated in learning and memory functions that seem to differ from its dorsal counterpart. The goal of this series of experiments was to provide further insight into the functional contributions of the vHPC. Our previous work implicated the vHPC in spatial learning, inhibitory learning, and fear conditioning to context. However, the specific role of vHPC on these different forms of learning are not clear. Accordingly, we assessed the effects of neurotoxic lesions of the ventral hippocampus on retention of a conditioned inhibitory association, early versus late spatial navigation in the water task, and discriminative fear conditioning to context under high ambiguity conditions. The results showed that the vHPC was necessary for the expression of conditioned inhibition, early spatial learning, and discriminative fear conditioning to context when the paired and unpaired contexts have high cue overlap. We argue that this pattern of effects, combined with previous work, suggests a key role for vHPC in the utilization of broad contextual representations for inhibition and discriminative memory in high ambiguity conditions. Copyright © 2018 Elsevier B.V. All rights reserved.

Changing viewer perspectives reveals constraints to implicit visual statistical learning.

PubMed

Jiang, Yuhong V; Swallow, Khena M

2014-10-07

Statistical learning-learning environmental regularities to guide behavior-likely plays an important role in natural human behavior. One potential use is in search for valuable items. Because visual statistical learning can be acquired quickly and without intention or awareness, it could optimize search and thereby conserve energy. For this to be true, however, visual statistical learning needs to be viewpoint invariant, facilitating search even when people walk around. To test whether implicit visual statistical learning of spatial information is viewpoint independent, we asked participants to perform a visual search task from variable locations around a monitor placed flat on a stand. Unbeknownst to participants, the target was more often in some locations than others. In contrast to previous research on stationary observers, visual statistical learning failed to produce a search advantage for targets in high-probable regions that were stable within the environment but variable relative to the viewer. This failure was observed even when conditions for spatial updating were optimized. However, learning was successful when the rich locations were referenced relative to the viewer. We conclude that changing viewer perspective disrupts implicit learning of the target's location probability. This form of learning shows limited integration with spatial updating or spatiotopic representations. © 2014 ARVO.

The Quest for Quality

ERIC Educational Resources Information Center

Chappuis, Stephen; Chappuis, Jan; Stiggins, Rick

2009-01-01

Instructional decisions based on quality assessments and a balanced assessment system most effectively promote student learning. To inform sound decisions, assessments need to satisfy five key standards of quality: (1) clear purpose; (2) clear learning targets; (3) sound assessment design; (4) effective communication of results; and (5) student…

The Way We Learn

ERIC Educational Resources Information Center

Caine, Renate Nummela; Caine, Geoffrey

2006-01-01

Although students' eclecticism can be overwhelming, all students are identical in at least one respect--they are biologically equipped to learn from experiences. Caine and Caine discuss neurological findings about decision-making capacities built into the brain. They describe Elkhonen Goldberg's concept of actor-centered adaptive decision making…

Short Term Gains, Long Term Pains: How Cues About State Aid Learning in Dynamic Environments

PubMed Central

Gureckis, Todd M.; Love, Bradley C.

2009-01-01

Successful investors seeking returns, animals foraging for food, and pilots controlling aircraft all must take into account how their current decisions will impact their future standing. One challenge facing decision makers is that options that appear attractive in the short-term may not turn out best in the long run. In this paper, we explore human learning in a dynamic decision-making task which places short- and long-term rewards in conflict. Our goal in these studies was to evaluate how people’s mental representation of a task affects their ability to discover an optimal decision strategy. We find that perceptual cues that readily align with the underlying state of the task environment help people overcome the impulsive appeal of short-term rewards. Our experimental manipulations, predictions, and analyses are motivated by current work in reinforcement learning which details how learners value delayed outcomes in sequential tasks and the importance that “state” identification plays in effective learning. PMID:19427635

Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

NASA Astrophysics Data System (ADS)

da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo

2018-02-01

In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process) and SAW (simple additive Weighting) method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

Linked Micromaps: Statistical Summaries in a Spatial Context

EPA Science Inventory

Communicating summaries of spatial data to decision makers and the public is challenging. We present a graphical method that provides both a geographic context and a statistical summary for such spatial data. Monitoring programs have a need for such geographical summaries. For ...

