Application of dynamic uncertain causality graph in spacecraft fault diagnosis: Logic cycle

NASA Astrophysics Data System (ADS)

Yao, Quanying; Zhang, Qin; Liu, Peng; Yang, Ping; Zhu, Ma; Wang, Xiaochen

2017-04-01

Intelligent diagnosis system are applied to fault diagnosis in spacecraft. Dynamic Uncertain Causality Graph (DUCG) is a new probability graphic model with many advantages. In the knowledge expression of spacecraft fault diagnosis, feedback among variables is frequently encountered, which may cause directed cyclic graphs (DCGs). Probabilistic graphical models (PGMs) such as bayesian network (BN) have been widely applied in uncertain causality representation and probabilistic reasoning, but BN does not allow DCGs. In this paper, DUGG is applied to fault diagnosis in spacecraft: introducing the inference algorithm for the DUCG to deal with feedback. Now, DUCG has been tested in 16 typical faults with 100% diagnosis accuracy.

Relevance feedback for CBIR: a new approach based on probabilistic feature weighting with positive and negative examples.

PubMed

Kherfi, Mohammed Lamine; Ziou, Djemel

2006-04-01

In content-based image retrieval, understanding the user's needs is a challenging task that requires integrating him in the process of retrieval. Relevance feedback (RF) has proven to be an effective tool for taking the user's judgement into account. In this paper, we present a new RF framework based on a feature selection algorithm that nicely combines the advantages of a probabilistic formulation with those of using both the positive example (PE) and the negative example (NE). Through interaction with the user, our algorithm learns the importance he assigns to image features, and then applies the results obtained to define similarity measures that correspond better to his judgement. The use of the NE allows images undesired by the user to be discarded, thereby improving retrieval accuracy. As for the probabilistic formulation of the problem, it presents a multitude of advantages and opens the door to more modeling possibilities that achieve a good feature selection. It makes it possible to cluster the query data into classes, choose the probability law that best models each class, model missing data, and support queries with multiple PE and/or NE classes. The basic principle of our algorithm is to assign more importance to features with a high likelihood and those which distinguish well between PE classes and NE classes. The proposed algorithm was validated separately and in image retrieval context, and the experiments show that it performs a good feature selection and contributes to improving retrieval effectiveness.

Probabilistic Reversal Learning in Schizophrenia: Stability of Deficits and Potential Causal Mechanisms.

PubMed

Reddy, Lena Felice; Waltz, James A; Green, Michael F; Wynn, Jonathan K; Horan, William P

2016-07-01

Although individuals with schizophrenia show impaired feedback-driven learning on probabilistic reversal learning (PRL) tasks, the specific factors that contribute to these deficits remain unknown. Recent work has suggested several potential causes including neurocognitive impairments, clinical symptoms, and specific types of feedback-related errors. To examine this issue, we administered a PRL task to 126 stable schizophrenia outpatients and 72 matched controls, and patients were retested 4 weeks later. The task involved an initial probabilistic discrimination learning phase and subsequent reversal phases in which subjects had to adjust their responses to sudden shifts in the reinforcement contingencies. Patients showed poorer performance than controls for both the initial discrimination and reversal learning phases of the task, and performance overall showed good test-retest reliability among patients. A subgroup analysis of patients (n = 64) and controls (n = 49) with good initial discrimination learning revealed no between-group differences in reversal learning, indicating that the patients who were able to achieve all of the initial probabilistic discriminations were not impaired in reversal learning. Regarding potential contributors to impaired discrimination learning, several factors were associated with poor PRL, including higher levels of neurocognitive impairment, poor learning from both positive and negative feedback, and higher levels of indiscriminate response shifting. The results suggest that poor PRL performance in schizophrenia can be the product of multiple mechanisms. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

The effect of social rank feedback on risk taking and associated reward processes in adolescent girls

PubMed Central

Bunge, Silvia A.; Bell, Orly N.; Kriegsfeld, Lance J.; Kayser, Andrew S.; Dahl, Ronald E.

2017-01-01

Abstract The onset of adolescence is associated with an increased tendency to engage in risky behaviors and a developmental shift toward peers that contributes to increased prioritization for learning about and achieving social status. There is relatively little understanding about the specific links between these adolescent-typical phenomena, particularly regarding their neural underpinnings. Based on existing models that suggest the role of puberty in promoting adolescent status-seeking and risk-taking tendencies, we investigated the relation of pubertal hormones with behavioral and neural responses to status-relevant social information in the context of risk taking. We used a probabilistic decision task in which 11- to 13-year-old girls chose to take a risk, or not, while receiving either social rank or monetary performance feedback. While feedback type did not differentially influence risk-taking behavior, whole-brain imaging results showed that activation in the anterior insula was increased for risk taking in the social rank feedback condition compared to the monetary feedback condition. This heightened activation was more pronounced in girls with higher estradiol levels. These findings suggest that brain processes involved in adolescent risky decisions may be influenced by the desire for social-status enhancement and provide preliminary evidence for the role of pubertal hormones in enhancing this adolescent-typical social sensitivity. PMID:27614768

Feedback-based probabilistic category learning is selectively impaired in attention/hyperactivity deficit disorder.

PubMed

Gabay, Yafit; Goldfarb, Liat

2017-07-01

Although Attention-Deficit Hyperactivity Disorder (ADHD) is closely linked to executive function deficits, it has recently been attributed to procedural learning impairments that are quite distinct from the former. These observations challenge the ability of the executive function framework solely to account for the diverse range of symptoms observed in ADHD. A recent neurocomputational model emphasizes the role of striatal dopamine (DA) in explaining ADHD's broad range of deficits, but the link between this model and procedural learning impairments remains unclear. Significantly, feedback-based procedural learning is hypothesized to be disrupted in ADHD because of the involvement of striatal DA in this type of learning. In order to test this assumption, we employed two variants of a probabilistic category learning task known from the neuropsychological literature. Feedback-based (FB) and paired associate-based (PA) probabilistic category learning were employed in a non-medicated sample of ADHD participants and neurotypical participants. In the FB task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of the response. In the PA learning task, participants viewed the cue and its associated outcome simultaneously without receiving an overt response or corrective feedback. In both tasks, participants were trained across 150 trials. Learning was assessed in a subsequent test without a presentation of the outcome or corrective feedback. Results revealed an interesting disassociation in which ADHD participants performed as well as control participants in the PA task, but were impaired compared with the controls in the FB task. The learning curve during FB training differed between the two groups. Taken together, these results suggest that the ability to incrementally learn by feedback is selectively disrupted in ADHD participants. These results are discussed in relation to both the ADHD dopaminergic dysfunction model and recent findings implicating procedural learning impairments in those with ADHD. Copyright © 2017 Elsevier Inc. All rights reserved.

Probabilistic Category Learning in Developmental Dyslexia: Evidence from Feedback and Paired-Associate Weather Prediction Tasks

PubMed Central

Gabay, Yafit; Vakil, Eli; Schiff, Rachel; Holt, Lori L.

2015-01-01

Objective Developmental dyslexia is presumed to arise from specific phonological impairments. However, an emerging theoretical framework suggests that phonological impairments may be symptoms stemming from an underlying dysfunction of procedural learning. Method We tested procedural learning in adults with dyslexia (n=15) and matched-controls (n=15) using two versions of the Weather Prediction Task: Feedback (FB) and Paired-associate (PA). In the FB-based task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of response. In the PA-based learning task, participants viewed the cue and its associated outcome simultaneously without overt response or feedback. In both versions, participants trained across 150 trials. Learning was assessed in a subsequent test without presentation of the outcome, or corrective feedback. Results The Dyslexia group exhibited impaired learning compared with the Control group on both the FB and PA versions of the weather prediction task. Conclusions The results indicate that the ability to learn by feedback is not selectively impaired in dyslexia. Rather it seems that the probabilistic nature of the task, shared by the FB and PA versions of the weather prediction task, hampers learning in those with dyslexia. Results are discussed in light of procedural learning impairments among participants with dyslexia. PMID:25730732

System Risk Assessment and Allocation in Conceptual Design

NASA Technical Reports Server (NTRS)

Mahadevan, Sankaran; Smith, Natasha L.; Zang, Thomas A. (Technical Monitor)

2003-01-01

As aerospace systems continue to evolve in addressing newer challenges in air and space transportation, there exists a heightened priority for significant improvement in system performance, cost effectiveness, reliability, and safety. Tools, which synthesize multidisciplinary integration, probabilistic analysis, and optimization, are needed to facilitate design decisions allowing trade-offs between cost and reliability. This study investigates tools for probabilistic analysis and probabilistic optimization in the multidisciplinary design of aerospace systems. A probabilistic optimization methodology is demonstrated for the low-fidelity design of a reusable launch vehicle at two levels, a global geometry design and a local tank design. Probabilistic analysis is performed on a high fidelity analysis of a Navy missile system. Furthermore, decoupling strategies are introduced to reduce the computational effort required for multidisciplinary systems with feedback coupling.

Performance monitoring and empathy during active and observational learning in patients with major depression.

PubMed

Thoma, Patrizia; Norra, Christine; Juckel, Georg; Suchan, Boris; Bellebaum, Christian

2015-07-01

Previous literature established a link between major depressive disorder (MDD) and altered reward processing as well as between empathy and (observational) reward learning. The aim of the present study was to assess the effects of MDD on the electrophysiological correlates - the feedback-related negativity (FRN) and the P300 - of active and observational reward processing and to relate them to trait cognitive and affective empathy. Eighteen patients with MDD and 16 healthy controls performed an active and an observational probabilistic reward-learning task while event- related potentials were recorded. Also, participants were assessed with regard to self-reported cognitive and affective trait empathy. Relative to healthy controls, patients with MDD showed overall impaired learning and attenuated FRN amplitudes, irrespective of feedback valence and learning type (active vs. observational), but comparable P300 amplitudes. In the patient group, but not in controls, higher trait perspective taking scores were significantly correlated with reduced FRN amplitudes. The pattern of results suggests impaired prediction error processing and a negative effect of higher trait empathy on feedback-based learning in patients with MDD. Copyright © 2015 Elsevier B.V. All rights reserved.

Summing up the noise in gene networks

NASA Astrophysics Data System (ADS)

Paulsson, Johan

2004-01-01

Random fluctuations in genetic networks are inevitable as chemical reactions are probabilistic and many genes, RNAs and proteins are present in low numbers per cell. Such `noise' affects all life processes and has recently been measured using green fluorescent protein (GFP). Two studies show that negative feedback suppresses noise, and three others identify the sources of noise in gene expression. Here I critically analyse these studies and present a simple equation that unifies and extends both the mathematical and biological perspectives.

Self-ordering and complexity in epizonal mineral deposits

USGS Publications Warehouse

Henley, Richard W.; Berger, Byron R.

2000-01-01

Giant deposits are relatively rare and develop where efficient metal deposition is spatially focused by repetitive brittle failure in active fault arrays. Some brief case histories are provided for epithermal, replacement, and porphyry mineralization. These highlight how rock competency contrasts and feedback between processes, rather than any single component of a hydrothermal system, govern the size of individual deposits. In turn, the recognition of the probabilistic nature of mineralization provides a firmer foundation through which exploration investment and risk management decisions can be made.

Biases in probabilistic category learning in relation to social anxiety

PubMed Central

Abraham, Anna; Hermann, Christiane

2015-01-01

Instrumental learning paradigms are rarely employed to investigate the mechanisms underlying acquired fear responses in social anxiety. Here, we adapted a probabilistic category learning paradigm to assess information processing biases as a function of the degree of social anxiety traits in a sample of healthy individuals without a diagnosis of social phobia. Participants were presented with three pairs of neutral faces with differing probabilistic accuracy contingencies (A/B: 80/20, C/D: 70/30, E/F: 60/40). Upon making their choice, negative and positive feedback was conveyed using angry and happy faces, respectively. The highly socially anxious group showed a strong tendency to be more accurate at learning the probability contingency associated with the most ambiguous stimulus pair (E/F: 60/40). Moreover, when pairing the most positively reinforced stimulus or the most negatively reinforced stimulus with all the other stimuli in a test phase, the highly socially anxious group avoided the most negatively reinforced stimulus significantly more than the control group. The results are discussed with reference to avoidance learning and hypersensitivity to negative socially evaluative information associated with social anxiety. PMID:26347685

Noradrenergic modulation of risk/reward decision making.

PubMed

Montes, David R; Stopper, Colin M; Floresco, Stan B

2015-08-01

Catecholamine transmission modulates numerous cognitive and reward-related processes that can subserve more complex functions such as cost/benefit decision making. Dopamine has been shown to play an integral role in decisions involving reward uncertainty, yet there is a paucity of research investigating the contributions of noradrenaline (NA) transmission to these functions. The present study was designed to elucidate the contribution of NA to risk/reward decision making in rats, assessed with a probabilistic discounting task. We examined the effects of reducing noradrenergic transmission with the α2 agonist clonidine (10-100 μg/kg), and increasing activity at α2A receptor sites with the agonist guanfacine (0.1-1 mg/kg), the α2 antagonist yohimbine (1-3 mg/kg), and the noradrenaline transporter (NET) inhibitor atomoxetine (0.3-3 mg/kg) on probabilistic discounting. Rats chose between a small/certain reward and a larger/risky reward, wherein the probability of obtaining the larger reward either decreased (100-12.5 %) or increased (12.5-100 %) over a session. In well-trained rats, clonidine reduced risky choice by decreasing reward sensitivity, whereas guanfacine did not affect choice behavior. Yohimbine impaired adjustments in decision biases as reward probability changed within a session by altering negative feedback sensitivity. In a subset of rats that displayed prominent discounting of probabilistic rewards, the lowest dose of atomoxetine increased preference for the large/risky reward when this option had greater long-term utility. These data highlight an important and previously uncharacterized role for noradrenergic transmission in mediating different aspects of risk/reward decision making and mediating reward and negative feedback sensitivity.

Reward Expectation Modulates Feedback-Related Negativity and EEG Spectra

PubMed Central

Cohen, Michael X; Elger, Christian E.; Ranganath, Charan

2007-01-01

The ability to evaluate outcomes of previous decisions is critical to adaptive decision-making. The feedback-related negativity (FRN) is an event-related potential (ERP) modulation that distinguishes losses from wins, but little is known about the effects of outcome probability on these ERP responses. Further, little is known about the frequency characteristics of feedback processing, for example, event-related oscillations and phase synchronizations. Here, we report an EEG experiment designed to address these issues. Subjects engaged in a probabilistic reinforcement learning task in which we manipulated, across blocks, the probability of winning and losing to each of two possible decision options. Behaviorally, all subjects quickly adapted their decision-making to maximize rewards. ERP analyses revealed that the probability of reward modulated neural responses to wins, but not to losses. This was seen both across blocks as well as within blocks, as learning progressed. Frequency decomposition via complex wavelets revealed that EEG responses to losses, compared to wins, were associated with enhanced power and phase coherence in the theta frequency band. As in the ERP analyses, power and phase coherence values following wins but not losses were modulated by reward probability. Some findings between ERP and frequency analyses diverged, suggesting that these analytic approaches provide complementary insights into neural processing. These findings suggest that the neural mechanisms of feedback processing may differ between wins and losses. PMID:17257860

Increasing Dopamine Levels in the Brain Improves Feedback-Based Procedural Learning in Healthy Participants: An Artificial-Grammar-Learning Experiment

ERIC Educational Resources Information Center

de Vries, Meinou H.; Ulte, Catrin; Zwitserlood, Pienie; Szymanski, Barbara; Knecht, Stefan

2010-01-01

Recently, an increasing number of studies have suggested a role for the basal ganglia and related dopamine inputs in procedural learning, specifically when learning occurs through trial-by-trial feedback (Shohamy, Myers, Kalanithi, & Gluck. (2008). "Basal ganglia and dopamine contributions to probabilistic category learning." "Neuroscience and…

Brain function during probabilistic learning in relation to IQ and level of education.

PubMed

van den Bos, Wouter; Crone, Eveline A; Güroğlu, Berna

2012-02-15

Knowing how to adapt your behavior based on feedback lies at the core of successful learning. We investigated the relation between brain function, grey matter volume, educational level and IQ in a Dutch adolescent sample. In total 45 healthy volunteers between ages 13 and 16 were recruited from schools for pre-vocational and pre-university education. For each individual, IQ was estimated using two subtests from the WISC-III-R (similarities and block design). While in the magnetic resonance imaging (MRI) scanner, participants performed a probabilistic learning task. Behavioral comparisons showed that participants with higher IQ used a more adaptive learning strategy after receiving positive feedback. Analysis of neural activation revealed that higher IQ was associated with increased activation in DLPFC and dACC when receiving positive feedback, specifically for rules with low reward probability (i.e., unexpected positive feedback). Furthermore, VBM analyses revealed that IQ correlated positively with grey matter volume within these regions. These results provide support for IQ-related individual differences in the developmental time courses of neural circuitry supporting feedback-based learning. Current findings are interpreted in terms of a prolonged window of flexibility and opportunity for adolescents with higher IQ scores. Copyright © 2011 Elsevier Ltd. All rights reserved.

Strategies in probabilistic feedback learning in Parkinson patients OFF medication.

PubMed

Bellebaum, C; Kobza, S; Ferrea, S; Schnitzler, A; Pollok, B; Südmeyer, M

2016-04-21

Studies on classification learning suggested that altered dopamine function in Parkinson's Disease (PD) specifically affects learning from feedback. In patients OFF medication, enhanced learning from negative feedback has been described. This learning bias was not seen in observational learning from feedback, indicating different neural mechanisms for this type of learning. The present study aimed to compare the acquisition of stimulus-response-outcome associations in PD patients OFF medication and healthy control subjects in active and observational learning. 16 PD patients OFF medication and 16 controls were examined with three parallel learning tasks each, two feedback-based (active and observational) and one non-feedback-based paired associates task. No acquisition deficit was seen in the patients for any of the tasks. More detailed analyses on the learning strategies did, however, reveal that the patients showed more lose-shift responses during active feedback learning than controls, and that lose-shift and win-stay responses more strongly determined performance accuracy in patients than controls. For observational feedback learning, the performance of both groups correlated similarly with the performance in non-feedback-based paired associates learning and with the accuracy of observed performance. Also, patients and controls showed comparable evidence of feedback processing in observational learning. In active feedback learning, PD patients use alternative learning strategies than healthy controls. Analyses on observational learning did not yield differences between patients and controls, adding to recent evidence of a differential role of the human striatum in active and observational learning from feedback. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Enhanced negative feedback responses in remitted depression.

PubMed

Santesso, Diane L; Steele, Katherine T; Bogdan, Ryan; Holmes, Avram J; Deveney, Christen M; Meites, Tiffany M; Pizzagalli, Diego A

2008-07-02

Major depressive disorder (MDD) is characterized by hypersensitivity to negative feedback that might involve frontocingulate dysfunction. MDD patients exhibit enhanced electrophysiological responses to negative internal (errors) and external (feedback) cues. Whether this dysfunction extends to remitted depressed (RD) individuals with a history of MDD is currently unknown. To address this issue, we examined the feedback-related negativity in RD and control participants using a probabilistic punishment learning task. Despite equivalent behavioral performance, RD participants showed larger feedback-related negativities to negative feedback relative to controls; group differences remained after accounting for residual anxiety and depressive symptoms. The present findings suggest that abnormal responses to negative feedback extend to samples at increased risk for depressive episodes in the absence of current symptoms.

Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

PubMed

Orhan, A Emin; Ma, Wei Ji

2017-07-26

Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

SCAP: a new methodology for safety management based on feedback from credible accident-probabilistic fault tree analysis system.

PubMed

Khan, F I; Iqbal, A; Ramesh, N; Abbasi, S A

2001-10-12

As it is conventionally done, strategies for incorporating accident--prevention measures in any hazardous chemical process industry are developed on the basis of input from risk assessment. However, the two steps-- risk assessment and hazard reduction (or safety) measures--are not linked interactively in the existing methodologies. This prevents a quantitative assessment of the impacts of safety measures on risk control. We have made an attempt to develop a methodology in which risk assessment steps are interactively linked with implementation of safety measures. The resultant system tells us the extent of reduction of risk by each successive safety measure. It also tells based on sophisticated maximum credible accident analysis (MCAA) and probabilistic fault tree analysis (PFTA) whether a given unit can ever be made 'safe'. The application of the methodology has been illustrated with a case study.

Effects of Differential Reinforcement and Rules with Feedback on Preference for Choice and Verbal Reports

ERIC Educational Resources Information Center

Karsina, Allen; Thompson, Rachel H.; Rodriguez, Nicole M.; Vanselow, Nicholas R.

2012-01-01

We evaluated the effects of differential reinforcement and accurate verbal rules with feedback on the preference for choice and the verbal reports of 6 adults. Participants earned points on a probabilistic schedule by completing the terminal links of a concurrent-chains arrangement in a computer-based game of chance. In free-choice terminal links,…

What is in the feedback? Effect of induced happiness vs. sadness on probabilistic learning with vs. without exploration.

PubMed

Bakic, Jasmina; De Raedt, Rudi; Jepma, Marieke; Pourtois, Gilles

2015-01-01

According to dominant neuropsychological theories of affect, emotions signal salience of events and in turn facilitate a wide spectrum of response options or action tendencies. Valence of an emotional experience is pivotal here, as it alters reward and punishment processing, as well as the balance between safety and risk taking, which can be translated into changes in the exploration-exploitation trade-off during reinforcement learning (RL). To test this idea, we compared the behavioral performance of three groups of participants that all completed a variant of a standard probabilistic learning task, but who differed regarding which mood state was actually induced and maintained (happy, sad or neutral). To foster a change from an exploration to an exploitation-based mode, we removed feedback information once learning was reliably established. Although changes in mood were successful, learning performance was balanced between the three groups. Critically, when focusing on exploitation-driven learning only, they did not differ either. Moreover, mood valence did not alter the learning rate or exploration per se, when titrated using complementing computational modeling. By comparing systematically these results to our previous study (Bakic et al., 2014), we found that arousal levels did differ between studies, which might account for limited modulatory effects of (positive) mood on RL in the present case. These results challenge the assumption that mood valence alone is enough to create strong shifts in the way exploitation or exploration is eventually carried out during (probabilistic) learning. In this context, we discuss the possibility that both valence and arousal are actually necessary components of the emotional mood state to yield changes in the use and exploration of incentives cues during RL.

Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval

PubMed Central

Karisani, Payam; Qin, Zhaohui S; Agichtein, Eugene

2018-01-01

Abstract The bioCADDIE dataset retrieval challenge brought together different approaches to retrieval of biomedical datasets relevant to a user’s query, expressed as a text description of a needed dataset. We describe experiments in applying a data-driven, machine learning-based approach to biomedical dataset retrieval as part of this challenge. We report on a series of experiments carried out to evaluate the performance of both probabilistic and machine learning-driven techniques from information retrieval, as applied to this challenge. Our experiments with probabilistic information retrieval methods, such as query term weight optimization, automatic query expansion and simulated user relevance feedback, demonstrate that automatically boosting the weights of important keywords in a verbose query is more effective than other methods. We also show that although there is a rich space of potential representations and features available in this domain, machine learning-based re-ranking models are not able to improve on probabilistic information retrieval techniques with the currently available training data. The models and algorithms presented in this paper can serve as a viable implementation of a search engine to provide access to biomedical datasets. The retrieval performance is expected to be further improved by using additional training data that is created by expert annotation, or gathered through usage logs, clicks and other processes during natural operation of the system. Database URL: https://github.com/emory-irlab/biocaddie PMID:29688379

Impaired implicit learning and feedback processing after stroke.

PubMed

Lam, J M; Globas, C; Hosp, J A; Karnath, H-O; Wächter, T; Luft, A R

2016-02-09

The ability to learn is assumed to support successful recovery and rehabilitation therapy after stroke. Hence, learning impairments may reduce the recovery potential. Here, the hypothesis is tested that stroke survivors have deficits in feedback-driven implicit learning. Stroke survivors (n=30) and healthy age-matched control subjects (n=21) learned a probabilistic classification task with brain activation measured using functional magnetic resonance imaging in a subset of these individuals (17 stroke and 10 controls). Stroke subjects learned slower than controls to classify cues. After being rewarded with a smiley face, they were less likely to give the same response when the cue was repeated. Stroke subjects showed reduced brain activation in putamen, pallidum, thalamus, frontal and prefrontal cortices and cerebellum when compared with controls. Lesion analysis identified those stroke survivors as learning-impaired who had lesions in frontal areas, putamen, thalamus, caudate and insula. Lesion laterality had no effect on learning efficacy or brain activation. These findings suggest that stroke survivors have deficits in reinforcement learning that may be related to dysfunctional processing of feedback-based decision-making, reward signals and working memory. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Self-reported strategies in decisions under risk: role of feedback, reasoning abilities, executive functions, short-term-memory, and working memory.

PubMed

Schiebener, Johannes; Brand, Matthias

2015-11-01

In decisions under objective risk conditions information about the decision options' possible outcomes and the rules for outcomes' occurrence are provided. Thus, deciders can base decision-making strategies on probabilistic laws. In many laboratory decision-making tasks, choosing the option with the highest winning probability in all trials (=maximization strategy) is probabilistically regarded the most rational behavior. However, individuals often behave less optimal, especially in case the individuals have lower cognitive functions or in case no feedback about consequences is provided in the situation. It is still unclear which cognitive functions particularly predispose individuals for using successful strategies and which strategies profit from feedback. We investigated 195 individuals with two decision-making paradigms, the Game of Dice Task (GDT) (with and without feedback), and the Card Guessing Game. Thereafter, participants reported which strategies they had applied. Interaction effects (feedback × strategy), effect sizes, and uncorrected single group comparisons suggest that feedback in the GDT tended to be more beneficial to individuals reporting exploratory strategies (e.g., use intuition). In both tasks, the self-reported use of more principled and more rational strategies was accompanied by better decision-making performance and better performances in reasoning and executive functioning tasks. The strategy groups did not significantly differ in most short-term and working-memory tasks. Thus, particularly individual differences in reasoning and executive functions seem to predispose individuals toward particular decision-making strategies. Feedback seems to be useful for individuals who rather explore the decision-making situation instead of following a certain plan.

The influence of trial order on learning from reward vs. punishment in a probabilistic categorization task: experimental and computational analyses.

PubMed

Moustafa, Ahmed A; Gluck, Mark A; Herzallah, Mohammad M; Myers, Catherine E

2015-01-01

Previous research has shown that trial ordering affects cognitive performance, but this has not been tested using category-learning tasks that differentiate learning from reward and punishment. Here, we tested two groups of healthy young adults using a probabilistic category learning task of reward and punishment in which there are two types of trials (reward, punishment) and three possible outcomes: (1) positive feedback for correct responses in reward trials; (2) negative feedback for incorrect responses in punishment trials; and (3) no feedback for incorrect answers in reward trials and correct answers in punishment trials. Hence, trials without feedback are ambiguous, and may represent either successful avoidance of punishment or failure to obtain reward. In Experiment 1, the first group of subjects received an intermixed task in which reward and punishment trials were presented in the same block, as a standard baseline task. In Experiment 2, a second group completed the separated task, in which reward and punishment trials were presented in separate blocks. Additionally, in order to understand the mechanisms underlying performance in the experimental conditions, we fit individual data using a Q-learning model. Results from Experiment 1 show that subjects who completed the intermixed task paradoxically valued the no-feedback outcome as a reinforcer when it occurred on reinforcement-based trials, and as a punisher when it occurred on punishment-based trials. This is supported by patterns of empirical responding, where subjects showed more win-stay behavior following an explicit reward than following an omission of punishment, and more lose-shift behavior following an explicit punisher than following an omission of reward. In Experiment 2, results showed similar performance whether subjects received reward-based or punishment-based trials first. However, when the Q-learning model was applied to these data, there were differences between subjects in the reward-first and punishment-first conditions on the relative weighting of neutral feedback. Specifically, early training on reward-based trials led to omission of reward being treated as similar to punishment, but prior training on punishment-based trials led to omission of reward being treated more neutrally. This suggests that early training on one type of trials, specifically reward-based trials, can create a bias in how neutral feedback is processed, relative to those receiving early punishment-based training or training that mixes positive and negative outcomes.

Hybrid Packet-Pheromone-Based Probabilistic Routing for Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Kashkouli Nejad, Keyvan; Shawish, Ahmed; Jiang, Xiaohong; Horiguchi, Susumu

Ad-Hoc networks are collections of mobile nodes communicating using wireless media without any fixed infrastructure. Minimal configuration and quick deployment make Ad-Hoc networks suitable for emergency situations like natural disasters or military conflicts. The current Ad-Hoc networks can only support either high mobility or high transmission rate at a time because they employ static approaches in their routing schemes. However, due to the continuous expansion of the Ad-Hoc network size, node-mobility and transmission rate, the development of new adaptive and dynamic routing schemes has become crucial. In this paper we propose a new routing scheme to support high transmission rates and high node-mobility simultaneously in a big Ad-Hoc network, by combining a new proposed packet-pheromone-based approach with the Hint Based Probabilistic Protocol (HBPP) for congestion avoidance with dynamic path selection in packet forwarding process. Because of using the available feedback information, the proposed algorithm does not introduce any additional overhead. The extensive simulation-based analysis conducted in this paper indicates that the proposed algorithm offers small packet-latency and achieves a significantly higher delivery probability in comparison with the available Hint-Based Probabilistic Protocol (HBPP).

Impairment of probabilistic reward-based learning in schizophrenia.

PubMed

Weiler, Julia A; Bellebaum, Christian; Brüne, Martin; Juckel, Georg; Daum, Irene

2009-09-01

Recent models assume that some symptoms of schizophrenia originate from defective reward processing mechanisms. Understanding the precise nature of reward-based learning impairments might thus make an important contribution to the understanding of schizophrenia and the development of treatment strategies. The present study investigated several features of probabilistic reward-based stimulus association learning, namely the acquisition of initial contingencies, reversal learning, generalization abilities, and the effects of reward magnitude. Compared to healthy controls, individuals with schizophrenia exhibited attenuated overall performance during acquisition, whereas learning rates across blocks were similar to the rates of controls. On the group level, persons with schizophrenia were, however, unable to learn the reversal of the initial reward contingencies. Exploratory analysis of only the subgroup of individuals with schizophrenia who showed significant learning during acquisition yielded deficits in reversal learning with low reward magnitudes only. There was further evidence of a mild generalization impairment of the persons with schizophrenia in an acquired equivalence task. In summary, although there was evidence of intact basic processing of reward magnitudes, individuals with schizophrenia were impaired at using this feedback for the adaptive guidance of behavior.

Regulating recognition decisions through incremental reinforcement learning.

PubMed

Han, Sanghoon; Dobbins, Ian G

2009-06-01

Does incremental reinforcement learning influence recognition memory judgments? We examined this question by subtly altering the relative validity or availability of feedback in order to differentially reinforce old or new recognition judgments. Experiment 1 probabilistically and incorrectly indicated that either misses or false alarms were correct in the context of feedback that was otherwise accurate. Experiment 2 selectively withheld feedback for either misses or false alarms in the context of feedback that was otherwise present. Both manipulations caused prominent shifts of recognition memory decision criteria that remained for considerable periods even after feedback had been altogether removed. Overall, these data demonstrate that incremental reinforcement-learning mechanisms influence the degree of caution subjects exercise when evaluating explicit memories.

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.

Behavioral and Electrophysiological Alterations for Reinforcement Learning in Manic and Euthymic Patients with Bipolar Disorder.

PubMed

Ryu, Vin; Ha, Ra Yeon; Lee, Su Jin; Ha, Kyooseob; Cho, Hyun-Sang

2017-03-01

Bipolar disorder is characterized by behavioral changes such as risk-taking and increasing goal-directed activities, which may result from altered reward processing. Patients with bipolar disorder show impaired reward learning in situations that require the integration of reinforced feedback over time. In this study, we examined the behavioral and electrophysiological characteristics of reward learning in manic and euthymic patients with bipolar disorder using a probabilistic reward task. Twenty-four manic and 20 euthymic patients with bipolar I disorder and 24 healthy control subjects performed the probabilistic reward task. We assessed response bias (RB) as a preference for the stimulus paired with the more frequent reward and feedback-related negativity (FRN) to correct identification of the rich stimulus. Both manic and euthymic patients showed significantly lower RB scores in the early learning stage (block 1) in comparison with the late learning stage (block 2 or block 3) of the task, as well as significantly lower RB scores in the early stage compared to healthy subjects. Relatively more negative FRN amplitude is elicited by no presentation of an expected reward, compared to that elicited by presentation of expected feedback. The FRN became significantly more negative from the early (block 1) to the later stages (blocks 2 and 3) in both manic and euthymic patients, but not in healthy subjects. Changes in RB scores and FRN amplitudes between blocks 2 and 3 and block 1 correlated positively in healthy controls, but correlated negatively in manic and euthymic patients. The severity of manic symptoms correlated positively with reward learning scores and negatively with the FRN. These findings suggest that patients with bipolar disorder during euthymic or manic states have behavioral and electrophysiological alterations in reward learning compared to healthy subjects. This dysfunctional reward processing may be related to the abnormal decision-making or altered goal-directed activities frequently seen in patients with bipolar disorder. © 2017 John Wiley & Sons Ltd.

Probabilistic Classification Learning with Corrective Feedback Is Selectively Impaired in Early Huntington's Disease--Evidence for the Role of the Striatum in Learning with Feedback

ERIC Educational Resources Information Center

Holl, Anna K.; Wilkinson, Leonora; Tabrizi, Sarah J.; Painold, Annamaria; Jahanshahi, Marjan

2012-01-01

In general, declarative learning is associated with the activation of the medial temporal lobes (MTL), while the basal ganglia (BG) are considered the substrate for procedural learning. More recently it has been demonstrated the distinction of these systems may not be as absolute as previously thought and that not only the explicit or implicit…

Advanced Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Technical Exchange Meeting

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

Smith, Curtis

2013-09-01

During FY13, the INL developed an advanced SMR PRA framework which has been described in the report Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Detailed Technical Framework Specification, INL/EXT-13-28974 (April 2013). In this framework, the various areas are considered: Probabilistic models to provide information specific to advanced SMRs Representation of specific SMR design issues such as having co-located modules and passive safety features Use of modern open-source and readily available analysis methods Internal and external events resulting in impacts to safety All-hazards considerations Methods to support the identification of design vulnerabilities Mechanistic and probabilistic data needs to support modelingmore » and tools In order to describe this framework more fully and obtain feedback on the proposed approaches, the INL hosted a technical exchange meeting during August 2013. This report describes the outcomes of that meeting.« less

A Unified Mathematical Definition of Classical Information Retrieval.

ERIC Educational Resources Information Center

Dominich, Sandor

2000-01-01

Presents a unified mathematical definition for the classical models of information retrieval and identifies a mathematical structure behind relevance feedback. Highlights include vector information retrieval; probabilistic information retrieval; and similarity information retrieval. (Contains 118 references.) (Author/LRW)

Striatum-medial prefrontal cortex connectivity predicts developmental changes in reinforcement learning.

PubMed

van den Bos, Wouter; Cohen, Michael X; Kahnt, Thorsten; Crone, Eveline A

2012-06-01

During development, children improve in learning from feedback to adapt their behavior. However, it is still unclear which neural mechanisms might underlie these developmental changes. In the current study, we used a reinforcement learning model to investigate neurodevelopmental changes in the representation and processing of learning signals. Sixty-seven healthy volunteers between ages 8 and 22 (children: 8-11 years, adolescents: 13-16 years, and adults: 18-22 years) performed a probabilistic learning task while in a magnetic resonance imaging scanner. The behavioral data demonstrated age differences in learning parameters with a stronger impact of negative feedback on expected value in children. Imaging data revealed that the neural representation of prediction errors was similar across age groups, but functional connectivity between the ventral striatum and the medial prefrontal cortex changed as a function of age. Furthermore, the connectivity strength predicted the tendency to alter expectations after receiving negative feedback. These findings suggest that the underlying mechanisms of developmental changes in learning are not related to differences in the neural representation of learning signals per se but rather in how learning signals are used to guide behavior and expectations.

Bidirectional Classical Stochastic Processes with Measurements and Feedback

NASA Technical Reports Server (NTRS)

Hahne, G. E.

2005-01-01

A measurement on a quantum system is said to cause the "collapse" of the quantum state vector or density matrix. An analogous collapse occurs with measurements on a classical stochastic process. This paper addresses the question of describing the response of a classical stochastic process when there is feedback from the output of a measurement to the input, and is intended to give a model for quantum-mechanical processes that occur along a space-like reaction coordinate. The classical system can be thought of in physical terms as two counterflowing probability streams, which stochastically exchange probability currents in a way that the net probability current, and hence the overall probability, suitably interpreted, is conserved. The proposed formalism extends the . mathematics of those stochastic processes describable with linear, single-step, unidirectional transition probabilities, known as Markov chains and stochastic matrices. It is shown that a certain rearrangement and combination of the input and output of two stochastic matrices of the same order yields another matrix of the same type. Each measurement causes the partial collapse of the probability current distribution in the midst of such a process, giving rise to calculable, but non-Markov, values for the ensuing modification of the system's output probability distribution. The paper concludes with an analysis of a classical probabilistic version of the so-called grandfather paradox.

The influence of trial order on learning from reward vs. punishment in a probabilistic categorization task: experimental and computational analyses

PubMed Central

Moustafa, Ahmed A.; Gluck, Mark A.; Herzallah, Mohammad M.; Myers, Catherine E.

2015-01-01

Previous research has shown that trial ordering affects cognitive performance, but this has not been tested using category-learning tasks that differentiate learning from reward and punishment. Here, we tested two groups of healthy young adults using a probabilistic category learning task of reward and punishment in which there are two types of trials (reward, punishment) and three possible outcomes: (1) positive feedback for correct responses in reward trials; (2) negative feedback for incorrect responses in punishment trials; and (3) no feedback for incorrect answers in reward trials and correct answers in punishment trials. Hence, trials without feedback are ambiguous, and may represent either successful avoidance of punishment or failure to obtain reward. In Experiment 1, the first group of subjects received an intermixed task in which reward and punishment trials were presented in the same block, as a standard baseline task. In Experiment 2, a second group completed the separated task, in which reward and punishment trials were presented in separate blocks. Additionally, in order to understand the mechanisms underlying performance in the experimental conditions, we fit individual data using a Q-learning model. Results from Experiment 1 show that subjects who completed the intermixed task paradoxically valued the no-feedback outcome as a reinforcer when it occurred on reinforcement-based trials, and as a punisher when it occurred on punishment-based trials. This is supported by patterns of empirical responding, where subjects showed more win-stay behavior following an explicit reward than following an omission of punishment, and more lose-shift behavior following an explicit punisher than following an omission of reward. In Experiment 2, results showed similar performance whether subjects received reward-based or punishment-based trials first. However, when the Q-learning model was applied to these data, there were differences between subjects in the reward-first and punishment-first conditions on the relative weighting of neutral feedback. Specifically, early training on reward-based trials led to omission of reward being treated as similar to punishment, but prior training on punishment-based trials led to omission of reward being treated more neutrally. This suggests that early training on one type of trials, specifically reward-based trials, can create a bias in how neutral feedback is processed, relative to those receiving early punishment-based training or training that mixes positive and negative outcomes. PMID:26257616

Decision making with uncertain reinforcement in children with attention deficit/hyperactivity disorder (ADHD).

PubMed

Drechsler, Renate; Rizzo, Patrizia; Steinhausen, Hans-Christoph

2010-01-01

Reward-related processes are impaired in children with ADHD. Whether these deficits can be ascribed to an aversion to delay or to an altered responsiveness to magnitude, frequency, valence, or the probability of rewards still needs to be explored. In the present study, children with ADHD and normal controls aged 7 to 10 years performed a simple probabilistic discounting task. They had to choose between alternatives where the magnitude of rewards was inversely related to the probability of outcomes. As a result, children with ADHD opted more frequently for less likely but larger rewards than normal controls. Shifts of the response category after positive or negative feedback, however, occurred as often in children with ADHD as in control children. In children with ADHD, the frequency of risky choices was correlated with neuropsychological measures of response time variability but unrelated to measures of inhibitory control. It is concluded that the tendency to select less likely but larger rewards possibly represents a separate facet of dysfunctional reward processing, independent of delay aversion or altered responsiveness to feedback.

Active and observational reward learning in adults with autism spectrum disorder: relationship with empathy in an atypical sample.

PubMed

Bellebaum, Christian; Brodmann, Katja; Thoma, Patrizia

2014-01-01

Autism spectrum disorders (ASDs) are characterised by disturbances in social behaviour. A prevailing hypothesis suggests that these problems are related to deficits in assigning rewarding value to social stimuli. The present study aimed to examine monetary reward processing in adults with ASDs by means of event-related potentials (ERPs). Ten individuals with mild ASDs (Asperger's syndrome and high-functioning autism) and 12 healthy control subjects performed an active and an observational probabilistic reward-learning task. Both groups showed similar overall learning performance. With respect to reward processing, subjects with ASDs exhibited a general reduction in feedback-related negativity (FRN) amplitude, irrespective of feedback valence and type of learning (active or observational). Individuals with ASDs showed lower scores for cognitive empathy, while affective empathy did not differ between groups. Correlation analyses revealed that higher empathy (both cognitive and affective) negatively affected performance in observational learning in controls and in active learning in ASDs (only cognitive empathy). No relationships were seen between empathy and ERPs. Reduced FRN amplitudes are discussed in terms of a deficit in fast reward processing in ASDs, which may indicate altered reward system functioning.

Uncertainty and the Social Cost of Methane Using Bayesian Constrained Climate Models

NASA Astrophysics Data System (ADS)

Errickson, F. C.; Anthoff, D.; Keller, K.

2016-12-01

Social cost estimates of greenhouse gases are important for the design of sound climate policies and are also plagued by uncertainty. One major source of uncertainty stems from the simplified representation of the climate system used in the integrated assessment models that provide these social cost estimates. We explore how uncertainty over the social cost of methane varies with the way physical processes and feedbacks in the methane cycle are modeled by (i) coupling three different methane models to a simple climate model, (ii) using MCMC to perform a Bayesian calibration of the three coupled climate models that simulates direct sampling from the joint posterior probability density function (pdf) of model parameters, and (iii) producing probabilistic climate projections that are then used to calculate the Social Cost of Methane (SCM) with the DICE and FUND integrated assessment models. We find that including a temperature feedback in the methane cycle acts as an additional constraint during the calibration process and results in a correlation between the tropospheric lifetime of methane and several climate model parameters. This correlation is not seen in the models lacking this feedback. Several of the estimated marginal pdfs of the model parameters also exhibit different distributional shapes and expected values depending on the methane model used. As a result, probabilistic projections of the climate system out to the year 2300 exhibit different levels of uncertainty and magnitudes of warming for each of the three models under an RCP8.5 scenario. We find these differences in climate projections result in differences in the distributions and expected values for our estimates of the SCM. We also examine uncertainty about the SCM by performing a Monte Carlo analysis using a distribution for the climate sensitivity while holding all other climate model parameters constant. Our SCM estimates using the Bayesian calibration are lower and exhibit less uncertainty about extremely high values in the right tail of the distribution compared to the Monte Carlo approach. This finding has important climate policy implications and suggests previous work that accounts for climate model uncertainty by only varying the climate sensitivity parameter may overestimate the SCM.

Impairments in learning by monetary rewards and alcohol-associated rewards in detoxified alcoholic patients.

PubMed

Jokisch, Daniel; Roser, Patrik; Juckel, Georg; Daum, Irene; Bellebaum, Christian

2014-07-01

Excessive alcohol consumption has been linked to structural and functional brain changes associated with cognitive, emotional, and behavioral impairments. It has been suggested that neural processing in the reward system is also affected by alcoholism. The present study aimed at further investigating reward-based associative learning and reversal learning in detoxified alcohol-dependent patients. Twenty-one detoxified alcohol-dependent patients and 26 healthy control subjects participated in a probabilistic learning task using monetary and alcohol-associated rewards as feedback stimuli indicating correct responses. Performance during acquisition and reversal learning in the different feedback conditions was analyzed. Alcohol-dependent patients and healthy control subjects showed an increase in learning performance over learning blocks during acquisition, with learning performance being significantly lower in alcohol-dependent patients. After changing the contingencies, alcohol-dependent patients exhibited impaired reversal learning and showed, in contrast to healthy controls, different learning curves for different types of rewards with no increase in performance for high monetary and alcohol-associated feedback. The present findings provide evidence that dysfunctional processing in the reward system in alcohol-dependent patients leads to alterations in reward-based learning resulting in a generally reduced performance. In addition, the results suggest that alcohol-dependent patients are, in particular, more impaired in changing an established behavior originally reinforced by high rewards. Copyright © 2014 by the Research Society on Alcoholism.

A new computational account of cognitive control over reinforcement-based decision-making: Modeling of a probabilistic learning task.

PubMed

Zendehrouh, Sareh

2015-11-01

Recent work on decision-making field offers an account of dual-system theory for decision-making process. This theory holds that this process is conducted by two main controllers: a goal-directed system and a habitual system. In the reinforcement learning (RL) domain, the habitual behaviors are connected with model-free methods, in which appropriate actions are learned through trial-and-error experiences. However, goal-directed behaviors are associated with model-based methods of RL, in which actions are selected using a model of the environment. Studies on cognitive control also suggest that during processes like decision-making, some cortical and subcortical structures work in concert to monitor the consequences of decisions and to adjust control according to current task demands. Here a computational model is presented based on dual system theory and cognitive control perspective of decision-making. The proposed model is used to simulate human performance on a variant of probabilistic learning task. The basic proposal is that the brain implements a dual controller, while an accompanying monitoring system detects some kinds of conflict including a hypothetical cost-conflict one. The simulation results address existing theories about two event-related potentials, namely error related negativity (ERN) and feedback related negativity (FRN), and explore the best account of them. Based on the results, some testable predictions are also presented. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Brain's Reward Response Occurs Even Without Actual Reward!

PubMed

Fielding, A; Fu, Y; Franz, E A

2018-06-01

What if the brain's response to reward occurs even when there is no reward? Wouldn't that be a further concern for people prone to problem gambling and other forms of addiction, like those related to eating? Electroencephalography was employed to investigate this possibility using probabilistic feedback manipulations and measures of known event-related potentials (ERPs) related to reward processing. We tested the hypothesis-that reward-based ERPs would occur even in the absence of a tangible reward and when manipulations on expectation are implicit. The well-known P300 response potential was a key focus, and was assessed in non-gambling volunteer undergraduates on a task involving experimentally-manipulated probabilities of positive or negative feedback comprising three trial types-80, 50, or 20% positive feedback. A feedback stimulus (F1) followed a guess response between two possible outcomes (implicit win/loss), and then a second feedback stimulus (F2) was presented to confirm an alleged 'win' or 'loss' (explicit win/loss). Results revealed that amplitude of the P300 in F1-locked data (implicit manipulation) was larger (more positive) on average for feedback outcomes that were manipulated to be less likely than expected. The effect is pronounced after increased time on task (later trials), even though the majority of participants were not explicitly aware of our probability manipulations. For the explicit effects in F2-locked data, no meaningful or significant effects were observed. These findings point to the existence of proposed success-response mechanisms that operate not only explicitly but also with implicit manipulations that do not involve any direct indication of a win or loss, and are not associated with tangible rewards. Thus, there seems to be a non-explicit form of perception (we call 'implicit') associated with an internal experience of wins/losses (in the absence of actual rewards or losses) that can be measured in associated brain processes. The potential significance of these findings is discussed in terms of implications for problem gambling.

Evolving autonomous learning in cognitive networks.

PubMed

Sheneman, Leigh; Hintze, Arend

2017-12-01

There are two common approaches for optimizing the performance of a machine: genetic algorithms and machine learning. A genetic algorithm is applied over many generations whereas machine learning works by applying feedback until the system meets a performance threshold. These methods have been previously combined, particularly in artificial neural networks using an external objective feedback mechanism. We adapt this approach to Markov Brains, which are evolvable networks of probabilistic and deterministic logic gates. Prior to this work MB could only adapt from one generation to the other, so we introduce feedback gates which augment their ability to learn during their lifetime. We show that Markov Brains can incorporate these feedback gates in such a way that they do not rely on an external objective feedback signal, but instead can generate internal feedback that is then used to learn. This results in a more biologically accurate model of the evolution of learning, which will enable us to study the interplay between evolution and learning and could be another step towards autonomously learning machines.

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

Effects of different feedback types on information integration in repeated monetary gambles

PubMed Central

Haffke, Peter; Hübner, Ronald

2015-01-01

Most models of risky decision making assume that all relevant information is taken into account (e.g., von Neumann and Morgenstern, 1944; Kahneman and Tversky, 1979). However, there are also some models supposing that only part of the information is considered (e.g., Brandstätter et al., 2006; Gigerenzer and Gaissmaier, 2011). To further investigate the amount of information that is usually used for decision making, and how the use depends on feedback, we conducted a series of three experiments in which participants choose between two lotteries and where no feedback, outcome feedback, and error feedback was provided, respectively. The results show that without feedback participants mostly chose the lottery with the higher winning probability, and largely ignored the potential gains. The same results occurred when the outcome of each decision was fed back. Only after presenting error feedback (i.e., signaling whether a choice was optimal or not), participants considered probabilities as well as gains, resulting in more optimal choices. We propose that outcome feedback was ineffective, because of its probabilistic and ambiguous nature. Participants improve information integration only if provided with a consistent and deterministic signal such as error feedback. PMID:25667576

Effects of different feedback types on information integration in repeated monetary gambles.

PubMed

Haffke, Peter; Hübner, Ronald

2014-01-01

Most models of risky decision making assume that all relevant information is taken into account (e.g., von Neumann and Morgenstern, 1944; Kahneman and Tversky, 1979). However, there are also some models supposing that only part of the information is considered (e.g., Brandstätter et al., 2006; Gigerenzer and Gaissmaier, 2011). To further investigate the amount of information that is usually used for decision making, and how the use depends on feedback, we conducted a series of three experiments in which participants choose between two lotteries and where no feedback, outcome feedback, and error feedback was provided, respectively. The results show that without feedback participants mostly chose the lottery with the higher winning probability, and largely ignored the potential gains. The same results occurred when the outcome of each decision was fed back. Only after presenting error feedback (i.e., signaling whether a choice was optimal or not), participants considered probabilities as well as gains, resulting in more optimal choices. We propose that outcome feedback was ineffective, because of its probabilistic and ambiguous nature. Participants improve information integration only if provided with a consistent and deterministic signal such as error feedback.

A probabilistic analysis of the crystal oscillator behavior at low drive levels

NASA Astrophysics Data System (ADS)

Shmaliy, Yuriy S.; Brendel, Rémi

2008-03-01

The paper discusses a probabilistic model of a crystal oscillator at low drive levels where the noise intensity is comparable with the oscillation amplitude. The stationary probability density of the oscillations envelope is derived and investigated for the nonlinear resonator loses. A stochastic explanation is given for the well-known phenomenon termed sleeping sickness associated with losing a facility of self-excitation by a crystal oscillator after a long storage without a power supply. It is shown that, with low drive levels leading to an insufficient feedback, a crystal oscillator generates the noise-induced oscillations rather than it absolutely "falls in sleep".

The visualisation and communication of probabilistic climate forecasts to renewable energy policy makers

NASA Astrophysics Data System (ADS)

Doblas-Reyes, F.; Steffen, S.; Lowe, R.; Davis, M.; Rodó, X.

2013-12-01

Despite the strong dependence of weather and climate variability on the renewable energy industry, and several initiatives towards demonstrating the added benefits of integrating probabilistic forecasts into energy decision making process, they are still under-utilised within the sector. Improved communication is fundamental to stimulate the use of climate forecast information within decision-making processes, in order to adapt to a highly climate dependent renewable energy industry. This paper focuses on improving the visualisation of climate forecast information, paying special attention to seasonal to decadal (s2d) timescales. This is central to enhance climate services for renewable energy, and optimise the usefulness and usability of inherently complex climate information. In the realm of the Global Framework for Climate Services (GFCS) initiative, and subsequent European projects: Seasonal-to-Decadal Climate Prediction for the Improvement of European Climate Service (SPECS) and the European Provision of Regional Impacts Assessment in Seasonal and Decadal Timescales (EUPORIAS), this paper investigates the visualisation and communication of s2d forecasts with regards to their usefulness and usability, to enable the development of a European climate service. The target end user will be renewable energy policy makers, who are central to enhance climate services for the energy industry. The overall objective is to promote the wide-range dissemination and exchange of actionable climate information based on s2d forecasts from Global Producing Centres (GPC's). Therefore, it is crucial to examine the existing main barriers and deficits. Examples of probabilistic climate forecasts from different GPC's were used to prepare a catalogue of current approaches, to assess their advantages and limitations and finally to recommend better alternatives. In parallel, interviews were conducted with renewable energy stakeholders to receive feedback for the improvement of existing visualisation techniques of forecasts. The overall aim is to establish a communication protocol for the visualisation of probabilistic climate forecasts, which does not currently exist. Global Producing Centres show their own probabilistic forecasts with limited consistency in their communication across different centres, which complicates the understanding for the end user. A communication protocol for both the visualisation and description of climate forecasts can help to introduce a standard format and message to end users from several climate-sensitive sectors, such as energy, tourism, agriculture and health. It is hoped that this work will facilitate the improvement of decision-making processes relying on forecast information and enable their wide-range dissemination based on a standardised approach.

Visualisation and communication of probabilistic climate forecasts to renewable-energy policy makers

NASA Astrophysics Data System (ADS)

Steffen, Sophie; Lowe, Rachel; Davis, Melanie; Doblas-Reyes, Francisco J.; Rodó, Xavier

2014-05-01

Despite the strong dependence on weather and climate variability of the renewable-energy industry, and the existence of several initiatives towards demonstrating the added benefits of integrating probabilistic forecasts into energy decision-making processes, weather and climate forecasts are still under-utilised within the sector. Improved communication is fundamental to stimulate the use of climate forecast information within decision-making processes, in order to adapt to a highly climate dependent renewable-energy industry. This work focuses on improving the visualisation of climate forecast information, paying special attention to seasonal time scales. This activity is central to enhance climate services for renewable energy and to optimise the usefulness and usability of inherently complex climate information. In the realm of the Global Framework for Climate Services (GFCS) initiative, and subsequent European projects: Seasonal-to-Decadal Climate Prediction for the Improvement of European Climate Service (SPECS) and the European Provision of Regional Impacts Assessment in Seasonal and Decadal Timescales (EUPORIAS), this paper investigates the visualisation and communication of seasonal forecasts with regards to their usefulness and usability, to enable the development of a European climate service. The target end user is the group of renewable-energy policy makers, who are central to enhance climate services for the energy industry. The overall objective is to promote the wide-range dissemination and exchange of actionable climate information based on seasonal forecasts from Global Producing Centres (GPCs). It examines the existing main barriers and deficits. Examples of probabilistic climate forecasts from different GPC's are used to make a catalogue of current approaches, to assess their advantages and limitations and, finally, to recommend better alternatives. Interviews have been conducted with renewable-energy stakeholders to receive feedback for the improvement of existing visualisation techniques of forecasts. The overall aim is to establish a communication protocol for the visualisation of probabilistic climate forecasts, which does not currently exist. GPCs show their own probabilistic forecasts with limited consistency in their communication across different centres, which complicates the understanding for the end user. The recommended communication protocol for both the visualisation and description of climate forecasts can help to introduce a standard format and message to end users from several climate-sensitive sectors, such as energy, tourism, agriculture and health.

Better Learning with More Error: Probabilistic Feedback Increases Sensitivity to Correlated Cues in Categorization

ERIC Educational Resources Information Center

Little, Daniel R.; Lewandowsky, Stephan

2009-01-01

Despite the fact that categories are often composed of correlated features, the evidence that people detect and use these correlations during intentional category learning has been overwhelmingly negative to date. Nonetheless, on other categorization tasks, such as feature prediction, people show evidence of correlational sensitivity. A…

The Ultimate Sampling Dilemma in Experience-Based Decision Making

ERIC Educational Resources Information Center

Fiedler, Klaus

2008-01-01

Computer simulations and 2 experiments demonstrate the ultimate sampling dilemma, which constitutes a serious obstacle to inductive inferences in a probabilistic world. Participants were asked to take the role of a manager who is to make purchasing decisions based on positive versus negative feedback about 3 providers in 2 different product…

Reinforcement learning deficits in people with schizophrenia persist after extended trials.

PubMed

Cicero, David C; Martin, Elizabeth A; Becker, Theresa M; Kerns, John G

2014-12-30

Previous research suggests that people with schizophrenia have difficulty learning from positive feedback and when learning needs to occur rapidly. However, they seem to have relatively intact learning from negative feedback when learning occurs gradually. Participants are typically given a limited amount of acquisition trials to learn the reward contingencies and then tested about what they learned. The current study examined whether participants with schizophrenia continue to display these deficits when given extra time to learn the contingences. Participants with schizophrenia and matched healthy controls completed the Probabilistic Selection Task, which measures positive and negative feedback learning separately. Participants with schizophrenia showed a deficit in learning from both positive feedback and negative feedback. These reward learning deficits persisted even if people with schizophrenia are given extra time (up to 10 blocks of 60 trials) to learn the reward contingencies. These results suggest that the observed deficits cannot be attributed solely to slower learning and instead reflect a specific deficit in reinforcement learning. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions

PubMed Central

Testolin, Alberto; Zorzi, Marco

2016-01-01

Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks) and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage. PMID:27468262

Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions.

PubMed

Testolin, Alberto; Zorzi, Marco

2016-01-01

Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks) and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage.

Dissociation between active and observational learning from positive and negative feedback in Parkinsonism.

PubMed

Kobza, Stefan; Ferrea, Stefano; Schnitzler, Alfons; Pollok, Bettina; Südmeyer, Martin; Bellebaum, Christian

2012-01-01

Feedback to both actively performed and observed behaviour allows adaptation of future actions. Positive feedback leads to increased activity of dopamine neurons in the substantia nigra, whereas dopamine neuron activity is decreased following negative feedback. Dopamine level reduction in unmedicated Parkinson's Disease patients has been shown to lead to a negative learning bias, i.e. enhanced learning from negative feedback. Recent findings suggest that the neural mechanisms of active and observational learning from feedback might differ, with the striatum playing a less prominent role in observational learning. Therefore, it was hypothesized that unmedicated Parkinson's Disease patients would show a negative learning bias only in active but not in observational learning. In a between-group design, 19 Parkinson's Disease patients and 40 healthy controls engaged in either an active or an observational probabilistic feedback-learning task. For both tasks, transfer phases aimed to assess the bias to learn better from positive or negative feedback. As expected, actively learning patients showed a negative learning bias, whereas controls learned better from positive feedback. In contrast, no difference between patients and controls emerged for observational learning, with both groups showing better learning from positive feedback. These findings add to neural models of reinforcement-learning by suggesting that dopamine-modulated input to the striatum plays a minor role in observational learning from feedback. Future research will have to elucidate the specific neural underpinnings of observational learning.

An Evaluation of the Interactive Query Expansion in an Online Library Catalogue with a Graphical User Interface.

ERIC Educational Resources Information Center

Hancock-Beaulieu, Micheline; And Others

1995-01-01

An online library catalog was used to evaluate an interactive query expansion facility based on relevance feedback for the Okapi, probabilistic, term weighting, retrieval system. A graphical user interface allowed searchers to select candidate terms extracted from relevant retrieved items to reformulate queries. Results suggested that the…

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

Ant system: optimization by a colony of cooperating agents.

PubMed

Dorigo, M; Maniezzo, V; Colorni, A

1996-01-01

An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.

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.

A Hough Transform Global Probabilistic Approach to Multiple-Subject Diffusion MRI Tractography

DTIC Science & Technology

2010-04-01

distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT A global probabilistic fiber tracking approach based on the voting process provided by...umn.edu 2 ABSTRACT A global probabilistic fiber tracking approach based on the voting process provided by the Hough transform is introduced in...criteria for aligning curves and particularly tracts. In this work, we present a global probabilistic approach inspired by the voting procedure provided

Probabilistic record linkage

PubMed Central

Sayers, Adrian; Ben-Shlomo, Yoav; Blom, Ashley W; Steele, Fiona

2016-01-01

Abstract Studies involving the use of probabilistic record linkage are becoming increasingly common. However, the methods underpinning probabilistic record linkage are not widely taught or understood, and therefore these studies can appear to be a ‘black box’ research tool. In this article, we aim to describe the process of probabilistic record linkage through a simple exemplar. We first introduce the concept of deterministic linkage and contrast this with probabilistic linkage. We illustrate each step of the process using a simple exemplar and describe the data structure required to perform a probabilistic linkage. We describe the process of calculating and interpreting matched weights and how to convert matched weights into posterior probabilities of a match using Bayes theorem. We conclude this article with a brief discussion of some of the computational demands of record linkage, how you might assess the quality of your linkage algorithm, and how epidemiologists can maximize the value of their record-linked research using robust record linkage methods. PMID:26686842

Probabilistic reversal learning is impaired in Parkinson's disease

PubMed Central

Peterson, David A.; Elliott, Christian; Song, David D.; Makeig, Scott; Sejnowski, Terrence J.; Poizner, Howard

2009-01-01

In many everyday settings, the relationship between our choices and their potentially rewarding outcomes is probabilistic and dynamic. In addition, the difficulty of the choices can vary widely. Although a large body of theoretical and empirical evidence suggests that dopamine mediates rewarded learning, the influence of dopamine in probabilistic and dynamic rewarded learning remains unclear. We adapted a probabilistic rewarded learning task originally used to study firing rates of dopamine cells in primate substantia nigra pars compacta (Morris et al. 2006) for use as a reversal learning task with humans. We sought to investigate how the dopamine depletion in Parkinson's disease (PD) affects probabilistic reward learning and adaptation to a reversal in reward contingencies. Over the course of 256 trials subjects learned to choose the more favorable from among pairs of images with small or large differences in reward probabilities. During a subsequent otherwise identical reversal phase, the reward probability contingencies for the stimuli were reversed. Seventeen Parkinson's disease (PD) patients of mild to moderate severity were studied off of their dopaminergic medications and compared to 15 age-matched controls. Compared to controls, PD patients had distinct pre- and post-reversal deficiencies depending upon the difficulty of the choices they had to learn. The patients also exhibited compromised adaptability to the reversal. A computational model of the subjects’ trial-by-trial choices demonstrated that the adaptability was sensitive to the gain with which patients weighted pre-reversal feedback. Collectively, the results implicate the nigral dopaminergic system in learning to make choices in environments with probabilistic and dynamic reward contingencies. PMID:19628022

Drift diffusion model of reward and punishment learning in schizophrenia: Modeling and experimental data.

PubMed

Moustafa, Ahmed A; Kéri, Szabolcs; Somlai, Zsuzsanna; Balsdon, Tarryn; Frydecka, Dorota; Misiak, Blazej; White, Corey

2015-09-15

In this study, we tested reward- and punishment learning performance using a probabilistic classification learning task in patients with schizophrenia (n=37) and healthy controls (n=48). We also fit subjects' data using a Drift Diffusion Model (DDM) of simple decisions to investigate which components of the decision process differ between patients and controls. Modeling results show between-group differences in multiple components of the decision process. Specifically, patients had slower motor/encoding time, higher response caution (favoring accuracy over speed), and a deficit in classification learning for punishment, but not reward, trials. The results suggest that patients with schizophrenia adopt a compensatory strategy of favoring accuracy over speed to improve performance, yet still show signs of a deficit in learning based on negative feedback. Our data highlights the importance of applying fitting models (particularly drift diffusion models) to behavioral data. The implications of these findings are discussed relative to theories of schizophrenia and cognitive processing. Copyright © 2015 Elsevier B.V. All rights reserved.

Dissociation between Active and Observational Learning from Positive and Negative Feedback in Parkinsonism

PubMed Central

Kobza, Stefan; Ferrea, Stefano; Schnitzler, Alfons; Pollok, Bettina

2012-01-01

Feedback to both actively performed and observed behaviour allows adaptation of future actions. Positive feedback leads to increased activity of dopamine neurons in the substantia nigra, whereas dopamine neuron activity is decreased following negative feedback. Dopamine level reduction in unmedicated Parkinson’s Disease patients has been shown to lead to a negative learning bias, i.e. enhanced learning from negative feedback. Recent findings suggest that the neural mechanisms of active and observational learning from feedback might differ, with the striatum playing a less prominent role in observational learning. Therefore, it was hypothesized that unmedicated Parkinson’s Disease patients would show a negative learning bias only in active but not in observational learning. In a between-group design, 19 Parkinson’s Disease patients and 40 healthy controls engaged in either an active or an observational probabilistic feedback-learning task. For both tasks, transfer phases aimed to assess the bias to learn better from positive or negative feedback. As expected, actively learning patients showed a negative learning bias, whereas controls learned better from positive feedback. In contrast, no difference between patients and controls emerged for observational learning, with both groups showing better learning from positive feedback. These findings add to neural models of reinforcement-learning by suggesting that dopamine-modulated input to the striatum plays a minor role in observational learning from feedback. Future research will have to elucidate the specific neural underpinnings of observational learning. PMID:23185586

Reinforcement Learning Deficits in People with Schizophrenia Persist after Extended Trials

PubMed Central

Cicero, David C.; Martin, Elizabeth A.; Becker, Theresa M.; Kerns, John G.

2014-01-01

Previous research suggests that people with schizophrenia have difficulty learning from positive feedback and when learning needs to occur rapidly. However, they seem to have relatively intact learning from negative feedback when learning occurs gradually. Participants are typically given a limited amount of acquisition trials to learn the reward contingencies and then tested about what they learned. The current study examined whether participants with schizophrenia continue to display these deficits when given extra time to learn the contingences. Participants with schizophrenia and matched healthy controls completed the Probabilistic Selection Task, which measures positive and negative feedback learning separately. Participants with schizophrenia showed a deficit in learning from both positive and negative feedback. These reward learning deficits persisted even if people with schizophrenia are given extra time (up to 10 blocks of 60 trials) to learn the reward contingencies. These results suggest that the observed deficits cannot be attributed solely to slower learning and instead reflect a specific deficit in reinforcement learning. PMID:25172610

Query Processing for Probabilistic State Diagrams Describing Multiple Robot Navigation in an Indoor Environment

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

Czejdo, Bogdan; Bhattacharya, Sambit; Ferragut, Erik M

2012-01-01

This paper describes the syntax and semantics of multi-level state diagrams to support probabilistic behavior of cooperating robots. The techniques are presented to analyze these diagrams by querying combined robots behaviors. It is shown how to use state abstraction and transition abstraction to create, verify and process large probabilistic state diagrams.

Drift diffusion model of reward and punishment learning in rare alpha-synuclein gene carriers.

PubMed

Moustafa, Ahmed A; Kéri, Szabolcs; Polner, Bertalan; White, Corey

To understand the cognitive effects of alpha-synuclein polymorphism, we employed a drift diffusion model (DDM) to analyze reward- and punishment-guided probabilistic learning task data of participants with the rare alpha-synuclein gene duplication and age- and education-matched controls. Overall, the DDM analysis showed that, relative to controls, asymptomatic alpha-synuclein gene duplication carriers had significantly increased learning from negative feedback, while they tended to show impaired learning from positive feedback. No significant differences were found in response caution, response bias, or motor/encoding time. We here discuss the implications of these computational findings to the understanding of the neural mechanism of alpha-synuclein gene duplication.

Probabilistic modeling of discourse-aware sentence processing.

PubMed

Dubey, Amit; Keller, Frank; Sturt, Patrick

2013-07-01

Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However, such models are often limited to syntactic factors. This restriction is unrealistic in light of experimental results suggesting interactions between syntax and other forms of linguistic information in human sentence processing. To address this limitation, this article introduces two sentence processing models that augment a syntactic component with information about discourse co-reference. The novel combination of probabilistic syntactic components with co-reference classifiers permits them to more closely mimic human behavior than existing models. The first model uses a deep model of linguistics, based in part on probabilistic logic, allowing it to make qualitative predictions on experimental data; the second model uses shallow processing to make quantitative predictions on a broad-coverage reading-time corpus. Copyright © 2013 Cognitive Science Society, Inc.

Blunted neural responses to reward in remitted major depression: A high-density event-related potential study

PubMed Central

Whitton, Alexis E.; Kakani, Pragya; Foti, Dan; Van’t Veer, Ashlee; Haile, Anja; Crowley, David J.; Pizzagalli, Diego A.

2015-01-01

Background Major depressive disorder (MDD) is a highly recurrent condition, and improving our understanding of the abnormalities that persist in remitted MDD (rMDD) may provide insight into mechanisms that contribute to relapse. MDD has been characterized by reward learning deficits linked to dysfunction in frontostriatal regions. Although initial behavioral evidence of reward learning deficits in rMDD has recently emerged, it is unclear whether these reflect impairments in neural reward processing that persist into remission. Methods We examined behavioral reward learning and 128-channel event-related potentials (ERP) during a well-validated probabilistic reward task in 26 rMDD individuals and 34 never-depressed controls. Temporo-spatial principal components analysis (PCA) was used to separate overlapping ERP components, and group differences in neural activity in a priori regions were examined using low-resolution electromagnetic tomography (LORETA). Results Individuals with rMDD displayed reduced behavioral reward learning, as well as blunted ERP amplitude to reward feedback. Importantly, the reduction in ERP amplitude occurred at a PCA factor that peaked during the time at which phasic reward feedback-related signaling – hypothesized to originate in the striatum and project to the anterior cingulate cortex (ACC) – are thought to modulate scalp-recorded activity. Consistent with this, LORETA analyses revealed reduced activity in the ACC in the rMDD group, and this blunting correlated with poorer reward learning. Conclusion These findings suggest that the reward learning impairment observed in acute MDD persists into full remission and that these impairments may be attributable to abnormalities in the neural processes that support reward feedback monitoring, particularly within the ACC. PMID:26858994

Applications of Probabilistic Combiners on Linear Feedback Shift Register Sequences

DTIC Science & Technology

2016-12-01

on the resulting output strings show a drastic increase in complexity, while simultaneously passing the stringent randomness tests required by the...a three-variable function. Our tests on the resulting output strings show a drastic increase in complex- ity, while simultaneously passing the...10001101 01000010 11101001 Decryption of a message that has been encrypted using bitwise XOR is quite simple. Since each bit is its own additive inverse

Functional model of biological neural networks.

PubMed

Lo, James Ting-Ho

2010-12-01

A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.

Bayesian Action–Perception Computational Model: Interaction of Production and Recognition of Cursive Letters

PubMed Central

Gilet, Estelle; Diard, Julien; Bessière, Pierre

2011-01-01

In this paper, we study the collaboration of perception and action representations involved in cursive letter recognition and production. We propose a mathematical formulation for the whole perception–action loop, based on probabilistic modeling and Bayesian inference, which we call the Bayesian Action–Perception (BAP) model. Being a model of both perception and action processes, the purpose of this model is to study the interaction of these processes. More precisely, the model includes a feedback loop from motor production, which implements an internal simulation of movement. Motor knowledge can therefore be involved during perception tasks. In this paper, we formally define the BAP model and show how it solves the following six varied cognitive tasks using Bayesian inference: i) letter recognition (purely sensory), ii) writer recognition, iii) letter production (with different effectors), iv) copying of trajectories, v) copying of letters, and vi) letter recognition (with internal simulation of movements). We present computer simulations of each of these cognitive tasks, and discuss experimental predictions and theoretical developments. PMID:21674043

Cost effectiveness of a pharmacist-led information technology intervention for reducing rates of clinically important errors in medicines management in general practices (PINCER).

PubMed

Elliott, Rachel A; Putman, Koen D; Franklin, Matthew; Annemans, Lieven; Verhaeghe, Nick; Eden, Martin; Hayre, Jasdeep; Rodgers, Sarah; Sheikh, Aziz; Avery, Anthony J

2014-06-01

We recently showed that a pharmacist-led information technology-based intervention (PINCER) was significantly more effective in reducing medication errors in general practices than providing simple feedback on errors, with cost per error avoided at £79 (US$131). We aimed to estimate cost effectiveness of the PINCER intervention by combining effectiveness in error reduction and intervention costs with the effect of the individual errors on patient outcomes and healthcare costs, to estimate the effect on costs and QALYs. We developed Markov models for each of six medication errors targeted by PINCER. Clinical event probability, treatment pathway, resource use and costs were extracted from literature and costing tariffs. A composite probabilistic model combined patient-level error models with practice-level error rates and intervention costs from the trial. Cost per extra QALY and cost-effectiveness acceptability curves were generated from the perspective of NHS England, with a 5-year time horizon. The PINCER intervention generated £2,679 less cost and 0.81 more QALYs per practice [incremental cost-effectiveness ratio (ICER): -£3,037 per QALY] in the deterministic analysis. In the probabilistic analysis, PINCER generated 0.001 extra QALYs per practice compared with simple feedback, at £4.20 less per practice. Despite this extremely small set of differences in costs and outcomes, PINCER dominated simple feedback with a mean ICER of -£3,936 (standard error £2,970). At a ceiling 'willingness-to-pay' of £20,000/QALY, PINCER reaches 59 % probability of being cost effective. PINCER produced marginal health gain at slightly reduced overall cost. Results are uncertain due to the poor quality of data to inform the effect of avoiding errors.

Research on probabilistic information processing

NASA Technical Reports Server (NTRS)

Edwards, W.

1973-01-01

The work accomplished on probabilistic information processing (PIP) is reported. The research proposals and decision analysis are discussed along with the results of research on MSC setting, multiattribute utilities, and Bayesian research. Abstracts of reports concerning the PIP research are included.

Probabilistic switching circuits in DNA

PubMed Central

Wilhelm, Daniel; Bruck, Jehoshua

2018-01-01

A natural feature of molecular systems is their inherent stochastic behavior. A fundamental challenge related to the programming of molecular information processing systems is to develop a circuit architecture that controls the stochastic states of individual molecular events. Here we present a systematic implementation of probabilistic switching circuits, using DNA strand displacement reactions. Exploiting the intrinsic stochasticity of molecular interactions, we developed a simple, unbiased DNA switch: An input signal strand binds to the switch and releases an output signal strand with probability one-half. Using this unbiased switch as a molecular building block, we designed DNA circuits that convert an input signal to an output signal with any desired probability. Further, this probability can be switched between 2n different values by simply varying the presence or absence of n distinct DNA molecules. We demonstrated several DNA circuits that have multiple layers and feedback, including a circuit that converts an input strand to an output strand with eight different probabilities, controlled by the combination of three DNA molecules. These circuits combine the advantages of digital and analog computation: They allow a small number of distinct input molecules to control a diverse signal range of output molecules, while keeping the inputs robust to noise and the outputs at precise values. Moreover, arbitrarily complex circuit behaviors can be implemented with just a single type of molecular building block. PMID:29339484

The analysis of probability task completion; Taxonomy of probabilistic thinking-based across gender in elementary school students

NASA Astrophysics Data System (ADS)

Sari, Dwi Ivayana; Budayasa, I. Ketut; Juniati, Dwi

2017-08-01

Formulation of mathematical learning goals now is not only oriented on cognitive product, but also leads to cognitive process, which is probabilistic thinking. Probabilistic thinking is needed by students to make a decision. Elementary school students are required to develop probabilistic thinking as foundation to learn probability at higher level. A framework of probabilistic thinking of students had been developed by using SOLO taxonomy, which consists of prestructural probabilistic thinking, unistructural probabilistic thinking, multistructural probabilistic thinking and relational probabilistic thinking. This study aimed to analyze of probability task completion based on taxonomy of probabilistic thinking. The subjects were two students of fifth grade; boy and girl. Subjects were selected by giving test of mathematical ability and then based on high math ability. Subjects were given probability tasks consisting of sample space, probability of an event and probability comparison. The data analysis consisted of categorization, reduction, interpretation and conclusion. Credibility of data used time triangulation. The results was level of boy's probabilistic thinking in completing probability tasks indicated multistructural probabilistic thinking, while level of girl's probabilistic thinking in completing probability tasks indicated unistructural probabilistic thinking. The results indicated that level of boy's probabilistic thinking was higher than level of girl's probabilistic thinking. The results could contribute to curriculum developer in developing probability learning goals for elementary school students. Indeed, teachers could teach probability with regarding gender difference.

Memory Indexing: A Novel Method for Tracing Memory Processes in Complex Cognitive Tasks

ERIC Educational Resources Information Center

Renkewitz, Frank; Jahn, Georg

2012-01-01

We validate an eye-tracking method applicable for studying memory processes in complex cognitive tasks. The method is tested with a task on probabilistic inferences from memory. It provides valuable data on the time course of processing, thus clarifying previous results on heuristic probabilistic inference. Participants learned cue values of…

Fear of negative evaluation biases social evaluation inference: evidence from a probabilistic learning task.

PubMed

Button, Katherine S; Kounali, Daphne; Stapinski, Lexine; Rapee, Ronald M; Lewis, Glyn; Munafò, Marcus R

2015-01-01

Fear of negative evaluation (FNE) defines social anxiety yet the process of inferring social evaluation, and its potential role in maintaining social anxiety, is poorly understood. We developed an instrumental learning task to model social evaluation learning, predicting that FNE would specifically bias learning about the self but not others. During six test blocks (3 self-referential, 3 other-referential), participants (n = 100) met six personas and selected a word from a positive/negative pair to finish their social evaluation sentences "I think [you are / George is]…". Feedback contingencies corresponded to 3 rules, liked, neutral and disliked, with P[positive word correct] = 0.8, 0.5 and 0.2, respectively. As FNE increased participants selected fewer positive words (β = -0.4, 95% CI -0.7, -0.2, p = 0.001), which was strongest in the self-referential condition (FNE × condition 0.28, 95% CI 0.01, 0.54, p = 0.04), and the neutral and dislike rules (FNE × condition × rule, p = 0.07). At low FNE the proportion of positive words selected for self-neutral and self-disliked greatly exceeded the feedback contingency, indicating poor learning, which improved as FNE increased. FNE is associated with differences in processing social-evaluative information specifically about the self. At low FNE this manifests as insensitivity to learning negative self-referential evaluation. High FNE individuals are equally sensitive to learning positive or negative evaluation, which although objectively more accurate, may have detrimental effects on mental health.

Increased anterior cingulate cortex response precedes behavioural adaptation in anorexia nervosa

PubMed Central

Geisler, Daniel; Ritschel, Franziska; King, Joseph A.; Bernardoni, Fabio; Seidel, Maria; Boehm, Ilka; Runge, Franziska; Goschke, Thomas; Roessner, Veit; Smolka, Michael N.; Ehrlich, Stefan

2017-01-01

Patients with anorexia nervosa (AN) are characterised by increased self-control, cognitive rigidity and impairments in set-shifting, but the underlying neural mechanisms are poorly understood. Here we used functional magnetic resonance imaging (fMRI) to elucidate the neural correlates of behavioural adaptation to changes in reward contingencies in young acutely ill AN patients. Thirty-six adolescent/young adult, non-chronic female AN patients and 36 age-matched healthy females completed a well-established probabilistic reversal learning task during fMRI. We analysed hemodynamic responses in empirically-defined regions of interest during positive feedback and negative feedback not followed/followed by behavioural adaptation and conducted functional connectivity analyses. Although overall task performance was comparable between groups, AN showed increased shifting after receiving negative feedback (lose-shift behaviour) and altered dorsal anterior cingulate cortex (dACC) responses as a function of feedback. Specifically, patients had increased dACC responses (which correlated with perfectionism) and task-related coupling with amygdala preceding behavioural adaption. Given the generally preserved task performance in young AN, elevated dACC responses specifically during behavioural adaption is suggestive of increased monitoring for the need to adjust performance strategies. Higher dACC-amygdala coupling and increased adaptation after negative feedback underlines this interpretation and could be related to intolerance of uncertainty which has been suggested for AN. PMID:28198813

Atom-by-atom assembly of defect-free one-dimensional cold atom arrays.

PubMed

Endres, Manuel; Bernien, Hannes; Keesling, Alexander; Levine, Harry; Anschuetz, Eric R; Krajenbrink, Alexandre; Senko, Crystal; Vuletic, Vladan; Greiner, Markus; Lukin, Mikhail D

2016-11-25

The realization of large-scale fully controllable quantum systems is an exciting frontier in modern physical science. We use atom-by-atom assembly to implement a platform for the deterministic preparation of regular one-dimensional arrays of individually controlled cold atoms. In our approach, a measurement and feedback procedure eliminates the entropy associated with probabilistic trap occupation and results in defect-free arrays of more than 50 atoms in less than 400 milliseconds. The technique is based on fast, real-time control of 100 optical tweezers, which we use to arrange atoms in desired geometric patterns and to maintain these configurations by replacing lost atoms with surplus atoms from a reservoir. This bottom-up approach may enable controlled engineering of scalable many-body systems for quantum information processing, quantum simulations, and precision measurements. Copyright © 2016, American Association for the Advancement of Science.

Learning Additional Languages as Hierarchical Probabilistic Inference: Insights From First Language Processing.

PubMed

Pajak, Bozena; Fine, Alex B; Kleinschmidt, Dave F; Jaeger, T Florian

2016-12-01

We present a framework of second and additional language (L2/L n ) acquisition motivated by recent work on socio-indexical knowledge in first language (L1) processing. The distribution of linguistic categories covaries with socio-indexical variables (e.g., talker identity, gender, dialects). We summarize evidence that implicit probabilistic knowledge of this covariance is critical to L1 processing, and propose that L2/L n learning uses the same type of socio-indexical information to probabilistically infer latent hierarchical structure over previously learned and new languages. This structure guides the acquisition of new languages based on their inferred place within that hierarchy, and is itself continuously revised based on new input from any language. This proposal unifies L1 processing and L2/L n acquisition as probabilistic inference under uncertainty over socio-indexical structure. It also offers a new perspective on crosslinguistic influences during L2/L n learning, accommodating gradient and continued transfer (both negative and positive) from previously learned to novel languages, and vice versa.

Learning Additional Languages as Hierarchical Probabilistic Inference: Insights From First Language Processing

PubMed Central

Pajak, Bozena; Fine, Alex B.; Kleinschmidt, Dave F.; Jaeger, T. Florian

2015-01-01

We present a framework of second and additional language (L2/Ln) acquisition motivated by recent work on socio-indexical knowledge in first language (L1) processing. The distribution of linguistic categories covaries with socio-indexical variables (e.g., talker identity, gender, dialects). We summarize evidence that implicit probabilistic knowledge of this covariance is critical to L1 processing, and propose that L2/Ln learning uses the same type of socio-indexical information to probabilistically infer latent hierarchical structure over previously learned and new languages. This structure guides the acquisition of new languages based on their inferred place within that hierarchy, and is itself continuously revised based on new input from any language. This proposal unifies L1 processing and L2/Ln acquisition as probabilistic inference under uncertainty over socio-indexical structure. It also offers a new perspective on crosslinguistic influences during L2/Ln learning, accommodating gradient and continued transfer (both negative and positive) from previously learned to novel languages, and vice versa. PMID:28348442

Probabilistic Evaluation of Advanced Ceramic Matrix Composite Structures

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2003-01-01

The objective of this report is to summarize the deterministic and probabilistic structural evaluation results of two structures made with advanced ceramic composites (CMC): internally pressurized tube and uniformly loaded flange. The deterministic structural evaluation includes stress, displacement, and buckling analyses. It is carried out using the finite element code MHOST, developed for the 3-D inelastic analysis of structures that are made with advanced materials. The probabilistic evaluation is performed using the integrated probabilistic assessment of composite structures computer code IPACS. The affects of uncertainties in primitive variables related to the material, fabrication process, and loadings on the material property and structural response behavior are quantified. The primitive variables considered are: thermo-mechanical properties of fiber and matrix, fiber and void volume ratios, use temperature, and pressure. The probabilistic structural analysis and probabilistic strength results are used by IPACS to perform reliability and risk evaluation of the two structures. The results will show that the sensitivity information obtained for the two composite structures from the computational simulation can be used to alter the design process to meet desired service requirements. In addition to detailed probabilistic analysis of the two structures, the following were performed specifically on the CMC tube: (1) predicted the failure load and the buckling load, (2) performed coupled non-deterministic multi-disciplinary structural analysis, and (3) demonstrated that probabilistic sensitivities can be used to select a reduced set of design variables for optimization.

The Gain-Loss Model: A Probabilistic Skill Multimap Model for Assessing Learning Processes

ERIC Educational Resources Information Center

Robusto, Egidio; Stefanutti, Luca; Anselmi, Pasquale

2010-01-01

Within the theoretical framework of knowledge space theory, a probabilistic skill multimap model for assessing learning processes is proposed. The learning process of a student is modeled as a function of the student's knowledge and of an educational intervention on the attainment of specific skills required to solve problems in a knowledge…

The role of linguistic experience in the processing of probabilistic information in production.

PubMed

Gustafson, Erin; Goldrick, Matthew

2018-01-01

Speakers track the probability that a word will occur in a particular context and utilize this information during phonetic processing. For example, content words that have high probability within a discourse tend to be realized with reduced acoustic/articulatory properties. Such probabilistic information may influence L1 and L2 speech processing in distinct ways (reflecting differences in linguistic experience across groups and the overall difficulty of L2 speech processing). To examine this issue, L1 and L2 speakers performed a referential communication task, describing sequences of simple actions. The two groups of speakers showed similar effects of discourse-dependent probabilistic information on production, suggesting that L2 speakers can successfully track discourse-dependent probabilities and use such information to modulate phonetic processing.

Solving probability reasoning based on DNA strand displacement and probability modules.

PubMed

Zhang, Qiang; Wang, Xiaobiao; Wang, Xiaojun; Zhou, Changjun

2017-12-01

In computation biology, DNA strand displacement technology is used to simulate the computation process and has shown strong computing ability. Most researchers use it to solve logic problems, but it is only rarely used in probabilistic reasoning. To process probabilistic reasoning, a conditional probability derivation model and total probability model based on DNA strand displacement were established in this paper. The models were assessed through the game "read your mind." It has been shown to enable the application of probabilistic reasoning in genetic diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Students’ difficulties in probabilistic problem-solving

NASA Astrophysics Data System (ADS)

Arum, D. P.; Kusmayadi, T. A.; Pramudya, I.

2018-03-01

There are many errors can be identified when students solving mathematics problems, particularly in solving the probabilistic problem. This present study aims to investigate students’ difficulties in solving the probabilistic problem. It focuses on analyzing and describing students errors during solving the problem. This research used the qualitative method with case study strategy. The subjects in this research involve ten students of 9th grade that were selected by purposive sampling. Data in this research involve students’ probabilistic problem-solving result and recorded interview regarding students’ difficulties in solving the problem. Those data were analyzed descriptively using Miles and Huberman steps. The results show that students have difficulties in solving the probabilistic problem and can be divided into three categories. First difficulties relate to students’ difficulties in understanding the probabilistic problem. Second, students’ difficulties in choosing and using appropriate strategies for solving the problem. Third, students’ difficulties with the computational process in solving the problem. Based on the result seems that students still have difficulties in solving the probabilistic problem. It means that students have not able to use their knowledge and ability for responding probabilistic problem yet. Therefore, it is important for mathematics teachers to plan probabilistic learning which could optimize students probabilistic thinking ability.

Scalable DB+IR Technology: Processing Probabilistic Datalog with HySpirit.

PubMed

Frommholz, Ingo; Roelleke, Thomas

2016-01-01

Probabilistic Datalog (PDatalog, proposed in 1995) is a probabilistic variant of Datalog and a nice conceptual idea to model Information Retrieval in a logical, rule-based programming paradigm. Making PDatalog work in real-world applications requires more than probabilistic facts and rules, and the semantics associated with the evaluation of the programs. We report in this paper some of the key features of the HySpirit system required to scale the execution of PDatalog programs. Firstly, there is the requirement to express probability estimation in PDatalog. Secondly, fuzzy-like predicates are required to model vague predicates (e.g. vague match of attributes such as age or price). Thirdly, to handle large data sets there are scalability issues to be addressed, and therefore, HySpirit provides probabilistic relational indexes and parallel and distributed processing . The main contribution of this paper is a consolidated view on the methods of the HySpirit system to make PDatalog applicable in real-scale applications that involve a wide range of requirements typical for data (information) management and analysis.

Development of Probabilistic Structural Analysis Integrated with Manufacturing Processes

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.; Nagpal, Vinod K.

2007-01-01

An effort has been initiated to integrate manufacturing process simulations with probabilistic structural analyses in order to capture the important impacts of manufacturing uncertainties on component stress levels and life. Two physics-based manufacturing process models (one for powdered metal forging and the other for annular deformation resistance welding) have been linked to the NESSUS structural analysis code. This paper describes the methodology developed to perform this integration including several examples. Although this effort is still underway, particularly for full integration of a probabilistic analysis, the progress to date has been encouraging and a software interface that implements the methodology has been developed. The purpose of this paper is to report this preliminary development.

Control of Stochastic Master Equation Models of Genetic Regulatory Networks by Approximating Their Average Behavior

NASA Astrophysics Data System (ADS)

Umut Caglar, Mehmet; Pal, Ranadip

2010-10-01

The central dogma of molecular biology states that ``information cannot be transferred back from protein to either protein or nucleic acid.'' However, this assumption is not exactly correct in most of the cases. There are a lot of feedback loops and interactions between different levels of systems. These types of interactions are hard to analyze due to the lack of data in the cellular level and probabilistic nature of interactions. Probabilistic models like Stochastic Master Equation (SME) or deterministic models like differential equations (DE) can be used to analyze these types of interactions. SME models based on chemical master equation (CME) can provide detailed representation of genetic regulatory system, but their use is restricted by the large data requirements and computational costs of calculations. The differential equations models on the other hand, have low calculation costs and much more adequate to generate control procedures on the system; but they are not adequate to investigate the probabilistic nature of interactions. In this work the success of the mapping between SME and DE is analyzed, and the success of a control policy generated by DE model with respect to SME model is examined. Index Terms--- Stochastic Master Equation models, Differential Equation Models, Control Policy Design, Systems biology

Assisting Movement Training and Execution With Visual and Haptic Feedback.

PubMed

Ewerton, Marco; Rother, David; Weimar, Jakob; Kollegger, Gerrit; Wiemeyer, Josef; Peters, Jan; Maeda, Guilherme

2018-01-01

In the practice of motor skills in general, errors in the execution of movements may go unnoticed when a human instructor is not available. In this case, a computer system or robotic device able to detect movement errors and propose corrections would be of great help. This paper addresses the problem of how to detect such execution errors and how to provide feedback to the human to correct his/her motor skill using a general, principled methodology based on imitation learning. The core idea is to compare the observed skill with a probabilistic model learned from expert demonstrations. The intensity of the feedback is regulated by the likelihood of the model given the observed skill. Based on demonstrations, our system can, for example, detect errors in the writing of characters with multiple strokes. Moreover, by using a haptic device, the Haption Virtuose 6D, we demonstrate a method to generate haptic feedback based on a distribution over trajectories, which could be used as an auxiliary means of communication between an instructor and an apprentice. Additionally, given a performance measurement, the haptic device can help the human discover and perform better movements to solve a given task. In this case, the human first tries a few times to solve the task without assistance. Our framework, in turn, uses a reinforcement learning algorithm to compute haptic feedback, which guides the human toward better solutions.

Probabilistic Structural Analysis of the SRB Aft Skirt External Fitting Modification

NASA Technical Reports Server (NTRS)

Townsend, John S.; Peck, J.; Ayala, S.

1999-01-01

NASA has funded several major programs (the PSAM Project is an example) to develop Probabilistic Structural Analysis Methods and tools for engineers to apply in the design and assessment of aerospace hardware. A probabilistic finite element design tool, known as NESSUS, is used to determine the reliability of the Space Shuttle Solid Rocket Booster (SRB) aft skirt critical weld. An external bracket modification to the aft skirt provides a comparison basis for examining the details of the probabilistic analysis and its contributions to the design process.

Probabilistic Structural Analysis of the Solid Rocket Booster Aft Skirt External Fitting Modification

NASA Technical Reports Server (NTRS)

Townsend, John S.; Peck, Jeff; Ayala, Samuel

2000-01-01

NASA has funded several major programs (the Probabilistic Structural Analysis Methods Project is an example) to develop probabilistic structural analysis methods and tools for engineers to apply in the design and assessment of aerospace hardware. A probabilistic finite element software code, known as Numerical Evaluation of Stochastic Structures Under Stress, is used to determine the reliability of a critical weld of the Space Shuttle solid rocket booster aft skirt. An external bracket modification to the aft skirt provides a comparison basis for examining the details of the probabilistic analysis and its contributions to the design process. Also, analysis findings are compared with measured Space Shuttle flight data.

Probabilistic Reinforcement Learning in Adults with Autism Spectrum Disorders

PubMed Central

Solomon, Marjorie; Smith, Anne C.; Frank, Michael J.; Ly, Stanford; Carter, Cameron S.

2017-01-01

Background Autism spectrum disorders (ASDs) can be conceptualized as disorders of learning, however there have been few experimental studies taking this perspective. Methods We examined the probabilistic reinforcement learning performance of 28 adults with ASDs and 30 typically developing adults on a task requiring learning relationships between three stimulus pairs consisting of Japanese characters with feedback that was valid with different probabilities (80%, 70%, and 60%). Both univariate and Bayesian state–space data analytic methods were employed. Hypotheses were based on the extant literature as well as on neurobiological and computational models of reinforcement learning. Results Both groups learned the task after training. However, there were group differences in early learning in the first task block where individuals with ASDs acquired the most frequently accurately reinforced stimulus pair (80%) comparably to typically developing individuals; exhibited poorer acquisition of the less frequently reinforced 70% pair as assessed by state–space learning curves; and outperformed typically developing individuals on the near chance (60%) pair. Individuals with ASDs also demonstrated deficits in using positive feedback to exploit rewarded choices. Conclusions Results support the contention that individuals with ASDs are slower learners. Based on neurobiology and on the results of computational modeling, one interpretation of this pattern of findings is that impairments are related to deficits in flexible updating of reinforcement history as mediated by the orbito-frontal cortex, with spared functioning of the basal ganglia. This hypothesis about the pathophysiology of learning in ASDs can be tested using functional magnetic resonance imaging. PMID:21425243

Probabilistic Structural Analysis Methods (PSAM) for Select Space Propulsion System Components

NASA Technical Reports Server (NTRS)

1999-01-01

Probabilistic Structural Analysis Methods (PSAM) are described for the probabilistic structural analysis of engine components for current and future space propulsion systems. Components for these systems are subjected to stochastic thermomechanical launch loads. Uncertainties or randomness also occurs in material properties, structural geometry, and boundary conditions. Material property stochasticity, such as in modulus of elasticity or yield strength, exists in every structure and is a consequence of variations in material composition and manufacturing processes. Procedures are outlined for computing the probabilistic structural response or reliability of the structural components. The response variables include static or dynamic deflections, strains, and stresses at one or several locations, natural frequencies, fatigue or creep life, etc. Sample cases illustrates how the PSAM methods and codes simulate input uncertainties and compute probabilistic response or reliability using a finite element model with probabilistic methods.

Process for computing geometric perturbations for probabilistic analysis

DOEpatents

Fitch, Simeon H. K. [Charlottesville, VA; Riha, David S [San Antonio, TX; Thacker, Ben H [San Antonio, TX

2012-04-10

A method for computing geometric perturbations for probabilistic analysis. The probabilistic analysis is based on finite element modeling, in which uncertainties in the modeled system are represented by changes in the nominal geometry of the model, referred to as "perturbations". These changes are accomplished using displacement vectors, which are computed for each node of a region of interest and are based on mean-value coordinate calculations.

Fear of Negative Evaluation Biases Social Evaluation Inference: Evidence from a Probabilistic Learning Task

PubMed Central

Button, Katherine S.; Kounali, Daphne; Stapinski, Lexine; Rapee, Ronald M.; Lewis, Glyn; Munafò, Marcus R.

2015-01-01

Background Fear of negative evaluation (FNE) defines social anxiety yet the process of inferring social evaluation, and its potential role in maintaining social anxiety, is poorly understood. We developed an instrumental learning task to model social evaluation learning, predicting that FNE would specifically bias learning about the self but not others. Methods During six test blocks (3 self-referential, 3 other-referential), participants (n = 100) met six personas and selected a word from a positive/negative pair to finish their social evaluation sentences “I think [you are / George is]…”. Feedback contingencies corresponded to 3 rules, liked, neutral and disliked, with P[positive word correct] = 0.8, 0.5 and 0.2, respectively. Results As FNE increased participants selected fewer positive words (β = −0.4, 95% CI −0.7, −0.2, p = 0.001), which was strongest in the self-referential condition (FNE × condition 0.28, 95% CI 0.01, 0.54, p = 0.04), and the neutral and dislike rules (FNE × condition × rule, p = 0.07). At low FNE the proportion of positive words selected for self-neutral and self-disliked greatly exceeded the feedback contingency, indicating poor learning, which improved as FNE increased. Conclusions FNE is associated with differences in processing social-evaluative information specifically about the self. At low FNE this manifests as insensitivity to learning negative self-referential evaluation. High FNE individuals are equally sensitive to learning positive or negative evaluation, which although objectively more accurate, may have detrimental effects on mental health. PMID:25853835

Spared internal but impaired external reward prediction error signals in major depressive disorder during reinforcement learning.

PubMed

Bakic, Jasmina; Pourtois, Gilles; Jepma, Marieke; Duprat, Romain; De Raedt, Rudi; Baeken, Chris

2017-01-01

Major depressive disorder (MDD) creates debilitating effects on a wide range of cognitive functions, including reinforcement learning (RL). In this study, we sought to assess whether reward processing as such, or alternatively the complex interplay between motivation and reward might potentially account for the abnormal reward-based learning in MDD. A total of 35 treatment resistant MDD patients and 44 age matched healthy controls (HCs) performed a standard probabilistic learning task. RL was titrated using behavioral, computational modeling and event-related brain potentials (ERPs) data. MDD patients showed comparable learning rate compared to HCs. However, they showed decreased lose-shift responses as well as blunted subjective evaluations of the reinforcers used during the task, relative to HCs. Moreover, MDD patients showed normal internal (at the level of error-related negativity, ERN) but abnormal external (at the level of feedback-related negativity, FRN) reward prediction error (RPE) signals during RL, selectively when additional efforts had to be made to establish learning. Collectively, these results lend support to the assumption that MDD does not impair reward processing per se during RL. Instead, it seems to alter the processing of the emotional value of (external) reinforcers during RL, when additional intrinsic motivational processes have to be engaged. © 2016 Wiley Periodicals, Inc.

Predictive Coding in Area V4: Dynamic Shape Discrimination under Partial Occlusion

PubMed Central

Choi, Hannah; Pasupathy, Anitha; Shea-Brown, Eric

2018-01-01

The primate visual system has an exquisite ability to discriminate partially occluded shapes. Recent electrophysiological recordings suggest that response dynamics in intermediate visual cortical area V4, shaped by feedback from prefrontal cortex (PFC), may play a key role. To probe the algorithms that may underlie these findings, we build and test a model of V4 and PFC interactions based on a hierarchical predictive coding framework. We propose that probabilistic inference occurs in two steps. Initially, V4 responses are driven solely by bottom-up sensory input and are thus strongly influenced by the level of occlusion. After a delay, V4 responses combine both feedforward input and feedback signals from the PFC; the latter reflect predictions made by PFC about the visual stimulus underlying V4 activity. We find that this model captures key features of V4 and PFC dynamics observed in experiments. Specifically, PFC responses are strongest for occluded stimuli and delayed responses in V4 are less sensitive to occlusion, supporting our hypothesis that the feedback signals from PFC underlie robust discrimination of occluded shapes. Thus, our study proposes that area V4 and PFC participate in hierarchical inference, with feedback signals encoding top-down predictions about occluded shapes. PMID:29566355

Stabilization of memory States by stochastic facilitating synapses.

PubMed

Miller, Paul

2013-12-06

Bistability within a small neural circuit can arise through an appropriate strength of excitatory recurrent feedback. The stability of a state of neural activity, measured by the mean dwelling time before a noise-induced transition to another state, depends on the neural firing-rate curves, the net strength of excitatory feedback, the statistics of spike times, and increases exponentially with the number of equivalent neurons in the circuit. Here, we show that such stability is greatly enhanced by synaptic facilitation and reduced by synaptic depression. We take into account the alteration in times of synaptic vesicle release, by calculating distributions of inter-release intervals of a synapse, which differ from the distribution of its incoming interspike intervals when the synapse is dynamic. In particular, release intervals produced by a Poisson spike train have a coefficient of variation greater than one when synapses are probabilistic and facilitating, whereas the coefficient of variation is less than one when synapses are depressing. However, in spite of the increased variability in postsynaptic input produced by facilitating synapses, their dominant effect is reduced synaptic efficacy at low input rates compared to high rates, which increases the curvature of neural input-output functions, leading to wider regions of bistability in parameter space and enhanced lifetimes of memory states. Our results are based on analytic methods with approximate formulae and bolstered by simulations of both Poisson processes and of circuits of noisy spiking model neurons.

Processing of action- but not stimulus-related prediction errors differs between active and observational feedback learning.

PubMed

Kobza, Stefan; Bellebaum, Christian

2015-01-01

Learning of stimulus-response-outcome associations is driven by outcome prediction errors (PEs). Previous studies have shown larger PE-dependent activity in the striatum for learning from own as compared to observed actions and the following outcomes despite comparable learning rates. We hypothesised that this finding relates primarily to a stronger integration of action and outcome information in active learners. Using functional magnetic resonance imaging, we investigated brain activations related to action-dependent PEs, reflecting the deviation between action values and obtained outcomes, and action-independent PEs, reflecting the deviation between subjective values of response-preceding cues and obtained outcomes. To this end, 16 active and 15 observational learners engaged in a probabilistic learning card-guessing paradigm. On each trial, active learners saw one out of five cues and pressed either a left or right response button to receive feedback (monetary win or loss). Each observational learner observed exactly those cues, responses and outcomes of one active learner. Learning performance was assessed in active test trials without feedback and did not differ between groups. For both types of PEs, activations were found in the globus pallidus, putamen, cerebellum, and insula in active learners. However, only for action-dependent PEs, activations in these structures and the anterior cingulate were increased in active relative to observational learners. Thus, PE-related activity in the reward system is not generally enhanced in active relative to observational learning but only for action-dependent PEs. For the cerebellum, additional activations were found across groups for cue-related uncertainty, thereby emphasising the cerebellum's role in stimulus-outcome learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Probabilistic Design and Analysis Framework

NASA Technical Reports Server (NTRS)

Strack, William C.; Nagpal, Vinod K.

2010-01-01

PRODAF is a software package designed to aid analysts and designers in conducting probabilistic analysis of components and systems. PRODAF can integrate multiple analysis programs to ease the tedious process of conducting a complex analysis process that requires the use of multiple software packages. The work uses a commercial finite element analysis (FEA) program with modules from NESSUS to conduct a probabilistic analysis of a hypothetical turbine blade, disk, and shaft model. PRODAF applies the response surface method, at the component level, and extrapolates the component-level responses to the system level. Hypothetical components of a gas turbine engine are first deterministically modeled using FEA. Variations in selected geometrical dimensions and loading conditions are analyzed to determine the effects of the stress state within each component. Geometric variations include the cord length and height for the blade, inner radius, outer radius, and thickness, which are varied for the disk. Probabilistic analysis is carried out using developing software packages like System Uncertainty Analysis (SUA) and PRODAF. PRODAF was used with a commercial deterministic FEA program in conjunction with modules from the probabilistic analysis program, NESTEM, to perturb loads and geometries to provide a reliability and sensitivity analysis. PRODAF simplified the handling of data among the various programs involved, and will work with many commercial and opensource deterministic programs, probabilistic programs, or modules.

Time Alignment as a Necessary Step in the Analysis of Sleep Probabilistic Curves

NASA Astrophysics Data System (ADS)

Rošt'áková, Zuzana; Rosipal, Roman

2018-02-01

Sleep can be characterised as a dynamic process that has a finite set of sleep stages during the night. The standard Rechtschaffen and Kales sleep model produces discrete representation of sleep and does not take into account its dynamic structure. In contrast, the continuous sleep representation provided by the probabilistic sleep model accounts for the dynamics of the sleep process. However, analysis of the sleep probabilistic curves is problematic when time misalignment is present. In this study, we highlight the necessity of curve synchronisation before further analysis. Original and in time aligned sleep probabilistic curves were transformed into a finite dimensional vector space, and their ability to predict subjects' age or daily measures is evaluated. We conclude that curve alignment significantly improves the prediction of the daily measures, especially in the case of the S2-related sleep states or slow wave sleep.

From information processing to decisions: Formalizing and comparing psychologically plausible choice models.

PubMed

Heck, Daniel W; Hilbig, Benjamin E; Moshagen, Morten

2017-08-01

Decision strategies explain how people integrate multiple sources of information to make probabilistic inferences. In the past decade, increasingly sophisticated methods have been developed to determine which strategy explains decision behavior best. We extend these efforts to test psychologically more plausible models (i.e., strategies), including a new, probabilistic version of the take-the-best (TTB) heuristic that implements a rank order of error probabilities based on sequential processing. Within a coherent statistical framework, deterministic and probabilistic versions of TTB and other strategies can directly be compared using model selection by minimum description length or the Bayes factor. In an experiment with inferences from given information, only three of 104 participants were best described by the psychologically plausible, probabilistic version of TTB. Similar as in previous studies, most participants were classified as users of weighted-additive, a strategy that integrates all available information and approximates rational decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing.

PubMed

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

PubMed Central

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. PMID:29062288

Probabilistic Estimates of Global Mean Sea Level and its Underlying Processes

NASA Astrophysics Data System (ADS)

Hay, C.; Morrow, E.; Kopp, R. E.; Mitrovica, J. X.

2015-12-01

Local sea level can vary significantly from the global mean value due to a suite of processes that includes ongoing sea-level changes due to the last ice age, land water storage, ocean circulation changes, and non-uniform sea-level changes that arise when modern-day land ice rapidly melts. Understanding these sources of spatial and temporal variability is critical to estimating past and present sea-level change and projecting future sea-level rise. Using two probabilistic techniques, a multi-model Kalman smoother and Gaussian process regression, we have reanalyzed 20th century tide gauge observations to produce a new estimate of global mean sea level (GMSL). Our methods allow us to extract global information from the sparse tide gauge field by taking advantage of the physics-based and model-derived geometry of the contributing processes. Both methods provide constraints on the sea-level contribution of glacial isostatic adjustment (GIA). The Kalman smoother tests multiple discrete models of glacial isostatic adjustment (GIA), probabilistically computing the most likely GIA model given the observations, while the Gaussian process regression characterizes the prior covariance structure of a suite of GIA models and then uses this structure to estimate the posterior distribution of local rates of GIA-induced sea-level change. We present the two methodologies, the model-derived geometries of the underlying processes, and our new probabilistic estimates of GMSL and GIA.

Effects of invalid feedback on learning and feedback-related brain activity in decision-making.

PubMed

Ernst, Benjamin; Steinhauser, Marco

2015-10-01

For adaptive decision-making it is important to utilize only relevant, valid and to ignore irrelevant feedback. The present study investigated how feedback processing in decision-making is impaired when relevant feedback is combined with irrelevant and potentially invalid feedback. We analyzed two electrophysiological markers of feedback processing, the feedback-related negativity (FRN) and the P300, in a simple decision-making task, in which participants processed feedback stimuli consisting of relevant and irrelevant feedback provided by the color and meaning of a Stroop stimulus. We found that invalid, irrelevant feedback not only impaired learning, it also altered the amplitude of the P300 to relevant feedback, suggesting an interfering effect of irrelevant feedback on the processing of relevant feedback. In contrast, no such effect on the FRN was obtained. These results indicate that detrimental effects of invalid, irrelevant feedback result from failures of controlled feedback processing. Copyright © 2015 Elsevier Inc. All rights reserved.

Conjoint-measurement framework for the study of probabilistic information processing.

NASA Technical Reports Server (NTRS)

Wallsten, T. S.

1972-01-01

The theory of conjoint measurement described by Krantz et al. (1971) is shown to indicate how a descriptive model of human processing of probabilistic information built around Bayes' rule is to be tested and how it is to be used to obtain subjective scale values. Specific relationships concerning these scale values are shown to emerge, and the theoretical prospects resulting from this development are discussed.

The Role of Informative and Ambiguous Feedback in Avoidance Behavior: Empirical and Computational Findings

PubMed Central

Moustafa, Ahmed A.; Sheynin, Jony; Myers, Catherine E.

2015-01-01

Avoidance behavior is a critical component of many psychiatric disorders, and as such, it is important to understand how avoidance behavior arises, and whether it can be modified. In this study, we used empirical and computational methods to assess the role of informational feedback and ambiguous outcome in avoidance behavior. We adapted a computer-based probabilistic classification learning task, which includes positive, negative and no-feedback outcomes; the latter outcome is ambiguous as it might signal either a successful outcome (missed punishment) or a failure (missed reward). Prior work with this task suggested that most healthy subjects viewed the no-feedback outcome as strongly positive. Interestingly, in a later version of the classification task, when healthy subjects were allowed to opt out of (i.e. avoid) responding, some subjects (“avoiders”) reliably avoided trials where there was a risk of punishment, but other subjects (“non-avoiders”) never made any avoidance responses at all. One possible interpretation is that the “non-avoiders” valued the no-feedback outcome so positively on punishment-based trials that they had little incentive to avoid. Another possible interpretation is that the outcome of an avoided trial is unspecified and that lack of information is aversive, decreasing subjects’ tendency to avoid. To examine these ideas, we here tested healthy young adults on versions of the task where avoidance responses either did or did not generate informational feedback about the optimal response. Results showed that provision of informational feedback decreased avoidance responses and also decreased categorization performance, without significantly affecting the percentage of subjects classified as “avoiders.” To better understand these results, we used a modified Q-learning model to fit individual subject data. Simulation results suggest that subjects in the feedback condition adjusted their behavior faster following better-than-expected outcomes, compared to subjects in the no-feedback condition. Additionally, in both task conditions, “avoiders” adjusted their behavior faster following worse-than-expected outcomes, and treated the ambiguous no-feedback outcome as less rewarding, compared to non-avoiders. Together, results shed light on the important role of ambiguous and informative feedback in avoidance behavior. PMID:26630279

Probabilistic Composite Design

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

1997-01-01

Probabilistic composite design is described in terms of a computational simulation. This simulation tracks probabilistically the composite design evolution from constituent materials, fabrication process, through composite mechanics and structural components. Comparisons with experimental data are provided to illustrate selection of probabilistic design allowables, test methods/specimen guidelines, and identification of in situ versus pristine strength, For example, results show that: in situ fiber tensile strength is 90% of its pristine strength; flat-wise long-tapered specimens are most suitable for setting ply tensile strength allowables: a composite radome can be designed with a reliability of 0.999999; and laminate fatigue exhibits wide-spread scatter at 90% cyclic-stress to static-strength ratios.

Probabilistic brains: knowns and unknowns

PubMed Central

Pouget, Alexandre; Beck, Jeffrey M; Ma, Wei Ji; Latham, Peter E

2015-01-01

There is strong behavioral and physiological evidence that the brain both represents probability distributions and performs probabilistic inference. Computational neuroscientists have started to shed light on how these probabilistic representations and computations might be implemented in neural circuits. One particularly appealing aspect of these theories is their generality: they can be used to model a wide range of tasks, from sensory processing to high-level cognition. To date, however, these theories have only been applied to very simple tasks. Here we discuss the challenges that will emerge as researchers start focusing their efforts on real-life computations, with a focus on probabilistic learning, structural learning and approximate inference. PMID:23955561

Establishing a probabilistic reversal learning test in mice: evidence for the processes mediating reward-stay and punishment-shift behaviour and for their modulation by serotonin.

PubMed

Ineichen, Christian; Sigrist, Hannes; Spinelli, Simona; Lesch, Klaus-Peter; Sautter, Eva; Seifritz, Erich; Pryce, Christopher R

2012-11-01

Valid animal models of psychopathology need to include behavioural readouts informed by human findings. In the probabilistic reversal learning (PRL) task, human subjects are confronted with serial reversal of the contingency between two operant stimuli and reward/punishment and, superimposed on this, a low probability (0.2) of punished correct responses/rewarded incorrect responses. In depression, reward-stay and reversals completed are unaffected but response-shift following punished correct response trials, referred to as negative feedback sensitivity (NFS), is increased. The aims of this study were to: establish an operant spatial PRL test appropriate for mice; obtain evidence for the processes mediating reward-stay and punishment-shift responding; and assess effects thereon of genetically- and pharmacologically-altered serotonin (5-HT) function. The study was conducted with wildtype (WT) and heterozygous mutant (HET) mice from a 5-HT transporter (5-HTT) null mutant strain. Mice were mildly food deprived and reward was sugar pellet and punishment was 5-s time out. Mice exhibited high motivation and adaptive reversal performance. Increased probability of punished correct response (PCR) trials per session (p = 0.1, 0.2 or 0.3) led to monotonic decrease in reward-stay and reversals completed, suggesting accurate reward prediction. NFS differed from chance-level at p PCR = 0.1, suggesting accurate punishment prediction, whereas NFS was at chance-level at p = 0.2-0.3. At p PCR = 0.1, HET mice exhibited lower NFS than WT mice. The 5-HTT blocker escitalopram was studied acutely at p PCR = 0.2: a low dose (0.5-1.5 mg/kg) resulted in decreased NFS, increased reward-stay and increased reversals completed, and similarly in WT and HET mice. This study demonstrates that testing PRL in mice can provide evidence on the regulation of reward and punishment processing that is, albeit within certain limits, of relevance to human emotional-cognitive processing, its dysfunction and treatment. Copyright © 2012 Elsevier Ltd. All rights reserved.

Probabilistic assessment of beach and dune changes

USGS Publications Warehouse

Sallenger, A.H.; Stockdon, H.; Haines, J.; Krabill, W.; Swift, R.; Brock, J.

2004-01-01

The recent availability of spatially-dense airborne lidar data makes assessment of the vulnerability of beaches and dunes to storm impacts practical over long reaches of coast. As an initial test, elevations of the tops (D high) and bases (Dlow) of foredune ridges along a 55-km reach on the northern Outer Banks, NC were found to have considerable spatial variability suggesting that different parts of the barrier island would respond differently to storms. Comparing statistics of storm wave runup to D high and Dlow, we found that net erosion due to overwash and dune retreat should be greatest at the northern and southern ends of the study area and least in the central section. This predicted spatial pattern of storm-induced erosion is similar to the spatial pattern of long-term erosion of the shoreline which may be controlled by additional processes (such as gradients in longshore transport) as well as the cross-shore processes considered here. However, consider feedback where at erosional hot spots there is a deficit of sand (caused by gradients in longshore transport) which lead to lower dunes and enhanced erosional cross-shore processes, such as overwash. Hence, the erosional hot spots would be exacerbated, further increasing the vulnerability of the beach and dunes to net erosion.

How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks

PubMed Central

Rombouts, Jaldert O.; Bohte, Sander M.; Roelfsema, Pieter R.

2015-01-01

Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions. PMID:25742003

A computational model of pattern separation efficiency in the dentate gyrus with implications in schizophrenia

PubMed Central

Faghihi, Faramarz; Moustafa, Ahmed A.

2015-01-01

Information processing in the hippocampus begins by transferring spiking activity of the entorhinal cortex (EC) into the dentate gyrus (DG). Activity pattern in the EC is separated by the DG such that it plays an important role in hippocampal functions including memory. The structural and physiological parameters of these neural networks enable the hippocampus to be efficient in encoding a large number of inputs that animals receive and process in their life time. The neural encoding capacity of the DG depends on its single neurons encoding and pattern separation efficiency. In this study, encoding by the DG is modeled such that single neurons and pattern separation efficiency are measured using simulations of different parameter values. For this purpose, a probabilistic model of single neurons efficiency is presented to study the role of structural and physiological parameters. Known neurons number of the EC and the DG is used to construct a neural network by electrophysiological features of granule cells of the DG. Separated inputs as activated neurons in the EC with different firing probabilities are presented into the DG. For different connectivity rates between the EC and DG, pattern separation efficiency of the DG is measured. The results show that in the absence of feedback inhibition on the DG neurons, the DG demonstrates low separation efficiency and high firing frequency. Feedback inhibition can increase separation efficiency while resulting in very low single neuron’s encoding efficiency in the DG and very low firing frequency of neurons in the DG (sparse spiking). This work presents a mechanistic explanation for experimental observations in the hippocampus, in combination with theoretical measures. Moreover, the model predicts a critical role for impaired inhibitory neurons in schizophrenia where deficiency in pattern separation of the DG has been observed. PMID:25859189

Probabilistic reasoning in data analysis.

PubMed

Sirovich, Lawrence

2011-09-20

This Teaching Resource provides lecture notes, slides, and a student assignment for a lecture on probabilistic reasoning in the analysis of biological data. General probabilistic frameworks are introduced, and a number of standard probability distributions are described using simple intuitive ideas. Particular attention is focused on random arrivals that are independent of prior history (Markovian events), with an emphasis on waiting times, Poisson processes, and Poisson probability distributions. The use of these various probability distributions is applied to biomedical problems, including several classic experimental studies.

The Study of the Relationship between Probabilistic Design and Axiomatic Design Methodology. Volume 1

NASA Technical Reports Server (NTRS)

Onwubiko, Chinyere; Onyebueke, Landon

1996-01-01

This program report is the final report covering all the work done on this project. The goal of this project is technology transfer of methodologies to improve design process. The specific objectives are: 1. To learn and understand the Probabilistic design analysis using NESSUS. 2. To assign Design Projects to either undergraduate or graduate students on the application of NESSUS. 3. To integrate the application of NESSUS into some selected senior level courses in Civil and Mechanical Engineering curricula. 4. To develop courseware in Probabilistic Design methodology to be included in a graduate level Design Methodology course. 5. To study the relationship between the Probabilistic design methodology and Axiomatic design methodology.

Generalized Anxiety Disorder and Social Anxiety Disorder, but Not Panic Anxiety Disorder, Are Associated with Higher Sensitivity to Learning from Negative Feedback: Behavioral and Computational Investigation

PubMed Central

Khdour, Hussain Y.; Abushalbaq, Oday M.; Mughrabi, Ibrahim T.; Imam, Aya F.; Gluck, Mark A.; Herzallah, Mohammad M.; Moustafa, Ahmed A.

2016-01-01

Anxiety disorders, including generalized anxiety disorder (GAD), social anxiety disorder (SAD), and panic anxiety disorder (PAD), are a group of common psychiatric conditions. They are characterized by excessive worrying, uneasiness, and fear of future events, such that they affect social and occupational functioning. Anxiety disorders can alter behavior and cognition as well, yet little is known about the particular domains they affect. In this study, we tested the cognitive correlates of medication-free patients with GAD, SAD, and PAD, along with matched healthy participants using a probabilistic category-learning task that allows the dissociation between positive and negative feedback learning. We also fitted all participants' data to a Q-learning model and various actor-critic models that examine learning rate parameters from positive and negative feedback to investigate effects of valence vs. action on performance. SAD and GAD patients were more sensitive to negative feedback than either PAD patients or healthy participants. PAD, SAD, and GAD patients did not differ in positive-feedback learning compared to healthy participants. We found that Q-learning models provide the simplest fit of the data in comparison to other models. However, computational analysis revealed that groups did not differ in terms of learning rate or exploration values. These findings argue that (a) not all anxiety spectrum disorders share similar cognitive correlates, but are rather different in ways that do not link them to the hallmark of anxiety (higher sensitivity to negative feedback); and (b) perception of negative consequences is the core feature of GAD and SAD, but not PAD. Further research is needed to examine the similarities and differences between anxiety spectrum disorders in other cognitive domains and potential implementation of behavioral therapy to remediate cognitive deficits. PMID:27445719

Generalized Anxiety Disorder and Social Anxiety Disorder, but Not Panic Anxiety Disorder, Are Associated with Higher Sensitivity to Learning from Negative Feedback: Behavioral and Computational Investigation.

PubMed

Khdour, Hussain Y; Abushalbaq, Oday M; Mughrabi, Ibrahim T; Imam, Aya F; Gluck, Mark A; Herzallah, Mohammad M; Moustafa, Ahmed A

2016-01-01

Anxiety disorders, including generalized anxiety disorder (GAD), social anxiety disorder (SAD), and panic anxiety disorder (PAD), are a group of common psychiatric conditions. They are characterized by excessive worrying, uneasiness, and fear of future events, such that they affect social and occupational functioning. Anxiety disorders can alter behavior and cognition as well, yet little is known about the particular domains they affect. In this study, we tested the cognitive correlates of medication-free patients with GAD, SAD, and PAD, along with matched healthy participants using a probabilistic category-learning task that allows the dissociation between positive and negative feedback learning. We also fitted all participants' data to a Q-learning model and various actor-critic models that examine learning rate parameters from positive and negative feedback to investigate effects of valence vs. action on performance. SAD and GAD patients were more sensitive to negative feedback than either PAD patients or healthy participants. PAD, SAD, and GAD patients did not differ in positive-feedback learning compared to healthy participants. We found that Q-learning models provide the simplest fit of the data in comparison to other models. However, computational analysis revealed that groups did not differ in terms of learning rate or exploration values. These findings argue that (a) not all anxiety spectrum disorders share similar cognitive correlates, but are rather different in ways that do not link them to the hallmark of anxiety (higher sensitivity to negative feedback); and (b) perception of negative consequences is the core feature of GAD and SAD, but not PAD. Further research is needed to examine the similarities and differences between anxiety spectrum disorders in other cognitive domains and potential implementation of behavioral therapy to remediate cognitive deficits.

Unsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses

NASA Astrophysics Data System (ADS)

Serb, Alexander; Bill, Johannes; Khiat, Ali; Berdan, Radu; Legenstein, Robert; Prodromakis, Themis

2016-09-01

In an increasingly data-rich world the need for developing computing systems that cannot only process, but ideally also interpret big data is becoming continuously more pressing. Brain-inspired concepts have shown great promise towards addressing this need. Here we demonstrate unsupervised learning in a probabilistic neural network that utilizes metal-oxide memristive devices as multi-state synapses. Our approach can be exploited for processing unlabelled data and can adapt to time-varying clusters that underlie incoming data by supporting the capability of reversible unsupervised learning. The potential of this work is showcased through the demonstration of successful learning in the presence of corrupted input data and probabilistic neurons, thus paving the way towards robust big-data processors.