A new spatial multiple discrete-continuous modeling approach to land use change analysis.

DOT National Transportation Integrated Search

2013-09-01

This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

Rapid Benefit Indicators (RBI) Spatial Analysis Toolset - Manual

EPA Science Inventory

The Rapid Benefit Indicators (RBI) approach consists of five steps and is outlined in Assessing the Benefits of Wetland Restoration - A Rapid Benefits Indicators Approach for Decision Makers. This spatial analysis tool is intended to be used to analyze existing spatial informatio...

Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task.

PubMed

Mochizuki, Kei; Funahashi, Shintaro

2016-01-01

While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. Copyright © 2016 the American Physiological Society.

Optimization of Apparatus Design and Behavioral Measures for the Assessment of Visuo-Spatial Learning and Memory of Mice on the Barnes Maze

ERIC Educational Resources Information Center

O'Leary, Timothy P.; Brown, Richard E.

2013-01-01

We have previously shown that apparatus design can affect visual-spatial cue use and memory performance of mice on the Barnes maze. The present experiment extends these findings by determining the optimal behavioral measures and test procedure for analyzing visuo-spatial learning and memory in three different Barnes maze designs. Male and female…

Place and Response Learning in the Open-field Tower Maze.

PubMed

Lipatova, Olga; Campolattaro, Matthew M; Toufexis, Donna J; Mabry, Erin A

2015-10-28

This protocol describes how the Open-field Tower Maze (OFTM) paradigm is used to study spatial learning in rodents. This maze is especially useful for examining how rats learn to use a place- or response-learning to successfully navigate in an open-field arena. Additionally, this protocol describes how the OFTM differs from other behavioral maze paradigms that are commonly used to study spatial learning in rodents. The OFTM described in this article was adapted from the one previously described by Cole, Clipperton, and Walt (2007). Specifically, the OFTM was created to test spatial learning in rodents without the experimenter having to consider how "stress" might play a role as a confounding variable. Experiments have shown that stress-alone can significantly affect cognitive function(1). The representative results section contains data from an experiment that used the OFTM to examine the effects of estradiol treatment on place- and response-learning in adult female Sprague Dawley rats(2). Future studies will be designed to examine the role of the hippocampus and striatum in place- and response-learning in the OFTM.

KBGIS-II: A knowledge-based geographic information system

NASA Technical Reports Server (NTRS)

Smith, Terence; Peuquet, Donna; Menon, Sudhakar; Agarwal, Pankaj

1986-01-01

The architecture and working of a recently implemented Knowledge-Based Geographic Information System (KBGIS-II), designed to satisfy several general criteria for the GIS, is described. The system has four major functions including query-answering, learning and editing. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial object language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multilayered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is performing all its designated tasks successfully. Future reports will relate performance characteristics of the system.

Simulating Spatial Growth Patterns in Developing Countries: A Case of Shama in the Western Region of Ghana.

NASA Astrophysics Data System (ADS)

Inkoom, J. N.; Nyarko, B. K.

2014-12-01

The integration of geographic information systems (GIS) and agent-based modelling (ABM) can be an efficient tool to improve spatial planning practices. This paper utilizes GIS and ABM approaches to simulate spatial growth patterns of settlement structures in Shama. A preliminary household survey on residential location decision-making choice served as the behavioural rule for household agents in the model. Physical environment properties of the model were extracted from a 2005 image implemented in NetLogo. The resulting growth pattern model was compared with empirical growth patterns to ascertain the model's accuracy. The paper establishes that the development of unplanned structures and its evolving structural pattern are a function of land price, proximity to economic centres, household economic status and location decision-making patterns. The application of the proposed model underlines its potential for integration into urban planning policies and practices, and for understanding residential decision-making processes in emerging cities in developing countries. Key Words: GIS; Agent-based modelling; Growth patterns; NetLogo; Location decision making; Computational Intelligence.