PCEMCAN - Probabilistic Ceramic Matrix Composites Analyzer: User's Guide, Version 1.0

NASA Technical Reports Server (NTRS)

Shah, Ashwin R.; Mital, Subodh K.; Murthy, Pappu L. N.

1998-01-01

PCEMCAN (Probabalistic CEramic Matrix Composites ANalyzer) is an integrated computer code developed at NASA Lewis Research Center that simulates uncertainties associated with the constituent properties, manufacturing process, and geometric parameters of fiber reinforced ceramic matrix composites and quantifies their random thermomechanical behavior. The PCEMCAN code can perform the deterministic as well as probabilistic analyses to predict thermomechanical properties. This User's guide details the step-by-step procedure to create input file and update/modify the material properties database required to run PCEMCAN computer code. An overview of the geometric conventions, micromechanical unit cell, nonlinear constitutive relationship and probabilistic simulation methodology is also provided in the manual. Fast probability integration as well as Monte-Carlo simulation methods are available for the uncertainty simulation. Various options available in the code to simulate probabilistic material properties and quantify sensitivity of the primitive random variables have been described. The description of deterministic as well as probabilistic results have been described using demonstration problems. For detailed theoretical description of deterministic and probabilistic analyses, the user is referred to the companion documents "Computational Simulation of Continuous Fiber-Reinforced Ceramic Matrix Composite Behavior," NASA TP-3602, 1996 and "Probabilistic Micromechanics and Macromechanics for Ceramic Matrix Composites", NASA TM 4766, June 1997.

Necessary Contributions of Human Frontal Lobe Subregions to Reward Learning in a Dynamic, Multidimensional Environment.

PubMed

Vaidya, Avinash R; Fellows, Lesley K

2016-09-21

Real-world decisions are typically made between options that vary along multiple dimensions, requiring prioritization of the important dimensions to support optimal choice. Learning in this setting depends on attributing decision outcomes to the dimensions with predictive relevance rather than to dimensions that are irrelevant and nonpredictive. This attribution problem is computationally challenging, and likely requires an interplay between selective attention and reward learning. Both these processes have been separately linked to the prefrontal cortex, but little is known about how they combine to support learning the reward value of multidimensional stimuli. Here, we examined the necessary contributions of frontal lobe subregions in attributing feedback to relevant and irrelevant dimensions on a trial-by-trial basis in humans. Patients with focal frontal lobe damage completed a demanding reward learning task where options varied on three dimensions, only one of which predicted reward. Participants with left lateral frontal lobe damage attributed rewards to irrelevant dimensions, rather than the relevant dimension. Damage to the ventromedial frontal lobe also impaired learning about the relevant dimension, but did not increase reward attribution to irrelevant dimensions. The results argue for distinct roles for these two regions in learning the value of multidimensional decision options under dynamic conditions, with the lateral frontal lobe required for selecting the relevant dimension to associate with reward, and the ventromedial frontal lobe required to learn the reward association itself. The real world is complex and multidimensional; how do we attribute rewards to predictive features when surrounded by competing cues? Here, we tested the critical involvement of human frontal lobe subregions in a probabilistic, multidimensional learning environment, asking whether focal lesions affected trial-by-trial attribution of feedback to relevant and irrelevant dimensions. The left lateral frontal lobe was required for filtering option dimensions to allow appropriate feedback attribution, while the ventromedial frontal lobe was necessary for learning the value of features in the relevant dimension. These findings argue that selective attention and associative learning processes mediated by anatomically distinct frontal lobe subregions are both critical for adaptive choice in more complex, ecologically valid settings. Copyright © 2016 the authors 0270-6474/16/369843-16$15.00/0.

Processing of probabilistic information in weight perception and motor prediction.

PubMed

Trampenau, Leif; van Eimeren, Thilo; Kuhtz-Buschbeck, Johann

2017-02-01

We studied the effects of probabilistic cues, i.e., of information of limited certainty, in the context of an action task (GL: grip-lift) and of a perceptual task (WP: weight perception). Normal subjects (n = 22) saw four different probabilistic visual cues, each of which announced the likely weight of an object. In the GL task, the object was grasped and lifted with a pinch grip, and the peak force rates indicated that the grip and load forces were scaled predictively according to the probabilistic information. The WP task provided the expected heaviness related to each probabilistic cue; the participants gradually adjusted the object's weight until its heaviness matched the expected weight for a given cue. Subjects were randomly assigned to two groups: one started with the GL task and the other one with the WP task. The four different probabilistic cues influenced weight adjustments in the WP task and peak force rates in the GL task in a similar manner. The interpretation and utilization of the probabilistic information was critically influenced by the initial task. Participants who started with the WP task classified the four probabilistic cues into four distinct categories and applied these categories to the subsequent GL task. On the other side, participants who started with the GL task applied three distinct categories to the four cues and retained this classification in the following WP task. The initial strategy, once established, determined the way how the probabilistic information was interpreted and implemented.

Exploring Term Dependences in Probabilistic Information Retrieval Model.

ERIC Educational Resources Information Center

Cho, Bong-Hyun; Lee, Changki; Lee, Gary Geunbae

2003-01-01

Describes a theoretic process to apply Bahadur-Lazarsfeld expansion (BLE) to general probabilistic models and the state-of-the-art 2-Poisson model. Through experiments on two standard document collections, one in Korean and one in English, it is demonstrated that incorporation of term dependences using BLE significantly contributes to performance…

An autonomous mobile system for the management of COPD.

PubMed

van der Heijden, Maarten; Lucas, Peter J F; Lijnse, Bas; Heijdra, Yvonne F; Schermer, Tjard R J

2013-06-01

Managing chronic disease through automated systems has the potential to both benefit the patient and reduce health-care costs. We have developed and evaluated a disease management system for patients with chronic obstructive pulmonary disease (COPD). Its aim is to predict and detect exacerbations and, through this, help patients self-manage their disease to prevent hospitalisation. The carefully crafted intelligent system consists of a mobile device that is able to collect case-specific, subjective and objective, physiological data, and to alert the patient by a patient-specific interpretation of the data by means of probabilistic reasoning. Collected data are also sent to a central server for inspection by health-care professionals. We evaluated the probabilistic model using cross-validation and ROC analyses on data from an earlier study and by an independent data set. Furthermore a pilot with actual COPD patients has been conducted to test technical feasibility and to obtain user feedback. Model evaluation results show that we can reliably detect exacerbations. Pilot study results suggest that an intervention based on this system could be successful. Copyright © 2013 Elsevier Inc. All rights reserved.

Probabilistic resource allocation system with self-adaptive capability

NASA Technical Reports Server (NTRS)

Yufik, Yan M. (Inventor)

1996-01-01

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and directed links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Reliability values are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

Probabilistic resource allocation system with self-adaptive capability

NASA Technical Reports Server (NTRS)

Yufik, Yan M. (Inventor)

1998-01-01

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and weighted links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Weights are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

UTOPIAN: user-driven topic modeling based on interactive nonnegative matrix factorization.

PubMed

Choo, Jaegul; Lee, Changhyun; Reddy, Chandan K; Park, Haesun

2013-12-01

Topic modeling has been widely used for analyzing text document collections. Recently, there have been significant advancements in various topic modeling techniques, particularly in the form of probabilistic graphical modeling. State-of-the-art techniques such as Latent Dirichlet Allocation (LDA) have been successfully applied in visual text analytics. However, most of the widely-used methods based on probabilistic modeling have drawbacks in terms of consistency from multiple runs and empirical convergence. Furthermore, due to the complicatedness in the formulation and the algorithm, LDA cannot easily incorporate various types of user feedback. To tackle this problem, we propose a reliable and flexible visual analytics system for topic modeling called UTOPIAN (User-driven Topic modeling based on Interactive Nonnegative Matrix Factorization). Centered around its semi-supervised formulation, UTOPIAN enables users to interact with the topic modeling method and steer the result in a user-driven manner. We demonstrate the capability of UTOPIAN via several usage scenarios with real-world document corpuses such as InfoVis/VAST paper data set and product review data sets.

Barriers and Facilitators to Effective Feedback: A Qualitative Analysis of Data From Multispecialty Resident Focus Groups.

PubMed

Reddy, Shalini T; Zegarek, Matthew H; Fromme, H Barrett; Ryan, Michael S; Schumann, Sarah-Anne; Harris, Ilene B

2015-06-01

Despite the importance of feedback, the literature suggests that there is inadequate feedback in graduate medical education. We explored barriers and facilitators that residents in anesthesiology, emergency medicine, obstetrics and gynecology, and surgery experience with giving and receiving feedback during their clinical training. Residents from 3 geographically diverse teaching institutions were recruited to participate in focus groups in 2012. Open-ended questions prompted residents to describe their experiences with giving and receiving feedback, and discuss facilitators and barriers. Data were transcribed and analyzed using the constant comparative method associated with a grounded theory approach. A total of 19 residents participated in 1 of 3 focus groups. Five major themes related to feedback were identified: teacher factors, learner factors, feedback process, feedback content, and educational context. Unapproachable attendings, time pressures due to clinical work, and discomfort with giving negative feedback were cited as major barriers in the feedback process. Learner engagement in the process was a major facilitator in the feedback process. Residents provided insights for improving the feedback process based on their dual roles as teachers and learners. Time pressures in the learning environment may be mitigated by efforts to improve the quality of teacher-learner relationships. Forms for collecting written feedback should be augmented by faculty development to ensure meaningful use. Efforts to improve residents' comfort with giving feedback and encouraging learners to engage in the feedback process may foster an environment conducive to increasing feedback.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise.

PubMed

Herzallah, Randa

2015-03-01

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained. Copyright © 2014 Elsevier Ltd. All rights reserved.

Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation.

PubMed

Pearce, Marcus T

2018-05-11

Music perception depends on internal psychological models derived through exposure to a musical culture. It is hypothesized that this musical enculturation depends on two cognitive processes: (1) statistical learning, in which listeners acquire internal cognitive models of statistical regularities present in the music to which they are exposed; and (2) probabilistic prediction based on these learned models that enables listeners to organize and process their mental representations of music. To corroborate these hypotheses, I review research that uses a computational model of probabilistic prediction based on statistical learning (the information dynamics of music (IDyOM) model) to simulate data from empirical studies of human listeners. The results show that a broad range of psychological processes involved in music perception-expectation, emotion, memory, similarity, segmentation, and meter-can be understood in terms of a single, underlying process of probabilistic prediction using learned statistical models. Furthermore, IDyOM simulations of listeners from different musical cultures demonstrate that statistical learning can plausibly predict causal effects of differential cultural exposure to musical styles, providing a quantitative model of cultural distance. Understanding the neural basis of musical enculturation will benefit from close coordination between empirical neuroimaging and computational modeling of underlying mechanisms, as outlined here. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

Trait-Dependent Biogeography: (Re)Integrating Biology into Probabilistic Historical Biogeographical Models.

PubMed

Sukumaran, Jeet; Knowles, L Lacey

2018-06-01

The development of process-based probabilistic models for historical biogeography has transformed the field by grounding it in modern statistical hypothesis testing. However, most of these models abstract away biological differences, reducing species to interchangeable lineages. We present here the case for reintegration of biology into probabilistic historical biogeographical models, allowing a broader range of questions about biogeographical processes beyond ancestral range estimation or simple correlation between a trait and a distribution pattern, as well as allowing us to assess how inferences about ancestral ranges themselves might be impacted by differential biological traits. We show how new approaches to inference might cope with the computational challenges resulting from the increased complexity of these trait-based historical biogeographical models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Random mechanics: Nonlinear vibrations, turbulences, seisms, swells, fatigue

NASA Astrophysics Data System (ADS)

Kree, P.; Soize, C.

The random modeling of physical phenomena, together with probabilistic methods for the numerical calculation of random mechanical forces, are analytically explored. Attention is given to theoretical examinations such as probabilistic concepts, linear filtering techniques, and trajectory statistics. Applications of the methods to structures experiencing atmospheric turbulence, the quantification of turbulence, and the dynamic responses of the structures are considered. A probabilistic approach is taken to study the effects of earthquakes on structures and to the forces exerted by ocean waves on marine structures. Theoretical analyses by means of vector spaces and stochastic modeling are reviewed, as are Markovian formulations of Gaussian processes and the definition of stochastic differential equations. Finally, random vibrations with a variable number of links and linear oscillators undergoing the square of Gaussian processes are investigated.

Online kinematic regulation by visual feedback for grasp versus transport during reach-to-pinch

PubMed Central

Nataraj, Raviraj; Pasluosta, Cristian; Li, Zong-Ming

2014-01-01

Purpose This study investigated novel kinematic performance parameters to understand regulation by visual feedback (VF) of the reaching hand on the grasp and transport components during the reach-to-pinch maneuver. Conventional metrics often signify discrete movement features to postulate sensory-based control effects (e.g., time for maximum velocity to signify feedback delay). The presented metrics of this study were devised to characterize relative vision-based control of the sub-movements across the entire maneuver. Methods Movement performance was assessed according to reduced variability and increased efficiency of kinematic trajectories. Variability was calculated as the standard deviation about the observed mean trajectory for a given subject and VF condition across kinematic derivatives for sub-movements of inter-pad grasp (distance between thumb and index finger-pads; relative orientation of finger-pads) and transport (distance traversed by wrist). A Markov analysis then examined the probabilistic effect of VF on which movement component exhibited higher variability over phases of the complete maneuver. Jerk-based metrics of smoothness (minimal jerk) and energy (integrated jerk-squared) were applied to indicate total movement efficiency with VF. Results/Discussion The reductions in grasp variability metrics with VF were significantly greater (p<0.05) compared to transport for velocity, acceleration, and jerk, suggesting separate control pathways for each component. The Markov analysis indicated that VF preferentially regulates grasp over transport when continuous control is modeled probabilistically during the movement. Efficiency measures demonstrated VF to be more integral for early motor planning of grasp than transport in producing greater increases in smoothness and trajectory adjustments (i.e., jerk-energy) early compared to late in the movement cycle. Conclusions These findings demonstrate the greater regulation by VF on kinematic performance of grasp compared to transport and how particular features of this relativistic control occur continually over the maneuver. Utilizing the advanced performance metrics presented in this study facilitated characterization of VF effects continuously across the entire movement in corroborating the notion of separate control pathways for each component. PMID:24968371

Temporal prediction restores the evaluative processing of delayed action feedback: an electrophysiological study.

PubMed

Kimura, Kenta; Kimura, Motohiro

2016-09-28

The evaluative processing of the valence of action feedback is reflected by an event-related brain potential component called feedback-related negativity (FRN) or reward positivity (RewP). Recent studies have shown that FRN/RewP is markedly reduced when the action-feedback interval is long (e.g. 6000 ms), indicating that an increase in the action-feedback interval can undermine the evaluative processing of the valence of action feedback. The aim of the present study was to investigate whether or not such undermined evaluative processing of delayed action feedback could be restored by improving the accuracy of the prediction in terms of the timing of action feedback. With a typical gambling task in which the participant chose one of two cards and received an action feedback indicating monetary gain or loss, the present study showed that FRN/RewP was significantly elicited even when the action-feedback interval was 6000 ms, when an auditory stimulus sequence was additionally presented during the action-feedback interval as a temporal cue. This result suggests that the undermined evaluative processing of delayed action feedback can be restored by increasing the accuracy of the prediction on the timing of the action feedback.

Learning to Obtain Reward, but Not Avoid Punishment, Is Affected by Presence of PTSD Symptoms in Male Veterans: Empirical Data and Computational Model

PubMed Central

Myers, Catherine E.; Moustafa, Ahmed A.; Sheynin, Jony; VanMeenen, Kirsten M.; Gilbertson, Mark W.; Orr, Scott P.; Beck, Kevin D.; Pang, Kevin C. H.; Servatius, Richard J.

2013-01-01

Post-traumatic stress disorder (PTSD) symptoms include behavioral avoidance which is acquired and tends to increase with time. This avoidance may represent a general learning bias; indeed, individuals with PTSD are often faster than controls on acquiring conditioned responses based on physiologically-aversive feedback. However, it is not clear whether this learning bias extends to cognitive feedback, or to learning from both reward and punishment. Here, male veterans with self-reported current, severe PTSD symptoms (PTSS group) or with few or no PTSD symptoms (control group) completed a probabilistic classification task that included both reward-based and punishment-based trials, where feedback could take the form of reward, punishment, or an ambiguous “no-feedback” outcome that could signal either successful avoidance of punishment or failure to obtain reward. The PTSS group outperformed the control group in total points obtained; the PTSS group specifically performed better than the control group on reward-based trials, with no difference on punishment-based trials. To better understand possible mechanisms underlying observed performance, we used a reinforcement learning model of the task, and applied maximum likelihood estimation techniques to derive estimated parameters describing individual participants’ behavior. Estimations of the reinforcement value of the no-feedback outcome were significantly greater in the control group than the PTSS group, suggesting that the control group was more likely to value this outcome as positively reinforcing (i.e., signaling successful avoidance of punishment). This is consistent with the control group’s generally poorer performance on reward trials, where reward feedback was to be obtained in preference to the no-feedback outcome. Differences in the interpretation of ambiguous feedback may contribute to the facilitated reinforcement learning often observed in PTSD patients, and may in turn provide new insight into how pathological behaviors are acquired and maintained in PTSD. PMID:24015254

Group Feedback for Continuous Learning

ERIC Educational Resources Information Center

London, Manuel; Sessa, Valerie I.

2006-01-01

This article explores relationships between feedback, group learning, and performance. It considers how feedback to individuals and the group as a whole supports continuous group learning. Feedback source, purpose, clarity, and valence may affect perceptions, processing, and outcomes of feedback. How feedback is processed and used may be…

An Envelope Based Feedback Control System for Earthquake Early Warning: Reality Check Algorithm

NASA Astrophysics Data System (ADS)

Heaton, T. H.; Karakus, G.; Beck, J. L.

2016-12-01

Earthquake early warning systems are, in general, designed to be open loop control systems in such a way that the output, i.e., the warning messages, only depend on the input, i.e., recorded ground motions, up to the moment when the message is issued in real-time. We propose an algorithm, which is called Reality Check Algorithm (RCA), which would assess the accuracy of issued warning messages, and then feed the outcome of the assessment back into the system. Then, the system would modify its messages if necessary. That is, we are proposing to convert earthquake early warning systems into feedback control systems by integrating them with RCA. RCA works by continuously monitoring and comparing the observed ground motions' envelopes to the predicted envelopes of Virtual Seismologist (Cua 2005). Accuracy of magnitude and location (both spatial and temporal) estimations of the system are assessed separately by probabilistic classification models, which are trained by a Sparse Bayesian Learning technique called Automatic Relevance Determination prior.

Design-based Sample and Probability Law-Assumed Sample: Their Role in Scientific Investigation.

ERIC Educational Resources Information Center

Ojeda, Mario Miguel; Sahai, Hardeo

2002-01-01

Discusses some key statistical concepts in probabilistic and non-probabilistic sampling to provide an overview for understanding the inference process. Suggests a statistical model constituting the basis of statistical inference and provides a brief review of the finite population descriptive inference and a quota sampling inferential theory.…

On the Measurement and Properties of Ambiguity in Probabilistic Expectations

ERIC Educational Resources Information Center

Pickett, Justin T.; Loughran, Thomas A.; Bushway, Shawn

2015-01-01

Survey respondents' probabilistic expectations are now widely used in many fields to study risk perceptions, decision-making processes, and behavior. Researchers have developed several methods to account for the fact that the probability of an event may be more ambiguous for some respondents than others, but few prior studies have empirically…

Physician performance feedback in a Canadian academic center.

PubMed

Garvin, Dennis; Worthington, James; McGuire, Shaun; Burgetz, Stephanie; Forster, Alan J; Patey, Andrea; Gerin-Lajoie, Caroline; Turnbull, Jeffrey; Roth, Virginia

2017-10-02

Purpose This paper aims at the implementation and early evaluation of a comprehensive, formative annual physician performance feedback process in a large academic health-care organization. Design/methodology/approach A mixed methods approach was used to introduce a formative feedback process to provide physicians with comprehensive feedback on performance and to support professional development. This initiative responded to organization-wide engagement surveys through which physicians identified effective performance feedback as a priority. In 2013, physicians primarily affiliated with the organization participated in a performance feedback process, and physician satisfaction and participant perceptions were explored through participant survey responses and physician leader focus groups. Training was required for physician leaders prior to conducting performance feedback discussions. Findings This process was completed by 98 per cent of eligible physicians, and 30 per cent completed an evaluation survey. While physicians endorsed the concept of a formative feedback process, process improvement opportunities were identified. Qualitative analysis revealed the following process improvement themes: simplify the tool, ensure leaders follow process, eliminate redundancies in data collection (through academic or licensing requirements) and provide objective quality metrics. Following physician leader training on performance feedback, 98 per cent of leaders who completed an evaluation questionnaire agreed or strongly agreed that the performance feedback process was useful and that training objectives were met. Originality/value This paper introduces a physician performance feedback model, leadership training approach and first-year implementation outcomes. The results of this study will be useful to health administrators and physician leaders interested in implementing physician performance feedback or improving physician engagement.

Probabilistic performance assessment of complex energy process systems - The case of a self-sustained sanitation system.

PubMed

Kolios, Athanasios; Jiang, Ying; Somorin, Tosin; Sowale, Ayodeji; Anastasopoulou, Aikaterini; Anthony, Edward J; Fidalgo, Beatriz; Parker, Alison; McAdam, Ewan; Williams, Leon; Collins, Matt; Tyrrel, Sean

2018-05-01

A probabilistic modelling approach was developed and applied to investigate the energy and environmental performance of an innovative sanitation system, the "Nano-membrane Toilet" (NMT). The system treats human excreta via an advanced energy and water recovery island with the aim of addressing current and future sanitation demands. Due to the complex design and inherent characteristics of the system's input material, there are a number of stochastic variables which may significantly affect the system's performance. The non-intrusive probabilistic approach adopted in this study combines a finite number of deterministic thermodynamic process simulations with an artificial neural network (ANN) approximation model and Monte Carlo simulations (MCS) to assess the effect of system uncertainties on the predicted performance of the NMT system. The joint probability distributions of the process performance indicators suggest a Stirling Engine (SE) power output in the range of 61.5-73 W with a high confidence interval (CI) of 95%. In addition, there is high probability (with 95% CI) that the NMT system can achieve positive net power output between 15.8 and 35 W. A sensitivity study reveals the system power performance is mostly affected by SE heater temperature. Investigation into the environmental performance of the NMT design, including water recovery and CO 2 /NO x emissions, suggests significant environmental benefits compared to conventional systems. Results of the probabilistic analysis can better inform future improvements on the system design and operational strategy and this probabilistic assessment framework can also be applied to similar complex engineering systems.

Modeling Array Stations in SIG-VISA

NASA Astrophysics Data System (ADS)

Ding, N.; Moore, D.; Russell, S.

2013-12-01

We add support for array stations to SIG-VISA, a system for nuclear monitoring using probabilistic inference on seismic signals. Array stations comprise a large portion of the IMS network; they can provide increased sensitivity and more accurate directional information compared to single-component stations. Our existing model assumed that signals were independent at each station, which is false when lots of stations are close together, as in an array. The new model removes that assumption by jointly modeling signals across array elements. This is done by extending our existing Gaussian process (GP) regression models, also known as kriging, from a 3-dimensional single-component space of events to a 6-dimensional space of station-event pairs. For each array and each event attribute (including coda decay, coda height, amplitude transfer and travel time), we model the joint distribution across array elements using a Gaussian process that learns the correlation lengthscale across the array, thereby incorporating information of array stations into the probabilistic inference framework. To evaluate the effectiveness of our model, we perform ';probabilistic beamforming' on new events using our GP model, i.e., we compute the event azimuth having highest posterior probability under the model, conditioned on the signals at array elements. We compare the results from our probabilistic inference model to the beamforming currently performed by IMS station processing.

Development of optimization-based probabilistic earthquake scenarios for the city of Tehran

NASA Astrophysics Data System (ADS)

Zolfaghari, M. R.; Peyghaleh, E.

2016-01-01

This paper presents the methodology and practical example for the application of optimization process to select earthquake scenarios which best represent probabilistic earthquake hazard in a given region. The method is based on simulation of a large dataset of potential earthquakes, representing the long-term seismotectonic characteristics in a given region. The simulation process uses Monte-Carlo simulation and regional seismogenic source parameters to generate a synthetic earthquake catalogue consisting of a large number of earthquakes, each characterized with magnitude, location, focal depth and fault characteristics. Such catalogue provides full distributions of events in time, space and size; however, demands large computation power when is used for risk assessment, particularly when other sources of uncertainties are involved in the process. To reduce the number of selected earthquake scenarios, a mixed-integer linear program formulation is developed in this study. This approach results in reduced set of optimization-based probabilistic earthquake scenario, while maintaining shape of hazard curves and full probabilistic picture by minimizing the error between hazard curves driven by full and reduced sets of synthetic earthquake scenarios. To test the model, the regional seismotectonic and seismogenic characteristics of northern Iran are used to simulate a set of 10,000-year worth of events consisting of some 84,000 earthquakes. The optimization model is then performed multiple times with various input data, taking into account probabilistic seismic hazard for Tehran city as the main constrains. The sensitivity of the selected scenarios to the user-specified site/return period error-weight is also assessed. The methodology could enhance run time process for full probabilistic earthquake studies like seismic hazard and risk assessment. The reduced set is the representative of the contributions of all possible earthquakes; however, it requires far less computation power. The authors have used this approach for risk assessment towards identification of effectiveness-profitability of risk mitigation measures, using optimization model for resource allocation. Based on the error-computation trade-off, 62-earthquake scenarios are chosen to be used for this purpose.

Speech processing using maximum likelihood continuity mapping

DOEpatents

Hogden, John E.

2000-01-01

Speech processing is obtained that, given a probabilistic mapping between static speech sounds and pseudo-articulator positions, allows sequences of speech sounds to be mapped to smooth sequences of pseudo-articulator positions. In addition, a method for learning a probabilistic mapping between static speech sounds and pseudo-articulator position is described. The method for learning the mapping between static speech sounds and pseudo-articulator position uses a set of training data composed only of speech sounds. The said speech processing can be applied to various speech analysis tasks, including speech recognition, speaker recognition, speech coding, speech synthesis, and voice mimicry.

Speech processing using maximum likelihood continuity mapping

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

Hogden, J.E.

Speech processing is obtained that, given a probabilistic mapping between static speech sounds and pseudo-articulator positions, allows sequences of speech sounds to be mapped to smooth sequences of pseudo-articulator positions. In addition, a method for learning a probabilistic mapping between static speech sounds and pseudo-articulator position is described. The method for learning the mapping between static speech sounds and pseudo-articulator position uses a set of training data composed only of speech sounds. The said speech processing can be applied to various speech analysis tasks, including speech recognition, speaker recognition, speech coding, speech synthesis, and voice mimicry.

Combining Bayesian Networks and Agent Based Modeling to develop a decision-support model in Vietnam

NASA Astrophysics Data System (ADS)

Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit

2016-04-01

Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.

Feedback Providing Improvement Strategies and Reflection on Feedback Use: Effects on Students' Writing Motivation, Process, and Performance

ERIC Educational Resources Information Center

Duijnhouwer, Hendrien; Prins, Frans J.; Stokking, Karel M.

2012-01-01

This study investigated the effects of feedback providing improvement strategies and a reflection assignment on students' writing motivation, process, and performance. Students in the experimental feedback condition (n = 41) received feedback including improvement strategies, whereas students in the control feedback condition (n = 41) received…

Ensemble reconstruction constraints on the global carbon cycle sensitivity to climate.

PubMed

Frank, David C; Esper, Jan; Raible, Christoph C; Büntgen, Ulf; Trouet, Valerie; Stocker, Benjamin; Joos, Fortunat

2010-01-28

The processes controlling the carbon flux and carbon storage of the atmosphere, ocean and terrestrial biosphere are temperature sensitive and are likely to provide a positive feedback leading to amplified anthropogenic warming. Owing to this feedback, at timescales ranging from interannual to the 20-100-kyr cycles of Earth's orbital variations, warming of the climate system causes a net release of CO(2) into the atmosphere; this in turn amplifies warming. But the magnitude of the climate sensitivity of the global carbon cycle (termed gamma), and thus of its positive feedback strength, is under debate, giving rise to large uncertainties in global warming projections. Here we quantify the median gamma as 7.7 p.p.m.v. CO(2) per degrees C warming, with a likely range of 1.7-21.4 p.p.m.v. CO(2) per degrees C. Sensitivity experiments exclude significant influence of pre-industrial land-use change on these estimates. Our results, based on the coupling of a probabilistic approach with an ensemble of proxy-based temperature reconstructions and pre-industrial CO(2) data from three ice cores, provide robust constraints for gamma on the policy-relevant multi-decadal to centennial timescales. By using an ensemble of >200,000 members, quantification of gamma is not only improved, but also likelihoods can be assigned, thereby providing a benchmark for future model simulations. Although uncertainties do not at present allow exclusion of gamma calculated from any of ten coupled carbon-climate models, we find that gamma is about twice as likely to fall in the lowermost than in the uppermost quartile of their range. Our results are incompatibly lower (P < 0.05) than recent pre-industrial empirical estimates of approximately 40 p.p.m.v. CO(2) per degrees C (refs 6, 7), and correspondingly suggest approximately 80% less potential amplification of ongoing global warming.

Hot and cold cognition in unmedicated depressed subjects with bipolar disorder.

PubMed

Roiser, Jonathan P; Cannon, Dara M; Gandhi, Shilpa K; Taylor Tavares, Joana; Erickson, Kristine; Wood, Suzanne; Klaver, Jacqueline M; Clark, Luke; Zarate, Carlos A; Sahakian, Barbara J; Drevets, Wayne C

2009-03-01

Neuropsychological studies in subjects with bipolar disorder (BD) have reported deficits on a variety of cognitive measures. However, because the majority of subjects were medicated at the time of testing in previous studies, it is currently unclear whether the pattern of deficits reported is related to BD itself or to psychotropic medication. We addressed this issue by examining cognitive performance in a group of unmedicated, currently depressed subjects with BD. Forty-nine unmedicated subjects who met DSM-IV criteria for BD, depressed phase, and 55 control subjects participated in this study. Most patients were diagnosed with bipolar II disorder. Performance on emotion-dependent, or 'hot', and emotion-independent, or 'cold', cognitive tasks was assessed using tests from the Cambridge Neuropsychological Test Automated Battery. The groups were well matched with respect to general intelligence and demographic variables. Deficits in the unmedicated depressed BD group were apparent on tests tapping 'hot' cognitive processing, for example the Cambridge Gamble task and the Probabilistic Reversal Learning task. However, other than a deficit on the Spatial Span test in the depressed BD subjects, the groups performed equivalently on most measures of 'cold' cognitive processing, for example visual memory, attention, and working memory. These data suggest that deficits on tests involving reward processing, short-term spatial memory storage, and sensitivity to negative feedback in depressed BD subjects represent an effect of the illness itself and not mood-stabilizing medication.

Emergence of spontaneous anticipatory hand movements in a probabilistic environment

PubMed Central

Bruhn, Pernille

2013-01-01

In this article, we present a novel experimental approach to the study of anticipation in probabilistic cuing. We implemented a modified spatial cuing task in which participants made an anticipatory hand movement toward one of two probabilistic targets while the (x, y)-computer mouse coordinates of their hand movements were sampled. This approach allowed us to tap into anticipatory processes as they occurred, rather than just measuring their behavioral outcome through reaction time to the target. In different conditions, we varied the participants’ degree of certainty of the upcoming target position with probabilistic pre-cues. We found that participants initiated spontaneous anticipatory hand movements in all conditions, even when they had no information on the position of the upcoming target. However, participants’ hand position immediately before the target was affected by the degree of certainty concerning the target’s position. This modulation of anticipatory hand movements emerged rapidly in most participants as they encountered a constant probabilistic relation between a cue and an upcoming target position over the course of the experiment. Finally, we found individual differences in the way anticipatory behavior was modulated with an uncertain/neutral cue. Implications of these findings for probabilistic spatial cuing are discussed. PMID:23833694

Ten tips for receiving feedback effectively in clinical practice

PubMed Central

Algiraigri, Ali H.

2014-01-01

Background Despite being recognized as a fundamental part of the educational process and emphasized for several decades in medical education, the influence of the feedback process is still suboptimal. This may not be surprising, because the focus is primarily centered on only one half of the process – the teachers. The learners are the targets of the feedback process and improvement needs to be shifted. Learners need to be empowered with the skills needed to receive and utilize feedback and compensate for less than ideal feedback delivery due to the busy clinical environment. Methods Based on the available feedback literature and clinical experience regarding feedback, the author developed 10 tips to empower learners with the necessary skills to seek, receive, and handle feedback effectively, regardless of how it is delivered. Although, most of the tips are directed at the individual clinical trainee, this model can be utilized by clinical educators involved in learner development and serve as a framework for educational workshops or curriculum. Results Ten practical tips are identified that specifically address the learner's role in the feedback process. These tips not only help the learner to ask, receive, and handle the feedback, but will also ease the process for the teachers. Collectively, these tips help to overcome most, if not all, of the barriers to feedback and bridge the gaps in busy clinical practices. Conclusions Feedback is a crucial element in the educational process and it is shown that we are still behind in the optimal use of it; thus, learners need to be taught how to better receive and utilize feedback. The focus in medical education needs to balance the two sides of the feedback process. It is time now to invest on the learner's development of skills that can be utilized in a busy day-to-day clinical practice. PMID:25079664

Gender differences in reward and punishment for monetary and social feedback in children: An ERP study

PubMed Central

Zou, Yuchen; Song, Yan; Xiao, Xue; Huang, Wanyi; Li, Yanfang

2017-01-01

Gender differences in feedback processing have been observed among adolescents and adults through event-related potentials. However, information on whether and how this feedback processing is affected by feedback valence, feedback type, and individual sensitivity in reward/punishment among children remains minimal. In this study, we used a guessing game task coupled with electroencephalography to investigate gender differences in feedback processing, in which feedback to reward and punishment was presented in the context of monetary and social conditions. Results showed that boys were less likely to switch their response after punishment, had generally less feedback-related negativity (FRN) amplitude, and longer FRN latency in monetary and punishment conditions than girls. Moreover, FRN for monetary punishment, which is related to individual difference in reward sensitivity, was observed only in girls. The study provides gender-specific evidence for the neural processing of feedback, which may offer educational guidance for appropriate feedback for girls and boys. PMID:28346515

Gender differences in reward and punishment for monetary and social feedback in children: An ERP study.

PubMed

Ding, Ying; Wang, Encong; Zou, Yuchen; Song, Yan; Xiao, Xue; Huang, Wanyi; Li, Yanfang

2017-01-01

Gender differences in feedback processing have been observed among adolescents and adults through event-related potentials. However, information on whether and how this feedback processing is affected by feedback valence, feedback type, and individual sensitivity in reward/punishment among children remains minimal. In this study, we used a guessing game task coupled with electroencephalography to investigate gender differences in feedback processing, in which feedback to reward and punishment was presented in the context of monetary and social conditions. Results showed that boys were less likely to switch their response after punishment, had generally less feedback-related negativity (FRN) amplitude, and longer FRN latency in monetary and punishment conditions than girls. Moreover, FRN for monetary punishment, which is related to individual difference in reward sensitivity, was observed only in girls. The study provides gender-specific evidence for the neural processing of feedback, which may offer educational guidance for appropriate feedback for girls and boys.

Feedback: A Systems Approach to Evaluation and Course Design. Working Papers No. 21.

ERIC Educational Resources Information Center

Holmes, John

Two types of feedback are examined, and their use in controlling the processes of instructional development and improvement are discussed. Closed-loop feedback, the most direct, uses immediate feedback about a process or product to make immediate adjustments in it. Open-loop feedback, in which input cannot be changed immediately, uses feedback to…

Hybrid Modeling of Cell Signaling and Transcriptional Reprogramming and Its Application in C. elegans Development.

PubMed

Fertig, Elana J; Danilova, Ludmila V; Favorov, Alexander V; Ochs, Michael F

2011-01-01

Modeling of signal driven transcriptional reprogramming is critical for understanding of organism development, human disease, and cell biology. Many current modeling techniques discount key features of the biological sub-systems when modeling multiscale, organism-level processes. We present a mechanistic hybrid model, GESSA, which integrates a novel pooled probabilistic Boolean network model of cell signaling and a stochastic simulation of transcription and translation responding to a diffusion model of extracellular signals. We apply the model to simulate the well studied cell fate decision process of the vulval precursor cells (VPCs) in C. elegans, using experimentally derived rate constants wherever possible and shared parameters to avoid overfitting. We demonstrate that GESSA recovers (1) the effects of varying scaffold protein concentration on signal strength, (2) amplification of signals in expression, (3) the relative external ligand concentration in a known geometry, and (4) feedback in biochemical networks. We demonstrate that setting model parameters based on wild-type and LIN-12 loss-of-function mutants in C. elegans leads to correct prediction of a wide variety of mutants including partial penetrance of phenotypes. Moreover, the model is relatively insensitive to parameters, retaining the wild-type phenotype for a wide range of cell signaling rate parameters.

A review for identification of initiating events in event tree development process on nuclear power plants

NASA Astrophysics Data System (ADS)

Riyadi, Eko H.

2014-09-01

Initiating event is defined as any event either internal or external to the nuclear power plants (NPPs) that perturbs the steady state operation of the plant, if operating, thereby initiating an abnormal event such as transient or loss of coolant accident (LOCA) within the NPPs. These initiating events trigger sequences of events that challenge plant control and safety systems whose failure could potentially lead to core damage or large early release. Selection for initiating events consists of two steps i.e. first step, definition of possible events, such as by evaluating a comprehensive engineering, and by constructing a top level logic model. Then the second step, grouping of identified initiating event's by the safety function to be performed or combinations of systems responses. Therefore, the purpose of this paper is to discuss initiating events identification in event tree development process and to reviews other probabilistic safety assessments (PSA). The identification of initiating events also involves the past operating experience, review of other PSA, failure mode and effect analysis (FMEA), feedback from system modeling, and master logic diagram (special type of fault tree). By using the method of study for the condition of the traditional US PSA categorization in detail, could be obtained the important initiating events that are categorized into LOCA, transients and external events.

Probabilistic Simulation of Multi-Scale Composite Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2012-01-01

A methodology is developed to computationally assess the non-deterministic composite response at all composite scales (from micro to structural) due to the uncertainties in the constituent (fiber and matrix) properties, in the fabrication process and in structural variables (primitive variables). The methodology is computationally efficient for simulating the probability distributions of composite behavior, such as material properties, laminate and structural responses. Bi-products of the methodology are probabilistic sensitivities of the composite primitive variables. The methodology has been implemented into the computer codes PICAN (Probabilistic Integrated Composite ANalyzer) and IPACS (Integrated Probabilistic Assessment of Composite Structures). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in composite typical laminates and comparing the results with the Monte Carlo simulation method. Available experimental data of composite laminate behavior at all scales fall within the scatters predicted by PICAN. Multi-scaling is extended to simulate probabilistic thermo-mechanical fatigue and to simulate the probabilistic design of a composite redome in order to illustrate its versatility. Results show that probabilistic fatigue can be simulated for different temperature amplitudes and for different cyclic stress magnitudes. Results also show that laminate configurations can be selected to increase the redome reliability by several orders of magnitude without increasing the laminate thickness--a unique feature of structural composites. The old reference denotes that nothing fundamental has been done since that time.

Model depicting aspects of audit and feedback that impact physicians' acceptance of clinical performance feedback.

PubMed

Payne, Velma L; Hysong, Sylvia J

2016-07-13

Audit and feedback (A&F) is a strategy that has been used in various disciplines for performance and quality improvement. There is limited research regarding medical professionals' acceptance of clinical-performance feedback and whether feedback impacts clinical practice. The objectives of our research were to (1) investigate aspects of A&F that impact physicians' acceptance of performance feedback; (2) determine actions physicians take when receiving feedback; and (3) determine if feedback impacts physicians' patient-management behavior. In this qualitative study, we employed grounded theory methods to perform a secondary analysis of semi-structured interviews with 12 VA primary care physicians. We analyzed a subset of interview questions from the primary study, which aimed to determine how providers of high, low and moderately performing VA medical centers use performance feedback to maintain and improve quality of care, and determine perceived utility of performance feedback. Based on the themes emergent from our analysis and their observed relationships, we developed a model depicting aspects of the A&F process that impact feedback acceptance and physicians' patient-management behavior. The model is comprised of three core components - Reaction, Action and Impact - and depicts elements associated with feedback recipients' reaction to feedback, action taken when feedback is received, and physicians modifying their patient-management behavior. Feedback characteristics, the environment, external locus-of-control components, core values, emotion and the assessment process induce or deter reaction, action and impact. Feedback characteristics (content and timeliness), and the procedural justice of the assessment process (unjust penalties) impact feedback acceptance. External locus-of-control elements (financial incentives, competition), the environment (patient volume, time constraints) and emotion impact patient-management behavior. Receiving feedback generated intense emotion within physicians. The underlying source of the emotion was the assessment process, not the feedback. The emotional response impacted acceptance, impelled action or inaction, and impacted patient-management behavior. Emotion intensity was associated with type of action taken (defensive, proactive, retroactive). Feedback acceptance and impact have as much to do with the performance assessment process as it does the feedback. In order to enhance feedback acceptance and the impact of feedback, developers of clinical performance systems and feedback interventions should consider multiple design elements.

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.

Disruption of the Right Temporoparietal Junction Impairs Probabilistic Belief Updating.

PubMed

Mengotti, Paola; Dombert, Pascasie L; Fink, Gereon R; Vossel, Simone

2017-05-31

Generating and updating probabilistic models of the environment is a fundamental modus operandi of the human brain. Although crucial for various cognitive functions, the neural mechanisms of these inference processes remain to be elucidated. Here, we show the causal involvement of the right temporoparietal junction (rTPJ) in updating probabilistic beliefs and we provide new insights into the chronometry of the process by combining online transcranial magnetic stimulation (TMS) with computational modeling of behavioral responses. Female and male participants performed a modified location-cueing paradigm, where false information about the percentage of cue validity (%CV) was provided in half of the experimental blocks to prompt updating of prior expectations. Online double-pulse TMS over rTPJ 300 ms (but not 50 ms) after target appearance selectively decreased participants' updating of false prior beliefs concerning %CV, reflected in a decreased learning rate of a Rescorla-Wagner model. Online TMS over rTPJ also impacted on participants' explicit beliefs, causing them to overestimate %CV. These results confirm the involvement of rTPJ in updating of probabilistic beliefs, thereby advancing our understanding of this area's function during cognitive processing. SIGNIFICANCE STATEMENT Contemporary views propose that the brain maintains probabilistic models of the world to minimize surprise about sensory inputs. Here, we provide evidence that the right temporoparietal junction (rTPJ) is causally involved in this process. Because neuroimaging has suggested that rTPJ is implicated in divergent cognitive domains, the demonstration of an involvement in updating internal models provides a novel unifying explanation for these findings. We used computational modeling to characterize how participants change their beliefs after new observations. By interfering with rTPJ activity through online transcranial magnetic stimulation, we showed that participants were less able to update prior beliefs with TMS delivered at 300 ms after target onset. Copyright © 2017 the authors 0270-6474/17/375419-10$15.00/0.

Modeling socio-cultural processes in network-centric environments

NASA Astrophysics Data System (ADS)

Santos, Eunice E.; Santos, Eugene, Jr.; Korah, John; George, Riya; Gu, Qi; Kim, Keumjoo; Li, Deqing; Russell, Jacob; Subramanian, Suresh

2012-05-01

The major focus in the field of modeling & simulation for network centric environments has been on the physical layer while making simplifications for the human-in-the-loop. However, the human element has a big impact on the capabilities of network centric systems. Taking into account the socio-behavioral aspects of processes such as team building, group decision-making, etc. are critical to realistically modeling and analyzing system performance. Modeling socio-cultural processes is a challenge because of the complexity of the networks, dynamism in the physical and social layers, feedback loops and uncertainty in the modeling data. We propose an overarching framework to represent, model and analyze various socio-cultural processes within network centric environments. The key innovation in our methodology is to simultaneously model the dynamism in both the physical and social layers while providing functional mappings between them. We represent socio-cultural information such as friendships, professional relationships and temperament by leveraging the Culturally Infused Social Network (CISN) framework. The notion of intent is used to relate the underlying socio-cultural factors to observed behavior. We will model intent using Bayesian Knowledge Bases (BKBs), a probabilistic reasoning network, which can represent incomplete and uncertain socio-cultural information. We will leverage previous work on a network performance modeling framework called Network-Centric Operations Performance and Prediction (N-COPP) to incorporate dynamism in various aspects of the physical layer such as node mobility, transmission parameters, etc. We validate our framework by simulating a suitable scenario, incorporating relevant factors and providing analyses of the results.

The composite load spectra project

NASA Technical Reports Server (NTRS)

Newell, J. F.; Ho, H.; Kurth, R. E.

1990-01-01

Probabilistic methods and generic load models capable of simulating the load spectra that are induced in space propulsion system components are being developed. Four engine component types (the transfer ducts, the turbine blades, the liquid oxygen posts and the turbopump oxidizer discharge duct) were selected as representative hardware examples. The composite load spectra that simulate the probabilistic loads for these components are typically used as the input loads for a probabilistic structural analysis. The knowledge-based system approach used for the composite load spectra project provides an ideal environment for incremental development. The intelligent database paradigm employed in developing the expert system provides a smooth coupling between the numerical processing and the symbolic (information) processing. Large volumes of engine load information and engineering data are stored in database format and managed by a database management system. Numerical procedures for probabilistic load simulation and database management functions are controlled by rule modules. Rules were hard-wired as decision trees into rule modules to perform process control tasks. There are modules to retrieve load information and models. There are modules to select loads and models to carry out quick load calculations or make an input file for full duty-cycle time dependent load simulation. The composite load spectra load expert system implemented today is capable of performing intelligent rocket engine load spectra simulation. Further development of the expert system will provide tutorial capability for users to learn from it.

MrLavaLoba: A new probabilistic model for the simulation of lava flows as a settling process

NASA Astrophysics Data System (ADS)

de'Michieli Vitturi, Mattia; Tarquini, Simone

2018-01-01

A new code to simulate lava flow spread, MrLavaLoba, is presented. In the code, erupted lava is itemized in parcels having an elliptical shape and prescribed volume. New parcels bud from existing ones according to a probabilistic law influenced by the local steepest slope direction and by tunable input settings. MrLavaLoba must be accounted among the probabilistic codes for the simulation of lava flows, because it is not intended to mimic the actual process of flowing or to provide directly the progression with time of the flow field, but rather to guess the most probable inundated area and final thickness of the lava deposit. The code's flexibility allows it to produce variable lava flow spread and emplacement according to different dynamics (e.g. pahoehoe or channelized-'a'ā). For a given scenario, it is shown that model outputs converge, in probabilistic terms, towards a single solution. The code is applied to real cases in Hawaii and Mt. Etna, and the obtained maps are shown. The model is written in Python and the source code is available at http://demichie.github.io/MrLavaLoba/.

Use of Probabilistic Risk Assessment in Shuttle Decision Making Process

NASA Technical Reports Server (NTRS)

Boyer, Roger L.; Hamlin, Teri, L.

2011-01-01

This slide presentation reviews the use of Probabilistic Risk Assessment (PRA) to assist in the decision making for the shuttle design and operation. Probabilistic Risk Assessment (PRA) is a comprehensive, structured, and disciplined approach to identifying and analyzing risk in complex systems and/or processes that seeks answers to three basic questions: (i.e., what can go wrong? what is the likelihood of these occurring? and what are the consequences that could result if these occur?) The purpose of the Shuttle PRA (SPRA) is to provide a useful risk management tool for the Space Shuttle Program (SSP) to identify strengths and possible weaknesses in the Shuttle design and operation. SPRA was initially developed to support upgrade decisions, but has evolved into a tool that supports Flight Readiness Reviews (FRR) and near real-time flight decisions. Examples of the use of PRA for the shuttle are reviewed.

An analytical probabilistic model of the quality efficiency of a sewer tank

NASA Astrophysics Data System (ADS)

Balistrocchi, Matteo; Grossi, Giovanna; Bacchi, Baldassare

2009-12-01

The assessment of the efficiency of a storm water storage facility devoted to the sewer overflow control in urban areas strictly depends on the ability to model the main features of the rainfall-runoff routing process and the related wet weather pollution delivery. In this paper the possibility of applying the analytical probabilistic approach for developing a tank design method, whose potentials are similar to the continuous simulations, is proved. In the model derivation the quality issues of such devices were implemented. The formulation is based on a Weibull probabilistic model of the main characteristics of the rainfall process and on a power law describing the relationship between the dimensionless storm water cumulative runoff volume and the dimensionless cumulative pollutograph. Following this approach, efficiency indexes were established. The proposed model was verified by comparing its results to those obtained by continuous simulations; satisfactory agreement is shown for the proposed efficiency indexes.

The Eruption Forecasting Information System (EFIS) database project

NASA Astrophysics Data System (ADS)

Ogburn, Sarah; Harpel, Chris; Pesicek, Jeremy; Wellik, Jay; Pallister, John; Wright, Heather

2016-04-01

The Eruption Forecasting Information System (EFIS) project is a new initiative of the U.S. Geological Survey-USAID Volcano Disaster Assistance Program (VDAP) with the goal of enhancing VDAP's ability to forecast the outcome of volcanic unrest. The EFIS project seeks to: (1) Move away from relying on the collective memory to probability estimation using databases (2) Create databases useful for pattern recognition and for answering common VDAP questions; e.g. how commonly does unrest lead to eruption? how commonly do phreatic eruptions portend magmatic eruptions and what is the range of antecedence times? (3) Create generic probabilistic event trees using global data for different volcano 'types' (4) Create background, volcano-specific, probabilistic event trees for frequently active or particularly hazardous volcanoes in advance of a crisis (5) Quantify and communicate uncertainty in probabilities A major component of the project is the global EFIS relational database, which contains multiple modules designed to aid in the construction of probabilistic event trees and to answer common questions that arise during volcanic crises. The primary module contains chronologies of volcanic unrest, including the timing of phreatic eruptions, column heights, eruptive products, etc. and will be initially populated using chronicles of eruptive activity from Alaskan volcanic eruptions in the GeoDIVA database (Cameron et al. 2013). This database module allows us to query across other global databases such as the WOVOdat database of monitoring data and the Smithsonian Institution's Global Volcanism Program (GVP) database of eruptive histories and volcano information. The EFIS database is in the early stages of development and population; thus, this contribution also serves as a request for feedback from the community.

Improving Instruction Using Statistical Process Control.

ERIC Educational Resources Information Center

Higgins, Ronald C.; Messer, George H.

1990-01-01

Two applications of statistical process control to the process of education are described. Discussed are the use of prompt feedback to teachers and prompt feedback to students. A sample feedback form is provided. (CW)

Effects of Written Peer-Feedback Content and Sender's Competence on Perceptions, Performance, and Mindful Cognitive Processing

ERIC Educational Resources Information Center

Berndt, Markus; Strijbos, Jan-Willem; Fischer, Frank

2018-01-01

Peer-feedback efficiency might be influenced by the oftentimes voiced concern of students that they perceive their peers' competence to provide feedback as inadequate. Feedback literature also identifies mindful processing of (peer)feedback and (peer)feedback content as important for its efficiency, but lacks systematic investigation. In a 2 × 2…

Probabilistic Teleportation of an Arbitrary Three-Level Two-Particle State and Classical Communication Cost

NASA Astrophysics Data System (ADS)

Dai, Hong-Yi; Kuang, Le-Man; Li, Cheng-Zu

2005-07-01

We propose a scheme to probabilistically teleport an unknown arbitrary three-level two-particle state by using two partial entangled two-particle states of three-level as the quantum channel. The classical communication cost required in the ideal probabilistic teleportation process is also calculated. This scheme can be directly generalized to teleport an unknown and arbitrary three-level K-particle state by using K partial entangled two-particle states of three-level as the quantum channel. The project supported by National Fundamental Research Program of China under Grant No. 2001CB309310, National Natural Science Foundation of China under Grant Nos. 10404039 and 10325523

Common problems in the elicitation and analysis of expert opinion affecting probabilistic safety assessments

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

Meyer, M.A.; Booker, J.M.

1990-01-01

Expert opinion is frequently used in probabilistic safety assessment (PSA), particularly in estimating low probability events. In this paper, we discuss some of the common problems encountered in eliciting and analyzing expert opinion data and offer solutions or recommendations. The problems are: that experts are not naturally Bayesian. People fail to update their existing information to account for new information as it becomes available, as would be predicted by the Bayesian philosophy; that experts cannot be fully calibrated. To calibrate experts, the feedback from the known quantities must be immediate, frequent, and specific to the task; that experts are limitedmore » in the number of things that they can mentally juggle at a time to 7 {plus minus} 2; that data gatherers and analysts can introduce bias by unintentionally causing an altering of the expert's thinking or answers; that the level of detail the data, or granularity, can affect the analyses; and the conditioning effect poses difficulties in gathering and analyzing of the expert data. The data that the expert gives can be conditioned on a variety of factors that can affect the analysis and the interpretation of the results. 31 refs.« less

In Situ Distribution Guided Analysis and Visualization of Transonic Jet Engine Simulations.

PubMed

Dutta, Soumya; Chen, Chun-Ming; Heinlein, Gregory; Shen, Han-Wei; Chen, Jen-Ping

2017-01-01

Study of flow instability in turbine engine compressors is crucial to understand the inception and evolution of engine stall. Aerodynamics experts have been working on detecting the early signs of stall in order to devise novel stall suppression technologies. A state-of-the-art Navier-Stokes based, time-accurate computational fluid dynamics simulator, TURBO, has been developed in NASA to enhance the understanding of flow phenomena undergoing rotating stall. Despite the proven high modeling accuracy of TURBO, the excessive simulation data prohibits post-hoc analysis in both storage and I/O time. To address these issues and allow the expert to perform scalable stall analysis, we have designed an in situ distribution guided stall analysis technique. Our method summarizes statistics of important properties of the simulation data in situ using a probabilistic data modeling scheme. This data summarization enables statistical anomaly detection for flow instability in post analysis, which reveals the spatiotemporal trends of rotating stall for the expert to conceive new hypotheses. Furthermore, the verification of the hypotheses and exploratory visualization using the summarized data are realized using probabilistic visualization techniques such as uncertain isocontouring. Positive feedback from the domain scientist has indicated the efficacy of our system in exploratory stall analysis.

Effects of Person- and Process-Focused Feedback on Prosocial Behavior in Middle Childhood

PubMed Central

Dunsmore, Julie C.

2014-01-01

Effects of person- and process-focused feedback, parental lay theories, and prosocial self-concept on children’s prosocial behavior were investigated with 143 9- and 10-year-old children who participated in a single session. Parents reported entity (person-focused) and incremental (process-focused) beliefs related to prosocial behavior. Children completed measures of prosocial self-concept, then participated in a virtual online chat with child actors who asked for help with service projects. After completing the chat, children could assist with the service projects. In the first cohort, children were randomly assigned to receive person-focused, process-focused, or control feedback about sympathy. In the second cohort, with newly-recruited families, children received no feedback. When given process-focused feedback, children spent less time spent helping and worked on fewer service projects. When given no feedback, children spent less time helping when parents held incremental (process-focused) beliefs. Children with higher prosocial self-concept who received no feedback worked on more service projects. PMID:25684859

A coherent optical feedback system for optical information processing

NASA Technical Reports Server (NTRS)

Jablonowski, D. P.; Lee, S. H.

1975-01-01

A unique optical feedback system for coherent optical data processing is described. With the introduction of feedback, the well-known transfer function for feedback systems is obtained in two dimensions. Operational details of the optical feedback system are given. Experimental results of system applications in image restoration, contrast control and analog computation are presented.

Neural correlates of anticipation and processing of performance feedback in social anxiety.

PubMed

Heitmann, Carina Y; Peterburs, Jutta; Mothes-Lasch, Martin; Hallfarth, Marlit C; Böhme, Stephanie; Miltner, Wolfgang H R; Straube, Thomas

2014-12-01

Fear of negative evaluation, such as negative social performance feedback, is the core symptom of social anxiety. The present study investigated the neural correlates of anticipation and perception of social performance feedback in social anxiety. High (HSA) and low (LSA) socially anxious individuals were asked to give a speech on a personally relevant topic and received standardized but appropriate expert performance feedback in a succeeding experimental session in which neural activity was measured during anticipation and presentation of negative and positive performance feedback concerning the speech performance, or a neutral feedback-unrelated control condition. HSA compared to LSA subjects reported greater anxiety during anticipation of negative feedback. Functional magnetic resonance imaging results showed deactivation of medial prefrontal brain areas during anticipation of negative feedback relative to the control and the positive condition, and medial prefrontal and insular hyperactivation during presentation of negative as well as positive feedback in HSA compared to LSA subjects. The results indicate distinct processes underlying feedback processing during anticipation and presentation of feedback in HSA as compared to LSA individuals. In line with the role of the medial prefrontal cortex in self-referential information processing and the insula in interoception, social anxiety seems to be associated with lower self-monitoring during feedback anticipation, and an increased self-focus and interoception during feedback presentation, regardless of feedback valence. © 2014 Wiley Periodicals, Inc.

When compliments don't hit but critiques do: an fMRI study into self-esteem and self-knowledge in processing social feedback.

PubMed

van Schie, C C; Chiu, C D; Rombouts, S A R B; Heiser, W J; Elzinga, B M

2018-02-27

The way we view ourselves may play an important role in our responses to interpersonal interactions. In this study, we investigate how feedback valence, consistency of feedback with self-knowledge and global self-esteem influence affective and neural responses to social feedback. Participants (N = 46) with a high range of self-esteem levels performed the social feedback task in an MRI scanner. Negative, intermediate and positive feedback was provided, supposedly by another person based on a personal interview. Participants rated their mood and applicability of feedback to the self. Analyses on trial basis on neural and affective responses are used to incorporate applicability of individual feedback words. Lower self-esteem related to low mood especially after receiving non-applicable negative feedback. Higher self-esteem related to increased PCC and precuneus activation (i.e., self-referential processing) for applicable negative feedback. Lower self-esteem related to decreased mPFC, insula, ACC and PCC activation (i.e, self-referential processing) during positive feedback and decreased TPJ activation (i.e., other referential processing) for applicable positive feedback. Self-esteem and consistency of feedback with self-knowledge appear to guide our affective and neural responses to social feedback. This may be highly relevant for the interpersonal problems that individuals face with low self-esteem and negative self-views.

Improved water allocation utilizing probabilistic climate forecasts: Short-term water contracts in a risk management framework

NASA Astrophysics Data System (ADS)

Sankarasubramanian, A.; Lall, Upmanu; Souza Filho, Francisco Assis; Sharma, Ashish

2009-11-01

Probabilistic, seasonal to interannual streamflow forecasts are becoming increasingly available as the ability to model climate teleconnections is improving. However, water managers and practitioners have been slow to adopt such products, citing concerns with forecast skill. Essentially, a management risk is perceived in "gambling" with operations using a probabilistic forecast, while a system failure upon following existing operating policies is "protected" by the official rules or guidebook. In the presence of a prescribed system of prior allocation of releases under different storage or water availability conditions, the manager has little incentive to change. Innovation in allocation and operation is hence key to improved risk management using such forecasts. A participatory water allocation process that can effectively use probabilistic forecasts as part of an adaptive management strategy is introduced here. Users can express their demand for water through statements that cover the quantity needed at a particular reliability, the temporal distribution of the "allocation," the associated willingness to pay, and compensation in the event of contract nonperformance. The water manager then assesses feasible allocations using the probabilistic forecast that try to meet these criteria across all users. An iterative process between users and water manager could be used to formalize a set of short-term contracts that represent the resulting prioritized water allocation strategy over the operating period for which the forecast was issued. These contracts can be used to allocate water each year/season beyond long-term contracts that may have precedence. Thus, integrated supply and demand management can be achieved. In this paper, a single period multiuser optimization model that can support such an allocation process is presented. The application of this conceptual model is explored using data for the Jaguaribe Metropolitan Hydro System in Ceara, Brazil. The performance relative to the current allocation process is assessed in the context of whether such a model could support the proposed short-term contract based participatory process. A synthetic forecasting example is also used to explore the relative roles of forecast skill and reservoir storage in this framework.

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

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

Chowdhary, Kenny; Najm, Habib N.

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

DOE PAGES

Chowdhary, Kenny; Najm, Habib N.

2016-04-13

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Hazard function analysis for flood planning under nonstationarity

NASA Astrophysics Data System (ADS)

Read, Laura K.; Vogel, Richard M.

2016-05-01

The field of hazard function analysis (HFA) involves a probabilistic assessment of the "time to failure" or "return period," T, of an event of interest. HFA is used in epidemiology, manufacturing, medicine, actuarial statistics, reliability engineering, economics, and elsewhere. For a stationary process, the probability distribution function (pdf) of the return period always follows an exponential distribution, the same is not true for nonstationary processes. When the process of interest, X, exhibits nonstationary behavior, HFA can provide a complementary approach to risk analysis with analytical tools particularly useful for hydrological applications. After a general introduction to HFA, we describe a new mathematical linkage between the magnitude of the flood event, X, and its return period, T, for nonstationary processes. We derive the probabilistic properties of T for a nonstationary one-parameter exponential model of X, and then use both Monte-Carlo simulation and HFA to generalize the behavior of T when X arises from a nonstationary two-parameter lognormal distribution. For this case, our findings suggest that a two-parameter Weibull distribution provides a reasonable approximation for the pdf of T. We document how HFA can provide an alternative approach to characterize the probabilistic properties of both nonstationary flood series and the resulting pdf of T.

Probabilistic simulation of multi-scale composite behavior

NASA Technical Reports Server (NTRS)

Liaw, D. G.; Shiao, M. C.; Singhal, S. N.; Chamis, Christos C.

1993-01-01

A methodology is developed to computationally assess the probabilistic composite material properties at all composite scale levels due to the uncertainties in the constituent (fiber and matrix) properties and in the fabrication process variables. The methodology is computationally efficient for simulating the probability distributions of material properties. The sensitivity of the probabilistic composite material property to each random variable is determined. This information can be used to reduce undesirable uncertainties in material properties at the macro scale of the composite by reducing the uncertainties in the most influential random variables at the micro scale. This methodology was implemented into the computer code PICAN (Probabilistic Integrated Composite ANalyzer). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in the material properties of a typical laminate and comparing the results with the Monte Carlo simulation method. The experimental data of composite material properties at all scales fall within the scatters predicted by PICAN.

A probabilistic approach to radiative energy loss calculations for optically thick atmospheres - Hydrogen lines and continua

NASA Technical Reports Server (NTRS)

Canfield, R. C.; Ricchiazzi, P. J.

1980-01-01

An approximate probabilistic radiative transfer equation and the statistical equilibrium equations are simultaneously solved for a model hydrogen atom consisting of three bound levels and ionization continuum. The transfer equation for L-alpha, L-beta, H-alpha, and the Lyman continuum is explicitly solved assuming complete redistribution. The accuracy of this approach is tested by comparing source functions and radiative loss rates to values obtained with a method that solves the exact transfer equation. Two recent model solar-flare chromospheres are used for this test. It is shown that for the test atmospheres the probabilistic method gives values of the radiative loss rate that are characteristically good to a factor of 2. The advantage of this probabilistic approach is that it retains a description of the dominant physical processes of radiative transfer in the complete redistribution case, yet it achieves a major reduction in computational requirements.

Parallel computing for probabilistic fatigue analysis

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Lua, Yuan J.; Smith, Mark D.

1993-01-01

This paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.

Integrated Risk-Informed Decision-Making for an ALMR PRISM

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

Muhlheim, Michael David; Belles, Randy; Denning, Richard S.

Decision-making is the process of identifying decision alternatives, assessing those alternatives based on predefined metrics, selecting an alternative (i.e., making a decision), and then implementing that alternative. The generation of decisions requires a structured, coherent process, or a decision-making process. The overall objective for this work is that the generalized framework is adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace ormore » supplement human decision makers with reconfigurable decision-making modules that can perform a given set of tasks rationally, consistently, and reliably. Risk-informed decision-making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The probabilistic portion of the decision-making engine of the supervisory control system is based on the control actions associated with an ALMR PRISM. Newly incorporated into the probabilistic models are the prognostic/diagnostic models developed by Pacific Northwest National Laboratory. These allow decisions to incorporate the health of components into the decision–making process. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic portion of the decision-making engine uses thermal-hydraulic modeling and components for an advanced liquid-metal reactor Power Reactor Inherently Safe Module. The deterministic multi-attribute decision-making framework uses various sensor data (e.g., reactor outlet temperature, steam generator drum level) and calculates its position within the challenge state, its trajectory, and its margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. The metrics that are evaluated are based on reactor trip set points. The integration of the deterministic calculations using multi-physics analyses and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermalhydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies, and developing a user interface to mimic display panels at a modern nuclear power plant.« less

"Only True Friends Could Be Cruelly Honest": Cognitive Scaffolding and Social-Affective Support in Teacher Feedback Literacy

ERIC Educational Resources Information Center

Xu, Yueting; Carless, David

2017-01-01

Feedback is an important but challenging aspect of higher education pedagogy. In addition to providing quality feedback, teachers are expected to develop students' skills and awareness for effective feedback processes. This case study addresses both processes and products of a Chinese university English teacher's feedback enabling practice by…

Architecture for Integrated Medical Model Dynamic Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

Jaworske, D. A.; Myers, J. G.; Goodenow, D.; Young, M.; Arellano, J. D.

2016-01-01

Probabilistic Risk Assessment (PRA) is a modeling tool used to predict potential outcomes of a complex system based on a statistical understanding of many initiating events. Utilizing a Monte Carlo method, thousands of instances of the model are considered and outcomes are collected. PRA is considered static, utilizing probabilities alone to calculate outcomes. Dynamic Probabilistic Risk Assessment (dPRA) is an advanced concept where modeling predicts the outcomes of a complex system based not only on the probabilities of many initiating events, but also on a progression of dependencies brought about by progressing down a time line. Events are placed in a single time line, adding each event to a queue, as managed by a planner. Progression down the time line is guided by rules, as managed by a scheduler. The recently developed Integrated Medical Model (IMM) summarizes astronaut health as governed by the probabilities of medical events and mitigation strategies. Managing the software architecture process provides a systematic means of creating, documenting, and communicating a software design early in the development process. The software architecture process begins with establishing requirements and the design is then derived from the requirements.

Software for Probabilistic Risk Reduction

NASA Technical Reports Server (NTRS)

Hensley, Scott; Michel, Thierry; Madsen, Soren; Chapin, Elaine; Rodriguez, Ernesto

2004-01-01

A computer program implements a methodology, denoted probabilistic risk reduction, that is intended to aid in planning the development of complex software and/or hardware systems. This methodology integrates two complementary prior methodologies: (1) that of probabilistic risk assessment and (2) a risk-based planning methodology, implemented in a prior computer program known as Defect Detection and Prevention (DDP), in which multiple requirements and the beneficial effects of risk-mitigation actions are taken into account. The present methodology and the software are able to accommodate both process knowledge (notably of the efficacy of development practices) and product knowledge (notably of the logical structure of a system, the development of which one seeks to plan). Estimates of the costs and benefits of a planned development can be derived. Functional and non-functional aspects of software can be taken into account, and trades made among them. It becomes possible to optimize the planning process in the sense that it becomes possible to select the best suite of process steps and design choices to maximize the expectation of success while remaining within budget.

Crossing the river: Developing a strategy to support understanding of uncertainty within probabilistic climate projections.

NASA Astrophysics Data System (ADS)

Walton, P.; Lamb, R.

2010-09-01

The UK Climate Impacts Programme (UKCIP) was established by government in 1997 to support the UK's engagement with becoming better adapted to a changing climate. As the lead organisation in the UK on climate change adaptation, UKCIP oversaw the development of the UK Climate Projections (UKCP09) which were launched in June 2009 providing, for the first time, probabilistic climate projections for the UK. As with previous generations of UKCIP climate scenarios, they were freely accessible and intended for a whole spectrum of users, from technical experts to a lay audience. . Prior to the launch of UKCP09 it was acknowledged that users would need support in understanding key concepts, such as the uncertainty inherent in the projections, to be able to use them appropriately. The user support strategy was therefore developed. It is founded on robust pedagogical principles and draws on the latest thinking on public understanding of science (PUS) that places the user at the centre of the communication process. The adopted approach first identifies profiles of the key users of the climate projections and the ways in which they would use and access the data. Based on these profiles it is possible to identify a range of mechanisms that allow the user to engage with understanding the projections in different ways and situations including lectures, workshops and online learning. Within this blended strategy an exercise was developed specifically to support users' understanding of the concept of uncertainty within the probabilistic climate projections. The ‘Crossing the River' exercise encourages the participants to actively consider the nature of information they are using, and how it could be applied in a specific decision. Reflection and discussion are key elements in supporting the users' understanding of the concept and allowing them to apply the principles in the exercise to their own context. Their reflection is facilitated through a range of mechanisms that provide social and personal spaces and is guided by the communicator. The exercise has been used successfully with a broad range of users (from government officers to environmental managers) in groups ranging from small community events to large corporate conferences. Feedback has shown that the majority of people who completed the exercise had a better understanding of the concept of uncertainty within the probabilistic climate projections as a result. We are now working to create an online version that can be freely accessed by users along with other resources that develop understanding of other key concepts associated with UKCP09 and the broader climate change adaptation agenda. This paper evaluates the development and application of the user support strategy and provides a practical illustration of how it can be used within a face-to-face group setting and also as an online resource.

When compliments do not hit but critiques do: an fMRI study into self-esteem and self-knowledge in processing social feedback

PubMed Central

van Schie, Charlotte C; Chiu, Chui-De; Rombouts, Serge A R B; Heiser, Willem J; Elzinga, Bernet M

2018-01-01

Abstract The way we view ourselves may play an important role in our responses to interpersonal interactions. In this study, we investigate how feedback valence, consistency of feedback with self-knowledge and global self-esteem influence affective and neural responses to social feedback. Participants (N = 46) with a high range of self-esteem levels performed the social feedback task in an MRI scanner. Negative, intermediate and positive feedback was provided, supposedly by another person based on a personal interview. Participants rated their mood and applicability of feedback to the self. Analyses on trial basis on neural and affective responses are used to incorporate applicability of individual feedback words. Lower self-esteem related to low mood especially after receiving non-applicable negative feedback. Higher self-esteem related to increased posterior cingulate cortex and precuneus activation (i.e. self-referential processing) for applicable negative feedback. Lower self-esteem related to decreased medial prefrontal cortex, insula, anterior cingulate cortex and posterior cingulate cortex activation (i.e. self-referential processing) during positive feedback and decreased temporoparietal junction activation (i.e. other referential processing) for applicable positive feedback. Self-esteem and consistency of feedback with self-knowledge appear to guide our affective and neural responses to social feedback. This may be highly relevant for the interpersonal problems that individuals face with low self-esteem and negative self-views. PMID:29490088

Social feedback processing from early to late adolescence: influence of sex, age, and attachment style

PubMed Central

Vrtička, Pascal; Sander, David; Anderson, Brittany; Badoud, Deborah; Eliez, Stephan; Debbané, Martin

2014-01-01

Objective The establishment of an accurate understanding of one's social context is a central developmental task during adolescence. A critical component of such development is to learn how to integrate the objective evaluation of one's behavior with the social response to the latter—here referred to as social feedback processing. Case report We measured brain activity by means of fMRI in 33 healthy adolescents (12–19 years old, 14 females). Participants played a difficult perceptual game with integrated verbal and visual feedback. Verbal feedback provided the participants with objective performance evaluation (won vs. lost). Visual feedback consisted of either smiling or angry faces, representing positive or negative social evaluations. Together, the combination of verbal and visual feedback gave rise to congruent versus incongruent social feedback combinations. In addition to assessing sex differences, we further tested for the effects of age and attachment style on social feedback processing. Results revealed that brain activity during social feedback processing was significantly modulated by sex, age, and attachment style in prefrontal cortical areas, ventral anterior cingulate cortex, anterior insula, caudate, and amygdala/hippocampus. We found indication for heightened activity during incongruent social feedback processing in females, older participants, and individuals with an anxious attachment style. Conversely, we observed stronger activity during processing of congruent social feedback in males and participants with an avoidant attachment style. Conclusion Our findings not only extend knowledge on the typical development of socio-emotional brain function during adolescence, but also provide first clues on how attachment insecurities, and particularly attachment avoidance, could interfere with the latter mechanisms. PMID:25328847

Common and distinct modulation of electrophysiological indices of feedback processing by autistic and psychopathic traits.

PubMed

Carter Leno, Virginia; Naples, Adam; Cox, Anthony; Rutherford, Helena; McPartland, James C

2016-01-01

Both autism spectrum disorder (ASD) and psychopathy are primarily characterized by social dysfunction; overlapping phenotypic features may reflect altered function in common brain mechanisms. The current study examined the degree to which neural response to social and nonsocial feedback is modulated by autistic versus psychopathic traits in a sample of typically developing adults (N = 31, 11 males, 18-52 years). Event-related potentials were recorded whilst participants completed a behavioral task and received feedback on task performance. Both autistic and psychopathic traits were associated with alterations in the neural correlates of feedback processing. Sensitivity to specific forms of feedback (social, nonsocial, positively valenced, negatively valenced) differed between the two traits. Autistic traits were associated with decreased sensitivity to social feedback. In contrast, the antisocial domain of psychopathic traits was associated with an overall decrease in sensitivity to feedback, and the interpersonal manipulation domain was associated with preserved processing of positively valenced feedback. Results suggest distinct alterations within specific mechanisms of feedback processing may underlie similar difficulties in social behavior.

Peer feedback for examiner quality assurance on MRCGP International South Asia: a mixed methods study.

PubMed

Perera, D P; Andrades, Marie; Wass, Val

2017-12-08

The International Membership Examination (MRCGP[INT]) of the Royal College of General Practitioners UK is a unique collaboration between four South Asian countries with diverse cultures, epidemiology, clinical facilities and resources. In this setting good quality assurance is imperative to achieve acceptable standards of inter rater reliability. This study aims to explore the process of peer feedback for examiner quality assurance with regard to factors affecting the implementation and acceptance of the method. A sequential mixed methods approach was used based on focus group discussions with examiners (n = 12) and clinical examination convenors who acted as peer reviewers (n = 4). A questionnaire based on emerging themes and literature review was then completed by 20 examiners at the subsequent OSCE exam. Qualitative data were analysed using an iterative reflexive process. Quantitative data were integrated by interpretive analysis looking for convergence, complementarity or dissonance. The qualitative data helped understand the issues and informed the process of developing the questionnaire. The quantitative data allowed for further refining of issues, wider sampling of examiners and giving voice to different perspectives. Examiners stated specifically that peer feedback gave an opportunity for discussion, standardisation of judgments and improved discriminatory abilities. Interpersonal dynamics, hierarchy and perception of validity of feedback were major factors influencing acceptance of feedback. Examiners desired increased transparency, accountability and the opportunity for equal partnership within the process. The process was stressful for examiners and reviewers; however acceptance increased with increasing exposure to receiving feedback. The process could be refined to improve acceptability through scrupulous attention to training and selection of those giving feedback to improve the perceived validity of feedback and improved reviewer feedback skills to enable better interpersonal dynamics and a more equitable feedback process. It is important to highlight the role of quality assurance and peer feedback as a tool for continuous improvement and maintenance of standards to examiners during training. Examiner quality assurance using peer feedback was generally a successful and accepted process. The findings highlight areas for improvement and guide the path towards a model of feedback that is responsive to examiner views and cultural sensibilities.

Feedback and the Reconstruction of Meaning.

ERIC Educational Resources Information Center

Langer, Philip; And Others

This investigation of the impact of feedback upon scrambled discourse was intended to show the effects of idiosyncratic processing and to provide a more sensitive indicator of feedback usefulness. Learner schemata, text organization, and feedback strategies interact in processing discourse, although past research has favored limited models…

Method and apparatus for detecting concealed weapons

DOEpatents

Kotter, Dale K.; Fluck, Frederick D.

2006-03-14

Apparatus for classifying a ferromagnetic object within a sensing area may include a magnetic field sensor that produces magnetic field data. A signal processing system operatively associated with the magnetic field sensor includes a neural network. The neural network compares the magnetic field data with magnetic field data produced by known ferromagnetic objects to make a probabilistic determination as to the classification of the ferromagnetic object within the sensing area. A user interface operatively associated with the signal processing system produces a user-discernable output indicative of the probabilistic determination of the classification of the ferromagnetic object within a sensing area.

Frontostriatal development and probabilistic reinforcement learning during adolescence.

PubMed

DePasque, Samantha; Galván, Adriana

2017-09-01

Adolescence has traditionally been viewed as a period of vulnerability to increased risk-taking and adverse outcomes, which have been linked to neurobiological maturation of the frontostriatal reward system. However, growing research on the role of developmental changes in the adolescent frontostriatal system in facilitating learning will provide a more nuanced view of adolescence. In this review, we discuss the implications of existing research on this topic for learning during adolescence, and suggest that the very neural changes that render adolescents vulnerable to social pressure and risky decision making may also stand to play a role in scaffolding the ability to learn from rewards and from performance-related feedback. Copyright © 2017 Elsevier Inc. All rights reserved.

Improving ontology matching with propagation strategy and user feedback

NASA Astrophysics Data System (ADS)

Li, Chunhua; Cui, Zhiming; Zhao, Pengpeng; Wu, Jian; Xin, Jie; He, Tianxu

2015-07-01

Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. The existing approach requires a threshold to produce matching candidates and use a small set of constraints acting as filter to select the final alignments. We introduce novel match propagation strategy to model the influences between potential entity mappings across ontologies, which can help to identify the correct correspondences and produce missed correspondences. The estimation of appropriate threshold is a difficult task. We propose an interactive method for threshold selection through which we obtain an additional measurable improvement. Running experiments on a public dataset has demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.

Stochastic Characterization of Communication Network Latency for Wide Area Grid Control Applications.

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

Ameme, Dan Selorm Kwami; Guttromson, Ross

This report characterizes communications network latency under various network topologies and qualities of service (QoS). The characterizations are probabilistic in nature, allowing deeper analysis of stability for Internet Protocol (IP) based feedback control systems used in grid applications. The work involves the use of Raspberry Pi computers as a proxy for a controlled resource, and an ns-3 network simulator on a Linux server to create an experimental platform (testbed) that can be used to model wide-area grid control network communications in smart grid. Modbus protocol is used for information transport, and Routing Information Protocol is used for dynamic route selectionmore » within the simulated network.« less

Metrics for Labeled Markov Systems

NASA Technical Reports Server (NTRS)

Desharnais, Josee; Jagadeesan, Radha; Gupta, Vineet; Panangaden, Prakash

1999-01-01

Partial Labeled Markov Chains are simultaneously generalizations of process algebra and of traditional Markov chains. They provide a foundation for interacting discrete probabilistic systems, the interaction being synchronization on labels as in process algebra. Existing notions of process equivalence are too sensitive to the exact probabilities of various transitions. This paper addresses contextual reasoning principles for reasoning about more robust notions of "approximate" equivalence between concurrent interacting probabilistic systems. The present results indicate that:We develop a family of metrics between partial labeled Markov chains to formalize the notion of distance between processes. We show that processes at distance zero are bisimilar. We describe a decision procedure to compute the distance between two processes. We show that reasoning about approximate equivalence can be done compositionally by showing that process combinators do not increase distance. We introduce an asymptotic metric to capture asymptotic properties of Markov chains; and show that parallel composition does not increase asymptotic distance.

System Level Uncertainty Assessment for Collaborative RLV Design

NASA Technical Reports Server (NTRS)

Charania, A. C.; Bradford, John E.; Olds, John R.; Graham, Matthew

2002-01-01

A collaborative design process utilizing Probabilistic Data Assessment (PDA) is showcased. Given the limitation of financial resources by both the government and industry, strategic decision makers need more than just traditional point designs, they need to be aware of the likelihood of these future designs to meet their objectives. This uncertainty, an ever-present character in the design process, can be embraced through a probabilistic design environment. A conceptual design process is presented that encapsulates the major engineering disciplines for a Third Generation Reusable Launch Vehicle (RLV). Toolsets consist of aerospace industry standard tools in disciplines such as trajectory, propulsion, mass properties, cost, operations, safety, and economics. Variations of the design process are presented that use different fidelities of tools. The disciplinary engineering models are used in a collaborative engineering framework utilizing Phoenix Integration's ModelCenter and AnalysisServer environment. These tools allow the designer to join disparate models and simulations together in a unified environment wherein each discipline can interact with any other discipline. The design process also uses probabilistic methods to generate the system level output metrics of interest for a RLV conceptual design. The specific system being examined is the Advanced Concept Rocket Engine 92 (ACRE-92) RLV. Previous experience and knowledge (in terms of input uncertainty distributions from experts and modeling and simulation codes) can be coupled with Monte Carlo processes to best predict the chances of program success.

Accuracy of Probabilistic Linkage Using the Enhanced Matching System for Public Health and Epidemiological Studies.

PubMed

Aldridge, Robert W; Shaji, Kunju; Hayward, Andrew C; Abubakar, Ibrahim

2015-01-01

The Enhanced Matching System (EMS) is a probabilistic record linkage program developed by the tuberculosis section at Public Health England to match data for individuals across two datasets. This paper outlines how EMS works and investigates its accuracy for linkage across public health datasets. EMS is a configurable Microsoft SQL Server database program. To examine the accuracy of EMS, two public health databases were matched using National Health Service (NHS) numbers as a gold standard unique identifier. Probabilistic linkage was then performed on the same two datasets without inclusion of NHS number. Sensitivity analyses were carried out to examine the effect of varying matching process parameters. Exact matching using NHS number between two datasets (containing 5931 and 1759 records) identified 1071 matched pairs. EMS probabilistic linkage identified 1068 record pairs. The sensitivity of probabilistic linkage was calculated as 99.5% (95%CI: 98.9, 99.8), specificity 100.0% (95%CI: 99.9, 100.0), positive predictive value 99.8% (95%CI: 99.3, 100.0), and negative predictive value 99.9% (95%CI: 99.8, 100.0). Probabilistic matching was most accurate when including address variables and using the automatically generated threshold for determining links with manual review. With the establishment of national electronic datasets across health and social care, EMS enables previously unanswerable research questions to be tackled with confidence in the accuracy of the linkage process. In scenarios where a small sample is being matched into a very large database (such as national records of hospital attendance) then, compared to results presented in this analysis, the positive predictive value or sensitivity may drop according to the prevalence of matches between databases. Despite this possible limitation, probabilistic linkage has great potential to be used where exact matching using a common identifier is not possible, including in low-income settings, and for vulnerable groups such as homeless populations, where the absence of unique identifiers and lower data quality has historically hindered the ability to identify individuals across datasets.

Social incentives improve deliberative but not procedural learning in older adults.

PubMed

Gorlick, Marissa A; Maddox, W Todd

2015-01-01

Age-related deficits are seen across tasks where learning depends on asocial feedback processing, however plasticity has been observed in some of the same tasks in social contexts suggesting a novel way to attenuate deficits. Socioemotional selectivity theory suggests this plasticity is due to a deliberative motivational shift toward achieving well-being with age (positivity effect) that reverses when executive processes are limited (negativity effect). The present study examined the interaction of feedback valence (positive, negative) and social salience (emotional face feedback - happy; angry, asocial point feedback - gain; loss) on learning in a deliberative task that challenges executive processes and a procedural task that does not. We predict that angry face feedback will improve learning in a deliberative task when executive function is challenged. We tested two competing hypotheses regarding the interactive effects of deliberative emotional biases on automatic feedback processing: (1) If deliberative emotion regulation and automatic feedback are interactive we expect happy face feedback to improve learning and angry face feedback to impair learning in older adults because cognitive control is available. (2) If deliberative emotion regulation and automatic feedback are not interactive we predict that emotional face feedback will not improve procedural learning regardless of valence. Results demonstrate that older adults show persistent deficits relative to younger adults during procedural category learning suggesting that deliberative emotional biases do not interact with automatic feedback processing. Interestingly, a subgroup of older adults identified as potentially using deliberative strategies tended to learn as well as younger adults with angry relative to happy feedback, matching the pattern observed in the deliberative task. Results suggest that deliberative emotional biases can improve deliberative learning, but have no effect on procedural learning.

All about the Money - External Performance Monitoring is Affected by Monetary, but Not by Socially Conveyed Feedback Cues in More Antisocial Individuals.

PubMed

Pfabigan, Daniela Melitta; Alexopoulos, Johanna; Bauer, Herbert; Lamm, Claus; Sailer, Uta

2011-01-01

This study investigated the relationship between feedback processing and antisocial personality traits measured by the PSSI questionnaire (Kuhl and Kazén, 1997) in a healthy undergraduate sample. While event-related potentials [feedback related negativity (FRN), P300] were recorded, participants encountered expected and unexpected feedback during a gambling task. As recent findings suggest learning problems and deficiencies during feedback processing in clinical populations of antisocial individuals, we performed two experiments with different healthy participants in which feedback about monetary gains or losses consisted either of social-emotional (facial emotion displays) or non-social cues (numerical stimuli). Since the FRN and P300 are both sensitive to different aspects of feedback processing we hypothesized that they might help to differentiate between individuals scoring high and low on an antisocial trait measure. In line with previous evidence FRN amplitudes were enhanced after negative and after unexpected feedback stimuli. Crucially, participants scoring high on antisocial traits displayed larger FRN amplitudes than those scoring low only in response to expected and unexpected negative numerical feedback, but not in response to social-emotional feedback - irrespective of expectancy. P300 amplitudes were not modulated by antisocial traits at all, but by subjective reward probabilities. The present findings indicate that individuals scoring high on antisociality attribute higher motivational salience to monetary compared to emotional-social feedback which is reflected in FRN amplitude enhancement. Contrary to recent findings, however, no processing deficiencies concerning social-emotional feedback stimuli were apparent in those individuals. This indicates that stimulus salience is an important aspect in learning and feedback processes in individuals with antisocial traits which has potential implications for therapeutic interventions in clinical populations.

Acute Stress Modulates Feedback Processing in Men and Women: Differential Effects on the Feedback-Related Negativity and Theta and Beta Power

PubMed Central

Banis, Stella; Geerligs, Linda; Lorist, Monicque M.

2014-01-01

Sex-specific prevalence rates in mental and physical disorders may be partly explained by sex differences in physiological stress responses. Neural networks that might be involved are those underlying feedback processing. Aim of the present EEG study was to investigate whether acute stress alters feedback processing, and whether stress effects differ between men and women. Male and female participants performed a gambling task, in a control and a stress condition. Stress was induced by exposing participants to a noise stressor. Brain activity was analyzed using both event-related potential and time-frequency analyses, measuring the feedback-related negativity (FRN) and feedback-related changes in theta and beta oscillatory power, respectively. While the FRN and feedback-related theta power were similarly affected by stress induction in both sexes, feedback-related beta power depended on the combination of stress induction condition and sex. FRN amplitude and theta power increases were smaller in the stress relative to the control condition in both sexes, demonstrating that acute noise stress impairs performance monitoring irrespective of sex. However, in the stress but not in the control condition, early lower beta-band power increases were larger for men than women, indicating that stress effects on feedback processing are partly sex-dependent. Our findings suggest that sex-specific effects on feedback processing may comprise a factor underlying sex-specific stress responses. PMID:24755943

Eye Movement Analysis of Information Processing under Different Testing Conditions.

ERIC Educational Resources Information Center

Dillon, Ronna F.

1985-01-01

Undergraduates were given complex figural analogies items, and eye movements were observed under three types of feedback: (1) elaborate feedback; (2) subjects verbalized their thinking and application of rules; and (3) no feedback. Both feedback conditions enhanced the rule-governed information processing during inductive reasoning. (Author/GDC)

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks.

PubMed

Dinov, Martin; Leech, Robert

2017-01-01

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses.

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks

PubMed Central

Dinov, Martin; Leech, Robert

2017-01-01

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses. PMID:29163110

Processing of Continuously Provided Punishment and Reward in Children with ADHD and the Modulating Effects of Stimulant Medication: An ERP Study

PubMed Central

Groen, Yvonne; Tucha, Oliver; Wijers, Albertus A.; Althaus, Monika

2013-01-01

Objectives Current models of ADHD suggest abnormal reward and punishment sensitivity, but the exact mechanisms are unclear. This study aims to investigate effects of continuous reward and punishment on the processing of performance feedback in children with ADHD and the modulating effects of stimulant medication. Methods 15 Methylphenidate (Mph)-treated and 15 Mph-free children of the ADHD-combined type and 17 control children performed a selective attention task with three feedback conditions: no-feedback, gain and loss. Event Related Potentials (ERPs) time-locked to feedback and errors were computed. Results All groups performed more accurately with gain and loss than without feedback. Feedback-related ERPs demonstrated no group differences in the feedback P2, but an enhanced late positive potential (LPP) to feedback stimuli (both gains and losses) for Mph-free children with ADHD compared to controls. Feedback-related ERPs in Mph-treated children with ADHD were similar to controls. Correlational analyses in the ADHD groups revealed that the severity of inattention problems correlated negatively with the feedback P2 amplitude and positively with the LPP to losses and omitted gains. Conclusions The early selective attention for rewarding and punishing feedback was relatively intact in children with ADHD, but the late feedback processing was deviant (increased feedback LPP). This may explain the often observed positive effects of continuous reinforcement on performance and behaviour in children with ADHD. However, these group findings cannot be generalised to all individuals with the ADHD, because the feedback-related ERPs were associated with the severity of the inattention problems. Children with ADHD-combined type with more inattention problems showed both deviant early attentional selection of feedback stimuli, and deviant late processing of non-reward and punishment. PMID:23555639

Processing of continuously provided punishment and reward in children with ADHD and the modulating effects of stimulant medication: an ERP study.

PubMed

Groen, Yvonne; Tucha, Oliver; Wijers, Albertus A; Althaus, Monika

2013-01-01

Current models of ADHD suggest abnormal reward and punishment sensitivity, but the exact mechanisms are unclear. This study aims to investigate effects of continuous reward and punishment on the processing of performance feedback in children with ADHD and the modulating effects of stimulant medication. 15 Methylphenidate (Mph)-treated and 15 Mph-free children of the ADHD-combined type and 17 control children performed a selective attention task with three feedback conditions: no-feedback, gain and loss. Event Related Potentials (ERPs) time-locked to feedback and errors were computed. All groups performed more accurately with gain and loss than without feedback. Feedback-related ERPs demonstrated no group differences in the feedback P2, but an enhanced late positive potential (LPP) to feedback stimuli (both gains and losses) for Mph-free children with ADHD compared to controls. Feedback-related ERPs in Mph-treated children with ADHD were similar to controls. Correlational analyses in the ADHD groups revealed that the severity of inattention problems correlated negatively with the feedback P2 amplitude and positively with the LPP to losses and omitted gains. The early selective attention for rewarding and punishing feedback was relatively intact in children with ADHD, but the late feedback processing was deviant (increased feedback LPP). This may explain the often observed positive effects of continuous reinforcement on performance and behaviour in children with ADHD. However, these group findings cannot be generalised to all individuals with the ADHD, because the feedback-related ERPs were associated with the severity of the inattention problems. Children with ADHD-combined type with more inattention problems showed both deviant early attentional selection of feedback stimuli, and deviant late processing of non-reward and punishment.

Automated segmentation of the prostate in 3D MR images using a probabilistic atlas and a spatially constrained deformable model.

PubMed

Martin, Sébastien; Troccaz, Jocelyne; Daanenc, Vincent

2010-04-01

The authors present a fully automatic algorithm for the segmentation of the prostate in three-dimensional magnetic resonance (MR) images. The approach requires the use of an anatomical atlas which is built by computing transformation fields mapping a set of manually segmented images to a common reference. These transformation fields are then applied to the manually segmented structures of the training set in order to get a probabilistic map on the atlas. The segmentation is then realized through a two stage procedure. In the first stage, the processed image is registered to the probabilistic atlas. Subsequently, a probabilistic segmentation is obtained by mapping the probabilistic map of the atlas to the patient's anatomy. In the second stage, a deformable surface evolves toward the prostate boundaries by merging information coming from the probabilistic segmentation, an image feature model and a statistical shape model. During the evolution of the surface, the probabilistic segmentation allows the introduction of a spatial constraint that prevents the deformable surface from leaking in an unlikely configuration. The proposed method is evaluated on 36 exams that were manually segmented by a single expert. A median Dice similarity coefficient of 0.86 and an average surface error of 2.41 mm are achieved. By merging prior knowledge, the presented method achieves a robust and completely automatic segmentation of the prostate in MR images. Results show that the use of a spatial constraint is useful to increase the robustness of the deformable model comparatively to a deformable surface that is only driven by an image appearance model.

Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity.

PubMed

Pecevski, Dejan; Maass, Wolfgang

2016-01-01

Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p (*) that generates the examples it receives. This holds even if p (*) contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference.

Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity123

PubMed Central

Pecevski, Dejan

2016-01-01

Abstract Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p* that generates the examples it receives. This holds even if p* contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference. PMID:27419214

Exploring cultural differences in feedback processes and perceived instructiveness during clerkships: replicating a Dutch study in Indonesia.

PubMed

Suhoyo, Yoyo; van Hell, Elisabeth A; Prihatiningsih, Titi S; Kuks, Jan B M; Cohen-Schotanus, Janke

2014-03-01

Cultural differences between countries may entail differences in feedback processes. By replicating a Dutch study in Indonesia, we analysed whether differences in processes influenced the perceived instructiveness of feedback. Over a two-week period, Indonesian students (n = 215) recorded feedback moments during clerkships, noting who provided the feedback, whether the feedback was based on observations, who initiated the feedback, and its perceived instructiveness. Data were compared with the earlier Dutch study and analysed with χ(2) tests, t-tests and multilevel techniques. Cultural differences were explored using Hofstede's Model, with Indonesia and the Netherlands differing on "power distance" and "individualism." Perceived instructiveness of feedback did not differ significantly between both countries. However, significant differences were found in feedback provider, observation and initiative. Indonesian students perceived feedback as more instructive if provided by specialists and initiated jointly by the supervisor and student (βresidents = -0.201, p < 0.001 and βjoint = 0.193, p = 0.001). Dutch students appreciated feedback more when it was based on observation. We obtained empirical evidence that one model of feedback does not necessarily translate to another culture. Further research is necessary to unravel other possible influences of culture in implementing feedback procedures in different countries.

Potentiated processing of negative feedback in depression is attenuated by anhedonia

PubMed Central

Mueller, E. M.; Pechtel, P.; Cohen, A.L.; Douglas, S.R.; Pizzagalli, D.A.

2014-01-01

Background Although cognitive theories of depression have postulated enhanced processing of negatively valenced information, previous EEG studies have shown both increased and reduced sensitivity for negative performance feedback in MDD. To reconcile these paradoxical findings, it has been speculated that sensitivity for negative feedback is potentiated in moderate MDD but reduced in highly anhedonic subjects. The goal of this study was to test this hypothesis by analyzing the feedback-related negativity (FRN), frontomedial theta power (FMT), and source-localized anterior midcingulate cortex (aMCC) activity after negative feedback. Methods Fourteen unmedicated participants with MDD and 15 control participants performed a reinforcement learning task while 128-channel EEG was recorded. FRN, FMT and LORETA source-localized aMCC activity after negative and positive feedback were compared between groups. Results The MDD group showed higher FRN amplitudes and aMCC activation to negative feedback than controls. Moreover, aMCC activation to negative feedback was inversely related to self-reported anhedonia. In contrast, self-reported anxiety correlated with feedback-evoked frontomedial theta (FMT) within the depression group. Conclusions The present findings suggest that, among depressed and anxious individuals, enhanced processing of negative feedback occurs relatively early in the information processing stream. These results extend prior work and indicate that although moderate depression is associated with elevated sensitivity for negative feedback, high levels of anhedonia may attenuate this effect. PMID:25620272

Evaluative-feedback stimuli selectively activate the self-related brain area: an fMRI study.

PubMed

Pan, Xiaohong; Hu, Yang; Li, Lei; Li, Jianqi

2009-11-06

Evaluative-feedback, occurring in our daily life, generally contains subjective appraisal of one's specific abilities and personality characteristics besides objective right-or-wrong information. Traditional psychological researches have proved it to be important in building up one's self-concept; however, the neural basis underlying its cognitive processing remains unclear. The present neuroimaging study revealed the mechanism of evaluative-feedback processing at the neural level. 19 healthy Chinese subjects participated in this experiment, and completed the time-estimation task to better their performance according to four types of feedback, namely positive evaluative- and performance-feedback as well as negative evaluative- and performance-feedback. Neuroimaging findings showed that evaluative- rather than performance-feedback can induce increased activities mainly distributed in the cortical midline structures (CMS), including medial prefrontal cortex (BA 8/9)/anterior cigulate cortex (ACC, BA 20), precuneus (BA 7/31) adjacent to posterior cingulate gyrus (PCC, BA 23) of both hemispheres, as well as right inferior lobule (BA 40). This phenomenon can provide evidence that evaluative-feedback may significantly elicit the self-related processing in our brain. In addition, our results also revealed that more brain areas, particularly some self-related neural substrates were activated by the positive evaluative-feedback, in comparative with the negative one. In sum, this study suggested that evaluative-feedback was closely correlated with the self-concept processing, which distinguished it from the performance-feedback.

A Software Tool for Quantitative Seismicity Analysis - ZMAP

NASA Astrophysics Data System (ADS)

Wiemer, S.; Gerstenberger, M.

2001-12-01

Earthquake catalogs are probably the most basic product of seismology, and remain arguably the most useful for tectonic studies. Modern seismograph networks can locate up to 100,000 earthquakes annually, providing a continuous and sometime overwhelming stream of data. ZMAP is a set of tools driven by a graphical user interface (GUI), designed to help seismologists analyze catalog data. ZMAP is primarily a research tool suited to the evaluation of catalog quality and to addressing specific hypotheses; however, it can also be useful in routine network operations. Examples of ZMAP features include catalog quality assessment (artifacts, completeness, explosion contamination), interactive data exploration, mapping transients in seismicity (rate changes, b-values, p-values), fractal dimension analysis and stress tensor inversions. Roughly 100 scientists worldwide have used the software at least occasionally. About 30 peer-reviewed publications have made use of ZMAP. ZMAP code is open source, written in the commercial software language Matlab by the Mathworks, a widely used software in the natural sciences. ZMAP was first published in 1994, and has continued to grow over the past 7 years. Recently, we released ZMAP v.6. The poster will introduce the features of ZMAP. We will specifically focus on ZMAP features related to time-dependent probabilistic hazard assessment. We are currently implementing a ZMAP based system that computes probabilistic hazard maps, which combine the stationary background hazard as well as aftershock and foreshock hazard into a comprehensive time dependent probabilistic hazard map. These maps will be displayed in near real time on the Internet. This poster is also intended as a forum for ZMAP users to provide feedback and discuss the future of ZMAP.

Factors influencing responsiveness to feedback: on the interplay between fear, confidence, and reasoning processes.

PubMed

Eva, Kevin W; Armson, Heather; Holmboe, Eric; Lockyer, Jocelyn; Loney, Elaine; Mann, Karen; Sargeant, Joan

2012-03-01

Self-appraisal has repeatedly been shown to be inadequate as a mechanism for performance improvement. This has placed greater emphasis on understanding the processes through which self-perception and external feedback interact to influence professional development. As feedback is inevitably interpreted through the lens of one's self-perceptions it is important to understand how learners interpret, accept, and use feedback (or not) and the factors that influence those interpretations. 134 participants from 8 health professional training/continuing competence programs were recruited to participate in focus groups. Analyses were designed to (a) elicit understandings of the processes used by learners and physicians to interpret, accept and use (or not) data to inform their perceptions of their clinical performance, and (b) further understand the factors (internal and external) believed to influence interpretation of feedback. Multiple influences appear to impact upon the interpretation and uptake of feedback. These include confidence, experience, and fear of not appearing knowledgeable. Importantly, however, each could have a paradoxical effect of both increasing and decreasing receptivity. Less prevalent but nonetheless important themes suggested mechanisms through which cognitive reasoning processes might impede growth from formative feedback. Many studies have examined the effectiveness of feedback through variable interventions focused on feedback delivery. This study suggests that it is equally important to consider feedback from the perspective of how it is received. The interplay observed between fear, confidence, and reasoning processes reinforces the notion that there is no simple recipe for the delivery of effective feedback. These factors should be taken into account when trying to understand (a) why self-appraisal can be flawed, (b) why appropriate external feedback is vital (yet can be ineffective), and (c) why we may need to disentangle the goals of performance improvement from the goals of improving self-assessment.

Electrophysiological responses of feedback processing are modulated by MAOA genotype in healthy male adolescents.

PubMed

Ma, Ren; Jia, Huiqiao; Yi, Fei; Ming, Qingsen; Wang, Xiang; Gao, Yidian; Yi, Jinyao; Yao, Shuqiao

2016-01-01

A functional polymorphism in the promoter region of the monoamine oxidase A (MAOA) gene is closely related to aggression. Although previous studies suggested that impaired ability of feedback processing might be associated with aggressive behaviour, studies concerning the MAOA gene-related aggression rarely focused on the link between MAOA gene and feedback processing. We therefore sought to investigate the effect of MAOA genotype on electrophysiological responses of feedback processing in 72 healthy male adolescents during a simple monetary gambling task. Feedback processing was investigated by measuring the feedback-related negativity (FRN) and the P300 as electrophysiological markers. We observed a decreased electrophysiological response of the loss-gain difference waves from 250 to 350 ms (dFRN) in individuals with the lower activity alleles (MAOA-L) during the task, an effect that was driven primarily by the considerably altered response to monetary gains. The reduced dFRN in MAOA-L group might indicate poor ability to learn from feedback, which is followed by adjusting future behaviour. And MAOA-L carriers exhibited lower P300 compared with subjects with higher activity alleles (MAOA-H), which suggested fewer attentional resources were allocated to feedback processing. In addition, MAOA-L carriers demonstrated higher aggression and the aggression were inversely correlated with dFRN across two groups; further analyses suggested that dFRN mediated the MAOA genotype-aggression relationship. Consequently, we concluded that it might be the altered feedback processing that makes MAOA-L carriers more vulnerable to aggressive behaviour. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

High Cycle Fatigue (HCF) Science and Technology Program 2002 Annual Report

DTIC Science & Technology

2003-08-01

Turbine Engine Airfoils, Phase I 4.3 Probabilistic Design of Turbine Engine Airfoils, Phase II 4.4 Probabilistic Blade Design System 4.5...XTL17/SE2 7.4 Conclusion 8.0 TEST AND EVALUATION 8.1 Characterization Test Protocol 8.2 Demonstration Test Protocol 8.3 Development of Multi ...transparent and opaque overlays for processing. The objective of the SBIR Phase I program was to identify and evaluate promising methods for

Patterns and reliability of EEG during error monitoring for internal versus external feedback in schizophrenia.

PubMed

Llerena, Katiah; Wynn, Jonathan K; Hajcak, Greg; Green, Michael F; Horan, William P

2016-07-01

Accurately monitoring one's performance on daily life tasks, and integrating internal and external performance feedback are necessary for guiding productive behavior. Although internal feedback processing, as indexed by the error-related negativity (ERN), is consistently impaired in schizophrenia, initial findings suggest that external performance feedback processing, as indexed by the feedback negativity (FN), may actually be intact. The current study evaluated internal and external feedback processing task performance and test-retest reliability in schizophrenia. 92 schizophrenia outpatients and 63 healthy controls completed a flanker task (ERN) and a time estimation task (FN). Analyses examined the ΔERN and ΔFN defined as difference waves between correct/positive versus error/negative feedback conditions. A temporal principal component analysis was conducted to distinguish the ΔERN and ΔFN from overlapping neural responses. We also assessed test-retest reliability of ΔERN and ΔFN in patients over a 4-week interval. Patients showed reduced ΔERN accompanied by intact ΔFN. In patients, test-retest reliability for both ΔERN and ΔFN over a four-week period was fair to good. Individuals with schizophrenia show a pattern of impaired internal, but intact external, feedback processing. This pattern has implications for understanding the nature and neural correlates of impaired feedback processing in schizophrenia. Published by Elsevier B.V.

Translational Rodent Paradigms to Investigate Neuromechanisms Underlying Behaviors Relevant to Amotivation and Altered Reward Processing in Schizophrenia

PubMed Central

Young, Jared W.; Markou, Athina

2015-01-01

Amotivation and reward-processing deficits have long been described in patients with schizophrenia and considered large contributors to patients’ inability to integrate well in society. No effective treatments exist for these symptoms, partly because the neuromechanisms mediating such symptoms are poorly understood. Here, we propose a translational neuroscientific approach that can be used to assess reward/motivational deficits related to the negative symptoms of schizophrenia using behavioral paradigms that can also be conducted in experimental animals. By designing and using objective laboratory behavioral tools that are parallel in their parameters in rodents and humans, the neuromechanisms underlying behaviors with relevance to these symptoms of schizophrenia can be investigated. We describe tasks that measure the motivation of rodents to expend physical and cognitive effort to gain rewards, as well as probabilistic learning tasks that assess both reward learning and feedback-based decision making. The latter tasks are relevant because of demonstrated links of performance deficits correlating with negative symptoms in patients with schizophrenia. These tasks utilize operant techniques in order to investigate neural circuits targeting a specific domain across species. These tasks therefore enable the development of insights into altered mechanisms leading to negative symptom-relevant behaviors in patients with schizophrenia. Such findings will then enable the development of targeted treatments for these altered neuromechanisms and behaviors seen in schizophrenia. PMID:26194891

A review for identification of initiating events in event tree development process on nuclear power plants

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

Riyadi, Eko H., E-mail: e.riyadi@bapeten.go.id

2014-09-30

Initiating event is defined as any event either internal or external to the nuclear power plants (NPPs) that perturbs the steady state operation of the plant, if operating, thereby initiating an abnormal event such as transient or loss of coolant accident (LOCA) within the NPPs. These initiating events trigger sequences of events that challenge plant control and safety systems whose failure could potentially lead to core damage or large early release. Selection for initiating events consists of two steps i.e. first step, definition of possible events, such as by evaluating a comprehensive engineering, and by constructing a top level logicmore » model. Then the second step, grouping of identified initiating event's by the safety function to be performed or combinations of systems responses. Therefore, the purpose of this paper is to discuss initiating events identification in event tree development process and to reviews other probabilistic safety assessments (PSA). The identification of initiating events also involves the past operating experience, review of other PSA, failure mode and effect analysis (FMEA), feedback from system modeling, and master logic diagram (special type of fault tree). By using the method of study for the condition of the traditional US PSA categorization in detail, could be obtained the important initiating events that are categorized into LOCA, transients and external events.« less

Data analysis using scale-space filtering and Bayesian probabilistic reasoning

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Kutulakos, Kiriakos; Robinson, Peter

1991-01-01

This paper describes a program for analysis of output curves from Differential Thermal Analyzer (DTA). The program first extracts probabilistic qualitative features from a DTA curve of a soil sample, and then uses Bayesian probabilistic reasoning to infer the mineral in the soil. The qualifier module employs a simple and efficient extension of scale-space filtering suitable for handling DTA data. We have observed that points can vanish from contours in the scale-space image when filtering operations are not highly accurate. To handle the problem of vanishing points, perceptual organizations heuristics are used to group the points into lines. Next, these lines are grouped into contours by using additional heuristics. Probabilities are associated with these contours using domain-specific correlations. A Bayes tree classifier processes probabilistic features to infer the presence of different minerals in the soil. Experiments show that the algorithm that uses domain-specific correlation to infer qualitative features outperforms a domain-independent algorithm that does not.

Probabilistic modeling of bifurcations in single-cell gene expression data using a Bayesian mixture of factor analyzers.

PubMed

Campbell, Kieran R; Yau, Christopher

2017-03-15

Modeling bifurcations in single-cell transcriptomics data has become an increasingly popular field of research. Several methods have been proposed to infer bifurcation structure from such data, but all rely on heuristic non-probabilistic inference. Here we propose the first generative, fully probabilistic model for such inference based on a Bayesian hierarchical mixture of factor analyzers. Our model exhibits competitive performance on large datasets despite implementing full Markov-Chain Monte Carlo sampling, and its unique hierarchical prior structure enables automatic determination of genes driving the bifurcation process. We additionally propose an Empirical-Bayes like extension that deals with the high levels of zero-inflation in single-cell RNA-seq data and quantify when such models are useful. We apply or model to both real and simulated single-cell gene expression data and compare the results to existing pseudotime methods. Finally, we discuss both the merits and weaknesses of such a unified, probabilistic approach in the context practical bioinformatics analyses.

Risk analysis of analytical validations by probabilistic modification of FMEA.

PubMed

Barends, D M; Oldenhof, M T; Vredenbregt, M J; Nauta, M J

2012-05-01

Risk analysis is a valuable addition to validation of an analytical chemistry process, enabling not only detecting technical risks, but also risks related to human failures. Failure Mode and Effect Analysis (FMEA) can be applied, using a categorical risk scoring of the occurrence, detection and severity of failure modes, and calculating the Risk Priority Number (RPN) to select failure modes for correction. We propose a probabilistic modification of FMEA, replacing the categorical scoring of occurrence and detection by their estimated relative frequency and maintaining the categorical scoring of severity. In an example, the results of traditional FMEA of a Near Infrared (NIR) analytical procedure used for the screening of suspected counterfeited tablets are re-interpretated by this probabilistic modification of FMEA. Using this probabilistic modification of FMEA, the frequency of occurrence of undetected failure mode(s) can be estimated quantitatively, for each individual failure mode, for a set of failure modes, and the full analytical procedure. Copyright © 2012 Elsevier B.V. All rights reserved.

Impact of Hydrologic Variability on Ecosystem Dynamics and the Sustainable Use of Soil and Water Resources

NASA Astrophysics Data System (ADS)

Porporato, A. M.

2013-05-01

We discuss the key processes by which hydrologic variability affects the probabilistic structure of soil moisture dynamics in water-controlled ecosystems. These in turn impact biogeochemical cycling and ecosystem structure through plant productivity and biodiversity as well as nitrogen availability and soil conditions. Once the long-term probabilistic structure of these processes is quantified, the results become useful to understand the impact of climatic changes and human activities on ecosystem services, and can be used to find optimal strategies of water and soil resources management under unpredictable hydro-climatic fluctuations. Particular applications regard soil salinization, phytoremediation and optimal stochastic irrigation.

Reliability and Probabilistic Risk Assessment - How They Play Together

NASA Technical Reports Server (NTRS)

Safie, Fayssal; Stutts, Richard; Huang, Zhaofeng

2015-01-01

Since the Space Shuttle Challenger accident in 1986, NASA has extensively used probabilistic analysis methods to assess, understand, and communicate the risk of space launch vehicles. Probabilistic Risk Assessment (PRA), used in the nuclear industry, is one of the probabilistic analysis methods NASA utilizes to assess Loss of Mission (LOM) and Loss of Crew (LOC) risk for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability distributions to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: 1) what can go wrong that would lead to loss or degraded performance (i.e., scenarios involving undesired consequences of interest), 2) how likely is it (probabilities), and 3) what is the severity of the degradation (consequences). Since the Challenger accident, PRA has been used in supporting decisions regarding safety upgrades for launch vehicles. Another area that was given a lot of emphasis at NASA after the Challenger accident is reliability engineering. Reliability engineering has been a critical design function at NASA since the early Apollo days. However, after the Challenger accident, quantitative reliability analysis and reliability predictions were given more scrutiny because of their importance in understanding failure mechanism and quantifying the probability of failure, which are key elements in resolving technical issues, performing design trades, and implementing design improvements. Although PRA and reliability are both probabilistic in nature and, in some cases, use the same tools, they are two different activities. Specifically, reliability engineering is a broad design discipline that deals with loss of function and helps understand failure mechanism and improve component and system design. PRA is a system scenario based risk assessment process intended to assess the risk scenarios that could lead to a major/top undesirable system event, and to identify those scenarios that are high-risk drivers. PRA output is critical to support risk informed decisions concerning system design. This paper describes the PRA process and the reliability engineering discipline in detail. It discusses their differences and similarities and how they work together as complementary analyses to support the design and risk assessment processes. Lessons learned, applications, and case studies in both areas are also discussed in the paper to demonstrate and explain these differences and similarities.

Facilitating the Feedback Process on a Clinical Clerkship Using a Smartphone Application.

PubMed

Joshi, Aditya; Generalla, Jenilee; Thompson, Britta; Haidet, Paul

2017-10-01

This pilot study evaluated the effects of a smartphone-triggered method of feedback delivery on students' perceptions of the feedback process. An interactive electronic feedback form was made available to students through a smartphone app. Students were asked to evaluate various aspects of the feedback process. Responses from a previous year served as control. In the first three quarters of academic year 2014-2015 (pre-implementation), only 65% of responders reported receiving oral feedback and 40% reported receiving written feedback. During the pilot phase (transition), these increased to 80% for both forms. Following full implementation in academic year 2015-2016 (post-implementation), 97% reported receiving oral feedback, and 92% reported receiving written feedback. A statistically significant difference was noted pre- to post-implementation for both oral and written feedback (p < 0.01). A significant increase from pre-implementation to transition was noted for written feedback (p < 0.01) and from transition to post-implementation for oral feedback (p < 0.01). Ninety-one and 94% of responders reported ease of access and timeliness of the feedback, 75% perceived the quality of the feedback to be good to excellent; 64% felt receiving feedback via the app improved their performance; 69% indicated the feedback method as better compared to other methods. Students acknowledged the facilitation of conversation with supervisors and the convenience of receiving feedback, as well as the promptness with which feedback was provided. The use of a drop-down menu was thought to limit the scope of conversation. These data point to the effectiveness of this method to cue supervisors to provide feedback to students.

A Discounting Framework for Choice With Delayed and Probabilistic Rewards

PubMed Central

Green, Leonard; Myerson, Joel

2005-01-01

When choosing between delayed or uncertain outcomes, individuals discount the value of such outcomes on the basis of the expected time to or the likelihood of their occurrence. In an integrative review of the expanding experimental literature on discounting, the authors show that although the same form of hyperbola-like function describes discounting of both delayed and probabilistic outcomes, a variety of recent findings are inconsistent with a single-process account. The authors also review studies that compare discounting in different populations and discuss the theoretical and practical implications of the findings. The present effort illustrates the value of studying choice involving both delayed and probabilistic outcomes within a general discounting framework that uses similar experimental procedures and a common analytical approach. PMID:15367080

Effect of delayed auditory feedback on stuttering with and without central auditory processing disorders.

PubMed

Picoloto, Luana Altran; Cardoso, Ana Cláudia Vieira; Cerqueira, Amanda Venuti; Oliveira, Cristiane Moço Canhetti de

2017-12-07

To verify the effect of delayed auditory feedback on speech fluency of individuals who stutter with and without central auditory processing disorders. The participants were twenty individuals with stuttering from 7 to 17 years old and were divided into two groups: Stuttering Group with Auditory Processing Disorders (SGAPD): 10 individuals with central auditory processing disorders, and Stuttering Group (SG): 10 individuals without central auditory processing disorders. Procedures were: fluency assessment with non-altered auditory feedback (NAF) and delayed auditory feedback (DAF), assessment of the stuttering severity and central auditory processing (CAP). Phono Tools software was used to cause a delay of 100 milliseconds in the auditory feedback. The "Wilcoxon Signal Post" test was used in the intragroup analysis and "Mann-Whitney" test in the intergroup analysis. The DAF caused a statistically significant reduction in SG: in the frequency score of stuttering-like disfluencies in the analysis of the Stuttering Severity Instrument, in the amount of blocks and repetitions of monosyllabic words, and in the frequency of stuttering-like disfluencies of duration. Delayed auditory feedback did not cause statistically significant effects on SGAPD fluency, individuals with stuttering with auditory processing disorders. The effect of delayed auditory feedback in speech fluency of individuals who stutter was different in individuals of both groups, because there was an improvement in fluency only in individuals without auditory processing disorder.

The Use of Video Feedback in Teaching Process-Approach EFL Writing

ERIC Educational Resources Information Center

Özkul, Sertaç; Ortaçtepe, Deniz

2017-01-01

This experimental study investigated the use of video feedback as an alternative to feedback with correction codes at an institution where the latter was commonly used for teaching process-approach English as a foreign language (EFL) writing. Over a 5-week period, the control and the experimental groups were provided with feedback based on…

Assessing Technology in the Absence of Proof: Trust Based on the Interplay of Others' Opinions and the Interaction Process.

PubMed

de Vries, Peter W; van den Berg, Stéphanie M; Midden, Cees

2015-12-01

The present research addresses the question of how trust in systems is formed when unequivocal information about system accuracy and reliability is absent, and focuses on the interaction of indirect information (others' evaluations) and direct (experiential) information stemming from the interaction process. Trust in decision-supporting technology, such as route planners, is important for satisfactory user interactions. Little is known, however, about trust formation in the absence of outcome feedback, that is, when users have not yet had opportunity to verify actual outcomes. Three experiments manipulated others' evaluations ("endorsement cues") and various forms of experience-based information ("process feedback") in interactions with a route planner and measured resulting trust using rating scales and credits staked on the outcome. Subsequently, an overall analysis was conducted. Study 1 showed that effectiveness of endorsement cues on trust is moderated by mere process feedback. In Study 2, consistent (i.e., nonrandom) process feedback overruled the effect of endorsement cues on trust, whereas inconsistent process feedback did not. Study 3 showed that although the effects of consistent and inconsistent process feedback largely remained regardless of face validity, high face validity in process feedback caused higher trust than those with low face validity. An overall analysis confirmed these findings. Experiential information impacts trust even if outcome feedback is not available, and, moreover, overrules indirect trust cues-depending on the nature of the former. Designing systems so that they allow novice users to make inferences about their inner workings may foster initial trust. © 2015, Human Factors and Ergonomics Society.

Teachers' Emotions and Test Feedback.

ERIC Educational Resources Information Center

Stough, Laura M.; Emmer, Edmund T.

1998-01-01

Investigates teachers thoughts about test-feedback sessions and their resulting emotions and strategies when delivering feedback to students. Explains that past experiences with feedback sessions, problem students, teachers beliefs about feedback processes, and their goals for providing feedback influence the teachers level of emotion; the…

Using client feedback in psychotherapy from an interpersonal process perspective.

PubMed

Reese, Robert J; Slone, Norah C; Miserocchi, Kristin M

2013-09-01

The process of monitoring treatment outcome, also known as "client feedback," is increasingly becoming a recommended practice for psychotherapy. One concern, however, is how to integrate such a process into the work that psychotherapists typically do. Three clinical examples are presented, illustrating how a client feedback system can be used in conjunction with a specific theoretical framework, interpersonal process therapy (Teyber, 2006). The examples highlight that client feedback not only can be of minimal disruption to the psychotherapy process, but may also offer the potential to augment a clinician's approach to helping. Theoretical and research support are provided for each example. 2013 APA, all rights reserved

Building a Culture of Engagement through Participatory Feedback Processes

ERIC Educational Resources Information Center

Hatchimonji, Danielle R.; Linsky, Arielle V.; DeMarchena, Sarah; Nayman, Samuel J.; Kim, Sarah; Elias, Maurice J.

2018-01-01

In response to school environments in which teachers and students feel disconnected from the learning process, we developed a three-part curriculum feedback system with the goal of creating a school-wide culture of engagement through participatory feedback processes. Here we describe the barriers to participation and ownership that are addressed…

Separable Neural Mechanisms Contribute to Feedback Processing in a Rule-Learning Task

ERIC Educational Resources Information Center

Zanolie, K.; Van Leijenhorst, L.; Rombouts, S. A. R. B.; Crone, E. A.

2008-01-01

To adjust performance appropriately to environmental demands, it is important to monitor ongoing action and process performance feedback for possible errors. In this study, we used fMRI to test whether medial prefrontal cortex (PFC)/anterior cingulate cortex (ACC) and dorsolateral (DL) PFC have different roles in feedback processing. Twenty adults…

Mind as Space

NASA Astrophysics Data System (ADS)

McKinstry, Chris

The present article describes a possible method for the automatic discovery of a universal human semantic-affective hyperspatial approximation of the human subcognitive substrate - the associative network which French (1990) asserts is the ultimate foundation of the human ability to pass the Turing Test - that does not require a machine to have direct human experience or a physical human body. This method involves automatic programming - such as Koza's genetic programming (1992) - guided in the discovery of the proposed universal hypergeometry by feedback from a Minimum Intelligent Signal Test or MIST (McKinstry, 1997) constructed from a very large number of human validated probabilistic propositions collected from a large population of Internet users. It will be argued that though a lifetime of human experience is required to pass a rigorous Turing Test, a probabilistic propositional approximation of this experience can be constructed via public participation on the Internet, and then used as a fitness function to direct the artificial evolution of a universal hypergeometry capable of classifying arbitrary propositions. A model of this hypergeometry will be presented; it predicts Miller's "Magical Number Seven" (1956) as the size of human short-term memory from fundamental hypergeometric properties. A system that can lead to the generation of novel propositions or "artificial thoughts" will also be described.

Temporal prediction modulates the evaluative processing of "good" action feedback: An electrophysiological study.

PubMed

Kimura, Kenta; Kimura, Motohiro; Iwaki, Sunao

2016-10-01

The present study aimed to investigate whether or not the evaluative processing of action feedback can be modulated by temporal prediction. For this purpose, we examined the effects of the predictability of the timing of action feedback on an ERP effect that indexed the evaluative processing of action feedback, that is, an ERP effect that has been interpreted as a feedback-related negativity (FRN) elicited by "bad" action feedback or a reward positivity (RewP) elicited by "good" action feedback. In two types of experimental blocks, the participants performed a gambling task in which they chose one of two cards and received an action feedback that indicated monetary gain or loss. In fixed blocks, the time interval between the participant's choice and the onset of the action feedback was fixed at 0, 500, or 1,000 ms in separate blocks; thus, the timing of action feedback was predictable. In mixed blocks, the time interval was randomly chosen from the same three intervals with equal probability; thus, the timing was less predictable. The results showed that the FRN/RewP was smaller in mixed than fixed blocks for the 0-ms interval trial, whereas there was no difference between the two block types for the 500-ms and 1,000-ms interval trials. Interestingly, the smaller FRN/RewP was due to the modulation of gain ERPs rather than loss ERPs. These results suggest that temporal prediction can modulate the evaluative processing of action feedback, and particularly good feedback, such as that which indicates monetary gain. © 2016 Society for Psychophysiological Research.