An integrated theory of attention and decision making in visual signal detection.

PubMed

Smith, Philip L; Ratcliff, Roger

2009-04-01

The simplest attentional task, detecting a cued stimulus in an otherwise empty visual field, produces complex patterns of performance. Attentional cues interact with backward masks and with spatial uncertainty, and there is a dissociation in the effects of these variables on accuracy and on response time. A computational theory of performance in this task is described. The theory links visual encoding, masking, spatial attention, visual short-term memory (VSTM), and perceptual decision making in an integrated dynamic framework. The theory assumes that decisions are made by a diffusion process driven by a neurally plausible, shunting VSTM. The VSTM trace encodes the transient outputs of early visual filters in a durable form that is preserved for the time needed to make a decision. Attention increases the efficiency of VSTM encoding, either by increasing the rate of trace formation or by reducing the delay before trace formation begins. The theory provides a detailed, quantitative account of attentional effects in spatial cuing tasks at the level of response accuracy and the response time distributions. (c) 2009 APA, all rights reserved

[Co-administration of RJR-2403 with low dose of 17beta-estradiol on spatial learning in ovariectomized rats].

PubMed

Fedotova, Yu O

2013-01-01

The aim of this work was to study the influence of stimulation or blockade Nalpha7-cholinoreceptors on dynamics of spatial learning in water Morris maze and on behavior in the "open field" test in adult ovariectomized (OVX) females given with a low dose of 17beta-estradiol. Agonist of Nalpha7-cholinoreceptors - RJR-2403 (1.0 mg/kg, i.p.) or antagonist of Nalpha7-cholinoreceptors - mecamylamine (1.0 mg/kg, i.p.) treated chronically (14 days) alone and in a combination with low dose of 17beta-estradiol (0.5 micro/rat, s.c.) to OVX rats. Co-administration of RJR-2403 with low dose of 17beta-estradiol completely restored impaired spatial learning in water Morris maze in OVX females. Moreover, OVX rats treated with RJR-2403 and low dose of 17beta-estradiol demonstrated increased exploratory and grooming behavior in the "open field" test. Both mecamylamine alone and in combination with low dose of 17beta-estradiol failed to influence on spatial learning and failed to modify behavior in the "open field" test in OVX rats. The results of the present study suggest a positive effect of RJR-2403 in combination with low dose of 17beta-estradiol on spatial learning at estrogen deficiency.

Resonant Cholinergic Dynamics in Cognitive and Motor Decision-Making: Attention, Category Learning, and Choice in Neocortex, Superior Colliculus, and Optic Tectum.

PubMed

Grossberg, Stephen; Palma, Jesse; Versace, Massimiliano

2015-01-01

Freely behaving organisms need to rapidly calibrate their perceptual, cognitive, and motor decisions based on continuously changing environmental conditions. These plastic changes include sharpening or broadening of cognitive and motor attention and learning to match the behavioral demands that are imposed by changing environmental statistics. This article proposes that a shared circuit design for such flexible decision-making is used in specific cognitive and motor circuits, and that both types of circuits use acetylcholine to modulate choice selectivity. Such task-sensitive control is proposed to control thalamocortical choice of the critical features that are cognitively attended and that are incorporated through learning into prototypes of visual recognition categories. A cholinergically-modulated process of vigilance control determines if a recognition category and its attended features are abstract (low vigilance) or concrete (high vigilance). Homologous neural mechanisms of cholinergic modulation are proposed to focus attention and learn a multimodal map within the deeper layers of superior colliculus. This map enables visual, auditory, and planned movement commands to compete for attention, leading to selection of a winning position that controls where the next saccadic eye movement will go. Such map learning may be viewed as a kind of attentive motor category learning. The article hereby explicates a link between attention, learning, and cholinergic modulation during decision making within both cognitive and motor systems. Homologs between the mammalian superior colliculus and the avian optic tectum lead to predictions about how multimodal map learning may occur in the mammalian and avian brain and how such learning may be modulated by acetycholine.