How does feedback in mini-CEX affect students' learning response?

PubMed

Sudarso, Sulistiawati; Rahayu, Gandes Retno; Suhoyo, Yoyo

2016-12-19

This study was aimed to explore students' learning response toward feedback during mini-CEX encounter. This study used a phenomenological approach to identify the students' experiences toward feedback during mini-CEX encounter. Data was collected using Focus Group Discussion (FGD) for all students who were in their final week of clerkship in the internal medicine rotation. There were 4 FGD groups (6 students for each group). All FGD were audio-taped and transcribed verbatim. The FGD transcripts were analyzed thematically and managed using Atlas-ti (version 7.0). Feedback content and the way of providing feedback on mini-CEX stimulated students' internal process, including self-reflection, emotional response, and motivation. These internal processes encouraged the students to take action or do a follow-up on the feedback to improve their learning process. In addition, there was also an external factor, namely consequences, which also influenced the students' reaction to the follow-up on feedback. In the end, this action caused several learning effects that resulted in the students' increased self-efficacy, attitude, knowledge and clinical skill. Feedback content and the way of providing feedback on mini-CEX stimulates the students' internal processes to do a follow-up on feedback. However, another external factor also affects the students' decision on the follow-up actions. The follow-ups result in various learning effects on the students. Feedback given along with summative assessment enhances learning effects on students, as well. It is suggested that supervisors of clinical education are prepared to comprehend every factor influencing feedback on mini CEX to improve the students' learning response.

Probabilistic Fracture Mechanics of Reactor Pressure Vessels with Populations of Flaws

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

Spencer, Benjamin; Backman, Marie; Williams, Paul

This report documents recent progress in developing a tool that uses the Grizzly and RAVEN codes to perform probabilistic fracture mechanics analyses of reactor pressure vessels in light water reactor nuclear power plants. The Grizzly code is being developed with the goal of creating a general tool that can be applied to study a variety of degradation mechanisms in nuclear power plant components. Because of the central role of the reactor pressure vessel (RPV) in a nuclear power plant, particular emphasis is being placed on developing capabilities to model fracture in embrittled RPVs to aid in the process surrounding decisionmore » making relating to life extension of existing plants. A typical RPV contains a large population of pre-existing flaws introduced during the manufacturing process. The use of probabilistic techniques is necessary to assess the likelihood of crack initiation at one or more of these flaws during a transient event. This report documents development and initial testing of a capability to perform probabilistic fracture mechanics of large populations of flaws in RPVs using reduced order models to compute fracture parameters. The work documented here builds on prior efforts to perform probabilistic analyses of a single flaw with uncertain parameters, as well as earlier work to develop deterministic capabilities to model the thermo-mechanical response of the RPV under transient events, and compute fracture mechanics parameters at locations of pre-defined flaws. The capabilities developed as part of this work provide a foundation for future work, which will develop a platform that provides the flexibility needed to consider scenarios that cannot be addressed with the tools used in current practice.« less

Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets.

PubMed

Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B

2017-05-01

Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% ( P  < 10 -20 ) by using probabilistic topic models to summarize clinical data into up to 32 topics. Many of these latent topics yield natural clinical interpretations (e.g., "critical care," "pneumonia," "neurologic evaluation"). Existing order sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets

PubMed Central

Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B

2017-01-01

Objective: Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. Materials and Methods: The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Results: Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% (P < 10−20) by using probabilistic topic models to summarize clinical data into up to 32 topics. Many of these latent topics yield natural clinical interpretations (e.g., “critical care,” “pneumonia,” “neurologic evaluation”). Discussion: Existing order sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Conclusion: Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. PMID:27655861

A qualitative study of the variable effects of audit and feedback in the ICU.

PubMed

Sinuff, Tasnim; Muscedere, John; Rozmovits, Linda; Dale, Craig M; Scales, Damon C

2015-06-01

Audit and feedback is integral to performance improvement and behaviour change in the intensive care unit (ICU). However, there remain large gaps in our understanding of the social experience of audit and feedback and the mechanisms whereby it can be optimised as a quality improvement strategy in the ICU setting. We conducted a modified grounded theory qualitative study. Seventy-two clinicians from five academic and five community ICUs in Ontario, Canada, were interviewed. Team members reviewed interview transcripts independently. Data analysis used constant comparative methods. Clinicians interviewed experienced audit and feedback as fragmented and variable in its effectiveness. Moreover, clinicians felt disconnected from the process. The audit process was perceived as being insufficiently transparent. Feedback was often untimely, incomplete and not actionable. Specific groups such as respiratory therapists and night-shift clinicians felt marginalised. Suggestions for improvement included improving information sharing about the rationale for change and the audit process, tools and metrics; implementing peer-to-peer quality discussions to avoid a top-down approach (eg, incorporating feedback into discussions at daily rounds); providing effective feedback which contains specific, transparent and actionable information; delivering timely feedback (ie, balancing feedback proximate to events with trends over time) and increasing engagement by senior management. ICU clinicians experience audit and feedback as fragmented communication with feedback being especially problematic. Attention to improving communication, integration of the process into daily clinical activities and making feedback timely, specific and actionable may increase the effectiveness of audit and feedback to affect desired change. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Probabilistic Risk Assessment Process for High-Power Laser Operations in Outdoor Environments

DTIC Science & Technology

2016-01-01

avionics data bus. In the case of a UAS-mounted laser system, the control path will additionally include a radio or satellite communications link. A remote...JBSA Fort Sam Houston, TX 78234 711 HPW/RHDO 11 . SPONSOR’S/MONITOR’S REPORT NUMBER(S) AFRL-RH-FS-JA-2015...hazard assessment pur- poses is not widespread within the laser safety community . The aim of this paper is to outline the basis of the probabilistic

Ambiguity and Uncertainty in Probabilistic Inference.

DTIC Science & Technology

1983-09-01

whether one was to judge the like- lihood that the majority or minority position was true . In order to sample a wide range of values of n and p, 40...AFD-A133 418 AMBIGUITY AND UNCERTAINTY IN PROBABILISTIC INFERENCE i/i U CLRS (U) CHICGO UNIT’ IL CENTER FOR DECISION RESERCH H J EINHORN ET AL. SEP...been demonstrated experimentally (Becker & Brownson, 1964; Yates & Zukowski, 1976). On the other hand, the process by which such second-order uncertainty

Concurrent Probabilistic Simulation of High Temperature Composite Structural Response

NASA Technical Reports Server (NTRS)

Abdi, Frank

1996-01-01

A computational structural/material analysis and design tool which would meet industry's future demand for expedience and reduced cost is presented. This unique software 'GENOA' is dedicated to parallel and high speed analysis to perform probabilistic evaluation of high temperature composite response of aerospace systems. The development is based on detailed integration and modification of diverse fields of specialized analysis techniques and mathematical models to combine their latest innovative capabilities into a commercially viable software package. The technique is specifically designed to exploit the availability of processors to perform computationally intense probabilistic analysis assessing uncertainties in structural reliability analysis and composite micromechanics. The primary objectives which were achieved in performing the development were: (1) Utilization of the power of parallel processing and static/dynamic load balancing optimization to make the complex simulation of structure, material and processing of high temperature composite affordable; (2) Computational integration and synchronization of probabilistic mathematics, structural/material mechanics and parallel computing; (3) Implementation of an innovative multi-level domain decomposition technique to identify the inherent parallelism, and increasing convergence rates through high- and low-level processor assignment; (4) Creating the framework for Portable Paralleled architecture for the machine independent Multi Instruction Multi Data, (MIMD), Single Instruction Multi Data (SIMD), hybrid and distributed workstation type of computers; and (5) Market evaluation. The results of Phase-2 effort provides a good basis for continuation and warrants Phase-3 government, and industry partnership.

Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review

PubMed Central

McClelland, James L.

2013-01-01

This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered. PMID:23970868

Probabilistic Learning by Rodent Grid Cells

PubMed Central

Cheung, Allen

2016-01-01

Mounting evidence shows mammalian brains are probabilistic computers, but the specific cells involved remain elusive. Parallel research suggests that grid cells of the mammalian hippocampal formation are fundamental to spatial cognition but their diverse response properties still defy explanation. No plausible model exists which explains stable grids in darkness for twenty minutes or longer, despite being one of the first results ever published on grid cells. Similarly, no current explanation can tie together grid fragmentation and grid rescaling, which show very different forms of flexibility in grid responses when the environment is varied. Other properties such as attractor dynamics and grid anisotropy seem to be at odds with one another unless additional properties are assumed such as a varying velocity gain. Modelling efforts have largely ignored the breadth of response patterns, while also failing to account for the disastrous effects of sensory noise during spatial learning and recall, especially in darkness. Here, published electrophysiological evidence from a range of experiments are reinterpreted using a novel probabilistic learning model, which shows that grid cell responses are accurately predicted by a probabilistic learning process. Diverse response properties of probabilistic grid cells are statistically indistinguishable from rat grid cells across key manipulations. A simple coherent set of probabilistic computations explains stable grid fields in darkness, partial grid rescaling in resized arenas, low-dimensional attractor grid cell dynamics, and grid fragmentation in hairpin mazes. The same computations also reconcile oscillatory dynamics at the single cell level with attractor dynamics at the cell ensemble level. Additionally, a clear functional role for boundary cells is proposed for spatial learning. These findings provide a parsimonious and unified explanation of grid cell function, and implicate grid cells as an accessible neuronal population readout of a set of probabilistic spatial computations. PMID:27792723

Probabilistic vs. deterministic fiber tracking and the influence of different seed regions to delineate cerebellar-thalamic fibers in deep brain stimulation.

PubMed

Schlaier, Juergen R; Beer, Anton L; Faltermeier, Rupert; Fellner, Claudia; Steib, Kathrin; Lange, Max; Greenlee, Mark W; Brawanski, Alexander T; Anthofer, Judith M

2017-06-01

This study compared tractography approaches for identifying cerebellar-thalamic fiber bundles relevant to planning target sites for deep brain stimulation (DBS). In particular, probabilistic and deterministic tracking of the dentate-rubro-thalamic tract (DRTT) and differences between the spatial courses of the DRTT and the cerebello-thalamo-cortical (CTC) tract were compared. Six patients with movement disorders were examined by magnetic resonance imaging (MRI), including two sets of diffusion-weighted images (12 and 64 directions). Probabilistic and deterministic tractography was applied on each diffusion-weighted dataset to delineate the DRTT. Results were compared with regard to their sensitivity in revealing the DRTT and additional fiber tracts and processing time. Two sets of regions-of-interests (ROIs) guided deterministic tractography of the DRTT or the CTC, respectively. Tract distances to an atlas-based reference target were compared. Probabilistic fiber tracking with 64 orientations detected the DRTT in all twelve hemispheres. Deterministic tracking detected the DRTT in nine (12 directions) and in only two (64 directions) hemispheres. Probabilistic tracking was more sensitive in detecting additional fibers (e.g. ansa lenticularis and medial forebrain bundle) than deterministic tracking. Probabilistic tracking lasted substantially longer than deterministic. Deterministic tracking was more sensitive in detecting the CTC than the DRTT. CTC tracts were located adjacent but consistently more posterior to DRTT tracts. These results suggest that probabilistic tracking is more sensitive and robust in detecting the DRTT but harder to implement than deterministic approaches. Although sensitivity of deterministic tracking is higher for the CTC than the DRTT, targets for DBS based on these tracts likely differ. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review.

PubMed

McClelland, James L

2013-01-01

This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered.

Brain Activity Elicited by Positive and Negative Feedback in Preschool-Aged Children

PubMed Central

Mai, Xiaoqin; Tardif, Twila; Doan, Stacey N.; Liu, Chao; Gehring, William J.; Luo, Yue-Jia

2011-01-01

To investigate the processing of positive vs. negative feedback in children aged 4–5 years, we devised a prize-guessing game that is analogous to gambling tasks used to measure feedback-related brain responses in adult studies. Unlike adult studies, the feedback-related negativity (FRN) elicited by positive feedback was as large as that elicited by negative feedback, suggesting that the neural system underlying the FRN may not process feedback valence in early childhood. In addition, positive feedback, compared with negative feedback, evoked a larger P1 over the occipital scalp area and a larger positive slow wave (PSW) over the right central-parietal scalp area. We believe that the PSW is related to emotional arousal and the intensive focus on positive feedback that is present in the preschool and early school years has adaptive significance for both cognitive and emotional development during this period. PMID:21526189

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

Why self-controlled feedback enhances motor learning: Answers from electroencephalography and indices of motivation.

PubMed

Grand, Kirk F; Bruzi, Alessandro T; Dyke, Ford B; Godwin, Maurice M; Leiker, Amber M; Thompson, Andrew G; Buchanan, Taylor L; Miller, Matthew W

2015-10-01

It was tested whether learners who choose when to receive augmented feedback while practicing a motor skill exhibit enhanced augmented feedback processing and intrinsic motivation, along with superior learning, relative to learners who do not control their feedback. Accordingly, participants were assigned to either self-control (Self) or yoked groups and asked to practice a non-dominant arm beanbag toss. Self participants received augmented feedback at their discretion, whereas Yoked participants were given feedback schedules matched to Self counterparts. Participants' visual feedback was occluded, and when they received augmented feedback, their processing of it was indexed with the electroencephalography-derived feedback-related negativity (FRN). Participants self-reported intrinsic motivation via the Intrinsic Motivation Inventory (IMI) after practice, and completed a retention and transfer test the next day to index learning. Results partially support the hypothesis. Specifically, Self participants reported higher IMI scores, exhibited larger FRNs, and demonstrated better accuracy on the transfer test, but not on the retention test, nor did they exhibit greater consistency on the retention or transfer tests. Additionally, post-hoc multiple regression analysis indicated FRN amplitude predicted transfer test accuracy (accounting for IMI score). Results suggest self-controlled feedback schedules enhance feedback processing, which enhances the transfer of a newly acquired motor skill. Copyright © 2015 Elsevier B.V. All rights reserved.

Experimental realization of a feedback optical parametric amplifier with four-wave mixing

NASA Astrophysics Data System (ADS)

Pan, Xiaozhou; Chen, Hui; Wei, Tianxiang; Zhang, Jun; Marino, Alberto M.; Treps, Nicolas; Glasser, Ryan T.; Jing, Jietai

2018-04-01

Optical parametric amplifiers (OPAs) play a fundamental role in the generation of quantum correlation for quantum information processing and quantum metrology. In order to increase the communication fidelity of the quantum information protocol and the measurement precision of quantum metrology, it requires a high degree of quantum correlation. In this Rapid Communication we report a feedback optical parametric amplifier that employs a four-wave mixing (FWM) process as the underlying OPA and a beam splitter as the feedback controller. We first construct a theoretical model for this feedback-based FWM process and experimentally study the effect of the feedback control on the quantum properties of the system. Specifically, we find that the quantum correlation between the output fields can be enhanced by tuning the strength of the feedback.

Reexamining the Affective Advantage of Peer Feedback in the ESL Writing Class.

ERIC Educational Resources Information Center

Zhang, Shuqiang

1995-01-01

Examines hypotheses concerning the appeal of three types of feedback in the second-language writing process: teacher-, peer-, and self-directed feedback. Results show that students overwhelmingly prefer teacher feedback to peer feedback. (Author/CK)

User perception and interpretation of tornado probabilistic hazard information: Comparison of four graphical designs.

PubMed

Miran, Seyed M; Ling, Chen; James, Joseph J; Gerard, Alan; Rothfusz, Lans

2017-11-01

Effective design for presenting severe weather information is important to reduce devastating consequences of severe weather. The Probabilistic Hazard Information (PHI) system for severe weather is being developed by NOAA National Severe Storms Laboratory (NSSL) to communicate probabilistic hazardous weather information. This study investigates the effects of four PHI graphical designs for tornado threat, namely, "four-color"," red-scale", "grayscale" and "contour", on users' perception, interpretation, and reaction to threat information. PHI is presented on either a map background or a radar background. Analysis showed that the accuracy was significantly higher and response time faster when PHI was displayed on map background as compared to radar background due to better contrast. When displayed on a radar background, "grayscale" design resulted in a higher accuracy of responses. Possibly due to familiarity, participants reported four-color design as their favorite design, which also resulted in the fastest recognition of probability levels on both backgrounds. Our study shows the importance of using intuitive color-coding and sufficient contrast in conveying probabilistic threat information via graphical design. We also found that users follows a rational perceiving-judging-feeling-and acting approach in processing probabilistic hazard information for tornado. Copyright © 2017 Elsevier Ltd. All rights reserved.

From cyclone tracks to the costs of European winter storms: A probabilistic loss assessment model

NASA Astrophysics Data System (ADS)

Renggli, Dominik; Corti, Thierry; Reese, Stefan; Wueest, Marc; Viktor, Elisabeth; Zimmerli, Peter

2014-05-01

The quantitative assessment of the potential losses of European winter storms is essential for the economic viability of a global reinsurance company. For this purpose, reinsurance companies generally use probabilistic loss assessment models. This work presents an innovative approach to develop physically meaningful probabilistic events for Swiss Re's new European winter storm loss model. The meteorological hazard component of the new model is based on cyclone and windstorm tracks identified in the 20th Century Reanalysis data. The knowledge of the evolution of winter storms both in time and space allows the physically meaningful perturbation of properties of historical events (e.g. track, intensity). The perturbation includes a random element but also takes the local climatology and the evolution of the historical event into account. The low-resolution wind footprints taken from 20th Century Reanalysis are processed by a statistical-dynamical downscaling to generate high-resolution footprints of the historical and probabilistic winter storm events. Downscaling transfer functions are generated using ENSEMBLES regional climate model data. The result is a set of reliable probabilistic events representing thousands of years. The event set is then combined with country- and risk-specific vulnerability functions and detailed market- or client-specific exposure information to compute (re-)insurance risk premiums.

Understanding Feedback: A Learning Theory Perspective

ERIC Educational Resources Information Center

Thurlings, Marieke; Vermeulen, Marjan; Bastiaens, Theo; Stijnen, Sjef

2013-01-01

This article aims to review literature on feedback to teachers. Because research has hardly focused on feedback among teachers, the review's scope also includes feedback in classrooms. The review proposes that the effectiveness of feedback and feedback processes depend on the learning theory adhered to. Findings show that regardless of the…

Look who's judging-Feedback source modulates brain activation to performance feedback in social anxiety.

PubMed

Peterburs, Jutta; Sandrock, Carolin; Miltner, Wolfgang H R; Straube, Thomas

2016-06-01

It is as yet unknown if behavioral and neural correlates of performance monitoring in socially anxious individuals are affected by whether feedback is provided by a person or a computer. This fMRI study investigated modulation of feedback processing by feedback source (person vs. computer) in participants with high (HSA) (N=16) and low social anxiety (LSA) (N=16). Subjects performed a choice task in which they were informed that they would receive positive or negative feedback from a person or the computer. Subjective ratings indicated increased arousal and anxiety in HSA versus LSA, most pronounced for social and negative feedback. FMRI analyses yielded hyperactivation in ventral medial prefrontal cortex (vmPFC)/anterior cingulate cortex (ACC) and insula for social relative to computer feedback, and in mPFC/ventral ACC for positive relative to negative feedback in HSA as compared to LSA. These activation patterns are consistent with increased interoception and self-referential processing in social anxiety, especially during processing of positive feedback. Increased ACC activation in HSA to positive feedback may link to unexpectedness of (social) praise as posited in social anxiety disorder (SAD) psychopathology. Activation in rostral ACC showed a reversed pattern, with decreased activation to positive feedback in HSA, possibly indicating altered action values depending on feedback source and valence. The present findings corroborate a crucial role of mPFC for performance monitoring in social anxiety. Copyright © 2016 Elsevier Inc. All rights reserved.

Attenuation of dopamine-modulated prefrontal value signals underlies probabilistic reward learning deficits in old age

PubMed Central

Axelsson, Jan; Riklund, Katrine; Nyberg, Lars; Dayan, Peter; Bäckman, Lars

2017-01-01

Probabilistic reward learning is characterised by individual differences that become acute in aging. This may be due to age-related dopamine (DA) decline affecting neural processing in striatum, prefrontal cortex, or both. We examined this by administering a probabilistic reward learning task to younger and older adults, and combining computational modelling of behaviour, fMRI and PET measurements of DA D1 availability. We found that anticipatory value signals in ventromedial prefrontal cortex (vmPFC) were attenuated in older adults. The strength of this signal predicted performance beyond age and was modulated by D1 availability in nucleus accumbens. These results uncover that a value-anticipation mechanism in vmPFC declines in aging, and that this mechanism is associated with DA D1 receptor availability. PMID:28870286

Do Losses Loom Larger for Children than Adults?

PubMed Central

Luking, Katherine R.; Pagliaccio, David; Luby, Joan L.; Barch, Deanna M.

2015-01-01

The large impact of loss of reward on behavior has been well documented in adult populations. However, whether responsiveness to loss relative to gain is similarly elevated in child versus adult populations remains unclear. It is also unclear whether relations between incentive behaviors and self-reported reward/punishment sensitivity are similar within different developmental stages. To investigate these questions, 7–10-year-old children (N=70) and young adults (N=70) completed the Behavioral Inhibition System/Behavioral Activation System (BIS/BAS) Scale, along with two probabilistic incentive tasks assessing gain approach and loss avoidance behavior. BIS/BAS subscales were calculated per Pagliaccio, Luking et al. 2015, which established an age invariant model of the BIS/BAS. Bias towards responses more frequently followed by gain feedback and away from responses more frequently followed by loss feedback, approach and avoidance behavior respectively, were quantified via signal detection statistics. Gain approach behavior did not differ across age groups, however children exhibited significantly elevated loss avoidance relative to adults. Children also showed greater reductions in accuracy and slower reaction times specifically following loss feedback relative to adults. Interestingly, despite age group differences in loss avoidance behavior, relations between self-report measures and approach/avoidance behaviors were similar across age groups. Participants reporting elevated motivation (BAS Drive) showed both elevated gain approach and elevated loss avoidance, with both types of behavior predicting unique variance in BAS Drive. Results highlight the often-neglected developmental and motivational roles of responsiveness to loss of reward. PMID:26524484

Frontal Theta Links Prediction Errors to Behavioral Adaptation in Reinforcement Learning

PubMed Central

Cavanagh, James F.; Frank, Michael J.; Klein, Theresa J.; Allen, John J.B.

2009-01-01

Investigations into action monitoring have consistently detailed a fronto-central voltage deflection in the Event-Related Potential (ERP) following the presentation of negatively valenced feedback, sometimes termed the Feedback Related Negativity (FRN). The FRN has been proposed to reflect a neural response to prediction errors during reinforcement learning, yet the single trial relationship between neural activity and the quanta of expectation violation remains untested. Although ERP methods are not well suited to single trial analyses, the FRN has been associated with theta band oscillatory perturbations in the medial prefrontal cortex. Medio-frontal theta oscillations have been previously associated with expectation violation and behavioral adaptation and are well suited to single trial analysis. Here, we recorded EEG activity during a probabilistic reinforcement learning task and fit the performance data to an abstract computational model (Q-learning) for calculation of single-trial reward prediction errors. Single-trial theta oscillatory activities following feedback were investigated within the context of expectation (prediction error) and adaptation (subsequent reaction time change). Results indicate that interactive medial and lateral frontal theta activities reflect the degree of negative and positive reward prediction error in the service of behavioral adaptation. These different brain areas use prediction error calculations for different behavioral adaptations: with medial frontal theta reflecting the utilization of prediction errors for reaction time slowing (specifically following errors), but lateral frontal theta reflecting prediction errors leading to working memory-related reaction time speeding for the correct choice. PMID:19969093

Deterministic entanglement of superconducting qubits by parity measurement and feedback.

PubMed

Ristè, D; Dukalski, M; Watson, C A; de Lange, G; Tiggelman, M J; Blanter, Ya M; Lehnert, K W; Schouten, R N; DiCarlo, L

2013-10-17

The stochastic evolution of quantum systems during measurement is arguably the most enigmatic feature of quantum mechanics. Measuring a quantum system typically steers it towards a classical state, destroying the coherence of an initial quantum superposition and the entanglement with other quantum systems. Remarkably, the measurement of a shared property between non-interacting quantum systems can generate entanglement, starting from an uncorrelated state. Of special interest in quantum computing is the parity measurement, which projects the state of multiple qubits (quantum bits) to a state with an even or odd number of excited qubits. A parity meter must discern the two qubit-excitation parities with high fidelity while preserving coherence between same-parity states. Despite numerous proposals for atomic, semiconducting and superconducting qubits, realizing a parity meter that creates entanglement for both even and odd measurement results has remained an outstanding challenge. Here we perform a time-resolved, continuous parity measurement of two superconducting qubits using the cavity in a three-dimensional circuit quantum electrodynamics architecture and phase-sensitive parametric amplification. Using postselection, we produce entanglement by parity measurement reaching 88 per cent fidelity to the closest Bell state. Incorporating the parity meter in a feedback-control loop, we transform the entanglement generation from probabilistic to fully deterministic, achieving 66 per cent fidelity to a target Bell state on demand. These realizations of a parity meter and a feedback-enabled deterministic measurement protocol provide key ingredients for active quantum error correction in the solid state.

The effects of outcome and process feedback

NASA Technical Reports Server (NTRS)

Johnson, Debra Steele

1990-01-01

A study was conducted to examine the effects of process and outcome feedback on performance during a skill acquisition phase and a transfer test phase. The research also examined the role of two moderators: self-efficacy and intrinsic motivation. Subjects were college students participating for course credit. The task involved using a computerized simulation of the Space Shuttle's Remote Manipulation System (RMS). Results provided evidence of the beneficial effects of process feedback during skill acquisition. Results also provided evidence that self-efficacy and intrinsic motivation moderate the effects of feedback type on performance.

Stochastic model for fatigue crack size and cost effective design decisions. [for aerospace structures

NASA Technical Reports Server (NTRS)

Hanagud, S.; Uppaluri, B.

1975-01-01

This paper describes a methodology for making cost effective fatigue design decisions. The methodology is based on a probabilistic model for the stochastic process of fatigue crack growth with time. The development of a particular model for the stochastic process is also discussed in the paper. The model is based on the assumption of continuous time and discrete space of crack lengths. Statistical decision theory and the developed probabilistic model are used to develop the procedure for making fatigue design decisions on the basis of minimum expected cost or risk function and reliability bounds. Selections of initial flaw size distribution, NDT, repair threshold crack lengths, and inspection intervals are discussed.

The Processing of Extraposed Structures in English

PubMed Central

Levy, Roger; Fedorenko, Evelina; Breen, Mara; Gibson, Ted

2012-01-01

In most languages, most of the syntactic dependency relations found in any given sentence are PROJECTIVE: the word-word dependencies in the sentence do not cross each other. Some syntactic dependency relations, however, are NON-PROJECTIVE: some of their word-word dependencies cross each other. Non-projective dependencies are both rarer and more computationally complex than projective dependencies; hence, it is of natural interest to investigate whether there are any processing costs specific to non-projective dependencies, and whether factors known to influence processing of projective dependencies also affect non-projective dependency processing. We report three self-paced reading studies, together with corpus and sentence completion studies, investigating the comprehension difficulty associated with the non-projective dependencies created by the extraposition of relative clauses in English. We find that extraposition over either verbs or prepositional phrases creates comprehension difficulty, and that this difficulty is consistent with probabilistic syntactic expectations estimated from corpora. Furthermore, we find that manipulating the expectation that a given noun will have a postmodifying relative clause can modulate and even neutralize the difficulty associated with extraposition. Our experiments rule out accounts based purely on derivational complexity and/or dependency locality in terms of linear positioning. Our results demonstrate that comprehenders maintain probabilistic syntactic expectations that persist beyond projective-dependency structures, and suggest that it may be possible to explain observed patterns of comprehension difficulty associated with extraposition entirely through probabilistic expectations. PMID:22035959

Probabilistic Cloning of Three Real States with Optimal Success Probabilities

NASA Astrophysics Data System (ADS)

Rui, Pin-shu

2017-06-01

We investigate the probabilistic quantum cloning (PQC) of three real states with average probability distribution. To get the analytic forms of the optimal success probabilities we assume that the three states have only two pairwise inner products. Based on the optimal success probabilities, we derive the explicit form of 1 →2 PQC for cloning three real states. The unitary operation needed in the PQC process is worked out too. The optimal success probabilities are also generalized to the M→ N PQC case.

Probabilistic teleportation without loss of information

NASA Astrophysics Data System (ADS)

Roa, Luis; Groiseau, Caspar

2015-01-01

We found a scheme for teleporting probabilistically an unknown pure state with optimal probability and without losing the information of the state to be teleported. Accordingly, without having to have copies of the unknown state, the teleportation process can be repeated as many times as one has available quantum channels. Thus, although the quantum channels have a weak entanglement, teleportation is achievable with a high number of repetitions, whereas for channels with strong entanglement only a small number of repetitions are required to guarantee successful teleportation.

Costing the satellite power system

NASA Technical Reports Server (NTRS)

Hazelrigg, G. A., Jr.

1978-01-01

The paper presents a methodology for satellite power system costing, places approximate limits on the accuracy possible in cost estimates made at this time, and outlines the use of probabilistic cost information in support of the decision-making process. Reasons for using probabilistic costing or risk analysis procedures instead of standard deterministic costing procedures are considered. Components of cost, costing estimating relationships, grass roots costing, and risk analysis are discussed. Risk analysis using a Monte Carlo simulation model is used to estimate future costs.

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association

PubMed Central

Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-01-01

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets’ state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems. PMID:29113085

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association.

PubMed

Liu, Yu; Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-11-05

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets' state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems.

Probabilistic framework for product design optimization and risk management

NASA Astrophysics Data System (ADS)

Keski-Rahkonen, J. K.

2018-05-01

Probabilistic methods have gradually gained ground within engineering practices but currently it is still the industry standard to use deterministic safety margin approaches to dimensioning components and qualitative methods to manage product risks. These methods are suitable for baseline design work but quantitative risk management and product reliability optimization require more advanced predictive approaches. Ample research has been published on how to predict failure probabilities for mechanical components and furthermore to optimize reliability through life cycle cost analysis. This paper reviews the literature for existing methods and tries to harness their best features and simplify the process to be applicable in practical engineering work. Recommended process applies Monte Carlo method on top of load-resistance models to estimate failure probabilities. Furthermore, it adds on existing literature by introducing a practical framework to use probabilistic models in quantitative risk management and product life cycle costs optimization. The main focus is on mechanical failure modes due to the well-developed methods used to predict these types of failures. However, the same framework can be applied on any type of failure mode as long as predictive models can be developed.

The role of feedback information for calibration and attunement in perceiving length by dynamic touch.

PubMed

Withagen, Rob; Michaels, Claire F

2005-12-01

Two processes have been hypothesized to underlie improvement in perception: attunement and calibration. These processes were examined in a dynamic touch paradigm in which participants were asked to report the lengths of unseen, wielded rods differing in length, diameter, and material. Two experiments addressed whether feedback informs about the need for reattunement and recalibration. Feedback indicating actual length induced both recalibration and reattunement. Recalibration did not occur when feedback indicated only whether 2 rods were of the same length or of different lengths. Such feedback, however, did induce reattunement. These results suggest that attunement and calibration are dissociable processes and that feedback informs which is needed. The observed change in variable use has implications also for research on what mechanical variables underlie length perception by dynamic touch. (c) 2005 APA, all rights reserved.

Overview of the SAE G-11 RMSL (Reliability, Maintainability, Supportability, and Logistics) Division Activities and Technical Projects

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.

2003-01-01

The SAE G-11 RMSL (Reliability, Maintainability, Supportability, and Logistics) Division activities include identification and fulfillment of joint industry, government, and academia needs for development and implementation of RMSL technologies. Four Projects in the Probabilistic Methods area and two in the area of RMSL have been identified. These are: (1) Evaluation of Probabilistic Technology - progress has been made toward the selection of probabilistic application cases. Future effort will focus on assessment of multiple probabilistic softwares in solving selected engineering problems using probabilistic methods. Relevance to Industry & Government - Case studies of typical problems encountering uncertainties, results of solutions to these problems run by different codes, and recommendations on which code is applicable for what problems; (2) Probabilistic Input Preparation - progress has been made in identifying problem cases such as those with no data, little data and sufficient data. Future effort will focus on developing guidelines for preparing input for probabilistic analysis, especially with no or little data. Relevance to Industry & Government - Too often, we get bogged down thinking we need a lot of data before we can quantify uncertainties. Not True. There are ways to do credible probabilistic analysis with little data; (3) Probabilistic Reliability - probabilistic reliability literature search has been completed along with what differentiates it from statistical reliability. Work on computation of reliability based on quantification of uncertainties in primitive variables is in progress. Relevance to Industry & Government - Correct reliability computations both at the component and system level are needed so one can design an item based on its expected usage and life span; (4) Real World Applications of Probabilistic Methods (PM) - A draft of volume 1 comprising aerospace applications has been released. Volume 2, a compilation of real world applications of probabilistic methods with essential information demonstrating application type and timehost savings by the use of probabilistic methods for generic applications is in progress. Relevance to Industry & Government - Too often, we say, 'The Proof is in the Pudding'. With help from many contributors, we hope to produce such a document. Problem is - not too many people are coming forward due to proprietary nature. So, we are asking to document only minimum information including problem description, what method used, did it result in any savings, and how much?; (5) Software Reliability - software reliability concept, program, implementation, guidelines, and standards are being documented. Relevance to Industry & Government - software reliability is a complex issue that must be understood & addressed in all facets of business in industry, government, and other institutions. We address issues, concepts, ways to implement solutions, and guidelines for maximizing software reliability; (6) Maintainability Standards - maintainability/serviceability industry standard/guidelines and industry best practices and methodologies used in performing maintainability/ serviceability tasks are being documented. Relevance to Industry & Government - Any industry or government process, project, and/or tool must be maintained and serviced to realize the life and performance it was designed for. We address issues and develop guidelines for optimum performance & life.

Monitoring and control of amygdala neurofeedback involves distributed information processing in the human brain.

PubMed

Paret, Christian; Zähringer, Jenny; Ruf, Matthias; Gerchen, Martin Fungisai; Mall, Stephanie; Hendler, Talma; Schmahl, Christian; Ende, Gabriele

2018-03-30

Brain-computer interfaces provide conscious access to neural activity by means of brain-derived feedback ("neurofeedback"). An individual's abilities to monitor and control feedback are two necessary processes for effective neurofeedback therapy, yet their underlying functional neuroanatomy is still being debated. In this study, healthy subjects received visual feedback from their amygdala response to negative pictures. Activation and functional connectivity were analyzed to disentangle the role of brain regions in different processes. Feedback monitoring was mapped to the thalamus, ventromedial prefrontal cortex (vmPFC), ventral striatum (VS), and rostral PFC. The VS responded to feedback corresponding to instructions while rPFC activity differentiated between conditions and predicted amygdala regulation. Control involved the lateral PFC, anterior cingulate, and insula. Monitoring and control activity overlapped in the VS and thalamus. Extending current neural models of neurofeedback, this study introduces monitoring and control of feedback as anatomically dissociated processes, and suggests their important role in voluntary neuromodulation. © 2018 Wiley Periodicals, Inc.

The Nature of Feedback: How Peer Feedback Features Affect Students' Implementation Rate and Quality of Revisions

ERIC Educational Resources Information Center

Patchan, Melissa M.; Schunn, Christian D.; Correnti, Richard J.

2016-01-01

Although feedback is often seen as a critical component of the learning process, many open questions about how specific feedback features contribute to the effectiveness of feedback remain--especially in regards to peer feedback of writing. Nelson and Schunn (2009) identified several important features of peer feedback in their nature of feedback…

Feedback: an essential element of student learning in clinical practice.

PubMed

Clynes, Mary P; Raftery, Sara E C

2008-11-01

Clinical practice is an essential component of the nursing curriculum. In order for the student to benefit fully from the experience regular performance feedback is required. Feedback should provide the student with information on current practice and offer practical advice for improved performance. The importance of feedback is widely acknowledged however it appears that there is inconsistency in its provision to students. The benefits of feedback include increased student confidence, motivation and self-esteem as well as improved clinical practice. Benefits such as enhanced interpersonal skills and a sense of personal satisfaction also accrue to the supervisor. Barriers to the feedback process are identified as inadequate supervisor training and education, unfavourable ward learning environment and insufficient time spent with students. In addition to the appropriate preparation of the supervisor effective feedback includes an appreciation of the steps of the feedback process, an understanding of the student response to feedback and effective communication skills.

Tradeoff methods in multiobjective insensitive design of airplane control systems

NASA Technical Reports Server (NTRS)

Schy, A. A.; Giesy, D. P.

1984-01-01

The latest results of an ongoing study of computer-aided design of airplane control systems are given. Constrained minimization algorithms are used, with the design objectives in the constraint vector. The concept of Pareto optimiality is briefly reviewed. It is shown how an experienced designer can use it to find designs which are well-balanced in all objectives. Then the problem of finding designs which are insensitive to uncertainty in system parameters are discussed, introducing a probabilistic vector definition of sensitivity which is consistent with the deterministic Pareto optimal problem. Insensitivity is important in any practical design, but it is particularly important in the design of feedback control systems, since it is considered to be the most important distinctive property of feedback control. Methods of tradeoff between deterministic and stochastic-insensitive (SI) design are described, and tradeoff design results are presented for the example of the a Shuttle lateral stability augmentation system. This example is used because careful studies have been made of the uncertainty in Shuttle aerodynamics. Finally, since accurate statistics of uncertain parameters are usually not available, the effects of crude statistical models on SI designs are examined.

Frontostriatal anatomical connections predict age- and difficulty-related differences in reinforcement learning.

PubMed

van de Vijver, Irene; Ridderinkhof, K Richard; Harsay, Helga; Reneman, Liesbeth; Cavanagh, James F; Buitenweg, Jessika I V; Cohen, Michael X

2016-10-01

Reinforcement learning (RL) is supported by a network of striatal and frontal cortical structures that are connected through white-matter fiber bundles. With age, the integrity of these white-matter connections declines. The role of structural frontostriatal connectivity in individual and age-related differences in RL is unclear, although local white-matter density and diffusivity have been linked to individual differences in RL. Here we show that frontostriatal tract counts in young human adults (aged 18-28), as assessed noninvasively with diffusion-weighted magnetic resonance imaging and probabilistic tractography, positively predicted individual differences in RL when learning was difficult (70% valid feedback). In older adults (aged 63-87), in contrast, learning under both easy (90% valid feedback) and difficult conditions was predicted by tract counts in the same frontostriatal network. Furthermore, network-level analyses showed a double dissociation between the task-relevant networks in young and older adults, suggesting that older adults relied on different frontostriatal networks than young adults to obtain the same task performance. These results highlight the importance of successful information integration across striatal and frontal regions during RL, especially with variable outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Motivational Beliefs, Student Effort, and Feedback Behaviour in Computer-Based Formative Assessment

ERIC Educational Resources Information Center

Timmers, Caroline F.; Braber-van den Broek, Jannie; van den Berg, Stephanie M.

2013-01-01

Feedback can only be effective when students seek feedback and process it. This study examines the relations between students' motivational beliefs, effort invested in a computer-based formative assessment, and feedback behaviour. Feedback behaviour is represented by whether a student seeks feedback and the time a student spends studying the…

Ambient Persuasive Technology Needs Little Cognitive Effort: The Differential Effects of Cognitive Load on Lighting Feedback versus Factual Feedback

NASA Astrophysics Data System (ADS)

Ham, Jaap; Midden, Cees

Persuasive technology can influence behavior or attitudes by for example providing interactive factual feedback about energy conservation. However, people often lack motivation or cognitive capacity to consciously process such relative complex information (e.g., numerical consumption feedback). Extending recent research that indicates that ambient persuasive technology can persuade the user without receiving the user's conscious attention, we argue here that Ambient Persuasive Technology can be effective while needing only little cognitive resources, and in general can be more influential than more focal forms of persuasive technology. In an experimental study, some participants received energy consumption feedback by means of a light changing color (more green=lower energy consumption, vs. more red=higher energy consumption) and others by means of numbers indicating kWh consumption. Results indicated that ambient feedback led to more conservation than factual feedback. Also, as expected, only for participants processing factual feedback, additional cognitive load lead to slower processing of that feedback. This research sheds light on fundamental characteristics of Ambient Persuasive Technology and Persuasive Lighting, and suggests that it can have important advantages over more focal persuasive technologies without losing its persuasive potential.

Effects of Intrinsic Motivation on Feedback Processing During Learning

PubMed Central

DePasque, Samantha; Tricomi, Elizabeth

2015-01-01

Learning commonly requires feedback about the consequences of one’s actions, which can drive learners to modify their behavior. Motivation may determine how sensitive an individual might be to such feedback, particularly in educational contexts where some students value academic achievement more than others. Thus, motivation for a task might influence the value placed on performance feedback and how effectively it is used to improve learning. To investigate the interplay between intrinsic motivation and feedback processing, we used functional magnetic resonance imaging (fMRI) during feedback-based learning before and after a novel manipulation based on motivational interviewing, a technique for enhancing treatment motivation in mental health settings. Because of its role in the reinforcement learning system, the striatum is situated to play a significant role in the modulation of learning based on motivation. Consistent with this idea, motivation levels during the task were associated with sensitivity to positive versus negative feedback in the striatum. Additionally, heightened motivation following a brief motivational interview was associated with increases in feedback sensitivity in the left medial temporal lobe. Our results suggest that motivation modulates neural responses to performance-related feedback, and furthermore that changes in motivation facilitates processing in areas that support learning and memory. PMID:26112370

Delayed excitatory and inhibitory feedback shape neural information transmission

NASA Astrophysics Data System (ADS)

Chacron, Maurice J.; Longtin, André; Maler, Leonard

2005-11-01

Feedback circuitry with conduction and synaptic delays is ubiquitous in the nervous system. Yet the effects of delayed feedback on sensory processing of natural signals are poorly understood. This study explores the consequences of delayed excitatory and inhibitory feedback inputs on the processing of sensory information. We show, through numerical simulations and theory, that excitatory and inhibitory feedback can alter the firing frequency response of stochastic neurons in opposite ways by creating dynamical resonances, which in turn lead to information resonances (i.e., increased information transfer for specific ranges of input frequencies). The resonances are created at the expense of decreased information transfer in other frequency ranges. Using linear response theory for stochastically firing neurons, we explain how feedback signals shape the neural transfer function for a single neuron as a function of network size. We also find that balanced excitatory and inhibitory feedback can further enhance information tuning while maintaining a constant mean firing rate. Finally, we apply this theory to in vivo experimental data from weakly electric fish in which the feedback loop can be opened. We show that it qualitatively predicts the observed effects of inhibitory feedback. Our study of feedback excitation and inhibition reveals a possible mechanism by which optimal processing may be achieved over selected frequency ranges.

Fear of negative evaluation modulates electrocortical and behavioral responses when anticipating social evaluative feedback.

PubMed

Van der Molen, Melle J W; Poppelaars, Eefje S; Van Hartingsveldt, Caroline T A; Harrewijn, Anita; Gunther Moor, Bregtje; Westenberg, P Michiel

2013-01-01

Cognitive models posit that the fear of negative evaluation (FNE) is a hallmark feature of social anxiety. As such, individuals with high FNE may show biased information processing when faced with social evaluation. The aim of the current study was to examine the neural underpinnings of anticipating and processing social-evaluative feedback, and its correlates with FNE. We used a social judgment paradigm in which female participants (N = 31) were asked to indicate whether they believed to be socially accepted or rejected by their peers. Anticipatory attention was indexed by the stimulus preceding negativity (SPN), while the feedback-related negativity and P3 were used to index the processing of social-evaluative feedback. Results provided evidence of an optimism bias in social peer evaluation, as participants more often predicted to be socially accepted than rejected. Participants with high levels of FNE needed more time to provide their judgments about the social-evaluative outcome. While anticipating social-evaluative feedback, SPN amplitudes were larger for anticipated social acceptance than for social rejection feedback. Interestingly, the SPN during anticipated social acceptance was larger in participants with high levels of FNE. None of the feedback-related brain potentials correlated with the FNE. Together, the results provided evidence of biased information processing in individuals with high levels of FNE when anticipating (rather than processing) social-evaluative feedback. The delayed response times in high FNE individuals were interpreted to reflect augmented vigilance imposed by the upcoming social-evaluative threat. Possibly, the SPN constitutes a neural marker of this vigilance in females with higher FNE levels, particularly when anticipating social acceptance feedback.

Probabilistic Weather Information Tailored to the Needs of Transmission System Operators

NASA Astrophysics Data System (ADS)

Alberts, I.; Stauch, V.; Lee, D.; Hagedorn, R.

2014-12-01

Reliable and accurate forecasts for wind and photovoltaic (PV) power production are essential for stable transmission systems. A high potential for improving the wind and PV power forecasts lies in optimizing the weather forecasts, since these energy sources are highly weather dependent. For this reason the main objective of the German research project EWeLiNE is to improve the quality the underlying numerical weather predictions towards energy operations. In this project, the German Meteorological Service (DWD), the Fraunhofer Institute for Wind Energy and Energy System Technology, and three of the German transmission system operators (TSOs) are working together to improve the weather and power forecasts. Probabilistic predictions are of particular interest, as the quantification of uncertainties provides an important tool for risk management. Theoretical considerations suggest that it can be advantageous to use probabilistic information to represent and respond to the remaining uncertainties in the forecasts. However, it remains a challenge to integrate this information into the decision making processes related to market participation and power systems operations. The project is planned and carried out in close cooperation with the involved TSOs in order to ensure the usability of the products developed. It will conclude with a demonstration phase, in which the improved models and newly developed products are combined into a process chain and used to provide information to TSOs in a real-time decision support tool. The use of a web-based development platform enables short development cycles and agile adaptation to evolving user needs. This contribution will present the EWeLiNE project and discuss ideas on how to incorporate probabilistic information into the users' current decision making processes.

Interference Alignment With Partial CSI Feedback in MIMO Cellular Networks

NASA Astrophysics Data System (ADS)

Rao, Xiongbin; Lau, Vincent K. N.

2014-04-01

Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. However, most existing IA designs require full channel state information (CSI) at the transmitters, which would lead to significant CSI signaling overhead. There are two techniques, namely CSI quantization and CSI feedback filtering, to reduce the CSI feedback overhead. In this paper, we consider IA processing with CSI feedback filtering in MIMO cellular networks. We introduce a novel metric, namely the feedback dimension, to quantify the first order CSI feedback cost associated with the CSI feedback filtering. The CSI feedback filtering poses several important challenges in IA processing. First, there is a hidden partial CSI knowledge constraint in IA precoder design which cannot be handled using conventional IA design methodology. Furthermore, existing results on the feasibility conditions of IA cannot be applied due to the partial CSI knowledge. Finally, it is very challenging to find out how much CSI feedback is actually needed to support IA processing. We shall address the above challenges and propose a new IA feasibility condition under partial CSIT knowledge in MIMO cellular networks. Based on this, we consider the CSI feedback profile design subject to the degrees of freedom requirements, and we derive closed-form trade-off results between the CSI feedback cost and IA performance in MIMO cellular networks.

Feedback Specificity, Information Processing, and Transfer of Training

ERIC Educational Resources Information Center

Goodman, Jodi S.; Wood, Robert E.; Chen, Zheng

2011-01-01

This study examines the effects of feedback specificity on transfer of training and the mechanisms through which feedback can enhance or inhibit transfer. We used concurrent verbal protocol methodology to elicit and operationalize the explicit information processing activities used by 48 trainees performing the Furniture Factory computer…

Utilizing time-frequency amplitude and phase synchrony measure to assess feedback processing in a gambling task.

PubMed

Watts, Adreanna T M; Tootell, Anne V; Fix, Spencer T; Aviyente, Selin; Bernat, Edward M

2018-04-29

The neurophysiological mechanisms involved in the evaluation of performance feedback have been widely studied in the ERP literature over the past twenty years, but understanding has been limited by the use of traditional time-domain amplitude analytic approaches. Gambling outcome valence has been identified as an important factor modulating event-related potential (ERP) components, most notably the feedback negativity (FN). Recent work employing time-frequency analysis has shown that processes indexed by the FN are confounded in the time-domain and can be better represented as separable feedback-related processes in the theta (3-7 Hz) and delta (0-3 Hz) frequency bands. In addition to time-frequency amplitude analysis, phase synchrony measures have begun to further our understanding of performance evaluation by revealing how feedback information is processed within and between various brain regions. The current study aimed to provide an integrative assessment of time-frequency amplitude, inter-trial phase synchrony, and inter-channel phase synchrony changes following monetary feedback in a gambling task. Results revealed that time-frequency amplitude activity explained separable loss and gain processes confounded in the time-domain. Furthermore, phase synchrony measures explained unique variance above and beyond amplitude measures and demonstrated enhanced functional integration between medial prefrontal and bilateral frontal, motor, and occipital regions for loss relative to gain feedback. These findings demonstrate the utility of assessing time-frequency amplitude, inter-trial phase synchrony, and inter-channel phase synchrony together to better elucidate the neurophysiology of feedback processing. Copyright © 2017. Published by Elsevier B.V.

Left-hemisphere activation is associated with enhanced vocal pitch error detection in musicians with absolute pitch

PubMed Central

Behroozmand, Roozbeh; Ibrahim, Nadine; Korzyukov, Oleg; Robin, Donald A.; Larson, Charles R.

2014-01-01

The ability to process auditory feedback for vocal pitch control is crucial during speaking and singing. Previous studies have suggested that musicians with absolute pitch (AP) develop specialized left-hemisphere mechanisms for pitch processing. The present study adopted an auditory feedback pitch perturbation paradigm combined with ERP recordings to test the hypothesis whether the neural mechanisms of the left-hemisphere enhance vocal pitch error detection and control in AP musicians compared with relative pitch (RP) musicians and non-musicians (NM). Results showed a stronger N1 response to pitch-shifted voice feedback in the right-hemisphere for both AP and RP musicians compared with the NM group. However, the left-hemisphere P2 component activation was greater in AP and RP musicians compared with NMs and also for the AP compared with RP musicians. The NM group was slower in generating compensatory vocal reactions to feedback pitch perturbation compared with musicians, and they failed to re-adjust their vocal pitch after the feedback perturbation was removed. These findings suggest that in the earlier stages of cortical neural processing, the right hemisphere is more active in musicians for detecting pitch changes in voice feedback. In the later stages, the left-hemisphere is more active during the processing of auditory feedback for vocal motor control and seems to involve specialized mechanisms that facilitate pitch processing in the AP compared with RP musicians. These findings indicate that the left hemisphere mechanisms of AP ability are associated with improved auditory feedback pitch processing during vocal pitch control in tasks such as speaking or singing. PMID:24355545

PubMed related articles: a probabilistic topic-based model for content similarity

PubMed Central

Lin, Jimmy; Wilbur, W John

2007-01-01

Background We present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document is about a particular topic is computed from term frequencies, modeled as Poisson distributions. Unlike previous probabilistic retrieval models, we do not attempt to estimate relevance–but rather our focus is "relatedness", the probability that a user would want to examine a particular document given known interest in another. We also describe a novel technique for estimating parameters that does not require human relevance judgments; instead, the process is based on the existence of MeSH ® in MEDLINE ®. Results The pmra retrieval model was compared against bm25, a competitive probabilistic model that shares theoretical similarities. Experiments using the test collection from the TREC 2005 genomics track shows a small but statistically significant improvement of pmra over bm25 in terms of precision. Conclusion Our experiments suggest that the pmra model provides an effective ranking algorithm for related article search. PMID:17971238

Discounting of Monetary Rewards that are Both Delayed and Probabilistic: Delay and Probability Combine Multiplicatively, not Additively

PubMed Central

Vanderveldt, Ariana; Green, Leonard; Myerson, Joel

2014-01-01

The value of an outcome is affected both by the delay until its receipt (delay discounting) and by the likelihood of its receipt (probability discounting). Despite being well-described by the same hyperboloid function, delay and probability discounting involve fundamentally different processes, as revealed, for example, by the differential effects of reward amount. Previous research has focused on the discounting of delayed and probabilistic rewards separately, with little research examining more complex situations in which rewards are both delayed and probabilistic. In two experiments, participants made choices between smaller rewards that were both immediate and certain and larger rewards that were both delayed and probabilistic. Analyses revealed significant interactions between delay and probability factors inconsistent with an additive model. In contrast, a hyperboloid discounting model in which delay and probability were combined multiplicatively provided an excellent fit to the data. These results suggest that the hyperboloid is a good descriptor of decision making in complicated monetary choice situations like those people encounter in everyday life. PMID:24933696

Probabilistic Approach to Enable Extreme-Scale Simulations under Uncertainty and System Faults. Final Technical Report

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

Knio, Omar

2017-05-05

The current project develops a novel approach that uses a probabilistic description to capture the current state of knowledge about the computational solution. To effectively spread the computational effort over multiple nodes, the global computational domain is split into many subdomains. Computational uncertainty in the solution translates into uncertain boundary conditions for the equation system to be solved on those subdomains, and many independent, concurrent subdomain simulations are used to account for this bound- ary condition uncertainty. By relying on the fact that solutions on neighboring subdomains must agree with each other, a more accurate estimate for the global solutionmore » can be achieved. Statistical approaches in this update process make it possible to account for the effect of system faults in the probabilistic description of the computational solution, and the associated uncertainty is reduced through successive iterations. By combining all of these elements, the probabilistic reformulation allows splitting the computational work over very many independent tasks for good scalability, while being robust to system faults.« less

Probabilistic inversion of expert assessments to inform projections about Antarctic ice sheet responses.

PubMed

Fuller, Robert William; Wong, Tony E; Keller, Klaus

2017-01-01

The response of the Antarctic ice sheet (AIS) to changing global temperatures is a key component of sea-level projections. Current projections of the AIS contribution to sea-level changes are deeply uncertain. This deep uncertainty stems, in part, from (i) the inability of current models to fully resolve key processes and scales, (ii) the relatively sparse available data, and (iii) divergent expert assessments. One promising approach to characterizing the deep uncertainty stemming from divergent expert assessments is to combine expert assessments, observations, and simple models by coupling probabilistic inversion and Bayesian inversion. Here, we present a proof-of-concept study that uses probabilistic inversion to fuse a simple AIS model and diverse expert assessments. We demonstrate the ability of probabilistic inversion to infer joint prior probability distributions of model parameters that are consistent with expert assessments. We then confront these inferred expert priors with instrumental and paleoclimatic observational data in a Bayesian inversion. These additional constraints yield tighter hindcasts and projections. We use this approach to quantify how the deep uncertainty surrounding expert assessments affects the joint probability distributions of model parameters and future projections.

Improving medium-range ensemble streamflow forecasts through statistical post-processing

NASA Astrophysics Data System (ADS)

Mendoza, Pablo; Wood, Andy; Clark, Elizabeth; Nijssen, Bart; Clark, Martyn; Ramos, Maria-Helena; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

Probabilistic hydrologic forecasts are a powerful source of information for decision-making in water resources operations. A common approach is the hydrologic model-based generation of streamflow forecast ensembles, which can be implemented to account for different sources of uncertainties - e.g., from initial hydrologic conditions (IHCs), weather forecasts, and hydrologic model structure and parameters. In practice, hydrologic ensemble forecasts typically have biases and spread errors stemming from errors in the aforementioned elements, resulting in a degradation of probabilistic properties. In this work, we compare several statistical post-processing techniques applied to medium-range ensemble streamflow forecasts obtained with the System for Hydromet Applications, Research and Prediction (SHARP). SHARP is a fully automated prediction system for the assessment and demonstration of short-term to seasonal streamflow forecasting applications, developed by the National Center for Atmospheric Research, University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation. The suite of post-processing techniques includes linear blending, quantile mapping, extended logistic regression, quantile regression, ensemble analogs, and the generalized linear model post-processor (GLMPP). We assess and compare these techniques using multi-year hindcasts in several river basins in the western US. This presentation discusses preliminary findings about the effectiveness of the techniques for improving probabilistic skill, reliability, discrimination, sharpness and resolution.

Technical report. The application of probability-generating functions to linear-quadratic radiation survival curves.

PubMed

Kendal, W S

2000-04-01

To illustrate how probability-generating functions (PGFs) can be employed to derive a simple probabilistic model for clonogenic survival after exposure to ionizing irradiation. Both repairable and irreparable radiation damage to DNA were assumed to occur by independent (Poisson) processes, at intensities proportional to the irradiation dose. Also, repairable damage was assumed to be either repaired or further (lethally) injured according to a third (Bernoulli) process, with the probability of lethal conversion being directly proportional to dose. Using the algebra of PGFs, these three processes were combined to yield a composite PGF that described the distribution of lethal DNA lesions in irradiated cells. The composite PGF characterized a Poisson distribution with mean, chiD+betaD2, where D was dose and alpha and beta were radiobiological constants. This distribution yielded the conventional linear-quadratic survival equation. To test the composite model, the derived distribution was used to predict the frequencies of multiple chromosomal aberrations in irradiated human lymphocytes. The predictions agreed well with observation. This probabilistic model was consistent with single-hit mechanisms, but it was not consistent with binary misrepair mechanisms. A stochastic model for radiation survival has been constructed from elementary PGFs that exactly yields the linear-quadratic relationship. This approach can be used to investigate other simple probabilistic survival models.

The Role of Working Memory in the Probabilistic Inference of Future Sensory Events.

PubMed

Cashdollar, Nathan; Ruhnau, Philipp; Weisz, Nathan; Hasson, Uri

2017-05-01

The ability to represent the emerging regularity of sensory information from the external environment has been thought to allow one to probabilistically infer future sensory occurrences and thus optimize behavior. However, the underlying neural implementation of this process is still not comprehensively understood. Through a convergence of behavioral and neurophysiological evidence, we establish that the probabilistic inference of future events is critically linked to people's ability to maintain the recent past in working memory. Magnetoencephalography recordings demonstrated that when visual stimuli occurring over an extended time series had a greater statistical regularity, individuals with higher working-memory capacity (WMC) displayed enhanced slow-wave neural oscillations in the θ frequency band (4-8 Hz.) prior to, but not during stimulus appearance. This prestimulus neural activity was specifically linked to contexts where information could be anticipated and influenced the preferential sensory processing for this visual information after its appearance. A separate behavioral study demonstrated that this process intrinsically emerges during continuous perception and underpins a realistic advantage for efficient behavioral responses. In this way, WMC optimizes the anticipation of higher level semantic concepts expected to occur in the near future. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Effective Instructor Feedback: Perceptions of Online Graduate Students

ERIC Educational Resources Information Center

Getzlaf, Beverley; Perry, Beth; Toffner, Greg; Lamarche, Kimberley; Edwards, Margaret

2009-01-01

This descriptive study explored online graduate students' perceptions of effective instructor feedback. The objectives of the study were to determine the students' perceptions of the content of effective instructor feedback ("what should be included in effective feedback?") and the process of effective instructor feedback ("how…

Maximizing the Value of 360-Degree Feedback: A Process for Successful Individual and Organizational Development.

ERIC Educational Resources Information Center

Tornow, Walter W.; London, Manuel

Ways in which organizations can enhance their use of "360-degree feedback" are presented. The book begins with a review of the process itself, emphasizing that 360-degree feedback should be a core element of self-development. The book is divided into three parts. Part 1 describes how to maximize the value of the process for individual…

Structuring the Peer Assessment Process: A Multilevel Approach for the Impact on Product Improvement and Peer Feedback Quality

ERIC Educational Resources Information Center

Gielen, M.; De Wever, B.