Resonant Cholinergic Dynamics in Cognitive and Motor Decision-Making: Attention, Category Learning, and Choice in Neocortex, Superior Colliculus, and Optic Tectum

PubMed Central

Grossberg, Stephen; Palma, Jesse; Versace, Massimiliano

2016-01-01

Freely behaving organisms need to rapidly calibrate their perceptual, cognitive, and motor decisions based on continuously changing environmental conditions. These plastic changes include sharpening or broadening of cognitive and motor attention and learning to match the behavioral demands that are imposed by changing environmental statistics. This article proposes that a shared circuit design for such flexible decision-making is used in specific cognitive and motor circuits, and that both types of circuits use acetylcholine to modulate choice selectivity. Such task-sensitive control is proposed to control thalamocortical choice of the critical features that are cognitively attended and that are incorporated through learning into prototypes of visual recognition categories. A cholinergically-modulated process of vigilance control determines if a recognition category and its attended features are abstract (low vigilance) or concrete (high vigilance). Homologous neural mechanisms of cholinergic modulation are proposed to focus attention and learn a multimodal map within the deeper layers of superior colliculus. This map enables visual, auditory, and planned movement commands to compete for attention, leading to selection of a winning position that controls where the next saccadic eye movement will go. Such map learning may be viewed as a kind of attentive motor category learning. The article hereby explicates a link between attention, learning, and cholinergic modulation during decision making within both cognitive and motor systems. Homologs between the mammalian superior colliculus and the avian optic tectum lead to predictions about how multimodal map learning may occur in the mammalian and avian brain and how such learning may be modulated by acetycholine. PMID:26834535

A preliminary study of sex differences in brain activation during a spatial navigation task in healthy adults.

PubMed

Sneider, Jennifer Tropp; Sava, Simona; Rogowska, Jadwiga; Yurgelun-Todd, Deborah A

2011-10-01

The hippocampus plays a significant role in spatial memory processing, with sex differences being prominent on various spatial tasks. This study examined sex differences in healthy adults, using functional magnetic resonance imaging (fMRI) in areas implicated in spatial processing during navigation of a virtual analogue of the Morris water-maze. There were three conditions: learning, hidden, and visible control. There were no significant differences in performance measures. However, sex differences were found in regional brain activation during learning in the right hippocampus, right parahippocampal gyrus, and the cingulate cortex. During the hidden condition, the hippocampus, parahippocampal gyrus, and cingulate cortex were activated in both men and women. Additional brain areas involved in spatial processing may be recruited in women when learning information about the environment, by utilizing external cues (landmarks) more than do men, contributing to the observed sex differences in brain activation.

Spatial memory and navigation by honeybees on the scale of the foraging range

PubMed

Dyer

1996-01-01

Honeybees and other nesting animals face the problem of finding their way between their nest and distant feeding sites. Many studies have shown that insects can learn foraging routes in reference to both landmarks and celestial cues, but it is a major puzzle how spatial information obtained from these environmental features is encoded in memory. This paper reviews recent progress by my colleagues and me towards understanding three specific aspects of this problem in honeybees: (1) how bees learn the spatial relationships among widely separated locations in a familiar terrain; (2) how bees learn the pattern of movement of the sun over the day; and (3) whether, and if so how, bees learn the relationships between celestial cues and landmarks.

Coupled hydrological, ecological, decision and economic models for monetary valuation of riparian ecosystem services

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Brookshire, D.; Broadbent, C.; Dixon, M. D.; Brand, L. A.; Thacher, J.; Benedict, K. K.; Lansey, K. E.; Stromberg, J. C.; Stewart, S.; McIntosh, M.