2015-01-01

In order to optimize students' peer feedback processes, this study investigates how an instructional intervention in the peer assessment process can have a beneficial effect on students' performance in a wiki environment in first-year higher education. The main aim was to study the effect of integrating a peer feedback template with a varying…

Mode identification using stochastic hybrid models with applications to conflict detection and resolution

NASA Astrophysics Data System (ADS)

Naseri Kouzehgarani, Asal

2009-12-01

Most models of aircraft trajectories are non-linear and stochastic in nature; and their internal parameters are often poorly defined. The ability to model, simulate and analyze realistic air traffic management conflict detection scenarios in a scalable, composable, multi-aircraft fashion is an extremely difficult endeavor. Accurate techniques for aircraft mode detection are critical in order to enable the precise projection of aircraft conflicts, and for the enactment of altitude separation resolution strategies. Conflict detection is an inherently probabilistic endeavor; our ability to detect conflicts in a timely and accurate manner over a fixed time horizon is traded off against the increased human workload created by false alarms---that is, situations that would not develop into an actual conflict, or would resolve naturally in the appropriate time horizon-thereby introducing a measure of probabilistic uncertainty in any decision aid fashioned to assist air traffic controllers. The interaction of the continuous dynamics of the aircraft, used for prediction purposes, with the discrete conflict detection logic gives rise to the hybrid nature of the overall system. The introduction of the probabilistic element, common to decision alerting and aiding devices, places the conflict detection and resolution problem in the domain of probabilistic hybrid phenomena. A hidden Markov model (HMM) has two stochastic components: a finite-state Markov chain and a finite set of output probability distributions. In other words an unobservable stochastic process (hidden) that can only be observed through another set of stochastic processes that generate the sequence of observations. The problem of self separation in distributed air traffic management reduces to the ability of aircraft to communicate state information to neighboring aircraft, as well as model the evolution of aircraft trajectories between communications, in the presence of probabilistic uncertain dynamics as well as partially observable and uncertain data. We introduce the Hybrid Hidden Markov Modeling (HHMM) formalism to enable the prediction of the stochastic aircraft states (and thus, potential conflicts), by combining elements of the probabilistic timed input output automaton and the partially observable Markov decision process frameworks, along with the novel addition of a Markovian scheduler to remove the non-deterministic elements arising from the enabling of several actions simultaneously. Comparisons of aircraft in level, climbing/descending and turning flight are performed, and unknown flight track data is evaluated probabilistically against the tuned model in order to assess the effectiveness of the model in detecting the switch between multiple flight modes for a given aircraft. This also allows for the generation of probabilistic distribution over the execution traces of the hybrid hidden Markov model, which then enables the prediction of the states of aircraft based on partially observable and uncertain data. Based on the composition properties of the HHMM, we study a decentralized air traffic system where aircraft are moving along streams and can perform cruise, accelerate, climb and turn maneuvers. We develop a common decentralized policy for conflict avoidance with spatially distributed agents (aircraft in the sky) and assure its safety properties via correctness proofs.

Rapid feedback processing in human nucleus accumbens and motor thalamus.

PubMed

Schüller, Thomas; Gruendler, Theo O J; Jocham, Gerhard; Klein, Tilmann A; Timmermann, Lars; Visser-Vandewalle, Veerle; Kuhn, Jens; Ullsperger, Markus

2015-04-01

The nucleus accumbens (NAcc) and thalamus are integral parts in models of feedback processing. Deep brain stimulation (DBS) has been successfully employed to alleviate symptoms of psychiatric conditions including obsessive-compulsive disorder (OCD) and Tourette's syndrome (TS). Common target structures are the NAcc and the ventral anterior and ventro-lateral nuclei (VA/VL) of the thalamus, for OCD and TS, respectively. The feedback related negativity (FRN) is an event-related potential associated with feedback processing reflecting posterior medial frontal cortex (pMFC) activity. Here we report on three cases where we recorded scalp EEG and local field potentials (LFP) from externalized electrodes located in the NAcc or thalamus (VA/VL) while patients engaged in a modified time estimation task, known to engage feedback processing and elicit the FRN. Additionally, scalp EEG were recorded from 29 healthy participants (HP) engaged in the same task. The signal in all structures (pMFC, NAcc, and thalamus) was differently modulated by positive and negative feedback. LFP activity in the NAcc showed a biphasic time course after positive feedback during the FRN time interval. Negative feedback elicited a much weaker and later response. In the thalamus a monophasic modulation was recorded during the FRN time interval. Again, this modulation was more pronounced after positive performance feedback compared to negative feedback. In channels outside the target area no modulation was observed. The surface-FRN was reliably elicited on a group level in HP and showed no significant difference following negative feedback between patients and HP. German Clinical Trial Register: Neurocognitive specification of dysfunctions within basal ganglia-cortex loops and their therapeutic modulation by deep brain stimulation in patients with obsessive compulsive disorder and Tourette syndrome, http://www.drks.de/DRKS00005316. Copyright © 2015 Elsevier Ltd. All rights reserved.

Reflection: A Link between Receiving and Using Assessment Feedback

ERIC Educational Resources Information Center

Sargeant, Joan M.; Mann, Karen V.; van der Vleuten, Cees P.; Metsemakers, Job F.

2009-01-01

Problem statement and background: Feedback is essential to learning and practice improvement, yet challenging both to provide and receive. The purpose of this paper was to explore reflective processes which physicians described as they considered their assessment feedback and the perceived utility of that reflective process. Methods: This is a…

Automatic and controlled processing in the corticocerebellar system.

PubMed

Ramnani, Narender

2014-01-01

During learning, performance changes often involve a transition from controlled processing in which performance is flexible and responsive to ongoing error feedback, but effortful and slow, to a state in which processing becomes swift and automatic. In this state, performance is unencumbered by the requirement to process feedback, but its insensitivity to feedback reduces its flexibility. Many properties of automatic processing are similar to those that one would expect of forward models, and many have suggested that these may be instantiated in cerebellar circuitry. Since hierarchically organized frontal lobe areas can both send and receive commands, I discuss the possibility that they can act both as controllers and controlled objects and that their behaviors can be independently modeled by forward models in cerebellar circuits. Since areas of the prefrontal cortex contribute to this hierarchically organized system and send outputs to the cerebellar cortex, I suggest that the cerebellum is likely to contribute to the automation of cognitive skills, and to the formation of habitual behavior which is resistant to error feedback. An important prerequisite to these ideas is that cerebellar circuitry should have access to higher order error feedback that signals the success or failure of cognitive processing. I have discussed the pathways through which such feedback could arrive via the inferior olive and the dopamine system. Cerebellar outputs inhibit both the inferior olive and the dopamine system. It is possible that learned representations in the cerebellum use this as a mechanism to suppress the processing of feedback in other parts of the nervous system. Thus, cerebellar processes that control automatic performance may be completed without triggering the engagement of controlled processes by prefrontal mechanisms. © 2014 Elsevier B.V. All rights reserved.

Motivational orientation modulates the neural response to reward.

PubMed

Linke, Julia; Kirsch, Peter; King, Andrea V; Gass, Achim; Hennerici, Michael G; Bongers, André; Wessa, Michèle

2010-02-01

Motivational orientation defines the source of motivation for an individual to perform a particular action and can either originate from internal desires (e.g., interest) or external compensation (e.g., money). To this end, motivational orientation should influence the way positive or negative feedback is processed during learning situations and this might in turn have an impact on the learning process. In the present study, we thus investigated whether motivational orientation, i.e., extrinsic and intrinsic motivation modulates the neural response to reward and punishment as well as learning from reward and punishment in 33 healthy individuals. To assess neural responses to reward, punishment and learning of reward contingencies we employed a probabilistic reversal learning task during functional magnetic resonance imaging. Extrinsic and intrinsic motivation were assessed with a self-report questionnaire. Rewarding trials fostered activation in the medial orbitofrontal cortex and anterior cingulate gyrus (ACC) as well as the amygdala and nucleus accumbens, whereas for punishment an increased neural response was observed in the medial and inferior prefrontal cortex, the superior parietal cortex and the insula. High extrinsic motivation was positively correlated to increased neural responses to reward in the ACC, amygdala and putamen, whereas a negative relationship between intrinsic motivation and brain activation in these brain regions was observed. These findings show that motivational orientation indeed modulates the responsiveness to reward delivery in major components of the human reward system and therefore extends previous results showing a significant influence of individual differences in reward-related personality traits on the neural processing of reward. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Attention to emotion and non-Western faces: revisiting the facial feedback hypothesis.

PubMed

Dzokoto, Vivian; Wallace, David S; Peters, Laura; Bentsi-Enchill, Esi

2014-01-01

In a modified replication of Strack, Martin, and Stepper's demonstration of the Facial Feedback Hypothesis (1988), we investigated the effect of attention to emotion on the facial feedback process in a non-western cultural setting. Participants, recruited from two universities in Ghana, West Africa, gave self-reports of their perceived levels of attention to emotion, and then completed cartoon-rating tasks while randomly assigned to smiling, frowning, or neutral conditions. While participants with low Attention to Emotion scores displayed the usual facial feedback effect (rating cartoons as funnier when in the smiling compared to the frowning condition), the effect was not present in individuals with high Attention to Emotion. The findings indicate that (1) the facial feedback process can occur in contexts beyond those in which the phenomenon has previously been studied, and (2) aspects of emotion regulation, such as Attention to Emotion can interfere with the facial feedback process.

Understanding feedback report uptake: process evaluation findings from a 13-month feedback intervention in long-term care settings.

PubMed

Sales, Anne E; Fraser, Kimberly; Baylon, Melba Andrea B; O'Rourke, Hannah M; Gao, Gloria; Bucknall, Tracey; Maisey, Suzanne

2015-02-12

Long-term care settings provide care to a large proportion of predominantly older, highly disabled adults across the United States and Canada. Managing and improving quality of care is challenging, in part because staffing is highly dependent on relatively non-professional health care aides and resources are limited. Feedback interventions in these settings are relatively rare, and there has been little published information about the process of feedback intervention. Our objectives were to describe the key components of uptake of the feedback reports, as well as other indicators of participant response to the intervention. We conducted this project in nine long-term care units in four facilities in Edmonton, Canada. We used mixed methods, including observations during a 13-month feedback report intervention with nine post-feedback survey cycles, to conduct a process evaluation of a feedback report intervention in these units. We included all facility-based direct care providers (staff) in the feedback report distribution and survey administration. We conducted descriptive analyses of the data from observations and surveys, presenting this in tabular and graphic form. We constructed a short scale to measure uptake of the feedback reports. Our analysis evaluated feedback report uptake by provider type over the 13 months of the intervention. We received a total of 1,080 survey responses over the period of the intervention, which varied by type of provider, facility, and survey month. Total number of reports distributed ranged from 103 in cycle 12 to 229 in cycle 3, although the method of delivery varied widely across the period, from 12% to 65% delivered directly to individuals and 15% to 84% left for later distribution. The key elements of feedback uptake, including receiving, reading, understanding, discussing, and reporting a perception that the reports were useful, varied by survey cycle and provider type, as well as by facility. Uptake, as we measured it, was consistently high overall, but varied widely by provider type and time period. We report detailed process data describing the aspects of uptake of a feedback report during an intensive, longitudinal feedback intervention in long-term care facilities. Uptake is a complex process for which we used multiple measures. We demonstrate the feasibility of conducting a complex longitudinal feedback intervention in relatively resource-poor long-term care facilities to a wider range of provider types than have been included in prior feedback interventions.

Making sense of feedback experiences: a multi-school study of medical students' narratives.

PubMed

Urquhart, Lynn M; Rees, Charlotte E; Ker, Jean S

2014-02-01

Until recently, the perspective of students in the feedback process has been ignored, with strategies for improvement focusing on the tutor and feedback delivery. We employed an original narrative interviewing approach to explore how medical students make sense of their experiences of feedback. A qualitative design was adopted employing three individual and 10 group interviews to elicit narratives of feedback experiences from 53 medical students at three 5-year undergraduate programmes in the UK during 2011. Thematic analysis was undertaken of students' understandings of feedback and of their narratives of positive and negative experiences of feedback at medical school. In addition, thematic and discourse analysis of the linguistic and paralinguistic features of talk within the narratives was conducted. Students typically constructed feedback as a monologic process that happened 'to' them rather than 'with' them. They shared 352 distinct narratives of feedback experiences, which were rich in linguistic and paralinguistic features of talk. Through the analysis of the interplay between the 'whats' and 'hows' of student talk, i.e. emotion, pronominal and metaphoric talk and laughter, we were able to understand how students find meaning in their experiences. Students used laughter as a coping strategy, emotion talk as a means to convince the audience of the impact of feedback, pronominal and metaphoric talk to describe their relationship (often adversarial) with their feedback providers and to communicate feelings that they might otherwise struggle to articulate. This research extends current feedback literature by focusing on medical students' lived experiences of feedback and their emotional impact through narrative. We go on to discuss the educational implications of our findings and to make recommendations for improvement of the feedback process for students, tutors and for institutions. © 2014 John Wiley & Sons Ltd.

A breakthrough in neuroscience needs a "Nebulous Cartesian System" Oscillations, quantum dynamics and chaos in the brain and vegetative system.

PubMed

Başar, Erol; Güntekin, Bahar

2007-04-01

The Cartesian System is a fundamental conceptual and analytical framework related and interwoven with the concept and applications of Newtonian Dynamics. In order to analyze quantum processes physicist moved to a Probabilistic Cartesian System in which the causality principle became a probabilistic one. This means the trajectories of particles (obeying quantum rules) can be described only with the concept of cloudy wave packets. The approach to the brain-body-mind problem requires more than the prerequisite of modern physics and quantum dynamics. In the analysis of the brain-body-mind construct we have to include uncertain causalities and consequently multiple uncertain causalities. These multiple causalities originate from (1) nonlinear properties of the vegetative system (e.g. irregularities in biochemical transmitters, cardiac output, turbulences in the vascular system, respiratory apnea, nonlinear oscillatory interactions in peristalsis); (2) nonlinear behavior of the neuronal electricity (e.g. chaotic behavior measured by EEG), (3) genetic modulations, and (4) additional to these physiological entities nonlinear properties of physical processes in the body. The brain shows deterministic chaos with a correlation dimension of approx. D(2)=6, the smooth muscles approx. D(2)=3. According to these facts we propose a hyper-probabilistic approach or a hyper-probabilistic Cartesian System to describe and analyze the processes in the brain-body-mind system. If we add aspects as our sentiments, emotions and creativity to this construct, better said to this already hyper-probabilistic construct, this "New Cartesian System" is more than hyper-probabilistic, it is a nebulous system, we can predict the future only in a nebulous way; however, despite this chain of reasoning we can still provide predictions on brain-body-mind incorporations. We tentatively assume that the processes or mechanisms of the brain-body-mind system can be analyzed and predicted similar to the metaphor of "finding the walking path in a cloudy or foggy day". This is meant by stating "The Nebulous Cartesian System" (NCS). Descartes, at his time undertaking his genius step, did not possess the knowledge of today's physiology and modern physics; we think that the time has come to consider such a New Cartesian System. To deal with this, we propose the utilization of the Heisenberg S-Matrix and a modified version of the Feynman Diagrams which we call "Brain Feynman Diagrams". Another metaphor to consider within the oscillatory approach of the NCS is the "string theory". We also emphasize that fundamental steps should be undertaken in order to create the own dynamical framework of the brain-body-mind incorporation; suggestions or metaphors from physics and mathematics are useful; however, the grammar of the brains intrinsic language must be understood with the help of a new biologically founded, adaptive-probabilistic Cartesian system. This new Cartesian System will undergo mutations and transcend to the philosophy of Henri Bergson in parallel to the Evolution theory of Charles Darwin to open gateways for approaching the brain-body-mind problem.

Motivation and attention: Incongruent effects of feedback on the processing of valence.

PubMed

Rothermund, Klaus

2003-09-01

Four experiments investigated the relation between outcome-related motivational states and processes of automatic attention allocation. Experiments 1-3 analyzed influences of feedback on evaluative decisions. Words of opposite valence to the feedback were processed faster, indicating that it is easier to allocate attention to the valence of an affectively incongruent word. Experiment 4 replicated the incongruent effect with interference effects of word valence in a grammatical-categorization task, indicating that the effect reflects automatic attentional capture. In all experiments, incongruent effects of feedback emerged only in a situation involving an attentional shift between words that differed in valence.

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2004-12-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2005-01-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

A Community-Based Participatory Approach to Personalized, Computer-Generated Nutrition Feedback Reports: The Healthy Environments Partnership

PubMed Central

Kannan, Srimathi; Schulz, Amy; Israel, Barbara; Ayra, Indira; Weir, Sheryl; Dvonch, Timothy J.; Rowe, Zachary; Miller, Patricia; Benjamin, Alison

2008-01-01

Background Computer tailoring and personalizing recommendations for dietary health-promoting behaviors are in accordance with community-based participatory research (CBPR) principles, which emphasizes research that benefits the participants and community involved. Objective To describe the CBPR process utilized to computer-generate and disseminate personalized nutrition feedback reports (NFRs) for Detroit Healthy Environments Partnership (HEP) study participants. METHODS The CBPR process included discussion and feedback from HEP partners on several draft personalized reports. The nutrition feedback process included defining the feedback objectives; prioritizing the nutrients; customizing the report design; reviewing and revising the NFR template and readability; producing and disseminating the report; and participant follow-up. Lessons Learned Application of CBPR principles in designing the NFR resulted in a reader-friendly product with useful recommendations to promote heart health. Conclusions A CBPR process can enhance computer tailoring of personalized NFRs to address racial and socioeconomic disparities in cardiovascular disease (CVD). PMID:19337572

Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Cess, R. D.; Potter, G. L.; Blanchet, J. P.; Boer, G. J.; Del Genio, A. D.

1990-01-01

The present study provides an intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. This intercomparison uses sea surface temperature change as a surrogate for climate change. The interpretation of cloud-climate interactions is given special attention. A roughly threefold variation in one measure of global climate sensitivity is found among the 19 models. The important conclusion is that most of this variation is attributable to differences in the models' depiction of cloud feedback, a result that emphasizes the need for improvements in the treatment of clouds in these models if they are ultimately to be used as reliable climate predictors. It is further emphazied that cloud feedback is the consequence of all interacting physical and dynamical processes in a general circulation model. The result of these processes is to produce changes in temperature, moisture distribution, and clouds which are integrated into the radiative response termed cloud feedback.

Probability or Reasoning: Current Thinking and Realistic Strategies for Improved Medical Decisions

PubMed Central

2017-01-01

A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy. PMID:29209469

When knowledge activated from memory intrudes on probabilistic inferences from description - the case of stereotypes.

PubMed

Dorrough, Angela R; Glöckner, Andreas; Betsch, Tilmann; Wille, Anika

2017-10-01

To make decisions in probabilistic inference tasks, individuals integrate relevant information partly in an automatic manner. Thereby, potentially irrelevant stimuli that are additionally presented can intrude on the decision process (e.g., Söllner, Bröder, Glöckner, & Betsch, 2014). We investigate whether such an intrusion effect can also be caused by potentially irrelevant or even misleading knowledge activated from memory. In four studies that combine a standard information board paradigm from decision research with a standard manipulation from social psychology, we investigate the case of stereotypes and demonstrate that stereotype knowledge can yield intrusion biases in probabilistic inferences from description. The magnitude of these biases increases with stereotype accessibility and decreases with a clarification of the rational solution. Copyright © 2017 Elsevier B.V. All rights reserved.

Probability or Reasoning: Current Thinking and Realistic Strategies for Improved Medical Decisions.

PubMed

Nantha, Yogarabindranath Swarna

2017-11-01

A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy.

Young children do not succeed in choice tasks that imply evaluating chances.

PubMed

Girotto, Vittorio; Fontanari, Laura; Gonzalez, Michel; Vallortigara, Giorgio; Blaye, Agnès

2016-07-01

Preverbal infants manifest probabilistic intuitions in their reactions to the outcomes of simple physical processes and in their choices. Their ability conflicts with the evidence that, before the age of about 5years, children's verbal judgments do not reveal probability understanding. To assess these conflicting results, three studies tested 3-5-year-olds on choice tasks on which infants perform successfully. The results showed that children of all age groups made optimal choices in tasks that did not require forming probabilistic expectations. In probabilistic tasks, however, only 5-year-olds made optimal choices. Younger children performed at random and/or were guided by superficial heuristics. These results suggest caution in interpreting infants' ability to evaluate chance, and indicate that the development of this ability may not follow a linear trajectory. Copyright © 2016 Elsevier B.V. All rights reserved.

Composite Load Spectra for Select Space Propulsion Structural Components

NASA Technical Reports Server (NTRS)

Ho, Hing W.; Newell, James F.

1994-01-01

Generic load models are described with multiple levels of progressive sophistication to simulate the composite (combined) load spectra (CLS) that are induced in space propulsion system components, representative of Space Shuttle Main Engines (SSME), such as transfer ducts, turbine blades and liquid oxygen (LOX) posts. These generic (coupled) models combine the deterministic models for composite load dynamic, acoustic, high-pressure and high rotational speed, etc., load simulation using statistically varying coefficients. These coefficients are then determined using advanced probabilistic simulation methods with and without strategically selected experimental data. The entire simulation process is included in a CLS computer code. Applications of the computer code to various components in conjunction with the PSAM (Probabilistic Structural Analysis Method) to perform probabilistic load evaluation and life prediction evaluations are also described to illustrate the effectiveness of the coupled model approach.

Enacting Feedback Utilization from a Task-Specific Perspective

ERIC Educational Resources Information Center

Lam, Ricky

2017-01-01

Feedback is central to successful teaching and learning. Despite extensive research on the relationship between feedback, pedagogy and learning, there remain no conclusive answers as to how feedback can be effectively utilized by learners. Recently, there is emerging research exploring how feedback is conceptualized as dialogic processes to…

Complexity, Cues and Relationships: Student Perceptions of Feedback

ERIC Educational Resources Information Center

Pokorny, Helen; Pickford, Pamela

2010-01-01

This article discusses issues relating to the effectiveness of feedback and the student perspective. The study described provides rich data relating to student perceptions of useful feedback, their perceptions of feedback cues and their feelings about the importance of feedback relationships in the process. The outcomes suggest that written…

Bayesian networks and information theory for audio-visual perception modeling.

PubMed

Besson, Patricia; Richiardi, Jonas; Bourdin, Christophe; Bringoux, Lionel; Mestre, Daniel R; Vercher, Jean-Louis

2010-09-01

Thanks to their different senses, human observers acquire multiple information coming from their environment. Complex cross-modal interactions occur during this perceptual process. This article proposes a framework to analyze and model these interactions through a rigorous and systematic data-driven process. This requires considering the general relationships between the physical events or factors involved in the process, not only in quantitative terms, but also in term of the influence of one factor on another. We use tools from information theory and probabilistic reasoning to derive relationships between the random variables of interest, where the central notion is that of conditional independence. Using mutual information analysis to guide the model elicitation process, a probabilistic causal model encoded as a Bayesian network is obtained. We exemplify the method by using data collected in an audio-visual localization task for human subjects, and we show that it yields a well-motivated model with good predictive ability. The model elicitation process offers new prospects for the investigation of the cognitive mechanisms of multisensory perception.

Using stochastic language models (SLM) to map lexical, syntactic, and phonological information processing in the brain.

PubMed

Lopopolo, Alessandro; Frank, Stefan L; van den Bosch, Antal; Willems, Roel M

2017-01-01

Language comprehension involves the simultaneous processing of information at the phonological, syntactic, and lexical level. We track these three distinct streams of information in the brain by using stochastic measures derived from computational language models to detect neural correlates of phoneme, part-of-speech, and word processing in an fMRI experiment. Probabilistic language models have proven to be useful tools for studying how language is processed as a sequence of symbols unfolding in time. Conditional probabilities between sequences of words are at the basis of probabilistic measures such as surprisal and perplexity which have been successfully used as predictors of several behavioural and neural correlates of sentence processing. Here we computed perplexity from sequences of words and their parts of speech, and their phonemic transcriptions. Brain activity time-locked to each word is regressed on the three model-derived measures. We observe that the brain keeps track of the statistical structure of lexical, syntactic and phonological information in distinct areas.

Initiatives to improve feedback culture in the final year of a veterinary program.

PubMed

Warman, Sheena M; Laws, Emma J; Crowther, Emma; Baillie, Sarah

2014-01-01

Despite the recognized importance of feedback in education, student satisfaction with the feedback process in medical and veterinary programs is often disappointing. We undertook various initiatives to try to improve the feedback culture in the final clinical year of the veterinary program at the University of Bristol, focusing on formative verbal feedback. The initiatives included E-mailed guidelines to staff and students, a faculty development workshop, and a reflective portfolio task for students. Following these initiatives, staff and students were surveyed regarding their perceptions of formative feedback in clinical rotations, and focus groups were held to further explore issues. The amount of feedback appeared to have increased, along with improved recognition of feedback by students and increased staff confidence and competence in the process. Other themes that emerged included inconsistencies in feedback among staff and between rotations; difficulties with giving verbal feedback to students, particularly when it relates to professionalism; the consequences of feedback for both staff and students; changes and challenges in students' feedback-seeking behavior; and the difficulties in providing accurate, personal end-of-rotation assessments. This project has helped improve the feedback culture within our clinics; the importance of sustaining and further developing the feedback culture is discussed in this article.

Schrödinger problem, Lévy processes, and noise in relativistic quantum mechanics

NASA Astrophysics Data System (ADS)

Garbaczewski, Piotr; Klauder, John R.; Olkiewicz, Robert

1995-05-01

The main purpose of the paper is an essentially probabilistic analysis of relativistic quantum mechanics. It is based on the assumption that whenever probability distributions arise, there exists a stochastic process that is either responsible for the temporal evolution of a given measure or preserves the measure in the stationary case. Our departure point is the so-called Schrödinger problem of probabilistic evolution, which provides for a unique Markov stochastic interpolation between any given pair of boundary probability densities for a process covering a fixed, finite duration of time, provided we have decided a priori what kind of primordial dynamical semigroup transition mechanism is involved. In the nonrelativistic theory, including quantum mechanics, Feynman-Kac-like kernels are the building blocks for suitable transition probability densities of the process. In the standard ``free'' case (Feynman-Kac potential equal to zero) the familiar Wiener noise is recovered. In the framework of the Schrödinger problem, the ``free noise'' can also be extended to any infinitely divisible probability law, as covered by the Lévy-Khintchine formula. Since the relativistic Hamiltonians ||∇|| and √-Δ+m2 -m are known to generate such laws, we focus on them for the analysis of probabilistic phenomena, which are shown to be associated with the relativistic wave (D'Alembert) and matter-wave (Klein-Gordon) equations, respectively. We show that such stochastic processes exist and are spatial jump processes. In general, in the presence of external potentials, they do not share the Markov property, except for stationary situations. A concrete example of the pseudodifferential Cauchy-Schrödinger evolution is analyzed in detail. The relativistic covariance of related wave equations is exploited to demonstrate how the associated stochastic jump processes comply with the principles of special relativity.

Fear of negative evaluation modulates electrocortical and behavioral responses when anticipating social evaluative feedback

PubMed Central

Van der Molen, Melle J. W.; Poppelaars, Eefje S.; Van Hartingsveldt, Caroline T. A.; Harrewijn, Anita; Gunther Moor, Bregtje; Westenberg, P. Michiel

2014-01-01

Cognitive models posit that the fear of negative evaluation (FNE) is a hallmark feature of social anxiety. As such, individuals with high FNE may show biased information processing when faced with social evaluation. The aim of the current study was to examine the neural underpinnings of anticipating and processing social-evaluative feedback, and its correlates with FNE. We used a social judgment paradigm in which female participants (N = 31) were asked to indicate whether they believed to be socially accepted or rejected by their peers. Anticipatory attention was indexed by the stimulus preceding negativity (SPN), while the feedback-related negativity and P3 were used to index the processing of social-evaluative feedback. Results provided evidence of an optimism bias in social peer evaluation, as participants more often predicted to be socially accepted than rejected. Participants with high levels of FNE needed more time to provide their judgments about the social-evaluative outcome. While anticipating social-evaluative feedback, SPN amplitudes were larger for anticipated social acceptance than for social rejection feedback. Interestingly, the SPN during anticipated social acceptance was larger in participants with high levels of FNE. None of the feedback-related brain potentials correlated with the FNE. Together, the results provided evidence of biased information processing in individuals with high levels of FNE when anticipating (rather than processing) social-evaluative feedback. The delayed response times in high FNE individuals were interpreted to reflect augmented vigilance imposed by the upcoming social-evaluative threat. Possibly, the SPN constitutes a neural marker of this vigilance in females with higher FNE levels, particularly when anticipating social acceptance feedback. PMID:24478667

Cardiac Concomitants of Feedback and Prediction Error Processing in Reinforcement Learning.

PubMed

Kastner, Lucas; Kube, Jana; Villringer, Arno; Neumann, Jane

2017-01-01

Successful learning hinges on the evaluation of positive and negative feedback. We assessed differential learning from reward and punishment in a monetary reinforcement learning paradigm, together with cardiac concomitants of positive and negative feedback processing. On the behavioral level, learning from reward resulted in more advantageous behavior than learning from punishment, suggesting a differential impact of reward and punishment on successful feedback-based learning. On the autonomic level, learning and feedback processing were closely mirrored by phasic cardiac responses on a trial-by-trial basis: (1) Negative feedback was accompanied by faster and prolonged heart rate deceleration compared to positive feedback. (2) Cardiac responses shifted from feedback presentation at the beginning of learning to stimulus presentation later on. (3) Most importantly, the strength of phasic cardiac responses to the presentation of feedback correlated with the strength of prediction error signals that alert the learner to the necessity for behavioral adaptation. Considering participants' weight status and gender revealed obesity-related deficits in learning to avoid negative consequences and less consistent behavioral adaptation in women compared to men. In sum, our results provide strong new evidence for the notion that during learning phasic cardiac responses reflect an internal value and feedback monitoring system that is sensitive to the violation of performance-based expectations. Moreover, inter-individual differences in weight status and gender may affect both behavioral and autonomic responses in reinforcement-based learning.

Cardiac Concomitants of Feedback and Prediction Error Processing in Reinforcement Learning

PubMed Central

Kastner, Lucas; Kube, Jana; Villringer, Arno; Neumann, Jane

2017-01-01

Successful learning hinges on the evaluation of positive and negative feedback. We assessed differential learning from reward and punishment in a monetary reinforcement learning paradigm, together with cardiac concomitants of positive and negative feedback processing. On the behavioral level, learning from reward resulted in more advantageous behavior than learning from punishment, suggesting a differential impact of reward and punishment on successful feedback-based learning. On the autonomic level, learning and feedback processing were closely mirrored by phasic cardiac responses on a trial-by-trial basis: (1) Negative feedback was accompanied by faster and prolonged heart rate deceleration compared to positive feedback. (2) Cardiac responses shifted from feedback presentation at the beginning of learning to stimulus presentation later on. (3) Most importantly, the strength of phasic cardiac responses to the presentation of feedback correlated with the strength of prediction error signals that alert the learner to the necessity for behavioral adaptation. Considering participants' weight status and gender revealed obesity-related deficits in learning to avoid negative consequences and less consistent behavioral adaptation in women compared to men. In sum, our results provide strong new evidence for the notion that during learning phasic cardiac responses reflect an internal value and feedback monitoring system that is sensitive to the violation of performance-based expectations. Moreover, inter-individual differences in weight status and gender may affect both behavioral and autonomic responses in reinforcement-based learning. PMID:29163004

Reduced sensitivity to neutral feedback versus negative feedback in subjects with mild depression: Evidence from event-related potentials study.

PubMed

Li, Peng; Song, Xinxin; Wang, Jing; Zhou, Xiaoran; Li, Jiayi; Lin, Fengtong; Hu, Zhonghua; Zhang, Xinxin; Cui, Hewei; Wang, Wenmiao; Li, Hong; Cong, Fengyu; Roberson, Debi

2015-11-01

Many previous event-related potential (ERP) studies have linked the feedback related negativity (FRN) component with medial frontal cortex processing and associated this component with depression. Few if any studies have investigated the processing of neutral feedback in mildly depressive subjects in the normal population. Two experiments compared brain responses to neutral feedback with behavioral performance in mildly depressed subjects who scored highly on the Beck Depression Inventory (high BDI) and a control group with lower BDI scores (low BDI). In the first study, the FRN component was recorded when neutral, negative or positive feedback was pseudo-randomly delivered to the two groups in a time estimation task. In the second study, real feedback was provided to the two groups in the same task in order to measure their actual accuracy of performance. The results of experiment one (Exp. 1) revealed that a larger FRN effect was elicited by neutral feedback than by negative feedback in the low BDI group, but no significant difference was found between neutral condition and negative condition in the High BDI group. The present findings demonstrated that depressive tendencies influence the processing of neutral feedback in medial frontal cortex. The FRN effect may work as a helpful index for investigating cognitive bias in depression in future studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Effects of intrinsic motivation on feedback processing during learning.

PubMed

DePasque, Samantha; Tricomi, Elizabeth

2015-10-01

Learning commonly requires feedback about the consequences of one's actions, which can drive learners to modify their behavior. Motivation may determine how sensitive an individual might be to such feedback, particularly in educational contexts where some students value academic achievement more than others. Thus, motivation for a task might influence the value placed on performance feedback and how effectively it is used to improve learning. To investigate the interplay between intrinsic motivation and feedback processing, we used functional magnetic resonance imaging (fMRI) during feedback-based learning before and after a novel manipulation based on motivational interviewing, a technique for enhancing treatment motivation in mental health settings. Because of its role in the reinforcement learning system, the striatum is situated to play a significant role in the modulation of learning based on motivation. Consistent with this idea, motivation levels during the task were associated with sensitivity to positive versus negative feedback in the striatum. Additionally, heightened motivation following a brief motivational interview was associated with increases in feedback sensitivity in the left medial temporal lobe. Our results suggest that motivation modulates neural responses to performance-related feedback, and furthermore that changes in motivation facilitate processing in areas that support learning and memory. Copyright © 2015. Published by Elsevier Inc.

Different Electrophysiological Responses to Informative Value of Feedback Between Children and Adults.

PubMed

Du, Bin; Cao, Bihua; He, Weiqi; Li, Fuhong

2018-01-01

The ability to learn from feedback is important for children's adaptive behavior and school learning. Feedback has two main components, informative value and valence. How to disentangle these two components and what is the developmental neural correlates of using the informative value of feedback is still an open question. In this study, 23 children (7-10 years old) and 19 adults (19-22 years old) were asked to perform a rule induction task, in which they were required to find a rule, based on the informative value of feedback. Behavioral results indicated that the likelihood of correct searching behavior under negative feedback was low for children. Event-related potentials showed that (1) the effect of valence was processed in a wide time window, particularly in the N2 component; (2) the encoding process of the informative value of negative feedback began later for children than for adults; (3) a clear P300 was observed for adults; for children, however, P300 was absent in the frontal region; and (4) children processed the informative value of feedback chiefly in the left sites during the P300 time window, whereas adults did not show this laterality. These results suggested that children were less sensitive to the informative value of negative feedback possibly because of the immature brain.

Translating evidence-based guidelines to improve feedback practices: the interACT case study.

PubMed

Barton, Karen L; Schofield, Susie J; McAleer, Sean; Ajjawi, Rola

2016-02-09

There has been a substantial body of research examining feedback practices, yet the assessment and feedback landscape in higher education is described as 'stubbornly resistant to change'. The aim of this paper is to present a case study demonstrating how an entire programme's assessment and feedback practices were re-engineered and evaluated in line with evidence from the literature in the interACT (Interaction and Collaboration via Technology) project. Informed by action research the project conducted two cycles of planning, action, evaluation and reflection. Four key pedagogical principles informed the re-design of the assessment and feedback practices. Evaluation activities included document analysis, interviews with staff (n = 10) and students (n = 7), and student questionnaires (n = 54). Descriptive statistics were used to analyse the questionnaire data. Framework thematic analysis was used to develop themes across the interview data. InterACT was reported by students and staff to promote self-evaluation, engagement with feedback and feedback dialogue. Streamlining the process after the first cycle of action research was crucial for improving engagement of students and staff. The interACT process of promoting self-evaluation, reflection on feedback, feedback dialogue and longitudinal perspectives of feedback has clear benefits and should be transferable to other contexts. InterACT has involved comprehensive re-engineering of the assessment and feedback processes using educational principles to guide the design taking into account stakeholder perspectives. These principles and the strategies to enact them should be transferable to other contexts.

Cultural influences on social feedback processing of character traits

PubMed Central

Korn, Christoph W.; Fan, Yan; Zhang, Kai; Wang, Chenbo; Han, Shihui; Heekeren, Hauke R.

2014-01-01

Cultural differences are generally explained by how people see themselves in relation to social interaction partners. While Western culture emphasizes independence, East Asian culture emphasizes interdependence. Despite this focus on social interactions, it remains elusive how people from different cultures process feedback on their own (and on others') character traits. Here, participants of either German or Chinese origin engaged in a face-to-face interaction. Consequently, they updated their self- and other-ratings of 80 character traits (e.g., polite, pedantic) after receiving feedback from their interaction partners. To exclude potential confounds, we obtained data from German and Chinese participants in Berlin [functional magnetic resonance imaging (fMRI)] and in Beijing (behavior). We tested cultural influences on social conformity, positivity biases, and self-related neural activity. First, Chinese conformed more to social feedback than Germans (i.e., Chinese updated their trait ratings more). Second, regardless of culture, participants processed self- and other-related feedback in a positively biased way (i.e., they updated more toward desirable than toward undesirable feedback). Third, changes in self-related medial prefrontal cortex activity were greater in Germans than in Chinese during feedback processing. By investigating conformity, positivity biases, and self-related activity in relation to feedback obtained in a real-life interaction, we provide an essential step toward a unifying framework for understanding the diversity of human culture. PMID:24772075

Vocal Responses to Perturbations in Voice Auditory Feedback in Individuals with Parkinson's Disease

PubMed Central

Liu, Hanjun; Wang, Emily Q.; Metman, Leo Verhagen; Larson, Charles R.

2012-01-01

Background One of the most common symptoms of speech deficits in individuals with Parkinson's disease (PD) is significantly reduced vocal loudness and pitch range. The present study investigated whether abnormal vocalizations in individuals with PD are related to sensory processing of voice auditory feedback. Perturbations in loudness or pitch of voice auditory feedback are known to elicit short latency, compensatory responses in voice amplitude or fundamental frequency. Methodology/Principal Findings Twelve individuals with Parkinson's disease and 13 age- and sex- matched healthy control subjects sustained a vowel sound (/α/) and received unexpected, brief (200 ms) perturbations in voice loudness (±3 or 6 dB) or pitch (±100 cents) auditory feedback. Results showed that, while all subjects produced compensatory responses in their voice amplitude or fundamental frequency, individuals with PD exhibited larger response magnitudes than the control subjects. Furthermore, for loudness-shifted feedback, upward stimuli resulted in shorter response latencies than downward stimuli in the control subjects but not in individuals with PD. Conclusions/Significance The larger response magnitudes in individuals with PD compared with the control subjects suggest that processing of voice auditory feedback is abnormal in PD. Although the precise mechanisms of the voice feedback processing are unknown, results of this study suggest that abnormal voice control in individuals with PD may be related to dysfunctional mechanisms of error detection or correction in sensory feedback processing. PMID:22448258

Effects of Achievement Goals on Challenge Seeking and Feedback Processing: Behavioral and fMRI Evidence

PubMed Central

Lee, Woogul; Kim, Sung-il

2014-01-01

We conducted behavioral and functional magnetic resonance imaging (fMRI) research to investigate the effects of two types of achievement goals—mastery goals and performance-approach goals— on challenge seeking and feedback processing. The results of the behavioral experiment indicated that mastery goals were associated with a tendency to seek challenge, both before and after experiencing difficulty during task performance, whereas performance-approach goals were related to a tendency to avoid challenge after encountering difficulty during task performance. The fMRI experiment uncovered a significant decrease in ventral striatal activity when participants received negative feedback for any task type and both forms of achievement goals. During the processing of negative feedback for the rule-finding task, performance-approach-oriented participants showed a substantial reduction in activity in the dorsolateral prefrontal cortex (DLPFC) and the frontopolar cortex, whereas mastery-oriented participants showed little change. These results suggest that performance-approach-oriented participants are less likely to either recruit control processes in response to negative feedback or focus on task-relevant information provided alongside the negative feedback. In contrast, mastery-oriented participants are more likely to modulate aversive valuations to negative feedback and focus on the constructive elements of feedback in order to attain their task goals. We conclude that performance-approach goals lead to a reluctant stance towards difficulty, while mastery goals encourage a proactive stance. PMID:25251396

Cultural influences on social feedback processing of character traits.

PubMed

Korn, Christoph W; Fan, Yan; Zhang, Kai; Wang, Chenbo; Han, Shihui; Heekeren, Hauke R

2014-01-01

Cultural differences are generally explained by how people see themselves in relation to social interaction partners. While Western culture emphasizes independence, East Asian culture emphasizes interdependence. Despite this focus on social interactions, it remains elusive how people from different cultures process feedback on their own (and on others') character traits. Here, participants of either German or Chinese origin engaged in a face-to-face interaction. Consequently, they updated their self- and other-ratings of 80 character traits (e.g., polite, pedantic) after receiving feedback from their interaction partners. To exclude potential confounds, we obtained data from German and Chinese participants in Berlin [functional magnetic resonance imaging (fMRI)] and in Beijing (behavior). We tested cultural influences on social conformity, positivity biases, and self-related neural activity. First, Chinese conformed more to social feedback than Germans (i.e., Chinese updated their trait ratings more). Second, regardless of culture, participants processed self- and other-related feedback in a positively biased way (i.e., they updated more toward desirable than toward undesirable feedback). Third, changes in self-related medial prefrontal cortex activity were greater in Germans than in Chinese during feedback processing. By investigating conformity, positivity biases, and self-related activity in relation to feedback obtained in a real-life interaction, we provide an essential step toward a unifying framework for understanding the diversity of human culture.

Blunted feedback processing during risk-taking in adolescents with features of problematic Internet use.

PubMed

Yau, Yvonne H C; Potenza, Marc N; Mayes, Linda C; Crowley, Michael J

2015-06-01

While the conceptualization of problematic Internet use (PIU) as a "behavioral addiction" resembling substance-use disorders is debated, the neurobiological underpinnings of PIU remain understudied. This study examined whether adolescents displaying features of PIU (at-risk PIU; ARPIU) are more impulsive and exhibit blunted responding in the neural mechanisms underlying feedback processing and outcome evaluation during risk-taking. Event-related potentials (ERPs) elicited by positive (i.e. reward) and negative (i.e. loss) feedback were recorded during performance on a modified version of the Balloon Analogue Risk Task (BART) among ARPIU (n=39) and non-ARPIU subjects (n=27). Compared to non-ARPIU, ARPIU adolescents displayed higher levels of urgency and lack of perseverance on the UPPS Impulsive Behavior Scale. Although no between-group difference in BART performance was observed, ERPs demonstrated overall decreased sensitivity to feedback in ARPIU compared to non-ARPIU adolescents, as indexed by blunted feedback-related negativity (FRN) and P300 amplitudes to both negative and positive feedback. The present study provides evidence for feedback processing during risk-taking as a neural correlate of ARPIU. Given recent concerns regarding the growing prevalence of PIU as a health concern, future work should examine the extent to which feedback processing may represent a risk factor for PIU, a consequence of PIU, or possibly both. Copyright © 2015 Elsevier Ltd. All rights reserved.

Visual crowding illustrates the inadequacy of local vs. global and feedforward vs. feedback distinctions in modeling visual perception

PubMed Central

Clarke, Aaron M.; Herzog, Michael H.; Francis, Gregory

2014-01-01

Experimentalists tend to classify models of visual perception as being either local or global, and involving either feedforward or feedback processing. We argue that these distinctions are not as helpful as they might appear, and we illustrate these issues by analyzing models of visual crowding as an example. Recent studies have argued that crowding cannot be explained by purely local processing, but that instead, global factors such as perceptual grouping are crucial. Theories of perceptual grouping, in turn, often invoke feedback connections as a way to account for their global properties. We examined three types of crowding models that are representative of global processing models, and two of which employ feedback processing: a model based on Fourier filtering, a feedback neural network, and a specific feedback neural architecture that explicitly models perceptual grouping. Simulations demonstrate that crucial empirical findings are not accounted for by any of the models. We conclude that empirical investigations that reject a local or feedforward architecture offer almost no constraints for model construction, as there are an uncountable number of global and feedback systems. We propose that the identification of a system as being local or global and feedforward or feedback is less important than the identification of a system's computational details. Only the latter information can provide constraints on model development and promote quantitative explanations of complex phenomena. PMID:25374554

Left-hemisphere activation is associated with enhanced vocal pitch error detection in musicians with absolute pitch.

PubMed

Behroozmand, Roozbeh; Ibrahim, Nadine; Korzyukov, Oleg; Robin, Donald A; Larson, Charles R

2014-02-01

The ability to process auditory feedback for vocal pitch control is crucial during speaking and singing. Previous studies have suggested that musicians with absolute pitch (AP) develop specialized left-hemisphere mechanisms for pitch processing. The present study adopted an auditory feedback pitch perturbation paradigm combined with ERP recordings to test the hypothesis whether the neural mechanisms of the left-hemisphere enhance vocal pitch error detection and control in AP musicians compared with relative pitch (RP) musicians and non-musicians (NM). Results showed a stronger N1 response to pitch-shifted voice feedback in the right-hemisphere for both AP and RP musicians compared with the NM group. However, the left-hemisphere P2 component activation was greater in AP and RP musicians compared with NMs and also for the AP compared with RP musicians. The NM group was slower in generating compensatory vocal reactions to feedback pitch perturbation compared with musicians, and they failed to re-adjust their vocal pitch after the feedback perturbation was removed. These findings suggest that in the earlier stages of cortical neural processing, the right hemisphere is more active in musicians for detecting pitch changes in voice feedback. In the later stages, the left-hemisphere is more active during the processing of auditory feedback for vocal motor control and seems to involve specialized mechanisms that facilitate pitch processing in the AP compared with RP musicians. These findings indicate that the left hemisphere mechanisms of AP ability are associated with improved auditory feedback pitch processing during vocal pitch control in tasks such as speaking or singing. Copyright © 2013 Elsevier Inc. All rights reserved.

Factors Influencing Responsiveness to Feedback: On the Interplay between Fear, Confidence, and Reasoning Processes

ERIC Educational Resources Information Center

Eva, Kevin W.; Armson, Heather; Holmboe, Eric; Lockyer, Jocelyn; Loney, Elaine; Mann, Karen; Sargeant, Joan

2012-01-01

Self-appraisal has repeatedly been shown to be inadequate as a mechanism for performance improvement. This has placed greater emphasis on understanding the processes through which self-perception and external feedback interact to influence professional development. As feedback is inevitably interpreted through the lens of one's self-perceptions it…

Feedback-related brain activity predicts learning from feedback in multiple-choice testing.

PubMed

Ernst, Benjamin; Steinhauser, Marco

2012-06-01

Different event-related potentials (ERPs) have been shown to correlate with learning from feedback in decision-making tasks and with learning in explicit memory tasks. In the present study, we investigated which ERPs predict learning from corrective feedback in a multiple-choice test, which combines elements from both paradigms. Participants worked through sets of multiple-choice items of a Swahili-German vocabulary task. Whereas the initial presentation of an item required the participants to guess the answer, corrective feedback could be used to learn the correct response. Initial analyses revealed that corrective feedback elicited components related to reinforcement learning (FRN), as well as to explicit memory processing (P300) and attention (early frontal positivity). However, only the P300 and early frontal positivity were positively correlated with successful learning from corrective feedback, whereas the FRN was even larger when learning failed. These results suggest that learning from corrective feedback crucially relies on explicit memory processing and attentional orienting to corrective feedback, rather than on reinforcement learning.

Unexpected Acceptance? Patients with Social Anxiety Disorder Manifest their Social Expectancy in ERPs During Social Feedback Processing.

PubMed

Cao, Jianqin; Gu, Ruolei; Bi, Xuejing; Zhu, Xiangru; Wu, Haiyan

2015-01-01

Previous studies on social anxiety have demonstrated negative-expectancy bias in social contexts. In this study, we used a paradigm that employed self-relevant positive or negative social feedback, in order to test whether this negative expectancy manifests in event-related potentials (ERPs) during social evaluation among socially anxious individuals. Behavioral data revealed that individuals with social anxiety disorder (SAD) showed more negative expectancy of peer acceptance both in the experiment and in daily life than did the healthy control participants. Regarding ERP results, we found a overally larger P2 for positive social feedback and also a group main effect, such that the P2 was smaller in SAD group. SAD participants demonstrated a larger feedback-related negativity (FRN) to positive feedback than to negative feedback. In addition, SAD participants showed a more positive ΔFRN (ΔFRN = negative - positive). Furthermore, acceptance expectancy in daily life correlated negatively with ΔFRN amplitude, while the Interaction Anxiousness Scale (IAS) score correlated positively with the ΔFRN amplitude. Finally, the acceptance expectancy in daily life fully mediated the relationship between the IAS and ΔFRN. These results indicated that both groups could differentiate between positive and negative social feedback in the early stage of social feedback processing (reflected on the P2). However, the SAD group exhibited a larger FRN to positive social feedback than to negative social feedback, demonstrating their dysfunction in the late stage of social feedback processing. In our opinion, such dysfunction is due to their greater negative social feedback expectancy.

Unexpected Acceptance? Patients with Social Anxiety Disorder Manifest their Social Expectancy in ERPs During Social Feedback Processing

PubMed Central

Cao, Jianqin; Gu, Ruolei; Bi, Xuejing; Zhu, Xiangru; Wu, Haiyan

2015-01-01

Previous studies on social anxiety have demonstrated negative-expectancy bias in social contexts. In this study, we used a paradigm that employed self-relevant positive or negative social feedback, in order to test whether this negative expectancy manifests in event-related potentials (ERPs) during social evaluation among socially anxious individuals. Behavioral data revealed that individuals with social anxiety disorder (SAD) showed more negative expectancy of peer acceptance both in the experiment and in daily life than did the healthy control participants. Regarding ERP results, we found a overally larger P2 for positive social feedback and also a group main effect, such that the P2 was smaller in SAD group. SAD participants demonstrated a larger feedback-related negativity (FRN) to positive feedback than to negative feedback. In addition, SAD participants showed a more positive ΔFRN (ΔFRN = negative – positive). Furthermore, acceptance expectancy in daily life correlated negatively with ΔFRN amplitude, while the Interaction Anxiousness Scale (IAS) score correlated positively with the ΔFRN amplitude. Finally, the acceptance expectancy in daily life fully mediated the relationship between the IAS and ΔFRN. These results indicated that both groups could differentiate between positive and negative social feedback in the early stage of social feedback processing (reflected on the P2). However, the SAD group exhibited a larger FRN to positive social feedback than to negative social feedback, demonstrating their dysfunction in the late stage of social feedback processing. In our opinion, such dysfunction is due to their greater negative social feedback expectancy. PMID:26635659

Willing to Wait: Elevated Reward-Processing EEG Activity Associated with a Greater Preference for Larger-But-Delayed Rewards

PubMed Central

Pornpattananangkul, Narun; Nusslock, Robin

2016-01-01

While almost everyone discounts the value of future rewards over immediate rewards, people differ in their so-called delay-discounting. One of the several factors that may explain individual differences in delay-discounting is reward-processing. To study individual-differences in reward-processing, however, one needs to consider the heterogeneity of neural-activity at each reward-processing stage. Here using EEG, we separated reward-related neural activity into distinct reward-anticipation and reward-outcome stages using time-frequency characteristics. Thirty-seven individuals completed a behavioral delay-discounting task. Reward-processing EEG activity was assessed using a separate reward-learning task, called a reward time-estimation task. During this task, participants were instructed to estimate time duration and were provided performance feedback on a trial-by-trial basis. Participants received monetary-reward for accurate-performance on Reward trials, but not on No-Reward trials. Reward trials, relative to No-Reward trials, enhanced EEG activity during both reward-anticipation stage (including, cued-locked delta power during cue-evaluation and pre-feedback alpha suppression during feedback-anticipation) and at the reward-outcome stage (including, feedback-locked delta, theta and beta power). Moreover, all of these EEG indices correlated with behavioral performance in the time-estimation task, suggesting their essential roles in learning and adjusting performance to maximize winnings in a reward-learning situation. Importantly, enhanced EEG power during Reward trials for 1) pre-feedback alpha suppression, 2) feedback-locked theta and 3) feedback-locked beta was associated with a greater preference for larger-but-delayed rewards. Results highlight the association between a stronger preference toward larger-but-delayed rewards and enhanced reward-processing. Moreover, our reward-processing EEG indices detail the specific stages of reward-processing where these associations occur. PMID:27477630

How Confident can we be in Flood Risk Assessments?

NASA Astrophysics Data System (ADS)

Merz, B.

2017-12-01

Flood risk management should be based on risk analyses quantifying the risk and its reduction for different risk reduction strategies. However, validating risk estimates by comparing model simulations with past observations is hardly possible, since the assessment typically encompasses extreme events and their impacts that have not been observed before. Hence, risk analyses are strongly based on assumptions and expert judgement. This situation opens the door for cognitive biases, such as `illusion of certainty', `overconfidence' or `recency bias'. Such biases operate specifically in complex situations with many factors involved, when uncertainty is high and events are probabilistic, or when close learning feedback loops are missing - aspects that all apply to risk analyses. This contribution discusses how confident we can be in flood risk assessments, and reflects about more rigorous approaches towards their validation.

General functioning predicts reward and punishment learning in schizophrenia.

PubMed

Somlai, Zsuzsanna; Moustafa, Ahmed A; Kéri, Szabolcs; Myers, Catherine E; Gluck, Mark A

2011-04-01

Previous studies investigating feedback-driven reinforcement learning in patients with schizophrenia have provided mixed results. In this study, we explored the clinical predictors of reward and punishment learning using a probabilistic classification learning task. Patients with schizophrenia (n=40) performed similarly to healthy controls (n=30) on the classification learning task. However, more severe negative and general symptoms were associated with lower reward-learning performance, whereas poorer general psychosocial functioning was correlated with both lower reward- and punishment-learning performances. Multiple linear regression analyses indicated that general psychosocial functioning was the only significant predictor of reinforcement learning performance when education, antipsychotic dose, and positive, negative and general symptoms were included in the analysis. These results suggest a close relationship between reinforcement learning and general psychosocial functioning in schizophrenia. Published by Elsevier B.V.

Probabilistic Learning in Junior High School: Investigation of Student Probabilistic Thinking Levels

NASA Astrophysics Data System (ADS)

Kurniasih, R.; Sujadi, I.

2017-09-01

This paper was to investigate level on students’ probabilistic thinking. Probabilistic thinking level is level of probabilistic thinking. Probabilistic thinking is thinking about probabilistic or uncertainty matter in probability material. The research’s subject was students in grade 8th Junior High School students. The main instrument is a researcher and a supporting instrument is probabilistic thinking skills test and interview guidelines. Data was analyzed using triangulation method. The results showed that the level of students probabilistic thinking before obtaining a teaching opportunity at the level of subjective and transitional. After the students’ learning level probabilistic thinking is changing. Based on the results of research there are some students who have in 8th grade level probabilistic thinking numerically highest of levels. Level of students’ probabilistic thinking can be used as a reference to make a learning material and strategy.

Eliciting expert opinion for economic models: an applied example.

PubMed

Leal, José; Wordsworth, Sarah; Legood, Rosa; Blair, Edward

2007-01-01

Expert opinion is considered as a legitimate source of information for decision-analytic modeling where required data are unavailable. Our objective was to develop a practical computer-based tool for eliciting expert opinion about the shape of the uncertainty distribution around individual model parameters. We first developed a prepilot survey with departmental colleagues to test a number of alternative approaches to eliciting opinions on the shape of the uncertainty distribution around individual parameters. This information was used to develop a survey instrument for an applied clinical example. This involved eliciting opinions from experts to inform a number of parameters involving Bernoulli processes in an economic model evaluating DNA testing for families with a genetic disease, hypertrophic cardiomyopathy. The experts were cardiologists, clinical geneticists, and laboratory scientists working with cardiomyopathy patient populations and DNA testing. Our initial prepilot work suggested that the more complex elicitation techniques advocated in the literature were difficult to use in practice. In contrast, our approach achieved a reasonable response rate (50%), provided logical answers, and was generally rated as easy to use by respondents. The computer software user interface permitted graphical feedback throughout the elicitation process. The distributions obtained were incorporated into the model, enabling the use of probabilistic sensitivity analysis. There is clearly a gap in the literature between theoretical elicitation techniques and tools that can be used in applied decision-analytic models. The results of this methodological study are potentially valuable for other decision analysts deriving expert opinion.

Dynamics of Team Reflexivity after Feedback

ERIC Educational Resources Information Center

Gabelica, Catherine; Van den Bossche, Piet; Segers, Mien; Gijselaers, Wim

2014-01-01

A great deal of work has been generated on feedback in teams and has shown that giving performance feedback to teams is not sufficient to improve performance. To achieve the potential of feedback, it is stated that teams need to proactively process this feedback and thus collectively evaluate their performance and strategies, look for…

Effects of Web-Based Feedback on Students' Learning

ERIC Educational Resources Information Center

van Kol, Simone; Rietz, Christian

2016-01-01

Feedback plays an important role in supporting students' learning process. Nonetheless, providing feedback is still rather unusual in higher education. Moreover, research on the design of ideal feedback as well as its effects is rare. In order to contribute to the development of this field, a web-based feedback system was implemented in a lecture…

Connecting Feedback, Classroom Research and Didaktik Perspectives

ERIC Educational Resources Information Center

Svanes, Ingvill Krogstad; Skagen, Kaare

2017-01-01

Feedback is frequently highlighted as a key contributor to students' learning. This literature study argues that the focus of some of the feedback literature appears too narrow to understand what is going on in a classroom. Parts of the feedback literature show the relationship between feedback and learning approximate to a process-product model…

Rethinking Feedback Practices in Higher Education: A Peer Review Perspective

ERIC Educational Resources Information Center

Nicol, David; Thomson, Avril; Breslin, Caroline

2014-01-01

Peer review is a reciprocal process whereby students produce feedback reviews on the work of peers and receive feedback reviews from peers on their own work. Prior research has primarily examined the learning benefits that result from the receipt of feedback reviews, with few studies specifically exploring the merits of producing feedback reviews…

Can corrective feedback improve recognition memory?

PubMed

Kantner, Justin; Lindsay, D Stephen

2010-06-01

An understanding of the effects of corrective feedback on recognition memory can inform both recognition theory and memory training programs, but few published studies have investigated the issue. Although the evidence to date suggests that feedback does not improve recognition accuracy, few studies have directly examined its effect on sensitivity, and fewer have created conditions that facilitate a feedback advantage by encouraging controlled processing at test. In Experiment 1, null effects of feedback were observed following both deep and shallow encoding of categorized study lists. In Experiment 2, feedback robustly influenced response bias by allowing participants to discern highly uneven base rates of old and new items, but sensitivity remained unaffected. In Experiment 3, a false-memory procedure, feedback failed to attenuate false recognition of critical lures. In Experiment 4, participants were unable to use feedback to learn a simple category rule separating old items from new items, despite the fact that feedback was of substantial benefit in a nearly identical categorization task. The recognition system, despite a documented ability to utilize controlled strategic or inferential decision-making processes, appears largely impenetrable to a benefit of corrective feedback.

Analytically tractable climate-carbon cycle feedbacks under 21st century anthropogenic forcing

NASA Astrophysics Data System (ADS)

Lade, Steven J.; Donges, Jonathan F.; Fetzer, Ingo; Anderies, John M.; Beer, Christian; Cornell, Sarah E.; Gasser, Thomas; Norberg, Jon; Richardson, Katherine; Rockström, Johan; Steffen, Will

2018-05-01

Changes to climate-carbon cycle feedbacks may significantly affect the Earth system's response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth system models. Here, we construct a stylised global climate-carbon cycle model, test its output against comprehensive Earth system models, and investigate the strengths of its climate-carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon cycle feedbacks and the operation of the carbon cycle. Specific results include that different feedback formalisms measure fundamentally the same climate-carbon cycle processes; temperature dependence of the solubility pump, biological pump, and CO2 solubility all contribute approximately equally to the ocean climate-carbon feedback; and concentration-carbon feedbacks may be more sensitive to future climate change than climate-carbon feedbacks. Simple models such as that developed here also provide workbenches for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the planetary boundaries, that are currently too uncertain to be included in comprehensive Earth system models.

Generating probabilistic Boolean networks from a prescribed transition probability matrix.

PubMed

Ching, W-K; Chen, X; Tsing, N-K

2009-11-01

Probabilistic Boolean networks (PBNs) have received much attention in modeling genetic regulatory networks. A PBN can be regarded as a Markov chain process and is characterised by a transition probability matrix. In this study, the authors propose efficient algorithms for constructing a PBN when its transition probability matrix is given. The complexities of the algorithms are also analysed. This is an interesting inverse problem in network inference using steady-state data. The problem is important as most microarray data sets are assumed to be obtained from sampling the steady-state.

Misfortune may be a blessing in disguise: Fairness perception and emotion modulate decision making.

PubMed

Liu, Hong-Hsiang; Hwang, Yin-Dir; Hsieh, Ming H; Hsu, Yung-Fong; Lai, Wen-Sung

2017-08-01

Fairness perception and equality during social interactions frequently elicit affective arousal and affect decision making. By integrating the dictator game and a probabilistic gambling task, this study aimed to investigate the effects of a negative experience induced by perceived unfairness on decision making using behavioral, model fitting, and electrophysiological approaches. Participants were randomly assigned to the neutral, harsh, or kind groups, which consisted of various asset allocation scenarios to induce different levels of perceived unfairness. The monetary gain was subsequently considered the initial asset in a negatively rewarded, probabilistic gambling task in which the participants were instructed to maintain as much asset as possible. Our behavioral results indicated that the participants in the harsh group exhibited increased levels of negative emotions but retained greater total game scores than the participants in the other two groups. Parameter estimation of a reinforcement learning model using a Bayesian approach indicated that these participants were more loss aversive and consistent in decision making. Data from simultaneous ERP recordings further demonstrated that these participants exhibited larger feedback-related negativity to unexpected outcomes in the gambling task, which suggests enhanced reward sensitivity and signaling of reward prediction error. Collectively, our study suggests that a negative experience may be an advantage in the modulation of reward-based decision making. © 2017 Society for Psychophysiological Research.