2011-12-01

Water is a critical component for sustaining both natural and human systems. Yet the value of water for sustaining ecosystem services is not well quantified in monetary terms. Ideally decisions involving water resource management would include an apples-to-apples comparison of the costs and benefits in dollars of both market and non-market goods and services - human and ecosystem. To quantify the value of non-market ecosystem services, scientifically defensible relationships must be developed that link the effect of a decision (e.g. human growth) to the change in ecosystem attributes from current conditions. It is this linkage that requires the "poly-disciplinary" coupling of knowledge and models from the behavioral, physical, and ecological sciences. In our experience another key component of making this successful linkage is development of a strong poly-disciplinary scientific team that can readily communicate complex disciplinary knowledge to non-specialists outside their own discipline. The time to build such a team that communicates well and has a strong sense of trust should not be underestimated. The research described in the presentation incorporated hydrologic, vegetation, avian, economic, and decision models into an integrated framework to determine the value of changes in ecological systems that result from changes in human water use. We developed a hydro-bio-economic framework for the San Pedro River Region in Arizona that considers groundwater, stream flow, and riparian vegetation, as well as abundance, diversity, and distribution of birds. In addition, we developed a similar framework for the Middle Rio Grande of New Mexico. There are six research components for this project: (1) decision support and scenario specification, (2) regional groundwater model, (3) the riparian vegetation model, (4) the avian model, (5) methods for displaying the information gradients in the valuation survey instruments (Choice Modeling and Contingent Valuation), and (6) the economic framework. Our modeling framework began with the identification of factors that influence spatial and temporal changes in riparian vegetation on the two rivers. The linked modeling framework was then employed for making spatial predictions of the changes in presence of surface water, vegetation change, and avian populations in both river systems. An overview of the overall project will be provided, with lessons learned, and initial valuation survey results.

Learn ++.NC: combining ensemble of classifiers with dynamically weighted consult-and-vote for efficient incremental learning of new classes.

PubMed

Muhlbaier, Michael D; Topalis, Apostolos; Polikar, Robi

2009-01-01

We have previously introduced an incremental learning algorithm Learn(++), which learns novel information from consecutive data sets by generating an ensemble of classifiers with each data set, and combining them by weighted majority voting. However, Learn(++) suffers from an inherent "outvoting" problem when asked to learn a new class omega(new) introduced by a subsequent data set, as earlier classifiers not trained on this class are guaranteed to misclassify omega(new) instances. The collective votes of earlier classifiers, for an inevitably incorrect decision, then outweigh the votes of the new classifiers' correct decision on omega(new) instances--until there are enough new classifiers to counteract the unfair outvoting. This forces Learn(++) to generate an unnecessarily large number of classifiers. This paper describes Learn(++).NC, specifically designed for efficient incremental learning of multiple new classes using significantly fewer classifiers. To do so, Learn (++).NC introduces dynamically weighted consult and vote (DW-CAV), a novel voting mechanism for combining classifiers: individual classifiers consult with each other to determine which ones are most qualified to classify a given instance, and decide how much weight, if any, each classifier's decision should carry. Experiments on real-world problems indicate that the new algorithm performs remarkably well with substantially fewer classifiers, not only as compared to its predecessor Learn(++), but also as compared to several other algorithms recently proposed for similar problems.

Acute stress differentially affects spatial configuration learning in high and low cortisol-responding healthy adults

PubMed Central

Meyer, Thomas; Smeets, Tom; Giesbrecht, Timo; Quaedflieg, Conny W. E. M.; Merckelbach, Harald