Cognitive flexibility impairment and reduced frontal cortex BDNF expression in the ouabain model of mania

PubMed Central

Amodeo, Dionisio A.; Grospe, Gena; Zang, Hui; Dwivedi, Yogesh; Ragozzino, Michael E.

2016-01-01

Central infusion of the Na+/K+-ATPase inhibitor, ouabain in rats serves as an animal model of mania because it leads to hyperactivity, as well as reproduces ion dysregulation and reduced BDNF levels similar to that observed in bipolar disorder. Bipolar disorder is also associated with cognitive inflexibility and working memory deficits. It is unknown whether ouabain treatment in rats leads to similar cognitive flexibility and working memory deficits. The present study examined the effects of an intracerebral ventricular infusion of ouabain in rats on spontaneous alternation, probabilistic reversal learning and BDNF expression levels in the frontal cortex. Ouabain treatment significantly increased locomotor activity, but did not affect alternation performance in a Y-maze. Ouabain treatment selectively impaired reversal learning in a spatial discrimination task using an 80/20 probabilistic reinforcement procedure. The reversal learning deficit in ouabain-treated rats resulted from an impaired ability to maintain a new choice pattern (increased regressive errors). Ouabain treatment also decreased sensitivity to negative feedback during the initial phase of reversal learning. Expression of BDNF mRNA and protein levels was downregulated in the frontal cortex which also negatively correlated with regressive errors. These findings suggest that the ouabain model of mania may be useful in understanding the neuropathophysiology that contributes to cognitive flexibility deficits and test potential treatments to alleviate cognitive deficits in bipolar disorder. PMID:27267245

Feedback loop compensates for rectifier nonlinearity

NASA Technical Reports Server (NTRS)

1966-01-01

Signal processing circuit with two negative feedback loops rectifies two sinusoidal signals which are 180 degrees out of phase and produces a single full-wave rectified output signal. Each feedback loop incorporates a feedback rectifier to compensate for the nonlinearity of the circuit.

Functional brain networks for learning predictive statistics.

PubMed

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

2017-08-18

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

Stereotype threat engenders neural attentional bias toward negative feedback to undermine performance.

PubMed

Forbes, Chad E; Leitner, Jordan B

2014-10-01

Stereotype threat, a situational pressure individuals experience when they fear confirming a negative group stereotype, engenders a cascade of physiological stress responses, negative appraisals, and performance monitoring processes that tax working memory resources necessary for optimal performance. Less is known, however, about how stereotype threat biases attentional processing in response to performance feedback, and how such attentional biases may undermine performance. Women received feedback on math problems in stereotype threatening compared to stereotype-neutral contexts while continuous EEG activity was recorded. Findings revealed that stereotype threatened women elicited larger midline P100 ERPs, increased phase locking between anterior cingulate cortex and dorsolateral prefrontal cortex (two regions integral for attentional processes), and increased power in left fusiform gyrus in response to negative feedback compared to positive feedback and women in stereotype-neutral contexts. Increased power in left fusiform gyrus in response to negative feedback predicted underperformance on the math task among stereotype threatened women only. Women in stereotype-neutral contexts exhibited the opposite trend. Findings suggest that in stereotype threatening contexts, neural networks integral for attention and working memory are biased toward negative, stereotype confirming feedback at very early speeds of information processing. This bias, in turn, plays a role in undermining performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Feedback in formative OSCEs: comparison between direct observation and video-based formats

PubMed Central

Junod Perron, Noëlle; Louis-Simonet, Martine; Cerutti, Bernard; Pfarrwaller, Eva; Sommer, Johanna; Nendaz, Mathieu

2016-01-01

Introduction Medical students at the Faculty of Medicine, University of Geneva, Switzerland, have the opportunity to practice clinical skills with simulated patients during formative sessions in preparation for clerkships. These sessions are given in two formats: 1) direct observation of an encounter followed by verbal feedback (direct feedback) and 2) subsequent review of the videotaped encounter by both student and supervisor (video-based feedback). The aim of the study was to evaluate whether content and process of feedback differed between both formats. Methods In 2013, all second- and third-year medical students and clinical supervisors involved in formative sessions were asked to take part in the study. A sample of audiotaped feedback sessions involving supervisors who gave feedback in both formats were analyzed (content and process of the feedback) using a 21-item feedback scale. Results Forty-eight audiotaped feedback sessions involving 12 supervisors were analyzed (2 direct and 2 video-based sessions per supervisor). When adjusted for the length of feedback, there were significant differences in terms of content and process between both formats; the number of communication skills and clinical reasoning items addressed were higher in the video-based format (11.29 vs. 7.71, p=0.002 and 3.71 vs. 2.04, p=0.010, respectively). Supervisors engaged students more actively during the video-based sessions than during direct feedback sessions (self-assessment: 4.00 vs. 3.17, p=0.007; active problem-solving: 3.92 vs. 3.42, p=0.009). Students made similar observations and tended to consider that the video feedback was more useful for improving some clinical skills. Conclusion Video-based feedback facilitates discussion of clinical reasoning, communication, and professionalism issues while at the same time actively engaging students. Different time and conceptual frameworks may explain observed differences. The choice of feedback format should depend on the educational goal. PMID:27834170

Feedback in formative OSCEs: comparison between direct observation and video-based formats.

PubMed

Junod Perron, Noëlle; Louis-Simonet, Martine; Cerutti, Bernard; Pfarrwaller, Eva; Sommer, Johanna; Nendaz, Mathieu

2016-01-01

Medical students at the Faculty of Medicine, University of Geneva, Switzerland, have the opportunity to practice clinical skills with simulated patients during formative sessions in preparation for clerkships. These sessions are given in two formats: 1) direct observation of an encounter followed by verbal feedback (direct feedback) and 2) subsequent review of the videotaped encounter by both student and supervisor (video-based feedback). The aim of the study was to evaluate whether content and process of feedback differed between both formats. In 2013, all second- and third-year medical students and clinical supervisors involved in formative sessions were asked to take part in the study. A sample of audiotaped feedback sessions involving supervisors who gave feedback in both formats were analyzed (content and process of the feedback) using a 21-item feedback scale. Forty-eight audiotaped feedback sessions involving 12 supervisors were analyzed (2 direct and 2 video-based sessions per supervisor). When adjusted for the length of feedback, there were significant differences in terms of content and process between both formats; the number of communication skills and clinical reasoning items addressed were higher in the video-based format (11.29 vs. 7.71, p= 0.002 and 3.71 vs. 2.04, p= 0.010, respectively). Supervisors engaged students more actively during the video-based sessions than during direct feedback sessions (self-assessment: 4.00 vs. 3.17, p= 0.007; active problem-solving: 3.92 vs. 3.42, p= 0.009). Students made similar observations and tended to consider that the video feedback was more useful for improving some clinical skills. Video-based feedback facilitates discussion of clinical reasoning, communication, and professionalism issues while at the same time actively engaging students. Different time and conceptual frameworks may explain observed differences. The choice of feedback format should depend on the educational goal.

Evaluating plant-soil feedback together with competition in a serpentine grassland.

PubMed

Casper, Brenda B; Castelli, Jeffrey P

2007-05-01

Plants can alter biotic and abiotic soil characteristics in ways that feedback to change the performance of that same plant species relative to co-occurring plants. Most evidence for this plant-soil feedback comes from greenhouse studies of potted plants, and consequently, little is known about the importance of feedback in relation to other biological processes known to structure plant communities, such as plant-plant competition. In a field experiment with three C4 grasses, negative feedback was expressed through reduced survival and shoot biomass when seedlings were planted within existing clumps of conspecifics compared with clumps of heterospecifics. However, the combined effects of feedback and competition were species-specific. Only Andropogon gerardii exhibited feedback when competition with the clumps was allowed. For Sorghastrum nutans, strong interspecific competition eliminated the feedback expressed in the absence of competition, and Schizachyrium scoparium showed no feedback at all. That arbuscular mycorrhizal (AM) fungi may play a role in the feedback was indicated by higher AM root colonization with conspecific plant neighbours. We suggest that feedback and competition should not be viewed as entirely separate processes and that their importance in structuring plant communities cannot be judged in isolation from each other.

Teaching the Art and Craft of Giving and Receiving Feedback

ERIC Educational Resources Information Center

Harms, Patricia L.; Roebuck, Deborah Britt

2010-01-01

In the workplace, the process of evaluating and discussing the performance of both employees and managers is referred to as feedback. The process generally involves a discussion of the individual's strengths or weaknesses, with suggestions on how to improve upon weaknesses. Feedback aligns workplace behavior with the overall goals of a team or an…

E-Feedback as a Scaffolding Teaching Strategy in the Online Language Classroom

ERIC Educational Resources Information Center

Alharbi, Wael

2017-01-01

Feedback plays an important role in the student learning process as it gives the learners greater insight into what they have actually done to arrive at an outcome. The importance of providing learners with feedback during the learning process comes from the fact that it highlights the difference between the intended outcome and the actual…

Quantifying the Relative Contributions of Divisive and Subtractive Feedback to Rhythm Generation

PubMed Central

Tabak, Joël; Rinzel, John; Bertram, Richard

2011-01-01

Biological systems are characterized by a high number of interacting components. Determining the role of each component is difficult, addressed here in the context of biological oscillations. Rhythmic behavior can result from the interplay of positive feedback that promotes bistability between high and low activity, and slow negative feedback that switches the system between the high and low activity states. Many biological oscillators include two types of negative feedback processes: divisive (decreases the gain of the positive feedback loop) and subtractive (increases the input threshold) that both contribute to slowly move the system between the high- and low-activity states. Can we determine the relative contribution of each type of negative feedback process to the rhythmic activity? Does one dominate? Do they control the active and silent phase equally? To answer these questions we use a neural network model with excitatory coupling, regulated by synaptic depression (divisive) and cellular adaptation (subtractive feedback). We first attempt to apply standard experimental methodologies: either passive observation to correlate the variations of a variable of interest to system behavior, or deletion of a component to establish whether a component is critical for the system. We find that these two strategies can lead to contradictory conclusions, and at best their interpretive power is limited. We instead develop a computational measure of the contribution of a process, by evaluating the sensitivity of the active (high activity) and silent (low activity) phase durations to the time constant of the process. The measure shows that both processes control the active phase, in proportion to their speed and relative weight. However, only the subtractive process plays a major role in setting the duration of the silent phase. This computational method can be used to analyze the role of negative feedback processes in a wide range of biological rhythms. PMID:21533065

a Generic Probabilistic Model and a Hierarchical Solution for Sensor Localization in Noisy and Restricted Conditions

NASA Astrophysics Data System (ADS)

Ji, S.; Yuan, X.

2016-06-01

A generic probabilistic model, under fundamental Bayes' rule and Markov assumption, is introduced to integrate the process of mobile platform localization with optical sensors. And based on it, three relative independent solutions, bundle adjustment, Kalman filtering and particle filtering are deduced under different and additional restrictions. We want to prove that first, Kalman filtering, may be a better initial-value supplier for bundle adjustment than traditional relative orientation in irregular strips and networks or failed tie-point extraction. Second, in high noisy conditions, particle filtering can act as a bridge for gap binding when a large number of gross errors fail a Kalman filtering or a bundle adjustment. Third, both filtering methods, which help reduce the error propagation and eliminate gross errors, guarantee a global and static bundle adjustment, who requires the strictest initial values and control conditions. The main innovation is about the integrated processing of stochastic errors and gross errors in sensor observations, and the integration of the three most used solutions, bundle adjustment, Kalman filtering and particle filtering into a generic probabilistic localization model. The tests in noisy and restricted situations are designed and examined to prove them.

Probabilistic TSUnami Hazard MAPS for the NEAM Region: The TSUMAPS-NEAM Project

NASA Astrophysics Data System (ADS)

Basili, R.; Babeyko, A. Y.; Baptista, M. A.; Ben Abdallah, S.; Canals, M.; El Mouraouah, A.; Harbitz, C. B.; Ibenbrahim, A.; Lastras, G.; Lorito, S.; Løvholt, F.; Matias, L. M.; Omira, R.; Papadopoulos, G. A.; Pekcan, O.; Nmiri, A.; Selva, J.; Yalciner, A. C.

2016-12-01

As global awareness of tsunami hazard and risk grows, the North-East Atlantic, the Mediterranean, and connected Seas (NEAM) region still lacks a thorough probabilistic tsunami hazard assessment. The TSUMAPS-NEAM project aims to fill this gap in the NEAM region by 1) producing the first region-wide long-term homogenous Probabilistic Tsunami Hazard Assessment (PTHA) from earthquake sources, and by 2) triggering a common tsunami risk management strategy. The specific objectives of the project are tackled by the following four consecutive actions: 1) Conduct a state-of-the-art, standardized, and updatable PTHA with full uncertainty treatment; 2) Review the entire process with international experts; 3) Produce the PTHA database, with documentation of the entire hazard assessment process; and 4) Publicize the results through an awareness raising and education phase, and a capacity building phase. This presentation will illustrate the project layout, summarize its current status of advancement and prospective results, and outline its connections with similar initiatives in the international context. The TSUMAPS-NEAM Project (http://www.tsumaps-neam.eu/) is co-financed by the European Union Civil Protection Mechanism, Agreement Number: ECHO/SUB/2015/718568/PREV26.

Probabilistic TSUnami Hazard MAPS for the NEAM Region: The TSUMAPS-NEAM Project

NASA Astrophysics Data System (ADS)

Basili, Roberto; Babeyko, Andrey Y.; Hoechner, Andreas; Baptista, Maria Ana; Ben Abdallah, Samir; Canals, Miquel; El Mouraouah, Azelarab; Bonnevie Harbitz, Carl; Ibenbrahim, Aomar; Lastras, Galderic; Lorito, Stefano; Løvholt, Finn; Matias, Luis Manuel; Omira, Rachid; Papadopoulos, Gerassimos A.; Pekcan, Onur; Nmiri, Abdelwaheb; Selva, Jacopo; Yalciner, Ahmet C.; Thio, Hong K.

2017-04-01

As global awareness of tsunami hazard and risk grows, the North-East Atlantic, the Mediterranean, and connected Seas (NEAM) region still lacks a thorough probabilistic tsunami hazard assessment. The TSUMAPS-NEAM project aims to fill this gap in the NEAM region by 1) producing the first region-wide long-term homogenous Probabilistic Tsunami Hazard Assessment (PTHA) from earthquake sources, and by 2) triggering a common tsunami risk management strategy. The specific objectives of the project are tackled by the following four consecutive actions: 1) Conduct a state-of-the-art, standardized, and updatable PTHA with full uncertainty treatment; 2) Review the entire process with international experts; 3) Produce the PTHA database, with documentation of the entire hazard assessment process; and 4) Publicize the results through an awareness raising and education phase, and a capacity building phase. This presentation will illustrate the project layout, summarize its current status of advancement including the firs preliminary release of the assessment, and outline its connections with similar initiatives in the international context. The TSUMAPS-NEAM Project (http://www.tsumaps-neam.eu/) is co-financed by the European Union Civil Protection Mechanism, Agreement Number: ECHO/SUB/2015/718568/PREV26.

Modelling Feedback in Virtual Patients: An Iterative Approach.

PubMed

Stathakarou, Natalia; Kononowicz, Andrzej A; Henningsohn, Lars; McGrath, Cormac

2018-01-01

Virtual Patients (VPs) offer learners the opportunity to practice clinical reasoning skills and have recently been integrated in Massive Open Online Courses (MOOCs). Feedback is a central part of a branched VP, allowing the learner to reflect on the consequences of their decisions and actions. However, there is insufficient guidance on how to design feedback models within VPs and especially in the context of their application in MOOCs. In this paper, we share our experiences from building a feedback model for a bladder cancer VP in a Urology MOOC, following an iterative process in three steps. Our results demonstrate how we can systematize the process of improving the quality of VP components by the application of known literature frameworks and extend them with a feedback module. We illustrate the design and re-design process and exemplify with content from our VP. Our results can act as starting point for discussions on modelling feedback in VPs and invite future research on the topic.

Incorporation of feedback during beat synchronization is an index of neural maturation and reading skills.

PubMed

Woodruff Carr, Kali; Fitzroy, Ahren B; Tierney, Adam; White-Schwoch, Travis; Kraus, Nina

2017-01-01

Speech communication involves integration and coordination of sensory perception and motor production, requiring precise temporal coupling. Beat synchronization, the coordination of movement with a pacing sound, can be used as an index of this sensorimotor timing. We assessed adolescents' synchronization and capacity to correct asynchronies when given online visual feedback. Variability of synchronization while receiving feedback predicted phonological memory and reading sub-skills, as well as maturation of cortical auditory processing; less variable synchronization during the presence of feedback tracked with maturation of cortical processing of sound onsets and resting gamma activity. We suggest the ability to incorporate feedback during synchronization is an index of intentional, multimodal timing-based integration in the maturing adolescent brain. Precision of temporal coding across modalities is important for speech processing and literacy skills that rely on dynamic interactions with sound. Synchronization employing feedback may prove useful as a remedial strategy for individuals who struggle with timing-based language learning impairments. Copyright © 2016 Elsevier Inc. All rights reserved.

Probabilistic confidence for decisions based on uncertain reliability estimates

NASA Astrophysics Data System (ADS)

Reid, Stuart G.

2013-05-01

Reliability assessments are commonly carried out to provide a rational basis for risk-informed decisions concerning the design or maintenance of engineering systems and structures. However, calculated reliabilities and associated probabilities of failure often have significant uncertainties associated with the possible estimation errors relative to the 'true' failure probabilities. For uncertain probabilities of failure, a measure of 'probabilistic confidence' has been proposed to reflect the concern that uncertainty about the true probability of failure could result in a system or structure that is unsafe and could subsequently fail. The paper describes how the concept of probabilistic confidence can be applied to evaluate and appropriately limit the probabilities of failure attributable to particular uncertainties such as design errors that may critically affect the dependability of risk-acceptance decisions. This approach is illustrated with regard to the dependability of structural design processes based on prototype testing with uncertainties attributable to sampling variability.

Classification of Company Performance using Weighted Probabilistic Neural Network

NASA Astrophysics Data System (ADS)

Yasin, Hasbi; Waridi Basyiruddin Arifin, Adi; Warsito, Budi

2018-05-01

Classification of company performance can be judged by looking at its financial status, whether good or bad state. Classification of company performance can be achieved by some approach, either parametric or non-parametric. Neural Network is one of non-parametric methods. One of Artificial Neural Network (ANN) models is Probabilistic Neural Network (PNN). PNN consists of four layers, i.e. input layer, pattern layer, addition layer, and output layer. The distance function used is the euclidean distance and each class share the same values as their weights. In this study used PNN that has been modified on the weighting process between the pattern layer and the addition layer by involving the calculation of the mahalanobis distance. This model is called the Weighted Probabilistic Neural Network (WPNN). The results show that the company's performance modeling with the WPNN model has a very high accuracy that reaches 100%.

Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference

PubMed Central

Campbell, Kieran R.

2016-01-01

Single cell gene expression profiling can be used to quantify transcriptional dynamics in temporal processes, such as cell differentiation, using computational methods to label each cell with a ‘pseudotime’ where true time series experimentation is too difficult to perform. However, owing to the high variability in gene expression between individual cells, there is an inherent uncertainty in the precise temporal ordering of the cells. Pre-existing methods for pseudotime estimation have predominantly given point estimates precluding a rigorous analysis of the implications of uncertainty. We use probabilistic modelling techniques to quantify pseudotime uncertainty and propagate this into downstream differential expression analysis. We demonstrate that reliance on a point estimate of pseudotime can lead to inflated false discovery rates and that probabilistic approaches provide greater robustness and measures of the temporal resolution that can be obtained from pseudotime inference. PMID:27870852

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

PubMed Central

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions. PMID:26089862

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

PubMed

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

Probabilistic performance-assessment modeling of the mixed waste landfill at Sandia National Laboratories.

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

Peace, Gerald; Goering, Timothy James; Miller, Mark Laverne

2007-01-01

A probabilistic performance assessment has been conducted to evaluate the fate and transport of radionuclides (americium-241, cesium-137, cobalt-60, plutonium-238, plutonium-239, radium-226, radon-222, strontium-90, thorium-232, tritium, uranium-238), heavy metals (lead and cadmium), and volatile organic compounds (VOCs) at the Mixed Waste Landfill (MWL). Probabilistic analyses were performed to quantify uncertainties inherent in the system and models for a 1,000-year period, and sensitivity analyses were performed to identify parameters and processes that were most important to the simulated performance metrics. Comparisons between simulated results and measured values at the MWL were made to gain confidence in the models and perform calibrations whenmore » data were available. In addition, long-term monitoring requirements and triggers were recommended based on the results of the quantified uncertainty and sensitivity analyses.« less

Exact and Approximate Probabilistic Symbolic Execution

NASA Technical Reports Server (NTRS)

Luckow, Kasper; Pasareanu, Corina S.; Dwyer, Matthew B.; Filieri, Antonio; Visser, Willem

2014-01-01

Probabilistic software analysis seeks to quantify the likelihood of reaching a target event under uncertain environments. Recent approaches compute probabilities of execution paths using symbolic execution, but do not support nondeterminism. Nondeterminism arises naturally when no suitable probabilistic model can capture a program behavior, e.g., for multithreading or distributed systems. In this work, we propose a technique, based on symbolic execution, to synthesize schedulers that resolve nondeterminism to maximize the probability of reaching a target event. To scale to large systems, we also introduce approximate algorithms to search for good schedulers, speeding up established random sampling and reinforcement learning results through the quantification of path probabilities based on symbolic execution. We implemented the techniques in Symbolic PathFinder and evaluated them on nondeterministic Java programs. We show that our algorithms significantly improve upon a state-of- the-art statistical model checking algorithm, originally developed for Markov Decision Processes.

Probabilistic graphlet transfer for photo cropping.

PubMed

Zhang, Luming; Song, Mingli; Zhao, Qi; Liu, Xiao; Bu, Jiajun; Chen, Chun

2013-02-01

As one of the most basic photo manipulation processes, photo cropping is widely used in the printing, graphic design, and photography industries. In this paper, we introduce graphlets (i.e., small connected subgraphs) to represent a photo's aesthetic features, and propose a probabilistic model to transfer aesthetic features from the training photo onto the cropped photo. In particular, by segmenting each photo into a set of regions, we construct a region adjacency graph (RAG) to represent the global aesthetic feature of each photo. Graphlets are then extracted from the RAGs, and these graphlets capture the local aesthetic features of the photos. Finally, we cast photo cropping as a candidate-searching procedure on the basis of a probabilistic model, and infer the parameters of the cropped photos using Gibbs sampling. The proposed method is fully automatic. Subjective evaluations have shown that it is preferred over a number of existing approaches.

CARES/Life Used for Probabilistic Characterization of MEMS Pressure Sensor Membranes

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.

2002-01-01

Microelectromechanical systems (MEMS) devices are typically made from brittle materials such as silicon using traditional semiconductor manufacturing techniques. They can be etched (or micromachined) from larger structures or can be built up with material deposition processes. Maintaining dimensional control and consistent mechanical properties is considerably more difficult for MEMS because feature size is on the micrometer scale. Therefore, the application of probabilistic design methodology becomes necessary for MEMS. This was demonstrated at the NASA Glenn Research Center and Case Western Reserve University in an investigation that used the NASA-developed CARES/Life brittle material design program to study the probabilistic fracture strength behavior of single-crystal SiC, polycrystalline SiC, and amorphous Si3N4 pressurized 1-mm-square thin-film diaphragms. These materials are of interest because of their superior high-temperature characteristics, which are desirable for harsh environment applications such as turbine engine and rocket propulsion system hot sections.

Blocked versus randomized presentation modes differentially modulate feedback-related negativity and P3b amplitudes

PubMed Central

Pfabigan, Daniela M.; Zeiler, Michael; Lamm, Claus; Sailer, Uta

2014-01-01

Objective Electrophysiological studies on feedback processing typically use a wide range of feedback stimuli which might not always be comparable. The current study investigated whether two indicators of feedback processing – feedback-related negativity (FRN) and P3b – differ for feedback stimuli with explicit (facial expressions) or assigned valence information (symbols). In addition, we assessed whether presenting feedback in either a trial-by-trial or a block-wise fashion affected these ERPs. Methods EEG was recorded in three experiments while participants performed a time estimation task and received two different types of performance feedback. Results Only P3b amplitudes varied consistently in response to feedback type for both presentation types. Moreover, the blocked feedback type presentation yielded more distinct FRN peaks, higher effect sizes, and a significant relation between FRN amplitudes and behavioral task performance measures. Conclusion Both stimulus type and presentation mode may provoke systematic changes in feedback-related ERPs. The current findings point at important potential confounds that need to be controlled for when designing FRN or P3b studies. Significance Studies investigating P3b amplitudes using mixed types of stimuli have to be interpreted with caution. Furthermore, we suggest implementing a blocked presentation format when presenting different feedback types within the same experiment. PMID:24144779

Telling good from bad news: ADHD differentially affects processing of positive and negative feedback during guessing.

PubMed

van Meel, Catharina S; Oosterlaan, Jaap; Heslenfeld, Dirk J; Sergeant, Joseph A

2005-01-01

Neuroimaging studies on ADHD suggest abnormalities in brain regions associated with decision-making and reward processing such as the anterior cingulate cortex (ACC) and orbitofrontal cortex. Recently, event-related potential (ERP) studies demonstrated that the ACC is involved in processing feedback signals during guessing and gambling. The resulting negative deflection, the 'feedback-related negativity' (FRN) has been interpreted as reflecting an error in reward prediction. In the present study, ERPs elicited by positive and negative feedback were recorded in children with ADHD and normal controls during guessing. 'Correct' and 'incorrect' guesses resulted in respectively monetary gains and losses. The FRN amplitude to losses was more pronounced in the ADHD group than in normal controls. Positive and negative feedback differentially affected long latency components in the ERP waveforms of normal controls, but not ADHD children. These later deflections might be related to further emotional or strategic processing. The present findings suggest an enhanced sensitivity to unfavourable outcomes in children with ADHD, probably due to abnormalities in mesolimbic reward circuits. In addition, further processing, such as affective evaluation and the assessment of future consequences of the feedback signal seems to be altered in ADHD. These results may further help understanding the neural basis of decision-making deficits in ADHD.

Probabilistic modeling of percutaneous absorption for risk-based exposure assessments and transdermal drug delivery.

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

Ho, Clifford Kuofei

Chemical transport through human skin can play a significant role in human exposure to toxic chemicals in the workplace, as well as to chemical/biological warfare agents in the battlefield. The viability of transdermal drug delivery also relies on chemical transport processes through the skin. Models of percutaneous absorption are needed for risk-based exposure assessments and drug-delivery analyses, but previous mechanistic models have been largely deterministic. A probabilistic, transient, three-phase model of percutaneous absorption of chemicals has been developed to assess the relative importance of uncertain parameters and processes that may be important to risk-based assessments. Penetration routes through the skinmore » that were modeled include the following: (1) intercellular diffusion through the multiphase stratum corneum; (2) aqueous-phase diffusion through sweat ducts; and (3) oil-phase diffusion through hair follicles. Uncertainty distributions were developed for the model parameters, and a Monte Carlo analysis was performed to simulate probability distributions of mass fluxes through each of the routes. Sensitivity analyses using stepwise linear regression were also performed to identify model parameters that were most important to the simulated mass fluxes at different times. This probabilistic analysis of percutaneous absorption (PAPA) method has been developed to improve risk-based exposure assessments and transdermal drug-delivery analyses, where parameters and processes can be highly uncertain.« less

Effects of Oxytocin and Vasopressin on Preferential Brain Responses to Negative Social Feedback.

PubMed

Gozzi, Marta; Dashow, Erica M; Thurm, Audrey; Swedo, Susan E; Zink, Caroline F

2017-06-01

Receiving negative social feedback can be detrimental to emotional, cognitive, and physical well-being, and fear of negative social feedback is a prominent feature of mental illnesses that involve social anxiety. A large body of evidence has implicated the neuropeptides oxytocin and vasopressin in the modulation of human neural activity underlying social cognition, including negative emotion processing; however, the influence of oxytocin and vasopressin on neural activity elicited during negative social evaluation remains unknown. Here 21 healthy men underwent functional magnetic resonance imaging in a double-blind, placebo-controlled, crossover design to determine how intranasally administered oxytocin and vasopressin modulated neural activity when receiving negative feedback on task performance from a study investigator. We found that under placebo, a preferential response to negative social feedback compared with positive social feedback was evoked in brain regions putatively involved in theory of mind (temporoparietal junction), pain processing (anterior insula and supplementary motor area), and identification of emotionally important visual cues in social perception (right fusiform). These activations weakened with oxytocin and vasopressin administration such that neural responses to receiving negative social feedback were not significantly greater than positive social feedback. Our results show effects of both oxytocin and vasopressin on the brain network involved in negative social feedback, informing the possible use of a pharmacological approach targeting these regions in multiple disorders with impairments in social information processing.

Event-related potentials reflect impaired temporal interval learning following haloperidol administration.

PubMed

Forster, Sarah E; Zirnheld, Patrick; Shekhar, Anantha; Steinhauer, Stuart R; O'Donnell, Brian F; Hetrick, William P

2017-09-01

Signals carried by the mesencephalic dopamine system and conveyed to anterior cingulate cortex are critically implicated in probabilistic reward learning and performance monitoring. A common evaluative mechanism purportedly subserves both functions, giving rise to homologous medial frontal negativities in feedback- and response-locked event-related brain potentials (the feedback-related negativity (FRN) and the error-related negativity (ERN), respectively), reflecting dopamine-dependent prediction error signals to unexpectedly negative events. Consistent with this model, the dopamine receptor antagonist, haloperidol, attenuates the ERN, but effects on FRN have not yet been evaluated. ERN and FRN were recorded during a temporal interval learning task (TILT) following randomized, double-blind administration of haloperidol (3 mg; n = 18), diphenhydramine (an active control for haloperidol; 25 mg; n = 20), or placebo (n = 21) to healthy controls. Centroparietal positivities, the Pe and feedback-locked P300, were also measured and correlations between ERP measures and behavioral indices of learning, overall accuracy, and post-error compensatory behavior were evaluated. We hypothesized that haloperidol would reduce ERN and FRN, but that ERN would uniquely track automatic, error-related performance adjustments, while FRN would be associated with learning and overall accuracy. As predicted, ERN was reduced by haloperidol and in those exhibiting less adaptive post-error performance; however, these effects were limited to ERNs following fast timing errors. In contrast, the FRN was not affected by drug condition, although increased FRN amplitude was associated with improved accuracy. Significant drug effects on centroparietal positivities were also absent. Our results support a functional and neurobiological dissociation between the ERN and FRN.

The role of GABAB receptors in human reinforcement learning.

PubMed

Ort, Andres; Kometer, Michael; Rohde, Judith; Seifritz, Erich; Vollenweider, Franz X

2014-10-01

Behavioral evidence from human studies suggests that the γ-aminobutyric acid type B receptor (GABAB receptor) agonist baclofen modulates reinforcement learning and reduces craving in patients with addiction spectrum disorders. However, in contrast to the well established role of dopamine in reinforcement learning, the mechanisms by which the GABAB receptor influences reinforcement learning in humans remain completely unknown. To further elucidate this issue, a cross-over, double-blind, placebo-controlled study was performed in healthy human subjects (N=15) to test the effects of baclofen (20 and 50mg p.o.) on probabilistic reinforcement learning. Outcomes were the feedback-induced P2 component of the event-related potential, the feedback-related negativity, and the P300 component of the event-related potential. Baclofen produced a reduction of P2 amplitude over the course of the experiment, but did not modulate the feedback-related negativity. Furthermore, there was a trend towards increased learning after baclofen administration relative to placebo over the course of the experiment. The present results extend previous theories of reinforcement learning, which focus on the importance of mesolimbic dopamine signaling, and indicate that stimulation of cortical GABAB receptors in a fronto-parietal network leads to better attentional allocation in reinforcement learning. This observation is a first step in our understanding of how baclofen may improve reinforcement learning in healthy subjects. Further studies with bigger sample sizes are needed to corroborate this conclusion and furthermore, test this effect in patients with addiction spectrum disorder. Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.

Effect of 3basic life support training programs in future primary school teachers. A quasi-experimental design.

PubMed

Navarro-Patón, R; Freire-Tellado, M; Basanta-Camiño, S; Barcala-Furelos, R; Arufe-Giraldez, V; Rodriguez-Fernández, J E

2018-05-01

To evaluate the learning of basic life support (BLS) measures on the part of laypersons after 3different teaching programs. A quasi-experimental before-after study involving a non-probabilistic sample without a control group was carried out. Primary school teacher students from the University of Santiago (Spain). A total of 124 students (68.8% women and 31.2% men) aged 20-39 years (M=22.23; SD=3.79), with no previous knowledge of BLS, were studied. Three teaching programs were used: a traditional course, an audio-visual approach and feedback devices. Chest compressions as sole cardiopulmonary resuscitation skill evaluation: average compression depth, compression rate, chest recoil percentage and percentage of correct compressions. Automated external defibrillator: time needed to apply a shock before and after the course. There were significant differences in the results obtained after 2minutes of chest compressions, depending on the training program received, with feedback devices having a clear advantage referred to average compression depth (p<0.001), compression rate (p<0.001), chest recoil percentage (p<0.001) and percentage of correct compressions (p<0.001). Regarding automated external defibrillator, statistically significant differences were found in T after (p=0.025). The teaching course using feedback devices obtained the best results in terms of the quality of chest compressions, followed by the traditional course and audio-visual approach. These favorable results were present in both men and women. All 3teaching methods reached the goal of reducing defibrillation time. Copyright © 2017 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

Probabilistic Inference: Task Dependency and Individual Differences of Probability Weighting Revealed by Hierarchical Bayesian Modeling

PubMed Central

Boos, Moritz; Seer, Caroline; Lange, Florian; Kopp, Bruno

2016-01-01

Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision. PMID:27303323

Probabilistic inversion of expert assessments to inform projections about Antarctic ice sheet responses

PubMed Central

Wong, Tony E.; Keller, Klaus

2017-01-01

The response of the Antarctic ice sheet (AIS) to changing global temperatures is a key component of sea-level projections. Current projections of the AIS contribution to sea-level changes are deeply uncertain. This deep uncertainty stems, in part, from (i) the inability of current models to fully resolve key processes and scales, (ii) the relatively sparse available data, and (iii) divergent expert assessments. One promising approach to characterizing the deep uncertainty stemming from divergent expert assessments is to combine expert assessments, observations, and simple models by coupling probabilistic inversion and Bayesian inversion. Here, we present a proof-of-concept study that uses probabilistic inversion to fuse a simple AIS model and diverse expert assessments. We demonstrate the ability of probabilistic inversion to infer joint prior probability distributions of model parameters that are consistent with expert assessments. We then confront these inferred expert priors with instrumental and paleoclimatic observational data in a Bayesian inversion. These additional constraints yield tighter hindcasts and projections. We use this approach to quantify how the deep uncertainty surrounding expert assessments affects the joint probability distributions of model parameters and future projections. PMID:29287095

Event-Based Media Enrichment Using an Adaptive Probabilistic Hypergraph Model.

PubMed

Liu, Xueliang; Wang, Meng; Yin, Bao-Cai; Huet, Benoit; Li, Xuelong

2015-11-01

Nowadays, with the continual development of digital capture technologies and social media services, a vast number of media documents are captured and shared online to help attendees record their experience during events. In this paper, we present a method combining semantic inference and multimodal analysis for automatically finding media content to illustrate events using an adaptive probabilistic hypergraph model. In this model, media items are taken as vertices in the weighted hypergraph and the task of enriching media to illustrate events is formulated as a ranking problem. In our method, each hyperedge is constructed using the K-nearest neighbors of a given media document. We also employ a probabilistic representation, which assigns each vertex to a hyperedge in a probabilistic way, to further exploit the correlation among media data. Furthermore, we optimize the hypergraph weights in a regularization framework, which is solved as a second-order cone problem. The approach is initiated by seed media and then used to rank the media documents using a transductive inference process. The results obtained from validating the approach on an event dataset collected from EventMedia demonstrate the effectiveness of the proposed approach.

ProbCD: enrichment analysis accounting for categorization uncertainty.

PubMed

Vêncio, Ricardo Z N; Shmulevich, Ilya

2007-10-12

As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test. We developed an open-source R-based software to deal with probabilistic categorical data analysis, ProbCD, that does not require a static contingency table. The contingency table for the enrichment problem is built using the expectation of a Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created to allow usage by non-programmers and is available at: http://xerad.systemsbiology.net/ProbCD/. We present an analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques and (ii) probabilistic gene annotation.

Probabilistic distributions of pinhole defects in atomic layer deposited films on polymeric substrates

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

Yersak, Alexander S., E-mail: alexander.yersak@colorado.edu; Lee, Yung-Cheng

Pinhole defects in atomic layer deposition (ALD) coatings were measured in an area of 30 cm{sup 2} in an ALD reactor, and these defects were represented by a probabilistic cluster model instead of a single defect density value with number of defects over area. With the probabilistic cluster model, the pinhole defects were simulated over a manufacturing scale surface area of ∼1 m{sup 2}. Large-area pinhole defect simulations were used to develop an improved and enhanced design method for ALD-based devices. A flexible thermal ground plane (FTGP) device requiring ALD hermetic coatings was used as an example. Using a single defectmore » density value, it was determined that for an application with operation temperatures higher than 60 °C, the FTGP device would not be possible. The new probabilistic cluster model shows that up to 40.3% of the FTGP would be acceptable. With this new approach the manufacturing yield of ALD-enabled or other thin film based devices with different design configurations can be determined. It is important to guide process optimization and control and design for manufacturability.« less

A Probabilistic Design Method Applied to Smart Composite Structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1995-01-01

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

Combined contributions of feedforward and feedback inputs to bottom-up attention

PubMed Central

Khorsand, Peyman; Moore, Tirin; Soltani, Alireza

2015-01-01

In order to deal with a large amount of information carried by visual inputs entering the brain at any given point in time, the brain swiftly uses the same inputs to enhance processing in one part of visual field at the expense of the others. These processes, collectively called bottom-up attentional selection, are assumed to solely rely on feedforward processing of the external inputs, as it is implied by the nomenclature. Nevertheless, evidence from recent experimental and modeling studies points to the role of feedback in bottom-up attention. Here, we review behavioral and neural evidence that feedback inputs are important for the formation of signals that could guide attentional selection based on exogenous inputs. Moreover, we review results from a modeling study elucidating mechanisms underlying the emergence of these signals in successive layers of neural populations and how they depend on feedback from higher visual areas. We use these results to interpret and discuss more recent findings that can further unravel feedforward and feedback neural mechanisms underlying bottom-up attention. We argue that while it is descriptively useful to separate feedforward and feedback processes underlying bottom-up attention, these processes cannot be mechanistically separated into two successive stages as they occur at almost the same time and affect neural activity within the same brain areas using similar neural mechanisms. Therefore, understanding the interaction and integration of feedforward and feedback inputs is crucial for better understanding of bottom-up attention. PMID:25784883

Marginally perceptible outcome feedback, motor learning and implicit processes.

PubMed

Masters, Rich S W; Maxwell, Jon P; Eves, Frank F

2009-09-01

Participants struck 500 golf balls to a concealed target. Outcome feedback was presented at the subjective or objective threshold of awareness of each participant or at a supraliminal threshold. Participants who received fully perceptible (supraliminal) feedback learned to strike the ball onto the target, as did participants who received feedback that was only marginally perceptible (subjective threshold). Participants who received feedback that was not perceptible (objective threshold) showed no learning. Upon transfer to a condition in which the target was unconcealed, performance increased in both the subjective and the objective threshold condition, but decreased in the supraliminal condition. In all three conditions, participants reported minimal declarative knowledge of their movements, suggesting that deliberate hypothesis testing about how best to move in order to perform the motor task successfully was disrupted by the impoverished disposition of the visual outcome feedback. It was concluded that sub-optimally perceptible visual feedback evokes implicit processes.

The strategic control of prospective memory monitoring in response to complex and probabilistic contextual cues.

PubMed

Bugg, Julie M; Ball, B Hunter

2017-07-01

Participants use simple contextual cues to reduce deployment of costly monitoring processes in contexts in which prospective memory (PM) targets are not expected. This study investigated whether this strategic monitoring pattern is observed in response to complex and probabilistic contextual cues. Participants performed a lexical decision task in which words or nonwords were presented in upper or lower locations on screen. The specific condition was informed that PM targets ("tor" syllable) would occur only in words in the upper location, whereas the nonspecific condition was informed that targets could occur in any location or word type. Context was blocked such that word type and location changed every 8 trials. In Experiment 1, the specific condition used the complex contextual cue to reduce monitoring in unexpected contexts relative to the nonspecific condition. This pattern largely was not evidenced when the complex contextual cue was probabilistic (Experiment 2). Experiment 3 confirmed that strategic monitoring is observed for a complex cue that is deterministic, but not one that is probabilistic. Additionally, Experiments 1 and 3 demonstrated a disadvantage associated with strategic monitoring-namely, that the specific condition was less likely to respond to a PM target in an unexpected context. Experiment 3 provided evidence that this disadvantage is attributable to impaired noticing of the target. The novel findings suggest use of a complex contextual cue per se is not a boundary condition for the strategic, context-specific allocation of monitoring processes to support prospective remembering; however, strategic monitoring is constrained by the predictive utility of the complex contextual cue.

Construction of a Calibrated Probabilistic Classification Catalog: Application to 50k Variable Sources in the All-Sky Automated Survey

NASA Astrophysics Data System (ADS)

Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Brink, Henrik; Crellin-Quick, Arien

2012-12-01

With growing data volumes from synoptic surveys, astronomers necessarily must become more abstracted from the discovery and introspection processes. Given the scarcity of follow-up resources, there is a particularly sharp onus on the frameworks that replace these human roles to provide accurate and well-calibrated probabilistic classification catalogs. Such catalogs inform the subsequent follow-up, allowing consumers to optimize the selection of specific sources for further study and permitting rigorous treatment of classification purities and efficiencies for population studies. Here, we describe a process to produce a probabilistic classification catalog of variability with machine learning from a multi-epoch photometric survey. In addition to producing accurate classifications, we show how to estimate calibrated class probabilities and motivate the importance of probability calibration. We also introduce a methodology for feature-based anomaly detection, which allows discovery of objects in the survey that do not fit within the predefined class taxonomy. Finally, we apply these methods to sources observed by the All-Sky Automated Survey (ASAS), and release the Machine-learned ASAS Classification Catalog (MACC), a 28 class probabilistic classification catalog of 50,124 ASAS sources in the ASAS Catalog of Variable Stars. We estimate that MACC achieves a sub-20% classification error rate and demonstrate that the class posterior probabilities are reasonably calibrated. MACC classifications compare favorably to the classifications of several previous domain-specific ASAS papers and to the ASAS Catalog of Variable Stars, which had classified only 24% of those sources into one of 12 science classes.

CONSTRUCTION OF A CALIBRATED PROBABILISTIC CLASSIFICATION CATALOG: APPLICATION TO 50k VARIABLE SOURCES IN THE ALL-SKY AUTOMATED SURVEY

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

Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.

2012-12-15

With growing data volumes from synoptic surveys, astronomers necessarily must become more abstracted from the discovery and introspection processes. Given the scarcity of follow-up resources, there is a particularly sharp onus on the frameworks that replace these human roles to provide accurate and well-calibrated probabilistic classification catalogs. Such catalogs inform the subsequent follow-up, allowing consumers to optimize the selection of specific sources for further study and permitting rigorous treatment of classification purities and efficiencies for population studies. Here, we describe a process to produce a probabilistic classification catalog of variability with machine learning from a multi-epoch photometric survey. In additionmore » to producing accurate classifications, we show how to estimate calibrated class probabilities and motivate the importance of probability calibration. We also introduce a methodology for feature-based anomaly detection, which allows discovery of objects in the survey that do not fit within the predefined class taxonomy. Finally, we apply these methods to sources observed by the All-Sky Automated Survey (ASAS), and release the Machine-learned ASAS Classification Catalog (MACC), a 28 class probabilistic classification catalog of 50,124 ASAS sources in the ASAS Catalog of Variable Stars. We estimate that MACC achieves a sub-20% classification error rate and demonstrate that the class posterior probabilities are reasonably calibrated. MACC classifications compare favorably to the classifications of several previous domain-specific ASAS papers and to the ASAS Catalog of Variable Stars, which had classified only 24% of those sources into one of 12 science classes.« less

Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches

PubMed Central

Zulkifley, Mohd Asyraf; Rawlinson, David; Moran, Bill

2012-01-01

In video analytics, robust observation detection is very important as the content of the videos varies a lot, especially for tracking implementation. Contrary to the image processing field, the problems of blurring, moderate deformation, low illumination surroundings, illumination change and homogenous texture are normally encountered in video analytics. Patch-Based Observation Detection (PBOD) is developed to improve detection robustness to complex scenes by fusing both feature- and template-based recognition methods. While we believe that feature-based detectors are more distinctive, however, for finding the matching between the frames are best achieved by a collection of points as in template-based detectors. Two methods of PBOD—the deterministic and probabilistic approaches—have been tested to find the best mode of detection. Both algorithms start by building comparison vectors at each detected points of interest. The vectors are matched to build candidate patches based on their respective coordination. For the deterministic method, patch matching is done in 2-level test where threshold-based position and size smoothing are applied to the patch with the highest correlation value. For the second approach, patch matching is done probabilistically by modelling the histograms of the patches by Poisson distributions for both RGB and HSV colour models. Then, maximum likelihood is applied for position smoothing while a Bayesian approach is applied for size smoothing. The result showed that probabilistic PBOD outperforms the deterministic approach with average distance error of 10.03% compared with 21.03%. This algorithm is best implemented as a complement to other simpler detection methods due to heavy processing requirement. PMID:23202226

A global empirical system for probabilistic seasonal climate prediction

NASA Astrophysics Data System (ADS)

Eden, J. M.; van Oldenborgh, G. J.; Hawkins, E.; Suckling, E. B.

2015-12-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

An empirical system for probabilistic seasonal climate prediction

NASA Astrophysics Data System (ADS)

Eden, Jonathan; van Oldenborgh, Geert Jan; Hawkins, Ed; Suckling, Emma

2016-04-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

Developing effective assignment feedback for an interprofessional learning module-An action research project.

PubMed

Strudwick, Ruth; Day, Jane

2015-09-01

The first year interprofessional learning module at University Campus Suffolk (UCS) is delivered to 300 students and the students' assignments are marked by 20 members of staff from different health and social care professions. We were keen to find a way to reduce any inconsistencies and work with both staff and students to ensure that the essay and subsequent feedback were useful for all involved. The aims of the project were to evaluate the current marking process and feedback sheets used for year one inter-professional learning (IPL) marking, and to develop an appropriate marking tool and feedback sheet that would enable markers to provide more consistent feedback to the students. Participatory action research was used with both students and staff members being involved. Focus group and questions were used to ascertain views about the assignment feedback. The feedback from this action learning project helped us to enhance the feedback for students. There was also an increase in engagement with the assessment and feedback process amongst both staff and students. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neurophysiological correlates of anhedonia in feedback processing

PubMed Central

Mies, Gabry W.; Van den Berg, Ivo; Franken, Ingmar H. A.; Smits, Marion; Van der Molen, Maurits W.; Van der Veen, Frederik M.

2013-01-01

Disturbances in feedback processing and a dysregulation of the neural circuit in which the cingulate cortex plays a key role have been frequently observed in depression. Since depression is a heterogeneous disease, instead of focusing on the depressive state in general, this study investigated the relations between the two core symptoms of depression, i.e., depressed mood and anhedonia, and the neural correlates of feedback processing using fMRI. The focus was on the different subdivisions of the anterior cingulate cortex (ACC). Undergraduates with varying levels of depressed mood and anhedonia performed a time-estimation task in which they received positive and negative feedback that was either valid or invalid (i.e., related vs. unrelated to actual performance). The rostral cingulate zone (RCZ), corresponding to the dorsal part of the ACC, was less active in response to feedback in more anhedonic individuals, after correcting for the influence of depressed mood, whereas the subgenual ACC was more active in these individuals. Task performance was not affected by anhedonia, however. No statistically significant effects were found for depressed mood above and beyond the effects of anhedonia. This study therefore implies that increasing levels of anhedonia involve changes in the neural circuitry underlying feedback processing. PMID:23532800

Acute effects of alcohol on feedback processing and outcome evaluation during risky decision-making: an ERP study.

PubMed

Euser, Anja S; van Meel, Catharina S; Snelleman, Michelle; Franken, Ingmar H A

2011-09-01

Although risky decision-making is one of the hallmarks of alcohol use disorders, relatively little is known about the acute psychopharmacological effects of alcohol on decision-making processes. The present study investigated the acute effects of alcohol on neural mechanisms underlying feedback processing and outcome evaluation during risky decision-making, using event-related brain potentials (ERPs). ERPs elicited by positive and negative feedback were recorded during performance of a modified version of the Balloon Analogue Risk Task in male participants receiving either a moderate dose of alcohol (0.65 g/kg alcohol; n = 32) or a non-alcoholic placebo beverage (n = 32). Overall, there was no significant difference in the mean number of pumps between the alcohol and the placebo condition. However, when analyzing over time, it was found that the alcohol group made more riskier choices at the beginning of the task than the placebo group. ERPs demonstrated that alcohol consumption did not affect early processing of negative feedback, indexed by the feedback-related negativity. By contrast, alcohol-intoxicated individuals showed significantly reduced P300 amplitudes in response to negative feedback as compared to sober controls, suggesting that more elaborate evaluation to losses was significantly diminished. These results suggest that alcohol consumption does not influence the ability to rapidly evaluate feedback valence, but rather the ability to assign sufficient attention to further process motivationally salient outcomes. Blunted P300 amplitudes may reflect poor integration of feedback across trials, particularly adverse ones. Consequently, alcohol may keep people from effectively predicting the probability of future gains and losses based on their reinforcement history.

"Are You Listening Please?" The Advantages of Electronic Audio Feedback Compared to Written Feedback

ERIC Educational Resources Information Center

Lunt, Tom; Curran, John

2010-01-01

Feedback on students' work is, probably, one of the most important aspects of learning, yet students' report, according to the National Union of Students (NUS) Survey of 2008, unhappiness with the feedback process. Students were unhappy with the quality, detail and timing of feedback. This paper examines the benefits of using audio, as opposed to…

Making Judgements: Investigating the Process of Composing and Receiving Peer Feedback

ERIC Educational Resources Information Center

McConlogue, Teresa

2015-01-01

Recent studies have argued that tutor feedback is failing to support students' progression. The potential for peer feedback, i.e. feedback composed by peer assessors, to support learning has been under researched. The aim of this paper was to explore a case study of a peer assessor composing and receiving peer feedback. The paper reports a case…

Probabilistic Perception, Empathy, and Dynamic Homeostasis: Insights in Autism Spectrum Disorders and Conduct Disorders

PubMed Central

Guilé, Jean Marc

2013-01-01

Homeostasis is not a permanent and stable state but instead results from conflicting forces. Therefore, infants have to engage in dynamic exchanges with their environment, in biological, cognitive, and affective domains. Empathy is an adaptive response to these environmental challenges, which contributes to reaching proper dynamic homeostasis and development. Empathy relies on implicit interactive processes, namely probabilistic perception and synchrony, which will be reviewed in the article. If typically-developed neonates are fully equipped to automatically and synchronously interact with their human environment, conduct disorders (CD) and autism spectrum disorders (ASD) present with impairments in empathetic communication, e.g., emotional arousal and facial emotion processing. In addition sensorimotor resonance is lacking in ASD, and emotional concern and semantic empathy are impaired in CD with Callous-Unemotional traits. PMID:24479115

Rocketdyne PSAM: In-house enhancement/application

NASA Technical Reports Server (NTRS)

Newell, J. F.; Rajagopal, K. R.; Ohara, K.

1991-01-01

The development was initiated of the Probabilistic Design Analysis (PDA) Process for rocket engines. This will enable engineers a quantitative assessment of calculated reliability during the design process. The PDA will help choose better designs, make them more robust, and help decide on critical tests to help demonstrate key reliability issues to aid in improving the confidence of the engine capabilities. Rockedyne's involvement with the Composite Loads Spectra (CLS) and Probabilistic Structural Analysis Methodology (PSAM) contracts started this effort and are key elements in the on-going developments. Internal development efforts and hardware applications complement and extend the CLS and PSAM efforts. The completion of the CLS option work and the follow-on PSAM developments will also be integral parts of this methodology. A brief summary of these efforts is presented.

The Effects of Feedback on Memory Strategies of Younger and Older Adults

PubMed Central

Zhang, Fan; Zhang, Xin; Luo, Meng; Geng, Haiyan

2016-01-01

Existing literature suggests that feedback could effectively reduce false memories in younger adults. However, it is unclear whether memory performance in older adults also might be affected by feedback. The current study tested the hypothesis that older adults can use immediate feedback to adjust their memory strategy, similar to younger adults, but after feedback is removed, older adults may not be able to maintain using the memory strategy. Older adults will display more false memories than younger adults due to a reduction in attentional resources. In Study 1, both younger and older adults adjusted gist processing and item-specific processing biases based on the feedback given (i.e., biased and objective feedback). In Study 2 after the feedback was removed, only younger adults with full attention were able to maintain the feedback-shaped memory strategy; whereas, both younger adults with divided attention and older adults had increased false memories after feedback was removed. The findings suggest that environmental support helps older adults as well as younger adults to adopt a memory strategy that demands high attentional resources, but when the support is removed, older adults can no longer maintain such a strategy. PMID:28033327

Factors influencing the effectiveness of audit and feedback: nurses' perceptions.

PubMed

Christina, Venessa; Baldwin, Kathryn; Biron, Alain; Emed, Jessica; Lepage, Karine

2016-11-01

To explore the perceptions of nurses in an acute care setting on factors influencing the effectiveness of audit and feedback. Audit and feedback is widely used and recommended in nursing to promote evidence-based practice and to improve care quality. Yet the literature has shown a limited to modest effect at most. Audit and feedback will continue to be unreliable until we learn what influences its effectiveness. A qualitative study was conducted using individual, semi-structured interviews with 14 registered nurses in an acute care teaching hospital in Montreal, Canada. Three themes were identified: the relevance of audit and feedback, particularly understanding the purpose of audit and feedback and the prioritisation of audit criteria; the audit and feedback process, including its timing and feedback characteristics; and individual factors, such as personality and perceived accountability. According to participants, they were likely to have a better response to audit and feedback when they perceived that it was relevant and that the process fitted their preferences. This study benefits nursing leaders and managers involved in quality improvement by providing a better understanding of nurses' perceptions on how best to use audit and feedback as a strategy to promote evidence-based practice. © 2016 John Wiley & Sons Ltd.

The Effects of Feedback on Memory Strategies of Younger and Older Adults.

PubMed

Zhang, Fan; Zhang, Xin; Luo, Meng; Geng, Haiyan

2016-01-01

Existing literature suggests that feedback could effectively reduce false memories in younger adults. However, it is unclear whether memory performance in older adults also might be affected by feedback. The current study tested the hypothesis that older adults can use immediate feedback to adjust their memory strategy, similar to younger adults, but after feedback is removed, older adults may not be able to maintain using the memory strategy. Older adults will display more false memories than younger adults due to a reduction in attentional resources. In Study 1, both younger and older adults adjusted gist processing and item-specific processing biases based on the feedback given (i.e., biased and objective feedback). In Study 2 after the feedback was removed, only younger adults with full attention were able to maintain the feedback-shaped memory strategy; whereas, both younger adults with divided attention and older adults had increased false memories after feedback was removed. The findings suggest that environmental support helps older adults as well as younger adults to adopt a memory strategy that demands high attentional resources, but when the support is removed, older adults can no longer maintain such a strategy.

Paper Review Revolution: Screencasting Feedback for Developmental Writers

ERIC Educational Resources Information Center

Boone, Joni; Carlson, Susan

2011-01-01

Researchers from Kaplan University present findings from a media-rich feedback pilot program that targets students from developmental writing courses. One study of student reactions reveals how screencasting feedback encouraged more formative, holistic feedback and students' awareness of writing process, audience, and revision. A second study…

Descriptive Feedback: Student Voice in K-5 Classrooms

ERIC Educational Resources Information Center

Rodgers, Carol

2018-01-01

In this article, the author argues the imperative of critical dialogue between learners and teachers on learners' experiences in the classroom. This dialogical process is called "descriptive feedback"--feedback given by students to teachers on their (students') experiences as learners. Drawing on the literature on feedback, descriptive…

Reduced activation in ventral striatum and ventral tegmental area during probabilistic decision-making in schizophrenia.

PubMed

Rausch, Franziska; Mier, Daniela; Eifler, Sarah; Esslinger, Christine; Schilling, Claudia; Schirmbeck, Frederike; Englisch, Susanne; Meyer-Lindenberg, Andreas; Kirsch, Peter; Zink, Mathias

2014-07-01

Patients with schizophrenia suffer from deficits in monitoring and controlling their own thoughts. Within these so-called metacognitive impairments, alterations in probabilistic reasoning might be one cognitive phenomenon disposing to delusions. However, so far little is known about alterations in associated brain functionality. A previously established task for functional magnetic resonance imaging (fMRI), which requires a probabilistic decision after a variable amount of stimuli, was applied to 23 schizophrenia patients and 28 healthy controls matched for age, gender and educational levels. We compared activation patterns during decision-making under conditions of certainty versus uncertainty and evaluated the process of final decision-making in ventral striatum (VS) and ventral tegmental area (VTA). We replicated a pre-described extended cortical activation pattern during probabilistic reasoning. During final decision-making, activations in several fronto- and parietocortical areas, as well as in VS and VTA became apparent. In both of these regions schizophrenia patients showed a significantly reduced activation. These results further define the network underlying probabilistic decision-making. The observed hypo-activation in regions commonly associated with dopaminergic neurotransmission fits into current concepts of disrupted prediction error signaling in schizophrenia and suggests functional links to reward anticipation. Forthcoming studies with patients at risk for psychosis and drug-naive first episode patients are necessary to elucidate the development of these findings over time and the interplay with associated clinical symptoms. Copyright © 2014 Elsevier B.V. All rights reserved.

Expectancy Learning from Probabilistic Input by Infants

PubMed Central

Romberg, Alexa R.; Saffran, Jenny R.

2013-01-01

Across the first few years of life, infants readily extract many kinds of regularities from their environment, and this ability is thought to be central to development in a number of domains. Numerous studies have documented infants’ ability to recognize deterministic sequential patterns. However, little is known about the processes infants use to build and update representations of structure in time, and how infants represent patterns that are not completely predictable. The present study investigated how infants’ expectations fora simple structure develope over time, and how infants update their representations with new information. We measured 12-month-old infants’ anticipatory eye movements to targets that appeared in one of two possible locations. During the initial phase of the experiment, infants either saw targets that appeared consistently in the same location (Deterministic condition) or probabilistically in either location, with one side more frequent than the other (Probabilistic condition). After this initial divergent experience, both groups saw the same sequence of trials for the rest of the experiment. The results show that infants readily learn from both deterministic and probabilistic input, with infants in both conditions reliably predicting the most likely target location by the end of the experiment. Local context had a large influence on behavior: infants adjusted their predictions to reflect changes in the target location on the previous trial. This flexibility was particularly evident in infants with more variable prior experience (the Probabilistic condition). The results provide some of the first data showing how infants learn in real time. PMID:23439947

Probabilistic Sizing and Verification of Space Ceramic Structures

NASA Astrophysics Data System (ADS)

Denaux, David; Ballhause, Dirk; Logut, Daniel; Lucarelli, Stefano; Coe, Graham; Laine, Benoit

2012-07-01

Sizing of ceramic parts is best optimised using a probabilistic approach which takes into account the preexisting flaw distribution in the ceramic part to compute a probability of failure of the part depending on the applied load, instead of a maximum allowable load as for a metallic part. This requires extensive knowledge of the material itself but also an accurate control of the manufacturing process. In the end, risk reduction approaches such as proof testing may be used to lower the final probability of failure of the part. Sizing and verification of ceramic space structures have been performed by Astrium for more than 15 years, both with Zerodur and SiC: Silex telescope structure, Seviri primary mirror, Herschel telescope, Formosat-2 instrument, and other ceramic structures flying today. Throughout this period of time, Astrium has investigated and developed experimental ceramic analysis tools based on the Weibull probabilistic approach. In the scope of the ESA/ESTEC study: “Mechanical Design and Verification Methodologies for Ceramic Structures”, which is to be concluded in the beginning of 2012, existing theories, technical state-of-the-art from international experts, and Astrium experience with probabilistic analysis tools have been synthesized into a comprehensive sizing and verification method for ceramics. Both classical deterministic and more optimised probabilistic methods are available, depending on the criticality of the item and on optimisation needs. The methodology, based on proven theory, has been successfully applied to demonstration cases and has shown its practical feasibility.

Transient flow conditions in probabilistic wellhead protection: importance and ways to manage spatial and temporal uncertainty in capture zone delineation

NASA Astrophysics Data System (ADS)

Enzenhoefer, R.; Rodriguez-Pretelin, A.; Nowak, W.

2012-12-01

"From an engineering standpoint, the quantification of uncertainty is extremely important not only because it allows estimating risk but mostly because it allows taking optimal decisions in an uncertain framework" (Renard, 2007). The most common way to account for uncertainty in the field of subsurface hydrology and wellhead protection is to randomize spatial parameters, e.g. the log-hydraulic conductivity or porosity. This enables water managers to take robust decisions in delineating wellhead protection zones with rationally chosen safety margins in the spirit of probabilistic risk management. Probabilistic wellhead protection zones are commonly based on steady-state flow fields. However, several past studies showed that transient flow conditions may substantially influence the shape and extent of catchments. Therefore, we believe they should be accounted for in the probabilistic assessment and in the delineation process. The aim of our work is to show the significance of flow transients and to investigate the interplay between spatial uncertainty and flow transients in wellhead protection zone delineation. To this end, we advance our concept of probabilistic capture zone delineation (Enzenhoefer et al., 2012) that works with capture probabilities and other probabilistic criteria for delineation. The extended framework is able to evaluate the time fraction that any point on a map falls within a capture zone. In short, we separate capture probabilities into spatial/statistical and time-related frequencies. This will provide water managers additional information on how to manage a well catchment in the light of possible hazard conditions close to the capture boundary under uncertain and time-variable flow conditions. In order to save computational costs, we take advantage of super-positioned flow components with time-variable coefficients. We assume an instantaneous development of steady-state flow conditions after each temporal change in driving forces, following an idea by Festger and Walter, 2002. These quasi steady-state flow fields are cast into a geostatistical Monte Carlo framework to admit and evaluate the influence of parameter uncertainty on the delineation process. Furthermore, this framework enables conditioning on observed data with any conditioning scheme, such as rejection sampling, Ensemble Kalman Filters, etc. To further reduce the computational load, we use the reverse formulation of advective-dispersive transport. We simulate the reverse transport by particle tracking random walk in order to avoid numerical dispersion to account for well arrival times.

Enabling multi-level relevance feedback on PubMed by integrating rank learning into DBMS.

PubMed

Yu, Hwanjo; Kim, Taehoon; Oh, Jinoh; Ko, Ilhwan; Kim, Sungchul; Han, Wook-Shin

2010-04-16

Finding relevant articles from PubMed is challenging because it is hard to express the user's specific intention in the given query interface, and a keyword query typically retrieves a large number of results. Researchers have applied machine learning techniques to find relevant articles by ranking the articles according to the learned relevance function. However, the process of learning and ranking is usually done offline without integrated with the keyword queries, and the users have to provide a large amount of training documents to get a reasonable learning accuracy. This paper proposes a novel multi-level relevance feedback system for PubMed, called RefMed, which supports both ad-hoc keyword queries and a multi-level relevance feedback in real time on PubMed. RefMed supports a multi-level relevance feedback by using the RankSVM as the learning method, and thus it achieves higher accuracy with less feedback. RefMed "tightly" integrates the RankSVM into RDBMS to support both keyword queries and the multi-level relevance feedback in real time; the tight coupling of the RankSVM and DBMS substantially improves the processing time. An efficient parameter selection method for the RankSVM is also proposed, which tunes the RankSVM parameter without performing validation. Thereby, RefMed achieves a high learning accuracy in real time without performing a validation process. RefMed is accessible at http://dm.postech.ac.kr/refmed. RefMed is the first multi-level relevance feedback system for PubMed, which achieves a high accuracy with less feedback. It effectively learns an accurate relevance function from the user's feedback and efficiently processes the function to return relevant articles in real time.

Enabling multi-level relevance feedback on PubMed by integrating rank learning into DBMS

PubMed Central

2010-01-01

Background Finding relevant articles from PubMed is challenging because it is hard to express the user's specific intention in the given query interface, and a keyword query typically retrieves a large number of results. Researchers have applied machine learning techniques to find relevant articles by ranking the articles according to the learned relevance function. However, the process of learning and ranking is usually done offline without integrated with the keyword queries, and the users have to provide a large amount of training documents to get a reasonable learning accuracy. This paper proposes a novel multi-level relevance feedback system for PubMed, called RefMed, which supports both ad-hoc keyword queries and a multi-level relevance feedback in real time on PubMed. Results RefMed supports a multi-level relevance feedback by using the RankSVM as the learning method, and thus it achieves higher accuracy with less feedback. RefMed "tightly" integrates the RankSVM into RDBMS to support both keyword queries and the multi-level relevance feedback in real time; the tight coupling of the RankSVM and DBMS substantially improves the processing time. An efficient parameter selection method for the RankSVM is also proposed, which tunes the RankSVM parameter without performing validation. Thereby, RefMed achieves a high learning accuracy in real time without performing a validation process. RefMed is accessible at http://dm.postech.ac.kr/refmed. Conclusions RefMed is the first multi-level relevance feedback system for PubMed, which achieves a high accuracy with less feedback. It effectively learns an accurate relevance function from the user’s feedback and efficiently processes the function to return relevant articles in real time. PMID:20406504

Quantifying climate feedbacks in polar regions.

PubMed

Goosse, Hugues; Kay, Jennifer E; Armour, Kyle C; Bodas-Salcedo, Alejandro; Chepfer, Helene; Docquier, David; Jonko, Alexandra; Kushner, Paul J; Lecomte, Olivier; Massonnet, François; Park, Hyo-Seok; Pithan, Felix; Svensson, Gunilla; Vancoppenolle, Martin

2018-05-15

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range of feedbacks, offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.

Students' Perceptions of Interventions for Supporting Their Engagement with Feedback

ERIC Educational Resources Information Center

Parker, Michael; Winstone, Naomi E.

2016-01-01

Recent approaches to assessment and feedback in higher education stress the importance of students' involvement in these processes, where effective reception of feedback is as important as effective delivery. Many interventions have been developed to support students' active use of feedback; however, students' engagement will be influenced by…

The Influence of Teacher Feedback on Children's Perceptions of Student-Teacher Relationships

ERIC Educational Resources Information Center

Skipper, Yvonne; Douglas, Karen

2015-01-01

Background: Teachers can deliver feedback using person ("you are clever") or process terms ("you worked hard"). Person feedback can lead to negative academic outcomes, but there is little experimental research examining the impact of feedback on children's perceptions of the student-teacher relationship. Aim: We examined the…

Keeping the Destination in Mind

ERIC Educational Resources Information Center

Lalor, Angela Di Michele

2012-01-01

The feedback process in school--and its effect on learners--resembles a global positioning system (GPS). When students receive clear, high-quality feedback that is tied to learning targets, student learning moves forward. When they are deprived of feedback or given feedback that is barely connected to learning targets, students get frustrated,…

The Problem of Feedback in Hearing Aids.

ERIC Educational Resources Information Center

Kates, James M.

1991-01-01

This paper discusses the problem of feedback in hearing aids and offers examples based on a computer simulation of hearing aid behavior. The available technology for dealing with feedback is reviewed, and the new digital signal-processing approaches which may finally solve the feedback problem are described. (Author/DB)

The Mythology of Feedback

ERIC Educational Resources Information Center

Adcroft, Andy

2011-01-01

Much of the general education and discipline-specific literature on feedback suggests that it is a central and important element of student learning. This paper examines feedback from a social process perspective and suggests that feedback is best understood through an analysis of the interactions between academics and students. The paper argues…

Probabilistic Risk Assessment Procedures Guide for NASA Managers and Practitioners (Second Edition)

NASA Technical Reports Server (NTRS)

Stamatelatos,Michael; Dezfuli, Homayoon; Apostolakis, George; Everline, Chester; Guarro, Sergio; Mathias, Donovan; Mosleh, Ali; Paulos, Todd; Riha, David; Smith, Curtis;

Development of a First-of-a-Kind Deterministic Decision-Making Tool for Supervisory Control System

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

Cetiner, Sacit M; Kisner, Roger A; Muhlheim, Michael David

2015-07-01

Decision-making is the process of identifying and choosing alternatives where each alternative offers a different approach or path to move from a given state or condition to a desired state or condition. The generation of consistent decisions requires that a structured, coherent process be defined, immediately leading to a decision-making framework. The overall objective of the generalized framework is for it to be adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or nomore » human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision- making modules that can perform a given set of tasks reliably. Risk-informed decision making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The implementation of the probabilistic portion of the decision-making engine of the proposed supervisory control system was detailed in previous milestone reports. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic multi-attribute decision-making framework uses variable sensor data (e.g., outlet temperature) and calculates where it is within the challenge state, its trajectory, and margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. Metrics to be evaluated include stability, cost, time to complete (action), power level, etc. The integration of deterministic calculations using multi-physics analyses (i.e., neutronics, thermal, and thermal-hydraulics) and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermal-hydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies.« less

Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems.

PubMed

Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

2016-01-01

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.

Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

PubMed Central

Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

2016-01-01

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning. PMID:27445958

Process-based modeling of silicate mineral weathering responses to increasing atmospheric CO2 and climate change

NASA Astrophysics Data System (ADS)

Banwart, Steven A.; Berg, Astrid; Beerling, David J.

2009-12-01

A mathematical model describes silicate mineral weathering processes in modern soils located in the boreal coniferous region of northern Europe. The process model results demonstrate a stabilizing biological feedback mechanism between atmospheric CO2 levels and silicate weathering rates as is generally postulated for atmospheric evolution. The process model feedback response agrees within a factor of 2 of that calculated by a weathering feedback function of the type generally employed in global geochemical carbon cycle models of the Earth's Phanerozoic CO2 history. Sensitivity analysis of parameter values in the process model provides insight into the key mechanisms that influence the strength of the biological feedback to weathering. First, the process model accounts for the alkalinity released by weathering, whereby its acceleration stabilizes pH at values that are higher than expected. Although the process model yields faster weathering with increasing temperature, because of activation energy effects on mineral dissolution kinetics at warmer temperature, the mineral dissolution rate laws utilized in the process model also result in lower dissolution rates at higher pH values. Hence, as dissolution rates increase under warmer conditions, more alkalinity is released by the weathering reaction, helping maintain higher pH values thus stabilizing the weathering rate. Second, the process model yields a relatively low sensitivity of soil pH to increasing plant productivity. This is due to more rapid decomposition of dissolved organic carbon (DOC) under warmer conditions. Because DOC fluxes strongly influence the soil water proton balance and pH, this increased decomposition rate dampens the feedback between productivity and weathering. The process model is most sensitive to parameters reflecting soil structure; depth, porosity, and water content. This suggests that the role of biota to influence these characteristics of the weathering profile is as important, if not more important, than the role of biota to influence mineral dissolution rates through changes in soil water chemistry. This process-modeling approach to quantify the biological weathering feedback to atmospheric CO2 demonstrates the potential for a far more mechanistic description of weathering feedback in simulations of the global geochemical carbon cycle.

Willing to wait: Elevated reward-processing EEG activity associated with a greater preference for larger-but-delayed rewards.

PubMed

Pornpattananangkul, Narun; Nusslock, Robin

2016-10-01

While almost everyone discounts the value of future rewards over immediate rewards, people differ in their so-called delay-discounting. One of the several factors that may explain individual differences in delay-discounting is reward-processing. To study individual-differences in reward-processing, however, one needs to consider the heterogeneity of neural-activity at each reward-processing stage. Here using EEG, we separated reward-related neural activity into distinct reward-anticipation and reward-outcome stages using time-frequency characteristics. Thirty-seven individuals first completed a behavioral delay-discounting task. Then reward-processing EEG activity was assessed using a separate reward-learning task, called a reward time-estimation task. During this EEG task, participants were instructed to estimate time duration and were provided performance feedback on a trial-by-trial basis. Participants received monetary-reward for accurate-performance on Reward trials, but not on No-Reward trials. Reward trials, relative to No-Reward trials, enhanced EEG activity during both reward-anticipation (including, cued-locked delta power during cue-evaluation and pre-feedback alpha suppression during feedback-anticipation) and reward-outcome (including, feedback-locked delta, theta and beta power) stages. Moreover, all of these EEG indices correlated with behavioral performance in the time-estimation task, suggesting their essential roles in learning and adjusting performance to maximize winnings in a reward-learning situation. Importantly, enhanced EEG power during Reward trials, as reflected by stronger 1) pre-feedback alpha suppression, 2) feedback-locked theta and 3) feedback-locked beta, was associated with a greater preference for larger-but-delayed rewards in a separate, behavioral delay-discounting task. Results highlight the association between a stronger preference toward larger-but-delayed rewards and enhanced reward-processing. Moreover, our reward-processing EEG indices detail the specific stages of reward-processing where these associations occur. Copyright © 2016 Elsevier Ltd. All rights reserved.

Understanding constructive feedback: a commitment between teachers and students for academic and professional development.

PubMed

Hamid, Yasir; Mahmood, Sajid

2010-03-01

This review highlights the need in the Pakistani medical education system for teachers and students to be able to: define constructive feedback; provide constructive feedback; identify standards for constructive feedback; identify a suitable model for the provision of constructive feedback and evaluate the use of constructive feedback. For the purpose of literature review we had defined the key word glossary as: feedback, constructive feedback, teaching constructive feedback, models for feedback, models for constructive feedback and giving and receiving feedback. The data bases for the search include: Medline (EBSCO), Web of Knowledge, SCOPUS, TRIP, ScienceDirect, Pubmed, U.K. Pubmed Central, ZETOC, University of Dundee Library catalogue, SCIRUS (Elsevier) and Google Scholar. This article states that the Pakistani medical schools do not reflect on or use the benefits of the constructive feedback process. The discussion about constructive feedback suggests that in the context of Pakistan, constructive feedback will facilitate the teaching and learning activities.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-10-01

The cloud processing scheme APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. It builds upon the physical principles that have served well in the original APOLLO scheme. Nevertheless, a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is no longer performed as a binary yes/no decision based on these physical principles. It is rather expressed as cloud probability for each satellite pixel. Consequently, the outcome of the algorithm can be tuned from being sure to reliably identify clear pixels to conditions of reliably identifying definitely cloudy pixels, depending on the purpose. The probabilistic approach allows retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for application to large amounts of historical satellite data. The radiative transfer solution is approximated by the same two-stream approach which also had been used for the original APOLLO. This allows the algorithm to be applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e., within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from NOAA-18 are presented.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-04-01

The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.

Probabilistic volcanic hazard assessments of Pyroclastic Density Currents: ongoing practices and future perspectives

NASA Astrophysics Data System (ADS)

Tierz, Pablo; Sandri, Laura; Ramona Stefanescu, Elena; Patra, Abani; Marzocchi, Warner; Costa, Antonio; Sulpizio, Roberto

2014-05-01

Explosive volcanoes and, especially, Pyroclastic Density Currents (PDCs) pose an enormous threat to populations living in the surroundings of volcanic areas. Difficulties in the modeling of PDCs are related to (i) very complex and stochastic physical processes, intrinsic to their occurrence, and (ii) to a lack of knowledge about how these processes actually form and evolve. This means that there are deep uncertainties (namely, of aleatory nature due to point (i) above, and of epistemic nature due to point (ii) above) associated to the study and forecast of PDCs. Consequently, the assessment of their hazard is better described in terms of probabilistic approaches rather than by deterministic ones. What is actually done to assess probabilistic hazard from PDCs is to couple deterministic simulators with statistical techniques that can, eventually, supply probabilities and inform about the uncertainties involved. In this work, some examples of both PDC numerical simulators (Energy Cone and TITAN2D) and uncertainty quantification techniques (Monte Carlo sampling -MC-, Polynomial Chaos Quadrature -PCQ- and Bayesian Linear Emulation -BLE-) are presented, and their advantages, limitations and future potential are underlined. The key point in choosing a specific method leans on the balance between its related computational cost, the physical reliability of the simulator and the pursued target of the hazard analysis (type of PDCs considered, time-scale selected for the analysis, particular guidelines received from decision-making agencies, etc.). Although current numerical and statistical techniques have brought important advances in probabilistic volcanic hazard assessment from PDCs, some of them may be further applicable to more sophisticated simulators. In addition, forthcoming improvements could be focused on three main multidisciplinary directions: 1) Validate the simulators frequently used (through comparison with PDC deposits and other simulators), 2) Decrease simulator runtimes (whether by increasing the knowledge about the physical processes or by doing more efficient programming, parallelization, ...) and 3) Improve uncertainty quantification techniques.

A student-centred feedback model for educators.

PubMed

Rudland, Joy; Wilkinson, Tim; Wearn, Andy; Nicol, Pam; Tunny, Terry; Owen, Cathy; O'Keefe, Maree

2013-04-01

Effective feedback is instrumental to effective learning. Current feedback models tend to be educator driven rather than learner-centred, with the focus on how the supervisor should give feedback rather than on the role of the learner in requesting and responding to feedback. An alternative approach emphasising the theoretical principles of student-centred and self-regulated learning is offered, drawing upon the literature and also upon the experience of the authors. The proposed feedback model places the student in the centre of the feedback process, and stresses that the attainment of student learning outcomes is influenced by the students themselves. This model emphasises the attributes of the student, particularly responsiveness, receptiveness and reflection, whilst acknowledging the important role that the context and attributes of the supervisor have in influencing the quality of feedback. Educational institutions should consider strategies to encourage and enable students to maximise the many feedback opportunities available to them. As a minimum, educators should remind students about their central role in the feedback process, and support them to develop confidence in meeting this role. In addition, supervisors may need support to develop the skills to shift the balance of responsibility and support students in precipitating feedback moments. Research is also required to validate the proposed model and to determine how to support students to adopt self-regulatory learning, with feedback as a central platform. © Blackwell Publishing Ltd 2013.

Blocked versus randomized presentation modes differentially modulate feedback-related negativity and P3b amplitudes.

PubMed

Pfabigan, Daniela M; Zeiler, Michael; Lamm, Claus; Sailer, Uta

2014-04-01

Electrophysiological studies on feedback processing typically use a wide range of feedback stimuli which might not always be comparable. The current study investigated whether two indicators of feedback processing - feedback-related negativity (FRN) and P3b - differ for feedback stimuli with explicit (facial expressions) or assigned valence information (symbols). In addition, we assessed whether presenting feedback in either a trial-by-trial or a block-wise fashion affected these ERPs. EEG was recorded in three experiments while participants performed a time estimation task and received two different types of performance feedback. Only P3b amplitudes varied consistently in response to feedback type for both presentation types. Moreover, the blocked feedback type presentation yielded more distinct FRN peaks, higher effect sizes, and a significant relation between FRN amplitudes and behavioral task performance measures. Both stimulus type and presentation mode may provoke systematic changes in feedback-related ERPs. The current findings point at important potential confounds that need to be controlled for when designing FRN or P3b studies. Studies investigating P3b amplitudes using mixed types of stimuli have to be interpreted with caution. Furthermore, we suggest implementing a blocked presentation format when presenting different feedback types within the same experiment. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Generalized Poisson-Kac Processes: Basic Properties and Implications in Extended Thermodynamics and Transport

NASA Astrophysics Data System (ADS)

Giona, Massimiliano; Brasiello, Antonio; Crescitelli, Silvestro

2016-04-01

We introduce a new class of stochastic processes in Rn,{{{mathbb R}}^n}, referred to as generalized Poisson-Kac (GPK) processes, that generalizes the Poisson-Kac telegrapher's random motion in higher dimensions. These stochastic processes possess finite propagation velocity, almost everywhere smooth trajectories, and converge in the Kac limit to Brownian motion. GPK processes are defined by coupling the selection of a bounded velocity vector from a family of N distinct ones with a Markovian dynamics controlling probabilistically this selection. This model can be used as a probabilistic tool for a stochastically consistent formulation of extended thermodynamic theories far from equilibrium.

Programming Probabilistic Structural Analysis for Parallel Processing Computer

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Chamis, Christos C.; Murthy, Pappu L. N.

1991-01-01

The ultimate goal of this research program is to make Probabilistic Structural Analysis (PSA) computationally efficient and hence practical for the design environment by achieving large scale parallelism. The paper identifies the multiple levels of parallelism in PSA, identifies methodologies for exploiting this parallelism, describes the development of a parallel stochastic finite element code, and presents results of two example applications. It is demonstrated that speeds within five percent of those theoretically possible can be achieved. A special-purpose numerical technique, the stochastic preconditioned conjugate gradient method, is also presented and demonstrated to be extremely efficient for certain classes of PSA problems.

How does culture affect experiential training feedback in exported Canadian health professional curricula?

PubMed Central

Mousa Bacha, Rasha; Abdelaziz, Somaia

2017-01-01

Objectives To explore feedback processes of Western-based health professional student training curricula conducted in an Arab clinical teaching setting. Methods This qualitative study employed document analysis of in-training evaluation reports (ITERs) used by Canadian nursing, pharmacy, respiratory therapy, paramedic, dental hygiene, and pharmacy technician programs established in Qatar. Six experiential training program coordinators were interviewed between February and May 2016 to explore how national cultural differences are perceived to affect feedback processes between students and clinical supervisors. Interviews were recorded, transcribed, and coded according to a priori cultural themes. Results Document analysis found all programs’ ITERs outlined competency items for students to achieve. Clinical supervisors choose a response option corresponding to their judgment of student performance and may provide additional written feedback in spaces provided. Only one program required formal face-to-face feedback exchange between students and clinical supervisors. Experiential training program coordinators identified that no ITER was expressly culturally adapted, although in some instances, modifications were made for differences in scopes of practice between Canada and Qatar.  Power distance was recognized by all coordinators who also identified both student and supervisor reluctance to document potentially negative feedback in ITERs. Instances of collectivism were described as more lenient student assessment by clinical supervisors of the same cultural background. Uncertainty avoidance did not appear to impact feedback processes. Conclusions Our findings suggest that differences in specific cultural dimensions between Qatar and Canada have implications on the feedback process in experiential training which may be addressed through simple measures to accommodate communication preferences. PMID:28315858

How does culture affect experiential training feedback in exported Canadian health professional curricula?

PubMed

Wilbur, Kerry; Mousa Bacha, Rasha; Abdelaziz, Somaia

2017-03-17

To explore feedback processes of Western-based health professional student training curricula conducted in an Arab clinical teaching setting. This qualitative study employed document analysis of in-training evaluation reports (ITERs) used by Canadian nursing, pharmacy, respiratory therapy, paramedic, dental hygiene, and pharmacy technician programs established in Qatar. Six experiential training program coordinators were interviewed between February and May 2016 to explore how national cultural differences are perceived to affect feedback processes between students and clinical supervisors. Interviews were recorded, transcribed, and coded according to a priori cultural themes. Document analysis found all programs' ITERs outlined competency items for students to achieve. Clinical supervisors choose a response option corresponding to their judgment of student performance and may provide additional written feedback in spaces provided. Only one program required formal face-to-face feedback exchange between students and clinical supervisors. Experiential training program coordinators identified that no ITER was expressly culturally adapted, although in some instances, modifications were made for differences in scopes of practice between Canada and Qatar.  Power distance was recognized by all coordinators who also identified both student and supervisor reluctance to document potentially negative feedback in ITERs. Instances of collectivism were described as more lenient student assessment by clinical supervisors of the same cultural background. Uncertainty avoidance did not appear to impact feedback processes. Our findings suggest that differences in specific cultural dimensions between Qatar and Canada have implications on the feedback process in experiential training which may be addressed through simple measures to accommodate communication preferences.

Multi-voxel Patterns Reveal Functionally Differentiated Networks Underlying Auditory Feedback Processing of Speech

PubMed Central

Zheng, Zane Z.; Vicente-Grabovetsky, Alejandro; MacDonald, Ewen N.; Munhall, Kevin G.; Cusack, Rhodri; Johnsrude, Ingrid S.

2013-01-01

The everyday act of speaking involves the complex processes of speech motor control. An important component of control is monitoring, detection and processing of errors when auditory feedback does not correspond to the intended motor gesture. Here we show, using fMRI and converging operations within a multi-voxel pattern analysis framework, that this sensorimotor process is supported by functionally differentiated brain networks. During scanning, a real-time speech-tracking system was employed to deliver two acoustically different types of distorted auditory feedback or unaltered feedback while human participants were vocalizing monosyllabic words, and to present the same auditory stimuli while participants were passively listening. Whole-brain analysis of neural-pattern similarity revealed three functional networks that were differentially sensitive to distorted auditory feedback during vocalization, compared to during passive listening. One network of regions appears to encode an ‘error signal’ irrespective of acoustic features of the error: this network, including right angular gyrus, right supplementary motor area, and bilateral cerebellum, yielded consistent neural patterns across acoustically different, distorted feedback types, only during articulation (not during passive listening). In contrast, a fronto-temporal network appears sensitive to the speech features of auditory stimuli during passive listening; this preference for speech features was diminished when the same stimuli were presented as auditory concomitants of vocalization. A third network, showing a distinct functional pattern from the other two, appears to capture aspects of both neural response profiles. Taken together, our findings suggest that auditory feedback processing during speech motor control may rely on multiple, interactive, functionally differentiated neural systems. PMID:23467350

Towards an improved ensemble precipitation forecast: A probabilistic post-processing approach

NASA Astrophysics Data System (ADS)

Khajehei, Sepideh; Moradkhani, Hamid

2017-03-01

Recently, ensemble post-processing (EPP) has become a commonly used approach for reducing the uncertainty in forcing data and hence hydrologic simulation. The procedure was introduced to build ensemble precipitation forecasts based on the statistical relationship between observations and forecasts. More specifically, the approach relies on a transfer function that is developed based on a bivariate joint distribution between the observations and the simulations in the historical period. The transfer function is used to post-process the forecast. In this study, we propose a Bayesian EPP approach based on copula functions (COP-EPP) to improve the reliability of the precipitation ensemble forecast. Evaluation of the copula-based method is carried out by comparing the performance of the generated ensemble precipitation with the outputs from an existing procedure, i.e. mixed type meta-Gaussian distribution. Monthly precipitation from Climate Forecast System Reanalysis (CFS) and gridded observation from Parameter-Elevation Relationships on Independent Slopes Model (PRISM) have been employed to generate the post-processed ensemble precipitation. Deterministic and probabilistic verification frameworks are utilized in order to evaluate the outputs from the proposed technique. Distribution of seasonal precipitation for the generated ensemble from the copula-based technique is compared to the observation and raw forecasts for three sub-basins located in the Western United States. Results show that both techniques are successful in producing reliable and unbiased ensemble forecast, however, the COP-EPP demonstrates considerable improvement in the ensemble forecast in both deterministic and probabilistic verification, in particular in characterizing the extreme events in wet seasons.

Feedbacks between air pollution and weather, part 2: Effects on chemistry

NASA Astrophysics Data System (ADS)

Makar, P. A.; Gong, W.; Hogrefe, C.; Zhang, Y.; Curci, G.; Žabkar, R.; Milbrandt, J.; Im, U.; Balzarini, A.; Baró, R.; Bianconi, R.; Cheung, P.; Forkel, R.; Gravel, S.; Hirtl, M.; Honzak, L.; Hou, A.; Jiménez-Guerrero, P.; Langer, M.; Moran, M. D.; Pabla, B.; Pérez, J. L.; Pirovano, G.; San José, R.; Tuccella, P.; Werhahn, J.; Zhang, J.; Galmarini, S.

2015-08-01

Fully-coupled air-quality models running in ;feedback; and ;no-feedback; configurations were compared against each other and observation network data as part of Phase 2 of the Air Quality Model Evaluation International Initiative. In the ;no-feedback; mode, interactions between meteorology and chemistry through the aerosol direct and indirect effects were disabled, with the models reverting to climatologies of aerosol properties, or a no-aerosol weather simulation, while in the ;feedback; mode, the model-generated aerosols were allowed to modify the models' radiative transfer and/or cloud formation processes. Annual simulations with and without feedbacks were conducted for domains in North America for the years 2006 and 2010, and for Europe for the year 2010. Comparisons against observations via annual statistics show model-to-model variation in performance is greater than the within-model variation associated with feedbacks. However, during the summer and during intense emission events such as the Russian forest fires of 2010, feedbacks have a significant impact on the chemical predictions of the models. The aerosol indirect effect was usually found to dominate feedbacks compared to the direct effect. The impacts of direct and indirect effects were often shown to be in competition, for predictions of ozone, particulate matter and other species. Feedbacks were shown to result in local and regional shifts of ozone-forming chemical regime, between NOx- and VOC-limited environments. Feedbacks were shown to have a substantial influence on biogenic hydrocarbon emissions and concentrations: North American simulations incorporating both feedbacks resulted in summer average isoprene concentration decreases of up to 10%, while European direct effect simulations during the Russian forest fire period resulted in grid average isoprene changes of -5 to +12.5%. The atmospheric transport and chemistry of large emitting sources such as plumes from forest fires and large cities were shown to be strongly impacted by the presence or absence of feedback mechanisms in the model simulations. Summertime model performance for ozone and other gases was improved through the inclusion of indirect effect feedbacks, while performance for particulate matter was degraded, suggesting that current parameterizations for in- and below cloud processes, once the cloud locations become more directly influenced by aerosols, may over- or under-predict the strength of these processes. Process parameterization-level comparisons of fully coupled feedback models are therefore recommended for future work, as well as further studies using these models for the simulations of large scale urban/industrial and/or forest fire plumes.

Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning

PubMed Central

Carl Aberg, Kristoffer; Doell, Kimberly C.; Schwartz, Sophie

2016-01-01

Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits. PMID:27851807

Adaptive role switching promotes fairness in networked ultimatum game.

PubMed

Wu, Te; Fu, Feng; Zhang, Yanling; Wang, Long

2013-01-01

In recent years, mechanisms favoring fair split in the ultimatum game have attracted growing interests because of its practical implications for international bargains. In this game, two players are randomly assigned two different roles respectively to split an offer: the proposer suggests how to split and the responder decides whether or not to accept it. Only when both agree is the offer successfully split; otherwise both get nothing. It is of importance and interest to break the symmetry in role assignment especially when the game is repeatedly played in a heterogeneous population. Here we consider an adaptive role assignment: whenever the split fails, the two players switch their roles probabilistically. The results show that this simple feedback mechanism proves much more effective at promoting fairness than other alternatives (where, for example, the role assignment is based on the number of neighbors).

Passage relevance models for genomics search.

PubMed

Urbain, Jay; Frieder, Ophir; Goharian, Nazli

2009-03-19

We present a passage relevance model for integrating syntactic and semantic evidence of biomedical concepts and topics using a probabilistic graphical model. Component models of topics, concepts, terms, and document are represented as potential functions within a Markov Random Field. The probability of a passage being relevant to a biologist's information need is represented as the joint distribution across all potential functions. Relevance model feedback of top ranked passages is used to improve distributional estimates of query concepts and topics in context, and a dimensional indexing strategy is used for efficient aggregation of concept and term statistics. By integrating multiple sources of evidence including dependencies between topics, concepts, and terms, we seek to improve genomics literature passage retrieval precision. Using this model, we are able to demonstrate statistically significant improvements in retrieval precision using a large genomics literature corpus.

Anxiety and feedback processing in a gambling task: Contributions of time-frequency theta and delta.

PubMed

Ellis, Jessica S; Watts, Adreanna T M; Schmidt, Norman; Bernat, Edward M

2018-05-02

The feedback negativity (FN) event-related potential (ERP) is widely studied during gambling feedback tasks. However, research on FN and anxiety is minimal and the findings are mixed. To clarify these discrepancies, the current study (N = 238) used time-frequency analysis to disentangle overlapping contributions of delta (0-3 Hz) and theta (3-7 Hz) to feedback processing in a clinically anxious sample, with severity assessed through general worry and physiological arousal scales. Greater general worry showed enhanced delta- and theta-FN broadly across both gain and loss conditions, with theta-FN stronger for losses. Regressions indicated delta-FN maintained unique effects, accounted for theta, and explained the blunted time domain FN for general worry. Increased delta was also associated with physiological arousal, but the effects were accounted for by general worry. Broadly, anxiety-related alterations in feedback processing can be explained by an overall heightened sensitivity to feedback as represented by enhanced delta-FN in relation to the general worry facet of anxiety. Copyright © 2018 Elsevier B.V. All rights reserved.

A Probabilistic Corpus-Based Model of Syntactic Parallelism

ERIC Educational Resources Information Center

Dubey, Amit; Keller, Frank; Sturt, Patrick

2008-01-01

Work in experimental psycholinguistics has shown that the processing of coordinate structures is facilitated when the two conjuncts share the same syntactic structure [Frazier, L., Munn, A., & Clifton, C. (2000). "Processing coordinate structures." "Journal of Psycholinguistic Research," 29(4) 343-370]. In the present paper, we argue that this…

Obtaining Accurate Probabilities Using Classifier Calibration

ERIC Educational Resources Information Center

Pakdaman Naeini, Mahdi

2016-01-01

Learning probabilistic classification and prediction models that generate accurate probabilities is essential in many prediction and decision-making tasks in machine learning and data mining. One way to achieve this goal is to post-process the output of classification models to obtain more accurate probabilities. These post-processing methods are…

Proceedings, Seminar on Probabilistic Methods in Geotechnical Engineering

NASA Astrophysics Data System (ADS)

Hynes-Griffin, M. E.; Buege, L. L.

1983-09-01

Contents: Applications of Probabilistic Methods in Geotechnical Engineering; Probabilistic Seismic and Geotechnical Evaluation at a Dam Site; Probabilistic Slope Stability Methodology; Probability of Liquefaction in a 3-D Soil Deposit; Probabilistic Design of Flood Levees; Probabilistic and Statistical Methods for Determining Rock Mass Deformability Beneath Foundations: An Overview; Simple Statistical Methodology for Evaluating Rock Mechanics Exploration Data; New Developments in Statistical Techniques for Analyzing Rock Slope Stability.

Feedback on Trait or Action Impacts on Caudate and Paracingulum Activity

PubMed Central

Appelgren, Alva; Bengtsson, Sara L

2015-01-01

There is a general conception that positive associations to one’s trait, e.g. ‘I’m clever’, are beneficial for cognitive performance. Scientific evidence shows that this is a simplification. In this functional magnetic resonance imaging (fMRI) study we used written trial-based trait feedback ‘you are clever’, or task feedback ‘your choice was correct’, on each correct response of a rule-switching task, to investigate how the character of positive self-associations influences performance outcome. Twenty participants took part in this crossover design study. We found that trait feedback was less beneficial for motivation and performance improvement, and resulting in enhanced neural activation on more difficult bivalent rule trials. This indicates that the task was treated as more complex in this condition. For example, ‘you are clever’ feedback led to enhanced activation in anterior caudate nucleus, an area known to process uncertainty. We further observed that activation in anterior paracingulate cortex was sensitive to whether self-reflection was imposed by external feedback or generated from internal processes, where the latter activation correlated positively with performance when following after task feedback. Our results illustrate how feedback can evoke self-reflections that either help or hinder motivation and performance, most likely by impacting on processes of uncertainty. The results support social psychological models stipulating that trait focus take resources away from task focus. PMID:26102501

Student Perceptions of Immediate Feedback Testing in Student Centered Chemistry Classes

ERIC Educational Resources Information Center

Schneider, Jamie L.; Ruder, Suzanne M.; Bauer, Christopher F.

2018-01-01

Feedback is an important aspect of the learning process. The immediate feedback assessment technique (IF-AT®) form allows students to receive feedback on their answers during a testing event. Studies with introductory psychology students supported both perceived and real student learning gains when this form was used with testing. Knowing that…

The Effectiveness of Aligned Developmental Feedback on the Overhand Throw in Third-Grade Students

ERIC Educational Resources Information Center

Cohen, Rona; Goodway, Jacqueline D.; Lidor, Ronnie

2012-01-01

Background: To improve student performance, teachers need to evaluate the developmental level of the child and to deliver feedback statements that correspond with the student's ability to process the information delivered. Therefore, feedback aligned with the developmental level of the child (aligned developmental feedback--ADF) is sometimes…

A Measurement Feedback System (MFS) Is Necessary to Improve Mental Health Outcomes

ERIC Educational Resources Information Center

Bickman, Leonard

2008-01-01

The importance of measurement feedback system (MFS) for the improvement of mental health services for youths is discussed. As feedback obtained from clients and families is subject to distortions, a standardized MFS including clinical processes, contexts, outcomes, and feedback to clinicians and supervisors is necessary for improvement in quality…

Teamwork and Feedback: Broadening the Base of Collaborative Writing.

ERIC Educational Resources Information Center

Gebhardt, Richard

Many advocates of collaborative writing place too little emphasis on the emotional benefits of feedback to the writer by restricting group feedback to relatively late points in the writing process. Collaboration is as appropriate during the early stages of writing as it is after the completion of a draft. Students can receive feedback from…

Enhancing the Impact of Formative Feedback on Student Learning through an Online Feedback System

ERIC Educational Resources Information Center

Hatziapostolou, Thanos; Paraskakis, Iraklis

2010-01-01

Formative feedback is instrumental in the learning experience of a student. It can be effective in promoting learning if it is timely, personal, manageable, motivational, and in direct relation with assessment criteria. Despite its importance, however, research suggests that students are discouraged from engaging in the feedback process primarily…

Analysis of Peer Review Comments: QM Recommendations and Feedback Intervention Theory

ERIC Educational Resources Information Center

Schwegler, Andria F.; Altman, Barbara W.

2015-01-01

Because feedback is a critical component of the continuous improvement cycle of the Quality Matters (QM) peer review process, the present research analyzed the feedback that peer reviewers provided to course developers after a voluntary, nonofficial QM peer review of online courses. Previous research reveals that the effects of feedback on…

Cloud Feedbacks in the Climate System: A Critical Review.

NASA Astrophysics Data System (ADS)

Stephens, Graeme L.

2005-01-01

This paper offers a critical review of the topic of cloud-climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet's hydrological cycle to climate radiative forcings.The paper provides a brief overview of the effects of clouds on the radiation budget of the earth-atmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative-convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global-time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis.It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model's credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress.Although progress in understanding the cloud feedback problem has been slow and confused by past analysis, there are legitimate reasons outlined in the paper that give hope for real progress in the future.

Visualizing Uncertainty for Probabilistic Weather Forecasting based on Reforecast Analogs

NASA Astrophysics Data System (ADS)

Pelorosso, Leandro; Diehl, Alexandra; Matković, Krešimir; Delrieux, Claudio; Ruiz, Juan; Gröeller, M. Eduard; Bruckner, Stefan

2016-04-01

Numerical weather forecasts are prone to uncertainty coming from inaccuracies in the initial and boundary conditions and lack of precision in numerical models. Ensemble of forecasts partially addresses these problems by considering several runs of the numerical model. Each forecast is generated with different initial and boundary conditions and different model configurations [GR05]. The ensembles can be expressed as probabilistic forecasts, which have proven to be very effective in the decision-making processes [DE06]. The ensemble of forecasts represents only some of the possible future atmospheric states, usually underestimating the degree of uncertainty in the predictions [KAL03, PH06]. Hamill and Whitaker [HW06] introduced the "Reforecast Analog Regression" (RAR) technique to overcome the limitations of ensemble forecasting. This technique produces probabilistic predictions based on the analysis of historical forecasts and observations. Visual analytics provides tools for processing, visualizing, and exploring data to get new insights and discover hidden information patterns in an interactive exchange between the user and the application [KMS08]. In this work, we introduce Albero, a visual analytics solution for probabilistic weather forecasting based on the RAR technique. Albero targets at least two different type of users: "forecasters", who are meteorologists working in operational weather forecasting and "researchers", who work in the construction of numerical prediction models. Albero is an efficient tool for analyzing precipitation forecasts, allowing forecasters to make and communicate quick decisions. Our solution facilitates the analysis of a set of probabilistic forecasts, associated statistical data, observations and uncertainty. A dashboard with small-multiples of probabilistic forecasts allows the forecasters to analyze at a glance the distribution of probabilities as a function of time, space, and magnitude. It provides the user with a more accurate measure of forecast uncertainty that could result in better decision-making. It offers different level of abstractions to help with the recalibration of the RAR method. It also has an inspection tool that displays the selected analogs, their observations and statistical data. It gives the users access to inner parts of the method, unveiling hidden information. References [GR05] GNEITING T., RAFTERY A. E.: Weather forecasting with ensemble methods. Science 310, 5746, 248-249, 2005. [KAL03] KALNAY E.: Atmospheric modeling, data assimilation and predictability. Cambridge University Press, 2003. [PH06] PALMER T., HAGEDORN R.: Predictability of weather and climate. Cambridge University Press, 2006. [HW06] HAMILL T. M., WHITAKER J. S.: Probabilistic quantitative precipitation forecasts based on reforecast analogs: Theory and application. Monthly Weather Review 134, 11, 3209-3229, 2006. [DE06] DEITRICK S., EDSALL R.: The influence of uncertainty visualization on decision making: An empirical evaluation. Springer, 2006. [KMS08] KEIM D. A., MANSMANN F., SCHNEIDEWIND J., THOMAS J., ZIEGLER H.: Visual analytics: Scope and challenges. Springer, 2008.

Teacher feedback during active learning: current practices in primary schools.

PubMed

van den Bergh, Linda; Ros, Anje; Beijaard, Douwe

2013-06-01

Feedback is one of the most powerful tools, which teachers can use to enhance student learning. It appears difficult for teachers to give qualitatively good feedback, especially during active learning. In this context, teachers should provide facilitative feedback that is focused on the development of meta-cognition and social learning. The purpose of the present study is to contribute to the existing knowledge about feedback and to give directions to improve teacher feedback in the context of active learning. The participants comprised 32 teachers who practiced active learning in the domain of environmental studies in the sixth, seventh, or eighth grade of 13 Dutch primary schools. A total of 1,465 teacher-student interactions were examined. Video observations were made of active learning lessons in the domain of environmental studies. A category system was developed based on the literature and empirical data. Teacher-student interactions were assessed using this system. Results. About half of the teacher-student interactions contained feedback. This feedback was usually focused on the tasks that were being performed by the students and on the ways in which these tasks were processed. Only 5% of the feedback was explicitly related to a learning goal. In their feedback, the teachers were directing (rather than facilitating) the learning processes. During active learning, feedback on meta-cognition and social learning is important. Feedback should be explicitly related to learning goals. In practice, these kinds of feedback appear to be scarce. Therefore, giving feedback during active learning seems to be an important topic for teachers' professional development. © 2012 The British Psychological Society.

Quantifying climate feedbacks in polar regions

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

Goosse, Hugues; Kay, Jennifer E.; Armour, Kyle C.

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range ofmore » feedbacks, thus offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.« less

Quantifying climate feedbacks in polar regions

DOE PAGES

Goosse, Hugues; Kay, Jennifer E.; Armour, Kyle C.; ...

2018-05-15

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range ofmore » feedbacks, thus offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.« less

Developing students' teaching through peer observation and feedback.

PubMed

Rees, Eliot L; Davies, Benjamin; Eastwood, Michael

2015-10-01

With the increasing popularity and scale of peer teaching, it is imperative to develop methods that ensure the quality of teaching provided by undergraduate students. We used an established faculty development and quality assurance process in a novel context: peer observation of teaching for undergraduate peer tutors. We have developed a form to record observations and aid the facilitation of feedback. In addition, experienced peer tutors have been trained to observe peer-taught sessions and provide tutors with verbal and written feedback. We have found peer observation of teaching to be a feasible and acceptable process for improving quality of teaching provided by undergraduate medical students. However, feedback regarding the quality of peer observer's feedback may help to develop students' abilities further.

Mind the gap! Automated concept map feedback supports students in writing cohesive explanations.

PubMed

Lachner, Andreas; Burkhart, Christian; Nückles, Matthias

2017-03-01

Many students are challenged with the demand of writing cohesive explanations. To support students in writing cohesive explanations, we developed a computer-based feedback tool that visualizes cohesion deficits of students' explanations in a concept map. We conducted three studies to investigate the effectiveness of such feedback as well as the underlying cognitive processes. In Study 1, we found that the concept map helped students identify potential cohesion gaps in their drafts and plan remedial revisions. In Study 2, students with concept map feedback conducted revisions that resulted in more locally and globally cohesive, and also more comprehensible, explanations than the explanations of students who revised without concept map feedback. In Study 3, we replicated the findings of Study 2 by and large. More importantly, students who had received concept map feedback on a training explanation 1 week later wrote a transfer explanation without feedback that was more cohesive than the explanation of students who had received no feedback on their training explanation. The automated concept map feedback appears to particularly support the evaluation phase of the revision process. Furthermore, the feedback enabled novice writers to acquire sustainable skills in writing cohesive explanations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Probabilistic Estimation of Rare Random Collisions in 3 Space

DTIC Science & Technology

2009-03-01

extended Poisson process as a feature of probability theory. With the bulk of research in extended Poisson processes going into parame- ter estimation, the...application of extended Poisson processes to spatial processes is largely untouched. Faddy performed a short study of spatial data, but overtly...the theory of extended Poisson processes . To date, the processes are limited in that the rates only depend on the number of arrivals at some time

A conceptual framework for regional feedbacks in a changing climate

NASA Astrophysics Data System (ADS)

Batlle Bayer, L.; van den Hurk, B. J. J. M.; Strengers, B.

2012-04-01

Terrestrial ecosystems and climate influence each other through biogeochemical (e.g. carbon cycle) and biogeophysical (e.g. albedo, water fluxes) processes. These interactions might be disturbed when a climate human-induced forcing takes place (e.g. deforestation); and the ecosystem responses to the climate system might amplify (positive feedback) or dampen (negative feedback) the initial forcing. Research on feedbacks has been mainly based on the carbon cycle at the global scale. However, biogeophysical feedbacks might have a great impact at the local or regional scale, which is the main focus of this article. A conceptual framework, with the major interactions and processes between terrestrial ecosystems and climate, is presented to further explore feedbacks at the regional level. Four hot spots with potential changes in land use/management and climate are selected: sub-Saharan Africa (SSA), Europe, the Amazon Basin and South and Southeast Asia. For each region, diverse climate human-induced forcings and feedbacks were identified based on relevant published literature. For Europe, the positive soil moisture-evapotranspiration (ET) is important for natural vegetation during a heat wave event, while the positive soil moisture-precipitation feedback plays a more important role for droughts in the Amazon region. Agricultural expansion in SSA will depend on the impacts of the changing climate on crop yields and the adopted agro-technologies. The adoption of irrigation in the commonly rainfed systems might turn the positive soil moisture- ET feedback into a negative one. In contrast, South and Southeast Asia might face water shortage in the future, and thus turning the soil moisture-ET feedback into a positive one. Further research is needed for the major processes that affect the ultimate sign of the feedbacks, as well as for the interactions, which effect remains uncertain, such as ET-precipitation interaction. In addition, socio-economic feedbacks need to be added in the ecosystems-climate system since they play an essential role in human decisions on land use and land cover change (LULCC).

A Digital Map From External Forcing to the Final Surface Warming Pattern and its Seasonal Cycle

NASA Astrophysics Data System (ADS)

Cai, M.

2015-12-01

Historically, only the thermodynamic processes (e.g., water vapor, cloud, surface albedo, and atmospheric lapse rate) that directly influence the top of the atmosphere (TOA) radiative energy flux balance are considered in climate feedback analysis. One of my recent research areas is to develop a new framework for climate feedback analysis that explicitly takes into consideration not only the thermodynamic processes that the directly influence the TOA radiative energy flux balance but also the local dynamical (e.g., evaporation, surface sensible heat flux, vertical convections etc) and non-local dynamical (large-scale horizontal energy transport) processes in aiming to explain the warming asymmetry between high and low latitudes, between ocean and land, and between the surface and atmosphere. In the last 5-6 years, we have developed a coupled atmosphere-surface climate feedback-response analysis method (CFRAM) as a new framework for estimating climate feedback and sensitivity in coupled general circulation models with a full physical parameterization package. In the CFRAM, the isolation of partial temperature changes due to an external forcing alone or an individual feedback is achieved by solving the linearized infrared radiation transfer model subject to individual energy flux perturbations (external or due to feedbacks). The partial temperature changes are addable and their sum is equal to the (total) temperature change (in the linear sense). The CFRAM is used to isolate the partial temperature changes due to the external forcing, due to water vapor feedback, clouds, surface albedo, local vertical convection, and non-local atmospheric dynamical feedbacks, as well as oceanic heat storage. It has been shown that seasonal variations in the cloud feedback, surface albedo feedback, and ocean heat storage/dynamics feedback, directly caused by the strong annual cycle of insolation, contribute primarily to the large seasonal variation of polar warming. Furthermore, the CO2 forcing, and water vapor and atmospheric dynamics feedbacks add to the maximum polar warming in fall/winter.

Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration.

PubMed

Oh-Descher, Hanna; Beck, Jeffrey M; Ferrari, Silvia; Sommer, Marc A; Egner, Tobias

2017-11-15

Real-life decision-making often involves combining multiple probabilistic sources of information under finite time and cognitive resources. To mitigate these pressures, people "satisfice", foregoing a full evaluation of all available evidence to focus on a subset of cues that allow for fast and "good-enough" decisions. Although this form of decision-making likely mediates many of our everyday choices, very little is known about the way in which the neural encoding of cue information changes when we satisfice under time pressure. Here, we combined human functional magnetic resonance imaging (fMRI) with a probabilistic classification task to characterize neural substrates of multi-cue decision-making under low (1500 ms) and high (500 ms) time pressure. Using variational Bayesian inference, we analyzed participants' choices to track and quantify cue usage under each experimental condition, which was then applied to model the fMRI data. Under low time pressure, participants performed near-optimally, appropriately integrating all available cues to guide choices. Both cortical (prefrontal and parietal cortex) and subcortical (hippocampal and striatal) regions encoded individual cue weights, and activity linearly tracked trial-by-trial variations in the amount of evidence and decision uncertainty. Under increased time pressure, participants adaptively shifted to using a satisficing strategy by discounting the least informative cue in their decision process. This strategic change in decision-making was associated with an increased involvement of the dopaminergic midbrain, striatum, thalamus, and cerebellum in representing and integrating cue values. We conclude that satisficing the probabilistic inference process under time pressure leads to a cortical-to-subcortical shift in the neural drivers of decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling the Evolution of Beliefs Using an Attentional Focus Mechanism

PubMed Central

Marković, Dimitrije; Gläscher, Jan; Bossaerts, Peter; O’Doherty, John; Kiebel, Stefan J.

2015-01-01

For making decisions in everyday life we often have first to infer the set of environmental features that are relevant for the current task. Here we investigated the computational mechanisms underlying the evolution of beliefs about the relevance of environmental features in a dynamical and noisy environment. For this purpose we designed a probabilistic Wisconsin card sorting task (WCST) with belief solicitation, in which subjects were presented with stimuli composed of multiple visual features. At each moment in time a particular feature was relevant for obtaining reward, and participants had to infer which feature was relevant and report their beliefs accordingly. To test the hypothesis that attentional focus modulates the belief update process, we derived and fitted several probabilistic and non-probabilistic behavioral models, which either incorporate a dynamical model of attentional focus, in the form of a hierarchical winner-take-all neuronal network, or a diffusive model, without attention-like features. We used Bayesian model selection to identify the most likely generative model of subjects’ behavior and found that attention-like features in the behavioral model are essential for explaining subjects’ responses. Furthermore, we demonstrate a method for integrating both connectionist and Bayesian models of decision making within a single framework that allowed us to infer hidden belief processes of human subjects. PMID:26495984

The effectiveness of learning material with Edmodo to enhance the level of student's probabilistic thinking

NASA Astrophysics Data System (ADS)

Sujadi, Imam; Kurniasih, Rini; Subanti, Sri

2017-05-01

In the era of 21st century learning, it needs to use technology as a learning media. Using Edmodo as a learning media is one of the options as the complement in learning process. However, this research focuses on the effectiveness of learning material using Edmodo. The aim of this research to determine whether the level of student's probabilistic thinking that use learning material with Edmodo is better than the existing learning materials (books) implemented to teach the subject of students grade 8th. This is quasi-experimental research using control group pretest and posttest. The population of this study was students grade 8 of SMPN 12 Surakarta and the sampling technique used random sampling. The analysis technique used to examine two independent sample using Kolmogorov-Smirnov test. The obtained value of test statistic is M=0.38, since 0.38 is the largest tabled critical one-tailed value M0.05=0.011. The result of the research is the learning materials with Edmodo more effectively to enhance the level of probabilistic thinking learners than the learning that use the existing learning materials (books). Therefore, learning material using Edmodo can be used in learning process. It can also be developed into another learning material through Edmodo.

Probabilistic Space Weather Forecasting: a Bayesian Perspective

NASA Astrophysics Data System (ADS)

Camporeale, E.; Chandorkar, M.; Borovsky, J.; Care', A.

2017-12-01

Most of the Space Weather forecasts, both at operational and research level, are not probabilistic in nature. Unfortunately, a prediction that does not provide a confidence level is not very useful in a decision-making scenario. Nowadays, forecast models range from purely data-driven, machine learning algorithms, to physics-based approximation of first-principle equations (and everything that sits in between). Uncertainties pervade all such models, at every level: from the raw data to finite-precision implementation of numerical methods. The most rigorous way of quantifying the propagation of uncertainties is by embracing a Bayesian probabilistic approach. One of the simplest and most robust machine learning technique in the Bayesian framework is Gaussian Process regression and classification. Here, we present the application of Gaussian Processes to the problems of the DST geomagnetic index forecast, the solar wind type classification, and the estimation of diffusion parameters in radiation belt modeling. In each of these very diverse problems, the GP approach rigorously provide forecasts in the form of predictive distributions. In turn, these distributions can be used as input for ensemble simulations in order to quantify the amplification of uncertainties. We show that we have achieved excellent results in all of the standard metrics to evaluate our models, with very modest computational cost.

Integrating statistical and process-based models to produce probabilistic landslide hazard at regional scale

NASA Astrophysics Data System (ADS)

Strauch, R. L.; Istanbulluoglu, E.

2017-12-01

We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.

Modeling and Simulation of Hydropower Station Diversion System's characteristic line method by introducing water head to flow feedback

NASA Astrophysics Data System (ADS)

Guangwen, Xu; Xi, Li; Ze, Yao

2018-06-01

To solve the damping problem of water hammer wave in the modeling method of water diversion system of hydropower station, this paper introduces the feedback regulation technology from head to flow, that is: A fixed water head is taken out for flow feedback, and the following conclusions are obtained through modeling and simulation. Adjusting the feedback coefficient F of the water head to the flow rate can change the damping characteristic of the system, which can simulate the attenuation process of the water shock wave in the true water diversion pipeline. Even if a small feedback coefficient is introduced, the damping effect of the system is very obvious, but it has little effect on the amplitude of the first water shock wave after the transition process. Therefore, it is feasible and reasonable to introduce water head to flow rate feedback coefficient F in hydraulic turbine diversion system.

Neuroticism and responsiveness to error feedback: adaptive self-regulation versus affective reactivity.

PubMed

Robinson, Michael D; Moeller, Sara K; Fetterman, Adam K

2010-10-01

Responsiveness to negative feedback has been seen as functional by those who emphasize the value of reflecting on such feedback in self-regulating problematic behaviors. On the other hand, the very same responsiveness has been viewed as dysfunctional by its link to punishment sensitivity and reactivity. The present 4 studies, involving 203 undergraduate participants, sought to reconcile such discrepant views in the context of the trait of neuroticism. In cognitive tasks, individuals were given error feedback when they made mistakes. It was found that greater tendencies to slow down following error feedback were associated with higher levels of accuracy at low levels of neuroticism but lower levels of accuracy at high levels of neuroticism. Individual differences in neuroticism thus appear crucial in understanding whether behavioral alterations following negative feedback reflect proactive versus reactive mechanisms and processes. Implications for understanding the processing basis of neuroticism and adaptive self-regulation are discussed.

Structure Learning in Bayesian Sensorimotor Integration

PubMed Central

Genewein, Tim; Hez, Eduard; Razzaghpanah, Zeynab; Braun, Daniel A.

2015-01-01

Previous studies have shown that sensorimotor processing can often be described by Bayesian learning, in particular the integration of prior and feedback information depending on its degree of reliability. Here we test the hypothesis that the integration process itself can be tuned to the statistical structure of the environment. We exposed human participants to a reaching task in a three-dimensional virtual reality environment where we could displace the visual feedback of their hand position in a two dimensional plane. When introducing statistical structure between the two dimensions of the displacement, we found that over the course of several days participants adapted their feedback integration process in order to exploit this structure for performance improvement. In control experiments we found that this adaptation process critically depended on performance feedback and could not be induced by verbal instructions. Our results suggest that structural learning is an important meta-learning component of Bayesian sensorimotor integration. PMID:26305797

Unifying Model-Based and Reactive Programming within a Model-Based Executive

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

1999-01-01

Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

International Space Station End-of-Life Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

Duncan, Gary W.

2014-01-01

The International Space Station (ISS) end-of-life (EOL) cycle is currently scheduled for 2020, although there are ongoing efforts to extend ISS life cycle through 2028. The EOL for the ISS will require deorbiting the ISS. This will be the largest manmade object ever to be de-orbited therefore safely deorbiting the station will be a very complex problem. This process is being planned by NASA and its international partners. Numerous factors will need to be considered to accomplish this such as target corridors, orbits, altitude, drag, maneuvering capabilities etc. The ISS EOL Probabilistic Risk Assessment (PRA) will play a part in this process by estimating the reliability of the hardware supplying the maneuvering capabilities. The PRA will model the probability of failure of the systems supplying and controlling the thrust needed to aid in the de-orbit maneuvering.

Evaluation of safety of hypobaric decompressions and EVA from positions of probabilistic theory

NASA Astrophysics Data System (ADS)

Nikolaev, V. P.

Formation and subsequent evolution of gas bubbles in blood and tissues of subjects exposed to decompression are casual processes in their nature. Such character of bubbling processes in a body predetermines probabilistic character of decompression sickness (DCS) incidence in divers, aviators and astronauts. Our original probabilistic theory of decompression safety is based on stochastic models of these processes and on the concept of critical volume of a free gas phase in body tissues. From positions of this theory, the probability of DCS incidence during single-stage decompressions and during hypobaric decompressions under EVA in particular, is defined by the distribution of possible values of nucleation efficiency in "pain" tissues and by its critical significance depended on the parameters of a concrete decompression. In the present study the following is shown: 1) the dimensionless index of critical nucleation efficiency for "pain" body tissues is a more adequate index of decompression stress in comparison with Tissue Ratio, TR; 2) a priory the decompression under EVA performed according to the Russian protocol is more safe than decompression under EVA performed in accordance with the U.S. protocol; 3) the Russian space suit operated at a higher pressure and having a higher "rigidity" induces a stronger inhibition of mechanisms of cavitation and gas bubbles formation in tissues of a subject located in it, and by that provides a more considerable reduction of the DCS risk during real EVA performance.

Global Infrasound Association Based on Probabilistic Clutter Categorization

NASA Astrophysics Data System (ADS)

Arora, Nimar; Mialle, Pierrick

2016-04-01

The IDC advances its methods and continuously improves its automatic system for the infrasound technology. The IDC focuses on enhancing the automatic system for the identification of valid signals and the optimization of the network detection threshold by identifying ways to refine signal characterization methodology and association criteria. An objective of this study is to reduce the number of associated infrasound arrivals that are rejected from the automatic bulletins when generating the reviewed event bulletins. Indeed, a considerable number of signal detections are due to local clutter sources such as microbaroms, waterfalls, dams, gas flares, surf (ocean breaking waves) etc. These sources are either too diffuse or too local to form events. Worse still, the repetitive nature of this clutter leads to a large number of false event hypotheses due to the random matching of clutter at multiple stations. Previous studies, for example [1], have worked on categorization of clutter using long term trends on detection azimuth, frequency, and amplitude at each station. In this work we continue the same line of reasoning to build a probabilistic model of clutter that is used as part of NETVISA [2], a Bayesian approach to network processing. The resulting model is a fusion of seismic, hydroacoustic and infrasound processing built on a unified probabilistic framework. References: [1] Infrasound categorization Towards a statistics based approach. J. Vergoz, P. Gaillard, A. Le Pichon, N. Brachet, and L. Ceranna. ITW 2011 [2] NETVISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013

A Probabilistic Approach to Predict Thermal Fatigue Life for Ball Grid Array Solder Joints

NASA Astrophysics Data System (ADS)

Wei, Helin; Wang, Kuisheng

2011-11-01

Numerous studies of the reliability of solder joints have been performed. Most life prediction models are limited to a deterministic approach. However, manufacturing induces uncertainty in the geometry parameters of solder joints, and the environmental temperature varies widely due to end-user diversity, creating uncertainties in the reliability of solder joints. In this study, a methodology for accounting for variation in the lifetime prediction for lead-free solder joints of ball grid array packages (PBGA) is demonstrated. The key aspects of the solder joint parameters and the cyclic temperature range related to reliability are involved. Probabilistic solutions of the inelastic strain range and thermal fatigue life based on the Engelmaier model are developed to determine the probability of solder joint failure. The results indicate that the standard deviation increases significantly when more random variations are involved. Using the probabilistic method, the influence of each variable on the thermal fatigue life is quantified. This information can be used to optimize product design and process validation acceptance criteria. The probabilistic approach creates the opportunity to identify the root causes of failed samples from product fatigue tests and field returns. The method can be applied to better understand how variation affects parameters of interest in an electronic package design with area array interconnections.