2013-01-01

Background Stress and stress hormones modulate memory formation in various ways that are relevant to our understanding of stress-related psychopathology, such as posttraumatic stress disorder (PTSD). Particular relevance is attributed to efficient memory formation sustained by the hippocampus and parahippocampus. This process is thought to reduce the occurrence of intrusions and flashbacks following trauma, but may be negatively affected by acute stress. Moreover, recent evidence suggests that the efficiency of visuo-spatial processing and learning based on the hippocampal area is related to PTSD symptoms. Objective The current study investigated the effect of acute stress on spatial configuration learning using a spatial contextual cueing task (SCCT) known to heavily rely on structures in the parahippocampus. Method Acute stress was induced by subjecting participants (N = 34) to the Maastricht Acute Stress Test (MAST). Following a counterbalanced within-subject approach, the effects of stress and the ensuing hormonal (i.e., cortisol) activity on subsequent SCCT performance were compared to SCCT performance following a no-stress control condition. Results Acute stress did not impact SCCT learning overall, but opposing effects emerged for high versus low cortisol responders to the MAST. Learning scores following stress were reduced in low cortisol responders, while high cortisol-responding participants showed improved learning. Conclusions The effects of stress on spatial configuration learning were moderated by the magnitude of endogenous cortisol secretion. These findings suggest a possible mechanism by which cortisol responses serve an adaptive function during stress and trauma, and this may prove to be a promising route for future research in this area. PMID:23671762

Exploring the Structure of Spatial Representations

PubMed Central

Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

2016-01-01

It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681

Exploring medical student decisions regarding attending live lectures and using recorded lectures.

PubMed

Gupta, Anmol; Saks, Norma Susswein

2013-09-01

Student decisions about lecture attendance are based on anticipated effect on learning. Factors involved in decision-making, the use of recorded lectures and their effect on lecture attendance, all warrant investigation. This study was designed to identify factors in student decisions to attend live lectures, ways in which students use recorded lectures, and if their use affects live lecture attendance. A total of 213 first (M1) and second year (M2) medical students completed a survey about lecture attendance, and rated factors related to decisions to attend live lectures and to utilize recorded lectures. Responses were analyzed overall and by class year and gender. M1 attended a higher percentage of live lectures than M2, while both classes used the same percentage of recorded lectures. Females attended more live lectures, and used a smaller percentage of recorded lectures. The lecturer was a key in attendance decisions. Also considered were the subject and availability of other learning materials. Students use recorded lectures as replacement for live lectures and as supplement to them. Lectures, both live and recorded, are important for student learning. Decisions about lecture placement in the curriculum need to be based on course content and lecturer quality.

Effects of in-vehicle warning information displays with or without spatial compatibility on driving behaviors and response performance.

PubMed

Liu, Yung-Ching; Jhuang, Jing-Wun

2012-07-01

A driving simulator study was conducted to evaluate the effects of five in-vehicle warning information displays upon drivers' emergent response and decision performance. These displays include visual display, auditory displays with and without spatial compatibility, hybrid displays in both visual and auditory format with and without spatial compatibility. Thirty volunteer drivers were recruited to perform various tasks that involved driving, stimulus-response, divided attention and stress rating. Results show that for displays of single-modality, drivers benefited more when coping with visual display of warning information than auditory display with or without spatial compatibility. However, auditory display with spatial compatibility significantly improved drivers' performance in reacting to the divided attention task and making accurate S-R task decision. Drivers' best performance results were obtained for hybrid display with spatial compatibility. Hybrid displays enabled drivers to respond the fastest and achieve the best accuracy in both S-R and divided attention tasks. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Salience from the decision perspective: You know where it is before you know it is there.

PubMed

Zehetleitner, Michael; Müller, Hermann J

2010-12-31

In visual search for feature contrast ("odd-one-out") singletons, identical manipulations of salience, whether by varying target-distractor similarity or dimensional redundancy of target definition, had smaller effects on reaction times (RTs) for binary localization decisions than for yes/no detection decisions. According to formal models of binary decisions, identical differences in drift rates would yield larger RT differences for slow than for fast decisions. From this principle and the present findings, it follows that decisions on the presence of feature contrast singletons are slower than decisions on their location. This is at variance with two classes of standard models of visual search and object recognition that assume a serial cascade of first detection, then localization and identification of a target object, but also inconsistent with models assuming that as soon as a target is detected all its properties, spatial as well as non-spatial (e.g., its category), are available immediately. As an alternative, we propose a model of detection and localization tasks based on random walk processes, which can account for the present findings.